Sara Vilar-Lluch, Dawn Knight · (2026) · "Type 1 and Type 2 diabetes in the UK press: A diachronic corpus-based analysis" · PLOS One · doi: 10.1371/journal.pone.0348079 · PMCID: PMC13132212 · PMID: 42060588

Question: What does the published research conclude about "Type 1 and Type 2 diabetes in the UK press: A diachronic corpus-based analysis"? Cite a peer-reviewed source.

Answer:
UK news media shows competing medical and free will discourses in T1D and T2D reports, and a gradual increase in the use of language recommended by diabetes guidelines, albeit the latter is not mirrored by a similar decrease in dispreferred language. Although the newspaper articles include references to diabetes types, references to diabetes ‘in general’ are common, supporting reported concerns of individuals living with T1D/T2D [ 13 , 17 ] and echoing findings of news media studies in other contexts (e.g., [ 20 ] in New Zealand). In the Diabetes UK News Media Corpus, general uses of ‘diabetes’ occur when reporting risks common for both diabetes types, but also stand metonymically for one type, ultimately relying on readers’ ability to discern the type of diabetes discussed (see example 10).

As observed in previous studies of diabetes representation in news media (e.g., [ 20 , 21 , 28 , 35 , 36 ]), medical discourse is also prominent in the corpus examined. In the Diabetes UK News Media Corpus, the medical discourse is used in articles that mention both diabetes types but is particularly common for T1D. The medical discourse alludes to medical causes and medicines as management strategies. It is also enacted by referring to T1D and T2D in the context of other medical conditions, either by portraying some observed similarity (specially for T1D), or by presenting diabetes as the causal factor (specially for T2D). Causal relations or common risk factors are sometimes explicitly stated. Other times, however, associations between medical conditions appear unclear, which can lead to erroneous inferences of causality or evaluations by association.

The medical discourse can contribute to reduce moral blame and stigma associated with T2D, popularly regarded as a consequence of unhealthy diet and sedentary lifestyle. While the medical discourse is adopted, discussions around the social determinants of health (SDH) [ 49 ] that may impact on diabetes development and management were not frequently featured in the articles. SDH are conditions in which people are born or live that, although not directly related to health, affect individuals’ health, such as income, food security, education or social inclusion [ 49 – 50 ]. Omission of societal factors is common in news media reporting of diabetes (e.g., [ 20 , 37 , 38 ]). Overlooking SDH ultimately contributes to depict diabetes (both types) as an individual problem, and diabetes management as an individual responsibility. The collocation analysis did not reveal any discussion around the affordability of healthy diets and the ongoing UK food crisis [ 51 – 53 ], neither did it include references to the affordability of adopting active lifestyles across demographics, or debates on economic policies to promote healthy eating. Instances referring to the economic and emotional burden of living with diabetes (T1D or T2D) have not been observed in the analysis.

The medical discourse competes with an underlying discourse of free will, particularly observed for T2D. References to lifestyle and diet do not predominate among the management strategies identified in the corpus, contrasting with previous studies which reported recurrent associations of T2D with individual behaviours and lifestyle changes as remedies (e.g., [ 20 , 35 , 36 ]). However, lifestyle (including dietary habits) features in descriptions of causes leading to T2D and in associations of T2D with obesity/overweight. The absence of discussions around factors leading to obesity/overweight (e.g., genetic, ill health, socioeconomic) can contribute to reinforce its association with over-indulgence; by inference, T2D is implicitly depicted as an individual moral failure. T1D is not associated with negative moral judgements, and autoimmune and genetic causes are emphasised, sometimes including explicit contrasting descriptions with T2D. Verbs conveying control are common in T1D reporting. These verbs depict T1D as requiring high individual responsibility, evoking positive assessments of those that manage it successfully. However, failure to refer to factors that hinder T1D management implicitly blames the individuals (or their parents/carers) for health complications.

Overall, this analysis has shown that UK news media reporting on T1D and T2D reflects competing societal discourses on health and wellbeing. The medical discourse promotes current scientific understanding and avoids moral blaming. The avoidance of discussions around societal structures (societal frames) in reporting management strategies and (T2D) causes, however, places health-preventive actions in the individual responsibility exclusively, overseeing prevalent inequalities that may contribute to develop T2D, or that interfere with T1D and T2D management.

— Source (conclusions, peer-reviewed): Sara Vilar-Lluch, Dawn Knight · (2026) · "Type 1 and Type 2 diabetes in the UK press: A diachronic corpus-based analysis" · PLOS One · doi: 10.1371/journal.pone.0348079 · PMCID: PMC13132212 · PMID: 42060588
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Dogus Vuralli · (2026) · "From Pathophysiology to Treatment: Contemporary Approaches to CFRD in the Pediatric and Adolescent Population" · Pediatric Diabetes · doi: 10.1155/pedi/5539725 · PMCID: PMC12811412 · PMID: 41552835

Question: What does the published research conclude about "From Pathophysiology to Treatment: Contemporary Approaches to CFRD in the Pediatric and Adolescent Population"? Cite a peer-reviewed source.

Answer:
CFRD represents a unique and increasingly important aspect of CF care as life expectancy continues to improve. While CFRD poses significant clinical challenges, it is also highly manageable with early detection, individualized insulin treatment, and continuous monitoring. The advent of CFTR modulators and the emergence of novel diabetes technologies have created new opportunities to optimize glycemic control and enhance quality of life for PwCFRD. Ongoing research evaluating the long‐term effects of CFTR modulators on insulin secretion and glycemic control, investigating noninsulin therapies, developing predictive biomarkers, and refining diagnostic tools will be instrumental in shaping future management strategies. Ultimately, integrating these advances into routine clinical care will be key to preserving pulmonary function, nutritional status, and quality of life, ensuring that PwCF can continue to thrive throughout their lifespan.

— Source (conclusions, peer-reviewed): Dogus Vuralli · (2026) · "From Pathophysiology to Treatment: Contemporary Approaches to CFRD in the Pediatric and Adolescent Population" · Pediatric Diabetes · doi: 10.1155/pedi/5539725 · PMCID: PMC12811412 · PMID: 41552835
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Catherine D. Zhang, Adriana G. Ioachimescu · (2024) · "Challenges in the postsurgical recovery of cushing syndrome: glucocorticoid withdrawal syndrome" · Frontiers in Endocrinology · doi: 10.3389/fendo.2024.1353543 · PMCID: PMC11045978 · PMID: 38681763

Question: Summarize the abstract of the paper titled "Challenges in the postsurgical recovery of cushing syndrome: glucocorticoid withdrawal syndrome".

Answer:
Glucocorticoid withdrawal syndrome is a challenging clinical phenomenon that can complicate the postsurgical recovery of Cushing syndrome. It is characterized by physical tolerance and dependence to supraphysiologic glucocorticoid exposure during active Cushing syndrome followed by the abrupt decline in cortisol levels after surgical treatment. The symptoms of glucocorticoid withdrawal often overlap with those of postoperative adrenal insufficiency and can be difficult for patients to cope with and for clinicians to treat. This mini review will discuss the clinical characteristics, pathophysiology, and management of glucocorticoid withdrawal syndrome while highlighting recent data in the field.

— Source (abstract, peer-reviewed): Catherine D. Zhang, Adriana G. Ioachimescu · (2024) · "Challenges in the postsurgical recovery of cushing syndrome: glucocorticoid withdrawal syndrome" · Frontiers in Endocrinology · doi: 10.3389/fendo.2024.1353543 · PMCID: PMC11045978 · PMID: 38681763
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Jiangli Zhao, Xuchen Liu, Qingyuan Sun, et al. · (2025) · "Identification of Seven in absentia homolog 2 as a potential efferocytosis-related biomarker in diabetic foot ulcers" · PLOS One · doi: 10.1371/journal.pone.0334163 · PMCID: PMC12582498 · PMID: 41183121

Question: Summarize the abstract of the paper titled "Identification of Seven in absentia homolog 2 as a potential efferocytosis-related biomarker in diabetic foot ulcers".

Answer:
Wound of diabetic foot ulcers (DFU) is chronic and hard to heal, characterized by impaired inflammatory response, dysfunction of keratinocyte and endothelial cells and improper removal of dying cells. Efferocytosis, as a trigger for phenotype switch of macrophages, plays a critical role in diabetic foot wound healing. Here, we showed the effect of efferocytosis in wound healing of diabetics and identified seven in absentia homolog 2 (SIAH2) as a potential efferocytosis-related biomarker.

Blood and skin samples were collected from 20 patients diagnosed type II diabetes at Qilu Hospital of Shandong University. Efferocytosis related genes in DFU were identified based on GSE147890 , GSE80178 datasets as well as RNA-seq data of blood samples. Enrichment analysis, clustering analysis and protein-protein interaction network analysis were conducted based on the efferocytosis related genes in DFU. An array diagram was constructed and survival analysis of DFU was performed based on the associated clinical data. Single-cell sequencing data analysis combined with experiments in vitro, we analyzed the role of SIAH2 in wound healing of DFU as well as its correlation with efferocytosis signal.

Overall efferocytosis and SIAH2 expression level were increased in DFU blood and tissue samples and associated with poor survival in patients. Single-cell analysis revealed elevated SIAH2 expression is positively associated with keratinocyte migration, angiogenesis and efferocytosis of macrophage in wound healing of DFU. SIAH2 involved in efferocytosis-related cell-to-cell communication, especially in “internalization” and “digestion” signals.

SIAH2 was identified to be one of the key efferocytosis genes and associated with poor prognosis of DFU. Protective upregulation of SIAH2 was involved in angiogenesis, keratinocyte migration and cell-to-cell communication mediated by efferocytosis in DFU wound healing.

— Source (abstract, peer-reviewed): Jiangli Zhao, Xuchen Liu, Qingyuan Sun, et al. · (2025) · "Identification of Seven in absentia homolog 2 as a potential efferocytosis-related biomarker in diabetic foot ulcers" · PLOS One · doi: 10.1371/journal.pone.0334163 · PMCID: PMC12582498 · PMID: 41183121
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Yuzhong Wang, Tianlin Gao, Hong Zhou, et al. · (2026) · "Correlation Analysis of Lower Limb Contrast‐Enhanced Ultrasound Findings With Serum VEGF and CXCL‐12 Levels in a Rabbit Model of Diabetic Foot" · BioMed Research International · doi: 10.1155/bmri/5408596 · PMCID: PMC13051869 · PMID: 41933922

Question: What did the discussion section of the paper "Correlation Analysis of Lower Limb Contrast‐Enhanced Ultrasound Findings With Serum VEGF and CXCL‐12 Levels in a Rabbit Model of Diabetic Foot" cover?

Answer:
Since skeletal muscle plays an important role in glucose metabolism, the occurrence of microcirculatory disorders will seriously affect the control of glucose metabolism in diabetic patients, thereby aggravating glucose metabolism disorders [ 22 ]. Currently, there are few dynamic and noninvasive methods for evaluating skeletal muscle microcirculation. Dynamic contrast‐enhanced magnetic resonance imaging and special sequences of magnetic resonance imaging can meet the requirements of dynamic evaluation and have good repeatability. They can be used to measure the maximum PI of the contrast agent and the TTP, enabling quantitative analysis of muscle microcirculation for the assessment of skeletal muscle perfusion [ 23 , 24 ]. However, this method has not been widely used in clinical practice yet. CEUS is a relatively noninvasive examination method that can real‐time evaluate the microcirculatory perfusion and blood flow distribution of the limbs. The blood flow velocity in blood vessels can be quantitatively expressed through the process of contrast agent perfusion and clearance, and it has been widely used in the detection and quantification of perfusion changes in muscle tissue and visceral tissue [ 25 , 26 ]. In this study, CEUS quantitative software was used to record the TIC during the contrast process. Among them, the blood flow volume during the microcirculatory filling phase can be reflected by PI and AUC; whereas TTP reflects the time efficiency of the contrast agent perfusing in the tissue and reaching the maximum enhancement, thereby reflecting the filling speed of the tissue microcirculation. The results showed that TTP, PI, and AUC increased sequentially in the normal stage, DM stage, and DFU stage, with statistically significant differences. However, TTP showed the most significant difference during the establishment of the diabetic foot model, and PI and AUC showed the most significant changes during the establishment of the DM model. The distinct patterns of parameter change across stages likely reflect a shifting pathophysiological dominance during the progression of diabetic microangiopathy in our acute model. Critically, this acute model may predominantly capture the early, dynamic phase of diabetic microvascular dysfunction, which is characterized by hemodynamic dysregulation and compensatory responses, rather than the end‐stage structural rarefaction seen in chronic disease. In the DM stage, the significant increases in PI and AUC may primarily indicate early functional disturbances in the local skeletal muscle microvasculature [ 27 ]. These include increased microvascular permeability and impaired venular outflow, leading to local pooling and delayed clearance of the contrast agent. This represents a state of hemodynamic dysregulation and functional decompensation within the muscle bed itself, effectively a pathological “hyper‐perfusion” state due to leakage and stasis, not adequate nutrient delivery [ 28 ].

The transition to the DFU stage is marked by the most dramatic prolongation of TTP. This suggests the superimposition of a new, dominant hemodynamic insult: significant inflow obstruction. Although progressive local capillary stenosis contributes [ 29 ], the extreme TTP prolongation strongly implies a major increase in upstream resistance [ 30 , 31 ], likely originating from the severely compromised distal microcirculation of the foot induced by the ulcer model, which aligns with the established concept of distal microvascular occlusion in diabetic foot pathology [ 32 ]. Thus, the DFU stage evolves into a state of severe perfusion failure characterized by the synergy of persistent local microvascular dysfunction and acute distal inflow obstruction.

This pathophysiological progression—from early dysregulation to late obstruction—provides a coherent framework to interpret the CEUS findings in our DM model. The observed “hyper‐perfusion” pattern (elevated PI/AUC) is interpreted as a specific form of early microcirculatory failure. In diabetic neuropathy, loss of sympathetic tone and pathological opening of arteriovenous shunts can lead to a state of “non‐nutritive hyperemia,” where total blood flow increases at the expense of nutritive capillary perfusion [ 33 ]. This classic hemodynamic derangement aligns with our hypothesis of early functional decompensation and directly explains the elevated PI and AUC due to increased but maldistributed flow.

The pattern of elevated PI and AUC observed in our DM animal model, along with the subsequent TTP prolongation in DFU, provides a dynamic depiction of microvascular evolution. Our acutely induced model, focusing on proximal skeletal muscle (gastrocnemius), captures the early neurogenic and hemodynamic phase of diabetic microangiopathy, characterized by dysregulated flow and shunting [ 33 , 34 ]. This phase may represent a critical transitional window in the natural history of the disease. Clinical studies often assess distal beds in patients with long‐standing diabetes, where structural changes and fixed hypoperfusion are predominant [ 35 ]. Therefore, our model offers a complementary perspective, illuminating the earlier functional disturbances that precede the well‐documented late‐stage structural ablation. The dynamic evolution of CEUS parameters observed here underscores their potential utility as biomarkers for staging disease progression and identifying early intervention points, which warrants further translational investigation.

The serum dynamics of VEGF and CXCL‐12 observed in this study—significantly elevated in DM and slightly declined yet still elevated in early DFU—can be interpreted within a dynamic “compensation‐to‐decompensation” framework of diabetic microangiopathy.

— Source (discussion, peer-reviewed): Yuzhong Wang, Tianlin Gao, Hong Zhou, et al. · (2026) · "Correlation Analysis of Lower Limb Contrast‐Enhanced Ultrasound Findings With Serum VEGF and CXCL‐12 Levels in a Rabbit Model of Diabetic Foot" · BioMed Research International · doi: 10.1155/bmri/5408596 · PMCID: PMC13051869 · PMID: 41933922
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Magdalena del Rocio Sevilla-Gonzalez, Alisa K Manning, Kenneth E Westerman, et al. · (2022) · "Metabolomic markers of glucose regulation after a lifestyle intervention in prediabetes" · BMJ Open Diabetes Research & Care · doi: 10.1136/bmjdrc-2022-003010 · PMCID: PMC9577902 · PMID: 36253014

Question: Summarize the abstract of the paper titled "Metabolomic markers of glucose regulation after a lifestyle intervention in prediabetes".

Answer:
Disentangling the specific factors that regulate glycemia from prediabetes to normoglycemia could improve type 2 diabetes prevention strategies. Metabolomics provides substantial insights into the biological understanding of environmental factors such as diet. This study aimed to identify metabolomic markers of regression to normoglycemia in the context of a lifestyle intervention (LSI) in individuals with prediabetes.

We conducted a single-arm intervention study with 24 weeks of follow-up. Eligible study participants had at least one prediabetes criteria according to the American Diabetes Association guidelines, and body mass index between 25 and 45 kg/m 2 . LSI refers to a hypocaloric diet and >150 min of physical activity per week. Regression to normoglycemia (RNGR) was defined as achieving hemoglobin A1c (HbA1c) <5.5% in the final visit. Baseline and postintervention plasma metabolomic profiles were measured using liquid chromatography-tandem mass spectrometry. To select metabolites associated with RNGR, we conducted the least absolute shrinkage and selection operator-penalized regressions.

The final sample was composed of 82 study participants. Changes in three metabolites were significantly associated with regression to normoglycemia; N-acetyl-D-galactosamine (OR=0.54; 95% CI 0.32 to 0.82), putrescine (OR=0.90, 95% CI 0.81 to 0.98), and 7-methylguanine (OR=1.06; 95% CI 1.02 to 1.17), independent of HbA1c and weight loss. In addition, metabolomic perturbations due to LSI displayed enrichment of taurine and hypotaurine metabolism pathway (p=0.03) compatible with biomarkers of protein consumption, lower red meat and animal fats and higher seafood and vegetables.

Evidence from this study suggests that specific metabolomic markers have an influence on glucose regulation in individuals with prediabetes after 24 weeks of LSI independently of other treatment effects such as weight loss.

— Source (abstract, peer-reviewed): Magdalena del Rocio Sevilla-Gonzalez, Alisa K Manning, Kenneth E Westerman, et al. · (2022) · "Metabolomic markers of glucose regulation after a lifestyle intervention in prediabetes" · BMJ Open Diabetes Research & Care · doi: 10.1136/bmjdrc-2022-003010 · PMCID: PMC9577902 · PMID: 36253014
License: CC-BY-NC. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Nico Steckhan, Tanja Manlik, Tillmann Int-Veen, et al. · (2025) · "Sensor-based evaluation of intermittent fasting regimes: a machine learning and statistical approach" · International Journal of Obesity (2005) · doi: 10.1038/s41366-025-01889-0 · PMCID: PMC12583124 · PMID: 40847068

Question: What is the published background on "Sensor-based evaluation of intermittent fasting regimes: a machine learning and statistical approach"? Cite a peer-reviewed source.

Answer:
In clinical research, the data interpretation relies heavily on study compliance, meaning the extent to which participants adhere to the study protocol [ 1 ]. This is crucial in human studies where self-reporting over extended periods is required.

Common methods for measuring compliance include clinician impressions, patient interviews, prescription records, monitoring devices, and pharmacological markers. Patient interviews are straightforward and cost-effective, while pharmacological markers provide objective assessments but require ethical consideration [ 2 ].

Fasting studies often monitor ketone levels from urine, blood, or use newly developed breath ketone monitors to objectively measure adherence, but these methods require active participation and ketone increase is under the detection limit upon short fasting duration such as 16:8 fasting. Conversely, video surveillance or clinic-based meal consumption methods lack blinding [ 3 ]. Alternatively, participants may use photo and text food diaries [ 4 , 5 ] or log fasting times to track adherence.

Mobile and wearable technologies, including accelerometers, glucose monitors, and heart rate monitors, are increasingly used to monitor health-related parameters. Type 2 diabetes, the most common and preventable form of diabetes, is frequently studied [ 6 ]. Despite challenges in wearable technologies for dietary intake, such as transient signal loss and inaccurate calorie estimations [ 7 ], recent advancements in mobile sensors have improved the timeliness of dietary information. Continuous glucose monitoring (CGM) and activity tracking enable passive, unobtrusive data collection, enhancing compliance, reducing participant burden, and generating vast amounts of dynamic data, which are well-suited for advanced machine learning applications. Integrating data and machine learning in clinical research can predict diabetes risk and detect early signals of glucose metabolism disorders [ 8 – 10 ].

Therefore, the primary aim of this study was to develop and assess the performance and applicability of different models utilizing sensor data to determine dietary adherence, e.g. the adherence of eating duration and the timely adherence regarding specific time-frames for eating within the context of intermittent fasting.

— Source (introduction, peer-reviewed): Nico Steckhan, Tanja Manlik, Tillmann Int-Veen, et al. · (2025) · "Sensor-based evaluation of intermittent fasting regimes: a machine learning and statistical approach" · International Journal of Obesity (2005) · doi: 10.1038/s41366-025-01889-0 · PMCID: PMC12583124 · PMID: 40847068
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Fernando Sebastian‐Valles, Rafael Simó, Jose Alfonso Arranz Martín, et al. · (2026) · "Association of Physical Activity and Socioeconomic Status With Glycaemic Control in Adults With Type 1 Diabetes: A Cross‐Sectional Study Using CGM Data" · Diabetes/Metabolism Research and Reviews · doi: 10.1002/dmrr.70146 · PMCID: PMC12949369 · PMID: 41761628

Question: What did the discussion section of the paper "Association of Physical Activity and Socioeconomic Status With Glycaemic Control in Adults With Type 1 Diabetes: A Cross‐Sectional Study Using CGM Data" cover?

Answer:
The main finding of this study is that physical activity is associated with clinically meaningful improvements in CGM‐derived glycaemic control and cardiometabolic profile in adults with type 1 diabetes, and these benefits appear consistent across socioeconomic strata. Specifically, both physical activity and SES were independently associated with TIR, TITR, and HbA1c, and we found no evidence of an SES‐by‐physical activity interaction, indicating that the glycaemic benefits of physical activity were comparable across socioeconomic strata. Importantly, our mediation framework indicates that differences in physical activity levels may contribute to the SES gradient in TIR, thus suggesting that physical activity could be a feasible and cost‐effective target to attenuate SES‐related glycaemic disparities within a universal public healthcare context. Taken together, these findings support a clear equity‐oriented message: even in a setting with publicly funded CGM, socioeconomic differences in glycaemic outcomes persist and, therefore, behavioural intervention through physical activity promotion seems warranted.

These results align with prior studies documenting the metabolic benefits of exercise in people with T1D, including improved glycaemic outcomes and reduced cardiovascular risk [ 1 , 28 , 29 ]. However, our study builds upon existing evidence by using objective CGM‐based glucose metrics and applying a formal mediation framework, enabling quantification of the specific contribution of physical activity to SES‐related disparities. Unlike prior studies conducted in predominantly privately insured populations [ 14 , 15 ], our data were collected within a universal public healthcare setting, which enhances its generalisability to systems where structural inequities might be mitigated through policy. Moreover, by incorporating TITR alongside TIR and HbA1c, we provide a granular description of glycaemic improvements that is directly interpretable for clinical practice and current CGM targets.

From a clinical perspective, the observed effects of physical activity on TIR (+8% points) and HbA1c (−0.47%, [–5 mmol/mol]) were both statistically and clinically significant, even after adjusting for SES and multiple covariates. Moreover, participants in the highest activity quartile had a 16% lower daily insulin requirement and more favourable lipid parameters, including lower triglycerides and remnant cholesterol. These secondary findings are directionally consistent with the expected physiological effects of exercise (improved insulin sensitivity and cardiometabolic risk profile) and reinforce the plausibility and coherence of the primary CGM‐based associations. This is particularly relevant given the growing evidence from Mendelian randomisation studies supporting a causal relationship between remnant cholesterol and cardiovascular disease [ 30 , 31 ], and its association with microvascular complications such as diabetic nephropathy, retinopathy [ 32 ], and foot disease in T1D [ 33 ]. At the physiological level, exercise enhances insulin sensitivity and mitigates oxidative stress and mitochondrial dysfunction, both of which are frequent findings in individuals with poorly controlled T1D [ 34 , 35 , 36 ]. Notably, studies in physically active older adults with well‐controlled T1D have reported preserved or even better mitochondrial function compared to non‐diabetic controls [ 37 ]. Exercise has also been associated with prolonged partial remission (‘honeymoon period’) after T1D onset, suggesting a protective effect on β‐cell function [ 38 ].

A central contribution of this study is the integration of socioeconomic context with CGM outcomes to address a clinically actionable question: does physical activity confer similar glycaemic benefits across SES strata? The absence of a significant SES × physical activity interaction, together with the progressive increase in TIR across physical activity levels, suggests that the association between physical activity and glycaemic control is broadly consistent across socioeconomic strata. This is important because it supports the potential scalability of physical activity interventions without assuming differential effectiveness depending on SES. At the same time, the four‐way decomposition indicated a significant pure indirect effect, with approximately one‐quarter of the total association between SES and TIR explained by physical activity differences. This quantitative estimate provides a pragmatic framework for intervention design: reducing SES gaps in physical activity may translate into measurable improvements in glycaemic equity, even when technological access to CGM is universal.

As a minor caveat, our data showed a slight increase in TBR and number of hypoglycaemic episodes among individuals with the highest levels of physical activity; however, this was not accompanied by a longer duration of hypoglycaemic episodes. This finding could be explained by the widespread use of CGM alarms, which have been shown to mitigate exercise‐induced hypoglycaemia [ 39 ]. From a clinical standpoint, these results reinforce the need to pair physical activity counselling with structured education on insulin and carbohydrate adjustments around exercise, particularly for individuals with higher activity levels.

Despite all these benefits, adherence to physical activity remains suboptimal, often limited by fear of hypoglycaemia, lack of professional support, inadequate access to safe environments, and low confidence in insulin adjustments around exercise [ 3 , 7 ]. Our findings imply that interventions aimed at promoting physical activity could improve glycaemic control across SES groups and serve as a powerful tool to reduce SES‐related health disparities. Moreover, the observed improvements in lipid profile—particularly reductions in triglycerides and remnant cholesterol, and increases in HDL—suggest a meaningful potential to lower cardiovascular risk. In parallel, the substantial reduction in insulin requirements among physically active individuals may translate into significant economic savings for both patients and healthcare systems, particularly in resource‐constrained settings. Given that many of the reported barriers are not unique to people with T1D [ 40 ] but are also common in the general population, scalable community‐based interventions‐such as supervised group programs, infrastructure enhancements, and digital support tools‐could be adapted and deployed effectively to promote physical activity in this vulnerable population. From an equity perspective, our findings support prioritising interventions that lower practical barriers to physical activity (tailored exercise education, accessible community programmes, and safe environments), which may complement technology‐access policies by addressing behavioural and environmental drivers of SES‐related differences in glycaemic outcomes.

This study has several limitations that should be acknowledged. Physical activity was assessed using a self‐reported questionnaire (IPAQ) rather than an accelerometer‐based measure, potentially overestimating activity levels [ 41 ]. As previously reported, IPAQ‐based estimates may overestimate true activity levels and are subject to recall and social desirability bias, which could have led to exposure misclassification and attenuation or inflation of associations. Notably, if measurement error in physical activity is largely non‐differential with respect to CGM outcomes, it would be expected to bias associations towards the null, suggesting that the observed estimates may be conservative. Second, we lacked information on certain potential confounders and contextual factors ‐such as alcohol intake and hypertension status‐ that may be associated with both physical activity and glycaemic outcomes. Third, the observed relationships between SES and physical activity may be affected by residual confounding from unmeasured individual‐ and neighbourhood‐level determinants (e.g., educational attainment, occupational characteristics, built environment, or health literacy), which could bias mediation estimates. In addition, SES was proxied using area‐level mean annual net income at the census‐tract level rather than individual‐level socioeconomic indicators. Although area‐based measures are widely used and correlate with deprivation indices, they may not fully capture within‐area heterogeneity and can introduce ecological misclassification. In principle, multilevel (hierarchical) modelling accounting for clustering by census tract could further disentangle individual‐ and area‐level effects; however, prior works [ 42 , 43 , 44 , 45 , 46 ] support the use of neighbourhood socioeconomic indicators as informative proxies for individual socioeconomic context in cardiometabolic research. We did not have complete, standardised CGM summaries over the preceding 12 months for all participants; therefore, we could not examine whether associations were consistent when using annual average CGM metrics, which would be valuable to reduce short‐term variability and better address temporality. Finally, the cross‐sectional design limits causal inference and temporality, particularly for mediation analyses, and reverse causation cannot be excluded (e.g., better glycaemic control enabling higher physical activity). Prospective longitudinal studies and intervention designs are therefore needed to confirm the directionality and magnitude of these associations. Accordingly, our mediation findings should be interpreted as quantifying associations under stated assumptions rather than as definitive causal effects.

In conclusion, physical activity is associated with better glycaemic and lipid control and lower insulin requirements in adults with T1D. Differences in physical activity account for nearly one‐fourth of the SES effect on glycaemic outcomes, and its benefits are consistent across income strata. Promoting physical activity and removing barriers to exercise might improve clinical outcomes, reduce healthcare costs, and help mitigate SES‐related disparities in T1D management. Future longitudinal and interventional studies should examine whether an increase in physical activity ‐particularly in lower‐SES contexts‐will result in sustained improvements in CGM targets and a reduction in SES‐related glycaemic outcomes.

— Source (discussion, peer-reviewed): Fernando Sebastian‐Valles, Rafael Simó, Jose Alfonso Arranz Martín, et al. · (2026) · "Association of Physical Activity and Socioeconomic Status With Glycaemic Control in Adults With Type 1 Diabetes: A Cross‐Sectional Study Using CGM Data" · Diabetes/Metabolism Research and Reviews · doi: 10.1002/dmrr.70146 · PMCID: PMC12949369 · PMID: 41761628
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Fatemah Saleh Bin Saleh, Ahmed R. Alibrahim, Awad S. Alshahrani, et al. · (2025) · "Lipid metabolism in type 1 and type 2 diabetes: A comparative cross-sectional study" · Medicine · doi: 10.1097/MD.0000000000046758 · PMCID: PMC12747025 · PMID: 41465900

Question: What is the published background on "Lipid metabolism in type 1 and type 2 diabetes: A comparative cross-sectional study"? Cite a peer-reviewed source.

Answer:
Diabetes mellitus is a chronic metabolic disease characterized by abnormalities in insulin action, secretion, or both, which lead to persistent hyperglycemia. [ 1 , 2 ] Types 1 and 2 diabetes mellitus (T1DM and T2DM, respectively) are the 2 primary forms of the disease. [ 3 , 4 ] Although the pathophysiological causes and clinical manifestations of each type differ, all can result in serious complications if left untreated. [ 4 ] Dyslipidemia, a prevalent disorder in patients with diabetes, considerably increases the cardiovascular risk associated with the disease. Therefore, monitoring and managing lipid profiles is a crucial aspect of diabetes management. [ 5 , 6 ]

In T1DM, the immune system targets and destroys the pancreatic beta cells that produce insulin. [ 7 ] This results in a complete lack of insulin. [ 7 ] T1DM can occur at any age; however, it usually manifests in childhood or adolescence. To manage blood glucose levels, patients with T1DM need lifelong insulin therapy. [ 7 ] In patients with T1DM-associated dyslipidemia, low-density lipoprotein cholesterol (LDL-C), triglycerides, and total cholesterol levels are often elevated, while high-density lipoprotein cholesterol (HDL-C) levels are typically decreased. [ 8 , 9 ] These anomalies are worsened by poor glycemic management, which increases the risk of cardiovascular disease (CVD). [ 9 ]

The main risk factors for T2DM are insulin resistance, a condition in which the body’s cells lose their sensitivity to insulin, and a relative insulin deficit. [ 10 ] T2DM is closely associated with poor dietary habits, obesity, physical inactivity, and hereditary factors. [ 10 ] Although T2DM usually manifests in adulthood, it is becoming more common in younger populations. [ 11 ] In contrast to T1DM, T2DM is frequently managed with dietary changes, oral hypoglycemic medications, and, occasionally, insulin therapy. [ 12 ] Compared with T1DM, dyslipidemia in T2DM is usually more severe and manifests as an increase in small, dense LDL particles, decreased HDL-C levels, and increased triglyceride levels. [ 13 ] Patients with T2DM have an increased risk of CVD, largely attributable to this lipid profile, referred to as atherogenic dyslipidemia. [ 13 ]

Although dyslipidemia is linked to both forms of diabetes, the patterns and underlying mechanisms differ. The main causes of lipid abnormalities in T1DM are inadequate insulin production and poor glycemic control. [ 8 ] On the other hand, central obesity, hypertension, and insulin resistance are major contributors to metabolic syndrome and T2DM-associated dyslipidemia. [ 13 ] With T2DM, the lipid profile is usually more atherogenic, which raises the risk of cardiovascular events. Understanding the distinctions in lipid profiles between T1DM and T2DM is essential for formulating customized treatment plans aimed at reducing the risk of CVD. A crucial component of comprehensive diabetes care involves managing dyslipidemia with medication, lifestyle changes, and optimal glycemic control. Further research into the mechanisms underlying these lipid abnormalities and their impact on cardiovascular outcomes will improve our capacity to properly monitor and treat diabetic dyslipidemia.

Despite the extensive literature on dyslipidemia in diabetes, there is limited research specifically characterizing lipid profile variations between T1DM and T2DM in Saudi Arabia. Given the unique genetic, lifestyle and environmental factors affecting the Saudi population, understanding these differences is essential for preventive and therapeutic strategies. This study aims to bridge this gap by analyzing and comparing lipid profile patterns among Saudi patients with T1DM and T2DM, providing data that can enhance region-specific clinical management of dyslipidemia and cardiovascular risk in diabetic individuals.

— Source (introduction, peer-reviewed): Fatemah Saleh Bin Saleh, Ahmed R. Alibrahim, Awad S. Alshahrani, et al. · (2025) · "Lipid metabolism in type 1 and type 2 diabetes: A comparative cross-sectional study" · Medicine · doi: 10.1097/MD.0000000000046758 · PMCID: PMC12747025 · PMID: 41465900
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Made Krisna Adi Jaya, Fita Rahmawati, Nanang Munif Yasin, et al. · (2025) · "Development and Validation of an Instrument to Assess the Safe Use of Antidiabetic Medication to Prevent Hypoglycemia Requiring Hospitalization Among Ambulatory Patients With Type 2 Diabetes Mellitus in Bali, Indonesia" · Journal of Preventive Medicine and Public Health · doi: 10.3961/jpmph.24.424 · PMCID: PMC11824621 · PMID: 39638302

Question: What is the published background on "Development and Validation of an Instrument to Assess the Safe Use of Antidiabetic Medication to Prevent Hypoglycemia Requiring…"? Cite a peer-reviewed source.

Answer:
Patient safety is an essential aspect of healthcare services in various countries, including Indonesia. However, the implementation of comprehensive patient safety measures in Indonesian healthcare facilities remains challenging. This is primarily due to the lack of effective collaboration among health workers, managers, and support staff [ 1 , 2 ]. Previous studies have shown that hypoglycemia is a severe condition that is recognized as a leading cause of death. It is also associated with higher mortality rates, increased disease morbidity, and reduced quality of life, all of which significantly impact healthcare costs borne by both patients and the government [ 3 , 4 ].

Several studies have indicated that the additional costs associated with hypoglycemia in patients with diabetes mellitus (DM) range from US$1353 to US$2285. In Indonesia, the government incurred total costs of US$23 million in 2016 for treating these cases [ 3 , 5 – 7 ]. Furthermore, the incidence of hypoglycemia among ambulatory DM patients resembles the iceberg phenomenon, with many cases remaining undetected and unreported within the health system. This issue may stem from patients’ limited knowledge and awareness of the condition. Approximately 90% of DM patients have reported experiencing mild to severe hypoglycemia while managing their condition with antidiabetic agents at home. A cohort study in Indonesia found that 99.4% of patients with type 2 diabetes mellitus (T2DM) experienced at least 1 hypoglycemic event over a 4-week period (prospective study), with a hypoglycemia incidence rate of 25.7 events per patient-year [ 8 – 10 ].

In line with these findings, clinical pharmacists play a crucial role in ensuring patient safety. These professionals are integral to drug services and are key in preventing adverse drug events [ 7 , 11 ]. Despite their significant role, clinical pharmacists still require guidance to effectively review medications. Currently, in Indonesia, there is no specific tool designed to assess the risk of hospitalization due to hypoglycemia caused by antihyperglycemic medications, highlighting a critical gap that needs to be addressed. Additionally, there is a local need for a simple and efficient method to evaluate the risk profile of T2DM patients experiencing ambulatory hypoglycemia, which can be conducted by clinical pharmacists. Consequently, this study aimed to develop an instrument for clinical pharmacists to assess the risk of medication-related hypoglycemia in ambulatory T2DM patients. The instrument, named “Medication-related Hypoglycemia Risk Score Assessment Tools (HYPOGLYRISK),” is expected to significantly enhance the quality of care and patient safety.

— Source (introduction, peer-reviewed): Made Krisna Adi Jaya, Fita Rahmawati, Nanang Munif Yasin, et al. · (2025) · "Development and Validation of an Instrument to Assess the Safe Use of Antidiabetic Medication to Prevent Hypoglycemia Requiring Hospitalization Among Ambulatory Patients With Type 2 Diabetes Mellitus in Bali, Indonesia" · Journal of Preventive Medicine and Public Health · doi: 10.3961/jpmph.24.424 · PMCID: PMC11824621 · PMID: 39638302
License: CC-BY-NC. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Carolina B. Lobato, Clara Tornøe Winding, Kirstine N. Bojsen‐Møller, et al. · (2026) · "Acarbose or Canagliflozin vs. Placebo to Ameliorate Post‐Bariatric Hypoglycaemia: The Clinical Outcomes of the HypoBar I Randomised Clinical Trial" · Diabetes, Obesity & Metabolism · doi: 10.1111/dom.70611 · PMCID: PMC13071188 · PMID: 41810556

Question: Summarize the abstract of the paper titled "Acarbose or Canagliflozin vs. Placebo to Ameliorate Post‐Bariatric Hypoglycaemia: The Clinical Outcomes of the HypoBar I Randomised Clinical Trial".

Answer:
Treatment options for post‐bariatric hypoglycaemia (PBH) are empirical. We aimed to investigate the efficacy and safety of acarbose and canagliflozin for the treatment of PBH.

We performed a randomised, double‐blinded, cross‐over, placebo‐controlled clinical trial where placebo, acarbose 50 mg thrice daily, and canagliflozin 300 mg twice daily were administered for 4 weeks. Treatment effects on blood glucose were monitored through blinded continuous glucose monitoring (CGM) for 10 days at the end of each intervention along with collection of patient‐reported outcomes. The primary outcome was the percentage of time below range during CGM (interstitial glucose below 3.9 mM/70 mg/dL).

Eleven participants with Roux‐en‐Y gastric bypass and documented PBH completed the trial. When compared with placebo, neither canagliflozin nor acarbose reduced the percentage of time below range (primary outcome, time below 3.9 mmol/L, median (IQR): screening 2.6 (0.7–5.1)%, placebo 1.2 (0.5–2.4)%, acarbose 1.1 (0.8–1.7)% and canagliflozin 0.8 (0.5–3.4)%). Both interventions, however, showed exploratory improvements in pre‐specified secondary outcomes, including time in range and glycaemic variability, as well as a reduction of symptoms of hypoglycaemia and frequency of symptomatic hypoglycaemic events, particularly with canagliflozin. Acarbose was associated with moderate and common side effects that caused treatment discontinuation in one participant. For both treatments, no severe adverse events were documented.

HypoBar I is the first randomised, placebo‐controlled study of the treatment of PBH with acarbose or canagliflozin. Reduction in time below range was not achieved by either treatment; nevertheless, improvements in hypothesis‐generating secondary findings merit further investigation and validation. EudraCT number 2022‐000157‐87.

— Source (abstract, peer-reviewed): Carolina B. Lobato, Clara Tornøe Winding, Kirstine N. Bojsen‐Møller, et al. · (2026) · "Acarbose or Canagliflozin vs. Placebo to Ameliorate Post‐Bariatric Hypoglycaemia: The Clinical Outcomes of the HypoBar I Randomised Clinical Trial" · Diabetes, Obesity & Metabolism · doi: 10.1111/dom.70611 · PMCID: PMC13071188 · PMID: 41810556
License: CC-BY-NC. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Beatrice Kennedy, Mona-Lisa Wernroth, Sophie Langenskiöld, et al. · (2025) · "The impact of child type 1 diabetes on parental incomes in a welfare state context: quasi-experimental evidence from Swedish national registers" · Diabetologia · doi: 10.1007/s00125-025-06492-6 · PMCID: PMC12423126 · PMID: 40781566

Question: What did the discussion section of the paper "The impact of child type 1 diabetes on parental incomes in a welfare state context: quasi-experimental evidence from Swedish national registers" cover?

Answer:
In this population-based study, parenting a child diagnosed with type 1 diabetes was linked to a sharp decline in work-related income. The decrease was more persistent in mothers and represented a larger proportion of their earnings than for fathers. In contrast, maternal pension-qualifying incomes increased after a child’s diabetes diagnosis, attributable to the parental care allowance. However, during the second half of the 17 year follow-up period, maternal pension-qualifying incomes gradually decreased and had not recovered by the end of the study period.

— Source (discussion, peer-reviewed): Beatrice Kennedy, Mona-Lisa Wernroth, Sophie Langenskiöld, et al. · (2025) · "The impact of child type 1 diabetes on parental incomes in a welfare state context: quasi-experimental evidence from Swedish national registers" · Diabetologia · doi: 10.1007/s00125-025-06492-6 · PMCID: PMC12423126 · PMID: 40781566
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Mingliang Liu, Shihang Chen, Shi Wu, et al. · (2026) · "Comparative predictive value of the cholesterol-high-density lipoprotein-glucose index versus the triglyceride-glucose index for gestational dysglycemia: a two-cohort study" · Frontiers in Endocrinology · doi: 10.3389/fendo.2026.1801546 · PMCID: PMC13158057 · PMID: 42125228

Question: Summarize the abstract of the paper titled "Comparative predictive value of the cholesterol-high-density lipoprotein-glucose index versus the triglyceride-glucose index for gestational dysglycemia: a two-cohort study".

Answer:
Early risk stratification for gestational dysglycemia is important for improving maternal and neonatal outcomes. Derived from fasting triglycerides and glucose, the triglyceride–glucose (TyG) index is widely used to approximate insulin resistance, whereas the cholesterol-high-density lipoprotein-glucose (CHG) index incorporates broader lipid metabolism. We compared the associations and discriminative performance of TyG and CHG in a national survey discovery cohort and an independent clinical validation cohort.

We analyzed a survey-weighted discovery cohort from NHANES 2007–2018, in which the primary outcome was self-reported GDM history. We further evaluated an independent validation cohort with clinically diagnosed GDM (n = 217). Associations and predictive performance were assessed using multivariable logistic regression, receiver operating characteristic (ROC) analysis, calibration analysis, and decision curve analysis (DCA). Additional analyses included adjustment for continuous fasting blood glucose in NHANES, supportive analyses restricted to currently pregnant NHANES participants from 2007–2012 using proxy-defined gestational fasting dysglycemia (fasting blood glucose ≥5.1 mmol/L), and gestational-week-adjusted sensitivity analyses in the validation cohort.

In the NHANES discovery cohort, CHG showed a stronger association with self-reported GDM history than TyG in the primary adjusted models and yielded a numerically higher AUC than TyG. After additional adjustment for continuous fasting blood glucose, the association for TyG was attenuated, whereas CHG remained significantly associated. In the clinical validation cohort, CHG also showed numerically higher discriminative performance than TyG, and the overall findings remained directionally consistent after gestational-week adjustment. Supportive analyses in currently pregnant NHANES participants showed directionally similar but statistically imprecise estimates because of the limited sample size.

Both TyG and CHG are simple, low-cost indices associated with gestational dysglycemia/GDM. Across the discovery and validation cohorts, CHG generally showed stronger associations and numerically better discrimination than TyG; however, its overall discriminative performance remained modest and should be interpreted as that of a potential risk marker rather than a standalone clinical screening tool. Further prospective studies are needed to validate these findings.

— Source (abstract, peer-reviewed): Mingliang Liu, Shihang Chen, Shi Wu, et al. · (2026) · "Comparative predictive value of the cholesterol-high-density lipoprotein-glucose index versus the triglyceride-glucose index for gestational dysglycemia: a two-cohort study" · Frontiers in Endocrinology · doi: 10.3389/fendo.2026.1801546 · PMCID: PMC13158057 · PMID: 42125228
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Hironori Bando, Masaaki Yamamoto, Shin Urai, et al. · (2024) · "Fluctuations in plasma adrenocorticotropic hormone concentration may predict the onset of immune checkpoint inhibitor-related hypophysitis" · Journal for Immunotherapy of Cancer · doi: 10.1136/jitc-2023-008634 · PMCID: PMC10910626 · PMID: 38418395

Question: What is the published background on "Fluctuations in plasma adrenocorticotropic hormone concentration may predict the onset of immune checkpoint inhibitor-related hypophysitis"? Cite a peer-reviewed source.

Answer:
Immune checkpoint inhibitors (ICIs) are widely used to treat various malignant neoplasms. Programmed cell death protein 1 (PD-1), programmed death ligand 1 (PD-L1), and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) are the ICI targets. However, ICI treatment can lead to immune-related adverse events (irAEs), including autoimmune endocrinopathies. Pituitary insufficiency due to ICI-related hypophysitis (ICI-RH) is a common irAE. The development of pituitary insufficiency in patients receiving ICIs is associated with better overall survival in several malignancies. 1 However, the appropriate diagnosis, early detection, and treatment of hypopituitarism are essential. Adrenal insufficiency due to hypopituitarism can be lethal if not properly managed. Life-threatening adrenal insufficiency is characterized by appetite loss, abdominal pain, and extreme fatigue, which mimics sepsis, brain metastasis, and cachexia. 2 The frequency and timing of onset vary with ICI class. The frequency of ICI-RH in anti-CTLA-4 antibody (Ab)-based regimens is 5%–10% with a median onset of 9–12 weeks, and that in anti-programmed cell death-1 (PD-1) and programmed cell death ligand 1 (PD-L1)-based regimens is <1% with a median onset of 26 weeks. 3 However, the timing of disease onset varies considerably among cases, hindering the prediction of disease onset.

The clinical features of anti-CTLA-4 and anti-PD-1/anti-PD-L1 Ab-RH differ. Anti-CTLA-4 Ab-RH causes panhypopituitarism, including secondary hypothyroidism, hypogonadotropic hypogonadism, and secondary adrenal insufficiency. 4 In contrast to anti-CTLA-4 Ab-RH, anti-PD-1/PD-L1 Ab-RH predominantly causes an isolated adrenocorticotropic hormone (ACTH) deficiency. 5 These different patterns may result from different underlying mechanisms. 6 However, secondary adrenal insufficiency accounts for 83% of ICI-RH cases. 7 Therefore, predictive markers for the onset of secondary adrenal insufficiency are essential.

Tahir et al reported autoantibodies against guanine nucleotide-binding protein G(olf) subunit alpha (GNAL) and integral membrane protein 2 B (ITM2B) as biomarkers for ICI-RH. 8 However, these biomarkers are still under investigation and cannot be measured routinely. Therefore, markers that can predict the onset of hypopituitarism under regular measures are necessary. Several studies have reported an elevation of the eosinophil fraction and count during the last visit and at the onset of hypopituitarism. 9 10 These studies raised a crucial point; however, one report also showed that the cortisol concentration had already mildly decreased at the last visit, which may be seen as a sign that ICI-RH is already under development. 9 Eosinophilia is a well-known marker of already developed adrenal insufficiency. 11

Thyroiditis is one of the most common irAEs. ICI-related thyroiditis typically occurs biphasically: thyrotoxicosis, followed by a subsequent persistent hypothyroidism. 12 In the initial thyrotoxicosis phase, free thyroxine and triiodothyronine levels are elevated while those of thyroid-stimulating hormone are suppressed. In the hypothyroidism phase, the pattern is reversed. The underlying mechanism of ICI-related thyroid dysfunction remains unknown. We speculated that, if the pituitary gland is damaged in ICI-RH by a mechanism similar to that of thyroiditis, plasma ACTH and serum cortisol levels, which are indicators of the hypothalamic pituitary adrenal (HPA) axis in routine practice, may fluctuate during the process. If so, they could potentially be used as predictive factors for the onset of secondary adrenal insufficiency in ICI-RH. To explore this possibility, we collected data on plasma ACTH and serum cortisol levels in patients using ICIs and analyzed fluctuations in hormone concentrations.

— Source (introduction, peer-reviewed): Hironori Bando, Masaaki Yamamoto, Shin Urai, et al. · (2024) · "Fluctuations in plasma adrenocorticotropic hormone concentration may predict the onset of immune checkpoint inhibitor-related hypophysitis" · Journal for Immunotherapy of Cancer · doi: 10.1136/jitc-2023-008634 · PMCID: PMC10910626 · PMID: 38418395
License: CC-BY-NC. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


So Won Baek, Jung Ho Noh, Yeon Sik Heo · (2023) · "Prevalence of Adrenal Insufficiency in Korean Patients undergoing Total Knee Arthroplasty" · Annals of Geriatric Medicine and Research · doi: 10.4235/agmr.23.0123 · PMCID: PMC10982440 · PMID: 37984965

Question: Summarize the abstract of the paper titled "Prevalence of Adrenal Insufficiency in Korean Patients undergoing Total Knee Arthroplasty".

Answer:
This study investigated the prevalence of adrenal insufficiency among patients admitted for total knee arthroplasty (TKA) due to osteoarthritis and identified factors contributing to adrenal insufficiency.

We divided the patients into two groups based on the results of preoperative standard-dose short synchronous stimulation tests: group 1 (adrenal insufficiency) and group 2 (normal adrenal function). We also assessed the prevalence of adrenal insufficiency and compared the numbers of patients who received oral steroids, the frequency of previous steroid injection use, and the frequency of systemic symptoms of steroid depletion such as fatigue and loss of appetite between the two groups. Multiple regression analysis was performed to identify factors related to adrenal insufficiency.

The prevalence of adrenal insufficiency was 60.0% (120/200). Group 1 had higher numbers of previous steroid injections (12.8±10.2 vs. 6.8±7.9) and patients taking oral steroids (18/120 vs. 3/80) (p<0.001 and p=0.011, respectively). The frequency of systemic symptoms of steroid depletion, such as fatigue and loss of appetite, was also higher in group 1 (94/120 vs. 42/80, p<0.001). Recent steroid injections and loss of appetite were associated with adrenal insufficiency (p=0.002 and p=0.009, respectively).

The results of this study revealed a high prevalence of adrenal insufficiency in Korean patients hospitalized for TKA due to end-stage osteoarthritis. Recent steroid injections were causally related to the development of adrenal insufficiency. Therefore, adrenal function should be assessed preoperatively to prevent postoperative complications related to adrenal insufficiency.

— Source (abstract, peer-reviewed): So Won Baek, Jung Ho Noh, Yeon Sik Heo · (2023) · "Prevalence of Adrenal Insufficiency in Korean Patients undergoing Total Knee Arthroplasty" · Annals of Geriatric Medicine and Research · doi: 10.4235/agmr.23.0123 · PMCID: PMC10982440 · PMID: 37984965
License: CC-BY-NC. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Wasu Mekniran, Wilma Diethelm, Victoire Stalder, et al. · (2026) · "Digital health technologies and stakeholder incentives in type-2 diabetes prevention" · Digital Health · doi: 10.1177/20552076261425402 · PMCID: PMC12982865 · PMID: 41836627

Question: What did the discussion section of the paper "Digital health technologies and stakeholder incentives in type-2 diabetes prevention" cover?

Answer:
Despite well-established scientific evidence for the prevention of T2D through sustained lifestyle change, 2 – 5 preventive programs are seldom integrated and sustained within traditional healthcare systems. How is the uptake and systemic implementation of prevention associated with stakeholder incentives, specifically between individuals, payers, and providers? Grounded in an ecosystem theory 8 , 34 and the e3-value ontology, 36 , 37 this is the first study, to our knowledge, that examines incentives among individuals, payers, and providers and the associations between DHT adoption and stakeholder value flows in the digital T2D prevention context.

Our findings support theoretical perspectives that prevention is contingent on a dynamic network of interdependent actors. 33 , 34 We identify three main insights. First, financial and non-financial incentives for lifestyle-based prevention are often temporally misaligned: engagement in lifestyle-based prevention may provide individuals with short-term benefits such as convenience, rewards, and improved health benefits, while payers are often motivated to support prevention programs as a function of long-term cost savings. Second, we find that DHT adoption for T2D prevention is associated with three main incentive patterns: personalization and convenience for individuals, value-based payment models for payers, and improving workflow efficiency for providers. DHTs may help support the realignment of stakeholder incentives through three key interrelated mechanisms: (i) sustaining individual engagement in prevention programs through personalized micro-incentives, (ii) supporting value-based payment models for payers, and (iii) automating workflows for providers. Using the e3-value framework, we visualize these reconfigured value exchanges ( Figure 2 ), illustrating how DHTs may support a shared data-driven infrastructure to enhance individual engagement, performance tracking, and shared accountability across the ecosystem. 28

Building on the stakeholder incentive literature, 10 , 13 our identification of varying financial and non-financial is consistent with perspectives that prevention incentives remain highly fragmented across stakeholder groups As detailed in Table 4 , this fragmentation is particularly evident in the temporal dimension: individuals are primarily motivated to engage in lifestyle programs and prevention efforts based on short-term, tangible rewards such as cashback, gamified tokens, or convenience-enhancing lifestyle tracking apps (i.e., “Upload [photos of] your meals for today. You earn a few utility tokens,” ID 23), In contrast, insurers and providers are more likely to prioritize delayed benefits like reduced readmissions or loyalty-based retention to their services and plans over extended periods of time, and at the population level (Prior work examining incentives has specifically focused on provider reimbursement models and patient adherence to treatment plans, finding fragmented financial incentives among various healthcare stakeholders (i.e., pay-for-service models disincentivizing preventive care). 17

Here, we also identified perceived trust in data fairness as an additional non-financial incentive for individuals to engage with DHTs for T2D prevention. This finding reframes data privacy, not as a compliance issue, 70 but as a potential behavioral motivator, potentially associated with willingness to engage with DHTs. For providers and payers, data privacy primarily functions as a regulatory compliance incentive, crucial for avoiding penalties and maintaining public trust. Furthermore, strong data privacy can also serve as a non-financial incentive for patient and customer acquisition or retention.

— Source (discussion, peer-reviewed): Wasu Mekniran, Wilma Diethelm, Victoire Stalder, et al. · (2026) · "Digital health technologies and stakeholder incentives in type-2 diabetes prevention" · Digital Health · doi: 10.1177/20552076261425402 · PMCID: PMC12982865 · PMID: 41836627
License: CC-BY-NC. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Yuuki Yanagisawa · (2023) · "How dietary amino acids and high protein diets influence insulin secretion" · Physiological Reports · doi: 10.14814/phy2.15577 · PMCID: PMC9875820 · PMID: 36695783

Question: What is the published background on "How dietary amino acids and high protein diets influence insulin secretion"? Cite a peer-reviewed source.

Answer:
Glucose is the simplest and most abundant monosaccharide known to man and is the primary biological fuel source for the human body (Hantzidiamantis & Lappin, 2022 ). Glucose is obtained from three fundamental sources—exogenously from dietary intake, from glycogenolysis in the liver and muscle, and gluconeogenesis in the liver, kidneys, and intestine (Aronoff et al., 2004 ).

Glucose homeostasis is the maintenance and regulation of blood glucose levels within the narrow range of 4 to 6 mmol/L and is critical for maintaining the normal physiological functioning of most organs and tissues (Pozo, 2018 ; Roder et al., 2016 ). Glucose homeostasis is achieved through the coordination of glucose sensing mechanisms which detect fluctuations in blood glucose concentration with multiple effector responses which act to re‐establish blood glucose levels within this tight target range (Pozo, 2018 ). Effector responses are mediated by several complex neural and endocrine networks, involving several neurotransmitters, neuropeptides, and glucoregulatory hormones (Aronoff et al., 2004 ). The pancreas is a critical source of glucoregulatory hormones, which are synthesized and secreted by collections of specialized endocrine cells found within the islets of Langerhans (Aronoff et al., 2004 ; Petersen, 2018 ; Roder et al., 2016 ). Insulin is an anabolic hormone secreted by pancreatic β cells in response to increased blood glucose concentration (Petersen, 2018 ). Insulin decreases blood glucose concentrations by promoting glucose uptake into muscle and adipose tissues, stimulating hepatic glycogenesis, and downregulating gluconeogenesis (Aronoff et al., 2004 ; Petersen, 2018 ). Insulin also increases cellular uptake of amino acids from the peripheral circulation, facilitating intracellular protein synthesis (Zakaria et al., 2021 ). In contrast, glucagon is released from α cells in states of fasting and hypoglycemia. Glucagon raises blood glucose concentration by inducing gluconeogenesis and glycogenolysis (Roder et al., 2016 ).

In addition to insulin and glucagon, several other glucoregulatory hormones contribute to glucose homeostasis (Aronoff et al., 2004 ; Renner et al., 2015 ). These include somatostatin, and the incretins glucagon‐like peptide 1 (GLP‐1) and glucose‐dependent insulinotropic peptide (GIP). Somatostatin is secreted from delta cells within the islets of Langerhans, stomach, and small intestine (O'Toole & Sharma, 2022 ). Somatostatin inhibits the release of both insulin and glucagon, as well as the release of pancreatic exocrine secretions (O'Toole & Sharma, 2022 ; Strowski et al., 2000 ). In comparison, the latter two peptide hormones GLP‐1 and GIP are secreted from L‐ and K‐enteroendocrine cells of the intestine, respectively (Aronoff et al., 2004 ). Both GLP‐1 and GIP potentiate glucose‐dependent insulin secretion, enhance β‐cell proliferation, and downregulate β‐cell apoptosis, and GLP‐1 also inhibits glucagon secretion (Renner et al., 2015 ).

Chronic impairment or deficiency of these glucoregulatory responses can lead to the development of diabetes mellitus, a major global health epidemic associated with considerable clinical sequelae, and vast financial and healthcare ramifications (O'Connell & Manson, 2019 ). At present, 463 million people worldwide are estimated to suffer from diabetes mellitus, which can be classified as Type 1 or Type 2 diabetes mellitus (T1DM or T2DM) (Saeedi et al., 2019 ). In the UK, approximately 90% of the diabetic population have T2DM, with T1DM accounting for 8% of patients (Diabetes UK, n.d. ). T2DM is characterized by peripheral resistance to insulin coupled with progressive β‐cell failure and relative insulin deficiency (Strowski et al., 2000 ). In contrast, T1DM is defined by complete or near complete insulin deficiency due to the autoimmune destruction of β cells (Diabetes UK, n.d. ).

Given the long‐term complications of T2DM such as cardiovascular and cerebrovascular disease, congestive heart failure, and predisposition to recurrent infection, an ever‐growing demand exists to better understand and improve persistent hyperglycemia associated with T2DM, potentially through the use of high protein diets (HPDs) (Diabetes UK, n.d. ; Toft‐Nielsen et al., 2001 ).

A HPD is specifically defined as a diet supplying 35% or more of daily total energy intake in the form of protein (O'Connell & Manson, 2019 ; Saeedi et al., 2019 ). Proteins are macronutrients, composed of one or more chains of different amino acids. Animal proteins such as whey, casein, egg, fish, beef, and chicken, along with plant‐based proteins including soy, pea, brown rice, and chickpea are essential for multiple physiological and homeostatic activities within the body (Lupton et al., 2005 ). In particular, amino acids and HPDs can also influence glucose homeostasis (Galbreath et al., 2018 ; Lupton et al., 2005 ; Morell, 2017 ; Parker et al., 2002 ; Pasiakos et al., 2013 ; Stokes et al., 2018 ; Tipton, 2011 ). Multiple studies conducted in rodents and humans have shown that consumption of protein and amino acids leads to weight loss and improves glucose homeostasis (Galbreath et al., 2018 ; Morell, 2017 ; Parker et al., 2002 ; Pasiakos et al., 2013 ; Stokes et al., 2018 ). Although the effects of HPDs are generated by the physiological activities of their constituent amino acids, pharmacological administration of amino acids can differentially impact glucose homeostasis. This is in part due to differences in digestion time, the rate of gastric emptying and release into the blood stream, and the utilization following digestion (Pena et al., 2015 ).

Despite the physiological benefits of amino acids and HPDs, there are concerns regarding the implications of their long‐term consumption, particularly nephrotoxicity (Cirillo et al., 2014 ; Knight et al., 2003 ; Pasiakos et al., 2013 ). Several long‐term observational studies conducted in adults have found an association between high protein intake and decline in renal function, in both participants with normal renal function and those with pre‐existing renal disease (Cirillo et al., 2014 ; Knight et al., 2003 ). These complications, along with relatively poor levels of adherence to HPDs, have raised the question if the mechanisms by which amino acids and HPDs improve glucose homeostasis can be exploited without the need for the consumption of high levels of dietary protein.

This review will examine the different insulinotropic and non‐insulinotropic mechanisms by which amino acids and HPDs influence glucose homeostasis and their supporting evidence. The translational potential to exploit these mechanisms for the management of diabetes mellitus will also be discussed.

— Source (introduction, peer-reviewed): Yuuki Yanagisawa · (2023) · "How dietary amino acids and high protein diets influence insulin secretion" · Physiological Reports · doi: 10.14814/phy2.15577 · PMCID: PMC9875820 · PMID: 36695783
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Vit Neuman, Lukas Plachy, Stepanka Pruhova, et al. · (2021) · "Low-Carbohydrate Diet among Children with Type 1 Diabetes: A Multi-Center Study" · Nutrients · doi: 10.3390/nu13113903 · PMCID: PMC8622801 · PMID: 34836158

Question: Summarize the abstract of the paper titled "Low-Carbohydrate Diet among Children with Type 1 Diabetes: A Multi-Center Study".

Answer:
Aims/hypothesis: The proportion of children with type 1 diabetes (T1D) who have experience with low-carbohydrate diet (LCD) is unknown. Our goal was to map the frequency of LCD among children with T1D and to describe their clinical and laboratory data. Methods: Caregivers of 1040 children with T1D from three centers were addressed with a structured questionnaire regarding the children’s carbohydrate intake and experience with LCD (daily energy intake from carbohydrates below 26% of age-recommended values). The subjects currently on LCD were compared to a group of non-LCD respondents matched to age, T1D duration, sex, type and center of treatment. Results: A total of 624/1040 (60%) of the subjects completed the survey. A total of 242/624 (39%) subjects reported experience with voluntary carbohydrate restriction with 36/624 (5.8%) subjects currently following the LCD. The LCD group had similar HbA1c (45 vs. 49.5, p = 0.11), lower average glycemia (7.0 vs. 7.9, p = 0.02), higher time in range (74 vs. 67%, p = 0.02), lower time in hyperglycemia >10 mmol/L (17 vs. 20%, p = 0.04), tendency to more time in hypoglycemia <3.9 mmol/L(8 vs. 5%, p = 0.05) and lower systolic blood pressure percentile (43 vs. 74, p = 0.03). The groups did not differ in their lipid profile nor in current body height, weight or BMI. The LCD was mostly initiated by the parents or the subjects themselves and only 39% of the families consulted their decision with the diabetologist. Conclusions/interpretation: Low carbohydrate diet is not scarce in children with T1D and is associated with modestly better disease control. At the same time, caution should be applied as it showed a tendency toward more frequent hypoglycemia.

— Source (abstract, peer-reviewed): Vit Neuman, Lukas Plachy, Stepanka Pruhova, et al. · (2021) · "Low-Carbohydrate Diet among Children with Type 1 Diabetes: A Multi-Center Study" · Nutrients · doi: 10.3390/nu13113903 · PMCID: PMC8622801 · PMID: 34836158
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Federico Baronio, Giacomo Biasucci, Egidio Candela, et al. · (2025) · "Glucose dynamics in glycogen storage disease type IXa with novel PHKA2 variants: insights from our experience and a comprehensive review of the disease spectrum" · Hormones (Athens, Greece) · doi: 10.1007/s42000-025-00712-9 · PMCID: PMC12678572 · PMID: 40866742

Question: What does the published research conclude about "Glucose dynamics in glycogen storage disease type IXa with novel PHKA2 variants: insights from our experience and a comprehensive review of…"? Cite a peer-reviewed source.

Answer:
Our clinical cases have shown that patients with GSX IXa present only with hypoglycemia without any liver abnormalities or other significant symptoms. Therefore, if a patient experiences recurrent episodes of ketotic hypoglycemia and other endocrinological causes that have been ruled out, it is crucial to consider genetic testing for GSX IXa. A timely diagnosis can help establish an appropriate diet plan and prevent complications.

— Source (conclusions, peer-reviewed): Federico Baronio, Giacomo Biasucci, Egidio Candela, et al. · (2025) · "Glucose dynamics in glycogen storage disease type IXa with novel PHKA2 variants: insights from our experience and a comprehensive review of the disease spectrum" · Hormones (Athens, Greece) · doi: 10.1007/s42000-025-00712-9 · PMCID: PMC12678572 · PMID: 40866742
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Colleen A. Macke, Iman Al-Gadi, Nidhi Bansal, et al. · (2025) · "Hypertriglyceridemia in New-Onset Type 1 Pediatric Diabetes" · Pediatric Diabetes · doi: 10.1155/pedi/8425032 · PMCID: PMC12226158 · PMID: 40612706

Question: Summarize the abstract of the paper titled "Hypertriglyceridemia in New-Onset Type 1 Pediatric Diabetes".

Answer:
Hypertriglyceridemia (HTG) in the setting of newly diagnosed diabetes is common in both adult and pediatric populations, as insulin deficiency promotes lipolysis and impairs triglyceride (TG) clearance. Severe HTG (defined as TG levels above 1000 mg/dL) in pediatric patients with new-onset type 1 diabetes mellitus (T1D) is rare; the true incidence and sequela of this phenomenon have not been well characterized. We present a single-center experience on severe HTG in pediatric patients with new-onset T1D between 2013 and 2022 and summarize the cases previously reported in the literature. Our cases display variability in their presentation and in their association with high-risk complications, such as acute pancreatitis. We discuss suggestions of early screening for HTG and pancreatitis in patients with protracted abdominal pain, and close monitoring of those identified to have significant HTG.

— Source (abstract, peer-reviewed): Colleen A. Macke, Iman Al-Gadi, Nidhi Bansal, et al. · (2025) · "Hypertriglyceridemia in New-Onset Type 1 Pediatric Diabetes" · Pediatric Diabetes · doi: 10.1155/pedi/8425032 · PMCID: PMC12226158 · PMID: 40612706
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


Yue-Yang Zhang, Yao-Wen Liu, Bing-Xue Chen, et al. · (2024) · "Association between gut microbiota and adrenal disease: a two-sample Mendelian randomized study" · Frontiers in Cellular and Infection Microbiology · doi: 10.3389/fcimb.2024.1421128 · PMCID: PMC11269257 · PMID: 39055981

Question: What is the published background on "Association between gut microbiota and adrenal disease: a two-sample Mendelian randomized study"? Cite a peer-reviewed source.

Answer:
Adrenal diseases are vital components of endocrine system disorders, chiefly encompassing Adrenocortical insufficiency (AI), Cushing syndrome(CS), and Hyperaldosteronism(HA) ( Salman and Cohen, 2021 ). AI manifests as adrenal cortex dysfunction, resulting in absolute or relative insufficiency of cortisol secretion ( Bancos et al., 2015 ). Primary adrenal insufficiency, such as Addison’s disease, is relatively rare and typically arises from direct adrenal failure ( Erichsen et al., 2009 ; Ross and Levitt, 2013 ; Bornstein et al., 2016 ). Conversely, secondary adrenal cortex insufficiency, more prevalent, stems mainly from pituitary damage affecting adrenocortical hormone secretion ( Grossman, 2010 ; Hahner et al., 2021 ). AI frequently progresses to adrenal crisis, significantly heightening patient mortality rates ( Dineen et al., 2019 ). Prolonged elevation of endogenous cortisol levels can result in Cushing’s syndrome, leading to numerous organ complications such as hypertension, obesity, dysregulation of glucose and lipid metabolism, and cognitive impairment ( Pivonello et al., 2016 ). These complications arise due to the impact on the nervous and immune systems, ultimately diminishing the patient’s quality of life ( Hatipoglu, 2012 ; Ferriere and Tabarin, 2020 ). Hyperaldosteronism primarily involves primary aldosterone elevation and stands as a frequent cause of hypertension, often inflicting direct damage on target organs ( Zennaro et al., 2020 ). Compared to diabetes, the incidence of adrenal diseases is relatively lower. However, with advancements in medical technology, their global incidence is on the rise. The prevalence of CS is 39.1 per million, with an annual incidence of 2.4 per 100,000. Reports indicate that since 1974, the prevalence of CS has increased almost linearly ( Steffensen et al., 2010 ), while the prevalence of AI has reached 100-140 per million ( Hahner et al., 2021 ). HS most commonly manifests as hypertension, and it is estimated that approximately 6%-10% of hypertensive patients are affected by HS ( Monticone et al., 2017 ). These data suggest that adrenal diseases are impacting an increasing number of patients, gradually becoming a significant focus of global public health efforts.

The gut microbiota, defined as the microbial community residing in the human gastrointestinal tract, has garnered increasing attention due to mounting evidence suggesting its close association with various diseases in the body. For example, a case-control study observed a reduction in Bacteroidetes and an increase in Firmicutes and Proteobacteria in patients with CS ( Zhang et al., 2022 ). In a study involving 54 psoriasis patients and 27 healthy controls, genetic material from gut bacteria was detected in the plasma of 16 psoriasis patients, but not in any healthy controls. This discrepancy may be attributed to a reduction in the abundance of potential probiotics in psoriasis patients, resulting in immune system imbalance ( Mahmud et al ). Moreover, the relationship between obesity and gut microbiota is well established ( Gomes et al., 2018 ). It is widely believed that gut microbiota dysbiosis primarily induces disease by influencing the gut-brain axis and regulating brain function ( Anand et al., 2022 ). Animal studies have shown that microbial colonization in mice affects the development of the hypothalamic-pituitary-adrenal axis postnatally, suggesting that gut microbiota significantly impact adrenal function ( Sudo et al., 2004 ). Another study found that the excessive release of lipopolysaccharides into the blood by Gram-negative bacteria can hyperactivate the hypothalamic-pituitary-adrenal axis, inducing systemic and neuroinflammation, leading to increased cortisol secretion and severely disrupting central nervous system homeostasis ( Moylan et al., 2014 ). The probiotic B. pseudocatenulatum (CECT 7765) has been shown to reverse abnormal stress responses caused by dysregulation of glucocorticoid receptors ( Agusti et al., 2018 ). Treatment with Lactobacillus sp. during early maternal separation stress can normalize hypothalamic-pituitary-adrenal axis activity ( Gareau et al., 2007 ). L. farciminis has also been found to prevent excessive activation of the hypothalamic-pituitary-adrenal axis caused by restraint stress ( Ait-Belgnaoui et al., 2012 ).However, due to challenges in confirming exposure and outcome times in case-control studies, and because similar observational studies draw conclusions based on changes in microbial composition in patients’ feces, they are susceptible to various confounding factors such as age and environment ( Rinninella et al., 2019 ). These limitations impede causal inferences between gut microbiota and adrenal diseases, leaving the causal relationship between gut microbiota and adrenal diseases unresolved.

Mendelian randomization(MR) is currently recognized as a method capable of inferring causality between exposure and outcome. It utilizes genetic variants associated with exposure as instrumental variables to assess the association between exposure and outcome ( Greenland, 2000 ; Emdin et al., 2017 ). According to Mendelian genetic laws, genetic information is randomly allocated at conception, occurring prior to the onset of any disease. This randomization significantly minimizes the influence of environmental and lifestyle confounding factors. MR has been widely utilized to explore causal relationships between gut microbiota and various diseases, including preeclampsia ( Li et al., 2022 ), autoimmune diseases ( Xu et al., 2021 ), and others. However, research on the relationship between gut microbiota and AI, CS, and HA is relatively scarce. Thus, this study aimed to investigate the causal relationship between gut microbiota and various adrenal diseases by conducting a comprehensive two-sample MR analysis on three adrenal diseases, namely AI, CS, and HA.

— Source (introduction, peer-reviewed): Yue-Yang Zhang, Yao-Wen Liu, Bing-Xue Chen, et al. · (2024) · "Association between gut microbiota and adrenal disease: a two-sample Mendelian randomized study" · Frontiers in Cellular and Infection Microbiology · doi: 10.3389/fcimb.2024.1421128 · PMCID: PMC11269257 · PMID: 39055981
License: CC-BY. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.


K Jayakrishnan, Poonam Joshi, Aparajita Guin, et al. · (2026) · "Lived experiences of children with type 1 diabetes mellitus and their parents: a qualitative descriptive study from eastern India" · BMJ Open · doi: 10.1136/bmjopen-2025-111570 · PMCID: PMC13034286 · PMID: 41887636

Question: What is the published background on "Lived experiences of children with type 1 diabetes mellitus and their parents: a qualitative descriptive study from eastern India"? Cite a peer-reviewed source.

Answer:
Type 1 diabetes mellitus (T1DM) in children under 20-year old is a chronic autoimmune disease where the body’s immune system mistakenly attacks and destroys insulin-producing cells in the pancreas. 1 This destruction leads to a deficiency in insulin, a hormone essential for regulating blood sugar levels, resulting in various short-term and long-term health complications. 2 In 2022, there were an estimated 8.75 million people globally living with T1DM, with a 95% uncertainty interval ranging from 8.4 to 9.1 million. Approximately one-fifth, or 1.9 million, of these individuals were from low-income and lower middle-income countries. 3

Iatrogenic hypoglycaemia is an inevitable aspect of life for individuals with T1DM. These individuals experience numerous episodes of asymptomatic hypoglycaemia. For instance, a study using subcutaneous glucose sensors in people with T1DM found that their glucose levels were at or below 70 mg/dL (3.9 mmol/L) for an average of 1.5 hours each day, which constitutes 6.3% of the time. 4 Severe hypoglycaemia in children with type 1 diabetes is marked by cognitive dysfunctions like convulsions and coma that require external help and can be fatal, causing 4%–10% of deaths of the hypoglycaemic children. 5 Children with type 1 diabetes, along with their families, are at risk of heightened anxiety, insufficient sleep and a reduced quality of life. Particularly for families with younger children, the fear of severe hypoglycaemia during the night is a major concern. 6 This fear may drive them to accept higher blood glucose levels and engage in behaviours that avoid hypoglycaemia, ultimately resulting in suboptimal glycaemic control. 57 9

Witnessing severe hypoglycaemia events, such as seizures or loss of consciousness, can cause lasting distress, even if the child does not remember the episode. The fear of hypoglycaemia reduces the quality of life for both parents and children, significantly affecting parents’ emotional well-being and daily life. Addressing these psychological issues is crucial for effective diabetes management, necessitating education, coping strategies and emotional support. 10 12

Managing a child’s chronic illness adds to the burden, with parents struggling with the technical aspects of blood glucose management and balancing these responsibilities with other obligations. This role disrupts family dynamics and places emotional burdens on parents, who must adapt as their child grows and takes on more responsibility. 13 14 Financial strain and lack of social support further exacerbate these challenges. Recognising and addressing these issues is essential for healthcare providers to support both the child with T1DM and their parents. 15 According to a cross-sectional survey from North India, families spend an average of ₹55 185 annually on diabetes care, with insulin and glucose monitoring alone accounting for more than 90% of direct medical costs. Alarmingly, over 30% of families spend more than half their income on T1DM-related expenses. 16 Similarly, a study from a government-funded hospital in Uttar Pradesh found that the average annual cost per child was ₹27 915, with 87% of costs paid out-of-pocket and insulin and glucose testing supplies comprising nearly 80% of expenses. 17 Continuous Glucose Monitors (CGMs) and flash glucose monitoring systems remain largely inaccessible to most families due to their high upfront and maintenance costs and the lack of government subsidies. While some families with higher socioeconomic status or employer insurance may afford such devices, their widespread adoption in lower income settings remains extremely limited, highlighting the need for policy-level interventions to improve access and affordability. 16

Shortly after diagnosis, parents often experience shock, sadness, anxiety, disbelief, fear, frustration and despair. 8 14 15 18 19 Uncertainty about the disease’s progression and social impact can trigger guilt and anxiety, exacerbated by the condition’s ‘invisibility’ before diagnosis. 20 Following a child’s hospital discharge, caregivers frequently report worry, anxiety, sadness, stigma, annoyance and guilt, intensified by uncertainty about disease progression. 1 Healthcare providers must address these issues to offer holistic support, helping caregivers manage their mental health while caring for a child with T1DM. 11 12

This study is necessary to comprehensively understand the multifaceted difficulties encountered by both children with T1DM and their parents in eastern India. To the best of our knowledge, there are no qualitative studies from India that explore the lived experiences of both children with T1DM and their parents. By exploring the experiences and perspectives of both parents and children, the study aims to identify specific challenges in managing T1DM and understand the psychological, emotional and practical implications of the disease. The objectives of this study are to explore the challenges faced by parents in managing their children’s condition and to delve into the challenges experienced by the children themselves.

— Source (introduction, peer-reviewed): K Jayakrishnan, Poonam Joshi, Aparajita Guin, et al. · (2026) · "Lived experiences of children with type 1 diabetes mellitus and their parents: a qualitative descriptive study from eastern India" · BMJ Open · doi: 10.1136/bmjopen-2025-111570 · PMCID: PMC13034286 · PMID: 41887636
License: CC-BY-NC. Retrieved from PubMed Central full text.

Note: This reproduces published research findings. It is not individualized medical advice. Please discuss your situation with your healthcare provider or care team.