Managing type 2 diabetes mellitus (T2DM) in adults with severe obesity frequently coexists with obstructive sleep apnea (OSA), complicating metabolic control and quality of life. Real-world, objective monitoring-documented trajectories through which pharmacologic weight loss enables withdrawal of continuous positive airway pressure (CPAP) remain clinically informative.

A 48-year-old man (height 178 cm; weight 129 kg; BMI 40.7 kg/m²) had T2DM and severe OSA diagnosed by polysomnography (PSG), with persistent daytime sleepiness despite CPAP and body-weight fluctuations between 108 and 129 kg.

T2DM with class III obesity and severe OSA with prior peak HbA1c of 8.2%.

Beginning in June 2023, tirzepatide was initiated with gradual dose escalation alongside nutritional counseling and light-to-moderate physical activity. At initiation, it was prescribed for glycemic control and weight reduction in T2DM and thus predated the subsequent U.S. FDA approval for OSA. OSA outcomes were later assessed with objective monitoring via CPAP telemonitoring as part of routine comorbidity care. CPAP was continued initially and reassessed after weight loss.

Within 3 months, weight decreased to 108 kg (BMI 34.1 kg/m²) with improved glycemic control. On CPAP telemonitoring, the device-derived residual apnea-hypopnea index decreased and remained low over time. Given sustained weight loss and improved symptoms, CPAP was discontinued under supervision. At the most recent follow-up, the patient weighed 82 kg (BMI 25.9 kg/m²) and reported improved daytime functioning. No severe adverse events occurred.

In selected adults with T2DM and OSA, tirzepatide-associated weight loss may contribute to device-monitored control of OSA on CPAP, enabling supervised withdrawal in carefully selected cases. While single-patient observations cannot establish causality, they complement emerging evidence and can guide patient counseling and hypothesis generation for prospective studies.

Immune checkpoint inhibitors have shown promising efficacy in treating various malignancies; however, their use is associated with immune-related adverse events, including rare but severe immune checkpoint inhibitor-induced diabetes mellitus (ICI-DM). Serplulimab-induced ICI-DM has been rarely reported, and its clinical presentation can be heterogeneous.

We report 2 patients with small cell lung cancer who developed serplulimab-induced ICI-DM, both complicated by diabetic ketoacidosis (DKA). Case 1 developed delayed-onset ICI-DM after 2 years of treatment, with elevated glycated hemoglobin and moderate C-peptide deficiency. Case 2 developed ICI-DM earlier, with severe insulin deficiency and classic type 1 diabetes features. Neither patient tested positive for diabetes-related autoantibodies.

Both patients were diagnosed with serplulimab-induced ICI-DM, confirmed by hyperglycemia, C-peptide deficiency, and DKA during ongoing programmed cell death protein 1 inhibitor therapy.

Standard DKA management was administered for both patients. They were transitioned to subcutaneous insulin therapy and continued serplulimab treatment under close glucose monitoring.

Both patients' DKA was successfully controlled. They continued serplulimab and insulin therapy after discharge, with no recurrence of acute DKA.

These cases highlight the clinical heterogeneity and diagnostic challenges of ICI-DM. Routine blood glucose and glycated hemoglobin monitoring before and during immunotherapy may aid early detection. Clinicians should maintain a high index of suspicion for ICI-DM, even in patients without typical risk factors. Early recognition and insulin initiation are essential to prevent life-threatening complications of DKA. This report contributes to the limited literature on serplulimab-induced ICI-DM and provides practical insights into its diagnosis and management.

Psoriasis is a prevalent, chronic papulosquamous skin disease, with generalized pustular psoriasis (GPP) representing a severe variant. Dysregulation of the IL-36 signaling pathway plays a crucial role in GPP, making biologics targeting this pathway the current therapeutic focus.

An elderly male patient presented with recurrent generalized erythematous, scaly patches and pustules. His medical history included GPP, psoriatic arthritis, rheumatoid arthritis, and type 2 diabetes mellitus. Previous treatments included methotrexate, glimepiride, metformin and voglibose, and adalimumab.

GPP was diagnosed based on clinical presentation, laboratory findings, and histopathological examination.

Due to inadequate response to previous treatments, spesolimab (900 mg) was administered via intravenous infusion.

Skin lesions subsided rapidly within 1 week after the initial dose. At the 6-month follow-up, the patient remained in complete clinical remission without adverse events.

This case demonstrates that spesolimab is highly effective not only for pustules in GPP but also promotes excellent regression of erythema and plaques.

Children of parents with type 2-diabetes have a fourfold risk of developing the condition. Family-based interventions can mitigate the risk, but identifying which families benefit is challenging. This study describes the prevalence and characteristics of children with parental type 2-diabetes to improve targeting.

This cross-sectional study uses data from Danish national registers. Latent class analysis classified families based on demographic, socioeconomic, and health factors.

We included 1,136,988 children and their parents. 40,442 children had a parent with type 2-diabetes. Children with parental type 2-diabetes were older, had more socioeconomic risk factors, and higher psychiatric healthcare usage. The parents had higher health service usage. We identified four latent classes in ages 0-2, 3-5, 6-11 years, and a fifth class for ages 12-17. "Class 1: Multiple risk factors", "Class 2: Advanced paternal age", "Class 3: High maternal and child healthcare use", "Class 4: Few risk factors", and "Class 5: High paternal healthcare use." Class 1 had the highest prevalence of parental type 2-diabetes, and Class 4 had the lowest prevalence.

This study identifies five classes of families with varying prevalence of parental type 2-diabetes. It adds to our understanding of subgroups and may help target family-oriented interventions.

Serum levels of carbohydrate-deficient transferrin (CDT, the sum of its asialylated and disialylated glycoforms) are a commercial marker of alcohol abuse. Our aim was to investigate the potential influence of metabolic factors on serum CDT levels and the predictive value of transferrin glycoforms for the development of type 2 diabetes in a general adult population.

We measured serum CDT levels by capillary electrophoresis in 1516 individuals (median age 52 years; 55.3% women) randomly selected from the general adult population of a municipality.

Insulin resistance and the associated body mass index and diabetes modified the effect of alcohol consumption on CDT levels; i.e., CDT in heavy drinkers was lower in individuals with obesity than in lean counterparts and was also lower in people with diabetes than in normoglycaemic individuals. The relative abundance of transferrin glycoforms was not significantly associated with the development of type 2 diabetes after a mean follow-up of 7.4 years.

There is an interaction between alcohol consumption and factors associated with insulin resistance in relation to transferrin sialylation. The sensitivity of CDT for detecting heavy alcohol consumption might be limited in people with obesity or diabetes.

Individual predictions of long-term chronic disease progression from data of limited duration provide valuable insights into estimating patient outcomes and therapeutic needs. Statistical Restoration of Fragmented Time course (SReFT) was developed to address this challenge, yet it is computationally too intensive for large-scale datasets. Although diabetes is a representative chronic disease with significant medical needs, it has been challenging to analyze long-term changes using large-scale patient data due to this limitation. In this study, we aimed to develop a new method (SReFT-machine learning, SReFT-ML) by applying machine learning to the concept of SReFT, and to confirm its performance using synthetic data and the data from a clinical trial, the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial (N = 10,251). SReFT-ML has successfully analyzed both synthetic and clinical data, and reconstructed biomarker trajectories over a 30-year period in patients with diabetes. Decreases in diastolic blood pressure and renal function may be important indicators of disease progression. Furthermore, although age and mortality data were not included in the model, survival analysis demonstrated a clear trend of hazard increases in mortality and diabetes-related outcomes with disease progression. This study introduced machine learning to enhance long-term disease progression modeling. The resulting model characterized a 30-year trajectory of disease risk in diabetes. The results provide a clinically meaningful hypothesis that incorporating systemic factors such as renal function and blood pressure, in addition to classic glycemic control, may enhance comprehensive diabetes care. Trial Registration: ClinicalTrials.gov number: NCT00000620.

As first-line therapies for metastatic hormone-sensitive prostate cancer (mHSPC) expand, real-world insights into the baseline characteristics and treatment patterns of mHSPC patients are critical. This study characterises baseline patient profiles and treatment patterns in a multinational real-world cohort from the PIONEER 2.0 Big Data Investigation Group.

This longitudinal observational study utilised health records, insurance claims, and cancer registries from eight European and North American databases. Men diagnosed with mHSPC between January 2016 and December 2020 were included. First-line regimes were classified into four cohorts: (1) androgen deprivation therapy (ADT) monotherapy, (2) ADT + chemotherapy, (3) ADT + androgen receptor pathway inhibitors (ARPIs), and (4) ADT + ARPI + chemotherapy. Baseline characteristics were analysed across treatment groups, and treatment patterns were evaluated over time.

A total of 69 680 mHSPC patients were identified across eight databases, of whom 71% presented with synchronous mHSPC. The median age ranged from 70 to 79 yr, and the most prevalent comorbidities were arterial hypertension peaking at 71% (OPTUM ADT monotherapy), obesity (up to 46%), and diabetes mellitus (up to 32%). Patients aged 70-79 yr were most often treated with ADT monotherapy or ADT + ARPI, whereas those aged 60-69 yr more frequently received ADT + chemotherapy or ADT + ARPI + chemotherapy. From 2016 through 2020, the adoption of ARPI-based combinations rose steadily, use of ADT + chemotherapy declined, and ADT monotherapy remained stable.

In this expansive real-world analysis of nearly 70 000 mHSPC patients, age and comorbidity burden emerged as the primary determinants of frontline therapy, alongside a clear shift towards the increased use of ADT + ARPI regimes from 2016 to 2020. Embedding these real-world insights into clinical guidelines and decision-making can enhance treatment personalisation, accelerate adoption of evidence-backed combinations, and ultimately enhance mHSPC patient outcomes.

In this study of nearly 70 000 men with metastatic hormone-sensitive prostate cancer, doctors' treatment decisions were influenced strongly by patients' age and other health issues, highlighting a growing preference for combination therapies. The findings highlight the importance of real-world evidence, which captures diverse, often under-represented, patients to complement clinical trials and guide more inclusive, evidence-based care.

Extracellular vesicles (EVs), particularly exosomes, have emerged as key players in diabetes pathogenesis, diagnosis, and therapy. They regulate intercellular communication, influence islet function, and contribute to diabetic complications such as retinopathy, nephropathy, and cardiomyopathy. Their potential as liquid biopsy biomarkers and engineered therapeutic carriers-delivering nucleic acids, proteins, or stem cell-derived regenerative signals-offers promising avenues for diabetes management. However, there are some critical challenges in clinical translation. Future research must prioritize (1) scalable GMP-compliant production with rigorous quality control, (2) targeted delivery systems via ligand modification or biomimetic engineering, (3) improved biocompatibility through cargo optimization and stealth coatings, and (4) large-scale clinical trials to validate efficacy and safety. Addressing these hurdles is essential to harness EVs' full potential and accelerate their transition into mainstream diabetic care.

Diabetic foot, one of the most severe chronic complications of diabetes mellitus, arises from complex interactions among neuropathy, vascular ischemia, and inflammatory dysregulation. This review systematically explores the inflammatory regulatory network centered on NF-κB and the interleukin (IL) family in the diabetic foot microenvironment and examines their roles in promoting tissue damage. Under hyperglycemic conditions, the AGE-RAGE axis potently activates the NF-κB signaling pathway, leading to upregulation of pro-inflammatory factors and suppression of anti-inflammatory mediators, thereby forming a vicious cycle of "inflammation-oxidative stress-tissue damage." Charcot foot, a distinct subtype characterized by neurogenic osteoarthropathy, is strongly linked to abnormal IL-6/RANKL pathway activation and impaired anti-inflammatory neuropeptide signaling. We further assess the diagnostic utility of inflammatory biomarkers, including procalcitonin (PCT), high-sensitivity C-reactive protein (hs-CRP), and the neutrophil-to-lymphocyte ratio (NLR), and summarize current therapeutic challenges along with emerging targeted strategies, such as NF-κB inhibition via salicylates. This review underscores the importance of spatiotemporal heterogeneity and dynamic equilibrium within inflammatory networks for clinical stratification and proposes that integrating multi-omics data with artificial intelligence models holds promise for developing personalized interventions. This approach offers novel theoretical insights to overcome therapeutic bottlenecks in diabetic foot management.

Euglycemic diabetic ketoacidosis (euDKA) is a rare but potentially life-threatening complication of diabetes, increasingly linked to SGLT-2 inhibitors (SGLT-2i) and, less frequently, GLP-1 receptor agonists (GLP-1 RA), especially in combination.

We present the case of a 36-year-old man with newly diagnosed type 2 diabetes who developed severe euDKA within days of starting combined therapy with semaglutide and dapagliflozin. Despite prior patient education and adherence to antidiabetic therapy, persistent vomiting and carbohydrate deficiency-likely related to GLP-1 RA side effects-led to decreased insulin administration and metabolic decompensation. This case was characterized by very early onset after initiation of therapy, absence of infection or other common triggers, and resistance to standard treatment with insulin, glucose, and fluid resuscitation. Intensive care with continuous veno-venous hemodiafiltration was required, resulting in full recovery.

This case emphasizes the potential severity of euDKA induced by GLP-1 RA and SGLT-2i combination therapy and highlights the risk of treatment resistance. The decision to initiate SGLT2i and GLP-1RA concurrently should be individualized or possibly spread apart in time, weighing the potential therapeutic benefits against the risk of rare but severe complication such as euDKA. Comprehensive education on ketone monitoring and insulin administration during intercurrent illness are essential to prevent this rare but serious complication.