Incretin hormones, specifically glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), serve as crucial mediators of postprandial glucose homeostasis by primarily enhancing glucose-stimulated insulin secretion. Research indicates that the incretin effect accounts for approximately 50% of insulin secretion in individuals without diabetes, which is significantly reduced to 30% or less in those with Type 2 Diabetes Mellitus (T2DM). The mechanisms underlying this incretin resistance have emerged as critical causes of postprandial hyperglycemia. Incretin-based therapies, including GLP-1 receptor agonists (GLP-1RAs) and DPP-4 inhibitors, have demonstrated efficacy in managing T2DM; however, intrinsic resistance mechanisms may limit their effectiveness. Understanding the processes by which T2DM affects incretin action, from hormone secretion to the modulation of signal transduction, is essential for optimizing current therapies and developing new interventions to enhance β-cell responsiveness and improve glycemic control. The concept of incretin resistance has a well-established history in literature, dating back to at least the early 1990 s. It is used to describe a reduced insulinotropic responsiveness to incretin hormones in individuals diagnosed with T2DM. This review examines how hyperglycemia, chronic inflammation, and genetic susceptibility collectively inhibit incretin signaling through distinct yet interconnected molecular pathways. This impairment exacerbates postprandial hyperglycemia and accelerates β-cell dysfunction. We propose novel hypotheses regarding selective β-arrestin signaling, enhancers, epigenetic regulation, interactions between gut microbiota and incretins, inflammation-induced endoplasmic reticulum (ER) stress, and genotype-specific therapeutic responses. The hypotheses presented in this review serve as a framework for future research and therapeutic development to combat the phenomenon of incretin resistance and improve the clinical management of T2DM.

Type 1 Diabetes Mellitus (T1DM) is a chronic autoimmune condition that alters salivary composition due to metabolic disturbances. Saliva provides a non-invasive means of detecting systemic changes. This pilot study compared salivary pH, sialic acid concentration, antioxidant capacity, and oral health indicators between children with and without T1DM.

A comparative cross-sectional study was conducted among 40 children aged 6-15 years (20 with T1DM, 20 healthy controls). Sociodemographic and clinical data were collected, and unstimulated saliva was analysed for pH, sialic acid, and antioxidant capacity. Oral examinations included salivary flow rate, plaque index, and gingival index. Statistical analyses were performed using the Shapiro-Wilk test. As several variables demonstrated non-normal distributions and subgroup sample sizes were small, non-parametric statistical methods were applied for between-group comparisons.

Children with T1DM demonstrated significantly lower salivary pH (6.70 ± 0.93 vs. 7.65 ± 0.27) and flow rate (3.93 ± 0.99 ml vs. 6.03 ± 1.18 ml), and higher sialic acid levels (78.13 ± 49.67 µg/ml vs. 36.84 ± 17.33 µg/ml) than controls. Plaque and gingival indices were also elevated in T1DM (p < 0.01). Antioxidant capacity was slightly higher but not statistically significant. Age-based analysis showed younger diabetic children (8-10 years) had elevated sialic acid and lower antioxidants, whereas older children (11-15 years) exhibited reduced flow rates and higher plaque/gingival indices, suggesting progressive oral changes with age.

T1DM significantly affects salivary composition and oral health in children, with age-specific variations. Salivary biomarkers, particularly sialic acid and pH, show potential as non-invasive tools for monitoring metabolic and periodontal changes in pediatric diabetes. Larger longitudinal studies are needed to validate these findings.

Although lipoprotein(a) [Lp(a)] is recognized as an independent risk factor for cardiovascular disease (CVD), its distribution and risk thresholds in the Japanese population remain unclear. This study aimed to characterize the distribution of Lp(a) in Japanese clinical settings and evaluate its association with CVD risk, including coronary artery disease (CAD), atherosclerotic cardiovascular disease (ASCVD), and familial hypercholesterolemia (FH).

The LEAP study is a multicenter retrospective cohort analysis of 6,173 patients from six Japanese institutions. The Lp(a) values were harmonized to nmol/L using kit-specific conversion equations, enabling a consistent analysis across different immunoassays. Associations with CAD, ASCVD, chronic kidney disease (CKD), diabetes mellitus (DM), and FH were assessed. The risk thresholds were defined using a receiver operating characteristic analysis.

The median Lp(a) concentration was 20.88 nmol/L, with a right-skewed distribution. Elevated Lp(a) levels were significantly associated with CAD, ASCVD, CKD, and FH. In contrast, DM was related to lower Lp(a). An ROC analysis identified 25 nmol/L as a screening threshold and 125 nmol/L as a high-risk boundary. The CAD prevalence increased stepwise across these categories: 20.2% (≤ 25 nmol/L), 30.3% (25-125 nmol/L), and 39.9% (＞125 nmol/L).

This study provides the first nmol/L-standardized Lp(a) distribution in Japanese patients and proposes provisional thresholds for clinical risk stratification.

The intertwined global epidemics of chronic obstructive pulmonary disease (COPD) and type 2 diabetes mellitus (T2DM) pose an increasing challenge in chronic disease management, constituting a clinically significant bidirectional threat. This review integrates current evidence to propose a pathological interactive axis underlying this comorbidity, driven by shared risk factors such as smoking, obesity, and physical inactivity, and mediated through interconnected inflammatory signaling (e.g. IL-6/NF-κB and NLRP3/IL-1β), metabolic dysregulation, and oxidative stress. Within this framework, pulmonary inflammation in COPD may exacerbate systemic metabolic abnormalities, whereas chronic hyperglycemia and insulin resistance in T2DM may, in turn, aggravate lung injury, sustaining a self-perpetuating cycle of multi-organ dysfunction. Against this background, sodium-glucose cotransporter 2 inhibitors (SGLT2i) have emerged as a pharmacological class of interest due to their pleiotropic metabolic and anti-inflammatory properties. Experimental and indirect clinical evidence suggests that SGLT2i may modulate key inflammatory and oxidative stress pathways, including macrophage polarization, AMPK/NF-κB/NLRP3 signaling, mitochondrial protection, and Nrf2-SIRT1 activation. In addition, SGLT2i-associated improvements in body weight, metabolic efficiency, and cardiopulmonary loading may indirectly influence pulmonary-metabolic interactions. However, evidence for direct benefits on COPD-specific clinical outcomes remains limited and largely hypothesis-generating. Despite these mechanistic insights, substantial gaps remain regarding cross-organ molecular interactions, the role of hypoxia, and translational limitations of current models. Future research should prioritize dedicated randomized controlled trials, advanced single-cell and spatial omics approaches, and integrated digital health strategies to refine individualized SGLT2i-based interventions and advance multi-organ protective therapies in this complex patient population.

BACKGROUND IgA-associated vasculitis (IgAV), although relatively uncommon in adults, is frequently associated with increased vasculitis severity. Sudden abdominal pain and bloody diarrhea are among the usual manifestations of IgAV in children. In older patients, clinical manifestations of the disease may be typical, but advanced age and comorbidities can make the final diagnosis unexpected. CASE REPORT A 67-year-old man with multiple underlying medical conditions, including diabetes mellitus and arterial hypertension, was admitted with acute abdominal pain. Baseline evaluation revealed venous ischemic necrosis of the ileum and concurrent acute kidney injury. Given the patient's age and diabetic status, an atherogenic etiology was initially considered. Further diagnostic investigation, including renal biopsy, identified features consistent with IgAV. The patient's clinical course was complicated by simultaneous gastrointestinal and renal involvement, highlighting the systemic nature of the vasculitis. CONCLUSIONS Although IgAV is predominantly a pediatric condition, its presentation in older adults is rare and often atypical, commonly mimicking other vascular or ischemic disorders; this pattern may delay diagnosis and appropriate treatment. The present case emphasizes the need to maintain awareness of IgAV in older patients who present with acute abdominal symptoms, particularly when renal dysfunction is present. Advanced age and diabetic status are associated with increased severity and worse renal outcomes, underscoring the need for thorough evaluation and close monitoring. This report contributes to the limited literature on IgAV in older patients; it illustrates the diagnostic and therapeutic challenges in this population.

Cancer represents one of the leading global public health challenges, with its burden shaped not only by biological factors but also by social and economic inequalities. In Brazil, even municipalities with a very high Human Development Index (HDI) exhibit persistent disparities. This study assessed temporal changes in cancer incidence, mortality, and social inequalities in Campinas, São Paulo State, Brazil.

A repeated cross-sectional study was conducted using incidence and mortality rates of the most frequent neoplasms among men and women residing in Campinas, SP, Brazil from 2010 to 2014 and 2015-2019 from the Population-Based Cancer Registry and the Mortality Information System. Age-standardized incidence and mortality rates were estimated for the most common cancers, stratified by levels of social vulnerability based on the São Paulo Social Vulnerability Index. Inequalities were analyzed using the Relative Index of Inequality (RII).

Among men, prostate cancer (RR= 0.94; 95% CI: 0.89-0.99) and stomach cancer (RR= 0.82; 95% CI: 0.72-0.93) incidence declined, while mortality remained stable for most cancers, except for an increase in colorectal cancer mortality (RR 1.15; 95% CI: 1.00-1.32 - p = 0.032 and a reduction in stomach cancer mortality (RR= 0.83; 95% CI: 0.66-1.04). Socially vulnerable men showed persistently higher mortality from prostate, stomach, and oral cavity cancers. Among women, breast cancer incidence increased (RR= 1.14; 95% CI: 1.08-1.20), and overall mortality rose (RR= 1.06; 95% CI: 1.01-1.12), particularly from lung cancer (RR= 1.25; 95% CI: 1.07-1.47). Vulnerable women exhibited consistently higher cervix uteri cancer incidence (2010-2014: RII= 2.90; 95% CI: 1.90-4.43 vs. 2015-2019: RII= 2.36; 95% CI: 1.58-3.53) and mortality (2010-2014: RII= 2.74; 95% CI: 1.42-5.26 vs. 2015-2019: RII= 3.60; 95% CI: 1.89-6.85), while breast cancer incidence remained higher among less vulnerable women (2010-2014: RII= 0.42; 95% CI: 0.37-0.49 vs. 2015-2019: RII= 0.49; 95% CI: 0.43-0.56). Inequalities in colorectal cancer incidence narrowed over time for both sexes; however, mortality inequality among men reversed, becoming higher among the most vulnerable in 2015-2019 (RII= 0.92; 95% CI: 0.66-1.29).

Despite high socioeconomic development, substantial social inequalities in cancer incidence and mortality persist in Campinas, with some disparities widening over time. These findings highlight the need for targeted and equity-oriented cancer control strategies to improve access to early diagnosis, treatment, and care among socially vulnerable populations.

This review examines the modern role of open partial nephrectomy (OPN), indications for this surgical approach, and outcomes associated with the open technique in the era of robotic surgery.

Robotic-assisted partial nephrectomy (RAPN) now predominates for small renal masses and is increasingly applied to larger and more complex masses. Across multiple comparative series and meta-analyses, RAPN offers equivalent oncologic control and functional preservation compared to OPN, while demonstrating reduced perioperative morbidity. Nonetheless, OPN remains valuable for tumors in hostile or re-operative fields, certain hereditary syndromes, solitary kidneys when cold ischemia is preferred, and settings without reliable robotic access. Declining open case exposure during training raises concerns about maintaining surgical competency. OPN remains an important option when use of the approach provides improved surgical exposure, ischemia management, intra-operative safety, or feasibility of nephron sparing. A pragmatic, surgeon-experience-based approach that prioritizes oncologic control, parenchymal preservation, and patient safety best serves individualized care.

Pancreatic cancer is characterized by its high malignancy, aggressive nature, and exceedingly poor prognosis. While surgical resection combined with systemic therapy offers the only potential for cure, the high recurrence rate significantly compromises long-term survival, even after radical surgery. The presence of peritoneal free tumor cells, detected via peritoneal cytology, represents a form of metastatic spread distinct from traditional distant metastases and exerts a similarly negative impact on patient outcomes. Peritoneal washing cytology is a practical and valuable diagnostic tool for identifying intraperitoneal free tumor cells, providing critical insights into disease progression and prognosis. Its status retains significant prognostic relevance even after initial clinical stratification based on resectability. Furthermore, peritoneal cytology plays a pivotal role in guiding clinical decision-making. Notably, the conversion from positive to negative cytology following preoperative therapy may select patients who could benefit from conversion surgery, potentially counteracting the adverse prognostic effects associated with peritoneal dissemination. This review comprehensively examines the etiology and risk factors associated with positive peritoneal cytology, integrates its prognostic value into current stratification systems, discusses its profound implications for clinical decision-making, explores emerging detection technologies, and shares future perspectives. By synthesizing existing evidence, this review aims to contribute to optimized individualized treatment approaches and improved clinical outcomes for patients with pancreatic cancer.

This literature review examines the transformative role of machine learning (ML) and deep learning (DL) in enhancing optical spectroscopy for breast cancer diagnosis. By synthesizing advancements from peer-reviewed studies (2015-2025), we evaluate how ML/DL integration improves the detection of malignancy-associated biochemical changes, enabling noninvasive, rapid, and accurate differentiation between healthy and cancerous tissues. This review highlights key spectroscopic modalities, such as Raman, fluorescence, diffusive optical spectroscopy (DOS), and photoacoustic spectroscopy (PAS), and their integration with AI-driven models, such as convolutional neural networks (CNNs), support vector machines (SVMs), and logistic regression. These techniques achieve diagnostic accuracies of up to 94% in subtype classification (e.g., luminal A, HER2-positive) by analyzing spectral biomarkers such as hemoglobin, lipids, and collagen. Challenges such as data variability, model interpretability, and clinical integration barriers are critically assessed. These findings underscore the potential of ML/DL-enhanced spectroscopy to standardize diagnostics, reduce unnecessary biopsies, and personalize treatment monitoring. Future directions emphasize the need for explainable AI (XAI), multimodal data fusion, and large-scale, diverse datasets to bridge translational gaps. By addressing technical, ethical, and regulatory hurdles, this integration promises to advance early detection, improve clinical outcomes, and reshape precision oncology.

Several anticancer drugs can cause chemotherapy-induced peripheral neurotoxicity (CIPN) in approximately 70% of patients; of these, 30% continue to have chronic symptoms hampering quality of life. As more people live with and beyond cancer therapy, it is becoming increasingly important for clinicians to assess those at higher risk of CIPN and provide care for managing CIPN severity. Biomarkers could be appropriate in this regard. However, an initial step towards biomarker-informed care is to advance scientific knowledge regarding the potential of current biomarkers such as neurofilament light chain (NfL). Here, outcomes of a CIPN biomarker workshop and discussions among clinical and scientific experts held during the MASCC 2024 annual conference are reported. The aims of this work are to (1) identify knowledge gaps regarding the potential for serum NfL (sNfL) as a predictive CIPN biomarker, (2) provide guidance for future biomarker research, and (3) explore whether sNfL is ready for use in clinical practice.

Consensus of the experts was gained using a Normative Group Technique. A two-stage iterative approach was used: Stage 1 involved a literature review and an in-person workshop; Stage 2 involved a virtual zoom event to confirm understanding and priorities following the workshop.

Eleven studies identified that increases in serum NfL after receiving 2-3 chemotherapy doses are associated with CIPN severity post treatment. Despite preliminary evidence suggesting positive correlations among sNfL and CIPN objective and subjective measures, wide variation in sNfL levels, the prescribed neurotoxic chemotherapy agent, dose and schedule, and symptom assessment time points make it difficult to use sNfL as a predictor of CIPN severity.

While there is potential for sNfL to be a useful biomarker, larger scale research exploring the predictive value is needed before sNfL can be used to inform clinical decision-making. Identifying links with validated clinical assessments could be utilized to enhance biomarker accuracy and to address the multiple pathological mechanisms of neurotoxicity that occur from the differing chemotherapies. Moreover, workshop participants identified significant barriers to biomarker implementation (e.g. costs, long processing time, and unknown cut off points).