The microbiota-gut-brain axis is a key conduit linking metabolism, mood, and cognition; however, its position within the continuous functional hierarchy of the cortex and the underlying mechanisms are unclear. In this study, a cross-modal brain-gut dataset from 88 healthy male participants was utilized. By integrating functional magnetic resonance imaging (fMRI) gradient analysis, microbiome sequencing, and dietary behavioral information, this study systematically evaluated the relationships between the abundance of unclassified Ruminococcaceae (Ruminococcaceae_unc), cerebral functional hierarchy, network topology, and emotional symptoms. The results demonstrated that increased abundance of this bacterial group was associated with a functional shift in the brain from unimodal to transmodal hubs, accompanied by a drift of the small-world network toward randomization. Functional gradient values were significantly negatively correlated with depression and anxiety scores and were tightly coupled with latent components in the dietary behavioral dimension, including education, physical activity, and nutrient intake. Transcriptomic analysis further revealed that the GPCR-Rho/integrin-vesicular trafficking pathway may serve as the key molecular mechanism. In conclusion, this study proposes a multiscale coupling framework encompassing the gut microbiota, functional gradients, and emotional health, thereby providing a theoretical basis for the development of microbiota-targeted intervention strategies for modulating transmodal emotions and cognition.

Pain and cancer-related fatigue (CRF) are common and debilitating symptoms among breast cancer survivors, significantly impairing quality of life. Psychological factors, including attachment styles, mindfulness skills, and cognitive emotion regulation strategies (CERS), are essential for symptom management.

This study examined the predictive roles of attachment styles, mindfulness skills, and CERS on pain perception and CRF severity in women with early-stage breast cancer.

A descriptive-correlational design was applied to 201 women recruited from Tehran Shohada Hospital. Participants completed the Adult Attachment Styles (AAS), Kentucky Inventory of Mindfulness Skills (KIMS), Cognitive Emotion Regulation Questionnaire-Short (CERQ-Short), McGill Pain Questionnaire (MPQ), and Fatigue Severity Scale (FSS). Regression analyses revealed that attachment styles accounted for 20% of the variance in pain perception and 24% in CRF, with secure attachment reducing and ambivalent attachment exacerbating symptoms. Mindfulness skills explained 45% of pain perception and 26% of CRF variance, with accepting without judgment being the strongest predictor. CERS contributed to 46% of the variance in pain perception and 21% in CRF, with adaptive strategies mitigating and maladaptive strategies amplifying symptoms.

Promoting secure attachment, cultivating mindfulness skills, particularly accepting without judgment, and training adaptive CERS can significantly alleviate pain and fatigue in breast cancer survivors. These findings underscore the value of psychological interventions in enhancing treatment outcomes and quality of life in this population.

Obesity and type 2 diabetes mellitus are increasingly recognized as important risk factors for cancer development and progression, including cancers of the digestive system. Indeed, epidemiologic evidence demonstrated that both conditions increase the risk of digestive system cancer incidence and mortality, although with sex-specific and ethnic variations for certain associations with specific types of cancers. While these associations were quite consistent, study design and quality differences, lack of uniform adjustment for confounding factors, heterogeneity and various biases require caution when interpreting the results. The intricate processes by which these two closely related metabolic diseases contribute to carcinogenesis involve increased substrate availability and metabolic dysregulation that create a cellular microenvironment permissive to the activation of multiple signaling pathways that contribute to tumor growth and proliferation. This review thoroughly explores the complex interplay of metabolic and inflammatory mechanisms underlying these processes, including hyperglycemia, insulin resistance, altered insulin‑like growth factor-1 signaling, dysregulated adipokines, hormonal imbalance, gut dysbiosis, chronic inflammation and altered immune response, altered mitochondrial function and oxidative stress, circadian rhythm disruption, altered autophagy. Nevertheless, most mechanistic evidence derives from in vitro systems or non-human animal models which may not fully replicate human pathophysiology and disease, and thus extrapolation to human cancer risk should be made cautiously. Given this complex mechanistic interplay, it is evident that obesity and T2DM-associated metabolic alterations play an important role in carcinogenesis, highlighting the need for targeted prevention strategies in high-risk populations, such as weight management and glycemic control, to mitigate cancer burden.

Diabetic sarcopenia (DS), an emerging diabetes complication, poses an increasing challenge to the elderly population. Shenqi paste (SQP) consists of 8 medicine-food homology substances: Astragalus membranaceus (Fisch.) Bge., Codonopsis pilosula (Franch.) Nannf., Polygonatum sibiricum Red., Dioscorea opposita Thunb., Poria cocos (Schw.) Wolf, Eucommia ulmoides Oliv., Hordeum vulgare L., and Ophiopogon japonicus (L.f.) Ker Gawl.. SQP has shown potential benefits for sarcopenia in clinical practice. Its efficacy and safety in DS have not been validated in a randomized controlled trial.

This study aimed to evaluate the efficacy, safety, and limitations, and provide insights into methods and strategies for utilizing SQP in DS management.

In this randomized, double-blind, placebo-controlled trial, community-dwelling older adults (≥ 60 years) with DS and spleen-kidney deficiency syndrome were allocated 1:1 to receive either SQP or placebo paste for 12 weeks. Primary outcomes were skeletal muscle mass index (SMI), handgrip strength, and five-time chair stand test (FCST) duration. Secondary outcomes included health-related scales and biochemical indicators. Assessments were conducted at the baseline (T0), week 6 (T1), and week 12 (T2). Safety evaluation included blood routine, liver and kidney function tests. Intention-to-treat analysis was applied to the primary outcomes data from all participants, with per-protocol analysis for sensitivity. Generalized estimating equations with covariate adjustment and t-tests or Wilcoxon rank-sum tests were used for statistical analysis.

Of 90 randomized participants, the SQP group showed greater improvements in handgrip strength (T2: interact p < 0.001), SMI (T2: interact p < 0.001), and FCST (T2: interact p < 0.001) versus control. Secondary outcome measures of 74 participants, including frailty, nutrition, physical activity, sleep quality, depression, and TCM syndrome scores, significantly improved (p < 0.05), with significant fasting blood glucose reduction (T2: interact p = 0.018) and C-reactive protein decrease (T2: interact p < 0.001). There was no statistically significant difference in the change in the difference between the two groups in fasting insulin, glycated hemoglobin and insulin resistance index before and after intervention (p > 0.05). Within-group analysis demonstrated significant reductions of SQP group in inflammatory cytokines, and sarcopenia-related biomarkers (p < 0.001) post-intervention. No serious adverse events occurred.

A 12-week SQP intervention enhanced muscle mass, strength, function, and metabolic and inflammatory profiles in older adults with DS, with good tolerability, supporting its potential as a safe, complementary therapy.

To develop a machine learning-based modeling approach for extracting elastic stiffness estimates from Ocular Response Analyzer (ORA) waveforms.

Prospective observational cohort study with model training and testing using development dataset and validation with independent dataset.

Participants were prospectively enrolled into six cohorts for the Development dataset, including control subjects (n=199), individuals diagnosed with keratoconus (n=54), diabetes mellitus with retinopathy (n=78) and without retinopathy (n=75), primary open-angle glaucoma (n=53), and ocular hypertension (n=44). Independent validation dataset comprised of two cohorts including healthy participants (n=145) and individuals diagnosed with keratoconus (n=44).

Intraocular pressure and biomechanical data were collected using the ORA and Corvis ST devices for the Development dataset. An Adaptive Temporal Mixture of Experts (AT-MoE) model, incorporating Long Short-Term Memory (LSTM) networks with dynamic expert selection, was trained using ORA waveform parameters and raw signals to predict stiffness parameters (SP) from Corvis ST, including SP-A1 representing corneal stiffness, SP-HC representing scleral stiffness, and SSI representing deformation stiffness. Predicted ORA stiffness estimates were independently validated with a separate dataset of keratoconus and healthy eyes. The ORA waveform parameters, as well as applanation and pressure signals, were used as input to the machine learning models to classify keratoconus versus healthy eyes, which was evaluated with Area Under Receiver Operator Characteristic (AUROC) Curves.

The primary outcome measures were the predicted ORA stiffness estimates: Corneal Stiffness estimate (CSe), Scleral Stiffness estimate (SSe), and Deformation Stiffness estimate (DSe).

The AT-MoE model significantly outperformed the baseline LSTM in predicting ocular stiffness estimates using ORA input data with reduction of prediction error. The AT-MoE model also resulted in improvement of keratoconus detection performance in the independent validation dataset with AUROC = 0.9512, which is similar to performance of tomographic detection approaches.

The AT-MoE model provides a novel and accurate framework for deriving elastic stiffness estimates from ORA waveforms and offers improved diagnostic capability for keratoconus compared to traditional machine learning models. This method has the potential to expand the utility of the ORA device for biomechanical assessment in clinical settings.

The latest data release from the Global Burden of Disease, Injuries, and Risk Factors Study (GBD) 2023 has enabled us to conduct an updated analysis of the trends and burdens of common metabolic diseases/risk factors from 1990 to 2023 in the Asia-Pacific region. We aimed to highlight disparities across geographic regions, over time, and by sex, while incorporating a predictive assessment of future trends through 2030.

We analyzed estimates of disability-adjusted life years (DALYs) and mortality for five common metabolic diseases and risk factors in the Asia-Pacific region (type 2 diabetes mellitus [T2DM], high systolic blood pressure [SBP], high body mass index [BMI], high LDL cholesterol, and metabolic dysfunction-associated steatotic liver disease [MASLD]). We also used Bayesian age-period-cohort (BAPC) models to project disease burdens through 2030.

In 2023, in Asia-Pacific region, high SBP accounted for the largest burden (~138 million DALYs; 6.27 million deaths), followed by high BMI (~55 million DALYs; 1.33 million deaths), high LDL cholesterol (~53 million DALYs; 2.02 million deaths), T2DM (~49 million DALYs; 1.13 million deaths), and MASLD (~1.26 million DALYs; 47 thousand deaths). From 1990 to 2023, total DALYs increased 1.7- to 3.7- fold, with absolute burdens highest in China, India, and Indonesia, and relative burdens concentrated in Pacific Islands. Projected trends through 2023 suggest that the burden of all metabolic diseases/risk factors, except MASLD, is likely to continue rising, with high SBP remaining the dominant contributor.

Analysis of the GBD 2023 and 2030 projections show that metabolic diseases/risk factors will remain a persistent challenge for the Asia-Pacific region, with substantial increases in DALYs and mortality. These findings call for coordinated, intensified global actions to address interconnected metabolic conditions and can have positive implications for the United Nations' 2030 health-related goals.

The evidence remains contradictory regarding the optimal glycaemic targets needed to address the long-term effects of hyperglycaemia in people with diabetes mellitus (T2DM). We examined the association between HbA1c levels and the risk of individual microvascular complications among people with T2DM.

We used the Clinical Practice Research Datalink (CPRD) GOLD database for a prospective cohort study, following patients ≥18 years old from diagnosis of T2DM between January 2007 and December 2017. Neuropathy included foot ulcers, peripheral arterial disease, gangrene, and amputation. Nephropathy was classified by chronic kidney disease stages, and retinopathy included blindness and macular oedema. The risk of each complication in five HbA1c intervals [1.0%] intervals compared to 48.0-57.9 mmol/mol (6.5-7.5%) was assessed using a multivariate time-varying Cox regression adjusted by various patients' characteristics. Subgroup analyses were performed according to age, hypertension, and the use of antihypertensive medications.

Our study included 172,869 patients (mean age 62.6 years and, 54.6% women). The risks were the highest in HbA1c levels >81.0 mmol/mol (>9.6%) (HR 1.27, 95%CI 1.17-1.39 for nephropathy; 1.55, 1.27-1.47 for neuropathy; 1.66, 1.41-1.96 for retinopathy). The lowest risks observed in levels 48.0-57.9 mmol/mol (6.5-7.5%) for nephropathy and in levels <48.0 mmol/mol (<6.5%) for neuropathy (0.98, 0.88-1.09) and for retinopathy (0.89, 0.79-0.99). In the subgroup analysis, higher HbA1c levels were associated with an increased risk of nephropathy, particularly in individuals over 60, those with hypertension, and those using antihypertensive medications. For neuropathy, being over 60 was associated with an increased risk across all HbA1c levels. In retinopathy, hypertension and the use of antihypertensive medications were associated with lower risk across all HbA1c levels, while individuals under 60 were associated with higher risks at elevated HbA1c levels compared to those over 60.

The risk of retinopathy and neuropathy was lowest in individuals with HbA1c levels within the non-diabetic range <48.0 mmol/mol (<6.5%) and increased progressively with higher HbA1c levels. In contrast, the lowest risk of nephropathy was observed in individuals with HbA1c levels between 48.0 and 57.9 mmol/mol (6.5-7.5%). These findings underscore the importance of a personalized approach to diabetes management that considers multiple risk factors and incorporates novel therapeutic strategies beyond glucose control.

Saccharomyces cerevisiae cell wall extract (SCCWE) contains a variety of bioactive compounds, yet its antidiabetic action mechanisms remain unclear. The current work aimed to characterize the chemical components using GC-MS of SCCWE along with its antidiabetic, hepatoprotective, antioxidant, and microbiome-modulating properties in streptozotocin (STZ)-induced diabetic rats. The rats were treated with glibenclamide, SCCWE (25, 50, or 100 mg/kg), or non-diabetic normal rats as a control. Key regulators (P-AMPK, HMGR, SREBP-1c, and LXRα) as well as metabolic parameters, oxidative and inflammatory indicators, and histopathology and FTIR analysis were evaluated. Trehalose (16.03%), turanose (15.05%), glycerol (12.24%), and mannobiose (7.38%) were found to be the primary constituents by GC-MS profiling. STZ elevated fasting glucose 1.5-fold and reduced lactic acid bacteria 6.6-fold. SCCWE lowered glucose by 27.4-30.4% and restored lactic acid bacteria by 266.7-711.6%. Serum ALT, increased 2.1-fold in diabetic rats, decreased by 35.3-55.6% with SCCWE. Dyslipidemia improved markedly, with total lipids, cholesterol, and triglycerides reduced by up to 45.6%, 63.9%, and 46%. SCCWE decreased hepatic MDA by 56.5% and increased GSH up to 607.2%. It elevated P-AMPK while suppressing HMGR (18.9-154.6%), SREBP-1c (29.7-92.6%), and LXRα mRNA (21.3-87.6%). Histopathology and FTIR confirmed tissue and membrane restoration. SCCWE demonstrates potent antidiabetic and hepatoprotective activities, supporting its potential as a natural therapeutic for diabetes.

While the effect of hyperglycemia on cutaneous wound healing is well recognized, the impact of high-glucose (HG) environment on UVB-induced skin tumor formation remains inconclusive. Similar to impaired wound healing, skin tumor formation involves keratinocyte proliferation and migration. Intriguingly, SOX2 has been recognized to play an important role in both wound healing and UVB-induced skin tumor formation by modulating cell proliferation and migration. As hyperglycemia results in impaired cutaneous wound healing, we hypothesized that the HG environment also impacts UVB-induced tumor formation of the skin. The present study aimed to explore the effects of HG environment on epidermal keratinocytes, focusing on the impact of UVB-induced cell proliferation and migration via SOX2 expression. In cultured keratinocytes, HG-cultivated keratinocytes showed reduced SOX2 levels compared to control with or without UVB treatment. SOX2 regulates keratinocyte migration and proliferation via modulation of AKT phosphorylation. Additionally, O-linked-N-acetylglucosamine glycosylation contributed to reduced SOX2 levels in HG-cultivated keratinocytes. Animal studies demonstrated that diabetic mice skin has significantly less UVB-induced tumor formation, epidermal thickening, SOX2, and pAKT expression than the control mice; mutant p53 expression was also lower in diabetic mice but did not reach statistical significance compared to control. In conclusion, HG environment reduces UVB-induced keratinocyte proliferation and migration, in association with decreased SOX2 expression and downstream AKT signaling. The current findings provide novel insights regarding UVB-induced skin tumor formation of skin in patients with diabetes.

Type 2 diabetes mellitus (T2DM) poses a major health and socioeconomic challenge, and long-term use of conventional hypoglycemic agents often causes adverse effects such as impaired gastrointestinal function. Natural polysaccharides have emerged as promising alternatives due to their safety and bioactivity. In this study, polysaccharides from raw Polygonatum cyrtonema Hua (RPCP) and processed Polygonatum cyrtonema Hua (PPCP) were successfully extracted using enzyme-assisted hot water extraction. The purified fractions of RPCP (RPCP-P) and PPCP (PPCP-P) were structurally characterized by molecular weight determination, monosaccharide composition, FT-IR, methylation, and NMR analyses. Their hypoglycemic effects and underlying mechanisms were evaluated in high-fat diet and streptozotocin-induced T2DM mice. Both RPCP and PPCP significantly reduced fasting blood glucose, improved insulin sensitivity, and ameliorated lipid metabolism disorders. Mechanistically, the polysaccharides modulated gut microbiota composition, promoted short-chain fatty acid (SCFA) production, upregulated colonic GPR41/43 expression, and increased glucagon-like peptide-1 (GLP-1) and peptide YY (PYY) secretion, thereby improving glucose homeostasis. Notably, PPCP exhibited superior antidiabetic effects to those of RPCP, which we attribute to its greater molecular heterogeneity and galactan-rich structure, suggesting that traditional steaming enhances polysaccharide bioactivity. These findings demonstrate that traditional processing enhances the functionality of Polygonatum cyrtonema polysaccharides through structure-dependent modulation of the gut microbiota-SCFA-host metabolic axis, providing a scientific basis for their development as functional food ingredients for glycemic regulation.