Intestinal epithelial dopamine receptor signaling drives sex-specific disease exacerbation in a mouse model of multiple sclerosis.

Although the gut microbiota can influence central nervous system (CNS) autoimmune diseases, the contribution of the intestinal epithelium to CNS autoimmunity is less clear. Here, we showed that intestinal epithelial dopamine D2 receptors (IEC DRD2) promoted sex-specific disease progression in an animal model of multiple sclerosis. Female mice lacking Drd2 selectively in intestinal epithelial cells showed a blunted inflammatory response in the CNS and reduced disease progression. In contrast, overexpression or activation of IEC DRD2 by phenylethylamine administration exacerbated disease severity. This was accompanied by altered lysozyme expression and gut microbiota composition, including reduced abundance of Lactobacillus species. Furthermore, treatment with N2-acetyl-L-lysine, a metabolite derived from Lactobacillus, suppressed microglial activation and neurodegeneration. Taken together, our study indicates that IEC DRD2 hyperactivity impacts gut microbial abundances and increases susceptibility to CNS autoimmune diseases in a female-biased manner, opening up future avenues for sex-specific interventions of CNS autoimmune diseases.

NRF1-mediated mitochondrial biogenesis antagonizes innate antiviral immunity.

Mitochondrial biogenesis is the process of generating new mitochondria to maintain cellular homeostasis. Here, we report that viruses exploit mitochondrial biogenesis to antagonize innate antiviral immunity. We found that nuclear respiratory factor-1 (NRF1), a vital transcriptional factor involved in nuclear-mitochondrial interactions, is essential for RNA (VSV) or DNA (HSV-1) virus-induced mitochondrial biogenesis. NRF1 deficiency resulted in enhanced innate immunity, a diminished viral load, and morbidity in mice. Mechanistically, the inhibition of NRF1-mediated mitochondrial biogenesis aggravated virus-induced mitochondrial damage, promoted the release of mitochondrial DNA (mtDNA), increased the production of mitochondrial reactive oxygen species (mtROS), and activated the innate immune response. Notably, virus-activated kinase TBK1 phosphorylated NRF1 at Ser318 and thereby triggered the inactivation of the NRF1-TFAM axis during HSV-1 infection. A knock-in (KI) strategy that mimicked TBK1-NRF1 signaling revealed that interrupting the TBK1-NRF1 connection ablated mtDNA release and thereby attenuated the HSV-1-induced innate antiviral response. Our study reveals a previously unidentified antiviral mechanism that utilizes a NRF1-mediated negative feedback loop to modulate mitochondrial biogenesis and antagonize innate immune response.

Gut Microbiota and Blood Metabolites Related to Fiber Intake and Type 2 Diabetes.

BACKGROUND: Consistent evidence suggests diabetes-protective effects of dietary fiber intake. However, the underlying mechanisms, particularly the role of gut microbiota and host circulating metabolites, are not fully understood. We aimed to investigate gut microbiota and circulating metabolites associated with dietary fiber intake and their relationships with type 2 diabetes (T2D). METHODS: This study included up to 11 394 participants from the HCHS/SOL (Hispanic Community Health Study/Study of Latinos). Diet was assessed with two 24-hour dietary recalls at baseline. We examined associations of dietary fiber intake with gut microbiome measured by shotgun metagenomics (350 species/85 genera and 1958 enzymes; n=2992 at visit 2), serum metabolome measured by untargeted metabolomics (624 metabolites; n=6198 at baseline), and associations between fiber-related gut bacteria and metabolites (n=804 at visit 2). We examined prospective associations of serum microbial-associated metabolites (n=3579 at baseline) with incident T2D over 6 years. RESULTS: We identified multiple bacterial genera, species, and related enzymes associated with fiber intake. Several bacteria (eg, Butyrivibrio, Faecalibacterium) and enzymes involved in fiber degradation (eg, xylanase EC3.2.1.156) were positively associated with fiber intake, inversely associated with prevalent T2D, and favorably associated with T2D-related metabolic traits. We identified 159 metabolites associated with fiber intake, 47 of which were associated with incident T2D. We identified 18 of these 47 metabolites associated with the identified fiber-related bacteria, including several microbial metabolites (eg, indolepropionate and 3-phenylpropionate) inversely associated with the risk of T2D. Both Butyrivibrio and Faecalibacterium were associated with these favorable metabolites. The associations of fiber-related bacteria, especially Faecalibacterium and Butyrivibrio, with T2D were attenuated after further adjustment for these microbial metabolites. CONCLUSIONS: Among United States Hispanics/Latinos, dietary fiber intake was associated with favorable profiles of gut microbiota and circulating metabolites for T2D. These findings advance our understanding of the role of gut microbiota and microbial metabolites in the relationship between diet and T2D.

DescribePROT in 2023: more, higher-quality and experimental annotations and improved data download options.

The DescribePROT database of amino acid-level descriptors of protein structures and functions was substantially expanded since its release in 2020. This expansion includes substantial increase in the size, scope, and quality of the underlying data, the addition of experimental structural information, the inclusion of new data download options, and an upgraded graphical interface. DescribePROT currently covers 19 structural and functional descriptors for proteins in 273 reference proteomes generated by 11 accurate and complementary predictive tools. Users can search our resource in multiple ways, interact with the data using the graphical interface, and download data at various scales including individual proteins, entire proteomes, and whole database. The annotations in DescribePROT are useful for a broad spectrum of studies that include investigations of protein structure and function, development and validation of predictive tools, and to support efforts in understanding molecular underpinnings of diseases and development of therapeutics. DescribePROT can be freely accessed at http://biomine.cs.vcu.edu/servers/DESCRIBEPROT/.

Cspg4high microglia contribute to microgliosis during neurodegeneration.

Microglia play a critical role in the pathogenic process of neurodegenerative diseases, such as Parkinson's disease (PD) and Alzheimer's disease (AD). Upon pathological stimulation, microglia are converted from a surveillant to an overactivated phenotype. However, the molecular characters of proliferating microglia and their contributions to the pathogenesis of neurodegeneration remain unclear. Here, we identify chondroitin sulfate proteoglycan 4 (Cspg4, also known as neural/glial antigen 2)-expressing microglia as a specific subset of microglia with proliferative capability during neurodegeneration. We found that the percentage of Cspg4+ microglia was increased in mouse models of PD. The transcriptomic analysis of Cspg4+ microglia revealed that the subcluster Cspg4high microglia displayed a unique transcriptomic signature, which was characterized by the enrichment of orthologous cell cycle genes and a lower expression of genes responsible for neuroinflammation and phagocytosis. Their gene signatures were also distinct from that of known disease-associated microglia. The proliferation of quiescent Cspg4high microglia was evoked by pathological α-synuclein. Following the transplantation in the adult brain with the depletion of endogenous microglia, Cspg4high microglia grafts showed higher survival rates than their Cspg4- counterparts. Consistently, Cspg4high microglia were detected in the brain of AD patients and displayed the expansion in animal models of AD. These findings suggest that Cspg4high microglia are one of the origins of microgliosis during neurodegeneration and may open up a avenue for the treatment of neurodegenerative diseases.

DIST: spatial transcriptomics enhancement using deep learning.

Spatially resolved transcriptomics technologies enable comprehensive measurement of gene expression patterns in the context of intact tissues. However, existing technologies suffer from either low resolution or shallow sequencing depth. Here, we present DIST, a deep learning-based method that imputes the gene expression profiles on unmeasured locations and enhances the gene expression for both original measured spots and imputed spots by self-supervised learning and transfer learning. We evaluate the performance of DIST for imputation, clustering, differential expression analysis and functional enrichment analysis. The results show that DIST can impute the gene expression accurately, enhance the gene expression for low-quality data, help detect more biological meaningful differentially expressed genes and pathways, therefore allow for deeper insights into the biological processes.

Composite healthy lifestyle, socioeconomic deprivation, and mental well-being during the COVID-19 pandemic: a prospective analysis.

The adverse psychological and social impacts of COVID-19 pandemic are well characterized, but the role of composite, modifiable lifestyle factors that may interact to mitigate these impacts is not. The effect of socioeconomic deprivation on these lifestyle risks also remains unclear. Based on a nationally representative, longitudinal cohort, we assessed the association between a combination of pre-pandemic lifestyle factors and mental health conditions during pandemic, and the contribution of deprivation to it. Composite lifestyle factors included BMI, smoking status, alcohol consumption, physical activity, sedentary time, sleep duration, and fruit and vegetable intake, with lifestyle scores and lifestyle categories calculated for each participant. Symptoms of depression and anxiety, and personal well-being were assessed by validated scales during the pandemic. Socioeconomic deprivation was characterized by both individual-level (income, wealth, and education) and group-level factors (Index of Multiple Deprivation). Of the 5049 eligible participants (mean [SD] age, 68.1 [10.9] years; 57.2% were female) included in the study, 41.6% followed a favorable lifestyle, 48.9% followed an intermediate lifestyle, and 9.5% followed an unfavorable lifestyle. Compared with favorable lifestyle category, participants in the intermediate and unfavorable lifestyle category were at increased risk of mental health conditions, with the hazard ratio (HR) for trend per increment change towards unfavorable category of 1.17 (95% CI 1.09-1.26) for depression, 1.23 (1.07-1.42) for anxiety, and 1.39 (1.20-1.61) for low well-being. A significant trend of lower risk for mental health conditions with increasing number of healthy lifestyle factors was observed (P < 0.001 for trend). There were no significant interactions between lifestyle factors and socioeconomic deprivation for any of the outcomes, with similar HRs for trend per one increment change in lifestyle category observed in each deprivation group. Compared with those in the least deprived group with favorable lifestyle, participants in the most deprived group adherent to unfavorable lifestyle had the highest risk of mental health outcomes. These results suggest that adherence to a broad combination of healthy lifestyle factors was associated with a significantly reduced risk of mental health conditions during the COVID-19 pandemic. Lifestyle factors, in conjunction with socioeconomic deprivation, independently contribute to the risk of mental health issues. Although further research is needed to assess causality, the current findings support public health strategies and individual-level interventions that provide enhanced support in areas of deprivation and target multiple lifestyle factors to reduce health inequalities and promote mental well-being during the ongoing COVID-19 pandemic.

Mefloquine targets NLRP3 to reduce lipopolysaccharide-induced systemic inflammation and neural injury.

The NLR family pyrin domain containing 3 (NLRP3) inflammasome plays an important role in the pathogenesis of a wide variety of human diseases. So far, drugs directly and specifically targeting the NLRP3 inflammasome are not available for clinical use since the safety and efficacy of new compounds are often unclear. A promising approach is thus to identify NLRP3 inhibitors from existing drugs that are already in clinical use. Here, we show that mefloquine, a well-known antimalarial drug, is a highly selective and potent NLRP3 inhibitor by screening a FDA-approved drug library. Mechanistically, mefloquine directly binds to the NLRP3 NACHT and LRR domains to prevent NLRP3 inflammasome activation. More importantly, mefloquine treatment attenuates the symptoms of lipopolysaccharide-induced systemic inflammation and Parkinson's disease-like neural damage in mice. Our findings identify mefloquine as a potential therapeutic agent for NLRP3-driven diseases and migth expand its clinical use considerably.

The Gasdermin D N-terminal fragment acts as a negative feedback system to inhibit inflammasome-mediated activation of Caspase-1/11.

Inflammatory pathways usually utilize negative feedback regulatory systems to prevent tissue damage arising from excessive inflammatory response. Whether such negative feedback mechanisms exist in inflammasome activation remains unknown. Gasdermin D (GSDMD) is the pyroptosis executioner of downstream inflammasome signaling. Here, we found that GSDMD, after its cleavage by caspase-1/11, utilizes its RFWK motif in the N-terminal ß1-ß2 loop to inhibit the activation of caspase-1/11 and downstream inflammation in a negative feedback manner. Furthermore, an RFWK motif-based peptide inhibitor can inhibit caspase-1/11 activation and its downstream substrates GSDMD and interleukin-1ß cleavage, as well as lipopolysaccharide-induced sepsis in mice. Collectively, these findings provide a demonstration of the N-terminal fragment of GSDMD as a negative feedback regulator controlling inflammasome activation and a detailed delineation of the underlying inhibitory mechanism.

A joint deep learning model enables simultaneous batch effect correction, denoising, and clustering in single-cell transcriptomics.

Recent developments of single-cell RNA-seq (scRNA-seq) technologies have led to enormous biological discoveries. As the scale of scRNA-seq studies increases, a major challenge in analysis is batch effects, which are inevitable in studies involving human tissues. Most existing methods remove batch effects in a low-dimensional embedding space. Although useful for clustering, batch effects are still present in the gene expression space, leaving downstream gene-level analysis susceptible to batch effects. Recent studies have shown that batch effect correction in the gene expression space is much harder than in the embedding space. Methods such as Seurat 3.0 rely on the mutual nearest neighbor (MNN) approach to remove batch effects in gene expression, but MNN can only analyze two batches at a time, and it becomes computationally infeasible when the number of batches is large. Here, we present CarDEC, a joint deep learning model that simultaneously clusters and denoises scRNA-seq data while correcting batch effects both in the embedding and the gene expression space. Comprehensive evaluations spanning different species and tissues showed that CarDEC outperforms Scanorama, DCA + Combat, scVI, and MNN. With CarDEC denoising, non-highly variable genes offer as much signal for clustering as the highly variable genes (HVGs), suggesting that CarDEC substantially boosted information content in scRNA-seq. We also showed that trajectory analysis using CarDEC's denoised and batch-corrected expression as input revealed marker genes and transcription factors that are otherwise obscured in the presence of batch effects. CarDEC is computationally fast, making it a desirable tool for large-scale scRNA-seq studies.

Maternal gestational diabetes and childhood adiposity risk from 6 to 8 years of age.

BACKGROUND/OBJECTIVE: Previous studies found conflicting results on the association between maternal gestational diabetes mellitus (GDM) and childhood overweight/obesity. This study was to assess the association between maternal GDM and offspring's adiposity risk from 6 to 8 years of age. METHODS: The present study longitudinally followed 1156 mother-child pairs (578 GDM and 578 non-GDM) at 5.9 ± 1.2 years postpartum and retained 912 mother-child pairs (486 GDM and 426 non-GDM) at 8.3 ± 1.6 years postpartum. Childhood body mass index (BMI), waist circumference, body fat and skinfold were measured using standardized methods. RESULTS: Compared with the counterparts born to mothers with normal glucose during pregnancy, children born to mothers with GDM during pregnancy had higher mean values of adiposity indicators (waist circumference, body fat, subscapular skinfold and suprailiac skinfold) at 5.9 and 8.3 years of age. There was a positive association of maternal GDM with changes of childhood adiposity indicators from the 5.9-year to 8.3-year visit, and ß values were significantly larger than zero: +0.10 (95% CI: 0.02-0.18) for z score of BMI for age, +1.46 (95% CI: 0.70-2.22) cm for waist circumference, +1.78% (95% CI: 1.16%-2.40%) for body fat, +2.40 (95% CI: 1.78-3.01) mm for triceps skinfold, +1.59 (95% CI: 1.10-2.09) mm for subscapular skinfold, and +2.03 (95% CI: 1.35-2.71) mm for suprailiac skinfold, respectively. Maternal GDM was associated with higher risks of childhood overweight/obesity, central obesity, and high body fat (Odd ratios 1.41-1.57 at 5.9 years of age and 1.73-2.03 at 8.3 years of age) compared with the children of mothers without GDM. CONCLUSIONS: Maternal GDM was a risk factor of childhood overweight/obesity at both 5.9 and 8.3 years of age, which was independent from several important confounders including maternal pre-pregnancy BMI, gestational weight gain, children's birth weight and lifestyle factors. This significant and positive association became stronger with age.

Propensity score matching enables batch-effect-corrected imputation in single-cell RNA-seq analysis.

Developments of single-cell RNA sequencing (scRNA-seq) technologies have enabled biological discoveries at the single-cell resolution with high throughput. However, large scRNA-seq datasets always suffer from massive technical noises, including batch effects and dropouts, and the dropout is often shown to be batch-dependent. Most existing methods only address one of the problems, and we show that the popularly used methods failed in trading off batch effect correction and dropout imputation. Here, inspired by the idea of causal inference, we propose a novel propensity score matching method for scRNA-seq data (scPSM) by borrowing information and taking the weighted average from similar cells in the deep sequenced batch, which simultaneously removes the batch effect, imputes dropout and denoises data in the entire gene expression space. The proposed method is testified on two simulation datasets and a variety of real scRNA-seq datasets, and the results show that scPSM is superior to other state-of-the-art methods. First, scPSM improves clustering accuracy and mixes cells of the same type, suggesting its ability to keep cell type separation while correcting for batch. Besides, using the scPSM-integrated data as input yields results free of batch effects or dropouts in the differential expression analysis. Moreover, scPSM not only achieves ideal denoising but also preserves real biological structure for downstream gene-based analyses. Furthermore, scPSM is robust to hyperparameters and small datasets with a few cells but enormous genes. Comprehensive evaluations demonstrate that scPSM jointly provides desirable batch effect correction, imputation and denoising for recovering the biologically meaningful expression in scRNA-seq data.

All-optical neuromorphic XOR and XNOR operation utilizing a photonic spiking neuron based on a passive add-drop microring resonator.

We propose a concise hardware architecture supporting efficient exclusive OR (XOR) and exclusive NOR (XNOR) operations, by employing a single photonic spiking neuron based on a passive add-drop microring resonator (ADMRR). The threshold mechanism and inhibitory dynamics of the ADMRR-based spiking neuron are numerically discussed on the basis of the coupled mode theory. It is shown that a precise XOR operation in the ADMRR-based spiking neuron can be implemented by adjusting temporal differences within the inhibitory window. Additionally, within the same framework, the XNOR function can also be carried out by accumulating the input power over time to trigger an excitatory behavior. This work presents a novel, to the best of our knowledge, and pragmatic technique for optical neuromorphic computing and information processing utilizing passive devices.

Interactive effects of gestational diabetes and high pre-pregnancy body mass index on adverse growth patterns of offspring.

AIMS: To examine the independent and interactive effects of maternal gestational diabetes mellitus (GDM) and high pre-pregnancy body mass index (BMI) on the risk of offspring adverse growth patterns. MATERIALS AND METHODS: One thousand six hundred and eighty one mother-child pairs were followed for 8 years in Tianjin, China. Group-based trajectory modelling was used to identify offspring growth patterns. Logistic regression was performed to obtain odds ratios (ORs) and 95% confidence intervals (CIs) of GDM and high pre-pregnancy BMI for offspring adverse growth patterns. Restricted cubic spline was used to identify cut-off points. Additive interactions and multiplicative interactions were used to test interactive effects between GDM and high pre-pregnancy BMI for adverse growth patterns. RESULTS: Four distinct growth patterns were identified in offspring, including normal growth pattern, persistent lean growth pattern, late obesity growth pattern (LOGP), and persistent obesity growth pattern (POGP). Maternal high pre-pregnancy BMI was associated with LOGP and POGP (adjusted OR, 95% CI: 2.38, 1.74-3.25 & 4.92, 2.26-10.73). GDM greatly enhanced the adjusted OR of high pre-pregnancy BMI for LOGP up to 3.48 (95% CI: 2.25-5.38). Additive interactions and multiplicative interactions between both risk factors were significant for LOGP but not for POGP. CONCLUSIONS: Maternal high pre-pregnancy BMI was associated with increased risk of LOGP and POGP, whereas GDM greatly enhanced the risk of high pre-pregnancy BMI for LOGP.

Effects of Non-Face-to-Face Chronic Care Management on Service Utilization and Outcomes Among US Medicare Beneficiaries with Diabetes.

BACKGROUND: Type 2 diabetes mellitus (T2DM) results in heavy economic and disease burdens in Louisiana. The Centers for Medicare and Medicaid Services has reimbursed non-face-to-face chronic care management (NFFCCM) for patients with two or more chronic conditions since 2015. OBJECTIVE: To assess the impacts of NFFCCM on healthcare utilization and health outcomes. DESIGN, SETTING, AND PARTICIPANTS: This retrospective cohort study included Medicare fee-for-service beneficiaries with T2DM and at least one additional chronic disease between 2014 and 2018. EXPOSURES: At least one record of NFFCCM Current Procedural Terminology codes. MAIN MEASURES: The health outcomes in the study included major adverse cardiovascular events (MACE), all-cause mortality, and heart failure. The monthly service utilization and continuity of care index for primary care were also included. The propensity score method was used to balance the baseline differences between the two groups. Weighted multivariate regression models were developed using propensity score weights to assess the impacts of NFFCCM on outcomes. KEY RESULTS: During the 5 years of study period, 8415 patients among the 118,643 Medicare beneficiaries received at least one NFFCCM. Patients receiving any NFFCCM had reduced healthcare utilization compared with patients not receiving NFFCCM, including 0.012 (95% CI - 0.014 to - 0.011; p < 0.001) fewer monthly hospital admissions, 0.017 (95% CI - 0.019 to - 0.016; p < 0.001) fewer monthly ED visits, and 0.399 (95% CI 0.375 to 0.423; p < 0.001) more monthly outpatient encounters. Patients receiving NFFCCM services had lower MACE event rates of 7.4% (95% CI 7.1 to 7.8%; p < 0.001), all-cause mortality rate of 7.8% (95% CI 7.4 to 8.1%; p < 0.001), and heart failure rate of 0.3% (95% CI 0.2 to 0.5%; p < 0.001), respectively. CONCLUSIONS AND RELEVANCE: These findings suggest that reimbursement for NFFCCM was associated with the shifting high-cost utilization to lower-cost primary health care settings among patients with diabetes in Louisiana.

Nomogram for predicting the probability of rectal anastomotic re-leakage after stoma closure: a retrospective study.

BACKGROUND: In this study, we aimed to identify the risk factors in patients with rectal anastomotic re-leakage and develop a prediction model to predict the probability of rectal anastomotic re-leakage after stoma closure. METHODS: This study was a single-center retrospective analysis of patients with rectal cancer who underwent surgery between January 2010 and December 2020. Among 3225 patients who underwent Total or Partial Mesorectal Excision (TME/PME) surgery for rectal cancer, 129 who experienced anastomotic leakage following stoma closure were enrolled. Risk factors for rectal anastomotic re-leakage were analyzed, and a prediction model was established for rectal anastomotic re-leakage. RESULTS: Anastomotic re-leakage after stoma closure developed in 13.2% (17/129) of patients. Multivariable analysis revealed that neoadjuvant chemoradiotherapy (odds ratio, 4.07; 95% confidence interval, 1.17-14.21; p = 0.03), blood loss > 50 ml (odds ratio, 4.52; 95% confidence interval, 1.31-15.63; p = 0.02), and intersphincteric resection (intersphincteric resection vs. low anterior resection: odds ratio, 6.85; 95% confidence interval, 2.01-23.36; p = 0.002) were independent risk factors for anastomotic re-leakage. A nomogram was constructed to predict the probability of anastomotic re-leakage, with an area under the receiver operating characteristic curve of 0.828 in the cohort. Predictive results correlated with the actual results according to the calibration curve. CONCLUSIONS: Neoadjuvant chemoradiotherapy, blood loss > 50 ml, and intersphincteric resection are independent risk factors for anastomotic re-leakage following stoma closure. The nomogram can help surgeons identify patients at a higher risk of rectal anastomotic re-leakage.

Habitual use of glucosamine and adverse liver outcomes among patients with type 2 diabetes and MASLD.

BACKGROUND: Glucosamine is a dietary supplement commonly used to support joint health. However, there has been interest in exploring other effects of glucosamine on health outcomes due to its ant-inflammation effect. OBJECTIVE: This study compared the risks of major adverse liver outcomes (MALOs) between regular users and non-users of glucosamine among patients with type 2 diabetes and metabolic dysfunction associated steatotic liver disease (MASLD) using the data from a large prospective cohort study. METHODS: Demographic, anthropometric, laboratory and medication prescription information among 18 753 patients with type 2 diabetes and MASLD was obtained from the UK Biobank. MASLD was identified based on hepatic steatosis defined by fatty liver index ≥60 plus the presence of any clues of metabolic dysregulation and cardio-metabolic risk factors, excluding patients with moderate to severe alcohol consumption. RESULTS: During a mean follow-up of 11.4 years, 826 incident MALOs events were recorded. Patients not regularly using glucosamine compared with patients using glucosamine showed a significantly higher risk of the composite MALOs (HR 1.36, 95% confidence interval [CI] 1.09-1.69) as well as most individual MALOs except for ascites. The multivariable-adjusted HRs of MALOs within 3, 5 and 10 years among non-users of glucosamine compared with regular users were 1.79 (95% CI .69-2.03), 1.88 (95% CI 1.21-2.54) and 1.32 (95% CI 1.05-1.72), respectively. Further subgroup analyses in participants with different baseline characteristics and sensitivity analyses excluding participants who regularly took any other supplements and participants who used self-reports to diagnose diabetes confirmed the findings. CONCLUSIONS: The present study indicated that habitual use of glucosamine was associated with a low risk of individual and composite MALOs among patients with type 2 diabetes and MASLD.

Serum tumor marker and CT body composition scoring system predicts outcomes in colorectal cancer surgical patients.

OBJECTIVE: To investigate the prognostic value of preoperative body composition and serum tumor markers (STM) in patients undergoing surgical treatment for colorectal cancer (CRC) and to establish the prognostic score for patients with CRC. METHODS: This study enrolled 365 patients (training set 245, validation set 120) with CRC who underwent surgical resection. The predictive value of various body composition features and STM for determining CRC prognosis were compared. A novel index score based on the independent risk factors from Cox regression for CRC patients was established and evaluated for its usefulness. RESULTS: Multivariate Cox regression showed that low skeletal muscle radiodensity (SMD) (p = 0.020), low subcutaneous fat area (SFA) (p = 0.029), high carcinoembryonic antigen (CEA) (p = 0.008), and high alpha-fetoprotein (AFP) (p = 0.039) were all independent prognostic factors for poor overall survival (OS). The multifactorial analysis indicated that high intermuscular fat area (IMFA) (p = 0.033) and high CEA (p = 0.009) were independent prognostic factors for poor disease-free survival (DFS). Based on these findings, two scoring systems for OS and DFS were established in the training datasets. CRC patients who scored higher on the new scoring systems had lower OS and DFS (both p < 0.001) as shown in the Kaplan-Meier survival curves in the training and validation datasets. CONCLUSION: In predicting the prognosis of CRC patients, SFA and SMD are superior to other body composition measurements. A scoring system based on body composition and STM can have prognostic value and clinical applicability. CLINICAL RELEVANCE STATEMENT: This scoring system, combining body composition and serum tumor markers, may help predict postoperative survival of CRC patients and help clinicians make well-informed decisions regarding the treatment of patients. KEY POINTS: Colorectal cancer prognosis can be related to body composition. High intermuscular fat area and CEA were independent prognostic factors for poor disease-free survival. This scoring system, based on body composition and tumor markers, can prognosticate for colorectal cancer patients.

A novel classification of posterior pelvic exenteration to assess prognosis in female patients with locally advanced primary rectal cancer: a retrospective cohort study from China PelvEx collaborative.

PURPOSE: Surgical techniques and the prognosis of posterior pelvic exenteration for locally advanced primary rectal cancer in female patients pose challenges that need to be addressed. Therefore, we investigated the short-term and survival outcomes of posterior pelvic exenteration in female patients using a novel Peking classification. METHODS: We retrospectively analysed a prospective database from China PelvEx Collaborative across three tertiary referral centres. A total of 172 patients who underwent combined resection for locally advanced primary rectal cancer were classified based on four subtypes (PPE-I [64/172], PPE-II [68/172], PPE-III [21/172], and PPE-IV [19/172]) according to the Peking classification; perioperative characteristics and short-term and oncological outcomes were analysed. RESULTS: Differences were significant among the four groups regarding colorectal reconstruction (p < 0.001), perineal reconstruction (p < 0.001), in-hospital complications (p < 0.05), and urinary retention (p < 0.05). The R0 resection rates for PPE-I, PPE-II, PPE-III, and PPE-IV were 90.6%, 89.7%, 90.5%, and 89.5%, respectively. The 5-year overall survival rates of the PPE-I, PPE-II, PPE-III, and PPE-IV groups were 73.4%, 68.8%, 54.7%, and 37.3%, respectively. Correspondingly, their 5-year disease-free survival rates were 76.0%, 62.5%, 57.7%, and 43.1%, respectively. Notably, the PPE-IV group demonstrated the lowest 5-year overall survival rate (p < 0.001) and 5-year disease-free survival rate (p < 0.001). CONCLUSION: The Peking classification can aid in determining suitable surgical techniques and conducting prognostic assessments in female patients with locally advanced primary rectal cancer.

The marine-derived compound TAG alleviates Parkinson's disease by restoring RUBCN-mediated lipid metabolism homeostasis.

Parkinson's disease (PD) is the second most common neurodegenerative disease, and its prevalence is increasing. Currently, no effective therapies for PD exist. Marine-derived natural compounds are considered important resources for the discovery of new drugs due to their distinctive structures and diverse activities. In this study, tetrahydroauroglaucin (TAG), a polyketide isolated from a marine sponge, was found to have notable neuroprotective effects on MPTP/MPP+-induced neurotoxicity. RNA sequencing analysis and metabolomics revealed that TAG significantly improved lipid metabolism disorder in PD models. Further investigation indicated that TAG markedly decreased the accumulation of lipid droplets (LDs), downregulated the expression of RUBCN, and promoted autophagic flux. Moreover, conditional knockdown of Rubcn notably attenuated PD-like symptoms and the accumulation of LDs, accompanied by blockade of the neuroprotective effect of TAG. Collectively, our results first indicated that TAG, a promising PD therapeutic candidate, could suppress the accumulation of LDs through the RUBCN-autophagy pathway, which highlighted a novel and effective strategy for PD treatment.