Cognitive interviewing validation of the Chinese version of the neurogenic bladder symptom score.

Background: The neurogenic bladder symptom score (NBSS) has been widely used to specifically measure symptoms and consequences of neurogenic bladder (NB). The cognitive interviewing (CI) is effective in assessing item clarity and identifying key issues related to the comprehension of the instrument. We aim to translate the NBSS into Chinese and use the CI approach to explore the thought processes of patients with NB in responding the Chinese Version of the NBSS, identify and modify the factors hinder the thought processes to enhance the face validity of the NBSS. Methods: The translation of the NBSS into Chinese was conducted with the guidance of the recommended frameworks. Patients with NB were recruited by purpose sampling. CI with the combination of thinking aloud and verbal probing techniques were used to explore thought processes. The interviews were transcribed and analyzed based on Tourangeau four-stage response model. Results: Two rounds of CI were carried out. The problems of comprehension, judgement and response mapping were identified in 8 items. Four items were revised based on the results of the interview. The revised items were verified and eventually integrated into the final version. Conclusion: The Chinese Version of the NBSS was easy to comprehend and use. The use of CI methodologies can increase the comprehensibility and cultural applicability of the NBSS, providing the evidence for the development of a clearer and more appropriate questionnaire.

Molecular Dynamics Simulation Combined with Neural Relationship Inference and Markov Model to Reveal the Relationship between Conformational Regulation and Bioluminescence Properties of Gaussia Luciferase.

Gaussia luciferase (Gluc) is currently known as the smallest naturally secreted luciferase. Due to its small molecular size, high sensitivity, short half-life, and high secretion efficiency, it has become an ideal reporter gene and is widely used in monitoring promoter activity, studying protein-protein interactions, protein localization, high-throughput drug screening, and real-time monitoring of tumor occurrence and development. Although studies have shown that different Gluc mutations exhibit different bioluminescent properties, their mechanisms have not been further investigated. The purpose of this study is to reveal the relationship between the conformational changes of Gluc mutants and their bioluminescent properties through molecular dynamics simulation combined with neural relationship inference (NRI) and Markov models. Our results indicate that, after binding to the luciferin coelenterazine (CTZ), the α-helices of the 109-119 residues of the Gluc Mutant2 (GlucM2, the flash-type mutant) are partially unraveled, while the α-helices of the same part of the Gluc Mutant1 (GlucM1, the glow-type mutant) are clearly formed. The results of Markov flux analysis indicate that the conformational differences between glow-type and flash-type mutants when combined with luciferin substrate CTZ mainly involve the helicity change of α7. The most representative conformation and active pocket distance analysis indicate that compared to the flash-type mutant GlucM2, the glow-type mutant GlucM1 has a higher degree of active site closure and tighter binding. In summary, we provide a theoretical basis for exploring the relationship between the conformational changes of Gluc mutants and their bioluminescent properties, which can serve as a reference for the modification and evolution of luciferases.

Catalpol ameliorates liver fibrosis via inhibiting aerobic glycolysis by EphA2/FAK/Src signaling pathway.

BACKGROUND: Hepatic fibrosis is a pathological process in a variety of acute or chronic liver injuries. Catalpol (CAT), an iridoid glycoside found in Rehmannia glutinosa, has several pharmacological properties, including anti-inflammatory, antidiabetic and anti-fibrotic effects. Nevertheless, there is currently no report on whether CAT regulates the aerobic glycolysis of hepatic stellate cells (HSCs) to inhibit liver fibrosis. OBJECTIVE: This study aimed to investigate the protective effects of CAT on hepatic fibrosis and elucidate its underlying mechanisms. METHODS: To explore whether CAT improved liver fibrosis in vivo and in vitro, hepatic fibrosis was induced to mice by intraperitoneally injecting carbon tetrachloride (CCl4). Additionally, LX-2 cells were stimulated with transforming growth factor-ß (TGF-ß) to simulate fibrosis in vitro. Serum markers of liver injury were examined by using an automatic biochemical analyzer. Histopathological staining, Immunofluorescence (IF) staining, Western blot (WB) analysis, co-immunoprecipitation (Co-IP), drug affinity responsive target stability (DARTS), cellular thermal shift assay (CETSA), etc. were employed to identify the targeting between CAT and EphA2 and detect the expression of aerobic glycolysis related proteins, fiber markers and signaling pathways that are responsible for CAT's anti-fibrotic effects of CAT. RESULTS: Results showed that CAT significantly inhibited hepatic injury, fibrogenesis and inflammation in mice treated with CCl4. This was demonstrated by the enhancement of fibrosis markers, liver function indices, and histopathology. In addition, CAT significantly inhibited the activation of HSCs in TGF-ß-induced LX-2 cells, as indicated by decreased proliferation, migration, and expression of collagen I and a-SMA. The study results also suggested that CAT may exert anti-fibrotic effects by inhibiting glycolysis in activated HSCs and in CCl4-treated mice. Mechanistically, CAT directly targets Ephrin type-A receptor 2 (EphA2) to reduce binding with focal adhesion kinases (FAK) and significantly inhibits the FAK/Src pathway. In addition, the pharmacological inhibition of EphA2 cannot further increase the therapeutic effects of CAT on liver fibrosis in vivo and in vitro. CONCLUSION: The study findings generally demonstrated that CAT presented a novel therapeutic method to treat hepatic fibrosis; this method which inhibits the aerobic glycolysis of activated HSCs through the EphA2/FAK/Src signaling pathway.

Maternal Hypertension and Fecundability: A Population-Based Cohort Study.

BACKGROUND: The association of hypertension and blood pressure control with fecundability among women is not yet elucidated. The purpose of this study was to evaluate the hypothesis that maternal preconception hypertension would be associated with reduced fecundability and that blood pressure control could reduce excess risk. METHODS: Using the National Free Preconception Checkup Projects in Guangdong Province, China, 1422 couples whose female partners had been diagnosed with hypertension and 997 703 reference couples whose female partners were without hypertension were included in this prospective cohort study. Fecundability was measured by time to pregnancy (TTP) and infertility (TTP >12 months). RESULTS: Compared with women without hypertension, those with controlled hypertension (time ratio, 1.47 [95% CI, 1.24-1.73]) or uncontrolled hypertension (time ratio, 1.59 [95% CI, 1.34-1.90]) were associated with prolonged TTP and increased risk of infertility (relative risk, 1.19 [95% CI, 1.09-1.31]; relative risk, 1.24 [95% CI, 1.14-1.34]). However, using instrumental variable analyses, there was no significant association between blood pressure control and TTP (time ratio, 0.68 [95% CI, 0.34-1.36]; P=0.270) or infertility (relative risk, 0.97 [95% CI, 0.70-1.34]; P=0.849) among women with hypertension. These results were consistent in the propensity score matching and inverse probability of treatment weighting analyses. CONCLUSIONS: Maternal hypertension, with or without controlled blood pressure, was independently associated with prolonged TTP and an increased risk of infertility. These findings may provide insights for the implementation of preconception hypertension screening and the design of future trials.

Potential mechanisms of ZiGongDing in treating HPV-induced cervical intraepithelial neoplasia: a network pharmacology and experimental verification study.

The onset of cervical intraepithelial neoplasia (CIN) is strongly associated with persistent infection caused by high-risk human papillomavirus (HPV). ZiGongDing (ZGD), a traditional Chinese medicine, has progressed to clinical application in HPV-induced CIN treatment, yet the underlying mechanism remains unclear. The objective of this paper is to explore the mechanism of ZGD in treating HPV-induced CIN by integrating a combination of network pharmacology and experimental validation. The active ingredients and targets of ZGD were obtained from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) database. CIN-related targets were sourced from GeneCards and the Online Mendelian Inheritance in Man (OMIM) database. Protein-protein interaction (PPI) and functional enrichment analyses were conducted to determine the potential molecular mechanism. The herb-active ingredient-target network was constructed by Cytoscape software. To further validate the therapeutic mechanism, molecular docking and in vitro experiments were performed. In this study, we identified 60 active ingredients in ZGD and 46 common targets in of CIN treatment. The PPI network analysis revealed estrogen receptor 1 (ESR1) as a pivotal target in ZGD against CIN. Functional enrichment analysis showed that the estrogen signaling pathway was mostly enriched, and ESR1 was involved. The herb-active ingredient-target network and relative literature identified cnidimol B as the primary active ingredient. Molecular docking demonstrated a strong binding affinity between ESR1 and cnidimol B. Cellular experiments revealed that cnidimol B could significantly decrease the viability of HeLa and CaSki cells. Moreover, the expression of ESR1 was notably upregulated in HeLa and CaSki cells after treatment with cnidimol B. Our study proposes a novel mechanism underlying ZGD against CIN, which involves the modulation of ESR1. This insight lays a solid foundation for further exploring and optimizing ZGD's therapeutic potential.

Optimizing the dosing regimen of roxadustat in kidney transplant recipients with early post-transplant anemia.

INTRODUCTION: Roxadustat, an oral inhibitor of hypoxia-inducible factor prolyl hydroxylase domain enzymes, has been approved for the treatment of renal anemia. However, there is a lack of study on its pharmacokinetics in kidney transplant recipients (KTRs) with early posttransplant anemia (PTA). Therefore, the aim of this study is to elucidate the pharmacokinetic characteristics of roxadustat in KTRs with early PTA and optimize the dosing regimen. METHODS: A population pharmacokinetic (PopPK) analysis was performed based on 72-hour full concentration-time profiles collected from 52 Chinese KTRs. Covariates influencing exposure were assessed using stepwise covariate modelling. Monte Carlo simulations were conducted to recommend the dosing regimen for patients with different levels of covariates. RESULTS: PopPK analysis showed that the concentration-time data can be fully described by a two-compartment model. Body weight (BW) and direct bilirubin (DBIL) levels significant affected the apparent clearance of roxadustat. Based on the established model and the estimated exposures of roxadustat by Monte Carlo simulations, a recommended dosing regimen for KTRs with early PTA at varying BW and DBIL levels were developed. Roxadustat at 100 mg three times weekly were suitable for the majority of KTRs with a DBIL level around 3 µmol/L and BW between 50 and 75 kg. The required dose may need to be increased with higher BW and lower DBIL levels, while decreased with lower BW and higher DBIL levels. CONCLUSIONS: It was the first PopPK analysis of roxadustat in KTRs with early PTA, which provide a research basis for optimizing the dosing regimen.

Comparative analysis of the immune repertoire between peripheral blood and bone marrow fluids in those infected by EBV and immunodeficiency: A retrospective case study.

High-throughput immune repertoire (IR) sequencing provides direct insight into the diversity of B cell receptor (BCR) and T cell receptor (TCR), with great potential to revolutionize the diagnosis, monitoring, and prevention of immune system-related disorders. In this study, multiplex PCR was applied to amplify the complementarity-determining regions of BCR and TCR, followed by comprehensive analysis by high-throughput sequencing. We compare the TCR (BCR) of bone marrow fluid (BMF) and peripheral blood (PB) samples from 17 patients in the Epstein-Barr and immunodeficiency groups, respectively. Our study shows that the diversity of the IR of blood samples is very similar to that of bone marrow samples statistically. However, the distributions of the monoclonal genes are significantly different in these 2 samples of most patients. This suggests that the BMFs can be replaced by the PB samples in diversity detection of IR to monitor the immune status of the body, while the detection of the BMFs is unreplaceable when the monoclonal change occurs. We used high-throughput sequencing to assess the TCR and BCR of the patients and provide a basis for the clinical analysis of PB and bone marrow samples and selection of disease diagnosis and monitoring methods.

Specific peptides targeting the myocardiocyte are prognostic markers for heart attack: Function of α-SMA protein.

Myocardial infarction (MI) is a serious cardiovascular disease that often results in a significant decline in heart function and associated complications. α-SMA (α-smooth muscle cell actin) is an important biomarker in the process of cardiac remodeling and repair, and its expression level is closely related to myocardial remodeling and prognosis. Therefore, the purpose of this study was to investigate the potential of nanoparticles containing cardiomyocyte targeting peptides in predicting prognosis and α-SMA protein expression after myocardial infarction, with a view to providing new therapeutic strategies and clinical guidelines. In this study, a novel targeting nanoparticle was constructed, using cardiomyocyte specific peptides as targeting ligands, and characterized by loading different drugs. Subsequently, a mouse model of myocardial infarction was used to systematically evaluate the effect of nanoparticles on α-SMA protein expression and prognosis prediction ability after MI. The expression level of α-SMA was analyzed by Western blot and immunohistochemistry, and the prognosis was evaluated by cardiac function assessment. The study found that nanoparticles containing cardiomyocyte targeting peptides significantly increased α-SMA expression levels and improved heart function in animal models of myocardial infarction. Compared with the control group, the application of targeted nanoparticles was closely related to the level of myocardial cell repair and fibrosis, and could effectively predict the prognosis after myocardial infarction. Therefore, nanoparticles containing cardiomyocyte targeting peptides can not only effectively improve the expression of α-SMA, but also serve as an important prognostic tool after myocardial infarction.

Waterborne polyurethane nanoparticles incorporating linoleic acid as a potential strategy for controlling antibiotic resistance spread in the mammalian intestine.

Plasmid-mediated conjugative transfer of antibiotic resistance genes (ARGs) within the human and animal intestine represents a substantial global health concern. linoleic acid (LA) has shown promise in inhibiting conjugation in vitro, but its in vivo effectiveness in the mammalian intestinal tract is constrained by challenges in efficiently reaching the target site. Recent advancements have led to the development of waterborne polyurethane nanoparticles for improved drug delivery. In this study, we synthesized four waterborne polyurethane nanoparticles incorporating LA (WPU@LA) using primary raw materials, including N-methyldiethanolamine, 2,2'-(piperazine-1,4-diyl) diethanol, isophorone diisocyanate, castor oil, and acetic acid. These nanoparticles, identified as WPU0.89@LA, WPU0.99@LA, WPU1.09@LA, and WPU1.19@LA, underwent assessment for their pH-responsive release property and biocompatibility. Among these, WPU0.99@LA displayed superior pH-responsive release properties and biocompatibility towards Caco-2 and IPEC-J2 cells. In a mouse model, a dosage of 10 mg/kg/day WPU0.99@LA effectively reduced the conjugation of IncX4 plasmids carrying the mobile colistin resistance gene (mcr-1) by more than 45.1-fold. In vivo toxicity assessment demonstrated that 10 mg/kg/day WPU0.99@LA maintains desirable biosafety and effectively preserves gut microbiota homeostasis. In conclusion, our study provides crucial proof-of-concept support, demonstrating that WPU0.99@LA holds significant potential in controlling the spread of antibiotic resistance within the mammalian intestine.

Causal Relationship Between Gut Microbiota and Chronic Obstructive Pulmonary Disease: A Bidirectional Two-Sample Mendelian Randomization Study.

Background: The associations between gut microbiota and chronic obstructive pulmonary disease (COPD) have gained increasing attention and research interest among scholars. However, it remains unclear whether gut microbiota serves as a causal factor for COPD or if it is a consequence of the disease. Therefore, we investigated the causal relationship between COPD and gut microbiota, with intention of providing novel insights and references for clinical diagnosis and treatment. Methods: Based on the genome-wide association study (GWAS) data, we employed MR-Egger regression, random-effects inverse variance-weighted (IVW) method, and weighted median method for bidirectional Mendelian randomization (MR) analysis. We conducted Cochran's Q test for heterogeneity assessment and performed multivariable analysis, sensitivity analysis, and heterogeneity testing to validate the reliability and stability of results. Results: Utilizing MR analysis, mainly employing the IVW method, we detected a collective of 11 gut microbiota species that exhibited associations with COPD. Among them, Bacteroidia, family XIII, Clostridium innocuum group, Barnesiella, Collinsella, Lachnospiraceae NK4A136 group, Lachnospiraceae UCG004, Lachnospiraceae UCG010, and Bacteroidales were found to be protective factors for COPD. On the other hand, Holdemanella and Marvinbryantia were identified as risk factors for COPD. Individuals with elevated levels of Holdemanella exhibited a 1.141-fold higher risk of developing COPD compared to their healthy counterparts, and those with increased levels of Marvinbryantia had a 1.154-fold higher risk. Reverse MR analysis yielded no evidence indicating a causal relationship between gut microbiota and COPD occurrence. Conclusion: Our study established a causal link between 11 specific gut microbiota species and COPD, offering novel insights and valuable references for targeted therapies in the clinical management of COPD. However, our results were mainly based on the analysis of database, and further clinical studies are needed to clarify the effects of gut microbiota on COPD and its specific protective mechanism.

LIG1 is a novel marker for bladder cancer prognosis: evidence based on experimental studies, machine learning and single-cell sequencing.

Background: Bladder cancer, a highly fatal disease, poses a significant threat to patients. Positioned at 19q13.2-13.3, LIG1, one of the four DNA ligases in mammalian cells, is frequently deleted in tumour cells of diverse origins. Despite this, the precise involvement of LIG1 in BLCA remains elusive. This pioneering investigation delves into the uncharted territory of LIG1's impact on BLCA. Our primary objective is to elucidate the intricate interplay between LIG1 and BLCA, alongside exploring its correlation with various clinicopathological factors. Methods: We retrieved gene expression data of para-carcinoma tissues and bladder cancer (BLCA) from the GEO repository. Single-cell sequencing data were processed using the "Seurat" package. Differential expression analysis was then performed with the "Limma" package. The construction of scale-free gene co-expression networks was achieved using the "WGCNA" package. Subsequently, a Venn diagram was utilized to extract genes from the positively correlated modules identified by WGCNA and intersect them with differentially expressed genes (DEGs), isolating the overlapping genes. The "STRINGdb" package was employed to establish the protein-protein interaction (PPI) network.Hub genes were identified through the PPI network using the Betweenness Centrality (BC) algorithm. We conducted KEGG and GO enrichment analyses to uncover the regulatory mechanisms and biological functions associated with the hub genes. A machine-learning diagnostic model was established using the R package "mlr3verse." Mutation profiles between the LIG1^high and LIG1^low groups were visualized using the BEST website. Survival analyses within the LIG1^high and LIG1^low groups were performed using the BEST website and the GENT2 website. Finally, a series of functional experiments were executed to validate the functional role of LIG1 in BLCA. Results: Our investigation revealed an upregulation of LIG1 in BLCA specimens, with heightened LIG1 levels correlating with unfavorable overall survival outcomes. Functional enrichment analysis of hub genes, as evidenced by GO and KEGG enrichment analyses, highlighted LIG1's involvement in critical function such as the DNA replication, cellular senescence, cell cycle and the p53 signalling pathway. Notably, the mutational landscape of BLCA varied significantly between LIG1high and LIG1low groups.Immune infiltrating analyses suggested a pivotal role for LIG1 in immune cell recruitment and immune regulation within the BLCA microenvironment, thereby impacting prognosis. Subsequent experimental validations further underscored the significance of LIG1 in BLCA pathogenesis, consolidating its functional relevance in BLCA samples. Conclusions: Our research demonstrates that LIG1 plays a crucial role in promoting bladder cancer malignant progression by heightening proliferation, invasion, EMT, and other key functions, thereby serving as a potential risk biomarker.

Quality characterization of tobacco flavor and tobacco leaf position identification based on homemade electronic nose.

A set of nine unique tobacco extract samples was analyzed using a self-developed electronic nose (E-nose) system, a commercial E-nose, and gas chromatography-mass spectrometry (GC-MS). The evaluation employed principal component analysis, statistical quality control, and soft independent modeling of class analogies (SIMCA). These multifaceted statistical methods scrutinized the collected data. Subsequently, a quality control model was devised to assess the stability of the sample quality. The results showed that the custom E-nose system could successfully distinguish between tobacco extracts with similar odors. After further training and the development of a quality control model for accepted tobacco extracts, it was possible to identify samples with normal and abnormal quality. To further validate our E-nose and extend its use within the tobacco industry, we collected and accurately classified the flavors of different tobacco leaf positions, with a remarkable accuracy rate of 0.9744. This finding facilitates the practical application of our E-nose system for the efficient identification of tobacco leaf positions.

An injectable composite hydrogel containing polydopamine-coated curcumin nanoparticles and indoximod for the enhanced combinational chemo-photothermal-immunotherapy of breast tumors.

The complexity and compensatory evolution of tumors weaken the effectiveness of single antitumor therapies. Therefore, multimodal combination therapies hold great promise in defeating tumors. Herein, we constructed a multi-level regulatory co-delivery system based on chemotherapy, phototherapy, and immunotherapy. Briefly, curcumin (Cur) was prepared as nanoparticles and coated with polydopamine (PDA) to form PCur-NPs, which along with an immune checkpoint inhibitor (indoximod, IND) were then loaded into a thermosensitive Pluronic F127 (F127) hydrogel to form a multifunctional nanocomposite hydrogel (PCur/IND@Gel). The in situ-formed hydrogel exhibited excellent photothermal conversion efficiency and sustained drug release behavior both in vitro and in vivo. In addition, PCur-NPs showed enhanced cellular uptake and cytotoxicity under NIR laser irradiation and induced potent immunogenic cell death (ICD). After intratumoral injection of PCur/IND@Gel, significant apoptosis in 4T1 tumors was induced, dendritic cells in lymph nodes were highly activated, potent CD8+ and CD4+ antitumor immune responses were elicited and regulative T cells in tumors were significantly reduced, which notably inhibited the tumor growth and prolonged the survive time of 4T1 tumor-bearing mice. Therefore, this injectable nanocomposite hydrogel is a promising drug co-delivery platform for chemo-photothermal-immunotherapy of breast tumors.

An RdDM-independent function of Pol V transcripts in gene regulation and plant defence.

RNA polymerase V (Pol V) and Pol IV are known to be specialized for RNA-directed DNA methylation (RdDM). Here we report that Pol V, but not Pol IV, regulates hundreds of genes including jasmonic acid-responsive genes and confers plant defence to Botrytis cinerea and Spodoptera exigua. About half of the Pol V-regulated genes are associated with Pol V transcripts (PVTs). We thus hypothesized that some PVTs could regulate gene expression in an RdDM-independent manner. To test this hypothesis, we studied three PVTs, PVT-ERF5a/b and PVT-ERF6, as models. PVT-ERF5a/b and PVT-ERF6 are transcribed from the upstream regions of ERF5 and ERF6 and positively regulate their transcription, thereby regulating plant defence. Such regulation involves PVT-dependent H3K4me3 deposition and requires the DRD1-DMS3-RDM1 complex that mediates Pol V recruitment to the target loci. These findings highlight an unprecedented role for PVTs in regulating gene transcription, apart from serving as scaffold RNAs to direct DNA methylation.

Association between different composite dietary antioxidant indexes and constipation in American male adults: a cross-sectional study.

Background: Oxidative stress is acknowledged as a pivotal factor in the intricate pathophysiological processes and pathogenesis of constipation. Modifying dietary patterns can elevate in vivo antioxidant biomarker levels, consequently mitigating oxidative stress. The Composite Dietary Antioxidant Index (CDAI) provides a dependable scoring mechanism for quantifying the potential antioxidant capacity of diets. The association between CDAI levels and the risk of constipation remains uncertain. Purpose: To investigate the potential correlation between CDAI and constipation, aiming to improve constipation management through dietary guidance. Methods: A total of 11,165 adults aged ≥20 years, drawn from the 2005-2010 National Health and Nutrition Examination Survey, were enrolled in this cross-sectional study. We evaluated the correlation between CDAI levels and the risk of constipation through three weighted logistic regression models. Restricted cubic spline (RCS) analysis was employed to assess nonlinear trends, and stratified analyses were conducted. Results: After adjusting for all confounding variables, the findings revealed an association between CDAI and constipation [OR = 0.937; 95% CI (0.892, 0.984), p = 0.012]. Moreover, individuals in the highest quartile of CDAI demonstrated a 40.1% lower likelihood of experiencing constipation compared to those in the lowest quartile [OR = 0.599; 95% CI (0.382, 0.939), p = 0.027]. The RCS analysis indicated a linear relationship between CDAI and constipation (P-non-linear =0.1016). Subgroup analysis by gender revealed a negative correlation in the male population [OR = 0.871; 95% CI (0.801, 0.947), p = 0.002], with men in the highest CDAI quartile exhibiting a 59.8% lower likelihood of experiencing constipation compared to those in the lowest quartile [OR = 0.402; 95% CI (0.206, 0.787), p = 0.010]. Furthermore, alterations in selenium [OR = 0.997; 95% CI (0.995, 1.000), p = 0.039] per milligram were independently linked to constipation. In a gender subgroup analysis of a single antioxidant, changes per milligram of vitamin E [OR = 0.904; 95% CI (0.838 to 0.975), p = 0.011] among males were independently associated with constipation. Conclusion: The fully adjusted model showed a correlation between CDAI and constipation and a significant correlation in quartiles. Meanwhile, subgroup analysis by gender showed that CDAI was negatively associated with constipation in the male population. Moreover, the findings of this study imply that investigations into antioxidant diets should be contextualized within dietary patterns.

DeepRisk: A deep learning approach for genome-wide assessment of common disease risk.

The potential for being able to identify individuals at high disease risk solely based on genotype data has garnered significant interest. Although widely applied, traditional polygenic risk scoring methods fall short, as they are built on additive models that fail to capture the intricate associations among single nucleotide polymorphisms (SNPs). This presents a limitation, as genetic diseases often arise from complex interactions between multiple SNPs. To address this challenge, we developed DeepRisk, a biological knowledge-driven deep learning method for modeling these complex, nonlinear associations among SNPs, to provide a more effective method for scoring the risk of common diseases with genome-wide genotype data. Evaluations demonstrated that DeepRisk outperforms existing PRS-based methods in identifying individuals at high risk for four common diseases: Alzheimer's disease, inflammatory bowel disease, type 2 diabetes, and breast cancer.

A CT-based radiomics tumor quality and quantity model to predict early recurrence after radical surgery for colorectal liver metastases.

PURPOSE: This study aimed to develop a tumor radiomics quality and quantity model (RQQM) based on preoperative enhanced CT to predict early recurrence after radical surgery for colorectal liver metastases (CRLM). METHODS: A retrospective analysis was conducted on 282 cases from 3 centers. Clinical risk factors were examined using univariate and multivariate logistic regression (LR) to construct the clinical model. Radiomics features were extracted using the least absolute shrinkage and selection operator (LASSO) for dimensionality reduction. The LR learning algorithm was employed to construct the radiomics model, RQQM (radiomics-TBS), combined model (radiomics-clinical), clinical risk score (CRS) model and tumor burden score (TBS) model. Inter-model comparisons were made using area under the curve (AUC), decision curve analysis (DCA) and calibration curve. Log-rank tests assessed differences in disease-free survival (DFS) and overall survival (OS). RESULTS: Clinical features screening identified CRS, KRAS/NRAS/BRAF and liver lobe distribution as risk factors. Radiomics model, RQQM, combined model demonstrated higher AUC values compared to CRS and TBS model in training, internal and external validation cohorts (Delong-test P < 0.05). RQQM outperformed the radiomics model, but was slightly inferior to the combined model. Survival curves revealed statistically significant differences in 1-year DFS and 3-year OS for the RQQM (P < 0.001). CONCLUSIONS: RQQM integrates both "quality" (radiomics) and "quantity" (TBS). The radiomics model is superior to the TBS model and has a greater impact on patient prognosis. In the absence of clinical data, RQQM, relying solely on imaging data, shows an advantage in predicting early recurrence after radical surgery for CRLM.

Effects of TET2-mediated methylation reconstruction on A2058 melanoma cell sensitivity to matrix stiffness in a 3D culture system.

Matrix stiffness is a crucial factor in the tumor microenvironment, impacting tumor progression and development. TET2 is vital for epigenetic regulation in melanoma and is significantly reduced in advanced melanomas compared with nevi and thin melanomas. However, it is unclear how TET2 mediates the effect of matrix stiffness on melanoma cells. This study utilized A2058 cell lines and prepared different stiffness collagen hydrogels to evaluate TET2 overexpression (TET2OE) and mutant (TET2M) melanoma cells' activity, proliferation, and invasion. A2058 melanoma cells' viability and invasion decreased with increased matrix stiffness, with TET2OE cells experiencing a more significant impact than TET2M cells. Methylation analysis revealed that TET2 determines gene methylation levels, influencing cell-ECM interactions. Transcriptome analysis confirmed that TET2 promotes matrix stiffness's effect on melanoma cell fate. This research provides promising directions and opportunities for melanoma treatment.

White matter structure and derived network properties are used to predict the progression from mild cognitive impairment of older adults to Alzheimer's disease.

OBJECTIVE: To identify white matter fiber injury and network changes that may lead to mild cognitive impairment (MCI) progression, then a joint model was constructed based on neuropsychological scales to predict high-risk individuals for Alzheimer's disease (AD) progression among older adults with MCI. METHODS: A total of 173 MCI patients were included from the Alzheimer's Disease Neuroimaging Initiative(ADNI) database and randomly divided into training and testing cohorts. Forty-five progressed to AD during a 4-year follow-up period. Diffusion tensor imaging (DTI) techniques extracted relevant DTI quantitative features for each patient. In addition, brain networks were constructed based on white matter fiber bundles to extract network property features. Ensemble dimensionality reduction was applied to reduce both DTI quantitative features and network features from the training cohort, and machine learning algorithms were added to construct white matter signature. In addition, 52 patients from the National Alzheimer's Coordinating Center (NACC) database were used for external validation of white matter signature. A joint model was subsequently generated by combining with scale scores, and its performance was evaluated using data from the testing cohort. RESULTS: Based on multivariate logistic regression, clinical dementia rating and Alzheimer's disease assessment scales (CDRS and ADAS, respectively) were selected as independent predictive factors. A joint model was constructed in combination with the white matter signature. The AUC, sensitivity, and specificity in the training cohort were 0.938, 0.937, and 0.91, respectively, and the AUC, sensitivity, and specificity in the test cohort were 0.905, 0.923, and 0.872, respectively. The Delong test showed a statistically significant difference between the joint model and CDRS or ADAS scores (P < 0.05), yet no significant difference between the joint model and the white matter signature (P = 0.341). CONCLUSION: The present results demonstrate that a joint model combining neuropsychological scales can be constructed by using machine learning and DTI technology to identify MCI patients who are at high-risk of progressing to AD.

Plant-inspired visible-light-driven bioenergetic hydrogels for chronic wound healing.

Chronic bioenergetic imbalances and inflammation caused by hyperglycemia are obstacles that delay diabetic wound healing. However, it is difficult to directly deliver energy and metabolites to regulate intracellular energy metabolism using biomaterials. Herein, we propose a light-driven bioenergetic and oxygen-releasing hydrogel (PTKM@HG) that integrates the thylakoid membrane-encapsulated polyphenol nanoparticles (PTKM NPs) to regulate the energy metabolism and inflammatory response in diabetic wounds. Upon red light irradiation, the PTKM NPs exhibited oxygen generation and H2O2 deletion capacity through a photosynthetic effect to restore hypoxia-induced mitochondrial dysfunction. Meanwhile, the PTKM NPs could produce exogenous ATP and NADPH to enhance mitochondrial function and facilitate cellular anabolism by regulating the leucine-activated mTOR signaling pathway. Furthermore, the PTKM NPs inherited antioxidative and anti-inflammatory ability from polyphenol. Finally, the red light irradiated PTKM@HG hydrogel augmented the survival and migration of cells keratinocytes, and then accelerated angiogenesis and re-epithelialization of diabetic wounds. In short, this study provides possibilities for effectively treating diseases by delivering key metabolites and energy based on such a light-driven bioenergetic hydrogel.