NIR-activatable nitric oxide generator based on nanoparticles loaded small-molecule photosensitizers for synergetic photodynamic/gas therapy.

BACKGROUND: Therapeutic approaches that combine conventional photodynamic therapy (PDT) with gas therapy (GT) to sensitize PDT are an attractive strategy, but the molecular structure design of the complex lacks effective guiding strategies. RESULTS: Herein, we have developed a nanoplatforms Cy-NMNO@SiO2 based on mesoporous silica materials loaded NIR-activatable small-molecule fluorescent probe Cy-NMNO for the synergistic treatment of photodynamic therapy/gas therapy (PDT/GT) in antibacterial and skin cancer. The theoretical calculation results showed that the low dissociation of N-NO in Cy-NMNO enabled it to dissociate effectively under NIR light irradiation, which is conducive to produce Cy and NO. Cy showed better 1O2 generation performance than Cy-NMNO. The cytotoxicity of Cy-NMNO obtained via the synergistic effect of GT and PDT synergistically enhances the effect of photodynamic therapy, thus achieving more effective tumor treatment and sterilization than conventional PDT. Moreover, the nanoplatforms Cy-NMNO@SiO2 realized efficient drug loading and drug delivery. CONCLUSIONS: This work not only offers a promising approach for PDT-GT synergistic drug delivery system, but also provides a valuable reference for the design of its drug molecules.

Development and application of diffusive gradients in thin-films for in-situ monitoring of 6PPD-Quinone in urban waters.

The occurrence and risk of N-(1,3-dimethylbutyl)-N'-phenyl-p-phenylenediamine-quinone (6PPD-Q), derived from the oxidation of the tire antidegradant 6PPD, has raised significant concern since it was found to cause acute mortality in coho salmon when exposed to urban runoff. Given the short half-life period and low solubility of 6PPD-Q, reliable in situ measurement techniques are required to accurately understand its occurrence and behaviour in aquatic environments. Here, using the diffusive gradients in thin-films (DGT) method with HLB as a binding agent, we developed a new methodology to measure 6PPD-Q in urban waters. 6PPD-Q was rapidly and strongly adsorbed on the HLB-binding gel and was efficiently extracted using organic solvents. The HLB-DGT accumulated 6PPD-Q linearly for >7 d and its performance was not significantly affected by pH (6.5-8.5), ionic strength (0.0001-0.5 M) or dissolved organic matter (0-20 mg L-1). Field evaluation of the DGT method demonstrated its effectiveness in urban runoff, detecting 6PPD-Q levels of 15.8-39.5 ng L-1 in rivers. In snowmelt, DGT detected 6PPD-Q levels of 210 ng L-1 which is two times higher than the value obtained by grab sampling. 6PPD-Q levels were much higher in snowmelt than those in rivers. This indicates that snowfall constitutes an important transport pathway for 6PPD-Q and that DGT effectively captured the fraction continuously released from dust particles in the snow samples. 6PPD-Q posed a substantial risk to migratory fish in urban waters, and its release from tire wear particles requires further investigation. This study is the first to develop a DGT-based method for 6PPD-Q determination in urban waters, and the method can ensure an accurate measurement of the release of 6PPD-Q to the environment, particularly in rainfall or snowmelt, important pathways for its entry into the aquatic environment.

The correlation between patients with type 2 diabetes mellitus and chronic microvascular complications during the glucose peak time.

INTRODUCTION: To assess the Type 2 Diabetes Mellitus (T2DM) patients in association with Chronic Microvascular Complications at Glucose Peak Time and the association among chronic microvascular complications in T2DM patients and the glucose peak period in the typical steamed bread meal test. METHODS: Overall 1095 T2DM patients were classified as three groups: (1) Group G1: glucose peak time ≤ 1 h (n = 84), Group G2: 1 h < glucose peak time ≤ 2 h (n = 648) and Group G3: glucose peak time > 2 h (n = 363). The clinical characteristics, insulin characteristics and glucose peak time and chronic microvascular complications markers of patients in each group was analyzed and compared. Statistical analyses were performed using SPSS 23.0, employing chi-square tests, Kruskal-Wallis tests, one-way ANOVA, and binary logistic regression analysis, with significance set at P < 0.05. RESULTS: Age, length of disease, glycated hemoglobin (HbA1c), urine albumin-creatinine ratio (UACR), and the number of patients with diabetic retinopathy (DR) increased (all P < 0.05) in those with postponed glucose peak time, while insulinogenic indexes, the AUC for C-p (AUCC-p), fasting, and 120-min C-peptide (C-p) decreased (all P < 0.05). Only age was connected to patients with diabetic kidney disease (DKD) independently in binary logistic regression analysis, although delayed glucose peak time was related to the presence of patients with DR. (all P < 0.05). CONCLUSION: Delayed glucose peak time contributed to DR. Attention should be paid to condition of chronic microvascular complications in T2DM patients with a postponed peak glucose timing.

Multi-omics analysis reveals the enhancing effects of Glycyrrhiza polysaccharides on the respiratory health of broilers.

This study investigated the impact of Glycyrrhiza polysaccharides (GPS) on the respiratory health of broilers. Specifically, 240 one-day-old male Arbor Acres (AA) broilers were randomly assigned to two groups: basal diet (CON) and GPS (supplemented with 150 mg/kg of Glycyrrhiza polysaccharides). When compared with the CON group, the GPS group significantly increased the broiler average daily gain, serum immunoglobulin A, immunoglobulin M, immunoglobulin G, antioxidant capacity, superoxide dismutase (SOD), glutathione peroxidase (GSH-Px), and tracheal messenger RNA (mRNA) expression levels of SOD1, SOD2, and GSH-Px. The GPS group also had a reduced feed conversion ratio, reduced lung IL-1ß and IL-6 levels, and upregulated tracheal mRNA expression of Occludin, Claudin1, and Mucin-2. Additionally, the GPS group had alterations in lung microbial diversity and composition. Transcriptomic and metabolomic analyses revealed the activation of the T cell receptor (TCR) signaling pathway and linoleic acid metabolic pathway in the GPS group. Correlation analysis demonstrated significant associations between differential bacteria, genes, serum metabolites, and phenotypic indicators. In conclusion, Glycyrrhiza polysaccharide supplementation positively influenced the respiratory health of broilers by modulating the lung microbiota, activating the TCR signaling pathway, and affecting the linoleic acid metabolism pathway.

Organic matter excreted by the protozoan Tetrahymena thermophila and its effects on the bioaccumulation of nanoparticles.

Although organic matter (exudate) excreted by aquatic organisms is an important component of dissolved organic matter (DOM) in the natural environment, its potential effects on the bioaccumulation of nanoparticles (NPs) remain unclear. In the present study, we examined the effects of the exudates from the protozoan Tetrahymena thermophila on the bioaccumulation (including uptake and cell surface adsorption) of iron oxide (Fe2O3, polyacrylate coated) and silica (SiO2) NPs in T. thermophila. The exudates were mostly (93.6 %, in carbon) composed of < 1-kDa molecules (e.g., lipids). When the exudates were mixed with the NPs, significant adsorption occurred on SiO2 NPs but not on Fe2O3 NPs. Independent of their adsorption by the NPs, the exudates significantly inhibited the bioaccumulation of both SiO2 NPs and Fe2O3 NPs by T. thermophila. This inhibitory effect was shown to be mainly due to their inhibition of NP adsorption on the cell surface. By contrast, the exudates had negligible effects on the uptake of either NP type, most likely due to their low molecular weight. Since DOM in the aquatic environment is dominated by molecules < 1 kDa, the potential effects of low-molecular-weight DOM, such as exudates from aquatic organisms, on the bioaccumulation of NPs merits greater attention. ENVIRONMENTAL IMPLICATION: Nanoparticles (NPs) are hazardous materials widespread in the natural environment. Previous studies showed that dissolved organic matter (DOM) in aquatic environments determine the environmental behavior and ecological effects of NPs. Although organic matter (exudate) excreted by aquatic organisms is an important component of DOM, its potential effects on the bioaccumulation of NPs remain unclear. In the present study, we found that the exudates inhibited the cell-surface adsorption of NPs but had no effects on NP uptake, as different from the well-known effects of DOM on NP bioaccumulation. This finding merits attention during evaluations of the environmental risks of NPs.

Chromosome doubling increases PECTIN METHYLESTERASE 2 expression, biomass, and osmotic stress tolerance in kiwifruit.

Chromosome doubling-induced polyploidization is a popular tool for crop breeding. Polyploidy crops commonly have multiple advantages, including increased biomass and stress tolerance. However, little is known about the genes responsible for these advantages. We found kiwifruit (Actinidia chinensis cv. Hongyang) PECTIN METHYLESTERASE 2 (AcPME2)is substantially upregulated in artificially created tetraploid plants that show increased biomass and enhanced tolerance to osmotic stress. Overexpression (OE) of AcPME2 led to increased biomass and enhanced stress tolerance in Arabidopsis (Arabidopsis thaliana), tomato (Solanum lycopersicum), and kiwifruit. Upon short-term osmotic stress treatment, AcPME2-OE plants showed higher levels of demethylesterified pectins and more Ca2+ accumulation in the cell wall than Col-0 plants, which led to increased cell wall stiffness. The stress-induced plasmolysis assays indicated that AcPME2 dynamically mediated the cell wall stiffness in response to osmotic stress, which is dependent on Ca2+ accumulation. Transcriptomic analysis discovered that dozens of stress-responsive genes were significantly upregulated in the AcPME2-OE plants under osmotic stress. Besides, AcPME2-mediated cell wall reinforcement prevented cell wall collapse and deformation under osmotic stress. Our results revealed a single gene contributes to two advantages of polyploidization (increased biomass and osmotic stress tolerance) and that AcPME2 dynamically regulates cell wall stiffness in response to osmotic stress.

Mapping cellular interactions from spatially resolved transcriptomics data.

Cell-cell communication (CCC) is essential to how life forms and functions. However, accurate, high-throughput mapping of how expression of all genes in one cell affects expression of all genes in another cell is made possible only recently through the introduction of spatially resolved transcriptomics (SRT) technologies, especially those that achieve single-cell resolution. Nevertheless, substantial challenges remain to analyze such highly complex data properly. Here, we introduce a multiple-instance learning framework, Spacia, to detect CCCs from data generated by SRTs, by uniquely exploiting their spatial modality. We highlight Spacia's power to overcome fundamental limitations of popular analytical tools for inference of CCCs, including losing single-cell resolution, limited to ligand-receptor relationships and prior interaction databases, high false positive rates and, most importantly, the lack of consideration of the multiple-sender-to-one-receiver paradigm. We evaluated the fitness of Spacia for three commercialized single-cell resolution SRT technologies: MERSCOPE/Vizgen, CosMx/NanoString and Xenium/10x. Overall, Spacia represents a notable step in advancing quantitative theories of cellular communications.

Prediction of non-muscle invasive bladder cancer recurrence using deep learning of pathology image.

We aimed to build a deep learning-based pathomics model to predict the early recurrence of non-muscle-infiltrating bladder cancer (NMIBC) in this work. A total of 147 patients from Xuzhou Central Hospital were enrolled as the training cohort, and 63 patients from Suqian Affiliated Hospital of Xuzhou Medical University were enrolled as the test cohort. Based on two consecutive phases of patch level prediction and WSI-level predictione, we built a pathomics model, with the initial model developed in the training cohort and subjected to transfer learning, and then the test cohort was validated for generalization. The features extracted from the visualization model were used for model interpretation. After migration learning, the area under the receiver operating characteristic curve for the deep learning-based pathomics model in the test cohort was 0.860 (95% CI 0.752-0.969), with good agreement between the migration training cohort and the test cohort in predicting recurrence, and the predicted values matched well with the observed values, with p values of 0.667766 and 0.140233 for the Hosmer-Lemeshow test, respectively. The good clinical application was observed using a decision curve analysis method. We developed a deep learning-based pathomics model showed promising performance in predicting recurrence within one year in NMIBC patients. Including 10 state prediction NMIBC recurrence group pathology features be visualized, which may be used to facilitate personalized management of NMIBC patients to avoid ineffective or unnecessary treatment for the benefit of patients.

A Nanofluorescent Probe for Evaluating the Fluctuation of Aminopeptidase N in Nonalcoholic Fatty Liver Disease and Hepatic Fibrosis.

Aminopeptidase N (APN/CD13) is a widely expressed transmembrane ectoenzyme that is crucial for maintaining normal physiological activities. It exhibits abnormal activity closely associated with hepatic fibrosis and nonalcoholic fatty liver disease (NAFLD). Therefore, there is a high demand for noninvasive detection of aminopeptidase N (APN) in the diagnosis and research of related diseases. Here, we developed a small molecule fluorescent probe, Hcy-APN, which is a fluorescent probe with high sensitivity and selectivity for the detection of APN. Furthermore, we synthesized the fluorescent nanoprobe Hcy-APN@MSN by self-assembling Hcy-APN and mesoporous silica nanoparticles in solution using a combination of molecular probe design and nanofunctionalization strategies. The detection limit of this probe was 1.5 ng/mL. Hcy-APN@MSN exhibits more stable spectral characteristics compared to Hcy-APN and is suitable for detecting APN activity in live cells and mice. Hcy-APN@MSN was utilized for in vivo and intracellular imaging of NAFLD and hepatic fibrosis at different stages, as well as for a systematic assessment of APN levels in the liver. The results confirm an elevation in the expression levels of APN in NAFLD and hepatic fibrosis models. Furthermore, we investigated the inhibitory effect of the APN inhibitor bestatin in nonalcoholic fatty liver and hepatic fibrosis disease models, confirming its regulatory effect on APN levels in cells and in vivo in both disease models. Therefore, this study may offer diagnostic possibilities for detecting NAFLD and hepatic fibrosis.

Co-delivery of Siape1 and Melatonin by 125I-loaded PSMA-targeted Nanoparticles for the Treatment of Prostate Cancer.

BACKGROUND: Both apurinic/apyrimidinic endodeoxyribonuclease 1 (APE1) inhibition and melatonin suppress prostate cancer (PCa) growth. OBJECTIVE: This study evaluated the therapeutic efficiency of self-assembled and prostate-specific membrane antigen (PSMA)-targeted nanocarrier loading 125I radioactive particles and encapsulating siRNA targeting APE1 (siAPE1) and melatonin for PCa. METHODS: The linear polyarginine R12 polypeptide was prepared using Fmoc-Arg-Pbf-OH. The PSMA-targeted polymer was synthesized by conjugating azide-modified R12 peptide to PSMA monoclonal antibody (mAb). Before experiments, the PSMA-R12 nanocarrier was installed with melatonin and siAPE1, which were subsequently labeled by 125I radioactive particles. In vitro biocompatibility and cytotoxicity of nanocomposites were examined in LNCaP cells and in vivo biodistribution and pharmacokinetics were determined using PCa tumor-bearing mice. RESULTS: PSMA-R12 nanocarrier was ~120 nm in size and was increased to ~150 nm by melatonin encapsulation. PSMA-R12 nanoparticles had efficient loading capacities of siAPE1, melatonin, and 125I particles. The co-delivery of melatonin and siAPE1 by PSMA-R12-125I showed synergistic effects on suppressing LNCaP cell proliferation and Bcl-2 expression and promoting cell apoptosis and caspase-3 expression. Pharmacokinetics analysis showed that Mel@PSMA-R12-125I particles had high uptake activity in the liver, spleen, kidney, intestine, and tumor, and were accumulated in the tumor sites within the first 8 h p.i., but was rapidly cleared from all the tested organs at 24 h p.i. Administration of nanoparticles to PCa tumors in vivo showed that Mel@PSMA-R12- 125I/siAPE1 had high efficiency in suppressing PCa tumor growth. CONCLUSION: The PSMA-targeted nanocarrier encapsulating siAPE1 and melatonin is a promising therapeutic strategy for PCa and can provide a theoretical basis for patent applications.

Assessing next-generation sequencing-based computational methods for predicting transcriptional regulators with query gene sets.

This article provides an in-depth review of computational methods for predicting transcriptional regulators (TRs) with query gene sets. Identification of TRs is of utmost importance in many biological applications, including but not limited to elucidating biological development mechanisms, identifying key disease genes, and predicting therapeutic targets. Various computational methods based on next-generation sequencing (NGS) data have been developed in the past decade, yet no systematic evaluation of NGS-based methods has been offered. We classified these methods into two categories based on shared characteristics, namely library-based and region-based methods. We further conducted benchmark studies to evaluate the accuracy, sensitivity, coverage, and usability of NGS-based methods with molecular experimental datasets. Results show that BART, ChIP-Atlas, and Lisa have relatively better performance. Besides, we point out the limitations of NGS-based methods and explore potential directions for further improvement.

AI-based digital pathology provides newer insights into lifestyle intervention-induced fibrosis regression in MASLD: An exploratory study.

BACKGROUND AND AIMS: Lifestyle intervention is the mainstay of therapy for metabolic dysfunction-associated steatohepatitis (MASH), and liver fibrosis is a key consequence of MASH that predicts adverse clinical outcomes. The placebo response plays a pivotal role in the outcome of MASH clinical trials. Second harmonic generation/two-photon excitation fluorescence (SHG/TPEF) microscopy with artificial intelligence analyses can provide an automated quantitative assessment of fibrosis features on a continuous scale called qFibrosis. In this exploratory study, we used this approach to gain insight into the effect of lifestyle intervention-induced fibrosis changes in MASH. METHODS: We examined unstained sections from paired liver biopsies (baseline and end-of-intervention) from MASH individuals who had received either routine lifestyle intervention (RLI) (n = 35) or strengthened lifestyle intervention (SLI) (n = 17). We quantified liver fibrosis with qFibrosis in the portal tract, periportal, transitional, pericentral, and central vein regions. RESULTS: About 20% (7/35) and 65% (11/17) of patients had fibrosis regression in the RLI and SLI groups, respectively. Liver fibrosis tended towards no change or regression after each lifestyle intervention, and this phenomenon was more prominent in the SLI group. SLI-induced liver fibrosis regression was concentrated in the periportal region. CONCLUSION: Using digital pathology, we could detect a more pronounced fibrosis regression with SLI, mainly in the periportal region. With changes in fibrosis area in the periportal region, we could differentiate RLI and SLI patients in the placebo group in the MASH clinical trial. Digital pathology provides new insight into lifestyle-induced fibrosis regression and placebo responses, which is not captured by conventional histological staging.

Unraveling the molecular landscape of breast muscle development in domestic Yuzhong pigeons and European meat pigeon: Insights from Iso-seq and RNA-seq analysis.

The mechanisms governing gene regulation in domestic Yuzhong pigeon breast muscle development remain largely elusive. Here, we conducted a comparative analysis using Iso-seq and RNA-seq data from domestic Yuzhong pigeons and European meat pigeons to uncover signaling pathways and genes involved in breast muscle development. The Iso-seq data from domestic Yuzhong pigeons yielded 131,377,075 subreads, resulting in 16,587 non-redundant high-quality full-length transcripts post-correction. Furthermore, utilizing pfam, CPC, PLEK, and CPAT, we predicted 5575, 4973, 2333, and 4336 lncRNAs, respectively. Notably, several genes potentially implicated in breast muscle development were identified, including tropomyosin beta chain, myosin regulatory light chain 2, and myosin binding protein C. KEGG enrichment analysis revealed critical signaling pathways in breast muscle development, spanning carbon metabolism, biosynthesis of amino acids, glycolysis/gluconeogenesis, estrogen signaling, PI3K-AKT signaling, protein processing in the endoplasmic reticulum, oxidative phosphorylation, pentose phosphate pathway, fructose and mannose metabolism, and tight junctions. These findings offer insights into the biological processes driving breast muscle development in domestic Yuzhong pigeon, contributing to our understanding of this complex phenomenon.

Rhoptry proteins affect the placental barrier in the context of Toxoplasma gondii infection: Signaling pathways and functions.

Toxoplasma gondii is an opportunistic and pathogenic obligate intracellular parasitic protozoan that is widespread worldwide and can infect most warm-blooded animals, seriously endangering human health and affecting livestock production. Toxoplasmosis caused by T. gondii infection has different clinical manifestations, which are mainly determined by the virulence of T. gondii and host differences. Among the manifestations of this condition, abortion, stillbirth, and fetal malformation can occur if a woman is infected with T. gondii in early pregnancy. Here, we discuss how the T. gondii rhoptry protein affects host pregnancy outcomes and speculate on the related signaling pathways involved. The effects of rhoptry proteins of T. gondii on the placental barrier are complex. Rhoptry proteins not only regulate interferon-regulated genes (IRGs) to ensure the survival of parasites in activated cells but also promote the spread of worms in tissues and the invasive ability of the parasites. The functions of these rhoptry proteins and the associated signaling pathways highlight relevant mechanisms by which Toxoplasma crosses the placental barrier and influences fetal development and will guide future studies to uncover the complexity of the host-pathogen interactions.

BIT: Bayesian Identification of Transcriptional Regulators.

BIT is a novel Bayesian hierarchical model capable of predicting transcriptional regulators (TRs) from the input of user-provided epigenomic regions. TRs are critical molecules in transcriptional regulation. Many diseases and cancers are linked to the dysfunction of TRs. Knowing TRs in certain biological process can help find new biomarkers or therapeutic targets. Thus, BIT formulates a novel Bayesian hierarchical model with the Pólya-gamma data augmentation strategy. Based on collected ChIP-seq datasets, BIT can identify TRs responsible for the genome-wide binding pattern within the user-provided epigenomic regions. BIT has been validated by using a simulation study and three applications.

A-to-I edited miR-154-p13-5p inhibited cell proliferation and migration and induced apoptosis by targeting LIX1L in the bladder cancer.

With the advancement of RNA sequencing technology, there has been a drive to uncover and elucidate the pivotal role of A-to-I RNA editing events in tumorigenesis. However, A-to-I miRNA editing events have been clearly identified in bladder cancer, the molecular mechanisms underlying their role in bladder cancer remain unclear. In our investigation, we observed a notable under-expression of edited miR-154-p13-5p in bladder cancer (BC) tissues, in contrast to normal counterparts. Remarkably, heightened expression levels of edited miR-154-p13-5p correlated with improved survival outcomes. To assess the impact of modified miR-154-p13-5p, we conducted a string of cell phenotype assays through transfection of the corresponding miRNAs or siRNAs. The results unequivocally demonstrate that edited miR-154-p13-5p exerts a substantial inhibitory influence on proliferation, migration, and induces apoptosis by specifically targeting LIX1L in bladder cancer. Moreover, we observed that the editing of miR-154-p13-5p or LIX1L-siRNAs inhibits the expression of LIX1L, thereby suppressing EMT-related proteins and cell cycle protein CDK2. Simultaneously, an upregulation in the expression levels of Caspase-3 and Cleaved Caspase-3 were also detected. Our research findings suggest that the upregulation of edited miR-154-p13-5p could potentially enhance the prognosis of bladder cancer, thereby presenting molecular biology-based therapeutic strategies.

Predictive value of TCCD and regional cerebral oxygen saturation for detecting early postoperative brain injury.

OBJECTIVE: This study aims to analyze the risk factors for early postoperative brain injury in patients undergoing cardiovascular surgery and explore the predictive value of transcranial color Doppler (TCCD) and regional cerebral oxygen saturation (rSO2) for detecting early postoperative brain injury in cardiovascular surgery patients. METHODS: A total of 55 patients undergoing cardiovascular surgery with cardiopulmonary bypass in Changzhou No.2 The People's Hospital of Nanjing Medical University were included in this study. Neuron-specific enolase (NSE) concentration was measured 24 h after operation. Patients were divided into brain injury (NSE ≥ 16.3 ng/mL) and normal (0 < NSE < 16.3 ng/mL) groups according to the measured NSE concentration. The clinical outcomes between the two groups were compared, including decreased rSO2 and cerebral blood flow (as measured by TCCD) levels. The risk factors of early postoperative brain injury were analyzed by multivariate logistic regression analysis, and the significant variables were analyzed by receiver operating characteristic (ROC) analysis. RESULTS: A total of 50 patients were included in this study, with 20 patients in the brain injury group and 30 patients in the normal group. Cardiopulmonary bypass time (min) (107 ± 29 vs. 90 ± 28, P = 0.047) and aortic occlusion time (min) (111 (IQR 81-127) vs. 87 (IQR 72-116), P = 0.010) were significantly longer in the brain injury group than in the normal group. Patients in the brain injury group had greater decreased rSO2 (%) (27.0 ± 7.3 vs. 17.5 ± 6.1, P < 0.001) and cerebral blood flow (%) (44.9 (IQR 37.8-69.2) vs. 29.1 (IQR 12.0-48.2), P = 0.004) levels. Multivariate logistic regression analysis suggested that decreased rSO2 and cerebral blood flow levels, aortic occlusion time, and history of atrial fibrillation were independent risk factors for early postoperative brain injury (P < 0.05). ROC analysis reported that the best cutoff values for predicting early postoperative brain injury were 21.4% and 37.4% for decreased rSO2 and cerebral blood flow levels, respectively (P < 0.05). CONCLUSION: The decreased rSO2 and cerebral blood flow levels, aorta occlusion time, and history of atrial fibrillation were independent risk factors for early postoperative brain injury. TCCD and rSO2 could effectively monitor brain metabolism and cerebral blood flow and predict early postoperative brain injury.

Clinical characteristics and molecular mechanisms underlying bladder cancer in individuals with spinal cord injury: a systematic review.

BACKGROUND: Patients with spinal cord injury have a relatively high risk for bladder cancer and often complicated with bladder cancer in advanced stages, and the degree of aggressiveness of malignancy is high. Most of the literature is based on disease clinical features while, our study reviews the clinical characteristics and molecular mechanisms of spinal cord injury patients with bladder cancer, so that it might help clinicians better recognize and manage these patients. METHOD: We searched PubMed, Web of Science and Embase, using retrieval type like ("Neurogenic Lower Urinary Tract Dysfunction" OR "Spinal cord injury" OR "Spinal Cord Trauma") AND ("bladder cancer" OR "bladder neoplasm" OR "bladder carcinoma" OR "Urinary Bladder Neoplasms" OR "Bladder Tumor"). In Web of Science, the retrieval type was searched as "Topic", and in PubMed and Embase, as "All Field". The methodological quality of eligible studies and their risk of bias were assessed using the Newcastle-Ottawa scale. This article is registered in PROSPERO with the CBD number: CRD42024508514. RESULT: In WOS, we searched 219 related papers, in PubMed, 122 and in Embase, 363. Thus, a total of 254 articles were included after passing the screening, within a time range between 1960 and 2023. A comprehensive analysis of the data showed that the mortality and incidence rates of bladder cancer in spinal cord injury patients were higher than that of the general population, and the most frequent pathological type was squamous cell carcinoma. In parallel to long-term urinary tract infection and indwelling catheterization, the role of molecules such as NO, MiR 1949 and Rb 1. was found to be crucial pathogenetically. CONCLUSION: This review highlights the risk of bladder cancer in SCI patients, comprehensively addressing the clinical characteristics and related molecular mechanisms. However, given that there are few studies on the molecular mechanisms of bladder cancer in spinal cord injury, further research is needed to expand the understanding of the disease.

Depression and the Risk of Dementia and All-Cause Mortality Among Japanese Older Adults: A 9-Year Longitudinal Study From JAGES.

BACKGROUND: This study aims to investigate the association and dose-response relationship between depression, dementia, and all-cause mortality based on a national cohort study of older adults in Japan. METHODS: We conducted a longitudinal study of 44,546 participants ≥65 years from 2010-2019 Japanese Gerontological Evaluation Study. The Geriatric Depression Scale-15 was used to assess depressive symptoms and the long-term care insurance was used to assess dementia. Fine-Gray models and Cox proportional hazard models were used to explore the effect of depression severity on the incidence of dementia and all-cause mortality, respectively. Causal mediation analysis were used to explore the extent of association between dementia-mediated depression and all-cause mortality. RESULTS: We found that both minor and major depressive symptoms were associated with the increased cumulative incidence of dementia and all-cause mortality, especially major depressive symptoms (p < .001). The multivariable-adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for dementia were 1.25 (1.19-1.32) for minor depressive symptoms and 1.42 (1.30-1.54) for major depressive symptoms in comparison to non-depression; p for trend < .001. The multivariable-adjusted HRs and 95% CIs for all-cause mortality were 1.27 (1.21-1.33) for minor depressive symptoms and 1.51 (1.41-1.62) for major depressive symptoms in comparison to non-depression; p for trend < .001. Depression has a stronger impact on dementia and all-cause mortality among the younger group. In addition, dementia significantly mediated the association between depression and all-cause mortality. DISCUSSION: Interventions targeting major depression may be an effective strategy for preventing dementia and premature death.

Variable Selection in Bayesian Multiple Instance Regression using Shotgun Stochastic Search.

In multiple instance learning (MIL), a bag represents a sample that has a set of instances, each of which is described by a vector of explanatory variables, but the entire bag only has one label/response. Though many methods for MIL have been developed to date, few have paid attention to interpretability of models and results. The proposed Bayesian regression model stands on two levels of hierarchy, which transparently show how explanatory variables explain and instances contribute to bag responses. Moreover, two selection problems are simultaneously addressed; the instance selection to find out the instances in each bag responsible for the bag response, and the variable selection to search for the important covariates. To explore a joint discrete space of indicator variables created for selection of both explanatory variables and instances, the shotgun stochastic search algorithm is modified to fit in the MIL context. Also, the proposed model offers a natural and rigorous way to quantify uncertainty in coefficient estimation and outcome prediction, which many modern MIL applications call for. The simulation study shows the proposed regression model can select variables and instances with high performance (AUC greater than 0.86), thus predicting responses well. The proposed method is applied to the musk data for prediction of binding strengths (labels) between molecules (bags) with different conformations (instances) and target receptors. It outperforms all existing methods, and can identify variables relevant in modeling responses.