Signature Construction and Disulfidptosis-Related Molecular Cluster Identification for Better Prediction of Prognosis in Glioma.

Disulfidptosis is a newly discovered form of regulatory cell death. However, the identification of disulfidptosis-related molecular subtypes and potential biomarkers in gliomas and their prognostic predictive potential need to be further elucidated. RNA sequencing profiles and the relevant clinical data were obtained from the Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). Disulfidptosis-related clusters were identified by unsupervised clustering analysis. Immune cell infiltration analysis and drug sensitivity analysis were used to explore the differences between clusters. Gene set enrichment analysis (GSEA) of differential genes between clusters was performed to explore the potential biological functions and signaling. A disulfidptosis-related scoring system (DRSS) was constructed based on a combined COX and LASSO analysis. Mendelian randomization (MR) analyses were used to further explore the causal relationship between levels of genes in DRSS and an increased risk of glioma. A prognosis nomogram was constructed based on the DRSS and 3 clinical features (age, WHO stage, and IDH status). The accuracy and stability of the prognosis nomogram were also validated in different cohorts. We identified two clusters that exhibited different prognoses, drug sensitivity profiles, and tumor microenvironment infiltration profiles. The overall survival (OS) of Cluster2 was significantly better than Cluster1. Cluster1 had an overall greater infiltration of immune cells compared to Cluster2. However, the Monocytes, activated B cells had higher infiltration abundance in Cluster2. GSEA results showed significant enrichment of immune-related biological processes in Cluster1, while Cluster2 was more enriched for functions related to neurotransmission and regulation. PER3, RAB34, NKX3-2, GPX7, FRA10AC1, and TGIF1 were finally included to construct DRSS. DRSS was independently related to prognosis. There was a significant difference in overall survival between the low-risk score group and the high-risk score group. Among six genes in DRSS, GPX7 levels were demonstrated to have a causal relationship with an increased risk of glioma. GPX7 may become a more promising biomarker for gliomas. The prognosis nomogram constructed based on the DRSS and three clinical features has considerable potential for predicting the prognosis of patients with glioma. Free online software for implementing this nomogram was established:  https://yekun-zhuang.shinyapps.io/DynNomapp/ . Our study established a novel glioma classification based on the disulfidptosis-related molecular subtypes. We constructed the DRSS and the prognosis nomogram to accurately stratify the prognosis of glioma patients. GPX7 was identified as a more promising biomarker for glioma. We provide important insights into the treatment and prognosis of gliomas.

Identification of prognostic signatures in remnant gastric cancer through an interpretable risk model based on machine learning: a multicenter cohort study.

OBJECTIVE: The purpose of this study was to develop an individual survival prediction model based on multiple machine learning (ML) algorithms to predict survival probability for remnant gastric cancer (RGC). METHODS: Clinicopathologic data of 286 patients with RGC undergoing operation (radical resection and palliative resection) from a multi-institution database were enrolled and analyzed retrospectively. These individuals were split into training (80%) and test cohort (20%) by using random allocation. Nine commonly used ML methods were employed to construct survival prediction models. Algorithm performance was estimated by analyzing accuracy, precision, recall, F1-score, area under the receiver operating characteristic curve (AUC), confusion matrices, five-fold cross-validation, decision curve analysis (DCA), and calibration curve. The best model was selected through appropriate verification and validation and was suitably explained by the SHapley Additive exPlanations (SHAP) approach. RESULTS: Compared with the traditional methods, the RGC survival prediction models employing ML exhibited good performance. Except for the decision tree model, all other models performed well, with a mean ROC AUC above 0.7. The DCA findings suggest that the developed models have the potential to enhance clinical decision-making processes, thereby improving patient outcomes. The calibration curve reveals that all models except the decision tree model displayed commendable predictive performance. Through CatBoost-based modeling and SHAP analysis, the five-year survival probability is significantly influenced by several factors: the lymph node ratio (LNR), T stage, tumor size, resection margins, perineural invasion, and distant metastasis. CONCLUSIONS: This study established predictive models for survival probability at five years in RGC patients based on ML algorithms which showed high accuracy and applicative value.

Colorimetric sensor array for the rapid distinction and detection of various antibiotic-resistant psychrophilic bacteria in raw milk based-on machine learning.

In this study, a rapid, inexpensive, and accurate colorimetric sensor for detecting psychrophilic bacteria was designed, comprising gold (Au) nanoparticles (NPs) modified by d-amino acid (D-AA) as color-metric probes. Based on the aggregation of Au NPs induced by psychrophilic bacteria, a noticeable color shift occurred within 6 h. Depending on the various metabolic behaviors of bacteria to different D-AA, four primary psychrophilic bacteria in raw milk were successfully distinguished by learning the response patterns. Furthermore, the quantification of single bacteria and the practical application in milk samples could be realized. Notably, a rapid colorimetric method was constructed by combining Au/D-AA with antibiotics for the minimum inhibitory concentration of psychrophilic bacteria, which relied on differences in bacteria metabolic activity in response to diverse antibiotic treatments. Therefore, the method enables the rapid detection and susceptibility evaluation of psychrophilic bacteria, promoting clinical practicability and antibiotic management.

Combination of urinary biomarkers and machine-learning models provided a higher predictive accuracy to predict long-term treatment outcomes of patients with interstitial cystitis/bladder pain syndrome.

PURPOSE: To identify predictive factors for satisfactory treatment outcome of the patients with IC/BPS using urine biomarkers and machine-learning models. METHODS: The IC/BPS patients were prospectively enrolled and provide urine samples. The targeted analytes included inflammatory cytokines, neurotrophins, and oxidative stress biomarkers. The patients with overall subjective symptom improvement of ≥ 50% were considered to have satisfactory results. Binary logistic regression, receiver-operating characteristic (ROC) curve, machine-learning decision tree, and random forest models were used to analyze urinary biomarkers to predict satisfactory results. RESULTS: Altogether, 57.4% of the 291 IC/BPS patients obtained satisfactory results. The patients with satisfactory results had lower levels of baseline urinary inflammatory cytokines and oxidative biomarkers than patients without satisfying results, including interleukin-6, monocyte chemoattractant protein-1 (MCP-1), C-X-C motif chemokine 10 (CXCL10), oxidative stress biomarkers 8-hydroxy-2'-deoxyguanosine (8-OHDG), 8-isoprostane, and total antioxidant capacity (TAC). Logistic regression and multivariable analysis revealed that lower levels of urinary CXCL10, MCP-1, 8-OHDG, and 8-isoprostane were independent factors. The ROC curve revealed that MCP-1 level had best area under curve (AUC: 0.797). In machine-learning decision tree model, combination of urinary C-C motif chemokine 5, 8-isoprostane, TAC, MCP-1, and 8-OHDG could predict satisfactory results (accuracy: 0.81). The random forest model revealed that urinary 8-isoprostance, MCP-1, and 8-OHDG levels had the most important influence on accuracy. CONCLUSION: Machine learning decision tree model provided a higher accuracy for predicting treatment outcome of patients with IC/BPS than logistic regression, and levels of 8-isoprostance, MCP-1, and 8-OHDG had the most important influence on accuracy.

A point-of-care electrochemical biosensor for the rapid and sensitive detection of biomarkers in murine models with LPS-induced sepsis.

Sepsis is a life-threatening condition, which is irreversible if diagnosis and intervention are delayed. The response of the immune cells towards an infection triggers widespread inflammation through the production of cytokines, which may result in multiple organ dysfunction and eventual death. Conventional detection techniques fail to provide a rapid diagnosis because of their limited sensitivity and tedious protocol. This study proposes a point-of-care (POC) electrochemical biosensor that overcomes the limitations of current biosensing technologies in the clinical setting by its integration with electrokinetics, enhancing the sensitivity to picogram level compared with the nanogram limit of current diagnostic technologies. This biosensor promotes the use of a microelectrode strip to address the limitations of conventional photolithographic fabrication methods. Tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and microRNA-155 (miR-155) were monitored in a lipopolysaccharide (LPS)-induced septic mouse model. The optimum target hybridization time in a high conductivity medium was observed to be 60 s leading to the completion of the whole operation within 5 min compared with the 4-h detection time of the traditional enzyme-linked immunosorbent assay (ELISA). The limit of detection (LOD) was calculated to be 0.84, 0.18, and 0.0014 pg mL-1, respectively. This novel sensor may have potential for the early diagnosis of sepsis in the clinical setting.

Association between organophosphate flame retardant exposure and lipid metabolism: data from the 2013-2014 National Health and Nutrition Examination Survey.

Organophosphate flame retardants (OPFRs) are emerging environmental pollutants that can be detected in water, dust, and biological organisms. Certain OPFRs can disrupt lipid metabolism in animal models and cell lines. However, the effects of OPFRs on human lipid metabolism remain unclear. We included 1,580 participants (≥20 years) from the 2013-2014 National Health and Nutrition Examination Survey (NHANES) to explore the relationship between OPFR exposure and lipid metabolism biomarkers. After adjusting for confounding factors, results showed that one-unit increases in the log levels of diphenyl phosphate (DPhP) (regression coefficient = -5.755; S.E. = 2.289; p = 0.023) and log bis-(1-chloro-2-propyl) phosphate (BCPP) (regression coefficient = -4.637; S.E. = 2.019; p = 0.036) were negatively associated with the levels of total cholesterol (TC) in all participants. One-unit increases in the levels of DPhP (regression coefficient = -2.292; S.E. = 0.802; p = 0.012), log bis (1,3-dichloro-2-propyl) phosphate (BDCPP) (regression coefficient = -2.046; S.E. = 0.825; p = 0.026), and log bis-2-chloroethyl phosphate (BCEP) (regression coefficient = -2.604; S.E. = 0.704; p = 0.002) were negatively associated with the levels of high-density lipoprotein cholesterol (HDL-C). With increasing quartiles of urine BDCPP levels, the mean TC levels significantly decreased in all participants (p value for trend = 0.028), and quartile increases in the levels of DPhP (p value for trend = 0.01), BDCPP (p value for trend = 0.001), and BCEP (p value for trend<0.001) were negatively corelated with HDL-C, with approximately 5.9, 9.9, and 12.5% differences between the upper and lower quartiles. In conclusion, DPhP, BDCPP, and BCEP were negatively related to HDL-C concentration, whereas DPhP and BCPP levels were negatively associated with TC level. Thus, exposure to OPFRs may interfere with lipid metabolism.

Succession of microbiota and its influence on the dynamics of volatile compounds in the semi-artificial inoculation fermentation of mulberry wine.

To improve the delightful flavor of mulberry wine through semi-artificial inoculation fermentation with Saccharomyces cerevisiae, we studied the dynamics change of microbiota, along with the physicochemical properties and metabolite profiles and their interaction relationship during the fermentation process. The abundance of lactic acid bacteria (Weissella, Lactobacillus, Fructobacillus, and Pediococcus) increased significantly during fermentation, while yeasts gradually established dominance. The inter-kingdom network of the dominant genera analysis further identified the following as core microbiota: Alternaria, Botrytis, Kazachstania, Acremonium, Mycosphaerella, Pediococcus, Gardnerella, and Schizothecium. Additionally, pH, alcohol, and total acid were significantly affected by microbiota variation. Fourteen of all identified volatile compounds with key different aromas were screened using PCA, OPLS-DA, and rOAV. The network of interconnected core microbiota with key different aromas revealed that Kazachstania and Pediococcus had stronger correlations with 1-butanol, 3-methyl-, propanoic acid, and 2-methyl-ethyl ester.

Cerebrospinal fluid shunt surgery reduces the risk of developing dementia and Alzheimer's disease in patients with idiopathic normal pressure hydrocephalus: a nationwide population-based propensity-weighted cohort study.

BACKGROUND: Patients with idiopathic normal-pressure hydrocephalus (iNPH) are predisposed to developing dementing disorders. Cerebrospinal fluid (CSF) shunt implantation is a treatment used to improve the motor and cognitive disabilities of these patients; however, its effect on the risk of developing dementing disorders remains unclear. We conducted a population-based propensity-weighted cohort study to investigate whether CSF shunt surgery may reduce the risk of subsequently developing dementia, Alzheimer's disease (AD), and vascular dementia in iNPH patients. METHODS: Patients aged ≥ 60 years who were diagnosed with iNPH (n = 2053) between January 2001 and June 2018 were identified from the Taiwan National Health Insurance Research Database. Various demographic characteristics (age, sex, and monthly income) and clinical data (incidence year, comorbidities, and Charlson comorbidity index) were collected and divided into the shunt surgery group (SSG) and the non-shunt surgery group (NSSG). Stabilized inverse probability of treatment weighting by using the propensity score was performed to achieve a balanced distribution of confounders across the two study groups. The cumulative incidence rate and risk of dementing disorders were estimated during a 16-year follow-up period. RESULTS: After weighting, the data of 375.0 patients in SSG and 1677.4 patients in NSSG were analyzed. Kaplan-Meier curve analysis indicated that the cumulative incidence rate of AD (p = 0.009), but not dementia (p = 0.241) and vascular dementia (p = 0.761), in SSG was significantly lower than that in NSSG over the 16-year follow-up period. Cox proportional hazards regression analysis revealed that SSG had a reduced hazard ratio (HR) for developing AD [HR (95% CI) 0.17 (0.04-0.69)], but not for dementia [HR (95% CI) 0.83 (0.61-1.12)] and vascular dementia [HR (95% CI) 1.18 (0.44-3.16)], compared with NSSG. Further Fine-Gray hazard regression analysis with death as a competing event demonstrated that SSG had a reduced subdistribution HR (sHR) for developing dementia [sHR (95% CI) 0.74 (0.55-0.99)] and AD [sHR (95% CI) 0.15 (0.04-0.61)], but not for vascular dementia [sHR (95% CI) 1.07 (0.40-2.86)]. CONCLUSION: CSF shunt surgery is associated with reduced risks of the subsequent development of dementia and AD in iNPH patients. Our findings may provide valuable information for assessing the benefit-to-risk profile of CSF shunt surgery.

Efficacy of fresh frozen plasma transfusion in decompensated cirrhosis patients with coagulopathy admitted to ICU: a retrospective cohort study from MIMIC-IV database.

We aimed to explore the association between FFP transfusion and outcomes of DC patients with significant coagulopathy. A total of 693 DC patients with significant coagulopathy were analyzed with 233 patients per group after propensity score matching (PSM). Patients who received FFP transfusion were matched with those receiving conventional therapy via PSM. Regression analysis showed FFP transfusion had no benefit in 30-day (HR: 1.08, 95% CI 0.83-1.4), 90-day (HR: 1.03, 95% CI 0.80-1.31) and in-hospital(HR: 1.30, 95% CI 0.90-1.89) mortality, associated with increased risk of liver failure (OR: 3.00, 95% CI 1.78-5.07), kidney failure (OR: 1.90, 95% CI 1.13-3.18), coagulation failure (OR: 2.55, 95% CI 1.52-4.27), respiratory failure (OR: 1.76, 95% CI 1.15-2.69), and circulatory failure (OR: 2.15, 95% CI 1.27-3.64), and even associated with prolonged the LOS ICU (ß: 2.61, 95% CI 1.59-3.62) and LOS hospital (ß: 6.59, 95% CI 2.62-10.57). In sensitivity analysis, multivariate analysis (HR: 1.09, 95%CI 0.86, 1.38), IPTW (HR: 1.11, 95%CI 0.95-1.29) and CAPS (HR: 1.09, 95% CI 0.86-1.38) showed FFP transfusion had no beneficial effect on the 30-day mortality. Smooth curve fitting demonstrated the risk of liver failure, kidney failure and circulatory failure increased by 3%, 2% and 2% respectively, for each 1 ml/kg increase in FFP transfusion. We found there was no significant difference of CLIF-SOFA and MELD score between the two group on day 0, 3, 7, 14. Compared with the conventional group, INR, APTT, and TBIL in the FFP transfusion group significantly increased, while PaO2/FiO2 significantly decreased within 14 days. In conclusion, FFP transfusion had no beneficial effect on the 30-day, 90-day, in-hospital mortality, was associated with prolonged the LOS ICU and LOS hospital, and the increased risk of liver failure, kidney failure, coagulation failure, respiratory failure and circulatory failure events. However, large, multi-center, randomized controlled trials, prospective cohort studies and external validation are still needed to verify the efficacy of FFP transfusion in the future.

Photo-Responsive Ascorbic Acid-Modified Ag2S-ZnS Heteronanostructure Dropping pH to Trigger Synergistic Antibacterial and Bohr Effects for Accelerating Infected Wound Healing.

Nonantibiotic approaches must be developed to kill pathogenic bacteria and ensure that clinicians have a means to treat wounds that are infected by multidrug-resistant bacteria. This study prepared matchstick-like Ag2S-ZnS heteronanostructures (HNSs). Their hydrophobic surfactants were then replaced with hydrophilic poly(ethylene glycol) (PEG) and thioglycolic acid (TGA) through the ligand exchange method, and this was followed by ascorbic acid (AA) conjugation with TGA through esterification, yielding well-dispersed PEGylated Ag2S-ZnS@TGA-AA HNSs. The ZnS component of the HNSs has innate semiconductivity, enabling the generation of electron-hole pairs upon irradiation with a light of wavelength 320 nm. These separate charges can react with oxygen and water around the HNSs to produce reactive oxygen species. Moreover, some holes can oxidize the surface-grafted AA to produce protons, decreasing the local pH and resulting in the corrosion of Ag2S, which releases silver ions. In evaluation tests, the PEGylated Ag2S-ZnS@TGA-AA had synergistic antibacterial ability and inhibited Gram-negative Escherichia coli and Gram-positive methicillin-resistant Staphylococcus aureus (MRSA). Additionally, MRSA-infected wounds treated with a single dose of PEGylated Ag2S-ZnS@TGA-AA HNSs under light exposure healed significantly more quickly than those not treated, a result attributable to the HNSs' excellent antibacterial and Bohr effects.

Review of electrospun microtube array membrane (MTAM)-a novel new class of hollow fiber for encapsulated cell therapy (ECT) in clinical applications.

Encapsulated cell therapy (ECT) shows significant potential for treating neurodegenerative disorders including Alzheimer's and Parkinson's, which currently lack curative medicines and must be managed symptomatically. This novel technique encapsulates functional cells with a semi-permeable membrane, providing protection while enabling critical nutrients and therapeutic substances to pass through. Traditional ECT procedures, on the other hand, pose difficulties in terms of cell survival and retrieval. We introduce the Microtube Array Membrane (MTAM), a revolutionary technology that solves these constraints, in this comprehensive overview. Microtube Array Membrane has distinct microstructures that improve encapsulated cells' long-term viability by combining the advantages of macro and micron scales. Importantly, the MTAM platform improves biosafety by allowing the entire encapsulated unit to be retrieved in the event of an adverse reaction. Our findings show that MTAM-based ECT has a great potential in a variety of illness situations. For cancer treatment, hybridoma cells secreting anti-CEACAM 6 antibodies inhibit triple-negative breast cancer cell lines for an extended period of time. In animal brain models of Alzheimer's disease, hybridoma cells secreting anti-pTau antibodies successfully reduce pTau buildup, accompanied by improvements in memory performance. In mouse models, MTAM-encapsulated primary cardiac mesenchymal stem cells dramatically improve overall survival and heart function. These findings illustrate the efficacy and adaptability of MTAM-based ECT in addressing major issues such as immunological isolation, cell viability, and patient safety. We provide new possibilities for the treatment of neurodegenerative illnesses and other conditions by combining the potential of ECT with MTAM. Continued research and development in this subject has a lot of promise for developing cell therapy and giving hope to people suffering from chronic diseases.

Intranasal corticosteroids reduced acute rhinosinusitis in children with allergic rhinitis: A nested case-control study.

BACKGROUND: Children with allergic rhinitis (AR) have substantially more acute rhinosinusitis than children without AR. We evaluated whether intranasal corticosteroids (INCS), second-generation antihistamines (SGH), and/or intranasal antihistamines (INH) for AR affect acute rhinosinusitis in children with AR aged 2-18 years. METHODS: By using the National Health Research Institutes Database 2005 of Taiwan, a cohort of patients with AR aged 2-18 years treated with AR medications between 2002 and 2018 was made, within which a nested case-control study was performed. Risk settings for acute rhinosinusitis cases matched controls for age, sex, and comorbidities. Current users of INCS, INH, and/or SGH were compared with remote and recent users of any AR medications and current users of INCS with and without SGH were compared with current users of SGH. RESULTS: Current users of SGH and/or INCS had a higher risk of acute rhinosinusitis than remote users of AR drugs, and current users of SGH had a higher risk of acute rhinosinusitis than recent users; however, no difference in the risk of acute rhinosinusitis was found between current users of INCS and recent users of AR drugs. Current users of INCS with and without SGH had a lower risk of acute rhinosinusitis than current users of SGH alone. CONCLUSIONS: Treatment of INCS with and without SGH diminished the risk of acute rhinosinusitis compared with treatment using SGH alone. Adequate INCS treatment for patients with AR is important to reduce the incidence of acute rhinosinusitis.

Risk of Bleeding Following Non-Vitamin K Antagonist Oral Anticoagulant Use in Patients With Acute Ischemic Stroke Treated With Alteplase.

Importance: Current guidelines advise against intravenous alteplase therapy for treatment of acute ischemic stroke in patients previously treated with non-vitamin K antagonist oral anticoagulants (NOACs). Objective: To evaluate the risk of bleeding and mortality after alteplase treatment for acute ischemic stroke among patients treated with NOACs compared to those not treated with NOACs. Design, Setting, and Participants: This nationwide, population-based cohort study was conducted in Taiwan using data from Taiwan's National Health Insurance Research Database from January 2011 through November 2020 and included 7483 patients treated with alteplase for acute ischemic stroke. A meta-analysis incorporating the results of the study with those of previous studies was performed, and the review protocol was prospectively registered with PROSPERO. Exposures: NOAC treatment within 2 days prior to stroke, compared to either no anticoagulant treatment or warfarin treatment. Main Outcomes and Measures: The primary outcome was intracranial hemorrhage after intravenous alteplase during the index hospitalization (the hospitalization subsequent to alteplase administration). Secondary outcomes were major bleeding events and mortality during the index hospitalization. Propensity score matching was used to control potential confounders. Logistic regression was used to estimate the odds ratio (OR) of outcome events. Meta-analysis was performed using a random-effects model. Results: Of the 7483 included patients (mean [SD] age, 67.4 [12.7] years; 2908 [38.9%] female individuals and 4575 [61.1%] male individuals), 91 (1.2%), 182 (2.4%), and 7210 (96.4%) received NOACs, warfarin, and no anticoagulants prior to their stroke, respectively. Compared to patients who were not treated with anticoagulants, those treated with NOACs did not have significantly higher risks of intracranial hemorrhage (risk difference [RD], 2.47% [95% CI, -4.23% to 9.17%]; OR, 1.37 [95% CI, 0.62-3.03]), major bleeding (RD, 4.95% [95% CI, -2.56% to 12.45%]; OR, 1.69 [95% CI, 0.83-3.45]), or in-hospital mortality (RD, -4.95% [95% CI, -10.11% to 0.22%]; OR, 0.45 [95% CI, 0.15-1.29]) in the propensity score-matched analyses. Furthermore, the risks of bleeding and mortality were not significantly different between patients treated with NOACs and those treated with warfarin. Similar results were obtained in the meta-analysis. Conclusions and Relevance: In this cohort study with meta-analysis, compared to no treatment with anticoagulants, treatment with NOACs prior to stroke was not associated with a higher risk of intracranial hemorrhage, major bleeding, or mortality in patients receiving intravenous alteplase for acute ischemic stroke.

Effect of a Single Light-intensity Walking Session on Sleep Quality of Patients with Bladder Cancer: A Randomized Cross-Over Study.

OBJECTIVES: Exercise has been recommended to enhance sleep. However, there is a paucity of studies investigating the relationships between exercise and sleep problems in patients with bladder cancer. The authors explored the effects of a single bout of light-intensity walking on the sleep quality of patients with bladder cancer who have sleep disorders. DATA SOURCES: A total of 14 patients with bladder cancer with sleep disorders were recruited for this trial. The participants were randomly assigned to the walking or control condition in a cross-over design to explore the effects of a single light-intensity walking session on objectively measured sleep quality. A two-way repeated measures analysis of variance and a nonparametric permutation test were used to examine intervention effects. Twelve participants (85.7%) completed the trial. A significant group × time interaction for sleep latency (P = .023) was identified. The pairwise comparison showed significant results (P = .012) for the difference between the post-test sleep latency and the pre-test. No significant group × time interactions were observed for the remaining seven sleep parameters. Additionally, only the main effects of time on length of awakening and time in bed were significant (P < .001). CONCLUSION: A single bout of light-intensity walking has a positive effect on shortening the sleep latency of patients with bladder cancer who have sleep disorders. IMPLICATIONS FOR NURSING PRACTICE: Oncology nurses can encourage patients with bladder cancer to exercise, even light-intensity walking, which may improve sleep quality.

Association between gestational exposure and risk of orofacial clefts: a systematic review and meta-analysis.

BACKGROUND: The occurrence of orofacial Clefts (OFCs) is a congenital disease caused by many factors. According to recent studies, air pollution has a strong correlation with the occurrence of OFCs. However, there are still some controversies about the current research results, and there is no relevant research to review the latest results in recent years. OBJECTIVE: In this paper, the authors conducted a systematic review and meta-analysis to explore the correlation between ambient air pollution and the occurrence of neonatal OFCs deformity. METHODS: We searched Pubmed, Web of science, and Embase databases from the establishment of the database to May 2023. We included observational studies on the relationship between prenatal exposure to fine particulate matter 2.5 (PM2.5), fine particulate matter 10 (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO) and the risk of cleft lip (CL), cleft palate (CP), cleft lip with or without palate (CL/P). the Newcastle-Ottawa quality assessment scale (NOS) was used to evaluate the quality of the literature. Funnel plot and Egger's regression were used to verify the publication bias. Random effect model or fixed effect model was used to estimate the combined relative risk (RR) and 95% confidence interval (95%CI). RESULTS: A total of eleven studies were included in this study, including four cohort studies and seven case-control studies, including 22,453 cases of OFCs. Ten studies had low risk of bias and only one study had high risk of bias. Three studies reported that PM2.5 was positively correlated with CL and CP, with a combined RR and 95%CI of 1.287(1.174,1.411) and 1.267 (1.105,1.454). Two studies reported a positive correlation between O3 and CL, with a combined RR and 95%CI of 1.132(1.047,1.225). Two studies reported a positive correlation between PM10 and CL, with a combined RR and 95%CI of 1.108 (1.017,1.206). No association was found between SO2, CO, NO2 exposure during pregnancy and the risk of OFCs. CONCLUSION: The results of this study showed that there was a significant statistical correlation between exposure to PM10, PM2.5, O3 and the risk of OFCs in the second month of pregnancy. Exposure assessment, research methods and mechanisms need to be further explored.

CXCL9 as a Reliable Biomarker for Discriminating Anti-IFN-γ-Autoantibody-Associated Lymphadenopathy that Mimics Lymphoma.

The diagnosis of adult-onset immunodeficiency syndrome associated with neutralizing anti-interferon γ autoantibodies (AIGA) presents substantial challenges to clinicians and pathologists due to its nonspecific clinical presentation, absence of routine laboratory tests, and resemblance to certain lymphoma types, notably nodal T follicular helper cell lymphoma, angioimmunoblastic type (nTFHL-AI). Some patients undergo lymphadenectomy for histopathological examination to rule out lymphoma, even in the absence of a preceding clinical suspicion of AIGA. This study aimed to identify reliable methods to prevent misdiagnosis of AIGA in this scenario through a retrospective case-control analysis of clinical and pathological data, along with immune gene transcriptomes using the NanoString nCounter platform, to compare AIGA and nTFHL-AI. The investigation revealed a downregulation of the C-X-C motif chemokine ligand 9 (CXCL9) gene in AIGA, prompting an exploration of its diagnostic utility. Immunohistochemistry (IHC) targeting CXCL9 was performed on lymph node specimens to assess its potential as a diagnostic biomarker. The findings exhibited a significantly lower density of CXCL9-positive cells in AIGA compared to nTFHL-AI, displaying a high diagnostic accuracy of 92.3% sensitivity and 100% specificity. Furthermore, CXCL9 IHC demonstrated its ability to differentiate AIGA from various lymphomas sharing similar characteristics. In conclusion, CXCL9 IHC emerges as a robust biomarker for differentiating AIGA from nTFHL-AI and other similar conditions. This reliable diagnostic approach holds the potential to avert misdiagnosis of AIGA as lymphoma, providing timely and accurate diagnosis.

The Antibiotic Resistome and Its Association with Bacterial Communities in Raw Camel Milk from Altay Xinjiang.

Raw camel milk is generally contaminated with varied microbiota, including antibiotic-resistant bacteria (ARB), that can act as a potential pathway for the spread of antibiotic resistance genes (ARGs). In this study, high-throughput quantitative PCR and 16S rRNA gene-based Illumine sequencing data were used to establish a comprehensive understanding of the antibiotic resistome and its relationship with the bacterial community in Bactrian camel milk from Xinjiang. A total of 136 ARGs and up to 1.33 × 108 total ARG copies per gram were identified, which predominantly encode resistance to ß-lactamas and multidrugs. The ARGs' profiles were mainly explained by interactions between the bacteria community and physicochemical indicators (77.9%). Network analysis suggested that most ARGs exhibited co-occurrence with Corynebacterium, Leuconostoc and MGEs. Overall, raw camel milk serves as a reservoir for ARGs, which may aggravate the spread of ARGs through vertical and horizontal gene transfer in the food chain.

Aptamer-functionalized field-effect transistor biosensors for disease diagnosis and environmental monitoring.

Nano-biosensors that are composed of recognition molecules and nanomaterials have been extensively utilized in disease diagnosis, health management, and environmental monitoring. As a type of nano-biosensors, molecular specificity field-effect transistor (FET) biosensors with signal amplification capability exhibit prominent advantages including fast response speed, ease of miniaturization, and integration, promising their high sensitivity for molecules detection and identification. With intrinsic characteristics of high stability and structural tunability, aptamer has become one of the most commonly applied biological recognition units in the FET sensing fields. This review summarizes the recent progress of FET biosensors based on aptamer functionalized nanomaterials in medical diagnosis and environmental monitoring. The structure, sensing principles, preparation methods, and functionalization strategies of aptamer modified FET biosensors were comprehensively summarized. The relationship between structure and sensing performance of FET biosensors was reviewed. Furthermore, the challenges and future perspectives of FET biosensors were also discussed, so as to provide support for the future development of efficient healthcare management and environmental monitoring devices.

Clinical narratives as a predictor for prognosticating functional outcomes after intracerebral hemorrhage.

BACKGROUND: Intracerebral hemorrhage (ICH) is a devastating stroke type that causes high mortality rates and severe disability among survivors. Many prognostic models are available for prognosticating patients with ICH. This study aimed to investigate whether clinical narratives can improve the performance for predicting functional outcomes after ICH. METHODS: This study used data from the hospital stroke registry and electronic health records. The study population (n = 1363) was randomly divided into a training set (75%, n = 1023) and a holdout test set (25%, n = 340). Five risk scores for ICH were used as baseline prognostic models. Using natural language processing (NLP), text-based markers were generated from the clinical narratives of the training set through machine learning (ML) and deep learning (DL) approaches. The primary outcome was a poor functional outcome (modified Rankin Scale score of 3 to 6) at hospital discharge. The predictive performance was compared between the baseline models and models enhanced by incorporating the text-based markers using the holdout test set. RESULTS: The enhanced prognostic models outperformed the baseline models, regardless of whether ML or DL approaches were used. The areas under the receiver operating characteristic curve (AUCs) of the baseline models were between 0.760 and 0.892. Adding the text-based marker to the baseline models significantly increased the model discrimination, with AUCs ranging from 0.861 to 0.914. The net reclassification improvement and integrated discrimination improvement indices also showed significant improvements. CONCLUSIONS: Using NLP to extract textual information from clinical narratives could improve the predictive performance of all baseline prognostic models for ICH.