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Purpose: This manuscript performed a meta-analysis to compare the effects of a low-fat diet (LFD) and a low-carbohydrate diet (LCD) on body weight and lipid levels in adolescents with overweight and obesity. Patients and Methods: PubMed and other databases were searched for the full-text literature comparing LFD and LCD up to November 2023 using a subject plus free word strategy, with search terms such as "low-fat diet", "low-carbohydrate diet", "obesity", "weight", "adolescents", "RCT", and so on. Two independent reviewers selected promising candidate trials, collected the data, and assessed the quality of the trials. RevMan 5.3 software was utilized to conduct a meta-analysis of the randomized controlled trials (RCTs) that were included. Results: 5 RCTs with 192 participants were included in this meta-analysis. Weight (mean difference -2.81; 95% CI -5.38 to -0.25), Body Mass Index (BMI) (-1.13; 95% CI -2.14 to -0.11) and Triglyceride (TG) (-0.36; 95% CI -0.46 to -0.27) of the LCD were significantly lower than that of the LFD. At the same time, the high-density lipoprotein cholesterol (HDL) levels of the LCD were significantly higher than those of the LFD (0.08; 95% CI 0.04 to 0.12) (P < 0.05). However, there was no significant difference in the Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), percent body fat, total cholesterol (TC), and low-density lipoprotein cholesterol (LDL) between the two groups (P>0.05). Conclusion: According to this study, LCD is more helpful in improving weight loss, HDL and TG. Thus, LCD may serve as an effective intervention for weight management in adolescents with overweight and obesity, although further research is needed to determine its long-term effects.
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Detecting side effects of drugs is a fundamental task in drug development. With the expansion of publicly available biomedical data, researchers have proposed many computational methods for predicting drug-side effect associations (DSAs), among which network-based methods attract wide attention in the biomedical field. However, the problem of data scarcity poses a great challenge for existing DSAs prediction models. Although several data augmentation methods have been proposed to address this issue, most of existing methods employ a random way to manipulate the original networks, which ignores the causality of existence of DSAs, leading to the poor performance on the task of DSAs prediction. In this paper, we propose a counterfactual inference-based data augmentation method for improving the performance of the task. First, we construct a heterogeneous information network (HIN) by integrating multiple biomedical data. Based on the community detection on the HIN, a counterfactual inference-based method is designed to derive augmented links, and an augmented HIN is obtained accordingly. Then, a meta-path-based graph neural network is applied to learn high-quality representations of drugs and side effects, on which the predicted DSAs are obtained. Finally, comprehensive experiments are conducted, and the results demonstrate the effectiveness of the proposed counterfactual inference-based data augmentation for the task of DSAs prediction.
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BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) is a prevalent chronic liver ailment that can lead to serious conditions such as cirrhosis and hepatocellular carcinoma. Hepatic Nogo-B regulates glucose and lipid metabolism, and its inhibition has been shown to be protective against metabolic syndrome. Increasing evidence suggests that imbalances in the gut microbiota (GM) and lipid metabolism disorders are significant contributors to NAFLD progression. Nevertheless, it is not yet known whether Nogo-B can affect NAFLD by influencing the gut microbiota and metabolites. Hence, the aim of the present study was to characterize this process and explore its possible underlying mechanisms. METHODS: A NAFLD model was constructed by administering a high-fat diet (HFD) to Nogo-B-/- and WT mice from the same litter, and body weight was measured weekly in each group. The glucose tolerance test (GTT) and insulin tolerance test (ITT) were performed to assess blood glucose levels. At the end of the 12-week period, samples of serum, liver, and intestinal contents were collected and used for serum biochemical marker and inflammatory factor detection; pathology evaluation; and gut microbiome and metabolomics analysis. Spearman's correlation analysis was performed to determine possible correlations between differential gut microbiota and differential serum metabolites between groups. RESULTS: Nogo-B deficiency attenuated the effects of the HFD, including weight gain, liver weight gain, impaired glucose tolerance, hepatic steatosis, elevated serum lipid biochemicals levels, and liver function. Nogo-B deficiency suppressed M1 polarization and promoted M2 polarization, thus inhibiting inflammatory responses. Furthermore, Nogo-B-/--HFD-fed mice presented increased gut microbiota richness and diversity, decreased Firmicutes/Bacteroidota (F/B) ratios, and altered serum metabolites compared with those of WT-HFD-fed mice. During analysis, several differential gut microbiota, including Lachnoclostridium, Harryflintia, Odoribacter, UCG-009, and unclassified_f_Butyricoccaceae, were screened between groups. These microbiota were found to be positively correlated with upregulated purine metabolism and bile acid metabolites in Nogo-B deficiency, while they were negatively correlated with downregulated corticosterone and tricarboxylic acid cyclic metabolites in Nogo-B deficiency. CONCLUSION: Nogo-B deficiency delayed NAFLD progression, as demonstrated by reduced hepatocellular lipid accumulation, attenuated inflammation and liver injury, and ameliorated gut microbiota dysbiosis and metabolic disorders. Importantly, Odoribacter was strongly positively correlated with ALB and taurodeoxycholic acid, suggesting that it played a considerable role in the influence of Nogo-B on the progression of NAFLD, a specific feature of NAFLD in Nogo-B-/- mice. The regulation of bile acid metabolism by the gut microbiota may be a potential target for Nogo-B deficiency to ameliorate NAFLD.
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BACKGROUND: The number and proportion of HIV/AIDS patients among older people are continuously and rapidly increasing in China. We conducted a detailed molecular epidemiological analysis of HIV-1 epidemic strains in a developed city in eastern China and found that elderly people play a crucial role in the transmission of subtypes and high pretreatment drug resistance (PDR). METHODS: A total of 1048 samples were obtained from 1129 (92.8%) newly confirmed HIV-1-positive and treatment-naive patients between 2019 and 2023. The 1316 bp target fragment of the pol gene was amplified by reverse transcription polymerase chain reaction (RTâPCR) and nested PCR, and Maximum-likelihood (ML) phylogenetic trees and molecular transmission network were constructed to analyse the subtypes and transmission clusters. Molecular transmission network was visualized using Cytoscape with the distance threshold of 0.0075. PDR-associated mutations were determined according to the Stanford University HIV Drug Resistance Database. RESULTS: A total of 933 pol sequences (89.0%, 933/1048) were successfully obtained, and twelve HIV-1 subtypes were detected. CRF07_BC was the predominant subtype, accounting for 48.1% (449/933) of sequences, followed by CRF01_AE (29.4%, 274/933). A total of 398 individuals (42.7%, 398/933) formed 89 clusters in the network. Multivariable logistic regression analysis revealed that age, nationality, subtype, and PDR were the most significant factors associated with clustering in the transmission network. The prevalence of PDR was 14.6% (136/933).PDR associated with non-nucleoside reverse transcriptase inhibitors (10.0%, 93/933) was much more common than that associated with nucleoside reverse transcriptase inhibitors (1.8%, 17/933) and protease inhibitors (3.2%, 30/933) (χ2 = 77.961, p < 0.001). The most frequent NNRTI mutations were K103N/S/KN/NS (52.2%, 71/136), which led to the highest proportion of high-level resistance to nevirapine and efavirenz (52.2%). CONCLUSIONS: Our study revealed the important influence of elderly people on CRF07_BC transmission and the high prevalence of PDR. The clustering of drug-resistant cases was significant, which suggested the potential for localized widespread transmission of drug-resistant strains. HIV screening and the determination of PDR are recommended for older patients to improve early detection and reduce treatment failure and second-generation transmission.
Subject(s)
Drug Resistance, Viral , HIV Infections , HIV-1 , Molecular Epidemiology , Phylogeny , Humans , HIV-1/genetics , HIV-1/drug effects , HIV-1/classification , China/epidemiology , HIV Infections/transmission , HIV Infections/virology , HIV Infections/epidemiology , HIV Infections/drug therapy , Male , Drug Resistance, Viral/genetics , Female , Middle Aged , Aged , Adult , Genotype , Young Adult , Anti-HIV Agents/pharmacology , Anti-HIV Agents/therapeutic use , Mutation , pol Gene Products, Human Immunodeficiency Virus/genetics , Aged, 80 and over , Adolescent , AgingABSTRACT
The outer dynein arm (ODA) is a large, multimeric protein complex essential for ciliary motility. The composition and assembly of ODA are best characterized in the green algae Chlamydomonas reinhardtii, where individual ODA subunits are synthesized and preassembled into a mature complex in the cytosol prior to ciliary import. The single-cellular parasite Trypanosoma brucei contains a motile flagellum essential for cell locomotion and pathogenesis. Similar to human motile cilia, T. brucei flagellum contains a two-headed ODA complex arranged at 24 nm intervals along the axonemal microtubule doublets. The subunit composition and the preassembly of the ODA complex in T. brucei, however, have not been investigated. In this study, we affinity-purified the ODA complex from T. brucei cytoplasmic extract. Proteomic analyses revealed the presence of two heavy chains (ODAα and ODAß), two intermediate chains (IC1and IC2) and several light chains. We showed that both heavy chains and both intermediate chains are indispensable for flagellar ODA assembly. Our study also provided biochemical evidence supporting the presence of a cytoplasmic, preassembly pathway for T. brucei ODA.
Subject(s)
Axoneme , Cytoplasm , Dyneins , Flagella , Protozoan Proteins , Trypanosoma brucei brucei , Trypanosoma brucei brucei/metabolism , Flagella/metabolism , Cytoplasm/metabolism , Axoneme/metabolism , Dyneins/metabolism , Protozoan Proteins/metabolism , Microtubules/metabolism , Proteomics/methods , Cilia/metabolismABSTRACT
The side reactions and dendrite growth at the interface of Zn anodes greatly limit their practical applications in Zn metal batteries. Herein, we propose a hybrid molecular sieve-based interfacial layer (denoted as Z7M3) with a hierarchical porous structure for Zn metal anodes, which contains 70 vol % microporous ZSM-5 molecular sieves and 30 vol % mesoporous MCM-41 molecular sieves. Through comprehensive molecular dynamics simulations, we demonstrate that the mesopores (â¼2.5 nm) of MCM-41 can limit the disordered diffusion of free water molecules and increase the wettability of the interfacial layer toward aqueous electrolytes. In addition, the micropores (â¼0.56 nm) of ZSM-5 can optimize the Zn2+ solvation structures by reducing the bonded water molecules, which simultaneously decrease the constraint force of solvated water molecules to Zn2+ ions, thus promoting the penetrability and diffusion kinetics of Zn2+ ions in Z7M3. The synergetic effects from the hybrid molecular sieves maintain a constant Zn2+ concentration on the surface of the Zn electrode during Zn deposition, contributing to dendrite-free Zn anodes. Consequently, Z7M3-coated Zn electrodes achieved excellent cycling stability in both half and full cells.
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RESEARCH QUESTION: Does the co-transfer of a good-quality embryo and a poor-quality embryo influence pregnancy outcomes in comparison to the transfer of a single good-quality embryo in vitrified-warmed blastocyst transfer cycles? DESIGN: This retrospective cohort study involved a total of 11,738 women who underwent IVF/intracytoplasmic sperm injection cycles and vitrified-warmed blastocyst transfer at a tertiary-care academic medical from January 2015 to June 2022. The study population was categorized into two groups: single-blastocyst transfer (SBT; participants who underwent single good-quality embryo transfer, nâ¯=â¯9338) versus double-blastocyst transfer (DBT; participants who underwent transfers with a poor and a good-quality embryo, nâ¯=â¯2400). RESULTS: The live birth rate (LBR) was significantly higher in the DBT group in comparison with the SBT group (65.6% versus 56.3%, P < 0.001). Multivariable logistic regression analysis showed that DBT was an independent predictor for LBR with a strong potential impact (adjusted odds ratio 1.55, 95% confidence interval 1.41-1.71; P < 0.001). However, the multiple birth rate was significantly higher in the good-quality embryo and poor-quality embryo group compared with patients undergoing a single good-quality embryo transfer (41.4% versus 1.8%; P < 0.001). CONCLUSIONS: In vitrified-warmed blastocyst transfer cycles, LBR was higher following DBT with one good-quality and one poor-quality embryo compared with SBT. However, this was at the expense of a marked increase in the likelihood of multiple gestations. Physicians should still balance the benefits and risks of double-embryo transfer.
Subject(s)
Embryo Transfer , Pregnancy Outcome , Vitrification , Humans , Female , Pregnancy , Adult , Embryo Transfer/methods , Retrospective Studies , Pregnancy Rate , Birth Rate , Blastocyst , Fertilization in Vitro/methods , CryopreservationABSTRACT
BACKGROUND AND AIMS: Drug-induced liver injury (DILI) is a prevalent adverse reaction in clinical settings. However, there is limited research on age-related differences in DILI. We performed a large-scale retrospective study to delineate the characteristics of DILI across different age groups. METHODS: We collected data on a total of 17,946 patients with confirmed DILI hospitalized at the Fifth Medical Center of the People's Liberation Army (PLA) General Hospital in Beijing, China, from January 1, 2002, to December 31, 2022. The patients were stratified based on age into the following groups: children (< 18 years), young adults (18-44 years), middle-aged individuals (45-64 years), and elderly individuals (≥ 65 years). We gathered demographic information, medical histories, laboratory results, disease severity assessments, and mortality statistics for all patients. RESULTS: Overall, the distribution of DILI cases across different age groups was as follows: 6.57% were children, 24.82% were young adults, 49.06% were middle-aged individuals, and 19.54% were elderly individuals. The percentage of females increased with age, rising from 36.47% in the pediatric group to 60.51% in the elderly group. Notably, central nervous system agents (15.44%) and anti-infectious agents (21.80%) were more commonly associated with DILI in children, while cardiovascular agents (10.58%) and herbal dietary supplements or traditional medicines (H/TMs) (26.29%) were more prevalent among elderly people with DILI. Among all age groups, hepatocellular-type DILI was more common in the pediatric group (p < 0.001), whereas cholestatic-type DILI and chronic DILI were more prevalent in the elderly group (p < 0.001). Acute liver failure (ALF) and fatal outcomes were more prevalent in the pediatric and elderly groups, particularly in the pediatric group (2.04%, p = 0.041; 0.85%, p = 0.007, respectively). CONCLUSIONS: Children and elderly individuals face a higher risk of adverse outcomes following DILI.
Subject(s)
Chemical and Drug Induced Liver Injury , Humans , Retrospective Studies , Chemical and Drug Induced Liver Injury/epidemiology , Chemical and Drug Induced Liver Injury/etiology , Female , Male , Adult , Middle Aged , China/epidemiology , Adolescent , Aged , Young Adult , Child , Age Factors , Child, PreschoolABSTRACT
Multimodal aspect-based sentiment classification (MABSC) aims to identify the sentiment polarity toward specific aspects in multimodal data. It has gained significant attention with the increasing use of social media platforms. Existing approaches primarily focus on analyzing the content of posts to predict sentiment. However, they often struggle with limited contextual information inherent in social media posts, hindering accurate sentiment detection. To overcome this issue, we propose a novel multimodal dual cause analysis (MDCA) method to track the underlying causes behind expressed sentiments. MDCA can provide additional reasoning cause (RC) and direct cause (DC) to explain why users express certain emotions, thus helping improve the accuracy of sentiment prediction. To develop a model with MDCA, we construct MABSC datasets with RC and DC by utilizing large language models (LLMs) and visual-language models. Subsequently, we devise a multitask learning framework that leverages the datasets with cause data to train a small generative model, which can generate RC and DC, and predict the sentiment assisted by these causes. Experimental results on MABSC benchmark datasets demonstrate that our MDCA model achieves the state-of-the-art performance, and the small fine-tuned model exhibits superior adaptability to MABSC compared to large models like ChatGPT and BLIP-2.
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BACKGROUND: Drug-induced liver injury (DILI) is one of the most common adverse events of medication use, and its incidence is increasing. However, early detection of DILI is a crucial challenge due to a lack of biomarkers and noninvasive tests. AIM: To identify salivary metabolic biomarkers of DILI for the future development of noninvasive diagnostic tools. METHODS: Saliva samples from 31 DILI patients and 35 healthy controls (HCs) were subjected to untargeted metabolomics using ultrahigh-pressure liquid chromatography coupled with tandem mass spectrometry. Subsequent analyses, including partial least squares-discriminant analysis modeling, t tests and weighted metabolite coexpression network analysis (WMCNA), were conducted to identify key differentially expressed metabolites (DEMs) and metabolite sets. Furthermore, we utilized least absolute shrinkage and selection operato and random fores analyses for biomarker prediction. The use of each metabolite and metabolite set to detect DILI was evaluated with area under the receiver operating characteristic curves. RESULTS: We found 247 differentially expressed salivary metabolites between the DILI group and the HC group. Using WMCNA, we identified a set of 8 DEMs closely related to liver injury for further prediction testing. Interestingly, the distinct separation of DILI patients and HCs was achieved with five metabolites, namely, 12-hydroxydodecanoic acid, 3-hydroxydecanoic acid, tetradecanedioic acid, hypoxanthine, and inosine (area under the curve: 0.733-1). CONCLUSION: Salivary metabolomics revealed previously unreported metabolic alterations and diagnostic biomarkers in the saliva of DILI patients. Our study may provide a potentially feasible and noninvasive diagnostic method for DILI, but further validation is needed.
Subject(s)
Biomarkers , Chemical and Drug Induced Liver Injury , Metabolomics , Saliva , Humans , Biomarkers/analysis , Biomarkers/metabolism , Chemical and Drug Induced Liver Injury/diagnosis , Chemical and Drug Induced Liver Injury/etiology , Chemical and Drug Induced Liver Injury/metabolism , Saliva/chemistry , Saliva/metabolism , Male , Female , Metabolomics/methods , Middle Aged , Adult , Case-Control Studies , Tandem Mass Spectrometry/methods , ROC Curve , Aged , Chromatography, High Pressure Liquid , Early DiagnosisABSTRACT
Background: The Zuojin Pill (ZJP) is widely used for treating chronic atrophic gastritis (CAG) in clinical practice, effectively ameliorating symptoms such as vomiting, pain, and abdominal distension in patients. However, the underlying mechanisms of ZJP in treating CAG has not been fully elucidated. Purpose: This study aimed to clarify the characteristic function of ZJP in the treatment of CAG and its potential mechanism. Methods: The CAG model was established by alternant administrations of ammonia solution and sodium deoxycholate, as well as an irregular diet. Therapeutic effects of ZJP on body weight, serum biochemical indexes and general condition were analyzed. HE staining and AB-PAS staining were analyzed to characterize the mucosal injury and the thickness of gastric mucosa. Furthermore, network pharmacology and molecular docking were used to predict the regulatory mechanism and main active components of ZJP in CAG treatment. RT-PCR, immunohistochemistry, immunofluorescence and Western blotting were used to measure the expression levels of apoptosis-related proteins, gastric mucosal barrier-associated proteins and PI3K/Akt signaling pathway proteins. Results: The results demonstrated that ZJP significantly improved the general state of CAG rats, alleviated weight loss and gastric histological damage and reduced the serum biochemical indicators. Network pharmacology and molecular docking found that ZJP in treating CAG by inhibiting inflammation, suppressing apoptosis, and protecting the gastric mucosal barrier via the PI3K/Akt signaling pathway. Further experiments confirmed that ZJP obviously modulated the expression of key proteins involved in gastric mucosal cell apoptosis, such as Bax, Bad, Apaf-1, cleaved-caspase-3, cleaved-caspase-9, Cytochrome C, Bcl-2, and Bcl-xl. Moreover, ZJP significantly reversed the protein expression of Occludin, ZO-1, Claudin-4 and E-cadherin. Conclusion: Our study revealed that ZJP treats CAG by inhibiting the PI3K/Akt signaling pathway. This research provided a scientific basis for the rational use of ZJP in clinical practice.
Subject(s)
Disease Models, Animal , Drugs, Chinese Herbal , Gastric Mucosa , Gastritis, Atrophic , Molecular Docking Simulation , Rats, Sprague-Dawley , Animals , Gastritis, Atrophic/drug therapy , Gastritis, Atrophic/pathology , Gastritis, Atrophic/metabolism , Rats , Drugs, Chinese Herbal/pharmacology , Drugs, Chinese Herbal/chemistry , Gastric Mucosa/drug effects , Gastric Mucosa/pathology , Gastric Mucosa/metabolism , Male , Chronic Disease , Signal Transduction/drug effects , Phosphatidylinositol 3-Kinases/metabolism , Apoptosis/drug effects , Network Pharmacology , Proto-Oncogene Proteins c-akt/metabolismABSTRACT
BACKGROUND: Maternal parenting self-efficacy plays a critical role in facilitating positive parenting practices and successful adaption to motherhood. The Perceived Maternal Parenting Self-Efficacy Scale (PMPS-E), as a task-specific measure, confirms its psychometric properties in cultural contexts. Compared with other tools, the advantages of the PMPS-E are as follows: (i) specific context or time period during the lifespan of a child, (ii) explicitly assess parenting self-efficacy across a diverse enough range of parenting tasks or activities during the perinatal/postnatal period and (iii) having robust psychometric properties. The aim of this study was to translate and determine the psychometric properties of the PMPS-E among Chinese postpartum women (C-PMPS-E). METHOD: The cross-cultural adaptation process followed Beaton et al.'s intercultural debugging guidelines. A total of 471 women were included to establish the psychometric properties of the C-PMPS-E. Mothers were asked to complete the C-PMPS-E, Edinburgh Postnatal Depression Scale (EPDS), the Generalized Anxiety Disorder-7 (GAD-7) and several demographic questions. The psychometric testing of the C-PMPS-E was established through item analysis, construct validity and internal consistency reliability. RESULTS: Item analysis showed that the critical ratios of all items were greater than 3 between the low-score group and high-score group, and all item-total correlation coefficients were greater than 0.4. The fit indices showed that the original correlated four-factor model of C-PMPS-E was observed to be an excellent fit to the data. The PMPS-E was negatively correlated with the EPDS and GAD-7 demonstrating its discriminant validity. As expected, no significant correlation was found between PMPS-E total or subscale scores and mothers' age. In addition, statistically significant differences for parity were detected for C-PMPS-E total and subscale scores with multipara having higher scores. This was taken as further evidence of the scale known-groups discriminant validity. In terms of internal consistency, the Cronbach's alpha of the C-PMPS-E total scale was 0.950, and subscales ranged from 0.76 to 0.89. Furthermore, a ROC curve analysis was conducted to establish the ability of the C-PMPS-E to distinguish between symptoms of depression and symptoms of anxiety. A cut-off value of 55 was identified that resulted in good specificity and fair sensitivity. CONCLUSION: The C-PMPS-E is a reliable and valid tool to assess maternal parenting self-efficacy in a Chinese context.
Subject(s)
Mothers , Parenting , Postpartum Period , Psychometrics , Self Efficacy , Humans , Female , Adult , Parenting/psychology , Postpartum Period/psychology , Reproducibility of Results , Mothers/psychology , China , Surveys and Questionnaires/standards , Young Adult , Translations , Depression, Postpartum/psychology , Depression, Postpartum/diagnosisABSTRACT
Nanorods assembled 3D microspheres of TiO2/MnO2 were prepared via a simple one-pot hydrothermal approach. The resultant composite material exhibited remarkable electrocatalytic activity for hydrogen peroxide (H2O2) in comparison to each single component. The electrochemical sensor constructed with TiO2/MnO2 exhibited a linear relationship within the range 0.0001-5.6 mmol·L-1 for H2O2. The limit of detection (LOD) and sensitivity for H2O2 were 0.03 µmol·L-1 (S/N = 3) and 316.6 µA (mmol·L-1)-1 cm-2. Moreover, this sensor can be employed to detect trace amount of H2O2 in serum and urine samples successfully, supporting an insight and strategy for a more sensitive electrochemical sensor.
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The crisis of antibiotic resistance has become a significant global threat to human health. Understanding properties of antibiotic resistance genes (ARGs) is the first step to mitigate this issue. Although many methods have been proposed for predicting properties of ARGs, most of these methods focus only on predicting antibiotic classes, while ignoring other properties of ARGs, such as resistance mechanisms and transferability. However, acquiring all of these properties of ARGs can help researchers gain a more comprehensive understanding of the essence of antibiotic resistance, which will facilitate the development of antibiotics. In this paper, the task of predicting properties of ARGs is modeled as a multi-task learning problem, and an effective subtask-aware representation learning-based framework is proposed accordingly. More specifically, property-specific expert networks and shared expert networks are utilized respectively to learn subtask-specific features for each subtask and shared features among different subtasks. In addition, a gating-controlled mechanism is employed to dynamically allocate weights to subtask-specific semantics and shared semantics obtained respectively from property-specific expert networks and shared expert networks, thus adjusting distinctive contributions of subtask-specific features and shared features to achieve optimal performance for each subtask simultaneously. Extensive experiments are conducted on publicly available data, and experimental results demonstrate the effectiveness of the proposed framework on the task of ARGs properties prediction.
Subject(s)
Computational Biology , Humans , Computational Biology/methods , Drug Resistance, Microbial/genetics , Machine Learning , Algorithms , Anti-Bacterial Agents/pharmacologyABSTRACT
Triclocarban (TCC) and triclosan (TCS) have been detected ubiquitously in human body and evoked increasing concerns. This study aimed to reveal the induction risks of TCC and TCS on triple negative breast cancer through non-genomic GPER-mediated signaling pathways. Molecular simulation indicated that TCC exhibited higher GPER binding affinity than TCS theoretically. Calcium mobilization assay displayed that TCC/TCS activated GPER signaling pathway with the lowest observed effective concentrations (LOEC) of 10 nM/100 nM. TCC and TCS also upregulated MMP-2/9, EGFR, MAPK3 but downregulated MAPK8 via GPER-mediated signaling pathway. Proliferation assay showed that TCC/TCS induced 4 T1 breast cancer cells proliferation with the LOEC of 100 nM/1000 nM. Wound-healing and transwell assays showed that TCC/TCS promoted 4 T1 cells migration in a concentration-dependent manner with the LOEC of 10 nM. The effects of TCC on breast cancer cells proliferation and migration were stronger than TCS and both were regulated by GPER. TCC/TCS induced migratory effects were more significantly than proliferative effect. Mechanism study showed that TCC/TCS downregulated the expression of epithelial marker (E-cadherin) but upregulated mesenchymal markers (snail and N-cadherin), which was reversed by GPER inhibitor G15. These biomarkers results indicated that TCC/TCS-induced 4 T1 cells migration was a classic epithelial to mesenchymal transition mechanism regulated by GPER signaling pathway. Orthotopic tumor model verified that TCC promoted breast cancer in-situ tumor growth and distal tissue metastasis via GPER-mediated signaling pathway at human-exposure level of 10 mg/kg/d. TCC-induced tissue metastasis of breast cancer was more significantly than in-situ tumor growth. Overall, we demonstrated for the first time that TCC/TCS could activate the GPER signaling pathways to induce breast cancer progression.
Subject(s)
Breast Neoplasms , Carbanilides , Receptors, Estrogen , Receptors, G-Protein-Coupled , Signal Transduction , Triclosan , Carbanilides/toxicity , Signal Transduction/drug effects , Triclosan/toxicity , Humans , Female , Breast Neoplasms/pathology , Receptors, G-Protein-Coupled/metabolism , Receptors, Estrogen/metabolism , Cell Line, Tumor , Cell Proliferation/drug effects , Mice , Animals , Cell Movement/drug effectsABSTRACT
Controlled aggregation is of great significance in designing nanodevices with high electrochemical performance. In this study, an in situ aggregation strategy with cyclodextrin polymer (CDP) was employed to prepare polyaniline (PANI)/MXene (MX) composites. MXene served as a two-dimensional structure template. Due to supramolecular interactions, CDP could be controllably modified with PANI layers, effectively preventing the self-polymerization of PANI. As a result, this integration facilitated a more uniform growth of PANI on MXene and further improved the capacitance performance of CDP-MX/PA. In a three-electrode system, the specific capacitance of MX/PA at 1 A g-1 was 460.8 F g-1, which increased to 523.8 F g-1 after CDP-induced growth. CDP-MX/PA exhibited a high energy density of 27.7 W h kg-1 at a power density of 700 W kg-1. This suggests that the synthetic strategy employed in this study holds promise in providing robust support for the preparation of high-performance energy-storage device.
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MOTIVATION: The crisis of antibiotic resistance, which causes antibiotics used to treat bacterial infections to become less effective, has emerged as one of the foremost challenges to public health. Identifying the properties of antibiotic resistance genes (ARGs) is an essential way to mitigate this issue. Although numerous methods have been proposed for this task, most of these approaches concentrate solely on predicting antibiotic class, disregarding other important properties of ARGs. In addition, existing methods for simultaneously predicting multiple properties of ARGs fail to account for the causal relationships among these properties, limiting the predictive performance. RESULTS: In this study, we propose a causality-guided framework for annotating properties of ARGs, in which causal inference is utilized for representation learning. More specifically, the hidden biological patterns determining the properties of ARGs are described by a Gaussian Mixture Model, and procedure of causal representation learning is used to derive the hidden features. In addition, a causal graph among different properties is constructed to capture the causal relationships among properties of ARGs, which is integrated into the task of annotating properties of ARGs. The experimental results on a real-world dataset demonstrate the effectiveness of the proposed framework on the task of annotating properties of ARGs. AVAILABILITY AND IMPLEMENTATION: The data and source codes are available in GitHub at https://github.com/David-WZhao/CausalARG.
Subject(s)
Anti-Bacterial Agents , Genes, Bacterial , Anti-Bacterial Agents/pharmacology , Drug Resistance, Microbial/genetics , SoftwareABSTRACT
Ischemic strokes, prevalence and impactful, underscore the necessity of advanced research models closely resembling human physiology. Our study utilizes nonhuman primates (NHPs) to provide a detailed exploration of ischemic stroke, integrating neuroimaging data, behavioral outcomes, and serum proteomics to elucidate the complex interplay of factors involved in stroke pathophysiology. We observed a consistent pattern in infarct volume, peaking at 1-month postmiddle cerebral artery occlusion (MCAO) and then stabilized. This pattern was strongly correlated to notable changes in motor function and working memory performance. Using diffusion tensor imaging (DTI), we detected significant alterations in fractional anisotropy (FA) and mean diffusivity (MD) values, signaling microstructural changes in the brain. These alterations closely correlated with the neurological and cognitive deficits that we observed, highlighting the sensitivity of DTI metrics in stroke assessment. Behaviorally, the monkeys exhibited a reliance on their unaffected limb for compensatory movements, a common response to stroke impairment. This adaptation, along with consistent DTI findings, suggests a significant impact of stroke on motor function and spatial perception. Proteomic analysis through MS/MS functional enrichment identified two distinct groups of proteins with significant changes post-MCAO. Notably, MMP9, THBS1, MB, PFN1, and YWHAZ were identified as potential biomarkers and therapeutic targets for ischemic stroke. Our results underscore the complex nature of stroke and advocate for an integrated approach, combining neuroimaging, behavioral studies, and proteomics, for advancing our understanding and treatment of this condition.
Subject(s)
Ischemic Stroke , Stroke , Animals , Humans , Ischemic Stroke/diagnostic imaging , Diffusion Tensor Imaging/methods , Proteomics , Tandem Mass Spectrometry , Stroke/diagnostic imaging , Neuroimaging , Primates , ProfilinsABSTRACT
Bitespiramycin, has been shown to have a therapeutic effect against respiratory tract inflammation, including a potential effect against COVID-19. A current clinical trial in China showed that bitespiramycin was an effective treatment for severe pneumonia and intracranial infection. However, there is lack of an analytical method to elucidate the distribution of bitespiramycin. In this study, a highly sensitive, rapid and reliable UPLC-MS/MS method was developed to comprehensively characterize the bitespiramycin distribution in various bio-samples, which is significantly improved upon the published work. A rapid sample preparation method was developed by using n-butanol as the solvent to extract bitespiramycin from different bio-samples. The extract was then directly analyzed by UPLC-MS/MS coupled with an alkaline-resistant column after centrifugation which avoids the time-consuming concentration process under nitrogen and redissolution. The method was employed to accurately quantify bitespiramycin and its metabolites in rat plasma, tissues, and human cerebrospinal fluid. Notably, the presence of bitespiramycin and its metabolites was identified for the first time in various rat organs including brain, testis, bladder and prostate as well as in human cerebrospinal fluid. This newly developed approach shows great promise for drug distribution assays including other antibiotics and can help elucidate the ADME of bitespiramycin.
Subject(s)
Liquid Chromatography-Mass Spectrometry , Spiramycin/analogs & derivatives , Male , Rats , Humans , Animals , Chromatography, Liquid/methods , Tandem Mass Spectrometry/methods , Chromatography, High Pressure Liquid/methodsABSTRACT
Objective: The study aims to evaluate and compare the efficacy and safety between ticagrelor and clopidogrel in acute coronary syndrome (ACS) patients undergoing percutaneous coronary intervention (PCI). Methods: We searched MEDLINE (via PubMed), Cochrane, Embase, and the Cochrane library databases for eligible citations (the last search was up to December 2021). Subgroup analyses were performed based on region, study design, dose, and single-center/multicenter. Meta regressions were conducted to explore the source of heterogeneity. A sensitivity analysis was conducted to assess the robustness of the results. Funnel plots and Egger's test were preformed to test publication bias of the meta-analysis. Results: A total of 29 studies were included, totaling 165,981 patients. Ticagrelor reduced the overall incidence rate of major adverse cardiovascular events (MACEs) (HR 0.74; 95% CI, 0.62, 0.89; P = 0.001; I2 = 88.3%, P < 0.001) and all-cause mortality (HR 0.85; 95% CI, 0.75, 0.97; P = 0.019; I2 = 39.7%, P = 0.052) compared with clopidogrel. However, there was a higher risk of major bleeding (HR 1.21; 95% CI, 1.02,1.44; P = 0.026, I2 = 59.3%, P = 0.012) and all bleeding (HR 1.42; 95% CI, 1.24, 1.62; P < 0.001, I2 = 76.4%, P < 0.001) with ticagrelor compared to clopidogrel. The stability of the results was demonstrated by sensitivity analysis. Furthermore, subgroup analyses and meta-regression revealed that the heterogeneity in the study may stem from factors such as whether it was conducted in a single-center or multicenter setting, as well as the geographical region. Conclusion: Ticagrelor has demonstrated superior efficacy compared to clopidogrel in ACS patients undergoing PCI, particularly in Asia and Europe. Nevertheless, it is crucial to acknowledge that the utilization of ticagrelor is linked to a heightened risk of bleeding. To provide guidance for clinical decision-making regarding the use of ticagrelor, future multicenter randomized trials that are relevant and encompass longer follow-up periods are necessary. The category of the manuscript a meta-analysis: PROSPERO registration number CRD42021274198.