BACKGROUND: The absence of clinically-validated biomarkers or objective protocols hinders effective major depressive disorder (MDD) diagnosis. Compared to healthy control (HC), MDD exhibits anomalies in plasma protein levels and neuroimaging presentations. Despite extensive machine learning studies in psychiatric diagnosis, a reliable tool integrating multi-modality data is still lacking. METHODS: In this study, blood samples from 100 MDD and 100 HC were analyzed, along with MRI images from 46 MDD and 49 HC. Here, we devised a novel algorithm, integrating graph neural networks and attention modules, for MDD diagnosis based on inflammatory cytokines, neurotrophic factors, and Orexin A levels in the blood samples. Model performance was assessed via accuracy and F1 value in 3-fold cross-validation, comparing with 9 traditional algorithms. We then applied our algorithm to a dataset containing both the aforementioned protein quantifications and neuroimages, evaluating if integrating neuroimages into the model improves performance. RESULTS: Compared to HC, MDD showed significant alterations in plasma protein levels and gray matter volume revealed by MRI. Our new algorithm exhibited superior performance, achieving an F1 value and accuracy of 0.9436 and 94.08 %, respectively. Integration of neuroimaging data enhanced our novel algorithm's performance, resulting in an improved F1 value and accuracy, reaching 0.9543 and 95.06 %. LIMITATIONS: This single-center study with a small sample size requires future evaluations on a larger test set for improved reliability. CONCLUSIONS: In comparison to traditional machine learning models, our newly developed MDD diagnostic model exhibited superior performance and showed promising potential for inclusion in routine clinical diagnosis for MDD.
Drug resistance in tumor cells remains a persistent clinical challenge in the pursuit of effective anticancer therapy. XIAP, a member of the inhibitor of apoptosis protein (IAP) family, suppresses apoptosis via its Baculovirus IAP Repeat (BIR) domains and is responsible for drug resistance in various human cancers. Therefore, XIAP has attracted significant attention as a potential therapeutic target. However, no XIAP inhibitor is available for clinical use to date. In this study, we surprisingly observed that arsenic trioxide (ATO) induced a rapid depletion of XIAP in different cancer cells. Mechanistic studies revealed that arsenic attacked the cysteine residues of BIR domains and directly bound to XIAP, resulting in the release of zinc ions from this protein. Arsenic-XIAP binding suppressed the normal anti-apoptosis functions of BIR domains, and led to the ubiquitination-dependent degradation of XIAP. Importantly, we further demonstrate that arsenic sensitized a variety of apoptosis-resistant cancer cells, including patient-derived colon cancer organoids, to the chemotherapy drug using cisplatin as a showcase. These findings suggest that targeting XIAP with ATO offers an attractive strategy for combating apoptosis-resistant cancers in clinical practice.
BACKGROUND: Guigan longmu decoction (GGLM), a traditional Chinese medicine compound, has demonstrated efficacy in treating rapid arrhythmia clinically. Nevertheless, its mechanism of action remains elusive. This study aims to elucidate the molecular mechanism underlying the efficacy of GGLM in treating arrhythmia utilizing non-targeted metabolomics, widely-targeted metabolomics, and network pharmacology, subsequently validated through animal experiments. METHODS: Initially, network pharmacology analysis and widely-targeted metabolomics were performed on GGLM. Subsequent to that, rats were administered GGLM intervention, and nontargeted metabolomics assays were utilized to identify metabolites in rat plasma postadministration. The primary signaling pathways, core targets, and key active ingredients of GGLM influencing arrhythmia were identified. Additionally, to validate the therapeutic efficacy of GGLM on arrhythmia rat models, a rat model of rapid arrhythmia was induced via subcutaneous injection of isoproterenol, and alterations in pertinent pathogenic pathways and proteins in the rat model were assessed through qRT-PCR and Western blot following GGLM administration. RESULTS: The results of network pharmacology showed that 99 active ingredients in GGLM acted on 249 targets and 201 signaling pathways, which may be key to treating arrhythmia. Widelytargeted metabolic quantification analysis detected a total of 448 active ingredients in GGLM, while non-targeted metabolomics identified 279 different metabolites and 10 major metabolic pathways in rats. A comprehensive analysis of the above results revealed that the core key active ingredients of GGLM in treating arrhythmia include calycosin, licochalcone B, glabridin, naringenin, medicarpin, formononetin, quercetin, isoliquiritigenin, and resveratrol. These active ingredients mainly act on the relevant molecules and proteins upstream and downstream of the MAPK pathway to delay the onset of arrhythmia. Animal experimental results showed that the heart rate of rats in the model group increased significantly, and the mRNA and protein expression of p38, MAPK, JNK, ERK, NF-kb, IL-1ß, and IL-12 in myocardial tissue also increased significantly. However, after intervention with GGLM, the heart rate of rats in the drug group decreased significantly, while the mRNA and protein expression of p38 MAPK, JNK, ERK1, NF-kb, IL-1ß, and IL-12 in myocardial tissue decreased significantly. CONCLUSION: GGLM, as an adjunctive therapy in traditional Chinese medicine, exhibits favorable therapeutic efficacy against arrhythmia. This can be attributed to the abundant presence of bioactive compounds in the formulation, including verminin, glycyrrhizin B, glabridine, naringenin, ononin, quercetin, isorhamnetin, and kaempferol. The metabolites derived from these active ingredients have the potential to mitigate myocardial inflammation and decelerate heart rate by modulating the expression of proteins associated with the MAPK signaling pathway in vivo.
Consuming a high-fat diet (HFD) is widely recognized to cause obesity and result in chronic brain inflammation that impairs cognitive function. Repetitive transcranial magnetic stimulation (rTMS) has shown effectiveness in both weight loss and cognitive improvement, although the exact mechanism is still unknown. Our study examined the effects of rTMS on the brain and intestinal microecological dysfunction. rTMS successfully reduced cognitive decline caused by an HFD in behavioral assessments involving the Y maze and novel object recognition. This was accompanied by an increase in the number of new neurons and the transcription level of genes related to synaptic plasticity (spindlin 1, synaptophysin, and postsynaptic protein-95) in the hippocampus. It was reached that rTMS decreased the release of high mobility group box 1, activation of microglia, and inflammation in the brains of HFD rats. rTMS also reduced hypothalamic hypocretin levels and improved peripheral blood lipid metabolism. In addition, rTMS recovered the HFD-induced gut microbiome imbalances, metabolic disorders, and, in particular, reduced levels of the microvirus. Our research emphasized that rTMS enhanced cognitive abilities, resulting in positive impacts on brain inflammation, neurodegeneration, and the microbiota in the gut, indicating the potential connection between the brain and gut, proposing that rTMS could be a new approach to addressing cognitive deficits linked to obesity.
Background: Oxidative stress plays a significant role in the pathogenesis of many retinal diseases. However, only a few systematic bibliometric studies have been conducted. This study aims to visualize research hotspots and developmental trends in oxidative stress in the retina from 2013 to 2023 by analyzing bibliometric data. Methods: We retrieved papers on oxidative stress in the retina published between 2013 and 2023 from the Web of Science Core Collection. The data were visually analyzed using CiteSpace and VOSviewer software. Results: The total number of 2100 publications were included in the analysis. An overall increasing trend in the number of publications is observed between 2013 and 2023. Chinese publications were the most contributive, but United States publications were the most influential. Shanghai Jiao Tong University was the most active and prolific institution. Antioxidants was the most productive journal, while Oxidative Medicine and Cellular Longevity were the journals with the most-cited articles. Kaarniranta K, from Finland, was the most productive and influential author. Examination of co-cited references revealed that researchers in the field are primarily focused on investigating the molecular mechanisms, preventive strategies, and utilization of antioxidants to address retinal oxidative damage. Diabetic retinopathy, endothelial growth factor, retinitis pigmentosa, retinal degeneration, antioxidant response, retinal ganglion cells, and genes are the research hotspots in this field. Metabolism, sodium iodate, and system are at the forefront of research in this field. Conclusion: Attention toward retinal oxidative stress has increased over the past decade. Current research focuses on the mechanisms of retinal diseases related to oxidative stress and the experimental study of antioxidants in retinal diseases, which may continue to be a trend in the future.
Numerous advanced and lightweight signal processing methods have been presented for single-channel speech enhancement (SE). It is imperative to carefully explore how to efficiently combine, integrate, and balance these methods. This paper proposes a more effective and less resource-intensive SE system, focused on the integration and adaptation of several approaches, especially the temporal cepstrum smoothing (TCS). First, a more robust fundamental frequency estimator is employed within TCS, mitigating the performance limitations caused by the inaccuracy of the original estimator. Additionally, a harmonic enhancement mechanism is introduced, effectively recovering the weak harmonic components. By incorporation of the modified TCS in the a posteriori speech presence probability estimation, the unbiased minimum mean square error noise power spectral density estimator can be refined. The modified TCS is also utilized for the a priori signal-to-noise ratio estimation. Moreover, this paper enhances the log-spectral amplitude estimator by applying both super-Gaussian speech priors and speech presence uncertainty for further improvement. Experimental evaluations demonstrate that the proposed method yields an improvement in speech quality while maintaining modest computational and storage requirements. Furthermore, the proposed system exhibits comparable performance to several baseline systems based on lightweight deep neural networks.
To investigate the utility of serum bile acid profiling for the diagnosis of inflammatory bowel disease (IBD). We analyzed 15 specific bile acids in the serum of 269 IBD patients, 200 healthy controls (HC), and 174 patients with other intestinal diseases (OID) using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Serum bile acid levels were compared between IBD group, HC group, and OID group. Binary logistic regression-based models were developed to model the bile acids and diagnose IBD. Furthermore, receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic accuracy of each bile acid and the model. Compared to HC group, IBD group exhibited significantly lower levels of chenodeoxycholic acid (CDCA), deoxycholic acid (DCA), glycodeoxycholic acid (GDCA), taurodeoxycholic acid (TDCA), lithocholic acid (LCA), glycolithocholic acid (GLCA), taurolithocholic acid (TLCA), and an elevated primary-to-secondary bile acid ratio. DCA had an area under the curve (AUC) of 0.860 for diagnosing IBD, with a sensitivity of 80.67% and a specificity of 82.50%. A model Y0 combining DCA and CDCA to distinguish between IBD group and HC group further improved accuracy (AUCâ =â 0.866, sensitivityâ =â 76.28%, specificityâ =â 89.37%). Compared to non-IBD group (which combined healthy controls and those with other intestinal diseases), IBD group had significantly lower levels of DCA, GDCA, TDCA, LCA, GLCA, and TLCA, and elevated levels of glycocholic acid (GCA) and glycochenodeoxycholic acid (GCDCA). A model Y1 incorporating GCDCA, DCA and TLCA to distinguish between IBD group and non-IBD group yielded an AUC of 0.792, with a sensitivity of 77.67% and specificity of 71.91%. IBD patients exhibit decreased serum secondary bile acid levels and an elevated primary-to-secondary bile acid ratio. Serum bile acid alterations are associated with the onset of IBD. A model consisting of CDCA and DCA has potential for distinguishing between IBD group and HC group, while a model incorporating GCDCA, DCA and TLCA may be suitable for distinguishing between IBD group and non-IBD group.
Bile Acids and Salts , Inflammatory Bowel Diseases , Humans , Bile Acids and Salts/blood , Male , Female , Inflammatory Bowel Diseases/diagnosis , Inflammatory Bowel Diseases/blood , Adult , Middle Aged , Sensitivity and Specificity , ROC Curve , Case-Control Studies , Tandem Mass Spectrometry/methods , Chromatography, Liquid , Biomarkers/blood , Young Adult
RNA editing, as an epigenetic mechanism, exhibits a strong correlation with the occurrence and development of cancers. Nevertheless, few studies have been conducted to investigate the impact of RNA editing on cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC). In order to study the connection between RNA editing and CESC patients' prognoses, we obtained CESC-related information from The Cancer Genome Atlas (TCGA) database and randomly allocated the patients into the training group or testing group. An RNA editing-based risk model for CESC patients was established by Cox regression analysis and least absolute shrinkage and selection operator (LASSO). According to the median score generated by this RNA editing-based risk model, patients were categorized into subgroups with high and low risks. We further constructed the nomogram by risk scores and clinical characteristics and analyzed the impact of RNA editing levels on host gene expression levels and adenosine deaminase acting on RNA. Finally, we also compared the biological functions and pathways of differentially expressed genes (DEGs) between different subgroups by enrichment analysis. In this risk model, we screened out 6 RNA editing sites with significant prognostic value. The constructed nomogram performed well in forecasting patients' prognoses. Furthermore, the level of RNA editing at the prognostic site exhibited a strong correlation with host gene expression. In the high-risk subgroup, we observed multiple biological functions and pathways associated with immune response, cell proliferation, and tumor progression. This study establishes an RNA editing-based risk model that helps forecast patients' prognoses and offers a new understanding of the underlying mechanism of RNA editing in CESC.
Nomograms , RNA Editing , Uterine Cervical Neoplasms , Humans , Uterine Cervical Neoplasms/genetics , Female , RNA Editing/genetics , Prognosis , Risk Assessment/methods , Middle Aged , Carcinoma, Squamous Cell/genetics , Adenocarcinoma/genetics , Adenosine Deaminase/genetics
Speech comprehension in noise depends on complex interactions between peripheral sensory and central cognitive systems. Despite having normal peripheral hearing, older adults show difficulties in speech comprehension. It remains unclear whether the brain's neural responses could indicate aging. The current study examined whether individual brain activation during speech perception in different listening environments could predict age. We applied functional near-infrared spectroscopy to 93 normal-hearing human adults (20 to 70 years old) during a sentence listening task, which contained a quiet condition and 4 different signal-to-noise ratios (SNR = 10, 5, 0, -5 dB) noisy conditions. A data-driven approach, the region-based brain-age predictive modeling was adopted. We observed a significant behavioral decrease with age under the 4 noisy conditions, but not under the quiet condition. Brain activations in SNR = 10 dB listening condition could successfully predict individual's age. Moreover, we found that the bilateral visual sensory cortex, left dorsal speech pathway, left cerebellum, right temporal-parietal junction area, right homolog Wernicke's area, and right middle temporal gyrus contributed most to prediction performance. These results demonstrate that the activations of regions about sensory-motor mapping of sound, especially in noisy conditions, could be sensitive measures for age prediction than external behavior measures.
Aging , Brain , Comprehension , Noise , Spectroscopy, Near-Infrared , Speech Perception , Humans , Adult , Speech Perception/physiology , Male , Female , Spectroscopy, Near-Infrared/methods , Middle Aged , Young Adult , Aged , Comprehension/physiology , Brain/physiology , Brain/diagnostic imaging , Aging/physiology , Brain Mapping/methods , Acoustic Stimulation/methods
Multiple Sclerosis (MS) is an immune-mediated condition that persistently harms the central nervous system. While existing treatments can slow its course, a cure remains elusive. Stem cell therapy has gained attention as a promising approach, offering new perspectives with its regenerative and immunomodulatory properties. This article reviews the application of stem cells in MS, encompassing various stem cell types, therapeutic potential mechanisms, preclinical explorations, clinical research advancements, safety profiles of clinical applications, as well as limitations and challenges, aiming to provide new insights into the treatment research for MS.
Serum B-cell maturation antigen (sBCMA) levels can serve as a sensitive biomarker in multiple myeloma (MM). In the research setting, sBCMA levels can be accurately detected by enzyme-linked immunosorbent assay (ELISA), but the approach has not been approved for clinical use. Here, we used a novel chemiluminescence method to assess sBCMA levels in 759 serum samples from 17 healthy donors and 443 patients with plasma cell (PC) diseases including AL amyloidosis, POEMS syndrome and MM. Serum BCMA levels were elevated 16.1-fold in patients with newly diagnosed MM compared to healthy donors and rare PC diseases patients. Specifically, the sBCMA levels in patients with progressive disease were 64.6-fold higher than those who showed partial response or above to treatment. The sBCMA level also correlated negatively with the response depth of MM patients. In newly diagnosed and relapsed MM patients, survival was significantly longer among those subjects whose sBCMA levels are below the median levels compared with those above the median value. We optimized the accuracy of the survival prediction further by integrating sBCMA level into the Second Revised International Staging System (R2-ISS). Our findings provide evidence that the novel chemiluminescence method is sensitive and practical for measuring sBCMA levels in clinical samples and confirm that sBCMA might serve as an independent prognostic biomarker for MM.
Establishing an advanced ecosystem incorporating freshwater harvesting, plastic utilization, and clean fuel acquisition is profoundly significant. However, low-efficiency evaporation, single energy utilization, and catalyst leakage severely hinder sustainable development. Herein, a nanofiber-based mortise-and-tenon structural Janus aerogel (MTSJA) is strategically designed in the first attempt and supports Z-scheme catalysts. By harnessing of the upper hydrophilic layer with hydrophilic channels embedding into the hydrophobic bottom layer to achieve tailoring bottom wettability states. MTSJA is capable of a fully-floating function for lower heat loss, water supply, and high-efficiency solar-to-vapor conversion. Benefiting from the ultrasonic cavitation effect and high sensitivity of materials to mechanical forces, this is also the first demonstration of synergistic solar and ultrasound fields to power simultaneous evaporation desalination and waste plastics as reusable substrates generating fuel energy. The system enables persistent desalination with an exceptional evaporation rate of 3.1 kg m-2 h-1 and 82.3% efficiency (21 wt.% NaCl solution and 1 sun), and realizes H2, CO, and CH4 yields with 16.1, 9.5, and 3 µmol h-1 g-1, respectively. This strategy holds great potential for desalination and plastics value-added transformation toward clean energy and carbon neutrality.
Forest soils are a critical component of terrestrial ecosystems and host a large number of animal decomposer species. One diverse and abundant decomposer taxon is oribatid mites (Acari: Oribatida), whose species composition varies with forest type and tree species composition. We used functional traits that indicate different niche dimensions, to infer assembly processes of oribatid mite communities in monocultures and mixed forests of native and introduced tree species. We found that coexisting species differed more in the resource-related niche dimension, i.e., reproductive mode and trophic guild, than in the morphological dimension, e.g., body length and width, sclerotization and concealability. These results suggest that both filtering and partitioning processes structure oribatid mite communities. In native European beech forests, but not in non-native Douglas fir forests, oribatid mites were mainly structured by filtering processes acting via traits related both to environmental tolerance and to resources. Furthermore, oribatid mite trait diversity, but not phylogenetic diversity, differed significantly between monocultures and mixed forests, demonstrating that multidimensional diversity indices provide additional information on soil biodiversity. Overall, the study provides evidence that traits representing different niche dimensions need to be considered for understanding assembly processes in soil animal communities and thereby soil biodiversity.
Glutamic acid decarboxylase antibody (GADAb) has emerged as a significant biomarker for clinical diagnosis and prognosis in type 1 diabetes (T1D). In this study, we investigated the potential utilization of glass capillary solid-state nanopores as a cost-effective and easily preparable platform for the detection of individual antigens, antibodies, and antigen-antibody complexes without necessitating any modifications to the nanopores. Our findings revealed notable characteristic variations in the translocation events of glutamic acid decarboxylase (GAD65) through nanopores under different voltage conditions, discovered that anomalous phenomenon of protein translocation events increasing with voltage may potentially be caused by the crowding of multiple proteins in the nanopores, and demonstrated that there are multiple components in the polyclonal antibodies (GADAb-poly). Furthermore, we achieved successful differentiation between GAD65, GADAb, and GADAb-GAD65 complexes. These results offer promising prospects for the development of a rapid and reliable GADAb detection method, which holds the potential to be applied in patient serum samples, thereby facilitating a label-free, cost-effective, and early diagnosis of type I diabetes.
Diabetes Mellitus, Type 1 , Glutamate Decarboxylase , Nanopores , Glutamate Decarboxylase/immunology , Humans , Diabetes Mellitus, Type 1/diagnosis , Biosensing Techniques , Antibodies , Glass
Epidemiological data is scarce regarding the association between exposure to mixtures of per- and polyfluoroalkyl substances (PFASs) and liver injury in the general populace. The current research used data from the National Health and Nutrition Examination Survey (2009-2018). The PFAS exposure levels were defined by the serum concentrations of PFASs with > 70% detection in samples, namely perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorohexane sulfonic acid (PFHxS), perfluorodecanoic acid (PFDeA), and perfluorooctane sulfonic acid (PFOS). Liver injury was assessed from two aspects: first, the degree of liver inflammation was determined based on serum alanine aminotransferase (ALT), aspartate aminotransferase (AST), glutamyltransferase (GGT), and total bilirubin (TBIL) levels; second, the degree of liver fibrosis was determined based on fibrosis-4 (FIB-4) index. We assessed the associations between individual or total PFAS exposure and these outcomes using multivariable linear regression models and logistic regression models, restricted cubic splines, and weighted quantile sum regression. Among the samples of 7484 American adults, the median concentration of PFOS was the highest, followed by PFOA and PFHxS. Using multivariable linear regression, a positive correlation was observed between all PFASs and liver enzymes such as ALT, AST, and TBIL. Additionally, the weighted quantile sum model indicated an overall positive association between the five PFASs and liver injury indicators. For liver function biomarkers and liver fibrosis, PFNA and PFOS were the most heavily weighting chemicals, respectively. Our findings provide new epidemiological evidence indicating a potential association between PFAS exposure and adverse effects on liver injury biomarkers, highlighting the potentially harmful effects of PFAS exposure on liver health.
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational speed. This study introduces a novel "divide- and-conquer" parallel algorithm built on the Wasserstein posterior approximation concept, aiming to enhance computational speed while maintaining accurate parameter estimation. This algorithm enables drawing parameters from segmented data subsets in parallel, followed by an amalgamation of these parameters via Wasserstein posterior approximation. Theoretical support for the algorithm is established through asymptotic optimality under certain regularity assumptions. Practical validation is demonstrated using real-world data from the Programme for International Student Assessment. Ultimately, this research proposes a transformative approach to managing educational big data, offering a scalable, efficient, and precise alternative that promises to redefine traditional practices in educational assessments.
Rice husks are rich in xylan, which can be hydrolyzed by xylanase to form xylooligosaccharides (XOS). XOS are a functional oligosaccharide such as improving gut microbiota and antioxidant properties. In this study, the structure and functional characteristics of XOS were studied. The optimal xylanase hydrolysis conditions through response surface methodology (RSM) were: xylanase dosage of 3000â¯U/g, hydrolysis time of 3â¯h, hydrolysis temperature of 50⯰C. Under this condition, the yield of XOS was 150.9â¯mg/g. The TG-DTG curve showed that XOS began to decompose at around 200⯰C. When the concentration of XOS reached 1.0â¯g/L, the clearance rate of DPPH reached 65.76â¯%, and the scavenging rate of OH reached 62.10â¯%, while the clearance rate of ABTS free radicals reached 97.70â¯%, which was equivalent to the clearance rate of VC. XOS had a proliferative effect on four probiotics: Lactobacillus plantarum, Lactobacillus brucelli, Lactobacillus acidophilus, and Lactobacillus rhamnosus. However, the further experiments are needed to explore the improvement effect of XOS on human gut microbiota, laying a foundation for the effective utilization of XOS. XOS have a wide range of sources, low price, and broad development prospects. The reasonable utilization of XOS can bring greater economic benefits.
Buttermilk is a potential material for the production of a milk fat globule membrane (MFGM) and can be mainly classified into two types: whole cream buttermilk and cheese whey cream buttermilk (WCB). Due to the high casein micelle content of whole cream buttermilk, the removal of casein micelles to improve the purity of MFGM materials is always required. This study investigated the effects of rennet and acid coagulation on the lipid profile of buttermilk rennet-coagulated whey (BRW) and buttermilk acid-coagulated whey (BAW) and compared them with WCB. BRW has significantly higher phospholipids (PLs) and ganglioside contents than BAW and WCB. The abundance of arachidonic acid (ARA)- and eicosapentaenoic acid (EPA)-structured PLs was higher in WCB, while docosahexaenoic acid (DHA)-structured PLs were higher in BRW, indicating that BRW and WCB intake might have a greater effect on improving cardiovascular conditions and neurodevelopment. WCB and BRW had a higher abundance of plasmanyl PL and plasmalogen PL, respectively. Phosphatidylcholine (PC) (28:1), LPE (20:5), and PC (26:0) are characteristic lipids among BRW, BAW, and WCB, and they can be used to distinguish MFGM-enriched whey from different sources.
Buttermilk , Cheese , Goats , Lipidomics , Whey , Animals , Buttermilk/analysis , Cheese/analysis , Whey/chemistry , Phospholipids/analysis , Phospholipids/chemistry , Glycolipids/chemistry , Milk/chemistry , Lipid Droplets/chemistry , Glycoproteins/chemistry , Glycoproteins/analysis , Lipids/chemistry , Lipids/analysis
Background: Levels of self-awareness may affect the decision-making ability of clinical nurses and may also be related to mental health. Therefore, it is crucial to develop tools to identify nurses' level of self-awareness. The purpose of this study was to investigate the reliability and validity of a short scale among Chinese nurses and to explore the factors associated with nurses' self-awareness. Methods: A total of 957 participants were recruited, 549 participants were used for reliability tests and 408 subjects were used for impact factor studies. They completed the General Information Questionnaire, the Self-Awareness Scale for Nurses, and the Psychological Distress Scale. Exploratory factor analysis, confirmatory factor analysis, Cronbach's alpha, and retest reliability were used to investigate the psychometric properties of the Self-Awareness Scale for Nurses. Multiple regression analyses were used in this study to investigate the relationship between nurses' self-awareness and the independent variables. Results: A 4-factor model of the Chinese version of the Self-Awareness Scale for Nurses was validated. The overall Cronbach's alpha value for the Chinese version of the Self-Awareness Scale for Nurses was 0.873. Cronbach's alpha values for each subscale ranged from 0.808 to 0.979. Significant predictors of each dimension of the Self-awareness and the total score of the scale were age and work experience. Conclusion: The Chinese version of the Self-Awareness Scale for Nurses is a valid and reliable scale.
Nurses , Psychometrics , Humans , Female , Male , Adult , Reproducibility of Results , Surveys and Questionnaires , China , Nurses/psychology , Middle Aged , Factor Analysis, Statistical , Awareness , Translations
Hand, Foot and Mouth Disease (HFMD) is a highly contagious viral illness primarily affecting children globally. A significant epidemiological transition has been noted in mainland China, characterized by a substantial increase in HFMD cases caused by non-Enterovirus A71 (EV-A71) and non-Coxsackievirus A16 (CVA16) enteroviruses (EVs). Our study conducts a retrospective examination of 36,461 EV-positive specimens collected from Guangdong, China, from 2013 to 2021. Epidemiological trends suggest that, following 2013, Coxsackievirus A6 (CVA6) and Coxsackievirus A10 (CVA10) have emerged as the primary etiological agents for HFMD. In stark contrast, the incidence of EV-A71 has sharply declined, nearing extinction after 2018. Notably, cases of CVA10 infection were considerably younger, with a median age of 1.8 years, compared to 2.3 years for those with EV-A71 infections, possibly indicating accumulated EV-A71-specific herd immunity among young children. Through extensive genomic sequencing and analysis, we identified the N136D mutation in the 2 A protein, contributing to a predominant subcluster within genogroup C of CVA10 circulating in Guangdong since 2017. Additionally, a high frequency of recombination events was observed in genogroup F of CVA10, suggesting that the prevalence of this lineage might be underrecognized. The dynamic landscape of EV genotypes, along with their potential to cause outbreaks, underscores the need to broaden surveillance efforts to include a more diverse spectrum of EV genotypes. Moreover, given the shifting dominance of EV genotypes, it may be prudent to re-evaluate and optimize existing vaccination strategies, which are currently focused primarily target EV-A71.
Genome, Viral , Genotype , Hand, Foot and Mouth Disease , Phylogeny , China/epidemiology , Humans , Hand, Foot and Mouth Disease/epidemiology , Hand, Foot and Mouth Disease/virology , Child, Preschool , Infant , Retrospective Studies , Female , Male , Child , Molecular Epidemiology , Enterovirus/genetics , Enterovirus/classification , Enterovirus/isolation & purification , Enterovirus A, Human/genetics , Enterovirus A, Human/isolation & purification , Genomics , Incidence , Adolescent , Enterovirus Infections/epidemiology , Enterovirus Infections/virology
