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Abstract Background Family caregivers (FCs) encounter a variety of health problems in older people with chronic illness, necessitating a certain level of health literacy to access, understand, appraise and apply health information and services. This study aimed to develop and validate a scale for measuring health literacy among FCs of older people with chronic illness. Methods Concept mapping was first employed to develop a conceptual model of health literacy of FCs. Scale domains were derived from the conceptual model, and item generation was performed using deductive and inductive methods. Quantitative methods, including merging scale dimensions and items, expert reviews, cognitive interviews, and item reduction analysis, were used to refine the scale. Confirmatory factor analysis was employed to validate the scale’s structure. Concurrent validity, internal consistency, and test-retest reliability were also examined. Results A 20-dimension conceptual model was developed, and 60 items were generated for the scale. Expert review (content validity index > 0.85) and cognitive interview with FCs confirmed the relevance and clarity of the majority of the generated scale items. Confirmatory factor analysis with 451 FCs of older people with chronic illness supported a 5-factor structure (symptom management, daily personal care and household tasks, care coordination, communication and relationship with the care recipient, and self-care of caregivers) with 42 finalized scale items, including four levels of health literacy skills (accessing, understanding, appraising and applying health information). Concurrent validity with the European Health Literacy Questionnaire (HLS-EU-Q47) was satisfactory (r = 0.67, p

The simultaneous administration of antibacterial treatment and acceleration of tissue regeneration are crucial for the effective healing of infected wounds. In this work, we developed a facile hydrogel (PCC hydrogel) through coordination and hydrogen interactions by polymerizing acrylamide monomers in the presence of carboxymethyl chitosan nanoparticles and copper ions. The prepared PCC hydrogel demonstrated effective bacterial capture from wound exudation and exhibited a potent bactericidal activity against methicillin-resistant Staphylococcus aureus (MRSA) and Pseudomonas aeruginosa. Furthermore, slow release of copper ions from the hydrogel facilitated wound healing by promoting cell migration, collagen deposition and angiogenesis. Additionally, the PCC hydrogel possessed excellent biocompatibility and hemostatic properties. The practical effectiveness of PCC hydrogel in addressing bacterial infections and facilitating wound healing was verified using a mouse model of MRSA-induced wound infections. Overall, this work presents a simple yet efficient multifunctional hydrogel platform that integrates antibacterial activity, promotion of wound healing, and hemostasis for managing bacteria-associated wounds.

Mg-based hydrides are too stable and the kinetics of hydrogen absorption and desorption is not satisfactory. An efficient way to improve these shortcomings is to employ reactive ball milling to synthesize the nanocomposite materials of Mg and additives. In this experiment, TiF3 was selected as an additive, and the mechanical milling method was employed to prepare the experimental alloys. The alloys used in this experiment were the as-cast Ce5Mg85Ni10, as-milled Ce5Mg85Ni10 and Ce5Mg85Ni10 + 3 wt.% TiF3. The phase transformation, structural evolution, isothermal and non-isothermal hydrogenation and dehydrogenation performances of the alloys were inspected by XRD, SEM, TEM, Sievert apparatus, DSC and TGA. It revealed that nanocrystalline appeared in the as-milled samples. Compared with the as-cast alloy, ball milling made the particle dimension and grain size decrease dramatically and the defect density increase significantly. The addition of TiF3 made the surface of ball milling alloy particles markedly coarser and more irregular. Ball milling and adding TiF3 distinctly improved the activation and kinetics of the alloys. Moreover, ball milling along with TiF3 can decrease the onset dehydrogenation temperature of Mg-based hydrides and slightly ameliorate their thermodynamics.

Nuclear export of the viral ribonucleoprotein (vRNP) is a critical step in the influenza A virus (IAV) life cycle and may be an effective target for the development of anti-IAV drugs. The host factor ras-related nuclear protein (RAN) is known to participate in the life cycle of several viruses, but its role in influenza virus replication remains unknown. In the present study, we aimed to determine the function of RAN in influenza virus replication using different cell lines and subtype strains. We found that RAN is essential for the nuclear export of vRNP, as it enhances the binding affinity of XPO1 toward the viral nuclear export protein NS2. Depletion of RAN constrained the vRNP complex in the nucleus and attenuated the replication of various subtypes of influenza virus. Using in silico compound screening, we identified that bepotastine could dissociate the RAN-XPO1-vRNP trimeric complex and exhibit potent antiviral activity against influenza virus both in vitro and in vivo. This study demonstrates the important role of RAN in IAV replication and suggests its potential use as an antiviral target.

ABSTRACT Candida albicans (C. albicans) and Lactiplantibacillus plantarum subsp. plantarum (L. plantarum) are frequently identified in various niches, but their dual-species interaction, especially with C. albicans in yeast form, remains unclear. This study aimed to investigate the dual-species interaction of L. plantarum and C. albicans, including proliferation, morphology, and transcriptomes examined by selective agar plate counting, microscopy, and polymicrobial RNA-seq, respectively. Maintaining a stable and unchanged growth rate, L. plantarum inhibited C. albicans yeast cell proliferation but not hyphal growth. Combining optical microscopy and atomic force microscopy, cell-to-cell direct contact and co-aggregation with L. plantarum cells surrounding C. albicans yeast cells were observed during dual-species interaction. Reduced C. albicans yeast cell proliferation in mixed culture was partially due to L. plantarum cell-free culture supernatant but not the acidic environment. Upon polymicrobial transcriptomics analysis, interesting changes were identified in both L. plantarum and C. albicans gene expression. First, two L. plantarum quorum-sensing systems showed contrary changes, with the activation of lamBDCA and repression of luxS. Second, the upregulation of stress response-related genes and downregulation of cell cycle, cell survival, and cell integrity-related pathways were identified in C. albicans, possibly connected to the stress posed by L. plantarum and the reduced yeast cell proliferation. Third, a large scale of pathogenesis and virulence factors were downregulated in C. albicans, indicating the potential interruption of pathogenic activities by L. plantarum. Fourth, partial metabolism and transport pathways were changed in L. plantarum and C. albicans. The information in this study might aid in understanding the behavior of L. plantarum and C. albicans in dual-species interaction.IMPORTANCEThe anti-Candida albicans activity of Lactiplantibacillus plantarum has been explored in the past decades. However, the importance of C. albicans yeast form and the effect of C. albicans on L. plantarum had also been omitted. In this study, the dual-species interaction of L. plantarum and C. albicans was investigated with a focus on the transcriptomes. Cell-to-cell direct contact and co-aggregation with L. plantarum cells surrounding C. albicans yeast cells were observed. Upon polymicrobial transcriptomics analysis, interesting changes were identified, including contrary changes in two L. plantarum quorum-sensing systems and reduced cell survival-related pathways and pathogenesis determinants in C. albicans.

Introduction Prostate cancer is the most common malignant disease within the male genitourinary system. Advances in cancer screening and treatment have significantly ameliorated the survival rates of patients with prostate cancer. Nonetheless, prostate cancer survivors report various degrees of cancer-related symptoms. These symptoms cause physiological and psychological suffering, leading to a deterioration of quality of life. Web-based interventions may facilitate the management of symptoms due to their flexibility, accessibility and convenience. However, the efficacy of web-based interventions in reducing symptom burden remains to be confirmed. Consequently, this systematic review and meta-analysis aims to comprehensively synthesise existing evidence, evaluate the effectiveness of web-based interventions in reducing symptom burden among patients and furnish a reference for clinical practice.Methods and analysis This protocol strictly adheres to the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocol guidelines. We will comprehensively search six databases (PubMed, Web of Science, Cochrane, Embase, CINAHL and PsycINFO) from their inception to March 2024 in order to identify clinical trials on the efficacy of web-based interventions for prostate cancer survivors. Two reviewers will independently conduct study selection, data extraction and quality assessment. The risk bias of included studies will be assessed using the Cochrane Risk of Bias Tool for randomised trials 2.0, and the strength of evidence will be assessed using Grading of Recommendations Assessment, Development and Evaluation (GRADE) guideline. Meta-analysis will be performed using STATA V.16.0, and the effect size will be calculated using the standardised mean difference and its 95% CI. Heterogeneity will be assessed using Cochran’s Q statics and inconsistency will be measured using the I2 statistics. Potential sources of bias will be evaluated.Ethics and dissemination Ethics approval is not required for this review as no human participants will be involved. The results will be disseminated via a peer-reviewed journal or an academic conference.PROSPERO registration number CRD42023457718.

Melanoma is a malignant skin tumor that threatens human life and health. Early detection is essential for effective treatment. However, the low contrast between melanoma lesions and normal skin and the irregularity in size and shape make skin lesions difficult to detect with the naked eye in the early stages, making the task of skin lesion segmentation challenging. Traditional encoder-decoder built with U-shaped networks using convolutional neural network (CNN) networks have limitations in establishing long-term dependencies and global contextual connections, while the Transformer architecture is limited in its application to small medical datasets. To address these issues, we propose a new skin lesion segmentation network, SUTrans-NET, which combines CNN and Transformer in a parallel fashion to form a dual encoder, where both CNN and Transformer branches perform dynamic interactive fusion of image information in each layer. At the same time, we introduce our designed multi-grouping module SpatialGroupAttention (SGA) to complement the spatial and texture information of the Transformer branch, and utilize the Focus idea of YOLOV5 to construct the Patch Embedding module in the Transformer to prevent the loss of pixel accuracy. In addition, we design a decoder with full-scale information fusion capability to fully fuse shallow and deep features at different stages of the encoder. The effectiveness of our method is demonstrated on the ISIC 2016, ISIC 2017, ISIC 2018 and PH2 datasets and its advantages over existing methods are verified.

BackgroundCervical cancer (CC) is a highly malignant gynecological cancer with a direct causal link to inflammation, primarily resulting from persistent high-risk human papillomavirus (HPV) infection. Given the challenges in early detection and mid to late-stage treatment, our research aims to identify inflammation-associated immune biomarkers in CC.MethodsUsing a bioinformatics approach combined with experimental validation, we integrated two CC datasets (GSE39001 and GSE63514) in the Gene Expression Omnibus (GEO) to eliminate batch effects. Immune-related inflammation differentially expressed genes (DGEs) were obtained by R language identification.ResultsThis analysis identified 37 inflammation-related DEGs. Subsequently, we discussed the different levels of immune infiltration between CC cases and controls. Weighted gene co-expression network analysis (WGCNA) identified seven immune infiltration-related modules in CC. We identified 15 immune DEGs associated with inflammation at the intersection of these findings. In addition, we constructed a protein interaction network using the String database and screened five hub genes using "CytoHubba": CXC chemokine ligand 8 (CXCL8), CXC chemokine ligand 10 (CXCL10), CX3C chemokine receptor 1 (CX3CR1), Fc gamma receptors 3B (FCGR3B), and SELL. The expression of these five genes in CC was determined by PCR experiments. In addition, we assessed their diagnostic value and further analyzed the association of immune cells with them.ConclusionsFive inflammation- and immune-related genes were identified, aiming to provide new directions for early diagnosis and mid to late-stage treatment of CC from multiple perspectives.

Abstract Numerous studies have reported that circulating cytokines (CCs) are linked to age-related neurodegenerative diseases (ANDDs); however, there is a lack of systematic investigation for the causal association. A two-sample bidirectional Mendelian Randomisation (MR) method was utilized to evaluate the causal effect. We applied genetic variants correlated with concentrations of CCs from a genome-wide association study meta-analysis (n = 8293) as instrumental variables. Summary data of three major ANDDs [Alzheimer’s disease (AD), Parkinson’s disease (PD), and Amyotrophic lateral sclerosis (ALS)] were identified from the IEU OpenGWAS platform (n = 627, 266). Inverse-variance weighted method is the main approach to analyse causal effect, and MR results are verified by several sensitivity and pleiotropy analyses. In directional MR, it suggested that several CCs were nominally correlated with the risk of ANDDs, with a causal odds ratio (OR) of Interleukin (IL)-5 of 0.909 for AD; OR of IL-2 of 1.169 for PD; and OR of Beta nerve growth factor of 1.142 for ALS). In reverse MR, there were some suggestively causal effects of ANDDs on CCs (AD on increased Basic fibroblast growth factor and IL-12 and decreased Stem cell growth factor beta; PD on decreased Monokine induced by interferon-gamma; ALS on decreased Basic fibroblast growth factor and IL-17). The findings were stable across sensitivity and pleiotropy analyses. However, after Bonferroni correction, there is no statistically significant association between CCs and ANDDs. Through the genetic epidemiological approach, our study assessed the role and presented possible causal associations between CCs and ANDDs. Further studies are warranted to verify the causal associations.

The emergence of new coronaviruses poses a significant threat to animal husbandry and human health. Porcine epidemic diarrhea virus (PEDV) is considered a re-emerging porcine enteric coronavirus, which causes fatal watery diarrhea in piglets. Currently, there are no effective drugs to combat PEDV. Drug repurposing screens have emerged as an attractive strategy to accelerate antiviral drug discovery and development. Here, we screened 206 natural products for antiviral activity using live PEDV infection in Vero cells and identified ten candidate antiviral agents. Among them, Tubercidin, a nucleoside analog derived from Streptomyces tubercidicus, showed promising antiviral activity against PEDV infection. Furthermore, we demonstrated that Tubercidin exhibited significant antiviral activity against both classical and variant PEDV. Time of addition assay showed that Tubercidin displayed a significant inhibitory effect on viral post-entry events but not during other periods. Molecular docking analysis indicated that Tubercidin had better docking efficiency and formed hydrophobic interactions with the active pocket of RNA-dependent RNA polymerase (RdRp) of PEDV and other nidoviruses. Additionally, Tubercidin can effectively suppress other porcine nidoviruses, such as SADS-CoV and PRRSV, demonstrating its broad-spectrum antiviral properties. In summary, our findings provide valuable evidence for the antiviral activity of Tubercidin and offer insights into the development of new strategies for the prevention and treatment of coronavirus infections.

Background: Nonalcoholic steatohepatitis (NASH) has caused a significant burden on public health care systems, the economy and society. However, there has still been no officially approved pharmacotherapy for NASH. It has been suggested that oxidative stress and mitochondrial dysfunction play vital roles in NASH pathological progression. Shugan Xiaozhi (SG) formula, as a kind of classical herbal formula, was shown to attenuate NASH. Purpose: This study aimed to explore the potential mechanisms of SG formula treating NASH. Study design and methods: Ultra-high-performance liquid chromatography-high resolution mass spectrometry combined with bioinformatics analysis was applied to explore the therapeutic targets and main components of SG formula. Moreover, in vivo NASH model was utilized to confirmed the therapeutic effects of SG formula. Molecular docking analysis and further validation experiments were conducted to verify the results of bioinformatics analysis. Results: The in vivo experiments confirmed SG formula significantly attenuated hepatic pathological progression and relieved oxidative stress in high-fat diet (HFD) induced - NASH model. Ultra-high-performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) combined with bioinformatics analysis expounded the components of SG formula and revealed the mitochondrial regulation mechanism of SG formula treating NASH. Further in vivo experiments validated that SG formula could alleviate oxidative stress by rehabilitating the structure and function of mitochondria, which was strongly related to regulating mitophagy. Conclusion: In summary, this study demonstrated that SG formula, which could attenuate NASH by regulating mitochondria and might be a potential pharmacotherapy for NASH.

Abstract Background Our previous studies have confirmed that miR-154-5p can regulate pRb expression, and thus, play a tumor suppressor role in HPV16 E7-induced cervical cancer. However, its upstream molecules have not been elucidated in the progression of cervical cancer. This study aimed to explore the role of the miR-154-5p upstream molecule, hsa_circ_0000276 in cervical cancer development and its possible mechanisms of action. Methods We detected differences in whole transcriptome expression profiles of cervical squamous carcinoma and tissues adjacent to cervical cancer tissues from patients using microarray technology to predict circular RNAs (circRNAs) with binding sites to miR-154-5p. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to detect the expression of hsa_circ_0000276 (which had the strongest binding capacity to miR-154 and was selected as the target molecule) in cervical cancer tissues, followed by in vitro functional assays. Downstream microRNAs (miRNAs) and mRNAs of hsa_circ_0000276 were identified using transcriptome microarray data and databases, while the protein–protein interaction networks were obtained using STRING. A competing endogenous RNA (ceRNA) network centered on hsa_circ_0000276 was constructed using Cytoscape and GO and KEGG databases. Abnormal expression and prognosis of critical downstream molecules were analyzed using gene databases and molecular experiments. qRT-PCR and western blot analysis was performed to verify the expression of candidate genes. Results We identified 4,001 differentially expressed circRNAs between HPV16-positive cervical squamous carcinoma and benign cervical tissues and 760 circRNAs targeting miR-154-5p, including hsa_circ_0000276. hsa_circ_0000276 and miR-154-5p directly bound, and hsa_circ_0000276 was upregulated, in cervical precancerous lesions and cervical cancer tissues and cells. Silencing hsa_circ_0000276 inhibited G1/S transition and cell proliferation and promoted apoptosis in SiHa and CaSki cells. Bioinformatics analysis showed that the hsa_circ_0000276 ceRNA network included 17 miRNAs and seven mRNAs, and downstream molecules of hsa_circ_0000276 were upregulated in cervical cancer tissues. These downstream molecules were associated with a poor prognosis and affected cervical cancer-associated immune infiltration. Of these, expression of CD47, LDHA, PDIA3, and SLC16A1 was downregulated in sh_hsa_circ_0000276 cells. Conclusions Our findings show that hsa_circ_0000276 exerts cancer-promoting effects in cervical cancer and is an underlying biomarker for cervical squamous cell carcinoma.

The immense representation power of deep learning frameworks has kept them in the spotlight in hyperspectral image (HSI) classification. Graph Convolutional Neural Networks (GCNs) can be used to compensate for the lack of spatial information in Convolutional Neural Networks (CNNs). However, most GCNs construct graph data structures based on pixel points, which requires the construction of neighborhood matrices on all data. Meanwhile, the setting of GCNs to construct similarity relations based on spatial structure is not fully applicable to HSIs. To make the network more compatible with HSIs, we propose a staged feature fusion model called SFFNet, a neural network framework connecting CNN and GCN models. The CNN performs the first stage of feature extraction, assisted by adding neighboring features and overcoming the defects of local convolution; then, the GCN performs the second stage for classification, and the graph data structure is constructed based on spectral similarity, optimizing the original connectivity relationships. In addition, the framework enables the batch training of the GCN by using the extracted spectral features as nodes, which greatly reduces the hardware requirements. The experimental results on three publicly available benchmark hyperspectral datasets show that our proposed framework outperforms other relevant deep learning models, with an overall classification accuracy of over 97%.

BackgroundPatients with prostate cancer (PCa) benefit significantly from pelvic floor exercises, but recent results indicate that these exercises have not been fully promoted in clinical settings. This scoping review aimed to identify the facilitators of and barriers to pelvic floor muscle training (PFMT) in PCa survivors.MethodsA scoping review was conducted in November 2022. Relevant studies were identified from CINAHL, Embase, PubMed, PsycINFO, and Web of Science databases from their inception to 20 November 2022. Data were analyzed and extracted by two formally trained researchers.ResultsA total of 53 studies were included, most of which were randomized controlled trials. The Tailored Implementation for Chronic Diseases (TICD) model framework was used to identify the contents of seven barriers and promotion areas, as well as a series of sub-domains. The most common barriers to implementing pelvic floor muscle training (PFMT) included the following: the lack of a common scheme in guidelines and the measurement of common standardized outcomes, inadequate self-monitoring or feedback from healthcare professionals to improve PFMT compliance, poor patient compliance, and a lack of implementation equipment and financial support. Good treatment effects and easy operation were the facilitators of PFMT.ConclusionThe implementation of PFMT faces several challenges and opportunities that should be understood thoroughly before implementation. In terms of guidelines and clinical practice, more work is needed, and the possibility of PFMT implementation in various hospitals and community health centers or clinics should be considered.

Abstract Background Acupuncture effectively improves cognitive function in Alzheimer’s disease (AD). Many neuroimaging studies have found significant brain alterations after acupuncture treatment of AD, but the underlying central modulation mechanism is unclear. Objective This review aims to provide neuroimaging evidence to understand the central mechanisms of acupuncture in patients with AD. Methods Relevant neuroimaging studies about acupuncture for AD were retrieved from eight English and Chinese medicine databases (PubMed, Embase, Cochrane Library, Web of Science, SinoMed, CNKI, WF, VIP) and other resources from inception of databases until June 1, 2022, and their methodological quality was assessed using RoB 2.0 and ROBINS - I. Brain neuroimaging information was extracted to investigate the potential neural mechanism of acupuncture for AD. Descriptive statistics were used for data analysis. Results Thirteen neuroimaging studies involving 275 participants were included in this review, and the overall methodological quality of included studies was moderate. The approaches applied included task-state functional magnetic resonance imaging (ts-fMRI; n = 9 studies) and rest-state functional magnetic resonance imaging (rs-fMRI; n = 4 studies). All studies focused on the instant effect of acupuncture on the brains of AD participants, including the cingulate gyrus, middle frontal gyrus, and cerebellum, indicating that acupuncture may regulate the default mode, central executive, and frontoparietal networks. Conclusion This study provides evidence of the neural mechanisms underlying the effect of acupuncture on AD involving cognitive- and motor-associated networks. However, this evidence is still in the preliminary investigation stage. Large-scale, well-designed, multimodal neuroimaging trials are still required to provide comprehensive insight into the central mechanism underlying the effect of acupuncture on AD. (Systematic review registration at PROSPERO, No. CRD42022331527).

Abstract Trichomonas vaginitis (TV) is the most common non-viral sexually transmitted infection (STI) worldwide. The high prevalence of TV combined with mild or asymptomatic early symptoms leads to clinical vulnerability from delayed diagnosis. Latent infection can increase the incidence of pelvic infections, infertility, and adverse pregnancy complications. Data from 898 women who underwent vaginal flora testing from June 2014 to December 2014 were used to create a nomogram to assess the risk of TV in women in order to guide TV prevention and clinical intervention. The prediction model was evaluated in terms of identification, calibration, and clinical utility using the C-index, calibration plots, decision curve analysis, and internal validation. Predictors in the TV nomogram included age, occupation, yearly income, tea drinking, bathing frequency, menopause, spontaneous abortion, use of contraceptives, history of gynecological surgery, and HPV infection. The C-index of the TV risk prediction model was 0.732 (95% confidence interval: 0.695–0.768). It showed good discriminatory and predictive power. Decision curve analysis indicated that the nomogram had a good net benefit when the threshold probability of TV in women was 2–80%. The established TV prediction model easily, accurately, and quickly predicts the risk of TV onset.

Abstract Background Research on aging is growing as the elderly make up a greater share of the population, focusing on reversing and inhibiting the aging process. The exhaustion and senescence of stem cells are the fundamental drivers behind aging. β-Carotene has been depicted to have many biological functions, and we speculate that it may have an anti-aging effect. Methods Firstly, the anti-aging property of β-carotene was investigated in vitro using mesenchymal stem cells (MSCs) induced by H2O2. The anti-aging effect was characterized using Western-bloting, confocal laser scanning microscopy, indirect immunofluorescence, and immunohistochemistry. The anti-aging property was also tested in vivo using aged mice. Results The in vitro experiment revealed that β-carotene could relieve the aging of MSCs, as evidenced by a series of aging marker molecules such as p16 and p21. β-Carotene appeared to inhibit aging by regulating the KAT7-P15 signaling axis. The in vivo experiment revealed that β-carotene treatment has significantly down-regulated the aging level of tissues and organs. Conclusions In this work, we explored the anti-aging effect of β-carotene in vivo and in vitro. The experimental results indicate that β-carotene may be an important potential anti-aging molecule, which can be used as a drug or in functional food to treat aging in the future.

Abstract Covalent organic frameworks (COFs) are one class of porous materials with permanent porosity and regular channels, and have a covalent bond structure. Due to their interesting characteristics, COFs have exhibited diverse potential applications in many fields. However, some applications require the frameworks to possess high structural stability, excellent crystallinity, and suitable pore size. COFs based on β-ketoenamine and imines are prepared through the irreversible enol-to-keto tautomerization. These materials have high crystallinity and exhibit high stability in boiling water, with strong resistance to acids and bases, resulting in various possible applications. In this review, we first summarize the preparation methods for COFs based on β-ketoenamine, in the form of powders, films and foams. Then, the effects of different synthetic methods on the crystallinity and pore structure of COFs based on β-ketoenamine are analyzed and compared. The relationship between structures and different applications including fluorescence sensors, energy storage, photocatalysis, electrocatalysis, batteries and proton conduction are carefully summarized. Finally, the potential applications, large-scale industrial preparation and challenges in the future are presented. Graphical Abstract

Background MicroRNA-154-5p (miR-154-5p) plays a role in tumorigenesis in diverse human malignancies. Nevertheless, little is known about the mechanism by which miR-154-5p alters the growth and metastasis of cervical cancer. This research aimed to analyze the role of miR-154-5p in the pathology of cervical cancer in vitro and in vivo. Methods The level of miR-154-5p in human papillomavirus 16 positive cervical cancer cells was examined by real-time quantitative polymerase chain reaction. Bioinformatics predicted the downstream targets and potential functions of miR-154-5p. Furthermore, lentiviral technology was used to construct SiHa cell lines with stable up- and down-expression levels of miR-154-5p. Its differential expression effects on the progress and metastasis of cervical cancer were analyzed using cell culture and animal models. Results MiR-154-5p showed low expression in cervical cancer cells. Overexpression of miR-154-5p could markedly inhibit the proliferation, migration, and colony formation ability of SiHa cells, concomitantly leading to G1 arrest of the cell cycle, while silencing miR-154-5p triggered the opposite results. Meanwhile, overexpression of miR-154-5p restrained the growth and metastasis of cervical cancer by silencing CUL2 in vivo. Additionally, miR-154-5p reduced CUL2 level, and overexpression of CUL2 influenced the effect of miR-154-5p in cervical cancer. In conclusion, miR-154-5p restrained the growth and metastasis of cervical cancer by directly silencing CUL2.

BackgroundAmnestic mild cognitive impairment (aMCI) is a pre-dementia condition associated with declined cognitive function dominated by memory impairment. The occurrence of aMCI is associated with the gut-brain axis. Previous studies have shown cognitive improvements in MCI after acupuncture treatment. This study evaluates whether acupuncture can produce a therapeutic effect in patients with aMCI by modulating the gut-brain axis.Methods and designThis is a prospective, parallel, multicenter randomized controlled trial. A total of 40 patients with aMCI will be randomly assigned to an acupuncture group (AG) or a waiting-list group (WG), participants in both groups will receive health education on improving cognitive function at each visit, and acupuncture will be conducted twice a week for 12 weeks in the AG. Another 20 matched healthy volunteers will be enrolled as normal control. The primary outcome will be the change in Alzheimer’s Disease Assessment Scale-cognitive scale score before and after treatment. Additionally, functional magnetic resonance imaging data, faeces, and blood will be collected from each participant to characterize the brain function, gut microbiota, and inflammatory cytokines, respectively. The differences between patients with aMCI and healthy participants, and the changes in the AG and WG groups before and after treatment will be observed. Ultimately, the correlation among brain function, gut microbiota, inflammatory cytokines, and clinical efficacy evaluation in patients with aMCI will be analyzed.DiscussionThis study will identify the efficacy and provide preliminary data on the possible mechanism of acupuncture in treating aMCI. Furthermore, it will also identify biomarkers of the gut microbiota, inflammatory cytokines, and brain function correlated with therapeutic effects. The results of this study will be published in peer-reviewed journals.Clinical trial registrationhttp://www.chictr.org.cn, identifier ChiCTR2200062084.

BackgroundEncephalitis has been recognized in patients with autoimmunity related to the 65-kDa isoform of glutamic acid decarboxylase (GAD65) antibodies; however, patients with meningoencephalitis associated with those antibodies have been rarely identified in the medical literature. We aimed to define the frequency, clinical features, response to therapy, and functional outcomes of patients with meningoencephalitis associated with GAD antibodies.MethodsWe retrospectively studied consecutive patients attending a tertiary care center for evaluation of an autoimmune neurological disorder from January 2018 to June 2022. The modified Rankin Scale (mRS) was used to assess the functional outcome at the last follow-up.ResultsWe evaluated 482 patients with confirmed autoimmune encephalitis during the study period. Four among the 25 patients with encephalitis related to GAD65 antibodies were identified. One patient was excluded owing to the coexistence of NMDAR antibodies. Three male patients aged 36, 24, and 16 years had an acute (n = 1) or subacute (n = 2) onset of confusion, psychosis, cognitive symptoms, seizures, or tremor. No patient had fever or clinical signs of meningeal irritation. Mild pleocytosis (

This study introduces a data augmentation technique based on generative adversarial networks (GANs) to improve the accuracy of day-ahead wind power predictions. To address the peculiarities of abrupt weather data, we propose a novel method for detecting mutation rates (MR) and local mutation rates (LMR). By analyzing historical data, we curated datasets that met specific mutation rate criteria. These transformed wind speed datasets were used as training instances, and using GAN-based methodologies, we generated a series of augmented training sets. The enriched dataset was then used to train the wind power prediction model, and the resulting prediction results were meticulously evaluated. Our empirical findings clearly demonstrate a significant improvement in the accuracy of day-ahead wind power prediction due to the proposed data augmentation approach. A comparative analysis with traditional methods showed an approximate 5% increase in monthly average prediction accuracy. This highlights the potential of leveraging mutated wind speed data and GAN-based techniques for data augmentation, leading to improved accuracy and reliability in wind power predictions. In conclusion, this paper presents a robust data augmentation method for wind power prediction, contributing to the potential enhancement of day-ahead prediction accuracy. Future research could explore additional mutation rate detection methods and strategies to further enhance GAN models, thereby amplifying the effectiveness of wind power prediction.

The Segment Anything Model (SAM) is a versatile image segmentation model that enables zero-shot segmentation of various objects in any image using prompts, including bounding boxes, points, texts, and more. However, studies have shown that the SAM performs poorly in agricultural tasks like crop disease segmentation and pest segmentation. To address this issue, the agricultural SAM adapter (ASA) is proposed, which incorporates agricultural domain expertise into the segmentation model through a simple but effective adapter technique. By leveraging the distinctive characteristics of agricultural image segmentation and suitable user prompts, the model enables zero-shot segmentation, providing a new approach for zero-sample image segmentation in the agricultural domain. Comprehensive experiments are conducted to assess the efficacy of the ASA compared to the default SAM. The results show that the proposed model achieves significant improvements on all 12 agricultural segmentation tasks. Notably, the average Dice score improved by 41.48% on two coffee-leaf-disease segmentation tasks.

BackgroundPsychological workplace violence (WPV) is the primary form of workplace violence suffered by nursing interns. Psychological WPV not only damages the physical and mental health of nursing interns, but also has a negative impact on their work quality and career choice.AimTo investigate the characteristics and types of psychological WPV suffered by nursing interns in China, analyze the influencing factors of psychological WPV among nursing interns, and explore the influence of psychological WPV on the professional commitment of nursing interns.MethodsThe subjects were 1,095 nursing interns from 14 medical colleges in Shandong Province. The data were collected electronically using the psychological WPV against nursing interns questionnaire and the professional commitment scale of nursing. The frequency and component ratio were used to describe the incidence and characteristics of psychological WPV. Binary logistic regression was used to analyze the influencing factors of psychological WPV, and linear regression investigated the influence of psychological WPV on the professional commitment of nursing interns.ResultsIn the study, 45.0% (n = 493) of nursing interns suffered at least one incidence of psychological WPV during clinical practice, mainly discrimination and verbal abuse. Patients and their relatives were the main perpetrators of psychological WPV. Discrimination and lack of trust were the two main reasons behind psychological WPV. Furthermore, 75.9% of psychological WPV incidents were not effectively reported. Logistic regression showed that clinical internship duration, place of family residence, and hospital level were the influencing factors of psychological WPV among nursing interns. Linear regression results showed that psychological WPV had a negative effect on nursing interns' professional commitment.ConclusionPsychological WPV against nursing interns is highly prevalent in China, negatively impacting their professional commitment. It is suggested that colleges should introduce courses for nursing interns to understand and cope with psychological WPV before entering clinical practice, and hospitals should establish a mechanism to prevent, cope with, report, and deal with psychological WPV to effectively reduce the incidence of psychological WPV against nursing interns, improve their ability to cope with psychological WPV, and enhance their professional commitment.

Mild cognitive impairment (MCI) is a multifactorial and complex central neurodegenerative disease. Acupuncture appears to be an effective method for cognitive function improvement in MCI patients. Neural plasticity remaining in the MCI brain implies that acupuncture-associated benefits may not be limited to the cognitive function. Instead, neurological alternations in the brain play a vital role in corresponding to the cognitive improvement. However, previous studies have mainly focused on the effects of cognitive function, leaving neurological findings relatively unclear. This systematic review summarized existing studies that used various brain imaging techniques to explore the neurological effect regarding acupuncture use for MCI treatment. Potential neuroimaging trials were searched, collected, and identified independently by two researchers. Four Chinese databases, four English databases, and additional sources were searched to identify studies reporting the use of acupuncture for MCI from the inception of databases until 1 June 2022. Methodological quality was appraised using the Cochrane risk-of-bias tool. In addition, general, methodological, and brain neuroimaging information was extracted and summarized to investigate the potential neural mechanisms by which acupuncture affects patients with MCI. In total, 22 studies involving 647 participants were included. The methodological quality of the included studies was moderate to high. The methods used included functional magnetic resonance imaging, diffusion tensor imaging, functional near-infrared spectroscopy, and magnetic resonance spectroscopy. Acupuncture-induced brain alterations observed in those patients with MCI tended to be observable in the cingulate cortex, prefrontal cortex, and hippocampus. The effect of acupuncture on MCI may play a role in regulating the default mode network, central executive network, and salience network. Based on these studies, researchers could extend the recent research focus from the cognitive domain to the neurological level. Future researches should develop additional relevant, well-designed, high-quality, and multimodal neuroimaging researches to detect the effects of acupuncture on the brains of MCI patients.

BackgroundThere is insufficient evidence to support the use of acupuncture for mild cognitive impairment (MCI), and there is no consensus on its efficacy. This review aimed to determine the acupuncture effect in patients with MCI.MethodsRelevant and potentially eligible randomized controlled trials (RCTs) of acupuncture for MCI were obtained from four Chinese databases, four English databases, and additional resources up to 1 August 2022. The primary outcome was the improvement in overall cognitive function (OCF). Secondary outcomes were improved memory function (MF) and activities of daily living (ADLs). The revised Cochrane collaboration risk of bias (ROB) assessment tool (ROB 2.0) was applied to evaluate their methodological quality. The Review Manager software v 5.4 was used for analyses. Trial sequential analysis (TSA) 0.9.5.10 β software was used to estimate the required sample size and test the reliability of the pooled outcome. The quality of evidence was assessed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) tool.ResultsThis meta-analysis included 11 RCTs with a total of 602 patients. The methodological quality of all trials was moderate. Low-quality evidence showed that acupuncture significantly improved OCF (Mini-Mental State Examination (MMSE): mean difference (MD) = 1.22, 95% confidence interval (CI): 0.78–1.66; the Montreal Cognitive Assessment Scale (MoCA): MD = 1.22, 95% CI: 0.47–1.97). In subgroup analyses, it was revealed that acupuncture significantly increased OCF in patients with MCI when compared to conventional medicine (CM) and sham acupuncture (SA). TSA's findings indicated that the evidence of improving OCF with acupuncture for patients with MCI was conclusive. Meanwhile, there is no statistical difference in the improvement of MF and ADL between acupuncture and CM. TSA showed that the evidence of improving MF and ADL for patients who had MCI and received acupuncture was inconclusive. The shreds of evidence of improving MF and ADL were ranked from low to critically low.ConclusionAcupuncture appears to be an effective clinical application method for improving OCF in patients with MCI. However, due to low-quality evidence, more relevant and high-quality research is needed in this field.Systematic review registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021291284, PROSPERO, No. CRD42021291284.

End-of-life (EOL) electric vehicle (EV) batteries have both economic and environmental benefits if recycled in an environmentally friendly manner while they may cause environmental pollution if treated improperly. China is currently working hard to promote the development of a circular economy by EOL EV battery recycling. However, conflicts of interest among electric vehicle manufacturers (EVMs), consumers, and the government often hinder efficient recycling. This study constructs a tripartite evolutionary game model under the condition of bounded rationality, analyzes the evolutionary stability strategy of three participants, and combines with numerical simulation to explore the feasible governance strategies of EOL EV battery recycling. The results show that four evolutionary stable strategies (ESSs) correspond to the three stages of the EOL EV battery recycling industry: early stage, development stage, and maturity stage. In the early stage, the punishment strategy is more critical to motivate EVMs and consumers to actively participate in battery recycling. The subsidy mechanisms can influence the strategic choices of the three participants, but the excessive subsidy is not conducive to the sustainable development of the EOL EV battery industry. In addition, when the industry matures, the government will gradually decrease intervention, thereby realizing the development path of EOL EV battery recycling from exogenous government supervision to endogenous profit drive.

Abstract Background Mutations in the DMD gene encoding dystrophin—a critical structural element in muscle cells—cause Duchenne muscular dystrophy (DMD), which is the most common fatal genetic disease. Clustered regularly interspaced short palindromic repeat (CRISPR)-mediated gene editing is a promising strategy for permanently curing DMD. Methods In this study, we developed a novel strategy for reframing DMD mutations via CRISPR-mediated large-scale excision of exons 46–54. We compared this approach with other DMD rescue strategies by using DMD patient-derived primary muscle-derived stem cells (DMD-MDSCs). Furthermore, a patient-derived xenograft (PDX) DMD mouse model was established by transplanting DMD-MDSCs into immunodeficient mice. CRISPR gene editing components were intramuscularly delivered into the mouse model by adeno-associated virus vectors. Results Results demonstrated that the large-scale excision of mutant DMD exons showed high efficiency in restoring dystrophin protein expression. We also confirmed that CRISPR from Prevotella and Francisella 1(Cas12a)-mediated genome editing could correct DMD mutation with the same efficiency as CRISPR-associated protein 9 (Cas9). In addition, more than 10% human DMD muscle fibers expressed dystrophin in the PDX DMD mouse model after treated by the large-scale excision strategies. The restored dystrophin in vivo was functional as demonstrated by the expression of the dystrophin glycoprotein complex member β-dystroglycan. Conclusions We demonstrated that the clinically relevant CRISPR/Cas9 could restore dystrophin in human muscle cells in vivo in the PDX DMD mouse model. This study demonstrated an approach for the application of gene therapy to other genetic diseases.

Abstract Background Transmembrane protein with EGF-like and two follistatin-like domains 2 (TMEFF2) is a transmembrane protein in the tomoregulin family. Little research has been performed to determine whether TMEFF2 methylation is a prognostic marker in adult diffuse gliomas. Methods In this study, we investigated TMEFF2 expression in surgical glioma tissue samples. In addition, we conducted bisulfite amplicon sequencing (BSAS) and methylation-specific PCR (MSP) to evaluate TMEFF2 methylation in glioblastoma (GBM) cells. Subsequently, we investigated the biological function of TMEFF2 in GBM cells. Moreover, we explored the prognostic significance of TMEFF2 in gliomas by analysing a cohort dataset from TCGA. Results Immunohistochemistry analysis of 75 paired glioma tumour and peritumoural tissues demonstrated that glioma tumour tissues expressed lower TMEFF2 levels than peritumoural tissues (P

Ploidy manipulation, such as triploidy, in farmed oysters has been used as a tool to enhance oyster quality throughout all seasons because triploid oysters allocate less energy to gametogenesis, and therefore are deemed better performers than fertile diploids. Nevertheless, scientific reports describing no differences between ploidies and, in certain conditions, disadvantages of triploids are not uncommon. As the use of triploid oyster seed increases culture cost for growers, consistency in performance of triploids is considered to be an important goal. Thus, research to assess how ploidy affects physiological processes underlying oyster performance is fundamental for the aquaculture industry. This work was undertaken to assess if ploidy-based differences in performance in the two most commonly cultivated commercial species of oyster in the United States, Crassostrea virginica and Crassostrea gigas, are associated with filtration, feeding, and metabolism. To test this hypothesis, biodeposition measurements were made with oysters exposed to ambient water conditions at locations and seasons providing a variety of environmental conditions. Oysters did not show differences in filtration and feeding associated with ploidy, but physiological feeding variables fluctuated with environmental characteristics associated with spatial and seasonal differences. A preliminarily test of the hypothesis that differences in energy metabolism may account for differences in performance among ploidy levels indicates that basal metabolic rates of diploid, triploid, and tetraploid Eastern oysters are not different.

BackgroundRestraint is widely used in nursing homes to address safety concerns. However, many studies have shown that improper restraint can lead to many adverse outcomes. Nursing staff are the main practitioners of physical restraint in nursing homes and play an important role in restraint decision-making and management. In China, there is still a lack of large-scale surveys on the current situation regarding the use of restraint. This study aimed to identify this situation and the influencing factors of the knowledge, attitude, and practice of nursing staff regarding physical restraint in elderly care institutions.MethodsA cross-sectional multicenter descriptive study was conducted. A total of 311 staff in 25 elderly care institutions in Zhejiang Province were recruited using a quota sampling method. A homemade questionnaire was administered to collect general information and information on knowledge, attitude and practice regarding physical restraint.ResultsThe average scoring rates of the knowledge and attitude dimensions of the 311 staff were 48.7 and 75.6%, respectively. The average scoring rate of the practice dimension of 140 staff who implemented restraint was 80.1%. Educational background and training experience were the influencing factors of restraint knowledge. Training experience, educational background and professional title were the influencing factors of restraint attitude. Restraint knowledge and length of service were the influencing factors of restraint practice.ConclusionsKnowledge of physical restraint among nursing staff is not promising. Their attitude toward restraint was inappropriate or irresponsible in some aspects. Restraint practice is not sufficiently standardized. It is necessary to strengthen restraint training for nursing staff to improve their overall level of restraint knowledge, attitude and practice.

Mechanical stretch is one type of common physiological activities such as during heart beating, lung breathing, blood flow through the vessels, and physical exercise. The mechanical stimulations regulate cellular functions and maintain body homeostasis. It still remains to further characterize the mechanical-biomechanical coupling mechanism. Here we applied fluorescence resonance energy transfer (FRET) technology to visualize ERK activity in airway smooth muscle (ASM) cells under cyclic stretch stimulation in airway smooth muscle (ASM) cells, and studied the mechanosensing pathway. FRET measurements showed apparent ERK activation by mechanical stretch, which was abolished by ERK inhibitor PD98059 pretreatment. Inhibition of extracellular Ca2+ influx reduced ERK activation, and selective inhibition of inositol 1,4,5-trisphosphate receptor (IP3R) Ca2+ channel or SERCA Ca2+ pump on endoplasmic reticulum (ER) blocked the activation. Chemical inhibition of the L-type or store-operated Ca2+ channels on plasma membrane, or inhibition of integrin β1 with siRNA had little effect on ERK activation. Disruption of actin cytoskeleton but not microtubule one inhibited the stretch-induced ERK activation. Furthermore, the ER IP3R-dependent ERK activation was not dependent on phospholipase C-IP3 signal, indicating possibly more mechanical mechanism for IP3R activation. It is concluded from our study that the mechanical stretch activated intracellular ERK signal in ASM cells through membrane Ca2+ channels mechanosensation but not integrin β1, which was mediated by actin cytoskeleton.

Abstract Background Duchenne muscular dystrophy (DMD) is a devastating genetic muscular disorder with no effective treatment that is caused by the loss of dystrophin. Human induced pluripotent stem cells (hiPSCs) offer a promising unlimited resource for cell-based therapies of muscular dystrophy. However, their clinical applications are hindered by inefficient myogenic differentiation, and moreover, the engraftment of non-transgene hiPSC-derived myogenic progenitors has not been examined in the mdx mouse model of DMD. Methods We investigated the muscle regenerative potential of myogenic progenitors derived from hiPSCs in mdx mice. The hiPSCs were transfected with enhanced green fluorescent protein (EGFP) vector and defined as EGFP hiPSCs. Myogenic differentiation was performed on EGFP hiPSCs with supplementary of basic fibroblast growth factor, forskolin, 6-bromoindirubin-3′-oxime as well as horse serum. EGFP hiPSCs-derived myogenic progenitors were engrafted into mdx mice via both intramuscular and intravenous injection. The restoration of dystrophin expression, the ratio of central nuclear myofibers, and the transplanted cells-derived satellite cells were accessed after intramuscular and systemic transplantation. Results We report that abundant myogenic progenitors can be generated from hiPSCs after treatment with these three small molecules, with consequent terminal differentiation giving rise to mature myotubes in vitro. Upon intramuscular or systemic transplantation into mdx mice, these myogenic progenitors engrafted and contributed to human-derived myofiber regeneration in host muscles, restored dystrophin expression, ameliorated pathological lesions, and seeded the satellite cell compartment in dystrophic muscles. Conclusions This study demonstrates the muscle regeneration potential of myogenic progenitors derived from hiPSCs using non-transgenic induction methods. Engraftment of hiPSC-derived myogenic progenitors could be a potential future therapeutic strategy to treat DMD in a clinical setting.

The transparent inhibition zone by p-coumaric acid (pCA) proving its inhibitory effect on quorum sensing. The treatment with a mixture of 0.1% Potassium Sorbate (PS)+0.01% pCA resulted in gradual inhibition of the viable counts of meat. In addition, the microbial counts of the samples treated with the mixture of pCA and PS were significantly lower than that treated with PS alone, which indicated that the effect of the mixture on bacteria and protein decomposition was stronger than that of PS alone, which can better delay the spoilage of meat. P-coumaric acid reduced the generation of biogenic amines, mitigating the spoilage of chilled pork meat. During sensory evaluation, pork meat treated with the mixture of pCA and PS scored higher than the control group. P-coumaric acid could be used to reduce the amount of PS, and the application of the mixture greatly enhanced the preservation efficiency and the quality of pork.

The power of deep learning and the enormous effort and money required to build a deep learning model makes stealing them a hugely worthwhile and highly lucrative endeavor. Worse still, model theft requires little more than a high-school understanding of computer functions, which ensures a healthy and vibrant black market full of choice for any would-be pirate. As such, estimating how many neural network models are likely to be illegally reproduced and distributed in future is almost impossible. Therefore, we propose an embedded `identity bracelet' for deep neural networks that acts as proof of a model's owner. Our solution is an extension to the existing trigger-set watermarking techniques that embeds a post-cryptographic-style serial number into the base deep neural network (DNN). Called a DNN-SN, this identifier works like an identity bracelet that proves a network's rightful owner. Further, a novel training method based on non-related multitask learning ensures that embedding the DNN-SN does not compromise model performance. Experimental evaluations of the framework confirm that a DNN-SN can be embedded into a model when training from scratch or in the student network component of Net2Net.

In this paper, a novel point cloud segmentation and completion framework is proposed to achieve high-quality leaf area measurement of melon seedlings. In particular, the input of our algorithm is the point cloud data collected by an Azure Kinect camera from the top view of the seedlings, and our method can enhance measurement accuracy from two aspects based on the acquired data. On the one hand, we propose a neighborhood space-constrained method to effectively filter out the hover points and outlier noise of the point cloud, which can enhance the quality of the point cloud data significantly. On the other hand, by leveraging the purely linear mixer mechanism, a new network named MIX-Net is developed to achieve segmentation and completion of the point cloud simultaneously. Different from previous methods that separate these two tasks, the proposed network can better balance these two tasks in a more definite and effective way, leading to satisfactory performance on these two tasks. The experimental results prove that our methods can outperform other competitors and provide more accurate measurement results. Specifically, for the seedling segmentation task, our method can obtain a 3.1% and 1.7% performance gain compared with PointNet++ and DGCNN, respectively. Meanwhile, the R2 of leaf area measurement improved from 0.87 to 0.93 and MSE decreased from 2.64 to 2.26 after leaf shading completion.

Duchenne muscular dystrophy (DMD) is a common hereditary neuromuscular disease characterized by progressive muscle wasting and weakness. DMD is caused by mutations in the DMD gene, resulting in the dysfunction of dystrophin. We generated an induced pluripotent stem cell (iPSC) from a patient with DMD carrying exon 51 deletion in the DMD gene. This iPSC line can serve as a model for studying the pathogenesis and therapeutics of DMD.

Objective To provide a validated Chinese-language measurement of the Nursing Home Survey on Patient Safety Culture (NHSOPS) in mainland China. The primary goal is to carry out a transcultural adaptation of the NHSOPS Questionnaire into Chinese and evaluate its psychometric properties.Design A psychometric evaluation study is constructed. First, the ‘translation–back-translation–cultural adaptation’ and the pretesting procedure were followed to introduce the NHSOPS. Second, a cross-sectional survey was used to assess the psychometric properties for the mainland China version of the NHSOPS (M-NHSOPS), and a test–retest survey was then applied.Setting and participants The survey was carried out among 1397 nursing home staff from 50 nursing homes in Southwest China.Outcome measures Exploratory factor analysis (EFA) was used to assess the potential structure, and confirmatory factor analysis (CFA) was then applied. Reliability was assessed by the content validity index, Cronbach’s α and the test–retest value.Results Among the 1397 respondents, 1211 were included (86.7%). EFA was used, and a nine-factor structure was explored. Five factors (Cronbach’s α ＞0.6) were selected into the new structure for the M-NHSOPS. Moreover, data showed that it was suitable for CFA, and convergent validity and discriminant validity were satisfactory. On the other hand, M-NHSOPS contains five dimensions and 22 items. The overall Cronbach’s α value was 0.883; the values of each dimension ranged from 0.648 to 0.913. Additionally, content validity showed significant performance. Eventually, test–retest reliability was 0.892, and each dimension was 0.713, 0.809, 0.924, 0.795 and 0.859, respectively (p

We propose a conceptually simple, general framework and end-to-end approach to point cloud completion, entitled PCA-Net. This approach differs from the existing methods in that it does not require a “simple” network, such as multilayer perceptrons (MLPs), to generate a coarse point cloud and then a “complex” network, such as auto-encoders or transformers, to enhance local details. It can directly learn the mapping between missing and complete points, ensuring that the structure of the input missing point cloud remains unchanged while accurately predicting the complete points. This approach follows the minimalist design of U-Net. In the encoder, we encode the point clouds into point cloud blocks by iterative farthest point sampling (IFPS) and k-nearest neighbors and then extract the depth interaction features between the missing point cloud blocks by the attention mechanism. In the decoder, we introduce a new trilinear interpolation method to recover point cloud details, with the help of the coordinate space and feature space of low-resolution point clouds, and missing point cloud information. This paper also proposes a method to generate multi-view missing point cloud data using a 3D point cloud hidden point removal algorithm, so that each 3D point cloud model generates a missing point cloud through eight uniformly distributed camera poses. Experiments validate the effectiveness and superiority of PCA-Net in several challenging point cloud completion tasks, and PCA-Net also shows great versatility and robustness in real-world missing point cloud completion.

Mastering the fluctuation of water levels and the water storage capacity of plateau lakes is greatly important for monitoring the water balance of the Tibetan Plateau and predicting regional and global climate change. The water level of plateau lakes is difficult to measure, and the ground measured data of long-time series are difficult to obtain. Ngoring Lake is considered in this study, using spaceborne single-photon lidar ICESat-2/ATL13 inland lake standard data products, the water level values provided by Hydroweb laboratory, and the image data of an optical remote sensing satellite. A new method is proposed in the absence of measured data. The method uses multisource remote sensing data to estimate the long-term changes in the water levels, surface area, and water storage capacity of Ngoring Lake in the past three decades. The results show that the water level values of ICESat-2 and Hydroweb on overlapping observation days are highly correlated, with R2 = 0.9776, MAE = 0.420 m, RMSE = 0.077 m, and the average absolute height difference is 0.049 m. The fusion of multiple altimetry data can obtain more continuous long-time series water-level observation results. From 1992 to 2021, the water body information of Ngoring Lake basin fluctuated greatly and showed different variation characteristics in different time periods. The lowest water level in January 1997 was approximately 4268.49 m, and it rose to its highest in October 2009, approximately 4272.44 m. The change in the water level in the basin was mainly affected by natural factors, such as precipitation, air temperature, and human activities. The analysis shows that ICESat-2 can be combined with other remote sensing data to realize the long-time series dynamic monitoring of plateau lakes, showing great advantages in the comprehensive observation of plateau lakes in no man’s land.

Convolutional neural networks have greatly improved the performance of image super-resolution. However, perceptual networks have problems such as blurred line structures and a lack of high-frequency information when reconstructing image textures. To mitigate these issues, a generative adversarial network based on multiscale asynchronous learning is proposed in this paper, whereby a pyramid structure is employed in the network model to integrate high-frequency information at different scales. Our scheme employs a U-net as a discriminator to focus on the consistency of adjacent pixels in the input image and uses the LPIPS loss for perceptual extreme super-resolution with stronger supervision. Experiments on benchmark datasets and independent datasets Set5, Set14, BSD100, and SunHays80 show that our approach is effective in restoring detailed texture information from low-resolution images.

Objective: Dysferlin deficiency causes dysferlinopathy. This study aimed to expand the mutational spectrum of dysferlinopathies, to further study one case with diagnostic ambiguity, and to identify the diagnostic value of dysferlin expression in total peripheral blood mononuclear cells (PBMC).Methods: The clinical and molecular profiles of dysferlinopathies in eight Chinese patients were evaluated. We also conducted magnetic resonance imaging (6/8) and determined dysferlin protein expression in muscle (7/8) and PBMC (3/8).Results: Nine of the 13 DYSF mutations identified were novel. One patient was homozygous for the Gln111Ter mutation by genomic DNA sequencing but was found to be heterozygous by sequencing of cDNA from total PBMC. A daughter of this patient did not carry any Gln111Ter mutation. Abnormal muscle MRI with predominant involvement of the medial gastrocnemius and soleus muscle was observed in 5/6 patients. Dysferlin levels were significantly reduced (immunohistochemistry/immunoblot) or absent (immunohistochemistry) in muscle and total PBMC (26–39%) for most patients. Sarcoplasmic accumulation of dysferlin was detected in one patient.Conclusion: Genomic DNA sequencing detects frequent homozygous mutations, while fewer heterozygous mutations in cDNA are detected after posttranscription. Total PBMC may serve as an alternative to confirm diagnosis and to guide further testing in dysferlinopathies. Our results contribute to the mutational spectrum of dysferlinopathies.

Background: Duchenne muscular dystrophy (DMD) is a fatal, X-linked recessive muscle disorder characterized by heterogeneous progression and severity. We aimed to study the effects of single nucleotide polymorphisms (SNPs) in SPP1 and LTBP4 on DMD progression in Chinese patients.Methods: We genotyped LTBP4 haplotypes and the SPP1 promoter SNPs rs28357094, rs11730582, and rs17524488 in 326 patients registered in the neuromuscular database of The First Affiliated Hospital of Sun Yat-sen University. Kaplan-Meier curves and log-rank tests were used to estimate and compare median age at loss of ambulation, while Cox proportional hazard regression models were used as to analyze the effects of glucocorticoids treatments, DMD genotype, and SPP1/LTBP4 SNPs on loss of ambulation.Results: The CC/CT genotype at rs11730582 was associated with a 1.33-year delay in ambulation loss (p = 0.006), with hazard ratio 0.63 (p = 0.008), in patients with truncated DMD genotype and undergoing steroid treatment. On the other hand, rs17524488 in SPP1 and the IAAM/IAAM haplotype in LTBP4 were not associated with time to ambulation loss.Conclusions:SPP1 rs11730582 is a genetic modifier of the long-term effects of steroid treatment in Chinese DMD patients. Thus, any future clinical study in DMD should adjust for glucocorticoids use, DMD genotype, and SPP1 polymorphisms.

Abstract The East River tidal strait, located between New York Harbor and Western Long Island Sound, is characterized by high suspended silt concentrations with low organic content kept in suspension by intense tidal currents. Inorganic nutrients, including nitrate, nitrite, ammonia, and phosphate, were high even during the summer. Dissolved inorganic nitrogen (DIN) concentrations generally were above 20 µM and did not likely limit phytoplankton growth. Despite high nutrient concentrations, median chlorophyll a concentration was only 1.53 µg l−1, making the East River tidal strait a high-nutrient, low-chlorophyll (HNLC) area, likely a result of suspended silt blocking light penetration into the surface water. There were times at which the ratio of mixed layer to depth of the euphotic zone was generally greater than what has been suggested for phytoplankton to produce net primary production. The high-nutrient East River tidal strait is likely one of the sources of nutrients fueling summer phytoplankton production and consequent hypoxia in the Western Long Island Sound as silt settles from surface water in the lower turbulence conditions of the western narrows of Long Island Sound, thereby allowing light penetration and subsequent consumption of dissolved nutrients by phytoplankton.

Molecular latent representations, derived from autoencoders (AEs), have been widely used for drug or material discovery over the past couple of years. In particular, a variety of machine learning methods based on latent representations have shown excellent performance on quantitative structure–activity relationship (QSAR) modeling. However, the sequence feature of them has not been considered in most cases. In addition, data scarcity is still the main obstacle for deep learning strategies, especially for bioactivity datasets. In this study, we propose the convolutional recurrent neural network and transfer learning (CRNNTL) method inspired by the applications of polyphonic sound detection and electrocardiogram classification. Our model takes advantage of both convolutional and recurrent neural networks for feature extraction, as well as the data augmentation method. According to QSAR modeling on 27 datasets, CRNNTL can outperform or compete with state-of-art methods in both drug and material properties. In addition, the performances on one isomers-based dataset indicate that its excellent performance results from the improved ability in global feature extraction when the ability of the local one is maintained. Then, the transfer learning results show that CRNNTL can overcome data scarcity when choosing relative source datasets. Finally, the high versatility of our model is shown by using different latent representations as inputs from other types of AEs.

The representation-based algorithm has raised a great interest in hyperspectral image (HSI) classification. l1-minimization-based sparse representation (SR) attempts to select a few atoms and cannot fully reflect within-class information, while l2-minimization-based collaborative representation (CR) tries to use all of the atoms leading to mixed-class information. Considering the above problems, we propose the pairwise elastic net representation-based classification (PENRC) method. PENRC combines the l1-norm and l2-norm penalties and introduces a new penalty term, including a similar matrix between dictionary atoms. This similar matrix enables the automatic grouping selection of highly correlated data to estimate more robust weight coefficients for better classification performance. To reduce computation cost and further improve classification accuracy, we use part of the atoms as a local adaptive dictionary rather than the entire training atoms. Furthermore, we consider the neighbor information of each pixel and propose a joint pairwise elastic net representation-based classification (J-PENRC) method. Experimental results on chosen hyperspectral data sets confirm that our proposed algorithms outperform the other state-of-the-art algorithms.

Summary: Tuberous sclerosis complex (TSC) is a disease featuring devastating and therapeutically challenging neurological abnormalities. However, there is a lack of specific neural progenitor cell models for TSC. Here, the pathology of TSC was studied using primitive neural stem cells (pNSCs) from a patient presenting a c.1444-2A>C mutation in TSC2. We found that TSC2 pNSCs had higher proliferative activity and increased PAX6 expression compared with those of control pNSCs. Neurons differentiated from TSC2 pNSCs showed enlargement of the soma, perturbed neurite outgrowth, and abnormal connections among cells. TSC2 astrocytes had increased saturation density and higher proliferative activity. Moreover, the activity of the mTOR pathway was enhanced in pNSCs and induced in neurons and astrocytes. Thus, our results suggested that TSC2 heterozygosity caused neurological malformations in pNSCs, indicating that its heterozygosity might be sufficient for the development of neurological abnormalities in patients. : In this article, Cheng and colleagues isolated primitive neural stem cells from a patient presenting a c.1444-2A>C mutation in TSC2. These iPSC-derived neural cells recapitulated the pathophysiology of TSC2-deficient patients and could be used for screening appropriate drugs for personalized therapies. Keywords: induced pluripotent stem cells, mTOR, neural differentiation, neurological abnormalities, primitive neural stem cells, tuberous sclerosis complex

Objective This study aimed to assess whether orosomucoid 1-like 3 (ORMDL3) expression and environmental and clinical factors are associated with wheezing episodes in preschool children. Methods Children diagnosed with wheezing episodes were classified according to their asthma predictive index (API) in the past year as follows: API+ (≥4 wheezing episodes), API− (1–3 wheezing episodes), and API0 (without wheezing). ORMDL3 expression was assessed by real-time polymerase chain reaction in peripheral blood mononuclear cells (PBMCs). Receiver operating characteristic curve analysis of ORMDL3 expression and the API was performed for diagnosing wheezing episodes. Correlations between ORMDL3 expression and asthma risk factors were examined using Spearman’s correlation. Results PBMC ORMDL3 expression was higher in the API+ group compared with the API− and API0 groups. The area under the curve for ORMDL3 expression was 0.820 (95% confidence interval, 0.771–0.869). ORMDL3 expression was positively correlated with the API ( r = 0.447), infantile eczema ( r = 0.499), wheezing ( r = 0.516), total immunoglobulin E ( r = 0.208), and environmental factors, including Dermatophagoides pteronyssinus ( r = 0.357), house dust mites ( r = 0.112), dog fur ( r = 0.226), and Aspergillus ( r = 0.257). ORMDL3 expression was negatively correlated with amaranth ( r = −0.122). Conclusions ORMDL3 expression in PBMCs is positively associated with the API and some asthma-related clinical and environmental risk factors in preschoolers.