Research on the innovative application of Shen Embroidery cultural heritage based on convolutional neural network.

In order to protect intangible cultural heritage and promote outstanding cultural works, this article introduces innovative research on Shen Embroidery using convolutional neural networks. The dataset of Shen Embroidery was preprocessed to augment the data required for experimentation. Moreover, the approach of transfer learning was introduced to fine-tune the recognition network. Specifically, Spatial Pyramid Pooling (SPP) is employed by replacing the avg pool in the MobileNet V1 network, achieving the fusion of local and global features. The experimental results showed that the improved MobileNet V1 achieved a recognition accuracy of 98.45%, which was 2.3% higher than the baseline MobileNet V1 network. The experiments demonstrated that the improved convolutional neural network can efficiently recognize Shen Embroidery and provide technical support for the intelligent development of intangible cultural heritage.

The effect of in-hospital breast milk intake on the gut microbiota of preterm infants.

OBJECTIVE: The aim of this study was to explore the effect of in-hospital breast milk intake on the development of early gut microbiota in preterm infants in two dimensions: longitudinal over time and cross-sectional between groups. METHODS: Researchers collected preterm infants' general data baseline characteristics, recorded their daily breast milk intake, probiotics, and antibiotics use, and collected their stool specimens at 1st week, 2 nd week, 3rd week and 4th week after birth. The researchers analyzed the effect of breast milk on gut microbiota of preterm infants by bioinformatics methods of intra-group longitudinal variation of gut microbiota structure and diversity in preterm infants and cross-sectional differences between >70 % in-hospital breast milk intake (BM) group and ≤70 % (PF) group. RESULTS: A total of 60 preterm infants were included in this study, and a total of 213 stool specimens were retained. BM had statistically different Shannon and Simpson indices between the first and fourth week after admission (P < 0.05), both of them showed a lower diversity in the later week than in the previous week. The Shannon index and Simpson index of BM from week 3 onwards were statistically different from PF (P < 0.05), and the Shannon index and Simpson index of BM were lower than those of PF. Significantly statistical differences (P < 0.05) were found in the beta diversity of gut microbiota in preterm infants as time progressed, and both showed a lower beta diversity in the later week than in the preceding week. The dominant taxa of PF in the first postnatal week were Bifidobacterium animalis, etc., the dominant taxa of BM in the third postnatal week were Clostridium_sensu_stricto _1, etc. CONCLUSIONS: The development and evolution of gut microbiota in preterm infants' in-hospital period was a continuous, non-random process, and similar trends in species composition and changes in gut microbes emerged in preterm infants with different ratio of breast milk intake. In the NICU setting, alpha diversity was lower in preterm infants in the >70 % breast milk intake group than in the ≤70 % group when compared between groups at the same time, which may be related to delayed maturation of gut microbes and represents a more developmental gut time window.

An MRI brain tumor segmentation method based on improved U-Net.

In order to improve the segmentation effect of brain tumor images and address the issue of feature information loss during convolutional neural network (CNN) training, we present an MRI brain tumor segmentation method that leverages an enhanced U-Net architecture. First, the ResNet50 network was used as the backbone network of the improved U-Net, the deeper CNN can improve the feature extraction effect. Next, the Residual Module was enhanced by incorporating the Convolutional Block Attention Module (CBAM). To increase characterization capabilities, focus on important features and suppress unnecessary features. Finally, the cross-entropy loss function and the Dice similarity coefficient are mixed to compose the loss function of the network. To solve the class unbalance problem of the data and enhance the tumor area segmentation outcome. The method's segmentation performance was evaluated using the test set. In this test set, the enhanced U-Net achieved an average Intersection over Union (IoU) of 86.64% and a Dice evaluation score of 87.47%. These values were 3.13% and 2.06% higher, respectively, compared to the original U-Net and R-Unet models. Consequently, the proposed enhanced U-Net in this study significantly improves the brain tumor segmentation efficacy, offering valuable technical support for MRI diagnosis and treatment.

SARS-CoV-2 infection causes dopaminergic neuron senescence.

COVID-19 patients commonly present with signs of central nervous system and/or peripheral nervous system dysfunction. Here, we show that midbrain dopamine (DA) neurons derived from human pluripotent stem cells (hPSCs) are selectively susceptible and permissive to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. SARS-CoV-2 infection of DA neurons triggers an inflammatory and cellular senescence response. High-throughput screening in hPSC-derived DA neurons identified several FDA-approved drugs that can rescue the cellular senescence phenotype by preventing SARS-CoV-2 infection. We also identified the inflammatory and cellular senescence signature and low levels of SARS-CoV-2 transcripts in human substantia nigra tissue of COVID-19 patients. Furthermore, we observed reduced numbers of neuromelanin+ and tyrosine-hydroxylase (TH)+ DA neurons and fibers in a cohort of severe COVID-19 patients. Our findings demonstrate that hPSC-derived DA neurons are susceptible to SARS-CoV-2, identify candidate neuroprotective drugs for COVID-19 patients, and suggest the need for careful, long-term monitoring of neurological problems in COVID-19 patients.

Large-Scale Synthesis of High Energy Thermal Battery Cathode Ni0.5Co0.5S2 by a Simple Sintering Technique.

With the synergies of multiple elements, bimetallic sulfides exhibit excellent performance as splendid electrode materials and effective catalysts. However, large-scale synthesis of high-performance single-phase multicomponent sulfides has always been a challenge. Based on thermodynamic calculations, the intermediate phases NiS2 and Co3S4 are devoted to the synthesis of single-phase Ni0.5Co0.5S2. Because the reaction from NiS2 and Co3S4 to Ni0.5Co0.5S2 goes through a lower energy, it thermodynamically contributes to achieving a single-phase structure. Thus, single-phase Ni0.5Co0.5S2 can be simply and quickly prepared by two-step sintering and successfully scalable for mass production. This technique can extend to the whole ingredients Ni1-xCoxS2. Ni0.5Co0.5S2 demonstrates excellent thermal stability and good conductivity. It delivers a specific capacity of 671 mAh·g-1 and a specific energy of 1173 Wh·kg-1 when applied to a thermal battery cathode, which are increased by 18.6% and 25.0%, respectively, compared to pristine NiS2 (566 mAh·g-1) and CoS2 (537 mAh·g-1). This work proposes an innovative sintering method, which is applicable for cost-efficient and large-scale synthesis of single-phase multicomponent sulfides.

The redox requirement and regulation during cell proliferation.

The intracellular metabolic network comprises a variety of reduction-oxidation (redox) reactions that occur in a temporally and spatially distinct manner. In order to coordinate these redox processes, mammalian cells utilize a collection of electron-carrying molecules common to many redox reactions, including NAD, NADP, coenzyme Q (CoQ), and glutathione (GSH). This review considers the metabolic basis of redox regulation in the context of cell proliferation by analyzing how cells acquire and utilize electron carriers to maintain directional carbon flux, sustain reductive biosynthesis, and support antioxidant defense. Elucidating the redox requirement during cell proliferation can advance the understanding of human diseases such as cancer, and reveal effective therapeutic opportunities in the clinic.

Diagnostic status and epidemiological characteristics of community-acquired bacterial meningitis in children from 2019 to 2020: a multicenter retrospective study.

Community-acquired bacterial meningitis (CABM) is the main cause of morbidity and mortality in children. The epidemiology of CABM is regional and highly dynamic. To clarify the diagnostic status and epidemiological characteristics of children with CABM in this region, and pay attention to the disease burden, so as to provide evidence for the prevention and treatment of CABM. By retrospective case analysis, the clinical data of 918 CABM cases in children aged 0-14 years in Zhejiang Province from January, 2019 to December, 2020 were collected. The etiological diagnosis rate of CABM in children was 23.1%, the annual incidence rate 4.42-6.15/100,000, the annual mortality rate 0.06-0.09/100,000,the cure and improvement rate 94.4%, and the case fatality rate 1.4%. The total incidence of neuroimaging abnormalities was 20.6%. The median length of stay for CABM children was 20(16) days, with an average cost of 21,531(24,835) yuan. In addition, the incidence rate was decreased with age. Escherichia coli(E.coli) and group B Streptococcus agalactiae(GBS) were the principal pathogens in CABM infant<3 months(43.3%, 34.1%), and Streptococcus pneumoniae(S. pneumoniae) was the most common pathogen in children ≥ 3 months(33.9%). In conclusion, the annual incidence and mortality of CABM in children aged 0-14 years in Zhejiang Province are at intermediate and low level. The distribution of CABM incidence and pathogen spectrum are different in age; the incidence of abnormal neuroimaging is high; and the economic burden is heavy.

Detecting Abnormality of Battery Lifetime from First-Cycle Data Using Few-Shot Learning.

The service life of large battery packs can be significantly influenced by only one or two abnormal cells with faster aging rates. However, the early-stage identification of lifetime abnormality is challenging due to the low abnormal rate and imperceptible initial performance deviations. This work proposes a lifetime abnormality detection method for batteries based on few-shot learning and using only the first-cycle aging data. Verified with the largest known dataset with 215 commercial lithium-ion batteries, the method can identify all abnormal batteries, with a false alarm rate of only 3.8%. It is also found that any capacity and resistance-based approach can easily fail to screen out a large proportion of the abnormal batteries, which should be given enough attention. This work highlights the opportunities to diagnose lifetime abnormalities via "big data" analysis, without requiring additional experimental effort or battery sensors, thereby leading to extended battery life, increased cost-benefit, and improved environmental friendliness.

Dynamically Cross-Linked, Self-Healable, and Stretchable All-Hydrogel Supercapacitor with Extraordinary Energy Density and Real-Time Pressure Sensing.

Wearable electronics with flexible, integrated, and self-powered multi-functions are becoming increasingly attractive, but their basic energy storage units are challenged in simultaneously high energy density, self-healing, and real-time sensing capability. To achieve this, a fully flexible and omni-healable all-hydrogel, that is dynamically crosslinked PVA@PANI hydrogel, is rationally designed and constructed via aniline/DMSO-emulsion-templated in situ freezing-polymerization strategy. The PVA@PANI sheet, not only possesses a honeycombed porous conductive mesh configuration with superior flexibility that provides numerous channels for unimpeded ions/electron transport and maximizes the utilization efficiency of pseudocapacitive PANI, but also can conform to complicated body surface, enabling effective detection and discrimination of body movements. As a consequence, the fabricated flexible PVA@PANI sheet electrode demonstrates an unprecedented specific capacitance (936.8 F g-1 ) and the assembled symmetric flexible all-solid-state supercapacitor delivers an extraordinary energy density of 40.98 Wh kg-1 , outperforming the previously highest-reported values of stretchable PVA@PANI hydrogel-based supercapacitors. What is more, such a flexible supercapacitor electrode enables precisely monitoring the full-range human activities in real-time, and fulfilling a quick response and excellent self-recovery. These outstanding flexible sensing and energy storage performances render this emerging PVA@PANI hydrogel highly promising for the next-generation wearable self-powered sensing electronics.

Multifunctional Regioisomeric Passivation Strategy for Fabricating Self-Driving, High Detectivity All-Inorganic Perovskite Photodetectors.

The fluorination of the aromatic multifunctional Lewis base passivation strategy has been demonstrated recently as an effective approach to markedly enhance the performance of perovskite photovoltaic devices. However, the regulation mechanisms of the passivation efficiency by varying the functional group position of fluorine (F) in the regioisomers have received little attention and inadequate research. Herein, a pair of bifluorine-substituted aminobenzoic acid regioisomers [3-amino-2,6-difluorobenzoic acid (13-FABA) and 4-amino-3,5-difluorobenzoic acid (14-FABA)] were employed to investigate the passivation effects of Lewis bases dependent on behaviors of the ortho/meta-substituted position of fluorine. The density functional theory calculation on electron cloud density, interaction energy, and the basicity of Lewis bases combined with experimental evidence reveal that the ortho-effect induced by fluorine substitution weakens the passivating effect of 13-FABA Lewis base and induces its molecular propensity to form internal salts, accelerating the degradation and deterioration of the device performance. Conversely, 14-FABA with meta-connected fluorine atoms exhibit superior efficacy in suppressing defects and enhancing hydrophobicity. Eventually, the 14-FABA-modified photodetectors (PDs) achieved a high detectivity of 1.69 × 1013 Jones, the comparatively lower dark current density of 2.2 × 10-10 A/cm2 among all-inorganic perovskite PD systems. Our work has not only clarified the fundamental mechanisms of the F-substituted position effects of Lewis base on suppressing defects but also provided a promising passivation strategy for perovskite films via designing the regioisomeric atoms in a multifunctional Lewis base molecule.

Development and accuracy of artificial intelligence-generated prediction of facial changes in orthodontic treatment: a scoping review. / äººå·¥æ™ºèƒ½é¢„æµ‹æ­£ç•¸é¢éƒ¨å˜åŒ–çš„ç ”ç©¶è¿›å±•å’Œå‡†ç¡®åº¦ï¼šæ¦‚å†µæ€§ç³»ç»Ÿç»¼è¿°.

Artificial intelligence (AI) has been utilized in soft-tissue analysis and prediction in orthodontic treatment planning, although its reliability has not been systematically assessed. This scoping review was conducted to outline the development of AI in terms of predicting soft-tissue changes after orthodontic treatment, as well as to comprehensively evaluate its prediction accuracy. Six electronic databases (PubMed, EBSCOhost, Web of Science, Embase, Cochrane Library, and Scopus) were searched up to March 14, 2023. Clinical studies investigating the performance of AI-based systems in predicting post-orthodontic soft-tissue alterations were included. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) and Joanna Briggs Institute (JBI) appraisal checklist for diagnostic test accuracy studies were applied to assess risk of bias, while the Grading of Recommendation, Assessment, Development, and Evaluation (GRADE) assessment was conducted to evaluate the certainty of outcomes. After screening 2500 studies, four non-randomized clinical trials were finally included for full-text evaluation. We found a low level of evidence indicating an estimated high overall accuracy of AI-generated prediction, whereas the lower lip and chin seemed to be the least predictable regions. Furthermore, the facial morphology simulated by AI via the fusion of multimodality images was considered to be reasonably true. Since all of the included studies that were not randomized clinical trials (non-RCTs) showed a moderate to high risk of bias, more well-designed clinical trials with sufficient sample size are needed in future work.

A predictive model for preterm infants with bronchopulmonary dysplasia based on ferroptosis-related lncRNAs.

BACKGROUND: Bronchopulmonary dysplasia (BPD) is the most challenging chronic lung disease for prematurity, with difficulties in early identification. Given lncRNA emerging as a novel biomarker and the regulator of ferroptosis, this study aims to develop a BPD predictive model based on ferroptosis-related lncRNAs (FRLs). METHODS: Using a rat model, we firstly explored mRNA levels of ferroptosis-related genes and ferrous iron accumulation in BPD rat lungs. Subsequently, a microarray dataset of umbilical cord tissue from 20 preterm infants with BPD and 34 preterm infants without BPD were downloaded from the Gene Expression Omnibus databases. Random forest and LASSO regression were conducted to identify diagnostic FRLs. Nomogram was used to construct a predictive BPD model based on the FRLs. Finally, umbilical cord blood lymphocytes of preterm infants born before 32 weeks gestational age and term infants were collected and determined the expression level of diagnostic FRLs by RT-qPCR. RESULTS: Increased iron accumulation and several dysregulated ferroptosis-associated genes were found in BPD rat lung tissues, indicating that ferroptosis was participating in the development of BPD. By exploring the microarray dataset of preterm infants with BPD, 6 FRLs, namely LINC00348, POT1-AS1, LINC01103, TTTY8, PACRG-AS1, LINC00691, were determined as diagnostic FRLs for modeling. The area under the receiver operator characteristic curve of the model was 0.932, showing good discrimination of BPD. In accordance with our analysis of microarray dataset, the mRNA levels of FRLs were significantly upregulated in umbilical cord blood lymphocytes from preterm infants who had high risk of BPD. CONCLUSION: The incorporation of FRLs into a predictive model offers a non-invasive approach to show promise in improving early detection and management of this challenging chronic lung disease in premature infant, enabling timely intervention and personalized treatment strategies.

Functional interrogation of twenty type 2 diabetes-associated genes using isogenic human embryonic stem cell-derived ß-like cells.

Genetic studies have identified numerous loci associated with type 2 diabetes (T2D), but the functional roles of many loci remain unexplored. Here, we engineered isogenic knockout human embryonic stem cell lines for 20 genes associated with T2D risk. We examined the impacts of each knockout on ß cell differentiation, functions, and survival. We generated gene expression and chromatin accessibility profiles on ß cells derived from each knockout line. Analyses of T2D-association signals overlapping HNF4A-dependent ATAC peaks identified a likely causal variant at the FAIM2 T2D-association signal. Additionally, the integrative association analyses identified four genes (CP, RNASE1, PCSK1N, and GSTA2) associated with insulin production, and two genes (TAGLN3 and DHRS2) associated with ß cell sensitivity to lipotoxicity. Finally, we leveraged deep ATAC-seq read coverage to assess allele-specific imbalance at variants heterozygous in the parental line and identified a single likely functional variant at each of 23 T2D-association signals.

Factors associated with afebrile presentation and delayed defervescence of bacterial meningitis in children under 3 years of age: a multi-centre retrospective analysis.

BACKGROUND: This multi-center study aimed to identify factors affecting fever and delayed defervescence in bacterial meningitis (BM) patients under 3 years of age because of the variability of fever in this patient population. METHODS: Only BM patients under 3 years treated at 49 centers in China from November 2018 to end-April 2021 were included in the study. Univariate and multivariate logistic regression analyses were performed to determine factors associated with afebrile presentation and fever of delayed defervescence. RESULTS: A total of 863 BM patients under 3 years were included in the study. Coagulase negative staphylococcus was associated with afebrile presentation (OR = 1.176), while septicaemia and ear-nose-throat infections were associated with fever (P < 0.05). The patients with fever were assigned into early and delayed defervescence groups based on defervescence time (less than and more than or equal to one week). Furthermore, Streptococcus agalactiae meningitis (OR = 1.124), concomitant gastrointestinal infection (OR = 1.276), encephalomalacia (or = 1.339), and subdural effusion (OR = 1.454) were independently associated with delayed defervescence (all P < 0.05). CONCLUSIONS: The findings can aid in the efficient utilization of fever in auxiliary diagnosis and evaluating the condition of the disease.

Managing Excess Lead Iodide with Ordered Distribution and Reduced Photoactivity via Chelating Ligands for Stable Inverted Perovskite Solar Cells.

Excess lead iodide (PbI2) aggregates distributed in perovskite photoreactive absorbers will perturb carrier collection and become a key source of instability in PSCs. Herein, a multisite heterocyclic ligand of 2-mercaptonicotinic acid (2-MNA) is introduced as a chelating agent to manage excess PbI2 in inverted PSCs. The chelating coordination of 2-MNA to Pb2+ ions through the carbonyl, sulfhydryl, and pyridinyl groups enables a high-quality perovskite film with reduced PbI2 aggregates and the formation of an ordered distribution at grain boundaries. Moreover, the coordination of 2-MNA with the [PbX6]4- octahedron effectively inhibits the photodecomposition of PbI2-rich perovskites, thus preventing the generation of metallic lead (Pb0) and iodine (I2) species in response to environmental stimuli. As a result, the inverted PSC based on a 2-MNA modified triple cation perovskite photoactive layer achieves a PCE of 21.27% and a fill factor of 82.07%, accompanied by improved thermal and photostability.

Proteogenomics of different urothelial bladder cancer stages reveals distinct molecular features for papillary cancer and carcinoma in situ.

The progression of urothelial bladder cancer (UC) is a complicated multi-step process. We perform a comprehensive multi-omics analysis of 448 samples from 190 UC patients, covering the whole spectrum of disease stages and grades. Proteogenomic integration analysis indicates the mutations of HRAS regulated mTOR signaling to form urothelial papilloma rather than papillary urothelial cancer (PUC). DNA damage is a key signaling pathway in the progression of carcinoma in situ (CIS) and related to APOBEC signature. Glucolipid metabolism increase and lower immune cell infiltration are associated with PUC compared to CIS. Proteomic analysis distinguishes the origins of invasive tumors (PUC-derived and CIS-derived), related to distinct clinical prognosis and molecular features. Additionally, loss of RBPMS, associated with CIS-derived tumors, is validated to increase the activity of AP-1 and promote metastasis. This study reveals the characteristics of two distinct branches (PUC and CIS) of UC progression and may eventually benefit clinical practice.

Plasma proteomic profiling discovers molecular features associated with upper tract urothelial carcinoma.

Upper tract urothelial carcinoma (UTUC) is often diagnosed late and exhibits poor prognosis. Limited data are available on potential non-invasive biomarkers for disease monitoring. Here, we investigate the proteomic profile of plasma in 362 UTUC patients and 239 healthy controls. We present an integrated tissue-plasma proteomic approach to infer the signature proteins for identifying patients with muscle-invasive UTUC. We discover a protein panel that reflects lymph node metastasis, which is of interest in identifying UTUC patients with high risk and poor prognosis. We also identify a ten-protein classifier and establish a progression clock predicting progression-free survival of UTUC patients. Finally, we further validate the signature proteins by parallel reaction monitoring assay in an independent cohort. Collectively, this study portrays the plasma proteomic landscape of a UTUC cohort and provides a valuable resource for further biological and diagnostic research in UTUC.

Brucea javanica oil inhibits tongue squamous cell invasion and metastasis by regulating miR-138-EZH2 pathway.

Tongue squamous cell carcinoma (TSCC) is one of the most common malignant tumors of head and neck. Its incidence is on the rise, and the proportion of young patients is gradually increasing, which is prone to tumor recurrence and metastasis. At present, there is no effective method to completely treat TSCC. Studies have shown that brucea javanica oil (BJO) has good antitumor activity against lung cancer and gastrointestinal tumors, but its therapeutic effect on TSCC is not clear. We have previously confirmed that oleic acid, the main component of BJO, can induce apoptosis of TSCC and reduce its invasion and metastasis ability. However, the anticancer effect and mechanism of BJO in TSCC remain unclear. In order to further explore the effects of BJO on the biological characteristics of TSCC cells, we studied the effects of different concentrations of BJO on the migration, invasion ability and epithelial mesenchymal transition (EMT) progression of TSCC cells and the possible mechanisms through in vitro experiments. We found that BJO could inhibit the invasion and metastasis of TSCC and up-regulate miR-138. After BJO treatment, the expression of E-cad was significantly increased, while the expression of EZH2, Slug, p-ERK1/2 and Vimentin was significantly decreased. EZH2 is a miR-138 target gene involved in TSCC. BJO inhibits TSCC invasion and metastasis by regulating the miR-138-EZH2 pathway. In vivo experiments have also well demonstrated the targeting effect of this pathway. This study provides a new therapeutic strategy for the treatment of TSCC.

Isogenic human trophectoderm cells demonstrate the role of NDUFA4 and associated variants in ZIKV infection.

Population-based genome-wide association studies (GWAS) normally require a large sample size, which can be labor intensive and costly. Recently, we reported a human induced pluripotent stem cell (hiPSC) array-based GWAS method, identifying NDUFA4 as a host factor for Zika virus (ZIKV) infection. In this study, we extended our analysis to trophectoderm cells, which constitute one of the major routes of mother-to-fetus transmission of ZIKV during pregnancy. We differentiated hiPSCs from various donors into trophectoderm cells. We then infected cells carrying loss of function mutations in NDUFA4, harboring risk versus non-risk alleles of SNPs (rs917172 and rs12386620) or having deletions in the NDUFA4 cis-regulatory region with ZIKV. We found that loss/reduction of NDUFA4 suppressed ZIKV infection in trophectoderm cells. This study validated our published hiPSC array-based system as a useful platform for GWAS and confirmed the role of NDUFA4 as a susceptibility locus for ZIKV in disease-relevant trophectoderm cells.