Search

Abstract The newly identified XBB.1.16‐containing sublineages, including XBB.1.5, have become the prevailing severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) variant in circulation. Unlike previous Omicron XBB variants (e.g., XBB.1.5 and XBB.1.9) harboring the F486P substitution, XBB.1.16 also carries a T478R substitution in the receptor‐binding domain (RBD). Numerous researchers have delved into the high transmissibility and immune evasion of XBB.1.16 subvariant. Therefore, developing a new vaccine targeting XBB.1.16, including variants of concern (VOCs), is paramount. In our study, we engineered a recombinant protein by directly linking the S‐RBD sequence of the XBB.1.16 strain of SARS‐CoV‐2 to the sequences of two heptad repeat sequences (HR1 and HR2) from the SARS‐CoV‐2 S2 subunit. Named the recombinant RBDXBB.1.16‐HR/trimeric protein, this fusion protein autonomously assembles into a trimer. Combined with an MF59‐like adjuvant, the RBDXBB.1.16‐HR vaccine induces a robust humoral immune response characterized by high titers of neutralizing antibodies against variant pseudovirus and authentic VOCs and cellular immune responses. Additionally, a fourth heterologous RBDXBB.1.16‐HR vaccine enhances both humoral and cellular immune response elicited by three‐dose mRNA vaccines. These findings demonstrate that the recombinant RBDXBB.1.16‐HR protein, featuring the new T478R mutation, effectively induces solid neutralizing antibodies to combat newly emerged XBB variants.

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants has decreased the efficacy of SARS-CoV-2 vaccines in containing coronavirus disease 2019 (COVID-19) over time, and booster vaccination strategies are urgently necessitated to achieve sufficient protection. Intranasal immunization can improve mucosal immunity, offering protection against the infection and sustaining the spread of SARS-CoV-2. In this study, an intranasal booster of the RBD-HR vaccine after two doses of the mRNA vaccine significantly increased the levels of specific binding antibodies in serum, nasal lavage fluid, and bronchoalveolar lavage fluid compared with only two doses of mRNA vaccine. After intranasal boosting with the RBD-HR vaccine, the levels of serum neutralizing antibodies against prototype and variant strains of SARS-CoV-2 pseudoviruses were markedly higher than those in mice receiving mRNA vaccine alone, and intranasal boosting with the RBD-HR vaccine also inhibited the binding of RBD to hACE2 receptors. Furthermore, the heterologous intranasal immunization regimen promoted extensive memory T cell responses and activated CD103+ dendritic cells in the respiratory mucosa, and potently enhanced the formation of T follicular helper cells and germinal center B cells in vital immune organs, including mediastinal lymph nodes, inguinal lymph nodes, and spleen. Collectively, these data infer that heterologous intranasal boosting with the RBD-HR vaccine elicited broad protective immunity against SARS-CoV-2 both locally and systemically.

Abstract Diabetes mellitus (DM) is a common chronic disease affecting humans globally. It is characterized by abnormally elevated blood glucose levels due to the failure of insulin production or reduction of insulin sensitivity and functionality. Insulin and glucagon‐like peptide (GLP)‐1 replenishment or improvement of insulin resistance are the two major strategies to treat diabetes. Recently, optogenetics that uses genetically encoded light‐sensitive proteins to precisely control cell functions has been regarded as a novel therapeutic strategy for diabetes. Here, we summarize the latest development of optogenetics and its integration with synthetic biology approaches to produce light‐responsive cells for insulin/GLP‐1 production, amelioration of insulin resistance and neuromodulation of insulin secretion. In addition, we introduce the development of cell encapsulation and delivery methods and smart bioelectronic devices for the in vivo application of optogenetics‐based cell therapy in diabetes. The remaining challenges for optogenetics‐based cell therapy in the clinical translational study are also discussed.

ObjectiveTo investigate the prevalence and influencing factors of stroke in residents aged 40 years and older in Guangdong province for developing stroke prevention and control policies. MethodsTotally 21 176 permanent residents aged 40 years and older were recruited with multistage random cluster sampling in urban and rural regions of 5 municipalities in Guangdong province for a survey conducted during July – December 2020. All the participants undertook face-to-face interview with a questionnaire designed by domestic experts, physical examination and laboratory tests. Unconditional multivariate logistic regression model was used to analyze influencing factors of stroke. ResultsAmong 16 993 participants surveyed effectively, 361 stroke sufferers were identified and the crude and age-adjusted stroke prevalence were 2 124.40/100 000 and 1 725.25/100 000, respectively. Multivariate unconditional logistic regression analysis revealed following risk factors of stroke among the participants: ≥ 50 years old, smoking, lack of physical activity, family history of stroke, hypertension, diabetes, dyslipidemia, high homocysteine, and atrial fibrillation or valvular heart disease; while, being female and with an individual annual income of 5 000 – 10 000 or more than 20 000 Chinese yuan were protective factors against stroke. ConclusionThe prevalence of stroke was relatively low and influenced mainly by gender, age, annual personal income, smoking, lack of physical activity, family history of stroke, hypertension, diabetes, dyslipidemia, high homocysteine, atrial fibrillation or valvular heart disease among urban and rural residents aged 40 years and older in Guangdong province.

Abstract Urgent research into innovative severe acute respiratory coronavirus‐2 (SARS‐CoV‐2) vaccines that may successfully prevent various emerging emerged variants, particularly the Omicron variant and its subvariants, is necessary. Here, we designed a chimeric adenovirus‐vectored vaccine named Ad5‐Beta/Delta. This vaccine was created by incorporating the receptor‐binding domain from the Delta variant, which has the L452R and T478K mutations, into the complete spike protein of the Beta variant. Both intramuscular (IM) and intranasal (IN) vaccination with Ad5‐Beta/Deta vaccine induced robust broad‐spectrum neutralization against Omicron BA.5‐included variants. IN immunization with Ad5‐Beta/Delta vaccine exhibited superior mucosal immunity, manifested by higher secretory IgA antibodies and more tissue‐resident memory T cells (TRM) in respiratory tract. The combination of IM and IN delivery of the Ad5‐Beta/Delta vaccine was capable of synergically eliciting stronger systemic and mucosal immune responses. Furthermore, the Ad5‐Beta/Delta vaccination demonstrated more effective boosting implications after two dosages of mRNA or subunit recombinant protein vaccine, indicating its capacity for utilization as a booster shot in the heterologous vaccination. These outcomes quantified Ad5‐Beta/Delta vaccine as a favorable vaccine can provide protective immunity versus SARS‐CoV‐2 pre‐Omicron variants of concern and BA.5‐included Omicron subvariants.

Wound infection is a major problem faced during wound healing. Therefore, it is necessary to develop wound dressings with excellent antimicrobial properties. Here, a smart response system of PVA-TPE/HA-AMP/SF/ALG wound dressing was prepared by a combination of chemical cross-linking and freeze-drying methods. We grafted AMP onto HA to endow the wound dressing with bacterial resistance and slow release of AMP. At the same time, the system detects bacterial activity in real time for precise antimicrobial activity (through the use of PVA-TPE) and modulates inflammation to reduce bacterial infection (through the use of AMP). In addition, the PVA-TPE/HA-AMP/SF/ALG wound dressing has a good three-dimensional mesh structure, which promotes cell proliferation, enhances collagen deposition and angiogenesis, and thus effectively promotes rapid healing of infected wounds. Moreover, it can induce the expression of inflammatory factors such as VEGF, TNF-α, IFN-γ, IL-4 and TGF-β1 in infected wounds through the Wnt/CAMK/p-PKC signaling pathway, inhibit inflammatory responses, promote wound healing and reduce scar formation. Therefore, the PVA-TPE/HA-AMP/SF/ALG wound dressing smart response system shows great promise in infected wound healing.

Abstract The transforming growth factor beta (TGF-β) is a crucial cytokine that get increasing concern in recent years to treat human diseases. This signal controls multiple cellular responses during embryonic development and tissue homeostasis through canonical and/or noncanonical signaling pathways. Dysregulated TGF-β signal plays an essential role in contributing to fibrosis via promoting the extracellular matrix deposition, and tumor progression via inducing the epithelial-to-mesenchymal transition, immunosuppression, and neovascularization at the advanced stage of cancer. Besides, the dysregulation of TGF-beta signal also involves in other human diseases including anemia, inflammatory disease, wound healing and cardiovascular disease et al. Therefore, this signal is proposed to be a promising therapeutic target in these diseases. Recently, multiple strategies targeting TGF-β signals including neutralizing antibodies, ligand traps, small-molecule receptor kinase inhibitors targeting ligand–receptor signaling pathways, antisense oligonucleotides to disrupt the production of TGF-β at the transcriptional level, and vaccine are under evaluation of safety and efficacy for the forementioned diseases in clinical trials. Here, in this review, we firstly summarized the biology and function of TGF-β in physiological and pathological conditions, elaborated TGF-β associated signal transduction. And then, we analyzed the current advances in preclinical studies and clinical strategies targeting TGF-β signal transduction to treat diseases.

The SARS-CoV-2 Omicron variant has quickly become the predominant circulating variant, due to the high transmissibility and immune escape. Here, the authors develop a trimeric protein vaccine candidate and show a sustained humoral immune response, and protection from challenge (Omicron and Delta) in various animal models.

Based on electrochemical biosensing technology, chitosan was used as bridge agent, combined with gold nanoparticles and horseradish peroxidase electrical signal amplification system, and FcεRI receptor protein was used as general molecular probe to adsorb anti-bovine milk α-casein antibody IgE, constructed a nano-gold immunosensor for the detection of allergen α-casein in bovine milk, and the milk α-casein was verified by time-current curve. The results showed that the kinetic equation of α-casein-IgE (immunoglobulins E) interaction conforms to the hyperbolic law, the results met the hyperbolic fitting criterion R2≥0.95, and had a substrate saturation effect similar to that of enzyme-substrate interaction. The value of the α-casein allosteric interaction constant (Ka) was 4.096×10−12 mol/L calculated by referring to the Michaelis constant. The biosensor developed in this study could bind to the specific IgE of allergens and realize ultrasensitive detection of allergens. The detection method had high sensitivity, simple operation and low cost, and could provide a new detection method for allergic reactions caused by low-dose allergens.

Abstract BA.4 and BA.5 (BA.4/5), the subvariants of Omicron, are more transmissible than BA.1 with more robust immune evasion capability because of its unique spike protein mutations. In light of such situation, the vaccination against severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is in desperate need of the third booster. It has been reported that heterologous boosters might produce more effective immunity against wild‐type SARS‐CoV‐2 and the variants. Additionally, the third heterologous protein subunit booster should be considered potentially. In the present study, we prepared a Delta full‐length spike protein sequence‐based mRNA vaccine as the “priming” shot and developed a recombinant trimeric receptor‐binding domain (RBD) protein vaccine referred to as RBD–HR/trimer as a third heterologous booster. Compared to the homologous mRNA group, the heterologous group (RBD–HR/trimer vaccine primed with two mRNA vaccines) induced higher neutralizing antibody titers against BA.4/5‐included SARS‐CoV‐2 variants. In addition, heterologous vaccination exhibited stronger cellular immune response and long‐lasting memory response than the homologous mRNA vaccine. In conclusion, a third heterologous boosting with RBD–HR/trimer following two‐dose mRNA priming vaccination should be a superior strategy than a third homologous mRNA vaccine. The RBD–HR/trimer vaccine becomes an appropriate candidate for a booster immune injection.

Connective tissue growth factor (CTGF), a multifunctional protein of the CCN family, regulates cell proliferation, differentiation, adhesion, and a variety of other biological processes. It is involved in the disease-related pathways such as the Hippo pathway, p53 and nuclear factor kappa-B (NF-κB) pathways and thus contributes to the developments of inflammation, fibrosis, cancer and other diseases as a downstream effector. Therefore, CTGF might be a potential therapeutic target for treating various diseases. In recent years, the research on the potential of CTGF in the treatment of diseases has also been paid more attention. Several drugs targeting CTGF (monoclonal antibodies FG3149 and FG3019) are being assessed by clinical or preclinical trials and have shown promising outcomes. In this review, the cellular events regulated by CTGF, and the relationships between CTGF and pathogenesis of diseases are systematically summarized. In addition, we highlight the current researches, focusing on the preclinical and clinical trials concerned with CTGF as the therapeutic target.

Abstract Transforming growth factor β (TGF-β) has long been identified with its intensive involvement in early embryonic development and organogenesis, immune supervision, tissue repair, and adult homeostasis. The role of TGF-β in fibrosis and cancer is complex and sometimes even contradictory, exhibiting either inhibitory or promoting effects depending on the stage of the disease. Under pathological conditions, overexpressed TGF-β causes epithelial-mesenchymal transition (EMT), extracellular matrix (ECM) deposition, cancer-associated fibroblast (CAF) formation, which leads to fibrotic disease, and cancer. Given the critical role of TGF-β and its downstream molecules in the progression of fibrosis and cancers, therapeutics targeting TGF-β signaling appears to be a promising strategy. However, due to potential systemic cytotoxicity, the development of TGF-β therapeutics has lagged. In this review, we summarized the biological process of TGF-β, with its dual role in fibrosis and tumorigenesis, and the clinical application of TGF-β-targeting therapies.

The morphology of urban residential blocks in China, which is strictly affected by regulations, can potentially improve or deteriorate microclimates. This paper first proposes a framework for identifying typical residential block typologies using Nanjing as an example. A thorough investigation, consisting of 114 samples, was conducted, and 18 typical residential block typologies were summarized. Second, 3D non-isothermal numerical simulations were performed on the hottest days of summer using the ENVI-met. The effect of morphological indices on the microclimate at the pedestrian level was explored using statistical methods and a novel graphic method named m-SpaceMate. The results revealed a strong correlation between the urban heat island intensity (UHII), mean radiation temperature, and universal thermal climate index (UTCI) and floor area ratio (FAR), as well as between wind velocity (U) and building coverage ratio (BCR). A significant increase in FAR (by approximately 1.0) can result in a low UTCI that was driven by MRT and shading conditions. Six-floor blocks, with FAR between 1.8 and 2.1, had a better overall thermal environment (except for lower U) than that of 11-floor blocks. When considering a similar BCR, blocks with slab-type buildings tended to have a U that was higher by approximately 30%.

Erythema multiforme is a widespread hypersensitivity reaction, its pathogenesis is related to a variety of factors, including drugs and viral and bacterial infections. It is true that erythema multiforme is often caused by viruses while current studies suggest that it is mostly associated with herpes simplex virus infection, rarely associated with varicella-zoster virus infection. Here, we report a 50-year-old man admitted to our hospital because of rashes on the left rib with pain for 9 days and on limbs and hands for 2 days. Laboratory data showed that varicella-zoster virus (VZV-DNA) test was negative in blood by qualitative polymerase chain reaction. Herpes zoster virus IgM (VZV-IgM) enzyme linked immune sorbent assay was negative, and herpes zoster virus IgG (VZV-IgG) enzyme linked immune sorbent assay was positive. Herpes zoster and erythema multiforme was diagnosed. After treatment with antiviral, antiallergic, and topical drugs, the rashes was significantly improved. Our case report contributes to the pathogenesis of erythema multiforme.

BackgroundThis study aimed to establish and validate an accurate prognostic model, based on demographic and clinical parameters, for predicting the cancer-specific survival (CSS) of patients with poorly differentiated thyroid carcinoma (PDTC).Materials and methodsPatients diagnosed with PDTC between 2004 to 2015 were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Randomly split the data into training and validation sets. Kaplan–Meier analysis with the log-rank test was performed to compare the survival distribution among cases. Univariate and multivariate Cox proportional hazards regression analyses were used to identify independent prognostic factors, which were subsequently utilized to construct a nomogram for predicting the 5- and 10-year cancer-specific survival of patients with PDTC. The discriminative ability and calibration of the nomogram model were assessed using the concordance index and calibration plots, respectively. In addition, we performed a decision curve analysis to assess the clinical value of the nomogram. Simultaneously, we compared the predictive performance of the nomogram model against that of the American Joint Committee on Cancer (AJCC) T-, N-, M-stage.ResultsA total of 970 eligible patients were randomly assigned to either a training cohort (n = 679) or a validation cohort (n = 291). The Kaplan–Meier analysis revealed that there were no significant differences in cumulative survival based on the race, radiation, and marital status of patients. The stepwise Cox regression model showed that the model was optimal when the following five variables were included: age, tumor size, T-, N-, and M-stage. A nomogram was developed as a graphical representation of the model and exhibited good calibration and discriminative ability in the study. Compared to the T-, N-, and M-stage, the C-index of nomogram (training group: 0.807, validation group: 0.802), the areas under the receiver operating characteristic curve of the training set (5-year AUC: 0.843, 10-year AUC:0.834) and the validation set (5-year AUC:0.878, 10-year AUC:0.811), and the calibration plots of this model all exhibited better performance. At last, compared with T-, N-, and M-stage, the decision curve analysis indicated that the nomogram had excellent clinical net benefit.ConclusionsThe nomogram developed by us can accurately predict the CSS of PDTC patients. It can help clinicians determine appropriate treatment strategies for poorly differentiated thyroid carcinoma patients.

Background and AimNon-alcoholic fatty liver disease (NAFLD) is closely related to cardiovascular diseases (CVD). A newly proposed definition is metabolic dysfunction-associated fatty liver disease (MAFLD), which was changed from NAFLD. The clinical effect of this change on abnormalities of cardiac structure and function is yet unknown. We aimed to examine whether MAFLD is associated with left ventricular (LV) diastolic dysfunction (LVDD) and cardiac remolding and further identify the impact of different subgroups and severity of MAFLD.MethodWe evaluated 228 participants without known CVDs. Participants were categorized by the presence of MAFLD and the normal group. Then, patients with MAFLD were subclassified into three subgroups: MAFLD patients with diabetes (diabetes subgroup), overweight/obesity patients (overweight/obesity subgroup), and lean/normal-weight patients who had two metabolic risk abnormalities (lean metabolic dysfunction subgroup). Furthermore, the severity of hepatic steatosis was assessed by transient elastography (FibroScan®) with a controlled attenuation parameter (CAP), and patients with MAFLD were divided into normal, mild, moderate, and severe hepatic steatosis groups based on CAP value. Cardiac structure and function were examined by echocardiography.ResultsLVDD was significantly more prevalent in the MAFLD group (24.6% vs. 60.8%, p < 0.001) compared to the normal group. The overweight subgroup and diabetes subgroup were significantly associated with signs of cardiac remolding, including interventricular septum thickness, LV posterior wall thickness, left atrial diameter (all p

The prevalence and incidence of metabolic-associated fatty liver disease (MAFLD), a clinically heterogeneous disease whose primary clinical therapies include dietary control and exercise therapy, is increasing worldwide and constitutes a significant medical burden. Gut microbes influence the physiopathological processes of the liver through different mechanisms based on the gut-liver axis. Exosomes are essential carriers of intercellular communication. Most previous studies have focused on adipocyte- and hepatocyte-derived exosomes, while the critical role of microbial-derived exosomes and the molecular mechanisms behind them in MAFLD have received little attention. Therefore, we searched and screened the latest relevant studies in the PubMeb database to elucidate the link between microbial-derived exosomes and the pathogenesis of MAFLD, mainly in terms of insulin resistance, intestinal barrier, inflammatory response, lipid metabolism, and liver fibrosis. The aim was to provide a theoretical framework and support for clinical protocols and innovative drug development.

PurposeAnaplastic thyroid carcinoma (ATC) and primary squamous cell carcinoma of the thyroid (PSCCTh) have similar histological findings and are currently treated using the same approaches; however, the characteristics and prognosis of these cancers are poorly researched. The objective of this study was to determine the differences in characteristics between ATC and PSCCTh and establish prognostic models.Patients and MethodsAll variables of patients with ATC and PSCCTh, diagnosed from 2004–2015, were retrieved from the Surveillance, Epidemiology, and End Results Program (SEER) database. Percentage differences for categorical data were compared using the Chi-square test. Kaplan-Meier curves, log-rank test, and Cox-regression for survival analysis, and C-index value was used to evaluate the performance of the prognostic models.ResultsAfter application of the inclusion and exclusion criteria, a total of 1164 ATC and 124 PSCCTh patients, diagnosed from 2004 to 2015, were included in the study. There were no differences in sex, ethnicity, age, marital status, or percentage of proximal metastases between the two cancers; however, radiotherapy, chemotherapy, incidence of surgical treatment, and presence of multiple primary tumors were higher in patients with ATC than those with PSCCTh. Further cancer-specific survival (CSS) of patients with PSCCTh was better than that of patients with ATC. Prognostic factors were not identical for the two cancers. Multivariate Cox model analysis indicated that age, sex, radiotherapy, chemotherapy, surgery, multiple primary tumors, marital status, and distant metastasis status are independent prognostic factors for CSS in patients with ATC, while for patients with PSCCTh, the corresponding factors are age, radiotherapy, multiple primary tumors, and surgery. The C-index values of the two models were both > 0.8, indicating that the models exhibited good discriminative ability.ConclusionPrognostic factors influencing CSS were not identical in patients with ATC and PSCCTh. These findings indicate that different clinical treatment and management plans are required for patients with these two types of thyroid cancer.

It is essential to estimate the indoor pesticides/insecticides exposure risk since reports show that 80% of human exposure to pesticides occurs indoors. As one of the three major contamination sources, surface collected pesticides contributed significantly to this risk. Here, a highly sensitive liquid freestanding membrane (FSM) SERS method based on iodide modified silver nanoparticles (Ag NPs) was developed for quantitative detection of insecticide deltamethrin (DM) residues in solution phase samples and on surfaces with good accuracy and high sensitivity. The DM SERS spectrum from 500 to 2500 cm−1 resembled the normal Raman counterpart of solid DM. Similar bands at 563, 1000, 1165, 1207, 1735, and 2253 cm−1 were observed as in the literature. For the quantitative analysis, the strongest peak at 1000 cm−1 that was assigned to the stretching mode of the benzene ring and the deformation mode of C-C was selected. The peak intensity at 1000 cm−1 and the concentration of DM showed excellent linearity from 39 to 5000 ppb with a regression equation I = 649.428 + 1.327 C (correlation coefficient R2 = 0.991). The limit of detection (LOD) of the DM was found to be as low as 11 ppb. Statistical comparison between the proposed and the HPLC methods for the analysis of insecticide deltamethrin (DM) residues in solution phase samples showed no significant difference. DM residue analysis on the surface was mimicked by dropping DM pesticide on the glass surface. It is found that DM exhibited high residue levels up to one week after exposure. This proposed SERS method could find application in the household pesticide residues analysis.

To achieve automatic disc cutter replacement of shield machines, measuring the accurate pose of the disc cutter holder by machine vision is crucial. However, under polluted and restricted illumination conditions, achieving pose estimation by vision is a great challenge. This paper proposes a line-features-based pose estimation method for the disc cutter holder of the shield machine by using a monocular camera. For the blurring effect of rounded corners on the image edge, a rounded edge model is established to obtain edge points that better match the 3D model of the workpiece. To obtain the edge search box corresponding to each edge, a contour separation method based on an adaptive threshold region growing method is proposed. By preprocesses on the edge points of each edge, the efficiency and the accuracy of RANSAC linear fitting are improved. The experimental result shows that the proposed pose estimation method is highly reliable and can meet the measurement accuracy requirements in practical engineering applications.

The motivation of this research is to explore the contributing factors of driving distraction and compare the contributing factors for three typical distracted driving behaviours: drinking water, answering a phone and using mobile phone application (APP) while driving. An online survey including a driving behaviour scale and the Theory of Planned Behaviour Questionnaire (TPB Questionnaire) was conducted to obtain data related to these driving distractions. An integral structural equation model based on the Theory of Planned Behaviour (TPB) was established to explain the factors causing three typical distracted behaviours, and the causes of differences for three typical distracted behaviours were compared. The result shows that the attitudes and perceived behaviour control are the main factors causing distracted behaviours, and the subjective norm has a significant impact on answering a phone while driving. The occurrence of a distracted driving behaviour is the consequence of behaviour intention and perceived behaviour control. These conclusions provide insights for implementing behaviour modification and traffic laws education.

Drowning is a major public health problem and a leading cause of death in children living in developing countries. We seek better machine learning (ML) algorithms to provide a novel risk-assessment insight on non-fatal drowning prediction. The data on non-fatal drowning were collected in Qingyuan city, Guangdong Province, China. We developed four ML models to predict the non-fatal drowning risk, including a logistic regression model (LR), random forest model (RF), support vector machine model (SVM), and stacking-based model, on three primary learners (LR, RF, SVM). The area under the curve (AUC), F1 value, accuracy, sensitivity, and specificity were calculated to evaluate the predictive ability of the different learning algorithms. This study included a total of 8390 children. Of those, 12.07% (1013) had experienced non-fatal drowning. We found the following risk factors are closely associated with the risk of non-fatal drowning: the frequency of swimming in open water, distance between the school and the surrounding open waters, swimming skills, personality (introvert) and relationality with family members. Compared to the other three base models, the stacking generalization model achieved a superior performance in the non-fatal drowning dataset (AUC = 0.741, sensitivity = 0.625, F1 value = 0.359, accuracy = 0.739 and specificity = 0.754). This study indicates that applying stacking ensemble algorithms in the non-fatal drowning dataset may outperform other ML models.

The health condition of a wheelset bearing, the key component of a railway bogie, has a considerable impact on the safety of a train. Traditional bearing fault diagnosis techniques generally extract signals manually and then diagnose the bearing health conditions through the classifier. However, high-speed trains (HSTs) are usually faced with variable loads, variable speeds, and strong environmental noise, which pose a huge challenge to the application of the traditional bearing fault diagnosis methods in wheelset bearing fault diagnosis. Therefore, this paper proposes a 1D residual block, and based on the block, a novel deeper 1D convolutional neural network (Der-1DCNN) is proposed. The framework includes the idea of residual learning and can effectively learn high-level and abstract features while effectively alleviating the problem of training difficulty and the performance degradation of a deeper network. Additionally, for the first time, we fully use the wide convolution kernel and dropout technology to improve the model's ability to learn low-frequency signal features related to the fault components and to enhance the network's generalization performance. By constructing a deep residual learning network, Der-1DCNN can adaptively learn the deep fault features of the original vibration signal. This method not only achieves very high diagnostic accuracy for the fault diagnosis task of wheelset bearings in HSTs under strong noise environment, but also its performance is quite superior when the train's working load changes without any domain adaptation algorithm processing. The proposed Der-1DCNN is evaluated on the dataset of the multi-operating conditions of the wheelset bearings of HSTs. Experiments show that this method shows a better diagnostic performance compared with the state-of-the-art deep learning methods of bearing fault diagnosis, which proves the method's effectiveness and superiority.

The proportion of universal segment in tunnel construction is constantly increasing. A key factor affecting the quality of tunnel construction is the selection of the shield segment assembly points. Nevertheless, the quality and efficiency of the current manual selection method cannot be guaranteed. To realize a high correct rate, high efficiency and intelligence of universal segment assembly points selection, an intelligent selection method of assembly points is proposed. First, the objective function is established by considering the thrust cylinder stroke and shield tail gap differences. Second, to adaptively optimize the weights of the objective function, the working conditions are divided into 81 intervals, and a genetic algorithm is proposed to optimize weights in each interval. Third, a Monte-Carlo-based method is proposed to generate an example dataset, which is used for the genetic algorithm to optimize the weights. Finally, the proposed method was applied to the segment assembly points selection for Line 8 of the Zhengzhou rail transit in China. The results show that the method of assembly segment selection can reach a 90.6% correct rate in the field. The research results of this paper can be used for the selection of the universal shield segment assembly points.

ObjectiveProspective negative imagery is suggested to play an important role in the development and maintenance of anxiety and depression. The Prospective Imagery Task (PIT) was developed to assess prospective imagery. Given the importance of prospective imagery for mental health in the Chinese cultural context, our objective was to examine the psychometric properties of the PIT in a Chinese sample.MethodsThe instrument was validated among a sample of 1,372 Chinese individuals (mean age = 19.98, SD = 4.57; 35.2% male) who completed the PIT immediately following the Beck Depression Inventory-II (BDI-II) and State-Trait Anxiety Inventory-Trait version (STAI-T).ResultsThe two-factor structure of the PIT was in line with the original study, with satisfactory reliability and positive correlations with the BDI-II and STAI-T scores. Latent profile analysis revealed a three-class pattern. The measurement invariance indicated that the instrument can be used among different age groups as well as among males and females.ConclusionThe Chinese version of the PIT is a reliable and valid tool to measure prospective imagery, and the positive subscale is meaningful for clinical psychology. Limitations and future research directions are discussed.

With an increase of service users’ demands on high quality of services (QoS), more and more efficient service computing models are proposed. The development of cloud computing, fog computing, and edge computing brings a number of challenges, e.g., QoS optimization and energy saving. We do a comprehensive survey on QoS optimization and energy saving in cloud computing, fog computing, edge computing, and IoT environments. We summarize the main challenges and analyze corresponding solutions proposed by existing works. This survey aims to help readers have a deeper understanding on the concepts of different computing models and study the techniques of QoS optimization and energy saving in these models.

The visual measurement system plays a vital role in the disc cutter changing robot of the shield machine, and its accuracy directly determines the success rate of the disc cutter grasping. However, the actual industrial environment with strong noise brings a great challenge to the pose measurement methods. The existing methods are difficult to meet the required accuracy of pose measurement based on machine vision under the disc cutter changing conditions. To solve this problem, we propose a monocular visual pose measurement method consisting of the high precision optimal solution to the PnP problem (OPnP) method and the highly robust distance matching (DM) method. First, the OPnP method is used to calculate the rough pose of the shield machine’s cutter holder, and then the DM method is used to measure its pose accurately. Simulation results show that the proposed monocular measurement method has better accuracy and robustness than the several mainstream PnP methods. The experimental results also show that the maximum error of the proposed method is 0.28° in the direction of rotation and 0.32 mm in the direction of translation, which can meet the measurement accuracy requirement of the vision system of the disc cutter changing robot in practical engineering application.

The authors wish to make the following correction to this paper [1]. Due to mislabeling, the following figures: [...]

Neonatal γ-immunoglobulin (IgG) Fc receptor (FcγRn) is a receptor that transports IgG across the intestinal mucosa, placenta, and mammary gland, ensuring the balance of IgG and albumin in the body. These functions of FcγRn depend on the intracellular signal transduction and activation caused by the combination of its extracellular domain and IgG Fc domain. Nevertheless, there are still no kinetic studies on this interaction. Consequently, in the present study, we successfully constructed the human FcγRn (hFcγRn) electrochemical receptor sensor. The signal amplification system formed by chitosan nanogold-hFcγRn protein and horseradish peroxidase was used to simulate the cell signal amplification system in vivo, and the kinetic effects between seven IgG and hFcγRn receptors from different species were quantitatively measured. The results showed that the interaction of these seven IgGs with hFcγRn was similar to the catalytic kinetics of enzyme and substrate, and there was a ligand-receptor saturation effect. The order of the interconnect allosteric constants (Ka), which is similar to the Michaelis constant (Km), was human IgG < bovine IgG < horse IgG < rabbit IgG < sheep IgG < donkey IgG < quail IgY. The results showed that hFcγRn had the strongest ability to transport human IgG, which was consistent with the evolution of the system. Therefore, our hFcγRn electrochemical receptor sensor can be used to measure and evaluate the interconnected allosteric network. It is also an essential parameter of the interaction between hFcγRn and different IgGs and, thus, provides a new detection and evaluation method for immunoemulsion, therapeutic monoclonal antibody therapy, heteroantibody treatment, and half-life research.

Background: Antimicrobial resistance (AMR) is a great threat to public health. The primary cause of AMR is human antibiotic misuse. Little is known about regional differences of antibiotic misuse behaviours in China. Objectives: To explore the antibiotic misuse behaviours among university students in western and eastern China and find out the regional differences. Methods: Participants were recruited from universities in less developed Guizhou Province and developed Zhejiang Province using a cluster random sampling method. A self-administered questionnaire was designed to collect data, and the χ2 test and logistic regression were adopted to assess the associations between region and antibiotic misuse behaviours. Results: A total of 2073 university students from Guizhou and 1922 from Zhejiang completed questionnaires. Students in Guizhou had lower household income, parents’ education, and urban residence proportion than those in Zhejiang. Compared with those in Zhejiang, students in Guizhou had higher antibiotic use prescribed by doctors (79.8% vs 56.2%) and self-medication with antibiotics (33.0% vs 16.1%). Students in Guizhou were more likely to buy over-the-counter antibiotics without prescriptions (73.9% vs 63.4%), ask for antibiotics from doctors (21.4% vs 15.6%), and use antibiotics prophylactically (29.9% vs 15.7%). Adjusted models showed that the less developed region was significantly associated with higher antibiotic misuse behaviours. Conclusions: Misuse of antibiotics by well-educated young adults was very high in two regions but most serious in the less developed one. Campaigns are urgently needed to promote appropriate antibiotic use especially in less developed regions.

Increased transcriptional levels of genes encoding antioxidant enzymes play important protective roles in coping with excessive accumulation of reactive oxygen species (ROS) in plants exposed to various abiotic stresses. To fully elucidate different evolutions and functions of ROS-scavenging enzymatic genes, we isolated iron superoxide dismutase (FeSOD), dehydroascorbate reductase (DHAR) and monodehydroascorbate reductase (MDHAR) from white clover for the first time and subsequently tested dynamic expression profiles of these genes together with previously identified other antioxidant enzyme genes including copper zinc superoxide dismutase (Cu/ZnSOD), manganese superoxide dismutase (MnSOD), glutathione reductase (GR), peroxidase (POD), catalase (CAT), and ascorbate peroxidase (APX) in response to cold, drought, salinity, cadmium stress and exogenous abscisic acid (ABA) or spermidine (Spd) treatment. The cloned fragments of FeSOD, DHAR and MDHAR genes were 630, 471 and 669 bp nucleotide sequences encoding 210, 157 and 223 amino acids, respectively. Phylogenetic analysis indicated that both amino acid and nucleotide sequences of these three genes are highly conservative. In addition, the analysis of genes expression showed the transcription of GR, POD, MDHAR, DHAR and Cu/ZnSOD were rapidly activated with relatively high abundance during cold stress. Differently, CAT, APX, FeSOD, Cu/ZnSOD and MnSOD exhibited more abundant transcripts compared to others under drought stress. Under salt stress, CAT was induced preferentially (3–12 h) compared to GR which was induced later (12–72 h). Cadmium stress mainly up-regulated Cu/ZnSOD, DHAR and MDHAR. Interestingly, most of genes expression induced by ABA or Spd happened prior to various abiotic stresses. The particular expression patterns and different response time of these genes indicated that white clover differentially activates genes encoding antioxidant enzymes to mitigate the damage of ROS during various environmental stresses.

Sudan grass (Sorghum sudanense) is an annual warm-season gramineous forage grass that is widely used as pasture, hay, and silage. However, drought stress severely impacts its yield, and there is limited information about the mechanisms of drought tolerance in Sudan grass. In this study, we used next-generation sequencing to identify differentially expressed genes (DEGs) in the Sudan grass variety Wulate No.1, and we developed simple sequence repeat (SSR) markers associated with drought stress. From 852,543,826 raw reads, nearly 816,854,366 clean reads were identified and used for analysis. A total of 80,686 unigenes were obtained via de novo assembly of the clean reads including 45,065 unigenes (55.9%) that were identified as coding sequences (CDSs). According to Gene Ontology analysis, 31,444 unigenes were annotated, 11,778 unigenes were identified to 25 categories in the clusters of orthologous groups of proteins (KOG) classification, and 11,223 unigenes were assigned to 280 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Additionally, there were 2,329 DEGs under a short-term of 25% polyethylene glycol (PEG) treatment, while 5,101 DEGs were identified under the long-term of 25% PEG treatment. DEGs were enriched in pathways of carbon fixation in photosynthetic organisms and plant hormone signal transduction which played a leading role in short-term of drought stress. However, DEGs were mainly enriched in pathway of plant hormone signal transduction that played an important role under long-term of drought stress. To increase accuracy, we excluded all the DEGs of all controls, specifically, five DEGs that were associated with high PEG concentrations were found through RNA-Seq. All five genes were up-regulated under drought stress, but the functions of the genes remain unclear. In addition, we identified 17,548 SSRs obtained from 80,686 unigenes. The newly identified drought tolerance DEGs will contribute to transgenic breeding efforts, while SSRs developed from high-throughput transcriptome data will facilitate marker-assisted selection for all traits in Sudan grass.

Operating under harsh conditions and exposed to fluctuating loads for extended periods, wind turbines experience a heightened vulnerability in their key components. Early fault detection is crucial to enhance the reliability of wind turbines, minimize downtime, and optimize power generation efficiency. Although deep learning techniques have been widely applied to fault diagnosis tasks, yielding remarkable performance, practical implementations frequently confront the obstacle of acquiring a substantial quantity of labeled data to train an effective deep learning model. Consequently, this paper introduces an unsupervised global and local domain adaptation network (GLDAN) for fault diagnosis across wind turbines, enabling the model to efficiently transfer acquired knowledge to the target domain in the absence of labeled data. This feature renders it an appropriate solution for situations with limited labeled data availability. Employing adversarial training, GLDAN aligns global domain distributions, diminishing the overall discrepancy between source and target domains, and local domain distributions within a single fault category for both domains, capturing more intricate and specific fault features. The proposed approach is corroborated using actual wind farm data, and comprehensive experimental results demonstrate that GLDAN surpasses deep global domain adaptation methods in cross-wind turbine fault diagnosis, underlining its practical value in the field. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Medical Biochemistry is the property of Society of Medical Biochemists of Serbia and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)