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Abstract Background The aim of this study was to investigate the effects of introducing the Enhanced Recovery After Surgery (ERAS) nursing model on postoperative delirium occurrence and rehabilitation quality in elderly patients with femoral neck fractures. Methods A total of 160 elderly patients with femoral neck fractures, who met the inclusion criteria and were admitted between March 2021 to March 2023, were divided into two groups: the traditional care group and the ERAS nursing model group. In addition to traditional care measures, the ERAS nursing model group received interventions based on the principles of the ERAS nursing model. The occurrence of delirium and sleep quality were observed at 24, 48, and 72 h postoperatively, as well as during the overall hospital stay. The duration of hospitalization, time to first mobilization, and post-discharge follow-up on quality of life were compared between the two groups. Results The ERAS nursing model group exhibited a significant difference in the occurrence of delirium at 48 and 72 h postoperatively, as well as during the overall hospital stay (P 0.05). The sleep quality of the two groups showed a statistically significant difference (P

Abstract Various exciton species in transition metal dichalcogenides (TMDs), such as neutral excitons, trions (charged excitons), dark excitons, and biexcitons, have been individually discovered with distinct light-matter interactions. In terms of valley-spin locked band structures and electron-hole configurations, these exciton species demonstrate flexible control of emission light with degrees of freedom (DOFs) such as intensity, polarization, frequency, and dynamics. However, it remains elusive to fully manipulate different exciton species on demand for practical photonic applications. Here, we investigate the contrasting light-matter interactions to control multiple DOFs of emission light in a hybrid monolayer WSe2-Ag nanowire (NW) structure by taking advantage of various exciton species. These excitons, including trions, dark excitons, and biexcitons, are found to couple independently with propagating surface plasmon polaritons (SPPs) of Ag NW in quite different ways, thanks to the orientations of transition dipoles. Consistent with the simulations, the dark excitons and dark trions show extremely high coupling efficiency with SPPs, while the trions demonstrate directional chiral-coupling features. This study presents a crucial step towards the ultimate goal of exploiting the comprehensive spectrum of TMD excitons for optical information processing and quantum optics.

ABSTRACTIce, Cloud, and land Elevation Satellite-2 (ICESat-2) provides effective photon-counting light detection and ranging (LiDAR) data for estimating forest height across extensive geographical areas. Although prior studies have illustrated canopy conditions during leaf-on and leaf-off phases may influence ICESat-2 derived forest heights, a comprehensive understanding of this effect remains incomplete. This study seeks to comprehensively assess how varying canopy conditions (leaf-on/leaf-off) affect ICESat-2 forest height retrieval and modelling. First, the accuracies of ICESat-2 terrain and canopy heights under leaf-on and leaf-off conditions were validated. Second, random forest algorithm was utilized to model forest height by integrating ICESat-2, Sentinel-2, and other ancillary datasets. Finally, we evaluated the influence of leaf-on and leaf-off conditions on forest height retrieval and modelling. Results reveal higher consistency between ICESat-2 and airborne LiDAR-derived terrain heights compared to the agreement between two canopy height datasets. Accuracies of ICESat-2 terrain and canopy heights are higher under leaf-off conditions in contrast to leaf-on conditions. Notably, the accuracies of ICESat-2 terrain and canopy heights under various conditions are closely linked to canopy cover. Furthermore, the accuracy of forest height modelling can be enhanced by combining ICESat-2 data collected during both leaf-on and leaf-off seasons with further eliminating low-quality samples.

The ICESat-2 (Ice, Cloud, and Land Elevation Satellite-2) can collect earth surface elevation data with high precision on a global scale. However, the collected photon data contains a large amount of background noise due to the influence of sunlight, cloud reflection, and other factors. For photon data of different scenes, how to effectively denoise and achieve accurate classification of photon point clouds is crucial for subsequent applications. This study proposes a random forest based method for denoising and classifying ICESat-2 photon data in urban areas by fusing spectral features from Sentinel-2 images and spatial distribution features from photon data. The experimental results show that the method can effectively identify various types of photons. Compared with the reference data, the overall accuracy of photon denoising and classification is 95.97% on average, and the average kappa coefficient is 94.18%. Further analysis demonstrates that the addition of sentinel-2 spectral information can effectively improve the classification accuracy of photon point clouds in urban areas, and the photon classification method of combining photon lidar data and optical images can be a promising solution to improve classification accuracy.

Spaceborne photon-counting LiDAR is significantly affected by noise, and existing denoising algorithms cannot be universally adapted to different surface types and topographies under all observation conditions. Accordingly, a new denoising method is presented to extract signal photons adaptively. The method includes two steps. First, the local neighborhood radius is calculated according to photons' density, then the first-step denoising process is completed via photons’ curvature feature based on KNN search and covariance matrix. Second, the local photon filtering direction and threshold are obtained based on the first-step denoising results by RANSAC and elevation frequency histogram, and the local dense noise photons that the first-step cannot be identified are further eliminated. The following results are drawn: (1) experimental results on MATLAS with different topographies indicate that the average accuracy of second-step denoising exceeds 0.94, and the accuracy is effectively improves with the number of denoising times; (2) experiments on ICESat-2 under different observation conditions demonstrate that the algorithm can accurately identify signal photons in different surface types and topographies. Overall, the proposed algorithm has good adaptability and robustness for adaptive denoising of large-scale photons, and the denoising results can provide more reasonable and reliable data for sustainable urban development.

This study was conducted to investigate the effect of Humulus scandens (HS) in diet on the production performance and intestinal barrier of rabbits. One hundred and sixty Laiwu black rabbits at 35 days of age with body weight of 692.5 ± 48.3 g were divided into four groups (five replicates per group and eight rabbits per replicate): fed on a basal diet free of HS (control), 4%, 8% or 12% HS powder supplement. The results showed that the dietary addition of HS decreased the ADFI, F/G, diarrhoea ratio and mortality ratio. Besides, the final body weight and ADG (P

AbstractSkin infection is a major health issue that usually is caused by the continuous proliferation of bacteria in wounds. With the abuse of antibiotics worldwide, the battle against skin infection is becoming more and more difficult. Therefore, the development of new ways with different antibacterial mechanisms to current antibiotics is urgently needed. Inspired by the powerful inhibition of ferroptosis used in cancer therapy, here in our study, ferric-loaded lipid nanoparticles (Fe-LNPs) with unform size (∼130 nm) and surface charge (∼12 mV) were constructed and found to effectively inhibit the growth of both Gram positive (Staphylococcus aureus, S. aureus) and negative (Escherichia coli, E. coli) strains, possibly due to induction of ferroptosis-like cell death mechanisms. Most importantly, Fe-LNPs can also effectively inhibit the proliferation of S. aureus in a skin infection model and promote the healing of wounds. The Fe-LNPs can be applied as a powerful antibacterial formulation for future application in clinic.

Abstract Pathogenic mutations in mitochondrial DNA cause severe and often lethal multi-system symptoms in primary mitochondrial defects. However, effective therapies for these defects are still lacking. Strategies such as employing mitochondrially targeted restriction enzymes or programmable nucleases to shift the ratio of heteroplasmic mutations and allotopic expression of mitochondrial protein-coding genes have limitations in treating mitochondrial homoplasmic mutations, especially in non-coding genes. Here, we conduct a proof of concept study applying a screened DdCBE pair to correct the homoplasmic m.A4300G mutation in induced pluripotent stem cells derived from a patient with hypertrophic cardiomyopathy. We achieve efficient G4300A correction with limited off-target editing, and successfully restore mitochondrial function in corrected induced pluripotent stem cell clones. Our study demonstrates the feasibility of using DdCBE to treat primary mitochondrial defects caused by homoplasmic pathogenic mitochondrial DNA mutations.

Abstract Background This study aimed to apply the backpropagation neural network (BPNN) to develop a model for predicting multidrug-resistant organism (MDRO) infection in critically ill patients. Methods This study collected patient information admitted to the intensive care unit (ICU) of the Affiliated Hospital of Qingdao University from August 2021 to January 2022. All patients enrolled were divided randomly into a training set (80%) and a test set (20%). The least absolute shrinkage and selection operator and stepwise regression analysis were used to determine the independent risk factors for MDRO infection. A BPNN model was constructed based on these factors. Then, we externally validated this model in patients from May 2022 to July 2022 over the same center. The model performance was evaluated by the calibration curve, the area under the curve (AUC), sensitivity, specificity, and accuracy. Results In the primary cohort, 688 patients were enrolled, including 109 (15.84%) MDRO infection patients. Risk factors for MDRO infection, as determined by the primary cohort, included length of hospitalization, length of ICU stay, long-term bed rest, antibiotics use before ICU, acute physiology and chronic health evaluation II, invasive operation before ICU, quantity of antibiotics, chronic lung disease, and hypoproteinemia. There were 238 patients in the validation set, including 31 (13.03%) MDRO infection patients. This BPNN model yielded good calibration. The AUC of the training set, the test set and the validation set were 0.889 (95% CI 0.852–0.925), 0.919 (95% CI 0.856–0.983), and 0.811 (95% CI 0.731–0.891), respectively. Conclusions This study confirmed nine independent risk factors for MDRO infection. The BPNN model performed well and was potentially used to predict MDRO infection in ICU patients.

Abstract Background and objective Consensus methods are crucial in developing clinical guidelines. Different methods, such as the Delphi and nominal group techniques, are commonly used, but there is a lack of detailed instructions on how to implement them effectively. The survey aims to explore the opinions and attitudes of the chair, panel and working group on the critical elements of the consensus methods during guideline development. Methods We used a cross-sectional design to conduct this study and sent a structured questionnaire to stakeholders, including the chair, panel members, and working group participants, through the popular mobile phone application WeChat.We selected participants using a combination of purposive and snowball sampling. The questionnaire gathered information on demographics, experiences, opinions, and concerns regarding consensus methods and guideline development. Results The sample comprised 290 participants representing 31 provinces or municipalities. Among them, the most significant number of respondents (n = 107, 36.9%) were from Beijing. Most participants, specifically 211 (72.76%), held senior professional titles, while 186 (64.14%) adhered to ongoing guidelines. The Delphi method was the most commonly used consensus method (n = 132, 42.31%), but the respondents had only a preliminary understanding of it (n = 147, 47.12%). The consensus process also revealed the insufficiency of involving pharmacoeconomists, patients, and nurses. Conclusions Consensus methods have to be standardised and used consistently in the guideline development process. The findings of this study offer insights into diverse roles and more effective ways to apply the consensus process during guideline development.

Hahnia, the most species-diversity genus of the comb-tailed spider family Hahniidae Bertkau, 1878, compromises 102 species distributed worldwide. To date, 24 species have been recorded from China.A new species of the genus Hahnia C. L. Koch, 1841 is described, based on both sexes from Shanyang Cave of Guizhou Province, China and is named H. jiangkou sp. nov. Diagnostic photos of habitus and copulatory organs, as well as a distributional map, are provided.

Objective: To investigate the diagnostic value of dual-source CT (DSCT) in evaluating adults with atrial septal defect (ASD) with pulmonary hypertension (PAH). Methods: Seventy-five adult patients with ASD in our hospital were retrospectively analyzed. The study sample was divided into 2 groups (PAH group (n=40) and non-PAH group (n=35 cases)) according to the mean pulmonary artery pressure (mPAP) obtained by right cardiac catheterization (RHC) (PAH: ≥ 25 mmHg). All patients were examined for congenital heart disease by DSCT one week before RHC. The ascending aorta diameter (AAD), main pulmonary artery diameter (MPAD), right pulmonary artery diameter (RPAD), left pulmonary artery diameter (LPAD), right lower pulmonary artery diameter (RLPAD), the maximum diameter of the short axis of both the ventricles (RVD, LVD), included the angle of the spinal ventricular septum and ASD diameter, were measured on the image. The MPAD to AAD ratio (rPA) and the RVD to LVD ratio (RVD/LVD) were calculated. Differences between the two groups in terms of clinical data, RHC indexes, and CT cardiovascular parameters were evaluated by a t-test. The ROC curve was used to determine the diagnostic efficacy of DSCT in adults with ASD and PAH. Pearson correlation coefficient was used to analyze the association between the CT parameters, mPAP, and PVR. Results: The statistically significant CT indexes between the two groups were MPAD, RPAD, LPAD, RLPAD, RVD including the angle of the spinal ventricular septum, rPA, RVD/LVD, and ASD diameter. Of these, the RPAD and LPAD including the angle of the spinal ventricular septum, rPA, RVD/LVD, and ASD diameter demonstrated moderate diagnostic efficacy for PAH (AUC>0.7). The MPAD, rPA, and ASD diameter with mPAP were moderately positively correlated. The MPAD, rPA, and RVD/LVD with PVR were also mildly positively correlated. Furthermore, the ASD diameter and PVR were highly positively correlated. Conclusion: DSCT is diagnostically valuable for the evaluation of adults with ASD complicated with PAH. In particular, DSCT may be used to provide a comprehensive evaluation before clinical treatment, as well as for long-term follow-up and management.

Abstract More than 80 million people worldwide permanently live at high altitudes, and living in such a hypoxic environment can impair cognitive functions. However, it is largely unknown how long-term exposure to high altitude affects neural oscillations underlying these cognitive functions. The present study employed a Go/NoGo task to investigate the effects of long-term exposure to high altitude on neural oscillations during cognitive control. We compared event-related spectral perturbations between the low-altitude and high-altitude groups, and the results revealed increased theta event-related synchronization (ERS) and decreased alpha and beta event-related desynchronizations (ERDs) during the NoGo condition compared to the Go condition. Importantly, the high-altitude group showed reduced alpha and beta ERDs compared to the low-altitude group, while the theta ERS was not affected by altitude. We suggest that long-term exposure to high altitude has an impact on top-down inhibitory control and movement preparation and execution in the Go/NoGo task.

Abstract RNA binding proteins (RBPs) are crucial for cell function, tissue growth, and disease development in disease or normal physiological processes. RNA binding motif protein 47 (RBM47) has been proven to have anti-tumor effects on many cancers, but its effect is not yet clear in renal cancer. Here, we demonstrated the expression and the prognostic role of RBM47 in public databases and clinical samples of clear cell renal carcinoma (ccRCC) with bioinformatics analysis. The possible mechanism of RBM47 in renal cancer was verified by gene function prediction and in vitro experiments. The results showed that RBM47 was downregulated in renal cancers when compared with control groups. Low RBM47 expression indicated poor prognosis in ccRCC. RBM47 expression in renal cancer cell lines was reduced significantly when compared to normal renal tubular epithelial cells. Epithelial-mesenchymal transition (EMT) and transforming growth factor-β signaling pathway was associated with RBM47 in ccRCC by Gene set enrichment analysis. RBM47 expression had a positive correlation with e-cadherin, but a negative correlation with snail and vimentin. RBM47 overexpression could repress the migration, invasion activity, and proliferation capacity of renal cancer cells, while RBM47 inhibition could promote the development of the malignant features through EMT signaling by RNA stability modification. Therefore, our results suggest that RBM47, as a new molecular biomarker, may play a key role in the cancer development of ccRCC.

Abstract To address the current objective of short‐term traffic flow prediction on roads, this paper aims to predict not only the future traffic flow on roads, but also the average speed of future roads. Specifically, the authors propose a short‐term traffic flow prediction method based on the Convolutional Neural Network—Gate Recurrent Unit—Multi Task Learning‐time‐separated attention mechanism (AST‐MTL‐CNN‐GRU). Firstly, the authors add a time‐separated attention mechanism that can effectively generate attention matrices independently for different locations and times of the day. Secondly, the three main parameters of traffic flow, average speed and occupancy are combined in pairs as input data while the multi‐task learning is applied to predict the future traffic flow and average speed on the road. Finally, the CNNs are used to extract the spatial features and the GRUs are used to extract temporal features. Compared with the baseline models (diffusion CNNs (DCRNN), 1D‐CNN‐long short‐term memory (1DCNN‐LSTM), convolutional LSTM (ConvLSTM), graph WaveNet and ST‐ResNet), the authors’ proposed model has high performance in terms of accuracy, stability and robustness. A large number of ablation experiments are conducted based on five‐fold cross validation using the Quanzhou city dataset and the California dataset. The experimental results show that the combination of average speed and occupancy for input has higher prediction accuracy. In addition, the authors’ proposed model can outperform the other models being compared in terms of accuracy, stability and robustness even with noise added.

Objectives The reconstruction of bone defects in tibial revision knee arthroplasty is challenging. In this study, we evaluated the primary stability of a novel three‐dimensional (3D)‐printed custom‐made metaphyseal cone for Anderson Orthopedic Research Institute (AORI) IIb or III bone defect reconstruction in tibial revision knee arthroplasty using the combination of finite‐element analysis and biomechanical experiments. Methods In the finite‐element analysis, AORI II b and III medial tibial bone defects were designed at varying depths. A novel 3D‐printed custom‐made metaphyseal cone was designed and used to reconstruct the bone defect with or without a stem in simulated revision total knee arthroplasty (RTKA). A no‐stem group and a stem group were established (based on whether a stem was used or not). Von Mises stress and micromotion were calculated with varying depths of bone defects, ranging from 5 mm to 35 mm, and then micromotions at the bone–implant interface were calculated and compared with the critical value of 150 μm. In the biomechanical experiment, the no‐stem group was used, and the same bone defects were made in four synthetic tibias using patient‐specific instruments. Micromotions at the bone–implant interface were investigated using a non‐contact optical digital image correlation system and compared with the critical value of 150 μm. Results When the bone defect was

In order to clarify the types and risk levels of residual pesticides in Xinjiang apricots, in this study, 77 samples from six major apricot producing areas of Xinjiang in 2021 and 2022 were selected as the research objects. The liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry were used to quantitatively analyze 99 kinds of pesticides in apricot, and acute and chronic dietary intake risks of pesticide residues in apricot were calculated and sorted. For the maximum residual limited pesticides detected in apricot, the recommended value of maximum residual limit was put forward. The results of the study showed that the detection rate of pesticide residues in Xinjiang apricot sample was 96.1%, and there were 23 pesticide residues in total, of which carbendazim, acetamiprid, and cyhalothrin had relatively high detection rates. The risk of acute and chronic dietary intake of residual pesticides was at acceptable levels. According to the order of pesticide risk assessment, four pesticides were identified as high risk pesticides, namely, carbofuran, phorate, emamectin benzoate, and triazophos, with risk scores of 25.3, 25.1, 20.2, and 20.1 respectively. There were no high risk samples in 77 samples, mainly low risk and very low risk samples. Of the pesticides detected, 10 had not yet been established maximum residue limits. Based on the comprehensive analysis, it iwas recommended to prioritize the maximum limit values of three residual pesticides, namely, tebufenozide, emamectin benzoate, and triazophos, and the recommended values were 6, 0.1, and 0.3 mg/kg, respectively. It can be seen that the quality and safety of Xinjiang apricot is generally good, and it is suggested to improve the maximum limit value of pesticides which is commonly used in apricot without pesticide residue.

A novel shear thickening gel with micro-scale hard/soft interface structure and low reaction temperature was proposed in this article. The gel was named TH and used as core material within Kevlar fabrics. Storage modulus of TH was proved to increase by around two orders with increasing of shear frequency, and dynamic properties indicated that TH could dissipate or store more energy. TH can adhere with Kevlar fabrics well and satisfactorily fulfill the gap between fabrics. As a result, shock wave peak pressure and positive impulse decreased markedly. Wavelet decomposition analysis show that high frequency energy was filtered by protection materials. Meanwhile, impact resistance test suggested the existence of TH changed the stress propagation routes and avoided pulling out for Kevlar fabrics. Samples filled with TH demonstrated a better shock wave mitigation ability and impact resistance. Energy dissipation structures with TH have a promising prospect in the application of defending area.

Featuring low density and high specific strength, magnesium (Mg) alloys have attracted wide interests in the fields of portable devices and automotive industry. However, the active chemical and electrochemical properties make them susceptible to corrosion in humid, seawater, soil, and chemical medium. Various strategies have revealed certain merits of protecting Mg alloys. Therein, engineering self-repairing coatings is considered as an effective strategy, because they can enable the timely repair for damaged areas, which brings about long-term protection for Mg alloys. In this review, self-repairing coatings on Mg alloys are summarized from two aspects, namely shape restoring coatings and function restoring coatings. Shape restoring coatings benefit for swelling, shrinking, or reassociating reversible chemical bonds to return to the original state and morphology when coatings broken; function self-repairing coatings depend on the release of inhibitors to generate new passive layers on the damaged areas. With the advancement of coating research and to fulfill the demanding requirements of applications, it is an inevitable trend to develop coatings that can integrate multiple functions (such as stimulus response, self-repairing, corrosion warning, and so on). As a novel carrier and barrier, porous solids, especially covalent organic frameworks (COFs), have been respected as the future development of self-repairing coatings on Mg alloys, due to their unique, diverse structures and adjustable functions.

Abstract Background Online communication platforms have the potential to facilitate commercial sex among female sex workers (FSW), increasing the risk of contracting sexually transmitted diseases (STD). This study aimed to describe the patterns of online commercial sex-seeking and examine the associated factors among FSW in China. Methods A venue-based cross-sectional study was conducted in five cities in Guangdong Province, China, between April and October 2020. Data on socio-demographic characteristics, sexual behaviors, and online commercial sex-seeking patterns were collected through face-to-face interviews. Venous blood and urine samples were collected for STD testing. Univariate and multivariable logistic regressions were used to explore the factors associated with online commercial sex-seeking. Results A total of 1155 FSW were recruited in physical venues for this study. Among them, 33.42% reported ever using online applications to seek commercial sex. The prevalence of HIV, syphilis, gonorrhea, chlamydia, and STD was 0.26%, 1.30%, 4.40%, 15.54%, and 18.39%, respectively, among FSW who had ever used both physical and online venues to seek commercial sex, which was higher than among FSW who had never sought commercial sex online. Multivariable logistic regression indicated that FSW who used online platforms to seek commercial sex were more likely to have STD (adjusted odds ratio (aOR) = 1.48, 95%CI: 1.05–2.09), experience unintended pregnancies due to commercial sex (aOR = 1.78, 95%CI: 1.21–2.62), be diagnosed as infertile (aOR = 3.20, 95%CI: 1.42–7.21), and undergo abortions (aOR = 1.69, 95%CI: 1.29–2.20). Conclusion A significant proportion of FSW who practiced in physical venues in China engaged in seeking commercial sex online, and this behavior is positively correlated with both STD and reproductive health outcomes. Given the high prevalence of online sex-seeking, it is crucial to provide a wide range of internet-based healthcare interventions and reproductive health services to Chinese FSW.

Abstract Background and aims The recurrence and metastasis of hepatocellular carcinoma (HCC) are mainly caused by microvascular invasion (MVI). Our study aimed to uncover the cellular atlas of MVI+ HCC and investigate the underlying immune infiltration patterns with radiomics features. Methods Three MVI positive HCC and three MVI negative HCC samples were collected for single-cell RNA-seq analysis. 26 MVI positive HCC and 30 MVI negative HCC tissues were underwent bulk RNA-seq analysis. For radiomics analysis, radiomics features score (Radscore) were built using preoperative contrast MRI for MVI prediction and overall survival prediction. We deciphered the metabolism profiles of MVI+ HCC using scMetabolism and scFEA. The correlation of Radscore with the level of APOE+ macrophages and iCAFs was identified. Whole Exome Sequencing (WES) was applied to distinguish intrahepatic metastasis (IM) and multicentric occurrence (MO). Transcriptome profiles were compared between IM and MO. Results Elevated levels of APOE+ macrophages and iCAFs were detected in MVI+ HCC. There was a strong correlation between the infiltration of APOE+ macrophages and iCAFs, as confirmed by immunofluorescent staining. MVI positive tumors exhibited increased lipid metabolism, which was attributed to the increased presence of APOE+ macrophages. APOE+ macrophages and iCAFs were also found in high levels in IM, as opposed to MO. The difference of infiltration level and Radscore between two nodules in IM was relatively small. Furthermore, we developed Radscore for predicting MVI and HCC prognostication that were also able to predict the level of infiltration of APOE+ macrophages and iCAFs. Conclusion This study demonstrated the interactions of cell subpopulations and distinct metabolism profiles in MVI+ HCC. Besides, MVI prediction Radscore and MVI prognostic Radscore were highly correlated with the infiltration of APOE+ macrophages and iCAFs, which helped to understand the biological significance of radiomics and optimize treatment strategy for MVI+ HCC.

Abstract The immunonutritional status has important effects on outcomes for cancer patients. Albumin-to-globulin ratio (AGR) and the prognostic nutrition index (PNI) are often used to assess the immunonutritional status of cancer patients. However, the clinical significance of these factors in colorectal cancer (CRC) remains unclear. We aimed to evaluate the clinical significance of the AGR and PNI in CRC. We reviewed the clinical data of 511 patients with CRC in two hospitals. Data from one institution was used as the training cohort. The optimal cutoff values for AGR and PNI in the training cohort were 1.4 and 48.65, respectively. Patients in both the low AGR and low PNI groups had poor overall survival (OS) and progression-free survival (PFS), while those in the low AGR-low PNI group had the lowest OS and PFS. Multivariate analysis revealed that preoperative AGR, preoperative PNI, gross type, and TNM stage were independent prognostic factors influencing OS in patients with CRC. Preoperative AGR, preoperative PNI, and TNM stage were independently associated with PFS in patients with CRC. According to the results of multivariate analysis in the training cohort, we developed the nomograms for OS and PFS and performed internal and external validation, which showed good prediction ability of the nomograms. In conclusion, preoperative AGR and PNI can be used as effective indicators to predict survival for patients with CRC. AGR and PNI may help develop effective adjuvant-therapy schedules.

Abstract Urban commercial centres are the most concentrated areas of economic activity. Understanding the spatial distribution pattern and comprehensive strength of urban commercial centres is important to guide the reasonable graded allocation of urban commercial space, spatial structure optimization and sustainable development of the commercial economy. Herein, mobile phone signalling data are used to identify the functional connection between recreational and residential places and local spatial autocorrelation analysis is used to identify the 24 commercial centres in the central city of Hefei. The comprehensive strength evaluation system of commercial centres is constructed from their basic conditions and customer consumption behaviours, and their comprehensive strength indices are accordingly measured and graded. The spatial distribution characteristics of commercial centres at all levels are analysed, and optimisation suggestions are made for the whole area and region. The following conclusions are drawn from the results of this study. (1) Compared to traditional single-perspective evaluations, the developed comprehensive strength evaluation system considers supply and demand perspectives for commercial centres, providing a more holistic and accurate portrayal of the strengths of various centres within a region. (2) The current commercial centres are characterised by ‘large dispersion and small concentration’ in spatial and hierarchical distribution. (3) The commercial centres in Hefei have formed a relatively complete ‘first, second, and third level’ commercial centre system, with the first level as the core and relying on the urban road system to form a network spatial connection. (4) Most of the commercial centres are concentrated in the First Ring Road, Swan Lake in the Government Affairs District and Binhu Century Town Estate, while most areas north of the Second Ring Road and Binhu New District still lack large-scale commercial centres. This study provides a technical reference for analysing urban commercial spatial structure patterns and provides decision support for optimising the spatial layout of urban commercial service functions.

Cutaneous squamous cell carcinoma (cSCC) is the second most common malignant skin tumor. Early and precise diagnosis of tumor staging is crucial for long-term outcomes. While pathological diagnosis has traditionally served as the gold standard, the assessment of differentiation levels heavily depends on subjective judgments. Therefore, how to improve the diagnosis accuracy and objectivity of pathologists has become an urgent problem to be solved. We used multispectral imaging (MSI) to enhance tumor classification. The hematoxylin and eosin (H&E) stained cSCC slides were from Shanghai Ruijin Hospital. Scale-invariant feature transform was applied to multispectral images for image stitching, while the adaptive threshold segmentation method and random forest segmentation method were used for image segmentation, respectively. Synthetic pseudo-color images effectively highlight tissue differences. Quantitative analysis confirms significant variation in the nuclear area between normal and cSCC tissues (p < 0.001), supported by an AUC of 1 in ROC analysis. The AUC within cSCC tissues is 0.57. Further study shows higher nuclear atypia in poorly differentiated cSCC tissues compared to well-differentiated cSCC (p < 0.001), also with an AUC of 1. Lastly, well differentiated cSCC tissues show more and larger keratin pearls. These results have shown that combined MSI with imaging processing techniques will improve H&E stained human cSCC diagnosis accuracy, and it will be well utilized to distinguish histopathological staging features.

This paper explores the use of few-shot learning in Wi-Fi-based indoor positioning, utilizing convolutional neural networks (CNNs) combined with meta-learning techniques to enhance the accuracy and efficiency of positioning systems. The focus is on addressing the challenge of limited labeled data, a prevalent issue in extensive indoor environments. The study explores various scenarios, comparing the performance of the base CNN and meta-learning models. The meta-learning approach involves few-shot learning tasks, such as three-way N-shot, five-way N-shot, etc., to enhance the model’s ability to generalize from limited data. The experiments were conducted across various scenarios, evaluating the performance of the models with different numbers of samples per class (K) after filtering by cosine similarity (FCS) during both the stages of data preprocessing and meta-learning. The scenarios included both base classes and novel classes, with and without meta-learning. The results indicated that the base CNN model achieved varying accuracy levels depending on the scenario and the number of samples per class retained after FCS. Meta-learning performed acceptably in scenarios with fewer samples, which are the distinct datasets pertaining to novel classes. With 20 samples per class, the base CNN achieved an accuracy of 0.80 during the pre-training stage, while meta-learning (three-way one-shot) achieved an accuracy of 0.78 on a new small dataset with novel classes.

The integration of multi-source remote sensing data, bolstered by advancements in deep learning, has emerged as a pivotal strategy for enhancing land use and land cover (LULC) classification accuracy. However, current methods often fail to consider the numerous prior knowledge of remote sensing images and the characteristics of heterogeneous remote sensing data, resulting in data loss between different modalities and the loss of a significant amount of useful information, thus affecting classification accuracy. To tackle these challenges, this paper proposes a LULC classification method based on remote sensing data that combines a Transformer and cross-pseudo-siamese learning deep neural network (TCPSNet). It first conducts shallow feature extraction in a dynamic multi-scale manner, fully leveraging the prior information of remote sensing data. Then, it further models deep features through the multimodal cross-attention module (MCAM) and cross-pseudo-siamese learning module (CPSLM). Finally, it achieves comprehensive fusion of local and global features through feature-level fusion and decision-level fusion combinations. Extensive experiments on datasets such as Trento, Houston 2013, Augsburg, MUUFL and Berlin demonstrate the superior performance of the proposed TCPSNet. The overall accuracy (OA) of the network on the Trento, Houston 2013 and Augsburg datasets is of 99.76%, 99.92%, 97.41%, 87.97% and 97.96%, respectively.

With the rising popularity of pet cats as companion animals, the survival of newborn kittens is often threatened by factors such as inadequate nursing, maternal behavior and blood incompatibility. These challenges require the use of milk replacers for nurturing. To investigate the effects that feeding kittens with an experimental milk replacer (EMR) have on growth and development, intestinal microbiota, immune response and nutrient metabolism, 12 British shorthair kittens were randomly divided into two groups after nursing for the first week of life. Kittens were fed queen’s milk or EMR, whereby kittens fed queen’s milk served as the control (CON) group. The findings revealed that the CON group exhibited superoxide dismutase (SOD) activity and total antioxidant capacity (T-AOC) (p < 0.01) on day 7. However, the EMR group had better growth performance during the later stage of the experiment (p < 0.05); the immunocompetence and antioxidant capacity of the EMR group were not significantly different from those of the CON group in the middle and late stages of the experiment, and the mean values of all the indexes were slightly better than those of the control group. Sequencing of the 16S rRNA gene in microbiota demonstrated that EMR increased the colonization of bacterial genera, including Lachnospiraceae, Enterococcus, Rothia and Ligilactobacillus. Compared to the CON group, acetate acid (p < 0.05), propionate acid (p < 0.01) and total SCFAs (p < 0.01) in the EMR group were significantly increased. Moreover, the intake of the EMR resulted in the production of distinct metabolites implicated in the metabolism of lipids and amino acids, among other nutrients, thus invigorating the associated metabolic pathways. These results elucidate the impact of administering a milk replacer on gastrointestinal health and nutrient assimilation in kittens. The study provides insights into the use of milk powder alternatives and sets the stage for future research on the formulation and effectiveness of kitten milk replacers.

Selenium (Se) is an essential trace element known for its significant role in maintaining human health and mitigating disease progression. Selenium and its compounds exhibit high selective cytotoxicity against tumor cells. However, their anti-cervical cancer (CC) effects and underlying mechanisms have not been fully explored. This study found that sodium selenite (SS) inhibits the viability of HeLa and SiHa cells in a dose- and time-dependent manner. Intraperitoneal injection of 3 and 6 mg/kg SS for 14 days in female nude mice significantly inhibited the growth of HeLa cell xenografts without evident hepatotoxicity or nephrotoxicity. RNA sequencing results indicated that the AMP-activated protein kinase (AMPK), Forkhead box protein O (FOXO), and apoptosis signaling pathways are key regulatory pathways in SS’s anti-CC effects, and SS’s inhibition of HeLa cell proliferation may be related to autophagy and ROS-induced apoptosis. Further research has revealed that SS induces cell autophagy and apoptosis through the AMPK/mTOR/FOXO3a pathway, characterized by the upregulation of p-AMPK/AMPK, FOXO3a, LC3-II, cleaved-caspase3, and cleaved-PARP and the downregulation of p-mTOR/mTOR and p62. Additionally, SS impaired mitochondrial function, including decreased mitochondrial membrane potential, mitochondrial Ca2+ overload, and accumulation of mitochondrial reactive oxygen species (mtROS). Pretreatment with Mitoquinone mesylate (Mito Q) and compound C partially reversed SS-induced apoptosis, autophagy, and proliferation inhibition. Pretreatment with 3-methyladenine (3-MA) enhances SS-induced apoptosis and proliferation inhibition in HeLa cells but reverses these effects in SiHa cells. In summary, SS induces apoptosis, autophagy, and proliferation inhibition in HeLa and SiHa cells through the activation of the AMPK/mTOR/FOXO3a signaling pathway via mtROS. Autophagy activation may be a major risk factor for SS-induced apoptosis in SiHa cells but can protect HeLa cells from SS-induced apoptosis. These findings provide new evidence for understanding the molecular mechanisms underlying SS in potential new drug development for CC.

Mapping wall-to-wall forest aboveground biomass (AGB) at large scales is critical for understanding global climate change and the carbon cycle. In previous studies, a regression-based method was commonly used to map the spatially continuous distribution of forest AGB with the aid of optical images, which may suffer from the saturation effect. The Global Ecosystem Dynamics Investigation (GEDI) can collect forest vertical structure information with high precision on a global scale. In this study, we proposed a collaborative kriging (co-kriging) interpolation-based method for mapping spatially continuous forest AGB by integrating GEDI and Sentinel-2 data. First, by fusing spectral features from Sentinel-2 images with vertical structure features from GEDI, the optimal estimation model for footprint-level AGB was determined by comparing different machine-learning algorithms. Second, footprint-level predicted AGB was used as the main variable, with rh95 and B12 as covariates, to build a co-kriging guided interpolation model. Finally, the interpolation model was employed to map wall-to-wall forest AGB. The results showed the following: (1) For footprint-level AGB, CatBoost achieved the highest accuracy by fusing features from GEDI and Sentinel-2 data (R2 = 0.87, RMSE = 49.56 Mg/ha, rRMSE = 27.06%). (2) The mapping results based on the interpolation method exhibited relatively high accuracy and mitigated the saturation effect in areas with higher forest AGB (R2 = 0.69, RMSE = 81.56 Mg/ha, rRMSE = 40.98%, bias = −3.236 Mg/ha). The mapping result demonstrates that the proposed method based on interpolation combined with multi-source data can be a promising solution for monitoring spatially continuous forest AGB.

Since their invention by Akachi in 1990s, pulsating heat pipes (PHPs) have attracted widespread interest and application in practice, e.g., grinding, chip cooling, the thermal management of batteries, etc., owing to their notable efficiency in heat transfer and their simplicity and flexibility in structure. Key factors influencing the heat transfer efficacy of pulsating heat pipes are mainly attributed to the thermophysical properties of the working fluid, the structural parameters, and the operating conditions. Research on pulsating heat pipes is conducted through theoretical investigations, numerical simulations, and visual experiments. In this paper, the research on PHPs in recent decades is reviewed with the consideration of the heat transfer performance mechanism and application of pulsating heat pipes, especially research under operation conditions such as with “status with motion” and with “inconsistent heat flux”.

Vegetation plays a crucial role in terrestrial ecosystems, and the FVC (Fractional Vegetation Coverage) is a key indicator reflecting the growth status of vegetation. The accurate quantification of FVC dynamics and underlying driving factors has become a hot topic. However, the scale effect on FVC changes and driving factors has received less attention in previous studies. In this study, the changes and driving factors of FVC at multiple scales were analyzed to reveal the spatial and temporal change in vegetation in the Henan section of the Yellow River basin. Firstly, based on the pixel dichotomy model, the FVC at different times and spatial scales was calculated using Landsat-8 data. Then, the characteristics of spatial and temporal FVC changes were analyzed using simple linear regression and CV (Coefficient of Variation). Finally, a GD (Geographic Detector) was used to quantitatively analyze the driving factors of FVC at different scales. The results of this study revealed that (1) FVC showed an upward trend at all spatial scales, increasing by an average of 0.55% yr−1 from 2014 to 2022. The areas with an increasing trend in FVC were 10.83% more than those with a decreasing trend. (2) As the spatial scale decreased, the explanatory power of the topography factors (aspect, elevation, and slope) for changes in FVC was gradually strengthened, while the explanatory power of climate factors (evapotranspiration, temperature, and rainfall) and anthropogenic activities (night light) for changes in FVC decreased. (3) The q value of evapotranspiration was always the highest across different scales, peaking notably at a spatial scale of 1000 m (q = 0.48).

The frequency support capacity of power loads is essential for maintaining active power symmetry and balance between the generation and demand sides of power systems. As the proportion of renewable energy sources and power electronic equipment increases, the inertia on the power generation side decreases, highlighting the growing importance of frequency support on the load side. As it is generally believed that the active power balance of power systems determines the frequency stability, few studies have considered the effect of voltage variation on the frequency response dynamics. It is important to note that the node voltage keeps fluctuating throughout the frequency dynamic process, which affects the active power of loads and should not be neglected. Based on the aforementioned rationales, this paper endeavors to investigate the modeling of power load frequency response and analyze its support capability considering the voltage variation effect. This paper initially establishes the small-signal model of dynamic load under frequency dynamics, derives the transfer function relating active power to system frequency deviation, and subsequently develops its frequency response model. Subsequently, commencing with the ZIP model of static load, the power fluctuation of load nodes is derived from the influence of preceding nodes, and the frequency response model of the static load is formulated and its frequency support capacity is scrutinized. Based on this foundation, a comprehensive aggregation model of the complex load is constructed, and its frequency support capability is assessed using actual data. Finally, the proposed model and analysis results are validated through simulation, confirming their correctness and effectiveness.

Aiming at the current power control problems of grid-side electrochemical energy storage power station in multiple scenarios, this paper proposes an optimal power model prediction control (MPC) strategy for electrochemical energy storage power station. This method is based on the power conversion system (PCS) grid-connected voltage and current to establish a power prediction model for energy storage power stations, achieving a one-step prediction of the power of the power station. The power prediction error is used as a power regulation feedback quantity to correct the reference power input. Considering the state of charge (SOC) constraint of the battery, partition the SOC into different states. Using SOC as the power regulation feedback, the power of the battery compartment can be adjusted according to the range of the battery SOC to prevent SOC from exceeding the limit value, simultaneously calculating the power loss of the energy storage power station to improve the energy efficiency. The objective function is to minimize the power deviation and power loss of the power station. By solving the objective function, the optimal switching voltage vector of the converter output is achieved to achieve optimal power control of the energy storage power station. The simulation results in various application scenarios of the energy storage power station show that the proposed control strategy enables the power of the storage station to quickly and accurately track the demand of grid scheduling, achieving the optimal power control of the electrochemical energy storage power station.

Heat shock proteins (HSPs) are molecular chaperones that play essential roles in plant development and in response to various environmental stresses. Understanding R. delavayi HSP genes is of great importance since R. delavayi is severely affected by heat stress. In the present study, a total of 76 RdHSP genes were identified in the R. delavayi genome, which were divided into five subfamilies based on molecular weight and domain composition. Analyses of the chromosome distribution, gene structure, and conserved motif of the RdHSP family genes were conducted using bioinformatics analysis methods. Gene duplication analysis showed that 15 and 8 RdHSP genes were obtained and retained from the WGD/segmental duplication and tandem duplication, respectively. Cis-element analysis revealed the importance of RdHSP genes in plant adaptations to the environment. Moreover, the expression patterns of RdHSP family genes were investigated in R. delavayi treated with high temperature based on our RNA-seq data, which were further verified by qRT-PCR. Further analysis revealed that nine candidate genes, including six RdHSP20 subfamily genes (RdHSP20.4, RdHSP20.8, RdHSP20.6, RdHSP20.3, RdHSP20.10, and RdHSP20.15) and three RdHSP70 subfamily genes (RdHSP70.15, RdHSP70.21, and RdHSP70.16), might be involved in enhancing the heat stress tolerance. The subcellular localization of two candidate RdHSP genes (RdHSP20.8 and RdHSP20.6) showed that two candidate RdHSPs were expressed and function in the chloroplast and nucleus, respectively. These results provide a basis for the functional characterization of HSP genes and investigations on the molecular mechanisms of heat stress response in R. delavayi.

Abstract In lead halide perovskites, organic A-site cations are generally introduced to fine-tune the properties. One of the questions under debate is whether organic A-site cations are essential for high-performance solar cells. In this study, we compare the band edge carrier dynamics and diffusion process in MAPbBr3 and CsPbBr3 single-crystal microplates. By transient absorption microscopy, the band-edge carrier diffusion constants are unraveled. With the replacement of inorganic A-site cations, the diffusion constant in CsPbBr3 increases almost 8 times compared to that in MAPbBr3. This work reveals that introducing inorganic A-site cations can lead to a much larger diffusion length and improve the performance of band-edge carriers. Graphical Abstract

Abstract Background Chlamydia Trachomatis (CT) is among the most prevalent sexually transmitted diseases (STDs) globally. According to the World Health Organization, more than 131 million people get infected with CT annually. CT is usually transmitted via sexual contact or perinatal exposure and can result in severe long-term complications. In developing nations, particularly, the prevention and control of CT is challenging. Hence, this study will explore the feedback mechanisms of chlamydia prevention and control, as well as identify the essential factors affecting the control and prevention of this infection in China. Methods Our study will employ a mixed-methods research design that encompasses both qualitative and quantitative methods. Firstly, we will develop a causal loop diagram (CLD) based on the literature review and optimize it via in-depth interviews with stakeholders. Additionally, we will utilize a quantitative method called MICMAC(Impact Matrix Cross-Reference Multiplication Applied to a Classification tool) to obtain consensus among different stakeholders and pinpoint the key information. Next, the CLD will be transformed into a system dynamics model (SDM) to evaluate the feedback mechanisms within the CLD. The causality in the CLD will be modeled using mathematical equations, which facilitate the transformation into an SDM. As such, we will be able to analyze the dynamic behavior of the system and its response to different decisions. Discussion Our study offers a systematic perspective on the control and prevention of chlamydia infection through system dynamics modeling, examining the dynamic properties and background factors of the system. The creation of the CLD affords stakeholders the chance to comprehend the functionality of their relationships and improve cooperation. Consequently, by evaluating the outcomes of these simulations, it will be possible to analyze and determine potential interventions and their effects on chlamydia infections. This modeling approach can help us gain insight into the dynamic characteristics of the system, evaluate the potential outcomes of different decisions, and design control strategies to either stabilize the system or adjust its behavior.

Abstract Mangrove reforestation with introduced species has been an important strategy to restore mangrove ecosystem functioning. However, how such activities affect microbially driven methane (CH4), nitrogen (N), and sulfur (S) cycling of rhizosphere microbiomes remains unclear. To understand the effect of environmental selection and the evolutionary process on microbially driven biogeochemical cycles in native and introduced mangrove rhizospheres, we analyzed key genomic and functional profiles of rhizosphere microbiomes from native and introduced mangrove species by metagenome sequencing technologies. Compared with the native mangrove (Kandelia obovata, KO), the introduced mangrove (Sonneratia apetala, SA) rhizosphere microbiome had significantly (p

Precise Point Positioning (PPP) technology has developed into a potent instrument for geodetic positioning, ionospheric modeling, tropospheric atmospheric parameter detection, and seismic monitoring. As atmospheric reanalysis data products' accuracy and spatiotemporal resolution have improved recently, it has become important to apply these products to obtain high-accuracy tropospheric delay parameters, like zenith tropospheric delay (ZTD) and tropospheric horizontal gradient. These tropospheric delay parameters can be applied to PPP to reduce the convergence time and to increase the accuracy in the vertical direction of the position. The European Centre for Medium-Range Weather Forecasts Reanalysis 5 (ERA5) atmospheric reanalysis data is the latest product with a high spatiotemporal resolution released by the European Center for Medium-Range Weather Forecasts (ECMWF). Only a few researches have evaluated the application of ERA5 data to Global Navigation Satellite System (GNSS) PPP. Therefore, this study compared and validated the ZTD products derived from ERA5 data using ZTD values provided by 290 global International GNSS Service (IGS) stations for 2016–2017. The results indicated a stable performance for ZTD, with annual average bias and RMS values of 0.23 cm and 1.09 cm, respectively. Further, GNSS observations for one week in each of the four seasons (spring: DOY 92–98; summer: DOY 199–205; autumn: DOY 275–281; and winter: DOY 22–28) from 34 multi-GNSS experiments (MGEX) stations distributed globally in 2016 were considered to evaluate the performance of ERA5-derived tropospheric delay products in GNSS PPP. The performance of ERA5-enhanced PPP was compared with that of the two standard GNSS PPP schemes (without estimated tropospheric horizontal gradient and with estimated tropospheric horizontal gradient). The results demonstrated that ERA5-enhanced GNSS PPP showed no significant improvement in the convergence times in both the Eastern (E) and Northern (N) directions, while the average convergence time over four weeks in the vertical (U) direction improved by 53.3% and 52.7%, respectively (in the case of pngm station). The average convergence times for each week in the U direction of the northern and southern hemisphere stations indicated a decrease of 16.3%, 12.6%, 9.6%, and 9.1%, and 16.9%, 9.6%, 8.9%, and 14.5%, respectively. Regarding positioning accuracy, ERA5-enhanced PPP showed an improvement of 13.3% and 16.2% over the two standard PPP schemes in the U direction, respectively. No significant improvement in the positioning performance was observed in both the E and N directions. Thus, this study demonstrated the potential application of the ERA5 tropospheric parameters-augmented approach to Beidou navigation and positioning.

Abstract In this paper, a method combining random demodulator (RD) and discrete fractional Fourier transform (DFRFT) dictionary is suggested to directly estimate the parameters of linear frequency modulation (LFM) signals from compressed sampling data. First, the RD system parameters are modified in accordance with the characteristics of the LFM signal to produce effective compressed sampling data. Next, a DFRFT dictionary is built using the fractional Fourier transform theory, and sparse representation coefficients are obtained by reconstructing the compressed sampling data using the recovery algorithm and DFRFT dictionary. The signal exhibits characteristics that make it pulse under the best fractional transform order, so the problem of signal parameter estimation can be reduced to searching for the location of the maximum value of sparse representation coefficients. The location is determined by a parameter optimization algorithm, and from there, the initial frequency and Chirp rate of the LFM signal can be estimated. Lastly, simulation and real data tests are performed to confirm that the suggested method can directly be utilized to estimate the parameter of LFM signals using compressed sampling data in addition to having high sparse representation ability for LFM signals.

Abstract Background Men who have sex with men (MSM) are at high risk of hepatitis C virus (HCV) infection, especially for those living with human immunodeficiency virus (HIV). Learning about knowledge of and attitudes towards HCV is essential to inform health promotion interventions development. This is one of very limited studies to examine the level of knowledge and attitudes towards HCV and their determinants among HIV-negative MSM and MSM living with HIV in China. Methods A cross-sectional survey was conducted across seven provinces in China from December 2021 to January 2022. All the MSM living with HIV were recruited offline, whereas the recruitment ratio for HIV-negative MSM was half online and half offline. Data on socio-demographic characteristics, sexual behaviors, knowledge about HCV, and attitude towards HCV from participants were collected through the online survey. Univariate and multivariable logistic regressions were used to determine the associated factors. Results Only 39.3% (33/84) of HIV-negative men and 44.0% (37/84) of men living with HIV had a good level knowledge about HCV. Nearly one-third (32.1%, 27/84) of HIV-negative men and 41.7% (35/84) of men living with HIV reported a positive attitude towards HCV. For HIV-negative men, positive attitude towards HCV was associated with the multiple sexual partners (aOR: 5.8, 95%CI:1.9–18.1) and the use of recreational substances (aOR: 3.1, 95%CI: 1.0-9.4). For men living with HIV, knowledge about HCV was associated with disclosing sexual orientation to healthcare providers, family or friends (aOR: 7.0, 1.9–26.0), the multiple sexual partners (aOR: 0.2, 0.1-1.0), the use of recreational substances (aOR: 3.7, 95%CI: 1.1–13.1) and the HBV testing history (aOR: 7.3, 95%CI: 1.6–32.7); positive attitude towards HCV was associated with the use of recreational substances (aOR: 3.1, 95%CI: 1.1-9.0). Conclusions The majority of Chinese MSM showed an inadequate knowledge of and negative attitude towards HCV irrespective of HIV infection status. More tailored education campaigns and multicomponent interventions are required to be targeted on MSM, and more researches are also needed to inform how best to address the negative attitudes of this population towards HCV.

Abstract Human immunodeficiency virus (HIV) and sexually transmitted diseases (STDs) cause substantial morbidity and mortality both in African and China. However, there is limited data available on the prevalence of HIV/STDs and the uptake of testing experience ever during in China among African migrants. A venue-based survey was conducted at a tertiary hospital in Guangzhou to investigate the prevalence of HIV/STDs through laboratory testing and identify the associated factors. A total of 200 eligible participants completed the survey and bring into the analysis from April to October 2019, and the temporary visitors were excluded. The prevalence rates of HIV, syphilis, NG, CT, and HBsAg among the participants were 1.0%, 2.5%, 1.0%, 1.5%, and 5.5%, respectively. The overall reported rate of HIV/STD testing was 37.0%, with rates of 23.0% for HIV, 16.5% for syphilis, 12.5% for NG, 6.5% for genital herpes, 5.0% for condyloma acuminata, and 2.5% for CT. HIV/STD testing was associated with living environment in Guangzhou, having medical insurance in China, and utilizing health services in China in the past year. HIV/STDs are prevalent among Africans in Guangzhou, and the epidemic is likely to spread due to a significant proportion of unprotected sexual behaviors and low rates of HIV/STD testing. Urgent interventions, including targeted health education, promotion of health service utilization, and active surveillance of HIV/STDs, are needed to reduce the risk of HIV/STD transmission.

Abstract Background Cardiovascular complications significantly augment the overall COVID-19 mortality, largely due to the susceptibility of human cardiomyocytes (CMs) to SARS-CoV-2 virus. SARS-CoV-2 virus encodes 27 genes, whose specific impacts on CM health are not fully understood. This study elucidates the deleterious effects of SARS-CoV-2 genes Nsp6, M, and Nsp8 on human CMs. Methods CMs were derived from human pluripotent stem cells (hPSCs), including human embryonic stem cells and induced pluripotent stem cells, using 2D and 3D differentiation methods. We overexpressed Nsp6, M, or Nsp8 in hPSCs and then applied whole mRNA-seq and mass spectrometry for multi-omics analysis. Co-immunoprecipitation mass spectrometry was utilized to map the protein interaction networks of Nsp6, M, and Nsp8 within host hiPSC-CMs. Results Nsp6, Nsp8, and M globally perturb the transcriptome and proteome of hPSC-CMs. SARS-CoV-2 infection and the overexpression of Nsp6, Nsp8, or M coherently upregulated genes associated with apoptosis and immune/inflammation pathways, whereas downregulated genes linked to heart contraction and functions. Global interactome analysis revealed interactions between Nsp6, Nsp8, and M with ATPase subunits. Overexpression of Nsp6, Nsp8, or M significantly reduced cellular ATP levels, markedly increased apoptosis, and compromised Ca2+ handling in hPSC-CMs. Importantly, administration of FDA-approved drugs, ivermectin and meclizine, could restore ATP levels, thereby mitigating apoptosis and dysfunction in hPSC-CMs overexpressing Nsp6, Nsp8, or M. Conclusion Overall, our findings uncover the extensive damaging effects of Nsp6, Nsp8, and M on hPSC-CMs, underlining the crucial role of ATP homeostasis in CM death and functional abnormalities induced by these SARS-CoV-2 genes, and reveal the potential therapeutic strategies to alleviate these detrimental effects with FDA-approved drugs.

Abstract The poor efficacy of chimeric antigen receptor T-cell therapy (CAR T) for solid tumors is due to insufficient CAR T cell tumor infiltration, in vivo expansion, persistence, and effector function, as well as exhaustion, intrinsic target antigen heterogeneity or antigen loss of target cancer cells, and immunosuppressive tumor microenvironment (TME). Here we describe a broadly applicable nongenetic approach that simultaneously addresses the multiple challenges of CAR T as a therapy for solid tumors. The approach reprograms CAR T cells by exposing them to stressed target cancer cells which have been exposed to the cell stress inducer disulfiram (DSF) and copper (Cu)(DSF/Cu) plus ionizing irradiation (IR). The reprogrammed CAR T cells acquire early memory-like characteristics, potent cytotoxicity, enhanced in vivo expansion, persistence, and decreased exhaustion. Tumors stressed by DSF/Cu and IR also reprogram and reverse the immunosuppressive TME in humanized mice. The reprogrammed CAR T cells, derived from peripheral blood mononuclear cells of healthy donors or metastatic female breast cancer patients, induce robust, sustained memory and curative anti-solid tumor responses in multiple xenograft mouse models, establishing proof of concept for empowering CAR T by stressing tumor as a promising therapy for solid tumors.

Abstract Pleomorphic adenoma (PA) is the most common benign tumour in the salivary gland and has high morphological complexity. However, the origin and intratumoral heterogeneity of PA are largely unknown. Here, we constructed a comprehensive atlas of PA at single-cell resolution and showed that PA exhibited five tumour subpopulations, three recapitulating the epithelial states of the normal parotid gland, and two PA-specific epithelial cell (PASE) populations unique to tumours. Then, six subgroups of PASE cells were identified, which varied in epithelium, bone, immune, metabolism, stemness and cell cycle signatures. Moreover, we revealed that CD36+ myoepithelial cells were the tumour-initiating cells (TICs) in PA, and were dominated by the PI3K-AKT pathway. Targeting the PI3K-AKT pathway significantly inhibited CD36+ myoepithelial cell-derived tumour spheres and the growth of PA organoids. Our results provide new insights into the diversity and origin of PA, offering an important clinical implication for targeting the PI3K-AKT signalling pathway in PA treatment.

Background: Chronic ankle instability (CAI) is a common sequela following an acute lateral ankle sprain (LAS). To treat an acute LAS more effectively and efficiently, it is important to identify patients at substantial risk for developing CAI. This study identifies magnetic resonance imaging (MRI) manifestations for predicting CAI development after a first episode of LAS and explores appropriate clinical indications for ordering MRI scans for these patients. Methods: All patients with a first-episode LAS who received plain radiograph and MRI scanning within the first 2 weeks after LAS from December 1, 2017 to December 1, 2019 were identified. Data were collected using the Cumberland Ankle Instability Tool at final follow-up. Demographic and other related clinical variables, including age, sex, body mass index, and treatment were also recorded. Univariable and multivariable analyses were performed successively to identify risk factors for CAI after first-episode LAS. Results: A total 131 out of 362 patients with a mean follow-up of 3.0 ± 0.6 years (mean ± SD; 2.0–4.1 years) developed CAI after first-episode LAS. According to multivariable regression, development of CAI after first-episode LAS was associated with 5 prognostic factors: age (odds ratio (OR) = 0.96, 95% confidence interval (95%CI): 0.93–1.00, p = 0.032); body mass index (OR = 1.09, 95%CI: 1.02–1.17, p = 0.009); posterior talofibular ligament injury (OR = 2.17, 95%CI: 1.05–4.48, p = 0.035); large bone marrow lesion of the talus (OR = 2.69, 95%CI: 1.30–5.58, p = 0.008), and Grade 2 effusion of the tibiotalar joint (OR = 2.61, 95%CI: 1.39–4.89, p = 0.003). When patients had at least 1 positive clinical finding in the 10-m walk test, anterior drawer test, or inversion tilt test, they had a 90.2% sensitivity and 77.4% specificity in terms of detecting at least 1 prognostic factor by MRI. Conclusion: MRI scanning is valuable in predicting CAI after first-episode LAS for those patients with at least 1 positive clinical finding in the 10-m walk test, anterior drawer test, and inversion tilt test. Further prospective and large-scale studies are necessary for validation.

Tailoring recrystallization via particle-stimulated nucleation (PSN) and pinning effects from secondary phase particles effectively weakens textures, which is still challenging for low-alloyed rare earth-free Mg alloys. Herein, the texture of a dilute cold-rolled Mg-2.2Al-0.33Ca (wt.%) alloy is found to reduce with the appearance of transverse direction (TD) texture components during static recrystallization. The texture transition is mainly attributed to the preferential growth of TD-oriented recrystallized grains, resulting from the preferential segregation of Al and Ca atoms on basal-oriented grain boundaries with low misorientation angles. The findings provide an in-depth understanding of texture modification in Mg alloys.