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Abstract The digital twin model of mine ventilation system (DTMVS) plays an important role in intelligent safety management. However, the uncertainty of the ventilation resistance coefficient, which is the core parameter of the model, makes it challenging to accurately construct a DTMVS. In this study, Latin Hypercube Sampling (LHS) and ventilation resistance coefficient estimation models (VRCEMs) are used to analyze the uncertainty. First, the LHS method was used to explore the effect of uncertainty in the simulated airflow by continuously increasing the level of uncertainty in the ventilation resistance coefficients. Subsequently, the ventilation resistance coefficients were estimated using the VRCEMs, and the uncertainty of the ventilation resistance coefficient and the simulated airflow was analyzed. The results showed that the ventilation resistance coefficients with a 5% coefficient of variation can cause the DTMVS to lose 34% of the real airflow data points. The degree of uncertainty in the ventilation resistance coefficients estimated by the VRCEM-GA (VRCEM using genetic algorithm) and VRCEM-DE (VRCEM using differential evolution algorithm) methods was enhanced by 27.4% and 4.4%, respectively, compared with VRCEM-ES (VRCEM using evolutionary strategy algorithm). The VRCEM-ES model had the least influence on the uncertainty of the simulated airflow of DTMVS. The simulated airflow of the DTMVS constructed based on VRCEMs fluctuated normally within the confidence interval. VRCEMs had a higher sensitivity to the ventilation resistance coefficients of branches with low coefficients of variation.

Abstract Background Obesity has emerged as a growing global public health concern over recent decades. Obesity prevalence exhibits substantial global variation, ranging from less than 5% in regions like China, Japan, and Africa to rates exceeding 75% in urban areas of Samoa. Aim To examine the involvement of metabolism-related genes. Methods Gene expression datasets GSE110729 and GSE205668 were accessed from the GEO database. DEGs between obese and lean groups were identified through DESeq2. Metabolism-related genes and pathways were detected using enrichment analysis, WGCNA, Random Forest, and XGBoost. The identified signature genes were validated by real-time quantitative PCR (qRT-PCR) in mouse models. Results A total of 389 genes exhibiting differential expression were discovered, showing significant enrichment in metabolic pathways, particularly in the propanoate metabolism pathway. The orangered4 module, which exhibited the highest correlation with propanoate metabolism, was identified using Weighted Correlation Network Analysis (WGCNA). By integrating the DEGs, WGCNA results, and machine learning methods, the identification of two metabolism-related genes, Storkhead Box 1 (STOX1), NACHT and WD repeat domain-containing protein 2(NWD2) was achieved. These signature genes successfully distinguished between obese and lean individuals. qRT-PCR analysis confirmed the downregulation of STOX1 and NWD2 in mouse models of obesity. Conclusion This study has analyzed the available GEO dataset in order to identify novel factors associated with obesity metabolism and found that STOX1 and NWD2 may serve as diagnostic biomarkers.

To determine the protective effects of FM0807 against diabetes-induced renal inflammation and fibrosis and the underlying mechanisms in vivo and in vitro. FM0807 was administered to db/db mice. Glomerular mesangial cells (HBZY-1) were cultured under high glucose conditions with or without FM0807. Gene and protein expression was assessed by quantitative real-time PCR, western blotting, and immunofluorescence. Mitochondrial reactive oxygen species were detected with MitoSOX Red. FM0807 markedly reduced blood glucose, glycosylated hemoglobin, triglycerides, and low-density lipoprotein-cholesterol levels and improved the liver organ index, the high-density lipoprotein-cholesterol level, and renal function, as evidenced by decreased 24-h urinary protein excretion and the creatinine and blood urea nitrogen levels. FM0807 ameliorated pathologic renal changes in diabetic mice (reduced glomerulosclerosis, diminished interstitial cellular inflammation, and less tubular luminal narrowing). Treatment with FM0807 also led to a significant reduction in the expression of inflammatory markers, including JAK2, STAT3, TNF-α, IL-1β, IL-6, TGF-β1, and Smad2/3, in addition to alterations in the expression of proteins associated with kidney injury. These data suggest that FM0807 alleviates diabetes-induced renal inflammation and fibrosis by modulating the JAK2/STAT3 and TGF-β1/SMAD2/3 signaling pathways.

Abstract Background Insulin like growth factor II mRNA binding protein 3 (IGF2BP3) has been implicated in numerous inflammatory and cancerous conditions. However, its precise molecular mechanisms in endometriosis (EMs) remains unclear. The aim of this study is to examine the influence of IGF2BP3 on the occurrence and progression of EMs and to elucidate its underlying molecular mechanism. Methods Efects of IGF2BP3 on endometriosis were confrmed in vitro and in vivo. Based on bioinformatics analysis, RNA immunoprecipitation (RIP), RNA pull-down assays and Fluorescent in situ hybridization (FISH) were used to show the association between IGF2BP3 and UCA1. Single-cell spatial transcriptomics analysis shows the expression distribution of glutaminase 1 (GLS1) mRNA in EMs. Study the effect on glutamine metabolism after ectopic endometriotic stromal cells (eESCs) were transfected with Sh-IGF2BP3 and Sh-UCA1 lentivirus. Results Immunohistochemical staining have revealed that IGF2BP3 was upregulated in ectopic endometriotic lesions (EC) compared to normal endometrial tissues (EN). The proliferation and migration ability of eESCs were greatly reduced by downregulating IGF2BP3. Additionally, IGF2BP3 has been observed to interact with urothelial carcinoma associated 1 (UCA1), leading to increased stability of GLS1 mRNA and subsequently enhancing glutamine metabolism. Results also demonstrated that IGF2BP3 directly interacts with the 3’ UTR region of GLS1 mRNA, influencing its expression and stability. Furthermore, UCA1 was able to bind with c-MYC protein, stabilizing c-MYC mRNA and consequently enhancing GLS1 expression through transcriptional promotion. Conclusion These discoveries underscored the critical involvement of IGF2BP3 in the elevation and stability of GLS1 mRNA in the context of glutamine metabolism by interacting with UCA1 in EMs. The implications of our study extended to the identification of possible therapeutic targets for individuals with EMs.

Abstract Background β-1,3-Xylooligosaccharides (XOS-3) extracted from Caulerpa lentillifera have shown potential antioxidative and anti-tumor properties, but research on their biological activities, particularly their anti-osteoarthritis effects, is still in early stages. Results XOS-3 were produced by eco-friendly enzymatic hydrolysis, displaying a semi-crystalline structure with predominant xylose, xylobiose, xylotriose, and xylotetraose components which were confirmed by IC, SEM, FT-IR, and XRD analysis. Compared with β-1,4-xylooligosaccharides, XOS-3 had stronger antioxidant properties, and the scavenging rate of O2 •− and DPPH• radicals was 82.31% and 58.44% at 2.0 mg/mL respectively. In vitro studies, XOS-3 significantly improved cell viability in IL-1β-induced rat chondrocytes from 43.41 to 73.5% at 100 μg/mL, demonstrating anti-inflammatory and cartilage-protective effects by modulating MMP13 and COL2A1 expression. Conclusions The study displayed the potential antioxidative and anti-osteoarthritis effects of XOS-3, offering new visuals for the development of marine polysaccharides in the treatment of osteoarthritis. Graphical Abstract

Millimeter waves are electromagnetic waves with wavelengths of 1–10 mm, which have characteristics of high frequency and short wavelength. They have gradually and widely been used in engineering and medical fields. We have identified studies related to millimeter waves in the biomedical field and summarized the biological effects of millimeter waves and their current status in medical applications. Finally, the shortcomings of existing studies and future developments were analyzed and discussed, with the aim of providing a reference for further research and development of millimeter waves in the medical field.

Abstract Background The long-term sequelae of Coronavirus disease 2019 (COVID-19) in children are unclear. We investigated COVID-19 symptoms in school-aged children to determine their impact on patients and their families. Methods This cross-sectional study, conducted on February 25–28, 2023, selected a representative kindergarten and 9-year school from Shenzhen, China. There were randomly two classes each for the 12 grades from kindergarten to junior high school. The school-aged children were aged 3–16 years. Literate parents completed an online questionnaire related to their children’s COVID-19 symptoms since December 1, 2022. Descriptive statistics were computed as necessary. Univariate and multivariable linear regression analyses were performed, and variables with a p-value

Superelastic shape memory alloys with an integration of large elastocaloric response and good cyclability are crucially demanded for the advancement of solid-state elastocaloric cooling technology. In this study, we demonstrate a giant elastocaloric effect with improved cyclic stability in a A textured polycrystalline (Ni50Mn31Ti19)99B1 alloy developed through directional solidification. It is shown that large adiabatic temperature variation (|ΔTad|) values more than 15 K are obtained across the temperature range from 283 K to 373 K. In particular, a giant ΔTad up to −27.2 K is achieved by unloading from a relatively low compressive stress of 412 MPa at 303 K. Moreover, persistent |ΔTad| values exceeding 8.5 K are sustained for over 12,000 cycles, exhibiting a very low attenuation behavior with a rate of 7.5 × 10−5 K per cycle. The enhanced elastocaloric properties observed in the present alloy are ascribed to the microstructure texturing as well as the introduction of a secondary phase due to boron alloying.

Abstract Aims Diabetic cardiomyopathy (DCM) is a major complication of diabetes and a risk factor for cardiovascular disease. Endothelial dysfunction is central to DCM, and endothelial-to-mesenchymal transition (EndMT) is a key form of endothelial dysfunction in diabetes. EndMT in DCM has been well-studied in model systems and has been found to be epigenetically regulated by non-coding RNAs (ncRNAs). However, EndMT in DCM and its associated epigenetic changes need further characterization in human patients. It is also not known if ncRNAs are affected by changes in DNA methylation in DCM. This study aims to confirm in human hearts, the findings from animal and cell studies, and potentially provide novel insight into interactions between DNA methylation and ncRNAs in EndMT in DCM. Methods and results Heart tissues were collected from autopsy patients, fixed in formalin, and embedded in paraffin. Thin sections from paraffin-embedded tissues were used for histology and immunofluorescence analyses, where we confirmed that diabetic patients showed increased cardiac fibrosis that EndMT had occurred. Tissue curls from the paraffin-embedded tissues were used for RT-qPCR and methylation analyses. RT-qPCR quantitatively showed that EndMT occurs in the hearts of diabetics, and that EndMT in human hearts corresponded to changes in key ncRNAs. Methylation analysis showed that some of the EndMT-related ncRNAs were regulated by DNA promoter methylation, while others may be regulated through different epigenetic mechanisms. Conclusions We show that EndMT is a relevant pathological process in human hearts during DCM, and that its occurrence coincides with changes in relevant ncRNAs. We further find that interplay between DNA methylation and certain ncRNAs involved in the regulation of EndMT may contribute to the observed changes in ncRNA expression. These findings reinforce the role of EndMT in patients afflicted with DCM and underscore the complexities and importance of the interactions between different facets of epigenetic regulation.

Abstract Endometriosis is a gynecological inflammatory disease that is linked with immune cells, specifically macrophages. IL-33 secreted from macrophages is known to accelerate the progression of endometriosis. The periodic and repeated bleeding that occurs in women with endometriosis leads to excess iron in the microenvironment that is conducive to ferroptosis, a process related to intracellular ROS production, lipid peroxidation and mitochondrial damage. It is suggested that eESCs may specifically be able to inhibit ferroptosis. However, it is currently unclear whether IL-33 directly regulates ferroptosis to influence the disease course in endometriosis. In this study, eESCs co-cultured with macrophages or stimulated with IL-33/ST2 were observed to have increased cell viability and migration. Additionally, IL-33/ST2 decreased intracellular iron levels and lipid peroxidation in eESCs exposed to erastin treatment. Furthermore, IL-33/ST2 treatment resulted in a notable upregulation in SLC7A11 expression in eESCs due to the downregulation of negative transcription factor ATF3, thereby suppressing ferroptosis. The P38/JNK pathway activated by IL-33/ST2 was also found to inhibit the transcription factor ATF3. Therefore, we concluded that IL-33/ST2 inhibits the ATF3-mediated reduction in SLC7A11 transcript levels via the P38/JNK pathway. The findings reveal that macrophage-derived IL-33 upregulates SLC7A11 in eESCs through the p38/JNK/ATF3 pathway, ultimately resulting in protection against ferroptosis in eESCs. Moreover, we conducted an experiment using endometriosis model mice that showed that a combination of IL-33-Ab and erastin treatment alleviated the disease, showing the promise of combining immunotherapy and ferroptosis therapy.

With the improvement of data abilities and the development of emerging technologies, there are profound changes occurring in economic patterns and competitive structure of industries.In order to better respond to future opportunities and challenges, and to improve competitiveness of enterprises in new situations, it is necessary to understand and master the knowledge of digital transformation.The new competitive situation was discussed in which traditional enterprises would gradually be replaced by digital-transformed ones, digital transformation was differentiated from digitalization.Main challenges facing traditional enterprises while undergoing digital transformation were pinpointed, which were the lack of funds, talents, data and consciousness.A digital transformation service platform oriented to new competitive situation was proposed, which provided a feasible solution to enhancing enterprise competitiveness and conducting digital transformation.

Abstract Background Given the ubiquitous nature of mycorrhizal symbioses, different symbiotic fungi have obvious differences in structure and function, which may affect associated tree aboveground and belowground C allocation dynamics. However, the mechanisms underlying tree aboveground and belowground C allocation and its response to symbiotic mycorrhizal types and other factors (e.g., resource availability) remain poorly understood. Results We used forest inventory data to explore the potential mechanism of tree aboveground and belowground C allocation patterns in Northeast China. Our results showed that tree-fungal symbioses were related to the patterns of tree C allocation. The ratio of aboveground to belowground C pool was significantly higher in ectomycorrhizal (EM)-associated trees than that in arbuscular mycorrhizal (AM)-associated trees. Symbiotic mycorrhizal types were associated with the responses of tree aboveground and belowground C allocation to different factors, such as mean annual precipitation (MAP) and mean annual temperature (MAT). Almost all factors significantly increased aboveground C allocation in AM-associated trees but significantly decreased it in EM-associated trees. Moreover, after controlling the other factors, the effects of climate factors (MAT and MAP) on the C allocation of AM- and EM-associated trees were similar. Increases in MAT and MAP significantly increased belowground and aboveground C allocation, respectively. Conclusions Our results demonstrate symbiotic mycorrhizal types play an important role in controlling tree aboveground and belowground C allocation and dynamics.

In rice cultivation, the traits of semi-dwarfism and glutinous texture are pivotal for optimizing yield potential and grain quality, respectively. Xiangdaowan (XDW) rice, renowned for its exceptional aromatic properties, has faced challenges due to its tall stature and high amylose content, resulting in poor lodging resistance and suboptimal culinary attributes. To address these issues, we employed CRISPR/Cas9 technology to precisely edit the SD1 and Wx genes in XDW rice, leading to the development of stable genetically homozygous lines with desired semi-dwarf and glutinous characteristics. The sd1-wx mutant lines exhibited reduced gibberellin content, plant height, and amylose content, while maintaining hardly changed germination rate and other key agronomic traits. Importantly, our study demonstrated that exogenous GA3 application effectively promoted growth by compensating for the deficiency of endogenous gibberellin. Based on this, a semi-dwarf glutinous elite rice (Oryza sativa L.) Lines was developed without too much effect on most agronomic traits. Furthermore, a comparative transcriptome analysis unveiled that differentially expressed genes (DEGs) were primarily associated with the anchored component of the membrane, hydrogen peroxide catabolic process, peroxidase activity, terpene synthase activity, and apoplast. Additionally, terpene synthase genes involved in catalyzing the biosynthesis of diterpenoids to gibberellins were enriched and significantly down-regulated. This comprehensive study provides an efficient method for simultaneously enhancing rice plant height and quality, paving the way for the development of lodging-resistant and high-quality rice varieties.

Bu-Shen-Yi-Qi granule (BSYQG), a Chinese herbal formula, has been used for the treatment of ischemic stroke with proven efficacy. The purpose of this study is to evaluate the therapeutic efficacy of BSYQG in neurovascular unit (NVU) and its mechanism of action on the thrombin expression in the cerebral ischemic/reperfusion (I/R) model. In the study, a rat model of I/R was established using middle cerebral artery occlusion operation (MCAO). Adult male Sprague–Dawley rats were divided into four groups (n = 36): sham-operation; I/R; I/R + BSYQG(6 g/kg/day), I/R + Argatroban (0.56 mg/ml). Apoptotic cells in the NVU were detected by doubling-labeling using TUNEL assay and immunofluorescence. The dynamics of thrombin expression was detected using immunofluorescence on both sides after I/R injury. Compared with I/R group the numbers and rates of neuronal apoptosis in BSYQG groups significantly decreased (P

Abstract Dermal fibroblasts and cutaneous nerves are important players in skin diseases, while their reciprocal roles during skin inflammation have not been characterized. Here we identify an inflammation-induced subset of papillary fibroblasts that promotes aberrant neurite outgrowth and psoriasiform skin inflammation by secreting the extracellular matrix protein tenascin-C (TNC). Single-cell analysis of fibroblast lineages reveals a Tnc + papillary fibroblast subset with pro-axonogenesis and neuro-regulation transcriptomic hallmarks. TNC overexpression in fibroblasts boosts neurite outgrowth in co-cultured neurons, while fibroblast-specific TNC ablation suppresses hyperinnervation and alleviates skin inflammation in male mice modeling psoriasis. Dermal γδT cells, the main producers of type 17 pathogenic cytokines, frequently contact nerve fibers in mouse psoriasiform lesions and are likely modulated by postsynaptic signals. Overall, our results highlight the role of an inflammation-responsive fibroblast subset in facilitating neuro-immune synapse formation and suggest potential avenues for future therapeutic research.

Abstract We explored a new artificial intelligence-assisted method to assist junior ultrasonographers in improving the diagnostic performance of uterine fibroids and further compared it with senior ultrasonographers to confirm the effectiveness and feasibility of the artificial intelligence method. In this retrospective study, we collected a total of 3870 ultrasound images from 667 patients with a mean age of 42.45 years ± 6.23 [SD] for those who received a pathologically confirmed diagnosis of uterine fibroids and 570 women with a mean age of 39.24 years ± 5.32 [SD] without uterine lesions from Shunde Hospital of Southern Medical University between 2015 and 2020. The DCNN model was trained and developed on the training dataset (2706 images) and internal validation dataset (676 images). To evaluate the performance of the model on the external validation dataset (488 images), we assessed the diagnostic performance of the DCNN with ultrasonographers possessing different levels of seniority. The DCNN model aided the junior ultrasonographers (Averaged) in diagnosing uterine fibroids with higher accuracy (94.72% vs. 86.63%, P

Psoriasis is an inflammatory disease which has proven difficult to cure. Prof. Honglin Wang’s team describes L-menthol for treating models of psoriasis and uncovers the dysfunctional HES1- IGBP1-PP6 axis in psoriasis pathology by using L-menthol as a probe.

Abstract The closed‐loop wireless power transfer (WPT) system can realize constant voltage output in the presence of perturbation. However, the parameter design of the controller is a difficult problem. The traditional trial‐and‐error method is time‐consuming and difficult to find optimal parameters. A parameter optimization strategy of control systems for uncertain WPT systems using the modified genetic algorithm (MGA) is proposed. Firstly, because the system has different characteristics at different periods, the simulation process is divided into three stages. The first one is the start‐up stage, in which we mainly consider the overshoot and the rate of the voltage rise. The second one is the tracking stage, in which the tracking time and switching loss are mainly considered. The third one is the stabilisation stage, in which the steady‐state error and switching loss are mainly considered. Secondly, three cost functions are designed according to the characteristics of the three stages, and then the optimal controller parameters of each stage are obtained by using MGA. Finally, the effectiveness of the proposed method is verified by simulation. The optimization results show that compared with the previous parameter optimization method, the optimal controller parameters obtained by the proposed method make the WPT system achieve better performance.

Abstract Cu2O has been intensively studied as an efficient catalyst for CO2 reduction reaction (CO2RR). By various methods for fine-tuning the morphology and surface modification, high selectivity and activity of different products can be achieved. Here, we report a novel Cu2O nanostructure design by facet-controlled etching, during which the catalyst structure switched from a cuboctahedron architecture to a hollow dice-like structure. The as-etched catalysts exhibit a high Faradic efficiency of formic acid, reaching 75.1% at a low potential of -1.0 V. Further characterizations indicate that the performance enhancement is attributed to the increased oxygen vacancies induced by the etching process. Our Cu2O nanostructure design provides a new approach for high-efficiency catalysts for formic acid production at low potentials.

ObjectivesTo explore an intelligent detection technology based on deep learning algorithms to assist the clinical diagnosis of distal radius fractures (DRFs), and further compare it with human performance to verify the feasibility of this method.MethodsA total of 3,240 patients (fracture: n = 1,620, normal: n = 1,620) were included in this study, with a total of 3,276 wrist joint anteroposterior (AP) X-ray films (1,639 fractured, 1,637 normal) and 3,260 wrist joint lateral X-ray films (1,623 fractured, 1,637 normal). We divided the patients into training set, validation set and test set in a ratio of 7:1.5:1.5. The deep learning models were developed using the data from the training and validation sets, and then their effectiveness were evaluated using the data from the test set. Evaluate the diagnostic performance of deep learning models using receiver operating characteristic (ROC) curves and area under the curve (AUC), accuracy, sensitivity, and specificity, and compare them with medical professionals.ResultsThe deep learning ensemble model had excellent accuracy (97.03%), sensitivity (95.70%), and specificity (98.37%) in detecting DRFs. Among them, the accuracy of the AP view was 97.75%, the sensitivity 97.13%, and the specificity 98.37%; the accuracy of the lateral view was 96.32%, the sensitivity 94.26%, and the specificity 98.37%. When the wrist joint is counted, the accuracy was 97.55%, the sensitivity 98.36%, and the specificity 96.73%. In terms of these variables, the performance of the ensemble model is superior to that of both the orthopedic attending physician group and the radiology attending physician group.ConclusionThis deep learning ensemble model has excellent performance in detecting DRFs on plain X-ray films. Using this artificial intelligence model as a second expert to assist clinical diagnosis is expected to improve the accuracy of diagnosing DRFs and enhance clinical work efficiency.

Objective: Explore a new deep learning (DL) object detection algorithm for clinical auxiliary diagnosis of lumbar spondylolisthesis and compare it with doctors’ evaluation to verify the effectiveness and feasibility of the DL algorithm in the diagnosis of lumbar spondylolisthesis.Methods: Lumbar lateral radiographs of 1,596 patients with lumbar spondylolisthesis from three medical institutions were collected, and senior orthopedic surgeons and radiologists jointly diagnosed and marked them to establish a database. These radiographs were randomly divided into a training set (n = 1,117), a validation set (n = 240), and a test set (n = 239) in a ratio of 0.7 : 0.15: 0.15. We trained two DL models for automatic detection of spondylolisthesis and evaluated their diagnostic performance by PR curves, areas under the curve, precision, recall, F1-score. Then we chose the model with better performance and compared its results with professionals’ evaluation.Results: A total of 1,780 annotations were marked for training (1,242), validation (263), and test (275). The Faster Region-based Convolutional Neural Network (R-CNN) showed better precision (0.935), recall (0.935), and F1-score (0.935) in the detection of spondylolisthesis, which outperformed the doctor group with precision (0.927), recall (0.892), f1-score (0.910). In addition, with the assistance of the DL model, the precision of the doctor group increased by 4.8%, the recall by 8.2%, the F1-score by 6.4%, and the average diagnosis time per plain X-ray was shortened by 7.139 s.Conclusion: The DL detection algorithm is an effective method for clinical diagnosis of lumbar spondylolisthesis. It can be used as an assistant expert to improve the accuracy of lumbar spondylolisthesis diagnosis and reduce the clinical workloads.

This paper presents a hierarchical lane-changing trajectory planner based on the least action principle for autonomous driving. Our approach aims to achieve reliable real-time avoidance of static and moving obstacles in multi-vehicle interaction scenarios on structured urban roads. Unlike previous studies that rely on subjective weight allocation and single weighting methods, we propose a novel trajectory planning strategy that decomposes the process into two stages: candidate trajectory generation and optimal trajectory decision-making. The candidate trajectory generation employs a path-velocity decomposition method, using B-spline curves to generate a multi-objective optimal lane-changing candidate path. Collision checking eliminates paths at risk of collision with static obstacles. Dynamic programming (DP) and quadratic programming (QP) are then used to plan the velocity of safe paths, generating candidate lane-changing trajectories based on curvature checking. The optimal trajectory decision-making process follows the decision mechanism of excellent drivers. We introduce a comprehensive evaluation function, the average action, which considers safety, comfort, and efficiency based on the least action principle. Feasible trajectories are ranked based on their average action, and the trajectory with the minimum average action and no collision risk with moving obstacles is selected as the tracking target. The effectiveness of the proposed method is validated through two common lane-changing scenarios. The results demonstrate that our approach enables smooth, efficient, and safe lane-changing while effectively tracking the planned velocity and path. This method offers a solution to local trajectory planning problems in complex environments and holds promising prospects in the field of autonomous driving.

Abstract Psoriasis is a common, chronic immune-mediated systemic disease that had no effective and durable treatment. Mesenchymal stem cells (MSCs) have immunomodulatory properties. Therefore, we performed a phase 1/2a, single-arm clinical trial to evaluate the safety and efficacy of human umbilical cord-derived MSCs (UMSCs) in the treatment of psoriasis and to preliminarily explore the possible mechanisms. Seventeen patients with psoriasis were enrolled and received UMSC infusions. Adverse events, laboratory parameters, PASI, and PGA were analyzed. We did not observe obvious side effects during the treatment and 6-month follow-up. A total of 47.1% (8/17) of the psoriasis patients had at least 40% improvement in the PASI score, and 17.6% (3/17) had no sign of disease or minimal disease based on the PGA score. And the efficiency was 25% (2/8) for males and 66.7% (6/9) for females. After UMSC transplantation (UMSCT), the frequencies of Tregs and CD4+ memory T cells were significantly increased, and the frequencies of T helper (Th) 17 and CD4+ naive T cells were significantly decreased in peripheral blood (PB) of psoriasis patients. And all responders showed significant increases in Tregs and CD4+ memory T cells, and significant decreases in Th17 cells and serum IL-17 level after UMSCT. And baseline level of Tregs in responders were significantly lower than those in nonresponders. In conclusion, allogeneic UMSCT is safe and partially effective in psoriasis patients, and level of Tregs may be used as a potent biomarker to predict the clinical efficacy of UMSCT. Trial registration Clinical Trials NCT03765957

Abstract Background Endometriosis (EMs) is a common benign gynecological disease that affects approximately 10% of females of reproductive age. Endometriosis ectopic lesions could recruit macrophages, which in turn facilitates endometriosis progression. Several studies have indicated that CCL20 derived from macrophages activates the expression of CCR6 in several cells and induces cell proliferation and migration. However, the function of the CCL20/CCR6 axis in the interactions between macrophages and endometriotic stromal cells (ESCs) in EMs has yet to be elucidated. Methods Ectopic and normal endometrial tissues were collected from 35 ovarian endometriosis patients and 21 control participants for immunohistochemical staining. It was confirmed that macrophages secreted CCL20 to promote CCR6 activation of ESCs during co-culture by ELISA, qRT-PCR and western blot analysis. CCK8 and Edu assays were used to detect cell proliferation, and wound healing and Transwell assay were used to detect cell migration. Autophagic flux was detected by measuring the protein expression levels of LC3 and P62by western blot and analyzing the red/yellow puncta after ESCs were transfected with mRFP-GFP-LC3 double fluorescence adenovirus (Ad‐LC3). Lysosomal function was tested by quantifying the fluorescent intensities of Lyso-tracker and Gal3 and activity of acid phosphatase. In addition, co-IP experiments verified the binding relationship between CCR6 and TFEB. Finally, the suppressive effect of CCL20-NAb on endometriosis lesions in vivo was demonstrated in mice models. Results We demonstrated that macrophages secreted CCL20 to promote CCR6 activation of ESCs during co-culture, which further induced the proliferation and migration of ESCs. We observed that the CCL20/CCR6 axis impaired lysosomal function and then blocked the autolysosome degradation process of autophagic flux in ESCs. The combination of CCR6 and TFEB to inhibit TFEB nuclear translocation mediates the role of the CCL20/CCR6 axis in the above process. We also found that co-culture with ESCs upregulated the production and secretion of CCL20 by macrophages. The suppression effect of CCL20-NAb on endometriosis lesions in vivo was demonstrated in mice models. Conclusions Our data indicate that macrophages block TFEB-mediated autolysosome degradation process of autophagic flux in ESCs via the CCL20/CCR6 axis, thereby promoting ESC proliferation and migration.

Abstract Background Chlamydia trachomatis (CT) infection could lead to seriously adverse outcomes if left untreated. This study aimed to determine CT-related knowledge, opinion to testing, and practices of providers among different sexually transmitted infections (STI) related departments in hospitals in Shenzhen city, China, and also to explore the differences in these responses. Materials and methods From 1st April 2018 to 15th April 2018, a cross-sectional study was conducted in Shenzhen and 64 of 66 hospitals agreed to participate in this study. In the hospital sites, all the providers from the department of obstetrics and gynecology, department of dermatology and venereology, department of urology, and anorectal surgical department were recruited. A structured paper-based questionnaire was used to obtain data on CT-related information. Results A total of 355 providers from 64 hospitals participated in the current study. Compared to providers from the department of dermatology and venereology, those from the department of obstetrics and gynecology (OR = 0.31, 95% CI 0.16—0.62), department of urology (OR = 0.32, 95% CI 0.16—0.65), and anorectal surgical department (OR = 0.25, 95% CI 0.09—0.71) were less likely to identify that “Be in a long-term mutually monogamous relationship with a partner who has been tested and has negative STI test results.” is an appropriate way for a sexually active person to reduce risk of getting CT. Also, those from the department of obstetrics and gynecology (OR = 0.45, 95% CI 0.23—0.87) were less likely to identify that “Use latex condoms the right way every time you have sex” is another appropriate way. A high proportion of providers agreed that all sexually active patients attending to their department should be screened regularly (77.1%), and they are willing to offer opportunistic CT screening (96.0%). Only 11.4% of respondents correctly identified that the appropriate time frame of the CT retesting is three months. Conclusions Providers among STI-related departments in hospitals showed a very high willingness to offer opportunistic CT screening. However, this study showed important gaps in providers’ knowledge and practices in China, targeted training in CT-related knowledge and practice is urgently needed.

Abstract Endometriosis is a chronic disorder characterized by the implantation of endometrial glands and stroma outside the uterus. However, the pathogenesis of endometriosis is still unclear. To date, there is no fully effective treatment without trauma because of various side effects. Recent data suggest that ferroptosis is a novel recognized form of nonapoptosis-regulated cell death characterized by iron-dependent and lethal lipid peroxidation accumulation, showing great promise in the treatment of many diseases. In the present study, we verified that erastin induced ferroptosis in ectopic endometrial stromal cells (EESCs). Furthermore, we found that the expression of metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) was decreased during erastin-induced ferroptosis. Knockdown of MALAT1 significantly aggravated the inhibition of cell viability and increased intracellular iron, Liperfluo, and MDA levels in EESCs upon erastin treatment. Mechanistically, we demonstrated that MALAT1 served as a competing endogenous RNA of miR-145-5p to regulate the expression of MUC1, a suppressor of ferroptosis. MALAT1 knockdown-mediated ferroptotic cell death and MUC1 downregulation could be abrogated by inhibition of miR-145-5p. In addition, miR-145-5p inhibition-mediated ferroptotic cell death could be abolished by MUC1 knockdown. Furthermore, erastin-induced ferroptosis shrunk endometriotic lesions via the MALAT1/miR-145-5p/MUC1 axis in vivo. Taken together, our data indicate that knockdown of MALAT1 facilitates ferroptosis upon erastin treatment via miR-145-5p/MUC1 signaling. The synergistic effect of MALAT1 knockdown and erastin induction in ferroptosis may be a new therapeutic strategy for endometriosis.

Regulatory T (Treg) cells constitute a dynamic population that is critical in autoimmunity. Treg cell therapies for autoimmune diseases are mainly focused on enhancing their suppressive activities. However, recent studies demonstrated that certain inflammatory conditions induce Treg cell instability with diminished FoxP3 expression and convert them into pathogenic effector cells. Therefore, the identification of novel targets crucial to both Treg cell function and plasticity is of vital importance to the development of therapeutic approaches in autoimmunity. In this study, we found that conditional Pp6 knockout (cKO) in Treg cells led to spontaneous autoinflammation, immune cell activation, and diminished levels of FoxP3 in CD4+ T cells in mice. Loss of Pp6 in Treg cells exacerbated two classical mouse models of Treg-related autoinflammation. Mechanistically, Pp6 deficiency increased CpG motif methylation of the FoxP3 locus by dephosphorylating Dnmt1 and enhancing Akt phosphorylation at Ser473/Thr308, leading to impaired FoxP3 expression in Treg cells. In summary, our study proposes Pp6 as a critical positive regulator of FoxP3 that acts by decreasing DNA methylation of the FoxP3 gene enhancer and inhibiting Akt signaling, thus maintaining Treg cell stability and preventing autoimmune diseases.

As a crucial staple crop in agricultural production, maize is extensively cultivated worldwide and plays a pivotal role in ensuring global food security. However, the significant deficiency of essential amino acids (EAA) and conditionally essential amino acids (CEAA), such as lysine (Lys), tryptophan (Trp), methionine (Met), and cysteine (Cys), leads to an imbalance of amino acids in the grain. This study investigates the regulatory mechanism of sulfur (S) application for regulating the amino acid balance of maize grains. The results demonstrate that S application has substantial effects on both the maize yield and nutritional quality. The S application resulted in an increase in maize yield by simultaneously enhancing the grain number per ear (GN) and 100-grain weight (GW), while S application elevated protein concentration through the augmentation of Cys concentration in maize grains. Furthermore, the Cys in grains optimizes the amino acid balance by regulating the ratio of other amino acids, thereby enhancing the nutritional quality of maize while ensuring a steady increase in protein concentration, simultaneously. Overall, the S application at 60–90 kg ha−1 synergistically improved both the yield and nutritional quality of maize, meeting the requirements for sustainable development in maize production. The findings offer a novel theoretical foundation and nutrient management approach for achieving high-yield and superior-quality maize production.

Establishing an accurate and computationally efficient model for driving risk assessment, considering the influence of vehicle motion state and kinematic characteristics on path planning, is crucial for generating safe, comfortable, and easily trackable obstacle avoidance paths. To address this topic, this paper proposes a novel dual-layered dynamic path-planning method for obstacle avoidance based on the driving safety field (DSF). The contributions of the proposed approach lie in its ability to address the challenges of accurately modeling driving risk, efficient path smoothing and adaptability to vehicle kinematic characteristics, and providing collision-free, curvature-continuous, and adaptable obstacle avoidance paths. In the upper layer, a comprehensive driving safety field is constructed, composed of a potential field generated by static obstacles, a kinetic field generated by dynamic obstacles, a potential field generated by lane boundaries, and a driving field generated by the target position. By analyzing the virtual field forces exerted on the ego vehicle within the comprehensive driving safety field, the resultant force direction is utilized as guidance for the vehicle’s forward motion. This generates an initial obstacle avoidance path that satisfies the vehicle’s kinematic and dynamic constraints. In the lower layer, the problem of path smoothing is transformed into a standard quadratic programming (QP) form. By optimizing discrete waypoints and fitting polynomial curves, a curvature-continuous and smooth path is obtained. Simulation results demonstrate that our proposed path-planning algorithm outperforms the method based on the improved artificial potential field (APF). It not only generates collision-free and curvature-continuous paths but also significantly reduces parameters such as path curvature (reduced by 62.29% to 87.32%), curvature variation rate, and heading angle (reduced by 34.11% to 72.06%). Furthermore, our algorithm dynamically adjusts the starting position of the obstacle avoidance maneuver based on the vehicle’s motion state. As the relative velocity between the ego vehicle and the obstacle vehicle increases, the starting position of the obstacle avoidance path is adjusted accordingly, enabling the proactive avoidance of stationary or moving single and multiple obstacles. The proposed method satisfies the requirements of obstacle avoidance safety, comfort, and stability for intelligent vehicles in complex environments.

Abstract Background Avian colibacillosis is an infectious bacterial disease caused by avian pathogenic Escherichia coli (APEC). APEC causes a wide variety of intestinal and extraintestinal infections, including InPEC and ExPEC, which result in enormous losses in the poultry industry. In this study, we investigated the prevalence of InPEC and ExPEC in Central China, and the isolates were characterized using molecular approaches and tested for virulence factors and antibiotic resistance. Results A total of 200 chicken-derived E. coli isolates were collected for study from 2019 and 2020. The prevalence of B2 and D phylogenic groups in the 200 chicken-derived E. coli was verified by triplex PCR, which accounted for 50.53% (48/95) and 9.52% (10/105) in ExPEC and InPEC, respectively. Additionally, multilocus sequence typing method was used to examine the genetic diversity of these E. coli isolates, which showed that the dominant STs of ExPEC included ST117 (n = 10, 20.83%), ST297 (n = 5, 10.42%), ST93 (n = 4, 8.33%), ST1426 (n = 4, 8.33%) and ST10 (n = 3, 6.25%), while the dominant ST of InPEC was ST117 (n = 2, 20%). Furthermore, antimicrobial susceptibility tests of 16 antibiotics for those strains were conducted. The result showed that more than 60% of the ExPEC and InPEC were resistant to streptomycin and nalidixic acid. Among these streptomycin resistant isolates (n = 49), 99.76% harbored aminoglycoside resistance gene strA, and 63.27% harbored strB. Among these nalidixic acid resistant isolates (n = 38), 94.74% harbored a S83L mutation in gyrA, and 44.74% harbored a D87N mutation in gyrA. Moreover, the prevalence of multidrug-resistant (MDR) in the isolates of ExPEC and InPEC was 31.25% (15/48) and 20% (2/10), respectively. Alarmingly, 8.33% (4/48) of the ExPEC and 20% (2/10) of the InPEC were extensively drug-resistant (XDR). Finally, the presence of 13 virulence-associated genes was checked in these isolates, which over 95% of the ExPEC and InPEC strains harbored irp2, feoB, fimH, ompT, ompA. 10.42% of the ExPEC and 10% of the InPEC were positive for kpsM. Only ExPEC isolates carried ibeA gene, and the rate was 4.17%. All tested strains were negative to LT and cnf genes. The carrying rate of iss and iutA were significantly different between the InPEC and ExPEC isolates (P

Abstract Background Interferon regulatory factor-8 (IRF8) and nuclear factor-activated T cells c1 (NFATc1) are two transcription factors that have an important role in osteoclast differentiation. Thanks to ChIP-seq technology, scientists can now estimate potential genome-wide target genes of IRF8 and NFATc1. However, finding target genes that are consistently up-regulated or down-regulated across different studies is hard because it requires analysis of a large number of high-throughput expression studies from a comparable context. Method We have developed a machine learning based method, called, Cohort-based TF target prediction system (cTAP) to overcome this problem. This method assumes that the pathway involving the transcription factors of interest is featured with multiple “functional groups” of marker genes pertaining to the concerned biological process. It uses two notions, Gene-Present Sufficiently (GP) and Gene-Absent Insufficiently (GA), in addition to log2 fold changes of differentially expressed genes for the prediction. Target prediction is made by applying multiple machine-learning models, which learn the patterns of GP and GA from log2 fold changes and four types of Z scores from the normalized cohort’s gene expression data. The learned patterns are then associated with the putative transcription factor targets to identify genes that consistently exhibit Up/Down gene regulation patterns within the cohort. We applied this method to 11 publicly available GEO data sets related to osteoclastgenesis. Result Our experiment identified a small number of Up/Down IRF8 and NFATc1 target genes as relevant to osteoclast differentiation. The machine learning models using GP and GA produced NFATc1 and IRF8 target genes different than simply using a log2 fold change alone. Our literature survey revealed that all predicted target genes have known roles in bone remodeling, specifically related to the immune system and osteoclast formation and functions, suggesting confidence and validity in our method. Conclusion cTAP was motivated by recognizing that biologists tend to use Z score values present in data sets for the analysis. However, using cTAP effectively presupposes assembling a sizable cohort of gene expression data sets within a comparable context. As public gene expression data repositories grow, the need to use cohort-based analysis method like cTAP will become increasingly important.

PurposeTo develop and assess a deep convolutional neural network (DCNN) model for the automatic detection of bone metastases from lung cancer on computed tomography (CT)MethodsIn this retrospective study, CT scans acquired from a single institution from June 2012 to May 2022 were included. In total, 126 patients were assigned to a training cohort (n = 76), a validation cohort (n = 12), and a testing cohort (n = 38). We trained and developed a DCNN model based on positive scans with bone metastases and negative scans without bone metastases to detect and segment the bone metastases of lung cancer on CT. We evaluated the clinical efficacy of the DCNN model in an observer study with five board-certified radiologists and three junior radiologists. The receiver operator characteristic curve was used to assess the sensitivity and false positives of the detection performance; the intersection-over-union and dice coefficient were used to evaluate the segmentation performance of predicted lung cancer bone metastases.ResultsThe DCNN model achieved a detection sensitivity of 0.894, with 5.24 average false positives per case, and a segmentation dice coefficient of 0.856 in the testing cohort. Through the radiologists-DCNN model collaboration, the detection accuracy of the three junior radiologists improved from 0.617 to 0.879 and the sensitivity from 0.680 to 0.902. Furthermore, the mean interpretation time per case of the junior radiologists was reduced by 228 s (p = 0.045).ConclusionsThe proposed DCNN model for automatic lung cancer bone metastases detection can improve diagnostic efficiency and reduce the diagnosis time and workload of junior radiologists.

Diabetes and its complications represent a great burden on the global healthcare system. Diabetic complications are fundamentally diseases of the vasculature, with endothelial cells being the centerpiece of early hyperglycemia-induced changes. Endothelial-to-mesenchymal transition is a tightly regulated process that results in endothelial cells losing endothelial characteristics and developing mesenchymal traits. Although endothelial-to-mesenchymal transition has been found to occur within most of the major complications of diabetes, it has not been a major focus of study or a common target in the treatment or prevention of diabetic complications. In this review we summarize the importance of endothelial-to-mesenchymal transition in each major diabetic complication, examine specific mechanisms at play, and highlight potential mechanisms to prevent endothelial-to-mesenchymal transition in each of the major chronic complications of diabetes.

BackgroundNeonatal hyperbilirubinemia is one of the leading causes of neonatal readmission—especially severe hyperbilirubinemia and its complications—and it influences disease burden as well as neonatal and maternal health. Smartphones have been shown to have satisfactory accuracy in screening neonatal bilirubin levels, but the impact of this technology on neonatal health care service and maternal health outcomes is still unknown. ObjectiveThe aim of this study was to evaluate the impact of a smartphone-based out-of-hospital neonatal jaundice screening program on neonatal readmission rates for jaundice and related maternal anxiety. MethodsThis was a 2-arm, unblinded, randomized controlled trial with 30 days of intervention and follow-up periods. From August 2019 to August 2020, healthy mother-infant dyads were recruited on-site from 3 public hospitals in Hainan, China. Intervention group mothers used the smartphone app to routinely monitor neonatal jaundice at home under the web-based guidance of pediatricians. Control group participants received routine care. The primary study outcome was the neonatal readmission rate due to jaundice within 30 days of the first hospital discharge. The secondary outcome was the maternal anxiety score associated with neonatal jaundice. The data were collected through a self-assessed questionnaire. All participants were included in the analysis (intention-to-treat). ResultsIn this study, 1424 mother-infant dyads were recruited, comprising 1424 mothers and 1424 newborns. The median age of the mothers was 29 (IQR 26-32) years, and there were 714 (50.1%) male neonates. These mother-infant dyads were randomly assigned to the intervention group and the control group, with 712 dyads in each group; only 1187 of these dyads completed the follow-up. We found that the adjusted 30-day neonatal readmission rate due to jaundice reduced by 10.5% (71/605, 11.7% vs 141/582, 24.2%; 95% CI 5%-15.9%; odds ratio 0.4, 95% CI 0.3-0.5; P

ObjectiveChlamydia trachomatis (CT) infection is one of the most common sexually transmitted infections (STIs) worldwide. This study aimed to provide prevalence and associated factors data among patients seeking clinic-based STI services for estimating the disease burden of CT.Study design and methodA cross-sectional survey was conducted among patients attending clinics for STI services. Patients' social-demographic and behavioral information was collected and CT infection was determined by nucleic acid amplification test (NAAT) with self-collected urine specimens. Associated factors were identified using logistic regression.ResultsAmong the 8,324 participants, the overall prevalence was 9.0% with 10.7% for males and 8.3% for females respectively. Multivariate analysis showed that aged < 24 [adjusted odds ratio (aOR) = 1.27, 95% confidence interval (CI) = 1.01–1.59], being unmarried (aOR = 1.64, 95%CI = 1.35–2.00), having junior high school or below education level (aOR = 1.47, 95%CI = 1.13–1.91), having no access to health insurance (aOR = 1.27, 95%CI = 1.07–1.51), and being positive for Neisseria gonorrhoeae (NG, aOR = 4.49, 95%CI = 3.25–6.21) were significantly associated with CT infection.ConclusionWe found that CT infection is prevalent among patients seeking clinic-based STI services in Southern China. Targeted interventions could be implemented for patients with a higher risk of CT infection including those aged < 24, being unmarried, having junior high school or below education level, having no access to health insurance, and being positive for NG. In addition, routine CT screening could be considered a public health strategy by the government.

ObjectiveThis study aimed to perform a cluster analysis of symptoms linked with Neisseria gonorrhoeae (NG) and Chlamydia trachomatis (CT) and to identify which cluster of symptoms was associated with a higher risk of NG and CT.Study designFrom 15 April to 16 May 2018, a cross-sectional study was conducted, and patients attending sexually transmitted infections (STI) related clinics were recruited from 22 medical institutions in six districts of Shenzhen city.MethodsA structured questionnaire was used to collect social-demographic information as well as STI symptoms, and urine samples were collected for nucleic acid detection. Cluster analysis and logistic regression were applied.ResultsAmong 8,207 participants, the prevalence of CT and NG infection was 9.04% (742/8,207) and 2.36% (194/8,207), respectively. Among male outpatients, four clusters with distinct symptomatic patterns were identified. Unmarried, having casual sexual partners in the past 6 months, cluster 2 (OR = 6.70, 95% CI = 3.36–13.35) and cluster 4 (OR = 24.53, 95% CI = 12.96–46.44) were risk factors associated with NG infection. Unmarried, cluster 2 (OR = 2.54, 95% CI = 1.83–3.53) and cluster 4 (OR = 3.31, 95% CI = 2.37–4.61) were risk factors associated with CT infection. Among female outpatients, five clusters with distinct symptomatic patterns were identified. Aged 24 years or below and cluster 3 (OR = 3.68, 95% CI = 1.61–8.39) were risk factors associated with NG infection. Aged 24 years or below, unmarried, having a high school/secondary technical school education, and having junior high school or below education were risk factors associated with CT infection.ConclusionThe cluster of symptoms integrated into risk assessment for CT and NG infections suggests a new strategy of symptomatic management. Healthcare providers in STI clinics and resource-limited places may use this strategy to identify more potential patients and deliver adequate, acceptable, and equitable STI care for outpatients with a high risk of STI.

BackgroundRectal Chlamydia trachomatis (CT) and Neisseria gonorrhoeae (NG) infections among men who have sex with men (MSM) have become an increasingly important concern. The study aimed to explore (1) the acceptability of rectal self-sampling for chlamydia and gonorrhea testing among MSM in non-clinical venues in Shenzhen city, China; (2) factors associated with the acceptability of rectal self-sampling; and (3) factors associated with rectal CT and NG infections, respectively.MethodsThis cross-sectional study was conducted in two non-clinical settings in Shenzhen, China, from April 2021 to October 2021. Mixed-effects logistic regression analysis was performed to explore the factors associated with acceptance of rectal self-collection for CT and NG testing.ResultsOf the 306 MSM who were offered to perform rectal self-sampling, 133 (43.46%) accepted, and 96.24% (128/133) of them successfully provided a valid rectal sample. The prevalence of urogenital CT and NG infections among 303 MSM was 4.29 and 0.66%, respectively. The prevalence of rectal CT and NG infections among 128 participants was 31.25 and 9.38%, respectively. Participants having been diagnosed with HIV infection showed a higher acceptance of rectal self-collection for CT and NG testing.ConclusionThis study reported that rectal self-sampling in non-clinical venues for CT and NG testing among MSM was barely acceptable and feasible in China. Most CT and NG infections would have been missed if urethral screening was offered alone, which implies that the CT and NG screening should be scaled up in the above setting. Integrating free CT tests into regular STI interventions for MSM could also be considered.

Objective: To explore a new artificial intelligence (AI)-aided method to assist the clinical diagnosis of femoral intertrochanteric fracture (FIF), and further compare the performance with human level to confirm the effect and feasibility of the AI algorithm.Methods: 700 X-rays of FIF were collected and labeled by two senior orthopedic physicians to set up the database, 643 for the training database and 57 for the test database. A Faster-RCNN algorithm was applied to be trained and detect the FIF on X-rays. The performance of the AI algorithm such as accuracy, sensitivity, miss diagnosis rate, specificity, misdiagnosis rate, and time consumption was calculated and compared with that of orthopedic attending physicians.Results: Compared with orthopedic attending physicians, the Faster-RCNN algorithm performed better in accuracy (0.88 vs. 0.84 ± 0.04), specificity (0.87 vs. 0.71 ± 0.08), misdiagnosis rate (0.13 vs. 0.29 ± 0.08), and time consumption (5 min vs. 18.20 ± 1.92 min). As for the sensitivity and missed diagnosis rate, there was no statistical difference between the AI and orthopedic attending physicians (0.89 vs. 0.87 ± 0.03 and 0.11 vs. 0.13 ± 0.03).Conclusion: The AI diagnostic algorithm is an available and effective method for the clinical diagnosis of FIF. It could serve as a satisfying clinical assistant for orthopedic physicians.

Aims: Poly (ADP-ribose) polymerase (PARP) inhibitor has been reported to attenuate inflammatory response in rat models of inflammation. This study was designed to investigate the effect of PARP signalling in osteoarthritis (OA) cartilage inflammatory response in an OA rat model. Methods: The OA model was established by anterior cruciate ligament transection with medial meniscectomy in Wistar rats. The poly (ADP-ribose) polymerase 1 (PARP-1) shRNA (short hairpin (sh)-PARP-1) and negative control shRNA (sh-NC) were delivered using a lentiviral vector and were intra-articularly injected into rats after surgery. The weight-bearing distribution of the hind limbs and the knee joint width were measured every two weeks. The expression levels of PARP-1, inducible nitric oxide synthase (iNOS), and cyclooxygenase-2 (COX-2) in cartilage were determined using real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR) and Western blot. The serum concentrations of inflammatory cytokines were detected using enzyme-linked immunosorbent assay (ELISA). Results: PARP-1 expression level significantly increased in the cartilage of the established OA rat model. sh-PARP-1 treatment suppressed PARP-1 levels, decreased the Δ Force (the difference between the weight on ipsilateral limb and contralateral limb) and the knee joint width, inhibited cartilage matrix catabolic enzymes, and ameliorated OA cartilage degradation and attenuated inflammatory response. Conclusion: PARP-1 inhibition attenuates OA cartilage inflammatory response in the OA rat model.

Nanoparticles have been found to possess unique advantages in many fields, especially in the field of cancer treatment. Herein, based on the unique physical and chemical properties of natural polysaccharides, the polysaccharide from the edible and medicinal fruits of Chaenomeles speciosa was prepared, and the complex nanoparticles constructed by combining C. speciosa polysaccharide with selenium have been successfully developed by a chemical method. Monodisperse spherical nanoparticles with the particle size of 80.5 nm were characterized by various methods, which exhibited ideal size distribution and prominent stability under physiological conditions and alkaline conditions. Cellular studies demonstrated the nanoparticles significantly inhibited the growth of MCF-7 cells with an IC50 value of 8.37 ± 0.97 μg/mL through inducing the apoptosis and arresting the cell circle at S phase. Moreover, the zebrafish assays confirmed the antitumor effects of the nanoparticles, which suppressed the proliferation and migration of tumor and blocked the angiogenesis of transgenic zebrafish. Collectively, the results suggested that the nanoparticles may be considered as a candidate agent to treat breast cancer.

Background & Aims: Sustained c-Jun N-terminal kinase (JNK) activation plays a major role in drug-induced liver injury (DILI). Stress-responsive microRNA-31 (miR-31) has been implicated in regulating different cellular damage, and JNK activation could induce miR-31 expression. However, the regulatory role of miR-31 in DILI has not been studied previously. We aimed to investigate whether miR-31 could ameliorate DILI and ascertain potential molecular mechanism. Methods: miR-31 gene knockout (31-KO) and wild-type C57BL/6J mice were used to construct an acetaminophen (APAP)-induced DILI model. Primary mouse hepatocytes, as well as alpha mouse liver 12 (AML-12) cell lines, were used for in vitro experiments. Argonaute 2–associated RNA immunoprecipitation combined with high-throughput sequencing were performed to identify specific targets of miR-31. Results: 31-KO mice showed a higher mortality rate, liver transaminase levels, and hepatic necrosis compared with those in wild-type mice after APAP-induced hepatotoxicity. The protective role of miR-31 on hepatocytes has been analyzed via constructing bone marrow chimeric mice. Mechanistically, we found that hepatic JNK phosphorylation increased significantly in 31-KO mice. This caused mitochondrial phosphorylated Src (p-Src) inactivation and more reactive oxygen species production, which directly amplifies hepatocyte necrotic cell death, while administration of JNK-specific inhibitor SP600125 could abrogate the differences. Moreover, bioinformatics analysis of RNA immunoprecipitation combined with high-throughput sequencing identified that guanosine triphosphatase, cell division cycle protein 42 (Cdc42), the upstream molecule of JNK signaling, was the specific target of miR-31 and could form a miR-31/Cdc42/phosphorylated mixed-lineage kinase 3 (p-MLK3) negative feedback loop to restrict JNK overactivation. Clinically, both miR-31 and phosphorylated JNK (p-JNK) were highly increased in liver tissues of DILI patients with different etiologies. Conclusions: miR-31 can down-regulate Cdc42 to restrict overactivation of reactive oxygen species/JNK/mitochondria necrotic death loop in hepatocytes of APAP-induced DILI, which might provide a new therapeutic target for alleviating JNK overactivation–based liver injury.

Compounds with regulating glucose metabolism and improving insulin resistance (IR) activity are abundant in nature and can be obtained from several sources. They have high potential to be used to treat diabetes mellitus. These compounds isolated from natural plants can be classified seven categories: terpenoids, alkaloids, quinones, flavonoids, phenols, phenyl propanoids, steroids, and other types of compounds. They exert biological effects by different ways and mechanisms. This review illustrated the potential natural products as a rich resource in regulation of glucose metabolism and IR, as well as their mechanisms.

Abstract Background The nitrogen isotope natural abundance (δ15N) provides integrated information on ecosystem N dynamics, and carbon isotope natural abundance (δ13C) has been used to infer how water-using processes of plants change in terrestrial ecosystems. However, how δ13C and δ15N abundances in plant life and soils respond to N addition and water availability change is still unclear. Thus, δ13C and δ15N abundances in plant life and soils were used to investigate the effects of long-time (10 years) N addition (+ 50 kg N·ha− 1·yr− 1) and precipitation reduction (− 30% of throughfall) in forest C and N cycling traits in a temperate forest in northern China. Results We analyzed the δ13C and δ15N values of dominant plant foliage, litterfall, fungal sporophores, roots, and soils in the study. The results showed that δ15N values of foliage, litterfall, and surface soil layer’s (0–10 cm) total N were significantly increased by N addition, while δ15N values of fine roots and coarse roots were considerably decreased. Nitrogen addition also significantly increased the δ13C value of fine roots and total N concentration of the surface soil layer compared with the control. The C concentration, δ13C, and δ15N values of foliage and δ15N values of fine roots were significantly increased by precipitation reduction, while N concentration of foliage and litterfall significantly decreased. The combined effects of N addition and precipitation reduction significantly increased the δ13C and δ15N values of foliage as well as the δ15N values of fine roots and δ13C values of litterfall. Furthermore, foliar δ15N values were significantly correlated with foliage δ13C values, surface soil δ15N values, surface soil C concentration, and N concentrations. Nitrogen concentrations and δ13C values of foliage were significantly correlated with δ15N values and N concentrations of fine roots. Conclusions This indicates that plants increasingly take up the heavier 15N under N addition and the heavier 13C and 15N under precipitation reduction, suggesting that N addition and precipitation reduction may lead to more open forest ecosystem C and N cycling and affect plant nutrient acquisition strategies.

Abstract Background Salmonella is an important zoonotic pathogen, and chickens are one of its main hosts. Every year, Salmonella infections pose a serious threat to the poultry industry in developing countries, especially China. In this study, a total of 84 Salmonella isolates recovered from sick and healthy-looking chickens in central China were characterized by serotyping, MLST-based strain typing, presence of potential virulence factors, and antimicrobial resistance profiles. Result Data showed that the main serotypes of Salmonella isolates in central China were Salmonella enterica serovar Gallinarum biovar Pullorum, Salmonella enterica serovar Gallinarum biovar Gallinarum, Salmonella enterica serovar Enteritidis and Salmonella enterica serovar Typhimurium, and among them, S. Pullorum was the dominant type in both sick and healthy-looking chickens, accounting for 43.9 and 46.5%, respectively, while S. Enteritidis was only found in healthy-looking chickens. All isolates exhibited higher resistance rates to ampicillin (97.6%), tetracycline (58.3%) and colistin (51.2%), and among these isolates, 49.5% were resistant to more than three drugs in different combinations. S. Enteritidis was the most severe multidrug-resistant serotype, which showed higher resistance rates to colistin, meropenem and ciprofloxacin. Multilocus sequence typing (MLST) revealed that S. Gallinarum and S. Enteritidis isolates were clustered in clade 1, which belonged to two and one STs, respectively. All S. Typhimurium isolates were clustered in clade 3, and belonged to three STs. However, S. Pullorum were distributed in three clades, which belonged to 7 STs. Twenty-seven virulence-associated genes were detected, and expected cdtB, which was absent in all the isolates, the other 26 genes were conserved in the closely related Salmonella serogroup D (S. Enteritidis, S. Pullorum, and S. Gallinarum). Conclusion Salmonella serogroup D was the major subgroup, and S. Pullorum was the most common type in sick and healthy-looking chickens in central China. Drug resistance assays showed serious multiple antimicrobial resistances, and S. Enteritidis was the most severe drug-resistant serotype. MLST showed that there was correlation between serotypes and genotypes in most Salmonella isolates, except S. Pullorum, which showed complicated genetic diversity firstly. These results provide important epidemiological information for us to control Salmonella in chickens.

Currently there is tremendous interest in the discovery of natural polysaccharide immunomodulators for treating immune-related diseases. Herein, the immunomodulatory activities of a polysaccharide fraction isolated from blackberry seeds (BSP-2) were examined in RAW264.7 cells. The results revealed that BSP-2 at 37.5–300 µg/mL could significantly enhance the phagocytic activity of RAW264.7 cells and their ability to release NO, TNF-α and IL-6 cytokines. BSP-2 could significantly up-regulate the mRNA expression of iNOS, TNF-α and IL-6, as well as the phosphorylation of p65, p38, ERK and JNK proteins. The mechanisms underlying the immunomodulatory actions of BSP-2 likely involve the activation of the NF-κB and MAPK signaling pathways and up-regulation of the phosphorylation of key proteins involved in these pathways. These findings suggest that BSP-2 could be applied as a polysaccharide immunotherapeutic adjuvant with the effective dose as low as 70 µg/mL (BSP-2 may be cytotoxic at levels > 600 μg/mL). Highlights Immunostimulatory potential of a blackberry seed polysaccharide (BSP-2) was examined. BSP-2 at 37.5–300 µg/mL could enhance the phagocytic activity of RAW264.7 cells. BSP-2 could significantly up-regulate the mRNA expression of iNOS, TNF-α and IL-6. BSP-2 up-regulated the phosphorylation of p65, p38, ERK and JNK proteins. Immunostimulatory BSP-2 acted via activating the NF-κB and MAPK signalling pathways.

Isolated Rh atoms are supported on hydrophobic dB-ZSM-5. Single-atom Rh on dB-ZSM-5 is characterized with Ac-HAADF/STEM and CO adsorption FTIR. Direct conversion of methane to oxygenates is carried out in an autoclave in water charged with CH4, O2 and CO at 150 °C. Hydrophobic Rh-dB-ZSM-5 is compared with hydrophilic Rh-ZSM-5 (Si/Al = 15) for its catalytic performance. Rh-dB-ZSM-5 catalyst exhibits higher CH3OH selectivity and lower CH3COOH and CO2 selectivity. The catalytic activity of Rh-dB-ZSM-5 is much higher than the activity of Rh-ZSM-5 when the reaction is carried out under low pressure.

Objective: The aim of this study is to explore the potential of mixed reality (MR) technology in the visualization of orthopedic surgery.Methods: The visualization system with MR technology is widely used in orthopedic surgery. The system is composed of a 3D imaging workstation, a cloud platform, and an MR space station. An intelligent segmentation algorithm is adopted on the 3D imaging workstation to create a 3D anatomical model with zooming and rotation effects. This model is then exploited for efficient 3D reconstruction of data for computerized tomography (CT) and magnetic resonance imaging (MRI). Additionally, the model can be uploaded to the cloud platform for physical parameter tuning, model positioning, rendering and high-dimensional display. Using Microsoft’s HoloLens glasses in combination with the MR system, we project and view 3D holograms in real time under different clinical scenarios. After each procedure, nine surgeons completed a Likert-scale questionnaire on communication and understanding, spatial awareness and effectiveness of MR technology use. In addition to that, the National Aeronautics and Space Administration Task Load Index (NASA-TLX) is also used to evaluate the workload of MR hologram support.Results: 1) MR holograms can clearly show the 3D structures of bone fractures, which improves the understanding of different fracture types and the design of treatment plans; 2) Holograms with three-dimensional lifelike dynamic features provide an intuitive communication tool among doctors and also between doctors and patients; 3) During surgeries, a full lesion hologram can be obtained and blended in real time with a patient’s virtual 3D digital model in order to give surgeons superior visual guidance through novel high-dimensional “perspectives” of the surgical area; 4) Hologram-based magnetic navigation improves the accuracy and safety of the screw placement in orthopaedics surgeries; 5) The combination of mixed reality cloud platform and telemedicine system based on 5G provides a new technology platform for telesurgery collaboration. Results of qualitative study encourage the usage of MR technology for orthopaedics surgery. Analysis of the Likert-scale questionnaire shows that MR adds significant value to understanding and communication, spatial awareness, learning and effectiveness. Based on the NASA TLX-scale questionnaire results, mixed reality scored significantly lower under the “mental,” “temporal,” “performance,” and “frustration” categories compared to usual 2D.Conclusion: The integration of MR technology in orthopaedic surgery reduces the dependence on surgeons’ experience and provides personalized 3D visualization models for accurate diagnosis and treatment of orthopaedic abnormalities. This integration is clearly one of the prominent future development directions in medical surgery.

Intervertebral disc degeneration (IVDD) has been reported to be the most prevalent contributor to low back pain, posing a significant strain on the healthcare systems on a global scale. Currently, there are no approved therapies available for the prevention of the progressive degeneration of intervertebral disc (IVD); however, emerging regenerative strategies that aim to restore the normal structure of the disc have been fundamentally promising. In the last decade, mesenchymal stem cells (MSCs) have received a significant deal of interest for the treatment of IVDD due to their differentiation potential, immunoregulatory capabilities, and capability to be cultured and regulated in a favorable environment. Recent investigations show that the pleiotropic impacts of MSCs are regulated by the production of soluble paracrine factors. Exosomes play an important role in regulating such effects. In this review, we have summarized the current treatments for disc degenerative diseases and their limitations and highlighted the therapeutic role and its underlying mechanism of MSC-derived exosomes in IVDD, as well as the possible future developments for exosomes.

The resistance variant faults (RVFs) observed in the mine ventilation system can utterly restrict mine safety production. Herein, a machine learning model, which is based on multi-label k-nearest neighbor (ML-KNN), is proposed to solve the problem of the rapid and accurate diagnosis of the RVFs that occur at multiple locations within the mine ventilation system. The air volume that passes through all the branches of the ventilation network, including the residual branches, was used as the diagnostic model input after the occurrence of multiple faults, whereas the label vector of the fault locations was used as the model's output. In total, seven evaluation indicators and 1800 groups of randomly simulated faults at the typical locations in a production mine with 153 nodes and 223 branches were considered to evaluate the feasibility of the proposed model to solve for multiple fault locations diagnostic and verify the model's generalization ability. After ten-fold cross-validation of the training sets containing 1600 groups of fault instances, the diagnostic accuracy of the model tested with the air volume of all 223 branches and the 71 residual branches' air volume as input was 73.6% and 72.3%, respectively. On the other hand, To further evaluate the diagnostic performance of the model, 200 groups of the multiple fault instances that were not included in the training were tested. The accuracy of the fault location diagnosis was 76.5% and 73.5%, and the diagnostic time was 9.9s and 12.16s for the multiple faults instances with all 223 branches' air volume and the 71 residual branches' air volume as observation characteristics, respectively. The data show that the machine learning model based on ML-KNN shows good performance in the problem of resistance variant multiple fault locations diagnoses of the mine ventilation system, the multiple fault locations diagnoses can be carried out with all the branches' air volume or the residual branches' air volume as the input of the model, the diagnostic average accuracy is higher than 70%, and the average diagnosis time is less than one minute. Hence, the proposed model's diagnostic accuracy and speed can meet the engineering requirements for the diagnosis of multiple fault locations for a real ventilation system in the field, and this model can effectively replace personnel to discover ventilation system failures, and also lays a good foundation for the construction of intelligent ventilation systems.