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The primary purpose of this research is to examine the impact of climate change on maize production in Pakistan. This research studied the impact of climate change on maize production in Pakistan from 1990 to 2020 using the Auto Regressive Distributed Lag (ARDL) technique and draws implications for the future of Pakistan's sustainable agricultural industry. According to ARDL's short-run and long-run analyses, variables such as average temperature (AVEGTP), carbon dioxide (CO2), precipitation (PRPT), and tube well irrigation (TWL) all have a significant short-run and long-run impact on maize yield at the 1 %, 5 %, and 10 % significance levels. The estimated findings were also affirmed through FMOLS and DOLS. The study's key findings indicated that variables such as average temperature, carbon dioxide, precipitation, and tube well irrigation had significant short-run and long-run impacts on maize yield. Climate change's impacts on maize yield underline the crucial need for action to address this global issue and ensure agriculture's future. A recent study has emphasized the significant impact of climate change on Pakistan's maize production, stressing the importance of addressing this global issue for food security. The study recommends selecting crop varieties and managing fertilizer applications based on projected climate change to mitigate the impending crisis. Policymakers can use the study's findings as valuable insights to formulate effective policies that ensure the resilience and sustainability of Pakistan's agricultural industry.

Background: Gastric cancer (GC) develops from gastric precancerous lesions (GPL), and early diagnosis and treatment at the premalignant stage may achieve a higher benefit‒cost ratio with a reduced necessity for surgery. However, reliable noninvasive screening biomarkers of GPL are currently lacking. Methods: The marker genes of GPL encoding extracellular proteins were identified by bioinformatics analysis and further verified by immunofluorescence and immunohistochemistry assays. Serum samples were collected to measure the levels of SERPINB5, the diagnostic efficacy of which was assessed by the area under the receiver operating characteristic (ROC) curve (AUC). Finally, the effect of SERPINB5 on the phenotypic conversion of macrophages was verified by public data and in vitro experiments. Results: SERPINB5 was identified as an extracellular biomarker of GPL that had good diagnostic efficacy. High expression of SERPINB5 was observed in the epithelial cells and adjacent extracellular matrix on sections of gastric high-grade intraepithelial neoplasia (HGIN). Importantly, SERPINB5 determined in serum was significantly increased in the HGIN group, and the AUC for discriminating between HGIN and chronic gastritis or low-grade intraepithelial neoplasia was 0.9936 and 0.9750, respectively. Moreover, SERPINB5 expression was positively correlated with macrophage infiltration, and M1 marker NOS2 expression, but negatively correlated with M2 marker CSF1R expression. In THP-1-derived macrophages, SERPINB5 upregulated expression of M1-related cytokines TNF-α and IL-12, and M1 marker CD86, but suppressed production of M2-related cytokines TGF-β and IL-10. Conclusions: Our study provides evidence that SERPINB5 may serve as a promising noninvasive serum biomarker for gastric HGIN screening and regulate macrophage phenotype conversion.

ObjectiveThis investigation sought to elucidate the potential correlation between a recently characterized adiposity metric, termed the Weight-Adjusted-Waist Index (WWI) and hyperuricemia.MethodsA cross-sectional design was employed in this study, featuring both hyperuricemic and non-hyperuricemic subjects with complete WWI data, sourced from the National Health and Nutrition Examination Survey (NHANES) spanning 2017 to March 2020. WWI was calculated utilizing the formula which involves the division of waist circumference (WC) by the square root of the body weight. In order to determine the relationship between WWI and hyperuricemia, both univariate and multivariate logistic regression models, appropriately weighted, were employed in the analysis. The linearity of relationships was validated using smooth curve fitting. Additionally, subgroup evaluations and interaction assessments were conducted.ResultsThe study sample comprised 7437 subjects, yielding a hyperuricemia prevalence of 18.22%. Stratifying WWI into tertiles, a progressive rise in hyperuricemia prevalence was evident with increasing WWI (Tertile 1: 11.62%, Tertile 2: 17.91%, Tertile 3: 25.13%). The odds ratio (OR) demonstrated that individuals within the highest WWI tertile were significantly more prone to hyperuricemia than those in the lowest tertile (OR = 2.41, 95% CI: 1.88-3.08).ConclusionThis study provides evidence that an elevated WWI is correlated with an increased risk of hyperuricemia in the adult population of the United States. These results suggest that WWI may serve as a viable anthropometric indicator for predicting hyperuricemia.

BackgroundGlucose metabolism (GM) plays a crucial role in cancer cell proliferation, tumor growth, and survival. However, the identification of glucose metabolism-related genes (GMRGs) for effective prediction of prognosis in head and neck squamous cell carcinoma (HNSC) is still lacking.MethodsWe conducted differential analysis between HNSC and Normal groups to identify differentially expressed genes (DEGs). Key module genes were obtained using weighted gene co-expression network analysis (WGCNA). Intersection analysis of DEGs, GMRGs, and key module genes identified GMRG-DEGs. Univariate and multivariate Cox regression analyses were performed to screen prognostic-associated genes. Independent prognostic analysis of clinical traits and risk scores was implemented using Cox regression. Gene set enrichment analysis (GSEA) was used to explore functional pathways and genes between high- and low-risk groups. Immune infiltration analysis compared immune cells between the two groups in HNSC samples. Drug prediction was performed using the Genomics of Drug Sensitivity in Cancer (GDSC) database. Quantitative real-time fluorescence PCR (qRT-PCR) validated the expression levels of prognosis-related genes in HNSC patients.ResultsWe identified 4973 DEGs between HNSC and Normal samples. Key gene modules, represented by black and brown module genes, were identified. Intersection analysis revealed 76 GMRG-DEGs. Five prognosis-related genes (MTHFD2, CDKN2A, TPM2, MPZ, and DNMT1) were identified. A nomogram incorporating age, lymph node status (N), and risk score was constructed for survival prediction in HNSC patients. Immune infiltration analysis showed significant differences in five immune cell types (Macrophages M0, memory B cells, Monocytes, Macrophages M2, and Dendritic resting cells) between the high- and low-risk groups. GDSC database analysis identified 53 drugs with remarkable differences between the groups, including A.443654 and AG.014699. DNMT1 and MTHFD2 were up-regulated, while MPZ was down-regulated in HNSC.ConclusionOur study highlights the significant association of five prognosis-related genes (MTHFD2, CDKN2A, TPM2, MPZ, and DNMT1) with HNSC. These findings provide further evidence of the crucial role of GMRGs in HNSC.

Leukemia cells prevent immune system from clearing tumor cells by inducing the immunosuppression of the bone marrow (BM) microenvironment. In recent years, further understanding of the BM microenvironment and immune landscape of leukemia has resulted in the introduction of several immunotherapies, including checkpoint inhibitors, T-cell engager, antibody drug conjugates, and cellular therapies in clinical trials. Among them, the programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1) axis is a significant checkpoint for controlling immune responses, the PD-1 receptor on tumor-infiltrating T cells is bound by PD-L1 on leukemia cells. Consequently, the activation of tumor reactive T cells is inhibited and their apoptosis is promoted, preventing the rejection of the tumor by immune system and thus resulting in the occurrence of immune tolerance. The PD-1/PD-L1 axis serves as a significant mechanism by which tumor cells evade immune surveillance, and PD-1/PD-L1 checkpoint inhibitors have been approved for the treatment of lymphomas and varieties of solid tumors. However, the development of drugs targeting PD-1/PD-L1 in leukemia remains in the clinical-trial stage. In this review, we tally up the basic research and clinical trials on PD-1/PD-L1 inhibitors in leukemia, as well as discuss the relevant toxicity and impacts of PD-1/PD-L1 on other immunotherapies such as hematopoietic stem cell transplantation, bi-specific T-cell engager, chimeric antigen receptor T-cell immunotherapy.

Abstract Bacteria often use multiple transcription factors to regulate specific biological processes. Biosynthesis of heat-stable antifungal factor (HSAF) is regulated by multiple factors in Lysobacter enzymogenes. However, the mechanism of HSAF biosynthesis regulation remains largely unknown. In this study, we screened a potential HSAF biosynthesis regulator, RecX, by a DNA pull-down assay. Deletion of recX resulted in a significant increase in the production of HSAF, and overexpression of recX significantly suppressed HSAF production. Importantly, our results showe that RecX directly binds to the promoter region of the lafB gene to inhibit its transcription and thus decreases HSAF production in L. enzymogenes. These findings reveal the novel mechanism of RecX regulation of antifungal antibiotic production in L. enzymogenes.

Probability of arc re-strike increases with the increment of break voltage, especially in an arc chamber of DC bridge-type contacts equipped with permanent magnets. Among all types of arc re-strikes, the most dangerous one is that part of the arc re-enters the contact gap, which is defined as swirl re-strike in this paper. In this paper, the arc images and arc voltage waveforms were analyzed, and the typical features of arc re-strike were identified. In addition, the probability of arc swirl re-strike when the supply voltages range from 270 V to 730 V and the magnetic flux densities ranges from 30 mT to 70 mT were revealed. Mechanism of the swirl re-strike is explained and it is due to the randomness of positions of both the arc igniting and the arc-root transferring on stationary contacts, as well as the non-uniformly distributed magnetic field in the arcing region. Finally, measures to prevent arc re-strike were proposed, and their effectiveness on eliminating re-strike were verified at the voltage range of up to 730V and magnetic flux. Occurrence probability of arc re-strike drops from unity to 13% at 730 V.

Cu2O-based photocathodes for photoelectrochemical water reduction suffer severe self-photo-corrosion issue. Here the authors report an in-situ encapsulation strategy with hydrogen-substituted graphdiyne to protect Cu2O for water reduction with a photocurrent density of −12.88 mA cm-2.

Strawberries are an important and high-value crop in the United States. The total value of strawberry production in the United States was $3.42 billion in 2021. However, a major pest of strawberries, two-spotted spider mites (TSSM) (Tetranychus urticae Koch), can cause severe economic losses due to mites feeding on chlorophyll which interferes with photosynthesis. Predatory mites (Neoseiulus californicus and Phytoseiulus persimilis) can control TSSM populations and provide an alternative to conventional pesticides. Predatory mites are more friendly to the environment than pesticides. To monitor TSSM and predatory mite populations in the field, frequent sampling is required. However, manual counting of mites using a hand lens is challenging for a large field. Therefore, this study applied deep learning models to detect TSSM and predatory mites in strawberries from smartphone images. Three different smartphones (Motorola Moto E5 Play, OnePlus A5000, and iPhone XR) and a 25x macro lens were used to collect a total of 3,013 images, including 1,779 TSSM images and 1,234 predatory mite images. TSSM images were collected by the three smartphones, and only the OnePlus A5000 and iPhone XR were used to collect predatory mite images that only contained predatory mites or contained both predatory mites and TSSM in the same image. TSSM images were used to compare two deep learning models (YOLOv4 and Faster R-CNN Resnet50) and three different smartphone cameras. This study found that the average detection accuracy of YOLOv4 and Faster R-CNN was 0.935 and 0.863, respectively. Deep learning models achieved the best detection accuracy on the image collected by iPhone XR. The YOLOv4 model was trained to compare the detection performance of three different input image sizes (160 × 160, 320 × 320, 640 × 640 pixels) for TSSM and predatory mite detection. This study found that the mean average precision of the YOLOv4 increased as the image size increased, and the model trained with an image size of 640 × 640 pixels achieved the detection accuracy of 0.933 for TSSM and predatory mites. This study also found that the YOLOv4 could detect pests under different field illumination conditions. The smartphone image-based method can detect the TSSM and predatory mites quickly from images and with high detection accuracy, which can help growers use less time to monitor mite populations in the field.

Recently, wearable sensors for human motion posture and medical diagnosis have received widespread attention. However, most wearable sensors rely on a power supply, and their preparation technology still faces limitations. Here, we used eyebrow powder to fabricate a triboelectric nanogenerator (E-TENG) for bio-mechanical energy harvesting and gait monitoring of patients with osteoarthritis. Under a maximum separation distance (5 mm) and a maximum motion frequency (6 Hz), the E-TENG device can attain a open-circuit voltage (Voc) of 169 V and a short-circuit current (Isc) of 5.5 µA. Meanwhile, the maximum output power of the E-TENG can arrive at 175 µW (load resistance: 20 MΩ). The E-TENG can detect human gait patterns (walking, running, and jumping), finger motion, and elbow joint movements. Further research has shown that the E-TENG can be used for gait recognition and monitoring in patients with osteoarthritis, providing reference data for osteoarthritis prevention and treatment. This research can promote the application of TENG devices based on cosmetic materials in medical diagnosis and adjuvant treatment.

ObjectiveBreast cancer is a prevalent malignancy that predominantly affects women. The development and progression of this disease are strongly influenced by the tumor microenvironment and immune infiltration. Therefore, investigating immune-related genes associated with breast cancer prognosis is a crucial approach to enhance the diagnosis and treatment of breast cancer.MethodsWe analyzed data from the TCGA database to determine the proportion of invasive immune cells, immune components, and matrix components in breast cancer patients. Using this data, we constructed a risk prediction model to predict breast cancer prognosis and evaluated the correlation between KLRB1 expression and clinicopathological features and immune invasion. Additionally, we investigated the role of KLRB1 in breast cancer using various experimental techniques including real-time quantitative PCR, MTT assays, Transwell assays, Wound healing assays, EdU assays, and flow cytometry.ResultsThe functional enrichment analysis of immune and stromal components in breast cancer revealed that T cell activation, differentiation, and regulation, as well as lymphocyte differentiation and regulation, play critical roles in determining the status of the tumor microenvironment. These DEGs are therefore considered key factors affecting TME status. Additionally, immune-related gene risk models were constructed and found to be effective predictors of breast cancer prognosis. Further analysis through KM survival analysis and univariate and multivariate Cox regression analysis demonstrated that KLRB1 is an independent prognostic factor for breast cancer. KLRB1 is closely associated with immunoinfiltrating cells. Finally, in vitro experiments confirmed that overexpression of KLRB1 inhibits breast cancer cell proliferation, migration, invasion, and DNA replication ability. KLRB1 was also found to inhibit the proliferation of breast cancer cells by blocking cell division in the G1/M phase.ConclusionKLRB1 may be a potential prognostic marker and therapeutic target associated with the microenzymic environment of breast cancer tumors, providing a new direction for breast cancer treatment.

Design basis accidents are investigated continuously for the European DEMO reactor accompanying its development. One selected postulated initial event (PIE) is a loss of vacuum (LOVA) in vacuum vessel (VV) with large ingress of air induced by rupture in a VV penetration. It has been investigated for the helium cooled pebble bed (HCPB) blanket concept according to the DEMO baseline 2017. The associated primary heat transfer system (PHTS) and the related systems in the tokamak building, from the VV to the PHTS vault and galleries, are considered for the investigation. The LOVA is postulated to occur at a port seal of the electron cyclotron equatorial port plug on the side of the closure plate with (i) a small leak of 1.0 × 10 ^−3 m ^2 , or (ii) a large break size of 1.0 × 10 ^−2 m ^2 . Air ingress from one port cell into the VV leads to the VV pressurization and the fusion power termination followed by an unmitigated plasma disruption. A loss of off-site power for 32 h is assumed to coincide with the disruption. An in-vessel loss of coolant accident (LOCA) is considered as a consequence if the affected first wall (FW) reaches the defined temperature of 1000 °C. The radioactive inventories in the VV (tritium, W-dust) can mobilize towards the VVPSS, the affected systems in the building and the environment due to pressurization, venting and leak conditions. MELCOR 1.8.6 for fusion is applied for this deterministic safety analysis. The resulting releases of radioactivity to the environment are then provided for dose calculation using the computer systems UFOTRI and COSYMA. Outcomes of this LOVA analysis are critically discussed: the transient evolutions of different cases are compared; hydrogen production is detected in case of aggravating FW failure; the source terms (tritium, W-dust) are transported to the connected systems; and the dose results from the environmental releases are provided.

To investigate the susceptibility of drifting snow along the Ya’an–Qamdo section of the railway, which is located in a high-altitude and cold plateau in Southwest China with scarce meteorological information, the Weather Research and Forecasting Model (WRF) is used in this paper to simulate the spatio-temporal distribution of meteorological data. According to the varying terrain, the railway section from Ya’an to Qamdo is divided into two regions along 100.8° E for double-layer nested simulation. The original land use data of the WRF model are used in region 1. Due to the increased number of mountains in region 2, the original data are replaced by the MCD12Q1v006 land use data, and the vertical direction layers are densified near the ground to increase simulation accuracy. The simulated results are compared with the observation data. It is found that after densification, the results have been significantly improved. The results obtained by the WRF model can accurately simulate the change trends of temperature, rainfall, and wind speed, and the correlation coefficients are relatively high, which verifies the accuracy of WRF for simulating complex terrain regions. The simulation results further indicate that approximately 300 km of the Ya’an–Qamdo railway may experience drifting snow. Among them, no drifting snow events occur in Ya’an County, and the areas with higher probability are located at the border between Luding County and Tianquan County, followed by Kangding area. The remaining areas have a probability of less than 10%. The WRF model demonstrates its capability in the drifting snow protection of railways with limited meteorological data.

Three new compounds (1, 11, and 12), together with 32 known ones, were isolated from the root bark of Morus alba L. using various chromatographic methods. The structures of the undescribed compounds were elucidated based on 1D, 2D NMR, and HRESIMS dataanalysis, while the known ones were identified by comparison of their spectroscopic data with those reported in the literature. All the isolates were evaluated for their cytotoxic activities against human gastric cancer HGC27 cells by CCK-8 assay. Among them, compounds 5, 8, 10, and 30 exhibited cytotoxic activities on HGC27 cells with IC50 values of 33.76 ± 2.64 μM, 28.94 ± 0.72 μM, 6.08 ± 0.34 μM, and 10.24 ± 0.89 μM, respectively. Furthermore, compound 10 was confirmed to reduce proliferation ability, increase apoptosis rate, and inhibit cell migration pathway by annexin V/PI double staining experiment, transwell experiment, and Western blot analysis.

Wind fields provide direct power for exchanging energy and matter in the atmosphere. All-fiber coherent Doppler lidar is a powerful tool for detecting boundary-layer wind fields. According to the characteristics of the lidar echo signal, an adaptive noise-reduction peak retrieval (ANRPR) algorithm is proposed in this study. Firstly, the power spectrum data are divided into several continuous range gates according to the time series. Then, the adaptive iterative reweighted penalized least-squares (airPLS) method is used to reduce the background noise. Secondly, the continuity between spectra is enhanced by 2D Gaussian low-pass filtering. Finally, an adaptive peak-retrieval algorithm is employed to extract the Doppler shift, facilitating the synthesis of a spatial atmospheric 3D wind field through the vector synthesis method. When comparing data from different heights of the meteorological gradient tower, both the horizontal wind-speed correlation and the horizontal wind-direction correlation exceed 0.90. Experimental results show that the proposed algorithm has better robustness and a longer detection distance than the traditional algorithm.

Abstract Deinococcus wulumuqiensis R12, which was isolated from arid irradiated soil in Xinjiang province of China, belongs to a genus that is well-known for its extreme resistance to ionizing radiation and oxidative stress. The DNA-binding protein Dps has been studied for its great contribution to oxidative resistance. To explore the role of Dps in D. wulumuqiensis R12, the Dps sequence and homology-modeled structure were analyzed. In addition, the dps gene was knocked out and proteomics was used to verify the functions of Dps in D. wulumuqiensis R12. Docking data and DNA binding experiments in vitro showed that the R12 Dps protein has a better DNA binding ability than the Dps1 protein from D. radiodurans R1. When the dps gene was deleted in D. wulumuqiensis R12, its resistance to H2O2 and UV rays was greatly reduced, and the cell envelope was destroyed by H2O2 treatment. Additionally, the qRT-PCR and proteomics data suggested that when the dps gene was deleted, the catalase gene was significantly down-regulated. The proteomics data indicated that the metabolism, transport and oxidation–reduction processes of D. wulumuqiensis R12 were down-regulated after the deletion of the dps gene. Overall, the data conformed that Dps protein plays an important role in D. wulumuqiensis R12.

Abstract Background The recurrence of bile duct stones is a long‐term outcome for patients undergoing laparoscopic common bile duct exploration (LCBDE) that is worthy of attention. This study aimed to investigate long‐term risk factors for stones recurrence after LCBDE and develop a nomogram for predicting the risk. Methods The clinical data on consecutive patients with bile duct stones undergoing LCBDE at Shanghai Tenth People's Hospital between January 2014 and February 2019 with a follow‐up period longer than 2 years were reviewed. Independent risk factors of stones recurrence identified by the Cox regression model were used to develop a nomogram in predicting stones recurrence after LCBDE. Results Eight hundred and twenty‐two patients were eventually included in this study. Of these patients, 42 (5.11%) developed stones recurrence. The cumulative incidences of stones recurrence at 1, 3, and 5 years after LCBDE were 1.34%, 4.36%, and 7.14%, respectively. Independent risk factors of stones recurrence were identified to be age (HR = 1.04, 95% CI = 1.02‐1.07), T‐tube drainage (HR = 3.28, 95% CI = 1.23‐8.72), fatty liver (HR = 2.69, 95% CI = 1.39‐5.20), urinary calculus (HR = 4.68, 95% CI = 2.29‐9.56), post‐cholecystectomy (HR = 5.21, 95% CI = 2.39‐11.33), and post‐ERCP + EST (HR = 2.87, 95% CI = 1.18‐6.96). By these factors, a developed nomogram showed a C‐index of 0.770 to predict stones recurrence. Conclusions The nomogram, based on identified risk factors, showed good accuracy for predicting stones recurrence, which is valuable to guide these patients’ follow‐up and prevention.

IntroductionVaccination rates for the COVID-19 vaccine have recently been stagnant worldwide. We aim to analyze the potential patterns of vaccination development from the first three doses to reveal the possible trends of the next round of vaccination and further explore the factors influencing vaccination in the selected populations.MethodsOn July 2022, a stratified multistage random sampling method in the survey was conducted to select 6,781 people from 4 provinces China, who were above the age of 18 years. Participants were divided into two groups based on whether they had a chronic disease. The data were run through Cochran-Armitage trend test and multivariable regression analyses.ResultsA total of 957 participants with chronic disease and 5,454 participants without chronic disease were included in this survey. Vaccination rates for the first, second and booster doses in chronic disease population were93.70% (95% CI: 92.19–95.27%), 91.12% (95%CI: 94.43–95.59%), and 83.18% (95%CI: 80.80–85.55%) respectively. By contrast, the first, second and booster vaccination rates for the general population were 98.02% (95% CI: 97.65–98.39%), 95.01% (95% CI: 94.43–95.59%) and 85.06% (95% CI: 84.11–86.00%) respectively. The widening gap in vaccination rates was observed as the number of vaccinations increases. Higher self-efficacy was a significant factor in promoting vaccination, which has been observed in all doses of vaccines. Higher education level, middle level physical activity and higher public prevention measures play a positive role in vaccination among the general population, while alcohol consumption acts as a significant positive factor in the chronic disease population (p

Motivated by the carbon neutrality target, strategic planning for a low-carbon transition of sludge treatment and disposal in China is challenging due to the unpredictability of technical, regional, socioeconomic, and political factors affecting greenhouse gas (GHG) emissions. This study combines the use of a Life Cycle Assessment and the Patient Rule Induction Method, accounting for possibilities that could achieve net-zero carbon emissions by exploring multiple plausible future profiles of sludge treatment and disposal. Results show that reducing sludge landfill and increasing anaerobic digestion are effective methods to facilitate GHG reduction. Achieving carbon neutrality is closely linked to developing a cleaner electricity mix. Based on a cascaded scenario analysis considering regional differences for 31 Chinese provinces, results demonstrated a maximum cumulative reduction potential of 371 Mt CO2 equivalents from 2020 to 2050, equal to 59.84% of the business-as-usual scenario. Together with GHG reductions, terrestrial acidification and ecotoxicity as well as freshwater ecotoxicity are synergistically reduced. However, the shifting environmental burden results in freshwater eutrophication, human toxicity, marine ecotoxicity, marine eutrophication, and photochemical oxidant formation. This study presents a novel method for systematically identifying possible future development paths toward carbon neutrality. The findings may support policy designs for achieving target carbon reduction effects for sludge disposal.

Cortical neural dynamics mediate information processing for the cerebral cortex, which is implicated in fundamental biological processes such as vision and olfaction, in addition to neurological and psychiatric diseases. Spontaneous pain is a key feature of human neuropathic pain. Whether spontaneous pain pushes the cortical network into an aberrant state and, if so, whether it can be brought back to a “normal” operating range to ameliorate pain are unknown. Using a clinically relevant mouse model of neuropathic pain with spontaneous pain–like behavior, we report that orofacial spontaneous pain activated a specific area within the primary somatosensory cortex (S1), displaying synchronized neural dynamics revealed by intravital two-photon calcium imaging. This synchronization was underpinned by local GABAergic interneuron hypoactivity. Pain-induced cortical synchronization could be attenuated by manipulating local S1 networks or clinically effective pain therapies. Specifically, both chemogenetic inhibition of pain-related c-Fos–expressing neurons and selective activation of GABAergic interneurons significantly attenuated S1 synchronization. Clinically effective pain therapies including carbamazepine and nerve root decompression could also dampen S1 synchronization. More important, restoring a “normal” range of neural dynamics through attenuation of pain-induced S1 synchronization alleviated pain-like behavior. These results suggest that spontaneous pain pushed the S1 regional network into a synchronized state, whereas reversal of this synchronization alleviated pain.

Cold environmental conditions may often lead to the early flowering of plants, and the mechanism by cold-induced flowering remains poorly understood. Microscopy analysis in this study demonstrated that cold conditioning led to early flower bud differentiation in two tobacco strains and an Agilent Tobacco Gene Expression microarray was adapted for transcriptomic analysis on the stem tips of cold treated tobacco to gain insight into the molecular process underlying flowering in tobacco. The transcriptomic analysis showed that cold treatment of two flue-cured tobacco varieties (Xingyan 1 and YunYan 85) yielded 4176 and 5773 genes that were differentially expressed, respectively, with 2623 being commonly detected. Functional distribution revealed that the differentially expressed genes (DEGs) were mainly enriched in protein metabolism, RNA, stress, transport, and secondary metabolism. Genes involved in secondary metabolism, cell wall, and redox were nearly all up-regulated in response to the cold conditioning. Further analysis demonstrated that the central genes related to brassinosteroid biosynthetic pathway, circadian system, and flowering pathway were significantly enhanced in the cold treated tobacco. Phytochemical measurement and qRT-PCR revealed an increased accumulation of brassinolide and a decreased expression of the flowering locus c gene. Furthermore, we found that overexpression of NtBRI1 could induce early flowering in tobacco under normal condition. And low-temperature-induced early flowering in NtBRI1 overexpression plants were similar to that of normal condition. Consistently, low-temperature-induced early flowering is partially suppressed in NtBRI1 mutant. Together, the results suggest that cold could induce early flowering of tobacco by activating brassinosteroid signaling.

BackgroundIt is reported that insulin resistance widely exists in non-diabetic patients with a recent history of transient ischemic attack (TIA) or ischemic stroke. There is currently strong evidence to prove the bidirectional effect of glucose metabolism disorders and stroke events. Therefore, it is necessary to retrospectively tease out the current status, hotspots, and frontiers of insulin resistance and ischemic cerebrovascular disease through CiteSpace.Materials and methodsWe searched the Web of Science (WOS) for studies related to insulin resistance and ischemic cerebrovascular disease from 1999 to April 2022, then downloaded the data into CiteSpace to generate a knowledge visualization map.ResultsA total of 1,500 publications relevant to insulin resistance and ischemic cerebrovascular disease were retrieved. The USA had the most articles on this topic, followed by PEOPLES R CHINA and JAPAN. WALTER N KERNAN was the most prolific author, whose research mainly focused on insulin resistance intervention after stroke (IRIS) trial. The most common keywords were myocardial ischemia, metabolic syndrome, ischemic stroke, cerebral ischemia, association, oxidative stress, inflammation, and adipose tissue. Major ongoing research trends include three aspects: (1) the association between insulin resistance and ischemic cerebrovascular disease in non-diabetic patients, (2) the intrinsic pathological mechanism between insulin resistance and ischemic cerebrovascular disease, and (3) early intervention of insulin resistance to improve the prognosis of stroke.ConclusionThe results of this bibliometric study provide the current status and trends of clinical research publications in the field of insulin resistance and ischemic cerebrovascular disease. Insulin resistance is strongly associated with the occurrence of ischemic stroke, early neurological deterioration in stroke patients, post-stroke depression, and cerebral small vessel disease. Early treatment of insulin resistance can be an effective way to prevent the onset of ischemic stroke and improve stroke prognosis. This study may help researchers to identify hot topics and explore new research directions.

Abstract Mitophagy plays a vital role in the maintenance of mitochondrial homeostasis and tumorigenesis. Noncoding RNA piR-823 contributes to colorectal tumorigenesis. In this study, we aim to evaluate piR-823-mediated mitophagy and its mechanistic association with colorectal cancer (CRC). Digital gene expression analysis was performed to explore the potential functions of piR-823. A piR-823 antagomir (Ant-823) was used to inhibit piR-823 expression, and piR-823 mimics (mimics-823) were used to increase piR-823 expression. Mitophagy was measured in vivo and in vitro by immunofluorescence and western blot analysis. JC-1 staining, ATP production, real-time PCR, and western blot analysis were used to measure changes in mitochondrial quality and number. siRNA transfection was used to inhibit mitophagy, and CCCP was used to induce mitophagy. RNA pull-down assays and RNA-binding protein immunoprecipitation assays were conducted to investigate the molecular mechanisms. Here, we found that CRC cells transfected with Ant-823 presented an altered expression of autophagic and mitophagy genes by Digital gene expression analysis. Ant-823 could promote Parkin activation and mitophagy in vitro and in vivo, followed by mitochondrial loss and dysfunction of some mitochondria, whereas mimics-823 exerted the opposite effects in CRC cells. The inhibition of mitophagy by siParkin alleviated Ant-823-induced mitochondrial loss and dysfunction, as well as apoptosis to a certain extent. Furthermore, piR-823 was found to interact with PINK1 and promote its ubiquitination and proteasome-dependent degradation, thus alleviating mitophagy. Finally, these findings were verifed in samples obtained by patients affected by colorectal cancer. In conclusion, we identify a novel mechanism by which piR-823 regulates mitophagy during CRC tumorigenesis by increasing PINK1 degradation.

Abstract Colon cancer (CC) is a disease with high incidence and mortality rate. The interaction between epithelial-mesenchymal transition (EMT) and immune status has important clinical significance. We aim to identify EMT-immune-related prognostic biomarkers in colon cancer. The GEO2R and GEPIA 2.0 were utilized to calculate the differential expression genes between CC and normal mucosa. Immport, InnateDB and EMTome databases were used to define EMT-immune-related genes. We conducted batch prognostic analysis by TCGA data. The expression patterns were verified by multiple datasets and lab experiments. GEPIA 2.0 and TIMER 2.0 were utilized to analyze the correlation of the hub genes with EMT markers and immune infiltration. GeneMANIA, STRING, and Metascape were used for co-expression and pathway enrichment analysis. Finally, we established a signature by the method of multivariate Cox regression analysis. CDKN2A, CMTM8 and ILK were filtered out as prognostic genes. CDKN2A and CMTM8 were up-regulated, while ILK was down-regulated in CC. CDKN2A was positively correlated with infiltration of macrophages, Th2 cells, Treg cells, and negatively correlated with NK cells. CMTM8 was negatively correlated with CD8+ T cells, dendritic cells, and NK cells. ILK was positively correlated with CD8+ T cells and dendritic cells. Moreover, CDKN2A, CMTM8 and ILK were significantly correlated with EMT markers. The three genes could participate in the TGF-β pathway. The prognosis model established by the three hub genes was an independent prognosis factor, which can better predict the prognosis. CDKN2A, CMTM8 and ILK are promising prognostic biomarkers and may be potential therapeutic targets in colon cancer.

Keypoints Clarified small molecular metabolites of C. fumosorosea for the first time. Identified three novel compounds with antimicrobial or antiaging activities. The fungus has development potentiality for rich in bioactive metabolites.

Gastrodia elata (G. elata) Blume is widely used as a health product with significant economic, medicinal, and ecological values. Due to variations in the geographical origin, soil pH, and content of organic matter, the levels of physiologically active ingredient contents in G. elata from different origins may vary. Therefore, rapid methods for predicting the geographical origin and the contents of these ingredients are important for the market. This paper proposes a visible–near-infrared (Vis-NIR) spectroscopy technology combined with machine learning. A variety of machine learning models were benchmarked against a one-dimensional convolutional neural network (1D-CNN) in terms of accuracy. In the origin identification models, the 1D-CNN demonstrated excellent performance, with the F1 score being 1.0000, correctly identifying the 11 origins. In the quantitative models, the 1D-CNN outperformed the other three algorithms. For the prediction set of eight physiologically active ingredients, namely, GA, HA, PE, PB, PC, PA, GA + HA, and total, the RMSEP values were 0.2881, 0.0871, 0.3387, 0.2485, 0.0761, 0.7027, 0.3664, and 1.2965, respectively. The Rp2 values were 0.9278, 0.9321, 0.9433, 0.9094, 0.9454, 0.9282, 0.9173, and 0.9323, respectively. This study demonstrated that the 1D-CNN showed highly accurate non-linear descriptive capability. The proposed combinations of Vis-NIR spectroscopy with 1D-CNN models have significant potential in the quality evaluation of G. elata.

The prevalence of schistosomiasis japonica in China is now characterized by a low epidemic rate and low-intensity infections. Some diagnostic methods with high sensitivity and specificity are urgently needed to better monitor this disease in the current situation. In this study, the detection efficacy of a real-time fluorescent quantitative PCR (qPCR) assay was assessed for schistosomiasis japonica in mice, and before and after treatment with praziquantel (PZQ). Our results showed that the sensitivity of the qPCR was 99.3% (152/153, 95% CI: 96.41–99.98%) and its specificity was 100% (77/77, 95% CI: 95.32–100%) in mice infected with different numbers of Schistosoma japonicum. After the oral administration of PZQ, mice infected with 10 cercariae or 40 cercariae were all Schistosoma japonicum-negative 6 weeks after treatment. However, the negativity rates on a soluble egg antigen (SEA)-based enzyme-linked immunosorbent assay (ELISA) were only 34.8% (8/23, 10 cercariae group) and 6.7% (1/15, 40 cercariae group) at the sixth week after PZQ treatment. These results demonstrated that the qPCR method had good sensitivity and specificity, and suggested that its sensitivity correlated with the infection intensity in mice. Moreover, this method had better potential utility for evaluating the treatment efficacy of PZQ in schistosome-infected mice than SEA-based ELISA.

Abstract Psoriasis is a complex long-lasting inflammatory skin disease with high prevalence and associated comorbidity. It is characterized by epidermal hyperplasia and dermal infiltration of immune cells. Here, we review the role of keratinocytes in the pathogenesis of psoriasis, focusing on factors relevant to genetics, cytokines and receptors, metabolism, cell signaling, transcription factors, non-coding RNAs, antimicrobial peptides, and proteins with other different functions. The critical role of keratinocytes in initiating and maintaining the inflammatory state suggests the great significance of targeting keratinocytes for the treatment of psoriasis.

In order to realize the low vibration design, variable leakage flux permanent magnet (VLF-PM) motor is investigated and purposefully optimized. Firstly, the variable flux characteristics of the VLF-PM motor are studied in detail. Then the electromagnetic vibration characteristics of the VLF-PM motor under different operating conditions are analyzed. On this basis, key electromagnetic force harmonics caused by the vibration at typical operating conditions and torque performances are selected to be optimized. By the adoption of multi-objective optimization, low radial electromagnetic force (REF) and high output torque can be achieved. Both simulation and experimental results verify the effectiveness of the reduced vibration design of LCF-PM motors, which provides a potential research path for the low vibration design of PM motors, especially multi-mode PM motors.

Photoplethysmography (PPG) signal is potentially suitable in atrial fibrillation (AF) detection for its convenience in use and similarity in physiological origin to electrocardiogram (ECG). There are a few preceding studies that have shown the possibility of using the peak-to-peak interval of the PPG signal (PPIp) in AF detection. However, as a generalized model, the accuracy of an AF detector should be pursued on the one hand; on the other hand, its generalizability should be paid attention to in view of the individual differences in PPG manifestation of even the same arrhythmia and the existence of sub-types. Moreover, a binary classifier for atrial fibrillation and normal sinus rhythm is not convincing enough for the similarity between AF and ectopic beats. In this study, we project the atrial fibrillation detection as a multiple-class classification and try to propose a training pipeline that is advantageous both to the accuracy and generalizability of the classifier by designing and determining the configurable options of the pipeline, in terms of input format, deep learning model (with hyperparameter optimization), and scheme of transfer learning. With a rigorous comparison of the possible combinations of the configurable components in the pipeline, we confirmed that first-order difference of heartbeat sequence as the input format, a 2-layer CNN–1-layer Transformer hybridR model as the learning model and the whole model fine-tuning as the implementing scheme of transfer learning is the best combination for the pipeline (F1 value: 0.80, overall accuracy: 0.87)R.

Aberrant expression of long non-coding RNAs (lncRNAs) has been reported in multiple cancers. However, the underlying mechanisms mediated by super-enhancers remain elusive. Here we sought to define the role of a novel lncRNA termed lncRNA-DAW in tumorigenesis. Our results revealed that lncRNA-DAW was driven by a liver-specific super-enhancer and transcriptionally activated by HNF4G, leading to frequent elevation in hepatocellular carcinoma (HCC) specimens. Ectopic expression of lncRNA-DAW promoted both in vivo and in vitro tumor growth. By using RNA sequencing, Wnt2 was screened out as a downstream effector of lncRNA-DAW. We next found that lncRNA-DAW physically interacted with EZH2, a negative regulator of Wnt2. This interplay subsequently potentiated CDK1-EZH2 interaction, leading to the phosphorylation and ubiquitination of EZH2. The lncRNA-DAW-mediated EZH2 degradation facilitated the de-repression of Wnt2 transcription, which eventually activated the Wnt/β-catenin pathway. Furthermore, we verified that Wnt2 potentiated in vitro and in vivo cancer cell growth by activating the Wnt/β-catenin pathway. Finally, Wnt2 amplification was confirmed as a common event in liver cancer, and the expression of lncRNA-DAW was positively correlated with Wnt2 in HCC specimens. Collectively, we are the first to identify lncRNA-DAW as a novel candidate oncogene in liver cancer, and this lncRNA may serve as a novel clinical diagnosis biomarker for liver cancer.

Abstract Deep learning has become an extremely popular method in recent years, and can be a powerful tool in complex, prior-knowledge-required areas, especially in the field of biomedicine, which is now facing the problem of inadequate medical resources. The application of deep learning in disease diagnosis has become a new research topic in dermatology. This paper aims to provide a quick review of the classification of skin disease using deep learning to summarize the characteristics of skin lesions and the status of image technology. We study the characteristics of skin disease and review the research on skin disease classification using deep learning. We analyze these studies using datasets, data processing, classification models, and evaluation criteria. We summarize the development of this field, illustrate the key steps and influencing factors of dermatological diagnosis, and identify the challenges and opportunities at this stage. Our research confirms that a skin disease recognition method based on deep learning can be superior to professional dermatologists in specific scenarios and has broad research prospects.

Abstract Plant metabolism is more complex relative to individual microbes. In single‐celled microbes, transcriptional regulation by single transcription factors (TFs) is sufficient to shift primary metabolism. Corresponding genome‐level transcriptional regulatory maps of metabolism reveal the underlying design principles responsible for these shifts as a model in which master regulators largely coordinate specific metabolic pathways. Plant primary and specialized metabolism occur within innumerable cell types, and their reactions shift depending on internal and external cues. Given the importance of plants and their metabolites in providing humanity with food, fiber, and medicine, we set out to develop a genome‐scale transcriptional regulatory map of Arabidopsis metabolic genes. A comprehensive set of protein–DNA interactions between Arabidopsis thaliana TFs and gene promoters in primary and specialized metabolic pathways were mapped. To demonstrate the utility of this resource, we identified and functionally validated regulators of the tricarboxylic acid (TCA) cycle. The resulting network suggests that plant metabolic design principles are distinct from those of microbes. Instead, metabolism appears to be transcriptionally coordinated via developmental‐ and stress‐conditional processes that can coordinate across primary and specialized metabolism. These data represent the most comprehensive resource of interactions between TFs and metabolic genes in plants.

Unprecedented urbanization-induced population migration in China severely affects the scale and geographic distribution of anthropogenic pollutant discharge. Understanding how pollutant discharge patterns respond to population migration can help guide future efforts to maintain water sustainability. Here, based on a new calculation framework with 18 dynamic parameters designed for anthropogenic discharges, we finely tracked and visualized the effects of population migration on the spatial and temporal changes in anthropogenic discharge from 1980 to 2019 in the Minjiang River basin. The results indicate that the increasing effect of population migration on anthropogenic discharges peaked in 2002 and started to contribute to pollutant reduction from 2010 onward. The direct impact of population migration only contributes to the shift of anthropogenic discharges from rural to urban areas, while the migration bonus is the key factor leading to the reduction in anthropogenic discharges. Population migration is highly beneficial for chemical oxygen demand (COD) reduction, which has contributed to a shift from COD to NH4+-N and total phosphorus (TP) as hotspot pollutants in the whole basin (NH4+-N in urban areas and TP in rural areas). Moreover, pollution reduction resulting from the demographic bonus phenomenon has remained limited only to urban areas. Since approximately 2010, the per capita amount and total amount of anthropogenic pollutant discharges in rural areas have exceeded those in urban areas; in particular, the per capita COD and TP discharges in rural areas reached four times those in urban areas. This suggests that future pollution control strategies should give more attention to rural areas and focus on the differentiation and targeting of urban and rural areas.

The family of Abelson interactor (Abi) proteins is a component of WAVE regulatory complex (WRC) and a downstream target of Abelson (Abl) tyrosine kinase. The fact that Abi proteins also interact with diverse membrane proteins and intracellular signaling molecules places these proteins at a central position in the network that controls cytoskeletal functions and cancer cell metastasis. Here, we identified a motif in Abi proteins that conforms to consensus sequences found in a cohort of receptor and non-receptor tyrosine kinases that bind to Cbl-tyrosine kinase binding domain. The phosphorylation of tyrosine 213 in this motif is essential for Abi degradation. Double knockout of c-Cbl and Cbl B in Bcr-Abl-transformed leukemic cells abolishes Abi1, Abi2, and WAVE2 degradation. Moreover, knockout of Abi1 reduces Src family kinase Lyn activation in Bcr-Abl-positive leukemic cells and promotes EGF-induced EGF receptor downregulation in breast cancer cells. Importantly, Abi1 depletion impeded breast cancer cell invasion in vitro and metastasis in mouse xenografts. Together, these studies uncover a novel mechanism by which the WRC and receptor/non-receptor tyrosine kinases are regulated and identify Abi1 as a potential therapeutic target for metastatic breast cancer.

Traditional university support structures have generally been predicated on a ‘one size fits all’ approach that stresses a mechanistic, bureaucratic approach. Support is transactional in nature with students accessing it only when needed. Support focuses on both individual tutorial and centralised mechanisms which have proved effective for only some students. This paper proposes an organic student support system that is based around five features: agility in the environment, a tutor-student partnership, informal two-way communication, a student-led community, the inclusion of a knowledge-hub. The student support system in this article is based around Chinese students at a large UK university who felt disenfranchised by the current support mechanisms, so an alternative model was set up using the group-based instant-messaging social media platform, WeChat. The findings of surveys and interviews with Chinese students demonstrated that the featured organic student support system proved extremely successful and is something that could be replicated with other groups of students in the future in UK higher education.

Mobile ad hoc networks in smart grid become more and more popular and significant. However, the deployment scenarios, the functionality requirements and the limited capabilities make them vulnerable to a large group of attacks, e.g., wormhole attacks. In this paper, a novel cluster-based scheme is proposed for the purpose of preventing wormhole attacks. Firstly, a clustering algorithm is proposed that employs a powerful analytical hierarchy process methodology to elect clusterheads. Afterwards, the elected clusterheads are required to implement the wormhole attacks prevention scheme which includes two phases, i.e., detection phase and location phase. By detection phase, the existence of wormhole attacks can be detected. By location phase, the wormhole nodes are able to be detected. Simulation results indicate the scheme in our paper can be used to prevent wormhole attacks in ad hoc networks efficiently.

The increasing quantity of air pollutants generated by automobiles can cause significant harm in relatively enclosed indoor environments. Studying the distribution of pollutants under different conditions in underground parking garages is of great significance for improving indoor air quality and reducing casualties in the event of a fire. This article presents a geometric model of an underground parking garage based on PHOENICS modeling. The related results of CO concentration distribution and fire temperature distribution under ventilation and fire conditions are obtained. Based on the CO concentration and velocity distribution as well as the temperature distribution during a fire, reasonable suggestions are proposed to improve indoor air quality and reduce casualty rates in fire incidents. The results show that under ventilation conditions, adjusting the position of the induced ventilation fan can maintain CO concentrations below 30 ppm in partitions one to three and below 37 ppm in partitions four to six. The temperature of smoke gases remained below 50 °C during the evacuation time, and only a small area exhibited CO levels exceeding 2000 ppm. The existing ventilation exhaust system provides effective fire protection, as it minimally affects personnel evacuation due to the relatively lower smoke temperature.

Low-density lipoprotein receptors (LDLRs) are a class of cell-surface endocytosis receptors that are mainly involved in cholesterol homeostasis and cellular signal transduction. Very-low-density lipoprotein receptors (VLDLRs), which are members of the LDLR family, have been regarded as multi-function receptors that fulfill diverse physiological functions. However, no VLDLR gene has been identified in protochordates to date. As a representative protochordate species, amphioxi are the best available example of vertebrate ancestors. Identifying and characterizing the VLDLR gene in amphioxi has high importance for exploring the evolutionary process of the LDLR family. With this study, a new amphioxus VLDLR gene (designated AmphiVLDLR) was cloned and characterized using RACE-PCR. The 3217 nt transcript of the AmphiVLDLR had a 2577 nt ORF, and the deduced 858 amino acids were highly conserved within vertebrate VLDLRs according to their primary structure and three-dimensional structure, both of which contained five characteristic domains. In contrast to other vertebrate VLDLRs, which had a conserved genomic structure organization with 19 exons and 18 introns, the AmphiVLDLR had 13 exons and 12 introns. The results of a selective pressure analysis showed that the AmphiVLDLR had numerous positive selection sites. Furthermore, the tissue expression of AmphiVLDLR using RT-qPCR showed that AmphiVLDLR RNA expression levels were highest in the gills and muscles, moderate in the hepatic cecum and gonads, and lowest in the intestines. The results of the evolutionary analysis demonstrated that the AmphiVLDLR gene is a new member of the VLDLR family whose family members have experienced duplications and deletions over the evolutionary process. These results imply that the functions of LDLR family members have also undergone differentiation. In summary, we found a new VLDLR gene homolog (AmphiVLDLR) in amphioxi. Our results provide insight into the function and evolution of the LDLR gene family.

Small cysteine-rich (SCR) proteins, including fungal avirulence proteins, play important roles in pathogen–plant interactions. SCR protein-encoding genes have been discovered in the genomes of Phytophthora pathogens but their functions during pathogenesis remain obscure. Here, we report the characterization of one Phytophthora capsici SCR protein (namely, SCR82) with similarity to Phytophthora cactorum phytotoxic protein PcF. The scr82 gene has 10 allelic sequences in the P. capsici population. Homologs of SCR82 were not identified in fungi or other organisms but in Phytophthora relative species. Initially, scr82 was weakly expressed during the mycelium, sporangium, and zoospore stages but quickly upregulated when the infection initiated. Both ectopic expression of SCR82 and recombinant yeast-expressed protein (rSCR82) caused cell death on tomato leaves. Upon treatment, rSCR82 induced plant defense responses, including the induction of defense gene expression, reactive oxygen species burst, and callose deposition. Knockout of scr82 in P. capsici by CRISPR/Cas9 severely impaired its virulence on host plants and significantly reduced its resistance against oxidative stress. Inversely, its overexpression increased the pathogen’s virulence and tolerance to oxidative stress. Our results collectively demonstrate that SCR82 functions as both an important virulence factor and plant defense elicitor, which is conserved across Phytophthora spp.[Graphic: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Abstract Prolonged use of tight-fitting PPE, e.g., by COVID-19 healthcare workers leads to skin injuries. An important contributor is the shear exerted on the skin due to static friction at the skin-PPE interface. This study aims to develop an optimised wax-oil lubricant that reduces the friction, or shear, in the skin-PPE contact for up to four hours. Lubricants with different wax-oil combinations were prepared using beeswax, paraffin wax, olive oil, and mineral oil. In-vivo friction measurements involving seven participants were conducted by sliding a polydimethylsiloxane ball against the volar forearms to simulate the skin-PPE interface. The maximum static coefficient of friction was measured immediately and four hours after lubricant application. It was found that the coefficient of friction of wax-oil lubricants is mainly governed by the ratio of wax to oil and the thermal stability and morphology of the wax. To maintain long-term lubricity, it is crucial to consider the absorption of oil into the PPE material. The best performing lubricant is a mixture of 20 wt% beeswax, 40 wt% olive oil, and 40 wt% mineral oil, which compared to unlubricated skin, provides 87% (P = 0.0006) and 59% (P = 0.0015) reduction in instantaneous and 4-h coefficient of friction, respectively.

BackgroundExtragonadal yolk sac tumor (YST) of peritoneum is a rare malignancy.Case DescriptionA 37-year-old Chinese woman was admitted to hospital with a 3-month abdominal pain 4 years ago. Alpha-fetoprotein was 228,499.0 ng/mL. Computed tomography scan revealed a massive mass in the left lower abdomen. Exploratory laparotomy exposed a huge mesenteric mass. Then, mesenteric tumor resection, partial sigmoidectomy, and single-lumen fistula of sigmoid colon were performed. Postoperative pathologic diagnosis reported a stage IV mesenteric YST. After surgery, the patient received 6 courses of BEP (bleomycin, etoposide, and cisplatin) chemotherapy. Seven months later, the patient underwent stoma reversion of sigmoid colon and received another 2 courses of BEP chemotherapy. Three months after the last chemotherapy, liver metastases were diagnosed. She subsequently underwent 3 surgeries, radiotherapy for liver metastases, and multiple tiers of palliative chemotherapies, including TP (docetaxel and carboplatin), VIP (ifosfamide, cisplatin, and etoposide), TIP (paclitaxel, ifosfamide, and cisplatin), and so on. After the third surgery (left hepatic lesion resection and right iliac lymph node resection), she received 4 cyclic chemotherapies of BEP´ (boanmycin, etoposide, and cisplatin) without pulmonary toxic side effects.ConclusionPostoperative histopathology and immunohistochemistry are gold standards for the diagnosis of peritoneal YST. The standard first-line treatment is surgery plus BEP chemotherapy. Second-line therapy regimens and above, including VIP and TIP, improve the prognosis of recurrent germ cell tumors. This relapsed and refractory patient with peritoneal YST benefits from the secondary BEP´ chemotherapy.

The work cognition of public employees lays importance on tackling an escalating health crisis situation. At the micro-level and macro-level, different factors contribute to different degrees of public employees' work cognition. However, there are limited studies examining the work cognition of public employees and its influencing factors, particularly in situations such as a public health crisis. Our research takes China's response to COVID-19 as an example. The data have been taken from six Chinese provinces, Hunan, Hubei, Jiangsu, Shanxi, Henan, and Shandong, through a total of 738 questionnaires and telephonic interviews. Furthermore, this study used a logistic multiple regression model to analyze the factors that influenced the public employees' work cognition when working under a public health crisis. The results of our study showed that at a micro-level, the educational background, attitudes, and actions (initiative, responsibility, administrative capacity, and timeliness of feedback), and their level of concern with work influenced the work cognition of the public employees. At a macro-level, we found that it was the anti-epidemic measures that most influenced public employees' work cognition. Our findings provide important policy implications for emergency preparedness and handling of major emergencies, and have important reference value for the management of public employees and the improvement of national governance capabilities under similar major challenges in the future.

BackgroundLupus nephritis (LN) is the most common and severe clinical manifestation of systemic lupus erythematosus (SLE) with considerable morbidity/mortality and limited treatment options. Since kidney biopsy is a relative hysteretic indicator, it is indispensable to investigate potential biomarkers for early diagnosis and predicting clinical outcomes of LN patients. Extracellular proteins may become the promising biomarkers by the secretion into body fluid. Our study linked extracellular proteins with lupus nephritis to identify the emerging biomarkers.MethodsThe expression profiling data were acquired from the Gene Expression Omnibus (GEO) database. Meanwhile, the two gene lists encoding extracellular proteins were collected from the Human Protein Atlas (HPA) and UniProt database. Subsequently, the extracellular protein-differentially expressed genes (EP-DEGs) were screened out, and the key EP-DEGs were determined by MCODE, MCC, and Degree methods via the protein–protein interaction (PPI) network. The expression level, immune characteristics, and diagnostic value of these candidate biomarkers were investigated. Finally, the Nephroseq V5 tool was applied to evaluate the clinical significance of the key EP-DEGs.ResultsA total of 164 DEGs were acquired by comparing LN samples with healthy controls based on GSE32591 datasets. Then, 38 EP-DEGs were screened out through the intersection between DEGs and extracellular protein gene lists. Function enrichment analysis indicated that these EP-DEGs might participate in immune response and constitute the extracellular matrix. Four key EP-DEGs (LUM, TGFBI, COL1A2, and POSTN) were eventually identified as candidate biomarkers, and they were all overexpressed in LN samples. Except that LUM expression was negatively correlated with most of the immune regulatory genes, there was a positive correlation between the remaining three biomarkers and the immune regulatory genes. In addition, these biomarkers had high diagnostic value, especially the AUC value of the LUM–TGFBI combination which reached almost 1 (AUC = 0.973), demonstrating high accuracy in distinguishing LN from controls. Finally, we found a meaningful correlation of these biomarkers with sex, WHO class, and renal function such as glomerular filtration rate (GFR), serum creatinine level, and proteinuria.ConclusionIn summary, our study comprehensively identified four key EP-DEGs exerting a vital role in LN diagnosis and pathogenesis and serving as promising therapeutic targets.

The knowledge graph (KG) that represents structural relations among entities has become an increasingly important research field for knowledge-driven artificial intelligence. In this survey, a comprehensive review of KG and KG reasoning is provided. It introduces an overview of KGs, including representation, storage, and essential technologies. Specifically, it summarizes several types of knowledge reasoning approaches, including logic rules-based, representation-based, and neural network-based methods. Moreover, this paper analyzes the representation methods of knowledge hypergraphs. To effectively model hyper-relational data and improve the performance of knowledge reasoning, a three-layer knowledge hypergraph model is proposed. Finally, it analyzes the advantages of three-layer knowledge hypergraphs through reasoning and update algorithms which could facilitate future research.

The prevalence and infectious intensity of schistosomiasis japonica has decreased significantly in China in the past few decades. However, more accurate and sensitive diagnostic methods are urgently required for the further control, surveillance, and final elimination of the disease. In this study, we assessed the diagnostic efficacy of a real-time fluorescence quantitative PCR (qPCR) method and recombinase polymerase amplification (RPA) combined with a lateral-flow dipstick (LFD) assay for detecting early infections of Schistosoma japonicum and different infection intensities. The sensitivity of the qPCR at 40 days post-infection (dpi) was 100% (8/8) in mice infected with 40 cercariae, which was higher than in mice infected with 10 cercariae (90%, 9/10) or five cercariae (77.8%, 7/9). The results of the RPA–LFD assays were similar, with sensitivities of 55.6% (5/9), 80% (8/10), and 100% (8/8) in mice infected with 5, 10, and 40 cercariae, respectively. In goats, both the qPCR and RPA–LFD assays showed 100% (8/8) sensitivity at 56 dpi. In the early detection of S. japonicum infection in mice and goats with qPCR, the first peak in positivity appeared at 3–4 dpi, when the positivity rate exceeded 40%, even in the low infection, intensity mice. In the RPA–LFD assays, positive results first peaked at 4–5 dpi in the mice, and the positivity rate was 37.5% in the goats at 1 dpi. In conclusion, neither of the molecular methods produced exceptional results for the early diagnosis of S. japonicum infection. However, they were useful methods for the regular diagnosis of schistosomiasis in mice and goats.

Vessel trajectory prediction supports navigation services and collision detection. To maintain safety and efficiency in maritime transportation, vessel trajectory prediction is always an important topic. By using automatic identification system (AIS) data and deep learning methods, the task of vessel trajectory prediction has made significant progress. However, this task is still full of challenges due to the complexity of historical information dependencies and the strong influence of spatial correlations. In this paper, we introduce a novel deep learning model, PESO, based on the structure of Seq2Seq, consisting of Parallel Encoders and a Ship-Oriented Decoder. The Parallel Encoders, including the Location Encoder and the Sailing Status Encoder are designed to integrate more information into feature representation. The Ship-Oriented Decoder is targeted to utilize the Semantic Location Vector (SLV) to guide the prediction, which better represents the spatial correlation of historical track points. In order to verify the efficiency and efficacy of PESO, we conducted comparative experiments with several baseline models. The experimental results demonstrate that PESO is superior to them both quantitatively and qualitatively.

Fiber-optic biosensors based on localized surface plasmon resonance (LSPR) have the advantages of great biocompatibility, label-free, strong stability, and real-time monitoring of various analytes. LSPR fiber-optic biosensors have attracted extensive research attention in the fields of environmental science, clinical medicine, disease diagnosis, and food safety. The latest development of LSPR fiber-optic biosensors in recent years has focused on the detection of clinical disease markers and the detection of various toxic substances in the environment and the progress of new sensitization mechanisms in LSPR fiber-optic sensors. Therefore, this paper reviews the LSPR fiber-optic sensors from the aspects of working principle, structure, and application fields in biosensors. According to the structure, the sensor can be divided into three categories: traditional ordinary optical fiber, special shape optical fiber, and specialty optical fiber. The advantages and disadvantages of existing and future LSPR fiber-optic biosensors are discussed in detail. Additionally, the prospect of future development of fiber-optic biosensors based on LSPR is addressed.

Abstract Background The soil microbiome drives soil ecosystem function, and soil microbial functionality is directly linked to interactions between microbes and the soil environment. However, the context-dependent interactions in the soil microbiome remain largely unknown. Results Using latent variable models (LVMs), we disentangle the biotic and abiotic interactions of soil bacteria, fungi and environmental factors using the Qinghai-Tibetan Plateau soil ecosystem as a model. Our results show that soil bacteria and fungi not only interact with each other but also shift from competition to facilitation or vice versa depending on environmental variation; that is, the nature of their interactions is context-dependent. Conclusions Overall, elevation is the environmental gradient that most promotes facilitative interactions among microbes but is not a major driver of soil microbial community composition, as evidenced by variance partitioning. The larger the tolerance of a microbe to a specific environmental gradient, the lesser likely it is to interact with other soil microbes, which suggests that facilitation does not necessarily lead to niche expansion.