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Single-cell genomics is a powerful tool for studying heterogeneous tissues such as the brain. Yet little is understood about how genetic variants influence cell-level gene expression. Addressing this, we uniformly processed single-nuclei, multiomics datasets into a resource comprising >2.8 million nuclei from the prefrontal cortex across 388 individuals. For 28 cell types, we assessed population-level variation in expression and chromatin across gene families and drug targets. We identified >550,000 cell type-specific regulatory elements and >1.4 million single-cell expression quantitative trait loci, which we used to build cell-type regulatory and cell-to-cell communication networks. These networks manifest cellular changes in aging and neuropsychiatric disorders. We further constructed an integrative model accurately imputing single-cell expression and simulating perturbations; the model prioritized ~250 disease-risk genes and drug targets with associated cell types.

Abstract Breast cancer is one of the most prevalent and diverse malignancies, and, with global cases increasing, the need for biomarkers to inform individual sensitivity to chemotherapeutics has never been greater. Our retrospective clinical analysis predicted that the expression of the fragile site-associated tumor suppressor (FATS) gene was associated with the sensitivity of breast cancer to neoadjuvant chemotherapy with paclitaxel. In vitro experiments subsequently demonstrated that FATS significantly increased the inhibitory effects of paclitaxel on breast cancer cells’ migration, growth, and survival. An interaction screen revealed that FATS interacted with MYH9 and promoted its degradation via the ubiquitin-proteasome pathway, thereby downregulating Wnt signaling. By overexpressing FATS and MYH9, we demonstrated that FATS enhanced paclitaxel-induced apoptosis in breast cancer cells by degrading MYH9 to downregulate the Wnt pathway. We also demonstrated in a mouse xenograft model that FATS significantly increased the chemosensitivity of breast cancer cells to paclitaxel in vivo. This study presents a new mechanism by which FATS interacts with MYH9 to suppress the Wnt/β-catenin signaling pathway and induce apoptosis, thus enhancing the sensitivity of breast cancer cells to paclitaxel chemotherapy. The results also propose novel biomarkers for predicting breast cancer sensitivity to neoadjuvant chemotherapy with paclitaxel. Finally, we provide in vivo evidence that the combination of paclitaxel with IWR-1, a novel Wnt pathway inhibitor, synergistically suppresses breast cancer growth, laying the foundation for future trials with this drug combination. These results therefore provide a number of potential solutions for more precise treatment of patients with breast cancer in the future.

Abstract Background Helicobacter pylori (H. pylori) is the predominant etiological agent of gastritis and disrupts the integrity of the gastric mucosal barrier through various pathogenic mechanisms. After H. pylori invades the gastric mucosa, it interacts with immune cells in the lamina propria. Macrophages are central players in the inflammatory response, and H. pylori stimulates them to secrete a variety of inflammatory factors, leading to the chronic damage of the gastric mucosa. Therefore, the study aims to explore the mechanism of gastric mucosal injury caused by inflammatory factors secreted by macrophages, which may provide a new mechanism for the development of H. pylori-related gastritis. Methods The expression and secretion of CCL3 from H. pylori infected macrophages were detected by RT-qPCR, Western blot and ELISA. The effect of H. pylori-infected macrophage culture medium and CCL3 on gastric epithelial cells tight junctions were analyzed by Western blot, immunofluorescence and transepithelial electrical resistance. EdU and apoptotic flow cytometry assays were used to detect cell proliferation and apoptosis levels. Dual-luciferase reporter assays and chromatin immunoprecipitation assays were used to study CCL3 transcription factors. Finally, gastric mucosal tissue inflammation and CCL3 expression were analyzed by hematoxylin and eosin staining and immunohistochemistry. Results After H. pylori infection, CCL3 expressed and secreted from macrophages were increased. H. pylori-infected macrophage culture medium and CCL3 disrupted gastric epithelial cells tight junctions, while CCL3 neutralizing antibody and receptor inhibitor of CCL3 improved the disruption of tight junctions between cells. In addition, H. pylori-infected macrophage culture medium and CCL3 recombinant proteins stimulated P38 phosphorylation, and P38 phosphorylation inhibitor improved the disruption of tight junctions between cells. Besides, it was identified that STAT1 was a transcription factor of CCL3 and H. pylori stimulated macrophage to secret CCL3 through the JAK1-STAT1 pathway. Finally, after mice were injected with murine CCL3 recombinant protein, the gastric mucosal injury and inflammation were aggravated, and the phosphorylation level of P38 was increased. Conclusions In summary, our findings demonstrate that H. pylori infection stimulates macrophages to secrete CCL3 via the JAK1-STAT1 pathway. Subsequently, CCL3 damages gastric epithelial tight junctions through the phosphorylation of P38. This may be a novel mechanism of gastric mucosal injury in H. pylori-associated gastritis.

ObjectiveIn recent years, there has been a significant increase in the severity of leaf diseases in maize, with a noticeable trend of mixed occurrence. This poses a serious threat to the yield and quality of maize. However, there is a lack of studies that combine the identification of different types of leaf diseases and their severity classification, which cannot meet the needs of disease prevention and control under the mixed occurrence of different diseases and different severities in actual maize fields.MethodsA method was proposed for identifying the types of typical leaf diseases in maize and classifying their severity using hyperspectral technology. Hyperspectral data of three leaf diseases of maize: northern corn leaf blight (NCLB), southern corn leaf blight (SCLB) and southern corn rust (SCR), were obtained through greenhouse pathogen inoculation and natural inoculation. The spectral data were preprocessed by spectral standardization, SG filtering, sensitive band extraction and vegetation index calculation, to explore the spectral characteristics of the three leaf diseases of maize. Then, the inverse frequency weighting method was utilized to balance the number of samples to reduce the overfitting phenomenon caused by sample imbalance. Relief-F and variable selection using random forests (VSURF) method were employed to optimize the sensitive spectral features, including band features and vegetation index features, to construct models for disease type identification based on the full stages of disease development (including all disease severities) and for individual disease severities using several representative machine learning approaches, demonstrating the effectiveness of the research method. Furthermore, the study individual occurrence severity classification models were also constructed for each single maize leaf disease, including the NCLB, SCLB and SCR severity classification models, respectively, aiming to achieve full-process recognition and disease severity classification for different leaf diseases. Overall accuracy (OA) and Macro F1 were used to evaluate the model accuracy in this study.Results and DiscussionThe research results showed significant spectrum changes of three kinds of maize leaf diseases primarily focusing on the visible (550-680 nm), red edge (740-760 nm), near-infrared (760-1 000 nm) and shortwave infrared (1 300-1 800 nm) bands. Disease-specific spectral features, optimized based on disease spectral response rules, effectively identified disease species and classify their severity. Moreover, vegetation index features were more effective in identifying disease-specific information than sensitive band features. This was primarily due to the noise and information redundancy present in the selected hyperspectral sensitive bands, whereas vegetation index could reduce the influence of background and atmospheric noise to a certain extent by integrating relevant spectral signals through band calculation, so as to achieve higher precision in the model. Among several machine learning algorithms, the support vector machine (SVM) method exhibited better robustness than random forest (RF) and decision tree (DT). In the full stage of disease development, the optimal overall accuracy (OA) of the disease classification model constructed by SVM based on vegetation index reached 77.51%, with a Macro F1 of 0.77, representing a 28.75% increase in OA and 0.30 higher of Macro F1 compared to the model based on sensitive bands. Additionally, the accuracy of the disease classification model with a single severity of the disease increased with the severity of the disease. The accuracy of disease classification during the early stage of disease development (OA=70.31%) closely approached that of the full disease development stage (OA=77.51%). Subsequently, in the moderate disease severity stage, the optimal accuracy of disease classification (OA=80.00%) surpassed the optimal accuracy of disease classification in the full disease development stage. Furthermore, the optimal accuracy of disease classification under severe severity reached 95.06%, with a Macro F1 of 0.94. This heightened accuracy during the severity stage can be attributed to significant changes in pigment content, water content and cell structure of the diseased leaves, intensifying the spectral response of each disease and enhancing the differentiation between different diseases. In disease severity classification model, the optimal accuracy of the three models for maize leaf disease severity all exceeded 70%. Among the three kinds of disease severity classification results, the NCLB severity classification model exhibited the best performance. The NCLB severity classification model, utilizing SVM based on the optimal vegetation index features, achieved an OA of 86.25%, with a Macro F1 of 0.85. In comparison, the accuracy of the SCLB severity classification model (OA=70.35%, Macro F1=0.70) and SCR severity classification model (OA=71.39%, Macro F1=0.69) were lower than that of NCLB.ConclusionsThe aforementioned results demonstrate the potential to effectively identify and classify the types and severity of common leaf diseases in maize using hyperspectral data. This lays the groundwork for research and provides a theoretical basis for large-scale crop disease monitoring, contributing to precision prevention and control as well as promoting green agriculture.

BackgroudIn recent years, as the number of people with obesity has surged, the number of morbidly obese patients has also grown. The pathophysiological changes in morbid obesity can lead to combined lung diseases, which may result in hypoventilation, hypoxemia, acute upper airway obstruction, acute respiratory distress syndrome, and sleep apnea syndrome, posing serious challenges to anesthesia management. Here, we describe a case of the administration of remimazolam combined with remifentanil in a patient with morbid obesity undergoing gastroscopy. This has rarely been reported in clinical practice, and we present our management experience here with the aim of providing a reference for clinical work.Case presentationWe report the case of a 32-year-old male hypertensive patient with a height of 180 cm, weight of 145 kg, and body mass index of 44.8 kg/m2. The patient’s main complaint was intermittent hunger pain for more than 1 year, and duodenal polyps were found. Considering the patient’s morbid obesity and the combination of sleep apnea syndrome and hypertension, we administered remimazolam along with remifentanil to ensure perioperative safety.ConclusionThe procedure lasted 30 min, and the anesthesia was satisfactory with no complications. Remimazolam combined with remifentanil intravenous anesthesia is safe for short gastroscopy in patients with morbidly obesity. The administration of a small dose of split-titration delivery facilitates the maintenance of stable vital signs.

A novel tungsten carbide (WC)-reinforced nickel (Ni)-based laser cladding layer was prepared through an in-situ synthesis process. The mechanism of the effect of scanning rates and laser power on the microstructures, wear and corrosion resistance of in-situ synthesized WC-reinforced Ni-based cladding layer were analyzed. The results revealed that the optimal in-situ synthesized WC laser cladding process entailed a scan rate of 3 mm/s and a laser power of 3000 W. The generation of WC phase has a significant strengthening effect on the cladding layer, which exhibits outstanding hardness (1261HV0.2). There is no clear linear relationship between scanning rate and abrasion resistance, and the coating abrasion resistance increased with increasing laser power. Furthermore, increasing the laser power improves the corrosion resistance of the cladding layer, while the scanning speed has a minimal effect on corrosion resistance.

Background and aim: The D-dimer to fibrinogen ratio (DFR) represents an emerging and significant clinical biomarker. However, its correlation with cerebral venous thrombosis (CVT) remains underexplored. This retrospective cohort study aims to elucidate the association between DFR values and the severity and prognosis of CVT. Methods: Severe CVT was defined as the presence of at least 1 of the following risk factors: mental status disorder, coma state, intracranial cerebral hemorrhage, or thrombosis of the deep cerebral venous system. The modified Rankin Scale was utilized to assess functional outcomes. DFR measurements were obtained within 24 h of hospital admission. Logistic regression analysis was employed to determine the prognostic significance of DFR. After Bonferroni correction, a two-tailed P value < 0.017 (0.05/3) was considered statistically significant. Result: A total of 196 patients were included in the study, among whom 85 patients were diagnosed with severe CVT, and 35 and 14 patients experienced short-term and long-term adverse outcomes, respectively. Receiver operating characteristic curve analysis demonstrated that DFR has predictive value for severe CVT, poor short-term and long-term outcomes, with area under the curve values of 0.690 [95% CI: 0.617–0.764, P <.001], 0.773 [95% CI: 0.701–0.845, P <.001], and 0.754 [95% CI: 0.619–0.886, P =.002], respectively. DFR ≥ 0.253 was identified as a significant predictor of severe CVT [adjusted odds ratio (aOR) (95% CI): 2.03 (1.10–3.75), P =.024]. Additionally, DFR ≥ 0.322 and DFR ≥ 0.754 were significantly associated with poor short-term outcomes at discharge [aOR (95% CI): 2.63 (1.43–4.76), P =.002] and poor long-term outcomes at 12 months [aOR (95% CI): 2.86 (1.32–6.25), P =.008], respectively. Conclusion: Elevated DFR is associated with increased severity of CVT. Additionally, higher DFR levels can predict poorer clinical outcomes in CVT. [ABSTRACT FROM AUTHOR]

Background: Currently, studies on the formation mechanism for the enlargement of arachnoid granulation (AG) are lacking. The impact of dyslipidemia on the formation of multiple large arachnoid granulations (LAGs) was studied in this research. Methods: The study included patients diagnosed with cerebral venous sinus stenosis (CVSS) related to LAG. The number of LAGs was assessed via high-resolution black blood magnetic resonance imaging. The relationships between blood lipids and multiple LAGs were explored to evaluate the effects of dyslipidemia on the formation of multiple LAGs. Results: A total of 163 participants with a diagnosis of LAG were included. The levels of total cholesterol (TC) (P = 0.004) and low-density lipoprotein cholesterol (LDL-c) (P = 0.01) in the multiple LAGs group were greater than those in the non-multiple LAGs group. Multivariate logistic regression analysis revealed that TC (odds ratio (OR), 2.19; 95% confidence interval (CI), 1.26–3.80; P = 0.006) and LDL-c (OR, 2.18; 95% CI, 1.16–4.07; P = 0.02) were independently associated with multiple LAGs. Conclusions: TC and LDL-c are independently related to multiple LAGs, indicating that dyslipidemia may be a potential cause of CVSS. Therefore, monitoring blood lipids may be necessary for patients with LAGs. [ABSTRACT FROM AUTHOR]

Background: With the evolution of disease patterns and the continuous pursuit of persons for high-quality nursing services, new nurses are the reserve talents of the nursing team and shoulder a major mission. However, due to their low work performance and high turnover rate, this is not conducive to the stable development of nursing teams, and it is urgent to solve this problem. The purpose of this study was to explore the effect of work readiness on the work performance of new nurses, focusing on the mediating role of organizational justice and professional identity. Method: A cross-sectional design was employed. Using convenience sampling methods, 607 new nurses were surveyed in 5 hospitals in Henan Province, China, from January to February 2023. Data were collected using demographic characteristics questionnaire, the Work Performance Scale, the Work Readiness Scale for Graduate Nurses, the Organizational Justice Scale, and the Professional Identity Rating Scale for Nurses. AMOS 26.0 was used for model drawing and mediation path testing, and SPSS 25.0 was used for data analysis. Results: The mediation model shows a good fit (χ2 /df = 2.747, CFI = 0.987, GFI = 0.948, AGFI = 0.926, TLI = 0.984, IFI = 0.987, and RMSEA = 0.054). In this study, we found professional identity is a mediating variable between work readiness and the work performance of new nurses (β = 0.113, P<0.01), organizational justice is a mediating variable between work readiness and the work performance of new nurses (β = 0.269, P<0.01) and Organizational justice and professional identity play a chain mediating role in work readiness and work performance (β = 0.066, P<0.01). Conclusions: The study highlights the importance of improving the work performance of new nurses. To improve work performance, managers should create a fair atmosphere, formulate transparent policies, improve the organizational justice of new nurses, and promote the professional identity and work readiness of new nurses by holding activities or conducting lectures. This will help stabilize the nursing team, improve the medical environment, stimulate the work enthusiasm of new nurses, and contribute to the development of the hospital. [ABSTRACT FROM AUTHOR]

Background: Cerebral venous sinus thrombosis (CVST) is a rare but potentially life-threatening subtype of stroke. Prompt and appropriate anticoagulation is crucial for improving the prognosis of CVST and preventing its recurrence. Identifying the underlying cause of CVST is decisive for guiding anticoagulant selection and determining treatment duration. Case Presentation: A 50-year-old man presented with a 35-day history of headache, nausea, vomiting, and blurred vision. Digital subtraction angiography performed at another facility revealed CVST. A contrast-enhanced black-blood MRI at our center confirmed the diagnosis, which was supported by a high intracranial pressure of 330mmH2O. Laboratory tests showed elevated leukocytes and platelet counts, raising suspicion of an underlying myeloproliferative neoplasms (MPNs). A bone marrow biopsy demonstrated increased megakaryocytes and granulocytes, and genetic testing identified the presence of the Janus kinase 2 V617F (JAK2 V617F) mutation, leading to a diagnosis of pre-primary myelofibrosis (pre-PMF). During hospitalization, anticoagulation with nadroparin calcium and fibrinolytic therapy were initiated. Upon discharge, rivaroxaban and aspirin were prescribed to prevent CVST recurrence and arterial thrombosis. Conclusion: This case highlights the importance of recognizing dynamic changes in routine blood tests that may link CVST to underlying hematological disorders. The JAK2 mutation is not only associated with MPNs but also increases the risk of thrombosis, including CVST. Further investigation is warranted to better understand the mechanisms by which JAK2 mutations contribute to thrombosis and to explore the potential benefits of JAK2 inhibitors in reducing this risk. [ABSTRACT FROM AUTHOR]

Objective: To explore whether miR-199a-5p regulated BBB integrity through PI3K/Akt pathway after ischemia stroke. Methods: Adult male Sprague-Dawley rats with permanent middle cerebral artery occlusion(MCAO) were used in experiment. The Ludmila Belayev 12-point scoring was used to measure the neurological function of MCAO rats. The Evans Blue Stain, immunofluorescence staining, western-blotting and RT-PCR were performed to evaluate the effects of miR-199a-5p mimic on BBB integrity in rats following MCAO. Results: The result suggested that miR-199a-5p mimic treatment possessed the potential to boost proprioception and motor activity of MCAO rats. MiR-199a-5p decreased the expression of PIK3R2 after MCAO, activated Akt signaling pathway, and increased the expression of Claudin-5 and VEGF in the ischemic penumbra. Furthermore, miR-199a-5p alleviated inflammation after cerebral ischemia. BBB leakage and neurocyte apoptosis were cut down in MCAO rats treated with miR-199a-5p mimic. Conclusions: MiR-199a-5p mimic decreased the expression of PIK3R2 and activated Akt signaling pathway after ischemia stroke, reduced the expression of inflammatory cytokines, and attenuated BBB disruption after ischemic stroke. [ABSTRACT FROM AUTHOR]

Planting salt-tolerant plants is an efficient method of biological improvement for saline–alkali land. However, few studies have examined the soil improvement effects of the rotation of the green manure plant sesbania and the grain crop sorghum. Thus, we planted sesbania in native soil on heavily saline–alkaline coastal land and subsequently planted sorghum after returning the sesbania straw to the soil. The effect of this sesbania–sorghum rotation on soil improvement was clarified by comparing indicators of soil quality before and after sesbania and sorghum were planted, such as the soil structure, water infiltration, soil salt content, and soil microbial changes. The results showed that the soil bulk density of the plow layer (0–40 cm) after crop harvest decreased by 9.63% compared with that of bare land, and the soil porosity increased by 5.67%. The cumulative infiltration, initial infiltration rate, and stable infiltration rate of saline soil were 3.6 times, 2.8 times, and 3.3 times higher than those of bare land, respectively. With the growth of sesbania and sorghum, the soil salt content in the plow layer of the cultivated land decreased by 37.73%, while that of bare land decreased by 9.1%. A further analysis of desalination showed that the total desalination amount in the plow layer was 15.58 t/ha, of which 5% was due to plant absorption, and the rest was from salt leaching. Moreover, sesbania–sorghum rotation increased the soil organic matter content in the plow layer from 69.1 t/ha to 73.8 t/ha. The quantities of some microorganisms that are mainly found in coastal saline soil decreased, while those of some common soil microorganisms increased, reflecting an improvement in the soil quality. The above results prove that sesbania–sorghum rotation had a significant effect on soil improvement and salt reduction, which is of great significance for the further utilization of saline–alkali land to enhance crop productivity. [ABSTRACT FROM AUTHOR]

Flavivirus infection capitalizes on cellular lipid metabolism to remodel the cellular intima, creating a specialized lipid environment conducive to viral replication, assembly, and release. The Japanese encephalitis virus (JEV), a member of the Flavivirus genus, is responsible for significant morbidity and mortality in both humans and animals. Currently, there are no effective antiviral drugs available to combat JEV infection. In this study, we embarked on a quest to identify anti-JEV compounds within a lipid compound library. Our research led to the discovery of two novel compounds, isobavachalcone (IBC) and corosolic acid (CA), which exhibit dose-dependent inhibition of JEV proliferation. Time-of-addition assays indicated that IBC and CA predominantly target the late stage of the viral replication cycle. Mechanistically, JEV nonstructural proteins 1 and 2A (NS1 and NS2A) impede 5′-adenosine monophosphate (AMP)-activated protein kinase (AMPK) activation by obstructing the liver kinase B1 (LKB1)–AMPK interaction, resulting in decreased p-AMPK expression and a consequent upsurge in lipid synthesis. In contrast, IBC and CA may stimulate AMPK by binding to its active allosteric site, thereby inhibiting lipid synthesis essential for JEV replication and ultimately curtailing viral infection. Most importantly, in vivo experiments demonstrated that IBC and CA protected mice from JEV-induced mortality, significantly reducing viral loads in the brain and mitigating histopathological alterations. Overall, IBC and CA demonstrate significant potential as effective anti-JEV agents by precisely targeting AMPK-associated signaling pathways. These findings open new therapeutic avenues for addressing infections caused by Flaviviruses. IMPORTANCE This study is the inaugural utilization of a lipid compound library in antiviral drug screening. Two lipid compounds, isobavachalcone (IBC) and corosolic acid (CA), emerged from the screening, exhibiting substantial inhibitory effects on the Japanese encephalitis virus (JEV) proliferation in vitro. In vivo experiments underscored their efficacy, with IBC and CA reducing viral loads in the brain and mitigating JEVinduced histopathological changes, effectively shielding mice from fatal JEV infection. Intriguingly, IBC and CA may activate 5′-adenosine monophosphate (AMP)-activated protein kinase (AMPK) by binding to its active site, curtailing the synthesis of lipid substances, and thus suppressing JEV proliferation. This indicates AMPK as a potential antiviral target. Remarkably, IBC and CA demonstrated suppression of multiple viruses, including Flaviviruses (JEV and Zika virus), porcine herpesvirus (pseudorabies virus), and coronaviruses (porcine deltacoronavirus and porcine epidemic diarrhea virus), suggesting their potential as broad-spectrum antiviral agents. These findings shed new light on the potential applications of these compounds in antiviral research. [ABSTRACT FROM AUTHOR]

The early and accurate mapping of winter canola is essential in predicting crop yield, assessing agricultural disasters, and responding to food price fluctuations. Although some methods have been proposed to map the winter canola at the flowering or later stages, mapping winter canola planting areas at the early stage is still challenging, due to the insufficient understanding of the multi-source remote sensing features sensitive for winter canola mapping. The objective of this study was to evaluate the potential of using the combination of optical and synthetic aperture radar (SAR) data for mapping winter canola at the early stage. We assessed the contributions of spectral features, backscatter coefficients, and textural features, derived from Sentinel-2 and Sentinel-1 SAR images, for mapping winter canola at early stages. Random forest (RF) and support vector machine (SVM) classification models were built to map winter canola based on early-stage images and field samples in 2017 and then the best model was applied to corresponding satellite data in 2018–2022. The following results were obtained: (1) The red edge and near-infrared-related spectral features were most important for the mapping of early-stage winter canola, followed by VV (vertical transmission, vertical reception), DVI (Difference vegetation index), and GOSAVI (Green Optimized Soil Adjusted Vegetation Index); (2) based on Sentinel-1 and Sentinel-2 data, winter canola could be mapped as early as 130 days prior to ripening (i.e., early overwinter stage), with the F-score over 0.85 and the OA (Overall Accuracy) over 81%; (3) adding Sentinel-1 could improve the OA by about 2–4% and the F-score by about 1–2%; and (4) based on the classifier transfer approach, the F-scores of winter canola mapping in 2018–2022 varied between 0.75 and 0.97, and the OAs ranged from 79% to 86%. This study demonstrates the potential of early-stage winter canola mapping using the combination of Sentinel-2 and Sentinel-1 images, which could enable the large-scale early mapping of canola and provide valuable information for stakeholders and decision makers. [ABSTRACT FROM AUTHOR]