[Analysis of influencing factors of early femoral head necrosis after femoral neck fracture and construction of nomogram prediction model].

OBJECTIVE: To explore the risk factors of early femoral head necrosis in patients with femoral neck fracture after operation, and to establish a nomogram prediction model. METHODS: A total of 167 patients with femoral neck fracture from January 2020 to April 2022 were selected and divided into necrosis group and non-necrosis group according to whether femoral head necrosis occurred in the early postoperative period. There were 21 males and 17 females in the necrosis group, aged from 33 to 72 years old, with an average of (53.49±10.96) years old, and the time from injury to operation ranged from 40 to 67 hours, with average time of(53.46±7.23) hours. There were 72 males and 57 females in the non-necrosis group, aged from 18 to 83 years, with an average of (52.78±12.55) years old, and the time from injury to operation was 18 to 65 hours, with an average time of(39.88±7.79) hours. The potential influencing factors, including patient gender, diabetes mellitus, hypertension, chronic liver disease, posterior inclination angle of the femoral head, operation mode, fracture displacement, fracture line location, preoperative braking traction, screw arrangement mode, reduction quality, age, body mass index(BMI), and injury to operation time were subjected to single factor analysis. Logistic multivariate regression analysis was conducted for factors with a significance level of P<0.05. RESULTS: The incidence of femoral head necrosis in 167 patients with femoral neck fracture was 22.76%. The following factors were identified as independent risk factors for early postoperative femoral head necrosis in patients with femoral neck fractures:coexisting diabetes[OR=5.139, 95%CI(1.405, 18.793), P=0.013], displaced fracture [OR=3.723, 95%CI(1.105, 12.541), P=0.034], preoperative immobilization[OR=3.444, 95%CI(1.038, 11.427), P=0.043], quality of reduction [OR=3.524, 95%CI(1.676, 7.411), P=0.001], and time from injury to surgery[OR=1.270, 95%CI(1.154, 1.399), P=0.000]. The Hosmer-Lemeshow goodness-of-fit test(χ2=3.951, P=0.862), the area under the receiver operator characteristic(ROC) curve was 0.944[P<0.001, 95%CI(0.903, 0.987)], with a sensitivity of 89.50%, the specificity was 88.40%, the maximum Youden index was 0.779, and the overall trend of the model correction curve was close to the ideal curve. Model regression equation was Z=1.637 × diabetes + 1.314× fracture displacement+1.237 × preoperative braking traction+1.260 × reduction quality + 0.239×injury to operation time-18.310. CONCLUSION: The occurrence of early femoral head necrosis in patients with femoral neck fracture postoperatively is affected by multiple factors. The risk early warning model established according to the factors has good predictive efficacy.

Precise detection of cell-type-specific domains in spatial transcriptomics.

Cell-type-specific domains are the anatomical domains in spatially resolved transcriptome (SRT) tissues where particular cell types are enriched coincidentally. It is challenging to use existing computational methods to detect specific domains with low-proportion cell types, which are partly overlapped with or even inside other cell-type-specific domains. Here, we propose De-spot, which synthesizes segmentation and deconvolution as an ensemble to generate cell-type patterns, detect low-proportion cell-type-specific domains, and display these domains intuitively. Experimental evaluation showed that De-spot enabled us to discover the co-localizations between cancer-associated fibroblasts and immune-related cells that indicate potential tumor microenvironment (TME) domains in given slices, which were obscured by previous computational methods. We further elucidated the identified domains and found that Srgn may be a critical TME marker in SRT slices. By deciphering T cell-specific domains in breast cancer tissues, De-spot also revealed that the proportions of exhausted T cells were significantly increased in invasive vs. ductal carcinoma.

Monitoring of parasite Orobanche cumana using Vis-NIR hyperspectral imaging combining with physio-biochemical parameters on host crop Helianthus annuus.

KEY MESSAGE: This study provided a non-destructive detection method with Vis-NIR hyperspectral imaging combining with physio-biochemical parameters in Helianthus annuus in response to Orobanche cumana infection that took insights into the monitoring of sunflower weed. Sunflower broomrape (Orobanche cumana Wallr.) is an obligate weed that attaches to the host roots of sunflower (Helianthus annuus L.) leading to a significant reduction in yield worldwide. The emergence of O. cumana shoots after its underground life-cycle causes irreversible damage to the crop. In this study, a fast visual, non-invasive and precise method for monitoring changes in spectral characteristics using visible and near-infrared (Vis-NIR) hyperspectral imaging (HSI) was developed. By combining the bands sensitive to antioxidant enzymes (SOD, GR), non-antioxidant enzymes (GSH, GSH + GSSG), MDA, ROS (O2-, OH-), PAL, and PPO activities obtained from the host leaves, we sought to establish an accurate means of assessing these changes and conducted imaging acquisition using hyperspectral cameras from both infested and non-infested sunflower cultivars, followed by physio-biochemical parameters measurement as well as analyzed the expression of defense related genes. Extreme learning machine (ELM) and convolutional neural network (CNN) models using 3-band images were built to classify infected or non-infected plants in three sunflower cultivars, achieving accuracies of 95.83% and 95.83% for the discrimination of infestation as well as 97.92% and 95.83% of varieties, respectively, indicating the potential of multi-spectral imaging systems for early detection of O. cumana in weed management.

Spatial distribution and enrichment characteristics of selenium in paddy soil and rice around the Dongting Lake.

Selenium (Se) deficiency is a major global health issue. Given that the Dongting Lake region is a significant agricultural production area in China, its soil and geographical properties have a marked influence on Se accumulation in rice. Investigating these factors and their importance can provide technical guidance for the production of Se-rich rice locally and in other similar regions worldwide. Such studies can foster Se-enriched agricultural practices on a global scale, contributing to improved human health and environmental quality. Therefore, in this study, we investigated 15,403 paddy soil samples and their corresponding rice grains from the Dongting Lake area, by analyzing their Se content, spatial distribution, and bioaccumulation factor (BCF). The effects of parent materials, soil characteristics (physicochemical), and geographical factors on Se content in soil, rice grains, and BCF were also assessed. We found that the average Se content in the paddy soil of the Dongting Lake area was 0.43 mg/kg, which was 1.48 folds higher than the background Se content (0.29 mg/kg) in Chinese soil. The average Se content in rice grains was 0.059 mg/kg, surpassing the Chinese standard for Se-rich rice (0.04 mg/kg). Se distribution in the paddy soil and rice were the highest in the western and central regions and lowest in the eastern region. Se-enriched rice and Se-enriched rice fields are widely distributed in Dongting Lake area. Seven parent materials significantly influenced soil Se and BCF. Correlation analysis revealed positive correlations between soil Se and soil organic matter (SOM), zinc, altitude, and mean annual precipitation. BCF was positively correlated with pH and mean annual temperature. The Random Forest model highlighted that SOM played a pivotal role in soil Se enrichment, being the most influential factor for both soil and rice enrichment (RR type), whereas pH exerted the most significant influence on soil enrichment without rice enrichment (RN type).

Immunotherapy, prognostic, and tumor biomarker based on pancancer analysis, SMARCD3.

BACKGROUND: SMARCD3 has recently been shown to be an important gene affecting cancer, playing an important role in medulloblastoma and pancreatic ductal adenocarcinoma. Therefore, we conducted this research to investigate the potential involvement of SMARCD3 across cancers and to offer recommendations for future studies. METHODS: Utilizing information on 33 malignancies in the UCSC Xena database, SMARCD3 expression and its prognostic value were assessed. The tumor microenvironment was evaluated with the "CIBERSORT" and "ESTIMATE" algorithms. SMARCD3 and immune-related genes were analyzed using the TISIDB website. The pathways related to the target genes were examined using GSEA. MSI (microsatellite instability), TMB (tumor mutational burden), and immunotherapy analysis were used to evaluate the impact of target genes on the response to immunotherapy. RESULTS: There is heterogeneity in terms of the expression and prognostic value of SMARCD3 among various cancers, but it is a risk factor for many cancers including uterine corpus endometrial cancer (UCEC), renal clear cell carcinoma (KIRC), and gastric adenocarcinoma (STAD). GSEA revealed that SMARCD3 is related to chromatin remodeling and transcriptional activation, lipid metabolism, and the activities of various immune cells. The TMB and MSI analyses suggested that SMARCD3 affects the immune response efficiency of KIRC, LUAD and STAD. Immunotherapy analysis suggested that SMARCD3 may be a potential immunotherapy target. RT-qPCR demonstrated the variation in SMARCD3 expression in KIRC, LUAD, and STAD. CONCLUSION: Our study revealed that SMARCD3 affects the prognosis and immunotherapy response of some tumors, providing a direction for further research on this gene.

Identification Of Endothelial Cell Immune-related Gene Signature for Lung Adenocarcinoma by Integrated Analysis of Single-cell and Bulk RNA Sequencing Data.

Background: The role of endothelial cells in tumor progression is considerable, yet the effect of endothelial cell immune-related genes (EIRGs) is still unclear. This research aimed to scrutinize the prognostic value of EIRGs in lung adenocarcinoma (LUAD) and provide further insights into the abovementioned uncertainties. Methods: After single-cell RNA sequencing (scRNA-seq) samples were obtained from the Gene Expression Omnibus (GEO) database, they were integrated with bulk RNA sequencing data from The Cancer Genome Atlas (TCGA). Prognostic markers were determined and a prognostic model was developed. From this model, a nomogram was constructed. We analyzed the biological mechanism of the EIRGs in LUAD, including functional enrichment, tumor mutational burden (TMB), tumor microenvironment (TME) analyses and drug sensitivity. We validated the signature by validating the external cohort GSE31210 and RT-qPCR. Results: After analyzing the model constructed from eight EIRGs, we observed that high-risk group (HG) LUAD patients (a risk score exceeding 4.65) exhibited unfavorable outcomes according to Kaplan‒Meier survival curves. This outcome was confirmed by GSE31210. The nomogram based on the model demonstrated significant predictive value. HG was influenced primarily by steroid hormone biosynthesis and ECM receptor interactions. The TMB in HGs was greater than that in the LG. Analysis of drug sensitivity revealed the direction for individualized treatment for both risk cohorts. Variations in the expression of EIRGs have been confirmed via RT-qPCR in several LUAD cell lines. Conclusions: The prognostic model and nomogram above are valuable for determining the survival rate and treatment options for LUAD patients.

Gefitinib metabolism-related lncRNAs for the prediction of prognosis, tumor microenvironment and drug sensitivity in lung adenocarcinoma.

The complete compound of gefitinib is effective in the treatment of lung adenocarcinoma. However, the effect on lung adenocarcinoma (LUAD) during its catabolism has not yet been elucidated. We carried out this study to examine the predictive value of gefitinib metabolism-related long noncoding RNAs (GMLncs) in LUAD patients. To filter GMLncs and create a prognostic model, we employed Pearson correlation, Lasso, univariate Cox, and multivariate Cox analysis. We combined risk scores and clinical features to create nomograms for better application in clinical settings. According to the constructed prognostic model, we performed GO/KEGG and GSEA enrichment analysis, tumor immune microenvironment analysis, immune evasion and immunotherapy analysis, somatic cell mutation analysis, drug sensitivity analysis, IMvigor210 immunotherapy validation, stem cell index analysis and real-time quantitative PCR (RT-qPCR) analysis. We built a predictive model with 9 GMLncs, which showed good predictive performance in validation and training sets. The calibration curve demonstrated excellent agreement between the expected and observed survival rates, for which the predictive performance was better than that of the nomogram without a risk score. The metabolism of gefitinib is related to the cytochrome P450 pathway and lipid metabolism pathway, and may be one of the causes of gefitinib resistance, according to analyses from the Gene Set Enrichment Analysis (GSEA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Immunological evasion and immunotherapy analysis revealed that the likelihood of immune evasion increased with risk score. Tumor microenvironment analysis found most immune cells at higher concentrations in the low-risk group. Drug sensitivity analysis found 23 sensitive drugs. Twenty-one of these drugs exhibited heightened sensitivity in the high-risk group. RT-qPCR analysis validated the characteristics of 9 GMlncs. The predictive model and nomogram that we constructed have good application value in evaluating the prognosis of patients and guiding clinical treatment.

Seed pretreatment with brassinosteroids stimulates sunflower immunity against parasitic weed (Orobanche cumana) infection.

Broomrape (Orobanche cumana) negatively affects sunflower, causing severe yield losses, and thus, there is a need to control O. cumana infestation. Brassinosteroids (BRs) play key roles in plant growth and provide resilience to weed infection. This study aims to evaluate the mechanisms by which BRs ameliorate O. cumana infection in sunflower (Helianthus annuus). Seeds were pretreated with BRs (1, 10, and 100 nM) and O. cumana inoculation for 4 weeks under soil conditions. O. cumana infection significantly reduced plant growth traits, photosynthesis, endogenous BRs and regulated the plant defence (POX, GST), BRs signalling (BAK1, BSK1 to BSK4) and synthesis (BRI1, BR6OX2) genes. O. cumana also elevated the levels of malondialdehyde (MDA), hydroxyl radical (OH-), hydrogen peroxide (H2O2) and superoxide (O2 •-) in leaves/roots by 77/112, 63/103, 56/97 and 54/89%, as well as caused ultrastructural cellular damages in both leaves and roots. In response, plants activated a few enzymes, superoxide dismutase (SOD), peroxidase (POD) and reduced glutathione but were unable to stimulate the activity of ascorbate peroxidase (APX) and catalase (CAT) enzymes. The addition of BRs (especially at 10 nM) notably recovered the ultrastructural cellular damages, lowered the production of oxidative stress, activated the key enzymatic antioxidants and induced the phenolic and lignin contents. The downregulation in the particular genes by BRs is attributed to the increased resilience of sunflower via a susceptible reaction. In a nutshell, BRs notably enhanced the sunflower resistance to O. cumana infection by escalating the plant immunity responses, inducing systemic acquired resistance, reducing oxidative or cellular damages, and modulating the expression of BR synthesis or signalling genes.

Treatment strategies for stage IA non-small cell lung cancer: A SEER-based population study.

BACKGROUND: There are various therapeutic methods for treating stage IA (T1N0M0) non-small cell lung cancer (NSCLC), but no studies have systematically assessed multiple treatments to determine the most effective therapy. METHODS: Stage IA NSCLC patient data collected between 2004 and 2018 were gathered from the Surveillance, Epidemiology, and End Results (SEER) database. Treatment modalities included observation, chemotherapy alone (CA), radiation alone (RA), radiation+chemotherapy (RC), surgery alone (SA), surgery+chemotherapy (SC), surgery+radiation (SR) and surgery+radiation+chemotherapy (SRC). Comparisons were made of overall survival (OS) and lung cancer-specific survival (LCSS) among patients based on different therapeutic methods by survival analysis. RESULTS: Ultimately, 89147 patients with stage IA NSCLC between 2004 and 2018 were enrolled in this study. The order of multiple treatment modalities based on the hazard ratio (HR) for OS for the entire cohort revealed the following results: SA (HR: 0.20), SC (HR: 0.25), SR (HR: 0.42), SRC (HR: 0.46), RA (HR: 0.56), RC (HR: 0.72), CA (HR: 0.91) (P<0.001), and observation (HR: Ref). The SA group had the best OS and LCSS, and similar results were found in most subgroup analyses (all P<0.001). The order of surgical modalities based on the HR for OS for the entire cohort revealed the following results: lobectomy (HR: 0.32), segmentectomy (HR: 0.41), wedge resection (HR: 0.52) and local tumor destruction (HR: Ref). Lobectomy had the best effects on OS and LCSS, and similar results were found in all subgroup analyses (all P<0.001). CONCLUSION: SA appeared to be the optimal treatment modality for patients with stage IA NSCLC, and lobectomy was associated with the best prognosis. There may be some indication and selection bias in our study, and the results of this study should be confirmed in a prospective study.

A cluster of putative resistance genes is associated with a dominant resistance to sunflower broomrape.

KEY MESSAGE: The HaOr5 resistance gene is located in a large genomic insertion containing putative resistance genes and provides resistance to O. cumana, preventing successful connection to the sunflower root vascular system. Orobanche cumana (sunflower broomrape) is a parasitic plant that is part of the Orobanchaceae family and specifically infests sunflower crops. This weed is an obligate parasitic plant that does not carry out photosynthetic activity or develop roots and is fully dependent on its host for its development. It produces thousands of dust-like seeds per plant. It possesses a high spreading ability and has been shown to quickly overcome resistance genes successively introduced by selection in cultivated sunflower varieties. The first part of its life cycle occurs underground. The connection to the sunflower vascular system is essential for parasitic plant survival and development. The HaOr5 gene provides resistance to sunflower broomrape race E by preventing the connection of O. cumana to the root vascular system. We mapped a single position of the HaOr5 gene by quantitative trait locus mapping using two segregating populations. The same location of the HaOr5 gene was identified by genome-wide association. Using a large population of thousands of F2 plants, we restricted the location of the HaOr5 gene to a genomic region of 193 kb. By sequencing the whole genome of the resistant line harboring the major resistance gene HaOr5, we identified a large insertion of a complex genomic region containing a cluster of putative resistance genes.

Switching action modes of miR408-5p mediates auxin signaling in rice.

MicroRNAs (miRNAs) play fundamental roles in many developmental and physiological processes in eukaryotes. MiRNAs in plants generally regulate their targets via either mRNA cleavage or translation repression; however, which approach plays a major role and whether these two function modes can shift remains elusive. Here, we identify a miRNA, miR408-5p that regulates AUXIN/INDOLE ACETIC ACID 30 (IAA30), a critical repressor in the auxin pathway via switching action modes in rice. We find that miR408-5p usually inhibits IAA30 protein translation, but in a high auxin environment, it promotes the decay of IAA30 mRNA when it is overproduced. We further demonstrate that IDEAL PLANT ARCHITECTURE1 (IPA1), an SPL transcription factor regulated by miR156, mediates leaf inclination through association with miR408-5p precursor promoter. We finally show that the miR156-IPA1-miR408-5p-IAA30 module could be controlled by miR393, which silences auxin receptors. Together, our results define an alternative auxin transduction signaling pathway in rice that involves the switching of function modes by miR408-5p, which contributes to a better understanding of the action machinery as well as the cooperative network of miRNAs in plants.

Fe(II)-catalyzed phase transformation of Cd(II)-bearing ferrihydrite-kaolinite associations under anoxic conditions: New insights to role of kaolinite and fate of Cd(II).

Cadmium-bearing ferrihydrite-kaolinite associations (Cd-associations) are commonly found in cadmium-contaminated paddy soils in tropical and subtropical regions. In the presence of anaerobic conditions caused by flooding, the creation of Fe(II) can facilitate the transformation of ferrihydrite into secondary Fe (hydr)oxides, resulting in the redistribution of Cd. However, the role of kaolinite in iron oxides transformation and changes in Cd chemical species have largely not been determined. In this study, Cd-associations were prepared for reaction with Fe(II) under anoxic conditions. The results obtained from powder XRD and EXAFS indicated that the presence of kaolinite association noticeably hastened the transformation of ferrihydrite into crystalline goethite. Specific surface area and electrochemical analyses revealed that smaller particle sizes and higher reactivity of ferrihydrite within Cd-associations collaboratively contribute to the acceleration. Chemical analyses demonstrated a significant negative correlation between ferrihydrite-Fe and aqueous-Cd, and a significant positive correlation between crystalline-Fe and residual-Cd. HRTEM analyses indicated that a portion of the Cd was incorporated into the crystal lattices of lepidocrocite and goethite, with the majority of Cd being sequestered within goethite lattice. These findings provide new insights into the roles of clay minerals in the geochemical cycling of Fe and Cd in paddy soils under anoxic conditions.

Differential responses of Brassica napus cultivars to dual effects of magnesium oxide nanoparticles.

Magnesium oxide nanoparticles (MgO NPs) have great potential to enhance the crop productivity and sustainability of agriculture. Still, a thorough understanding is lacking about its essentiality or toxicity and precise dose for the safe cultivation of oilseed crops. Thus, we assessed the dual effects of MgO NPs (control, 5, 10, 20, 40, 80, and 200 mg/L) on the seed germination, growth performance, photosynthesis, total soluble protein, total carbohydrates, oxidative stress markers (hydrogen peroxide as H2O2 and superoxide anion as O2•‒), lipid peroxidation as MDA, and antioxidant defence machinery (SOD, CAT, APX, and GR activities, and GSH levels) of seven different oilseeds (Brassica napus L.) cultivars (ZY 758, ZD 649, ZD 635, ZD 619, GY 605, ZD 622, and ZD 630). Our findings revealed that low doses of MgO NPs (mainly at 10 mg/L) markedly boosted the seed germination, plant growth (shoot and root lengths) (15‒22%), and biomass (fresh and dry) (11‒19%) by improving the levels of photosynthetic pigments (14‒27%), net photosynthetic rate, stomatal conductance, photosynthetic efficiency (Fv/Fm), total soluble protein and total carbohydrates (16‒36%), antioxidant defence, and reducing the oxidative stress in B. napus tissues. Among all B. napus cultivars, these beneficial effects of MgO NPs were pronounced in ZD 635. ile, elevated levels of MgO NPs (particularly at 200 mg/L) induced oxidative stress, impaired antioxidant scavenging potential, photosynthetic inhibition, protein oxidation, and carbohydrate degradation and lead to inhibit the plant growth attributes. These inhibitory effects were more pronounced in ZD 622. Collectively, low-dose MgO NPs reinforced the Mg contents, protected the plant growth, photosynthesis, total soluble carbohydrates, enzyme activities, and minimized the oxidative stress. While, the excessive MgO NP levels impaired the above-reported traits. Overall, ZD 622 was highly susceptible to MgO NP toxicity and ZD 635 was found most tolerant to MgO NP toxicity.

Silicon dioxide nanoparticles enhance plant growth, photosynthetic performance, and antioxidants defence machinery through suppressing chromium uptake in Brassica napus L.

Chromium (Cr) is a highly toxic heavy metal that is extensively released into the soil and drastically reduces plant yield. Silicon nanoparticles (Si NPs) were chosen to mitigate Cr toxicity due to their ability to interact with heavy metals and reduce their uptake. This manuscript explores the mechanisms of Cr-induced toxicity and the potential of Si NPs to mitigate Cr toxicity by regulating photosynthesis, oxidative stress, and antioxidant defence, along with the role of transcription factors and heavy metal transporter genes in rapeseed (Brassica napus L.). Rapeseed plants were grown hydroponically and subjected to hexavalent Cr stress (50 and 100 µM) in the form of K2Cr2O7 solution. Si NPs were foliar sprayed at concentrations of 50, 100 and 150 µM. The findings showed that 100 µM Si NPs under 100 µM Cr stress significantly increased the leaf Si content by 169% while reducing Cr uptake by 92% and 76% in roots and leaves, respectively. The presence of Si NPs inside the plant leaf cells was confirmed by using energy-dispersive spectroscopy, inductively coupled plasma‒mass spectrometry, and confocal laser scanning microscopy. The study's findings showed that Cr had adverse effects on plant growth, photosynthetic gas exchange attributes, leaf mesophyll ultrastructure, PSII performance and the activity of enzymatic and nonenzymatic antioxidants. However, Si NPs minimized Cr-induced toxicity by reducing total Cr accumulation and decreasing oxidative damage, as evidenced by reduced ROS production (such as H2O2 and MDA) and increased enzymatic and nonenzymatic antioxidant activities in plants. Interestingly, Si NPs under Cr stress effectively increased the NPQ, ETR and QY of PSII, indicating a robust protective response of PSII against stress. Furthermore, the enhancement of Cr tolerance facilitated by Si NPs was linked to the upregulation of genes associated with antioxidant enzymes and transcription factors, alongside the concurrent reduction in metal transporter activity.

Scalable fabrication of free-standing and integrated electrodes with commercial level of areal capacity for aqueous zinc-ion batteries.

Aqueous zinc-ion batteries (AZIBs) present a highly promising avenue for the deployment of grid-scale energy storage systems. However, the electrodes fabricated through conventional methodologies not only suffer from insufficient mass loadings, but also are susceptible to exfoliation under deformations. Herein, a scalable and cost-effective freezing-thawing method is developed to construct free-standing and integrated electrode, comprising H11Al2V6O23.2, carboxymethyl cellulose, and carbon nanotubes. Benefiting from the synergistic effect of these components, the resultant electrode exhibits superior flexibility and robustness, large tensile strength, exceptional electrical conductivity, and favorable electrolyte wettability. Under a large mass loading of 8 mg cm-2 (corresponding to a negative/positive electrode capacity ratio of 2.09), the electrode achieves remarkable capacity of 345.2 mAh/g (2.76 mAh cm-2) at 0.2 A/g and maintains 235.2 mAh/g (1.88 mAh cm-2) at 4 A/g, while sustaining an impressive capacity retention of 97.7 % over 5000 cycles. These considerably outperform conventional electrodes employing traditional binders. Even at an elevated mass loading of 14 mg cm-2 or when operated at a low temperature of - 30 °C, the electrode continues to deliver excellent electrochemical performance (e.g., extraordinary areal capacity of 4.32 mAh cm-2). In addition, the electrode owns outstanding tolerance to external forces. This research contributes to our understanding of the pivotal challenges within the realm of AZIB technology.

Factors controlling accumulation and bioavailability of selenium in paddy soils: A case study in Luxi County, China.

Selenium (Se) accumulation in rice (Oryza sativa L.) has become a major global concern. Se offers multiple health benefits in humans; however, its inadequate or excessive intake can be harmful. Therefore, determining the factors driving Se abundance and bioavailability in paddy soils is essential to ensure the safety of human Se intake. This study investigated the accumulation, bioavailability, and distribution of Se in 820 paddy soil and rice grain samples from Luxi County, China to assess how soil properties (soil organic matter [SOM], cation exchange capacity [CEC], and pH), geographical factors (parent materials, elevation, and mean annual precipitation [MAP] and temperature [MAT]), and essential micronutrients (copper [Cu], zinc [Zn], and manganese [Mn]) govern Se accumulation and bioavailability in paddy soils. Results showed that the average soil Se content was 0.36 mg kg-1, which was higher than that in China (0.29 mg kg-1). Alternatively, the average rice grain Se content was 0.032 mg kg-1, which was lower than the minimum allowable content in Se-rich rice grains (0.04 mg kg-1). Five studied parent materials all had a significant effect on soil Se content but had little effect on Se bioavailability (p < 0.05). CEC, elevation, and SOM, as well as the soil contents of Cu, Zn, and Mn were positively correlated with soil Se content, but pH, MAP, and MAT were negatively correlated. Correspondingly, Se bioavailability was negatively correlated with SOM and soil Zn content, but positively correlated with MAP and grain contents of Cu, Zn, and Mn. Furthermore, partial least squares path analysis revealed the interactive impacts of the influencing factors on Se accumulation and bioavailability in soils. On this basis, prediction models were established to predict Se accumulation and bioavailability in paddy soils, thereby providing theoretical support for developing efficient control measures to meet Se challenges in agriculture.

Antidepressant duloxetine hydrochloride protects against ovariectomy-induced bone loss in mice by inhibiting osteoclast differentiation.

BACKGROUND: Several studies have reported the association between osteoporosis and major depressive disorder (MDD) as well as the use of antidepressants. However, it remains to be elucidated whether these associations are related to exposure to antidepressants, a consequence of a disease process, or a combination of both. METHODS: This study investigates the independent effect of the antidepressant duloxetine hydrochloride (DH) on ovariectomy-induced bone loss in mice. One week after ovariectomy, the treated mice received DH. To explore the mechanism underlying the rescue of bone loss, bone marrow cells were isolated from mouse femurs and tibias, and macrophages extracted from them were induced to become osteoclasts in vitro while being treated with DH. Subsequently, the osteoclasts underwent Bulk RNA-Seq to reveal the involved signaling pathways. The results of the bioinformatic analysis were then validated through in vitro experiments. RESULTS: The in vivo experiments demonstrated that DH treatment compromised ovariectomy-induced bone loss after 7 weeks. The in vitro experiments suggested that DH treatment attenuated osteoclast differentiation via the MAPKs/NFATc1 signaling pathway. CONCLUSION: The findings from this study suggest that DH, instead of causing bone mass loss, may assist in alleviating postmenopausal osteoporosis. These results can serve as a reference for the clinical treatment of patients with perimenopausal or postmenopausal depression using antidepressants.

Segmentation and Phenotype Calculation of Rapeseed Pods Based on YOLO v8 and Mask R-Convolution Neural Networks.

Rapeseed is a significant oil crop, and the size and length of its pods affect its productivity. However, manually counting the number of rapeseed pods and measuring the length, width, and area of the pod takes time and effort, especially when there are hundreds of rapeseed resources to be assessed. This work created two state-of-the-art deep learning-based methods to identify rapeseed pods and related pod attributes, which are then implemented in rapeseed pots to improve the accuracy of the rapeseed yield estimate. One of these methods is YOLO v8, and the other is the two-stage model Mask R-CNN based on the framework Detectron2. The YOLO v8n model and the Mask R-CNN model with a Resnet101 backbone in Detectron2 both achieve precision rates exceeding 90%. The recognition results demonstrated that both models perform well when graphic images of rapeseed pods are segmented. In light of this, we developed a coin-based approach for estimating the size of rapeseed pods and tested it on a test dataset made up of nine different species of Brassica napus and one of Brassica campestris L. The correlation coefficients between manual measurement and machine vision measurement of length and width were calculated using statistical methods. The length regression coefficient of both methods was 0.991, and the width regression coefficient was 0.989. In conclusion, for the first time, we utilized deep learning techniques to identify the characteristics of rapeseed pods while concurrently establishing a dataset for rapeseed pods. Our suggested approaches were successful in segmenting and counting rapeseed pods precisely. Our approach offers breeders an effective strategy for digitally analyzing phenotypes and automating the identification and screening process, not only in rapeseed germplasm resources but also in leguminous plants, like soybeans that possess pods.

Five or more gender- and size-diverse customizations of distal femur prostheses are needed to improve fit for Chinese knees.

PURPOSE: Mismatch between partial imported prostheses and Chinese anatomy affects the clinical outcome of the procedure. The purpose of this study was to measure the anatomical dimensions of Chinese distal femurs to provide guidance for the design of more compatible distal femoral prostheses. METHODS: A total of 406 healthy distal femurs were reconstructed and measured. Consistency of these measurements and differences in sides, gender, and populations were examined. Parameter correlations were analyzed, and pairs with strong correlations underwent linear regression analysis. The design of distal femoral prostheses was referenced from the results of K-means and hierarchical clustering analysis. RESULTS: Ten parameters were measured, including the trans-epicondylar axis, width of the distal femur (ML), anteroposterior diameter of the distal femur (AP), etc. The intra-class correlation coefficient ranged from 0.795 to 0.999 for intra-observer consistency, and from 0.796 to 0.998 for inter-observer consistency. Males exhibited significantly larger parameters than females, except for the posterior condylar angle (all P values < 0.05). Compared to other populations, substantial differences were observed for most parameters, such as ML, AP, width of lateral femoral condyle, etc. (all P values < 0.05). Clustering analysis suggested that distal femoral prostheses should include at least five sizes to adequately accommodate the sampled population. ML sizes for males were 68, 70, 83, 73, and 89 mm, and for females 64, 65, 71, 67, and 77 mm. AP sizes for males were 56, 60, 60, 64, and 64 mm, and for females 48, 52, 54, 57, and 58 mm. CONCLUSIONS: Chinese distal femur morphology, as analyzed using 3D techniques, varies significantly between genders and when compared with international data. For improved patient fit, the creation of five or more distal femur prostheses, diversified by gender and size and informed by the associated morphological parameters, is recommended. LEVEL OF EVIDENCE: IV.