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Background: The patellar height index is important; however, the measurement procedures are time-consuming and prone to significant variability among and within observers. We developed a deep learning-based automatic measurement system for the patellar height and evaluated its performance and generalization ability to accurately measure the patellar height index. Methods: We developed a dataset containing 3,923 lateral knee X-ray images. Notably, all X-ray images were from three tertiary level A hospitals, and 2,341 cases were included in the analysis after screening. By manually labeling key points, the model was trained using the residual network (ResNet) and high-resolution network (HRNet) for human pose estimation architectures to measure the patellar height index. Various data enhancement techniques were used to enhance the robustness of the model. The root mean square error (RMSE), object keypoint similarity (OKS), and percentage of correct keypoint (PCK) metrics were used to evaluate the training results. In addition, we used the intraclass correlation coefficient (ICC) to assess the consistency between manual and automatic measurements. Results: The HRNet model performed excellently in keypoint detection tasks by comparing different deep learning models. Furthermore, the pose_hrnet_w48 model was particularly outstanding in the RMSE, OKS, and PCK metrics, and the Insall–Salvati index (ISI) automatically calculated by this model was also highly consistent with the manual measurements (intraclass correlation coefficient [ICC], 0.809–0.885). This evidence demonstrates the accuracy and generalizability of this deep learning system in practical applications. Conclusion: We successfully developed a deep learning-based automatic measurement system for the patellar height. The system demonstrated accuracy comparable to that of experienced radiologists and a strong generalizability across different datasets. It provides an essential tool for assessing and treating knee diseases early and monitoring and rehabilitation after knee surgery. Due to the potential bias in the selection of datasets in this study, different datasets should be examined in the future to optimize the model so that it can be reliably applied in clinical practice. Trial registration: The study was registered at the Medical Research Registration and Filing Information System (medicalresearch.org.cn) MR-61-23-013065. Date of registration: May 04, 2023 (retrospectively registered). [ABSTRACT FROM AUTHOR]

Multiple Sclerosis (MS) is an immune-related disease and the relationship between MS and cancer has raised attention. Previous studies of the relationship between MS and cancer have reached conflicting conclusions. In this study, the two-sample MR method is used to investigate whether MS has a causal correlation with cancers and offer scientific evidence for cancer prevention. Single nucleotide polymorphisms (SNPs) related to MS were obtained from the genome-wide association study (GWAS) based on International Multiple Sclerosis Genetics Consortium (IMSGC) and SNPs related to 15 types of cancers were obtained from the GWASs based on UK Biobank. Inverse variance weighted (IVW) method was mainly used to assess causal effects. Sensitivity analyses were conducted with Cochran's Q-test, MR Egger intercept, leave-one-out test, and MR Steiger method. IVW analysis showed that MS was only associated with a marginal increased risk of cervical cancer (OR 1.0004, 95% CI 1.0002–1.0007, p = 0.0003). Sensitivity analyses showed that the results of MR analysis were robust and found no heterogeneity, no pleiotropy, and no reverse causation. In conclusion, this study finds no causal relationship between MS and 15 types of cancers except cervical cancer. [ABSTRACT FROM AUTHOR]

The PTEN-induced kinase 1 (PINK1)-Parkin pathway plays a vital role in maintaining a healthy pool of mitochondria in higher eukaryotic cells. While the downstream components of this pathway are well understood, the upstream triggers remain less explored. In this study, we conducted an extensive analysis of inhibitors targeting various mitochondrial electron transport chain (ETC) complexes to investigate their potential as activators of the PINK1–Parkin pathway. We identified cloflucarban, an antibacterial compound, as a novel pathway activator that simultaneously inhibits mitochondrial complexes III and V, and V. RNA interference (RNAi) confirmed that the dual inhibition of these complexes activates the PINK1–Parkin pathway. Intriguingly, we discovered that albumin, specifically bovine serum albumin (BSA) and human serum albumin (HSA) commonly present in culture media, can hinder carbonyl cyanide m-chlorophenyl hydrazone (CCCP)-induced pathway activation. However, cloflucarban's efficacy remains unaffected by albumin, highlighting its reliability for studying the PINK1–Parkin pathway. This study provides insights into the activation of the upstream PINK1–Parkin pathway and underscores the influence of culture conditions on research outcomes. Cloflucarban emerges as a promising tool for investigating mitochondrial quality control and neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Disruption of the epithelial-mesenchymal transition (EMT) of activated lung cells is an important strategy to inhibit the progression of idiopathic pulmonary fibrosis (IPF). The present study investigated the role of exosomes derived from airway basal cells on EMT of lung cells and elucidate the underlying mechanism. Exosomes were characterized by nanoparticle tracking analysis, transmission electron microscopy imaging and markers detection. The role of exosome on the EMT of lung epithelial cells and lung fibroblasts induced by TGF-β1 was detected. RNA sequencing screened dysregulated genes in exosome-treated group, followed by the bioinformatical analysis. One of the candidates, anoctamin-1 (ANO1), was selected for further gain-and-loss phenotype assays. A bleomycin-induced pulmonary fibrosis model was used to evaluate the treatment effect of exosomes. Exosomes were round-like and positively expressed CD63 and tumor susceptibility gene 101 protein. Treatment with exosomes inhibited the EMT of lung cells activated by TGF-β1. 4158 dysregulated genes were identified in exosome-treated group under the threshold of |log2 fold-change| value >1 and they were involved in the metabolism of various molecules, as well as motility-related biological processes. A key gene, ANO1, was verified by reverse transcription-quantitative PCR, whose overexpression induced the EMT of lung cells. By contrast, ANO1 knockdown reversed the EMT induced by TGF-β1. In vivo assay indicated that exosome treatment ameliorated pulmonary fibrosis and inhibited the upregulation of ANO1 induced by bleomycin. In conclusion, airway basal cell-derived exosomes suppressed the EMT of lung cells via the downregulation of ANO1. These exosomes represent a potential therapeutic option for patients with IPF. [ABSTRACT FROM AUTHOR]

[Display omitted] • The incorporation of Al provided abundant As 2 O 3 adsorption sites. • Facilitates the dissociation of O 2 and promotes reaction with chained As 2 O 3. • Lower activation energy for the oxidation of As(III) to As(V). • Transformation of the Ca site from physisorption sites to chemisorption sites. Doping techniques have the potential to enhance the adsorption and oxidation of As 2 O 3 by metal oxides for the augmentation of arsenic capture. However, the mechanisms of this facilitating effect, especially concerning the oxidation of As 2 O 3 , require further exploration. This study focuses on the effect of Al doping on As 2 O 3 adsorption and oxidation through experimental and density functional theory calculations. The introduction of aluminum increases the specific surface area and stimulates charge transfer, converting Ca atoms into new As 2 O 3 adsorption sites with strong adsorption capacity. The arsenic capture capacity of Al 2 O 3 /CaO is almost twice that of CaO when the molar ratio of Al and Ca is 1:6. For arsenic oxidation, Al doping promotes the dissociation of O 2 adsorbed on the sorbent surface, making it more prone to react with As 2 O 3. This catalytic effect lowered the activation energy for the conversion of As(III) to As(V), increasing the oxidation efficiency by 2–10%. These results serve as valuable references for the development of efficient arsenic sorbents. [ABSTRACT FROM AUTHOR]

Over the past decades, complex deposition patterns after the evaporation of particle-laden droplets spark intense interest in interpreting the formation of deposition patterns due to their numerous applications in biomedicine, ink-jet printing, biopsy, etc. This work experimentally studies the formation of deposition patterns during evaporation of the magnetic nanofluid (MNF) droplet stands on a smooth glass/hydrophobic surface at different substrate temperatures. A CCD camera mounted on the microscopy is used to capture the process of droplet evaporation. An infrared camera is applied to quantify the temperature distribution along the vapour-liquid interface of the evaporating droplet. Additionally, 3 μm sized microbeads are applied to track the flow motion of the solute inside for different temperatures. The evaporation of sessile droplets has been conducted by controlling substrate temperature, which ranges from 10 °C to 70 °C. The experimental results show that there are three distinct patterns with the increasing temperature, namely a uniform pattern, a typical 'coffee ring' pattern, and a dual ring pattern. The experimental results show that Marangoni flow becomes essential for the formation of a secondary ring pattern with increasing substrate temperatures. This study shows that controlling substrate temperature is an efficient and simple method to control the formation of the sessile droplet. [ABSTRACT FROM AUTHOR]

Cancer driver genes (CDGs) and the driver mutations disrupt the homeostasis of numerous critical cell activities, thereby playing a critical role in tumor initiation and progression. In this study, integrative bioinformatics analyses were performed based on a series of online databases, aiming to identify driver genes with high frequencies of mutations in head and neck cancers. Higher myeloma overexpressed (MYEOV) genetic variation frequency and expression level were connected to a poorer prognosis in head and neck cancer patients. MYEOV was dramatically upregulated within head and neck tumor samples and cells. Consistently, MYEOV overexpression remarkably enhanced the aggressiveness of head and neck cancer cells by promoting colony formation, cell invasion, and cell migration. Conversely, MYEOV knockdown attenuated cancer cell aggressiveness and inhibited tumor growth and metastasis in the oral orthotopic tumor model. In conclusion, MYEOV is overexpressed in head and neck cancer, with greater mutation frequencies correlating to a poorer prognosis in head and neck cancer patients. MYEOV serves as an oncogene in head and neck cancer through the promotion of tumor cell colony formation, invasion, and migration, as well as promoting tumor growth and metastasis in the oral orthotopic tumor model. [ABSTRACT FROM AUTHOR]

Soil fungi are involved in the decomposition of organic matter, and they alter soil structure and physicochemical properties and drive the material cycle and energy flow in terrestrial ecosystems. Fungal community assembly processes were dissimilar in different soil layers and significantly affected soil microbial community function and plant growth. Grazing exclusion is one of the most common measures used to restore degraded grasslands worldwide. However, changes in soil fungal community characteristics during grazing exclusion in different types of grasslands are unknown. Here, we investigated the effects of a 9‐year grazing exclusion on soil properties, fungal community composition, and diversity in three grassland types (temperate desert, temperate steppe, and mountain meadow). The results showed that (1) in the 0–5 cm soil layer, grazing exclusion significantly increased the differences in SWC, SOC, KN, and N:P among the three grassland types, while the final pH, BD, TP, C:N, and C:P values were consistent with the results before exclusion. In the 5–10 cm soil layer, grazing exclusion significantly increased total phosphorus (TP) in temperate deserts by 34.1%, while significantly decreasing bulk density (BD) by 9.8% and the nitrogen: phosphorus ratio (N:P) by 47.1%. (2) The soil fungal community composition differed among the grassland types, For example, significant differences were found among the three grassland types for the Glomeromycota and Mucoromycota. (3) Under the influence of both grazing exclusion and grassland type, there was no significant change in soil fungal alpha diversity, but there were significant differences in fungal beta diversity. (4) Grassland type was the most important factor influencing changes in fungal community diversity, and vegetation cover and soil kjeldahl nitrogen were the main factors influencing fungal diversity. Our research provides a long‐term perspective for better understanding and managing different grasslands, as well as a better scientific basis for future research on grass–soil–microbe interactions. [ABSTRACT FROM AUTHOR]