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Abstract Endothelial cell (EC) senescence and vascular aging are important hallmarks of chronic metabolic diseases. An improved understanding of the precise regulation of EC senescence may provide novel therapeutic strategies for EC and vascular aging-related diseases. This study examined the potential functions of Spinster homolog 2 (SPNS2) in EC senescence and vascular aging. We discovered that the expression of SPNS2 was significantly lower in older adults, aged mice, hydrogen peroxide-induced EC senescence models and EC replicative senescence model, and was correlated with the expression of aging-related factors. in vivo experiments showed that the EC-specific knockout of SPNS2 markedly aggravated vascular aging by substantially, impairing vascular structure and function, as evidenced by the abnormal expression of aging factors, increased inflammation, reduced blood flow, pathological vessel dilation, and elevated collagen levels in a naturally aging mouse model. Moreover, RNA sequencing and molecular biology analyses revealed that the loss of SPNS2 in ECs increased cellular senescence biomarkers, aggravated the senescence-associated secretory phenotype (SASP), and inhibited cell proliferation. Mechanistically, silencing SPNS2 disrupts pyruvate metabolism homeostasis via pyruvate kinase M (PKM), resulting in mitochondrial dysfunction and EC senescence. Overall, SPNS2 expression and its functions in the mitochondria are crucial regulators of EC senescence and vascular aging.

Abstract Objectives To analyze the lung structure of small airway dysfunction (SAD) defined by spirometry and parametric response mapping (PRM) using high-resolution computed tomography (HRCT), and to analyze the predictive factors for SAD. Methods A prospective study was conducted with 388 participants undergoing pulmonary function test (PFT) and inspiratory-expiratory chest CT scans. The clinical data and HRCT assessments of SAD patients defined by both methods were compared. A prediction model for SAD was constructed based on logistic regression. Results SAD was defined in 122 individuals by spirometry and 158 by PRM. In HRCT visual assessment, emphysema, tree-in-bud sign, and bronchial wall thickening have higher incidence in SAD defined by each method. (p

Purpose: Explore the causal relationship between the gut microbiota and erectile dysfunction (ED) at phylum, class, order, family, and genus levels, and identify specific pathogenic bacteria that may be associated with the onset and progression of ED. Materials and Methods: The genetic variation data of 196 human gut microbiota incorporated in our study came from the human gut microbiome Genome Wide Association Studies (GWAS) dataset released by the MiBioGen Consortium. The GWAS statistics for ED were extracted from one study by Bovijn et al., which included 223,805 participants of European ancestry, of whom 6,175 were diagnosed with ED. Subsequently, Mendelian randomization (MR) analysis was carried out to explore whether a causal relationship exists between the gut microbiota and ED. Additionally, bidirectional MR analysis was performed to examine the directionality of the causal relationship. Results: Through MR analysis, we found that family Lachnospiraceae (odds ratio [OR]: 1.27, 95% confidence interval [CI]: 1.05–1.52, p=0.01) and its subclass genus LachnospiraceaeNC2004 group (OR: 1.17, 95% CI: 1.01–1.37, p=0.04) are associated with a higher risk of ED. In addition, genus Oscillibacter (OR: 1.17, 95% CI: 1.02–1.35, p=0.03), genus Senegalimassilia (OR: 1.32, 95% CI: 1.06–1.64, p=0.01) and genus Tyzzerella3 (OR: 1.14, 95% CI: 1.02–1.27, p=0.02) also increase the risk of ED. In contrast, the inverse variance weighted estimate of genus RuminococcaceaeUCG013 (OR: 0.77, 95% CI: 0.61–0.96, p=0.02) suggests that it has a protective effect against the occurrence of ED. Conclusions: This study preliminarily identified 6 bacterial taxa that may have a causal relationship with ED, including family Lachnospiraceae, genus Lachnospiraceae NC2004 group, Oscillibacter, Senegalimassilia, Tyzzerella 3 and Ruminococcaceae UCG013. These identified important bacterial taxa may serve as candidates for microbiome intervention in future ED clinical trials.

This study reports on the results of a semester-long Chinese-American telecollaborative exchange via WeChat, in which students from China and the U.S. shared thematically similar songs in their respective languages and discussed relevant cultural topics that were suggested by the students. Various types of qualitative data collected from the exchange (i.e. WeChat group discussion transcripts, videoconferencing audio recordings, final reflection journals, and end-of-semester interviews) showed that the students participated actively in the program and were able to engage in in-depth conversations on various topics with their partners through WeChat group discussion and one-on-one videoconferencing. Many students attributed their positive experience to the intrinsic ability of music to engage college students. In order to evaluate the students' intercultural learning, Byram's intercultural competence assessment model was adopted to guide the data analysis. Results showed that the students demonstrated evidence of developing four types of intercultural competences during the exchange: interest in knowing other people's way of life and introducing one's own culture to others, knowledge about one's own and others' culture for intercultural communication, ability to change perspective, and knowledge about the intercultural communication process, with particularly overwhelming evidence indicating the prominence of the first two types.

Guided tissue regeneration (GTR) has been widely used in the periodontal treatment of intrabony and furcation defects for nearly four decades. The treatment outcomes have shown effectiveness in reducing pocket depth, improving attachment gain and bone filling in periodontal tissue. Although applying GTR could reconstruct the periodontal tissue, the surgical indications are relatively narrow, and some complications and race ethic problems bring new challenges. Therefore, it is challenging to achieve a consensus concerning the clinical benefits of GTR. With the appearance of stem cell-based regenerative medicine, mesenchymal stem/stromal cells (MSCs) have been considered a promising cell resource for periodontal regeneration. In this review, we highlight preclinical and clinical periodontal regeneration using MSCs derived from distinct origins, including non-odontogenic and odontogenic tissues and induced pluripotent stem cells, and discuss the transplantation procedures, therapeutic mechanisms, and concerns to evaluate the effectiveness of MSCs.

Abstract Objective Achieving textbook outcome (TO) implies a smooth recovery post-operation without specified composite complications. This study aimed to evaluate TO in laparoscopic pancreaticoduodenectomy (LPD) and identify independent risk factors associated with achieving TO. Methods We conducted a retrospective analysis of data from a randomized controlled trial on LPD at West China Hospital (ChiCTR1900026653). Patients were categorized into the TO and non-TO groups. Perioperative variables were compared between these groups. Multivariate logistic regression was utilized to identify the risk factors. Results A total of 200 consecutive patients undergoing LPD were included in this study. TO was achieved in 82.5% (n = 165) of the patients. Female patients (OR: 2.877, 95% CI: 1.219–6.790; P = 0.016) and those with a hard pancreatic texture (OR: 2.435, 95% CI: 1.018–5.827; P = 0.046) were associated with an increased likelihood of achieving TO. Conclusions TO can be achieved in more than 80% of patients in a high-volume LPD center. Independent risk factors associated with achieving TO included gender (male) and pancreatic texture (soft).

Abstract Objective Shift work and Shift Work Sleep Disorder (SWSD) are known to affect the secretion of several neurotransmitters and hormones associated with premature ejaculation (PE). However, their specific influence on the regulation of male ejaculation remains unclear. This study explores the relationship between shift work, SWSD, and PE. Methods From April to October 2023, a cross-sectional survey was conducted across five regions of China to explore the work schedules, sleep quality, and sexual function of male workers. Participants' sleep quality was evaluated using a validated SWSD questionnaire, and their erectile function and ejaculatory control were assessed with the International Inventory of Erectile Function (IIEF-5) scores and Premature Ejaculation Diagnostic Tool (PEDT) scores, respectively. Univariate and multivariate linear regression analyses were employed to identify risk factors associated with PE. Confounders were controlled using multiple regression models, and clinical prediction models were developed to predict PE onset and assess the contribution of risk factors. Results The study included 1239 eligible participants, comprising 840 non-shift workers and 399 shift workers (148 with SWSD and 251 without SWSD). Compared to non-shift working males, those involved in shift work (β 1.58, 95% CI 0.75 – 2.42, p

Rock sheds is one of the main engineering solutions for mitigating rockfall disaster in the mountainous regions of western China. Typically, the roof of a rock shed is covered with a soil cushion composed of sand or gravel. The function of soil cushion is to avoid the direct impact of rockfall on the shed and absorb the impact force of the falling rocks. For a long time, there has been limited studies on the influence of soil cushion thickness on its buffering effect, leading to a lack of a unified theory guiding the design of soil cushion thickness. In this study, the discrete element method was employed to establish a numerical model of rockfall impacting onto soil cushion, and the influence of cushion thickness and rockfall falling height on the buffering characteristics of soil cushion for the rockfall impact force was investigated. The results show that there is a power function relationship between the peak of rockfall impact force and the rockfall falling height, along with a linear positive correlation between the peak of roof center force and the rockfall falling height. The peak of rockfall impact force decreases with increasing cushion thickness. Once the cushion thickness reaches 1.0 times of the diameter of rockfall, the peak of rockfall impact force becomes independent of cushion thickness as cushion thickness increases, the ratio of the peak bottom center force to the peak rockfall impact force decreases, indicating an enhancement in the soil cushion's buffering effect. However, when the cushion thickness reaches 1.5 times of the rockfall diameter, the enhancement in buffering effect becomes less significant. Therefore, the recommended cushion thickness is 1.5 times the rockfall diameter.

Abstract Pancreatic ductal adenocarcinoma (PDAC) is not sensitive to most chemotherapy drugs, leading to poor chemotherapy efficacy. Recently, Trametinib and Palbociclib have promising prospects in the treatment of pancreatic cancer. This article aims to explore the effects of Trametinib on pancreatic cancer and address the underlying mechanism of resistance as well as its reversal strategies. The GDSC (Genomics of Drug Sensitivity in Cancer) and CTD2 (Cancer Target Discovery and Development) were utilized to screen the potential drug candidate in PDAC cell lines. The dose-increase method combined with the high-dose shock method was applied to induce the Trametinib-resistant PANC-1 and MIA PaCa-2 cell lines. The CCK8 proliferation assay, colony formation assay, flow cytometry, and western blot were conducted to verify the inhibitory effect of Trametinib and Palbociclib. RNA-seq was performed in resistant PDAC cell lines to find the differential expression genes related to drug resistance and predict pathways leading to the reversal of Trametinib resistance. The GDSC and CTD2 database screening revealed that Trametinib demonstrates a significant inhibitory effect on PDAC. We found that Trametinib has a lower IC50 than Gemcitabine in PDAC cell lines. Both Trametinib and Gemcitabine can decrease the proliferation capacity of pancreatic cells, induce cell cycle arrest, and increase apoptosis. Simultaneously, the phosphorylation of the AKT and ERK pathways were inhibited by the treatment of Trametinib. In addition, the RNA-seq of Trametinib-induced resistance PDAC cell lines reveals that the cyclin-dependent kinase (CDK)-RB-E2F regulatory axis and G2/M DNA damage checkpoint might lead the drug resistance. Besides, the combination of Trametinib with Palbociclib could inhibit the proliferation and cell cycle of both resistant cells lines and also restore the sensitivity of drug-resistant cells to Trametinib. Last but not least, the interferon-α and interferon-γ expression were upregulated in resistance cell lines, which might lead to the reversal of drug resistance. The study shows Trametinib has a critical inhibitory effect on PDAC. Besides, the combination of Trametinib with Palbociclib can inhibit the proliferation of PDAC-resistant cells.

Abstract Background Fibrodysplasia ossificans progressiva (FOP) is a rare genetic disease caused by a gain-of-function mutation in ACVR1, which is a bone morphogenetic protein (BMP) type I receptor. Moreover, it causes progressive heterotopic ossification (HO) in connective tissues. Using FOP patient-derived induced pluripotent stem cells (FOP-iPSCs) and mouse models, we elucidated the underlying mechanisms of FOP pathogenesis and identified a candidate drug for FOP. Methods In the current study, healthy mesenchymal stem/stromal cells derived from iPSCs (iMSCs) expressing ACVR2B-Fc (iMSCACVR2B-Fc), which is a neutralizing receptobody, were constructed. Furthermore, patient-derived iMSCs and FOP mouse model (ACVR1R206H, female) were used to confirm the inhibitory function of ACVR2B-Fc fusion protein secreted by iMSCACVR2B-Fc on BMP signaling pathways and HO development, respectively. Results We found that secreted ACVR2B-Fc attenuated BMP signaling initiated by Activin-A and BMP-9 in both iMSCs and FOP-iMSCs in vitro. Transplantation of ACVR2B-Fc-expressing iMSCs reduced primary HO in a transgenic mouse model of FOP. Notably, a local injection of ACVR2B-Fc-expressing iMSCs and not an intraperitoneal injection improved the treadmill performance, suggesting compound effects of ACVR2B-Fc and iMSCs. Conclusions These results offer a new perspective for treating FOP through stem cell therapy.

AbstractBackground Previous research has shown that testosterone deficiency (TD) increases the risk of anemia, but it is unclear whether anemia affects testosterone levels. This study investigated the influence of anemia on testosterone levels.Methods Utilizing data from six NHANES cycles, including demographic, testosterone levels, and hemoglobin concentrations, we employed multivariable-adjusted logistic regression to investigate the relationship between anemia and testosterone levels. Moreover, a two-sample Mendelian randomization (MR) study employing genome-wide association study (GWAS) data examined the causal relationship. Kaplan–Meier survival estimation was used to compared the overall survival (OS) of anemic and nonanemic patients with low testosterone and normal testosterone levels.Results The inclusion of 21,786 participants (2318 with anemia and19,468 without anemia) revealed that nonanemic patients exhibited higher testosterone levels than did anemic patients (β = 22.616, 95% CI: 3.873–41.359, p = 0.01807). MR analysis confirmed anemia as a cause of TD (OR = 1.045, 95% CI: 1.020–1.071, p

IntroductionInherited retinal diseases (IRDs) affect ∼4.5 million people worldwide. Elusive pathogenic variants in over 280 genes are associated with one or more clinical forms of IRDs. It is necessary to understand the complex interaction among retinal cell types and pathogenic genes by constructing a regulatory network. In this study, we attempt to establish a panoramic expression view of the cooperative work in retinal cells to understand the clinical manifestations and pathogenic bases underlying IRDs.MethodsSingle-cell RNA sequencing (scRNA-seq) data on the retinas from 35 retina samples of 3 species (human, mouse, and zebrafish) including 259,087 cells were adopted to perform a comparative analysis across species. Bioinformatic tools were used to conduct weighted gene co-expression network analysis (WGCNA), single-cell regulatory network analysis, cell–cell communication analysis, and trajectory inference analysis.ResultsThe cross-species comparison revealed shared or species-specific gene expression patterns at single-cell resolution, such as the stathmin family genes, which were highly expressed specifically in zebrafish Müller glias (MGs). Thirteen gene modules were identified, of which nine were associated with retinal cell types, and Gene Ontology (GO) enrichment of module genes was consistent with cell-specific highly expressed genes. Many IRD genes were identified as hub genes and cell-specific regulons. Most IRDs, especially the retinitis pigmentosa (RP) genes, were enriched in rod-specific regulons. Integrated expression and transcription regulatory network genes, such as congenital stationary night blindness (CSNB) genes GRK1, PDE6B, and TRPM1, showed cell-specific expression and transcription characteristics in either rods or bipolar cells (BCs). IRD genes showed evolutionary conservation (GNAT2, PDE6G, and SAG) and divergence (GNAT2, MT-ND4, and PDE6A) along the trajectory of photoreceptors (PRs) among species. In particular, the Leber congenital amaurosis (LCA) gene OTX2 showed high expression at the beginning of the trajectory of both PRs and BCs.ConclusionWe identified molecular pathways and cell types closely connected with IRDs, bridging the gap between gene expression, genetics, and pathogenesis. The IRD genes enriched in cell-specific modules and regulons suggest that these diseases share common etiological bases. Overall, mining of interspecies transcriptome data reveals conserved transcriptomic features of retinas across species and promising applications in both normal retina anatomy and retina pathology.

In the realm of neuroscience, mapping the three-dimensional (3D) neural circuitry and architecture of the brain is important for advancing our understanding of neural circuit organization and function. This study presents a novel pipeline that transforms mouse brain samples into detailed 3D brain models using a collaborative data analytics platform called “Texera.” The user-friendly Texera platform allows for effective interdisciplinary collaboration between team members in neuroscience, computer vision, and data processing. Our pipeline utilizes the tile images from a serial two-photon tomography/TissueCyte system, then stitches tile images into brain section images, and constructs 3D whole-brain image datasets. The resulting 3D data supports downstream analyses, including 3D whole-brain registration, atlas-based segmentation, cell counting, and high-resolution volumetric visualization. Using this platform, we implemented specialized optimization methods and obtained significant performance enhancement in workflow operations. We expect the neuroscience community can adopt our approach for large-scale image-based data processing and analysis.

IntroductionRapid and accurate estimation of leaf area index (LAI) is of great significance for the precision agriculture because LAI is an important parameter to evaluate crop canopy structure and growth status.MethodsIn this study, 20 vegetation indices were constructed by using cotton canopy spectra. Then, cotton LAI estimation models were constructed based on multiple machine learning (ML) methods extreme learning machine (ELM), random forest (RF), back propagation (BP), multivariable linear regression (MLR), support vector machine (SVM)], and the optimal modeling strategy (RF) was selected. Finally, the vegetation indices with a high correlation with LAI were fused to construct the VI-fusion RF model, to explore the potential of multi-vegetation index fusion in the estimation of cotton LAI.ResultsThe RF model had the highest estimation accuracy among the LAI estimation models, and the estimation accuracy of models constructed by fusing multiple VIs was higher than that of models constructed based on single VIs. Among the multi-VI fusion models, the RF model constructed based on the fusion of seven vegetation indices (MNDSI, SRI, GRVI, REP, CIred-edge, MSR, and NVI) had the highest estimation accuracy, with coefficient of determination (R2), rootmean square error (RMSE), normalized rootmean square error (NRMSE), and mean absolute error (MAE) of 0.90, 0.50, 0.14, and 0.26, respectively. DiscussionAppropriate fusion of vegetation indices can include more spectral features in modeling and significantly improve the cotton LAI estimation accuracy. This study will provide a technical reference for improving the cotton LAI estimation accuracy, and the proposed method has great potential for crop growth monitoring applications.

IntroductionCotton yield estimation is crucial in the agricultural process, where the accuracy of boll detection during the flocculation period significantly influences yield estimations in cotton fields. Unmanned Aerial Vehicles (UAVs) are frequently employed for plant detection and counting due to their cost-effectiveness and adaptability.MethodsAddressing the challenges of small target cotton bolls and low resolution of UAVs, this paper introduces a method based on the YOLO v8 framework for transfer learning, named YOLO small-scale pyramid depth-aware detection (SSPD). The method combines space-to-depth and non-strided convolution (SPD-Conv) and a small target detector head, and also integrates a simple, parameter-free attentional mechanism (SimAM) that significantly improves target boll detection accuracy.ResultsThe YOLO SSPD achieved a boll detection accuracy of 0.874 on UAV-scale imagery. It also recorded a coefficient of determination (R2) of 0.86, with a root mean square error (RMSE) of 12.38 and a relative root mean square error (RRMSE) of 11.19% for boll counts.DiscussionThe findings indicate that YOLO SSPD can significantly improve the accuracy of cotton boll detection on UAV imagery, thereby supporting the cotton production process. This method offers a robust solution for high-precision cotton monitoring, enhancing the reliability of cotton yield estimates.

Abstract Background The role of Acyl-CoA dehydrogenase long chain (ACADL) in different tumor types had different inhibiting or promoting effect. However, its role in non-small cell lung cancer (NSCLC) carcinogenicity is not clear. Method In this study, we utilized The Cancer Genome Atlas (TCGA) database to analyze ACADL expression in NSCLC and its correlation with overall survival. Furthermore, we investigated the function of ACADL on cellular proliferation, invasion, colony, apoptosis, cell cycle in vitro with NSCLC cells. Mechanistically, we evaluated the regulatory effect of ACADL expression on its downstream factor yes-associated protein (YAP) by assessing YAP phosphorylation levels and its cellular localization. Finally, we verified the tumorigenic effect of ACADL on NSCLC cells through xenograft experiments in vivo. Results Compared to adjacent non-cancerous samples, ACADL significantly down-regulated in NSCLC. Overexpression of ACADL, effectively reduced the proliferative, colony, and invasive capabilities of NSCLC cells, while promoting apoptosis and inducing cell cycle arrest. Moreover, ACADL overexpression significantly enhanced YAP phosphorylation and hindered its nuclear translocation. However, the inhibitory effect of the overexpression of ACADL in NSCLC cells mentioned above can be partially counteracted by YAP activator XMU-MP-1 application both in vitro and in vivo. Conclusion The findings suggest that ACADL overexpression could suppress NSCLC development by modulating YAP phosphorylation and limiting its nuclear shift. This role of ACADL-YAP axis provided novel insights into NSCLC carcinogenicity and potential therapeutic strategies.

In recent years, S-(alkyl)thianthrenium salts have become an important means of functionalizing alcohol compounds. However, additional transition metal catalysts and/or visible light are required. Herein, a direct thioetherification/amination reaction of thianthrenium salts is realized under metal-free conditions. This strategy exhibits good functional-group tolerance, operational simplicity, and an extensive range of compatible substrates.

Recent years have encountered a noticeable expansion of point cloud-based 3D applications that compels the necessity of high-efficiency point cloud compression. Preserving the local density of point cloud is crucial for compression, however, it’s challenging due to the unordered nature of points in 3D space and has been overlooked by the majority of the existing compression methods. Recently, the farthest point method has demonstrated effectiveness in sampling point clouds across various state-of-the-art methods, its limitation lies in being non-density aware, yielding reconstructions that fall short of the desired quality. Intending to achieve density-aware compression for improved reconstruction, this paper proposes an end-to-end learnable cluster-based compression method for efficient lossy point cloud geometry compression. Our method utilizes an autoencoder architecture that performs point-wise operation for compression and reconstruction. To extract effective latent features, the encoder segments the point clouds into clusters using a different approach than farthest point sampling that is capable of well capturing uneven point densities and employs cluster-wise compression independently. To enhance density retention further, we leveraged the capabilities of an attention mechanism, allowing it to learn complex point-wise dependencies within clusters and effectively capture local density information. At the decoder, decompressed clusters are accumulated to reconstruct point clouds completely. In terms of rate-distortion trade-off, the experimental analysis reveals the superiority of the proposed method over prior arts. Furthermore, our approach adapts well to different datasets, for example, the model learned from the ModelNet40 dataset works well and achieves state-of-the-art performances on ShapeNet datasets. Finally, the qualitative comparison demonstrates that the proposed framework can preserve satisfactory local geometry details of point clouds compared to existing Representative methods.

Fallen leaves and their decomposition directly deposit leaf wax n-alkanes into sediments, which can be used to identify local flora. These n-alkanes are important for studying past vegetation and climate, but their distribution in sediments must be known. Aeolian sand n-alkanes are particularly important for understanding paleoclimates in arid regions, despite the challenges of extraction due to their extremely low abundance. To investigate the preservation of plant leaf wax n-alkanes in deserts, we analyzed n-alkanes in aeolian sands from the Northern Ulan Buh Desert (UBD), China, and compared them to the surrounding vegetation. We calculated the total n-alkane concentration (ΣALK), average chain length (ACL21–35), and carbon preference index (CPI21–35). In the Northern UBD, aeolian sand n-alkanes have lower ΣALK, indicating microbial degradation. The eastern aeolian sand has lower CPI21–35 and ACL21–35 than the adjacent vegetation, whereas the western sand values are consistent with the plants, likely due to the transport of plant-derived materials by wind and water from the nearby mountains. Our study shows that sedimentary n-alkane signatures are not only determined by local vegetation but also influenced by environmental factors like temperature and precipitation. Additionally, local deposition processes play a significant role in determining the properties of these n-alkanes.

The authors regret to pinpoint two editorial errors in [...]

Frying is a critical process in the food industry, where selecting appropriate vegetable oils is key to achieving optimal results. In this study, French fries were fried at 175 °C with five different oils, the changes in the physicochemical indexes and free radical scavenging rate of the oils during the frying process were investigated, and the most suitable oils for frying were identified through comparative analysis using principal component analysis (PCA). We assessed the frying performances of hot-pressed high-oleic-acid rapeseed oil (HHRO), cold-pressed high-oleic-acid rapeseed oil (CHRO), soybean oil, rice bran oil, and palm oil utilizing principal component analysis over an 18 h period. The HHRO and CHRO showed lower acid values (0.31, 0.26 mg/g), peroxide values (2.09, 1.96 g/100 g), p-anisidine values (152.48, 178.88 g/mL), and total polar compound percentages (27.60%, 32.10%) than other oils. Furthermore, both the HHRO and CHRO demonstrated enhanced free radical scavenging abilities, indicative of their higher antioxidant capacities, as corroborated by the PCA results. Benzopyridine, 3-monochloropropane-1,2-diol ester, squalene, tocopherols, and polyphenol from the HHRO and CHRO during frying were compared. A comprehensive examination of harmful substances versus nutrient retention during frying revealed that the HHRO contained fewer hazardous compounds, while CHRO retained more nutrients. Therefore, this study analyzes the oxidation regulation of HHRO in frying applications, highlights the prospects of HHRO for frying in terms of health and economy, and contributes valuable insights for informed vegetable oil selection within the food industry.

Purpose: To evaluate the feasibility of rib fracture detection in low-dose computed tomography (CT) images with a RetinaNet-based approach and to evaluate the potential of lowdose CT for rib fracture detection compared with regular-dose CT images. Materials and methods: The RetinaNet-based deep learning model was trained using 7300 scans with 50,410 rib fractures that were used as internal training datasets from four multicenter. The external test datasets consisted of both regular-dose and low-dose chest-abdomen CT images of rib fractures; the MICCAI 2020 RibFrac Challenge Dataset was used as the public dataset. Radiologists' interpretations were used as reference standards. The performance of the model in rib fracture detection was compared with the radiologists’ interpretation. Results: In total, 728 traumatic rib fractures of 100 patients [60 men (60 %); mean age, 53.45 ± 11.19 (standard deviation (SD)); range, 18–77 years] were assessed in the external datasets. In these patients, the regular-dose group had a mean CT dose index volume (CTDIvol) of 7.18 mGy (SD: 2.22) and a mean dose length product (DLP) of 305.38 mGy cm (SD: 95.31); the low-dose group had a mean CTDIvol of 2.79 mGy (SD: 1.11) and a mean DLP of 131.52 mGy cm (SD: 55.58). The sensitivity of the RetinaNet-based model and that of the radiologists was 0.859 and 0.721 in the low-dose CT images and 0.886 and 0.794 in the regular-dose CT images, respectively. Conclusions: These findings indicate that the RetinaNet-based model can detect rib fractures in low-dose CT images with a robust performance, indicating its feasibility in assisting radiologists with rib fracture diagnosis.

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IntroductionHeavy metals are ubiquitous environmental pollutants, and fish could be contaminated by these metals, potentially posing a threat to human health through the food chain. Understanding the accumulation of these metals in fish tissues is crucial for assessing the safety of consuming fish products.MethodsIn this study, the distribution of nickel (Ni), copper (Cu), zinc (Zn), cadmium (Cd), and lead (Pb) in tissues of eight fish species (Ctenopharyngodon idellus, Megalobrama amblycephala, Hypophthalmichthys molitrix, Hypophthalmichthys nobilis, Carassius auratus, Cyprinus carpio, Culter alburnus, and Lateolabrax japonicas) collected from the Baishazhou market with different trophic levels and habitat preference was investigated using inductively coupled plasma mass spectrometry (ICP-MS). The metal accumulation capacity of different fish tissues and species was assessed, and the metal pollution index (MPI) was calculated to evaluate the extent of metal accumulation ability in each species. Additionally, the health risk assessment was conducted to evaluate the potential threat to human health posed by consuming these fish species.ResultsThe levels of metals exhibited variation among different fish tissues and species, showing an order of Zn > Cu > Ni > Pb > Cd. In terms of tissues, fish head demonstrated a greater capacity for metal accumulation compared to the muscles. Regarding fish species, the extent of accumulation ability varied depending on the specific metal, exhibiting the following order according to MPI: H. molitrix (0.568) > C. auratus (0.508) > M. amblycephala (0.469) > C. idellus (0.336) > C. alburnus (0.315) > C. carpio (0.274) > L. japonicus (0.263) > H. nobilis (0.206). Furthermore, in accordance with the results of health risk assessment, there was no potential health risk associated with the consumption of these fish species, as all target hazard quotient (THQ) values (ranger from not detected to 0.192) were below 1, and the maximum hazard index (HI) value was observed in C. carpio (0.519 for adults, 0.622 for children).ConclusionThe findings of this study demonstrate the distribution of heavy metals in fish tissues and indicate there were no potential health risk associated with consuming these fish bought from the Baishazhou market.

Novel brain clearing methods revolutionize imaging by increasing visualization throughout the brain at high resolution. However, combining the standard tool of immunostaining targets of interest with clearing methods has lagged behind. We integrate whole-mount immunostaining with PEGASOS tissue clearing, referred to as iPEGASOS (immunostaining-compatible PEGASOS), to address the challenge of signal quenching during clearing processes. iPEGASOS effectively enhances molecular-genetically targeted fluorescent signals that are otherwise compromised during conventional clearing procedures. Additionally, we demonstrate the utility of iPEGASOS for visualizing neurochemical markers or viral labels to augment visualization that transgenic mouse lines cannot provide. Our study encompasses three distinct applications, each showcasing the versatility and efficacy of this approach. We employ whole-mount immunostaining to enhance molecular signals in transgenic reporter mouse lines to visualize the whole-brain spatial distribution of specific cellular populations. We also significantly improve the visualization of neural circuit connections by enhancing signals from viral tracers injected into the brain. Last, we show immunostaining without genetic markers to selectively label beta-amyloid deposits in a mouse model of Alzheimer’s disease, facilitating the comprehensive whole-brain study of pathological features.

Non-alcoholic fatty liver disease (NAFLD) is increasingly recognized for its global prevalence and potential progression to more severe liver diseases such as non-alcoholic steatohepatitis (NASH). The gut microbiota plays a pivotal role in the pathogenesis of NAFLD, yet the detailed characteristics and ecological alterations of gut microbial communities during the progression from non-alcoholic fatty liver (NAFL) to NASH remain poorly understood. Methods: In this study, we conducted a comparative analysis of gut microbiota composition in individuals with NAFL and NASH to elucidate differences and characteristics. We utilized 16S rRNA sequencing to compare the intestinal gut microbiota among a healthy control group (65 cases), NAFL group (64 cases), and NASH group (53 cases). Random forest machine learning and database validation methods were employed to analyze the data. Results: Our findings indicate a significant decrease in the diversity of intestinal flora during the progression of NAFLD (p

Enzymatically prepared aromatic oils commonly have high purity and aroma quality. However, amino acid type and content vary greatly according to the type of oil, which impacts overall aroma and quality. In this study, the effects of lysine (Lys), arginine (Arg), proline (Pro), and glutamic (Glu) acid on physicochemical indices, nutrients, hazardous substances, fatty acid composition, and flavor during fragrant rapeseed oil (FRO) enzymatic preparation were investigated using the Maillard reaction (MR). In the lysine-treated group, the unsaturated fatty acids (93.16 %), α-tocopherol (183.06 mg/kg), γ-tocopherol (404.37 mg/kg), and δ-tocopherol (12.69 mg/kg) contents were the highest, whereas the acid value (1.27 mg/g) and moisture (0.10 %) and benzo[a]pyrene (1.45 μg/kg) contents were the lowest. Sensory evaluation showed that lysine effectively enhanced FRO flavor by enhancing the nutty/toasted flavor (4.80 scores). Principle component analysis (PCA) showed that the nutty/toasted flavor correlated mainly with 2,6-dimethylpyrazine, 2,5-dimethyl-pyrazine, 2-methyl-pyrazine, and trimethylpyrazine, nutty/toasted flavor strength increased with pyrazine content, which were the highest in the lysine group (24.02 μg/g). This study provides a guide for FRO preparation by adding external MR prerequisites.

Abstract Background Pulmonary nodule growth rate assessment is critical in the management of subsolid pulmonary nodules (SSNs) during clinical follow-up. The present study aimed to develop a model to predict the growth rate of SSNs. Methods A total of 273 growing SSNs with clinical information and 857 computed tomography (CT) scans were retrospectively analyzed. The images were randomly divided into training and validation sets. All images were categorized into fast-growth (volume doubling time (VDT) ≤ 400 days) and slow-growth (VDT > 400 days) groups. Models for predicting the growth rate of SSNs were developed using radiomics and clinical features. The models’ performance was evaluated using the area under the curve (AUC) values for the receiver operating characteristic curve. Results The fast- and slow-growth groups included 108 and 749 scans, respectively, and 10 radiomics features and three radiographic features (nodule density, presence of spiculation, and presence of vascular changes) were selected to predict the growth rate of SSNs. The nomogram integrating radiomics and radiographic features (AUC = 0.928 and AUC = 0.905, respectively) performed better than the radiographic (AUC = 0.668 and AUC = 0.689, respectively) and radiomics (AUC = 0.888 and AUC = 0.816, respectively) models alone in both the training and validation sets. Conclusion The nomogram model developed by combining radiomics with radiographic features can predict the growth rate of SSNs more accurately than traditional radiographic models. It can also optimize clinical treatment decisions for patients with SSNs and improve their long-term management.

【Objective】The tensile force of tobacco leaves is one of the physical characteristics of tobacco leaves, which reflects the processing resistance of tobacco leaves. Studying the tensile force characteristics of tobacco leaves can provide reference for the setting of processing parameters of threshing and redrying tobacco leaves, and further improve the economic benefits of tobacco processing.【Method】In order to improve the stability and accuracy of measuring the tensile force of tobacco leaves by texture analyzer, three factors and three levels parameters were designed by Box-Behnken principle, and the influence of each parameter on the coefficient of variation of the results was analyzed by response surface method, and the optimal parameter combination for measuring the tensile force was obtained. The effect of moisture content on tobacco leaf tension was studied. Further, the BP neural network prediction model of moisture content X- tension Y of tobacco leaves was established.【Result】The analysis results of response surface method show that it can be seen that the sample width has a significant influence on the coefficient of variation of tensile force, and the test rate has a significant influence, but the trigger force has no obvious influence. The optimal parameter combination was obtained: the sample width was 10 mm, the test rate was 0.5 mm/s, the trigger force was 0.1 N. The coefficient of variation of the tensile force measured by these parameters decreased significantly to 13.8%. With the increase of moisture content, the tensile strength of tobacco leaves first increased and then decreased. When the moisture content of Jingdong C3F was 18.41%, the tensile strength reached the maximum, which was 0.456 N/mm. The tensile strength of Jingdong C1F was only 0.288 N/mm, when the moisture content was 18.46%. When the moisture content of Honghe C3F and Pu 'er C3F were 20.64% and 18.47%, the maximum tensile strength were 0.447 N/mm and 0.310 N/mm respectively. There are differences in the tension of tobacco leaves in different regions and grades. The BP neural network prediction model of moisture content X- tension Y of tobacco leaves was established. The predicted value was in good agreement with the real value, with the mean square error MSE of 0.04761 and the root mean square error RMSE of 0.2182.【Conclusion】Response surface analysis can be used to analyze the influence of parameters on the results of tobacco tensile test, and the stability of the results is improved after the parameters are optimized. The tensile force of tobacco leaves in different regions and grades is significantly different, and it first increases and then decreases with the increase of moisture content. According to this law, the appropriate moisture content can be selected to make tobacco leaves have the best processing resistance. The established BP neural network model has small error and good accuracy, and can be used to predict the tensile force of tobacco leaves.

Isoxazole derivatives were synthesized via a one-pot method utilizing 2-methylquinoline derivatives as template substrates, sodium nitrite as a nitrogen-oxygen source, and solely using aluminum trichloride as the additive. This approach circumvents the need for costly or highly toxic transition metals and presents a novel pathway for the synthesis of isoxazole derivatives.

Background Percutaneous coronary intervention (PCI) via distal transradial artery approach (dTRA) is effective in reducing the incidence of radial artery occlusion, however, there are no reports on the feasibility, safety and timing of secondary PCI via dTRA domestically. Objective To explore the feasibility, safety and timing of secondary PCI via dTRA. Methods A total of 70 patients who were to undergo secondary PCI via dTRA in Fuwai Hospital, CAMS&PUMC from July 2021 to July 2022 were consecutively included and divided into ≤30 d group (n=33) and >30 d group (n=37) according to the time interval since the last PCI via dTRA. The general clinical data, operation-related indicators, coronary artery lesions and radial artery inner diameters at 5, 10 and 15 cm proximal to the radial styloid process before and 24 h after PCI were compared between the two groups. Results The dTRA puncture and catheterization were successfully conducted in 69 of 70 patients, with a success rate of 98.6% (69/70) . Second PCI via dTRA was successfully completed in 66 of 67 patients assessed for secondary PCI, with a success rate of 98.5% (66/67) . There were significantly difference in age, platelet count, incidence of diabetes, number of lesioned vessels and ACC/AHA coronary artery lesions typing (P30 d group before and 24 h after PCI when comparing between the two groups, respectively (P30 d group (P30 days from the first dTRA PCI) , and the timing of secondary PCI via dTRA should be determined according to the patient's condition and puncture site.

Ulcerative colitis (UC) is a typical inflammatory bowel disease (IBD), impairing the quality of life of patients. Dehydroevodiamine (DHE) is an active alkaloid isolated from Tetradium ruticarpum that exerts significant anti-inflammatory effects in gastrointestinal diseases. However, the effect and mechanisms of DHE on UC remain unclear. We performed a DSS-induced experimental UC rat model to reveal the efficacy and potential mechanisms of DHE on UC. HE and AB-PAS staining were used for the evaluation of pathologies, and 16S rRNA sequencing was used to detect changes in gut microbes. Metabolomics was used to detect changes in serum metabolites. Network pharmacology and transcriptomics were conducted to reveal the underlying mechanisms of DHE for UC. HuProt proteome microarrays, molecular docking, and SPR were used to reveal the targets of action of DHE. WB, RT-qPCR, and IHC were used to assess the action effects of DHE. DHE demonstrated significant alleviation of DSS-induced colitis symptoms in rats by suppressing inflammatory and oxidative stress responses, amending colonic barrier injury, and inhibiting apoptosis. In terms of gut microbial modulation, DHE decreased the abundance of Allobaculum, Clostridium, Escherichia, Enterococcus, and Barnesiella and increased the abundance of Lactobacillus, Bifidobacterium, and SMB5. Moreover, metabolomics suggested that the regulation of DHE in DSS-induced UC rats mainly involved aminoacyl-tRNA biosynthesis, vitamin B6 metabolism, phenylalanine, tyrosine, and so on. Mechanically, DHE alleviated UC in rats by targeting AKT1, thereby inhibiting the PI3K/AKT/NF-κB signaling pathway.

Incorporating renewable energy sources into the grid poses challenges due to their volatility and uncertainty in optimizing dispatch strategies. In response, this article proposes a cloud–edge collaborative scheduling strategy for distributed multi-energy systems, operating across various time scales. The strategy integrates day-ahead dispatch, intra-day optimization, and real-time adjustments to minimize operational costs, reduce the wastage of renewable energy, and enhance overall system reliability. Furthermore, the cloud–edge collaborative framework helps mitigate scalability challenges. Crucially, the strategy considers the multi-timescale characteristics of two types of energy storage systems (ESSs) and three types of demand response (DR), aimed at optimizing resource allocation efficiently. Comparative simulation results evaluate the strategy, providing insights into the significant impacts of different ESS and DR types on system performance. By offering a comprehensive approach, this strategy aims to address operational complexities. It aims to contribute to the seamless integration of renewable energy into distributed systems, potentially enhancing sustainability and resilience in energy management.

Psychological health education is the main battlefield for promoting the mental health of college students. This article studies the impact of ideological and political education in universities on the mental health of college students. Research on Student Mental Health Based on DL. A student emotion recognition model based on DL (deep learning) has been established. The separable CNN (Convolutional neural network) is used to detect the face in the image, and the face is located and tracked through the tracker. After normalizing the facial image, it is input into a deep separable CNN for classification. The results indicate that the regression equation can explain 74.106% of the total variation. The political characteristics of Demographics characteristics have a significant impact on college students’ political entity identity, while gender, grade, and major have no significant impact on college students’ Party identification. Social practice and campus culture have a significant positive impact on the political entity identity of college students. Compared with traditional machine learning-based emotion recognition methods, the classification accuracy of the proposed method in this paper has been improved by 8.036%, and research based on DL technology has significant advantages in accuracy.