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Abstract Background Hypertension is a common disease, often overlooked in its early stages due to mild symptoms. And persistent elevated blood pressure can lead to adverse outcomes such as coronary heart disease, stroke, and kidney disease. There are many risk factors that lead to hypertension, including various environmental chemicals that humans are exposed to, which are believed to be modifiable risk factors for hypertension. Objective To investigate the role of environmental chemical exposures in predicting hypertension. Methods A total of 11,039 eligible participants were obtained from NHANES 2003–2016, and multiple imputation was used to process the missing data, resulting in 5 imputed datasets. 8 Machine learning algorithms were applied to the 5 imputed datasets to establish hypertension prediction models, and the average accuracy score, precision score, recall score, and F1 score were calculated. A generalized linear model was also built to predict the systolic and diastolic blood pressure levels. Results All 8 algorithms had good predictions for hypertension, with Support Vector Machine (SVM) being the best, with accuracy, precision, recall, F1 scores and area under the curve (AUC) of 0.751, 0.699, 0.717, 0.708 and 0.822, respectively. The R2 of the linear model on the training and test sets was 0.28, 0.25 for systolic and 0.06, 0.05 for diastolic blood pressure. Conclusions In this study, relatively accurate prediction of hypertension was achieved using environmental chemicals with machine learning algorithms, demonstrating the predictive value of environmental chemicals for hypertension.

Abstract Background A short cervix in mid-trimester pregnancy is a risk factor for spontaneous preterm birth. However, there is currently a lack of predictive models and classification systems for predicting spontaneous preterm birth in these patients, especially those without additional risk factors for spontaneous preterm birth. Methods A retrospective observational cohort study of low-risk singleton pregnant women with a short cervix (≤ 25 mm) measured by transvaginal ultrasonography between 22 and 24 weeks was conducted. A multivariate logistic regression model for spontaneous preterm birth 146, respectively. The predicted probabilities of spontaneous preterm birth

Summary: Under the background of the accelerating speed of urban and rural construction, the geographical environment of overhead transmission lines has also changed greatly. Using unmanned aerial vehicle (UAV) to realize intelligent line inspection can significantly shorten inspection time and improve inspection efficiency. In this paper, the intelligent power inspection of UAVs is studied from two levels: path planning and UAV control, and the insulator is identified through actual image recognition. At the path planning level, the improved swarm intelligence algorithm is used to conduct simulation experiments on the UAV flight path to find a safe and effective route. Insulator identification and defect location of overhead transmission lines are trained on the insulator dataset collected by deep learning technology to achieve accurate insulator identification and improve the efficiency of UAV inspection, which has great application prospects in engineering.

Abstract Epilepsies are a group of neurological disorders characterized by abnormal spontaneous brain activity, involving multiscale changes in brain functional organizations. However, it is not clear to what extent the epilepsy-related perturbations of spontaneous brain activity affect macroscale intrinsic dynamics and microcircuit organizations, that supports their pathological relevance. We collect a sample of patients with temporal lobe epilepsy (TLE) and genetic generalized epilepsy with tonic-clonic seizure (GTCS), as well as healthy controls. We extract massive temporal features of fMRI BOLD time-series to characterize macroscale intrinsic dynamics, and simulate microcircuit neuronal dynamics used a large-scale biological model. Here we show whether macroscale intrinsic dynamics and microcircuit dysfunction are differed in epilepsies, and how these changes are linked. Differences in macroscale gradient of time-series features are prominent in the primary network and default mode network in TLE and GTCS. Biophysical simulations indicate reduced recurrent connection within somatomotor microcircuits in both subtypes, and even more reduced in GTCS. We further demonstrate strong spatial correlations between differences in the gradient of macroscale intrinsic dynamics and microcircuit dysfunction in epilepsies. These results emphasize the impact of abnormal neuronal activity on primary network and high-order networks, suggesting a systematic abnormality of brain hierarchical organization.

Abstract Introduction As a novel internal fixation for femoral neck fractures, the femoral neck system has some advantages for young Pauwels type III femoral neck fractures without clear biomechanical effects and mechanisms. Thus, the objection of the study is to realize the biomechanical effects and mechanism of FNS cannulated screws on treating young patients with Pauwels type III femoral neck fractures compared to cannulated screws which are commonly used for femoral neck fractures by finite element analysis. Methods Firstly, the model of young Pauwels type III femoral neck fractures, femoral neck system (FNS), and three cannulated screws (CS) arranged in an inverted triangle were established, and the internal fixations were set up to fix young Pauwels type III femoral neck fractures. Under 2100 N load, the finite element was performed, and the deformation, peak von Mises stress (VMS), and contact at fracture segments were recorded to analyze the biomechanical effects and mechanism of FNS and three-CS fixing young Pauwels type III femoral neck fractures. Results Compared to three-CS, the deformation of the whole model, internal fixation, and fracture segments after FNS fixation were lower, and the peak VMS of the whole model and the internal fixation after FNS were higher with lower peak VMS of the distal femur and the fracture segments. With a sticking contact status, the contact pressure at fracture segments after FNS fixation was lower than that of three-CS. Conclusions FNS can provide better mechanical effects for young patients with Pauwels type III femoral neck fractures, which may be the mechanical mechanism of the clinical effects of FNS on femoral neck fracture. Although there is high stress on FNS, it is still an effective and safe internal fixation for young patients with Pauwels type III femoral neck fractures.

Retinitis pigmentosa (RP) is an inherited retinal disease in which there is a loss of cone-mediated daylight vision. As there are >100 disease genes, our goal is to preserve cone vision in a disease gene-agnostic manner. Previously we showed that overexpressing TXNIP, an α-arrestin protein, prolonged cone vision in RP mouse models, using an AAV to express it only in cones. Here, we expressed different alleles of Txnip in the retinal pigmented epithelium (RPE), a support layer for cones. Our goal was to learn more of TXNIP’s structure-function relationships for cone survival, as well as determine the optimal cell type expression pattern for cone survival. The C-terminal half of TXNIP was found to be sufficient to remove GLUT1 from the cell surface, and improved RP cone survival, when expressed in the RPE, but not in cones. Knock-down of HSP90AB1, a TXNIP-interactor which regulates metabolism, improved the survival of cones alone and was additive for cone survival when combined with TXNIP. From these and other results, it is likely that TXNIP interacts with several proteins in the RPE to indirectly support cone survival, with some of these interactions different from those that lead to cone survival when expressed only in cones.

Abstract As an effective and non‐invasive treatment modality for cancer, photodynamic therapy (PDT) has attracted considerable interest. With the recent advances in the photosensitizing agents, the fiber‐optic systems, and other aspects, its application is extended to a wide range of superficial and localized cancers. However, for the few clinically used photosensitizers, most of them suffer from the drawback of causing prolonged photosensitivity after the treatment. As a result, post‐PDT management is also a crucial issue. Herein, a facile bioorthogonal approach is reported that can effectively suppress this common side effect of PDT in nude mice. It involves the use of an antidote that contains a black‐hole quencher BHQ‐3 conjugated with a bicyclo[6.1.0]non‐4‐yne (BCN) moiety and a tetrazine‐substituted boron dipyrromethene‐based photosensitizer. By using tumor‐bearing nude mice as an animal model, it is demonstrated that after PDT with this photosensitizer, the administration of the antidote can effectively quench the photodynamic activity of the residual photosensitizer by bringing the BHQ‐3 quencher close to the photosensitizing unit through a rapid click reaction. It results in substantial reduction in skin damage upon light irradiation. The overall results demonstrate that this simple and facile strategy can provide an effective means for minimizing the photosensitivity after PDT.

Immunotherapy, specifically immune checkpoint inhibitors, has emerged as a promising approach for treating malignant tumors. The gut, housing approximately 70 % of the body's immune cells, is abundantly populated with gut bacteria that actively interact with the host's immune system. Different bacterial species within the intestinal flora are in a delicate equilibrium and mutually regulate each other. However, when this balance is disrupted, pathogenic microorganisms can dominate, adversely affecting the host's metabolism and immunity, ultimately promoting the development of disease. Emerging researches highlight the potential of interventions such as fecal microflora transplantation (FMT) to improve antitumor immune response and reduce the toxicity of immunotherapy. These remarkable findings suggest the major role of intestinal flora in the development of cancer immunotherapy and led us to the hypothesis that intestinal flora transplantation may be a new breakthrough in modifying immunotherapy side effects.

Traffic flow prediction is crucial in intelligent transportation systems. Considering the severe disruptions caused by traffic accidents or congestion, a time series model is developed for traffic flow prediction based on multiple random walks on graphs (MRWG) and the bidirectional spatiotemporal attention mechanism (BSAM), which can adapt to both normal and exceptional situations. The MRWG mechanism is applied to capture spatial features of urban areas during traffic accidents and congestion, especially the spatial dependencies among neighboring regions. Further, a local position attention module is applied to acquire the spatial correlations between different regions to investigate their impact on the global area, while a local temporal attention module is adopted to extract short-term periodic time correlations from traffic flow data. Finally, a spatiotemporal bidirectional attention module is applied to simultaneously extract both the temporal and spatial correlations of the historical traffic flow data in order to generate the output prediction. Experiments have been conducted on NYCTaxi and NYCBike datasets with abnormal events, and the results indicate that the developed model can efficiently predict traffic flow in abnormal events, especially short-term traffic disruptions, outperforming the baseline methods under both abnormal and normal conditions.

Objective To investigate dynamic shifts in the oral microbiota and their association with the progression and aggravation of radiotherapy-induced oral mucositis(RIOM) in patients with head and neck malignancies undergoing radiotherapy. Methods Based on 16S rRNA gene sequencing, dynamic changes of oral microbiota in patients was analyzed. Results Firmicutes, Bacteroidetes, and Actinobacteria consistently constituted the predominant bacteria in the oral cavity. While there were no significant changes in the absolute abundance of microbiota, there were notable alterations in their relative richness and evenness. Analyses including CCA/RDA and Kruskal-Wallis indicated a significant increase in the proportions of Streptococcus and Lactobacillus genera in the later stages post-radiotherapy, showing statistically meaningful differences. Conclusion RIOM is associated with dysbiosis of oral microbiota. Microbial dysbiosis may aggravate the severity of RIOM. Streptococcus and Lactobacillus could be closely related to the progression of RIOM, pending further validation through animal experiments.