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Objective To explore the predictive value of T cell activation in peripheral blood of patients with hepatocellular carcinoma(HCC) after anti PD-1 therapy and its ratio to tumor burden on the efficacy of immunotherapy. Methods Serum specimens were obtained before and after treatment from 85 patients with HCC who received anti-PD-1 treatment. Indicators such as cell subpopulations and T cell activation were detected by flow cytometry. Combined with imaging analysis, cutoff value was obtained by X-tile software. Survival analysis was used to evaluate patients' outcomes. Results The maximum fold change of Ki-67+/PD-1+/CD8+ T cells in treatment cycles and the tumor burden determined by imaging were associated with prognoses. The ratio of T cell Ki-67+/PD-1+/CD8+ expression to tumor burden ratio greater than 0.6 at the first cycle of anti-PD-1 immunotherapy was associated with improvements in progression-free survival and overall survival (P < 0.05). Conclusion The ratio of activationa in T cells in peripheral blood after immunotherapy to the tumor burden may be related to the clinical efficacy of anti-PD-1 immunotherapy for HCC.

Coverage quantification is required in many sequencing datasets within the field of genomics research. However, most existing tools fail to provide comprehensive statistical results and exhibit limited performance gains from multithreading. Here, we present PanDepth, an ultra-fast and efficient tool for calculating coverage and depth from sequencing alignments. PanDepth outperforms other tools in computation time and memory efficiency for both BAM and CRAM-format alignment files from sequencing data, regardless of read length. It employs chromosome parallel computation and optimized data structures, resulting in ultrafast computation speeds and memory efficiency. It accepts sorted or unsorted BAM and CRAM-format alignment files as well as GTF, GFF and BED-formatted interval files or a specific window size. When provided with a reference genome sequence and the option to enable GC content calculation, PanDepth includes GC content statistics, enhancing the accuracy and reliability of copy number variation analysis. Overall, PanDepth is a powerful tool that accelerates scientific discovery in genomics research. [ABSTRACT FROM AUTHOR]

Geological hazards are widely distributed, cause huge losses, and have always been the focus of attention for engineering and environmental geologists. Geological hazard evaluation is the basis of research and has important theoretical significance for preventing and controlling geological hazards. Therefore, geological hazard evaluation has become the focus of engineering and environmental geology. The question of how to build a universal index system model of geological hazard evaluation is an urgent problem that needs to be solved in geological hazard evaluation. Based on a large amount of previous research data, this paper takes landslide hazard as an example and systematically expounds the main problems that need to be solved in the current geological hazard evaluation from five aspects: basic concept, evaluation scope and accuracy, evaluation index system and evaluation criteria, evaluation method, and applicability of evaluation results. A landslide hazard assessment index system model is proposed, which applies to all regions, including all of the factors that may affect the formation of landslides. It is also hoped that this will be used as an example to establish various types of disaster evaluation and assessment systems. If the parameter has no value in the assessment process, it can be processed as 0. On this basis, further research is suggested from the perspectives of the geological hazard evaluation level, geological hazard evaluation theory, and method. To provide thoughts on and suggestions for geological hazard risk assessment method research, standard revision, investigation and evaluation, and risk management and control need to be considered. [ABSTRACT FROM AUTHOR]

Summary: Self‐incompatibility (SI) is a widespread prezygotic mechanism for flowering plants to avoid inbreeding depression and promote genetic diversity. Citrus has an S‐RNase‐based SI system, which was frequently lost during evolution. We previously identified a single nucleotide mutation in Sm‐RNase, which is responsible for the loss of SI in mandarin and its hybrids. However, little is known about other mechanisms responsible for conversion of SI to self‐compatibility (SC) and we identify a completely different mechanism widely utilized by citrus. Here, we found a 786‐bp miniature inverted‐repeat transposable element (MITE) insertion in the promoter region of the FhiS2‐RNase in Fortunella hindsii Swingle (a model plant for citrus gene function), which does not contain the Sm‐RNase allele but are still SC. We demonstrate that this MITE plays a pivotal role in the loss of SI in citrus, providing evidence that this MITE insertion prevents expression of the S‐RNase; moreover, transgenic experiments show that deletion of this 786‐bp MITE insertion recovers the expression of FhiS2‐RNase and restores SI. This study identifies the first evidence for a role for MITEs at the S‐locus affecting the SI phenotype. A family‐wide survey of the S‐locus revealed that MITE insertions occur frequently adjacent to S‐RNase alleles in different citrus genera, but only certain MITEs appear to be responsible for the loss of SI. Our study provides evidence that insertion of MITEs into a promoter region can alter a breeding strategy and suggests that this phenomenon may be broadly responsible for SC in species with the S‐RNase system. [ABSTRACT FROM AUTHOR]

SUMMARY: Chromoplasts act as a metabolic sink for carotenoids, in which plastoglobules serve as versatile lipoprotein particles. PGs in chloroplasts have been characterized. However, the features of PGs from non‐photosynthetic plastids are poorly understood. We found that the development of chromoplast plastoglobules (CPGs) in globular and crystalloid chromoplasts of citrus is associated with alterations in carotenoid storage. Using Nycodenz density gradient ultracentrifugation, an efficient protocol for isolating highly purified CPGs from sweet orange (Citrus sinensis) pulp was established. Forty‐four proteins were defined as likely comprise the core proteome of CPGs using comparative proteomics analysis. Lipidome analysis of different chromoplast microcompartments revealed that the nonpolar microenvironment within CPGs was modified by 35 triacylglycerides, two sitosterol esters, and one stigmasterol ester. Manipulation of the CPG‐localized gene CsELT1 (esterase/lipase/thioesterase) in citrus calli resulted in increased lipids and carotenoids, which is further evidence that the nonpolar microenvironment of CPGs contributes to carotenoid accumulation and storage in the chromoplasts. This multi‐feature analysis of CPGs sheds new light on the role of chromoplasts in carotenoid metabolism, paving the way for manipulating carotenoid content in citrus fruit and other crops. [ABSTRACT FROM AUTHOR]

The development of facial recognition technology has become an increasingly powerful tool in wild animal individual recognition. In this paper, we develop an automatic detection and recognition method with the combinations of body features of big cats based on the deep convolutional neural network (CNN). We collected dataset including 12 244 images from 47 individual Amur tigers (Panthera tigris altaica) at the Siberian Tiger Park by mobile phones and digital camera and 1940 images and videos of 12 individual wild Amur leopard (Panthera pardus orientalis) by infrared cameras. First, the single shot multibox detector algorithm is used to perform the automatic detection process of feature regions in each image. For the different feature regions of the image, like face stripe or spots, CNNs and multi‐layer perceptron models were applied to automatically identify tiger and leopard individuals, independently. Our results show that the identification accuracy of Amur tiger can reach up to 93.27% for face front, 93.33% for right body stripe, and 93.46% for left body stripe. Furthermore, the combination of right face, left body stripe, and right body stripe achieves the highest accuracy rate, up to 95.55%. Consequently, the combination of different body parts can improve the individual identification accuracy. However, it is not the higher the number of body parts, the higher the accuracy rate. The combination model with 3 body parts has the highest accuracy. The identification accuracy of Amur leopard can reach up to 86.90% for face front, 89.13% for left body spots, and 88.33% for right body spots. The accuracy of different body parts combination is lower than the independent part. For wild Amur leopard, the combination of face with body spot part is not helpful for the improvement of identification accuracy. The most effective identification part is still the independent left or right body spot part. It can be applied in long‐term monitoring of big cats, including big data analysis for animal behavior, and be helpful for the individual identification of other wildlife species. [ABSTRACT FROM AUTHOR]

So far, there has been no safe and convenient method to weigh the large fierce animals, like Amur tigers. To address this problem, we built models to predict the body weight of Amur tigers based on the fact that body weight is proportional to body measurements or age. Using the method of body measurements, we extracted the body measurements from 4 different kinds of the lateral body image of tigers, that is, total lateral image, central lateral image, ellipse fitting image, and rectangle fitting image, and then we respectively used artificial neural network (ANN) and power regression model to analyze the predictive relationships between body weight and body measurements. Our results demonstrated that, among all ANN models, the model built with rectangle fitting image had the smallest mean square error. Comparatively, we screened power regression models which had the smallest Akakai information criteria (AIC). In addition, using the method of age, we fitted nonlinear regression models for the relationship between body weight and age and found that, for male tigers, logistic model had the smallest AIC. For female tigers, Gompertz model had the smallest AIC. Consequently, this study could be applied to estimate body weight of captive, or even wild, Amur tigers safely and conveniently, helping to monitor individual health and growth of the Amur tiger populations. [ABSTRACT FROM AUTHOR]