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The PANTHER classification system (http://www.pantherdb.org) is a comprehensive system that combines genomes, gene function classifications, pathways and statistical analysis tools to enable biologists to analyze large-scale genome-wide experimental data. The current system (PANTHER v.14.0) covers 131 complete genomes organized into gene families and subfamilies; evolutionary relationships between genes are represented in phylogenetic trees, multiple sequence alignments and statistical models (hidden Markov models (HMMs)). The families and subfamilies are annotated with Gene Ontology (GO) terms, and sequences are assigned to PANTHER pathways. A suite of tools has been built to allow users to browse and query gene functions and analyze large-scale experimental data with a number of statistical tests. PANTHER is widely used by bench scientists, bioinformaticians, computer scientists and systems biologists. Since the protocol for using this tool (v.8.0) was originally published in 2013, there have been substantial improvements and updates in the areas of data quality, data coverage, statistical algorithms and user experience. This Protocol Update provides detailed instructions on how to analyze genome-wide experimental data in the PANTHER classification system.Here the authors provide an update to their 2013 protocol for using the PANTHER classification system, detailing how to analyze genome-wide experimental data with the newest version of PANTHER (v.14.0), with improvements in the areas of data quality, data coverage, statistical algorithms and user experience.

The accurate prediction of the pavement structural modulus is crucial for maintenance planning and life-cycle assessment. While recent deep learning models have improved predictive accuracy using Falling Weight Deflectometer data, challenges remain in effectively structuring time-series inputs and ensuring robustness against noise measurement. This paper presents an integrated framework that combines systematic time-step modeling with perturbation-based robustness evaluation. Five distinct input sequencing strategies (Plan A through Plan E) were developed to investigate the impact of temporal structure on model performance. A hybrid Wide & Deep ResRNN architecture incorporating SimpleRNN, GRU, and LSTM components was designed to jointly predict four-layer moduli. To simulate real-world sensor uncertainty, Gaussian noise with ±3% variance was injected into inputs, allowing the Monte-Carlo-style estimation of confidence intervals. Experimental results revealed that time-step design plays a critical role in both prediction accuracy and robustness, with Plan D consistently achieving the best balance between accuracy and stability. These findings offer a practical and generalizable approach for deploying deep sequence models in pavement modulus prediction tasks, particularly under uncertain field conditions.

Intersection management is a sophisticated event in the intelligent transportation system due to a variety of behavior for traffic participants. This paper primarily overviews recent studies on the scenes of intersection, aiming at improving the efficiency or guaranteeing the safety when vehicles pass the crossing. These studies are respectively surveyed from the perspectives of efficiency and safety. Firstly, recent contributions to efficiency-oriented, intersection management overviews from four scenes, including congestion avoidance, green light optimized speed advisory (GLOSA), trajectory planning, and emergency vehicle priority preemption control. Furthermore, the studies on intersection collision detection and abnormal information warning are surveyed in the safety category. The corresponding algorithms for velocity and route management presented in the surveyed works are discussed.

Long-term variations in ocean acidification indices in the Northwest Pacific were examined using observational data and a biogeochemical model with an operational ocean model product for the period 1993–2018. The model and observational data for the surface ocean (< 100-m depth) exhibit consistent patterns of ocean acidification in the subtropical and Kuroshio Extension regions and relative alkalinization (i.e., reduced acidification) in the subarctic region of the Northwest Pacific. Below 100-m depth, acidification dominated in the subtropical regions and alkalinization in the subarctic regions. We attribute the excess acidification in the subtropical and Kuroshio regions to the vertical mixing of dissolved inorganic carbon (DIC) exceeding the DIC release by air–sea exchange. These regional differences in acidification and alkalinization are attributed to spatially variable biological processes in the upper ocean and horizontal and vertical physical redistribution of DIC. Our model and observational results have implications for the spatial extent and pattern of ocean acidification, along with the strength of the ocean carbon sink, which are key aspects of global climate change.

Reliable, automatic, multifunctional, and high-throughput phenotypic technologies are increasingly considered important tools for rapid advancement of genetic gain in breeding programs. With the rapid development in high-throughput phenotyping technologies, research in this area is entering a new era called 'phenomics.' The crop phenotyping community not only needs to build a multi-domain, multi-level, and multi-scale crop phenotyping big database, but also to research technical systems for phenotypic traits identification and develop bioinformatics technologies for information extraction from the overwhelming amounts of omics data. Here, we provide an overview of crop phenomics research, focusing on two parts, from phenotypic data collection through various sensors to phenomics analysis. Finally, we discussed the challenges and prospective of crop phenomics in order to provide suggestions to develop new methods of mining genes associated with important agronomic traits, and propose new intelligent solutions for precision breeding.

The Mu Us Sandy Land is located in the middle of the farming pastoral ecotone of northern China. The direction of the development of desertification has a direct impact on the economy and development of the northern region. Six remote sensing images acquired during 1990–2017 served as data sources. Using an ENVI 5.3 and ArcGIS 10.3 platform an analysis was conducted of the dynamic changes nearly 30 years in desertified land using a center of gravity moving model, annual change rate, a transfer matrix, and an aeolian desertification index; the factors driving desertification were discussed. The research shows that the time period can be divided into three stages of desertification: development (1990–2000), rapid reversal (2000–2010), and stable reversal (2010–2017). A total of 1680 km 2 of desertification were managed over the three stages. Spatially, the distribution of the center of desertification from west to east includes mild, moderate, severe, and extreme desertification, which is consistent with the spatial distribution trends of desertified land in the Mu Us Sandy Land. By the end of 2017, the degree of desertification of the Mu Us Sandy Land was in the central area > northwest > southwest > east > south. Nearly 30 years, the wind speed has decreased year by year at the rate of 0.1 m s −1 , which directly reduce the ability to winds to transport soil in the Mu Us Sandy Land and promoted the reversal of desertification. From 1990 to 2010, the climate tended to become warmer and drier. Environmental protection policies along with human intervention and control of desertification have played important roles in reversing desertification. From 2010 to 2020, under the general background of a warm-wet climatic tendency, rational use of sand resources and strengthening scientific control of desertification inducing factors are the keys to reversing desertification.

Objective To investigate the effect of capecitabine on the sensitivity of oxaliplatin and on the level of transcription factor forkhead box P1 (FOXP1) and gamma-glutamyl transpeptidase (GGT) in patients with intermediate and advanced gastric cancer. Methods A total of 152 Patients with advanced gastric cancer who were continuously diagnosed and treated in our hospital were selected as the study objects. The general data were retrospectively analyzed. The patients in the control group received oxaliplatin, while the patients in the study group received capecitabine on the basis of the control group. The FOXP1 expression level was detected using immunohistochemistry. Serum levels of GGT were measured by chemiluminescence. Protein levels were detected by Western blot. The prognostic factors were analyzed by the COX regression model. The Kaplan–Meier survival curve was used to analyze the survival of gastric cancer. Results The effective rates (complete response, partial response, and stability) of the study group and the control group were 94.74% and 76.32%, respectively. Compared with adjacent normal tissues, the expression level of FOXP1 in gastric cancer tissues was lower ( P  < 0.05). After treatment, the average expression level of FOXP1 in the gastric cancer tissue of the study group was higher than the control group ( P  < 0.05). Moreover, lower FOXP1 expression was associated with lower overall survival (OS) (1-year survival and 3-year survival were 75.76% and 53.03%, respectively) ( P  < 0.05). Further analysis showed that capecitabine combined with oxaliplatin down-regulated the expression of DNA repair related-proteins and up-regulated the expression of key molecules of the apoptosis pathway, thus enhancing the killing effect of oxaliplatin on gastric cancer cells ( P  < 0.05). Both the 1-year and 3-year survival rates of the study group were higher than that in the control group ( P  < 0.05). The 1-year survival rate of 152 patients with gastric cancer was 84.87% (129/152) and the 3-year survival rate was 63.17% (96/152). Age, tumor-node-metastasis (TNM) stage, lymph node metastasis, chemotherapy regimen, FOXP1, and GGT levels were important factors in determining OS. Conclusion Capecitabine effectively enhanced the sensitivity of intermediate and advanced gastric cancer to oxaliplatin, improved the therapeutic effect and ameliorated the prognosis of patients. Graphical Abstract

Immune checkpoint blockade (ICB) therapy has evolved as a revolutionized therapeutic modality to eradicate tumor cells by releasing the brake of the antitumor immune response. However, only a subset of patients could benefit from ICB treatment currently. Phototherapy usually includes photothermal therapy (PTT) and photodynamic therapy (PDT). PTT exerts a local therapeutic effect by using photothermal agents to generate heat upon laser irradiation. PDT utilizes irradiated photosensitizers with a laser to produce reactive oxygen species to kill the target cells. Both PTT and PDT can induce immunogenic cell death in tumors to activate antigen-presenting cells and promote T cell infiltration. Therefore, combining ICB treatment with PTT/PDT can enhance the antitumor immune response and prevent tumor metastases and recurrence. In this review, we summarized the mechanism of phototherapy in cancer immunotherapy and discussed the recent advances in the development of phototherapy combined with ICB therapy to treat malignant tumors. Moreover, we also outlined the significant progress of phototherapy combined with targeted therapy or chemotherapy to improve ICB in preclinical and clinical studies. Finally, we analyzed the current challenges of this novel combination treatment regimen. We believe that the next-generation technology breakthrough in cancer treatment may come from this combinational win-win strategy of photoimmunotherapy.

Notch signaling represents a key mechanism mediating cancer metastasis and stemness. To understand how Notch signaling is overactivated to couple tumor metastasis and self-renewal in NSCLC cells, we performed the current study and showed that RFC4, a DNA replication factor amplified in more than 40% of NSCLC tissues, directly binds to the Notch1 intracellular domain (NICD1) to competitively abrogate CDK8/FBXW7-mediated degradation of NICD1. Moreover, RFC4 is a functional transcriptional target gene of Notch1 signaling, forming a positive feedback loop between high RFC4 and NICD1 levels and sustained overactivation of Notch signaling, which not only leads to NSCLC tumorigenicity and metastasis but also confers NSCLC cell resistance to treatment with the clinically tested drug DAPT against NICD1 synthesis. Furthermore, together with our study, analysis of two public datasets involving more than 1500 NSCLC patients showed that RFC4 gene amplification, and high RFC4 and NICD1 levels were tightly correlated with NSCLC metastasis, progression and poor patient prognosis. Therefore, our study characterizes the pivotal roles of the positive feedback loop between RFC4 and NICD1 in coupling NSCLC metastasis and stemness properties and suggests its therapeutic and diagnostic/prognostic potential for NSCLC therapy. Activated Notch signalling promotes cancer metastasis and stemness. Here the authors show that Notch1 activates transcription of DNA replication factor RCF4 and that RCF4 binds and stabilises Notch1 intracellular domain (NICD1) to promote cancer metastasis.

Planting forests is an effective way to improve desertification. In order to elucidate the impacts of different vegetation types on soil development and restoration of degraded lands, we compared the properties of soils at different depths in three plantation forests in the Hunsandak Sandy Land in the Chinese agro-pastoral ecotone ( Ulmus pumila , Pinus sylvestris var. mongolica , and Populus simonii ). The results show that all three plantation forests were able to significantly improve the soil properties, and they resulted in soil nutrient enrichment in the surface layer. As the soil depth increased, the soil became progressively poorer in nutrients, the fine particle content decreased, and the bulk density and water content increased. The orders of the fractal dimension characterization and soil improvement effects of the different tree species were as follows: U. pumila  >  P. sylvestris var. mongolica  >  P. simonii . Compared with the bare sand, the soil bulk density under the U. pumila plantation was 19% lower; the soil water content was 74% higher; the soil organic matter, total N, P, and K were 336%, 207%, 106%, and 31% higher; the available N, P, and K were 41%, 125%, and 21% higher; and the clay and silt contents were 498% and 387% higher, respectively. The ranges of the soil fractal dimension were 1.67–2.08 for the bare sandy land and 2.14–2.32 for the planted forests. The soil fractal dimension was strongly correlated with the soil physicochemical properties, especially with the soil nutrients and fine particle content, which exhibited highly significant correlations ( p  < 0.01), and the correlation coefficients were all greater than 0.8. Therefore, we believe that U. pumila is a suitable sand-fixing plant species in this area. In addition, the soil fractal dimension can be used as an important reference index for characterizing soil properties in sandy areas.