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Lower hybrid wave (LHW) current drive plays a crucial role in sustaining steady-state (SS) discharges on the Experimental Advanced Superconducting Tokamak (EAST). Hotspots frequently form on the wave antenna and guard limiters during SS operations. Although both experimental and theoretical studies suggest that fast electrons could be responsible for these hotspots, the underlying mechanisms of fast electron generation under typical EAST operational parameters and their impact on the hotspots remain unresolved. In this work, particle-in-cell simulations are used to investigate the interactions between LHWs and electrons in front of the antenna, taking into account the realistic incident power spectra and localized field effects. The results show that, due to resonance overlap, fast electrons are produced through resonant interactions between electrons and LHW components with a high parallel refractive index ( N _∥ ). The velocity distribution function in velocity space is found to significantly depend on plasma parameters near the antenna, such as q _95 , electron temperature, and input power. These fast electrons notably enhance the sheath potential on the guard limiters and increase the heat flux to the wall.

Oncolytic viruses (OVs) have emerged as a potential strategy for tumor treatment due to their ability to selectively replicate in tumor cells, induce apoptosis, and stimulate immune responses. However, the therapeutic efficacy of single OVs is limited by the complexity and immunosuppressive nature of the tumor microenvironment (TME). To overcome these challenges, engineering OVs has become an important research direction. This review focuses on engineering methods and multi-modal combination therapies for OVs aimed at addressing delivery barriers, viral phagocytosis, and antiviral immunity in tumor therapy. The engineering approaches discussed include enhancing in vivo immune response, improving replication efficiency within the tumor cells, enhancing safety profiles, and improving targeting capabilities. In addition, this review describes the potential mechanisms of OVs combined with radiotherapy, chemotherapy, cell therapy and immune checkpoint inhibitors (ICIs), and summarizes the data of ongoing clinical trials. By continuously optimizing engineering strategies and combination therapy programs, we can achieve improved treatment outcomes and quality of life for cancer patients.

Remote sensing image analysis plays a vital role in achieving intelligent agricultural monitoring. However, the acquisition of high-resolution agricultural remote sensing data can be resource-intensive, resulting in an imbalance between training samples and artificial intelligence model parameters. In order to achieve accurate agricultural land recognition of limited-resolution remote sensing images, this article proposes a joint network of super-resolution and active learning (AL). The network introduces a pretrained image super-resolution model and optimizes this for remote sensing classification tasks. It effectively detects detailed features and completes the reconstruction. Based on the reconstructed data, an AL algorithm is proposed with a DBSS. It balances the contributions between interclass and boundary samples. Furthermore, we propose a semisupervisory assistance strategy based on consistency, it fully utilizes the predictive power of deep learning models aiming to reduce labeling costs. This framework is proved effective by experiments on an agricultural remote sensing image dataset, it reduces the cost of agricultural data annotation and improves the efficiency of model learning for low-resolution agricultural remote sensing.

Abstract Bladder cancer (BC) is one of the most prevalent malignancies worldwide and FGFR3 alterations are particularly common in BC. Despite approval of erdafitinib, durable responses for FGFR inhibitors are still uncommon and most patients relapse to metastatic disease. Given the necessity to discover more efficient therapies for BC, herein, we sought to explore promising synergistic combinations for BC with FGFR3 fusions. Our studies confirmed the synergy between FGFR and HDAC inhibitors in vitro and demonstrated its benefits in vivo. Mechanistic studies revealed that quisinostat can downregulate FGFR3 expression by suppressing FGFR3 translation. Additionally, quisinostat can also sensitize BC cells to erdafitinib by downregulating HDGF. Furthermore, the synergy was also confirmed in BC cells with FGFR3 S249C. This study discovers a new avenue for treatment of FGFR3-driven BC and uncovers new mechanistic insights. These preclinical studies pave the way for a direct translation of this combination to early phase clinical trials.

Abstract Intrahepatic cholangiocarcinoma (ICC) remains a deadly malignancy lacking systemic therapies for advanced disease. Recent advancements include selective FGFR1–3 inhibitors for the 15% of ICC patients harboring fusions, although survival is limited by poor response and resistance. Herein we report generation of a patient-derived FGFR2 fusion-positive ICC model system consisting of a cell line, organoid, and xenograft, which have undergone complete histologic, genomic, and phenotypic characterization, including testing standard-of-care systemic therapies. Using these FGFR2 fusion-positive ICC models, we conducted an unbiased high-throughput small molecule screen to prioritize combination strategies with FGFR inhibition, from which HDAC inhibition together with pemigatinib was validated in vitro and in vivo as a synergistic therapy for ICC. Additionally, we demonstrate broad utility of the FGFR/HDAC combination for other FGFR fusion-positive solid tumors. These data are directly translatable and justify early phase trials to establish dosing, safety, and therapeutic efficacy of this synergistic combination.

Soy molasses is rich in oligosaccharides like sucrose, stachyose, and raffinose, with stachyose and raffinose being functional oligosaccharides. Harnessing soy molasses for the production of functional soy oligosaccharides (FSO) can significantly elevate its value. Biological purification, a method leveraging the selective utilization of different carbon sources by microorganisms, allows for the specific removal of sucrose from soy molasses while preserving stachyose and raffinose, thereby increasing the FSO content. This research identified a yeast named YT312 with strong purification capabilities for soy molasses and optimized the purification conditions. The study revealed that yeast YT312 was Wickerhamomyces anomalus, exhibiting a broad range of growth temperatures and pH levels alongside a high tolerance to glucose, sucrose, and NaCl. Through single-factor and orthogonal experiments, it was established that under specific conditions—0.375% inoculum size, 30 °C fermentation temperature, 150 rpm shaking speed, 10-fold dilution ratio, pH of 7, and 12 h of fermentation—sucrose was completely removed from soy molasses, while functional raffinose and stachyose were retained at rates of 96.1% and 90.2%, respectively. Consequently, W. anomalus YT312 displayed exceptional characteristics for the biological purification of soy molasses and the production of FSO.

The altered expression of ARMCX1 in patients with gastric cancer has been reported frequently, yet its correlation to prognosis and chemotherapy needs to be unveiled. In combination of the gene expression data retrieved from TCGA database and bioinformatic analysis, this study discovered 590 differentially expressed genes in the cancerous biopsies isolated from gastric patients, compared with controls. Among which, ARMCX1 exhibited great potential to serve as a prognostic biomarker for gastric patients; furthermore, patients with low expression of ARMCX1 could be more sensitive to these 9 chemotherapeutic agents: A-770041, AMG-706, ATRA, BEZ235, bortezomib, CGP60474, dasatinib, HG-64-1, and pazopanib, rather than the other chemotherapeutic agents. This study helps the improvement of evaluating the prognosis of gastric cancer patients, and would help optimize chemotherapeutic strategies in consideration of the expression of ARMCX1.

Ferroptosis resistance is vital for B cell development, especially in inflammatory diseases, yet the underlying mechanism is still unclear. In this study, based on the scRNA-seq technique and flow cytometry, we discovered a proportion of neutrophils exhibited upregulated expression of the IL-6 and correlated with the expression of IL-6 receptor and SLC7A11 from B cells in lupus kidney. Moreover, we identified that in lupus kidney, neutrophils could provide IL-6 to facilitate ferroptosis resistance in B cells via SLC7A11, and inhibition of SLC7A11 could significantly enhance ferroptosis in B cells and could decrease B cell proliferation. This study helps understand the crosstalk between neutrophils and B cells in the kidney in the development of lupus.

Head and neck squamous cell carcinoma (HNSCC) usually has a poor prognosis and is associated with a high mortality rate. Its etiology is mainly the result from long-term exposure to either alcohol, tobacco or human papillomavirus (HPV) infection or a combination of these insults. However, HNSCC patients with HPV have been found to show a survival advantage over those without the virus, but the mechanism that confers this advantage is unclear. Due to the large number of HPV-independent HNSCC cases, there is a possibility that the difference in prognosis between HPV-positive (HPV+) and negative (HPV-) patients is due to different carcinogens. To clarify this, we used scRNA data and viral tracking methods in order to identify HPV+ and HPV- cells in the tumour tissues of patients infected with HPV. By comparing HPV+ and HPV- malignant cells, we found a higher level of tumour stemness in HPV- tumour cells. Using tumour stemness-related genes, we established a six-gene prognostic signature that was used to divide the patients into low- and high-risk groups. It was found that HPV patients who were at low-risk of contracting HNSCC had a higher number of CD8+ T-cells as well as a higher expression of immune checkpoint molecules. Correspondingly, we found that HPV+ tumour cells expressed higher levels of CCL4, and these were highly correlated with CD8+ T cells infiltration and immune checkpoint molecules. These data suggest that the stemness features of tumour cells are not only associated with the prognostic risk, but that it could also affect the immune cell interactions and associated signalling pathways.

Post-stroke depression (PSD) is a common cerebrovascular complication characterized by complex pathogenesis and poor treatment effects. Here, we tested the influence of differentially expressed genes (DEGs), non-targeted metabolites, and intestinal microbes on the occurrence and development of PSD. We acquired gene expression profiles for stroke patients, depression patients, and healthy controls from the Gene Expression Omnibus database. After screening for DEGs using differential expression analysis, we identified common DEGs in stroke and depression patients that were considered to form the molecular basis of PSD. Functional enrichment analysis of DEGs also revealed that the majority of biological functions were closely related to metabolism, immunity, the nervous system, and microorganisms, and we also collected blood and stool samples from healthy controls, stroke patients, and PSD patients and performed 16S rDNA sequencing and untargeted metabolomics. After evaluating the quality of the sequencing data, we compared the diversity of the metabolites and intestinal flora within and between groups. Metabolic pathway enrichment analysis was used to identify metabolic pathways that were significantly involved in stroke and PSD, and a global metabolic network was constructed to explore the pathogenesis of PSD. Additionally, we constructed a global regulatory network based on 16S rDNA sequencing, non-targeted metabolomics, and transcriptomics to explore the pathogenesis of PSD through correlation analysis. Our results suggest that intestinal flora associates the dysregulation of cerebral cortex gene expression and could potentially promote the occurrence of depression by affecting the metabolism of stroke patients. Our findings may be helpful in identifying new targets for the prevention and treatment of PSD.

Oriented object detection is a challenging task in scene text detection and remote sensing image analysis, and it has attracted extensive attention due to the development of deep learning in recent years. Currently, mainstream oriented object detectors are anchor-based methods. These methods increase the computational load of the network and cause a large amount of anchor box redundancy. In order to address this issue, we proposed an anchor-free oriented object detection method based on Gaussian centerness (AOGC), which is a single-stage anchor-free detection method. Our method uses contextual attention FPN (CAFPN) to obtain the contextual information of the target. Then, we designed a label assignment method for the oriented objects, which can select positive samples with higher quality and is suitable for large aspect ratio targets. Finally, we developed a Gaussian kernel-based centerness branch that can effectively determine the significance of different anchors. AOGC achieved a mAP of 74.30% on the DOTA-1.0 datasets and 89.80% on the HRSC2016 datasets, respectively. Our experimental results show that AOGC exhibits superior performance to other methods in single-stage oriented object detection and achieves similar performance to the two-stage methods.

Rapid urbanization has led to a significant expansion of urban space, causing ecological problems such as fragmentation, declining landscape connectivity, and decreasing biodiversity. There is an urgent need to mitigate the conflict between urban expansion and ecological environmental protection by constructing ecological networks to help promote sustainable regional development. This study selected the Funiu Mountain area as the study area. Morphological spatial pattern analysis, the minimal cumulative resistance model, and network index evaluation were used to construct an ecological network in the study area and conduct a comparative analysis with local nature reserves. The results showed: (1) nine ecological source sites were identified, concentrated in the central and northern regions, which had a high spatial overlap with local nature reserves; (2) 34 ecological corridors were extracted, which could effectively connect all ecological source sites as well as most nature reserves; (3) 32 ecological nodes were identified, of which 20 strategic points were scattered along ecological corridors, and 12 artificial environment points were scattered in low-lying areas around nature reserves; (4) the ecological network showed a structure of central concentration and peripheral dispersion. The structural evaluation of the network indicated that it had strong integrity.

Gastrointestinal (GI) symptoms represented by constipation were significant non-motor symptoms of Parkinson’s disease (PD) and were considered early manifestations and aggravating factors of the disease. This paper reviewed the research progress of the mechanism of the gut-brain axis (GBA) in PD and discussed the roles of α-synuclein, gut microbiota, immune inflammation, neuroendocrine, mitochondrial autophagy, and environmental toxins in the mechanism of the GBA in PD. Treatment of PD based on the GBA theory has also been discussed, including (1) dietary therapy, such as probiotics, vitamin therapy, Mediterranean diet, and low-calorie diet, (2) exercise therapy, (3) drug therapy, including antibiotics; GI peptides; GI motility agents, and (4) fecal flora transplantation can improve the flora. (5) Vagotomy and appendectomy were associated but not recommended.

High-risk human papillomavirus (hrHPV) infection has been associated with a higher probability of progression to cervical cancer. However, several extensive studies have reported that the presence of hrHPV can lead to a better prognosis, but the mechanism of how this occurs is unclear. In this study, microbiological analysis was used to identify HPV infection as a factor for the prognosis of patients with cervical squamous cell carcinoma (CSCC). Comparing the interactions of HPV+ and HPV- malignant cells with immune cells as well as the trajectory of malignant cells either with or without HPV, we found that most of the HPV+ cells are well differentiated while HPV- cells appear to be hypo-fractionated. Using transcriptomic and immunostaining data, we validated a set of unfavourable molecules in the HPV- CSCC cells, including KRT16, ITGB1, CXCR1, VEGFA, CRCT1 and TNFRSF10B/DR5. This study provides a basis for the development of a rational post-operative follow-up programme and the development of an appropriate treatment plan for patients with cervical cancer.

Clear cell renal cell carcinoma (ccRCC) usually affects multiple organs (e.g., bone and brain), and patient prognosis is usually poor. Although it is known that CD8+ T cell infiltration can potentially alleviate ccRCC progression, few studies have concentrated on the correlation between CD8+ T cell infiltration and ccRCC prognosis. In this study, ten genes expressed by infiltrated CD8+ T cells (i.e., AMD1, CCSER2, CIB1, DRAP1, HMGB2, HMGN1, NPIPB5, PTP4A2, RORA, and SAP18) were suggested as potential ccRCC prognostic biomarkers, by using next-generation sequencing (i.e. bulk sequencing and single-cell sequencing) of ccRCC, papillary renal cell carcinoma (papRCC), and control kidney biopsies. Specifically, we identified four genes (i.e., CCSER2, DRAP1, NPIPB5, and SAP18) as potential novel prognostic biomarkers for ccRCC. It is noteworthy that SAP18 derived from CD8+ T cells negatively correlates to Atg7+ neutrophils in ccRCC, compared with papRCC, indicating a potential decreased neutrophil metabolic function in autophagy and fatty acids. This study elucidated the protective role of infiltrated CD8+ T cells in ccRCC and identified ten candidate genes related to an improved prognosis in patients with ccRCC.

Cardiac rehabilitation, which combines cardiology and preventive medicine, is an important part of treatment for cardiovascular diseases. Systematically, cardiac rehabilitation, including simultaneously inhibiting endothelial injury and promoting endothelial repair, is beneficial for physical and mental recovery and reduces the risks of recurrence and death in patients with cardiovascular diseases. Cardiac rehabilitation has developed rapidly in the last 50 years. A preliminary system for cardiac rehabilitation has been developed in China. The present article mainly focuses on the progress of cardiac rehabilitation from the aspects of goals, measures, and modes of research in the current scenario.

Inhibition of triple-negative breast cancer metastasis has long been a challenge, mainly due to the difficulty in identifying factors that contribute to this process. In this study, freshly isolated triple-negative breast cancer biopsied cells obtained from consenting patients were subjected to flow cytometry and bioinformatic analysis to identify three endothelial cell subclusters: EC (ATP1B3), EC (HSPA1B), and EC (KRT7) in the tumor microenvironment. These endothelial cell subclusters exhibited distinguishing biological features. Based on differentially expressed genes derived from the subclusters, gene set enrichment analysis showed that EC (ATP1B3) and EC (HSPA1B) contribute to the process of metastasis, for example, in fibrosarcoma and anaplastic carcinoma. In this study, we identified the heterogeneity of endothelial cells in the human breast cancer and have provided insights into its role in metastasis.

BackgroundCD8+ T cells, vital effectors pertaining to adaptive immunity, display close relationships to the immunization responses to kill tumor cells. Understanding the effect exerted by tumor infiltration CD8+ T cells in papillary renal cell carcinoma (papRCC) is critical for assessing the prognosis process and responses to immunization therapy in cases with this disease.Materials and ApproachesThe single-cell transcriptome data of papRCC were used for screening CD8+ T-cell-correlated differentially expressed genes to achieve the following investigations. On that basis, a prognosis gene signature associated with tumor infiltration CD8+ T cell was built and verified with The Cancer Genome Atlas data set. Risk scores were determined for papRCC cases and categorized as high- or low-risk groups. The prognosis significance for risk scores was assessed with multiple-variate Cox investigation and Kaplan–Meier survival curves. In addition, the possible capability exhibited by the genetic profiles of cases to assess the response to immunization therapy was further explored.ResultsSix hundred twenty-one cell death-inhibiting RNA genes were screened using single-cell RNA sequencing. A gene signature consisting of seven genes (LYAR, YBX1, PNRC1, TCF25, MYL12B, MINOS1, and LINC01420) was then identified, and this collective was considered to be an independent prognosis indicator that could strongly assess overall survival in papRCC. In addition, the data allowed papRCC cases to fall to cohorts at high and low risks, exhibiting a wide range of clinically related features as well as different CD8+ T-cell immunization infiltration and immunization therapy responses.ConclusionsOur work provides a possible explanation for the limited response of current immunization checkpoint-inhibiting elements for combating papRCC. Furthermore, the researchers built a novel genetic signature that was able to assess the prognosis and immunotherapeutic response of cases. This may also be considered as a promising therapeutic target for the disease.

One key task in virtual screening is to accurately predict the binding affinity (△G) of protein-ligand complexes. Recently, deep learning (DL) has significantly increased the predicting accuracy of scoring functions due to the extraordinary ability of DL to extract useful features from raw data. Nevertheless, more efforts still need to be paid in many aspects, for the aim of increasing prediction accuracy and decreasing computational cost. In this study, we proposed a simple scoring function (called OnionNet-2) based on convolutional neural network to predict △G. The protein-ligand interactions are characterized by the number of contacts between protein residues and ligand atoms in multiple distance shells. Compared to published models, the efficacy of OnionNet-2 is demonstrated to be the best for two widely used datasets CASF-2016 and CASF-2013 benchmarks. The OnionNet-2 model was further verified by non-experimental decoy structures from docking program and the CSAR NRC-HiQ data set (a high-quality data set provided by CSAR), which showed great success. Thus, our study provides a simple but efficient scoring function for predicting protein-ligand binding free energy.

BackgroundCD8+ T cells, which play a vital role in response to adaptive immunity, are closely related to the immunization responses to kill tumor cells. Understanding the effects exerted by tumor-infiltrated CD8+ T cells in HPV+ and HPV- head and neck squamous cell carcinoma (HNSCC) patients is critical for predicting their prognosis as well as their responses towards immunization-related therapy.Materials and MethodsHNSCC single cell transcriptome was used to screen for differentially expressed genes (DEGs) based on CD8+ T cells. A gene signature associated with CD8+ T cells was built and verified with the cancer genome atlas dataset with a view to predicting the prognosis of HNSCC patients. Risk scores were calculated for HNSCC cases and categorized into either high- or low-risk cohorts. The prognosis-correlated data of the risk scores were analyzed by using Kaplan-Meier survival curves and multi-variate Cox regression plots. In addition, the possibility of using the genetic profiles to predict responses toward immunization-related therapy was explored.ResultsFrom the DEGs screened from the sequencing of single-cell RNA, a gene signature of 4 genes (ACAP1, ANKRD28, C12orf75, and M6PR) were identified. It was seen that these genes could predict overall survival in HPV+ HNSCC patients. In addition, high- and low-risk HPV+ HNSCC patients showed marked differences in their CD8+ T-cell infiltration due to immunization when clinical characteristics were taken into consideration. This correlated with their immunization therapy responses.ConclusionsOur work provides insights into explaining the restricted responses of current immunization checkpoint inhibiting substances in HPV+ HNSCC patients. A novel genetic signature to predict the prognosis and immunization-correlated therapeutic responses is presented. This will provide potential new therapeutic opportunities for HPV+ HNSCC patients.

COVID-19 pneumonia requires effective medical therapies. However, it is a challenge to find therapeutic drugs that not only inhibit viral replication, but also inhibit the accompanying cytokine storm and maintain an appropriate immune response. In this study, the effects of SARS-CoV-2 on gene expression in lung epithelial cells from patients with COVID-19 were systematically evaluated with bioinformatics analysis methods. Transcriptome expression specific to bystander (exposed but uninfected) and infected cells were found, and the vital pathways were identified by conducting differentially expressed gene analysis regarding the relationship between gene signatures of COVID-19 infection and disease severity. We found that a high viral load did not necessarily imply a low response of epithelial cells or a poor disease convalescence. The ability to distinguish the role of virus-correlated genes facilitates the development of potential new medicines and therapies for COVID-19 infection.

Although immune therapy can improve the treatment of clear cell renal cell carcinoma (ccRCC) significantly, there are still a large proportion of ccRCC patients who progress to metastasis. Targeting the pro-metastatic immune cell in the ccRCC microenvironment could provide a solution to this problem. In this study, B cells in ccRCC biopsies were identified by using scRNA-seq and flow cytometry. The findings indicated the presence of a pro-metastatic B cell type which could be further classified into 3 subpopulations, MARCH3, B2M and DTWD1, based on their large-scaled genetic profiles, rather than traditional Immature/Mature ones. Although all of the 3 subpopulations appeared to contribute to distant metastasis, B cell (B2M) was deemed to be the most essential. Moreover, STX16, CLASRP, ATIC, ACIN1 and SEMA4B, were genes found to be commonly up-regulated in the 3 subpopulations and this was correlated to a poor prognosis of ccRCC. Furthermore, the heterogeneity of plasma cells in ccRCC was also found to contribute to metastasis of the disease. This study offers potential novel therapeutic targets against distant metastasis of cancers, and can help to improve the therapeutic efficiency of ccRCC patients.

Multiple myeloma (MM) is a lethal hematological malignancy characterized by abundant myeloid cells in the microenvironment that fuel tumor progression. But the mechanism by which myeloid cells support myeloma cells has not been fully explored. We aimed to examine their effect on bone marrow cells of MM patients by scRNA-seq transcriptome analysis and reveal a high-resolution gene profile of myeloma cells and myeloma-associated myeloid cells. Based on correlation analysis of integrated scRNA-seq and bulk RNA-seq datasets from patients, we confirmed that myeloid-derived S100A9 was involved in TNFSF13B-dependent myeloma cell proliferation and survival. In the animal experiments, S100A9 was found to be critical for MM cell proliferation and survival via TNFSF13B production by myeloid cells, neutrophils, and macrophages. In-vitro analysis of patient primary myeloma cells further demonstrated that enhanced TNFSF13B signaling triggered the canonical NF-κB pathway to boost tumor cell proliferation. All these results suggest that myeloid-derived S100A9 is required for TNFSF13B/TNFRSF13B-dependent cell-fate specification, which provides fresh insights into MM progression.

Plantation forestry of Eucalyptus urophylla × Eucalyptus grandis supplies high-quality raw material for pulp, paper, wood, and energy and thereby reduces the pressures on native forests and their associated biodiversity. Nevertheless, owing to the heterozygosity of the E. urophylla × E. grandis genetic background, germplasm improvement by crossbreeding tends to be inefficient. As an alternative approach, genetic engineering of Eucalyptus can be used to effectively improve germplasm resources. From a strategic standpoint, increasing the plantation productivity and wood quality by transgenic technology has become increasingly important for forest industry. In this study, we established a fluorescence labelling method using CRISPR/Cas9 technology to obtain positive transformed progenies. The positive transformed progenies were easily obtained from the genetically modified population via fluorescence screening. This system can be used as a plant genome site-specific editing tool and may be useful for improving Eucalyptus genetic resources.

In this study, we analyzed differences in the enzyme activities and transcriptomes of embryogenic and non-embryogenic calli to gain insights for improving the success of tissue culture-based breeding. A total of 2,856 differentially expressed genes (DEGs; 1,632 up-regulated and 1,224 down-regulated) were identified based on RNA sequencing and verified by reverse transcription quantitative polymerase chain reaction. Gene set enrichment analysis revealed that many of the up-regulated DEGs in embryogenic callus were enriched in the photosynthesis processes. Furthermore, the enzyme activity, hormone content, and cytokinin oxidase/dehydrogenase (CKX) gene expression analyses were found to be consistent with the transcriptome results. Cytokinin biosynthesis in N-phenyl-N′-[6-(2-chlorobenzothiazol)-yl] urea (PBU)-induced embryogenic callus increased owing to CKX repression. Measurement of endogenous hormones by high-performance liquid chromatography revealed that, compared with non-embryogenic callus, in embryogenic callus, the indole-3-acetic acid, abscisic acid and trans-zeatin riboside content had significantly higher values of 129.7, 127.8 and 78.9 ng/g, respectively. Collectively, the findings of this study will provide a foundation for elucidating the molecular mechanisms underlying embryogenic callus differentiation and can potentially contribute to developing procedures aimed at enhancing the success of callus-based plant regeneration.

Stroke is a cerebrovascular disease that results in decreased blood flow. Although Panax notoginseng (PN), a Chinese herbal medicine, has been proven to promote stroke recovery, its molecular mechanism remains unclear. In this study, middle cerebral artery occlusion (MCAO) was induced in rats with thrombi generated by thread and subsequently treated with PN. After that, staining with 2,3,5-triphenyltetrazolium chloride was employed to evaluate the infarcted area, and electron microscopy was used to assess ultrastructural changes of the neurovascular unit. RNA-Seq was performed to determine the differential expressed genes (DEGs) which were then verified by qPCR. In total, 817 DEGs were identified to be related to the therapeutic effect of PN on stroke recovery. Further analysis by Gene Oncology analysis and Kyoto Encyclopedia of Genes and Genomes revealed that most of these genes were involved in the biological function of nerves and blood vessels through the regulation of neuroactive live receptor interactions of PI3K-Akt, Rap1, cAMP, and cGMP-PKG signaling, which included in the 18 pathways identified in our research, of which, 9 were reported firstly that related to PN’s neuroprotective effect. This research sheds light on the potential molecular mechanisms underlying the effects of PN on stroke recovery.

Immune tolerance research is essential for kidney transplantation. Other than antibody and T cell-mediated immune rejection, macrophage-mediated innate immunity plays an important role in the onset phase of transplantation rejection. However, due to the complexity of the kidney environment as well as its diversity and low abundance, studies pertaining to monocyte/macrophages in kidney transplantation require further elucidation. In this study, kidney samples taken from healthy human adults and biopsy specimens from patients undergoing rejection following kidney transplantation were analysed and studied. By conducting a single-cell RNA analysis, the type and status of monocyte/macrophages in kidney transplantation were described, in which monocyte/macrophages were observed to form two different subpopulations: resident and infiltrating monocyte/macrophages. Furthermore, previously defined genes were mapped to all monocyte/macrophage types in the kidney and enriched the differential genes of the two main subpopulations using gene expression databases. Considering that various cases of rejection may be of the monocyte/macrophage type, the present data may serve as a reference for studies regarding immune tolerance following kidney transplantation.

We introduce a deep learning-based ligand pose scoring model called zPoseScore for predicting protein–ligand complexes in the 15th Critical Assessment of Protein Structure Prediction (CASP15). Our contributions are threefold: first, we generate six training and evaluation data sets by employing advanced data augmentation and sampling methods. Second, we redesign the “zFormer” module, inspired by AlphaFold2's Evoformer, to efficiently describe protein–ligand interactions. This module enables the extraction of protein–ligand paired features that lead to accurate predictions. Finally, we develop the zPoseScore framework with zFormer for scoring and ranking ligand poses, allowing for atomic-level protein–ligand feature encoding and fusion to output refined ligand poses and ligand per-atom deviations. Our results demonstrate excellent performance on various testing data sets, achieving Pearson's correlation R = 0.783 and 0.659 for ranking docking decoys generated based on experimental and predicted protein structures of CASF-2016 protein–ligand complexes. Additionally, we obtain an averaged local distance difference test (lDDT pli = 0.558) of AIchemy LIG2 in CASP15 for de novo protein–ligand complex structure predictions. Detailed analysis shows that accurate ligand binding site prediction and side-chain orientation are crucial for achieving better prediction performance. Our proposed model is one of the most accurate protein–ligand pose prediction models and could serve as a valuable tool in small molecule drug discovery. [ABSTRACT FROM AUTHOR]