Core Module Research Articles

Uncoupling the TFIIH Core and Kinase Modules Leads To Misregulated RNA Polymerase II CTD Serine 5 Phosphorylation.

TFIIH is an essential transcription initiation factor for RNA polymerase II (RNApII). This multi-subunit complex comprises two modules that are physically linked by the subunit Tfb3 (MAT1 in metazoans). The TFIIH Core Module, with two DNA-dependent ATPases and several additional subunits, promotes DNA unwinding. The TFIIH Kinase Module phosphorylates Serine 5 of the C-terminal domain (CTD) of RNApII subunit Rpb1, a modification that coordinates exchange of initiation and early elongation factors. While it is not obvious why these two disparate activities are bundled into one factor, the connection may provide temporal coordination during early initiation. Here we show that Tfb3 can be split into two parts to uncouple the TFIIH modules. The resulting cells grow slower than normal, but are viable. Chromatin immunoprecipitation of the split TFIIH shows that the Core Module, but not the Kinase, is properly recruited to promoters. Instead of the normal promoter-proximal peak, high CTD Serine 5 phosphorylation is seen throughout transcribed regions. Therefore, coupling the TFIIH modules is necessary to localize and limit CTD kinase activity to early stages of transcription. These results are consistent with the idea that the two TFIIH modules began as independent functional entities that became connected by Tfb3 during early eukaryotic evolution.

Uncovering periodontitis-associated markers through the aggregation of transcriptomics information from diverse sources.

Periodontitis, a common chronic inflammatory disease, significantly impacted oral health. To provide novel biological indicators for the diagnosis and treatment of periodontitis, we analyzed public microarray datasets to identify biomarkers associated with periodontitis. The Gene Expression Omnibus (GEO) datasets GSE16134 and GSE106090 were downloaded. We performed differential analysis and robust rank aggregation (RRA) to obtain a list of differential genes. To obtain the core modules and core genes related to periodontitis, we evaluated differential genes through enrichment analysis, correlation analysis, protein-protein interaction (PPI) network and competing endogenous RNA (ceRNA) network analysis. Potential biomarkers for periodontitis were identified through comparative analysis of dual networks (PPI network and ceRNA network). PPI network analysis was performed in STRING. The ceRNA network consisted of RRA differentially expressed messenger RNAs (RRA_DEmRNAs) and RRA differentially expressed long non-coding RNAs (RRA_DElncRNAs), which regulated each other's expression by sharing microRNA (miRNA) target sites. RRA_DEmRNAs were significantly enriched in inflammation-related biological processes, osteoblast differentiation, inflammatory response pathways and immunomodulatory pathways. Comparing the core ceRNA module and the core PPI module, C1QA, CENPK, CENPU and BST2 were found to be the common genes of the two core modules, and C1QA was highly correlated with inflammatory functionality. C1QA and BST2 were significantly enriched in immune-regulatory pathways. Meanwhile, LINC01133 played a significant role in regulating the expression of the core genes during the pathogenesis of periodontitis. The identified biomarkers C1QA, CENPK, CENPU, BST2 and LINC01133 provided valuable insight into periodontitis pathology.

Deciphering the Binding of 5' Stem Loop RNA to the La Domain of Human LARP6.

La-related protein 6 regulates the highly organized biosynthesis of type I procollagen polypeptides and affects proper assembly of procollagen peptides into heterotrimers of type I procollagen. LARP6-mediated regulation of collagen biosynthesis is mediated through interaction with the 5' stem loop motif found in type I and III collagen mRNA. Recent studies highlight the involvement of HsLARP6 in fibroproliferative diseases and its potential as a target for therapeutic intervention. The intrinsic instability of the La domain of HsLARP6 hampers studies probing the molecular basis of biologically- and disease-relevant structure-function relationship, particularly when high concentrations are required. This work provides detailed procedures to produce milligram amounts of RNase-free and functional La domain of HsLARP6. Furthermore, we investigated the effect of the construct length as well as RNA binding on protein stability. N- and C-terminal extensions greatly impact stability based on interactions with the core domain and modulation of the pI. When in complex with its cognate 5'SL RNA, the La domain shows unprecedented stability compared to the aggregation-prone unbound state. The protein-RNA complex remains stable for at least 50x longer than the unbound state, under identical conditions, likely due to a global change in conformational plasticity upon RNA binding. These results provide a foundation for further studies of the molecular recognition of 5'SL by HsLARP6 as well as a platform for refining potential antifibrotic therapeutics.

Tsc22d3 promotes morphine tolerance in mice through the GPX4 ferroptosis pathway.

Morphine tolerance refers to gradual reduction in response to drug with continuous or repeated use of morphine, requiring higher doses to achieve same effect. The morphine tolerance dataset GSE7762 profiles, obtained from gene expression omnibus (GEO) database, were used to identify differentially expressed genes (DEGs). Weighted Gene Co-expression Network Analysis (WGCNA) was applied to explore core modules of DEGs related to morphine tolerance. Core genes were input into Comparative Toxicogenomics Database (CTD). Animal experiments were performed to validate role of Tsc22d3 in morphine tolerance and its relationship with ferroptosis-related pathway. 500 DEGs were identified. DEGs were primarily enriched in negative regulation of brain development, neuronal apoptosis processes, and neurosystem development. Core gene was identified as Tsc22d3. Tsc22d3 gene-associated miRNAs were mmu-miR-196b-5p and mmu-miR-196a-5p. Compared to Non-morphine tolerant group, Tsc22d3 expression was significantly upregulated in Morphine tolerant group. Tsc22d3 expression was upregulated in Morphine tolerant+Tsc22d3_OE, expression of HIF-1alpha, GSH, GPX4 in GPX4 ferroptosis-related pathway showed a more pronounced decrease. As Tsc22d3 expression was downregulated in Morphine tolerant+Tsc22d3_KO, expression of HIF-1alpha, GSH, GPX4 in GPX4 ferroptosis-related pathway exhibited a more pronounced increase. Upregulation of Tsc22d3 in Morphine tolerant+Tsc22d3_OE led to a more pronounced increase in expression of apoptosis proteins (P53, Caspase-3, Bax, SMAC, FAS). The expression of inflammatory factors (IL6, TNF-alpha, CXCL1, CXCL2) showed a more pronounced increase with upregulated Tsc22d3 expression in Morphine tolerant+Tsc22d3_OE. Tsc22d3 is highly expressed in brain tissue of morphine-tolerant mice, activating ferroptosis pathway, enhancing apoptosis, promoting inflammatory responses in brain cells.

Establishment of a prognostic model for hypoxia-associated genes in OPSCC and revelation of intercellular crosstalk.

Hypoxia exerts a profound influence on the tumor microenvironment and immune response, shaping treatment outcomes and prognosis. Utilizing consistency clustering, we discerned two hypoxia subtypes in OPSCC bulk sequencing data from GEO. Key modules within OPSCC were identified through weighted gene correlation network analysis (WGCNA). Core modules underwent CIBERSORT immune infiltration analysis and GSEA functional enrichment. Univariate Cox and LASSO analyses were employed to construct prognostic models for seven hypoxia-related genes. Further investigation into clinical characteristics, the immune microenvironment, and TIDE algorithm prediction for immunotherapy response was conducted in high- and low-risk groups. scRNA-seq data were visually represented through TSNE clustering, employing the scissors algorithm to map hypoxia phenotypes. Interactions among cellular subpopulations were explored using the Cellchat package, with additional assessments of metabolic and transcriptional activities. Integration with clinical data unveiled a prevalence of HPV-positive patients in the low hypoxia and low-risk groups. Immunohistochemical validation demonstrated low TDO2 expression in HPV-positive (P16-positive) patients. Our prediction suggested that HPV16 E7 promotes HIF-1α inhibition, leading to reduced glycolytic activity, ultimately contributing to better prognosis and treatment sensitivity. The scissors algorithm effectively segregated epithelial cells and fibroblasts into distinct clusters based on hypoxia characteristics. Cellular communication analysis illuminated significant crosstalk among hypoxia-associated epithelial, fibroblast, and endothelial cells, potentially fostering tumor proliferation and metastasis.

Comprehensive pan-cancer analysis of mitochondrial outer membrane permeabilisation activity reveals positive immunomodulation and assists in identifying potential therapeutic targets for immunotherapy resistance.

Mitochondrial outer membrane permeabilisation (MOMP) plays a pivotal role in cellular death and immune activation. A deeper understanding of the impact of tumour MOMP on immunity will aid in guiding more effective immunotherapeutic strategies. A comprehensive pan-cancer dataset comprising 30 cancer-type transcriptomic cohorts, 20 immunotherapy transcriptomic cohorts and three immunotherapy scRNA-seq datasets was collected and analysed to determine the influence of tumour MOMP activity on clinical prognosis, immune infiltration and immunotherapy effectiveness. Leveraging 65 scRNA-Seq datasets, the MOMP signature (MOMP.Sig) was developed to accurately reflect tumour MOMP activity. The clinical predictive value of MOMP.Sig was explored through machine learning models. Integration of the MOMP.Sig model and a pan-cancer immunotherapy CRISPR screen further investigated potential targets to overcome immunotherapy resistance, which subsequently underwent clinical validation. Our research revealed that elevated MOMP activity reduces mortality risk in cancer patients, drives the formation of an anti-tumour immune environment and enhances the response to immunotherapy. This finding emphasises the potential clinical application value of MOMP activity in immunotherapy. MOMP.Sig, offering a more precise indicator of tumour cell MOMP activity, demonstrated outstanding predictive efficacy in machine-learning models. Moreover, with the assistance of the MOMP.Sig model, FOXO1 was identified as a core modulator that promotes immune resistance. Finally, these findings were successfully validated in clinical immunotherapy cohorts of skin cutaneous melanoma and triple-negative breast cancer patients. This study enhances our understanding of MOMP activity in immune modulation, providing valuable insights for more effective immunotherapeutic strategies across diverse tumours.

Statistical Testing for Protein Equivalence Identifies Core Functional Modules Conserved across 360 Cancer Cell Lines and Presents a General Approach to Investigating Biological Systems.

Quantitative proteomics has enhanced our capability to study protein dynamics and their involvement in disease using various techniques, including statistical testing, to discern the significant differences between conditions. While most focus is on what is different between conditions, exploring similarities can provide valuable insights. However, exploring similarities directly from the analyte level, such as proteins, genes, or metabolites, is not a standard practice and is not widely adopted. In this study, we propose a statistical framework called QuEStVar (Quantitative Exploration of Stability and Variability through statistical hypothesis testing), enabling the exploration of quantitative stability and variability of features with a combined statistical framework. QuEStVar utilizes differential and equivalence testing to expand statistical classifications of analytes when comparing conditions. We applied our method to an extensive data set of cancer cell lines and revealed a quantitatively stable core proteome across diverse tissues and cancer subtypes. The functional analysis of this set of proteins highlighted the molecular mechanism of cancer cells to maintain constant conditions of the tumorigenic environment via biological processes, including transcription, translation, and nucleocytoplasmic transport.

G-Quadruplex-Programmed Versatile Nanorobot Combined with Chemotherapy and Gene Therapy for Synergistic Targeted Therapy.

Developing synergistic targeted therapeutics to improve treatment efficacy while reducing side effects has proven promising for anticancer therapies, but how to conveniently modulate multidrug cooperation remains a challenge. Here, a novel synergistic strategy using a G-quadruplex-programmed versatile nanorobot (G4VN) containing two subunits of DNAzyme (DzG4) and ligand-drug conjugates (LDCs) is proposed to precisely target tumors and then execute both gene silencing and chemotherapy. As the core module of this nanorobot, a well-designed G4 responding to a high level of K+ in tumor microenvironment smartly kills three birds with one stone, which makes two TfR aptamers proximate to improve their efficiency of targeting tumor cells, and in situ activates a split 10-23 DNAzyme to downregulate target mRNA expression, meanwhile promotes the cell uptake of a GSH-responsive LDCs to enhance drug efficacy. Such a design enables a potently synergistic anticancer therapy with low side effects in vivo, showing great promise for broad applications in precision disease treatment.

Design and Implementation of Dongba Character Font Style Transfer Model Based on AFGAN.

Dongba characters are ancient ideographic scripts with abstract expressions that differ greatly from modern Chinese characters; directly applying existing methods cannot achieve the font style transfer of Dongba characters. This paper proposes an Attention-based Font style transfer Generative Adversarial Network (AFGAN) method. Based on the characteristics of Dongba character images, two core modules are set up in the proposed AFGAN, namely void constraint and font stroke constraint. In addition, in order to enhance the feature learning ability of the network and improve the style transfer effect, the Convolutional Block Attention Module (CBAM) mechanism is added in the down-sampling stage to help the network better adapt to input font images with different styles. The quantitative and qualitative analyses of the generated font and the real font were conducted by consulting with professional artists based on the newly built small seal script, slender gold script, and Dongba character dataset, and the styles of the small seal script and slender gold script were transferred to Dongba characters. The results indicate that the proposed AFGAN method has advantages in evaluation indexes and visual quality compared to existing networks. At the same time, this method can effectively learn the style features of small seal script and slender gold script, and transfer them to Dongba characters, indicating the effectiveness of this method.

Systems Genetics Analyses Reveals Key Genes Related to Behavioral Traits in the Striatum of CFW Mice.

The striatum plays a central role in directing many complex behaviors ranging from motor control to action choice and reward learning. In our study, we used 55 male CFW mice with rapid decay linkage disequilibrium to systematically mine the striatum-related behavioral functional genes by analyzing their striatal transcriptomes and 79 measured behavioral phenotypic data. By constructing a gene coexpression network, we clustered the genes into 13 modules, with most of them being positively correlated with motor traits. Based on functional annotations as well as Fisher's exact and hypergeometric distribution tests, brown and magenta modules were identified as core modules. They were significantly enriched for striatal-related functional genes. Subsequent Mendelian randomization analysis verified the causal relationship between the core modules and dyskinesia. Through the intramodular gene connectivity analysis, Adcy5 and Kcnma1 were identified as brown and magenta module hub genes, respectively. Knock outs of both Adcy5 and Kcnma1 lead to motor dysfunction in mice, and KCNMA1 acts as a risk gene for schizophrenia and smoking addiction in humans. We also evaluated the cellular composition of each module and identified oligodendrocytes in the striatum to have a positive role in motor regulation.

FinMem: A Performance-Enhanced LLM Trading Agent with Layered Memory and Character Design

Recent advancements in Large Language Models (LLMs) have exhibited notable efficacy in question-answering (QA) tasks across diverse domains. Their prowess in integrating extensive web knowledge has fueled interest in developing LLM-based autonomous agents. While LLMs are efficient in decoding human instructions and deriving solutions by holistically processing historical inputs, transitioning to purpose-driven agents requires a supplementary rational architecture to process multi-source information, establish reasoning chains, and prioritize critical tasks. Addressing this, we introduce FinMem, a novel LLM-based agent framework devised for financial decision-making. It encompasses three core modules: Profiling, to customize the agent's characteristics; Memory, with layered message processing, to aid the agent in assimilating hierarchical financial data; and Decision-making, to convert insights gained from memories into investment decisions. Notably, FinMem's memory module aligns closely with the cognitive structure of human traders, offering robust interpretability and real-time tuning. Its adjustable cognitive span allows for the retention of critical information beyond human perceptual limits, thereby enhancing trading outcomes. This framework enables the agent to self-evolve its professional knowledge, react agilely to new investment cues, and continuously refine trading decisions in the volatile financial environment. We first compare FinMem with various algorithmic agents on a scalable real-world financial dataset, underscoring its leading trading performance in stocks. We then fine-tuned the agent's perceptual span and character setting to achieve a significantly enhanced trading performance. Collectively, FinMem presents a cutting-edge LLM agent framework for automated trading, boosting cumulative investment returns.

Motorized Insurance with Group of Data Analysis

Storing a policy of commercial and non-commercial vehicles. So, the policies are generated from different kind of authorized companies. In these applications the branch master can analyse what is the status of issued policies. The analysis is depended on issued data policy, starting date, ending date of policy and also to manage the next intent policies, so far a kind of activities in branches are handled by excels and paper work by this work, lakh of data losing and had problem with filter of existing customers. This application is based on web technology, we have one more portal for collect number of information of vehicles and insurance companies. Storing and accessing essential information related to insurance policies, including policy holder details, coverage terms, and effective data. This module serves as a reference point for users to quickly retrieve policy- specific information.In addition to the core modules focused on insurance policy management, our student project includes a Renewal Date Reminder module to ensure timely renewal of policies on an annual basis. The Renewal Date Reminder module is designed to streamline the renewal process and mitigate the risk of policy lapses by proactively notifying policyholders and administrators of upcoming renewal deadlines. Prior to the renewal date, the system generates personalized notifications to remind policyholders of the impending deadline. These notifications can be sent via email, SMS, or through the system's dashboard, depending on user preferences.

A hierarchical occupancy network with multi‐height attention for vision‐centric 3D occupancy prediction

AbstractThe precise geometric representation and ability to handle long‐tail targets have led to the increasing attention towards vision‐centric 3D occupancy prediction, which models the real world as a voxel‐wise model solely through visual inputs. Despite some notable achievements in this field, many prior or concurrent approaches simply adapt existing spatial cross‐attention (SCA) as their 2D–3D transformation module, which may lead to informative coupling or compromise the global receptive field along the height dimension. To overcome these limitations, we propose a hierarchical occupancy (HierOcc) network featuring our innovative height‐aware cross‐attention (HACA) and hierarchical self‐attention (HSA) as its core modules to achieve enhanced precision and completeness in 3D occupancy prediction. The former module enables 2D–3D transformation, while the latter promotes voxels’ intercommunication. The key insight behind both modules is our multi‐height attention mechanism which ensures each attention head corresponds explicitly to a specific height, thereby decoupling height information while maintaining global attention across the height dimension. Extensive experiments show that our method brings significant improvements compared to baseline and surpasses all concurrent methods, demonstrating its superiority.

A Digital Behavioral Activation Intervention (JuNEX) for Pregnant Women With Subclinical Depression Symptoms: Explorative Co-Design Study.

Digital interventions are gaining increasing interest due to their structured nature, ready availability, and self-administered capabilities. Perinatal women have expressed a desire for such interventions. In this regard, behavioral activation interventions may be particularly suitable for digital administration. This study aims to exploratorily investigate and compare the feasibility of the internet-based self-help guided versus unguided version of the Brief Behavioral Activation Treatment for Depression-Revised, an empirically supported in-person behavioral activation protocol, targeting pregnant women with subclinical depression symptoms. A user-centered design is used, whereby data are collected with the intent of evaluating how to adjust the intervention in line with pregnant women's needs. Usability and user engagement were evaluated. A total of 11 Italian pregnant women with subclinical depressive symptoms based on the Patient Health Questionnaire-9 (scoring<15) participated in this study; of them, 6 (55%) women were randomly assigned to the guided group (age: mean 32.17, SD 4.36 years) and 5 (45%) to the unguided group (age: mean 31, SD 4.95 years). The Moodle platform was used to deliver the interventions in an e-learning format. It consisted of 6 core modules and 3 optional modules; the latter aimed at revising the content of the former. In the guided group, each woman had weekly chats with their assigned human guide to support them in the homework revisions. The intervention content included text, pictures, and videos. Semistructured interviews were conducted, and descriptive statistics were analyzed. Collectively, the data suggest that the guided intervention was better accepted than the unguided one. However, the high rates of dropout (at T6: guided group: 3/6, 50%; unguided: 4/5, 80%) suggest that a digital replica of Behavioral Activation Treatment for Depression-Revised may not be feasible in an e-learning format. The reduced usability of the platform used was reported, and homework was perceived as too time-consuming and effort-intensive. Moreover, the 6 core modules were deemed sufficient for the intervention's goals, suggesting that the 3 optional modules could be eliminated. Nevertheless, participants from both groups expressed satisfaction with the content and found it relevant to their pregnancy experiences. Overall, the findings have emphasized both the intervention's merits and shortcomings. Results highlight the unsuitability of replicating an in-person protocol digitally as well as of the use of nonprofessional tools for the implementation of self-help interventions, ultimately making the intervention not feasible. Pregnant women have nonetheless expressed a desire to receive psychological support and commented on the possibilities of digital psychosocial supports, particularly those that are app-based. The information collected and the issues identified here are important to guide the development and co-design of a more refined platform for the intervention deployment and to tailor the intervention's content to pregnant women's needs.

MyD88 Inhibition Attenuates Cerebral Ischemia-reperfusion Injury by Regulating the Inflammatory Response and Reducing Blood–brain Barrier Damage

Myeloid differentiation primary response gene 88 (MyD88), a downstream molecule directly linked to Toll-like receptor (TLRs) and IL1 receptor, has been implicated in ischemia-reperfusion injury across various organs. However, its role in cerebral ischemia-reperfusion injury (CIRI) remains unclear. Five transient middle cerebral artery occlusion (tMCAO) microarray datasets were obtained from the Gene Expression Omnibus (GEO) database. We screened these datasets for differentially expressed genes (DEGs) using the GSE35338 and GSE58720 datasets and performed weighted gene co-expression network analysis (WGCNA) using the GSE30655, GSE28731, and GSE32529 datasets to identify the core module related to tMCAO. A protein–protein interaction (PPI) network was constructed using the intersecting DEGs and genes in the core module. Finally, we identified Myd88 was the core gene. In addition, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Set Enrichment Analysis (GSEA) validated that TNFα, IL17, and MyD88 signaling pathways were significantly enriched in tMCAO. Subsequently, we investigated the mechanistic role of MyD88 in the tMCAO model using male C57BL/6 mice. MyD88 expression increased significantly 24 h after reperfusion. After intraperitoneal administration of TJ-M2010-5, a MyD88-specific inhibitor, during reperfusion, the infarction volumes in the mice were ameliorated. TJ-M2010-5 inhibits the activation of microglia and astrocytes. Moreover, it attenuates the upregulation of inflammatory cytokines TNFα, IL17, and MMP9 while preserving the expression level of ZO1 after tMCAO, thereby safeguarding against blood-brain barrier (BBB) disruption. Finally, our findings suggest that MyD88 regulates the IRAK4/IRF5 signaling pathway associated with microglial activation. MyD88 participates in CIRI by regulating the inflammatory response and BBB damage following tMCAO.

Mongolian Education Resource Platform Based on Springmvc+Hibernate+Spring Integration Framework

With the popularization of educational informatization and the advancement of computer technology and multimedia playback, the process of educational networking has reached new heights nationwide. The education networking in Inner Mongolia Autonomous Region is currently in a rapid development stage. In order to provide Mongolian-speaking students with the benefits of educational networking, it is imperative to design and implement a Mongolian language educational resource platform. The designed Mongolian Language Educational Resource Platform in this paper adopts a B/S architecture and utilizes the SpringMVC, Hibernate, and Spring frameworks for overall development. Firstly, the relevant technical knowledge used is introduced, including the B/S architecture, the main frameworks used, and CSS technology, among others. Then, the requirements specification and detailed design plan of the platform are elaborated, including the database design. Finally, the implementation process of the core functionalities of this Mongolian language educational resource platform is described, and unit testing methods are employed to test these core modules. The system in this paper achieves the basic functionalities of the Mongolian language educational resource platform, and the entire platform's functionalities have met the expected goals.

Holographic voice-interactive system with Taylor Rayleigh-Sommerfeld based point cloud gridding

In recent years, intelligent voice interaction technology and holographic display technology have garnered significant attention. We propose a holographic voice-interactive system. The holographic voice interaction system can provide users with a virtual assistant proficient in accurately handling user voice queries, facilitating smoother interactions. Additionally, users can interact with virtual objects via holographic projection, enhancing realism and engagement. In this research, we introduce the U-blocks and U-net based reverse attention residual algorithm to generate more effective and accurate point cloud datasets during the acquisition phase. Furthermore, we integrate the ChatGLM pre-trained language model as the core module for voice interaction in the holographic display system, covering aspects such as text interaction and output control. Additionally, we propose a Taylor Rayleigh-Sommerfeld point cloud gridding method aimed at improving the computational speed of hologram generation. We validate the feasibility of our proposed methods through numerical simulations and optical experiments.

Identification of core genes involved in the response of Apocynum venetum to salt stress based on transcriptome sequencing and WGCNA.

Apocynum venetum L. belongs to the Apocynaceae family and is a plant that is highly resistant to stress. It is important in the fields of ecology, feeding, industry and medicine. The molecular mechanism underlying salt tolerance has not been elucidated. In this study, RNA-seq based transcriptome sequencing of A. venetum leaves after 0, 2, 6, 12, 24 and 48 h of treatment with 300 mM NaCl was performed. We conducted a comprehensive analysis of the transcriptome expression profiles of A. venetum under salt stress using the WGCNA method and identified red, black, and brown as the core modules regulating the salt tolerance of A. venetum. A co-expression regulatory network was constructed to identify the core genes in the module according to the correlations between genes. The genes TRINITY_DN102_c0_g1 (serine carboxypeptidase), TRINITY_DN3073_c0_g1 (SOS signaling pathway) and TRINITY_DN6732_c0_g1 (heat shock transcription factor) in the red module were determined to be the core genes. Two core genes in the black module, TRINITY_DN9926_c0_g1 and TRINITY_DN7962_c0_g1, are pioneer candidate salt tolerance-associated genes in A. venetum. The genes in the brown module were mainly enriched in two pathways, namely photosynthesis and osmotic balance. Among them, the TRINITY_DN6321_c0_g2 and TRINITY_DN244_c0_g1 genes encode aquaporin, which is helpful for maintaining the cell water balance and plays a protective role in defending A. venetum under abiotic stress. Our findings contribute to the identification of core genes involved in the response of A. venetum to salt stress.

BEEC psychosocial screening at Royal Manchester Children's Hospital

Bladder Exstrophy and Epispadias Complex (BEEC) is associated with psychosocial difficulties. Screening questionnaires, alongside consultation with a clinical psychologist, can help identify children/young people for further assessment and track trends over time to improve service delivery. To screen paediatric BEEC patients for a range of general psychosocial difficulties in a multi-disciplinary out-patient clinic setting and compare these results with our previous study and against published norms. The current service evaluation collected data at outpatient BEEC clinic appointments between 2016 and 2022 (2016-2022 sample). Children aged 4-5, 10-11 and 14-15 years and their parents/proxy were asked to complete two standardised psychosocial questionnaires: Paediatric Quality of Life Inventory (PedsQL 4.0 Generic Core and Family Impact Module) and the Strengths and Difficulties Questionnaires (SDQ). 79 children (CYP) and 93 parent/proxy (P/P) responses were recorded. The sample included paired CYP and P/P responses for the PedsQL (n=67) and SDQ (n=35). The mean age for CYP was 9.9 years (SD 3.99, range 2-17), 69.8% (n=120) of responses for male children. The percentage of total CYP scores falling within the 'At Risk' category on the PedsQL increased in the 2016-2022 sample compared to our 2015 sample, indicating the prevalence of greater difficulties. Differences between P/P and CYP responses on both the PedsQL and SDQ favoured CYP. Age, gender, and diagnosis appeared to influence certain questionnaire responses, depending on respondent (CYP or P/P). A significant difference between P/P and CYP in the emotional domain of the PedsQL for those aged 13-18 was observed (p=0.020), with P/P reporting greater difficulties, but this was not seen in the younger age ranges. Physical Health on the PedsQL were significantly lower for children with a cloacal exstrophy diagnosis, in comparison to bladder exstrophy and epispadias. P/P SDQ scores for boys were significantly higher in several domains. The results demonstrate the need for psychosocial screening, providing benchmarking for psychosocial difficulties within this patient group. Results indicate that patients accessing our clinic are reporting a higher level of challenge across psychosocial domains in recent years reflected by the percentage within the 'At Risk' category for psychosocial difficulty. Linked questionnaire data with condition specific information and surgical history would improve service evaluations. CYP reaching clinical thresholds are offered further psychological assessment within the service.

Design and Study of Composite Film Preparation Platform

This study aims to develop equipment for the preparation of composite films and successfully implement a film thickness prediction function. During the research process, we segmented the mechanical structure of the composite thin film preparation equipment into distinct modules, completed the structural design of the core module, and validated the stability of the process chamber, as well as the reasonableness of the strength and stiffness through simulation. Additionally, we devised a regression model for predicting the film thickness of composite films. The input features for the model included the sputtering air pressure, sputtering current, and sputtering time for magnetron sputtering process samples, as well as the evaporation volume and evaporation current for vacuum evaporation process samples. Simultaneously, the output features were the film thickness for both process samples. Subsequently, we established the designed composite film preparation equipment and conducted experimental verification. During the experiments, we successfully prepared Cr-Al composite films and utilized AFM for surface morphology analysis. The results confirmed the excellent performance of the Cr-Al composite films produced by the equipment, demonstrating the reliability of the equipment.