Unsupervised low-dose CT denoising using bidirectional contrastive network.

BACKGROUND AND OBJECTIVE: Low-dose computed tomography (LDCT) scans significantly reduce radiation exposure, but introduce higher levels of noise and artifacts that compromise image quality and diagnostic accuracy. Supervised learning methods have proven effective in denoising LDCT images, but are hampered by the need for large, paired datasets, which pose significant challenges in data acquisition. This study aims to develop a robust unsupervised LDCT denoising method that overcomes the reliance on paired LDCT and normal-dose CT (NDCT) samples, paving the way for more accessible and practical denoising techniques. METHODS: We propose a novel unsupervised network model, Bidirectional Contrastive Unsupervised Denoising (BCUD), for LDCT denoising. This model innovatively combines a bidirectional network structure with contrastive learning theory to map the precise mutual correspondence between the noisy LDCT image domain and the clean NDCT image domain. Specifically, we employ dual encoders and discriminators for domain-specific data generation, and use unique projection heads for each domain to adaptively learn customized embedded representations. We then align corresponding features across domains within the learned embedding spaces to achieve effective noise reduction. This approach fundamentally improves the model's ability to match features in latent space, thereby improving noise reduction while preserving fine image detail. RESULTS: Through extensive experimental validation on the AAPM-Mayo public dataset and real-world clinical datasets, the proposed BCUD method demonstrated superior performance. It achieved a peak signal-to-noise ratio (PSNR) of 31.387 dB, a structural similarity index measure (SSIM) of 0.886, an information fidelity criterion (IFC) of 2.305, and a visual information fidelity (VIF) of 0.373. Notably, subjective evaluation by radiologists resulted in a mean score of 4.23, highlighting its advantages over existing methods in terms of clinical applicability. CONCLUSIONS: This paper presents an innovative unsupervised LDCT denoising method using a bidirectional contrastive network, which greatly improves clinical applicability by eliminating the need for perfectly matched image pairs. The method sets a new benchmark in unsupervised LDCT image denoising, excelling in noise reduction and preservation of fine structural details.

An innovative prognostic auxiliary for colon adenocarcinoma based on zinc finger protein genes.

Background: The carcinogenesis and progression of colon adenocarcinoma (COAD) are intensively related to the abnormal expression of the zinc finger (ZNF) protein genes. We aimed to employ these genes to provide a reliable prognosis and treatment stratification tool for COAD patients. Methods: Cox and the least absolute shrinkage and selection operator (LASSO) regression analysis were applied, utilizing The Cancer Genome Atlas (TCGA) metadata, to build a ZNF protein gene-based prognostic model. Using this model, patients in the training cohort and testing cohort (GSE17537) were labelled as either high or low risk. Kaplan-Meier (KM) survival analysis and time-dependent receiver operating characteristic (ROC) curve analysis were performed in the patients with opposite risk status to assess the predictive ability in each cohort. The potentiality of the mechanism was explored by the estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE), single-sample gene set enrichment analysis (ssGSEA), gene set enrichment analysis (GSEA), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG). Finally, the degrees of expression of model genes were validated by immunohistochemistry (IHC). Results: The prognostic model consisting of INSM1, PHF21B, RNF138, SYTL4, WRNIP1, ZNF585B, and ZNF514, classified patients into opposite risk statuses. Patients in the high-risk subset had a considerably lower chance of surviving compared to those in the low-risk subset. There is a high probability that these model genes were attached to immune-related biological processes, which can be confirmed by the results of the above mechanistic methods. Moreover, patients in the low-risk subset also significantly outperformed the patients in the high-risk subset when calculating immune cells and function scores. Drug sensitivity and tumor immune dysfunction and exclusion (TIDE) analyses showed a clear difference in the immunological and chemotherapeutic efficacy predictions within the two risk groups. Additionally, the degrees of expression of model genes in high-risk and low-risk subsets presented great discrepancies. Conclusions: The signature may be applied as a predictive classifier to shepherd special medication for COAD patients.

Air trap and removal on a pressure driven PDMS-based microfluidic device.

With the development of microfluidic technology, microfluidic chips have played a positive role in applications such as cell culture, microfluidic PCR, and nanopore gene sequencing. However, the presence of bubbles interferes with fluid flow and has a significant impact on experimental results. There are many reasons for the generation of bubbles in microfluidic chips, such as pressure changes inside the chip, air vibration inside the chip, and the open chip guiding air into the chip when driving fluid. This study designed and prepared a microfluidic device based on polydimethylsiloxane. First, air was actively introduced into the microfluidic chip, and bubbles were captured through the microfluidic device to simulate the presence of bubbles inside the chip in biological experiments. To remove bubbles trapped in the microfluidic chip, distilled water, distilled water containing surfactants, and mineral oil were pumped into the microfluidic chip. We compared and discussed the bubble removal efficiency under different driving fluids, driving pressures, and open/closed channel configurations. This study helps to understand the mechanism of bubble formation and removal in microfluidic devices, optimize chip structure design and experimental reagent selection, prevent or eliminate bubbles, and reduce the impact of bubbles on experiments.

All-visible-light-driven stiff-stilbene photoswitches.

Molecular photoswitches are potent tools to construct dynamic functional systems and responsive materials that can be controlled in a non-invasive manner. As P-type photoswitches, stiff-stilbenes attract increasing interest, owing to their superiority in quantum yield, significant geometric differences between isomers, excellent thermostability and robust switching behavior. Nevertheless, the UV-light-triggered photoisomerization of stiff-stilbenes has been a main drawback for decades as UV light is potentially harmful and has low penetration depth. Here, we provided a series of para-formylated stiff-stilbenes by Rieche ortho-formylation to achieve all-visible-light-responsiveness. Additional phenolic groups provide access to late-stage chemical modification facilitating design of molecules responsive to visible light. Remarkably, the photoisomerization of aldehyde-appended stiff-stilbenes could be fully manipulated using visible light, accompanied by a high photostationary state (PSS) distribution. These features render them excellent candidates for future visible-light-controllable smart materials and dynamic systems.

Development and Validation of an Explainable Deep Learning Model to Predict In-Hospital Mortality for Patients With Acute Myocardial Infarction: Algorithm Development and Validation Study.

BACKGROUND: Acute myocardial infarction (AMI) is one of the most severe cardiovascular diseases and is associated with a high risk of in-hospital mortality. However, the current deep learning models for in-hospital mortality prediction lack interpretability. OBJECTIVE: This study aims to establish an explainable deep learning model to provide individualized in-hospital mortality prediction and risk factor assessment for patients with AMI. METHODS: In this retrospective multicenter study, we used data for consecutive patients hospitalized with AMI from the Chongqing University Central Hospital between July 2016 and December 2022 and the Electronic Intensive Care Unit Collaborative Research Database. These patients were randomly divided into training (7668/10,955, 70%) and internal test (3287/10,955, 30%) data sets. In addition, data of patients with AMI from the Medical Information Mart for Intensive Care database were used for external validation. Deep learning models were used to predict in-hospital mortality in patients with AMI, and they were compared with linear and tree-based models. The Shapley Additive Explanations method was used to explain the model with the highest area under the receiver operating characteristic curve in both the internal test and external validation data sets to quantify and visualize the features that drive predictions. RESULTS: A total of 10,955 patients with AMI who were admitted to Chongqing University Central Hospital or included in the Electronic Intensive Care Unit Collaborative Research Database were randomly divided into a training data set of 7668 (70%) patients and an internal test data set of 3287 (30%) patients. A total of 9355 patients from the Medical Information Mart for Intensive Care database were included for independent external validation. In-hospital mortality occurred in 8.74% (670/7668), 8.73% (287/3287), and 9.12% (853/9355) of the patients in the training, internal test, and external validation cohorts, respectively. The Self-Attention and Intersample Attention Transformer model performed best in both the internal test data set and the external validation data set among the 9 prediction models, with the highest area under the receiver operating characteristic curve of 0.86 (95% CI 0.84-0.88) and 0.85 (95% CI 0.84-0.87), respectively. Older age, high heart rate, and low body temperature were the 3 most important predictors of increased mortality, according to the explanations of the Self-Attention and Intersample Attention Transformer model. CONCLUSIONS: The explainable deep learning model that we developed could provide estimates of mortality and visual contribution of the features to the prediction for a patient with AMI. The explanations suggested that older age, unstable vital signs, and metabolic disorders may increase the risk of mortality in patients with AMI.

Prediction of Subsequent Vertebral Fracture After Acute Osteoporotic Fractures from Clinical and Paraspinal Muscle Features.

To construct a nomogram based on clinical factors and paraspinal muscle features to predict vertebral fractures occurring after acute osteoporotic vertebral compression fracture (OVCF). We retrospectively enrolled 307 patients with acute OVCF between January 2013 and August 2022, and performed magnetic resonance imaging of the L3/4 and L4/5 intervertebral discs (IVDs) to estimate the cross-sectional area (CSA) and degree of fatty infiltration (FI) of the paraspinal muscles. We also collected clinical and radiographic data. We used univariable and multivariable Cox proportional hazards models to identify factors that should be included in the predictive nomogram. Post-OVCF vertebral fracture occurred within 3, 12, and 24 months in 33, 69, and 98 out of the 307 patients (10.8%, 22.5%, and 31.9%, respectively). Multivariate analysis revealed that this event was associated with percutaneous vertebroplasty treatment, higher FI at the L3/4 IVD levels of the psoas muscle, and lower relative CSA of functional muscle at the L4/5 IVD levels of the multifidus muscle. Area under the curve values for subsequent vertebral fracture at 3, 12, and 24 months were 0.711, 0.724, and 0.737, respectively, indicating remarkable accuracy of the nomogram. We developed a model for predicting post-OVCF vertebral fracture from diagnostic information about prescribed treatment, FI at the L3/4 IVD levels of the psoas muscle, and relative CSA of functional muscle at the L4/5 IVD levels of the multifidus muscle. This model could facilitate personalized predictions and preventive strategies.

MRI-based radiomic models for the preoperative prediction of extramural venous invasion in rectal cancer: A systematic review and meta-analysis.

AIM: To estimate the diagnostic value of magnetic resonance imaging (MRI)-based radiomic models in detecting the extramural venous invasion (EMVI) of rectal cancer. MATERIALS AND METHODS: Appropriate studies in multiple electronic databases were systematically retrieved. The Quality Assessment of Diagnostic Accuracy Studies 2 and Radiomics Quality Score (RQS) were used to evaluate the eligible studies' methodology quality. Summary accuracy metrics were calculated, and the publication bias was detected using Deek's funnel plot. The sensitivity and meta-regression analysis were performed to investigate the causes of heterogeneity. RESULTS: For the seven eligible studies, which included 1175 patients, the pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, and diagnostic odds ratio were 0.80 (95 % CI, 0.70-0.88), 0.89 (95 % CI, 0.84-0.92), 7.0 (95 % CI, 4.7, 10.4), 0.22 (95 % CI, 0.14, 0.34), and 32 (95 % CI, 16, 65), respectively. The area under the receiver operating characteristic curve (AUC) was 0.91 (95 % CI, 0.88, 0.93). Moderate heterogeneity was found due to I2 values of 38.63 % and 32.29 % in sensitivity and specificity, respectively. Meta-regression analysis suggested that the patient enrollment, number of patients, segmentation method, and RQS score were the source of the heterogeneity. The head-to-head analysis suggested that radiomics model had a higher sensitivity for detection of EMVI than subjective evaluation by radiologist (0.47 vs. 0.73, p ≤ 0.001). CONCLUSION: Our study suggests that MRI-based radiomic models have good diagnostic value in detecting EMVI for rectal cancer patients. Nevertheless, more prospective and high-quality studies with larger sample sizes are needed in the future to validate these results.

Effects of plyometric training on health-related physical fitness in untrained participants: a systematic review and meta-analysis.

Plyometric training (PT) is an effective training method for improving physical fitness among trained individuals; however, its impact on health-related physical fitness in untrained participants remains ambiguous. Therefore, this meta-analysis aimed to evaluate the effects of PT on health-related physical fitness among untrained participants. Six electronic databases (PubMed, CINAHL Plus, MEDLINE Complete, Web of Science Core Collection, SCOPUS, and SPORTDiscus) were systematically searched until March 2024. We included controlled trials that examined the effects of PT on health-related physical fitness indices in untrained participants. Twenty-one studies were eligible, including a total of 1263 participants. Our analyses revealed small to moderate effects of PT on body mass index, muscular strength, cardiorespiratory fitness, and flexibility (ES = 0.27-0.61; all p > 0.05). However, no significant effects were detected for body fat percentage and lean mass (ES = 0.21-0.41; all p > 0.05). In conclusion, the findings suggest that PT may be potentially effective in improving health-related physical fitness indices (i.e., body mass index, muscular strength, cardiorespiratory fitness, and flexibility) in untrained participants. However, the results should be interpreted cautiously due to data limitations in some fitness variables.

Polybrominated diphenyl ethers (PBDEs) decreased the protein quality of rice grains by disturbing amino acid metabolism.

Polybrominated diphenyl ethers (PBDEs) in soils posed potential risks to crop growth and food safety due to their prevalence and persistence. PBDEs were capable of being absorbed and accumulated into crops, impacting their growth, whereas the interference on metabolic components and nutritional composition deserves further elucidation. This study integrated a combined non-targeted and targeted metabolomics method to explore the influences of 2,2',4,4'-tetrabromodiphenyl ether (BDE-47), 2,2',4,4',5-pentabromodiphenyl ether (BDE-99) and decabromodiphenyl ether (BDE-209) on the metabolic responses of rice (Oryza sativa). Metabolic pathways, which were associated with sugars, organic acids, and amino acids, were significantly disturbed under PBDE stresses. Particularly, 75% of the marked altered pathways belonged to amino acid metabolism, with alanine/aspartate/glutamate metabolism being commonly enhanced. The degradation of aspartic acid promoted the formation of downstream amino acids, among which the levels of lysine, methionine, isoleucine, and asparagine were increased by 1.31-3.15 folds compared to the control. Thus, the antioxidant capacity in rice plants was enhanced, particularly through the significant promotion of ascorbic acid-glutathione (AsA-GSH) cycle in rice leaves. The amino acids were promoted to resist reactive oxygen species (ROS) efficiently, thus were deficient for nutrient storage. When exposed to 4 µmol/kg PBDEs, the contents of amino acids and proteins in grains decreased by 9.1-32.1% and 8.6-34.8%, respectively. In particular, glutelin level was decreased by 5.6-41.2%, resulting in a decline in nutritional quality. This study demonstrated that PBDEs deteriorated the protein nutrition in rice grains by affecting amino acid metabolism, providing a new perspective for evaluating the ecological risks of PBDEs and securing agricultural products.

A longitudinal study of the brain structure network changes in HIV patients with ANI: combined VBM with SCN.

Background: Despite the widespread adoption of combination antiretroviral therapy (cART) in managing HIV, the virus's impact on the brain structure of patients remains significant. This study aims to longitudinally explore the persistent effects of HIV on brain structure, focusing on changes in gray matter volume (GMV) and structural covariance network (SCN) among patients at the Asymptomatic Neurocognitive Impairment (ANI) stage. Methods: This research involved 45 HIV patients diagnosed with ANI and 45 demographically matched healthy controls (HCs). The participants were observed over a 1.5-year period. Differences in GMV between groups were analyzed using voxel-based morphometry (VBM), while the graph theory model facilitated the establishment of topological metrics for assessing network indices. These differences were evaluated using two-sample t-tests and paired-sample t-tests, applying the network-based statistics method. Additionally, the study examined correlations between GMV and cognitive performance, as well as clinical variables. Results: Compared with HCs, HIV patients demonstrated reduced GMV in the right middle temporal gyrus and left middle frontal gyrus (FWE, p < 0.05), along with decreased betweenness centrality (BC) in the left anterior cingulate and paracingulate cortex. Conversely, an increase in the clustering coefficient (Cp) was observed (FDR, p < 0.05). During the follow-up period, a decline in GMV in the right fusiform gyrus (FWE, p < 0.05) and a reduction in node efficiency (Ne) in the triangular part of the inferior frontal gyrus were noted compared with baseline measurements (FDR, p < 0.05). The SCN of HIV patients exhibited small-world properties across most sparsity levels (Sigma >1), and area under the curve (AUC) analysis revealed no significant statistical differences between groups. Conclusion: The findings suggest that despite the administration of combination antiretroviral therapy (cART), HIV continues to exert slow and sustained damage on brain structures. However, when compared to HCs, the small-world properties of the patients' SCNs did not significantly differ, and the clustering coefficient, indicative of the overall information-processing capacity of the brain network, was slightly elevated in HIV patients. This elevation may relate to compensatory effects of brain area functions, the impact of cART, functional reorganization, or inflammatory responses.

Reconstitution of the Early Stage of Chetomin Biosynthesis in Aspergillus fumigatus Leads to the Production of Epipolythiodioxopiperazines.

Using CRISPR-Cas9 technology and a microhomology-mediated end-joining repair system, we substituted genes of the gliotoxin pathway in Aspergillus fumigatus with genes responsible for chetomin biosynthesis from Chaetomium cochliodes, leading to the production of three new epipolythiodioxopiperazines (ETPs). This work represents the first successful endeavor to produce ETPs in a non-native host. Additionally, the simultaneous disruption of five genes in a single transformation marks the most extensive gene knockout event in filamentous fungi to date.

Comparison of orbital fibroblasts from Graves' ophthalmopathy and healthy control.

Graves' ophthalmopathy (GO) is an extrathyroidal manifestation of Graves' disease, Orbital fibroblasts (OFs) are recognized as key players in GO pathogenesis, involved in orbital inflammation, tissue remodeling, and fibrosis. This study offers a primary exploration of cell behavior and characteristics on OFs from GO (GO-OFs), and compared to OFs from healthy control (HC-OFs). Results reveal that GO-OFs exhibit delayed migration from tissue fragments, while no significant difference in cell proliferation is observed between GO-OFs and HC-OFs. Aberrant expression pattern of surface proteins Thy-1, TSHR, and IGF-1R suggests shared autoantigens and pathways between GO and GD, contributing to inflammation and fibrosis. Investigations into cytokine responses unveil elevated secretion of hyaluronic acid (HA) and prostaglandin E2 (PGE2) in GO-OFs, emphasizing their role in tissue remodeling. These findings deepen our understanding of OFs in GO pathogenesis, offering potential therapeutic avenues.

Protein crotonylation: Basic research and clinical diseases.

Crotonylation is an importantly conserved post-translational modification, which is completely different from acetylation. In recent years, it has been confirmed that crotonylation occurs on histone and non-histone. Crotonylated Histone primarily affects gene expression through transcriptional regulation, while non-histone Crotonylation mainly regulates protein functions including protein activity, localization, and stability, as well as protein-protein interactions. The change in protein expression and function will affect the physiological process of cells and even cause disease. Reviewing previous studies, this article summarizes the mechanisms of histone and non-histone crotonylation in regulating diseases and cellular physiological processes to explore the possibility of precise regulation of crotonylation sites as potential targets for disease treatment.

Efficacy of fire needle combined with 308 nm excimer laser therapy for vitiligo: A systematic review and meta-analysis of randomized controlled trials.

INTRODUCTION: Vitiligo is a common depigmenting skin disorder. This work is performed to systematically evaluate the efficacy and safety of fire needles combined with 308 nm excimer laser therapy in treating vitiligo. METHODS: We searched the PubMed, EMBASE, Cochrane Library, Web of Science, CNKI, Wanfang, and VIP databases. Randomized controlled trials (RCTs) on fire needles combined with 308 nm excimer laser therapy with 308 nm excimer laser therapy alone for vitiligo were included. The Cochrane Collaborative Network Tool was used to assess the risk of bias. Statistical analysis was completed using RevMan5.3 software and Stata 15.0 software. The GRADE system was used to evaluate the quality of evidence for outcomes. RESULTS: In this study, 10 RCTs and 1333 patients were included. The results showed that compared with 308 nm excimer laser therapy alone, fire needle combined with 308 nm excimer laser therapy is more effective in improving clinical effective rate (RR = 1.36, 95% CI [1.24, 1.50], p < 0.00001), serum CD4+ level (MD = 3.12, 95% CI [2.50, 3.74], p < 0.00001), CD4+/CD8+ ratio (MD = 0.24, 95% CI [0.09, 0.39], p = 0.001), and quality of life measured by the Dermatology Life Quality Index (DLQI) (MD = 3.76, 95% CI [3.33, 4.19], p < 0.00001), and reducing the Vitiligo Area Score Index (VASI) (MD = -5.47, 95% CI [-6.56, -4.37], p < 0.00001). The reported adverse events, including redness, swelling, pain, blisters, and itching, were controllable, and all these events were well tolerated. CONCLUSION: The current evidence indicates that fire needle combined with 308 nm excimer laser therapy is effective and safe for vitiligo. However, owing to the suboptimal quality of the included studies, more high-quality and large-scale RCTs are needed for comprehensive analysis and further validation.

A Systematic Review and Meta-Analysis of the Predictive Power of China-PAR Against Cardiovascular Disease.

Background and Purpose: To evaluate the predictive power of the China-PAR model for cardiovascular disease (CVD).Methods: Dominate databases, including PubMed, Web of Science, CNKI, Wanfang Data Knowledge Service Platform, Chinese Biomedical Literature Service System, and VIP self-built database, were searched from January 1, 2016 to February 22, 2022. The primary outcome included observed events and predicted events by China-PAR. Meta-analysis was performed using RevMan 5.3 software. Stroke, arteriosclerotic cardiovascular disease (ASCVD), male, and female were divided into subgroup analyses. Funnel plots were used to assess publication bias.Results: A total of nine studies, which included 221,918 participants, were analyzed. Meta-analysis showed the combined observed incidence of CVD was 3.97%, and the combined predicted incidence was 9.59% by China-PAR. There was no significant difference between the observed and the predicted events. Subgroup analysis showed there was no statistical significance between the observed and the predicted events for stroke or for ASCVD. The difference between the observed and the predicted events by China-PAR was not statistically significant in either males or females.Conclusions: China-PAR model has important public health significance to further improve the primary prevention strategy of CVD.

Phosphoproteomic analysis reveals changes in A-Raf-related protein phosphorylation in response to Toxoplasma gondii infection in porcine macrophages.

BACKGROUND: Toxoplasma gondii is an obligate intracellular protozoan parasite that causes severe threats to humans and livestock. Macrophages are the cell type preferentially infected by T. gondii in vivo. Protein phosphorylation is an important posttranslational modification involved in diverse cellular functions. A rapidly accelerated fibrosarcoma kinase (A-Raf) is a member of the Raf family of serine/threonine protein kinases that is necessary for MAPK activation. Our previous research found that knockout of A-Raf could reduce T. gondii-induced apoptosis in porcine alveolar macrophages (3D4/21 cells). However, limited information is available on protein phosphorylation variations and the role of A-Raf in macrophages infected with T. gondii. METHODS: We used immobilized metal affinity chromatography (IMAC) in combination with liquid chromatography tandem mass spectrometry (LC-MS/MS) to profile changes in phosphorylation in T. gondii-infected 3D4/21 and 3D4/21-ΔAraf cells. RESULTS: A total of 1647 differentially expressed phosphorylated proteins (DEPPs) with 3876 differentially phosphorylated sites (DPSs) were identified in T. gondii-infected 3D4/21 cells (p3T group) when compared with uninfected 3D4/21 cells (pho3 group), and 959 DEPPs with 1540 DPSs were identified in the p3T group compared with infected 3D4/21-ΔAraf cells (p3KT group). Venn analysis revealed 552 DPSs corresponding to 406 DEPPs with the same phosphorylated sites when comparing p3T/pho3 versus p3T/p3KT, which were identified as DPSs and DEPPs that were directly or indirectly related to A-Raf. CONCLUSIONS: Our results revealed distinct responses of macrophages to T. gondii infection and the potential roles of A-Raf in fighting infection via phosphorylation of crucial proteins.

Simultaneous Defect Passivation and Electric Level Regulation with Rubidium Fluoride for High-Efficiency CsPbI2Br Perovskite Solar Cells.

Due to the good balance of efficiency and stability, CsPbI2Br perovskite solar cells (PSCs) recently have attracted widespread attention. However, the improvement in photovoltaic performance for CsPbI2Br PSCs was mainly limited by massive defects and unmatched energy levels. Surface modification is the most convenient and effective strategy to decrease defect densities of perovskite films. Herein, we deposited rubidium fluoride (RbF) onto the surface of CsPbI2Br perovskite films by spin-coating. The numerous defects could be significantly passivated by RbF, resulting in suppressed nonradiative recombination. Furthermore, the CsPbI2Br perovskite film after RbF treatment exhibits a deeper Fermi level, and an additional built-in electric field forms to promote charge transport. Consequently, the champion device achieves a high efficiency of 10.82% with an improved VOC of 1.14 V, and it also exhibits excellent stability after long-term storage. This work offers a simple and effective approach to enhance the photovoltaic performance and stability of PSCs for broader applications in the future.

Cotton sphingosine kinase GhLCBK1 participates in fiber cell elongation by affecting sphingosine-1-phophate and auxin synthesis.

Sphingolipids serve as essential components of biomembrane and possess significant bioactive properties. Sphingosine-1-phophate (S1P) plays a key role in plant resistance to stress, but its specific impact on plant growth and development remains to be fully elucidated. Cotton fiber cells are an ideal material for investigating the growth and maturation of plant cells. In this study, we examined the content and composition of sphingosine (Sph) and S1P throughout the progression of fiber cell development. The content of S1P elevated gradually during fiber elongation but declined during the transition stage. Exogenous application of S1P promoted fiber elongation while using of FTY720 (an antagonist of S1P), and DMS (an inhibitor of LCBK) hindered fiber elongation. Cotton Long Chain Base Kinase 1 (GhLCBK1) was notably expressed during the fiber elongation stage, containing all conserved domains of LCBK protein and localized in the endoplasmic reticulum. Overexpression GhLCBK1 increased the S1P content and promoted fiber elongation while retarded secondary cell wall (SCW) deposition. Conversely, downregulation of GhLCBK1 reduced the S1P levels, and suppressed fiber elongation, and accelerated SCW deposition. Transcriptome analysis revealed that upregulating GhLCBK1 or applying S1P induced the expression of GhEXPANSIN and auxin related genes. Furthermore, the levels of IAA were elevated and reduced in the fibers when up-regulating or down-regulating GhLCBK1, respectively. Our investigation demonstrated that GhLCBK1 and its product S1P facilitated the elongation of fiber cells by affecting auxin biosynthesis. This study contributes novel insights into the intricate regulatory pathways involved in fiber cell elongation, identifying GhLCBK1 as a potential target gene and laying the groundwork for enhancing fiber quality via genetic manipulation.

Detection of common pathogenesis of rheumatoid arthritis and atherosclerosis via microarray data analysis.

Despite extensive research reveal rheumatoid arthritis (RA) is related to atherosclerosis (AS), common pathogenesis between these two diseases still needs to be explored. In current study, we explored the common pathogenesis between rheumatoid arthritis (RA) and atherosclerosis (AS) by identifying 297 Differentially Expressed Genes (DEGs) associated with both diseases. Through KEGG and GO functional analysis, we highlighted the correlation of these DEGs with crucial biological processes such as the vesicle transport, immune system process, signaling receptor binding, chemokine signaling and many others. Employing Protein-Protein Interaction (PPI) network analysis, we elucidated the associations between DEGs, revealing three gene modules enriched in immune system process, vesicle, signaling receptor binding, Pertussis, and among others. Additionally, through CytoHubba analysis, we pinpointed 11 hub genes integral to intergrin-mediated signaling pathway, plasma membrane, phosphotyrosine binding, chemokine signaling pathway and so on. Further investigation via the TRRUST database identified two key Transcription Factors (TFs), SPI1 and RELA, closely linked with these hub genes, shedding light on their regulatory roles. Finally, leveraging the collective insights from hub genes and TFs, we proposed 10 potential drug candidates targeting the molecular mechanisms underlying RA and AS pathogenesis. Further investigation on xCell revealed that 14 types of cells were all different in both AS and RA. This study underscores the shared pathogenic mechanisms, pivotal genes, and potential therapeutic interventions bridging RA and AS, offering valuable insights for future research and clinical management strategies.