IQAGPT: computed tomography image quality assessment with vision-language and ChatGPT models.

Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various tasks and attracted increasing interest as a natural language interface across many domains. Recently, large vision-language models (VLMs) that learn rich vision-language correlation from image-text pairs, like BLIP-2 and GPT-4, have been intensively investigated. However, despite these developments, the application of LLMs and VLMs in image quality assessment (IQA), particularly in medical imaging, remains unexplored. This is valuable for objective performance evaluation and potential supplement or even replacement of radiologists' opinions. To this end, this study introduces IQAGPT, an innovative computed tomography (CT) IQA system that integrates image-quality captioning VLM with ChatGPT to generate quality scores and textual reports. First, a CT-IQA dataset comprising 1,000 CT slices with diverse quality levels is professionally annotated and compiled for training and evaluation. To better leverage the capabilities of LLMs, the annotated quality scores are converted into semantically rich text descriptions using a prompt template. Second, the image-quality captioning VLM is fine-tuned on the CT-IQA dataset to generate quality descriptions. The captioning model fuses image and text features through cross-modal attention. Third, based on the quality descriptions, users verbally request ChatGPT to rate image-quality scores or produce radiological quality reports. Results demonstrate the feasibility of assessing image quality using LLMs. The proposed IQAGPT outperformed GPT-4 and CLIP-IQA, as well as multitask classification and regression models that solely rely on images.

A lightweight intelligent laryngeal cancer detection system for rural areas.

OBJECTIVE: Early diagnosis of laryngeal cancer (LC) is crucial, particularly in rural areas. Despite existing studies on deep learning models for LC identification, challenges remain in selecting suitable models for rural areas with shortages of laryngologists and limited computer resources. We present the intelligent laryngeal cancer detection system (ILCDS), a deep learning-based solution tailored for effective LC screening in resource-constrained rural areas. METHODS: We compiled a dataset comprised of 2023 laryngoscopic images and applied data augmentation techniques for dataset expansion. Subsequently, we utilized eight deep learning models-AlexNet, VGG, ResNet, DenseNet, MobileNet, ShuffleNet, Vision Transformer, and Swin Transformer-for LC identification. A comprehensive evaluation of their performances and efficiencies was conducted, and the most suitable model was selected to assemble the ILCDS. RESULTS: Regarding performance, all models attained an average accuracy exceeding 90 % on the test set. Particularly noteworthy are VGG, DenseNet, and MobileNet, which exceeded an accuracy of 95 %, with scores of 95.32 %, 95.75 %, and 95.99 %, respectively. Regarding efficiency, MobileNet excels owing to its compact size and fast inference speed, making it an ideal model for integration into ILCDS. CONCLUSION: The ILCDS demonstrated promising accuracy in LC detection while maintaining modest computational resource requirements, indicating its potential to enhance LC screening accuracy and alleviate the workload on otolaryngologists in rural areas.

Environmental factors drive latitudinal patterns of fine-root architectures of 96 xerophytic species in the dry valleys of Southwest China.

Fine-root architecture is critical feature reflecting root explorative and exploitative strategies for soil resources and soil space occupancy. Yet, studies on the variation of fine-root architecture across different species are scare and little work has been done to integrate the potential drivers on these variations along a biogeographical gradient in arid ecosystems. We measured root branching intensity, topological index, and root branching ratios as well as morphological traits (root diameter and length) in dry valley along a 1000 km latitudinal gradient. Influence of phylogeny, environmental factors on fine-root architecture and trade-offs among root traits were evaluated. With increasing latitude, the topological index and second to third root order branching ratio decreased, whereas first-to-second branching ratio increased. Root branching intensity was associated with short and thin fine roots, but has no significant latitudinal pattern. As a whole, soil microbial biomass was the most important driver in the variation of root branching intensity, and soil texture was the strongest predictor of topological index. Additionally, mean annual temperature was an important factor influencing first-to-second branching ratio. Our results suggest variations in fine-root architectures were more dependent on environmental variables than phylogeny, signifying that fine-root architecture is sensitive to environmental variations.

Phytochemical components analysis and hypolipidemic effect on hyperlipidemia mice of the aerial parts from Allium sativum.

Background: The bulbs of Allium sativum are widely used as food or seasoning (garlic), while they have also been utilized as a famous traditional medicine since ancient eras for the treatment of scabies, tuberculosis, pertussis, diarrhea and dysentery, etc. However, very few studies focus on their abundant aerial parts, which are normally discarded during the harvest season. Methods: The hyperlipidemic mice model has been used to study the lipid-lowering effect of the aerial parts in this article. 180 mice were randomly divided into 18 groups, including blank control (BC), model (Mod), positive control (PC), and low-, medium-, and high-dose groups of the crude extract, petroleum ether, ethyl acetate, n-butanol, and residual water extracts (corresponding to CE, PEE, EAE, NBE, WE), with 10 mice in each group. The preventive effects of the extracts on hyperlipidemic mice lasted for four weeks. Ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-Q/TOF-MS) and gas chromatography tandem mass spectrometry (GC-MS/MS) were used to analyze the chemical components of NBE and PEE respectively. Results: The results of the mice experiment showed that n-butanol extract (NBE) and petroleum ether extract (PEE) from the aerial parts could significantly reduce the contents of total cholesterol (TC), triglycerides (TG), low density lipoprotein cholesterol (LDL-C), alanine transaminase (ALT) and aspartate transaminase (AST) in serum of hyperlipidemic mice, and increase the contents of high density lipoprotein cholesterol (HDL-C). They could enhance the activity of superoxide dismutase (SOD) in liver and reduce the level of malondialdehyde (MDA). At the same time, they could improve steatosis and inflammation of liver cells. The results of phytochemical components analysis showed that NBE was rich in organic acids, flavonoids and nitrogen-containing constituents, while PEE contained organic sulfur compounds, aliphatic acids and derivatives, alkaloids, phytosterols, etc. Conclusion: These results support that the aerial parts of A. sativum are an interesting source of bioactive ingredients that may be useful in the prevention and treatment of hyperlipidemia.

Whole-genome sequencing and pathogenicity analysis of Rhodococcus equi isolated in horses.

BACKGROUND: Rhodococcus equi (R. equi) is a Gram-positive zoonotic pathogen that frequently leads to illness and death in young horses (foals). This study presents the complete genome sequence of R. equi strain BJ13, which was isolated from a thoroughbred racehorse breeding farm in Beijing, China. RESULTS: The BJ13 genome has a length of 5.30 Mb and consists of a complete chromosome and a plasmid measuring 5.22 Mb and 0.08 Mb, respectively. We predicted 4,929 coding gene open reading frames, along with 52 tRNAs and 12 rRNAs. Through analysis of mobile genetic elements, we identified 6 gene islands and 1 prophage gene. Pathogenic system analysis predicted the presence of 418 virulence factors and 225 drug resistance genes. Secretion system analysis revealed the prediction of 297 secreted proteins and 1,106 transmembrane proteins. BJ13 exhibits genomic features, virulence-associated genes, potential drug resistance, and a virulence plasmid structure that may contribute to the evolution of its pathogenicity. Lastly, the pathogenicity of the isolated strain was assessed through animal experiments, which resulted in inflammatory reactions or damage in the lungs, liver, and spleen of mice. Moreover, by the 7th day post-infection, the mortality rate of the mice reached 50.0%, indicating complex immune regulatory mechanisms, including overexpression of IL-10 and increased production of pro-inflammatory cytokines like TNF-α. These findings validate the strong pathogenicity of the isolated strain and provide insights for studying the pathogenic mechanisms of Rhodococcus equi infection. CONCLUSIONS: The complete genome sequence of R. equi strain BJ13 provides valuable insights into its genomic characteristics, virulence potential, drug resistance, and secretion systems. The strong pathogenicity observed in animal experiments underscores the need for further investigation into the pathogenic mechanisms of R. equi infection.

A transcriptional cascade involving BBX22 and HY5 finely regulates both plant height and fruit pigmentation in citrus.

Dwarfing is a pivotal agronomic trait affecting both yield and quality. Citrus species exhibit substantial variation in plant height, among which internode length is a core element. However, the molecular mechanism governing internode elongation remains unclear. Here, we unveiled that the transcriptional cascade consisting of B-BOX DOMAIN PROTEIN 22 (BBX22) and ELONGATED HYPOCOTYL 5 (HY5) finely tunes plant height and internode elongation in citrus. Loss-of-function mutations of BBX22 in an early-flowering citrus (Citrus hindsii "SJG") promoted internode elongation and reduced pigment accumulation, whereas ectopic expression of BBX22 in SJG, sweet orange (C. sinensis), pomelo (C. maxima) or heterologous expression of BBX22 in tomato (Solanum lycopersicum) significantly decreased internode length. Furthermore, exogenous application of gibberellin A3 (GA3) rescued the shortened internode and dwarf phenotype caused by BBX22 overexpression. Additional experiments revealed that BBX22 played a dual role in regulation internode elongation and pigmentation in citrus. On the one hand, it directly bound to and activated the expression of HY5, GA metabolism gene (GA2 OXIDASE 8, GA2ox8), carotenoid biosynthesis gene (PHYTOENE SYNTHASE 1, PSY1) and anthocyanin regulatory gene (Ruby1, a MYB DOMAIN PROTEIN). On the other hand, it acted as a cofactor of HY5, enhancing the ability of HY5 to regulate target genes expression. Together, our results reveal the critical role of the transcriptional cascade consisting of BBX22 and HY5 in controlling internode elongation and pigment accumulation in citrus. Unraveling the crosstalk regulatory mechanism between internode elongation and fruit pigmentation provides key genes for breeding of novel types with both dwarf and health-beneficial fortification in citrus.

Injectable Gelled Multiple Emulsion for Glucose-Responsive Insulin Delivery.

A glucose-responsive insulin delivery system that sustains blood glucose equilibrium for an extended duration can address the low therapeutic window of insulin in diabetes treatment. Herein, insulin is loaded in a water-in-oil-in-water (W1/O/W2) gelled multiple emulsion using poly (4-vinylphenylboronic acid) (PVPBA) homopolymer as an effective emulsifier. The gelled multiple emulsion exhibits a high encapsulation efficiency (99%), enhanced stability and remarkable shear-thinning behavior, making it easy to inject. Under hyperglycemic conditions, the gelled emulsion system instantly binds to glucose molecules and reduces the hydrogen bonds of the PVPBA homopolymer, resulting in insulin release. In a streptozotocin-induced type 1 diabetic mouse model, a single subcutaneous injection of the gelled emulsion rapidly responds to high blood glucose concentration (BGC) and release insulin in a glucose dependent manner, thus prolonging the antihyperglycemic effect compared with free insulin.

Utilizing bifurcated allogeneic vein grafts: a novel approach for preventing sinistral portal hypertension following Pancreaticoduodenectomy. a 10-year before and after study.

BACKGROUND: Sinistral portal hypertension (SPH) may occurs in patients with pancreatic carcinoma after pancreaticoduodenectomy (PD) with spleno-mesenterico-portal (S-M-P) cofluence resection. This study aimed to evaluate outcomes with the bifurcated allogeneic vein replacement in the prevention of SPH in pancreatic carcinoma patients. MATERIALS AND METHODS: A total of 81 patients were included. We retrospectively collected clinicopathological data from 66 patients underwent PD with S-M-P confluence resection in our hospital from Jan. 2011 to Dec. 2021, compared the correlation between different venous reconstruction methods using log-rank tests and clinical outcomes through univariate and multivariate analyses. Secondly, we prospectively collected clinical data and outcomes of 15 patients who underwent splenic vein reconstruction from Jan. 2021 to Jan. 2023. RESULTS: In the retrospective study, 43 cases received reconstruction by bifurcated allogeneic vein (Reconstruction group) and 23 cases received simply SV ligation (Ligation group). The preoperative platelet counts and spleen volume were similar between two groups (P>0.05). Nevertheless, at 1 month, 3 months and 6 months after operation, the related indexes of SPH such as platelet count, spleen volume, spleen volume ratio and esophagogastric varices (EGV) grade in Reconstruction group were better than those in Ligation group (P<0.05). 6 months after surgery, the incidence of SPH in Ligation group was significantly higher than in Reconstruction group (36.4% vs. 8.1%, respectively). In the prospective study, the incidence of SPH in patients undergoing SV reconstruction was 6.7% (1/15). CONCLUSION: Without compromising surgical outcomes, reconstruction of the S-M-P confluence by bifurcated allogeneic vein is a better method to avoid SPH in patients with advanced pancreatic carcinoma.

Wearable solid-phase microextraction sampling for enhanced detection of volatile analytes in human ears.

BACKGROUND: Investigating ear at molecule level is challenging task, since there is a lack of molecular detection by traditional diagnosis techniques such as otologic endoscopy, ear swab culture, and imaging diagnostic technique. Therefore, new development of noninvasive, highly sensitive, and convenient analytical method for investigating human ears is highly needed. RESULTS: We developed a wearable sampling device for extracting trace analytes in ear by fixing solid-phase microextraction fibers into modified earmuffs (SPME-in-earmuffs). After sampling, SPME fiber was coupled with gas chromatography-mass spectrometry (GC-MS) for identification and quantification of extracted analytes. Enhanced detection of various analytes such as volatile metabolites, exposures, and therapeutic drugs of ears were demonstrated in this work. Particularly, sport-induced metabolic changes such as fatty acids, aldehyde compounds and oxidative produces were found from human ears using this method. Acceptable analytical performances were obtained by using this newly developed method for detecting ear medicines, e.g., low limit of detection (LOD, 0.005-0.021 ng/mL) and limit of quantification (LOQ, 0.018-0.071 ng/mL), excellent linear dynamic responses (R2 > 0.99, ranging from 0.050-8.00 ng/mL), good relative standard deviations (RSDs, 13.19 % âˆ¼ 21.40 %, n = 6) and accuracy (84.43-150.18 %, n = 6) at different concentrations. SIGNIFICANCE: For the first time, this work provides a simple, convenient, and wearable microextraction method for enhanced detection of trace volatiles in human ears. The enclosed space between ear and earmuff allows headspace SPME sampling of volatile analytes, and thus provides a new wearable method for monitoring ear metabolites and human exposures, showing potential applications in human health, disease diagnosis, and sport science.

HiTE: a fast and accurate dynamic boundary adjustment approach for full-length transposable element detection and annotation.

Recent advancements in genome assembly have greatly improved the prospects for comprehensive annotation of Transposable Elements (TEs). However, existing methods for TE annotation using genome assemblies suffer from limited accuracy and robustness, requiring extensive manual editing. In addition, the currently available gold-standard TE databases are not comprehensive, even for extensively studied species, highlighting the critical need for an automated TE detection method to supplement existing repositories. In this study, we introduce HiTE, a fast and accurate dynamic boundary adjustment approach designed to detect full-length TEs. The experimental results demonstrate that HiTE outperforms RepeatModeler2, the state-of-the-art tool, across various species. Furthermore, HiTE has identified numerous novel transposons with well-defined structures containing protein-coding domains, some of which are directly inserted within crucial genes, leading to direct alterations in gene expression. A Nextflow version of HiTE is also available, with enhanced parallelism, reproducibility, and portability.

Causal Brain Network in Clinically-Annotated Epileptogenic Zone Predicts Surgical Outcomes of Drug-Resistant Epilepsy.

OBJECTIVE: Patients with drug-resistant epilepsy (DRE) are commonly treated using neurosurgery, while its success rate is limited with approximately 50%. Predicting surgical outcomes is currently a prominent topic. The DRE is recognized as a network disorder involving a seizure triggering mechanism within epileptogenic zone (EZ); however, a systematic exploration of the EZ causal network remains lacking. METHODS: This paper will advance DRE study by: (1) developing a novel causal coupling algorithm, "full convergent cross mapping (FCCM)" to improve the quantization performance; (2) characterizing the DRE's multi-frequency epileptogenic network by FCCM calculation of ictal iEEG; (3) predicting surgical outcomes using network features and machine learning. Numerical validations demonstrate the FCCM's superior quantization in terms of nonlinearity, accuracy, and stability. A multicenter cohort containing 22 DRE patients with 81 seizures is included. RESULT: Based on the Mann-Whitney-U-test, coupling strength of the epileptogenic network in successful surgeries is significantly higher than that of the failed group, with the most significant difference observed in α -iEEG network (p = 1.52e - 07 ) Other clinical covariates are also considered and all th α -iEEG networks demonstrate consistent differences comparing successful and failed groups, with p = 0.014 and 9.23e - 06 for lesional and non-lesional DRE, p = 2.32e - 05, 0.0074 and 0.0030 for three clinical centers CHFU, JHU and NIH. Using FCCM features and 10-fold cross validation, the SVM achieves the highest accuracy of 87.65% in predicting surgical outcomes. CONCLUSION: The epileptogenic causal network is a reliable biomarker for estimating DRE's surgical outcomes. SIGNIFICANCE: The proposed approach is promising to facilitate DRE precision medicine.

Prognostic Assessment in Patients With Primary Diffuse Large B-Cell Lymphoma of the Central Nervous System Using MRI-Based Radiomics.

BACKGROUND: Primary central nervous system lymphoma (PCNSL) carries a poor prognosis. Radiomics may hold potential value in prognostic assessment. PURPOSE: To develop and validate an MRI-based radiomics model and combine it with clinical factors to assess progression-free survival (PFS) and overall survival (OS) of patients with PCNSL. STUDY TYPE: Retrospective and prospective. POPULATION: Three hundred seventy-nine patients (179 female, 53 ± 7 years) from 2014 to 2022. FIELD STRENGTH/SEQUENCE: T2/fluid-attenuated inversion recovery, contrast-enhanced T1WI and diffusion-weighted echo-planar imaging sequences on 3.0 T. ASSESSMENT: Radiomics features were extracted from enhanced tumor regions on preoperative multi-sequence MRI. Using a least absolute shrinkage and selection operator (LASSO) Cox regression model to select radiomic signatures in training cohort (N = 169). Cox proportional hazards models were constructed for clinical, radiomics, and combined models, with internal (N = 72) and external (N = 32) cohorts validating model performance. STATISTICAL TESTS: Chi-squared, Mann-Whitney, Kaplan-Meier, log-rank, LASSO, Cox, decision curve analysis, time-dependent Receiver Operating Characteristic, area under the curve (AUC), and likelihood ratio test. P-value <0.05 was considered significant. RESULTS: Follow-up duration was 28.79 ± 22.59 months (median: 25). High-risk patients, determined by the median radiomics score, showed significantly lower survival rates than low-risk patients. Compared with NCCN-IPI, conventional imaging and clinical models, the combined model achieved the highest C-index for both PFS (0.660 internal, 0.802 external) and OS (0.733 internal, 0.781 external) in validation. Net benefit was greater with radiomics than with clinical alone. The combined model exhibited performance with AUCs of 0.680, 0.752, and 0.830 for predicting 1-year, 3-year, and 5-year PFS, and 0.770, 0.789, and 0.863 for OS in internal validation, with PFS AUCs of 0.860 and 0.826 and OS AUCs of 0.859 and 0.748 for 1-year and 3-year survival in external validation. DATA CONCLUSION: Incorporating a multi-sequence MR-based radiomics model into clinical models enhances the assess accuracy for the prognosis of PCNSL. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Study on the treatment of dysphagia after stroke with electromyographic biofeedback intensive training.

BACKGROUND: Dysphagia, or swallowing disorder, is a common complication following stroke, significantly impacting patients' quality of life. Electromyographic biofeedback (EMGBF) therapy has emerged as a potential rehabilitation technique to improve swallowing function, but its efficacy in comparison with conventional treatments remains to be further explored. AIM: To investigate the effects of different treatment intensities of EMGBF on swallowing function and motor speed after stroke. METHODS: The participants were divided into three groups, all of which received routine neurological drug therapy and motor function rehabilitation training. On the basis of routine swallowing disorder training, the EMGBF group received additional EMGBF training, while the enhanced EMGBF group received two additional training sessions. Four weeks before and after treatment, the degree of swallowing disorder was evaluated using the degree of swallowing disorder score (VGF) and the Rosenbek penetration-aspiration scale (PAS). RESULTS: Initially, there was no significant difference in VGF and PAS scores among the groups (P > 0.05). After four weeks, all groups showed significant improvement in both VGF scores and PAS scores. Furthermore, the standardized swallowing assessment and videofluoroscopic dysphagia scale scores also improved significantly post-treatment, indicating enhanced swallowing function and motor function of the hyoid-bone laryngeal complex, particularly in the intensive EMGBF group. CONCLUSION: EMGBF training is more effective than traditional swallowing training in improving swallowing function and the movement rate of the hyoid laryngeal complex in patients with post-stroke dysphagia.

Fed-MStacking: Heterogeneous Federated Learning with Stacking Misaligned Labels for Abnormal Heart Sound Detection.

Ubiquitous sensing has been widely applied in smart healthcare, providing an opportunity for intelligent heart sound auscultation. However, smart devices contain sensitive information, raising user privacy concerns. To this end, federated learning (FL) has been adopted as an effective solution, enabling decentralised learning without data sharing, thus preserving data privacy in the Internet of Health Things (IoHT). Nevertheless, traditional FL requires the same architectural models to be trained across local clients and global servers, leading to a lack of model heterogeneity and client personalisation. For medical institutions with private data clients, this study proposes Fed-MStacking, a heterogeneous FL framework that incorporates a stacking ensemble learning strategy to support clients in building their own models. The secondary objective of this study is to address scenarios involving local clients with data characterised by inconsistent labelling. Specifically, the local client contains only one case type, and the data cannot be shared within or outside the institution. To train a global multi-class classifier, we aggregate missing class information from all clients at each institution and build meta-data, which then participates in FL training via a meta-learner. We apply the proposed framework to a multi-institutional heart sound database. The experiments utilise random forests (RFs), feedforward neural networks (FNNs), and convolutional neural networks (CNNs) as base classifiers. The results show that the heterogeneous stacking of local models performs better compared to homogeneous stacking.

Evidence of a distinct collective mode in Kagome superconductors.

The collective modes of the superconducting order parameter fluctuation can provide key insights into the nature of the superconductor. Recently, a family of superconductors has emerged in non-magnetic kagome materials AV3Sb5 (A = K, Rb, Cs), exhibiting fertile emergent phenomenology. However, the collective behaviors of Cooper pairs have not been studied. Here, we report a distinct collective mode in CsV3-xTaxSb5 using scanning tunneling microscope/spectroscopy. The spectral line-shape is well-described by one isotropic and one anisotropic superconducting gap, and a bosonic mode due to electron-mode coupling. With increasing x, the two gaps move closer in energy, merge into two isotropic gaps of equal amplitude, and then increase synchronously. The mode energy decreases monotonically to well below 2 Δ and survives even after the charge density wave order is suppressed. We propose the interpretation of this collective mode as Leggett mode between different superconducting components or the Bardasis-Schrieffer mode due to a subleading superconducting component.

Mechanisms of Postischemic Stroke Angiogenesis: A Multifaceted Approach.

Ischemic stroke constitutes a significant global health care challenge, and a comprehensive understanding of its recovery mechanisms is imperative for the development of innovative therapeutic strategies. Angiogenesis, a pivotal element of ischemic tissue repair, facilitates the restoration of blood flow to damaged regions, thereby promoting neuronal regeneration and functional recovery. Nevertheless, the mechanisms underlying postischemic stroke angiogenesis remain incompletely elucidated. This review meticulously examines the constituents of the neurovascular unit, ion channels, molecular mediators, and signaling pathways implicated in angiogenesis following stroke. Furthermore, it delves into prospective therapeutic strategies informed by these factors. Our objective is to provide detailed and exhaustive information on the intricate mechanisms governing postischemic stroke angiogenesis, thus providing a robust scientific foundation for the advancement of novel neurorepair therapies.

MARCH1 negatively regulates TBK1-mTOR signaling pathway by ubiquitinating TBK1.

BACKGROUND: TBK1 positively regulates the growth factor-mediated mTOR signaling pathway by phosphorylating mTOR. However, it remains unclear how the TBK1-mTOR signaling pathway is regulated. Considering that STING not only interacts with TBK1 but also with MARCH1, we speculated that MARCH1 might regulate the mTOR signaling pathway by targeting TBK1. The aim of this study was to determine whether MARCH1 regulates the mTOR signaling pathway by targeting TBK1. METHODS: The co-immunoprecipitation (Co-IP) assay was used to verify the interaction between MARCH1 with STING or TBK1. The ubiquitination of STING or TBK1 was analyzed using denatured co-immunoprecipitation. The level of proteins detected in the co-immunoprecipitation or denatured co-immunoprecipitation samples were determined by Western blotting. Stable knocked-down cells were constructed by infecting lentivirus bearing the related shRNA sequences. Scratch wound healing and clonogenic cell survival assays were used to detect the migration and proliferation of breast cancer cells. RESULTS: We showed that MARCH1 played an important role in growth factor-induced the TBK1- mTOR signaling pathway. MARCH1 overexpression attenuated the growth factor-induced activation of mTOR signaling pathway, whereas its deficiency resulted in the opposite effect. Mechanistically, MARCH1 interacted with and promoted the K63-linked ubiquitination of TBK1. This ubiquitination of TBK1 then attenuated its interaction with mTOR, thereby inhibiting the growth factor-induced mTOR signaling pathway. Importantly, faster proliferation induced by MARCH1 deficiency was weakened by mTOR, STING, or TBK1 inhibition. CONCLUSION: MARCH1 suppressed growth factors mediated the mTOR signaling pathway by targeting the STING-TBK1-mTOR axis.

Resting-state dynamic functional connectivity in major depressive disorder: A systematic review.

As a novel measure, dynamic functional connectivity (dFC) provides insight into the dynamic nature of brain networks and their interactions in resting-state, surpassing traditional static functional connectivity in pathological conditions such as depression. Since a comprehensive review is still lacking, we then reviewed forty-five eligible papers to explore pathological mechanisms of major depressive disorder (MDD) from perspectives including abnormal brain regions and functional networks, brain state, topological properties, relevant recognition, along with longitudinal studies. Though inconsistencies could be found, common findings are: (1) From different perspectives based on dFC, default-mode network (DMN) with its subregions exhibited a close relation to the pathological mechanism of MDD. (2) With a corrupted integrity within large-scale functional networks and imbalance between them, longer fraction time in a relatively weakly-connected state may be a possible property of MDD concerning its relation with DMN. Abnormal transition frequencies between states were correlated to the severity of MDD. (3) Including dynamic properties in topological network metrics enhanced recognition effect. In all, this review summarized its use for clinical diagnosis and treatment, elucidating the non-stationary of MDD patients' aberrant brain activity in the absence of stimuli and bringing new views into its underlying neuro mechanism.

Targeting the transmembrane cytokine co-receptor neuropilin-1 in distal tubules improves renal injury and fibrosis.

Neuropilin-1 (NRP1), a co-receptor for various cytokines, including TGF-ß, has been identified as a potential therapeutic target for fibrosis. However, its role and mechanism in renal fibrosis remains elusive. Here, we show that NRP1 is upregulated in distal tubular (DT) cells of patients with transplant renal insufficiency and mice with renal ischemia-reperfusion (I-R) injury. Knockout of Nrp1 reduces multiple endpoints of renal injury and fibrosis. We find that Nrp1 facilitates the binding of TNF-α to its receptor in DT cells after renal injury. This signaling results in a downregulation of lysine crotonylation of the metabolic enzyme Cox4i1, decreases cellular energetics and exacerbation of renal injury. Furthermore, by single-cell RNA-sequencing we find that Nrp1-positive DT cells secrete collagen and communicate with myofibroblasts, exacerbating acute kidney injury (AKI)-induced renal fibrosis by activating Smad3. Dual genetic deletion of Nrp1 and Tgfbr1 in DT cells better improves renal injury and fibrosis than either single knockout. Together, these results reveal that targeting of NRP1 represents a promising strategy for the treatment of AKI and subsequent chronic kidney disease.