Improving the academic resilience of hospital nursing interns through a hybrid multi-criteria decision analysis model.

Purpose: To identify the main variables affecting the academic adaptability of hospital nursing interns and key areas for improvement in preparing for future unpredictable epidemics. Methods: The importance of academic resilience-related variables for all nursing interns was analyzed using the random forest method, and key variables were further identified. An importance-performance analysis was used to identify the key improvement gaps regarding the academic resilience of nursing interns in the case hospital. Results: The random forest showed that five items related to cooperation, motivation, confidence, communication, and difficulty with coping were the main variables impacting the academic resilience of nursing interns. Moreover, the importance-performance analysis revealed that three items regarding options examination, communication, and confidence were the key improvement areas for participating nursing interns in the case hospital. Conclusions: For the prevention and control of future unpredictable pandemics, hospital nursing departments can strengthen the link between interns, nurses, and physicians and promote their cooperation and communication during clinical practice. At the same time, an application can be created considering the results of this study and combined with machine learning methods for more in-depth research. These will improve the academic resilience of nursing interns during the routine management of pandemics within hospitals.

Clot patterns determined by DSA and CTA can help predict intracranial atherosclerotic stenosis in acute ischemic stroke patients.

Background: This study examines whether clot patterns at large artery occlusion sites, as observed using digital subtraction angiography (DSA) and computed tomography angiography (CTA), can reliably indicate intracranial atherosclerotic stenosis (ICAS) in acute ischemic stroke (AIS) patients. Methods: We conducted a retrospective analysis of patients treated with stent retriever thrombectomy for intracranial occlusions at our institute since 2017, with follow-up assessments conducted at 3 months. The patients were grouped based on the initial angiography clot topographies (i.e., cut-off or tapered signs). We assessed the potential of these topographies in predicting ICAS, including a clinical outcome analysis based on clot pattern, age, Trial of Org 10172 in Acute Stroke Treatment (TOAST) classification, and onset-to-door time. Results: Among 131 patients (with a mean age of 66.6 years), the clot pattern emerged as a significant predictor of ICAS. The DSA-based model had a predictive area under the curve (AUC) of 0.745, with 55.1% sensitivity and 94.0% specificity. A multivariate model including age, onset-to-door time, TOAST classification as large artery atherosclerosis (LAA), and the presence of the tapered sign in clot patterns had an AUC of 0.916. In patients over 65 years of age with an onset-to-door time of >5 h and exhibiting a tapered sign in the clot pattern, the AUC reached 0.897. The predictive ability of the tapered sign was similar in DSA and CTA, showing 73.4% agreement between modalities. Conclusion: The clot pattern with the tapered sign as observed using DSA is significantly associated with ICAS. Incorporating this clot pattern with age, TOAST classification as LAA, and onset-to-door time enhances the prediction of ICAS. The clot pattern identified by CTA is also a reliable predictor, highlighting the importance of assessing clot patterns in ICAS identification.

Using status of secondary prevention medications in post-stroke dysphagia patients: time to raise awareness and develop special formulations.

Post-stroke dysphagia (PSD) is an increasingly common complication of stroke. Despite its intuitively unfavorable impact on secondary prevention medication use, limited awareness is available regarding this issue. Herein, a cross-sectional survey was conducted to determine the current use, patient-perceived needs and preferences for secondary prevention medications among PSD patients. To emphasize the unique context related to dysphagia, we recruited Chinese stroke patients with a duration of less than 5 years. These patients were initially categorized into PSD respondents with and without dysphagia. Among the 3490 eligible respondents, 42.7% reported experiencing dysphagia after stroke. Those PSD respondents were more likely to consume multiple medications and suffer from anticoagulants-associated gastrointestinal bleeding as compared to non-PSD ones (p < 0.001). More crucially, 40.2% of them had frequent difficulty in swallowing pills, 37.1% routinely crushed solid oral dosage forms (SODFs), and 23.5% coughed frequently when taking SODFs. In consequence, 87.4% responded a need for PSD-specific formulations where safe swallowing, easy swallowing, and reduced medication frequency were preferred pharmaceutical factors. These findings demonstrate an unsatisfactory situation and definite needs for PSD patients in using secondary prevention medications. Awareness should be increased to develop PSD-specific formulations for safe and effective secondary prevention.

Characterization and Dissolution Mechanism of Low-Molecular-Weight Organic Acids or Inorganic Mesoporous Particle-Based Piperine Amorphous Solid Dispersions.

The objective of the current study is to prepare amorphous solid dispersions (ASDs) containing piperine (PIP) by utilizing organic acid glycyrrhizic acid (GA) and inorganic disordered mesoporous silica 244FP (MSN/244FP) as carriers and to investigate their dissolution mechanism. The physicochemical properties of ASDs were characterized with scanning electron microscopy (SEM), powder X-ray diffraction (PXRD), and differential scanning calorimetry (DSC). Fourier transform infrared spectroscopy (FTIR) and one-dimensional proton nuclear magnetic resonance (1H NMR) studies collectively proved that strong hydrogen-bonding interactions formed between PIP and the carriers in ASDs. Additionally, molecular dynamic (MD) simulation was conducted to simulate and predict the physical stability and dissolution mechanisms of the ASDs. Interestingly, it revealed a significant increase in the dissolution of amorphous PIP in ASDs in in vitro dissolution studies. Rapid dissolution of GA in pH 6.8 medium resulted in the immediate release of PIP drugs into a supersaturated state, acting as a dissolution-control mechanism. This exhibited a high degree of fitting with the pseudo-second-order dynamic model, with an R2 value of 0.9996. Conversely, the silanol groups on the outer surface of the MSN and its porous nanostructures enabled PIP to display a unique two-step drug release curve, indicating a diffusion-controlled mechanism. This curve conformed to the Ritger-Peppas model, with an R2 > 0.9. The results obtained provide a clear evidence of the proposed transition of dissolution mechanism within the same ASD system, induced by changes in the properties of carriers in a solution medium of varying pH levels.

GluOC promotes proliferation and metastasis of TNBC through the ROCK1 signaling pathway.

BACKGROUND: Triple negative breast cancer (TNBC) is a type of breast cancer that is negative for oestrogen receptor, progesterone receptor and human epidermal growth factor receptor 2, is highly malignant and aggressive, lacks of corresponding targeted therapy, and has a relatively poor prognosis. Therefore, understanding the mechanism of TNBC development and formulating effective treatment strategies for inducing cell death are still urgent tasks in the treatment of TNBC. Research has shown that uncarboxylated osteocalcin can promote the proliferation of prostate cancer, lung adenocarcinoma and TNBC cells, but the mechanism by which GluOC affects TNBC growth and metastasis needs further study. METHODS: MDA-MB-231 breast cancer cells were used for in vitro cell analysis. Key target molecules or pathways were identified by RNA sequencing, and migration ability was detected by scratch assays, Transwell assays, cell adhesion assays and western blot analysis. Fluorescence staining, colony detection, qRT‒PCR and flow cytometry were used to detect apoptosis, oxidative stress, the cell cycle and the stemness of cancer cells, and a xenotransplantation model in BALB/C nude mice was used for in vivo analysis. RESULTS: This study demonstrated that GluOC facilitates the migration of MDA-MB-231 breast cancer cells through the ROCK1/MYPT1/MLC2 signalling pathway and promotes the proliferation of TNBC cells via the ROCK1/JAK2/PIK3CA/AKT signalling pathway. Experiments in nude mice demonstrated that GluOC promoted tumour cell proliferation and metastasis in tumour-bearing mice, which further clarified the molecular mechanism of TNBC growth and invasion. CONCLUSION: Our findings highlight the importance of GluOC in driving TNBC progression and its association with poor patient outcomes. This study clarifies the functional effects of GluOC on TNBC growth, providing insight into the molecular basis of TNBC and potentially providing new ideas for developing targeted therapies to improve patient outcomes.

Juvenile bright light exposure ameliorates adult behavioral abnormalities by enhancing neurogenesis in a N-methyl-D-aspartate receptor dysfunction mouse model relevant for cognitive impairment in schizophrenia.

Exposure to light has been demonstrated to stimulate brain regions associated with cognition; however, investigations into its cognitive-enhancing effects have primarily focused on wild-type rodents. This study seeks to elucidate how bright light exposure mitigates cognitive deficits associated with schizophrenia by examining its impact on hippocampal neurogenesis and its potential to alleviate sub-chronic MK-801-induced cognitive impairments in mice. Following three weeks of juvenile bright light exposure (5-8 weeks old), significant increases in proliferating neurons (BrdU+) and immature neurons (DCX+ cells) were observed in the dentate gyrus (DG) and lateral ventricle of MK-801-treated mice. Long-term bright light treatment further promoted the differentiation of BrdU+ cells into immature neurons (BrdU+ DCX+ cells), mature neurons (BrdU+ NeuN+ cells), or astrocytes (BrdU+ GFAP+ cells) in the hippocampal DG. This augmented neurogenesis correlated with the attenuation of sub-chronic MK- 801-induced cognitive deficits, as evidenced by enhancements in Y-maze, novel object recognition (NOR), novel location recognition (NLR), and Morris water maze (MWM) test performances. These findings suggest a promising noninvasive clinical approach for alleviating cognitive impairments associated with neuropsychiatric disorders.

Memantine alleviates cognitive impairment and hippocampal morphology injury in a mouse model of chronic alcohol exposure.

Alcohol-related cognitive impairment (ARCI) is highly prevalent among patients with alcohol abuse and dependence. The pathophysiology of ARCI, pivotal for refined therapeutic approaches, is not fully elucidated, posing a risk of progression to severe neurological sequelae such as Korsakoff's syndrome (KS) and Alcohol-Related Dementia (ARD). This study ventures into the underlying mechanisms of chronic alcohol-induced neurotoxicity, notably glutamate excitotoxicity and cytoskeletal disruption, and explores the therapeutic potential of Memantine, a non-competitive antagonist of the N-methyl-d-aspartate (NMDA) receptor known for its neuroprotective effect against excitotoxicity. Our investigation centers on the efficacy of Memantine in mitigating chronic alcohol-induced cognitive and hippocampal damages in vivo. Male C57BL/6J mice were subjected to 30 % (v/v, 6.0 g/kg) ethanol via intragastric administration alongside Memantine co-treatment (10 mg/kg/day, intraperitoneally) for six weeks. The assessment involved Y maze, Morris water maze, and novel object recognition tests to evaluate spatial and recognition memory deficits. Histopathological evaluations of the hippocampus were conducted to examine the extent of alcohol-induced morphological changes and the potential protective effect of Memantine. The findings reveal that Memantine significantly improves chronic alcohol-compromised cognitive functions and mitigates hippocampal pathological changes, implicating a moderating effect on the disassembly of actin cytoskeleton and microtubules in the hippocampus, induced by chronic alcohol exposure. Our results underscore Memantine's capability to attenuate chronic alcohol-induced cognitive and hippocampal morphological harm may partly through regulating cytoskeleton dynamics, offering valuable insights into innovative therapeutic strategies for ARCI.

The cytotoxic natural compound erianin binds to colchicine site of ß-tubulin and overcomes taxane resistance.

Erianin, a natural compound derived from Dendrobium, has shown significant anticancer properties against a wide range of cancer cells. Despite the identification of multiple mechanisms of action for erianin, none of these mechanisms fully account for its broad-spectrum effect. In this study, we aimed to identify the cellular target and underlying mechanism responsible for the broad-spectrum antitumor effects of erianin. We found that erianin effectively inhibited tubulin polymerization in cancer cells and purified tubulin. Through competition binding assays and X-ray crystallography, it was revealed that erianin bound to the colchicine site of ß-tubulin. Importantly, the X-ray crystal structure of the tubulin-erianin complex was solved, providing clear insight into the orientation and position of erianin in the colchicine-binding site. Erianin showed activity against paclitaxel-resistant cells, evidenced by G2/M cell cycle arrest, apoptosis-related PARP and Caspase-3 cleavage, and in vivo xenograft studies. The study concluded that erianin bound reversibly to the colchicine site of ß-tubulin, inhibited tubulin polymerization, and displayed anticancer activity against paclitaxel-resistant cells, offering valuable insights for further exploration as potential anticancer agents.

Global trends in the research on older population dizziness/vertigo: a 20-year bibliometric and visualization analysis.

OBJECTIVE: Dizziness or vertigo in older population frequently presents in clinical settings, yet its etiology remains elusive. The objective of this study was to delineate global trends and identify frontiers in research concerning dizziness or vertigo among older population. METHODS: We searched the research literature published from 2003 to 2022 on older population with dizziness or vertigo using two databases from the Web of Science Core Collection. A bibliometric and visualization analysis was conducted. Bibliometric tools facilitated co-authorship, co-citation, and keyword co-occurrence analyses, encompassing countries or regions, institutions, authors, journals, and references. RESULTS: The analysis included 1322 publications authored by 6524 individuals from 2244 institutions across 67 countries or regions, spanning 92 subject categories. A steady increase in publications was noted from 2003 to 2022. The University of Munich, Harvard University, and the University of California System emerged as leading institutions with the highest publication outputs. The United States, Germany, and China were predominant in publication counts. Eva Grill was identified as the most prolific author. Otology & Neurotology and Geriatrics & Gerontology emerged as the most prolific journal and subject category, respectively. The most prevalent keywords were "dizziness", "vertigo", "falls", and "geriatric", with "management", "gait", and "association" recognized as the principal research hotspots. CONCLUSION: This study provides a systematic analysis of global scientific research on older population dizziness/vertigo, revealing significant advancements in understanding over the past two decades. Management, gait, and association have emerged as the primary research focuses on recent years. These findings offer valuable insights for directing current research efforts to capture prevailing trends and explore new frontiers in this field.

Real-world data of tenecteplase vs. alteplase in the treatment of acute ischemic stroke: a single-center analysis.

Background: This retrospective observational cohort study aimed to evaluate whether tenecteplase's use for acute ischemic stroke (AIS) has time management advantages and clinical benefits. Methods: 144 AIS patients treated with alteplase and 120 with tenecteplase were included. We compared baseline clinical characteristics, key reperfusion therapy time indices [onset-to-treatment time (OTT), door-to-needle time (DNT), and door-to-puncture time (DPT)] and clinical outcomes (24-h post-thrombolysis NIHSS improvement, and intracranial hemorrhage incidence) between the groups using univariate analysis. We assessed hospital stay durations and used binary logistic regression to examine tenecteplase's association with DNT and DPT target times, NIHSS improvement, and intracranial hemorrhage. Results: Baseline characteristics showed no significant differences except hyperlipidemia and atrial fibrillation. OTT (133 vs. 163.72, p = 0.001), DNT (36.5 vs. 50, p < 0.001) and DPT (117 vs. 193, p = 0.002) were significantly faster in the tenecteplase group. The rates of DNT ≤ 45 min (65.83% vs. 40.44%, p < 0.001) and DPT ≤ 120 min (59.09% vs. 13.79%, p = 0.001) were significantly higher in the tenecteplase group. Tenecteplase was an independent predictor of achieving target DNT (OR 2.951, 95% CI 1.732-5.030; p < 0.001) and DPT (OR 7.867, 95% CI 1.290-47.991; p = 0.025). Clinically, the proportion NIHSS improvement 24 h post-thrombolysis was higher in the tenecteplase group (64.17% vs. 50%, p = 0.024). No significant differences were observed in symptomatic intracranial hemorrhage (sICH) or any intracranial hemorrhage (ICH). Patients receiving tenecteplase had shorter hospital stays (6 vs. 8 days, p < 0.001). Tenecteplase was an independent predictor of NIHSS improvement at 24 h (OR 1.715, 95% CI 1.011-2.908; p = 0.045). There was no significant association between thrombolytic choice and sICH or any ICH. Conclusion: Tenecteplase significantly reduced DNT and DPT. It was associated with early neurological function improvement (at 24 h), without compromising safety compared to alteplase. The findings support tenecteplase's application in AIS.

Autoantigenic Peptide and Immunomodulator Codelivery System for Rheumatoid Arthritis Treatment by Reestablishing Immune Tolerance.

Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by abnormal activation of CD4+ T cells and an imbalance of T helper 17 (Th17) and regulatory T (Treg) cells. Tolerogenic therapy via administration of self-antigens is a promising strategy for RA treatment, but delivery of autoantigens alone may exacerbate disease conditions. Current studies indicated that codelivery of autoantigens with immunomodulators can lead to a more tolerogenic immune response. Here, we constructed an autoantigen type II collagen peptide (CII250-270)- and immunomodulator leflunomide (LEF)-coloaded phosphatidylserine liposome vaccine (CII250-270-LEF-PSL) for RA treatment via induction of tolerant dendritic cells (tolDC) for further activation of Treg cells. The in vivo results showed that CII250-270-LEF-PSL can effectively induce tolDC, regulate the balance of Th1/Th2 and Th17/Treg, and reduce the secretion of pro-inflammatory cytokines (IFN-γ, IL-1ß, and IL-17A) and IgG antibodies to inhibit synovial inflammation and bone erosion. Furthermore, our study also suggested that LEF regulated Th1 cell differentiation by inhibiting the activation of the JAK1/STAT1 signaling pathway, further alleviating RA. Overall, this work proved that the combination of autoantigenic peptides and immunomodulators was a promising modality for RA treatment by reestablishing antigen-specific immune tolerance, which also inspired additional insights into the development of combination therapies for the tolerability of RA.

Abdominal physical examinations in early stages benefit critically ill patients without primary gastrointestinal diseases: a retrospective cohort study.

Background: Gastrointestinal (GI) function is critical for patients in intensive care units (ICUs). Whether and how much critically ill patients without GI primary diseases benefit from abdominal physical examinations remains unknown. No evidence from big data supports its possible additive value in outcome prediction. Methods: We performed a big data analysis to confirm the value of abdominal physical examinations in ICU patients without GI primary diseases. Patients were selected from the Medical Information Mart for Intensive Care (MIMIC)-IV database and classified into two groups depending on whether they received abdominal palpation and auscultation. The primary outcome was the 28-day mortality. Statistical approaches included Cox regression, propensity score matching, and inverse probability of treatment weighting. Then, the abdominal physical examination group was randomly divided into the training and testing cohorts in an 8:2 ratio. And patients with GI primary diseases were selected as the validation group. Several machine learning algorithms, including Random Forest, Gradient Boosting Decision Tree, Adaboost, Extra Trees, Bagging, and Multi-Layer Perceptron, were used to develop in-hospital mortality predictive models. Results: Abdominal physical examinations were performed in 868 (2.63%) of 33,007 patients without primary GI diseases. A significant benefit in terms of 28-day mortality was observed among the abdominal physical examination group (HR 0.75, 95% CI 0.56-0.99; p = 0.043), and a higher examination frequency was associated with improved outcomes (HR 0.62, 95%CI 0.40-0.98; p = 0.042). Machine learning studies further revealed that abdominal physical examinations were valuable in predicting in-hospital mortality. Considering both model performance and storage space, the Multi-Layer Perceptron model performed the best in predicting mortality (AUC = 0.9548 in the testing set and AUC = 0.9833 in the validation set). Conclusion: Conducting abdominal physical examinations improves outcomes in critically ill patients without GI primary diseases. The results can be used to predict in-hospital mortality using machine learning algorithms.

The potential application of complement inhibitors-loaded nanosystem for autoimmune diseases via regulation immune balance.

The complement is an important arm of the innate immune system, once activated, the complement system rapidly generates large quantities of protein fragments that are potent mediators of inflammation. Recent studies have shown that over-activated complement is the main proinflammatory system of autoimmune diseases (ADs). In addition, activated complements interact with autoantibodies, immune cells exacerbate inflammation, further worsening ADs. With the increasing threat of ADs to human health, complement-based immunotherapy has attracted wide attention. Nevertheless, efficient and targeted delivery of complement inhibitors remains a significant challenge owing to their inherent poor targeting, degradability, and low bioavailability. Nanosystems offer innovative solutions to surmount these obstacles and amplify the potency of complement inhibitors. This prime aim to present the current knowledge of complement in ADs, analyse the function of complement in the pathogenesis and treatment of ADs, we underscore the current situation of nanosystems assisting complement inhibitors in the treatment of ADs. Considering technological, physiological, and clinical validation challenges, we critically appraise the challenges for successfully translating the findings of preclinical studies of these nanosystem assisted-complement inhibitors into the clinic, and future perspectives were also summarised. (The graphical abstract is by BioRender.).

Insight into the Storage Mechanism of Sandwich-Like Molybdenum Disulphide/Carbon Nanofibers Composite in Aluminum-Ion Batteries.

Aluminum-ion batteries (AIBs) have become a research hotspot in the field of energy storage due to their high energy density, safety, environmental friendliness, and low cost. However, the actual capacity of AIBs is much lower than the theoretical specific capacity, and their cycling stability is poor. The exploration of energy storage mechanisms may help in the design of stable electrode materials, thereby contributing to improving performance. In this work, molybdenum disulfide (MoS2) was selected as the host material for AIBs, and carbon nanofibers (CNFs) were used as the substrate to prepare a molybdenum disulfide/carbon nanofibers (MoS2/CNFs) electrode, exhibiting a residual reversible capacity of 53 mAh g-1 at 100 mA g-1 after 260 cycles. The energy storage mechanism was understood through a combination of electrochemical characterization and first-principles calculations. The purpose of this study is to investigate the diffusion behavior of ions in different channels in the host material and its potential energy storage mechanism. The computational analysis and experimental results indicate that the electrochemical behavior of the battery is determined by the ion transport mechanism between MoS2 layers. The insertion of ions leads to lattice distortion in the host material, significantly impacting its initial stability. CNFs, serving as a support material, not only reduce the agglomeration of MoS2 grown on its surface, but also effectively alleviate the volume expansion caused by the host material during charging and discharging cycles.

Structure-based design and synthesis of BML284 derivatives: A novel class of colchicine-site noncovalent tubulin degradation agents.

Our previous studies have demonstrated that BML284 is a colchicine-site tubulin degradation agent. To improve its antiproliferative properties, 45 derivatives or analogs of BML284 were designed and synthesized based on the cocrystal structure of BML284 and tubulin. Among them, 5i was the most potent derivative, with IC50 values ranging from 0.02 to 0.05 µM against the five tested tumor cell lines. Structure-activity relationship studies verified that the N1 atom of the pyrimidine ring was the key functional group for its tubulin degradation ability. The 5i-tubulin cocrystal complex revealed that the binding pattern of 5i to tubulin is similar to that of BML284. However, replacing the benzodioxole ring with an indole ring strengthened the hydrogen bond formed by the 2-amino group with E198, which improved the antiproliferative activity of 5i. Compound 5i effectively suppressed tumor growth at an intravenous dose of 40 mg/kg (every 2 days) in paclitaxel sensitive A2780S and paclitaxel resistant A2780T ovarian xenograft models, with tumor growth inhibition values of 79.4% and 82.0%, respectively, without apparent side effects, showing its potential to overcome multidrug resistance. This study provided a successful example of crystal structure-guided discovery of 5i as a colchicine-targeted tubulin degradation agent, expanding the scope of targeted protein degradation.

Effect of anesthesia mode during endovascular treatment on neurological functional outcomes in patients with acute posterior circulation stroke. / éº»é†‰æ–¹å¼å¯¹æ€¥æ€§åŽå¾ªçŽ¯è„‘å’ä¸­è¡€ç®¡å† æ²»ç–—æ‚£è€ ç¥žç»åŠŸèƒ½ç»“å±€çš„å½±å“.

OBJECTIVES: To compare the effect of anesthesia mode on the neurological functional outcomes in patients undergoing endovascular treatment for acute posterior circulation ischemic stroke. METHODS: Clinical data of 656 patients undergoing intravascular therapy for acute posterior circulation ischemic stroke registered in online Acute Stroke Patients for Stroke Management Quality Evaluation Database from January 2017 to December 2022 were retrospectively analyzed. The data included 163 cases with conscious sedation and 493 cases with general anesthesia during the procedure. After propensity score matching, 428 patients were included in the analysis, including 155 cases in the conscious sedation group and 273 cases in the general anesthesia group. The differences of operation mode, etiology type, vascular recanalization, hemorrhagic transformation at 24 h, modified Rankin Scale (mRS) score at 3 months and mortality within 3 months were compared between the two groups. Binary logistic regression was used to explore the effect of different anesthesia mode on neurological functional outcomes. RESULTS: There was a significant difference in operation mode between the two groups (P<0.01), while there were no significant differences in etiology type, vascular recanalization, hemorrhagic transformation at 24 h, mRS score at 3 months or mortality within 3 months (all P>0.05). Binary logistic regression analysis revealed that anesthesia modes were not significantly associated with functional outcomes of patients (OR=1.151, 95%CI: 0.751-1.765, P>0.05). CONCLUSIONS: Anesthesia mode (conscious sedation or general anesthesia) will not affect the neurological functional outcomes in patients with acute posterior circulation ischemic stroke undergoing endovascular treatment.

NU6300 covalently reacts with cysteine-191 of gasdermin D to block its cleavage and palmitoylation.

Gasdermin D (GSDMD) serves as a vital mediator of inflammasome-driven pyroptosis. In our study, we have identified NU6300 as a specific GSDMD inhibitor that covalently interacts with cysteine-191 of GSDMD, effectively blocking its cleavage while not affecting earlier steps such as ASC oligomerization and caspase-1 processing in AIM2- and NLRC4-mediated inflammation. On the contrary, NU6300 robustly inhibits these earlier steps in NLRP3 inflammasome, confirming a unique feedback inhibition effect in the NLRP3-GSDMD pathway upon GSDMD targeting. Our study reveals a previously undefined mechanism of GSDMD inhibitors: NU6300 impairs the palmitoylation of both full-length and N-terminal GSDMD, impeding the membrane localization and oligomerization of N-terminal GSDMD. In vivo studies further demonstrate the efficacy of NU6300 in ameliorating dextran sodium sulfate-induced colitis and improving survival in lipopolysaccharide-induced sepsis. Overall, these findings highlight the potential of NU6300 as a promising lead compound for the treatment of inflammatory diseases.

PolypMixNet: Enhancing semi-supervised polyp segmentation with polyp-aware augmentation.

BACKGROUND: AI-assisted polyp segmentation in colonoscopy plays a crucial role in enabling prompt diagnosis and treatment of colorectal cancer. However, the lack of sufficient annotated data poses a significant challenge for supervised learning approaches. Existing semi-supervised learning methods also suffer from performance degradation, mainly due to task-specific characteristics, such as class imbalance in polyp segmentation. PURPOSE: The purpose of this work is to develop an effective semi-supervised learning framework for accurate polyp segmentation in colonoscopy, addressing limited annotated data and class imbalance challenges. METHODS: We proposed PolypMixNet, a semi-supervised framework, for colorectal polyp segmentation, utilizing novel augmentation techniques and a Mean Teacher architecture to improve model performance. PolypMixNet introduces the polyp-aware mixup (PolypMix) algorithm and incorporates dual-level consistency regularization. PolypMix addresses the class imbalance in colonoscopy datasets and enhances the diversity of training data. By performing a polyp-aware mixup on unlabeled samples, it generates mixed images with polyp context along with their artificial labels. A polyp-directed soft pseudo-labeling (PDSPL) mechanism was proposed to generate high-quality pseudo labels and eliminate the dilution of lesion features caused by mixup operations. To ensure consistency in the training phase, we introduce the PolypMix prediction consistency (PMPC) loss and PolypMix attention consistency (PMAC) loss, enforcing consistency at both image and feature levels. Code is available at https://github.com/YChienHung/PolypMix. RESULTS: PolypMixNet was evaluated on four public colonoscopy datasets, achieving 88.97% Dice and 88.85% mIoU on the benchmark dataset of Kvasir-SEG. In scenarios where the labeled training data is limited to 15%, PolypMixNet outperforms the state-of-the-art semi-supervised approaches with a 2.88-point improvement in Dice. It also shows the ability to reach performance comparable to the fully supervised counterpart. Additionally, we conducted extensive ablation studies to validate the effectiveness of each module and highlight the superiority of our proposed approach. CONCLUSION: PolypMixNet effectively addresses the challenges posed by limited annotated data and unbalanced class distributions in polyp segmentation. By leveraging unlabeled data and incorporating novel augmentation and consistency regularization techniques, our method achieves state-of-the-art performance. We believe that the insights and contributions presented in this work will pave the way for further advancements in semi-supervised polyp segmentation and inspire future research in the medical imaging domain.

Rapid dataset generation methods for stacked construction solid waste based on machine vision and deep learning.

The development of urbanization has brought convenience to people, but it has also brought a lot of harmful construction solid waste. The machine vision detection algorithm is the crucial technology for finely sorting solid waste, which is faster and more stable than traditional methods. However, accurate identification relies on large datasets, while the datasets from the field working conditions are scarce, and the manual annotation cost of datasets is high. To rapidly and automatically generate datasets for stacked construction waste, an acquisition and detection platform was built to automatically collect different groups of RGB-D images for instances labeling. Then, based on the distribution points generation theory and data augmentation algorithm, a rapid-generation method for synthetic construction solid waste datasets was proposed. Additionally, two automatic annotation methods for real stacked construction solid waste datasets based on semi-supervised self-training and RGB-D fusion edge detection were proposed, and datasets under real-world conditions yield better models training results. Finally, two different working conditions were designed to validate these methods. Under the simple working condition, the generated dataset achieved an F1-score of 95.98, higher than 94.81 for the manually labeled dataset. In the complicated working condition, the F1-score obtained by the rapid generation method reached 97.74. In contrast, the F1-score of the dataset obtained manually labeled was only 85.97, which demonstrates the effectiveness of proposed approaches.