Left atrial appendage thrombus is associated with a higher fractal dimension in patients with atrial fibrillation.

PURPOSE: To assess the anatomical complexity of the left atrial appendage (LAA) using fractal dimension (FD) based on cardiac computed tomography angiography (CTA) and the association between LAA FD and LAA thrombosis. MATERIALS AND METHODS: Patients with atrial fibrillation (AF) who underwent both cardiac CTA and transesophageal echocardiography (TEE) between December 2018 and December 2022 were retrospectively analyzed. Patients were categorized into normal (n = 925), circulatory stasis (n = 82), and thrombus groups (n = 76) based on TEE results and propensity score matching (PSM) was performed for subsequent analysis. FD was calculated to quantify the morphological heterogeneity of LAA. Independent risk factors for thrombus were screened using logistic regression. The diagnostic performance of FD and CHA2DS2-VaSc score for predicting thrombus was evaluated using the area under the receiver operating characteristics curve (AUC). RESULTS: LAA FD was higher in the thrombus group (1.61 [1.49, 1.70], P < 0.001) than in the circulatory stasis (1.33 [1.18, 1.47]) and normal groups (1.30 [1.18, 1.42]) both before and after PSM. LAA FD was also an independent risk factor in the thrombus (OR [odds ratio] = 570,861.15 compared to normal, 41,122.87 compared to circulatory stasis; all P < 0.001) and circulatory stasis group (OR = 98.87, P = 0.001) after PSM. The diagnostic performance of LAA FD was significantly better than the CHA2DS2-VaSc score in identifying thrombus. CONCLUSIONS: Patients with high LAA FD are more likely to develop LAA thrombus, and the use of FD provides an effective method for assessing the risk of thrombosis in AF patients, thereby guiding individualized clinical treatment.

BiVO4 Film Coupling with CoAl2O4 Nanoparticles for Photoelectrochemical Water Splitting Utilizing Broad Solar Spectrum through p-n Heterojunction, Photothermal, and Cocatalytic Synergism.

Water oxidation is an endothermic and kinetics-sluggish reaction; the research of photoanodes with photothermal and cocatalytic properties is of great significance. Herein, BiVO4/CoAl2O4 film photoanodes were studied for solar water splitting through coupling spinel p-type CoAl2O4 nanoparticles on n-type BiVO4 films. Compared to the BiVO4 photoanode, better performance was observed on the BiVO4/CoAl2O4 photoanode during water oxidation. A photocurrent of 3.47 mA/cm2 was produced on the BiVO4/CoAl2O4 photoanode at 1.23 V vs RHE, which is two-fold to the BiVO4 photoanode (1.70 mA/cm2). Additionally, the BiVO4/CoAl2O4 photoanodes showed an acceptable stability for water oxidation. The BiVO4/CoAl2O4 photoanode being of higher water oxidation performance could be attributed to the presence of p-n heterojunction, cocatalytic, and photothermal effects. In specific, under the excitation of λ < 520 nm light, the holes produced in/on BiVO4 can be transferred to CoAl2O4 owing to the p-n heterojunctions of BiVO4/CoAl2O4. Meanwhile, the temperature on the BiVO4/CoAl2O4 photoanode rises quickly up to ∼53 °C under AM 1.5 G irradiation due to the photothermal property of CoAl2O4 through capturing the 520 < λ < 720 nm light. The temperature rising on the BiVO4/CoAl2O4 photoanode improves the cocatalytic activity of CoAl2O4 and modifies the wettability of BiVO4/CoAl2O4 for effective water oxidation.

Predicting Durable Clinical Benefits of Postoperative Adjuvant Chemotherapy in Non-small Cell Lung Cancer: A Nomogram Based on CT Imaging and Immune Type.

PURPOSE: To develop a model based on conventional CT signs and the tumor microenvironment immune types (TIMT) to predict the durable clinical benefits (DCB) of postoperative adjuvant chemotherapy in non-small cell lung cancer (NSCLC). METHODS AND MATERIALS: A total of 205 patients with NSCLC underwent preoperative CT and were divided into two groups: DCB (progression-free survival (PFS) ≥ 18 months) and non-DCB (NDCB, PFS <18 months). The density percentiles of PD-L1 and CD8 + tumor-infiltrating lymphocytes (TIL) were quantified to estimate the TIMT. Clinical characteristics and conventional CT signs were collected. Multivariate logistic regression was employed to select the most discriminating parameters, construct a predictive model, and visualize the model as a nomogram. Receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA) were used to evaluate prediction performance and clinical utility. RESULTS: Precisely 118 patients with DCB and 87 with NDCB in NSCLC received postoperative adjuvant chemotherapy. TIMT was statistically different between the DCB and NDCB groups (P < 0.05). Clinical characteristics (neuron-specific enolase, squamous cell carcinoma antigen, Ki-76, and cM stage) and conventional CT signs (spiculation, bubble-like lucency, pleural retraction, maximum diameter, and CT value of the venous phase) varied between the four TIMT groups (P < 0.05). Furthermore, clinical characteristics (lymphocyte count [LYMPH] and cM stage) and conventional CT signs (bubble-like lucency and Pleural effusion) differed between the DCB and NDCB groups (P < 0.05). Multivariate analysis revealed that TIMT, cM stage, LYMPH, and pleural effusion were independently associated with DCB and were used to construct a nomogram. The area under the curve (AUC) of the combined model was 0.70 (95%CI: 0.64-0.76), with sensitivity and specificity of 0.73 and 0.60, respectively. CONCLUSION: Conventional CT signs and the TIMT offer a promising approach to predicting clinical outcomes for patients treated with postoperative adjuvant chemotherapy in NSCLC.

High Ambipolar Mobility and Long-Range Carrier Transport in Violet Phosphorus Nanosheet.

Carrier transport capacity with high mobility and long-range diffusion length holds particular significance for the advancement of modern optoelectronic devices. Herein, we have unveiled the carrier dynamics and transport properties of a pristine violet phosphorus (VP) nanosheet by a transient absorption microscopy. Under the excitation (2.41 eV) above the exciton band, two photoinduced absorption peaks with the energy difference of approximately 520 meV emerge within a broadband transient absorption background which originates from the prompt generation of free carriers and the concomitant formation of excitons (lifetime of 467.21 ps). This observation is consistent with the established band-edge model of VP. Intriguingly, we have determined the ambipolar diffusion coefficient and mobility of VP to be approximately 47.32 cm2·s-1 and 1798 cm2·V-1·s-1, respectively, which further indicate a long-range carrier transport of approximately 2.10 µm. This work unveils the significant carrier transport capacity of VP, highlighting its potential for future optoelectronic and excitonic applications.

SPP1 promotes the polarization of M2 macrophages through the Jak2/Stat3 signaling pathway and accelerates the progression of idiopathic pulmonary fibrosis.

Idiopathic pulmonary fibrosis (IPF) is a fatal pulmonary disease that requires further investigation to understand its pathogenesis. The present study demonstrated that secreted phosphoprotein 1 (SPP1) was aberrantly highly expressed in the lung tissue of patients with IPF and was significantly positively associated with macrophage and T­cell activity. Cell localization studies revealed that SPP1 was primarily overexpressed in macrophages, rather than in T cells. Functionally, knocking down SPP1 expression in vitro inhibited the secretion of fibrosis­related factors and M2 polarization in macrophages. Furthermore, knocking down SPP1 expression inhibited the macrophage­induced epithelial­to­mesenchymal transition in both epithelial and fibroblastic cells. Treatment with SPP1 inhibitors in vivo enhanced lung function and ameliorated pulmonary fibrosis. Mechanistically, SPP1 appears to promote macrophage M2 polarization by regulating the JAK/STAT3 signaling pathway both in vitro and in vivo. In summary, the present study found that SPP1 promotes M2 polarization of macrophages through the JAK2/STAT3 signaling pathway, thereby accelerating the progression of IPF. Inhibition of SPP1 expression in vivo can effectively alleviate the development of IPF, indicating that SPP1 in macrophages may be a potential therapeutic target for IPF.

PFC/M1 activation and excitability: a longitudinal cohort study on fatigue symptoms in healthcare workers post-COVID-19.

BACKGROUND: Fatigue is one of the most common neurological symptoms reported post coronavirus disease 2019 (COVID-19) infection. In order to establish effective early intervention strategies, more emphasis should be placed on the correlation between fatigue and cortical neurophysiological changes, especially in healthcare workers, who are at a heightened risk of COVID-19 infection. METHODS: A prospective cohort study was conducted involving 29 COVID-19 medical workers and 24 healthy controls. The assessment included fatigue, sleep and health quality, psychological status, and physical capacity. Functional near-infrared spectroscopy (fNIRS) was employed to detect activation of brain regions. Bilateral primary motor cortex (M1) excitabilities were measured using single- and paired-pulse transcranial magnetic stimulation. Outcomes were assessed at 1, 3, and 6 months into the disease course. RESULTS: At 1-month post-COVID-19 infection, 37.9% of patients experienced severe fatigue symptoms, dropping to 10.3% at 3 months. Interestingly, the remarkable decreased activation/excitability of bilateral prefrontal lobe (PFC) and M1 were closely linked to fatigue symptoms after COVID-19. Notably, greater increase in M1 region excitability correlated with more significant fatigue improvement. Re-infected patients exhibited lower levels of brain activation and excitability compared to single-infection patients. CONCLUSIONS: Both single infection and reinfection of COVID-19 lead to decreased activation and excitability of the PFC and M1. The degree of excitability improvement in the M1 region correlates with a greater recovery in fatigue. Based on these findings, targeted interventions to enhance and regulate the excitability of M1 may represent a novel strategy for COVID-19 early rehabilitation. TRIAL REGISTRATION: The Ethics Review Committee of Xijing Hospital, No. KY20232051-F-1; www.chictr.org.cn , ChiCTR2300068444.

CMGWO: Grey wolf optimizer for fusion cell-like P systems.

The grey wolf optimizer is a widely used parametric optimization algorithm. It is affected by the structure and rank of grey wolves and is prone to falling into the local optimum. In this study, we propose a grey wolf optimizer for fusion cell-like P systems. Cell-like P systems can parallelize computation and communicate from cell membrane to cell membrane, which can help the grey wolf optimizer jump out of the local optimum. Design new convergence factors and use different convergence factors in other cell membranes to balance the overall exploration and utilization capabilities of the algorithm. At the same time, dynamic weights are introduced to accelerate the convergence speed of the algorithm. Experiments are performed on 24 test functions to verify their global optimization performance. Meanwhile, a support vector machine model optimized by the grey wolf optimizer for fusion cell-like P systems has been developed and tested on six benchmark datasets. Finally, the optimizing ability of grey wolf optimizer for fusion cell-like P systems on constrained optimization problems is verified on three real engineering design problems. Compared with other algorithms, grey wolf optimizer for fusion cell-like P systems obtains higher accuracy and faster convergence speed on the test function, and at the same time, it can find a better parameter set stably for the optimization of support vector machine parameters, in addition to being more competitive on constrained engineering design problems. The results show that grey wolf optimizer for fusion cell-like P systems improves the searching ability of the population, has a better ability to jump out of the local optimum, has a faster convergence speed, and has better stability.

Based on machine learning, CDC20 has been identified as a biomarker for postoperative recurrence and progression in stage I & II lung adenocarcinoma patients.

Objective: By utilizing machine learning, we can identify genes that are associated with recurrence, invasion, and tumor stemness, thus uncovering new therapeutic targets. Methods: To begin, we obtained a gene set related to recurrence and invasion from the GEO database, a comprehensive gene expression database. We then employed the Weighted Gene Co-expression Network Analysis (WGCNA) to identify core gene modules and perform functional enrichment analysis on them. Next, we utilized the random forest and random survival forest algorithms to calculate the genes within the key modules, resulting in the identification of three crucial genes. Subsequently, one of these key genes was selected for prognosis analysis and potential drug screening using the Kaplan-Meier tool. Finally, in order to examine the role of CDC20 in lung adenocarcinoma (LUAD), we conducted a variety of in vitro and in vivo experiments, including wound healing assay, colony formation assays, Transwell migration assays, flow cytometric cell cycle analysis, western blotting, and a mouse tumor model experiment. Results: First, we collected a total of 279 samples from two datasets, GSE166722 and GSE31210, to identify 91 differentially expressed genes associated with recurrence, invasion, and stemness in lung adenocarcinoma. Functional enrichment analysis revealed that these key gene clusters were primarily involved in microtubule binding, spindle, chromosomal region, organelle fission, and nuclear division. Next, using machine learning, we identified and validated three hub genes (CDC45, CDC20, TPX2), with CDC20 showing the highest correlation with tumor stemness and limited previous research. Furthermore, we found a close association between CDC20 and clinical pathological features, poor overall survival (OS), progression-free interval (PFI), progression-free survival (PFS), and adverse prognosis in lung adenocarcinoma patients. Lastly, our functional research demonstrated that knocking down CDC20 could inhibit cancer cell migration, invasion, proliferation, cell cycle progression, and tumor growth possibly through the MAPK signaling pathway. Conclusion: CDC20 has emerged as a novel biomarker for monitoring treatment response, recurrence, and disease progression in patients with lung adenocarcinoma. Due to its significance, further research studying CDC20 as a potential therapeutic target is warranted. Investigating the role of CDC20 could lead to valuable insights for developing new treatments and improving patient outcomes.

Predicting lymphovascular invasion in N0 stage non-small cell lung cancer: A nomogram based on Dual-energy CT imaging and clinical findings.

PURPOSE: To construct a nomogram for predicting lymphovascular invasion (LVI) in N0 stage non-small cell lung cancer (NSCLC) using dual-energy computed tomography (DECT) findings combined with clinical findings. METHODS: We retrospectively recruited 135 patients with N0 stage NSCLC from two hospitals underwent DECT before surgery and were divided into development cohort (n = 107) and validation cohort (n = 28). The clinical findings (baseline characteristics, biochemical markers, serum tumor markers and Immunohistochemical markers), DECT-derived parameters (iodine concentration [IC], effective atomic number [Eff-Z] and normalized iodine concentration [NIC], iodine enhancement [IE] and NIC ratio [NICr]) and Fractal dimension (FD) were collected and measured. A nomogram was constructed using significant findings to predict LVI in N0 stage NSCLC and was externally validated. RESULTS: Multivariable analysis revealed that lymphocyte count (LYMPH, odds ratio [OR]: 3.71, P=0.014), IC in arterial phase (ICa, OR: 1.25, P=0.021), NIC in venous phase (NICv, OR: 587.12, P=0.009) and FD (OR: 0.01, P=0.033) were independent significant factors for predicting LVI in N0 stage NSCLC, and were used to construct a nomogram. The nomogram exhibited robust predictive capabilities in both the development and validation cohort, with AUCs of 0.819 (95 % CI: 72.6-90.4) and 0.844 (95 % CI: 68.2-95.8), respectively. The calibration plots showed excellent agreement between the predicted probabilities and the actual rates of positive LVI, on external validation. CONCLUSIONS: Combination of clinical and DECT imaging findings could aid in predicting LVI in N0 stage NSCLC using significant findings of LYMPH, ICa, NICv and FD.

High-Sensitive Uncooled Mid-Wave Infrared Detector Based on TiS3 Nanoribbon.

High-sensitive uncooled mid-wave infrared (MWIR) photodetection with fast speed is highly desired for biomedical imaging, optical communication, and night vision technology. Low-dimensional materials with low dark current and broadband photoresponse hold great promise for use in MWIR detection. Here, this study reports a high-performance MWIR photodetector based on a titanium trisulfide (TiS3) nanoribbon. This device demonstrates an ultra-broadband photoresponse ranging from the visible spectrum to the MWIR spectrum (405-4275 nm). In the MWIR spectral range, the photodetector achieves competitive high photoresponsivity (R) of 21.1 A W-1, and an impressive specific detectivity (D*) of 5.9 × 1010 cmHz1/2 W-1 in ambient air. Remarkably, the photoresponse speed in the MWIR with τr = 1.3 ms and τd = 1.5 ms is realized which is much faster than the thermal time constant of 15 ms. These findings pave the way for highly sensitive, room-temperature MWIR photodetectors with exceptionally fast response speed.

Nomogram of magnetic resonance imaging (MRI) histogram analysis to predict telomerase reverse transcriptase promoter mutation status in glioblastoma.

Background: Telomerase reverse transcriptase promoter (pTERT) status is a strong biomarker to diagnose and predict the prognosis of glioblastoma (GBM). In this study, we explored the predictive value of preoperative magnetic resonance imaging (MRI) histogram analysis in the form of nomogram for evaluating pTERT mutation status in GBM. Methods: The clinical and imaging data of 181 patients with GBM at our hospital between November 2018 and April 2023 were retrospectively assessed. We used the molecular sequencing results to classify the datasets into pTERT mutations (C228T and C250T) and pTERT-wildtype groups. FireVoxel software was used to extract preoperative T1-weighted contrast-enhanced (T1C) histogram parameters of GBM patients. The T1C histogram parameters were compared between groups. Univariate and multivariate logistic regression analyses were used to construct the nomogram, and the predictive efficacy of model was evaluated using calibration and decision curves. Receiver operating characteristic curve was used to assess model performance. Results: Patient age and percentage of unenhanced tumor area showed statistically significant differences between the pTERT mutation and pTERT-wildtype groups (P<0.001). Among the T1C histogram features, the maximum, standard deviation (SD), variance, coefficient of variation (CV), skewness, 5th, 10th, 25th, 95th and 99th percentiles were statistically significantly different between groups (P=0.000-0.040). Multivariate logistic regression analysis showed that age, percentage of unenhanced tumor area, SD and CV were independent risk factors for predicting pTERT mutation status in GBM patients. The logistic regression model based on these four features showed a better sample predictive performance, and the area under the curve (AUC) [95% confidence interval (CI)], accuracy, sensitivity, specificity were 0.842 (0.767-0.917), 0.796, 0.820, and 0.729, respectively. There were no significant differences in the T1C histogram parameters between the C228T and C250T groups (P=0.055-0.854). Conclusions: T1C histogram parameters can be used to evaluate pTERT mutations status in GBM. A nomogram based on conventional MRI features and T1C histogram parameters is a reliable tool for the pTERT mutation status, allowing for non-invasive radiological prediction before surgery.

Predicting the 28-day prognosis of acute-on-chronic liver failure patients based on machine learning.

BACKGROUND: We aimed to establish a prognostic predictive model based on machine learning (ML) methods to predict the 28-day mortality of acute-on-chronic liver failure (ACLF) patients, and to evaluate treatment effectiveness. METHODS: ACLF patients from six tertiary hospitals were included for analysis. Features for ML models' development were selected by LASSO regression. Models' performance was evaluated by area under the curve (AUC) and accuracy. Shapley additive explanation was used to explain the ML model. RESULTS: Of the 736 included patients, 587 were assigned to a training set and 149 to an external validation set. Features selected included age, hepatic encephalopathy, total bilirubin, PTA, and creatinine. The eXtreme Gradient Boosting (XGB) model outperformed other ML models in the prognostic prediction of ACLF patients, with the highest AUC and accuracy. Delong's test demonstrated that the XGB model outperformed Child-Pugh score, MELD score, CLIF-SOFA, CLIF-C OF, and CLIF-C ACLF. Sequential assessments at baseline, day 3, day 7, and day 14 improved the predictive performance of the XGB-ML model and can help clinicians evaluate the effectiveness of medical treatment. CONCLUSIONS: We established an XGB-ML model to predict the 28-day mortality of ACLF patients as well as to evaluate the treatment effectiveness.

Liensinine inhibits IL-1ß-stimulated inflammatory response in chondrocytes and attenuates papain-induced osteoarthritis in rats.

Osteoarthritis (OA) is a joint disease caused by inflammation of cartilage and synovial tissue. Suppressing the process of inflammatory reaction and the generation of oxidative stress is an effective strategy to alleviate the progression of OA. Liensinine is one of the main components of lotus seeds, which has anti-hypertensive and anti-arrhythmia activities. In this study, we aimed to determine the anti-inflammatory effect of liensinine in an OA. Here, we found that liensinine significantly inhibited the inflammatory response of SW1353 cells and primary chondrocytes by inhibiting the release of inflammatory cytokines and oxidative stress. Moreover, we showed that liensinine was able to inhibit the activation of the NF-κB signaling pathway in IL-1ß-induced SW1353 cells. Lastly, we found that liensinine significantly ameliorated cartilage damage and inflammatory response in papain-induced rats. Our study demonstrated a significant protective effect of liensinine against OA, which might be by inhibiting the activation of the NF-κB signaling pathway, and provide a new insight for the treatment of OA using liensinine.

Emission characteristics of lead and particulate matter from lead and zinc smelters in China.

Understanding the emission characteristics of particulate matter and associated heavy metals is essential for assessing their environmental and health impacts post-emission, as well as for identifying potential control technologies for the sources. Here, a field test was conducted at two advanced smelting plants equipped with comprehensive air pollution control devices. The particles emitted from different stages of lead and zinc smelting exhibited bi-modal size distributions, with peaks observed in PM0.1-1.0 and PM2.5-10, respectively. Particulate-bound Pb was identified as the predominant Pb species in the flue gas, primarily originating from ore crushing. Consequently, over 80 % of Pb was emitted in the form of coarse particles, a marked contrast to coal-fired power plants where Pb concentrated on fine particles. High efficiencies in Pb removal were achieved by dust collectors, flue gas purification systems, and acid plants with desulfurization systems, resulting in overall Pb emission factors in lead and zinc smelting were only 89.3 and 2.60 g t-1 (of metal production), respectively. Importantly, the contribution of gas-phase Pb, which accounts for approximately 16.6 % of total emissions, must not be neglected in future emission monitoring and control efforts.

Effects of dietary salidroside on intestinal health, immune parameters and intestinal microbiota in largemouth bass (Micropterus salmoides).

The largemouth bass has become one of the economically fish in China, according to the latest China Fishery Statistical Yearbook. The farming scale is constantly increasing. Salidroside has been found in past studies to have oxidative stress reducing and immune boosting properties. In this study, the addition of six different levels of salidroside supplements were 0、40、80、120、160 and 200 mg/kg. A 56-day feeding trial was conducted to investigate the effects of salidroside on the intestinal health, immune parameters and intestinal microbiota composition of largemouth bass. Dietary addition of salidroside significantly affected the Keap-1ß/Nrf-2 pathway as well as significantly increased antioxidant enzyme activities resulting in a significant increase in antioxidant capacity of largemouth bass. Dietary SLR significantly reduced feed coefficients. The genes related to tight junction proteins (Occludin, ZO-1, Claudin-4, Claudin-5) were found to be significantly upregulated in the diet supplemented with salidroside, indicating that salidroside can improve the intestinal barrier function (p < 0.05). The dietary administration of salidroside was found to significantly reduce the transcription levels of intestinal tumor necrosis factor-α (TNF-α) and interleukin-1ß (IL-1ß) (p < 0.05). Furthermore, salidroside was observed to reduce the transcription levels of intestinal apoptosis factor Bcl-2 associated death promoter (BAD) and recombinant Tumor Protein p53 (P53) (p < 0.05). Concomitantly, the beneficial bacteria, Fusobacteriota and Cetobacterium, was significantly increased in the SLR12 group, while that of pathogenic bacteria, Proteobacteria, was significantly decreased (p < 0.05). In conclusion, the medium-sized largemouth bass optimal dosage of salidroside in the diet is 120mg/kg-1.

A strategy to reconstitute immunity without GVHD via adoptive allogeneic Tscm therapy.

Introduction: Adoption of allogeneic T cells directly supplements the number of T cells and rapidly induces T-cell immunity, which has good efficacy for treating some tumors and immunodeficiency diseases. However, poor adoptive T-cell engraftment and graft-versus-host disease (GVHD) limit the application of these methods. Alloreactive T-cell clones were eliminated from the donor T-cell repertoire, and the remaining T-cell clones were prepared as Tscm for T-cell adoptive treatment to reconstruct recipient T-cell immunity without GVHD. Methods: The subjects in this study included three different strains of mice. Lymphocytes from mice (C57BL/6) were used as the donor T-cell repertoire, from which the Tscm allo-reactive T cell clone was depleted (ATD-Tscm). This was confirmed by showing that the Tscm was not responsive to the alloantigen of the recipient (BALB/c). To prepare ATD-Tscm cells, we used recipient lymphocytes as a simulator, and coculture of mouse and recipient lymphocytes was carried out for 7 days. Sorting of non-proliferative cells ensured that the prepared Tscm cells were nonresponsive. The sorted lymphocytes underwent further expansion by treatment with TWS119 and cytokines for an additional 10 days, after which the number of ATD-Tscm cells increased. The prepared Tscm cells were transferred into recipient mice to observe immune reconstitution and GVHD incidence. Results: Our protocol began with the use of 1×107 donor lymphocytes and resulted in 1 ×107 ATD-Tscm cells after 17 days of preparation. The prepared ATD-Tscm cells exhibited a nonresponse upon restimulation of the recipient lymphocytes. Importantly, the prepared ATD-Tscm cells were able to bind long and reconstitute other T-cell subsets in vivo, effectively recognizing and answering the "foreign" antigen without causing GVHD after they were transferred into the recipients. Discussion: Our strategy was succeeded to prepare ATD-Tscm cells from the donor T-cell repertoire. The prepared ATD-Tscm cells were able to reconstitute the immune system and prevent GVHD after transferred to the recipients. This study provides a good reference for generating ATD-Tscm for T-cell adoptive immunotherapy.

Cross-Anatomy Transfer Learning via Shape- Aware Adaptive Fine-Tuning for 3D Vessel Segmentation.

Deep learning methods have recently achieved remarkable performance in vessel segmentation applications, yet require numerous labor-intensive labeled data. To alleviate the requirement of manual annotation, transfer learning methods can potentially be used to acquire the related knowledge of tubular structures from public large-scale labeled vessel datasets for target vessel segmentation in other anatomic sites of the human body. However, the cross-anatomy domain shift is a challenging task due to the formidable discrepancy among various vessel structures in different anatomies, resulting in the limited performance of transfer learning. Therefore, we propose a cross-anatomy transfer learning framework for 3D vessel segmentation, which first generates a pre-trained model on a public hepatic vessel dataset and then adaptively fine-tunes our target segmentation network initialized from the model for segmentation of other anatomic vessels. In the framework, the adaptive fine-tuning strategy is presented to dynamically decide on the frozen or fine-tuned filters of the target network for each input sample with a proxy network. Moreover, we develop a Gaussian-based signed distance map that explicitly encodes vessel-specific shape context. The prediction of the map is added as an auxiliary task in the segmentation network to capture geometry-aware knowledge in the fine-tuning. We demonstrate the effectiveness of our method through extensive experiments on two small-scale datasets of coronary artery and brain vessel. The results indicate the proposed method effectively overcomes the discrepancy of cross-anatomy domain shift to achieve accurate vessel segmentation for these two datasets.

A bibliometric analysis of immune-related adverse events in cancer patients and a meta-analysis of immune-related adverse events in patients with hepatocellular carcinoma.

Background and Objectives: Immunotherapy has become the standard treatment for hepatocellular carcinoma (HCC), but it carries a risk of immune-related adverse events (irAEs) that can be life-threatening. This study employs bibliometric analysis to understand global scientific research on irAEs in cancer, focusing on characteristics and areas of interest. Additionally, a meta-analysis provides a comprehensive overview of irAEs in HCC patients receiving immune checkpoint inhibitor (ICI)-based therapies. Methods: We conducted a thorough search of Web of Science Core Collection (WoSCC) publications from 1999 to 2022. R and VOSviewer software were used for analysis. A meta-analysis was performed using data from PubMed, Embase, and the Cochrane Library databases up to March 22, 2022. Trials with HCC patients reporting irAE incidence were included. Quality assessment followed Cochrane risk of bias, Newcastle-Ottawa Scale (NOS), and Methodological Index for Non-Randomized Studies (MINORS). We used random-effects or fixed-effects models based on I2 values. Primary outcomes included any-grade irAEs and grade ≥ 3 irAEs. This review and meta-analysis are registered in PROSPERO as CRD42022318885. Results: In bibliometric analysis, we included 2946 papers, showing a consistent rise in annual publications on irAEs in cancer research. Frequent keywords were "nivolumab", "immune checkpoint inhibitor", and "immune-related adverse event". "Hepatocellular carcinoma" emerged as a prominent research focus linked to irAEs. We conducted a comprehensive meta-analysis on irAE incidence in HCC patients, including 29 studies. The overall incidence of any-grade irAEs was 61.0% (95% CI 38.5%-81.3%), and grade ≥ 3 irAEs was 13.2% (95% CI 7.9%-19.6%). Treatment-related mortality occurred in 3.1% (95% CI 0.8%-6.3%), with treatment discontinuation at 10.7% (95% CI 6.3%-16.0%). Reactive cutaneous capillary endothelial proliferation (RCCEP) was the most common any-grade irAE, while elevated aspartate aminotransferase (AST) was the most common grade ≥ 3 irAE. Treatment strategies were independently associated with specific irAEs, as indicated by multivariable analysis. Conclusion: This study provides valuable insights into the current research landscape of irAEs in cancer and ofers a comprehensive overview of irAEs in HCC patients undergoing ICI-based therapy. The relatively high incidence of irAEs and their association with treatment strategies emphasize the need for careful management by clinicians when treating HCC patients. These findings offer significant guidance for optimizing care and treatment for HCC patients.

2,5-Dihydroxyacetophenone attenuates acute kidney injury induced by intra-abdominal infection in rats.

AIMS: As one of the most serious complications of sepsis, acute kidney injury (AKI) is pathologically associated with excessive inflammation. 2,5-Dihydroxyacetophenone (DHAP) is isolated from Radix rehmanniae praeparata and exhibit potent anti-inflammatory property. This research aimed at determining the role of DHAP in sepsis-associated AKI (SA-AKI) and the underlying mechanism. METHODS: Plasma creatinine (Cre), blood urea nitrogen (BUN), tumour necrosis factor-α (TNF-α) and interleukin-1ß (IL-1ß) levels of SA-AKI patients were detected to evaluate their clinical characteristics. SA-AKI rat models were established by using caecum ligation puncture (CLP) surgery. CLP-induced rats were administered via oral gavage with 20 or 40 mg DHAP after 2 h of CLP surgery. Subsequently, survival rates, serum indexes, histopathological changes, inflammatory factors, renal function indexes and extracellular regulated protein kinases (ERK) and nuclear factor-κB (NF-κB) signalling pathways were detected. RESULTS: SA-AKI patients exhibited markedly higher levels of plasma Cre, BUN, TNF-α and IL-1ß than healthy people. Compared with sham rats, CLP-induced septic rats showed significantly decreased survival rate, increased serum lactate dehydrogenase activity and serum lactate level, obvious renal histopathological injury, upregulated TNF-α, IL-1ß and TGF-ß1 levels, elevated serum creatinine, BUN and serum cystatin C concentrations, serum neutrophil gelatinase-associated lipocalin and kidney injury molecule-1 levels and reduced renal artery blood flow. All the above CLP-induced changes in septic rats were mitigated after DHAP administration. Additionally, CLP-induced elevation in phosphorylated-ERK1/2 and nuclear NF-κB p65 protein levels was inhibited by DHAP treatment. CONCLUSION: DHAP hinders SA-AKI progression in rat models by inhibiting ERK and NF-κB signalling pathways.

Association between Pericoronary Fat Attenuation Index Values and Plaque Composition Volume Fraction Measured by Coronary Computed Tomography Angiography.

RATIONALE AND OBJECTIVES: The pericoronary fat attenuation index (FAI) values around plaques may reveal the relationship between periplaque vascular inflammation and different plaque component volume fractions. We aimed to evaluate the potential associations between periplaque FAI values and plaque component volume fractions. MATERIALS AND METHODS: 496 patients (1078 lesions) with coronary artery disease, who underwent computed tomography angiography (CCTA) between September 2022 and August 2023, were analyzed retrospectively. Each lesion was characterized and the plaque component volume fractions and periplaque FAI values were measured. Multiple linear regression, weighted quantile sum (WQS) regression, and quantile g-computation (Qgcomp) were used to explore the relationship between plaque component volume fractions and the risk of elevated periplaque FAI values. RESULTS: After adjusting for clinical characteristics, multiple linear regression identified that lipid components volume fraction (ß = 0.162, P < 0.001) were independent risk factors for elevated periplaque FAI values whereas calcified components volume fraction (ß = -0.066, P = 0.025) were independent protective factors. The WQS regression models indicated an increase in the overall confounding effect of the adjusted lipid indices and plaque composition volume fraction on the risk of elevated periplaque FAI values (P = 0.004). Qgcomp analysis indicated lipid component volume fraction and calcified component volume fraction was positively and negatively correlated with elevated plaque FAI values, respectively (all P < 0.05). CONCLUSIONS: Periplaque FAI values quantified by CCTA were strongly correlated with lipid and calcification component volume fractions.