Rapid in-situ calibration of computational micro-spectrometer with few-shot meta-learning.

Computational micro-spectrometers comprised of detector arrays and encoding structure arrays, such as on-chip Fabry-Perot (FP) cavity filters, have great potential in many in-situ applications owing to their compact size and snapshot imaging ability. Given manufacturing deviation and environmental influence are inevitable, easy and effective calibration for spectrometer is necessary, especially for in-situ applications. Currently calibration strategies based on iterative algorithms or neural networks require accurate measurements of pixel-level (spectral) encoding functions through monochromator or large amounts of standard samples. These procedures are time-consuming and expensive, thereby impeding in-situ applications. Meta-learning algorithms with few-shot learning ability can address this challenge by incorporating the prior knowledge in the simulated dataset. In this work, we propose a meta-learning algorithm free of measuring encoding function or large amounts of standard samples to calibrate a micro-spectrometer with manufacturing deviation effectively. Our micro-spectrometer comprises 16 types of FP filters covering a wavelength range of 550-720 nm. The center wavelength of each filter type deviates from the design up to 6 nm. After calibration with 15 different color data, the average reconstruction error on the test dataset decreased from 7.2 × 10-3 to 1.2 × 10-3, and further decreased to 9.4 × 10-4 when the calibration data increased to 24. The performance is comparable to algorithms trained with measured encoding function both in reconstruction error and generalization ability. We estimated that the cost of in-situ calibration through reflectance measurements of color chart decreased to one percent of the cost through monochromator measurements. By exploiting prior deviation information in simulation data with meta-learning, the efficiency and cost of calibration are significantly improved, thereby facilitating the large-scale production and in-situ application of micro-spectrometers.

Pathogenic spectrum and drug resistance of bloodstream infection in patients with acute myeloid leukaemia: a single centre retrospective study.

Background: Bloodstream infection (BSI) represent a prevalent complication in haematological malignancies (HMs). Typically, Patients with BSI usually undergo empirical treatment pending pathogen identification. The timely and effective management of BSIs significantly influences patient prognosis. However, pathogen distribution in BSIs exhibits regional variation. In this study, we investigated the clinical characteristics, pathogen spectrum, drug resistance, risk factors of short-term prognosis and long-term prognostic factors of acute myeloid leukemia (AML) patients with BSI at Zhejiang Provincal People's Hospital. Methods: From 2019 to 2021, a total of 56 AML patients with BSI were treated in the Department of Haematology at Zhejiang Province People's Hospital. Data regarding pathogen spectrum and drug resistance were collected for analysis. The patients were stratified into non-survivor cohort and survivor cohort within 30 days after BSI, and the predictors of 30-days mortality were identified through both univariate and multivariate Logistic regression analyses. Furthermore, Kaplan-Meier survival analysis and Cox regression analysis were employed to ascertain the risk factors associated with poor prognosis in AML patients complicated by BSI. Results: A total of 70 strains of pathogenic bacteria were isolated from 56 AML patients with BSI. Gram-negative bacteria constituted the predominant pathogens (71.4%), with Klebsiella pneumoniae being the most prevalent (22.9%). Gram-positive bacteria and fungi accounted for 22.9% and 5.7%, respectively. Univariate and multivariate analyses revealed significant differences in total protein, albumin levels, and the presence of septic shock between the non-survivor cohort and the survior cohort 30 days post-BSI. COX regression analysis showed that agranulocytosis duration exceeding 20 days (HR:3.854; 95% CI: 1.451-10.242) and septic shock (HR:3.788; 95% CI: 1.729-8.299) were independent risk factors for poor prognosis in AML patients complicated by BSI. Notably, the mortality rate within 30 days after Stenotrophomonas maltophilia infection was up to 71.4%. Conclusions: In this study, Gram-negative bacteria, predominantly Klebsiella pneumoniae, constituted the primary pathogens among AML patients with BSIs. Serum albumin levels and the presence of septic shock emerged as independent risk factors for mortality within 30 days among AML patients with BSI. In terms of long-term prognosis, extended agranulocytosis duration exceeding 20 days and septic shock were associated with elevated mortality rates in AML patients with BSI. Additionally, in our centre, Stenotrophomonas maltophilia infection was found to be associated with a poor prognosis. Early intervention for Stenotrophomonas maltophilia infection in our centre could potentially improve patient outcomes.

A novel repair strategy using knotless squeeze anchors for lumbar disc herniation with endplate junction lesions under biportal endoscopic spinal surgery.

BACKGROUND: Annulus fibrosus-endplate (AF-EP) junction lesions are important determinants for lumbar disc herniation (LDH). Utilizing biportal endoscopic spinal surgery (BESS), we introduce a novel repair method using bioabsorbable PushLock anchors with suture fibers to stretch disconnected AF tissues to the vertebral cortex. METHODS: The viewing and working portals are established to excise herniated disc materials causing radiculopathy. Through the working portal, a suture strand is passed through the intact AF tissue near the lesion and retrieved using the Suture Crossing Device. Then, the knotless suture limbs are secured into the cortical bone socket of the vertebral body with a PushLock anchor. CONCLUSION: The procedure is a simple, safe, and feasible knotless suturing technique for the treatment of LDH with AF-EP junction lesions.

Study on the Influence of Label Image Accuracy on the Performance of Concrete Crack Segmentation Network Models.

A high-quality dataset is a basic requirement to ensure the training quality and prediction accuracy of a deep learning network model (DLNM). To explore the influence of label image accuracy on the performance of a concrete crack segmentation network model in a semantic segmentation dataset, this study uses three labelling strategies, namely pixel-level fine labelling, outer contour widening labelling and topological structure widening labelling, respectively, to generate crack label images and construct three sets of crack semantic segmentation datasets with different accuracy. Four semantic segmentation network models (SSNMs), U-Net, High-Resolution Net (HRNet)V2, Pyramid Scene Parsing Network (PSPNet) and DeepLabV3+, were used for learning and training. The results show that the datasets constructed from the crack label images with pix-el-level fine labelling are more conducive to improving the accuracy of the network model for crack image segmentation. The U-Net had the best performance among the four SSNMs. The Mean Intersection over Union (MIoU), Mean Pixel Accuracy (MPA) and Accuracy reached 85.47%, 90.86% and 98.66%, respectively. The average difference between the quantized width of the crack image segmentation obtained by U-Net and the real crack width was 0.734 pixels, the maximum difference was 1.997 pixels, and the minimum difference was 0.141 pixels. Therefore, to improve the segmentation accuracy of crack images, the pixel-level fine labelling strategy and U-Net are the best choices.

Magnetic resonance imaging with upconversion nanoprobes capable of crossing the blood-cerebrospinal fluid barrier.

The central nervous system (CNS) maintains homeostasis with its surrounding environment by restricting the ingress of large hydrophilic molecules, immune cells, pathogens, and other external harmful substances to the brain. This function relies heavily on the blood-cerebrospinal fluid (B-CSF) and blood-brain barrier (BBB). Although considerable research has examined the structure and function of the BBB, the B-CSF barrier has received little attention. Therapies for disorders associated with the central nervous system have the potential to benefit from targeting the B-CSF barrier to enhance medication penetration into the brain. In this study, we synthesized a nanoprobe ANG-PEG-UCNP capable of crossing the B-CSF barrier with high targeting specificity using a hydrocephalus model for noninvasive magnetic resonance ventriculography to understand the mechanism by which the CSF barrier may be crossed and identify therapeutic targets of CNS diseases. This magnetic resonance nanoprobe ANG-PEG-UCNP holds promising potential as a safe and effective means for accurately defining the ventricular anatomy and correctly locating sites of CSF obstruction.

A novel missense COL9A3 variant in a pedigree with multiple lumbar disc herniation.

Trp3 allele in COL9A3 gene has been widely studied in populations with intervertebral disc disease. We identified a novel pathogenic variant in COL9A3 gene in a pedigree with multiple lumbar disc herniation (LDH). The proband was a 14-year-old boy who developed LDH at the L4/5 and L5/S1 spinal segments. His father, paternal aunt and grandfather were diagnosed with LDH at an age of 35, 30 and 23, respectively. By applying whole exome sequencing, a heterozygous missense variant (c.1150C > T, p.Arg384Trp) in COL9A3 was identified. According to the ACMG guidelines, this variant is predicted to be pathogenic. In addition, prediction tools found COL9A3 protein of this variant a reduced stability, some changed charge properties, and an altered spatial conformation. Findings expanded the mutational spectrum of LDH and contributed to the understanding of COL9A3 in the pathogenesis of LDH.

Unilateral Biportal Endoscopic Posterior Cervical Foraminotomy: An Outcome Comparison With the Full-endoscopic Posterior Cervical Foraminotomy.

STUDY DESIGN: Retrospective control study. OBJECTIVE: To compare the curative effects of unilateral biportal endoscopic posterior cervical foraminotomy (UBE-PCF) with full-endoscopic posterior cervical foraminotomy (FPCF). SUMMARY OF BACKGROUND DATA: There are few studies directly comparing outcomes between UBE-PCF and FPCF. The objective of this study was to compare outcomes between UBE-PCF and FPCF. METHODS: A retrospective control study was conducted for 69 patients of cervical radiculopathy from July 2019 to December 2021. Clinical outcomes scores, including neck disability index, visual analog scale (VAS)-arm, and VAS-neck were evaluated. Serum creatine kinase levels and the size of the operating hole were measured. RESULTS: Postoperative neck disability index, VAS-neck, and VAS-arm scores showed statistically significant improvement over preoperative scores ( P <0.01). The operating time was significantly shorter in the UBE-PCF group ( P <0.001). No significant differences were found in serum creatine kinase levels between the 2 groups ( P >0.05). The mean area of the operating hole was 1.47+0.05 cm 2 in the FPCF group and 1.79+0.11 cm 2 in the UBE-PCF group. The difference was statistically significant ( P <0.001). CONCLUSIONS: Both UBE-PCF and FPCF are safe and effective procedures for cervical radiculopathy. Predictable and sufficient decompression could be achieved by UBE-PCF in a shorter operation time. LEVEL OF EVIDENCE: Treatment Benefits Level III.

Comparison of Intraoperative Endplate Injury between Mini-Open Lateral Lumbar Interbody Fusion (LLIF) and Transforaminal Lumbar Interbody Fusion (TLIF) and Analysis of Risk Factors: A Retrospective Study.

OBJECTIVE: The study aimed to compare the incidence of intraoperative endplate injury in patients who underwent Transforaminal interbody fusion (TLIF) and mini-open lumbar interbody fusion (LLIF) surgery. The independent risk factors related to endplate injury in LLIF procedure were analyzed. METHODS: A total of 199 patients who underwent LLIF (n = 106) or TLIF (n = 93) surgery from June 2019 to September 2021 were reviewed. The endplate injury was assessed by postoperative sagittal CT scan. A binary logistic analysis model were used to identify independent risk factors related to LLIF endplate injury based on univariate analysis. RESULTS: There was an obvious difference in the occurrence of intraoperative endplate injury between LLIF (42/106, 39.6%) and TLIF group (26/93, 28%), although it did not reach the significant level. L1 CT value (OR = 0.985, 95% CI = 0.972-0.998), cage position (OR = 3.881, 95% CI = 1.398-10.771) and height variance (OR = 1.263, 95% CI = 1.013-1.575) were independent risk factors for endplate injury in LLIF procedure. According to the cage settlement patterns, there 5 types of A to E. The severity of the facet joint degeneration was positively related to the occurrence of endplate injury. CONCLUSIONS: The incidence of intraoperative endplate injury is higher in LLIF than in TLIF procedures. Low bone quantity, cage posterior position and larger height variance are risk factors to induce endplate injury in LLIF surgery. The facet joint degeneration may be related to severe endplate injuries and even fractures.

Identification of potential drug targets for rheumatoid arthritis from genetic insights: a Mendelian randomization study.

INTRODUCTION: Rheumatoid arthritis (RA) is a chronic inflammatory illness that mostly affects the joints of the hands and feet and can reduce life expectancy by an average of 3 to 10 years. Although tremendous progress has been achieved in the treatment of RA, a large minority of patients continue to respond poorly to existing medications, owing in part to a lack of appropriate therapeutic targets. METHODS: To find therapeutic targets for RA, a Mendelian randomization (MR) was performed. Cis-expression quantitative trait loci (cis-eQTL, exposure) data were obtained from the eQTLGen Consortium (sample size 31,684). Summary statistics for RA (outcome) were obtained from two largest independent cohorts: sample sizes of 97,173 (22,350 cases and 74,823 controls) and 269,377 (8279 cases and 261,098), respectively. Colocalisation analysis was used to test whether RA risk and gene expression were driven by common SNPs. Drug prediction and molecular docking was further used to validate the medicinal value of drug targets. RESULTS: Seven drug targets were significant in both cohorts in MR analysis and supported by localization. PheWAS at the gene level showed only ATP2A1 associated with other traits. These genes are strongly associated with immune function in terms of biological significance. Molecular docking showed excellent binding for drugs and proteins with available structural data. CONCLUSION: This study identifies seven potential drug targets for RA. Drugs designed to target these genes have a higher chance of success in clinical trials and is expected to help prioritise RA drug development and save on drug development costs.

Research on the Efficiency of Bridge Crack Detection by Coupling Deep Learning Frameworks with Convolutional Neural Networks.

Bridge crack detection based on deep learning is a research area of great interest and difficulty in the field of bridge health detection. This study aimed to investigate the effectiveness of coupling a deep learning framework (DLF) with a convolutional neural network (CNN) for bridge crack detection. A dataset consisting of 2068 bridge crack images was randomly split into training, verification, and testing sets with a ratio of 8:1:1, respectively. Several CNN models, including Faster R-CNN, Single Shot MultiBox Detector (SSD), You Only Look Once (YOLO)-v5(x), U-Net, and Pyramid Scene Parsing Network (PSPNet), were used to conduct experiments using the PyTorch, TensorFlow2, and Keras frameworks. The experimental results show that the Harmonic Mean (F1) values of the detection results of the Faster R-CNN and SSD models under the Keras framework are relatively large (0.76 and 0.67, respectively, in the object detection model). The YOLO-v5(x) model of the TensorFlow2 framework achieved the highest F1 value of 0.67. In semantic segmentation models, the U-Net model achieved the highest detection result accuracy (AC) value of 98.37% under the PyTorch framework. The PSPNet model achieved the highest AC value of 97.86% under the TensorFlow2 framework. These experimental results provide optimal coupling efficiency parameters of a DLF and CNN for bridge crack detection. A more accurate and efficient DLF and CNN model for bridge crack detection has been obtained, which has significant practical application value.

Discovery of acylated isoquercitrin derivatives as potent anti-neuroinflammatory agents in vitro and in vivo.

Neuroinflammation is considered as an important pathological mechanism in neurodegenerative diseases. The natural isoquercitrin (IQ) was reported to have potential anti-neuroinflammatory activity. The acylation of glycoside in IQ enhanced its hydrophobicity, which was expected to enhance the protective effect against inflammation. In this study, three carboxylic acids with anti-neuroinflammatory effects including cinnamic acid, ibuprofen (IBU) and acetylsalicylic acid were introduced into the 6''-OH of IQ through the corresponding vinyl esters intermediates (8a-8c). Ultimately, the acylated IQ derivatives (Compound 9a-9c) were obtained with 35-42% yields using immobilized lipase Novozym 435 as catalyst. Subsequently, their anti-neuroinflammatory activities were evaluated in lipopolysaccharide (LPS)-induced BV2 cells. Compound 9b improved cell viability in the range of ≤50 µM and significantly decreased NO, PGE2 production and TNF-α, IL-1ß release and oxidative stress level with a concentration-dependent manner. Also, it could downregulate iNOS, COX-2, TNF-α and IL-1ß expression levels, approximately 40% reduction were achieved when 15µM compound 9b was employed. In addition, compound 9b resisted phosphorylation and degradation of IkBαs, suppressing the activation of NF-κB signaling pathway, exhibiting excellent neuroinflammatory inhibition. Moreover, the administration of compound 9b (30, 60 mg/kg) alleviated behavioral disorders and neuronal damages in LPS-induced neuroinflammatory mice. Meanwhile, the decreased TNF-α, IL-1ß release, expression and the inhibited glial cells activation were obtained in compound 9b-treated group, which was superior to that of IQ or IBU. Overall, these findings demonstrated that compound 9b, formed by the introduction of ibuprofen into IQ, can serve as a novel promising therapeutic agent for anti-neuroinflammation.

Ferroptosis-Related Prognostic Gene LAMP2 Is a Potential Biomarker Differential Expressed in Castration Resistant Prostate Cancer.

Background: It remains unclear about the mechanisms of prostate cancer progressing to castration resistant prostate cancer (CRPC) and the correlation with ferroptosis. Methods: We compared the gene profiles between localized prostate cancer and metastatic CRPC using the GEO dataset and intersected with a cluster of known ferroptosis-related genes. We received differentially expressed genes (DEGs) in CRPC related to ferroptosis and performed survival analysis to analyze the prognostic values. Furthermore, we conducted single sample gene set enrichment analysis (ssGSEA) to analyze immune infiltration and investigate microRNA crosstalk and methylation for prognostic genes using online databases. Results: We identified 84 DEGs in CRPC related to ferroptosis and 19 hub genes densely connected into networks by enrichment analysis. We performed survival analysis and Cox regression for these genes and identified LAMP2 with significantly prognostic values in overall survival (OS) and disease-specific survival (DSS) of prostate cancer. Furthermore, we found immune infiltration of various immune cells significantly correlated with LAMP2 expression in prostate cancer and identified multiple microRNAs associated with LAMP2 expression in prostate cancer. In addition, we found that the methylation level of LAMP2 in prostate cancer was significantly associated with cancer and identified 8 methylation sites for LAMP2. Conclusion: Ferroptosis-related gene LAMP2 is a potential biomarker with prognostic value for prostate cancer.

Cancer/testis antigen HEMGN correlated with immune infiltration serves as a prognostic biomarker in lung adenocarcinoma.

HEMGN belongs to the Cancer/testis antigens (CTAs), which are expressed in various types of human cancers and have received particular attention in cancer immunotherapy. However, the potential function of HEMGN involved in lung cancer and the immune response is not yet elucidated. HEMGN expression in lung adenocarcinoma (LUAD) was estimated via the Tumor Immune Estimation Resource (TIMER), The Cancer Genome Atlas (TCGA), The University of Alabama at Birmingham Cancer data analysis Portal (UALCAN), and Human Protein Atlas databases. The prognostic role of HEMGN was investigated by Gene Expression Profiling Interactive Analysis (GEPIA), PrognoScan, and Kaplan-Meier plotter databases. The associations between HEMGN and clinicopathological parameters were analyzed with UALCAN database. Then, immunohistochemical and Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) analysis were performed to further verify the associations in tissue or serum samples. Serum from patients were detected for HEMGN antibody by enzyme-linked immunosorbent assay (ELISA). Flow cytometry was used to detect immune cell infiltration in peripheral blood of patients with LUAD. In addition, Gene Set Enrichment Analysis (GSEA) was conducted to investigate the functional role of HEMGN. Furthermore, we obtained the somatic mutation data from the TCGA LUAD dataset and analyzed the mutation profiles with "maftools" package. Finally, we evaluated the associations between HEMGN and immune infiltration level and the characteristic markers of immune cells in TIMER, GEPIA, and CIBERSORT. The mRNA and protein expressions of HEMGN were significantly decreased in LUAD patients. High HEMGN expression was remarkably associated with better prognosis in LUAD patients. The concentration levels of anti-HEMGN antibody in LUAD were significantly higher than that in healthy individuals and were closely correlated with clinical stage. In addition, HEMGN was involved in distinct typical genomic alterations in LUAD. GSEA demonstrated that HEMGN was significantly connected with immunity and substance metabolism. Notably, HEMGN was significantly related to immune infiltrates, including B cells, CD8 + T cells, CD4 + T cells, neutrophils, macrophages, dendritic cells (DCs), and various kinds of functional T cells. Furthermore, HEMGN had a significant association with diverse immune gene markers. HEMGN can be considered as a prognostic biomarker of LUAD and is associated with immune infiltration.

Antifungal susceptibility profiles and drug resistance mechanisms of clinical Candida duobushaemulonii isolates from China.

Candida duobushaemulonii, type II Candida haemulonii complex, is closely related to Candida auris and capable of causing invasive and non-invasive infections in humans. Eleven strains of C. duobushaemulonii were collected from China Hospital Invasive Fungal Surveillance Net (CHIF-NET) and identified using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF), VITEK 2 Yeast Identification Card (YST), and internal transcribed spacer (ITS) sequencing. Whole genome sequencing of C. duobushaemulonii was done to determine their genotypes. Furthermore, C. duobushaemulonii strains were tested by Sensititre YeastOne™ and Clinical and Laboratory Institute (CLSI) broth microdilution panel for antifungal susceptibility. Three C. duobushaemulonii could not be identified by VITEK 2. All 11 isolates had high minimum inhibitory concentrations (MICs) to amphotericin B more than 2 µg/ml. One isolate showed a high MIC value of ≥64 µg/ml to 5-flucytosine. All isolates were wild type (WT) for triazoles and echinocandins. FUR1 variation may result in C. duobushaemulonii with high MIC to 5-flucytosine. Candida duobushaemulonii mainly infects patients with weakened immunity, and the amphotericin B resistance of these isolates might represent a challenge to clinical treatment.

The ALFF Alterations of Spontaneous Pelvic Pain in the Patients of Chronic Prostatitis/Chronic Pelvic Pain Syndrome Evaluated by fMRI.

Chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS) is a challenging entity with complicated symptoms for treatment in the male crowd. Accumulating evidence revealed the dysfunction in the central system should be a critical factor for the pathogenesis and development in the CP/CPPS. Therefore, we recruited 20 patients of CP/CPPS and 20 healthy male volunteers, aged 20 to 50 years. Through resting-state functional magnetic resonance imaging (fMRI), we analyzed the mean amplitude of low-frequency fluctuations (mALFF) and the mean fractional amplitude of low-frequency fluctuations (mfALFF) to reflect the spontaneous abnormal activated regions in the brains of CP/CPPS patients. Compared to the healthy controls, the group with CP/CPPS had significantly increased mALFF values in the thalamus and augmented fALFF values in the inferior parietal lobule and cingulate gyrus. Significant positive correlations were observed in the extracted mALFF values in the midbrain periaqueductal gray matter (PAG) and the pain intensity (r = 0.2712, p = 0.0019), mALFF values in the thalamus and the scores of Hospital Anxiety and Depression Scale (HADS) anxiety subscale (r = 0.08477, p = 0.0461), and mfALFF values in the superior frontal gyrus (SFG) and the scores of the HADS anxiety subscale (r = 0.07102, p = 0.0282). Therefore, we delineated the clinical alterations in patients of CP/CPPS that might be attributed to the functional abnormality of the thalamus, inferior parietal lobule, and cingulate gyrus. Among these regions, the PAG, thalamus, and SFG may further play an important role in the pathogenesis, with their regulating effect on pain or emotion.

Stroke prevention of thoracoscopic left atrial appendage clipping in patients with non-valvular atrial fibrillation at high risk of stroke and bleeding: study protocol for a non-randomised controlled clinical trial.

INTRODUCTION: Non-valvular atrial fibrillation (NVAF) is a high-risk factor for ischaemic stroke. The 2016 European Society of Cardiology Atrial Fibrillation Management guidelines recommend oral anticoagulants (OACs) to prevent stroke in men with CHA2DS2-VASc scores ≥2 and women ≥3. However, in patients with a high risk of stroke and a high risk of bleeding (HAS-BLED (Hypertension, Abnormal renal/liver function, Stroke, Bleeding history or predisposition, Labile international normalized ratio, Elderly (> 65 years), Drugs/alcohol concomitantly) score≥3), OAC had a higher risk of bleeding. Left atrial appendage closure (LAAC) is non-inferior to OAC as a means of preventing stroke in several studies. As a minimally invasive intervention to prevent stroke, transthoracic LAAC (TS-LAAC) has a high successful closure rate, but there is a lack of literature reports directly comparing it with OAC. Our research compares TS-LAAC with novel oral anticoagulants (NOACs) and provides an appropriate programme for stroke prevention in a specific population. METHODS AND ANALYSIS: This is a non-randomised controlled trial study protocol, and we will conduct this study from April 2022 to April 2025. The study included 186 patients with confirmed NVAF, 93 of whom completed thoracoscopic LAAC, and the control group treated with NOACs. The primary outcome was the incidence of stroke and systemic embolism, as well as the composite endpoint events (stroke, systemic embolism, myocardial infarction, bleeding, cardiovascular death, etc). Secondary outcomes were ischaemic stroke, haemorrhagic stroke, any bleeding events, death from cardiovascular causes, death from all causes, residual root rate in the surgery group, device-related thrombosis in the surgery group, changes in blood pressure, cardiac chamber size changes, etc. Each subject completed at least 1 year of follow-up. ETHICS AND DISSEMINATION: The study has been approved by the Medical Ethics Committee of Beijing Tiantan Hospital, Capital Medical University, China (approval number: KY2022-013-02). The results from this study will be disseminated through manuscript publications and national/international conferences. TRIAL REGISTRATION NUMBER: ChiCTR2200058109.

Soluble Immune Checkpoint-Related Proteins in Blood Are Associated With Invasion and Progression in Non-Small Cell Lung Cancer.

Background: Immune checkpoint inhibition therapy has been achieved significant success in the treatment of non-small cell lung cancer (NSCLC). However, the role of soluble immune checkpoint- related proteins in NSCLC remains obscure. Methods: We evaluated the circulating levels of 14 immune checkpoint-related proteins panel (BTLA, LAG-3, GITR, IDO, PD-L2, PD-L1, PD-1, HVEM, Tim-3, CD28, CD27, CD80, CD137 and CTLA-4) and their associations with the risk of invasive disease and the risk of NSCLC in 43 pre-invasive (AIS), 81 invasive NSCLC (IAC) patients and matched 35 healthy donors using a multiplex Luminex assay. Gene expression in tumors from TCGA were analyzed to elucidate potential mechanisms. The multivariate logistic regression model was applied in the study. ROC(receiver operator characteristic) curve and calibration curve were used in the performance evaluation. Results: We found that sCD27, sCD80, CD137 and sPDL2 levels were significantly increased in IAC cases compared to AIS cases (P= 1.05E-06, 4.44E-05, 2.30E-05 and 1.16E-06, respectively), whereas sPDL1 and sPDL2 levels were significantly increased in NSCLC cases compared to healthy controls (P=3.25E-05 and 1.49E-05, respectively). Unconditional univariate logistic regression analysis indicated that increased sCD27, sCD80, sCD137, and sPDL2 were significantly correlated with the risk of invasive diseases. The model with clinical variables, sCD27 and sPDL2 demonstrated the best performance (AUC=0.845) in predicting the risk of IAC. CD27 and PDCD1LG2 (PDL2) showed significant association with cancer invasion signature in TCGA dataset. Conclusion: Our study provides evidence that soluble immune checkpoint-related proteins may associate with the risk of IAC, and we further established an optimized multivariate predictive model, which highlights their potential application in the treatment of NSCLC patients. Future studies may apply these biomarkers to test their predictive value of survival and treatment outcome during immunotherapy in NSCLC patients.

Emergence of Plasmids Co-Harboring Carbapenem Resistance Genes and tmexCD2-toprJ2 in Sequence Type 11 Carbapenem Resistant Klebsiella pneumoniae Strains.

Objectives: To characterize two plasmids co-harboring carbapenem resistance genes and tmexCD2-toprJ2 in carbapenem-resistant Klebsiella pneumoniae (CRKP) strains. Methods: Two clinical CRKP strains were isolated and characterized by antimicrobial susceptibility testing, conjugation assays, whole-genome sequencing, and bioinformatics analysis. Results: The two CRKP strains NB4 and NB5 were both resistant to imipenem, meropenem and tigecycline. Whole-genome sequencing revealed that two CRKP strains belonged to the ST11 type and carried multiple resistance genes. The tmexCD2-toprJ2 clusters in both strains were located on the IncFIB(Mar)-like/HI1B-like group of hybrid plasmids, which co-harbored the metallo-ß-lactamase gene blaNDM-1. In addition, the co-existence of blaNDM-1 and blaKPC-2 and the presence of tmexCD2-toprJ2 in CRKP strain NB5 was observed. Conclusions: In this study, tmexCD2-toprJ2 gene clusters were identified in two NDM-1-producing CRKP ST11 strains. These gene clusters will likely spread into clinical high-risk CRKP clones and exacerbate the antimicrobial resistance crisis. In addition, we detected the co-occurrence of blaNDM-1, blaKPC-2 and tmexCD2-toprJ2 in a single strain, which will undoubtedly accelerate the formation of a "superdrug resistant" bacteria. Hence, effective control measures should be implemented to prevent the further dissemination of such organisms in clinical settings.

Optimization of Heat Treatment for 38Si7 Spring Steel with Excellent Mechanical Properties and Controlled Decarburization.

Optimizing the heat treatment procedure with 13 mm diameter 38Si7 spring steel is critical for developing high-performance, low-cost, large spring steel for railway clips. The effects of quenching temperature, holding time, tempering temperature, and tempering time on the microstructure and mechanical properties were investigated using an orthogonal experiment, designed with four factors and three levels. The best heat treatment settings were explored, as well as the variation laws of mechanical properties, decarburization behavior, and fracture morphology. The results demonstrated that quenching temperature and tempering temperature had the most impact on plasticity and tempering temperature, while time had the most effect on strength. The optimized heat treatment schemes made the elongation increase by up to 106% and the reduction in area increase by up to 67%, compared with the standard BS EN 10089-2002, and there were mixed fractures caused by ductility and brittleness. The fracture tests showed a good performance of 20.2 GPa·%, and the heat treatment processes' minimum decarburization depth of 93.4 µm was determined. The optimized process would obtain stronger plastic deposition and better decarburization performance. The microstructure was simply lightly tempered martensite, and the matrix still retained the acicular martensite. The optimal heat treatment process is quenching at 900 °C for 30 min (water cooling), followed by tempering at 430 °C for 60 min (air cooling). The research led to a solution for increasing the overall mechanical characteristics and decreasing the surface decarburization of 38Si7 spring steel with a diameter of 13 mm, and it set the foundation for increasing the mass production of railway clips of this size.