Research on the Solid-Liquid Composite Casting Process of Incoloy825/P110 Steel Composite Pipe.

Bimetallic composites have a wide range of application prospects in various industries. Different bonding temperatures, as one of the influencing factors, directly affect the bonding effectiveness as well as the performance and application of the materials. Using metallurgical bonding techniques ensures a strong bond at the interface of bimetallic materials, resulting in high-quality composite pipe billets. This paper describes an Incoloy825/P110 steel bimetal composite material made by the solid-liquid composite method. By utilizing ProCAST 14.5 software for simulation and deriving theoretical formulas, an initial range of temperatures for bimetallic preparation has been tentatively determined. And this temperature range will be utilized for on-site experiments to prepare bimetallic samples. After the preparation process is completed, samples will be selected. The influence of the external mold temperature on the interface bonding of Incoloy825/P110 steel solid-liquid composite material is studied using an ultra-depth three-dimensional morphology microscope and a scanning electron microscope. Through research, the optimal preheating temperature range for the solid-liquid composite outer mold of Incoloy825/P110 bimetallic composite material has been determined. The casting temperature of the inner mold has a significant impact on the interface bonding of this bimetal composite material. As the casting temperature of the inner mold increases, the interface thickness gradually increases. At lower temperatures, the interface thickness is lower and the bonding is poorer. At higher temperatures, melting may occur, leading to coarse grains at the interface. When the temperatures of the inner and outer molds are within a certain range, a new phase appears at the interface. Indeed, it increases the strength of the interface bonding. Due to co-melting of the bimetal near the interface, element migration occurs, resulting in increased Ni and Cr content at the interface and enhanced corrosion resistance.

A machine learning-based model analysis for serum markers of liver fibrosis in chronic hepatitis B patients.

Early assessment and accurate staging of liver fibrosis may be of great help for clinical diagnosis and treatment in patients with chronic hepatitis B (CHB). We aimed to identify serum markers and construct a machine learning (ML) model to reliably predict the stage of fibrosis in CHB patients. The clinical data of 618 CHB patients between February 2017 and September 2021 from Zhejiang Provincial People's Hospital were retrospectively analyzed, and these data as a training cohort to build the model. Six ML models were constructed based on logistic regression, support vector machine, Bayes, K-nearest neighbor, decision tree (DT) and random forest by using the maximum relevance minimum redundancy (mRMR) and gradient boosting decision tree (GBDT) dimensionality reduction selected features on the training cohort. Then, the resampling method was used to select the optimal ML model. In addition, a total of 571 patients from another hospital were used as an external validation cohort to verify the performance of the model. The DT model constructed based on five serological biomarkers included HBV-DNA, platelet, thrombin time, international normalized ratio and albumin, with the area under curve (AUC) values of the DT model for assessment of liver fibrosis stages (F0-1, F2, F3 and F4) in the training cohort were 0.898, 0.891, 0.907 and 0.944, respectively. The AUC values of the DT model for assessment of liver fibrosis stages (F0-1, F2, F3 and F4) in the external validation cohort were 0.906, 0.876, 0.931 and 0.933, respectively. The simulated risk classification based on the cutoff value showed that the classification performance of the DT model in distinguishing hepatic fibrosis stages can be accurately matched with pathological diagnosis results. ML model of five serum markers allows for accurate diagnosis of hepatic fibrosis stages, and beneficial for the clinical monitoring and treatment of CHB patients.

Unified Convolutional Sparse Transformer for Disease Diagnosis, Monitoring, Drug Development, and Therapeutic Effect Prediction from EEG Raw Data.

Electroencephalogram (EEG) analysis plays an indispensable role across contemporary medical applications, which encompasses diagnosis, monitoring, drug discovery, and therapeutic assessment. This work puts forth an end-to-end deep learning framework that is uniquely tailored for versatile EEG analysis tasks by directly operating on raw waveform inputs. It aims to address the challenges of manual feature engineering and the neglect of spatial interrelationships in existing methodologies. Specifically, a spatial channel attention module is introduced to emphasize the critical inter-channel dependencies in EEG signals through channel statistics aggregation and multi-layer perceptron operations. Furthermore, a sparse transformer encoder is used to leverage selective sparse attention in order to efficiently process long EEG sequences while reducing computational complexity. Distilling convolutional layers further concatenates the temporal features and retains only the salient patterns. As it was rigorously evaluated on key EEG datasets, our model consistently accomplished a superior performance over the current approaches in detection and classification assignments. By accounting for both spatial and temporal relationships in an end-to-end paradigm, this work facilitates a versatile, automated EEG understanding across diseases, subjects, and objectives through a singular yet customizable architecture. Extensive empirical validation and further architectural refinement may promote broader clinical adoption prospects.

Evaluating the predictive value of initial lactate/albumin ratios in determining prognosis of sepsis patients.

Sepsis remains a significant clinical challenge owing to its complex pathophysiology and variable prognosis. The early identification of patients at a higher risk of poor outcomes can be crucial for improving treatment strategies. This study aimed to evaluate the predictive value of early serum lactate and albumin levels and the lactate/albumin (L/A) ratio for 28-day prognosis in patients with sepsis. Patients diagnosed with sepsis between January 2021 and December 2022 were evaluated using a retrospective cohort methodology. Inclusion followed the International Consensus on sepsis and septic shock (Sepsis-3) guidelines and patients were selected based on well-defined criteria. Variables such as lactate, albumin, and the L/A ratio were documented within the first 24 hours of admission. Statistical analyses were performed using various tools, including the nonparametric Mann-Whitney U test and receiver operating characteristic curves. A total of 301 patients were divided into the survival (n = 167) and death (n = 134) groups. Notable differences were detected in the incidence of pulmonary infection, shock, lactate, albumin, and the L/A ratio. The L/A ratio was identified as a key predictor with an area under the curve of 0.868, an optimal cutoff value of >0.17, a sensitivity of 56.21%, and a specificity of 94.18%. Significant disparities in mortality rates and survival times were observed for the lactate, albumin, and L/A levels. This study underscores the predictive value of early serum lactate and albumin levels and the L/A ratio for 28-day prognosis in patients with sepsis, with the L/A ratio showing a superior predictive capability. These findings highlight the importance of L/A ratio as a robust and precise marker for evaluating the future clinical course of patients with sepsis, potentially aiding early detection and management.

Estimation of multiple networks with common structures in heterogeneous subgroups.

Network estimation has been a critical component of high-dimensional data analysis and can provide an understanding of the underlying complex dependence structures. Among the existing studies, Gaussian graphical models have been highly popular. However, they still have limitations due to the homogeneous distribution assumption and the fact that they are only applicable to small-scale data. For example, cancers have various levels of unknown heterogeneity, and biological networks, which include thousands of molecular components, often differ across subgroups while also sharing some commonalities. In this article, we propose a new joint estimation approach for multiple networks with unknown sample heterogeneity, by decomposing the Gaussian graphical model (GGM) into a collection of sparse regression problems. A reparameterization technique and a composite minimax concave penalty are introduced to effectively accommodate the specific and common information across the networks of multiple subgroups, making the proposed estimator significantly advancing from the existing heterogeneity network analysis based on the regularized likelihood of GGM directly and enjoying scale-invariant, tuning-insensitive, and optimization convexity properties. The proposed analysis can be effectively realized using parallel computing. The estimation and selection consistency properties are rigorously established. The proposed approach allows the theoretical studies to focus on independent network estimation only and has the significant advantage of being both theoretically and computationally applicable to large-scale data. Extensive numerical experiments with simulated data and the TCGA breast cancer data demonstrate the prominent performance of the proposed approach in both subgroup and network identifications.

Hierarchical Polyimide Microparticles with Controllable Morphology.

Hierarchical polyimides (PIs) not only show outstanding thermal stability and high mechanical strength but also have great advantages in terms of microstructure and surface area, which makes them highly valuable in various fields such as aerospace, microelectronics, adsorption, catalysis, and energy storage. However, great challenges still remain in the synthesis of hierarchical PIs with well-defined microstructure. Herein, polyamide acid salts (PAAS) with tunable ionization degree are synthesized first via the polymerization of dianhydride and diamine monomers in deionized water with 1,2-dimethylimidazole (DMIZ). Then cationic cetyltrimethylammonium chloride (CTAC) is added to the PAAS aqueous solution to induce the formation of polyelectrolyte-surfactant complexes based on electrostatic interaction. After a typical hydrothermal reaction (HTR) procedure, hierarchical PIs with different microstructures such as urchin-like PI microparticles, flower-like PI microparticles, and lamellar PI petals can be fabricated simply by changing the additive amount of DMIZ and CTAC. The nanostructure self-assemblies of PAAS are dominated by the charges on macromolecular chains and the formation of hierarchical structures of polymers is ascribed to a geometrical selection process during crystal growth. This work provides valuable insights into the self-assembly behaviors of polyelectrolyte systems for synthesizing well-defined hierarchical polymers.

Imaging risk factors for predicting postoperative complications of intramedullary nailing for tibial fracture.

OBJECTIVE: The objective of this study was to analyze the ratio of fracture site diameter to tibial isthmus diameter (TFI ratio) as a predictor of postoperative complications, including malunion and delayed union, after tibial intramedullary nailing for middle and lower tibial fractures. METHODS: Data were collected from all adult patients older than 20 years of age who underwent tibial intramedullary nailing for middle and lower tibial fractures between January 2015 and January 2023 and were followed up for at least 1 year. Diabetes history, smoking history, fracture type, injury mechanism, surgical method, surgical approach, diameter of the medullary cavity at the fracture site, and diameter of the tibial isthmus were recorded. Logistic regression analysis was used to determine the variables affecting the occurrence of complications. The TFI ratio was used to calculate the sensitivity and specificity of the parameters, and ROC curves were generated to establish TFI ratio thresholds for predicting complications. RESULTS: A total of 123 patients with middle and lower tibial fractures were treated with intramedullary nails. The mean age of the patients was 43.72 years (range, 21-81 years); 89 were males, and 34 were females. Univariate logistic regression analysis showed that fracture type, open reduction surgery, superior patellar approach, and TFI ratio were significantly correlated with postoperative complications after intramedullary nailing of a tibial fracture. Multivariate logistic regression analysis showed that the TFI ratio was an independent risk factor for complications (P = 0.001*). By using the TFI ratio as a predictor of complications, an ROC curve was generated to establish a threshold. The ROC curve showed that a TFI ratio ≥ 1.31 had a sensitivity of 0.89, a specificity of 0.71, and an area under the ROC curve of 0.82 for predicting complications. CONCLUSIONS: The results of this study suggest that a wider intramedullary diameter and a shorter fixed length at the fracture site are associated with a higher incidence of complications after tibial intramedullary nailing. The TFI ratio may be used as a reliable parameter for predicting complications after such surgery. In patients with a high TFI ratio (≥ 1.31), additional reduction and fixation techniques may be needed to obtain and maintain fracture reduction.

Molecular Mechanism of SOX18 in Lipopolysaccharide-Induced Injury of Human Umbilical Vein Endothelial Cells.

Endothelial dysfunction is associated with the progression of sepsis. This study sought to probe the molecular route of sex-determining region on the Y chromosome-box transcription factor 18 (SOX18) in sepsis-associated endothelial injury. Human umbilical vein endothelial cells (HUVECs) were treated with lipopolysaccharide (LPS) to establish the sepsis cell model. Cell viability, lactate dehydrogenase (LDH) release, oxidative stress (reactive oxygen species/malondialdehyde/superoxide dismutase), and inflammation (interleukin-1ß/tumor necrosis factor-α/interleukin-6) were evaluated by cell counting kit-8 assay and relevant assay kits. The expression levels of SOX18, microRNA (miR)-204-5p, and cadherin-2 (CDH2) in cells were determined by real-time quantitative polymerase chain reaction and Western blot assay. The interaction of SOX18, miR-204-5p, and CDH2 was analyzed by chromatin immunoprecipitation and dual-luciferase assay. LPS induced HUVECs injury and downregulation of SOX18. SOX18 overexpression increased cell viability, while decreased LDH activity, oxidative stress, and inflammation. SOX18 bound to the miR-204-5p promoter to promote miR-204-5p expression, and further repressed CDH2 expression. miR-204-5p knockdown and CDH2 overexpression abrogated the protective role of SOX18 in HUVECs injury. Overall, SOX18 alleviated LPS-induced injury of HUVECs by promoting miR-204-5p and repressing CDH2, suggesting it as a potential target for sepsis treatment.

Environmental drivers of the rising incidence of early-onset colorectal cancer in the United States.

Incidence of early-onset (diagnosed before age 50) colorectal cancer (EOCRC) has increased alarmingly since the 1990s in the United States. This study investigated what environmental exposures may have driven this increase. We obtained EOCRC incidence data from the Surveillance, Epidemiology, and End Results Program, and data for 11 exposures, for example, body mass index (BMI), from long-term national surveys. We aggregated these data for 30 to 49-year-olds during 1992 to 2016 by population subgroups defined by calendar period, age, race and sex, and used negative binomial regression models to identify and estimate associations of EOCRC with multiple exposures. Furthermore, we used counterfactual modeling to quantify contributions of identified risk factors to EOCRC incidence. The top models (with lowest Bayesian Information Criteria) consistently identified excess body weight, represented by overweight and obesity (BMI ≥25) or obesity alone (BMI ≥30), as the strongest risk factor. The best-performing model estimated increased EOCRC incidence due to overweight and obesity, with an incidence rate ratio (95% confidence interval) of 1.20 (1.17-1.22) for white men, 1.04 (1.00-1.08) for black men, 1.17 (1.15-1.21) for white women and 1.03 (0.97-1.08) for black women. Increases in overweight and obesity prevalence contributed to an estimated 30% (standard error: 1%) for men and 28% (standard error: 2%) for women of ECORC incidence during 1992 to 2016. These findings suggest excess body weight substantially contributed to and is likely a primary driver of the rising incidence of EOCRC in the United States. Prevention of excess weight gain may help lower colorectal cancer risk early in life.

Experimental study on influencing mechanism of the multiple effect of steel slag powder for coarse tailings cemented backfill.

The gradation of aggregate and the hydration reaction of cementitious materials are important factors affecting the performance of backfill materials. Steel slag powder (SSP) can be used as both aggregate and cementitious material according to different particle size. SSP has multiple influencing effects on coarse tailings cemented backfill (CTCB). Experiment with different content SSP in the CTCB was designed. And uniaxial compression, nuclear magnetic resonance and scanning electron microscopy techniques were used to characterize its macro and micro characteristics. The relationship model of aggregate characteristics on strength and porosity was established by analyzing the characteristics of aggregate using gradation and fractal. The conclusions mainly include: (1) SSP plays three main roles in the CTCB: optimizing the gradation, generating hydration reaction and influencing the hydration reaction of cement. (2) There are good gradation and fractal characteristics between SSP and coarse tailings, with a grading index of 0.30-0.61 and a fractal dimension of 2.12-2.61. (3) The relationship between strength, porosity and gradation, fractal dimension was quadratic function relation, and then the grading index and fractal dimension for optimal strength and pore characteristics are 0.45-0.49 and 2.33-2.40 respectively.

Typical hemophagocytic syndrome associated with cytomegalovirus infection in an immunocompetent patient: a case report and literature review. / ä¸€ä¾‹èŠ¦å¯æ›¿å°¼æˆåŠŸæ•‘æ²»å ç–«åŠŸèƒ½æ­£å¸¸æ‚£è€ å› å·¨ç»†èƒžç— æ¯’æ„ŸæŸ“å¯¼è‡´å—œè¡€ç»†èƒžç»¼åˆå¾çš„ç— ä¾‹æŠ¥å‘ŠåŠæ–‡çŒ®å›žé¡¾.

Cytomegalovirus (CMV) infection is currently prevalent in populations throughout the world, and 56%|-94% of the global population is seropositive for CMV. CMV infection mainly affects immunocompromised hosts. In these cases, it can cause significant symptoms, tissue-invasive disease, and many sequelae including death (Dioverti and Razonable, 2016). The vast majority of healthy adults with CMV infection experience an asymptomatic course; when symptomatic, it manifests as a mononucleosis-like syndrome in approximately 10% of patients (Sridhar et al., 2018). The gastrointestinal tract and central nervous system appear to be the most frequent sites of severe CMV infection in immunocompetent individuals (Rafailidis et al., 2008). However, CMV infection is relatively rarely recorded in immunocompetent hosts.

[Vertical Migration Characteristics and Fate of Heavy Metals from Zinc Smelting Slag in Soil Profile].

To investigate the influence of heavy metals in smelting waste residue on the quality of soil and groundwater, a simulation column experiment was conducted to study the migration characteristics of heavy metals from the leaching solution of zinc volatilizing kiln residue in the site soil profile under continuous or intermittent leaching for 90 days. The concentrations of Cd, Cu, Pb, and Zn in leachate and their accumulation, chemical fractions, and particle size distribution characteristics in the soil profile were analyzed, and the retention mechanism of heavy metals was also discussed. The results showed that the concentration of heavy metals in the soil column leachate decreased rapidly after reaching the peak at the earlier leaching stage, and the Cd concentration far exceeded the threshold limit of 0.1 mg·L-1(class Ⅳ) of the Quality Standard for Groundwater(GB/T 14848-2017), indicating that there was Cd pollution risk of groundwater. The soil profile had a great adsorption capacity for heavy metals in the waste residue. Cd, Cu, Pb, and Zn were predominately accumulated in the shallow soil depth(0-10 cm), which was 237-429, 1.25-16.2, 1.38-2.31, and 1.79-3.17 times of the content of corresponding heavy metals in the soil profile before leaching, respectively. The migration distance of heavy metals in the slag under continuous leaching was longer than that under intermittent leaching, and Cd was significantly accumulated in the deep layer of the soil column. The contribution of soil coarse particles(0.5-2.0 mm) to the total cumulative amount of Cd, Cu, and Zn was larger, whereas Pb was more prone to accumulate in the particle size of<0.25 mm. The results of BCR sequential extraction fraction showed that the accumulated Cd, Cu, and Zn in shallow soil depth were mainly present in the weak acid extraction, accounting for 62.4%-76.7%, 72.0%-95.8%, and 67.6%-85.8% of total content, respectively. The X-ray diffraction(XRD) and Fourier transform infrared spectroscopy(FTIR) analysis showed that exogenous heavy metals in slag entering the soil would not form a stable mineral phase within 90 days, and the soil hydroxyl(-OH) and carbonyl(C=O) functional groups and iron aluminum silicate oxides were the main retention factors.

Anti-PD-1 immunotherapy with androgen deprivation therapy induces robust immune infiltration in metastatic castration-sensitive prostate cancer.

When compared to other malignancies, the tumor microenvironment (TME) of primary and castration-resistant prostate cancer (CRPC) is relatively devoid of immune infiltrates. While androgen deprivation therapy (ADT) induces a complex immune infiltrate in localized prostate cancer, the composition of the TME in metastatic castration-sensitive prostate cancer (mCSPC), and the effects of ADT and other treatments in this context are poorly understood. Here, we perform a comprehensive single-cell RNA sequencing (scRNA-seq) profiling of metastatic sites from patients participating in a phase 2 clinical trial (NCT03951831) that evaluated standard-of-care chemo-hormonal therapy combined with anti-PD-1 immunotherapy. We perform a longitudinal, protein activity-based analysis of TME subpopulations, revealing immune subpopulations conserved across multiple metastatic sites. We also observe dynamic changes in these immune subpopulations in response to treatment and a correlation with clinical outcomes. Our study uncovers a therapy-resistant, transcriptionally distinct tumor subpopulation that expands in cell number in treatment-refractory patients.

Engineered hydrogel reveals contribution of matrix mechanics to esophageal adenocarcinoma and identifies matrix-activated therapeutic targets.

Increased extracellular matrix (ECM) stiffness has been implicated in esophageal adenocarcinoma (EAC) progression, metastasis, and resistance to therapy. However, the underlying protumorigenic pathways are yet to be defined. Additional work is needed to develop physiologically relevant in vitro 3D culture models that better recapitulate the human tumor microenvironment and can be used to dissect the contributions of matrix stiffness to EAC pathogenesis. Here, we describe a modular, tumor ECM-mimetic hydrogel platform with tunable mechanical properties, defined presentation of cell-adhesive ligands, and protease-dependent degradation that supports robust in vitro growth and expansion of patient-derived EAC 3D organoids (EAC PDOs). Hydrogel mechanical properties control EAC PDO formation, growth, proliferation, and activation of tumor-associated pathways that elicit stem-like properties in the cancer cells, as highlighted through in vitro and in vivo environments. We also demonstrate that the engineered hydrogel serves as a platform for identifying potential therapeutic targets to disrupt the contribution of protumorigenic matrix mechanics in EAC. Together, these studies show that an engineered PDO culture platform can be used to elucidate underlying matrix-mediated mechanisms of EAC and inform the development of therapeutics that target ECM stiffness in EAC.

Low-dose lipopolysaccharide inhibits spinal cord injury-induced neuronal apoptosis by regulating autophagy through the lncRNA MALAT1/Nrf2 axis.

Background: Spinal cord injury (SCI) is a neurological disease associated with a high disability rate. Low-dose lipopolysaccharide (LPS) has been reported to activate cross-immune tolerance and alleviate the effects of various traumatic stimuli. The present study aimed to explore the effect of LPS on SCI and the potential molecular mechanism. Methods: Male Sprague-Dawley (SD) rats were used to established an in vivo SCI model and were intraperitoneally injected with lentivirus particles encoding a MALAT1 small interfering RNA (siRNA) on day 10 prior to SCI and with 0.2 mg/kg LPS 72 h prior to SCI. Basso, Beattie, and Bresnahan (BBB) scoring; HE staining; and TUNEL assay were used to assess neurological function and pathophysiological changes. Western blot and immunohistochemistry (IHC) were used to detect cell autophagy and Nrf2 nuclear translocation. PC12 cells were exposed to oxygen-glucose deprivation/reoxygenation (OGD/R) to establish an in vitro SCI model. In vitro SCI model cells were pretreated with LPS and transfected with siMALAT1 or MALAT1 overexpression plasmid aimed at knocking down MALAT1 or overexpressing MALAT1. The cell counting kit-8 (CCK-8) assay was used to measure the toxicity of LPS towards PC12 cells. Flow cytometry and immunofluorescence analysis were performed to investigate cell apoptosis and Nrf2 nuclear translocation. Results: SCI rats preconditioned with low-dose LPS had higher BBB scores, reduced SCI injury, increased MALAT1 expression and activated autophagy and Nrf2 nuclear translocation in the in vivo SCI model. In the in vitro SCI model, low-dose LPS treatment suppressed the apoptotic ratio of PC12 cells, increased MALAT1 expression, activated autophagy, and promoted Nrf2 nuclear translocation. Silencing MALAT1 exacerbated OGD/R injury in vitro and weakened the protective effect of low-dose LPS. Overexpression of MALAT1 inhibits OGD/R-induced apoptosis by inducing autophagy and promoting Nrf2 nuclear translocation. This was also been confirmed in animal experiments, silencing MALAT1 blocked the promotion of Nrf2 by low-dose LPS and the alleviated of SCI apoptosis. Conclusions: Low-dose LPS exhibited a protective role on SCI by activating autophagy and suppressing nerve cell apoptosis via the lncRNA MALAT1/Nrf2 axis.

Diagnostic Performance of Metagenomic Next-Generation Sequencing in Central Nervous System Cryptococcosis Using Cerebrospinal Fluid.

Purpose: Metagenomic next-generation sequencing (mNGS) has been widely used to diagnose infectious diseases. However, there are few studies on its diagnostic performance in the central nervous system (CNS) cryptococcosis. This study examined the diagnostic efficacy of mNGS in identifying Cryptococcus spp. in cerebrospinal fluid (CSF) samples. Patients and Methods: From March 2021 to March 2023, 290 patients with suspected CNS infection were recruited from the First Affiliated Hospital, School of Medicine, Zhejiang University, and 74 patients were ultimately included in the study. Lastly, 22 patients with CNS cryptococcosis were included. Of these patients, 25 CSF samples were enrolled. The diagnostic performance of conventional assays [including India ink, cryptococcal antigen (CrAg) testing, and culture] and mNGS was evaluated for CNS cryptococcosis. Results: In the 25 samples collected, the coincidence rates of mNGS with India ink, CrAg, and culture were 64.0% (16/25), 80.0% (20/25), and 80.0% (20/25), respectively. Without antifungal drug exposure, the coincidence rates were increased to 66.7% (10/15), 100.0% (15/15), and 93.3% (14/15), respectively. The coincidence rates after antifungal therapy were all decreased to 60.0% (6/10), 50.0% (5/10), and 60.0% (6/10), respectively. Moreover, in the 25 samples, the sensitivity of mNGS reached 80.0%, and of India ink, CrAg testing, and culture were 68.0, 100.0, and 60.0%, respectively. The mNGS showed an excellent positive rate (100.0%) in the 15 samples collected without antifungal drug exposure, which was significantly higher than the antifungal drug-exposed group (n = 10) (50.0%) (P = 0.005). The reads of Cryptococcus spp. before antifungal therapy were significantly higher than after it (median, 25,915 vs 2, P = 0.008). Conclusion: mNGS is an effective tool for diagnosing CNS cryptococcosis using CSF; however, its sensitivity decreases considerably in patients who have been effectively treated with antifungal drugs.

Immunomodulatory and Antiviral Therapy Improved Functional Cure Rate in CHB Patients with High HBsAg Level Experienced NA.

Background and Aims: A functional cure, or hepatitis B virus (HBV) surface antigen (HBsAg) loss, is difficult to achieve in patients with hepatitis B virus e antigen (HBeAg)-positive chronic hepatitis B. The HBV vaccine and granulocyte-macrophage colony-stimulating factor (GM-CSF) have been reported to help reduce HBsAg levels and promote HBsAg loss. In this prospective randomized trial, we evaluated HBsAg loss in patients receiving pegylated interferon-α2b (PEGIFN-α2b) and tenofovir disoproxil fumarate (TDF), with and without GM-CSF and HBV vaccination. Methods: A total of 287 patients with HBeAg positive chronic hepatitis B and seroconversion after nucleot(s)ide analog treatment were assigned randomly to three treatment groups for 48 weeks, TDF alone (control), PEGIFN-α2b + TDF, and PEGIFN-α2b + TDF + GM-CSF + HBV vaccine. The primary endpoints were the proportions of patients with HBsAg loss and seroconversion at 48 and 72 weeks. Results: The cumulative HBsAg loss rates in the control, PEGIFN-α2b + TDF, and PEGIFN-α2b + TDF + GM-CSF + HBV vaccine groups at week 48 were 0.0%, 28.3%, and 41.1%, respectively. The cumulative HBsAg seroconversion rates in these groups at week 48 were 0.0%, 21.7%, and 33.9%, respectively. Multivariate regression analysis showed that GM-CSF use plus HBV vaccination was significantly associated with HBsAg loss (p=0.017) and seroconversion (p=0.030). Conclusions: In patients with HBeAg-positive chronic hepatitis B and seroconversion after nucleot(s)ide analog treatment, immunomodulatory/antiviral treatment regimens effectively improved HBsAg loss, and the regimen including GM-CSF and HBV vaccination was most effective.

Diagnosis of Non-Tuberculous Mycobacterial Pulmonary Disease by Metagenomic Next-Generation Sequencing on Bronchoalveolar Lavage Fluid.

Purpose: Metagenomic next-generation sequencing (mNGS) has been extensively used in the diagnosis of infectious diseases but has rarely been applied in non-tuberculous mycobacterial pulmonary disease (NTMPD). This study analyzed the diagnostic performance of mNGS in bronchoalveolar lavage fluid (BALF) samples to identify non-tuberculous mycobacteria (NTM). Patients and Methods: A total of 231 patients with suspected NTMPD were recruited from the First Affiliated Hospital, School of Medicine, Zhejiang University, from March 2021 to October 2022. A total of 118 cases were ultimately included. Of these patients, 61 cases were enrolled in the NTMPD group, 23 cases were enrolled in the suspected-NTMPD group, and 34 cases were enrolled in the non-NTMPD group. The diagnostic performance of traditional culture, acid-fast staining (AFS), and mNGS for NTMPD was assessed. Results: Patients in the NTMPD group had a higher proportion of bronchiectasis (P=0.007). Among mNGS-positive samples in the NTMPD group, a significantly higher reads number of NTM was observed in AFS-positive patients [61.50 (22.00, 395.00) vs 15.50 (6.00, 36.25), P=0.008]. Meanwhile, mNGS demonstrated a sensitivity of 90.2%, which was far superior to AFS (42.0%) and culture (77.0%) (P<0.001). The specificity of mNGS in detecting NTM was 100%, which was the same as that of traditional culture. The area under the receiver operating characteristic curve of mNGS was 0.951 (95% CI 0.906-0.996), which was higher than that of culture (0.885 [95% CI 0.818-0.953]) and AFS (0.686 [95% CI 0.562-0.810]). In addition to NTM, other pulmonary pathogens were also found by mNGS. Conclusion: mNGS using BALF samples is a rapid and effective diagnostic tool for NTMPD, and mNGS is recommended for patients with suspected NMTPD or NTM coinfected pneumonia.

Engineering Characteristics and Microscopic Mechanism of Soil-Cement-Bentonite (SCB) Cut-Off Wall Backfills with a Fixed Fluidity.

Soil-cement-bentonite (SCB) backfill has been widely used in constructing cut-off walls to inhibit groundwater movement in contaminated sites. This study prepares SCB backfill with fixed fluidity. We conducted a series of experiments to investigate the engineering characteristics and microscopic mechanism of the backfill. The results indicate that the water content in the slurry was more sensitive to the bentonite content. The unconfined compression strength (UCS) value increased with an increase in the cement content, and the change with an increase in bentonite content was not noticeable. The permeability coefficient decreased distinctly with an increase in the cement and bentonite contents. The porosity of the SCB backfill increased with increasing bentonite content and decreased with increasing cement content. The UCS of SCB backfill was linearly and negatively correlated with the porosity; the permeability coefficient was not significantly related to the porosity. The percentage of micro- and small-pore throats in the backfill increased with increasing bentonite and cement contents. As cement and bentonite content increased by 6% in the backfill, the proportion of micro- and small-pore throats increased by 0.7% and 1.2%, respectively. The percentage of micro- and small-pore throats is deduced to be more suitable as a characterization parameter for the permeability of the SCB backfill. The overall results of this study show that the reasonably proportioned SCB backfill has potential as an eco-friendly and cost-effective material. Based on the requirements of strength and permeability coefficient (UCS > 100 kPa, 28 days permeability coefficient <1 × 10-7 cm/s), we suggested using a backfill with 12% bentonite and 9% cement as the cut-off wall mix ratio.