Integrating bulk-RNA sequencing and single-cell sequencing analyses to characterize adenosine-enriched tumor microenvironment landscape and develop an adenosine-related prognostic signature predicting immunotherapy in lung adenocarcinoma.

The adenosine-signaling axis has been recognized as an important immunomodulatory pathway in tumor immunity. However, the biological role of the adenosine-signaling axis in the remodeling of the tumor microenvironment (TME) in lung adenocarcinoma (LUAD) remains unclear. Here, we quantified adenosine signaling (ado_sig) in LUAD samples using the GSVA method and assessed the prognostic value of adenosine in LUAD. Afterward, we explored the heterogeneity of the tumor-immune microenvironment at different adenosine levels. In addition, we analyzed the potential biological pathways engaged by adenosine. Next, we established single-cell transcriptional profiles of LUAD and analyzed cellular composition and cell-cell communication analysis under different adenosine microenvironments. Moreover, we established adenosine-related prognostic signatures (ARS) based on comprehensive bioinformatics analysis and evaluated the efficacy of ARS in predicting immunotherapy. The results demonstrated that adenosine signaling adversely impacted the survival of immune-enriched LUAD. The high-adenosine microenvironment exhibited elevated pro-tumor-immune infiltration, including M2 macrophages and displayed notably increased epithelial-mesenchymal transition (EMT) transformation. Furthermore, adenosine signaling displayed significant associations with the expression patterns and prognostic value of immunomodulators within the TME. Single-cell sequencing data revealed increased fibroblast occupancy and a prominent activation of the SPP1 signaling pathway in the high adenosine-signaling microenvironment. The ARS exhibited promising effectiveness in prognostication and predicting immunotherapy response in LUAD. In summary, overexpression of adenosine can cause a worsened prognosis in the LUAD with abundant immune infiltration. Moreover, increased adenosine levels are associated with pro-tumor-immune infiltration, active EMT transformation, pro-tumor angiogenesis, and other factors promoting cancer progression, which collectively contribute to the formation of an immunosuppressive microenvironment. Importantly, the ARS developed in this study demonstrate high efficacy in evaluating the response to immunotherapy.

Integrated multi-omics analysis and machine learning to refine molecular subtypes, prognosis, and immunotherapy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to metastasis. There is still a lack of suitable biomarkers to facilitate the refinement of precision-based therapeutic regimens. We used a combination of 10 known clustering algorithms and the omics data from 4 dimensions to identify high-resolution molecular subtypes of LUAD. Subsequently, consensus machine learning-related prognostic signature (CMRS) was developed based on subtypes related genes and an integrated program framework containing 10 machine learning algorithms. The efficiency of CMRS was analyzed from the perspectives of tumor microenvironment, genomic landscape, immunotherapy, drug sensitivity, and single-cell analysis. In terms of results, through multi-omics clustering, we identified 2 comprehensive omics subtypes (CSs) in which CS1 patients had worse survival outcomes, higher aggressiveness, mRNAsi and mutation frequency. Subsequently, we developed CMRS based on 13 key genes up-regulated in CS1. The prognostic predictive efficiency of CMRS was superior to most established LUAD prognostic signatures. CMRS demonstrated a strong correlation with tumor microenvironmental feature variants and genomic instability generation. Regarding clinical performance, patients in the high CMRS group were more likely to benefit from immunotherapy, whereas low CMRS were more likely to benefit from chemotherapy and targeted drug therapy. In addition, we evaluated that drugs such as neratinib, oligomycin A, and others may be candidates for patients in the high CMRS group. Single-cell analysis revealed that CMRS-related genes were mainly expressed in epithelial cells. The novel molecular subtypes identified in this study based on multi-omics data could provide new insights into the stratified treatment of LUAD, while the development of CMRS could serve as a candidate indicator of the degree of benefit of precision therapy and immunotherapy for LUAD.

CDC45 promotes the stemness and metastasis in lung adenocarcinoma by affecting the cell cycle.

OBJECTIVE: This study aimed to assess the functions of cell division cycle protein 45 (CDC45) in Non-small cell lung cancer (NSCLC) cancer and its effects on stemness and metastasis. METHODS: Firstly, differentially expressed genes related to lung cancer metastasis and stemness were screened by differential analysis and lasso regression. Then, in vitro, experiments such as colony formation assay, scratch assay, and transwell assay were conducted to evaluate the impact of CDC45 knockdown on the proliferation and migration abilities of lung cancer cells. Western blotting was used to measure the expression levels of related proteins and investigate the regulation of CDC45 on the cell cycle. Finally, in vivo model with subcutaneous injection of lung cancer cells was performed to verify the effect of CDC45 on tumor growth. RESULTS: This study identified CDC45 as a key gene potentially influencing tumor stemness and lymph node metastasis. Knockdown of CDC45 not only suppressed the proliferation and migration abilities of lung cancer cells but also caused cell cycle arrest at the G2/M phase. Further analysis revealed a negative correlation between CDC45 and cell cycle-related proteins, stemness-related markers, and tumor mutations. Mouse experiments confirmed that CDC45 knockdown inhibited tumor growth. CONCLUSION: As a novel regulator of stemness, CDC45 plays a role in regulating lung cancer cell proliferation, migration, and cell cycle. Therefore, CDC45 may serve as a potential target for lung cancer treatment and provide a reference for further mechanistic research and therapeutic development.

RACGAP1 promotes the progression and poor prognosis of lung adenocarcinoma through its effects on the cell cycle and tumor stemness.

OBJECTION: Investigating the key genes and mechanisms that influence stemness in lung adenocarcinoma. METHODS: First, consistent clustering analysis was performed on lung adenocarcinoma patients using stemness scoring to classify them. Subsequently, WGCNA was utilized to identify key modules and hub genes. Then, machine learning methods were employed to screen and identify the key genes within these modules. Lastly, functional analysis of the key genes was conducted through cell scratch assays, colony formation assays, transwell migration assays, flow cytometry cell cycle analysis, and xenograft tumor models. RESULTS: First, two groups of patients with different stemness scores were obtained, where the high stemness score group exhibited poor prognosis and immunotherapy efficacy. Next, LASSO regression analysis and random forest regression were employed to identify genes (PBK, RACGAP1) associated with high stemness scores. RACGAP1 was significantly upregulated in the high stemness score group of lung adenocarcinoma and closely correlated with clinical pathological features, poor overall survival (OS), recurrence-free survival (RFS), and unfavorable prognosis in lung adenocarcinoma patients. Knockdown of RACGAP1 suppressed the migration, proliferation, and tumor growth of cancer cells. CONCLUSION: RACGAP1 not only indicates poor prognosis and limited immunotherapy benefits but also serves as a potential targeted biomarker influencing tumor stemness.

Celastrol Pyrazine Derivative Alleviates Silicosis Progression via Inducing ROS-Mediated Apoptosis in Activated Fibroblasts.

Silicosis is a complex occupational disease without recognized effective treatment. Celastrol, a natural product, has shown antioxidant, anti-inflammatory, and anti-fibrotic activities, but the narrow therapeutic window and high toxicity severely limit its clinical application. Through structural optimization, we have identified a highly efficient and low-toxicity celastrol derivative, CEL-07. In this study, we systematically investigated the therapeutic potential and underlying mechanisms of CEL-07 in silicosis fibrosis. By constructing a silicosis mouse model and analyzing with HE, Masson, Sirius Red, and immunohistochemical staining, CEL-07 significantly prevented the progress of inflammation and fibrosis, and it effectively improved the lung respiratory function of silicosis mice. Additionally, CEL-07 markedly suppressed the expression of inflammatory factors (IL-6, IL-1α, TNF-α, and TNF-ß) and fibrotic factors (α-SMA, collagen I, and collagen III), and promoted apoptosis of fibroblasts by increasing ROS accumulation. Moreover, bioinformatics analysis combined with experimental validation revealed that CEL-07 inhibited the pathways associated with inflammation (PI3K-AKT and JAK2-STAT3) and the expression of apoptosis-related proteins. Overall, these results suggest that CEL-07 may serve as a potential candidate for the treatment of silicosis.

SPOCK1, as a potential prognostic and therapeutic biomarker for lung adenocarcinoma, is associated with epithelial-mesenchymal transition and immune evasion.

BACKGROUND: The occurrence of epithelial-mesenchymal transition (EMT) and immune evasion is considered to contribute to poor prognosis in lung adenocarcinoma (LUAD). Therefore, this study aims to explore the key oncogenes that promote EMT and immune evasion and reveal the expression patterns, prognostic value, and potential biological functions. METHODS: Firstly, we identified gene modules associated with EMT and Tumor Immune Dysfunction and Exclusion (TIDE) through weighted gene co-expression network analysis (WGCNA). Next, we utilized differential analysis and machine learning to identify the key genes and validate them. Moreover, we analyzed the correlation between key genes and tumor microenvironment remodeling, drug sensitivity, as well as mutation frequency. Furthermore, we explored and validated their malignant biological characteristics through in vitro experiments and clinical samples. Finally, potential drugs for LUAD were screened based on CMap and validated through experiments. RESULTS: Firstly, WGCNA analysis revealed that red and green modules were highly correlated with EMT and TIDE. Among them, upregulated expression of SPOCK1 was observed in lung adenocarcinoma tissues and was associated with poor prognosis. Additionally, patients in the high SPOCK1 group showed more activation of malignant oncogenic pathways, higher infiltration of immunosuppressive components, and a higher frequency of mutations. The knockdown of SPOCK1 suppressed invasion and metastasis capabilities of lung adenocarcinoma cells, and the high expression of SPOCK1 was associated with low infiltration of CD8+ T cells. Therapeutic aspects, SPOCK1 can be a candidate indicator for drug sensitivity and CMap showed that VER-155008 was the drug candidate with the largest perturbation effect on the SPOCK1 expression profile. In vitro and in vivo experiments validated the cancer-inhibitory effect of VER-155008 in LUAD. CONCLUSION: This study revealed through comprehensive bioinformatics analysis and experimental analysis that SPOCK1 can promote EMT and immune escape in LUAD, and it may serve as a promising candidate prognostic biomarker and therapeutic target for LUAD.

Construction and Validation of a Novel Immune-Related Gene Pairs-Based Prognostic Model in Lung Adenocarcinoma.

OBJECT: Focus on immune-related gene pairs (IRGPs) and develop a prognostic model to predict the prognosis of patients with lung adenocarcinoma (LUAD). METHODS: First, the LUAD patient dataset was downloaded from The Cancer Genome Atlas database, and paired analysis of immune-related genes was subsequently conducted. Then, LASSO regression was used to screen prognostic IRGPs for building a risk prediction model. Meanwhile, the Gene Expression Omnibus database was used for external validation of the model. Next, the clinical predictive power of IRGPs features was assessed by uni-multivariate Cox regression analysis, the infiltration of key immune cells in high and low IRGPs risk groups was analyzed with CIBERSORT, quanTIseq, and Timer, and the key pathways enriched for IRGPs were assessed using the Kyoto Encyclopedia of Genes and Genomes. Finally, the expression and related functions of key immune cells and genes were verified by immunofluorescence and cell experiments of tissue samples. RESULTS: It was revealed that the risk score of 19 IRGPs could be used as accurate indicators to evaluate the prognosis of LUAD patients, and the risk score was mainly related to T cell infiltration based on CIBERSORT analysis. Two genes of IRGPs, IL6, and CCL2, were found to be closely associated with the expression of PD-1/PD-L1 and the function of T-cells. Depending on the results of tissue immunofluorescence, IL6, CCL2, and T cells were highly expressed in the LUAD tissues of patients. Furthermore, IL6 and CCL2 were positively correlated with the expression of T cells. Besides, qRT-PCR assay in four different LUAD cells proved that IL6 and CCL2 were positively correlated with the expression of PD-L1 (P < .001). CONCLUSIONS: Based on 19 IRGPs, an effective prognosis model was established to predict the prognosis of LUAD patients. In addition, IL6 and CCL2 are closely related to the function of T-cells.

Whole genome sequencing and evolution analyses of Human metapneumovirus.

Human metapneumovirus (HMPV) is a major pathogen of acute respiratory tract infections (ARTIs) in children. Whole genome sequence analyses could help understand the evolution and transmission events of this virus. In this study, we sequenced HMPV whole genomes to improve the identification of molecular epidemiology in Beijing, China. Nasopharyngeal aspirates of hospitalized children aged < 14 years old with ARTIs were screened for HMPV infection using qPCR. Fourteen pairs of overlapping primers were used to amplify whole genome sequences of HMPV from positive samples with high viral loads. The epidemiology of HMPV was analysed and 27 HMPV whole genome sequences were obtained. Sequence identity and the positional entropy analyses showed that most regions of HMPV genome are conserved, whereas the G gene contained many variations. Phylogenetic analysis identified 25 HMPV sequences that belonged to a newly defined subtype A2b1; G gene sequences from 24 of these contained a 111-nucleotide duplication. HMPV is an important respiratory pathogen in paediatric patients. The new subtype A2b1 with a 111-nucleotide duplication has become predominate in Beijing, China.

High Triglyceride-Glucose Index Is Associated with Poor Prognosis in Patients with Acute Pancreatitis.

BACKGROUND: Acute pancreatitis (AP) is a common gastrointestinal disease worldwide. Severe acute pancreatitis (SAP) is characterized as persistent organ failure with a mortality rate as high as 20-30%. Early assessment of the severity and screening out possible SAP is of great significance. Given that there is still a lack of both convenient and practical tools for evaluating SAP, we conducted this study to explore the association between TyG index and acute pancreatitis prognosis. METHODS: A total of 353 in-patients diagnosed with acute pancreatitis in the Second Hospital of Shandong University were retrospectively enrolled from January 2018 to November 2021 in this study. According to the Atlanta Classification, they were divided into two groups based on the AP severity. Demographic information and clinical materials were retrospectively collected. The TyG index calculation formula is as follows: ln [fasting triglycerides (mg/dL) × fasting plasma glucose (mg/dL)/2]. Statistical analyses were performed using SPSS software (IBM version 22.0) and Medcalc software. Multivariable logistic regression analyses were used to investigate independent predictors for SAP. ROC curve was plotted to assess the predictive ability and cutoffs of TyG index. RESULTS: A total of 353 AP patients were respectively enrolled in this study, of which 47 suffered from SAP. Compared with the non-SAP group, TyG index was significantly higher in the SAP group (10.44 ± 1.55 vs 9.33 ± 1.44, P < 0.001). Multivariate logistic regression analysis showed that TyG index was an independent risk factor for SAP (OR 1.835, 95% CI 1.380-2.442 P < 0.001), with a cutoff of 8.76 for non-HTG/AAP and 11.81 for HTG/AAP by ROC curve. TyG index of patients who suffered from SIRS, OF, APFC, and ANC was higher than those without (P < 0.05). CONCLUSIONS: The triglyceride-glucose index is an independent risk factor for SAP. High TyG index is closely related to SAP and AP-related complications.

Surgical Treatment is Still Recommended for Patients Over 75 Years with IA NSCLC: A Predictive Model Based on Surveillance, Epidemiology and End Results Database.

BACKGROUND: To determine the populations who suitable for surgical treatment in elderly patients (age ≥ 75 y) with IA stage. METHODS: The clinical data of NSCLC patients diagnosed from 2010 to 2015 were collected from the SEER database and divided into surgery group (SG) and no-surgery groups (NSG). The confounders were balanced and differences in survival were compared between groups using PSM (Propensity score matching, PSM). Cox regression analysis was used to screen the independent factors that affect the Cancer-specific survival (CSS). The surgery group was defined as the patients who surgery-benefit and surgery-no benefit according to the median CSS of the no-surgery group, and then randomly divided into training and validation groups. A surgical benefit prediction model was constructed in the training and validation group. Finally, the model is evaluated using a variety of methods. RESULTS: A total of 7297 patients were included. Before PSM (SG: n = 3630; NSG: n = 3665) and after PSM (SG: n = 1725, NSG: n = 1725) confirmed that the CSS of the surgery group was longer than the no-surgery group (before PSM: 82 vs. 31 months, P < .0001; after PSM: 55 vs. 39 months, P < .0001). Independent prognostic factors included age, gender, race, marrital, tumor grade, histology, and surgery. In the surgery cohort after PSM, 1005 patients (58.27%) who survived for more than 39 months were defined as surgery beneficiaries, and the 720 patients (41.73%) were defined surgery-no beneficiaries. The surgery group was divided into training group 1207 (70%) and validation group 518 (30%). Independent prognostic factors were used to construct a prediction model. In training group (AUC = .678) and validation group (AUC = .622). Calibration curve and decision curve prove that the model has better performance. CONCLUSIONS: This predictive model can well identify elderly patients with stage IA NSCLC who would benefit from surgery, thus providing a basis for clinical treatment decisions.

Relationship Between Neutrophil-To-Lymphocyte Ratio and Brain Metastasis in Non-Small Cell Lung Cancer Patients.

OBJECTIVE: To investigate the relationship between the neutrophil-to-lymphocyte ratio (NLR) of patients with non-small cell lung cancer (NSCLC) and their risk of developing brain metastases after adjusting for confounding factors. METHODS: A retrospective observational study of the general data of patients with NSCLC diagnosed from January 2016 to December 2020. Multivariate logistic regression was used to calculate the dominance ratio (OR) with 95% confidence interval (CI) for NLR and NSCLC brain metastases with subgroup analysis. Generalized summation models and smoothed curve fitting were used to identify whether there was a nonlinear relationship between them. RESULTS: In all 3 models, NLR levels were positively correlated with NSCLC brain metastasis (model 1: OR: 1.12, 95% CI: 1.01-1.23, P = .025; model 2: OR: 1.16, 95% CI: 1.04-1.29, P = .007; model 3: OR: 1.20, 95% CI: 1.05-1.37, P = .006). Stratified analysis showed that this positive correlation was present in patients with adenocarcinoma (LUAD) and female patients (LUAD: OR: 1.30, 95% CI: 1.10-1.54, P = .002; female: OR: 1.52, 95% CI: 1.05-2.20, P = .026), while there was no significant correlation in patients with squamous carcinoma (LUSC) and male patients (LUSC: OR:0.76,95% CI:0.38- 1.53, P = .443; male: OR:1.13, 95% CI:0.95-1.33, P = .159). CONCLUSION: This study showed that elevated levels of NLR were independently associated with an increased risk of developing brain metastases in patients with NSCLC, and that this correlation varied by TYPE and SEX, with a significant correlation in female patients and patients with LUAD.

Development and Validation of Machine Learning Models to Predict Epidermal Growth Factor Receptor Mutation in Non-Small Cell Lung Cancer: A Multi-Center Retrospective Radiomics Study.

OBJECTIVE: To develop and validate a generalized prediction model that can classify epidermal growth factor receptor (EGFR) mutation status in non-small cell lung cancer patients. METHODS: A total of 346 patients (296 in the training cohort and 50 in the validation cohort) from four centers were included in this retrospective study. First, 1085 features were extracted using IBEX from the computed tomography images. The features were screened using the intraclass correlation coefficient, hypothesis tests and least absolute shrinkage and selection operator. Logistic regression (LR), decision tree (DT), random forest (RF), and support vector machine (SVM) were used to build a radiomics model for classification. The models were evaluated using the following metrics: area under the curve (AUC), calibration curve (CAL), decision curve analysis (DCA), concordance index (C-index), and Brier score. RESULTS: Sixteen features were selected, and models were built using LR, DT, RF, and SVM. In the training cohort, the AUCs was .723, .842, .995, and .883; In the validation cohort, the AUCs were .658, 0567, .88, and .765. RF model with the best AUC, its CAL, C-index (training cohort=.998; validation cohort=.883), and Brier score (training cohort=.007; validation cohort=0.137) showed a satisfactory predictive accuracy; DCA indicated that the RF model has better clinical application value. CONCLUSION: Machine learning models based on computed tomography images can be used to evaluate EGFR status in patients with non-small cell lung cancer, and the RF model outperformed LR, DT, and SVM.

Clinical efficacy of chemotherapy in colorectal cancer patients over 80 years old.

PURPOSE: Colorectal cancer (CRC) is a common and aggressive gastrointestinal cancer, and the prognostic impact associated with chemotherapy in super elderly (over 80 years old) patients remains poorly defined. We aimed to define the effect of chemotherapy on the prognosis of patients with CRC over 80 years old. PATIENTS AND METHODS: A retrospective study including CRC patients over 80 years old was conducted. The patients were screened from the Surveillance Epidemiology and End Results (SEER) database from 2010 to 2015. Overall survival (OS) and cancer-specific survival (CSS) were applied as the primary and secondary outcome. Cox proportional hazards regression models were used to evaluate factors associated with OS and CSS. Survival curves of OS and CSS were estimated by Kaplan-Meier method and compared by log-rank test. RESULTS: In total, 14,748 CRC patients over 80 years old were included in this study. The median patient age was 85 (IQR: 82-87). All patients were divided into surgical group and non-surgical group. The OS and CSS of the surgical group were significantly better than those of the non-surgical group (P < 0.001). Chemotherapy can improve OS and CSS for patients with stage III and IV (P < 0.001) in surgical group. For the super elderly patients with CRC, chemotherapy significantly improved OS and CSS in all TNM stages in non-surgical group. CONCLUSION: For super elderly patients with colorectal cancer, tumor treatment should not be abandoned because of their age. It is necessary to carry out clinical trials in super elderly patients.

Analysis of the RCF crack detection phenomenon based on induction thermography.

Eddy current pulsed thermography (ECPT) is used to detect rolling contact fatigue (RCF) cracks on the rail. It is observed that some of the cracks disappear in the thermal image with the increase of heating time. Based on the finite element method, with double cracks as the basic unit, three different crack models are established, and the mutual disturbance relationship between the double cracks is discussed based on the eddy current distribution and thermal diffusion process. The simulation and experimental results show that different crack models are affected by thermal diffusion in different heating stages to different degrees, and the time of the crack thermal image disappearance is obtained. According to the above conclusions, the RCF cracks are extracted and classified based on the influence of thermal diffusion. The possibility of rail condition assessment and maintenance based on the disappearance time is explained.

Bibliometrics and visualisation analysis of literature on varicocele: From 2002 to 2021.

Varicocele is a common disease in men, with a global incidence of approximately 25%. A comprehensive and systematic analysis of the knowledge map on it will help in assessing frontier research and identify knowledge gaps. In total, 4103 articles published from 2002 to 2021 in 1066 journals were included. They represent the current research status worldwide, potential hotspots and future research directions. In the past decades, the number of publications and citations of varicocele-related studies have increased steadily. Academic institutions in the United States played a leading role in varicocele research. The country, institution, journal and author with the most publications were the United States (779), Cleveland Clinic Foundation (132), Andrologia (246) and Agarwal A (106), respectively. The most frequently used keywords were Varicocele (1620), Male Infertility (944), Varicocelectomy (288), Testis (245), Sperm (166), Oxidative Stress (144), Azoospermia (119), Semen Analysis (118), Laparoscopy (116) and Adolescent (97). Currently, the main focus of current varicocele research is its surgical treatment method and effect on sperm quality. The frontier research hotspot is the specific mechanism of varicocele-induced decrease in sperm quality.

Homocysteine promotes migration of adventitial fibroblasts via angiotensin II type 1 receptor activation to aggravate atherosclerosis.

This study clarified the effect of homocysteine on adventitial fibroblasts (AFs) and its relationship with angiotensin II type 1 receptor (AT1R). Hyperhomocysteinemia aggravated the plaque area and increased the expression of IL-6, MCP-1, and macrophage infiltration in the plaque and adventitia of the aorta, whereas telmisartan improved this effect. Hyperhomocysteinemia induced the occurrence of the AFs marker protein ER-TR7 in the plaque and entire layer of the aorta, whereas telmisartan improved these effects, indicating that homocysteine induced AFs migration and that AT1R mediated this process. The migration experiments of AFs also reached the same conclusion. Homocysteine increased the phosphorylation levels of PKC and ERK1/2 in the AFs and HEK293A cells transfected with the AT1R plasmid, whereas telmisartan inhibited this effect, indicating that homocysteine activated AT1R intracellular signaling pathway. Homocysteine also increased the AFs At1R expression. Conclusion, homocysteine promoted adventitial inflammation, induced AFs migration, and aggravated atherosclerosis by activating AT1R.

DOPNet: Achieving Accurate and Efficient Point Cloud Registration Based on Deep Learning and Multi-Level Features.

Point cloud registration aims to find a rigid spatial transformation to align two given point clouds; it is widely deployed in many areas of computer vision, such as target detection, 3D localization, and so on. In order to achieve the desired results, registration error, robustness, and efficiency should be comprehensively considered. We propose a deep learning-based point cloud registration method, called DOPNet. DOPNet extracts global features of point clouds with a dynamic graph convolutional neural network (DGCNN) and cascading offset-attention modules, and the transformation is predicted by a multilayer perceptron (MLP). To enhance the information interaction between the two branches, the feature interaction module is inserted into the feature extraction pipeline to implement early data association. We compared DOPNet with the traditional method of using the iterative closest point (ICP) algorithm along with four learning-based registration methods on the Modelnet40 data set. In the experiments, the source and target point clouds were generated by sampling the original point cloud twice independently; we also conducted additional experiments with asymmetric objects. Further evaluation experiments were conducted with point cloud models from Stanford University. The results demonstrated that our DOPNet method outperforms these comparative methods in general, achieving more accurate and efficient point cloud registration.

Characterization of Edible Fungus Substrate Modified Biochar and Its Adsorption Capacity for Ciprofloxacin Hydrochloride.

In this study, silver-ytterbium-modified biochar (MBC) was prepared to adsorb ciprofloxacin hydrochloride. It was compared with biochar (BC) and alkali-modified biochar (NBC). The results show that the MBC had more functional groups and a larger specific surface area than the BC and NBC. The saturated adsorption capacity of the MBC (312.500 mg g-1) was 3 and 19 times higher than that of the NBC and BC, respectively. The adsorption data were consistent with the pseudo-second-order kinetics model and the Langmuir isotherm model. In addition, the mechanism of CIP adsorption onto NBC and MBC may be dominated by π-π electron donor-accepter interactions. C-O, C=O and -NH2 play important roles in adsorption, and Ag-O and Yb-O groups participate in the adsorption of CIP onto MBC.

Major adverse kidney events within 30 days in patients with acute pancreatitis: a tertiary-center cohort study.

BACKGROUND: To evaluate the event rate of major adverse kidney events within 30 days (MAKE30) in acute pancreatitis (AP) and its potential risk factors. METHODS: A retrospective analysis of a tertiary center data on all AP patients admitted within 72 h after onset of abdominal pain between June 2015 and June 2019 was conducted. MAKE30 - a composite of death, new renal replacement therapy (RRT), or persistent renal dysfunction (PRD) - and its individual components were retrieved at discharge or 30 days. Logistic regression analysis was used to assess the risk factors for MAKE30. RESULTS: 295 patients were enrolled and 16% experienced MAKE30. For individual components, the incidence was 3% for death, 15% for new RRT, and 5% for PRD. In multivariate logistic regression analysis, hyperchloremia at admission [OR = 8.38 (1.07-65.64); P = 0.043] and SOFA score [OR 1.63 (1.18-2.26); P = 0.003] were independent risk factors in predicting MAKE30. Further analysis showed that patients with hyperchloremia had more requirements of RRT (57% vs. 10%, P < 0.001), more PRD (14% vs. 4%, P = 0.034). CONCLUSION: MAKE30 is a common event in AP patients. Hyperchloremia and SOFA score at admission were two independent risk factors for MAKE30.

Epidemiology and genotypic diversity of human metapneumovirus in paediatric patients with acute respiratory infection in Beijing, China.

BACKGROUND: Acute respiratory tract infections (ARTIs) causes high amounts of morbidity and mortality worldwide every year. Human metapneumovirus (HMPV) is a major pathogen of ARTIs in children. In this study, we aimed to investigate the epidemiology and genotypic diversity of HMPV in children hospitalized with ARTIs in Beijing, China. METHODS: Hospitalized children aged < 14 years with ARTIs were enrolled from April 2017 to March 2018; nasopharyngeal aspirates were collected and subjected to real-time polymerase chain reaction tests for HMPV. HMPV-positive samples were genotyped based on a partial N gene. Whole genome sequences were determined for samples with high viral loads. RESULTS: 4.08% (52/1276) enrolled paediatric patients were identified as having HMPV infection. The epidemic season is winter and early spring, children aged ≤ 4 years were more susceptible to HMPV infection (47/52, 90.38%). The co-infection rate were 36.54% (19/52), the most common co-infected virus were influenza and respiratory syncytial virus. The main diagnoses of HMPV infection were pneumonia (29/52, 55.77%) and bronchitis (23/52, 44.23%), while the main clinical manifestations were cough, fever, rhinorrhoea, and sneeze. Among 48 HMPV-positive specimens, A2b (19/48, 39.58%) and B1 (26/48, 54.17%) were the main epidemic subtypes. Patients with HMPV genotype A infection had a higher viral load compared to genotype B patients (6.07 vs. 5.37 log10 RNA copies/ml). Five complete sequences of HMPV were obtained. This is the first report of a whole genome sequence of HMPV-B1 isolated in China. CONCLUSIONS: HMPV is an important respiratory pathogen in paediatric patients. Cases of HMPV infection could burden hospitals in the epidemic season. HMPV viral loads and genotypes have no correlation with co-infection or clinical characteristics.