Inward motion of diamond nanoparticles inside an iron crystal.

In the absence of externally applied mechanical loading, it would seem counterintuitive that a solid particle sitting on the surface of another solid could not only sink into the latter, but also continue its rigid-body motion towards the interior, reaching a depth as distant as thousands of times the particle diameter. Here, we demonstrate such a case using in situ microscopic as well as bulk experiments, in which diamond nanoparticles ~100 nm in size move into iron up to millimeter depth, at a temperature about half of the melting point of iron. Each diamond nanoparticle is nudged as a whole, in a displacive motion towards the iron interior, due to a local stress induced by the accumulation of iron atoms diffusing around the particle via a short and easy interfacial channel. Our discovery underscores an unusual mass transport mode in solids, in addition to the familiar diffusion of individual atoms.

Automated classification of ulcerative lesions in small intestine using densenet with channel attention and residual dilated blocks.

Objective. Ulceration of the small intestine, which has a high incidence, includes Crohn's disease (CD), intestinal tuberculosis (ITB), primary small intestinal lymphoma (PSIL), cryptogenic multifocal ulcerous stenosing enteritis (CMUSE), and non-specific ulcer (NSU). However, the ulceration morphology can easily be misdiagnosed through enteroscopy.Approach. In this study, DRCA-DenseNet169, which is based on DenseNet169, with residual dilated blocks and a channel attention block, is proposed to identify CD, ITB, PSIL, CMUSE, and NSU intelligently. In addition, a novel loss function that incorporates dynamic weights is designed to enhance the precision of imbalanced datasets with limited samples. DRCA-Densenet169 was evaluated using 10883 enteroscopy images, including 5375 ulcer images and 5508 normal images, which were obtained from the Shanghai Changhai Hospital.Main results. DRCA-Densenet169 achieved an overall accuracy of 85.27% ± 0.32%, a weighted-precision of 83.99% ± 2.47%, a weighted-recall of 84.36% ± 0.88% and a weighted-F1-score of 84.07% ± 2.14%.Significance. The results demonstrate that DRCA-Densenet169 has high recognition accuracy and strong robustness in identifying different types of ulcers when obtaining immediate and preliminary diagnoses.

Identification of integrated proteomics and transcriptomics signature of alcohol-associated liver disease using machine learning.

Distinguishing between alcohol-associated hepatitis (AH) and alcohol-associated cirrhosis (AC) remains a diagnostic challenge. In this study, we used machine learning with transcriptomics and proteomics data from liver tissue and peripheral mononuclear blood cells (PBMCs) to classify patients with alcohol-associated liver disease. The conditions in the study were AH, AC, and healthy controls. We processed 98 PBMC RNAseq samples, 55 PBMC proteomic samples, 48 liver RNAseq samples, and 53 liver proteomic samples. First, we built separate classification and feature selection pipelines for transcriptomics and proteomics data. The liver tissue models were validated in independent liver tissue datasets. Next, we built integrated gene and protein expression models that allowed us to identify combined gene-protein biomarker panels. For liver tissue, we attained 90% nested-cross validation accuracy in our dataset and 82% accuracy in the independent validation dataset using transcriptomic data. We attained 100% nested-cross validation accuracy in our dataset and 61% accuracy in the independent validation dataset using proteomic data. For PBMCs, we attained 83% and 89% accuracy with transcriptomic and proteomic data, respectively. The integration of the two data types resulted in improved classification accuracy for PBMCs, but not liver tissue. We also identified the following gene-protein matches within the gene-protein biomarker panels: CLEC4M-CLC4M, GSTA1-GSTA2 for liver tissue and SELENBP1-SBP1 for PBMCs. In this study, machine learning models had high classification accuracy for both transcriptomics and proteomics data, across liver tissue and PBMCs. The integration of transcriptomics and proteomics into a multi-omics model yielded improvement in classification accuracy for the PBMC data. The set of integrated gene-protein biomarkers for PBMCs show promise toward developing a liquid biopsy for alcohol-associated liver disease.

Innate and adaptive immune cell interaction drives inflammasome activation and hepatocyte apoptosis in murine liver injury from immune checkpoint inhibitors.

Immune checkpoints (CTLA4 & PD-1) are inhibitory pathways that block aberrant immune activity and maintain self-tolerance. Tumors co-opt these checkpoints to avoid immune destruction. Immune checkpoint inhibitors (ICIs) activate immune cells and restore their tumoricidal potential, making them highly efficacious cancer therapies. However, immunotolerant organs such as the liver depend on these tolerogenic mechanisms, and their disruption with ICI use can trigger the unintended side effect of hepatotoxicity termed immune-mediated liver injury from ICIs (ILICI). Learning how to uncouple ILICI from ICI anti-tumor activity is of paramount clinical importance. We developed a murine model to recapitulate human ILICI using CTLA4+/- mice treated with either combined anti-CTLA4 + anti-PDL1 or IgG1 + IgG2. We tested two forms of antisense oligonucleotides to knockdown caspase-3 in a total liver (parenchymal and non-parenchymal cells) or in a hepatocyte-specific manner. We also employed imaging mass cytometry (IMC), a powerful multiplex modality for immunophenotyping and cell interaction analysis in our model. ICI-treated mice had significant evidence of liver injury. We detected cleaved caspase-3 (cC3), indicating apoptosis was occurring, as well as Nod-like receptor protein 3 (NLRP3) inflammasome activation, but no necroptosis. Total liver knockdown of caspase-3 worsened liver injury, and induced further inflammasome activation, and Gasdermin-D-mediated pyroptosis. Hepatocyte-specific knockdown of caspase-3 reduced liver injury and NLRP3 inflammasome activation. IMC-generated single-cell data for 77,692 cells was used to identify 22 unique phenotypic clusters. Spatial analysis revealed that cC3+ hepatocytes had significantly closer interactions with macrophages, Kupffer cells, and NLRP3hi myeloid cells than other cell types. We also observed zones of three-way interaction between cC3+ hepatocytes, CD8 + T-cells, and macrophages. Our work is the first to identify hepatocyte apoptosis and NLRP3 inflammasome activation as drivers of ILICI. Furthermore, we report that the interplay between adaptive and innate immune cells is critical to hepatocyte apoptosis and ILICI.

Conventional and multi-omics assessments of subacute inhalation toxicity due to propylene glycol and vegetable glycerin aerosol produced by electronic cigarettes.

Propylene glycol (PG) and vegetable glycerin (VG) are the most common solvents used in electronic cigarette liquids. No long-term inhalation toxicity assessments have been performed combining conventional and multi-omics approaches on the potential respiratory effects of the solvents in vivo. In this study, the systemic toxicity of aerosol generated from a ceramic heating coil-based e-cigarette was evaluated. First, the aerosol properties were characterized, including carbonyl emissions, the particle size distribution, and aerosol temperatures. To determine toxicological effects, rats were exposed, through their nose only, to filtered air or a propylene glycol (PG)/ glycerin (VG) (50:50, %W/W) aerosol mixture at the target concentration of 3 mg/L for six hours daily over a continuous 28-day period. Compared with the air group, female rats in the PG/VG group exhibited significantly lower body weights during both the exposure period and recovery period, and this was linked to a reduced food intake. Male rats in the PG/VG group also experienced a significant decline in body weight during the exposure period. Importantly, rats exposed to the PG/VG aerosol showed only minimal biological effects compared to those with only air exposure, with no signs of toxicity. Moreover, the transcriptomic, proteomic, and metabolomic analyses of the rat lung tissues following aerosol exposure revealed a series of candidate pathways linking aerosol inhalation to altered lung functions, especially the inflammatory response and disease. Dysregulated pathways of arachidonic acids, the neuroactive ligand-receptor interaction, and the hematopoietic cell lineage were revealed through integrated multi-omics analysis. Therefore, our integrated multi-omics approach offers novel systemic insights and early evidence of environmental-related health hazards associated with an e-cigarette aerosol using two carrier solvents in a rat model.

Comprehensive comparative analysis of the prognostic impact of systemic inflammation biomarkers for patients underwent cardiac surgery.

Background: Inflammation plays an integral role in the development of cardiovascular disease, and few studies have identified different biomarkers to predict the prognosis of cardiac surgery. But there is a lack of reliable and valid evidence to determine the optimal systemic inflammatory biomarkers to predict prognosis. Methods: From December 2015 and March 2021, we collected 10 systemic inflammation biomarkers among 820 patients who underwent cardiac surgery. Time-dependent receiver operating characteristic curves (ROC) curve at different time points and C-index was compared at different time points. Kaplan-Meier method was performed to analyze overall survival (OS). Cox proportional hazard regression analyses were used to assess independent risk factors for OS. A random internal validation was conducted to confirm the effectiveness of the biomarkers. Results: The area under the ROC of lymphocyte-to-C-reactive protein ratio (LCR) was 0.655, 0.620 and 0.613 at 1-, 2- and 3-year respectively, and C-index of LCR for OS after cardiac surgery was 0.611, suggesting that LCR may serve as a favorable indicator for predicting the prognosis of cardiac surgery. Patients with low LCR had a higher risk of postoperative complications. Besides, Cox proportional hazard regression analyses indicated that LCR was considered as an independent risk factor of OS after cardiac surgery. Conclusion: LCR shows promise as a noteworthy representative among the systemic inflammation biomarkers in predicting the prognosis of cardiac surgery. Screening for low LCR levels may help surgeons identify high-risk patients and guide perioperative management strategies.

Toward a Value-Based Therapy Recommendation Model.

Patient value is an important factor in clinical decision making, but conventionally, it is not incorporated in the decision processes. Clinical decision making has some clinical guidelines as a reference. There are very few value-based clinical guidelines, but knowledge about how values affect decision making is mentioned in some scattered studies in the literature. We use a literature review method to extract evidence and integrate it as part of the decision-making model. In this paper, a value-based therapy recommendation comprehensive model is proposed. A literature analysis is conducted to collect value-based evidence. The patients' values are defined and classified with fine granularity. Categorized values and candidate therapies are used in combination as filtering keywords to build this literature database. The literature analysis method generates a literature database used as a source of arguments for influencing decision making based on values. Then, a formalism model is put forward to integrate the value-based evidence with clinical evidence, and the literature databases and clinical guidelines are collected and analyzed to populate the evidence repository. During the decision-making processes, the evidence repository is utilized to match patients' clinical information and values. Decision-makers can dynamically adjust the relative importance of the two pieces of evidence to obtain a treatment plan that is more suitable for the patient. A prototype system was implemented using a case study for breast cancer and validated for feasibility and effectiveness through controlled experiments.

On-chip clearing for live imaging of 3D cell cultures.

Three-dimensional (3D) cell cultures provide an important model for various biological studies by bridging the gap between two-dimensional (2D) cell cultures and animal tissues. Microfluidics has recently provided controllable platforms for handling and analyzing 3D cell cultures. However, on-chip imaging of 3D cell cultures within microfluidic devices is hindered by the inherent high scattering of 3D tissues. Tissue optical clearing techniques have been used to address this concern but remain limited to fixed samples. As such, there is still a need for an on-chip clearing method for imaging live 3D cell cultures. Here, to achieve on-chip clearing for live imaging of 3D cell cultures, we conceived a simple microfluidic device by integrating a U-shaped concave for culture, parallel channels with micropillars, and differentiated surface treatment to enable on-chip 3D cell culture, clearing, and live imaging with minimal disturbance. The on-chip tissue clearing increased the imaging performance of live 3D spheroids with no influence on cell viability or spheroid proliferation and demonstrated robust compatibility with several commonly used cell probes. It allowed dynamic tracking of lysosomes in live tumor spheroids and enabled quantitative analysis of their motility in the deeper layer. Our proposed method of on-chip clearing for live imaging of 3D cell cultures provides an alternative for dynamic monitoring of deep tissue on a microfluidic device and has the potential to be used in 3D culture-based assays for high-throughput applications.

Thoracic sarcopenia predicts clinical outcomes in patients undergoing coronary artery bypass grafting: A 6-year cohort study.

BACKGROUND: The relationship between thoracic sarcopenia and clinical outcomes in patients underwent coronary artery bypass grafting (CABG) is unclear. This study aims to evaluate whether thoracic sarcopenia has a satisfactory prognostic effect on adverse outcomes after CABG. METHODS: From December 2015 to May 2021, 338 patients who underwent isolated CABG at our institution were recruited in this study. Skeletal muscle area at T12 level acquired by chest computed tomography (CT) was normalized to assess thoracic sarcopenia. Univariate and multivariate analyses were performed to evaluate the risk factors of postoperative complications and overall survival (OS). RESULTS: The prevalence of thoracic sarcopenia in patients underwent CABG was 13.02%. The incidence of total major complication was significantly higher in thoracic sarcopenia group (81.8% vs 61.9%, p = 0.010). Thoracic sarcopenic patients also had longer postoperative hospital stays (p = 0.047), intensive care unit (ICU) stays (p = 0.001), higher costs (p = 0.001) and readmission rates within 30 days of discharge (18.2% vs 4.4%, p = 0.001). Patients without thoracic sarcopenia showed significantly higher OS at the 2-year follow-up period (93.9% vs 72.7%, p<0.001). Multivariate analyses demonstrated that thoracic sarcopenia was significantly and independently associated with postoperative complications and long-term OS after CABG. CONCLUSION: Thoracic sarcopenia is an effective clinical predictor of adverse postoperative complications and long-term OS in patients underwent CABG. Thoracic sarcopenia based on chest CT should be included in preoperative risk assessment of CABG.

Prognostic implications of Global Leadership Initiative on Malnutrition-defined malnutrition in older patients who underwent cardiac surgery in China.

BACKGROUND: The proportion of older patients who are candidates for cardiac surgery is increasing. Growing evidence has shown that malnutrition is associated with a poor prognosis after cardiac surgery. The present study aimed to investigate the prognostic implications of malnutrition defined by the Global Leadership Initiative on Malnutrition in older patients who underwent cardiac surgery. METHODS: From November 2015 to January 2021, 401 older patients who underwent cardiac surgery were retrospectively enrolled and evaluated using the Global Leadership Initiative on Malnutrition criteria. The perioperative characteristics and clinical outcomes were collected. The independent risk factors for postoperative complications and overall survival were analyzed. RESULTS: The prevalence of Global Leadership Initiative on Malnutrition-defined malnutrition was 22.7% in this study. Patients with Global Leadership Initiative on Malnutrition-defined malnutrition had higher risks of postoperative complications (65.9% vs 49.7%, P = .006) and poor overall survival (68.1% vs 83.9%, P = .0019). Global Leadership Initiative on Malnutrition-defined malnutrition was also related to a longer postoperative hospital stay and prolonged intensive care stay. Five factors were identified as independent risk factors for overall survival: Global Leadership Initiative on Malnutrition-defined malnutrition (P = .009), chronic heart failure (P = .007), atrial fibrillation (P = .029), operative time (P < .001) and hemoglobin (P = .044). CONCLUSION: We demonstrated the prognostic implications of Global Leadership Initiative on Malnutrition-defined malnutrition in older patients who underwent cardiac surgery for the first time. This study highlights the necessity of using the Global Leadership Initiative on Malnutrition assessment in the comprehensive preoperative risk assessment of cardiac surgery.

Machine learning-based models for predicting gas breakthrough pressure of porous media with low/ultra-low permeability.

Gas breakthrough pressure is a significant parameter for the gas exploration and safety evaluation of engineering barrier systems in the carbon dioxide storage, remediation of contaminated sites, and deep geological repository for disposal of high-level nuclear waste, etc. Test for determining gas breakthrough pressure is very difficult and time-consuming, due to the low/ultra-low conductivity of the specimen. It is also difficult to get a comprehensive and high-precision model based on limited results obtained through individual experiments, as the measurements of gas breakthrough pressure were influenced by many factors. In this study, a collected database was built that covered a lot of former test data, and then, two models were developed by the random forest (RF) algorithm and multiexpression programming (MEP) method. The MEP model constructed with explicit expressions for the gas breakthrough pressure overcame the drawbacks of common "black box" models. Meanwhile, five significant indicators were selected from ten common features using the permutation importance algorithm. The RF model was interpreted by the Shapley value and the PDP/ICE plots, while the MEP model was analyzed through the proposed explicit expression, showing strong consistence with that in former studies. Finally, robustness analysis was conducted, and stability of the proposed two models was verified.

[Establishment of a nomogram model for the early diagnosis of childhood sepsis]. / 基于列线图的儿童脓毒症早期诊断模型的建立.

OBJECTIVES: To establish a nomogram model for the early diagnosis of sepsis in children. METHODS: A total of 76 children with sepsis who were admitted to Sichuan Maternal and Child Health Hospital from January 2018 to June 2021 were retrospectively selected as the sepsis group. After matching for sex and age (±2 years) at a ratio of 1:1:1, 76 children with local infection who were hospitalized during the same period were enrolled as the local infection group, and 76 children with non-infectious diseases were enrolled as the control group. The three groups were compared in terms of laboratory markers and the results of quick Sequential Organ Failure Assessment (qSOFA) and Pediatric Critical Illness Score (PCIS). A multivariate logistic regression analysis was used to investigate the association between the above indicators and sepsis. R4.1.3 software was used to establish and validate the nomogram model for the early diagnosis of sepsis based on the results of the multivariate analysis. A receiver operating characteristic (ROC) curve analysis was used to evaluate the value of the nomogram model, and the Bootstrap method was used to perform the internal validation of the model. RESULTS: The multivariate logistic regression analysis showed that soluble triggering receptor expressed on myeloid cells-1, qSOFA score, PCIS score, C-reactive protein, interleukin-6, and interleukin-10 were independently associated with childhood sepsis (P<0.05). The above indicators were used to establish a nomogram for the early diagnosis of sepsis, with an area under the ROC curve of 0.837 (95%CI: 0.760-0.914), and the calibration curve results showed a mean absolute error of 0.024, suggesting that the performance of this model was basically consistent with that of the ideal model. CONCLUSIONS: The indicators soluble triggering receptor expressed on myeloid cells-1, qSOFA score, PCIS score, C-reactive protein, interleukin-6, and interleukin-10 are independently associated with childhood sepsis, and the nomogram model established based on these indicators has high discriminatory ability and accuracy in the early diagnosis of sepsis in children.

Integrated Transcriptomic and Proteomic Analysis Identifies Plasma Biomarkers of Hepatocellular Failure in Alcohol-Associated Hepatitis.

Alcohol-associated hepatitis (AH) is a form of liver failure with high short-term mortality. Recent studies have shown that defective function of hepatocyte nuclear factor 4 alpha (HNF4a) and systemic inflammation are major disease drivers of AH. Plasma biomarkers of hepatocyte function could be useful for diagnostic and prognostic purposes. Herein, an integrative analysis of hepatic RNA sequencing and liquid chromatography-tandem mass spectrometry was performed to identify plasma protein signatures for patients with mild and severe AH. Alcohol-related liver disease cirrhosis, nonalcoholic fatty liver disease, and healthy subjects were used as comparator groups. Levels of identified proteins primarily involved in hepatocellular function were decreased in patients with AH, which included hepatokines, clotting factors, complement cascade components, and hepatocyte growth activators. A protein signature of AH disease severity was identified, including thrombin, hepatocyte growth factor α, clusterin, human serum factor H-related protein, and kallistatin, which exhibited large abundance shifts between severe and nonsevere AH. The combination of thrombin and hepatocyte growth factor α discriminated between severe and nonsevere AH with high sensitivity and specificity. These findings were correlated with the liver expression of genes encoding secreted proteins in a similar cohort, finding a highly consistent plasma protein signature reflecting HNF4A and HNF1A functions. This unbiased proteomic-transcriptome analysis identified plasma protein signatures and pathways associated with disease severity, reflecting HNF4A/1A activity useful for diagnostic assessment in AH.

Only transesophageal echocardiography guided patent foramen ovale closure: A single-center experience.

Background: An increasing number of studies have proved that patent foramen ovale (PFO) occlusion could reduce the incidence of recurrent stroke more than drug therapy alone under certain conditions. Which is the "best" guidance technique still remains to be discussed. Methods: A single center retrospective study enrolled 120 patients (mean age 52.51 ± 14.29 years) who underwent PFO closure between April 2019 and March 2021. 87 patients (72.5%) had suffered cryptogenic stroke (CS) at least one time, and 24 patients (20%) had repetitive episodes of hemicrania unsourced. 65 patients were in the transesophageal echocardiography (TEE) guidance group (T-group), and the other 55 patients were in the angiographic guidance group (A-group). Results: There were no significant differences in crucial clinical characteristics between the two groups. In T-group, the procedural success rate was higher (100% vs. 92.7%, P = 0.028), and the procedural time was shorter (23.15 ± 13.87 vs. 25.75 ± 7.19, P = 0.001). No difference was detected in the procedural complication rate. Follow-up were performed at least 12 months. At 12 months, new atrial fibrillation occurred in 1 patient (1.5%) in the T-group and in 1 patient (1.8%) in the A-group (P = 0.905). Residual shunt occurred in 1 patient (1.5%) in the T-group and in 3 patients (5.5%) in the A-group (P = 0.236). Recurrent cerebral ischemia occurred in 2 patient (3.1%) in the T-group and in 2 patients (3.6%) in the A-group (P = 0.865). Conclusion: The use of only intra-procedural TEE guidance for PFO closure is safe and effective. The whole procedure can be performed without fluoroscopy and contrast medium. The short and medium follow-up results are satisfactory, especially in the residual shunt.

Research advance of natural products in tumor immunotherapy.

Cancer immunotherapy has emerged as a novel anti-tumor treatment. Despite significant breakthroughs, cancer immunotherapy remains focused on several types of tumors that are sensitive to the immune system. Therefore, effective strategies to expand its indications and improve its efficacy become key factors for the further development of cancer immunotherapy. In recent decades, the anticancer activities of natural products are reported to have this effect on cancer immunotherapy. And the mechanism is largely attributed to the remodeling of the tumor immunosuppressive microenvironment. The compelling data highlight that natural products offer an alternative method option to improve immune function in the tumor microenvironment (TME). Currently, more attention is being paid to the discovery of new potential modulators of tumor immunotherapy from natural products. In this review, we describe current advances in employing natural products and natural small-molecule drugs targeting immune cells to avoid tumor immune escape, which may bring some insight for guiding tumor treatment.

Differentiating between liver diseases by applying multiclass machine learning approaches to transcriptomics of liver tissue or blood-based samples.

Background & Aims: Liver disease carries significant healthcare burden and frequently requires a combination of blood tests, imaging, and invasive liver biopsy to diagnose. Distinguishing between inflammatory liver diseases, which may have similar clinical presentations, is particularly challenging. In this study, we implemented a machine learning pipeline for the identification of diagnostic gene expression biomarkers across several alcohol-associated and non-alcohol-associated liver diseases, using either liver tissue or blood-based samples. Methods: We collected peripheral blood mononuclear cells (PBMCs) and liver tissue samples from participants with alcohol-associated hepatitis (AH), alcohol-associated cirrhosis (AC), non-alcohol-associated fatty liver disease, chronic HCV infection, and healthy controls. We performed RNA sequencing (RNA-seq) on 137 PBMC samples and 67 liver tissue samples. Using gene expression data, we implemented a machine learning feature selection and classification pipeline to identify diagnostic biomarkers which distinguish between the liver disease groups. The liver tissue results were validated using a public independent RNA-seq dataset. The biomarkers were computationally validated for biological relevance using pathway analysis tools. Results: Utilizing liver tissue RNA-seq data, we distinguished between AH, AC, and healthy conditions with overall accuracies of 90% in our dataset, and 82% in the independent dataset, with 33 genes. Distinguishing 4 liver conditions and healthy controls yielded 91% overall accuracy in our liver tissue dataset with 39 genes, and 75% overall accuracy in our PBMC dataset with 75 genes. Conclusions: Our machine learning pipeline was effective at identifying a small set of diagnostic gene biomarkers and classifying several liver diseases using RNA-seq data from liver tissue and PBMCs. The methodologies implemented and genes identified in this study may facilitate future efforts toward a liquid biopsy diagnostic for liver diseases. Lay summary: Distinguishing between inflammatory liver diseases without multiple tests can be challenging due to their clinically similar characteristics. To lay the groundwork for the development of a non-invasive blood-based diagnostic across a range of liver diseases, we compared samples from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, and non-alcohol-associated fatty liver disease. We used a machine learning computational approach to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to discover a small set of gene biomarkers for effective diagnosis of these liver diseases.

The promising immune checkpoint LAG-3 in cancer immunotherapy: from basic research to clinical application.

LAG-3, a type of immune checkpoint receptor protein belonging to the immunoglobulin superfamily, is confirmed to be expressed on activated immune cells, mainly including activated T cells. LAG-3 can negatively regulate the function of T cells, exerting important effects on maintaining the homeostasis of the immune system under normal physiological conditions and promoting tumor cells immune escape in the tumor microenvironment. Given its important biological roles, LAG-3 has been regarded as a promising target for cancer immunotherapy. To date, many LAG-3 inhibitors have been reported, which can be divided into monoclonal antibody, double antibody, and small molecule drug, some of which have entered the clinical research stage. LAG-3 inhibitors can negatively regulate and suppress T cell proliferation and activation through combination with MHC II ligand. Besides, LAG-3 inhibitors can also affect T cell function via binding to Galectin-3 and LSECtin. In addition, LAG-3 inhibitors can prevent the FGL1-LAG-3 interaction, thereby enhancing the human body's antitumor immune effect. In this review, we will describe the function of LAG-3 and summarize the latest LAG-3 inhibitors in the clinic for cancer therapy.

Prognostic Effect of Thoracic Sarcopaenia on Short- and Long-Term Clinical Outcomes in Patients Who Underwent Cardiac Valve Surgery.

BACKGROUND: As the proportion of elderly patients increases, higher incidence of malnutrition is found among patients with valvular heart disease. Sarcopaenia is one of the main manifestations of malnutrition. Studies have shown the certain predictive effect of sarcopaenia on the clinical outcome in different cases. This study aims to clarify the impact of computed tomography (CT)-derived thoracic sarcopaenia on clinical outcomes of patients who underwent cardiac valve surgery. METHODS: The clinical data of 216 patients who underwent cardiac valve surgery from December 2015 to June 2020 were retrospectively collected. Skeletal muscle mass at 12th thoracic vertebra level was measured to diagnose thoracic sarcopaenia. Postoperative complications and follow-up data were collected. Medium follow-up was 3.2 years. RESULTS: The prevalence of thoracic sarcopaenia was 16.7% in this study. The incidence of total complications and in-hospital mortality were higher in thoracic sarcopaenia group (p=0.024 and p=0.014, respectively). Multivariate analysis revealed that thoracic sarcopaenia is a significant predictor for postoperative complications (OR 2.319; 95% CI 1.003-5.366; p=0.049). Decreased long-term survival was observed in patients with thoracic sarcopaenia. Thoracic sarcopaenia (HR 4.178; 95% CI 2.062-8.465; p<0.001) was determined to be an independent risk factor for late mortality. CONCLUSION: Thoracic sarcopaenia defined by chest CT was independently associated with higher incidence of postoperative complications and long-term mortality. Routine preoperative evaluation of thoracic sarcopaenia deserves further consideration to enhance the predictive performance for operation risk.

Development and Validation of Global Leadership Initiative on Malnutrition for Prognostic Prediction in Patients Who Underwent Cardiac Surgery.

The Global Leadership Initiative on Malnutrition (GLIM) has achieved a consensus for the diagnosis of malnutrition in recent years. This study aims to determine the prognostic effect of the GLIM after cardiac surgery. A total of 603 patients in the training cohort and 258 patients in the validation cohort were enrolled in this study. Perioperative characteristics and follow-up data were collected. A nomogram based on independent prognostic predictors was developed for survival prediction. In total, 114 (18.9%) and 48 (18.6%) patients were defined as being malnourished according to the GLIM criteria in the two cohorts, respectively. Multivariate regression analysis showed that GLIM-defined malnutrition was an independent risk factor of total complication (OR 1.661, 95% CI: 1.063-2.594) and overall survival (HR 2.339, 95% CI: 1.504-3.637). The c-index was 0.72 (95% CI: 0.66-0.79) and AUC were 0.800, 0.798, and 0.780 for 1-, 2-, and 3-year survival prediction, respectively. The calibration curves of the nomogram fit well. In conclusion, GLIM criteria can efficiently identify malnutrition and has a prognostic effect on clinical outcomes after cardiac surgery. GLIM-based nomogram has favorable performance in survival prediction.

Endolymphatic Hydrop Phenotype in Familial Norrie Disease Caused by Large Fragment Deletion of NDP.

Norrie disease (ND; OMIM 310600), a rare X-linked recessive genetic disorder, is characterized by congenital blindness and occasionally, sensorineural hearing loss, and developmental delay. The congenital blindness of ND patients is almost untreatable; thus, hearing is particularly important for them. However, the mechanism of hearing loss of ND patients is unclear, and no good treatment is available except wearing hearing-aid. Therefore, revealing the mechanism of hearing loss in ND patients and exploring effective treatment methods are greatly important. In addition, as a serious monogenic genetic disease, convenient gene identification method is important for ND patients and their family members, as well as prenatal diagnosis and preimplantation genetic diagnosis to block intergenerational transmission of pathogenic genes. In this study, a Norrie family with two male patients was reported. This pedigree was ND caused by large fragment deletion of NDP (norrin cystine knot growth factor NDP) gene. In addition to typical severe ophthalmologic and audiologic defects, the patients showed new pathological features of endolymphatic hydrops (EH), and they also showed acoustic nerves abnormal as described in a very recent report. PCR methods were developed to analyze and diagnose the variation of the family members. This study expands the understanding of the clinical manifestation and pathogenesis of ND and provides a new idea for the treatment of patients in this family and a convenient method for the genetic screen for this ND family.