D-SAT: dual semantic aggregation transformer with dual attention for medical image segmentation

Objective. Medical image segmentation is significantly essential to assist clinicians in facilitating a quick and accurate diagnoses. However, most of the existing methods are still challenged by the loss of semantic information, blurred boundaries and the huge semantic gap between the encoder and decoder.Approach. To tackle these issues, a dual semantic aggregation transformer with dual attention is proposed for medical image segmentation. Firstly, the dual-semantic feature aggregation module is designed to build a bridge between convolutional neural network (CNN) and Transformer, effectively aggregating CNN's local feature detail ability and Transformer's long-range modeling ability to mitigate semantic information loss. Thereafter, the strip spatial attention mechanism is put forward to alleviate the blurred boundaries during encoding by constructing pixel-level feature relations across CSWin Transformer blocks from different spatial dimensions. Finally, a feature distribution gated attention module is constructed in the skip connection between the encoder and decoder to decrease the large semantic gap by filtering out the noise in low-level semantic information when fusing low-level and high-level semantic features during decoding.Main results. Comprehensive experiments conducted on abdominal multi-organ segmentation, cardiac diagnosis, polyp segmentation and skin lesion segmentation serve to validate the generalization and effectiveness of the proposed dual semantic aggregation transformer with dual attention (D-SAT). The superiority of D-SAT over current state-of-the-art methods is substantiated by both subjective and objective evaluations, revealing its remarkable performance in terms of segmentation accuracy and quality.Significance. The proposed method subtly preserves the local feature details and global context information in medical image segmentation, providing valuable support to improve diagnostic efficiency for clinicians and early disease control for patients. Code is available athttps://github.com/Dxkm/D-SAT.

Precision nephrotoxicity testing using 3D in vitro models

Nephrotoxicity is a significant concern during the development of new drugs or when assessing the safety of chemicals in consumer products. Traditional methods for testing nephrotoxicity involve animal models or 2D in vitro cell cultures, the latter of which lack the complexity and functionality of the human kidney. 3D in vitro models are created by culturing human primary kidney cells derived from urine in a 3D microenvironment that mimics the fluid shear stresses of the kidney. Thus, 3D in vitro models provide more accurate and reliable predictions of human nephrotoxicity compared to existing 2D models. In this review, we focus on precision nephrotoxicity testing using 3D in vitro models with human autologous urine-derived kidney cells as a promising approach for evaluating drug safety.

[Investigating ocular parameters for predicting anomalous vault among phakic intraocular lens patients]

Objective: To analyze the relationships between preoperative ocular parameters and postoperative anomalous vaults, and research their predictive diagnostic value. Methods: In this retrospective case series study, 664 eyes from 332 patients underwent posterior chamber phakic intraocular lens (pIOL) implantation at Shanghai Bright Eye Hospital and Wuxi Huaxia Eye Hospital from November 2020 to November 2021. Preoperative ocular parameters, including spherical equivalent, intraocular pressure, horizontal/vertical ciliary sulcus diameters (HCS/VCS), white-to-white diameters (WTW), corneal steep/flat curvature, central corneal thickness, anterior chamber depth (ACD), lens thickness (LT), and axial length were collected. The pIOL vaults were measured 3 months after surgery. Patients were categorized into low vault group, optimal vault group, and high vault group based on whether the vault fell within the ideal range (250 to 750 μm). Using the optimal vault group as a benchmark, receiver operating characteristic (ROC) curves were drawn for each ocular parameter of the low and high vault groups to analyze diagnostic efficiency and cut-off values for abnormal vaults after pIOL operation. Each ocular parameter was used as an independent variable to establish a multivariate logistic regression model for two different vault anomalies. ROC curves were drawn and analyzed again based on the regression results. Results: Statistically significant differences were observed in WTW, HCS-WTW, ACD, and LT among the three groups. Comparisons between each pair of groups indicated that WTW in the high vault group significantly differed from the other two groups (P<0.05), HCS-WTW in the low vault group significantly differed from the other groups (P<0.05), and ACD and LT explained statistical differences among the three groups (P<0.05), while other parameters showed no differences. ROC curves illustrated that independent ocular parameters such as LT, HCS-WTW, and ACD had clinical predictive diagnostic significance for low vault abnormalities. The area under the curve (AUC), sensitivity, and specificity for these parameters were 0.829(0.952, 0.561), 0.745(0.857, 0.644), and 0.730(0.619, 0.853), respectively. The diagnostic cut-off values were 3.745, 0.020, and 2.975 mm, respectively. The clinical predictive significance of independent ocular parameters in diagnosing the high vault group was poor (AUC<0.7). The predictive Logistic model equation for low vault was Logistic(V1)=-10.067+5.328·HCS-3.620·WTW+6.263·LT, and the predictive model for high vault was Logistic(V2)=6.232+1.323·WTW-3.358·LT. The new parameters in the predictive equation significantly improved the diagnostic efficiency of low and high vault abnormalities, reaching 0.884(0.810, 0.824) and 0.736(0.810, 0.554), respectively. Conclusions: Preoperative predictive diagnostic parameters for postoperative low vault group included LT, HCS-WTW, and ACD, while the high vault group had no independent predictive diagnostic parameters. Logistic regression improved the predictive diagnostic efficiency of abnormal vaults.

Mapping and modeling human colorectal carcinoma interactions with the tumor microenvironment

The initiation and progression of cancer are intricately linked to the tumor microenvironment (TME). Understanding the function of specific cancer-TME interactions poses a major challenge due in part to the complexity of the in vivo microenvironment. Here we predict cancer-TME interactions from single cell transcriptomic maps of both human colorectal cancers (CRCs) and mouse CRC models, ask how these interactions are altered in human tumor organoid (tumoroid) cultures, and functionally recapitulate human myeloid-carcinoma interactions in vitro. Tumoroid cultures suppress gene expression programs involved in inflammation and immune cell migration, providing a reductive platform for re-establishing carcinoma-immune cell interactions in vitro. Introduction of human monocyte-derived macrophages into tumoroid cultures instructs macrophages to acquire immunosuppressive and pro-tumorigenic gene expression programs similar to those observed in vivo. This includes hallmark induction of SPP1, encoding Osteopontin, an extracellular CD44 ligand with established oncogenic effects. Taken together, these findings offer a framework for understanding CRC-TME interactions and provide a reductionist tool for modeling specific aspects of these interactions.

Simulation Investigation on the Influence Mechanism of Toluene and Heptane on the Aggregation of Asphaltene Molecules

Asphaltenes are a group of compounds that are soluble in benzene and toluene but insoluble in nonpolar small molecule n-alkanes. The asphaltene aggregation in the asphaltene-heptane-toluene system was studied using molecular dynamics (MD) simulation, and the interaction between asphaltene molecules during this process was also revealed from the evolution of the density field, radial distribution function (RDF), and intermolecular distance of asphaltenes. Three main findings were made: (1) more asphaltene precipitates (heptane) were contained, and more asphaltene dimers or trimers were formed during the MD simulation; (2) asphaltene molecules interacted with each other to form aggregates in the form of π-π or H-bond interaction. The stable distance of the π-π interaction was 3.3-3.5 Å, and the stable distance of the H-bond connection was 1.7-1.9 Å. (3) The asphaltene interaction in the heptane-rich system was dominated by π-π interaction between asphaltene molecules. However, the asphaltene interactions in the toluene-rich system were mainly the π-π interaction between asphaltene molecules and toluene and the H-bond interaction between the side chains of asphaltene molecules. The results of this study can aid in understanding how asphaltene molecules aggregate and self-associate and can also offer theoretical support for flow assurance in systems used to produce crude oil.

GPR35 acts a dual role and therapeutic target in inflammation

GPR35 is a G protein-coupled receptor with notable involvement in modulating inflammatory responses. Although the precise role of GPR35 in inflammation is not yet fully understood, studies have suggested that it may have both pro- and anti-inflammatory effects depending on the specific cellular environment. Some studies have shown that GPR35 activation can stimulate the production of pro-inflammatory cytokines and facilitate the movement of immune cells towards inflammatory tissues or infected areas. Conversely, other investigations have suggested that GPR35 may possess anti-inflammatory properties in the gastrointestinal tract, liver and certain other tissues by curbing the generation of inflammatory mediators and endorsing the differentiation of regulatory T cells. The intricate role of GPR35 in inflammation underscores the requirement for more in-depth research to thoroughly comprehend its functional mechanisms and its potential significance as a therapeutic target for inflammatory diseases. The purpose of this review is to concurrently investigate the pro-inflammatory and anti-inflammatory roles of GPR35, thus illuminating both facets of this complex issue.

[Advances in clinical significance and detection methods research of high density lipoprotein subfractions]

High density lipoprotein (HDL) is an important biochemical index of clinical cardiovascular disease. Many new studies have demonstrated abnormalities of plasma HDL subfractions in patients with this disease,and their clinical significance is greater than the overall abnormalities of HDL. Therefore,the HDL subfraction as an important factor in cardiovascular disease has attracted extensive research and attention. This article summarizes current research on HDL subfractions,their measurements and their relationships with atherosclerosis and coronary artery disease.

SOX combined with sintilimab versus SOX alone in the perioperative management of locally advanced gastric cancer: a propensity score-matched analysis

OBJECTIVES

To evaluate the efficacy of SOX combined with a programmed cell death protein-1 (PD-1) inhibitor compared with SOX alone in the perioperative management of locally advanced gastric cancer and to explore biomarkers that may predict response to anti-PD-1 therapy.

METHODS

Data of patients with clinical stage T3-4aN0-3M0 (IIb-III) gastric cancer were reviewed to create a primary database. Patients treated with perioperative SOX combined with sintilimab were included in Group A, while those treated with SOX alone were included in Group B. After one-to-one propensity score matching, pathological response and short-term survival outcomes were compared between the two groups. In addition, potential efficacy-related biomarkers were analyzed.

RESULTS

Between January 2018 and December 2022, a total of 150 patients were included in the analysis, with 75 patients in each group. The rates of pathological complete response (21.3% vs. 4.0%; P = 0.001) and major pathological response (45.3% vs. 22.7%; P = 0.003) in Group A were statistically higher than those in Group B. There was no significant difference in 1-year overall survival (92.8% vs. 92.0%; P = 0.392) and disease-free survival (88.9% vs. 88.0%; P = 0.357) between the two groups. Subgroup analysis of Group A showed that the pathological complete response (40.6% vs. 8.6%; P = 0.002) and major pathological response (65.6% vs. 28.6%; P = 0.002) rates were significantly higher in programmed death ligand-1-positive patients with a combined positive score of ≥ 5. A pathological complete response was achieved in 42.9% patients (3/7) with mismatch repair deficiency. For the two patients confirmed as Epstein-Barr virus-positive, one patient achieved a pathological complete response and the other achieved a major pathological response.

CONCLUSIONS

The adoption of SOX combined with a PD-1 inhibitor may improve the pathological response rate of patients with locally advanced gastric cancer, especially those with programmed death ligand-1 combined positive score ≥ 5, Epstein-Barr virus-positivity and mismatch repair deficiency. However, further prospective studies are still warranted to confirm the long-term survival benefit.

Characterization and properties of manganese oxide film coated clinoptilolite as filter material in fixed-bed columns for removal of Mn(II) from aqueous solution

A new filter material, manganese oxide film coated clinoptilolite (MOFCC), was characterized and introduced to explore the effect in treating high concentration of manganese (1.71-2.12 mg L-1) from aqueous solution in fixed-bed column. Adsorption behavior of Mn(II) can be approximately described with the Langmuir isotherm. During the continuous 30 days filtration experiment, the removal rate of Mn(II) has maintained to be above 95.51%, the accumulated removal amount (806.42 mg) is much higher than the theoretical adsorption capacity (89.71 mg), which indicated that the removal of manganese by MOFCC includes both adsorption and auto-catalytic oxidation process, and it does not require a start-up period. SEM, EDS, XPS, XRD, ZETA potential and BET analyses were used to observe the surface properties of MOFCC. The manganese oxide film of MOFCC exhibits in clusters, apparently on occupied surface, the main component of the manganese oxide film is (Na0.7Ca0.3)Mn7O14·2.8H2O, the specific surface area of MOFCC is 38.76 m2 g-1, and the pore size is concentrated in the range of 3-40 nm, within the mesoporous range mesopores. pHpzc (point of zero charge) value is about 2.36. The characteristics of MOFCC make it an excellent manganese removal filter material for water treatment plant. Therefore, there is a long-term practical significance to develop new system for deep removal of manganese based on MOFCC.

Prediction of recurrent ischaemic stroke using radiomics data and machine learning methods in patients with acute ischaemic stroke: protocol for a multicentre, large sample, prospective observational cohort study in China

INTRODUCTION

Stroke is a leading cause of mortality and disability worldwide. Recurrent strokes result in prolonged hospitalisation and worsened functional outcomes compared with the initial stroke. Thus, it is critical to identify patients who are at high risk of stroke recurrence. This study is positioned to develop and validate a prediction model using radiomics data and machine learning methods to identify the risk of stroke recurrence in patients with acute ischaemic stroke (AIS).

METHODS AND ANALYSIS

A total of 1957 patients with AIS will be needed. Enrolment at participating hospitals will continue until the required sample size is reached, and we will recruit as many participants as possible. Multiple indicators including basic clinical data, image data, laboratory data, CYP2C19 genotype and follow-up data will be assessed at various time points during the registry, including baseline, 24 hours, 7 days, 1 month, 3 months, 6 months, 9 months and 12 months. The primary outcome was stroke recurrence. The secondary outcomes were death events, prognosis scores and adverse events. Imaging images were processed using deep learning algorithms to construct a programme capable of automatically labelling the lesion area and extracting radiomics features. The machine learning algorithms will be applied to integrate cross-scale, multidimensional data for exploratory analysis. Then, an ischaemic stroke recurrence prediction model of the best performance for patients with AIS will be established. Calibration, receiver operating characteristic and decision curve analyses will be evaluated.

ETHICS AND DISSEMINATION

This study has received ethical approval from the Medical Ethics Committee of the Second Affiliated Hospital of Nanchang University (medical research review No.34/2021), and informed consent will be obtained voluntarily. The research findings will be disseminated through publication in journals and presented at conferences.

TRIAL REGISTRATION NUMBER

ChiCTR2200055209.

Logic gate-driven dual-index balanced visualization strategy for tumor metastasis diagnosis

Exfoliated tumor cells are integral to malignant tumors diagnosis. The process of clinical cytology of exfoliation involves several complex steps that require at least two days of preparation. Here, we develop a balanced-etching visual kit based on concentration differences of Glutathione/Glucose (GSH/Glu) to distinguish normal from exfoliated tumor cells rapidly and accurately. The balanced-etching visualization kit can be used to obtain color cards and screen exfoliated tumor cells initially (within 10 min). Furthermore, by utilizing logic gates and machine learning algorithms for RGB extraction of the color card obtained from the kit, accurate screening of exfoliated tumor cells is achieved. Finally, a series of clinical tumor samples, such as urine, pleural fluids, ascites, and gastric fluids, have been validated. With effective experimental methods, accurate disease information, and appropriate therapeutic programs, the novel diagnostic strategy is expected to promote precision medicine.

PMJAF-Net: Pyramidal multi-scale joint attention and adaptive fusion network for explainable skin lesion segmentation

Traditional convolutional neural networks have achieved remarkable success in skin lesion segmentation. However, the successive pooling operations and convolutional spans reduce the feature resolution and hinder the dense prediction for spatial information, resulting in blurred boundaries, low accuracy and poor interpretability for irregular lesion segmentation under low contrast. To solve the above issues, a pyramidal multi-scale joint attention and adaptive fusion network for explainable (PMJAF-Net) skin lesion segmentation is proposed. Firstly, an adaptive spatial attention module is designed to establish the long-term correlation between pixels, enrich the global and local contextual information, and refine the detailed features. Subsequently, an efficient pyramidal multi-scale channel attention module is proposed to capture the multi-scale information and edge features by using the pyramidal module. Meanwhile, a channel attention module is devised to establish the long-term correlation between channels and highlight the most related feature channels to capture the multi-scale key information on each channel. Thereafter, a multi-scale adaptive fusion attention module is put forward to efficiently fuse the scale features at different decoding stages. Finally, a novel hybrid loss function based on region salient features and boundary quality is presented to guide the network to learn from map-level, patch-level and pixel-level and to accurately predict the lesion regions with clear boundaries. In addition, visualizing attention weight maps are utilized to visually enhance the interpretability of our proposed model. Comprehensive experiments are conducted on four public skin lesion datasets, and the results demonstrate that the proposed network outperforms the state-of-the-art methods, with the segmentation assessment evaluation metrics Dice, JI, and ACC improved to 92.65%, 87.86% and 96.26%, respectively.

Hyperthermic intraperitoneal chemotherapy (HIPEC) plus systemic chemotherapy versus systemic chemotherapy alone in locally advanced gastric cancer after D2 radical resection: a randomized-controlled study

BACKGROUND

Currently, there is a lack of an effective strategy for the prevention of peritoneal metastasis (PM) from locally advanced gastric cancer (AGC). This randomized-controlled study aimed to evaluate the outcome of D2 radical resection with hyperthermic intraperitoneal chemotherapy (HIPEC) plus systemic chemotherapy versus systemic chemotherapy alone in locally AGC patients.

METHODS

All enrolled patients were randomly assigned to receive HIPEC plus systemic chemotherapy (HIPEC group) or systemic chemotherapy alone (non-HIPEC group) after radical gastrectomy. HIPEC was performed intraperitoneally with cisplatin (40 mg/m2) within 72 h after surgery, while systemic chemotherapy based on the SOX regimen (S-1 combined with oxaliplatin) was administered 4-6 weeks after radical surgery. Patterns of recurrence, adverse events, 3-year disease-free survival (DFS), and overall survival (OS) were analyzed.

RESULTS

A total of 134 patients were enrolled in the present study. The 3-year DFS rate was 73.8% in the HIPEC group, which was significantly higher than that in the non-HIPEC group (61.2%, P = 0.031). The 3-year OS rate was 73.9% in the HIPEC group and 77.6% in the non-HIPEC group, with no significant difference (P = 0.737). PM was the most common distant metastasis in both groups. The occurrence rate of PM in the HIPEC group was statistically lower than that in the non-HIPEC group (20.9% vs. 40.3%, P = 0.015). Grade 3 or 4 adverse events occurred in 19 (14.2%) patients, and there was no significant difference between the two groups.

CONCLUSION

Radical surgery followed by HIPEC combined with systemic chemotherapy is a safe and feasible strategy for locally AGC patients and could effectively improve DFS and reduce the occurrence of PM. However, more prospective randomized studies with a large sample size are warranted.

TRIAL REGISTRATION

This study was registered with www.medresman.org.cn as ChiCTR2200055966 on 10/12/2016.

Insights into the mechanisms of natural organic matter on the photodegradation of indomethacin under natural sunlight and simulated light irradiation

Indomethacin (INDO) is an antipyretic and analgesic pharmaceutical that has been widely detected in the aquatic environment. Photodegradation is an essential pathway for removal of INDO in sunlit surface water, however the effect of dissolved organic matter (DOM) on its photodegradation and the ecotoxicity of photodegradation products are largely unknown. In this study, the effect of DOM on the photodegradation of INDO under both natural and simulated light irradiation was studied. The results showed that indirect photolysis is the main photodegradation pathway of INDO in presence of DOM where 3DOM* plays the most important promoting role. Compared to commercial DOM (SRNOM and SRFA), DOM extracted from local-lake water (SLDOM) promoted the photodegradation to the highest extent. Although the steady-state concentrations of 3DOM* of SRNOM and SRFA were higher than SLDOM, their inhibition effect surpassed SLDOM namely higher light screening effect and phenolic antioxidant concentrations. The photodegradation pathway in pure water is different from that in DOM system where the decarboxylation of acetic acid chain and the oxidative fracture of indole ring are the main degradation pathways. Density Functional Theory (DFT) calculation further supports the proposed degradation pathways of INDO. ECOSAR calculation showed that the toxicity of INDO photodegradation products to aquatic organisms may maintain or even exceed its parent compound. Therefore, comprehensive understanding of the impact of DOM on the photodegradation of INDO is of crucial significance for evaluating its ecological risk in the natural environment.

Immortalization-upregulated protein promotes pancreatic cancer progression by regulating NPM1/FHL1-mediated cell-cycle-checkpoint protein activity

Immortalization-upregulated protein (IMUP) plays a vital role in cell proliferation and tumor progression. However, its role in pancreatic ductal adenocarcinoma (PDAC) remains unclear. Here, we select IMUP as an alternative gene based on GeneChip analysis of clinical PDAC tissues and transcriptome data from The Cancer Genome Atlas. IMUP expression is upregulated in PDAC tumor tissues. Moreover, high IMUP expression correlates with poor prognosis, while IMUP depletion inhibits PDAC cell proliferation and colony formation capacity in vitro, and decreases xenograft tumor growth in vivo. IMUP downregulation leads to cell-cycle arrest in the S phase. IMUP knockdown increases the expression of four-and-a-half LIM domain protein 1 (FHL1), which regulates the phosphorylation of cell division cycle 25A (CDC25A) by cycle checkpoint kinase 1 (CHK1) and promotes cytoplasmic distribution of CDC25A by interaction with 14-3-3ξ. Furthermore, FHL1 knockdown restores the effects induced by IMUP depletion. Liquid chromatography tandem mass spectrometry and immunoprecipitation analysis further show that IMUP interacts directly with nucleophosmin (NPM1) and enhances its stability. DNA methylation sequencing shows that FHL1 promoter methylation decreases when IMUP is downregulated. Overexpression of NPM1 can increase the methylation level of FHL1, thereby decreasing its expression. Our study provides a novel perspective on IMUP/NPM1/FHL1-mediated cell-cycle arrest by regulating CDC25A phosphorylation in PDAC. These findings may provide a new therapeutic target for PDAC.

Screening of Ginkgo Individuals with Superior Growth Structural Characteristics in Different Genetic Groups Using Terrestrial Laser Scanning (TLS) Data

With the concept of sustainable management of plantations, individual trees with excellent characteristics in plantations have received attention from breeders. To improve and maintain long-term productivity, accurate and high-throughput access to phenotypic characteristics is essential when establishing breeding strategies. Meanwhile, genetic diversity is also an important issue that must be considered, especially for plantations without seed source information. This study was carried out in a ginkgo timber plantation. We used simple sequence repeat (SSR) markers for genetic background analysis and high-density terrestrial laser scanning for growth structural characteristic extraction, aiming to provide a possibility of applying remote sensing approaches for forest breeding. First, we analyzed the genetic diversity and population structure, and grouped individual trees according to the genetic distance. Then, the growth structural characteristics (height, diameter at breast height, crown width, crown area, crown volume, height to living crown, trunk volume, biomass of all components) were extracted. Finally, individual trees in each group were comprehensively evaluated and the best-performing ones were selected. Results illustrate that terrestrial laser scanning (TLS) point cloud data can provide nondestructive estimates of the growth structural characteristics at fine scale. From the ginkgo plantation containing high genetic diversity (average polymorphism information content index was 0.719) and high variation in growth structural characteristics (coefficient of variation ranged from 21.822% to 85.477%), 11 excellent individual trees with superior growth were determined. Our study guides the scientific management of plantations and also provides a potential for applying remote sensing technologies to accelerate forest breeding.

Comparison of the Predictive Value of Inflammatory Biomarkers for the Risk of Stroke-Associated Pneumonia in Patients with Acute Ischemic Stroke

Purpose

To investigate the predictive value of various inflammatory biomarkers in patients with acute ischemic stroke (AIS) and evaluate the relationship between stroke-associated pneumonia (SAP) and the best predictive index.

Patients and Methods

We calculated the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), prognostic nutritional index (PNI), systemic inflammation response index (SIRI), systemic immune inflammation index (SII), Glasgow prognostic score (GPS), modified Glasgow prognostic score (mGPS), and prognostic index (PI). Variables were selectively included in the logistic regression analysis to explore the associations of NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI with SAP. We assessed the predictive performance of biomarkers by analyzing receiver operating characteristic (ROC) curves. We further used restricted cubic splines (RCS) to investigate the association. Next, we conducted subgroup analyses to investigate whether specific populations were more susceptible to NLR.

Results

NLR, PLR, MLR, SIRI, SII, GPS, mGPS, and PI increased significantly in SAP patients, and PNI was significantly decreased. After adjustment for potential confounders, the association of inflammatory biomarkers with SAP persisted. NLR showed the most favorable discriminative performance and was an independent risk factor predicting SAP. The RCS showed an increasing nonlinear trend of SAP risk with increasing NLR. The AUC of the combined indicator of NLR and C-reactive protein (CRP) was significantly higher than those of NLR and CRP alone (DeLong test, P<0.001). Subgroup analyses suggested good generalizability of the predictive effect.

Conclusion

NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI can predict the occurrence of SAP. Among the indices, the NLR was the best predictor of SAP occurrence. It can therefore be used for the early identification of SAP.

A pan-cancer analysis of potassium channel tetramerization domain containing 12 in human cancer

Abnormal expression of the potassium channel tetramerization domain containing 12 (KCTD12) is closely related to the occurrence and development of various tumors, but a pan-cancer analysis of KCTD12 has not yet been conducted. We explored the association between KCTD12 and more than 30 human malignancies using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. First, the mRNA and protein levels of KCTD12 were examined and their correlations with tumor stage and survival were explored. Second, we analyzed the infiltration of CD8+ and CD4+ T cells and cancer-associated fibroblasts in tumors and explored the correlation between KCTD12 expression and tumor cell stemness, genomic heterogeneity, and diagnostic specificity. Finally, we explored the molecular mechanisms associated with KCTD12 using KEGG/GO analysis. The results showed that KCTD12 mRNA and protein expression levels decreased in most tumors was significantly associated with the prognosis of tumor patients, and the phosphorylation level of KCTD12 decreased in several tumors, such as S200 and T196, pancreatic adenocarcinoma (PAAD), lung adenocarcinoma (LUAD), and breast invasive cancer (BRCA). The expression of KCTD12 was positively correlated with the degree of cancer-associated fibroblasts infiltration in cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC), head and neck squamous cell carcinoma (HNSC), PAAD, and stomach adenocarcinoma (STAD). The relationship between KCTD12 expression and CD8+ and CD4+ T cell infiltration was also clarified. KCTD12 showed high diagnostic sensitivity for various types of tumors and may be involved in tumor cell biology by affecting tumor cell stemness, tumor burden, and other characteristics. Finally, we analyzed the molecular functions of KCTD12 and possible KEGG/GO signaling pathways. In this study, we developed a biological marker for diagnosis, prognosis, and immune infiltration of the pan-cancers.

Identification and In Silico Analysis of ACE-Inhibitory Peptides Derived from Milk Fermented by Lacticaseibacillus paracasei

Inhibition of angiotensin I-converting enzyme (ACE) activity is an effective way to treat hypertension. In the present study, the ability to produce ACE-inhibitory peptides during fermentation of skimmed milk by the Lacticaseibacillus paracasei M3 strain was evaluated, and the inhibitory mechanism and stability were studied by bioinformatics analysis. The results showed that the ACE inhibition activity of fermented milk was 71.94 ± 1.39%. After digestion with gastric juice and pancreatic juice, the ACE inhibitory activities of the fermented milk were 78.40 ± 1.93 and 74.96 ± 1.73%, respectively. After the fermented milk was purified using ultrafiltration and gel chromatography, 11 peptides from milk proteins were identified and sequenced by Nano LC-MS/MS. Molecular docking displayed that peptide PWIQPK had a high affinity, with ACE showing a binding energy of -6.10 kcal/mol. Hydrogen bonds were formed between PWIQPK and Glu384 in the S1 active pocket of ACE and Asp358. In addition, van der Waals forces were observed. In silico proteolysis suggested that PWIQPK could resist the digestion of pepsin and trypsin, indicating that it is relatively stable in the digestive tract. All results indicate that milk fermented by L. paracasei M3 has the potential to be used as a functional food having antihypertensive effects.

Efficacy of chemotherapy combined with surgical resection for gastric cancer with synchronous ovarian metastasis: A propensity score matching analysis

BACKGROUND

Ovarian metastasis from gastric cancer (GC) is characterized by aggressive biological behavior and poor outcome. Currently, there is no standard treatment mode for such patients. Thus, we evaluated the efficacy of conversion therapy in patients with synchronous ovarian metastasis from GC in this study.

METHODS

About 219 GC patients with ovarian metastasis in 2011-2020 were enrolled. Two groups were established based on the different treatment: the conversion therapy group (chemotherapy combined with surgical resection, CS group) and the non-conversion therapy group (NCS group). Propensity score matching (PSM) was used to analyze the efficacy of different treatment modes on the prognosis of these patients.

RESULTS

Ninety-two patients were included according to PSM results, with 46 patients each in CS and NCS groups. The median overall survival (OS) in the CS group was notably better than that in the NCS group (p < 0.001). Twenty-six patients (56.52%) in the CS group achieved R0 resection, and they had a better prognosis (p = 0.003). Compared with patients who underwent simultaneous gastrectomy and ovarian metastasectomy (CSb group), those who underwent ovarian metastasectomy before systemic chemotherapy (CSa group) had a higher R0 resection rate (p = 0.016) and longer survival time (p = 0.002). A total of 38 patients (41.30%) across both groups received hyperthermic intraperitoneal chemotherapy (HIPEC), and these patients had a better survival (p = 0.043).

CONCLUSION

The conversion therapy is safe and effective for patients with synchronous ovarian metastasis from GC and can improve their prognosis. However, our results need to be confirmed by more randomized controlled clinical studies.

Comprehensive Detection of PD-L1 Protein and mRNA in Tumor Cells and Extracellular Vesicles through a Real-Time qPCR Assay

A growing number of studies have shown that tumor cells secrete extracellular vesicles (EVs) containing programmed death-ligand 1 (PD-L1) protein. These vesicles can travel to lymph nodes and remotely inactivate T cells, thereby evading immune system attack. Therefore, the simultaneous detection of PD-L1 protein expression in cells and EVs is of great significance in guiding immunotherapy. Herein, we developed a method based on qPCR for the simultaneous detection of PD-L1 protein and mRNA in EVs and their parental cells (PREC-qPCR assay). Lipid probes immobilized on magnetic beads were used to capture EVs directly from samples. For RNA assay, EVs were directly broken by heating and quantified with qPCR. As to protein assay, EVs were recognized and bound with specific probes (such as aptamers), which were used as templates in subsequent qPCR analysis. This method was used to analyze EVs of patient-derived tumor clusters (PTCs) and plasma samples from patients and healthy volunteers. The results revealed that the expression of exosomal PD-L1 in PTCs was correlated with tumor types and significantly higher in plasma-derived EVs from tumor patients than that of healthy individuals. When extended to cells and PD-L1 mRNAs, the results showed that the expression of PD-L1 protein was consistent with mRNA in cancer cell lines, while PTCs demonstrated significant heterogeneity. This comprehensive detection of PD-L1 at four levels (cell, EVs, protein, and mRNA) is believed to enhance our understanding of the relationship among PD-L1, tumors, and the immune system and to provide a promising tool for predicting the benefits of immunotherapy.

Tailoring Electronic Structure to Achieve Maximum Utilization of Transition Metal Redox for High-Entropy Na Layered Oxide Cathodes

Charge compensation from cationic and anionic redox couples accompanying Na⁺ (de)intercalation in layered oxide cathodes contributes to high specific capacity. However, the engagement level of different redox couples remains unclear and their relationship with Na⁺ content is less studied. Here we discover that it is possible to take full advantage of the high-voltage transition metal (TM) redox reaction through low-valence cation substitution to tailor the electronic structure, which involves an increased ratio of Na⁺ content to available charge transfer number of TMs. Taking Na_xCu_0.11Ni_0.11Fe_0.3Mn_0.48O₂ as the example, the Li⁺ substitution increases the ratio to facilitate the high-voltage TM redox activity, and further F-ion substitution decreases the covalency of the TM-O bond to relieve structural changes. As a consequence, the final high-entropy Na_0.95Li_0.07Cu_0.11Ni_0.11Fe_0.3Mn_0.41O_1.97F_0.03 cathode demonstrates ∼29% capacity increase contributed by the high-voltage TMs and exhibits excellent long-term cycling stability due to the improved structural reversibility. This work provides a paradigm for the design of high-energy-density electrodes by simultaneous electronic and crystal structure modulation.

High-Temperature Liquid-Liquid Phase Transition in Glass-Forming Liquid Pd43Ni20Cu27P10

Liquid-liquid phase transition (LLPT) is a transition from one liquid state to another with the same composition but distinct structural change, which provides an opportunity to explore the relationships between structural transformation and thermodynamic/kinetic anomalies. Herein the abnormal endothermic LLPT in Pd₄₃Ni₂₀Cu₂₇P₁₀ glass-forming liquid was verified and studied by flash differential scanning calorimetry (FDSC) and ab initio molecular dynamics (AIMD) simulations. The results show that the change of the atomic local structure of the atoms around the Cu-P bond leads to the change in the number of specific clusters <0 2 8 0> and <1 2 5 3>, which leads to the change in the liquid structure. Our findings reveal the structural mechanisms that induce unusual heat-trapping phenomena in liquids and advance the understanding of LLPT.

Therapeutic Benefits of Stem Cells and Exosomes for Sulfur-Mustard-Induced Tissue Damage

Sulfur mustard (SM) is a highly toxic chemical agent that causes severe tissue damage, particularly to the eyes, lungs, and skin. Despite advances in treatment, there is a need for more effective therapies for SM-induced tissue injury. Stem cell and exosome therapies are emerging as promising approaches for tissue repair and regeneration. Stem cells can differentiate into multiple cell types and promote tissue regeneration, while exosomes are small vesicles that can deliver therapeutic cargo to target cells. Several preclinical studies demonstrated the potential of stem cell, exosome, or combination therapy for various tissue injury, showing improvements in tissue repairing, inflammation, and fibrosis. However, there are also challenges associated with these therapies, such as the requirement for standardized methods for exosome isolation and characterization, the long-term safety and efficacy and reduced SM-induced tissue injury of these therapies. Stem cell or exosome therapy was used for SM-induced eye and lung injury. Despite the limited data on the use for SM-induced skin injury, this therapy is a promising area of research and may offer new treatment options in the future. In this review, we focused on optimizing these therapies, evaluating their safety and efficacy, and comparing their efficacy to other emerging therapeutic approaches potentially for SM-induced tissue injury in the eye, lung, and skin.

MCE-Net: Polyp segmentation with multiple branch series-parallel attention and channel interaction via edge distribution guidance

OBJECTIVE

Accurate polyp segmentation is vital for diagnosing colorectal cancer. However, it is still challenging for accurate polyp segmentation and several bottlenecks exist, such as incomplete boundary, localization bias and lack of micro blocks along with large fragmented boundaries in uncertain regions.

APPROACH

To address the above issues, a novel polyp segmentation network with multiple branch series-parallel attention and channel interaction via edge distribution guidance is proposed. Initially, the edge distribution guidance strategy is proposed to generate the edge distribution following Cauchy distribution to capture complementary edges with sufficient details. Subsequently, a multiple branch series-parallel attention (MBSA) module is put forward to extract features from various receptive fields to pinpoint tiny polyps by a multiple kernel dilated convolution block, while combining semantics of different dimensions to filter out noise and refining the details of micro target. Ultimately, the channel interaction model (CIM) is proposed to improve the segmentation accuracy of the polyps in uncertain area by splitting channels into groups and conducts group-wise interaction to excavate subtle clues contained in different channels.

MAIN RESULTS

Extensive experimental results demonstrate that the proposed method is superior over the state-of-the-art methods with the mean dice of 0.8972, 0.9420, 0.8312, 0.8064 and 0.9214 on five public polyp datasets.

SIGNIFICANCE

The proposed method improves the integrity of the margins and internal details for polyp segmentation, which will provide a powerful aid for doctors to achieve accurate judgments, reducing the likelihood of colorectal cancer and improving the survival chances of patients.