Regulatory Mechanism of Sodium/Calcium Ratio on Texture Quality of Kelp Pickle during Shelf-Life Period

This work aims to study the regulatory mechanism of calcium fortification on the texture of kelp pickle during the shelf-life period in order to provide theoretical support for improving its texture quality using exogenous calcium. The effects of fermentation acidity and sodium/calcium ratio on the texture of kelp pickle during its shelf life at 4 ℃ were studied, and the evolution of water distribution and the structure of calcium ion bridge was analyzed. The results showed the hardness of kelp pickle decreased with increasing fermentation acidity, but its changes were effectively slowed down by exogenous calcium lactate. The rate of hardness preservation of kelp pickle with a sodium/calcium of 1.5:1 increased by 92.8% compared with the control group. The results of scanning electron microscopy (SEM) and low-frequency nuclear magnetic resonance (NMR) spectroscopy showed calcium lactate alleviated the morphological damage of kelp tissues caused by acid produced during fermentation, and inhibited the transition of bound water to free water during the shelf-life period. The proportion of free water in kelp pickle with a sodium/calcium ratio of 2:1 increased by only 10.29 percentage points after six months of storage. The results of X-ray photoelectron spectroscopy (XPS) showed that the mechanism by which calcium lactate enhanced the texture of kelp pickle during its shelf-life might be related to the formation of a stable calcium ion bridge at a sodium/calcium ratio of 2:1 or 1.5:1

TEA-PSE 3.0: Tencent-Ethereal-Audio-Lab Personalized Speech Enhancement System For ICASSP 2023 DNS Challenge

This paper introduces the Unbeatable Team's submission to the ICASSP 2023 Deep Noise Suppression (DNS) Challenge. We expand our previous work, TEA-PSE, to its upgraded version -- TEA-PSE 3.0. Specifically, TEA-PSE 3.0 incorporates a residual LSTM after squeezed temporal convolution network (S-TCN) to enhance sequence modeling capabilities. Additionally, the local-global representation (LGR) structure is introduced to boost speaker information extraction, and multi-STFT resolution loss is used to effectively capture the time-frequency characteristics of the speech signals. Moreover, retraining methods are employed based on the freeze training strategy to fine-tune the system. According to the official results, TEA-PSE 3.0 ranks 1st in both ICASSP 2023 DNS-Challenge track 1 and track 2.Comment: Accepted by ICASSP 202

Microbial source tracking identifies sources of contamination for a river flowing into the Yellow Sea

The excessive input of nutrients into rivers can lead to contamination and eutrophication, which poses a threat to the health of aquatic ecosystems. It is crucial to identify the sources of contaminants to develop effective management plans for eutrophication. However, traditional methods for identifying pollution sources have been insufficient, making it difficult to manage river health effectively. High-throughput sequencing offers a novel method for microbial community source tracking, which can help identify dominant pollution sources in rivers. The Wanggang River was selected for study, as it has suffered accelerated eutrophication due to considerable nutrient input from riparian pollutants. The present study identified the dominant microbial communities in the Wanggang River basin, including Proteobacteria, Actinobacteria, Bacteroidetes, Cyanobacteria, Verrucomicrobia, and Firmicutes. The Source Tracker machine-learning classification system was used to create source-specific microbial community fingerprints to determine the primary sources of contaminants in the basin, with agricultural fertilizer being identified as the main pollutant source. By identifying the microbial communities of potential pollution sources, the study determined the contributing pollutant sources in several major sections of the Wanggang River, including industry, urban land, pond culture, and livestock land. These findings can be used to improve the identification of pollution sources in specific environments and develop effective pollution management plans for polluted river water

Time Irreversibility from Time Series for Analyzing Oil-in-Water Flow Transition

We first experimentally collect conductance fluctuation signals of oil-in-water two-phase flow in a vertical pipe. Then we detect the flow pattern asymmetry character from the collected signals with multidimensional time irreversibility and multiscale time irreversibility index. Moreover, we propose a novel criterion, that is, AMSI (average of multiscale time irreversibility), to quantitatively investigate the oil-in-water two-phase flow pattern dynamics. The results show that AMSI is sensitive to the flow pattern evolution that can be used to predict the flow pattern transition and bubble coalescence

Case report: Surgical repair of congenitally corrected transposition of the great arteries with the guidance of three-dimensional printing

A 10-year-old girl presented with obvious cyanosis, and the saturation of arterial blood oxygen (SpO2) was decreased to 60.5% in the outpatient examination. Computed tomography angiography (CTA) and echocardiography suggested congenitally corrected transposition of the great arteries (ccTGAs), membranous ventricular septal aneurysm (MVSA), atrial septal defect (ASD), severe pulmonary stenosis (PS), and severe tricuspid regurgitation (TR). Due to the complex pathological anatomical structures, the three-dimensional printed model was used for preoperative assessment. After a comprehensive evaluation was completed, the operation was performed by physiological correction under cardiopulmonary bypass, including the resection of MVSA, repair using the bovine pericardial patch for ASD, and linear valvuloplasty of the tricuspid valve. Due to the special anatomical structures of ccTGA, PS was treated by extracardiac pipe technique. After the operation, the patient recovered well, cyanosis disappeared, SpO2 was up to 96%, and the extracardiac pipe was well-functioning without regurgitation or obstruction

KNL1 is a prognostic and diagnostic biomarker related to immune infiltration in patients with uterine corpus endometrial carcinoma

BackgroundThe incidence and mortality of uterine corpus endometrial carcinoma (UCEC) are increasing yearly. There is currently no screening test for UCEC, and progress in its treatment is limited. It is important to identify new biomarkers for screening, diagnosing and predicting the outcomes of UCEC. A large number of previous studies have proven that KNL1 is crucial in the development of lung cancer, colorectal cancer and cervical cancer, but there is a lack of studies about the role of KNL1 in the development of UCEC.MethodsThe mRNA and protein expression data of KNL1 in The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and UALCAN databases and related clinical data were used to analyze the expression differences and clinical correlations of KNL1 in UCEC. A total of 108 clinical samples were collected, and the results of bioinformatics analysis were verified by immunohistochemistry. KNL1 and its related differentially expressed genes were used to draw a volcano map, construct a PPI protein interaction network, and perform gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA) and immune infiltration analysis to predict the function of KNL1 during UCEC progression. The prognostic data of TCGA and 108 clinical patients were used to analyze the correlation of KNL1 expression with the survival of patients, and KM survival curves were drawn. The UCEC cell lines Ishikawa and Hec-1-A were used to verify the function of KNL1.ResultsKNL1 is significantly overexpressed in UCEC and is associated with a poor prognosis. KNL1 overexpression is closely related to cell mitosis, the cell cycle and other functions and is correlated with the International Federation of Gynecology and Obstetrics (FIGO) stage, histological grade and other characteristics of UCEC patients. Knockdown of KNL1 expression in UCEC cell lines can inhibit their proliferation, invasion, metastasis and other phenotypes.ConclusionKNL1 is a prognostic and diagnostic biomarker associated with immune evasion in patients with UCEC

The transmembrane channel-like 6 (TMC6) in primary sensory neurons involving thermal sensation via modulating M channels

Introduction: The transmembrane channel-like (TMC) protein family contains eight members, TMC1–TMC8. Among these members, only TMC1 and TMC2 have been intensively studied. They are expressed in cochlear hair cells and are crucial for auditory sensations. TMC6 and TMC8 contribute to epidermodysplasia verruciformis, and predispose individuals to human papilloma virus. However, the impact of TMC on peripheral sensation pain has not been previously investigated.Methods: RNAscope was employed to detect the distribution of TMC6 mRNA in DRG neurons. Electrophysiological recordings were conducted to investigate the effects of TMC6 on neuronal characteristics and M channel activity. Zn2+ indicators were utilized to detect the zinc concentration in DRG tissues and dissociated neurons. A series of behavioural tests were performed to assess thermal and mechanical sensation in mice under both physiological and pathological conditions.Results and Discussion: We demonstrated that TMC6 is mainly expressed in small and medium dorsal root ganglion (DRG) neurons and is involved in peripheral heat nociception. Deletion of TMC6 in DRG neurons hyperpolarizes the resting membrane potential and inhibits neuronal excitability. Additionally, the function of the M channel is enhanced in TMC6 deletion DRG neurons owing to the increased quantity of free zinc in neurons. Indeed, heat and mechanical hyperalgesia in chronic pain are alleviated in TMC6 knockout mice, particularly in the case of heat hyperalgesia. This suggests that TMC6 in the small and medium DRG neurons may be a potential target for chronic pain treatment

Circulating tumor DNA clearance predicts prognosis across treatment regimen in a large real-world longitudinally monitored advanced non-small cell lung cancer cohort

Background: Although growth advantage of certain clones would ultimately translate into a clinically visible disease progression, radiological imaging does not reflect clonal evolution at molecular level. Circulating tumor DNA (ctDNA), validated as a tool for mutation detection in lung cancer, could reflect dynamic molecular changes. We evaluated the utility of ctDNA as a predictive and a prognostic marker in disease monitoring of advanced non-small cell lung cancer (NSCLC) patients.Methods: This is a multicenter prospective cohort study. We performed capture-based ultra-deep sequencing on longitudinal plasma samples utilizing a panel consisting of 168 NSCLC-related genes on 949 advanced NSCLC patients with driver mutations to monitor treatment responses and disease progression. The correlations between ctDNA and progression-free survival (PFS)/overall survival (OS) were performed on 248 patients undergoing various treatments with the minimum of 2 ctDNA tests.Results: The results of this study revealed that higher ctDNA abundance (P=0.012) and mutation count (P=8.5x10(-4)) at baseline are associated with shorter OS. We also found that patients with ctDNA clearance, not just driver mutation clearance, at any point during the course of treatment were associated with longer PFS (P=2.2x10(-1)6, HR 0.28) and OS (P=4.5x10(-6), HR 0.19) regardless of type of treatment and evaluation schedule.Conclusions: This prospective real-world study shows that ctDNA clearance during treatment may serve as predictive and prognostic marker across a wide spectrum of treatment regimens