Heterogeneous changes in gut and tumor microbiota in patients with pancreatic cancer: insights from clinical evidence.

BACKGROUND: Pancreatic cancer is the foremost contributor to cancer-related deaths globally, and its prevalence continues to rise annually. Nevertheless, the underlying mechanisms behind its development remain unclear and necessitate comprehensive investigation. METHODS: In this study, a total of 29 fresh stool samples were collected from patients diagnosed with pancreatic cancer. The gut microbial data of healthy controls were obtained from the SRA database (SRA data number: SRP150089). Additionally, 28 serum samples and diseased tissues were collected from 14 patients with confirmed pancreatic cancer and 14 patients with chronic pancreatitis. Informed consent was obtained from both groups of patients. Microbial sequencing was performed using 16s rRNA. RESULTS: The results showed that compared with healthy controls, the species abundance index of intestinal flora in patients with pancreatic cancer was increased (P < 0.05), and the number of beneficial bacteria at the genus level was reduced (P < 0.05). Compared with patients with chronic pancreatitis, the expression levels of CA242 and CA199 in the serum of patients with pancreatic cancer were increased (P < 0.05). The bacterial richness index of tumor microorganisms in patients with pancreatic cancer increased, while the diversity index decreased(P < 0.05). Furthermore, there was a change in the species composition at the genus level. Additionally, the expression level of CA242 was found to be significantly positively correlated with the relative abundance of Acinetobacter(P < 0.05). CONCLUSION: Over all, the expression levels of serum tumor markers CA242 and CA19-9 in patients with pancreatic cancer are increased, while the beneficial bacteria in the intestine and tumor microenvironment are reduced and pathogenic bacteria are increased. Acinetobacter is a specific bacterial genus highly expressed in pancreatic cancer tissue.

MMGAT: a graph attention network framework for ATAC-seq motifs finding.

BACKGROUND: Motif finding in Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) data is essential to reveal the intricacies of transcription factor binding sites (TFBSs) and their pivotal roles in gene regulation. Deep learning technologies including convolutional neural networks (CNNs) and graph neural networks (GNNs), have achieved success in finding ATAC-seq motifs. However, CNN-based methods are limited by the fixed width of the convolutional kernel, which makes it difficult to find multiple transcription factor binding sites with different lengths. GNN-based methods has the limitation of using the edge weight information directly, makes it difficult to aggregate the neighboring nodes' information more efficiently when representing node embedding. RESULTS: To address this challenge, we developed a novel graph attention network framework named MMGAT, which employs an attention mechanism to adjust the attention coefficients among different nodes. And then MMGAT finds multiple ATAC-seq motifs based on the attention coefficients of sequence nodes and k-mer nodes as well as the coexisting probability of k-mers. Our approach achieved better performance on the human ATAC-seq datasets compared to existing tools, as evidenced the highest scores on the precision, recall, F1_score, ACC, AUC, and PRC metrics, as well as finding 389 higher quality motifs. To validate the performance of MMGAT in predicting TFBSs and finding motifs on more datasets, we enlarged the number of the human ATAC-seq datasets to 180 and newly integrated 80 mouse ATAC-seq datasets for multi-species experimental validation. Specifically on the mouse ATAC-seq dataset, MMGAT also achieved the highest scores on six metrics and found 356 higher-quality motifs. To facilitate researchers in utilizing MMGAT, we have also developed a user-friendly web server named MMGAT-S that hosts the MMGAT method and ATAC-seq motif finding results. CONCLUSIONS: The advanced methodology MMGAT provides a robust tool for finding ATAC-seq motifs, and the comprehensive server MMGAT-S makes a significant contribution to genomics research. The open-source code of MMGAT can be found at https://github.com/xiaotianr/MMGAT , and MMGAT-S is freely available at https://www.mmgraphws.com/MMGAT-S/ .

Deferasirox exerts anti-epileptic effects by improving brain iron homeostasis via regulation of ITPRIP.

Epilepsy constitutes a global health concern, affecting millions of individuals and approximately one-third of patients exhibit drug resistance. Recent investigations have revealed alterations in cerebral iron content in both epilepsy patients and animal models. However, the extant literature lacks a comprehensive exploration into the ramifications of modulating iron homeostasis as an intervention in epilepsy. This study investigated the impact of deferasirox, a iron ion chelator, on epilepsy. This study unequivocally substantiated the antiepileptic efficacy of deferasirox in a kainic acid-induced epilepsy model. Furthermore, deferasirox administration mitigated seizure susceptibility in a pentylenetetrazol-induced kindling model. Conversely, the augmentation of iron levels through supplementation has emerged as a potential exacerbating factor in the precipitating onset of epilepsy. Intriguingly, our investigation revealed a hitherto unreported discovery: ITPRIP was identified as a pivotal modulator of excitatory synaptic transmission, regulating seizures in response to deferasirox treatment. In summary, our findings indicate that deferasirox exerts its antiepileptic effects through the precise targeting of ITPRIP and amelioration of cerebral iron homeostasis, suggesting that deferasirox is a promising and novel therapeutic avenue for interventions in epilepsy.

Synthesis, optical properties, and application of novel chalcone skeleton as pH fluorescent probe: Based AIE + ESIPT strategy.

A series of "turn off" pH fluorescence probes with chalcone skeleton for basic system have been developed. The molecules emitted bright yellow fluorescence under acidic condition, resulting AIE coupled ESIPT characteristic and ICT process. What's more, the compounds exhibited excellent sensitivity and selectivity for detecting pH as a facile "On-Off" fluorescence probe, and the fluorescence of them were quenched with the ESIPT process interrupted under alkaline condition. Theoretical calculation for the related compounds also performed to verify the electron effect on photophysical properties and confirm the rational speculation on the mechanism.

GNNMF: a multi-view graph neural network for ATAC-seq motif finding.

BACKGROUND: The Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) utilizes the Transposase Tn5 to probe open chromatic, which simultaneously reveals multiple transcription factor binding sites (TFBSs) compared to traditional technologies. Deep learning (DL) technology, including convolutional neural networks (CNNs), has successfully found motifs from ATAC-seq data. Due to the limitation of the width of convolutional kernels, the existing models only find motifs with fixed lengths. A Graph neural network (GNN) can work on non-Euclidean data, which has the potential to find ATAC-seq motifs with different lengths. However, the existing GNN models ignored the relationships among ATAC-seq sequences, and their parameter settings should be improved. RESULTS: In this study, we proposed a novel GNN model named GNNMF to find ATAC-seq motifs via GNN and background coexisting probability. Our experiment has been conducted on 200 human datasets and 80 mouse datasets, demonstrated that GNNMF has improved the area of eight metrics radar scores of 4.92% and 6.81% respectively, and found more motifs than did the existing models. CONCLUSIONS: In this study, we developed a novel model named GNNMF for finding multiple ATAC-seq motifs. GNNMF built a multi-view heterogeneous graph by using ATAC-seq sequences, and utilized background coexisting probability and the iterloss to find different lengths of ATAC-seq motifs and optimize the parameter sets. Compared to existing models, GNNMF achieved the best performance on TFBS prediction and ATAC-seq motif finding, which demonstrates that our improvement is available for ATAC-seq motif finding.

Bioturbation effect of artificial inoculation on the flavor metabolites and bacterial communities in the Chinese Mao-tofu fermentation.

A comparison between artificially inoculated Mao-tofu (CC) and naturally fermented Mao-tofu (MM) indicated that artificially adding Mucor plasmaticus to Mao-tofu dramatically enhanced the essential amino acid (EAA) content, as well as umami and sweet amino acids. Gas chromatography-tandem mass spectrometry (GC-MS/MS) analysis revealed that phenol (3.226 µg/g), 1-octen-3-ol (5.031 µg/g), ethyl heptanoate (1.646 µg/g), and indole (3.422 µg/g) were the key flavor components in Mao-tofu. Unlike MM, CC displayed a substantial increase in esters and a considerable decrease in foul odor substances, including sulfur-containing compounds and indole. Lactococcus raffinolactis, Enterobacter sp. 638, and Streptococcus parauberis KCTC 11537 represented the key bacterial species altering the amino acids and flavor of Mao-tofu according to PacBio single-molecule real-time (SMRT) sequencing and correlation analysis. This study presents the technical feasibility of artificially inoculating Mao-tofu to regulate the core bacterial communities and control the quality of fermented soybean products.

Estimating tongue deformation during laryngoscopy using a hybrid FEM-multibody model and intraoperative tracking - a cadaver study.

Throat tumour margin control remains difficult due to the tight, enclosed space of the oral and throat regions and the tissue deformation resulting from placement of retractors and scopes during surgery. Intraoperative imaging can help with better localization but is hindered by non-image-compatible surgical instruments, cost, and unavailability. We propose a novel method of using instrument tracking and FEM-multibody modelling to simulate soft tissue deformation in the intraoperative setting, without requiring intraoperative imaging, to improve surgical guidance accuracy. We report our first empirical study, based on four trials of a cadaveric head specimen with full neck anatomy, yields a mean TLE of 10.8 ± 5.5 mm, demonstrating methodological feasibility.

Mental health status and related factors influencing healthcare workers during the COVID-19 pandemic: A systematic review and meta-analysis.

BACKGROUND: The mental health of healthcare workers during the coronavirus-2019 pandemic was seriously affected, and the risk of mental health problems was high. The present study sought to systematically evaluate the mental health problems of healthcare workers worldwide during the pandemic and to determine the latest global frequency of COVID-19 associated mental health problems. METHODS: Data in the Cumulative Index to Nursing and Allied Health Literature (CINAHL), EMBASE, Elsevier, MEDLINE, PubMed, PsycINFO and the Web of Science before November 11, 2022, were systematically searched. Cohort, case-control and cross-sectional studies were included. The meta-analysis used a random effects model to synthesize the comprehensive prevalence rate of mental health problems. Subgroup analyses were performed based on time of data collection; whether the country was or was not developed; continent; doctors and nurses; doctors/nurses vs. other healthcare workers; and psychological evaluation scale. RESULTS: A total of 161 studies were included, including 341,014 healthcare workers worldwide, with women accounting for 82.8%. Occupationally, 16.2% of the healthcare workers were doctors, 63.6% were nurses and 13.3% were other medical staff. During the pandemic, 47% (95% confidence interval [CI], 35-60%) of healthcare workers reported job burnout, 38% (95% CI, 35-41%) experienced anxiety, 34% (95% CI 30-38%) reported depression, 30% (95% CI, 29-31%) had acute stress disorder, and 26% (95% CI, 21-31%) had post-traumatic stress disorder. CONCLUSIONS: The study found that there were common mental health problems among health care workers during the COVID-19 pandemic. The most common was job burnout, followed by anxiety, depression, acute stress and post-traumatic stress disorder. Although the global pandemic has been brought under control, its long-term impact on the mental health of healthcare workers cannot be ignored. Additional research is required to develop measures to prevent, monitor and treat psychological disorders among healthcare workers.

Intravenous immunoglobulin for treatment of hospitalized COVID-19 patients: an evidence mapping and meta-analysis.

BACKGROUND: The clinical efficacy and safety of intravenous immunoglobulin (IVIg) treatment for COVID-19 remain controversial. This study aimed to map the current status and gaps of available evidence, and conduct a meta-analysis to further investigate the benefit of IVIg in COVID-19 patients. METHODS: Electronic databases were searched for systematic reviews/meta-analyses (SR/MAs), primary studies with control groups, reporting on the use of IVIg in patients with COVID-19. A random-effects meta-analysis with subgroup analyses regarding study design and patient disease severity was performed. Our outcomes of interest determined by the evidence mapping, were mortality, length of hospitalization (days), length of intensive care unit (ICU) stay (days), number of patients requiring mechanical ventilation, and adverse events. RESULTS: We included 34 studies (12 SR/MAs, 8 prospective and 14 retrospective studies). A total of 5571 hospitalized patients were involved in 22 primary studies. Random-effects meta-analyses of very low to moderate evidence showed that there was little or no difference between IVIg and standard care or placebo in reducing mortality (relative risk [RR] 0.91; 95% CI 0.78-1.06; risk difference [RD] 3.3% fewer), length of hospital (mean difference [MD] 0.37; 95% CI - 2.56, 3.31) and ICU (MD 0.36; 95% CI - 0.81, 1.53) stays, mechanical ventilation use (RR 0.92; 95% CI 0.68-1.24; RD 2.8% fewer), and adverse events (RR 0.98; 95% CI 0.84-1.14; RD 0.5% fewer) of patients with COVID-19. Sensitivity analysis using a fixed-effects model indicated that IVIg may reduce mortality (RR 0.76; 95% CI 0.60-0.97), and increase length of hospital stay (MD 0.68; 95% CI 0.09-1.28). CONCLUSION: Very low to moderate certainty of evidence indicated IVIg may not improve the clinical outcomes of hospitalized patients with COVID-19. Given the discrepancy between the random- and fixed-effects model results, further large-scale and well-designed RCTs are warranted.

Metformin potentiates nephrotoxicity by promoting NETosis in response to renal ferroptosis.

Given the rapidly aging population, aging-related diseases are becoming an excessive burden on the global healthcare system. Metformin has been shown to be beneficial to many age-related disorders, as well as increase lifespan in preclinical animal models. During the aging process, kidney function progressively declines. Currently, whether and how metformin protects the kidney remains unclear. In this study, among longevity drugs, including metformin, nicotinamide, resveratrol, rapamycin, and senolytics, we unexpectedly found that metformin, even at low doses, exacerbated experimentally-induced acute kidney injury (AKI) and increased mortality in mice. By single-cell transcriptomics analysis, we found that death of renal parenchymal cells together with an expansion of neutrophils occurs upon metformin treatment after AKI. We identified programmed cell death by ferroptosis in renal parenchymal cells and blocking ferroptosis, or depleting neutrophils protects against metformin-induced nephrotoxicity. Mechanistically, upon induction of AKI, ferroptosis in renal parenchymal cells initiates the migration of neutrophils to the site of injury via the surface receptor CXCR4-bound to metformin-iron-NGAL complex, which results in NETosis aggravated AKI. Finally, we demonstrated that reducing iron showed protective effects on kidney injury, which supports the notion that iron plays an important role in metformin-triggered AKI. Taken together, these findings delineate a novel mechanism underlying metformin-aggravated nephropathy and highlight the mechanistic relationship between iron, ferroptosis, and NETosis in the resulting AKI.

Causes of death among patients with testicular cancer during the survivorship.

OBJECTIVE: The aim was to evaluate the causes of death for patients with testicular cancer (TC), and calculate mortality risks for each cause. METHODS: Patients diagnosed between 2000 and 2017 were identified. Main causes of death including TC, second malignant tumor (SMT) and non-tumor diseases, and the standardized mortality rate (SMR) of each cause were analyzed. RESULTS: 27,143 patients with localized TC were included, and 1171 of them died including 215 TC deaths, 236 SMT deaths, and 720 non-tumor deaths. Main SMT deaths were cancer from lung and bronchus, colon and rectum, etc. Main non-cancer causes were diseases of heart, accidents and adverse effects and suicide and self-inflicted injury. Compared with the general population, the mortality risks from diseases of heart and accidents and adverse effects were significantly reduced. For 11,719 patients with regional and distant metastasis TC, 1733 died including 964 TC deaths, 345 SMT deaths and 424 non-tumor deaths. The main SMT and non-tumor deaths were lung and bronchus, diseases of heart and suicide and self-inflicted injury. CONCLUSION: The leading causes of death besides TC were lung and bronchus cancer, colon and rectum cancer, diseases of heart, accidents and adverse effects, suicide and self-inflicted injury for TC patients. The localized TC patients were associated with similar risks of SMT deaths and lower risks of main non-tumor causes of death. IMPACT: We evaluated all causes of death of TC patients and SMR for each cause of death. Our results could provide valuable information about the priority of healthcare during testicular cancer survival.

Synthesis, Optical Properties, and Applications of Luminescent Benzothiazole: Base Promoted Intramolecular C-S Bond Formation.

A novel base-catalyzed method for the synthesis of luminescent benzothiazole derivatives had been developed under metal-free conditions via C-S bond formation, which provided an efficient, convenient, and mild alternative method for constructing substituted benzothiazoles. As-prepared benzothiazole derivatives thus produced emissions in solution with quantum yield up to 85%. In addition, they still exhibited fairly strong fluorescence in the solid state. Furthermore, the compounds were used as a facile "On-Off" fluorescence probe to create handy test strips for detecting NaClO by naked eyes.

Spatially resolved expression landscape and gene-regulatory network of human gastric corpus epithelium.

Molecular knowledge of human gastric corpus epithelium remains incomplete. Here, by integrated analyses using single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and single-cell assay for transposase accessible chromatin sequencing (scATAC-seq) techniques, we uncovered the spatially resolved expression landscape and gene-regulatory network of human gastric corpus epithelium. Specifically, we identified a stem/progenitor cell population in the isthmus of human gastric corpus, where EGF and WNT signaling pathways were activated. Meanwhile, LGR4, but not LGR5, was responsible for the activation of WNT signaling pathway. Importantly, FABP5 and NME1 were identified and validated as crucial for both normal gastric stem/progenitor cells and gastric cancer cells. Finally, we explored the epigenetic regulation of critical genes for gastric corpus epithelium at chromatin state level, and identified several important cell-type-specific transcription factors. In summary, our work provides novel insights to systematically understand the cellular diversity and homeostasis of human gastric corpus epithelium in vivo.

Second malignant tumors and non-tumor causes of death for patients with localized and regional kidney cancer after diagnosis.

BACKGROUND: To evaluate the second malignant tumors (SMTs) and non-tumor causes of death among patients diagnosed with localized and regional kidney cancer. METHODS: Patients diagnosed with kidney cancer between 2000 and 2017 in the Surveillance, Epidemiology, and End Results (SEER) program database were identified. All causes of death for patients during the follow-up and standardized mortality ratio (SMR) were analyzed. RESULT: 113,734 patients with localized kidney cancer with 30,390 cases of death were analyzed. 60.4% of the death cases were due to non-tumor caused and 23.6% were second malignant tumors (SMTs). Main SMTs included cancers of lung and bronchus [n = 1,283, SMR: 1.00 (0.95-1.06)] and pancreas [n = 393, SMR: 1.27 (1.15-1.41)]. Causes of death for non-tumor mainly included heart diseases [n = 6,161, SMR: 1.25 (1.21-1.28)] and chronic obstructive pulmonary disease (COPD) [n = 1,185, SMR: 0.99 (0.94-1.05)]. 14,437 of 29,602 patients with regional kidney cancer died. 14.6% of all deaths were due to SMTs and 23.6% due to non-tumor causes. Main SMTs contained bladder cancer [n = 371, SMR: 10.90 (9.81-12.06)] and lung and bronchus cancer [n = 346, SMR: 1.21 (1.08-1.34)]. The main non-tumor death was heart disease [n = 1,424, SMR: 1.26 (1.2-1.33)]. When stratified by pathological types, patients with clear cell renal cell carcinoma (RCC) did not have increased mortality risks of bladder cancer and lung cancer but patients with non-clear cell RCC did. CONCLUSION: SMTs and non-tumor diseases including lung and bronchus cancer, bladder cancer, pancreas cancer, diseases of heart, COPD, and cerebrovascular diseases are the leading causes of death besides kidney cancer and should be paid more attention during patients' survival period.

Statistical Analysis of Two-Compartment Pharmacokinetic Models with Drug Non-adherence.

Poor drug adherence is considered one of major barriers to achieving the clinical and public health benefits of many pharmacotherapies. In the current paper, we aim to investigate the impact of dose omission on the plasma concentrations of two-compartment pharmacokinetic models with two typical routes of drug administration, namely the intravenous bolus and extravascular first-order absorption. First, we reformulate the classical two-compartment pharmacokinetic models with a new stochastic feature, where a binomial random model of dose intake is integrated. Then, we formalize the explicit expressions of expectation and variance for trough concentrations and limit concentrations, with the latter proved of the existence and uniqueness for steady-state distribution. Moreover, we mathematically demonstrate the strict stationarity and ergodicity of trough concentrations as a Markov chain. In addition, we numerically simulate the impact of drug non-adherence to different extents on the variability and regularity of drug concentration and compare the drug pharmacokinetic preference between one and two compartment pharmacokinetic models. The results of sensitivity analysis also suggest the drug non-adherence as one of the most sensitive model parameters to the expectation of limit concentration. Our modelling and analytical approach can be integrated into the chronic disease models to estimate or quantitatively predict the therapy efficacy with drug pharmacokinetics presumably affected by random dose omissions.

Application of Clostridium butyricum, Rummeliibacillus suwonensis, and Issatchenkia orientalis for Nongxiangxing baijiu fermentation: Improves the microbial communities and flavor of upper fermented grain.

Ethyl hexanoate and ethyl butyrate are essential to the flavor compounds in Nongxiangxing baijiu, but low levels of these two esters in upper fermented grains (FG) decreases the quality of upper distilled baijiu, representing the main challenge in Nongxiangxing baijiu production. This paper enhanced fermentation by inoculating functional Clostridium butyricum, Rummeliibacillus suwonensis, and Issatchenkia orientalis strains into upper FG. The results showed that the ethyl butyrate content in the upper FG increased significantly and the content of ethyl hexanoate did improve from the results of many determinations. High-throughput sequencing indicated that the dominant phyla in the FG were Firmicutes, Actinobacteriota, Proteobacteria, Ascomycota, and Basidiomycota. The canonical correspondence analysis (CCA) and person correlation network revealed the relationship between the microbial community, physicochemical environment, and flavor compounds. The temperature, oxygen, and acidity were closely related to the microbial community, while most flavor compounds were positively correlated with Caldicoprobacter, Caproiciproducens, Delftia, Hydrogenispora, Thermoactinomyces, Issatchenkia Bacillus, and Aspergillus. These results helped improve the quality of Nongxiangxing baijiu.

Contrast Optimization for Size Invariant Visual Cryptography Scheme.

Visual cryptography scheme (VCS) serves as an effective tool in image security. Size-invariant VCS (SI-VCS) can solve the pixel expansion problem in traditional VCS. On the other hand, it is anticipated that the contrast of the recovered image in SI-VCS should be as high as possible. The investigation of contrast optimization for SI-VCS is carried out in this article. We develop an approach to optimize the contrast by stacking t ( k ≤ t ≤ n ) shadows in (k, n) -SI-VCS. Generally, a contrast-maximizing problem is linked with a (k, n) -SI-VCS, where the contrast by t shadows is considered as an objective function. An ideal contrast by t shadows can be produced by addressing this problem using linear programming. However, there exist (n-k+1) different contrasts in a (k, n) scheme. An optimization-based design is further introduced to provide multiple optimal contrasts. These (n-k+1) different contrasts are regarded as objective functions and it is transformed into a multi-contrast-maximizing problem. The ideal point method and lexicographic method are adopted to address this problem. Additionally, if the Boolean XOR operation is used for secret recovery, a technique is also provided to offer multiple maximum contrasts. The effectiveness of the proposed schemes is verified by extensive experiments. Comparisons illustrate significant advancement on contrast is provided.

Qianjin Wenwu decoction suppresses renal interstitial fibrosis by enhancing the degradation of extracellular matrix in mice with unilateral ureteral obstruction.

Diabetic kidney disease (DKD) is the most common complication of diabetes mellitus (DM). Qianjin Wenwu decoction (QWD), a well-known traditional Korean medicine, has been used for the treatment of DKD, with satisfactory therapeutic effects. This study was designed to investigate the active components and mechanisms of action of QWD in the treatment of DKD. The results demonstrated that a total of 13 active components in five types were found in QWD, including flavonoids, flavonoid glycosides, phenylpropionic acids, saponins, coumarins, and lignins. Two key proteins, TGF-ß1 and TIMP-1, were identified as the target proteins through molecular docking. Furthermore, QWD significantly suppressed Scr and BUN levels which increased after unilateral ureteral obstruction (UUO). Hematoxylin & eosin (H&E) and Masson staining results demonstrated that QWD significantly alleviated renal interstitial fibrosis in UUO mice. We also found that QWD promoted ECM degradation by regulating MMP-9/TIMP-1 homeostasis to improve renal tubulointerstitial fibrosis and interfere with the expression and activity of TGF- ß1 in DKD treatment. These findings explain the underlying mechanism of QWD for the treatment of DKD, and also provide methodological reference for investigating the mechanism of traditional medicine in the treatment of DKD.