Antibacterial activity and mechanism of Stevia extract against antibiotic-resistant Escherichia coli by interfering with the permeability of the cell wall and the membrane.

Natural plant-derived compounds with broad-spectrum antimicrobial activity have become an effective strategy against multidrug-resistant bacteria. The present study was designed to compare the antibacterial activity of six chlorogenic acid (CA) isomers extracted from stevia and investigated the underlying antibacterial mechanisms involved. The results indicated that isochlorogenic acid C (ICAC) exhibited the strongest antibacterial activity against the tested bacteria, especially E. coli, at a 2 mg/mL minimum inhibitory concentration (MIC) and 8 mg/mL minimum bactericidal concentration (MBC). At the MBC, ICAC inhibited 72.66% of the clinical multidrug-resistant strains. Scanning electron microscopy (SEM) revealed that ICAC induced considerable morphological alterations in E. coli ATCC25922 and C4E2. The significant increase in the activity of extracellular alkaline phosphatase (AKP) indicated that ICAC damages the permeability of the bacterial cell wall. Additionally, the intracellular membrane (IM) permeability and the content of lipopolysaccharide (LPS), a main component of the outer membrane (OM), were determined. The significant decrease in LPS content and increased leakage of intracellular proteins and K+ from E. coli indicated that ICAC could induce the exfoliation of OM and disrupt IM permeability, resulting in the loss of barrier function. The uptake of propidium iodide (PI), a compromised cell membrane nucleic acid stain, and confocal laser scanning microscopy (CLSM) further demonstrated that ICAC disrupted IM integrity. Moreover, the bactericidal effect and damage to bacterial microstructural function occurred in a dose-dependent manner. These data demonstrate that ICAC has excellent antibacterial activity and is a promising approach for overcoming the antibiotic resistance of pathogenic bacteria.

Syntheses, crystal structures and photocurrent responses of Cs2Ag2Sb2S5 and CsAgSb4S7 with thiourea as a mineralizer.

Two layered compounds Cs2Ag2Sb2S5 (1) and CsAgSb4S7 (2) were successfully synthesized using a mild solvothermal method with thiourea as a mineralizer. The syntheses of these two silver-containing quaternary sulfides indicate that thiourea is a novel effective mineralizer. Both compounds are semiconductors and compound 1 exhibits excellent photocurrent response properties.

The essential role of dual-energy x-ray absorptiometry in the prediction of subclinical cardiovascular disease.

Subclinical cardiovascular disease (Sub-CVD) is an early stage of cardiovascular disease and is often asymptomatic. Risk factors, including hypertension, diabetes, obesity, and lifestyle, significantly affect Sub-CVD. Progress in imaging technology has facilitated the timely identification of disease phenotypes and risk categorization. The critical function of dual-energy x-ray absorptiometry (DXA) in predicting Sub-CVD was the subject of this research. Initially used to evaluate bone mineral density, DXA has now evolved into an indispensable tool for assessing body composition, which is a pivotal determinant in estimating cardiovascular risk. DXA offers precise measurements of body fat, lean muscle mass, bone density, and abdominal aortic calcification, rendering it an essential tool for Sub-CVD evaluation. This study examined the efficacy of DXA in integrating various risk factors into a comprehensive assessment and how the application of machine learning could enhance the early discovery and control of cardiovascular risks. DXA exhibits distinct advantages and constraints compared to alternative imaging modalities such as ultrasound, computed tomography, magnetic resonance imaging, and positron emission tomography. This review advocates DXA incorporation into cardiovascular health assessments, emphasizing its crucial role in the early identification and management of Sub-CVD.

Progress in the application of artificial intelligence in skin wound assessment and prediction of healing time.

Since the 1970s, artificial intelligence (AI) has played an increasingly pivotal role in the medical field, enhancing the efficiency of disease diagnosis and treatment. Amidst an aging population and the proliferation of chronic disease, the prevalence of complex surgeries for high-risk multimorbid patients and hard-to-heal wounds has escalated. Healthcare professionals face the challenge of delivering safe and effective care to all patients concurrently. Inadequate management of skin wounds exacerbates the risk of infection and complications, which can obstruct the healing process and diminish patients' quality of life. AI shows substantial promise in revolutionizing wound care and management, thus enhancing the treatment of hospitalized patients and enabling healthcare workers to allocate their time more effectively. This review details the advancements in applying AI for skin wound assessment and the prediction of healing timelines. It emphasizes the use of diverse algorithms to automate and streamline the measurement, classification, and identification of chronic wound healing stages, and to predict wound healing times. Moreover, the review addresses existing limitations and explores future directions.

A photoelectrochemical sensor based on In2S3/AgInS2 in situ Z-type heterojunction with "photo-modulated interface charge" for sensitive detection of Programmed Death-Ligand 1.

The construction of heterostructure photoelectrodes can enhance the performance of photoelectrochemical (PEC) sensors. However, it is still a critical challenge to achieve efficient transfer of interface carriers. In this paper, we propose a strategy of "photo-modulated interface charge" to design a PEC sensor based on a hollow hexagonal tubular In2S3/AgInS2 in situ Z-type heterojunction for the susceptible detection of Programmed Death-ligand 1 (PD-L1). The hollow structured In2S3/AgInS2 is ingeniously synthesized employing indium-sourced MIL-68 as a sacrificial template and in situ cation exchange technique. This composite material has close contact interfaces due to in situ growth, which facilitates the spontaneous establishment of a robust and stable built-in electric field between the interfaces. Moreover, the inner cavity structure promotes multiple light refractions and scatterings, significantly enhancing light trapping capability. Under the influence of both light irradiation and electric field force, the migration direction of the interfacial charge is reversed, forming a Z-transfer path, which effectively delays the compounding of the electron-hole pairs (e-/h+) and further improves the sensitivity of the sensor. The minimum detection threshold of the PEC sensor is 26.58 fg/mL, and the feasibility of real samples is investigated, providing new insights for early diagnosis and prognostic treatment of diseases.

Association between loneliness and mental health among nurses: a cross-sectional research in China.

This study explored the association between loneliness and mental health among nurses in China during the COVID-19 pandemic. This cross-sectional study was conducted from March to April 2022. We enrolled 2,811 nurses from a tertiary hospital in China. Demographic characteristics, lifestyle factors, work-related factors, and psychological characteristics were collected from participants via a self-reported questionnaire. Loneliness was measured with the three-item short form of the Revised UCLA Loneliness Scale, and the Patient Health Questionnaire (PHQ-9) and the General Anxiety Disorder (GAD-7) scale were used to measure mental health. Adjusted odds ratios (ORs) and 95% confidence intervals (CI) were determined using binary logistic regression. Among participants in this study, 12.0% (337) experienced loneliness, and 7.8% (219) and 6.7% (189) reported depression and anxiety, respectively. The loneliness scores were categorized into three levels (3, 4-6, and 7-9). For depression, compared with the lowest reference, the ORs and 95% CI across the tertile were 1.31 (0.69-1.84) and 2.53 (1.11-5.76) after adjustment, respectively, and the P-value for trend was 0.045. For anxiety, compared with the lowest reference, the ORs and 95%CI across the tertile were 1.84 (1.28-2.63) and 2.52 (1.57-4.10) after adjustment, respectively; the P-value for trend was 0.004. This study showed that loneliness was significantly associated with poor mental health among nurses during the COVID-19 pandemic. These findings suggested that medical establishments should offer interventions for nurses to prevent mental health problems by targeting this modifiable risk factor.

A multi-classifier system integrated by clinico-histology-genomic analysis for predicting recurrence of papillary renal cell carcinoma.

Integrating genomics and histology for cancer prognosis demonstrates promise. Here, we develop a multi-classifier system integrating a lncRNA-based classifier, a deep learning whole-slide-image-based classifier, and a clinicopathological classifier to accurately predict post-surgery localized (stage I-III) papillary renal cell carcinoma (pRCC) recurrence. The multi-classifier system demonstrates significantly higher predictive accuracy for recurrence-free survival (RFS) compared to the three single classifiers alone in the training set and in both validation sets (C-index 0.831-0.858 vs. 0.642-0.777, p < 0.05). The RFS in our multi-classifier-defined high-risk stage I/II and grade 1/2 groups is significantly worse than in the low-risk stage III and grade 3/4 groups (p < 0.05). Our multi-classifier system is a practical and reliable predictor for recurrence of localized pRCC after surgery that can be used with the current staging system to more accurately predict disease course and inform strategies for individualized adjuvant therapy.

Improved Patient Adherence to Family-Based Helicobacter pylori Infection Control and Management Strategy in Central China and Its Influencing Factors.

BACKGROUND: Patient adherence status to the newly introduced family-based Helicobacter pylori (H. pylori) infection control and management strategy remains unclear, so are its influencing factors. We aim to investigate family members' adherence and its influencing factors during the family-based H. pylori infection management practice for related disease prevention. MATERIALS AND METHODS: Based on our previously family-based H. pylori survey in 2021, 282 families including 772 individuals were followed up 2 years after the initial survey to compare if the investigation and education might improve family member's adherence. The participant's adherence to H. pylori infection awareness, retest, treatment, publicity, gastroscopy, and hygiene habits were followed up, and their influencing factors were also analyzed. RESULTS: The overall participant's adherence to recommendations on H. pylori awareness, retest, treatment, publicity, gastroscopy, and hygiene habits were 77% (187/243), 67.3% (138/205), 60.1% (211/351), 46.5% (107/230), 45.6% (159/349), and 39.1% (213/545), respectively; and all showed improvements compared with their prior survey stages. The top reasons for rejection to treatment, retest, and gastroscopy were forgetting or unaware of H. pylori infection (30.3%), busy (32.8%), and asymptomatic (67.9%), respectively. Independent risk factor for low adherence to treatment was occupation (e.g., staff: OR 4.49, 95% CI 1.34-15.10). Independent favorable factors for treatment adherence were individuals at the ages of 18-44 years (OR 0.19, 95% CI 0.04-0.89) and had a large family size (e.g., four family members: OR 0.15, 95% CI 0.06-0.41); for retest adherence, it was individuals at the ages of 60-69 years (OR 0.23, 95% CI 0.06-0.97); for gastroscopy adherence, it was individuals at the age of 60-69 years (OR 0.46, 95% CI 0.28-0.75), and with gastrointestinal symptoms (OR 0.57, 95% CI 0.36-0.90). CONCLUSIONS: Family-based H. pylori management increases individual adherence to treatment, retest, and awareness, and there are also improved adherence to gastroscopy, publicity, and personal hygiene recommendations; further efforts are required to enhance the individual adherence rate for related disease prevention.

The Potential Role of Non-coding RNAs in Regulating Ferroptosis in Cancer: Mechanisms and Application Prospects.

Cancer is the second leading cause of death globally. Despite some successes, conventional cancer treatments are insufficient to address the growing problem of drug resistance in tumors and to achieve efficient treatment outcomes. Therefore, there is an urgent need to explore new therapeutic options. Ferroptosis, a type of iron- and reactive oxygen species-dependent regulated cell death, has been closely associated with cancer development and progression. Non-coding RNAs (ncRNAs) are a class of RNAs that do not code for proteins, and studies have demonstrated their involvement in the regulation of ferroptosis in cancer. This review aims to explore the molecular regulatory mechanisms of ncRNAs involved in ferroptosis in cancer and to emphasize the feasibility of ferroptosis and ncRNAs as novel therapeutic strategies for cancer. We conducted a systematic and extensive literature review using PubMed, Google Scholar, Web of Science, and various other sources to identify relevant studies on ferroptosis, ncRNAs, and cancer. A deeper understanding of ferroptosis and ncRNAs could facilitate the development of new cancer treatment strategies.

Volatile Profile Characterization of Jujube Fruit via HS-SPME-GC/MS and Sensory Evaluation.

Current research does not fully elucidate the key compounds and their mechanisms that define the aroma profile of fresh jujube fruits. Therefore, this study conducted a comprehensive analysis of both free and glycosidically bound aroma compounds in fresh jujube fruits of ten cultivars. Utilizing gas chromatography-mass spectrometry (GC-MS), we identified 76 volatile free aroma compounds and 19 glycosidically bound volatile compounds, with esters, aldehydes, and ketones emerging as the predominant volatile compounds in the jujube fruits. Odor activity value (OAV) analysis revealed that the primary aroma profile of the jujubes is characterized by fruity and fatty odors, with ß-damascenone being a key contributor to the fruity aroma, and (E)-2-oct-en-1-al and nonanal significantly influencing the fatty aroma. Moreover, the integration of sensory evaluation and partial least squares regression (PLSR) analysis pinpointed octanal, (E)-2-oct-en-1-al, nonanal, ß-damascenone, and pentanal as significant contributors to the jujube's characteristic aroma, while isoamyl acetate was identified as significantly influencing the fatty acid taste. This study not only underscores the complexity of the jujube aroma composition but also highlights the impact of environmental factors on aroma profiles, offering valuable insights into the sensory characteristics of jujube fruits.

Association between Life's Essential 8 and estimated pulse wave velocity among adults in the US: a cross-sectional study of NHANES 2011-2018.

Background: Arterial stiffness, typically evaluated via estimated pulse wave velocity (ePWV), is believed to have a significant association with cardiovascular diseases. The objective of this study was to investigate the correlation between Life's Essential 8 (LE8), a newly revised metric of cardiovascular health, and ePWV among adult population in the United States. Methods: This research employed a cross-sectional methodology, drawing upon data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2011 to 2018. To explore the relationship between LE8 and ePWV among adults in the US, both univariate and multivariate linear regression analyses were carried out. Additionally, the restricted cubic splines method was utilized to examine any non-linear correlation. Results: The study comprised 6,742 participants with an average age of 48.30 ± 0.35 years. Among these, 3,236 were males, representing a weighted percentage of 48%. The population's weighted average LE8 score was 68.68 ± 0.37, while the average ePWV was 8.18 ± 0.04. An entirely adjusted model revealed a negative correlation between ePWV and LE8 scores [in the moderate LE8 group, coefficient - 0.17, 95% CI -0.28 to -0.06, p = 0.004; in the high LE8 group, coefficient - 0.44, 95% CI -0.56 to -0.32, p < 0.0001]. This negative correlation was consistent with the findings in demographic subgroup analysis, with the effect size being more pronounced among adults under the age of 60, and individuals without hypertension, cardiovascular disease, or diabetes. Conclusion: Our study reveals a negative correlation between LE8 and ePWV in the adult population of the US, suggesting that LE8 could potentially serve as an indicative marker for evaluating the risk of vascular stiffness. This inverse relationship is markedly stronger in adults below 60 years and those without diagnosed vascular diseases. This implies that lifestyle upgrades and risk factor management could be especially advantageous in curbing arterial stiffness within these groups. These conclusions underscore the importance of primary prevention in mitigating the risk of vascular aging in a relatively healthy group, emphasizing the significance of early intervention and risk factor management in cardiovascular disease.

The effect of miR-381 on proliferation and prognosis of breast cancer by altering CCNA2 expression.

BACKGROUND: MiR-381 can regulate the expression of cyclin A2 (CCNA2) to inhibit the proliferation and migration of bladder cancer cells, but whether miR-381 has the same function in breast cancer is not well know. METHODS: The over express or silence miR-381 expressing cell lines were constructed by lentivirus infection to reveal the biological functions of miR-381 in vitro. The expression of miR-381 and CCNA2 in 162 breast cancer patients were detected to further reveal their impact and predictive value on progression-free survival (PFS) and overall survival (OS). RESULTS: After transfection of MDA-MB-231 and MCF-7 cells with miR-381 mimics, the expression of miR-381 was effectively up-regulated and CCNA2 was effectively down-regulated, while the opposite results were observed in tumour cell which transfected with miR-381 inhibitors. After transfection of cell lines with miR-381 mimics, tumour cell activity was significantly reduced, while the opposite results were observed in tumour cell which transfected with miR-381 inhibitors. The area under curves (AUCs) of miRNA-381 and CCNA2 for predicting PFS and OS were 0.711, 0.695, 0.694 and 0.675 respectively. Cox regression analysis showed that miRNA-381 ≥ 1.65 2-ΔΔCt and CCNA ≥ 2.95 2-ΔΔCt were the influence factors of PFS and OS, the hazard ratio (HR) values were 0.553, 2.075, 0.462 and 2.089, respectively. CONCLUSION: miR-381 inhibitors breast cancer cells proliferation and migration by down-regulating the expression of CCNA2, both of them can predict the prognosis of breast cancer.

miR-381 can regulate the expression of cyclin A2 and inhibit the proliferation and migration of bladder cancer cells, but whether miR-381 has the same function in breast cancer is not well know. We analysed the levels of miR-381 and cyclin A2 in breast cancer patients and breast cancer cells to reveal the mechanism of miR-381 affecting the expression of cyclin A2. We found miRNA-381 affects the proliferation and migration of breast cancer cells by down-regulating the expression of cyclin A2. The expression of serum miR-381 and cyclin A2 have important values in predicting the prognosis of breast cancer. Our findings provide mechanistic insights into how miR-381 regulates the proliferation and migration of breast cancer, as well as a new target for clinical treatment. Future research may focus on how to improve patient prognosis by up-regulating expression of miR-381 and down-regulating the expression of cyclin A2.

LncRNA MTC-p65 Protein Mediates Skin Fibroblast Proliferation in Liaoning Cashmere Goat by Regulating the Nuclear Factor-Kappa B Signaling Pathway.

The aim of this study is to investigate the activation of NF-κB signaling pathway and the regulation of the expression of genes related to chorionic villus growth by the binding of LncRNA MTC (XLOC_005914) and p65 (transcription factor p65 [Capra hircus], XP_017898873.1). In addition, the regulation of LncRNA MTC and p65 binding on the proliferation of Liaoning Cashmere Goat skin fibroblasts is investigated. The upregulation of LncRNA MTC promoted the proliferation of skin fibroblasts, and the NF-κB signaling pathway played an important role in this process. Compared with the negative control (NC group), the expression of TNFα and NFKB2(NF-κB) genes was highly significantly up-regulated (P < 0.001), and NFKBIA(IκBɑ) genes were highly significantly down-regulated (P < 0.01) after LncRNA MTC overexpression (OE group). The expression levels of TNFα and NFκB-P-p65 proteins were upregulated in the OE group; NF-κB-p65 expression levels were upregulated in the nucleus, IκBα expression levels were downregulated in the cytoplasm, and P-IκBα expression levels were upregulated. LncRNA MTC and p65 proteins were co-localized in the cells. Meanwhile, LncRNA MTC and p65 protein showed significant nucleation in the OE group. RNA pull-down and LC-MS/MS verified that p65 protein was indeed an interacting protein of LncRNA MTC. LncRNA MTC binds to p65 protein, upregulates the expression of TNFα protein, nucleates p65 protein, and activates NF-κB signaling pathway to promote the proliferation of skin fibroblasts in Liaoning Cashmere Goat.

Identification of Key Genes of Fruit Shape Variation in Jujube with Integrating Elliptic Fourier Descriptors and Transcriptome.

Jujube (Ziziphus jujuba) exhibits a rich diversity in fruit shape, with natural occurrences of gourd-like, flattened, and other special shapes. Despite the ongoing research into fruit shape, studies integrating elliptical Fourier descriptors (EFDs) with both Short Time-series Expression Miner (STEM) and weighted gene co-expression network analysis (WGCNA) for gene discovery remain scarce. In this study, six cultivars of jujube fruits with distinct shapes were selected, and samples were collected from the fruit set period to the white mature stage across five time points for shape analysis and transcriptome studies. By combining EFDs with WGCNA and STEM, the study aimed to identify the critical periods and key genes involved in the formation of jujube fruit shape. The findings indicated that the D25 (25 days after flowering) is crucial for the development of jujube fruit shape. Moreover, ZjAGL80, ZjABI3, and eight other genes have been implicated to regulate the shape development of jujubes at different periods of fruit development, through seed development and fruit development pathway. In this research, EFDs were employed to precisely delineate the shape of jujube fruits. This approach, in conjunction with transcriptome, enhanced the precision of gene identification, and offered an innovative methodology for fruit shape analysis. This integration facilitates the advancement of research into the morphological characteristics of plant fruits, underpinning the development of a refined framework for the genetic underpinnings of fruit shape variation.

Artificial intelligence for the detection of glaucoma with SD-OCT images: a systematic review and Meta-analysis.

AIM: To quantify the performance of artificial intelligence (AI) in detecting glaucoma with spectral-domain optical coherence tomography (SD-OCT) images. METHODS: Electronic databases including PubMed, Embase, Scopus, ScienceDirect, ProQuest and Cochrane Library were searched before May 31, 2023 which adopted AI for glaucoma detection with SD-OCT images. All pieces of the literature were screened and extracted by two investigators. Meta-analysis, Meta-regression, subgroup, and publication of bias were conducted by Stata16.0. The risk of bias assessment was performed in Revman5.4 using the QUADAS-2 tool. RESULTS: Twenty studies and 51 models were selected for systematic review and Meta-analysis. The pooled sensitivity and specificity were 0.91 (95%CI: 0.86-0.94, I2=94.67%), 0.90 (95%CI: 0.87-0.92, I2=89.24%). The pooled positive likelihood ratio (PLR) and negative likelihood ratio (NLR) were 8.79 (95%CI: 6.93-11.15, I2=89.31%) and 0.11 (95%CI: 0.07-0.16, I2=95.25%). The pooled diagnostic odds ratio (DOR) and area under curve (AUC) were 83.58 (95%CI: 47.15-148.15, I2=100%) and 0.95 (95%CI: 0.93-0.97). There was no threshold effect (Spearman correlation coefficient=0.22, P>0.05). CONCLUSION: There is a high accuracy for the detection of glaucoma with AI with SD-OCT images. The application of AI-based algorithms allows together with "doctor+artificial intelligence" to improve the diagnosis of glaucoma.

Jeotgalibacillus haloalkalitolerans sp. nov., a novel alkalitolerant and halotolerant bacterium, isolated from the confluence of the Fenhe River and the Yellow River.

A Gram-stain positive, aerobic, alkalitolerant and halotolerant bacterium, designated HH7-29 T, was isolated from the confluence of the Fenhe River and the Yellow River in Shanxi Province, PR China. Growth occurred at pH 6.0-12.0 (optimum, pH 8.0-8.5) and 15-40℃ (optimum, 32℃) with 0.5-24% NaCl (optimum, 2-9%). The predominant fatty acids (> 10.0%) were iso-C15:0 and anteiso-C15:0. The major menaquinones were MK-7 and MK-8. The polar lipids were phosphatidylglycerol, diphosphatidylglycerol and two unidentified phospholipids. Phylogenetic analyses based on the 16S rRNA gene sequence revealed that strain HH7-29 T was a member of the genus Jeotgalibacillus, exhibiting high sequence similarity to the 16S rRNA gene sequences of Jeotgalibacillus alkaliphilus JC303T (98.4%), Jeotgalibacillus salarius ASL-1 T (98.1%) and Jeotgalibacillus alimentarius YKJ-13 T (98.1%). The genomic DNA G + C content was 43.0%. Gene annotation showed that strain HH7-29 T had lower protein isoelectric points (pIs) and possessed genes related to ion transport and organic osmoprotectant uptake, implying its potential tolerance to salt and alkali. The average nucleotide identity, digital DNA-DNA hybridization values, amino acid identity values, and percentage of conserved proteins values between strain HH7-29 T and its related species were 71.1-83.8%, 19.5-27.4%, 66.5-88.4% and 59.8-76.6%, respectively. Based on the analyses of phenotypic, chemotaxonomic, phylogenetic and genomic features, strain HH7-29 T represents a novel species of the genus Jeotgalibacillus, for which the name Jeotgalibacillus haloalkalitolerans sp. nov. is proposed. The type strain is HH7-29 T (= KCTC 43417 T = MCCC 1K07541T).

The metabolic reprogramming of γ-aminobutyrate in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is the most common head and neck malignancy. The oncometabolites have been studied in OSCC, but the mechanism of metabolic reprogramming remains unclear. To identify the potential metabolic markers to distinguish malignant oral squamous cell carcinoma (OSCC) tissue from adjacent healthy tissue and study the mechanism of metabolic reprogramming in OSCC. We compared the metabolites between cancerous and paracancerous tissues of OSCC patients by 1HNMR analysis. We established OSCC derived cell lines and analyzed their difference of RNA expression by RNA sequencing. We investigated the metabolism of γ-aminobutyrate in OSCC derived cells by real time PCR and western blotting. Our data revealed that much more γ-aminobutyrate was produced in cancerous tissues of OSCC patients. The investigation based on OSCC derived cells showed that the increase of γ-aminobutyrate was promoted by the synthesis of glutamate beyond the mitochondria. In OSCC cancerous tissue derived cells, the glutamate was catalyzed to glutamine by glutamine synthetase (GLUL), and then the generated glutamine was metabolized to glutamate by glutaminase (GLS). Finally, the glutamate produced by glutamate-glutamine-glutamate cycle was converted to γ-aminobutyrate by glutamate decarboxylase 2 (GAD2). Our study is not only benefit for understanding the pathological mechanisms of OSCC, but also has application prospects for the diagnosis of OSCC.

Cloning of CAT genes in Satsuma mandarin and their expression characteristics in response to environmental stress and arbuscular mycorrhizal fungi.

KEY MESSAGE: CitCAT1 and CitCAT2 were cloned and highly expressed in mature leaves. High temperatures up-regulated CitCAT1 expression, while low temperatures and Diversispora versiformis up-regulated CitCAT2 expression, maintaining a low oxidative damage. Catalase (CAT), a tetrameric heme-containing enzyme, removes hydrogen peroxide (H2O2) to maintain low oxidative damage in plants exposed to environmental stress. This study aimed to clone CAT genes from Citrus sinensis cv. "Oita 4" and analyze their expression patterns in response to environmental stress, exogenous abscisic acid (ABA), and arbuscular mycorrhizal fungal inoculation. Two CAT genes, CitCAT1 (NCBI accession: PP067858) and CitCAT2 (NCBI accession: PP061394) were cloned, and the open reading frames of their proteins were 1479 bp and 1539 bp, respectively, each encoding 492 and 512 amino acids predicted to be localized in the peroxisome, with CitCAT1 being a stable hydrophilic protein and CitCAT2 being an unstable hydrophilic protein. The similarity of their amino acid sequences reached 83.24%, and the two genes were distantly related. Both genes were expressed in stems, leaves, flowers, and fruits, accompanied by the highest expression in mature leaves. In addition, CitCAT1 expression was mainly up-regulated by high temperatures (37 °C), exogenous ABA, and PEG stress within a short period of time, whereas CitCAT2 expression was up-regulated by exogenous ABA and low-temperature (4 °C) stress. Low temperatures (0 °C) for 12 h just up-regulated CitCAT2 expression in Diversispora versiformis-inoculated plants, and D. versiformis inoculation up-regulated CitCAT2 expression, along with lower hydrogen peroxide and malondialdehyde levels in mycorrhizal plants at low temperatures. It is concluded that CitCAT2 has an important role in resistance to low temperatures as well as mycorrhizal enhancement of host resistance to low temperatures.

Evaluating the Predictive Value of a Coagulation-Related Gene Model in Glioma.

AIM: To evaluate coagulation related gene model as a biomarker for predicting prognosis of gliomas. MATERIAL AND METHODS: The mRNA expression and clinical data of glioma were downloaded from the TCGA and CGGA databases. Coagulation-related genes were downloaded from the KEGG database. The expression model was constructed using LASSO regression. The GBM data were divided into high and low-risk expression groups based on the median risk score, and the differences in overall survival and progression-free survival between them were calculated. The prognostic model was further validated using the TCGA-LGG and CGGA glioma databases, respectively. The accuracy of the risk score was calculated by ROC analysis for 1 year and 3 years. RESULTS: Four model genes, namely the SERPINA5, PLAUR, BDKRB1, and PTGIR, were identified, and the risk score was calculated as follows: risk score= SERPINA5*0.126264111304559 + PLAUR*0.288587629696211 + BDKRB1*0.349215422945011 + PTGIR*0.17334527969703, respectively. Based on glioma data from three groups, patients were divided into high and low-risk groups according to the median risk score. The overall survival, progression-free survival, and risk scores of the high-risk score group were worse than the low-risk group. The ROC curve analysis showed that the AUC values of the coagulation-related gene model at 1 year, 3 years, and 5 years were more than 0.65, validating the reliability of the prognostic model. CONCLUSION: This study established the correlation between the coagulation-related gene model and glioma prognosis, providing deeper insight into the mechanism and treatment of glioma.

Histopathology language-image representation learning for fine-grained digital pathology cross-modal retrieval.

Large-scale digital whole slide image (WSI) datasets analysis have gained significant attention in computer-aided cancer diagnosis. Content-based histopathological image retrieval (CBHIR) is a technique that searches a large database for data samples matching input objects in both details and semantics, offering relevant diagnostic information to pathologists. However, the current methods are limited by the difficulty of gigapixels, the variable size of WSIs, and the dependence on manual annotations. In this work, we propose a novel histopathology language-image representation learning framework for fine-grained digital pathology cross-modal retrieval, which utilizes paired diagnosis reports to learn fine-grained semantics from the WSI. An anchor-based WSI encoder is built to extract hierarchical region features and a prompt-based text encoder is introduced to learn fine-grained semantics from the diagnosis reports. The proposed framework is trained with a multivariate cross-modal loss function to learn semantic information from the diagnosis report at both the instance level and region level. After training, it can perform four types of retrieval tasks based on the multi-modal database to support diagnostic requirements. We conducted experiments on an in-house dataset and a public dataset to evaluate the proposed method. Extensive experiments have demonstrated the effectiveness of the proposed method and its advantages to the present histopathology retrieval methods. The code is available at https://github.com/hudingyi/FGCR.