Deep Learning Used with a Colorimetric Sensor Array to Detect Indole for Nondestructive Monitoring of Shrimp Freshness.

Intelligent colorimetric freshness indicator is a low-cost way to intuitively monitor the freshness of fresh food. A colorimetric strip sensor array was prepared by p-dimethylaminocinnamaldehyde (PDL)-doped poly(vinyl alcohol) (PVA) and chitosan (Chit) for the quantitative analysis of indole, which is an indicator of shrimp freshness. As a result of indole simulation, the array strip turned from faint yellow to pink or mulberry color with the increasing indole concentration, like a progress bar. The indicator film exhibited excellent permeability, mechanical and thermal stability, and color responsiveness to indole, which was attributed to the interactions between PDL and Chit/PVA. Furthermore, the colorimetric strip sensor array provided a good relationship between the indole concentration and the color intensity within a range of 50-350 ppb. The pathogens and spoilage bacteria of shrimp possessed the ability to produce indole, which caused the color changes of the strip sensor array. In the shrimp freshness monitoring experiment, the color-changing progress of the strip sensor array was in agreement with the simulation and could distinguish the shrimp freshness levels. The image classification system based on deep learning were developed, the accuracies of four DCNN algorithms are above 90%, with VGG16 achieving the highest accuracy at 97.89%. Consequently, a "progress bar" strip sensor array has the potential to realize nondestructive, more precise, and commercially available food freshness monitoring using simple visual inspection and intelligent equipment identification.

Computational identification of mitochondrial dysfunction biomarkers in severe SARS-CoV-2 infection: Facilitating therapeutic applications of phytomedicine.

BACKGROUND: Currently, SARS-CoV-2 has not disappeared and continues to prevail worldwide, with the ongoing risk of mutations and the potential for severe COVID-19. The impairment of monocyte mitochondrial function caused by SARS-CoV-2, leading to a metabolic and immune dysregulation, is a crucial factor in the development of severe COVID-19. PURPOSE: Discover effective phytomedicines based on mitochondrial-related biomarkers in severe SARS-CoV-2 infection. METHODS: Firstly, differential gene analysis and gene set enrichment analysis (GSEA) were conducted on monocytes datasets to identify genes and pathways distinguishing severe patients from uninfected individuals. Then, GO and KEGG enrichment analysis on the differentially expressed genes (DEGs) obtained. Take the DEGs and intersect them with the MitoCarta 3.0 gene set to obtain the differentially expressed mitochondrial-related genes (DE-MRGs). Subsequently, machine learning algorithms were employed to screen potential mitochondrial dysfunction biomarkers for severe COVID-19 based on score values. ROC curves were then plotted to assess the distinguish capability of the biomarkers, followed by validation using two additional independent datasets. Next, the effects of the identified biomarkers on metabolic pathways and immune cells were explored through Gene Set Variation Analysis (GSVA) and CIBERSORT. Finally, potential nature products for severe COVID-19 were screened from the expression profile dataset based on dysregulated mitochondrial-related genes, followed by in vitro experimental validation. RESULTS: There are 1812 DEGs and 17 dysregulated mitochondrial processes between severe COVID-19 patients and uninfected individuals. A total of 77 DE-MRGs were identified, and the potential biomarkers were identified as RECQL4, PYCR1, PIF1, POLQ, and GLDC. In both the training and validation sets, the area under the ROC curve (AUC) for these five biomarkers was greater than 0.9. And they did not show significant changes in mild to moderate patients (p > 0.05), indicating their ability to effectively distinguish severe COVID-19. These biomarkers exhibit a highly significant correlation with the dysregulated metabolic processes (p < 0.05) and immune cell imbalance (p < 0.05) in severe patients, as demonstrated by GSVA and CIBERSORT algorithms. Curcumin has the highest score in the predictive model based on transcriptomic data from 496 natural compounds (p = 0.02; ES = 0.90). Pre-treatment with curcumin for 8 h has been shown to alleviate mitochondrial membrane potential damage caused by the SARS-CoV-2 S1 protein (p < 0.05) and reduce elevated levels of reactive oxygen species (ROS) (p < 0.01). CONCLUSION: The results of this study indicate a significant correlation between severe SARS-CoV-2 infection and mitochondrial dysfunction. The proposed mitochondrial dysfunction biomarkers identified in this study are associated with the disease progression, metabolic and immune changes in severe SARS-CoV-2 infected patients. Curcumin has a potential role in preventing severe COVID-19 by protecting mitochondrial function. Our findings provide new strategies for predicting the prognosis and enabling early intervention in SARS-CoV-2 infection.

A 5:2 Intermittent Fasting Meal Replacement Diet and Glycemic Control for Adults With Diabetes: The EARLY Randomized Clinical Trial.

Importance: An intermittent fasting plan consisting of 2 nonconsecutive fasting days and 5 days of habitual intake per week and meal replacement diet (5:2 MR) could provide additional benefits to patients with type 2 diabetes. Objective: To evaluate the effect of the 5:2 MR on glycemic control among patients with early type 2 diabetes compared with metformin and empagliflozin. Design, Setting, and Participants: The EARLY (Exploration of Treatment of Newly Diagnosed Overweight/Obese Type 2 Diabetes Mellitus) study is a randomized, open-label, active parallel-controlled clinical trial conducted between November 13, 2020, and December 29, 2022, in 9 centers across China. A total of 509 eligible patients underwent screening, out of which 405 were randomly assigned to 3 groups and included in the intention-to-treat analysis. Interventions: Patients were randomly allocated in a 1:1:1 ratio to receive either metformin, empagliflozin, or 5:2 MR. The treatment was 16 weeks, with an 8-week follow-up. Main Outcomes and Measures: The primary end point was the change in hemoglobin A1c (HbA1c) level from baseline to 16 weeks. Secondary end points included changes in body weight, anthropometric measurements, and biochemical parameters. Results: Of the 405 randomized participants (265 men [65.4%]; mean [SD] age, 45.5 [11.0] years; mean [SD] body mass index, 29.5 [4.1]; and mean [SD] HbA1c level, 7.9% [0.6%]), 332 completed the 16-week treatment. From baseline to week 16, participants in the 5:2 MR group showed the greatest reduction in HbA1c (least-squares mean [LSM], -1.9% [SE, 0.2%]), significantly greater than patients receiving metformin (LSM, -1.6% [SE, 0.2%]; adjusted LSM difference, -0.3% [95% CI, -0.4% to -0.1%]) and empagliflozin (LSM, -1.5% [SE, 0.2%]; adjusted LSM difference, -0.4% [95% CI, -0.6% to -0.2%]). At week 16, the mean weight loss in the 5:2 MR group (LSM, -9.7 kg [SE, 2.2 kg]) was greater than that in the metformin group (LSM, -5.5 kg [SE, 2.3 kg]) and empagliflozin group (LSM, -5.8 kg [SE, 2.3 kg]). Conclusions and Relevance: This randomized clinical trial of Chinese adults with overweight or obesity and with early type 2 diabetes found that 5:2 MR could improve glycemic outcomes and weight loss in the short term compared with metformin or empagliflozin, making it a promising initial intervention and early management for type 2 diabetes. Trial Registration: Chinese Clinical Trial Registry Identifier: ChiCTR2000040656.

Successful endoscopic closure of alveolar-pleural fistula due to Aspergillus empyema using a ventricular septal defect occluder.

We report a patient with fever and cough for 2 months who was finally given a diagnosis of alveolar-pleural fistula due to aspergillus empyema. We successfully closed the alveolar-pleural fistula with a ventricular septal defect occluder through bronchoscopy. Endoscopic closure of an alveolar-pleural fistula with ventricular septal defect occluder is worth being explored.

SATB1, senescence and senescence-related diseases.

Aging leads to an accumulation of cellular mutations and damage, increasing the risk of senescence, apoptosis, and malignant transformation. Cellular senescence, which is pivotal in aging, acts as both a guard against cellular transformation and as a check against cancer progression. It is marked by stable cell cycle arrest, widespread macromolecular changes, a pro-inflammatory profile, and altered gene expression. However, it remains to be determined whether these differing subsets of senescent cells result from unique intrinsic programs or are influenced by their environmental contexts. Multiple transcription regulators and chromatin modifiers contribute to these alterations. Special AT-rich sequence-binding protein 1 (SATB1) stands out as a crucial regulator in this process, orchestrating gene expression by structuring chromatin into loop domains and anchoring DNA elements. This review provides an overview of cellular senescence and delves into the role of SATB1 in senescence-related diseases. It highlights SATB1's potential in developing antiaging and anticancer strategies, potentially contributing to improved quality of life and addressing aging-related diseases.

Effects of Klebsiella michiganensis LDS17 on Codonopsis pilosula growth, rhizosphere soil enzyme activities, and microflora, and genome-wide analysis of plant growth-promoting genes.

Codonopsis pilosula is a perennial herbaceous liana with medicinal value. It is critical to promote Codonopsis pilosula growth through effective and sustainable methods, and the use of plant growth-promoting bacteria (PGPB) is a promising candidate. In this study, we isolated a PGPB, Klebsiella michiganensis LDS17, that produced a highly active 1-aminocyclopropane-1-carboxylate deaminase from the Codonopsis pilosula rhizosphere. The strain exhibited multiple plant growth-promoting properties. The antagonistic activity of strain LDS17 against eight phytopathogenic fungi was investigated, and the results showed that strain LDS17 had obvious antagonistic effects on Rhizoctonia solani, Colletotrichum camelliae, Cytospora chrysosperma, and Phomopsis macrospore with growth inhibition rates of 54.22%, 49.41%, 48.89%, and 41.11%, respectively. Inoculation of strain LDS17 not only significantly increased the growth of Codonopsis pilosula seedlings but also increased the invertase and urease activities, the number of culturable bacteria, actinomycetes, and fungi, as well as the functional diversity of microbial communities in the rhizosphere soil of the seedlings. Heavy metal (HM) resistance tests showed that LDS17 is resistant to copper, zinc, and nickel. Whole-genome analysis of strain LDS17 revealed the genes involved in IAA production, siderophore synthesis, nitrogen fixation, P solubilization, and HM resistance. We further identified a gene (koyR) encoding a plant-responsive LuxR solo in the LDS17 genome. Klebsiella michiganensis LDS17 may therefore be useful in microbial fertilizers for Codonopsis pilosula. The identification of genes related to plant growth and HM resistance provides an important foundation for future analyses of the molecular mechanisms underlying the plant growth promotion and HM resistance of LDS17. IMPORTANCE: We comprehensively evaluated the plant growth-promoting characteristics and heavy metal (HM) resistance ability of the LDS17 strain, as well as the effects of strain LDS17 inoculation on the Codonopsis pilosula seedling growth and the soil qualities in the Codonopsis pilosula rhizosphere. We conducted whole-genome analysis and identified lots of genes and gene clusters contributing to plant-beneficial functions and HM resistance, which is critical for further elucidating the plant growth-promoting mechanism of strain LDS17 and expanding its application in the development of plant growth-promoting agents used in the environment under HM stress.

Validation of artificial intelligence-based bowel preparation assessment in screening colonoscopy (with video).

BACKGROUND AND AIMS: Accurate bowel preparation assessment is essential for determining colonoscopy screening intervals. Patients with suboptimal bowel preparation are at a high risk of missing >5 mm adenomas and should undergo an early repeat colonoscopy. In this study, we used artificial intelligence (AI) to evaluate bowel preparation and validated the ability of the system to accurately identify patients who are at high risk of having >5 mm adenomas missed due to inadequate bowel preparation. METHODS: This prospective, single-center, observational study was conducted at the Eighth Affiliated Hospital, Sun Yat-sen University, from October 8, 2021, to November 9, 2022. Eligible patients who underwent screening colonoscopy were consecutively enrolled. The AI assessed bowel preparation using the e-Boston Bowel Preparation Scale (e-BBPS) while endoscopists made evaluations using BBPS. If both BBPS and e-BBPS deemed preparation adequate, the patient immediately underwent a second colonoscopy; otherwise, the patient underwent bowel re-cleansing before the second colonoscopy. RESULTS: Among the 393 patients, 72 adenomas >5 mm in size were detected; 27 adenomas >5 mm in size were missed. In unqualified-AI patients, the >5 mm adenoma miss rate (AMR) was significantly higher than in qualified-AI patients (35.71% vs 13.19% [P = .0056]; odds ratio [OR], .2734 [95% CI, .1139-.6565]), as were the AMR (50.89% vs 20.79% [P < .001]; OR, .2532 [95% CI, .1583-.4052]) and >5 mm polyp miss rate (35.82% vs 19.48% [P = .0152]; OR, .4335 [95% CI, .2288-.8213]). CONCLUSIONS: This study confirmed that patients classified as inadequate by AI exhibited an unacceptable >5 mm AMR, providing key evidence for implementing AI in guiding bowel re-cleansing and potentially standardizing future colonoscopy screening. (Clinical trial registration number: NCT05145712.).

Deep learning assists detection of esophageal cancer and precursor lesions in a prospective, randomized controlled study.

Endoscopy is the primary modality for detecting asymptomatic esophageal squamous cell carcinoma (ESCC) and precancerous lesions. Improving detection rate remains challenging. We developed a system based on deep convolutional neural networks (CNNs) for detecting esophageal cancer and precancerous lesions [high-risk esophageal lesions (HrELs)] and validated its efficacy in improving HrEL detection rate in clinical practice (trial registration ChiCTR2100044126 at www.chictr.org.cn). Between April 2021 and March 2022, 3117 patients ≥50 years old were consecutively recruited from Taizhou Hospital, Zhejiang Province, and randomly assigned 1:1 to an experimental group (CNN-assisted endoscopy) or a control group (unassisted endoscopy) based on block randomization. The primary endpoint was the HrEL detection rate. In the intention-to-treat population, the HrEL detection rate [28 of 1556 (1.8%)] was significantly higher in the experimental group than in the control group [14 of 1561 (0.9%), P = 0.029], and the experimental group detection rate was twice that of the control group. Similar findings were observed between the experimental and control groups [28 of 1524 (1.9%) versus 13 of 1534 (0.9%), respectively; P = 0.021]. The system's sensitivity, specificity, and accuracy for detecting HrELs were 89.7, 98.5, and 98.2%, respectively. No adverse events occurred. The proposed system thus improved HrEL detection rate during endoscopy and was safe. Deep learning assistance may enhance early diagnosis and treatment of esophageal cancer and may become a useful tool for esophageal cancer screening.

PLD2 deletion ameliorates sepsis-induced cardiomyopathy by suppressing cardiomyocyte pyroptosis via the NLRP3/caspase 1/GSDMD pathway.

OBJECTIVE: Sepsis-induced cardiomyopathy (SICM) is a life-threatening complication. Phospholipase D2 (PLD2) is crucial in mediating inflammatory reactions and is associated with the prognosis of patients with sepsis. Whether PLD2 is involved in the pathophysiology of SICM remains unknown. This study aimed to investigate the effect of PLD2 knockout on SICM and to explore potential mechanisms. METHODS: The SICM model was established using cecal ligation and puncture in wild-type and PLD2-knockout mice and lipopolysaccharide (LPS)-induced H9C2 cardiomyocytes. Transfection with PLD2-shRNA lentivirus and a PLD2 overexpression plasmid were used to interfere with PLD2 expression in H9C2 cells. Cardiac pathological alterations, cardiac function, markers of myocardial injury, and inflammatory factors were used to evaluate the SICM model. The expression of pyroptosis-related proteins (NLRP3, cleaved caspase 1, and GSDMD-N) was assessed using western blotting, immunofluorescence, and immunohistochemistry. RESULTS: SICM mice had myocardial tissue damage, increased inflammatory response, and impaired heart function, accompanied by elevated PLD2 expression. PLD2 deletion improved cardiac histological changes, mitigated cTNI production, and enhanced the survival of the SICM mice. Compared with controls, PLD2-knockdown H9C2 exhibits a decrease in inflammatory markers and lactate dehydrogenase production, and scanning electron microscopy results suggest that pyroptosis may be involved. The overexpression of PLD2 increased the expression of NLRP3 in cardiomyocytes. In addition, PLD2 deletion decreased the expression of pyroptosis-related proteins in SICM mice and LPS-induced H9C2 cells. CONCLUSION: PLD2 deletion is involved in SICM pathogenesis and is associated with the inhibition of the myocardial inflammatory response and pyroptosis through the NLRP3/caspase 1/GSDMD pathway.

Combination of retagliptin and henagliflozin as add-on therapy to metformin in patients with type 2 diabetes inadequately controlled with metformin: A multicentre, randomized, double-blind, active-controlled, phase 3 trial.

AIM: This study assessed the efficacy and safety of co-administering retagliptin and henagliflozin versus individual agents at corresponding doses in patients with type 2 diabetes mellitus who were inadequately controlled with metformin. METHODS: This multicentre, phase 3 trial consisted of a 24-week, randomized, double-blind, active-controlled period. Patients with glycated haemoglobin (HbA1c) levels between 7.5% and 10.5% were randomized to receive once-daily retagliptin 100 mg (R100; n = 155), henagliflozin 5 mg (H5; n = 156), henagliflozin 10 mg (H10; n = 156), co-administered R100/H5 (n = 155), or R100/H10 (n = 156). The primary endpoint was the change in HbA1c from baseline to week 24. RESULTS: Based on the primary estimand, the least squares mean reductions in HbA1c at week 24 were significantly greater in the R100/H5 (-1.51%) and R100/H10 (-1.54%) groups compared with those receiving the corresponding doses of individual agents (-0.98% for R100, -0.86% for H5 and -0.95% for H10, respectively; p < .0001 for all pairwise comparisons). Achievement of HbA1c <7.0% at week 24 was observed in 27.1% of patients in the R100 group, 21.2% in the H5 group, 24.4% in the H10 group, 57.4% in the R100/H5 group and 56.4% in the R100/H10 group. Reductions in fasting plasma glucose and 2-h postprandial glucose were also more pronounced in the co-administration groups compared with the individual agents at corresponding doses. Decreases in body weight and systolic blood pressure were greater in the groups containing henagliflozin than in the R100 group. The incidence rates of adverse events were similar across all treatment groups, with no reported episodes of severe hypoglycaemia. CONCLUSIONS: For patients with type 2 diabetes mellitus inadequately controlled by metformin monotherapy, the co-administration of retagliptin and henagliflozin yielded more effective glycaemic control through 24 weeks compared with the individual agents at their corresponding doses.

Identification of prognostic signatures in remnant gastric cancer through an interpretable risk model based on machine learning: a multicenter cohort study.

OBJECTIVE: The purpose of this study was to develop an individual survival prediction model based on multiple machine learning (ML) algorithms to predict survival probability for remnant gastric cancer (RGC). METHODS: Clinicopathologic data of 286 patients with RGC undergoing operation (radical resection and palliative resection) from a multi-institution database were enrolled and analyzed retrospectively. These individuals were split into training (80%) and test cohort (20%) by using random allocation. Nine commonly used ML methods were employed to construct survival prediction models. Algorithm performance was estimated by analyzing accuracy, precision, recall, F1-score, area under the receiver operating characteristic curve (AUC), confusion matrices, five-fold cross-validation, decision curve analysis (DCA), and calibration curve. The best model was selected through appropriate verification and validation and was suitably explained by the SHapley Additive exPlanations (SHAP) approach. RESULTS: Compared with the traditional methods, the RGC survival prediction models employing ML exhibited good performance. Except for the decision tree model, all other models performed well, with a mean ROC AUC above 0.7. The DCA findings suggest that the developed models have the potential to enhance clinical decision-making processes, thereby improving patient outcomes. The calibration curve reveals that all models except the decision tree model displayed commendable predictive performance. Through CatBoost-based modeling and SHAP analysis, the five-year survival probability is significantly influenced by several factors: the lymph node ratio (LNR), T stage, tumor size, resection margins, perineural invasion, and distant metastasis. CONCLUSIONS: This study established predictive models for survival probability at five years in RGC patients based on ML algorithms which showed high accuracy and applicative value.

Bacterial elimination via cell membrane penetration by violet phosphorene peripheral sub-nanoneedles combined with oxidative stress.

The effectiveness of an antibacterial agent is strongly influenced by its antibacterial mechanism, which, in turn, depends on the agent's topological structure. In the natural world, the nanoprotrusions on the surface of insect wings give them excellent antimicrobial properties through physical penetration while being compatible with host cells. Inspired by the novel nanostructure of insect wings, violet phosphorus (VP), a new member of the phosphorus family, has antibacterial potential due to the sub-nanoneedle on its edge. Here, we demonstrate that VP and its exfoliated product, violet phosphorene nanosheets (VPNSs), have superior antibacterial capability against pathogens via cell membrane penetration induced by peripheral sub-nanoneedles combined with oxidative stress. The results show that VPNSs can inactivate more than 99.9% of two common pathogens (Escherichia coli and Staphylococcus aureus) and more than 99.9% of two antibiotic-resistant bacteria (Escherichia coli pUC19 and methicillin-resistant Staphylococcus aureus), while showing almost no toxicity toward normal cells at a high concentration of 2.0 mg mL-1. Moreover, VPNSs can achieve effective treatment of induced skin wound infections and bacterial keratitis (BK) by Staphylococcus aureus and methicillin-resistant Staphylococcus aureus, respectively, showing promising potential for ocular and skin wound infection theragnostics.

Clustering human dental pulp fibroblasts spontaneously activate NLRP3 and AIM2 inflammasomes and induce IL-1ß secretion.

Objectives: The objective of the present study was to investigate whether NOD-like receptor family pyrin domain-containing 3 (NLRP3) and absent in melanoma 2 (AIM2) inflammasomes pathways were involved in an experimental model of fibroblast activation named nemosis, which was used to mimic circumstances without bacteria stimulation. Methods: Nemosis of human dental pulp fibroblast (DPFs) was induced by three-dimensional culture in U-shaped 96-well plates and investigated by scanning electron microscopy (SEM). DPFs monolayers were used as control. Annexin V-FITC/7-AAD apoptosis assay was performed on the DPFs spheroids by flowcytometry. Caspase-1 activity detection assay was conducted on the DPFs spheroids. Quantitative real-time polymerase chain reaction (qRT-PCR), cytokine measurements, Western blot and the effect of COX-2 inhibitor on spheroids was studied. Results: SEM study observed human dental pulp fibroblast clusters and cell membranes damage on the surface of DPFs spheroids. The percentages of necrotic cells from DPFs spheroids gradually increased as the incubation time increased. A statistically significant increase in caspase-1 activity was observed after DPFs spheroids formation. DPFs spheroids displayed significant amounts of NLRP3, AIM2 mRNA and protein expression, caspase-1 mRNA expression and cleaved Caspase-1 protein expression and high IL-1ß concentrations (P < 0.05) than DPFs monolayers. Specific COX-2 inhibitor (NS-398) decreased NLRP3 mRNA and protein expression, cleaved Caspase-1 protein expression, Caspase-1 activity and IL-1ß mRNA expression and IL-1ß concentrations (P < 0.05). However, Specific COX-2 inhibitor had no impact on AIM2 mRNA and protein expression, caspase-1 mRNA expression and pro-Caspase-1 protein expression. Conclusions: In conclusion, clustering human DPFs spontaneously activated NLRP3 and AIM2 inflammasomes and induced IL-1ß secretion which could be partially attenuated by COX-2 inhibitor. Thus, nemosis could become a powerful model for studying mechanisms underlying aseptic pulpitis.

Role of the circular RNA regulatory network in the pathogenesis of biliary atresia.

Circular RNAs (circRNAs) serve an essential role in the occurrence and development of cholangiocarcinoma, but the expression and function of circRNA in biliary atresia (BA) is not clear. In the present study, circRNA expression profiles were investigated in the liver tissues of patients with BA as well as in the choledochal cyst (CC) tissues of control patients using RNA sequencing. A total of 78 differentially expressed circRNAs (DECs) were identified between the BA and CC tissues. The expression levels of eight circRNAs (hsa_circ_0006137, hsa_circ_0079422, hsa_circ_0007375, hsa_circ_0005597, hsa_circ_0006961, hsa_circ_0081171, hsa_circ_0084665 and hsa_circ_0075828) in the liver tissues of the BA group and control group were measured using reverse transcription-quantitative polymerase chain reaction. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis demonstrated that the identified DECs are involved in a variety of biological processes, including apoptosis and metabolism. In addition, based on the GO and KEGG pathway enrichment analyses, it was revealed that target genes that can be affected by circRNAs regulatory network were enriched in the TGF-ß signaling pathway, EGFR tyrosine kinase inhibitor resistance pathway and transcription factor regulation pathway as well as other pathways that may be associated with the pathogenesis of BA. The present study revealed that circRNAs are potentially implicated in the pathogenesis of BA and could help to find promising targets and biomarkers for BA.

Inhibition of multiple SARS-CoV-2 variants entry by Lycium barbarum L. polysaccharides through disruption of spike protein-ACE2 interaction.

Viral respiratory infections are major human health concerns. The most striking epidemic disease, COVID-19 is still on going with the emergence of fast mutations and drug resistance of pathogens. A few polysaccharide macromolecules from traditional Chinese medicine (TCM) have been found to have direct anti-SARS-CoV-2 activity but the mechanism remains unclear. In this study, we evaluated the entry inhibition effect of Lycium barbarum polysaccharides (LBP) in vitro and in vivo. We found LBP effectively suppressed multiple SARS-CoV-2 variants entry and protected K18-hACE2 mice from invasion with Omicron pseudovirus (PsV). Moreover, we found LBP interfered with early entry events during infection in time-of-addition (TOA) assay and SEM observation. Further surface plasmon resonance (SPR) study revealed the dual binding of LBP with Spike protein and ACE2, which resulted in the disruption of Spike-ACE2 interaction and subsequently triggered membrane fusion. Therefore, LBP may act as broad-spectrum inhibitors of virus entry and nasal mucosal protective agent against newly emerging respiratory viruses, especially SARS-CoV-2.

The difference of transcriptome of HPV-infected patients contributes more to the occurrence of cervical cancer than the mutations of E6 and E7 genes in HPV16.

Human papillomavirus (HPV) E6 and E7 genes are biomarkers and drivers of the progression of cervical cancer (CxCa). The aim of this study was to investigate the relationship between HPV16 E6, E7 gene mutations and the occurrence and development of CxCa. Cervical exfoliated cells and clinical data of patients with cervical diseases were collected. Sample DNA was extracted, the E6 and E7 gene fragments were amplified by PCR, and the mutations were detected by Sanger sequencing and compared with standard sequences. Microarray was used to sequence the transcriptome of cells. Data of transcriptome analyzed and visualized using R software and its packages. Analysis of clinical characteristics demonstrated the association of HPV16 infection with CxCa (P < .05). Sanger sequencing results showed that the mutation sites of E6 gene included T178G/A, T350G, A131C, and T241G; among these, A131C and T241G were synonymous mutations. The mutation sites of E7 gene included A647G, T846C, G666A, T843C, and T760C, and all of them were synonymous mutations except A647G. There was no significant difference in the distribution of HPV16 E6, E7 mutations among CxCa, cervical intraepithelial neoplasia, and infection groups (P > .05). Compared with the non- CxCa group, gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis of differentially expressed genes (DEGs) showed more significant enrichment of DEGs in the biological processes, pathways, and diseases closely related to cancer. Compared with the non-mutation group, the DEGs in the E6, E7 gene mutation group were significantly enriched in the events related to infection and immunity. To summarize, HPV16 may be associated with the occurrence and development of CxCa, but HPV16 E6 and E7 gene mutations have little effect on the occurrence and development of CxCa. Individual differences may have a greater effect on the progression of CxCa.

Current status of quality control in screening esophagogastroduodenoscopy and the emerging role of artificial intelligence.

Esophagogastroduodenoscopy (EGD) screening is being implemented in countries with a high incidence of upper gastrointestinal (UGI) cancer. High-quality EGD screening ensures the yield of early diagnosis and prevents suffering from advanced UGI cancer and minimal operational-related discomfort. However, performance varied dramatically among endoscopists, and quality control for EGD screening remains suboptimal. Guidelines have recommended potential measures for endoscopy quality improvement and research has been conducted for evidence. Moreover, artificial intelligence offers a promising solution for computer-aided diagnosis and quality control during EGD examinations. In this review, we summarized the key points for quality assurance in EGD screening based on current guidelines and evidence. We also outline the latest evidence, limitations, and future prospects of the emerging role of artificial intelligence in EGD quality control, aiming to provide a foundation for improving the quality of EGD screening.

Construction of photocatalytic coating for alleviating the shriveling of postharvest fruit cucumber after simulated transportation.

The shriveling of fruit cucumber was commonly occurred during supply chain, photocatalyst exposed to UV light can endow the coatings with ethylene removal capacity to reduce the respiration of fruit and water loss. The study developed a novel photodynamic technology responsive photocatalytic coating with exceptional ultraviolet (UV) photocatalytic degradation of ethylene ability to decay the shriveling of postharvest fruit cucumber during supply chain. This coating involved the integration of Carbon dots (CDs)-loaded nano ZnO and the skillful selection of pullulan (Pul) and apple pectin (AP) matrix. The CDs/ZnO coatings boasted an impressive array of photocatalytic degradation of ethylene and adhesion properties, including high ethylene removal rates of 32.04 % in 60 min UV light stimulation. The decrease of cell-wall strength, degradation of the cell wall polysaccharides and water loss resulted in cucumber shriveling. Compared with CK sample, after UV-CDs/ZnO coating treatment, the higher firmness and cell wall polysaccharides were found in cucumbers with lower cell wall degrading enzymes activities, weight loss and water movement, which was associated with the decrease of respiration and ethylene accumulation. The UV-CDs/ZnO coatings possessed promising potential for alleviating the shriveling of postharvest fruit cucumber and applications in fruits preservation in the future.

Starch-based carbon aerogels prepared by an innovative KOH activation method for supercapacitors.

Biomass-based carbon aerogels hold promising application prospect in the field of supercapacitors. In this research, starch was selected as a raw material for preparing carbon aerogels. The preparation process of starch hydrogels was simplified by using KOH, which can change starch suspension into hydrogels at room temperature. Moreover, the molecular mixing of KOH and starch was realized, so that KOH can be fully utilized in the activation process. The specific surface area of the starch-based carbon aerogels prepared by this method was 1349 m2/g, and the proportion of micropores was 43.7 %. Remarkably, as electrode materials for supercapacitors, the starch-based carbon aerogels exhibited outstanding electrochemical performance. In a three-electrode system, the carbon aerogels exhibited specific capacitance of 211.5 F/g at 0.5 A/g and 138.5 F/g at 10 A/g, suggesting their suitability for high-current applications. In a symmetrical supercapacitor configuration, the materials exhibited an energy density of 11.3 Wh/kg at a power density of 0.5 kW/kg and the specific capacitance can maintain 98.91 % after 10,000 cycles. Overall, this work provides a new method for mixing activators, which will foster potential advances in starch based carbon aerogels.