Adipose-derived stem cells promote glycolysis and peritoneal metastasis via TGF-ß1/SMAD3/ANGPTL4 axis in colorectal cancer.

Peritoneal metastasis, the third most common metastasis in colorectal cancer (CRC), has a poor prognosis for the rapid progression and limited therapeutic strategy. However, the molecular characteristics and pathogenesis of CRC peritoneal metastasis are poorly understood. Here, we aimed to elucidate the action and mechanism of adipose-derived stem cells (ADSCs), a prominent component of the peritoneal microenvironment, in CRC peritoneal metastasis formation. Database analysis indicated that ADSCs infiltration was increased in CRC peritoneal metastases, and high expression levels of ADSCs marker genes predicted a poor prognosis. Then we investigated the effect of ADSCs on CRC cells in vitro and in vivo. The results revealed that CRC cells co-cultured with ADSCs exhibited stronger metastatic property and anoikis resistance, and ADSCs boosted the intraperitoneal seeding of CRC cells. Furthermore, RNA sequencing was carried out to identify the key target gene, angiopoietin like 4 (ANGPTL4), which was upregulated in CRC specimens, especially in peritoneal metastases. Mechanistically, TGF-ß1 secreted by ADSCs activated SMAD3 in CRC cells, and chromatin immunoprecipitation assay showed that SMAD3 facilitated ANGPTL4 transcription by directly binding to ANGPTL4 promoter. The ANGPTL4 upregulation was essential for ADSCs to promote glycolysis and anoikis resistance in CRC. Importantly, simultaneously targeting TGF-ß signaling and ANGPTL4 efficiently reduced intraperitoneal seeding in vivo. In conclusion, this study indicates that tumor-infiltrating ADSCs promote glycolysis and anoikis resistance in CRC cells and ultimately facilitate peritoneal metastasis via the TGF-ß1/SMAD3/ANGPTL4 axis. The dual-targeting of TGF-ß signaling and ANGPTL4 may be a feasible therapeutic strategy for CRC peritoneal metastasis.

The Missing Chalcogen Bonding Donor: Strongly Polarized Oxygen of Water.

A biscyclen molecular cabin, synthesized by connecting two cyclen macrocycles with four linkages, entraps a Li+···H2O···Li+ trimer with a water molecule clamped by two Li+ ions. This configuration results in strongly polarized water, characterized by a water proton resonance shift of up to 10.00 ppm. The arrangement facilitates unprecedented O-centered chalcogen bonds between the lone pairs of pyridinyl nitrogen atoms and polarized water oxygen, as confirmed by X-ray crystallography, NMR spectroscopy, and theoretical calculations. Further observation of O-centered chalcogen bonding in a H2O·(LiCl)2 cluster suggests its widespread presence in hydrated salt systems.

Deficiency of SDHC promotes metastasis by reprogramming fatty acid metabolism in colorectal cancer.

BACKGROUND: Several studies have demonstrated a strong correlation between impaired Succinate dehydrogenase (SDH) function and the advancement of tumors. As a subunit of SDH, succinate dehydrogenase complex subunit C (SDHC) has been revealed to play tumor suppressive roles in several cancers, while its specific role in colorectal cancer (CRC) still needs further investigation. METHODS: Online database were utilized to investigate the expression of SDHC in colorectal cancer and to assess its correlation with patient prognosis. Cell metastasis was assessed using transwell and wound healing assays, while tumor metastasis was studied in a nude mice model in vivo. Drug screening and RNA sequencing were carried out to reveal the tumor suppressor mechanism of SDHC. Triglycerides, neutral lipids and fatty acid oxidation were measured using the Triglyceride Assay Kit, BODIPY 493/503 and Colorimetric Fatty Acid Oxidation Rate Assay Kit, respectively. The expression levels of enzymes involved in fatty acid metabolism and the PI3K/AKT signaling pathway were determined by quantitative real-time PCR and western blot. RESULTS: Downregulation of SDHC was found to be closely associated with a poor prognosis in CRC. SDHC knockdown promoted CRC metastasis both in vitro and in vivo. Through drug screening and Gene set enrichment analysis, it was discovered that SDHC downregulation was positively associated with the fatty acid metabolism pathways significantly. The effects of SDHC silencing on metastasis were reversed when fatty acid synthesis was blocked. Subsequent experiments revealed that SDHC silencing activated the PI3K/AKT signaling axis, leading to lipid accumulation by upregulating the expression of aldehyde dehydrogenase 3 family member A2 (ALDH3A2) and reduction of fatty acid oxidation rate by suppressing the expression of acyl-coenzyme A oxidase 1 (ACOX1) and carnitine palmitoyltransferase 1A (CPT1A). CONCLUSIONS: SDHC deficiency could potentially enhance CRC metastasis by modulating the PI3K/AKT pathways and reprogramming lipid metabolism.

CircDiaph3 aggravates H/R-induced cardiomyocyte apoptosis and inflammation through miR-338-3p/SRSF1 axis.

Acute myocardial infarction (AMI) is one of the most prevalent cardiovascular diseases, accounting for a high incidence rate and high mortality worldwide. Hypoxia/reoxygenation (H/R)-induced myocardial cell injury is the main cause of AMI. Several studies have shown that circular RNA contributes significantly to the pathogenesis of AMI. Here, we established an AMI mouse model to investigate the effect of circDiaph3 in cardiac function and explore the functional role of circDiaph3 in H/R-induced cardiomyocyte injury and its molecular mechanism. Bioinformatics tool and RT-qPCR techniques were applied to detect circDiaph3 expression in human patient samples, heart tissues of AMI mice, and H/R-induced H9C2 cells. CCK-8 was used to examine cell viability, while annexin-V/PI staining was used to assess cell apoptosis. Myocardial reactive oxygen species (ROS) levels were detected by immunofluorescence. Western blot was used to detect the protein expression of anti-apoptotic Bcl-2 while pro-apoptotic Bax and cleaved-Caspase-3. Furthermore, ELISA was used to detect inflammatory cytokines production. While bioinformatics tool and RNA pull-down assay were used to verify the interaction between circDiaph3 and miR-338-3p. We found that circDiaph3 expression was high in AMI patients and mice, as well as in H/R-treated H9C2 cells. CircDiaph3 silencing ameliorated apoptosis and inflammatory response of cardiomyocytes in vivo. Moreover, the knockdown of cirDiaph3 mitigated H/R-induced apoptosis and the release of inflammatory mediators like IL-1ß, IL-6, and TNF-α in H9C2 cells. Mechanistically, circDiaph3 induced cell apoptosis and inflammatory responses in H/R-treated H9C2 cells by sponging miR-338-3p. Overexpressing miR-338-3p in H/R-treated cells prominently reversed circDiaph3-induced effects. Notably, miR-338-3p inhibited SRSF1 expression in H/R-treated H9C2 cells. While overexpressing SRSF1 abrogated miR-338-3p-mediated alleviation of apoptosis and inflammation after H/R treatment. To summarize, circDiaph3 aggravates H/R-induced cardiomyocyte apoptosis and inflammation through the miR-338-3p/SRSF1 axis. These findings suggest that the circDiaph3/miR-338-3pp/SRSF1 axis could be a potential therapeutic target for treating H/R-induced myocardial injury.

Long daytime napping: A silent danger for hypertensive individuals.

BACKGROUND AND PURPOSE: Hypertension significantly contributes to stroke. Previous research has indicated a connection between daytime napping and stroke. Research on the connection between daytime napping duration and first stroke in hypertensive individuals is lacking nevertheless. METHODS: This research, which ran from 24 August 2013 to 31 December 2022, recruited 11,252 individuals with hypertension and without a history of stroke from the China Stroke Primary Prevention Trial. To determine the relationship between daytime napping duration and stroke onset in hypertensive individuals, we conducted analyses for threshold effects, multivariate-adjusted Cox proportional hazard regression models, and Kaplan-Meier survival curves. RESULTS: The duration of daytime napping (<75 min) was positively correlated with stroke risk; beyond 75 min, the risk did not increase further. When compared to hypertensive individuals who napped for 1-30 min, daytime napping 31-60 min (hazard ratio [HR] = 1.27, 95% confidence interval [CI] = 1.06-1.53) and >60 min (HR = 1.37, 95% CI = 1.14-1.65) were substantially related with a greater risk of first stroke. Additionally, this correlation was absent in cases of hemorrhagic stroke, but present in cases of ischemic stroke, specifically for hypertensive individuals who napped for 31-60 min or >60 min (p < 0.05). Kaplan-Meier survival curves displayed that hypertensive individuals who extended daytime napping had an elevated incidence of stroke. CONCLUSIONS: Hypertensive individuals who take longer daytime naps (>30 min) are at an elevated risk of stroke onset, particularly ischemic stroke, irrespective of other factors.

A Deep Learning Application of Capsule Endoscopic Gastric Structure Recognition Based on a Transformer Model.

BACKGROUND: Gastric structure recognition systems have become increasingly necessary for the accurate diagnosis of gastric lesions in capsule endoscopy. Deep learning, especially using transformer models, has shown great potential in the recognition of gastrointestinal (GI) images according to self-attention. This study aims to establish an identification model of capsule endoscopy gastric structures to improve the clinical applicability of deep learning to endoscopic image recognition. METHODS: A total of 3343 wireless capsule endoscopy videos collected at Nanfang Hospital between 2011 and 2021 were used for unsupervised pretraining, while 2433 were for training and 118 were for validation. Fifteen upper GI structures were selected for quantifying the examination quality. We also conducted a comparison of the classification performance between the artificial intelligence model and endoscopists by the accuracy, sensitivity, specificity, and positive and negative predictive values. RESULTS: The transformer-based AI model reached a relatively high level of diagnostic accuracy in gastric structure recognition. Regarding the performance of identifying 15 upper GI structures, the AI model achieved a macroaverage accuracy of 99.6% (95% CI: 99.5-99.7), a macroaverage sensitivity of 96.4% (95% CI: 95.3-97.5), and a macroaverage specificity of 99.8% (95% CI: 99.7-99.9) and achieved a high level of interobserver agreement with endoscopists. CONCLUSIONS: The transformer-based AI model can accurately evaluate the gastric structure information of capsule endoscopy with the same performance as that of endoscopists, which will provide tremendous help for doctors in making a diagnosis from a large number of images and improve the efficiency of examination.

An improved method for diagnosis of Parkinson's disease using deep learning models enhanced with metaheuristic algorithm.

Parkinson's disease (PD) is challenging for clinicians to accurately diagnose in the early stages. Quantitative measures of brain health can be obtained safely and non-invasively using medical imaging techniques like magnetic resonance imaging (MRI) and single photon emission computed tomography (SPECT). For accurate diagnosis of PD, powerful machine learning and deep learning models as well as the effectiveness of medical imaging tools for assessing neurological health are required. This study proposes four deep learning models with a hybrid model for the early detection of PD. For the simulation study, two standard datasets are chosen. Further to improve the performance of the models, grey wolf optimization (GWO) is used to automatically fine-tune the hyperparameters of the models. The GWO-VGG16, GWO-DenseNet, GWO-DenseNet + LSTM, GWO-InceptionV3 and GWO-VGG16 + InceptionV3 are applied to the T1,T2-weighted and SPECT DaTscan datasets. All the models performed well and obtained near or above 99% accuracy. The highest accuracy of 99.94% and AUC of 99.99% is achieved by the hybrid model (GWO-VGG16 + InceptionV3) for T1,T2-weighted dataset and 100% accuracy and 99.92% AUC is recorded for GWO-VGG16 + InceptionV3 models using SPECT DaTscan dataset.

Combination therapy of metformin and atorvastatin against benzopyrene-induced lung cancer via inflammatory signaling pathway.

The most prevalent cause of lung cancer is smoking tobacco, but exposure to second hand smoke, air pollution, and certain chemicals and substances at work can also raise the risk of disease. In this study, we scrutinized the chemoprotective effect of the metformin and atorvastatin combination against benzo[a]pyrene (BaP)-induced lung cancer in mice of Swiss albino. BaP (50 mg/kg) was used for induction of lung cancer and mice were treated with metformin, atorvastatin or their combination. Metformin + atorvastatin combination significantly (p< 0.001) improved the body weight, liver weight, suppressed the lung weight and tumor incidence and altered the levels of immunocompetent cells, polyamines, lung tumor markers, lung parameters and antioxidant parameters, respectively. Metformin + atorvastatin combination also suppressed cytokines levels, inflammatory parameters and caspase parameters. On the basis of the results, we can conclude that metformin + atorvastatin combination remarkably suppressed lung cancer via the inflammatory pathway.

Spleen tyrosine kinase facilitates the progression of papillary thyroid cancer regulated by the hsa_circ_0006417/miR-377-3p axis.

Papillary thyroid cancer (PTC) is a prevalent malignancy worldwide. Spleen tyrosine kinase (SYK) is a crucial enzyme that participates in various biological processes, including cancer progression. This study aims to uncover the biological function of SYK in PTC. SYK expression patterns in PTC were evaluated using quantitative real time polymerase chain reaction (qRT-PCR), immunohistochemistry (IHC), and western blot. Cell function assays were performed to assess the effects of SYK on PTC. Bioinformatics analysis was conducted to identify intriguing microRNA (miRNA) and circular RNA (circRNA). Dual-Luciferase Reporter or RNA immunoprecipitation assays were used to investigate the correlation among SYK, miR-377-3p, and hsa_circ_0006417. SYK was upregulated in PTC. Overexpression of SYK exhibited a positive correlation with tumor size, lymph node metastasis, and unfavorable disease-free survival. Functional assays revealed that SYK exerted tumorigenic effect on PTC cells through mTOR/4E-BP1 pathway. Mechanistically, hsa_circ_0006417 and miR-377-3p regulated SYK expression, offering modulating its tumor-promoting effects. Collectively, SYK acts as an oncogene in PTC through mTOR/4E-BP1 pathway, which is regulated by the hsa_circ_0006417/miR-377-3p axis, thereby providing a potential alternative for PTC treatment.

Pathogenic Aspergillus Strains Identification and Antifungal Susceptibility Analysis of 452 Cases with Otomycosis in Jingzhou, China.

OBJECTIVE: To study the distribution of pathogenic Aspergillus strains of otomycosis in central China and the identification of their antifungal sensitivity. METHODS: We collected external ear canal secretions clinically diagnosed as otomycosis from April 2020 to January 2023 from the Department of Otolaryngology-Head and Neck Surgery in central China. The pathogenic Aspergillus strains were identified through morphological examination and sequencing. The antifungal sensitivity was performed using the broth microdilution method described in the Clinical Laboratory Standard Institute document M38-A3. RESULTS: In the 452 clinical strains isolated from the external ear canal, 284 were identified as Aspergillus terreus (62.83%), 92 as Aspergillus flavus (20.35%), 55 as Aspergillus niger (12.17%). In antifungal susceptibility tests the MIC of Aspergillus strains to bifonazole and clotrimazole was high,all the MIC90 is > 16 ug/mL. However, most Aspergillus isolates show moderate greatly against terbinafine, itraconazole and voriconazole. CONCLUSION: A. terreus is the most common pathogenic Aspergillus strain in otomycosis in central China. The selected topical antifungal drugs were bifonazole and clotrimazole; the drug resistance rate was approximately 30%. If the infection is persistent and requires systemic treatment, terbinafine and itraconazole can be used. The resistance of Aspergillus in otomycosis to voriconazole should be screened to avoid the systemic spread of infection in immunocompromised people and poor compliance with treatment. However, the pan-azole-resistant strain of Aspergillus should be monitored, particularly in high-risk patients with otomycosis.

Occurrence and risk assessment of azole fungicides during the urban water cycle: A year-long study along the Yangtze River, China.

Azole fungicides (AFs) play an important role in the prevention and treatment of fungal diseases in agricultural crops. However, limited studies are addressing the fate and ecological risk of AFs in the urban water cycle at a large watershed scale. To address this gap, we investigated the spatiotemporal distribution and ecological risk of twenty AFs in the lower reaches of the Yangtze River across four seasons. Carbendazim (CBA), tebuconazole (TBA), tricyclazole (TCA), and propiconazole (PPA) were found to be the dominant compounds. Their highest concentrations were measured in January (188.3 ng/L), and November (2197.1 ng/L), July (162.0 ng/L), and November (1801.9 ng/L), respectively. The comparison between wastewater treatment plants (WWTPs) effluents and surface water suggested that industrial WWTPs are major sources of AFs in the Yangtze River. In particular, TBA and PPA were found to be the most recalcitrant AFs in industrial WWTPs, while difenoconazole (DFA) was found to be the most potent pollutant in municipal WWTPs, with an average removal rate of less than 60%. The average risk quotient (RQ) for the entire AFs was 6.45 in the fall, which was higher than in January (0.98), April (0.61), and July (0.40). This indicates that AFs in surface water posed higher environmental risks during the dry season. Additionally, the exposure risk of AFs via drinking water for sensitive populations deserves more attention. This study provides benchmark data on the occurrence of AFs in the lower reaches of the Yangtze River, and offers suggestions for better reduction of AFs.

A novel and innovative cancer classification framework through a consecutive utilization of hybrid feature selection.

Cancer prediction in the early stage is a topic of major interest in medicine since it allows accurate and efficient actions for successful medical treatments of cancer. Mostly cancer datasets contain various gene expression levels as features with less samples, so firstly there is a need to eliminate similar features to permit faster convergence rate of classification algorithms. These features (genes) enable us to identify cancer disease, choose the best prescription to prevent cancer and discover deviations amid different techniques. To resolve this problem, we proposed a hybrid novel technique CSSMO-based gene selection for cancer classification. First, we made alteration of the fitness of spider monkey optimization (SMO) with cuckoo search algorithm (CSA) algorithm viz., CSSMO for feature selection, which helps to combine the benefit of both metaheuristic algorithms to discover a subset of genes which helps to predict a cancer disease in early stage. Further, to enhance the accuracy of the CSSMO algorithm, we choose a cleaning process, minimum redundancy maximum relevance (mRMR) to lessen the gene expression of cancer datasets. Next, these subsets of genes are classified using deep learning (DL) to identify different groups or classes related to a particular cancer disease. Eight different benchmark microarray gene expression datasets of cancer have been utilized to analyze the performance of the proposed approach with different evaluation matrix such as recall, precision, F1-score, and confusion matrix. The proposed gene selection method with DL achieves much better classification accuracy than other existing DL and machine learning classification models with all large gene expression dataset of cancer.

CPPVec: an accurate coding potential predictor based on a distributed representation of protein sequence.

Long non-coding RNAs (lncRNAs) play a crucial role in numbers of biological processes and have received wide attention during the past years. Since the rapid development of high-throughput transcriptome sequencing technologies (RNA-seq) lead to a large amount of RNA data, it is urgent to develop a fast and accurate coding potential predictor. Many computational methods have been proposed to address this issue, they usually exploit information on open reading frame (ORF), protein sequence, k-mer, evolutionary signatures, or homology. Despite the effectiveness of these approaches, there is still much room to improve. Indeed, none of these methods exploit the contextual information of RNA sequence, for example, k-mer features that counts the occurrence frequencies of continuous nucleotides (k-mer) in the whole RNA sequence cannot reflect local contextual information of each k-mer. In view of this shortcoming, here, we present a novel alignment-free method, CPPVec, which exploits the contextual information of RNA sequence for coding potential prediction for the first time, it can be easily implemented by distributed representation (e.g., doc2vec) of protein sequence translated from the longest ORF. The experimental findings demonstrate that CPPVec is an accurate coding potential predictor and significantly outperforms existing state-of-the-art methods.

Reversible Macrocycle-to-Macrocycle Interconversion Driven by Solvent Selection.

Macrocycle-to-macrocycle interconversions are of interest because they can allow access to a variety of structures. However, reversible interconversion between different sized macrocycles remains challenging to control. Herein, we report a facile one-pot synthesis of a series of self-assembled macrocycles from readily prepared α,α'-linked oligopyrrolic dialdehydes and various alkyl diamines. The condensation of pyridine-bridged oligopyrrolic dialdehyde 3 and simple alkyl diamines proved independent of solvent, always yielding the [2 + 2] macrocyclic products. However, when 3 was condensed with 2,2'-oxybis(ethylamine) 14, either ([1 + 1] or [2 + 2]) products are obtained depending on the choice of solvent. Reaction of 3 and 14 in methanol, ethanol, or chloroform gave the [1 + 1] macrocycle as the sole product. In contrast, condensation of 3 and 14 in dimethyl sulfoxide (DMSO), N,N-dimethylformamide (DMF), or acetonitrile (MeCN) yielded the [2 + 2] macrocycle as the major product in the form of a precipitate. Reversible interconversion between the [1 + 1] and [2 + 2] macrocycles could be achieved by tuning the solvent, with the ratio driven by thermodynamic and solubility considerations.

Identification of microRNAs and gene regulatory networks in cleft lip common in humans and mice.

The etiology of cleft lip with/without cleft palate (CL/P), one of the most frequent craniofacial birth defects worldwide, is complicated by contributions of both genetic and environmental factors. Understanding the etiology of these conditions is essential for developing preventive strategies. This study thus aims to identify regulatory networks of microRNAs (miRNAs), transcriptional factors (TFs) and non-TF genes associated with cleft lip (CL) that are conserved in humans and mice. Notably, we found that miR-27b, miR-133b, miR-205, miR-376b and miR-376c were involved in the regulation of CL-associated gene expression in both humans and mice. Among the candidate miRNAs, the overexpression of miR-27b, miR-133b and miR-205, but not miR-376b and miR-376c, significantly inhibited cell proliferation through suppression of CL-associated genes (miR-27b suppressed PAX9 and RARA; miR-133b suppressed FGFR1, PAX7, and SUMO1; and miR-205 suppressed PAX9 and RARA) in cultured human and mouse lip mesenchymal cells. Taken together, our results suggest that elevated expression of miR-27b, miR-133b and miR-205 may play a crucial role in CL through the suppression of genes associated with CL.

The K18-Human ACE2 Transgenic Mouse Model Recapitulates Non-severe and Severe COVID-19 in Response to an Infectious Dose of the SARS-CoV-2 Virus.

A comprehensive analysis and characterization of a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection model that mimics non-severe and severe coronavirus disease 2019 (COVID-19) in humans is warranted for understating the virus and developing preventive and therapeutic agents. Here, we characterized the K18-hACE2 mouse model expressing human (h)ACE2 in mice, controlled by the human keratin 18 (K18) promoter, in the epithelia, including airway epithelial cells where SARS-CoV-2 infections typically start. We found that intranasal inoculation with higher viral doses (2 × 103 and 2 × 104 PFU) of SARS-CoV-2 caused lethality of all mice and severe damage of various organs, including lung, liver, and kidney, while lower doses (2 × 101 and 2 × 102 PFU) led to less severe tissue damage and some mice recovered from the infection. In this hACE2 mouse model, SARS-CoV-2 infection damaged multiple tissues, with a dose-dependent effect in most tissues. Similar damage was observed in postmortem samples from COVID-19 patients. Finally, the mice that recovered from infection with a low dose of virus survived rechallenge with a high dose of virus. Compared to other existing models, the K18-hACE2 model seems to be the most sensitive COVID-19 model reported to date. Our work expands the information available about this model to include analysis of multiple infectious doses and various tissues with comparison to human postmortem samples from COVID-19 patients. In conclusion, the K18-hACE2 mouse model recapitulates both severe and non-severe COVID-19 in humans being dose-dependent and can provide insight into disease progression and the efficacy of therapeutics for preventing or treating COVID-19. IMPORTANCE The pandemic of coronavirus disease 2019 (COVID-19) has reached nearly 240 million cases, caused nearly 5 million deaths worldwide as of October 2021, and has raised an urgent need for the development of novel drugs and therapeutics to prevent the spread and pathogenesis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To achieve this goal, an animal model that recapitulates the features of human COVID-19 disease progress and pathogenesis is greatly needed. In this study, we have comprehensively characterized a mouse model of SARS-CoV-2 infection using K18-hACE2 transgenic mice. We infected the mice with low and high doses of SARS-CoV-2 to study the pathogenesis and survival in response to different infection patterns. Moreover, we compared the pathogenesis of the K18-hACE2 transgenic mice with that of the COVID-19 patients to show that this model could be a useful tool for the development of antiviral drugs and therapeutics.

Inhibition of USP7 upregulates USP22 and activates its downstream cancer-related signaling pathways in human cancer cells.

Deubiquitinases (DUBs) play important roles in various human cancers and targeting DUBs is considered as a novel anticancer therapeutic strategy. Overexpression of ubiquitin specific protease 7 and 22 (USP7 and USP22) are associated with malignancy, therapy resistance, and poor prognosis in many cancers. Although both DUBs are involved in the regulation of similar genes and signaling pathways, such as histone H2B monoubiquitination (H2Bub1), c-Myc, FOXP3, and p53, the interdependence of USP22 and USP7 expression has never been described. In the study, we found that targeting USP7 via either siRNA-mediated knockdown or pharmaceutical inhibitors dramatically upregulates USP22 in cancer cells. Mechanistically, the elevated USP22 occurs through a transcriptional pathway, possibly due to desuppression of the transcriptional activity of SP1 via promoting its degradation upon USP7 inhibition. Importantly, increased USP22 expression leads to significant activation of downstream signal pathways including H2Bub1 and c-Myc, which may potentially enhance cancer malignancy and counteract the anticancer efficacy of USP7 inhibition. Importantly, targeting USP7 further suppresses the in vitro proliferation of USP22-knockout (USP22-Ko) A549 and H1299 lung cancer cells and induces a stronger activation of p53 tumor suppressor signaling pathway. In addition, USP22-Ko cancer cells are more sensitive to a combination of cisplatin and USP7 inhibitor. USP7 inhibitor treatment further suppresses in vivo angiogenesis and tumor growth and induced more apoptosis in USP22-Ko cancer xenografts. Taken together, our findings demonstrate that USP7 inhibition can dramatically upregulate USP22 in cancer cells; and targeting USP7 and USP22 may represent a more effective approach for targeted cancer therapy, which warrants further study. Video Abstract.

Efficacy of genotypic susceptibility-guided tailored therapy for Helicobacter pylori infection: A systematic review and single arm meta-analysis.

BACKGROUND AND AIM: The prevalence of antibiotic resistance for Helicobacter pylori (H. pylori) has been increasing over the year, making it more difficult for traditional empirical therapy to successfully eradicate H. pylori. Thus, tailored therapy (TT) guided by molecular-based antibiotic susceptibility testing (AST) has been frequently recommended. We conducted a single-arm meta-analysis to determine the efficacy of tailored therapy guided by molecular-based AST. METHODS: A systematic literature review was performed on multiple databases, and studies on molecular-based TT were included. The eradication rates of TT by intention-to-treat (ITT) and per-protocol (PP) analyses were pooled respectively. RESULTS: A total of 35 studies from 31 literature (4626 patients) were included in the single-arm meta-analysis. Overall, the pooled eradication rate of TT was 86.9% (95% CI:84.7%-89.1%) by the ITT analysis, and 91.5% (95% CI:89.8%-93.2%) by PP analysis. The pooled eradication rates of first-line TT and rescue TT were 86.6% and 85.1% by ITT analysis and 92.0% and 87.9% by PP analysis, respectively. When tailored rescue therapy was based on the genotypic resistance to at least four antibiotics, the pooled eradication rates reached 89.4% by ITT analysis and 92.1% by PP analysis. For genotype-susceptive strains, the pooled eradication rate of TT with targeted antibiotics was 93.1% (95% CI:91.3%-94.9%), among which the pooled eradication rate of tailored bismuth quadruple therapy was the highest (94.3%). Besides, the eradication rate of 7-day TT or tailored triple therapy without bismuth for genotype-susceptive strains could both reach more than 93.0%. CONCLUSION: Tailored therapy guided by molecular-based AST can achieve somewhat ideal therapeutic outcomes. TT with a 7-day duration or without bismuth for genotype-susceptible strains can achieve good eradication efficacy. The effectiveness of TT can be improved to some extent by expanding the coverage of AST or by adding bismuth.

Psittacosis caused severe community-acquired pneumonia accompanied by acute hypoxic respiratory failure: a multicenter retrospective cohort study from China.

INTRODUCTION: Psittacosis can cause severe community-acquired pneumonia (CAP). The clinical manifestations of psittacosis range from subclinical to fulminant psittacosis with multi-organ failure. It is essential to summarize the clinical characteristic of patients with severe psittacosis accompanied by acute hypoxic respiratory failure (AHRF). METHODS: This retrospective study included patients with severe psittacosis caused CAP accompanied by AHRF from 19 tertiary hospitals of China. We recorded the clinical data, antimicrobial therapy, respiratory support, complications, and outcomes. Chlamydia psittaci was detected on the basis of metagenomic next-generation sequencing performed on bronchoalveolar lavage fluid samples. Patient outcomes were compared between the treatment methods. RESULTS: This study included 45 patients with severe CAP and AHRF caused by psittacosis from April 2018 to May 2021. The highest incidence of these infections was between September and April. There was a history of poultry contact in 64.4% of the patients. The median PaO2/FiO2 of the patients was 119.8 (interquartile range, 73.2 to 183.6) mmHg. Four of 45 patients (8.9%) died in the ICU, and the median ICU duration was 12 days (interquartile range, 8 to 21) days. There were no significant differences between patients treated with fluoroquinolone initially and continued after the diagnosis, fluoroquinolone initially followed by tetracycline, and fluoroquinolone combined with tetracycline. CONCLUSION: Psittacosis caused severe CAP seems not rare, especially in the patients with the history of exposure to poultry or birds. Empirical treatment that covers atypical pathogens may benefit such patients, which fluoroquinolones might be considered as an alternative.

Identification and validation of autophagy-related genes in Kawasaki disease.

BACKGROUND: Kawasaki disease (KD) is a systemic vasculitis of unknown etiology affecting mainly children. Studies have shown that the pathogenesis of KD may be related to autophagy. Using bioinformatics analysis, we assessed the significance of autophagy-related genes (ARGs) in KD. METHODS: Common ARGs were identified from the GeneCards Database, the Molecular Signatures Database (MSigDB), and the Gene Expression Omnibus (GEO) database. ARGs were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis and protein-protein interaction (PPI) network analysis. Furthermore, related microRNAs (miRNAs), transcription factors (TFs), and drug interaction network were predicted. The immune cell infiltration of ARGs in tissues was explored. Finally, we used receiver operating characteristic (ROC) curves and quantitative real-time PCR (qRT-PCR) to validate the diagnostic value and expression levels of ARGs in KD. RESULTS: There were 20 ARGs in total. GO analysis showed that ARGs were mainly rich in autophagy, macro-autophagy, and GTPase activity. KEGG analysis showed that ARGs were mainly rich in autophagy-animal and the collecting duct acid secretion pathway. The expression of WIPI1, WDFY3, ATP6V0E2, RALB, ATP6V1C1, GBA, C9orf72, LRRK2, GNAI3, and PIK3CB is the focus of PPI network. A total of 72 related miRNAs and 130 related TFs were predicted by miRNA and TF targeting network analyses. Ten pairs of gene-drug interaction networks were also predicted; immune infiltration analysis showed that SH3GLB1, ATP6V0E2, PLEKHF1, RALB, KLHL3, and TSPO were closely related to CD8 + T cells and neutrophils. The ROC curve showed that ARGs had good diagnostic value in KD. qRT-PCR showed that WIPI1 and GBA were significantly upregulated. CONCLUSION: Twenty potential ARGs were identified by bioinformatics analysis, and WIPI1 and GBA may be used as potential drug targets and biomarkers.