Multi-scale nested UNet with transformer for colorectal polyp segmentation.

BACKGROUND: Polyp detection and localization are essential tasks for colonoscopy. U-shape network based convolutional neural networks have achieved remarkable segmentation performance for biomedical images, but lack of long-range dependencies modeling limits their receptive fields. PURPOSE: Our goal was to develop and test a novel architecture for polyp segmentation, which takes advantage of learning local information with long-range dependencies modeling. METHODS: A novel architecture combining with multi-scale nested UNet structure integrated transformer for polyp segmentation was developed. The proposed network takes advantage of both CNN and transformer to extract distinct feature information. The transformer layer is embedded between the encoder and decoder of a U-shape net to learn explicit global context and long-range semantic information. To address the challenging of variant polyp sizes, a MSFF unit was proposed to fuse features with multiple resolution. RESULTS: Four public datasets and one in-house dataset were used to train and test the model performance. Ablation study was also conducted to verify each component of the model. For dataset Kvasir-SEG and CVC-ClinicDB, the proposed model achieved mean dice score of 0.942 and 0.950 respectively, which were more accurate than the other methods. To show the generalization of different methods, we processed two cross dataset validations, the proposed model achieved the highest mean dice score. The results demonstrate that the proposed network has powerful learning and generalization capability, significantly improving segmentation accuracy and outperforming state-of-the-art methods. CONCLUSIONS: The proposed model produced more accurate polyp segmentation than current methods on four different public and one in-house datasets. Its capability of polyps segmentation in different sizes shows the potential clinical application.

Development of an immune-related diagnostic predictive model for oral lichen planus.

Oral lichen planus (OLP) was a chronic inflammatory disease of unknown etiology with a 1.4% chance of progressing to malignancy. However, it has been suggested in several studies that immune system disorders played a dominant role in the onset and progression of OLP. Therefore, this experiment aimed to develop a diagnostic prediction model for OLP based on immunopathogenesis to achieve early diagnosis and treatment and prevent cancer. In this study, 2 publicly available OLP datasets from the gene expression omnibus database were filtered. In the experimental group (GSE52130), the level of immune cell infiltration was assessed using MCPcounter and ssGSEA algorithms. Subsequently, differential expression analysis and gene set enrichment analysis were performed between the OLP and control groups. The resulting differentially expressed genes were intersected with immunologically relevant genes provided on the immunology database and analysis portal database (ImmPort) website to obtain differentially expressed immunologically relevant genes (DEIRGs). Furthermore, the gene ontology and kyoto encyclopedia of genes and genomes analyses were carried out. Finally, protein-protein interaction network and least absolute shrinkage and selection operator regression analyses constructed a model for OLP. Receiver operating characteristic curves for the experimental and validation datasets (GSE38616) were plotted separately to validate the model's credibility. In addition, real-time quantitative PCR experiment was performed to verify the expression level of the diagnostic genes. Immune cell infiltration analysis revealed a more significant degree of inflammatory infiltration in the OLP group compared to the control group. In addition, the gene set enrichment analysis results were mainly associated with keratinization, antibacterial and immune responses, etc. A total of 774 differentially expressed genes was obtained according to the screening criteria, of which 65 were differentially expressed immunologically relevant genes. Ultimately, an immune-related diagnostic prediction model for OLP, which was composed of 5 hub genes (BST2, RNASEL, PI3, DEFB4A, CX3CL1), was identified. The verification results showed that the model has good diagnostic ability. There was a significant correlation between the 5 hub diagnostic biomarkers and immune infiltrating cells. The development of this model gave a novel insight into the early diagnosis of OLP.

Accumulation mechanism of metabolite markers identified by machine learning between Qingyuan and Xiushui counties in Polygonatum cyrtonema Hua.

Polygonatum cyrtonema Hua is a traditional Chinese medicinal plant acclaimed for its therapeutic potential in diabetes and various chronic diseases. Its rhizomes are the main functional parts rich in secondary metabolites, such as flavonoids and saponins. But their quality varies by region, posing challenges for industrial and medicinal application of P. cyrtonema. In this study, 482 metabolites were identified in P. cyrtonema rhizome from Qingyuan and Xiushui counties. Cluster analysis showed that samples between these two regions had distinct secondary metabolite profiles. Machine learning methods, specifically support vector machine-recursive feature elimination and random forest, were utilized to further identify metabolite markers including flavonoids, phenolic acids, and lignans. Comparative transcriptomics and weighted gene co-expression analysis were performed to uncover potential candidate genes including CHI, UGT1, and PcOMT10/11/12/13 associated with these compounds. Functional assays using tobacco transient expression system revealed that PcOMT10/11/12/13 indeed impacted metabolic fluxes of the phenylpropanoid pathway and phenylpropanoid-related metabolites such as chrysoeriol-6,8-di-C-glucoside, syringaresinol-4'-O-glucopyranosid, and 1-O-Sinapoyl-D-glucose. These findings identified metabolite markers between these two regions and provided valuable genetic insights for engineering the biosynthesis of these compounds.

Concurrent enhancement of biomass production and phycocyanin content in salt-stressed Arthrospira platensis: A glycine betaine- supplementation approach.

In industrial-scale cultivation of microalgae, salinity stress often stimulates high-value metabolites production but decreases biomass yield. In this research, we present an extraordinary response of Arthrospira platensis to salinity stress. Specifically, we observed a significant increase in both biomass production (2.58 g L-1) and phycocyanin (PC) content (22.31%), which were enhanced by 1.26-fold and 2.62-fold, respectively, compared to the control, upon exposure to exogenous glycine betaine (GB). The biochemical analysis reveals a significant enhancement in carbonic anhydrase activity and chlorophyll a level, concurrent with reductions in carbohydrate content and reactive oxygen species (ROS) levels. Further, transcriptomic profiling indicates a downregulation of genes associated with the tricarboxylic acid (TCA) cycle and an upregulation of genes linked to nitrogen assimilation, hinting at a rebalanced carbon/nitrogen metabolism favoring PC accumulation. This work thus presents a promising strategy for simultaneous enhancement of biomass production and PC content in A. platensis and expands our understanding of PC biosynthesis and salinity stress responses in A. platensis.

Advances in targeted therapy of cholangiocarcinoma.

Cholangiocarcinoma (CCA) is a malignant tumor originating in the bile duct and its branching epithelium. Due to its high heterogeneity, there are no specific clinical indications at the early stage, the diagnosis is often in advanced CCA. With surgical resection, the 5-year postoperative survival rate (long-term survival rate) is very poor. The regimen of gemcitabine combined with platinum has been used as the first-line chemotherapy for advanced patients. In recent years, targeted therapy for a variety of malignant tumors has made great progress, showing good efficacy and safety in advanced CCA. However, the current targeted therapy of CCA still has many challenges, such as adverse reactions, drug resistance, and individual differences. Therefore, the researches need to further explore the targeted therapy mechanism of CCA malignancies in depth, develop more effective and safe drugs, and accurately formulate plans based on patient characteristics to further improve patient prognosis in the future. This article reviews the recent progress of targeted therapy for CCA, aiming to provide a strategy for the research and clinical work of targeted therapy for CCA.

For these patients without surgical indications, chemotherapy and radiation therapy are the main treatment options, among which gemcitabine combined with cisplatin is the standard recognized chemotherapy regimen.With the gradual maturity of gene detection technology, the molecular pathology of CCA has gradually been revealed and precision oncology has become a promising method for the treatment of CCA.

CRISPR/Cas9-mediated knockout of the Vanin-1 gene in the Leghorn Male Hepatoma cell line and its effects on lipid metabolism.

OBJECTIVE: Vanin-1 (VNN1) is a pantetheinase that catalyses the hydrolysis of pantetheine to produce pantothenic acid and cysteamine. Our previous studies have shown that the VNN1 is specifically expressed in chicken liver which negatively regulated by microRNA-122. However, the functions of the VNN1 in lipid metabolism in chicken liver haven't been elucidated. METHODS: First, we detected the VNN1 mRNA expression in 4-week chickens which were fasted 24 hours. Next, knocked out VNN1 via CRISPR/Cas9 system in the chicken Leghorn Male Hepatoma cell line. Detected the lipid deposition via oil red staining and analysis the content of triglycerides (TG), low-density lipoprotein-C (LDL-C), and highdensity lipoprotein-C (HDL-C) after VNN1 knockout in Leghorn Male Hepatoma cell line. Then we captured various differentially expressed genes (DEGs) between VNN1-modified LMH cells and original LMH cells by RNA-seq. RESULTS: Firstly, fasting-induced expression of VNN1. Meanwhile, we successfully used the CRISPR/Cas9 system to achieve targeted mutations of the VNN1 in the chicken LMH cell line. Moreover, the expression level of VNN1 mRNA in LMH-KO-VNN1 cells decreased compared with that in the wild-type LMH cells (p<0.0001). Compared with control, lipid deposition was decreased after knockout VNN1 via oil red staining, meanwhile, the contents of TG and LDL-C were significantly reduced, and the content of HDL-C was increased in LMH-KO-VNN1 cells. Transcriptome sequencing showed that there were 1,335 DEGs between LMH-KO-VNN1 cells and original LMH cells. Of these DEGs, 431 were upregulated, and 904 were downregulated. Gene ontology analyses of all DEGs showed that the lipid metabolism-related pathways, such as fatty acid biosynthesis and long-chain fatty acid biosynthesis, were enriched. KEGG pathway analyses showed that "lipid metabolism pathway", "energy metabolism", and "carbohydrate metabolism" were enriched. A total of 76 DEGs were involved in these pathways, of which 29 genes were upregulated (such as cytochrome P450 family 7 subfamily A member 1, ELOVL fatty acid elongase 2, and apolipoprotein A4) and 47 genes were downregulated (such as phosphoenolpyruvate carboxykinase 1) by VNN1 knockout in the LMH cells. CONCLUSION: These results suggest that VNN1 plays an important role in coordinating lipid metabolism in the chicken liver.

A protocol to investigate the effects of lncRNAs on in vivo protein-protein interactions using proximity ligation assay.

A large variety of cellular signals are triggered and transmitted by protein-protein interactions (PPIs). Long noncoding RNAs regulate PPIs by enhancing or destabilizing these interactions. Here, we use the proximity ligation assay technique to determine PPIs between p53 and SET regulated by long intergenic noncoding RNA 324 (LINC00324). We detail procedures for establishing LINC00324 knockdown and overexpression U2OS and HepG2 cells followed by in situ PLA protocol. This approach has many potential applications for the study of cellular factors that regulate PPIs. For complete details on the use and execution of this protocol, please refer to Zhang et al. (2023).1.

Identification of immune-related biomarkers in peripheral blood of schizophrenia using bioinformatic methods and machine learning algorithms.

Schizophrenia is a group of severe neurodevelopmental disorders. Identification of peripheral diagnostic biomarkers is an effective approach to improving diagnosis of schizophrenia. In this study, four datasets of schizophrenia patients' blood or serum samples were downloaded from the GEO database and merged and de-batched for the analyses of differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WCGNA). The WGCNA analysis showed that the cyan module, among 9 modules, was significantly related to schizophrenia, which subsequently yielded 317 schizophrenia-related key genes by comparing with the DEGs. The enrichment analyses on these key genes indicated a strong correlation with immune-related processes. The CIBERSORT algorithm was adopted to analyze immune cell infiltration, which revealed differences in eosinophils, M0 macrophages, resting mast cells, and gamma delta T cells. Furthermore, by comparing with the immune genes obtained from online databases, 95 immune-related key genes for schizophrenia were screened out. Moreover, machine learning algorithms including Random Forest, LASSO, and SVM-RFE were used to further screen immune-related hub genes of schizophrenia. Finally, CLIC3 was found as an immune-related hub gene of schizophrenia by the three machine learning algorithms. A schizophrenia rat model was established to validate CLIC3 expression and found that CLIC3 levels were reduced in the model rat plasma and brains in a brain-regional dependent manner, but can be reversed by an antipsychotic drug risperidone. In conclusion, using various bioinformatic and biological methods, this study found an immune-related hub gene of schizophrenia - CLIC3 that might be a potential diagnostic biomarker and therapeutic target for schizophrenia.

Development of a Brief Cognitive Screening Tool for Predicting Postoperative Delirium in Patients with Parkinson's Disease: A Secondary Analysis.

Background: A simple, rapid, and effective cognitive screening test appropriate for fast-paced settings with limited resources and staff is essential, especially preoperatively. This study aimed to develop and validate the short versions of Mini-Mental State Examination (MMSE) and Montreal Cognitive Assessment (MoCA) for predicting postoperative delirium (POD) in patients with Parkinson's disease (PD) who were scheduled for surgery. Methods: The current study was a secondary analysis of data collected from 128 inpatients scheduled for deep brain stimulation of the subthalamic nuclei (STN-DBS) lasting >60 min, at Tsinghua University Yuquan Hospital, China. Preoperative cognitive screening was performed during the preoperative visit using the MMSE and MoCA. The optimal MMSE and MoCA cut-off scores for detecting PD-MCI was 27 and 23 respectively. The POD was assessed twice a day on the first postoperative day until discharge by the confusion assessment method. The backward conditional logistic regression analysis was used to organize the reduced versions of the MMSE or MoCA. Also, the areas under the receiver operating characteristic curves (AUCs) were examined using the DeLong test. Results: 125/128 PD patients were included in the analysis, and 27 (21.6%) developed POD. The MMSE reduced version (orientation to time, attention and calculation, and comprehension) demonstrated performance similar to the original MMSE in predicting POD (z=0.820, p=0.412). The AUC of the original MoCA and the short MoCA (visuospatial and executive attention and orientation) were 0.808 and 0.826, respectively. There was no significantly difference in the AUC values between the tests (z=0.561, p=0.575). Conclusion: Our simplified MMSE and MoCA could be efficiently used to identify patients at risk for POD. Also, short cognitive tests could be considered while predicting POD in fast-paced preoperative settings with limited resources and staff.

Activation of the N-methyl-D-aspartate receptor and calcium/calmodulin-dependent protein kinase IIα signal in the rostral anterior cingulate cortex is involved in pain-related aversion in rats with peripheral nerve injury.

The rostral anterior cingulate cortex (rACC) of rat brain is associated with pain-related emotions. However, the underlying molecular mechanism remains unclear. Here, we investigated the effects of the N-methyl-D-aspartate (NMDA) receptor and Ca2+/Calmodulin-dependent protein kinase type II (CaMKII)α signal on pain-related aversion in the rACC of a rat model of neuropathic pain (NP). Mechanical and thermal hyperalgesia were examined using von Frey and hot plate tests in a rat model of NP induced by spared nerve injury (SNI) of the unilateral sciatic nerve. Bilateral rACC pretreatment with the CaMKII inhibitor tat-CN21 (derived from the cell-penetrating tat sequence and CaM-KIIN amino acids 43-63) or tat-Ctrl (the tat sequence and the scrambled sequence of CN21) was performed on postoperative days 29-35 in Sham rats or rats with SNI. Spatial memory performance was tested using an eight-arm radial maze on postoperative days 34-35. Pain-related negative emotions (aversions) were evaluated using the place escape/avoidance paradigm on postoperative day 35 following the spatial memory performance test. The percentage of time spent in the light area was used to assess pain-related negative emotions (i.e., aversion). The expression levels of the NMDA receptor GluN2B subunit, CaMKIIα, and CaMKII-Threonine at position 286 (Thr286) phosphorylation in contralateral rACC specimens were detected by Western blot or real time PCR following the aversion test. Our data showed that pretreatment of the rACC with tat-CN21 increased determinate behavior but did not alter hyperalgesia or spatial memory performance in rats with SNI. In addition, tat-CN21 reversed the enhanced CaMKII-Thr286 phosphorylation and had no effect on the upregulated expression of GluN2B, CaMKIIα protein, and mRNA. Our data suggested that activation of the NMDA receptor-CaMKIIα signal in rACC is associated with pain-related aversion in rats with NP. These data may provide a new approach for the development of drugs that modulate cognitive and emotional pain aspects.

DCLRE1A Contributes to DNA Damage Repair and Apoptosis in Age-Related Cataracts by Regulating the lncRNA/miRNA/mRNA Axis.

PURPOSE: Age-related cataract (ARC) is associated with the deregulation of transcription and defects in DNA repair in lens epithelial cells (LECs). DCLRE1A acted in DNA interstrand cross-links pathway to improve DNA replication and transcription. The aim of this study was to examined the further regulatory effect on DCLRE1A in the lncRNA-miRNA-mRNA network using a cell model of DCLRE1A overexpression (OE-DCLRE1A) in LECs. METHODS: The expression level of DCLRE1A in ARC tissues and SRA01/04 cells after H2O2 treatment was measured as protein and mRNA by qRT-PCR and Western Blot(WB). CCK8, and TUNEL assays detected the change in cell viability and apoptosis, respectively. Furthermore, Immunofluorescence assays detect the expression of DNA damaged and repair marker proteins after OE-DCLRE1A. The global expression profiles of lncRNAs, miRNAs, and mRNAs were determined using high-throughput sequencing. KEGG and GO enrichment analysis disclose the possible function of differentially expressed (DE) lncRNA, miRNA, and mRNA. RESULTS: The protein and mRNA of DCLRE1A were decreased in the anterior capsule of ARC and SRA01/04 cells treated by H2O2. OE-DCLRE1A improved damaged-DNA repair and enhanced cell viability against apoptosis after H2O2 treatment. Furthermore, we demonstrated the DE-molecules between the OE-DCLRE1A and control groups including 595 DE-lncRNAs, 221 DE-miRNAs, and 4718 DE-mRNAs. Next, bioinformatics analysis not only found that the DE-mRNAs are mainly involved in DNA repair-related signaling pathways after OE-DCLRE1A, but also screened two lncRNA-miRNA-mRNA networks focusing on DNA damage activated by OE-DCLRE1A, which involved 2 lncRNAs, 2 miRNAs, and 53 mRNAs. CONCLUSION: We revealed that DCLRE1A activated the lncRNA/miRNA/DNA-repair network to take part in DNA repair processes, which not only represents a new regulatory mechanism employed by DCLRE1A but also uncovers the screening lncRNA may hold potential therapeutic values in ARC formation. However, these conclusions will need to be confirmed by future studies in vitro and in vivo models.

Perturbing BEAMs: EEG adversarial attack to deep learning models for epilepsy diagnosing.

Deep learning models have been widely used in electroencephalogram (EEG) analysis and obtained excellent performance. But the adversarial attack and defense for them should be thoroughly studied before putting them into safety-sensitive use. This work exposes an important safety issue in deep-learning-based brain disease diagnostic systems by examining the vulnerability of deep learning models for diagnosing epilepsy with brain electrical activity mappings (BEAMs) to white-box attacks. It proposes two methods, Gradient Perturbations of BEAMs (GPBEAM), and Gradient Perturbations of BEAMs with Differential Evolution (GPBEAM-DE), which generate EEG adversarial samples, for the first time by perturbing BEAMs densely and sparsely respectively, and find that these BEAMs-based adversarial samples can easily mislead deep learning models. The experiments use the EEG data from CHB-MIT dataset and two types of victim models each of which has four different deep neural network (DNN) architectures. It is shown that: (1) these BEAM-based adversarial samples produced by the proposed methods in this paper are aggressive to BEAM-related victim models which use BEAMs as the input to internal DNN architectures, but unaggressive to EEG-related victim models which have raw EEG as the input to internal DNN architectures, with the top success rate of attacking BEAM-related models up to 0.8 while the top success rate of attacking EEG-related models only 0.01; (2) GPBEAM-DE outperforms GPBEAM when they are attacking the same victim model under a same distortion constraint, with the top attack success rate 0.8 for the former and 0.59 for the latter; (3) a simple modification to the GPBEAM/GPBEAM-DE will make it have aggressiveness to both BEAMs-related and EEG-related models (with top attack success rate 0.8 and 0.64), and this capacity enhancement is done without any cost of distortion increment. The goal of this study is not to attack any of EEG medical diagnostic systems, but to raise concerns about the safety of deep learning models and hope to lead to a safer design.

A p53/LINC00324 positive feedback loop suppresses tumor growth by counteracting SET-mediated transcriptional repression.

The p53 tumor suppressor exerts antitumor functions through its ability to regulate the transcription of its downstream targets. Long noncoding RNAs (lncRNAs) act as oncogenes or tumor suppressors implicated in tumorigenesis and tumor progression. Here, we identify the lncRNA LINC00324 (long intergenic noncoding RNA 00324) as a direct p53 transcriptional target. Knockdown of LINC00324 expression promotes tumor growth by reducing p53 transcriptional activity, whereas ectopic LINC00324 expression demonstrates a reverse effect. Notably, LINC00324 is present in the endogenous p53 complex in tumor cells and directly binds to the C-terminal domain of p53 in vitro. Mechanistically, LINC00324 enables p53 transactivation by competitively disrupting the p53-SET interaction, resulting in an increase of p300/CBP-mediated H3K18 and H3K27 acetylation on the p53 target promoters. Lower LINC00324 expression is associated with more aggressive disease status and predicts worse overall survival of patients with cancer. Our study identifies a p53/LINC00324 positive feedback loop that suppresses tumor growth by counteracting SET-mediated transcriptional repression.

Study on the ozonation degradation of methylene blue enhanced by microchannel and ultrasound.

Azo dye-containing wastewater poses serious risks of environmental pollution because it is generally biologically toxic and resistant to conventional wastewater treatment methods. A novel degradation system integrating ozone, microchannel, and ultrasound was designed to effectively degrade azo dye-contaminated wastewater. The effects of discharge voltage of dielectric barrier discharge (DBD) reactor, liquid flow rate, microchannel width, ultrasonic power, initial pH, and reaction temperature on methylene blue (MB) decolorization were studied. A maximum MB decolorization efficiency of 92.7% was obtained in the ozone/microchannel/ultrasound (O3/MC/US) system with 14 min of treatment. In addition, the 14-min decolorization efficiency and TOC removal efficiency obtained in O3/MC/US system were increased by 12.6 and 6.5%, respectively, compared to those obtained in the pure O3 system. Based on the results of scavenging experiments, the combined effects of microchannel and ultrasound were proved to improve the contribution rate of hydroxyl radicals, thus improving the decolorization efficiency. The present work clearly illustrates that ozonation degradation can be effectively enhanced by microchannel and ultrasound, and also provides a feasible method for the treatment of organic wastewater.

Upadacitinib inhibits corneal inflammation and neovascularization by suppressing M1 macrophage infiltration in the corneal alkali burn model.

Alkali burn-induced corneal inflammation and subsequent corneal neovascularization (CNV) are major causes of corneal opacity and vision loss. M1 macrophages play a central role in inflammation and CNV. Therefore, modulation of M1 macrophage polarization is a promising strategy for corneal alkali burns. Here, we illustrate the effect and underlying mechanisms of upadacitinib on corneal inflammation and CNV induced by alkali burns in mice. The corneas of BALB/c mice were administered with 1 M NaOH for 30 s and randomly assigned to the vehicle group and the upadacitinib-treated group. Corneal opacity and corneal epithelial defects were assessed clinically. Quantitative real-time PCR (qRT-PCR), immunohistochemistry, and western blot analysis were performed to detect M1 macrophage polarization and CD31+ corneal blood vessels. The results showed that upadacitinib notably decreased corneal opacity, and promoted corneal wound healing. On day 7 and 14 after alkali burns, upadacitinib significantly suppressed CNV. Corneal alkali injury caused M1 macrophage recruitment in the cornea. In contrast to the vehicle, upadacitinib suppressed M1 macrophage infiltration and decreased the mRNA expression levels of inducible nitric oxide synthase (iNOS), monocyte chemotactic protein-1 (MCP-1), tumor necrosis factor-alpha (TNF-α), interleukin (IL)-6, IL-1ß, and vascular endothelial growth factor A (VEGF-A) in alkali-injured corneas. Moreover, upadacitinib dose-dependently inhibited M1 macrophage polarization by suppressing interferon (IFN)-γ-/lipopolysaccharide-stimulated STAT1 activation in vitro. Our findings reveal that upadacitinib can efficiently alleviate alkali-induced corneal inflammation and neovascularization by inhibiting M1 macrophage infiltration. These data demonstrate that upadacitinib is an effective drug for the treatment of corneal alkali burns.

Missing puzzle pieces of time-restricted-eating (TRE) as a long-term weight-loss strategy in overweight and obese people? A systematic review and meta-analysis of randomized controlled trials.

The efficacy of using time restricted eating (TRE) for weight management and to mitigate metabolic disorders in overweight and obese people remains debatable. This meta-analysis quantified the impact of TRE on weight loss and metabolic health in overweight and obese people. The pooled results were subjected to a random-effects modeling using Hartung-Knapp-Sidik-Jonkman (HKSJ) method. Additionally, subgroup analysis was conducted based on study types, randomized controlled trials (RCTs) vs. non-randomized studies of interventions (NRSIs). Pooled results showed that subjects on TRE regimen (> 4 weeks) achieved a significant weight loss in comparison with unrestricted time regimen (weighted mean difference: -2.32%; 95% CI: -3.50, -1.14%; p < 0.01); however, weight loss was mainly attributed to the loss of lean mass rather than fat mass. The magnitude of weight loss was inversely correlated with daily fasting duration in RCTs. TRE significantly decreased the diastolic blood pressure and fasting insulin. An increase of low-density lipoprotein cholesterol (LDL-C) was observed in the TRE group. Favorable effect of TRE was observed on glucose metabolism but not on lipid profiles independent of weight loss. Hence TRE shall be administered with caution to overweight and obese people who have comorbidities such as dyslipidemia and sarcopenia.Supplemental data for this article is available online at https://doi.org/10.1080/10408398.2021.1974335.

FtsH4 protease controls biogenesis of the PSII complex by dual regulation of high light-inducible proteins.

FtsH proteases are membrane-embedded proteolytic complexes important for protein quality control and regulation of various physiological processes in bacteria, mitochondria, and chloroplasts. Like most cyanobacteria, the model species Synechocystis sp. PCC 6803 contains four FtsH homologs, FtsH1-FtsH4. FtsH1-FtsH3 form two hetero-oligomeric complexes, FtsH1/3 and FtsH2/3, which play a pivotal role in acclimation to nutrient deficiency and photosystem II quality control, respectively. FtsH4 differs from the other three homologs by the formation of a homo-oligomeric complex, and together with Arabidopsis thaliana AtFtsH7/9 orthologs, it has been assigned to another phylogenetic group of unknown function. Our results exclude the possibility that Synechocystis FtsH4 structurally or functionally substitutes for the missing or non-functional FtsH2 subunit in the FtsH2/3 complex. Instead, we demonstrate that FtsH4 is involved in the biogenesis of photosystem II by dual regulation of high light-inducible proteins (Hlips). FtsH4 positively regulates expression of Hlips shortly after high light exposure but is also responsible for Hlip removal under conditions when their elevated levels are no longer needed. We provide experimental support for Hlips as proteolytic substrates of FtsH4. Fluorescent labeling of FtsH4 enabled us to assess its localization using advanced microscopic techniques. Results show that FtsH4 complexes are concentrated in well-defined membrane regions at the inner and outer periphery of the thylakoid system. Based on the identification of proteins that co-purified with the tagged FtsH4, we speculate that FtsH4 concentrates in special compartments in which the biogenesis of photosynthetic complexes takes place.

Bacteriophages allow selective depletion of gut bacteria to produce a targeted-bacterium-depleted mouse model.

The gut microbiome is essential for human health. Mouse microbiota models, including gnotobiotic mice, are the most prominent tools to elucidate the functions of gut bacteria. Here, we propose a targeted-bacterium-depleted (TBD) model using lytic bacteriophage to selectively deplete gut bacterium of healthy or otherwise defined mice. These phage-treated animals should have a near-complete spectrum of gut bacteria except for the depleted bacterium. To prove the concept, we employed Escherichia coli-specific phage T7 to repress E. coli in the healthy mice. Our results showed that the E. coli-depleted mice exhibited bravery-like behaviors, correlated to the presence of E. coli rather than the equilibrium among gut bacteria. Thus, we demonstrate that the TBD model is a powerful tool to elucidate the function of a specific bacterial species within a near-intact gut microbiota environment and complements gnotobiotic mice models.

Detection Analysis of Perioperative Plasma and CSF Reveals Risk Biomarkers of Postoperative Delirium of Parkinson's Disease Patients Undergoing Deep Brain Stimulation of the Subthalamic Nuclei.

Objective: This study aimed to explore possible biomarkers of postoperative delirium (POD) of Parkinson's disease (PD) patients received deep brain stimulation (DBS) of the subthalamic nuclei. Materials and methods: This nested case control study analyzed perioperative plasma and cerebral spinal fluid (CSF) of patients (n = 40) who developed POD undergone DBS surgery (n = 10) and those who did not (n = 30). Blood sample was collected before surgery and on the first day postoperative, CSF sample was collected at the beginning of the operation. POD was assessed by the Confusion Assessment Method (CAM) twice a day between 7:00 am and 7:00 pm after the surgery until discharge. Plasma and CSF sample from the two groups were analyzed to investigate possible biomarkers for POD in PD patients. Results: There was no difference between POD and Non-POD groups on the concentration of Interleukin 6 and Tumor Necrosis Factor-α in CSF, preoperative plasma and postoperative plasma. There was no difference between POD and Non-POD groups on the concentration of S100 calcium-binding protein ß protein (S100ß) and Neurofilament light chain (NFL) in preoperative plasma and postoperative plasma. The concentration of C-reactive protein (CRP), NFL and S100ß were significant higher in POD group than non-POD group in CSF. The concentration of CRP was significantly higher in POD group than non-POD group in preoperative plasma and postoperative plasma. CSF concentration of S100ß might be a potential biomarker for POD via the receiver operating characteristic curve analysis and the area under the curve value of 0.973. Conclusion: For PD patients received DBS surgery, CSF S100ß might be a marker for aiding detection of high-risk patients with delirium. This requires further confirmation in clinical trials.

[Solid phase microextraction of benzenes in river water by pomelo peel biochar].

Pomelo peel, as a by-product of pomelo consumption, is rich in various fiber and functional compounds. The utilization of the valuable components found in pomelo peel may mitigate environmental concerns. In this study, pomelo peel rich in lignin and oxygen-containing functional groups was used to prepare pomelo peel biochar (PPB) via temperature-programmed pyrolysis at different temperatures (800 ℃ and 1000 ℃). Their structures were investigated by N2 adsorption-desorption isotherms and BJH pore size distribution. The results showed that PPB1000 (pomelo peel biochar prepared at 1000 ℃) had a higher specific surface area (749.9 m2/g), larger pore volume (0.42 cm3/g), more concentrated pore size distribution (2-3 nm), and better adsorption performance than commercial activated carbon. PPB1000 exhibited excellent capability to capture benzenes (BTEX, including benzene (B), toluene (T), ethylbenzene (E), and xylene (X)) through hydrogen bonds, π-π, and electrostatic interactions. Additionally, their honeycomb porous structure could provide additional adsorption sites and material transport paths. PPB1000 was coated on iron wire using the sol-gel method to prepare chemically and mechanically stable solid phase microextraction (SPME) fibers. By combining PPB1000-based SPME analysis with gas chromatography-flame ionization detection (GC-FID), an effective method was developed for the extraction and determination of BTEX. The optimized method had low LODs (0.004-0.032 µg/L), wide linear range (1-100 µg/L), and good linear relationship (determination coefficients, r2≥0.9919). The RSDs of the intra-batch (n=6) and inter-batch (n=5) precisions were 1.04%-6.56% and 1.03%-12.42%, respectively. The method validation results showed that PPB1000 had good stability. Compared with the commercial reagent polydimethylsiloxane (7 µm), PPB1000 had a higher extraction efficiency. When applied to the analysis of BTEX in natural water samples, trace levels of ethylbenzene (4.80 µg/L), o-xylene (3. 00 µg/L), and m-xylene and p-xylene (2.46 µg/L) were detected. Recovery tests were performed to validate the reliability of the method, and recoveries were between 75.7% and 117.6%. This effective pretreatment process combined with GC-FID could realize the rapid detection of BTEX and is promising for the analysis of BTEX in complex matrixes in the future.