RNA processing modification mediated subtypes illustrate the distinctive features of tumor microenvironment in hepatocellular carcinoma.

Multiple transcript isoforms of genes can be formed by processing and modifying the 5' and 3' ends of RNA. Herein, the aim of this study is to uncover the characteristics of RNA processing modification (RPM) in hepatocellular carcinoma (HCC), and to identify novel biomarkers and potential targets for treatment. Firstly, integrated bioinformatics analysis was carried out to identify risk prognostic RPM regulators (RPMRs). Then, we used these RPMRs to identify subtypes of HCC and explore differences in immune microenvironment and cellular function improvement pathways between the sub-types. Finally, we used the principal component analysis algorithms to estimate RPMscore, which were applied to 5 cohorts. Lower RPMscore among patients correlated with a declined survival rate, increased immune infiltration, and raised expression of immune checkpoints, aligning with the "immunity tidal model theory". The RPMscore exhibited robust, which was validated in multiple datasets. Mechanistically, low RPMscore can create an immunosuppressive microenvironment in HCC by manipulating tumor-associated macrophages. Preclinically, patients with high RPMscore might benefit from immunotherapy. The RPMscore is helpful in clustering HCC patients with distinct prognosis and immunotherapy. Our RPMscore model can help clinicians to select personalized therapy for HCC patients, and RPMscore may act a part in the development of HCC.

In vitro and in vivo activity of ceftazidime/avibactam and aztreonam alone or in combination against mcr-9, serine- and metallo-ß-lactamases-co-producing carbapenem-resistant Enterobacter cloacae complex.

PURPOSE: Enterobacteriaceae carrying mcr-9, in particularly those also co-containing metallo-ß-lactamase (MBL) and TEM type ß-lactamase, present potential transmission risks and lack adequate clinical response methods, thereby posing a major threat to global public health. The aim of this study was to assess the antimicrobial efficacy of a combined ceftazidime/avibactam (CZA) and aztreonam (ATM) regimen against carbapenem-resistant Enterobacter cloacae complex (CRECC) co-producing mcr-9, MBL and TEM. METHODS: The in vitro antibacterial activity of CZA plus ATM was evaluated using a time-kill curve assay. Furthermore, the in vivo interaction between CZA plus ATM was confirmed using a Galleria mellonella (G. mellonella) infection model. RESULTS: All eight clinical strains of CRECC, co-carrying mcr-9, MBL and TEM, exhibited high resistance to CZA and ATM. In vitro time-kill curve analysis demonstrated that the combination therapy of CZA + ATM exerted significant bactericidal activity against mcr-9, MBL and TEM-co-producing Enterobacter cloacae complex (ECC) isolates with a 100% synergy rate observed in our study. Furthermore, in vivo survival assay using Galleria mellonella larvae infected with CRECC strains co-harboring mcr-9, MBL and TEM revealed that the CZA + ATM combination significantly improved the survival rate compared to the drug-treatment alone and untreated control groups. CONCLUSION: To our knowledge, this study represents the first report on the in vitro and in vivo antibacterial activity of CZA plus ATM against CRECC isolates co-harboring mcr-9, MBL and TEM. Our findings suggest that the combination regimen of CZA + ATM provides a valuable reference for clinicians to address the increasingly complex antibiotic resistance situation observed in clinical microorganisms.

MSF-PFP: A Novel Multisource Feature Fusion Model for Protein Function Prediction.

Protein function prediction is essential for disease treatment and drug development; yet, traditional biological experimental methods are less efficient in annotating protein function, and existing automated methods fail to fully leverage protein multisource data. Here, we present MSF-PFP, a computational framework that fuses multisource data features to predict protein function with high accuracy. Our framework designs specific models for feature extraction based on the characteristics of various data sources, including a global-local-individual strategy for local location features. MSF-PFP then integrates extracted features through a multisource feature fusion model, ultimately categorizing protein functions. Experimental results demonstrate that MSF-PFP outperforms eight state-of-the-art models, achieving FMax scores of 0.542, 0.675, and 0.624 for the biological process (BP), molecular function (MF), and cellular component (CC), respectively. The source code and data set for MSF-PFP are available at https://swanhub.co/TianGua/MSF-PFP, facilitating further exploration and validation of the proposed framework. This study highlights the potential of multisource data fusion in enhancing protein function prediction, contributing to improved disease therapy and medication discovery strategies.

H*ads dynamics engineering via bimetallic Pd-Cu@MXene catalyst for enhanced electrocatalytic hydrodechlorination.

Electrocatalytic hydrodechlorination (EHDC) is a promising approach to safely remove halogenated emerging contaminants (HECs) pollutants. However, sluggish production dynamics of adsorbed atomic H (H*ads) limit the applicability of this green process. In this study, bimetallic Pd-Cu@MXene catalysts were synthesized to achieve highly efficient removal of HECs. The alloy electrode (Pd-Cu@MX/CC) exhibited better EHDC performance in comparison to Pd@MX/CC electrode, resulting in diclofenac degradation efficiency of 93.3 ± 0.1%. The characterization analysis revealed that the Pd0/PdII ratio decreased by forming bimetallic Pd-Cu alloy. Density functional theory calculations further demonstrated the electronic configuration modulation of the Pd-Cu@MXene catalysts, optimizing binging energies for H* and thereby facilitating H*ads production and tuning the reduction capability of H*ads. Noteably, the amounts and reduction potential of H*ads for Pd-Cu@MXene catalysts were 1.5 times higher and 0.37 eV lower than those observed for the mono Pd electrode. Hence, the introduction of Cu into the Pd catalyst optimized the dynamics of H*ads production, thereby conferring significant advantages to EHDC reactions. This augmentation was underscored by the successful application of the alloy catalysts supported by MXene in EHDC experiments involving other HECs, which represented a new paradigm for EHDC for efficient recalcitrant pollutant removal by H*ads.

A Multidrug-Resistant Extended-Spectrum Beta-Lactamase (ESBL)-Producing Enterobacter hormaechei Strain from Mixed Sprouts.

Fresh vegetables can harbor antibiotic-resistant bacteria, including extended-spectrum ß-lactamase (ESBL)-producing Enterobacterales. Enterobacter hormaechei is a bacterium belonging to the Enterobacterales order and the most commonly identified nosocomial pathogen of Enterobacter cloacae complex. The purpose of this study was to characterize a multi-drug resistant ESBL-producing E. hormaechei strain isolated from a sample of mixed sprouts. Vegetable samples were pre-enriched in buffered peptone water, followed by enrichment in Enterobacteria Enrichment Broth, and isolation on Chromagar™ ESBL plates. One isolate from a sprout sample was confirmed to produce both ESBL and AmpC ß-lactamases through the combination disk diffusion assay using antibiotic disks containing cefotaxime and ceftazidime with or without clavulanate, and with or without cloxacillin, respectively. The isolate was also resistant to multiple antibiotics, including cefotaxime, ceftazidime, chloramphenicol, trimethoprim-sulfamethoxazole, tetracycline, gentamicin, ampicillin, and amoxicillin-clavulanate, as determined by antimicrobial susceptibility testing. Through whole genome sequencing, the isolate was identified as E. hormaechei 057-E1, which carried multiple antibiotic resistance (AR) genes and a sul2-aph(3″)-Ib-aph(6)-Id-blaTEM-1-ISEcp1 -blaCTX-M-15 gene cluster. Our results further demonstrate the important role of fresh vegetables in AR and highlight the need to develop strategies for AR mitigation in fresh vegetables.

Huntington's Disease: Complex Pathogenesis and Therapeutic Strategies.

Huntington's disease (HD) arises from the abnormal expansion of CAG repeats in the huntingtin gene (HTT), resulting in the production of the mutant huntingtin protein (mHTT) with a polyglutamine stretch in its N-terminus. The pathogenic mechanisms underlying HD are complex and not yet fully elucidated. However, mHTT forms aggregates and accumulates abnormally in neuronal nuclei and processes, leading to disruptions in multiple cellular functions. Although there is currently no effective curative treatment for HD, significant progress has been made in developing various therapeutic strategies to treat HD. In addition to drugs targeting the neuronal toxicity of mHTT, gene therapy approaches that aim to reduce the expression of the mutant HTT gene hold great promise for effective HD therapy. This review provides an overview of current HD treatments, discusses different therapeutic strategies, and aims to facilitate future therapeutic advancements in the field.

CeRNASeek: an R package for identification and analysis of ceRNA regulation.

Competitive endogenous RNA (ceRNA) represents a novel layer of gene regulation that controls both physiological and pathological processes. However, there is still lack of computational tools for quickly identifying ceRNA regulation. To address this problem, we presented an R-package, CeRNASeek, which allows identifying and analyzing ceRNA-ceRNA interactions by integration of multiple-omics data. CeRNASeek integrates six widely used computational methods to identify ceRNA-ceRNA interactions, including two global and four context-specific ceRNA regulation prediction methods. In addition, it provides several downstream analyses for predicted ceRNA-ceRNA pairs, including regulatory network analysis, functional annotation and survival analysis. With examples of cancer-related ceRNA prioritization and cancer subtyping, we demonstrate that CeRNASeek is a valuable tool for investigating the function of ceRNAs in complex diseases. In summary, CeRNASeek provides a comprehensive and efficient tool for identifying and analysis of ceRNA regulation. The package is available on the Comprehensive R Archive Network (CRAN) at https://CRAN.R-project.org/package=CeRNASeek.

Antimony Doping Enabled Photoluminescence Quantum Yield Enhancement in 0D Inorganic Bismuth Halide Crystals.

Owing to the exterior self-trapped excitons (STEs) with adjustable fluorescence beams, low-dimensional ns2-metal halides have recently received considerable attention in solid-state light-emitting applications. However, the photoluminescence (PL) mechanism in metal halides remains a major challenge in achieving high efficiency and controllable PL properties because the excited-state energy of ns2 conformational ions varies inhomogeneously with their coordination environments. Here, a novel zero-dimensional (0D) lead-free bismuth-based Rb3BiCl6·0.5H2O crystal was reported as a pristine crystal to modulate the optical properties. By doping Sb3+ ions with 5s2 electrons into Rb3BiCl6·0.5H2O crystals, bright orange emission at room temperature was obtained with a photoluminescence quantum yield of 39.7%. Optical characterizations and theoretical studies show that the Sb3+ doping can suppress the strong exciton-phonon coupling, optimize the electronic energy band structure, improve the thermal activation energy, soften the structural lattice of the host crystals, deepen the STE states, and ultimately lead to strong photoluminescence. This work manifests a fruitful manipulation in ripening bismuth-based halides with high-efficiency PL properties, and the PL enhancement mechanisms will guide future research in the exploration of emerging luminescent materials.

Characterization of Antibiotic-Resistant Stenotrophomonas Isolates from Painted Turtles Living in the Wild.

Stenotrophomonas maltophilia is a ubiquitous multidrug-resistant opportunistic pathogen commonly associated with nosocomial infections. The purpose of this study was to isolate and characterize extended-spectrum beta-lactamase (ESBL) producing bacteria from painted turtles (Chrysemys picta) living in the wild and captured in southeastern Wisconsin. Fecal samples from ten turtles were examined for ESBL producing bacteria after incubation on HardyCHROM™ ESBL agar. Two isolates were cultivated and identified by 16S rRNA gene sequencing and whole genome sequencing (WGS) as Stenotrophomonas sp. 9A and S. maltophilia 15A. They were multidrug-resistant, as determined by antibiotic susceptibility testing. Stenotrophomonas sp. 9A was found to produce an extended spectrum beta-lactamase (ESBL) and both isolates were found to be carbapenem-resistant. EDTA-modified carbapenem inactivation method (eCIM) and the modified carbapenem inactivation method (mCIM) tests were used to examine the carbapenemase production and the test results were negative. Through WGS several antimicrobial resistance genes were identified in S. maltophilia 15A. For example a chromosomal L1 ß-lactamase gene, which is known to hydrolyze carbapenems, a L2 ß-lactamase gene, genes for the efflux systems smeABC and smeDEF and the aminoglycosides resistance genes aac(6')-lz and aph(3')-llc were found. An L2 ß-lactamase gene in Stenotrophomonas sp. 9A was identified through WGS.

Exploring the Common Gene Signatures Between Myocardial Infarction-Reperfusion Injury and the Gut Microbiome Using Bioinformatics.

BACKGROUND: This bioinformatics report attempts to explore the cross-talk genes, transcription factors (TFs), and pathways related to myocardial ischemia-reperfusion injury (MIRI) as well as the gut microbiome. METHOD: The datasets GSE61592 (three MIRI and three sham samples) and GSE160516 (twelve MIRI and four sham samples) were selected in the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) identification (p < 0.05 and |log FC (fold change)| ≥1) together with functional annotation (p < 0.05) was implemented. The Cytoscape platform established the protein-protein interaction (PPI) network. Genes associated with gut microbiome disorder were extracted based on the DisGeNET database, and those associated with MIRI were overlapped. The Recursive Feature Elimination (RFE) algorithm was adopted for selecting features, and cross-talk genes were predicted by the Support Vector Machine (SVM) models. A network encompassing cross-talk genes along with the TFs was thereby established. RESULT: The MIRI datasets comprised 138 shared DEGs, with 101 showing up-regulation whereas 37 showing down-regulation. Notably, the PPI interwork for MIRI contained 2517 edges along with 1818 nodes. By using RFE and SVM methods, six feature genes with the highest prediction were identified: B2m, VCAM-1, PDIA4, Ptgds, Mlxipl, and ACADS. Among these genes, B2m and PDIA4 were most highly expressed in MIRI and the gut microbiome disorder. CONCLUSION: B2m and PDIA4 were identified to be significantly correlated with candidate cross-talk genes of MIRI with gut microbiome disorder, implying a similarity between MIRI and Gut microbiome disorder (GMD). These genes can serve as an experimental research basis for future studies.

Edaravone ameliorates depressive and anxiety-like behaviors via Sirt1/Nrf2/HO-1/Gpx4 pathway.

BACKGROUND: The inflammation and oxidative stress (OS) have been considered crucial components of the pathogenesis of depression. Edaravone (EDA), a free radical scavenger, processes strong biological activities including antioxidant, anti-inflammatory and neuroprotective properties. However, its role and potential molecular mechanisms in depression remain unclear. The present study aimed to investigate the antidepressant activity of EDA and its underlying mechanisms. METHODS: A chronic social defeat stress (CSDS) depression model was performed to explore whether EDA could produce antidepressant effects. Behaviors tests were carried out to examine depressive, anxiety-like and cognitive behaviors including social interaction (SI) test, sucrose preference test (SPT), open field test (OFT), elevated plus maze (EPM), novel object recognition (NOR), tail suspension test (TST) and forced swim test (FST). Hippocampal and medial prefrontal cortex (mPFC) tissues were collected for Nissl staining, immunofluorescence, targeted energy metabolomics analysis, enzyme-linked immunosorbent assay (ELISA), measurement of MDA, SOD, GSH, GSH-PX, T-AOC and transmission electron microscopy (TEM). Western blotting (WB) and quantitative real-time polymerase chain reaction (qRT-PCR) detected the Sirt1/Nrf2/HO-1/Gpx4 signaling pathway. EX527, a Sirt1 inhibitor and ML385, a Nrf2 inhibitor were injected intraperitoneally 30 min before EDA injection daily. Knockdown experiments were performed to determine the effects of Gpx4 on CSDS mice with EDA treatment by an adeno-associated virus (AAV) vector containing miRNAi (Gpx4)-EGFP infusion. RESULTS: The administrated of EDA dramatically ameliorated CSDS-induced depressive and anxiety-like behaviors. In addition, EDA notably attenuated neuronal loss, microglial activation, astrocyte dysfunction, oxidative stress damage, energy metabolism and pro-inflammatory cytokines activation in the hippocampus (Hip) and mPFC of CSDS-induced mice. Further examination indicated that the application of EDA after the CSDS model significantly increased the protein expressions of Sirt1, Nrf2, HO-1 and Gpx4 in the Hip. EX527 abolished the antidepressant effect of EDA as well as the protein levels of Nrf2, HO-1 and Gpx4. Similarly, ML385 reversed the antidepressant and anxiolytic effects of EDA via decreased expressions of HO-1 and Gpx4. In addition, Gpx4 knockdown in CSDS mice abolished EDA-generated efficacy on depressive and anxiety-like behaviors. CONCLUSION: These findings suggest that EDA possesses potent antidepressant and anxiolytic properties through Sirt1/Nrf2/HO-1/Gpx4 axis and Gpx4-mediated ferroptosis may play a key role in this effect.

Large-scale DNA barcoding of the subfamily Culterinae (Cypriniformes: Xenocyprididae) in East Asia unveils a geographical scale effect, taxonomic warnings and cryptic diversity.

Geographical scale might be expected to impact significantly the efficiency of DNA barcoding as spatially comprehensive sampling provides opportunities to uncover intricate relationships among closely related species and to detect cryptic diversity for widespread taxa. Here, we present a DNA barcoding study on a Xencyprididae subfamily (Culterinae) involving the production of 998 newly generated DNA barcodes from East Asian drainages (80 localities). Together with 513 barcodes mined from BOLD and GenBank, a reference library consisting of 1511 DNA barcodes (116 localities) for 42 species was assembled, accounting for 66% of known Culterinae species. Intraspecific genetic distances are positively correlated to geographical scale, while a negative correlation is detected between interspecific genetic distances and geographical scale. The present study demonstrates that geographical scale influences the efficiency of DNA barcoding by narrowing the width of the barcoding gap. DNA-based species delimitation analyses delimited 44 molecular operational taxonomic units (MOTUs). Rampant cryptic diversity is detected within eight species with multiple MOTUs, whereas 25 species present mismatch between morphological and molecular delimitations. A total of 18 species are lumped into nine MOTUs due to low interspecific divergence and/or mixed lineages. Several MOTU divergences are hypothesized to relate to known biogeographical barriers and geological events during the Pliocene and Pleistocene. This study provides new insights into the taxonomy and phylogeography of the subfamily Culterinae.

New insights into the diagnostic characteristics and clinical application of serum biomarkers for lung cancer, and human epididymis protein 4 as a new biomarker?

The value of serum tumor biomarkers used for lung cancer diagnosis is still controversial in clinical practice. This study aimed to further dissect and evaluate the clinical value of serum progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), squamous cell carcinoma antigen (SCC-Ag), carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA21-1) together with a potential new biomarker, the human epididymis protein 4 (HE4) for lung cancer diagnosis, in a large cohort of a Chinese population. Ostensibly healthy individuals, as well as those with benign non-cancerous diseases, benign tumors, lung cancers, and other types of malignancies, were enrolled in the study. Serum ProGRP, NSE, SCC-Ag, CEA, CYFRA21-1, and HE4 were analyzed using the chemiluminescence immunoassay. Data were analyzed utilizing the SPSS and GraphPad Prism software. Detailed dissection of the diagnostic characteristics of serum 6 biomarkers on lung cancer was performed. All 6 biomarkers showed capabilities in characterizing lung cancer from other diseases. ProGRP and NSE were highly specific to small cell lung cancer (SCLC); SCC-Ag was a fair biomarker for NSCLC, specifically SCC histotype; CEA showed specificity to SCLC, followed by NSCLC; CYFRA21-1 was a good biomarker for both SCLC and NSCLC; HE4 showed high specificity to SCLC. For NSCLC characterization, CYFRA21-1+HE4+CEA was the best combinatory pattern in the terms of diagnostic performance (AUC=0.8110). The best combinatory analysis for SCLC was ProGRP+NSE+HE4 (AUC=0.9282). Patients with advanced stage, larger tumor, males, and age 50 or older had higher serum biomarkers levels than those with early stage, smaller tumor, females, and age under 50. Six biomarkers had capabilities in characterizing lung cancer with high or fair diagnostic performance. HE4 is a potential biomarker for both SCLC and NSCLC diagnosis, which merits further investigation.

Isolation of AmpC- and extended spectrum ß-lactamase-producing Enterobacterales from fresh vegetables in the United States.

Vegetables may serve as a reservoir for antibiotic resistant bacteria and resistance genes. AmpC ß-lactamases and extended spectrum beta-lactamases (ESBL) inactivate commonly used ß-lactam antibiotics, including penicillins and cephalosporins. In this study, we determined the prevalence of AmpC and ESBL-producing Enterobacterales in retail vegetables in the United States. A total of 88 vegetable samples were collected for the screening of AmpC and ESBL-producing Enterobacterales using CHROMagar ESBL agar. These vegetables included washed ready-to-eat salad (23), microgreens/sprouts (13), lettuce (11), herbs (11), spinach (5), mushrooms (5), brussels sprouts (4), kale (3), and other vegetable samples (13). AmpC and ESBL activity in these isolates were determined using double disk combination tests. Two vegetable samples (2.27%), organic basil and brussels sprouts, were positive for AmpC-producing Enterobacterales and eight samples (9.09%), including bean sprouts, organic parsley, organic baby spinach, and several mixed salads, were positive for ESBL-producing Enterobacterales. Whole genome sequencing was used to identify the bacterial species and resistance genes in these isolates. Genes encoding AmpC ß-lactamases were found in Enterobacter hormaechei strains S43-1 and 74-2, which were consistent with AmpC production phenotypes. Multidrug-resistant E. hormaechei strains S11-1, S17-1, and S45-4 possess an ESBL gene, blaSHV66 , whereas five Serratia fonticola isolates contain genes encoding a minor ESBL, FONA-5. In addition, we used shotgun metagenomic sequencing approach to examine the microbiome and resistome profiles of three spinach samples. We found that Pseudomonas was the most prevalent bacteria genus in the spinach samples. Within the Enterobacteriaceae family, Enterobacter was the most abundant genus in the spinach samples. Moreover, antibiotic resistance genes encoding 12 major classes of antibiotics, including ß-lactam antibiotics, aminoglycoside, macrolide, fluoroquinolone, and others, were found in these spinach samples. Therefore, vegetables can serve as an important vehicle for transmitting antibiotic resistance. The study highlights the need for antibiotic resistance surveillance in vegetable products.

Temporal Analysis Reveals the Transient Differential Expression of Transcription Factors That Underlie the Trans-Differentiation of Human Monocytes to Macrophages.

The activation of monocytes and their trans-differentiation into macrophages are critical processes of the immune response. Prior work has characterized the differences in the expression between monocytes and macrophages, but the transitional process between these cells is poorly detailed. Here, we analyzed the temporal changes of the transcriptome during trans-differentiation of primary human monocytes into M0 macrophages. We find changes with many transcription factors throughout the process, the vast majority of which exhibit a maximally different expression at the intermediate stages. A few factors, including AP-1, were previously known to play a role in immunological transitions, but most were not. Thus, these findings indicate that this trans-differentiation requires the dynamic expression of many transcription factors not previously discussed in immunology, and provide a foundation for the delineation of the molecular mechanisms associated with healthy or pathological responses that involve this transition.

MicroRNA Transcriptomics Analysis Identifies Dysregulated Hedgehog Signaling Pathway in a Mouse Model of Acute Intracerebral Hemorrhage Exposed to Hyperglycemia.

OBJECTIVE: Hyperglycemia is often observed in the patients after acute stroke. This study aims to elucidate the potential effect and mechanism of hyperglycemia by screening microRNAs expression in intracerebral hemorrhage mice. METHODS: We employed the collagenase model of intracerebral hemorrhage. Twenty male C57BL/6 mice were used and randomly divided in normo- and hyperglycemic. The hyperglycemia was induced by intraperitoneally injection of 50% of Dextrose (8 mL/kg) 3 hours after intracerebral hemorrhage. The neurologic impairment was investigated by neurologic deficit scale. To study the specific mechanisms of hyperglycemia, microRNAs expression in perihematomal area was investigated by RNA sequencing. MicroRNAs expression in hyperglycemic intracerebral hemorrhage animals were compared normoglycemic mice. Functional annotation analysis was used to indicate potential pathological pathway, underlying observed effects. Finally, polymerase chain reaction validation was administered. RESULTS: Intraperitoneal injection of dextrose significantly increased blood glucose level. That was associated with aggravation of neurological deficits in hyperglycemic compared to normoglycemic animals. A total of 73 differentially expressed microRNAs were identified via transcriptomics analysis. Bioinformatics analyses showed that these microRNAs were significantly altered in several signaling pathways, of which the hedgehog signaling pathway was regarded as the most potential pathway associated with the effect of hyperglycemia on acute intracerebral hemorrhage. Furthermore, polymerase chain reaction results validated the correlation between microRNAs and hedgehog signaling pathway. CONCLUSIONS: MicroRNA elevated in hyperglycemia group may be involved in worsening the neurological function via inhibiting the hedgehog signaling, which provides a novel molecular physiological mechanism and lays the foundation for treatment of intracerebral hemorrhage.

U-net model for brain extraction: Trained on humans for transfer to non-human primates.

Brain extraction (a.k.a. skull stripping) is a fundamental step in the neuroimaging pipeline as it can affect the accuracy of downstream preprocess such as image registration, tissue classification, etc. Most brain extraction tools have been designed for and applied to human data and are often challenged by non-human primates (NHP) data. Amongst recent attempts to improve performance on NHP data, deep learning models appear to outperform the traditional tools. However, given the minimal sample size of most NHP studies and notable variations in data quality, the deep learning models are very rarely applied to multi-site samples in NHP imaging. To overcome this challenge, we used a transfer-learning framework that leverages a large human imaging dataset to pretrain a convolutional neural network (i.e. U-Net Model), and then transferred this to NHP data using a small NHP training sample. The resulting transfer-learning model converged faster and achieved more accurate performance than a similar U-Net Model trained exclusively on NHP samples. We improved the generalizability of the model by upgrading the transfer-learned model using additional training datasets from multiple research sites in the Primate Data-Exchange (PRIME-DE) consortium. Our final model outperformed brain extraction routines from popular MRI packages (AFNI, FSL, and FreeSurfer) across a heterogeneous sample from multiple sites in the PRIME-DE with less computational cost (20 s~10 min). We also demonstrated the transfer-learning process enables the macaque model to be updated for use with scans from chimpanzees, marmosets, and other mammals (e.g. pig). Our model, code, and the skull-stripped mask repository of 136 macaque monkeys are publicly available for unrestricted use by the neuroimaging community at https://github.com/HumanBrainED/NHP-BrainExtraction.

Dissection of the Glycosylation in the Biosynthesis of the Heptadecaglycoside Antibiotic Saccharomicin A.

Oligosaccharide natural products have diverse biological activities and represent a potentially important source for drug development. In this study, we focus on the glycosylation pathway in the biosynthesis of saccharomicin A (SA-A), an oligosaccharide antibiotic containing 17 sugar moieties. By extensive gene-knockout studies with comparative metabolic profile analysis, we established a complete pathway in assembling the heptadecasaccharide chain of SA-A, the longest saccharide chain found in natural products.

A pediatric case of primary amoebic meningoencephalitis due to Naegleria fowleri diagnosed by next-generation sequencing of cerebrospinal fluid and blood samples.

BACKGROUND: Primary amoebic meningoencephalitis (PAM) is a rare, acute and fatal disease of the central nervous system caused by infection with Naegleria fowleri (Heggie, in Travel Med Infect Dis 8:201-6, 2010). Presently, the majority of reported cases in the literature have been diagnosed through pathogen detection pathogens in the cerebrospinal fluid (CSF). This report highlights the first case of pediatric PAM diagnosed with amoeba infiltration within CSF and bloodstream of an 8-year-old male child, validated through meta-genomic next-generation sequencing (mNGS). CASE PRESENTATION: An 8-year-old male child was admitted to hospital following 24 h of fever, headache and vomiting and rapidly entered into a coma. CSF examination was consistent with typical bacterial meningitis. However, since targeted treatment for this condition proved to be futile, the patient rapidly progressed to brain death. Finally, the patient was referred to our hospital where he was confirmed with brain death. CSF and blood samples were consequently analyzed through mNGS. N. fowleri was detected in both samples, although the sequence copy number in the blood was lower than for CSF. The pathogen diagnosis was further verified by PCR and Sanger sequencing. CONCLUSIONS: This is the first reported case of pediatric PAM found in mainland China. The results indicate that N. fowleri may spread outside the central nervous system through a damaged blood-brain barrier.

Age-stratified and gender-specific reference intervals of six tumor markers panel of lung cancer: A geographic-based multicenter study in China.

BACKGROUND: Serum biomarkers have been widely adopted in clinical practice for assisting lung cancer diagnoses, therapeutic monitoring, and prognostication. The function of a well-performing tumor biomarker depends on a reliable reference interval (RI) with consideration of the study subjects' age, gender, and geographical location. This study aimed to establish a RI for each of 6 lung cancer biomarkers for use in the whole country of China on Mindray platform. METHODS: The levels of serum 6 lung cancer biomarkers-namely progastrin-releasing peptide (ProGRP), neuron-specific enolase (NSE), squamous cell carcinoma antigen (SCC), carcinoembryonic antigen (CEA), cytokeratin-19 fragment (CYFRA21-1), and human epididymis protein 4 (HE4)-were measured utilizing the chemiluminescence immunoassay on the Mindray CL-6000i platform following the laboratory standard operating procedures in apparently healthy Chinese individuals on large cohort, multicenter, and geographical consideration bases. The CLSI EP28-A3C guideline was followed for the enrollment of study subjects. RESULTS: The age-stratified, gender-specific RIs for ProGRP, NSE, SCC, CEA, CYFRA21-1, and HE4 lung cancer biomarkers in the Chinese population have been established as described in the results and discussion in this work. In addition, various levels of the six lung cancer biomarkers among nine geographical locations in China have been observed. CONCLUSIONS: The sample volume of study cohort, age, and geographical location should be considered upon establishing a reliable biomarker RI. A RI for each of six lung cancer biomarkers has been established. The results from this study would be helpful for clinical laboratories in interpreting the analytical results and for clinicians in patient management.