Constructing hollow core-shell Z-scheme heterojunction CdS@CoTiO3 nanorods for enhancing the photocatalytic degradation of 2,4-DCP and TC.

Constructing Z-scheme heterojunctions incorporating an exquisite hollow structure is an effective performance regulation strategy for the realization of high quantum efficiency and a strong redox ability over photocatalysts. Herein, we report the delicate design and preparation of a core-shell hollow CdS@CoTiO3 Z-scheme heterojunction with a CdS nanoparticle (NP)-constructed outer shell supported on a CoTiO3 nanorod (NR) inner shell. The in situ growth synthetic method led to a tightly connected interface for the heterojunction between CdS and CoTiO3, which shortened the transport distance of photoinduced charges from the interface to the surface. The promoted charge carrier separation efficiency and the retained strong redox capacity caused by the Z-scheme photoinduced charge-transfer mechanism were mainly responsible for the boosted photocatalytic performance. Additionally, the well-designed core-shell structure afforded a larger interfacial area by the multiple direction contact between CdS and CoTiO3, ensuring sufficient channels for efficient charge transfer, and thus further boosting the photocatalytic activity. As an efficient photocatalyst, the optimized CdS@CoTiO3 nanohybrids displayed excellent 2,4-dichlorophenol (2,4-DCP) and tetracycline (TC) degradation efficiencies of 91.3% and 91.8%, respectively. This study presents a Z-scheme heterojunction based on ecofriendly CoTiO3, which could be valuable for the development of metal perovskite photocatalysts for application in environmental remediation, and also demonstrated the tremendous potential of integrating a Z-scheme heterojunction with the morphology design of photocatalyts.

Neutron penumbral image reconstruction with a convolution neural network using fast Fourier transform.

In Inertial Confinement Fusion (ICF), the asymmetry of a hot spot is an important influence factor in implosion performance. Neutron penumbral imaging, which serves as an encoded-aperture imaging technique, is one of the most important diagnostic methods for detecting the shape of a hot spot. The detector image is a uniformly bright range surrounded by a penumbral area, which presents the strength distribution of hot spots. The present diagnostic modality employs an indirect imaging technique, necessitating the reconstruction process to be a pivotal aspect of the imaging protocol. The accuracy of imaging and the applicable range are significantly influenced by the reconstruction algorithm employed. We develop a neural network named Fast Fourier transform Neural Network (FFTNN) to reconstruct two-dimensional neutron emission images from the penumbral area of the detector images. The FFTNN architecture consists of 16 layers that include a FFT layer, convolution layer, fully connected layer, dropout layer, and reshape layer. Due to the limitations in experimental data, we propose a phenomenological method for describing hot spots to generate datasets for training neural networks. The reconstruction performance of the trained FFTNN is better than that of the traditional Wiener filtering and Lucy-Richardson algorithm on the simulated dataset, especially when the noise level is high as indicated by the evaluation metrics, such as mean squared error and structure similar index measure. This proposed neural network provides a new perspective, paving the way for integrating neutron imaging diagnosis into ICF.

Metabolic syndrome prediction model using Bayesian optimization and XGBoost based on traditional Chinese medicine features.

Metabolic syndrome (MetS) has a high prevalence and is prone to many complications. However, current MetS diagnostic methods require blood tests that are not conducive to self-testing, so a user-friendly and accurate method for predicting MetS is needed to facilitate early detection and treatment. In this study, a MetS prediction model based on a simple, small number of Traditional Chinese Medicine (TCM) clinical indicators and biological indicators combined with machine learning algorithms is investigated. Electronic medical record data from 2040 patients who visited outpatient clinics at Guangdong Chinese medicine hospitals from 2020 to 2021 were used to investigate the fusion of Bayesian optimization (BO) and eXtreme gradient boosting (XGBoost) in order to create a BO-XGBoost model for screening nineteen key features in three categories: individual bio-information, TCM indicators, and TCM habits that influence MetS prediction. Subsequently, the predictive diagnostic model for MetS was developed. The experimental results revealed that the model proposed in this paper achieved values of 93.35 %, 90.67 %, 80.40 %, and 0.920 for the F1, sensitivity, FRS, and AUC metrics, respectively. These values outperformed those of the seven other tested machine learning models. Finally, this study developed an intelligent prediction application for MetS based on the proposed model, which can be utilized by ordinary users to perform self-diagnosis through a web-based questionnaire, thereby accomplishing the objective of early detection and intervention for MetS.

ING1 inhibits Twist1 expression to block EMT and is antagonized by the HDAC inhibitor vorinostat.

ING1 is a chromatin targeting subunit of the Sin3a histone deacetylase (HDAC) complex that alters chromatin structure to subsequently regulate gene expression. We find that ING1 knockdown increases expression of Twist1, Zeb 1&2, Snai1, Bmi1 and TSHZ1 drivers of EMT, promoting EMT and cell motility. ING1 expression had the opposite effect, promoting epithelial cell morphology and inhibiting basal and TGF-ß-induced motility in 3D organoid cultures. ING1 binds the Twist1 promoter and Twist1 was largely responsible for the ability of ING1 to reduce cell migration. Consistent with ING1 inhibiting Twist1 expression in vivo, an inverse relationship between ING1 and Twist1 levels was seen in breast cancer samples from The Cancer Genome Atlas (TCGA). The HDAC inhibitor vorinostat is approved for treatment of multiple myeloma and cutaneous T cell lymphoma and is in clinical trials for solid tumours as adjuvant therapy. One molecular target of vorinostat is INhibitor of Growth 2 (ING2), that together with ING1 serve as targeting subunits of the Sin3a HDAC complex. Treatment with sublethal (LD25-LD50) levels of vorinostat promoted breast cancer cell migration several-fold, which increased further upon ING1 knockout. These observations indicate that correct targeting of the Sin3a HDAC complex, and HDAC activity in general decreases luminal and basal breast cancer cell motility, suggesting that use of HDAC inhibitors as adjuvant therapies in breast cancers that are prone to metastasize may not be optimal and requires further investigation.

LDLR promotes autophagy-mediated cisplatin resistance in ovarian cancer associated with the PI3K/AKT/mTOR signaling pathway.

Autophagy is one of the underlying causes of resistance to many antitumor drugs, including cisplatin (DDP). The low-density lipoprotein receptor (LDLR) is a regulator of ovarian cancer (OC) progression. However, whether LDLR regulates DDP resistance in OC via autophagy-related pathways remains unclear. LDLR expression was measured by quantitative real-time PCR, western blot (WB) and IHC staining. A Cell Counting Kit 8 assay was employed to evaluate DDP resistance and cell viability, and flow cytometry was used to assess apoptosis. WB analysis was employed to evaluate the expression of autophagy-related proteins and PI3K/AKT/mTOR signaling pathway proteins. The autophagolysosomes and the fluorescence intensity of LC3 were observed by transmission electron microscopy and immunofluorescence staining, respectively. A xenograft tumor model was established to explore the role of LDLR in vivo. LDLR was highly expressed in OC cells, which was correlated with disease progression. In DDP-resistant OC cells, high LDLR expression was related to DDP resistance and autophagy. Downregulation of LDLR repressed autophagy and growth in DDP-resistant OC cell lines by activating the PI3K/AKT/mTOR pathway, and these effects were eliminated by an mTOR inhibitor. In addition, LDLR knockdown also reduced OC tumor growth by suppressing autophagy associated with the PI3K/AKT/mTOR pathway. LDLR promoted autophagy-mediated DDP resistance in OC associated with the PI3K/AKT/mTOR pathway, indicating that LDLR might be a new target to prevent DDP resistance in OC patients.

Identification of potential biomarkers for diagnosis of syphilis from the cerebrospinal fluid based on untargeted metabolomic analysis.

The infection rate of syphilis continues to rise globally, and the difficulty in diagnosis of neurosyphilis promptly needs to be resolved. More specific and sensitive diagnostic markers for latent syphilis and neurosyphilis should be found. Here the metabolic profiles of 88 cerebrospinal fluid samples from syphilis patients and controls were analyzed by LC/MS-based untargeted metabolomics. In total, 272 metabolites based on 3937 features obtained in ESI- mode and 252 metabolites based on 3799 features in ESI+ mode were identified. The experimental process was evaluated by principal component analysis, partial least squares discriminant analysis, and hierarchical cluster analysis. A clear separation between latent syphilis and neurosyphilis was found. Levels of lipid and linoleic acid metabolites, such as 9-oxo-octadecadienoic acid and 9,10,13-trihydroxyoctadecenoic acid, were increased in syphilis patients. In patients with neurosyphilis, significant changes in levels of 5-hydroxy-L-tryptophan (5-HTP) and acetyl-N-formyl-5-methoxykynurenamine (AFMK) in the tryptophan-kynurenine pathway were also detected. Only one metabolite, theophylline, differed significantly between symptomatic and asymptomatic neurosyphilis patients. Additionally, KEGG analysis revealed significant enrichment of tryptophan metabolism pathways, indicating a high correlation between tryptophan metabolism and syphilis symptoms. Levels of linoleic acid metabolites, 5-HTP, AFMK and theophylline were significantly altered in different patients. The role of these differential metabolites in the development of syphilis is worthy of further exploration. Our results may promote the development of biomarkers for diagnosis of latent syphilis from neurosyphilis, and for that of asymptomatic neurosyphilis from symptomatic neurosyphilis in the future.

Role of symbiotic microbiota dysbiosis in the progression of chronic kidney disease accompanied with vascular calcification.

Background: Chronic kidney disease (CKD) is now globally recognized as a critical public health concern. Vascular calcification (VC) represents a significant risk factor for cardiovascular events in individuals with CKD. It is the accessible and precise diagnostic biomarkers for monitoring the progression of CKD and the concurrent VC are urgently needed. Methods: The adenine diet-induced CKD rat model was utilized to investigate chronic kidney injury, calcification in the kidney and thoracic aorta, and dysregulation of biochemical indices. Enzyme-linked immune sandwich assays were employed to analyze changes in calcification-related proteins. 16S rRNA sequencing was performed to delineate the microbiota characteristics in the gut and blood of CKD-afflicted rats. Additionally, transcriptome sequencing of kidney tissue was conducted to explore the relationship between CKD-associated microbiota features and alterations in kidney function. Results: The adenine diet-induced CKD inhibited body weight gain, and led to kidney injury, and pronounced calcification in kidney and thoracic aorta. The microbiota both in the gut and blood of these affected rats exhibited significantly lower alpha diversity and distinctive beta diversity than those in their healthy counterparts. CKD resulted in dysregulation of several biochemical indices (including elevated levels of creatinine, low-density lipoprotein-cholesterol, sodium, phosphorous, total cholesterol, and urea and decreased levels of albumin, calcium, lactate dehydrogenase, and total bilirubin). Moreover, it upregulated calcification-related factors (bone sialoprotein [BSP], Klotho, fibroblast growth factor [FGF]-23, and sclerostin [SOST]) and lipopolysaccharide (LPS). Notably, the increased Acinetobacter in the blood was positively associated with calcifications in the kidney and thoracic aorta, in addition to the positive correlation with gut microbiota. The enrichment of Acinetobacter was concurrent with increases in calcification factors (BSP, FGF-23, and SOST), LPS, and phosphorous. Furthermore, transcriptome sequencing revealed that the enrichment of Acinetobacter was positively correlated with the majority of upregulated genes and negatively correlated with downregulated genes involved in the mineral absorption pathway. Conclusion: Our findings, for the first time, underscore that dysbiosis of symbiotic microbiota, both in the gut and blood, is involved in the progression of CKD. Particularly, the enrichment of Acinetobacter in blood emerges as a potential risk factor for CKD and its accompanying VC.

Evaluation of novel obesity- and lipid-related indices as predictors of abnormal glucose tolerance in Chinese women with polycystic ovary syndrome.

PURPOSE: We aimed to evaluate the performance of Chinese visceral adiposity index (CVAI), visceral adiposity index (VAI), lipid accumulation product (LAP), triglyceride glucose (TyG) as indices in screening abnormal glucose tolerance (AGT) in Chinese women with polycystic ovary syndrome (PCOS), using the oral glucose tolerance test (OGTT) as a reference test. In addition, we essentially compared the abilities of these indices with body mass index (BMI), waist circumference (WC), fasting plasma glucose (FPG). MATERIALS AND METHODS: All 1113 PCOS patients evaluated in this study underwent OGTTs. The 2-h post-oral glucose load (2 h-PG) level was used to categorize subjects into two groups: those having AGT or normal glucose tolerance (NGT) levels. RESULTS: A statistically significant positive correlation between levels of 2 h-PG and FPG, BMI, WC, LAP, VAI, CVAI, TyG, (P < 0.05), was observed. The strongest correlation was found between the levels of 2 h-PG and CVAI (r = 0.47). The CVAI provided the highest area under the receiver-operating characteristic curve (AUC) for AGT, followed by LAP, BMI, TyG, VAI, WC, and FPG. The CVAI of 32.61 (with AUC: 0.76, sensitivity: 73%, specificity: 70%, positive preductive value (PPV): 0.41, negative predictive value (NPV): 0.90) was found to be the cut-off point for AGT in Chinese women with PCOS. CONCLUSIONS: CVAI may not reliably detect AGT in Chinese women with PCOS. However, it is suitable as a first screening indicator to guide physicians to ordering OGTT.

Research on Bending Performance of Three-Dimensional Deep Angle Interlock Kevlar/EP Armor Material.

Three-dimensional (3D) woven composites have attracted much attention in the lightweight research of protective armor due to their high specific strength and good impact resistance. However, there are still many gaps in terms of the performance and influencing factors of three-dimensional deep-angle-interlock (3DDAI) Kevlar/EP armor materials. Therefore, in order to prepare 3DDAI Kevlar/EP armor materials with excellent ballistic resistance and mechanical properties, this paper studies the bending performance of 3DDAI Kevlar/EP armor materials and the influence of the number of stacking layers, resin content, laying method, and weft density. Finally, we compare it with the traditional two-dimensional (2D) plain laminated Kevlar/EP armor material. The results showed that when the 3DDAI Kevlar/EP armor material was subjected to bending load, the upper and bottom layers of the material had a great influence on the initial stiffness and fracture strength of the material, respectively; when the material's warp and weft density are quite different, the utilization rate of the yarn and the strength of the material are negatively affected; the fracture energy of the 3DDAI Kevlar/EP armor material prepared by the orthogonal laying method was about 20% higher than that of the 3DDAI Kevlar/EP armor material with the unidirectional layering method; and the bending performance of the 3DDAI Kevlar/EP armor material in the weft direction was better than that of the 2D plain laminated Kevlar/EP armor material, with the 3DDAI Kevlar/EP armor material having better delamination resistance. The research results will lay the foundation for structural optimization and engineering applications of such materials.

A Peptidomic Approach to Identify Novel Antigen Biomarkers for the Diagnosis of Tuberculosis.

Background: Here, we conducted a peptidomic study in murine model to identify novel antigen biomarkers for the diagnosis of tuberculosis (TB) with improved performance. Methods: Four recombinant proteins, including Mycobacterium tuberculosis protein 32 (MPT32), Mycobacterium tuberculosis protein 64 (MPT64), culture filtrate protein 10 (CFP10), and phosphate ABC transporter substrate-binding lipoprotein (PstS1) were expressed and intravenously injected into BALB/c mice. The serum were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS). The concentrations of candidate peptides in serum of suspected TB patients were determined using competitive enzyme-linked immunosorbent assay. Results: A total of 65 peptides from 4 MTB precursor recombinant proteins were identified in mouse serum by LC-MS/MS, of which 5 peptides were selected as candidates for serological analysis. The concentrations of peptides MPT64-2, CFP10-2 and PstS1-2 in TB patients were significantly higher than those in non-TB patients. MPT64-2 exhibited the most promising sensitivity (81.4%), followed by PstS1-2 and CFP10-2. In addition, PstS1-2 had the highest specificity (93.3%), followed by CFP10-2 and MPT64-2. According to the area under the curve (AUC), MPT64-2 (AUC = 0.863), PstS1-2 (AUC = 0.812) and CFP10-2 (AUC = 0.809) exhibited better diagnostic validity. Conclusion: We develop an effective approach to identify new antigen biomarkers via LC-MS/MS-based peptidomics. Multiple peptides exhibit promising efficacy in diagnosis of active TB patients.

Accuracy of ultrasound elastography for predicting breast cancer response to neoadjuvant chemotherapy: A systematic review and meta-analysis.

BACKGROUND: Several studies have reported the prognostic value of ultrasound elastography (UE) in patients receiving neoadjuvant chemotherapy (NACT) for breast cancer. However, the assessment of parameters differed between shear-wave elastography and strain elastography in terms of measured elasticity parameter and mode of imaging. It is important, therefore, to assess the accuracy of the two modes of elastography. AIM: To assess the accuracy of UE for predicting the pathologic complete response (pCR) in breast cancer patients following NACT. METHODS: A comprehensive and systematic search was performed in the databases of MEDLINE, EMBASE, SCOPUS, PubMed Central, CINAHL, Web of Science and Cochrane library from inception until December 2020. Meta-analysis was performed using STATA software "Midas" package. RESULTS: A total of 14 studies with 989 patients were included. The pooled sensitivities were 86% [95% confidence interval (CI): 76%-92%] for UE, 77% (95%CI: 68%-84%) for shear-wave elastography, and 92% (95%CI: 73%-98%) for strain-wave elastography. The pooled score specificities were 86% (95%CI: 80%-90%) for UE, 84% (95%CI: 72%-91%) for shear-wave elasticity, and 87% (95%CI: 81%-92%) for strain-wave elastography. A significant heterogeneity was found among studies based on the chi-square test results and an I 2 statistic > 75%. CONCLUSION: Strain-wave type of UE can accurately predict the pCR following NACT amongst breast cancer patients. Studies exploring its accuracy in different ethnic populations are required to strengthen the evidence.

Characterization of O-mannosylated proteins profiling in bacillus Calmette-Guérin via gel-based and gel-free approaches.

Posttranslational modifications (PTMs) could influence many aspects of protein behavior and function in organisms. Protein glycosylation is one of the major PTMs observed in bacteria, which is crucial for functional regulations of many prokaryotic and eukaryotic organisms. Mycobacterium bovis bacillus Calmette-Guérin (BCG) vaccine has been recognized as an indispensable tool in the global fight against tuberculosis (TB) worldwide over several decades. Nevertheless, analysis of glycoprotein profiles of BCG has not been clearly investigated. In this study, we performed O-mannosylated protein analysis in BCG bacteria using gel-based and gel-free approaches. In total, 1,670 hexosylated peptides derived from 754 mannosylated proteins were identified. Furthermore, 20 novel protein products supported by 78 unique peptides not annotated in the BCG database were detected. Additionally, the translational start sites of 384 proteins were confirmed, and 78 proteins were validated through the extension of translational start sites based on N-terminus-derived peptides. The bioinformatic analysis of the O-mannosylated proteins was performed and the expression profiles of four randomly selected proteins were validated through Western blotting. A number of proteins involved in metabolic pathways, including the tricarboxylic acid cycle, glycolysis, oxidative phosphorylation, and two-component system, are discussed. Taken together, these results offer the first O-mannosylated protein analysis of a member of mycobacteria reported to date by using complementary gel-based and gel-free approaches. Some of the proteins identified in this study have important roles involved in metabolic pathways, which could provide insight into the immune molecular mechanisms of this recognized vaccine strain.

One-step in situ formation of 3D hollow sphere-like V2O5 incorporated Ni3V2O8 hybrids with enhanced photocatalytic performance.

3-D hollow sphere-like Ni3V2O8 immobilizing V2O5 nanoparticles were successfully synthesized via in situ recrystallization method without any template. The compact contact between V2O5 and Ni3V2O8 ensuring the photo-inducted carriers fast transport, which would be beneficial for inhibiting recombination rate of electron-hole (e-/h+) pairs. Moreover, the hollow sphere-like structure composed of the smaller nanoparticle could effectively improve of visible light capture capacity (multiple scattering for hollow architectures). Benefiting the synergistic promoting effect of the suitable heterojunction and the fascinating 3D hollow feature, the V2O5@Ni3V2O8 indicated significantly degradation performance when evaluated as photocatalyst for degradation antibiotics and chlorophenols under visible light irradiation. Impressively, the 2-V2O5@Ni3V2O8 heterojunction deliver the optimal degradation efficiency for TC (OTC) and 2,4-DCP (4-CP) were 90.0% (~91.2%) and 92.6% (~90.0%), respectively. The appearance mechanism for the enhancement photocatalytic performance was also elucidated in detail. The facile strategy provides a novel insight into the designing of the photocatalyst with advantages of charges separation and light-harvesting for degradation of contaminants in wastewater.

Evaluation of Novel Obesity and Lipid-Related Indices as Indicators for the Diagnosis of Metabolic Syndrome and Premetabolic Syndrome in Chinese Women with Polycystic Ovary Syndrome.

OBJECTIVES: According to the International Diabetes Federation (IDF) criteria, previous studies in Chinese women with polycystic ovary syndrome (PCOS) reported a low prevalence of metabolic syndrome (MS); however, the same population predisposed to developing pre-MS. Early identification and treatment of individuals with MS and pre-MS are imperative to prevent their adverse consequences. Moreover, fasting plasma glucose (FPG) was not accurate in detecting pathoglycemia in women with PCOS as they have shown characteristically postprandial abnormalities in the carbohydrate metabolism. Therefore, we aimed to compare the discriminative performance of various indices for identifying MS and pre-MS/MS (pre-MS and MS) using the updated Chinese Diabetes Society (uCDS) criteria in Chinese women with PCOS. METHODS: 1083 Chinese women with PCOS were included in this study. We measured and evaluated 8 indices in all individuals. Based on the uCDS criteria for MS, patients who had no less than two components of MS but did not meet the criteria for the diagnosis of MS were considered as having pre-MS. Receiver operating characteristic (ROC) curves and the area under ROC curves (AUCs) levels were used to assess the accuracy of each index in detecting MS and pre-MS/MS. RESULTS: Among the 8 indices assessed, the lipid accumulation product (LAP) provided the highest AUCs for detecting MS and pre-MS/MS, followed by CVAI, WTI, VAI, TyG, TG/HDL, WC, and BMI. The optimal cutoff points determined for LAP were 45.13 (sensitivity 88.0%, specificity 88.4%, and Youden index 0.764) for MS and 28.01 (sensitivity 87.5%, specificity 80.7%, and Youden index 0.681) for pre-MS/MS, respectively. CONCLUSIONS: uCDS criteria are reasonably more suitable for detecting MS and pre-MS in Chinese women with PCOS. Based on this criterion, LAP is the best index for the diagnosis of MS and pre-MS/MS in Chinese women with PCOS, out of the 8 obesity and lipid-related indices assessed.

Polypeptide LTX-315 reverses the cisplatin chemoresistance of ovarian cancer cells via regulating Beclin-1/PI3K/mTOR signaling pathway.

OBJECTIVE: Polypeptide LTX-315 induces immunogenic cell death, thus having the potential to improve the effect of anticancer treatment. However, the function of LTX-315 in reversing chemoresistance in ovarian cancer (OC) still remains elusive. Our study aims to decipher the effect of LTX-315 on reversing the chemoresistance of OC cells and explore its mechanism. METHODS: SKOV3, A2780, SKOV3/DDP, and A2780/DDP cells (cisplatin [DDP]-resistant cells] were treated with different concentrations of LTX-315 (10 and 20 µmol/L), respectively. Cell counting kit-8 assay, Transwell assay, and flow cytometry were used to assess cell viability, migration, invasion, apoptosis rate, and cell cycle of the cells. Western blot was performed to examine the expression of cleaved caspase 3, caspase 3, cleaved Poly (ADP-ribose) polymerase (PARP), PARP, Bax, Bcl-2, Beclin-1, p-Akt, Akt, p-mammalian target of rapamycin (mTOR), and mTOR. Furthermore, OC cells were treated with autophagy inhibitor 3-methyladenine (3-MA), and "rescue experiments" were performed. RESULTS: DDP-resistant OC cell models were established, and LTX-315 treatment resulted in lower IC50 of DDP. In OC cells treated with LTX-315, the viability, migration, invasion and the expression of Bcl-2 of were repressed, but the apoptotic rate and the expression of cleaved caspase 3, cleaved PARP and Bax were increased, and the cell cycle was arrested. Moreover, LTX-315 promoted Beclin-1 expression level and inhibited p-Akt and p-mTOR expression levels, whereas 3-MA could partially reverse the biological effects of LTX-315 on OC cells. CONCLUSION: LTX-315 can inhibit the resistance of OC cells to DDP in vitro and plays a role by regulating Beclin-1/phosphatidylinositol-3-kinase/mTOR signaling pathway.

Urinary proteomic analysis to identify a potential protein biomarker panel for the diagnosis of tuberculosis.

Tuberculosis (TB) is caused by Mycobacterium tuberculosis and is one of the primary causes of death worldwide. Rapid and accurate diagnosis of TB is one of the most direct means to reduce the incidence of TB. In this study, urinary proteomic profiling of TB patients and non-TB individual controls (HCs) was performed, and differentially expressed urinary proteins between TB and HCs were compared and exclusively expressed proteins in TB patients were selected to establish a clinically useful disease marker panel. In total, these top 11 targeted proteins with 265 peptides were scheduled for multiple reaction monitoring validation analysis by using urine samples from 52 TB patients and 52 HCs. The result demonstrated that a three-protein combination out of the five-protein panel (namely P22352, Q9P121, P15151, Q13291, and Q8NDA2) exhibited sensitivity rate of 82.7% in the diagnosis of TB. Furthermore, the three-protein combination could differentiate TB from the latent tuberculosis (LTB) effectively, which exhibited specificity rate of 92.3% for the diagnosis of TB from the LTB category. Although more numbers of clinical samples are required for further verification, the results provided preliminary evidence that this "three-protein combination" out of the five-protein panel could probably be a novel TB diagnostic biomarker in clinical application.

Urinary metabolomic analysis to identify potential markers for the diagnosis of tuberculosis and latent tuberculosis.

Tuberculosis (TB) is a serious infectious disease with high infection and mortality rates. 5%-10% of the latent tuberculosis infections (LTBI) are likely to develop into active TB, and there are currently no clinical biomarkers that can distinguish between LTBI, active TB and other non-tuberculosis populations. Therefore, it is necessary to develop rapid diagnostic methods for active TB and LTBI. In this study, urinary metabolome of 30 active TB samples and the same number of LTBI and non-TB control samples were identified and analyzed by UPLC-Q Exactive MS. In total, 3744 metabolite components were obtained in ESI- mode and 4086 in ESI + mode. Orthogonal partial least square discriminant analysis (OPLS-DA) and hierarchical cluster analysis (HCA) showed that there were significant differences among LTBI, active TB and non-TB. Six differential metabolites were screened in positive and negative mode, 3-hexenoic acid, glutathione (GSH), glycochenodeoxycholate-3-sulfate, N-[4'-hydroxy-(E)-cinnamoyl]-l-aspartic acid, deoxyribose 5-phosphate and histamine. The overlapping pathways differential metabolites involved were mainly related to immune regulation and urea cycle. The results showed that the urine metabolism of TB patients was disordered and many metabolic pathways changed. Multivariate statistical analysis revealed that GSH and histamine were selected as potential molecular markers, with area under curve of receiver operating characteristic curve over 0.75. Among the multiple differential metabolites, GSH and histamine changed to varying degrees in active TB, LTBI and the non-TB control group. The levels of GSH and histamine in 48 urinary samples were measured by ELISA in validation phase, and the result in our study provided the potential for non-invasive biomarkers of TB.

Frequency-Domain Fusing Convolutional Neural Network: A Unified Architecture Improving Effect of Domain Adaptation for Fault Diagnosis.

In recent years, transfer learning has been widely applied in fault diagnosis for solving the problem of inconsistent distribution of the original training dataset and the online-collecting testing dataset. In particular, the domain adaptation method can solve the problem of the unlabeled testing dataset in transfer learning. Moreover, Convolutional Neural Network (CNN) is the most widely used network among existing domain adaptation approaches due to its powerful feature extraction capability. However, network designing is too empirical, and there is no network designing principle from the frequency domain. In this paper, we propose a unified convolutional neural network architecture from a frequency domain perspective for a domain adaptation named Frequency-domain Fusing Convolutional Neural Network (FFCNN). The method of FFCNN contains two parts, frequency-domain fusing layer and feature extractor. The frequency-domain fusing layer uses convolution operations to filter signals at different frequency bands and combines them into new input signals. These signals are input to the feature extractor to extract features and make domain adaptation. We apply FFCNN for three domain adaptation methods, and the diagnosis accuracy is improved compared to the typical CNN.

Preparation of hemodialysis centers in fighting against the novel coronavirus disease during the 2019-2020 epidemic: the experience in Sichuan province, China.

BACKGROUND: Dialysis patients are at high risk of being infected by the novel coronavirus. This article aimed to share our experience in preparing hemodialysis centers in fighting against the COVID-19 in Sichuan province. METHODS: To control COVID-19, the Sichuan Renal Disease Quality Control Center (SRDQCC) organized a multidisciplinary team to draft and distribute documents for dialysis centers. The SRDQCC also established an online education system and a registry. A survey was used to assess the resources and the preparation of the dialysis centers. Patients with infected COVID-19 were transferred to the referral hospitals and treated with continuous renal replacement therapy (CRRT) in isolated rooms. RESULTS: All 21 regions in Sichuan province had designated specific referral hospitals for COVID-19. The documents drafted by the SRDQCC were distributed to all dialysis centers. A total of 313 records from the survey showed that 96% (301/313) of the dialysis centers had set up an emergency program based on the relevant documents. Only 39% (121/313) of the centers had emergency isolated room(s) for COVID-19. Also, 22% (68/313) of the centers had their patient(s) moved to other centers. The online system educated medical staff in 87% (271/313) of the centers. The online registry received 329 records. Four cases of COVID-19-infected dialysis patients were reported until March 3rd, 2020. There were no outbreaks of COVID-19 in any dialysis center in Sichuan province. CONCLUSIONS: The experience of dialysis centers in Sichuan province in fighting against COVID-19 is worth sharing. Dialysis centers need to be prepared to cope with infectious epidemics guided by national as well as regional quality control centers or other similar organizations.

Knockdown of BAG3 synergizes with olaparib to kill ovarian cancer cells via repressing autophagy.

This study aimed at expounding the synergistic effect of Bcl-2-associated athanogene 3 (BAG3) knockdown and poly ADP-ribose polymerase (PARP) inhibitor on ovarian cancer (OC) cells and the potential mechanism. Short hairpin RNA (shRNA) targeting BAG3 (sh-BAG3) was transfected into SK-OV-3 (SKOV-3 ;SKOV3) and A2780 cells, and western blot assay was used to detect transfection efficiency. Cell proliferation and apoptosis were detected by the cell counting kit-8 method, 5-Bromodeoxyuridine (BrdU) experiment and flow cytometry analysis, respectively. The expressions of apoptosis-related proteins Bax and Bcl-2, as well as the expressions of autophagy-related proteins LC3-I, LC3-II and Beclin-1, were examined by western blot assay. Additionally, the cells were treated with autophagy activator rapamycin to investigate whether the tumor-suppressive function of BAG3 knockdown+PARP inhibitor was dependent on autophagy. In this work, we demonstrated that BAG3 knockdown further sensitized OC cells to olaparib treatment, reducing cellular viability and promoting apoptosis. Both sh-BAG3 and olaparib decreased the expression of Beclin-1 and the LC3-Ⅱ:LC3-I ratio, and their synergism further inhibited the process of autophagy. However, the aforementionede effects were reversed after the cells were treated with rapamycin. Based on these results, we concluded that BAG3 knockdown synergizes with olaparib to kill OC cells in vitro by repressing autophagy.