Bias-Switchable Dual-Mode Organic Photodetector with High Operational Stability Using Self-Trapped Cs3Cu2I5 Interfacial Layer.

Conventional photovoltaic (PV)-photodetectors are hard to detect fainted signals, while photomultiplication (PM)-capable devices indispensable for detecting weak light and are prone to degrade under strong light illumination and large bias, and it is urgent to realize highly efficient integrated detecting system with both PM and PV operation modes. In this work, one lead-free Cs3Cu2I5 nanocrystals with self-trapping exciton nature was introduced as interfacial layer adjacent to bulk and layer-by-layer heterojunction structure, and corresponding organic photodetectors with bias-switchable dual modes are demonstrated. The fabricated device exhibits low operating bias (0 V for PV mode and 0.8 V for PM mode), high specific detectivity (~1013 Jones), fast response speed as low as 1.59 µs, large bandwidth over 0.2 MHz and long-term operational stability last for 4 months in ambient condition. This synergy strategy also validated in different materials and device architectures, providing a convenient and scalable production process to develop highly efficient bias-switchable multi-functional organic optoelectrical applications.

Effect of the gut microbiome, plasma metabolome, peripheral cells, and inflammatory cytokines on obesity: a bidirectional two-sample Mendelian randomization study and mediation analysis.

Background: Obesity is a metabolic and chronic inflammatory disease involving genetic and environmental factors. This study aimed to investigate the causal relationship among gut microbiota abundance, plasma metabolomics, peripheral cell (blood and immune cell) counts, inflammatory cytokines, and obesity. Methods: Summary statistics of 191 gut microbiota traits (N = 18,340), 1,400 plasma metabolite traits (N = 8,299), 128 peripheral cell counts (blood cells, N = 408,112; immune cells, N = 3,757), 41 inflammatory cytokine traits (N = 8,293), and 6 obesity traits were obtained from publicly available genome-wide association studies. Two-sample Mendelian randomization (MR) analysis was applied to infer the causal links using inverse variance-weighted, maximum likelihood, MR-Egger, weighted median, weighted mode, and Wald ratio methods. Several sensitivity analyses were also utilized to ensure reliable MR results. Finally, we used mediation analysis to identify the pathway from gut microbiota to obesity mediated by plasma metabolites, peripheral cells, and inflammatory cytokines. Results: MR revealed a causal effect of 44 gut microbiota taxa, 281 plasma metabolites, 27 peripheral cells, and 8 inflammatory cytokines on obesity. Among them, five shared causal gut microbiota taxa belonged to the phylum Actinobacteria, order Bifidobacteriales, family Bifidobacteriaceae, genus Lachnospiraceae UCG008, and species Eubacterium nodatum group. Furthermore, we screened 42 shared causal metabolites, 7 shared causal peripheral cells, and 1 shared causal inflammatory cytokine. Based on known causal metabolites, we observed that the metabolic pathways of D-arginine, D-ornithine, linoleic acid, and glycerophospholipid metabolism were closely related to obesity. Finally, mediation analysis revealed 20 mediation relationships, including the causal pathway from gut microbiota to obesity, mediated by 17 metabolites, 2 peripheral cells, and 1 inflammatory cytokine. Sensitivity analysis represented no heterogeneity or pleiotropy in this study. Conclusion: Our findings support a causal relationship among gut microbiota, plasma metabolites, peripheral cells, inflammatory cytokines, and obesity. These biomarkers provide new insights into the mechanisms underlying obesity and contribute to its prevention, diagnosis, and treatment.

A Hierarchical Graph Neural Network Framework for Predicting Protein-Protein Interaction Modulators With Functional Group Information and Hypergraph Structure.

Accurate prediction of small molecule modulators targeting protein-protein interactions (PPIMs) remains a significant challenge in drug discovery. Existing machine learning-based models rely on manual feature engineering, which is tedious and task-specific. Recently, deep learning models based on graph neural networks have made remarkable progress in molecular representation learning. However, many graph-based approaches ignore molecular hierarchical structure modeling guided by domain knowledge. In chemistry, the functional groups of a molecule determine its interaction with specific targets. Therefore, we propose a hierarchical graph neural network framework (called HiGPPIM) for predicting PPIMs by integrating atom-level and functional group-level features of molecules. HiGPPIM constructs atom-level and functional group-level graphs based on chemical knowledge and learns graph representations using graph attention networks. Furthermore, a hypergraph attention network is designed in HiGPPIM to aggregate and transform two-level graph information. We evaluate the performance of HiGPPIM on eight PPI families and two prediction tasks, namely PPIM identification and potency prediction. Experimental results demonstrate that HiGPPIM achieves state-of-the-art performance on both tasks and that using functional group information to guide PPIM prediction is effective.

Orientation of graphene nanosheets in suspension under an electric field: theoretical model and molecular dynamic simulations.

Orientation regulation of nanoparticles in a suspension by an electric field is a powerful tool to tune its mechanical, thermal, optical, electrical properties etc. However, how molecular modification can affect the orientation of two-dimensional nanoparticles is still unclear. In this paper, the influence of molecular modification on the orientation of graphene nanosheets (GNS) in water was investigated through theoretical analyses and molecular dynamics (MD) simulations. Firstly, a new orientation angle model was proposed, which considers hydration effects, dipole moments and resistance torque. Then, MD simulations were conducted to investigate the effects of position, direction, type, and number of functional groups on the orientation of GNS. The trend observed in MD simulations is consistent with the proposed theoretical model. The results reveal that, under the combined influence of the dipole moment and hydration effects, the modification with hydrophilic functional groups can reduce the orientation angle from 21.31° to 8.34°, while the modification with hydrophobic functional groups increases it to 26.43°. Among the hydrophilic functional groups, orientation of hydroxylated GNS is the best. With an increase in the number of hydroxyl groups, orientation angle is decreased from 12.61° to 8.34°. This work can provide valuable guidance for the design of high-performance suspensions and composites, such as thermal smart materials with adjustable thermal conductivity and intelligent devices with tailored capabilities.

Microbiota in colorectal cancer related to liver metastasis.

The prevalence of colorectal cancer (CRC) is increasing annually and metastasis is the principal cause of death in patients with CRC, with the liver being the most frequently affected site. Many studies have shown a strong interplay between the gut flora, particularly Fusobacterium nucleatum (F. nucleatum), Escherichia coli, and Bacteroides fragilis, and the development of gut tumors. Some strains can induce gut inflammation and produce toxins that directly harm gut epithelial cells, ultimately accelerating the onset and progression of CRC. However, little clinical evidence exists on the specific interplay between the gut microflora and colorectal cancer liver metastasis (CRLM). Some research showed the existence of viable F. nucleatum in distant metastasis of CRC. Subsequently, gut microbiota products, such as lipopolysaccharides, sodium butyrate, and protein cathepsin K, were also found to affect the development of CRC. This article summarizes the mechanism and research status of the interplay between gut microflora and CRLM, discusses the importance of gut microflora in the treatment of CRLM, and proposes a new approach to understanding the mechanism of CRLM and potential treatments for the microbiome. It is anticipated that the gut microbiota will be a formidable therapeutic and prophylactic tool for treating and preventing CRLM.

PPII-AEAT: Prediction of protein-protein interaction inhibitors based on autoencoders with adversarial training.

Protein-protein interactions (PPIs) have shown increasing potential as novel drug targets. The design and development of small molecule inhibitors targeting specific PPIs are crucial for the prevention and treatment of related diseases. Accordingly, effective computational methods are highly desired to meet the emerging need for the large-scale accurate prediction of PPI inhibitors. However, existing machine learning models rely heavily on the manual screening of features and lack generalizability. Here, we propose a new PPI inhibitor prediction method based on autoencoders with adversarial training (named PPII-AEAT) that can adaptively learn molecule representation to cope with different PPI targets. First, Extended-connectivity fingerprints and Mordred descriptors are employed to extract the primary features of small molecular compounds. Then, an autoencoder architecture is trained in three phases to learn high-level representations and predict inhibitory scores. We evaluate PPII-AEAT on nine PPI targets and two different tasks, including the PPI inhibitor identification task and inhibitory potency prediction task. The experimental results show that our proposed PPII-AEAT outperforms state-of-the-art methods.

Silica-induced macrophage pyroptosis propels pulmonary fibrosis through coordinated activation of relaxin and osteoclast differentiation signaling to reprogram fibroblasts.

Silica nanoparticle (SiNP) exposure induces severe pulmonary inflammation and fibrosis, but the pathogenesis remains unclear, and effective therapies are currently lacking. To explore the mechanism underlying SiNPs-induced pulmonary fibrosis, we constructed in vivo silica exposure animal models and in vitro models of silica-induced macrophage pyroptosis and fibroblast transdifferentiation. We found that SiNP exposure elicits upregulation of pulmonary proteins associated with pyroptosis, including NLRP3, ASC, IL-1ß, and GSDMD, while the immunofluorescence staining co-localized NLRP3 and GSDMD with macrophage-specific biomarker F4/80 in silica-exposed lung tissues. However, the NLRP3 inhibitor MCC950 and classical anti-fibrosis drug pirfenidone (PFD) were found to be able to alleviate silica-induced collagen deposition in the lungs. In in vitro studies, we exposed the fibroblast to a conditioned medium from silica-induced pyroptotic macrophages and found enhanced expression of α-SMA, suggesting increased transdifferentiation of fibroblast to myofibroblast. In line with in vivo studies, the combined treatment of MCC950 and PFD was demonstrated to inhibit the expression of α-SMA and attenuate fibroblast transdifferentiation. Mechanistically, we adopted high throughput RNA sequencing on fibroblast with different treatments and found activated signaling of relaxin and osteoclast differentiation pathways, where the expression of the dysregulated genes in these two pathways was examined and found to be consistently altered both in vitro and in vivo. Collectively, our study demonstrates that SiNP exposure induces macrophage pyroptosis, which subsequently causes fibroblast transdifferentiation to myofibroblasts, in which the relaxin and osteoclast differentiation signaling pathways play crucial roles. These findings may provide valuable references for developing new therapies for pulmonary fibrosis.

Effectiveness of a novel rat model of off-target PLA2R1 knockout to renal impairment.

Phospholipase A2 receptor 1 (PLA2R1) plays a crucial role in various diseases, including membranous nephropathy. However, the precise implications of PLA2R1 deficiency remain poorly understood. In this study, we created PLA2R1 knockout rats to explore potential consequences resulting from the loss of the PLA2R1 gene. Unexpectedly, our PLA2R1 knockout rats exhibited symptoms resembling those of chronic kidney disease after an 8-week observation period. Notably, several rats developed persistent proteinuria, a hallmark of renal dysfunction. Immunohistochemical and immunofluorescence analyses revealed insignificant glomerular fibrosis, reduced podocyte count, and augmented glomerular expression of complement C3 (C3) compared to immunoglobin A (IgA) and immunoglobin G(IgG) in the rat model. These findings suggest that the loss of PLA2R1 may contribute to the pathogenesis of membranous nephropathy and related conditions. Our knockout rat model provides a valuable tool for investigating the underlying pathology of PLA2R1-associated diseases, and may facilitate the development of targeted therapies for membranous nephropathy and other related disorders.

CXCL16 promotes tumor metastasis by regulating angiogenesis in the tumor micro-environment of BRAF V600E mutant colorectal cancer.

Patients of colorectal cancer (CRC) with BRAF V600E mutation obtain poor prognosis. This study aimed to explore the role and mechanism of BRAF V600E mutation in angiogenesis of tumor micro-environment (TME). It has been reported that CXCL16 expression in TME is closely related to BRAF mutation. Clinicopathological features of CRC with BRAF V600E mutant or wild type were collected in this study. Immunohistochemistry (IHC) assays were conducted to test the expressions of vascular endothelial growth factor (VEGF), CD31 and CXCL16. ROC curve was used to determine the optimal cut off values of CXCL16. A total of 680 patients including 141 BRAF V600E type and 679 wild type were included. BRAF V600E mutant tumors were presented with significant worse clinicopathological features and a shorter overall survival (OS) than wild-type. Besides, chemokines CXCL16 was up-regulated in BRAF V600E mutant tissues and was associated with poorer prognosis. In addition, VEGF levels and vascular endothelial cell density was significantly increased in BRAF mutation. At last, CXCL16 was positively correlated with VEGF expression and vascular endothelial cell density. In conclusion, BRAF V600E mutations may promote metastasis of CRC by regulating CXCL16 expression and promoting angiogenesis in the TME.

Construction and application of a QSRR approach for identifying flavonoids.

A quantitative structure retention relationship (QSRR) method was developed to identify flavonoid isomers auxiliary using an ultra high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) method based on the linear relationships between the Ln(k') values of flavonoids and their hydrogen bonding energy (XAH) and dissolution energy (ES). Chromatographic separation was achieved with a Hypersil GOLD C18 (100 mm × 2.1 mm, 1.9 µm) column and Agilent SB-C18 (2.1 ×50 mm, 1.8 µm) column on a Dionex Ultimate 3000 RSLC chromatograph. Compounds were eluted isocratically using a mobile phase containing 0.1% formic acid/water solution and methanol at a ratio of 55:45 (v/v). Mass spectrometry was performed in the negative and positive ionization modes on a Thermo Fisher Q Exactive Orbitrap mass spectrometer equipped with an electrospray ionization interface. The established QSRR model was Ln(k') = 5.6163 + 0.0469ES - 0.0984XAH, with a determination coefficient (R2) of 0.9981, adjusted determination coefficient (adjR2) of 0.9976, and corrected root mean square error of 0.0682. The determination coefficient of the leave-one-out (LOO) cross-validation (Q2LOO) was 0.9976, and the cross-verification root mean square error was 0.0754. Simulated samples containing 7 flavonoids were used to validate the feasibility of the method. The classical method (UHPLC-MS/MS combined the CD software and the mzCloud, mzVault and Chemspider databases) was used to identify the seven flavonoids in the simulated samples. This classic identification strategy cannot provide accurate identification results, which provided multiple identification results for each compound in the simulated samples. On the basis of the results, the 7 flavonoids were accurately identified by the established QSRR model, and the reference standards were used to validate it. The relative error of retention time(RE(tR)) between the model calculation and experimental results was less than 10%. This method effectively complements and improves the classical methods, that UHPLC-MS/MS combined the CD software and the mass spectra databases were used to identify flavonoids identification.

ANGPTL3 negatively regulates IL-1ß-induced NF-κB activation by inhibiting the IL1R1-associated signaling complex assembly.

Interleukin-1ß (IL-1ß)-induced signaling is one of the most important pathways in regulating inflammation and immunity. The assembly of the receptor complex, consisting of the ligand IL-1ß, the IL-1 receptor (IL-1R) type 1 (IL1R1), and the IL-1R accessory protein (IL1RAP), initiates this signaling. However, how the IL1R1-associated complex is regulated remains elusive. Angiopoietin like 3 (ANGPTL3), a key inhibitor of plasma triglyceride clearance, is mainly expressed in the liver and exists in both intracellular and extracellular secreted forms. Presently, ANGPTL3 has emerged as a highly promising drug target for hypertriglyceridemia and associated cardiovascular diseases. However, most studies have focused on the secreted form of ANGPTL3, while its intracellular role is still largely unknown. Here, we report that intracellular ANGPTL3 acts as a negative regulator of IL-1ß-triggered signaling. Overexpression of ANGPTL3 inhibited IL-1ß-induced NF-κB activation and the transcription of inflammatory genes in HepG2, THP1, and HEK293T cells, while knockdown or knockout of ANGPTL3 resulted in opposite effects. Mechanistically, ANGPTL3 interacted with IL1R1 and IL1RAP through its intracellular C-terminal fibrinogen-like domain (FLD) and disrupted the assembly of the IL1R1-associated complex. Taken together, our study reveals a novel role for ANGPTL3 in inflammation, whereby it inhibits the physiological interaction between IL1R1 and IL1RAP to maintain immune tolerance and homeostasis in the liver.

Impact of ambient temperature on adverse pregnancy outcomes: a birth cohort study in Fuzhou, China.

Background: Previous studies have identified a series of specific adverse pregnancy outcomes (APOs) linked with temperature extremes. Most of them focus on preterm birth, low birth weight, and stillbirth. Other possible adverse outcomes were under-researched. This study aimed to investigate the impact of ambient temperature on maternal complications, white blood cell count (WBC), newborn hearing, and neonatal jaundice. Methods: A total of 418 participants were recruited from Fuzhou Maternity & Child Healthcare Hospital in 2016. Participants were invited to fill out a structured questionnaire. The gridded near-surface air temperatures at a resolution of 0.1°* 0.1° for Fuzhou were extracted from a published dataset. Meteorological data and PM2.5 were extracted based on participants' residential addresses using R packages "ncdf4" and "raster." Multivariate logistic regression models were used to quantify the effects of ambient temperature on APOs after controlling for confounders. Results: Overall, there were 107 APOs, accounting for 25.6% of all participants. Every 1°C increase in mean temperature was associated with a 10.0% increase in APOs (aOR = 1.100, 95%CI 1.006-1.203) during the period of early pregnancy. However, negative associations were observed in the middle pregnancy period, and a 1°C increase in mean temperature was associated 8.8% decrease in APOs (aOR = 0.912, 95%CI 0.846-0.982). Diurnal temperature variation had a significant impact on APOs in the third trimester. Infant jaundice was negatively associated with temperature exposure in the middle and late pregnancy periods. The risk of neonatal jaundice increased at lag weeks 2-9 in the first trimester, with the greatest lagged effect (aOR = 1.201, 95%CI 1.020-1.413) observed at lag week 3. A 1°C increase in mean temperature led to a 29.6% (aOR = 1.296, 95%CI 1.019-1.649) increase in high WBC. A 1°C increase in temperature variation was associated with more than two times (aOR = 2.469, 95%CI 1.001-6.089) increase of high WBC in the first trimester and about five times (aOR = 4.724, 95%CI 1.548-14.409) increase in the third trimester. Conclusion: Ambient temperature affects neonatal jaundice, newborn hearing loss, and infections during pregnancy. In addition to the identified epidemiologic link and susceptible exposure windows, there is a need to understand the underlying biological mechanisms for better recommendations for climate change adaptation policies.

Metagenomic Analysis of Intratumoral Microbiome Linking to Response to Neoadjuvant Chemoradiotherapy in Rectal Cancer.

PURPOSE: To assess taxonomic and functional characteristics of tumor-bearing microbiota and its association with response to neoadjuvant chemoradiation therapy (nCRT) in patients with locally advanced rectal cancer. METHODS AND MATERIALS: We performed metagenomic sequencing of biopsy tumoral tissues from 73 patients with locally advanced rectal cancer before nCRT. Patients were classified into poor responders (PR) and good responders (GR) according to response to nCRT. Subsequent investigation of network alteration, key community, microbial biomarkers, and function related to nCRT responses were carried out. RESULTS: The network-driven analysis systematically revealed 2 co-occurring bacteria modules that exhibited opposite relationship with rectal cancer radiosensitivity. In the 2 modules, prominent alteration of global graph properties and community structure was observed between networks of PR and GR group. By quantifying changes in between-group association patterns and abundances, a total of 115 discriminative biomarker species linked to nCRT response were found, and 35 microbial variables were selected to establish the optimal randomForest classifier for nCRT response prediction. It yielded an area under the curve value of 85.5% (95% CI, 73.3%-97.8%) in the training cohort and 88.4% (95% CI, 77.5%-99.4%) in the validation cohort. In a comprehensive consideration, 5 key bacteria showed high relevance with inducing resistance to nCRT, including Streptococcus equinus, Schaalia odontolytica, Clostridium hylemonae, Blautia producta, and Pseudomonas azotoformans. One key hub including several butyrate-formation bacteria involving with driving network alteration from GR to PR indicate that microbiota-derived butyrate may also be involved in reducing the antitumor effects of nCRT, especially Coprococcus. The functional analysis of metagenome linked the nitrate and sulfate-sulfur assimilation, histidine catabolic process, and resistance to cephamycin to the reduced therapeutic response. It also linked to leucine degradation, isoleucine biosynthesis, taurine, and hypotaurine metabolism to the improved response to nCRT. CONCLUSIONS: Our data offer novel potential microbial factors and shared metagenome function linked to resistance to nCRT.

Construction of highly-stable covalent organic framework with combined enol-imine and keto-enamine linkages.

A novel covalent organic framework (COF) (Tp-BI-COF) with combined ketimine-type enol-imine and keto-enamine linkages was prepared through a cascade of ketimine condensation followed by aldimine condensation and characterized by XRD, solid state 13C NMR, IR, TGA and BET. Tp-BI-COF showed high stability toward acid, organic solvent, and boiling water. The 2D COF exhibited photochromic properties after being irradiated with a xenon lamp. The stable COF, with aligned one-dimensional nanochannels, provided nitrogen sites on pore walls, which confine and stabilize the H3PO4 in the channel via hydrogen-bonding interactions. After loading with H3PO4, the material showed excellent anhydrous proton conductivity.

Using a stacked ensemble learning framework to predict modulators of protein-protein interactions.

Identifying small molecule protein-protein interaction modulators (PPIMs) is a highly promising and meaningful research direction for drug discovery, cancer treatment, and other fields. In this study, we developed a stacking ensemble computational framework, SELPPI, based on a genetic algorithm and tree-based machine learning method for effectively predicting new modulators targeting protein-protein interactions. More specifically, extremely randomized trees (ExtraTrees), adaptive boosting (AdaBoost), random forest (RF), cascade forest, light gradient boosting machine (LightGBM), and extreme gradient boosting (XGBoost) were used as basic learners. Seven types of chemical descriptors were taken as the input characteristic parameters. Primary predictions were obtained with each basic learner-descriptor pair. Then, the 6 methods mentioned above were used as meta learners and trained on the primary prediction in turn. The most efficient method was utilized as the meta learner. Finally, the genetic algorithm was used to select the optimal primary prediction output as the input of the meta learner for secondary prediction to obtain the final result. We systematically evaluated our model on the pdCSM-PPI datasets. To our knowledge, our model outperformed all existing models, which demonstrates its great power.

Epidemiological characteristics of overseas imported COVID-19 cases into China: A scoping literature review.

Previous studies investigating the characteristics of imported cases were mostly limited to a certain province/city or a specific sub-group during a certain period with a small sample size, which may not provide an overall picture of the characteristics of imported cases. In this scoping literature review, we comprehensively synthesized the epidemiological characteristics of overseas imported COVID-19 cases into China by retrieving six literature databases, with aims to provide implications for more targeted control, prevention, and medical treatment of this disease. After dropping duplicates and reviewing titles, abstracts, and full-texts, 50 articles were included in the review finally, including 26 (52%) articles in English and 24 (48%) articles in Chinese. According to the type of data sources, the 50 studies were divided into three categories: 13 (26%) articles using data sourced from the Chinese Infectious Diseases Online Reporting System, 15 (30%) articles using data from the websites of national/local health departments, and 22 (44%) articles using hospital admission data. Most of the overseas imported COVID-19 cases were young and middle-aged Chinese students and businessmen returning from the United States, Europe, and some neighboring countries. Airport routine health screening measures could not identify COVID-cases effectively, although scheduled multiple nucleic acid tests were required before boarding. Almost all imported cases were identified during the hotel quarantine period. Although a large proportion of imported cases were asymptomatic or with mild symptoms in the published literature, they may be due to participant selection bias. The exact proportion of asymptomatic cases may need to be further investigated especially through population-based large-scale studies.

Variation and development of the turtle chondrocranium, with a description of the common musk turtle (Sternotherus odoratus, Kinosternidae, Cryptodira, Testudines).

Based on histological cross-sections, the chondrocranium of the common musk turtle (Sternotherus odoratus) was reconstructed, described, and compared with other turtles. It differs from that of other turtle chondrocrania by possessing elongated, slightly dorsally orientated nasal capsules with three dorsolateral foramina, which might be homologous to the foramen epiphaniale, and by having an enlarged crista parotica. Additionally, the posterior part of the palatoquadrate is more elongated and more slender than in other turtles, while its ascending process is connected to the otic capsule by appositional bone. The proportions of the chondrocranium were also compared with those of "mature" chondrocrania of other turtle species in a Principal Component Analysis (PCA). Other than expected, the S. odoratus chondrocranium is not similar in proportions to those of chelydrids, the closest related species in the sample. The results indicate to differences in the proportions among larger turtle clades (e.g., Durocryptodira, Pleurodira, and Trionychia). S. odoratus is an exception to this pattern since it shows elongated nasal capsules similar to the trionychid Pelodiscus sinensis. A second PCA comparing the chondrocranial proportions of multiple developmental "stages" mostly shows differences between trionychids and all other turtles. S. odoratus is again similar to trionychids along PC1, but its proportions are the most similar along PC2 and PC3 to older "stages" of americhelydians, including the chelydrid Chelydra serpentina, which is related to chondrocranium height and quadrate width. We discuss potential ecological correlations of our findings mirrored in late embryonic stages.

Co-infection of tick-borne bacterial pathogens in ticks in Inner Mongolia, China.

Tick-borne infectious diseases pose a serious health threat in certain regions of the world. Emerging infectious diseases caused by novel tick-borne pathogens have been reported that are causing particular concern. Several tick-borne diseases often coexist in the same foci, and a single vector tick can transmit two or more pathogens at the same time, which greatly increases the probability of co-infection in host animals and humans and can lead to an epidemic of tick-borne disease. The lack of epidemiological data and information on the specific clinical symptoms related to co-infection with tick-borne pathogens means that it is not currently possible to accurately and rapidly distinguish between a single pathogen infection and co-infection with multiple pathogens, which can have serious consequences. Inner Mongolia in the north of China is endemic for tick-borne infectious diseases, especially in the eastern forest region. Previous studies have found that more than 10% of co-infections were in host-seeking ticks. However, the lack of data on the specific types of co-infection with pathogens makes clinical treatment difficult. In our study, we present data on the co-infection types and the differences in co-infection among different ecological regions through genetic analysis of tick samples collected throughout Inner Mongolia. Our findings may aid clinicians in the diagnosis of concomitant tick-borne infectious diseases.

T-cell infiltration in the central nervous system and their association with brain calcification in Slc20a2-deficient mice.

Primary familial brain calcification (PFBC) is a rare neurodegenerative and neuropsychiatric disorder characterized by bilateral symmetric intracranial calcification along the microvessels or inside neuronal cells in the basal ganglia, thalamus, and cerebellum. Slc20a2 homozygous (HO) knockout mice are the most commonly used model to simulate the brain calcification phenotype observed in human patients. However, the cellular and molecular mechanisms related to brain calcification, particularly at the early stage much prior to the emergence of brain calcification, remain largely unknown. In this study, we quantified the central nervous system (CNS)-infiltrating T-cells of different age groups of Slc20a2-HO and matched wild type mice and found CD45+CD3+ T-cells to be significantly increased in the brain parenchyma, even in the pre-calcification stage of 1-month-old -HO mice. The accumulation of the CD3+ T-cells appeared to be associated with the severity of brain calcification. Further immunophenotyping revealed that the two main subtypes that had increased in the brain were CD3+ CD4- CD8- and CD3+ CD4+ T-cells. The expression of endothelial cell (EC) adhesion molecules increased, while that of tight and adherents junction proteins decreased, providing the molecular precondition for T-cell recruitment to ECs and paracellular migration into the brain. The fusion of lymphocytes and EC membranes and transcellular migration of CD3-related gold particles were captured, suggesting enhancement of transcytosis in the brain ECs. Exogenous fluorescent tracers and endogenous IgG and albumin leakage also revealed an impairment of transcellular pathway in the ECs. FTY720 significantly alleviated brain calcification, probably by reducing T-cell infiltration, modulating neuroinflammation and ossification process, and enhancing the autophagy and phagocytosis of CNS-resident immune cells. This study clearly demonstrated CNS-infiltrating T-cells to be associated with the progression of brain calcification. Impairment of blood-brain barrier (BBB) permeability, which was closely related to T-cell invasion into the CNS, could be explained by the BBB alterations of an increase in the paracellular and transcellular pathways of brain ECs. FTY720 was found to be a potential drug to protect patients from PFBC-related lesions in the future.