Discovery and genetic characterization of novel paramyxoviruses from small mammals in Hubei Province, Central China.

Paramyxoviruses are a group of single-stranded, negative-sense RNA viruses, some of which are responsible for acute human disease, including parainfluenza virus, measles virus, Nipah virus and Hendra virus. In recent years, a large number of novel paramyxoviruses, particularly members of the genus Jeilongvirus, have been discovered in wild mammals, suggesting that the diversity of paramyxoviruses may be underestimated. Here we used hemi-nested reverse transcription PCR to obtain 190 paramyxovirus sequences from 969 small mammals in Hubei Province, Central China. These newly identified paramyxoviruses were classified into four clades: genera Jeilongvirus, Morbillivirus, Henipavirus and Narmovirus, with most of them belonging to the genus Jeilongvirus. Using Illumina sequencing and Sanger sequencing, we successfully recovered six near-full-length genomes with different genomic organizations, revealing the more complex genome content of paramyxoviruses. Co-divergence analysis of jeilongviruses and their known hosts indicates that host-switching occurred more frequently in the evolutionary histories of the genus Jeilongvirus. Together, our findings demonstrate the high prevalence of paramyxoviruses in small mammals, especially jeilongviruses, and highlight the diversity of paramyxoviruses and their genome content, as well as the evolution of jeilongviruses.

BPI-GNN: Interpretable brain network-based psychiatric diagnosis and subtyping.

Converging evidence increasingly suggests that psychiatric disorders, such as major depressive disorder (MDD) and autism spectrum disorder (ASD), are not unitary diseases, but rather heterogeneous syndromes that involve diverse, co-occurring symptoms and divergent responses to treatment. This clinical heterogeneity has hindered the progress of precision diagnosis and treatment effectiveness in psychiatric disorders. In this study, we propose BPI-GNN, a new interpretable graph neural network (GNN) framework for analyzing functional magnetic resonance images (fMRI), by leveraging the famed prototype learning. In addition, we introduce a novel generation process of prototype subgraph to discover essential edges of distinct prototypes and employ total correlation (TC) to ensure the independence of distinct prototype subgraph patterns. BPI-GNN can effectively discriminate psychiatric patients and healthy controls (HC), and identify biological meaningful subtypes of psychiatric disorders. We evaluate the performance of BPI-GNN against 11 popular brain network classification methods on three psychiatric datasets and observe that our BPI-GNN always achieves the highest diagnosis accuracy. More importantly, we examine differences in clinical symptom profiles and gene expression profiles among identified subtypes and observe that our identified brain-based subtypes have the clinical relevance. It also discovers the subtype biomarkers that align with current neuro-scientific knowledge.

Thiol-Ene Click Reaction Modified Triazinyl-Based Covalent Organic Framework for Pb(II) Ion Effective Removal.

As a common water pollutant, Pb2+ has harmful effects on the nervous, hematopoietic, digestive, renal, cardiovascular, and endocrine systems. Due to the drawbacks of traditional adsorbents such as structural disorder, poor stability, and difficulty in introducing adsorption active sites, the adsorption capacity is low, and it is difficult to accurately study the adsorption mechanism. Herein, vinyl-functionalized covalent organic frameworks (COFs) were synthesized at room temperature, and sulfur-containing active groups were introduced by the click reaction. By precisely tuning the chemical structure of the sulfur-containing reactive groups through the click reaction, we found that the adsorption activity of the sulfhydryl group was higher than that of the sulfur atom in the thioether. Moreover, the incorporation of flexible linking groups was observed to enhance the adsorption activity at the active site. The maximum adsorption capacity of the postmodified COF TAVA-S-Et-SH for Pb(II) reached 303.0 mg/g, which is 2.9 times higher than that of the unmodified COF. This work not only demonstrates the remarkable potential of the "thiol-ene" click reaction for the customization of active adsorption sites but also demonstrates the remarkable potential of the "thiol-alkene" click reaction to explore the structure-effect relationship between the active adsorption sites and the metal ion adsorption capacity.

The clinical outcome of COVID-19 is strongly associated with microbiome dynamics in the upper respiratory tract.

OBJECTIVES: The respiratory tract is the portal of entry for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Although a variety of respiratory pathogens other than SARS-CoV-2 have been associated with severe cases of COVID-19 disease, the dynamics of the upper respiratory microbiota during disease the course of disease, and how they impact disease manifestation, remain uncertain. METHODS: We collected 349 longitudinal upper respiratory samples from a cohort of 65 COVID-19 patients (cohort 1), 28 samples from 28 recovered COVID-19 patients (cohort 2), and 59 samples from 59 healthy controls (cohort 3). All COVID-19 patients originated from the earliest stage of the epidemic in Wuhan. Based on a modified clinical scale, the disease course was divided into five clinical disease phases (pseudotimes): "Healthy" (pseudotime 0), "Incremental" (pseudotime 1), "Critical" (pseudotime 2), "Complicated" (pseudotime 3), "Convalescent" (pseudotime 4), and "Long-term follow-up" (pseudotime 5). Using meta-transcriptomics, we investigated the features and dynamics of transcriptionally active microbes in the upper respiratory tract (URT) over the course of COVID-19 disease, as well as its association with disease progression and clinical outcomes. RESULTS: Our results revealed that the URT microbiome exhibits substantial heterogeneity during disease course. Two clusters of microbial communities characterized by low alpha diversity and enrichment for multiple pathogens or potential pathobionts (including Acinetobacter and Candida) were associated with disease progression and a worse clinical outcome. We also identified a series of microbial indicators that classified disease progression into more severe stages. Longitudinal analysis revealed that although the microbiome exhibited complex and changing patterns during COVID-19, a restoration of URT microbiomes from early dysbiosis toward more diverse status in later disease stages was observed in most patients. In addition, a group of potential pathobionts were strongly associated with the concentration of inflammatory indicators and mortality. CONCLUSION: This study revealed strong links between URT microbiome dynamics and disease progression and clinical outcomes in COVID-19, implying that the treatment of severe disease should consider the full spectrum of microbial pathogens present.

A prospective study of nanopore-targeted sequencing in the diagnosis of central nervous system infections.

Central nervous system (CNS) infections are a leading cause of death in patients. Nanopore-targeted sequencing (NTS) has begun to be used for pathogenic microbial detection. This study aims to evaluate the ability of NTS in the detection of pathogens in cerebrospinal fluid (CSF) through a prospective study. Fifty CSF specimens collected from 50 patients with suspected CNS infections went through three methods including NTS, metagenomic next-generation sequencing (mNGS), and microbial culture in parallel. When there was an inconsistency between NTS results and the results of the mNGS, the 16S rDNA gene was amplified followed by Sanger sequencing to further verify pathogens detected by NTS. Among 50 CSF specimens, 76% were NTS-positive, which is lower than mNGS (94.0%), yet higher than microbial culture (16.0%). The overall validation rate, diagnostic accordance rate (DAR), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of NTS were 86.7%, 50.0%, 71.0%, 15.8%, 57.9%, and 25.0%, respectively. In the CSF total nucleated cell (TNC) number ≤10 cells/µL, DAR, specificity, and PPV were 20%, 11.1%, and 11.1%, whereas in that with CSF TNC number >10 cells/µL, DAR, sensitivity, specificity, PPV, and NPV were 57.5%, 70.0%, 20.0%, 72.4%, and 18.2%, respectively. Although NTS has a higher microbial detection rate than microbial culture, it should combine CSF TNC result to evaluate the value of NTS for the diagnosis of CNS infections. IMPORTANCE: This study aims to prospectively evaluate the ability of nanopore-targeted sequencing (NTS) in the detection of pathogens in cerebrospinal fluid (CSF). It was the first time combining mNGS and microbial culture to verify the NTS-positive results also using 16S rDNA amplification with Sanger sequencing. Although microbial culture was thought to be the gold standard for pathogens detection and diagnosis of infectious diseases, this study suggested that microbial culture of CSF is not the most appropriate way for diagnosing central nervous system (CNS) infection. NTS should be recommended to be used in CSF for diagnosing CNS infection. When evaluating the value of NTS for diagnosis of CNS infections, the results of CSF TNC should be combined, and NTS-positive result is observed to be more reliable in patients with CSF TNC level >10 cells/µL.

Diversity and genetic characterization of orthohantavirus from small mammals and humans during 2012-2022 in Hubei Province, Central China.

Hemorrhagic fever with renal syndrome (HFRS) is a significant public health problem in Hubei Province, China, where a novel strain of orthohantavirus, HV004, was reported in 2012. However, no systematic study has investigated the prevalence and variation of orthohantavirus in rodents and humans. Herein, 2137 small mammals were collected from ten HFRS epidemic areas in Hubei Province from 2012 to 2022, and 143 serum samples from patients with suspected hemorrhagic fever were collected from two hospitals from 2017 to 2021. Orthohantavirus RNA was recovered from 134 lung tissue samples from five rodent species, with a 6.27 % prevalence, and orthohantavirus was detected in serum samples from 25 patients. Genetic analyses revealed that orthohantavirus hantanense (HTNV), orthohantavirus seoulense (SEOV), and orthohantavirus dabieshanense (DBSV) are co-circulating in rodents in Hubei, and HTNV and SEOV were identified in patient serum. Phylogenetic analysis showed that most of the HTNV sequences were clustered with HV004, indicating that HV004-like orthohantavirus was the main HNTV subtype in rodents. Two genetic reassortments and six recombination events were observed in Hubei orthohantaviruses. In summary, this study identified the diversity of orthohantaviruses circulating in Hubei over the past decade, with the HV004-like subtype being the main genotype in rodents and patients. These findings highlight the need for continued attention and focus on orthohantaviruses, especially concerning newly identified strains.

Pathogenicity of novel hantavirus isolate and antigenicity and immunogenicity of novel strain-based inactivated vaccine.

BACKGROUND: Hantaan virus (HTNV, Orthohantavirus hantanensae species, Hantaviridae family) is the main etiological agent responsible for hemorrhagic fever with renal syndrome (HFRS). The novel HTNV may pose a potential danger to the control and prevention of HFRS in China, which highlights the importance of vaccine development in public health management. In previous studies, our laboratory discovered and successfully isolated a new HTNV strain, HV004 strain, from Apodemus agrarius captured in an epidemic area in Hubei, China. METHODS: An initial biological and pathogenicity characterization of HTNV 76-118 (standard train), HV114 strain (a clinical isolate from Hubei province in 1986), and the novel isolate HV004 strain from the epidemic areas of Hubei province were performed in susceptible cells and in vivo. An experimental HV004 strain inactivated vaccine was prepared, and its corresponding immunogenicity was analyzed in BALB/c mice. RESULTS: HV004 strain had a similar but higher pathogenicity than HTNV 76-118 and HV114 in suckling mice. A subcutaneous vaccination (s.c.) with the inactivated HTNV vaccine adjuvanted with aluminum, followed by a challenge intraperitoneally with 106 FFU/ml HTNV, afforded full protection against an HTNV challenge. All immunized mice in every group elicited serum neutralizing antibodies with increasing dosages, which may protect mice from HTNV infection. A dose-dependent stimulation index of splenocytes was also observed in immunized mice. The percentage of IFN-γ-producing CD3+CD8+ T cells was significantly higher in the spleens of immunized mice than in those of control mice. CONCLUSIONS: These findings suggest that the inactivated HTNV vaccine may stimulate mice to produce high levels of antibodies with neutralization activity and elicit specific anti-HTNV humoral and cellular immune responses in BALB/c mice against the prevalent strain of HTNV in south central China.

Extensive genetic diversity of severe fever with thrombocytopenia syndrome virus circulating in Hubei Province, China, 2018-2022.

Severe fever with thrombocytopenia syndrome virus (SFTSV), an etiological agent causing febrile human disease was identified as an emerging tick-borne bunyavirus. The clinical disease characteristics and case fatality rates of SFTSV may vary across distinct regions and among different variant genotypes. From 2018 to 2022, we surveyed and recruited 202 severe fever with thrombocytopenia syndrome (SFTS) patients in Hubei Province, a high-incidence area of the epidemic, and conducted timely and systematic research on the disease characteristics, SFTSV diversity, and the correlation between virus genome variation and clinical diseases. Our study identified at least 6 genotypes of SFTSV prevalent in Hubei Province based on the analysis of the S, M, and L genome sequences of 88 virus strains. Strikingly, the dominant genotype of SFTSV was found to change during the years, indicating a dynamic shift in viral genetic diversity in the region. Phylogenetic analysis revealed the genetic exchange of Hubei SFTSV strains was relatively frequent, including 3 reassortment strains and 8 recombination strains. Despite the limited sample size, SFTSV C1 genotype may be associated with higher mortality compared to the other four genotypes, and the serum amyloid A (SAA) level, an inflammatory biomarker, was significantly elevated in these patients. Overall, our data summarize the disease characteristics of SFTSV in Hubei Province, highlight the profound changes in viral genetic diversity, and indicate the need for in-depth monitoring and exploration of the relationship between viral mutations and disease severity.

Analysis of Lung Microbiome in COVID-19 Patients during Time of Hospitalization.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the pathogenic agent of the rapidly spreading pneumonia called coronavirus disease 2019 (COVID-19), primarily infects the respiratory and digestive tract. Several studies have indicated the alterations of the bacterial microbiome in the lower respiratory tract during viral infection. However, both bacterial and fungal microbiota in the lung of COVID-19 patients remained to be explored. METHODS: In this study, we conducted nanopore sequencing analyses of the lower respiratory tract samples from 38 COVID-19 patients and 26 non-COVID-19 pneumonia controls. Both bacterial and fungal microbiome diversities and microbiota abundances in the lung were compared. RESULTS: Our results revealed significant differences in lung microbiome between COVID-19 patients and non-COVID-19 controls, which were strongly associated with SARS-CoV-2 infection and clinical status. COVID-19 patients exhibited a notably higher abundance of opportunistic pathogens, particularly Acinetobacter baumannii and Candida spp. Furthermore, the potential pathogens enriched in COVID-19 patients were positively correlated with inflammation indicators. CONCLUSIONS: Our study highlights the differences in lung microbiome diversity and composition between COVID-19 patients and non-COVID-19 patients. This may contribute to predicting co-pathogens and selecting optimal treatments for respiratory infections caused by SARS-CoV-2.

Salt-Assisted Fabrication of a Water-Based Covalent Organic Framework Ink and Its Hybrid Films for Photothermal Actuators.

The exceptional properties of two-dimensional covalent organic framework materials (2D-COFs), including their large π-conjugated structure at the molecular level and π-π multilayer stacking, have attracted interest for soft photothermal actuator applications. However, the conventional synthesis of COFs as microcrystalline powders limits their processing in water due to their limited dispersibility. Herein, we present a simple and environmentally friendly method to fabricate water-suspended COF inks by adjusting the surface potential of COF powders through adsorption of ionic species such as Na+ and Cl-. This technique effectively prevents the accumulation and aggregation of COF powder, resulting in an aqueous COF ink that can be easily cast into homogeneous hybrid COF films by Mayer-rod coating. In addition, the resulting photothermal actuator exhibited a fast response time within 3 s at a curvature of 2.35 cm-1 in the near-infrared light. This facile and practical approach to fabricating water-based COFs ink represents a promising strategy for the development of practical applications of COFs in photothermal actuators.

An integrated finite element method and machine learning algorithm for brain morphology prediction.

The human brain development experiences a complex evolving cortical folding from a smooth surface to a convoluted ensemble of folds. Computational modeling of brain development has played an essential role in better understanding the process of cortical folding, but still leaves many questions to be answered. A major challenge faced by computational models is how to create massive brain developmental simulations with affordable computational sources to complement neuroimaging data and provide reliable predictions for brain folding. In this study, we leveraged the power of machine learning in data augmentation and prediction to develop a machine-learning-based finite element surrogate model to expedite brain computational simulations, predict brain folding morphology, and explore the underlying folding mechanism. To do so, massive finite element method (FEM) mechanical models were run to simulate brain development using the predefined brain patch growth models with adjustable surface curvature. Then, a GAN-based machine learning model was trained and validated with these produced computational data to predict brain folding morphology given a predefined initial configuration. The results indicate that the machine learning models can predict the complex morphology of folding patterns, including 3-hinge gyral folds. The close agreement between the folding patterns observed in FEM results and those predicted by machine learning models validate the feasibility of the proposed approach, offering a promising avenue to predict the brain development with given fetal brain configurations.

Incidence of Orthohantavirus infection in humans follows observed changes in rodent reservoirs, Hubei Province, China (1984-2010).

OBJECTIVE: Orthohantaviruses (genus Orthohantavirus, family Hantaviridae of order Bunyavirales) are rodent-borne viruses causing 2 human diseases: hemorrhagic fever with renal syndrome (HFRS) and hantavirus pulmonary syndrome (HPS), which are mainly prevalent in Eurasia and the Americas, respectively. We initiated this study to investigate and analyze the Orthohantaviruses infection in rodent reservoirs and humans in the Hubei Province of China from 1984 to 2010. SAMPLE: The study included 10,314 mouse and 43,753 human serum samples. PROCEDURES: In this study, we analyzed the incidence of Orthohantavirus infection in humans and observed changes in rodent reservoirs in Hubei Province. RESULTS: The results indicated that although the incidence of HFRS declined from the 1990s, the human inapparent infection did not decrease dramatically. Although elements of the disease ecology have changed over the study period, Apodemus agrarius and Rattus norvegicus remain the major species and a constituent ratio of Rattus norvegicus increased. Rodent population density fluctuated between 16.65% and 2.14%, and decreased quinquennially, showing an obvious downward trend in recent years. The average orthohantaviruses-carrying rate was 6.36%, of which the lowest rate was 2.92% from 2006 to 2010. The analysis of rodent species composition showed that Rattus norvegicus and Apodemus agrarius were the dominant species over time (68.6% [1984 to 1987] and 90.4% [2000 to 2011]), while the composition and variety of other species decreased. The density of rodents was closely related to the incidence of HFRS (r = 0.910, P = .032). CLINICAL RELEVANCE: Our long-term investigation demonstrated that the occurrence of HFRS is closely related to rodent demographic patterns. Therefore, rodent monitoring and rodent control measures for prevention against HFRS in Hubei are warranted.

Four-dimensional mapping of dynamic longitudinal brain subcortical development and early learning functions in infants.

Brain subcortical structures are paramount in many cognitive functions and their aberrations during infancy are predisposed to various neurodevelopmental and neuropsychiatric disorders, making it highly essential to characterize the early subcortical normative growth patterns. This study investigates the volumetric development and surface area expansion of six subcortical structures and their associations with Mullen scales of early learning by leveraging 513 high-resolution longitudinal MRI scans within the first two postnatal years. Results show that (1) each subcortical structure (except for the amygdala with an approximately linear increase) undergoes rapid nonlinear volumetric growth after birth, which slows down at a structure-specific age with bilaterally similar developmental patterns; (2) Subcortical local area expansion reveals structure-specific and spatiotemporally heterogeneous patterns; (3) Positive associations between thalamus and both receptive and expressive languages and between caudate and putamen and fine motor are revealed. This study advances our understanding of the dynamic early subcortical developmental patterns.

In situgrowth strategy to construct perovskite quantum dot@covalent organic framework composites with enhanced water stability.

Metal halide perovskite quantum dots (QDs) have excellent optoelectronic properties; however, their poor stability under water or thermal conditions remains an obstacle to commercialization. Here, we used a carboxyl functional group (-COOH) to enhance the ability of a covalent organic framework (COF) to adsorb lead ions and grow CH3NH3PbBr3(MAPbBr3) QDsin situinto a mesoporous carboxyl-functionalized COF to construct MAPbBr3QDs@COF core-shell-like composites to improve the stability of perovskites. Owing to the protection of the COF, the as-prepared composites exhibited enhanced water stability, and the characteristic fluorescence was maintained for more than 15 d. These MAPbBr3QDs@COF composites can be used to fabricate white light-emitting diodes with a color comparable to natural white emission. This work demonstrates the importance of functional groups for thein situgrowth of perovskite QDs, and coating with a porous structure is an effective way to improve the stability of metal halide perovskites.

iBEAT V2.0: a multisite-applicable, deep learning-based pipeline for infant cerebral cortical surface reconstruction.

The human cerebral cortex undergoes dramatic and critical development during early postnatal stages. Benefiting from advances in neuroimaging, many infant brain magnetic resonance imaging (MRI) datasets have been collected from multiple imaging sites with different scanners and imaging protocols for the investigation of normal and abnormal early brain development. However, it is extremely challenging to precisely process and quantify infant brain development with these multisite imaging data because infant brain MRI scans exhibit (a) extremely low and dynamic tissue contrast caused by ongoing myelination and maturation and (b) inter-site data heterogeneity resulting from the use of diverse imaging protocols/scanners. Consequently, existing computational tools and pipelines typically perform poorly on infant MRI data. To address these challenges, we propose a robust, multisite-applicable, infant-tailored computational pipeline that leverages powerful deep learning techniques. The main functionality of the proposed pipeline includes preprocessing, brain skull stripping, tissue segmentation, topology correction, cortical surface reconstruction and measurement. Our pipeline can handle both T1w and T2w structural infant brain MR images well in a wide age range (from birth to 6 years of age) and is effective for different imaging protocols/scanners, despite being trained only on the data from the Baby Connectome Project. Extensive comparisons with existing methods on multisite, multimodal and multi-age datasets demonstrate superior effectiveness, accuracy and robustness of our pipeline. We have maintained a website, iBEAT Cloud, for users to process their images with our pipeline ( http://www.ibeat.cloud ), which has successfully processed over 16,000 infant MRI scans from more than 100 institutions with various imaging protocols/scanners.

Longitudinal development of the cerebellum in human infants during the first 800 days.

Revealing early dynamic development of the normative cerebellar structures contributes to exploring cerebellum-related neurodevelopmental disorders. Here, leveraging infant-tailored cerebellar image processing techniques, we studied the dynamic volumetric developmental trajectories of cerebellum and 27 cerebellar sub-regions and their relationships with behavioral scores based on 511 high-resolution structural MRI scans during the first 800 postnatal days. The ratio of the entire cerebellum to the intracranial volume increases rapidly at first and then peaks at 13 months after birth. Both the absolute and relative volumes of most cerebellar sub-structures exhibit rapid increase at first, then the relative volumes decrease slightly after arriving at peaks (except for X lobules). Each lobule depicts larger absolute volume in males than in females. The within-subject variation of the cerebellar volumetric percentile score is generally stable. The volumetric development of several lobules (e.g., V, Crus I, and Crus II) has a significantly positive correlation with fine motor skills during the age range examined.

Metagenomic next-generation sequencing versus traditional laboratory methods for the diagnosis of central nervous system opportunistic infections in HIV-infected Chinese adults.

To evaluate clinical value of metagenomic next-generation sequencing (mNGS) in people living with HIV/AIDS (PLWHA) who had CNS disorders. Cerebrospinal fluid (CSF) samples from 48 PLWHA presenting with CNS disorders were sequenced using mNGS and compared with clinical conventional diagnostic methods. In total, 36/48 ss(75%) patients were diagnosed with pathogen(s) infection by mNGS, and the positive detection proportion by mNGS was higher than that by clinical conventional diagnostic methods (75% vs 52.1%, X2 = 5.441, P = 0.020). Thirteen out of 48 patients (27.1%) were detected with 3-7 pathogens by mNGS. Moreover, 77 pathogen strains were detected, of which 94.8% (73/77) by mNGS and 37.0% (30/77) by clinical conventional methods (X2 = 54.206, P < 0.001). The sensitivity and specificity of pathogens detection by mNGS were 63.9% (23/36) and 66.7% (8/12), respectively, which were superior to that by clinical conventional methods (23/36 vs 9/25, X2 = 4.601, P = 0.032; 8/12 vs 5/23, X2 = 5.029, P = 0.009). The application of mNGS was superior for its ability to detect a variety of unknown pathogens and multiple pathogens infection, and relatively higher sensitivity and specificity in diagnosis of CNS disorders in PLWHA.

An attention-based context-informed deep framework for infant brain subcortical segmentation.

Precise segmentation of subcortical structures from infant brain magnetic resonance (MR) images plays an essential role in studying early subcortical structural and functional developmental patterns and diagnosis of related brain disorders. However, due to the dynamic appearance changes, low tissue contrast, and tiny subcortical size in infant brain MR images, infant subcortical segmentation is a challenging task. In this paper, we propose a context-guided, attention-based, coarse-to-fine deep framework to precisely segment the infant subcortical structures. At the coarse stage, we aim to directly predict the signed distance maps (SDMs) from multi-modal intensity images, including T1w, T2w, and the ratio of T1w and T2w images, with an SDM-Unet, which can leverage the spatial context information, including the structural position information and the shape information of the target structure, to generate high-quality SDMs. At the fine stage, the predicted SDMs, which encode spatial-context information of each subcortical structure, are integrated with the multi-modal intensity images as the input to a multi-source and multi-path attention Unet (M2A-Unet) for achieving refined segmentation. Both the 3D spatial and channel attention blocks are added to guide the M2A-Unet to focus more on the important subregions and channels. We additionally incorporate the inner and outer subcortical boundaries as extra labels to help precisely estimate the ambiguous boundaries. We validate our method on an infant MR image dataset and on an unrelated neonatal MR image dataset. Compared to eleven state-of-the-art methods, the proposed framework consistently achieves higher segmentation accuracy in both qualitative and quantitative evaluations of infant MR images and also exhibits good generalizability in the neonatal dataset.

Ultrathin Covalent Organic Framework Nanosheets/Ti3C2Tx-Based Photoelectrochemical Biosensor for Efficient Detection of Prostate-Specific Antigen.

Designable and ultrathin covalent organic framework nanosheets (CONs) with good photoelectric activity are promising candidates for the construction of photoelectrochemical (PEC) biosensors for the detection of low-abundance biological substrates. However, achieving highly sensitive PEC properties by using emerging covalent organic framework nanosheets (CONs) remains a great challenge due to the polymeric nature and poor photoelectric activity of CONs. Herein, we report for the first time the preparation of novel composites and their PEC sensing properties by electrostatic self-assembly of ultrathin CONs (called TTPA-CONs) with Ti3C2Tx. The prepared TTPA-CONs/Ti3C2Tx composites can be used as photocathodes for PEC detection of prostate-specific antigen (PSA) with high sensitivity, low detection limit, and good stability. This work not only expands the application of CONs but also opens new avenues for the development of efficient PEC sensing platforms.

Transcriptome Analysis Explored the Differential Genes' Expression During the Development of the Stropharia rugosoannulata Fruiting Body.

Stropharia rugosoannulata (S. rugosoannulata) is a fungus with great edible and nutritional values; however, the development mechanism of its fruiting body has not been studied. Thus, this study aimed to analyze the differentially expressed genes (DEGs) in four stages; primordia stage (Sra1), young mushroom stage (Sra2), picking stage (Sra3), and opening umbrella stage (Sra4). Therefore, total RNA was extracted for further RNA-sequencing analysis. In three pairwise comparison groups (PCGs), Sra1 vs. Sra2, Sra2 vs. Sra3, and Sra3 vs. Sra4, a total of 3,112 DEGs were identified among the three PCGs. A GO analysis of the DEGs showed that there were 21 terms significantly enriched in Sra1 vs. Sra2 PCG. There was no significantly enriched GO term in the other two PCGs. Furthermore, KEGG pathway analysis showed that these DEGs were mainly enriched in glucose and amino acid metabolisms. Moreover we found that intron retention (IR) and the alternative 3' splice site (A3SS) accounted for more than 80%. The development of the S. rugosoannulata fruiting body mainly involved glucose and amino acid metabolisms. IR and A3SS were the two main types of ASE, which played an important role in the development and maturation of the S. rugosoannulata fruiting body.