Development of a Novel Prediction Tool for Response to First-Line Treatments of Monosymptomatic Nocturnal Enuresis-A Randomized, Controlled International Multicenter Study (DRYCHILD).

PURPOSE: Nocturnal urine volume and bladder reservoir function are key pathogenic factors behind monosymptomatic nocturnal enuresis (MNE). We investigated the predictive value of these together with other demographic and clinical variables for response to first-line treatments in children with MNE. MATERIALS AND METHODS: A randomized, controlled, international multicenter study was conducted in 324 treatment-naïve children (6-14 years) with primary MNE. The children were randomized to treatment with or without prior consideration of voiding diaries. In the group where treatment choice was based on voiding diaries, children with nocturnal polyuria and normal maximum voided volume (MVV) received desmopressin (dDAVP) treatment and children with reduced MVV and no nocturnal polyuria received an enuresis alarm. In the other group, treatment with dDAVP or alarm was randomly allocated. RESULTS: A total of 281 children (72% males) were qualified for statistical analysis. The change of responding to treatment was 21% higher in children where treatment was individualized compared to children where treatment was randomly selected (RR = 1.21 (1.02-1.45), P = .032). In children with reduced MVV and no nocturnal polyuria (35% of all children), individualized treatment was associated with a 46% improvement in response compared to random treatment selection (RR = 1.46 (1.14-1.87), P = .003). Furthermore, we developed a clinically relevant prediction model for response to dDAVP treatment (ROC 0.85). CONCLUSIONS: The present study demonstrates that treatment selection based on voiding diaries improve response to first line treatment, particularly in specific subtypes. Information from voiding diaries together with clinical and demographic information provides the basis for predicting response.

The pseudogene GBP1P1 suppresses influenza A virus replication by acting as a protein decoy for DHX9.

Recently, substantial evidence has demonstrated that pseudogene-derived long noncoding RNAs (lncRNAs) as regulatory RNAs have been implicated in basic physiological processes and disease development through multiple modes of functional interaction with DNA, RNA, and proteins. Here, we report an important role for GBP1P1, the pseudogene of guanylate-binding protein 1, in regulating influenza A virus (IAV) replication in A549 cells. GBP1P1 was dramatically upregulated after IAV infection, which is controlled by JAK/STAT signaling. Functionally, ectopic expression of GBP1P1 in A549 cells resulted in significant suppression of IAV replication. Conversely, silencing GBP1P1 facilitated IAV replication and virus production, suggesting that GBP1P1 is one of the interferon-inducible antiviral effectors. Mechanistically, GBP1P1 is localized in the cytoplasm and functions as a sponge to trap DHX9 (DExH-box helicase 9), which subsequently restricts IAV replication. Together, these studies demonstrate that GBP1P1 plays an important role in antagonizing IAV replication.IMPORTANCELong noncoding RNAs (lncRNAs) are extensively expressed in mammalian cells and play a crucial role as regulators in various biological processes. A growing body of evidence suggests that host-encoded lncRNAs are important regulators involved in host-virus interactions. Here, we define a novel function of GBP1P1 as a decoy to compete with viral mRNAs for DHX9 binding. We demonstrate that GBP1P1 induction by IAV is mediated by JAK/STAT activation. In addition, GBP1P1 has the ability to inhibit IAV replication. Importantly, we reveal that GBP1P1 acts as a decoy to bind and titrate DHX9 away from viral mRNAs, thereby attenuating virus production. This study provides new insight into the role of a previously uncharacterized GBP1P1, a pseudogene-derived lncRNA, in the host antiviral process and a further understanding of the complex GBP network.

A novel quantity assessment of landscape ecological risk using human-nature driving mechanism for sustainable society.

The rapid advancement of global economic integration and urbanization has severely damaged the stability of the ecological environment and hindered the ecological carbon sink capacity. In this study, we evaluated the spatiotemporal evolution pattern of landscape ecological risk (LER) in the Loess Plateau from 2010 to 2020. This was examined under the driving mechanism of human and natural dual factors. We combined the random forest algorithm with the Markov chain to jointly simulate and predict the development trend of LER in 2030. From 2010 to 2020, LER on the Loess Plateau showed a distribution pattern with higher values in the southeast and lower values in the northwest. Under the interaction of human and natural factors, annual precipitation exerted the strongest constraint on LER. The driving of land use and natural factors significantly influenced the spatial differentiation of the LER, with a q-value >0.30. In all three projected scenarios for 2030, there was an increase in construction land area and a significant reduction in cultivated land area. The urban development scenario showed the greatest expansion of high-risk areas, with a 5.29 % increase. Conversely, the ecological protection scenario showed a 1.53 % increase in high-risk areas. The findings have provided a reference for ecological risk prevention and control, and sustainable development of the ecological environment in arid regions.

Notable dysthymia: evolving trends of major depressive disorders and dysthymia in China from 1990 to 2019, and projections until 2030.

BACKGROUND: Depressive disorders have been identified as a significant contributor to non-fatal health loss in China. Among the various subtypes of depressive disorders, dysthymia is gaining attention due to its similarity in clinical severity and disability to major depressive disorders (MDD). However, national epidemiological data on the burden of disease and risk factors of MDD and dysthymia in China are scarce. METHODS: This study aimed to evaluate and compare the incidence, prevalence, and disability-adjusted life-years (DALYs) caused by MDD and dysthymia in China between 1990 and 2019. The temporal trends of the depressive disorder burden were evaluated using the average annual percentage change. The comparative risk assessment framework was used to estimate the proportion of DALYs attributed to risk factors, and a Bayesian age-period-cohort model was applied to project the burden of depressive disorders. RESULTS: From 1990 to 2019, the overall age-standardized estimates of dysthymia in China remained stable, while MDD showed a decreasing trend. Since 2006, the raw prevalence of dysthymia exceeded that of MDD for the first time, and increased alternately with MDD in recent years. Moreover, while the prevalence and burden of MDD decreased in younger age groups, it increased in the aged population. In contrast, the prevalence and burden of dysthymia remained stable across different ages. In females, 11.34% of the DALYs attributable to depressive disorders in 2019 in China were caused by intimate partner violence, which has increasingly become prominent among older women. From 2020 to 2030, the age-standardized incidence, prevalence, and DALYs of dysthymia in China are projected to remain stable, while MDD is expected to continue declining. CONCLUSIONS: To reduce the burden of depressive disorders in China, more attention and targeted strategies are needed for dysthymia. It's also urgent to control potential risk factors like intimate partner violence and develop intervention strategies for older women. These efforts are crucial for improving mental health outcomes in China.

The combined effects of polystyrene of different sizes and cadmium in mouse kidney tissues.

Environmental accumulation of nano- and microplastics pose serious risks to human health. Polystyrene (PS) is a polymer commonly used in the production of plastics. However, PS can adsorb cadmium (Cd), thereby influencing bioavailability and toxicity in vivo. Moreover, PS and Cd can accumulate in the mammalian kidney. Therefore, the aim of the present study was to assess the effects of combined exposure to PS and Cd in the kidney. Kidney damage was evaluated in male mice gavaged with PS (diameter, 100 nm and/or 1 µm) and Cd for 25 days.The results showed that PS at 100 nm caused more severe oxidative damage and cell apoptosis than PS at 1 µm. Combined exposure to PS at both 100 nm and 1 µm caused more severe kidney damage than the single administration groups. The extent of kidney toxicity caused by Cd differed with the combination of PS particles at 100 nm vs. 1 µm. The degree of damage to kidney function, pathological changes, and cell apoptosis induced by Cd+100 nm PS+1µm PS was the most severe. An increase in the Bax/Bcl2 ratio and overexpression of p53 and caspase-3 revealed that renal cell apoptosis might be induced via the mitochondrial pathway. Collectively, these findings demonstrate that the size of PS particles dictates the combined effects of PS and Cd in kidney tissues. Kidney damage caused by the combination of different sizes of PS particle and Cd is more complicated under actual environmental conditions.

Pseudospin-dependent acoustic topological edge and corner states in silica aerogel metamaterialsa).

Fueled by the concepts of topological insulators, analogous topological acoustics offer an alternative approach to manipulate sound. Theoretical proposals for subwavelength acoustic topological insulators are considered to be ideal effective parameters or utilizeing artificial coiling-space metamaterials. However, the corresponding realization using realistic soft metamaterials remains challenging. In this study, we present the design of an acoustic subwavelength second-order topological insulator using nanoscale porous solid material, silica aerogel, which supports pseudospin-dependent topological edge and corner states simultaneously. Through simulations and experiments, we demonstrate that silica aerogel can function as a soft acoustic metamaterial at the subwavelength scale. By embedding silica aerogel in an air matrix to construct a honeycomb lattice, a double Dirac cone is obtained. A topological phase transition is induced by expanding or contracting the supercell, resulting in band inversion. Additionally, we propose topologically robust acoustic transmission along the one-dimensional edge. Furthermore, we discover that the proposed sonic crystal sustains zero-dimensional corner states, which can efficiently confine energy at subwavelength corners. These findings offer potential for the realization of subwavelength topological acoustic devices using realistic soft metamaterials.

Aberrant individual structure covariance network in patients with mesial temporal lobe epilepsy.

Objective: Mesial temporal lobe epilepsy (mTLE) is a complex neurological disorder that has been recognized as a widespread global network disorder. The group-level structural covariance network (SCN) could reveal the structural connectivity disruption of the mTLE but could not reflect the heterogeneity at the individual level. Methods: This study adopted a recently proposed individual structural covariance network (IDSCN) method to clarify the alternated structural covariance connection mode in mTLE and to associate IDSCN features with the clinical manifestations and regional brain atrophy. Results: We found significant IDSCN abnormalities in the ipsilesional hippocampus, ipsilesional precentral gyrus, bilateral caudate, and putamen in mTLE patients than in healthy controls. Moreover, the IDSCNs of these areas were positively correlated with the gray matter atrophy rate. Finally, we identified several connectivities with weak associations with disease duration, frequency, and surgery outcome. Significance: Our research highlights the role of hippo-thalamic-basal-cortical circuits in the pathophysiologic process of disrupted whole-brain morphological covariance networks in mTLE, and builds a bridge between brain-wide covariance network changes and regional brain atrophy.

Microfluidic Biochips for Single-Cell Isolation and Single-Cell Analysis of Multiomics and Exosomes.

Single-cell multiomic and exosome analyses are potent tools in various fields, such as cancer research, immunology, neuroscience, microbiology, and drug development. They facilitate the in-depth exploration of biological systems, providing insights into disease mechanisms and aiding in treatment. Single-cell isolation, which is crucial for single-cell analysis, ensures reliable cell isolation and quality control for further downstream analyses. Microfluidic chips are small lightweight systems that facilitate efficient and high-throughput single-cell isolation and real-time single-cell analysis on- or off-chip. Therefore, most current single-cell isolation and analysis technologies are based on the single-cell microfluidic technology. This review offers comprehensive guidance to researchers across different fields on the selection of appropriate microfluidic chip technologies for single-cell isolation and analysis. This review describes the design principles, separation mechanisms, chip characteristics, and cellular effects of various microfluidic chips available for single-cell isolation. Moreover, this review highlights the implications of using this technology for subsequent analyses, including single-cell multiomic and exosome analyses. Finally, the current challenges and future prospects of microfluidic chip technology are outlined for multiplex single-cell isolation and multiomic and exosome analyses.

Low energy-consumption oriented membrane fouling control strategy in anaerobic fluidized membrane bioreactor.

Anaerobic fluidized membrane bioreactors (AFMBR) has attracted growing interest as an emerging wastewater treatment technology towards energy recovery from wastewater. AFMBR combines the advantages of anaerobic digestion and membrane bioreactors and shows great potential in overcoming limiting factors such as membrane fouling and low efficiency in treating low-strength wastewater such as domestic sewage. In AFMBR, the fluidized media performs significant role in reducing the membrane fouling, as well as improving the anaerobic microbial activity of AFMBRs. Despite extensive research aimed at mitigating membrane fouling in AFMBR, there has yet to emerge a comprehensive review focusing on strategies for controlling membrane fouling with an emphasis on low energy consumption. Thus, this work overviews the recent progress of AFMBR by summarizing the factors of membrane fouling and energy consumption in AFMBR, and provides targeted in-depth analysis of energy consumption related to membrane fouling control. Additionally, future development directions for AFMBR are also outlooked, and further promotion of AFMBR engineering application is expected. By shedding light on the relationship between energy consumption and membrane fouling control, this review offers a useful information for developing new AFMBR processes with an improved efficiency, low membrane fouling and low energy consumption, and encourages more research efforts and technological advancements in the domain of AFMBR.

Antarctic Snow Failure Mechanics: Analysis, Simulations, and Applications.

Snow failure is the process by which the stability of snow or snow-covered slopes is destroyed, resulting in the collapse or release of snow. Heavy snowfall, low temperatures, and volatile weather typically cause consequences in Antarctica, which can occur at different scales, from small, localized collapses to massive avalanches, and result in significant risk to human activities and infrastructures. Understanding snow damage is critical to assessing potential hazards associated with snow-covered terrain and implementing effective risk mitigation strategies. This review discusses the theoretical models and numerical simulation methods commonly used in Antarctic snow failure research. We focus on the various theoretical models proposed in the literature, including the fiber bundle model (FBM), discrete element model (DEM), cellular automata (CA) model, and continuous cavity-expansion penetration (CCEP) model. In addition, we overview some methods to acquire the three-dimensional solid models and the related advantages and disadvantages. Then, we discuss some critical numerical techniques used to simulate the snow failure process, such as the finite element method (FEM) and three-dimensional (3D) material point method (MPM), highlighting their features in capturing the complex behavior of snow failure. Eventually, different case studies and the experimental validation of these models and simulation methods in the context of Antarctic snow failure are presented, as well as the application of snow failure research to facility construction. This review provides a comprehensive analysis of snow properties, essential numerical simulation methods, and related applications to enhance our understanding of Antarctic snow failure, which offer valuable resources for designing and managing potential infrastructure in Antarctica.

The Interplay Between Epilepsy and Parkinson's Disease: Gene Expression Profiling and Functional Analysis.

The results of many epidemiological studies suggest a bidirectional causality may exist between epilepsy and Parkinson's disease (PD). However, the underlying molecular landscape linking these two diseases remains largely unknown. This study aimed to explore this possible bidirectional causality by identifying differentially expressed genes (DEGs) in each disease as well as their intersection based on two respective disease-related datasets. We performed enrichment analyses and explored immune cell infiltration based on an intersection of the DEGs. Identifying a protein-protein interaction (PPI) network between epilepsy and PD, and this network was visualised using Cytoscape software to screen key modules and hub genes. Finally, exploring the diagnostic values of the identified hub genes. NetworkAnalyst 3.0 and Cytoscape software were also used to construct and visualise the transcription factor-micro-RNA regulatory and co-regulatory networks, the gene-microRNA interaction network, as well as gene-disease association. Based on the enrichment results, the intersection of the DEGs mainly revealed enrichment in immunity-, phosphorylation-, metabolism-, and inflammation-related pathways. The boxplots revealed similar trends in infiltration of many immune cells in epilepsy and Parkinson's disease, with greater infiltration in patients than in controls. A complex PPI network comprising 186 nodes and 512 edges were constructed. According to node connection degree, top 15 hub genes were considered the kernel targets of epilepsy and PD. The area under curve values of hub gene expression profiles confirmed their excellent diagnostic values. This study is the first to analyse the molecular landscape underlying the epidemiological link between epilepsy and Parkinson's disease. The two diseases are closely linked through immunity-, inflammation-, and metabolism-related pathways. This information was of great help in understanding the pathogenesis, diagnosis, and treatment of the diseases. The present results may provide guidance for further in-depth analysis about molecular mechanisms of epilepsy and PD and novel potential targets.

EF-Net: Mental State Recognition by Analyzing Multimodal EEG-fNIRS via CNN.

Analysis of brain signals is essential to the study of mental states and various neurological conditions. The two most prevalent noninvasive signals for measuring brain activities are electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS). EEG, characterized by its higher sampling frequency, captures more temporal features, while fNIRS, with a greater number of channels, provides richer spatial information. Although a few previous studies have explored the use of multimodal deep-learning models to analyze brain activity for both EEG and fNIRS, subject-independent training-testing split analysis remains underexplored. The results of the subject-independent setting directly show the model's ability on unseen subjects, which is crucial for real-world applications. In this paper, we introduce EF-Net, a new CNN-based multimodal deep-learning model. We evaluate EF-Net on an EEG-fNIRS word generation (WG) dataset on the mental state recognition task, primarily focusing on the subject-independent setting. For completeness, we report results in the subject-dependent and subject-semidependent settings as well. We compare our model with five baseline approaches, including three traditional machine learning methods and two deep learning methods. EF-Net demonstrates superior performance in both accuracy and F1 score, surpassing these baselines. Our model achieves F1 scores of 99.36%, 98.31%, and 65.05% in the subject-dependent, subject-semidependent, and subject-independent settings, respectively, surpassing the best baseline F1 scores by 1.83%, 4.34%, and 2.13% These results highlight EF-Net's capability to effectively learn and interpret mental states and brain activity across different and unseen subjects.

Insight into key interactions between diverse factors and membrane fouling mitigation in anaerobic membrane bioreactor.

Anaerobic membrane bioreactors (AnMBRs) have garnered considerable attention as a low-energy and low-carbon footprint treatment technology. With an increasing number of scholars focusing on AnMBR research, its outstanding performance in the field of water treatment has gradually become evident. However, the primary obstacle to the widespread application of AnMBR technology lies in membrane fouling, which leads to reduced membrane flux and increased energy demand. To ensure the efficient and long-term operation of AnMBRs, effective control of membrane fouling is imperative. Nevertheless, the interactions between various fouling factors are complex, making it challenging to predict the changes in membrane fouling. Therefore, a comprehensive analysis of the fouling factors in AnMBRs is necessary to establish a theoretical basis for subsequent membrane fouling control in AnMBR applications. This review aims to provide a thorough analysis of membrane fouling issues in AnMBR applications, particularly focusing on fouling factors and fouling control. By delving into the mechanisms behind membrane fouling in AnMBRs, this review offers valuable insights into mitigating membrane fouling, thus enhancing the lifespan of membrane components in AnMBRs and identifying potential directions for future AnMBR research.

Stereo Visual Servoing Control of a Soft Endoscope for Upper Gastrointestinal Endoscopic Submucosal Dissection.

Quickly and accurately completing endoscopic submucosal dissection (ESD) operations within narrow lumens is currently challenging because of the environment's high flexibility, invisible collision, and natural tissue motion. This paper proposes a novel stereo visual servoing control for a dual-segment robotic endoscope (DSRE) for ESD surgery. Departing from conventional monocular-based methods, our DSRE leverages stereoscopic imaging to rapidly extract precise depth data, enabling quicker controller convergence and enhanced surgical accuracy. The system's dual-segment configuration enables agile maneuverability around lesions, while its compliant structure ensures adaptability within the surgical environment. The implemented stereo visual servo controller uses image features for real-time feedback and dynamically updates gain coefficients, facilitating rapid convergence to the target. In visual servoing experiments, the controller demonstrated strong performance across various tasks. Even when subjected to unknown external forces, the controller maintained robust performance in target tracking. The feasibility and effectiveness of the DSRE were further verified through ex vivo experiments. We posit that this novel system holds significant potential for clinical application in ESD surgeries.

Oligotrophic microbes are recruited to resist multiple global change factors in agricultural subsoils.

An increasing number of anthropogenic pressures can have negative effects on biodiversity and ecosystem functioning. However, our understanding of how soil microbial communities and functions in response to multiple global change factors (GCFs) is still incomplete, particularly in less frequently disturbed subsoils. In this study, we examined the impact of different levels of GCFs (0-9) on soil functions and bacterial communities in both topsoils (0-20 cm) and subsoils (20-40 cm) of an agricultural ecosystem, and characterized the intrinsic factors influencing community resistance based on microbial life history strategy. Our experimental results showed a decline in soil multifunctionality, bacterial diversity, and community resistance as the number of GCFs increased, with a more drastic reduction in community resistance of subsoils. Specifically, we observed a significantly positive relationship between the oligotroph/copiotroph ratio and community resistance in subsoils, which was also verified by the negative correlation between 16S rRNA operon (rrn) copy number and community resistance. Structural equation modeling further revealed the direct effects of community resistance in promoting the ecosystem functioning, regardless of top- and subsoils. Therefore, these results suggested that subsoils may recruit more oligotrophic microbes to enhance their originally weaker community resistance under multiple GCFs, which was essential for maintaining sustainable agroecological functions and services. Overall, our study represents a significant advance in linking microbial life history strategy to the resistance of belowground microbial community and functionality.

IDH1 mutation predicts seizure occurrence and prognosis in lower-grade glioma adults.

Epileptic seizures are frequently the first symptom in glioma patients. However, the causal relationship between glioma and epilepsy is not yet fully understood, as it cannot be explained solely by tumor mass effect or peritumoral factors. In this study, we retrospectively enrolled 320 patients with grade 2-4 glioma who received treatment between January 2019 and July 2022, and explored the biomarkers of seizure occurrence and seizure outcome prediction using univariate and multivariate logistic regression analyses. Our results showed that IDH1 R132H mutation was an independent risk factor for seizure occurrence in lower-grade glioma (LGG) patients (OR = 4.915, 95%CI = 1.713 - 14.103, P = 0.003). Additionally, IDH1 R132H mutation predicted higher seizure-free ratios in LGG patients with intact ATRX expression (OR = 6.793, 95%CI = 1.217 - 37.923, P = 0.029) one year after diagnosis. Therefore, our findings suggest that IDH1 mutation can predict seizure occurrence and control in LGG patients, providing further insights into the relationship between glioma and epilepsy.

Tidal Variations of Fish Larvae Measured Using a 15-Day Continuous Ichthyoplankton Survey in Subei Shoal: Management Implications for the Red-Crowned Crane (Grus japonensis) Population in Yancheng Nature Reserve.

The National Yancheng Rare Birds Nature Reserve is a vitally important staging habitat for the wild population of red-crowned cranes (Grus japonensis) in China. The population relies on local high-protein food sources, such as fish juveniles, to fuel their migratory journeys. However, little is known about the ecology of the fish larvae and juveniles that migrate to the inshore area via tidal rhythm in Subei Shoal, which is adjacent to the reserve. Therefore, we used a fixed study station (32°55'1.2″ N, 121°19'58.8″ E) to conduct a continuous 15-day ichthyoplankton survey at 2 h intervals beginning at 05:00 on 25 April and ending at 03:00 on 10 May 2019. We identified the tidal variations in the number of fish larvae and juveniles and the number at various developmental stages and assessed how they were related to environmental variables such as sea surface temperature, salinity, turbidity, and tidal height in the Dafeng Sea area of Subei Shoal. We found that the number of species and larval individuals were highest and lowest, respectively, at the highest and lowest tidal height, and they obviously increased and decreased with the rising and ebb tide, respectively. Our findings indicate that the variation in numbers of the larvae and juveniles depends on species and developmental stage. The species Acanthogobius ommaturus, Pholis fangi, Cynoglossus joyneri, Liza haematocheila, and Lateolabrax japonicus and the total number of larvae were most influenced by tidal height. These results provide a better understanding of the habitat of prey species of the red-crowned crane wild population as well as scientific data that can be applied to manage the wild population in the reserve sustainably.

Alterations of regional spontaneous brain activity in obsessive-compulsive disorders: A meta-analysis.

BACKGROUND: Recent studies using resting-state functional magnetic resonance imaging (rs-fMRI) demonstrate that there is aberrant regional spontaneous brain activity in obsessive-compulsive disorders (OCD). Nevertheless, the results of previous studies are contradictory, especially in the abnormal brain regions and the directions of their activities. It is necessary to perform a meta-analysis to identify the common pattern of altered regional spontaneous brain activity in patients with OCD. METHODS: The present study conducted a systematic search for studies in English published up to May 2023 in PubMed, Web of Science, and Embase. These studies measured differences in regional spontaneous brain activity at the whole brain level using regional homogeneity (ReHo), the amplitude of low-frequency fluctuations (ALFF) and the fractional amplitude of low-frequency fluctuations (fALFF). Then the Anisotropic effect-size version of seed-based d mapping (AES-SDM) was used to investigate the consistent abnormality of regional spontaneous brain activity in patients with OCD. RESULTS: 27 studies (33 datasets) were included with 1256 OCD patients (650 males, 606 females) and 1176 healthy controls (HCs) (588 males, 588 females). Compared to HCs, patients with OCD showed increased spontaneous brain activity in the right inferior parietal gyrus (Brodmann Area 39), left median cingulate and paracingulate gyri (Brodmann Area 24), bilateral inferior cerebellum, right middle frontal gyrus (Brodmann Area 46), left inferior frontal gyrus in triangular part (Brodmann Area 45) and left middle frontal gyrus in orbital part (Brodmann Area 11). Meanwhile, decreased spontaneous brain activity was identified in the right precentral gyrus (Brodmann Area 4), right insula (Brodmann Area 48), left postcentral gyrus (Brodmann Area 43), bilateral superior cerebellum and left caudate (Brodmann Area 25). CONCLUSIONS: This meta-analysis provided a quantitative review of spontaneous brain activity in OCD. The results demonstrated that the brain regions in the frontal lobe, sensorimotor cortex, cerebellum, caudate and insula are crucially involved in the pathophysiology of OCD. This research contributes to the understanding of the pathophysiologic mechanism underlying OCD and could provide a new perspective on future diagnosis and treatment of OCD.

Agricultural tillage practice and rhizosphere selection interactively drive the improvement of soybean plant biomass.

Rhizosphere microbes play key roles in plant growth and productivity in agricultural systems. One of the critical issues is revealing the interaction of agricultural management (M) and rhizosphere selection effects (R) on soil microbial communities, root exudates and plant productivity. Through a field management experiment, we found that bacteria were more sensitive to the M × R interaction effect than fungi, and the positive effect of rhizosphere bacterial diversity on plant biomass existed in the bacterial three two-tillage system. In addition, inoculation experiments demonstrated that the nitrogen cycle-related isolate Stenotrophomonas could promote plant growth and alter the activities of extracellular enzymes N-acetyl- d-glucosaminidase and leucine aminopeptidase in rhizosphere soil. Microbe-metabolites network analysis revealed that hubnodes Burkholderia-Caballeronia-Paraburkholderia and Pseudomonas were recruited by specific root metabolites under the M × R interaction effect, and the inoculation of 10 rhizosphere-matched isolates further proved that these microbes could promote the growth of soybean seedlings. Kyoto Encyclopaedia of Genes and Genomes pathway analysis indicated that the growth-promoting mechanisms of these beneficial genera were closely related to metabolic pathways such as amino acid metabolism, melatonin biosynthesis, aerobactin biosynthesis and so on. This study provides field observation and experimental evidence to reveal the close relationship between beneficial rhizosphere microbes and plant productivity under the M × R interaction effect.

High-throughput sperm DNA analysis at the single-cell and population levels.

Clinical semen quality assessment is critical to the treatment of infertility. Sperm DNA integrity testing provides critical information that can steer treatment and influence outcomes and offspring health. Flow cytometry is the gold standard approach to assess DNA integrity, but it is not commonly applied at the clinical level. The sperm chromatin dispersion (SCD) assay provides a simpler and cheaper alternative. However, SCD is low-throughput and non-quantitative - sperm assessment is serial, manual and suffers inter- and intra-observer variations. Here, an automated SCD analysis method is presented that enables quantitative sperm DNA quality assessment at the single-cell and population levels. Levering automated optical microscopy and a chromatin diffusion-based analysis, a sample of thousands of sperm that would otherwise require 5 hours is assessed in under 10 minutes - a clinically viable workflow. The sperm DNA diffusion coefficient (DDNA) measurement correlates (R2 = 0.96) with DNA fragmentation index (DFI) from the cytometry-based sperm chromatin structure assay (SCSA). The automated measurement of population-level sperm DNA fragmentation (% sDF) prevents inter-observer variations and shows a good agreement with the SCSA % DFI (R2 = 0.98). This automated approach standardizes and accelerates SCD-based sperm DNA analysis, enabling the clinical application of sperm DNA integrity assessment.