Ambient Air Pollution and Hospitalizations for Schizophrenia in China.

Importance: Schizophrenia episodes may be triggered by short-term environmental stimuli. Short-term increases in ambient air pollution levels may elevate the risk of schizophrenia episodes, yet few epidemiologic studies have examined this association. Objective: To investigate whether short-term increases in air pollution levels are associated with an additional risk of schizophrenia episodes, independent of absolute air pollution concentrations, and whether sustained increases in air pollution levels for several days are associated with more pronounced risks of schizophrenia episodes. Design, Setting, and Participants: This nationwide, population-based, time-stratified case-crossover study was performed based on hospitalization records for schizophrenia across 295 administrative divisions of prefecture-level or above cities in China. Records were extracted from 2 major health insurance systems from January 1, 2013, to December 31, 2017. Thirty-six cities with a small number of schizophrenia hospitalizations (n < 50) were excluded. Data analysis for this study was performed from January to March 2024. Exposure: Daily absolute concentrations of fine particulate matter (PM2.5), inhalable particulate matter (PM10), nitrogen dioxide, sulfur dioxide, ozone, and carbon monoxide were collected. Air pollution increases between neighboring days (APINs) were generated as the differences in absolute air pollution concentrations on the current day minus that on the previous day. Sustained increases (APIN ≥5 µg/m3 for PM2.5 and PM10, APIN ≥1 µg/m3 for nitrogen dioxide and sulfur dioxide, and APIN ≥0.05 mg/m3 for carbon monoxide) lasting for 1 or more to 4 or more days were defined for different air pollutants. Main Outcome and Measure: Patients with schizophrenia episodes were identified by principal discharge diagnoses of schizophrenia. A conditional logistic regression model was used to capture the associations of absolute concentrations, APINs, and sustained increase events for different air pollutants with risks of schizophrenia hospitalizations. Results: The study included 817 296 hospitalization records for schizophrenia across 259 Chinese cities (30.6% aged 0-39 years, 56.4% aged 40-64 years, and 13.0% aged ≥65 years; 55.04% male). After adjusting for the absolute concentrations of respective air pollutants, per-IQR increases in 6-day moving average (lag0-5) APINs of PM2.5, PM10, nitrogen dioxide, sulfur dioxide, and carbon monoxide were associated with increases of 2.37% (95% CI, 0.88%-3.88%), 2.95% (95% CI, 1.46%-4.47%), 4.61% (95% CI, 2.93%-6.32%), 2.16% (95% CI, 0.59%-3.76%), and 2.02% (95% CI, 0.39%-3.68%) in schizophrenia hospitalizations, respectively. Greater risks of schizophrenia hospitalizations were associated with sustained increases in air pollutants lasting for longer durations up to 4 or more days. Conclusions and Relevance: This case-crossover study of the association between ambient air pollution increases and schizophrenia hospitalizations provides novel evidence that short-term increases in ambient air pollution levels were positively associated with an elevated risk of schizophrenia episodes. Future schizophrenia prevention practices should pay additional attention to APINs, especially sustained increases in air pollution levels for longer durations, besides the absolute air pollution concentrations.

Cell-Specific Gene Expressions Underlie Selective White Matter Loss Vulnerability in Mild Traumatic Brain Injury.

Traumatic brain injury (TBI), a risk factor for later-life dementia, leads to salient brain atrophy, particularly in the white matter. It is not clear how white matter atrophy progresses or why some brain regions are damaged while others are spared. We hypothesized that spatial variations of cell-specific gene expression contributed to the selective white matter loss vulnerability following mild TBI (mTBI). Gene expression data were sourced from the publicly available Allen Human Brain Atlas, which comprises microarray data spanning nearly the entire brain, derived from six neurologically normal adult donors. A total of 100 patients with acute stage (within 7 days post-injury) mTBI were enrolled. Of these, 60 patients were followed up at 3 months post-injury and 37 were followed up at 6-12 months post-injury. In addition, 59 healthy controls (HCs), matched for age, gender, and education, were included for comparative analysis. White matter volume changes were analyzed at both the acute stage, 3 months, and 6-12 months follow-up in mTBI patients compared with HCs. Patients with mTBI exhibited significant white matter atrophy in the frontal, parietal, and temporal cortices at 3 months post-injury, which even persisted at 6-12 months follow-up. In addition, mTBI patients with cognitive deficits showed more severe brain atrophy compared with those without cognitive deficits. Crucially, the gene expression marking endothelial cells and S1 pyramidal neurons were associated with increased brain atrophy, whereas the gene expression marking microglia and CA1 pyramidal neurons were associated with decreased brain atrophy in mTBI patients at 3 months post-injury. Microglia and endothelial cells can explain 23.6% of regional variations in the white matter atrophy. These findings suggested that modulating cellular activation, especially by promoting microglial activation at 3 months post-injury, might be a promising approach to prevent white matter atrophy, enhance cognitive outcomes, and reduce the risk of later-life dementia.

Potential Early Effect Biomarkers for Ambient Air Pollution Related Mental Disorders.

Air pollution is one of the greatest environmental risks to health, with 99% of the world's population living where the World Health Organization's air quality guidelines were not met. In addition to the respiratory and cardiovascular systems, the brain is another potential target of air pollution. Population- and experiment-based studies have shown that air pollution may affect mental health through direct or indirect biological pathways. The evidence for mental hazards associated with air pollution has been well documented. However, previous reviews mainly focused on epidemiological associations of air pollution with some specific mental disorders or possible biological mechanisms. A systematic review is absent for early effect biomarkers for characterizing mental health hazards associated with ambient air pollution, which can be used for early warning of related mental disorders and identifying susceptible populations at high risk. This review summarizes possible biomarkers involved in oxidative stress, inflammation, and epigenetic changes linking air pollution and mental disorders, as well as genetic susceptibility biomarkers. These biomarkers may provide a better understanding of air pollution's adverse effects on mental disorders and provide future research direction in this arena.

Brain age prediction using interpretable multi-feature-based convolutional neural network in mild traumatic brain injury.

BACKGROUND: Convolutional neural network (CNN) can capture the structural features changes of brain aging based on MRI, thus predict brain age in healthy individuals accurately. However, most studies use single feature to predict brain age in healthy individuals, ignoring adding information from multiple sources and the changes in brain aging patterns after mild traumatic brain injury (mTBI) were still unclear. METHODS: Here, we leveraged the structural data from a large, heterogeneous dataset (N = 1464) to implement an interpretable 3D combined CNN model for brain-age prediction. In addition, we also built an atlas-based occlusion analysis scheme with a fine-grained human Brainnetome Atlas to reveal the age-sstratified contributed brain regions for brain-age prediction in healthy controls (HCs) and mTBI patients. The correlations between brain predicted age gaps (brain-PAG) following mTBI and individual's cognitive impairment, as well as the level of plasma neurofilament light were also examined. RESULTS: Our model utilized multiple 3D features derived from T1w data as inputs, and reduced the mean absolute error (MAE) of age prediction to 3.08 years and improved Pearson's r to 0.97 on 154 HCs. The strong generalizability of our model was also validated across different centers. Regions contributing the most significantly to brain age prediction were the caudate and thalamus for HCs and patients with mTBI, and the contributive regions were mostly located in the subcortical areas throughout the adult lifespan. The left hemisphere was confirmed to contribute more in brain age prediction throughout the adult lifespan. Our research showed that brain-PAG in mTBI patients was significantly higher than that in HCs in both acute and chronic phases. The increased brain-PAG in mTBI patients was also highly correlated with cognitive impairment and a higher level of plasma neurofilament light, a marker of neurodegeneration. The higher brain-PAG and its correlation with severe cognitive impairment showed a longitudinal and persistent nature in patients with follow-up examinations. CONCLUSION: We proposed an interpretable deep learning framework on a relatively large dataset to accurately predict brain age in both healthy individuals and mTBI patients. The interpretable analysis revealed that the caudate and thalamus became the most contributive role across the adult lifespan in both HCs and patients with mTBI. The left hemisphere contributed significantly to brain age prediction may enlighten us to be concerned about the lateralization of brain abnormality in neurological diseases in the future. The proposed interpretable deep learning framework might also provide hope for testing the performance of related drugs and treatments in the future.

Pangenome and multi-tissue gene atlas provide new insights into the domestication and highland adaptation of yaks.

BACKGROUND: The genetic diversity of yak, a key domestic animal on the Qinghai-Tibetan Plateau (QTP), is a vital resource for domestication and breeding efforts. This study presents the first yak pangenome obtained through the de novo assembly of 16 yak genomes. RESULTS: We discovered 290 Mb of nonreference sequences and 504 new genes. Our pangenome-wide presence and absence variation (PAV) analysis revealed 5,120 PAV-related genes, highlighting a wide range of variety-specific genes and genes with varying frequencies across yak populations. Principal component analysis (PCA) based on binary gene PAV data classified yaks into three new groups: wild, domestic, and Jinchuan. Moreover, we proposed a 'two-haplotype genomic hybridization model' for understanding the hybridization patterns among breeds by integrating gene frequency, heterozygosity, and gene PAV data. A gene PAV-GWAS identified a novel gene (BosGru3G009179) that may be associated with the multirib trait in Jinchuan yaks. Furthermore, an integrated transcriptome and pangenome analysis highlighted the significant differences in the expression of core genes and the mutational burden of differentially expressed genes between yaks from high and low altitudes. Transcriptome analysis across multiple species revealed that yaks have the most unique differentially expressed mRNAs and lncRNAs (between high- and low-altitude regions), especially in the heart and lungs, when comparing high- and low-altitude adaptations. CONCLUSIONS: The yak pangenome offers a comprehensive resource and new insights for functional genomic studies, supporting future biological research and breeding strategies.

APOE ε4 allele status modulates the spatial patterns of progressive atrophy in the temporal lobes after mild traumatic brain injury.

INTRODUCTION: We evaluated how the apolipoprotein E (APOE) ε4 allele modulated the spatial patterns of longitudinal atrophy in the Alzheimer's disease-vulnerable brain areas of patients with mild traumatic brain injury (mTBI) from the acute to chronic phase post injury. METHODS: Fifty-nine adult patients with acute mTBI and 48 healthy controls with APOE ε4 allele testing underwent T1-weighted magnetic resonance imaging and neuropsychological assessments with 6 to 12 months of follow-up. Progressive brain volume loss was compared voxel-wise in the temporal lobes. RESULTS: Patients with the APOE ε4 allele presented significant longitudinal atrophy in the left superior and middle temporal gyri, where the progressive gray matter volume loss predicted longitudinal impairment in language fluency, whereas mTBI APOE ε4 allele noncarriers showed mainly significant longitudinal atrophy in the medial temporal lobes, without significant neuropsychological relevance. DISCUSSION: The atrophy progression observed in mTBI patients with the APOE ε4 allele may increase the possibility of developing a specific phenotype of Alzheimer's disease with language dysfunction. Highlights: The apolipoprotein E (APOE) ε4 allele and mild traumatic brain injury (mTBI) are risk factors for Alzheimer's disease (AD) progression.It is unclear how the interaction of mTBI with the APOE ε4 allele impacts the progressive atrophy topography in AD-vulnerable brain regions.In this study, patients with the APOE ε4 allele showed progressive atrophy patterns similar to the early stage of logopenic variant of primary progressive aphasia (lvPPA) phenotype of AD. APOE ε4 allele carriers with mTBI history may be at the risk of developing a given AD phenotype with language dysfunction.

Serum biomarkers and disease progression in CT-negative mild traumatic brain injury.

Blood proteins are emerging as potential biomarkers for mild traumatic brain injury (mTBI). Molecular pathology of mTBI underscores the critical roles of neuronal injury, neuroinflammation, and vascular health in disease progression. However, the temporal profile of blood biomarkers associated with the aforementioned molecular pathology after CT-negative mTBI, their diagnostic and prognostic potential, and their utility in monitoring white matter integrity and progressive brain atrophy remain unclear. Thus, we investigated serum biomarkers and neuroimaging in a longitudinal cohort, including 103 CT-negative mTBI patients and 66 matched healthy controls (HCs). Angiogenic biomarker vascular endothelial growth factor (VEGF) exhibited the highest area under the curve of 0.88 in identifying patients from HCs. Inflammatory biomarker interleukin-1ß and neuronal cell body injury biomarker ubiquitin carboxyl-terminal hydrolase L1 were elevated in acute-stage patients and associated with deterioration of cognitive function from acute-stage to 6-12 mo post-injury period. Notably, axonal injury biomarker neurofilament light (NfL) was elevated in acute-stage patients, with higher levels associated with impaired white matter integrity in acute-stage and progressive gray and white matter atrophy from 3- to 6-12 mo post-injury period. Collectively, our findings emphasized the potential clinical value of serum biomarkers, particularly NfL and VEGF, in diagnosing mTBI and monitoring disease progression.

Cylindrical granules in the development of mesalazine solid formulations (â ): Physical properties, compression behaviors, and tableting performances.

Cylindrical granules have been employed in the pharmaceutical industry. However, to our knowledge, the study on the compressibility and tabletability of cylindrical granules has not been reported. This study aimed to explore the effects of the physical properties of cylindrical granules on the compression behaviors and the tableting performances, with mesalazine (MSZ) as a model drug. First, the six formulations of MSZ cylindrical granules were extruded by changing the ethanol proportion in the binder. Then, the physical characteristics of MSZ cylindrical granules were systematically studied. Subsequently, the compressibility and tabletability were evaluated using different mathematic models. It was worth noting that highly porous cylindrical granules possessed favorable compressibility and good tabletability due to the increased pore volume, reduced density, and decreased fracture forces. Finally, dissolution tests were conducted and highly porous granules showed higher dissolution rates than the less porous ones, but an opposite trend was observed for the corresponding tablets. This study proved the importance of physical properties in the tableting process of cylindrical granules and provided strategies to improve their compressibility and tabletability.

First report of the ectomycorrhizal fungal community associated with two herbaceous plants in Inner Mongolia, China.

Ectomycorrhizal (EM) fungi play a vital role in ensuring plant health, plant diversity, and ecosystem function. However, the study on fungal diversity and community assembly of EM fungi associated with herbaceous plants remains poorly understood. Thus, in our study, Carex pediformis and Polygonum divaricatum in the subalpine meadow of central Inner Mongolia, China were selected for exploring EM fungal diversity and community assembly mechanisms by using llumina MiSeq sequencing of the fungal internal transcribed spacer 2 region (ITS2). We evaluated the impact of soil, climatic, and spatial variables on EM fungal diversity and community turnover. Deterministic vs. stochastic processes for EM fungal community assembly were quantified using ß-Nearest taxon index scores. The results showed that a total of 70 EM fungal OTUs belonging to 21 lineages were identified, of which Tomentella-Thelephora, Helotiales1, Tricholoma, Inocybe, Wilcoxina were the most dominant EM fungal lineages. EM fungal communities were significantly different between the two herbaceous plants and among the two sampling sites, and this difference was mainly influenced by soil organic matter (OM) content and mean annual precipitation (MAP). The neutral community model (NCM) explained 45.7% of the variations in EM fungi community assembly. A total of 99.27% of the ß-Nearest Taxa Index (ßNTI) value was between -2 and 2. These results suggest that the dominant role of stochastic processes in shaping EM fungal community assembly. In addition, RCbray values showed that ecological drift in stochastic processes dominantly determined community assembly of EM fungi. Overall, our study shed light on the EM fungal diversity and community assembly associated with herbaceous plants in the subalpine region of central Inner Mongolia for the first time, which provided a better understanding of the role of herbaceous EM fungi.

HGM-cNet: Integrating hippocampal gray matter probability map into a cascaded deep learning framework improves hippocampus segmentation.

A robust cascaded deep learning framework with integrated hippocampal gray matter (HGM) probability map was developed to improve the hippocampus segmentation (called HGM-cNet) due to its significance in various neuropsychiatric disorders such as Alzheimer's disease (AD). Particularly, the HGM-cNet cascaded two identical convolutional neural networks (CNN), where each CNN was devised by incorporating Attention Block, Residual Block, and DropBlock into the typical encoder-decoder architecture. The two CNNs were skip-connected between encoder components at each scale. The adoption of the cascaded deep learning framework was to conveniently incorporate the HGM probability map with the feature map generated by the first CNN. Experiments on 135T1-weighted MRI scans and manual hippocampal labels from publicly available ADNI-HarP dataset demonstrated that the proposed HGM-cNet outperformed seven multi-atlas-based hippocampus segmentation methods and six deep learning methods under comparison in most evaluation metrics. The Dice (average > 0.89 for both left and right hippocampus) was increased by around or more than 1% over other methods. The HGM-cNet also achieved a superior hippocampus segmentation performance in each group of cognitive normal, mild cognitive impairment, and AD. The stability, conveniences and generalizability of the cascaded deep learning framework with integrated HGM probability map in improving hippocampus segmentation was validated by replacing the proposed CNN with 3D-UNet, Atten-UNet, HippoDeep, QuickNet, DeepHarp, and TransBTS models. The integration of the HGM probability map in the cascaded deep learning framework was also demonstrated to facilitate capturing hippocampal atrophy more accurately than alternative methods in AD analysis. The codes are publicly available at https://github.com/Liu1436510768/HGM-cNet.git.

Hierarchical brain structural-functional coupling associated with cognitive impairments in mild traumatic brain injury.

Mild traumatic brain injury (mTBI) disrupts the integrity of white matter microstructure, which affects brain functional connectivity supporting cognitive function. Although the relationship between structural and functional connectivity (SC and FC), here called SC-FC coupling, has been studied on global level in brain disorders, the long-term disruption of SC-FC coupling in mTBI at regional scale was still unclear. The current study investigated the alteration pattern of regional SC-FC coupling in 104 acute mTBI patients (41 with 6-12 months of follow-up) and 56 healthy controls (HCs). SC and FC networks were constructed to measure regional, intra-network, and inter-network SC-FC coupling. Compared with HCs, acute mTBI exhibited altered SC-FC coupling of the sensorimotor network (SMN). The coupling laterality indicators of the SMN can identify mTBI from controls. The persistent SC-FC decoupling of the SMN and the additional decoupling of the default mode network (DMN) were observed in chronic mTBI. Crucially, decoupling of the SMN and DMN predicted better cognitive outcomes. The findings revealed the SC-FC coupling alternations exhibited hierarchical trend originating from the sensorimotor cortex to high-order cognitive regions with the progression of mTBI. The regional and hierarchical SC-FC coupling may be a prognostic biomarker to provide insights into the pathophysiology mechanism of mTBI.

Baseline white matter function predicts short-term treatment response in first-episode schizophrenia.

BACKGROUND AND PURPOSE: The detection and characterization of functional activities in the gray matter of schizophrenia (SZ) have been widely explored. However, the relationship between resting-state functional signals in the white matter of first-episode SZ and short-term treatment response remains unclear. METHODS: Thirty-six patients with first-episode SZ and 44 matched healthy controls were recruited in this study. Patients were classified as nonresponders and responders based on response to antipsychotic medication during a single hospitalization. The fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) of white matter were calculated. The relationships between functional changes and clinical features were analyzed. In addition, voxel-based morphometry was performed to analyze the white matter volume. RESULTS: One-way analysis of variance showed significant differences of fALFF and ReHo in the left posterior thalamic radiation and left cingulum (hippocampus) in the patient group, and the areas were regarded as seeds. The FC was calculated between seeds and other white matter networks. Compared with responders, nonresponders showed significantly increased FC between the left cingulum (hippocampus) and left posterior thalamic radiation, splenium of corpus callosum, and left tapetum, and were associated with the changes of clinical assessment. However, there was no difference in white matter volume between groups. CONCLUSION: Our work provides a novel insight that psycho-neuroimaging-based white matter function holds promise for influencing the clinical diagnosis and treatment of SZ.

Brain dynamics in triple-network interactions and its relation to multiple cognitive impairments in mild traumatic brain injury.

Traumatic brain injury (TBI) disrupt the coordinated activity of triple-network and produce impairments across several cognitive domains. The triple-network model posits a key role of the salience network (SN) that regulates interactions with the central executive network (CEN) and default mode network (DMN). However, the aberrant dynamic interactions among triple-network and associations with neurobehavioral symptoms in mild TBI was still unclear. In present study, we used brain network interaction index (NII) and dynamic functional connectivity to examine the time-varying cross-network interactions among the triple-network in 109 acute patients, 41 chronic patients, and 65 healthy controls. Dynamic cross-network interactions were significantly increased and more variable in mild TBI compared to controls. Crucially, mild TBI exhibited an increased NII as enhanced integrations between the SN and CEN while reduced coupling of the SN with DMN. The increased NII also implied much severer and multiple domains of cognitive impairments at both acute and chronic mild TBI. Abnormities in time-varying engagement of triple-network is a clinically relevant neurobiological signature of psychopathology in mild TBI. The findings provided align with and advance an emerging perspective on the importance of aberrant brain dynamics associated with highly disparate cognitive and behavioral outcomes in trauma.

Reorganized Hubs of Brain Functional Networks after Acute Mild Traumatic Brain Injury.

Mild traumatic brain injury (mTBI)-associated damage to hub regions can lead to disrupted modular structures of functional brain networks and may result in widespread cognitive and behavioral deficits. The spatial layout of brain connections and modules is essential for understanding the reorganization of brain networks to trauma. We investigated the roles of hubs in inter-subnetwork information coordination and integration using participation coefficients (PCs) in 74 patients with acute mTBI and 51 matched healthy controls. In some brain networks, such as default mode network (DMN) and frontoparietal network (FPN), mild TBI patients had decreased PC levels, while this measure was saliently increased in patients in other networks, such as the visual network. The hub disruption index was defined as the gradient of a straight line fitted to scatterplots of individual mTBI in participation coefficient versus mean participation coefficient of healthy groups. There was a trend of radical reorganization of some efficient "hub" nodes in patients (κ = -0.15), compared with controls (κ close to 0). The PC of brain hubs can also differentiate mTBI patients from controls with an 88% accuracy, and decreased PC levels in FPN can predict patient' s worse cognitive information processing speed (r = 0.36, p < 0.002) and working memory performance (r = 0.35, p < 0.002). Reduced PC within the DMN was associated with patients' complaints of post-concussion symptoms (r = -0.35, p < 0.002). This evidence suggests a trend of spatial transition of hub profiles in acute mTBI, and graph metrics of PC measures can be used as potential diagnostic biomarkers.

Arterial spin labeling magnetic resonance evaluates changes of cerebral blood flow in patients with mild traumatic brain injury. / åŠ¨è„‰è‡ªæ—‹æ ‡è®°ç£å ±æŒ¯è¯„ä¼°è½»åº¦è„‘å¤–ä¼¤æ‚£è€ çš„è„‘è¡€æµå˜åŒ–.

OBJECTIVES: The patients with mild traumatic brain injury (mTBI) accounts for more than 80% of the patients with brain injury. Most patients with mTBI have no abnormalities in CT examination. Therefore, most patients choose to self-care and recover rather than seeking medical treatment. In fact, mTBI may result in persistent cognitive decline and neurobehavioral dysfunction. In addition, changes occurred in neurochemistry, metabolism, and cells after injury may cause changes in cerebral blood flow (CBF), which is one of the causes of secondary injury and slow brain repair. This study aims to evaluate the changes of CBF with the progression of the disease in patients with mTBI based on arterial spin labeling (ASL) magnetic resonance imaging technology. METHODS: In the outpatient or emergency department of the Second Affiliated Hospital of Wenzhou Medical University, 43 mTBI patients were collected as an mTBI group, and 43 normal subjects with age, gender, and education level matching served as a control group. They all received clinical neuropsychology and cognitive function evaluation and magnetic resonance imaging. In the mTBI group, 22 subjects were followed up at acute phase, 1 month, 3 months, and 12 months. Based on the control group, the abnormal regions of CBF in the whole brain of mTBI patients were analyzed. The abnormal regions were taken as the regions of interest (ROI). The correlation of the values of the CBF in ROIs with clinical indications, cognitive function, and the changes of CBF in ROI at each time point during the follow-up were analyzed. RESULTS: Compared with the control group, the CBF in the bilateral dorsolateral superior frontal gyrus and auxiliary motor areas in the cortical region, as well as the right putamen, caudate nucleus, globus pallidus, and parahippocampus in the subcutaneous regions in the acute phase of the mTBI group were significantly increased (all P<0.01, TFCE-FWE correction). The analysis results of correlation of CBF with neuropsychology and cognitive domain showed that in the mTBI group, whole brain (r=0.528, P<0.001), right caudate nucleus (r=0.512, P<0.001), putamen (r=0.486, P<0.001), and globus pallidus (r=0.426, P=0.006) values of the were positively correlated with Backward Digit Span Test (BDST) score (reflectting working memory ability), and the right globus pallidus CBF was negatively correlated with the Post-Traumatic Stress Disorder Cheeklist-CivilianVersion (PCL-C) score (r=-0.402, P=0.010). Moreover, the follow-up study showed that abnormal CBF in these areas had not been restored. The correlation of CBF was negatively correlated with PCL-C and BDST at 1 months, 3 months, and 12 months (all P>0.05). CONCLUSIONS: The elevated CBF value is one of the stress characteristics of brain injury in the mTBI patients at the acute phase. There is abnormal elevation of CBF values in multiple cortex or subcortical areas. Multi-time point studies show that there is no obvious change of CBF in abnormal areas, suggesting that potential clinical treatment is urgently needed for the mTBI patients.

Effects of water levels on plant traits and nitrogen use efficiency in monoculture and intercropped artificial grasslands.

Water availability is the main factor affecting the forage productivity of artificial grasslands, particularly in semi-arid regions. Generally, intercropping of gramineous grass and leguminous grass can achieve high productivity. However, how different water availability levels affect the productivity of intercropping system remains unclear. Here, we conducted a 3-year (2015-2017) study by manipulating the water conditions (CK equivalent to the annual precipitation, +50% treatment equivalent to 50% increase over the average precipitation, and -50% treatment equivalent to 50% decrease over the average precipitation) to explore the responses of plant traits, nitrogen use efficiency, and biomass of the monoculture of Medicago sativa (a leguminous grass, M.s), monoculture of Elymus nutans (a gramineous grass, E.n), and intercropping of M.s and E.n in a semi-arid region in Inner Mongolia, China. The results showed that the biomass obtained by intercropping of M.s and E.n decreased by 24.4% in -50% treatment compared to the CK treatment, while that of the monoculture of M.s decreased by 34.4% under the -50% treatment compared to the CK treatment. However, there was no significant difference in the biomass between intercropping artificial grassland and monoculture M. sativa under +50% treatment. Compared to monoculture, M.s can obtain more nitrogen by biological nitrogen fixation and decrease the proportion of nitrogen absorbed from soils under intercropping in the same water conditions. Under the intercropping system, the proportions of nitrogen absorbed from soils by M.s were 87.4%, 85.1, and 76.9% in -50%, CK, and +50% treatments, respectively. Under monoculture, these proportions were 91.9, 89.3, and 82.3% in -50%, CK, and +50% treatments, respectively. Plant trait, but not soil nitrogen content, was the main regulator for the productivity responses to water level changes. Our results highlight that intercropping can achieve higher productivity in both dry and wet conditions. Therefore, considering the fluctuating rainfall events in the future, it might be useful to alter the proportions of intercropped forage species in an artificial grassland to obtain optimal productivity by reducing the limitations of nitrogen availability. However, the economic viability of intercropping M. sativa and E. nutans should be evaluated in the future.

Preclinical studies of a high drug-loaded meloxicam nanocrystals injection for analgesia.

Meloxicam (MLX) is considered to have significant analgesic properties. However, the analgesic effects of MLX are compromised by its poor water solubility and thus the low drug loading. The purpose of this study was to develop a high drug-loaded MLX injection by formulating it into nanocrystals (NCs) for the treatment of analgesia. The developed MLXNCs exhibited satisfactory particle sizes and remarkably in vitro dissolution behaviors. In addition, the plasma concentrations of MLXNCs were comparable with the MLX solution (formulated with 1.0% polyoxyethylene castor oil 35) in rats. The acetic acid-induced writhing tests, hot plate tests and hind paw incision experiments demonstrated that the MLXNCs had significant analgesic effects. The findings provide insights into the developed high drug-loaded MLXNCs and provide new therapeutic options for acute and chronic pain management.

Discovery and structure-activity relationship studies of novel Bcl-2/Mcl-1 dual inhibitors with indole scaffold.

The Bcl-2 anti-apoptotic proteins were widely overexpressed in diverse tumor cells, especially for Bcl-2 and Mcl-1, which regarding as important targets of apoptosis induction and resistance of chemotherapy. We identified novel Bcl-2/Mcl-1 dual inhibitors with indole scaffold by the optimization of hit 1. Structure modification against several moieties including hydrophobic fragment, side chain and benzoic acid fragment was conducted and the structure-activity relationship was analyzed. The representative compound 12f exhibited sub-micromolar binding affinities to Bcl-2/Mcl-1 without binding affinity to Bcl-XL. Mechanism of action studies suggested that compound 12f dose-dependently triggered apoptosis in HL-60 cells. Compound 12f represents a novel Bcl-2/Mcl-1 dual inhibitor which deserving further study.

Trends in targeting Bcl-2 anti-apoptotic proteins for cancer treatment.

Apoptosis is the major mode of programmed cell death, which conduces to maintain tissue homeostasis, clearance of abnormal cells and development of organisms. Over the past two decades, great progress and significant clinical benefits in cancer treatment have been made by targeting Bcl-2 anti-apoptotic proteins. However, with the deep research of clinic, the therapeutic value of single target inhibitors is restricted due to the limited monotherapy activity, potential and complex drug resistance as well as monotherapy safety. This review focuses on recent advance in discovery of novel apoptosis inducers targeting Bcl-2 anti-apoptotic proteins aiming to overcome existing therapeutic limitations, and introduce the strategies and advanced technologies in the drug design and optimization.