The global burden and risk factors of cardiovascular diseases in adolescent and young adults, 1990-2019.

BACKGROUND: To provide details of the burden and the trend of the cardiovascular disease (CVD) and its risk factors in adolescent and young adults. METHODS: Age-standardized rates (ASRs) of incidence, mortality and Disability-Adjusted Life Years (DALYs) were used to describe the burden of CVD in adolescents and young adults. Estimated Annual Percentage Changes (EAPCs) of ASRs were used to describe the trend from 1990 to 2019. Risk factors were calculated by Population Attributable Fractions (PAFs). RESULTS: In 2019, the age-standardized incidence rate (ASIR), age-standardized mortality rate (ASMR) and age-standardized DALYs rate (ASDR) of CVD were 129.85 per 100 000 (95% Confidence interval (CI): 102.60, 160.31), 15.12 per 100 000 (95% CI: 13.89, 16.48) and 990.64 per 100 000 (95% CI: 911.06, 1076.46). The highest ASRs were seen in low sociodemographic index (SDI) and low-middle SDI regions. The burden was heavier in male and individuals aged 35-39. From 1990 to 2019, 72 (35.29%) countries showed an increasing trend of ASIR and more than 80% countries showed a downward trend in ASMR and ASDR. Rheumatic heart disease had the highest ASIR and Ischemic Heart Disease was the highest in both ASMR and ASDR. The main attributable risk factor for death and DALYs were high systolic blood pressure, high body-mass index and high LDL cholesterol. CONCLUSIONS: The burden of CVD in adolescent and young adults is a significant global health challenge. It is crucial to take into account the disparities in SDI levels among countries, gender and age characteristics of the population, primary types of CVD, and the attributable risk factors when formulating and implementing prevention strategies.

Divergent redistribution behavior of divalent metal cations associated with Fe(II)-mediated jarosite phase transformation.

The Fe(II)/Fe(III) cycle is an important driving force for dissolution and transformation of jarosite. Divalent heavy metals usually coexist with jarosite; however, their effects on Fe(II)-induced jarosite transformation and different repartitioning behavior during mineral dissolution-recrystallization are still unclear. Here, we investigated Fe(II)-induced (1 mM Fe(II)) jarosite conversion in the presence of Cd(II), Mn(II), Co(II), Ni(II) and Pb(II) (denoted as Me(II), 1 mM), respectively, under anaerobic condition at neutral pH. The results showed that all co-existing Me(II) retarded Fe(II)-induced jarosite dissolution. In the Fe(II)-only system, jarosite first rapidly transformed to lepidocrocite (an intermediate product) and then slowly to goethite; lepidocrocite was the main product. In Fe(II)-Cd(II), -Mn(II), and -Pb(II) systems, coexisting Cd(II), Mn(II) and Pb(II) retarded the above process and lepidocrocite was still the dominant conversion product. In Fe(II)-Co(II) system, coexisting Co(II) promoted lepidocrocite transformation into goethite. In Fe(II)-Ni(II) system, jarosite appeared to be directly converted into goethite, although small amounts of lepidocrocite were detected in the final product. In all treatments, the appearance or accumulation of lepidocrocite may be also related to the re-adsorption of released sulfate. By the end of reaction, 6.0 %, 4.0 %, 76.0 % 11.3 % and 19.2 % of total Cd(II), Mn(II), Pb(II) Co(II) and Ni(II) were adsorbed on the surface of solid products. Up to 49.6 %, 44.3 %, and 21.6 % of Co(II), Ni(II), and Pb(II) incorporated into solid product, with the reaction indicating that the dynamic process of Fe(II) interaction with goethite may promote the continuous incorporation of Co(II), Ni(II), and Pb(II).

MiR-2110 induced by chemically synthesized cinobufagin functions as a tumor-metastatic suppressor via targeting FGFR1 to reduce PTEN ubiquitination degradation in nasopharyngeal carcinoma.

Tumor cell metastasis is the key cause of death in patients with nasopharyngeal carcinoma (NPC). MiR-2110 was cloned and identified in Epstein-Barr virus (EBV)-positive NPC, but its role is unclear in NPC. In this study, we investigated the effect of miR-2110 on NPC metastasis and its related molecular basis. In addition, we also explored whether miR-2110 can be regulated by cinobufotalin (CB) and participate in the inhibition of CB on NPC metastasis. Bioinformatics, RT-PCR, and in situ hybridization were used to observe the expression of miR-2110 in NPC tissues and cells. Scratch, Boyden, and tail vein metastasis model of nude mouse were used to detect the effect of miR-2110 on NPC metastasis. Western blot, Co-IP, luciferase activity, colocalization of micro confocal and ubiquitination assays were used to identify the molecular mechanism of miR-2110 affecting NPC metastasis. Finally, miR-2110 induced by CB participates in CB-stimulated inhibition of NPC metastasis was explored. The data showed that increased miR-2110 significantly suppresses NPC cell migration, invasion, and metastasis. Suppressing miR-2110 markedly restored NPC cell migration and invasion. Mechanistically, miR-2110 directly targeted FGFR1 and reduced its protein expression. Decreased FGFR1 attenuated its recruitment of NEDD4, which downregulated NEDD4-induced phosphatase and tensin homolog (PTEN) ubiquitination and degradation and further increased PTEN protein stability, thereby inactivating PI3K/AKT-stimulated epithelial-mesenchymal transition signaling and ultimately suppressing NPC metastasis. Interestingly, CB, a potential new inhibitory drug for NPC metastasis, significantly induced miR-2110 expression by suppressing PI3K/AKT/c-Jun-mediated transcription inhibition. Suppression of miR-2110 significantly restored cell migration and invasion in CB-treated NPC cells. Finally, a clinical sample assay indicated that reduced miR-2110 was negatively correlated with NPC lymph node metastasis and positively related to NPC patient survival prognosis. In summary, miR-2110 is a metastatic suppressor involving in CB-induced suppression of NPC metastasis.

Diagnosing schizophrenia using deep learning: Novel interpretation approaches and multi-site validation.

Schizophrenia is a profound and enduring mental disorder that imposes significant negative impacts on individuals, their families, and society at large. The development of more accurate and objective diagnostic tools for schizophrenia can be expedited through the employment of deep learning (DL), that excels at deciphering complex hierarchical non-linear patterns. However, the limited interpretability of deep learning has eroded confidence in the model and restricted its clinical utility. At the same time, if the data source is only derived from a single center, the model's generalizability is difficult to test. To enhance the model's reliability and applicability, leave-one-center-out validation with a large and diverse sample from multiple centers is crucial. In this study, we utilized Nine different global centers to train and test the 3D Resnet model's generalizability, resulting in an 82% classification performance (area under the curve) on all datasets sourced from different countries, employing a leave-one-center-out-validation approach. Per our approximation of the feature significance of each region on the atlas, we identified marked differences in the thalamus, pallidum, and inferior frontal gyrus between individuals with schizophrenia and healthy controls, lending credence to prior research findings. At the same time, in order to translate the model's output into clinically applicable insights, the SHapley Additive exPlanations (SHAP) permutation explainer method with an anatomical atlas have been refined, thereby offering precise neuroanatomical and functional interpretations of different brain regions.

Simultaneous assessment of stress hyperglycemia ratio and glycemic variability to predict mortality in patients with coronary artery disease: a retrospective cohort study from the MIMIC-IV database.

BACKGROUND: Stress hyperglycemia and glycemic variability (GV) can reflect dramatic increases and acute fluctuations in blood glucose, which are associated with adverse cardiovascular events. This study aimed to explore whether the combined assessment of the stress hyperglycemia ratio (SHR) and GV provides additional information for prognostic prediction in patients with coronary artery disease (CAD) hospitalized in the intensive care unit (ICU). METHODS: Patients diagnosed with CAD from the Medical Information Mart for Intensive Care-IV database (version 2.2) between 2008 and 2019 were retrospectively included in the analysis. The primary endpoint was 1-year mortality, and the secondary endpoint was in-hospital mortality. Levels of SHR and GV were stratified into tertiles, with the highest tertile classified as high and the lower two tertiles classified as low. The associations of SHR, GV, and their combination with mortality were determined by logistic and Cox regression analyses. RESULTS: A total of 2789 patients were included, with a mean age of 69.6 years, and 30.1% were female. Overall, 138 (4.9%) patients died in the hospital, and 404 (14.5%) patients died at 1 year. The combination of SHR and GV was superior to SHR (in-hospital mortality: 0.710 vs. 0.689, p = 0.012; 1-year mortality: 0.644 vs. 0.615, p = 0.007) and GV (in-hospital mortality: 0.710 vs. 0.632, p = 0.004; 1-year mortality: 0.644 vs. 0.603, p < 0.001) alone for predicting mortality in the receiver operating characteristic analysis. In addition, nondiabetic patients with high SHR levels and high GV were associated with the greatest risk of both in-hospital mortality (odds ratio [OR] = 10.831, 95% confidence interval [CI] 4.494-26.105) and 1-year mortality (hazard ratio [HR] = 5.830, 95% CI 3.175-10.702). However, in the diabetic population, the highest risk of in-hospital mortality (OR = 4.221, 95% CI 1.542-11.558) and 1-year mortality (HR = 2.013, 95% CI 1.224-3.311) was observed in patients with high SHR levels but low GV. CONCLUSIONS: The simultaneous evaluation of SHR and GV provides more information for risk stratification and prognostic prediction than SHR and GV alone, contributing to developing individualized strategies for glucose management in patients with CAD admitted to the ICU.

Non-insulin-based insulin resistance indexes in predicting atrial fibrillation recurrence following ablation: a retrospective study.

BACKGROUND: Insulin resistance (IR) is involved in the pathophysiological processes of arrhythmias. Increasing evidence suggests triglyceride and glucose (TyG) index, metabolic score for insulin resistance (METS-IR), triglyceride glucose-body mass index (TyG-BMI), and triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio are simple and reliable surrogates for IR. Although they have been associated with atrial fibrillation (AF), evidence supporting this is limited. Here, this is the first study to investigate the association between TyG-BMI index and AF recurrence following radiofrequency catheter ablation (RFCA). The performance of the four non-insulin-based IR indexes in predicting AF recurrence after ablation was explored. METHODS: A total of 2242 AF patients who underwent a de novo RFCA between June 2018 to January 2022 at two hospitals in China were included in this retrospective study. The predictive values of IR indexes for AF recurrence after ablation were assessed. RESULTS: During 1-year follow-up, 31.7% of patients experienced AF recurrence. The multivariable analysis revealed that TyG index, METS-IR, and TyG-BMI index were independent risk factors for AF recurrence. Restricted cubic spline analysis revealed a connection between METS-IR, TyG-BMI index, and AF recurrence (P < 0.001). Furthermore, incorporating the METS-IR or TyG-BMI index to the basic risk model with fully adjusted factors considerably enhanced the forecast of AF recurrence, as demonstrated by the C-statistic, continuous net reclassification improvement, and integrated discrimination improvement. CONCLUSIONS: TyG index, METS-IR, and TyG-BMI index were independently associated with AF recurrence following ablation. Among the four non-insulin-based IR indexes, TyG-BMI had the highest predictive value, followed by METS-IR.

Associations of variability in blood glucose and systolic blood pressure with mortality in patients with coronary artery disease: A retrospective cohort study from the MIMIC-IV database.

AIMS: Variability of metabolic parameters, such as glycemic variability (GV) and systolic blood pressure variability (SBPV), are associated with adverse cardiovascular outcomes. However, whether these parameters have additive effects on mortality in patients with coronary artery disease (CAD) hospitalized in the intensive care unit (ICU) remains unclear. METHODS: We retrospectively enrolled patients with CAD from the Medical Information Mart for Intensive Care-IV database. The highest tertile of variability was defined as high variability. A variability scoring system was established, which assigned 0 points to tertile 1, 1 point to tertile 2, and 2 points to tertile 3 for GV and SBPV. RESULTS: Among 4237 patients with CAD, 400 patients died in hospital, and 967 patients died during 1-year follow-up. High GV and high SBPV were associated with an increased risk of mortality. The effects of GV and SBPV on in-hospital mortality were partially mediated by ventricular arrhythmias (18.0 % and 6.6 %, respectively). The risk of mortality gradually increased with the number of high-variability parameters and increasing variability scores. CONCLUSIONS: GV and SBPV have additive effects on the risk of mortality in patients with CAD hospitalized in the ICU. Ventricular arrhythmias partially mediate the effects of GV and SBPV on in-hospital mortality.

Maximum stress hyperglycemia ratio within the first 24 h of admission predicts mortality during and after the acute phase of acute coronary syndrome in patients with and without diabetes: A retrospective cohort study from the MIMIC-IV database.

AIMS: The stress hyperglycemia ratio (SHR) is significantly associated with short-term adverse cardiovascular events. However, the association between SHR and mortality after the acute phase of acute coronary syndrome (ACS) remains controversial. METHODS: This study used data from the Medical Information Mart for Intensive Care-IV database. Patients with ACS hospitalized in the intensive care unit (ICU) were retrospectively enrolled. RESULTS: A total of 2668 ACS patients were enrolled. The incidence of in-hospital and 1-year mortality was 4.7 % and 13.2 %, respectively. The maximum SHR had a higher prognostic value for predicting both in-hospital and 1-year mortality than the first SHR. Adding the maximum SHR to the SOFA score could significantly improve the prognostic prediction. In the landmark analysis at 30 days, the maximum SHR was a risk factor for mortality within 30 days regardless of whether patients had diabetes. However, it was no longer associated with mortality after 30 days in patients with diabetes after adjustment (HR = 1.237 per 1-point increment, 95 % CI 0.854-1.790). CONCLUSIONS: The maximum SHR was significantly associated with mortality in patients with ACS hospitalized in the ICU. However, caution is warranted if it is used for predicting mortality after 30 days in patients with diabetes.

A generic pump-free organ-on-a-chip platform for assessment of intestinal drug absorption.

Organ-on-a-chip technology has shown great potential in disease modeling and drug evaluation. However, traditional organ-on-a-chip devices are mostly pump-dependent with low throughput, which makes it difficult to leverage their advantages. In this study, we have developed a generic, pump-free organ-on-a-chip platform consisting of a 32-unit chip and an adjustable rocker, facilitating high-throughput dynamic cell culture with straightforward operation. By utilizing the rocker to induce periodic fluid forces, we can achieve fluidic conditions similar to those obtained with traditional pump-based systems. Through constructing a gut-on-a-chip model, we observed remarkable enhancements in the expression of barrier-associated proteins and the spatial distribution of differentiated intestinal cells compared to static culture. Furthermore, RNA sequencing analysis unveiled enriched pathways associated with cell proliferation, lipid transport, and drug metabolism, indicating the ability of the platform to mimic critical physiological processes. Additionally, we tested seven drugs that represent a range of high, medium, and low in vivo permeability using this model and found a strong correlation between their Papp values and human Fa, demonstrating the capability of this model for drug absorption evaluation. Our findings highlight the potential of this pump-free organ-on-a-chip platform as a valuable tool for advancing drug development and enabling personalized medicine.

Key Role of Vegetation Cover in Alleviating Microplastic-Enhanced Carbon Emissions.

Microplastics (MPs) are considered to influence fundamental biogeochemical processes, but the effects of plant residue-MP interactions on soil carbon turnover in urban greenspaces are virtually unknown. Here, an 84-day incubation experiment was constructed using four types of single-vegetation-covered soils (6 years), showing that polystyrene MP (PSMP) pollution caused an unexpectedly large increase in soil CO2 emissions. The additional CO2 originating from highly bioavailable active dissolved organic matter molecules (<380 °C, predominantly polysaccharides) was converted from persistent carbon (380-650 °C, predominantly aromatic compounds) rather than PSMP derivatives. However, the priming effect of PSMP derivatives was weakened in plant-driven soils (resistivity: shrub > tree > grass). This can be explained from two perspectives: (1) Plant residue-driven humification processes reduced the percentage of bioavailable active dissolved organic matter derived from the priming effects of PSMPs. (2) Plant residues accelerated bacterial community succession (dominated by plant residue types) but slowed fungal community demise (retained carbon turnover-related functional taxa), enabling specific enrichment of glycolysis, the citric acid cycle and the pentose phosphate pathway. These results provide a necessary theoretical basis to understand the role of plant residues in reducing PSMP harm at the ecological level and refresh knowledge about the importance of biodiversity for ecosystem stability.

Polygenic effects on brain functional endophenotype for deficit and non-deficit schizophrenia.

Deficit schizophrenia (DS) is a subtype of schizophrenia (SCZ). The polygenic effects on the neuroimaging alterations in DS still remain unknown. This study aims to calculate the polygenic risk scores for schizophrenia (PRS-SCZ) in DS, and further explores the potential associations with functional features of brain. PRS-SCZ was calculated according to the Whole Exome sequencing and Genome-wide association studies (GWAS). Resting-state fMRI, as well as biochemical features and neurocognitive data were obtained from 33 DS, 47 NDS and 41 HCs, and association studies of genetic risk with neuroimaging were performed in this sample. The analyses of amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo) and functional connectivity (FC) were performed to detect the functional alterations between DS and NDS. In addition, correlation analysis was used to investigate the relationships between functional features (ALFF, ReHo, FC) and PRS-SCZ. The PRS-SCZ of DS was significantly lower than that in NDS and HC. Compared to NDS, there was a significant increase in the ALFF of left inferior temporal gyrus (ITG.L) and left inferior frontal gyrus (IFG.L) and a significant decrease in the ALFF of right precuneus (PCUN.R) and ReHo of right middle frontal gyrus (MFG.R) in DS. FCs were widely changed between DS and NDS, mainly concentrated in default mode network, including ITG, PCUN and angular gyrus (ANG). Correlation analysis revealed that the ALFF of left ITG, the ReHo of right middle frontal gyrus, the FC value between insula and ANG, left ITG and right corpus callosum, left ITG and right PCUN, as well as the scores of Trail Making Test-B, were associated with PRS-SCZ in DS. The present study demonstrated the differential polygenic effects on functional changes of brain in DS and NDS, providing a potential neuroimaging-genetic perspective for the pathogenesis of schizophrenia.

Plasma oxidative stress marker levels related to functional brain abnormalities in first-episode drug-naive major depressive disorder.

Major Depressive Disorder (MDD) is marked by abnormal brain function and elevated plasma oxidative stress markers. The specific relationship between these factors in MDD remains unclear. In this study, we conducted resting-state fMRI scans on fifty-seven first-episode, drug-naive MDD patients and sixty healthy controls. Plasma levels of oxidative stress markers (superoxide dismutase (SOD) and glutathione reductase (GSR)) were assessed using ELISA. Our results revealed a positive correlation between plasma SOD and GSR levels in MDD patients and the amplitude of low-frequency fluctuation (ALFF) values in key brain regions-thalamus, anterior cingulate gyrus, and superior frontal gyrus. Further analysis indicated positive correlations between plasma SOD and GSR levels and specific ALFF values in MDD patients without suicidal ideation, with these correlations not significant in MDD patients with suicidal ideation. Additionally, seed-based whole-brain functional connectivity analysis demonstrated a negative correlation between plasma GSR levels and connectivity between the thalamus and insula, while plasma SOD levels showed a positive correlation with connectivity between the thalamus and precuneus. These findings contribute to our understanding of MDD's pathophysiology and heterogeneity, highlighting the association between plasma oxidative stress markers and functional abnormalities in diverse brain regions.

Individualized Texture Similarity Network in Schizophrenia.

BACKGROUND: Structural covariance network disruption has been considered an important pathophysiological indicator for schizophrenia. Here, we introduced a novel individualized structural covariance network measure, referred to as a texture similarity network (TSN), and hypothesized that the TSN could reliably reveal unique intersubject heterogeneity and complex dysconnectivity patterns in schizophrenia. METHODS: The TSN was constructed by measuring the covariance of 180 three-dimensional voxelwise gray-level co-occurrence matrix feature maps between brain areas in each participant. We first tested the validity and reproducibility of the TSN in characterizing the intersubject variability in 2 longitudinal test-retest healthy cohorts. The TSN was further applied to elucidate intersubject variability and dysconnectivity patterns in 10 schizophrenia case-control datasets (609 schizophrenia cases vs. 579 controls) as well as in a first-episode depression dataset (69 patients with depression vs. 69 control participants). RESULTS: The test-retest analysis demonstrated higher TSN intersubject than intrasubject variability. Moreover, the TSN reliably revealed higher intersubject variability in both chronic and first-episode schizophrenia, but not in depression. The TSN also reproducibly detected coexistent increased and decreased TSN strength in widespread brain areas, increased global small-worldness, and the coexistence of both structural hyposynchronization in the central networks and hypersynchronization in peripheral networks in patients with schizophrenia but not in patients with depression. Finally, aberrant intersubject variability and covariance strength patterns revealed by the TSN showed a missing or weak correlation with other individualized structural covariance network measures, functional connectivity, and regional volume changes. CONCLUSIONS: These findings support the reliability of a TSN in revealing unique structural heterogeneity and complex dysconnectivity in patients with schizophrenia.

Cheese consumption on atherosclerosis, atherosclerotic cardiovascular diseases and its complications: A two-sample Mendelian randomization study.

BACKGROUND AND AIM: Evidence from prospective cohort studies has revealed an inverse association between cheese consumption and the development of atherosclerosis (AS), atherosclerotic cardiovascular diseases (ASCVD), and their complications. However, it remains unclear whether this observed association is influenced by potential confounding factors that may arise during the long-term development process of AS, ASCVD, and its complications. Therefore, to further clarify the causal relationship between cheese consumption and AS, ASCVD, and its complications, we conducted a two-sample Mendelian randomization (MR) analysis to explore the causal association between cheese intake and the aforementioned health outcomes. METHODS AND RESULTS: We employed a two-sample MR analysis based on publicly available genome-wide association studies (GWAS) to infer the causal relationship, with no overlap between their participating populations. The effect estimates were calculated using the random-effects inverse-variance-weighted method. Sensitivity analyses were conducted using Cochran's Q statistic, funnel plot, leave-one-out analysis, and MR-Egger intercept tests. The genetically predicted cheese intake was found to be associated with lower risks of coronary AS (odds ratio [OR] = 0.72, 95 % confidence interval [CI] 0.59-0.88, P = 0.001), peripheral vascular AS (OR = 0.56, 95 % CI 0.37-0.84, P = 0.006), other vascular AS (OR = 0.66, 95 % CI 0.44-0.99, P = 0.043), coronary artery disease (OR = 0.64, 95 % CI 0.56-0.74, P = 1.57e-09), angina pectoris (OR = 0.70, 95 % CI 0.58-0.84, P = 4.92e-05), myocardial infarction (OR = 0.63, 95 % CI 0.52-0.77, P = 3.56e-06), heart failure (OR = 0.62, 0.49-0.79, P = 1.20e-04), total ischemic stroke (OR = 0.76, 95 % CI 0.63-0.91, P = 0.003), peripheral artery disease (OR = 0.64, 95 % CI 0.43-0.95, P = 0.028), and cognitive impairment (OR = 0.65, 95 % CI 0.56-0.74, P = 3.40e-10). However, no associations were observed for cerebrovascular AS, arrhythmia, cardiac death, ischemic stroke (large artery AS), ischemic stroke (small vessel), ischemic stroke (cardioembolic), and transient ischemic attack. CONCLUSION: This two-sample MR analysis reveals a causally inverse association between cheese intake and multi-vascular AS (including coronary AS, peripheral vascular AS, and other vascular AS), as well as multiple types of ASCVD and its complications (such as coronary artery disease, angina pectoris, myocardial infarction, heart failure, total ischemic stroke, and peripheral artery disease). The findings from this study may lay a stronger theoretical foundation and present new opportunities for the dietary management of future atherosclerotic cardiovascular diseases.

Sex-dependent phenological responses to climate vary across species' ranges.

Anthropogenic climate change has significantly altered the flowering times (i.e., phenology) of plants worldwide, affecting their reproduction, survival, and interactions. Recent studies utilizing herbarium specimens have uncovered significant intra- and inter-specific variation in flowering phenology and its response to changes in climate but have mostly been limited to animal-pollinated species. Thus, despite their economic and ecological importance, variation in phenological responses to climate remain largely unexplored among and within wind-pollinated dioecious species and across their sexes. Using both herbarium specimens and volunteer observations of cottonwood (Populus) species, we examined how phenological sensitivity to climate varies across species, their ranges, sexes, and phenophases. The timing of flowering varied significantly across and within species, as did their sensitivity to spring temperature. In particular, male flowering generally happened earlier in the season and was more sensitive to warming than female flowering. Further, the onset of flowering was more sensitive to changes in temperature than leaf out. Increased temporal gaps between male and female flowering time and between the first open flower date and leaf out date were predicted for the future under two climate change scenarios. These shifts will impact the efficacy of sexual reproduction and gene flow among species. Our study demonstrates significant inter- and intra-specific variation in phenology and its responses to environmental cues, across species' ranges, phenophases, and sex, in wind-pollinated species. These variations need to be considered to predict accurately the effects of climate change and assess their ecological and evolutionary consequences.

Genome-wide association study of hippocampal blood-oxygen-level-dependent-cerebral blood flow correlation in Chinese Han population.

Correlation between blood-oxygen-level-dependent (BOLD) and cerebral blood flow (CBF) has been used as an index of neurovascular coupling. Hippocampal BOLD-CBF correlation is associated with neurocognition, and the reduced correlation is associated with neuropsychiatric disorders. We conducted the first genome-wide association study of the hippocampal BOLD-CBF correlation in 4,832 Chinese Han subjects. The hippocampal BOLD-CBF correlation had an estimated heritability of 16.2-23.9% and showed reliable genome-wide significant association with a locus at 3q28, in which many variants have been linked to neuroimaging and cerebrospinal fluid markers of Alzheimer's disease. Gene-based association analyses showed four significant genes (GMNC, CRTC2, DENND4B, and GATAD2B) and revealed enrichment for mast cell calcium mobilization, microglial cell proliferation, and ubiquitin-related proteolysis pathways that regulate different cellular components of the neurovascular unit. This is the first unbiased identification of the association of hippocampal BOLD-CBF correlation, providing fresh insights into the genetic architecture of hippocampal neurovascular coupling.

Glycosylation Contributes to Thermostability and Proteolytic Resistance of rFIP-nha (Nectria haematococca).

Glycosylation is an important post-translational modification of proteins, contributing to protein function, stability and subcellular localization. Fungal immunomodulatory proteins (FIPs) are a group of small proteins with notable immunomodulatory activity, some of which are glycoproteins. In this study, the impact of glycosylation on the bioactivity and biochemical characteristics of FIP-nha (from Nectria haematococca) is described. Three rFIP-nha glycan mutants (N5A, N39A, N5+39A) were constructed and expressed in Pichia pastoris to study the functionality of the specific N-glycosylation on amino acid N5 and N39. Their protein characteristics, structure, stability and activity were tested. WT and mutants all formed tetramers, with no obvious difference in crystal structures. Their melting temperatures were 82.2 °C (WT), 81.4 °C (N5A), 80.7 °C (N39A) and 80.1 °C (N5+39A), indicating that glycosylation improves thermostability of rFIP-nha. Digestion assays showed that glycosylation on either site improved pepsin resistance, while 39N-glycosylation was important for trypsin resistance. Based on the 3D structure and analysis of enzyme cleavage sites, we conclude that glycosylation might interfere with hydrolysis via increasing steric hindrance. WT and mutants exerted similar bioactivity on tumor cell metabolism and red blood cells hemagglutination. Taken together, these findings indicate that glycosylation of FIP-nha impacts its thermostability and digestion resistance.

Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia.

BACKGROUND: Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated. METHODS: A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively. RESULTS: Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen's Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western). CONCLUSIONS: These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.

MRAß: A multimodal MRI-derived amyloid-ß biomarker for Alzheimer's disease.

Florbetapir 18 F (AV45), a highly sensitive and specific positron emission tomographic (PET) molecular biomarker binding to the amyloid-ß of Alzheimer's disease (AD), is constrained by radiation and cost. We sought to combat it by combining multimodal magnetic resonance imaging (MRI) images and a collaborative generative adversarial networks model (CollaGAN) to develop a multimodal MRI-derived Amyloid-ß (MRAß) biomarker. We collected multimodal MRI and PET AV45 data of 380 qualified participants from the ADNI dataset and 64 subjects from OASIS3 dataset. A five-fold cross-validation CollaGAN were applied to generate MRAß. In the ADNI dataset, we found MRAß could characterize the subject-level AV45 spatial variations in both AD and mild cognitive impairment (MCI). Voxel-wise two-sample t-tests demonstrated amyloid-ß depositions identified by MRAß in AD and MCI were significantly higher than healthy controls (HCs) in widespread cortices (p < .05, corrected) and were much similar to those by AV45 (r > .92, p < .001). Moreover, a 3D ResNet classifier demonstrated that MRAß was comparable to AV45 in discriminating AD from HC in both the ADNI and OASIS3 datasets, and in discriminate MCI from HC in ADNI. Finally, we found MRAß could mimic cortical hyper-AV45 in HCs who later converted to MCI (r = .79, p < .001) and was comparable to AV45 in discriminating them from stable HC (p > .05). In summary, our work illustrates that MRAß synthesized by multimodal MRI could mimic the cerebral amyloid-ß depositions like AV45 and lends credence to the feasibility of advancing MRI toward molecular-explainable biomarkers.