The posterior hippocampus (pHp) plays a major role in the processing and storage of drug-related cues and is linked to striatal-limbic brain circuits involved with craving and drug salience. We have recently reported that increased basal regional cerebral blood flow (rCBF) in a pHp loci, as measured by pseudo-continuous arterial spin labeling magnetic resonance imaging, predicted days to cocaine relapse following residential treatment. In this secondary analysis, we explored whether rCBF in this same pHp region would successfully predict 30-day point prevalence abstinence 60 days following residential treatment in an independent group of previously studied participants with cocaine dependence. rCBF was assessed with single photon emission computerized tomography during a saline infusion in 21 cocaine dependence and 22 healthy control participants. pHp rCBF was significantly higher in those endorsing substance use (n = 10) relative to both abstinent (n = 11) (p < 0.001) and control (p < 0.05) participants. There were no significant differences in measured demographic or clinical variables between the actively using and non-using participants. This replicative finding suggests that heightened pHp activation is a significant predictor of substance use in cocaine-dependent individuals, possibly reflecting a neural susceptibility to continued drug cues.

Metagenomics yields enormous numbers of microbial sequences that can be assigned a metabolic function. Using such data to infer community-level metabolic divergence is hindered by the lack of a suitable statistical framework. Here, we describe a novel hierarchical Bayesian model, called BiomeNet (Bayesian inference of metabolic networks), for inferring differential prevalence of metabolic subnetworks among microbial communities. To infer the structure of community-level metabolic interactions, BiomeNet applies a mixed-membership modelling framework to enzyme abundance information. The basic idea is that the mixture components of the model (metabolic reactions, subnetworks, and networks) are shared across all groups (microbiome samples), but the mixture proportions vary from group to group. Through this framework, the model can capture nested structures within the data. BiomeNet is unique in modeling each metagenome sample as a mixture of complex metabolic systems (metabosystems). The metabosystems are composed of mixtures of tightly connected metabolic subnetworks. BiomeNet differs from other unsupervised methods by allowing researchers to discriminate groups of samples through the metabolic patterns it discovers in the data, and by providing a framework for interpreting them. We describe a collapsed Gibbs sampler for inference of the mixture weights under BiomeNet, and we use simulation to validate the inference algorithm. Application of BiomeNet to human gut metagenomes revealed a metabosystem with greater prevalence among inflammatory bowel disease (IBD) patients. Based on the discriminatory subnetworks for this metabosystem, we inferred that the community is likely to be closely associated with the human gut epithelium, resistant to dietary interventions, and interfere with human uptake of an antioxidant connected to IBD. Because this metabosystem has a greater capacity to exploit host-associated glycans, we speculate that IBD-associated communities might arise from opportunist growth of bacteria that can circumvent the host's nutrient-based mechanism for bacterial partner selection.

Recent imaging connectomics studies have demonstrated that the spontaneous human brain functional networks derived from resting-state functional MRI (R-fMRI) include many non-trivial topological properties, such as highly efficient small-world architecture and densely connected hub regions. However, very little is known about dynamic functional connectivity (D-FC) patterns of spontaneous human brain networks during rest and about how these spontaneous brain dynamics are constrained by the underlying structural connectivity. Here, we combined sub-second multiband R-fMRI data with graph-theoretical approaches to comprehensively investigate the dynamic characteristics of the topological organization of human whole-brain functional networks, and then employed diffusion imaging data in the same participants to further explore the associated structural substrates. At the connection level, we found that human whole-brain D-FC patterns spontaneously fluctuated over time, while homotopic D-FC exhibited high connectivity strength and low temporal variability. At the network level, dynamic functional networks exhibited time-varying but evident small-world and assortativity architecture, with several regions (e.g., insula, sensorimotor cortex and medial prefrontal cortex) emerging as functionally persistent hubs (i.e., highly connected regions) while possessing large temporal variability in their degree centrality. Finally, the temporal characteristics (i.e., strength and variability) of the connectional and nodal properties of the dynamic brain networks were significantly associated with their structural counterparts. Collectively, we demonstrate the economical, efficient, and flexible characteristics of dynamic functional coordination in large-scale human brain networks during rest, and highlight their relationship with underlying structural connectivity, which deepens our understandings of spontaneous brain network dynamics in humans.

Resting-state fMRI studies have increasingly focused on multi-contrast techniques, such as BOLD and ASL imaging. However, these techniques may reveal different aspects of brain activity (e.g., static vs. dynamic), and little is known about the similarity or disparity of these techniques in detecting resting-state brain activity. It is therefore important to assess the static and dynamic characteristics of these fMRI techniques to guide future applications. Here we acquired fMRI data while subjects were in eyes-closed (EC) and eyes-open (EO) states, using both ASL and BOLD techniques, at two research centers (NIDA and HNU). Static brain activity was calculated as voxel-wise mean cerebral blood flow (CBF) using ASL, i.e., CBF-mean, while dynamic activity was measured by the amplitude of low frequency fluctuations (ALFF) of BOLD, i.e., BOLD-ALFF, at both NIDA and HNU, and CBF, i.e., CBF-ALFF, at NIDA. We showed that mean CBF was lower under EC than EO in the primary visual cortex, while BOLD-ALFF was higher under EC in the primary somatosensory cortices extending to the primary auditory cortices and lower in the lateral occipital area. Interestingly, mean CBF and BOLD-ALFF results overlapped at the visual cortex to a very small degree. Importantly, these findings were largely replicated by the HNU dataset. State differences found by CBF-ALFF were located in the primary auditory cortices, which were generally a subset of BOLD-ALFF and showed no spatial overlap with CBF-mean. In conclusion, static brain activity measured by mean CBF and dynamic brain activity measured by BOLD- and CBF-ALFF may reflect different aspects of resting-state brain activity and a combination of ASL and BOLD may provide complementary information on the biophysical and physiological processes of the brain.

The insula, a cortical region that integrates heterogeneous signals about internal states and contributes to executive functions, has been implicated as an important role in the maintenance of nicotine dependence. Previous studies have indicated that insula damage may contribute to quitting smoking successfully, but few studies have examined whether quitting successfully is related to cortical structural integrity of insular subregions before smoking cessation treatment. Moreover, although prior researches have shown group differences in insular cortex structure in chronic cigarette smokers compared to nonsmokers, less is known about how cortical structural integrity of insular subregions relate to smoking behaviors in smokers. This study, therefore, aimed to (1) further explore the association between the cortical structural integrity of insular subregions prior to the target quit date and the treatment outcomes of smoking cessation therapy; and (2) further evaluate how the cortical structural integrity of insular subregions are related to smoking behaviors. In the present study, a total of 83 smokers and 41 nonsmokers were enrolled and high-resolution structural magnetic resonance images were acquired from all participants. After a 12-week smoking cessation treatment, 28 smokers succeeded in quitting smoking, 46 failed, and 9 were unable to be contacted. Our analysis showed that gray-matter volume of bilateral anterior insula were negatively correlated with nicotine dependence scores. However, the smoking cessation outcomes showed no correlations with the gray-matter volume and seed-based structural covariance network of insular subregions prior to smoking cessation. The present study further clarified the more precise roles of the insular cortex in smoking behaviors, which might improve the understanding of the mechanism in the nicotine dependence.

Bamboo is one of the most important nontimber forestry products worldwide. However, a chromosome-level reference genome is lacking, and an evolutionary view of alternative splicing (AS) in bamboo remains unclear despite emerging omics data and improved technologies.

The deprivation of sensory input after hearing damage results in functional reorganization of the brain including cross-modal plasticity in the sensory cortex and changes in cognitive processing. However, it remains unclear whether partial deprivation from unilateral auditory loss (UHL) would similarly affect the neural circuitry of cognitive processes in addition to the functional organization of sensory cortex. Here, we used resting-state functional magnetic resonance imaging to investigate intrinsic activity in 34 participants with UHL from acoustic neuroma in comparison with 22 matched normal controls. In sensory regions, we found decreased regional homogeneity (ReHo) in the bilateral calcarine cortices in UHL. However, there was an increase of ReHo in the right anterior insular cortex (rAI), the key node of cognitive control network (CCN) and multimodal sensory integration, as well as in the left parahippocampal cortex (lPHC), a key node in the default mode network (DMN). Moreover, seed-based resting-state functional connectivity analysis showed an enhanced relationship between rAI and several key regions of the DMN. Meanwhile, lPHC showed more negative relationship with components in the CCN and greater positive relationship in the DMN. Such reorganizations of functional connectivity within the DMN and between the DMN and CCN were confirmed by a graph theory analysis. These results suggest that unilateral sensory input damage not only alters the activity of the sensory areas but also reshapes the regional and circuit functional organization of the cognitive control network.

Machine learning techniques have been applied to resting-state fMRI data to predict neurological or neuropsychiatric disease states. Existing studies have used either a single type of resting-state feature or a few feature types (<4) in the prediction model. However, resting-state data can be processed in many different ways, yielding different feature types containing complementary and/or novel information, leaving uncertain the most informative features to provide to the classifier. In this study, multiple resting-state features were calculated from two main analytical categories: local measures and network measures. Feature selection was adopted using an optimized grid-search approach selecting top ranked features from statistical tests. We then tested three optimized frameworks: feature combination, kernel combination, and classifier combination, all using the support vector machine as an elementary classifier, to combine these resting-state feature types. When applied to nicotine addiction, with a cohort size of 100 smokers and 100 non-smokers, via a 10-fold cross-validation procedure, the feature combination and the classifier combination achieved an accuracy of 75.5%, while the kernel combination achieved a 73.0% accuracy; all three combination frameworks improved classification performance compared to the single feature type based results (best accuracy 70.5%). This study not only reveals the discriminative power of resting-state data, but also demonstrates the efficiency of combining multiple features from one data phenotype to improve classification performance.

To investigate whether single nucleotide polymorphisms (SNPs) in the vascular endothelial growth factor (VEGF) gene are associated with diabetic retinopathy (DR) in a cohort of Chinese patients with type 2 diabetes mellitus (T2DM).

(1) H magnetic resonance spectroscopy has demonstrated alterations in several neurometabolites in methamphetamine (METH)-dependent individuals in brain regions implicated in addiction. Yet, it is unclear whether these neurochemicals return to homeostatic levels after an individual abstains from drug use, a difficult question to address due to high recidivism and poor study retention in human subjects. We thus utilized a non-human primate model of addiction to explore the effects of long-term drug exposure and withdrawal on brain neurochemistry. Ten rhesus macaque monkeys on an active METH self-administration protocol (average use 4.6 ± 0.8 years, average daily intake between 0.4 and 1.2 mg/kg) and 10 age- and sex-matched drug-naive controls (CONT) served as subjects. Concentrations of several neurochemicals were evaluated at several timepoints following withdrawal from drug availability (10 monkeys at 1 week and 1 and 3 months, and 6 monkeys at 6 and 12 months; CONT examined at one timepoint). At 1 week following METH withdrawal, we found increases in myo-inositol in anterior cingulate cortex in the METH group relative to CONT. These alterations showed a linear pattern of decreased levels ('normalization') by 1 year of abstinence. We also found decreases in glutamine and Glx (composed mainly of glutamate and glutamine) in the caudate-putamen of the same animals at early withdrawal that showed a similar linear pattern of increasing concentration by 1 year. These results demonstrate that despite protracted, long-term use, neurochemical changes seen following long-term drug administration do not persist following prolonged abstinence, suggesting therapeutic effects of long-term withdrawal from drug use.

Utilizing a classic stroke model in rodents, middle cerebral artery occlusion (MCAo), we describe a novel neuroregenerative approach using the repeated intranasal administration of cocaine- and amphetamine-regulated transcript (CART) peptide starting from day 3 poststroke for enhancing the functional recovery of injured brain. Adult rats were separated into two groups with similar infarction sizes, measured by magnetic resonance imaging on day 2 after MCAo, and were treated with CART or vehicle. The CART treatment increased CART level in the brain, improved behavioral recovery, and reduced neurological scores. In the subventricular zone (SVZ), CART enhanced immunolabeling of bromodeoxyuridine, a neural progenitor cell marker Musashi-1, and the proliferating cell nuclear antigen, as well as upregulated brain-derived neurotrophic factor (BDNF) mRNA. AAV-GFP was locally applied to the SVZ to examine migration of SVZ cells. The CART enhanced migration of GFP(+) cells from SVZ toward the ischemic cortex. In SVZ culture, CART increased the size of neurospheres. The CART-mediated cell migration from SVZ explants was reduced by anti-BDNF blocking antibody. Using (1)H-MRS (proton magnetic resonance spectroscopy), increases in N-acetylaspartate levels were found in the lesioned cortex after CART treatment in stroke brain. Cocaine- and amphetamine-regulated transcript increased the expression of GAP43 and fluoro-ruby fluorescence in the lesioned cortex. In conclusion, our data suggest that intranasal CART treatment facilitates neuroregeneration in stroke brain.

The Cre/lox system is widely used in mice to achieve cell-type-specific gene expression. However, a strong and universally responding system to express genes under Cre control is still lacking. We have generated a set of Cre reporter mice with strong, ubiquitous expression of fluorescent proteins of different spectra. The robust native fluorescence of these reporters enables direct visualization of fine dendritic structures and axonal projections of the labeled neurons, which is useful in mapping neuronal circuitry, imaging and tracking specific cell populations in vivo. Using these reporters and a high-throughput in situ hybridization platform, we are systematically profiling Cre-directed gene expression throughout the mouse brain in several Cre-driver lines, including new Cre lines targeting different cell types in the cortex. Our expression data are displayed in a public online database to help researchers assess the utility of various Cre-driver lines for cell-type-specific genetic manipulation.

The thalamus and visual cortex are two key components associated with the alpha power of electroencephalography. However, their functional relationship remains to be elucidated. Here, we employ resting-state functional MRI to investigate the temporal correlations of spontaneous fluctuations between the thalamus [the whole thalamus and its three largest nuclei (bilateral mediodorsal, ventrolateral and pulvinar nuclei)] and visual cortex under both eyes open and eyes closed conditions. The whole thalamus show negative correlations with the visual cortex and positive correlations with its contralateral counterpart in eyes closed condition, but which are significantly decreased in eyes open condition, consistent with previous findings of electroencephalography desynchronization during eyes open resting state. Furthermore, we find that bilateral thalamic mediodorsal nuclei and bilateral ventrolateral nuclei have remarkably similar connectivity maps, and resemble to those of the whole thalamus, suggesting their crucial contributions to the thalamus-visual correlations. The bilateral pulvinar nuclei are found to show distinct functional connectivity patterns, compatible with previous findings of the asymmetry of anatomical and functional organization in the nuclei. Our data provides evidence for the associations of intrinsic spontaneous neuronal activity between the thalamus and visual cortex under different resting conditions, which might have implications on the understanding of the generation and modulation of the alpha rhythm.

Betulinic acid (BA) is a complex lupane triterpenoid with unique antineoplastic activity. However, its antiproliferative activity is far from satisfaction. In order to improve its anticancer efficacy, betulinic acid was conjugated with a nitric oxide (NO)-releasing moiety to get a novel hybrid, BA-78.

The relationship between clinical prognosis and transforming growth factor-β (TGF-β) receptor mutations in Chinese pediatric patients with idiopathic/hereditary pulmonary arterial hypertension (IPAH/HPAH) remains unclear. We retrospectively studied the clinical characteristics and outcomes of pediatric patients with IPAH/HPAH who visited our Hospital from September 2008 to December 2020. One hundred and five pediatric patients with IPAH/HPAH were included, 46 of whom carried TGF-β receptor mutations with a mean age at diagnosis of 82.8 ± 52.7 months, and 67 of them underwent right cardiac catheterization examinations and acute vasodilator testing. The result showed that mutation carriers demonstrated higher pulmonary vascular resistance (p = 0.012), higher right atrial pressure (p = 0.026), and lower cardiac index (p = 0.003). The 1-, 2-, and 3-year survival rates of mutation carriers were 79.4%, 61.5% and 55.6%, respectively, compared with 96.6%, 91.1%, and 85.4% for nonmutation carriers (p = 0.0001). The prognosis of mutation carriers was significantly worse than that of nonmutation carriers. TGF-β receptor gene mutation is an independent risk factor for death (p = 0.049, odd raito = 3.809, 95% confidence interval 1.006-14.429). In conclusion, TGF-β receptor mutation is an important genetic factor for the onset of IPAH/PAH in Chinese pediatric patients. Those who carrying TGF-β receptor mutations have a poor clinical prognosis. Therefore, TGF-β receptor gene screening for pediatric patients with PAH and more aggressive treatment for mutation carriers are recommended.

Cardiovascular disease is a leading cause of morbidity and mortality in individuals with Down syndrome. Congenital heart disease is the most common cardiovascular condition in this group, present in up to 50% of people with Down syndrome and contributing to poor outcomes. Additional factors contributing to cardiovascular outcomes include pulmonary hypertension; coexistent pulmonary, endocrine, and metabolic diseases; and risk factors for atherosclerotic disease. Moreover, disparities in the cardiovascular care of people with Down syndrome compared with the general population, which vary across different geographies and health care systems, further contribute to cardiovascular mortality; this issue is often overlooked by the wider medical community. This review focuses on the diagnosis, prevalence, and management of cardiovascular disease encountered in people with Down syndrome and summarizes available evidence in 10 key areas relating to Down syndrome and cardiac disease, from prenatal diagnosis to disparities in care in areas of differing resource availability. All specialists and nonspecialist clinicians providing care for people with Down syndrome should be aware of best clinical practice in all aspects of care of this distinct population.

Recent studies suggest that there is a potential connection between obstructive sleep apnea (OSA) and osteoporosis through dysregulation of bone metabolism. Orexin-A, a neuroprotective peptide secreted by the hypothalamus, is at a lower level in the plasma of OSA patients, which regulates appetite, energy expenditure and sleep-wake states. However, the protective effect of orexin-A on bone metabolism in OSA is unclear.

Centrosomal proteins are necessary components of the centrosome, a conserved eukaryotic organelle essential to the reproductive process. However, few centrosomal proteins have been genetically linked to fertility. Herein we identify a homozygous missense variant of CEP128 (c.665 G > A [p.R222Q]) in two infertile males. Remarkably, male homozygous knock-in mice harboring the orthologous CEP128R222Q variant show anomalies in sperm morphology, count, and motility. Moreover, Cep128 knock-out mice manifest male infertility associated with disrupted sperm quality. We observe defective sperm flagella in both homozygous Cep128 KO and KI mice; the cilia development in other organs is normal-suggesting that CEP128 variants predominantly affected the ciliogenesis in the testes. Mechanistically, CEP128 is involved in male reproduction via regulating the expression of genes and/or the phosphorylation of TGF-β/BMP-signalling members during spermatogenesis. Altogether, our findings unveil a crucial role for CEP128 in male fertility and provide important insights into the functions of centrosomal proteins in reproductive biology.

Despite that obesity is associated with many metabolic diseases, a significant proportion (10-30 %) of obese individuals is recognized as 'metabolically healthy obeses' (MHOs). The aim of the current study is to characterize the gut microbiome for MHOs as compared to 'metabolically unhealthy obeses' (MUOs). We compared the gut microbiome of 172 MHO and 138 MUO individuals from Chongqing (China) (inclined to eat red meat and food with a spicy taste), and performed validation with selected biomarkers in 40 MHOs and 33 MUOs from Quanzhou (China) (inclined to eat seafood and food with a light/bland taste). The genera Alistipes, Faecalibacterium and Odoribacter had increased abundance in both Chongqing and Quanzhou MHOs. We also observed different microbial functions in MUOs compared to MHOs, including an increased abundance of genes associated with glycan biosynthesis and metabolism. In addition, the microbial gene markers identified from the Chongqing cohort bear a moderate accuracy [AUC (area under the operating characteristic curve)=0.69] for classifying MHOs distinct from MUOs in the Quanzhou cohort. These findings indicate that gut microbiome is significantly distinct between MHOs and MUOs, implicating the potential of the gut microbiome in stratification and refined management of obesity.

Biological aging can be defined as a gradual loss of homeostasis across various aspects of molecular and cellular function. Aging is a complex and dynamic process which influences distinct cell types in a myriad of ways. The cellular architecture of the mammalian brain is heterogeneous and diverse, making it challenging to identify precise areas and cell types of the brain that are more susceptible to aging than others. Here, we present a high-resolution single-cell RNA sequencing dataset containing ~1.2 million high-quality single-cell transcriptomic profiles of brain cells from young adult and aged mice across both sexes, including areas spanning the forebrain, midbrain, and hindbrain. We find age-associated gene expression signatures across nearly all 130+ neuronal and non-neuronal cell subclasses we identified. We detect the greatest gene expression changes in non-neuronal cell types, suggesting that different cell types in the brain vary in their susceptibility to aging. We identify specific, age-enriched clusters within specific glial, vascular, and immune cell types from both cortical and subcortical regions of the brain, and specific gene expression changes associated with cell senescence, inflammation, decrease in new myelination, and decreased vasculature integrity. We also identify genes with expression changes across multiple cell subclasses, pointing to certain mechanisms of aging that may occur across wide regions or broad cell types of the brain. Finally, we discover the greatest gene expression changes in cell types localized to the third ventricle of the hypothalamus, including tanycytes, ependymal cells, and Tbx3+ neurons found in the arcuate nucleus that are part of the neuronal circuits regulating food intake and energy homeostasis. These findings suggest that the area surrounding the third ventricle in the hypothalamus may be a hub for aging in the mouse brain. Overall, we reveal a dynamic landscape of cell-type-specific transcriptomic changes in the brain associated with normal aging that will serve as a foundation for the investigation of functional changes in the aging process and the interaction of aging and diseases.