Brain function abnormalities and neuroinflammation in people living with HIV-associated anxiety disorders

BackgroundPeople living with HIV (PLWH) exhibits an increased susceptibility to anxiety disorders, concomitant with heightened vulnerability to aberrant immune activation and inflammatory responses, and endocrine dysfunction. There exists a dearth of scholarly investigations pertaining to the neurological, immune, and endocrine dimensions of HIV-associated anxiety disorders.MethodThis study aimed to compare a group of 16 individuals diagnosed with HIV-associated anxiety disorders (HIV ANXs) according to the Diagnostic and statistical manual of mental disorders (5th ed.), with a HIV individual control group (HIV control) of 49 PLWH without mental disorders. Muti-modal magnetic resonance was employed to assess the brain function and structure of both groups. Seed-based functional connectivity (FC) was used to assess the regional intrinsic brain activity and the influence of regional disturbances on FC with other brain regions. Peripheral blood cytokines and chemokines concentrations were measured using liquid chip and ELISA.ResultsAmplitude of low-frequency fluctuations in the right inferior temporal gyrus (ITG) was increased. There is a significant decreased regional homogeneity in HIV ANXs in the right superior occipital gyrus (SOG). The right ITG and the right SOG were separately set as the seed brain region of interest (ROI 1 and ROI 2) to be analyzed the FC. FC decreased in HIV ANXs between ROI1 and the right middle occipital gyrus, the right SOG, FC between ROI2 and left ITG increased in HIV ANXs. No significant structural difference was found between two groups. Pro-inflammatory chemokines showed higher levels in the HIV ANXs. Pro-inflammatory cytokines, neurotrophic factors, and endocrine factors were significantly correlated with alterations in brain function.ConclusionThis study suggests that patients with HIV-associated anxiety disorders may exhibit abnormalities in neurologic, immune, and endocrine functioning. Consequently, it is imperative to implement additional screening and intervention measures for anxiety disorders among PLWH

Pathological proliferation: a potential mechanism for poor CD4+ T cell recovery in people living with HIV

BackgroundPeople living with HIV (PLWH) fail to achieve normalization of CD4+ T cell counts and function, especially in immunological non-responders (INRs). The frequencies of Ki67+CD4+ T cells were inversely associated with CD4+ T cell counts in HIV infected patients. Early ART did not normalize CD4+ T cell proliferation. However, the features of the abnormal proliferation CD4+ T cell in INRs are far from known.MethodPLWH were divided into INRs (n= 16) and immunological responders (IRs, n= 53) groups. Mass cytometry was applied to peripheral blood T cells to profile the immune cells and liquid chip technique was used to measure plasma levels of cytokines and chemokines. Correlation analyses were conducted to evaluate associations between the degree of CD4+ T cell proliferation and immune function.ResultsThe percentage of Ki67+ CD4+ T cells were significant higher in INRs, and we defined these cells with significant higher level of Ki67, as over-proliferating cells. No significant difference of markers’ expression (HLA-DR, CD38, CD57, PD-1, PD-L1, CD107a, perforin) was found between INRs and IRs. Compared with naïve CD4+ T cells in INRs, Ki67+ CD4+ T cells exhibited lower levels of CD57 and CD38. Whereas Ki67+ T cells exhibited higher levels of CD38 and CD57 and activation compared with differentiated mature central memory CD4+ T cells and effector memory CD4+ T cells. Ki67+ cells did not show higher levels of senescence and activation compared to certain Ki67- CD4+ central memory T cells in IRs. Furthermore, Ki67+ CD4+ Tcm cells exhibited positive correlations with pro-inflammatory cytokines.ConclusionWe proposed and validated the hypothesis of “pathological proliferation” in INRs: excessive proliferation of CD4+ T cells in INRs may be accompanied by aberrant activation, senescence and loss of immune function. Eventually, such over-proliferating but poor-quality cells in INRs result in incomplete recovery of both CD4+ T cell counts and function. An intervention that enhancing the proliferative capacity or functional ability or both of CD4+ T cell in INRs might therefore be beneficial

Comprehensive analysis of the cuproptosis-related gene DLD across cancers: A potential prognostic and immunotherapeutic target

DLD is a key gene involved in “cuproptosis,” but its roles in tumor progression and immunity remain unclear. Exploring the potential mechanisms and biological roles of DLD may provide new insights for therapeutic strategies for tumors. In the present study, we analyzed the role of DLD in a variety of tumors by using several bioinformatic tools. The results showed that compared with normal tissues, tumor tissues representing multiple cancers showed significant differential expression of DLD. High DLD expression was associated with a good prognosis in BRCA, KICH, and LUAD. Conversely, high expression levels of DLD were detrimental to patient prognosis in many other tumors, such as COAD, KIRC, and KIRP. In addition, the associations of DLD with infiltrating immune cells, genetic alterations and methylation levels across cancers were assessed. Aberrant expression of DLD was positively correlated with most infiltrating immune cells, especially neutrophils. The DLD methylation level was significantly decreased in COAD, LIHC, and LUSC but significantly increased in BRCA. DLD had the highest mutation rate (6.04%) in ESCA. In LUSC, patients with genetic alterations in DLD showed a poorer prognosis. At the single-cell level, the roles of DLD in regulating cancer-associated biological functions, such as metastasis, inflammation, and differentiation, were explored. Afterward, we further investigated whether several disease-associated genes could be correlated with DLD. GO enrichment analysis indicated that DLD-related genes were mainly associated with mitochondria-related cellular components, aerobic respiration and the tricarboxylic acid cycle. Finally, the correlations between DLD expression and immunomodulatory genes, immune checkpoints, and sensitivity to some antitumor drugs were investigated. It is worth noting that DLD expression was positively correlated with immune checkpoint genes and immunomodulatory genes in most cancers. In conclusion, this study comprehensively analyzed the differential expression, prognostic value and immune cell infiltration-related function of DLD across cancers. Our results suggest that DLD has great potential to serve as a candidate marker for pancancer prognosis and immunotherapy and may provide a new direction for cancer treatment development

Impact of biogenic SOA loading on the molecular composition of wintertime PM2.5 in urban Tianjin: an insight from Fourier transform ion cyclotron resonance mass spectrometry

Biomass burning is one of the key sources of urban aerosols in the North China Plain, especially in winter when the impact of secondary organic aerosols (SOA) formed from biogenic volatile organic compounds (BVOCs) is generally considered to be minor. However, little is known about the influence of biogenic SOA loading on the molecular composition of wintertime organic aerosols. Here, we investigated the water-soluble organic compounds in fine particles (PM2.5) from urban Tianjin by ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Our results show that most of the CHO and CHON compounds were derived from biomass burning; they contain O-poor and highly unsaturated compounds with aromatic rings, which are sensitive to photochemical reactions, and some of which probably contribute to light-absorbing chromophores. Under moderate to high SOA loading conditions, the nocturnal chemistry is more efficient than photooxidation to generate secondary CHO and CHON compounds with high oxygen content. Under low SOA-loading, secondary CHO and CHON compounds with low oxygen content are mainly formed by photochemistry. Secondary CHO compounds are mainly derived from oxidation of monoterpenes. But nocturnal chemistry may be more productive to sesquiterpene-derived CHON compounds. In contrast, the number- and intensity-weight of S-containing groups (CHOS and CHONS) increased significantly with the increase of biogenic SOA-loading, which agrees with the fact that a majority of the S-containing groups are identified as organosulfates and nitrooxy-organosulfates that are derived from the oxidation of BVOCs. Terpenes may be potential major contributors to the chemical diversity of organosulfates and nitrooxy-organosulfates under photo-oxidation. While the nocturnal chemistry is more beneficial to the formation of organosulfates and nitrooxy-organosulfates under low SOA-loading. The SOA-loading is an important factor associating with the oxidation degree, nitrate group content and chemodiversity of nitrooxy-organosulfates. Furthermore, our study suggests that the hydrolysis of nitrooxy-organosulfates is a possible pathway for the formation of organosulfates.</p

Deep learning-based polygenic risk analysis for Alzheimer's disease prediction

BACKGROUND: The polygenic nature of Alzheimer's disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual's genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk. METHODS: We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model. RESULTS: The deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms. CONCLUSION: Our results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms

Alternative strategies of nutrient acquisition and energy conservation map to the biogeography of marine ammonia-oxidizing archaea

Ammonia-oxidizing archaea (AOA) are among the most abundant and ubiquitous microorganisms in the ocean, exerting primary control on nitrification and nitrogen oxides emission. Although united by a common physiology of chemoautotrophic growth on ammonia, a corresponding high genomic and habitat variability suggests tremendous adaptive capacity. Here, we compared 44 diverse AOA genomes, 37 from species cultivated from samples collected across diverse geographic locations and seven assembled from metagenomic sequences from the mesopelagic to hadopelagic zones of the deep ocean. Comparative analysis identified seven major marine AOA genotypic groups having gene content correlated with their distinctive biogeographies. Phosphorus and ammonia availabilities as well as hydrostatic pressure were identified as selective forces driving marine AOA genotypic and gene content variability in different oceanic regions. Notably, AOA methylphosphonate biosynthetic genes span diverse oceanic provinces, reinforcing their importance for methane production in the ocean. Together, our combined comparative physiological, genomic, and metagenomic analyses provide a comprehensive view of the biogeography of globally abundant AOA and their adaptive radiation into a vast range of marine and terrestrial habitats

The microbial dark matter and “wanted list” in worldwide wastewater treatment plants

Abstract Background Wastewater treatment plants (WWTPs) are one of the largest biotechnology applications in the world and are of critical importance to modern urban societies. An accurate evaluation of the microbial dark matter (MDM, microorganisms whose genomes remain uncharacterized) proportions in WWTPs is of great value, while there is no such research yet. This study conducted a global meta-analysis of MDM in WWTPs with 317,542 prokaryotic genomes from the Genome Taxonomy Database and proposed a “wanted list” for priority targets in further investigations of activated sludge. Results Compared with the Earth Microbiome Project data, WWTPs had relatively lower genome-sequenced proportions of prokaryotes than other ecosystems, such as the animal related environments. Analysis showed that the median proportions of the genome-sequenced cells and taxa (100% identity and 100% coverage in 16S rRNA gene region) in WWTPs reached 56.3% and 34.5% for activated sludge, 48.6% and 28.5% for aerobic biofilm, and 48.3% and 28.5% for anaerobic digestion sludge, respectively. This result meant MDM had high proportions in WWTPs. Besides, all of the samples were occupied by a few predominant taxa, and the majority of the sequenced genomes were from pure cultures. The global-scale “wanted list” for activated sludge contained four phyla that have few representatives and 71 operational taxonomic units with the majority of them having no genome or isolate yet. Finally, several genome mining methods were verified to successfully recover genomes from activated sludge such as hybrid assembly of the second- and third-generation sequencing. Conclusions This work elucidated the proportion of MDM in WWTPs, defined the “wanted list” of activated sludge for future investigations, and certified potential genome recovery methods. The proposed methodology of this study can be applied to other ecosystems and improve understanding of ecosystem structure across diverse habitats. Video Abstrac

Cytostatic gene therapy for occlusive vascular disease Read More: http://informahealthcare.com/doi/abs/10.1517/13543776.16.4.507

16 páginas.-- El documento en word es la versión post-print.The formation of occlusive vascular lesions during the course of atherosclerosis, in-stent restenosis, transplant vasculopathy and vessel graft failure is a chronic inflammatory process characterised by excessive cellular proliferation within the injured artery wall. Therefore, candidate targets for the treatment of vasculoproliferative disease include cell cycle regulatory factors, such as cyclin-dependent kinases (CDKs), cyclins, CDK inhibitory proteins (CKIs), tumour suppressors, growth factors and their receptors, and transcription factors involved in cell cycle control. Although several genetically-modified mouse models have conclusively demonstrated that increased cell proliferation aggravates atheroma development, the potential benefit of cytostatic strategies for the treatment of atherosclerosis in the clinic is doubtful because human atherosclerosis is often diagnosed at advanced stages when neointimal proliferation appears low or absent. In contrast, restenosis and graft atherosclerosis appear amenable for cytostatic strategies because neointimal lesions typically develop over a short period of time after revascularisation (e.g., 2 – 12 months) and are localised at the site of the intervention. Vascular interventions, both endovascular and open surgical, allow minimally invasive, easily monitored gene delivery. In this review, the preclinical studies and clinical trials utilising cytostatic gene therapy for occlusive vascular disease will be discussed.Peer reviewe

Privacy-preserving voluntary-tallying leader election for internet of things

The Internet of Things (IoT) is commonly deployed with devices of limited power and computation capability. A centralized IoT architecture provides a simplified management for IoT system but brings redundancy by the unnecessary data traffic with a data center. A decentralized IoT reduces the cost on data traffic and is resilient to the single-point-of-failure. The blockchain technique has attracted a large amount of research, which is redeemed as a perspective of decentralized IoT system infrastructure. It also brings new privacy challenges for that the blockchain is a public ledger of all digital events executed and shared among all participants. The decentralized IoT system relies on the leader election deeply to implement the decentralized communications among the distributed nodes. The conventional leader election must have a centralized authority, contrasting to the decentralization. As an alternative, self-tallying type schemes have been proposed in the literature for decentralized systems. These schemes suffer from adaptive and abortive issues. Also, some additional factors should be considered, such as the availability of candidate nodes. If the candidate node is unavailable after the voting phase due to being offline or ongoing tasks, the next available candidate should be elected. To accommodate such a need, in this paper, we propose a new leader election paradigm called voluntary-tallying leader election, which achieves the core requirements such as ballet secrecy, voter privacy and the additional feature of voluntary-tallying. We formalize the system and security models for this new election paradigm and present a secure and practical construction

Maximizing energy efficiency for multiple DF relay system with QoS constraint

Multiple relays assisted transmission is an effective way to enhance the reliability of wireless communication network. However multiple relays joining in the transmission costs more energy and may reduce the energy efficiency of the system. In this paper, we investigate the energy efficiency performance of multiple decode-and-forward relays system under a quality of service constraint. In particular, we study a feedback-limited scenario where only the knowledge of average channel gain is available at the source. First, we define a tradeoff factor and based on it design a tradeoff mechanism between energy efficiency and outage probability. Second, we prove that the energy efficiency of the system is a piecewise strictly monotonic function of our tradeoff factor and has only one extreme value which is the global maximum. Third, by means of simulation we show that the numerical results perfectly match our theoretical analysis. In addition, we show that energy efficiency can achieve the extreme value under the loose QoS constraint.QC 20140102</p