Decoding chromatin states by proteomic profiling of nucleosome readers.

DNA and histone modifications combine into characteristic patterns that demarcate functional regions of the genome1,2. While many 'readers' of individual modifications have been described3-5, how chromatin states comprising composite modification signatures, histone variants and internucleosomal linker DNA are interpreted is a major open question. Here we use a multidimensional proteomics strategy to systematically examine the interaction of around 2,000 nuclear proteins with over 80 modified dinucleosomes representing promoter, enhancer and heterochromatin states. By deconvoluting complex nucleosome-binding profiles into networks of co-regulated proteins and distinct nucleosomal features driving protein recruitment or exclusion, we show comprehensively how chromatin states are decoded by chromatin readers. We find highly distinctive binding responses to different features, many factors that recognize multiple features, and that nucleosomal modifications and linker DNA operate largely independently in regulating protein binding to chromatin. Our online resource, the Modification Atlas of Regulation by Chromatin States (MARCS), provides in-depth analysis tools to engage with our results and advance the discovery of fundamental principles of genome regulation by chromatin states.

asteRIa enables robust interaction modeling between chromatin modifications and epigenetic readers.

Chromatin, the nucleoprotein complex consisting of DNA and histone proteins, plays a crucial role in regulating gene expression by controlling access to DNA. Chromatin modifications are key players in this regulation, as they help to orchestrate DNA transcription, replication, and repair. These modifications recruit epigenetic 'reader' proteins, which mediate downstream events. Most modifications occur in distinctive combinations within a nucleosome, suggesting that epigenetic information can be encoded in combinatorial chromatin modifications. A detailed understanding of how multiple modifications cooperate in recruiting such proteins has, however, remained largely elusive. Here, we integrate nucleosome affinity purification data with high-throughput quantitative proteomics and hierarchical interaction modeling to estimate combinatorial effects of chromatin modifications on protein recruitment. This is facilitated by the computational workflow asteRIa which combines hierarchical interaction modeling, stability-based model selection, and replicate-consistency checks for a stable estimation of Robust Interactions among chromatin modifications. asteRIa identifies several epigenetic reader candidates responding to specific interactions between chromatin modifications. For the polycomb protein CBX8, we independently validate our results using genome-wide ChIP-Seq and bisulphite sequencing datasets. We provide the first quantitative framework for identifying cooperative effects of chromatin modifications on protein binding.

Atrial fibrillation: age at diagnosis, incident cardiovascular events, and mortality.

BACKGROUND AND AIMS: Patients with atrial fibrillation (AF) are at increased risks of cardiovascular diseases and mortality, but risks according to age at diagnosis have not been reported. This study investigated age-specific risks of outcomes among patients with AF and the background population. METHODS: This nationwide population-based cohort study included patients with AF and controls without outcomes by the application of exposure density matching on the basis of sex, year of birth, and index date. The absolute risks and hazard rates were stratified by age groups and assessed using competing risk survival analyses and Cox regression models, respectively. The expected differences in residual life years among participants were estimated. RESULTS: The study included 216 579 AF patients from year 2000 to 2020 and 866 316 controls. The mean follow-up time was 7.9 years. Comparing AF patients with matched controls, the hazard ratios among individuals ≤50 years was 8.90 [95% confidence interval (CI), 7.17-11.0] for cardiomyopathy, 8.64 (95% CI, 7.74-9.64) for heart failure, 2.18 (95% CI, 1.89-2.52) for ischaemic stroke, and 2.74 (95% CI, 2.53-2.96) for mortality. The expected average loss of life years among individuals ≤50 years was 9.2 years (95% CI, 9.0-9.3) years. The estimates decreased with older age. CONCLUSIONS: The findings show that earlier diagnosis of AF is associated with a higher hazard ratio of subsequent myocardial disease and shorter life expectancy. Further studies are needed to determine causality and whether AF could be used as a risk marker among particularly younger patients.

Impact of doping on the mechanical properties of conjugated polymers.

Conjugated polymers exhibit a unique portfolio of electrical and electrochemical behavior, which - paired with the mechanical properties that are typical for macromolecules - make them intriguing candidates for a wide range of application areas from wearable electronics to bioelectronics. However, the degree of oxidation or reduction of the polymer can strongly impact the mechanical response and thus must be considered when designing flexible or stretchable devices. This tutorial review first explores how the chain architecture, processing as well as the resulting nano- and microstructure impact the rheological and mechanical properties. In addition, different methods for the mechanical characterization of thin films and bulk materials such as fibers are summarized. Then, the review discusses how chemical and electrochemical doping alter the mechanical properties in terms of stiffness and ductility. Finally, the mechanical response of (doped) conjugated polymers is discussed in the context of (1) organic photovoltaics, representing thin-film devices with a relatively low charge-carrier density, (2) organic thermoelectrics, where chemical doping is used to realize thin films or bulk materials with a high doping level, and (3) organic electrochemical transistors, where electrochemical doping allows high charge-carrier densities to be reached, albeit accompanied by significant swelling. In the future, chemical and electrochemical doping may not only allow modulation and optimization of the electrical and electrochemical behavior of conjugated polymers, but also facilitate the design of materials with a tunable mechanical response.

Scaffold Matcher: A CMA-ES based algorithm for identifying hotspot aligned peptidomimetic scaffolds.

The design of protein interaction inhibitors is a promising approach to address aberrant protein interactions that cause disease. One strategy in designing inhibitors is to use peptidomimetic scaffolds that mimic the natural interaction interface. A central challenge in using peptidomimetics as protein interaction inhibitors, however, is determining how best the molecular scaffold aligns to the residues of the interface it is attempting to mimic. Here we present the Scaffold Matcher algorithm that aligns a given molecular scaffold onto hotspot residues from a protein interaction interface. To optimize the degrees of freedom of the molecular scaffold we implement the covariance matrix adaptation evolution strategy (CMA-ES), a state-of-the-art derivative-free optimization algorithm in Rosetta. To evaluate the performance of the CMA-ES, we used 26 peptides from the FlexPepDock Benchmark and compared with three other algorithms in Rosetta, specifically, Rosetta's default minimizer, a Monte Carlo protocol of small backbone perturbations, and a Genetic algorithm. We test the algorithms' performance on their ability to align a molecular scaffold to a series of hotspot residues (i.e., constraints) along native peptides. Of the 4 methods, CMA-ES was able to find the lowest energy conformation for all 26 benchmark peptides. Additionally, as a proof of concept, we apply the Scaffold Match algorithm with CMA-ES to align a peptidomimetic oligooxopiperazine scaffold to the hotspot residues of the substrate of the main protease of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our implementation of CMA-ES into Rosetta allows for an alternative optimization method to be used on macromolecular modeling problems with rough energy landscapes. Finally, our Scaffold Matcher algorithm allows for the identification of initial conformations of interaction inhibitors that can be further designed and optimized as high-affinity reagents.

Sex-specific pleiotropic changes in emotional behavior and alcohol consumption in human α-synuclein A53T transgenic mice during early adulthood.

Point mutations in the α-synuclein coding gene may lead to the development of Parkinson's disease (PD). PD is often accompanied by other psychiatric conditions, such as anxiety, depression, and drug use disorders, which typically emerge in adulthood. Some of these point mutations, such as SNCA and A30T, have been linked to behavioral effects that are not commonly associated with PD, especially regarding alcohol consumption patterns. In this study, we investigated whether the familial PD point mutation A53T is associated with changes in alcohol consumption behavior and emotional states at ages not yet characterized by α-synuclein accumulation. The affective and alcohol-drinking phenotypes remained unaltered in female PDGF-hA53T-synuclein-transgenic (A53T) mice during both early and late adulthood. Brain region-specific activation of ceramide-producing enzymes, acid sphingomyelinase (ASM), and neutral sphingomyelinase (NSM), known for their neuroprotective properties, was observed during early adulthood but not in late adulthood. In males, the A53T mutation was linked to a reduction in alcohol consumption in both early and late adulthood. However, male A53T mice displayed increased anxiety- and depression-like behaviors during both early and late adulthood. Enhanced ASM activity in the dorsal mesencephalon and ventral hippocampus may potentially contribute to these adverse behavioral effects of the mutation in males during late adulthood. In summary, the A53T gene mutation was associated with diverse changes in emotional states and alcohol consumption behavior long before the onset of PD, and these effects varied by sex. These alterations in behavior may be linked to changes in brain ceramide metabolism.

Single-cell transcription profiles in Bloom syndrome patients link BLM deficiency with altered condensin complex expression signatures.

Bloom syndrome (BS) is an autosomal recessive disease clinically characterized by primary microcephaly, growth deficiency, immunodeficiency and predisposition to cancer. It is mainly caused by biallelic loss-of-function mutations in the BLM gene, which encodes the BLM helicase, acting in DNA replication and repair processes. Here, we describe the gene expression profiles of three BS fibroblast cell lines harboring causative, biallelic truncating mutations obtained by single-cell (sc) transcriptome analysis. We compared the scRNA transcription profiles from three BS patient cell lines to two age-matched wild-type controls and observed specific deregulation of gene sets related to the molecular processes characteristically affected in BS, such as mitosis, chromosome segregation, cell cycle regulation and genomic instability. We also found specific upregulation of genes of the Fanconi anemia pathway, in particular FANCM, FANCD2 and FANCI, which encode known interaction partners of BLM. The significant deregulation of genes associated with inherited forms of primary microcephaly observed in our study might explain in part the molecular pathogenesis of microcephaly in BS, one of the main clinical characteristics in patients. Finally, our data provide first evidence of a novel link between BLM dysfunction and transcriptional changes in condensin complex I and II genes. Overall, our study provides novel insights into gene expression profiles in BS on an sc level, linking specific genes and pathways to BLM dysfunction.

Bulk-Processed Plasmonic Plastic Nanocomposite Materials for Optical Hydrogen Detection.

ConspectusSensors are ubiquitous, and their importance is only going to increase across many areas of modern technology. In this respect, hydrogen gas (H2) sensors are no exception since they allow mitigation of the inherent safety risks associated with mixtures of H2 and air. The deployment of H2 technologies is rapidly accelerating in emerging energy, transport, and green steel-making sectors, where not only safety but also process monitoring sensors are in high demand. To meet this demand, cost-effective and scalable routes for mass production of sensing materials are required. Here, the state-of-the-art often resorts to processes derived from the microelectronics industry where surface-based micro- and nanofabrication are the methods of choice and where (H2) sensor manufacturing is no exception.In this Account, we discuss how our recent efforts to develop sensors based on plasmonic plastics may complement the current state-of-the-art. We explore a new H2 sensor paradigm, established through a series of recent publications, that combines (i) the plasmonic optical H2 detection principle and (ii) bulk-processed nanocomposite materials. In particular, plasmonic plastic nanocomposite sensing materials are described that comprise plasmonic H2-sensitive colloidally synthesized nanoparticles dispersed in a polymer matrix and enable the additive manufacturing of H2 sensors in a cost-effective and scalable way. We first discuss the concept of plasmonic plastic nanocomposite materials for the additive manufacturing of an active plasmonic sensing material on the basis of the three key components that require individual and concerted optimization: (i) the plasmonic sensing metal nanoparticles, (ii) the surfactant/stabilizer molecules on the nanoparticle surface from colloidal synthesis, and (iii) the polymer matrix. We then introduce the working principle of plasmonic H2 detection, which relies on the selective absorption of H species into hydride-forming metal nanoparticles that, in turn, induces distinct changes in their optical plasmonic signature in proportion to the H2 concentration in the local atmosphere. Subsequently, we assess the roles of the key components of a plasmonic plastic for H2 sensing, where we have established that (i) alloying Pd with Au and Cu eliminates hysteresis and introduces intrinsic deactivation resistance at ambient conditions, (ii) surfactant/stabilizer molecules can significantly accelerate and decelerate H2 sorption and thus sensor response, and (iii) polymer coatings accelerate sensor response, reduce the limit of detection (LoD), and enable molecular filtering for sensor operation in chemically challenging environments. Based on these insights, we discuss the rational development and detailed characterization of bulk-processed plasmonic plastics based on glassy and fluorinated matrix polymers and on tailored flow-chemistry-based synthesis of Pd and PdAu alloy colloidal nanoparticles with optimized stabilizer molecules. In their champion implementation, they enable highly stable H2 sensors with response times in the 2 s range and an LoD of few 10 ppm of H2. To put plasmonic plastics in a wider perspective, we also report their implementation using different polymer matrix materials that can be used for 3D printing and (an)isotropic Au nanoparticles that enable the manufacturing of macroscopic plasmonic objects with, if required, dichroic optical properties and in amounts that can be readily upscaled. We advertise that melt processing of plasmonic plastic nanocomposites is a viable route toward the realization of plasmonic objects and sensors, produced by scalable colloidal synthesis and additive manufacturing techniques.

Chemoselective Post-Synthesis Modification of Pyridyl-Substituted, Aromatic Phosphorus Heterocycles: Cationic Ligands for Coordination Chemistry.

Triazaphospholes are potential polydentate ligands due to the presence of both phosphorus and nitrogen donor atoms within the aromatic 5-membered heterocycle. The incorporation of an additional pyridyl-substituent opens up the possibility of a post-synthesis modification via chemoselective and also stepwise alkylation exclusively of the nitrogen atoms. This can be controlled by the choice and by the stoichiometry of the electrophile and allows the targeted synthesis of a variety of novel mono- and dicationic ligands. Reaction with Cu(I)-halides causes the formation of cuprates of the type [CuXn](n-1)-, which enables coordination of the π-acidic phosphorus donor to the negatively charged metal core, which is favored over the coordination by a strongly σ-donating nitrogen atom. The use of cationic triazaphosphole derivatives can be used as a strategy to enforce the coordination of the ligand to an electron rich metal solely via the phosphorus atom. However, there is a subtle balance between the formation of either coordination polymers or dimeric structures, as the substitution pattern on the heterocycle and the nature of the halide have a large influence on the coordination motifs formed.

Development of a highly effective combination monoclonal antibody therapy against Herpes simplex virus.

BACKGROUND: Infections with Herpes simplex virus (HSV)-1 or -2 usually present as mild chronic recurrent disease, however in rare cases can result in life-threatening conditions with a large spectrum of pathology. Monoclonal antibody therapy has great potential especially to treat infections with virus resistant to standard therapies. HDIT101, a humanized IgG targeting HSV-1/2 gB was previously investigated in phase 2 clinical trials. The aim of this study was to develop a next-generation therapy by combining different antiviral monoclonal antibodies. METHODS: A lymph-node derived phage display library (LYNDAL) was screened against recombinant gB from Herpes simplex virus (HSV) -1 and HDIT102 scFv was selected for its binding characteristics using bio-layer interferometry. HDIT102 was further developed as fully human IgG and tested alone or in combination with HDIT101, a clinically tested humanized anti-HSV IgG, in vitro and in vivo. T-cell stimulating activities by antigen-presenting cells treated with IgG-HSV immune complexes were analyzed using primary human cells. To determine the epitopes, the cryo-EM structures of HDIT101 or HDIT102 Fab bound to HSV-1F as well as HSV-2G gB protein were solved at resolutions < 3.5 Å. RESULTS: HDIT102 Fab showed strong binding to HSV-1F gB with Kd of 8.95 × 10-11 M and to HSV-2G gB with Kd of 3.29 × 10-11 M. Neutralization of cell-free virus and inhibition of cell-to-cell spread were comparable between HDIT101 and HDIT102. Both antibodies induced internalization of gB from the cell surface into acidic endosomes by binding distinct epitopes in domain I of gB and compete for binding. CryoEM analyses revealed the ability to form heterogenic immune complexes consisting of two HDIT102 and one HDIT101 Fab bound to one gB trimeric molecule. Both antibodies mediated antibody-dependent phagocytosis by antigen presenting cells which stimulated autologous T-cell activation. In vivo, the combination of HDIT101 and HDIT102 demonstrated synergistic effects on survival and clinical outcome in immunocompetent BALB/cOlaHsd mice. CONCLUSION: This biochemical and immunological study showcases the potential of an effective combination therapy with two monoclonal anti-gB IgGs for the treatment of HSV-1/2 induced disease conditions.

Self-management with alcohol over lifespan: psychological mechanisms, neurobiological underpinnings, and risk assessment.

Self-management includes all behavioural measures and cognitive activities aimed at coping with challenges arising throughout the lifespan. While virtually all of these challenges can be met without pharmacological means, alcohol consumption has long been instrumentalized as a supporting tool to help coping with problems arising selectively at adolescence, adulthood, and ageing. Here, we present, to our knowledge, the first systematic review of alcohol instrumentalization throughout lifespan. We searched MEDLINE, Google Scholar, PsycINFO and CINAHL (from Jan, 1990, to Dec, 2022) and analysed consumption patterns, goals and potential neurobiological mechanisms. Evidence shows a regular non-addictive use of alcohol to self-manage developmental issues during adolescence, adulthood, and ageing. Alcohol is selectively used to overcome problems arising from dysfunctional personality traits, which manifest in adolescence. A large range of psychiatric disorders gives rise to alcohol use for the self-management of distinct symptoms starting mainly in adulthood. We identify those neuropharmacological effects of alcohol that selectively serve self-management under specific conditions. Finally, we discuss the adverse effects and associated risks that arise from the use of alcohol for self-management. Even well-controlled alcohol use adversely impacts health. Based on these findings, we suggest the implementation of an entirely new view. Health policy action may actively embrace both sides of the phenomenon through a personalized informed use that allows for harm-controlled self-management with alcohol.

Arc controls alcohol cue relapse by a central amygdala mechanism.

Alcohol use disorder (AUD) is a chronic and fatal disease. The main impediment of the AUD therapy is a high probability of relapse to alcohol abuse even after prolonged abstinence. The molecular mechanisms of cue-induced relapse are not well established, despite the fact that they may offer new targets for the treatment of AUD. Using a comprehensive animal model of AUD, virally-mediated and amygdala-targeted genetic manipulations by CRISPR/Cas9 technology and ex vivo electrophysiology, we identify a mechanism that selectively controls cue-induced alcohol relapse and AUD symptom severity. This mechanism is based on activity-regulated cytoskeleton-associated protein (Arc)/ARG3.1-dependent plasticity of the amygdala synapses. In humans, we identified single nucleotide polymorphisms in the ARC gene and their methylation predicting not only amygdala size, but also frequency of alcohol use, even at the onset of regular consumption. Targeting Arc during alcohol cue exposure may thus be a selective new mechanism for relapse prevention.

Over-optimism in unsupervised microbiome analysis: Insights from network learning and clustering.

In recent years, unsupervised analysis of microbiome data, such as microbial network analysis and clustering, has increased in popularity. Many new statistical and computational methods have been proposed for these tasks. This multiplicity of analysis strategies poses a challenge for researchers, who are often unsure which method(s) to use and might be tempted to try different methods on their dataset to look for the "best" ones. However, if only the best results are selectively reported, this may cause over-optimism: the "best" method is overly fitted to the specific dataset, and the results might be non-replicable on validation data. Such effects will ultimately hinder research progress. Yet so far, these topics have been given little attention in the context of unsupervised microbiome analysis. In our illustrative study, we aim to quantify over-optimism effects in this context. We model the approach of a hypothetical microbiome researcher who undertakes four unsupervised research tasks: clustering of bacterial genera, hub detection in microbial networks, differential microbial network analysis, and clustering of samples. While these tasks are unsupervised, the researcher might still have certain expectations as to what constitutes interesting results. We translate these expectations into concrete evaluation criteria that the hypothetical researcher might want to optimize. We then randomly split an exemplary dataset from the American Gut Project into discovery and validation sets multiple times. For each research task, multiple method combinations (e.g., methods for data normalization, network generation, and/or clustering) are tried on the discovery data, and the combination that yields the best result according to the evaluation criterion is chosen. While the hypothetical researcher might only report this result, we also apply the "best" method combination to the validation dataset. The results are then compared between discovery and validation data. In all four research tasks, there are notable over-optimism effects; the results on the validation data set are worse compared to the discovery data, averaged over multiple random splits into discovery/validation data. Our study thus highlights the importance of validation and replication in microbiome analysis to obtain reliable results and demonstrates that the issue of over-optimism goes beyond the context of statistical testing and fishing for significance.

Doping Approaches for Organic Semiconductors.

Electronic doping in organic materials has remained an elusive concept for several decades. It drew considerable attention in the early days in the quest for organic materials with high electrical conductivity, paving the way for the pioneering work on pristine organic semiconductors (OSCs) and their eventual use in a plethora of applications. Despite this early trend, however, recent strides in the field of organic electronics have been made hand in hand with the development and use of dopants to the point that are now ubiquitous. Here, we give an overview of all important advances in the area of doping of organic semiconductors and their applications. We first review the relevant literature with particular focus on the physical processes involved, discussing established mechanisms but also newly proposed theories. We then continue with a comprehensive summary of the most widely studied dopants to date, placing particular emphasis on the chemical strategies toward the synthesis of molecules with improved functionality. The processing routes toward doped organic films and the important doping-processing-nanostructure relationships, are also discussed. We conclude the review by highlighting how doping can enhance the operating characteristics of various organic devices.

Masculine depression and its problem behaviors: use alcohol and drugs, work hard, and avoid psychiatry!

The gender role influences vulnerability to mental illness. Substance use, even critical in scale, is perceived as masculine, just like hard (over-)work, while not seeking help. With the ongoing separation between gender and sex, masculine norms become more relevant also to females' mental health. The male depression concept highlights the role of male symptoms in affective disorders. However, the empirical evidence is still limited. Here, we use the denomination 'masculine depression' to open the category for female patients and tested substance use patterns, health services' utilization, and working hours as predictors in a case-control study of 163 depressed in-patients (44% women; masculine vs. non-masculine depression according to a median split of the Male Depression Rating Scale-22) and 176 controls (51% women). We assessed higher depression severity in patients with masculine (vs. non-masculine) depression. Masculine depression (vs. non-masculine depression and vs. no depression) was predicted by more frequent and critical use of alcohol (including binge drinking), tobacco, and illicit drugs, and by longer working times. Moreover, fewer health services contacts due to mental complaints during the previous year were associated with masculine (vs. non-masculine) depression. Alarmingly, even critical substance misuse was not significantly associated with more frequent health services contacts; however, the higher the depression severity, the more contacts the patients reported. Here, we provide evidence that patients with masculine depression are highly burdened and undertreated, which applies equally to female and male patients. This study identified promising targets to establish specialized care offers.

The ReCoDe addiction research consortium: Losing and regaining control over drug intake-Findings and future perspectives.

Substance use disorders (SUDs) are seen as a continuum ranging from goal-directed and hedonic drug use to loss of control over drug intake with aversive consequences for mental and physical health and social functioning. The main goals of our interdisciplinary German collaborative research centre on Losing and Regaining Control over Drug Intake (ReCoDe) are (i) to study triggers (drug cues, stressors, drug priming) and modifying factors (age, gender, physical activity, cognitive functions, childhood adversity, social factors, such as loneliness and social contact/interaction) that longitudinally modulate the trajectories of losing and regaining control over drug consumption under real-life conditions. (ii) To study underlying behavioural, cognitive and neurobiological mechanisms of disease trajectories and drug-related behaviours and (iii) to provide non-invasive mechanism-based interventions. These goals are achieved by: (A) using innovative mHealth (mobile health) tools to longitudinally monitor the effects of triggers and modifying factors on drug consumption patterns in real life in a cohort of 900 patients with alcohol use disorder. This approach will be complemented by animal models of addiction with 24/7 automated behavioural monitoring across an entire disease trajectory; i.e. from a naïve state to a drug-taking state to an addiction or resilience-like state. (B) The identification and, if applicable, computational modelling of key molecular, neurobiological and psychological mechanisms (e.g., reduced cognitive flexibility) mediating the effects of such triggers and modifying factors on disease trajectories. (C) Developing and testing non-invasive interventions (e.g., Just-In-Time-Adaptive-Interventions (JITAIs), various non-invasive brain stimulations (NIBS), individualized physical activity) that specifically target the underlying mechanisms for regaining control over drug intake. Here, we will report on the most important results of the first funding period and outline our future research strategy.

Kratom (Mitragyna speciosa) Use and Mental Health: A Systematic Review and Multilevel Meta-Analysis.

INTRODUCTION: Kratom (Mitragyna speciosa) is a medicinal tree native to Southeast Asia. The present multilevel meta-analysis describes the association between kratom use and the positive and negative indicators of mental health. METHODS: A total of thirty-six articles were included in the meta-analysis to examine the associations, using a random-effects model. RESULTS: The pooled effect size showed a very small positive association between kratom use and negative indicators of mental health {r = 0.092, 95% confidence interval (CI) = [0.020, 0.164], p < 0.05}, while no significant association was found with positive indicators of mental health (r = -0.031, 95% CI = [-0.149, 0.087], p > 0.05). Pooled effect sizes of specific mental health outcomes indicated that kratom use showed only a small positive correlation with externalizing disorders (r = 0.201, 95% CI = [0.107, 0.300], p < 0.001). No significant association was found between kratom use and quality of life (r = 0.069, 95% CI = [-0.104, 0.242], p > 0.05) and internalizing disorders (r = -0.001, 95% CI = [-0.115, 0.095], p > 0.05). Multilevel moderator analysis showed that the pooled effect size of the association between kratom use and substance use disorder was stronger in Malaysia (r = 0.347, 95% CI = [0.209, 0.516], p < 0.001), and with the mean age (ß1 = -0.035, 95% CI = [-0.055, -0.014], p = 0.003), and the drug profile of those who were not co-using other drugs (r = 0.347, 95% CI = [0.209, 0.516], p < 0.001). CONCLUSION: The meta-analysis supports the kratom instrumentalization concept, in that a positive gain from kratom consumption can be achieved without any significant adverse associations with mental health.

Ceramide levels in blood plasma correlate with major depressive disorder severity and its neutralization abrogates depressive behavior in mice.

Major depressive disorder (MDD) is a severe disease of unknown pathogenesis that will affect ∼10% of people during their lifetime. Therapy for MDD requires prolonged treatment and often fails, predicating a need for novel treatment strategies. Here, we report increased ceramide levels in the blood plasma of MDD patients and in murine stress-induced models of MDD. These blood plasma ceramide levels correlated with the severity of MDD in human patients and were independent of age, sex, or body mass index. In addition, intravenous injection of anti-ceramide antibodies or neutral ceramidase rapidly abrogated stress-induced MDD, and intravenous injection of blood plasma from mice with MDD induced depression-like behavior in untreated mice, which was abrogated by ex vivo preincubation of the plasma with anti-ceramide antibodies or ceramidase. Mechanistically, we demonstrate that ceramide accumulated in endothelial cells of the hippocampus of stressed mice, evidenced by the quantitative measurement of ceramide in purified hippocampus endothelial cells. We found ceramide inhibited the activity of phospholipase D (PLD) in endothelial cells in vitro and in the hippocampus in vivo and thereby decreased phosphatidic acid in the hippocampus. Finally, we show intravenous injection of PLD or phosphatidic acid abrogated MDD, indicating the significance of this pathway in MDD pathogenesis. Our data indicate that ceramide controls PLD activity and phosphatidic acid formation in hippocampal endothelial cells and thereby mediates MDD. We propose that neutralization of plasma ceramide could represent a rapid-acting targeted treatment for MDD.

Proteomic profiling of longitudinal changes in kidney function among middle-aged and older men and women: the KORA S4/F4/FF4 study.

BACKGROUND: Due to the asymptomatic nature of the early stages, chronic kidney disease (CKD) is usually diagnosed at late stages and lacks targeted therapy, highlighting the need for new biomarkers to better understand its pathophysiology and to be used for early diagnosis and therapeutic targets. Given the close relationship between CKD and cardiovascular disease (CVD), we investigated the associations of 233 CVD- and inflammation-related plasma proteins with kidney function decline and aimed to assess whether the observed associations are causal. METHODS: We included 1140 participants, aged 55-74 years at baseline, from the Cooperative Health Research in the Region of Augsburg (KORA) cohort study, with a median follow-up time of 13.4 years and 2 follow-up visits. We measured 233 plasma proteins using a proximity extension assay at baseline. In the discovery analysis, linear regression models were used to estimate the associations of 233 proteins with the annual rate of change in creatinine-based estimated glomerular filtration rate (eGFRcr). We further investigated the association of eGFRcr-associated proteins with the annual rate of change in cystatin C-based eGFR (eGFRcys) and eGFRcr-based incident CKD. Two-sample Mendelian randomization was used to infer causality. RESULTS: In the fully adjusted model, 66 out of 233 proteins were inversely associated with the annual rate of change in eGFRcr, indicating that higher baseline protein levels were associated with faster eGFRcr decline. Among these 66 proteins, 21 proteins were associated with both the annual rate of change in eGFRcys and incident CKD. Mendelian randomization analyses on these 21 proteins suggest a potential causal association of higher tumor necrosis factor receptor superfamily member 11A (TNFRSF11A) level with eGFR decline. CONCLUSIONS: We reported 21 proteins associated with kidney function decline and incident CKD and provided preliminary evidence suggesting a potential causal association between TNFRSF11A and kidney function decline. Further Mendelian randomization studies are needed to establish a conclusive causal association.