Apolar Extracts of St. John's Wort Alleviate the Effects of ß-Amyloid Toxicity in Early Alzheimer's Disease.

Hypericum perforatum (St. John's wort) has been described to be beneficial for the treatment of Alzheimer's disease (AD). Different extractions have demonstrated efficiency in mice and humans, esp. extracts with a low hypericin and hyperforin content to reduce side effects such as phototoxicity. In order to systematically elucidate the therapeutic effects of H. perforatum extracts with different polarities, APP-transgenic mice were treated with a total ethanol extract (TE), a polar extract obtained from TE, and an apolar supercritical CO2 (scCO2) extract. The scCO2 extract was formulated with silicon dioxide (SiO2) for better oral application. APP-transgenic mice were treated with several extracts (total, polar, apolar) at different concentrations. We established an early treatment paradigm from the age of 40 days until the age of 80 days, starting before the onset of cerebral ß-amyloid (Aß) deposition at 45 days of age. Their effects on intracerebral soluble and insoluble Aß were analyzed using biochemical analyses. Our study confirms that the scCO2H. perforatum formulation shows better biological activity against Aß-related pathological effects than the TE or polar extracts. Clinically, the treatment resulted in a dose-dependent improvement in food intake with augmentation of the body weight, and, biochemically, it resulted in a significant reduction in both soluble and insoluble Aß (-27% and -25%, respectively). We therefore recommend apolar H. perforatum extracts for the early oral treatment of patients with mild cognitive impairment or early AD.

Predictors of clinical evolution of SARS-CoV-2 infection in hematological patients: A systematic review and meta-analysis.

Main aim of this systematic review is to quantify the risk and identify predictors of clinical evolution of SARS-CoV-2 in hematological patients compared to different control populations. Two independent reviewers screened the literature assessing clinical outcomes of SARS-CoV-2 infection in adult patients with active hematological malignancies published up to June 2021. Primary outcome was COVID-19 related mortality, secondary outcomes were hospital and intensive-care admission, mechanical ventilation (MV), and thromboembolic events. Variables related to study setting, baseline patients' demographic, comorbidities, underlying hematological disease, ongoing chemotherapy, COVID-19 presentation, and treatments were extracted. A total of 67 studies including 10,061 hematological patients and 111,143 controls were included. Most of the studies were retrospective cohorts (51 studies, 76%) and only 19 (13%) provided data for a control group. A significant increased risk of clinical progression in the hematological population compared to the controls was found in terms of COVID-19 related mortality (OR, 2.12; 95% CI, 1.77-2.54), hospitalization (OR, 1.98; 95% CI, 1.15-3.43), intensive-care admission (OR, 1.77; 95% CI, 1.38-2.26), and MV (OR, 2.17; 95% CI, 1.71-2.75). The risk remained significantly higher in the subgroup analysis comparing hematological patients versus solid cancer. Meta-regression analysis of uncontrolled studies showed that older age, male sex, and hypertension were significantly related to worse clinical outcomes of COVID-19 in hematological population. Older age and hypertension were found to be associated also to thromboembolic events. In conclusion, hematological patients have a higher risk of COVID-19 clinical progression compared to both the general population and to patients with solid cancer.

Development of a New Voltammetric Method for Aceclofenac Determination on Glassy Carbon Electrode Modified with Hierarchical Nanocomposite.

Aceclofenac (ACL) is an anti-inflammatory drug, which is taken by patients who mainly suffer from rheumatoid conditions. In this work, we propose a new voltammetric method that allows the determination of ACL in pharmaceutics, urine, and plasma. As a working electrode, a glassy carbon electrode (GCE) modified with carbon nanofibers, carbon nanotubes, and NiCo nanoparticles (eCNF/CNT/NiCo-GCE) was used. The mentioned sensors are characterized by good repeatability and sensitivity, and their process of preparation is simple, fast, and cost-effective. Instrumental and method parameters were optimized, and the influence of interferences was investigated. To validate the analytical performance of the method, calibration was conducted. Good linearity was obtained (0.05-1.4 µM, r = 0.998), as well as excellent limit of detection (LOD) and limit of quantification (LOQ) values (0.7 nM and 2.1 nM, respectively). Calculated recoveries that were in the range of 98%-105% indicate that this method is accurate and might be used in routine laboratory practice.

Getting through COVID-19 together: Understanding local governments' social media communication.

This study provides new insights into how local governments (LGs) manage pandemic-related crisis communication with citizens on their social media (SM) profiles. We analyze over 3000 posts published on SM profiles of selected LGs in Poland to get insights on rhetorical communication strategies during the COVID-19 pandemic. We document LGs as they go beyond the simple transmission of information to citizens and use SM in an engaging and educational manner. We found three types of rhetorical strategies and their resonance with the public. Our analysis suggests that LGs are likely to apply the Together communication strategy, which is the most engaging.

Human immunodeficiency virus-1/simian immunodeficiency virus infection induces opening of pannexin-1 channels resulting in neuronal synaptic compromise: A novel therapeutic opportunity to prevent NeuroHIV.

In healthy conditions, pannexin-1 (Panx-1) channels are in a close state, but in several pathological conditions, including human immunodeficiency virus-1 (HIV) and NeuroHIV, the channel becomes open. However, the mechanism or contribution of Panx-1 channels to the HIV pathogenesis and NeuroHIV is unknown. To determine the contribution of Panx-1 channels to the pathogenesis of NeuroHIV, we used a well-established model of simian immunodeficiency virus (SIV) infection in macaques (Macaca mulatta) in the presence of and absence of a Panx-1 blocker to later examine the synaptic/axonal compromise induced for the virus. Using Golgi's staining, we demonstrated that SIV infection compromised synaptic and axonal structures, especially in the white matter. Blocking Panx-1 channels after SIV infection prevented the synaptic and axonal compromise induced by the virus, especially by maintaining the more complex synapses. Our data demonstrated that targeting Panx-1 channels can prevent and maybe revert brain synaptic compromise induced by SIV infection.

Assessment of COVID-19 progression on day 5 from symptoms onset.

BACKGROUND: A major limitation of current predictive prognostic models in patients with COVID-19 is the heterogeneity of population in terms of disease stage and duration. This study aims at identifying a panel of clinical and laboratory parameters that at day-5 of symptoms onset could predict disease progression in hospitalized patients with COVID-19. METHODS: Prospective cohort study on hospitalized adult patients with COVID-19. Patient-level epidemiological, clinical, and laboratory data were collected at fixed time-points: day 5, 10, and 15 from symptoms onset. COVID-19 progression was defined as in-hospital death and/or transfer to ICU and/or respiratory failure (PaO2/FiO2 ratio < 200) within day-11 of symptoms onset. Multivariate regression was performed to identify predictors of COVID-19 progression. A model assessed at day-5 of symptoms onset including male sex, age > 65 years, dyspnoea, cardiovascular disease, and at least three abnormal laboratory parameters among CRP (> 80 U/L), ALT (> 40 U/L), NLR (> 4.5), LDH (> 250 U/L), and CK (> 80 U/L) was proposed. Discrimination power was assessed by computing area under the receiver operating characteristic (AUC) values. RESULTS: A total of 235 patients with COVID-19 were prospectively included in a 3-month period. The majority of patients were male (148, 63%) and the mean age was 71 (SD 15.9). One hundred and ninety patients (81%) suffered from at least one underlying illness, most frequently cardiovascular disease (47%), neurological/psychiatric disorders (35%), and diabetes (21%). Among them 88 (37%) experienced COVID-19 progression. The proposed model showed an AUC of 0.73 (95% CI 0.66-0.81) for predicting disease progression by day-11. CONCLUSION: An easy-to-use panel of laboratory/clinical parameters computed at day-5 of symptoms onset predicts, with fair discrimination ability, COVID-19 progression. Assessment of these features at day-5 of symptoms onset could facilitate clinicians' decision making. The model can also play a role as a tool to increase homogeneity of population in clinical trials on COVID-19 treatment in hospitalized patients.

Poly(Vinyl Alcohol) Cryogel Membranes Loaded with Resveratrol as Potential Active Wound Dressings.

Hydrogel wound dressings are highly effective in the therapy of wounds. Yet, most of them do not contain any active ingredient that could accelerate healing. The aim of this study was to prepare hydrophilic active dressings loaded with an anti-inflammatory compound - trans-resveratrol (RSV) of hydrophobic properties. A special attention was paid to select such a technological strategy that could both reduce the risk of irritation at the application site and ensure the homogeneity of the final hydrogel. RSV dissolved in Labrasol was combined with an aqueous sol of poly(vinyl) alcohol (PVA), containing propylene glycol (PG) as a plasticizer. This sol was transformed into a gel under six consecutive cycles of freezing (-80 °C) and thawing (RT). White, uniform and elastic membranes were successfully produced. Their critical features, namely microstructure, mechanical properties, water uptake and RSV release were studied using SEM, DSC, MRI, texture analyser and Franz-diffusion cells. The cryogels made of 8 % of PVA showed optimal tensile strength (0.22 MPa) and elasticity (0.082 MPa). The application of MRI enabled to elucidate mass transport related phenomena in this complex system at the molecular (detection of PG, confinement effects related to pore size) as well as at the macro level (swelling). The controlled release of RSV from membranes was observed for 48 h with mean dissolution time of 18 h and dissolution efficiency of 35 %. All in all, these cryogels could be considered as a promising new active wound dressings.

Highly Sensitive Levodopa Determination by Means of Adsorptive Stripping Voltammetry on Ruthenium Dioxide-Carbon Black-Nafion Modified Glassy Carbon Electrode.

A new, highly sensitive Adsorptive Stripping Voltammetric method for levodopa determination was developed. As a working electrode, the glassy carbon electrode (GCE) modified with carbon black (CB), RuO2·xH2O (RuO2) and Nafion was used (CB-RuO2-Nafion GCE). Levodopa signal obtained on the modified electrode was 12 times higher compared to GCE. During research, instrumental parameters were optimized: sampling time ts = 10 ms, waiting time tw = 10 ms, step potential Es = 5 mV and pulse amplitude ΔE = 50 mV. Preconcentration potential Eprec was equal to 0 mV. The best results were obtained in 0.025 M perchloric acid (approx. pH 1.4). Signal repeatability measured on the CB-RuO2-Nafion modified electrode for 0.2 µM of levodopa was equal to 2.1% (levodopa concentration 1 µM, n = 5). Linearity of the method was achieved in the concentration range from 1 to 8 µM. Limit of detection was equal to 17 nM. Recoveries calculated for pharmaceutical products and tap water measurements were in the range 102-105%, which confirms the accuracy of the developed. The applicability of the method was confirmed by analysis of pharmaceutical products and tap water samples. Based on obtained results, it might be concluded that the developed voltammetric method could be a useful tool in routine drug analysis.

Gap junctions coordinate the propagation of glycogenolysis induced by norepinephrine in the pineal gland.

Chemical and electrical synapses are the two major communication systems that permit cell-to-cell communication within the nervous system. Although most studies are focused on chemical synapses (glutamate, γ-aminobutyric acid, and other neurotransmitters), clearly both types of synapses interact and cooperate to allow the coordination of several cell functions within the nervous system. The pineal gland has limited independent axonal innervation and not every cell has access to nerve terminals. Thus, additional communication systems, such as gap junctions, have been postulated to coordinate metabolism and signaling. Using acutely isolated glands and dissociated cells, we found that gap junctions spread glycogenolytic signals from cells containing adrenoreceptors to the entire gland lacking these receptors. Our data using glycogen and lactate quantification, electrical stimulation, and high-performance liquid chromatography with electrochemical detection, demonstrate that gap junctional communication between cells of the rat pineal gland allows cell-to-cell propagation of norepinephrine-induced signal that promotes glycogenolysis throughout the entire gland. Thus, the interplay of both synapses is essential for coordinating glycogen metabolism and lactate production in the pineal gland.

Analysis of ribosomal inter-subunit sites as targets for complementary oligonucleotides.

The bacterial ribosome has many functional ribosomal RNA (rRNA) sites. We have computationally analyzed the rRNA regions involved in the interactions between the 30S and 50S subunits. Various properties of rRNA such as solvent accessibility, opening energy, hydrogen bonding pattern, van der Waals energy, thermodynamic stability were determined. Based on these properties we selected rRNA targets for hybridization with complementary 2'-O-methyl oligoribonucleotides (2'-OMe RNAs). Further, the inhibition efficiencies of the designed ribosome-interfering 2'-OMe RNAs were tested using a ß-galactosidase assay in a translation system based on the E. coli extract. Several of the oligonucleotides displayed IC50 values below 1 µM, which were in a similar range as those determined for known ribosome inhibitors, tetracycline and pactamycin. The calculated opening and van der Waals stacking energies of the rRNA targets correlated best with the inhibitory efficiencies of 2'-OMe RNAs. Moreover, the binding affinities of several oligonucleotides to both 70S ribosomes and isolated 30S and 50S subunits were measured using a double-filter retention assay. Further, we applied heat-shock chemical transformation to introduce 2'-OMe RNAs to E. coli cells and verify inhibition of bacterial growth. We observed high correlation between IC50 in the cell-free extract and bacterial growth inhibition. Overall, the results suggest that the computational analysis of potential rRNA targets within the conformationally dynamic regions of inter-subunit bridges can help design efficient antisense oligomers to probe the ribosome function.

MEGAN Community Edition - Interactive Exploration and Analysis of Large-Scale Microbiome Sequencing Data.

There is increasing interest in employing shotgun sequencing, rather than amplicon sequencing, to analyze microbiome samples. Typical projects may involve hundreds of samples and billions of sequencing reads. The comparison of such samples against a protein reference database generates billions of alignments and the analysis of such data is computationally challenging. To address this, we have substantially rewritten and extended our widely-used microbiome analysis tool MEGAN so as to facilitate the interactive analysis of the taxonomic and functional content of very large microbiome datasets. Other new features include a functional classifier called InterPro2GO, gene-centric read assembly, principal coordinate analysis of taxonomy and function, and support for metadata. The new program is called MEGAN Community Edition (CE) and is open source. By integrating MEGAN CE with our high-throughput DNA-to-protein alignment tool DIAMOND and by providing a new program MeganServer that allows access to metagenome analysis files hosted on a server, we provide a straightforward, yet powerful and complete pipeline for the analysis of metagenome shotgun sequences. We illustrate how to perform a full-scale computational analysis of a metagenomic sequencing project, involving 12 samples and 800 million reads, in less than three days on a single server. All source code is available here: https://github.com/danielhuson/megan-ce.

MINT: software to identify motifs and short-range interactions in trajectories of nucleic acids.

Structural biology experiments and structure prediction tools have provided many high-resolution three-dimensional structures of nucleic acids. Also, molecular dynamics force field parameters have been adapted to simulating charged and flexible nucleic acid structures on microsecond time scales. Therefore, we can generate the dynamics of DNA or RNA molecules, but we still lack adequate tools for the analysis of the resulting huge amounts of data. We present MINT (Motif Identifier for Nucleic acids Trajectory) - an automatic tool for analyzing three-dimensional structures of RNA and DNA, and their full-atom molecular dynamics trajectories or other conformation sets (e.g. X-ray or nuclear magnetic resonance-derived structures). For each RNA or DNA conformation MINT determines the hydrogen bonding network resolving the base pairing patterns, identifies secondary structure motifs (helices, junctions, loops, etc.) and pseudoknots. MINT also estimates the energy of stacking and phosphate anion-base interactions. For many conformations, as in a molecular dynamics trajectory, MINT provides averages of the above structural and energetic features and their evolution. We show MINT functionality based on all-atom explicit solvent molecular dynamics trajectory of the 30S ribosomal subunit.

Towards Autonomous Living Meta-Analyses: A Framework for Automation of Systematic Review and Meta-Analyses.

Systematic review and meta-analysis constitute a staple of evidence-based medicine, an obligatory step in developing the guideline and recommendation document. It is a formalized process aiming at extracting and summarizing knowledge from the published work, grading, and considering the quality of the included studies. It is very laborious and time-consuming. Therefore, the meta-analyses are rarely updated and seldom living, decreasing their utility with time. Here, we present a framework for integrating the large language models and natural language processing techniques applied to the previously published systematic review and meta-analysis of the diagnostic test accuracy of the point of care tests. We show that the framework can be used to automate the screening step of the existing meta-analyses with minimal costs to quality and, to a large extent, the extraction step while maintaining the strict nature of the systematic review process.

Mechanisms of HIV-mediated blood-brain barrier compromise and leukocyte transmigration under the current antiretroviral era.

HIV-associated neurological compromise is observed in more than half of all people with HIV (PWH), even under antiretroviral therapy (ART). The mechanism has been associated with the early transmigration of HIV-infected monocytes across the BBB in a CCL2 and HIV replication-dependent manner. However, the mechanisms of chronic brain damage are unknown. We demonstrate that all PWH under ART have elevated circulating ATP levels that correlate with the onset of cognitive impairment even in the absence of a circulating virus. Serum ATP levels found in PWH with the most severe neurocognitive impairment trigger the transcellular migration of HIV-infected leukocytes across the BBB in a JAM-A and LFA-1-dependent manner. We propose that targeting transcellular leukocyte transmigration could reduce or prevent the devastating consequences of HIV within the brains of PWH under ART.

Evaluation of cerebrospinal fluid (CSF) and interstitial fluid (ISF) mouse proteomes for the validation and description of Alzheimer's disease biomarkers.

BACKGROUND: Mass spectrometry (MS)-based cerebrospinal fluid (CSF) proteomics is an important method for discovering biomarkers of neurodegenerative diseases. CSF serves as a reservoir for interstitial fluid (ISF), and extensive communication between the two fluid compartments helps to remove waste products from the brain. NEW METHOD: We performed proteomic analyses of both CSF and ISF fluid compartments using intracerebral microdialysis to validate and detect novel biomarkers of Alzheimer's disease (AD) in APPtg and C57Bl/6J control mice. RESULTS: We identified up to 625 proteins in ISF and 4483 proteins in CSF samples. By comparing the biofluid profiles of APPtg and C57Bl/6J mice, we detected 37 and 108 significantly up- and downregulated candidates, respectively. In ISF, 7 highly regulated proteins, such as Gfap, Aldh1l1, Gstm1, and Txn, have already been implicated in AD progression, whereas in CSF, 9 out of 14 highly regulated proteins, such as Apba2, Syt12, Pgs1 and Vsnl1, have also been validated to be involved in AD pathogenesis. In addition, we also detected new interesting regulated proteins related to the control of synapses and neurotransmission (Kcna2, Cacng3, and Clcn6) whose roles as AD biomarkers should be further investigated. COMPARISON WITH EXISTING METHODS: This newly established combined protocol provides better insight into the mutual communication between ISF and CSF as an analysis of tissue or CSF compartments alone. CONCLUSIONS: The use of multiple fluid compartments, ISF and CSF, for the detection of their biological communication enables better detection of new promising AD biomarkers.

Privacy-Preserving Workflow for the Cross-Border Federated Analysis of Clinical Data.

The motivation behind this research is to perform a privacy-preserving analysis of data located at remote sites and in different jurisdictions with no possibility of sharing individual-level information. Here, we present key findings from requirements analysis and a resulting federated data analysis workflow built using open-source research software, where patient-level information is securely stored and never exposed during the analysis process. We present additional improvements to further strengthen the security of the workflow. We emphasize and showcase the use of data harmonization in the analysis. The data analysis is done using the R language for statistical computing and DataSHIELD libraries for non-disclosive analysis of sensitive data. The workflow was validated against two data analysis scenarios, confirming the results obtained with a centralized analysis approach. The clinical datasets are part of the large Pan-European SARS-Cov-2 cohort, collected and managed by the ORCHESTRA project. We demonstrate the viability of establishing a cross-border federated data analysis framework and conducting an analysis without exposing patient-level information, achieving results equivalent to centralized non-secure analysis. However, it is vital to ensure requirements associated with data harmonization, anonymization and IT infrastructure to maintain availability, usability and data security.

Gut Microbiome Disruption Following SARS-CoV-2: A Review.

COVID-19 has been associated with having a negative impact on patients' gut microbiome during both active disease and in the post-acute phase. In acute COVID-19, rapid alteration of the gut microbiome composition was observed, showing on one side a reduction in beneficial symbionts (e.g., Roseburia, Lachnospiraceae) and on the other side an increase in opportunistic pathogens such as Enterococcus and Proteobacteria. Alpha diversity tends to decrease, especially initially with symptom onset and hospital admission. Although clinical recovery appears to align with improved gut homeostasis, this process could take several weeks, even in mild infections. Moreover, patients with COVID-19 post-acute syndrome showed changes in gut microbiome composition, with specific signatures associated with decreased respiratory function up to 12 months following acute disease. Potential treatments, especially probiotic-based therapy, are under investigation. Open questions remain on the possibility to use gut microbiome data to predict disease progression and on potential confounders that may impair result interpretation (e.g., concomitant therapies in the acute phase; reinfection, vaccines, and occurrence of novel conditions or diseases in the post-acute syndrome). Understanding the relationships between gut microbiome dynamics and disease progression may contribute to better understanding post-COVID syndrome pathogenesis or inform personalized treatment that can affect specific targets or microbiome markers.

Chemosensory assessment and impact on quality of life in neurosensorial cluster of the post COVID 19 syndrome.

COVID-19 pandemic brought chemosensory impairment to the forefront of medicine, revealing gaps in the knowledge of pathophysiological mechanisms, true prevalence and preventive/therapeutic alternatives. This is a sub-study of the ORCHESTRA cohort focusing on post-COVID-19 chemosensory symptoms. Risk factors for neurosensorial cluster of post-COVID-19 syndrome (NSc-PCS) were assessed through multivariable analysis. Psychophysical validated tests were applied on a sub-population of 50 patients. Qualitative chemosensory symptoms as well as nasal and oral chemesthesis were evaluated through anamnestic interview and the quality of life through the SF-36 questionnaire. Chemosensory symptoms evolution and olfactory training's outcome were assessed through phone-call interviews. Out of 1187 patients (female, N = 630), 550 (47%) presented NSc-PCS, with a lower risk for older age and monoclonal antibodies treatment, and a higher risk in females (p < 0.001). Out of the 50 patients evaluated with psychophysical tests, 66% showed smell reduction with a qualitative alteration in 50% of hyposmic and 35% of normosmic patients. Hypogeusia was present in 14 (28%) of the patients assessed, with 56% showing a qualitative alteration; 53% of normogeusic patients presented qualitative disorders. NSc-PCS has a complex, fluctuating, multifaceted presentation. Quantifying and characterizing COVID-19-related chemosensory impairment is key to understand underlying mechanisms and to develop preventive and therapeutic treatment.

The gut microbiota as an early predictor of COVID-19 severity.

Several studies reported alterations of the human gut microbiota (GM) during COVID-19. To evaluate the potential role of the GM as an early predictor of COVID-19 at disease onset, we analyzed gut microbial samples of 315 COVID-19 patients that differed in disease severity. We observed significant variations in microbial diversity and composition associated with increasing disease severity, as the reduction of short-chain fatty acid producers such as Faecalibacterium and Ruminococcus, and the growth of pathobionts as Anaerococcus and Campylobacter. Notably, we developed a multi-class machine-learning classifier, specifically a convolutional neural network, which achieved an 81.5% accuracy rate in predicting COVID-19 severity based on GM composition at disease onset. This achievement highlights its potential as a valuable early biomarker during the first week of infection. These findings offer promising insights into the intricate relationship between GM and COVID-19, providing a potential tool for optimizing patient triage and streamlining healthcare during the pandemic.IMPORTANCEEfficient patient triage for COVID-19 is vital to manage healthcare resources effectively. This study underscores the potential of gut microbiota (GM) composition as an early biomarker for COVID-19 severity. By analyzing GM samples from 315 patients, significant correlations between microbial diversity and disease severity were observed. Notably, a convolutional neural network classifier was developed, achieving an 81.5% accuracy in predicting disease severity based on GM composition at disease onset. These findings suggest that GM profiling could enhance early triage processes, offering a novel approach to optimizing patient management during the pandemic.

International Clinical Research Data Ecosystem: From Data Standardization to Federated Analysis.

Within the HORIZON 2020 project ORCHESTRA, patient data from numerous clinical studies in Europe related to COVID-19 were harmonized to create new knowledge on the disease. In this article, we describe the ecosystem that was established for the management of data collected and contributed by project partners. Study protocols elements were mapped to interoperability standards to establish a common terminology. That served as the basis of identifying common concepts used across several studies. Harmonized data were used to perform analysis directly on a central database and also through federated analysis when data was not permitted to leave the local server(s). This ecosystem facilitates the answering of research questions and generation of new knowledge available for the scientific community.