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Recombinant adeno-associated virus (rAAV)-based gene therapies are expanding in their application. Despite progress in manufacturing, current analytical methods for product quantification and characterization remain largely unchanged. Although critical for product and process development, in-process testing, and batch release, current analytical methods are labor-intensive, costly, and hampered by extended turnaround times and low throughput. The field requires more efficient, cost-effective analytical techniques capable of handling large sample quantities to accelerate product and process development. Here, we evaluated Stunner from Unchained Labs for quantifying and characterizing rAAVs and compared it with established analytical methods. Stunner is a combinatorial analytic technology platform that interpolates ultraviolet-visible (UV-Vis) absorption with static and dynamic light scattering (SLS/DLS) analysis to determine capsid and genomic titer, empty and full capsid ratio, and assess vector size and polydispersity. The platform offers empirical measurements with minimal sample requirements. Upon testing hundreds of rAAV vectors, comprising various serotypes and transgenes, the data show a strong correlation with established analytical methods and exhibit high reproducibility and repeatability. Some analyses can be applied to in-process samples from different purification stages and processes, fulfilling the demand for rapid, high-throughput analysis during development. In sum, the pipeline presented streamlines small- and large-batch analytics.

Abstract The heterogeneity inherent in today’s biotherapeutics, especially as a result of heavy glycosylation, can affect a molecule’s safety and efficacy. Characterizing this heterogeneity is crucial for drug development and quality assessment, but existing methods are limited in their ability to analyze intact glycoproteins or other heterogeneous biotherapeutics. Here, we present an approach to the molecular assessment of biotherapeutics that uses proton-transfer charge-reduction with gas-phase fractionation to analyze intact heterogeneous and/or glycosylated proteins by mass spectrometry. The method provides a detailed landscape of the intact molecular weights present in biotherapeutic protein preparations in a single experiment. For glycoproteins in particular, the method may offer insights into glycan composition when coupled with a suitable bioinformatic strategy. We tested the approach on various biotherapeutic molecules, including Fc-fusion, VHH-fusion, and peptide-bound MHC class II complexes to demonstrate efficacy in measuring the proteoform-level diversity of biotherapeutics. Notably, we inferred the glycoform distribution for hundreds of molecular weights for the eight-times glycosylated fusion drug IL22-Fc, enabling correlations between glycoform sub-populations and the drug’s pharmacological properties. Our method is broadly applicable and provides a powerful tool to assess the molecular heterogeneity of emerging biotherapeutics.

AbstractHuman DNA topoisomerases are essential for crucial cellular processes, including DNA replication, transcription, chromatin condensation, and maintenance of its structure. One of the significant strategies employed in cancer treatment involves the inhibition of a specific type of topoisomerase, known as topoisomerase II (Topo II). Carbazole derivatives, recognised for their varied biological activities, have recently become a significant focus in oncological research. This study assesses the efficacy of three symmetrically substituted carbazole derivatives: 2,7-Di(2-furyl)-9H-carbazole (27a), 3,6-Di(2-furyl)-9H-carbazole (36a), and 3,6-Di(2-thienyl)-9H-carbazole (36b) – as anticancer agents. Among investigated carbazole derivatives, compound 3,6-di(2-furyl)-9H-carbazole bearing two furan moieties emerged as a novel catalytic inhibitor of Topo II. Notably, 3,6-di(2-furyl)-9H-carbazole effectively selectively inhibited the relaxation and decatenation activities of Topo IIα, with minimal effects on the IIβ isoform. These findings underscore the potential of compound 3,6-Di(2-furyl)-9H-carbazole as a promising lead candidate warranting further investigation in the realm of anticancer drug development.

Abstract Many functional aspects of the protein kinase p38α have been illustrated by more than three hundred structures determined in the presence of reducing agents. These structures correspond to free forms and complexes with activators, substrates, and inhibitors. Here we report the conformation of an oxidized state with an intramolecular disulfide bond between Cys119 and Cys162 that is conserved in vertebrates. The structure of the oxidized state does not affect the conformation of the catalytic site, but alters the docking groove by partially unwinding and displacing the short αD helix due to the movement of Cys119 towards Cys162. The transition between oxidized and reduced conformations provides a mechanism for fine-tuning p38α activity as a function of redox conditions, beyond its activation loop phosphorylation. Moreover, the conformational equilibrium between these redox forms reveals an unexplored cleft for p38α inhibitor design that we describe in detail.

Purpose: The paper investigates the learning practices carried out by Higher Education Institutions (HEIs) in the transition from strictly face-to-face to remote teaching in response to the coronavirus disease 2019 (COVID-19) pandemic. It also analyses how these practices could be used as a baseline to support new perspectives on learning in the technological education field. Design/methodology/approach: The authors conducted a single-case study of a Brazilian technological university. Findings: This study's findings indicate that institutional planning and providing support to faculty and students were essential measures for a successful transition from face-to-face teaching to emergency remote teaching. Planning includes careful selection by the HEI of the tools that make a virtual learning environment and the strategies used to replace face-to-face teaching with emergency remote teaching. Our study points out the lessons learned during the pandemic. It presents guidelines for HEIs on how to prepare for a return to face-to-face teaching, embodying some learning dimensions such as synchronous or asynchronous, active or passive, individual or collective, and mediated or not mediated by information and communication technologies (ICTs). Originality/value: The paper provides reflections on the four dimensions to support decisions to leverage learning in each educational institution. This paper's main contribution is that the concept of teaching and learning must be comprehensive and inclusive according to the particular HEI context.

Abstract p38α is a versatile protein kinase that can control numerous processes and plays important roles in the cellular responses to stress. Dysregulation of p38α signaling has been linked to several diseases including inflammation, immune disorders and cancer, suggesting that targeting p38α could be therapeutically beneficial. Over the last two decades, numerous p38α inhibitors have been developed, which showed promising effects in pre-clinical studies but results from clinical trials have been disappointing, fueling the interest in the generation of alternative mechanisms of p38α modulation. Here, we report the in silico identification of compounds that we refer to as non-canonical p38α inhibitors (NC-p38i). By combining biochemical and structural analyses, we show that NC-p38i efficiently inhibit p38α autophosphorylation but weakly affect the activity of the canonical pathway. Our results demonstrate how the structural plasticity of p38α can be leveraged to develop therapeutic opportunities targeting a subset of the functions regulated by this pathway.

Suicide-related media content has preventive or harmful effects depending on the specific content. Proactive media screening for suicide prevention is hampered by the scarcity of machine learning approaches to detect specific characteristics in news reports. This study applied machine learning to label large quantities of broadcast (TV and radio) media data according to media recommendations reporting suicide. We manually labeled 2519 English transcripts from 44 broadcast sources in Oregon and Washington, USA, published between April 2019 and March 2020. We conducted a content analysis of media reports regarding content characteristics. We trained a benchmark of machine learning models including a majority classifier, approaches based on word frequency (TF-IDF with a linear SVM) and a deep learning model (BERT). We applied these models to a selection of more simple (e.g., focus on a suicide death), and subsequently to putatively more complex tasks (e.g., determining the main focus of a text from 14 categories). Tf-idf with SVM and BERT were clearly better than the naive majority classifier for all characteristics. In a test dataset not used during model training, F1-scores (i.e., the harmonic mean of precision and recall) ranged from 0.90 for celebrity suicide down to 0.58 for the identification of the main focus of the media item. Model performance depended strongly on the number of training samples available, and much less on assumed difficulty of the classification task. This study demonstrates that machine learning models can achieve very satisfactory results for classifying suicide-related broadcast media content, including multi-class characteristics, as long as enough training samples are available. The developed models enable future large-scale screening and investigations of broadcast media.

Abstract Background Identifying mechanisms to maintain CBPR studies during an infectious disease pandemic is vital. The current paper describes the changes in methods and processes conducted within a CBPR mixed-methods study to a virtual setting during the novel coronavirus (COVID-19) pandemic. Method The DC Community Organizing for Optimal Culinary Knowledge study with Heart (DC COOKS with Heart) was designed to assess the feasibility of a dietary behavior intervention among African-American adults that are at risk for cardiovascular disease (CVD). The study is under the umbrella of an ongoing CBPR study and community advisory board that facilitates community involvement in study design and promotes ongoing engagement with community members and leaders. The study population for D.C. COOKS with Heart consists of adult African-American individuals who live in two low-resource neighborhoods in Washington, D.C., which were impacted disproportionately by COVID. Eligible study participants who previously participated in the DC CHOC community-based studies were contacted to participate in Phase 1. The quantitative part of the mixed-methods included survey data collection. Results Due to the pandemic, the mode of data collection for surveys changed from self-administered face-to-face to internet-based. All virtual study procedures were conducted between March and April, 2021. Anticipated benefits of the virtual setting included participant safety during the pandemic, ease of logistics for participants. Anticipated challenges included administration of electronic devices to participants, research team training, and potential threats to established trust related to the privacy and confidentiality of participants. Conclusion The transition to a virtual setting for study procedures in a mixed-methods study was conducted successfully in terms of recruitment, retention of participants, and training of research team members. The virtual transition required established and ongoing engagement through the community advisory board and CBPR practices, institutional support through virtual research policies, collaborations with information technology-based teams, and equipment administration for the study. Trials registration NCT04305431 . Registered on March 12, 2020.

Abstract Telomerase reactivation is one of the hallmarks of cancer, which plays an important role in cellular immortalization and the development and progression of the tumor. Chemical telomerase inhibitors have been shown to trigger replicative senescence and apoptotic cell death both in vitro and in vivo. Due to its upregulation in various cancers, telomerase is considered a potential target in cancer therapy. In this study, we identified potent, small-molecule telomerase inhibitors using a telomerase repeat amplification protocol assay. The results of the assay are the first evidence of telomerase inhibition by anthraquinone derivatives that do not exhibit G-quadruplex-stabilizing properties. The stability of telomerase in the presence of its inhibitor was evaluated under nearly physiological conditions using a cellular thermal shift assay. Our data showed that the compound induced aggregation of the catalytic subunit (hTERT) of human telomerase, and molecular studies confirmed the binding of the hit compound with the active site of the enzyme. The ability of new derivatives to activate DNA double-strand breaks (DSBs) was determined by high-resolution microscopy and flow cytometry in tumor cell lines differing in telomere elongation mechanism. The compounds triggered DSBs in TERT-positive A549 and H460 lung cancer cell lines, but not in TERT-negative NHBE normal human bronchial epithelial and ALT-positive U2OS osteosarcoma cell lines, which indicates that the induction of DSBs was dependent on telomerase inhibition. The observed DNA damage activated DNA damage response pathways involving ATM/Chk2 and ATR/Chk1 cascades. Additionally, the compounds induced apoptotic cell death through extrinsic and intrinsic pathways in lung cancer cells. Taken together, our study demonstrated that anthraquinone derivatives can be further developed into novel telomerase-related anticancer agents.

FoxH1 is an essential maternal pioneer factor during embryonic development. Here, the authors present several FoxH1—DNA structures that reveal the molecular basis for FoxH1 binding specificity and pioneer factor activity.

Background: Cooking is an identified dietary strategy that is positively associated with optimal diet quality. Prior to initiating cooking interventions, evaluating the prospective acceptability of the intervention among community members living within low food access areas and understanding geospatial food shopping locations may aid in designing community-tailored interventions. Methods: A sequential mixed methods study was conducted to determine the prospective acceptability of a planned community-located cooking intervention among African American adults living in a low food access area and with at least one cardiovascular disease risk factor. A semi-structured guide was used to conduct five virtual focus groups. Qualitative data were analyzed using thematic analysis and validated through participant check-in interviews. Survey responses were analyzed based on descriptive data. Geospatial analysis of participant locations that were reported for food shopping was conducted to show food environment utilization. Results: Focus groups with study participants (n = 20, all female, mean age 60.3, SD 9.3, mean cooking frequency per week 4.0, food insecure n = 7) were conducted between March and April, 2021. Thematic analysis of the focus group transcripts identified five main themes as follows: (A) Barriers to Cooking (family and caregiving, transportation, COVID-19 pandemic, time availability, household composition); (B) Motivators for Cooking (family, caregiving, health, enjoyment, COVID-19 pandemic); (C) Strategies (food shopping, social support, social media, meal planning); (D) Neighborhood (gentrification, perceived safety, stigmatization, disparities in grocery stores); (E) and Acceptability of the Intervention (reasons to participate, barriers, recruitment, intervention delivery). Participant validation interviews confirmed the themes and subthemes as well as the illustrative quotes. Geospatial analysis showed a majority of locations were outside of the participants’ residential areas. Conclusions: Prospective acceptability of a community-tailored cooking intervention found that the planned intervention could be modified to address individual level factors, such as caregiving and health, community contextual factors, such as perceived safety, and the general health needs of the community.

Abstract Background Escherichia coli (E. coli) is a promising host for production of recombinant proteins (including antibodies and antibody fragments) that don’t require complex post-translational modifications such as glycosylation. During manufacturing-scale production of a one-armed antibody in E. coli (periplasmic production), variability in the degree of reduction of the antibody’s disulfide bonds was observed. This resulted in variability in the free thiol content, a potential critical product quality attribute. This work was initiated to understand and prevent the variability in the total free thiol content during manufacturing. Results In this study, we found that the reduction in antibody’s disulfide bonds was observed to occur during homogenization and the ensuing homogenate hold step where in the antibody is exposed to redox enzymes and small molecule reductants present in homogenate. Variability in the downstream processing time between the start of homogenization and end of the homogenate hold step resulted in variability in the degree of antibody disulfide bond reduction and free thiol content. The disulfide bond reduction in the homogenate is catalyzed by the enzyme disulfide bond isomerase C (DsbC) and is highly site-specific and occurred predominantly in the intra-chain disulfide bonds present in the Fc CH2 region. Our results also imply that lack of glycans in E. coli produced antibodies may facilitate DsbC accessibility to the disulfide bond in the Fc CH2 region, resulting in its reduction. Conclusions During E. coli antibody manufacturing processes, downstream processing steps such as homogenization and subsequent processing of the homogenate can impact degree of disulfide bond reduction in the antibody and consequently product quality attributes such as total free thiol content. Duration of the homogenate hold step should be minimized as much as possible to prevent disulfide bond reduction and free thiol formation. Other approaches such as reducing homogenate temperature, adding flocculants prior to homogenization, using enzyme inhibitors, or modulating redox environments in the homogenate should be considered to prevent antibody disulfide bond reduction during homogenization and homogenate processing steps in E. coli antibody manufacturing processes.

Introduction The connection of the microbiome to human health intersects with the physical environment of humans. Each microbiome location can be influenced by environmental conditions that relate to specific geographical locations, which in turn are influenced by social determinants of health such as a neighbourhood. The objective of this scoping review is to explore the current evidence on the relationships between microbiome and neighbourhood to explain microbiome-related health outcomes.Methods and analysis Arksey and O’Malley’s literature review framework will be employed throughout the process, as well as Page, et al’s 2020 Preferred Reporting Items for Systematic Review and Meta-Analysis updated workflow to process search results. The literature search will be completed using PubMed/Medline (NLM), Embase (Elsevier), Web of Science, Core Collection (Clarivate Analytics), Scopus (Elsevier), medRxiv preprint server and Open Science Framework server. The search will be conducted using a list of pre-identified Medical Subject Headings (MeSH) terms relating to neighbourhood, microbiome and individual characteristics. There will be no date or language restrictions used in the search. In order to be included in the study, a piece must include an evaluation of the relationship between microbiome diversity and neighbourhood (including at least one measurement of the neighbourhood and at least one human microbiome site). Excluded from the review will be those works that do not include all of these measures, literature reviews based on secondary sources and postmortem populations with no report of premortem health factors. The review itself will be an iterative process completed by two reviewers, with a third individual identified to break ties. Documents will be undergoing a risk assessment of bias in order for the authors to comment on the quality of the literature in this area. Finally, results will be discussed with identified stakeholders, including individuals connected to neighbourhoods facing structural inequity and experts in the topics of study through a community advisory board, for their feedback and knowledge transfer.Ethics and dissemination This review does not require ethical approval. Results of this search will be disseminated through peer-reviewed publications. Furthermore, this work is completed in conjunction with a community advisory board so as to ensure dissemination to multiple stakeholders.

We investigate pattern formation in a two-dimensional manifold using the Otha-Kawasaki model for micro-phase separation of diblock copolymers. In this model, the total energy includes a short-range and a long-range term. The short-range term is a Landau-type free energy that is common in phase separation problems and favors large domains with minimum perimeter. The inhibitory long-range interaction term is the Otha-Kawasaki functional derived from the theory of diblock copolymers and favors small domains. The balance of these terms leads to equilibrium states that exhibit a variety of patterns, including disk-like droplets, droplet assemblies, elongated droplets, dog-bone shaped droplets, stripes, annular rings, wriggled stripes and combinations thereof. For problems where analytical results are known, we compare our numerical results and find good agreement. Where analytical results are not available, our numerical methods allow us to explore the solution space revealing new stable patterns. We focus on the triaxial ellipsoid, but our methods are general and can be applied to higher genus surfaces and surfaces with boundaries.

Abstract Lung cancer is considered to account for approximately one-fifth of all malignant tumor-related deaths worldwide and is therefore one of the most lethal malignancies. Pyrazole scaffold possesses a wide range of biological and pharmacological activities, which play important roles in medicinal chemistry. The present study reports the synthesis and in vitro biological characterization of nine pyrazoles derived from chalcones as potential anticancer agents for non-small cell lung cancer A-549, H226, and H460 cell lines. Most of the compounds efficiently inhibited the growth of all the tested cancer cell lines at micromolar concentrations. One of the most active compounds (PCH-1) was further evaluated for its effect on cell cycle distribution, apoptosis, migration, epithelial–mesenchymal transition, and oxidative stress. Furthermore, studies on the mechanism of action revealed that PCH-1 disrupts microtubule assembly, leading to cancer cell death. Molecular modeling studies confirmed the potent interaction of PCH-1 with the vinblastine binding site on tubulin. Overall, this study provides novel opportunities to identify anticancer agents in the pyrazole series.

Background: With the increased use of robotic surgery, robotic transabdominal preperitoneal repair (R-TAPP) has become a commonly used approach for inguinal hernia repair. The laparoscopic totally extraperitoneal repair (L-TEP) has the advantage of not entering the peritoneal cavity; however, it has greater technical difficulty. Robotic surgery has demonstrated superiority over laparoscopy in many surgical settings, but there is limited evidence comparing L-TEP and R-TAPP. Methods: This was a retrospective review of patients who underwent L-TEP and R-TAPP at Baylor University Medical Center between December 2011 and January 2022. Information on patient demographic characteristics, comorbidities, postoperative complications, hospital length of stay, and postoperative complications requiring a procedure was collected. Results: A total of 298 patients were analyzed; 245 underwent R-TAPP and 53 underwent L-TEP. Hernia recurrence was significantly decreased in those who underwent R-TAPP (1.2%) compared to L-TEP (9.4%) (P = 0.01). Postoperative pain was also significantly decreased in the R-TAPP group (5.3%) as compared to the L-TEP group (13.2%) (P = 0.01). Conclusions: With the transition from L-TEP to R-TAPP over recent years, there is limited evidence supporting this change in practice. Our single-center retrospective review demonstrates that R-TAPP is noninferior to L-TEP and has significantly decreased hernia recurrence. [ABSTRACT FROM AUTHOR]

Abstract Background The results of recent surveys indicate that more than 50% of the German population has experience with complementary and alternative medicine (CAM) or uses CAM regularly. This study investigated the CAM usage and CAM-related needs of hospitalized patients at university medical centres in the state of Baden-Württemberg, Germany. Methods A multi-centre, paper-based, pseudonymous survey was carried out by the members of the Academic Centre for Complementary and Integrative Medicine. Patients of all ages, regardless of sex, diagnosis and treatment, who were hospitalized in the Department of Cardiology, Gastroenterology, Oncology, Gynaecology or Surgery at the university medical centres in Freiburg, Heidelberg, Tübingen and Ulm were eligible for inclusion. Results Of the 1275 eligible patients, 67% (n = 854) consented to participate in the survey. Forty-eight percent of the study participants stated that they were currently using CAM. The most frequently used therapies were exercise (63%), herbal medicine (54%) and dietary supplements (53%). Only 16% of the patients discussed CAM usage with their attending physician. Half of the patients (48%) were interested in CAM consultations. More than 80% of the patients desired reliable CAM information and stated that physicians should be better informed about CAM. Conclusions The frequency of CAM usage and the need for CAM counselling among hospitalized patients at university medical centres in Baden-Württemberg are high. To better meet patients’ needs, CAM research and physician education should be intensified. Trial registration German Clinical Trial register ( DRKS00015445 ).

BackgroundResearch has repeatedly shown that exposure to suicide-related news media content is associated with suicide rates, with some content characteristics likely having harmful and others potentially protective effects. Although good evidence exists for a few selected characteristics, systematic and large-scale investigations are lacking. Moreover, the growing importance of social media, particularly among young adults, calls for studies on the effects of the content posted on these platforms. ObjectiveThis study applies natural language processing and machine learning methods to classify large quantities of social media data according to characteristics identified as potentially harmful or beneficial in media effects research on suicide and prevention. MethodsWe manually labeled 3202 English tweets using a novel annotation scheme that classifies suicide-related tweets into 12 categories. Based on these categories, we trained a benchmark of machine learning models for a multiclass and a binary classification task. As models, we included a majority classifier, an approach based on word frequency (term frequency-inverse document frequency with a linear support vector machine) and 2 state-of-the-art deep learning models (Bidirectional Encoder Representations from Transformers [BERT] and XLNet). The first task classified posts into 6 main content categories, which are particularly relevant for suicide prevention based on previous evidence. These included personal stories of either suicidal ideation and attempts or coping and recovery, calls for action intending to spread either problem awareness or prevention-related information, reporting of suicide cases, and other tweets irrelevant to these 5 categories. The second classification task was binary and separated posts in the 11 categories referring to actual suicide from posts in the off-topic category, which use suicide-related terms in another meaning or context. ResultsIn both tasks, the performance of the 2 deep learning models was very similar and better than that of the majority or the word frequency classifier. BERT and XLNet reached accuracy scores above 73% on average across the 6 main categories in the test set and F1-scores between 0.69 and 0.85 for all but the suicidal ideation and attempts category (F1=0.55). In the binary classification task, they correctly labeled around 88% of the tweets as about suicide versus off-topic, with BERT achieving F1-scores of 0.93 and 0.74, respectively. These classification performances were similar to human performance in most cases and were comparable with state-of-the-art models on similar tasks. ConclusionsThe achieved performance scores highlight machine learning as a useful tool for media effects research on suicide. The clear advantage of BERT and XLNet suggests that there is crucial information about meaning in the context of words beyond mere word frequencies in tweets about suicide. By making data labeling more efficient, this work has enabled large-scale investigations on harmful and protective associations of social media content with suicide rates and help-seeking behavior.

Background: Comorbidities between Substance Use Disorder (SUD) and mental health disorders are highly prevalent, yet there remains a lack of information regarding how mental health conditions may affect addiction severity. Consequently, this study sought to investigate the relationship between internalizing disorders (anxiety and mood disorders) and addiction severity in patients hospitalized for SUD-related medical complications. Individual difference predictors and history of prior treatment for SUD were also examined. Methods: Participants (N = 200) were hospitalized patients who consented to receive peer-based recovery support services for their SUD. To be eligible for the study, participants needed to have a SUD diagnosis due to alcohol, opioids, methamphetamine, cocaine, or a combination of these substances (polysubstance use). Participants completed self-report questionnaires regarding demographics, mental health history, prior SUD treatment, and addiction severity (Drug and Alcohol Screening Test; DAST-10) during their hospitalization. Results: Results showed that patients with Generalized Anxiety Disorder (GAD) ( M = 6.68, SD = 2.97) had greater addiction severity compared to those without GAD ( M = 5.41, SD = 3.34), P = .016. Addiction severity results stratified by SUD type showed that the relationship was significant among patients with Alcohol Use Disorder ( P = .014), but not among those with other SUD types ( P s > .27). Major Depressive Disorder (MDD) and Post-Traumatic Stress Disorder (PTSD) were not linked to addiction severity. Among those with GAD, 81.4% had previously been to treatment compared to only 53.1% of those without GAD, P = .010. The only participant characteristic linked with addiction severity was insurance status. Conclusions: GAD may represent a risk factor for advanced alcohol addiction trajectories, including greater addiction severity and severe health complications requiring inpatient hospitalization.

Abstract Aims Remote patient monitoring (RPM) in the management of heart failure (HF), including telemonitoring, thoracic impedance, implantable pulmonary artery pressure (PAP) monitors, and cardiac implantable electronic device (CIED)‐based sensors, has had varying outcomes in single platform studies. Uncertainty remains regarding the development of single‐centre RPM programs; additionally, no studies examine the effectiveness of dual platform RPM programs for HF. This study describes the implementation and outcomes of a dual platform RPM program for HF at a single centre. Methods and results An RPM program was developed to include two platforms (e.g. CardioMEMS™ HF System and HeartLogic™ HF Diagnostic). To examine changes within each participant over time, study‐related outcomes including total hospitalizations (TH), total length of stay (TLOS), cardiac hospitalizations (CH), cardiac LOS (CLOS), and cardiac‐related emergency department (ED) visits were compared in two timeframes: 12 months pre‐enrolment and post‐enrolment into RPM. For 141 participants enrolled, there was a significant reduction in the likelihood of experiencing a CH by 19% (0.77 vs. 0.61 events/patient‐year; HR: 0.81, 95% CI: 0.67–0.97, P = 0.03) and a cardiac‐related ED visit by 28% (0.48 vs. 0.34 events/patient‐year; HR: 0.72, 95% CI: 0.55–0.93, P = 0.01). There was also a 51% decrease (SE = 1.41, 95% CI: 2.79–8.38 days, P

Mangiferin is a strong antioxidant that presents a wide range of biological activities. The aim of this study was to evaluate, for the first time, the influence of mangiferin on tyrosinase, an enzyme responsible for melanin synthesis and the unwanted browning process of food. The research included both the kinetics and molecular interactions between tyrosinase and mangiferin. The research proved that mangiferin inhibits tyrosinase activity in a dose-dependent manner with IC50 290 +/− 6.04 µM, which was found comparable with the standard kojic acid (IC50 217.45 +/− 2.54 µM). The mechanism of inhibition was described as mixed inhibition. The interaction between tyrosinase enzyme and mangiferin was confirmed with capillary electrophoresis (CE). The analysis indicated the formation of two main, and four less significant complexes. These results have also been supported by the molecular docking studies. It was indicated that mangiferin binds to tyrosinase, similarly to L-DOPA molecule, both in the active center and peripheral site. As it was presented in molecular docking studies, mangiferin and L-DOPA molecules can interact in a similar way with surrounding amino acid residues of tyrosinase. Additionally, hydroxyl groups of mangiferin may interact with amino acids on the tyrosinase external surface causing non-specific interaction.

Smad transcription factors are the main downstream effectors of the Transforming growth factor β superfamily (TGFβ) signalling network. The DNA complexes determined here by X-ray crystallography for the Bone Morphogenetic Proteins (BMP) activated Smad5 and Smad8 proteins reveal that all MH1 domains bind [GGC(GC)|(CG)] motifs similarly, although TGFβ-activated Smad2/3 and Smad4 MH1 domains bind as monomers whereas Smad1/5/8 form helix-swapped dimers. Dimers and monomers are also present in solution, as revealed by NMR. To decipher the characteristics that defined these dimers, we designed chimeric MH1 domains and characterized them using X-ray crystallography. We found that swapping the loop1 between TGFβ- and BMP- activated MH1 domains switches the dimer/monomer propensities. When we scanned the distribution of Smad-bound motifs in ChIP-Seq peaks (Chromatin immunoprecipitation followed by high-throughput sequencing) in Smad-responsive genes, we observed specific site clustering and spacing depending on whether the peaks correspond to BMP- or TGFβ-responsive genes. We also identified significant correlations between site distribution and monomer or dimer propensities. We propose that the MH1 monomer or dimer propensity of Smads contributes to the distinct motif selection genome-wide and together with the MH2 domain association, help define the composition of R-Smad/Smad4 trimeric complexes.

Values of static and kinetic friction coefficient in micro slide bearings, consisting of journals and bushings (with the diameter of 3.5 mm) made of pairs of 5 polymer materials (16 chosen combinations of PA11, ABS, PC, PS and PETP), were determined. A method of measuring static and kinetic friction coefficient, at various values of: load, rotational speed, and standstill time, as well as the structure of a dedicated test rig, were discussed. Chosen mechanical properties of polymers measured using indentation method, and conclusions from the conducted experiments, are shown. The presented results provide key information for a proper choice of polymer materials, which are to work as a friction node. The biggest observed difference in the moment of friction among the tested slide bearings reached almost 40% (with respect to the highest value).

This research investigates the use of a Binary Phase Shift Key (BPSK) sequence derived from the 192-bit key Advanced Encryption Standard (AES-192) algorithm for radar signal modulation to mitigate Doppler and range ambiguities. The AES-192 BPSK sequence has a non-periodic nature resulting in a single large and narrow main lobe in the matched filter response but also produces undesired periodic side lobes that can be mitigated through the use of a CLEAN algorithm. The performance of the AES-192 BPSK sequence is compared to an Ipatov–Barker Hybrid BPSK code, which effectively extends the maximum unambiguous range but has some limitations in terms of signal processing requirements. The AES-192 based BPSK sequence has the advantage of having no maximum unambiguous range limit, and when the pulse location within the Pulse Repetition Interval (PRI) is randomized, the upper limit on the maximum unambiguous Doppler frequency shift is greatly extended.

Trimethylamine N-oxide (TMAO)—a microbial metabolite derived from the hepatic–gut axis—is linked to inflammation, hyperlipidemia, and cardiovascular disease (CVD). Proprotein convertase subtilisin/kexin type 9 (PCSK9), which is largely hepatically expressed, blocks low-density lipoprotein (LDL) receptor recycling, also leading to hyperlipidemia. The primary objective of this study was to investigate a previously hypothesized potential relationship between TMAO and PCSK9 in order to explore novel mechanisms linking TMAO and CVD risk. African American adults at risk of CVD living in the Washington DC area were recruited to participate in a cross-sectional community-based study (n = 60, 93% female, BMI = 33). Fasting levels of inflammatory cytokines (i.e., interleukin (IL)-1 beta, tumor necrosis factor-alpha, and interleukin-8), TMAO, and PCSK9 were measured using Luminex and ELISA, respectively. Univariate and multivariate linear regression analyses and structural equation mediation analyses were conducted using STATA. All models were adjusted for body mass index (BMI) and atherosclerotic CVD risk score (ASCVD). A significant association between TMAO and PCSK9 was identified (β = 0.31, p = 0.02). Both TMAO and PCSK9 were significantly associated with IL-8 (TMAO: β = 0.45, p = 0.00; PCSK9: β = 0.23, p = 0.05) in adjusted models. Mediation analysis indicated that 34.77% of the relationship between TMAO and PCSK9 was explained by IL-8. Our findings indicate a potential PCSK9-involved pathway for TMAO and CVD risk, with potential mediation by IL-8.