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Introduction Involuntary admissions are increasing in numbers across Europe.1 They can be traumatic for the patients2 and are associated with large societal costs.3 Individuals with psychotic disorder are at particularly elevated risk of involuntary admission. Objectives This study aims to investigate whether machine learning methods including natural language processing can predict involuntary admission among patients with psychotic disorder. Methods We have obtained a dataset based on electronic health records for all patients having had at least one contact with the psychiatric services in the Central Denmark Region from 2011 to 2021. This dataset covers more than 120,000 patients, of which approximately 10,000 have been diagnosed with a psychotic disorder. The dataset contains both structured data, such as diagnoses, blood tests etc., as well as unstructured data (text). We will train machine learning models, basic logistic regression-models as well as state-of-the-art neural networks, to predict involuntary admission after contacts to the psychiatric services. Results As the machine learning models are under development, no results are available at this time. Preliminary results are expected in spring 2022. Conclusions If involuntary admission can be predicted among patients with psychotic disorder based on data from electronic health records, it will pave the way for potentially preventive interventions. References: 1. Sheridans-Rains, L et al., 2019 2. Frueh, B.C et al., 2005 3. Smith,S., 2020 Disclosure No significant relationships.

Background: Genetic immunization is expected to induce the expression of antigens in a native form. The encoded peptide epitopes are presented on endogenous MHC molecules, mimicking antigen presentation during a viral infection. We have explored the potential of enfuvirtide (T20), a short HIV peptide with antiviral properties, to enhance immune response to HIV antigens. To generate an expression vector, the T20 sequence was cloned into a conventional plasmid, the novel minicircle construct, and a replicon plasmid. In addition, 3 conventional plasmids that express the envelope of HIV-1 subtypes A, B and C and contain T20 in their gp41 sequences were also tested. Results: All combinations induced HIV-specific antibodies and cellular responses. The addition of T20 as a peptide and as an expression cassette in the 3 DNA vectors enhanced antibody responses. The highest anti-HIV-1 Env titers were obtained by the replicon T20 construct. This demonstrates that besides its known antiviral activity, T20 promotes immune responses. We also confirm that the combination of slightly divergent antigens improves immune responses. Conclusions: The antiretroviral T20 HIV-1 sequence can be used as an immunogen to elicit binding and neutralizing antibodies against HIV-1. These, or similarly modified gp41 genes/peptides, can be used as priming or boosting components for induction of broadly neutralizing anti-HIV antibodies. Future comparative studies will reveal the optimal mode of T20 administration.

Background Juvenile‐onset spinocerebellar ataxia has been recognized in Jack Russell Terriers and related Russell group terriers (RGTs) for over 40 years. Ataxia occurs with varying combinations of myokymia, seizures, and other signs of neurologic disease. More than 1 form of the disease has been suspected. Hypothesis/Objectives The objective was to identify the mutation causing the spinocerebellar ataxia associated with myokymia, seizures, or both and distinguish the phenotype from other ataxias in the RGTs. Animals DNA samples from 16 RGTs with spinocerebellar ataxia beginning from 2 to 12 months of age, 640 control RGTs, and 383 dogs from 144 other breeds along with the medical records of affected dogs were studied. Methods This case‐control study compared the frequencies of a KCNJ10 allele in RGTs with spinocerebellar ataxia versus control RGTs. This allele was identified in a whole‐genome sequence of a single RGT with spinocerebellar ataxia and myokymia by comparison to whole‐genome sequences from 81 other canids that were normal or had other diseases. Results A missense mutation in the gene coding for the inwardly rectifying potassium channel Kir4.1 (KCNJ10:c.627C>G) was significantly (P

Abstract Obesity impairs tissue insulin sensitivity and signaling, promoting type-2 diabetes. Although improving insulin signaling is key to reversing diabetes, the multi-organ mechanisms regulating this process are poorly defined. Here, we screen the secretome and receptome in Drosophila to identify the hormonal crosstalk affecting diet-induced insulin resistance and obesity. We discover a complex interplay between muscle, neuronal, and adipose tissues, mediated by Bone Morphogenetic Protein (BMP) signaling and the hormone Bursicon, that enhances insulin signaling and sugar tolerance. Muscle-derived BMP signaling, induced by sugar, governs neuronal Bursicon signaling. Bursicon, through its receptor Rickets, a Leucine-rich-repeat-containing G-protein coupled receptor (LGR), improves insulin secretion and insulin sensitivity in adipose tissue, mitigating hyperglycemia. In mouse adipocytes, loss of the Rickets ortholog LGR4 blunts insulin responses, showing an essential role of LGR4 in adipocyte insulin sensitivity. Our findings reveal a muscle-neuronal-fat-tissue axis driving metabolic adaptation to high-sugar conditions, identifying LGR4 as a critical mediator in this regulatory network.

Objective: To evaluate the heterogeneity in treatment effect in posttraumatic stress disorder (PTSD) trials. Patients and Methods: We downloaded data from a publicly available repository that captured PTSD trials published from January 1988 through February 2023. We applied restricted maximum-likelihood random-effect meta-analyses and meta-regression to explore potential moderators of treatment effect including methodologic study features (risk of bias domains and control group response rate), characteristics of the population, and intervention features following the theme, intensity, and platform framework. Results: We included 199 PTSD trials that reported the outcomes of diagnosis resolution (122 trials, 8437 patients) and clinically meaningful improvement (133 trials, 9895 patients). Multiple treatments demonstrated effectiveness but with significant heterogeneity. Statistically significant moderators included risk of bias domains of randomization sequence and outcome measurement, control group response rate reflecting severity of PTSD in the enrolled population, and whether the psychotherapeutic approach was trauma focused (P values

ABSTRACT Bacilli and pseudomonads are among the most well-studied microorganisms commonly found in soil and frequently co-isolated. Isolates from these two genera are frequently used as plant beneficial microorganisms; therefore, their interaction in the plant rhizosphere is relevant for agricultural applications. Despite this, no systematic approach has been employed to assess the coexistence of members from these genera. Here, we screened 720 fluorescent soil isolates for their effects on Bacillus subtilis pellicle formation in two types of media and found a predictor for interaction outcome in Pseudomonas taxonomy. Interactions were context-dependent, and both medium composition and culture conditions strongly influenced interactions. Negative interactions were associated with Pseudomonas capeferrum, Pseudomonas entomophila, and Pseudomonas protegens, and 2,4-diacetylphloroglucinol was confirmed as a strong (but not exclusive) inhibitor of B. subtilis. Non-inhibiting strains were closely related to Pseudomonas trivialis and Pseudomonas lini. Using such a non-inhibiting isolate, Pseudomonas P9_31, which increased B. subtilis pellicle formation demonstrated that the two species were spatially segregated in cocultures. Our study is the first one to propose an overall negative outcome from pairwise interactions between B. subtilis and fluorescent pseudomonads; hence, cocultures comprising members from these groups are likely to require additional microorganisms for coexistence.IMPORTANCEThere is a strong interest in the microbial ecology field to predict interaction among microorganisms, whether two microbial isolates will promote each other’s growth or compete for resources. Numerous studies have been performed based on surveying the available literature or testing phylogenetically diverse sets of species in synthetic communities. Here, a high throughput screening has been performed using 720 Pseudomonas isolates, and their impact on the biofilm formation of Bacillus subtilis was tested. The aim was to determine whether a majority of Pseudomonas will promote or inhibit the biofilms of B. subtilis in the co-cultures. This study reports that Pseudomonas taxonomy is a good predictor of interaction outcome, and only a minority of Pseudomonas isolates promote Bacillus biofilm establishment.

Influenza viruses continually evolve new antigenic variants, through mutations in epitopes of their major surface proteins, hemagglutinin (HA) and neuraminidase (NA). Antigenic drift potentiates the reinfection of previously infected individuals, but the contribution of this process to variability in annual epidemics is not well understood. Here, we link influenza A(H3N2) virus evolution to regional epidemic dynamics in the United States during 1997—2019. We integrate phenotypic measures of HA antigenic drift and sequence-based measures of HA and NA fitness to infer antigenic and genetic distances between viruses circulating in successive seasons. We estimate the magnitude, severity, timing, transmission rate, age-specific patterns, and subtype dominance of each regional outbreak and find that genetic distance based on broad sets of epitope sites is the strongest evolutionary predictor of A(H3N2) virus epidemiology. Increased HA and NA epitope distance between seasons correlates with larger, more intense epidemics, higher transmission, greater A(H3N2) subtype dominance, and a greater proportion of cases in adults relative to children, consistent with increased population susceptibility. Based on random forest models, A(H1N1) incidence impacts A(H3N2) epidemics to a greater extent than viral evolution, suggesting that subtype interference is a major driver of influenza A virus infection ynamics, presumably via heterosubtypic cross-immunity.

Abstract Endothelial dysfunction develops with age and may precede cardiovascular disease. Animal data suggest that T‐type calcium channels play an important role in endothelial function, but data from humans are lacking. This study included 15 healthy, sedentary, elderly males for a double blinded, randomized controlled trial. For 8 weeks, they were given 40 mg/day of either efonidipine (L‐ and T‐type calcium channel blocker (CCB)) or nifedipine (L‐type CCB). Vascular function was evaluated by graded femoral arterial infusions of acetylcholine (ACh; endothelium‐dependent vasodilator) and sodium nitroprusside (endothelium‐independent vasodilator) both with and without co‐infusion of N‐acetylcysteine (NAC; antioxidant). We measured leg blood flow and mean arterial pressure and calculated leg vascular conductance to evaluate the leg vascular responses. Despite no significant change in blood pressure in either group, we observed higher leg blood flow responses (Δ 0.43 ± 0.45 l/min, P = 0.006) and leg vascular conductance (Δ 5.38 ± 5.67 ml/min/mmHg, P = 0.005) to intra‐arterial ACh after efonidipine, whereas there was no change in the nifedipine group, and no differences between groups. We found no upregulation of endothelial nitric oxide synthase in vastus lateralis muscle biopsies within or between groups. Smooth muscle cell responsiveness was unaltered by efonidipine or nifedipine. Intravenous co‐infusion of NAC did not affect endothelium‐dependent vasodilatation in either of the CCB groups. These results suggest that 8 weeks’ inhibition of T‐ and L‐type calcium channels augments endothelium‐dependent vasodilatory function in healthy elderly males. Further studies are required to elucidate if T‐type calcium channel inhibition can counteract endothelial dysfunction.

Abstract Many studies have used mobile device location data to model SARS-CoV-2 dynamics, yet relationships between mobility behavior and endemic respiratory pathogens are less understood. We studied the effects of population mobility on the transmission of 17 endemic viruses and SARS-CoV-2 in Seattle over a 4-year period, 2018-2022. Before 2020, visits to schools and daycares, within-city mixing, and visitor inflow preceded or coincided with seasonal outbreaks of endemic viruses. Pathogen circulation dropped substantially after the initiation of COVID-19 stay-at-home orders in March 2020. During this period, mobility was a positive, leading indicator of transmission of all endemic viruses and lagging and negatively correlated with SARS-CoV-2 activity. Mobility was briefly predictive of SARS-CoV-2 transmission when restrictions relaxed but associations weakened in subsequent waves. The rebound of endemic viruses was heterogeneously timed but exhibited stronger, longer-lasting relationships with mobility than SARS-CoV-2. Overall, mobility is most predictive of respiratory virus transmission during periods of dramatic behavioral change and at the beginning of epidemic waves.

Cancer is considered a risk factor for COVID-19 mortality, yet several countries have reported that deaths with a primary code of cancer remained within historic levels during the COVID-19 pandemic. Here, we further elucidate the relationship between cancer mortality and COVID-19 on a population level in the US. We compared pandemic-related mortality patterns from underlying and multiple cause (MC) death data for six types of cancer, diabetes, and Alzheimer’s. Any pandemic-related changes in coding practices should be eliminated by study of MC data. Nationally in 2020, MC cancer mortality rose by only 3% over a pre-pandemic baseline, corresponding to ~13,600 excess deaths. Mortality elevation was measurably higher for less deadly cancers (breast, colorectal, and hematological, 2–7%) than cancers with a poor survival rate (lung and pancreatic, 0–1%). In comparison, there was substantial elevation in MC deaths from diabetes (37%) and Alzheimer’s (19%). To understand these differences, we simulated the expected excess mortality for each condition using COVID-19 attack rates, life expectancy, population size, and mean age of individuals living with each condition. We find that the observed mortality differences are primarily explained by differences in life expectancy, with the risk of death from deadly cancers outcompeting the risk of death from COVID-19.

Abstract The aim of this study is to describe a case of haemoglobinuria in a cat after near‐drowning. A 6‐year‐old male neutered domestic short hair cat weighing 6.5 kg with a pre‐existing seizure disorder presented to an emergency hospital after near‐drowning in a swimming pool during a seizure episode. On presentation, the patient was obtunded, dyspnoeic, bradycardic and hypothermic. Imaging revealed evidence of severe bilateral pulmonary infiltrates. Treatment with intravenous diazepam, amoxicillin, fluid therapy, active warming and oxygen therapy was administered. The cat developed haemoglobinuria approximately 6 h after nearly drowning. Despite improvements in mentation, pulse quality and heart rate, respiratory compromise and poor oxygen saturation persisted, prompting euthanasia approximately 10 h after admission. To the author's knowledge, this is the first reported clinical case of haemoglobinuria following near‐drowning in veterinary medicine.

Advances in automatic speaker verification (ASV) promote research into the formulation of spoofing detection systems for real-world applications. The performance of ASV systems can be degraded severely by multiple types of spoofing attacks, namely, synthetic speech (SS), voice conversion (VC), replay, twins and impersonation, especially in the case of unseen synthetic spoofing attacks. A reliable and robust spoofing detection system can act as a security gate to filter out spoofing attacks instead of having them reach the ASV system. A weighted additive angular margin loss is proposed to address the data imbalance issue, and different margins has been assigned to improve generalization to unseen spoofing attacks in this study. Meanwhile, we incorporate a meta-learning loss function to optimize differences between the embeddings of support versus query set in order to learn a spoofing-category-independent embedding space for utterances. Furthermore, we craft adversarial examples by adding imperceptible perturbations to spoofing speech as a data augmentation strategy, then we use an auxiliary batch normalization (BN) to guarantee that corresponding normalization statistics are performed exclusively on the adversarial examples. Additionally, A simple attention module is integrated into the residual block to refine the feature extraction process. Evaluation results on the Logical Access (LA) track of the ASVspoof 2019 corpus provides confirmation of our proposed approaches’ effectiveness in terms of a pooled EER of 0.87%, and a min t-DCF of 0.0277. These advancements offer effective options to reduce the impact of spoofing attacks on voice recognition/authentication systems.

A 2-D Lattice Boltzmann Method, designed to ensure stability at high Reynolds numbers, is combined with an Actuator Line Model to compute the loads on a two-bladed vertical axis wind turbine. Tests on the kernel size at a high mesh resolution reveal that a size equal to half of the full chord length yields the most accurate results. The aerodynamic load solution is validated against a fully resolved Scale-Adaptive Simulation (SAS) output, demonstrating high correlation, and enabling an assessment of near wake and downstream effects. The model’s adaptability to various rotor operating conditions is confirmed through tests at high and low tip-speed ratios. Additionally, a Biot–Savart-based Vortex Model (VM) is employed for further comparison, showing good agreement with the Lattice Boltzmann output. The results indicate that the Highly Stable Lattice Boltzmann Method integrated with the Actuator Line Model enhances the accuracy of flow field resolution and effectively captures complex aerodynamic phenomena, making it a valuable tool for simulating vertical axis wind turbines.

Abstract Aldosterone has been suggested to be involved in the microvascular complications observed in type 2 diabetes. We aimed to investigate the effect of mineralocorticoid receptor (MR) blockade on endothelial function in individuals with type 2 diabetes compared to healthy controls. We included 12 participants with type 2 diabetes and 14 controls. We measured leg hemodynamics at baseline and during femoral arterial infusion of acetylcholine and sodium nitroprusside before and 8 weeks into treatment with MR blockade (eplerenone). Acetylcholine infusion was repeated with concomitant n‐acetylcysteine (antioxidant) infusion. No difference in leg blood flow or vascular conductance was detected before or after the treatment with MR blockade in both groups and there was no difference between groups. Infusion of n‐acetylcysteine increased baseline blood flow and vascular conductance, but did not change the vascular response to acetylcholine before or after treatment with MR blockade. Skeletal muscle eNOS content was unaltered by MR blockade and no difference between groups was detected. In conclusion, we found no effect of MR blockade endothelial function in individuals with and without type 2 diabetes. As the individuals with type 2 diabetes did not have vascular dysfunction, these results might not apply to individuals with vascular dysfunction.

At the University of Nebraska Medical Center College of Pharmacy, a longitudinal project is underway to assess how the college is functioning in terms of keeping Justice, Equity, Diversity, and Inclusion (JEDI) at the forefront of the institution. This study is intended to showcase areas of excellence within the college and as a quality improvement exercise to show the institution potential areas in need of improvement. This process was also initiated because such assessments may soon become a requirement for colleges of pharmacy to earn full accreditation. Upon analyzing the Justice component of JEDI and the 32 justice-related ideas that were recommended for exploration and discussion, and further sub-categorized under the terms representation, curriculum and education, policies and procedures, support and resources, and college climate, useful data were discovered. Overall, the information found on representation, policy and procedure, and college climate was difficult to quantify as much of the information was subjective; however, this does not automatically discount this information from being useful. Information relating to curriculum and education was more quantifiable but may be underrepresented. Analyzing information found relating to resources was made possible by identifying readily available support offered at the college for faculty, staff, and students. In identifying these resources, the college was able to take note of any missing support that needed to be implemented to ensure justice was being maintained. This longitudinal process not only allows the college to see areas where they thrive, but it also highlights any shortcomings of the college while providing the institution with information to spark innovative ideas to strengthen and further promote justice.

Endothelial cell (EC) injury is a crucial contributor to the progression of diabetic kidney disease (DKD), but the specific EC populations and mechanisms involved remain elusive. Kidney ECs (n = 5464) were collected at three timepoints from diabetic BTBRob/ob mice and non-diabetic littermates. Their heterogeneity, transcriptional changes, and alternative splicing during DKD progression were mapped using SmartSeq2 single-cell RNA sequencing (scRNAseq) and elucidated through pathway, network, and gene ontology enrichment analyses. We identified 13 distinct transcriptional EC phenotypes corresponding to different kidney vessel subtypes, confirmed through in situ hybridization and immunofluorescence. EC subtypes along nephrons displayed extensive zonation related to their functions. Differential gene expression analyses in peritubular and glomerular ECs in DKD underlined the regulation of DKD-relevant pathways including EIF2 signaling, oxidative phosphorylation, and IGF1 signaling. Importantly, this revealed the differential alteration of these pathways between the two EC subtypes and changes during disease progression. Furthermore, glomerular and peritubular ECs also displayed aberrant and dynamic alterations in alternative splicing (AS), which is strongly associated with DNA repair. Strikingly, genes displaying differential transcription or alternative splicing participate in divergent biological processes. Our study reveals the spatiotemporal regulation of gene transcription and AS linked to DKD progression, providing insight into pathomechanisms and clues to novel therapeutic targets for DKD treatment.

This paper identifies subgenres of asymmetric virtual reality (AVR) games and proposes the AVR Game Genre (AVRGG) framework for developing AVR games. We examined 66 games “in the wild” to develop the AVRGG and used it to identify 5 subgenres of AVR games including David(s) vs. Goliath, Hide and Seek, Perspective Puzzle, Order Simulation, and Lifeline. We describe these genres, which account for nearly half of the 66 games reviewed, in terms of the AVRGG framework that highlights salient asymmetries in the mechanics, dynamics, and aesthetics categories. To evaluate the usefulness of the AVRGG framework, we conducted four workshops (two with the AVRGG framework and two without) with novice game designers who generated 16 original AVR game concepts. Comparisons between the workshop groups, observations of the design sessions, focus groups, and surveys showed the promise and limitations of the AVRGG framework as a design tool. We found that novice designers were able to understand and apply the AVRGG framework after only a brief introduction. The observations indicated two primary challenges that AVR designers face: balancing the game between VR and non-VR player(s) and generating original game concepts. The AVRGG framework helped overcome the balancing concerns due to its ability to inspire novice game designers with example subgenres and draw attention to the asymmetric mechanics and competitive/cooperative nature of games. While half of those who used the AVRGG framework to design with created games that fit directly into existing subgenres, the other half viewed the subgenres as “creative constraints” useful in jumpstarting novel game designs that combined, modified, or purposefully avoided existing subgenres. Additional benefits and limitations of the AVRGG framework are outlined in the paper.

Protein aggregation is a predominant feature of many neurodegenerative diseases, including synucleinopathies, which are characterized by cellular inclusions containing α-Synuclein (αSyn) phosphorylated at serine 129 (pSer129). In the present study, we characterized the development of αSyn pre-formed fibril (PFF)-induced pSer129-αSyn pathology in F28tg mice overexpressing human wild-type αSyn, as well as in ex vivo organotypic cultures and in vitro primary cultures from the same mouse model. Concurrently, we collected cerebrospinal fluid (CSF) from mice and conditioned media from ex vivo and in vitro cultures and quantified the levels of neurofilament light chain (NFL), a biomarker of neurodegeneration. We found that the intra-striatal injection of PFFs induces the progressive spread of pSer129-αSyn pathology and microglial activation in vivo, as well as modest increases in NFL levels in the CSF. Similarly, PFF-induced αSyn pathology occurs progressively in ex vivo organotypic slice cultures and is accompanied by significant increases in NFL release into the media. Using in vitro primary hippocampal cultures, we further confirmed that pSer129-αSyn pathology and NFL release occur in a manner that correlates with the fibril dose and the level of the αSyn protein. Overall, we demonstrate that αSyn pathology is associated with NFL release across preclinical models of seeded αSyn aggregation and that the pharmacological inhibition of αSyn aggregation in vitro also significantly reduces NFL release.

Abstract Diabetic kidney disease (DKD) is the leading cause of kidney failure worldwide. Mortality and morbidity associated with DKD are increasing with the global prevalence of type 2 diabetes. Chronic, sub-clinical, non-resolving inflammation contributes to the pathophysiology of renal and cardiovascular disease associated with diabetes. Inflammatory biomarkers correlate with poor renal outcomes and mortality in patients with DKD. Targeting chronic inflammation may therefore offer a route to novel therapeutics for DKD. However, the DKD patient population is highly heterogeneous, with varying etiology, presentation and disease progression. This heterogeneity is a challenge for clinical trials of novel anti-inflammatory therapies. Here, we present a conceptual model of how chronic inflammation affects kidney function in five compartments: immune cell recruitment and activation; filtration; resorption and secretion; extracellular matrix regulation; and perfusion. We believe that the rigorous alignment of pathophysiological insights, appropriate animal models and pathology-specific biomarkers may facilitate a mechanism-based shift from recruiting ‘all comers’ with DKD to stratification of patients based on the principal compartments of inflammatory disease activity.