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Abstract The widespread use of devices like mobile phones and wearables allows for automatic monitoring of human daily activities, generating vast datasets that offer insights into long-term human behavior. A structured and controlled data collection process is essential to unlock the full potential of this information. While wearable sensors for physical activity monitoring have gained significant traction in healthcare, sports science, and fitness applications, securing diverse and comprehensive datasets for research and algorithm development poses a notable challenge. In this proof-of-concept study, we underscore the significance of semantic representation in enhancing data interoperability and facilitating advanced analytics for physical activity sensor observations. Our approach focuses on enhancing the usability of physical activity datasets by employing a medical-grade (CE certified) sensor to generate synthetic datasets. Additionally, we provide insights into ethical considerations related to synthetic datasets. The study conducts a comparative analysis between real and synthetic activity datasets, assessing their effectiveness in mitigating model bias and promoting fairness in predictive analysis. We have created an ontology for semantically representing observations from physical activity sensors and conducted predictive analysis on data collected using MOX2-5 activity sensors. Until now, there has been a lack of publicly available datasets for physical activity collected with MOX2-5 activity monitoring medical grade (CE certified) device. The MOX2-5 captures and transmits high-resolution data, including activity intensity, weight-bearing, sedentary, standing, low, moderate, and vigorous physical activity, as well as steps per minute. Our dataset consists of physical activity data collected from 16 adults (Male: 12; Female: 4) over a period of 30–45 days (approximately 1.5 months), yielding a relatively small volume of 539 records. To address this limitation, we employ various synthetic data generation methods, such as Gaussian Capula (GC), Conditional Tabular General Adversarial Network (CTGAN), and Tabular General Adversarial Network (TABGAN), to augment the dataset with synthetic data. For both the authentic and synthetic datasets, we have developed a Multilayer Perceptron (MLP) classification model for accurately classifying daily physical activity levels. The findings underscore the effectiveness of semantic ontology in semantic search, knowledge representation, data integration, reasoning, and capturing meaningful relationships between data. The analysis supports the hypothesis that the efficiency of predictive models improves as the volume of additional synthetic training data increases. Ontology and Generative AI hold the potential to expedite advancements in behavioral monitoring research. The data presented, encompassing both real MOX2-5 and its synthetic counterpart, serves as a valuable resource for developing robust methods in activity type classification. Furthermore, it opens avenues for exploration into research directions related to synthetic data, including model efficiency, detection of generated data, and considerations regarding data privacy.

Low crop diversification in highly productive areas has led to declines in total organic carbon (TOC) in soil, essential nutrients for plant’s growth and microbial diversity/activity. This could have an impact on the movement of water in the soil profile and, consequently, on the production of crops. To address these challenges there is growing support for crops intensification, which involves increasing the number/variety of crops throughout the year. The purpose of this study was to assess the influence of crop intensification on the initial infiltration of water in the upper layer of the soil profile and the activity/abundance of soil microorganisms involved in the turnover of TOC and phosphorus (P). Three crop regimes were assessed in a long-term experiment established in the southeast of the Argentinean Pampas: without intensification (Monocrop: soybean), intensified (Cover crop: CC [oat]/soybean) and Rotation (CC [oat]/soybean-corn-wheat). Soil in the Monocrop regime exhibited the highest sorptivity values and a lower TOC, suggesting a higher initial rate of water entry into the profile, which could break down soil aggregates. Under rotation, the highest infiltration rate was recorded, which would guarantee more water flow into the profile. Intensified soils showed the highest total glomalin content and root colonization with arbuscular mycorrhizal fungi (AMF), which are known to contribute to plant nutrient uptake and growth and soil aggregate stability. Trichoderma abundance and their P-solubilizing capacity were also higher under Rotation, which could favor AMF activity. Correlation analysis revealed a significant positive correlation between sorptivity and glomalin under Rotation. Our study suggests that soils from the Argentinean south-eastern Humid Pampas under crop intensification promote soil water storage and maintenance of soil structure in the upper layers compared to Monocrop, which could be attributed —at least in part— to a greater microbiological activity and TOC content.

Abstract Introduction Lichen planus (LP) is an inflammatory skin disorder that can present in various forms across the body, including lesions on the skin (cutaneous LP [CLP]), scalp (lichen planopilaris [LPP]) and mucosal regions (mucosal LP [MLP]). Several existing patient-reported outcome measures (PROMs) were identified for potential use in LP clinical development programs. This study aimed to assess the content validity and psychometric measurement properties of the Dermatology Life Quality Index (DLQI), Epworth Sleepiness Scale (ESS), Scalpdex and Oral Lichen Planus Symptom Severity Measure (OLPSSM) in an LP population. Methods Patients completed the PROs at various time points as part of an international Phase 2 clinical study in adults with MLP (n = 37), LPP (n = 37) and CLP (n = 37). Test-retest reliability, construct validity and sensitivity to change were assessed. In addition, qualitative cognitive debriefing interviews were conducted with adults with MLP (n = 20), LPP (n = 19) and CLP (n = 19) in the USA and Germany to examine the PROM content validity. Results The DLQI demonstrated adequate reliability and validity, although its ability to detect change was modest and most items were considered not relevant in qualitative interviews. The ESS had good reliability but limited evidence of validity and ability to detect change. Conceptual relevance varied according to the qualitative interview data. The Scalpdex was miscellaneous across domains, but the ‘Symptoms’ domain performed well overall. Overall, Scalpdex concepts were reported as relevant by most LPP patients interviewed. The OLPSSM demonstrated good psychometric properties and strong evidence of content validity. Conclusions The psychometric and qualitative findings support the use of the OLPSSM and Scalpdex within specific LP subtypes but cautioned use of the DLQI. Administration of the ESS is not recommended in LP because of its poor psychometric performance. Given these limitations, further validation of non-specific disease measures is needed and/or the development of additional LP-specific PROMs. Trial Registration NCT04300296.

Abstract Introduction Lichen planus (LP) is an inflammatory skin disorder that can present in various forms across the body, including lesions on the skin (cutaneous LP [CLP]), scalp (lichen planopilaris [LPP]), and mucosal regions (mucosal LP [MLP]). Qualitative exploration of the patient experience of LP, notably symptoms and impacts on health-related quality of life (HRQoL), is limited. A scarcity of research was also identified relating to emotional wellbeing impacts of CLP patients. Two qualitative studies were conducted with LP patients to address these gaps. Methods Study 1 consisted of exit interviews conducted with a subset of adult patients with MLP (n = 5), CLP (n = 4), and LPP (n = 4) enrolled in an LP clinical study in the United States (US) to explore the patient experience. Study 2 consisted of independent qualitative interviews conducted with adult CLP patients (n = 13) from the US and Germany to further explore impacts on emotional wellbeing. Results Exit interviews found that itch , pain, and skin lesions were most frequently reported as signs/symptoms of LP. Itch and skin lesions were experienced across all LP subtypes, while pain was only reported by CLP and MLP patients. These signs/symptoms impacted HRQoL including emotional wellbeing (frustration, embarrassment), daily activities (oral hygiene, clothing options), social functioning (intimacy, social activities), and physical functioning (chewing/swallowing, opening/moving mouth). Impacts on activities of daily living (ADL) and physical functioning were mostly experienced by MLP patients. Independent qualitative interviews, which further explored impacts of CLP on patients’ emotional wellbeing, identified frustration, worry, sadness, embarrassment, and depression as the most frequently experienced. Conclusion The findings contribute to the literature by providing qualitative insights into signs/symptoms and HRQoL impacts of LP, from the adult patient perspective. The findings also highlight the importance of considering assessment of HRQoL impacts in future clinical LP research, particularly impacts on emotional wellbeing when selecting instruments for assessment of HRQoL in the CLP population. Trial Registration NCT04300296.

Sex identification is a common objective in molecular ecology. While many vertebrates display sexual dimorphism, determining the sex can be challenging in certain situations, such as species lacking clear sex-related phenotypic characteristics or in studies using non-invasive methods. In these cases, DNA analyses serve as valuable tools not only for sex determination but also for validating sex assignment based on phenotypic traits. In this study, we developed a bioinformatic framework for sex assignment using genomic data obtained through GBS, and having an available closely related genome assembled at the chromosome level. Our method consists of two ad hoc indexes that rely on the different properties of the mammalian heteromorphic sex chromosomes. For this purpose, we mapped RAD-seq loci to a reference genome and then obtained missingness and coverage depth values for the autosomes and X and Y chromosomes of each individual. Our methodology successfully determined the sex of 165 fur seals that had been phenotypically sexed in a previous study and 40 sea lions sampled in a non-invasive way. Additionally, we evaluated the accuracy of each index in sequences with varying average coverage depths, with Index Y proving greater reliability and robustness in assigning sex to individuals with low-depth coverage. We believe that the approach presented here can be extended to any animal taxa with known heteromorphic XY/ZW sex chromosome systems and that it can tolerate various qualities of GBS sequencing data.

Wound healing after skin injury is a complex process, particularly in equines where leg wounds are prevalent and their repair is complicated due to the anatomical characteristics. Conventional treatments are not effective enough. The umbilical cord offers an unlimited source of adult mesenchymal stem cells (ucMSCs) from Wharton’s jelly tissue. The present study aims to demonstrate the safety and therapeutic potential of the allogeneic use of equine ucMSCs (e-ucMSCs) in the healing of severe equine leg wounds. The methods employed were the isolation, culture and expansion of e-ucMSCs. Flow cytometry and a PCR assay were used for cell characterization. This study included an immunomodulation assay, a murine pre-clinical trial and the first phase of an equine clinical trial. Our results showed that e-ucMSCs express a functional HLA-G homolog, EQMHCB2. In the immunomodulation assay, the e-ucMSCs inhibited the proliferation of activated equine peripheral blood mononuclear cells (e-PBMCs). In the murine pre-clinical trial, e-ucMSCs reduced healing time by 50%. In the equine clinical trial, the injection of e-ucMSCs into severe leg lesions improved the closure time and quality of the tissues involved, regenerating them without fibrous tissue scar formation. In conclusion, the results of this study suggest that e-ucMSCs can be used allogeneically for wound healing by creating a tolerogenic environment.

Abstract A significant proportion of the personal and economic burden of schizophrenia can be attributed to the late diagnosis or misdiagnosis of the disorder. A novel, objective diagnostic approaches could facilitate the early detection and treatment of schizophrenia and improve patient outcomes. In the present study, we aimed to identify robust schizophrenia-specific blood biomarkers, with the goal of developing an accurate diagnostic model. The levels of selected serum and peripheral blood mononuclear cell (PBMC) markers relevant to metabolic and immune function were measured in healthy controls (n = 26) and recent-onset schizophrenia patients (n = 36) using multiplexed immunoassays and flow cytometry. Analysis of covariance revealed significant upregulation of insulin receptor (IR) and fatty acid translocase (CD36) levels in T helper cells (F = 10.75, P = 0.002, Q = 0.024 and F = 21.58, P = 2.8 × 10−5, Q = 0.0004, respectively), as well as downregulation of glucose transporter 1 (GLUT1) expression in monocytes (F = 21.46, P = 2.9 × 10−5, Q = 0.0004). The most robust predictors, monocyte GLUT1 and T helper cell CD36, were used to develop a diagnostic model, which showed a leave-one-out cross-validated area under the receiver operating characteristic curve (AUC) of 0.78 (95% CI: 0.66–0.92). The diagnostic model was validated in two independent datasets. The model was able to distinguish first-onset, drug-naïve schizophrenia patients (n = 34) from healthy controls (n = 39) with an AUC of 0.75 (95% CI: 0.64–0.86), and also differentiated schizophrenia patients (n = 22) from patients with other neuropsychiatric conditions, including bipolar disorder, major depressive disorder and autism spectrum disorder (n = 68), with an AUC of 0.83 (95% CI: 0.75–0.92). These findings indicate that PBMC-derived biomarkers have the potential to support an accurate and objective differential diagnosis of schizophrenia.

Abstract There have been no new drugs for the treatment of schizophrenia in several decades and treatment resistance represents a major unmet clinical need. The drugs that exist are based on serendipitous clinical observations rather than an evidence-based understanding of disease pathophysiology. In the present review, we address these bottlenecks by integrating common, rare, and expression-related schizophrenia risk genes with knowledge of the druggability of the human genome as a whole. We highlight novel drug repurposing opportunities, clinical trial candidates which are supported by genetic evidence, and unexplored therapeutic opportunities in the lesser-known regions of the schizophrenia genome. By identifying translational gaps and opportunities across the schizophrenia disease space, we discuss a framework for translating increasingly well-powered genetic association studies into personalized treatments for schizophrenia and initiating the vital task of characterizing clinically relevant drug targets in underexplored regions of the human genome.

Patchy saturation is a term used in the seismic prospecting literature to describe the state of a geological formation in which two immiscible pore fluids prevail in mesoscopic-scale clusters. If the pore fluids have contrasting compressibilities, wave-induced fluid pressure diffusion (FPD) processes may induce significant attenuation and velocity dispersion on seismic waves. Biot's monophasic poroelasticity theory is widely used to model the seismic response of rocks containing binary patches of two immiscible pore fluids. Even though effective fluid approximations may help to represent more realistic partially saturated patches using Biot's monophasic equations, the so inferred dissipation may not be representative of actual biphasic FPD phenomena. In this work, Biot's equations for mono- and biphasic fluids are combined to model FPD processes in porous media, comprising fully and partially saturated patches. An analytical solution for one-dimensional layered patchy-saturated media is presented which permits to explain some, as of yet enigmatic, experimentally observed characteristics such as increased seismic attenuation and stiffening effects occurring at low saturations. The results show that the existence of an additional diffusive wave mode within partially saturated patches may render conventional binary and effective fluid approaches incorrect and error prone. [ABSTRACT FROM AUTHOR]

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Abstract Cancer immunotherapies based mainly on the blockade of immune-checkpoint (IC) molecules by anti-IC antibodies offer new alternatives for treatment in oncological diseases. However, a considerable proportion of patients remain unresponsive to them. Hence, the development of novel clinical immunotherapeutic approaches and/or targets are crucial.W In this context, targeting the immune-checkpoint HLA-G/ILT2/ILT4 has caused great interest since it is abnormally expressed in several malignancies generating a tolerogenic microenvironment. Here, we used CRISPR/Cas9 gene editing to block the HLA-G expression in two tumor cell lines expressing HLA-G, including a renal cell carcinoma (RCC7) and a choriocarcinoma (JEG-3). Different sgRNA/Cas9 plasmids targeting HLA-G exon 1 and 2 were transfected in both cell lines. Downregulation of HLA-G was reached to different degrees, including complete silencing. Most importantly, HLA-G − cells triggered a higher in vitro response of immune cells with respect to HLA-G + wild type cells. Altogether, we demonstrated for the first time the HLA-G downregulation through gene editing. We propose this approach as a first step to develop novel clinical immunotherapeutic approaches in cancer.

Engineered nanoparticles (ENPs), products from modern nanotechnologies, can potentially impact the marine environment to pose serious threats to marine ecosystems. However, the cellular responses of marine phytoplankton to ENPs are still not well established. Here, we investigate four different diatom species (Odontella mobiliensis, Skeletonema grethae, Phaeodactylum tricornutum, Thalassiosira pseudonana) and one green algae (Dunaliella tertiolecta) for their extracellular polymeric substances (EPS) release under model ENP treatments: 25 nm titanium dioxide (TiO2), 10-20 nm silicon dioxide (SiO2), and 15-30 nm cerium dioxide (CeO2). We found SiO2 ENPs can significantly stimulate EPS release from these algae (200-800%), while TiO2 ENP exposure induced the lowest release. Furthermore, the increase of intracellular Ca2+ concentration can be triggered by ENPs, suggesting that the EPS release process is mediated through Ca2+ signal pathways. With better understanding of the cellular mechanism mediated ENP-induced EPS release, potential preventative and safety measures can be developed to mitigate negative impact on the marine ecosystem.

Abstract Patagonia is an understudied area, especially when it comes to population genomic studies with relevance to fishery management. However, the dynamic and heterogeneous landscape in this area can harbor an important but cryptic genetic population structure. Once such information is revealed, it can be integrated into the management of infrequently investigated species. Eleginops maclovinus is a protandrous hermaphrodite species with economic importance for local communities that are currently managed as a single genetic unit. In this study, we sampled five locations distributed across a salinity cline from Northern Patagonia to investigate the genetic population structure of E. maclovinus. We used restriction site‐associated DNA (RAD) sequencing and outlier tests to obtain neutral and adaptive loci, using FST and GEA approaches. We identified a spatial pattern of structuration with gene flow and spatial selection by environmental association. Neutral and adaptive loci showed two and three genetic groups, respectively. The effective population sizes estimated ranged from 572 (Chepu) to 14,454 (Chaitén) and were influenced more by locality than by salinity cline. We found loci putatively associated with salinity suggesting that salinity may act as a selective driver in E. maclovinus populations. These results suggest a complex interaction between genetic drift, gene flow, and natural selection in this area. Our findings also suggest several evolutionary significant units in this area, and the information should be integrated into the management of this species. We discussed the significance of these results for fishery management and suggest future directions to improve our understanding of how E. maclovinus has adapted to the dynamic waters of Northern Patagonia.

Abstract Mental health disorders are a leading cause of disability worldwide. Challenges such as disease heterogeneity, incomplete characterization of the targets of existing drugs and a limited understanding of functional interactions of complex genetic risk loci and environmental factors have compromised the identification of novel drug candidates. There is a pressing clinical need for drugs with new mechanisms of action which address the lack of efficacy and debilitating side effects of current medications. Here we discuss a novel strategy for neuropsychiatric drug discovery which aims to address these limitations by identifying disease-related functional responses (‘functional cellular endophenotypes’) in a variety of patient-derived cells, such as induced pluripotent stem cell (iPSC)-derived neurons and organoids or peripheral blood mononuclear cells (PBMCs). Disease-specific alterations in cellular responses can subsequently yield novel drug screening targets and drug candidates. We discuss the potential of this approach in the context of recent advances in patient-derived cellular models, high-content single-cell screening of cellular networks and changes in the diagnostic framework of neuropsychiatric disorders.

Abstract The vast personal and economic burden of mood disorders is largely caused by their under- and misdiagnosis, which is associated with ineffective treatment and worsening of outcomes. Here, we aimed to develop a diagnostic algorithm, based on an online questionnaire and blood biomarker data, to reduce the misdiagnosis of bipolar disorder (BD) as major depressive disorder (MDD). Individuals with depressive symptoms (Patient Health Questionnaire-9 score ≥5) aged 18–45 years were recruited online. After completing a purpose-built online mental health questionnaire, eligible participants provided dried blood spot samples for biomarker analysis and underwent the World Health Organization World Mental Health Composite International Diagnostic Interview via telephone, to establish their mental health diagnosis. Extreme Gradient Boosting and nested cross-validation were used to train and validate diagnostic models differentiating BD from MDD in participants who self-reported a current MDD diagnosis. Mean test area under the receiver operating characteristic curve (AUROC) for separating participants with BD diagnosed as MDD (N = 126) from those with correct MDD diagnosis (N = 187) was 0.92 (95% CI: 0.86–0.97). Core predictors included elevated mood, grandiosity, talkativeness, recklessness and risky behaviour. Additional validation in participants with no previous mood disorder diagnosis showed AUROCs of 0.89 (0.86–0.91) and 0.90 (0.87–0.91) for separating newly diagnosed BD (N = 98) from MDD (N = 112) and subclinical low mood (N = 120), respectively. Validation in participants with a previous diagnosis of BD (N = 45) demonstrated sensitivity of 0.86 (0.57–0.96). The diagnostic algorithm accurately identified patients with BD in various clinical scenarios, and could help expedite accurate clinical diagnosis and treatment of BD.