Genomic Loci Influencing Cue-Reactivity in Heterogeneous Stock Rats.

Addiction vulnerability is associated with the tendency to attribute incentive salience to reward predictive cues; both addiction and the attribution of incentive salience are influenced by environmental and genetic factors. To characterize the genetic contributions to incentive salience attribution, we performed a genome-wide association study (GWAS) in a cohort of 1,645 genetically diverse heterogeneous stock (HS) rats. We tested HS rats in a Pavlovian conditioned approach task, in which we characterized the individual responses to food-associated stimuli ("cues"). Rats exhibited either cue-directed "sign-tracking" behavior or food-cup directed "goal-tracking" behavior. We then used the conditioned reinforcement procedure to determine whether rats would perform a novel operant response for unrewarded presentations of the cue. We found that these measures were moderately heritable (SNP heritability, h2 = .189-.215). GWAS identified 14 quantitative trait loci (QTLs) for 11 of the 12 traits we examined. Interval sizes of these QTLs varied widely. 7 traits shared a QTL on chromosome 1 that contained a few genes (e.g. Tenm4, Mir708) that have been associated with substance use disorders and other mental health traits in humans. Other candidate genes (e.g. Wnt11, Pak1) in this region had coding variants and expression-QTLs in mesocorticolimbic regions of the brain. We also conducted a Phenome-Wide Association Study (PheWAS) on other behavioral measures in HS rats and found that regions containing QTLs on chromosome 1 were also associated with nicotine self-administration in a separate cohort of HS rats. These results provide a starting point for the molecular genetic dissection of incentive salience and provide further support for a relationship between attribution of incentive salience and drug abuse-related traits.

Multi-ancestry meta-analysis of tobacco use disorder identifies 461 potential risk genes and reveals associations with multiple health outcomes.

Tobacco use disorder (TUD) is the most prevalent substance use disorder in the world. Genetic factors influence smoking behaviours and although strides have been made using genome-wide association studies to identify risk variants, most variants identified have been for nicotine consumption, rather than TUD. Here we leveraged four US biobanks to perform a multi-ancestral meta-analysis of TUD (derived via electronic health records) in 653,790 individuals (495,005 European, 114,420 African American and 44,365 Latin American) and data from UK Biobank (ncombined = 898,680). We identified 88 independent risk loci; integration with functional genomic tools uncovered 461 potential risk genes, primarily expressed in the brain. TUD was genetically correlated with smoking and psychiatric traits from traditionally ascertained cohorts, externalizing behaviours in children and hundreds of medical outcomes, including HIV infection, heart disease and pain. This work furthers our biological understanding of TUD and establishes electronic health records as a source of phenotypic information for studying the genetics of TUD.

A phenome-wide association and Mendelian randomisation study of alcohol use variants in a diverse cohort comprising over 3 million individuals.

BACKGROUND: Alcohol consumption is associated with numerous negative social and health outcomes. These associations may be direct consequences of drinking, or they may reflect common genetic factors that influence both alcohol consumption and other outcomes. METHODS: We performed exploratory phenome-wide association studies (PheWAS) of three of the best studied protective single nucleotide polymorphisms (SNPs) in genes encoding ethanol metabolising enzymes (ADH1B: rs1229984-T, rs2066702-A; ADH1C: rs698-T) using up to 1109 health outcomes across 28 phenotypic categories (e.g., substance-use, mental health, sleep, immune, cardiovascular, metabolic) from a diverse 23andMe cohort, including European (N ≤ 2,619,939), Latin American (N ≤ 446,646) and African American (N ≤ 146,776) populations to uncover new and perhaps unexpected associations. These SNPs have been consistently implicated by both candidate gene studies and genome-wide association studies of alcohol-related behaviours but have not been investigated in detail for other relevant phenotypes in a hypothesis-free approach in such a large cohort of multiple ancestries. To provide insight into potential causal effects of alcohol consumption on the outcomes significant in the PheWAS, we performed univariable two-sample and one-sample Mendelian randomisation (MR) analyses. FINDINGS: The minor allele rs1229984-T, which is protective against alcohol behaviours, showed the highest number of PheWAS associations across the three cohorts (N = 232, European; N = 29, Latin American; N = 7, African American). rs1229984-T influenced multiple domains of health. We replicated associations with alcohol-related behaviours, mental and sleep conditions, and cardio-metabolic health. We also found associations with understudied traits related to neurological (migraines, epilepsy), immune (allergies), musculoskeletal (fibromyalgia), and reproductive health (preeclampsia). MR analyses identified evidence of causal effects of alcohol consumption on liability for 35 of these outcomes in the European cohort. INTERPRETATION: Our work demonstrates that polymorphisms in genes encoding alcohol metabolising enzymes affect multiple domains of health beyond alcohol-related behaviours. Understanding the underlying mechanisms of these effects could have implications for treatments and preventative medicine. FUNDING: MVJ, NCK, SBB, SSR and AAP were supported by T32IR5226 and 28IR-0070. SSR was also supported by NIDA DP1DA054394. NCK and RBC were also supported by R25MH081482. ASH was supported by funds from NIAAA K01AA030083. JLMO was supported by VA 1IK2CX002095. JLMO and JJMM were also supported by NIDA R21DA050160. JJMM was also supported by the Kavli Postdoctoral Award for Academic Diversity. EGA was supported by K01MH121659 from the NIMH/NIH, the Caroline Wiess Law Fund for Research in Molecular Medicine and the ARCO Foundation Young Teacher-Investigator Fund at Baylor College of Medicine. MSA was supported by the Instituto de Salud Carlos III and co-funded by the European Union Found: Fondo Social Europeo Plus (FSE+) (P19/01224, PI22/00464 and CP22/00128).

Race and Ethnicity Are Related to Undesirable Home Health Care Outcomes in Seriously Ill Older Adults.

OBJECTIVES: Medicare Home Health Care (HHC) services are integral to the care of homebound seriously ill older adults requiring ongoing specialized medical care. Although disparities in health outcomes are well documented in inpatient and primary care, disparities experienced by historically marginalized racial and ethnic groups underrepresented in HHC are understudied. This study aimed to examine the relationship between individual characteristics and differences in HHC health outcomes for seriously ill older adults. DESIGN: Secondary data analysis, repeated measure. SETTING AND PARTICIPANTS: Seriously ill older adults who received HHC in 2016 in the HHC Outcome and Assessment Information Set (OASIS). METHODS: Start of care and discharge data from the 2016 HCC OASIS were used to examine the relationship between individual characteristics and differences in HHC health outcomes identified by the Centers for Medicare and Medicaid Services as key indicators of quality in HHC, including dyspnea, pain frequency, cognitive functioning, and presence of unhealed pressure ulcer stage II or higher. A generalized ordered logit model with partial proportional odds was used for the ordinal categorical outcomes and a logistic regression was used for the binary dependent variable (pressure ulcer). RESULTS: Findings indicated that of 227,402 seriously ill individuals with an HHC episode in 2016, those from underrepresented racial and ethnic groups had between 14% and 57% higher odds of worse health outcomes compared with non-Hispanic White patients with the exception of pain frequency. CONCLUSIONS AND IMPLICATIONS: For people living with serious illness, there are significant differences in Medicare HHC health outcomes when comparing underrepresented racial or ethnic beneficiaries with White counterparts. More research is needed to understand how health care processes such as referral patterns or time to care initiation, and structural factors such as HHC agency quality and neighborhood social deprivation are related to health differences observed in the population.

A Preliminary Validation of an Optimal Cutpoint in Total Number of Patient-Reported Symptoms in Head and Neck Cancer for Effective Alignment of Clinical Resources with Patients' Symptom Burden.

Background: Patients with head and neck cancer (HNC) often experience high symptom burden leading to lower quality of life (QoL). Objective: This study aims to conceptually model optimal cutpoint by examining where total number of patient-reported symptoms exceeds patients' coping capacity, leading to a decline in QoL in patients with HNC. Methods: Secondary data analysis of 105 individuals with HNC enrolled in a clinical usefulness study of the NYU Electronic Patient Visit Assessment (ePVA)©, a digital patient-reported symptom measure. Patients completed ePVA and European Organization for Research and Treatment of Cancer (EORTC©) QLQ-C30 v3.0. The total number of patient-reported symptoms was the sum of symptoms as identified by the ePVA questionnaire. Analysis of variance (ANOVA) was used to define optimal cutpoint. Results: Study participants had a mean age of 61.5, were primarily male (67.6%), and had Stage IV HNC (53.3%). The cutpoint of 10 symptoms was associated with significant decline of QoL (F= 44.8, P<.0001), dividing the population into categories of low symptom burden (< 10 symptoms) and high symptom burden (≥ 10 symptoms). Analyses of EORTC© function subscales supported the validity of 10 symptoms as the optimal cutpoint (Physical: F=28.3, P<.0001; Role: F=21.6, P<.0001; Emotional: F=9.5, P=.003; Social: F=33.1, P<.0001). Conclusions: In HNC, defining optimal cutpoints in the total number of patient-reported symptoms is feasible. Implications for Practice: Cutpoints in the total number of patient-reported symptoms may identify patients experiencing a high symptom burden from HNC. Foundational: Using optimal cutpoints of the total number of patient-reported symptoms may help effectively align clinical resources with patients' symptom burden.

Antibody response to malaria vaccine candidates in pregnant women with Plasmodium falciparum and Schistosoma haematobium infections.

Malaria in pregnancy has severe consequences for the mother and foetus. Antibody response to specific malaria vaccine candidates (MVC) has been associated with a decreased risk of clinical malaria and its outcomes. We studied Plasmodium falciparum (Pf) and Schistosoma haematobium (Sh) infections and factors that could influence antibody responses to MVC in pregnant women. A total of 337 pregnant women receiving antenatal care (ANC) and 139 for delivery participated in this study. Pf infection was detected by qPCR and Sh infection using urine filtration method. Antibody levels against CSP, AMA-1, GLURP-R0, VAR2CSA and Pfs48/45 MVC were quantified by ELISA. Multivariable linear regression models identified factors associated with the modulation of antibody responses. The prevalence of Pf and Sh infections was 27% and 4% at ANC and 7% and 4% at delivery. Pf infection, residing in Adidome and multigravidae were positively associated with specific IgG response to CSP, AMA-1, GLURP-R0 and VAR2CSA. ITN use and IPTp were negatively associated with specific IgG response to GLURP-R0 and Pfs48/45. There was no association between Sh infection and antibody response to MVC at ANC or delivery. Pf infections in pregnant women were positively associated with antibody response to CSP, GLURP-R0 and AMA-1. Antibody response to GLURP-R0 and Pfs48/45 was low for IPTp and ITN users. This could indicate a lower exposure to Pf infection and low malaria prevalence observed at delivery.

Phylosymbiosis and metabolomics resolve phenotypically plastic and cryptic sponge species in the genus Agelas across the Caribbean basin.

Fundamental to holobiont biology is recognising how variation in microbial composition and function relates to host phenotypic variation. Sponges often exhibit considerable phenotypic plasticity and also harbour dense microbial communities that function to protect and nourish hosts. One of the most prominent sponge genera on Caribbean coral reefs is Agelas. Using a comprehensive set of morphological (growth form, spicule), chemical and molecular data on 13 recognised species of Agelas in the Caribbean basin, we were able to define only five species (=clades) and found that many morphospecies designations were incongruent with phylogenomic and population genetic analyses. Microbial communities were also strongly differentiated between phylogenetic species, showing little evidence of cryptic divergence and relatively low correlation with morphospecies assignment. Metagenomic analyses also showed strong correspondence to phylogenetic species, and to a lesser extent, geographical and morphological characters. Surprisingly, the variation in secondary metabolites produced by sponge holobionts was explained by geography and morphospecies assignment, in addition to phylogenetic species, and covaried significantly with a subset of microbial symbionts. Spicule characteristics were highly plastic, under greater impact from geographical location than phylogeny. Our results suggest that while phenotypic plasticity is rampant in Agelas, morphological differences within phylogenetic species affect functionally important ecological traits, including the composition of the symbiotic microbial communities and metabolomic profiles.

Implementation Outcomes for the SLUMBER Sleep Improvement Program in Long-Term Care.

OBJECTIVES: To describe the implementation of a mentored staff-delivered sleep program in nursing facilities. DESIGN: Modified stepped-wedge unit-level intervention. SETTING AND PARTICIPANTS: This program was implemented in 2 New York City nursing facilities, with partial implementation (due to COVID-19) in a third facility. METHODS: Expert mentors provided staff webinars, in-person workshops, and weekly sleep pearls via text messaging. We used the integrated Promoting Action on Research Implementation in Health Services (i-PARiHS) framework as a post hoc approach to describe key elements of the SLUMBER implementation. We measured staff participation in unit-level procedures and noted their commentary during unit workshops. RESULTS: We completed SLUMBER within 5 units across 2 facilities and held 15 leadership meetings before and during program implementation. Sessions on each unit included 3 virtual webinar presentations and 4 in-person workshops for each nursing shift, held over a period of 3 to 4 months. Staff attendance averaged >3 sessions per individual staff member. Approximately 65% of staff present on each unit participated in any given session. Text messaging was useful for engagement, educational reinforcement, and encouraging attendance. We elevated staff as experts in the care of their residents as a strategy for staff engagement and behavior change and solicited challenging cases from staff during workshops to provide strategies to address resident behavior and encourage adoption when successful. CONCLUSIONS AND IMPLICATIONS: Engaging staff, leadership, residents, and family of nursing facilities in implementing a multicomponent sleep quality improvement program is feasible for improving nursing facilities' sleep environment. The program required gaining trust at multiple levels through presence and empathy, and reinforcement mechanisms (primarily text messages). To improve scalability, SLUMBER could evolve from an interdisciplinary investigator-based approach to internal coaches in a train-the-trainer model to effectively and sustainably implement this program to improve sleep quality for facility residents.

Improving Sleep Using Mentored Behavioral and Environmental Restructuring (SLUMBER).

OBJECTIVES: To evaluate the impact of a mentoring program to encourage staff-delivered sleep-promoting strategies on sleep, function, depression, and anxiety among skilled nursing facility (SNF) residents. DESIGN: Modified stepped-wedge unit-level intervention. SETTING AND PARTICIPANTS: Seventy-two residents (mean age 75 ± 15 years; 61.5% female, 41% non-Hispanic white, 35% Black, 20% Hispanic, 3% Asian) of 2 New York City urban SNFs. METHODS: Expert mentors provided SNF staff webinars, in-person workshops, and weekly sleep pearls via text messaging. Resident data were collected at baseline, post-intervention (V1), and 3-month follow-up (V2), including wrist actigraphy, resident behavioral observations, Pittsburgh Sleep Quality Index (PSQI), Patient Health Questionnaire-9 (PHQ-9) depression scale, Brief Anxiety and Depression Scale (BADS), Brief Cognitive Assessment Tool (BCAT), and select Minimum Data Set 3.0 (MDS 3.0) measures. Linear mixed models were fit for continuous outcomes and mixed-effects logistic models for binary outcomes. Outcomes were modeled as a function of time. Planned contrasts compared baseline to V1 and V2. RESULTS: There was significant improvement in PSQI scores from baseline to V1 (P = .009), and from baseline to V2 (P = .008). Other significant changes between baseline and V1 included decreased depression (PHQ-9) (P = .028), increased daytime observed out of bed (P ≤ .001), and increased daytime observed being awake (P < .001). At V2 (vs baseline) being observed out of bed decreased (P < .001). Daytime sleeping by actigraphy increased from baseline to V1 (P = .004), but not V2. MDS 3.0 activities of daily living and pain showed improvements by the second quarter following implementation of SLUMBER (P's ≤ .034). There were no significant changes in BADS or BCAT between baseline and V1 or V2. CONCLUSIONS AND IMPLICATIONS: SNF residents had improvements in sleep quality and depression with intervention, but improvements were not sustained at 3-month follow-up. The COVID-19 pandemic led to premature study termination, so full impacts remain unknown.

A revamped rat reference genome improves the discovery of genetic diversity in laboratory rats.

The seventh iteration of the reference genome assembly for Rattus norvegicus-mRatBN7.2-corrects numerous misplaced segments and reduces base-level errors by approximately 9-fold and increases contiguity by 290-fold compared with its predecessor. Gene annotations are now more complete, improving the mapping precision of genomic, transcriptomic, and proteomics datasets. We jointly analyzed 163 short-read whole-genome sequencing datasets representing 120 laboratory rat strains and substrains using mRatBN7.2. We defined ∼20.0 million sequence variations, of which 18,700 are predicted to potentially impact the function of 6,677 genes. We also generated a new rat genetic map from 1,893 heterogeneous stock rats and annotated transcription start sites and alternative polyadenylation sites. The mRatBN7.2 assembly, along with the extensive analysis of genomic variations among rat strains, enhances our understanding of the rat genome, providing researchers with an expanded resource for studies involving rats.

Rare and Common Variants Associated with Alcohol Consumption Identify a Conserved Molecular Network.

Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, rare variants have only begun to be studied for their role in alcohol consumption. No studies have examined whether common and rare variants implicate the same genes and molecular networks. To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N=666,978) and whole exome sequencing data (Genebass, N=393,099) to identify a set of common and rare variants for alcohol consumption. Gene-based analysis of each dataset have implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified only by rare variant analysis, but have been associated with related psychiatric traits. We then used a network colocalization procedure to propagate the common and rare gene sets onto a shared molecular network, revealing significant overlap. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. 74 of the genes in the network were previously implicated in comorbid psychiatric or substance use disorders, but had not previously been identified for alcohol-related behaviors, including EXOC2, EPM2A, CACNB3, and CACNG4. Differential gene expression analysis showed enrichment in the liver and several brain regions supporting the role of network genes in alcohol consumption. Thus, genes implicated by common and rare variants identify shared functions relevant to alcohol consumption, which also underlie psychiatric traits and substance use disorders that are comorbid with alcohol use.

Environmental enrichment promotes adaptive responding during tests of behavioral regulation in male heterogeneous stock rats.

Organisms must regulate their behavior flexibly in the face of environmental challenges. Failure can lead to a host of maladaptive behavioral traits associated with a range of neuropsychiatric disorders, including attention deficit hyperactivity disorder, autism, and substance use disorders. This maladaptive dysregulation of behavior is influenced by genetic and environmental factors. For example, environmental enrichment produces beneficial neurobehavioral effects in animal models of such disorders. The present study determined the effects of environmental enrichment on a range of measures related to behavioral regulation using a large cohort of male, outbred heterogeneous stock (HS) rats as subjects. Subjects were reared from late adolescence onwards either in pairs in standard housing with minimal enrichment (n = 200) or in groups of 16 in a highly enriched environment consisting of a large multi-level cage filled with toys, running wheels, and shelters (n = 64). Rats were subjected to a battery of tests, including: (i) locomotor response to novelty, (ii) light reinforcement, (iii) social reinforcement, (iv) reaction time, (v) a patch-depletion foraging test, (vi) Pavlovian conditioned approach, (vii) conditioned reinforcement, and (viii) cocaine conditioned cue preference. Results indicated that rats housed in the enriched environment were able to filter out irrelevant stimuli more effectively and thereby regulate their behavior more efficiently than standard-housing rats. The dramatic impact of environmental enrichment suggests that behavioral studies using standard housing conditions may not generalize to more complex environments that may be more ethologically relevant.

Interaction models matter: an efficient, flexible computational framework for model-specific investigation of epistasis.

PURPOSE: Epistasis, the interaction between two or more genes, is integral to the study of genetics and is present throughout nature. Yet, it is seldom fully explored as most approaches primarily focus on single-locus effects, partly because analyzing all pairwise and higher-order interactions requires significant computational resources. Furthermore, existing methods for epistasis detection only consider a Cartesian (multiplicative) model for interaction terms. This is likely limiting as epistatic interactions can evolve to produce varied relationships between genetic loci, some complex and not linearly separable. METHODS: We present new algorithms for the interaction coefficients for standard regression models for epistasis that permit many varied models for the interaction terms for loci and efficient memory usage. The algorithms are given for two-way and three-way epistasis and may be generalized to higher order epistasis. Statistical tests for the interaction coefficients are also provided. We also present an efficient matrix based algorithm for permutation testing for two-way epistasis. We offer a proof and experimental evidence that methods that look for epistasis only at loci that have main effects may not be justified. Given the computational efficiency of the algorithm, we applied the method to a rat data set and mouse data set, with at least 10,000 loci and 1,000 samples each, using the standard Cartesian model and the XOR model to explore body mass index. RESULTS: This study reveals that although many of the loci found to exhibit significant statistical epistasis overlap between models in rats, the pairs are mostly distinct. Further, the XOR model found greater evidence for statistical epistasis in many more pairs of loci in both data sets with almost all significant epistasis in mice identified using XOR. In the rat data set, loci involved in epistasis under the XOR model are enriched for biologically relevant pathways. CONCLUSION: Our results in both species show that many biologically relevant epistatic relationships would have been undetected if only one interaction model was applied, providing evidence that varied interaction models should be implemented to explore epistatic interactions that occur in living systems.

An Evolutionary Concept Analysis of the "Fighter" in the Intensive Care Unit.

The purpose of this article was to analyze the concept of "the fighter in the intensive care unit (ICU)" per the scientific literature and the impact this mentality has on care administered in the ICU. A literature review and a concept analysis based on Rodger's evolutionary method were performed to identify surrogate terms, antecedents, attributes, and consequences pertaining to the "fighter" in the ICU. Thirteen articles with a focus on "the fighter" were included in this analysis. There is a strong desire to remain optimistic and maintain high spirits as a coping mechanism in the face of extreme prognostic uncertainty. Themes that emerged from the literature were the need to find inner strength and persist in the face of adversity. The concept of "the fighter in the ICU" can serve as either adaptive or maladaptive coping, depending on the larger clinical picture. Patient experiences in the ICU are fraught with physical and psychological distress. How the patient and family unit cope during this anxiety-provoking time is based on the individual. Maintaining optimism and identifying as a fighter can be healthy ways to adapt to the circumstances. This concept analysis highlights the importance of holistic care and instilling hope particularly as patients may be nearing the end of life.

Evaluating Large Language Models in Extracting Cognitive Exam Dates and Scores.

Importance: Large language models (LLMs) are crucial for medical tasks. Ensuring their reliability is vital to avoid false results. Our study assesses two state-of-the-art LLMs (ChatGPT and LlaMA-2) for extracting clinical information, focusing on cognitive tests like MMSE and CDR. Objective: Evaluate ChatGPT and LlaMA-2 performance in extracting MMSE and CDR scores, including their associated dates. Methods: Our data consisted of 135,307 clinical notes (Jan 12th, 2010 to May 24th, 2023) mentioning MMSE, CDR, or MoCA. After applying inclusion criteria 34,465 notes remained, of which 765 underwent ChatGPT (GPT-4) and LlaMA-2, and 22 experts reviewed the responses. ChatGPT successfully extracted MMSE and CDR instances with dates from 742 notes. We used 20 notes for fine-tuning and training the reviewers. The remaining 722 were assigned to reviewers, with 309 each assigned to two reviewers simultaneously. Inter-rater-agreement (Fleiss' Kappa), precision, recall, true/false negative rates, and accuracy were calculated. Our study follows TRIPOD reporting guidelines for model validation. Results: For MMSE information extraction, ChatGPT (vs. LlaMA-2) achieved accuracy of 83% (vs. 66.4%), sensitivity of 89.7% (vs. 69.9%), true-negative rates of 96% (vs 60.0%), and precision of 82.7% (vs 62.2%). For CDR the results were lower overall, with accuracy of 87.1% (vs. 74.5%), sensitivity of 84.3% (vs. 39.7%), true-negative rates of 99.8% (98.4%), and precision of 48.3% (vs. 16.1%). We qualitatively evaluated the MMSE errors of ChatGPT and LlaMA-2 on double-reviewed notes. LlaMA-2 errors included 27 cases of total hallucination, 19 cases of reporting other scores instead of MMSE, 25 missed scores, and 23 cases of reporting only the wrong date. In comparison, ChatGPT's errors included only 3 cases of total hallucination, 17 cases of wrong test reported instead of MMSE, and 19 cases of reporting a wrong date. Conclusions: In this diagnostic/prognostic study of ChatGPT and LlaMA-2 for extracting cognitive exam dates and scores from clinical notes, ChatGPT exhibited high accuracy, with better performance compared to LlaMA-2. The use of LLMs could benefit dementia research and clinical care, by identifying eligible patients for treatments initialization or clinical trial enrollments. Rigorous evaluation of LLMs is crucial to understanding their capabilities and limitations.

New Trends in Biosurfactants: From Renewable Origin to Green Enhanced Oil Recovery Applications.

Enhanced oil recovery (EOR) processes are technologies used in the oil and gas industry to maximize the extraction of residual oil from reservoirs after primary and secondary recovery methods have been carried out. The injection into the reservoir of surface-active substances capable of reducing the surface tension between oil and the rock surface should favor its extraction with significant economic repercussions. However, the most commonly used surfactants in EOR are derived from petroleum, and their use can have negative environmental impacts, such as toxicity and persistence in the environment. Biosurfactants on the other hand, are derived from renewable resources and are biodegradable, making them potentially more sustainable and environmentally friendly. The present review intends to offer an updated overview of the most significant results available in scientific literature on the potential application of biosurfactants in the context of EOR processes. Aspects such as production strategies, techniques for characterizing the mechanisms of action and the pros and cons of the application of biosurfactants as a principal method for EOR will be illustrated and discussed in detail. Optimized concepts such as the HLD in biosurfactant choice and design for EOR are also discussed. The scientific findings that are illustrated and reviewed in this paper show why general emphasis needs to be placed on the development and adoption of biosurfactants in EOR as a substantial contribution to a more sustainable and environmentally friendly oil and gas industry.

Cerebral Microvascular Perfusion Assessed in Elderly Adults by Spin-Echo Dynamic Susceptibility Contrast MRI at 7 Tesla.

Perfusion measures of the total vasculature are commonly derived with gradient-echo (GE) dynamic susceptibility contrast (DSC) MR images, which are acquired during the early passes of a contrast agent. Alternatively, spin-echo (SE) DSC can be used to achieve specific sensitivity to the capillary signal. For an improved contrast-to-noise ratio, ultra-high-field MRI makes this technique more appealing to study cerebral microvascular physiology. Therefore, this study assessed the applicability of SE-DSC MRI at 7 T. Forty-one elderly adults underwent 7 T MRI using a multi-slice SE-EPI DSC sequence. The cerebral blood volume (CBV) and cerebral blood flow (CBF) were determined in the cortical grey matter (CGM) and white matter (WM) and compared to values from the literature. The relation of CBV and CBF with age and sex was investigated. Higher CBV and CBF values were found in CGM compared to WM, whereby the CGM-to-WM ratios depended on the amount of largest vessels excluded from the analysis. CBF was negatively associated with age in the CGM, while no significant association was found with CBV. Both CBV and CBF were higher in women compared to men in both CGM and WM. The current study verifies the possibility of quantifying cerebral microvascular perfusion with SE-DSC MRI at 7 T.

Thinner inner retinal layers are associated with lower cognitive performance, lower brain volume, and altered white matter network structure-The Maastricht Study.

INTRODUCTION: The retina may provide non-invasive, scalable biomarkers for monitoring cerebral neurodegeneration. METHODS: We used cross-sectional data from The Maastricht study (n = 3436; mean age 59.3 years; 48% men; and 21% with type 2 diabetes [the latter oversampled by design]). We evaluated associations of retinal nerve fiber layer, ganglion cell layer, and inner plexiform layer thicknesses with cognitive performance and magnetic resonance imaging indices (global grey and white matter volume, hippocampal volume, whole brain node degree, global efficiency, clustering coefficient, and local efficiency). RESULTS: After adjustment, lower thicknesses of most inner retinal layers were significantly associated with worse cognitive performance, lower grey and white matter volume, lower hippocampal volume, and worse brain white matter network structure assessed from lower whole brain node degree, lower global efficiency, higher clustering coefficient, and higher local efficiency. DISCUSSION: The retina may provide biomarkers that are informative of cerebral neurodegenerative changes in the pathobiology of dementia.

Variation in Home Healthcare Use by Dementia Status Among a National Cohort of Older Adults.

BACKGROUND: Medicare-funded home healthcare (HHC) delivers skilled nursing, therapy, and related services through visits to the patient's home. Nearly one-third (31%) of HHC patients have diagnosed dementia, but little is currently known regarding how HHC utilization and care delivery differ for persons living with dementia (PLwD). METHODS: We drew on linked 2012-2018 Health and Retirement Study and Medicare claims for a national cohort of 1 940 community-living older adults. We described differences in HHC admission, length of stay, and referral source by patient dementia status and used weighted, multivariable logistic and negative binomial models to estimate the relationship between dementia and HHC visit type and intensity while adjusting for sociodemographic characteristics, health and functional status, and geographic/community factors. RESULTS: PLwD had twice the odds of using HHC during a 2-year observation period, compared to those without dementia (odds ratio [OR]: 2.03; p < .001). They were more likely to be referred to HHC without a preceding hospitalization (49.4% vs 32.1%; p < .001) and incurred a greater number of HHC episodes (1.4 vs 1.0; p < .001) and a longer median HHC length of stay (55.8 days vs 40.0 days; p < .001). Among post-acute HHC patients, PLwD had twice the odds of receiving social work services (unadjusted odds ratio [aOR]: 2.15; p = .008) and 3 times the odds of receiving speech-language pathology services (aOR: 2.92; p = .002). CONCLUSIONS: Findings highlight HHC's importance as a care setting for community-living PLwD and indicate the need to identify care delivery patterns associated with positive outcomes for PLwD and design tailored HHC clinical pathways for this patient subpopulation.

Uveitis Associated with Monogenic Autoinflammatory Syndromes in Children.

Monogenic autoinflammatory syndromes (MAISs), are caused by pathogenic genetic variants in the innate immune system, leading to dysregulation and aberrant inflammasome activation spontaneously or with minimal triggering. The diagnosis and treatment of MAISs can be intricate, relying on an increased recognition of potential differential diagnoses. This review examines the clinical features of MAIS, with a special focus on uveitis. It also evaluates treatment options and assesses the effects of activating molecular and cytokine pathways.