The Implementation Moonshot Project for Alternative Chemical Testing (IMPACT) toward a Human Exposome Project.

The Human Exposome Project aims to revolutionize our understanding of how environmental exposures affect human health by systematically cataloging and analyzing the myriad exposures individuals encounter throughout their lives. This initiative draws a parallel with the Human Genome Project, expanding the focus from genetic factors to the dynamic and complex nature of environ-mental interactions. The project leverages advanced methodologies such as omics technologies, biomonitoring, microphysiological systems (MPS), and artificial intelligence (AI), forming the foun-dation of exposome intelligence (EI) to integrate and interpret vast datasets. Key objectives include identifying exposure-disease links, prioritizing hazardous chemicals, enhancing public health and regulatory policies, and reducing reliance on animal testing. The Implementation Moonshot Project for Alternative Chemical Testing (IMPACT), spearheaded by the Center for Alternatives to Animal Testing (CAAT), is a new element in this endeavor, driving the creation of a public-private part-nership toward a Human Exposome Project with a stakeholder forum in 2025. Establishing robust infrastructure, fostering interdisciplinary collaborations, and ensuring quality assurance through sys-tematic reviews and evidence-based frameworks are crucial for the project's success. The expected outcomes promise transformative advancements in precision public health, disease prevention, and a more ethical approach to toxicology. This paper outlines the strategic imperatives, challenges, and opportunities that lie ahead, calling on stakeholders to support and participate in this landmark initiative for a healthier, more sustainable future.

This paper outlines a proposal for a "Human Exposome Project" to comprehensively study how environmental exposures affect human health throughout our lives. The exposome refers to all the environmental factors we are exposed to, from chemicals to diet to stress. The project aims to use advanced technologies like artificial intelligence, lab-grown mini-organs, and detailed biological measurements to map how different exposures impact our health. This could help identify causes of diseases and guide better prevention strategies. Key goals include finding links between spe­cific exposures and health problems, determining which chemicals are most concerning, improving public health policies, and reducing animal testing. The project requires collaboration between researchers, government agencies, companies, and others. While ambitious, this effort could revo­lutionize our understanding of environmental health risks. The potential benefits for improving health and preventing disease make this an important endeavor to a precise and comprehensive approach to public health and disease prevention.

An investment decision framework for offshore CCUS project under interval-valued fermatean fuzzy environment.

Carbon Capture, Utilization and Storage (CCUS) is an indispensable technology for achieving a net-zero emission society. The offshore CCUS project is still in its infancy. To promote its sustainable development, developing a comprehensive framework for investment decision-making is very crucial. First, a comprehensive evaluation criteria system is established. Second, in order to characterize the ambiguity and uncertainty of information in the process of making decisions, the interval-valued fermatean fuzzy set (IVFFS) is introduced, and the extended variance method of IVFFS is proposed to systematically calculate the weights of experts. Then, the power weighted average (PWA) operator based similarity measure of IVFFSs is developed to aggregate different expert information. Meanwhile, the fuzzy-weighted zero-inconsistency (FWZIC) method and the method based on the removal effects of criteria (MEREC) are used to determine the criteria weights. In addition, considering the interactions between the criteria, we introduce the Hamacher operator into the measurement of alternatives and ranking according to the compromise solution (MARCOS) method to select the optimal alternative in the interval-valued fermatean fuzzy (IVFF) environment. The suggested framework is then used to analyse a case study. After that, sensitivity and comparative analyses are conducted to confirm its robustness and viability. This study creates a practical investment framework for offshore CCUS projects, identifies a number of investment-sensitive criteria and provides management insights. The proposed framework expands the methods and applications in the field of decision-making and provides a scientific approach for investment decision-making in offshore CCUS projects, which can be a useful reference for managers.

Microbial artists: the role of parasite microbiomes in explaining colour polymorphism among amphipods and potential link to host manipulation.

Parasite infections are increasingly reported to change the microbiome of the parasitised hosts, while parasites bring their own microbes to what can be a multi-dimensional interaction. For instance, a recent hypothesis suggests that the microbial communities harboured by parasites may play a role in the well-documented ability of many parasites to manipulate host phenotype, and explain why the degree to which host phenotype is altered varies among conspecific parasites. Here, we explored whether the microbiomes of both hosts and parasites are associated with variation in host manipulation by parasites. Using colour quantification methods applied to digital images, we investigated colour variation among uninfected Transorchestia serrulata amphipods, as well as amphipods infected with Plagiorhynchus allisonae acanthocephalans and with a dilepidid cestode. We then characterised the bacteriota of amphipod hosts and of their parasites, looking for correlations between host phenotype and the bacterial taxa associated with hosts and parasites. We found large variation in amphipod colours, and weak support for a direct impact of parasites on the colour of their hosts. Conversely, and most interestingly, the parasite's bacteriota was more strongly correlated with colour variation among their amphipod hosts, with potential impact of amphipod-associated bacteria as well. Some bacterial taxa found associated with amphipods and parasites may have the ability to synthesise pigments, and we propose they may interact with colour determination in the amphipods. This study provides correlational support for an association between the parasite's microbiome and the evolution of host manipulation by parasites and host-parasite interactions more generally.

Student-led Doctor of Nursing Practice projects in the clinical environment: Viewpoint from hospital-based nurse scientists and leaders.

BACKGROUND: Exponential increases in Doctor of Nursing Practice (DNP) program enrollment have come with a rapid rise in the number of capstone projects conducted in clinical environments. However, misaligned priorities between students, faculty, and clinician leaders have created significant challenges. PURPOSE: Identify opportunities to strengthen collaboration between academic and clinical stakeholders to better support DNP projects and education. METHODS: Experienced hospital-based nurse leaders engaged in scholarly discourse supplemented by policy and research in DNP education. FINDINGS: Facilitating a DNP project requires significant investment of time, resources, and funds from the healthcare institution. Discord has arisen due to unclear responsibilities or decision-making ability for clinical stakeholders, ethical dilemmas for students who are also employees of the clinical site, and mismatched priorities between clinical need and student/academic project desires. Clinical leaders have raised significant concerns about DNP project proposals that are research-focused, diverge from healthcare institution goals, and lack a sustainability plan. DISCUSSION: Fortification of academic-practice partnerships and clarification of roles in the DNP student project are necessary to ensure that the project is of educational value to the student, a demonstration of learning for faculty, and of sustained clinical value to the healthcare system.

Development of maximum relevant prior feature ensemble (MRPFE) index to characterize future drought using global climate models.

Drought is one of the foremost outcomes of global warming and global climate change. It is a serious threat to humans and other living beings. To reduce the adverse impact of drought, mitigation strategies as well as sound projections of extreme events are essential. This research aims to strengthen the robustness of anticipated twenty-first century drought by combining different Global Climate Models (GCMs). In this article, we develop a new drought index, named Maximum Relevant Prior Feature Ensemble index that is based on the newly proposed weighting scheme, called weighted ensemble (WE). In the application, this study considers 32 randomly scattered grid points within the Tibetan Plateau region and 18 GCMs of Coupled Model Intercomparison Project Phase 6 (CMIP6) of precipitation. In this study, the comparative inferences of the WE scheme are made with the traditional simple model averaging (SMA). To investigate the trend and long-term probability of various classes, this research employs Markov chain steady states probability, Mann-Kendall trend test, and Sen's Slope estimator. The outcomes of this research are twofold. Firstly, the comparative inference shows that the proposed weighting scheme has greater efficiency than SMA to conflate GCMs. Secondly, the research indicates that the Tibetan Plateau is projected to experience "moderate drought (MD)" in the twenty-first century.

Glucose Fluctuations in Acute Ischemic Stroke.

INTRODUCTION: The Oxfordshire Community Stroke Project denotes four subtypes of ischemic stroke (total and partial anterior infarct, posterior, and lacunar). Hyperglycemia has been associated with a larger infarct size and poor prognosis. AIM: The purpose of the study was to investigate the correlation of glucose fluctuations with the Oxford sub-categories and patient outcomes using a blinded continuous glucose monitoring system. METHODS: This is a non-interventional prospective observational study. Stroke patients with symptoms onset in the last 24h, participated in the study. A glucose sensor was placed for 72 hours. Disability was assessed using the modified Rankin Scale. Stroke subtypes were compared with total mean glucose and time in range using ANOVA analysis. Multiple ordinal logistic regression was employed to analyze outcomes and survival. RESULTS: The sample consisted of 105 diabetic and non-diabetic patients. The overall mean glucose was 127.06 mg/dL and the time in range (70-140 mg/dL) was 70.98%. There was no significant difference between the stroke sub-categories and the total mean glucose. For every one-point increase in the time in range, we expect a 1.5% reduction in the odds of having a worse outcome. Patients with total anterior infarct are 2.31 times more likely to have a worse outcome than lacunar patients. CONCLUSION: The utilization of the Oxford classification may not be necessary for managing acute ischemic stroke glucose levels. Achieving glucose regulation and an increase in time in range can be attained through meticulous control, potentially extending life expectancy. Continuous glucose monitors may aid in achieving this objective.

Using Novel Multimethod Evaluation Approaches to Understand Complex Food System Interventions: Insights from a Supply Chain Intervention Intended to Improve Nutrition.

Background: A "food system" approach to improve diet quality by intervening within areas such as food supply chains is gaining prominence. However, evidence of such interventions' impact, and understanding of appropriate methods to evaluate them, is lacking. Objectives: We present an impact evaluation of an intervention that aimed to increase consumption of nutritious foods by supporting food-producing firms in Kenya. In doing so, we demonstrate how multiple methods, including those from other disciplines, can be used to evaluate a complex food systems intervention. Methods: Four methods focused on food-producing firms and their management, including a survey of intervention participants (n = 83 individuals), a "laboratory-in-the-field" experiment (n = 83 individuals), baseline/endline data on firm performance (n = 71 firms), and semistructured interviews (n = 19 firms). Three methods focused on consumers in neighborhoods targeted by a supported firm: a randomized field experiment tested effects of making a supported product exhaustively available on consumers' purchases and consumption (n = 1295 consumers); 3 discrete choice experiments (n = 1295 consumers) tested factors influencing consumers' willingness to pay for foods with relevant characteristics. Results: Among firms, we saw suggestive evidence of increased networking and business relationships, while laboratory-in-the-field experiments indicated the intervention might foster cooperation among participants. Qualitative interviews suggested that the intervention enabled firms to increase production, improve management, increase revenues, and lower costs. Baseline/endline data confirmed a positive effect only on the launch of new products and hiring workers. In the field experiment, consumption of the supported product increased in areas where it was made available relative to a control group, but this did not increase overall consumption of the food type or dietary diversity. Conclusions: Results showed positive signs of the intervention improving firm-level outcomes but limited impact on consumers' diet quality. The evaluation also demonstrates how diverse methods can be used to evaluate complex interventions.

Validation of a New Test for Measuring the Contrast Sensitivity Function (Optopad-CSF) at Near Vision.

Our purpose is to develop and validate a new iPad-based contrast sensitivity (CS) test for measuring the contrast sensitivity function at near vision (Optopad-CSF). A total of 200 eyes of 100 healthy subjects (ages 17-63) were evaluated in a comparative study between the Optopad-CSF test (near vision) and the CSV-1000E test (distance vision). The agreement between tests was assessed with the index of contrast sensitivity (ICS) and the area under the curve (AUC). CS for all the spatial frequencies in both eyes showed a negative significant correlation with age, and corrected distance, and near visual acuities (r ≤ -0.512, p ≤ 0.013). A significantly lower CS was found with the Optopad-CSF test in the over-40-year-old subgroup for all the spatial frequencies evaluated compared to the below-40 subgroup (p ≤ 0.008). The mean AUC of the Optopad-CSF test (5.84) was twice that of the CSV-1000E test (2.76). The mean ICS of the Optopad-CSF (-0.019) and CSV-1000E (-0.075) tests showed similar values, both close to 0 (p = 0.3). There was a weak but significant correlation between the Optopad-CSF and CSV-1000E ICS tests (r = 0.246, p < 0.02). A range of normality for the values obtained with the Optopad-CSF test was calculated. The mean CS values in 16 bilateral cataract patients were out of the normal range for all the spatial frequencies evaluated (p < 0.001). Optopad-CSF is a valid portable system for measuring CS at near vision for five spatial frequencies, allowing the detection of age-related changes in CSF with age and CSF loss in cataracts, with no ceiling effect.

Identifying pesticides of high concern for ecosystem, plant, animal, and human health: A comprehensive field study across Europe and Argentina.

The widespread and excessive use of pesticides in modern agricultural practices has caused pesticide contamination of the environment, animals, and humans, with confirmed serious health consequences. This study aimed to identify the 20 most critical substances based on an analysis of detection frequency (DF) and median concentrations (MC) across environmental and biological matrices. A sampling campaign was conducted across 10 case study sites in Europe and 1 in Argentina, each encompassing conventional and organic farming systems. We analysed 209 active substances in a total of 4609 samples. All substances ranked among the 20 most critical were detected in silicon wristbands worn by humans and animals and indoor dust from both farming systems. Five of them were detected in all environmental matrices. Overall, higher values of DF and MC, including in the blood plasma of animals and humans, were recorded in samples of conventional compared to organic farms. The differences between farming systems were greater in the environmental samples and less in animal and human samples. Ten substances were detected in animal blood plasma from conventional farms and eight in animal blood plasma from organic farms. Two of those, detected in both farming systems, are classified as hazardous for mammals (acute). Five substances detected in animal blood plasma from organic farms and seven detected in animal blood plasma from conventional farms are classified as hazardous for mammals (dietary). Three substances detected in human blood plasma are classified as carcinogens. Seven of the substances detected in human blood plasma are classified as endocrine disruptors. Six substances, of which five were detected in human blood plasma, are hazardous for reproduction/development. Efforts are needed to elucidate the unknown effects of mixtures, and it is crucial that such research also considers biocides and banned substances, which constitute a baseline of contamination that adds to the effect of substances used in agriculture.

Urban diabetes: analysis of diabetes prevalence in cities of the Lombardy region participating in the cities changing diabetes project.

AIM: The urban population increases by about 60 million people/year. Urbanization, unhealthy lifestyle and aging of the population are reflected in a constant growth in the prevalence of diabetes. In 2014, Steno Diabetes Centre in Copenhagen, University College London and Novo Nordisk, launched the Cities Changing Diabetes® program with the aim of creating a unified movement that would stimulate policy-makers to prioritize urban diabetes. METHODS: The socio-demographic data derive from (1) ISTAT (National Institute of Statistics of Italy), (2) ATS Metropolitan City of Milan, (3) ATS Val Padana-Cremona, (4) ATS Insubria-Varese, (5) The unemployment rates of the various municipalities have been extrapolated from an ISTAT-MEF elaboration published by Sole 24 Ore journal. RESULTS: In the different sanitary districts of the Metropolitan City of Milan, a strong linear correlation was found between the prevalence of diabetes and the prevalence of heart disease (R = 0.695, p < 0.001), as well as between the prevalence of diabetes and of nephropathies (R = 0.316, p < 0.001). The analysis concerning the province of Cremona showed a fair correlation between the prevalence of diabetes and cardiovascular disease (R = 0.658, p < 0.001). Even for the municipalities of Varese, the analysis documented a good correlation between the prevalence of diabetes and heart disease (R = 0.419, p < 0.001), but not between diabetes and nephropathies. CONCLUSIONS: Interesting differences in the relationship of diabetes prevalence with several diseases and socio-demographic factors have been found when comparing the metropolitan City of Milan with two smaller size cities as Varese and Cremona. Our present data confirm the hypothesis that urban diabetes will be the challenge for our society during the next decades.

Risk factors for colonisation by Multidrug-Resistant bacteria in critical care units.

INTRODUCTION: Antimicrobial resistance is a major public health challenge recognised by the WHO as an urgent global healthcare concern. Patients in Intensive Care Units (ICUs) are particularly prone to colonisation and/or infection by multidrug-resistant organisms (MDROs). OBJECTIVES: Delineate the epidemiological characteristics and risk factors for MDROs colonisation in mixed ICUs and Resuscitation Units by focusing on initial and nosocomial colonisation. MATERIAL AND METHODS: A descriptive observational study with analytical elements. It uses the Zero-Resistance register from the Preventive Medicine Service of the Albacete General University Hospital (Spain) from April 2016 to December 2021. It identifies the risk factors for MDROs colonisation. RESULTS: Of 7,541 cases, 61.0 % with initial colonisation had risk factors for MDROs versus 34.0 % not colonised upon hospitalisation (p < 0.001). Significant risk factors for initial colonisation included hospitalisation for ≥ 5 days within the last 3 months, prior MDROs colonisation/infection and institutionalization. No significant risk factor differences were found for nosocomial colonisation. An association between longer ICU stays and nosocomial colonisation (p < 0.001) was noted. CONCLUSIONS: Significant risk factors for initial MDROs colonisation were hospitalisation for ≥ 5 days in the last 3 months, prior MDROs colonisation/infection and institutionalisation. Longer ICU stays increased the nosocomial colonisation risk. IMPLICATIONS FOR CLINICAL PRACTICE: This study underscores the importance to early identify and manage patients at risk for MDROs colonisation in ICUs. By recognising factors (i.e. previous hospitalisations, existing colonisation or infection, impact of prolonged ICU stay), healthcare providers can implement targeted strategies to mitigate the spread of MDROs; e.g. enhanced surveillance, stringent infection control measures and judicious antibiotics use. Our findings highlight the need for a comprehensive approach to manage antimicrobial resistance in critical care settings to ultimately improve patient outcomes and reduce MDROs burden in hospitals.

Use of Azithromycin Attributable to Acute SARS-CoV-2 Infection.

PURPOSE: In the early stages of the COVID-19 pandemic, preliminary results that later proved to be incorrect suggested the possible efficacy of anti-infective drugs such as azithromycin for the treatment of SARS-CoV-2 infection. These preliminary data may have influenced the prescription of azithromycin. However, no individual-level data linking the use of this antibiotic to acute SARS-CoV-2 infection are available. The present analysis aims to fill this gap. METHODS: A retrospective population-based cohort design was used including patients diagnosed with SARS-CoV-2 infection in the period ranging from February 2020 to February 2022. The data source for antibiotic consumption was the drug database of outpatient prescriptions of Emilia-Romagna Region (Italy). Antibiotics were classified according to the Anatomical Therapeutic Chemical (ATC) classification system. Consumption rates and percentages of azithromycin DDDs (defined daily doses) during the acute phase of the infection were compared with a previous control period and with the post-acute phase. Analyses were stratified by four groups according to the prevalent virus variant at time of diagnosis. RESULTS: Comparing the previous control period with the acute phase of infections, the rates of azithromycin consumption (DDD per 1000 individuals per day) increased from 1.17 to 23.11, from 0.80 to 33.03, from 0.81 to 21.01, and from 1.02 to 9.76, in the pre-Alpha, Alpha, Delta, and Omicron periods, respectively. Similarly, the percentages of individuals receiving azithromycin, and the azithromycin DDDs percentages over total systemic antibiotics DDDs increased in acute phases of infection compared with control periods. The consumption rates and percentages returned to preinfection levels in the post-acute phase. In the study period, 12.9% of the use of azithromycin in the entire adult population of Emilia-Romagna was attributable to acute SARS-CoV-2 infection. CONCLUSIONS: Considering the low likelihood of bacterial coinfections, the increased azithromycin consumption in the acute phase of SARS-CoV-2 infection suggests inappropriate prescribing of this antibiotic.

The Transdiagnostic Connectome Project: a richly phenotyped open dataset for advancing the study of brain-behavior relationships in psychiatry.

An important aim in psychiatry is the establishment of valid and reliable associations linking profiles of brain functioning to clinically relevant symptoms and behaviors across patient populations. To advance progress in this area, we introduce an open dataset containing behavioral and neuroimaging data from 241 individuals aged 18 to 70, comprising 148 individuals meeting diagnostic criteria for a broad range of psychiatric illnesses and a healthy comparison group of 93 individuals. These data include high-resolution anatomical scans, multiple resting-state, and task-based functional MRI runs. Additionally, participants completed over 50 psychological and cognitive assessments. Here, we detail available behavioral data as well as raw and processed MRI derivatives. Associations between data processing and quality metrics, such as head motion, are reported. Processed data exhibit classic task activation effects and canonical functional network organization. Overall, we provide a comprehensive and analysis-ready transdiagnostic dataset, which we hope will accelerate the identification of illness-relevant features of brain functioning, enabling future discoveries in basic and clinical neuroscience.

Fostering reflective impact orientation in transdisciplinary research-A multi-method workshop format.

The primary objective of transdisciplinary research (TDR) is to contribute to the solution of complex 'real-world' problems by integrating heterogeneous knowledge and achieving societal effects. However, establishing a continuous impact orientation during TDR processes remains a challenge, as the necessary tools are not yet sufficiently available. We developed and tested a half-day workshop format for strengthening the impact-oriented project management and research activities of seven TDR projects. Our findings indicate that the reflective impact workshops supported participants in pursuing societal effects systematically. Applying the methodological approach also fosters TDR process qualities such as knowledge integration. Conducted at different project stages, the results can serve as a basis for monitoring and adapting the project design. The reflective approach•includes scientific and non-scientific TDR project team members,•draws on Theory of Change as a conceptual framework and motivates participants to reflect on plausible impact pathways and make implicit assumptions about interlinkages between different forms of societal effects explicit, and•provides results which enable project partners to adjust their project design for greater societal effectiveness.

A genome assembly of the American black bear, Ursus americanus, from California.

The American black bear, Ursus americanus, is a widespread and ecologically important species in North America. In California, the black bear plays an important role in a variety of ecosystems and serves as an important species for recreational hunting. While research suggests that the populations in California are currently healthy, continued monitoring is critical to maintaining healthy populations, with genomic analyses providing an important surveillance tool. Here we report a high-quality, near chromosome-level genome assembly from a U. americanus sample from California. The primary assembly has a total length of 2.5 Gb contained in 317 scaffolds, a contig N50 of 58.9 Mb, a scaffold N50 of 67.6 Mb, and a BUSCO completeness score of 96%. This U. americanus genome assembly from a California sample will provide an important resource for the targeted management of black bear populations in California, with the goal of achieving an appropriate balance between the recreational value of black bears and the maintenance of viable populations. The high quality of this genome assembly will also make it a valuable resource for comparative genomic analyses among black bear populations and among bear species.

Paramedic clinical practice guideline development in Australia and New Zealand: A qualitative descriptive analysis.

BACKGROUND: This collaborative study by The Australasian College of Paramedicine's Clinical Practice Guidelines (CPG) Working Group aimed to examine CPG development practices in Australian and New Zealand ambulance services. METHODS: Employing a qualitative descriptive design, the research utilised thematic analysis to extract insights from interviews with eleven experts actively involved in CPG development. The study embraced a nominalist and constructivist approach, recognising the intricate connection between individual experiences and the realities of CPG development in the paramedic field. RESULTS: Key findings revealed significant heterogeneity in CPG development practices, emphasising a lack of formal training and a substantial reliance on existing guidelines. The study highlighted challenges in project management flexibility, limited research capacity, and inconsistencies in external consultations and resource utilisation. CONCLUSION: The study recommends adopting project management frameworks, investing in training, and utilising evidence evaluation methodologies like GRADE. It emphasises the need for multidisciplinary teams and formal expertise in evidence synthesis, advocating for targeted training programs. Funding challenges highlight the importance of dedicated budgets and collaborative efforts for resource allocation. Knowledge translation and implementation issues underscore the significance of training programs for evidence evaluation and knowledge translation in overcoming these challenges.

Water transfer projects and microplastics: Analyzing changes in lake environments with a focus on Wabu Lake, China.

Microplastics are widespread in freshwaters, yet their interaction with navigational structures remains unclear. This study compared the distribution and characteristics of microplastics before and after navigation in Wabu Lake. Microplastic concentrations decreased significantly in both surface water and sediment due to navigation opened, from 13.7 ± 6.56 to 3.12 ± 1.8 p L-1 (p < 0.001) and from 568 ± 286 to 174 ± 60.2 p kg-1 (p < 0.001), respectively. Acrylates copolymer was frequently detected in surface water and sediment before navigation, whereas the dominant polymer after navigation was chlorinated polyisoprene in surface water and chlorinated polyethylene in sediment. The results showed that three-years dredging induced relatively severe microplastic pollution before navigation, however, these microplastics were apparently eliminated after navigation, as the distribution and characteristics of microplastics thoroughly varied. This study provides a valuable finding that microplastic transport process can be facilitated by water transfer project, which should be considered for preventing microplastic pollution.

Predictors of Outcomes in Cerebellar Stroke: A Retrospective Cohort Study From the National Inpatient Sample Data.

Cerebellar strokes have high morbidity and mortality due to bleeding or edema, leading to increased pressure in the posterior fossa. This retrospective cohort study analyzed three outcomes following a cerebellar stroke: in-hospital mortality, length of hospital stay, and total hospitalization costs. It uses data from the National Inpatient Sample (NIS) and aims to identify the predictors of outcomes in cerebellar stroke patients, including 464,324 patients, 18 years of age and older, hospitalized between 2010 and 2015 in US hospitals with cerebellar strokes. In our study, for every decade age increased beyond 59 years, there was a significant increase in mortality; those aged 80+ years had 5.65 odds of mortality (95% CI: 5.32-6.00; P < 0.0001). Significant differences in patient characteristics were observed between patients who survived to discharge and those who did not, including older age (77.4 vs. 70.3 years; P < 0.0001), female sex (58% vs. 52%; P < 0.0001), and being transferred from another healthcare facility (17% vs. 10%; P < 0.0001). Patients admitted directly rather than through the emergency department were more likely to die (29% vs. 16%; P < 0.0001). The mortality rate was lower for blacks (OR: 0.75; P < 0.0001), Hispanics (OR: 0.91; P = 0.005), and Asians (OR: 0.89; P = 0.03), as compared to the white population, for females in comparison to males, and geographically, in all other areas (Midwest, South, and West) in contrast to the Northeast. Cerebellar stroke incidence and high mortality were seen in the traditional stroke belt. Mortality is also affected by the severity of the disease and increases with the Charlson Comorbidity Index (CCI), All Patient Refined Diagnosis Related Groups (APR-DRG) scores, and indirectly by place of receiving care, length of stay (LOS), cost of stay, type of insurance, and emergency department admissions. LOS increased with age, in males in the Northeast, and was less in whites compared to other races. Trend analysis showed a decrease in LOS and costs from 2010 to 2015. Increased costs were seen in non-whites, males, higher household income based on zip code, being covered under Medicaid, transfers, CCI ≥ 5, and discharges in the western US. Median household income based on the patient's zip code was well-balanced between those who lived and those who died (P = 0.091). However, payers were not evenly distributed between the two groups (P < 0.0001 for the overall comparison). A higher proportion of discharges associated with in-hospital mortality were covered under Medicare (70% vs. 65% in the died vs. lived groups, respectively). Fewer discharges were associated with death if they were covered by commercial insurance or paid for out-of-pocket (15% vs. 19% for commercial insurance and 3% vs. 5% for out-of-pocket). In-hospital mortality was associated with a longer length of hospital stay (5.6 days vs. 4.5 days; P < 0.0001) and higher costs ($16,815 vs. $11,859; P < 0.0001). Variables that were significantly associated with lower total costs were older age, having commercial insurance, paying out-of-pocket or other payers, not being admitted through the emergency department, having a lower comorbidity index (CCI = 1-2), and being discharged from a hospital that was small- or medium-sized, located in the Midwest or South, and/or was non-teaching (rural or urban).

"I've got yer back": A community art and anatomy project.

This article describes a community collaborative project, "I've got yer back," that utilized the craft of needle felting to raise awareness and develop understanding of the anatomy of the human spine. The project took place in 2023 and engaged with participants from across the United Kingdom and abroad and its completion was timed to coincide with National Back Health Awareness week in October 2023. We describe the process of creating a vertebra using needle felt and examine how the particularities of the process and the use of the sense of touch helped participants notice and understand the complex form of the human vertebra. We consider how the project encompassed creative processes of hands-on learning to enhance knowledge about this aspect of human anatomy. We discuss how the project evolved to include public and academic participation in a shared goal and argue for the effectiveness of seemingly simple and straightforward art or craft workshops in teaching relatively complex science. The article includes detailed feedback from participants who reflect on the process of learning through making and how it went on to affect individuals in very different, and sometimes very personal, ways.

Predicting dyslipidemia incidence: unleashing machine learning algorithms on Lifestyle Promotion Project data.

BACKGROUND: Dyslipidemia, characterized by variations in plasma lipid profiles, poses a global health threat linked to millions of deaths annually. OBJECTIVES: This study focuses on predicting dyslipidemia incidence using machine learning methods, addressing the crucial need for early identification and intervention. METHODS: The dataset, derived from the Lifestyle Promotion Project (LPP) in East Azerbaijan Province, Iran, undergoes a comprehensive preprocessing, merging, and null handling process. Target selection involves five distinct dyslipidemia-related variables. Normalization techniques and three feature selection algorithms are applied to enhance predictive modeling. RESULT: The study results underscore the potential of different machine learning algorithms, specifically multi-layer perceptron neural network (MLP), in reaching higher performance metrics such as accuracy, F1 score, sensitivity and specificity, among other machine learning methods. Among other algorithms, Random Forest also showed remarkable accuracies and outperformed K-Nearest Neighbors (KNN) in metrics like precision, recall, and F1 score. The study's emphasis on feature selection detected meaningful patterns among five target variables related to dyslipidemia, indicating fundamental shared unities among dyslipidemia-related factors. Features such as waist circumference, serum vitamin D, blood pressure, sex, age, diabetes, and physical activity related to dyslipidemia. CONCLUSION: These results cooperatively highlight the complex nature of dyslipidemia and its connections with numerous factors, strengthening the importance of applying machine learning methods to understand and predict its incidence precisely.