Management Of Disease Research Articles

The Mediator complex subunit MoMed15 plays an important role in conferring sensitivity to isoprothiolane by modulating xenobiotic metabolism in M. oryzae.

Rice blast caused by Magnaporthe oryzae is one of the most economically important rice diseases. Fungicides such as isoprothiolane (IPT) have been used extensively for rice blast control, but resistance to IPT in M. oryzae is an emerging threat. In this study, molecular mechanisms of resistance in IPT-resistant mutants were identified. Through whole-genome sequencing and genetic transformation, we identified the gene MoMed15, encoding a transcriptional glutamine-rich co-activator Mediator complex subunit, in which mutations or deletion resulted in moderate IPT resistance. Further research found that MoMed15 physically interacted with the IPT resistance regulatory factor MoIRR to simultaneously regulate both MoIRR expression and the expression of multiple xenobiotic-metabolizing enzymes in response to IPT stress. We hypothesize that some xenobiotic-metabolizing enzymes enhance IPT toxicity by modifying the IPT structure. Variation of MoMed15 affected the recruitment of the transcriptional Mediator complex and decreased the expression of these xenobiotic-metabolizing enzymes, resulting in moderate IPT resistance. We also found that MoPGR1, encoding a protein that activates cytochrome P450 enzymes, was essential to confer IPT sensitivity, and its expression was directly regulated by MoIRR.IMPORTANCEIsoprothiolane (IPT) has been used extensively for the management of rice blast disease and IPT-resistant subpopulations have emerged in Chinese rice fields. The emergence of resistant pathogen populations has led to a steep increase in fungicide use, increasing pesticide risk for the applicator and the environment. The molecular mechanisms of IPT resistance in M. oryzae remain elusive. In this study, we demonstrated that transcriptional co-activator MoMed15 interacts with IPT resistance regulator MoIRR to recruit the Mediator complex, which promotes the expression of xenobiotic-metabolizing enzymes, leading to exacerbated IPT toxicity. The MoMed15 could be used for IPT resistance detection in rice fields.

Explainable early detection of Alzheimer's disease using ROIs and an ensemble of 138 3D vision transformers.

Early detection and accurate diagnosis of brain morphological abnormalities are essential for the effective management and treatment of Alzheimer's disease (AD) and mild cognitive impairment (MCI). Structural magnetic resonance imaging (MRI) is a powerful support tool to aid in disease diagnosis and prediction. In this research study, we present an innovative approach to predict Alzheimer's disease (AD) and mild cognitive impairment (MCI) using MRI data, which integrates regional interest (ROI)-based methodology and deep learning within a comprehensible framework. The proposed method involves dividing the brain into 138 predetermined sections based on anatomical information. Next, we apply three-dimensional vision transformers (3D-ViTs) to each ROI individually, harnessing the power of deep learning. To improve prediction accuracy, we employ a deep belief network (DBN) as an ensemble learning model. Evaluating our approach on the baseline structural MRI dataset obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort, and comparing it against five other competing models, we demonstrate its performance across four binary classification tasks and a three-class classification test (AD vs MCI vs CN (Cognitively Normal)). The proposed system outperforms existing models and provides interpretable insights into the brain regions that significantly contribute to solving each classification problem. Our findings align with the existing body of literature and hold promise for guiding future research directions in this domain.

Health Monitoring and Prediction Using Non-invasive Sensors in IoT Environment

Introduction: IoT's blend with non-invasive sensors has made health state prediction possible and constant real-time monitoring transformed healthcare. Using photoplethysmography (PPG) and electrocardiograms (ECG), this device evaluates important parameters including heart rate, blood oxygen saturation, and blood pressure. As healthcare systems face increasing demands, this technology provides a patient-centered and efficient method for long-term health tracking—needed for early intervention and management of chronic diseases. Objectives: The main goal is to evaluate using time-series data from PPG and ECG sensors the efficiency of an IoT-enabled health monitoring system coupled with machine learning models in predicting health conditions including arrhythmias and hypoxia. Methods: This system detects events based on temporal pattern recognition by use of Long Short-Term Memory (LSTM) networks and Random Forest classifiers. Noise reduction is preprocessed and wearable device data is labeled for training of machine learning models. The design combines wearable sensors, a smartphone app, and cloud-based analysis for continuous monitoring and real-time input. Results: Experimental data shows that the LSTM model attained a 95% accuracy while the Random Forest classifier attained a 92.5% accuracy. Both models displayed remarkable accuracy and recall even while the LSTM model excels in identifying anomalies in time-series data and the Random Forest classifier skillfully detects health events depending on certain criteria. Conclusions: This study demonstrates the capability of IoT-based health monitoring systems to enhance patient outcomes through continuous, non-invasive monitoring and predictive analytics. Despite its potential, difficulties persist, including data security, sensor reliability, and energy efficiency, necessitating additional research for broad use and clinical integration.

Abstract 4123370: Distance to a Cardiac Imaging Center and Likelihood of Imaging Receipt: Defining Imaging Deserts

Background: Cardiovascular imaging is critical for the diagnosis and management of cardiovascular disease. Whether geographic distance to a cardiovascular imaging center (CVIC) impacts access to care is unknown. Methods: We evaluated all Medicare beneficiaries (Fee-for-service and Medicare Advantage) from 2018-2022, excluding those < 65, without continuous Medicare enrollment in the previous year, individuals missing zip code of residence, or CVICs missing zip codes. We estimated distance from the centroid of an individual’s zip code of residence to the centroid of the zip code with the nearest CVIC (defined as > 10 imaging procedures/year). Multivariable regression models were used to estimate likelihood of imaging receipt by distance. Results/Data: A total of 64,260,530 individuals (age 73.0 ± 8 years, 54.6% female, 80.1% White) received care at 3,886 CVICS. The vast majority (95%) lived within 16 miles of a CVIC, but varied considerably by modality with substantially greater distances for cardiac CT, cardiac MRI, and PET (Median [IQR] distance in miles to CVIC, Echo: 3.4 [0.4-7.0]; SPECT: 3.8 [1.3-7.9]; cardiac CT: 8.1 [3.7-21.3]; cardiac MRI: 17.4 [7.3-43.3]; PET: 88.9 [26.2-194.6]). CVICs performing cardiac CT, cardiac MRI, or PET were nearly all in metropolitan locations. Likelihood of imaging receipt was triphasic: lowest within 0-10 miles of a CVIC (mainly metropolitan locations), greater within 10-15 miles, and then increasingly lower beyond 15 miles ( Figure 1 ). Sites beyond the 16-mile threshold were predominantly in the Midwest and West ( Figure 2 ). Conclusions: In this study of 64 million Medicare beneficiaries, 2018-2022, 95% of the US population was found to live within 16 miles of a CVIC, though varied by modality. While those living > 16 miles from a CVIC received less imaging, the lowest use was identified among individuals living in the same zip code as a CVIC, suggesting a possible disconnect between access to imaging care and proximity.

Clinical application and challenges of thermal vapor lung volume reduction

There are major clinical challenges in the management of chronic obstructive pulmonary disease (COPD). Recent studies suggest that thermal vapor lung volume reduction may be an important interventional method in the treatment of emphysema phenotype of COPD. In this article, we reviewed and summarized the research and development, the current situation of clinical application, and the clinical challenges of thermal vapor lung volume reduction, to provide further clinical evidence for the standardized application of thermal vapor lung volume reduction.

Allergy Modulation: Exploring the Role of Prebiotics, Probiotics, and Synbiotics in Enhancing Health Outcomes - A Literature Review

This literature review explores the role of prebiotics, probiotics, and synbiotics in the prevention and management of allergic diseases, including eczema, asthma, allergic rhinitis, and food allergies. The review delves into the mechanisms by which these dietary interventions modulate the gut microbiome, influence immune system responses, and enhance the epithelial barrier. While prebiotics promote the growth of beneficial gut bacteria and the production of short-chain fatty acids, probiotics introduce live microorganisms that restore balance in the gut ecosystem. Synbiotics combine both approaches to synergistically improve gut health. Despite the promising potential of these interventions, the evidence remains mixed, with their efficacy varying across different allergic conditions. This review underscores the need for further research to clarify the effectiveness of prebiotics, probiotics, and synbiotics in allergy prevention and management, highlighting the complexities involved in translating these findings into clinical practice.

Abstract 4137479: Integrating Ambulatory Care Pharmacists into Value-Based Primary Care: A Scalable Model for Addressing Cardiometabolic Disease

Background: Chronic disease is common, costly, and complicated. In the shift to value-based payment models, interventions to engage patients and improve disease control are necessary to reduce morbidity, mortality, and cost. The use of ambulatory pharmacists has demonstrated improved management of chronic diseases. Traditionally, ambulatory pharmacists are employed by healthcare systems. In this study, we test if integrating ambulatory pharmacists hired, trained, and managed by a retail pharmacy into value-based primary care (VBPC) clinics improves care. Hypothesis: Integrating a Walgreens pharmacist empowered by collaborative drug therapy management agreements (CDTM) into Village Medical (VMD) clinics will improve indicators of chronic disease control. Aims: Improve hemoglobin A1c (HbA1c) in patients with type 2 diabetes (T2D) and systolic blood pressure (SBP) and diastolic blood pressure (DBP) measurements in patients with hypertension (HTN). Methods: An ambulatory pharmacist was embedded into VMD clinics in Phoenix, Arizona under the supervision of VMD primary care providers via a CDTM. The pharmacist provided education, coaching, and medication management by prescribing and titrating therapies for treating T2D and HTN - enabled by access to pharmacy dispensing data. β was generated from difference-in-differences (DID) analyses with propensity score matched controls. Results: 125 patients had T2D, and 43 patients had HTN in the intervention group with 250 and 86 in the matched control group, respectively. The mean age was 65 years, 54% were female, 2% non-English speaking, and 29% racial/ethnic minorities. The average baseline HbA1c was 9% in the intervention group and 10% in the matched cohort. The average baseline SBP was 146 mmHg in the intervention group and 142 mmHg in the matched cohort. The β in the T2D group was -1.61% (p<0.001) while the β in the HTN group was -10.2 mmHg (p<0.01) for SBP and -2.0 mmHg (p=0.42) for DBP. Conclusion: We saw significant reductions in SBP and HbA1c in the pharmacist-managed group compared with matched controls. These results demonstrate that pharmacist integration into VBPC clinics may improve measures of chronic disease known to be associated with morbidity and mortality.

Abstract 4136403: Impact of Coronary Artery Calcium Scores on Cardiovascular Risk and Preventive Therapies: A Systematic Review and Meta-Analysis

Introduction: Coronary artery calcium (CAC) serves as a key marker of atherosclerosis and is widely utilized in the noninvasive evaluation of coronary artery disease. We aim to compare cardiovascular risk outcomes and the likelihood of initiating or continuing pharmacological and lifestyle preventive therapies in asymptomatic and symptomatic patients with a CAC score greater than zero and those with a CAC score of zero with no established diagnosis of coronary artery disease. Methods: We performed systematic searches of PubMed, Scopus, Google Scholar, Cochrane Central, and ClinicalTrials.gov from inception to May 2024. Our search focused on randomized controlled trials and observational studies comparing outcomes between patients with a CAC score greater than zero and those with a CAC score of zero. Results: We included 53 observational studies, incorporating data from 210,672 asymptomatic and 32,477 symptomatic patients. Over a mean follow-up duration of 8.6 years, we observed that a CAC score greater than zero significantly correlated with an elevated risk of major adverse cardiovascular events (MACE) (OR: 5.58; 95% CI: 4.05–7.69; P < 0.00001). This association extended to all-cause mortality (OR: 3.90; 95% CI: 2.78–5.48; P < 0.00001), myocardial infarction (OR: 4.01; 95% CI: 3.45–4.65; P < 0.00001), and the need for revascularization (OR: 11.90; 95% CI: 6.82–20.78; P < 0.00001). Patients with a CAC score greater than zero were more likely to commence and continue aspirin therapy (OR: 2.45; 95% CI: 1.56–3.83; P < 0.0001 for initiation and OR: 1.71; 95% CI: 1.31–2.23; P < 0.0001 for continuation). Similar trends were noted for lipid-lowering medications (OR: 2.44; 95% CI: 1.57–3.79; P < 0.0001 for initiation and OR: 2.48; 95% CI: 1.53–4.01; P = 0.0002 for continuation), as well as the initiation of blood pressure medications (OR: 1.94; 95% CI: 1.61–2.33; P < 0.00001). Furthermore, a CAC score greater than zero was linked to increased adoption of lifestyle modifications, including enhanced physical activity (OR: 1.84; 95% CI: 1.41–2.41; P < 0.00001) and dietary changes (OR: 1.94; 95% CI: 1.52–2.49; P < 0.00001). Conclusion: Patients with elevated CAC scores are more likely to initiate and continue preventive pharmacological therapies and adopt beneficial lifestyle modifications. These findings underscore the importance of CAC scoring in guiding the management and prevention of cardiovascular disease in both asymptomatic and symptomatic populations.

The effect of comorbidity on 28-day perioperative mortality rate among non-cardiac surgical patients in Northwest Ethiopia: a prospective cohort study using propensity score matching.

Non-communicable diseases account for nearly three-fourths of global deaths impacting public health and development. Coexisting diseases can complicate the management of surgical diseases, increasing the risk of perioperative mortality. Despite this, few studies have examined the burden of comorbidities among surgical patients and their effect on perioperative outcomes in low-income countries. In this study, we assessed the impact of comorbidity burden on 28-day perioperative mortality using a prospective data set. This was a facility-based prospective cohort study. Adult patients aged ≥ 18 who underwent non-cardiac surgery were included. Patients were followed for 28 days following surgery. Perioperative data were collected using an electronic data collection system from June 01, 2019, to June 30, 2021, at Tibebe Ghion Specialized Hospital, Northwest, Ethiopia. A propensity score-matched analysis was employed to assess the effect of comorbidity on the 28-day perioperative mortality rate. Of the 3030 patients included in this study, 715 (23.59%) had at least one comorbidity. Based on the prevalence rate, the top four comorbid conditions observed were hypertension (0.050), cancer (0.036), diabetes mellitus (0.021), and human immunodeficiency virus (0.021). The 28-day perioperative mortality rate was shown to be significantly higher among patients with comorbidity, where 45 (6.29%) of the 715 patients with comorbidity died compared to 49 (2.12%) of the 2315 patients with no comorbidity (p-value < 0.0001). After propensity score matching potential confounders, patients who have comorbidity had a 2.52% (average treatment effect on treated (ATT) = 0.0252) higher risk of perioperative death at 28 days after surgery compared with patients who did not have comorbidity. This study found a moderate prevalence of comorbid illnesses among non-cardiac surgical patients, with comorbidity increasing the risk of 28-day perioperative mortality. Preoperative screening and optimization are highly recommended for patients with comorbid illness to decrease perioperative mortality rate.

The Present Difficulties and Potential Benefits of Dopaminergic Agents in Parkinson's Disease Treatment

Parkinson's disease (PD) is a progressive neurological condition characterized by bradykinesia, rigidity, tremors, and impaired balance, among other motor impairments. The issue arises from dopaminergic neurons located in the spinal column of the brain. This research report examines the therapeutic potential of dopaminergic medications in the management of Parkinson's disease. The central concept of Parkinson's disease (PD) revolves around the notion that dopaminergic pathways exert significant influence over the regulation of movement. The book examines various dopaminergic medications, elucidating their mechanisms of action and the impact they exert on dopamine signaling. Examples of these medications include levodopa, dopamine agonists, and monoamine oxidase-B (MAO-B) inhibitors. Although dopaminergic medicines initially aid in the treatment of Parkinson's disease (PD), prolonged usage of these medications gives rise to several complications. Experiencing dyskinesias and motor fluctuations, characterized by episodes of involuntary movements and behaviors that are undesired, is a significant challenge. This study investigates the underlying causes of these difficulties and explores potential treatment options, including the use of controlled-release formulations and further therapy. The book discusses the non-motor symptoms of Parkinson's disease (PD), as well as the use of dopaminergic medications to treat mood disorders, autonomic dysfunction, and cognitive loss. Dopaminergic medications remain crucial in reducing motor symptoms and enhancing the quality of life for those with Parkinson's disease. Parkinson's disease (PD) is a complex condition with multiple distinct variations. In order to address its existing challenges and explore its potential implications for future Parkinson's disease medications, a comprehensive and effectively coordinated strategy is required.

Abstract 4138220: Traditional and HIV-specific Risk Factors Are Associated with Incident Non-valvular Atrial Fibrillation and Atrial Flutter among Underrepresented Racial and Ethnic Minority Groups Living with HIV

Introduction: With effective antiretroviral therapy (ART), HIV can now be managed as a chronic disease. Chronic disease and cardiovascular risk factor management is especially important for underrepresented racial and ethnic minority groups (UREG). Non-valvular atrial fibrillation and atrial flutter (NVAF) have not been adequately studied in UREG with HIV. Research Questions: Among UREG with HIV, what is the incidence of NVAF? What factors are associated with incident NVAF? Aims: To narrow an evidence gap among UREG with HIV by 1) describing the incidence of NVAF and 2) identifying factors associated with incident NVAF. Methods: This is an ancillary study of the Pathways to Cardiovascular Disease Prevention and Impact of Specialty Referral in Underrepresented Racial and Ethnic Minorities with HIV (PATHWAYS) study, a retrospective population-based study of HIV care patterns among UREG with HIV. Patients without a known history of NVAF entered our study cohort at the date of their first documented HIV diagnosis. We computed the cumulative incidence of NVAF over five years of follow-up (mean 3.4, SD 1.6), handling death as a competing risk. Cox regression analysis was used to examine the univariate associations between characteristics at HIV diagnosis and incident NVAF, adjusting for site and date of HIV diagnosis. Results: From 2015-2019, 10,945 UREG meeting entry criteria were identified. On average, patients were 67.1% male, 94.4% Black, and 8.5% Hispanic. Average CHA2DS2VASc score was 0.92 (SD 1.1) and 63.4% were on ART. Cumulative incidence of NVAF at one and five years after HIV diagnosis were 0.48% (95% CI 0.36-0.63) and 2.16% (95% CI 1.85-2.51), respectively. HIV-related factors associated with incident NVAF included baseline CD4 count &lt;200 (HR 1.84, 95% CI 1.20-2.80) and initial ART including protease inhibitors (HR 1.56, 95% CI 1.14-2.13) and/or integrase strand transfer inhibitors (HR 1.47, 95% CI 1.08-1.99). Additional associated factors included older age, Medicare, cardiology visit(s) in prior year, and co-morbid diseases including hypertension, hyperlipidemia, coronary and peripheral artery disease, prior stroke/transient ischemic attack, heart failure, and chronic kidney disease. Conclusions: In a large cohort of UREG living with HIV, both traditional and HIV-specific risk factors are associated with increased risk of incident NVAF. Interventions to mitigate NVAF risk in this population will require interdisciplinary, team-based approaches.

The Role Of Machine Learning In Transforming Healthcare: A Systematic Review

This systematic review explores the transformative role of machine learning (ML) in healthcare, focusing on its applications in disease diagnosis, personalized medicine, healthcare operations, and patient monitoring. By analyzing 167 peer-reviewed studies published between 2015 and 2024, the review highlights how ML algorithms have significantly improved early disease detection, treatment personalization, and operational efficiencies in healthcare settings. Findings reveal that ML-powered diagnostic tools, especially deep learning models, demonstrate accuracy levels comparable to human experts in areas like cancer detection. Additionally, ML models tailored for personalized medicine have shown promise in optimizing treatment protocols based on genetic profiles, reducing adverse reactions and improving patient outcomes. In healthcare operations, ML applications have streamlined hospital resource management, enhanced workflow efficiency, and reduced administrative burdens through predictive analytics and natural language processing (NLP). Moreover, ML-driven remote patient monitoring systems have enabled proactive interventions for chronic disease management. Despite these advancements, challenges related to data privacy, algorithmic transparency, and regulatory compliance persist. Addressing these barriers is critical for realizing the full potential of ML in healthcare, ensuring ethical deployment and equitable access. The review concludes by emphasizing the need for robust regulatory frameworks and further research to enhance the integration of ML technologies into clinical practice.

Abstract 4136758: Apabetalone: evaluating cardiovascular and safety outcomes in meta-analysis

Background: Epigenetic mechanisms play a pivotal role in the transcriptional programs associated with cardiovascular disease (CVD). Apabetalone, an orally available inhibitor of BET proteins that serve as key epigenetic readers, and modulating gene expression - holds promise as a therapeutic intervention in CVD management. Understanding its efficacy and tolerability is crucial for delineating its potential impact on disease progression and patient outcomes. Purpose: This systematic review and meta-analysis aimed to assess the impact of apabetalone in patients with cardiovascular disease. Methods: The meta-analysis was registered with PROSPERO (CRD42023423298). Databases searched included Cochrane CENTRAL, PubMed, Ovid Medline, and Web of Science. Three unique RCTs with total of 2897 patients were included, with trial durations ranging from 12 to 124 weeks. Primary outcomes assessed were all-cause mortality and non-fatal myocardial infarction (MI). Data analysis was performed using the inverse variance common effect model. Subgroup analyses were conducted based on the presence of atherosclerotic cardiovascular disease (ASCVD) or its increased risk. Results: Among the primary outcomes, no significant effects of apabetalone were observed on all-cause mortality (RR 0.88, 95% CI 0.63 to 1.23) or non-fatal MI (RR 0.83, 95% CI 0.62 to 1.11). Apabetalone demonstrated favorable effects on increasing Apo A1 (SMD 0.20, 95% CI 0.04 to 0.35) and HDL (SMD 0.29, 95% CI 0.09 to 0.49). However, no significant effects were observed for changes in Apo B, LDL, non-HDL, total cholesterol. Subgroup analysis did not reveal any significant differences in outcomes. Significant effects were noted in secondary outcomes. Apabetalone showed a significant increase in adverse events (AEs) leading to withdrawal (RR 1.61, 95% CI 1.21 to 2.15) and ALT and AST increases greater than three times the normal value (RR 4.50, 95% CI 2.73 to 7.41). Conclusion: Our meta-analysis highlights the significant impact of apabetalone on certain lipid parameters and adverse events. However, it did not demonstrate significant effects on all-cause mortality or non-fatal MI. Further well-designed and reported RCTs were warranted to elucidate the clinical implications of apabetalone in selected group of patients that might benefit the most from apabetalone that may also improve cardiovascular disease management.

Analysis of the Prevalence of Bacterial Pathogens and Antimicrobial Resistance Patterns of Edwardsiella piscicida in Largemouth Bass (Micropterus salmoides) from Guangdong, China

To gain insights into the prevalence and antimicrobial resistance patterns of major bacterial pathogens affecting largemouth bass (Micropterus salmoides) in the Pearl River Delta (PRD) region, Guangdong, China, a study was conducted from August 2021 to July 2022. During this period, bacteria were isolated and identified from the internal organs of diseased largemouth bass within the PRD region. The antimicrobial resistance patterns of 11 antibiotics approved for use in aquaculture in China were analyzed in 80 strains of Edwardsiella piscicida using the microbroth dilution method. The results showed that 151 bacterial isolates were obtained from 532 samples, with E. piscicida (17.29%, 92/532), Aeromonas veronii (4.70%, 25/532), and Nocardia seriolae (2.26%, 12/532) being the main pathogens. Notably, E. piscicida accounted for the highest proportion of all isolated bacteria, reaching 60.92% (92/151), and mainly occurred from November to April, accounting for 68.48% (63/92) of the cases. The symptoms in largemouth bass infected with E. piscicida included ascites, enteritis, and hemorrhaging of tissues and organs. The drug sensitivity results showed that the resistance rates of all E. piscicida strains to ciprofloxacin, all sulfonamides, thiamphenicol, florfenicol, enrofloxacin, doxycycline, flumequine, and neomycin were 96.25%, 60–63%, 56.25%, 43.75%, 40%, 32.5%, 16.25%, and 1.25%, respectively. In addition, 76.25% (61/80) of these strains demonstrated resistance to more than two types of antibiotics. Cluster analysis revealed 23 antibiotic types (A–W) among the 80 isolates, which were clustered into two groups. Therefore, tailored antibiotic treatment based on regional antimicrobial resistance patterns is essential for effective disease management. The findings indicate that in the event of an Edwardsiella infection in largemouth bass, neomycin, doxycycline, and flumequine are viable treatment options. Alternatively, one may choose drugs that are effective as determined by clinical drug sensitivity testing.

Koala ocular disease grades are defined by chlamydial load changes and increases in Th2 immune responses

IntroductionThis study employs bulk RNA sequencing, PCR, and ELISA assays to analyze the pathological factors affecting the outcomes of C. pecorum ocular infections in koalas. It investigates the immune responses and gene expression profiles associated with various stages of koala ocular chlamydiosis.MethodsA cohort of 114 koalas from Queensland, Australia were assessed, with 47% displaying clinical signs of ocular disease. Animals were classified into three cohorts: acute active disease (G1), chronic active disease (G2), and chronic inactive disease (G3), along with subclinical Chlamydia pecorum positive (H2) and healthy (H1) cohorts.ResultsAnalysis of clinical, microbiological, humoral immune and cellular immune biomarkers revealed varying chlamydial loads and anti-chlamydial IgG levels across disease grades, with a negative correlation observed between ocular chlamydial load and anti-chlamydial IgG. Koala ocular mucosa gene expression analysis from 27 koalas identified shared expression pathways across disease cohorts, with a significant upregulation of IFNγ expression and tryptophan metabolism in all disease stages.DiscussionThese findings help elucidate immune response dynamics and molecular pathways underlying koala ocular chlamydiosis, providing insights crucial for disease management strategies.

Abstract 4126893: Feasibility and Acceptability of a Nurse-Pharmacist Post-Discharge Telehealth Model of Care for Heart Failure Patients

Background: Suboptimal medication management is common in patients with heart failure (HF), particularly during transitions-of-care. To date, there are few studies assessing the feasibility of a nurse-pharmacist post-discharge telehealth service for medication optimisation in patients with HF. We performed a feasibility study to determine service uptake and acceptability, and ability to identify medication-related issues for HF patients as they transition from hospital to home. Methods: HF patients were referred to an existing post-discharge telehealth service and offered medication reconciliation and education in addition to their usual care; a service we termed ‘MedRec’ (MR). Primary outcomes were feasibility, measured through recruitment and successful MR completion, and acceptability, measured by an investigator-developed survey. Secondary outcomes were medication-related issues detected during MR. Results: A total of 100 HF patients were offered a post-discharge MR. Mean age of patients was 68.5 ±14.2 years, and mostly male sex (62%). Pharmacist MRs were requested by 80% of patients. In total 62 MRs (77.5%) were performed; 9 patients declined MR during follow-up and an additional 9 patients were uncontactable. Mean time to MR following nurse referral was 10.98 ±9.74 days. Drug-related toxicity or adverse effect presentation was identified in 25 (40.3%) MR recipients at the time of consultation and subsequently required general practitioner follow-up. Medication compliance issues were detected by the pharmacist in 13 (20.9%) patients; forgotten doses being the most common concern. Undertreated medical conditions, such as symptomatic HF and chronic pain, were identified in 12 (19.3%) MR recipients. Medications prescribed without any apparent indication were found in 8 (12.9%) patients. Drug or disease management information was requested by 35 (56.4%) MR recipients. A total of 35 (56.5%) post-MR surveys were successfully completed. All participants who completed a post-MR survey agreed that a post-discharge telehealth MR was an acceptable form of education provision. Engagement with a pharmacist MR was perceived to ease anxiety associated with understanding medication-related changes and empowered greater medication self-management. Conclusions: A post-discharge nurse-pharmacist telehealth service is a feasible and acceptable model of care. Inclusion of a routine MR post-discharge may be an effective means of maintaining continuity of care for HF patients.

Exploring participants’ characteristics and self-assessed readiness to conduct clinical trials in general practice – baseline analysis of the RaPHaeL practice-based research network

Background Primary care is integral to healthcare systems extending beyond traditional illness management to include preventive care, chronic disease management, and health promotion. Practice-based research networks (PBRNs) have emerged as essential infrastructures for conducting clinical research in primary care. This study explores the establishment of the ‘Research-Practices Halle-Leipzig’ (RaPHaeL) PBRN in Germany, evaluating the characteristics and research readiness of participating practices. Methods A cross-sectional survey (MORNING II) was conducted among all general practitioners (GPs) joining the RaPHaeL PBRN, assessing socio-demographic characteristics, practice infrastructure, and research readiness. After a descriptive analysis, we compared data with a previous study (MORNING) to examine potential differences between PBRN participants and non-participants. We developed a research readiness score (RRS) to quantify practices’ ability to perform clinical research subtasks. Results The response rate was 97.1% and our participants were often male, involved in undergraduate education, generally interested in research or had previous research experiences. However, they differed widely in age and size, staff structure, and patient demographics of their practices. Initially, around two-thirds of the practices were not sufficiently prepared to conduct clinical trials (self-assessed feasibility of relevant subtasks). If further research and documentation tasks are required, patient recruitment estimations are lower than for patient identification and information. Conclusion This study highlights the variability in research readiness among GP practices and shows the need for targeted training. By systematically assessing and enhancing research capabilities of participating GPs, PBRNs can facilitate high-quality clinical research in primary care to improve patient outcomes and healthcare delivery.

Characterization of Disease Patterns in Children with Intracranial Abscesses for Enhanced Clinical Decision-Making

Background: Intracranial suppurative infections in pediatric patients, while rare, pose a significant risk to patient mortality. Early recognition and fast initiation of diagnosis and treatment are crucial to prevent fatal outcomes. Between December 2022 and May 2023, a significant cluster of nine cases emerged, each necessitating neurosurgical intervention. This series highlights an important trend in clinical outcomes and raises questions about underlying factors contributing to this pattern. The need for surgical procedures in all instances suggests a commonality in severity, warranting further investigation into potential causes and preventative measures. This retrospective monocentric study aims to explore the clinical features associated with these cases to identify specific disease patterns that can expedite management in clinical practice. Methods: Cramer’s V effect size was employed to evaluate combinations of clinical features, followed by Fisher’s exact test applied to a constructed contingency table. A p-value was assessed for significance analysis, with combinations achieving a Cramer’s V value of 0.7 or higher being classified as exhibiting very strong correlations. Results: The analysis revealed distinct patterns of clinical features among children diagnosed with intracranial abscesses. Significant associations were identified, including correlations between sinusitis and Streptococcus pyogenes, and fever accompanied by affected temporal, frontal, and frontobasal lobe regions. Conclusions: Despite the generally limited statistical analysis of pediatric intracranial abscesses in the existing literature, this study provides meaningful significant associations between clinical features, delineating specific disease patterns for children with intracranial abscesses. By addressing this gap, the findings contribute valuable insights and offer a framework that could enhance clinical decision-making and support timely disease management in pediatric cases.

Novel Method for Detecting Coughing Pigs with Audio-Visual Multimodality for Smart Agriculture Monitoring

While the pig industry is crucial in global meat consumption, accounting for 34% of total consumption, respiratory diseases in pigs can cause substantial economic losses to pig farms. To alleviate this issue, we propose an advanced audio-visual monitoring system for the early detection of coughing, a key symptom of respiratory diseases in pigs, that will enhance disease management and animal welfare. The proposed system is structured into three key modules: the cough sound detection (CSD) module, which detects coughing sounds using audio data; the pig object detection (POD) module, which identifies individual pigs in video footage; and the coughing pig detection (CPD) module, which pinpoints which pigs are coughing among the detected pigs. These modules, using a multimodal approach, detect coughs from continuous audio streams amidst background noise and accurately pinpoint specific pens or individual pigs as the source. This method enables continuous 24/7 monitoring, leading to efficient action and reduced human labor stress. It achieved a substantial detection accuracy of 0.95 on practical data, validating its feasibility and applicability. The potential to enhance farm management and animal welfare is shown through proposed early disease detection.

An Algerian Soil-Living Streptomyces alboflavus Strain as Source of Antifungal Compounds for the Management of the Pea Pathogen Fusarium oxysporum f. sp. pisi

Fusarium wilt caused by Fusarium oxysporum f. sp. pisi (Fop) poses significant threats to pea cultivation worldwide. Controlling this disease is mainly achieved through the integration of various disease management procedures, among which biological control has proven to be a safe and effective approach. This study aims to extract and identify antifungal secondary metabolites from Streptomyces alboflavus KRO3 strain and assess their effectiveness in inhibiting the in vitro growth of Fop. This bacterial strain exerts in vitro antagonistic activity against Fop, achieving highly significant inhibition over one week. The ethyl acetate extract, obtained from its ISP2 agar medium culture, also exhibited strong antifungal activity, maintaining an inhibition rate of approximately 90% at concentrations up to 250 µg/plug compared to the control. Thus, the organic extract has been fractionated using chromatographic techniques and its bioguided purification allowed us to isolate the main bioactive compound. This latter was identified as metacycloprodigiosin using nuclear magnetic resonance (NMR) spectroscopy, electrospray ionization mass spectrometry (ESI-MS), and specific optical rotation data. Metacycloprodigiosin demonstrates dose-dependent inhibitory activity against the phytopathogen with an effective concentration of 125 µg/plug. The other secondary metabolites present in the ethyl acetate extract were also identified by gas chromatography–mass spectrometry (GC-MS) and nuclear magnetic resonance (NMR). This study highlighted the potential of S. alboflavus KRO3 strain and its antimicrobial compounds for the management of the pea pathogen Fusarium oxysporum f. sp. pisi.