Individual Variation In Response Research Articles

A Pharmacogenomics-Based In Silico Investigation of Opioid Prescribing in Post-operative Spine Pain Management and Personalized Therapy.

Considering the variability in individual responses to opioids and the growing concerns about opioid addiction, prescribing opioids for postoperative pain management after spine surgery presents significant challenges. Therefore, this study undertook a novel pharmacogenomics-based in silico investigation of FDA-approved opioid medications. The DrugBank database was employed to identify all FDA-approved opioids. Subsequently, the PharmGKB database was utilized to filter through all variant annotations associated with the relevant genes. In addition, the dpSNP ( https://www.ncbi.nlm.nih.gov/snp/ ), a publicly accessible repository, was used. Additional analyses were conducted using STRING-MODEL (version 12), Cytoscape (version 3.10.1), miRTargetLink.2, and NetworkAnalyst (version 3). The study identified 125 target genes of FDA-approved opioids, encompassing 7019 variant annotations. Of these, 3088 annotations were significant and pertained to 78 genes. During variant annotation assessments (VAA), 672 variants remained after filtration. Further in-depth filtration based on variant functions yielded 302 final filtered variants across 56 genes. The Monoamine GPCRs pathway emerged as the most significant signaling pathway. Protein-protein interaction (PPI) analysis revealed a fully connected network comprising 55 genes. Gene-miRNA Interaction (GMI) analysis of these 55 candidate genes identified miR-16-5p as a pivotal miRNA in this network. Protein-Drug Interaction (PDI) assessment showed that multiple drugs, including Ibuprofen, Nicotine, Tramadol, Haloperidol, Ketamine, L-Glutamic Acid, Caffeine, Citalopram, and Naloxone, had more than one interaction. Furthermore, Protein-Chemical Interaction (PCI) analysis highlighted that ABCB1, BCL2, CYP1A2, KCNH2, PTGS2, and DRD2 were key targets of the proposed chemicals. Notably, 10 chemicals, including carbamylhydrazine, tetrahydropalmatine, Terazosin, beta-methylcholine, rubimaillin, and quinelorane, demonstrated dual interactions with the aforementioned target genes. This comprehensive review offers multiple strong, evidence-based in silico findings regarding opioid prescribing in spine pain management, introducing 55 potential genes. The insights from this report can be applied in exome analysis as a pharmacogenomics (PGx) panel for pain susceptibility, facilitating individualized opioid prescribing through genotyping of related variants. The article also points out that African Americans represent an important group that displays a high catabolism of opioids and suggest the need for a personalized therapeutic approach based on genetic information.

Exploring individual responses to welfare issues in growing-finishing pig feeding behaviour

The feeding behaviour of individual growing-finishing pigs can be continuously monitored using sensors such as electronic feeding stations (EFSs), and this could be further used to monitor pig welfare. To make accurate conclusions about individual pig welfare, however, it is important to know whether deviations in feeding behaviour in response to welfare issues are shown only on average or by each individual pig. Therefore, this study aimed (1) to quantify the individual variation in feeding behaviour changes in response to a range of welfare issues, and (2) to explain this individual variation by quantifying the responses to welfare issues for specific subgroups of pigs. We monitored four rounds of 110 growing-finishing pigs each (3–4 months per round). We collected feeding behaviour data using IVOG® EFSs and identified health issues and heat stress using climate sensors and twice-weekly health observations. For each pig, a generalised additive model was fitted, which modelled feeding behaviour through time and estimated the effect of each welfare issue that the pig had suffered from. The range of these effect estimates was compared between pigs to study the individual variation in responses. Subsequently, pigs were repeatedly grouped using physical and feeding characteristics, and, with meta–subset analysis, it was determined for each group whether a deviation in response to the welfare issue (i.e. their combined effect estimates) was present. We found that the range in effect estimates was very large, approaching normal distributions for most combinations of welfare issues and feeding variables. This indicates that most pigs did not show feeding behaviour deviations during the welfare issue, while those that did could show both increases and reductions. One exception was heat stress, for which almost all pigs showed reductions in their feed intake, feeding duration and feeding frequency. When looking at subgroups of pigs, it was seen that especially for lameness and tail damage pigs with certain physical characteristics or feeding strategies did consistently deviate on some feeding components during welfare issues (e.g. only relatively heavier pigs reduced their feeding frequency during lameness). In conclusion, while detection of individual pigs suffering from heat stress using feeding variables should be feasible, detection of (mild) health issues would be difficult due to pigs responding differently, if at all, to a given health issue. For some pigs with specific physical or behavioural characteristics, nevertheless, detection of some health issues, such as lameness or tail damage, may be possible.

The patterns in urine excretion and transvascular fluid exchange in human subjects during intravenous fluid infusion: A quantitative analysis.

Investigations of responses of animals and humans to changes of plasma volume are usually reported as average responses of groups of individuals. This ignores considerable quantitative variation between individuals. We examined the hypothesis that individual responses follow a common temporal pattern with variations reflecting different parameters describing that pattern. We illustrate this approach using data of Hahn, Lindahl and Drobin (Acta Anaesthesiol Scand.2011, 55:987-94) who measured urine volume and haemoglobin dilution of 10 female subjects during intravenous Ringer infusions for 30 min and subsequent 3.5 h. The published time courses were digitised and analysed to determine if a family of mathematical functions accounted for the variation in individual responses. Urine excretion was characterised by a time delay (Td) before urine flow increased and a time course of cumulative urine excretion described by a logarithmic function. This logarithmic relation forms the theoretical basis of a family of linear relations describing urine excretion as a function of Td. Measurement of Td enables estimation of subsequent values of urine excretion and thereby the fraction of infused fluid retained in the body. The approach might be useful for physiologists and clinical investigators to compare the response to infusion protocols when both test and control responses can be described by linear relations between cumulative urine volume at specific times and Td. The approach may also be useful for clinicians by complementing strategies to guide fluid therapy by enabling the later responses of an individual to be predicted from their earlier response.

Pharmacokinetic/Pharmacodynamic Assessment of the Structural Refinement of Clopidogrel Focusing on the Balance between Bioactivation and Deactivation.

The delicate balance between ischemic and bleeding risks is a critical factor in antiplatelet therapy administration. Clopidogrel and prasugrel, belonging to the thienopyridine class of antiplatelet drugs, are known for their variability in individual responsiveness and high incidence of bleeding events, respectively. The present study is centered on the development and assessment of a range of deuterated thienopyridine derivatives, leveraging insights from structure-pharmacokinetic relationships of clopidogrel and prasugrel. Our approaches were grounded in the molecular framework of clopidogrel and incorporated the C2-pharmacophore design from prasugrel. The selection of ester or carbamate substituents at the C2-position facilitated the generation of the 2-oxointermediate through hydrolysis, akin to prasugrel, thereby bypassing the issue of CYP2C19 dependency. The bulky C2-pharmacophore in our approach distinguishes itself from prasugrel's acetyloxy substituent by exhibiting a moderated hydrolysis rate, resulting in a more gradual formation of the active metabolite. Excessive and rapid release of the active metabolite, believed to be linked with an elevated risk of bleeding, is thus mitigated. Our proposed structural modification retains the hydrolysis-sensitive methyl ester of clopidogrel but substitutes it with a deuterated methyl group, shown to effectively reduce metabolic deactivation. Three promising compounds demonstrated a pharmacokinetic profile similar to that of clopidogrel at four times the dose, while also augmenting its antiplatelet activity. SIGNIFICANCE STATEMENT: Inspired by the structure-pharmacokinetic relationship of clopidogrel and prasugrel, a range of clopidogrel derivatives were designed, synthesized, and assessed. Among them, three promising compounds have been identified, striking a delicate balance between efficacy and safety for antiplatelet therapy. Additionally, the ozagrel prodrug conjugate was discovered to exert a synergistic therapeutic effect alongside clopidogrel.

Probabilistic neural network based visual data mining for the healthcare sector.

The need for personalised care in the long-term management of patient health is paramount due to the variability in individual features and responses to specific medication. With the availability of large quantities of electronic patient records, big data analysis presents a valuable opportunity to gain insights into disease presentation and patient impact. This study aims to utilise data science in the medical field to extract unknown information from databases, validate previously obtained data, and enhance personalised patient care. An analytics suite is developed for monitoring patient health and treating cholesterol, thyroid, and diabetes disorders. This suite employs exploratory, predictive, and visual analytics to categorise patient data into multiple tiers and forecast related complication risk and treatment response. The study found that the analytics suite could successfully identify correlations between various biological indicators of patients and disorders. The suite also showcased potential in predicting health risks and responses to treatments. The analytics employed in this study suggest advanced methods of data analysis, which could serve as potential decision-making tools for healthcare providers. These methods might lead to improved treatment outcomes, contributing significantly to personalised patient care.

A new evaluation system for drug-microbiota interactions.

The drug response phenotype is determined by a combination of genetic and environmental factors. The high clinical conversion failure rate of gene-targeted drugs might be attributed to the lack of emphasis on environmental factors and the inherent individual variability in drug response (IVDR). Current evidence suggests that environmental variables, rather than the disease itself, are the primary determinants of both gut microbiota composition and drug metabolism. Additionally, individual differences in gut microbiota create a unique metabolic environment that influences the in vivo processes underlying drug absorption, distribution, metabolism, and excretion (ADME). Here, we discuss how gut microbiota, shaped by both genetic and environmental factors, affects the host's ADME microenvironment within a new evaluation system for drug-microbiota interactions. Furthermore, we propose a new top-down research approach to investigate the intricate nature of drug-microbiota interactions in vivo. This approach utilizes germ-free animal models, providing foundation for the development of a new evaluation system for drug-microbiota interactions.

Perspectives from the Inaugural "Spinal CSF Leak: Bridging the Gap" Conference: A Convergence of Clinical and Patient Expertise.

The inaugural "Spinal CSF Leak: Bridging the Gap" Conference was organized to address the complexities of diagnosing and treating spinal CSF leaks. This event aimed to converge the perspectives of clinicians, researchers, and patients with a patient-centered focus to explore the intricacies of spinal CSF leaks across 3 main domains: diagnosis, treatment, and aftercare. Physician and patient speakers were invited to discuss the varied clinical presentations and diagnostic challenges of spinal CSF leaks, which often lead to misdiagnosis or delayed treatment. Patient narratives were interwoven with discussions on advanced radiologic techniques and clinical assessments. Treatment-focused sessions highlighted patient experiences with various therapeutic options, including epidural blood patches, surgical interventions, and percutaneous and endovascular therapies. The intricacies of immediate and long-term postprocedural management were explored. Key outcomes from the conference included the recognition of the need for increased access to specialized CSF leak care for patients and heightened awareness among health care providers, especially for atypical symptoms and presentations. Discussions underscored the variability in individual treatment responses and the necessity for personalized diagnostic and treatment algorithms. Postprocedural challenges such as managing incomplete symptom relief and rebound intracranial hypertension were also addressed, emphasizing the need for effective patient monitoring and follow-up care infrastructures. The conference highlighted the need for adaptable diagnostic protocols, collaborative multidisciplinary care, and enhanced patient support. These elements are vital for improving the recognition, diagnosis, and management of spinal CSF leaks, thereby optimizing patient outcomes and quality of life. The event established a foundation for future advancements in spinal CSF leak management, advocating for a patient-centered model that harmonizes procedural expertise with an in-depth understanding of patient experiences.

The impact of growth hormone (GH) therapy on glucose metabolism: A narrative review mainly focused on GH-deficient (GHD) children and adolescents

Introduction: Growth hormone (GH) deficiency (GHD) in children and adolescents is traditionally managed with GH therapy, which, while effective for promoting growth, poses potential metabolic repercussions, particularly concerning glucose metabolism. This review delineates the complex interplay between GH therapy, insulin sensitivity, and glucose homeostasis. Objective: To synthesize existing literature on the effects of GH therapy on glucose metabolism, insulin secretion, and insulin sensitivity in GH-deficient pediatric populations, aiming to illuminate the nuanced metabolic consequences and to optimize therapeutic outcomes. Results: The reviewed studies illuminate a complex influence of GH therapy on metabolic parameters. While GH promotes growth and improves body composition, it may concurrently impair insulin sensitivity, elevate fasting glucose levels, and, in some cases, induce glucose intolerance. However, the dysglycemic effect during GH therapy appears to be transient and reversible on discontinuation of therapy. The counterbalancing role of insulin-like growth factor 1 (IGF-1) and its contribution to maintaining glucose homeostasis is also highlighted, illustrating a complex metabolic interplay induced by GH therapy. Discussion: The findings underscore the variability in individual metabolic responses to GH therapy. The balance between GH-induced insulin resistance and IGF-1-mediated insulin sensitivity is crucial. Monitoring and adjusting GH therapy based on glycemic response is imperative to prevent adverse metabolic outcomes. Conclusion: GH therapy in GH-deficient children and adolescents requires careful consideration of its metabolic effects. Personalized treatment strategies and vigilant monitoring of glucose metabolism are essential to optimize therapeutic outcomes and minimize the risk of metabolic complications. Further research is warranted to establish comprehensive guidelines for managing the metabolic aspects of GH therapy in this vulnerable population.

In vivo assessment of human corneal epithelial cells in orthokeratology lens wearers: A pilot study.

Central corneal epithelial thinning associated with midperipheral epithelial thickening has been reported as the main factor contributing to the effectiveness of orthokeratology (ortho-k) in myopia control. Yet, the cellular mechanism governing the regional change in refractive power remains elusive. This study aimed to evaluate the correlation between the regional change in corneal epithelial thickness and cell density in ortho-k wearers. A new human prototype of a polarization-dependent optical coherence microscope was developed to enable noncontact and noninvasive in vivo imaging of corneal epithelial cells in ortho-k wearers with and without their ortho-k lens. The epithelial thickness and cell density were evaluated at the central and midperipheral corneal locations in four ortho-k wearers and four spectacle wearers serving as controls. Polarization-dependent optical coherence microscope achieved in vivo volumetric imaging of all epithelial cell types in ortho-k wearers with and without their lens over a field of view of 0.5 × 0.5 mm2 with an isotropic resolution of ~2.2 mm. The central epithelial thinning and midperipheral epithelial thickening were consistent across all ortho-k wearers. However, the inconsistency in their regional epithelial cell density highlighted a great variability in individual response to ortho-k treatment. There was no strong correlation between epithelial thickness and cell density, especially at the midperipheral cornea, in ortho-k participants. This study constitutes our first step toward uncovering the cellular mechanism underlying the effectiveness of ortho-k in myopia control. Future studies will focus on the longitudinal evaluation of epithelial cells before and during ortho-k treatment to identify factors governing individual response to ortho-k treatment and ultimately inform the dynamics of epithelial cells taking place during the ortho-k treatment.

Precision Medicine for COVID-19 Based on the Inflammatory Response

Background The threat due to the global pandemic of the coronavirus disease 2019 (COVID-19) demands a search for effective treatments to combat the severity of the infections and their associated morbidity and mortality in vulnerable populations. One of the medications with putative antiviral, anti-inflammatory, and immunomodulatory effects is fluvoxamine, a selective serotonin reuptake inhibitor and σ-1 receptor agonist. A few studies have reported doses of 100–300 mg/day to be effective. Aim This retrospective study evaluates the outcomes of an individually tailored dosing strategy for fluvoxamine, based on measurements of inflammatory status, in treating COVID-19-positive individuals in India. Methods This study included patients with severe acute respiratory syndrome coronavirus 2 infection visiting the outpatient department of a super speciality hospital in India from February to July 2021. Fluvoxamine was initiated at 50 mg or 100 mg twice daily based on their individual C-reactive protein (CRP) and D-dimer status. By day five, patients with rising or static levels of CRP and D-dimer were up-titrated. Results In a population of 104 individuals infected with COVID-19, 10 required up-titration of dose, and 94 patients did not need up-titration. Overall, there was very low mortality (N = 1) and hospitalization rate (8.7%). Those individuals who required an up-titration on day five had significantly elevated CRP and D-dimer levels compared to those who were maintained at the initial dose of 50 mg twice daily. In such patients, up-titration of the dose on day 5 appeared to offer better treatment benefits and outcomes. In our study population, there was only one mortality during the course of COVID-19. Conclusions Given the individual variability in the host immune response to severe acute respiratory syndrome coronavirus 2 infection, tailoring the dose of a drug such as fluvoxamine based on the inflammatory status of the individual may be beneficial. Individually tailored dosing could combat disease progression while reducing side effects.

The Importance of Recovery in Resistance Training Microcycle Construction.

Systemic resistance training aims to enhance performance by balancing stress, fatigue and recovery. While fatigue is expected, insufficient recovery may temporarily impair performance. The aim of this review was to examine evidence regarding manipulation of resistance training variables on subsequent effects on recovery and performance. PubMed, Medline, SPORTDiscus, Scopus and CINAHL were searched. Only studies that investigated recovery between resistance training sessions were selected, with a total of 24 articles included for review. Training to failure may lengthen recovery times, potentially impairing performance; however, it may be suitable if implemented strategically ensuring adequate recovery between sessions of similar exercises or muscle groups. Higher volumes may increase recovery demands, especially when paired with training to failure, however, with wide variation in individual responses, it is suggested to start with lower volume, monitor recovery, and gradually increase training volume if appropriate. Exercises emphasising the lower body, multi-joint movements, greater muscle recruitment, eccentric contractions, and/or the lengthened position may require longer recovery times. Adjusting volume and frequency of these exercises can affect recovery demands depending on the goals and training logistics. Daily undulating programming may maximise performance on priority sessions while maintaining purposeful and productive easy days. For example, active recovery in the form of training opposing muscle groups, light aerobic cardio, or low-volume power-type training may improve recovery and potentially elicit a post activation potentiation priming effect compared to passive recovery. However, it is possible that training cessation may be adequate for allowing sufficient recovery prior to sessions of importance.

Atypical anti-glomerular basement membrane disease with membranous hyperplasia: diagnostic challenges and treatment variability

This case report presents a detailed analysis of a 31-year-old male patient who presented with a complex array of clinical symptoms, including proteinuria, hematuria, edema, and kidney insufficiency. Despite undergoing multiple tests, the results for anti-glomerular basement membrane antibodies yielded negative findings. Subsequently, kidney biopsy pathology revealed a distinct diagnosis of atypical anti-glomerular basement membrane (anti-GBM) disease with membrane hyperplasia. Treatment was initiated with a comprehensive approach involving high doses of corticosteroids therapy and cyclophosphamide (CTX). However, contrary to expectations, the patient’s kidney function exhibited rapid deterioration following this therapeutic regimen. The culmination of these complications necessitated a pivotal transition to maintenance hemodialysis. This case underscores the intricate challenges associated with diagnosing and managing rare and atypical presentations of kidney disorders. The negative anti-GBM antibody results and subsequent identification of atypical anti-GBM nephropathy highlight the need for tailored diagnostic strategies to discern subtle nuances within complex clinical scenarios. Additionally, the unexpected response to the treatment regimen emphasizes the potential variability in individual patient responses, underlining the necessity for vigilant monitoring and adaptable treatment strategies. This case report contributes to the evolving understanding of atypical kidney pathologies and the complexities involved in their management.

Exploring Intervention Techniques for Alzheimer’s Disease: Conventional Methods and the Role of AI in Advancing Care

Alzheimer’s disease (AD) is a neurodegenerative condition characterized by cognitive decline and functional impairment. This study compares conventional intervention techniques with emerging artificial intelligence (AI) approaches to AD. Intervention technique refers to a specific method or approach employed to bring about positive change in a particular situation. In the context of AD, such techniques are crucial as they aim to slow down the progression of symptoms, alleviate behavioral challenges, and support patients and their caretakers in managing the complexities of the condition. Conventional intervention techniques, such as cognitive stimulation and reality orientation, have demonstrated benefits in improving cognitive function and emotional well-being. Conventional intervention approaches are widely preferred as they have a proven track record of effectiveness, personalized response, cost-effectiveness, and patient-centered care. Despite these benefits, they are limited by individual variability in response and long-term effectiveness. On the other hand, AI-based approaches such as computer vision and deep learning hold the potential to revolutionize Alzheimer’s interventions. These technologies offer early detection, personalized care, and remote monitoring capabilities. They can provide tailored interventions, assist decision-making, and enhance caregiver support. Although AI-based interventions face challenges such as data privacy and implementation complexity, their potential to transform Alzheimer’s care is significant. This research paper compares conventional and AI-based approaches. It reveals that while traditional techniques are well established and have proven benefits, AI-based interventions offer novel opportunities for personalized and advanced care. Combining the strengths of both approaches may lead to more comprehensive and effective interventions for individuals with AD. Continued research and collaboration are crucial to harness the full potential of AI in improving Alzheimer’s care and enhancing the quality of life for affected individuals and their caregivers.

Exploring Ciprofol Alternatives: A Comprehensive Review of Intravenous Anesthesia Options.

Ciprofol is a recently developed, short-acting γ-aminobutyric acid receptor agonist sedative that is more potent than propofol. Still, there have been few clinical studies of this agent to date. This review explores alternative intravenous anesthesia options to ciprofol, considering their pharmacology, clinical efficacy, safety profile, and practical considerations. While ciprofol offers advantages such as rapid onset and predictable offset, concerns regarding its safety profile and individual variability in response have prompted the search for alternatives. Propofol, etomidate, ketamine, and dexmedetomidine are discussed as established options, each with unique characteristics and potential benefits. Emerging agents, including remimazolam, sufentanil, alfaxalone, and brexanolone, are examined for their potential role in anesthesia management. Recommendations for future research include large-scale comparative studies, optimization of dosing strategies, and personalized approaches guided by pharmacogenomic insights. Ultimately, the future of intravenous anesthesia lies in a multifaceted approach that integrates evidence-based practices, technological innovations, and individualized patient care to enhance safety, efficacy, and patient satisfaction across the perioperative continuum. Collaboration among stakeholders will be crucial in advancing the field and shaping the future landscape of intravenous anesthesia options.

Ramadan Fasting and Its Impact on Patients With Chronic Kidney Disease: Insights and Guidelines.

Fasting during the month of Ramadan is a religious practice observed by millions of Muslims worldwide, including those with chronic kidney disease (CKD). This comprehensive review aims to reflect uponthe impacts of Ramadan fasting on CKD patients, excluding those on renal replacement therapy, through an analysis of clinical trials, observational studies, and expert reviews from diverse geographic and methodological backgrounds. It addresses renal function stability, broader health considerations, hydration and electrolyte balance, individual variability in fasting responses, clinical and biochemical effects, nutritional considerations, and metabolic effects. This review reveals that, with appropriate monitoring, dietary management, and individualized care plans, many CKD patients can safely participate in Ramadan fasting without adversely affecting their renal function or overall health. It emphasizes the need for a multidisciplinary approach to patient education, pre-Ramadan assessment, and post-Ramadan follow-up. Furthermore, it highlights the importance of considering individual variability and comorbidities in fasting guidance and underscores the necessity of future research to develop robust, patient-centered fasting guidelines. This review aims to provide healthcare professionals with evidence-based recommendations to support CKD patients wishing to observe Ramadan fasting, ensuring patient safety and optimizing care outcomes.

Herbs Used in Diabetic Wounds

Diabetic wounds present a formidable healthcare challenge due to their protracted healing process and heightened risk of complications. Fortunately, nature has bestowed us with a rich reserve of medicinal herbs steeped in centuries of traditional use, to foster wound healing and diabetes management. These herbs offer a promising avenue for addressing and overseeing diabetic wounds, providing potential advantages such as enhanced blood circulation, antimicrobial attributes and the mitigation of inflammation. In this article, we will explore the wide spectrum of herbs exhibiting potential in diabetic wound care. We will delve into their mechanisms of action, active constituents and the scientific substantiation endorsing their effectiveness in facilitating wound healing and addressing diabetic symptoms. Integrating these herbs into wound care regimens may expedite the healing process, diminish infection risks, relieve discomfort and conceivably elevate the overall well-being of those grappling with diabetes. Additionally, it is vital to consider individual variations in responses to these herbs, along with potential interactions with existing medications or allergies before incorporating them into a treatment regimen. Through our exploration of the captivating realm of herbs in diabetic wound care, we aspire to illuminate their therapeutic potential and contribute to the ongoing investigation and comprehension of natural remedies for diabetic wounds. Together, we can unveil the potency of nature in supporting the healing journey and enhancing the lives of individuals confronting the complexities of diabetes-related wound management.

Comparative disposition kinetics of oral deracoxib in sheep and goats.

This study investigates the pharmacokinetics (PK) of deracoxib (DX), a selective COX-2 inhibitor, in sheep and goats following a single oral dose. DX, approved for dogs, holds potential as an alternative NSAID in small ruminants, particularly in light of heightened concern regarding abomasal ulceration. The study employed an oral administration of DX at a dose of 150 mg/head (sheep and goats), and plasma concentrations were determined after validating a high-performance liquid chromatography method, coupled to a UV detector. The PK parameters, including maximum plasma concentration (Cmax), time to reach Cmax (Tmax), elimination half-life (t1/2), and area under the curve (AUC), were evaluated through non-compartmental analysis. Results showed detectable DX in plasma up to 48 h, with no observed adverse effects. No significant differences in any PK parameters were noted between sheep and goats. Notably, t1/2 values were relatively long, at 16.66 h for sheep and 22.86 h for goats. Despite the fact that both species exhibited comparable drug exposure, high individual variability was noted within each species, suggesting to take into account individual variations in response to DX treatment, rather than species-specific considerations. Additional research involving pharmacodynamics and multiple-dose studies is warranted to comprehensively assess the profile of DX in these species.

Synergistic response to climate stressors in coral is associated with genotypic variation in baseline expression.

As environments are rapidly reshaped due to climate change, phenotypic plasticity plays an important role in the ability of organisms to persist and is considered an especially important acclimatization mechanism for long-lived sessile organisms such as reef-building corals. Often, this ability of a single genotype to display multiple phenotypes depending on the environment is modulated by changes in gene expression, which can vary in response to environmental changes via two mechanisms: baseline expression and expression plasticity. We used transcriptome-wide expression profiling of eleven genotypes of common-gardened Acropora cervicornis to explore genotypic variation in the expression response to thermal and acidification stress, both individually and in combination. We show that the combination of these two stressors elicits a synergistic gene expression response, and that both baseline expression and expression plasticity in response to stress show genotypic variation. Additionally, we demonstrate that frontloading of a large module of coexpressed genes is associated with greater retention of algal symbionts under combined stress. These results illustrate that variation in the gene expression response of individuals to climate change stressors can persist even when individuals have shared environmental histories, affecting their performance under future climate change scenarios.

Advances and Limitations on the Current Treatment for Schizophrenia and its Future Prospect

Schizophrenia is a challenging mental disorder marked by recurring psychosis. This article provides an in-depth overview of the current status of research and treatment techniques for schizophrenia. The introductory part gives a thorough explanation of the illness, including all of its many phases and symptoms. The review analyzes the genes involved in cell signaling and neurotransmission, including NRG1, DTNBP1, DISC1, and RGS4, which are important contributors to schizophrenia susceptibility. The article discusses the limitations and challenges associated with existing treatment modalities, including antipsychotic drugs (both typical and atypical), transcranial magnetic stimulation, deep brain stimulation, virtual reality, electroconvulsive therapy, and the ketogenic diet. These approaches have demonstrated efficacy in managing different aspects of schizophrenia symptoms, but they also come with limitations such as side effects, individual variability in response, and ethical concerns. To overcome these limitations, the study offers CRISPR gene editing as a viable future therapeutic option. To improve the efficacy and safety of schizophrenia therapies, the conclusion underlines the need for tailored treatment planning, continuous research, and creative approaches. The changing landscape of schizophrenia research and therapy gives promise for better results and quality of life for people living with the condition.

Investigation of deep learning model for predicting immune checkpoint inhibitor treatment efficacy on contrast-enhanced computed tomography images of hepatocellular carcinoma

Although the use of immune checkpoint inhibitors (ICIs)-targeted agents for unresectable hepatocellular carcinoma (HCC) is promising, individual response variability exists. Therefore, we developed an artificial intelligence (AI)-based model to predict treatment efficacy using pre-ICIs contrast-enhanced computed tomography (CT) imaging characteristics. We evaluated the efficacy of atezolizumab and bevacizumab in 43 patients at the Nagasaki University Hospital from 2020 to 2022 using the modified Response Evaluation Criteria in Solid Tumors. A total of 197 Progressive Disease (PD), 271 Partial Response (PR), and 342 Stable Disease (SD) contrast CT images of HCC were used for training. We used ResNet-18 as the Convolutional Neural Network (CNN) model and YOLOv5, YOLOv7, YOLOv8 as the You Only Look Once (YOLO) model with precision-recall curves and class activation maps (CAMs) for diagnostic performance evaluation and model interpretation, respectively. The 3D t-distributed Stochastic Neighbor Embedding was used for image feature analysis. The YOLOv7 model demonstrated Precision 53.7%, Recall 100%, F1 score 69.8%, mAP@0.5 99.5% for PD, providing accurate and clinically versatile predictions by identifying decisive points. The ResNet-18 model had Precision 100% and Recall 100% for PD. However, the CAMs sites did not align with the tumors, suggesting the CNN model is not predicting that a given CT slice is PD, PR, or SD, but that it accurately predicts Individual Patient's CT slices. Preparing substantial training data for tumor drug effect prediction models is challenging compared to general tumor diagnosis models; hence, large-scale validation using an efficient YOLO model is warranted.