Variation In Response Research Articles

How is variability in physiological responses to social stress related to punishment and reward sensitivities? Preliminary findings from the revised reinforcement sensitivity theory of personality perspective

ABSTRACT Objective: Although personality traits are assumed to have biological/physiological foundations, research has yielded mixed evidence regarding the relationship between personality and physiological stress responses. Moreover, the field has often overlooked the contemporary neuroscience-based personality approach, known as the Reinforcement Sensitivity Theory (RST) of Personality, in stress research. Method: The present study examined the relationship between the revised RST's personality dimensions and heart rate and skin conductance level (SCL) in response to the Trier Social Stress Test in a sample of 61 healthy university students. Results: Piecewise latent growth curve analysis controlling for the participants’ current life stress, smoking use, and caffeine intake revealed that individuals with higher behavioral inhibition exhibited higher physiological reactivity, whereas those with high reward sensitivity showed smaller heart rate reactivity. The behavioral disengagement facet of the behavioral inhibition scale was associated with reduced sympathetic arousal during the stress task. Additionally, reward interest was associated with a larger recovery of SCL. Conclusion: Results were generally in line with the revised theory. The study findings were discussed within the paradigm of the approach-avoidance conflict and highlighted the importance of reward sensitivity in stress resilience.

Effect on emergence from anesthesia following induction with diazepam and its association with CYP2C9, CYP2C19 and CYP3A4 gene polymorphisms

Introduction & Objectives: Benzodiazepines are commonly used as adjuvants to IV anesthetic agents. Diazepam dosage varies widely depending on the desired endpoints. The rationale behind such inter-individual variability in drug responses has been attributed to genetically determined alterations in the enzyme activities. We assessed the emergence time in patients after induction of anesthesia with two different doses of diazepam and evaluated if any correlation exists between the emergence time and genetic polymorphism in drug metabolizers CYP2C19, CYP2C9, and CYP3A4 genes. Methodology: The study was conducted on randomly selected adult patients scheduled for elective surgery between 40-60 y of age with predefined inclusion and exclusion criteria. The patients were distributed into 2 groups, with group 1 receiving 0.2 mg/kg and group 2 given 0.3 mg/kg diazepam. Wake-up time after surgery was determined after a standardized verbal command played by a tape-recorder. Three ml blood in Ethylenediaminetetraacetic acid (EDTA) was collected before administering anesthesia. Results: Wake-up time between 8-18 min did not vary between the two groups. Comparatively persons having 2C19 2 took longer time to wake-up but this association was not statistically significant. However, CYP2C9 2 and 2 C9 3 and CYP3A4 genotypes had no influence on wake-up time. Conclusion: The pilot study suggests the emergence time from diazepam is longer in patients having 2C19 2 which confers slow-metabolizer phenotype. However, this study needs to be replicated in larger sample size to arrive at definitive conclusions before clinical applications. Abbreviations: BDZ- benzodiazepine; EDTA- Ethylenediaminetetraacetic acid; GA-General Anesthesia Key words: Diazepam; Emergence; Gene Polymorphism; Pharmacogenetics Citation: Mittal T, Badhe VK, Badhe DSD, Ahluwalia P, Mitta Bl, Mittal R. Effect on emergence from anesthesia following induction with diazepam and its association with CYP2C9, CYP2C19 and CYP3A4 gene polymorphisms. Anaesth. pain intensive care 2024;28(1):126-138. DOI: 10.35975/apic.v28i1.2380 Received: July 20, 2023; Reviewed: December 07, 2023; Accepted: December 07, 2023

Prefrontal intra-individual ERP variability and its asymmetry: exploring its biomarker potential in mild cognitive impairment

BackgroundThe worldwide trend of demographic aging highlights the progress made in healthcare, albeit with health challenges like Alzheimer’s Disease (AD), prevalent in individuals aged 65 and above. Its early detection at the mild cognitive impairment (MCI) stage is crucial. Event-related potentials (ERPs) obtained by averaging EEG segments responded to repeated events are vital for cognitive impairment research. Consequently, examining intra-trial ERP variability is vital for comprehending fluctuations within psychophysiological processes of interest. This study aimed to investigate cognitive deficiencies and instability in MCI using ERP variability and its asymmetry from a prefrontal two-channel EEG device.MethodsIn this study, ERP variability for both target and non-target responses was examined using the response variance curve (RVC) in a sample comprising 481 participants with MCI and 1,043 age-matched healthy individuals. The participants engaged in auditory selective attention tasks. Cognitive decline was assessed using the Seoul Neuropsychological Screening Battery (SNSB) and the Mini-Mental State Examination (MMSE). The research employed various statistical methods, including independent t-tests, and univariate and multiple logistic regression analyses. These analyses were conducted to investigate group differences and explore the relationships between neuropsychological test results, ERP variability and its asymmetry measures, and the prevalence of MCI.ResultsOur results showed that patients with MCI exhibited unstable cognitive processing, characterized by increased ERP variability compared to cognitively normal (CN) adults. Multiple logistic regression analyses confirmed the association between ERP variability in the target and non-target responses with MCI prevalence, independent of demographic and neuropsychological factors.DiscussionThe unstable cognitive processing in the MCI group compared to the CN individuals implies abnormal neurological changes and reduced and (or) unstable attentional maintenance during cognitive processing. Consequently, utilizing ERP variability measures from a portable EEG device could serve as a valuable addition to the conventional ERP measures of latency and amplitude. This approach holds significant promise for identifying mild cognitive deficits and neural alterations in individuals with MCI.

Personalized approach to outpatient management of patients taking tamoxifen by gynecologists

BACKGROUND: 30% of women with luminal breast cancer receiving adjuvant tamoxifen experience disease recurrence within 15 years. This demonstrates the wide variability in clinical response to tamoxifen. Both nongenetic (age, gender, body mass index, duration of drug use) and genetic factors have been described to influence the high variability of response to tamoxifen. Differences in the genes encoding the enzymes CYP2D6, CYP2C, and CYP3A (CYP2D6*4, CYP3A5*3, CYP2C9*2, CYP2C9*3, CYP2C19*2, CYP2C19*3) and the ABCB1 gene (C3435T) may also be the main factors of susceptibility to the occurrence of undesirable effects when taking tamoxifen, which in turn may lead to decreased patient adherence to therapy.
 AIM: The aim of this study was to create a concept and an algorithm for a personalized approach to outpatient management of patients taking tamoxifen by a gynecologist in connection with the carriage of polymorphisms of cytochrome P450 and drug transporter genes.
 MATERIALS AND METHODS: In 2017–2018, the outpatient records of 230 patients with breast cancer were analyzed retrospectively. A single-stage pharmacogenetic study of 120 women with stage I–III luminal breast cancer taking tamoxifen was conducted prospectively for the presence of cytochrome P450 gene polymorphisms using the polymerase chain reaction method and assessing associations with adverse drug reactions, and 54 patients were interviewed after five-year follow-up to assess adherence and satisfaction with medical supervision.
 RESULTS: The likelihood of developing endometrial hyperplasia has been shown to increase while taking tamoxifen with increasing average age, body mass index, duration of tamoxifen use, and postmenopause. Significant associations have been identified between the carriage of the CYP2D6, CYP2C9, CYP2C19, CYP3A5, and ABCB1 gene polymorphisms and the development of adverse drug reactions. Predictive models have been developed to determine the risk of adverse drug reactions. All studied adverse drug reactions associated with various genetic polymorphisms predominated in the group of patients who stopped taking tamoxifen due to poor intolerance. Gynecologists regularly observed 57.4% of patients. Moreover, the higher the adherence to therapy was, the higher was the regularity of observation by a gynecologist.
 CONCLUSIONS: A plan for outpatient management of patients receiving adjuvant endocrine therapy with tamoxifen by a gynecologist has been developed.

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.

Precursors to infant sensorimotor synchronization to speech and non-speech rhythms: A longitudinal study.

Impaired sensorimotor synchronization (SMS) to acoustic rhythm may be a marker of atypical language development. Here, Motion Capture was used to assess gross motor rhythmic movement at six time points between 5- and 11 months of age. Infants were recorded drumming to acoustic stimuli of varying linguistic and temporal complexity: drumbeats, repeated syllables and nursery rhymes. Here we show, for the first time, developmental change in infants' movement timing in response to auditory stimuli over the first year of life. Longitudinal analyses revealed that whilst infants could not yet reliably synchronize their movement to auditory rhythms, infant spontaneous motor tempo became faster with age, and by 11 months, a subset of infants decelerate from their spontaneous motor tempo, which better accords with the incoming tempo. Further, infants became more regular drummers with age, with marked decreases in the variability of spontaneous motor tempo and variability in response to drumbeats. This latter effect was subdued in response to linguistic stimuli. The current work lays the foundation for using individual differences in precursors of SMS in infancy to predict later language outcomes. RESEARCH HIGHLIGHT: We present the first longitudinal investigation of infant rhythmic movement over the first year of life Whilst infants generally move more quickly and with higher regularity over their first year, by 11 months infants begin to counter this pattern when hearing slower infant-directed song Infant movement is more variable to speech than non-speech stimuli In the context of the larger Cambridge UK BabyRhythm Project, we lay the foundation for rhythmic movement in infancy to predict later language outcomes.

Molecular basis of distinct responses to drought between rice and wheat genotypes

The water-intensive cultivation of rice in flooded conditions poses a great challenge to global water resources, particularly in the face of climate change. Wheat requires significantly less water than rice with fairly high yields. A main research question is whether there are any drought adaptive mechanisms in rice similar to those existing in wheat. We report a study, where precise moisture stress was imposed at the vegetative stage using a high-throughput drought simulator phenomics facility. Variability in stress response was captured through untargeted metabolome analysis. In the first experiment, using two rice cultivars with contrasting drought responses (IR64 and Apo) and a wheat cultivar, Weebill, we found distinct variations in regulation of metabolite levels under well-watered or water-limited conditions, both between and within species. Several biosynthetic pathways, including those of polyamines, flavonoids, flavones, and specific metabolites like sphinganine-1-phosphate and anthranilate were enhanced under water-limited conditions. These metabolites were more abundant in wheat than in rice. Among the rice cultivars, Apo had higher abundance of metabolites than IR64. Regulatory patterns governing these metabolic pathways provided basis for stress responses of the tolerant rice cultivar and wheat. A second experiment was conducted to screen rice germplasm lines for acquired tolerance traits contrasting for drought responsiveness. Eight genotypes (four sensitive and four tolerant ones) were selected to validate the candidate metabolites from the first experiment. In the third experiment, an RT-PCR analysis of the key regulatory genes governing the metabolic pathways was conducted, using plant materials from both experiments. The results of this third experiment provided a strong validation for the relevance of these metabolic pathways under stress in rice. We identified promising rice genotypes that exhibited fold change levels of stress resistance metabolites comparable to those of the wheat cultivar Weebill. This study helped identify key candidate metabolites that can be either developed as markers or as elicitors, and genotypes that can be used as trait donor lines for rice improvement.

Maternal GBS vaccination for preventing group B streptococcus disease in newborns: A mini review of current evidence.

Group B streptococcus (GBS) poses a significant threat to neonates, leading to morbidity and mortality. Intrapartum antibiotics, although effective, have limitations, prompting the exploration of maternal vaccination. This study reviews the current evidence for maternal GBS vaccination in the prevention of early-onset GBS disease in newborns. A search on Google Scholar, PubMed, and Scopus identified studies assessing the impact of maternal GBS vaccination on early-onset GBS disease. Inclusion criteria comprised English-language clinical trials or observational studies. Data extraction included study details, immunogenicity profiles, effectiveness, safety outcomes, and relevant findings. Qualitative synthesis was employed for data analysis. Five studies meeting the inclusion criteria were reviewed. Maternal GBS vaccines demonstrated efficacy with sustained immunogenicity. Adverse events, although documented, were predominantly non-severe. Variability in immune responses and maternal-to-infant antibody ratios show the need for tailored vaccination approaches. Long-term follow up and surveillance are essential to assess persistence and identify unintended effects. Positive outcomes in vaccine efficacy support GBS vaccination integration into maternal health programs. Implementation challenges in diverse healthcare infrastructures require tailored approaches, especially in resource-limited settings. Overcoming cultural barriers and ensuring healthcare provider awareness are crucial for successful vaccination.

Immunotherapy and Radiation Therapy Combinatorial Approaches in Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC), a prevalent and often fatal liver cancer, presents significant treatment challenges, especially in its advanced stages. This article delves into the promising approach of combining immunotherapy, particularly immune checkpoint inhibitors, with radiation therapy, a cornerstone of HCC management. Our review synthesizes current preclinical and clinical research, highlighting the potential synergistic effects of this combinational treatment. Emerging evidence suggests that this synergy enhances tumor control and improves patient survival rates. The combination leverages the localized, tumor-targeting ability of radiation therapy and the systemic, immune-boosting effects of immunotherapy, potentially overcoming the limitations inherent in each treatment modality when used separately. This integrative approach is especially promising in addressing the complex tumor microenvironment of HCC. However, the treatment landscape is nuanced, with challenges such as patient-specific response variability and potential resistance to therapies. Future research directions should focus on refining these combination strategies, tailoring them to individual patient profiles, and understanding the underlying mechanisms that govern the interaction between immunotherapy and radiation therapy. Such advancements could significantly improve HCC management, setting new standards for patient care and treatment efficacy.

Abstract B017: Understanding the impact of transporter heterogeneity on the efficacy of PARP inhibitors

Abstract B017: Understanding the impact of transporter heterogeneity on the efficacy of PARP inhibitors

Abstract A105: Untangling the effect of ascites in shaping high grade serous ovarian cancer progression

Abstract High Grade Serous Ovarian Cancer (HGSOC) is the eighth cause of cancer-related mortality worldwide. Progress in eradicating this disease has been hampered by several factors, including the uncertainty about its tissues of origin, late diagnosis coupled to early dissemination through accumulation of ascitic fluid and extensive inter-patient variability. While being histopathologically homogeneous, HGSOC is characterized by several layers of heterogeneity that require the development of ad hoc research strategies and to focus on specific scales in order to deconvolve HGSOC pathogenetic mechanisms. In this context, our lab has previously shown that HGSOC can be derived both from the distal tract of the fallopian tube (fallopian tube epithelium, FTE) and the ovarian surface epithelium (OSE), with a prognostic impact for the tissue of origin and origin-specific molecular phenotypes, including an immune-suppressive response in the more aggressive OSE-derived subtype (Lo Riso, Villa et al. 2020), pointing at the role of tumor microenvironment in shaping therapeutical response. Moreover, we have also shown the role of ascitic fluid in sustaining the generation of single cell-derived metastatic ovarian cancer spheroids (sMOCS), that enrich for cancer stem-like cells, and allowing to identify a consistent intra-patient variability in response to carboplatin treatment (Velletri, Villa, Cilli, Barzaghi et al. 2022). To understand the specific impact of the tumor microenvironment in shaping HGSOC complexity, here we show an experimental framework aimed at the identification of the downstream effect of ascites in shaping cellular and molecular features of HGSOC. Here we leverage a newly generated single cell transcriptomic atlas, encompassing 1.5 million cells from 79 patients derived from primary tumors, ascites and metastatic samples, to identify specific expression networks activated during the metastatization process. In parallel, we derive from bulk transcriptomic data the set of genes that are induced upon ascitic fluid supplementation in 2D and 3D in vitro models, that are coupled to model-specific phenotypes, including cell proliferation, stemness and invasiveness. These genes are then integrated in the single-cell derived metastasis-specific expression networks to identify the upstream regulators imputable to ascitic fluid exposure. The linked regulators and downstream effectors are then used to identify in the atlas cell populations whose expression landscape is directly affected by ascitic fluid. The identification of such cell populations will allow to highlight cell-to-cell interactions existing between i) different tumor subpopulations; ii) tumor and tumor-associated compartments, in both primary and metastatic samples, that can be ascribed to the presence of ascitic fluid. Moreover, the molecular characterization of these interacting populations will allow to identify novel targets, paving the way to the identification of novel therapeutical avenues for HGSOC patients. Citation Format: Pietro Lo Riso, Carlo Emanuele Villa, Bianca Barzaghi, Marta R. Sallese, Giulia Picco, Alessia Gatto, Ugo Cavallaro, Giuseppe Testa. Untangling the effect of ascites in shaping high grade serous ovarian cancer progression [abstract]. In: Proceedings of the AACR Special Conference on Ovarian Cancer; 2023 Oct 5-7; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(5 Suppl_2):Abstract nr A105.

Leaf trait variation in grassland plant species in response to soil phosphorus

AbstractQuestionsIncreased soil phosphorus (P) availability in fertilized grasslands can drive both community degradation and delayed community recovery upon agricultural abandonment. Beyond describing grassland community patterns along gradients in P availability, it remains unclear how individual species with different strategies respond to increasing phosphorus. Here we studied intraspecific variability of leaf functional traits in response to soil phosphorus, for species with contrasting resource‐use strategies.MethodsWe set up a pot experiment with communities containing four species, assembled from a pool of 20 mesotrophic grassland species growing along a soil P gradient. Species selection included various growth forms (grasses vs forbs) and resource‐use strategies (acquisitive vs conservative resource use). We measured three variables characterizing the (a)biotic environmental context: bioavailable soil P concentration, total community biomass as a proxy for the intensity of competition, and the proportional biomass of a species in the community as a proxy for its competitive dominance. We investigated the effect of this environmental context on the expression of two leaf traits, specific leaf area (SLA) and leaf dry matter content (LDMC).ResultsWe found an acquisitive trait expression within species (increase in SLA and decrease in LDMC) in response to increased soil P supply and a conservative trait expression (decrease in SLA and increase in LDMC) in response to an increase in total community biomass. Importantly, the trait responses to the environmental context were generally consistent for species representing very different resource‐use strategies and growth forms.ConclusionsSpecies responded with a shift from an acquisitive to a conservative trait expression in response to limited resources; i.e., driven by a decrease in soil phosphorus concentration or an increase in total community biomass. Unexpectedly, the intraspecific variability in response to the changing environmental conditions was not clearly mediated by the species’ strategy. These findings show that plant ecological strategies are probably not the main driver for intraspecific trait variability in an experimental grassland community.

Population Pharmacokinetics of Valproate in Children: The Importance of Total Daily Dose, Compliance and Co-Treatment

Abstract Valproate represents one of the most commonly used anticonvulsants worldwide, whose narrow therapeutic range and high potential for drug-drug interactions leads to pronounced intra- and inter-individual variability in plasma concentration and response. The aim of our study was to apply population pharmacokinetics analysis to comprehensively investigate and detect the most important factors affecting pharmacokinetics of valproate in Serbian children with epilepsy. This retrospective observational study was based on demographic and medical data retrieved from the medical records on epileptic patients treated with valproate at the pediatric department of the Clinical Centre, Kragujevac, Serbia. Valproate serum concentrations were obtained as a part of routine medical practice. Population pharmacokinetics analysis was performed by MonolixSuite 2019R1 (Lixoft, Antony, France) software, using one-compartment model with first order absorption and linear elimination. The study included 1642 valproate concentrations obtained from 232 patients, of which 201 (1420 concentrations) were included in the index set used for the modelling, while the other 31 (222 concentrations) were the validation set used for external validation of the final model. Covariate testing based on the whole index set revealed that only total daily valproate dose significanly affected the clearance of valproate: Cl (l/h)= 0.135×1.002DD. When only compliant patients were included, co-treatment with carbamazepine was shown to be of significance as well: Cl(l/h)=0.121×1.002DD×1.2CBZ. Our study demonstrated that valproate clearance correlates with total valproate daily dose. The influence of co-treatment with carbamazepine on valproate pharmacokinetics can be observed and used for clearance estimation only in compliant patients.

Genetic Determinants of Response to Statins in Cardiovascular Diseases.

Despite extensive efforts to identify patients with cardiovascular disease (CVD) who could most benefit from the treatment approach, patients vary in their benefit from therapy and propensity for adverse drug events. Genetic variability in individual responses to drugs (pharmacogenetics) is considered an essential determinant in responding to a drug. Thus, understanding these pharmacogenomic relationships has led to a substantial focus on mechanisms of disease and drug response. In turn, understanding the genomic and molecular bases of variables that might be involved in drug response is the main step in personalized medicine. There is a growing body of data evaluating drug-gene interactions in recent years, some of which have led to FDA recommendations and detection of markers to predict drug responses (e.g., genetic variant in VKORC1 and CYP2C9 genes for prediction of drug response in warfarin treatment). Also, statins are widely prescribed drugs for the prevention of CVD. Atorvastatin, fluvastatin, rosuvastatin, simvastatin, and lovastatin are the most common statins used to manage dyslipidemia. This review provides an overview of the current knowledge on the pharmacogenetics of statins, which are being used to treat cardiovascular diseases.

The autocorrelated Bayesian sampler: A rational process for probability judgments, estimates, confidence intervals, choices, confidence judgments, and response times.

Normative models of decision-making that optimally transform noisy (sensory) information into categorical decisions qualitatively mismatch human behavior. Indeed, leading computational models have only achieved high empirical corroboration by adding task-specific assumptions that deviate from normative principles. In response, we offer a Bayesian approach that implicitly produces a posterior distribution of possible answers (hypotheses) in response to sensory information. But we assume that the brain has no direct access to this posterior, but can only sample hypotheses according to their posterior probabilities. Accordingly, we argue that the primary problem of normative concern in decision-making is integrating stochastic hypotheses, rather than stochastic sensory information, to make categorical decisions. This implies that human response variability arises mainly from posterior sampling rather than sensory noise. Because human hypothesis generation is serially correlated, hypothesis samples will be autocorrelated. Guided by this new problem formulation, we develop a new process, the Autocorrelated Bayesian Sampler (ABS), which grounds autocorrelated hypothesis generation in a sophisticated sampling algorithm. The ABS provides a single mechanism that qualitatively explains many empirical effects of probability judgments, estimates, confidence intervals, choice, confidence judgments, response times, and their relationships. Our analysis demonstrates the unifying power of a perspective shift in the exploration of normative models. It also exemplifies the proposal that the "Bayesian brain" operates using samples not probabilities, and that variability in human behavior may primarily reflect computational rather than sensory noise. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Balancing Act: A Comprehensive Review of Vestibular Evaluation in Cochlear Implants.

Cochlear implantation, a transformative intervention for individuals with profound hearing loss, has evolved significantly over the years. However, its impact on the vestibular system, responsible for balance and spatial orientation, remains a subject of ongoing research and clinical consideration. This narrative review highlights key aspects of vestibular evaluation in patients undergoing cochlear implantation. Preoperative vestibular assessment is crucial to establish baseline vestibular function and identify any pre-existing balance issues. Various tests, including caloric, rotational chair,vestibular-evoked myogenic potential, and video head impulse tests, play a vital role in evaluating vestibular function. The goal is to assess the risk of vestibular disturbances arising from the surgery, guide surgical planning, anddetect pre-existing alterations that could be totally or partially compensated. While some patients experience minimal vestibular disruptions, others may encounter transient or persistent balance issues following cochlear implant surgery. Postoperative vestibular testing allows for the early detection of such disturbances, enabling timely interventions like vestibular rehabilitation and evaluating changes produced due to surgical complications or changes in the patient's prior conditions. Challenges in vestibular evaluation include individual variability in patient responses, the proximity of the cochlea to the vestibular system, and the need to tailor testing protocols to individual needs.Further research is essential to refine testing protocols, minimize vestibular disturbances, and improve outcomes for cochlear implant candidates. A multidisciplinary approach involving otolaryngologists, audiologists, and physical therapists is integral to comprehensive patient care in this context. In conclusion, vestibular evaluation in patients undergoing cochlear implantation is critical for optimizing surgical planning, managing postoperative issues, and enhancing the overall quality of life for individuals embarking on the journey of restored hearing.

The polymorphisms of candidate pharmacokinetic and pharmacodynamic genes and their pharmacogenetic impacts on the effectiveness of risperidone maintenance therapy among Saudi children with autism.

Antipsychotics, including risperidone (RIS), are frequently indicated for various autism spectrum disorder (ASD) manifestations; however, "actionable" PGx testing in psychiatry regarding antipsychotic dosing and selection has limited applications in routine clinical practice because of the lack of standard guidelines, mostly due to the inconsistency and scarcity of genetic variant data. The current study is aimed at examining the association of RIS effectiveness, according to ABC-CV and CGI indexes, with relevant pharmacokinetics (PK) and pharmacodynamics (PD) genes. Eighty-nine ASD children who received a consistent RIS-based regimen for at least 8weeks were included. The Axiom PharmacoFocus Array technique was employed to generate accurate star allele-predicted phenotypes of 3 PK genes (CYP3A4, CYP3A5, and CYP2D6). Genotype calls for 5 candidate PD receptor genes (DRD1, DRD2, DRD3, HTR2C, and HTR2A) were obtained and reported as wild type, heterozygous, or homozygous for 11 variants. Based on the ABC total score, 42 (47.2%) children were classified as responders, while 47 (52.8%) were classified as nonresponders. Multivariate logistic regression analyses, adjusted for nongenetic factors, suggested nonsignificant impacts of the star allele-predicted phenotypes of all 3 PK genes on improvement in ASD symptoms or CGI scores. However, significant positive or negative associations of certain PD variants involved in dopaminergic and serotonergic pathways were observed with specific ASD core and noncore symptom subdomains. Our significant polymorphism findings, mainly those in DRD2 (rs1800497, rs1799978, and rs2734841), HTR2C (rs3813929), and HTR2A (rs6311), were largely consistent with earlier findings (predictors of RIS effectiveness in adult schizophrenia patients), confirming their validity for identifying ASD children with a greater likelihood of core symptom improvement compared to noncarriers/wild types. Other novel findings of this study, such as significant improvements in DRD3 rs167771 carriers, particularly in ABC total and lethargy/social withdrawal scores, and DRD1 rs1875964 homozygotes and DRD2 rs1079598 wild types in stereotypic behavior, warrant further verification in biochemical and clinical studies to confirm their feasibility for inclusion in a PGx panel. In conclusion, we provide evidence of potential genetic markers involved in clinical response variability to RIS therapy in ASD children. However, replication in prospective samples with greater ethnic diversity and sample sizes is necessary.

Knowledge and attitudes on implementing cardiovascular pharmacogenomic testing.

Pharmacogenomics has the potential to inform drug dosing and selection, reduce adverse events, and improve medication efficacy; however, provider knowledge of pharmacogenomic testing varies across provider types and specialties. Given that many actionable pharmacogenomic genes are implicated in cardiovascular medication response variability, this study aimed to evaluate cardiology providers' knowledge and attitudes on implementing clinical pharmacogenomic testing. Sixty-one providers responded to an online survey, including pharmacists (46%), physicians (31%), genetic counselors (15%), and nurses (8%). Most respondents (94%) reported previous genetics education; however, only 52% felt their genetics education prepared them to order a clinical pharmacogenomic test. In addition, most respondents (66%) were familiar with pharmacogenomics, with genetic counselors being most likely to be familiar (p < 0.001). Only 15% of respondents had previously ordered a clinical pharmacogenomic test and a total of 36% indicated they are likely to order a pharmacogenomic test in the future; however, the vast majority of respondents (89%) were interested in pharmacogenomic testing being incorporated into diagnostic cardiovascular genetic tests. Moreover, 84% of providers preferred pharmacogenomic panel testing compared to 16% who preferred single gene testing. Half of the providers reported being comfortable discussing pharmacogenomic results with their patients, but the majority (60%) expressed discomfort with the logistics of test ordering. Reported barriers to implementation included uncertainty about the clinical utility and difficulty choosing an appropriate test. Taken together, cardiology providers have moderate familiarity with pharmacogenomics and limited experience with test ordering; however, they are interested in incorporating pharmacogenomics into diagnostic genetic tests and ordering pharmacogenomic panels.

Anthracyclines induce cardiotoxicity through a shared gene expression response signature.

TOP2 inhibitors (TOP2i) are effective drugs for breast cancer treatment. However, they can cause cardiotoxicity in some women. The most widely used TOP2i include anthracyclines (AC) Doxorubicin (DOX), Daunorubicin (DNR), Epirubicin (EPI), and the anthraquinone Mitoxantrone (MTX). It is unclear whether women would experience the same adverse effects from all drugs in this class, or if specific drugs would be preferable for certain individuals based on their cardiotoxicity risk profile. To investigate this, we studied the effects of treatment of DOX, DNR, EPI, MTX, and an unrelated monoclonal antibody Trastuzumab (TRZ) on iPSC-derived cardiomyocytes (iPSC-CMs) from six healthy females. All TOP2i induce cell death at concentrations observed in cancer patient serum, while TRZ does not. A sub-lethal dose of all TOP2i induces limited cellular stress but affects calcium handling, a function critical for cardiomyocyte contraction. TOP2i induce thousands of gene expression changes over time, giving rise to four distinct gene expression response signatures, denoted as TOP2i early-acute, early-sustained, and late response genes, and non-response genes. There is no drug- or AC-specific signature. TOP2i early response genes are enriched in chromatin regulators, which mediate AC sensitivity across breast cancer patients. However, there is increased transcriptional variability between individuals following AC treatments. To investigate potential genetic effects on response variability, we first identified a reported set of expression quantitative trait loci (eQTLs) uncovered following DOX treatment in iPSC-CMs. Indeed, DOX response eQTLs are enriched in genes that respond to all TOP2i. Next, we identified 38 genes in loci associated with AC toxicity by GWAS or TWAS. Two thirds of the genes that respond to at least one TOP2i, respond to all ACs with the same direction of effect. Our data demonstrate that TOP2i induce thousands of shared gene expression changes in cardiomyocytes, including genes near SNPs associated with inter-individual variation in response to DOX treatment and AC-induced cardiotoxicity.

Using forest plots to interpret covariate effects in pharmacometric models.

The inclusion of covariates in pharmacometric models is important due to their ability to explain variability in drug exposure and response. Clear communication of the impact of covariates is needed to support informed decision making in clinical practice and in drug development. However, effectively conveying these effects to key stakeholders and decision makers can be challenging. Forest plots have been proposed to meet these communication needs. However, forest plots for the illustration of covariate effects in pharmacometrics are complex combinations of model predictions, uncertainty estimates, tabulated results, and reference lines and intervals. The purpose of this tutorial is to outline the aspects that influence the interpretation of forest plots, recommend best practices, and offer specific guidance for a clear and transparent communication of covariate effects.