Significant Individual Differences Research Articles

A longitudinal study on self-rated health changes in disabled older people.

There is a growing demand for quality healthcare for senior citizens among the disabled older population, considering their rising numbers. This study examines the longitudinal change in the health status of disabled older people and determines its effects on social exclusion and differences based on age at disability onset. The analysis was performed using a multilevel growth model on the health data for disabled older people (≥60 years) derived from the Korea Welfare Panel Study (KWePS). The following findings were observed based on the stated model: (1) The Self-Rated Health (SRH) of disabled older people increased over time, with significant individual differences in the initial status and growth rate; (2) The domains of economic and social network exclusion were associated with changes in the health status of disabled older people; and (3) The longitudinal effects of social exclusion on SRH changes in disabled older people varied according to the age at disability onset. Based on these results, strategies and implications for the development of health-promoting interventions for disabled older people were presented.

Genome-wide association exploratory studies in individuals with ultra-high risk for schizophrenia in Chinese Han nationality in two years follow-up: A subpopulation study

BackgroundAlthough ultra-high risk for schizophrenia (UHR) is related to both genetic and environment factors, the precise pathogenesis is still unknow. To date, few studies have explored the Genome-Wide Association Studies (GWAS) in UHR or HR individuals especially in Han population in China. MethodsIn this study, a GWAS analysis for 36 participants with UHR and 43 with HR were performed, and all deletion variations in 22q11 region were also compared. Results: Sixteen individuals with UHR (44.4%) and none with HR converted into schizophrenia in follow-up after two years. Six loci including neurexin-1(NRXN1) (rs1045881), dopamine D1 receptor (DRD1) (rs686, rs4532), chitinase-3-like protein 1 (CHI3L1) (rs4950928), velocardiofacial syndrome (ARVCF) (rs165815), dopamine D2 receptor (DRD2) (rs1076560) were identified higher expression with significant difference in individuals converted into schizophrenia after two years. The Family with Sequence Similarity 230 Member H (FAM230H) gene in the 22q11 region were also found high expression in UHR group. ConclusionsFurther expansion of sample size and validation studies are needed to explore the pathogenesis of these risk loci in UHR conversion into schizophrenia in the future.

Baseline immunoglobulin G and immune function in non-Hodgkin lymphoma: a retrospective analysis.

Non-Hodgkin's lymphoma (NHL) encompasses a diverse group of lymphoma subtypes with a wide range in disease course. Previous studies show that hypogammaglobulinemia in treatment-naïve patients is associated with poorer survival in high grade B-cell non-Hodgkin's lymphomas, though it is not known how this applies across all B-cell lymphoid malignancies. We conducted a retrospective study of immunoglobulin levels and clinical outcomes including survival, hospitalization, and infection rates in patients diagnosed with B-cell non-Hodgkin lymphomas of all grades at our institution. Two-hundred twenty-three adults (aged = 18 years) with available pre-treatment IgG levels were selected, with hypogammaglobulinemia defined as IgG< 500 mg/mL. For this analysis, we grouped DLBCL (n=90), Primary CNS (n=5), and Burkitt lymphoma (n=1) together as high-grade, while CLL (n=52), mantle cell (n=20), marginal zone (n=25), follicular (n=21), and Waldenstrom macroglobulinemia (n=5) were low-grade. The incidence of hypogammaglobulinemia in our cohort of both high and low-grade lymphoma patients was 13.5% (n=30). Across all NHL subtypes, individuals with baseline IgG< 500 mg/dL showed an increased rate of hospitalization (4.453, CI: 1.955-10.54, p= 0.0005) and higher mortality (3.325, CI: 1.258, 8.491, p= 0.013), yet no association in number of infections when compared with those with IgG=500 mg/dL. There was a higher hospitalization rate (3.237, CI: 1.77-6.051, p=0.0017) in those with high-grade lymphoma with hypogammaglobulinemia when compared with low-grade. There was no statistically significant difference in individuals who were alive after three years in those with baseline IgG<500 mg/dL. Our study is the first to analyze incidence of hypogammaglobulinemia at the time of diagnosis of NHL as a potential biomarker of interest for future outcomes including hospitalization and infection.

Intra and interspecific variation in thermal performance and critical limits in anurans from southern Chile

The relationship between temperature and performance can be illustrated through a thermal performance curve (TPC), which has proven useful in describing various aspects of ectotherms' thermal ecology and evolution. The parameters of the TPC can vary geographically due to large-scale variations in environmental conditions. However, only some studies have attempted to quantify how thermal performance varies over relatively small spatial scales, even in the same location or consistently among individuals within a species. Here, we quantified individual and species variation in thermal sensitivity of locomotor performance in five amphibia Eupsophus species found in the temperate rainforests of southern Chile and compared their estimates against co-occurring species that exhibit a substantially more extensive distributional range. We measured critical thermal limits and jumping performance under five different temperatures. Our results suggest that thermal responses are relatively conserved along the phylogeny, as the locomotor performance and thermal windows for activity remained narrow in Eupsophus species when compared against results observed for Batrachyla taeniata and Rhinella spinulosa. Additionally, we found significant individual differences in locomotor performance within most species, with individual consistency in performance observed across varied temperatures. Further analyses explored the influence of body size on locomotor performance and critical thermal limits within and between species. Our results suggest a trade-off scenario between thermal tolerance breadth and locomotor performance, where species exhibiting broader thermal ranges might have compromised performance. Interestingly, these traits seem partly mediated by body size variations, raising questions about potential ecological implications.

Nomogram model of survival prediction for nasopharyngeal carcinoma with lung metastasis: developed from the SEER database and validated externally.

Distant metastasis occurs in some patients at the first diagnosis of nasopharyngeal carcinoma (NPC), the prognosis is poor, and there are significant individual differences. This study established a nomogram model of lung metastasis of NPC as a supplement to TNM staging. The training cohort is used to build the nomogram model, and the validation cohort is used to evaluate the model. The training cohort of 177 patients is from the Surveillance, Epidemiology, and End Results (SEER) database. Factors affecting overall survival (OS) in patients with lung metastasis of NPC analysis by Cox regression analysis and then a nomogram were established. 122 patients from the Affiliated Tumor Hospital of Guangxi Medical University were selected as the external validation cohort. The concordance index (C-index), the area under the curve (AUC), and the calibration curve were used to assess the accuracy of the nomogram and used the decision curve analysis (DCA) curve to measure the clinical benefit capacity of the model. The patients were separated into two groups with different risks, and the "Kaplan-Meier (KM)" survival analysis was used to evaluate the differentiation ability of the model. Age, T-stage, radiation, chemotherapy, and brain metastases can affect the OS in NPC with lung metastasis. A nomogram was developed according to the above five factors. The C-index of the training cohort and the validation cohort were 0.726 (95% CI: 0.692-0.760) and 0.762 (95% CI: 0.733-0.791). The AUC of the nomogram was better than that of the TNM staging. In the training cohort, the nomogram predicted OS AUC values of 0.767, 0.746, and 0.750 at 1, 2, and 3 years, TNM stage of 0.574, 0.596, and 0.640. In the validation cohort, nomogram predictions of OS AUC values of 0.817, 0.857, and 0.791 for 1, 2, and 3 years, TNM stage of 0.575, 0.612, and 0.663. DCA curves suggest that nomogram have better clinical net benefits than TNM staging. The KM survival analysis shows that the nomogram has a reasonable risk stratification ability. This study successfully established a nomogram model of NPC lung metastasis, which can be used as a supplement to TNM staging and provide reference for clinicians.

CPhaMAS: An online platform for pharmacokinetic data analysis based on optimized parameter fitting algorithm

Background and objectiveClinical pharmacological modeling and statistical analysis software is an essential basic tool for drug development and personalized drug therapy. The learning curve of current basic tools is steep and unfriendly to beginners. The curve is even more challenging in cases of significant individual differences or measurement errors in data, resulting in difficulties in accurately estimating pharmacokinetic parameters by existing fitting algorithms. Hence, this study aims to explore a new optimized parameter fitting algorithm that reduces the sensitivity of the model to initial values and integrate it into the CPhaMAS platform, a user-friendly online application for pharmacokinetic data analysis. MethodsIn this study, we proposed an optimized Nelder-Mead method that reinitializes simplex vertices when trapped in local solutions and integrated it into the CPhaMAS platform. The CPhaMAS, an online platform for pharmacokinetic data analysis, includes three modules: compartment model analysis, non-compartment analysis (NCA) and bioequivalence/bioavailability (BE/BA) analysis. Our proposed CPhaMAS platform was evaluated and compared with existing WinNonlin. ResultsThe platform was easy to learn and did not require code programming. The accuracy investigation found that the optimized Nelder-Mead method of the CPhaMAS platform showed better accuracy (smaller mean relative error and higher R2) in two-compartment and extravascular administration models when the initial value was set to true and abnormal values (10 times larger or smaller than the true value) compared with the WinNonlin. The mean relative error of the NCA calculation parameters of CPhaMAS and WinNonlin was <0.0001 %. When calculating BE for conventional, high-variability and narrow-therapeutic drugs. The main statistical parameters of the parameters Cmax, AUCt, and AUCinf in CPhaMAS have a mean relative error of <0.01% compared to WinNonLin. ConclusionsIn summary, CPhaMAS is a user-friendly platform with relatively accurate algorithms. It is a powerful tool for analysing pharmacokinetic data for new drug development and precision medicine.

Biological age assessment method teenage students

To assess the biological age of adolescents, the special literature offers 9 methods for boys and 14 methods for girls. The aim of the article was to determine the more informative methods for boys and girls. Methods: anthropometry, somatometry, somatoscopy, tonometry, spirometry, dynamometry, Hench and Shtange tests, Ruffier and Robinson indices. The interaction of the results of different methods for the assessment of biological age was analysed using factor analysis (principal components method) for groups of subjects of the same gender and age. Boys aged 14-15 (n=102) and girls aged 12-13 (n=101) were studied. The choice of these age groups was explained by the presence of the most significant individual differences in morpho-functional features in the school students of this age. Results: among the methods for assessment of biological age in adolescent school students proposed in the literature, there is not a single one that would be statistically siginificantly related to the other methods. This applies to both boys and girls. The biological age of adolescents can be reliably determined using a set of three components: an assessment of physical development, the heterochronicity index, and the degree of manifestation of secondary sexual characteristics (for boys with a probability of 90.2%, for girls - 92.1%). The percentage ratio of these components has gender peculiarities. Methods for assessing biological age for scientific purposes and quick assessment for use in the practice of physical education and sports are proposed. The indicators in quick assessment technique include body length and the degree of development of the axillary hair. The reliability of the quick assessment technique is 81.4% for boys and 83.2% for girls. Conclusion: the development of adequate physical activity for adolescents of different biological ages will help to improve the physical health of the younger generation.

Nonalcoholic Fatty Liver Disease: Changes in Gut Microbiota and Blood Lipids.

The global prevalence of nonalcoholic fatty liver disease (NAFLD) is 25%. This study aimed to explore differences in the gut microbial community and blood lipids between normal livers and those affected by NAFLD using 16S ribosomal deoxyribonucleic acid sequencing. Gut microbiome profiles of 40 NAFLD and 20 non-NAFLD controls were analyzed. Information about four blood lipids and 13 other clinical features was collected. Patients were divided into three groups by ultrasound and FibroScan, those with a normal liver, mild FL (FL1), and moderate-to-severe FL (FL2). FL1 and FL2 patients were divided into two groups, those with either hyperlipidemia or non-hyperlipidemia based on their blood lipids. Potential keystone species within the groups were identified using univariate analysis and a specificity-occupancy plot. Significant difference in biochemical parameters ion NAFLD patients and healthy individuals were identified by detrended correspondence analysis and canonical correspondence analysis. Decreased gut bacterial diversity was found in patients with NAFLD. Firmicutes/Bacteroidetes decreased as NAFLD progressed. Faecalibacterium and Ruminococcus 2 were the most representative fatty-related bacteria. Glutamate pyruvic transaminase, aspartate aminotransferase, and white blood cell count were selected as the most significant biochemical indexes. Calculation of areas under the curve identified two microbiomes combined with the three biochemical indexes that identified normal liver and FL2 very well but performed poorly in diagnosing FL1. Faecalibacterium and Ruminococcus 2, combined with glutamate pyruvic transaminase, aspartate aminotransferase, and white blood cell count distinguished NAFLD. We speculate that regulating the health of gut microbiota may release NAFLD, in addition to providing new targets for clinicians to treat NAFLD.

“…So that only the memory of anger remains…”: An autoethnographic analysis of the loss and mourning of addicted parents

Growing up in a family with addiction can have an impact at many points not only on childhood but also on adulthood. A child who grows up in a dysfunctional family could experience a grieving process from childhood, of which two layers can be distinguished—the grief associated with the loss of childhood and the loss of the idealized parent. The grieving process becomes complicated when the parent dies; this is the third layer of grief. Through the first author’s auto ethnographic account, we will show characteristics of a complicated grieving process that an adult child may experience after the loss of a parent. The analysis reveals a specific pattern of grieving following the deaths of parents who have struggled with addiction, with general findings and probably significant individual differences. The pattern appears to be the least marked in the mourning of parents, with considerable grief and self-work required both before and after the parent’s death.

HBB contributes to individualized aconitine-induced cardiotoxicity in mice via interfering with ABHD5/AMPK/HDAC4 axis

The root of Aconitum carmichaelii Debx. (Fuzi) is an herbal medicine used in China that exerts significant efficacy in rescuing patients from severe diseases. A key toxic compound in Fuzi, aconitine (AC), could trigger unpredictable cardiotoxicities with high-individualization, thus hinders safe application of Fuzi. In this study we investigated the individual differences of AC-induced cardiotoxicities, the biomarkers and underlying mechanisms. Diversity Outbred (DO) mice were used as a genetically heterogeneous model for mimicking individualization clinically. The mice were orally administered AC (0.3, 0.6, 0.9 mg· kg−1 ·d−1) for 7 d. We found that AC-triggered cardiotoxicities in DO mice shared similar characteristics to those observed in clinic patients. Most importantly, significant individual differences were found in DO mice (variation coefficients: 34.08%–53.17%). RNA-sequencing in AC-tolerant and AC-sensitive mice revealed that hemoglobin subunit beta (HBB), a toxic-responsive protein in blood with 89% homology to human, was specifically enriched in AC-sensitive mice. Moreover, we found that HBB overexpression could significantly exacerbate AC-induced cardiotoxicity while HBB knockdown markedly attenuated cell death of cardiomyocytes. We revealed that AC could trigger hemolysis, and specifically bind to HBB in cell-free hemoglobin (cf-Hb), which could excessively promote NO scavenge and decrease cardioprotective S-nitrosylation. Meanwhile, AC bound to HBB enhanced the binding of HBB to ABHD5 and AMPK, which correspondingly decreased HDAC-NT generation and led to cardiomyocytes death. This study not only demonstrates HBB achievement a novel target of AC in blood, but provides the first clue for HBB as a novel biomarker in determining the individual differences of Fuzi-triggered cardiotoxicity.

Responsiveness to exoskeleton loading during bimanual reaching is associated with corticospinal tract integrity in stroke.

Device-based rehabilitation of upper extremity impairment following stroke often employs one-sized-fits-all approaches that do not account for individual differences in patient characteristics. Determine if corticospinal tract lesion load could explain individual differences in the responsiveness to exoskeleton loading of the arms in chronic stroke participants. Fourteen stroke participants performed a bimanual shared cursor reaching task in virtual reality while exoskeletons decreased the effective weight of the more-impaired arm and increased the effective weight of the less-impaired arm. We calculated the change in relative displacement between the arms (RC) and the change in relative muscle activity (MC) between the arms from the biceps and deltoids. We calculated corticospinal tract lesion load (wCSTLL) in a subset of 10 participants. Exoskeleton loading did not change RC (p = 0.07) or MC (p = 0.47) at the group level, but significant individual differences emerged. Participants with little overlap between the lesion and corticospinal tract responded to loading by decreasing muscle activity in the more-impaired arm relative to the less-impaired arm. The change in deltoid MC was associated with smaller wCSTLL (R2 = 0.43, p = 0.039); there was no such relationship for biceps MC (R2 < 0.001, p = 0.98). Here we provide evidence that corticospinal tract integrity is a critical feature that determines one's ability to respond to upper extremity exoskeleton loading. Our work contributes to the development of personalized device-based interventions that would allow clinicians and researchers to titrate constraint levels during bimanual activities.

Few-shot meta-learning for pre-symptomatic detection of Covid-19 from limited health tracker data

Detecting (or screening for) Covid-19 even before symptoms fully manifest, could enable patients to receive timely and life-saving treatment. Prior work has demonstrated that heart rate and step data from low-end wearables analyzed using deep learning models can detect Covid-19 reliably. However, significant individual differences in vital sign manifestation (high inter-subject variability) present a challenge to the generalization of deep learning models across diverse users. The limited amount of data in many medical scenarios further exacerbates this issue. Consequently, neural network models that can learn from limited vital sign data and varied inter-subject patterns are compelling. Meta-learning has emerged as a powerful technique for tackling various machine learning challenges, including insufficient data, domain shifts across datasets, and issues with generalization. This study proposes MetaCovid, a deep adaptation framework that employs meta-learning to address the variability of vital sign manifestation between subjects using only two days of data in order to detect Covid-19 before symptoms manifest. MetaCovid leverages heart rate and step measurements collected from consumer-grade health trackers over the preceding 2 days, extracts 45 digital bio-markers (features), which along with raw data, are fed into a deep GRU-based network with an attention mechanism, followed by uncertainty filtering. MetaCovid is trained using OC-MAML, a one-class few-shot MAML variant that adapts to the target distribution/user using only samples from the majority class. MetaCovid generalized well across two relatively small, publicly available Covid-19 datasets, achieving a recall of 0.81 and 0.92, and detecting 61% (14 out of 23) and 50% (17 out of 34) of users infected with Covid-19 before symptom onset. When OC-MAML was excluded from MetaCovid in an ablation study, the F2 score dropped by 36%, highlighting that meta-learning indeed facilitates adaptation of deep sensing models to varying vital sign patterns. Notably, MetaCovid outperforms the current state-of-art method by predicting Covid-19 early on day N using heart rate and step measurements from only the preceding 2 days compared to 28 days, reducing data requirements by 93%. To the best of our knowledge, our study is the first to propose utilizing meta-learning to mitigate vital sign variability with limited data for Covid-19 screening. We believe that MetaCovid will pave the way for innovative Covid-19 interventions that are accurate even with limited data and help contain the spread of infectious diseases in the future.

Determination of three C18-oxygenated steroids in adrenal lesion segments in primary aldosteronism by super-selective adrenal venous sampling and LC/ESI-MS/MS.

Super-selective adrenal venous sampling (ssAVS) can collect the adrenal tributary venous blood in the aldosterone (ALD)-hypersecreting segments in primary aldosteronism. The concentrations of the C18-oxygenated steroids, especially 18-oxocortisol (18-oxoF), in the lesion segments might be more useful indices than those in the peripheral or adrenal central veins (current candidate indexes) for the differential diagnosis of unilateral ALD-producing adenoma (APA) and bilateral adrenal hyperplasia (BAH). To verify this hypothesis, we developed a liquid chromatography/electrospray ionization-tandem mass spectrometry (LC/ESI-MS/MS) method for simultaneously quantifying ALD, 18-oxoF and 18-hydroxycortisol in the adrenal tributary venous serum sample collected by ssAVS (ssAVS serum) and compared their concentrations between APA and BAH patients. Only deproteinization was required for a 10 μl sample prior to the LC/ESI-MS/MS analysis. Endogenous corticoids did not interfere with the quantifications, and the intra-assay and interassay precisions (≤ 8.3%) and accuracies (94.2-102.7%) were acceptable. The clinical study revealed that the 18-oxoF concentration was significantly higher in the ALD-producing tumor tissues (from APA patients) than in the hyperplastic tissues (from BAH patients). However, in conclusion, the 18-oxoF concentration in the ssAVS serum sample can be a rough indication but cannot be decisive for the differential diagnosis between APA and BAH owing to the significant individual difference.

Dynamic Threshold Distribution Domain Adaptation Network: A Cross-Subject Fatigue Recognition Method Based on EEG Signals

Electroencephalogram (EEG) has been widely used in driver fatigue recognition due to its high-resolution and non-invasive characteristics in recent years. However, EEG signals have strong variability and significant individual differences, which put forward extremely high requirements on the generalization ability of the model in practical use. To address these issues, a dynamic threshold distribution domain adaptation network (DTDDAN) is proposed to classify the EEG signals for driver fatigue recognition. In the model, the domain discriminator is introduced to alleviate the marginal distribution difference of different domains, and a new loss, Jensen–Shannon loss (JS loss), is applied to relieve the conditional distribution difference of different domains to learn cross-subject invariant deep features of EEG signals. In addition, we propose a dynamic threshold pseudo label strategy to assign pseudo labels to the samples of the target domain in the training process of the model. This strategy can make sure that the high-quality unlabeled data of the target domain contribute to the model training and the model can fully learn the information of the target domain. With extensive experiments on our self-constructed EEG-based fatigue driving dataset, competitive performance is achieved for the cross-subject classification task, with average classification sensitivity, specificity, and accuracy of 89.8%,93.8% and 92.2%, respectively. And it is shown that our model can effectively extract cross-subject invariant EEG signals deep features by the experimental results.

Clinical description of dengue and chikungunya virus infections amongst acute febrile patients in a malaria endemic area of Mfou, the Centre region of Cameroon

This study aims to determine the frequency and clinical manifestations of dengue and chikungunya viral infections in the district hospital of Mfou, Centre region of Cameroon where malaria is endemic. Blood samples were collected from suspected cases and tested for Plasmodium parasites and for the molecular detection of viral RNAs (dengue, zika and chikungunya viruses) using TRIOPLEX qPCR. A total of 108 patients were clinically suspected among which 25 % were male and 50 % were less than 15.5 years old. Of these 14.8 % (16/108) and 2.8 % (3/108) had acute dengue and chikungunya fevers respectively. Co-infection with malaria was reported in 56.3 % (9/16) of Dengue cases and 33.3 % (1/3) of chikungunya cases. Clinical profiling further revealed that nausea and vomiting show a significant difference in dengue infected individuals to those of non-infected individuals (P = 0.027). The presence of dengue fever and chikungunya fever and the absence of specific clinical manifestations highlight the need to strengthen surveillance of acute febrile infections for a better estimation of the burden of arboviruses.

Exploring Structure Incentive Domain Adversarial Learning for Generalizable Sleep Stage Classification

Sleep stage classification is crucial for sleep state monitoring and health interventions. In accordance with the standards prescribed by the American Academy of Sleep Medicine, a sleep episode follows a specific structure comprising five distinctive sleep stages that collectively form a sleep cycle. Typically, this cycle repeats about five times, providing an insightful portrayal of the subject’s physiological attributes. The progress of deep learning and advanced domain generalization methods allows automatic and even adaptive sleep stage classification. However, applying models trained with visible subject data to invisible subject data remains challenging due to significant individual differences among subjects. Motivated by the periodic category-complete structure of sleep stage classification, we propose a Structure Incentive Domain Adversarial learning (SIDA) method that combines the sleep stage classification method with domain generalization to enable cross-subject sleep stage classification. SIDA includes individual domain discriminators for each sleep stage category to decouple subject dependence differences among different categories and fine-grained learning of domain-invariant features. Furthermore, SIDA directly connects the label classifier and domain discriminators to promote the training process. Experiments on three benchmark sleep stage classification datasets demonstrate that the proposed SIDA method outperforms other state-of-the-art sleep stage classification and domain generalization methods and achieves the best cross-subject sleep stage classification results.

Radiologic Examination of High Riding Vertebral Artery and Analysis of Secure Areas

ObjectiveTo radiologically examine the pedicle, lamina, and vertebral artery foraminal anatomies at the C2 vertebra for pedicular and laminar screw instrumentation at the axis in a Turkish population. Materials and MethodsFrom 2018 to 2019, we evaluated 100 patients who underwent cervical computed tomography (CT) for various reasons (excluding cervical pathologies) at Marmara University Hospital. The C2 pedicles were measured on CT images using measurement tools. In addition, axial computed tomography was performed at 0.1-mm intervals. Bilateral measurements were performed for each case. ResultsThe median right and left pedicle axial diameters were respectively 5.01 and 5.09 mm for the male patients and 4.31 and 4.38 mm for the female patients, showing a statistically significant difference between the sexes (p < 0.01). Of the patients, 15% had narrow pedicles. The pedicle sagittal diameters were smaller than 5 mm in 30% of the computed tomographic series. The internal height was <2 mm in 4% of the cases. ConclusionOur findings suggest significant individual and sex-related differences. Vertebral artery groove anomalies are commonly observed. Before performing a posterior craniocervical instrumentation surgery, a CT examination is beneficial because high-riding vertebral arteries must be kept in mind in determining the appropriate screw diameter and screw trajectory.

Association of Valproic Acid and Its Main Metabolites' Plasma Concentrations with Clinical Outcomes among Epilepsy Patients: A 10-Year Retrospective Study Based on Therapeutic Drug Monitoring.

Valproic acid (VPA) is a first-line antiepileptic drug with broad efficacy. Due to significant individual differences in its metabolism, therapeutic drug monitoring is commonly used. However, the recommended therapeutic range (50-100 μg/mL) is inadequate for predicting clinical outcomes. Additionally, the relationship between VPA metabolites and clinical outcomes remains unclear. In this retrospective study, 485 Chinese Southern Han epilepsy patients receiving VPA monotherapy were analyzed after reaching steady-state levels. Plasma concentrations of VPA and its five main metabolites were determined by liquid chromatography-mass spectrometry (LC-MS). We assessed the relevance of the recommended therapeutic VPA range for clinical outcomes and explored the association between VPA/metabolites levels and treatment efficacy/adverse effects. Vitro experiments were conducted to assess 4-ene-VPA hepatotoxicity. The therapeutic range of VPA exhibited no significant correlation with clinical outcomes, and plasma concentrations of VPA failed to serve as predictive indicators for treatment response/adverse effects. Treatment responders had higher 2-PGA concentrations (median, 26.39 ng/mL versus 13.68 ng/mL), with a threshold of 36.5 ng/mL for optimal epilepsy treatment. Patients with abnormal liver function had a higher 4-ene-VPA median concentration (6.41 μg/mL versus 4.83 μg/mL), and the ratio of 4-ene-VPA to VPA better predicted VPA-induced hepatotoxicity (area under the curve, 0.718) than 4-ene-VPA concentration. Vitro experiments revealed that 4-ene-VPA was more hepatotoxic than VPA in HepaRG and L02 cell lines. Total plasma VPA concentration does not serve as a predictor of clinical outcomes. 2-PGA concentrations may be associated with efficacy, whereas the ratio of 4-ene-VPA to VPA may be considered a better biomarker (threshold 10.03%) for VPA-induced hepatotoxicity. SIGNIFICANCE STATEMENT: This was the first and largest observational cohort in China to explore the relationship between patients' parent and metabolites concentrations of VPA and clinical outcomes during the maintenance of VPA monotherapy in epileptic patients. This study provided feasible references of VPA for epilepsy clinical treatment with a larger sample of patients compared with previous studies for a more definitive conclusion based on real-world situations. We found two potential biomarkers in predicting efficacy and liver injury, respectively. This breakthrough has the potential to assist in the rational use of VPA.

An Atrial Fibrillation Detection Strategy in Dynamic ECGs With Significant Individual Differences

An Atrial Fibrillation Detection Strategy in Dynamic ECGs With Significant Individual Differences

Behavioral Responses to Touch and Leading in Lippizan Mares: Natural vs. Traditional Handling Method

Background: Proper handling and a well-established human-animal relationship influence both the behavior and the welfare of an animal. Methods: In this study, we compared the behavioral responses to touch and leading in mares using two handling methods. A traditional method (T) was based on forced cooperation and a natural (TTEAM) on tactile stimulation and mares’ natural behavior. Twenty-two group housed Lipizzan mares participated. Throughout four consecutive weeks, there were six observational days per method and based on a predefined ethogram, mares were scored daily on a 6-point scale. Higher scores indicated better reception of touch and leading, relaxation and cooperation, whereas lower scores indicated agonistic and/or fear-related behaviors. The time spent to implement touch and leading was also recorded. Result: Despite significant individual differences, touch and leading scores were found to be higher in the TTEAM compared to the T. Our results imply that mares were more relaxed, displayed better cooperation and had reduced agonistic and fear-related behavior during TTEAM. We suggest that implementation of TTEAM positively affected mares’ reception of touch and leading, but due to variation in behavioral plasticity, the importance of mare’s individuality is accentuated.