Comprehensive Test Research Articles

A Programme of Hepatitis C Surveillance With Active Linkage to Care (HEAL) for Inpatients in Two Tertiary Hospitals in Jiangsu, China.

Hepatitis C virus (HCV) infection is a major public health burden in China, affecting more than 10 million individuals. We aimed to evaluate the effectiveness of a hospital-based intervention programme for HCV Surveillance with linkage to care (HEAL) in a prospective cohort. The HEAL programme was carried out targeting inpatients from non-infectious departments of two tertiary hospitals in Jiangsu, China. It consisted of an educational campaign to raise awareness of physicians from non-IDs to promote HCV surveillance, a patient-navigator-centred clinical algorithm responsible for the efficient follow-up of patients with positive HCV antibody, including comprehensive testing, diagnosis and treatment. We characterised the rate of linkage to HCV diagnosis, care and treatment during the pre-intervention period (from 1 July 2016 and June 30, 2018) and after the intervention (from March 2019 to May 2021). During the pre-intervention period, 89,303 (45.3%) out of 196,780 non-ID inpatients were screened for anti-HCV, and 631 patients were tested positive. One hundred and fifty-six (24.7%) patients was followed up for HCV RNA confirmatory testing, and 58 (37.1%) of patients further were diagnosed with chronic HCV infection (CHC). Only 18 (31.3%) of the diagnosed patients with CHC were linked to hepatitis C clinics for treatment, 10 (55.6%) patients received antiviral regimen. Among them, two (11.1%) received DAA treatment, while eight (44.4%) adopted peginterferon/ribavirin regimen. During the intervention period, 232,275 patients were hospitalised in non-infectious department and 151,203 (65.1%) were screened for anti-HCV. Of these, 960 patients tested positive for HCV antibodies, resulting in a prevalence of anti-HCV positivity of 0.63%. Six hundred and seventy (69.8%) patients were enrolled, and 100% were followed up for HCV RNA confirmatory testing. Two hundred and ninety-one (43.4%) individuals with active HCV were identified. Two hundred and thirty-eight (81.8%) of HCV-infected individuals were linked to HCV care, and 157 (65.9%) were linked to treatment. Compared to the pre-intervention period, there was a 2.61-fold increase in the percentage of patients linked to care and a 5.94-fold increase in the proportion of patients who started DAAs therapy. This HEAL programme achieved enhanced HCV Surveillance with linkage to care, which has been demonstrated as an effective strategy in the hospital setting to improve the hepatitis C care continuum by identifying inpatients unaware of their HCV status and facilitating their access to HCV treatment.

Congruences of factor solutions of quantitative indicators for understanding the written form of deaf children's communication through the use of words types

In deaf students, there is no contextual understanding and recognition of word types through linguistic competence testing compared to the hearing population, because 67.10% do not understand, and 10.00% of deaf respondents partially understand the contextual application of word types in a written text task. In written communication, deaf students use nouns (65.70%), pronouns (34.30%), verbs (45.7%), adjectives (28.60%), adverbs (22.90%), prepositions (54.30%), exclamations (15.70%), particles (12.90%) and numbers (32.90%). The aim of the study was to examine the factor solutions of quantitative indicators of contextual understanding of the word’s types used and the relation of isolated factors of the words types words in the written text task of deaf students. The study was conducted on a sample of 140 respondents. The first subsample of respondents, the experimental group consisted of 70 deaf students, and the second subsample, the control group of 70 hearing students, of the same chronological age and gender. The measurement instrument “Test of comprehension of the written form of expression” was applied. The collected data were processed using the method of oblique rotation and the method of factor analysis. The results of the study showed that the language discourse of the deaf in the quantitative use of word types in the written form of expression is organized significantly differently compared to the hearing population. By factor analysis, three main factors were isolated in the deaf population, and four main factors were isolated in the hearing population. Considering the saturation of variability, it is possible to accurately determine in practice the direction of teaching deaf children the types of words in their native language. Isolated factors are part of separate, statistically unrelated entities in both deaf and hearing respondents and confirm the justification of successive teaching of the deaf respondents according to the types of words that are present in the comparative analysis of hearing respondents.

Instance Space Analysis of Testing of Autonomous Vehicles in Critical Scenarios

Before being deployed on roads, Autonomous Vehicles (AVs) must undergo comprehensive testing. Safety-critical situations, however, are infrequent in usual driving conditions, so simulated scenarios are used to create them. A test scenario comprises static and dynamic features related to the AV and the test environment; the representation of these features is complex and makes testing a heavy process. A test scenario is effective if it identifies incorrect behaviors of the AV. In this article, we present a technique for identifying key features of test scenarios associated with their effectiveness using Instance Space Analysis (ISA). ISA generates a ( \(2D\) ) representation of test scenarios and their features. This visualization helps to identify combinations of features that make a test scenario effective. We present a graphical representation of each feature that helps identify how well each testing technique explores the search space. While identifying key features is a primary goal, this study specifically seeks to determine the critical features that differentiate the performance of algorithms. Finally, we present metrics to assess the robustness of testing algorithms and the scenarios generated. Collecting essential features in combination with their values associated with effectiveness can be used for selection and prioritization of effective test cases.

The effect of augmented reality storybooks on the story comprehension and retelling of preschool children.

This study aimed to compare the retelling and story comprehension performance of two groups of preschool children-an experimental and a control group-who experienced printed and augmented reality storybooks. The participant group consisted of 90 participants, with 45 in the experimental group (22 girls, 23 boys) and 45 in the control group (21 girls, 24 boys). The average age of the children was 54.2 months. In the study, the researcher evaluated children's story-retelling performance using the rubric and used a Story Comprehension Test to measure their story comprehension performance. The researchers utilized the ROAR application to incorporate augmented reality content into the books. In the pre-test phase, the teachers read the designated texts to the children in the experimental and control groups. After the eight-week break, the control group experienced the same texts with printed books, while the experimental group experienced them with augmented reality support. Each child participated individually in the reading process with the teacher. In the study, teachers asked the children to retell the story and asked the questions from the Story Comprehension Test at the end of each book reading section for pre-test and post-test measurements. The pre-test results revealed no significant difference in the two groups' story-retelling and Story Comprehension Test scores. The post-test results indicated a significant difference in the story-retelling performance and Story Comprehension Test scores between the experimental and control groups, favoring the experimental group. Based on these findings, the augmented reality content can potentially enhance children's retelling and story comprehension performances.

High-dimensional Biomarker Identification for Scalable and Interpretable Disease Prediction via Machine Learning Models.

Omics data generated from high-throughput technologies and clinical features jointly impact many complex human diseases. Identifying key biomarkers and clinical risk factors is essential for understanding disease mechanisms and advancing early disease diagnosis and precision medicine. However, the high-dimensionality and intricate associations between disease outcomes and omics profiles present significant analytical challenges. To address these, we propose an ensemble data-driven biomarker identification tool, Hybrid Feature Screening (HFS), to construct a candidate feature set for downstream advanced machine learning models. The pre-screened candidate features from HFS are further refined using a computationally efficient permutation-based feature importance test, forming the comprehensive High-dimensional Feature Importance Test (HiFIT) framework. Through extensive numerical simulations and real-world applications, we demonstrate HiFIT's superior performance in both outcome prediction and feature importance identification. An R package implementing HiFIT is available on GitHub ( https://github.com/BZou-lab/HiFIT ).

Breaking a dogma: orthodontic tooth movement alters systemic immunity

BackgroundThe prevailing paradigm posits orthodontic tooth movement (OTM) as primarily a localized inflammatory process. In this study, we endeavor to elucidate the potential ramifications of mechanical force on systemic immunity, employing a time-dependent approach.Materials and methodsA previously described mouse orthodontic model was used. Ni-Ti. springs were set to move the upper 1st-molar in C57BL/6 mice and the amount of OTM was. measured by µCT. Mice were allocated randomly into four experimental groups, each. corresponding to clinical phases of OTM, relative to force application. Terminal blood. samples were collected and a comprehensive blood count test for 7 cell types as well as. proteome profiling of 111 pivotal cytokines and chemokines were conducted. Two controls. groups were included: one comprised non-treated mice and the other mice with inactivated springs.ResultsSerum immuno-profiling unveiled alterations in cellular immunity, manifesting as. changes in percentages of leukocytes, monocytes, macrophages, neutrophils, and. lymphocytes, alongside key signaling factors in comparison to both control groups. The systemic cellular and molecular alterations triggered by OTM mirrored the dynamics previously described in the local immune response.ConclusionsAlthough the exact interplay between local and systemic immune responses to orthodontic forces require further elucidation, our findings demonstrate a tangible link between the two. Future investigations should aim to correlate these results with human subjects, and strive to delve deeper into the specific mechanisms by which mechanical force modulates the systemic immune response.

A Case of the Uncommon Cause of Chronic Coronary Syndrome: Coronary Fistula and Coronary Stenosis, Which One to Intervene?

AbstractWe report a case of chronic coronary syndrome (CCS) that had two completely distinct mechanisms in one patient. We applied comprehensive diagnostic tools using noninvasive and invasive physiology and imaging tests before, during, and after the intervention procedure to evaluate the outcome. The patient had previously visited many physicians and was diagnosed with noncardiac chest pain. He was referred to our department due to the increased frequency and intensity of angina pectoris. After a careful diagnosis, we found a nonsignificant stenosis (50%) in the mid-left anterior descending (mid-LAD) artery and an unexpectedly high-flow coronary artery fistula from the LAD to the main pulmonary artery (MPA). We tried a combination therapy with escalation of the anti-ischemic therapy but failed. He was rehospitalized with unstable angina pectoris. After a comprehensive physiology and imaging test, our team decided to perform fistula embolization with detachable coils and defer stenting in the mid-LAD artery. After the intervention procedure, his angina subsided, and his exercise capacity was remarkably improved. Cardiac computed tomography angiography (CCTA) and cardiac magnetic resonance (CMR) evaluation in 3 months revealed all coils in situ and improved cardiac function. We postulate that comprehensive diagnostic tools are required to select appropriate management and prevent unnecessary procedures.

Evaluation of the water weakening coefficient of sandstones by using non-destructive physical parameters

IntroductionThe presence of water significantly reduces the mechanical strength of rocks and induces various engineering geological hazards. The water weakening coefficient Kp is used to quantify this effect, defined as the ratio of wet uniaxial compressive strength to the dry value.MethodsA comprehensive physico-mechanical test was conducted on fifteen sandstones under dry and saturated conditions to predict the water weakening coefficient using easily obtainable physical parameters. Multiple linear regression was employed to establish the relationship between these parameters and the saturated water weakening coefficient.ResultsThe saturated water weakening coefficient decreases with increasing porosity and increases with higher Primary wave velocity (P-wave velocity). Rocks with higher porosity but lower P-wave velocity typically absorb more water. The P-wave velocity and clay mineral content were identified as the best predictors of the saturated water weakening coefficient (R2 = 0.82). Unsaturated water weakening coefficients at any water saturation level were well estimated using a previous exponential function.DiscussionThe roles of different clay minerals and P-wave velocity in the water weakening process of rocks are comprehensively discussed. This study enhances the understanding of the water weakening mechanism and provides an improved evaluation model for the water weakening coefficient of sandstones using physical parameters.

Improved YOLOv8n for Lightweight Ship Detection

Automatic ship detection is a crucial task within the domain of maritime transportation management. With the progressive success of convolutional neural networks (CNNs), a number of advanced CNN models have been presented in order to detect ships. Although these detection models have achieved marked performance, several undesired results may occur under complex maritime conditions, such as missed detections, false positives, and low detection accuracy. Moreover, the existing detection models endure large number of parameters and heavy computation cost. To deal with these problems, we suggest a lightweight ship model of detection called DSSM–LightNet based upon the improved YOLOv8n. First, we introduce a lightweight Dual Convolutional (DualConv) into the model to lower both the number of parameters and the computational complexity. The principle is that DualConv combines two types of convolution kernels, 3x3 and 1x1, and utilizes group convolution techniques to effectively reduce computational costs while processing the same input feature map channels. Second, we propose a Slim-neck structure in the neck network, which introduces GSConv and VoVGSCSP modules to construct an efficient feature-fusion layer. This fusion strategy helps the model better capture the features of targets of different sizes. Meanwhile, a spatially enhanced attention module (SEAM) is leveraged to integrate with a Feature Pyramid Network (FPN) and the Slim-neck to achieve simple yet effective feature extraction, minimizing information loss during feature fusion. CIoU may not accurately reflect the relative positional relationship between bounding boxes in some complex scenarios. In contrast, MPDIoU can provide more accurate positional information in bounding-box regression by directly minimizing point distance and considering comprehensive loss. Therefore, we utilize the minimum point distance IoU (MPDIoU) rather than the Complete Intersection over Union (CIoU) Loss to further enhance the detection precision of the suggested model. Comprehensive tests carried out on the publicly accessible SeaShips dataset have demonstrated that our model greatly exceeds other algorithms in relation to their detection accuracy and efficiency, while reserving its lightweight nature.

6370 New-Onset Autoimmune Diabetes Following COVID-19 Infection and its Implications for Identical Twin Siblings

Abstract Disclosure: G. Wintermyer: None. S. Gillis-Funderburk: None. COVID-19 patients face many post-recovery complications,including autoimmune disorders. Late autoimmune diabetes ofadults (LADA) is one such disorder. Studies suggest that SARS-CoV may trigger proinflammatory cytokines that damage beta cellsand impair insulin secretion. Here, we explore a case of new-onsetLADA in a patient after recovery from COVID-19. Further, asidentical twins of LADA patients have a higher risk of developingit, we discuss how we approached the patient’s identical twin.A 29-year-old female with history of obesity (BMI 32.3) presentedto our endocrinology clinic. She complained of difficulty losingweight and fatigue and reported having COVID-19 three monthsearlier. She also mentioned having polyuria. She underwent labtests, including CBC, CMP, TSH, A1C, and a lipid panel. The testresults were within normal limits, except for her A1C of 11.3%.She was started on metformin and weekly Semaglutide injections.Given her recent COVID-19 history, she was assessed for LADA.Anti-GAD-65 and ZNT8 antibodies were 120 U/mL and 150U/mL, respectively. Serum C-peptide and IA-antibodies werewithin normal ranges. The patient informed us of her twin sister’sconcurrent COVID-19 infection. Due to the risk of LADA in hertwin sister, we recommended an evaluation by our clinic. Duringthe sister’s first visit, her BMI was 37.5, and she asked for weightloss medication. Comprehensive testing, including LADAantibodies, was conducted, with results within normal ranges andA1C level of 4.9%. The sister was also started on Semaglutide forweight management.The patient had quarterly follow-up appointments at the clinic.After a year, her A1C and continuous glucose monitoring machine(CGM) readings showed improvement. Her BMI decreased to 24.She never required insulin therapy, as her diabetes was well-managed and her average monthly glucose level on GCM readings were 125, 123 and 119 mg/dL in three different periods. Antibodieswere retested. This time IA-2 antibody was also elevated.Similarly, her twin sister continued to follow-up at our clinic. Thesister achieved significant weight loss without complications. HerLADA antibodies remained negative, and her A1C remainednormal. Clinicians should be vigilant for post-COVID LADA. In this case,Semaglutide aided weight loss, which benefits diabetesmanagement. Ongoing studies explore the potential of GLP-1medications in early-stage LADA. Historically, LADA patientswere started on insulin. However, CGM has enabled close glucosemonitoring, offering management of LADA with non-insulinmedications. It is also important to remember that autoimmunedisease risk is elevated in identical twins. In this case, although thetwin sister did not develop antibodies, the risk remains. Regularevaluation of high-risk patients is crucial for early detection ofantibodies, facilitating timely treatment to prevent adverseoutcomes. Presentation: 6/3/2024

Metalinguistic explanations and their impact on incidental grammar acquisition: An eye-movement study

Recent research highlights the value of metalinguistic explanations in facilitating second language (L2) grammar acquisition. Nevertheless, a notable research gap persists regarding how these explanations influence incidental grammar acquisition and their impact on overall reading processes and comprehension. Furthermore, whether the potentially positive effects of metalinguistic explanations transfer to the acquisition of subsequent constructions without explicit guidance is an unexplored domain. This study addresses these research gaps by recruiting 42 Korean undergraduate students and assigning them to the metalinguistic or baseline groups. The metalinguistic group read an English text supplemented with bottom-margin metalinguistic explanations, which elucidated the first half of the target grammar (without explanations for the second half), whereas the baseline group read the same text without explanations. This study used eye-tracking technology to register participants’ eye movements during reading, followed by an announced reading comprehension test and an unannounced error correction test. Statistical analyses using linear mixed-effects models (LMMs) and t-tests revealed that metalinguistic explanations significantly enhanced incidental grammar acquisition in L2 learners without compromising overall reading processes and comprehension. However, the benefits of metalinguistic explanations in the metalinguistic group failed to extend to the incidental learning of other unexplained constructions.

Synchronized magnet-induced displacement detection in non-magnetic plates via smart materials near-field sensing

Accurate monitoring of small displacements in non-magnetic thin-walled plates is essential for assessing their manufacturing precision and vibrational characteristics. Optical techniques are limited by environmental disturbances and spatial constraints, while contact methods are compromised by mechanical forces and wear. A synchronized magnet-induced displacement detection method (SMDDM) using heteropolar permanent magnets (HPMs) and smart materials for non-magnetic plates is proposed. Supported by a magnetic-mechanical–electrical coupling model and a joint algorithm with dynamic linear extension and analytic hierarchy process (DLE-AHP), the prototype’s parameters are refined through experimental design, neural networks, and multi-objective optimization. Comprehensive tests show that SMDDM achieves an accuracy of 2 μm and a resolution of 1 μm, with smaller measurement errors observed in low-frequency, small-displacement tests. This validates the method’s effectiveness in multi-scale displacement measurement and vibration testing, highlighting its potential for in-situ monitoring in thin-plate applications.

Emphasizing the need for preconceptional, prenatal genetic counseling and comprehensive genetic testing in consanguinity: challenges and experience.

Preconception and prenatal genetic counseling is a well-established means of risk assessment in many parts of the world, and in recent years, an emerging concept in India. Likelihood of an offspring having autosomal recessive disorder increases based on the degree of consanguinity. Hence, genetic testing of the couple for the identification of carrier status for disease-causing variants is crucial. The purpose of this study is to understand the frequency of genetic abnormalities in consanguineous marriages by using a comprehensive genetic testing algorithm where in karyotyping, FISH, exome sequencing and microarray are used sequentially to determine the genetic etiology based on the clinical presentation and to evaluate the need and benefits of preconceptional and prenatal genetic counseling. This retrospective study includes 66 couples having consanguinity referred for genetic counseling and testing. Of the 66 couples, 58 underwent comprehensive genetic testing which included Karyotyping, Fluorescence in Situ Hybridization (FISH), Microarray and Exome sequencing based on their clinical presentation. The analyses revealed a genetic abnormality in approximately 31% and chromosomal polymorphic variations & variants of uncertain significance in 17% of the couples. Counseling in these couples helped in identifying the carrier status and enabled them to take an informed decision in subsequent pregnancies. These findings reiterate the acute need for preconception and prenatal genetic counseling services in India.

The effect of speech and non-speech noise on comprehension of storybook reading for elementary school children

Children are generally more affected by surrounding noise than are adults, and are more disturbed by speech than by non-speech noise. Storybook reading, which is one of the main activities in school curricula, is known to improve children's language skills, social abilities, and behavior. However, classrooms are generally noisy environments, and the effectiveness of storybook reading in noise is unclear. This study aimed to investigate how noise affects storybook reading comprehension among elementary schoolchildren. A practiced speaker read picture books to 11 elementary school schoolchildren (age range, 6-9 years) under three listening conditions: quiet, speech noise (babble noise), and non-speech noise (noise recorded in a boiler room). A comprehension test (e.g., story flow, character behaviors, keywords) was conducted after each book was read. No significant difference in story comprehension scores was found among the listening conditions, likely because the visual information helped the children understand the stories even in noise. However, the story comprehension score under the speech noise condition was significantly higher for children who frequently played outside as compared with inside. These results suggest that children's comprehension of storybook reading in noise is affected by not only surrounding noise, but also the play area.

Optimization of Ultra-High Performance Concrete Based on Response Surface Methodology and NSGA-II.

This study systematically investigated three influential factors-water-to-binder ratio, cement/sand ratio, and steel fiber content-that significantly impact the performance of ultra-high-performance concrete (UHPC). Utilizing the Response Surface Methodology (RSM) with a Central Composite Design (CCD), 20 carefully designed mix proportions underwent comprehensive experimental testing. Through rigorous statistical analysis, models were established to elucidate the complex relationships between the specified factors and the overall properties of UHPC. Variance analysis reveals significant effects of the three factors on UHPC performance, with workability and compressive strength increasing with higher cement/sand ratios while flexural strength decreases. Moreover, increased water-to-binder ratios exhibit substantial negative impacts on both 28-day compressive and flexural strengths. Despite adversely affecting workability, higher steel fiber dosages contribute positively to mechanical performance. Furthermore, Monte Carlo sampling and the multi-objective non-dominated sorting genetic algorithm-II (NSGA-II) were employed to validate the reliability of the statistical model and to conduct multi-objective optimization. The final UHPC mix design obtained consists of a cement/sand ratio of 1.12, a water/binder ratio of 0.16, and a steel fiber content of 2.94%. Experimental results yielded a slump flow of 802 mm, compressive strength of 122.7 MPa, and flexural strength of 24.3 MPa.

Dynamic Testing and Fatigue Analysis of the I-31P Nose Landing Gear

Abstract The landing gear is a critical safety component of any aircraft, playing a key role in managing the significant loads experienced during landing and ground maneuvers. In the case of the I-31P aircraft, a redesign of the I-23 landing gear system, required comprehensive testing to validate its performance, after change of landing gear parts manufacturer and minor updates to materials and technologies. This study focuses on the dynamic testing of the I-31P nose landing gear (NLG), particularly to assess its energy dissipation and fatigue resistance under operational conditions. Dynamic tests, performed in accordance with CS-23 standards, utilized strain gauges to monitor potential stress concentrations, especially on the half-fork design. Results demonstrated that the I-31P nose landing gear meets the required safety standards, with key performance metrics such as deflection and load factors within acceptable limits. The findings also highlighted the importance of continued monitoring for potential fatigue issues, offering valuable insights for future design enhancements.

A category incremental continuous learning model for imbalance arrhythmia detection

Abstract The development of efficient arrhythmia detection systems is crucial for physiological measurements and computer-aided diagnosis. Existing systems rely mainly on offline learning methods and lack the ability to assimilate new data or recognize emerging categories. To address these challenges, this study introduces an arrhythmia detection model that is resistant to data imbalance and has continuous learning capabilities, specifically for incremental learning of new ECG data categories. The system incorporates constraints derived from the new class data and implements a dynamic mechanism for updating connection weights, facilitating the incremental continual learning of classes. Confronted with the problem of models forgetting the original data and overfitting with the added data in continuous learning, we introduce a data balancing method by regularization to balance the model's memory and learning of the two types of data. Facing the data imbalance problem in continuous learning, we introduce a posteriori probability weighting strategy. This strategy assigns greater importance to high-value samples based on the model's posterior residual kernel density estimates. Comprehensive testing of the model using various datasets from the MIT-BIH database indicates superior performance in incremental learning tasks. The results reveal that the model not only excels in class incremental learning but also ensures effective balancing across different data classes.

Investigating the relationship between cognitive impairment and brain white matter tracts using diffusion tensor imaging in patients with prolactinoma.

Cognitive impairment is known to occur in patients with prolactinoma, but the underlying mechanism is unclear. To evaluate cognitive function in patients with prolactinoma and to investigate the basis of possible cognitive impairment in brain white matter changes using diffusion tensor imaging (DTI). 37 consecutive patients with prolactinoma and 37 healthy controls of similar age, sex, and education were enrolled in the study. Hormone levels were determined in all participants, comprehensive neuropsychological testing was performed, and DTI was used to reconstruct and evaluate white matter tracts. In patients with prolactinoma, short- and long-term visual and verbal memory, attention, concentration, and executive and language functions were impaired compared to the healthy group. When comparing the DTI results, lower fractional anisotropy (FA) values were found in the patients' right uncinate fasciculus (R-UF), indicating neuronal damage. After applying the Bonferroni correction, the two groups had no significant difference in 42 tracts (p > 0.0012 for all). A positive correlation was found between poor FA scores on the R-UF and low scores on long-term memory, category and letter fluency tests. In addition, patients with hypoprolactinemia had the worst short-term memory scores, while normoprolactinemia had the best scores. Also, the poorer R-UF FA values were found in the patients with hypoprolactinemia and the highest in those with normoprolactinemia. This study is the first to investigate reasons for cognitive dysfunction in patients with prolactinoma by DTI. No significant structural changes were found in brain tracts of patients with prolactinoma. Still, there may be a link between potential damage in the R-UF and cognitive dysfunction, and further research is needed. In addition, the results showed that the development of hypoprolactinemia is associated with cognitive dysfunction and emphasized that overtreatment should be avoided.

Cisplatin vestibulotoxicity: a current review.

Cisplatin, a commonly used chemotherapy drug, is well-established for its ototoxic effects, primarily attributed to the damage it inflicts on cochlear hair cells. However, its impact on the vestibular system remains inadequately understood. Here, we provide a comprehensive review of existing literature concerning cisplatin-induced vestibulotoxicity. Animal studies have shown that cisplatin induces a vestibular hair cell loss that is dose-dependent, with the severity of damage also varying according to the route of administration. Notably, intratympanic and systemic injections in animal models have manifested significant damage primarily to utricular hair cells, with a lesser degree of damage observed for the other vestibular end organs. The underlying mechanisms of cisplatin induced vestibular hair cell loss include apoptosis, oxidative stress, and inflammatory cytokines. Several protective agents, such as Pifithrin-α, DAPT, Ginkgolide B, and heat shock proteins, have demonstrated efficacy in inhibiting cisplatin-induced vestibular damage in preclinical studies. Human clinical findings indicate that cisplatin treatment can cause vestibular dysfunction, characterized by symptoms ranging from transient dizziness to persistent vertigo. Challenges in diagnosis, including the limited utilization of comprehensive vestibular testing for many patients, contribute to the variability in reported outcomes. Cisplatin-induced vestibulotoxicity is a significant complication of chemotherapy, necessitating further research to understand its mechanisms and to improve diagnosis and management, ultimately aiming to enhance the quality of life for cancer patients undergoing cisplatin therapy.

B-099 Validation and Clinical Implementation of Organ Procurement Serology Testing: Our Analytical and Regulatory Experience in Implementing a New Donor Testing Program

Abstract Background The Mount Sinai Hospital recently implemented a comprehensive organ donor testing program to service the clinical needs of transplant services in the New York City metro area. Conventional serology testing is not approved by the FDA for donor testing. To support this program, the MSH Chemistry Laboratory implemented and validated a comprehensive donor testing panel on the Abbott Alinity S donor testing platform. We validated donor serology testing for the following assays: HIV-1/2 (HIV), Anti-Hepatitis B Core (Anti-HBc), Hepatitis B Surface Antigen (HBsAg), Human T-lymphotropic virus I and II (HTLV-I/II), Anti-Hepatitis C (Anti-HCV), and Trypanosoma cruzi antibodies (T.Cruzi). The Alinity S System is an automated immunoassay-based analyzer FDA-approved for donor testing. The analyzer consists of two distinct sample ‘paths’ and is effectively two instruments combined in one analyzer. The analyzer is approved for use in living donor serum and plasma and in cadaveric serum. Prior to going live, we found that there was limited guidance on laboratory quality assurance programs related to donor testing. In addition to confirming assay analytical performance, we designed and implemented a comprehensive quality assurance program prior to satisfy compliance with regulatory guidelines, addressing proficiency compliance, sample TAT, and control ranges, amongst other quality indicators. Methods Inter and Intraday precision was assessed through replicate analysis of positive and negative controls, where 10 replicates of both controls were assayed on a single day, and one replicate of each control was assayed daily for 7 distinct days, results were represented as %CV. Result accuracy was assessed through split sample analysis of known serologically positive (n=20) and negative samples (n=40). Each sample was assayed on two distinct lots of reagents, each with its own unique calibration curve. Accuracy was confirmed in both living donor (n=30), and cadaveric samples (n=10). In addition, split sample analysis was performed between the Alinity S and FDA-approved donor testing assays in a reference laboratory (N=7). A carryover study was performed through the analysis of triplicate replicates of low, high, and then low controls. These analyses were performed for all 6 assays. Results Intraday precision using assay general controls afforded the following %CV: HIV: 3.1%, 6.5%; Anti-HBc: 1.3%, 2.6%; Anti-HCV: 3.3%, 11.7%; HTLV-I,II: 2.5%, 5.9%; T.Cruzi: 2.8%, 0%; HBsAg: 3.2%, 11.6%. Interday precision yielded the following in %CV: HIV: 2.9%, 10.0%; Anti-HBc: 3.0%, 5.6%; Anti-HCV: 3.3%, 3.4%; HTLV-I,II: 2.8%, 4.6%; T.Cruzi: 2.4%, 0%; HBsAg: 4.7%, 7.8%. Accuracy studies yielded 100% positive and negative correlation for all 6 assays in both living donor and cadaveric samples. In addition, there was a 100% serological correlation for samples compared to reference laboratories. Carryover studies showed no evidence of sample carryover. Conclusions The Abbott Alinity S shows acceptable assay precision on all 6 validated assays. The assays are serologically accurate in both cadaveric and living donor samples. As such, the assays and platform are acceptable for use in donor screening. We designed a unique quality assurance program including a comprehensive self-proficiency and instrument crosscheck program to ensure analyzer accuracy, as well as adherence to regulatory guidelines.