Validity Of Trials Research Articles

Pengembangan Media Pembelajaran Berbasis Whatsapp dengan Fitur Chatbot untuk Meningkatkan Pemahaman Siswa pada Materi Kebijakan Moneter dan Fiskal Kelas XI SMAS Islam Nurul Amanah

The purpose of this development research is to produce a whatsapp-based learning media product with a chatbot feature to improve students' understanding of monetary and fiscal policy materials. SMAS Islam Nurul Amanah Class XI is the subject of this study. In this study, a type of development research (Development Research) is used. The development model in this study uses the ADDIE development model. This model consists of five main phases or stages, namely Analysis, Design, Development, Implementation, and Evaluation. In this study, quantitative and qualitative methods are used. The results of the study showed that the whatsapp-based learning media with the chatbot feature was considered quite valid based on the results of a questionnaire filled out by material validators with a score of 70%, media validators with a score of 78%, and obtained a very valid assessment from economic learning practitioners with a score of 87%. Based on the results of validation and field trials, whatsapp-based learning media with a chatbot feature that has been developed by researchers is feasible to be used in the learning process in economics lessons, especially in monetary and fiscal policy material for grade XI of SMAS Islam Nurul Amanah.

Endogenous Attention Affects Decision-related Neural Activity but Not Afferent Visual Responses.

Endogenous shifts of spatial attention toward an upcoming stimulus are associated with improvements in behavioral responses to the stimulus, preparatory retinotopic shifts in alpha power, and changes in ERPs. Although attentional modulation of several early sensory ERPs is well established, there is still debate about under what circumstances attention affects the earliest cortical visual evoked response-the C1 ERP component-which is putatively generated from afferent input into primary visual cortex. Moreover, the effects of spatial attention on the recently discovered ERP signature of evidence accumulation-the central parietal positivity (CPP)-have not been fully characterized. The present study assessed the effect of spatial attention on the C1 and CPP components through a spatially cued contrast discrimination task using stimuli that were specifically designed to produce large-amplitude C1 responses and that varied in sensory evidence strength to characterize the CPP. Participants responded according to which of two checkerboard stimuli had greater contrast following an 80% valid cue toward the upper or lower visual field. Prestimulus alpha power changed topographically based on the cue, suggesting participants shifted attention to prepare for the upcoming stimuli. Despite these attentional shifts in alpha power and the fact that the stimuli reliably elicited C1 responses several times greater than many prior studies, there was no evidence of an attention effect on the C1. The CPP, however, showed a clear increase in build-up rate on valid trials. Our findings suggest that endogenous attention may not affect the early C1 ERP component but may improve behavior at a decision stage, as reflected in brain signals related to evidence accumulation (the CPP).

Methodological Approach for the Development of Standard C-UAS Scenarios

The integration of unmanned aircraft systems (UAS), commonly referred to as drones, into various sectors including agriculture, healthcare, and military operations has transformed industries and services. While drones offer numerous benefits, they have also been exploited by terrorists and criminals for illicit activities, such as smuggling and surveillance. Incidents involving drones flying over restricted airspaces or sensitive locations have highlighted the vulnerabilities of critical infrastructure and limitations of current law enforcement capabilities. To address these challenges, there is a growing need for effective counter-UAS (C-UAS) systems including detection, tracking, and identification technologies. However, evaluating the capabilities of these systems poses a significant challenge, leading to the demand for standardized test methodologies. The COURAGEOUS project seeks to fill this gap by developing standardized scenarios covering various use cases, such as airport security, critical infrastructure protection, and border security. These scenarios are informed by a systematic approach involving a literature review, analysis of previous incidents, assessment of current C-UAS frameworks, and gathering feedback from end users. The resulting standardized test methodology aims to enhance the understanding of C-UAS system capabilities, improve preparedness against evolving threats, and facilitate the global dissemination of project results. Through validation trials and feedback from law enforcement agencies, the COURAGEOUS project strives to contribute to a broader network of counter-UAS initiatives, ultimately enhancing the lower airspace security.

Flashcard Development to Improve Learning Outcomes in Private 4th Class Science Learning

This research aims to develop flashcard products equipped with barcodes, test the feasibility of flashcard media in science learning to improve student learning outcomes; and knowing the effectiveness of using flashcard media in increasing average scores. This type of research is Research and Development (R&D) using the Borg & Gall development model which includes eight stages, namely potential and problems, gathering information, product design, design validation, design improvement, product testing, product revision, and usage trials. The subjects of this research were fourth grade students at SDN 01 Bojongkoneng. The research results showed: Flashcard learning media, product validity as seen from the validation results by material expert validators got a percentage of 90%, and media experts got a percentage of 92%; The effectiveness of the product can be seen from the results of student responses which include small group trials getting an average pretest score of 54 and posttest 82, and large group trials getting an average pretest score of 51 and posttest 85. In the small class the score is n- the gain was 0.60 in the medium category, while the large class obtained an n-gain value of 0.68 in the medium category. Thus, the research results show that learning media in the form of flashcards and equipped with barcodes is feasible and effective in learning science and technology as an improvement in student learning outcomes.

Artificial intelligence-assisted delineation for postoperative radiotherapy in patients with lung cancer: a prospective, multi-center, cohort study

BackgroundPostoperative radiotherapy (PORT) is an important treatment for lung cancer patients with poor prognostic features, but accurate delineation of the clinical target volume (CTV) and organs at risk (OARs) is challenging and time-consuming. Recently, deep learning-based artificial intelligent (AI) algorithms have shown promise in automating this process.ObjectiveTo evaluate the clinical utility of a deep learning-based auto-segmentation model for AI-assisted delineating CTV and OARs in patients undergoing PORT, and to compare its accuracy and efficiency with manual delineation by radiation oncology residents from different levels of medical institutions.MethodsWe previously developed an AI auto-segmentation model in 664 patients and validated its contouring performance in 149 patients. In this multi-center, validation trial, we prospectively involved 55 patients and compared the accuracy and efficiency of 3 contouring methods: (i) unmodified AI auto-segmentation, (ii) fully manual delineation by junior radiation oncology residents from different medical centers, and (iii) manual modifications based on AI segmentation model (AI-assisted delineation). The ground truth of CTV and OARs was delineated by 3 senior radiation oncologists. Contouring accuracy was evaluated by Dice similarity coefficient (DSC), Hausdorff distance (HD), and mean distance of agreement (MDA). Inter-observer consistency was assessed by volume and coefficient of variation (CV).ResultsAI-assisted delineation achieved significantly higher accuracy compared to unmodified AI auto-contouring and fully manual delineation by radiation oncologists, with median HD, MDA, and DCS values of 20.03 vs. 21.55 mm, 2.57 vs. 3.06 mm, 0.745 vs. 0.703 (all P<0.05) for CTV, respectively. The results of OARs contours were similar. CV for OARs was reduced by approximately 50%. In addition to better contouring accuracy, the AI-assisted delineation significantly decreased the consuming time and improved the efficiency.ConclusionAI-assisted CTV and OARs delineation for PORT significantly improves the accuracy and efficiency in the real-world setting, compared with pure AI auto-segmentation or fully manual delineation by junior oncologists. AI-assisted approach has promising clinical potential to enhance the quality of radiotherapy planning and further improve treatment outcomes of patients with lung cancer.

Reinforcement Learning to Optimize Ventilator Settings for Patients on Invasive Mechanical Ventilation: Retrospective Study.

One of the significant changes in intensive care medicine over the past 2 decades is the acknowledgment that improper mechanical ventilation settings substantially contribute to pulmonary injury in critically ill patients. Artificial intelligence (AI) solutions can optimize mechanical ventilation settings in intensive care units (ICUs) and improve patient outcomes. Specifically, machine learning algorithms can be trained on large datasets of patient information and mechanical ventilation settings. These algorithms can then predict patient responses to different ventilation strategies and suggest personalized ventilation settings for individual patients. In this study, we aimed to design and evaluate an AI solution that could tailor an optimal ventilator strategy for each critically ill patient who requires mechanical ventilation. We proposed a reinforcement learning-based AI solution using observational data from multiple ICUs in the United States. The primary outcome was hospital mortality. Secondary outcomes were the proportion of optimal oxygen saturation and the proportion of optimal mean arterial blood pressure. We trained our AI agent to recommend low, medium, and high levels of 3 ventilator settings-positive end-expiratory pressure, fraction of inspired oxygen, and ideal body weight-adjusted tidal volume-according to patients' health conditions. We defined a policy as rules guiding ventilator setting changes given specific clinical scenarios. Off-policy evaluation metrics were applied to evaluate the AI policy. We studied 21,595 and 5105 patients' ICU stays from the e-Intensive Care Unit Collaborative Research (eICU) and Medical Information Mart for Intensive Care IV (MIMIC-IV) databases, respectively. Using the learned AI policy, we estimated the hospital mortality rate (eICU 12.1%, SD 3.1%; MIMIC-IV 29.1%, SD 0.9%), the proportion of optimal oxygen saturation (eICU 58.7%, SD 4.7%; MIMIC-IV 49%, SD 1%), and the proportion of optimal mean arterial blood pressure (eICU 31.1%, SD 4.5%; MIMIC-IV 41.2%, SD 1%). Based on multiple quantitative and qualitative evaluation metrics, our proposed AI solution outperformed observed clinical practice. Our study found that customizing ventilation settings for individual patients led to lower estimated hospital mortality rates compared to actual rates. This highlights the potential effectiveness of using reinforcement learning methodology to develop AI models that analyze complex clinical data for optimizing treatment parameters. Additionally, our findings suggest the integration of this model into a clinical decision support system for refining ventilation settings, supporting the need for prospective validation trials.

Exploring Epidermodysplasia Verruciformis: A Case Report, Treatment Strategies, and Emerging Therapies

Abstract Introduction/Objective Epidermodysplasia verruciformis (EV) is a rare cutaneous disorder with both inherited and acquired forms. Inherited cases involve mutations in genes such as ERV1 and ERV2, crucial for HPV immunity, while acquired cases affect immunocompromised individuals. EV is linked to cutaneous squamous cell carcinoma (SCC), highlighting the need for prompt diagnosis and treatment. Methods/Case Report A 54-year-old HIV-positive man was referred with a persistent, itchy eruption on his forearms despite given ARV regimen, oral retinoids and topical therapies. Physical examination revealed hypopigmentation and hyperkeratotic plaques on both forearms. Histologic examination revealed large cells with blue-gray cytoplasm and perinuclear halo in the upper epidermis, consistent with EV. Although advised for papilloma virus vaccination and planned for a trial of topical cidofovir, the patient was lost to follow-up. Treatment strategies for EV vary depending on lesion severity. Severe keratinized or precancerous lesions typically require surgical removal as the first-line approach. For early-stage EV with few small lesions, 5-FU, cidofovir, glycolic acid, and imiquimod is recommended. Tazarotene 0.5% cream used twice weekly has shown success in resolving lesions within 14 days. Topical imiquimod’s efficacy appears variable. In HIV-positive patients with EV, topical 1% cidofovir showed success in some cases. Systemic and topical retinoids are advised for diffuse lesions, with electrocautery or cryotherapy as options if initial treatments fail. HPV vaccination combined with oral acitretin, topical tretinoin and imiquimod led to lesion flattening. Continuous low-dose isotretinoin achieved prolonged remission of EV, but its efficacy in acquired EV remains unclear. Topical methyl aminolevulinate followed by photodynamic therapy has also shown promise. Results (if a Case Study enter NA) NA Conclusion Since its discovery in the 1970s, Acquired EV has been observed across diverse demographics, including HIV patients and organ transplant recipients. Advanced HPV typing and sequencing techniques aid in predicting SCC risk. Emerging treatments like topical cidofovir and combination therapies show promise, necessitating larger clinical trials for validation.

From flames to lab: A robust non-destructive sampling method for evaluating PAH exposure in firefighters’ personal protection equipment

Polycyclic aromatic hydrocarbons (PAHs) are compounds with high carcinogenic potential, produced during incomplete combustion. Certain professions, such as firefighting, expose workers to significant levels of PAHs during their operations, making it essential to investigate sampling protocols to evaluate their exposure in the work environment.This study presents a non-destructive and cost-effective sampling method for monitoring PAHs in firefighters’ personal protective equipment (PPE) and intervention vehicles. Sampling was conducted using three isopropanol wipes per collection zone, with comprehensive validation trials ensuring the method’s effectivenes. The method was tested under both natural contamination and spiking scenarios, showing similar results in both protocols.Analysis of contaminated PPE revealed significant PAH contamination in specific zones, such as gloves, lower back sleeves, and knees, due to direct exposure to flames and smoke during firefighting, with the highest concentrations in the outer and moisture layers. The cleaning efficacy of PPE was also evaluated employing specific washing machines, showing substantial reductions in PAH levels of approximately 76%. Additionally, non-targeted analysis detected organophosphate flame retardants (OPFRs) and furans, suggesting broader utility for environmental monitoring. This comprehensive approach improves the accessibility of chemical exposure studies in high-risk professions, contributing to better protective measures and occupational health and safety.

Pengaruh Reward, Punishment dan Motivasi Kerja terhadap Kinerja Karyawan

Recently global era, such an extraordinary competitive power increasingly tight also broad. Human redources are among thise so crucial aspect of company. At successfully achieve the target. The target the following study was for analyzing the effect reward, punishment also working motivation at employee performance on PT Rapi Trans Logistik. The method of collecting samples used purposive sampling with the criteria permanent employee respondents who had work period at least 1 period. By using Roscoe's theory, the sample used was 86 respondents. The questionnaire was applied to obtain data. compiler tool, also SPSS 25 was used as a data testing tool. Data processing acquisition were at the declaration of informant explanations, variable explanations, validity trial acquisition, reliability trial acquisition, F trial acquisition, coefficient test results (R²) and hypothesis trial result. Discussion results show rewards has a positively also significantly impact at worker performance, punishment doesn’t having impact at worker performance, also working motivation has positively also significant impact at worker performance

Triple and quadruple optimization for feature selection in cancer biomarker discovery

The proliferation of omics data has advanced cancer biomarker discovery but often falls short in external validation, mainly due to a narrow focus on prediction accuracy that neglects clinical utility and validation feasibility. We introduce three- and four-objective optimization strategies based on genetic algorithms to identify clinically actionable biomarkers in omics studies, addressing classification tasks aimed at distinguishing hard-to-differentiate cancer subtypes beyond histological analysis alone. Our hypothesis is that by optimizing more than one characteristic of cancer biomarkers, we may identify biomarkers that will enhance their success in external validation. Our objectives are to: (i) assess the biomarker panel’s accuracy using a machine learning (ML) framework; (ii) ensure the biomarkers exhibit significant fold-changes across subtypes, thereby boosting the success rate of PCR or immunohistochemistry validations; (iii) select a concise set of biomarkers to simplify the validation process and reduce clinical costs; and (iv) identify biomarkers crucial for predicting overall survival, which plays a significant role in determining the prognostic value of cancer subtypes. We implemented and applied triple and quadruple optimization algorithms to renal carcinoma gene expression data from TCGA. The study targets kidney cancer subtypes that are difficult to distinguish through histopathology methods. Selected RNA-seq biomarkers were assessed against the gold standard method, which relies solely on clinical information, and in external microarray-based validation datasets. Notably, these biomarkers achieved over 0.8 of accuracy in external validations and added significant value to survival predictions, outperforming the use of clinical data alone with a superior c-index. The provided tool also helps explore the trade-off between objectives, offering multiple solutions for clinical evaluation before proceeding to costly validation or clinical trials.

Development of android-based self-assessment application for basic pencak silat techniques

In Physical Education learning (PE), the absence of effective self-assessment to measure basic pencak silat techniques can hinder student learning and skill development. This research aimed to develop an Android-based self-assessment application for basic pencak silat techniques in PE classes. The study follows the Research and Development (R&D) method, incorporating the ADDIE model: Analysis, Design, Development, Implementation, and Evaluation. Through expert validation and field trials at State High School 1 Bengkalis, the application's feasibility and effectiveness were assessed. Results showed a high level of feasibility and effectiveness, with significant improvement in students' understanding and skills in basic pencak silat techniques. The application offers benefits such as ease of use for teachers, increased student interest, and clear learning objectives. However, challenges include dependence on internet connectivity and device limitations. Despite limitations, this study contributes to innovative and efficient learning aids, enhancing skill assessment in PE. The implications extend to curriculum integration and improved assessment methods for teachers, empowering students to monitor their progress and enhance their skills independently. Future research could explore broader applications in sports learning and address specific needs in pencak silat education.

Whole body sweat rate prediction: indoor treadmill and cycle ergometer exercise.

This article describes the development and validation of accurate whole body sweat rate prediction equations for individuals performing indoor cycle ergometer and treadmill exercise, where power output can be measured or derived from simple inputs. For cycle ergometry, 112 trials (67 participants) were used for model development and another 56 trials (42 participants) for model validation. For treadmill exercise, 171 trials (67 participants) were used for model development and another 95 trials (63 participants) for model validation. Trials were conducted over a range of dry-bulb temperature (20°C to 40°C), relative humidity (14% to 60%), and exercise intensity (∼40% to 85% of peak aerobic power) conditions, which were matched between model development and model validation. Whole body sweat rates were measured, and proprietary prediction models were developed (accounting for all relevant biophysical factors) and then validated. For model validation, mean absolute error for predicted sweating rate was 0.01 and 0.02 L·h-1 for cycle and treadmill trials, respectively. The 95% confidence intervals were modest for cycle ergometer (+0.25 and -0.22 L·h-1) and treadmill exercise (+0.33 and -0.29 L·h-1). The accounted for variance between predicted and measured values was 92% and 78% for cycle and treadmill exercise, respectively. Bland-Altman analysis indicated that zero and one predicted value exceeded the a priori acceptable level of agreement (equivalent to ±2% of total body mass in 3 h) for cycle and treadmill exercise, respectively. There were fewer trials with female subjects, but their values did not differ from those expected for males. This is the foremost study to develop and validate whole body sweat rate prediction equations for indoor treadmill and cycle ergometer exercise of moderate to high intensity. These prediction equations are publicly available for use (https://sweatratecalculator.com).NEW & NOTEWORTHY This study presents the development of new proprietary whole body sweat rate prediction models for people exercising indoors on a cycle ergometer or treadmill using simple input parameters and delivered through a publicly available online calculator: https://sweatratecalculator.com. In an independent validation group, the predictive models for both indoor cycling and treadmill exercise were accurate across moderate to high exercise intensities in temperate to hot conditions. These equations will enable individualized hydration management during physical training and exercise physiology experiments.

Designing Student Worksheets Based on Local Wisdom Using a Detailed Learning Model Integrated Discovery Learning on Biodiversity Material

The research that has been carried out is intended to produce student worksheets, which in Indonesian are abbreviated as LKPD. for Biology Learning based on Kerinci local wisdom, which is integrated with the Discovery Learning model on biodiversity material. This research is development research using the 4D model. The subject of this research is the class used in class X SMAN 2 Kerinci which consists of small group trials (9 people) and product trials (33 people). The data collection instrument in this research was a questionnaire where, at the development stage, the student worksheets were validated by material experts and design experts and assessed through responses from biology subject teachers. The data analysis technique used in this research uses a Likert scale. The research results show that material expert validation, with a percentage of 88.33%, is in the very good category. Furthermore, the design validation results are with a percentage of 98.33% in the very good category. The research results also showed that biology teachers responded to the developed student worksheets with a percentage of 87.50% in the "very good" category. The results of the small group trial of students were 76.62% in the "good" category, while the results of the large group trial were 80.37% in the "very good" category. Based on the results of validation and field trials, the LKPD based on Kerinci local wisdom, which is integrated with the Discovery Learning learning model on biodiversity material, is good and suitable for application in biology learning, especially on biodiversity material.

Hb Co-Pilot: Machine Learning Algorithm for Real-Time Hemoglobin Estimation during Hemodialysis and a Multicenter International Validation Trial

Hb Co-Pilot: Machine Learning Algorithm for Real-Time Hemoglobin Estimation during Hemodialysis and a Multicenter International Validation Trial

Student Worksheets Literacy-Based to Improve High-Level Thinking Skill

This research is motivated by the lack of availability of LKPD that supports literacy activities to improve high-level thinking skills. This type of research is Research and Development (R&D) with the ADDIE model development method. The discussion of the research is adjusted to the ADDIE research and development procedures, namely: analyze, design, development, implementation, and evaluation. The subjects of this study were 24 students of grade V SDN 101867 Payagambar. Determination of the level of feasibility of LKPD or Student worksheets is based on expert validation tests and trials on students through student response questionnaires. The effectiveness of LKPD was obtained from the results of the pretest and posttest of grade V students. The results of this study indicate that the validation of material experts was 80% with a feasible category, validation of language experts was 85.41% with a very feasible category, validation of layout design experts was 90.47% with a very feasible category. The percentage results of the student response questionnaire were 86.70 which were categorized as very feasible, so it can be said that LKPD is feasible for use by grade V elementary school students. The results of the student pretest reached an average score of 69.3 with classical completeness reaching 42% with an incomplete category. While the results of the posttest after using LKPD reached an average of 84.50 with classical completeness reaching 100% and declared complete. Based on the pretest and posttest values, the gainscore value can be seen as 0.51 with a moderate effectiveness category. This shows that the use of literacy-based LKPD to improve high-level thinking skills has been effectively used by grade V students of SDN 101867 Payagambar, Batang Kuis District.

Development of A Career Understanding Application for Elementary School Students Based on Augmented Reality

This research aims to develop an augmented reality-based career understanding of media for elementary school students. The research and development procedure consists of 7 steps out of 10 main steps, namely: (1) potential and problems, (2) data collection, (3) product design, (4) design validation, (5) product/design revision, (6) products trial, (7) product revisions. Data were collected using a questionnaire consisting of (1) an expert validation questionnaire (guidance and counseling media expert, career guidance and counseling expert, Indonesian language expert), and (2) a small group trial questionnaire (elementary school teachers). Data analysis uses qualitative analysis to analyze data from expert validation and small group trials distributed through the instrument. The research results show that the research product in the form of augmented reality-based career understanding media containing content from 17 professional fields is suitable for use to improve elementary school students' career understanding, considering that this product has been validated through expert validation and small group trials. The implications of the results of this study emphasize the importance of career understanding in elementary schools, to shape children's future aspirations based on augmented reality (AR) as an interactive media for career guidance services in schools, thereby increasing students' interest in various job professions that change career guidance service methods to be more modern as well as developing students' technological competencies in facing the digital era as part of Generation Z and Alpha. Practically, guidance and counseling teachers can improve students' understanding of various professions through AR technology that facilitates understanding of the duties and responsibilities of job professions, schools can also integrate this application into a technology-based curriculum, encourage project-based learning, and inspire students' creativity and innovation in exploring and designing future careers.

Preoperative geriatric assessment to predict functional outcome after major urologic operations: Results from a multicenter study

IntroductionMajor urological tumor surgery entails a severe risk of unexpected adverse events, persistent functional deterioration, and death in older patients. The Erlangen Index (EI) geriatric assessment tool has previously been shown to predict incomplete functional recovery following major urological tumor surgery in an elderly patient collective. We prospectively evaluated assessment tools including EI in a multicenter setting. Materials and methodsA total of 340 patients over the age of 65 were assessed prospectively before and after cystectomy, prostatectomy, or renal tumor surgery at three academic centers in Germany and Austria. Endpoints were long-term functional deterioration (Activities of daily living (ADL) measured by Barthel-Index) at day 30 and day 180, and mortality at day 180. ResultsIn this study 58 (17.0 %) patients underwent cystectomy, 140 (41.2 %) prostatectomy and 142 (41.8 %) a kidney tumor operation. Mean age was 74.8 years. ADL impairment as a measure of incomplete recovery at day 30 and 180 after surgery were recorded in 47.6 % and 37.4 % of cases, respectively. The EI showed good sensitivity for mortality at day 180 (reference cohort: 85 %, validation center 1: 100 %, validation center 2: 50 %) and for ADL impairment at day 180 (reference cohort 75.4 %, validation center 1 72.3 %, validation center 2 83.3 %). ConclusionElderly patients with a poor performance status have a high risk of persistent functional deterioration. Data from this multicenter external validation trial confirms the EI as an accurate and reliable tool to identify patients with high risk of mortality or persistent postoperative functional impairment.

A rigorous multi-laboratory study of known PDAC biomarkers identifies increased sensitivity and specificity over CA19-9 alone

A blood test that enables surveillance for early-stage pancreatic ductal adenocarcinoma (PDAC) is an urgent need. Independent laboratories have reported PDAC biomarkers that could improve biomarker performance over CA19-9 alone, but the performance of the previously reported biomarkers in combination is not known. Therefore, we conducted a coordinated case/control study across multiple laboratories using common sets of blinded training and validation samples (132 and 295 plasma samples, respectively) from PDAC patients and non-PDAC control subjects representing conditions under which surveillance occurs. We analyzed the training set to identify candidate biomarker combination panels using biomarkers across laboratories, and we applied the fixed panels to the validation set. The panels identified in the training set, CA19-9 with CA199.STRA, LRG1, TIMP-1, TGM2, THSP2, ANG, and MUC16.STRA, achieved consistent performance in the validation set. The panel of CA19-9 with the glycan biomarker CA199.STRA improved sensitivity from 0.44 with 0.98 specificity for CA19-9 alone to 0.71 with 0.98 specificity (p < 0.001, 1000-fold bootstrap). Similarly, CA19-9 combined with the protein biomarker LRG1 and CA199.STRA improved specificity from 0.16 with 0.94 sensitivity for CA19-9 to 0.65 with 0.89 sensitivity (p < 0.001, 1000-fold bootstrap). We further validated significantly improved performance using biomarker panels that did not include CA19-9. This study establishes the effectiveness of a coordinated study of previously discovered biomarkers and identified panels of those biomarkers that significantly increased the sensitivity and specificity of early-stage PDAC detection in a rigorous validation trial.

Characterization of spatiotemporal and kinetic gait variables in dogs with hindlimb ataxia and bilateral hindlimb lameness

BackgroundDiscriminating the underlying cause of gait abnormalities can be challenging in a clinical setting, especially in the presence of bilateral disease. Pressure-sensitive walkways (PSWs) have been utilized to characterize the gait of dogs with various neurologic or orthopaedic conditions. The potential use of the PSW includes the discrimination of conditions that can be similar in clinical presentation, such as bilateral hindlimb lameness and hindlimb ataxia. The primary aim of this study was to describe the spatial, temporal, and kinetic gait parameters of dogs with hindlimb ataxia or bilateral hindlimb lameness and compare them to those of normal dogs. Forty-six dogs were prospectively recruited. The normal group included 20 dogs with normal neurologic and orthopaedic exams. The orthopaedic group included 15 dogs with bilateral hindlimb orthopaedic diseases with weight-bearing hindlimb lameness and normal neurologic exams. The neurologic group included 11 dogs with ambulatory paraparesis and normal orthopaedic exams. Each dog was walked across the PSW, and at least 3 valid trials were collected. The stride time, stance time, swing time, stride length, gait velocity, peak vertical force (PVF), vertical impulse (VI), and limb symmetry were recorded. The mean values of all parameters from the valid trials were calculated and used for data analysis. The outcomes were compared among all groups.ResultsCompared with the normal group, the orthopaedic group had a significantly greater percent body weight distribution (%BWD) and vertical impulse distribution (VID) in the forelimbs. When comparing the spatiotemporal parameters, the neurologic group showed an increase in forelimb stance time compared to that of the normal group. Compared with that in the normal group, the stride velocity in the forelimbs in the orthopaedic group was greater. There were no significant differences in the kinetic parameters between the neurologic group and the normal group, nor in stride time or stride length among the groups.ConclusionThe gait parameters obtained by PSW demonstrated that the orthopaedic and neurologic groups may have different compensatory mechanisms for their gait deficiencies. These parameters can potentially be used to construct a predictive model to evaluate PSW as a diagnostic tool in future studies.

Genome-Derived Ampullary Adenocarcinoma Classifier and Postresection Prognostication

Ampullary adenocarcinoma (AA) is characterized by clinical and genomic heterogeneity. A previously developed genomic classifier defined biologically distinct phenotypes with greater accuracy than standard histologic classification. External validation is needed before routine clinical use. To test external validity of the prognostic value of the hidden genome classifier of AA. This retrospective cohort study took place at 6 international academic institutions. Consecutive patients (n = 192) who underwent curative-intent resection of histologically confirmed AA were included. The data were analyzed from January 2005 through July 2020. The multilevel meta-feature regression model previously trained on a prospectively sequenced cohort of 3411 patients (1001 pancreatic adenocarcinoma, 165 distal bile duct adenocarcinoma, and 2245 colorectal adenocarcinoma) was applied to AA sequencing data to quantify the relative proportions of parental cell of origin. Genomic classification was correlated with immunohistologic subtype (intestinal [INT] or pancreatobiliary [PB]) and with overall survival (OS), using the log-rank test and Cox proportional hazard models. Among 192 patients with AA (median age, 69.0 [IQR, 60.0-74.0] years and 134 were male [64%]), concordance between immunohistologic and genomic subtypes was 55%. Most INT subtype tumors were categorized into the colorectal genomic subtype (43 of 57 [72.9%]). Of the 114 PB subtype tumors, 29 had a pancreatic genomic profile (25.4%) and 24 had a distal bile duct genomic profile (21.1%). Whereas the standard immunohistologic subtypes were not associated with survival (log rank P = .26), predicted genomic probabilities were correlated with survival probability. Genomic scores with higher colorectal probability were associated with higher survival probability; higher pancreatic and distal bile duct probabilities were associated with lower survival probability. The AA genomic classifier is reproducible with available molecular testing in a diverse international cohort of patients and improves stratification of the divergent clinical outcomes beyond standard immunohistologic classification. These data provide a molecular classification that may be incorporated into clinical trials for prospective validation.