Clinical Use Research Articles

Adolescents and Young Adults With Respiratory Failure in U.S. PICUs: A Pediatric Health Information System Database Study, 2011–2022

Objectives: To examine the clinical characteristics, outcomes, and resource use of adolescents and young adults (AYAs) admitted to PICUs in the United States with respiratory failure. Design: Retrospective cohort study. Setting: De-identified data from 48 U.S. children’s hospitals contributing to the Pediatric Health Information System (PHIS) database. Patients: All patients older than 30 days old with respiratory failure, defined as encounters with clinical transaction codes for noninvasive or invasive mechanical ventilation, admitted to PHIS database PICUs from January 2011 to December 2022. Patients were categorized into five cohorts (< 15, 15–18, 19–21, 22–25, and > 25 yr old). Interventions: None. Measurements and Main Results: A total of 430,238 patients were identified. AYA (≥ 15 yr old) accounted for 15% (65,740) of all PICU admissions with respiratory failure. Forty-nine percent (32,232/65,740) of AYA older than 25 years had medical technology dependence compared with 39% in those younger than 15 years (p < 0.001). Sixty-one percent of AYA older than 25 years had a cardiovascular comorbidity compared with 35% of those younger than 15 years (p < 0.001). Forty percent of AYA older than 25 years had a neurologic comorbidity, and 27% a gastrointestinal comorbidity, compared with 27% and 31%, respectively, in those younger than 15 years (all p < 0.001). Compared with those younger than 15 years, AYA median hospital crude mortality rate was higher at 7.7% compared with 5.2%, as were median hospital charges per encounter at $163K (interquartile range [IQR], $77K–$350K) vs. $121K (IQR, $53K–$278K; all p < 0.001). Median ventilator days and hospital length of stay in survivors were similar for all age cohorts. Conclusions: AYA represent a substantial proportion of patients admitted to the PICU with respiratory failure. These individuals have unique comorbidities and are at risk for increased mortality and resource utilization compared with younger patients during hospitalization. Medical complexity and sequelae of pediatric illness may delay the transition of AYA to adult care, necessitating collaboration between adult and pediatric critical care physicians to increase research across the age spectrum and develop and implement appropriate evidence-based guidelines.

Updates on Clinical Language Sampling Practices: A Survey of Speech-Language Pathologists Practicing in the United States.

Language sample analysis (LSA) provides many benefits for assessing, identifying therapy goals, and monitoring the progress of children with language disorders. Despite these widely recognized advantages, previous surveys suggest the declining use of LSA by speech-language pathologists (SLPs). This study aimed to provide updates on clinical LSA use following the recent introduction of two new LSA protocols, namely, the Sampling Utterances and Grammatical Analysis Revised (SUGAR) protocol and the Computerized Language Analysis KIDEVAL program. Survey data from SLPs practicing in the United States (N = 337) were used to examine rates of LSA use, methods, and protocols. Factors predicting LSA use and reported facilitators and barriers were also examined. Results indicated that 60% of SLPs used LSA in the past year. LSA skill level, training, and serving preschool or elementary school children predicted LSA use, whereas workplace, caseload, and years of experience were not significant predictors. Most SLPs reported using self-designed LSA protocols (62%), followed by Systematic Analysis of Language Transcripts (23%) and SUGAR (12%) protocols. SLPs who did not use LSA reported limited time (74%), limited resources (59%), and limited expertise (41%) as barriers and identified additional training on LSA computer programs (52%) and access to automatic speech recognition programs (49%) as facilitators to their adoption of LSA. Reported rates of LSA use and methods were consistent with previous survey findings. This study's findings highlight the ongoing needs for more extensive preprofessional training in LSA.

Strength of Evidence Underlying the CMS-FDA Parallel Review of Comprehensive Genomic Profiling Tests in the Cancer Setting.

Although use of comprehensive genomic profiling (CGP) was approved by a novel CMS/FDA parallel review process, the quality of the supporting evidence is unclear. We evaluated the rigor of the peer-reviewed literature cited in the National Coverage Determination Memorandum for the FoundationOne CDx (F1CDx). We identified studies cited in the memorandum. Two independent researchers evaluated each study and applied a modified version of the Fryback and Thornbury hierarchy[1], an established framework for evaluating the efficacy of diagnostic tests. Studies focused on clinical outcomes were then categorized by study design, guided by recommendations from the Center for Medical Technology Policy. The sample included 113 scientific studies. The majority (n = 60, 53.1%) used CGP outside the course of clinical care, and there was significant heterogeneity in the cancer types assessed and sequencing depth. We found 8 (7.1%) studies that assessed whether clinical care had changed due to CGP testing, and 38 (33.6%) assessed clinical outcomes. After excluding studies that tested for five or fewer genomic alterations, 25 remained in the clinical outcomes sample: Of these, only one included a comparator group that did not receive CGP testing. Only four studies used F1CDx as the primary genomic test, none of which compared the outcomes of patients who did vs did not receive the F1CDx test. The findings indicate gaps in the supporting evidence for broad CGP use in patients with solid tumors. More rigorous studies that assess clinical utility would better inform the approval process for novel diagnostic tests.

Ultrasound-based radiomics nomogram for predicting HER2-low expression breast cancer

PurposeAccurate preoperative identification of Human epidermal growth factor receptor 2 (HER2) low expression breast cancer (BC) is critical for clinical decision-making. Our aim was to use machine learning methods to develop and validate an ultrasound-based radiomics nomogram for predicting HER2-low expression in BC.MethodsIn this retrospective study, 222 patients (108 HER2-0 expression and 114 HER2-low expression) with BC were included. The enrolled patients were randomly divided into a training cohort and a test cohort with a ratio of 8:2. The tumor region of interest was manually delineated from ultrasound image, and radiomics features were subsequently extracted. The features underwent dimension reduction using the least absolute shrinkage and selection operator (LASSO) algorithm, and rad-score were calculated. Five machine learning algorithms were applied for training, and the algorithm demonstrating the best performance was selected to construct a radiomics (USR) model. Clinical risk factors were integrated with rad-score to construct the prediction model, and a nomogram was plotted. The performance of the nomogram was assessed using receiver operating characteristic curve and decision curve analysis.ResultsA total of 480 radiomics features were extracted, out of which 11 were screened out. The majority of the extracted features were wavelet features. Subsequently, the USR model was established, and rad-scores were computed. The nomogram, incorporating rad-score, tumor shape, border, and microcalcification, achieved the best performance in both the training cohort (AUC 0.89; 95%CI 0.836-0.936) and the test cohort (AUC 0.84; 95%CI 0.722-0.958), outperforming both the USR model and clinical model. The calibration curves showed satisfactory consistency, and DCA confirmed the clinical utility of the nomogram.ConclusionThe nomogram model based on ultrasound radiomics exhibited high prediction value for HER2-low BC.

An 8-SNP LDL Cholesterol Polygenic Score: Associations with Cardiovascular Risk Traits, Familial Hypercholesterolemia Phenotype, and Premature Coronary Heart Disease in Central Romania

Familial hypercholesterolemia (FH) is the most significant inherited risk factor for coronary heart disease (CHD). Current guidelines focus on monogenic FH, but the polygenic form is more common and less understood. This study aimed to assess the clinical utility of an 8-SNP LDLC polygenic score in a central Romanian cohort. The cohort included 97 healthy controls and 125 patients with premature (P)CHD. The weighted LDLC polygenic risk score (wPRS) was analyzed for associations with relevant phenotypic traits, PCHD risk, and clinical FH diagnosis. The wPRS positively correlated with LDLC and DLCN scores, and LDLC concentrations could be predicted by wPRS. A trend of increasing LDLC and DLCN scores with wPRS deciles was observed. A +1 SD increase in wPRS was associated with a 36% higher likelihood of having LDLC > 190 mg/dL and increases in LDLC (+0.20 SD), DLCN score (+0.16 SD), and BMI (+0.15 SD), as well as a decrease in HDLC (−0.14 SD). Although wPRS did not predict PCHD across the entire spectrum of values, individuals above the 90th percentile were three times more likely to have PCHD compared to those within the 10th or 20th percentiles. Additionally, wPRS > 45th percentile identified “definite” clinical FH (DLCN score > 8) with 100% sensitivity and 45% specificity. The LDLC polygenic score correlates with key phenotypic traits, and individuals with high scores are more likely to have PCHD. Implementing this genetic tool may enhance risk prediction and patient stratification. These findings, the first of their kind in Romania, are consistent with the existing literature.

Deep learning-assisted distinguishing breast phyllodes tumors from fibroadenomas based on ultrasound images: a diagnostic study.

To evaluate the performance of ultrasound-based deep learning (DL) models in distinguishing breast phyllodes tumors (PTs) from fibroadenomas (FAs) and their clinical utility in assisting radiologists with varying diagnostic experiences. We retrospectively collected 1180 ultrasound images from 539 patients (247 PTs and 292 FAs). Five DL network models with different structures were trained and validated using nodule regions annotated by radiologists on breast ultrasound images. DL models were trained using the methods of transfer learning and 3-fold cross-validation. The model demonstrated the best evaluation index in the 3-fold cross-validation was selected for comparison with radiologists' diagnostic decisions. Two-round reader studies were conducted to investigate the value of DL model in assisting six radiologists with different levels of experience. Upon testing, Xception model demonstrated the best diagnostic performance (AUC: 0.87, 95%CI: 0.81-0.92), outperforming all radiologists (all p < 0.05). Additionally, the DL model enhanced the diagnostic performance of radiologists. Accuracy demonstrated improvements of 4%, 4%, and 3% for senior, intermediate, and junior radiologists, respectively. The DL models showed superior predictive abilities compared to experienced radiologists in distinguishing breast PTs from FAs. Utilizing the model led to improved efficiency and diagnostic performance for radiologists with different levels of experience (6-25 years of work). We developed and validated a DL model based on the largest available dataset to assist in diagnosing PTs. This model has the potential to allow radiologists to discriminate two types of breast tumors which are challenging to identify with precision and accuracy, and subsequently to make more informed decisions about surgical plans.

Lipid-based nanoparticles: innovations in ocular drug delivery

Ocular drug delivery presents significant challenges due to intricate anatomy and the various barriers (corneal, tear, conjunctival, blood-aqueous, blood-retinal, and degradative enzymes) within the eye. Lipid-based nanoparticles (LNPs) have emerged as promising carriers for ocular drug delivery due to their ability to enhance drug solubility, improve bioavailability, and provide sustained release. LNPs, particularly solid lipid nanoparticles (SLNs), nanostructured lipid carriers (NLCs), and cationic nanostructured lipid carriers (CNLCs), have emerged as promising solutions for enhancing ocular drug delivery. This review provides a comprehensive summary of lipid nanoparticle-based drug delivery systems, emphasizing their biocompatibility and efficiency in ocular applications. We evaluated research and review articles sourced from databases such as Google Scholar, TandFonline, SpringerLink, and ScienceDirect, focusing on studies published between 2013 and 2023. The review discusses the materials and methodologies employed in the preparation of SLNs, NLCs, and CNLCs, focusing on their application as proficient carriers for ocular drug delivery. CNLCs, in particular, demonstrate superior effectiveness attributed due to their electrostatic bioadhesion to ocular tissues, enhancing drug delivery. However, continued research efforts are essential to further optimize CNLC formulations and validate their clinical utility, ensuring advancements in ocular drug delivery technology for improved patient outcomes.

BCL2 expression is enriched in advanced prostate cancer with features of lineage plasticity.

The widespread use of potent androgen receptor signaling inhibitors (ARSIs) has led to an increasing emergence of AR-independent castration-resistant prostate cancer (CRPC), typically driven by loss of AR expression, lineage plasticity, and transformation to prostate cancers (PCs) that exhibit phenotypes of neuroendocrine or basal-like cells. The anti-apoptotic protein BCL2 is upregulated in neuroendocrine cancers and may be a therapeutic target for this aggressive PC disease subset. There is an unmet clinical need, therefore, to clinically characterize BCL2 expression in metastatic CRPC (mCRPC), determine its association with AR expression, uncover its mechanisms of regulation, and evaluate BCL2 as a therapeutic target and/or biomarker with clinical utility. Here, using multiple PC biopsy cohorts and models, we demonstrate that BCL2 expression is enriched in AR-negative mCRPC, associating with shorter overall survival and resistance to ARSIs. Moreover, high BCL2 expression associates with lineage plasticity features and neuroendocrine marker positivity. We provide evidence that BCL2 expression is regulated by DNA methylation, associated with epithelial-mesenchymal transition, and increased by the neuronal transcription factor ASCL1. Finally, BCL2 inhibition had antitumor activity in some, but not all, BCL2-positive PC models, highlighting the need for combination strategies to enhance tumor cell apoptosis and enrich response.

Clinical Value of ABCB1 and PAI-1 Gene Polymorphisms in Predicting Glucocorticoid-induced Adverse Reactions in Nephrotic Syndrome Patients.

Glucocorticoid (GC)-induced adverse reactions (ARs) have been extensively studied due to their potential impact on patients' health. This study aimed to examine the potential correlation between two polymorphisms [adenosine triphosphate-binding cassette B1 (ABCB1) C3435T and plasminogen activator inhibitor-1 (PAI-1) 4G/5G] and various GC-induced ARs in nephrotic syndrome (NS) patients. In this study, 513 NS patients who underwent GC treatment were enrolled. Then, the patients were divided into two groups based on ABCB1 C3435T and PAI-1 4G/5G genotyping, and intergroup comparisons of clinicopathological data and GC-induced ARs were performed. Univariate and multivariate logistic analyses were subsequently conducted to identify potential risk factors for GC-induced ARs, and a nomogram was subsequently established and validated via the area under the ROC curve (AUC), calibration curve and decision curve analysis (DCA). We identified ABCB1 C3435T as an independent risk factor for the development of steroid-associated avascular necrosis of the femoral head (SANFH) (OR: 2.191, 95% CI: 1.258-3.813, P=0.006) but not as a risk factor for the occurrence of steroid diabetes mellitus (S-DM). On the other hand, PAI-1 4G/5G was identified as an independent risk factor for the development of both SANFH (OR: 2.198, 95% CI: 1.267-3.812, P=0.005) and S-DM (OR: 2.080, 95% CI: 1.166-3.711, P=0.013). Notably, no significant correlation was found between the two gene polymorphisms and other GC-induced ARs. In addition, two nomograms were established and validated to demonstrate strong calibration capability and clinical utility. Assessing ABCB1 C3435T and PAI-1 4G/5G before steroid treatment in NS patients could be useful for identifying patients at a high risk of developing SANFH and S-DM.

Effect of the dose, timing, and route of administration of mesenchymal stem cells on their regenerative capacity after myocardial infarction: A systematic review

Background The global rise in cases of acute myocardial infarction (AMI) poses a significant health challenge, which is why adult stem cells have gained great importance in recent years, due to their potential to promote the regeneration of the flowcardiac tissue, among which multipotent mesenchymal stromal cells (MSCs) stand out, thanks to their clinical usefulness. Objectives To evaluate the effect of the dose, timing, and route of administration of MSCs on their regenerative capacity after MI. Methods We searched for randomized clinical trials and experimental studies published up to April 25, 2024, in Medline (PubMed) and Scopus. Results Nine clinical studies were included in the qualitative assessment. The main routes of application were coronary, intramyocardially, epicardial topical and systemic venous perfusion, which could have clinical effectiveness with doses of 1x106 MSC/Kg,1 to 3 x 106, 4x106 and those greater than 0.5x106, respectively. The median number of viable cells administered was 2.4x106 (IQR: 1.6-2.4) in the PCI group versus 1.6x106 in the RCVI group (p=0.167). Median ex vivo retention was 2.55% in the RCVI group, 30 days after AMI, and 39.40% in the PCI group. At 4 and 12 months of follow-up, a better left ventricular end-to-end (LVEF) was observed in the group treated with ADSCs, at 4 (51.8% ±5.4% vs. 35.5% ±1.9%) and 8 weeks (52.1%± 3.4% versus 34.2% ±4.7%, p = 0.048). Conclusions The dosing, timing of administration, and routes of administration were important factors to assess the efficacy of the MSC.

A pilot study: Examining cytoskeleton gene expression profiles in Pakistani children with autism spectrum disorder.

Finding effective pharmacological interventions to address the complex array of neurodevelopmental disorders is currently an urgent imperative within the scientific community as these conditions present significant challenges for patients and their families, often impacting cognitive, emotional, and social development. In this study, we aimed to explore non-invasive method to diagnose autism spectrum disorders (ASD) within Pakistan children population and to identify clinical drugs for its treatment. The current report outlines a comprehensive bidirectional investigation showcasing the successful utilization of saliva samples to quantify the expression patterns of profilins (PFN1, 2, and 3); and ERM (ezrin, radixin, and moesin) proteins; and additionally moesin pseudogene 1 and moesin pseudogene 1 antisense (MSNP1AS). Subsequently, these expression profiles were employed to forecast interactions between drugs and genes in children diagnosed with ASD. This study sought to delve into the intricate gene expression profiles using qualitative polymerase chain reaction of profilin isoforms (PFN1, 2, and 3) and ERM genes extracted from saliva samples obtained from children diagnosed with ASD. Through this analysis, we aimed to elucidate potential molecular mechanisms underlying ASD pathogenesis, shedding light on novel biomarkers and therapeutic targets for this complex neurological condition. (n = 22). Subsequently, we implemented a diagnostic model utilizing sparse partial least squares discriminant analysis (sPLS-DA) to predict drugs against our genes of interest. Furthermore, connectivity maps were developed to illustrate the predicted associations of 24 drugs with the genes expression. Our study results showed varied expression profile of cytoskeleton linked genes. Similarly, sPLS-DA model precisely predicted drug to genes response. Sixteen of the examined drugs had significant positive correlations with the expression of the targeted genes whereas eight of the predicted drugs had shown negative correlations. Here we report the role of cytoskeleton linked genes (PFN and ERM) in co-relation to ASD. Furthermore, variable yet significant quantitative expression of these genes successfully predicted drug-gene interactions as shown with the help of connectivity maps that can be used to support the clinical use of these drugs to treat individuals with ASD in future studies.

Traditional vs novel out-of-office method for collecting cytology and HPV DNA - a comparative study.

The integration of high-risk human papillomavirus (HPV) detection into cervical cancer screening in Poland aims to improve early detection, yet challenges in coverage and adherence persist. Innovative approaches, like sampling for HPV testing and cytology outside medical settings, have been proposed. This study assesses the feasibility and agreement of results between traditional and novel sampling methods. A cohort of 50 women aged 25-74 underwent HPV DNA and liquid-based cytology sampling both in-office using standard method and outside the medical setting by trained personnel. Samples were analyzed for HPV DNA using Real-Time PCR and cytology according to the Bethesda System. Cytology and HPV DNA positivity rates showed substantial agreement between methods, with almost perfect agreement for high-risk HPV types. Visual assessment of the cervix was successfully conducted in all cases. Preliminary results suggest remote sampling for HPV DNA and cytology is a viable alternative to traditional methods, with the effectiveness in detecting HPV and cytological abnormalities comparable to this reported in literature, offering potential benefits for individuals with mobility limitations or logistical barriers to attending medical appointments. The study highlights the potential role of remote sampling for HPV DNA and cytology in enhancing cervical cancer screening accessibility and adherence. Implementation of such methods could improve coverage, particularly among underserved populations. Further research is needed to validate and optimize these approaches for broader clinical use.

Intravitreal chlorhexidine for sterilizing the vitreous cavity in an animal model of bacterial endophthalmitis

Purpose To evaluate the efficacy and safety of intravitreal chlorhexidine (CHX) for sterilising the vitreous cavity in bacterial endophthalmitis. Methods For in-vitro experiments, full-thickness retina explants were harvested from freshly enucleated pig eyes. Six-millimeter circular sensory retina patches were then incubated in varying concentrations of CHX (0.625-800 µg/mL) for 24 hours. Retinal cell viability was determined at the end of the incubation period with a live-dead assay. The bactericidal effects of the tested CHX concentrations were determined using a quantitative suspension test on Staphylococcus epidermidis. The safety of CHX was also tested by injecting varying doses of CHX (50-400 µg/mL) into the vitreous cavity of albino rabbits followed by flash electroretinography (ERG) and light microscopy. The bactericidal effect of the non-toxic CHX doses was determined using the rabbit model of endophthalmitis created by injecting 3000 CFU/0.1 mL of Staphylococcus epidermidis. Results In vitro concentrations of CHX greater than 6.25 µgr/mL exerted a bactericidal effect, while concentrations of CHX less than 200 µg/mL did not impair retinal cell viability. Intravitreal concentrations of CHX between 20-100 µg/mL were adequate to sterilise the infected rabbit vitreous cavity in the animal model. No significant functional or anatomical deleterious effect was observed with ERG or light microscopy. Conclusion CHX can sterilise the vitreous cavity in an animal model of bacterial endophthalmitis without impairing retinal cell viability. Our results encourage further research for clinical use of chlorhexidine in treatment of bacterial endophthalmitis.

Development and validation of a nomogram for predicting the interstitial fibrosis and tubular atrophy in patients with lupus nephritis.

Interstitial fibrosis and tubular atrophy (IFTA) were frequent histologic features of lupus nephritis (LN), and LN patients with IFTA have poor renal outcomes. In this study, we aimed to construct prediction models for the IFTA in LN patients. This retrospective study included 303 patients with biopsy proven LN at the Affiliated Hospital of Qingdao University and Union Hospital of Fujian Medical University. The participants were randomly divided into development and validation cohorts. They were further divided into IFTA and non-IFTA groups. The least absolute shrinkage and selection operator (LASSO) regression model with laboratory test results collected at the time of kidney biopsy was used to optimize feature selection for the risk model. Multivariable logistic regression analysis was applied to build a predicting model incorporating the feature selected in the LASSO regression model. Discrimination, calibration, and clinical usefulness of the predicting model were assessed using the C-index, calibration plot, and ROC curve analysis. Internal validation was assessed using the bootstrapping validation. A nomogram for individual assessment was constructed based on the preferable model. Predictors contained in the prediction nomogram included age, body mass index (BMI), mean arterial pressure (MAP), logANA, C3, eGFR and serum uric acid. The model displayed good discrimination with a C-index of 0.794 (95% CI 0.734-0.854) and good calibration. High C-index value of 0.857 (95% CI 0.776-0.938) could still be reached in the interval validation. A nomogram model based on the LASSO model was created for producing a probability score of IFTA in LN patients. With excellent predictive abilities, the nomogram may provide a simple and reliable tool to distinguish LN patients with IFTA and helps physicians make clinical decisions in their comprehensive assessment.

"Academic Influence and Industry Funding in Nerve Allograft Research: A Co-Authorship Network Analysis".

Clinical use of acellular nerve allografts is rapidly increasing despite limited high-quality, comparative evidence of superiority. Simultaneously, non-research payments to clinicians by the nerve allograft industry exceeds $14,000,000 over the last decade. In this study, the authors hypothesized that nerve allograft-related academic influence would correlate with industry funding. PubMed studies on nerve allografts in plastic and reconstructive surgery journals were reviewed. Using author lists from extracted studies, a co-authorship network was generated and degree centralities - quantitative measurements of influence within a network - were calculated. Open Payments data from the nerve allograft industry was summated for each author. Finally, Pearson correlation and linear regression were used to analyze the relationship between centrality and payments received. 185 studies were included, with 581 unique authors (nodes) and 2,406 co-authorships (ties) between them. Among authors with exceptional network influence (centrality >10, 75th percentile; n=113), 56 were clinicians with valid NPIs and therefore eligible for inclusion in the Open Payments database. 44 (79%) of these authors received at least one payment from the industry. Pearson correlation revealed a moderate (0.4<r<0.6) positive correlation between centrality and payments received (r=0.51, p<0.001). Linear regression demonstrated an estimated 16% increase in total pay per additional unit of centrality (p<0.001; 95% CI [8%, 25%]). There is a significant connection between academic influence and financial support from the nerve allograft industry. Such results warrant discussion concerning conflicts of interest in clinical research and best practices for mitigating potential bias related to commercially backed treatments.

A Novel Recombinant Vitronectin Variant Supports the Expansion and Differentiation of Pluripotent Stem Cells in Defined Animal-Free Workflows

An essential aspect of harnessing the potential of pluripotent stem cells (PSCs) and their derivatives for regenerative medicine is the development of animal-free and chemically defined conditions for ex vivo cultivation. PSCs, including embryonic and induced PSCs (iPSCs), are in the early stages of clinical trials for various indications, including degenerative diseases and traumatic injury. A key step in the workflows generating these cells for more widespread clinical use is their safe and robust ex vivo cultivation. This entails optimization of cell culture media and substrates that are safe and consistent while maintaining robust functionality. Here, we describe the design of a human vitronectin (hVTN) variant with improved manufacturability in a bacterial expression system along with improved function in comparison to wild-type VTN and other previously characterized polypeptide fragments. In conjunction with an animal component-free media formulation, our hVTN fragment provides animal-free conditions for the enhanced expansion of iPSCs. This hVTN variant also supports the reprogramming of PBMCs into iPSCs. Furthermore, we show that these iPSCs can be efficiently differentiated into the three major germ layers and cortical neurons, thereby closing the loop on a completely defined animal-free workflow for cell types relevant for regenerative medicine.

Circulating ECM proteins decorin and alpha-L-iduronidase differentiate ATTRwt-CM from ATTRwt-negative HFpEF/HFmrEF.

Wild-type transthyretin cardiac amyloidosis (ATTRwt-CM) is an under-recognized aetiology of heart failure (HF), necessitating early detection for timely treatment. Our study aimed to differentiate patients with ATTRwt-CM from ATTRwt-negative HFpEF/HFmrEF patients by identifying and validating circulating protein biomarkers. In addition, we measured the same biomarkers in patients with cardiomyopathy due to light chain amyloidosis (AL)-CM to gain disease-specific insights. In this observational study, serum concentrations of 363 protein biomarkers were measured in a discovery cohort consisting of 73 ATTRwt-CM, 55 AL-CM, and 59 ATTRwt-negative HFpEF/HFmrEF patients, using multiplex proximity extension assays. Sparse partial least squares analyses showed overlapping ATTRwt-CM and AL-CM biomarker profiles with clear visual differentiation from ATTRwt-negative patients. Pathway analyses with g:Profiler revealed significantly up-regulated proteoglycans (PG) and cell adhesion pathways in both ATTRwt-CM and AL-CM. Penalized regression analysis revealed that the proteoglycan decorin (DCN), lysosomal hydrolase alpha-L-iduronidase (IDUA) and glycosyl hydrolase galactosidase β-1 (GLB-1) most effectively distinguished ATTRwt-CM from ATTRwt-negative patients (R2 = 0.71). In a prospective validation cohort of 35 ATTRwt-CM patients and 25 ATTRwt-negative patients, DCN and IDUA significantly predicted ATTRwt-CM in the initial analysis (DCN: OR 3.3, IDUA: OR 0.4). While DCN remained significant after correcting for echocardiographic parameters, IDUA did not. DCN showed moderate discriminative ability (AUC, 0.74; 95% CI, 0.61-0.87; sensitivity, 0.91; specificity, 0.52) as did IDUA (AUC, 0.78; 95% CI, 0.65-0.91; sensitivity, 0.91; specificity, 0.61). A model combining clinical factors (AUC 0.92) outperformed DCN but not IDUA, a combination of the biomarkers was not significantly better. Neither DCN nor IDUA correlated with established disease markers. ATTRwt-CM has a distinctly different biomarker profile compared with HFpEF/HFmrEF, while ATTRwt-CM patients share a similar biomarker profile with AL-CM patients characterized by up-regulation of proteoglycans and cell-adhesion pathways. The biomarkers DCN and IDUA show the potential to serve as an initial screening tool for ATTTRwt-CM. Further research is needed to determine the clinical usefulness of these and other extracellular matrix components in identifying ATTRwt-CM.

A Behavior-Based Model to Validate Electronic Systems Designed to Collect Patient-Reported Outcomes: Model Development and Application.

The merits of technology have been adopted in capturing patient-reported outcomes (PROs) by incorporating PROs into electronic systems. Following the development of an electronic system, evaluation of system performance is crucial to ensuring the collection of meaningful data. In contemporary PRO literature, electronic system validation is overlooked, and evidence on validation methods is lacking. This study aims to introduce a generalized concept to guide electronic patient-reported outcome (ePRO) providers in planning for system-specific validation methods. Since electronic systems are essentially products of software engineering endeavors, electronic systems used to collect PRO should be viewed from a computer science perspective with consideration to the health care environment. On this basis, a testing model was blueprinted and applied to a newly developed ePRO system designed for clinical use in pediatric dentistry (electronic Personal Assessment Questionnaire-Paediatric Dentistry) to investigate its thoroughness. A behavior-based model of ePRO system validation was developed based on the principles of user acceptance testing and patient-centered care. The model allows systematic inspection of system specifications and identification of technical errors through simulated positive and negative usage pathways in open and closed environments. The model was able to detect 15 positive errors with 1 unfavorable response when applied to electronic Personal Assessment Questionnaire-Paediatric Dentistry system testing. The application of the behavior-based model to a newly developed ePRO system showed a high ability for technical error detection in a systematic fashion. The proposed model will increase confidence in the validity of ePRO systems as data collection tools in future research and clinical practice.

Case report: Successful combination of CLL1 CAR-T therapy and hematopoietic stem cell transplantation in a 73-year-old patient diagnosed with refractory acute myeloid leukemia

The incidence of Acute myeloid leukemia (AML) increases with advancing age, and the prognosis for elderly patients is significantly poorer compared to younger patients. Although the combination therapy of venetoclax and hypomethylating agents has demonstrated improved prognosis in patients unable to tolerate intensive chemotherapy, there remains a therapeutic blank for those who fail to achieve remission with current treatment regimens. Here, we report the successful clinical utilization of autogenous CLL1 CAR-T therapy combined with hematopoietic stem cell transplantation in a 73-year-old patient diagnosed with refractory AML. The patient achieved morphological complete remission (CR) with incomplete marrow recovery and a slight presence of minimal residual disease (MRD) after receiving CLL1 CAR-T therapy. To further enhance the treatment and promote the recovery of hemopoiesis, we performed bridged allogenic hematopoietic stem cell transplantation (allo-HSCT) 20 days after the infusion of CLL1 CAR-T cells. The patient achieved MRD-negative CR following HSCT treatment. His primary disease maintained a complete remission status during the 11-month follow-up period. The patient encountered grade 2 cytokine release syndrome and grade 4 granulocytopenia subsequent to the infusion of CAR-T cells, while several rounds of infection and graft-versus-host disease were observed following allo-HSCT. Nevertheless, all these concerns were successfully addressed through comprehensive provision of supportive treatments. We have successfully demonstrated a highly effective and safe combination strategy involving CLL1 CAR-T therapy and allo-HSCT, which has exhibited remarkable tolerability and holds great promise even for elderly patients with AML.

The Clinical Utility of Finding Unexpected Subclinical Spikes Detected by High-Density EEG During Neurodiagnostic Investigations.

This study aimed to analyze the frequency of unexpected subclinical spikes (USCS) in pediatric patients who underwent high-density electroencephalogram (HD-EEG). Of the 4481 successful HD-EEG studies, 18.5% (829) were abnormal, and 49.7% of these abnormal studies showed SCS, of which 64.1% were USCS. USCS were found to be correlated with attention/concentration deficits and executive dysfunction, often accompanied by the dual psychiatric diagnosis of ADHD. MRI revealed abnormal findings in 32.6% of the subjects with USCS, such as abnormal signal or signal hyperintensity in brain parenchyma, temporal or arachnoid cysts, and vascular malformations. Moreover, the USCS group who received neuropsychiatric testing scored lower than the population mean on Full-Scale Intelligence Quotient, Working Memory Index, and Processing Speed Index. This study highlights the potential of USCS as biomarkers that can lead to changes in clinical management and outcomes, provide valuable information about pathophysiological mechanisms, and suggest potential treatment pathways.