Translational Research Research Articles

Implementation of Obesity Science Into Clinical Practice: A Scientific Statement From the American Heart Association.

Obesity is a recognized public health epidemic with a prevalence that continues to increase dramatically in nearly all populations, impeding progress in reducing incidence rates of cardiovascular disease. Over the past decade, obesity science has evolved to improve knowledge of its multifactorial causes, identifying important biological causes and sociological determinants of obesity. Treatments for obesity have also continued to develop, with more evidence-based programs for lifestyle modification, new pharmacotherapies, and robust data to support bariatric surgery. Despite these advancements, there continues to be a substantial gap between the scientific evidence and the implementation of research into clinical practice for effective obesity management. Addressing barriers to obesity science implementation requires adopting feasible methodologies and targeting multiple levels (eg, clinician, community, system, policy) to facilitate the delivery of obesity-targeted therapies and maximize the effectiveness of guideline-driven care to at-need patient populations. This scientific statement (1) describes strategies shown to be effective or promising for enhancing translation and clinical application of obesity-based research; (2) identifies key gaps in the implementation of obesity science into clinical practice; and (3) provides guidance and resources for health care professionals, health care systems, and other stakeholders to promote broader implementation and uptake of obesity science for improved population-level obesity management. In addition, advances in implementation science that hold promise to bridge the know-do gap in obesity prevention and treatment are discussed. Last, this scientific statement highlights implications for health research policy and future research to improve patient care models and optimize the delivery and sustainability of equitable obesity-related care.

Modeling social cognition in alcohol use disorder: lessons from schizophrenia.

A better understanding of social deficits in alcohol use disorder (AUD) has the potential to improve our understanding of the disorder. Clinical research shows that AUD is associated with interpersonal problems and the loss of a social network which impedes response to treatment. Translational research between animal models and clinical research may benefit from a discussion of the models and methods that currently guide research into social cognition in AUD. We propose that research in AUD should harness recent technological developments to improve ecological validity while maintaining experimental control. Novel methods allow us to parse naturalistic social cognition into tangible components, and to investigate previously neglected aspects of social cognition. Furthermore, to incorporate social cognition as a defining element of AUD, it is critical to clarify the timing of these social disturbances. Currently, there is limited evidence to distinguish factors that influence social cognition as a consequence of AUD, and those that precede the onset of the disorder. Both increasing the focus on operationalization of social cognition into objective components and adopting a perspective that spans the clinical spectrum will improve our understanding in humans, but also possibly increase methodological consistency and translational dialogue across species. This commentary underscores current challenges and perspectives in this area of research.

Integrating the Patient's Voice into the Research Agenda for Treatment of Chemosensory Disorders.

World-wide some 658 million people were infected with COVID-19 and millions suffer from chemosensory impairment associated with long COVID. Current treatments for taste and smell disorders are limited. Involving patients has the potential to catalyze the dynamic exchange and development of new ideas and approaches to facilitate biomedical research and therapeutics. We assessed patients' perceptions of the efficacy of treatments for chemosensory impairment using an online questionnaire completed by 5,815 people in the U.S. Logistic regression determined variables predictive of reported treatment efficacy for patients aged 18-24, 25-39, 40-60 and 60+ yrs. who were treated with nasal steroids, oral steroids, zinc, nasal rinse, smell training, theophylline, platelet rich plasma, and Omega 3. The most consistent predictor was age, with the majority of those 40-60 and 60+ reporting that nasal steroids, oral steroids, zinc, nasal rinse and smell training were only slightly effective or not effective at all. Many of these treatment strategies target regeneration and immune response, processes compromised by age. Only those under 40 reported more than slight efficacy of steroids or smell training. Findings emphasize the need to include patients of all ages in clinical trials. Older adults with olfactory impairment are at increased risk for Alzheimer's disease (AD). We speculate that olfactory impairment associated with long COVID introduces the potential for a significant rise in AD. Long COVID-associated chemosensory impairment increases the urgency for translational and clinical research on novel treatment strategies. Suggestions for high priority areas for epidemiological, basic, and clinical research on chemosensory impairment follow.

Role of Machine Learning and Artificial Intelligence in Arrhythmias and Electrophysiology.

Machine learning (ML), a subset of artificial intelligence (AI) centered on machines learning from extensive datasets, stands at the forefront of a technological revolution shaping various facets of society. Cardiovascular medicine has emerged as a key domain for ML applications, with considerable efforts to integrate these innovations into routine clinical practice. Within cardiac electrophysiology, ML applications, especially in the automated interpretation of electrocardiograms, have garnered substantial attention in existing literature. However, less recognized are the diverse applications of ML in cardiac electrophysiology and arrhythmias, spanning basic science research on arrhythmia mechanisms, both experimental and computational, as well as contributions to enhanced techniques for mapping cardiac electrical function and translational research related to arrhythmia management. This comprehensive review delves into various ML applications within the scope of this journal, organized into 3 parts. The first section provides a fundamental understanding of general ML principles and methodologies, serving as a foundational resource for readers interested in exploring ML applications in arrhythmia research. The second part offers an in-depth review of studies in arrhythmia and electrophysiology that leverage ML methodologies, showcasing the broad potential of ML approaches. Each subject is thoroughly outlined, accompanied by a review of notable ML research advancements. Finally, the review delves into the primary challenges and future perspectives surrounding ML-driven cardiac electrophysiology and arrhythmias research.

The Epidemiology of Errors in Data Capture, Management, and Analysis: A Scoping Review of Retracted Articles and Retraction Notices in Clinical and Translational Research

The Epidemiology of Errors in Data Capture, Management, and Analysis: A Scoping Review of Retracted Articles and Retraction Notices in Clinical and Translational Research

Quantitative analysis of the effects of brushing, flossing, and mouthrinsing on supragingival and subgingival plaque microbiota: 12-week clinical trial.

Translational microbiome research using next-generation DNA sequencing is challenging due to the semi-qualitative nature of relative abundance data. A novel method for quantitative analysis was applied in this 12-week clinical trial to understand the mechanical vs. chemotherapeutic actions of brushing, flossing, and mouthrinsing against the supragingival dental plaque microbiome. Enumeration of viable bacteria using vPCR was also applied on supragingival plaque for validation and on subgingival plaque to evaluate interventional effects below the gingival margin. Subjects with gingivitis were enrolled in a single center, examiner-blind, virtually supervised, parallel group controlled clinical trial. Subjects with gingivitis were randomized into brushing only (B); brushing and flossing (BF); brushing and rinsing with Listerine® Cool Mint® Antiseptic (BA); brushing and rinsing with Listerine® Cool Mint® Zero (BZ); or brushing, flossing, and rinsing with Listerine® Cool Mint® Zero (BFZ). All subjects brushed twice daily for 1min with a sodium monofluorophosphate toothpaste and a soft-bristled toothbrush. Subjects who flossed used unflavored waxed dental floss once daily. Subjects assigned to mouthrinses rinsed twice daily. Plaque specimens were collected at the baseline visit and after 4 and 12 weeks of intervention. Bacterial cell number quantification was achieved by adding reference amounts of DNA controls to plaque samples prior to DNA extraction, followed by shallow shotgun metagenome sequencing. 286 subjects completed the trial. The metagenomic data for supragingival plaque showed significant reductions in Shannon-Weaver diversity, species richness, and total and categorical bacterial abundances (commensal, gingivitis, and malodor) after 4 and 12 weeks for the BA, BZ, and BFZ groups compared to the B group, while no significant differences were observed between the B and BF groups. Supragingival plaque vPCR further validated these results, and subgingival plaque vPCR demonstrated significant efficacy for the BFZ intervention only. This publication reports on a successful application of a quantitative method of microbiome analysis in a clinical trial demonstrating the sustained and superior efficacy of essential oil mouthrinses at controlling dental plaque compared to mechanical methods. The quantitative microbiological data in this trial also reinforce the safety and mechanism of action of EO mouthrinses against plaque microbial ecology and highlights the importance of elevating EO mouthrinsing as an integral part of an oral hygiene regimen. The trial was registered on ClinicalTrials.gov on 31/10/2022. The registration number is NCT05600231.

Scan With Me (SWiM): A train-the-trainer program to upskill MRI personnel in low- and middle- income countries.

Access to magnetic resonance imaging (MRI) in low-and-middle-income countries (LMICs) remains among the poorest in the world. The lack of skilled MRI personnel exacerbates access gaps, reinforcing longstanding health disparities. The SWiM Program aims to sustainably create a network of highly skilled MRI technologists in LMICs who will facilitate the transfer of MRI knowledge and skills to their peers and contribute to implementation of highly valuable imaging protocols for impactful clinical and research use. The program introduces a case-based curriculum designed using a novel train-the-trainer approach, integrated with peer collaborative learning to upskill practicing MRI technologists in LMICs. The six-week curriculum uses the Teach-Try-Use approach, which combines self-paced didactic lectures covering the basics of MR image acquisition (teach) with hands-on expert-guided scanning experience (try), and implementation of protocols tailored to provide the best possible images on their infrastructures (use). Each program includes research translation skills training using an established advanced MRI technique relevant to LMICs. A pilot program focused on cardiac MRI (CMR) was conducted to assess the program's curriculum, delivery, and evaluation methods. Forty-three MRI technologists from 16 LMICs participated in the pilot CMR program and over the course of the training, implemented optimized CMR protocols that reduced acquisition times while improving image quality. The training resources and scanner-specific standardized protocols are published openly for public use on an online repository. In general, at the end of the program, learners reported considerable improvements in CMR knowledge and skills. All respondents to the program evaluation survey agreed to recommend the program to their colleagues, while 87% indicated interest in returning to help train others. The SWiM Program is the first masterclass in MRI acquisition for practicing imaging technologists in LMICS. The program holds the potential to help reduce disparities in MRI expertise and access. The support of the MRI community, imaging societies, and funding agencies will increase its reach and further its impact in democratizing MRI.

MicroRNA as a promising molecular biomarker in the diagnosis of breast cancer

Introduction: Breast cancer represents the most prevalent malignancy among women. Recent advancements in translational research have focused on the identification of novel biomarkers capable of providing valuable insights into patient outcomes. Furthermore, comprehensive investigations aimed at discovering novel miRNAs, unraveling their biological functions, and deciphering their target genes have significantly contributed to our understanding of the roles miRNAs play in tumorigenesis. Consequently, these investigations have facilitated the way for the development of miRNA-based approaches for breast cancer prognosis, diagnosis, and treatment. However, conducting a more extensive array of studies, particularly among diverse ethnic groups, is imperative to expand the scope of research and validate the significance of miRNAs. This study aimed to assess the expression patterns of circulating miRNAs in plasma as a prospective biomarker for breast cancer patients within a population primarily consisting of individuals from Black, Indigenous, and People of Color (BIPOC) communities.Methods: We evaluated 49 patients with breast cancer compared to 44 healthy women.Results and discussion: All miRNAs analyzed in the plasma of patients with breast cancer were downregulated. ROC curve analysis of miR-21 (AUC = 0.798, 95% CI: 0.682–0.914, p <0.0001), miR-1 (AUC = 0.742, 95% CI: 0.576–0.909, p = 0.004), miR-16 (AUC = 0.721, 95% CI: 0.581–0.861, p = 0.002) and miR-195 (AUC = 0.672, 95% CI: 0.553–0.792, p = 0.004) showed better diagnostic accuracy in discrimination of breast cancer patients in comparison with healthy women. miR-210, miR-21 showed the highest specificities values (97.3%, 94.1%, respectively). Following, miR-10b and miR-195 showed the highest sensitivity values (89.3%, and 77.8%, respectively). The panel with a combination of four miRNAs (miR-195 + miR-210 + miR-21 + miR-16) had an AUC of 0.898 (0.765–0.970), a sensitivity of 71.4%, and a specificity of 100.0%. Collectively, our results highlight the miRNA combination in panels drastically improves the results and showed high accuracy for the diagnosis of breast cancer displaying good sensitivity and specificity.

An Anticipatory Approach to Ethico-Legal Implications of Future Neurotechnology

This paper provides a justificatory rationale for recommending the inclusion of imagined future use cases in neurotechnology development processes, specifically for legal and policy ends. Including detailed imaginative engagement with future applications of neurotechnology can serve to connect ethical, legal, and policy issues potentially arising from the translation of brain stimulation research to the public consumer domain. Futurist scholars have for some time recommended approaches that merge creative arts with scientific development in order to theorise possible futures toward which current trends in technology development might be steered. Taking a creative, imaginative approach like this in the neurotechnology context can help move development processes beyond considerations of device functioning, safety, and compliance with existing regulation, and into an active engagement with potential future dynamics brought about by the emergence of the neurotechnology itself. Imagined scenarios can engage with potential consumer uses of devices that might come to challenge legal or policy contexts. An anticipatory, creative approach can imagine what such uses might consist in, and what they might imply. Justifying this approach also prompts a co-responsibility perspective for policymaking in technology contexts. Overall, this furnishes a mode of neurotechnology’s emergence that can avoid crises of confidence in terms of ethico-legal issues, and promote policy responses balanced between knowledge, values, protected innovation potential, and regulatory safeguards.

The Water Resources Rebound Effect Threatening the Achievement of Sustainable Development Goal 6 (SDG 6)

Coaction of climate change and human activities exerts a significant impact on the fate of water resources, provoking the rebound effect in water resources and threatening the achievement of SDG (sustainable development goal) 6. However, the mechanisms of interactions between this effect and SDG 6 and how to decrease this effect towards the achievement of SDG 6 are less known. In this paper, a water resources rebound effect (WRRE) model is integrated into a river basin sustainable development decision support system to simulate and project the interactions between the WRRE and SDG 6 under multiple combination scenarios. The results show that multiple drivers, including precipitation, technological advances, and ecological water flow, coaffect the WRRE, not the silo technology factor. The transfer fate of the saved water is a major root cause leading to the WRRE and harming the achievement of SDG 6, and the WRRE is positively correlated to SDG 6 overall, which, nevertheless, can sometimes be reversed by technological advances. Our outcomes indicate that decoupling SDG 6 from the WRRE can promote the achievement of SDG 6 and decrease the rebound effect, relying on holistic integration that couples climatic, socioeconomic, and behavioral interaction between SDG 6 and the WRRE and translation of scientific research into available decision-making information for strict scientific-research-based policy actions.

Geroscience: just another name or is there more to it?

The widespread use of the name 'geroscience' in the science of aging is sometimes met with a wary attitude by biogerontologists other than its inventors. Here, we provide an overview of its origin and evolution to assess what exactly it is and to discuss its theoretical and biological relationship to earlier movements of anti-aging medicine and biogerontology more generally. Geroscience posits that targeting aging may offer a cost-effective approach to improve late-life health in humans, and because aging is malleable in model organisms and what regulates this is sufficiently understood, the time is ripe for moving forward to translational and clinical research. The geroscience agenda has rebranded imagery of past traditions, yet the claim that therapies for human aging are ready or within the imminent future is contestable and on brand with tradition, even if biogerontology has made great progress in the past decades.

Speeding up Glioblastoma Cancer Research: Highlighting the Zebrafish Xenograft Model

Glioblastoma multiforme (GBM) is a very aggressive and lethal primary brain cancer in adults. The multifaceted nature of GBM pathogenesis, rising from complex interactions between cells and the tumor microenvironment (TME), has posed great treatment challenges. Despite significant scientific efforts, the prognosis for GBM remains very poor, even after intensive treatment with surgery, radiation, and chemotherapy. Efficient GBM management still requires the invention of innovative treatment strategies. There is a strong necessity to complete cancer in vitro studies and in vivo studies to properly evaluate the mechanisms of tumor progression within the complex TME. In recent years, the animal models used to study GBM tumors have evolved, achieving highly invasive GBM models able to provide key information on the molecular mechanisms of GBM onset. At present, the most commonly used animal models in GBM research are represented by mammalian models, such as mouse and canine ones. However, the latter present several limitations, such as high cost and time-consuming management, making them inappropriate for large-scale anticancer drug evaluation. In recent years, the zebrafish (Danio rerio) model has emerged as a valuable tool for studying GBM. It has shown great promise in preclinical studies due to numerous advantages, such as its small size, its ability to generate a large cohort of genetically identical offspring, and its rapid development, permitting more time- and cost-effective management and high-throughput drug screening when compared to mammalian models. Moreover, due to its transparent nature in early developmental stages and genetic and anatomical similarities with humans, it allows for translatable brain cancer research and related genetic screening and drug discovery. For this reason, the aim of the present review is to highlight the potential of relevant transgenic and xenograft zebrafish models and to compare them to the traditionally used animal models in GBM research.

The American College of Rheumatology White Paper: The Effects of Climate Change on Rheumatic Conditions - An Evolving Landscape and a Path Forward.

Increases in global temperatures and extreme weather events associated with climate change have complex yet poorly understood detrimental impacts on human health. We reviewed the current published literature on climate change-related effects and rheumatic conditions. To summarize our current understanding of the likely effects of climate change, including increased air pollution, on rheumatic disease, we searched the published, peer-reviewed English-language literature from January 2000-December 2022. Articles were reviewed by a team of rheumatologists and clinical and translational science researchers. Systematic review articles were not included but informed additional literature searches. After extensive examination and adjudication, 88 articles met inclusion criteria and were selected for review. Much of the epidemiologic investigations assessed associations between air pollution and increased risk of development of rheumatoid arthritis, anti-citrullinated protein antibodies, flares of gout and hospitalizations for systemic lupus erythematosus. Increased heat vulnerability was associated with higher odds of recurrent hospitalizations across rheumatic conditions. Mechanisms for observed associations are poorly understood but could include the effects of epigenetic changes, oxidative stress, and inflammatory cytokines. Studies had limitations including restricted geography and populations studied without focus on historically marginalized communities at highest risk for adverse effects from pollution and climate change, the relative lack of mechanistic evaluations, and most with only indirect links to climate change. To date, the published literature lacks studies that directly examine effects of climate change on rheumatic diseases. Collaborative translational and epidemiologic research is needed to enhance our understanding and awareness in this area.

A large-scale machine learning analysis of inorganic nanoparticles in preclinical cancer research.

Owing to their distinct physical and chemical properties, inorganic nanoparticles (NPs) have shown promising results in preclinical cancer therapy, but designing and engineering them for effective therapeutic purposes remains a challenge. Although a comprehensive database of inorganic NP research is not currently available, it is crucial for developing effective cancer therapies. In this context, machine learning (ML) has emerged as a transformative tool, but its adaptation to nanomedicine is hindered by inexistent or small datasets. Here we assembled a large database of inorganic NPs, comprising experimental datasets from 745 preclinical studies in cancer nanomedicine. Using descriptive statistics and explainable ML models we mined this database to gain knowledge of inorganic NP design patterns and inform future NP research for cancer treatment. Our analyses suggest that NP shape and therapy type are prominent features in determining in vivo efficacy, measured as a percentage of tumour reduction. Moreover, our database provides a large-scale open-access resource for discriminative ML that the broader nanotechnology community can utilize. Our work blueprints data mining for translational cancer research and offers evidence for standardizing NP reporting to accelerate and de-risk inorganic NP-based drug delivery, which may help to improve patient outcomes in clinical settings.

Laser Doppler Fluximetry in Cutaneous Vasculature: Methods for Data Analyses

Introduction: Acquisition of a deeper understanding of microvascular function across physiological and pathological conditions can be complicated by poor accessibility of the vascular networks and the necessary sophistication or intrusiveness of the equipment needed to acquire meaningful data. Laser Doppler fluximetry (LDF) provides a mechanism wherein investigators can readily acquire large amounts of data with minor inconvenience for the subject. However, beyond fairly basic analyses of erythrocyte perfusion (fluximetry) data within the cutaneous microcirculation (i.e., perfusion at rest and following imposed challenges), a deeper understanding of microvascular perfusion requires a more sophisticated approach that can be challenging for many investigators. Methods: This manuscript provides investigators with clear guidance for data acquisition from human subjects for full analysis of fluximetry data, including levels of perfusion, single- and multiscale Lempel-Ziv complexity (LZC) and sample entropy (SampEn), and wavelet-based analyses for the major physiological components of the signal. Representative data and responses are presented from a recruited cohort of healthy volunteers, and computer codes for full data analysis (MATLAB) are provided to facilitate efforts by interested investigators. Conclusion: It is anticipated that these materials can reduce the challenge to investigators integrating these approaches into their research programs and facilitate translational research in cardiovascular science.

The road less traveled: Developing pharmacist clinician-scientists through divergent training pathways.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. Professional organizations have emphasized the growing need for pharmacists to possess advanced research skills; however, there is a scarcity of training programs aimed at nurturing clinician-scientists. This report outlines 3 critical care-focused research programs, each offering a unique approach to training clinician-scientists. Limited resources and formalized programs are available to bridge the gap between the demand for and availability of skilled clinician-scientists. Several programs have stepped forward to share their experiences in establishing and executing training initiatives aimed at cultivating skilled clinician-scientists in the critical care practice space. Enhancing the development of clinician-scientists for clinical and translational research is necessary in the critical care clinical pharmacy community.

Characterization in the rat of the individual tendency to rely on alcohol to cope with distress and the ensuing vulnerability to drink compulsively

Abstract Only some vulnerable individuals who recreationally drink alcohol eventually develop the compulsive drinking pattern that characterizes alcohol use disorder. A new frontier in biomedical research lies in understanding the neurobehavioral mechanisms of this individual vulnerability, a necessary step towards developing novel effective therapeutic strategies. Translational research has been hindered by the lack of valid, reliable and robust approaches that enable the study of the influence of the reliance on alcohol to cope with stress or self-medicate negative emotional states on the subsequent transition to alcohol use disorder. We have therefore developed a behavioral task in the rat that enables the investigation of the neural and cellular basis of the exacerbation of the vulnerability to develop compulsive alcohol drinking by the use of alcohol to develop an adjunctive, anxiolytic, polydipsic drinking behavior in a schedule-induced polydipsia procedure. Hence, in our task, alcohol is introduced in the schedule-induced polydipsia context after several weeks of training with water so that rats are exposed to alcohol for the first time in a distressing context and learn to drink alcohol as a coping strategy. Capitalizing on this protocol, we have consistently been able to identify a subpopulation of rats that were unable to learn to cope with negative states by drinking water and relied on alcohol to do so. This maladaptive reliance on alcohol-drinking to cope with distress has been shown to be associated with an exacerbation of the subsequent transition to compulsive drinking. Furthermore, these vulnerable rats reached blood alcohol levels comparable to that of intoxication in humans, thereby developing two key features of alcohol use disorder, namely excessive alcohol intake and compulsive drinking. Altogether, this behavioral task provides a novel and unique tool for the investigation of the neurobehavioral mechanisms underlying the exacerbation of the individual vulnerability to developing compulsive alcohol drinking by the use of alcohol as a strategy to cope with distress, and for the evaluation of the efficacy of potential therapeutic strategies in a personalized medicine approach. This procedure, which focuses on an understudied but key factor of the development of alcohol use disorder, may become widely used as it benefits the fields of alcohol, emotion regulation and stress, the interest in which has substantially increased since the evidence of a profound exacerbation of alcohol use and alcohol-related negative consequences by the distress and social isolation engendered by the various measures implemented worldwide in response to the COVID-19 pandemic.

Refined movement analysis in the Staircase test reveals differential motor deficits in mouse models of stroke

Accurate assessment of post-stroke deficits is crucial in translational research. Recent advances in machine learning offer precise quantification of rodent motor behavior post-stroke, yet detecting lesion-specific upper extremity deficits remains unclear. Employing proximal middle cerebral artery occlusion (MCAO) and cortical photothrombosis (PT) in mice, we assessed post-stroke impairments via the Staircase test. Lesion locations were identified using 7 T-MRI. Machine learning was applied to reconstruct forepaw kinematic trajectories and feature analysis was achieved with MouseReach, a new data-processing toolbox. Lesion reconstructions pinpointed ischemic centers in the striatum (MCAO) and sensorimotor cortex (PT). Pellet retrieval alterations were observed, but were unrelated to overall stroke volume. Instead, forepaw slips and relative reaching success correlated with increasing cortical lesion size in both models. Striatal lesion size after MCAO was associated with prolonged reach durations that occurred with delayed symptom onset. Further analysis on the impact of selective serotonin reuptake inhibitors in the PT model revealed no clear treatment effects but replicated strong effect sizes of slips for post-stroke deficit detection. In summary, refined movement analysis unveiled specific deficits in two widely-used mouse stroke models, emphasizing the value of deep behavioral profiling in preclinical stroke research to enhance model validity for clinical translation.

Resurgence of destructive behavior following decreases in alternative reinforcement: A prospective analysis.

Basic and retrospective translational research has shown that the magnitude of resurgence is determined by the size of the decrease in alternative reinforcement, with larger decreases producing more resurgence. However, this finding has not been evaluated prospectively with a clinical population. In Experiment 1, five participants experienced a fixed progression of reinforcement schedule-thinning steps during treatment of their destructive behavior. Resurgence occurred infrequently across steps and participants, and when resurgence did occur, its clinical meaningfulness was often minimal. In Experiment 2, five new participants experienced these same schedule-thinning steps but in a counterbalanced order. Resurgence occurred most often and was generally largest with larger decreases in alternative reinforcement programmed earlier in the evaluation. Large decreases in alternative reinforcement may be more problematic clinically when they occur earlier in treatment. Whether larger transitions can be recommended in the clinic following the success of smaller ones will require additional research.

Efficient hepatocyte differentiation of primary human hepatocyte-derived organoids using three dimensional nanofibers (HYDROX) and their possible application in hepatotoxicity research

Human liver organoids are in vitro three dimensionally (3D) cultured cells that have a bipotent stem cell phenotype. Translational research of human liver organoids for drug discovery has been limited by the challenge of their low hepatic function compared to primary human hepatocytes (PHHs). Various attempts have been made to develop functional hepatocyte-like cells from human liver organoids. However, none have achieved the same level of hepatic functions as PHHs. We here attempted to culture human liver organoids established from cryopreserved PHHs (PHH-derived organoids), using HYDROX, a chemically defined 3D nanofiber. While the proliferative capacity of PHH-derived organoids was lost by HYDROX-culture, the gene expression levels of drug-metabolizing enzymes were significantly improved. Enzymatic activities of cytochrome P450 3A4 (CYP3A4), CYP2C19, and CYP1A2 in HYDROX-cultured PHH-derived organoids (Org-HYDROX) were comparable to those in PHHs. When treated with hepatotoxic drugs such as troglitazone, amiodarone and acetaminophen, Org-HYDROX showed similar cell viability to PHHs, suggesting that Org-HYDROX could be applied to drug-induced hepatotoxicity tests. Furthermore, Org-HYDROX maintained its functions for up to 35 days and could be applied to chronic drug-induced hepatotoxicity tests using fialuridine. Our findings demonstrated that HYDROX could possibly be a novel biomaterial for differentiating human liver organoids towards hepatocytes applicable to pharmaceutical research.