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Over the past 3 decades, a substantial number of studies were published with the purpose of improving the effectiveness and efficiency of rehabilitation clinical practice. Clinicians and researchers face considerable challenges in successfully implementing these research findings into routine clinical practice. Knowledge translation includes the synthesis, dissemination, exchange, and ethically sound application of knowledge to improve health, provide more effective health services and products, and strengthen the health care system. An aim of knowledge translation research is to identify strategies to accelerate implementation of evidence into practice. A recent citation analysis on a commonly used knowledge translation framework, the Knowledge-to-Action Framework, identified implementation activities performed in physical medicine and rehabilitation. Although this citation analysis describes activities performed and outcomes assessed while conducting knowledge translation projects, successful knowledge translation also requires a robust social and physical infrastructure. In this commentary, we offer several observations that appear related to the increased likelihood of implementation success. Funders, higher education institutions, health care payers, and health care organizations contribute to successful implementation and must embrace their roles in implementation. Administrators, clinicians, and consumers of physical medicine and rehabilitation also have essential roles in knowledge translation.

While commendable strides have been made in reducing smoking initiation and improving smoking cessation rates, current available smoking cessation treatment options are still only mildly efficacious and show substantial interindividual variability in their therapeutic responses. Therefore, the primary goal of preclinical research has been to further the understanding of the neural substrates and genetic influences involved in nicotine's effects and reassess potential drug targets. Pronounced advances have been made by investing in new translational approaches and placing more emphasis on bridging the gap between human and rodent models of dependence. Functional neuroimaging studies have identified key brain structures involved with nicotine-dependence phenotypes such as craving, impulsivity, withdrawal symptoms, and smoking cessation outcomes. Following up with these findings, rodent-modeling techniques have made it possible to dissect the neural circuits involved in these motivated behaviors and ascertain mechanisms underlying nicotine's interactive effects on brain structure and function. Likewise, translational studies investigating single-nucleotide polymorphisms (SNPs) within the cholinergic, dopaminergic, and opioid systems have found high levels of involvement of these neurotransmitter systems in regulating the reinforcing aspects of nicotine in both humans and mouse models. These findings and coordinated efforts between human and rodent studies pave the way for future work determining gene by drug interactions and tailoring treatment options to each individual smoker.

Disparities in urology are well-documented but less is known about the role of translational research within existing interventional models to address inequalities. In this narrative review, we utilize an accepted framework of the process of translational research in mitigating disparities to investigate current translational and interventional urologic programs that bridge the gap. Three established, disparity-focused urologic interventional programs were identified and are highlighted in depth. Finally, we extrapolate from these findings to provide 10 policy relevant implications to help move urologic disparities research from evidence synthesis to translational research.

Chronic pain is a leading cause of disability worldwide and its prevalence is likely to increase over the next decades. Treatment for chronic pain remains insufficient and therapeutical advances have not made comparable progress with that for many chronic disorders, thus amplifying the concern on the future burden of the disease. At the same time, and even after decades of intense research, the underlying pathophysiology of chronic pain remains minimally understood. We believe advancing our current understanding of chronic pain requires mechanistically explicit, hypothesis-driven, and clinically focused models. In this review we highlight some of the main findings over the last decades that have contributed to the present knowledge of brain mechanisms of chronic pain, and how such advances were possible due to a reverse translational research approach. We argue that this approach is essential in the chronic pain field, in order to generate new scientific hypotheses, probe physiological mechanisms, develop therapeutic strategies and translate findings back into promising human clinical trials.

International audience; Cardiotoxicity is a common side effect induced by cancer therapies, which increases the risk of long-term morbidity and mortality in cancer survivors. To date, the mechanism leading to this toxicity is still unclear, thus complicating cardiac safety assessment and predictive factor identification. The advances in technology, particularly regarding radiation therapy and constant development of novel antineoplastic agents, require urgent development of efficient preclinical models to detect drug cardiotoxicity. A myriad of empirical preclinical models have been used to investigate cardiotoxicity, though with limited success. Recently, multicellular spheroid models have gained attention by mimicking the in vivo microenvironment. The aim of this review is to focus on the most relevant preclinical models used to assess antineoplastic drug- and radiotherapy-related cardiotoxicities, with an overview on their current use. It also aims to discuss the possible directions of translational research in the cardio-oncology field.

Background Translational research is an ideology focussed on streamlining the transition of novel research into clinical practice to ultimately benefit populations. Central to this approach is overcoming barriers to research involvement and interdisciplinary collaboration. Identifying barriers has been the subject of several studies focused on communities with large academic hospitals. The Windsor-Essex region is currently built around community hospitals which have less of an emphasis on research, employ fewer physicians holding academic appointments and generally do not provide incentivised time for research and training. In this study, we surveyed clinicians and researchers working in Windsor-Essex to gain insight into barriers to translational research important to those working in smaller sized, community-based research networks. Methods Using an anonymous close-ended Qualtrics survey distributed via email, we surveyed faculty members from The University of Windsor and clinical care providers from Windsor-Essex (n = 68). This included 24 physicians, 14 allied health professionals, and 30 non-clinician researchers. Results Managing competing interests, lack of time, funding, infrastructure, and networks were identified by greater than 75% of participants as barriers to research involvement. 62% of physicians identified the lack of permanent post-graduate medical trainees as a barrier. Clinicians were consistently less experienced in research skills compared to others; particularly in publishing results and applying for funding (p Conclusions This study identifies several important barriers to translational research in Windsor-Essex and suggests that many motivated researchers are unhappy with their current involvement. These results will inform decision making in the research community of Windsor-Essex and provides insight for communities of similar size and research capacity. Ultimately, enabling the translation of clinical research in all communities is required to ensure equitable access to cutting edge care.

The field of cellular microbiology, rooted in the co-evolution of microbes and their hosts, studies intracellular pathogens and their manipulation of host cell machinery. In this review, we highlight emerging technologies and infection models that recently promoted opportunities in cellular microbiology. We overview the explosion of microscopy techniques and how they reveal unprecedented detail at the host-pathogen interface. We discuss the incorporation of robotics and artificial intelligence to image-based screening modalities, biochemical mapping approaches, as well as dual RNA-sequencing techniques. Finally, we describe chips, organoids and animal models used to dissect biophysical and in vivo aspects of the infection process. As our knowledge of the infected cell improves, cellular microbiology holds great promise for development of anti-infective strategies with translational applications in human health., Cellular microbiology is a field that combines the study of infection and cell biology. In this review, we highlight emerging technologies and infection models that recently transformed our understanding of the infected cell and may inspire future medicine.

GDC‐0334 is a novel small molecule inhibitor of transient receptor potential cation channel member A1 (TRPA1), a promising therapeutic target for many nervous system and respiratory diseases. The pharmacokinetic (PK) profile and pharmacodynamic (PD) effects of GDC‐0334 were evaluated in this first‐in‐human (FIH) study. A starting single dose of 25 mg was selected based on integrated preclinical PK, PD, and toxicology data following oral administration of GDC‐0334 in guinea pigs, rats, dogs, and monkeys. Human PK and PK‐PD of GDC‐0334 were characterized after single and multiple oral dosing using a population modeling approach. The ability of GDC‐0334 to inhibit dermal blood flow (DBF) induced by topical administration of allyl isothiocyanate (AITC) was evaluated as a target‐engagement biomarker. Quantitative models were developed iteratively to refine the parameter estimates of the dose‐concentration‐effect relationships through stepwise estimation and extrapolation. Human PK analyses revealed that bioavailability, absorption rate constant, and lag time increase when GDC‐0334 was administered with food. The inhibitory effect of GDC‐0334 on the AITC‐induced DBF biomarker exhibited a clear sigmoid‐Emax relationship with GDC‐0334 plasma concentrations in humans. This study leveraged emerging preclinical and clinical data to enable iterative refinement of GDC‐0334 mathematical models throughout the FIH study for dose selection in subsequent cohorts throughout the study. Study Highlights WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC? GDC‐0334 is a novel, small molecule TRPA1 inhibitor and a pharmacokinetic‐pharmacodynamic (PK‐PD) modeling strategy could be implemented in a systematic and step‐wise manner to build and learn from emerging data for early clinical development. WHAT QUESTION DID THIS STUDY ADDRESS? Can noncompartmental and population‐based analyses be used to describe the PK and PD characteristics of GDC‐0334 in preclinical and clinical studies? WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE? GDC‐0334 exposure generally increased with dose in rats, dogs, and monkeys. The starting dose (25 mg) in the clinical study was determined based on the preclinical data. GDC‐0334 exhibited linear PK in humans and the bioavailability was increased with food. The inhibitory effect of GDC‐0334 on dermal blood flow induced by the TRPA1 agonist allyl isothiocyanate in humans indicates a clear PK‐PD relationship. HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE? The models developed based on TRPA1 agonist‐induced dermal blood flow inhibition data can be used to predict PK‐PD relationships in future preclinical and clinical studies evaluating new drug entities that target TRPA1.

Due to the ongoing opioid epidemic, innovative scientific perspectives and approaches are urgently needed to reduce the unprecedented personal and societal burdens of nonmedical and recreational opioid use. One promising opportunity is to focus on the relationship between sleep deficiency and opioid use. In this review, we examine empirical evidence: (1) at the interface of sleep deficiency and opioid use, including hypothesized bidirectional associations between sleep efficiency and opioid abstinence; (2) as to whether normalization of sleep deficiency might directly or indirectly improve opioid abstinence (and vice versa); and (3) regarding mechanisms that could link improvements in sleep to opioid abstinence. Based on available data, we identify candidate sleep-restorative therapeutic approaches that should be examined in rigorous clinical trials.

Nociception and opioid antinociception in females are pliable processes, varying qualitatively and quantitatively over the reproductive cycle. Spinal estrogenic signaling via membrane estrogen receptors (mERs), in combination with multiple other signaling molecules [spinal dynorphin, kappa-opioid receptors (KOR), glutamate and metabotropic glutamate receptor 1 (mGluR(1))], appears to function as a master coordinator, parsing functionality between pronociception and antinociception. This provides a window into pharmacologically accessing intrinsic opioid analgesic/anti-allodynic systems. In diestrus, membrane estrogen receptor alpha (mERα) signals via mGluR(1) to suppress spinal endomorphin 2 (EM2) analgesia. Strikingly, in the absence of exogenous opioids, interfering with this suppression in a chronic pain model elicits opioid anti-allodynia, revealing contributions of endogenous opioid(s). In proestrus, robust spinal EM2 analgesia is manifest but this requires spinal dynorphin/KOR and glutamate-activated mGluR(1). Furthermore, spinal mGluR(1) blockade in a proestrus chronic pain animal (eliminating spinal EM2 analgesia) exacerbates mechanical allodynia, revealing tempering by endogenous opioid(s). A complex containing mu-opioid receptor, KOR, aromatase, mGluRs, and mERα are foundational to eliciting endogenous opioid anti-allodynia. Aromatase-mERα oligomers are also plentiful, in a central nervous system region-specific fashion. These can be independently regulated and allow estrogens to act intracellularly within the same signaling complex in which they are synthesized, explaining asynchronous relationships between circulating estrogens and central nervous system estrogen functionalities. Observations with EM2 highlight the translational relevance of extensively characterizing exogenous responsiveness to endogenous opioids and the neuronal circuits that mediate them along with the multiplicity of estrogenic systems that concomitantly function in phase and out-of-phase with the reproductive cycle.

Owing to clinical success of immune-checkpoint blockade, immunotherapy is becoming a cornerstone of modern oncology, and immuno-oncology is at the forefront of basic cancer research. This commentary outlines future opportunities for immuno-oncology modeling.

Laboratory mice have long been an invaluable tool in biomedical science and have made significant contributions in research into life-threatening diseases. However, the translation of research results from mice to humans often proves difficult due to the incomplete nature of laboratory animal-based research. Hence, there is increasing demand for complementary methods or alternatives to laboratory mice that can better mimic human physiological traits and potentially bridge the translational research gap. Under these circumstances, the natural/naturalized mice including “wild”, “dirty”, “wildling”, and “wilded” systems have been found to better reflect some aspects of human pathophysiology. Here, we discuss the pros and cons of the laboratory mouse system and contemplate how wild mice and wild microbiota are able to help in refining such systems to better mimic the real-world situation and contribute to more productive translational research.

Altering the human epigenome with gene-editing technology in attempt to treat a variety of diseases and conditions seems scientifically feasible. We explore some of the ethical and regulatory issues related to the clinical translation of human epigenetic editing arguing that such approaches should be considered akin to somatic therapies.

Heart failure is one of the leading causes of death worldwide. A stimulated heart undergoes either adaptive physiological hypertrophy, which can maintain a normal heart function, or maladaptive pathological remodeling, which can deteriorate heart function. These 2 kinds of remodeling often co-occur at the early stages of many heart diseases and have important effects on cardiac function. The Bcl2-associated athanogene 3 (BAG3) protein is highly expressed in the heart and has many functions. However, it is unknown how BAG3 is regulated and what its function is during physiological hypertrophy and pathological remodeling. We generated tamoxifen-induced, heart-specific heterozygous and homozygous BAG3 knockout mouse models (BAG3 protein level decreased by approximately 40% and 80% in the hearts after tamoxifen administration). BAG3 knockout models were subjected to swimming training or phenylephrine (PE) infusion to induce cardiac physiological hypertrophy and pathological remodeling. Neonatal rat ventricular cardiomyocytes (NRVCs) were used to study BAG3 functions and mechanisms in vitro. We found that BAG3 was upregulated in physiological hypertrophy and in pathological remodeling both in vivo and in vitro. Heterozygous or homozygous knockout BAG3 in mouse hearts and knockdown of BAG3 in the NRVCs blunted physiological hypertrophy and aggravated pathological remodeling, while overexpression of BAG3 promoted physiological hypertrophy and inhibited pathological remodeling in NRVCs. Mechanistically, BAG3 overexpression in NRVCs promoted physiological hypertrophy by activating the protein kinase B (AKT)/mammalian (or mechanistic) target of rapamycin (mTOR) pathway. BAG3 knockdown in NRVCs aggravated pathological remodeling through activation of the calcineurin/nuclear factor of activated T cells 2 (NFATc2) pathway. Because BAG3 has a dual role in cardiac remodeling, heart-specific regulation of BAG3 may be an effective therapeutic strategy to protect against deterioration of heart function and heart failure caused by many heart diseases.

Murine animal models are an established standard in translational research and provides a potential platform for studying heart valve disease. To date, studies on heart valve disease using murine models have been hindered by a lack of appropriate methodologies due to their small scale. In the present study, we developed a multi-scale, imaging-based approach to extract the functional structure and geometry for the murine heart valve. We chose the pulmonary valve (PV) to study, due to its importance in congenital heart valve disease. Excised pulmonary outflow tracts from eleven 1-year old C57BL/6J mice were fixed at 10, 20, and 30 mmHg to simulate physiological loading. Micro-computed tomography was used to reconstruct the 3D organ-level PV geometry, which was then spatially correlated with serial en-face scanning electron microscopy imaging to quantify local collagen fiber distributions. From the acquired volume renderings, we obtained the geometric descriptors of the murine PV under increasing transvalvular pressures, which demonstrated remarkable consistency. Results to date suggest that the preferred collagen orientation was predominantly in the circumferential direction, as in larger mammalian valves. The present study represents a first step in establishing organ-level murine models for the study of heart valve disease.

The gonadotropin-releasing hormone (GnRH) signaling pathway controls reproductive functions and cancer growth and progression. However, few studies investigated roles of genetic variants of GnRH pathway genes in survival of patients with non-small cell lung cancer (NSCLC). Therefore, we first evaluated associations between 22,528 single-nucleotide polymorphisms (SNPs) in 101 GnRH pathway genes and survival of 1185 NSCLC patients using a dataset from Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. We found 572 SNPs to be significantly associated with overall survival (OS) of NSCLC (P ≤ 0.05, Bayesian false discovery probability ≤0.80). We then validated these SNPs in another dataset with 984 NSCLC patients from the Harvard Lung Cancer Susceptibility Study. Finally, two independent SNPs (HBEGF rs4150236G>A and ITPR3 rs116454384C>T) remained significantly associated with NSCLC OS in the combined analysis with hazards ratios of 0.84 (95% confidence interval = 0.76–0.92, P = 0.0003) and 0.85 (0.78–0.94, 0.0012), respectively; their genetic score (the number of protective genotypes) was associated with a better OS and disease-specific survival (Ptrend = 0.0002 and 0.0001, respectively). Further expression quantitative trail loci analysis showed a significant correlation between ITPR3 rs116454384 T allele and an increased mRNA expression level in both whole blood and normal lung tissue, and high ITPR3 mRNA expression levels in tumors were associated with a better survival of NSCLC patients. Because ITPR3 mutations were rare in tumors, ITPR3 rs116454384C>T likely had an effect on cancer progression by regulating the gene expression. Therefore, genetic variants of HBEGF rs4150236G>A and ITPR3 rs116454384C>T may be predictors for NSCLC survival, but HBEGF rs4150236G>A functional relevance remains to be determined.

Retinoids play a pivotal role in adrenal development and differentiation. Recent clinical trials revealed therapeutic potential of both all-trans and 9-cis retinoic acid in patients with cortisol excess due to a pituitary ACTH-secreting adenoma and indicated that retinoids might act also on the adrenal. Aim of the present study was to evaluate the effect of 9-cis retinoic acid on adrenals from patients with ACTH-dependent Cushing’s syndrome. Adrenal specimens from six patients with Cushing’s disease were incubated with 10 nM–1 µM 9-cis retinoic acid with and without 10 nM ACTH. Cortisol secretion was measured by immunoassay and expression of genes involved in steroidogenesis as well as retinoic acid action were evaluated by real-time RT-PCR. Incubation with 10–100 nM 9-cis retinoic acid increased spontaneous cortisol secretion and expression of STAR and CYP17A. On the other hand, in wells treated with ACTH, 9-cis retinoic acid markedly diminished ACTH receptor upregulation and no stimulatory effect on cortisol secretion or steroidogenic enzyme synthesis was observed. ACTH itself increased ligand-induced retinoic acid receptor expression, possibly enhancing sensitivity to retinoic acid. Our findings indicate that the effect of 9-cis retinoic acid in presence of ACTH is distinct from unchallenged wells and support the hypothesis of a direct adrenal action in patients with Cushing’s disease.

Clinical observation and ex vivo studies have established a strong association between inflammation and postoperative atrial fibrillation (POAF). However, it is unclear whether the inflammatory phenotype is causally linked to this event or is an epiphenomenon, and it is not known which inflammatory meditators may increase susceptibility to POAF. The limitations of available animal models of spontaneous POAF (sPOAF) makes it difficult to select an experimental system. Here, we provide experimental and clinical evidence for mechanistic involvement of interleukin-6 (IL-6) in sPOAF. PHASE I: We established a mouse model of cardiac surgery with nonpaced sPOAF. IL-6 knockout mice were protected from sPOAF compared with wild-type mice. PHASE II: At 48 hours after surgery, the heart was separated into 6 regions and cultured. IL-6 was expressed in all regions, with highest abundance in the left atrium (LA). In PHASE III, we demonstrated that IL-6 in the LA elicited early profibrotic properties in atria via the pSTAT3/STAT3 signaling pathway and contributed to sPOAF. PHASE IV: In a translational prospective clinical study, we demonstrated that humans with POAF had a higher IL-6 concentration in pericardial drainage (PD). This study provides preliminary evidence of a causal relationship between IL-6 and POAF in a novel nonpaced sPOAF mouse model. IL-6 is a crucial prerequisite for eliciting profibrotic properties in cardiac myocytes via the pSTAT3 pathway during the early postoperative period, leading to an increased susceptibility to POAF. Measuring IL-6 in PD could be a new noninvasive biomarker for the clinical prediction of POAF.

Immunomodulatory medications are a mainstay of treatment for autoimmune diseases and malignancies. In addition to their direct effects on immune cells, these medications also impact the gut microbiota. Drug-induced shifts in commensal microbes can lead to indirect but important changes in the immune response. We performed a comprehensive literature search focusing on immunotherapy/microbe interactions. Immunotherapies were categorized into five subtypes based on their mechanisms of action: cell trafficking inhibitors, immune checkpoint inhibitors, immunomodulators, anti-proliferative drugs, and inflammatory cytokine inhibitors. Although no consistent relationships were observed between types of immunotherapy and microbiota, most immunotherapies were associated with shifts in specific colonizing bacterial taxa. The relationships between colonizing microbes and drug efficacy were not well-studied for autoimmune diseases. In contrast, the efficacy of immune checkpoint inhibitors for cancer was tied to the baseline composition of the gut microbiota. There was a paucity of high-quality data; existing data were generated using heterogeneous sampling and analytic techniques, and most studies involved small numbers of participants. Further work is needed to elucidate the extent and clinical significance of immunotherapy effects on the human microbiome.

Neutrophil extracellular traps (NETs) have been implicated in the pathogenesis of abdominal aortic aneurysms (AAAs). This study has addressed the notion that NET components might serve as AAA biomarkers or novel targets of AAA therapy. Thus, parameters of neutrophil activation and NET formation were measured in plasma. Their diagnostic marker value was explored in 41 AAA patients and 38 healthy controls. The NET parameter citrullinated histone H3 (citH3) was then validated in 63 AAA patients and 63 controls matched for cardiovascular disease. The prognostic marker potential was investigated in 54 observation periods of AAA growth over 6 months. NETs were further assessed in conditioned medium and sections of aortic tissue. CitH3 was found to be increased in blood (median 362 vs 304 ng/mL, P = 0.004) and aortic tissue (50 vs 1.5 ng/mg, P0.001) of AAA patients compared to healthy controls and accumulated in the intraluminal thrombus (629 ng/mg). The diagnostic potential of citH3 ranged at 0.705 area under the ROC curve (AUROC) and was validated with the independent sample set. Furthermore, plasma citH3 predicted AAA growth over the next 6 months (AUROC: 0.707, P = 0.015) and dropped significantly after surgical aneurysm repair. In an angiotensin II - based mouse model of experimental AAA, an inhibitor of histone citrullination was applied to block NET formation and AAA progression. Of note, further growth of an established aneurysm was prevented in mice treated with the NET inhibitor (P = 0.040). In conclusion, histone citrullination represents a promising AAA biomarker and potential therapeutic target to control disease progression.

Lung cancer screening detects early-stage cancers, but also a large number of benign nodules. Molecular markers can help in the lung cancer screening process by refining inclusion criteria or guiding the management of indeterminate pulmonary nodules. In this study, we developed a diagnostic model based on the quantification in plasma of complement-derived fragment C4c, cytokeratin fragment 21-1 (CYFRA 21-1) and C-reactive protein (CRP). The model was first validated in two independent cohorts, and showed a good diagnostic performance across a range of lung tumor types, emphasizing its high specificity and positive predictive value. We next tested its utility in two clinically relevant contexts: assessment of lung cancer risk and nodule malignancy. The scores derived from the model were associated with a significantly higher risk of having lung cancer in asymptomatic individuals enrolled in a computed tomography (CT)-screening program (OR = 1.89; 95% CI = 1.20–2.97). Our model also served to discriminate between benign and malignant pulmonary nodules (AUC: 0.86; 95% CI = 0.80–0.92) with very good specificity (92%). Moreover, the model performed better in combination with clinical factors, and may be used to reclassify patients with intermediate-risk indeterminate pulmonary nodules into patients who require a more aggressive work-up. In conclusion, we propose a new diagnostic biomarker panel that may dictate which incidental or screening-detected pulmonary nodules require a more active work-up.

Once thought of as arising from “junk DNA,” non-coding RNAs (ncRNAs) have emerged as key molecules in cellular processes and response to stress. From diseases such as cancer, coronary artery disease, and diabetes to the effects of ionizing radiation (IR), ncRNAs play important roles in disease progression and as biomarkers of damage. Non-coding RNAs regulate cellular processes by competitively binding DNA, mRNA, proteins, and other ncRNAs. Through these interactions, specific ncRNAs can modulate the radiosensitivity of cells and serve as diagnostic and prognostic biomarkers of radiation damage, whether from incidental exposure in radiotherapy or in accidental exposure scenarios. Analysis of RNA expression after radiation exposure has shown alterations not only in mRNAs, but also in ncRNAs (primarily miRNA, circRNA, and lncRNA), implying an important role in cellular stress response. Due to their abundance and stability in serum and other biofluids, ncRNAs also have great potential as minimally invasive biomarkers with advantages over current biodosimetry methods. Several studies have examined changes in ncRNA expression profiles in response to IR and other forms of oxidative stress. Furthermore, some studies have reported modulation of radiosensitivity by altering expression levels of these ncRNAs. This review discusses the roles of ncRNAs in the radiation response and evaluates prior research on ncRNAs as biomarkers of radiation damage. Future directions and applications of ncRNAs in radiation research are introduced, including the potential for a clinical ncRNA assay for assessing radiation damage and for the therapeutic use of RNA interference (RNAi).

Evidence suggests that intranasal application of oxytocin facilitates empathy and modulates its underlying neural processes, which are often impaired in individuals with autism spectrum disorders (ASD). Oxytocin has therefore been considered a promising candidate for the treatment of social difficulties in ASD. However, evidence linking oxytocin treatment to social behavior and brain function in ASD is limited and heterogeneous effects might depend on variations in the oxytocin-receptor gene (OXTR). We examined 25 male ASD patients without intellectual disability in a double-blind, cross-over, placebo-controlled fMRI-protocol, in which a single dose of oxytocin or placebo was applied intranasally. Patients performed three experiments in the MRI examining empathy for other’s physical pain, basic emotions, and social pain. All participants were genotyped for the rs53576 single-nucleotide polymorphism of the OXTR. Oxytocin increased bilateral amygdala responsiveness during the physical pain task for both painful and neutral stimuli. Other than that, there were no effects of oxytocin treatment. OXTR genotype did not significantly interact with oxytocin treatment. Our results contribute to the growing body of empirical literature suggesting heterogenous effects of oxytocin administration in ASD. To draw clinically relevant conclusions regarding the usefulness of oxytocin treatment, however, empirical studies need to consider methods of delivery, dose, and moderating individual factors more carefully in larger samples.

Chronic kidney disease (CKD) is a frequent comorbidity of aortic valve stenosis (AVS). Circulating chaperones have emerged as both effectors and prognostic markers for various diseases. We investigated the role of circulating chaperones in patients with severe AVS undergoing transcatheter aortic valve replacement (TAVR). In this observational cohort study, 159 consecutive patients undergoing TAVR were included and serum levels of Glucose-regulated protein 78 (GRP78) and heat shock protein 27 (HSP27) were measured by ELISA. The primary end point was defined as 1-year mortality. Patients with lower levels of circulating GRP78 (

BackgroundKnowledge translation (KT) theories, frameworks, and models (TFMs) can help guide and explain KT processes, and facilitate the evaluation of implementation outcomes. They play a critical role in conducting KT research and practice. Currently, little is known about the usage of TFMs in KT in Chinese healthcare settings. The aim of this scoping review is to identify which TFMs had been used for KT in healthcare settings in China, and how these TFMs were used.MethodsThe protocol for this scoping review is in accordance with the Arksey and O’Malley framework and further enhanced by the recommendations suggested by Levac et al. We will search 8 databases (4 Chinese and 4 English) to identify relevant studies. Four reviewers (2 for Chinese, 2 for English) will independently screen studies based on the eligibility criteria. The basic characteristic of studies and the TFMs utilization (i.e., what, why, and how) will be extracted. Methodological quality and reporting quality will be assessed using the Mixed Method Appraisal Tool (MMAT) and the Standards for Reporting Implementation Studies (StaRI) (or Standards for Quality Improvement Reporting Excellence, SQUIRE 2.0 for quality improvement studies), respectively. All the retrieved TFMs will be categorized into Nilsen’s classifications of TFMs for KT research. We will employ the qualitative content analysis approach to summarize how these TFMs have been used, and the rationale. A consultation will be conducted through a 1-h interactive virtual meeting with an expert panel of knowledge users.DiscussionBy conducting this scoping review, we expect to gain a comprehensive and in-depth understanding of why and how TFMs have been used in KT research and practice in China, and to identify gaps and provide recommendations for more efficient and meaningful use of TFMs in the future.Systematic review registrationThis review has been registered with the Open Science Framework (10.17605/OSF.IO/8NXAM).

Background To support evidence-informed education, health professions education (HPE) stakeholders encourage the creation and use of knowledge syntheses or reviews. However, it is unclear if these knowledge syntheses are ready for translation into educational practice. Without understanding the readiness, defined by three criteria—quality, accessibility and relevance—we risk translating weak evidence into practice and/or providing information that is not useful to educators. Methods A librarian searched Web of Science for knowledge syntheses, specifically Best Evidence in Medical Education (BEME) Guides. This meta-synthesis focuses on BEME Guides because of their explicit goal to inform educational practice and policy. Two authors extracted data from all Guides, guided by the 25-item STructured apprOach to the Reporting In healthcare education of Evidence Synthesis (STORIES). Results Forty-two Guides published in Medical Teacher between 1999 and 2017 were analyzed. No Guide met all STORIES criteria, but all included structured summaries and most described their literature search (n = 39) and study inclusion/exclusion (n = 40) procedures. Eleven Guides reported the presence of theory and/or educational principles, and eight consulted with external subject matter experts. Accessibility to each Guide’s full-text and supplemental materials was variable. Discussion For a subset of HPE knowledge syntheses, BEME Guides, this meta-synthesis identifies factors that support readiness and indicates potential areas of improvement, such as consistent access to Guides and inclusion of external subject matter experts on the review team. This analysis is useful for understanding the current readiness of HPE knowledge syntheses and informing future reviews to evolve so they can catalyze translation of evidence into educational practice.

Purpose Cancer remains to be a leading cause of death worldwide, accounting for almost 10 million deaths in 2018. Radiation therapy (RT) is a common nonsurgical treatment in the management of patients with cancer that reduces disease recurrence and improves overall survival. However, preclinical RT modeling for accelerated bench-to-bedside translation of combination therapies is largely missing. While genetically engineered mouse models (GEMM) faithfully recapitulate human disease, conventional linear particle accelerator systems, commonly utilized in clinical settings, are not suited for state-of-the-art, image-guided targeted RT (IGRT) of these murine autochthonous tumors. Thus, we employed the CyberKnife (Accuray) platform for IGRT of GEMM-derived non-small cell lunger cancer (NSCLC) lesions. The CyberKnife (CK) is a stereotactic radiosurgery system (SRS) delivering high-dose RT precisely to the target area with minimal damage to the surrounding tissues based on intra-fraction image-guidance. Material and methods GEMM-derived NSCLC flank tumors driven by oncogenic Kras (KrasLSL-G12D/+) and deletion of Tp53 (Trp53fl/fl) were irradiated using the CK RT platform. We applied IGRT of 2, 4, 6, and 8 Gy using field sizes of 5 to 12.5 mm to average gross tumor volumes (GTV) of 0.9 cm3 (minimal 0.03 cm3) using Xsight Spine Tracking (Accuray) spine-based tumor localization. Results We found that a 0 mm planning target volume (PTV) margin is sufficient for IGRT of murine tumors using the CK. Furthermore, we analyzed the impact of CK-mediated IGRT on tumor infiltrating leukocytes by flow cytometry. We observed that higher RT doses (6-8 Gy) decreased absolute cell numbers of lymphocytes and myeloid cells by approximately half compared to low doses (2-4 Gy) or mock treated tumors within one hour, but even with low dose RT (2 Gy) tumor infiltrating leukocytes (TIL) were found to be reduced after 8 to 24 hours and recovered partly after 3 days. Conclusion In summary, we here demonstrate that the CK RT system allows for targeted IGRT of murine tumors with high precision and thus constitutes a novel promising platform for translational mouse RT studies, particularly performed in a longitudinal multimodal manner.

With rates of psychiatric illnesses such as depression continuing to rise, additional preclinical models are needed to facilitate translational neuroscience research. In the current study, the raccoon (Procyon lotor) was investigated due to its similarities with primate brains, including comparable proportional neuronal densities, cortical magnification of the forepaw area, and cortical gyrification. Specifically, we report on the cytoarchitectural characteristics of raccoons profiled as high, intermediate, or low solvers in a multi-access problem-solving task. Isotropic fractionation indicated that high-solvers had significantly more cells in the hippocampus (HC) than the other solving groups; further, a nonsignificant trend suggested that this increase in cell profile density was due to increased non-neuronal (e.g., glial) cells. Group differences were not observed in the cellular density of the somatosensory cortex. Thionin-based staining confirmed the presence of von Economo neurons (VENs) in the frontoinsular (FI) cortex, although no impact of solving ability on VEN cell profile density levels was observed. Elongated fusiform cells were quantified in the hippocampus dentate gyrus where high-solvers were observed to have higher levels of this cell type than the other solving groups. In sum, the current findings suggest that varying cytoarchitectural phenotypes contribute to cognitive flexibility. Additional research is necessary to determine the translational value of cytoarchitectural distribution patterns on adaptive behavioral outcomes associated with cognitive performance and mental health. This article is protected by copyright. All rights reserved.

Traumatic brain injury (TBI) is a leading cause of death and disability. Yet, despite immense research efforts, treatment options remain elusive. Translational failures in TBI are often attributed to the heterogeneity of the TBI population and limited methods to capture these individual variabilities. Advances in machine learning (ML) have the potential to further personalized treatment strategies and better inform translational research. However, the use of ML has yet to be widely assessed in pre-clinical neurotrauma research, where data are strictly limited in subject number. To better establish ML's feasibility, we utilized the fluid percussion injury (FPI) portion of the rich, rat data set collected by Operation Brain Trauma Therapy (OBTT), which tested multiple pharmacological treatments. Previous work has provided confidence that both unsupervised and supervised ML techniques can uncover useful insights from this OBTT pre-clinical research data set. As a proof-of-concept, we aimed to better evaluate the multi-variate recovery profiles afforded by the administration of nine different experimental therapies. We assessed supervised pairwise classifiers trained on a pre-processed data set that incorporated metrics from four feature groups to determine their ability to correctly identify specific drug treatments. In all but one of the possible pairwise combinations of minocycline, levetiracetam, erythropoietin, nicotinamide, and amantadine, the baseline was outperformed by one or more supervised classifiers, the exception being nicotinamide versus amantadine. Further, when the same methods were employed to assess different doses of the same treatment, the ML classifiers had greater difficulty in understanding which treatment each sample received. Our data serve as a critical first step toward identifying optimal treatments for specific subgroups of samples that are dependent on factors such as types and severity of traumatic injuries, as well as informing the prediction of therapeutic combinations that may lead to greater treatment effects than individual therapies.

Atrial fibrillation (AF) is the most common sustained clinical arrhythmia, with a lifetime incidence of up to 37%, and is a major contributor to population morbidity and mortality. Important components of AF management include control of cardiac rhythm, rate, and thromboembolic risk. In this narrative review article, we focus on rhythm-control therapy. The available therapies for cardiac rhythm control include antiarrhythmic drugs and catheter-based ablation procedures; both of these are presently neither optimally effective nor safe. In order to develop improved treatment options, it is necessary to use preclinical models, both to identify novel mechanism-based therapeutic targets and to test the effects of putative therapies before initiating clinical trials. Extensive research over the past 30 years has provided many insights into AF mechanisms that can be used to design new rhythm-maintenance approaches. However, it has proven very difficult to translate these mechanistic discoveries into clinically applicable safe and effective new therapies. The aim of this article is to explore the challenges that underlie this phenomenon. We begin by considering the basic problem of AF, including its clinical importance, the current therapeutic landscape, the drug development pipeline, and the notion of upstream therapy. We then discuss the currently available preclinical models of AF and their limitations, and move on to regulatory hurdles and considerations and then review industry concerns and strategies. Finally, we evaluate potential paths forward, attempting to derive insights from the developmental history of currently used approaches and suggesting possible paths for the future. While the introduction of successful conceptually innovative new treatments for AF control is proving extremely difficult, one significant breakthrough is likely to revolutionize both AF management and the therapeutic development landscape.

Immunotherapy has revolutionized cancer treatment, however, not all tumor types and patients are completely responsive to this approach. Establishing predictive pre‐clinical models would allow for more accurate and practical immunotherapeutic drug development. Mouse models are extensively used as in vivo system for biomedical research. However, due to the significant differences between rodents and human, it is impossible to translate most of the findings from mouse models to human. Pharmacological development and advancing personalized medicine using patient‐derived xenografts relies on producing mouse models in which murine cells and genes are substituted with their human equivalent. Humanized mice (HM) provide a suitable platform to evaluate xenograft growth in the context of a human immune system. In this review, we discussed recent advances in the generation and application of HM models. We also reviewed new insights into the basic mechanisms, pre‐clinical evaluation of onco‐immunotherapies, current limitations in the application of these models as well as available improvement strategies. Finally, we pointed out some issues for future studies., Establishing predictive pre‐clinical models leads toward more accurate and practical immunotherapeutic development. Humanized mice (HM) provide a suitable platform to discern human‐specific disease pathogenesis and evaluate an array of novel therapeutics. This review discusses recent progresses in the production and deployment of HM in the study of cancer immunotherapy.

Functional magnetic resonance imaging (fMRI) has significant potential to evaluate changes in brain network activity after traumatic brain injury (TBI) and enable early prognosis of potential functional (e.g., motor, cognitive, behavior) deficits. In this study, resting-state and task-based fMRI (rs- and tb-fMRI) were utilized to examine network changes in a pediatric porcine TBI model that has increased predictive potential in the development of novel therapies. rs- and tb-fMRI were performed one day post-TBI in piglets. Activation maps were generated using group independent component analysis (ICA) and sparse dictionary learning (sDL). Activation maps were compared to pig reference functional connectivity atlases and evaluated using Pearson spatial correlation coefficients and mean ratios. Nonparametric permutation analyses were used to determine significantly different activation areas between the TBI and healthy control groups. Significantly lower Pearson values and mean ratios were observed in the visual, executive control, and sensorimotor networks for TBI piglets compared to controls. Significant differences were also observed within several specific individual anatomical structures within each network. In conclusion, both rs- and tb-fMRI demonstrate the ability to detect functional connectivity disruptions in a translational TBI piglet model, and these disruptions can be traced to specific affected anatomical structures.

The mouse is the pre-eminent model organism for studies of mammalian gene function and has provided an extraordinarily rich range of insights into basic genetic mechanisms and biological systems. Over several decades, the characterization of mouse mutants has illuminated the relationship between gene and phenotype, providing transformational insights into the genetic bases of disease. However, if we are to deliver the promise of genomic and precision medicine, we must develop a comprehensive catalogue of mammalian gene function that uncovers the dark genome and elucidates pleiotropy. Advances in large-scale mouse mutagenesis programmes allied to high-throughput mouse phenomics are now addressing this challenge and systematically revealing novel gene function and multi-morbidities. Alongside the development of these pan-genomic mutational resources, mouse genetics is employing a range of diversity resources to delineate gene–gene and gene–environment interactions and to explore genetic context. Critically, mouse genetics is a powerful tool for assessing the functional impact of human genetic variation and determining the causal relationship between variant and disease. Together these approaches provide unique opportunities to dissect in vivo mechanisms and systems to understand pathophysiology and disease. Moreover, the provision and utility of mouse models of disease has flourished and engages cumulatively at numerous points across the translational spectrum from basic mechanistic studies to pre-clinical studies, target discovery and therapeutic development.

Research in schizophrenia (SZ) emphasizes the need for new therapeutic approaches based on antioxidant/anti-inflammatory compounds and psycho-social therapy. A hallmark of SZ is a dysfunction of parvalbumin-expressing fast-spiking interneurons (PVI), which are essential for neuronal synchrony during sensory/cognitive processing. Oxidative stress and inflammation during early brain development, as observed in SZ, affect PVI maturation. We compared the efficacy of N-acetyl-cysteine (NAC) and/or environmental enrichment (EE) provided during juvenile and/or adolescent periods in rescuing PVI impairments induced by an additional oxidative insult during childhood in a transgenic mouse model with gluthation deficit (Gclm KO), relevant for SZ. We tested whether this rescue was promoted by the inhibition of MMP9/RAGE mechanism, both in the mouse model and in early psychosis (EP) patients, enrolled in a double-blind, randomized, placebo-controlled clinical trial of NAC supplementation for 6 months. We show that a sequential combination of NAC+EE applied after an early-life oxidative insult recovers integrity and function of PVI network in adult Gclm KO, via the inhibition of MMP9/RAGE. Six-month NAC treatment in EP patients reduces plasma sRAGE in association with increased prefrontal GABA, improvement of cognition and clinical symptoms, suggesting similar neuroprotective mechanisms. The sequential combination of NAC+EE reverses long-lasting effects of an early oxidative insult on PVI/perineuronal net (PNN) through the inhibition of MMP9/RAGE mechanism. In analogy, patients vulnerable to early-life insults could benefit from a combined pharmacological and psycho-social therapy.

A citation map connecting patents to biomedical publications provides insights that can be used to better evaluate productivity, diversity and translational impact.

Visualization and quantification of the skin microvasculature are important for studying the health of the human microcirculation. We correlated structural and pathophysiological changes of the dermal capillary-level microvasculature with age and blood pressure by using the reactive hyperemia optical coherence tomography angiography (RH-OCT-A) technique and evaluated both conventional OCT-A and the RH-OCT-A method as non-invasive imaging alternatives to histopathology. This observational pilot study acquired OCT-A and RH-OCT-A images of the dermal microvasculature of 13 young and 12 old healthy Caucasian female subjects. Two skin biopsies were collected per subject for histological analysis. The dermal microvasculature in OCT-A, RH-OCT-A, and histological images were automatically quantified and significant indications of vessel rarefaction in both old subjects and subjects with high blood pressure were observed by RH-OCT-A and histopathology. We showed that an increase in dermal microvasculature perfusion in response to reactive hyperemia was significantly lower in high blood pressure subjects compared to normal blood pressure subjects (117% vs. 229%). These results demonstrate that RH-OCT-A imaging holds functional information of the microvasculature with respect to physiological factors such as age and blood pressure that may help to monitor early disease progression and assess overall vascular health. Additionally, our results suggest that RH-OCT-A images may serve as a non-invasive alternative to histopathology for vascular analysis.

Background There is general scarcity of research on key elements of implementation processes and the factors which impact implementation success. Implementation of healthcare interventions is a complex process. Tools to support implementation can facilitate this process and improve effectiveness of the interventions and clinical outcomes. Understanding the impact of implementation support tools is a critical aspect of this process. The objective of this study was to solicit knowledge and agreement from relevant implementation science and knowledge translation healthcare experts in order to develop a process model of key elements in the implementation process. Methods A two round, modified Delphi study involving international experts in knowledge translation and implementation (researchers, scientists, professors, decision-makers) was conducted. Participants rated and commented on all aspects of the process model, including the organization, content, scope, and structure. Delphi questions rated at 75% agreement or lower were reviewed and revised. Qualitative comments supported the restructuring and refinement. A second-round survey followed the same process as Round 1. Results Fifty-four experts participated in Round 1, and 32 experts participated in Round 2. Twelve percent (n = 6) of the Round 1 questions did not reach agreement. Key themes for revision and refinement were: stakeholder engagement throughout the process, iterative nature of the implementation process; importance of context; and importance of using guiding theories or frameworks. The process model was revised and refined based on the quantitative and qualitative data and reassessed by the experts in Round 2. Agreement was achieved on all items in Round 2 and the Delphi concluded. Additional feedback was obtained regarding terminology, target users and definition of the implementation process. Conclusions High levels of agreement were attained for all sub-domains, elements, and sub-elements of the Implementation Process Model. This model will be used to develop an Implementation Support Tool to be used by healthcare providers to facilitate effective implementation and improved clinical outcomes.

The ISSCR's revised Guidelines for Stem Cell Research and Clinical Translation reflect the organization's commitment to opposing premature commercialization of stem cell-based interventions and supporting the development of products that meet stringent ethical, scientific, and regulatory standards. The Guidelines contain five important new recommendations concerning clinical translation of stem cell products.

Remote ischemic conditioning (RIC) has well‐established cardioprotective effects in preclinical studies and promising results in preclinical stroke research. Effective translation from preclinical studies to clinical trials has yet to be accomplished, perhaps because of the use of multiple applications of RIC (e.g., pre‐, per‐, or post‐conditioning) in preclinical studies by both invasive and non‐invasive protocols, some of which not clinically applicable. Our systematic review conformed to PRISMA guidelines and addressed differences in clinically relevant RIC applications and outcomes between preclinical and clinical studies. We retrieved a total of 30 studies (8 human; 22 animal) that met the inclusion criteria of testing clinically relevant procedures; namely, non‐invasive and per‐ or post‐conditioning protocols. Per‐conditioning was applied in 6 animal and 3 human studies, post‐conditioning was applied in 16 animal and 5 human studies, and both conditioning methods were applied in 2 animal studies. Application of RIC varied between human and animal studies regarding initiation, duration, repetition, and number of limbs included. Study designs did not systematically apply blinding, randomization, or placebo controls. On only a few occasions did preclinical studies include animals with clinically relevant comorbidities. Clinical trials were challenged by not completing the intended number of RIC cycles or addressing this deficit in the data analysis. Consistency and transferability of methods used for positive animal studies and subsequent human studies are essential for the optimal translation of results. Consensus on preclinical and clinical RIC procedures should be reached for a full understanding of the possible beneficial effects of RIC treatment in stroke.

The National Institutes of Health (NIH) has prioritized efforts to increase diversity in the biomedical research workforce. NIH-funded institutional career development awards may serve as one mechanism to facilitate these efforts. In 2013, the Duke University KL2 program, an internal career development program funded by the National Center for Advancing Translational Sciences, set a goal to increase the number of investigators from underrepresented racial and ethnic groups (UREGs) to ≥ 50% of KL2 awardees. From 2013 to 2019, 133 KL2 applications were received, 38% from UREG investigators. Of the 21 scholars selected, 10 (47.6%) were UREG investigators; all were Black/African American. This represents a threefold increase in the proportion of UREG applications and a sixfold increase in the proportion of UREG KL2 scholars compared with Duke's previous KL2 cycles (2003-2012), during which only 13% of applicants and 8.3% of funded scholars were UREGs. Of the 12 KL2 scholars (7 UREG) who completed the program, 5 have received NIH funding as principal investigators of an external K award or R01, and 4 of them are UREG investigators; this constitutes a post-KL2 NIH funding success rate of 57% (4/7) for UREG scholars. Achieving this programmatic priority was facilitated by institutional support, clear communication of goals to increase the proportion of UREG KL2 awardees, and intentional strategies to identify and support applicants. Strategies included targeted outreach to UREG investigators, partnerships with other institutional entities, structured assistance for investigators with preparing their applications, and a KL2 program structure addressing common barriers to success for UREG investigators, such as lack of consistent mentorship, protected research time, and peer support. The authors' experience suggests that KL2 and other internal career development programs may represent a scalable, national strategy to increase diversity in the biomedical research workforce.

There has been an exponential growth of artificial intelligence (AI) and machine learning (ML) publications aimed at advancing our understanding of atrial fibrillation (AF), which has been mainly driven by the confluence of two factors: the advances in deep neural networks (DeepNNs) and the availability of large, open access databases. It is observed that most of the attention has centred on applying ML for dvsetecting AF, particularly using electrocardiograms (ECGs) as the main data modality. Nearly a third of them used DeepNNs to minimize or eliminate the need for transforming the ECGs to extract features prior to ML modelling; however, we did not observe a significant advantage in following this approach. We also found a fraction of studies using other data modalities, and others centred in aims, such as risk prediction, AF management, and others. From the clinical perspective, AI/ML can help expand the utility of AF detection and risk prediction, especially for patients with additional comorbidities. The use of AI/ML for detection and risk prediction into applications and smart mobile health (mHealth) technology would enable ‘real time’ dynamic assessments. AI/ML could also adapt to treatment changes over time, as well as incident risk factors. Incorporation of a dynamic AI/ML model into mHealth technology would facilitate ‘real time’ assessment of stroke risk, facilitating mitigation of modifiable risk factors (e.g. blood pressure control). Overall, this would lead to an improvement in clinical care for patients with AF., Graphical Abstract

In an analysis of randomized trials, use of efavirenz for treatment of human immunodeficiency virus (HIV) infection was associated with increased suicidal thoughts/behaviors. However, analyses of observational data have found no evidence of increased risk. To assess whether population differences might explain this divergence, we transported the effect of efavirenz use from these trials to a specific target population. Using inverse odds weights and multiple imputation, we transported the effect of efavirenz on suicidal thoughts/behaviors in these randomized trials (participants were enrolled in 2001–2007) to a trials-eligible cohort of US adults initiating antiretroviral therapy while receiving HIV clinical care at medical centers between 1999 and 2015. Overall, 8,291 cohort participants and 3,949 trial participants were eligible. Prescription of antidepressants (19% vs. 13%) and injection drug history (16% vs. 10%) were more frequent in the cohort than in the trial participants. Compared with the effect in trials, the estimated hazard ratio for efavirenz on suicidal thoughts/behaviors was attenuated in our target population (trials: hazard ratio (HR) = 2.3 (95% confidence interval (CI): 1.2, 4.4); transported: HR = 1.8 (95% CI: 0.9, 4.4)), whereas the incidence rate difference was similar (trials: HR = 5.1 (95% CI: 1.6, 8.7); transported: HR = 5.4 (95% CI: −0.4, 11.4)). In our target population, there was greater than 20% attenuation of the hazard ratio estimate as compared with the trials-only estimate. Transporting results from trials to a target population is informative for addressing external validity.

The purpose of the current pilot study was to determine if 12 weeks of increased physical activity improved cognitive function in individuals with mild cognitive impairment (MCI). Participants used commercial wearable technology to objectively measure daily steps. Participants wore an activity tracker for approximately 12 hours per day and received telephone support every 2 weeks. The Montreal Cognitive Assessment (MoCA) was used to measure pre/posttest cognitive function. Increased step count was positively correlated with improvement in cognitive function with a moderate effect size (Pearson's r = 0.55; p = 0.04); 5,396 steps per day was the decision boundary for MoCA score improvement. Increased physical activity over 12 weeks improved cognitive function in individuals with MCI. It is feasible for individuals with MCI to wear an activity tracker on a daily basis. [ Journal of Gerontological Nursing, 47 (5), 14–18.]

Background A large evidence-practice gap exists regarding provision of nutrition to patients following surgery. The aim of this study was to evaluate the processes supporting the implementation of an intervention designed to improve the timing and adequacy of nutrition following bowel surgery. Methods A mixed-method pilot study, using an integrated knowledge translation (iKT) approach, was undertaken at a tertiary teaching hospital in Australia. A tailored, multifaceted intervention including ten strategies targeted at staff or patients were co-developed with knowledge users at the hospital and implemented in practice. Process evaluation outcomes included reach, intervention delivery and staffs’ responses to the intervention. Quantitative data, including patient demographics and surgical characteristics, intervention reach, and intervention delivery were collected via chart review and direct observation. Qualitative data (responses to the intervention) were sequentially collected from staff during one-on-one, semi-structured interviews. Quantitative data were summarized using median (IQR), mean (SD) or frequency(%), while qualitative data were analysed using content analysis. Results The intervention reached 34 patients. Eighty-four percent of nursing staff received an awareness and education session, while 0% of medical staff received a formal orientation or awareness and education session, despite the original intention to deliver these sessions. Several strategies targeted at patients had high fidelity, including delivery of nutrition education (92%); and prescription of oral nutrition supplements (100%) and free fluids immediately post-surgery (79%). Prescription of a high energy high protein diet on postoperative day one (0%) and oral nutrition supplements on postoperative day zero (62%); and delivery of preoperative nutrition handout (74%) and meal ordering education (50%) were not as well implemented. Interview data indicated that staff regard nutrition-related messages as important, however, their acceptance, awareness and perceptions of the intervention were mixed. Conclusions Approximately half the patient-related strategies were implemented well, which is likely attributed to the medical and nursing staff involved in intervention design championing these strategies. However, some strategies had low delivery, which was likely due to the varied awareness and acceptance of the intervention among staff on the ward. These findings suggest the importance of having buy-in from all staff when using an iKT approach to design and implement interventions.

Context Translational research in uro-oncology depends on the availability of high-quality biospecimens and associated data to advance precision medicine and improve clinical outcomes. Procurement, storage, and annotation of these specimens represent critical steps towards this end. Objective To review best-practice experiences gained via the McCain GU BioBank, a repository of more than 750 000 biospecimens obtained from more than 16 000 patients attending clinics at the University Health Network in Toronto, Canada. Evidence acquisition The review summarizes our experiences at a large single-institution genitourinary oncology biorepository. Evidence synthesis Key findings are placed in the context of emerging trends in genitourinary oncology, with a focus on integration of molecular profiling and clinical data with traditional biorepository management. Proposed approaches provide high-quality biospecimens with comprehensive and reliable clinical data that can fuel innovation and discovery in research. Conclusions Biorepositories are vital for improving clinical outcomes and advancing personalized medicine. High-quality biospecimens and their associated clinical data are crucial for validation of biomarkers in oncology. Efforts to procure, store, and annotate clinical specimens represent critical steps in translational research. Elements such as biobank size, biospecimen types, disease cohorts, predetermined collection protocols, broad informed consent, sample handling and storage protocols, and available infrastructure directly influence the effectiveness and capacity of a biobank. Patient summary Biorepositories, or biobanks, are facilities that store biospecimens such as blood, urine, or tissue (usually collected from humans) for use in research. Biobanks have become an important resource in medical research, as they provide high-quality specimens to support different types of contemporary research such as genomics, biomarker discovery, and personalized medicine. Clinical management and treatment of genitourinary cancers, such as prostate, kidney, and bladder cancers, are particularly suited for biomarker research. The provision of biospecimens and their associated clinical data have become crucial for validation of biomarkers in these cancers.

Recent advancements in cancer biology, microbiology, and bioengineering have spurred the development of engineered live biotherapeutics for targeted cancer therapy. In particular, natural tumor-targeting and probiotic bacteria have been engineered for controlled and sustained delivery of anticancer agents into the tumor microenvironment (TME). Here, we review the latest advancements in the development of engineered bacteria for cancer therapy and additional engineering strategies to potentiate the delivery of therapeutic payloads. We also explore the use of combination therapies comprising both engineered bacteria and conventional anticancer therapies for addressing intratumor heterogeneity. Finally, we discuss prospects for the development and clinical translation of engineered bacteria for cancer prevention and treatment.

Rectal cancer remains a challenging disease to treat. Therapy for locally advanced rectal cancer (LARC), the most frequent presentation, has evolved to include a multimodal approach of radiation, chemotherapy, and surgery. While this approach improves local disease control, the distant recurrence rate is nearly 30% and treatment-related morbidity is substantial, thus underscoring the need for new therapeutic approaches with better efficacy and lower side effects. Immunotherapy could potentially fill this need, but its promise is not yet realized in rectal cancer. In this translational science review, we address what is known about how cytotoxic therapies shape rectal cancer immunity and potentially prime the tumor microenvironment for response to immune checkpoint inhibitors and other immunotherapies. We also address the role of current immunotherapies in colorectal cancer and highlight where novel immunotherapy approaches are currently being evaluated in LARC. Finally, we address important future directions in LARC immunotherapy including the need to define optimal therapeutic sequencing, predictive biomarkers, strategies to limit treatment-related side effects and the potential of gut microbiome manipulation to improve outcomes. In summary, this review provides a framework to guide future research and inform immunotherapy trial design so as to advance rectal cancer care.

International audience; In 2017, the Food and Drug Administration published a safety recommendation to limit the exposure to general anesthesia as much as possible below the age of three. Indeed, several preclinical and clinical studies have questioned the possible toxicity of general anesthesia on the developing brain. Since then, recent clinical studies tried to mitigate this alarming issue. What is true, what is false? Contrary to some perceptions, the debate is not over yet. Only stronger translational research will allow scientists to provide concrete answers to this public health issue. In this review, we will provide and discuss the more recent data in this field, including the point of view of preclinical researchers, neuropsychologists and pediatric anesthesiologists. Through translational research, preclinical researchers have more than ever a role to play to better understand and identify long-term effects of general anesthesia for pediatric surgery on brain development in order to minimize it.

Objectives The pathology report serves as a crucial communication tool among a number of stakeholders. It can sometimes be challenging to understand. A communication barrier exists among pathologists, other clinicians, and patients when interpreting the pathology report, leaving both clinicians and patients less empowered when making treatment decisions. Miscommunication can lead to delays in treatment or other costly medical interventions. Methods In this review, we highlight miscommunication in pathology reporting and provide potential solutions to improve communication. Results Up to one-third of clinicians do not always understand pathology reports. Several causes of report misinterpretation include the use of pathology-specific jargon, different versions of staging or grading systems, and expressions indicative of uncertainty in the pathologist’s report. Active communication has proven to be crucial between the clinician and the pathologist to clarify different aspects of the pathology report. Direct communication between pathologists and patients is evolving, with promising success in proof-of-principle studies. Special attention needs to be paid to avoiding inaccuracy while trying to simplify the pathology report. Conclusions There is a need for active and adequate communication among pathologists, other clinicians, and patients. Clarity and consistency in reporting, quantifying the level of confidence in diagnosis, and avoiding misnomers are key steps toward improving communications.

Despite significant advances in its detection, understanding and management, atrial fibrillation (AF) remains a highly prevalent cardiac arrhythmia with a major impact on morbidity and mortality of millions of patients. AF results from complex, dynamic interactions between risk factors and comorbidities that induce diverse atrial remodelling processes. Atrial remodelling increases AF vulnerability and persistence, while promoting disease progression. The variability in presentation and wide range of mechanisms involved in initiation, maintenance and progression of AF, as well as its associated adverse outcomes, make the early identification of causal factors modifiable with therapeutic interventions challenging, likely contributing to suboptimal efficacy of current AF management. Computational modelling facilitates the multilevel integration of multiple datasets and offers new opportunities for mechanistic understanding, risk prediction and personalized therapy. Mathematical simulations of cardiac electrophysiology have been around for 60 years and are being increasingly used to improve our understanding of AF mechanisms and guide AF therapy. This narrative review focuses on the emerging and future applications of computational modelling in AF management. We summarize clinical challenges that may benefit from computational modelling, provide an overview of the different in silico approaches that are available together with their notable achievements, and discuss the major limitations that hinder the routine clinical application of these approaches. Finally, future perspectives are addressed. With the rapid progress in electronic technologies including computing, clinical applications of computational modelling are advancing rapidly. We expect that their application will progressively increase in prominence, especially if their added value can be demonstrated in clinical trials., Graphical Abstract