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Neural induction of human pluripotent stem cells often yields heterogeneous cell populations that can hamper quantitative and comparative analyses. There is a need for improved differentiation and enrichment procedures that generate highly pure populations of neural stem cells (NSC), glia and neurons. One way to address this problem is to identify cell-surface signatures that enable the isolation of these cell types from heterogeneous cell populations by fluorescence activated cell sorting (FACS). We performed an unbiased FACS- and image-based immunophenotyping analysis using 190 antibodies to cell surface markers on naïve human embryonic stem cells (hESC) and cell derivatives from neural differentiation cultures. From this analysis we identified prospective cell surface signatures for the isolation of NSC, glia and neurons. We isolated a population of NSC that was CD184(+)/CD271(-)/CD44(-)/CD24(+) from neural induction cultures of hESC and human induced pluripotent stem cells (hiPSC). Sorted NSC could be propagated for many passages and could differentiate to mixed cultures of neurons and glia in vitro and in vivo. A population of neurons that was CD184(-)/CD44(-)/CD15(LOW)/CD24(+) and a population of glia that was CD184(+)/CD44(+) were subsequently purified from cultures of differentiating NSC. Purified neurons were viable, expressed mature and subtype-specific neuronal markers, and could fire action potentials. Purified glia were mitotic and could mature to GFAP-expressing astrocytes in vitro and in vivo. These findings illustrate the utility of immunophenotyping screens for the identification of cell surface signatures of neural cells derived from human pluripotent stem cells. These signatures can be used for isolating highly pure populations of viable NSC, glia and neurons by FACS. The methods described here will enable downstream studies that require consistent and defined neural cell populations.

Induced pluripotent stem cells are shown to be useful for studying phenotypes relevant to familial and sporadic Alzheimer’s disease, even though it can take decades for the disease to manifest in patients. Alzheimer's disease in a dish Induced pluripotent stem (iPS) cell cultures are being used as models for various genetic diseases, including Parkinson's disease and diabetes. Alzheimer's disease seems an unlikely candidate for such a technique, because it can take decades for the disease to manifest in patients. But here, Lawrence Goldstein and colleagues provide evidence that iPS cell technology can be used to study phenotypes that are relevant to familial and sporadic Alzheimer's disease. Patient-derived fibroblasts were reprogrammed as iPS cells and differentiated into neurons expressing various biochemical markers of Alzheimer's disease, including elevated amyloid-β secretion. Treatment of neurons with a γ-secretase inhibitor, a type of drug considered a candidate for Alzheimer's therapy, significantly reduced both amyloid-β and phospho-tau levels. Our understanding of Alzheimer’s disease pathogenesis is currently limited by difficulties in obtaining live neurons from patients and the inability to model the sporadic form of the disease. It may be possible to overcome these challenges by reprogramming primary cells from patients into induced pluripotent stem cells (iPSCs). Here we reprogrammed primary fibroblasts from two patients with familial Alzheimer’s disease, both caused by a duplication of the amyloid-β precursor protein gene 1 ( APP ; termed APP Dp ), two with sporadic Alzheimer’s disease (termed sAD1, sAD2) and two non-demented control individuals into iPSC lines. Neurons from differentiated cultures were purified with fluorescence-activated cell sorting and characterized. Purified cultures contained more than 90% neurons, clustered with fetal brain messenger RNA samples by microarray criteria, and could form functional synaptic contacts. Virtually all cells exhibited normal electrophysiological activity. Relative to controls, iPSC-derived, purified neurons from the two APP Dp patients and patient sAD2 exhibited significantly higher levels of the pathological markers amyloid-β(1–40), phospho-tau(Thr 231) and active glycogen synthase kinase-3β (aGSK-3β). Neurons from APP Dp and sAD2 patients also accumulated large RAB5-positive early endosomes compared to controls. Treatment of purified neurons with β-secretase inhibitors, but not γ-secretase inhibitors, caused significant reductions in phospho-Tau(Thr 231) and aGSK-3β levels. These results suggest a direct relationship between APP proteolytic processing, but not amyloid-β, in GSK-3β activation and tau phosphorylation in human neurons. Additionally, we observed that neurons with the genome of one sAD patient exhibited the phenotypes seen in familial Alzheimer’s disease samples. More generally, we demonstrate that iPSC technology can be used to observe phenotypes relevant to Alzheimer’s disease, even though it can take decades for overt disease to manifest in patients.

A major goal of stem-cell research is to identify conditions that reliably regulate their differentiation into specific cell types. This goal is particularly important for human stem cells if they are to be used for in vivo transplantation or as a platform for drug development. Here we describe the establishment of procedures to direct the differentiation of human embryonic stem cells and human induced pluripotent stem cells into forebrain neurons that are capable of forming synaptic connections. In addition, HEK293T cells expressing Neuroligin (NLGN) 3 and NLGN4, but not those containing autism-associated mutations, are able to induce presynaptic differentiation in human induced pluripotent stem cell-derived neurons. We show that a mutant NLGN4 containing an in-frame deletion is unable to localize correctly to the cell surface when overexpressed and fails to enhance synapse formation in human induced pluripotent stem cell-derived neurons. These findings establish human pluripotent stem cell-derived neurons as a viable model for the study of synaptic differentiation and function under normal and disorder-associated conditions.

Defined transcription factors can induce epigenetic reprogramming of adult mammalian cells into induced pluripotent stem cells. Although DNA factors are integrated during some reprogramming methods, it is unknown whether the genome remains unchanged at the single nucleotide level. Here we show that 22 human induced pluripotent stem (hiPS) cell lines reprogrammed using five different methods each contained an average of five protein-coding point mutations in the regions sampled (an estimated six protein-coding point mutations per exome). The majority of these mutations were non-synonymous, nonsense or splice variants, and were enriched in genes mutated or having causative effects in cancers. At least half of these reprogramming-associated mutations pre-existed in fibroblast progenitors at low frequencies, whereas the rest occurred during or after reprogramming. Thus, hiPS cells acquire genetic modifications in addition to epigenetic modifications. Extensive genetic screening should become a standard procedure to ensure hiPS cell safety before clinical use. Genetic abnormalities in iPS cells Epigenomic reprogramming of somatic cells to produce iPS (induced pluripotent stem) cells has important therapeutic potential and is the basis of potentially important disease models. Recent reports that the reprogramming and in vitro culture of iPS cells can induce genetic and epigenetic abnormalities raise concerns over the implications of these abnormalities for clinical applications of iPS cells. Three papers in this issue present genomics studies of human iPS and embryonic stem (ES) cells, and taken together, the results confirm that chromosomal, subchromosomal and single-base level anomalies do accumulate in iPS cells. Hussein et al . compare copy number alterations of early and intermediate passage human iPS cells and report a higher level of copy number variations associated with reprogramming. During moderate length culture, however, iPS cells undergo a selection process leading to a decreased mutation load equivalent to that seen in ES cells. Gore et al . report protein-coding point mutations in 22 human iPS cell lines reprogrammed using five different methods; some mutations were pre-existing in the somatic cells, others were new mutations linked to reprogramming. Lister et al . used whole-genome DNA methylation profiling of human ES, iPS and somatic progenitor cell lines to reveal 'hotspots' in the genomes of iPS cells that are aberrantly reprogrammed. Reprogramming of somatic cells to induced pluripotent stem (iPS) cells that can be differentiated into many cell types has great potential for personalized therapy. This study finds that 22 human iPS cell lines that were reprogrammed using five different methods contain protein coding point mutations. Some mutations were pre existing in the somatic cells, others were new mutations that occurred during and after reprogramming. Therefore, it will be important to ensure iPS cell safety before clinical use.

Background Expression and activity of heparanase, an endoglycosidase that cleaves heparan sulfate (HS) side chains of proteoglycans, is associated with progression and poor prognosis of many cancers which makes it an attractive drug target in cancer therapeutics. Methods In the present work, we report the in vitro screening of a library of 150 small molecules with the scaffold bearing quinolones, oxazines, benzoxazines, isoxazoli(di)nes, pyrimidinones, quinolines, benzoxazines, and 4-thiazolidinones, thiadiazolo[3,2-a]pyrimidin-5-one, 1,2,4-triazolo-1,3,4-thiadiazoles, and azaspiranes against the enzymatic activity of human heparanase. The identified lead compounds were evaluated for their heparanase-inhibiting activity using sulfate [ 35 S] labeled extracellular matrix (ECM) deposited by cultured endothelial cells. Further, anti-invasive efficacy of lead compound was evaluated against hepatocellular carcinoma (HepG2) and Lewis lung carcinoma (LLC) cells. Results Among the 150 compounds screened, we identified 1,2,4-triazolo-1,3,4-thiadiazoles bearing compounds to possess human heparanase inhibitory activity. Further analysis revealed 2,4-Diiodo-6-(3-phenyl-[1, 2, 4]triazolo[3,4-b][1, 3, 4]thiadiazol-6yl)phenol (DTP) as the most potent inhibitor of heparanase enzymatic activity among the tested compounds. The inhibitory efficacy was demonstrated by a colorimetric assay and further validated by measuring the release of radioactive heparan sulfate degradation fragments from [ 35 S] labeled extracellular matrix. Additionally, lead compound significantly suppressed migration and invasion of LLC and HepG2 cells with IC 50 value of ~5 μM. Furthermore, molecular docking analysis revealed a favourable interaction of triazolo-thiadiazole backbone with Asn-224 and Asp-62 of the enzyme. Conclusions Overall, we identified biologically active heparanase inhibitor which could serve as a lead structure in developing compounds that target heparanase in cancer.

Background The physician shortage in the United States (US) continues to become more apparent. We aimed to evaluate the relationship between the US physician distribution from 2012-2019 by specialty at the state/regional level relative to the corresponding population growth. Methods US matched residents and practicing physicians from 2012-2019 were extracted from the National Resident Matching Program and Association of American Medical College databases, respectively. Residents and practicing physicians were divided by geographic regions (West, Midwest, South, Northeast), states, and specialties (anesthesiology, emergency medicine, family medicine, general surgery (GS), internal medicine, obstetrics/gynecology and pediatrics). Results Entering residents and physicians increased across 7 specialties from 2012-2019 with the exception of GS, which showed .2% decrease in practicing physicians. GS experienced decreases in entering residents in all US regions except the South. All specialties showed a decrease in the people-per-physician (PPP) except GS and pediatrics, which had a 4.1% and 71.3% increase, respectively. EM showed the largest growth overall, both in entering residents and overall workforce. Conclusion GS experienced slow growth of residents, decreases in practicing physicians and workforce overall, and an increase in PPP from 2012-2019. Our findings suggest that current population growth rate is exceeding the rate of physicians entering the field of GS and highlights the need for interventions to promote the recruitment of GS residents and retainment of attending physicians, particularly for rural areas. Future research to measure surgeon distribution in relation to patient outcomes and the efficacy of recent policy to address shortages can help define additional interventions to address physician shortages moving forward.

An automated, accurate method is needed for unbiased assessment quantifying accrual of joint space narrowing and erosions on radiographic images of the hands and wrists, and feet for clinical trials, monitoring of joint damage over time, assisting rheumatologists with treatment decisions. Such a method has the potential to be directly integrated into electronic health records. To design and implement an international crowdsourcing competition to catalyze the development of machine learning methods to quantify radiographic damage in rheumatoid arthritis (RA). This diagnostic/prognostic study describes the Rheumatoid Arthritis 2-Dialogue for Reverse Engineering Assessment and Methods (RA2-DREAM Challenge), which used existing radiographic images and expert-curated Sharp-van der Heijde (SvH) scores from 2 clinical studies (674 radiographic sets from 562 patients) for training (367 sets), leaderboard (119 sets), and final evaluation (188 sets). Challenge participants were tasked with developing methods to automatically quantify overall damage (subchallenge 1), joint space narrowing (subchallenge 2), and erosions (subchallenge 3). The challenge was finished on June 30, 2020. Scores derived from submitted algorithms were compared with the expert-curated SvH scores, and a baseline model was created for benchmark comparison. Performances were ranked using weighted root mean square error (RMSE). The performance and reproductivity of each algorithm was assessed using Bayes factor from bootstrapped data, and further evaluated with a postchallenge independent validation data set. The RA2-DREAM Challenge received a total of 173 submissions from 26 participants or teams in 7 countries for the leaderboard round, and 13 submissions were included in the final evaluation. The weighted RMSEs metric showed that the winning algorithms produced scores that were very close to the expert-curated SvH scores. Top teams included Team Shirin for subchallenge 1 (weighted RMSE, 0.44), HYL-YFG (Hongyang Li and Yuanfang Guan) subchallenge 2 (weighted RMSE, 0.38), and Gold Therapy for subchallenge 3 (weighted RMSE, 0.43). Bootstrapping/Bayes factor approach and the postchallenge independent validation confirmed the reproducibility and the estimation concordance indices between final evaluation and postchallenge independent validation data set were 0.71 for subchallenge 1, 0.78 for subchallenge 2, and 0.82 for subchallenge 3. The RA2-DREAM Challenge resulted in the development of algorithms that provide feasible, quick, and accurate methods to quantify joint damage in RA. Ultimately, these methods could help research studies on RA joint damage and may be integrated into electronic health records to help clinicians serve patients better by providing timely, reliable, and quantitative information for making treatment decisions to prevent further damage.

Locomotion is an ancient and fundamental output of the nervous system required for animals to perform many other complex behaviors. Although the formation of motor circuits is known to be under developmental control of transcriptional mechanisms that define the fates and connectivity of the many neurons, glia and muscle constituents of these circuits, relatively little is known about the role of post-transcriptional regulation of locomotor behavior. MicroRNAs have emerged as a potentially rich source of modulators for neural development and function. In order to define the microRNAs required for normal locomotion in Drosophila melanogaster, we utilized a set of transgenic Gal4-dependent competitive inhibitors (microRNA sponges, or miR-SPs) to functionally assess ca. 140 high-confidence Drosophila microRNAs using automated quantitative movement tracking systems followed by multiparametric analysis. Using ubiquitous expression of miR-SP constructs, we identified a large number of microRNAs that modulate aspects of normal baseline adult locomotion. Addition of temperature-dependent Gal80 to identify microRNAs that act during adulthood revealed that the majority of these microRNAs play developmental roles. Comparison of ubiquitous and neural-specific miR-SP expression suggests that most of these microRNAs function within the nervous system. Parallel analyses of spontaneous locomotion in adults and in larvae also reveal that very few of the microRNAs required in the adult overlap with those that control the behavior of larval motor circuits. These screens suggest that a rich regulatory landscape underlies the formation and function of motor circuits and that many of these mechanisms are stage and/or parameter-specific.

Despite evidence in scientific literature indicating the effectiveness of both cognitive behavioral therapy (CBT) and physical exercise in the management of major depressive disorder (MDD), few studies have directly compared them. This study aims to evaluate and compare the effectiveness of group CBT, physical exercise, and only wait-listing to receive treatment-as-usual (TAU) in the management of MDD. The investigators hypothesize that participants with MDD assigned to the group CBT or exercise arms of the study will achieve superior outcomes compared with participants wait-listed to receive TAU only. This prospective rater-blinded randomized controlled trial assesses the benefits of group CBT and exercise for participants with MDD. A total of 120 patients with MDD referred to addiction and mental health clinics in Edmonton, Canada, will be randomly assigned to one of the three equal-sized arms of the study to receive either weekly sessions of group CBT plus TAU, group exercise three times a week plus TAU, or only TAU for 14 weeks. Participants will be assessed at enrollment, 3 and 6 months post enrollment, midtreatment, and upon treatment completion for primary (functional and symptom variables) and secondary outcomes (service variables and health care utilization). In addition, participants in the intervention groups would be evaluated weekly with one functional measure. The data will be analyzed using repeated measures and effect size analyses, and correlational analyses will be completed between measures at each time point. The study will be conducted in accordance with the Declaration of Helsinki (Hong Kong amendment) and Good Clinical Practice (Canadian guidelines). Written informed consent will be obtained from each subject. The study received ethical clearance from the Health Ethics Research Board of the University of Alberta on September 7, 2018 (Pro 00080975) and operational approval from the provincial health authority (Alberta Health Services 43638). As of October 13, 2019, we have enrolled 32 participants. The results will be disseminated at several levels, including patients, practitioners, academics, researchers, and health care organizations. The results of the pilot trial may inform the implementation of a multicenter clinical trial and provide useful information for administrators and clinicians who are interested in incorporating group CBT and group exercise interventions into existing care. ClinicalTrials.gov NCT03731728; https://clinicaltrials.gov/ct2/show/NCT03731728. PRR1-10.2196/14309.

AI policymakers are responsible for delivering effective governance mechanisms that can provide safe, aligned and trustworthy AI development. However, the information environment offered to policymakers is characterised by an unnecessarily low Signal-To-Noise Ratio, favouring regulatory capture and creating deep uncertainty and divides on which risks should be prioritised from a governance perspective. We posit that the current publication speeds in AI combined with the lack of strong scientific standards, via weak reproducibility protocols, effectively erodes the power of policymakers to enact meaningful policy and governance protocols. Our paper outlines how AI research could adopt stricter reproducibility guidelines to assist governance endeavours and improve consensus on the AI risk landscape. We evaluate the forthcoming reproducibility crisis within AI research through the lens of crises in other scientific domains; providing a commentary on how adopting preregistration, increased statistical power and negative result publication reproducibility protocols can enable effective AI governance. While we maintain that AI governance must be reactive due to AI's significant societal implications we argue that policymakers and governments must consider reproducibility protocols as a core tool in the governance arsenal and demand higher standards for AI research. Code to replicate data and figures: https://github.com/IFMW01/reproducibility-the-new-frontier-in-ai-governance