Nonparametric estimation of concave production technologies by entropic methods

An econometric methodology is developed for nonparametric estimation of concave production technologies. The methodology, bases on the priciple of maximum likelihood, uses entropic distance and concvex programming techniques to estimate production functions.convex programming, production functions, entropy

Dialysis Care around the World: A Global Perspectives Series.

Introduction Worldwide, ESKD prevalence per million population (PMP) has steadily increased from 2003 to 2016 (1), with the greatest proportional increases occurring in lower- and middle-income countries (2). Although dialysis is a lifesaving therapy, it is also extraordinarily expensive, so its use is limited in lower-income countries with less resources available for healthcare. Specifically, the prevalence of dialysis in 2010 was 1176 PMP in higher-income countries, 688 PMP in upper-middle-income countries, 170 PMP in lowerincome countries, and 16 PMP in lower-income countries (2). The most common modality of kidney replacement therapy globally is dialysis (78%) and, among patients receiving dialysis, only 11% receive peritoneal dialysis (3

Chronic kidney disease and arrhythmias: conclusions from a Kidney Disease: Improving Global Outcomes (KDIGO) Controversies Conference.

Patients with chronic kidney disease (CKD) are predisposed to heart rhythm disorders, including atrial fibrillation (AF)/atrial flutter, supraventricular tachycardias, ventricular arrhythmias, and sudden cardiac death (SCD). While treatment options, including drug, device, and procedural therapies, are available, their use in the setting of CKD is complex and limited. Patients with CKD and end-stage kidney disease (ESKD) have historically been under-represented or excluded from randomized trials of arrhythmia treatment strategies,1 although this situation is changing.2 Cardiovascular society consensus documents have recently identified evidence gaps for treating patients with CKD and heart rhythm disorders [...

Automated Seizure Detection Based on State-Space Model Identification

In this study, we developed a machine learning model for automated seizure detection using system identification techniques on EEG recordings. System identification builds mathematical models from a time series signal and uses a small number of parameters to represent the entirety of time domain signal epochs. Such parameters were used as features for the classifiers in our study. We analyzed 69 seizure and 55 non-seizure recordings and an additional 10 continuous recordings from Thomas Jefferson University Hospital, alongside a larger dataset from the CHB-MIT database. By dividing EEGs into epochs (1 s, 2 s, 5 s, and 10 s) and employing fifth-order state-space dynamic systems for feature extraction, we tested various classifiers, with the decision tree and 1 s epochs achieving the highest performance: 96.0% accuracy, 92.7% sensitivity, and 97.6% specificity based on the Jefferson dataset. Moreover, as the epoch length increased, the accuracy dropped to 94.9%, with a decrease in sensitivity to 91.5% and specificity to 96.7%. Accuracy for the CHB-MIT dataset was 94.1%, with 87.6% sensitivity and 97.5% specificity. The subject-specific cases showed improved results, with an average of 98.3% accuracy, 97.4% sensitivity, and 98.4% specificity. The average false detection rate per hour was 0.5 ± 0.28 in the 10 continuous EEG recordings. This study suggests that using a system identification technique, specifically, state-space modeling, combined with machine learning classifiers, such as decision trees, is an effective and efficient approach to automated seizure detection

The Human Cell Atlas.

The recent advent of methods for high-throughput single-cell molecular profiling has catalyzed a growing sense in the scientific community that the time is ripe to complete the 150-year-old effort to identify all cell types in the human body. The Human Cell Atlas Project is an international collaborative effort that aims to define all human cell types in terms of distinctive molecular profiles (such as gene expression profiles) and to connect this information with classical cellular descriptions (such as location and morphology). An open comprehensive reference map of the molecular state of cells in healthy human tissues would propel the systematic study of physiological states, developmental trajectories, regulatory circuitry and interactions of cells, and also provide a framework for understanding cellular dysregulation in human disease. Here we describe the idea, its potential utility, early proofs-of-concept, and some design considerations for the Human Cell Atlas, including a commitment to open data, code, and community

The experience of mortgage distress in Western Sydney

Mortgage distress is affecting a growing number of Australian households. Distress ranges from arrears in mortgage payments to defaults, foreclosures and repossessions. The impacts of mortgage distress are complex and include issues relating to the ongoing financial viability of the affected households, wider neighbourhood effects, and a range of psychological and social impacts. In recent years, mortgage stress has had a consistently higher prevalence in certain parts of Western Sydney than in any other region across Australia.This study is an attempt to uncover the experiences of mortgage distress in Western Sydney and of mortgage holders’ coping strategies. While not claiming to be a representative sample of mortgagors in distress, the report reveals much about the circumstances contributing to mortgage distress and its considerable impacts on the lives of those affected

Injury activates transient olfactory stem cell states with diverse lineage capacities

Tissue homeostasis and regeneration are mediated by programs of adult stem cell renewal and differentiation. However, the mechanisms that regulate stem cell fates under such widely varying conditions are not fully understood. Using single-cell techniques, we assessed the transcriptional changes associated with stem cell self-renewal and differentiation and followed the maturation of stem cell-derived clones using sparse lineage tracing in the regenerating mouse olfactory epithelium. Following injury, quiescent olfactory stem cells rapidly shift to activated, transient states unique to regeneration and tailored to meet the demands of injury-induced repair, including barrier formation and proliferation. Multiple cell fates, including renewed stem cells and committed differentiating progenitors, are specified during this early window of activation. We further show that Sox2 is essential for cells to transition from the activated to neuronal progenitor states. Our study highlights strategies for stem cell-mediated regeneration that may be conserved in other adult stem cell niches

Deconstructing olfactory stem cell trajectories at single-cell resolution

A detailed understanding of the paths that stem cells traverse to generate mature progeny is vital for elucidating the mechanisms governing cell fate decisions and tissue homeostasis. Adult stem cells maintain and regenerate multiple mature cell lineages in the olfactory epithelium. Here we integrate single-cell RNA sequencing and robust statistical analyses with in vivo lineage tracing to define a detailed map of the postnatal olfactory epithelium, revealing cell fate potentials and branchpoints in olfactory stem cell lineage trajectories. Olfactory stem cells produce support cells via direct fate conversion in the absence of cell division, and their multipotency at the population level reflects collective unipotent cell fate decisions by single stem cells. We further demonstrate that Wnt signaling regulates stem cell fate by promoting neuronal fate choices. This integrated approach reveals the mechanisms guiding olfactory lineage trajectories and provides a model for deconstructing similar hierarchies in other stem cell niches

Therapeutic potential of injectable Nano-mupirocin liposomes for infections involving multidrug-resistant bacteria

Antibiotic resistance is a global health threat. There are a few antibiotics under development, and even fewer with new modes of action and no cross-resistance to established antibiotics. Accordingly, reformulation of old antibiotics to overcome resistance is attractive. Nano-mupirocin is a PEGylated nano-liposomal formulation of mupirocin, potentially enabling parenteral use in deep infections, as previously demonstrated in several animal models. Here, we describe extensive in vitro profiling of mupirocin and Nano-mupirocin and correlate the resulting MIC data with the pharmacokinetic profiles seen for Nano-mupirocin in a rat model. Nano-mupirocin showed no cross-resistance with other antibiotics and retained full activity against vancomycin-, daptomycin-, linezolid- and methicillin- resistant Staphylococcus aureus, against vancomycin-resistant Enterococcus faecium, and cephalosporin-resistant Neisseria gonorrhoeae. Following Nano-mupirocin injection to rats, plasma levels greatly exceeded relevant MICs for > 24 h, and a biodistribution study in mice showed that mupirocin concentrations in vaginal secretions greatly exceeded the MIC 90 for N. gonorrhoeae (0.03 µg/mL) for > 24 h. In summary, Nano-mupirocin has excellent potential for treatment of several infection types involving multiresistant bacteria. It has the concomitant benefits from utilizing an established antibiotic and liposomes of the same size and lipid composition as Doxil®, an anticancer drug product now used for the treatment of over 700,000 patients globally