Risk Stratification for Sudden Cardiac Death In Patients With Non-ischemic Dilated Cardiomyopathy

Non ischemic dilated cardiomyopathy (NIDCM) is a disorder of myocardium. It has varying etiologies. Albeit the varying etiologies of this heart muscle disorder, it presents with symptoms of heart failure, and rarely as sudden cardiac death (SCD). Manifestations of this disorder are in many ways similar to its counterpart, ischemic dilated cardiomyopathy (IDCM). A proportion of patients with NIDCM carries a grave prognosis and is prone to sudden cardiac death from sustained ventricular arrhythmias. Identification of this subgroup of patients who carry the risk of sudden cardiac death despite adequate medical management is a challenge .Yet another method is a blanket treatment of patients with this disorder with anti arrhythmic medications or anti tachyarrhythmia devices like implantable cardioverter defibrillators (ICD). However this modality of treatment could be a costly exercise even for affluent economies. In this review we try to analyze the existing data of risk stratification of NIDCM and its clinical implications in practice

A prospective study on clinical outcome of humerus shaft fracture and nonunion treated with antero medial plating

Background: Humeral shaft fractures have an incidence of 13 per 100000 per year and account for 3% of total fractures. The following study is carried out with intention for determining and verifying facts around plate osteosynthesis on anteromedial surface of humerus through anterior approach.Methods: This is a prospective study of 38 patients presenting with humerus shaft fracture and non-union to the Balaji Institute of Surgery Research and Rehabilitation for the Disabled (BIRRD) from April 2015 to March 2016. Inclusion criteria were age>18 years, acute humerus shaft fractures and nonunion of humerus shaft. Exclusion criteria were undisplaced fractures, fractures associated with neurovascular injury, compound and pathological fractures, infected non unions. The functional outcome was graded based on the QuickDASH score. Fisher’s exact test was used to find the association between categorical data.Results: Clinical union was noted in 87% of the patients and radiological union in 74% at the end of three months. The average time period required to achieve union was 13.57 weeks. Based on Quick DASH score, 66% of them had excellent outcome, 24% had good outcome, 10% had fair outcome, and none had poor outcome.Conclusions: It may be concluded that, anteromedial plating through anterior approach for the treatment of humerus shaft fractures and non union leads to a satisfactory functional outcome in most of the patients. Most of the fractures were united by 3 months with good range of motion of shoulder and elbow

Two-part segmentation of text documents.

We consider the problem of segmenting text documents that have a two-part structure such as a problem part and a solution part. Documents of this genre include incident reports that typically involve description of events relating to a problem followed by those pertaining to the solution that was tried. Segmenting such documents into the component two parts would render them usable in knowledge reuse frameworks such as Case-Based Reasoning. This segmentation problem presents a hard case for traditional text segmentation due to the lexical inter-relatedness of the segments. We develop a two-part segmentation technique that can harness a corpus of similar documents to model the behavior of the two segments and their inter-relatedness using language models and translation models respectively. In particular, we use separate language models for the problem and solution segment types, whereas the interrelatedness between segment types is modeled using an IBM Model 1 translation model. We model documents as being generated starting from the problem part that comprises of words sampled from the problem language model, followed by the solution part whose words are sampled either from the solution language model or from a translation model conditioned on the words already chosen in the problem part. We show, through an extensive set of experiments on real-world data, that our approach outperforms the state-of-the-art text segmentation algorithms in the accuracy of segmentation, and that such improved accuracy translates well to improved usability in Case-based Reasoning systems. We also analyze the robustness of our technique to varying amounts and types of noise and empirically illustrate that our technique is quite noise tolerant, and degrades gracefully with increasing amounts of noise

CIRCLE: Capture In Rich Contextual Environments

Synthesizing 3D human motion in a contextual, ecological environment is important for simulating realistic activities people perform in the real world. However, conventional optics-based motion capture systems are not suited for simultaneously capturing human movements and complex scenes. The lack of rich contextual 3D human motion datasets presents a roadblock to creating high-quality generative human motion models. We propose a novel motion acquisition system in which the actor perceives and operates in a highly contextual virtual world while being motion captured in the real world. Our system enables rapid collection of high-quality human motion in highly diverse scenes, without the concern of occlusion or the need for physical scene construction in the real world. We present CIRCLE, a dataset containing 10 hours of full-body reaching motion from 5 subjects across nine scenes, paired with ego-centric information of the environment represented in various forms, such as RGBD videos. We use this dataset to train a model that generates human motion conditioned on scene information. Leveraging our dataset, the model learns to use ego-centric scene information to achieve nontrivial reaching tasks in the context of complex 3D scenes. To download the data please visit https://stanford-tml.github.io/circle_dataset/

Competency-Based Assessment Tool for Pediatric Tracheotomy: International Modified Delphi Consensus

Objectives/Hypothesis: Create a competency-based assessment tool for pediatric tracheotomy. Study Design: Blinded, modified, Delphi consensus process. Methods: Using the REDCap database, a list of 31 potential items was circulated to 65 expert surgeons who perform pediatric tracheotomy. In the first round, items were rated as “keep” or “remove,” and comments were incorporated. In the second round, experts were asked to rate the importance of each item on a seven-point Likert scale. Consensus criteria were determined a priori with a goal of 7 to 25 final items. Results: The first round achieved a response rate of 39/65 (60.0%), and returned questionnaires were 99.5% complete. All items were rated as “keep,” and 137 comments were incorporated. In the second round, 30 task-specific and seven previously validated global rating items were distributed, and the response rate was 44/65 (67.7%), with returned questionnaires being 99.3% complete. Of the Task-Specific Items, 13 reached consensus, 10 were near consensus, and 7 did not achieve consensus. For the 7 previously validated global rating items, 5 reached consensus and two were near consensus. Conclusions: It is feasible to reach consensus on the important steps involved in pediatric tracheotomy using a modified Delphi consensus process. These items can now be considered to create a competency-based assessment tool for pediatric tracheotomy. Such a tool will hopefully allow trainees to focus on the important aspects of this procedure and help teaching programs standardize how they evaluate trainees during this procedure. Level of Evidence: 5 Laryngoscope, 130:2700–2707, 2020

Advances in Developing Therapies to Combat Zika Virus: Current Knowledge and Future Perspectives

Zika virus (ZIKV) remained largely quiescent for nearly six decades after its first appearance in 1947. ZIKV reappeared after 2007, resulting in a declaration of an international “public health emergency” in 2016 by the World Health Organization (WHO). Until this time, ZIKV was considered to induce only mild illness, but it has now been established as the cause of severe clinical manifestations, including fetal anomalies, neurological problems, and autoimmune disorders. Infection during pregnancy can cause congenital brain abnormalities, including microcephaly and neurological degeneration, and in other cases, Guillain-Barré syndrome, making infections with ZIKV a substantial public health concern. Genomic and molecular investigations are underway to investigate ZIKV pathology and its recent enhanced pathogenicity, as well as to design safe and potent vaccines, drugs, and therapeutics. This review describes progress in the design and development of various anti-ZIKV therapeutics, including drugs targeting virus entry into cells and the helicase protein, nucleosides, inhibitors of NS3 protein, small molecules, methyltransferase inhibitors, interferons, repurposed drugs, drugs designed with the aid of computers, neutralizing antibodies, convalescent serum, antibodies that limit antibody-dependent enhancement, and herbal medicines. Additionally, covalent inhibitors of viral protein expression and anti-Toll-like receptor molecules are discussed. To counter ZIKV-associated disease, we need to make rapid progress in developing novel therapies that work effectually to inhibit ZIKV

Donkey milk: chemical make-up, biochemical features, nutritional worth, and possible human health benefits - Current state of scientific knowledge

Milk and milk derivatives are widely consumed because of their high nutritional density. Donkey milk and milk products have been consumed since ancient times. The use of donkey milk in the human diet is gaining popularity. The abundance of antibacterial components and protective elements in donkey milk sets it apart from the milk of other animals. Like human milk, donkey milk has low fat, high lactose, and low casein/whey protein ratio. Donkey milk whey protein's anti-proliferative properties imply lung cancer treatment. Alpha-lactalbumin, a type of protein, has been found to have antiviral, anticancer, and anti-stress properties. Donkey milk, like human milk, includes a low amount of casein and a smaller quantity of beta-lactoglobulin than cow milk. Donkey milk is an alternative for newborns with cow milk protein allergy and lactose intolerance since it has a higher amount of lactose, improves palatability, and prevents allergies. Osteogenesis, arteriosclerosis therapy, cardiac rehabilitation, accelerated aging, and hypocholesterolemic diets are some areas where donkey milk is beneficial. Since it contains probiotic lactobacilli strains, fermented beverages can be made with donkey milk. Donkey milk moisturizes skin due to its high vitamin, mineral, and polyunsaturated fatty acid content. The chemical makeup and potential therapeutic benefits of donkey milk warrant additional research. This has led to a rise in interest in producing dairy goods derived from donkey milk. Donkey milk has been used to make cheese, ice cream, milk powder, and even some experimental useful fermented drinks. The present article summarises what we know about donkey milk's chemical makeup, biological functions, nutritional worth, and possible human health benefits