Human Gait Database for Normal Walk Collected by Smart Phone Accelerometer

The goal of this study is to introduce a comprehensive gait database of 93 human subjects who walked between two endpoints during two different sessions and record their gait data using two smartphones, one was attached to the right thigh and another one on the left side of the waist. This data is collected with the intention to be utilized by a deep learning-based method which requires enough time points. The metadata including age, gender, smoking, daily exercise time, height, and weight of an individual is recorded. this data set is publicly available

The Prevalence of Iron Deficiency Anemia among High School Students in Iran: A Systematic Review

Introduction: Iron is one of the most important elements forming the body and an essential metal for many biological processes in mammals. According to studies, anemia can cause numerous side effects in the body. Because of the effectiveness of iron in myelinated nerves, this illness can cause hearing loss and vision problems as well, and in students, it can even cause academic failure and learning problems and intensify behavioral disorders. Therefore, to collect the statistics of the prevalence of the disorder in order to inform parents, the present study was conducted to assess the prevalence of iron deficiency anemia in high school students in Iran using meta-analysis method.Method: This study was continued in review form using the key words anemia, iron deficiency anemia, and anemia prevalence with a review of the articles in Pubmed, Iranmedex databases and Scientific Information Database of SID in related topics with 89 articles. Time domain for searching articles and related books and was mainly from 1991 onwards.Results: Studies on the prevalence of iron deficiency anemia in high school students show different results. Recent statistics based on published articles at home and abroad show the prevalence of iron deficiency anemia equal to 10.6%, (with a 95% confidence interval: 9.7 to 11.5) until 2014.Conclusion: The disease can cause hearing and vision disorders in adolescents. Moreover, it can cause academic failure and learning problems and intensify behavioral disorders in students.  Given that children's health is an indicator of health planning of family for them, attention to the factors preventing iron deficiency anemia and its treatment is essential for students. Following this study, it is suggested that by correcting diet as the first step of prevention of catching this diseases, we take a step towards preventing it

Application of Graphical Models in Protein-Protein Interactions and Dynamics

Every organism contains a few hundred to thousands of proteins. A protein is made of a sequence of molecular building blocks named amino acids. Amino acids will be referred to as residues. Every protein performs one or more functions in the cell. In order for a protein to do its job, it requires to bind properly to other partner proteins. Many genetic diseases such as cancer are caused by mutations (changes) of specific residues which cause disturbances in the functions of those proteins. The problem of prediction of protein binding site is a crucial topic in computational biology. A protein is usually made up of 50 to a few thousand residues. A contact site can occur within a protein or with other proteins. By having a robust and accurate model for identifying residues that are involved in the binding site, scientists can investigate the impact of critical mutations and residues that can cause genetic diseases. The main focus of this thesis is to propose a machine learning model for predicting the binding site between two proteins. By extracting structural information from a protein, we can have additional knowledge of binding sites. This structural information can be converted into a penalty matrix for a graphical model to be learned from the protein sequence. The second part of this thesis is mostly focused on motion planning algorithms for proteins and simulation of the protein pathway changes using a Monte Carlo based method. Later, by applying a novel geometry based scoring function, we cluster the intermediate conformations into corresponding subsets that may indicate interesting intermediate states

Thermo-hydraulic performance optimization of a disk-shaped microchannel heat sink applying computational fluid dynamics, artificial neural network, and response surface methodology

The current research focuses on optimizing the Nusselt number (Nu) and pressure drop (ΔP) in a bionic fractal heat sink. The artificial neural network (ANN) and response surface methodology (RSM) were used to model the thermos-hydraulic behavior of the MCHS. The aspect ratios of t/b (cavities' upper side to bottom side ratio) and h/b (cavities’ height to bottom side ratio), as well as the Reynolds number, were set as the independent variables in both ANN and RSM models. After finding the optimum state for the copper-made MCHS (containing the optimum design of the cavities along with the best applied velocity), different materials were tested and compared with the base case (heat sink made of copper). The obtained results indicated that both ANN and RSM models (with determination coefficient of 99.9 %) could exactly anticipate heat transfer and ΔP to a large extent. To achieve the optimal design of the microchannel heat sink (MCHS) with the objective of maximizing Nu and minimizing ΔP, the efficiency index of the device was evaluated. The analysis revealed that the highest efficiency index (1.070 by RSM and 1.067 by ANN methods) was attained when the aspect ratios were t/b = 0.2, h/b = 0.2, and the Reynolds number was 1000. Next, the effect of the different materials on heat sink performance was investigated, and it was observed that by reducing the thermal conductivity, the thermal resistance of the heat sink increased and its overall performance decreased

The germline factor DDX4 contributes to the chemoresistance of small cell lung cancer cells

DDX4, a conserved germline factor and RNA helicase, increases small cell lung cancer cell survival by regulating DNA damage and immune response pathways and contributes to cisplatin-mediated drug resistance

Dynamic single-cell RNA sequencing identifies immunotherapy persister cells following PD-1 blockade.

Resistance to oncogene-targeted therapies involves discrete drug-tolerant persister cells, originally discovered through in vitro assays. Whether a similar phenomenon limits efficacy of programmed cell death 1 (PD-1) blockade is poorly understood. Here, we performed dynamic single-cell RNA-Seq of murine organotypic tumor spheroids undergoing PD-1 blockade, identifying a discrete subpopulation of immunotherapy persister cells (IPCs) that resisted CD8+ T cell-mediated killing. These cells expressed Snai1 and stem cell antigen 1 (Sca-1) and exhibited hybrid epithelial-mesenchymal features characteristic of a stem cell-like state. IPCs were expanded by IL-6 but were vulnerable to TNF-α-induced cytotoxicity, relying on baculoviral IAP repeat-containing protein 2 (Birc2) and Birc3 as survival factors. Combining PD-1 blockade with Birc2/3 antagonism in mice reduced IPCs and enhanced tumor cell killing in vivo, resulting in durable responsiveness that matched TNF cytotoxicity thresholds in vitro. Together, these data demonstrate the power of high-resolution functional ex vivo profiling to uncover fundamental mechanisms of immune escape from durable anti-PD-1 responses, while identifying IPCs as a cancer cell subpopulation targetable by specific therapeutic combinations