Meta Analysis: Relationship of Tuberculosis Patient Contact, Density And Ventilation Area With Tuberculosis Events

Tuberculosis is one of 10 causes of death in the world. In 2018 TB sufferers in Indonesia reached 840 thousand people, the third-highest figure in the world after India and China. The purpose of this study was to analyze the relationship between contact with tuberculosis patients, occupancy density and ventilation area with tuberculosis’ incidence. This study used meta-analysis, the articles’ sources were from Google Scholar, PubMed and DOAJ published from 2011-2020. There were 12 articles that met the conditions for contact-free variables with tuberculosis patients, 12 articles of occupancy density, and 10 articles of ventilation area variable. The results were contacting with tuberculosis patients had 5.93 times more of getting tuberculosis compared to people who had no contact with tuberculosis patients, people who lived in densely populated areas were 2.41 times more getting tuberculosis compared to people living in occupancy that is not crowded, people who live in dwellings with a non-standard ventilation area were 2.14 times more getting tuberculosis when compared to people who live in an area where the ventilation area meets the standard. The conclusion of this study is tuberculosis patient contact, occupancy density, and ventilation area with the incidence of tuberculosis have a significant relationship.

Perspectives for the reconstruction of 3D chromatin conformation using single cell Hi-C data

Construction of chromosomes 3D models based on single cell Hi-C data constitute an important challenge. We present a reconstruction approach, DPDchrom, that incorporates basic knowledge whether the reconstructed conformation should be coil-like or globular and spring relaxation at contact sites. In contrast to previously published protocols, DPDchrom can naturally form globular conformation due to the presence of explicit solvent. Benchmarking of this and several other methods on artificial polymer models reveals similar reconstruction accuracy at high contact density and DPDchrom advantage at low contact density. To compare 3D structures insensitively to spatial orientation and scale, we propose the Modified Jaccard Index. We analyzed two sources of the contact dropout: contact radius change and random contact sampling. We found that the reconstruction accuracy exponentially depends on the number of contacts per genomic bin allowing to estimate the reconstruction accuracy in advance. We applied DPDchrom to model chromosome configurations based on single-cell Hi-C data of mouse oocytes and found that these configurations differ significantly from a random one, that is consistent with other studies.

Influence of Particle Shape on the Macroscopic and Mesolevel Mechanical Properties of Slip Zone Soil Based on 3D Scanning and 3D DEM

The macroscopic and mesolevel mechanical mechanisms of slip zone soil are a crucial subject for the research of landslide deformation evolution and slope control, but the effects of the shape and psephicity of coarse particles in a slip zone soil on the mechanical properties of the slip soil zone still need to be explored. Discrete element method (DEM) can effectively monitor and track the mesolevel mechanical parameters of geotechnical materials, such as displacement vector field, contact force chain, and particle coordination number. The rock blocks in the medium-sized shear test undergo a sophisticated process by 3D scanning technology, and a database of the blocks is established and accurately modeled by combining 3D DEM to simulate the indoor medium-sized shear test for numerical investigation in line with the test conditions. The numerical simulation results demonstrate that the psephicity and particle shape of the rock blocks significantly affect the dilatancy and mesolevel mechanical parameters of the slip zone soil specimens. In addition, the numerical models featured by poorer psephicity and more irregular particle shape display more evident dilatancy, larger particle coordination numbers, as well as better contact density inside the model. Some references for the study of the macroscopic and mesolevel mechanical mechanisms of slip zone soil are provided.

Single-cell adhesion strength and contact density drops in the M phase of cancer cells

The high throughput, cost effective and sensitive quantification of cell adhesion strength at the single-cell level is still a challenging task. The adhesion force between tissue cells and their environment is crucial in all multicellular organisms. Integrins transmit force between the intracellular cytoskeleton and the extracellular matrix. This force is not only a mechanical interaction but a way of signal transduction as well. For instance, adhesion-dependent cells switch to an apoptotic mode in the lack of adhesion forces. Adhesion of tumor cells is a potential therapeutic target, as it is actively modulated during tissue invasion and cell release to the bloodstream resulting in metastasis. We investigated the integrin-mediated adhesion between cancer cells and their RGD (Arg-Gly-Asp) motif displaying biomimetic substratum using the HeLa cell line transfected by the Fucci fluorescent cell cycle reporter construct. We employed a computer-controlled micropipette and a high spatial resolution label-free resonant waveguide grating-based optical sensor calibrated to adhesion force and energy at the single-cell level. We found that the overall adhesion strength of single cancer cells is approximately constant in all phases except the mitotic (M) phase with a significantly lower adhesion. Single-cell evanescent field based biosensor measurements revealed that at the mitotic phase the cell material mass per unit area inside the cell-substratum contact zone is significantly less, too. Importantly, the weaker mitotic adhesion is not simply a direct consequence of the measured smaller contact area. Our results highlight these differences in the mitotic reticular adhesions and confirm that cell adhesion is a promising target of selective cancer drugs as the vast majority of normal, differentiated tissue cells do not enter the M phase and do not divide.

Intraoperative microseizure detection using a high-density micro-electrocorticography electrode array

One-third of epilepsy patients suffer from medication-resistant seizures. While surgery to remove epileptogenic tissue helps some patients, 30–70% of patients continue to experience seizures following resection. Surgical outcomes may be improved with more accurate localization of epileptogenic tissue. We have previously developed novel thin-film, subdural electrode arrays with hundreds of microelectrodes over a 100–1,000 mm2 area to enable high-resolution mapping of neural activity. Here we used these high-density arrays to study microscale properties of human epileptiform activity. We performed intraoperative micro-electrocorticographic recordings within epileptic cortex (the site of seizure onset and early spread) in nine patients with epilepsy. In two of these patients, we obtained recordings from cortical areas distal to the epileptic cortex. Additionally, we recorded from two non-epileptic patients with movement disorders undergoing deep brain stimulator implantation as non-epileptic tissue controls. A board-certified epileptologist identified microseizures, which resembled electrographic seizures normally observed with clinical macroelectrodes. Epileptic cortex exhibited a significantly higher microseizure rate (2.01 events/min) than non-epileptic cortex (0.01 events/min; permutation test, P=0.0068). Using spatial averaging to simulate recordings from larger electrode contacts, we found that the number of detected microseizures decreased rapidly with increasing contact diameter and decreasing contact density. In cases in which microseizures were spatially distributed across multiple channels, the approximate onset region was identified. Our results suggest that micro-electrocorticographic electrode arrays with a high density of contacts and large coverage are essential for capturing microseizures in epilepsy patients and may be beneficial for localizing epileptogenic tissue to plan surgery or target brain stimulation.

Distance-based Reconstruction of Protein Quaternary Structures from Inter-Chain Contacts

Predicting the quaternary structure of protein complex is an important problem. Inter-chain residue-residue contact prediction can provide useful information to guide the ab initio reconstruction of quaternary structures. However, few methods have been developed to build quaternary structures from predicted inter-chain contacts. Here, we introduce a gradient descent optimization algorithm (GD) to build quaternary structures of protein dimers utilizing inter-chain contacts as distance restraints. We evaluate GD on several datasets of homodimers and heterodimers using true or predicted contacts. GD consistently performs better than a simulated annealing method and a Markov Chain Monte Carlo simulation method. Using true inter-chain contacts as input, GD can reconstruct high-quality structural models for homodimers and heterodimers with average TM-score ranging from 0.92 to 0.99 and average interface root mean square distance (I-RMSD) from 0.72 Å to 1.64 Å. On a dataset of 115 homodimers, using predicted inter-chain contacts as input, the average TM-score of the structural models built by GD is 0.76. For 46% of the homodimers, high-quality structural models with TM-score >= 0.9 are reconstructed from predicted contacts. There is a strong correlation between the quality of the reconstructed models and the precision and recall of predicted contacts. If the precision or recall of predicted contacts is >20%, GD can reconstruct good models for most homodimers, indicating only a moderate precision or recall of inter-chain contact prediction is needed to build good structural models for most homodimers. Moreover, the accuracy of reconstructed models positively correlates with the contact density in dimers.

Spatiotemporal contact density explains the disparity of COVID-19 spread in urban neighborhoods

The rapid early spread of COVID-19 in the US was experienced very differently by different socioeconomic groups and business industries. In this study, we study aggregate mobility patterns of New York City and Chicago to identify the relationship between the amount of interpersonal contact between people in urban neighborhoods and the disparity in the growth of positive cases among these groups. We introduce an aggregate spatiotemporal contact density index (CDI) to measure the strength of this interpersonal contact using mobility data collected from mobile phones, and combine it with social distancing metrics to show its effect on positive case growth. With the help of structural equations modeling, we find that the effect of CDI on case growth was consistently positive and that it remained consistently higher in lower-income neighborhoods, suggesting a causal path of income on case growth via CDI. Using the CDI, schools and restaurants are identified as high contact density industries, and the estimation suggests that implementing specific mobility restrictions on these point-of-interest categories is most effective. This analysis can be useful in providing insights for government officials targeting specific population groups and businesses to reduce infection spread as reopening efforts continue to expand across the nation.

Distance-based Reconstruction of Protein Quaternary Structures from Inter-Chain Contacts

Predicting the quaternary structure of a protein complex is an important and challenging problem. Inter-chain residue-residue contact prediction can provide useful information to guide the ab initio reconstruction of quaternary structures of protein complexes. However, few methods have been developed to build quaternary structures from predicted inter-chain contacts. Here, we introduce a new gradient descent optimization algorithm (GD) to build quaternary structures of protein dimers utilizing inter-chain contacts as distance restraints. We evaluate GD on several datasets of homodimers and heterodimers using true or predicted contacts. GD consistently performs better than a simulated annealing method and a Markov Chain Monte Carlo simulation method. Using true inter-chain contacts as input, GD can reconstruct high-quality structural models for homodimers and heterodimers with average TM-score ranging from 0.92 to 0.99 and average interface root mean square distance (I-RMSD) from 0.72 Å to 1.64 Å. On a dataset of 115 homodimers, using predicted inter-chain contacts as input, the average TM-score of the structural models built by GD is 0.76. For 46% of the homodimers, high-quality structural models with TM-score >= 0.9 are reconstructed from predicted contacts. There is a strong correlation between the quality of the reconstructed models and the precision and recall of predicted contacts. If the precision or recall of predicted contacts is >20%, GD can reconstruct good models for most homodimers, indicating only a moderate precision or recall of inter-chain contact prediction is needed to build good structural models for most homodimers. Moreover, the accuracy of reconstructed models positively correlates with the contact density in dimers and depends on the initial model and the probability threshold of selecting predicted contacts for the distance-based structure optimization.