EuMicroSatdb: A database for microsatellites in the sequenced genomes of eukaryotes

<p>Abstract</p> <p>Background</p> <p>Microsatellites have immense utility as molecular markers in different fields like genome characterization and mapping, phylogeny and evolutionary biology. Existing microsatellite databases are of limited utility for experimental and computational biologists with regard to their content and information output. EuMicroSat<it>db </it>(<b>Eu</b>karyotic <b>MicroSat</b>ellite <b><it>d</it></b>ata<b><it>b</it></b>ase) <url>http://ipu.ac.in/usbt/EuMicroSatdb.htm</url> is a web based relational database for easy and efficient positional mining of microsatellites from sequenced eukaryotic genomes.</p> <p>Description</p> <p>A user friendly web interface has been developed for microsatellite data retrieval using Active Server Pages (ASP). The backend database codes for data extraction and assembly have been written using Perl based scripts and C++. Precise need based microsatellites data retrieval is possible using different input parameters like microsatellite type (simple perfect or compound perfect), repeat unit length (mono- to hexa-nucleotide), repeat number, microsatellite length and chromosomal location in the genome. Furthermore, information about clustering of different microsatellites in the genome can also be retrieved. Finally, to facilitate primer designing for PCR amplification of any desired microsatellite locus, 200 bp upstream and downstream sequences are provided.</p> <p>Conclusion</p> <p>The database allows easy systematic retrieval of comprehensive information about simple and compound microsatellites, microsatellite clusters and their locus coordinates in 31 sequenced eukaryotic genomes. The information content of the database is useful in different areas of research like gene tagging, genome mapping, population genetics, germplasm characterization and in understanding microsatellite dynamics in eukaryotic genomes.</p

Yoga Posture Classification using Computer Vision

There has been over the past few years, a very increased popularity for yoga. A lot of literatures have been published that claim yoga to be beneficial in improving the overall lifestyle and health especially in rehabilitation, mental health and more. Considering the fast-paced lives that individuals live, people usually prefer to exercise or work-out from the comfort of their homes and with that a need for an instructor arises. Hence why, we have developed a self-assisted system which can be used to detect and classify yoga asanas, which is discussed in-depth in this paper. Especially now when the pandemic has taken over the world, it is not feasible to attend physical classes or have an instructor over. Using the technology of Computer Vision, a computer-assisted system such as the one discussed, comes in very handy. The technologies such as ml5.js, PoseNet and Neural Networks are made use for the human pose estimation and classification. The proposed system uses the above-mentioned technologies to take in a real-time video input and analyze the pose of an individual, and classifies the poses into yoga asanas. It also displays the name of the yoga asana that is detected along with the confidence score

Stabilization of a G-Quadruplex from Unfolding by Replication Protein A Using Potassium and the Porphyrin TMPyP4

Replication protein A (RPA) plays an essential role in DNA replication by binding and unfolding non-canonical single-stranded DNA (ssDNA) structures. Of the six RPA ssDNA binding domains (labeled A-F), RPA-CDE selectively binds a G-quadruplex forming sequence (5′-TAGGGGAAGGGTTGGAGTGGGTT-3′ called Gq23). In K+, Gq23 forms a mixed parallel/antiparallel conformation, and in Na+ Gq23 has a less stable (TM lowered by ∼20°C), antiparallel conformation. Gq23 is intramolecular and 1D NMR confirms a stable G-quadruplex structure in K+. Full-length RPA and RPA-CDE-core can bind and unfold the Na+ form of Gq23 very efficiently, but complete unfolding is not observed with the K+ form. Studies with G-quadruplex ligands, indicate that TMPyP4 has a thermal stabilization effect on Gq23 in K+, and inhibits complete unfolding by RPA and RPA-CDE-core. Overall these data indicate that G-quadruplexes present a unique problem for RPA to unfold and ligands, such as TMPyP4, could possibly hinder DNA replication by blocking unfolding by RPA

Identification of the DNA-Binding Domains of Human Replication Protein A That Recognize G-Quadruplex DNA

Replication protein A (RPA), a key player in DNA metabolism, has 6 single-stranded DNA-(ssDNA-) binding domains (DBDs) A-F. SELEX experiments with the DBDs-C, -D, and -E retrieve a 20-nt G-quadruplex forming sequence. Binding studies show that RPA-DE binds preferentially to the G-quadruplex DNA, a unique preference not observed with other RPA constructs. Circular dichroism experiments show that RPA-CDE-core can unfold the G-quadruplex while RPA-DE stabilizes it. Binding studies show that RPA-C binds pyrimidine- and purine-rich sequences similarly. This difference between RPA-C and RPA-DE binding was also indicated by the inability of RPA-CDE-core to unfold an oligonucleotide containing a TC-region 5′ to the G-quadruplex. Molecular modeling studies of RPA-DE and telomere-binding proteins Pot1 and Stn1 reveal structural similarities between the proteins and illuminate potential DNA-binding sites for RPA-DE and Stn1. These data indicate that DBDs of RPA have different ssDNA recognition properties

Prospective nutritional, therapeutic, and dietary benefits of camel milk making it a viable option for human consumption: Current state of scientific knowledge

For over five thousand years, people in Asia and Africa have known about the health benefits of camel milk. Thus, it is used not only as a food source but also as a medicine. The similarities between camel milk and human milk have been scientifically proven. Camel milk is unique among ruminant milk because it is high in vitamins C and E and low in sugar and cholesterol. Still, it contains a wide variety of beneficial minerals (including sodium, potassium, iron, copper, zinc, and magnesium), besides being rich in several nutrients, including monounsaturated and polyunsaturated fatty acids, serum albumin, lactoferrin, immunoglobulins, lysozyme and the hormone insulin. Because of these components, many medical professionals now recommend camel milk as a treatment for various human ailments. It has been demonstrated to be effective in treating gastrointestinal issues, Type 1 diabetes, and food allergies. As a bonus, camel milk has been utilized to cure autism, lower cholesterol, prevent psoriasis, heal inflammation, aid tuberculosis patients, boost the body's natural defences, and impede the spread of cancer cells. Those who have problems digesting lactose may still be able to tolerate it. Conversely, camel milk can also help reduce an excessively high bilirubin, globulin, and granulocyte count. Drinking camel milk does not affect the erythrocyte sedimentation rate, hemoglobin concentration, and leukocyte count. The proteins in camel milk have an adequate ratio of critical amino acids. Immunoglobulins, which fight disease, are contained inside, and their small size allows antigens to penetrate and boosts the immune system's efficacy. This article highlights the health benefits and medicinal uses of camel milk

Replication Protein A (RPA) Hampers the Processive Action of APOBEC3G Cytosine Deaminase on Single-Stranded DNA

deamination assays and expression of A3G in yeast, we show that replication protein A (RPA), the eukaryotic single-stranded DNA (ssDNA) binding protein, severely inhibits the deamination activity and processivity of A3G. on long ssDNA regions. This resembles the “hit and run” single base substitution events observed in yeast., we propose that RPA plays a role in the protection of the human genome cell from A3G and other deaminases when they are inadvertently diverged from their natural targets. We propose a model where RPA serves as one of the guardians of the genome that protects ssDNA from the destructive processive activity of deaminases by non-specific steric hindrance

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals &lt;1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Impact of forest governance and enforcement on deforestation and forest degradation at the district level: A study in West Bengal State, India

According to the United Nations Environmental Programme (UNEP), the world loses 1.0 ​× ​106 ​hm2 forest land through deforestation annually. About 1.6 ​× ​106 people who depend on forests for livelihood are negatively affected by deforestation and forest degradation. The paper attempts to study the impact of forest governance, enforcement and socio-economic factors on deforestation and forest degradation at the local level in West Bengal State, India. The study was based on questionnaire survey data during 2020–2021 collected from three western districts (Purulia, Bankura, and Paschim Medinipur) where deforestation and poverty rates are higher than other districts in West Bengal State. The total number of selected villages was 29, and the total sample households were 693. A stratified random sampling technique was used to collect data, and a questionnaire was followed. Forest governance and enforcement indices were constructed using United Nation Development Programme (UNDP) methodology and a step-wise logistic regression model was used to identify the factors affecting deforestation and forest degradation. The result of this study showed that four factors (illegal logging, weak forest administration, encroachment, and poverty) are identified for the causes of deforestation and forest degradation. It is observed that six indices of forest governance (rule of law, transparency, accountability, participation, inclusiveness and equitability, and efficiency and effectiveness) is relatively high in Purulia District. Moreover, this study shows that Purulia and Bankura districts follow medium forest governance, while Paschim Medinipur District has poor forest governance. The enforcement index is found to be highest in Purulia District (0.717) and lowest for Paschim Medinipur District (0.257). Finally, weak forest governance, poor socio-economic conditions of the households, and weak enforcement lead to the deforestation and forest degradationin the study area. Therefore, governments should strengthen law enforcement and encourage sustainable forest certification schemes to combat illegal logging