A simple method to reduce infection of ventriculoperitoneal shunts Clinical article

Object: Postoperative shunt infection is the most common and feared complication of ventriculoperitoneal (VP) shunt placement for treatment of hydrocephalus. The rate of shunt infection is highest in the 1st postoperative month. The most common organisms responsible for shunt infection include coagulase-negative Staphylococcus and Staphylococcus aureus. This suggests a transfer of Patient\u27s skin flora via the surgeons\u27 glove as a possible means of infection. The authors conducted a study to determine if the rate of postoperative shunt infections could be reduced simply by changing gloves before handling the shunt catheter. Methods: A total of 111 neonates born with congenital hydrocephalus requiring a VP shunt were enrolled retrospectively and divided into 2 groups: a control group of 54 neonates treated with standard protocol VP shunt placement (Group A) and a treatment group of 57 neonates in whom, after initially double gloving, the outer pair of gloves was removed before handling the shunt catheter (Group B). Shunt infection rates were compared up to 6 months postoperatively. Results: There was a statistically significant reduction of infection rate from 16.33% in Group A (control) to 3.77% in Group B (p = 0.0458). Conclusions: The study shows that a changing of gloves before handling the shunt catheter may be a simple and cost-effective way to reduce the burden of postoperative shunt infections

Frequencies of two functionally significant SNPs and their haplotypes of organic anion transporting polypeptide 1B1 SLCO1B1 gene in six ethnic groups of Pakistani population

Objective(s):Organic anion transporter polypeptide 1B1 (OATP1B1) encoded by solute carrier organic transporter 1B1 (SLCO1B1) gene; a transporter involved in the uptake of drugs and endogenous compounds is present in hepatocyte sinusoidal membrane. Aim of this study was to investigate the frequencies of functionally significant SNPs (388A>G and 521T>C) and their haplotypes in 6 ethnic groups of Pakistani population through the development of rapid and efficient Tetra amplification refractory mutation system (T. ARMS) genotyping assay. Materials and Methods: Frequencies of alleles, genotype, and haplotypes of two functionally significant Single nucleotide polymorphism in 180 healthy Pakistani subjects and distributions in six ethnic groups by using a single step T. ARMS genotyping assay. Results: The allelic frequency for 388A>G SNP was 50% in total Pakistani population with distributions of 9.7%, 15.1%, 19.4%, 16.1%, 18.3%, and 21.5% in Punjabi, Sindhi, Balouchi, Pathan, Kashmiri and Hazara/Baltistan groups respectively; and for 521T>C SNP it was 23.9% in total Pakistani population with distributions of 11.1%, 8.9%, 15.6%, 11.1%, 31.1% and 22.2% in Punjabi, Sindhi, Balouchi, Pathan, Kashmiri, and Hazara/Baltistan groups. Both functionally significant SNPs occurred in four major haplotypes with a frequency of 35.5% for 388A/521T (*1A), 40.5% for 388G/521T (*1B), 14.4% for 388A/521C (*5), and 9.4% for 388G/521C (*15) with varying distributions among six ethnic groups. Conclusion: The 388A>G and 521T>C genotypes and corresponding haplotypes are present at varying frequencies in various ethnic groups of Pakistani population. Pharmacokinetic and pharmacodynami

Dataset of Pakistan Sign Language and Automatic Recognition of Hand Configuration of Urdu Alphabet through Machine Learning

Social correspondence is one of the most significant columns that the public dependent on. Notably, language is the best way to communicate and associate with one another both verbally and nonverbally. There is a persistent communication gap among deaf and non-deaf communities because non-deaf people have less understanding of sign languages. Every region/country has its sign language. In Pakistan, the sign language of Urdu is a visual gesture language that is being used for communication among deaf peoples. However, the dataset of Pakistan Sign Language (PSL) is not available publicly. The dataset of PSL has been generated by acquiring images of different hand configurations through a webcam. In this work, 40 images of each hand configuration with multiple orientations have been captured. In addition, we developed, an interactive android mobile application based on machine learning that minimized the communication barrier between the deaf and non-deaf communities by using the PSL dataset. The android application recognizes the Urdu alphabet from input hand configuration