GenePath Dx (India)

The great quantity of social networking sites has had a significant impact on behaviour, particularly with relation to online buying. One of the most crucial elements influencing consumers' purchases now is social media celebrity presence. They may convert people's opinions and boost revenue. This study investigates how social media signal analysis may be used to project influencer behaviour on online shopping. Important indicators of an influencer's efficacy include social media cues like likes, shares, comments, and interactions amongst followers. Using data analytics and machine learning, this research investigates how much influencers really matter and how one may use these indicators to predict what people would purchase. This research looks for relationships between social media signals and activities like clicks, sales, and purchase intentions by means of predictive modelling. We also examine other types of media, including advertising postings, reviews, and unboxing videos, to see how these influence behaviour. The research findings provide us with insightful knowledge on how businesses may cooperate with powerful individuals to make their marketing initiatives more successful and better target the appropriate target clients.

Skin disease classification is a choir cognate for early diagnosis and therapy. The novelty of this study lies in integrating the Grasshopper Optimisation Algorithm (GOA) with a DETR (DEtection TRansformer) model which is developed for the classification of skin disease. Hyperparameter tuning using GOA optimizes the critical parameters of the proposed model to improve classification accuracy. After extensive testing on a large dataset of skin disease photos, the optimised DETR model returned an accuracy of at least 99.26%. The superiority of the DETR improved using GOA compared to standard ones indicates its potential to be used for automatically diagnosing skin diseases. Findings demonstrate that the proposed method contributes to enhancing diagnostic accuracy and creates a basis for improving transformer-based medical image analysis.

Abstract Lysergic acid diethylamide (LSD) and other psychedelic substances profoundly alter human consciousness. While several studies have demonstrated changes in brain function and connectivity associated with psychedelics, we still have a limited understanding of how LSD reshapes brain networks operating across different frequency bands. In this study, we applied the recently developed FREQ-NESS method to MEG data from 14 healthy participants who received LSD under four conditions: eyes-closed with or without music and eyes-open with or without a video stimulus. LSD significantly restructures canonical networks in the alpha and beta bands. Relative to broadband brain activity, it enhances the prominence of high alpha (12.1, 13.3 Hz) across all experimental conditions and high beta (25.3 Hz) in three conditions. Conversely, LSD decreases the prominence of low beta (18.1, 19.3 Hz) in both Open and Closed conditions and low alpha (8.5 Hz) in the latter. In addition, LSD substantially alters the spatial distributions or topographies of the networks. Under LSD, the low alpha (8.5 Hz) network shifts anteriorly toward the motor cortex, while high alpha (12.1, 13.3 Hz) becomes more localized to the visual cortex. Low beta (18.1, 19.3 Hz) expands over the temporal and occipital cortices, whereas high beta (25.3, 26.5 Hz) topographies remain unchanged. Our findings provide critical insights into the specific frequencies and spatial networks in which LSD modulates brain connectivity, adding nuance to prevailing theories about network disintegration under psychedelics. Significance statement Psychedelic substances such as lysergic acid diethylamide (LSD) profoundly alter perception and cognition, yet their effect on brain activity across different frequency bands remains unclear. Using FREQ-NESS applied to MEG data, we show that LSD reorganizes brain networks by enhancing high-frequency alpha and beta rhythms while suppressing lower-frequency counterparts. These changes occur across various experimental conditions and shift the spatial distribution of brain activity, particularly in motor and visual regions. Our findings suggest that LSD modulates brain connectivity in a frequency- and region-specific manner, offering new insights into how psychedelics alter consciousness. This work advances our understanding of LSD’s neural effects, which may be relevant for therapeutic applications and models of brain function.

Diagnosis of female genital tuberculosis (FGTB) remains elusive due to the paucibacillary nature of the disease. We evaluated if analysis of inflammatory pathways of endometrial tissue could establish a better diagnosis of FGTB. One hundred and four infertile women suspected of having GTB or having been treated for GTB in the past, underwent endometrial biopsies for diagnosis and Gene Inflammatory Pathways analysis at our center between 2018-2020. Diagnosis of FGTB was based on acid-fast bacilli culture, immunocytochemistry, nested-polymerase chain reaction, histopathological examination, TB GeneXpert, or combinations thereof. Gene expression profiles were also analyzed. Based on diagnostic tests of 104 women, 44 (42%) were considered TB-positive, 35 (34%) TB-negative, and 25 (24%) TB-negative after TB treatment in the past. Inflammatory pathways were significantly upregulated in TB-positive women versus TB-negative (41%vs. 6%; p =.0005), and in women who were TB-negative after TB treatment in the past versus TB-negative (never treated for TB in the past) (38%vs. 6%; p =.0037). Two-hundred seventy-one genes were upregulated, and 61 genes were downregulated in TB-positive women versus those who were TB-negative. Differentially expressed genes were mapped to various interlinked inflammatory signaling pathways, including mitogen-activated protein kinase (MAPK), Natural Killer (NK) cells, nuclear factor kappa-B (NF-kB), tumor necrosis factor (TNF), and Toll-like receptors (TLR) signaling. Inflammatory pathways and gene expression profiles add to the diagnostic tools to identify TB-positive women at an early stage. The results from this study are still experimental and large multi-centric studies are suggested before their recommendation in routine clinical practice.

Pregnancy-associated hemolytic uremic syndrome (P-aHUS) is an important cause of peripartum acute kidney injury. Studies from Europe have described mutations in complement regulator genes, and data in Indian patients is scarce. Hence this study used multiplex ligation-dependent probe amplification (MLPA) to identify variants in complement genes in P-aHUS patients. We present 17 patients of P-aHUS who were investigated for complement protein levels and genetic analysis with MLPA for complement genes. Plasma exchange therapy was offered to all patients presenting in acute phase. Mean age 26.74 (3.36) years with 15/17 delivered by caesarean section. Eleven patients received early (within 7 days) plasma exchange, three were dialysis-dependent at 3months and seven were dialysis-free. Only one of the three patients receiving late (after 7 days) plasma exchange was dialysis-free. MLPA showed that 11 patients had heterozygous deletions of exons 3, 5, 6 of CFHR1 and upstream region of exons 1, 2, 3, 6 and intron 4 of CFHR3 gene while four patients had homozygous deletions at the same loci. Two patients had no MLPA-detectable variations. This study reports a high proportion of deletions of exons of CFHR1 & CFHR3 genes in Indian P-aHUS patients detectable by MLPA by copy number variations. This needs confirmation in large multicentre studies. Plasma exchange can be an effective therapy in the non-availability of Eculizumab.

MicroRNA are short and non-coding RNA, 18-25 nucleotides in length. They are produced at the early stage of viral infection. The roles played by cellular miRNAs and miRNA-mediated gene-silencing in the COVID-19 epidemic period is critical in order to develop novel therapeutics. We analyzed SARS-CoV-2 Surface Glycoprotein (S) nucleotide sequence originating from India as well as Iran, Australia, Germany, Italy, Russia, China, Japan and Turkey and identified mutation in potential seed location of several human miRNA. Seventy single nucleotide polymorphisms (SNP) were detected in the S gene out of which, 36, 32 and 2 were cases of transitions, transversions and deletions respectively. Eleven human miRNA targets were identified on the reference S gene sequence with a score >80 in the miRDB database. Mutation A845S erased a common binding site of 7 human miRNA (miR-195-5p, miR-16-5p, miR-15b-5p, miR-15a-5p, miR-497-5p, miR-424-5p and miR-6838-5p). A synonymous mutation altered the wild type Ochre stop codon within the S gene sequence (Italy) to Opal thereby changing the seed sequence of miR-511-3p. Similar (synonymous) mutations were detected at amino acid position 659 and 1116 of the S gene where amino acids serine and threonine were retained, abolishing potential seed location for miR-219a-1-3p and miR-20b-3p respectively. The significance of this finding in reference to the strategy to use synthetic miRNA combinations as a novel therapeutic tool is discussed.

The end of 2019 witnessed the outbreak of Coronavirus Disease 2019 (COVID-19), which has continued to be the cause of plight for millions of lives and businesses even in 2020. As the world recovers from the pandemic and plans to return to a state of normalcy, there is a wave of anxiety among all individuals, especially those who intend to resume in-person activity. Studies have proved that wearing a face mask significantly reduces the risk of viral transmission as well as provides a sense of protection. However, it is not feasible to manually track the implementation of this policy. Technology holds the key here. We introduce a Deep Learning based system that can detect instances where face masks are not used properly. Our system consists of a dual-stage Convolutional Neural Network (CNN) architecture capable of detecting masked and unmasked faces and can be integrated with pre-installed CCTV cameras. This will help track safety violations, promote the use of face masks, and ensure a safe working environment.