Population differentiation of southern Indian male lineages correlates with agricultural expansions predating the caste system

Previous studies that pooled Indian populations from a wide variety of geographical locations, have obtained contradictory conclusions about the processes of the establishment of the Varna caste system and its genetic impact on the origins and demographic histories of Indian populations. To further investigate these questions we took advantage that both Y chromosome and caste designation are paternally inherited, and genotyped 1,680 Y chromosomes representing 12 tribal and 19 non-tribal (caste) endogamous populations from the predominantly Dravidian-speaking Tamil Nadu state in the southernmost part of India. Tribes and castes were both characterized by an overwhelming proportion of putatively Indian autochthonous Y-chromosomal haplogroups (H-M69, F-M89, R1a1-M17, L1-M27, R2-M124, and C5-M356; 81% combined) with a shared genetic heritage dating back to the late Pleistocene (10–30 Kya), suggesting that more recent Holocene migrations from western Eurasia contributed <20% of the male lineages. We found strong evidence for genetic structure, associated primarily with the current mode of subsistence. Coalescence analysis suggested that the social stratification was established 4–6 Kya and there was little admixture during the last 3 Kya, implying a minimal genetic impact of the Varna (caste) system from the historically-documented Brahmin migrations into the area. In contrast, the overall Y-chromosomal patterns, the time depth of population diversifications and the period of differentiation were best explained by the emergence of agricultural technology in South Asia. These results highlight the utility of detailed local genetic studies within India, without prior assumptions about the importance of Varna rank status for population grouping, to obtain new insights into the relative influences of past demographic events for the population structure of the whole of modern India.

Hemoglobin Athens-Georgia, or alpha 2 beta 2 40(C6)Arg replaced by Lys, a hemoglobin variant with an increased oxygen affinity

A new hemoglobin variant, termed hemoglobin Athens-Georgia, has been found in a 23-year-old Caucasian student and three members of her family. The electrophoretic mobility of this variant at pH 9.0 is slightly less than that of hemoglobin-A. Arginyl residue in position 40 of the beta chain, corresponding to position 6 of the C helix, has been replaced by a lysyl residue. This amino acid substitution is at the alpha1-beta2 contact and slightly affects the oxygen binding properties of the hemoglobin molecule. Hemoglobin Athens-Georgia has an increased affinity for oxygen, a normal heme-heme interaction and a normal Bohr effect. Hematological abnormalities are not associated with this variant.

Hb-Alberta or alpha2beta2 (101(G3) Glu replaced by Gly), a new high-oxygen-affinity hemoglobin variant causing erythrocytosis

Hb-Alberta has been found in a 51 year old Caucasian male with erythrocytosis. The substitution in this variant involves the glutamyl residue in position 101(G3) of the beta chain which is replaced by a glycyl residue. Hb-Alberta accounts for about 45% in the heterozygote, and readily forms hybrid tetramers with other hemoglobins. The oxygen affinity of Hb-Alberta is greatly increased, its Bohr effect reduced, and its subunit interaction greatly diminished.

Deep transfer learning for COVID-19 detection and infection localization with superpixel based segmentation

The evolution the novel corona virus disease (COVID-19) as a pandemic has inflicted several thousand deaths per day endangering the lives of millions of people across the globe. In addition to thermal scanning mechanisms, chest imaging examinations provide valuable insights to the detection of this virus, diagnosis and prognosis of the infections. Though Chest CT and Chest X-ray imaging are common in the clinical protocols of COVID-19 management, the latter is highly preferred, attributed to its simple image acquisition procedure and mobility of the imaging mechanism. However, Chest X-ray images are found to be less sensitive compared to Chest CT images in detecting infections in the early stages. In this paper, we propose a deep learning based framework to enhance the diagnostic values of these images for improved clinical outcomes. It is realized as a variant of the conventional SqueezeNet classifier with segmentation capabilities, which is trained with deep features extracted from the Chest X-ray images of a standard dataset for binary and multi class classification. The binary classifier achieves an accuracy of 99.53% in the discrimination of COVID-19 and Non COVID-19 images. Similarly, the multi class classifier performs classification of COVID-19, Viral Pneumonia and Normal cases with an accuracy of 99.79%. This model called the COVID-19 Super pixel SqueezNet (COVID-SSNet) performs super pixel segmentation of the activation maps to extract the regions of interest which carry perceptual image features and constructs an overlay of the Chest X-ray images with these regions. The proposed classifier model adds significant value to the Chest X-rays for an integral examination of the image features and the image regions influencing the classifier decisions to expedite the COVID-19 treatment regimen.

KIR : HLA association with clinical manifestations of HBV infection in Madurai, south India

The antiviral action of natural killer (NK) cells is regulated by a wide repertoire of germ-line encoded membrane receptors which recognize the expression of certain self-molecules on target cells. Among the receptors, killer cell immunoglobulinlike receptor (KIR) which recognizes the expression of human leukocyte antigen (HLA) class I has a predominant role in regulating the effector functions of NK cells, particularly in viral infections.We studied a total of 128 hepatitis B virus (HBV) patients (15 acute, 43 asymptomatic, 27 chronic and 43 with other liver diseases) while attending the Department of Medical Gastroenterology, Government Rajaji Hospital, Madurai, India, and 128 ethnic matched control to find the association between the KIR : HLA genes and differential manifestations of HBV. KIR and its ligand HLA polymorphism were identified by DNAPCR methods. The activatory receptor KIR-2DS1 was significantly elevated in various disease categories, namely asymptomatic, chronic and other HBV, except acute HBV infection. Whereas, KIR 2DS3 in acute and chronic patients and KIR 2DS5 and 3DS1 in asymptomatic individuals. Among various KIR-HLA combinations, homozygous 2DS2:C1 and individuals with 3DSI:BW4 (OR = 3.23, CI = 1.55-6.7, Pc = 0.02) are associated with HBV asymptomatism, while most of the two domain inhibitory receptors with their ligands showed significant risk in other liver diseases. Further, KIR3DL1 : HLA Bw4Iso80 (OR = 3.89, 95% CI = 1.58-9.55, Pc = 0.004) is related with higher risk for asymptomatic infection when compared with chronic HBV. Thus, the select KIR : HLA alleles and combinations seem to direct the NK cell activities and immune response in different directions resulting in varied symptoms and manifestations in the subgroups of HBV-infected patients studied.

SLC30A8 Gene rs13266634 C/T Polymorphism in Children with Type 1 Diabetes in Tamil Nadu, India

Objective

Zinc transporter 8 (ZnT8) is a multi-transmembrane protein situated in the insulin secretory granule of the islets of β-cells and is identified as a novel auto-antigen in type 1 diabetes (T1D). The gene coding for ZnT8, solute carrier family 30 member 8 (SLC30A8) is located on chromosome 8q24.11. This study aimed to identify the association of SLC30A8 rs13266634 C/T gene polymorphism with T1D in a sample of T1D children in Tamil Nadu, India.

Methods

The family based study was conducted in 121 T1D patients and 214 of their family members as controls. The SLC30A8 gene rs13266634 C/T polymorphism was evaluated by polymerase chain reaction-restriction fragment length polymorphism.

Results

No significant differences were observed in either allele (odds ratio: 0.92; confidence interval: 0.33-2.58; p=0.88) and genotype (CC: p=0.74; CT: p=0.82; TT: p=0.80) frequencies of rs13266634 C/T between T1D patients and controls. Transmission disequilibrium test has identified over-transmission of mutant T allele from parents to affected children (T: U=9:7) without statistical significance. Metaanalysis on the overall effects of rs13266634 C allele frequency was not different (p=0.10 and Pheterogeneity=0.99) in T1D patients as compared to the controls.

Conclusion

The present study along with the meta-analysis does not show any substantial association of the rs13266634 C/T polymorphism with T1D development in this population.

Association of CTLA-4 and CD28 Gene Polymorphisms with Type 1 Diabetes in South Indian Population

Each functional gene illustrates the complexity of genetic predisposition to disease; however, it is difficult to bring out these traits with reference to autoimmune diseases like type 1 diabetes (T1D). To find out the genetic contribution of CTLA-4 + 49A/G, CTLA-4 -318C/T and CD28 + 17T/C polymorphisms toward T1D, the present study was performed with 124 T1D patients, 54 siblings and 125 parents including 39 trios in South Indian population. The association and linkage of CTLA-4 + 49A/G, CTLA-4 -318C/T and CD28 + 17T/C polymorphisms with T1D were analyzed and transmission disequilibrium test was performed. CTLA-4 G allele carrying genotypes (GG+AG) showed a higher risk association and can be considered as susceptible to develop T1D among patients with age at diagnosis from 0 to 10 years as compared to siblings (OR = 2.9; p_c = 0.047) and parents (OR = 2.7; p_c = 0.036). On the other hand, a strong protection against the disease (age at diagnosis; 0-10 years) was observed with CTLA-4 + 49AA genotype (OR = 0.37; p_c = 0.036) and combined AA/CC genotype (OR = 0.31; p_c = 0.034) of CTLA-4 + 49A/G and CTLA-4 -318C/T polymorphisms. However, a significant association was not observed between CTLA-4 -318C/T and CD28 + 17T/C polymorphisms and T1D. This family-based study reports a strong association between possible genotypes of CTLA-4 gene polymorphism and T1D in South Indian population, particularly in younger individuals.

A genetic algorithm-based energy-aware multi-hop clustering scheme for heterogeneous wireless sensor networks

BACKGROUND

The energy-constrained heterogeneous nodes are the most challenging wireless sensor networks (WSNs) for developing energy-aware clustering schemes. Although various clustering approaches are proven to minimise energy consumption and delay and extend the network lifetime by selecting optimum cluster heads (CHs), it is still a crucial challenge.

METHODS

This article proposes a genetic algorithm-based energy-aware multi-hop clustering (GA-EMC) scheme for heterogeneous WSNs (HWSNs). In HWSNs, all the nodes have varying initial energy and typically have an energy consumption restriction. A genetic algorithm determines the optimal CHs and their positions in the network. The fitness of chromosomes is calculated in terms of distance, optimal CHs, and the node's residual energy. Multi-hop communication improves energy efficiency in HWSNs. The areas near the sink are deployed with more supernodes far away from the sink to solve the hot spot problem in WSNs near the sink node.

RESULTS

Simulation results proclaim that the GA-EMC scheme achieves a more extended network lifetime network stability and minimises delay than existing approaches in heterogeneous nature.

Association of Killer Cell Immunoglobulin-Like Receptors and Their HLA-Ligands with Type 1 Diabetes Among South Indian Population

BACKGROUND

Type 1 diabetes (T1D) is a multifactorial autoimmune disease, involving strong genetic components with familial predisposition. Killer cell immunoglobulin-like receptors (KIRs) found on the surface of NK cells have ligands of human leukocyte antigen (HLA) class I that are associated with T1D. The present study evaluates the influence of KIR genes and their HLA-ligands in the aetiology of T1D among the South Indian population.

METHODS

A total of 125 T1D patients, along with their parents (n = 126) and siblings (n = 52) were recruited. PCR-based genotyping was performed for KIR genes and HLA class I ligands. The gene frequencies were compared between patients and siblings/parents. Linkage-disequilibrium (LD) analysis was performed to assess the genetic association between KIR gene pairs.

RESULTS

The results show significant differences in HLA-ligands of KIR genes between patients and parents. The HLA-C1C1 homozygosity was found to be a predisposing risk factor, and HLA-C1C2 heterozygosity was protective towards T1D along with either the activating KIR2DS2 or inhibitory KIRs 2DL1, 2DL2, 2DL3. However, the frequency of inhibitory KIR3DL1 significantly increased in the presence of HLA-B Bw4 Ile80 in parents when compared to patients showing a protective effect on T1D. Two pairs of KIR genes, 2DS4-3DL1 and 2DS1-2DL5, showed strong LD in patients, siblings and parents.

CONCLUSION

The KIR-HLA ligand combinations have a significant effect on T1D aetiology among the South Indian population. This study defines a pattern for family-based association studies with genotypic information about KIR genes and their HLA-ligands, providing the first evidence towards T1D among the South Indian population.

Optimization of fuzzy K-objective fractional assignment problem using fuzzy programming model

The assignment problem is one of the core combinatorial optimization problems in the optimization branch, and the theory and applications of fractional programming have made great strides in recent years. Usually, the possible coefficient values of linear fractional programming and real-world problems are frequently only known to the decision in vague or uncertain terms. Hence, it would be more acceptable to interpret the coefficients for as fuzzy numerical information. In this paper, a fuzzy bi-objective fractional assignment (FBOFAP) has been formulated. A problem has been defined. Here, triangular shapes are used to indicate the parameters. The fuzzy problem is turned into a typical crisp problem through α-cut using a fuzzy number and then the compromise solution is generated by fuzzy programming.

Relook at Aileron to Rudder Interconnect

The implementation of interconnect gain from aileron to rudder surface on the majority of the aircraftis to decrease sideslip which is generated because of adverse yaw with the movement of control stick in lateral axis and also enhances the turning rate performance.The Aileron to Rudder Interconnect (ARI)involves significant part to decouple the Dutch roll oscillations from roll rate response to aileron command. ARI is feed-forward gain whichis susceptible to aircraft system uncertainty. Incorrect ARI gain can lead to side slip buildup which can cause aircraft to depart in case of fault scenarios. Four systematic ARI design methods are proposed. One of the proposed methods which use the norm of ARI transfer function at roll damping frequency is suitable for online reconfiguration of control law. The reconfiguration of ARI gain is illustratedwith the simulation responses of fault scenario case of aileron surface damage.

Navigating green synthesized metal-based nanoparticles as anti-inflammatory agent - Comprehensive review

The biosynthesis of nanomaterials is a vast and expanding field of study due to their applications in a variety of fields, particularly the pharmaceutical and biomedical fields. Various synthetic routes, including physical and chemical methods, have been developed in order to generate metal nanoparticles (NPs) with definite shapes and sizes. In this review, focused on the recent advancements in the green synthetic methods for the generation of silver, zinc and copper NPs with simple and eco-friendly approaches and the potential of the biosynthesized metal and metal oxide NPs as alternative and therapeutic agent for the treatment of inflammatory diseases. Inflammation is a body's own defense mechanism that can become chronic inflammation affecting healthy cells. Owning to the size-based advantages of NPs which can mitigate in theses medical conditions and serve as anti-inflammatory drugs. The factors influencing their physicochemical properties, toxicity, biocompatibility and mode of action to formulate an effective nanomedicine in the treatment of inflammation.