Autonomous healing of fatigue cracks via cold welding.

Fatigue in metals involves gradual failure through incremental propagation of cracks under repetitive mechanical load. In structural applications, fatigue accounts for up to 90% of in-service failure1,2. Prevention of fatigue relies on implementation of large safety factors and inefficient overdesign3. In traditional metallurgical design for fatigue resistance, microstructures are developed to either arrest or slow the progression of cracks. Crack growth is assumed to be irreversible. By contrast, in other material classes, there is a compelling alternative based on latent healing mechanisms and damage reversal4-9. Here, we report that fatigue cracks in pure metals can undergo intrinsic self-healing. We directly observe the early progression of nanoscale fatigue cracks, and as expected, the cracks advance, deflect and arrest at local microstructural barriers. However, unexpectedly, cracks were also observed to heal by a process that can be described as crack flank cold welding induced by a combination of local stress state and grain boundary migration. The premise that fatigue cracks can autonomously heal in metals through local interaction with microstructural features challenges the most fundamental theories on how engineers design and evaluate fatigue life in structural materials. We discuss the implications for fatigue in a variety of service environments.

Discovery of potent inhibitors of α-synuclein aggregation using structure-based iterative learning.

Machine learning methods hold the promise to reduce the costs and the failure rates of conventional drug discovery pipelines. This issue is especially pressing for neurodegenerative diseases, where the development of disease-modifying drugs has been particularly challenging. To address this problem, we describe here a machine learning approach to identify small molecule inhibitors of α-synuclein aggregation, a process implicated in Parkinson's disease and other synucleinopathies. Because the proliferation of α-synuclein aggregates takes place through autocatalytic secondary nucleation, we aim to identify compounds that bind the catalytic sites on the surface of the aggregates. To achieve this goal, we use structure-based machine learning in an iterative manner to first identify and then progressively optimize secondary nucleation inhibitors. Our results demonstrate that this approach leads to the facile identification of compounds two orders of magnitude more potent than previously reported ones.

Genome-wide transcriptomic and biochemical profiling of major depressive disorder: Unravelling association with susceptibility, severity, and antidepressant response.

Identifying biomarkers for diagnosing Major Depressive Disorder (MDD), assessing its severity, and guiding treatment is crucial. We conducted whole genome transcriptomic study in North Indian population, and analyzed biochemical parameters. Our longitudinal study investigated gene-expression profiles from 72 drug-free MDD patients and 50 healthy controls(HCs) at baseline and 24 patients after 12-weeks of treatment. Gene expression analyses identified differentially expressed genes(DEGs) associated with MDD susceptibility, symptom severity and treatment response, independently validated by qPCR. Hierarchical clustering revealed distinct expression patterns between MDD and HCs, also between mild and severe cases. Enrichment analyses of significant DEGs revealed inflammatory, apoptosis, and immune-related pathways in MDD susceptibility, severity, and treatment response. Simultaneously, we assessed thirty biochemical parameters in the same cohort, showed significant differences between MDD and HCs in 13 parameters with monocytes, eosinophils, creatinine, SGPT, and total protein remained independent predictors of MDD in a multivariate-regression model. Our study supports the role of altered immune/inflammatory signaling in MDD pathophysiology, offering clinically relevant biochemical parameters and insights into transcriptomic gene regulation in MDD pathogenesis and treatment response.

Immune checkpoint molecules in neuroblastoma: A clinical perspective.

High-risk neuroblastoma (NB) is challenging to treat with 5-year long-term survival in patients remaining below 50% and low chances of survival after tumor relapse or recurrence. Different strategies are being tested or under evaluation to destroy resistant tumors and improve survival outcomes in NB patients. Immunotherapy, which uses certain parts of a person's immune system to recognize or kill tumor cells, effectively improves patient outcomes in several types of cancer, including NB. One of the immunotherapy strategies is to block immune checkpoint signaling in tumors to increase tumor immunogenicity and anti-tumor immunity. Immune checkpoint proteins put brakes on immune cell functions to regulate immune activation, but this activity is exploited in tumors to evade immune surveillance and attack. Immune checkpoint proteins play an essential role in NB biology and immune escape mechanisms, which makes these tumors immunologically cold. Therapeutic strategies to block immune checkpoint signaling have shown promising outcomes in NB but only in a subset of patients. However, combining immune checkpoint blockade with other therapies, including conjugated antibody-based immunotherapy, radioimmunotherapy, tumor vaccines, or cellular therapies like modified T or natural killer (NK) cells, has shown encouraging results in enhancing anti-tumor immunity in the preclinical setting. An analysis of publicly available dataset using computational tools has unraveled the complexity of multiple cancer including NB. This review comprehensively summarizes the current information on immune checkpoint molecules, their biology, role in immune suppression and tumor development, and novel therapeutic approaches combining immune checkpoint inhibitors with other therapies to combat high-risk NB.

HIF-1α regulates the expression of the non-conventional isoform of the cd5 gene in T cells under the hypoxic condition: A potential mechanism for CD5neg/low phenotype of infiltrating cells in solid tumors.

CD5, a T-cell receptor (TCR) negative regulator, is reduced on the surface of CD8+ lymphocytes in the tumor microenvironment (TME). Reduced surface CD5 expression (sCD5) occurs due to the preferential transcription of HERV-E derived exon E1B, i.e., anon-conventional formofthe cd5gene instead of its conventional exon E1A. A tumor employs several mechanisms to evade anti-tumor response, and hypoxia is one such mechanism that prevails in the TME and modulates the infiltrated T lymphocytes. We identified hypoxia response elements (HREs) upstream of E1B. We showed binding of HIF-1α onto these HREs and increased E1B mRNA expression in hypoxic T cells. This results in decreased sCD5 expression and increased cytoplasmic accumulation in T cells. We also validated our study in a solid tumor, i.e., colorectal cancer (CRC) patient samples. This hypoxia-driven mechanism reduces the surface CD5 expression on infiltrated T-cells in solid tumors.

Genetic Landscape of Major Depressive Disorder: Assessment of Potential Diagnostic and Antidepressant Response Markers.

BACKGROUND: The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery of evidence-based diagnosis and treatment regimen. This study attempts to curate all genetic association findings to evaluate potential variants for clinical translation. METHODS: We systematically reviewed all candidates and genome-wide association studies for both MDD susceptibility and antidepressant response, independently, using MEDLINE, particularly to identify replicated findings. These variants were evaluated for functional consequences using different in silico tools and further estimated their diagnostic predictability by calculating positive predictive values. RESULTS: A total of 217 significantly associated studies comprising 1200 variants across 545 genes and 128 studies including 921 variants across 412 genes were included with MDD susceptibility and antidepressant response, respectively. Although the majority of associations were confirmed by a single study, we identified 31 and 18 replicated variants (in at least 2 studies) for MDD and antidepressant response. Functional annotation of these 31 variants predicted 20% coding variants as deleterious/damaging and 80.6% variants with regulatory effect. Similarly, the response-related 18 variants revealed 25% coding variant as damaging and 88.2% with substantial regulatory potential. Finally, we could calculate the diagnostic predictability of 19 and 5 variants whose positive predictive values ranges from 0.49 to 0.66 for MDD and 0.36 to 0.66 for response. CONCLUSIONS: The replicated variants presented in our data are promising for disease diagnosis and improved response outcomes. Although these quantitative assessment measures are solely directive of available observational evidence, robust homogenous validation studies are required to strengthen these variants for molecular diagnostic application.

Angle-dependent phononic dynamics for data-driven source localization.

The source angle localization problem is studied based on scattering of elastic waves in two dimensions by a phononic array and the exceptional points of its band structure. Exceptional points are complex singularities of a parameterized eigen-spectrum, where two modes coalesce with identical mode shapes. These special points mark the qualitative transitions in the system behavior and have been proposed for sensing applications. The equi-frequency band structures are analyzed with focus on the angle-dependent modal behaviors. At the exceptional points and critical angles, the eigen-modes switch their energy characteristics and symmetry, leading to enhanced sensitivity as the scattering response of the medium is inherently angle-dependent. An artificial neural network is trained with randomly weighted and superposed eigen-modes to achieve deep learning of the angle-dependent dynamics. The trained algorithm can accurately classify the incident angle of an unknown scattering signal, with minimal sidelobe levels and suppressed main lobewidth. The neural network approach shows superior localization performance compared with standard delay-and-sum technique. The proposed application of the phononic array highlights the physical relevance of band topology and eigen-modes to a technological application, adds extra strength to the existing localization methods, and can be easily enhanced with the fast-growing data-driven techniques.

Insight into the Epigenetics of Kaposi's Sarcoma-Associated Herpesvirus.

Epigenetic reprogramming represents a series of essential events during many cellular processes including oncogenesis. The genome of Kaposi's sarcoma-associated herpesvirus (KSHV), an oncogenic herpesvirus, is predetermined for a well-orchestrated epigenetic reprogramming once it enters into the host cell. The initial epigenetic reprogramming of the KSHV genome allows restricted expression of encoded genes and helps to hide from host immune recognition. Infection with KSHV is associated with Kaposi's sarcoma, multicentric Castleman's disease, KSHV inflammatory cytokine syndrome, and primary effusion lymphoma. The major epigenetic modifications associated with KSHV can be labeled under three broad categories: DNA methylation, histone modifications, and the role of noncoding RNAs. These epigenetic modifications significantly contribute toward the latent-lytic switch of the KSHV lifecycle. This review gives a brief account of the major epigenetic modifications affiliated with the KSHV genome in infected cells and their impact on pathogenesis.

SGLT2i as a First-line Antihyperglycemic in the Management of Type 2 Diabetes in the Context of Indians: A Systematic Review and Consensus.

BACKGROUND: Sodium-glucose cotransporter-2 inhibitors (SGLT2i) have been used for almost a decade and have proven to be effective not only in managing Type 2 diabetes (T2D), but their cardio and renal protective features make them very useful in managing patients with risk of multiple comorbidities. This systematic review was undertaken by the authors because there is no evidence currently available in India that has studied the suitability of SGLT2i as a first-line agent in patients newly diagnosed with T2D in India. MATERIALS AND METHODS: First, literature was searched to identify features that are considered important when deciding on a first-line agent for managing T2D. A total of 5 broad topics were identified-glycemic control, extra glycemic effects, antihyperglycemic combination therapy, safety, and cost-effectiveness. These domains had further subheadings, and a total of 16 domains were identified. Metformin is the drug of choice as a first-line agent in such situations and has been considered the gold standard for evaluating the effects of SGLT2i across these domains. A systematic literature review on each domain was conducted to compare SGLT2i with the gold standard in Indian patients newly diagnosed with T2D. Evidence was graded (levels of evidence (LoE)-A, B, and C), and recommendations (class of recommendation (CoR)-I, II, and III) were classified by the expert group as defined in the methodology. RESULTS: According to the systematic reviews conducted, 11 domains had Level A evidence, 2 domains (impact on lipids and gut microbiome) had Level B, and 3 domains had Level C (ß-cell function, renal protection, and glycemic variability) evidence. Based on evidence and expert opinion, the authors recommend SGLT2i as a first-line agent for managing newly diagnosed patients with T2D with a Class I recommendation for 13 domains and Class II for the remaining 3 (impact on lipids, gut microbiome, and ß-cell function). Although a poorer level of evidence (Level C) was available for the glycemic variability domain, the authors still reported this as Class I recommendations according to their expert opinion and consensus. CONCLUSION: This article advocates adopting SGLT2 inhibitors as the primary treatment choice for treating patients with newly diagnosed T2D in India.

miR-378a regulates keratinocyte responsiveness to interleukin-17A in psoriasis.

BACKGROUND: Psoriasis is an immune-mediated inflammatory skin disease, in which an interplay between infiltrating immune cells and keratinocytes sustains chronic skin inflammation. Interleukin (IL)-17A is a key inflammatory cytokine in psoriasis and its main cellular targets are keratinocytes. OBJECTIVES: To explore the role of miR-378a in psoriasis. METHODS: Keratinocytes obtained from psoriatic skin and healthy epidermis were separated by magnetic sorting, and the expression of miR-378a was analysed by quantitative polymerase chain reaction. The regulation and function of miR-378a was studied using primary human keratinocytes. The expression of miR-378a was modulated by synthetic mimics, and nuclear factor kappa B (NF-κB) activity and transcriptomic changes were studied. Synthetic miR-378a was delivered to mouse skin in conjunction with induction of psoriasiform skin inflammation by imiquimod. RESULTS: We show that miR-378a is induced by IL-17A in keratinocytes through NF-κB, C/EBP-ß and IκBζ and that it is overexpressed in psoriatic epidermis. In cultured keratinocytes, ectopic expression of miR-378a resulted in the nuclear translocation of p65 and enhanced NF-κB-driven promoter activity even in the absence of inflammatory stimuli. Moreover, miR-378a potentiated the effect of IL-17A on NF-κB nuclear translocation and downstream activation of the NF-κB pathway. Finally, injection of miR-378a into mouse skin augmented psoriasis-like skin inflammation with increased epidermal proliferation and induction of inflammatory mediators. Mechanistically, miR-378a acts as a suppressor of NFKBIA/IκBζ, an important negative regulator of the NF-κB pathway in keratinocytes. CONCLUSIONS: Collectively, our findings identify miR-378a as an amplifier of IL-17A-induced NF-κB signalling in keratinocytes and suggest that increased miR-378a levels contribute to the amplification of IL-17A-driven skin inflammation in psoriasis.

Forensic characterization of 124 SNPs in the central Indian population using precision ID Identity Panel through next-generation sequencing.

With the advent of next-generation sequencing technology, SNP markers are being explored as a useful alternative to conventional capillary electrophoresis-based STR typing. Low mutation rate and short-sized amplicons are added advantages of SNP markers over the STRs. However, to achieve a sufficient level of discrimination among individuals, a higher number of SNPs need to be characterized simultaneously. Hence, the NGS technique is highly useful to analyze a sufficiently higher number of SNPs simultaneously. Though the technique is in its nascent stage, an attempt has been made to assess its usability in the central Indian population by analyzing 124 SNPs (90 autosomal and 34 Y-chromosome) in 95 individuals. Various quality parameters such as locus balance, locus strand balance, heterozygosity balance, and noise level showed a good quality sequence obtained from the Ion GeneStudio S5 instrument. Obtained frequency of SNP alleles ranged from 0.001 to 0.377 in autosomal SNPs. rs9951171 was found to be the most informative SNP in the studied population with the highest PD and lowest MP value. The cumulative MP of 90 SNPs was found to be 4.76698 × 10-37. Analysis of 34 Y-chromosome SNPs reveals 11 unique haplogroups in 54 male samples with R1a1 as the most frequent haplogroup found in 22.22% of samples. Interpopulation comparison by FST analysis, PCA plot, and STRUCTURE analysis showed genetic stratification of the studied population suggesting the utility of SNP markers present in the Precision ID Identity Panel for forensic demands of the Indian population.

Genetic portrait of 23 Y-STR loci in the Naga tribes of Nagaland, India.

To explore the genomic diversity and forensic characterization of Naga tribes, Nagaland, haplotypes for 23 Y-STR markers have been analyzed. In this study, 203 unrelated male individuals residing in the Northeast Indian state of Nagaland were selected. A total of 203 unique haplotypes were observed. The value of gene diversity (GD) and discrimination capacity (DC) was observed as 0.999999998927955 and 1 respectively. Forensic interest parameters viz., power of discrimination (PD), polymorphic information content (PIC), and matching probability (PM) were found to be 0.999999998695503, 0.999999976671191, and 1.3 × 10-9 respectively, for the studied population. Inter-population comparison study showed that the Naga tribes were found to have a distinct gene pool which is reflected in the neighbor-joining tree, principle coordinate analysis, and heat map. This is the first genetic study on Naga tribes based on 23 Y-STR markers. The Y chromosomal STR data will be useful for forensic DNA application and will enrich the existing Indian Y-STR database.

Molecular characterization of 23 Y chromosomal STR markers in the Gurjar population of National Capital Region (NCR), India.

In the present study, DNA samples of 202 unrelated male individuals of Gurjar population were evaluated for the molecular diversity at 23 Y chromosomal Y-STR markers. Out of selected individuals, results showed 143 unique haplotypes. Highest degree of gene diversity (GD), polymorphic information content (PIC), and power of discrimination (PD) was observed as 0.7941, 0.7590, and 0.7902, respectively, for the locus DYS385a/b. Haplotype diversity (HD), gene diversity (GD), polymorphic information content (PIC), and power of discrimination (PD) was found to be 0.7079, 0.999999999989, 0.9999999996, and 0.999999999986, respectively, for the studied 23 Y-STR markers. Allele 11 of locus DYS392 was found to be the most frequent allele with the frequency of 0.762. In inter-population relationship, studied population showed genetic relatedness with the population of Jammu and Kashmir, India, and Ladakh, India. The haplotype data of the present study will not only enrich the existing Indian Y-STR data but will also be useful for forensic DNA application.

An evaluation of inter and intra population structure of Uttar Pradesh, inferred from 24 autosomal STRs.

AIM: The present study was designed to explore the STR diversity and genomic history of the inhabitants of the most populous subdivision of the country. A set of 24 hypervariable autosomal STRs was used to estimate the genetic diversity within the studied population. A panel of 15 autosomal STRs, which is most common in the previously reported data sets, was used to estimate the genetic diversity between the studied population, and obtained unique relations were reported here. METHOD: The genetic diversity and polymorphism among 636 individuals of different ethnic groups, residing in Bareilly, Pilibhit, Shahjahanpur, Gorakhpur, Jhansi, and Varanasi regions of Uttar Pradesh, India, was investigated. This investigation was carried out via 24 autosomal STRs. RESULT: The 24 loci studied showed the highest value of combined power of discrimination (CPD = 1), combined power of exclusion (CPE = 0.99999999985), combined paternity index (CPI = 6.10 × 109) and lowest combined matching probability (CPM = 7.90 × 10-31). CONCLUSION: The studied population showed genetic closeness with the population of Uttarakhand, the Jats of Delhi,the Jat Sikh (Punjab), and the population of Rajasthan. Among the tested loci, SE33 and Penta E were found to be most useful in terms of the highest discrimination power, lowest matching probability, the highest power of exclusion, and highest polymorphism information content for the Uttar Pradesh population .

Simplex Back Propagation Estimation Method for Out-of-Sequence Attitude Sensor Measurements.

For a small satellite, the processor onboard the attitude determination and control system (ADCS) is required to monitor, communicate, and control all the sensors and actuators. In addition, the processor is required to consistently communicate with the satellite bus. Consequently, the processor is unable to ensure all the sensors and actuators will immediately respond to the data acquisition request, which leads to asynchronous data problems. The extended Kalman filter (EKF) is commonly used in the attitude determination process, but it assumes fully synchronous data. The asynchronous data problem would greatly degrade the attitude determination accuracy by EKF. To minimize the attitude estimation accuracy loss due to asynchronous data while ensuring a reasonable computational complexity for small satellite applications, this paper proposes the simplex-back-propagation Kalman filter (SBPKF). The proposed SBPKF incorporates the time delay, gyro instability, and navigation error into both the measurement and covariance estimation during the Kalman update process. The performance of SBPKF has been compared with EKF, modified adaptive EKF (MAEKF), and moving-covariance Kalman filter (MC-KF). Simulation results show that the attitude estimation error of SBPKF is at least 30% better than EKF and MC-KF. In addition, the SBPKF's computational complexity is 17% lower than MAEKF and 29% lower than MC-KF.

Cross-talk between IFN-γ and TWEAK through miR-149 amplifies skin inflammation in psoriasis.

BACKGROUND: Psoriasis is a chronic inflammatory skin disease with disturbed interplay between immune cells and keratinocytes. A strong IFN-γ signature is characteristic for psoriasis skin, but the role of IFN-γ has been elusive. MicroRNAs are short RNAs regulating gene expression. OBJECTIVE: Our aim was to investigate the role of miR-149 in psoriasis and in the inflammatory responses of keratinocytes. METHODS: miR-149 expression was measured by quantitative RT-PCR in keratinocytes isolated from healthy skin and lesional and nonlesional psoriasis skin. Synthetic miR-149 was injected intradermally into the back skin of mice, and imiquimod was applied to induce psoriasis-like skin inflammation, which was then evaluated at the morphologic, histologic, and molecular levels. miR-149 was transiently overexpressed or inhibited in keratinocytes in combination with IFN-γ- and/or TNF-related weak inducer of apoptosis (TWEAK)-treatment. RESULTS: Here we report a microRNA-mediated mechanism by which IFN-γ primes keratinocytes to inflammatory stimuli. Treatment with IFN-γ results in a rapid and long-lasting suppression of miR-149 in keratinocytes. Depletion of miR-149 in keratinocytes leads to widespread transcriptomic changes and induction of inflammatory mediators with enrichment of the TWEAK pathway. We show that IFN-γ-mediated suppression of miR-149 leads to amplified inflammatory responses to TWEAK. TWEAK receptor (TWEAKR/Fn14) is identified as a novel direct target of miR-149. The in vivo relevance of this pathway is supported by decreased miR-149 expression in psoriasis keratinocytes, as well as by the protective effect of synthetic miR-149 in the imiquimod-induced mouse model of psoriasis. CONCLUSION: Our data define a new mechanism, in which IFN-γ primes keratinocytes for TWEAK-induced inflammatory responses through suppression of miR-149, promoting skin inflammation.

Chromatin interactions in differentiating keratinocytes reveal novel atopic dermatitis- and psoriasis-associated genes.

BACKGROUND: Hundreds of variants associated with atopic dermatitis (AD) and psoriasis, 2 common inflammatory skin disorders, have previously been discovered through genome-wide association studies (GWASs). The majority of these variants are in noncoding regions, and their target genes remain largely unclear. OBJECTIVE: We sought to understand the effects of these noncoding variants on the development of AD and psoriasis by linking them to the genes that they regulate. METHODS: We constructed genomic 3-dimensional maps of human keratinocytes during differentiation by using targeted chromosome conformation capture (Capture Hi-C) targeting more than 20,000 promoters and 214 GWAS variants and combined these data with transcriptome and epigenomic data sets. We validated our results with reporter assays, clustered regularly interspaced short palindromic repeats activation, and examination of patient gene expression from previous studies. RESULTS: We identified 118 target genes of 82 AD and psoriasis GWAS variants. Differential expression of 58 of the 118 target genes (49%) occurred in either AD or psoriatic lesions, many of which were not previously linked to any skin disease. We highlighted the genes AFG1L, CLINT1, ADO, LINC00302, and RP1-140J1.1 and provided further evidence for their potential roles in AD and psoriasis. CONCLUSIONS: Our work focused on skin barrier pathology through investigation of the interaction profile of GWAS variants during keratinocyte differentiation. We have provided a catalogue of candidate genes that could modulate the risk of AD and psoriasis. Given that only 35% of the target genes are the gene nearest to the known GWAS variants, we expect that our work will contribute to the discovery of novel pathways involved in AD and psoriasis.

Comparative Effectiveness of Pre-Identified Homeopathic Medicines in Asymptomatic COVID-19 Individuals Receiving Standard Care-An Open-Label, Randomized, Controlled Exploratory Trial.

BACKGROUND: Asymptomatic COVID-19 subjects can transmit the infection for as many as 14 days and are regarded as a significant factor in the rapid spread of the COVID-19 pandemic. This exploratory study aimed to determine any additional benefits of selected homeopathic medicines compared with placebo in asymptomatic COVID-19 individuals receiving standard care. METHODS: This open-label, randomized, placebo-controlled, exploratory trial was undertaken at a COVID Care Centre (CCC) in Madhya Pradesh, India. Patients (n = 200, 18-65 years, both sexes) having a positive RT-PCR and asymptomatic during admission were enrolled. They were randomly assigned to one of four groups (each n = 50): Arsenicum album 30C (Ars. alb.), Camphora 1M (Camph.), Bryonia alba 30C (Bry. alb.) and placebo (Pl.). All the patients were given standard care. The primary outcome was the number of patients becoming RT-PCR negative for SARS-CoV-2 at days 5, 10 and 15. RESULTS: In total, 200 asymptomatic COVID-19 patients were enrolled. One hundred and seventy-seven patients became RT-PCR negative by day 15; 88%, 80%, 98% and 88% from Ars. alb., Camph., Bry. alb. and Pl. respectively. A Chi-square test of association for the total patients who became RT-PCR negative for SARS-Cov-2 in each group showed a marginal statistical significance (Chi-square: 8.1, p = 0.04). A two-proportion Z-test comparing each pre-identified homeopathic medicine with placebo showed marginal statistical significance (p = 0.05) for Bry alb. only. Median time in days to RT-PCR negative (Kaplan Meier analysis) was 10 days in each of the groups. CONCLUSION: There was some evidence that, compared with Ars alb., Camph. or Pl., Bry. alb. was associated with an increased number of patients who became RT-PCR negative for COVID-19 by day 15. The possible effect exerted needs to be investigated in additional research.

Genetic diversity and forensic characterization of 15 autosomal microsatellite markers in the North-east Indian Tripuri population.

This study was conducted to explore the genomic diversity and forensic characterization of 15 autosomal microsatellite markers in the East Indian Tripuri population. In the studied population, we observed 158 different alleles with the average 10.53 alleles per locus. The locus D2S1338 (PIC= 0.862) was found to be the most polymorphic wheres locus TPOX (PIC= 0.647) as the least polymorphic, among all the studied loci. The locus FGA was found with the highest number of effective alleles (Nall=19) whereas locus TH01 showed least number of effective alleles (Nall=6). The cumulative values for matching probability (CPm), power of discrimination (CPD), power of exclusion CPE), and paternity index (CPI) were found as 1.94×10-18, 1, 0.999998, and 4.8×105 respectively. The studied population showed genetic closeness with the Gorkha population. In neighbor-joining tree, Tripura population pooled with the population of Nepal and Tibet. The genetic data obtained from the present study will not only enrich the existing autosomal STR database but will also be useful for forensic DNA application and genealogical studies.

Forensic characterization and genomic diversity of Assam population viewed from 23 autosomal STRs.

In order to find out the genetic structure and characterize the forensic features of 23 autosomal STRs in the population of Assam, PowerPlex® Fusion 6C amplification kit was employed to genotype 292 unrelated individuals from Assam, India. A total of 79 different alleles were observed across 23 autosomal STRs with the corresponding frequency of alleles, which ranges from 0.002 to 0.406. Selected 23 loci were observed useful together with the highest value of combined discrimination power (CPD = 1), combined exclusion power (CPE = 0.999999999914), combined paternity index (CPI = 3.04 × 109), and all studied loci combined showing the lowest matching probability which is (CPM = 1.29 × 10-29). Additionally, in comparison with neighboring population, Assam population showed genetic closeness with Indian population. The genetic data of the present study will enrich the existing Indian autosomal DNA database and be useful for forensic and genealogical applications.