257 research outputs found
Oocyte Age‐Dependent DNA Damage Can Be Reverted by the DNA Repair Competent Karyoplasm of Young Oocytes
No full textMammalian fully grown oocytes are believed to exhibit a weakened DNA damage response, leading to the accumulation of substantial levels of DNA damage and increased frequency of aneuploidies in an age-dependent manner. These hallmarks of reproductive ageing are generally presumed to be irreversible by rendering the oocyte chromosome complement incompatible with development. To test whether this is indeed true, we performed a series of germinal vesicle (GV) transfers between oocytes from females of late breeding/post-breeding age and oocytes from young animals. Our results show that age-associated DNA damage can be effectively suppressed: introducing the GVs of advanced-maternal-age (AMA) oocytes into DNA repair-competent cytoplasts generated by selective enucleation (SE) of young oocytes effectively suppresses the signs of age-dependent DNA damage. This is accompanied by a partial recovery of the chromatin dynamics and, surprisingly, a higher fidelity of chromosome segregation. By dissecting the GV fractions, we show that the ability to sense and repair DNA is linked to the free, non-chromatin-bound nuclear factors but not the oocyte nucleolus. Finally, we show that the overall improved state of the reconstructed oocytes is accompanied by enhanced full-term development. Therefore, contrary to popular belief, our results show that the age-associated decline in oocyte quality can be effectively mitigated, opening new possibilities for cell-based oocyte therapy
Clinical-exome sequencing unveils the genetic landscape of polycystic ovarian syndrome (PCOS) focusing on lean and obese phenotypes: implications for cost-effective diagnosis and personalized treatment
No full textAbstract Polycystic ovarian syndrome (PCOS) is one of the most common endocrinopathies among reproductive women worldwide, contributing greatly on the incidence of female infertility and gynecological cancers. It is a complex health condition combining of multiple symptoms like androgen excess, uncontrolled weight gain, alopecia, hirsutism, etc. Conventionally PCOS was associated with obesity while it is often found among lean women nowadays, making the disease more critical to diagnose as well treatment. The disorder has an impact on several signal transduction pathways, including steroidogenesis, steroid hormone activity, gonadotrophin regulation, insulin secretion, energy balance, and chronic inflammation. Understanding the aetiology and pathophysiology of PCOS is difficult due to its multiple causes, which include environmental factors, intricate genetic predisposition, and epigenetic modifications. Despite research supporting the role of familial aggregations in PCOS outcomes, the inheritance pattern remains unknown. Henceforth, to reduce the burden of PCOS, it is inevitably important to diagnose at early ages as well as intervene through personalized medicine. With this brief background, it was imperative to elucidate the genetic architecture of PCOS considering BMI as an controlling factor. This study aims to investigate the genetic basis behind obesity-mediated PCOS, focusing on both obese and lean individuals. It uses a comprehensive bioinformatics methodology to depict pathways and functionality enrichment, allowing for cost-effective risk prediction and management. In the present research, the representative study participants (N = 2) were chosen from a cross-sectional epidemiological survey, based on their anthropometric parameters and confirmation of PCOS. Upon voluntary participation and written consent, biological fluids (whole blood and buccal swab) were taken from where DNA was extracted. The clinical-exome sequencing was performed by the Next-generation Illumina platform using the Twist Human Comprehensive Exome Kit. A comprehensive bioinformatics methodology was employed to identify the most important, unique, and common genes. A total of 26,550 variants were identified in clinically important exomes from two samples, with 5170 common and 2232 and 2322 unique among PCOS lean and obese phenotypes, respectively. Only 262 and 94 variants were PCOS-specific in lean and obese PCOS. Three filters were applied to shortlist the most potent variants, with 4 unique variants in lean PCOS, 2 unique variants in obese PCOS, and 5 common variants in both. The study found that leptin signalling impairment and insulin resistance, as well as mutations in CYP1A1, CYP19A1, ESR1, AR, AMH, AdipoR1, NAMPT, NPY, PTEN, EGFR, and Akt, all play significant roles in PCOS in the studied group. Young women in West Bengal, India, are more likely to have co-occurring PCOS, which includes estrogen resistance, leptin receptor insufficiency, folate deficiency, T2DM, and acanthosis nigricans, with obesity being a common phenotypic expression
Risk of occupational exposure to asbestos, silicon and arsenic on pulmonary disorders: Understanding the genetic-epigenetic interplay and future prospects
No full textIndia needs a better gully erosion map
No full textGully erosion affects India widely. Badlands, the most extreme form of land degradation caused by gullying, are also observed across large parts of Central and Western India. Akin to other environmental issues, accurate maps are critical in planning and implementing land management measures to address gully erosion. While country-wide gully erosion maps are rare commodities, India is probably the only country having several datasets including such maps. Gullies and badlands have been mapped as part of nationwide geomorphological, land degradation and wastelands mapping endeavours. However, upon examination of said maps using high-resolution imagery on Google Earth, it was found that they are largely imprecise, with each having false positive rates (gully erosion mapped where it is not present) of greater than 70%. It is suspected that the coarse spatial resolution of the satellite images used (LISS-III 23.5 m) is the root cause of such low accuracy, but feature misinterpretation by the analysts might also have contributed to it. As such, there is little to no reliable information on the magnitude of the gully erosion problem in India. Therefore, a bespoke high-resolution gully erosion map is of the essence in India’s drive to realize land degradation neutrality by 2030
India needs a better gully erosion map
No full textGully erosion affects India widely. Badlands, the most
extreme form of land degradation caused by gullying,
are also observed across large parts of Central and
Western India. Akin to other environmental issues, accurate maps are critical in planning and implementing
land management measures to address gully erosion.
While country-wide gully erosion maps are rare commodities, India is probably the only country having several
datasets including such maps. Gullies and badlands
have been mapped as part of nationwide geomorphological, land degradation and wastelands mapping endeavours. However, upon examination of said maps using
high-resolution imagery on Google Earth, it was found
that they are largely imprecise, with each having false
positive rates (gully erosion mapped where it is not
present) of greater than 70%. It is suspected that the
coarse spatial resolution of the satellite images used
(LISS-III 23.5 m) is the root cause of such low accuracy,
but feature misinterpretation by the analysts might also
have contributed to it. As such, there is little to no reliable information on the magnitude of the gully erosion
problem in India. Therefore, a bespoke high-resolution
gully erosion map is of the essence in India’s drive to
realize land degradation neutrality by 2030
Epigenetic alteration of mismatch repair genes in the population chronically exposed to arsenic in West Bengal, India
No full textLPWAN Performance Enhancement for IoT in the Smart Grid
No full textWith the proliferation of IoT devices across the globe, the adoption of IoT related technologies has been increasing rapidly. Newer technologies which fall in the category of Low Power Wide Area Network (LPWAN) have increased this adoption even further. A lot of research is being done in LPWAN licensed band as well as unlicensed band technologies to make them more efficient, such as in terms of power consumption and latency. In this thesis the author has focused on cellular IoT technologies (licensed spectrum LPWAN technologies), to improve the end-to-end behavior. The focus is to see and improve the effect of the device on the network behavior. We have done tests on different networks and went through the 3GPP Specification Release 14 to find possible areas of improvement. Keeping this in mind we have designed a solution to increase the number of pageable devices that can be maintained by the network compared to its original capacity (when not using our solution). This solution can be used to optimize as per the use case, whether to provide lower latency or save energy consumption of the device. To verify that the solution can be used in real life, we have tested it with Stedin critical application device in their substation.Electrical Engineering | Embedded System
Understanding Interactions in Social Networks and Committees
No full textWhile much of the literature on cross section dependence has fo?cused mainly on estimation of the regression coefficients in the under?lying model, estimation and inferences on the magnitude and strength of spill-overs and interactions has been largely ignored. At the same time, such inferences are important in many applications, not least because they have structural interpretations and provide useful inter?pretation and structural explanation for the strength of any interac?tions. In this paper we propose GMM methods designed to uncover underlying (hidden) interactions in social networks and committees. Special attention is paid to the interval censored regression model. Our methods are applied to a study of committee decision making within the Bank of England¡¯s monetary policy committee.Committee Decision Making, Social Networks, Cross Section and Spatial Interaction, Generalised Method of Moments, Censored Regression Model, Expectation-Maximisation Algorithm, Monetary Policy, Interest Rates.
COVID-19 and persistence in the stock market: a study on a leading emerging market
No full textData availability:
The data that support the findings of this study are available from the corresponding author upon reasonable request.In this study, we examine how sectors of the National Stock Exchange from India respond to the uncertainties introduced by the COVID-19 pandemic. By examining the synchronization between the sector-specific and overall market index (NIFTY 50) reaction to COVID-19, we contribute to the inconclusive ongoing academic literature regarding the impact of COVID-19 on the stock market, especially in the context of persistence in an emerging market. To analyze the persistence of sectoral indices, we apply multifractal detrended fluctuation analysis (MFDFA). We use the generalized Hurst exponent and singularity spectrum as indicators for persistence and spectral width as a measure of volatility. Our analysis shows that the sample sectoral indices are persistent before and after the announcement of COVID-19; however, volatility in some sectors reduces post-announcement of COVID-19. The findings will enrich the academic literature on the relationship between sector-specific and overall market indexes. In practice, the paper will guide investors to organize their portfolios, especially during future economic uncertainty
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