Risk-based Probabilistic Quantification of Power Distribution System Operational Resilience

It is of growing concern to ensure the resilience in electricity infrastructure systems to extreme weather events with the help of appropriate hardening measures and new operational procedures. An effective mitigation strategy requires a quantitative metric for resilience that can not only model the impacts of the unseen catastrophic events for complex electric power distribution networks but also evaluate the potential improvements offered by different planning measures. In this paper, we propose probabilistic metrics to quantify the operational resilience of the electric power distribution systems to high-impact low-probability (HILP) events. Specifically, we define two risk-based measures: Value-at-Risk ($VaR_\alpha$) and Conditional Value-at-Risk ($CVaR_\alpha$) that measure resilience as the maximum loss of energy and conditional expectation of a loss of energy, respectively for the events beyond a prespecified risk threshold, $\alpha$. Next, we present a simulation-based framework to evaluate the proposed resilience metrics for different weather scenarios with the help of modified IEEE 37-bus and IEEE 123-bus system. The simulation approach is also extended to evaluate the impacts of different planning measures on the proposed resilience metrics.Comment: 12 pages, 11 figures, journa

Simulation-Integrated Distributed Optimal Power Flow for Unbalanced Power Distribution Systems

Distributed optimization methods have been extensively applied for the optimization of electric power distribution systems, especially for grid-edge coordination. Existing distributed optimization algorithms applied to power distribution systems require many communication rounds among the distributed agents and may pose convergence challenges in difficult nonlinear settings. The communication network parameters also significantly impact the algorithm's performance. In this paper, we propose a scalable, equivalent network approximation-based, distributed optimization algorithm that employs simulation within optimization using the system's digital twin (DT) to solve the optimal power problems (OPF) for a three-phase unbalanced distribution system. The proposed approach is implemented using a cyber-physical co-simulation platform to validate the robustness of the proposed distributed algorithm under stressed communication. The proposed approach is thoroughly validated using the IEEE 123-bus test system.Comment: 9 page

CHEMICAL INVESTIGATION OF NEEM LEAF GLYCOPROTEIN USED AS IMMUNOPROPHYLACTIC AGENT FOR TUMOR GROWTH RESTRICTION

Objective: Unique immune modulatory function of an aqueous preparation of neem leaf (NLP) in relation to cancer has already been reported. The objective of this present study is to find out the active component present in NLP.Methods: NLP was exposed to a gradient of temperature, pH and enzymes to use for mice immunization before tumor inoculation. Glycoprotein extracted from NLP was purified and analyzed by using Folin's phenol reagent, polyacrylamide gel electrophoresis, scanning electron microscopy and amino acid analysis. Carbohydrate moiety of this protein was analysed by GLC-MS. Immunogenicity was checked by ELISA and immunoblotting.Results: Exposure of NLP to adverse temperature and pH causes significant reduction in tumor growth restricting function of NLP. Treatment of NLP with proteolytic enzymes results abolition of the tumor growth restriction in mice. Biochemical assays indicated the presence of a glycoprotein in NLP, designated as neem leaf glycoprotein (NLGP) which appeared in non-denatured PAGE as a single band, and as three bands in SDS-PAGE having molecular weights 48 Kda, 24 Kda and 15 Kda. NLGP constitutes the carbohydrate moiety of about 33% consisting of arabinose, galactose and glucose. This glycoprotein consisted of seventeen amino acids of which nine were essential. Immunogenecity of this protein was defined by strong reaction of the ant-NLGP sera with NLGP by ELISA and immunoblot.Conclusion: Overall results demonstrated the immense potential of newly identified NLGP, present in NLP as an immunoprophylactic agent for tumor growth restriction.Â

High monocytic MDSC signature predicts multi-drug resistance and cancer relapse in non-Hodgkin lymphoma patients treated with R-CHOP

IntroductionNon-Hodgkin Lymphoma (NHL) is a heterogeneous lymphoproliferative malignancy with B cell origin. Combinatorial treatment of rituximab, cyclophsphamide, hydroxydaunorubicin, oncovin, prednisone (R-CHOP) is the standard treatment regimen for NHL, yielding a complete remission (CR) rate of 40-50%. Unfortunately, considerable patients undergo relapse after CR or initial treatment, resulting in poor clinical implications. Patient’s response to chemotherapy varies widely from static disease to cancer recurrence and later is primarily associated with the development of multi-drug resistance (MDR). The immunosuppressive cells within the tumor microenvironment (TME) have become a crucial target for improving the therapy efficacy. However, a better understanding of their involvement is needed for distinctive response of NHL patients after receiving chemotherapy to design more effective front-line treatment algorithms based on reliable predictive biomarkers.MethodsPeripheral blood from 61 CD20+ NHL patients before and after chemotherapy was utilized for immunophenotyping by flow-cytometry at different phases of treatment. In-vivo and in-vitro doxorubicin (Dox) resistance models were developed with murine Dalton’s lymphoma and Jurkat/Raji cell-lines respectively and impact of responsible immune cells on generation of drug resistance was studied by RT-PCR, flow-cytometry and colorimetric assays. Gene silencing, ChIP and western blot were performed to explore the involved signaling pathways.ResultsWe observed a strong positive correlation between elevated level of CD33+CD11b+CD14+CD15- monocytic MDSCs (M-MDSC) and MDR in NHL relapse cohorts. We executed the role of M-MDSCs in fostering drug resistance phenomenon in doxorubicin-resistant cancer cells in both in-vitro, in-vivo models. Moreover, in-vitro supplementation of MDSCs in murine and human lymphoma culture augments early expression of MDR phenotypes than culture without MDSCs, correlated well with in-vitro drug efflux and tumor progression. We found that MDSC secreted cytokines IL-6, IL-10, IL-1β are the dominant factors elevating MDR expression in cancer cells, neutralization of MDSC secreted IL-6, IL-10, IL-1β reversed the MDR trait. Moreover, we identified MDSC secreted IL-6/IL-10/IL-1β induced STAT1/STAT3/NF-κβ signaling axis as a targeted cascade to promote early drug resistance in cancer cells.ConclusionOur data suggests that screening patients for high titre of M-MDSCs might be considered as a new potential biomarker and treatment modality in overcoming chemo-resistance in NHL patients

Global burden of 369 diseases and injuries in 204 countries and territories, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: In an era of shifting global agendas and expanded emphasis on non-communicable diseases and injuries along with communicable diseases, sound evidence on trends by cause at the national level is essential. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) provides a systematic scientific assessment of published, publicly available, and contributed data on incidence, prevalence, and mortality for a mutually exclusive and collectively exhaustive list of diseases and injuries. Methods: GBD estimates incidence, prevalence, mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) due to 369 diseases and injuries, for two sexes, and for 204 countries and territories. Input data were extracted from censuses, household surveys, civil registration and vital statistics, disease registries, health service use, air pollution monitors, satellite imaging, disease notifications, and other sources. Cause-specific death rates and cause fractions were calculated using the Cause of Death Ensemble model and spatiotemporal Gaussian process regression. Cause-specific deaths were adjusted to match the total all-cause deaths calculated as part of the GBD population, fertility, and mortality estimates. Deaths were multiplied by standard life expectancy at each age to calculate YLLs. A Bayesian meta-regression modelling tool, DisMod-MR 2.1, was used to ensure consistency between incidence, prevalence, remission, excess mortality, and cause-specific mortality for most causes. Prevalence estimates were multiplied by disability weights for mutually exclusive sequelae of diseases and injuries to calculate YLDs. We considered results in the context of the Socio-demographic Index (SDI), a composite indicator of income per capita, years of schooling, and fertility rate in females younger than 25 years. Uncertainty intervals (UIs) were generated for every metric using the 25th and 975th ordered 1000 draw values of the posterior distribution. Findings: Global health has steadily improved over the past 30 years as measured by age-standardised DALY rates. After taking into account population growth and ageing, the absolute number of DALYs has remained stable. Since 2010, the pace of decline in global age-standardised DALY rates has accelerated in age groups younger than 50 years compared with the 1990–2010 time period, with the greatest annualised rate of decline occurring in the 0–9-year age group. Six infectious diseases were among the top ten causes of DALYs in children younger than 10 years in 2019: lower respiratory infections (ranked second), diarrhoeal diseases (third), malaria (fifth), meningitis (sixth), whooping cough (ninth), and sexually transmitted infections (which, in this age group, is fully accounted for by congenital syphilis; ranked tenth). In adolescents aged 10–24 years, three injury causes were among the top causes of DALYs: road injuries (ranked first), self-harm (third), and interpersonal violence (fifth). Five of the causes that were in the top ten for ages 10–24 years were also in the top ten in the 25–49-year age group: road injuries (ranked first), HIV/AIDS (second), low back pain (fourth), headache disorders (fifth), and depressive disorders (sixth). In 2019, ischaemic heart disease and stroke were the top-ranked causes of DALYs in both the 50–74-year and 75-years-and-older age groups. Since 1990, there has been a marked shift towards a greater proportion of burden due to YLDs from non-communicable diseases and injuries. In 2019, there were 11 countries where non-communicable disease and injury YLDs constituted more than half of all disease burden. Decreases in age-standardised DALY rates have accelerated over the past decade in countries at the lower end of the SDI range, while improvements have started to stagnate or even reverse in countries with higher SDI. Interpretation: As disability becomes an increasingly large component of disease burden and a larger component of health expenditure, greater research and developm nt investment is needed to identify new, more effective intervention strategies. With a rapidly ageing global population, the demands on health services to deal with disabling outcomes, which increase with age, will require policy makers to anticipate these changes. The mix of universal and more geographically specific influences on health reinforces the need for regular reporting on population health in detail and by underlying cause to help decision makers to identify success stories of disease control to emulate, as well as opportunities to improve. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950-2019 : a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2·72 (95% uncertainty interval [UI] 2·66–2·79) in 2000 to 2·31 (2·17–2·46) in 2019. Global annual livebirths increased from 134·5 million (131·5–137·8) in 2000 to a peak of 139·6 million (133·0–146·9) in 2016. Global livebirths then declined to 135·3 million (127·2–144·1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2·1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27·1% (95% UI 26·4–27·8) of global livebirths. Global life expectancy at birth increased from 67·2 years (95% UI 66·8–67·6) in 2000 to 73·5 years (72·8–74·3) in 2019. The total number of deaths increased from 50·7 million (49·5–51·9) in 2000 to 56·5 million (53·7–59·2) in 2019. Under-5 deaths declined from 9·6 million (9·1–10·3) in 2000 to 5·0 million (4·3–6·0) in 2019. Global population increased by 25·7%, from 6·2 billion (6·0–6·3) in 2000 to 7·7 billion (7·5–8·0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58·6 years (56·1–60·8) in 2000 to 63·5 years (60·8–66·1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019

Overexpressed PKCδ downregulates the expression of PKCα in B16F10 melanoma: induction of apoptosis by PKCδ via ceramide generation.

In the present study, we observed a marked variation in the expression of PKCα and PKCδ isotypes in B16F10 melanoma tumor cells compared to the normal melanocytes. Interestingly, the tumor instructed expression or genetically manipulated overexpression of PKCα isotype resulted in enhanced G1 to S transition. This in turn promoted cellular proliferation by activating PLD1 expression and subsequent AKT phosphorylation, which eventually resulted in suppressed ceramide generation and apoptosis. On the other hand, B16F10 melanoma tumors preferentially blocked the expression of PKCδ isotype, which otherwise could exhibit antagonistic effects on PKCα-PLD1-AKT signaling and rendered B16F10 cells more sensitive to apoptosis via generating ceramide and subsequently triggering caspase pathway. Hence our data suggested a reciprocal PKC signaling operational in B16F10 melanoma cells, which regulates ceramide generation and provide important clues to target melanoma cancer by manipulating the PKCδ-ceramide axis

Neem leaf glycoprotein optimizes effector and regulatory functions within tumor microenvironment to intervene therapeutically the growth of B16 melanoma in C57BL/6 mice

Therapy with neem leaf glycoprotein (NLGP) inhibits murine B16-melanoma in vivo and improves survivability. Studies on tumor-microenvironment (TME) from NLGP treated mice (NLGP-TME) suggests that anti-tumor effect is directly associated with enhanced CD8+T cell activity, dominance of type 1 cytokines/chemokine network with downregulation of suppressive cellular functions. NLGP-TME educated CD8+T cells showed higher perforin and granzymeB expression with greater in vitro cytotoxicity against B16 melanoma. These CD8+T cells showed proportionally lower FasR expression, denotes prevention from activation induced cell death by NLGP. Accumulated evidences strongly suggest NLGP influenced normalized TME allows CD8+T cells to perform optimally to inhibit melanoma growth

Normalization of tumor microenvironment by neem leaf glycoprotein potentiates effector T cell functions and therapeutically intervenes in the growth of mouse sarcoma.

We have observed restriction of the murine sarcoma growth by therapeutic intervention of neem leaf glycoprotein (NLGP). In order to evaluate the mechanism of tumor growth restriction, here, we have analyzed tumor microenvironment (TME) from sarcoma bearing mice with NLGP therapy (NLGP-TME, in comparison to PBS-TME). Analysis of cytokine milieu within TME revealed IL-10, TGFβ, IL-6 rich type 2 characters was switched to type 1 microenvironment with dominance of IFNγ secretion within NLGP-TME. Proportion of CD8(+) T cells was increased within NLGP-TME and these T cells were protected from TME-induced anergy by NLGP, as indicated by higher expression of pNFAT and inhibit related downstream signaling. Moreover, low expression of FasR(+) cells within CD8(+) T cell population denotes prevention from activation induced cell death. Using CFSE as a probe, better migration of T cells was noted within TME from NLGP treated mice than PBS cohort. CD8(+) T cells isolated from NLGP-TME exhibited greater cytotoxicity to sarcoma cells in vitro and these cells show higher expression of cytotoxicity related molecules, perforin and granzyme B. Adoptive transfer of NLGP-TME exposed T cells, but not PBS-TME exposed cells in mice, is able to significantly inhibit the growth of sarcoma in vivo. Such tumor growth inhibition by NLGP-TME exposed T cells was not observed when mice were depleted for CD8(+) T cells. Accumulated evidences strongly suggest NLGP mediated normalization of TME allows T cells to perform optimally to inhibit the tumor growth