Strategies to modulate charge variants of a Biosmilar monoclonal antibody through cell culture conditions

Monoclonal antibodies (mAb) are the most successful and rapidly growing class of biopharmaceuticals used in treating several diseases. Biosimilar mAb, an approved version of an original biological medicinal product (reference product) with demonstrated similarity to the reference in terms of critical quality attributes, safety and efficacy, is an increasingly accepted solution to provide greater access at affordable cost to the patients across the world. But, given the complex nature of mAbs, developing a biosimilar using a new cell line and a process is challenging, especially with regards to matching the glycosylation and charge profiles to the appropriate level. It is reported that culture environment during the production of monoclonal antibody affects its various quality attributes including charge variant profiles1. The charge variants are usually formed due to chemical modification of amino acids by deamidation, oxidation, glycation and methylglyoxal adducts2, and may lead to increase in acidic charge variants. These unintended changes in the protein are mainly due to it being exposed during the long duration of the cell culture to an environment, like elevated temperature, nutrients from media and feed, metabolites from live and lysed cells, culture pH, which favours certain chemical modifications. Understanding and controlling cell culture process parameters are vital in developing a protein biologic to ensure process consistency and product quality. In the present study, we discuss a case study of development of a cell culture process to produce a proposed biosimilar mAb using a CHO cell line, and ways to modulate its charge variants in the cell culture. The initial screening experiments were performed in an ambr® 15 cell culture micro bioreactor system, from which an optimal 12-day process was chosen and subsequently tested in 3L and 10L bioreactors. Significant time-dependent increase in acidic charge variants was observed from day 10 to 12 at both bioreactor scales, while all other quality parameters remained largely unchanged during the last days of the culture. Further various strategies such as use of different basal media, feed, and additives (amino acids/metal ions and insulin), and changes in culture temperature and pH, were applied during the cell culture process to control the charge variants, in particular the acidic charge variants. The impact of various additives, cell culture pH, temperature on the charge profiles, as well as on productivity and glycosylation, during the development of this biosimilar mAb using a CHO cell line is discussed in detail. References: Liu, H., Nowak, C., Shao, M., Ponniah, G. and Neill, A. (2016), Impact of cell culture on recombinant monoclonal antibody product heterogeneity. Biotechnol Progress, 32: 1103–1112. Chumsae, C., Gifford, K., Lian, W., Liu, H., Radziejewski, C. H., & Zhou, Z. S. (2013). Arginine modifications by methylglyoxal: discovery in a recombinant monoclonal antibody and contribution to acidic species. Analytical chemistry, 85(23), 11401-11409

Remotely Activated Protein-Producing Nanoparticles

The development of responsive nanomaterials, nanoscale systems that actively respond to stimuli, is one general goal of nanotechnology. Here we develop nanoparticles that can be controllably triggered to synthesize proteins. The nanoparticles consist of lipid vesicles filled with the cellular machinery responsible for transcription and translation, including amino acids, ribosomes, and DNA caged with a photolabile protecting group. These particles served as nanofactories capable of producing proteins including green fluorescent protein (GFP) and enzymatically active luciferase. In vitro and in vivo, protein synthesis was spatially and temporally controllable, and could be initiated by irradiating micrometer-scale regions on the time scale of milliseconds. The ability to control protein synthesis inside nanomaterials may enable new strategies to facilitate the study of orthogonal proteins in a confined environment and for remotely activated drug delivery.National Cancer Institute (U.S.) (MIT-Harvard Center for Cancer Nanotechnology Excellence Grant U54 CA151884)Marie D. and Pierre Casimir-Lambert FundNational Cancer Institute (U.S.) (Cancer Center Support (Core) Grant P30-CA14051)National Institutes of Health (U.S.) (Grant EB000244

Burden of disease scenarios for 204 countries and territories, 2022–2050: a forecasting analysis for the Global Burden of Disease Study 2021

Background: Future trends in disease burden and drivers of health are of great interest to policy makers and the public at large. This information can be used for policy and long-term health investment, planning, and prioritisation. We have expanded and improved upon previous forecasts produced as part of the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) and provide a reference forecast (the most likely future), and alternative scenarios assessing disease burden trajectories if selected sets of risk factors were eliminated from current levels by 2050. Methods: Using forecasts of major drivers of health such as the Socio-demographic Index (SDI; a composite measure of lag-distributed income per capita, mean years of education, and total fertility under 25 years of age) and the full set of risk factor exposures captured by GBD, we provide cause-specific forecasts of mortality, years of life lost (YLLs), years lived with disability (YLDs), and disability-adjusted life-years (DALYs) by age and sex from 2022 to 2050 for 204 countries and territories, 21 GBD regions, seven super-regions, and the world. All analyses were done at the cause-specific level so that only risk factors deemed causal by the GBD comparative risk assessment influenced future trajectories of mortality for each disease. Cause-specific mortality was modelled using mixed-effects models with SDI and time as the main covariates, and the combined impact of causal risk factors as an offset in the model. At the all-cause mortality level, we captured unexplained variation by modelling residuals with an autoregressive integrated moving average model with drift attenuation. These all-cause forecasts constrained the cause-specific forecasts at successively deeper levels of the GBD cause hierarchy using cascading mortality models, thus ensuring a robust estimate of cause-specific mortality. For non-fatal measures (eg, low back pain), incidence and prevalence were forecasted from mixed-effects models with SDI as the main covariate, and YLDs were computed from the resulting prevalence forecasts and average disability weights from GBD. Alternative future scenarios were constructed by replacing appropriate reference trajectories for risk factors with hypothetical trajectories of gradual elimination of risk factor exposure from current levels to 2050. The scenarios were constructed from various sets of risk factors: environmental risks (Safer Environment scenario), risks associated with communicable, maternal, neonatal, and nutritional diseases (CMNNs; Improved Childhood Nutrition and Vaccination scenario), risks associated with major non-communicable diseases (NCDs; Improved Behavioural and Metabolic Risks scenario), and the combined effects of these three scenarios. Using the Shared Socioeconomic Pathways climate scenarios SSP2-4.5 as reference and SSP1-1.9 as an optimistic alternative in the Safer Environment scenario, we accounted for climate change impact on health by using the most recent Intergovernmental Panel on Climate Change temperature forecasts and published trajectories of ambient air pollution for the same two scenarios. Life expectancy and healthy life expectancy were computed using standard methods. The forecasting framework includes computing the age-sex-specific future population for each location and separately for each scenario. 95% uncertainty intervals (UIs) for each individual future estimate were derived from the 2·5th and 97·5th percentiles of distributions generated from propagating 500 draws through the multistage computational pipeline. Findings: In the reference scenario forecast, global and super-regional life expectancy increased from 2022 to 2050, but improvement was at a slower pace than in the three decades preceding the COVID-19 pandemic (beginning in 2020). Gains in future life expectancy were forecasted to be greatest in super-regions with comparatively low life expectancies (such as sub-Saharan Africa) compared with super-regions with higher life expectancies (such as the high-income super-region), leading to a trend towards convergence in life expectancy across locations between now and 2050. At the super-region level, forecasted healthy life expectancy patterns were similar to those of life expectancies. Forecasts for the reference scenario found that health will improve in the coming decades, with all-cause age-standardised DALY rates decreasing in every GBD super-region. The total DALY burden measured in counts, however, will increase in every super-region, largely a function of population ageing and growth. We also forecasted that both DALY counts and age-standardised DALY rates will continue to shift from CMNNs to NCDs, with the most pronounced shifts occurring in sub-Saharan Africa (60·1% [95% UI 56·8–63·1] of DALYs were from CMNNs in 2022 compared with 35·8% [31·0–45·0] in 2050) and south Asia (31·7% [29·2–34·1] to 15·5% [13·7–17·5]). This shift is reflected in the leading global causes of DALYs, with the top four causes in 2050 being ischaemic heart disease, stroke, diabetes, and chronic obstructive pulmonary disease, compared with 2022, with ischaemic heart disease, neonatal disorders, stroke, and lower respiratory infections at the top. The global proportion of DALYs due to YLDs likewise increased from 33·8% (27·4–40·3) to 41·1% (33·9–48·1) from 2022 to 2050, demonstrating an important shift in overall disease burden towards morbidity and away from premature death. The largest shift of this kind was forecasted for sub-Saharan Africa, from 20·1% (15·6–25·3) of DALYs due to YLDs in 2022 to 35·6% (26·5–43·0) in 2050. In the assessment of alternative future scenarios, the combined effects of the scenarios (Safer Environment, Improved Childhood Nutrition and Vaccination, and Improved Behavioural and Metabolic Risks scenarios) demonstrated an important decrease in the global burden of DALYs in 2050 of 15·4% (13·5–17·5) compared with the reference scenario, with decreases across super-regions ranging from 10·4% (9·7–11·3) in the high-income super-region to 23·9% (20·7–27·3) in north Africa and the Middle East. The Safer Environment scenario had its largest decrease in sub-Saharan Africa (5·2% [3·5–6·8]), the Improved Behavioural and Metabolic Risks scenario in north Africa and the Middle East (23·2% [20·2–26·5]), and the Improved Nutrition and Vaccination scenario in sub-Saharan Africa (2·0% [–0·6 to 3·6]). Interpretation: Globally, life expectancy and age-standardised disease burden were forecasted to improve between 2022 and 2050, with the majority of the burden continuing to shift from CMNNs to NCDs. That said, continued progress on reducing the CMNN disease burden will be dependent on maintaining investment in and policy emphasis on CMNN disease prevention and treatment. Mostly due to growth and ageing of populations, the number of deaths and DALYs due to all causes combined will generally increase. By constructing alternative future scenarios wherein certain risk exposures are eliminated by 2050, we have shown that opportunities exist to substantially improve health outcomes in the future through concerted efforts to prevent exposure to well established risk factors and to expand access to key health interventions

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Aging and Immune System: An Overview

 The world is seeing a quick segment move towards a more established populace, a pattern with significant clinical, social, monetary and political ramifications. Maturing is a multifaceted procedure, including various sub-atomic and cell components with regards to various organ frameworks. A urgent part of maturing is a lot of useful and auxiliary adjustments in the invulnerable framework that can show as a diminished capacity to battle contamination, lessened reaction to inoculation, increased incidence of cancer, higher prevalence of autoimmunity and constitutive low- grade inflammation, among others. In addition to cell-intrinsic changes in both innate and adaptive immune cells, alteration in the stromal microenvironment in primary and secondary lymphoid organs plays an important role in age-associated immune dysfunction. This review will provide a broad overview of these phenomena and point out some of their clinical and therapeutic implications. This review study setting, discussing the gradual aging immune system. Data for this study is collected from different search engines like PubMed, Google Scholar, MeSH, Semantic scholar, Cochrane, NCBI, Medline, core science. A total of 53 articles were selected. The aging of the immune system is associated with dramatic changes in the distribution and competence of immune cells. Anti-Aging therapy should aim at prolonging T cells’ survival while weakening inflammation prone to innate immunity

Knowledge, attitude, and awareness of childhood cancer among undergraduate medical students in South India

Background :In India roughly 60000 childhood cancer cases are diagnosed annually with only nearly 100 pediatric oncologists. So it′s pertinent that the physicians and pediatricians are adequately equipped to recognize and refer them appropriately. Hence this study was conducted to assess the knowledge, attitude and awareness of childhood cancer among undergraduate medical students in South India. Materials and Methods: The study was conducted among 240 undergraduate students from all over South India in a undergraduate pediatric clinical training. A 24 point questionnaire was given to assess their understanding of pediatric malignancies and their interest towards pediatric oncology. Statistical analysis was done with SPSS 18.V software. Results: 50% were interested in pursuing pediatrics as their career but 80% of them were not interested in pursuing pediatric oncology as their career. 55% of the students have not encountered any pediatric oncology patients in the ward. 40% did not have any lecture classes on pediatric oncology. 65.5% felt that their knowledge of childhood cancer did not make them competent to suspect and refer appropriately during their practice. 84% supported that there is a need to improve pediatric oncology teaching in their medical curriculum. Conclusions : The study unambiguously states that the future physicians lack confidence in identifying and managing childhood malignancies and pediatric oncology is far down in their career options. There is a need to reform the undergraduate medical students by increasing their exposure to pediatric oncology to improve their competence levels and interest in pursuing it as a career also

Cathepsin B Degradable Star-Shaped Peptidic Macromolecules for Delivery of 2‑Methoxyestradiol

2-Methoxyestradiol (2ME), a natural metabolite of estradiol, has antiproliferative and antiangiogenic activity. However, its clinical success is limited due to poor water solubility and poor pharmacokinetic parameters suggesting the need for a delivery vehicle. In this study we evaluated cathepsin B degradable star-shaped peptidic macromolecules (SPMs) that can potentially be used to create higher generation and high molecular weight peptidic polymer as delivery vehicle of 2ME. Two peptidic macromolecules having positively charged amine (ASPM) or negatively charged carboxyl surface groups (CSPM) were synthesized and evaluated for their degradation in the presence of cathepsin B and stability in the presence of neutral or acidic buffer and serum. Both ASPM and CSPM degraded rapidly in the presence of cathepsin B. Both were stable in neutral and acidic buffer whereas only CSPM exhibited substantial stability in the presence of serum. Both macromolecules were nontoxic toward breast cancer cells whereas 2ME-containing macromolecules exhibited antiproliferative activity in the micromolar range. Overall, results from the current study indicate that tetrapeptide GFLG can be used to create star-shaped macromolecules that are degraded in the presence of cathepsin B and have the potential to be developed as delivery vehicles of 2ME

Systematic review and meta-analysis of prediction models used in cervical cancer

BACKGROUND: Cervical cancer is one of the most common cancers in women with an incidence of around 6.5 % of all the cancer in women worldwide. Early detection and adequate treatment according to staging improve the patient's life expectancy. Outcome prediction models might aid treatment decisions, but a systematic review on prediction models for cervical cancer patients is not available. DESIGN: We performed a systematic review for prediction models in cervical cancer following PRISMA guidelines. Key features that were used for model training and validation, the endpoints were extracted from the article and data were analyzed. Selected articles were grouped based on prediction endpoints i.e. Group1: Overall survival, Group2: progression-free survival; Group3: recurrence or distant metastasis; Group4: treatment response; Group5: toxicity or quality of life. We developed a scoring system to evaluate the manuscript. As per our criteria, studies were divided into four groups based on scores obtained in our scoring system, the Most significant study (Score > 60 %); Significant study (60 % > Score > 50 %); Moderately Significant study (50 % > Score > 40 %); least significant study (score 0.7) in endpoint prediction. CONCLUSIONS: Prediction models of cervical cancer toxicity, local or distant recurrence and survival prediction show promising results with reasonable prediction accuracy [c-index/AUC/R 2 > 0.7]. These models should also be validated on external data and evaluated in prospective clinical studies

Derivation of iPSC lines from two patients with familial Alzheimer's disease from India

The current prevalence of diagnosable dementia in India is 1% of people over 60 years (~3.7 million people), but is estimated to increase significantly, as ~15% world's aged population (>65 years) would be resident here by 2020 (Shah et al., 2016). While several mutations that pose a familial risk have been identified, the ethnic background may influence disease susceptibility, clinical presentation and treatment response. In this study, we report a detailed characterization of two representative HiPSC lines from a well-characterized dementia cohort from India. Availability of these lines, and associated molecular and clinical information, would be useful in the detailed exploration of the genomic contribution(s) to AD