Design, synthesis and mechanistic anticancer activity of new acetylated 5-aminosalicylate-thiazolinone hybrid derivatives

The development of hybrid compounds has been widely considered as a promising strategy to circumvent the difficulties that emerge in cancer treatment. The well-established strategy of adding acetyl groups to certain drugs has been demonstrated to enhance their therapeutic efficacy. Based on our previous work, an approach of accommodating two chemical entities into a single structure was implemented to synthesize new acetylated hybrids (HH32 and HH33) from 5-aminosalicylic acid and 4-thiazolinone derivatives. These acetylated hybrids showed potential anticancer activities and distinct metabolomic profile with antiproliferative properties. The in-silico molecular docking predicts a strong binding of HH32 and HH33 to cell cycle regulators, and transcriptomic analysis revealed DNA repair and cell cycle as the main targets of HH33 compounds. These findings were validated using in vitro models. In conclusion, the pleiotropic biological effects of HH32 and HH33 compounds on cancer cells demonstrated a new avenue to develop more potent cancer therapies

Global age-sex-specific mortality, life expectancy, and population estimates in 204 countries and territories and 811 subnational locations, 1950–2021, and the impact of the COVID-19 pandemic: a comprehensive demographic analysis for the Global Burden of Disease Study 2021

Background Estimates of demographic metrics are crucial to assess levels and trends of population health outcomes. The profound impact of the COVID-19 pandemic on populations worldwide has underscored the need for timely estimates to understand this unprecedented event within the context of long-term population health trends. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 provides new demographic estimates for 204 countries and territories and 811 additional subnational locations from 1950 to 2021, with a particular emphasis on changes in mortality and life expectancy that occurred during the 2020–21 COVID-19 pandemic period. Methods 22 223 data sources from vital registration, sample registration, surveys, censuses, and other sources were used to estimate mortality, with a subset of these sources used exclusively to estimate excess mortality due to the COVID-19 pandemic. 2026 data sources were used for population estimation. Additional sources were used to estimate migration; the effects of the HIV epidemic; and demographic discontinuities due to conflicts, famines, natural disasters, and pandemics, which are used as inputs for estimating mortality and population. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate under-5 mortality rates, which synthesised 30 763 location-years of vital registration and sample registration data, 1365 surveys and censuses, and 80 other sources. ST-GPR was also used to estimate adult mortality (between ages 15 and 59 years) based on information from 31 642 location-years of vital registration and sample registration data, 355 surveys and censuses, and 24 other sources. Estimates of child and adult mortality rates were then used to generate life tables with a relational model life table system. For countries with large HIV epidemics, life tables were adjusted using independent estimates of HIV-specific mortality generated via an epidemiological analysis of HIV prevalence surveys, antenatal clinic serosurveillance, and other data sources. Excess mortality due to the COVID-19 pandemic in 2020 and 2021 was determined by subtracting observed all-cause mortality (adjusted for late registration and mortality anomalies) from the mortality expected in the absence of the pandemic. Expected mortality was calculated based on historical trends using an ensemble of models. In location-years where all-cause mortality data were unavailable, we estimated excess mortality rates using a regression model with covariates pertaining to the pandemic. Population size was computed using a Bayesian hierarchical cohort component model. Life expectancy was calculated using age-specific mortality rates and standard demographic methods. Uncertainty intervals (UIs) were calculated for every metric using the 25th and 975th ordered values from a 1000-draw posterior distribution. Findings Global all-cause mortality followed two distinct patterns over the study period: age-standardised mortality rates declined between 1950 and 2019 (a 62·8% [95% UI 60·5–65·1] decline), and increased during the COVID-19 pandemic period (2020–21; 5·1% [0·9–9·6] increase). In contrast with the overall reverse in mortality trends during the pandemic period, child mortality continued to decline, with 4·66 million (3·98–5·50) global deaths in children younger than 5 years in 2021 compared with 5·21 million (4·50–6·01) in 2019. An estimated 131 million (126–137) people died globally from all causes in 2020 and 2021 combined, of which 15·9 million (14·7–17·2) were due to the COVID-19 pandemic (measured by excess mortality, which includes deaths directly due to SARS-CoV-2 infection and those indirectly due to other social, economic, or behavioural changes associated with the pandemic). Excess mortality rates exceeded 150 deaths per 100 000 population during at least one year of the pandemic in 80 countries and territories, whereas 20 nations had a negative excess mortality rate in 2020 or 2021, indicating that all-cause mortality in these countries was lower during the pandemic than expected based on historical trends. Between 1950 and 2021, global life expectancy at birth increased by 22·7 years (20·8–24·8), from 49·0 years (46·7–51·3) to 71·7 years (70·9–72·5). Global life expectancy at birth declined by 1·6 years (1·0–2·2) between 2019 and 2021, reversing historical trends. An increase in life expectancy was only observed in 32 (15·7%) of 204 countries and territories between 2019 and 2021. The global population reached 7·89 billion (7·67–8·13) people in 2021, by which time 56 of 204 countries and territories had peaked and subsequently populations have declined. The largest proportion of population growth between 2020 and 2021 was in sub-Saharan Africa (39·5% [28·4–52·7]) and south Asia (26·3% [9·0–44·7]). From 2000 to 2021, the ratio of the population aged 65 years and older to the population aged younger than 15 years increased in 188 (92·2%) of 204 nations. Interpretation Global adult mortality rates markedly increased during the COVID-19 pandemic in 2020 and 2021, reversing past decreasing trends, while child mortality rates continued to decline, albeit more slowly than in earlier years. Although COVID-19 had a substantial impact on many demographic indicators during the first 2 years of the pandemic, overall global health progress over the 72 years evaluated has been profound, with considerable improvements in mortality and life expectancy. Additionally, we observed a deceleration of global population growth since 2017, despite steady or increasing growth in lower-income countries, combined with a continued global shift of population age structures towards older ages. These demographic changes will likely present future challenges to health systems, economies, and societies. The comprehensive demographic estimates reported here will enable researchers, policy makers, health practitioners, and other key stakeholders to better understand and address the profound changes that have occurred in the global health landscape following the first 2 years of the COVID-19 pandemic, and longer-term trends beyond the pandemic

Proteomic and metabolomic signatures of U87 glioblastoma cells treated with cisplatin and/or paclitaxel

AbstractBackground Glioblastoma (GBM) is a primary malignancy of the central nervous system and is classified as a grade IV astrocytoma by the World Health Organization (WHO). Although GBM rarely metastasizes, its prognosis remains poor. Moreover, the standard treatment for GBM, temozolomide (TMZ), is associated with chemoresistance, which is a major factor behind GBM-related deaths. Investigating drugs with repurposing potential in the context of GBM is worthwhile to bypass lengthy bench-to-bedside research. The field of omics has garnered significant interest in scientific research because of its potential to delineate the intricate regulatory network underlying tumor development. In particular, proteomic and metabolomic analyses are powerful approaches for the investigation of metabolic enzymes and intermediate metabolites since they represent the functional end of the cancer phenotype.Methods We chose two of the most widely prescribed anticancer drugs, cisplatin and paclitaxel. To our knowledge, the current literature lacks studies examining their effects on metabolic and proteomic alterations in GBM. We employed the mass spectrometry technological platform ‘UHPLC-Q-TOF-MS/MS’ to examine the changes in the proteome and metabolome profiles of the U87 cell line with defined concentrations of cisplatin and/or paclitaxel via an untargeted approach.Results A total of 1,419 distinct proteins and 90 metabolites were generated, and subsequent analysis was performed. We observed that upon treatment with cisplatin (9.5 μM), U87 cells exhibited apparent efforts to cope with this exogenous stressor, understanding the effect of paclitaxel (5.3 μM) on altering the transport machinery of the cell, and how the combination of cisplatin and/or paclitaxel suggests potential interactions with promising benefits in GBM therapeutics.Conclusion Our research provides a detailed map of alterations in response to cisplatin and paclitaxel treatment, provides crucial insights into the molecular basis of their action, and paves the way for further research to identify molecular targets for this elusive malignancy

Preclinical and Clinical Applications of Metabolomics and Proteomics in Glioblastoma Research

Glioblastoma (GB) is a primary malignancy of the central nervous system that is classified by the WHO as a grade IV astrocytoma. Despite decades of research, several aspects about the biology of GB are still unclear. Its pathogenesis and resistance mechanisms are poorly understood, and methods to optimize patient diagnosis and prognosis remain a bottle neck owing to the heterogeneity of the malignancy. The field of omics has recently gained traction, as it can aid in understanding the dynamic spatiotemporal regulatory network of enzymes and metabolites that allows cancer cells to adjust to their surroundings to promote tumor development. In combination with other omics techniques, proteomic and metabolomic investigations, which are a potent means for examining a variety of metabolic enzymes as well as intermediate metabolites, might offer crucial information in this area. Therefore, this review intends to stress the major contribution these tools have made in GB clinical and preclinical research and highlights the crucial impacts made by the integrative “omics” approach in reducing some of the therapeutic challenges associated with GB research and treatment. Thus, our study can purvey the use of these powerful tools in research by serving as a hub that particularly summarizes studies employing metabolomics and proteomics in the realm of GB diagnosis, treatment, and prognosis

Simultaneous Determination of Pharmaceuticals by Solid-phase Extraction and Liquid Chromatography-Tandem Mass Spectrometry: A Case Study from Sharjah Sewage Treatment Plant

The present work describes the optimization and validation of a highly selective and sensitive analytical method using solid phase extraction and liquid chromatography tandem mass spectrometry (SPE LC-MS/MS) for the determination of some frequently prescribed pharmaceuticals in urban wastewater received and treated by Sharjah sewage treatment plant (STP). The extraction efficiency of different SPE cartridges was tested and the simultaneous extraction of pharmaceuticals was successfully accomplished using hydrophilic-lipophilic-balanced reversed phase Waters® Oasis HLB cartridge (200 mg/ 6 mL) at pH 3. The analytes were separated on an Aquity BEH C18 column (1.7 µm, 2.1 mm × 150 mm) using gradient elution and mass spectrometric analysis were performed in multiple reactions monitoring (MRM) selecting two precursor ions to produce ion transition for each pharmaceutical using positive electrospray ionization (+ESI) mode. The correlation coefficient values in the linear calibration plot for each target compound exceeded 0.99 and the recovery percentages of the investigated pharmaceuticals were more than 84%. Limit of detection (LOD) varied between 0.1⁻1.5 ng/L and limit of quantification (LOQ) was 0.3⁻5 ng/L for all analytes. The precision of the method was calculated as the relative standard deviation (RSD%) of replicate measurements and was found to be in the ranges of 2.2% to 7.7% and 2.2% to 8.6% for inter and intra-day analysis, respectively. All of the obtained validation parameters satisfied the requirements and guidelines of analytical method validation

Metabolic Profiling of Candida auris, a Newly-Emerging Multi-Drug Resistant Candida Species, by GC-MS.

Candidaauris, a newly-emerging Candida species, is a serious global health threat due to its multi-drug resistant pattern, difficulty to diagnose, and the high mortality associated with its invasive and bloodstream infections. Unlike C. albicans, and C.dubliniensis which can form true hyphae, C.auris grows as yeast or pseudohyphae and is capable of developing biofilms. The reasons for the inability of C.auris to form true hyphae are currently unknown. Metabolites secreted by microorganisms, including Candida, are known as important factors in controlling morphogenesis and pathogenesis. Metabolic profiling of C.auris and C. albicans cultures was performed using gas chromatography⁻mass spectrometry (GC⁻MS). Compared to C. albicans, C.auris secreted several hyphae-inhibiting metabolites, including phenylethyl, benzyl and isoamyl alcohols. Furthermore, a biofilm-forming metabolite-tyrosol-was identified. On the other hand, several other biomarkers identified from C.auris but not from C. albicans cultures may be produced by the organism to overcome the host immune system or control fungal adaptations, and hence ease its invasion and infections. The results from this study are considered as the first identification of C.auris metabolic activities as a step forward to understand its virulence mechanisms

Long-COVID, Metabolic and Endocrine Disease

In the aftermath of the corona pandemic, long-COVID or post-acute COVID-19 syndrome still represents a great challenge, and this topic will continue to represent a significant health problem in the coming years. At present, the impact of long-COVID on our health system cannot be fully assessed but according to current studies, up to 40% of people who have been infected with SARS-CoV-2 suffer from clinically relevant symptoms of long-COVID syndrome several weeks to months after the acute phase. The main symptoms are chronic fatigue, dyspnea, and various cognitive symptoms. Initial studies have shown that people with overweight and diabetes mellitus have a higher risk of developing long-COVID associated symptoms. Furthermore, repeated treatment of acute COVID-19 and long-COVID with steroids can contribute to long-term metabolic and endocrine disorders. Therefore, a structured program with rehabilitation and physical activity as well as optimal dietary management is of utmost importance, especially for patients with metabolic diseases and/or long-COVID. Furthermore, the removal of autoantibodies and specific therapeutic apheresis procedures could lead to a significant improvement in the symptoms of long-COVID in individual patients

Metabolic Profiling of Candida auris, a Newly-Emerging Multi-Drug Resistant Candida Species, by GC-MS

Candida auris, a newly-emerging Candida species, is a serious global health threat due to its multi-drug resistant pattern, difficulty to diagnose, and the high mortality associated with its invasive and bloodstream infections. Unlike C. albicans, and C. dubliniensis which can form true hyphae, C. auris grows as yeast or pseudohyphae and is capable of developing biofilms. The reasons for the inability of C. auris to form true hyphae are currently unknown. Metabolites secreted by microorganisms, including Candida, are known as important factors in controlling morphogenesis and pathogenesis. Metabolic profiling of C. auris and C. albicans cultures was performed using gas chromatography⁻mass spectrometry (GC⁻MS). Compared to C. albicans, C. auris secreted several hyphae-inhibiting metabolites, including phenylethyl, benzyl and isoamyl alcohols. Furthermore, a biofilm-forming metabolite—tyrosol—was identified. On the other hand, several other biomarkers identified from C. auris but not from C. albicans cultures may be produced by the organism to overcome the host immune system or control fungal adaptations, and hence ease its invasion and infections. The results from this study are considered as the first identification of C. auris metabolic activities as a step forward to understand its virulence mechanisms