A hybrid soft solar cell based on the mycobacterial porin MspA linked to a sensitizer-viologen diad

A prototype of a nano solar cell containing the mycobacterial channel protein MspA has been successfully designed. MspA, an octameric transmembrane channel protein from Mycobacterium smegmatis, is one of the most stable proteins known to date. Eight Ruthenium(II) aminophenanthroline-viologen maleimide Diads (Ru-Diads) have been successfully bound to the MspA mutant MspAA96C via cysteine-maleimide bonds. MspA is known to form double layers in which it acts as nanoscopic surfactant. The nanostructured layer that is formed by (Ru-Diad)(8)MspA at the TiO2 electrode is photochemically active. The resulting "protein nano solar cell" features an incident photon conversion efficiency of 1% at 400 nm. This can be regarded as a proof-of-principle that stable proteins can be successfully integrated into the design of solar cells

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

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

Loss of Genome Fidelity: Beta HPVs and the DNA Damage Response

While the role of genus alpha human papillomaviruses in the tumorigenesis and tumor maintenance of anogenital and oropharyngeal cancers is well-established, the role of genus beta human papilloviruses (β-HPVs) in non-melanoma skin cancers (NMSCs) is less certain. Persistent β-HPV infections cause NMSCs in sun-exposed skin of people with a rare genetic disorder, epidermodysplasia verruciformis. However, β-HPV infections in people without epidermodysplasia verruciformis are typically transient. Further, β-HPV gene expression is not necessary for tumor maintenance in the general population as on average there is fewer than one copy of the β-HPV genome per cell in NMSC tumor biopsies. Cell culture, epidemiological, and mouse model experiments support a role for β-HPV infections in the initiation of NMSCs through a “hit and run” mechanism. The virus is hypothesized to act as a cofactor, augmenting the genome destabilizing effects of UV. Supporting this idea, two β-HPV proteins (β-HPV E6 and E7) disrupt the cellular response to UV exposure and other genome destabilizing events by abrogating DNA repair and deregulating cell cycle progression. The aberrant damage response increases the likelihood of oncogenic mutations capable of driving tumorigenesis independent of a sustained β-HPV infection or continued viral protein expression. This review summarizes what is currently known about the deleterious effects of β-HPV on genome maintenance in the context of the virus's putative role in NMSC initiation

Fermentation optimization of Mycobacterium smegmatis using experimental design

The exceptionally stable mycobacterial protein porin A (MspA) from Mycobacterium smegmatis has potential applications in protein-based solar cells, and as a biotemplate for nano-wires and nano-dots. These applications would be enabled by an efficient and cost effective method to grow the host organism at high cell mass yields, and recover purified MspA. In this work, the cell mass yield was maximized and costs lowered by applying experimental design (varying nitrogen and iron contents according to a Doehlert matrix) based on a minimal fermentation medium that was reported earlier. Glucose use was minimized by adjusting glucose feed based on analyzing residual glucose after fermentation. The costs for extracted and purified MspA were lowered by 67% for the minimum medium and the optimized composition derived here compared to commercial medium (7H9 Middlebrook)

Cervical cancer cell lines are sensitive to sub-erythemal UV exposure

High risk human papillomavirus (HPV) infections are the causative agent in virtually every cervical cancer as well as a host of other anogenital and oropharyngeal malignancies. These viruses must activate DNA repair pathways to facilitate their replication, while avoiding the cell cycle arrest and apoptosis that can accompany DNA damage. HPV oncoproteins facilitate each of these goals, but also reduce genome stability. Our data dissect the cytotoxic and cytoprotective characteristics of HPV oncogenes in cervical cancer cells. These data show that while the transformation of keratinocytes by HPV oncogene leaves these cells more sensitive to UV, the oncogenes also protect against UV-induced apoptosis. Cisplatin and UV resistant cervical cancer cell lines were generated and probed for their sensitivity to genotoxic agents. Cervical cancer cells can acquire resistance to one DNA crosslinking agent (UV or cisplatin) without gaining broad tolerance of crosslinked DNA. Further, cisplatin resistance may or may not result in sensitivity to PARP1 inhibition

Cervical Cancer Development: Implications of HPV16 E6E7-NFX1-123 Regulated Genes

High-risk human papillomavirus (HR HPV) causes nearly all cervical cancers, half of which are due to HPV type 16 (HPV16). HPV16 oncoprotein E6 (16E6) binds to NFX1-123, and dysregulates gene expression, but their clinical implications are unknown. Additionally, HPV16 E7’s role has not been studied in concert with NFX1-123 and 16E6. HR HPVs express both oncogenes, and transformation requires their expression, so we sought to investigate the effect of E7 on gene expression. This study’s goal was to define gene expression profiles across cervical precancer and cancer stages, identify genes correlating with disease progression, assess patient survival, and validate findings in cell models. We analyzed NCBI GEO datasets containing transcriptomic data linked with cervical cancer stage and utilized LASSO analysis to identify cancer-driving genes. Keratinocytes expressing 16E6 and 16E7 (16E6E7) and exogenous NFX1-123 were tested for LASSO-identified gene expression. Ten out of nineteen genes correlated with disease progression, including CEBPD, NOTCH1, and KRT16, and affected survival. 16E6E7 in keratinocytes increased CEBPD, KRT16, and SLPI, and decreased NOTCH1. Exogenous NFX1-123 in 16E6E7 keratinocytes resulted in significantly increased CEBPD and NOTCH1, and reduced SLPI. This work demonstrates the clinical relevance of CEBPD, NOTCH1, KRT16, and SLPI, and shows the regulatory effects of 16E6E7 and NFX1-123

Early detection of non-small cell lung cancer in liquid biopsies by ultrasensitive protease activity analysis

Aim: A significant fraction of mortalities from non-small cell lung cancer could be prevented, if the cancer would be diagnosed earlier. Nanobiosensors for the ultrasensitive detection of active proteases in serum were designed to detect a significant protease activity signature of non-small cell lung cancer (stage I and higher).Methods: We determined the activity of nine protease biomarkers in the sera of non-small cell lung cancer patients and compared them with the protease activities of a control group of healthy human subjects using optical nanobiosensors. They consist of a central Fe/Fe3O4 core/shell nanoparticle with an attached Fluorescence resonance energy transfer-pair [tetrakis-carboxyphenyl porphyrin (TCPP) and cyanine 5.5]. TCPP is attached to the central nanoparticle via a protease-cleavable tether, whereas cyanine 5.5 is tethered permanently to the dopamine-layer surrounding the nanoparticle.Results: Based on the activity pattern of urokinase plasminogen activator, matrix metalloproteinases 1, 2, 3, 7, 9, and 13, and cathepsins B and L as well, non-small cell lung cancer could be detected at stage I by means of a liquid biopsy.Conclusion: This feasibility study, comprising 33 non-small cell lung cancer patients and 20 apparently healthy subjects, clearly demonstrated the feasibility of minimally invasive early diagnosis of non-small cell lung cancer, starting with stage I

Adaptation of Mycobacterium smegmatis to an industrial scale medium and isolation of the mycobacterial porinMspA

The adaptation of the organism to a simple and cost-effective growth medium is mandatory in developing a process for large scale production of the octamericporinMspA, which is isolated from Mycobacterium smegmatis. A fermentation optimization with the minimal nutrients required for growth has been performed. During the fermentation, the iron- and ammonium chloride concentrations in the medium were varied to determine their impact on the observed growth rates and cell mass yields. Common antibiotics to control contamination were eliminated in favor of copper sulfate to reduce costs. MspA has been successfully isolated from the harvested M. smegmatisusing aqueous nOPOE (noctyloligooxyethylene) at 65°C. Because of the extraordinary stability of MspA, it is possible to denature and precipitate virtually all other proteins and contaminants by following this approach. To further purify the product, acetone is used for precipitation. Gel electrophoresis confirmed the presence and purity of MspA. A maximum of 840µg (via Bradford assay) of pure MspA per liter of the optimized simple growth medium has been obtained. This is a 40% increase with respect to the previously reported culture medium for MspA