Bone seeking matrix metalloproteinase-2 inhibitors prevent bone metastatic breast cancer growth

Bone metastasis is common during breast cancer progression. Matrix metalloproteinase-2 (MMP-2) is significantly associated with aggressive breast cancer and poorer overall survival. In bone, tumor or host derived MMP-2 contributes to breast cancer growth and does so by processing substrates including type I collagen and transforming growth factorβ (TGFβ) latency proteins. These data provide strong rationale for the application of MMP-2 inhibitors to treat the disease. However, in vivo, MMP-2 is systemically expressed. Therefore, to overcome potential toxicities noted with previous broad-spectrum MMP inhibitors (MMPIs), we used highly selective bisphosphonic based MMP-2 inhibitors (BMMPIs) that allowed for specific bone targeting. In vitro, BMMPIs impacted the viability of breast cancer cell lines and osteoclast precursors but not osteoblasts. In vivo, we demonstrated using two bone metastatic models (PyMT-R221A and 4T1) that BMMPI treatment significantly reduced tumor growth and tumor associated bone destruction. Additionally, BMMPIs are superior in promoting tumor apoptosis compared to the standard of care bisphosphonate, zoledronate. We demonstrated MMP-2 selective inhibition in the bone microenvironment using specific and broad spectrum MMP probes. Further, compared to zoledronate, BMMPI treated mice had significantly lower levels of TGFβ signaling and MMP generated type I collagen carboxy-terminal (ICTP) fragments. Taken together, our data show the feasibility of selective inhibition of MMPs in the bone metastatic breast cancer microenvironment. We posit that BMMPIs could be easily translated to the clinical setting for the treatment of bone metastases given the well-tolerated nature of bisphosphonates

Foot-and-Mouth Disease Virus Serotype A in Egypt

We describe the characterization of a foot-and-mouth disease (FMD) serotype A virus responsible for recent outbreaks of disease in Egypt. Phylogenetic analysis of VP1 nucleotide sequences demonstrated a close relationship to recent FMD virus isolates from East Africa, rather than to viruses currently circulating in the Middle East

A first in man phase I trial of the oral immunomodulator, indoximod, combined with docetaxel in patients with metastatic solid tumors

BackgroundIndoleamine 2,3-dioxygenase (IDO) is an enzyme that tumors use to create a state of immunosuppression. Indoximod is an IDO pathway inhibitor. Preclinical studies demonstrated that indoximod combined with chemotherapy was synergistic in a mouse model of breast cancer. A phase I 3+3 trial was designed to study the combination of docetaxel and indoximod.MethodsDocetaxel was administered at 60 mg/m2 intravenously every 3 weeks dose levels 1-4 and 75 mg/m2 for dose level 5. Indoximod was given at 300, 600, 1000, 2000, and 1200 mg PO twice daily continuously for levels 1-5, respectively. Serum drug levels were measured.ResultsTwenty-seven patients were treated, with 22 evaluable for response. DLTs included grade 3 dehydration (level 1), hypotension(level 4), mucositis (level 4) and grade 5 enterocolitis (level 2). Dose level 5 is the recommended phase II dose. The most frequent adverse events were fatigue (58.6%), anemia (51.7%), hyperglycemia (48.3%), infection (44.8%), and nausea (41.4%). There were 4 partial responses (2 breast, 1 NSCLC, 1 thymic tumor). No drug-drug interactions were noted.ConclusionsDocetaxel plus indoximod was well tolerated with no increase in expected toxicities or pharmacokinetic interactions. It was active in a pretreated population of patients with metastatic solid tumors

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

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

Diversity of insect pollinators with reference to their impact on yield production of canola (Brassica napus L.) in Ismailia, Egypt

A study of insect pollinators and their impact on canola yield was conducted during the 2013/2014 and 2014/2015 growing seasons. The study was carried out at an experimental farm, Faculty of Agriculture, Suez Canal University, Ismailia. The results revealed that 21 species of insect pollinators belonging to 14 families under four orders visited canola flowers. The abundance of Hymenoptera insects reached the maximum of 67.90%, followed by Diptera 14.97%, Coleoptera 13.61%, then Lepidoptera 2.26% as average of both seasons. In open pollination, Colletes lacunatus had the maximum percent abundance in the two seasons (30.45 and 29.34%, respectively) followed by Apis mellifera (12.34 and 17.73%, respectively), compared to other bees and different pollinators. Peaks of foraging activity of both C. lacunatus and A. mellifera were mainly observed from 1:00 to 3:00 pm and they corresponded to the number of flowering plants. Open pollination increased the number of pods per plant, seeds per pod, weight of 1000 seeds, yield per plant, yield per feddan (1 fed = 0.42 ha) and seed germination, compared to non-open pollination