Simultaneous assessment of acidogenesis-mitigation and specific bacterial growth-inhibition by dentifrices

Dentifrices can augment oral hygiene by inactivating bacteria and at sub-lethal concentrations may affect bacterial metabolism, potentially inhibiting acidogenesis, the main cause of caries. Reported herein is the development of a rapid method to simultaneously measure group-specific bactericidal and acidogenesis-mitigation effects of dentifrices on oral bacteria. Saliva was incubated aerobically and anaerobically in Tryptone Soya Broth, Wilkins-Chalgren Broth with mucin, or artificial saliva and was exposed to dentifrices containing triclosan/copolymer (TD); sodium fluoride (FD); stannous fluoride and zinc lactate (SFD1); or stannous fluoride, zinc lactate and stannous chloride (SFD2). Minimum inhibitory concentrations (MIC) were determined turbidometrically whilst group-specific minimum bactericidal concentrations (MBC) were assessed using growth media and conditions selective for total aerobes, total anaerobes, streptococci and Gram-negative anaerobes. Minimum acid neutralization concentration (MNC) was defined as the lowest concentration of dentifrice at which acidification was inhibited. Differences between MIC and MNC were calculated and normalized with respect to MIC to derive the combined inhibitory and neutralizing capacity (CINC), a cumulative measure of acidogenesis-mitigation and growth inhibition. The overall rank order for growth inhibition potency (MIC) under aerobic and anaerobic conditions was: TD> SFD2> SFD1> FD. Acidogenesis-mitigation (MNC) was ordered; TD> FD> SFD2> SFD1. CINC was ordered TD> FD> SFD2> SFD1 aerobically and TD> FD> SFD1> SFD2 anaerobically. With respect to group-specific bactericidal activity, TD generally exhibited the greatest potency, particularly against total aerobes, total anaerobes and streptococci. This approach enables the rapid simultaneous evaluation of acidity mitigation, growth inhibition and specific antimicrobial activity by dentifrices

Global, regional, and national burden of meningitis and its aetiologies, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Although meningitis is largely preventable, it still causes hundreds of thousands of deaths globally each year. WHO set ambitious goals to reduce meningitis cases by 2030, and assessing trends in the global meningitis burden can help track progress and identify gaps in achieving these goals. Using data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we aimed to assess incident cases and deaths due to acute infectious meningitis by aetiology and age from 1990 to 2019, for 204 countries and territories. Methods: We modelled meningitis mortality using vital registration, verbal autopsy, sample-based vital registration, and mortality surveillance data. Meningitis morbidity was modelled with a Bayesian compartmental model, using data from the published literature identified by a systematic review, as well as surveillance data, inpatient hospital admissions, health insurance claims, and cause-specific meningitis mortality estimates. For aetiology estimation, data from multiple causes of death, vital registration, hospital discharge, microbial laboratory, and literature studies were analysed by use of a network analysis model to estimate the proportion of meningitis deaths and cases attributable to the following aetiologies: Neisseria meningitidis, Streptococcus pneumoniae, Haemophilus influenzae, group B Streptococcus, Escherichia coli, Klebsiella pneumoniae, Listeria monocytogenes, Staphylococcus aureus, viruses, and a residual other pathogen category. Findings: In 2019, there were an estimated 236 000 deaths (95% uncertainty interval [UI] 204 000–277 000) and 2·51 million (2·11–2·99) incident cases due to meningitis globally. The burden was greatest in children younger than 5 years, with 112 000 deaths (87 400–145 000) and 1·28 million incident cases (0·947–1·71) in 2019. Age-standardised mortality rates decreased from 7·5 (6·6–8·4) per 100 000 population in 1990 to 3·3 (2·8–3·9) per 100 000 population in 2019. The highest proportion of total all-age meningitis deaths in 2019 was attributable to S pneumoniae (18·1% [17·1–19·2]), followed by N meningitidis (13·6% [12·7–14·4]) and K pneumoniae (12·2% [10·2–14·3]). Between 1990 and 2019, H influenzae showed the largest reduction in the number of deaths among children younger than 5 years (76·5% [69·5–81·8]), followed by N meningitidis (72·3% [64·4–78·5]) and viruses (58·2% [47·1–67·3]). Interpretation: Substantial progress has been made in reducing meningitis mortality over the past three decades. However, more meningitis-related deaths might be prevented by quickly scaling up immunisation and expanding access to health services. Further reduction in the global meningitis burden should be possible through low-cost multivalent vaccines, increased access to accurate and rapid diagnostic assays, enhanced surveillance, and early treatment. Funding: Bill & Melinda Gates Foundation

The Bifidobacterium dentium Bd1 Genome Sequence Reflects Its Genetic Adaptation to the Human Oral Cavity

Bifidobacteria, one of the relatively dominant components of the human intestinal microbiota, are considered one of the key groups of beneficial intestinal bacteria (probiotic bacteria). However, in addition to health-promoting taxa, the genus Bifidobacterium also includes Bifidobacterium dentium, an opportunistic cariogenic pathogen. The genetic basis for the ability of B. dentium to survive in the oral cavity and contribute to caries development is not understood. The genome of B. dentium Bd1, a strain isolated from dental caries, was sequenced to completion to uncover a single circular 2,636,368 base pair chromosome with 2,143 predicted open reading frames. Annotation of the genome sequence revealed multiple ways in which B. dentium has adapted to the oral environment through specialized nutrient acquisition, defences against antimicrobials, and gene products that increase fitness and competitiveness within the oral niche. B. dentium Bd1 was shown to metabolize a wide variety of carbohydrates, consistent with genome-based predictions, while colonization and persistence factors implicated in tissue adhesion, acid tolerance, and the metabolism of human saliva-derived compounds were also identified. Global transcriptome analysis demonstrated that many of the genes encoding these predicted traits are highly expressed under relevant physiological conditions. This is the first report to identify, through various genomic approaches, specific genetic adaptations of a Bifidobacterium taxon, Bifidobacterium dentium Bd1, to a lifestyle as a cariogenic microorganism in the oral cavity. In silico analysis and comparative genomic hybridization experiments clearly reveal a high level of genome conservation among various B. dentium strains. The data indicate that the genome of this opportunistic cariogen has evolved through a very limited number of horizontal gene acquisition events, highlighting the narrow boundaries that separate commensals from opportunistic pathogens

From Cleanroom to Desktop: Emerging Micro-Nanofabrication Technology for Biomedical Applications

This review is motivated by the growing demand for low-cost, easy-to-use, compact-size yet powerful micro-nanofabrication technology to address emerging challenges of fundamental biology and translational medicine in regular laboratory settings. Recent advancements in the field benefit considerably from rapidly expanding material selections, ranging from inorganics to organics and from nanoparticles to self-assembled molecules. Meanwhile a great number of novel methodologies, employing off-the-shelf consumer electronics, intriguing interfacial phenomena, bottom-up self-assembly principles, etc., have been implemented to transit micro-nanofabrication from a cleanroom environment to a desktop setup. Furthermore, the latest application of micro-nanofabrication to emerging biomedical research will be presented in detail, which includes point-of-care diagnostics, on-chip cell culture as well as bio-manipulation. While significant progresses have been made in the rapidly growing field, both apparent and unrevealed roadblocks will need to be addressed in the future. We conclude this review by offering our perspectives on the current technical challenges and future research opportunities

Twelve-month observational study of children with cancer in 41 countries during the COVID-19 pandemic

Introduction Childhood cancer is a leading cause of death. It is unclear whether the COVID-19 pandemic has impacted childhood cancer mortality. In this study, we aimed to establish all-cause mortality rates for childhood cancers during the COVID-19 pandemic and determine the factors associated with mortality. Methods Prospective cohort study in 109 institutions in 41 countries. Inclusion criteria: children <18 years who were newly diagnosed with or undergoing active treatment for acute lymphoblastic leukaemia, non-Hodgkin's lymphoma, Hodgkin lymphoma, retinoblastoma, Wilms tumour, glioma, osteosarcoma, Ewing sarcoma, rhabdomyosarcoma, medulloblastoma and neuroblastoma. Of 2327 cases, 2118 patients were included in the study. The primary outcome measure was all-cause mortality at 30 days, 90 days and 12 months. Results All-cause mortality was 3.4% (n=71/2084) at 30-day follow-up, 5.7% (n=113/1969) at 90-day follow-up and 13.0% (n=206/1581) at 12-month follow-up. The median time from diagnosis to multidisciplinary team (MDT) plan was longest in low-income countries (7 days, IQR 3-11). Multivariable analysis revealed several factors associated with 12-month mortality, including low-income (OR 6.99 (95% CI 2.49 to 19.68); p<0.001), lower middle income (OR 3.32 (95% CI 1.96 to 5.61); p<0.001) and upper middle income (OR 3.49 (95% CI 2.02 to 6.03); p<0.001) country status and chemotherapy (OR 0.55 (95% CI 0.36 to 0.86); p=0.008) and immunotherapy (OR 0.27 (95% CI 0.08 to 0.91); p=0.035) within 30 days from MDT plan. Multivariable analysis revealed laboratory-confirmed SARS-CoV-2 infection (OR 5.33 (95% CI 1.19 to 23.84); p=0.029) was associated with 30-day mortality. Conclusions Children with cancer are more likely to die within 30 days if infected with SARS-CoV-2. However, timely treatment reduced odds of death. This report provides crucial information to balance the benefits of providing anticancer therapy against the risks of SARS-CoV-2 infection in children with cancer

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe