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Abstract Burkholderia pseudomallei (B. pseudomallei) is a Gram-negative pathogen that causes melioidosis, a deadly but neglected tropical disease. B. pseudomallei is intrinsically resistant to a growing list of antibiotics, and alternative antimicrobial agents are being sought with urgency. In this study, we synthesize andrographolide-stabilized silver nanoparticles (andro-AgNPs, spherically shaped with 16 nm average diameter) that show excellent antimicrobial activity against B. pseudomallei, including ceftazidime-resistant strains, being 1–3 orders of magnitude more effective than ceftazidime and 1–2 orders of magnitude more effective than other green-synthesized AgNPs. The andro-AgNPs are meanwhile non-toxic to mammalian cell lines. The mode of action of Andro-AgNPs toward B. pseudomallei is unraveled by killing kinetics, membrane neutralization, silver ions (Ag+) release, reactive oxygen species (ROS) induction, membrane integrity, and cell morphology change studies. The antimicrobial activity and mode of action of andro-AgNPs against B. pseudomallei reported here may pave the way to alternative treatments for melioidosis.

Abstract The ability of MALDI-TOF for the identification of nontuberculous mycobacteria (NTM) has improved recently thanks to updated databases and optimized protein extraction procedures. Few multicentre studies on the reproducibility of MALDI-TOF have been performed so far, none on mycobacteria. The aim of this study was to evaluate the reproducibility of MALDI-TOF for the identification of NTM in 15 laboratories in 9 European countries. A total of 98 NTM clinical isolates were grown on Löwenstein-Jensen. Biomass was collected in tubes with water and ethanol, anonymized and sent out to the 15 participating laboratories. Isolates were identified using MALDI Biotyper (Bruker Daltonics). Up to 1330 MALDI-TOF identifications were collected in the study. A score ≥ 1.6 was obtained for 100% of isolates in 5 laboratories (68.2–98.6% in the other). Species-level identification provided by MALDI-TOF was 100% correct in 8 centres and 100% correct to complex-level in 12 laboratories. In most cases, the misidentifications obtained were associated with closely related species. The variability observed for a few isolates could be due to variations in the protein extraction procedure or to MALDI-TOF system status in each centre. In conclusion, MALDI-TOF showed to be a highly reproducible method and suitable for its implementation for NTM identification.

Abstract The deazaflavin cofactor F420 is a low-potential, two-electron redox cofactor produced by some Archaea and Eubacteria that is involved in methanogenesis and methanotrophy, antibiotic biosynthesis, and xenobiotic metabolism. However, it is not produced by bacterial strains commonly used for industrial biocatalysis or recombinant protein production, such as Escherichia coli, limiting our ability to exploit it as an enzymatic cofactor and produce it in high yield. Here we have utilized a genome-scale metabolic model of E. coli and constraint-based metabolic modelling of cofactor F420 biosynthesis to optimize F420 production in E. coli. This analysis identified phospho-enol pyruvate (PEP) as a limiting precursor for F420 biosynthesis, explaining carbon source-dependent differences in productivity. PEP availability was improved by using gluconeogenic carbon sources and overexpression of PEP synthase. By improving PEP availability, we were able to achieve a ~ 40-fold increase in the space–time yield of F420 compared with the widely used recombinant Mycobacterium smegmatis expression system. This study establishes E. coli as an industrial F420-production system and will allow the recombinant in vivo use of F420-dependent enzymes for biocatalysis and protein engineering applications.

Abstract High-throughput nucleic acid sequencing has greatly accelerated the discovery of viruses in the environment. Mosquitoes, because of their public health importance, are among those organisms whose viromes are being intensively characterized. Despite the deluge of sequence information, our understanding of the major drivers influencing the ecology of mosquito viromes remains limited. Using methods to increase the relative proportion of microbial RNA coupled with RNA-seq we characterize RNA viruses and other symbionts of three mosquito species collected along a rural to urban habitat gradient in Thailand. The full factorial study design allows us to explicitly investigate the relative importance of host species and habitat in structuring viral communities. We found that the pattern of virus presence was defined primarily by host species rather than by geographic locations or habitats. Our result suggests that insect-associated viruses display relatively narrow host ranges but are capable of spreading through a mosquito population at the geographical scale of our study. We also detected various single-celled and multicellular microorganisms such as bacteria, alveolates, fungi, and nematodes. Our study emphasizes the importance of including ecological information in viromic studies in order to gain further insights into viral ecology in systems where host specificity is driving both viral ecology and evolution.

The COVID-19 pandemic and ensuing lockdowns led to sweeping changes in the everyday lives of children and families, including school closures, remote work and learning, and social distancing. To date no study has examined whether these profound changes in young childrens day to day social interactions impacted the development of social cognition skills in early childhood. To address this question, we compared the performance of two cohorts of 3.5- to 5.5-year-old children tested before and after the COVID-19 lockdowns on several measures of false-belief understanding, a critical social cognition skill that undergoes important developments in this age range. Controlling for age and language skills, children tested after the pandemic demonstrated significantly worse false-belief understanding than those tested before the pandemic, and this difference was larger for children from lower socioeconomic status (SES) backgrounds. These results suggest that the pandemic negatively impacted the development of social cognition skills in early childhood, especially for lower SES children.

Artificial light at night (ALAN) changes animal behavior in multiple invertebrates and vertebrates and can result in decreased fitness. However, ALAN effects have not been studied in European honey bees (Apis mellifera), an important pollinator in which foragers show strong circadian rhythmicity. Colonies can be exposed to ALAN in swarm clusters, when bees cluster outside the nest on hot days and evenings, and, in limited cases, when they build nests in the open. We captured and maintained foragers in incubated cages and subjected them to constant light (LL), constant dark (DD), or 12 h light:12 h dark (LD) cycle, and observed them with infrared cameras. After 79 h, there was a significant interaction of treatment and time because LL bees slept less. In detail, the bees maintained a regular sleep pattern for three days but LL bees showed a shift on the fourth day. LL bees had the largest sleep differences from LD controls, with trends of lengthened periods and increased phase misalignment from both LD and DD bees. LL bees also experienced significantly more disturbances from their nestmates and preferred to sleep in the lower portion of the cages, which had significantly lower light intensity. These findings suggest that ALAN can disrupt the sleep of honey bee foragers, which has implications for their behavior and overall colony health.

Prior literature has debated whether syntax is separable from semantics in the brain. Using functional magnetic resonance imaging and multi-voxel pattern analysis, our previous studies investigated brain activity during morpho-syntactic versus semantic processing. These studies only detected semantic specialization in activation patterns and no syntactic specialization in 5- to 6-year-old and 7- to 8-year-old children. To examine if older children who have mastered morpho-syntactic skills would show specialization for syntax, the current study examined 64 9- to 10-year-old children using the same design and analyses. We observed that only the left IFG pars opercularis was sensitive to syntactic but not semantic information, supporting the hypothesis that this region serves as a core region for syntax. In addition, the left STG which has been implicated in the integration of semantics and syntax, as well as the left MTG and IFG pars triangularis which have been implicated in semantics, were sensitive to both semantic and syntactic information with no evidence of specialization. These findings suggest a lexicalized view of syntax, which argues that semantically sensitive regions are also critical regions for syntactic processing during language comprehension.

The effects of the COVID-19 pandemic on comprehensive maternal deaths in Brazil have not been fully explored. Using publicly available data from the Brazilian Mortality Information (SIM) and Information System on Live Births (SINASC) databases, we used two complementary forecasting models to predict estimates of maternal mortality ratios using maternal deaths (MMR) and comprehensive maternal deaths (MMRc) in the years 2020 and 2021 based on data from 2008 to 2019. We calculated national and regional standardized mortality ratio estimates for maternal deaths (SMR) and comprehensive maternal deaths (SMRc) for 2020 and 2021. The observed MMRc in 2021 was more than double the predicted MMRc based on the Holt-Winters and autoregressive integrated moving average models (127.12 versus 60.89 and 59.12 per 100,000 live births, respectively). We found persisting sub-national variation in comprehensive maternal mortality: SMRc ranged from 1.74 (95% confidence interval [CI] 1.64, 1.86) in the Northeast to 2.70 (95% CI 2.45, 2.96) in the South in 2021. The observed national estimates for comprehensive maternal deaths in 2021 were the highest in Brazil in the past three decades. Increased resources for prenatal care, maternal health, and postpartum care may be needed to reverse the national trend in comprehensive maternal deaths.

Continued spread of chronic wasting disease (CWD) through wild cervid herds negatively impacts populations, erodes wildlife conservation, drains resource dollars, and challenges wildlife management agencies. Risk factors for CWD have been investigated at state scales, but a regional model to predict locations of new infections can guide increasingly efficient surveillance efforts. We predicted CWD incidence by county using CWD surveillance data depicting white-tailed deer (Odocoileus virginianus) in 16 eastern and midwestern US states. We predicted the binary outcome of CWD-status using four machine learning models, utilized five-fold cross-validation and grid search to pinpoint the best model, then compared model predictions against the subsequent year of surveillance data. Cross validation revealed that the Light Boosting Gradient model was the most reliable predictor given the regional data. The predictive model could be helpful for surveillance planning. Predictions of false positives emphasize areas that warrant targeted CWD surveillance because of similar conditions with counties known to harbor CWD. However, disagreements in positives and negatives between the CWD Prediction Web App predictions and the on-the-ground surveillance data one year later underscore the need for state wildlife agency professionals to use a layered modeling approach to ensure robust surveillance planning. The CWD Prediction Web App is at https://cwd-predict.streamlit.app/ .

Managed colonies of the European honey bee, Apis mellifera, have faced considerable losses in recent years. A widespread contributing factor is a microsporidian pathogen, Nosema ceranae, which occurs worldwide, is increasingly resistant to antibiotic treatment, and can alter the hosts immune response and nutritional uptake. These obligate gut pathogens share their environment with a natural honey bee microbiome whose composition can affect pathogen resistance. We tested the effect of N. ceranae infection on this microbiome by feeding 5 day-old adult bees that had natural, fully developed microbiomes with live N. ceranae spores (40,000 per bee) or a sham inoculation, sterile 2.0 M sucrose solution. We caged and reared these bees in a controlled lab environment and tracked their mortality over 12 d, after which we dissected them, measured their infection levels (gut spore counts), and analyzed their microbiomes. Bees fed live spores had two-fold higher mortality by 12 d and 36.5-fold more spores per bee than controls. There were also strong colony effects on infection levels, and 9% of spore-inoculated bees had no spore counts at all (defined as fed-spores-but-not-infected). Nosema ceranae infection had significant but subtle effects on the gut microbiomes of experimentally infected bees, bees with different infection levels, and fed-spores-but-not-infected vs. bees with gut spores. Specific bacteria, including Gilliamella ASVs, were positively associated with infection, indicating that multiple strains of core gut microbes either facilitate or resist N. ceranae infection. Future studies on the interactions between bacterial, pathogen, and host genotypes would be illuminating.

Production of hard X-ray via inverse Compton scattering at photon energies below 100 keV range aimed at potential applications in medicine and material research is reported. Experiments have been performed at the Brookhaven National Laboratory, Accelerator Test Facility, employing the counter collision of a 70 MeV, 0.3 nC electron beam with a near infra-red Nd: YAG laser (1064 nm wavelength) pulse containing ~ 100 mJ in a single shot basis. The radiation distribution of the scattered photon beam is assessed to be sufficiently quasi monochromatic to produce clear contrast from the Au K- edge at 80.7 keV.

Using pooled vaginal microbiota data from pregnancy cohorts (N = 683 participants) in the Environmental influences on Child Health Outcomes (ECHO) Program, we analyzed 16S rRNA gene amplicon sequences to identify clinical and demographic host factors that associate with vaginal microbiota structure in pregnancy both within and across diverse cohorts. Using PERMANOVA models, we assessed factors associated with vaginal community structure in pregnancy, examined whether host factors were conserved across populations, and tested the independent and combined effects of host factors on vaginal community state types (CSTs) using multinomial logistic regression models. Demographic and social factors explained a larger amount of variation in the vaginal microbiome in pregnancy than clinical factors. After adjustment, lower education, rather than self-identified race, remained a robust predictor of L. iners dominant (CST III) and diverse (CST IV) (OR = 8.44, 95% CI = 4.06-17.6 and OR = 4.18, 95% CI = 1.88-9.26, respectively). In random forest models, we identified specific taxonomic features of host factors, particularly urogenital pathogens associated with pregnancy complications (Aerococcus christensenii and Gardnerella spp.) among other facultative anaerobes and key markers of community instability (L. iners). Sociodemographic factors were robustly associated with vaginal microbiota structure in pregnancy and should be considered as sources of variation in human microbiome studies.

A key control on the magnitude of coastal eutrophication is the degree to which currents quickly transport nitrogen derived from human sources away from the coast to the open ocean before eutrophication develops. In the Southern California Bight (SCB), an upwelling-dominated eastern boundary current ecosystem, anthropogenic nitrogen inputs increase algal productivity and cause subsurface acidification and oxygen (O 2 ) loss along the coast. However, the extent of anthropogenic influence on eutrophication beyond the coastal band, and the physical transport mechanisms and biogeochemical processes responsible for these effects are still poorly understood. Here, we use a submesoscale-resolving numerical model to document the detailed biogeochemical mass balance of nitrogen, carbon and oxygen, their physical transport, and effects on offshore habitats. Despite management of terrestrial nutrients that has occurred in the region over the last 20 years, coastal eutrophication continues to persist. The input of anthropogenic nutrients promote an increase in productivity, remineralization and respiration offshore, with recurrent O 2 loss and pH decline in a region located 30-90 km from the mainland. During 2013 to 2017, the spatially averaged 5-year loss rate across the Bight was 1.3 mmol m -3 O 2 , with some locations losing on average up to 14.2 mmol m -3 O 2 . The magnitude of loss is greater than model uncertainty assessed from data-model comparisons and from quantification of intrinsic variability. This phenomenon persists for 4 to 6 months of the year over an area of 278,40 km 2 ( ∼ 30% of SCB area). These recurrent features of acidification and oxygen loss are associated with cross-shore transport of nutrients by eddies and plankton biomass and their accumulation and retention within persistent eddies offshore within the SCB.

Prostate cancer pathology plays a crucial role in clinical management but is time-consuming. Artificial intelligence (AI) shows promise in detecting prostate cancer and grading patterns. We tested an AI-based digital twin of a pathologist, vPatho, on 2603 histological images of prostate tissue stained with hematoxylin and eosin. We analyzed various factors influencing tumor grade discordance between the vPatho system and six human pathologists. Our results demonstrated that vPatho achieved comparable performance in prostate cancer detection and tumor volume estimation, as reported in the literature. The concordance levels between vPatho and human pathologists were examined. Notably, moderate to substantial agreement was observed in identifying complementary histological features such as ductal, cribriform, nerve, blood vessel, and lymphocyte infiltration. However, concordance in tumor grading decreased when applied to prostatectomy specimens (κ = 0.44) compared to biopsy cores (κ = 0.70). Adjusting the decision threshold for the secondary Gleason pattern from 5 to 10% improved the concordance level between pathologists and vPatho for tumor grading on prostatectomy specimens (κ from 0.44 to 0.64). Potential causes of grade discordance included the vertical extent of tumors toward the prostate boundary and the proportions of slides with prostate cancer. Gleason pattern 4 was particularly associated with this population. Notably, the grade according to vPatho was not specific to any of the six pathologists involved in routine clinical grading. In conclusion, our study highlights the potential utility of AI in developing a digital twin for a pathologist. This approach can help uncover limitations in AI adoption and the practical application of the current grading system for prostate cancer pathology.