Application of microbial resources in biorefineries: Current trend and future prospects.

The recent growing interest in sustainable and alternative sources of energy and bio-based products has driven the paradigm shift to an integrated model termed "biorefinery." Biorefinery framework implements the concepts of novel eco-technologies and eco-efficient processes for the sustainable production of energy and value-added biomolecules. The utilization of microbial resources for the production of various value-added products has been documented in the literatures. However, the appointment of these microbial resources in integrated resource management requires a better understanding of their status. The main of aim of this review is to provide an overview on the defined positioning and overall contribution of the microbial resources, i.e., algae, fungi and bacteria, for various bioprocesses and generation of multiple products from a single biorefinery. By utilizing waste material as a feedstock, biofuels can be generated by microalgae while sequestering environmental carbon and producing value added compounds as by-products. In parallel, fungal biorefineries are prolific producers of lignocellulose degrading enzymes along with pharmaceutically important novel products. Conversely, bacterial biorefineries emerge as a preferred platform for the transformation of standard cells into proficient bio-factories, developing chassis and turbo cells for enhanced target compound production. This comprehensive review is poised to offer an intricate exploration of the current trends, obstacles, and prospective pathways of microbial biorefineries, for the development of future biorefineries.

Predicting the Climate Impact of Healthcare Facilities Using Gradient Boosting Machines.

Health care accounts for 9-10% of greenhouse gas (GHG) emissions in the United States. Strategies for monitoring these emissions at the hospital level are needed to decarbonize the sector. However, data collection to estimate emissions is challenging, especially for smaller hospitals. We explored the potential of gradient boosting machines (GBM) to impute missing data on resource consumption in the 2020 survey of a consortium of 283 hospitals participating in Practice Greenhealth. GBM imputed missing values for selected variables in order to predict electricity use and beef consumption (R2=0.82) and anesthetic gas desflurane use (R2=0.51), using administrative data readily available for most hospitals. After imputing missing consumption data, estimated GHG emissions associated with these three examples totaled over 3 million metric tons of CO2 equivalent emissions (MTCO2e). Specifically, electricity consumption had the largest total carbon footprint (2.4 MTCO2e), followed by beef (0.6 million MTCO2e) and desflurane consumption (0.03 million MTCO2e) across the 283 hospitals. The approach should be applicable to other sources of hospital GHGs in order to estimate total emissions of individual hospitals and to refine survey questions to help develop better intervention strategies.

Detection of driver mutations and genomic signatures in endometrial cancers using artificial intelligence algorithms.

Analyzed endometrial cancer (EC) genomes have allowed for the identification of molecular signatures, which enable the classification, and sometimes prognostication, of these cancers. Artificial intelligence algorithms have facilitated the partitioning of mutations into driver and passenger based on a variety of parameters, including gene function and frequency of mutation. Here, we undertook an evaluation of EC cancer genomes deposited on the Catalogue of Somatic Mutations in Cancers (COSMIC), with the goal to classify all mutations as either driver or passenger. Our analysis showed that approximately 2.5% of all mutations are driver and cause cellular transformation and immortalization. We also characterized nucleotide level mutation signatures, gross chromosomal re-arrangements, and gene expression profiles. We observed that endometrial cancers show distinct nucleotide substitution and chromosomal re-arrangement signatures compared to other cancers. We also identified high expression levels of the CLDN18 claudin gene, which is involved in growth, survival, metastasis and proliferation. We then used in silico protein structure analysis to examine the effect of certain previously uncharacterized driver mutations on protein structure. We found that certain mutations in CTNNB1 and TP53 increase protein stability, which may contribute to cellular transformation. While our analysis retrieved previously classified mutations and genomic alterations, which is to be expected, this study also identified new signatures. Additionally, we show that artificial intelligence algorithms can be effectively leveraged to accurately predict key drivers of cancer. This analysis will expand our understanding of ECs and improve the molecular toolbox for classification, diagnosis, or potential treatment of these cancers.

Funding for Refugee Health Research From the National Institutes of Health Between 2000 and 2020.

Importance: The US has historically resettled more refugees than any other country, with over 3.5 million refugees since 1980. The National Institutes of Health (NIH) is the largest public funder of biomedical research and development, but its role in mitigating many health disparities refugees experience through its funded research remains unknown. Objective: To examine the NIH's research funding patterns on refugee health research over the last 2 decades. Design, Setting, and Participants: Secondary analysis of NIH-funded grants between 2000 and 2020 using a cross-sectional study design. The NIH Research Portfolio Online Reporting Tools database was used to find relevant grants. Data were analyzed from November 2021 to September 2022. Main Outcomes and Measures: NIH grants awarded by year, state, grant type, research area, funding institute, grant duration, and amount funded. Results: Of 1.7 million NIH grants funded over the 20-year study period, only 78 addressed refugee health. Funded grants were mostly training grants (23 grants [29%]), followed by hypothesis-driven research (R01 grants; 22 grants [28%]), pilot or preliminary investigation proposals (13 grants [17%]), and other types of grants (20 grants [26%]). The most studied research domain was mental health (36 grants [46%]), followed by refugee family dynamics and women's and children's health (14 grants [18%]). A total of 26 grants (33%) were funded by the National Institute of Mental Health and 15 (19%) were funded by the National Institute of Child Health and Human Development. Most grants were US-based (60 grants [76%]) and the state of Massachusetts received the greatest amount of funding ($14 825 852 [18%]). In 2020, the NIH allocated about $2.3 million to refugee health research, or less than 0.01% of its $42 billion budget that year. The number of grants funded in each time period did not always reflect changes in the number of refugees resettled in the US over the years. Conclusions and Relevance: This cross-sectional study found that there remain significant gaps in the understanding of and interventions in the health research needs of refugees locally and along the migratory route. To close these gaps, the NIH should increase its investments in comprehensive studies assessing the physical, mental, and social well-being of this expanding population. This can be achieved by ensuring that all NIH institutes allocate budgets specifically for refugee health research and extend support for the training of refugee researchers.

Self-reported Disability Among Recently Resettled Refugees in the United States: Results from the National Annual Survey of Refugees.

The prevalence rates and correlates of mental or physical disability among recently resettled refugees, who undergo strenuous journeys before arriving in the US, remain unknown, masking potential health disparities. Self-reported disability was measured by the 2018 Annual Survey of Refugees (ASR), and defined as having a physical, mental, or other health condition for more than 6 months that precluded one from working. Prevalence rates of self-reported disability and sample correlates were investigated using descriptive and logistic regression analyses. Of N = 4259 participating refugees in ASR (Mean Age = 28.2, SD = 17.2; 52.5% male), 2875 responded to the disability question and 21.4% reported disability. About 33.7% were born in the Middle East region, 29.5% had no formal education, and 35% had an income of less than $15,000. Age (OR = 1.06, 95% Confidence Interval (CI) [1.06,1.07], p < 0.001), region of birth (OR = 1.82, 95% CI [1.31, 2.51], p < 0.001), employment status (OR = 3.31, 95% CI [2.67, 4.11], p < 0.001), and receiving food stamps (OR = 2.09, 95% CI [1.66, 2.62], p < 0.001) were associated with self-reported disability. Disability levels among refugees recently resettled in the United States are comparable to national disability rates in the US. Our results suggest that multiple aspects of the refugee experience (i.e., demographics, socioeconomic status, contextual migration history) need to be considered to understand the risk for health outcomes. Future investigations of disabilities in diverse refugee populations over time and tailored public health interventions to mitigate potential risk factors are warranted to promote health equity.

Time-restricted feeding normalizes hyperinsulinemia to inhibit breast cancer in obese postmenopausal mouse models.

Accumulating evidence indicates that obesity with its associated metabolic dysregulation, including hyperinsulinemia and aberrant circadian rhythms, increases the risk for a variety of cancers including postmenopausal breast cancer. Caloric restriction can ameliorate the harmful metabolic effects of obesity and inhibit cancer progression but is difficult to implement and maintain outside of the clinic. In this study, we aim to test a time-restricted feeding (TRF) approach on mouse models of obesity-driven postmenopausal breast cancer. We show that TRF abrogates the obesity-enhanced mammary tumor growth in two orthotopic models in the absence of calorie restriction or weight loss. TRF also reduces breast cancer metastasis to the lung. Furthermore, TRF delays tumor initiation in a transgenic model of mammary tumorigenesis prior to the onset of obesity. Notably, TRF increases whole-body insulin sensitivity, reduces hyperinsulinemia, restores diurnal gene expression rhythms in the tumor, and attenuates tumor growth and insulin signaling. Importantly, inhibition of insulin secretion with diazoxide mimics TRF whereas artificial elevation of insulin through insulin pumps implantation reverses the effect of TRF, suggesting that TRF acts through modulating hyperinsulinemia. Our data suggest that TRF is likely to be effective in breast cancer prevention and therapy.

Degradation of splicing factor SRSF3 contributes to progressive liver disease.

Serine rich splicing factor 3 (SRSF3) plays a critical role in liver function and its loss promotes chronic liver damage and regeneration. As a consequence, genetic deletion of SRSF3 in hepatocytes caused progressive liver disease and ultimately led to hepatocellular carcinoma. Here we show that SRSF3 is decreased in human liver samples with non-alcoholic fatty liver disease (NAFLD), non-alcoholic steatohepatitis (NASH), or cirrhosis that was associated with alterations in RNA splicing of known SRSF3 target genes. Hepatic SRSF3 expression was similarly decreased and RNA splicing dysregulated in mouse models of NAFLD and NASH. We showed that palmitic acid-induced oxidative stress caused conjugation of the ubiquitin like NEDD8 protein to SRSF3 and proteasome mediated degradation. SRSF3 was selectively neddylated at lysine11 and mutation of this residue (SRSF3-K11R) was sufficient to prevent both SRSF3 degradation and alterations in RNA splicing. Finally prevention of SRSF3 degradation in vivo partially protected mice from hepatic steatosis, fibrosis and inflammation. These results highlight a neddylation-dependent mechanism regulating gene expression in the liver that is disrupted in early metabolic liver disease and may contribute to the progression to NASH, cirrhosis and ultimately hepatocellular carcinoma.