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BackgroundThere is a critical need for non-narcotic analgesic adjuncts in the treatment of thoracic pain. We evaluated the efficacy of intercostal cryoneurolysis as an analgesic adjunct for chest wall pain, specifically addressing the applicability of intercostal cryoneurolysis for pain control after chest wall trauma.MethodsA systematic review was performed through searches of PubMed, EMBASE, and the Cochrane Library. We included studies involving patients of all ages that evaluated the efficacy of intercostal cryoneurolysis as a pain adjunct for chest wall pathology. Quantitative and qualitative synthesis was performed.ResultsTwenty-three studies including 570 patients undergoing cryoneurolysis met eligibility criteria for quantitative analysis. Five subgroups of patients treated with intercostal cryoneurolysis were identified: pectus excavatum (nine studies); thoracotomy (eight studies); post-thoracotomy pain syndrome (three studies); malignant chest wall pain (two studies); and traumatic rib fractures (one study). There is overall low-quality evidence supporting intercostal cryoneurolysis as an analgesic adjunct for chest wall pain. A majority of studies demonstrated decreased inpatient narcotic use with intercostal cryoneurolysis compared with conventional pain modalities. Intercostal cryoneurolysis may also lead to decreased hospital length of stay. The procedure did not definitively increase operative time, and risk of complications was low.ConclusionsGiven the favorable risk-to-benefit profile, both percutaneous and thoracoscopic intercostal cryoneurolysis may serve as a worthwhile analgesic adjunct in trauma patients with rib fractures who have failed conventional medical management. However, further prospective studies are needed to improve quality of evidence.Level of evidenceLevel IV systematic reviews and meta-analyses.

Efforts to model the gut microbiome have yielded important insights into the mechanisms of interspecies interactions, the impact of priority effects on ecosystem dynamics, and the role of diet and nutrient availability in determining community composition. However, the model communities studied to date have been defined or complex but not both, limiting their utility. Here, we construct a defined community of 104 bacterial strains composed of the most common taxa from the human gut microbiota. By propagating this community in growth media missing one amino acid at a time, we show that branched-chain amino acids have an outsize impact on community structure and identify a pathway in Clostridium sporogenes for generating ATP from arginine. We constructed and propagated the complete set of single-strain dropout communities, revealing a sparse network of strain-strain interactions including a novel interaction between C. sporogenes and Lactococcus lactis driven by metabolism. This work forms a foundation for studying strain-strain and strain-nutrient interactions in highly complex defined communities, and it provides a starting point for interrogating the rules of synthetic ecology at the 100+ strain scale.

Efforts to model the human gut microbiome in mice have led to important insights into the mechanisms of host-microbe interactions. However, the model communities studied to date have been defined or complex but not both, limiting their utility. In accompanying work, we constructed a complex synthetic community (104 strains, hCom1) containing the most common taxa in the human gut microbiome. Here, we used an iterative experimental process to improve hCom1 by filling open metabolic and/or anatomical niches. When we colonized germ-free mice with hCom1 and then challenged it with a human fecal sample, the consortium exhibited surprising stability; 89% of the cells and 58% of the taxa derive from the original community, and the pre- and post-challenge communities share a similar overall structure. We used these data to construct a second version of the community, adding 22 strains that engrafted following fecal challenge and omitting 7 that dropped out (119 strains, hCom2). In gnotobiotic mice, hCom2 exhibited increased stability to fecal challenge and robust colonization resistance against pathogenic Escherichia coli. Mice colonized by hCom2 versus human feces are similar in terms of microbiota-derived metabolites, immune cell profile, and bacterial density in the gut, suggesting that this consortium is a prototype of a model system for the human gut microbiome.

Electronics waste production has been fueled by economic growth and the demand for faster, more efficient consumer electronics. The glass and metals in end-of-life electronics components can be reused or recycled; however, conventional extraction methods rely on energy-intensive processes that are inefficient when applied to recycling e-waste that contains mixed materials and small amounts of metals. To make e-waste recycling economically viable and competitive with obtaining raw materials, recovery methods that lower the cost of metal reclamation and minimize environmental impact need to be developed. Microbial surface adsorption can aid in metal recovery with lower costs and energy requirements than traditional metal-extraction approaches. We introduce a novel method for metal recovery by utilizing metal-binding peptides to functionalize fungal mycelia and enhance metal recovery from aqueous solutions such as those found in bioremediation or biomining processes. Using copper-binding as a proof-of-concept, we compared binding parameters between natural motifs and those derived in silico, and found comparable binding affinity and specificity for Cu. We then combined metal-binding peptides with chitin-binding domains to functionalize a mycelium-based filter to enhance metal recovery from a Cu-rich solution. This finding suggests that engineered peptides could be used to functionalize biological surfaces to recover metals of economic interest and allow for metal recovery from metal-rich effluent with a low environmental footprint, at ambient temperatures, and under circumneutral pH.

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IMPORTANCECritical burn management decisions rely on accurate percent total body surface area (%TBSA) burn estimation. Existing %TBSA burn estimation models (eg, Lund-Browder chart and rule of nines) were derived from a linear formula and a limited number of individuals a century ago and do not reflect the range of body habitus of the modern population.OBJECTIVE To develop a practical %TBSA burn estimation tool that accounts for exact burn injury pattern, sex, and body habitus. DESIGN, SETTING, AND PARTICIPANTSThis population-based cohort study evaluated the efficacy of a computer vision algorithm application in processing an adult laser body scan data set. High-resolution surface anthropometry laser body scans of 3047 North American and European adults aged 18 to 65 years from the Civilian American and European Surface Anthropometry Resource data set (1998)(1999)(2000)(2001) were included. Of these, 1517 participants (49.8%) were male. Race and ethnicity data were not available for analysis. Analyses were conducted in 2020. MAIN OUTCOMES AND MEASURESThe contributory %TBSA for 18 body regions in each individual. Mobile application for real-time %TBSA burn computation based on sex, habitus, and exact burn injury pattern. RESULTSOf the 3047 individuals aged 18 to 65 years for whom body scans were available, 1517 (49.8%) were male. Wide individual variability was found in the extent to which major body regions contributed to %TBSA, especially in the torso and legs. Anterior torso %TBSA increased with increasing body habitus (mean [SD], 15.1 [0.9] to 19.1 [2.0] for male individuals; 15.1 [0.8] to 18.0 [1.7] for female individuals). This increase was attributable to increase in abdomen %TBSA (mean [SD], 5.3 [0.7] to 8.7 [1.8]) among male individuals and increase in abdomen (mean [SD], 4.6 [0.6] to 6.8 [1.7]) and pelvis (mean [SD], 1.5 [0.2] to 2.9 [0.9]) %TBSAs among female individuals. For most body regions, Lund-Browder chart and rule of nines estimates fell outside the population's measured interquartile ranges. The mobile application tested in this study, Burn Area, facilitated accurate %TBSA burn computation based on exact burn injury pattern for 10 sex and body habitus-specific models.CONCLUSIONS AND RELEVANCE Computer vision algorithm application to a large laser body scan data set may provide a practical tool that facilitates accurate %TBSA burn computation in the modern era.