From patterns to patients: Advances in clinical machine learning for cancer diagnosis, prognosis, and treatment.

Machine learning (ML) is increasingly used in clinical oncology to diagnose cancers, predict patient outcomes, and inform treatment planning. Here, we review recent applications of ML across the clinical oncology workflow. We review how these techniques are applied to medical imaging and to molecular data obtained from liquid and solid tumor biopsies for cancer diagnosis, prognosis, and treatment design. We discuss key considerations in developing ML for the distinct challenges posed by imaging and molecular data. Finally, we examine ML models approved for cancer-related patient usage by regulatory agencies and discuss approaches to improve the clinical usefulness of ML.

Cannabinoid receptor 1 antagonist genistein attenuates marijuana-induced vascular inflammation.

Epidemiological studies reveal that marijuana increases the risk of cardiovascular disease (CVD); however, little is known about the mechanism. Δ9-tetrahydrocannabinol (Δ9-THC), the psychoactive component of marijuana, binds to cannabinoid receptor 1 (CB1/CNR1) in the vasculature and is implicated in CVD. A UK Biobank analysis found that cannabis was an risk factor for CVD. We found that marijuana smoking activated inflammatory cytokines implicated in CVD. In silico virtual screening identified genistein, a soybean isoflavone, as a putative CB1 antagonist. Human-induced pluripotent stem cell-derived endothelial cells were used to model Δ9-THC-induced inflammation and oxidative stress via NF-κB signaling. Knockdown of the CB1 receptor with siRNA, CRISPR interference, and genistein attenuated the effects of Δ9-THC. In mice, genistein blocked Δ9-THC-induced endothelial dysfunction in wire myograph, reduced atherosclerotic plaque, and had minimal penetration of the central nervous system. Genistein is a CB1 antagonist that attenuates Δ9-THC-induced atherosclerosis.

Leveraging physiology and artificial intelligence to deliver advancements in health care.

Artificial intelligence in health care has experienced remarkable innovation and progress in the last decade. Significant advancements can be attributed to the utilization of artificial intelligence to transform physiology data to advance health care. In this review, we explore how past work has shaped the field and defined future challenges and directions. In particular, we focus on three areas of development. First, we give an overview of artificial intelligence, with special attention to the most relevant artificial intelligence models. We then detail how physiology data have been harnessed by artificial intelligence to advance the main areas of health care: automating existing health care tasks, increasing access to care, and augmenting health care capabilities. Finally, we discuss emerging concerns surrounding the use of individual physiology data and detail an increasingly important consideration for the field, namely the challenges of deploying artificial intelligence models to achieve meaningful clinical impact.

2-(3-Indolyl)acetamides and their oxazoline analogues: Anticancer SAR study.

We previously studied 2-aryl-2-(3-indolyl)acetohydroxamates as potential agents against melanoma. These compounds were ineffective in a mouse melanoma xenograft model, most likely due to unfavorable metabolic properties, specifically due to glucuronidation of the N-hydroxyl of the hydoxamic moiety. In the present work, we prepared a series of analogues, 2-aryl-2-(3-indolyl)acetamides and their oxazoline derivatives, which do not contain the N-hydroxyl group. We investigated the structure-activity relationship in both series of compounds and found that the 2-naphthyl is a preferred group at C-2 of the indole in the amide series, whereas the tetralin moiety is favorable in the same location in the oxazoline series. Overall, three compounds in the amide series have GI50 values as low as 0.2-0.3 µM and the results clearly indicate that the N-hydroxyl group is not necessary for high potency in vitro.

Buckle me up! A randomised controlled trial using a tablet-based emergency department intervention for child car safety education.

BACKGROUND AND OBJECTIVES: Correct child car restraint use significantly reduces risk of death and serious injury in motor vehicle crashes, but millions of US children ride with improper restraints. We created a tablet-based car restraint educational intervention using Computer Intervention Authoring Software (CIAS) and examined its impact on knowledge and behaviours among parents in the paediatric emergency department (PED). METHODS: This was a non-blinded, randomised controlled trial of parents of PED patients ages 0-12 years. Participants were evaluated for baseline car restraint knowledge and behaviour. The intervention group completed an interactive tablet-based module, while the control group received printed handouts on car restraint safety. After 1 week, both groups received a follow-up survey assessing changes in car restraint knowledge and behaviour. Logistic regressions determined predictors of knowledge retention and behavioural changes. Parents in the CIAS group were also surveyed on programme acceptability. RESULTS: 211 parents completed the study with follow-up data. There was no significant difference in baseline car restraint knowledge (74.3% correct in intervention, 61.8% in control, p=0.15), or increase in follow-up restraint knowledge. Significantly more intervention-group caregivers reported modifying their child's car restraint at follow-up (52.5% vs 31.8%,p=0.003), and 93.7% of them found CIAS helpful in learning to improve car safety. CONCLUSION: Parents had overall high levels of car restraint knowledge. Using CIAS led to positive behavioural changes regarding child car restraint safety, with the vast majority reporting positive attitudes towards CIAS. This novel, interactive, tablet-based tool is a useful PED intervention for behavioural change in parents. TRIAL REGISTRATION NUMBER: NCT03799393.

Changing the default meal option at university events to reduce harmful environmental impacts: Six randomized controlled trials.

Animal agriculture is a leading contributor to greenhouse gas emissions and other harmful environmental impacts, which underscores the need to shift away from the consumption of animal-based products. One promising nudge intervention is making plant-based meals the default option, so we tested this approach at six different university events across four academic institutions for effecting sustainable dietary change. Event attendees pre-selected their meal on one of two randomly assigned RSVP forms: one with a plant-based default and one with a meal with meat default. The results from our randomized controlled trial showed that participants had a 43-percentage point greater probability of selecting the plant-based meal when it was indicated as the default option. This effect was similar across events and academic institutions, which indicates that this default intervention is generalizable and can be successfully implemented at university events. The combined effect of using plant-based defaults at these six events was an estimated reduction of 104,387 kg of CO2 emissions, 299.9 m2 of land use, 959.0 g of nitrogen use, and 259.5 g of phosphorus use, which represent roughly 45-46.2% reductions in harmful environmental impacts relative to the meals chosen when using a meat default. Given the significance and magnitude of these environmental benefits, our results support the widespread implementation of plant-based defaults for helping universities improve their sustainability.

Dual burden of infectious and chronic disease in low-resource U.S. communities: examining relationships between infection, adiposity, and inflammation.

BACKGROUND: Rising global obesity rates are linked with inflammation and associated morbidities. These negative outcomes are generally more common in low-resource communities within high-income countries; however, it is unclear how frequent infectious disease exposures in these settings may influence the relationship between adiposity and inflammation. AIM: We test associations between adiposity measures and distinct forms of inflammation among adults (n = 80) living in low-resource U.S. communities experiencing high levels of obesity and pathogen exposure. SUBJECTS AND METHODS: Adiposity measures included BMI and percent body fat. Inflammation measures included systemic inflammation (C-reactive protein [CRP]) and localised intestinal inflammation (faecal calprotectin [FC]). The relationship between a condition characterised by elevated inflammation (Helicobacter pylori infection) and adiposity was also considered. RESULTS: Adiposity was not significantly related to FC concentration. However, both adiposity measures were positively related with odds of CRP elevation and H. pylori infection was associated with significantly lower adiposity measures (all p < 0.05). CONCLUSION: For this disadvantaged U.S. sample, the association between adiposity and inflammation varies by the systemic/localised nature of inflammation and the likely underlying cause of inflammation. Defining these associations will improve understanding of how rising obesity rates shape long-term health inequities, with implications for more effective intervention design.

Dysplastic hips demonstrate increased joint translation at higher body mass index.

OBJECTIVE: To determine which radiographic measures used to define the severity of hip dysplasia are associated with hip joint translation and to investigate relationships between position, body mass index, and joint translation. MATERIALS AND METHODS: This is a cross-sectional retrospective study evaluating 10 validated radiographic measures of dysplasia on weight-bearing AP pelvis and supine 45-degree bilateral Dunn radiographs of 93 young adults with symptomatic hip dysplasia presenting to a single academic institution between October 2016 and May 2019. We determined the difference between standing and supine measurements for each hip and the correlation of each measure with the patient's body mass index. RESULTS: Femoral head extrusion index was 2.49% lower on supine X-ray (p = 0.0020). Patients with higher body mass index had higher center gap distance (p = 0.0274), femoral head extrusion (p = 0.0170), and femoral head lateralization (p = 0.0028) when standing. They also had higher Tönnis angle (pstanding = 0.0076, psupine = 0.0121) and lower lateral center-edge angle (pstanding = 0.0196, psupine = 0.0410) in both positions. The difference in femoral head lateralization between standing and supine positions increased with higher body mass index (p = 0.0081). CONCLUSION: Translation of the hip joint with position change is demonstrated by decreased femoral head extrusion index on supine X-ray. Patients with higher body mass index had more dysplastic hips, as measured by five of six radiographic outcomes of dysplasia, and experienced more translation with weight-bearing, reflected by increased femoral head lateralization.

Case Report: A Child With Omental Infarction.

BACKGROUND: Omental infarction (OI) is a rare cause of acute abdominal pain, which is benign and self-limited. It is diagnosed by imaging. The etiology of OI is either idiopathic or secondary and due to torsion, trauma, hypercoagulability, vasculitis, or pancreatitis. CASE REPORT: Here, we present a case of OI in a child with acute severe right upper quadrant pain. WHY SHOULD AN EMERGENCY PHYSICIAN BE AWARE OF THIS?: Correct diagnosis of OI via imaging can prevent unnecessary surgery.

Adaptive laboratory evolution for improved tolerance of isobutyl acetate in Escherichia coli.

Previously, Escherichia coli was engineered to produce isobutyl acetate (IBA). Titers greater than the toxicity threshold (3 g/L) were achieved by using layer-assisted production. To avoid this costly and complex method, adaptive laboratory evolution (ALE) was applied to E. coli for improved IBA tolerance. Over 37 rounds of selective pressure, 22 IBA-tolerant mutants were isolated. Remarkably, these mutants not only tolerate high IBA concentrations, they also produce higher IBA titers. Using whole-genome sequencing followed by CRISPR/Cas9 mediated genome editing, the mutations (SNPs in metH, rho and deletion of arcA) that confer improved tolerance and higher titers were elucidated. The improved IBA titers in the evolved mutants were a result of an increased supply of acetyl-CoA and altered transcriptional machinery. Without the use of phase separation, a strain capable of 3.2-fold greater IBA production than the parent strain was constructed by combing select beneficial mutations. These results highlight the impact improved tolerance has on the production capability of a biosynthetic system.

Microbial production of human milk oligosaccharide lactodifucotetraose.

Human milk oligosaccharides (HMOs) are potent bioactive compounds that modulate neonatal health and are of interest for development as potential drug treatments for adult diseases. The potential of these molecules, their limited access from natural sources, and difficulty in large-scale isolation of individual HMOs for studies and applications have motivated the development of chemical syntheses and in vitro enzymatic catalysis strategies. Whole cell biocatalysts are emerging as alternative self-regulating production platforms that have the potential to reduce the cost for enzymatic synthesis of HMOs. Whole cell biocatalysts for the production of short-chained, linear and small monofucosylated HMOs have been reported but those for fucosylated structures with higher complexity have not been explored. In this study, we established a strategy for producing a difucosylated HMO, lactodifucotetraose (LDFT), from lactose and L-fucose in Escherichia coli. We used two bacterial fucosyltransferases with narrow acceptor selectivity to drive the sequential fucosylation of lactose and intermediate 2'-fucosyllactose (2'-FL) to produce LDFT. Deletion of substrate degradation pathways that decoupled cellular growth from LDFT production, enhanced expression of native substrate transporters and modular induction of the genes in the LDFT biosynthetic pathway allowed complete conversion of lactose into LDFT and minor quantities of the side product 3-fucosyllactose (3-FL). Overall, 5.1 g/L of LDFT was produced from 3 g/L lactose and 3 g/L L-fucose in 24 h. Our results demonstrate promising applications of engineered microbial biosystems for the production of multi-fucosylated HMOs for biochemical studies.

TAP AND INJECT VERSUS PARS PLANA VITRECTOMY FOR POSTPROCEDURAL ENDOPHTHALMITIS: A Meta-analysis.

PURPOSE: To compare the visual outcomes after prompt pars plana vitrectomy (PPV) with tap biopsy and intravitreal antimicrobial injection to treat postinjection and postsurgery endophthalmitis. METHODS: The Cochrane Central Register of Controlled Trials, Ovid MEDLINE, and Ovid Embase databases were searched for articles published between January 2010 and November 2020. Two independent reviewers selected articles and extracted data. We analyzed data in RevMan 5.3 and assessed methodological quality using the Cochrane ROBINS-I tool. The mean improvement in visual outcome was compared between PPV and intravitreal antimicrobial injection as a relative risk of improving ≥2 lines and a mean logarithm of the minimal angle of resolution difference in improvement. RESULTS: Fifteen retrospective case series (1,355 eyes), of which 739 eyes (55%) received intravitreal antimicrobial injection and 616 (45%) received PPV as initial treatment, were included. The overall relative risk of improving 2 or more lines in PPV in comparison with intravitreal antimicrobial injection was 1.04 (95% CI 0.88-1.23; P = 0.61; I2 = 0%) with a mean difference of 0.04 (95% CI -0.18 to 0.27; P = 0.69; I2 = 0%). The results stayed robust when subgroup analysis based on causative procedure for endophthalmitis was performed. CONCLUSION: Intravitreal antimicrobial injection is noninferior to PPV for the treatment of postcataract operation, postinjection, and post-PPV endophthalmitis.

Coordinate regulation of long non-coding RNAs and protein-coding genes in germ-free mice.

BACKGROUND: Long non-coding RNAs (lncRNAs) are increasingly recognized as regulators of tissue-specific cellular functions and have been shown to regulate transcriptional and translational processes, acting as signals, decoys, guides, and scaffolds. It has been suggested that some lncRNAs act in cis to regulate the expression of neighboring protein-coding genes (PCGs) in a mechanism that fine-tunes gene expression. Gut microbiome is increasingly recognized as a regulator of development, inflammation, host metabolic processes, and xenobiotic metabolism. However, there is little known regarding whether the gut microbiome modulates lncRNA gene expression in various host metabolic organs. The goals of this study were to 1) characterize the tissue-specific expression of lncRNAs and 2) identify and annotate lncRNAs differentially regulated in the absence of gut microbiome. RESULTS: Total RNA was isolated from various tissues (liver, duodenum, jejunum, ileum, colon, brown adipose tissue, white adipose tissue, and skeletal muscle) from adult male conventional and germ-free mice (n = 3 per group). RNA-Seq was conducted and reads were mapped to the mouse reference genome (mm10) using HISAT. Transcript abundance and differential expression was determined with Cufflinks using the reference databases NONCODE 2016 for lncRNAs and UCSC mm10 for PCGs. Although the constitutive expression of lncRNAs was ubiquitous within the enterohepatic (liver and intestine) and the peripheral metabolic tissues (fat and muscle) in conventional mice, differential expression of lncRNAs by lack of gut microbiota was highly tissue specific. Interestingly, the majority of gut microbiota-regulated lncRNAs were in jejunum. Most lncRNAs were co-regulated with neighboring PCGs. STRING analysis showed that differentially expressed PCGs in proximity to lncRNAs form tissue-specific networks, suggesting that lncRNAs may interact with gut microbiota/microbial metabolites to regulate tissue-specific functions. CONCLUSIONS: This study is among the first to demonstrate that gut microbiota critically regulates the expression of lncRNAs not only locally in intestine but also remotely in other metabolic organs, suggesting that common transcriptional machinery may be shared to transcribe lncRNA-PCG pairs, and lncRNAs may interact with PCGs to regulate tissue-specific pathways.

Metabolic engineering tools in model cyanobacteria.

Developing sustainable routes for producing chemicals and fuels is one of the most important challenges in metabolic engineering. Photoautotrophic hosts are particularly attractive because of their potential to utilize light as an energy source and CO2 as a carbon substrate through photosynthesis. Cyanobacteria are unicellular organisms capable of photosynthesis and CO2 fixation. While engineering in heterotrophs, such as Escherichia coli, has result in a plethora of tools for strain development and hosts capable of producing valuable chemicals efficiently, these techniques are not always directly transferable to cyanobacteria. However, recent efforts have led to an increase in the scope and scale of chemicals that cyanobacteria can produce. Adaptations of important metabolic engineering tools have also been optimized to function in photoautotrophic hosts, which include Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-Cas9, 13C Metabolic Flux Analysis (MFA), and Genome-Scale Modeling (GSM). This review explores innovations in cyanobacterial metabolic engineering, and highlights how photoautotrophic metabolism has shaped their development.

Mechanisms for Joint Pain in Rheumatoid Arthritis (RA): from Cytokines to Central Sensitization.

PURPOSE OF REVIEW: Pain in rheumatoid arthritis (RA) may be due to different etiologies, ranging from peripheral inflammation to dysregulation of central nervous system (CNS) processing. This review evaluates relevant literature published on RA pain mechanisms in recent years. RECENT FINDINGS: Despite successes of disease-modifying antirheumatic drugs (DMARDs), pain persists for many RA patients. Studies involving patient-reported outcomes, quantitative sensory testing, and neuroimaging indicate that, in addition to joint inflammation, abnormalities in CNS pain processing may contribute to pain. Some DMARDs (e.g., janus kinus inhibitors) may work via multiple pathways to decrease pain. Adjunctive treatments (e.g., antidepressants, antiepileptics) may also be useful in managing pain in RA patients with well-controlled disease. Both peripheral and central mechanisms play key roles in the expression of pain in RA. To effectively manage pain, physicians need accurate assessment tools to identify the pathways involved in each patient so that treatments may be appropriately targeted.