Standardizing the skin tape stripping method for sensitization and using it to create a mouse model of peanut allergy.

BACKGROUND: Animal models for food allergies serve as crucial tools in understanding allergy mechanisms and assessing the efficacy of potential desensitization methods. The effectiveness of inducing allergies in mice through intragastric lavage sensitization varies. The intraperitoneal method can trigger systemic anaphylaxis, however it lacks anatomical relevance. Hence, a uniform and reliable allergy induction method in mice is required. Tape stripping can mimic atopic dermatitis (AD), a precursor to lifelong peanut allergies in humans. Furthermore, skin damage triggers the upregulation of skin alarmins and the expansion of small-intestinal mast cells, both implicated in allergy development. METHODS: We standardized a skin-based sensitization method in a mouse model of peanut allergy using skin tape stripping followed by allergen application. We compared this method with intragastric sensitization. RESULTS: Skin-based sensitization led to increased mast cells, goblet cells, and eosinophils in the small intestine, elevated systemic IgE levels, murine mast cell protease-1 (mMCP-1), histamine, and eosinophilic activity in peripheral blood. Moreover, it resulted in a significant hypothermic response, with nearly 30% mortality following an oral challenge one-month post-sensitization. CONCLUSION: Our research offers a standardized and readily reproducible method for inducing peanut allergy in mice, which could also be adapted for other food allergens.

Recommendations on visit duration and sample number requirements for an automated head chamber system.

Automated head chamber systems (AHCS; GreenFeed, C-Lock Inc., Rapid City, SD) increasingly are being used for measuring the gas flux of unrestrained cattle. There are a wide range of recommendations for what constitutes a "good" visit (i.e., duration) to an AHCS and how many visits are required for the AHCS to quantify gas fluxes accurately and precisely. Accordingly, the purpose of this experiment was to investigate the effects of visit duration thresholds and the subsequent effects of these thresholds on the number of visits needed to provide adequate estimates of carbon dioxide (CO2) and methane (CH4) emissions, and oxygen (O2) consumption by beef cattle. This analysis utilized data from three previously published experiments with grazing beef steers and one experiment with finishing beef steers, with 103 steers total. When comparing all available visits, there was excellent agreement [Lin's concordance correlation coefficient (CCC) ≥ 0.96] between visits ≥ 3 min in duration and those ≥ 2 min for the three gases in all four experiments. When data from all four experiments were pooled, there was excellent agreement between visits ≥ 3 min and those ≥ 2 min and ≥ 1 min for all gases (CCC ≥ 0.96). These results suggest that estimates from visits ≥ 2 min are like those from visits ≥ 3 min. Next, we investigated if including visits ≥ 2 min or ≥ 1 min would increase the minimal number of visits required to provide excellent agreement with the "gold-standard" (mean of all visits ≥ 3 min). For this, we used only one of the experiments and randomly selected visits per animal ranging from n = 5 to 60, in increments of 5. The sole experiment was used because all animals had more than 60 visits. We then assessed the agreement between the "gold-standard" (mean of all visits ≥ 3 min [144 ±â€…55.01 visits per steer]) estimates of CO2, O2, and CH4. The minimum number of visits required to achieve excellent agreement (CCC ≥ 0.90) to the "gold-standard" estimate for all gases was 30 visits ≥ 3 min in duration, or 40 visits ≥ 2 min in duration. Visits ≥ 1 min in duration did not achieve excellent agreement, even when 60 were used. Based on these results, we recommend excluding visits < 3 min in duration with 30 minimum visit records per animal. However, if researchers choose to implement a 2-min visit duration threshold then 40 visit records are needed per animal.

GreenFeed systems (C-Lock Inc., Rapid City, SD) are being increasingly used for measuring carbon dioxide (CO2) and methane (CH4) emissions and oxygen consumption (O2) of free-roaming cattle. These systems utilize averages of multiple visits to provide estimates of daily gas flux. There currently exists a range of recommendations for what constitutes a "good" visit to GreenFeed. Additionally, the number of recommended visits required to achieve adequate estimates of these gas fluxes appears to be dependent on the minimum visit duration that is used. To date, there has been only one experiment that has investigated visit duration and the recommended number of visits for CO2 and CH4 emissions and to our knowledge this has not been assessed for O2 consumption. Based on the results of this experiment, we recommend using a 3-min minimum visit duration threshold with 30 visit records per animal. If researchers choose to use a 2-min visit duration threshold, then 40 visit records per animal are recommended.

An exploratory study of service user and clinical outcomes in telehealth-delivered dialectical behavior therapy for adolescents skills groups.

The COVID-19 pandemic led many in-office therapeutic programs to pivot to virtual programming without empirical data supporting the acceptability and efficacy of the remote-delivered adaptations. These adaptations were essential for continuing care and addressing surging youth psychological problems at the time. To serve adolescents with comorbid psychiatric disorders and associated problems (e.g., emotion dysregulation), we adapted and implemented virtual and hybrid formats of a dialectical behavior therapy for adolescents (DBT-A; Rathus & Miller, 2015) program within a public university training clinic, such as separating the traditional multifamily group into adolescent-only and caregiver-only groups. Building on qualitative reports on virtual DBT-A, we explored preliminary service user and clinical outcomes of the virtual and hybrid DBT-A adolescent skills group component in a longitudinal retrospective cohort study for teenagers treated during the first 2 years of the pandemic (N = 21; 81% Hispanic/Latinx; 100% White). Aim 1 described service user outcomes (e.g., retention, group cohesion, client satisfaction) in the remote-delivered skills groups. Most youth completed treatment. Caregiver satisfaction was high, whereas adolescent satisfaction was mild. Aim 2 explored preliminary clinical outcomes of remote-delivered skills group adaptations. Overall anxiety, panic, and two emotion regulation facets (i.e., emotional awareness; goal pursuit when upset) significantly reduced across treatment. There were no significant reductions in depression. No suicide attempts or suicides occurred during the program. Further work is needed to clarify the efficacy of telehealth formats of DBT-A skills groups in larger, more racially diverse samples and to identify which adolescents are most appropriate for virtual and/or hybrid DBT-A. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Morphological and molecular data establishes Clinostomum dolichorchum n. sp. (Digenea: Clinostomidae) in the great blue heron Ardea herodias L. and American bullfrog Rana catesbeiana Shaw.

Clinostomum is a cosmopolitan genus of trematodes that infect piscivorous birds, freshwater molluscs, freshwater fish and amphibians. Herein, a novel species of Clinostomum is described based on morphological and molecular data from an adult in the oral cavity of the great blue heron Ardea herodias and metacercariae collected from the gills and skin of American bullfrog tadpoles Rana catesbeiana. The novel species shares similar qualitative and quantitative morphological features with a congener, Clinostomum marginatum, which has overlap in host and geographic distribution. The most notable morphological difference when compared to C. marginatum is the greater posterior testis length of the novel species. Molecular data resolved similarities with morphological comparisons to nominal species and supports the establishment of a novel species. Molecular data include partial small ribosomal subunit (18S rRNA gene), ribosomal internal transcribed spacer regions (ITS1, 5.8S rRNA gene, and ITS2), partial large ribosomal subunit (28S rRNA gene), cytochrome c oxidase subunit 1 gene (cox1), and nicotinamide adenine dinucleotide dehydrogenase subunit 1 gene (nad1) sequences. Phylogenetic analyses place the novel species in a sister clade to C. marginatum. Morphological and molecular data, combined with phylogenetic analyses support the establishment of Clinostomum dolichorchum n. sp.

A reduced proteomic signature in critically ill Covid-19 patients determined with plasma antibody micro-array and machine learning.

BACKGROUND: COVID-19 is a complex, multi-system disease with varying severity and symptoms. Identifying changes in critically ill COVID-19 patients' proteomes enables a better understanding of markers associated with susceptibility, symptoms, and treatment. We performed plasma antibody microarray and machine learning analyses to identify novel proteins of COVID-19. METHODS: A case-control study comparing the concentration of 2000 plasma proteins in age- and sex-matched COVID-19 inpatients, non-COVID-19 sepsis controls, and healthy control subjects. Machine learning was used to identify a unique proteome signature in COVID-19 patients. Protein expression was correlated with clinically relevant variables and analyzed for temporal changes over hospitalization days 1, 3, 7, and 10. Expert-curated protein expression information was analyzed with Natural language processing (NLP) to determine organ- and cell-specific expression. RESULTS: Machine learning identified a 28-protein model that accurately differentiated COVID-19 patients from ICU non-COVID-19 patients (accuracy = 0.89, AUC = 1.00, F1 = 0.89) and healthy controls (accuracy = 0.89, AUC = 1.00, F1 = 0.88). An optimal nine-protein model (PF4V1, NUCB1, CrkL, SerpinD1, Fen1, GATA-4, ProSAAS, PARK7, and NET1) maintained high classification ability. Specific proteins correlated with hemoglobin, coagulation factors, hypertension, and high-flow nasal cannula intervention (P < 0.01). Time-course analysis of the 28 leading proteins demonstrated no significant temporal changes within the COVID-19 cohort. NLP analysis identified multi-system expression of the key proteins, with the digestive and nervous systems being the leading systems. CONCLUSIONS: The plasma proteome of critically ill COVID-19 patients was distinguishable from that of non-COVID-19 sepsis controls and healthy control subjects. The leading 28 proteins and their subset of 9 proteins yielded accurate classification models and are expressed in multiple organ systems. The identified COVID-19 proteomic signature helps elucidate COVID-19 pathophysiology and may guide future COVID-19 treatment development.

Physiology evolves convergently but lags behind warming in cities.

Cities, through the generation of urban heat islands, provide a venue for exploring contemporary convergent evolution to climatic warming. We quantified how repeatable the evolution of heat tolerance, cold tolerance, and body size were among diverse lineages in response to urban heat islands. Our study revealed significant shifts towards higher heat tolerance and diminished cold tolerance among urban populations. We further found that the magnitude of trait divergence was significantly and positively associated with the magnitude of the urban heat island, suggesting that temperature played a major role in the observed divergence in thermal tolerance. Despite these trends, the magnitude of trait responses lagged behind environmental warming. Heat tolerance responses exhibited a deficit of 0.84°C for every 1°C increase in warming, suggesting limits on adaptive evolution and consequent adaptational lags. Other moderators were predictive of greater divergence in heat tolerance, including lower baseline tolerance and greater divergence in body size. Although terrestrial species did not exhibit systematic shifts towards larger or smaller body size, aquatic species exhibited significant shifts towards smaller body size in urban habitats. Our study demonstrates how cities can be used to address long-standing questions in evolutionary biology regarding the repeatability of evolution. Importantly, this work also shows how cities can be used as forecasting tools by quantifying adaptational lags and by developing trait-based associations with responses to contemporary warming.

MYBPC3-c.772G>A mutation results in haploinsufficiency and altered myosin cycling kinetics in a patient induced stem cell derived cardiomyocyte model of hypertrophic cardiomyopathy.

Approximately 40% of hypertrophic cardiomyopathy (HCM) mutations are linked to the sarcomere protein cardiac myosin binding protein-C (cMyBP-C). These mutations are either classified as missense mutations or truncation mutations. One mutation whose nature has been inconsistently reported in the literature is the MYBPC3-c.772G > A mutation. Using patient-derived human induced pluripotent stem cells differentiated to cardiomyocytes (hiPSC-CMs), we have performed a mechanistic study of the structure-function relationship for this MYBPC3-c.772G > A mutation versus a mutation corrected, isogenic cell line. Our results confirm that this mutation leads to exon skipping and mRNA truncation that ultimately suggests ∼20% less cMyBP-C protein (i.e., haploinsufficiency). This, in turn, results in increased myosin recruitment and accelerated myofibril cycling kinetics. Our mechanistic studies suggest that faster ADP release from myosin is a primary cause of accelerated myofibril cross-bridge cycling due to this mutation. Additionally, the reduction in force generating heads expected from faster ADP release during isometric contractions is outweighed by a cMyBP-C phosphorylation mediated increase in myosin recruitment that leads to a net increase of myofibril force, primarily at submaximal calcium activations. These results match well with our previous report on contractile properties from myectomy samples of the patients from whom the hiPSC-CMs were generated, demonstrating that these cell lines are a good model to study this pathological mutation and extends our understanding of the mechanisms of altered contractile properties of this HCM MYBPC3-c.772G > A mutation.

Associations between sleep health, negative reinforcement learning, and alcohol use among South Florida college students with elevated internalizing symptoms.

Negative reinforcement is proposed to mediate associations between sleep and alcohol use, especially among people with depression and/or anxiety symptoms. Worse sleep (e.g., shorter duration, less efficiency, more irregular timing) exacerbates negative emotions, which alcohol may temporarily relieve. Not yet examined, we propose sleep indirectly impacts early stages of alcohol use via differences in negative reinforcement learning (NRL), since sleep impacts emotion, reward response, and learning. The current study aimed to replicate associations between sleep and alcohol use, test associations with NRL, and examine indirect associations between sleep health and alcohol use via NRL among 60 underage college students (ages 18-20 years, 77% female) varying in depression and anxiety symptoms. Participants wore Fitbit smartwatches and completed daily diaries measuring sleep and substance use for ∼14 days before completing two computer tasks assessing social (SNRL) and monetary (MNRL) negative reinforcement learning. Robust generalized linear models tested direct associations within the proposed model. SNRL performance was positively associated with alcohol use, but no other associations were observed. Statistical mediation models failed to indicate indirect effects of sleep on alcohol use via SNRL or MNRL performance. Post-hoc exploratory models examining depression and anxiety symptoms as moderators of direct associations indicated several interactions. Positive associations between sleep timing variability and alcohol use were weakened at higher anxiety symptom severity and stronger at higher depression symptom severity. The positive association between SNRL performance and alcohol use was also stronger at higher depression symptom severity. Among students with elevated depression symptoms, variable sleep timing and stronger SNRL performance were independently associated with more alcohol use, but indirect effects were not supported. Future research should replicate findings, confirm causality of interactions, and examine sleep timing and behavioral responses to negative social stimuli as targets for improving alcohol-related outcomes among underage college students with elevated depressive symptoms.

Generation of Broad Protection against Influenza with Di-Tyrosine-Cross-Linked M2e Nanoclusters.

Tyrosine cross-linking has recently been used to produce nanoclusters (NCs) from peptides to enhance their immunogenicity. In this study, NCs were generated using the ectodomain of the ion channel Matrix 2 (M2e) protein, a conserved influenza surface antigen. The NCs were administered via intranasal (IN) or intramuscular (IM) routes in a mouse model in a prime-boost regimen in the presence of the adjuvant CpG. After boost, a significant increase in anti-M2e IgG and its subtypes was observed in the serum and lungs of mice vaccinated through the IM and IN routes; however, significant enhancement in anti-M2e IgA in lungs was observed only in the IN group. Analysis of cytokine concentrations in stimulated splenocyte cultures indicated a Th1/Th17-biased response. Mice were challenged with a lethal dose of A/California/07/2009 (H1N1pdm), A/Puerto Rico/08/1934 (H1N1), or A/Hong Kong/08/1968 (H3N2) strains. Mice that received M2e NCs + CpG were significantly protected against these strains and showed decreased lung viral titers compared with the naive mice and M2e NC-alone groups. The IN-vaccinated group showed superior protection against the H3N2 strain as compared to the IM group. This research extends our earlier efforts involving the tyrosine-based cross-linking method and highlights the potential of this technology in enhancing the immunogenicity of short peptide immunogens.

Lip, oral and oropharyngeal cancer incidence among Aboriginal and Torres Strait Islander Peoples: First report from Australian population-based cancer registry, 1999-2018.

BACKGROUND: The Australian Burden of Disease Study has shown that cancer is the single most important entity responsible for the greatest cause of health burden in Australia. Unfortunately, Aboriginal and Torres Strait Islander peoples experience a greater burden of this disease, with cancer of the lung, breast, bowel and prostrate being the most common. Lip, oral cavity and pharyngeal cancer incidence is rapidly rising globally and is now the sixth most common cancer in Australia. This paper aims to summarize, for the first time, the incidence and prevalence trends of lip, oral cavity and pharyngeal cancers in Aboriginal and Torres Strait Islander Australians. METHODS: Data were obtained from the Australian Cancer Database (ACD), which is compiled at the Australian Institute of Health and Welfare (AIHW) from 1999 to 2018 to estimate the incidence and prevalence of certain head and neck cancers (ICD-10 codes C00-C10, C14). The other variables requested were age groups and sex. RESULTS: Results were stratified by ICD-10 code, sex and age group at diagnosis and time period (i.e. grouped years of diagnosis). The total incidence of lip, oral cavity and pharyngeal cancers increased by 1.3 times from 1999 to 2008 (107/100 000) to 2009-2018 (135/100 000). The overall 5-year prevalence of lip, oral cavity and pharyngeal cancers was 0.17% (0.24% for men and 0.09% for women). CONCLUSIONS: The significantly increased incidence of lip, oral cavity and pharyngeal cancers in Aboriginal and Torres Strait Islander peoples in Australia is concerning and should be explored. A targeted, comprehensive and culturally safe model of care for Aboriginal and Torres Strait Islander peoples with lip, oral cavity and pharyngeal cancers is imperative.

MBNL1 Regulates Programmed Postnatal Switching Between Regenerative and Differentiated Cardiac States.

BACKGROUND: Discovering determinants of cardiomyocyte maturity is critical for deeply understanding the maintenance of differentiated states and potentially reawakening endogenous regenerative programs in adult mammalian hearts as a therapeutic strategy. Forced dedifferentiation paired with oncogene expression is sufficient to drive cardiac regeneration, but elucidation of endogenous developmental regulators of the switch between regenerative and mature cardiomyocyte cell states is necessary for optimal design of regenerative approaches for heart disease. MBNL1 (muscleblind-like 1) regulates fibroblast, thymocyte, and erythroid differentiation and proliferation. Hence, we examined whether MBNL1 promotes and maintains mature cardiomyocyte states while antagonizing cardiomyocyte proliferation. METHODS: MBNL1 gain- and loss-of-function mouse models were studied at several developmental time points and in surgical models of heart regeneration. Multi-omics approaches were combined with biochemical, histological, and in vitro assays to determine the mechanisms through which MBNL1 exerts its effects. RESULTS: MBNL1 is coexpressed with a maturation-association genetic program in the heart and is regulated by the MEIS1/calcineurin signaling axis. Targeted MBNL1 overexpression early in development prematurely transitioned cardiomyocytes to hypertrophic growth, hypoplasia, and dysfunction, whereas loss of MBNL1 function increased cardiomyocyte cell cycle entry and proliferation through altered cell cycle inhibitor transcript stability. Moreover, MBNL1-dependent stabilization of estrogen-related receptor signaling was essential for maintaining cardiomyocyte maturity in adult myocytes. In accordance with these data, modulating MBNL1 dose tuned the temporal window of neonatal cardiac regeneration, where increased MBNL1 expression arrested myocyte proliferation and regeneration and MBNL1 deletion promoted regenerative states with prolonged myocyte proliferation. However, MBNL1 deficiency was insufficient to promote regeneration in the adult heart because of cell cycle checkpoint activation. CONCLUSIONS: Here, MBNL1 was identified as an essential regulator of cardiomyocyte differentiated states, their developmental switch from hyperplastic to hypertrophic growth, and their regenerative potential through controlling an entire maturation program by stabilizing adult myocyte mRNAs during postnatal development and throughout adulthood. Targeting loss of cardiomyocyte maturity and downregulation of cell cycle inhibitors through MBNL1 deletion was not sufficient to promote adult regeneration.

ATR blocks telomerase from converting DNA breaks into telomeres.

Telomerase, the enzyme that maintains telomeres at natural chromosome ends, should be repressed at double-strand breaks (DSBs), where neotelomere formation can cause terminal truncations. We developed an assay to detect neotelomere formation at Cas9- or I-SceI-induced DSBs in human cells. Telomerase added telomeric repeats to DSBs, leading to interstitial telomeric repeat insertions or the formation of functional neotelomeres accompanied by terminal deletions. The threat that telomerase poses to genome integrity was minimized by ataxia telangiectasia and Rad3-related (ATR) kinase signaling, which inhibited telomerase at resected DSBs. In addition to acting at resected DSBs, telomerase used the extruded strand in the Cas9 enzyme-product complex as a primer for neotelomere formation. We propose that although neotelomere formation is detrimental in normal human cells, it may allow cancer cells to escape from breakage-fusion-bridge cycles.

Retrospective Evaluation of Cystatin C as a Measure of Renal Function in Pediatric Hematopoietic Stem Cell Transplant Patients Receiving Foscarnet for Cytomegalovirus Reactivation.

BACKGROUND: Cytomegalovirus (CMV) infection following allogeneic hematopoietic cell transplantation has considerable morbidity and mortality, and foscarnet is a treatment option that requires renal dose adjustment. Serum creatinine (SCr)-based estimated glomerular filtration rate (eGFR) equations are used to estimate renal function for patients receiving foscarnet, but cystatin C (cysC) has been shown as a possible alternative. Data examining cysC-based eGFR in this population is sparse. Our primary objective was to evaluate outcomes of patients treated with foscarnet dosed utilizing cysC-based eGFR versus SCr-based eGFR. METHODS: We analyzed patients on the transplantation and cellular therapies service at Memorial Sloan Kettering Kids from January 2011 to September 2021 who received allogeneic hematopoietic cell transplantation and ≥14 days of foscarnet for CMV infection. Patients with cysC-based eGFR were compared to a historical cohort of patients who only had SCr-based eGFR. Outcomes included time to CMV clearance, death or change in anti-CMV therapy. Cumulative incidence curves and cause-specific hazards model were used for analysis. RESULTS: In 61 analyzed patients, no differences were found between the cohorts in cumulative incidence of change in anti-CMV therapy ( P = 0.17) or death ( P = 0.69). After adjustment for multiple confounders, patients in the SCr cohort seemed to have a higher chance of CMV clearance compared with the cysC cohort, but the difference was not statistically significant (hazard ratio = 2.42, P = 0.089). Patients who received corticosteroids appeared to have lower incidence of CMV clearance ( P = 0.056). CONCLUSIONS: We did not find differences in outcomes when dosing foscarnet using cysC versus SCr for treatment of CMV infection.

Prediction of Pathologic Complete Response for Rectal Cancer Based on Pretreatment Factors Using Machine Learning.

BACKGROUND: Pathologic complete response after neoadjuvant therapy is an important prognostic indicator for locally advanced rectal cancer and may give insights into which patients might be treated nonoperatively in the future. Existing models for predicting pathologic complete response in the pretreatment setting are limited by small data sets and low accuracy. OBJECTIVE: We sought to use machine learning to develop a more generalizable predictive model for pathologic complete response for locally advanced rectal cancer. DESIGN: Patients with locally advanced rectal cancer who underwent neoadjuvant therapy followed by surgical resection were identified in the National Cancer Database from years 2010 to 2019 and were split into training, validation, and test sets. Machine learning techniques included random forest, gradient boosting, and artificial neural network. A logistic regression model was also created. Model performance was assessed using an area under the receiver operating characteristic curve. SETTINGS: This study used a national, multicenter data set. PATIENTS: Patients with locally advanced rectal cancer who underwent neoadjuvant therapy and proctectomy. MAIN OUTCOME MEASURES: Pathologic complete response defined as T0/xN0/x. RESULTS: The data set included 53,684 patients. Pathologic complete response was experienced by 22.9% of patients. Gradient boosting showed the best performance with an area under the receiver operating characteristic curve of 0.777 (95% CI, 0.773-0.781), compared with 0.684 (95% CI, 0.68-0.688) for logistic regression. The strongest predictors of pathologic complete response were no lymphovascular invasion, no perineural invasion, lower CEA, smaller size of tumor, and microsatellite stability. A concise model including the top 5 variables showed preserved performance. LIMITATIONS: The models were not externally validated. CONCLUSIONS: Machine learning techniques can be used to accurately predict pathologic complete response for locally advanced rectal cancer in the pretreatment setting. After fine-tuning a data set including patients treated nonoperatively, these models could help clinicians identify the appropriate candidates for a watch-and-wait strategy. See Video Abstract . EL CNCER DE RECTO BASADA EN FACTORES PREVIOS AL TRATAMIENTO MEDIANTE EL APRENDIZAJE AUTOMTICO: ANTECEDENTES:La respuesta patológica completa después de la terapia neoadyuvante es un indicador pronóstico importante para el cáncer de recto localmente avanzado y puede dar información sobre qué pacientes podrían ser tratados de forma no quirúrgica en el futuro. Los modelos existentes para predecir la respuesta patológica completa en el entorno previo al tratamiento están limitados por conjuntos de datos pequeños y baja precisión.OBJETIVO:Intentamos utilizar el aprendizaje automático para desarrollar un modelo predictivo más generalizable para la respuesta patológica completa para el cáncer de recto localmente avanzado.DISEÑO:Los pacientes con cáncer de recto localmente avanzado que se sometieron a terapia neoadyuvante seguida de resección quirúrgica se identificaron en la Base de Datos Nacional del Cáncer de los años 2010 a 2019 y se dividieron en conjuntos de capacitación, validación y prueba. Las técnicas de aprendizaje automático incluyeron bosque aleatorio, aumento de gradiente y red neuronal artificial. También se creó un modelo de regresión logística. El rendimiento del modelo se evaluó utilizando el área bajo la curva característica operativa del receptor.ÁMBITO:Este estudio utilizó un conjunto de datos nacional multicéntrico.PACIENTES:Pacientes con cáncer de recto localmente avanzado sometidos a terapia neoadyuvante y proctectomía.PRINCIPALES MEDIDAS DE VALORACIÓN:Respuesta patológica completa definida como T0/xN0/x.RESULTADOS:El conjunto de datos incluyó 53.684 pacientes. El 22,9% de los pacientes experimentaron una respuesta patológica completa. El refuerzo de gradiente mostró el mejor rendimiento con un área bajo la curva característica operativa del receptor de 0,777 (IC del 95%: 0,773 - 0,781), en comparación con 0,684 (IC del 95%: 0,68 - 0,688) para la regresión logística. Los predictores más fuertes de respuesta patológica completa fueron la ausencia de invasión linfovascular, la ausencia de invasión perineural, un CEA más bajo, un tamaño más pequeño del tumor y la estabilidad de los microsatélites. Un modelo conciso que incluye las cinco variables principales mostró un rendimiento preservado.LIMITACIONES:Los modelos no fueron validados externamente.CONCLUSIONES:Las técnicas de aprendizaje automático se pueden utilizar para predecir con precisión la respuesta patológica completa para el cáncer de recto localmente avanzado en el entorno previo al tratamiento. Después de realizar ajustes en un conjunto de datos que incluye pacientes tratados de forma no quirúrgica, estos modelos podrían ayudar a los médicos a identificar a los candidatos adecuados para una estrategia de observar y esperar. (Traducción-Dr. Ingrid Melo ).

Outcomes in Obese Adult Veno-Venous Extracorporeal Membrane Oxygenation: A Systematic Review.

Obesity is associated with an overall increased risk of morbidity and mortality. However, in patients with critical illness, sepsis, and acute respiratory distress syndrome, obesity may be protective, termed "the obesity paradox." This is a systematic literature review of articles published from 2000 to 2022 evaluating complications and mortality in adults with respiratory failure on veno-venous extracorporeal membrane oxygenation (VV ECMO) based on body mass index (BMI). Eighteen studies with 517 patients were included. Common complications included acute renal failure (175/377, 46.4%), venous thrombosis (175/293, 59.7%), and bleeding (28/293, 9.6%). Of the six cohort studies, two showed improved mortality among obese patients, two showed a trend toward improved mortality, and two showed no difference. Comparing all patients in the studies with BMI of less than 30 to those with BMI of greater than or equal to 30, we noted decreased mortality with obesity (92, 37.1% of BMI <30 vs. 30, 11% of BMI ≥30, p ≤ 0.0001). Obesity may be protective against mortality in adult patients undergoing VV ECMO. Morbid and super morbid obesity should not be considered a contraindication to cannulation, with patients with BMI ≥ 80 surviving to discharge. Complications may be high, however, with higher rates of continuous renal replacement therapy and thrombosis among obese patients.

Caveolin-1 promotes mitochondrial health and limits mitochondrial ROS through ROCK/AMPK regulation of basal mitophagic flux.

Caveolin-1 (CAV1), the main structural component of caveolae, is phosphorylated at tyrosine-14 (pCAV1), regulates signal transduction, mechanotransduction, and mitochondrial function, and plays contrasting roles in cancer progression. We report that CRISPR/Cas9 knockout (KO) of CAV1 increases mitochondrial oxidative phosphorylation, increases mitochondrial potential, and reduces ROS in MDA-MB-231 triple-negative breast cancer cells. Supporting a role for pCAV1, these effects are reversed upon expression of CAV1 phosphomimetic CAV1 Y14D but not non-phosphorylatable CAV1 Y14F. pCAV1 is a known effector of Rho-associated kinase (ROCK) signaling and ROCK1/2 signaling mediates CAV1 promotion of increased mitochondrial potential and decreased ROS production in MDA-MB-231 cells. CAV1/ROCK control of mitochondrial potential and ROS is caveolae-independent as similar results were observed in PC3 prostate cancer cells lacking caveolae. Increased mitochondrial health and reduced ROS in CAV1 KO MDA-MB-231 cells were reversed by knockdown of the autophagy protein ATG5, mitophagy regulator PINK1 or the mitochondrial fission protein Drp1 and therefore due to mitophagy. Use of the mitoKeima mitophagy probe confirmed that CAV1 signaling through ROCK inhibited basal mitophagic flux. Activation of AMPK, a major mitochondrial homeostasis protein inhibited by ROCK, is inhibited by CAV1-ROCK signaling and mediates the increased mitochondrial potential, decreased ROS, and decreased basal mitophagy flux observed in wild-type MDA-MB-231 cells. CAV1 regulation of mitochondrial health and ROS in cancer cells therefore occurs via ROCK-dependent inhibition of AMPK. This study therefore links pCAV1 signaling activity at the plasma membrane with its regulation of mitochondrial activity and cancer cell metabolism through control of mitophagy.

A novel multiplex biomarker panel for profiling human acute and chronic kidney disease.

Acute and chronic kidney disease continues to confer significant morbidity and mortality in the clinical setting. Despite high prevalence of these conditions, few validated biomarkers exist to predict kidney dysfunction. In this study, we utilized a novel kidney multiplex panel to measure 21 proteins in plasma and urine to characterize the spectrum of biomarker profiles in kidney disease. Blood and urine samples were obtained from age-/sex-matched healthy control subjects (HC), critically-ill COVID-19 patients with acute kidney injury (AKI), and patients with chronic or end-stage kidney disease (CKD/ESKD). Biomarkers were measured with a kidney multiplex panel, and results analyzed with conventional statistics and machine learning. Correlations were examined between biomarkers and patient clinical and laboratory variables. Median AKI subject age was 65.5 (IQR 58.5-73.0) and median CKD/ESKD age was 65.0 (IQR 50.0-71.5). Of the CKD/ESKD patients, 76.1% were on hemodialysis, 14.3% of patients had kidney transplant, and 9.5% had CKD without kidney replacement therapy. In plasma, 19 proteins were significantly different in titer between the HC versus AKI versus CKD/ESKD groups, while NAG and RBP4 were unchanged. TIMP-1 (PPV 1.0, NPV 1.0), best distinguished AKI from HC, and TFF3 (PPV 0.99, NPV 0.89) best distinguished CKD/ESKD from HC. In urine, 18 proteins were significantly different between groups except Calbindin, Osteopontin and TIMP-1. Osteoactivin (PPV 0.95, NPV 0.95) best distinguished AKI from HC, and ß2-microglobulin (PPV 0.96, NPV 0.78) best distinguished CKD/ESKD from HC. A variety of correlations were noted between patient variables and either plasma or urine biomarkers. Using a novel kidney multiplex biomarker panel, together with conventional statistics and machine learning, we identified unique biomarker profiles in the plasma and urine of patients with AKI and CKD/ESKD. We demonstrated correlations between biomarker profiles and patient clinical variables. Our exploratory study provides biomarker data for future hypothesis driven research on kidney disease.

Medication Reconciliation during Transitions of Care Across Institutions: A Quantitative Analysis of Challenges and Opportunities.

OBJECTIVE: Medication discrepancies between clinical systems may pose a patient safety hazard. In this paper, we identify challenges and quantify medication discrepancies across transitions of care. METHODS: We used structured clinical data and free-text hospital discharge summaries to compare active medications' lists at four time points: preadmission (outpatient), at-admission (inpatient), at-discharge (inpatient), and postdischarge (outpatient). Medication lists were normalized to RxNorm. RxNorm identifiers were further processed using the RxNav API to identify the ingredient. The specific drugs and ingredients from inpatient and outpatient medication lists were compared. RESULTS: Using RxNorm drugs, the median percentage intersection when comparing active medication lists within the same electronic health record system ranged between 94.1 and 100% indicating substantial overlap. Similarly, when using RxNorm ingredients the median percentage intersection was 94.1 to 100%. In contrast, the median percentage intersection when comparing active medication lists across EHR systems was significantly lower (RxNorm drugs: 6.1-7.1%; RxNorm ingredients: 29.4-35.0%) indicating that the active medication lists were significantly less similar (p < 0.05).Medication lists in the same EHR system are more similar to each other (fewer discrepancies) than medication lists in different EHR systems when comparing specific RxNorm drug and the more general RxNorm ingredients at transitions of care. Transitions of care that require interoperability between two EHR systems are associated with more discrepancies than transitions where medication changes are expected (e.g., at-admission vs. at-discharge). Challenges included lack of access to structured, standardized medication data across systems, and difficulty distinguishing medications from orderable supplies such as lancets and diabetic test strips. CONCLUSION: Despite the challenges to medication normalization, there are opportunities to identify and assist with medication reconciliation across transitions of care between institutions.

Comparison of the Effect of Corn-fermented Protein and Traditional Ingredients on the Fecal Microbiota of Dogs.

Corn-fermented protein (CFP), a co-product from the ethanol industry, is produced using post-fermentation technology to split the protein and yeast from fiber prior to drying. The objective of this study was to determine the effect of CFP compared to traditional ingredients on the fecal microbiota of dogs. The four experimental diets included a control with no yeast and diets containing either 3.5% brewer's dried yeast, 2.5% brewer's dried yeast plus 17.5% distiller's dried grains with solubles, or 17.5% CFP. The experimental diets were fed to adult dogs (n = 12) in a 4 × 4 replicated Latin square design. Fresh fecal samples (n = 48) were analyzed by 16S metagenomic sequencing. Raw sequences were processed through mothur. Community diversity was evaluated in R. Relative abundance data were analyzed within the 50 most abundant operational taxonomic units using a mixed model of SAS. Alpha and beta diversity were similar for all treatments. Predominant phyla among all samples were Firmicutes (73%), Bacteroidetes (15%), Fusobacteria (8%), and Actinobacteria (4%). There were no quantifiable (p > 0.05) shifts in the predominant phyla among the treatments. However, nine genera resulted in differences in relative abundance among the treatments. These data indicate that compared to traditional ingredients, CFP did not alter the overall diversity of the fecal microbiota of healthy adult dogs over 14 days.