Younghickman0178

system relies on fatigued physicians, particularly trainees, and provides few mechanisms to critically examine fatigue. Successful implementation of fatigue risk management in residency training may prove elusive if clinical supervisors are skeptical of the potentially negative impact of workplace fatigue.

To review our experience using sirolimus in a single center pediatric intestinal transplantation cohort.

Intestinal transplant patients with more than 3 months follow-up were divided in two groups according to their immunosuppression regimen tacrolimus, (TAC group, n=45 grafts) or sirolimus (SRL group, n=38 grafts), which included those partially or completely converted from tacrolimus to sirolimus. The indications to switch were tacrolimus side-effects and immunological complications. Survival and complications were retrospectively analyzed comparing both groups.

SRL was introduced 9 months (0 months-16.9 years) after transplant. The main cause for conversion was worsening renal function (45%), followed by hemolytic anemia (21%) and graft-versus-host-disease (16%). Both groups showed a similar overall patient/graft survival (p=0.76/0.08) and occurrence of rejection (24%/17%, p=0.36). Immunological complications did not recur after conversion. Renal function significantly improved in most SRL patients. After a median follow-up of 65.17 months, 28/46 survivors were on SRL, 26 with monotherapy, with good graft function.

Over one-third of our patients eventually required SRL conversion that allowed to improve their kidney function and immunological events, without entailing additional complications or survival impairment. Further trials are warranted to clarify the potential improvement of the standard tacrolimus maintenance by sirolimus conversion or addition.

Over one-third of our patients eventually required SRL conversion that allowed to improve their kidney function and immunological events, without entailing additional complications or survival impairment. Further trials are warranted to clarify the potential improvement of the standard tacrolimus maintenance by sirolimus conversion or addition.Bismuth (Bi) is a topological crystalline insulator (TCI), which has gapless topological surface states (TSSs) protected by a specific crystalline symmetry that strongly depends on the facet. Bi is also a promising electrochemical CO2 reduction reaction (ECO2 RR) electrocatalyst for formate production. In this study, single-crystalline Bi rhombic dodecahedrons (RDs) exposed with (104) and (110) facets are developed. The Bi RDs demonstrate a very low overpotential and high selectivity for formate production (Faradic efficiency >92.2%) in a wide partial current density range from 9.8 to 290.1 mA cm-2 , leading to a remarkably high full-cell energy efficiency (69.5%) for ECO2 RR. The significantly reduced overpotential is caused by the enhanced *OCHO adsorption on the Bi RDs. The high selectivity of formate can be ascribed to the TSSs and the trivial surface states opening small gaps in the bulk gap on Bi RDs, which strengthens and stabilizes the preferentially adsorbed *OCHO and mitigates the competing adsorption of *H during ECO2 RR. This study describes a promising application of Bi RDs for high-rate formate production and high-efficiency energy storage of intermittent renewable electricity. Optimizing the geometry of TCIs is also proposed as an effective strategy to tune the TSSs of topological catalysts.

Skin exposure to chemicals may induce an inflammatory disease known as contact dermatitis(CD). Distinguishing the allergic and irritant forms of CD often proves challenging in the clinic.

To characterize the molecular signatures of chemical-induced skin inflammation, we conducted a comprehensive transcriptomic analysis on the skin lesions of 47 patients with positive patch tests to reference contact allergens and nonallergenic irritants.

A clear segregation was observed between allergen- and irritant-induced gene profiles. Distinct modules pertaining to the epidermal compartment, metabolism, and proliferation were induced by both contact allergens and irritants; whereas only contact allergens prompted strong activation of adaptive immunity, notably of cytotoxic T-cell responses. Our results also confirmed that (a) unique pathways characterize allergen- and irritant-induced dermatitis; (b) the intensity of the clinical reaction correlates with the magnitude of immune activation. Finally, using a machine-learning approach, we identified and validated several minimal combinations of biomarkers to distinguish contact allergy from irritation.

These results highlight the value of molecular profiling of chemical-induced skin inflammation for improving the diagnosis of allergic versus irritant contact dermatitis.

These results highlight the value of molecular profiling of chemical-induced skin inflammation for improving the diagnosis of allergic versus irritant contact dermatitis.In the analysis of gene expression data, when there are two or more disease conditions/groups (e.g., diseased and normal, responder and nonresponder, and multiple stages/subtypes), differential analysis has been extensively conducted to identify key differences and has important implications. Network analysis takes a system perspective and can be more informative than that limited to simple statistics such as mean and variance. In differential network analysis, a common practice is to first estimate a gene expression network for each condition/group, and then spectral clustering can be applied to the network difference(s) to identify key genes and biological mechanisms that lead to the differences. Compared to "simple" analysis such as regression, differential network analysis can be more challenging with the significantly larger number of parameters. In this study, taking advantage of the increasing popularity of multidimensional profiling data, we develop an assisted analysis strategy and propose incorporating regulator information to improve the identification of key genes (that lead to the differences in gene expression networks). An effective computational algorithm is developed. Comprehensive simulation is conducted, showing that the proposed approach can outperform the benchmark alternatives in identification accuracy. With the The Cancer Genome Atlas lung adenocarcinoma data, we analyze the expressions of genes in the KEGG cell cycle pathway, assisted by copy number variation data. The proposed assisted analysis leads to identification results similar to the alternatives but different estimations. Overall, this study can deliver an efficient and cost-effective way of improving differential network analysis.Crystallographic B-factors provide direct dynamical information on the internal mobility of proteins that is closely linked to function, and are also widely used as a benchmark in assessing elastic network models. A significant question in the field is what is the exact amount of thermal vibrations in protein crystallographic B-factors? This work sets out to answer this question. First, we carry out a thorough, statistically sound analysis of crystallographic B-factors of over 10 000 structures. Second, by employing a highly accurate all-atom model based on the well-known CHARMM force field, we obtain computationally the magnitudes of thermal vibrations of nearly 1000 structures. Our key findings are (i) the magnitude of thermal vibrations, surprisingly, is nearly protein-independent, as a corollary to the universality for the vibrational spectra of globular proteins established earlier; (ii) the magnitude of thermal vibrations is small, less than 0.1 Å2 at 100 K; (iii) the percentage of thermal vibrations in B-factors is the lowest at low resolution and low temperature ( less then 10%) but increases to as high as 60% for structures determined at high resolution and at room temperature. The significance of this work is that it provides for the first time, using an extremely large dataset, a thorough analysis of B-factors and their thermal and static disorder components. The results clearly demonstrate that structures determined at high resolution and at room temperature have the richest dynamics information. Since such structures are relatively rare in the PDB database, the work naturally calls for more such structures to be determined experimentally.

After local excision of early rectal cancer, definitive lymph node status is not available. Selleckchem TDI-011536 An alternative means for accurate assessment of recurrence risk is required to determine the most appropriate subsequent management. Currently used measures are suboptimal. We assess three measures of tumour stromal content to determine their predictive value after local excision in a well-characterized cohort of rectal cancer patients without prior radiotherapy.

143 patients were included. H&E sections were scanned for 1) deep neural network (DNN, a machine learning algorithm) tumour segmentation into compartments including desmoplastic stroma and inflamed stroma; and 2) digital assessment of tumour stromal fraction (TSR) and optical DNA ploidy analysis. 3' mRNA sequencing was performed to obtain gene expression data, from which stromal and immune scores were calculated using the ESTIMATE method. Full results were available for 139 samples and compared with disease-free survival. All three methods were prognostic. Most strongly predictive was a DNN-determined ratio of desmoplastic to inflamed stroma >5.41 (p<0.0001). A ratio of ESTIMATE stromal to immune score <1.19 was also predictive of disease-free survival (p=0.00051), as was stromal fraction >36.5% (p=0.037).

The DNN-determined ratio of desmoplastic to inflamed ratio is a novel and powerful predictor of disease recurrence in locally excised early rectal cancer. It can be assessed on a single H&E section so could be applied in routine clinical practice to improve the prognostic information available to patients and clinicians to inform the decision about further management.

The DNN-determined ratio of desmoplastic to inflamed ratio is a novel and powerful predictor of disease recurrence in locally excised early rectal cancer. It can be assessed on a single H&E section so could be applied in routine clinical practice to improve the prognostic information available to patients and clinicians to inform the decision about further management.

Increasing the number of physicians who identify as an underrepresented minority (URM) has been a focus for decades. Despite the US Department of Health and Human Services establishing The Council on Graduate Medical Education focussing on the underrepresentation of minorities in medicine in 1990, US medical students in 1998-1999 were15.2% URM and twenty years later, URM students comprise only 14.6% of matriculants. This reflected our experience at University of Maryland School of Medicine despite our diverse community where over 60% of the population identify as Black or African-American. We share our strategies to mitigate bias in the admissions process and our resulting outcomes.

We implemented multiple interventions including interviewer training, recruitment strategies, holistic screening, changes in the interview process and increased racial, ethnic and gender diversity on our admissions committee. These changes were made over a two-year period initially focussing on the committee, followed by focussed interventions for interviewers.