to experienced clinics.

In this review article, we will highlight ethical issues faced by hematologists due to a growing constellation of expensive diagnostics and therapeutics in hematology. We outline the important issues surrounding this topic including stakeholders, cost considerations, and various ethical challenges surrounding access to care, communication about costs, and individual vs. societal responsibilities. We review available tools to navigate these ethical themes and offer potential solutions.

We identified several gaps in the literature on the topic of ethical issues in hematology treatment and supplement by non-hematological cancer and general medical literature. We propose proactive solutions to address these problems to include cost transparency, utilization of evidence-based decision making tools, application of the four quadrant approach to ethical care, and advanced systems-based practice curriculum for physician trainees.

We identified several gaps in the literature on the topic of ethical issues in hematology treatment and supplement by non-hematological cancer and general medical literature. We propose proactive solutions to address these problems to include cost transparency, utilization of evidence-based decision making tools, application of the four quadrant approach to ethical care, and advanced systems-based practice curriculum for physician trainees.

XPD Lys751Gln polymorphism may modulate inter-individual variation in repair capacity of DNA, which may enhance a person’s susceptibility to develop colorectal cancer (CRC). The analysis of XPD Lys751Gln polymorphism may provide important information for identifying high-risk individuals and for selecting the most appropriate treatment for poor prognostic CRC patients.

The overall objective was to find out the association of XPD Lys751Gln gene polymorphism with the risk of having a colorectal cancer and the ultimate clinical outcomes. In this study a total of 300 subjects (CRC and Controls), were genotyped for XPD Lys751Gln.

Using PCR-RFLP methods, the association of XPD Lys751Gln gene polymorphism with the risk of having a colorectal cancer was studied. In addition to overall risk assessment, genotyping results were also investigated with respect to the lifestyle risk factors, patients treated with oxaliplatin-based chemotherapy and clinicopathological characteristics.

The overall correlation between the XPD Lys751Gln genetic variation and the CRC risk was observed to be significant with both the homozygous variant genotype Gln/Gln as well as heterozygous genotype Lys/Gln being associated with the increased risk of CRC. Additional stratified analyses revealed that XPD Lys751Gln variants remarkably increased risk of CRC in males and younger individuals (≤ 50years), Naswar users (8.09-fold) and high intake of red meat.

Our findings suggest that the relationship between the XPD Lys751Gln variants and lifestyle factors modulates the risk for CRC in Pakistani population.

Our findings suggest that the relationship between the XPD Lys751Gln variants and lifestyle factors modulates the risk for CRC in Pakistani population.

Acinetobacter baumannii is a major opportunistic pathogen causing nosocomial infections. Acinetobacterbaumannii possesses a quorum sensing system consisting of abaI, encoding an autoinducer synthase, and abaR, encoding a putative LuxR type regulator. AbaI is required for motility and biofilm formation in A. baumannii. However, the functions of AbaR on the expression of abaI, motility, and the formation of biofilm and pellicle have not yet been explored.

The aim of this study was to investigate the effects of abaR mutation on the expression of abaI, motility, and the formation of biofilm and pellicle.

Functions of AbaR were assessed by the construction of an isogenic mutant and by evaluating the effects of abaR mutation on the expression of abaI, motility, and the formation of biofilm and pellicle.

The abaR mutant revealed a significant decrease in the expression of abaI. The disruption of abaR resulted in substantial defects in motility and the formation of biofilm and pellicle. Fluorescein isothiocyanate isomer I Introduction of abaR in trans complemented the defects.

AbaR of A. baumannii is required for the expression of abaI and plays important roles in motility and the formation of biofilm and pellicle. AbaR may be considered to be a target of anti-biofilm agents.

AbaR of A. baumannii is required for the expression of abaI and plays important roles in motility and the formation of biofilm and pellicle. AbaR may be considered to be a target of anti-biofilm agents.

Accurate prediction of postoperative remission is beneficial for effective patient-physician communication in acromegalic patients. This study aims to train and validate machine learning prediction models for early endocrine remission of acromegalic patients.

The training cohort included 833 patients with growth hormone (GH) secreting pituitary adenoma from 2010 to 2018. We trained a partial model (only using pre-operative variables) and a full model (using all variables) to predict off-medication endocrine remission at six-month follow-up after surgery using multiple algorithms. The models were validated in 99 prospectively collected patients from a second campus and 52 patients from a third institution.

C-statistic and the accuracy of the best partial model was 0.803 (95% CI 0.757-0.849) and 72.5% (95% CI 67.6-77.5%), respectively. C-statistic and the accuracy of the best full model was 0.888 (95% CI 0.861-0.914) and 80.3% (95% CI 77.5-83.1%), respectively. The c-statistics (and accuracy) of using only Knosp grade, total resection, or postoperative day 1 GH level as the single predictor were lower than our partial model or full model (p < 0.001). C-statistics remained similar in the prospective cohort (partial model 0.798, and full model 0.903) and in the external cohort (partial model 0.771, and full model 0.871). A web-based application integrated with the trained models was published at https//deepvep.shinyapps.io/Acropred/ .

We developed and validated interpretable and applicable machine learning models to predict early endocrine remission after surgical resection of a GH-secreting pituitary adenoma. Predication accuracy of the trained models were better than those using single variables.

We developed and validated interpretable and applicable machine learning models to predict early endocrine remission after surgical resection of a GH-secreting pituitary adenoma. Predication accuracy of the trained models were better than those using single variables.