The Use of Putative Dialysis Initiation Time in Comparative Outcomes of Patients with Advanced Chronic Kidney Disease: Methodological Aspects

The latest data from the United States Renal Data Systems show over 134,000 individuals with end-stage kidney disease (ESKD) starting dialysis in the year 2019. ESKD patients on dialysis, the default treatment strategy, have high mortality and hospitalization, especially in the first year of dialysis. An alternative treatment strategy is (non-dialysis) conservative management (CM). The relative effectiveness of CM with respect to various patient outcomes, including survival, hospitalization, and health-related quality of life among others, especially in elderly ESKD or advanced chronic kidney disease patients with serious comorbidities, is an active area of research. A technical challenge inherent in comparing patient outcomes between CM and dialysis patient groups is that the start of follow-up time is “not defined” for patients on CM because they do not initiate dialysis. One solution is the use of putative dialysis initiation (PDI) time. In this work, we examine the validity of the use of PDI time to determine the start of follow-up for longitudinal retrospective and prospective cohort studies involving CM. We propose and assess the efficacy of estimating PDI time using linear mixed effects model of kidney function decline over time via simulation studies. We also illustrate how the estimated PDI time can be used to effectively estimate the survival distribution

High-Dimensional Fixed Effects Profiling Models and Applications in End-Stage Kidney Disease Patients: Current State and Future Directions

Profiling analysis aims to evaluate health care providers, including hospitals, nursing homes, or dialysis facilities among others with respect to a patient outcome, such as 30-day unplanned hospital readmission or mortality. Fixed effects (FE) profiling models have been developed over the last decade, motivated by the overall need to (a) improve accurate identification or “flagging” of under-performing providers, (b) relax assumptions inherent in random effects (RE) profiling models, and (c) take into consideration the unique disease characteristics and care/treatment processes of end-stage kidney disease (ESKD) patients on dialysis. In this paper, we review the current state of FE methodologies and their rationale in the ESKD population and illustrate applications in four key areas: profiling dialysis facilities for (1) patient hospitalizations over time (longitudinally) using standardized dynamic readmission ratio (SDRR), (2) identification of dialysis facility characteristics (e.g., staffing level) that contribute to hospital readmission, and (3) adverse recurrent events using standardized event ratio (SER). Also, we examine the operating characteristics with a focus on FE profiling models. Throughout these areas of applications to the ESKD population, we identify challenges for future research in both methodology and clinical studies

Association of US Dialysis Facility Staffing with Profiling of Hospital-Wide 30-Day Unplanned Readmission.

Background:Unplanned hospital readmissions are a major source of morbidity among dialysis patients, in whom the risk of hospital readmission is exceptionally high. The contribution of dialysis facility staffing to hospital readmission has been largely overlooked. Methods:Using annual data of dialysis patients from the United States Renal Data System from 2010 to 2013, we assessed dialysis facilities with a significantly worse (SW) and facilities with a nonsignificant (NS) standardized readmission ratio (SRR). SRR estimates were risk adjusted for patient factors, past year comorbidities, and index hospitalization characteristics. Facility staffing variables were compared between 2 exposure groups: facilities with SW and NS SRRs. Four measures of staffing, including patient-to-staffing ratio, were compared between SW and matched NS facilities. Results:About 136,000-148,000 dialysis patients with 269,000-319,000 index hospital discharges were used to identify facilities with SW and facilities with NS SRR annually. Approximately 3-4% of facilities were identified as having SW SRR among > 5,000 facilities annually. The percent of nurses-to-total staff was significantly lower in 2010 for SW facilities than in matched NS facilities (42.5 vs. 45.6%, p = 0.012), but this disparity was attenuated by 2013 (44.8 vs. 44.7%, p = 0.949). There was a higher patient-to-nurse ratio for SW facilities than for NS facilities (mean 16.4 vs. 15.2, p = 0.038) in 2010 as well, and the disparity was reduced by 2013. The trends were similar for patient-to-total staff and patient-to-registered nurse, but not statistically significant. Conclusions:This study found that dialysis facilities with SW 30-day readmission rates had lower proportions of nurses-to-total staff and higher patient-to-nurse ratios, but this disparity improved in recent years. Additional research is warranted focusing on how evidence-based staffing at dialysis facilities can contribute to reduction of hospital readmission, and this knowledge is needed to inform clinical practice guidelines and policy decisions regarding optimal dialysis patient staffing

Canonical Wnt signaling is antagonized by noncanonical Wnt5a in hepatocellular carcinoma cells

<p>Abstract</p> <p>Background</p> <p>β-catenin mutations that constitutively activate the canonical Wnt signaling have been observed in a subset of hepatocellular carcinomas (HCCs). These mutations are associated with chromosomal stability, low histological grade, low tumor invasion and better patient survival. We hypothesized that canonical Wnt signaling is selectively activated in well-differentiated, but repressed in poorly differentiated HCCs. To this aim, we characterized differentiation status of HCC cell lines and compared their expression status of Wnt pathway genes, and explored their activity of canonical Wnt signaling.</p> <p>Results</p> <p>We classified human HCC cell lines into "well-differentiated" and "poorly differentiated" subtypes, based on the expression of hepatocyte lineage, epithelial and mesenchymal markers. Poorly differentiated cell lines lost epithelial and hepatocyte lineage markers, and overexpressed mesenchymal markers. Also, they were highly motile and invasive. We compared the expression of 45 Wnt pathway genes between two subtypes. TCF1 and TCF4 factors, and LRP5 and LRP6 co-receptors were ubiquitously expressed. Likewise, six Frizzled receptors, and canonical Wnt3 ligand were expressed in both subtypes. In contrast, canonical ligand Wnt8b and noncanonical ligands Wnt4, Wnt5a, Wnt5b and Wnt7b were expressed selectively in well- and poorly differentiated cell lines, respectively. Canonical Wnt signaling activity, as tested by a TCF reporter assay was detected in 80% of well-differentiated, contrary to 14% of poorly differentiated cell lines. TCF activity generated by ectopic mutant β-catenin was weak in poorly differentiated SNU449 cell line, suggesting a repressive mechanism. We tested Wnt5a as a candidate antagonist. It strongly inhibited canonical Wnt signaling that is activated by mutant β-catenin in HCC cell lines.</p> <p>Conclusion</p> <p>Differential expression of Wnt ligands in HCC cells is associated with selective activation of canonical Wnt signaling in well-differentiated, and its repression in poorly differentiated cell lines. One potential mechanism of repression involved Wnt5a, acting as an antagonist of canonical Wnt signaling. Our observations support the hypothesis that Wnt pathway is selectively activated or repressed depending on differentiation status of HCC cells. We propose that canonical and noncanonical Wnt pathways have complementary roles in HCC, where the canonical signaling contributes to tumor initiation, and noncanonical signaling to tumor progression.</p

Prevalence, characterization and antibiotic resistance of enterococci from traditional cheeses in Turkey

The aim of the present work is to provide information about Enterococcus strains isolated from traditional Turkish cheese samples in Ankara (Turkey), focusing on their prevalence, phenotypic and genotypic characteristics, and antibiotic resistance. A total of 213 probable enterococcal isolates isolated from 215 samples were identified by phenotypic and genotypic methods. As a result of 16S rDNA sequence analysis, 88 of the 213 enterococci strains were identified as Enterococcus faecium and 125 as Enterococcus faecalis. The E. faecalis strains (58.7%) were identified as the dominant species isolated from cheese samples in Turkey. The 213 Enterococcus strains were tested for susceptibility to 12 different antimicrobial agents. The resistance phenotype were as follow: nalidixic acid (100%), kanamycin (98.6%), rifampicin (78.4%), ampicillin (48.8%), ciprofloxacin (45.5%), erythromycin (18.8%), tetracycline (11.7%), penicillin G (5.6%), chloramphenicol (4.2%), gentamycin (3.8%) and streptomycin (1.4%). None of the strains was resistant to vancomycin. E. faecium strains showed more resistant phenotypes than E. faecalis strains as shown by the antibiotic resistance levels. It was also observed that the resistance of E. faecium and E. faecalis strains against the antibiotics was statistically significant (p ˂ 0.05). In total, 100% of E. faecium and 88.8% of E. faecalis strains were resistant to multiple drugs

Elements of Hard Landscape Design and New Approaches on Their Use

Aim of study: The objective of the research is classification of hard landscape design materials and reveal the new approaches in their usage

The Use of Putative Dialysis Initiation Time in Comparative Outcomes of Patients with Advanced Chronic Kidney Disease: Methodological Aspects.

The latest data from the United States Renal Data Systems show over 134,000 individuals with end-stage kidney disease (ESKD) starting dialysis in the year 2019. ESKD patients on dialysis, the default treatment strategy, have high mortality and hospitalization, especially in the first year of dialysis. An alternative treatment strategy is (non-dialysis) conservative management (CM). The relative effectiveness of CM with respect to various patient outcomes, including survival, hospitalization, and health-related quality of life among others, especially in elderly ESKD or advanced chronic kidney disease patients with serious comorbidities, is an active area of research. A technical challenge inherent in comparing patient outcomes between CM and dialysis patient groups is that the start of follow-up time is "not defined" for patients on CM because they do not initiate dialysis. One solution is the use of putative dialysis initiation (PDI) time. In this work, we examine the validity of the use of PDI time to determine the start of follow-up for longitudinal retrospective and prospective cohort studies involving CM. We propose and assess the efficacy of estimating PDI time using linear mixed effects model of kidney function decline over time via simulation studies. We also illustrate how the estimated PDI time can be used to effectively estimate the survival distribution

Wild-type IDH1 Knockout Leads to G0/G1 Arrest, Impairs Cancer Cell Proliferation, Altering Glycolysis, and the TCA Cycle in Colon Cancer

The isocitrate dehydrogenase (IDH), which participates in the TCA cycle, is an important key enzyme in regulating cell metabolism. The effect of the metabolic IDH enzyme on cancer pathogenesis has recently been shown in different types of cancer. However, the role of wild-type (wt) IDH1 in the development of colon cancer is still unknown. Our study investigated the role of the IDH1 enzyme in key hallmarks of colon cancer using various methods such as wound healing, cell cycle, colony formation ability, invasion, and apoptosis analysis. Furthermore, cell metabolism was investigated by pyruvate analysis, dinitrosalicylic acid, and HPLC methods. In addition, CRISPR/Cas9 tool was utilized to knockout the IDH1 gene in colon adenocarcinoma cells (SW620). Further studies were performed in two isogenic IDH1 KO clones. Our findings in both clones suggest that IDH1 KO results in G0/G1 arrest, and reduces proliferation by approximately twofold compared to IDH1 WT cells. In addition, the invasion, migration, and colony formation abilities of IDH1 KO clones were significantly decreased accompanied by significant morphological changes. In the context of metabolism, intracellular glucose, pyruvate, alpha KG, and malate levels were decreased, while the intracellular citrate level was increased in IDH1 KO clones as compared to IDH1 WT cells. Our results reveal that wt IDH1 knockout leads to a decrease in the aggressive features of colon cancer cells. In conclusion, we reported that wt IDH1 has an effective role in colon cancer progression and could be a potential therapeutic target

Pre-Treatment and Post-Treatment Demodex Densities in Patients under Immunosuppressive Treatments

Background and Objectives: Demodex species are common obligatory parasites and normally present in low number in human beings. Immunosuppression was suggested to be associated with increased density of Demodex mites. Systemic glucocorticoids, cyclosporine, methotrexate, and azathioprine are commonly used immunosuppressive agents. We aim to determine the pre- and post-treatment Demodex densities in patients receiving immunosuppressive therapy and compare with those of healthy subjects. Materials and Methods: Demodex density was investigated at the beginning, first, and third months of the immunosuppressive therapy in 45 patients who received methotrexate, cyclosporine, systemic steroid, or azathioprine treatments and in 45 healthy subjects at the same time as the patients. Five standardized skin surface biopsies were taken from cheeks, forehead, nose, and chin of the patients and control group. The presence of five or more parasites in 1 cm2 area was considered as positive. Results: Demodex test was negative at the beginning of the treatment in all patients. Demodex test was positive in one patient in the first and third months of treatment and in three patients only in the third month of treatment. In the control group, Demodex test was determined as positive in just one healthy individual at the beginning, first and third months of the study. When the patient and control groups were evaluated in terms of Demodex number, there was a statistically significant difference in Demodex density in patients treated with immunosuppressive treatment in the first and third months when compared with the control group (p &lt; 0.05). Conclusion: Immunosuppressive treatment might increase the number of Demodex mites and demodicidosis should be kept in mind in patients on immunosuppressive treatment