From Bench to Bedside: Clinical and Biomedical Investigations on Hepatitis C Virus (HCV) Genotypes and Risk Factors for Albuminuria.

An extrahepatic manifestation of nephropathies can be a feature of the chronic hepatitis C virus (HCV) infection. Albuminuria is a major risk factor for nephropathies and chronic kidney disease (CKD). The correlation between HCV genotypes and albuminuria is still unclear. In this study, investigations have been done for the biomedical tools and methodologies used in the National Health and Nutrition Examination Survey (NHANES) public database. We searched the 2007−2016 NHANES public database to retrieve data regarding the different HCV genotypes and clinical scenarios. This study attempted to investigate the impacts of HCV genetic diversity, associated comorbidities, and racial differences on albuminuria. The urine albumin/creatinine ratio (ACR) was the primary endpoint. Among 40,856 participants, 336 participants with positive and 237 with negative HCV RNA tests were analyzed, excluding 14,454 participants with negative HCV antibodies and 25,828 which were missed. After controlling for sex, race, education level, smoking, diabetes mellitus, hepatitis B, alcohol use, and body mass index (BMI) with a generalized linear equation, HCV genotype 2 was more likely than any other genotype to cause albuminuria based on the urine ACR (p < 0.001). The generalized linear equation also demonstrated a significantly higher urine ACR, including hepatitis B (p < 0.001), diabetes mellitus (p < 0.001), and smoking (p = 0.026). In summary, the patients with HCV genotype 2 presented with increased albuminuria in comparison with other HCV genotypes in this 10-year retrospective analysis. HCV infection could be a risk factor of CKD; early diagnosis and appropriate treatment may improve clinical outcomes.

Genetic co-expression networks contribute to creating predictive model and exploring novel biomarkers for the prognosis of breast cancer.

Genetic co-expression network (GCN) analysis augments the understanding of breast cancer (BC). We aimed to propose GCN-based modeling for BC relapse-free survival (RFS) prediction and to discover novel biomarkers. We used GCN and Cox proportional hazard regression to create various prediction models using mRNA microarray of 920 tumors and conduct external validation using independent data of 1056 tumors. GCNs of 34 identified candidate genes were plotted in various sizes. Compared to the reference model, the genetic predictors selected from bigger GCNs composed better prediction models. The prediction accuracy and AUC of 3 ~ 15-year RFS are 71.0-81.4% and 74.6-78% respectively (rfm, ACC 63.2-65.5%, AUC 61.9-74.9%). The hazard ratios of risk scores of developing relapse ranged from 1.89 ~ 3.32 (p < 10-8) over all models under the control of the node status. External validation showed the consistent finding. We found top 12 co-expressed genes are relative new or novel biomarkers that have not been explored in BC prognosis or other cancers until this decade. GCN-based modeling creates better prediction models and facilitates novel genes exploration on BC prognosis.

Usability of Wearable Devices With a Novel Cardiac Force Index for Estimating the Dynamic Cardiac Function: Observational Study.

BACKGROUND: Long-distance running can be a form of stress to the heart. Technological improvements combined with the public's gradual turn toward mobile health (mHealth), self-health, and exercise effectiveness have resulted in the widespread use of wearable exercise products. The monitoring of dynamic cardiac function changes during running and running performance should be further studied. OBJECTIVE: We investigated the relationship between dynamic cardiac function changes and finish time for 3000-meter runs. Using a wearable device based on a novel cardiac force index (CFI), we explored potential correlations among 3000-meter runners with stronger and weaker cardiac functions during running. METHODS: This study used the American product BioHarness 3.0 (Zephyr Technology Corporation), which can measure basic physiological parameters including heart rate, respiratory rate, temperature, maximum oxygen consumption, and activity. We investigated the correlations among new physiological parameters, including CFI = weight * activity / heart rate, cardiac force ratio (CFR) = CFI of running / CFI of walking, and finish times for 3000-meter runs. RESULTS: The results showed that waist circumference, smoking, and CFI were the significant factors for qualifying in the 3000-meter run. The prediction model was as follows: ln (3000 meters running performance pass probability / fail results probability) = -2.702 - 0.096 × [waist circumference] - 1.827 × [smoke] + 0.020 × [ACi7]. If smoking and the ACi7 were controlled, contestants with a larger waist circumference tended to fail the qualification based on the formula above. If waist circumference and ACi7 were controlled, smokers tended to fail more often than nonsmokers. Finally, we investigated a new calculation method for monitoring cardiac status during exercise that uses the CFI of walking for the runner as a reference to obtain the ratio between the cardiac force of exercise and that of walking (CFR) to provide a standard for determining if the heart is capable of exercise. A relationship is documented between the CFR and the performance of 3000-meter runs in a healthy 22-year-old person. During the running period, data are obtained while participant slowly runs 3000 meters, and the relationship between the CFR and time is plotted. The runner's CFR varies with changes in activity. Since the runner's acceleration increases, the CFR quickly increases to an explosive peak, indicating the runner's explosive power. At this period, the CFI revealed a 3-fold increase (CFR=3) in a strong heart. After a time lapse, the CFR is approximately 2.5 during an endurance period until finishing the 3000-meter run. Similar correlation is found in a runner with a weak heart, with the CFR at the beginning period being 4 and approximately 2.5 thereafter. CONCLUSIONS: In conclusion, the study results suggested that measuring the real-time CFR changes could be used in a prediction model for 3000-meter running performance.

Six novel immunoglobulin genes as biomarkers for better prognosis in triple-negative breast cancer by gene co-expression network analysis.

Gene co-expression network analysis (GCNA) can detect alterations in regulatory activities in case/control comparisons. We propose a framework to detect novel genes and networks for predicting breast cancer recurrence. Thirty-four prognosis candidate genes were selected based on a literature review. Four Gene Expression Omnibus Series (GSE) microarray datasets (n = 920) were used to create gene co-expression networks based on these candidates. We applied the framework to four comparison groups according to node (+/-) and recurrence (+/-). We identified a sub-network containing two candidate genes (LST1 and IGHM) and six novel genes (IGHA1, IGHD, IGHG1, IGHG3, IGLC2, and IGLJ3) related to B cell-specific immunoglobulin. These novel genes were correlated with recurrence under the control of node status and were found to function as tumor suppressors; higher mRNA expression indicated a lower risk of recurrence (hazard ratio, HR = 0.87, p = 0.001). We created an immune index score by performing principle component analysis and divided the genes into low and high groups. This discrete index significantly predicted relapse-free survival (RFS) (high: HR = 0.77, p = 0.019; low: control). Public tool KM Plotter and TCGA-BRCA gene expression data were used to validate. We confirmed these genes are correlated with RFS and distal metastasis-free survival (DMFS) in triple-negative breast cancer (TNBC) and general breast cancer.

Albuminuria and neck circumference are determinate factors of successful accurate estimation of glomerular filtration rate in high cardiovascular risk patients.

BACKGROUND: Estimated glomerular filtration rate (eGFR) is used for diagnosis of chronic kidney disease (CKD). The eGFR models based on serum creatinine or cystatin C are used more in clinical practice. Albuminuria and neck circumference are associated with CKD and may have correlations with eGFR. AIM: We explored the correlations and modelling formulates among various indicators such as serum creatinine, cystatin C, albuminuria, and neck circumference for eGFR. DESIGN: Cross-sectional study. METHODS: We reviewed the records of patients with high cardiovascular risk from 2010 to 2011 in Taiwan. 24-hour urine creatinine clearance was used as the standard. We utilized a decision tree to select for variables and adopted a stepwise regression method to generate five models. Model 1 was based on only serum creatinine and was adjusted for age and gender. Model 2 added serum cystatin C, models 3 and 4 added albuminuria and neck circumference, respectively. Model 5 simultaneously added both albuminuria and neck circumference. RESULTS: Total 177 patients were recruited in this study. In model 1, the bias was 2.01 and its precision was 14.04. In model 2, the bias was reduced to 1.86 with a precision of 13.48. The bias of model 3 was 1.49 with a precision of 12.89, and the bias for model 4 was 1.74 with a precision of 12.97. In model 5, the bias could be lower to 1.40 with a precision of 12.53. CONCLUSIONS: In this study, the predicting ability of eGFR was improved after the addition of serum cystatin C compared to serum creatinine alone. The bias was more significantly reduced by the calculation of albuminuria. Furthermore, the model generated by combined albuminuria and neck circumference could provide the best eGFR predictions among these five eGFR models. Neck circumference can be investigated potentially in the further studies.

Risk analysis of colorectal cancer incidence by gene expression analysis.

BACKGROUND: Colorectal cancer (CRC) is one of the leading cancers worldwide. Several studies have performed microarray data analyses for cancer classification and prognostic analyses. Microarray assays also enable the identification of gene signatures for molecular characterization and treatment prediction. OBJECTIVE: Microarray gene expression data from the online Gene Expression Omnibus (GEO) database were used to to distinguish colorectal cancer from normal colon tissue samples. METHODS: We collected microarray data from the GEO database to establish colorectal cancer microarray gene expression datasets for a combined analysis. Using the Prediction Analysis for Microarrays (PAM) method and the GSEA MSigDB resource, we analyzed the 14,698 genes that were identified through an examination of their expression values between normal and tumor tissues. RESULTS: Ten genes (ABCG2, AQP8, SPIB, CA7, CLDN8, SCNN1B, SLC30A10, CD177, PADI2, and TGFBI) were found to be good indicators of the candidate genes that correlate with CRC. From these selected genes, an average of six significant genes were obtained using the PAM method, with an accuracy rate of 95%. The results demonstrate the potential of utilizing a model with the PAM method for data mining. After a detailed review of the published reports, the results confirmed that the screened candidate genes are good indicators for cancer risk analysis using the PAM method. CONCLUSIONS: Six genes were selected with 95% accuracy to effectively classify normal and colorectal cancer tissues. We hope that these results will provide the basis for new research projects in clinical practice that aim to rapidly assess colorectal cancer risk using microarray gene expression analysis.

Verification of gene expression profiles for colorectal cancer using 12 internet public microarray datasets.

AIM: To verify gene expression profiles for colorectal cancer using 12 internet public microarray datasets. METHODS: Logistic regression analysis was performed, and odds ratios for each gene were determined between colorectal cancer (CRC) and controls. Twelve public microarray datasets of GSE 4107, 4183, 8671, 9348, 10961, 13067, 13294, 13471, 14333, 15960, 17538, and 18105, which included 519 cases of adenocarcinoma and 88 normal mucosa controls, were pooled and used to verify 17 selective genes from 3 published studies and estimate the external generality. RESULTS: We validated the 17 CRC-associated genes from studies by Chang et al (Model 1: 5 genes), Marshall et al (Model 2: 7 genes) and Han et al (Model 3: 5 genes) and performed the multivariate logistic regression analysis using the pooled 12 public microarray datasets as well as the external validation. The goodness-of-fit test of Hosmer-Lemeshow (H-L) showed statistical significance (P = 0.044) for Model 2 of Marshall et al in which observed event rates did not match expected event rates in subgroups of the model population. Expected and observed event rates in subgroups were similar, which are called well calibrated, in Models 1, 3 and 4 with non-significant P values of 0.460, 0.194 and 1.000 for H-L tests, respectively. A 7-gene model of CPEB4, EIF2S3, MGC20553, MS4A1, ANXA3, TNFAIP6 and IL2RB was pairwise selected, which showed the best results in logistic regression analysis (H-L P = 1.000, R (2) = 0.951, areas under the curve = 0.999, accuracy = 0.968, specificity = 0.966 and sensitivity = 0.994). CONCLUSION: A novel gene expression profile was associated with CRC and can potentially be applied to blood-based detection assays.

Gene expression profile of peripheral blood in colorectal cancer.

AIM: Optimal molecular markers for detecting colorectal cancer (CRC) in a blood-based assay were evaluated. METHODS: A matched (by variables of age and sex) case-control design (111 CRC and 227 non-cancer samples) was applied. Total RNAs isolated from the 338 blood samples were reverse-transcribed, and the relative transcript levels of candidate genes were analyzed. The training set was made of 162 random samples of the total 338 samples. A logistic regression analysis was performed, and odds ratios for each gene were determined between CRC and non-cancer. The samples (n = 176) in the testing set were used to validate the logistic model, and an inferred performance (generality) was verified. By pooling 12 public microarray datasets(GSE 4107, 4183, 8671, 9348, 10961, 13067, 13294, 13471, 14333, 15960, 17538, and 18105), which included 519 cases of adenocarcinoma and 88 controls of normal mucosa, we were able to verify the selected genes from logistic models and estimate their external generality. RESULTS: The logistic regression analysis resulted in the selection of five significant genes (P < 0.05; MDM2, DUSP6, CPEB4, MMD, and EIF2S3), with odds ratios of 2.978, 6.029, 3.776, 0.538 and 0.138, respectively. The five-gene model performed stably for the discrimination of CRC cases from controls in the training set, with accuracies ranging from 73.9% to 87.0%, a sensitivity of 95% and a specificity of 95%. In addition, a good performance in the test set was obtained using the discrimination model, providing 83.5% accuracy, 66.0% sensitivity, 92.0% specificity, a positive predictive value of 89.2% and a negative predictive value of 73.0%. Multivariate logistic regressions analyzed 12 pooled public microarray data sets as an external validation. Models that provided similar expected and observed event rates in subgroups were termed well calibrated. A model in which MDM2, DUSP6, CPEB4, MMD, and EIF2S3 were selected showed the result in logistic regression analysis (H-L P = 0.460, R2= 0.853, AUC = 0.978, accuracy = 0.949, specificity = 0.818 and sensitivity = 0.971). CONCLUSION: A novel gene expression profile was associated with CRC and can potentially be applied to blood-based detection assays.

Gene expression profiling of colorectal tumors and normal mucosa by microarrays meta-analysis using prediction analysis of microarray, artificial neural network, classification, and regression trees.

BACKGROUND: Microarray technology shows great potential but previous studies were limited by small number of samples in the colorectal cancer (CRC) research. The aims of this study are to investigate gene expression profile of CRCs by pooling cDNA microarrays using PAM, ANN, and decision trees (CART and C5.0). METHODS: Pooled 16 datasets contained 88 normal mucosal tissues and 1186 CRCs. PAM was performed to identify significant expressed genes in CRCs and models of PAM, ANN, CART, and C5.0 were constructed for screening candidate genes via ranking gene order of significances. RESULTS: The first screening identified 55 genes. The test accuracy of each model was over 0.97 averagely. Less than eight genes achieve excellent classification accuracy. Combining the results of four models, we found the top eight differential genes in CRCs; suppressor genes, CA7, SPIB, GUCA2B, AQP8, IL6R and CWH43; oncogenes, SPP1 and TCN1. Genes of higher significances showed lower variation in rank ordering by different methods. CONCLUSION: We adopted a two-tier genetic screen, which not only reduced the number of candidate genes but also yielded good accuracy (nearly 100%). This method can be applied to future studies. Among the top eight genes, CA7, TCN1, and CWH43 have not been reported to be related to CRC.

Systematic review and meta-analysis of nonpharmacological interventions for fatigue in children and adolescents with cancer.

BACKGROUND: Fatigue is one of the most distressing and prevalent symptoms reported by pediatric oncology patients. With the increase in cancer survival rates, medical teams have focused on methods that control cancer-related fatigue in children during the disease and its treatment in order to increase the quality of life for these patients. AIM: The objective of this systematic review was to synthesize the best available evidence concerning the effectiveness of nonpharmacological interventions for fatigue in children and adolescents with cancer. METHODS: The search strategy was designed to retrieve studies published between 1960 and 2010 in either English or Chinese. This review included randomized controlled trials and quasi-experimental studies. The studies that were selected for retrieval were assessed by two independent reviewers for methodological validity prior to inclusion in the review using standardized critical-appraisal instruments. RESULTS: The review included six studies, and the meta-analysis revealed a statistically significant effect of exercise interventions in reducing general fatigue (effect size = -0.76; 95% CI [-1.35, -0.17]) in children and adolescents with cancer. CONCLUSIONS AND IMPLICATIONS: The review provides an evidence-based guide to future priorities for clinical practice. Exercise interventions could reduce the levels of general fatigue in children aged 6-18 years. In particular, exercise interventions for fatigue are feasible and safe.

Gene expression profiling of breast cancer survivability by pooled cDNA microarray analysis using logistic regression, artificial neural networks and decision trees.

BACKGROUND: Microarray technology can acquire information about thousands of genes simultaneously. We analyzed published breast cancer microarray databases to predict five-year recurrence and compared the performance of three data mining algorithms of artificial neural networks (ANN), decision trees (DT) and logistic regression (LR) and two composite models of DT-ANN and DT-LR. The collection of microarray datasets from the Gene Expression Omnibus, four breast cancer datasets were pooled for predicting five-year breast cancer relapse. After data compilation, 757 subjects, 5 clinical variables and 13,452 genetic variables were aggregated. The bootstrap method, Mann-Whitney U test and 20-fold cross-validation were performed to investigate candidate genes with 100 most-significant p-values. The predictive powers of DT, LR and ANN models were assessed using accuracy and the area under ROC curve. The associated genes were evaluated using Cox regression. RESULTS: The DT models exhibited the lowest predictive power and the poorest extrapolation when applied to the test samples. The ANN models displayed the best predictive power and showed the best extrapolation. The 21 most-associated genes, as determined by integration of each model, were analyzed using Cox regression with a 3.53-fold (95% CI: 2.24-5.58) increased risk of breast cancer five-year recurrence. CONCLUSIONS: The 21 selected genes can predict breast cancer recurrence. Among these genes, CCNB1, PLK1 and TOP2A are in the cell cycle G2/M DNA damage checkpoint pathway. Oncologists can offer the genetic information for patients when understanding the gene expression profiles on breast cancer recurrence.

Androgenic alopecia is associated with less dietary soy, lower [corrected] blood vanadium and rs1160312 1 polymorphism in Taiwanese communities.

BACKGROUND: Although the genetic basis of androgenic alopecia has been clearly established, little is known about its non-genetic causes, such as environmental and lifestyle factors. OBJECTIVE: This study investigated blood and urine heavy metals concentrations, environmental exposure factors, personal behaviors, dietary intakes and the genotypes of related susceptibility genes in patients with androgenic alopecia (AGA). DESIGN: Age, AGA level, residence area, work hours, sleep patterns, cigarette usage, alcohol consumption, betel nut usage, hair treatments, eating habits, body heavy metals concentrations and rs1998076, rs913063, rs1160312 and rs201571 SNP genotype data were collected from 354 men. Logistic regression analysis was performed to examine whether any of the factors displayed odds ratios (ORs) indicating association with moderate to severe AGA (≥ IV). Subsequently, Hosmer-Lemeshow, Nagelkerke R(2) and accuracy tests were conducted to help establish an optimal model. RESULTS: Moderate to severe AGA was associated with the AA genotype of rs1160312 (22.50, 95% CI 3.99-126.83), blood vanadium concentration (0.02, 95% CI 0.01-0.04), and regular consumption of soy bean drinks (0.23, 95% CI 0.06-0.85), after adjustment for age. The results were corroborated by the Hosmer-Lemeshow test (P = 0.73), Nagelkerke R(2) (0.59), accuracy test (0.816) and area under the curve (AUC; 0.90, 0.847-0.951) analysis. CONCLUSIONS: Blood vanadium and frequent soy bean drink consumption may provide protect effects against AGA. Accordingly, blood vanadium concentrations, the AA genotype of rs1160312 and frequent consumption of soy bean drinks are associated with AGA.

Impaired natural killer cell phenotype and function in idiopathic and heritable pulmonary arterial hypertension.

BACKGROUND: Beyond their role as innate immune effectors, natural killer (NK) cells are emerging as important regulators of angiogenesis and vascular remodeling. Pulmonary arterial hypertension (PAH) is characterized by severe pulmonary vascular remodeling and has long been associated with immune dysfunction. Despite this association, a role for NK cells in disease pathology has not yet been described. METHODS AND RESULTS: Analysis of whole blood lymphocytes and isolated NK cells from PAH patients revealed an expansion of the functionally defective CD56(-)/CD16(+) NK subset that was not observed in patients with chronic thromboembolic pulmonary hypertension. NK cells from PAH patients also displayed decreased levels of the activating receptor NKp46 and the killer immunoglobulin-like receptors 2DL1/S1 and 3DL1, reduced secretion of the cytokine macrophage inflammatory protein-1ß, and a significant impairment in cytolytic function associated with decreased killer immunoglobulin-like receptor 3DL1 expression. Genotyping patients (n=222) and controls (n=191) for killer immunoglobulin-like receptor gene polymorphisms did not explain these observations. Rather, we show that NK cells from PAH patients exhibit increased responsiveness to transforming growth factor-ß, which specifically downregulates disease-associated killer immunoglobulin-like receptors. NK cell number and cytotoxicity were similarly decreased in the monocrotaline rat and chronic hypoxia mouse models of PAH, accompanied by reduced production of interferon-γ in NK cells from hypoxic mice. NK cells from PAH patients also produced elevated quantities of matrix metalloproteinase 9, consistent with a capacity to influence vascular remodeling. CONCLUSIONS: Our work is the first to identify an impairment of NK cells in PAH and suggests a novel and substantive role for innate immunity in the pathobiology of this disease.

The effectiveness of non-pharmacological interventions on fatigue in children and adolescents with cancer: a systematic review.

BACKGROUND: Fatigue is one of the most distressing and prevalent symptoms reported by paediatric oncology patients. With the increase in cancer survival rate, how to control children's cancer-related fatigue during treatments or the coexisting period with the disease to further increase their quality of life has become the focus of medical teams who provide care to children with cancer. OBJECTIVES: The objective of this systematic review was to synthesise the best available evidence concerning the effectiveness of non-pharmacological interventions on fatigue in children and adolescents with cancer. SEARCH STRATEGY: The search strategy aimed to find studies published between 1960 and 2010, in either the English or Chinese languages. Reference lists of studies that met the inclusion criteria were also searched for additional studies. TYPES OF STUDIES: This review included randomised controlled trials and quasi-experimental studies that examined the effectiveness of non-pharmacological interventions for fatigue in children and adolescents with cancer. TYPES OF PARTICIPANTS: Children and adolescents aged between one to 18 years old, with cancer either during or after the chemotherapy. The types of cancer included were acute lymphoblastic leukaemia, acute myeloid leukaemia, lymphoma and solid tumours. TYPES OF INTERVENTIONS: Non-pharmacological interventions for fatigue in children and adolescents with cancer including: activity enhancement (exercise, physical activity), psychosocial interventions, cognitive behavioural therapy, stress management, relaxation, nutrition consultation, massage and educational interventions. The intervention descriptions included the length, frequency, setting and intervention providers. TYPES OF OUTCOME MEASURES: The outcome measures considered fatigue scores assessment. TYPES OF SETTING: The review considered studies conducted either in a hospital or a community setting. DATA COLLECTION AND SYNTHESIS: The data were extracted and synthesised using the standardised data extraction tool and synthesis function offered by the Joanna Briggs Institute Meta-Analysis of Statistics Assessment and Review Instrument. RESULTS: The review included six studies - five English-language papers and one Chinese-language paper. Meta-analysis did not show a statistically significant impact on the effectiveness of exercise interventions in reducing overall fatigue in children and adolescents with cancer. Exercise interventions did lead to a statistically significant improvement (p = 0.01) in general fatigue (i.e. tiredness, physical weakness) (effect size = -0.76; 95% Confidence Interval -1.35 to -0.17). CONCLUSIONS: The results of this systematic review show that exercise interventions can effectively reduce the level of general fatigue of children aged six to 18 years. No strong conclusions can be made for the use of massage therapy or health education measures, as there was only one article for each of these interventions. IMPLICATIONS FOR PRACTICE: The review provides an evidenced-based guide to future priorities for clinical practice. Exercise intervention could reduce the level of general fatigue of children aged six to 18 years. In particular, exercise interventions for fatigue are feasible and safe. IMPLICATIONS FOR RESEARCH: There is still a lack of rigorous research on this specific topic. Further research requires more rigorous study design and reporting of methodological issues, such as randomised controlled trials using concealment of allocation. Other non-pharmacological interventions for this problem should also be examined, including cognitive behavioural therapy, stress management, relaxation, support groups and massage therapy.

Alternative mRNA splicing creates transcripts encoding soluble proteins from most LILR genes.

Leucocyte Ig-like receptors (LILR) are a family of innate immune receptors expressed on myeloid and lymphoid cells that influence adaptive immune responses. We identified a common mechanism of alternative mRNA splicing, which generates transcripts that encode soluble protein isoforms of the majority of human LILR. These alternative splice variants lack transmembrane and cytoplasmic encoding regions, due to the transcription of a cryptic stop codon present in an intron 5' of the transmembrane encoding exon. The alternative LILR transcripts were detected in cell types that express their membrane-associated isoforms. Expression of the alternative LILRB1 transcript in transfected cells resulted in the release of a soluble approximately 65 Kd LILRB1 protein into culture supernatants. Soluble LILRB1 protein was also detected in the culture supernatants of monocyte-derived DC. In vitro assays suggested that soluble LILRB1 could block the interaction between membrane-associated LILRB1 and HLA-class I. Soluble LILRB1 may act as a dominant negative regulator of HLA-class I-mediated LILRB1 inhibition. Soluble isoforms of the other LILR may function in a comparable way.

Craniofacial gunshot injury resulting in pseudoaneurysm of the left internal maxillary artery and Collet-Sicard syndrome.

Facial gunshot is a challenging medico-surgical emergency because of the complex neurovascular structure in the area. We present a patient who sustained a facial gunshot injury, with massive nasal and oral bleeding that resulted in shock. We review the management of gunshot injury to the internal maxillary artery, both in acute and chronic stages. In addition, we describe the clinical course of the rarely occurring Collet-Sicard syndrome, which involves injury to the 9th, 10th, 11th, and 12th cranial nerves associated with gunshot injury.

Orbitozygomatic approach for excisions of orbital tumors with 1 piece of craniotomy bone flap: 2 case reports.

BACKGROUND: Orbital tumors are classified as primary and secondary. For primary entities, there are variable pathologies with benign and malignant natures. Many of the orbital tumors should be excised through neurosurgical approaches. We reported 2 cases of orbital tumors, which were clearly disclosed by magnetic resonance imaging. CASE DESCRIPTION: Case 1 was a 70-year-old woman and case 2 was a 57-year-old woman. Both cases were presented with progressive unilateral proptosis. The pathologies were intraorbital cavernous hemangioma and lacrimal mixed adenoma, respectively. With the scalp incision all posterior to the hairline, frontotemporal orbitozygomatic approach with 1 piece of craniotomy bone flap was performed after freeing all the remaining periorbita and other soft tissue attachments. This approach assures maximum exposure for successful en bloc excisions of these tumors with minimal bone loss, so the cosmetic results are satisfactory. CONCLUSIONS: Even though most orbital tumors are diagnosed by ophthalmologists, most of them should be operated on by neurosurgeons because neurosurgical approaches offer wide and safe surgical windows.

Methods for isolation of cells from the human fetal-maternal interface.

During human pregnancy, fetal placental cells known as trophoblast invade into the uterine mucosal lining, coming into contact with maternal cells including a specialized population of leukocytes. In order to understand the interaction of maternal cells with trophoblast, it is useful to be able to isolate the various cell types from the fetal-maternal interface so that they may be characterized and co-cultured in vitro. This chapter details the methods we use in our laboratory for enrichment and/or purification of trophoblast cells, decidual leukocytes, decidual natural killer cells, decidual stromal cells, and decidual glandular epithelial cells from human first-trimester tissue samples.

Evaluating quality of life in children with cancer using children's self-reports and parent-proxy reports.

BACKGROUND: Assessment of quality of life (QOL) of children is complex due to the developmental differences in understanding the content being measured. The validity of parent-proxy reports versus children's self-reports remains to be clarified. OBJECTIVES: To examine the agreement on QOL measures between children's self-reports and parent-proxy reports at different points in time, including at baseline and at 6-month follow up, as well as the change in scores between 6-month follow up and baseline. METHOD: A longitudinal study of QOL assessment of children with cancer for parents and children was conducted. At baseline assessment, 126 children with cancer and at least one of their parents participated (n = 252). Forty boys, 25 girls, and their parents (n = 130) completed the 6-month follow up assessment. RESULTS: Parents tended to report better QOL than did the children at both baseline and 6-month follow up assessments in both the on- and off-treatment groups. Agreement on QOL measure between children and parent proxies varied as a result of the following factors: treatment status (on and off treatment), time (at baseline vs. at 6-month follow up), and changes in score between the time of the baseline assessment and the 6-month follow up. The effects of time, age, gender, and severity of illness had different degrees of significance as predictors on various subscales. DISCUSSION: The predictors of agreement between patients' reports and parent-proxy reports, including the passage of time (from baseline to 6-month follow up), gender, age, and illness severity, have not been conclusively determined. Further studies are needed to examine patient-proxy agreement during a longer follow up period at more than two points in time and using the same patients through the stages of confirmation of diagnosis, acceptance of diagnosis, treatment, and after treatment.