(η6-Benzene)-chlorido-[(S)-2-(4-isopropyl-4,5-di-hydro-oxazol-2-yl)phenolato]ruthenium(II).

The title compound, [Ru(C12H14NO2)Cl(η6-C6H6)], exhibits a half-sandwich tripod stand structure and crystallizes in the ortho-rhom-bic space group P212121. The arene group is η6 π-coordinated to the Ru atom with a centroid-to-metal distance of 1.6590 (5) Å, with the (S)-2-(4-isopropyl-4,5-di-hydro-oxazol-2-yl)phenolate chelate ligand forming a bite angle of 86.88 (19)° through its N and phenolate O atoms. The pseudo-octa-hedral geometry assumed by the complex is completed by a chloride ligand. The coordination of the optically pure bidentate ligand induces metal centered chirality onto the complex with a Flack parameter of -0.056.

Statistical Models for High-Risk Intestinal Metaplasia with DNA Methylation Profiling.

We consider the newly developed multinomial mixed-link models for a high-risk intestinal metaplasia (IM) study with DNA methylation data. Different from the traditional multinomial logistic models commonly used for categorical responses, the mixed-link models allow us to select the most appropriate link function for each category. We show that the selected multinomial mixed-link model (Model 1) using the total number of stem cell divisions (TNSC) based on DNA methylation data outperforms the traditional logistic models in terms of cross-entropy loss from ten-fold cross-validations with significant p-values 8.12×10-4 and 6.94×10-5. Based on our selected model, the significance of TNSC's effect in predicting the risk of IM is justified with a p-value less than 10-6. We also select the most appropriate mixed-link models (Models 2 and 3) when an additional covariate, the status of gastric atrophy, is available. When the status is negative, mild, or moderate, we recommend Model 2; otherwise, we prefer Model 3. Both Models 2 and 3 can predict the risk of IM significantly better than Model 1, which justifies that the status of gastric atrophy is informative in predicting the risk of IM.

Lifestyle patterns and incident type 2 diabetes in the Dutch lifelines cohort study.

We aimed to identify the underlying subgroups of the population characterized by distinct lifestyle patterns, and to investigate the associations between lifestyle patterns and risk of incident type 2 diabetes. Using data from the Dutch Lifelines cohort study, latent class analysis was performed to derive lifestyle patterns on five lifestyle factors, i.e., smoking, diet quality, TV watching time, physical activity level, and risk drinking. Associations between lifestyle patterns and incident type 2 diabetes were estimated. Among 61,869 participants analyzed, we identified 900 cases of type 2 diabetes during follow-up (205,696 person-years; incidence rate 4.38 per 1000 person-years). Five lifestyle pattern groups were identified. Using the "healthy lifestyle group" as reference, the "unhealthy lifestyle group" had the highest risk for type 2 diabetes (HR 1.51 [95%CI 1.24, 1.85]), followed by the "poor diet and low physical activity group" (HR 1.26 [95%CI 1.03, 1.55]). The "risk drinker group" and the "couch potato group" (characterized by excessive TV watching) showed no significantly elevated risk. These models were adjusted for age, sex, total energy intake, education, BMI, family history of diabetes, and blood glucose level at baseline. Our study shows that lifestyle factors tended to cluster in unique behavioral patterns within the heterogeneous population. These lifestyle patterns were differentially associated with incident type 2 diabetes. Our findings support the relevance of considering lifestyle patterns in type 2 diabetes prevention. Tailored prevention strategies that target multiple lifestyle risk factors for different lifestyle pattern groups may optimize the effectiveness of diabetes prevention at the population level.

Viro-Immunological, Clinical Outcomes and Costs of Switching to BIC/TAF/FTC in a Cohort of People Living with HIV: A 48-Week Prospective Analysis.

To date, therapeutic switches are performed to reduce and prevent toxicity, improve adherence, promote virological control, and save costs. Drug switches are a daily challenge in the management of people living with HIV (PLWH), especially in those with multiple comorbidities and on polypharmacy. The objectives of this prospective analysis were: (I) to evaluate the viro-immunological efficacy of BIC/FTC/TAF in a cohort of PLWH who switched to this regimen from any other previous, at the Infectious and Tropical Diseases Unit of the Padua University Hospital; (II) to assess the impact on body weight, lipids, and renal function parameters at week 48; and (III) to evaluate daily costs changes, adherence, and the rate and causes of discontinuation of the regimen. We included all adult PLWH who switched to BIC/FTC/TAF from 1 February 2020 to 31 October 2021. We collected demographic, clinical, and laboratory data at baseline and week 48 after the switch. In addition, the estimated cART-related cost changes over the follow-up period were calculated. Over the study period, 290 individuals who switched to BIC/FTC/TAF, 76.9% were males, with a median age of 52 years, and 94.8% had an undetectable baseline HIV viremia. After a median time of 35 days (IQR: 1-55), 41 (14.1%) individuals discontinued the regimen. Factors significantly associated with discontinuation were switching from dual regimens, and neurological disorders. At week 48, we detected a significant increase in body weight, BMI, CD4 T-cell count, and CD4/CD8 ratio, and a significant reduction in triglycerides and costs; all patients had undetectable HIV RNA. Our results showed that switching to BIC/FTC/TAF may favor slightly immunological recovery and cost saving (-4.2 EUR/day from baseline to week 48, equivalent to a mean saving of 1533 EUR/year/person). The reduction in triglycerides does not appear to be clinically relevant, even if statistically significant, nor do both the increase in body weight and BMI (+1 kg and +0.29 BMI, respectively) and the increase in CD4 T-cell count (+45 cells/mmc). Further studies are needed to confirm our results.

Improved nonparametric penalized maximum likelihood estimation for arbitrarily censored survival data.

Nonparametric maximum likelihood estimation encompasses a group of classic methods to estimate distribution-associated functions from potentially censored and truncated data, with extensive applications in survival analysis. These methods, including the Kaplan-Meier estimator and Turnbull's method, often result in overfitting, especially when the sample size is small. We propose an improvement to these methods by applying kernel smoothing to their raw estimates, based on a BIC-type loss function that balances the trade-off between optimizing model fit and controlling model complexity. In the context of a longitudinal study with repeated observations, we detail our proposed smoothing procedure and optimization algorithm. With extensive simulation studies over multiple realistic scenarios, we demonstrate that our smoothing-based procedure provides better overall accuracy in both survival function estimation and individual-level time-to-event prediction (imputation) by reducing overfitting. Our smoothing procedure decreases the bias (discrepancy between the estimated and true simulated survival function) using interval-censored data by up to 48% compared to the raw un-smoothed estimate, with similar improvements of up to 34% and 23% in within-sample and out-of-sample prediction, respectively. Our smoothing algorithm also demonstrates significant overall improvement across all three metrics when compared to a popular semiparametric B-splines estimation method. Finally, we apply our method to real data on censored breast cancer diagnosis, which similarly shows improvement when compared to empirical survival estimates from uncensored data. We provide an R package, SISE, for implementing our penalized likelihood method.

Prevalence, Predictors, and Outcomes of Esophageal Candidiasis in Cirrhosis: An Observational Study With Systematic Review and Meta-Analysis (CANDID-VIEW).

BACKGROUND: Gastrointestinal candidiasis is often neglected and potentially serious infection in cirrhosis patients. Therefore, we evaluated the prevalence, risk factors, and outcomes of esophageal candidiasis (EC) in cirrhotics and did a systematic review to summarize EC's available evidence in cirrhosis. METHODS: Consecutive patients with cirrhosis posted for esophagogastroduodenoscopy (EGD) at a tertiary care institute were screened for EC (cases) between January 2019 and March 2020. EC was diagnosed on EGD findings and/or brush cytology. Controls (without EC) were recruited randomly, and EC's risk factors and outcomes were compared between cases and controls.Four electronic databases were searched for studies describing EC in cirrhosis. Prevalence estimates of EC were pooled on random-effects meta-analysis, and heterogeneity was assessed by I2. A checklist for prevalence studies was used to evaluate the risk of bias in studies. RESULTS: EC was diagnosed in 100 of 2762 patients with cirrhosis (3.6%). Patients with EC had a higher model for end-stage liver disease (MELD) (12.4 vs. 11.2; P = 0.007), acute-on-chronic liver failure (ACLF) (26% vs. 10%; P = 0.003) and concomitant bacterial infections (24% vs. 7%; P = 0.001), as compared with controls. A multivariable model, including recent alcohol binge, hepatocellular carcinoma (HCC), upper gastrointestinal (UGI) bleed, ACLF, diabetes, and MELD, predicted EC's development in cirrhosis with excellent discrimination (C-index: 0.918). Six percent of cases developed the invasive disease and worsened with multiorgan failures, and four patients with EC died on follow-up.Of 236 articles identified, EC's pooled prevalence from 8 studies (all with low-risk of bias) was 2.1% (95% CI: 0.8-5.8). Risk factors and outcomes of EC in cirrhosis were not reported in the literature. CONCLUSIONS: EC is not a rare infection in cirrhosis patients, and it may predispose to invasive candidiasis and untimely deaths. Alcohol binge, HCC, UGI bleed, ACLF, diabetes, and higher MELD are the independent predictors of EC in cirrhosis. At-risk patients with cirrhosis or those with deglutition symptoms should be rapidly screened and treated for EC.

Cardiovascular damage phenotypes and all-cause and CVD mortality in older adults.

PURPOSE: The association between CVD risk factors and mortality is well established, however, current tools for addressing subgroups have focused on the overall burden of disease. The identification of risky combinations of characteristics may lead to a better understanding of physiologic pathways that underlie morbidity and mortality in older adults. METHODS: Participants included 5067 older adults from the Cardiovascular Health Study, followed for up to 6 years. Using latent class analysis (LCA), we created CV damage phenotypes based on probabilities of abnormal brain infarctions, major echocardiogram abnormalities, N-terminal probrain natriuretic peptide, troponin T, interleukin-6, c reactive-protein, galectin-3, cystatin C. We assigned class descriptions based on the probability of having an abnormality among risk factors, such that a healthy phenotype would have low probabilities in all risk factors. Participants were assigned to phenotypes based on the maximum probability of membership. We used Cox-proportional hazards regression to evaluate the association between the categorical CV damage phenotype and all-cause and CVD-mortality. RESULTS: The analysis yielded 5 CV damage phenotypes consistent with the following descriptions: healthy (59%), cardio-renal (11%), cardiac (15%), multisystem morbidity (6%), and inflammatory (9%). All four phenotypes were statistically associated with a greater risk of all-cause mortality when compared with the healthy phenotype. The multisystem morbidity phenotype had the greatest risk of all-cause death (HR: 4.02; 95% CI: 3.44, 4.70), and CVD-mortality (HR: 4.90, 95% CI: 3.95, 6.06). CONCLUSIONS: Five CV damage phenotypes emerged from CVD risk factor measures. CV damage across multiple systems confers a greater mortality risk compared to damage in any single domain.

EXPERIMENTAL STUDY OF BONE REBUILDING IN THE PERIIMPLANTATION AREA UNDER IMMEDIATE LOADING ON DENTAL IMPLANTS.

OBJECTIVE: The aim: Study of the dynamics of morphological rearrangement of bone under conditions of immediate occlusive functional load and the effect of splinting of implants with temporary orthopedic structures with the analysis of the coefficient of stability of implants during immediate implantation in the experiment. PATIENTS AND METHODS: Materials and methods: A series of experiments was performed on 6 male Duroc pigs at the age of 6 months and weighing 40-60 kg. In the course of recent advances, the following methods have been used: the clinical protocol of immediate - implantation of time-consuming clothes, the definition of COEFICIENT, morphometry and light microscopy of the slides, statistical analysis. RESULTS: Results: By morphometric examination after 3 months the BIC in the series with splinting was 1.68 times higher compared to 1 month. studies, in a series of experiments without splinting - 1.9 times, after 3 months. the difference between implantation experiments with splinting components and without splinting is 1.6 times. During the functional study of the resonant - frequency analyzer, there is an increase in the ISQ in the second and third months after surgery, but this figure is higher in the study using the splint component. CONCLUSION: Conclusions: Stagnation of the shingle component in the case of intrinsic intraoperative functional juvenile implantation accelerates the dynamics of osteointegration, so that high indicators of the efficiency of the implant stability can be achieved.

Improved osteosarcoma survival with addition of mifamurtide to conventional chemotherapy - Observational prospective single institution analysis.

PURPOSE: Conventional osteosarcoma is an orphan disease. Current treatment approaches include combining a three drug chemotherapy schedule and surgery. The 3- and 5-year event-free survival (EFS) in localized disease is roughly 65 and 60%, respectively. The registration study of mifamurtide reported survival benefit, but some methodological controversies have been insufficient for FDA market authorization in contrast to EMA. METHODS: prospective single centre survival analysis of a mifamurtide addition to conventional therapy in 23 patients over a 5.5 year enrolment period is reported and compared to a historical control of 26 patient with localized disease. Bias arising from observational methodology was addressed using Landmark analysis and time-dependent Cox models. Blood count dynamics were analysed during the treatment. RESULTS: The adverse event profile was as expected with no dose limiting toxicities. There were no local relapses observed, one patient died in the first complete remission due to doxorubicin cardiotoxicity, one patient had pulmonary metastatic relapse. The observed 3- and 5-year EFS was 87.4% (CI 72.4-100%) and 87.4% (CI 72.4-100%), progression free survival (PFS) was 92.9% (CI 80.3-100%) and 92.9% (CI 80.3-100%), overall survival was 94.1% (CI 83.6-100) and 80.7% (CI 58.3-100), respectively. Comparison to the historical control showed statistically significant better PFS for mifamurtide patients (Landmark analysis; p = 0.044). Risk of progression was 5-times lower for the mifamurtide group (Cox model; HR 0.21, p = 0.136). Only subtle differences in lymphocyte counts were observed across treatment. CONCLUSION: the PFS benefit of mifamurtide is reported herein. The addition of mifamurtide could be considered as a best treatment option for localized osteosarcoma.

Models for optimizing selection based on adaptability and stability of cotton genotypes / Modelos para otimizar a seleção baseada em adaptabilidade e estabilidade de genótipos de algodão

ABSTRACT: In multi-environment trials (MET), large networks are assessed for results improvement. However, genotype by environment interaction plays an important role in the selection of the most adaptable and stable genotypes in MET framework. In this study, we tested different residual variances and measure the selection gain of cotton genotypes accounting for adaptability and stability, simultaneously. Twelve genotypes of cotton were bred in 10 environments, and fiber length (FL), fiber strength (FS), micronaire (MIC), and fiber yield (FY) were determined. Model selection for different residual variance structures (homogeneous and heterogeneous) was tested using the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). The variance components were estimated through restricted maximum likelihood and genotypic values were predicted through best linear unbiased prediction. The harmonic mean of relative performance of genetic values (HMRPGV) were applied for simultaneous selection for adaptability, stability, and yield. According to BIC heterogeneous residual variance was the best model fit for FY, whereas homogeneous residual variance was the best model fit for FL, FS, and MIC traits. The selective accuracy was high, indicating reliability of the prediction. The HMRPGV was capable to select for stability, adaptability and yield simultaneously, with remarkable selection gain for each trait.

RESUMO: Em ensaios multi-ambientes, grandes redes experimentais são utilizadas para a avaliação de genótipos, tentando contornar o efeito que a interação genótipo por ambiente desempenha na seleção genotípica. Neste estudo, objetivamos testar diferentes estruturas de variância residual e medir o ganho de seleção de genótipos de algodão, baseados em produtividade, adaptabilidade e estabilidade, simultaneamente. Doze genótipos de algodão foram plantados em 10 ambientes, sendo determinados o comprimento da fibra (CF), a resistência da fibra (RF), a micronaire (MIC) e produtividade de fibras (PF). A seleção do modelo para diferentes estruturas de variância residual (homogênea e heterogênea) foi testada usando o Critério de Informação de Akaike (AIC) e o Critério de Informação Bayesiano (BIC). Os componentes de variância foram estimados através de máxima verossimilhança restrita e os valores genotípicos foram preditos através da melhor predição linear não viesada. A média harmônica do desempenho relativo dos valores genéticos (HMRPGV) foram aplicadas para seleção simultânea para adaptabilidade, estabilidade e produtividade. De acordo com o BIC, a estrutura residual heterogênea apresentou o melhor ajuste para a característica PF, enquanto a estrutura residual homogênea apresentou o melhor ajuste para as características CF, RF e MIC. A acurácia seletiva foi alta, indicando confiabilidade da predição. O método HMRPGV foi capaz de selecionar para estabilidade, adaptabilidade e produtividade, simultaneamente, com notável ganho de seleção para cada característica.

Latent class trajectories: U.S. adolescents' nicotine use and its association with nicotine dependence.

INTRODUCTION: Twenty-seven percent of adolescents used a nicotine/tobacco product in 2018. Our study analyzed three waves from the Population Assessment of Tobacco and Health (PATH) Study and examined adolescent nicotine/tobacco use trajectories over time to determine which latent classes were associated with symptoms of nicotine dependence. METHODS: The PATH Study used a four-stage, stratified area probability sample and annual household interviews with adolescents (12-17 years). Adolescents who indicated past 30-day nicotine/tobacco use at least once were included (n = 1101). We used latent class analysis (LCA) to identify nicotine/tobacco trajectories across three waves of PATH data and their association with six symptoms consistent with nicotine dependence from the Wisconsin Inventory of Smoking Dependence Motives (WISDM-68). RESULTS: All types of past 30-day nicotine/tobacco use increased across the three waves. An LCA model fit was assessed using both the CIV and entropy measures in conjunction with the Vuong-Lo-Mendell-Rubin LRT. A five latent class solution had the lowest BIC value (BIC = 9784.272), and resulted in: (1) "Stable/consistent multiproduct use trajectory", (2) "Increasing cigarette use trajectory", (3) "Increasing e-cigarette use trajectory", (4) "Experimental (poly-nicotine/tobacco) use trajectory", and (5) "Increasing other nicotine/tobacco use trajectory". The most prevalent was the "Experimental (poly-nicotine/tobacco) use trajectory" (33.8%) although sex, race, and social class were associated with different trajectories. Those represented by the "Increasing cigarette use trajectory" (19.4%) reported significantly more past-year nicotine dependence symptoms (b = 1.73, p < 0.001) compared to the "Increasing e-cigarette use trajectory". Findings varied by sex and race. CONCLUSIONS: Results indicate that the relationship between e-cigarette use and other forms of nicotine/tobacco and substance use is complex and that adolescent nicotine/tobacco users are a heterogenous group with different risks for nicotine dependence. Findings can inform tailored prevention education and messaging for different groups of youth.

Bicalutamide Elicits Renal Damage by Causing Mitochondrial Dysfunction via ROS Damage and Upregulation of HIF-1.

Combined androgen blockade using bicalutamide (Bic) is a therapeutic choice for treating prostate cancer (PCa). However, even at regular clinical dosages, Bic frequently shows adverse effects associated with cardiovascular and renal damage. Previously, we found that Bic selectively damaged mesangial cells compared to tubular cells and in an in vivo rat model, we also found renal damage caused by Bic. In the present study, a rat mesangial cell model was used to further the investigation. Results indicated that Bic enhanced lactate dehydrogenase release, reactive oxygen species (ROS) production, lysosome population and kidney injury molecule-1 and decreased N-cadherin. Bic elicited mitochondrial swelling and reduced the mitochondrial potential, resulting in severe suppression of the oxygen consumption rate (OCR), maximum respiration and ATP production. The hypoxia-inducible factor (HIF)-1 transcriptional activity and messenger RNA were significantly upregulated in dose-dependent manners. The HIF-1 protein reached a peak value at 24 h then rapidly decayed. BCL2/adenovirus E1B 19-kDa protein-interacting protein 3 and cleaved caspase-3 were dose-dependently upregulated by Bic (60 M) and that eventually led to cell apoptosis. It is suggested that Bic induces renal damage via ROS and modulates HIF-1 pathway and clinically, some protective agents like antioxidants are recommended for co-treatment.

Degradation and Biocompatibility of AZ31 Magnesium Alloy Implants In Vitro and In Vivo: A Micro-Computed Tomography Study in Rats.

In current orthodontic practice, miniscrew implants (MSIs) for anchorage and bone fixation plates (BFPs) for surgical orthodontic treatment are commonly used. MSIs and BFPs that are made of bioabsorbable material would avoid the need for removal surgery. We investigated the mechanical, degradation and osseointegration properties and the bone-implant interface strength of the AZ31 bioabsorbable magnesium alloy to assess its suitability for MSIs and BFPs. The mechanical properties of a Ti alloy (TiA), AZ31 Mg alloy (MgA), pure Mg and poly-L-lactic acid (PLA) were investigated using a nanoindentation test. Also, pH changes in the solution and degradation rates were determined using immersion tests. Three-dimensional, high-resolution, micro-computed tomography (CT) of implants in the rat femur was performed. Biomechanical push-out testing was conducted to calculate the maximum shear strength of the bone-implant interface. Scanning electron microscopy (SEM), histological analysis and an evaluation of systemic inflammation were performed. MgA has mechanical properties similar to those of bone, and is suitable for implants. The degradation rate of MgA was significantly lower than that of Mg. MgA achieved a significantly higher bone-implant bond strength than TiA. Micro-CT revealed no significant differences in bone density or bone-implant contact between TiA and MgA. In conclusion, the AZ31 Mg alloy is suitable for both MSIs and BFPs.

Sparse semiparametric canonical correlation analysis for data of mixed types.

Canonical correlation analysis investigates linear relationships between two sets of variables, but often works poorly on modern datasets due to high-dimensionality and mixed data types (continuous/binary/zero-inflated). We propose a new approach for sparse canonical correlation analysis of mixed data types that does not require explicit parametric assumptions. Our main contribution is the use of truncated latent Gaussian copula to model the data with excess zeroes, which allows us to derive a rank-based estimator of latent correlation matrix without the estimation of marginal transformation functions. The resulting semiparametric sparse canonical correlation analysis method works well in high-dimensional settings as demonstrated via numerical studies, and application to the analysis of association between gene expression and micro RNA data of breast cancer patients.

Quantifying the Power and Precision of QTL Analysis in Autopolyploids Under Bivalent and Multivalent Genetic Models.

New genotyping technologies, offering the possibility of high genetic resolution at low cost, have helped fuel a surge in interest in the genetic analysis of polyploid species. Nevertheless, autopolyploid species present extra challenges not encountered in diploids and allopolyploids, such as polysomic inheritance or double reduction. Here we investigate the power and precision of quantitative trait locus (QTL) analysis in outcrossing autopolyploids, comparing the results of a model that assumes random bivalent chromosomal pairing during meiosis to one that also allows for multivalents and double reduction. Through a series of simulation studies we found that marginal gains in QTL detection power are achieved using the double reduction model when multivalent pairing occurs. However, when exploring the effect of variable genotypic information across parental homologs, we found that both QTL detection power and precision require high and uniform genotypic information contents. This effect far outweighed considerations regarding bivalent or multivalent pairing (and double reduction) during meiosis. We propose that autopolyploid QTL studies be accompanied by both marker coverage information and per-homolog genotypic information coefficients (GIC). Application of these methods to an autotetraploid potato (Solanum tuberosum L.) mapping population confirmed our ability to locate and dissect QTL in highly heterozygous outcrossing autotetraploid populations.

A Feedback Loop between MicroRNA 155 (miR-155), Programmed Cell Death 4, and Activation Protein 1 Modulates the Expression of miR-155 and Tumorigenesis in Tongue Cancer.

MicroRNA 155 (miR-155) is an oncomir, generated as a noncoding RNA from the BIC gene whose promoter activity is mainly controlled via activation protein 1 (AP-1) and NF-κB transcription factors. We found that the expression levels of miR-155 and programmed cell death 4 (Pdcd4) exhibit inverse relationships in tongue cancer cells (SAS and AWL) and tumor tissues compared to their relationships in normal FBM cells and normal tongue tissues, respectively. In silico and in vitro studies with the 3' untranslated region (UTR) of Pdcd4 via luciferase reporter assays, quantitative PCR (qPCR), and Western blotting showed that miR-155 directly targets Pdcd4 mRNA and blocks its expression. Ectopic expression of Pdcd4 or knockdown of miR-155 in tongue cancer cells predominantly reduces AP-1-dependent transcriptional activity of the BIC promoter and decreases miR-155 expression. In this study, we demonstrate that miR-155 expression is modulated by a feedback loop between Pdcd4, AP-1, and miR-155 which results in enhanced expression of miR-155 with a consequent progression of tongue tumorigenesis. Further, miR-155 knockdown increases apoptosis, arrests the cell cycle, regresses tumor size in xenograft nude mice, and reduces cell viability and colony formation in soft-agar and clonogenic assays. Thus, the restoration of Pdcd4 levels by the use of molecular manipulation such as using a miR-155 sponge has an essential role in the therapeutic intervention of cancers, including tongue cancer.

Transformed low-rank ANOVA models for high-dimensional variable selection.

High-dimensional data are often encountered in biomedical, environmental, and other studies. For example, in biomedical studies that involve high-throughput omic data, an important problem is to search for genetic variables that are predictive of a particular phenotype. A conventional solution is to characterize such relationships through regression models in which a phenotype is treated as the response variable and the variables are treated as covariates; this approach becomes particularly challenging when the number of variables exceeds the number of samples. We propose a general framework for expressing the transformed mean of high-dimensional variables in an exponential distribution family via ANOVA models in which a low-rank interaction space captures the association between the phenotype and the variables. This alternative method transforms the variable selection problem into a well-posed problem with the number of observations larger than the number of variables. In addition, we propose a model selection criterion for the new model framework with a diverging number of parameters, and establish the consistency of the selection criterion. We demonstrate the appealing performance of the proposed method in terms of prediction and detection accuracy through simulations and real data analyses.

Using Resonance Frequency Analysis to Compare Delayed and Immediate Progressive Loading for Implants Placed in the Posterior Maxilla: A Pilot Study.

OBJECTIVE: Implants placed in the posterior region of the maxilla have a high incidence of implant failure due to poor bone quality, especially when immediate implant loading is needed. Immediate Progressive Loading (IPL) can enhance bone quality and may offer an alternative solution when Immediate Implant loading is needed. METHODS: Six patients (one male and five females; 34-62 years old) were included in this study. Twelve implants were inserted in the posterior region of the maxilla. Resonance Frequency Analysis (RFA) was performed at the time of implant placement and after 1, 2, 3 and 6 months. ISQ (Implant Stability Quotient) values were compared between the Delayed Loading (DL) group after 2 months and the Progressive Loading (PL) group and between different time points for each group. RESULTS: At implant placement, the mean ISQ values for PL and DL implants were 63 and 57, respectively. One month after implant placement, the mean ISQ value for PL implants was 73.Two months after implant placement, the mean ISQ value for PL implants was 75. Three months after implant placement, the mean ISQ values for PL and DL implants were 76 and 69, respectively. Six months after implant placement, the mean ISQ values for PL and DL implants were 79 and 76, respectively. CONCLUSION: Despite its limitations, this pilot study indicated that compared to DL, PL can enhance bone density and implant stability, resulting in greater early functionality and fewer surgery sessions.

Quantification of Multiple Tumor Clones Using Gene Array and Sequencing Data.

Cancer development is driven by genomic alterations, including copy number aberrations. The detection of copy number aberrations in tumor cells is often complicated by possible contamination of normal stromal cells in tumor samples and intratumor heterogeneity, namely the presence of multiple clones of tumor cells. In order to correctly quantify copy number aberrations, it is critical to successfully de-convolute the complex structure of the genetic information from tumor samples. In this article, we propose a general Bayesian method for estimating copy number aberrations when there are normal cells and potentially more than one tumor clones. Our method provides posterior probabilities for the proportions of tumor clones and normal cells. We incorporate prior information on the distribution of the copy numbers to prioritize biologically more plausible solutions and alleviate possible identifiability issues that have been observed by many researchers. Our model is flexible and can work for both SNP array and next-generation sequencing data. We compare our method to existing ones and illustrate the advantage of our approach in multiple datasets.

Drugs, doses, and durations of intraperitoneal chemotherapy: standardising HIPEC and EPIC for colorectal, appendiceal, gastric, ovarian peritoneal surface malignancies and peritoneal mesothelioma.

Peritoneal surface malignancy (PSM) is a common manifestation of digestive and gynaecologic malignancies alike. At present, patients with isolated PSM are treated with a combination therapy of cytoreductive surgery (CRS) and hyperthermic peroperative intraperitoneal chemotherapy (HIPEC). The combination of CRS and intraperitoneal (IP) chemotherapy should now be considered standard of care for PSM from appendiceal epithelial cancers, colorectal cancer and peritoneal mesothelioma. Although there is a near universal standardisation regarding the CRS, we are still lacking a much-needed standardisation amongst the various IP chemotherapy treatment modalities used today in clinical practice. Pharmacologic evidence should be generated to answer important questions raised by the myriad of variables associated with IP chemotherapy.