Development of physical and mathematical models for the Porous Ceramic Tube Plant Nutrification System (PCTPNS)

A physical model of the Porous Ceramic Tube Plant Nutrification System (PCTPNS) was developed through microscopic observations of the tube surface under various operational conditions. In addition, a mathematical model of this system was developed which incorporated the effects of the applied suction pressure, surface tension, and gravitational forces as well as the porosity and physical dimensions of the tubes. The flow of liquid through the PCTPNS was thus characterized for non-biological situations. One of the key factors in the verification of these models is the accurate and rapid measurement of the 'wetness' or holding capacity of the ceramic tubes. This study evaluated a thermistor based moisture sensor device and recommendations for future research on alternative sensing devices are proposed. In addition, extensions of the physical and mathematical models to include the effects of plant physiology and growth are also discussed for future research

Evolving Patterns of Metastasis in Renal Cell Carcinoma: Do We Need to Perform Routine Bone Imaging?

Advance diagnostic and treatment modalities have improved outcomes for renal cell carcinoma (RCC) patients, but the prognosis for those with metastatic disease (mRCC) remains poor. As given metastatic distribution is critical in guiding treatment decisions for mRCC patients, we evaluated evolving metastatic patterns to assess if our current practice standards effectively address patient needs. A systematic literature review was performed to identify all publicly available prospective clinical trials in metastatic renal cell carcinoma (mRCC) from 1990 to 2018. A total of 16,899 mRCC patients from 127 qualified phase I–III clinical trials with metastatic site documentations were included for analysis for incidence of metastases to lung, liver, bone, and lymph nodes (LNs) over time. Studies were categorized into three treatment eras based on the timing of regulatory approval: Cytokine Era (1990-2004), vascular endothelial growth factor/tyrosine kinase inhibitor (TKI) Era (2005-2016), and immune checkpoint inhibitor/TKI Era (ICI-TKI, 2017-2018) and also classified as first-line only (FLO) or second-line and beyond (SLB). Overall, an increase in the incidence of bone and LNs metastases in FLO and SLB, and lung metastases in FLO, was seen over the three treatment eras. Generally, the burden of disease is higher in SLB when compared with FLO. Importantly, in the ICI-TKI era, the incidences of bone metastasis are 28% in FLO and 29% in SLB settings. The disease burden in patients with mRCC has increased steadily over the past three decades. Given the unexpectedly high rate of bone metastasis, routine dedicated bone imaging should be considered in all patients with mRCC

Network Influence of the Cerebellum for Predicting DBS Response in Patients with Advanced Parkinson’s Disease

Introduction: Deep brain stimulation (DBS) is a treatment option for reducing motor symptoms in patients with Parkinson’s Disease (PD) when first-line medication becomes ineffective. Existing literature has hypothesized that the clinical outcome of DBS may depend on brain connectivity profiles of the stimulation site to distant brain regions. However, the potential of brain connectivity profiles to predict response to DBS in PD remains unclear. Objective: This study aimed to investigate how changes in structural and functional connectivity may relate to patient response to DBS, through the examination of brain network changes using graph theory. Methods: Ten patients with advanced PD were included in this study. Diffusion tensor imaging (DTI) and resting-state fMRI scans were acquired prior to DBS implantation. Pre-DBS and post-DBS UPDRS-III scores were obtained. Network analysis of the DTI and fMRI scans was performed using GRETNA to compute structural and functional graph theory metrics, respectively. Metrics were correlated with UPDRS-III improvement to identify significant correlations to UPDRS improvement due to DBS. Results: Combined structural and functional graph theory metrics highlighted 32 structures to be significantly correlated with UPDRS-III improvement. Mainly, connections to the cerebellum were found to be significantly correlated with UPDRS-III improvement across several metrics for both structural and functional connectivity. Discussion: This work combined DTI, fMRI, and graph theory analysis to evaluate improvement with DBS. Several imaging biomarkers were identified that are robust predictors for UPDRS-III improvement. This work warrants investigation into the compensatory effect of the cerebellum and other potential biomarkers for identifying DBS candidates

Telomerase activation in nasopharyngeal carcinomas.

Nasopharyngeal carcinomas (NPC) are common in Hong Kong and southern China but rare in Western countries. Telomerase activation is common in human cancers but has not been reported previously in NPC. Telomerase activation in NPC was determined using the sensitive TRAP (telomerase rapid amplification protocol) assay in 45 nasopharyngeal biopsies (36 NPC, nine normal nasopharyngeal mucosae) in four xenografted NPC tumours established in nude mice and in five in vitro NPC cell lines. Telomerase activation is common in NPC and can be detected at high frequencies (85% in primary tumours and 100% in recurrent tumours). The frequency of telomerase activation was lowest in NPC biopsies without lymph node involvement (60%) compared with those with positive lymph node involvement (100%), and the difference is statistically significant (P < 0.05; Fisher exact test). All the xenografted NPC tumours and in vitro NPC cell lines were strongly positive for telomerase activity. Our results suggest that telomerase activation is common in NPC and it may be useful as a diagnostic marker in the detection of tumour cells in nasopharyngeal biopsies. The high frequency of telomerase activation in stage I NPC (80% positive) suggests that it is an early event in tumour progression

Molecular signature of clinical severity in recovering patients with severe acute respiratory syndrome coronavirus (SARS-CoV)

BACKGROUND: Severe acute respiratory syndrome (SARS), a recent epidemic human disease, is caused by a novel coronavirus (SARS-CoV). First reported in Asia, SARS quickly spread worldwide through international travelling. As of July 2003, the World Health Organization reported a total of 8,437 people afflicted with SARS with a 9.6% mortality rate. Although immunopathological damages may account for the severity of respiratory distress, little is known about how the genome-wide gene expression of the host changes under the attack of SARS-CoV. RESULTS: Based on changes in gene expression of peripheral blood, we identified 52 signature genes that accurately discriminated acute SARS patients from non-SARS controls. While a general suppression of gene expression predominated in SARS-infected blood, several genes including those involved in innate immunity, such as defensins and eosinophil-derived neurotoxin, were upregulated. Instead of employing clustering methods, we ranked the severity of recovering SARS patients by generalized associate plots (GAP) according to the expression profiles of 52 signature genes. Through this method, we discovered a smooth transition pattern of severity from normal controls to acute SARS patients. The rank of SARS severity was significantly correlated with the recovery period (in days) and with the clinical pulmonary infection score. CONCLUSION: The use of the GAP approach has proved useful in analyzing the complexity and continuity of biological systems. The severity rank derived from the global expression profile of significantly regulated genes in patients may be useful for further elucidating the pathophysiology of their disease

Counter-current chromatography for the separation of terpenoids: A comprehensive review with respect to the solvent systems employed

Copyright @ 2014 The Authors.This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.Natural products extracts are commonly highly complex mixtures of active compounds and consequently their purification becomes a particularly challenging task. The development of a purification protocol to extract a single active component from the many hundreds that are often present in the mixture is something that can take months or even years to achieve, thus it is important for the natural product chemist to have, at their disposal, a broad range of diverse purification techniques. Counter-current chromatography (CCC) is one such separation technique utilising two immiscible phases, one as the stationary phase (retained in a spinning coil by centrifugal forces) and the second as the mobile phase. The method benefits from a number of advantages when compared with the more traditional liquid-solid separation methods, such as no irreversible adsorption, total recovery of the injected sample, minimal tailing of peaks, low risk of sample denaturation, the ability to accept particulates, and a low solvent consumption. The selection of an appropriate two-phase solvent system is critical to the running of CCC since this is both the mobile and the stationary phase of the system. However, this is also by far the most time consuming aspect of the technique and the one that most inhibits its general take-up. In recent years, numerous natural product purifications have been published using CCC from almost every country across the globe. Many of these papers are devoted to terpenoids-one of the most diverse groups. Naturally occurring terpenoids provide opportunities to discover new drugs but many of them are available at very low levels in nature and a huge number of them still remain unexplored. The collective knowledge on performing successful CCC separations of terpenoids has been gathered and reviewed by the authors, in order to create a comprehensive document that will be of great assistance in performing future purifications. © 2014 The Author(s)

Randomized, Noncomparative, Phase II Trial of Early Switch From Docetaxel to Cabazitaxel or Vice Versa, With Integrated Biomarker Analysis, in Men With Chemotherapy-Naïve, Metastatic, Castration-Resistant Prostate Cancer

Purpose The TAXYNERGY trial ( ClinicalTrials.gov identifier: NCT01718353) evaluated clinical benefit from early taxane switch and circulating tumor cell (CTC) biomarkers to interrogate mechanisms of sensitivity or resistance to taxanes in men with chemotherapy-naïve, metastatic, castration-resistant prostate cancer. Patients and Methods Patients were randomly assigned 2:1 to docetaxel or cabazitaxel. Men who did not achieve ≥ 30% prostate-specific antigen (PSA) decline by cycle 4 (C4) switched taxane. The primary clinical endpoint was confirmed ≥ 50% PSA decline versus historical control (TAX327). The primary biomarker endpoint was analysis of post-treatment CTCs to confirm the hypothesis that clinical response was associated with taxane drug-target engagement, evidenced by decreased percent androgen receptor nuclear localization (%ARNL) and increased microtubule bundling. Results Sixty-three patients were randomly assigned to docetaxel (n = 41) or cabazitaxel (n = 22); 44.4% received prior potent androgen receptor-targeted therapy. Overall, 35 patients (55.6%) had confirmed ≥ 50% PSA responses, exceeding the historical control rate of 45.4% (TAX327). Of 61 treated patients, 33 (54.1%) had ≥ 30% PSA declines by C4 and did not switch taxane, 15 patients (24.6%) who did not achieve ≥ 30% PSA declines by C4 switched taxane, and 13 patients (21.3%) discontinued therapy before or at C4. Of patients switching taxane, 46.7% subsequently achieved ≥ 50% PSA decrease. In 26 CTC-evaluable patients, taxane-induced decrease in %ARNL (cycle 1 day 1 v cycle 1 day 8) was associated with a higher rate of ≥ 50% PSA decrease at C4 ( P = .009). Median composite progression-free survival was 9.1 months (95% CI, 4.9 to 11.7 months); median overall survival was not reached at 14 months. Common grade 3 or 4 adverse events included fatigue (13.1%) and febrile neutropenia (11.5%). Conclusion The early taxane switch strategy was associated with improved PSA response rates versus TAX327. Taxane-induced shifts in %ARNL may serve as an early biomarker of clinical benefit in patients treated with taxanes

MUC1-associated proliferation signature predicts outcomes in lung adenocarcinoma patients

Background: MUC1 protein is highly expressed in lung cancer. The cytoplasmic domain of MUC1 (MUC1-CD) induces tumorigenesis and resistance to DNA-damaging agents. We characterized MUC1-CD-induced transcriptional changes and examined their significance in lung cancer patients. Methods: Using DNA microarrays, we identified 254 genes that were differentially expressed in cell lines transformed by MUC1-CD compared to control cell lines. We then examined expression of these genes in 441 lung adenocarcinomas from a publicly available database. We employed statistical analyses independent of clinical outcomes, including hierarchical clustering, Student's t-tests and receiver operating characteristic (ROC) analysis, to select a seven-gene MUC1-associated proliferation signature (MAPS). We demonstrated the prognostic value of MAPS in this database using Kaplan-Meier survival analysis, log-rank tests and Cox models. The MAPS was further validated for prognostic significance in 84 lung adenocarcinoma patients from an independent database. Results: MAPS genes were found to be associated with proliferation and cell cycle regulation and included CCNB1, CDC2, CDC20, CDKN3, MAD2L1, PRC1 and RRM2. MAPS expressors (MAPS+) had inferior survival compared to non-expressors (MAPS-). In the initial data set, 5-year survival was 65% (MAPS-) vs. 45% (MAPS+, p < 0.0001). Similarly, in the validation data set, 5-year survival was 57% (MAPS-) vs. 28% (MAPS+, p = 0.005). Conclusions: The MAPS signature, comprised of MUC1-CD-dependent genes involved in the control of cell cycle and proliferation, is associated with poor outcomes in patients with adenocarcinoma of the lung. These data provide potential new prognostic biomarkers and treatment targets for lung adenocarcinoma

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types