Low Pressure Ethenolysis of Renewable Methyl Oleate in a Microchemical System

A microchemical system for ethenolysis of renewable methyl oleate was developed, in which the dual-phase, microfluidic design enabled efficient diffusion of ethylene gas into liquid methyl oleate through an increased contact area. The increased mass transfer of ethylene favored the formation of desired commodity chemicals with significantly suppressed homometathesis when compared to the bulk system. In addition to higher selectivity and conversion, this system also provides the typical advantages of a microchemical system, including the possibility of convenient scale-up

Predictive Capability of Anorectal Physiologic Tests for Unfavorable Outcomes Following Biofeedback Therapy in Dyssynergic Defecation

The purpose of this study is to evaluate the predictive capability of anorectal physiologic tests for unfavorable outcomes prior to the initiation of biofeedback therapy in patients with dyssynergic defecation. We analyzed a total of 80 consecutive patients who received biofeedback therapy for chronic idiopathic functional constipation with dyssynergic defecation. After classifying the patients into two groups (responders and non-responders), univariate and multivariate analyses were performed to determine the predictors associated with the responsiveness to biofeedback therapy. Of the 80 patients, 63 (78.7%) responded to biofeedback therapy and 17 (21.3%) did not. On univariate analysis, the inability to evacuate an intrarectal balloon (P=0.028), higher rectal volume for first, urgent, and maximal sensation (P=0.023, P=0.008, P=0.007, respectively), and increased anorectal angle during squeeze (P=0.020) were associated with poor outcomes. On multivariate analysis, the inability to evacuate an intrarectal balloon (P=0.018) and increased anorectal angle during squeeze (P=0.029) were both found to be independently associated with a lack of response to biofeedback therapy. Our data show that the two anorectal physiologic test factors are associated with poor response to biofeedback therapy for patients with dyssynergic defecation. These findings may assist physicians in predicting the responsiveness to therapy for this patient population

Atomic-layer-confined multiple quantum wells enabled by monolithic bandgap engineering of transition metal dichalcogenides

Quantum wells (QWs), enabling effective exciton confinement and strong light-matter interaction, form an essential building block for quantum optoelectronics. For two-dimensional (2D) semiconductors, however, constructing the QWs is still challenging because suitable materials and fabrication techniques are lacking for bandgap engineering and indirect bandgap transitions occur at the multilayer. Here, we demonstrate an unexplored approach to fabricate atomic-layer-confined multiple QWs (MQWs) via monolithic bandgap engineering of transition metal dichalcogenides and van der Waals stacking. The WOX/WSe2 hetero-bilayer formed by monolithic oxidation of the WSe2 bilayer exhibited the type I band alignment, facilitating as a building block for MQWs. A superlinear enhancement of photoluminescence with increasing the number of QWs was achieved. Furthermore, quantum-confined radiative recombination in MQWs was verified by a large exciton binding energy of 193 meV and a short exciton lifetime of 170 ps. This work paves the way toward monolithic integration of band-engineered hetero-structures for 2D quantum optoelectronics

Genetic Susceptibility on CagA-Interacting Molecules and Gene-Environment Interaction with Phytoestrogens: A Putative Risk Factor for Gastric Cancer

OBJECTIVES: To evaluate whether genes that encode CagA-interacting molecules (SRC, PTPN11, CRK, CRKL, CSK, c-MET and GRB2) are associated with gastric cancer risk and whether an interaction between these genes and phytoestrogens modify gastric cancer risk. METHODS: In the discovery phase, 137 candidate SNPs in seven genes were analyzed in 76 incident gastric cancer cases and 322 matched controls from the Korean Multi-Center Cancer Cohort. Five significant SNPs in three genes (SRC, c-MET and CRK) were re-evaluated in 386 cases and 348 controls in the extension phase. Odds ratios (ORs) for gastric cancer risk were estimated adjusted for age, smoking, H. pylori seropositivity and CagA strain positivity. Summarized ORs in the total study population (462 cases and 670 controls) were presented using pooled- and meta-analysis. Plasma concentrations of phytoestrogens (genistein, daidzein, equol and enterolactone) were measured using the time-resolved fluoroimmunoassay. RESULTS: SRC rs6122566, rs6124914, c-MET rs41739, and CRK rs7208768 showed significant genetic effects for gastric cancer in both the pooled and meta-analysis without heterogeneity (pooled OR = 3.96 [95% CI 2.05-7.65], 1.24 [95% CI = 1.01-1.53], 1.19 [95% CI = 1.01-1.41], and 1.37 [95% CI = 1.15-1.62], respectively; meta OR = 4.59 [95% CI 2.74-7.70], 1.36 [95% CI = 1.09-1.70], 1.20 [95% CI = 1.00-1.44], and 1.32 [95% CI = 1.10-1.57], respectively). Risk allele of CRK rs7208768 had a significantly increased risk for gastric cancer at low phytoestrogen levels (p interaction<0.05). CONCLUSIONS: Our findings suggest that SRC, c-MET and CRK play a key role in gastric carcinogenesis by modulating CagA signal transductions and interaction between CRK gene and phytoestrogens modify gastric cancer risk

The multiplex bead array approach to identifying serum biomarkers associated with breast cancer

Introduction Breast cancer is the most common type of cancer seen in women in western countries. Thus, diagnostic modalities sensitive to early-stage breast cancer are needed. Antibody-based array platforms of a data-driven type, which are expected to facilitate more rapid and sensitive detection of novel biomarkers, have emerged as a direct, rapid means for profiling cancer-specific signatures using small samples. In line with this concept, our group constructed an antibody bead array panel for 35 analytes that were selected during the discovery step. This study was aimed at testing the performance of this 35-plex array panel in profiling signatures specific for primary non-metastatic breast cancer and validating its diagnostic utility in this independent population. Methods Thirty-five analytes were selected from more than 50 markers through screening steps using a serum bank consisting of 4,500 samples from various types of cancer. An antibody-bead array of 35 markers was constructed using the Luminex (TM) bead array platform. A study population consisting of 98 breast cancer patients and 96 normal subjects was analysed using this panel. Multivariate classification algorithms were used to find discriminating biomarkers and validated with another independent population of 90 breast cancer and 79 healthy controls. Results Serum concentrations of epidermal growth factor, soluble CD40-ligand and proapolipoprotein A1 were increased in breast cancer patients. High-molecular-weight-kininogen, apolipoprotein A1, soluble vascular cell adhesion molecule-1, plasminogen activator inhibitor-1, vitamin-D binding protein and vitronectin were decreased in the cancer group. Multivariate classification algorithms distinguished breast cancer patients from the normal population with high accuracy (91.8% with random forest, 91.5% with support vector machine, 87.6% with linear discriminant analysis). Combinatorial markers also detected breast cancer at an early stage with greater sensitivity. Conclusions The current study demonstrated the usefulness of the antibody-bead array approach in finding signatures specific for primary non-metastatic breast cancer and illustrated the potential for early, high sensitivity detection of breast cancer. 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AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Search for gravitational-lensing signatures in the full third observing run of the LIGO-Virgo network

Gravitational lensing by massive objects along the line of sight to the source causes distortions of gravitational wave-signals; such distortions may reveal information about fundamental physics, cosmology and astrophysics. In this work, we have extended the search for lensing signatures to all binary black hole events from the third observing run of the LIGO--Virgo network. We search for repeated signals from strong lensing by 1) performing targeted searches for subthreshold signals, 2) calculating the degree of overlap amongst the intrinsic parameters and sky location of pairs of signals, 3) comparing the similarities of the spectrograms amongst pairs of signals, and 4) performing dual-signal Bayesian analysis that takes into account selection effects and astrophysical knowledge. We also search for distortions to the gravitational waveform caused by 1) frequency-independent phase shifts in strongly lensed images, and 2) frequency-dependent modulation of the amplitude and phase due to point masses. None of these searches yields significant evidence for lensing. Finally, we use the non-detection of gravitational-wave lensing to constrain the lensing rate based on the latest merger-rate estimates and the fraction of dark matter composed of compact objects