Adjuvant chemotherapy after surgery improves survival of patients with stage II–III, resectable gastric cancer. However, the overall survival benefit observed after adjuvant chemotherapy is moderate, ...suggesting that not all patients with resectable gastric cancer treated with adjuvant chemotherapy benefit from it. We aimed to develop and validate a predictive test for adjuvant chemotherapy response in patients with resectable, stage II–III gastric cancer.
In this multi-cohort, retrospective study, we developed through a multi-step strategy a predictive test consisting of two rule-based classifier algorithms with predictive value for adjuvant chemotherapy response and prognosis. Exploratory bioinformatics analyses identified biologically relevant candidate genes in gastric cancer transcriptome datasets. In the discovery analysis, a four-gene, real-time RT-PCR assay was developed and analytically validated in formalin-fixed, paraffin-embedded (FFPE) tumour tissues from an internal cohort of 307 patients with stage II–III gastric cancer treated at the Yonsei Cancer Center with D2 gastrectomy plus adjuvant fluorouracil-based chemotherapy (n=193) or surgery alone (n=114). The same internal cohort was used to evaluate the prognostic and chemotherapy response predictive value of the single patient classifier genes using associations with 5-year overall survival. The results were validated with a subset (n=625) of FFPE tumour samples from an independent cohort of patients treated in the CLASSIC trial (NCT00411229), who received D2 gastrectomy plus capecitabine and oxaliplatin chemotherapy (n=323) or surgery alone (n=302). The primary endpoint was 5-year overall survival.
We identified four classifier genes related to relevant gastric cancer features (GZMB, WARS, SFRP4, and CDX1) that formed the single patient classifier assay. In the validation cohort, the prognostic single patient classifier (based on the expression of GZMB, WARS, and SFRP4) identified 79 (13%) of 625 patients as low risk, 296 (47%) as intermediate risk, and 250 (40%) as high risk, and 5-year overall survival for these groups was 83·2% (95% CI 75·2–92·0), 74·8% (69·9–80·1), and 66·0% (60·1–72·4), respectively (p=0·012). The predictive single patient classifier (based on the expression of GZMB, WARS, and CDX1) assigned 281 (45%) of 625 patients in the validation cohort to the chemotherapy-benefit group and 344 (55%) to the no-benefit group. In the predicted chemotherapy-benefit group, 5-year overall survival was significantly improved in those patients who had received adjuvant chemotherapy after surgery compared with those who received surgery only (80% 95% CI 73·5–87·1 vs 64·5% 56·8–73·3; univariate hazard ratio 0·47 95% CI 0·30–0·75, p=0·0015), whereas no such improvement in 5-year overall survival was observed in the no-benefit group (72·9% 66·5–79·9 in patients who received chemotherapy plus surgery vs 72·5% 65·8–79·9 in patients who only had surgery; 0·93 0·62–1·38, p=0·71). The predictive single patient classifier groups (chemotherapy benefit vs no-benefit) could predict adjuvant chemotherapy benefit in terms of 5-year overall survival in the validation cohort (pinteraction=0·036 in univariate analysis). Similar results were obtained in the internal evaluation cohort.
The single patient classifiers validated in this study provide clinically important prognostic information independent of standard risk-stratification methods and predicted chemotherapy response after surgery in two independent cohorts of patients with resectable, stage II–III gastric cancer. The single patient classifiers could complement TNM staging to optimise decision making in patients with resectable gastric cancer who are eligible for adjuvant chemotherapy after surgery. Further validation of these results in prospective studies is warranted.
Ministry of ICT and Future Planning; Ministry of Trade, Industry, and Energy; and Ministry of Health and Welfare.
Coronavirus disease 2019 (COVID-19) is a global pandemic that had affected more than eight million people worldwide by June 2020. Given the importance of the presence of diabetes mellitus (DM) for ...host immunity, we retrospectively evaluated the clinical characteristics and outcomes of moderate-to-severe COVID-19 in patients with diabetes.
We conducted a multi-center observational study of 1,082 adult inpatients (aged ≥18 years) who were admitted to one of five university hospitals in Daegu because of the severity of their COVID-19-related disease. The demographic, laboratory, and radiologic findings, and the mortality, prevalence of severe disease, and duration of quarantine were compared between patients with and without DM. In addition, 1:1 propensity score (PS)-matching was conducted with the DM group.
Compared with the non-DM group (
=847), patients with DM (
=235) were older, exhibited higher mortality, and required more intensive care. Even after PS-matching, patients with DM exhibited more severe disease, and DM remained a prognostic factor for higher mortality (hazard ratio, 2.40; 95% confidence interval, 1.38 to 4.15). Subgroup analysis revealed that the presence of DM was associated with higher mortality, especially in older people (≥70 years old). Prior use of a dipeptidyl peptidase-4 inhibitor or a renin-angiotensin system inhibitor did not affect mortality or the clinical severity of the disease.
DM is a significant risk factor for COVID-19 severity and mortality. Our findings imply that COVID-19 patients with DM, especially if elderly, require special attention and prompt intensive care.
Pyroelectric energy harvesting systems have recently received substantial attention for their potential applications as power generators. In particular, the pyroelectric effect, which converts ...thermal energy into electrical energy, has been utilized as an infrared (IR) sensor, but upcoming sensor technology that requires a miniscule amount of power is able to utilize pyroelectric nanogenerators (PyNGs) as a power source. Herein, an overview of the progress in the development of PyNGs for an energy harvesting system that uses environmental or artificial energies such as the sun, body heat, and heaters, is provided. It begins with a brief introduction of the pyroelectric effect, and various polymer and ceramic materials based PyNGs are reviewed in detail. Various approaches for developing polymer‐based PyNGs and various ceramic materials–based PyNGs are summarized in particular. Finally, challenges and perspectives regarding the PyNGs are described.
Converting thermal energy into electrical energy using pyroelectric nanogenerators is a promising technology to utilize abundant thermal energy. Herein, a variety of polymers and ceramic‐based flexible, stretchable, and hybrid pyroelectric nanogenerators are reviewed. The working mechanism of the pyroelectric nanogenerators is provided, and a perspective for high performance pyroelectric nanogenerators is presented.
2D transition metal dichalcogenides (TMDs) have attracted much attention for their gas sensing applications due to their superior responsivity at typical room temperature. However, low power ...consumption and reliable selectivity are the two main requirements for gas sensors to be applicable in future electronic devices. Herein, a p‐type (WSe2/WS2) and n‐type (MoS2/WSe2) photovoltaic self‐powered gas sensor is demonstrated using 2D TMD heterostructures for the first time. The gas sensors are operated by the photovoltaic effect of 2D TMD heterostructures, which are uniformly synthesized by the vacuum‐based synthesis. The gas sensing properties of the WSe2/WS2 and MoS2/WSe2 heterostructure gas sensors are investigated for NO2 and NH3 with changing gas concentration, and each sensor exhibits selectivity to NO2 and NH3. From the results, it is confirmed that the 2D TMD heterostructures can be a viable platform for highly sensitive, selective gas sensor applications without external bias due to their photovoltaic features. Further, this study contributes toward revealing the gas sensor mechanism in 2D TMD heterostructure.
A photovoltaic self‐powered gas sensor is demonstrated using a 2D transition metal dichalcogenide (TMD) heterostructure. Depending on the surface layer, p‐ and n‐type gas sensors are fabricated with selectivity to NO2 and NH3 gas. In addition, this study contributes toward revealing the sensing mechanism in 2D TMD heterostructures.
Metal‐halide perovskites present exceptional optoelectronic properties such as large light absorption coefficients, long free charge carrier diffusion lengths with ambipolar character. They are ...apparently protected by what is often described as a “defect tolerance” which has allowed to achieve, relatively quickly, highly performing devices. Nevertheless, there also exists a “defect intolerance” when it is dealt with stability. Further rationalization of the passivation strategies, especially for complex chemical systems, will be beneficial to achieve a full materials library which can be the platform for an efficient and reliable technology.
Defect tolerance of metal‐halide perovskites is a commonly evoked concept to explain the development of high efficiency solar cells upon solution processing. However, moving the attention to solar cell stability, these materials seem to be defect intolerant. Further material engineering is needed to obtain a 100% defect tolerant materials platform.
Recently, sustainable green energy harvesting systems have been receiving great attention for their potential use in self‐powered smart wireless sensor network (WSN) systems. In particular, though ...the developed WSN systems are able to advance public good, very high and long‐term budgets will be required in order to use them to supply electrical energy through temporary batteries or connecting power cables. This report summarizes recent significant progress in the development of hybrid nanogenerators for a sustainable energy harvesting system that use natural and artificial energies such as solar, wind, wave, heat, machine vibration, and automobile noise. It starts with a brief introduction of energy harvesting systems, and then summarizes the different hybrid energy harvesting systems: integration of mechanical and photovoltaic energy harvesters, integration of mechanical and thermal energy harvesters, integration of thermal and photovoltaic energy harvesters, and others. In terms of the reported hybrid nanogenerators, a systematic summary of their structures, working mechanisms, and output performances is provided. Specifically, electromagnetic induction, triboelectric, piezoelectric, photovoltaic, thermoelectric, and pyroelectric effects are reviewed on the basis of the individual and hybrid power performances of hybrid nanogenerators and their practical applications with various device designs. Finally, the perspectives on and challenges in developing high performance and sustainable hybrid nanogenerator systems are presented.
Recent progress in the development of sustainable hybrid nanogenerators is summarized, by focusing on the integration of mechanical and photovoltaic energy harvesters, integration of mechanical and thermal energy harvesters, integration of thermal and photovoltaic energy harvesters, and others. The working mechanism of the hybrid nanogenerators is provided, and challenges and perspectives for a high‐performance sustainable hybrid nanogenerator systems are presented.
Plasmonic high-harmonic generation (HHG) drew attention as a means of producing coherent extreme ultraviolet (EUV) radiation by taking advantage of field enhancement occurring in metallic ...nanostructures. Here a metal-sapphire nanostructure is devised to provide a solid tip as the HHG emitter, replacing commonly used gaseous atoms. The fabricated solid tip is made of monocrystalline sapphire surrounded by a gold thin-film layer, and intended to produce EUV harmonics by the inter- and intra-band oscillations of electrons driven by the incident laser. The metal-sapphire nanostructure enhances the incident laser field by means of surface plasmon polaritons, triggering HHG directly from moderate femtosecond pulses of ∼0.1 TW cm
intensities. The measured EUV spectra exhibit odd-order harmonics up to ∼60 nm wavelengths without the plasma atomic lines typically seen when using gaseous atoms as the HHG emitter. This experimental outcome confirms that the plasmonic HHG approach is a promising way to realize coherent EUV sources for nano-scale near-field applications in spectroscopy, microscopy, lithography and atto-second physics.
Machine learning based on big data has emerged as a powerful solution in various chemical problems. We investigated the feasibility of machine learning models for the prediction of activation ...energies of gas‐phase reactions. Six different models with three different types, including the artificial neural network, the support vector regression, and the tree boosting methods, were tested. We used the structural and thermodynamic properties of molecules and their differences as input features without resorting to specific reaction types so as to maintain the most general input form for broad applicability. The tree boosting method showed the best performance among others in terms of the coefficient of determination, mean absolute error, and root mean square error, the values of which were 0.89, 1.95, and 4.49 kcal mol−1, respectively. Computation time for the prediction of activation energies for 2541 test reactions was about one second on a single computing node without using accelerators.
Activation energy prediction: The performance of various machine learning models for prediction of activation energies of gas‐phase reactions was examined. Fast prediction with desirable accuracy was feasible by using only the thermodynamic and structural properties of reactants and products without knowing the reaction paths. The tree boosting method showed the best performance (mean absolute error=1.95 kcal mol−1) over the artificial neural network and supporting vector regression methods.
This review focuses on the recent development and various strategies in the preparation, microstructure, and magnetic properties of bare and surface functionalized iron oxide nanoparticles (IONPs); ...their corresponding biological application was also discussed. In order to implement the practical in vivo or in vitro applications, the IONPs must have combined properties of high magnetic saturation, stability, biocompatibility, and interactive functions at the surface. Moreover, the surface of IONPs could be modified by organic materials or inorganic materials, such as polymers, biomolecules, silica, metals, etc. The new functionalized strategies, problems and major challenges, along with the current directions for the synthesis, surface functionalization and bioapplication of IONPs, are considered. Finally, some future trends and the prospects in these research areas are also discussed.
We propose a molecular generative model based on the conditional variational autoencoder for de novo molecular design. It is specialized to control multiple molecular properties simultaneously by ...imposing them on a latent space. As a proof of concept, we demonstrate that it can be used to generate drug-like molecules with five target properties. We were also able to adjust a single property without changing the others and to manipulate it beyond the range of the dataset.
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