The value of thromboelastography in evaluating the efficacy of Xueshuantong combined with edaravone in the treatment of acute cerebral infarction.

To explore the value of thromboelastography (TEG) in evaluating the efficacy of Xueshuantong combined with edaravone for the treatment of acute cerebral infarction (ACI). We retrospectively analyzed the clinical data of 96 patients with ACI treated with Xueshuantong combined with edaravone and monitored by TEG. The correlation between the results of TEG examination and treatment outcomes in patients after treatment was analyzed. After treatment, 65 of 96 patients showed good efficacy and 31 had poor efficacy. kinetic time (KT), reaction time (RT), and the percentage of clot lysis at 30 minutes after Ma value (LY30) of patients with good therapeutic effects were significantly higher than those with poor therapeutic effects; However, maximum amplitude (MA) and coagulation index (CI) were significantly lower than those with poor efficacy (P < .05). There was a significant positive correlation between KT, RT, and LY30 and the therapeutic effect of ACI, and a significant negative correlation between the therapeutic effects of MA, CI, and ACI (P < .05). Logistic analysis confirmed that KT, RT, and LY30 were protective factors for the therapeutic effect of ACI; MA and CI were risk factors for the therapeutic effect of ACI (P < .05). TEG has a high value in evaluating the efficacy of Xueshuantong combined with edaravone in the treatment of ACI. It can clarify changes in the coagulation function of patients, thereby guiding clinical follow-up treatment.

Regulating ion affinity and dehydration of metal-organic framework sub-nanochannels for high-precision ion separation.

Membrane consisting of ordered sub-nanochannels has been pursued in ion separation technology to achieve applications including desalination, environment management, and energy conversion. However, high-precision ion separation has not yet been achieved owing to the lack of deep understanding of ion transport mechanism in confined environments. Biological ion channels can conduct ions with ultrahigh permeability and selectivity, which is inseparable from the important role of channel size and "ion-channel" interaction. Here, inspired by the biological systems, we report the high-precision separation of monovalent and divalent cations in functionalized metal-organic framework (MOF) membranes (UiO-66-(X)2, X = NH2, SH, OH and OCH3). We find that the functional group (X) and size of the MOF sub-nanochannel synergistically regulate the ion binding affinity and dehydration process, which is the key in enlarging the transport activation energy difference between target and interference ions to improve the separation performance. The K+/Mg2+ selectivity of the UiO-66-(OCH3)2 membrane reaches as high as 1567.8. This work provides a gateway to the understanding of ion transport mechanism and development of high-precision ion separation membranes.

Recent Progress in the Application of Ion Beam Technology in the Modification and Fabrication of Nanostructured Energy Materials.

The development of green, renewable energy conversion and storage systems is an urgent task to address the energy crisis and environmental issues in the future. To achieve high performance, stable, and safe operation of energy conversion and storage systems, energy materials need to be modified and fabricated through rationalization. Among various modification and fabrication strategies, ion beam technology has been widely used to introduce various defects/dopants into energy materials and fabricate various nanostructures, where the structure, composition, and property of prefabricated materials can be further accurately tailored to achieve better performance. In this paper, we review the recent progress in the application of ion beam technology in material modification and fabrication, focusing on nanostructured energy materials for energy conversion and storage including photo- (electro-) water splitting, batteries (solar cells, fuel cells, and metal-ion batteries), supercapacitors, thermoelectrics, and hydrogen storage. This review first provides a brief basic overview of ion beam technology and describes the classification and technological advantages of ion beam technology in the modification and fabrication of materials. Then, modification of energy materials by ion beams is reviewed mainly concerning doping and defect introduction. Fabrication of energy materials is also discussed mainly in terms of heterojunctions, nanoparticles, nanocavities, and other nanostructures. In particular, we emphasize the advantages of ion beam technology in improving the performance of energy materials. Finally, we point out our understanding of challenges and future perspectives in applying ion beam technology for the modification and fabrication of energy materials.

Janus Metal-Organic Framework Membranes Boosting the Osmotic Energy Harvesting.

The unique ion-transport properties in nanoconfined pores enable nanofluidic devices with great potential in harvesting osmotic energy. The energy conversion performance could be significantly improved by the precise regulation of the "permeability-selectivity" trade-off and the ion concentration polarization effect. Here, we take the advantage of electrodeposition technique to fabricate a Janus metal-organic framework (J-MOF) membrane that possesses rapid ion-transport capability and impeccable ion selectivity. The asymmetric structure and asymmetric surface charge distribution of the J-MOF device can suppress the ion concentration polarization effect and enhance the ion charge separation, exhibiting an improved energy harvesting performance. An output power density of 3.44 W/m2 has been achieved with the J-MOF membrane at a 1000-fold concentration gradient. This work provides a new strategy for fabricating high-performance energy-harvesting devices.

Homochiral Zeolitic Imidazolate Framework with Defined Chiral Microenvironment for Electrochemical Enantioselective Recognition.

The recognition and separation of chiral molecules with similar structure are of great industrial and biological importance. Development of highly efficient chiral recognition systems is crucial for the precise application of these chiral molecules. Herein, a homochiral zeolitic imidazolate frameworks (c-ZIF) functionalized nanochannel device that exhibits an ideal platform for electrochemical enantioselective recognition is reported. Its distinct chiral binding cavity enables more sensitive discrimination of tryptophan (Trp) enantiomer pairs than other smaller chiral amino acids owing to its size matching to the target molecule. It is found that introducing neighboring aldehyde groups into the chiral cavity will result in an inferior chiral Trp recognition due to the decreased adsorption-energy difference of D- and L-Trp on the chiral sites. This study may provide an alternative strategy for designing efficient chiral recognition devices by utilizing the homochiral reticular materials and tailoring their chiral environments.

Single-cell thermometry with a nanothermocouple probe.

Herein, a nanopipette-based thermocouple probe that possesses high temperature resolution, rapid response, good reversibility and stability was constructed and successfully applied for single-cell temperature sensing. Different intracellular temperatures were observed in diverse types of cells, which reveals differences in their metabolism levels. Temperature responses of cancer and normal cells against various exogenous drugs were also demonstrated. The spatially resolved temperature sensing of three-dimensional cell culture models unveils the existence of their inner temperature gradients. This work would facilitate drug screening and disease diagnosis.

Light-Enhanced Osmotic Energy Harvester Using Photoactive Porphyrin Metal-Organic Framework Membranes.

High ion selectivity and permeability, as two contradictory aspects for the membrane design, highly hamper the development of osmotic energy harvesting technologies. Metal-organic frameworks (MOFs) with ultra-small and high-density pores and functional surface groups show great promise in tackling these problems. Here, we propose a facile and mild cathodic deposition method to directly prepare crack-free porphyrin MOF membranes on a porous anodic aluminum oxide for osmotic energy harvesting. The abundant carboxyl groups of the functionalized porphyrin ligands together with the nanoporous structure endows the MOF membrane with high cation selectivity and ion permeability, thus a large output power density of 6.26 W m-2 is achieved. The photoactive porphyrin ligands further lead to an improvement of the power density to 7.74 W m-2 upon light irradiation. This work provides a promising strategy for the design of high-performance osmotic energy harvesting systems.

Electrochemically Switchable Double-Gate Nanofluidic Logic Device as Biomimetic Ion Pumps.

Biological ion pumps with two separate gates can actively transport ions against the concentration gradient. Developing an artificial nanofluidic device with multiple responsive sites is of great importance to improve its controllability over ion transport to further explore its logic function and mimic the biological process. Here, we propose an electrochemical polymerization method to fabricate electrochemically switchable double-gate nanofluidic devices. The ion transport of the double-gate nanofluidic device can be in situ and reversibly switched among four different states. The logic function of this nanofluidic device is systematically investigated by assuming the gate state as the input and the transmembrane ionic conductance as the output. A biomimetic electrochemical ion pump is then established by alternately applying two different specific logic combinations, realizing an active ion transport under a concentration gradient. This work would inspire further studies to construct complex logical networks and explore bioinspired ion pump systems.

Risk factors associated with loss to follow-up of breast cancer patients: A retrospective analysis.

BACKGROUND: Loss to follow-up (LTFU) during post-operative surveillance of breast cancer patients is detrimental. The pattern of LTFU and its risk factors in Chinese breast cancer patients remains unknown. METHOD: Eligible non-metastatic breast cancer patients who underwent surgery at our institution between 2009 and 2012 were included. The clinicopathological features, as well as the LTFU status, were retrieved from the REDCap database. LTFU was defined as the absence of patients for at least 12 months since her last contact. 5-year LTFU was defined as the LTFU status of each patients at 5 years after surgery. The incidence and potential risk factors of LTFU were analyzed. A LTFU-risk score was developed to quantify the risk of LTFU. RESULTS: A total of 1536 patients with breast cancer were included, and 411(26.8%) patients were 5-year LTFU. 198 patients were LTFU in the first year. Univariate and multivariate analysis revealed that age (younger and older), a lack of medical insurance, longer distance from residence to the hospital, pathology (DCIS/Paget's/Phyllodes), lymph node metastasis, the absence of endocrine therapy and fewer than five contact numbers were significantly and independently associated with the risk of LTFU. A LTFU-risk score was developed and was predictive of LTFU. CONCLUSIONS: A series of risk factors were significantly associated with post-operative LTFU of breast cancer patients. Patients with different risks of LTFU could possibly be identified, and surveillance plans could be individualized for different patients, so as to effectively reduce the overall LTFU rate, and optimize the allocation of medical resources.

Highly Selective Fluorescent Probe Based on Hydroxylation of Phenylboronic Acid Pinacol Ester for Detection of Tyrosinase in Cells.

The detection of tyrosinase, a biomarker for melanoma, is of great significance. Herein, a fluorescent tyrosinase probe, with resorufin as the fluorophore and m-tolylboronic acid pinacol ester as the receptor, is proposed. The response relies on the tyrosinase-catalyzed hydroxylation of phenylboronic acid pinacol ester at an adjacent position followed by 1,6-rearrangement elimination to release resorufin. This probe well quantifies tyrosinase in the range from 1 to 100 U mL-1 with a detection limit of 0.5 U mL-1. Importantly, the probe exhibits high selectivity for tyrosinase over other biological substances including reactive oxygen species. In addition, it is successfully applied to the imaging of tyrosinase in cells. This probe provides a novel platform for selective detection of tyrosinase in biosystems.

Identifying the gene signatures from gene-pathway bipartite network guarantees the robust model performance on predicting the cancer prognosis.

For the purpose of improving the prediction of cancer prognosis in the clinical researches, various algorithms have been developed to construct the predictive models with the gene signatures detected by DNA microarrays. Due to the heterogeneity of the clinical samples, the list of differentially expressed genes (DEGs) generated by the statistical methods or the machine learning algorithms often involves a number of false positive genes, which are not associated with the phenotypic differences between the compared clinical conditions, and subsequently impacts the reliability of the predictive models. In this study, we proposed a strategy, which combined the statistical algorithm with the gene-pathway bipartite networks, to generate the reliable lists of cancer-related DEGs and constructed the models by using support vector machine for predicting the prognosis of three types of cancers, namely, breast cancer, acute myeloma leukemia, and glioblastoma. Our results demonstrated that, combined with the gene-pathway bipartite networks, our proposed strategy can efficiently generate the reliable cancer-related DEG lists for constructing the predictive models. In addition, the model performance in the swap analysis was similar to that in the original analysis, indicating the robustness of the models in predicting the cancer outcomes.

Improving the prediction of chemotherapeutic sensitivity of tumors in breast cancer via optimizing the selection of candidate genes.

Estrogen receptor status and the pathologic response to preoperative chemotherapy are two important indicators of chemotherapeutic sensitivity of tumors in breast cancer, which are used to guide the selection of specific regimens for patients. Microarray-based gene expression profiling, which is successfully applied to the discovery of tumor biomarkers and the prediction of drug response, was suggested to predict the cancer outcomes using the gene signatures differentially expressed between two clinical states. However, many false positive genes unrelated to the phenotypic differences will be involved in the lists of differentially expressed genes (DEGs) when only using the statistical methods for gene selection, e.g. Student's t test, and subsequently affect the performance of the predictive models. For the purpose of improving the prediction of clinical outcomes, we optimized the selection of DEGs by using a combined strategy, for which the DEGs were firstly identified by the statistical methods, and then filtered by a similarity profiling approach that used for candidate gene prioritization. In our study, we firstly verified the molecular functions of the DEGs identified by the combined strategy with the gene expression data generated in the microarray experiments of Si-Wu-Tang, which is a popular formula in traditional Chinese medicine. The results showed that, for Si-Wu-Tang experimental data set, the cancer-related signaling pathways were significantly enriched by gene set enrichment analysis when using the DEG lists generated by the combined strategy, confirming the potentially cancer-preventive effect of Si-Wu-Tang. To verify the performance of the predictive models in clinical application, we used the combined strategy to select the DEGs as features from the gene expression data of the clinical samples, which were collected from the breast cancer patients, and constructed models to predict the chemotherapeutic sensitivity of tumors in breast cancer. After refining the DEG lists by a similarity profiling approach, the Matthew's correlation coefficients of predicting estrogen receptor status and the pathologic response to preoperative chemotherapy with the DEGs selected by the fold change ranking were 0.770 and 0.428, respectively, and were 0.748 and 0.373 with the DEGs selected by SAM, respectively, which were generally higher than those achieved with unrefined DEG lists and those achieved by the candidate models in the second phase of Microarray Quality Control project (0.732 and 0.301, respectively). Our results demonstrated that the strategy of integrating the statistical methods with the gene prioritization methods based on similarity profiling was a powerful tool for DEG selection, which effectively improved the performance of prediction models in clinical applications and can guide the personalized chemotherapy better.