Nontrivial Periodic Solutions for Nonlinear Second-Order Difference Equations

This paper is concerned with the existence of nontrivial periodic solutions and positive periodic solutions to a nonlinear second-order difference equation. Under some conditions concerning the first positive eigenvalue of the linear equation corresponding to the nonlinear second-order equation, we establish the existence results by using the topological degree and fixed point index theories

Hierarchical Co2P microspheres assembled from nanorods grown on reduced graphene oxide as anode material for Lithium-ion batteries

Transition metal phosphides (TMPs) have been studied as promising electrodes for energy storage and conversion due to their large theoretical capacities and high activities. Herein, a hierarchically structured Co2P coupling with the reduced graphene oxide (RGO) composite (Co2P/RGO) was synthesized by a simple solid state method for Li storage. The Co2P/RGO hybrid composite exhibits a high reversible capacity of 61 mAh g−1 at 60 mA g−1, good rate capability of 327 mAh g−1 at 3000 mA g−1 and long cycle life (397 mAh g−1 at 500 mA g−1 for after 1000 cycles). The excellent electrochemical performance can be attributed to the synergistic effect of Co2P micro/nano architecture and graphene modulation, which provide more activity sites for Li+-ions and maintain the structural integrity of active material. This work may provide a new path for preparation of other metal phosphides as potential electrode materials for application in energy storage fields

Clusterin is a potential molecular predictor for ovarian cancer patient's survival: targeting Clusterin improves response to paclitaxel

<p>Abstract</p> <p>Background</p> <p>Clusterin is a cytoprotective chaperone protein involved in numerous physiological processes, carcinogenesis, tumor growth and tissue remodelling. The purpose of this study was to investigate whether clusterin (CLU), an antiapoptotic molecule, could be a potential predictor molecule for ovarian cancer and whether or not targeting this molecule can improve survival of ovarian cancer patients.</p> <p>Methods</p> <p>Clusterin expression was compared between ten primary and their recurrent tumors from same patients immunohistochemically. We analyzed prognostic significance of CLU expression in another 47 ovarian cancer tissue samples by immunohistochemistry. We used small interference RNA to knock down CLU in the chemo-resistant ovarian cancer cell lines. KF-TX and SKOV-3-TX, paclitaxel-resistant ovarian cancer cells, were established from parental KF and SKOV-3 chemo-sensitive cell lines, respectively. Either siRNA or second generation antisense oligodeoxynucleotide against CLU (OGX-011), which is currently evaluated in clinical phase II trials in other cancer s, was used to modulate sensitivity to paclitaxel (TX) in ovarian cancer cells <it>in vitro</it>. Cellular viability assay, FACS analysis and annexin V staining were used to evaluate the comparative effect of CLU knocking down in ovarian cancer cells.</p> <p>Results</p> <p>Immunohistochemical analysis of CLU expression in primary ovarian cancer tissue specimens and their recurrent counterparts from same patients demonstrated higher expression of CLU in the recurrent resistant tumors compared with their primary tumors. High expression of CLU by immunohistochemistry among 47 surgical tissue specimens of early-stage (stage I/II) ovarian cancer, who underwent complete cytoreduction as a primary surgery, significantly related to poor survival, while none of other clinicopathological factors analyzed were related to survival in this patient cohort. Secretory CLU (s-CLU; 60 KDa) expression was upregulated in TX-resistant ovarian cancer cells compared to parental cells. Transfection of siRNA or OGX-011 clearly reduced CLU expression. Cell viability assay, FACS analysis and annexin V staining demonstrated that targeting CLU expression by siRNA or OGX-011 sensitized ovarian cancer cells to TX.</p> <p>Conclusion</p> <p>We conclude that CLU could be a potential molecular target to predict survival while targeting this s-CLU may improve survival of patients with ovarian cancer.</p

Monitoring response to neoadjuvant therapy for breast cancer in all treatment phases using an ultrasound deep learning model

PurposeThe aim of this study was to investigate the value of a deep learning model (DLM) based on breast tumor ultrasound image segmentation in predicting pathological response to neoadjuvant chemotherapy (NAC) in breast cancer.MethodsThe dataset contains a total of 1393 ultrasound images of 913 patients from Renmin Hospital of Wuhan University, of which 956 ultrasound images of 856 patients were used as the training set, and 437 ultrasound images of 57 patients underwent NAC were used as the test set. A U-Net-based end-to-end DLM was developed for automatically tumor segmentation and area calculation. The predictive abilities of the DLM, manual segmentation model (MSM), and two traditional ultrasound measurement methods (longest axis model [LAM] and dual-axis model [DAM]) for pathological complete response (pCR) were compared using changes in tumor size ratios to develop receiver operating characteristic curves.ResultsThe average intersection over union value of the DLM was 0.856. The early-stage ultrasound-predicted area under curve (AUC) values of pCR were not significantly different from those of the intermediate and late stages (p&lt; 0.05). The AUCs for MSM, DLM, LAM and DAM were 0.840, 0.756, 0.778 and 0.796, respectively. There was no significant difference in AUC values of the predictive ability of the four models.ConclusionUltrasonography was predictive of pCR in the early stages of NAC. DLM have a similar predictive value to conventional ultrasound for pCR, with an add benefit in effectively improving workflow

The effects of pharmaceutical interventions on potentially inappropriate medications in older patients: a systematic review and meta-analysis

IntroductionPotentially inappropriate medications (PIMs) is a particular concern in older patients and is associated with negative health outcomes. As various interventions have been developed to manage it, we performed a systematic review and meta-analysis to evaluate the effect of pharmaceutical interventions on outcomes of PIMs in older patients.MethodsMeta-analysis of eligible randomized controlled trials (RCTs) was conducted to report the outcomes of pharmaceutical interventions in older patients searching from the databases of Cochrane Library, PubMed, Embase, Web of Science, Clinicaltrials.gov, SinoMed and Chinese Clinical Trial Registry (ChiCTR). The PRISMA guidelines were followed and the protocol was registered in PROSPERO (CRD42019134754). Cochrane bias risk assessment tool and the modified Jadad scale were used to assess the risk bias. RevMan software was used for data processing, analysis and graphical plotting.ResultsSixty-five thousand, nine hundred seventy-one patients in 14 RCTs were included. Of the primary outcomes, pharmaceutical interventions could significantly reduce the incidence of PIMs in older patients (OR = 0.51, 95% CI: 0.42, 0.62; p &lt; 0.001), and the number of PIMs per person (MD = -0.41, 95%CI: −0.51, −0.31; p &lt; 0.001), accompanying by a low heterogeneity. Subgroup analysis showed that the application of computer-based clinical decision support for pharmacological interventions could remarkably decrease the incidence of PIMs and two assessment tools were more effective. Of the secondary outcomes, the meta-analysis showed that pharmacological interventions could reduce the number of drugs used per person (MD = -0.94, 95%CI: −1.51, −0.36; p = 0.001) and 30-day readmission rate (OR = 0.58, 95%CI: 0.36, 0.92; p = 0.02), accompanying by a low heterogeneity. However, the pharmaceutical interventions demonstrated no significant improvement on all-cause mortality and the number of falls.ConclusionOur findings supported the efficacy of pharmaceutical interventions to optimize the use and management of drugs in older patients.Systematic review registrationhttps://clinicaltrials.gov/, CRD42019134754