30 research outputs found

    Brain Injury Differences in Frontal Impact Crash Using Different Simulation Strategies

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    In the real world crashes, brain injury is one of the leading causes of deaths. Using isolated human head finite element (FE) model to study the brain injury patterns and metrics has been a simplified methodology widely adopted, since it costs significantly lower computation resources than a whole human body model does. However, the degree of precision of this simplification remains questionable. This study compared these two kinds of methods: (1) using a whole human body model carried on the sled model and (2) using an isolated head model with prescribed head motions, to study the brain injury. The distribution of the von Mises stress (VMS), maximum principal strain (MPS), and cumulative strain damage measure (CSDM) was used to compare the two methods. The results showed that the VMS of brain mainly concentrated at the lower cerebrum and occipitotemporal region close to the cerebellum. The isolated head modelling strategy predicted higher levels of MPS and CSDM 5%, while the difference is small in CSDM 10% comparison. It suggests that isolated head model may not equivalently reflect the strain levels below the 10% compared to the whole human body model

    Decoding the spermatogonial stem cell niche under physiological and recovery conditions in adult mice and humans

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    The intricate interaction between spermatogonial stem cell (SSC) and testicular niche is essential for maintaining SSC homeostasis; however, this interaction remains largely uncharacterized. In this study, to characterize the underlying signaling pathways and related paracrine factors, we delineated the intercellular interactions between SSC and niche cell in both adult mice and humans under physiological conditions and dissected the niche-derived regulation of SSC maintenance under recovery conditions, thus uncovering the essential role of C-C motif chemokine ligand 24 and insulin-like growth factor binding protein 7 in SSC maintenance. We also established the clinical relevance of specific paracrine factors in human fertility. Collectively, our work on decoding the adult SSC niche serves as a valuable reference for future studies on the aetiology, diagnosis, and treatment of male infertility.</p

    Clinical Application of a Modified Double Purse-String Continuous Suture Technique for Pancreaticojejunostomy: Reliable for Laparoscopic Surgery and Small Size Main Pancreatic Duct

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    Background. The technical challenge of pancreatojejunostomy (PJ) is the greatest barrier for surgeons to complete pancreatoduodenectomy (PD). The authors present an easy-to-master PJ anastomosis technique with limited technical requirements. This technique uses two layers of sutures and double purse-string sutures to complete the entire anastomosis. This anastomosis technique has achieved good results in laparoscopic surgery (LS) and small size main pancreatic duct (MPD). Methods. From February 2015 to August 2020, 63 patients who met the surgical indications underwent a modified double purse-string continuous suture pancreaticojejunostomy technique in our center. We collected patient demographic characteristics and perioperative outcomes and analyzed these data. Results. A total of 63 patients underwent PD using our new anastomosis technique. Thirty-eight patients underwent LS, and 26 patients had a small MPD (<3 mm). The median operative time (OT) was 270 min, and the median estimated blood loss (EBL) was 200 ml. Ten patients had grade B postoperative pancreatic fistula (POPF), while no patients had grade C POPF. No 90-day mortality was observed. There were significant differences in the OT and postoperative hospital stay (PHS) among groups with different surgical procedures, while there were no significant differences among groups with different MPD sizes. Neither the surgical procedure nor the MPD size affected early postoperative complications. Conclusion. This new technique can not only reduce the incidence of POPF but also is reliable for LS and surgeries with small size MPD. Therefore, this technique is worthy of clinical promotion and application in the future

    HMGN5 Silencing Suppresses Cell Biological Progression via AKT/MAPK Pathway in Human Glioblastoma Cells

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    HMGN5 regulates biological function and molecular transcription via combining with a nucleosome. There has been growing evidence that aberrant expression of HMGN5 is associated with malignant neoplasm development and progression. In the present study, we found that the expression of HMGN5 is significantly higher in high-grade glioblastoma tissues than in low-grade samples. To clarify the function of HMGN5 in glioblastoma, we knocked down HMGN5 in U87 and U251 glioblastoma cells via siRNA. The results demonstrated that HMGN5 was involved in the regulation of proliferation and apoptosis, migration, and invasion of glioblastoma cells. These outcomes also indicated that silencing HMGN5 possibly suppressed the expression of p-AKT and p-ERK1/2. Taken together, our research reveals that HMGN5 might be an efficient target for glioblastoma-targeted therapy

    A Low Phase Noise Frequency Synthesizer with a Fourth-Order RLC Loop Filter

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    The current work employs the HMC830 phase-locked loop chip to design a frequency synthesizer operating in the L-band. The frequency synthesizer can provide a local oscillation signal for the RF receiver front end. This article employs the phase-locked synthesis technique to describe the design scheme. Due to the advantages of the passive loop filters, such as simplicity, low cost, and low phase noise, a passive fourth-order RLC loop filter is proposed to improve the output signal quality and reduce phase noise. The performance of this loop filter is compared with the passive fourth-order RC loop filter. The effects of these two loop filters on phase noise, loop capture time, and spur suppression are analyzed. Subsequently, the design scheme, simulation analysis, and test results of the frequency synthesizer are presented under these two loop filters. The test results indicate that the passive fourth-order RLC loop filter outperforms the passive fourth-order RC loop filter; its output signal phase noise is higher than −100 dBc/Hz@1 kHz, loop capture time is less than 100 us, and spur suppression is better than 60 dBc. This frequency synthesizer can provide high-performance local oscillation signals for wireless communication equipment such as transmitters and receivers. It meets the application requirements of many radio communication circuit structures and has good application prospects

    Characterization of glial-restricted precursors from rhesus monkey embryonic stem cells

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    Glial-restricted precursor (GRP) cells, the earliest glial progenitors for both astrocytes and oligodendrocytes, have been derived from embryos and embryonic stem cells (ESC) in rodents. However, knowledge regarding the equivalent cell type in primates is limited due to restrictions imposed by ethics and resources. Here we report successful derivation and characterization of primate GRP cells from rhesus monkey ESC. The purified monkey GRP cells were A2B5-positive and FGF2-dependent for survival and proliferation. The differentiation assays indicated that they were tri-potential in vitro and bi-potential in vivo. These newly purified GRP cells will help to facilitate understanding of the molecular mechanism of glial development in primates as well as provide a source of therapeutic donor cells for use in neuroregenerative medicine

    Machine Learning to Predict the Response to Lenvatinib Combined with Transarterial Chemoembolization for Unresectable Hepatocellular Carcinoma

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    Background: Lenvatinib and transarterial chemoembolization (TACE) are first-line treatments for unresectable hepatocellular carcinoma (HCC), but the objective response rate (ORR) is not satisfactory. We aimed to predict the response to lenvatinib combined with TACE before treatment for unresectable HCC using machine learning (ML) algorithms based on clinical data. Methods: Patients with unresectable HCC receiving the combination therapy of lenvatinib combined with TACE from two medical centers were retrospectively collected from January 2020 to December 2021. The response to the combination therapy was evaluated over the following 4–12 weeks. Five types of ML algorithms were applied to develop the predictive models, including classification and regression tree (CART), adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), random forest (RF), and support vector machine (SVM). The performance of the models was assessed by the receiver operating characteristic (ROC) curve and area under the receiver operating characteristic curve (AUC). The Shapley Additive exPlanation (SHAP) method was applied to explain the model. Results: A total of 125 unresectable HCC patients were included in the analysis after the inclusion and exclusion criteria, among which 42 (33.6%) patients showed progression disease (PD), 49 (39.2%) showed stable disease (SD), and 34 (27.2%) achieved partial response (PR). The nonresponse group (PD + SD) included 91 patients, while the response group (PR) included 34 patients. The top 40 most important features from all 64 clinical features were selected using the recursive feature elimination (RFE) algorithm to develop the predictive models. The predictive power was satisfactory, with AUCs of 0.74 to 0.91. The SVM model and RF model showed the highest accuracy (86.5%), and the RF model showed the largest AUC (0.91, 95% confidence interval (CI): 0.61–0.95). The SHAP summary plot and decision plot illustrated the impact of the top 40 features on the efficacy of the combination therapy, and the SHAP force plot successfully predicted the efficacy at the individualized level. Conclusions: A new predictive model based on clinical data was developed using ML algorithms, which showed favorable performance in predicting the response to lenvatinib combined with TACE for unresectable HCC. Combining ML with SHAP could provide an explicit explanation of the efficacy prediction
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