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Purpose Recently, competing risk nomograms were widely applied to predict prognosis in numerous tumors other than chordoma. Here, we aimed to construct and validate a competing-risk-based prognostic nomogram to predict 3- and 5-year cancer-specific death (CSD) in patients with spinal and pelvic chordoma. Methods All chordoma patient data were abstracted from the Surveillance, Epidemiology, and End Results (SEER) resource, and a total of 485 chordoma patients were eventually included in this study. Multivariate competing risk model and multivariate Cox model were used to determine independent prognostic factors, respectively, and the results of the two models were compared. Nomogram was employed to visualize the competing risk model. The discrimination, calibration, and clinical utility of this model were evaluated by Harrell concordance index (C-index), time-dependent receiver operating characteristic (ROC) curves, calibration plots, and decision curve analysis (DCA). Ten-fold cross-validation was further utilized to validate the prognostic nomogram. Results Significant prognostic factors affecting CSD were age (P = 0.016), localized involvement (P P Conclusion We successfully built the first competing-risk-based nomogram to predict clinical outcomes in patients with spinal and pelvic chordoma. This well-established nomogram hopes to help clinicians with precise prognostic assessment and thus improve clinical outcomes.

Pelvic fracture is a severe injury resulting in high mortality and disability rate, and brought heavy health burden. However, existing research conclusions only restricted to the national level while global estimation of pelvic fracture was lack. We aimed to estimate the global incidence, prevalence, and years lived with disability (YLDs) of pelvic fracture by region, age, gender, cause and sociodemographic index (SDI).Publicly available data was gained based on the Global Burden of Disease Study (GBD) 2019. We calculated the estimated annual percent change (EAPC) to analyze the temporal trends of pelvic fractures from 1990 to 2019. Incidence, prevalence and YLDs were analyzed by region, age, gender, cause and SDI. Spearman's rank order correlation was used to determine the correlation between SDI and incidence, prevalence and YLDs.Globally, there were about 6 million incident cases, 18.8 million prevalent cases and 3.2 million YLDs cases of pelvic fractures for both sexes in 2019. The incidence number increased over 40% compared to 1990. However, the age standardized rate of incidence (ASIR) (EAPC = -0.22; 95% CI, -0.38 to -0.05), prevalence (ASPR) (EAPC = -0.42; 95% CI, -0.51 to -0.32) and YLDs (ASYR) (EAPC = -0.41; 95% CI, -0.50 to -0.32) all presented downward trends. Males had higher ASIR, ASPR and ASYR than females in each year from 1990 to 2019. The incidence, prevalence and YLDs rates were higher in males in early adulthood but exceeded in females at older age. A positive correlation was observed between ASIR and SDI (rho = 0.3732, p 0.01). Regions with higher SDI tended to have higher ASIR, ASPR and ASYR than lower SDI regions. Falls and road injuries were the major causes of pelvic fracture at all ages and during the whole period.The global health burden of pelvic fracture still remained high during the past thirty years. More policies and strategies are needed to face the challenge brought by population growth and aging.

In this work, tB-MoS2 and MoSe2 flower-like structures were produced using a CVD method. An indirect-to-direct energy band gap transition was shown in the region away from the flower center in the structures, accompanied by an enhanced PL intensity.

Objectives Early recognition and timely intervention for urosepsis are key to reducing morbidity and mortality. Blood culture has low sensitivity, and a long turnaround time makes meeting the needs of clinical diagnosis difficult. This study aimed to use biomarkers to build a machine learning model for early prediction of urosepsis. Methods Through retrospective analysis, we screened 157 patients with urosepsis and 417 patients with urinary tract infection. Laboratory data of the study participants were collected, including data on biomarkers, such as procalcitonin, D-dimer, and C-reactive protein. We split the data into training (80%) and validation datasets (20%) and determined the average model prediction accuracy through cross-validation. Results In total, 26 variables were initially screened and 18 were statistically significant. The influence of the 18 variables was sorted using three ranking methods to further determine the best combination of variables. The Gini importance ranking method was found to be suitable for variable filtering. The accuracy rates of the six machine learning models in predicting urosepsis were all higher than 80%, and the performance of the artificial neural network (ANN) was the best among all. When the ANN included the eight biomarkers with the highest influence ranking, its model had the best prediction performance, with an accuracy rate of 92.9% and an area under the receiver operating characteristic curve of 0.946. Conclusions Urosepsis can be predicted using only the top eight biomarkers determined by the ranking method. This data-driven predictive model will enable clinicians to make quick and accurate diagnoses.

We investigated the imaging performance of a fast convergent ordered-subsets algorithm with subiteration-dependent preconditioners (SDPs) for positron emission tomography (PET) image reconstruction. In particular, we considered the use of SDP with the block sequential regularized expectation maximization (BSREM) approach with the relative difference prior (RDP) regularizer due to its prior clinical adaptation by vendors. Because the RDP regularization promotes smoothness in the reconstructed image, the directions of the gradients in smooth areas more accurately point toward the objective function's minimizer than those in variable areas. Motivated by this observation, two SDPs have been designed to increase iteration step-sizes in the smooth areas and reduce iteration step-sizes in the variable areas relative to a conventional expectation maximization preconditioner. The momentum technique used for convergence acceleration can be viewed as a special case of SDP. We have proved the global convergence of SDP-BSREM algorithms by assuming certain characteristics of the preconditioner. By means of numerical experiments using both simulated and clinical PET data, we have shown that the SDP-BSREM algorithms substantially improve the convergence rate, as compared to conventional BSREM and a vendor's implementation as Q.Clear. Specifically, SDP-BSREM algorithms converge 35\%-50\% faster in reaching the same objective function value than conventional BSREM and commercial Q.Clear algorithms. Moreover, we showed in phantoms with hot, cold and background regions that the SDP-BSREM algorithms approached the values of a highly converged reference image faster than conventional BSREM and commercial Q.Clear algorithms., Comment: 12 pages, 9 figures

Active noise control technology shows good performance in those low-frequency narrowband noise control applications. Suffering from time-varying frequencies and secondary path, the performance of narrowband active noise control system may deteriorate seriously. In this work, an improved narrowband active noise control system is proposed to improve the noise reduction performance in those time-varying system. In the improved system, a frequency tracker based on the adaptive notch filter is adopted to estimate the frequencies of the noise signal. The result of frequency estimation is used to generate the reference signal and the prior information of the secondary-path modeling process. Then, the local secondary-path modeling can be conducted in the system with unknown fixed tonal noise signal or time-varying tones. Simulations and experiments are conducted to verify the performance of the proposed algorithm, and the results show that the proposed algorithm has good behavior.

Hepatocellular carcinoma (HCC) is resistant to current immunotherapy. This poor outcome mainly results from the immunosuppressive characteristics of tumor microenvironment (TME). Accumulating evidence indicates that some chemotherapy agents trigger immunogenic cell death (ICD), providing a promising strategy to remodel the immunosuppressive TME. The role of Plumbagin (PLB, a naphthoquinone compound from Plumbago zeylanica L.) as the ICD inducer for HCC cells was confirmed in this study. Dihydrotanshinone I (DIH, a phenanthraquinone compound of Salvia miltiorrhiza) functioned as the ICD enhancer by generating the reactive oxygen species (ROS). A poly(D,L-lactic-co-glycolic acid) (PLGA)-based nanoparticle (NP) was used to co-encapsulate PLB, DIH and NH

In order to assess the impact of Daya Bay Nuclear Power Base on the surrounding environment during its operation, the radioactive level of the surrounding environmental media was monitored and investigated according to the monitoring standard (HJ 61-2021). The monitoring results show that during the operation of Daya Bay Nuclear Power Base, the radioactivity level of the surrounding environmental media is at the natural background level. The nuclear power base did not cause radioactive pollution to the surrounding environment. The research results provide technical support for nuclear emergency response and data basis for evaluating the impact of Fukushima radioactive waste water.

Supplementary Table S1 shows the association between PARP1 expression and the clinicopathological features in ovarian cancer patients.

Supplementary Figure S1 shows the expression of IGF1R and p-Akt in let-7e-inhibited xenograft tumors.

Supplementary Figure S2 shows the cellular viability of A2780, SKOV3 and Caov3 cell lines treated with cisplatin and/or olaparib for indicated duration.

Supplementary Table S2 shows the association between different parameters and the PFS, OS and chemotherapy response in ovarian cancer patients.

Multiferroic materials have great potential in non-volatile devices for low-power and ultra-high density information storage, owing to their unique characteristic of coexisting ferroelectric and ferromagnetic orders. The effective manipulation of their intrinsic anisotropy makes it promising to control multiple degrees of the storage “medium”. Here, we have discovered intriguing in-plane electrical and magnetic anisotropies in van der Waals (vdW) multiferroic CuCrP2S6. The uniaxial anisotropies of current rectifications, magnetic properties and magnon modes are demonstrated and manipulated by electric direction/polarity, temperature variation and magnetic field. More important, we have discovered the spin-flop transition corresponding to specific resonance modes, and determined the anisotropy parameters by consistent model fittings and theoretical calculations. Our work provides in-depth investigation and quantitative analysis of electrical and magnetic anisotropies with the same easy axis in vdW multiferroics, which will stimulate potential device applications of artificial bionic synapses, multi-terminal spintronic chips and magnetoelectric devices.

Background: The aim of this study was to investigate the effect of Sacubitril/valsartan (Sac/Val) in patients diagnosed with nonvalvular atrial fibrillation (AF) without systolic heart failure (SHF). Methods: Nonvalvular AF patients without SHF admitted to the People’s Hospital of Boltala Mongolian Autonomous Prefecture from December 2020 to December 2021 were enrolled and randomly divided into the Sac/Val treatment group (group T) and valsartan treatment group (group C, control). For subgroup analysis, patients were divided into subgroups with and without diastolic heart failure (DHF). After a 1-month run-in period and subsequent 3-month treatment period, patients were followed up in the cardiology clinic. Plasma levels of biochemical markers and echocardiographic parameters before and after treatment were compared, and DHF scores were calculated for comparison of diastolic function. Results: Of 61 enrolled patients, 46 patients completed the follow-up. Sac/Val treatment did not increase the proportion of sinus rhythm. Although NT-proBNP expression tended to be reduced in both groups after 3 months of treatment, the differences compared with respective baseline levels and between groups were not significant. Subgroup analysis suggested that NT-proBNP expression in the subgroup with DHF was decreased at follow-up versus baseline, but the difference was not significant. Similarly, no marked differences in echocardiographic parameters or tissue Doppler parameters related to DHF were detected between the groups (P>0.05). Subgroup analysis also showed no significant differences in the echocardiographic parameters between subgroups (P>0.05). Conclusion: Sac/Val is not superior to valsartan in the treatment for patients suffering with AF without SHF.

Multiferroic materials have great potential in non-volatile devices for low-power and ultra-high density information storage, owing to their unique characteristic of coexisting ferroelectric and ferromagnetic orders. The effective manipulation of their intrinsic anisotropy makes it promising to control the multiple degrees of freedom of the storage "medium". Here, we have discovered intriguing electrical and magnetic anisotropies within the intralayer of CuCrP2S6, a promising van der Waals multiferroic material. The in-plane uniaxial anisotropies of the current rectifications, magnetic properties and magnon modes are demonstrated and manipulated by electric direction/polarity, temperature variation and magnetic field. More important, we have observed spin-flop transition corresponding to specific magnon modes, and it is well supported by theoretical calculations. Our work provides the first observation of electrical and magnetic anisotropies with same easy axis in van der Waals multiferroics, which will stimulate novel device applications of artificial bionic synapses, multi-terminal spintronic chips and magnetoelectric devices.

Talking about osteoporosis, we tend to focus on post-menopause women who are at increased risk due to estrogen depletion, while less attention has been paid to the disease in men. Currently, there is a lack of understanding about the difference of osteoporosis incidence and burden by sex. In this study, we used data from the Global Burden of Disease Study 2019 (GBD 2019) to compare the difference in the prevalence and burden of low bone mineral density (LBMD) between men and women, by location, year, age and socio-demographic index. We found the prevalence of LBMD was higher in women than in men. However, the age standardized mortality rate was greatly higher in men than in women. Using disability-adjusted life year (DALY) to measure the burden, we also observed higher age standardized DALY rate in men. Using sociodemographic index (SDI) as the measure of social development level, we found that higher mortality and DALY rates were mainly seen in middle and high SDI countries. Falls were the leading cause for of deaths and disabilities in both men and women with LBMD, followed by transport injuries. Fall-related mortality was higher in women, while transport injuries caused more deaths and disabilities in men. Conclusively, more attention should be paid to osteoporosis in men, and related policies, clinical practices, and guidelines are in need to reduce the burden of LBMD and osteoporosis in men.

To enable a quick and accurate access of targeted scientific and technological literature from massive stocks, here a deep content-based collaborative filtering method, namely DeepCCF, for personalized scientific and technological literature resources recommendation was proposed. By combining content-based filtering (CBF) and neural network-based collaborative filtering (NCF), the approach transforms the problem of scientific and technological literature recommendation into a binary classification task. Firstly, the word2vec is used to train the words embedding of the papers’ titles and abstracts. Secondly, an academic literature topic model is built using term frequency–inverse document frequency (TF-IDF) and word embedding. Thirdly, the search and view history and published papers of researchers are utilized to construct the model that portrays the interests of researchers. Deep neural networks (DNNs) are then used to learn the nonlinear and complicated high-order interaction features between users and papers, and the top k recommendation list is generated by predicting the outputs of the model. The experimental results show that our proposed method can quickly and accurately capture the latent relations between the interests of researchers and the topics of paper, and be able to acquire the researchers’ preferences effectively as well. The proposed method has tremendous implications in personalized academic paper recommendation, to propel technological progress.

Immunogenic cell death (ICD, also known as immunogenic apoptosis) of malignant cells is confirmed to activate the host immune system to prevent, control, and eliminate tumors. Recently, a range of chemotherapeutic drugs have been repurposed as ICD inducers and applied for tumor immunotherapy. However, several hurdles to the widespread application of chemotherapeutic ICD inducers remain, namely poor water solubility, short blood circulation, non-specific tissue distribution, and severe toxicity. Recent advances in nanotechnology and pharmaceutical formulation foster the development of nano drug delivery systems to tackle the aforementioned hurdles and expedite safe, effective, and specific delivery. This review will describe delivery barriers to chemical ICD inducers and highlight recent nanoformulations for these drugs in tumor immunotherapy.

In this work, different proportions of N-doped carbon quantum dots/porous Co

Due to the unique physical characteristics of intervertebral disc degeneration (IVDD) and the pathological microenvironment that it creates, including inflammation and oxidative stress, effective self-repair is impossible. During the process of intervertebral disc degeneration, there is an increase in the infiltration of M1 macrophages and the secretion of proinflammatory cytokines. Here, we designed a novel injectable composite hydrogel scaffold: an oligo [poly (ethylene glycol) fumarate]/sodium methacrylate (OPF/SMA) hydrogel scaffold loaded with dual-drug/sustained-release PLGA microspheres containing IL-4 (IL-4-PLGA) and kartogenin (KGN-PLGA). This scaffold exhibited good mechanical properties and low immunogenicity while also promoting the sustained release of drugs. By virtue of the PLGA microspheres loaded with IL-4 (IL-4-PLGA), the composite hydrogel scaffold induced macrophages to transition from the M1 phenotype into the M2 phenotype during the early induced phase and simultaneously exhibited a continuous anti-inflammatory effect through the PLGA microspheres loaded with kartogenin (KGN-PLGA). Furthermore, we investigated the mechanisms underlying the immunomodulatory and anti-inflammatory effects of the composite hydrogel scaffold. We found that the scaffold promoted cell proliferation and improved cell viability in vitro. While ensuring mechanical strength, this composite hydrogel scaffold regulated the local inflammatory microenvironment and continuously repaired tissue in the nucleus pulposus via the sequential release of drugs in vivo. When degenerative intervertebral discs in a rat model were injected with the scaffold, there was an increase in the proportion of M2 macrophages in the inflammatory environment and higher expression levels of type II collagen and aggrecan; this was accompanied by reduced levels of MMP13 expression, thus exhibiting long-term anti-inflammatory effects. Our research provides a new strategy for promoting intervertebral disc tissue regeneration and a range of other inflammatory diseases.

Glioma is one of the most aggressive intracranial tumors in the central nervous system. The long non-coding RNA P21 associated ncRNA DNA damage activated (PANDAR) has been reported to be an oncogene or tumor suppressor in several cancers. However, the prognostic value and biological function of PANDAR in glioma have not been described. Here, we report that expression of PANDAR is significantly up-regulated in glioma tissues and cell lines. PANDAR expression was correlated with tumor size (p=0.044) and World Health Organization (WHO) grades (p=0.005), as shown by chi-squared test. Moreover, significant upregulation of PANDAR was found to correlate with poor prognosis in glioma, as shown using Kaplan-Meier method and Cox multivariate survival analysis. Furthermore, PANDAR knockdown suppressed cell proliferation, G1/S transition, migration and invasion, and promoted apoptosis in glioma cell lines (U251 and U87). PANDAR knockdown decreased expression of CDK4, Bcl-2, N-cadherin and Vimentin, but increased E-cadherin expression in glioma cells. In conclusion, our data suggest PANDAR as a potential prognostic biomarker and therapeutic candidate for glioma.

Catalytic conversion of biomass to fuels and chemicals has attracted considerable attention in addressing the global challenges associated with energy and environmental crisis. Catalyst plays a crucial role in the biomass conversion process, and the characteristic of catalysts are continuously improved to meet the requirements. Niobium (Nb) based catalysts, generally in the form of niobic acid, niobium pentoxide (Nb2O5), niobium phosphate (NbOPO4), and their supporting materials, have been widely employed for bioenergy production. This review summarizes the special characteristics of Nb-based catalysts, and the application of these catalysts on the catalytic conversion of biomass, including (I) properties of Nb-based catalysts, (II) catalytic hydrolysis/dehydration for platform chemicals, (III) catalytic pyrolysis for hydrocarbons, (IV) catalytic esterification, (V) catalytic hydrogenation, and (VI) catalytic oxidation. The Nb compounds become an attractive candidate in the bioenergy field, and this review serves as a basis for future research on biomass catalytic conversion over Nb-based catalysts.

Aim To share our experiences of resuming the treatments for gynecologic patients after lifting the lockdown in a hotspot area for the Coronavirus Disease 2019 (COVID‐19) pandemic. Methods The triage process used to resume medical activities for gynecologic patients at the Wuhan Union Hospital after a 76‐day lockdown of the city is described, and its effectiveness in preventing COVID‐19 nosocomial transmission is shown. Results Nonemergency patients were pretriaged based on their contact history and body temperature at an outpatient clinic, and negative COVID‐19 screening test results were required for admission to the buffering rooms at the gynecologic department. The buffering lasted at least 3 days for symptom monitoring, and a second round of COVID‐19 testing was required before patients could be transferred to the regular gynecologic wards. For patients who needed emergency surgery, the first screening was completed at the isolation wards after surgery, followed by buffering at the gynecologic department. We received 19 298 outpatient visits, admitted 326 patients, and performed 223 operations in the first 2 months after the lockdown was lifted. No COVID‐19 cases occurred in the hospitalized patients, while the proportion of potentially high‐risk patients with cancer and severe anemia was increased in comparison to that observed during the same period in 2019 and the first 2 months of 2020 before the lockdown. Conclusions We provide an effective triage system with buffering at two levels to guarantee safe and timely treatment for non‐COVID‐19 gynecologic patients in the postlockdown phase.

This paper examines the changing spatial distribution of electronic information manufacturing (EIM) industry in China by focusing on the location choice of new firms. A three‐pronged “global‐regional‐local” nexus framework was proposed to identify the factors that influence firm location choice. Tobit regression analysis was performed to evaluate the impacts of these factors. The study reveals the spatial concentration of the EIM industry and a trend of westward diffusion. The regression analyses stratified by time period and by region demonstrate spatial and temporal variabilities in the influence of many factors, especially the regional advantage factors (e.g., labor cost, localization economies, and urbanization economies). Meanwhile, some factors, such as foreign direct investment, the presence of state‐owned enterprises, and local government policies, show stable effects over time and across regions.

It is still a significant challenge to replace noble metal based catalysts by non-noble metal-based, highly efficient and earth-abundant catalysts in the H2 generation upon hydrolysis of sodium borohydride. Herein, we first design and synthesize the highly selective and heterogeneous CoxWy nanocomposites from ZIF-67 as robust catalysts for H2 production upon the hydrolysis of sodium borohydride. Among them, the Co0.45W0.55 nanocatalyst exhibits the highest TOF of 1770 mLH2 gcat−1 min−1 (the TOF related to only cobalt nanoparticles 8401 mLH2 gCo−1 min−1) over pure ZIF-67 or W nanoparticles and other ones. In addition, the Co0.45W0.55 catalyst has been successfully recycled at least 5 times without any significant activity loss, although the W (VI) has been partly reduced to W (V), W (IV) and W (0) in the hydrolysis of sodium borohydride. This stability is taken into account by the highly active Co species rather than the activity of W itself. Based on the results obtained, we have shown that Co0.45W0.55 nanocomposite can be a potential candidate for the replacement of a noble metal catalyst for H2 generation.

It is of vital importance to search for an objective quality metric which can provide insights into the geometric strength of the underlying adjustment model. The Minimal Detectable Bias (MDB) meas...

Surface ripple, as an important factor of corrugations in two-dimensional (2D) atomic crystals, plays important roles in determining their mechanical and physical properties. Here, we systematicall...