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Jie Liu,1,&ast; Yilei Ma,2,&ast; Wanli Xie,1,&ast; Xia Li,1 Yanting Wang,1 Zhenzhen Xu,1 Yunxiao Bai,1 Ping Yin,2 Qingping Wu1 1Department of Anesthesiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China; 2School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Qingping Wu, Email wqp1968@126.comBackground: The predictive effect of systemic inflammatory factors on postoperative pulmonary complications in elderly patients remains unclear. In addition, machine learning models are rarely used in prediction models for elderly patients.Patients and Methods: We retrospectively evaluated elderly patients who underwent general anesthesia during a 6-year period. Eligible patients were randomly assigned in a 7:3 ratio to the development group and validation group. The Least logistic absolute shrinkage and selection operator (LASSO) regression model and multiple logistic regression analysis were used to select the optimal feature. The discrimination, calibration and net reclassification improvement (NRI) of the final model were compared with “the Assess Respiratory Risk in Surgical Patients in Catalonia” (ARISCAT) model.Results: Of the 9775 patients analyzed, 8.31% developed PPCs. The final model included age, preoperative SpO2, ANS (the Albumin/NLR Score), operation time, and red blood cells (RBC) transfusion. The concordance index (C-index) values of the model for the development cohort and the validation cohort were 0.740 and 0.748, respectively. The P values of the Hosmer–Lemeshow test in two cohorts were insignificant. Our model outperformed ARISCAT model, with C-index (0.740 VS 0.717, P = 0.003) and NRI (0.117, P < 0.001).Conclusion: Based on LASSO machine learning algorithm, we constructed a prediction model superior to ARISCAT model in predicting the risk of PPCs. Clinicians could utilize these predictors to optimize prospective and preventive interventions in this patient population.Keywords: older adult, postoperative complications, ANS, the albumin/NLR score, risk factors

BackgroundConducting geriatric trials is the most feasible way to address the vast underrepresentation of older adults in clinical trials of cancer therapies. This study is a globally comprehensive examination of geriatric trials for solid tumor worldwide over the last decade.MethodsUp-to-date information on cancer drug trials in older adults aged over 59 years from the beginning of 2012 to the end of 2021 was collected from Trialtrove and Pharmaprojects. The number of identified trials was the dependent variable and corresponding analysis was conducted from the perspective of time trend, status quo and comparisons by region and country, sponsor type and cancer type, study status and phase.ResultsA total of 292 geriatric cancer drug trials were identified, of which 287 were single-region studies, 219 were initiated by academic groups, and 55 (18.8%) were terminated. Decreasing trends in the annual number of all trials (−9.2% per year) and the annual number of trials by academic groups (−9.4%) were observed over time. Of the geriatric trials, 183 were conducted in Asia; this number was significantly higher than that in Europe (74), North America (37), Oceania (4), and South America (1). Similar difference was found in participation rate in trials by academic groups ranging from 71.7% in Asia to 0.5% in South America. Of the trials, 19 and 97 were initiated before drug and indication approval, respectively, and the remaining 176 were initiated after indication approval. Phase II trials accounted for the highest proportion of trials (213, 72.9%), while phase I trials accounted for the lowest proportion (14, 4.8%). Trials by academic groups had a higher termination rate (21.5% vs. 11.0%) and fewer were phase IV trials (8.2% vs. 21.9%). Treatment was explored for 16 different cancers, with lung, colorectal and breast cancers being the most common.ConclusionGeriatric trials of solid tumor drugs are scarce and partially prematurely terminated. Moreover, the number of geriatric trials has decreased and differs according to region. Global guidance and regulatory supervision are needed to facilitate the acquisition of adequate evidence on drug risk-benefit profiles in older adults, and thus to achieve high-quality care and safe medication.

All two-dimensional hard regular polygons have stable crystalline structures above a finite phase-transition density, and adding short-range interactions is believed not to qualitatively change their thermal stabilities. By molecular dynamics simulation, however, we find that adding a short-range Lennard-Jones interaction on each vertex of the hard regular triangle leads to ground-state degeneracy of the triangular system due to the fact that the unit cell of the crystal formed by a dimer has two isotopic structures with identical potential energies, which induces spontaneous crystalline instability and allows the system to be in the glassy state at any finite temperatures before liquidizing. At a fixed finite temperature, the initial crystalline structure eventually evolves to the glassy state spontaneously through a down-hill process after it comes over a single energy barrier. This mechanism is further verified by the observation that forbidding one of the two isotopic structures of the unit cell extremely heightens the energy barrier.

Purpose: To establish a pharmacist-led olaparib follow-up program for ovarian cancer patients, provide patient education, get information on adverse drug reactions (ADRs), and identify and manage drug-related problems.Methods: Ambulatory adult patients with ovarian cancer receiving olaparib were enrolled. At least one follow-up session was conducted by clinical pharmacists. Pharmacists collected data on the type and grade of ADRs, drug adherence, olaparib dosing, concomitant medications, and pharmacists’ suggestions.Results: 83 patients were enrolled with the median age of 58. The average number of the follow-up sessions provided to each patient was 1.31, and the average duration of each follow-up was 17.78 min. The olaparib starting dose for most patients (97.59%) was 600 mg/d. 36.14% of the patients had missed olaparib doses and 27.71% of the patients had dose adjustments due to ADRs. The most common ADRs (incidence≥10%) were: fatigue (40.96%), anemia (36.14%), leukopenia (36.14%), nausea (28.92%), thrombocytopenia (16.87%), anorexia (16.87%), dyspepsia (15.66%). The tolerability profiles were generally similar between patients treated for “first-line maintenance” and those treated for “recurrence maintenance” (p > .05). There were 42% of the patients who were concomitantly taking medications without exact chemical contents (such as formulated Chinese medicines and Chinese decoctions), and common types of concomitant medications with exact drug names were antihypertensive, anti-hyperglycemic, and anti-hyperlipidemic medications. The pharmacists identified 4 clinically significant drug-drug interactions (DDIs) in two patients. Pharmacists made 196 suggestions mainly related to rational use of the medications and management of ADRs.Conclusion: The study provides the first report about pharmacist-led follow-up service for olaparib. The types of ADRs were similar to those previously observed in clinical trials, and the profiles of ADRs in different types of patients (first-line maintenance vs. recurrence maintenance) were also similar. Pharmacists identified drug-related problems (such as adherence, DDIs and management of ADRs) and offer suggestions for the patients.

BackgroundSuccessful weaning and extubation after cardiac surgery is an important step of postoperative recovery. Delayed extubation is associated with poor prognosis and high mortality, thereby contributing to a substantial economic burden. The aim of this study was to develop and validate a prediction model estimate the risk of delayed extubation after cardiac surgery based on perioperative risk factors.MethodsWe performed a retrospective cohort study of adult patients undergoing cardiac surgery from 2014 to 2019. Eligible participants were randomly assigned into the development and validation cohorts, with a ratio of 7:3. Variables were selected using least absolute shrinkage and selection operator (LASSO) logistic regression model with 10-fold cross-validation. Multivariable logistic regression was applied to develop a predictive model by introducing the predictors selected from the LASSO regression. Receiver operating characteristic (ROC) curve, calibration plot, decision curve analysis (DCA) and clinical impact curve were used to evaluate the performance of the predictive risk score model.ResultsAmong the 3,919 adults included in our study, 533 patients (13.6%) experienced delayed extubation. The median ventilation time was 68 h in the group with delayed extubation and 21 h in the group without delayed extubation. A predictive scoring system was derived based on 10 identified risk factors based on 10 identified risk factors including age, BMI ≥ 28 kg/m2, EF < 50%, history of cardiac surgery, type of operation, emergency surgery, CPB ≥ 120 min, duration of surgery, IABP and eGFR < 60 mL/min/1.73 m2. According to the scoring system, the patients were classified into three risk intervals: low, medium and high risk. The model performed well in the validation set with AUC of 0.782 and a non-significant p-value of 0.901 in the Hosmer-Lemeshow test. The DCA curve and clinical impact curve showed a good clinical utility of this model.ConclusionsWe developed and validated a prediction score model to predict the risk of delayed extubation after cardiac surgery, which may help identify high-risk patients to target with potential preventive measures.

Oral lichen planus (OLP) is a localized autoimmune disease of the oral mucosa, with an incidence of up to 2%. Although corticosteroids are the first-line treatment, they cause several adverse effects. Quercetin, a naturally occurring compound, has fewer side-effects and provides long-term benefits. Besides, it has powerful anti‑inflammatory activities. Here, we combined network pharmacology with experimental verification to predict and verify the key targets of quercetin against OLP. First, 66 quercetin-OLP common targets were analyzed from various databases. The protein–protein interaction (PPI) network was constructed. Topology analysis and MCODE cluster analysis of common targets were conducted to identify 12 key targets including TP53, IL-6 and IFN-γ and their connections. Gene functions and key signaling pathways, including reactive oxygen species metabolism, IL-17 pathway and AGE-RAGE pathway, were enriched by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Then, in vitro experiments showed that quercetin interfered with Th1/Th2 balance by acting on IL-6 and IFN-γ to modulate the immune system in treating OLP. Quercetin considerably affected the apoptosis and migration of T lymphocytes in OLP patients. Our study reveals the potential therapeutic targets and signaling pathways of quercetin associated with OLP, and establishes the groundwork for future clinical applications.

Additional file 2: Table S1. Numbers of Animals Used in the Different Experiments.

Additional file 2: Figure S1. Applicability test of previously established NIRS modes [35]. A Spectrum variation range of prediction set and modeling set. B Distribution of prediction set and modeling set in principal components space of spectra. C–E Accuracy verification of NIRS models by comparing experimental and predicted values of 20 rice samples. ASL, acid soluble lignin; AIL, acid insoluble lignin; Glc-Rel1, glucose released after biomass enzymatic digestion following 1% (m/v) NaOH pretreatment. The fitting equations and coefficients are shown at the top of the plot. * and ** as significant correlations at P < 0.05 and 0.01, respectively. Figure S2. Frequency distributions of monosaccharides, acid soluble/insoluble lignin and biomass saccharification. A Mannose; B Galactose; C Acid soluble lignin; D Acid insoluble lignin; E Glucose yields released from enzymatic hydrolyses after 1% NaOH pretreatments (n = 215). Figure S3. Correlation analysis between lignin/cellulose related traits and enzymatic saccharification of alkaline pretreated rice straw. (A–G) Correlations of ρ-hydroxy-phenyl lignin H, syringyl lignin S, guaiacyl lignin G, acid soluble lignin (ASL), acid insoluble lignin (AIL), cellulose crystallinity index (CrI) and crystalline cellulose (Cry-cel) with glucose released after enzymatic digestion following 0.025% (m/v) NaOH pretreatment (Glc-Rel0.025). (H–N) Correlations of H, S, G, ASL, AIL, CrI and Cry-cel with glucose released after enzymatic digestion following 1% (m/v) NaOH pretreatment (Glc-Rel1). The fitting equations and coefficients are shown at the top of the plot. * and ** indicate the correlations are significant at p < 0.05 and 0.01, respectively. n = 100

Additional file 1: Table S1. Cellulose and lignin related traits of 100 rice straw samples. Table S2. Coefficient determination of calibration of 42 mannose and galactose NIRS models

Additional file 1: Figure S1. Analysis of agronomic traits of myb103 mutant and OsMYB103L-RNAi transgenic plant. A Stem strength, B plant height, C lodging index and D 1000-Grain weight of myb103 mutant and OsMYB103L-RNAi transgenic plant (RNAi-1) compared with WT. **As significant differences between myb103 and RNAi-1 with WT at p

Lithium-sulfur (Li-S) batteries have recently attracted a large amount of attention as promising candidates for next-generation high-power energy storage devices because of their high theoretical capacity and energy density. However, the shuttle effect of polysulfides and poor conductivity of sulfur are still vital issues that constrain their specific capacity and cyclic stability. Here, we design coaxial MnO2 -graphitic carbon hollow nanofibers as sulfur hosts for high-performance lithium-sulfur batteries. The hollow C/MnO2 coaxial nanofibers are synthesized via electrospinning and carbonization of the carbon nanofibers (CNFs), followed by an in situ redox reaction to grow MnO2 nanosheets on the surface of CNFs. The inner graphitic carbon layer not only maintains intimate contact with sulfur and outer MnO2 shell to significantly increase the overall electrical conductivity but also acts as a protective layer to prevent dissolution of polysulfides. The outer MnO2 nanosheets restrain the shuttle effect greatly through chemisorption and redox reaction. Therefore, the robust S@C/MnO2 nanofiber cathode delivers an extraordinary rate capability and excellent cycling stability with a capacity decay rate of 0.044 and 0.051 % per cycle after 1000 cycles at 1.0 C and 2.0 C, respectively. Our present work brings forward a new facile and efficient strategy for the functionalization of inorganic metal oxide on graphitic carbons as sulfur hosts for high performance Li-S batteries.

Aiming at the problems of boiler heating surface from clean to produce ash and slag, the heat transfer efficiency of boiler is reduced. With the cleanliness factor as the monitoring index, a real-time soot blowing prediction method based on unscented Kalman filter algorithm is proposed. The cleanliness factor degradation data was analyzed by double exponential function fitting, and the model parameters were updated by the unscented Kalman filter algorithm, and the future trend of the cleanliness factor was predicted. At the same time, a soot-blowing optimization model with the largest heat transfer per unit time is proposed to further optimize the soot blowing time. Taking the cleanliness factor data of a economizer as an example, by comparing with the extended Kalman filter algorithm, it is found that the proposed method can predict the soot blowing time more accurately, and the calculation of the soot-blowing optimization example is carried out to verify the feasibility of the proposed optimization model.

Lithium-sulfur batteries have currently attracted wide interest due to their high theoretical capacity, but the practical applications are being hampered by capacity decay, mainly attributed to the polysulfide shuttle. Here, we have designed a novel three-dimensional (3D) nanostructure of graphene hollow spheres (HGs) as the sulfur host. The 3D HGs were successfully prepared via a self-assembly method of wrapping graphene oxide (GO) on SiO 2 spheres, and then followed by carbonization and etching of the SiO 2 . The impregnation of sulfur into the hollow graphene spheres lead to obtaining the HGs/S cathode, which reaches up a high sulfur loading of 90 wt% in the composite (72 wt % in the whole cathode). The HGs/S cathode material remains a high discharge capacity of 810 mAh g −1 after 200 cycles at 0.5C rate. Furthermore, it demonstrates a low capacity-decay rate of 0.083% per cycle after 600 cycles at 1C rate. Compared with pristine reduced graphene oxide/sulfur composites (RGO/S), the as-prepared 3D self-assembled graphene hollow spheres HGs/S exhibit significantly improved electrochemical performances in terms of high specific capacity, remarkable rate capability and excellent cycling stability. These synergistic effects are achieved by more effective 3D ion/electron transport pathways, and efficient confinement of polysulfide dissolution and shuttling.

SF6 gas is widely used in various power equipment. In this paper, a baseline correction algorithm based on spectral detection method based on optimal wavelet basis is proposed. The algorithm selects the optimal wavelet base, removes the strong spectrum information by threshold method, eliminates the influence of continuum fitting, and performs the least squares fitting on the residual signal to obtain the continuum, and removes the continuum from the original spectrum to obtain the required Line spectrum. The accuracy of the quantitative analysis of the line spectrum intensity after processing is greatly improved, and the baseline is effectively estimated and corrected, and the fitting accuracy is higher than the traditional iterative wavelet baseline correction algorithm.

In order to reduce the influence of complex measurement noise, an improved track association fusion method was proposed. The method took into account the nonzero system error of the position parameters, relaxed the threshold of the position component association test, increased the association test of the first difference of the position parameter, and formed a position-velocity association test. At the same time, considering the influence of the gross error caused by the complex electromagnetic environment, the method applied the robust statistics to the related processes, such as distributed filtering, track association and weighted fusion, and obtained the final track association fusion method. The test of typical measured data showed that the proposed method had strong practicability.

The full-bridge modular multilevel converter (FB-MMC) has potential applications in overhead line flexible HVDC transmission system because of its ability to block the DC fault current. But plenty of switching devices in converters result in a huge amount of calculation in electromagnetic transient simulation program and make it very slow. To solve this problem, a detailed equivalent model of the FB-MMC is proposed. And for further decreasing the simulation time, an average equivalent model of numerical simulation is established by simplifying the voltage balancing control of MMC and eliminating the difference among sub-modules. A FB-MMC HVDC system is established on a platform of PSCAD/EMTDC, and the simulation results show that the proposed simulation model is valid.

In the face of limited educational resources, the investors are most concerned about the problem of choosing the best investing objective which can produce the utmost yield. This paper selected the first 10 universities on the basis of the statistical analysis on the resource endowment out of 88 universities and colleges in H province. Then the paper compared the potential of the knowledge field among the 10 major universities through applying Data Envelopment Analysis (DEA), C2R model and establishing input and output index system. Finally, 5 universities were selected as the growth pole to cultivate. The result of this paper is of great significance to the uneven development of the knowledge field among higher educational institutions in H province.

The information industry can stimulate economic growth and create enormous social wealth. This paper analysis the integral part of China's information industry. At the same time, this paper researches its development status. Combining the characteristics of information industry, we find out the inadequacies of the information industrial policy. At last, this paper provides kinds of policy to promote the development of information industry.

In this paper, the knowledge potential of knowledge field has been studied in the way of vector field, the Laplace's equation of knowledge potential has been built up, the establishment of mathematical model of knowledge potential has been explored, and the solution of mathematical model of knowledge potential is in the way of variables separation. It aimed at providing a way of quantitative analysis to the diffusion of knowledge, and it combined natural science with social science more effectively.

In today's highly developed society, we are faced with many choices or decision-making problems, and a number of socio-economic factors influencing the choice of these decisions. For effective decision-making, people simulate the human brain's neural network works, and establish a learning model, which can take fully advantage of experiential knowledge accumulation and find the optimal solution and minimize the error between the actual value and the best.

D-S theory is a popular assessment method on physical science. For this method, first, the scope of research regions should be determined, then some samples selected randomly from the sample space which is set up, so the samples quality can be assessed based on fuzzy theory. And then, the results of these assessments should be put as a “different sources, used to assess sample” multi-channel information, and the information be integrated in order to get the assessment results of the entire sample space based on D-S theory. At last, the assessment results can be explained as confidence interval is [0, 1].This text takes a province as an example, the economic development level of the province is 0.65286 based on this method.

采用液相色谱-四极杆/飞行时间(LC-Triple TOF ® )高分辨质谱组合化学计量学方法建立了婴幼儿配方乳粉中化学危害物的快速筛查模型。实验采用人工添加外源化学物质(沙丁胺醇、林可霉素、磺胺嘧啶、螺旋霉素、双氯西林和醋酸甲地孕酮)模拟婴幼儿配方乳粉中未知化学危害物污染,15种不同的乳粉等量混合后用水复溶,配制代表性乳粉溶液样品。依据添加与否将样品分为参照组(不含添加的化合物)和添加组。乳粉溶液试样加入乙腈进行提取,经Captiva ND Lipids 固相萃取柱净化,CORTECS TM UPLC C 18+ 柱液相色谱分离,以0.3%(v/v)甲酸-5%(v/v)水-乙腈溶液和0.3%(v/v)甲酸-5%(v/v)乙腈-水溶液为流动相梯度洗脱;飞行时间质谱全扫描(TOF MS)-信息依赖性采集(IDA)-子离子扫描(product ion scan)正离子模式采集样品数据。数据经MarkerView TM 软件预处理后导入SIMCA-P软件,对比分析参照组和添加组样品数据,拟合构建正交偏最小二乘法-判别分析(OPLS-DA)模型,并利用此模型进行样品组别区分和添加化合物识别。结果表明,实验构建的筛查模型拟合度和预测能力良好( R 2 X (cum)=0.742, R 2 Y (cum)=0.997, Q 2 Y (cum)=0.905),参照组和添加组样品被显著区分,6种添加的化合物(最低添加水平为50 μg/kg,以乳粉计)全部被可靠地识别。该研究建立的方法为婴幼儿配方乳粉质量安全主动分析监控体系提供了有益技术参考。

The application of the new algorithm for the calculating of the power quality factors is presented in the paper. To estimate their spectra and fundamental frequency, the current and voltage signals are first processed and then the power quality factors calculated. The algorithm considers frequency, amplitude and phase as unknown parameters. The proposed algorithm was evaluated using a theoretical signal and a real signal.