Search

Background: Lymphovascular invasion (LVI) is a significant risk factor for lymph node metastasis in gastric cancer (GC) and is closely related to the prognosis and recurrence of GC. This study aimed to establish clinical models, radiomics models and combination models for the diagnosis of GC vascular invasion. Methods: This study enrolled 146 patients with GC proved by pathology and who underwent radical resection of GC. The patients were assigned to the training and validation cohorts. A total of 1,702 radiomic features were extracted from contrast-enhanced computed tomography images of GC. Logistic regression analyses were performed to establish a clinical model, a radiomics model and a combined model. The performance of the predictive models was measured by the receiver operating characteristic (ROC) curve. Results: In the training cohort, the age of LVI negative (-) patients and LVI positive (+) patients were 62.41 ± 8.41 and 63.76 ± 10.08 years, respectively, and there were more male (n = 63) than female (n = 19) patients in the LVI (+) group. Diameter and differentiation were the independent risk factors for determining LVI (-) and (+). A combined model was found to be relatively highly discriminative based on the area under the ROC curve for both the training (0.853, 95% CI: 0.784-0.920, sensitivity: 0.650 and specificity: 0.907) and the validation cohorts (0.742, 95% CI: 0.559-0.925, sensitivity: 0.736 and specificity: 0.700). Conclusions: The combined model had the highest diagnostic effectiveness, and the nomogram established by this model had good performance. It can provide a reliable prediction method for individual treatment of LVI in GC before surgery. [ABSTRACT FROM AUTHOR]

Background: Due to the limited role of chronic pain medication in military personnel and the distress caused to the military population, mindfulness-based therapy has been considered for the follow-up treatment of military personnel with chronic pain. The purpose of this review is to explore the effect and the implementation of mindfulness-based therapy for the military population with chronic pain. Methods: The keywords for the search included "mindfulness" AND ("pain" OR "chronic pain") AND ("military" OR "veteran"). The PubMed, Embase, and Cochrane Library databases were searched. The Cochrane Collaboration tool was used to independently assess the risk of bias of the included randomized controlled trials, and the Newcastle–Ottawa Scale was used to independently assess the risk of bias of the included case–control studies. Results: A total of 175 papers were identified; 65 duplicates were excluded, and 59 papers that did not meet the inclusion criteria were excluded after reading the titles and abstracts. The remaining 51 papers were read in full, 42 of which did not meet the inclusion criteria. Nine papers met the inclusion criteria and were included in the study. The nine studies included 507 veterans and 56 active-duty female military personnel. All pain interventions were mindfulness-based therapy, and all of them were integrated into or adapted from standard mindfulness courses. The results all showed that after mindfulness-based therapy, the relevant indicators improved. Conclusions: Mindfulness-based therapy is an effective treatment method for the military population with chronic pain. The review indicates that future research should focus on the best setting for mindfulness-based therapy, including the course content and time. [ABSTRACT FROM AUTHOR]

In air combat missions, unmanned combat aerial vehicles (UCAVs) must take strategic actions to establish combat advantages, enabling effective tracking and attacking of enemy UCAVs. Currently, a lot of reinforcement learning algorithms are applied to the air combat mission of unmanned fighter aircraft. However, most algorithms can only select policies based on the current state of both sides. This leads to the inability to effectively track and attack when the enemy performs large angle maneuvering. Additionally, these algorithms cannot adapt to different situations, resulting in the unmanned fighter aircraft being at a disadvantage in some cases. To solve these problems, this paper proposes predictive air combat decision model with segmented reward allocation for air combat tracking and attacking. On the basis of the air combat environment, we propose the prediction soft actor-critic (Pre-SAC) algorithm, which combines the prediction of enemy states with the states of UCAV for model training. This enables the UCAV to predict the next move of the enemy UCAV in advance and establish a greater air combat advantage for us. Furthermore, by adopting a segmented reward allocation model and combining it with the Pre-SAC algorithm, we propose the segmented reward allocation soft actor-critic (Sra-SAC) algorithm, which solves the problem of UCAVs being unable to adapt to different situations. The results show that the prediction-based segmented reward allocation the Sra-SAC algorithm outperforms the traditional soft actor-critic (SAC) algorithm in terms of overall reward, travel distance, and relative advantage. [ABSTRACT FROM AUTHOR]

Background: The expression and function of coexpression genes of M1 macrophage in cervical cancer have not been identified. And the CXCL9-expressing tumour-associated macrophage has been poorly reported in cervical cancer. Methods: To clarify the regulatory gene network of M1 macrophage in cervical cancer, we downloaded gene expression profiles of cervical cancer patients in TCGA database to identify M1 macrophage coexpression genes. Then we constructed the protein-protein interaction networks by STRING database and performed functional enrichment analysis to investigate the biological effects of the coexpression genes. Next, we used multiple bioinformatics databases and experiments to overall investigate coexpression gene CXCL9, including western blot assay and immunohistochemistry assay, GeneMANIA, Kaplan-Meier Plotter, Xenashiny, TISCH2, ACLBI, HPA, TISIDB, GSCA and cBioPortal databases. Results: There were 77 positive coexpression genes and 5 negative coexpression genes in M1 macrophage. The coexpression genes in Ml macrophage participated in the production and function of chemokines and chemokine receptors. Especially, CXCL9 was positively correlated with M1 macrophage infiltration levels in cervical cancer. CXCL9 expression would significantly decrease and high CXCL9 levels were linked to good prognosis in the cervical cancer tumour patients, it manifestly expressed in blood immune cells, and was positively related to immune checkpoints. CXCL9 amplification was the most common type of mutation. The CXCL9 gene interaction network could regulate immune-related signalling pathways, and CXCL9 amplification was the most common mutation type in cervical cancer. Meanwhile, CXCL9 may had clinical significance for the drug response in cervical cancer, possibly mediating resistance to chemotherapy and targeted drug therapy. Conclusion: Our findings may provide new insight into the Ml macrophage coexpression gene network and molecular mechanisms in cervical cancer, and indicated that Ml macrophage association gene CXCL9 may serve as a good prognostic gene and a potential therapeutic target for cervical cancer therapies. [ABSTRACT FROM AUTHOR]

Background: Adrenocortical carcinoma (ACC) is a rare malignant tumor that occurs in the adrenal cortex. It has a high degree of malignancy and comparatively poor overall prognosis. Surgery is the standard curative therapy for localized ACC patients. The combination regimen of etoposide, doxorubicin, cisplatin (EDP) plus mitotane has been considered as the standardized chemotherapy regimen for advanced ACC. However, new effective regimens are emerging for specific conditions in metastatic ACC. Case presentation: We report a case of a 66-year-old man diagnosed with metastatic ACC who had a large left adrenal mass (110 mm × 87 mm) and multiple metastases in both lungs. The patient was treated with EP and sintilimab for six cycles; anlotinib was introduced after the third cycle. Follow-ups after the second to fourth cycles found significantly reduced lung metastases with all imaging examinations indicating partial response (PR) status. The patient received maintenance therapy thereafter with sintilimab plus anlotinib. Until recently, the patient’s lung metastases and the left adrenal gland area mass (39mm × 29mm) have disappeared, and no disease progression has been observed. The progression-free survival of this patient has been extended to approximately 31 months, in sharp contrast to a median survival time of 12 months for majority of advanced ACC. The main adverse events during treatment were appetite loss and grade I myelosuppression and revealed only grade I hypertension and grade I hypothyroidism. Conclusion: This case highlights the remarkable response of our patient’s ACC to treatment with a novel combination of EP and sintilimab combined with anlotinib. Our findings suggest a safe and more effective combination therapeutic option for patients with adrenocortical carcinoma. [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel method to recognize the digital modulation communication signals with alpha-stable noise over fading channels. Specifically, the probability density function of alpha-stable noise is determined by kernel density estimation, and the fading channel parameters are measured by utilizing the improved expectation conditional maximization algorithm. Then we leverage the compound hypothesis test model, which serves as a classifier, to implement modulation recognition. Simulation results show that the proposed method is robust to alpha-stable noise over fading channels. Moreover, the correct average recognition rates of the digital modulation communication signals under alpha-stable noise is more than 90%, when the generalized signal-to-noise ratio is 10dB. [ABSTRACT FROM AUTHOR]

Objective: To identify recurrent venous thromboembolism (VTE) after discontinuation of anticoagulation in patients with isolated distal deep vein thrombosis based on its anatomic localization (axial or muscular veins). Methods: Data were sourced from PubMed, Embase, Cochrane Library, Web of Science, and ClinicalTrials.gov databases in the time period up to October 2023. The study followed PRISMA guidelines using a registered protocol (CRD42023443029). Studies reporting recurrent VTE in patients with axial or muscular DVT were included in the analysis. Results: Five studies with a total of 1,403 participants were evaluated. The results showed a pooled odds ratio of 1.12 (95% confidence interval 0.77–1.63) between axial and muscular DVT. Heterogeneity was low (I2 = 0%, p = 0.91) and there was no significant difference in the rate of recurrent VTE between axial and muscular DVT in each subgroup. Conclusions: Muscular and axial DVT showed comparable recurrent VTE rates after anticoagulation. However, uncertainties regarding the possibility of recurrence affecting the popliteal vein or resulting in pulmonary embolism following muscular DVT anticoagulation persisted. Randomized trials in patients with isolated distal DVT are still needed to clarify its prognosis for different anatomical thrombus locations. [ABSTRACT FROM AUTHOR]

Background: Patients with coronavirus disease 2019 have a high incidence of thrombosis that decreases after recovery. When coronavirus disease 2019 is accompanied by diseases prone to thrombosis, risk of post-infection thrombotic events may increase. Case presentation: We report a case of digital ischemic gangrene in a 24-year-old Chinese female with systemic lupus erythematosus after recovery from coronavirus disease 2019. The pathogenesis was related to clinical characteristics of systemic lupus erythematosus, hypercoagulability caused by coronavirus disease 2019, and second-hit due to viral infection. Conclusion: Patients with autoimmune diseases should remain alert to autoimmune system disorders induced by severe acute respiratory syndrome coronavirus 2 and other viruses. Treatment for these patients should be strictly standardized, and appropriate anticoagulation methods should be selected to prevent thrombosis. [ABSTRACT FROM AUTHOR]

Objective: To compare the predictive efficacy of the PADUA and Caprini models for pulmonary embolism (PE) in gynecological inpatients, analyze the risk factors for PE, and validate whether both models can effectively predict mortality rates. Methods: A total of 355 gynecological inpatients who underwent computed tomography pulmonary angiography (CTPA) were included in the retrospective analysis. The comparative assessment of the predictive capabilities for PE between the PADUA and Caprini was carried out using receiver operating characteristic (ROC) curves. Logistic regression analysis was used to identify risk factors associated with PE. Additionally, Kaplan–Meier survival analysis plots were generated to validate the predictive efficacy for mortality rates. Results: Among 355 patients, the PADUA and Caprini demonstrated the area under the curve (AUC) values of 0.757 and 0.756, respectively. There was no statistically significant difference in the AUC between the two models (P = 0.9542). Multivariate logistic analysis revealed immobility (P < 0.001), history of venous thromboembolism (VTE) (P = 0.002), thrombophilia (P < 0.001), hormonal treatment (P = 0.022), and obesity (P = 0.019) as independent risk factors for PE. Kaplan–Meier survival analysis demonstrated the reliable predictive efficacy of both the Caprini (P = 0.00051) and PADUA (P = 0.00031) for mortality. ROC for the three- and six-month follow-ups suggested that the Caprini model exhibited superior predictive efficacy for mortality. Conclusions: The PADUA model can serve as a simple and effective tool for stratifying high-risk gynecological inpatients before undergoing CTPA. The Caprini model demonstrated superior predictive efficacy for mortality rates. [ABSTRACT FROM AUTHOR]

Acute promyelocytic leukemia (APL) is a type of acute myeloid leukemia. About 2% of APL is characterized by atypical rearrangements. Here we reported one APL case with atypical manifestations and morphology. A 35-year-old woman patient, mainly due to fatigue, poor appetite for over 10 days and intermittent fever for 3 days. combined with the results of flow cytometry, fusion gene and chromosome, the patient was diagnosed as AML-M3 with atypical morphology. Double induction therapy with retinoic acid and arsenous acid was immediately administrated. Idarubicin was administrated on the 18th day. A re-examination was performed in the 5th week, both the blood routine test and myelogram showed normal results, and the fusion gene turned negative, indicating complete remission. When atypical morphology occurs, peripheral blood POX staining may be performed to check the abnormal cells. Flow cytometry, chromosome analysis, and fusion gene analysis are also required for further diagnosis. [ABSTRACT FROM AUTHOR]

Olivine (Fo80-88) from the Shitoukengde deposit exhibits low levels of Ca, Cr, and Al (< 220 ppm) and varying Ni content. The low Ca-Cr-Al contents in olivine and subsolidus temperatures (600–900 °C) indicated by olivine-spinel thermometers align with subsolidus equilibria, emphasizing substantial postcumulus modifications. Therefore, the postcumulus effect must be considered when applying olivine-spinel oxybarometers to intrusive rocks. Back-calculating the spinel Fe–Mg contents to magmatic temperature, the estimated oxidation fugacity (fO2) range between FQM − 1.5 and FQM − 3.0, approximately 0.5 to 1.5 ΔFQM more reduced compared to those calculated from the raw spinel composition. Moreover, the fO2 aligns with results obtained from the olivine-sulfide pair (FMQ − 3.0 to FMQ 0). The considerably reducing state and wide oxidation variation are consistent with the graphite occurrence within the reduced intervals and the systematic fO2 indicated by olivine V/Sc ratios. Combined with the wide olivine Ni range (200–1500 ppm) and the restricted Ni tenor in coexisting sulfides, those findings imply that the olivine-sulfide interaction was predominantly controlled by fO2. Diffusion modeling at magmatic temperatures reveals that the core-level Fe–Ni re-equilibration after crystallization requires hundreds of years. The homogeneous olivine composition suggests that re-equilibrium has been achieved in Shitoukengde. However, in fast cooling systems, olivine may record the status approaching olivine-sulfide equilibration, leading to extensive intragrain Ni variation (up to 1000 ppm). This study highlights that extreme Ni depletion in olivine from sulfide-bearing rocks is a sign of reducing conditions. Strongly Ni-rich olivine, such as those in the Kevitsa deposit, could result from interaction with high-Ni tenor sulfides at oxidizing conditions. [ABSTRACT FROM AUTHOR]

Variability in seasonal weather in north‐west Europe is substantially determined by jet stream variability. The North Atlantic Oscillation (NAO) has been well studied as a key representation of this jet stream variability, but other circulation indices are also important. Here the first three principal component empirical orthogonal functions (EOFs) of 500 hPa geopotential height (GPH), which broadly correspond to the NAO, the East Atlantic pattern (EA) and Scandinavian pattern (SCA), as well as jet speed and latitude, are correlated with temperature and precipitation anomalies over Europe with a focus on north‐west Europe, as well as measures of persistence and variability. In high summer (July and August), all three of the principal EOFs are significantly correlated with extreme temperatures in large areas of northern Europe. In winter, for much of north‐west Europe, both temperatures and precipitation are positively correlated with the jet speed, and precipitation is negatively correlated with EOF3. There is some non‐stationarity in some of the relationships, notably between winter precipitation and EOF1, and between July/August precipitation and EOF2. In addition to single variate correlations, multiple correlation coefficients are also used to determine areas of significant correlation when combining two or three of the circulation indices. The multiple correlation analyses show that combining the three EOFs produces significant correlations with temperature and precipitation over much of Europe. These analyses provide scope for using seasonal forecasts to predict likely temperature and precipitation anomalies based on predicting the atmospheric circulation anomalies and downscaling them. Improved seasonal forecasts of temperature and precipitation, including persistence and variability, will be useful to a number of users, such as agrifood, transport, energy supply and insurance. [ABSTRACT FROM AUTHOR]

Purpose: Proximal contact loss (PCL) between implant-supported fixed dental prostheses (FDPs) and adjacent teeth has been reported as a common complication of implant therapy. The prevalence of PCL and its potential risk factors have been extensively studied. However, few studies have discussed the recurrent PCL after intervention to restore the proximal contacts. Thus, this retrospective study aimed to evaluate the recurrence rate of PCL and its potential risk factors. Materials and Methods: This study included 41 patients (with 45 implants in the posterior region), who had experienced PCL between implant restorations and adjacent teeth and had received contact repair. Recurrent PCL was recorded and evaluated during routine follow-ups with an interval of 6 to 12 months. The recurrence rates and time were measured. The potential influential factors of PCL were also assessed. Fisher exact test, t test, univariate logistic regression analyses, and multivariate logistic regression model were utilized to identify factors influencing PCL. Results: The recurrence rates of mesial PCL were high (> 50%) and the recurrence time became progressively rapid after each repair (5, 3.2, and 2.2 years). Implants with the first PCL recurrence were more likely to be splinted than those implants without recurrence (54.5% vs 18.8%; P = .032). In addition, patients with the first recurrence were slightly older than those without recurrence (55.8 vs 50.1 years; P = .087). Age, implant restoration (splinted vs single), frequent use of interdental brushes, and time to first complaint were the candidate factors associated with recurrent PCL in the univariate logistic regression analysis. The multivariate logistic regression model revealed that only splinted implant restoration was independently associated with a higher risk of recurrence (odds ratio 4.99; 95% confidence interval 1.02--24.31; P = .047). Conclusion: The recurrence rates of mesial PCL were high and associated with the splinted-type design. Also, the recurrence time of PCL accelerated after each repair. Therefore, routine follow-up monitoring PCL and carefully assessing patient compliance after implant therapy are recommended. [ABSTRACT FROM AUTHOR]

Tide level forecasting plays an important role in environmental management and development. Current tide level forecasting methods are usually implemented for solving single task problems, that is, a model built based on the tide level data at an individual location is only used to forecast tide level of the same location but is not used for tide forecasting at another location. This study proposes a new method for tide level prediction at multiple locations simultaneously. The method combines nonlinear autoregressive moving average with exogenous inputs (NARMAX) model and recurrent neural networks (RNNs), and incorporates them into a multi-task learning (MTL) framework. Experiments are designed and performed to compare single task learning (STL) and MTL with and without using non-linear autoregressive models. Three different RNN variants, namely, long shortterm memory (LSTM), gated recurrent unit (GRU) and bidirectional LSTM (BiLSTM) are employed together with non-linear autoregressive models. A case study on tide level forecasting at many different geographical locations (5 to 11 locations) is conducted. Experimental results demonstrate that the proposed architectures outperform the classical single-task prediction methods. [ABSTRACT FROM AUTHOR]

Dynamical seasonal forecast models are improving with time but tend to underestimate the amplitude of atmospheric circulation variability and to have lower skill in predicting summer variability than in winter. Here, we construct Nonlinear AutoRegressive Moving Average models with eXogenous inputs (NARMAX) to develop the analysis of drivers of North Atlantic atmospheric circulation and jet‐stream variability, focusing on the East Atlantic (EA) and Scandinavian (SCA) patterns as well as the North Atlantic Oscillation (NAO) index. New time series of these indices are developed from empirical orthogonal function (EOF) analysis. Geopotential height data from the ERA5 reanalysis are used to generate the EOFs. Sets of predictors with known associations with these drivers are developed and used to formulate a sliding‐window NARMAX model. This model demonstrates a high degree of predictive accuracy, as indicated by its average correlation coefficients over the testing period (2006–2021): 0.78 for NAO, 0.83 for EA and 0.68 for SCA. In comparison, the SEAS5 and GloSea5 dynamical forecast models exhibit lower correlations with observed circulation changes: for NAO, the correlation coefficients are 0.51 for SEAS5 and 0.34 for GloSea5, for EA they are 0.15 and 0.09, respectively, and for SCA, they are 0.28 and 0.24, respectively. Comparison of NARMAX predictions with forecasts and hindcasts from the SEAS5 and GloSea5 models highlights areas where NARMAX can be used to help improve seasonal forecast skill and inform the development of dynamical models, especially in the case of summer. [ABSTRACT FROM AUTHOR]

A critical event in the pathogenesis of kidney fibrosis is the transition of macrophages into myofibroblasts (MMT). Exosomes play an important role in crosstalk among cells in the kidney and the development of renal fibrosis. However, the role of myofibroblast-derived exosomes in the process of MMT and renal fibrosis progression remains unknown. Here, we examined the role of myofibroblast-derived exosomes in MMT and kidney fibrogenesis. In vitro, transforming growth factor-β1 stimulated the differentiation of kidney fibroblasts into myofibroblasts and promoted exosome release from myofibroblasts. RAW264.7 cells were treated with exosomes derived from myofibroblasts. We found purified exosomes from myofibroblasts trigger the MMT. By contrast, inhibition of exosome production with GW4869 or exosome depletion from the conditioned media abolished the ability of myofibroblasts to induce MMT. Mice treatment with myofibroblast-derived exosomes (Myo-Exo) exhibited severe fibrotic lesion and more abundant MMT cells in kidneys with folic acid (FA) injury, which was negated by TANK-banding kinase-1 inhibitor. Furthermore, suppression of exosome production reduced collagen deposition, extracellular matrix protein accumulation, and MMT in FA nephropathy. Collectively, Myo-Exo enhances the MMT and kidney fibrosis. Blockade of exosomes mediated myofibroblasts– macrophages communication may provide a novel therapeutic target for kidney fibrosis. [ABSTRACT FROM AUTHOR]

Supervisory control and data acquisition (SCADA) systems are widely utilized in power equipment for condition monitoring. For the collected data, there generally exists a problem—missing data of different types and patterns. This leads to the poor quality and utilization difficulties of the collected data. To address this problem, this paper customizes methodology that combines an asymmetric denoising autoencoder (ADAE) and moving average filter (MAF) to perform accurate missing data imputation. First, convolution and gated recurrent unit (GRU) are applied to the encoder of the ADAE, while the decoder still utilizes the fully connected layers to form an asymmetric network structure. The ADAE extracts the local periodic and temporal features from monitoring data and then decodes the features to realize the imputation of the multi-type missing. On this basis, according to the continuity of power data in the time domain, the MAF is utilized to fuse the prior knowledge of the neighborhood of missing data to secondarily optimize the imputed data. Case studies reveal that the developed method achieves greater accuracy compared to existing models. This paper adopts experiments under different scenarios to justify that the MAF-ADAE method applies to actual power equipment monitoring data imputation. [ABSTRACT FROM AUTHOR]

Background: Enhanced imaging techniques have the overwhelming advantages of being noninvasive and sensitive enough to evaluate the microcirculation of lesions, thus making them accurate in the diagnosis of hepatic lesions. Unfortunately, there is very little research on and knowledge of the imaging features of a rare cancerous condition: hepatic angiosarcoma (HA). Case summary: In this study, we retrospectively collected the data of six patients who underwent both contrast-enhanced ultrasound (CEUS) and contrast-enhanced computed tomography (CECT), and subsequently obtained a definitive histopathologic diagnosis of HA. We described the imaging appearances of HA by comparing CEUS and CECT images. Furthermore, we analyzed these imaging characteristics from the perspective of histopathology and tumorigenesis. The study included the largest number (six) of histopathologically confirmed HA patients who had received CEUS examinations to date. Conclusion: By offering readers comprehensive knowledge of contrast imaging, especially CEUS, in the diagnosis of HA, our study may reduce misdiagnosis and further improve treatment options. [ABSTRACT FROM AUTHOR]

Objective: Primary blepharospasm (BSP) is a clinically heterogeneous disease that manifests not only as spasmodic closure of the eyelids but also sometimes with apraxia of eyelid opening (AEO). This cross-sectional study aimed to investigate differences in the neural mechanisms of isolated BSP and BSP-associated AEO subtypes, which may reveal the pathophysiology underlying different phenotypes. Methods: A total of 29 patients manifested as isolated BSP, 17 patients manifested as BSP associated with AEO, and 28 healthy controls underwent resting-state functional near-infrared spectroscopy (fNIRS). We assessed functional connectivity (FC) between regions of interest (ROIs) in the fronto-parietal control network (PFCN) and sensorimotor network (SMN). We also examined the relationship between altered FC and behavioral data. Results: In the FPCN, ROI- analyses showed decreased FC between the left premotor cortex and supramarginal gyrus in the BSP with AEO group compared to the isolated BSP group. In the SMN, both subgroups showed hypoconnectivity of the left premotor cortex with the right primary motor cortex, primary sensory cortex, and somatosensory association cortex. This hypoconnectivity was positively correlated with the total number of botulinum toxin A treatments, which suggests that long-term botulinum toxin A treatment may modulate motor sequence planning and coordination. Conclusion: These findings showed different connectivity alterations in neural networks associated with motor and cognitive control among different behavioral phenotypes of BSP. The identification of specific alterations in various networks that correspond to clinical heterogeneity may inform the identification of potential biomarkers for early diagnosis and personalized neuromodulation targets for treating different BSP subphenotypes. [ABSTRACT FROM AUTHOR]

Rainfall-induced hydrological processes and surface water flow hydrodynamics may play a key role in initiating debris flows. In this study, a new framework based on an integrated hydrological and hydrodynamic model is proposed to estimate the Intensity-Duration (I-D) rainfall thresholds that trigger debris flows. In the new framework, intensity-duration-frequency (IDF) analysis is carried out to generate design rainfall to drive the integrated models to calculate grid-based hydrodynamic indices (i.e. unit-width discharge). The hydrodynamic indices are subsequently compared with hydrodynamic thresholds to indicate the occurrence of debris flows and derive rainfall thresholds through the introduction of a zone threshold. The capability of the new framework in predicting the occurrence of debris flows is verified and confirmed by application to a small catchment in Zhejiang Province, China, where observed hydrological data are available. Compared with the traditional statistical approaches to derive Intensity-Duration (I-D) thresholds, the current physically-based framework can effectively take into account the hydrological processes controlled by meteorological conditions and spatial topographic properties, making it more suitable for application in ungauged catchments where historical debris flow data is lacking. [ABSTRACT FROM AUTHOR]

Fractional‐order calculus has broad application scenarios in engineering and physics. Unlike integer‐order calculus, fractional‐order calculus has the ability to analyze nonclassical phenomena in science and engineering. For industrial processes with strong nonlinear characteristics, nonlinear models such as the Wiener model have become research hotspots. This paper studies the parameter identification of the fractional‐order Wiener system. In this paper, the forgetting factor extended stochastic gradient (FF‐ESG) algorithm and the gradient iterative (GI) algorithm are proposed to identify the parameters of the fractional‐order Wiener system. Then, the convergence of the FF‐ESG algorithm for the fractional‐order Wiener system is analyzed. Both proposed algorithms can obtain exact parameter estimates, which are verified by a numerical example and a case study of a fluid control valve. [ABSTRACT FROM AUTHOR]

The modelling and analysis of appliance energy use (AEU) of residential buildings are important for energy consumption control, energy management and maintenance, building performance evaluation, and so on. Although some traditional machine learning methods have been applied to produce good prediction results, these models are usually not interpretable, in that they fail to explain how appliance factors make contributions to the variation of AEU individually and interactively. Explicitly knowing the role played by each of the appliance factors in explaining AEU, however, is very important for energy saving. Motivated by this observation, this study introduces an interpretable machine learning approach which is built upon the nonlinear autoregressive moving average with eXogenous inputs model. The advantage of the proposed model is that in comparison with other state-of-the-art machine learning methods, for example, feedforward neural network, recurrent neural network (e.g., gated recurrent unit), and long short-term memory network, the established model is not only able to produce more accurate energy use prediction, but more importantly, also fully transparent and physically interpretable, clearly and explicitly indicating which factors significantly affect the variation of AEU. The findings of this study provide meaningful insights for improving the AEU efficiency. [ABSTRACT FROM AUTHOR]

Fixed-wing unmanned aerial vehicles (UAVs) will play a vital role in forthcoming military conflicts. Effectively avoiding threats and improving the survivability of fixed-wing UAV in dynamic hostile environments are the keys to the success of combat missions. Hence, endowing fixed-wing UAVs with the ability to autonomously generate evasive maneuver is the primary problem that should be solved. With considering the threat of air-to-air missile attacks, this paper designs a novel hierarchical goal-guided learning (HGGL) method, which combines with traditional off-policy deep reinforcement learning (DRL) algorithms and endows the agent with the ability to evade a series of air-to-air missiles. The pivotal idea of the proposed algorithm is to use the hierarchical features of the goal, it improves the availability of training data to eliminate the limitation of the convergence rate of traditional DRL algorithms owing to sparse rewards. We demonstrate the performance of our algorithm in several simulation experiments. All experiments are applied on the XSimStudio platform. The results demonstrate that the proposed algorithm improves the convergence speed and outperforms the state-of-the-art traditional algorithms. [ABSTRACT FROM AUTHOR]

Adverse pressure gradients can cause severe flow separation within typical S-shaped inlets. This results in a total pressure distortion at the aerodynamic interface plane (AIP). The expansive bending pipe, where flow separation also occurs due to the adverse pressure gradient, is the basis for investigations into S-shaped inlets. In this study, surface dielectric barrier discharge (SDBD) plasma actuators are used to moderate the total pressure distortion in the AIP of an expansive bending pipe under a 10 m/s incoming flow. Also, the influences of actuation voltage amplitude and pulsed frequency on the total pressure distortion of the AIP are investigated under two plasma actuation modes, nanosecond pulsed SDBD and alternating current (AC) SDBD. Under optimal actuation parameters, the nanosecond pulsed SDBD and the AC-SDBD can reduce the distortion index by 14.93% and 32.22%, respectively. The results demonstrate the effectiveness of SDBD plasma actuators in suppressing flow separation within expansive bending pipes. [ABSTRACT FROM AUTHOR]

Objective: Compression therapy with the use of graduated compression stockings (GCSs) is a common treatment strategy for chronic venous disease (CVD). However, there is no uniform and objective standard to assess adherence to the use of GCSs. The aim of this study is to develop and validate a GCS Compliance Scale (GCSAS) to fill gaps in internationally recognized comprehensive scales and provide a useful tool for future research. Methods: The items included in the GCSAS were based on a review of the literature and open-ended interviews with experts, who screened the initial items using an item-level content validity index. Then, pilot tests were conducted three times with 50 participants. After exclusion of redundant and cross-loading items by exploratory factor analysis, 290 subjects were recruited to evaluate the reliability and validity of the proposed GCSAS. Analyses included internal consistency, test–retest reliability, split-half reliability, construct validity, criterion validity, convergent validity, and discriminant validity. Results: The final GCSAS consisted of 17 items and 5 dimensions. The results of the exploratory factor analysis indicated that the variances of each factor explained were 22.03%, 14.85%, 14.74%, 14.16%, and 13.35%, and all 5 factors explained 79.13% of the variance among the 17 items. The factor loadings of all items were >0.7. Confirmatory factor analysis indicated that the indices were adequate. A significant positive correlation was found between the GCSAS and the Venous Insufficiency Epidemiological and Economic Study - Quality of Life questionnaire scores (r = 0.76, p < 0.001). The Cronbach's alpha coefficient was 0.90, test–retest reliability was 0.81, and split-half reliability was 0.92. Conclusions: The GCSAS showed good validity and reliability to assess compliance with the use of GCSs among patients with CVD. [ABSTRACT FROM AUTHOR]

In this article, the problem of parameter estimation for a multiple‐input single‐output Hammerstein controlled autoregressive (MISO‐HCAR) model is solved. After establishing the identification model of MISO‐HCAR system, an improved adaptive moment estimation algorithm with decreasing weight (IADAM) is proposed. The improved algorithm transforms the nonlinear system identification problem into a parameter space optimization problem, according to the input and output data obtained from the system, and uses the parallel search ability of the IADAM algorithm to estimate all the parameters of the system simultaneously. Two numerical examples and the case study example of chemical continuously stirred tank reactor (CSTR) system show that the proposed IADAM algorithm with decreasing weight has better identification effect on the MISO‐HCAR model and CSTR system than the stochastic gradient descent (SGD) algorithm and the basic adaptive moment estimation (ADAM) algorithm, and the estimation accuracy and convergence speed are greatly improved. Thus, the IADAM can estimate the parameters of the MISO‐HCAR system and the CSTR system more effectively. [ABSTRACT FROM AUTHOR]

Objective: Since coronary artery lesions (CALs) are the most severe complication of Kawasaki disease (KD), clinically speaking, early prediction of CALs is crucial. The authors aimed to investigate the predictive value of C-reactive protein (CRP) in predicting CALs in KD patients. Methods: KD patients were divided into the CALs group and the non-CALs group. The clinical and laboratory parameters were collected and compared. Multivariate logistic regression analysis was used to determine the independent risk factors of CALs. The receiver operating characteristic curve was applied to determine the optimal cut-off value. Results: 851 KD patients who met the inclusion criteria were studied, including 206 in the CALs group and 645 in the non-CALs group. Children in the CALs group had significantly higher CRP levels than the non-CALs group (p < 0.05). Multivariable logistic regression analysis showed that incomplete KD, male, lower hemoglobin, and higher CRP were independent risk factors for predicting CAL (all p < 0.05). The optimal cut-off value of initial serum CRP for predicting CALs was 105.5 mg/L, with a sensitivity of 47.57% and a specificity of 69.61%. In addition, KD patients with high CRP ((105.5 mg/L) had a higher occurrence of CALs than those with low CRP (<105.5 mg/L) (33% vs 19%, p < 0.001). Conclusion: The incidence of CALs was significantly higher in patients with high CRP. CRP is an independent risk factor for CALs formation and may be useful for predicting CALs in KD patients. [ABSTRACT FROM AUTHOR]

Data-driven fault detection techniques have attracted extensive attention in engineering, industry and many other areas in recent years. In many real applications, the following situation often occurs: data for certain types of faults (unseen faults) are not available to train models that are used for fault detection. Such a scenario can occur when data collection becomes highly time-consuming or destructive. To address this challenging problem, a novel fault detection method using zero-shot learning (ZSL) is proposed in this paper, which contains three phases: feature extraction, label embedding, and feature embedding. The method first extracts features from raw signals by applying a one-dimensional convolutional neural network (1D CNN), then builds semantic descriptions (human-defined) as fault attributes shared between seen faults and unseen faults, and finally uses a bi-linear compatibility function to find the highest-ranking fault type. The proposed semantic space based zero-shot learning with 1D CNN is called SSB-ZSL-1DCNN. The cosine distance is used to measure the similarity between feature embeddings and fault attributes. An important characteristic of SSB-ZSL-1DCNN is that the model, trained using only samples of seen faults, can be used to detect unseen defects. To evaluate the proposed method, two case studies are designed based on two well-known benchmarks (the Tennessee-Eastman chemical control process and the rolling bearing experiments at the Case Western Reserve University, respectively). The results demonstrate that the proposed method shows remarkable performance in detecting unseen faults. [ABSTRACT FROM AUTHOR]

ZrB2-SiC-Zr2Al4C5 multi-phase ceramics with uniform structure and high density were successfully prepared through the introduction of in situ synthesized Zr2Al4C5 into ZrB2-SiC ceramic via SPS at 1800 °C. A systematic analysis and discussion of the experimental results and proposed mechanisms were carried out to demonstrate the composition-dependent sintering properties, mechanical properties and oxidation behavior. The results showed that the in situ synthesized Zr2Al4C5 could be evenly distributed in the ZrB2-SiC ceramic matrix and inhibited the growth of ZrB2 grains, which played a positive role in the sintering densification of the composite ceramics. With increasing Zr2Al4C5 content, the Vickers hardness and Young's modulus of composite ceramics gradually decreased. The fracture toughness showed a trend that first increased and then decreased, and was increased by about 30% compared with ZrB2-SiC ceramics. The major phases resulting from the oxidation of samples were ZrO2, ZrSiO4, aluminosilicate and SiO2 glass. With increasing Zr2Al4C5 content, the oxidative weight showed a trend that first increased then decreased; the composite ceramic with 30 vol.% Zr2Al4C5 showed the smallest oxidative weight gain. We believe that the presence of Zr2Al4C5 results in the formation of Al2O3 during the oxidation process, subsequently resulting in a lowering of the viscosity of the glassy silica scale, which in turn intensifies the oxidation of the composite ceramics. This would also increase oxygen permeation through the scale, adversely affecting the oxidation resistance of the composites with high Zr2Al4C5 content. [ABSTRACT FROM AUTHOR]

Objective: To explore the carrying status and homology of carbapenem resistant Acinetobacter baumannii (CRAB) in our hospital. Methods: From January 2015 to December 2017, 52 strains of acinetobacter baumannii isolated from the bacteria room of the clinical laboratory of Baogang hospital in Inner Mongolia were selected as the research object. KB disk diffusion method and Vitek-2 were used to determine the drug sensitivity of Acinetobacter baumannii. The drug resistance gene was detected by polymerase chain reaction (PCR) and its homology was analyzed by pulsed field gel electrophoresis (PFGE). Results: Except for Cefoperazone/sulbactam, other antibiotics were resistant to ab. The detection rate of drug resistance gene class C b-lactamases (ADC) was 100%, and the higher detection rates of other drug resistance genes were class D b-lactamases (OXA)-51 (36 strains, 90.0%), disinfectant gene qacE1-sull (32 strains, 80.0%), and klebsiella pneumoniae carbapenemase (KPC) gene was not detected. 2-8 drug resistance genes were detected in each CRAB strain, and the strains with 6 drug resistance genes were the most (15 strains, 37.5%); Among the detected drug-resistant gene combinations, ADC+OXA-23 + OXA-51 gene was detected at the same time (29 strains, 72.5%), followed by ADC+ intl1 + qacE1-sull gene (26 strains, 65.0%), ADC + qacE 1-sull + ant (3") -i gene (19 strains, 47.5%), and 11 strains (27.5%). There were 19 different types in PFGE homology test, each type was 1-9 strains, including 9 strains of A5 type and 8 strains of A18 type, mainly from intensive care unit. Conclusion: CRAB in the hospital is highly resistant to common clinical antibiotics. OXA-23 and OXA-51 genes are most likely to be the main factors causing drug resistance of Acinetobacter baumannii in the hospital. Homology analysis showed that there was CRAB nosocomial infection transmission in different wards of the hospital. [ABSTRACT FROM AUTHOR]

This study aimed to explore the characteristics of bongkrekic acid (BA) produced by Burkholderia gladioli pathovar cocovenenans (BGC) and the effects of ambient temperature and humidity on BA production in the fermented glutinous rice flour (FGRF). In the specific environment with various ambient temperatures (10±1, 15±1, 20±1, 25±1, 30±1, 36±1 °C) and relative humidity (20%, 40%, 60%), The FGRF was incubated with different bacteria counts of BGC (10³, 105, 107 CFU/mL), and BA in the FGRF was measured with high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The results revealed that BA could be detectable after only one day of incubation. The BA produced and accumulated by BGC with an initial bacteria count of 10³ CFU/mL was more than that in the groups with the initial bacteria counts of 105 and 107 CFU/mL (with a difference of 1-3 μg/kg between groups). Lower temperatures (10±1, 15±1, 20±1 °C) and humidity (20%) were found to reduce the BA production of BGC in the FGRF. To minimize the risk of foodborne BA poisoning, it is recommended to consume freshly prepared FGRF promptly and avoid storing it for extended periods under hot and humid conditions. [ABSTRACT FROM AUTHOR]

To assess the safety and efficacy of endovascular embolization techniques, we compared the short- to medium-term prognosis of coil embolization for symptomatic visceral aneurysms (SVAA) and asymptomatic visceral aneurysms (ASVAA) to identify risk factors associated with 30-day mortality. Explore the symptom profile and intrinsic associations of SVAA. A retrospective study of 66 consecutive patients at two tertiary care hospitals from 2010 to 2020 compared the short- to mid-term outcomes of 22 symptomatic VAAs and 44 asymptomatic VAAs treated with coil embolization. Univariate and log-rank tests were used to analyze the prognostic impact of SVAA and ASVAA. SVAA group had significantly higher 30-day mortality than ASVAA group (2(9.1%) vs 0, P = 0.042), both patients who died had symptomatic pseudoaneurysms. Perioperative complications such as end-organ ischemia (P = 0.293) and reintervention (P = 1) were similar in both groups. No difference in event-free survival was identified between the two groups (P = 0.900), but we found that the majority of pseudoaneurysms were SVAA (4/5) and that they had a much higher event rate than true aneurysms. In addition, dyslipidemia may be an influential factor in the development of VAA (P = 0.010). Coil embolization is a safe and effective method of treatment for VAA. Most pseudoaneurysms have symptoms such as abdominal pain and bleeding, and in view of their risk, more attention should be paid to symptomatic patients and the nature of the aneurysm should be determined as soon as possible to determine the next stage of treatment. [ABSTRACT FROM AUTHOR]

Purpose: Minimal hepatic encephalopathy (MHE) is characterized by mild neuropsychological and neurophysiological alterations that are not detectable by routine clinical examination. Abnormal brain activity (in terms of the amplitude of low-frequency fluctuation (ALFF) has been observed in MHE patients. However, little is known concerning temporal dynamics of intrinsic brain activity. The present study aimed to investigate the abnormal dynamics of brain activity (dynamic ALFF; dALFF) and static measures [static ALFF; (sALFF)] in MHE patients and to strive for a reliable imaging neuromarkers for distinguishing MHE patients from cirrhosis patients. In addition, the present study also investigated whether intrinsic brain activity predicted the severity of liver damage. Methods: Thirty-four cirrhosis patients with MHE, 28 cirrhosis patients without MHE, and 33 age-, sex-, and education-matched healthy controls (HCs) underwent resting-state magnetic resonance imaging (rs-fMRI). dALFF was estimated by combining the ALFF method with the sliding-window method, in which temporal variability was quantized over the whole-scan timepoints and then compared among the three groups. Additionally, dALFF, sALFF and both two features were utilized as classification features in a support vector machine (SVM) to distinguish MHE patients from cirrhosis patients. The severity of liver damage was reflected by the Child-Pugh score. dALFF, sALFF and both two features were used to predict Child-Pugh scores in MHE patients using a general linear model. Results: Compared with HCs, MHE patients showed significantly increased dALFF in the left inferior occipital gyrus, right middle occipital gyrus, and right insula; increased dALFF was also observed in the right posterior lobe of the cerebellum (CPL) and right thalamus. Compared with HCs, noMHE patients exhibited decreased dALFF in the right precuneus. In contrast, compared with noMHE patients, MHE patients showed increased dALFF in the right precuneus, right superior frontal gyrus, and right superior occipital gyrus. Furthermore, the increased dALFF values in the left precuneus were positively associated with poor digit-symbol test (DST) scores (r = 0.356, p = 0.038); however, dALFF in the right inferior temporal gyrus (ITG) was negatively associated with the number connection test-A (NCT-A) scores (r = -0.784, p = 0.000). A significant positive correlation was found between dALFF in the left inferior occipital gyrus (IOG) and high blood ammonia levels (r = 0.424, p = 0.012). Notably, dALFF values yielded a higher classification accuracy than sALFF values in distinguishing MHE patients from cirrhosis patients. Importantly, the dALFF values predicted the Child-Pugh score (r = 0.140, p = 0.030), whereas sALFF values did not in the current dataset. Combining two features had high accuracy in classification in distinguishing MHE patients from cirrhotic patients and yielded prediction in the severity of liver damage. Conclusion: These findings suggest that combining dALFF and sALFF features is a useful neuromarkers for distinguishing MHE patients from cirrhosis patients and highlights the important role of dALFF feature in predicting the severity of liver damage in MHE. [ABSTRACT FROM AUTHOR]

Osteoporosis is a significant global health concern that can be difficult to detect early due to a lack of symptoms. At present, the examination of osteoporosis depends mainly on methods containing dual-energy X-ray, quantitative CT, etc., which are high costs in terms of equipment and human time. Therefore, a more efficient and economical method is urgently needed for diagnosing osteoporosis. With the development of deep learning, automatic diagnosis models for various diseases have been proposed. However, the establishment of these models generally requires images with only lesion areas, and annotating the lesion areas is time-consuming. To address this challenge, we propose a joint learning framework for osteoporosis diagnosis that combines localization, segmentation, and classification to enhance diagnostic accuracy. Our method includes a boundary heat map regression branch for thinning segmentation and a gated convolution module for adjusting context features in the classification module. We also integrate segmentation and classification features and propose a feature fusion module to adjust the weight of different levels of vertebrae. We trained our model on a self-built dataset and achieved an overall accuracy rate of 93.3% for the three label categories (normal, osteopenia, and osteoporosis) in the testing datasets. The area under the curve for the normal category is 0.973; for the osteopenia category, it is 0.965; and for the osteoporosis category, it is 0.985. Our method provides a promising alternative for the diagnosis of osteoporosis at present. [ABSTRACT FROM AUTHOR]

Objective: To investigate the optimal timing of initial intravenous immunoglobulin (IVIG) treatment in Kawasaki disease (KD) patients. Methods: KD patients were classified as the early group (day 1-4), conventional group (day 5-7), conventional group (day 8-10), and late group (after day 10). Differences among the groups were analyzed by ANOVA and Chi-square analysis. Predictors of IVIG resistance and the optimal cut-off value were determined by multiple logistic regression analyses and receiver operating characteristic (ROC) curve analysis. Results: There were no significant differences in IVIG resistance among the 4 groups (p = 0.335). The sensitivity analysis also confirmed no difference in the IVIG resistance between those who started the initial IVIG ≤ day 7 of illness and those who received IVIG >day 7 of illness (p = 0.761). In addition, patients who received IVIG administration more than 7 days from the onset had a higher proportion of coronary artery abnormalities (p = 0.034) and longer length of hospitalization (p = 0.033) than those who started IVIG administration less than 7 days. The optimal cut-off value of initial IVIG administration time for predicting IVIG resistance was >7 days, with a sensitivity of 75.25% and specificity of 82.41%. Conclusions: IVIG therapy within 7 days of illness is found to be more effective for reducing the risk of coronary artery abnormalities than those who received IVIG >day 7 of illness. IVIG treatment within the 7 days of illness seems to be the optimal therapeutic window of IVIG. However, further prospective studies with long-term follow-up are required. [ABSTRACT FROM AUTHOR]

Reward signal reinforcement learning algorithms can be used to solve sequential learning problems. However, in practice, they still suffer from the problem of reward imbalance, which limits their use in many contexts. To solve this unbalanced reward problem, in this paper, we propose a novel model-based reinforcement learning algorithm called the expected n-step value iteration (EnVI). Unlike traditional model-based reinforcement learning algorithms, the proposed method uses a new return function that changes the discount of future rewards while reducing the influence of the current reward. We evaluated the performance of the proposed algorithm on a Treasure-Hunting game and a Hill-Walking game. The results demonstrate that the proposed algorithm can reduce the negative impact of unbalanced rewards and greatly improve the performance of traditional reinforcement learning algorithms. [ABSTRACT FROM AUTHOR]

Although deep reinforcement learning (DRL) algorithms with experience replay have been used to solve many sequential learning problems, applications of DRL in real-world robotics still face some serious challenges, such as the problem of smooth movement. A robot's motion trajectory needs to be smoothly coded, with no sudden acceleration or jerk. In this paper, a novel hierarchical reinforcement learning control framework named the hierarchical dynamic movement primitive (HDMP) framework is proposed to achieve the smooth movement of robots. In contrast to traditional algorithms, the HDMP framework consists of two learning hierarchies: a lower-level controller learning hierarchy and an upper-level policy learning hierarchy. In the lower-level controller learning hierarchy, modified dynamic movement primitives (DMPs) are utilized to generate a smooth motion trajectory. In the upper-level policy learning hierarchy, an improved local proximal policy optimization (L-PPO) method is proposed to endow the robot with autonomous learning capabilities. The performance achieved with the HDMP algorithm has been evaluated in a classical reaching movement task based on a Sawyer robot. The experimental results demonstrate that the proposed HDMP algorithm can endow a robot with the ability to smoothly execute motor skills and learn autonomously. [ABSTRACT FROM AUTHOR]

Iododerma is an uncommon dermatosis caused by excessive iodine exposure and is associated with significant morbidity and mortality. Because of its heterogenous clinical presentation and variable histopathological findings, which depend on the time the skin biopsy is performed, the diagnosis of iododerma is often delayed. We report a rare case of acute iododerma in a woman with end‐stage diabetic nephropathy with antecedent radioiodine contrast exposure, presenting histopathologically as cryptococcoid neutrophilic dermatosis (CND). We underscore important clinicopathological pitfalls to avoid misdiagnosis with similar overlapping entities such as Sweet syndrome, review all published cases of CND and draw novel insights into its associated entities. [ABSTRACT FROM AUTHOR]

By taking the public welfare forest land in Jiangshan City of Zhejiang Province as the research object, based on the measured data of fixed sample plots and sublot of public welfare forest, the water conservation capacity and value of litter layer and soil layer in different forest stands were quantitatively measured and analyzed. The results showed that the effective interception amount of litter in different forest types of public welfare forest in Jiangshan City was coniferous and broad-leaved mixed forest>broad-leaved forest>Chinese fir forest>pine forest>moso bamboo forest. In the same depth of soil layer, the difference of soil physical properties and water holding capacity was not obvious. The soil layer contributed more than 99 % of the water conservation quantity of forest land. The order of water conservation ability was coniferous and broad-leaved mixed forest>broad-leaved forest>moso bamboo forest> Chinese fir forest>coniferous mixed forest>pine forest>shrub forest. The total annual water conservation quantity of public welfare forests in the whole city was 18 7,7869 million tons, with the value quantity of 1.979 billion yuan. The water conservation quantity per unit area was about 2813 t ⋅ hm-2, and the value quantity per unit area was about 29,700 yuan ⋅ hm-2. In Jiangshan City, the water conservation capacity of public welfare forest was stronger in the east, while the water conservation capacity of public welfare forest in the north was relatively weak. [ABSTRACT FROM AUTHOR]

Enkianthus calophyllus was once treated as a synonym of E. serrulatus. However, field observations indicate that E. calophyllus is distinct from E. serrulatus but resembles E. perulatus in flowers, leaves, fruits and seeds. Hence, a taxonomic revision of these species was conducted based on morphological comparisons of flowers, leaves, fruits and seeds, as well as molecular analyses of nuclear ribosomal internal transcribed spacer (nrITS) and six plastid DNA markers (psbA-trnH, rpl32-trnL, trnL-trnF, rps16-trnQ, psbJ-petA and matK). The morphological and molecular results reject the synonymization of E. calophyllus with E. serrulatus, and instead show it to be placed in a clade with E. perulatus. Based on molecular evidence and a reassessment of the morphology we synonymize E. calophyllus with the older name E. perulatus. [ABSTRACT FROM AUTHOR]

Polymyxin A1 was a rarely investigated member in the polymyxins family produced by Bacillus aerosporus. As a cyclic non-ribosomal lipopeptide, it was purified from Paenibacillus thiaminolyticus for the first time. The producing strain SY20 was screened from Chinese natural fermented bamboo shoots and identified as P. thiaminolyticus SY20 using 16S rRNA homology along with whole genome sequencing. The optimum incubation time was 32 h by the growth kinetics of antimicrobial agent production. The proteinaceous nature of antimicrobial agents was characterized according to the physicochemical properties of the cell-free supernatant. Subsequently, the active antimicrobial agent was purified from the supernatant using ammonium sulfate-graded precipitation, ion-exchange chromatography, and C18-H chromatography. The active agent was identified as polymyxin A1 with a molecular weight 1156.7 Da and antimicrobial activity mainly against Gram-negative bacteria. The molecular structure, a cyclic heptapeptide and a tripeptide side chain acylated by a fatty acid at the amino terminus, was elucidated using the combination of liquid chromatography-tandem mass spectrometry (LCMS/MS), matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS), amino acid analysis, and whole genome mining tool. Meanwhile, the biosynthetic gene cluster of polymyxin A1 including five open reading frames (ORFs) was demonstrated in the genome. The compound should be further explored for its efficacy and toxicity in vivo to develop its application. [ABSTRACT FROM AUTHOR]

Background: Selecting an appropriate and personalized Gn starting dose (GSD) is an essential procedure for determining the quality and quantity of oocytes in the controlled ovarian stimulation (COS) process of the in-vitro fertilization (IVF) treatment cycle. The current approach for determining the GSD is mainly based on the experience of a clinician, lacking unified and scientific standards. This study aims to establish a prediction model of GSD, based on which good COS outcomes can be achieved with the influencing factors comprehensively evaluated quantitatively.Material and Methods: We collected a total of 1555 patients undergoing the first oocytes retrieving cycle and conducted correlation analysis to find the significant factors related to the GSD. Two GSD models are built based on two popular machine learning approaches, and the one with better model performance is selected as the final model. Finally, clinical application and validation were conducted to verify the effectiveness of the proposed model.Results: (1) Age, duration of infertility, type of infertility, body mass index (BMI), antral follicle count (AFC), basal follicle stimulating hormone (bFSH), estradiol (E2), luteinizing hormone (LH), anti-Müllerian hormone (AMH) and COS treatment regimen were closely related to the GSD (P < 0.05). (2) The selected model has good modeling performance in terms of both root mean square error (RMSE) (29.87 ~ 34.21) and regression coefficient R (0.947 ~ 0.953). (3) A comprehensive evaluation of influencing factors for GSD is conducted and shows that the top four most significant factors are age, AMH, AFC, and BMI. (4) The proposed GSD can approximate the actual value well in the clinical application, with the mean absolute error of only 11.26 units, and the recommended results can prompt the number of oocytes retrieved (NOR) close to the optimal number.Conclusion: Modeling the GSD value with machine learning approaches is feasible and effective, and the proposed model has good clinical application for determining the GSD in the IVF treatment cycle. [ABSTRACT FROM AUTHOR]

Objective: This study aims to explore the risk signals of osteonecrosis of the jaw induced by antiresorptive drugs and provide references for the clinical safety application. Method: According to the FDA's Adverse Event Reporting System (FAERS), from January 2004 to September 2021, we chose "Osteonecrosis of the jaw (10064658)" and "Exposed bone in jaw (10071014)" as preferred terms, "antiresorptive drugs" as the target drugs, and primary suspect drug as the drug role code in the dataset. We evaluated the association between drugs and adverse events by using reporting odds ratio (ROR) based on disproportionality analysis. We took the High-Level Terms (HLT) of MedDRA® as the classification level of indications to calculate ROR to compare the signal difference of ONJ in different indications. In addition, patients with antiresorptive-induced osteonecrosis of the jaw and the time of onset of the condition following different antiresorptive medications were collected for the study. Results: The FAERS contained 18,421 reports relating to jaw osteonecrosis from January 2004 to September 2021. A total of eight antiresorptive agents were included in the analysis. From high to low, the ROR of ONJ induced by antiresorptive agents (regardless of indication) is pamidronate (ROR = 494.8), zoledronic acid (ROR = 431.9), denosumab (ROR = 194.8), alendronate (ROR = 151.2), risedronate (ROR = 140.2), etidronic acid (ROR = 64.5), ibandronate (ROR = 40.8), and romosozumab (ROR = 6.4). HLT ROR values for "metabolic bone disorders" were the lowest for each drug, while HLT ROR values were high for "tumor-related indications," including breast and nipple neoplasms malignant, plasma cell myelomas, and prostatic neoplasms malignant. The onset time for osteonecrosis of the jaw as median (Q1, Q3), osteoporosis-related indications, and the onset time for ONJ were 730 (368, 1268), 489.5 (236.3, 909.8), 722.5 (314, 1055), 761 (368, 1720), and 153 (50, 346) for zoledronic acid, denosumab, ibandronate, risedronate, and romosozumab, respectively. Cancer-related indications: the onset time for ONJ were 680.5 (255.3, 1283), 488 (245, 851), and 696.5 (347, 1087) for zoledronic acid, denosumab, and pamidronate, respectively. Conclusion: When antiresorptive drugs are used for metastasis, they have the largest risk signal, followed by malignancy, and the smallest is osteoporosis. The onset time of ONJ may not be related to the indications. The onset time of ONJ for BPs was about 2 years, denosumab about 1.3 years, and romosozumab less than 1 year, which may be related to sequential treatment. When used according to the instructions, the risk of ONJ caused by denosumab was higher than that of zoledronic acid, regardless of the indication. Based on these findings, researchers will continue to monitor and identify risk factors. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is ranked as the second leading cancer-related death in the world. Chemotherapy is one of the most commonly used strategies for HCC patients, while the clinical application is hampered by its cytotoxicity. To address this dilemma, tumor-targeted nanotechnology has been proposed to balance the toxicity and efficacy of chemotherapy. Tumor-targeted selenium nanoparticles (HA-SeNPs) were prepared to load an anticancer drug doxorubicin (DOX). In this drug delivery system, hyaluronic acid (HA) was used as a tumor-targeted moiety to bind with its receptor highly expressed in hepatocellular carcinoma cells. The transmission electron microscopy (TEM) and dynamic light scattering assays showed that HA-Se@DOX was a small and high stable nanocomposite. The cell viability, scratch migration, and invasion chamber assays indicated that HA-Se@DOX showed stronger ability to suppress HepG2 cells growth and migration/invasion compared to Se@DOX or DOX alone. Moreover, HA-Se@DOX could induce HepG2 cells apoptosis probably through the reactive oxygen species (ROS). In summary, the results indicated that HA-Se@DOX exhibits great potential to be a prodrug against hepatocellular carcinoma. [ABSTRACT FROM AUTHOR]

In order to improve the utilization rate of construction waste, C40 concrete is prepared by mixing recycled micro powder and fly ash according to different mass ratios as composite cementitious materials, replacing part of cement. The influence rules and mechanism of composite cementitious material substitution rate, recycled micro powder content and grinding time on the slump, water absorption and compressive strength of C40 concrete are revealed. The results show that the slump increases with the increase of the replacement rate of composite cementitious materials, and decreases with the increase of the amount of recycled micro powder. When the substitution rate is 10% and 20%, the compressive strength decreases with the increase of recycled micro powder content, and the porosity and water absorption reach the lowest when the substitution rate is 20% and the recycled micro powder content is 30%. The milled recycled micro powder will reduce the slump, porosity and water absorption of C40 concrete and improve the compressive strength. In terms of comprehensive performance, the best grinding time is 5h. [ABSTRACT FROM AUTHOR]

Purpose: Critically ill patients with premorbid diabetes can suffer from relative hypoglycemia (RHG), falling below the normal blood glucose (BG) target. However, these events have not been well defined or studied. In the present study, we aimed to explore the incidence and clinical significance of RHG events in critically ill patients with diabetes. Patients and methods: Patients with a history of diabetes who stayed in the intensive care unit (ICU) for more than three days with at least 12 BG recordings were retrospectively included in the study. A BG level > 30% below the estimated average according to patient hemoglobin A1c measured at admission was defined as a single RHG event. Outcomes were compared between patients with and those without RHG events. Results: In total, 113 patients were included in the final analysis. RHG was detected in 73 patients (64.6%). Those who experienced RHG events had a significantly higher incidence of ICU delirium. They also had a higher risk of 28-day mortality, but this was not statistically significant. However, patients with a higher frequency of RHG events did have a significantly higher risk of overall mortality (57.1% for more than four events vs 15.4% for three to four events, P=0.006 and 15.1% for one to two events, P=0.003). Conclusion: In conclusion, RHG is a common finding in critically ill patients with diabetes and is associated with mortality and the occurrence of delirium. [ABSTRACT FROM AUTHOR]

When trains pass through damaged switch rails, rail head damage will change wheel–rail contact states from rolling frictions to unsteady contacts, which will result in impact vibrations and threaten structural safeties. In addition, under approaching and moving away rolling contact excitations and complex wheel–rail contacts, the non-stationary vibrations make it difficult to extract and analyze impact vibrations. In view of the above problems, this paper proposes a variational-mode-decomposition (VMD)-spectral-subtraction (SS)-based impact vibration extraction method. Firstly, the time domain feature analysis method is applied to calculate the time moments that the wheels pass joints, and to correct vehicle velocities. This can help estimate and confine impact vibration distribution ranges. Then, the stationary intrinsic mode function (IMF) components of the impact vibration are decomposed and analyzed with the VMD method. Finally, impact vibrations are further filtered with the SS method. For rail head damage with different dimensions, under different velocity experiments, the frequency and amplitude features of the impact vibrations are analyzed. Experimental results show that, in low-velocity scenarios, the proposed VMD–SS–based method can extract impact vibrations, the frequency features are mainly concentrated in 3500–5000 Hz, and the frequency and peak-to-peak features increase with the increase in excitation velocities. [ABSTRACT FROM AUTHOR]

Renal fibrosis commonly occurs in the process of chronic kidney diseases. Here, we explored the role of Jumonji domain containing 3 (Jmjd3)/interferon regulatory factor 4 (IRF4) axis in activation of myeloid fibroblasts and transition of M2 macrophages into myofibroblasts transition (M2MMT) in kidney fibrosis. In mice, Jmjd3 and IRF4 were highly induced in interstitial cells of kidneys with folic acid or obstructive injury. Jmjd3 deletion in myeloid cells or Jmjd3 inhibitor reduced the levels of IRF4 in injured kidneys. Myeloid Jmjd3 depletion impaired bone marrow-derived fibroblasts activation and M2MMT in folic acid or obstructive nephropathy, resulting in reduction of extracellular matrix (ECM) proteins expression, myofibroblasts formation and renal fibrosis progression. Pharmacological inhibition of Jmjd3 also prevented myeloid fibroblasts activation, M2MMT, and kidney fibrosis development in folic acid nephropathy. Furthermore, IRF4 disruption inhibited myeloid myofibroblasts accumulation, M2MMT, ECM proteins accumulation, and showed milder fibrotic response in obstructed kidneys. Bone marrow transplantation experiment showed that wild-type mice received IRF4-/- bone marrow cells presented less myeloid fibroblasts activation in injured kidneys and exhibited much less kidney fibrosis after unilateral ureteral obstruction. Myeloid Jmjd3 deletion or Jmjd3 inhibitor attenuated expressions of IRF4, α-smooth muscle actin and fibronectin and impeded M2MMT in cultured monocytes exposed to IL-4. Conversely, overexpression IRF4 abrogated the effect of myeloid Jmjd3 deletion on M2MMT. Thus, Jmjd3/IRF4 signaling has a crucial role in myeloid fibroblasts activation, M2 macrophages to myofibroblasts transition, extracellular matrix protein deposition, and kidney fibrosis progression. [ABSTRACT FROM AUTHOR]