Search

Semantic segmentation in aerial imagery is still an important yet challenging task due to the complex characteristics of remote sensing data. The critical issues consist of 1) extreme foreground-background imbalance, 2) large intra-class variance and 3) arbitrary-oriented, dense and small objects. The above challenges make it unlikely to model the effective global interdependencies of semantic heterogeneous regions. Besides, general semantic segmentation methods suffer from feature ambiguity due to the joint feature learning paradigm, leading to inferior detail information. In this paper, we propose an improved semantic segmentation framework to tackle these problems via graph reasoning and disentangled learning. On the one hand, a simple yet effective graph reasoning (GR) unit is introduced to implement coordinate-interaction space mapping and perform relation reasoning over the graph. It can be deployed on the feature pyramid network (FPN) to exploit cross-stage multi-scale information. On the other hand, we propose a so-called disentangled learning paradigm to explicitly model the foreground and boundary objects, instantiated as foreground prior estimation and boundary alignment. The indication of the intermediate feature can be effectively emphasized to enhance the discriminative abilities of the network. Extensive experiments over iSAID, ISPRS Vaihingen and the general Cityscapes data sets demonstrate the effectiveness and efficiency of the proposed framework over other state-of-the-art semantic segmentation methods.

Acute kidney injury (AKI) is common after cardiac surgery and is difficult to predict. N-terminal pro-B-type natriuretic peptide (NT-proBNP) is highly predictive for perioperative cardiovascular complications and may also predict renal injury. We therefore tested the hypothesis that preoperative NT-proBNP concentration is associated with renal injury after major cardiac surgery.We included 35 337 patients who had cardiac surgery and measurements of preoperative NT-proBNP and postoperative creatinine. The primary outcome was Kidney Disease: Improving Global Outcomes Stages 1-3 AKI. We also separately considered severe AKI, including Stage 2, Stage 3, and new-onset dialysis.Postoperative AKI occurred in 11 999 (34.0%) patients. Stage 2 AKI occurred in 1200 (3.4%) patients, Stage 3 AKI in 474 (1.3%) patients, and new-onset dialysis was required in 241 (0.7%) patients. The NT-proBNP concentrations (considered continuously or in quartiles) were significantly correlated with any-stage AKI and severe AKI (all adjusted P0.01). Including NT-proBNP significantly improved AKI prediction (net reclassification improvement: 0.24 [0.22-0.27]; P0.001) beyond basic models derived from other baseline factors in the overall population. Reclassification was especially improved for higher grades of renal injury: 0.30 (0.25-0.36) for Stage 2, 0.46 (0.37-0.55) for Stage 3, and 0.47 (0.35-0.60) for dialysis.Increased preoperative NT-proBNP concentrations were associated with postoperative AKI in patients having cardiac surgery. Including NT-proBNP substantially improves AKI predictions based on other preoperative factors.

Parkinson's disease (PD) is one of the most common degenerative diseases of the human nervous system and has a wide range of serious impacts on human health and quality of life. Recently, research targeting high mobility group box 1 (HMGB1) in PD has emerged, and a variety of laboratory methods for inhibiting HMGB1 have achieved good results to a certain extent. However, given that HMGB1 undergoes a variety of intracellular modifications and three different forms of extracellular redox, the possible roles of these forms in PD are likely to be different. General inhibition of all forms of HMGB1 is obviously not ideal and has become one of the biggest obstacles in the clinical application of targeting HMGB1. In this review, pure mechanistic research of HMGB1 and in vivo research targeting HMGB1 were combined, the effects of HMGB1 on neurons and immune cell responses in PD are discussed in detail, and the problems that need to be focused on in the future are addressed.

Background: The aim of this study was to explore the risk of invasive colorectal cancer (CRC) in relatives of patients with colorectal carcinoma in situ (CCIS), which is lacking in the literature. Patients and Methods: We collected data from Swedish family-cancer datasets and calculated standardized incidence ratio (SIR) and cumulative risk of CRC in family histories of CCIS in first- and second-degree relatives. Family history was defined as a dynamic (time-dependent) variable allowing for changes during the follow-up period from 1958 to 2015. Of 12,829,251 individuals with available genealogical data, 173,796 were diagnosed with CRC and 40,558 with CCIS. Results: The lifetime (0–79 years) cumulative risk of CRC in first-degree relatives of patients with CCIS was 6.5%, which represents a 1.6-fold (95% CI, 1.5–1.7; n=752) increased risk. A similarly increased lifetime cumulative risk (6.7%) was found among first-degree relatives of patients with CRC (SIR, 1.6; 95% CI, 1.6–1.7; n=6,965). An increased risk of CRC was also found in half-siblings of patients with CCIS (SIR, 1.9; 95% CI, 1.1–3.0; n=18) and also in half-siblings of patients with CRC (SIR, 1.7; 95% CI, 1.3–2.1; n=78). Moreover, the increased risk of CRC was higher for younger age at diagnosis of CCIS in the affected first-degree relative and for younger age at diagnosis of CRC in the index person. Conclusions: Results of this study show that first-degree relatives and half-siblings of patients with CCIS have an increased risk of CRC, which is comparable in magnitude to the risk of those with a family history of invasive CRC. These findings extend available evidence on familial risk of CRC and may help to refine guidelines and recommendations for CRC screening.

Purpose: The aim of this study was to explore the diagnostic value of different fluorine-18 (18F)-labeled tracers for lymph node/bone metastasis and biochemical recurrence detection in advanced prostate cancer (PCa). Methods: PubMed, Embase, Web of Science, Cochrane databases, and the WHO International Clinical Trial Center were searched. The inclusion criteria were determined based on the Preferred Report Items of the Systematic Review and Meta-Analysis Guidelines. The Quality Assessment of Diagnostic Accuracy Studies-2 was used to assess the quality assessment of the included studies. The quantitative analysis of the included literature was performed on the patient and lesion basis, and the equivocal findings were considered negative or positive results, respectively. Results: Thirty-seven articles were included. On the patient basis, the pooled sensitivity and specificity of [18F]-labeled tracers were 0.80 (95% confidence interval [CI]: 0.78–0.83) and 0.89 (95% CI: 0.87–0.90) when equivocal results were considered to be positive and 0.80 (95% CI: 0.77–0.82) and 0.87 (95% CI: 0.85–0.89) when equivocal results were considered to be negative. On the lesion basis, the pooled sensitivity and specificity of [18F]-labeled tracers were 0.82 (95% CI: 0.80–0.83) and 0.91 (95% CI: 0.90–0.92) when equivocal lesions were regarded as positive and 0.81 (95% CI: 0.80–0.82) and 0.91 (95% CI: 0.90–0.92) when equivocal lesions were considered to be negative. Conclusion: [18F]-labeled tracers have high diagnostic efficacy for lymph node/bone metastasis and biochemical recurrence in advanced PCa.

Objectives This study was performed to internally derive and then validate risk score systems using preoperative and intraoperative variables to predict the occurrence of any-stage (stage 1, 2, 3) and stage-3 acute kidney injury (AKI) within seven days of cardiac surgery. Design Single-center, retrospective, observational study. Setting Single, large, tertiary care center. Participants Adult patients undergoing open cardiac surgery between January 1, 2012, and January 1, 2019. Measurements and Main Results The clinical data were divided into the following two groups: a derivation cohort (n = 43,799) and a validation cohort (n = 14,600). AKI was defined using the Kidney Disease: Improving Global Outcomes criteria. Multivariate logistic regression analysis was used to develop the prediction models. The overall prevalence of any-stage AKI and stage-3 AKI after cardiac surgery were 34.3% and 1.7%, respectively. The discriminatory ability of the any-stage AKI prediction model measured with the area under the curve (AUC) was acceptable (AUC = 0.69, 95% confidence interval 0.68-0.69), and the calibration measured with the Hosmer-Lemeshow test was good (p = 0.95). The AUC for the stage-3 AKI prediction model was 0.84 (95% confidence interval 0.83-0.85), and the Hosmer-Lemeshow test also indicated a good calibration (p = 0.73). Conclusions This research study, which used preoperative and intraoperative variables, derived and internally validated two predictive scoring systems for any-stage AKI and stage-3 AKI as defined by modified Kidney Disease: Improving Global Outcomes criteria using a very large cohort of Chinese cardiac surgical patients.

Objective To explore the clinical therapeutic effect on premature ovarian failure (POF) treated with the combination of mild moxibustion and western medication. Methods A total of 66 patients were divided into a control group and an observation group according to random number table, 33 cases in each one. In the control group, the conventional western medication was administered. In the observation group, besides the treatment as the control group, mild moxibustion was supplemented at Guānyuan (关元CV4), Qihai (气海CV6), Pishū (脾俞BL20) (bilateral) and Shenshū (肾俞BL23) (bilateral). The duration of treatment was 3 menstrual cycles in either group. Before treatment and on the 9th day of menstruation after 3-menstrual cycle treatment, the number of antral follicles and ovarian volume were detected by color Doppler ultrasound respectively. Before treatment and on day 2 to 4 of menstruation after 3-menstrual cycle treatment, the levels of serum estrogen (E2), follicle-stimulating hormone (FSH), interleukin-21 (IL-21) and vascular endothelial growth factor (VEGF) were determined separately and the therapeutic effect was evaluated in two groups separately. Results The effective rate was 93.94% in the observation group and was 72.73% in the control group (P 0.05). But in the observation group, the levels of serum IL-21 and VEGF after treatment changed apparently as compared with those before treatment (both P Conclusion The combined treatment of mild moxibustion with western medication achieves the definite therapeutic effect on POF and it increases the number of antral follicles and ovarian volume and regulates sex hormone level, which is probably related to the regulation of serum IL-21 and VEGF.

Gecko-inspired controllable dry adhesion has promising applications in various fields such as transfer printing, advanced robotics, and space technology. In this study, we proposed a multi-legged self-adaptive gripper based on gecko-inspired controllable adhesion to manipulate both flat and curved objects. It consists of four symmetric adhesive units, each modulated by two adaptive-locking mechanisms for compression and rotation, respectively, and one peeling mechanism. The two adaptive-locking mechanisms adapt to surfaces with height and curvature differences to ensure intimate contact and then lock the adaption configuration to enable equal load sharing for strong attachment. The peeling mechanism rapidly peels the adhesive surfaces from the substrate for easy detachment. Therefore, this gripper can achieve controllable load sharing to reliably grasp and easily release smooth objects with various surface shapes. Furthermore, the effects of object posture and structural parameters on its grasping performance were analyzed, which can guide its optimal design by improving equal load sharing among adhesive units. This work provides an equal load-sharing strategy for multi-unit adhesive system design and demonstrates its potential for emerging industrial applications.

Background Clinical features of epidermal growth factor receptor (EGFR) mutations have been commonly recognized in variant cancers. The role of EGFR mutations in non-small cell lung cancer (NSCLC) has spurred research and drug development efforts. However, there are still mutations that have not been widely reported, and their influences on NSCLC have not been fully elucidated; EGFR G873R mutation is just one of them. The aim of this study was to investigate the correlation between EGFR G873R mutation and the prognosis of chemotherapy in NSCLC. Methods A total of 54 patients with NSCLC were enrolled in this study. Immunohistochemical staining was used to detect the expression of EGFR. A DNA extraction kit (GeneRead DNA FFPE Kit) was used to extract total DNA from resected cancer tissues. Genomic DNA targets were amplified by polymerase chain reaction (PCR), and then the amplicons were purified and sequenced. Statistical methods were performed to detect the relationship between EGFR G873R mutation and various clinicopathological features and the effect of EGFR G873R mutation on the prognosis of chemotherapy. Results EGFR G873R mutation did not show statistical significance, with EGFR high expression identified in 30 cases (P>0.05). Patients with EGFR G873R mutation had a significantly favorable prognosis of docetaxel (P=0.032), and for patients treated with docetaxel, EGFR G873R mutation was significantly correlated with better 5-year disease-free survival (DFS; P=0.026) and overall survival (OS; P=0.026). However, there was no statistical significance found between EGFR G873R mutation and the prognosis of vinorelbine (P>0.05), and for patients treated with vinorelbine, EGFR G873R mutation had no statistical significance with 5-year DFS (P>0.05) and OS (P>0.05). Conclusions EGFR G873R mutation was remarkably correlated with the prognosis of docetaxel in NSCLC, which indicates that EGFR G873R may be employed as a promising biomarker to identify individuals with better prognosis of docetaxel and as an antitumor target for NSCLC treatment.

Introduction Androgen deprivation therapy (ADT) is a key treatment modality in the management of prostate cancer (PCa), especially for patients with metastatic disease. Increasing evidences suggest that patients who received ADT have increased incidence of diabetes, myocardial infarction, stroke, and even mortality. It is important to understand the pathophysiological mechanisms on how ADT increases cardiovascular risk and induces cardiovascular events, which would provide important information for potential implementation of preventive measures. Methods Twenty-six 12-week-old male SD rats were divided into four groups for different types of ADTs including: the bilateral orchidectomy group (Orx), LHRH agonist group (leuprolide), LHRH antagonist group (degarelix), and control group. After treated with drug or adjuvant injection every 3 weeks for 24 weeks, all rats were sacrificed and total blood were collected. Aorta, renal arteries, and kidney were preserved for functional assay, immunohistochemistry, western blot, and quantitative reverse-transcription polymerase chain reaction. Results In vascular reactivity assays, aorta, intrarenal, and coronary arteries of all three ADT groups showed endothelial dysfunction. AT1R and related molecules at protein and messenger RNA (mRNA) level were tested, and AT1R pathway was shown to be activated and played a role in endothelial dysfunction. Both ACE and AT1R mRNA levels were doubled in the aorta in the leuprolide group while Orx and degarelix groups showed upregulation of AT1R in the kidney tissues. By immunohistochemistry, our result showed higher expression of AT1R in the intrarenal arteries of leuprolide and degarelix groups. The role of reactive oxygen species in endothelial dysfunction was confirmed by DHE fluorescence, nitrotyrosine overexpression, and upregulation of NOX2 in the different ADT treatment groups. Conclusion ADT causes endothelial dysfunction in male rats. GnRH receptor agonist compared to GnRH receptor antagonist, showed more impairment of endothelial function in the aorta and intrarenal arteries. Such change might be associated with upregulation and activation of AngII-AT1R-NOX2 induced oxidative stress in the vasculature. These results help to explain the different cardiovascular risks and outcomes related to different modalities of ADT treatment.

To evaluate in a laboratory setting, the impact of three designs of endodontic access cavities on dentine removal and effectiveness of canal instrumentation in extracted maxillary first molars using micro-computed tomography (micro-CT).A total of 30 extracted intact maxillary first molars were selected and scanned by micro-CT with a voxel size of 24 µm and randomly distributed into three groups: the traditional endodontic cavity (TEC) group, the conservative endodontic cavity (CEC) group and the guided endodontic cavity (GEC) group. The pulp chambers of teeth in the groups were accessed accordingly. After root canal preparation, the teeth were rescanned. The volume of dentine removed after canal preparation, the noninstrumented canal areas, canal transportation and centring ratio were analysed. Data were analysed statistically using one-way analysis of variance. Tukey's post hoc test was used for multiple comparisons. The significance level was set at p .05.The total volume of dentine removed was significantly greater in the TEC group after root canal preparation (p .05). No significant differences in the volume of dentine removed occurred between the CEC and GEC groups (p .05). The volume of dentine removed in the crown, pericervical dentine and coronal third of the canal was significantly lower in CEC and GEC groups when compared to that in the TEC group (p .05), no difference was observed in the middle third of the canal and apical third of the canal amongst the three groups (p .05). There was no significant difference in noninstrumented canal area, canal transportation and centring ratio amongst the TEC, CEC and GEC groups (p .05).In extracted maxillary molars tested in a laboratory setting, CEC and GEC preserved more tooth tissue in the crown, pericervical dentine and coronal third of the canal compared with TEC after root canal preparation. The design of the endodontic access cavity did not impact on the effectiveness of canal instrumentation in terms of noninstrumented canal area, canal transportation and centring ratio.

The recent discovery of immune checkpoint inhibitors is a significant milestone in cancer immunotherapy research. However, some patients with primary or adaptive drug resistance might not benefit from the overall therapeutic potential of immunotherapy in oncology. Thus, it is becoming increasingly critical for oncologists to explore the availability of new immune checkpoint inhibitors. An emerging co-inhibitory receptor, CD112R (also called PVRIG), is most commonly expressed on natural killer (NK) and T cells. It binds to its ligand (CD112 or PVRL2/nectin-2) and inhibits the strength with which T cells and NK cells respond to cancer. Therefore, CD112R is being presented as a new immune checkpoint inhibitor with high potential in cancer immunotherapy. CD112 is easily detectable on antigen-presenting or tumor cells, and its high level of expression has been linked with tumor progression and poor outcomes in most cancer patients. This review explores the molecular and functional relationship between CD112R, TIGIT, CD96, and CD226 in T cell responses. In addition, this review comprehensively discusses the recent developments of CD112R/CD112 immune checkpoints in cancer immunotherapy and prognosis.

In this study, we present a wavelength sensor that is capable of distinguishing the spectrum in the range from ultraviolet (UV) to near-infrared (NIR) light. The filterless device is composed of two horizontally stacking PdSe2/20 μm Si/PdSe2 heterojunction photodetectors with a photovoltaic (PV) behavior, which makes it possible for the device to work at 0 bias voltage. Due to the relatively small thickness of Si and the wavelength-dependent absorption coefficient, the two PdSe2/20 μm Si/PdSe2 photodetectors according to theoretical simulation display a sharp contrast in distribution of the photoabsorption rate. As a result, the photocurrents of both photodetectors evolve in completely different ways with increasing wavelengths, leading to a monotonic decrease in the photocurrent ratio from 6800 to 22 when the wavelength gradually increases from 265 to 1050 nm. The corresponding relationship between both the photocurrent ratio and wavelength can be easily described by the monotonic function, which can help to precisely determine the wavelength in the range from 265 to 1050 nm, with an average relative error less than ±1.6%. It is also revealed that by slightly revising the monotonic function, the wavelength in other different temperatures can also be estimated.

The Cox proportional hazards model is one of the most widely used methods for analyzing survival data. Data from multiple data providers are required to improve the generalizability and confidence of the results of Cox analysis; however, such data sharing may result in leakage of sensitive information, leading to financial fraud, social discrimination or unauthorized data abuse. Some privacy-preserving Cox regression protocols have been proposed in past years, but they lack either security or functionality. In this paper, we propose a privacy-preserving Cox regression protocol for multiple data providers and researchers. The proposed protocol allows researchers to train models on horizontally or vertically partitioned datasets while providing privacy protection for both the sensitive data and the trained models. Our protocol utilizes threshold homomorphic encryption to guarantee security. Experimental results demonstrate that with the proposed protocol, Cox regression model training over 9 variables in a dataset of 113,035 samples takes approximately 44 min, and the trained model is almost the same as that obtained with the original nonsecure Cox regression protocol; therefore, our protocol is a potential candidate for practical real-world applications in multicenter medical research.

Bio-inspired reversible adhesion has significant potential in many fields requiring flexible grasping and manipulation, such as precision manufacturing, flexible electronics, and intelligent robotics. Despite extensive efforts for adhesive synthesis with a high adhesion strength at the interface, an effective strategy to actively tune the adhesion capacity between a strong attachment and an easy detachment spanning a wide range of scales has been lagged. Herein, we report a novel soft-hard-soft sandwiched composite design to achieve a stable, repeatable, and reversible strong adhesion with an easily scalable performance for a large area ranging from ∼1.5 to 150 cm2 and a high load ranging from ∼20 to 700 N. Theoretical studies indicate that this design can enhance the uniform loading for attachment by restraining the lateral shrinkage in the natural state, while facilitate a flexible peeling for detachment by causing stress concentration in the bending state, yielding an adhesion switching ratio of ∼54 and a switching time of less than ∼0.2 s. This design is further integrated into versatile grippers, climbing robots, and human climbing grippers, demonstrating its robust scalability for a reversible strong adhesion. This biomimetic design bridges microscopic interfacial interactions with macroscopic controllable applications, providing a universal and feasible paradigm for adhesion design and control.

Acute abdomen in obstetrics and gynecology is a common disease in clinical emergency, most of the patients have the characteristics of complex condition and rapid progress, and need to be treated through clinical diagnosis. There are many traditional diagnosis methods, but the accuracy is not ideal. Ultrasound is a widely used imaging technique in recent years, which has the characteristics of simple operation and high accuracy, so it is favored by doctors and patients in obstetrics and gynecology. In this study, 200 patients with acute abdomen in obstetrics and gynecology were selected, and the results of pathological examination were taken as the gold standard to evaluate the clinical value of ultrasound examination. As a result, the misdiagnosed ultrasound group was significantly lower after the diagnosis than in the normal group, the difference was significant (P < 0.05). Therefore, the use of ultrasound imaging, the clinical diagnosis of acute abdominal diseases in gynecology and obstetrics achieves a clear diagnostic effect, improves the diagnostic accuracy of patients with acute abdominal disease in the clinical. It is very important for the development of targeted therapeutic programmes.

Survival analysis is a commonly used method in the medical field to analyze and predict the time of events. In medicine, this approach plays a key role in determining the course of treatment, developing new drugs, and improving hospital procedures. Most of the existing work in this area has addressed the problem by making strong assumptions about the underlying stochastic process. However, these assumptions are usually violated in the real-world data. This paper proposed a semisupervised multitask learning (SSMTL) method based on deep learning for survival analysis with or without competing risks. SSMTL transforms the survival analysis problem into a multitask learning problem that includes semisupervised learning and multipoint survival probability prediction. The distribution of survival times and the relationship between covariates and outcomes were modeled directly without any assumptions. Semisupervised loss and ranking loss are used to deal with censored data and the prior knowledge of the nonincreasing trend of the survival probability. Additionally, the importance of prognostic factors is determined, and the time-dependent and nonlinear effects of these factors on survival outcomes are visualized. The prediction performance of SSMTL is better than that of previous models in settings with or without competing risks, and the effects of predictors are successfully described. This study is of great significance for the exploration and application of deep learning methods involving medical structured data and provides an effective deep-learning-based method for survival analysis with complex-structured clinical data.

Coronavirus disease 2019 (COVID-19), resulting from infection by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), can cause severe and fatal pneumonia along with other life-threatening complications. The COVID-19 pandemic has taken a heavy toll on the healthcare system globally and has hit the economy hard in all affected countries. As a result, there is an unmet medical need for both the prevention and treatment of COVID-19 infection. Several herbal remedies have claimed to show promising clinical results, but the mechanisms of action are not clear. We set out to identify the anti-viral natural products of these herbal remedies that presumably inhibit the life cycle of SARS-CoV-2. Particularly we chose four key SARS-CoV-2 viral enzymes as targets: Papain-like protease, Main protease, RNA dependent RNA polymerase, and 2’-O-ribose methyltransferase, which were subjected to an unbiased in silico screening against a small molecule library of 33,765 compounds originating from herbs and medicinal plants. The small molecules were then ranked based on their free energy of fitting into the “druggable” pockets on the surface of each target protein. We have analyzed the best “fit” molecules and annotated them according to their plant sources and pharmacokinetic properties. Here we present a list of potential anti-viral ingredients of herbal remedies targeting SARS-CoV-2 and explore the potential mechanisms of action of these compounds as a framework for further development of chemoprophylaxis agents against COVID-19. Graphic abstract Supplementary Information The online version contains supplementary material available at 10.1007/s12539-021-00461-4.

Metabolic dysfunction-associated fatty liver disease (MAFLD) is highly prevalent worldwide. Recent clinical and experimental studies have addressed the association between cholecystectomy and MAFLD, confirming that cholecystectomy is an independent risk factor for MAFLD. In this review, we describe the epidemiologic evidence that links cholecystectomy to MAFLD, and discuss the possible mechanisms behind these connections, in order to unveil the metabolic and chronobiologic signals conveyed by the waves of the bile acid enterohepatic circulation.

Pharmacomechanical thrombolysis (PMT) and catheter-directed thrombolysis (CDT) are frequently employed for treating deep venous thrombosis (DVT). However, there have been relatively few studies comparing PMT outcomes to those associated with CDT. The present study was thus designed to compare short- and mid-term PMT and CDT patient outcomes following the treatment of DVT of the lower extremities.This study was a retrospective analysis of 98 patients treated at the 3rd Affiliated Hospital of Shenzhen University (Shenzhen, China) and Beijing Chao Yang Hospital (Beijing, China). All patients had undergone treatment for symptomatic DVT of the lower legs via either CDT or PMT. Clinical records and outcome data between the patients in these 2 treatment groups were compared.Of the 98 patients analyzed in this retrospective study, 50 had been treated via CDT while 48 had undergone PMT. These PMT and CDT operations were associated with mean treatment durations of 0.97 ± 0.20 hr and 32.48 ± 7.46 hr, respectively (P0.0001). Complete lysis was achieved in 78 patients (42 and 36 in the PMT and CDT groups, respectively P = 0.057), while effective lysis was achieved in 96 patients (48 and 48 in the PMT and CDT groups, respectively P = 0.162), with lysis being ineffective in the 2 remaining patients. PMT was associated with a significantly decreased length of hospital stay, usage of UK dose, and treatment duration relative to CDT(P0.0001). No major complications or MACE incidence were noted in either group, although 18 patients in the PMT group suffered from bradyarrhythmia (P = 0.007). Clinical efficacy was achieved in 96 patients (48 in each treatment group) at time of discharge (P = 0.162). A Kaplan-Meier analysis revealed that 2-year primary patency rates did not differ significantly between these 2 groups (P = 0.442).PMT is an effective treatment modality in patients with symptomatic DVT. Relative to CDT it is associated with high treatment success rates, reduced treatment duration, and reduced hospitalization duration, although it is also associated with higher rates of systemic complications.

Tumor recurrence after surgery is the main cause of treatment failure. However, the initial stage of recurrence is not easy to detect, and it is difficult to cure in the late stage. In order to improve the life quality of postoperative patients, an efficient synergistic immunotherapy was developed to achieve early diagnosis and treatment of post-surgical tumor recurrence, simultaneously. In this paper, two kinds of theranostic agents based on gold nanorods (AuNRs) platform were prepared. AuNRs and quantum dots (QDs) in one agent was used for the detection of carcinoembryonic antigen (CEA), using fluorescence resonance energy transfer (FRET) technology to indicate the occurrence of in situ recurrence, while AuNRs in the other agent was used for photothermal therapy (PTT), together with anti-PDL1 mediated immunotherapy to alleviate the process of tumor metastasis. A series of assays indicated that this synergistic immunotherapy could induce tumor cell death and the increased generation of CD3+/CD4+ T-lymphocytes and CD3+/CD8+ T-lymphocytes. Besides, more immune factors (IL-2, IL-6, and IFN-γ) produced by synergistic immunotherapy were secreted than mono-immunotherapy. This cooperative immunotherapy strategy could be utilized for diagnosis and treatment of postoperative tumor recurrence at the same time, providing a new perspective for basic and clinical research., Graphical abstract This efficient synergistic immunotherapy was developed to achieve early diagnosis and treatment of post-surgical tumor recurrence, simultaneously.Image 1

Continuum hyper-redundant manipulators (CHRMs) have been widely applied in aerospace, medical or other fields to complete tasks in narrow and multi-obstacles environments with its unique structural advantages. Due to the redundancy, the inverse kinematics of CHRMs is rather complex and the trajectory planning has always been the focal and challenging point in the research of CHRMs. To tackle this issue, the present study proposes an overall configuration planning method of CHRMs based on the improved artificial potential field (APF) method. The method avoids the complicated inverse kinematics and vastly reduces the computational complexity. First, a virtual guiding pipeline (VGP) with no obstacles inside is constructed based on a known target configuration and the minimum safe distance. The movement of the CHRM is restricted to the pipe by the APF method. Then, we propose a method to construct a guided potential field in the VGP to solve the local minimum problem of the traditional artificial potential field method. Further, to address the issue of contradictory forces in the overall configuration planning, the maximum-work planning strategy is proposed. Finally, simulations are conducted and the results demonstrate the high performance of the method in terms of planning efficiency, environmental adaptability.

BACKGROUND Transcatheter aortic valve replacement (TAVR) has been increasingly used in all levels of risk patients, which is less invasive and has fewer complications. However, the benefits of transcatheter and surgical methods of aortic valve replacement remain controversial for aortic stenosis (AS) patients with advanced chronic kidney disease (stage 3-5). METHODS We comprehensively searched PubMed, Embase, the Cochrane Library, and the International Clinical Trials Registry Platform (ICTRP) from January 2000 to October 2020 and performed a systematic review to evaluate the two techniques. Two investigators independently conducted the literature searches, study eligibility assessment, and data extraction in duplicate. RESULTS Compared to surgical aortic valve replacement (SAVR), TAVR had lower risk of in-hospital mortality [odds ratio (OR): 0.53; 95% confidence interval (CI): 0.36-0.78; P=0.001], lower stroke rate (OR: 0.68; 95% CI: 0.47-0.96; P=0.03), lower risk of acute kidney injury (AKI) (OR: 0.42; 95% CI: 0.34-0.52; P

Non-used clinical information has negative implications on healthcare quality. Clinicians pay priority attention to clinical information relevant to their specialties during routine clinical practices but may be insensitive or less concerned about information showing disease risks beyond their specialties, resulting in delayed and missed diagnoses or improper management. In this study, we introduced an electronic health record (EHR)-oriented knowledge graph system to efficiently utilize non-used information buried in EHRs. EHR data were transformed into a semantic patient-centralized information model under the ontology structure of a knowledge graph. The knowledge graph then creates an EHR data trajectory and performs reasoning through semantic rules to identify important clinical findings within EHR data. A graphical reasoning pathway illustrates the reasoning footage and explains the clinical significance for clinicians to better understand the neglected information. An application study was performed to evaluate unconsidered chronic kidney disease (CKD) reminding for non-nephrology clinicians to identify important neglected information. The study covered 71,679 patients in non-nephrology departments. The system identified 2,774 patients meeting CKD diagnosis criteria and 10,377 patients requiring high attention. A follow-up study of 5,439 patients showed that 82.1% of patients who met the diagnosis criteria and 61.4% of patients requiring high attention were confirmed to be CKD positive during follow-up research. The application demonstrated that the proposed approach is feasible and effective in clinical information utilization. Additionally, it's valuable as an explainable artificial intelligence to provide interpretable recommendations for specialist physicians to understand the importance of non-used data and make comprehensive decisions.

Multimodal Named Entity Recognition task aims to identify named entities in user-generated posts containing both images and texts. Previous multimodal named entity recognition methods greatly benefit from visual features when the text and the image are well aligned, but this is not always the case in social media. On condition that the image is missing or mismatched with the text, these models usually fail to provide excellent performance. Besides, previous models use only single attention to capture the semantic interaction between different modalities, which largely ignore the existence of multiple entity objects in images and texts of the posts. To alleviate these issues, we present a novel model named Hierarchical Self-adaptation Network (HSN) to address these issues. The HSN contains 1) a Cross-modal Interaction Module to promote semantic interaction for the multiple entity objects in different modalities, which is proved to suppress wrong or incomplete attention in multimodal interactivity; 2) a Self-adaptive Multimodal Integration module to handle the problems that the images are missing or mismatched with the texts. Additionally, to evaluate the adaptability of HSN in real-life social media, we construct a Real-world NER dataset consisting of plain text posts and multimodal posts from Twitter. Extensive experiments demonstrate that our model achieves state-of-the-art results on the Real-world multimodal NER dataset and the Twitter multimodal NER dataset.

The establishment of the precision diagnosis and treatment system and the advent of the digital intelligence era have not only deepened people's understanding of liver cancer but also continuously improved the diagnosis and treatment methods of liver cancer. Cutting-edge computer technology represented by artificial intelligence (AI) has been used in the prediction, screening, diagnosis, treatment, and rehabilitation of liver cancer. The rise of AI has given new vitality to liver surgery, as well as individualized treatment experience and greater healing opportunities for patients. We focus on summarizing the latest applications and developments of AI in liver cancer diagnosis and treatment from six aspects: virtual assistants, medical imaging diagnosis, adjuvant therapy, risk and treatment response prediction, drug development and testing, and postoperative rehabilitation management. Especially in the two major aspects of medical imaging diagnosis and adjuvant therapy, the development and achievements of AI are gratifying. Finally, we put forward a view on the current challenges of AI in the precise diagnosis and treatment of liver cancer and how to promote its development, and we have a prospect for the future development direction.

The presence of the blood-brain barrier (BBB) remains a challenge in the treatment of central nervous system (CNS) diseases, as it hinders the infiltration of many therapeutic drugs into the brain parenchyma. Therefore, developing efficacious pharmacological agents that can traverse the BBB is crucial for optimal treatment of diseases of the CNS such as neurodegenerative conditions and brain tumors. Adeno-associated virus (AAV), one of the most promising gene therapy vectors, has been shown to cross the BBB safely and is non-pathogenic in nature and therefore has been utilized for numerous diseases of the CNS. Along with the development of protein engineering techniques such as directed evolution including DNA shuffling, a great number of BBB-crossing AAVs have been developed, that could be systemically injected for therapeutic benefit. In this review, we discuss several feasible approaches to improve transportation of therapeutic agents to the CNS. We also discuss the advantages of using BBB-crossing AAVs, their role as a gene delivery agent and highlight the different types of BBB-AAV vectors that have been developed in order to provide a greater insight into how they can be used in diseases of the CNS.

This paper presents a new full-reference image quality assessment (IQA) method for conducting the perceptual quality evaluation of the light field (LF) images, called the symmetry and depth feature-based model (SDFM). Specifically, the radial symmetry transform is first employed on the luminance components of the reference and distorted LF images to extract their symmetry features for capturing the spatial quality of each view of an LF image. Second, the depth feature extraction scheme is designed to explore the geometry information inherited in an LF image for modeling its LF structural consistency across views. The similarity measurements are subsequently conducted on the comparison of their symmetry and depth features separately, which are further combined to achieve the quality score for the distorted LF image. Note that the proposed SDFM that explores the symmetry and depth features is conformable to the human vision system, which identifies the objects by sensing their structures and geometries. Extensive simulation results on the dense light fields dataset have clearly shown that the proposed SDFM outperforms multiple classical and recently developed IQA algorithms on quality evaluation of the LF images.

The investigation of the dielectric properties of bastnasite concentrate has critical directing centrality for the microwave roasting process of bastnasite concentrate. The dielectric properties are correlated with information such as thermogravimetry-differential scanning calorimetry and temperature rise curves. This combination permits a targeted study of the mechanism of the microwave roasting process, providing new evidence about the unique conditions of this microwave roasting process. This work also explores the response surface methodology based on a central composite design to optimize the microwave non-oxidative roasting process. Single-factor tests were conducted to determine the suitable range of factors such as the content of activated carbon, holding time, and roasting temperature. The interactions between parameters were investigated through the analysis of variance method. It was indicated that the models are available to navigate the design space. Also, the optimal roasting temperature, content of activated carbon, and holding time were 1100 °C, 20%, and 21.5 min, respectively. Under these conditions, the decomposition rate of bastnasite concentrate (hereinafter to be referred as DRBC) and the oxidation rate of cerium (hereinafter to be referred as ORC) was 99.8% and less than 0.3%, respectively. The new non-oxidizing roasting method significantly shortens the roasting time, reduces the energy consumption, and has great significance for industrial applications.

Intermolecular interaction is the material basis for cells to achieve their functions, and protein-protein interaction is an important approach to illuminate the regulation network of biological molecules and has important theoretical significance and potential application value for revealing the activity law of life in nature. This paper mainly summarizes and analyzes the new advances and applications of modern biotechnologies in the study of protein-protein interactions, including local surface plasmon resonance (LSPR), yeast two-hybrid, GST-Pull-down, bimolecular fluorescence complementation, and co­immunoprecipitation. At the same time, the principles of different research methods for protein-protein interaction and their other applications in the field of life sciences are also discussed, all of these will provide a reference value for the analysis of protein-protein interaction and the molecular regulation mechanism of biomacromolecules.

Background In a minority of cases, foramen ovales (FOs) are difficult to access due to single confounding anatomical variations. However, there is no method reported where the FO has been successfully targeted via a single puncture in the presence of two or more anatomical variations. Objectives To observe the effect of a new stereotactic bidirectional approach guiding technique utilized in a patient who harbored a particularly difficult-to-access FO due to multiple anatomical variations. Methods During operation of a unique facial entry point's trigeminal neuralgia patient, make one plane which identified by a three-dimensional (3D) coordinates of the FO target and arc angle value on stereotactic frame, make this plane intersected with another plane which determined by the 3D CT-reconstruction's facial entry point data on a ruler, so as to elucidate the appropriate trajectory. The authors coined the approach "Air-to-air meeting" method. Results We completed the radiofrequency thermocoagulation (RFT) with a single puncture to successfully target the FO according to the preoperative plan confirmed by C-arm radiography. Postoperative pain scores using a visual analog scale decreased from 10 to 3 by the first day after the procedure. There were no permanent complications or morbidity from the surgery. Conclusions To the authors' knowledge, this is the first report describing a unique facial entry point determined by this technique for the treatment of a patient with trigeminal neuralgia.

Foodborne pathogens are the main cause of human foodborne diseases and pose a serious threat to food safety. The control of them has always been a significant issue in food industry. With good biocompatibility and stability, nanomaterials display excellent bactericidal properties against many kinds of bacteria. In this review, the generation and application of nanostructures as antibacterial in the control of foodborne pathogens was summarized. The antibacterial effects of photocatalytic and contact bacteriostatic nanomaterials agents were mainly introduced. The influence factors and mechanisms of nanomaterials on the inactivation of foodborne pathogens were displayed. The photocatalytic nanostructured bacteriostatic agents can produce reactive oxygen species (ROS) and lead to charge transfer, which result in damaging of cell wall and leakage of small molecules under light irradiation. In addition, metals and metal oxide nanoparticles can kill bacterial cells by releasing metal ions, forming ROS and electrostatic interaction with cell membrane. Besides, the synergistic action of nanoparticles with natural antibacterial agents can improve the stability of these agents and their bactericidal performance. These current researches provided a broader idea for the control of microorganisms in food.

Since regenerating islet-derived 3β (Reg3β) was first reported, various studies have been conducted to explore the involvement of Reg3β in a gamut of maladies, such as diabetes, pancreatitis, pancreatic ductal adenocarcinoma, and extrapancreatic maladies such as inflammatory bowel disease, acute liver failure, and myocardial infarction. Surprisingly, there is currently no systematic review of Reg3β. Therefore, we summarize the structural characteristics, transcriptional regulation, putative receptors, and signaling pathways of Reg3β. The exact functional roles in various diseases, especially gastrointestinal and liver diseases, are also discussed. Reg3β plays multiple roles in promoting proliferation, inducing differentiation, preventing apoptosis, and resisting bacteria. The present review may provide new directions for the diagnosis and treatment of gastrointestinal, liver, and pancreatic diseases.

The automated interpretation of rock structure can improve the efficiency, accuracy, and consistency of the geological risk assessment of tunnel face. Because of the high uncertainties in the geological images as a result of different regional rock types, as well as in-situ conditions (e.g., temperature, humidity, and construction procedure), previous automated methods have limited performance in classification of rock structure of tunnel face during construction. This paper presents a framework for classifying multiple rock structures based on the geological images of tunnel face using convolutional neural networks (CNN), namely Inception-ResNet-V2 (IRV2). A prototype recognition system is implemented to classify 5 types of rock structures including mosaic, granular, layered, block, and fragmentation structures. The proposed IRV2 network is trained by over 35,000 out of 42,400 images extracted from over 150 sections of tunnel faces and tested by the remaining 7400 images. Furthermore, different hyperparameters of the CNN model are introduced to optimize the most efficient algorithm parameter. Among all the discussed models, i.e., ResNet-50, ResNet-101, and Inception-v4, Inception-ResNet-V2 exhibits the best performance in terms of various indicators, such as precision, recall, F-score, and testing time per image. Meanwhile, the model trained by a large database can obtain the object features more comprehensively, leading to higher accuracy. Compared with the original image classification method, the sub-image method is closer to the reality considering both the accuracy and the perspective of error divergence. The experimental results reveal that the proposed method is optimal and efficient for automated classification of rock structure using the geological images of the tunnel face.

A wavelength sensor as a representative optoelectronic device plays an important role in many fields including visible light communication, medical diagnosis, and image recognition. In this study, a wavelength-sensitive detector with a new operation mechanism was reported. The as-proposed wavelength sensor which is composed of two parallel PtSe2/thin Si Schottky junction photodetectors is capable of distinguishing wavelength in the range from ultraviolet to near infrared (UV-NIR) light (265 to 1050 nm), in that the relationship between the photocurrent ratio of both photodetectors and incident wavelength can be numerically described by a monotonic function. The unique operation mechanism of the thin Si based wavelength sensor was unveiled by theoretical simulation based on Synopsys Sentaurus Technology Computer Aided Design (TCAD). Remarkably, the wavelength sensor has an average absolute error of ±4.05 nm and an average relative error less than ±0.56%, which are much better than previously reported devices. What is more, extensive analysis was performed to reveal how and to what extent the working temperature and incident light intensity, and the thickness of the PtSe2 layer will influence the performance of the wavelength sensor.

The effectiveness of inactivated SARS-CoV-2 vaccines against the Delta variant, which has been associated with greater transmissibility and virulence, remains unclear. We conducted a test-negative case–control study to explore the vaccine effectiveness (VE) in real-world settings. We recruited participants aged 18–59 years who consisted of SARS-CoV-2 test-positive cases (n = 74) and test-negative controls (n = 292) during the outbreak of the Delta variant in May 2021 in Guangzhou city, China. Vaccination status was compared to estimate The VE of SARS-CoV-2 inactivated vaccines. A single dose of inactivated SARS-CoV-2 vaccine yielded the VE of only 13.8%. After adjusting for age and sex, the overall VE for two-dose vaccination was 59.0% (95% confidence interval: 16.0% to 81.6%) against coronavirus disease 2019 (COVID-19) and 70.2% (95% confidence interval: 29.6–89.3%) against moderate COVID-19 and 100% against severe COVID-19 which might be overestimated due to the small sample size. The VE of two-dose vaccination against COVID-19 reached 72.5% among participants aged 40–59 years, and was higher in females than in males against COVID-19 and moderate diseases. While single dose vaccination was not sufficiently protective, the two-dose dosing scheme of the inactivated vaccines was effective against the Delta variant infection in real-world settings, with the estimated efficacy exceeding the World Health Organization minimal threshold of 50%.

Deep learning (DL) has seen great success in the computer vision (CV) field, and related techniques have been used in security, healthcare, remote sensing, and many other fields. As a parallel development, visual data has become universal in daily life, easily generated by ubiquitous low-cost cameras. Therefore, exploring DL-based CV may yield useful information about objects, such as their number, locations, distribution, motion, etc. Intuitively, DL-based CV can also facilitate and improve the designs of wireless communications, especially in dynamic network scenarios. However, so far, such work is rare in the literature. The primary purpose of this article, then, is to introduce ideas about applying DL-based CV in wireless communications to bring some novel degrees of freedom to both theoretical research and engineering applications. To illustrate how DL-based CV can be applied in wireless communications, an example of using a DL-based CV with a millimeter-wave (mmWave) system is given to realize optimal mmWave multiple-input and multiple-output (MIMO) beamforming in mobile scenarios. In this example, we propose a framework to predict future beam indices from previously observed beam indices and images of street views using ResNet, 3-dimensional ResNext, and a long short-term memory network. The experimental results show that our frameworks achieve much higher accuracy than the baseline method, and that visual data can significantly improve the performance of the MIMO beamforming system. Finally, we discuss the opportunities and challenges of applying DL-based CV in wireless communications.

Organic-inorganic hybrid lead halide perovskites are potential candidates for next-generation light-emitting diodes (LEDs) in terms of tunable emission wavelengths, high electroluminescence efficiency, and excellent color purity. However, the device performance is still limited by severe non-radiative recombination losses and operational instability due to a high degree of defect states on the perovskite surface. Here, an effective surface engineering method is developed via the assistance of guanidinium iodide (GAI), which allows the formation of surface-2D heterophased perovskite nanograins and surface defect passivation due to the bonding with undercoordinated halide ions. Efficient and stable red-emission LEDs are realized with the improved optoelectronic properties of GAI-modified perovskite nanograins by suppressing the trap-mediated non-radiative recombination loss. The champion device with a high color purity at 692 nm achieves an external quantum efficiency of 17.1%, which is 2.3 times that of the control device. Furthermore, the operational stability is highly improved, showing a half-lifetime of 563 min at an initial luminance of 1000 cd m-2. The proposed GAI-assisted surface engineering is a promising approach for defect passivation and phase engineering in perovskite films to achieve high-performance perovskite LEDs.

Background The recent novel conception of neoadjuvant immunotherapy has generated interest among surgeons worldwide, especially the lack of experience involving surgical treatment for the neoadjuvant immunotherapy population. Methods Patients with non-small cell lung cancer (NSCLC), who underwent neoadjuvant immunotherapy or chemo-immunotherapy, were retrospectively collected between September 2018 and April 2020. Demographic data, pathological and clinical features, therapeutic regimens and outcome data of all individuals were collected by retrospective chart review. Operative details, information of neoadjuvant therapy, were also abstracted. Results In total, 31 patients were included in the final analysis. The patients’ median age was 61 years. In total, 29 of the patients were males, while 2 were females. Patients received a median of 3 doses before resection. The median duration from final treatment to surgery was 34 days. After neoadjuvant treatment, post-treatment computed tomography scan showed that 24 patients had partial response. In total, 12 of 31 patients had a major pathological response, 15 pathological downstaging. Three patients had no residual viable tumor. A positive surgical margin was identified in 7 cases. One or more postoperative complications occurred in 18 of all 31 patients. In total, 26 patients underwent next-generation sequencing before surgery in total. Among them, 2 patients were detected STK11 mutations, none of whom had a major pathological response by final pathological examination. Conclusions Pulmonary resection after neoadjuvant immunotherapy or chemo-immunotherapy for resectable NSCLC appears to be safe with low operative mortality and morbidity rate in the current population.

Purpose Ulcerative colitis (UC) patients have an increased risk of colorectal cancer (CRC), and compared with sporadic CRC, ulcerative colitis-associated colorectal cancer (CAC) is more aggressive with a worse prognosis. This study aimed to identify a gene signature to predict the risk of CAC for patients with UC in remission. Patients and Methods Series of quiescent UC-related transcriptome data obtained from the Gene Expression Omnibus (GEO) data set were divided into a training set and a validation set. Gene Set Variation Analysis (GSVA), Gene Set Enrichment Analysis (GSEA), and \Weighted Correlation Network Analysis (WGCNA) combined with protein-protein interaction (PPI) analysis were used to identify the pathways and gene signatures related to tumorigenesis among quiescent UC patients. A generalized linear model (GLM) of Poisson regression based on the training set was applied to estimate the diagnostic power of the gene signature in our validation set. Results The tumor necrosis factor (TNF) signaling via NF-κB pathway was significantly augmented with the highest normalized enrichment score (NES). The genes in the brown module from WGCNA have shown a significant correlation with CAC (Pearson coefficient = 0.83, p = 6e-06). A subset of NF-κB related genes (FOS, CCL4, CXCL1, MYC, CEBPB, ATF3, and JUNB) were identified with a relatively higher expression level in CAC samples. The diagnostic value of this 7-gene biomarker was estimated by the receiver operating characteristic (ROC) curve with an area under the ROC curve (AUC) at 0.82 (p

As an efficient supplement for terrestrial communications, e.g., fifth-generation communication networks, satellite communication has been proved as a promising choice to realize seamless coverage, due to its inherent superiority over common wireless communication systems, like large-scale coverage area and flexibility of deployment. In this article, a satellite-terrestrial transmission (STT) system including a satellite transmitter (S) and a group of terrestrial receivers (D) is focused on. Considering the randomness of D and employing stochastic geometry, the outage performance and diversity gain of three hybrid automatic repeat request (HARQ) schemes, generalized slotted ALOHA (GSA), repetition time diversity (RTD) and general incremental redundancy (IR), are respectively studied. In detail, the exact closed-form analytical expression for the outage probability (OP) is derived for the GSA scheme, while the approximated expression for the OP of RTD scheme is presented and a useful expression for the OP of IR scheme is derived. Furthermore, the diversity gains of the three considered HARQ schemes are respectively investigated in STT scenarios. Finally, some numerical results are provided to validate the proposed analysis models.

Rice is one of the most important food crops in the world, and about half of the world’s population uses it as the main food source. China’s annual rice output accounts for about 34% of the world’s annual rice output, ranking first in the world, thus China is known as the "Rice Kingdom". Rice has high nutritional value, providing the human body with 35% of the total energy intake and about 28% of the required protein. Therefore, the nutritional value of rice is directly related to human nutrition and health. In this paper, the three aspects of rice nutrition and human health, factors affecting rice nutritional quality and genetic improvement of nutritional quality of rice are reviewed. The new challenges of rice nutrition quality were analyzed, and the prospect of improving rice nutritional quality was prospected. The results provide theoretical basis for genetic improvement of rice nutrition quality and cultivation of new high-quality rice varieties in the future.

Indoor airborne fungi have been associated with adverse human health effects. Therefore, it is important to understand the causes of underlying variation in airborne fungi in indoor environments. This study consequently aimed to investigate the association between indoor fungi with temporal variation, environmental parameters, and potential confounders over 10 months in four library rooms using Andersen samplers. Indoor fungal concentrations peaked in October and were lowest in March in both stack rooms, whereas the highest concentrations in both reading rooms were observed in September with lowest concentrations in July. Nonparametric analyses revealed higher fungal concentrations in the rooms that were significantly associated with relative humidity ≥ 60%, PM2.5 ≥ 35 μg/m3, number of people ≥ 16, open windows, working air conditioners, and room area

Zhibai Dihuang pill (ZBDH), a Chinese herbal formula, has been widely used as an adjunctive therapy to help reduce the patient's steroid dose and maintain low disease activity in systemic lupus erythematosus (SLE).This systematic review evaluates the therapeutic effect of modified ZBDH in reducing steroid use in patients with SLE.A systematic literature search was carried out using seven databases, including PubMed, Embase, Cochrane Central Register of Controlled Trials, Chinese Biomedical Literature Database, Chinese National Knowledge Infrastructure, Chinese VIP Information and Wanfang Database, from their inception to June 1st, 2019. The search terms included "systemic lupus erythematosus," "Chinese medicine" and "clinical trial," and their synonyms. Subject headings matching the above terms were also used.This meta-analysis included randomized controlled trials that evaluated the reduction of steroid dose in patients with SLE. Traditional Chinese medicine (TCM) formulas in experimental group should be prescribed based on ZBDH and used as adjunctive therapy and the comparator should contain steroids.Two authors independently conducted database search, study selection, data extraction and quality assessment. The extracted information contained study design, sample size, recruitment mode, diagnostic criteria, inclusion and exclusion criteria, participant characteristics, TCM patterns, TCM formulas and treatment outcomes. The primary outcome was the change of steroid dose. Secondary outcomes included SLE Disease Activity Index (SLEDAI), biomarkers of disease activity and clinical response rate. STATA 15.0 was used to analyze the pooled effects reported as weighted mean difference (WMD) or odds ratio, with a 95% confidence interval (CI).In total, 20 trials involving 1470 SLE patients were included. The pooled result showed that modified ZBDH taken in combination with standard care led to a larger reduction in steroid dose, compared to standard care alone (WMD: 3.79; 95% CI: 2.58-5.01; P 0.001). Favorable outcomes were also seen in secondary outcome criteria, such as SLEDAI and complement 3. The modified ZBDH treatments were well tolerated without increasing adverse effects.The systematic review provided preliminary evidence supporting the use of ZBDH as a co-therapy to aid steroid dose reduction in patients with SLE. However, more rigorous studies should be conducted to validate these findings, and explore the mechanisms of ZBDH's relevant bioactive constituents.

Acute intermittent porphyria (AIP) is a dominant inherited disorder with a low penetrance that is caused by mutations in the gene coding for hydroxymethylbilane synthase (HMBS). Information about the epidemiology and molecular genetic features of this rare disorder is crucial to clinical research, and particularly to the evaluation of new treatments. Variations in the prevalence and penetrance of AIP in various studies may due to the different inclusion criteria and methods of assessment. Here, the prevalence and penetrance of AIP are analyzed systematically, and the genetic traits of different populations and findings regarding the genotype-phenotype correlation are summarized. In addition, quite a few studies have indicated that AIP susceptibility was affected by other factors, such as modifying genes. Findings regarding possible modifying genes are documented here, helping to reveal the pathogenesis of and treatments for AIP. The status of research on AIP in China reveals the lack of epidemiological and genetic studies of the Chinese population, a situation that needs to be promptly remedied.

Purpose Sitting time (ST) is a serious global health issue and positively associated with cardiometabolic disease. The present study investigated associations between objectively measured ST, sedentary patterns, and cardiometabolic biomarkers in physically active young males. Methods Cross-sectional analysis was completed in 94 males 18–35 yr of age. Total ST, prolonged sedentary bouts (≥30 min with no interruption), and sedentary breaks (transitions from sitting/lying to standing/stepping) were assessed using activPAL. Lipids, insulin, C-peptide, C-reactive protein (CRP), vascular cellular adhesion molecule-1, intercellular adhesion molecule 1, E-selectin, P-selectin, leptin, resistin, and adiponectin were measured using assay kits. The expression of specific proteins related to endothelial dysfunction was determined using quantitative real-time polymerase chain reaction. Associations between total ST, prolonged sedentary bouts, and sedentary breaks with cardiometabolic biomarkers and total ST and levels of gene expression were assessed using generalized linear models. Results Total ST was significantly associated with triglycerides (B = 1.814), insulin (B = 2.117), homeostasis model assessment of insulin resistance (B = 0.071), and E-selectin (B = 2.052). Leptin (B = 0.086), E-selectin (B = 1.623), and P-selectin (B = 2.519) were significantly associated with prolonged sedentary bouts, whereas leptin (B = −0.017) and CRP (B = −0.016) were associated with sedentary breaks. After adjustment for moderate to vigorous physical activity, the associations between triglycerides (B = 2.048) and total ST, and between CRP (B = −0.016) and sedentary breaks, remained significant. E-selectin mRNA levels (B = 0.0002) were positively associated with ST with or without adjustment for moderate to vigorous physical activity. Conclusions Total ST and prolonged sedentary bouts were positively associated with several cardiometabolic biomarkers, with interruptions in ST potentially contributing to reduced cardiometabolic risk in physically active young male adults.

The main purpose in this study was to understand the interactions of coal particles with three amphiphilic humic acid-based polymers, which were designed and synthesized through the copolymerization of humic acid (HA) with maleic anhydride-polyethylene glycol 400 monoester, methacrylatoethyl trimethyl ammonium chloride or both of them, respectively, abbreviated as HAM, HAD and HMD. The adsorption quantities of HMD and HAD increased monotonically with the equilibrium concentration of dispersant, which were well described by Freundlich adsorption equation, but the Langmuir adsorption equation was more suitable for HAD dispersant. Besides, the wettability of HMD solutions on the coal surface was better than others. Moreover, the HMD dispersant exhibited better viscosity-reducing and stabilizing capability for coal-water slurry (CWS) than that of HAD and HAM, which were due to the strong adsorption force that was good for improving the hydrophily and enhancing the steric hindrance and electrostatic repulsion among coal particles.

Background and Aims Endoscopy guidelines recommend adhering to policies such as resect and discard only if the optical biopsy is accurate. However, accuracy in predicting histology can vary greatly. Computer-aided diagnosis (CAD) for characterization of colorectal lesions may help with this issue. In this study, CAD software developed at the University of Adelaide (Australia) that includes serrated polyp differentiation was validated with Japanese images on narrow-band imaging (NBI) and blue-laser imaging (BLI). Methods CAD software developed using machine learning and densely connected convolutional neural networks was modeled with NBI colorectal lesion images (Olympus 190 series - Australia) and validated for NBI (Olympus 290 series) and BLI (Fujifilm 700 series) with Japanese datasets. All images were correlated with histology according to the modified Sano classification. The CAD software was trained with Australian NBI images and tested with separate sets of images from Australia (NBI) and Japan (NBI and BLI). Results An Australian dataset of 1235 polyp images was used as training, testing, and internal validation sets. A Japanese dataset of 20 polyp images on NBI and 49 polyp images on BLI was used as external validation sets. The CAD software had a mean area under the curve (AUC) of 94.3% for the internal set and 84.5% and 90.3% for the external sets (NBI and BLI, respectively). Conclusions The CAD achieved AUCs comparable with experts and similar results with NBI and BLI. Accurate CAD prediction was achievable, even when the predicted endoscopy imaging technology was not part of the training set.