General Condition for Polymer Cononsolvency in Binary Mixed Solvents.

Starting from a generic model based on the thermodynamics of mixing and abstracted from the chemistry and microscopic details of solution components, three consistent and complementary computational approaches are deployed to investigate the general condition for polymer cononsolvency in binary mixed solvents at the zeroth order. The study reveals χPS - χPC + χSC as the underlying universal parameter that regulates cononsolvency, where χαß is the immiscibility parameter between the α- and ß-component. Two disparate cononsolvency regimes are identified for χPS - χPC + χSC < 0 and χPS - χPC + χSC > 2, respectively, based on the behavior of the second osmotic virial coefficient at varying solvent mixture composition x C. The predicted condition is verified using self-consistent field calculations by directly examining the polymer conformational transition as a function of x C. It is further shown that in the regime χPS - χPC + χSC < 0, the reentrant polymer conformation transition is driven by maximizing the solvent-cosolvent contact, but in the regime χPS - χPC + χSC > 2, it is driven by promoting polymer and cosolvent contact. In-between the two regimes when neither effect is dominant, a monotonic response of polymer conformation to x C is observed. Effects of the mean-field approximation on the predicted condition are evaluated by comparing the mean-field calculations with computer simulations. It shows that the fluctuation effects lead to a higher threshold value of χPS - χPC + χSC in the second regime, where local enrichment of cosolvent in polymer proximity plays a critical role.

The Serum NLRP1 Level and Coronary Artery Calcification: From Association to Development of a Risk-Prediction Nomogram.

Background: To investigate the correlation between inflammasomes and coronary artery calcification (CAC), and develop and validating a nomogram for predicting the risk of CAC in patients with coronary artery disease (CAD). Methods: A total of 626 patients with CAD at the Affiliated Hospital of Xuzhou Medical University were enrolled in this study. The patients were divided into the calcification group and the non-calcification group based on the assessment of coronary calcification. We constructed a training set and a validation set through random assignment. The least absolute shrinkage and selection operator (LASSO) regression and multivariate analysis were performed to identify independent risk factors of CAC in patients with CAD. Based on these independent predictors, we developed a web-based dynamic nomogram prediction model. The area under the receiver operating characteristic curve (AUC-ROC), calibration curves, and decision curve analysis (DCA) were used to evaluate this nomogram. Results: Age, smoking, diabetes mellitus (DM), hyperlipidemia, the serum level of nucleotide-binding oligomerization domain (NOD)-like receptor protein 1 (NLRP1), alkaline phosphatase (ALP) and triglycerides (TG) were identified as independent risk factors of CAC. The AUC-ROC of the nomogram is 0.881 (95% confidence interval (CI): 0.850-0.912) in the training set and 0.825 (95% CI: 0.760-0.876) in the validation set, implying high discriminative ability. Satisfactory performance of this model was confirmed using calibration curves and DCA. Conclusions: The serum NLRP1 level is an independent predictor of CAC. We established a web-based dynamic nomogram, providing a more accurate estimation and comprehensive perspective for predicting the risk of CAC in patients with CAD.

The Relationship Between the Serum NLRP3 and Adiponectin Levels and Coronary Lesions in Patients with Unstable Angina with Type 2 Diabetes.

Objective: To investigate the Levels of Nucleotide-binding, leucine-rich repeat and pyrin domain-containing protein 3 (NLRP3) and Adiponectin (APN) and their relationship with the severity of coronary artery disease in patients with Unstable Angina (UA) and Type 2 Diabetes (T2D). Methods: Two hundred and thirty-one patients with UA were diagnosed by CAG in the Department of Cardiology of the Affiliated Hospital of Xuzhou Medical University from July 2022 to May 2023 were included, and 74 healthy subjects were included as the control group. The levels of NLRP3 and APN in each group were detected by ELISA and the Gensini score in each patient according to the results of CAG. The correlations between NLRP3, APN, and Gensini score were analyzed. According to whether complicated with T2D or not, we further analyze the effect of NLRP3 and APN levels of patients with UA and T2D on the severity of coronary artery stenosis. Results: The levels of NLRP3 in UA with T2D group were the highest, followed by simple UA group, and the lowest in the control group, and the level of APN was the opposite. Spearman Correlation analysis showed that the level of NLRP3 was positively correlated with Gensini score (ρ1=0.688, P<0.05) and the level of APN was negatively associated with Gensini score (ρ2= -0.515, P<0.05). There was a negative correlation between NLRP3 and the level of APN (ρ3= -0.366, P<0.05). High NLRP3 and low APN levels are the risk factors for atherosclerosis. Conclusion: The NLRP3 and APN were abnormally expressed in patients with UA complicated with T2D. With the aggravation of atherosclerosis, the level of NLRP3 increased and the level of APN decreased.

Process of mercury accumulation in urban strip river artificial wetland ecosystems: a case study of Changchun, a typical industrial city in Northeast China.

Mercury (Hg), as a global pollutant, is persistent, migratory, insidious, highly biotoxic and highly enriched, and is widely distributed in the atmosphere, hydrosphere, biosphere and lithosphere. Wetland ecosystems, as active mercury reservoirs, have become the most important sources and sinks of heavy metal mercury. Distinguished from natural wetlands, artificial wetlands located in urban sections of rivers face problems such as diverse urban pollution sources and complex spatial and temporal changes. Therefore, in this study, five intermittently distributed artificial wetlands were selected from the upstream to the downstream of the Changchun section of the Yitong River, a tributary of the Songhua River basin in the old industrial base of Northeast China. The mercury levels in the water bodies, sediments and plants of the artificial wetlands were collected and tested in four quarters from April 2023 to analyse the spatial and temporal distribution characteristics of total mercury. The results showed that the mercury levels in the water bodies, sediments and plants of the five wetlands showed a fluctuating trend with the river flow direction and had certain spatial and temporal distribution characteristics. This phenomenon was attributed to the sinking of external mercury pollution sources. In general, the wetland ecosystems showed a decreasing trend in the total Hg output of the downstream watershed. This may be due to the retention of particulate matter by aquatic plants in artificial wetlands to regular salvage of dead aquatic plants. At the same time urbanization and industrialization affect mercury levels in aquatic environments, so the risk of residential exposure needs to be looked at.

A CT-based Deep Learning Radiomics Nomogram for the Prediction of EGFR Mutation Status in Head and Neck Squamous Cell Carcinoma.

RATIONALE AND OBJECTIVES: Accurately assessing epidermal growth factor receptor (EGFR) mutation status in head and neck squamous cell carcinoma (HNSCC) patients is crucial for prognosis and treatment selection. This study aimed to construct and validate a contrast-enhanced computed tomography (CECT)-based deep learning radiomics nomogram (DLRN) to predict EGFR mutation status of HNSCC. MATERIALS AND METHODS: A total of 300 HNSCC patients who underwent CECT scans were enrolled in this study. Participants from two hospitals were separated into a training set (n = 200, 56 EGFR-negative and 144 EGFR-positive) from one hospital and an external test set from the other hospital (n = 100, 37 EGFR-negative and 63 EGFR-positive). The least absolute shrinkage and selection operator method was used to select the key features from CECT-based manually extracted radiomics (MER) features and features automatically extracted using a deep learning model (DL, extracted using a GoogLeNet model). The selected independent clinical factors, MER features, and DL features were then combined to construct a DLRN. The DLRN's performance was evaluated using receiver operating characteristics curves. RESULTS: Five MER and six DL features were finally chosen. The DLRN, which includes "gender" and "necrotic areas," along with the selected features, predicted EGFR mutation status of HNSCC (EGFR-negative vs. positive) well in both the training (area under the curve [AUC], 0.901) and test (AUC, 0.875) sets. CONCLUSION: A DLRN using CECT was built to predict EGFR mutation in HNSCC. The model showed high predictive ability and may aid in treatment selection and patient prognosis.

Prediction of subsolid pulmonary nodule growth rate using radiomics.

BACKGROUND: Pulmonary nodule growth rate assessment is critical in the management of subsolid pulmonary nodules (SSNs) during clinical follow-up. The present study aimed to develop a model to predict the growth rate of SSNs. METHODS: A total of 273 growing SSNs with clinical information and 857 computed tomography (CT) scans were retrospectively analyzed. The images were randomly divided into training and validation sets. All images were categorized into fast-growth (volume doubling time (VDT) ≤ 400 days) and slow-growth (VDT > 400 days) groups. Models for predicting the growth rate of SSNs were developed using radiomics and clinical features. The models' performance was evaluated using the area under the curve (AUC) values for the receiver operating characteristic curve. RESULTS: The fast- and slow-growth groups included 108 and 749 scans, respectively, and 10 radiomics features and three radiographic features (nodule density, presence of spiculation, and presence of vascular changes) were selected to predict the growth rate of SSNs. The nomogram integrating radiomics and radiographic features (AUC = 0.928 and AUC = 0.905, respectively) performed better than the radiographic (AUC = 0.668 and AUC = 0.689, respectively) and radiomics (AUC = 0.888 and AUC = 0.816, respectively) models alone in both the training and validation sets. CONCLUSION: The nomogram model developed by combining radiomics with radiographic features can predict the growth rate of SSNs more accurately than traditional radiographic models. It can also optimize clinical treatment decisions for patients with SSNs and improve their long-term management.

[Collagen peptide partially restores immune function in mice under the condition of X-ray irradiation combined with simulated weightlessness].

Objective To investigate the effects of collagen peptides on the immune function of mice under the condition of X-ray irradiation combined with simulated weightlessness. Methods Mice were randomly divided into control group, modelling group and collagen peptide group. Mice in collagen peptide group were intraperitoneally injected with collagen peptide (600 mg/kg) once a day from the first day of the experiment, while mice in the other two groups were intraperitoneally injected with normal saline. On the fourth day of the experiment, mice in the modelling group and collagen peptide group were simultaneously exposed to X-ray irradiation (2 Gy) and hindlimb-unloaded simulated weightlessness by tail-suspension. On the 10th day of the experiment, the mice were terminated by cervical dislocation. Automated hematology analyzer was used to detect Leukocyte classification of peripheral blood. Splenic lymphocyte subsets, cell cycle and apoptosis of bone marrow cells were analyzed by flow cytometry. The expressions of 19 plasma cytokines were tested with liquid suspension chips. Results Compared with the control group, the modelling group had a significant reduction in the total number of white blood cells and lymphocytes in the peripheral blood, the total number of splenocyte and the number of T cells, CD4+ and CD8+ T cells, B cells, and natural killer (NK) cells in the spleen, an decrease in 18 cytokines in the plasma, and an increase in myelocyte apoptosis in mice of the modelling group. Compared with the modelling group, most immunological parameters had improved in the mice of the collagen peptide group except some cytokines. Conclusion Collagen peptides can effectively improve the immune function of mice under the condition of X-ray irradiation combined with simulated weightlessness.

Rapid Segmentation and Diagnosis of Breast Tumor Ultrasound Images at the Sonographer Level Using Deep Learning.

BACKGROUND: Breast cancer is one of the most common malignant tumors in women. A noninvasive ultrasound examination can identify mammary-gland-related diseases and is well tolerated by dense breast, making it a preferred method for breast cancer screening and of significant clinical value. However, the diagnosis of breast nodules or masses via ultrasound is performed by a doctor in real time, which is time-consuming and subjective. Junior doctors are prone to missed diagnoses, especially in remote areas or grass-roots hospitals, due to limited medical resources and other factors, which bring great risks to a patient's health. Therefore, there is an urgent need to develop fast and accurate ultrasound image analysis algorithms to assist diagnoses. METHODS: We propose a breast ultrasound image-based assisted-diagnosis method based on convolutional neural networks, which can effectively improve the diagnostic speed and the early screening rate of breast cancer. Our method consists of two stages: tumor recognition and tumor classification. (1) Attention-based semantic segmentation is used to identify the location and size of the tumor; (2) the identified nodules are cropped to construct a training dataset. Then, a convolutional neural network for the diagnosis of benign and malignant breast nodules is trained on this dataset. We collected 2057 images from 1131 patients as the training and validation dataset, and 100 images of the patients with accurate pathological criteria were used as the test dataset. RESULTS: The experimental results based on this dataset show that the MIoU of tumor location recognition is 0.89 and the average accuracy of benign and malignant diagnoses is 97%. The diagnosis performance of the developed diagnostic system is basically consistent with that of senior doctors and is superior to that of junior doctors. In addition, we can provide the doctor with a preliminary diagnosis so that it can be diagnosed quickly. CONCLUSION: Our proposed method can effectively improve diagnostic speed and the early screening rate of breast cancer. The system provides a valuable aid for the ultrasonic diagnosis of breast cancer.

FCAN-XGBoost: A Novel Hybrid Model for EEG Emotion Recognition.

In recent years, artificial intelligence (AI) technology has promoted the development of electroencephalogram (EEG) emotion recognition. However, existing methods often overlook the computational cost of EEG emotion recognition, and there is still room for improvement in the accuracy of EEG emotion recognition. In this study, we propose a novel EEG emotion recognition algorithm called FCAN-XGBoost, which is a fusion of two algorithms, FCAN and XGBoost. The FCAN module is a feature attention network (FANet) that we have proposed for the first time, which processes the differential entropy (DE) and power spectral density (PSD) features extracted from the four frequency bands of the EEG signal and performs feature fusion and deep feature extraction. Finally, the deep features are fed into the eXtreme Gradient Boosting (XGBoost) algorithm to classify the four emotions. We evaluated the proposed method on the DEAP and DREAMER datasets and achieved a four-category emotion recognition accuracy of 95.26% and 94.05%, respectively. Additionally, our proposed method reduces the computational cost of EEG emotion recognition by at least 75.45% for computation time and 67.51% for memory occupation. The performance of FCAN-XGBoost outperforms the state-of-the-art four-category model and reduces computational costs without losing classification performance compared with other models.

Stiffness changes in internal rotation muscles of the shoulder and its influence on hemiplegic shoulder pain.

Background: Hemiplegic shoulder pain (HSP) is a common complication in patients with stroke. The pathogenesis of HSP is complex, and muscle hypertonia, especially the hypertonia of internal rotation muscles of the shoulder, may be one of the important causes of shoulder pain. However, the relationship between muscle stiffness and HSP has not been well studied. The purpose of this study is to explore the correlations between the stiffness of internal rotation muscles and clinical symptoms in patients with HSP. Methods: A total of 20 HSP patients and 20 healthy controls were recruited for this study. The stiffness of internal rotation muscles was quantified using shear wave elastography, and Young's modulus (YM) of the pectoralis major (PM), anterior deltoid (AD), teres major ™, and latissimus dorsi (LD) were measured. Muscle hypertonia and pain intensity were evaluated using the Modified Ashworth Scale (MAS) and Visual Analog Scale (VAS), respectively. The mobility of the shoulder was evaluated using the Neer score. The correlations between muscle stiffness and the clinical scales were analyzed. Results: YM of internal rotation muscles on the paretic side was higher than that of the control group in the resting and passive stretching positions (P < 0.05). YM of internal rotation muscles on the paretic side during passive stretching was significantly higher than that at rest (P < 0.05). YM of PM, TM, and LD during passive stretching were correlated with MAS (P < 0.05). In addition, the YM of TM during passive stretching was positively correlated with VAS and negatively correlated with the Neer score (P < 0.05). Conclusion: Increased stiffness of PM, TM, and LD was observed in patients with HSP. The stiffness of TM was associated with pain intensity of the shoulder and shoulder mobility.

Comparison the acute toxicity of two different induction chemotherapy schedules with cisplatin and fluorouracil in nasopharyngeal carcinoma patients.

PURPOSE: To compare the acute toxicity of two different induction chemotherapy (IndCT) regimen followed by the same IMRT in patients with advanced nasopharyngeal carcinoma (NPC). MATERIALS AND METHODS: From July 2015 to December 2016, 110 NPC patients with stage III-IV diseases were prospectively randomized to receive either a conventional triweekly cisplatin + 5-fluorouracil (PF) for 3 cycles or weekly P-F for 10 doses, followed by the same IMRT to both arms. The primary endpoints of this study were grade 3/4 and any grade acute toxicities during IndCT period. The secondary endpoints included tumor response and various survivals. RESULTS: Baseline patient characteristics were comparable in both groups. Patients who received weekly P-F experienced significant reduction of grade 3/4 acute toxicities, including neutropenia (12.7% vs. 40.0%, P = 0.0012), anorexia (0% vs. 14.6%, P = 0.0059), mucositis (0% vs. 14.6%, P = 0.0059), and hyponatremia (0% vs. 16.4%, P = 0.0027), compared with the triweekly PF group, resulting in fewer IndCT interruptions (1.8% vs. 16.4%, P = 0.0203), emergency room visits (0% vs. 12.7%, P = 0.0128), and additional hospitalizations (0% vs. 9.1%, P = 0.0568). The acute toxicities during IMRT period were similar. Weekly P-F arm had higher complete response rates (83.6% vs. 61.8%, P = 0.0152) and lower relapse rates (16.4% vs. 33.3%, P = 0.0402) after a median follow-up of 67 months. Kaplan-Meier survival analyses revealed a better trend of locoregional failure-free (P = 0.0892), distant metastasis failure-free (P = 0.0775), and progression-free (P = 0.0709) survivals, favoring the weekly P-F arm. CONCLUSION: IndCT of weekly schedule does reduce acute toxicities without compromised tumor response and survivals.

The Relationship between the Serum NLRP1 Level and Coronary Lesions in Patients with Coronary Artery Disease.

Background: The pathogenesis of coronary artery disease is complex, and inflammation is one of the regulatory factors. The nucleotide-binding oligomerization domain (NOD)-like receptor protein 1 (NLRP1) plays an important role in the cellular inflammatory response, cell apoptosis, cell death, and autoimmune diseases. Whether the level of NLRP1 is related to the severity of coronary artery stenosis in patients with coronary artery disease (CAD) has not been reported. Objective: To test the serum level of NLRP1 in unstable angina (UA) patients and investigate the effect of NLRP1 on coronary stenosis severity of the coronary artery disease (CAD). Methods: 307 patients hospitalized in the Department of Cardiology of the Affiliated Hospital of Xuzhou Medical University for coronary angiography from January 1, 2021, to December 31, 2022 were included. We detect the level of NLRP1 in the serum of the included patients. Patients were divided into UA group and control group according to coronary angiography results and other clinical data. We use logistic regression to screen the influencing factors of UA. Then, subgroups were divided according to the Gensini score and the number of coronary artery lesions, and the difference of serum NLRP1 level between the groups was compared. Spearman correlation analysis was used to explore the correlation between the serum NLRP1 level and Gensini score. We analyze the diagnostic value of NLRP1 for UA by drawing ROC curve. Results: The median level of serum NLRP1 in patients with UA (n = 257) was 49.71 pg/ml, IQR 30.15, 80.21, and that in patients without UA (n = 50) was 24.75 pg/ml, IQR 13.49, 41.95. Serum NLRP1 levels were significantly different among different subgroups. The patient's Gensini score was correlated with the patient's serum NLRP1 level. Conclusion: The serum NLRP1 level is increased in patients with UA, which is increased with the increasing severity of coronary lesions.

Ralstonia solanacearum - A soil borne hidden enemy of plants: Research development in management strategies, their action mechanism and challenges.

Plant pathogens present in soil cause severe losses to plants every year. Among them, Ralstonia solanacearum, because of its destructive nature, is the world's second most damaging bacterial phytopathogen. Over 310 species of plants belonging to 42 plant families are infected by this deadly pathogen. Around the world, the bacterial wilt (BW) disease causes yield losses that range from 20 to 100%. Control measures for managing this pathogen comprises several diverse approaches. Regardless of whether several control methods are developed to manage the BW disease, efficient management strategies with eco-friendly effects and the desired level of effective control is still awaited and there is need to developed effective management methods to eliminate this fetal disease in several crops under field conditions. An analysis of development in the management strategies will provide an effective way to search and develop control methods with desirable level of effectiveness. In this review, we discussed and analyzed the information reported on the development of various management strategies for the management of R. solanacearum along with the comprehensive presentation on action mechanism of these management strategies. We have also made an effort to summarize the challenges that make hurdle in the effective management of this deadly pathogen. The analysis of the information in this review article will assist in future implications of management strategies and help in developing effective control measures with more efficacy.

Two new species of the genus Diestramima from China (Orthoptera: Rhaphidophoridae: Aemodogryllinae).

The genus Diestramima comprises 41 species from Asia with 31 species distributed in China. In this study, we reconstruct the phylogeny tree of Diestramima species by maximum likelihood and Bayesian inference based on three mitochondrial genes (COI, 12S and 16S). The result indicates that the phylogenetic results are coherent with that based on five molecular markers (COI, 12S, 16S, 18S and 28S). Moreover, two new species, D. pingmengensis sp. nov. He & Zong and D. gulinjingensis. sp. nov. Zong & He are described. Their validities are also supported by morphological features. Furthermore, D. sichuanensis Zhu & Shi, 2022 is treated as a junior synonym of D. guangxiensis Qin, Wang, Liu & Li, 2016 based on both morphological and molecular features.

KLF9 Aggravates Streptozotocin-Induced Diabetic Cardiomyopathy by Inhibiting PPARγ/NRF2 Signalling.

AIMS: Krüppel-like Factor 9 (KLF9) is a transcription factor that regulates multiple disease processes. Studies have focused on the role of KLF9 in the redox system. In this study, we aimed to explore the effect of KLF9 on diabetic cardiomyopathy. METHODS AND RESULTS: Cardiac-specific overexpression or silencing of KLF9 in C57BL/6 J mice was induced with an adeno-associated virus 9 (AAV9) delivery system. Mice were also subjected to streptozotocin injection to establish a diabetic cardiomyopathy model. In addition, neonatal rat cardiomyocytes were used to assess the possible role of KLF9 in vitro by incubation with KLF9 adenovirus or small interfering RNA against KLF9. To clarify the involvement of peroxisome proliferator-activated receptors (PPARγ), mice were subjected to GW9662 injection to inhibit PPARγ. KLF9 was upregulated in the hearts of mice with diabetic cardiomyopathy and in cardiomyocytes. In addition, KLF9 overexpression in the heart deteriorated cardiac function and aggravated hypertrophic fibrosis, the inflammatory response and oxidative stress in mice with diabetic cardiomyopathy. Conversely, cardiac-specific silencing of KLF9 ameliorated cardiac dysfunction and alleviated hypertrophy, fibrosis, the cardiac inflammatory response and oxidative stress. In vitro, KLF9 silencing in cardiomyocytes enhanced inflammatory cytokine release and oxidative stress; KLF9 overexpression increased these detrimental responses. Moreover, KLF9 was found to regulate the transcription of PPARγ, which suppressed the expression and nuclear translocation of nuclear Factor E2-related Factor 2 (NRF2). In mice injected with a PPARγ inhibitor, the protective effects of KLF9 knockdown on diabetic cardiomyopathy were counteracted by GW9662 injection. CONCLUSIONS: KLF9 aggravates cardiac dysfunction, the inflammatory response and oxidative stress in mice with diabetic cardiomyopathy. KLF9 may become a therapeutic target for diabetic cardiomyopathy.

Overexpression of Dermokine-α enhances the proliferation and epithelial-mesenchymal transition of pancreatic tumor cells.

Pancreatic cancer is a prevalent malignancy of the digestive system and a major cause of cancer-associated deaths. Previous studies have shown that mutation in the dermokine-ß (DMKN-ß) gene causes pancreatic and colorectal cancer. The role of the carboxy-terminal domain of DMKN-ß and dermokine-α (DMKN-α) genes in cancer tumorigenesis. Herein, the role of DMKN-α in pancreatic cancer (PC) tumorigenesis and the mechanisms underlying this process were investigated. Differentially expressed genes between PC and matched normal cells were identified through RNA-seq analysis, and the corresponding protein expression levels were verified using Western blot analysis. In vivo tumor formation experiment was also performed in nude mice. We found that the DMKN-α gene was overexpressed in cancerous pancreatic cell lines compared to normal pancreatic cell lines. CCK-8, colony formation, RTCA test, wound healing, as well as transwell test showed that the overexpression of DMKN-α enhanced the proliferation, migration, invasion, and EMT of PC cells. In vivo assays confirmed that DMKN-α promotes tumorigenesis. The findings of this study show that DMKN-α is a potential oncogene for pancreatic cancer.

Taxonomic revision of the genus Hemigyrus Brunner von Wattenwyl, 1893 (Orthoptera: Tettigoniidae: Pseudophyllinae).

Hemigyrus was established by Brunner von Wattenwyl in 1893. In this study, we collected samples from Chongqing, Guangxi, Hainan, Sichuan, Tibet and Yunnan of China, and reconstructed phylogenetic tree based on COI gene. The results supported the classification of dividing this genus into two subgenera: Tomomima and Hemigyrus. With larger size and evidently branched phylogenetic position, a new subspecies H. (T.) spinosus robustus subsp. nov. Xie, Wang He is described here. H. (H.) acutifolius is firstly reported from China. Males of H. (H.) amplus and H. (H.) acutifolius, females of H. (H.) minor are described for the first time. All materials were deposited in Biological History Museum of East China Normal University (ECNU) and the Shanghai Entomological Museum, Chinese Academy of Sciences (SEM).

Complement Factor H related protein 1 and immune inflammatory disorders.

Human complement Factor H-related protein 1 (FHR-1) is one of complement Factor H-related proteins (FHRs) and plays an important role in innate immunity. In particular, FHR-1 promotes complement activation by competing with Factor H (FH) for ligands on different surfaces or directly binding to C3b and native C3. Paradoxically, FHR-1 restrains complement activation by inhibiting C5 convertase and terminal complement complex (TCC) formation, and in vitro assays showed that the physiological concentration of FHR-1 had no obvious C3 and C5 regulatory activity. FHR-1 also plays a role in the inflammatory process. MDA-bound FHR-1 promotes inflammatory cytokine release from monocytes in a complement-independent manner. However, its deficiency increases TNFα, IL1ß, IL6, and IL10 secretion from monocytes stimulated with LPS and R484. These contradictory effects of FHR-1 in innate immunity indicate that FHR-1 may function differently in different scenarios. Dysregulation of innate immunity due to frequent CFHR1 variations is associated with various immune inflammatory disorders. Mutations in the C-terminus of FHR-1 that increase its similarity with FH are associated with atypical haemolytic uraemia syndrome (aHUS). In contrast, mutations in the N-terminus that increase the multimerization of FHRs are associated with C3 glomerulopathy (C3G). Changes in FHR-1 concentration have been observed in other diseases. The different functions of the C-terminus and N-terminus of FHR-1 and the distinct function of FHR-1 under various conditions may explain the association of CFHR1 variations with different diseases. Here, we summarized the recent progress on FHR-1 and dissected its role in various immune inflammatory disorders, helping to comprehend and further explore the disease pathogenesis.

Qishen Taohong Granule () as Adjuvant Therapy for Improving Cardiac Function and Quality of Life in Patients with Chronic Heart Failure: A Randomized Controlled Trial / 中国结合医学杂志

OBJECTIVE@#To confirm the improvement of cardiac function and quality of life (QOL) in patients with chronic heart failure (CHF) via Chinese medicine (CM) Qishen Taohong Granule (, QTG).@*METHODS@#This study was a single-center, prospective, randomized, controlled clinical trial. Seventy-six patients from 27 to 84 years old diagnosed with CHF New York Heart Association (NYHA) class II or III in stage C were enrolled and randomly assigned at a 1:1 ratio to receive QTG or trimetazidine (TMZ), in addition to their standard medications for the treatment of CHF. The study period was 4 weeks. The primary outcomes included cardiac function evaluated by NYHA classification and left ventricular ejection fraction (LVEF), as well as QOL evaluated by CHF Integrated Chinese and Western Medicine Survival Scale (CHFQLS). The secondary outcomes included 6-min walking test (6MWT), CM syndrome score, symptom and sign scores and N-terminal pro-B-type natriuretic peptide (NT-proBNP). All indices were measured at baseline and the end of the trial.@*RESULTS@#At the 4-week follow-up period, the effective rate according to NYHA classification in the QTG group was better than that in the TMZ group (74.29% vs. 54.29%, P<0.05). But there was no significant difference in post-treatment level of LVEF between the two groups (P>0.05). The CHFQLS scores improved by 13.82±6.04 vs. 7.49±2.28 in the QTG and TMZ groups, respectively (P<0.05). Subgroup analysis of the CHFQLS results showed that physiological function, role limitation and vitality were significantly higher in the QTG group than in the TMZ group (15.76±7.85 vs. 7.40±3.36, P<0.05; 16.00±8.35 vs. 10.53±4.64, P<0.05; 15.31±8.09 vs. 7.89±4.60, P<0.05). Compared with TMZ group, treatment with QTG also demonstrated superior performance with respect to 6MWT, CM syndrome, shortness of breath, fatigue, gasping, general edema and NT-proBNP level. No significant adverse reactions or adverse cardiac events occurred during treatment in either group.@*CONCLUSION@#In addition to conventional treatments, the use of QTG as an adjuvant therapy significantly improved cardiac function and QOL in patients with CHF class II or III in stage C. [Registration No. ChiCTR1900022036 (retrospectively registered)].