Objective To investigate whether chemokine CC motif 2 (CCL2) is involved in the high residual platelet response,and the mechanism of CCL2 being involved in the regulation of platelets.Methods Forty patients with ST elevation myocardial infarction (STEMI) were admitted.P2Y12 reaction unit (PRU) was detected by VerifyNow.Forty patients were divided into high platelet reactivity group (high reactivity group,n=24) and normal platelet reactivity group (normal reactivity group,n=16) according to the results of PRU detection.Plasma CCL2 concentration of the STEMI patients was examined by ELISA.The expressions of CCL2 and CCR2 in the platelets were detected by Western blotting.After CCL2 stimulation,the kinases of which phosphorylation was changed in the platelets were screened by ARY003B protein chips.The phosphorylation of p38MAPK and HSP27 in the platelets was tested by Western blotting after CCL2 stimulation in the presence or absence of CCR2 antagonist (RS 102895) or p38MAPK signal pathway inhibitor (SB 203580).Results The plasma CCL2 concentration of high reactivity group was markedly higher than that of normal reactivity group.Moreover,compared with normal reactivity group,the expressions of CCL2 and CCR2 in the platelets of high reactivity group significantly increased.After the platelets were stimulated by CCL2,the phosphorylation of p38α and HSP27 enhanced in the platelets by protein chips screening.When RS 102895 or SB 203580 was treated before CCL2 stimulation,the phosphorylation of p38MAPK and HSP27 decreased.Conclusions CCL2 participates in high residual platelet response in an autocrine/paracrine way.CCL2/CCR2 might affect the function ofplatelets through p38MAPKHSP27 signal pathway.

Objective To conduct an in vitro study of the growth of Pseudomonas aeruginosa,Staphylococcus aureus and Acin- etobacter spp.,and evaluate their response to various concentrations of tumor necrosis factor(TNF)-?,interleukin (IL)-1?, and IL-6.Methods To monitor the growth of bacteria incubated with the cytokines TNF?,IL-1?and IL-6 that were added to RPMI 1640 medium in various concentrations (10,50.100,500 pg,1 and 10 ng) at 2,4 to 6,8 and 16-18 h.The bacterial concentration was estimated when the mixtures of cytokines and specific neutralizing monoclonal antibodies (MoAbs) were in- cubated.Results We found that all three bacterial species showed concentration-dependent growth enhancement when incubated with one or more tested cytokines.Blockade by specific neutralizing cytokine significantly inhibited cytokine-induced growth. When compared with control,the 6 h growth response was maximal with IL-1?for Staphylococcus aureus and Acinetobacter spp.,and with IL-6 for Pseudomonas aeruginosa.Conclusions In this study we provide additional evidence for a newly de- scribed mechanism for bacterial proliferation in the presence of exaggerated and protracted inflammation.The effect that cyto kine-induced growth enhancement inhibited by specific neutralizing cytokine MoAbs may be useful for antimicrobial therapy.

Syndrome differentiation is the character of Chinese medicine (CM). Disease differentiation is the principle of Western medicine (WM). Identifying basic syndromes feature and structure of disease of WM is an important avenue for prevention and treatment of integrated Chinese and Western medicine. The idea here is first to divide all patients suffering from a disease of WM into several groups in the light of the stage of the disease, and secondly to identify basic syndromes feature in a distinct stage, and finally to achieve the purpose of syndrome differentiation. Syndrome differentiation is simply taken as a classifier that classifies patients into distinct classes primarily based on overall observation of their symptoms. Previous clustering methods are unable to cope with the complexity of CM. We therefore show a new multi-dimensional clustering method in the form of general latent structure (GLS) model, which is a suitable statistical learning technique of latent class analysis. In this paper, we learn an optimal GLS model which reflects much better model quality compared with other latent class models from the osteoporosis patient of community women (OPCW) real data including 40-65 year-old women whose bone mineral density (BMD) is less than mean-2.0 standard deviation (M-2.0SD). Further, we illustrate a case analysis of statistical identification of CM syndromes feature and structure of OPCW from qualitative and quantitative contents through the GLS model. Our analysis has discovered natural clusters and structures that correspond well to CM basic syndrome and factors of osteoporosis patients (OP). The GLS model suggests the possibility of establishing objective and quantitative diagnosis standards for syndrome differentiation on OPCW. Hence, for the future it can provide a reference for the similar study from the perspective of a combination of disease differentiation and syndrome differentiation.
Adult ; Aged ; Bone Density ; physiology ; Diagnosis, Differential ; Disease ; classification ; Female ; Humans ; Male ; Medicine, Chinese Traditional ; methods ; Middle Aged ; Models, Statistical ; Osteoporosis ; diagnosis ; metabolism ; physiopathology ; Research Design ; statistics & numerical data ; Surveys and Questionnaires ; Syndrome ; Western World

This study is to report the evaluation of the micromeritic properties of LubriTose AN, which is expected to provide preliminary theoretical basis for the direct compression technology. From the aspects of flowability, compressibility and dilution potential, the angle of repose, flow velocity, the Carr' index, tensile strength, elastic recovery, yield pressure and the lubricating ability of LubriTose AN were determined. Also, model drugs were selected to investigate the dilute potential under the desirable compressing performance. Compared to the physical mixtures, the flowability of LubriTose AN was better, and the deformation mechanism was the same with anhydrous lactose, both brittle deformation. The compressibility and compaction of LubriTose AN was slightly better than that of physical mixtures under low and moderate pressure. The dilution potential of LubriTose AN were high for most of hydrophobic drugs. The lubricate ability was desirable under different rotational speeds. LubriTose AN is an excellent co-processed excipient, which is helpful for the promotion and improvement of the tablet manufacturing level.
Drug Compounding ; Elasticity ; Excipients ; chemistry ; Glycerides ; chemistry ; Ibuprofen ; administration & dosage ; chemistry ; Lactose ; chemistry ; Lubricants ; chemistry ; Lubrication ; Particle Size ; Pressure ; Technology, Pharmaceutical ; methods ; Tensile Strength

Objective:To evaluate the value of Sonazoid contrast enhanced ultrasound (CEUS) in preoperative prediction of proliferating cell nuclear antigen 67 (Ki-67) level of hepatocellular carcinoma (HCC) by establishing predictive model based on radiomics features of Kupffer phase.Methods:From October 2020 to August 2021, patients with histologically confirmed HCC lesion and who underwent Sonazoid CEUS examination 1 week before surgery were prospectively enrolled. The radiomics signatures were extracted from the whole tumor region on gray scale images and Kupffer phase images. Two predictive radiomics models were constructed using radiomic method. The predictive performance of 2 models was compared.Results:A total of 50 patients with histologically confirmed single HCC lesions were prospectively enrolled in this study. Among them, histological results revealed 24 HCC lesions with high level representation of Ki-67 (>20%) and 26 HCC lesions with low level representation of Ki-67 (≤20%). Two radiomics predictive models were established based on gray scale images and Kupffer phase images respectively. While compared with model based on B-mode ultrasound images, model based on Kupffer phase images showed significantly higher area under receiver operating characteristic curve (0.753 vs 0.535, P=0.017), accuracy (0.720 vs 0.580, P=0.023) and sensitivity (0.458 vs 0.250, P=0.043). Calibration plot indicated that Kupffer phase model showed better consistency with the actual Ki-67 level than gray scale model. Conclusions:The radiomics model based on Kupffer phase features of Sonazoid CEUS is a preoperative and noninvasive prediction the presentation level of Ki-67 in HCC lesions.

OBJECTIVETo test the safety and accuracy of the computer-assisted orthopaedic system for distal locking of intramedullary nails and apply it to internal fixation with intramedullary nails in the lower limb.

METHODSAccording to the theory of mechanical arms stereotactic localization in computer-assisted orthopaedic surgery (CAOS), we design a CAOS system for distal locking of intramedullary nails. The system comprised 2 independent modules: computer-assisted imaging and registration workstation; mechanical stereotactic framework. Ten plastic tibia models, 20 plastic femur models (Synbone AG, Malans, Switzerland) and 6 human cadaver lower limbs were randomly divided into 2 groups undergoing internal fixation with intramedullary nails (Orthofix, Germany). The first group (CAOS group with 5 plastic tibia models, 10 plastic femur models, 6 human cadaver tibia, 6 human cadaver femur; each nail had 2 holes, and 2 distal locking screws were inserted in each bone, which gave a total number of 54 holes) used a computer-assisted orthopaedic system, the second group (CONTROL GROUP is the same as CAOS group) used Orthofix mechanical targeting device for distal locking. Comparison between 2 groups was made in radiation exposure time, operating time, percentage of correctly placed screws.

RESULTSCAOS group: operating time was (4.44 +/- 2.99) min; radiation exposure time was (1.16 +/- 0.38) min; correctly placed screws rate was (100 +/- 0)%.

CONTROL GROUPoperating time was (10.42 +/- 4.18) min; radiation exposure time was (4.71 +/- 3.86) min; correctly placed screws rate was (94.44 +/- 0.36)%. Operating time and radiation exposure time in CAOS group were significantly shorter than those in control group (P < 0.05), no differences were found between 2 groups in relation to the percentage of correctly placed screws.

CONCLUSIONSBy using CAOS system for distal locking of intramedullary nails, the locking holes can be drilled accurately and safely. Radiation exposure significantly reduced.

Cadaver ; Equipment Design ; Femur ; surgery ; Fracture Fixation, Intramedullary ; instrumentation ; Humans ; Models, Anatomic ; Random Allocation ; Surgery, Computer-Assisted ; instrumentation ; Tibia ; surgery

OBJECTIVETo establish a convenient and high-throughput respiratory virus detection method to facilitate epidemiological viral monitoring.

METHODSWe used high-throughput microsphere-based flexible multi-analyte profiling technology (xMAP) coupled with signal amplification molecules to simultaneously detect RNAs of 8 viruses including influenza viruses A and B, parainfluenza viruses type 1, 2 and 3, respiratory syncytial viruses A and B, and metapneumovirus in a 96-well plate format. The sensitivity and specificity of the method for the synthetic viral RNAs were evaluated.

RESULTSThere was no cross-reactivity among the 8 respiratory viral target RNAs. The detection limits for the 8 viral in intro-transcribed RNAs ranged from 1204 to 4695 RNA copies.

CONCLUSIONWe establish a sensitive, specific, convenient, and high-throughput multiplex detection method suitable for detecting multiple respiratory viral RNAs for epidemiological viral monitoring.

High-Throughput Screening Assays ; methods ; Influenza A virus ; genetics ; isolation & purification ; Influenza B virus ; genetics ; isolation & purification ; Limit of Detection ; Metapneumovirus ; genetics ; isolation & purification ; Nucleic Acid Amplification Techniques ; methods ; RNA, Viral ; analysis ; Respiratory Syncytial Viruses ; genetics ; isolation & purification ; Respiratory System ; virology ; Respirovirus ; genetics ; isolation & purification ; Reverse Transcription ; Sensitivity and Specificity

Chronic lymphocytic leukemia(CLL)/small lymphocytic lymphoma(SLL)is a relatively inert B lymphocyte proliferative disease.In recent years with the launch of new drugs,chemotherapy has been gradually replaced by targeted therapy,which significantly prolongs the survival of patients and reduces the side effects of treatment.At present,BTK inhibitors,PI3K inhibitors,spleen tyrosine kinase(SYK)inhibitors and BCL-2 inhibitors are the most studied targeted therapeutic drugs for CLL/SLL.This article reviews the research progress of different types of targeted therapeutic drugs in the treatment of CLL/SLL.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.

Objective: Machine learning (ML) has been reported to have better predictive capability than traditional statistical techniques. The aim of this study was to assess the efficacy of ML algorithms and logistic regression (LR) for predicting depressive symptoms during the COVID-19 pandemic. Methods: Analyses were carried out in a national cross-sectional study involving 21,916 participants. The ML algorithms in this study included random forest (RF), support vector machine (SVM), neural network (NN), and gradient boosting machine (GBM) methods. The performance indices were sensitivity, specificity, accuracy, precision, F1-score, and area under the receiver operating characteristic curve (AUC). Results: LR and NN had the best performance in terms of AUCs. The risk of overfitting was found to be negligible for most ML models except for RF, and GBM obtained the highest sensitivity, specificity, accuracy, precision, and F1-score. Therefore, LR, NN, and GBM models ranked among the best models. Conclusion Compared with ML models, LR model performed comparably to ML models in predicting depressive symptoms and identifying potential risk factors while also exhibiting a lower risk of overfitting.