Background and purpose:For patients with human epidermal growth factor receptor 2(HER2)-positive metastatic breast cancer,trastuzumab treatment can prolong the overall survival and significantly improve the prognosis of patients.However,the reference original research trastuzumab(Herceptin?)is more expensive.Biosimilars have comparable efficacy and safety profiles while increasing patient access to treatment.This clinical trial aimed to evaluate the efficacy,pharmacokinetics,safety and immunogenicity of the trastuzumab biosimilar AK-HER2 compared to trastuzumab(Herceptin?)in patients with HER2-positive metastatic breast cancer.Methods:This multi-center,randomised,double-blind phase Ⅲ clinical trial was conducted in 43 subcenters in China.This study complied with the research protocol,the ethical principles stated in the Declaration of Helsinki and the quality management standards for drug clinical trials.It was approved by the hospital's medical ethics committee.The clinical trial registration agency is the State Food and Drug Administration(clinical trial approval number:2015L04224;clinical trial registration number:CTR20170516).Written informed consent was obtained from subjects before enrollment.Enrolled patients were randomly assigned to the AK-HER2 group and the control group,respectively receiving AK-HER2 or trastuzumab(initial loading dose 8 mg/kg,maintenance dose 6 mg/kg,every 3 weeks as a treatment cycle,total treatment time is 16 cycles)in combination with docetaxel(75 mg/m2,treatment duration is at least 9 cycles).The primary endpoint of this clinical trial was the objective response rate(ORR9)between the AK-HER2 group and the control group in the 9th cycle.Secondary efficacy endpoints included ORR16,disease control rate(DCR),clinical benefit rate(CBR),progression-free survival(PFS)and 1-year survival rate.In this study,100 subjects(AK-HER2 group to control group=1:1)were randomly selected for blood sample collection after the 6th cycle of medication,The collection time points were 45 minutes after infusion(the end of administration),4,8,24,72,120,168,336,and 504 hours after the end of administration.After collection,blood samples were analyzed by PK parameter set(PKPS).Other evaluation parameters included safety and immunogenicity assessment.Results:A total of 550 patients with HER2-positive metastatic breast cancer were enrolled in this clinical trial between Sep.2017 and Mar.2021.In the AK-HER2 group(n=237),129 subjects in the experimental group achieved complete response(CR)or partial response(PR),and the ORR9 was 54.4%.There were 134 subjects in the control group(n=241)who achieved CR or PR,and the ORR9 was 55.6%.The ORR9 ratio between the AK-HER2 group and the control group was 97.9%[90%confidence interval(CI):85.4%-112.2%,P=0.784],which was not statistically significant.In all secondary efficacy endpoints,no statistically significant differences were observed between the two groups.We conducted a mean ratio analysis of pharmacokinetics(PK)parameters between the AK-HER2 group and the control group,and the results suggested that the pharmacokinetic characteristics of the two drugs are similar.The incidence of treatment emergent adverse event(TEAE)leading to drug reduction or suspension during trastuzumab treatment was 3.6%(10 cases)in the AK-HER2 group and 8.1%(22 cases)in the control group.There was statistically significant difference between the two groups(P=0.027).The incidence rate was significantly lower in the AK-HER2 group than in the control group,and there was no statistically significant difference among the other groups.The differences in the positive rates of anti-drug antibodies(ADA)and neutralizing antibodies(NAB)between groups were of no statistical significance(P=0.385 and P=0.752).Conclusion:In patients with HER2-positive metastatic breast cancer,AK-HER2 was comparable to the trastuzumab(Herceptin?)in terms of drug efficacy,pharmacokinetics,safety and immunogenicity.

Rare diseases still lack effective treatments, and the development of drugs for rare diseases (known as orphan drugs) is an urgent medical problem. As natural active ingredients in living organisms, some biomacromolecule drugs have good biocompatibility, low immunogenicity, and high targeting. They have become one of the most promising fields in drug research and development in the 21st century. However, there are still many obstacles in terms of in vivo delivery. In view of the unique advantages of nanocarriers prepared from polymers, lipids, organic biomimetic and inorganic materials in drug delivery, researchers are committed to building an efficient delivery system with versatility and synergy to solve the bottleneck issues in treating rare diseases with biomacromolecule drugs. Therefore, this article reviews the research progress of nanocarrier delivering proteins, peptides and nucleic acids in the field of rare disease treatment in the past ten years, which provides ideas for researches on biomacromolecule drug nanosystems in the field of treatment of rare diseases.

Myeloid neoplasms (MNs) belong to a group of hematological malignancies characterized by the abnormal biological functions of hematopoietic stem progenitor cells. The abnormal immune and hematopoietic microenvironment of patients with MN interact with malignant clonal hematopoietic stem cells, promoting the occurrence and development of their diseases. MN large granular lymphocyte proliferation (MN-LGLP) is a special and rare clinical phenomenon in this type of disease. Currently, research on this disease in domestic and international cohorts is limited. This study analyzes the clinical and laboratory characteristics of this type of patient and explores the impact of LGLP on the clinical characteristics and survival of patients with MN. Patients with MN-LGLP are prone to neutropenia and splenomegaly. The presence of LGLP is not a risk factor affecting the survival of patients with MN-LGLP. STAG, ASXL1, and TET2 are the most common accompanying gene mutations in MN-LGLP, and patients with MN-LGLP and STAG2 mutations have poor prognoses.

Background::Although overnight fasting is recommended prior to endoscopic retrograde cholangiopancreatography (ERCP), the benefits and safety of high-carbohydrate fluid diet (CFD) intake 2 h before ERCP remain unclear. This study aimed to analyze whether high-CFD intake 2 h before ERCP can be safe and accelerate patients’ recovery.Methods::This prospective, multicenter, randomized controlled trial involved 15 tertiary ERCP centers. A total of 1330 patients were randomized into CFD group ( n = 665) and fasting group ( n = 665). The CFD group received 400 mL of maltodextrin orally 2 h before ERCP, while the control group abstained from food/water overnight (>6 h) before ERCP. All ERCP procedures were performed using deep sedation with intravenous propofol. The investigators were blinded but not the patients. The primary outcomes included postoperative fatigue and abdominal pain score, and the secondary outcomes included complications and changes in metabolic indicators. The outcomes were analyzed according to a modified intention-to-treat principle. Results::The post-ERCP fatigue scores were significantly lower at 4 h (4.1 ± 2.6 vs. 4.8 ± 2.8, t = 4.23, P <0.001) and 20 h (2.4 ± 2.1 vs. 3.4 ± 2.4, t= 7.94, P <0.001) in the CFD group, with least-squares mean differences of 0.48 (95% confidence interval [CI]: 0.26–0.71, P <0.001) and 0.76 (95% CI: 0.57–0.95, P <0.001), respectively. The 4-h pain scores (2.1 ± 1.7 vs. 2.2 ± 1.7, t = 2.60, P = 0.009, with a least-squares mean difference of 0.21 [95% CI: 0.05–0.37]) and positive urine ketone levels (7.7% [39/509] vs. 15.4% [82/533], χ2 = 15.13, P <0.001) were lower in the CFD group. The CFD group had significantly less cholangitis (2.1% [13/634] vs. 4.0% [26/658], χ2 = 3.99, P = 0.046) but not pancreatitis (5.5% [35/634] vs. 6.5% [43/658], χ2 = 0.59, P = 0.444). Subgroup analysis revealed that CFD reduced the incidence of complications in patients with native papilla (odds ratio [OR]: 0.61, 95% CI: 0.39–0.95, P = 0.028) in the multivariable models. Conclusion::Ingesting 400 mL of CFD 2 h before ERCP is safe, with a reduction in post-ERCP fatigue, abdominal pain, and cholangitis during recovery.Trail Registration::ClinicalTrials.gov, No. NCT03075280.

Objective To screen and verify the genes that play key role in the occurrence and development of esophageal cancer by u-sing bioinformatics and real-time fluorescence quantitative PCR(qRT-PCR)methods to find new markers for diagnosis of esophageal cancer(ESCA).Methods Using the TCGA database and Wayne plot analysis,the cross genes between the differentially expressed genes of ESCA and the genes which have the most significant impacts on disease-free survival(DFS)rate in esophageal cancer patients were preliminarily identified.Following conducting protein-protein interaction(PPI)network analysis on the overlapping genes,GO and KEGG functional analysis was performed to screen the potential key genes as the diagnostic markers of esophageal cancer.qRT-PCR was used to quantitatively analyze the expression of mRNA of the key gene in peripheral blood.Statistical analysis was con-ducted based on the clinico-pathological characteristics of the patients to determine its potential value as a new diagnostic marker for e-sophageal cancer.Results After overlapping of differentially expressed genes of ESCA and disease-free survival genes in the TCGA database,39 upregulated genes and 20 downregulated genes were found to be differentially expressed,all of which affected disease-free survival rate.After conducting PPI network analysis,15 upregulated genes with core interactions were identified,and the downregulat-ed genes did not form any interaction network.Further enrichment analysis of these 15 core interacting genes through GO and KEGG,revealed that fibronectin 1(FN1)may be a potential biomarker for ESCA diagnosis.The qRT-PCR results showed that compared with the healthy control group,the mRNA expression level of FN1 in the peripheral blood of esophageal cancer patients was significantly ele-vated.After analyzing the clinical characteristics of patients,it was found that the patients with poor differentiation and high clinico-pathological staging had significantly increased peripheral blood FN1 mRNA levels.The model with FN1 mRNA expression levels can distinguish esophageal cancer patients from healthy individuals.Conclusion FN1 mRNA may be a potential non-invasive diagnostic biomarker for esophageal cancer.

In the research on cancer theranostics, most environment-sensitive drug delivery systems can only achieve unidirectional and irreversible responsive changes under pathological conditions, thereby improving the targeting effect and drug release performance of the delivery system. However, such irreversible changes pose potential safety hazards when the dynamically distributed delivery system returns to the blood circulation or transports to the normal physiological environment. Intelligent reversible drug delivery systems can respond to normal physiological and pathological microenvironments to achieve bidirectional and reversible structural changes. This feature will help to precisely control the drug release of the delivery system, prolong the blood circulation time, improve the targeting efficiency, and avoid the potential safety hazards of the irreversible drug delivery system. In this review, we describe the research progress of intelligent reversible drug delivery system from two main aspects: controlled drug release and prolonged blood circulation time/enhanced cellular internalization of drug.

Malignant tumor is a major disease affecting human health. The nano-delivery system itself has a unique size effect and it can achieve tumor-targeted distribution of drug molecules, improve the therapeutic effect, and reduce the toxic and side effects on normal tissues and cells after functional modification. Patient-derived xenografts (PDX) models can be established by transplanting patient-derived cancer cells or small tumor tissue into immunodeficient mice directly. Compared with the tumor cell line model, this model can preserve the key features of the primary tumor such as histomorphology, heterogeneity, and genetic abnormalities, and keep them stable between generations. PDX models are widely used in drug evaluation, target discovery and biomarker development, especially providing a reliable research platform for the diagnosis and treatment evaluation of nano-delivery systems. This review summarizes the application of several common cancer PDX models in the evaluation of nano-delivery systems, in order to provide references for researchers to perform related research.

This paper reported a case of severe COVID-19 in the recovery stage with acute lymphoblastic leukemia treated by integrated traditional Chinese and western medicine， with the intention of shedding light on the clinical diagnosis and treatment of similar conditions. The patient， who had acute lymphoblastic leukemia， developed COVID-19 infection during the bone marrow suppression period after chemotherapy. Treatment with western medicine was mainly anti-infection， symptomatic management， and supportive care. During the recovery stage， considering the patient's chemotherapy history and disease progression， the overall syndrome was identified as deficiency of both qi and yin and binding of phlegm and blood. Based on the “state-target” combined treatment strategy， herbal prescriptions were selected and modified to address the “deficiency state”， “disease target”， and “symptom target”. In addition to western medicine， the patient was administered with Shengmai Powder （生脉散） and Compound Zhebei Granules （复方浙贝颗粒） in its modifications to boost qi， nourish yin， and reinforce healthy qi， nourish and cool the blood， ultimately achieving satisfactory therapeutic effects.

Objective: To investigate the association between muscle mass and quality of life in adults in Shaanxi adults. Methods: The data in this analysis were part of the baseline survey of the Regional Ethnic Cohort Study in Northwest China from June 2018 to May 2019 in Shaanxi Province. The participants' quality of life, including physical component summary (PCS) and mental component summary (MCS), was assessed by the 12-Item Short Form Survey, and the Body Fat Determination System measured muscle mass. A logistic regression model with adjustment for confounding factors was established to analyze the association between muscle mass and quality of life in different genders. Further, sensitivity and subgroup analyses were conducted to explore its stability. Finally, a restricted cubic spline was employed to investigate the dose-response relationship between muscle mass and quality of life in different genders. Results: A total of 20 595 participants were included, with an average age of 55.0, and 33.4% were male. After controlling for potential confounders, compared with the Q₁ group, the risk of low PCS was reduced by 20.6% (OR=0.794, 95%CI: 0.681-0.925) and the risk of low MCS was lower reduced by 20.1% (OR=0.799, 95%CI: 0.689-0.926) in female Q₅ groups. Compared with the Q₁ group, the risk of low PCS was reduced by 24.4% (OR=0.756, 95%CI: 0.644-0.888) in the male Q₂ group. However, no significant association between muscle mass and MCS in males has been found. In females, restricted cubic spline analysis showed a significant linear dose-response relationship between muscle mass and PCS and MCS. Conclusions: There is a positive association between muscle mass and quality of life in Shaanxi adults, especially females. With the increase in muscle mass, the physical and mental functions of the population continue to improve.
Humans ; Female ; Adult ; Male ; Quality of Life ; Cohort Studies ; Adipose Tissue ; China ; Muscles

Objective: To develop a multi-classification orthodontic image recognition system using the SqueezeNet deep learning model for automatic classification of orthodontic image data. Methods: A total of 35 000 clinical orthodontic images were collected in the Department of Orthodontics, Capital Medical University School of Stomatology, from October to November 2020 and June to July 2021. The images were from 490 orthodontic patients with a male-to-female ratio of 49∶51 and the age range of 4 to 45 years. After data cleaning based on inclusion and exclusion criteria, the final image dataset included 17 453 face images (frontal, smiling, 90° right, 90° left, 45° right, and 45° left), 8 026 intraoral images [frontal occlusion, right occlusion, left occlusion, upper occlusal view (original and flipped), lower occlusal view (original and flipped) and coverage of occlusal relationship], 4 115 X-ray images [lateral skull X-ray from the left side, lateral skull X-ray from the right side, frontal skull X-ray, cone-beam CT (CBCT), and wrist bone X-ray] and 684 other non-orthodontic images. A labeling team composed of orthodontic doctoral students, associate professors, and professors used image labeling tools to classify the orthodontic images into 20 categories, including 6 face image categories, 8 intraoral image categories, 5 X-ray image categories, and other images. The data for each label were randomly divided into training, validation, and testing sets in an 8∶1∶1 ratio using the random function in the Python programming language. The improved SqueezeNet deep learning model was used for training, and 13 000 natural images from the ImageNet open-source dataset were used as additional non-orthodontic images for algorithm optimization of anomaly data processing. A multi-classification orthodontic image recognition system based on deep learning models was constructed. The accuracy of the orthodontic image classification was evaluated using precision, recall, F1 score, and confusion matrix based on the prediction results of the test set. The reliability of the model's image classification judgment logic was verified using the gradient-weighted class activation mapping (Grad-CAM) method to generate heat maps. Results: After data cleaning and labeling, a total of 30 278 orthodontic images were included in the dataset. The test set classification results showed that the precision, recall, and F1 scores of most classification labels were 100%, with only 5 misclassified images out of 3 047, resulting in a system accuracy of 99.84%(3 042/3 047). The precision of anomaly data processing was 100% (10 500/10 500). The heat map showed that the judgment basis of the SqueezeNet deep learning model in the image classification process was basically consistent with that of humans. Conclusions: This study developed a multi-classification orthodontic image recognition system for automatic classification of 20 types of orthodontic images based on the improved SqueezeNet deep learning model. The system exhibitted good accuracy in orthodontic image classification.
Humans ; Male ; Female ; Child, Preschool ; Child ; Adolescent ; Young Adult ; Adult ; Middle Aged ; Deep Learning ; Reproducibility of Results ; Radiography ; Algorithms ; Cone-Beam Computed Tomography