Neutralizing antibodies have been designed to specifically target and bind to the receptor binding domain (RBD) of spike (S) protein to block severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus from attaching to angiotensin converting enzyme 2 (ACE2). This study reports a distinctive nanobody, designated as VHH21, that directly catalyzes the S-trimer into an irreversible transition state through postfusion conformational changes. Derived from camels immunized with multiple antigens, a set of nanobodies with high affinity for the S1 protein displays abilities to neutralize pseudovirion infections with a broad resistance to variants of concern of SARS-CoV-2, including SARS-CoV and BatRaTG13. Importantly, a super-resolution screening and analysis platform based on visual fluorescence probes was designed and applied to monitor single proteins and protein subunits. A spontaneously occurring dimeric form of VHH21 was obtained to rapidly destroy the S-trimer. Structural analysis via cryogenic electron microscopy revealed that VHH21 targets specific conserved epitopes on the S protein, distinct from the ACE2 binding site on the RBD, which destabilizes the fusion process. This research highlights the potential of VHH21 as an abzyme-like nanobody (nanoabzyme) possessing broad-spectrum binding capabilities and highly effective anti-viral properties and offers a promising strategy for combating coronavirus outbreaks.
Single-Domain Antibodies/immunology* ; Spike Glycoprotein, Coronavirus/metabolism* ; SARS-CoV-2/immunology* ; Animals ; Humans ; Antibodies, Neutralizing/immunology* ; Camelus ; COVID-19/immunology* ; Antibodies, Viral/immunology* ; Angiotensin-Converting Enzyme 2

Objective This study aimed to explore the effect of pituitary tumor-transforming gene 1(PTT-G1)on the invasion and proliferation of oral squamous cell carcinoma(OSCC)cell lines under the action of miR-362-3p.Methods The bioinformatics online database was used to query the expression of PTTG1 in head and neck squamous cell carcinoma(HNSCC).The expression of PTTG1 in the Cal-27,HN-30,and HOK cell lines was detected by Western blot.A wound-healing assay was used to determine the effect of PTTG1 on the migration ability of the OSCC cells.The Transwell assay was used to examine the changes in cell-invasion ability.5-ethynyl-2'-deoxyuridine(EdU)cell-proliferation assay was used to detect changes in cell-proliferation ability.Bioinformatics approach predicted the upstream miRNA of PTTG1.The targeting relationship between miR-362-3p and PTTG1 was examined by the dual luciferase assay,and quantitative real-time polymerase chain reaction(qRT-PCR)was used to determine the expression of miRNA in OSCC tissues.Results The ENCORI database showed that PTTG1 expression was up-regulated in OSCC tissues.Western blot confirmed that PTTG1 expression was up-regulated in Cal-27 and HN-30 cells than HOK cells.PTTG1 knockout can inhibit the migration,invasion,and prolif-eration of Cal-27 and HN-30 cells(P<0.05).Bioinformatics prediction websites predicted that the upstream miRNA of PTTG1 was miR-362-3p,and PTTG1 can bind to miR-362-3p.Results of qRT-PCR showed that miR-362-3p expression was downregulated in OSCC tissues compared with normal tissue(P<0.05).Transwell and EdU experiments confirmed that miR-362-3p knockdown can promote the invasion and proliferation of Cal-27 and HN-30 after PTTG1 knockdown.Conclusion miR-362-3p can inhibit the invasion and proliferation of Cal-27 and HN-30 cells by targeting PTTG1.

OBJECTIVE: Antiretroviral drugs covered by medical insurance have been gradually used by people living with human immunodeficiency virus (PLWH) in recent years in China. This study aimed to analyze their willingness to pay (WTP) for antiretroviral drugs. METHODS: A mixed-methods study design involving a cross-sectional survey and in-depth interviews was conducted. A cross-sectional survey was performed to collect data on the general characteristics, economic status, antiretroviral therapy (ART) status, and WTP of PLWH in 18 Chinese cities from August 2022 to February 2023. Multivariate logistic regression was used to analyze the factors associated with WTP. Representatives of PLWH were interviewed via in-depth interviews, and the data were thematically analyzed. RESULTS: Among the 941 PLWH, 271 (28.80%) were willing to pay for antiretroviral drugs covered by medical insurance. For basic medical insurance for urban and rural residents, PLWH with the following characteristics were more willing to pay: an educational level of senior high school or technical secondary school, having an undergraduate degree or higher, frequently working away from their hometowns, and homosexual transmission. Off-farm workers and recipients of government medical aid were more unwilling to pay. For basic medical insurance for urban employees, PLWH with the following characteristics were more willing to pay: frequently working away from their hometowns; homosexual transmission; personal annual income ≥ 100,000 CNY; and adverse events of antiretroviral drugs. The main reasons for PLWH's WTP for antiretroviral drugs covered by medical insurance were that the drugs had fewer adverse events and were easier to administer. The main reasons for PLWH's unwillingness to pay were financial difficulties and privacy concerns. CONCLUSION Nearly one-third of PLWH are willing to pay for antiretroviral drugs covered by medical insurance. In the future, PLWH with a high WTP can be guided to use these drugs.
Humans ; HIV Infections/economics* ; China ; Male ; Female ; Adult ; Cross-Sectional Studies ; Middle Aged ; Anti-Retroviral Agents/economics* ; Cities ; Insurance, Health/economics* ; Young Adult

Nitrate is the main form of inorganic nitrogen that crop absorbs, and nitrate transporter 2 (NRT2) is a high affinity transporter using nitrate as a specific substrate. When the available nitrate is limited, the high affinity transport systems are activated and play an important role in the process of nitrate absorption and transport. Most NRT2 cannot transport nitrates alone and require the assistance of a helper protein belonging to nitrate assimilation related family (NAR2) to complete the absorption or transport of nitrates. Crop nitrogen utilization efficiency is affected by environmental conditions, and there are differences between varieties, so it is of great significance to develop varieties with high nitrogen utilization efficiency. Sorghum bicolor has high stress tolerance and is more efficient in soil nitrogen uptake and utilization. The S. bicolor genome database was scanned to systematically analyze the gene structure, chromosomal localization, physicochemical properties, secondary structure and transmembrane domain, signal peptide and subcellular localization, promoter region cis-acting elements, phylogenetic evolution, single nucleotide polymorphism (SNP) recognition and annotation, and selection pressure of the gene family members. Through bioinformatics analysis, 5 NRT2 gene members (designated as SbNRT2-1a, SbNRT2-1b, SbNRT2-2, SbNRT2-3, and SbNRT2-4) and 2 NAR2 gene members (designated as SbNRT3-1 and SbNRT3-2) were identified, the number of which was less than that of foxtail millet. SbNRT2/3 were distributed on 3 chromosomes, and could be divided into four subfamilies. The genetic structure of the same subfamilies was highly similar. The average value of SbNRT2/3 hydrophilicity was positive, indicating that they were all hydrophobic proteins, whereas α-helix and random coil accounted for more than 70% of the total secondary structure. Subcellular localization occurred on plasma membrane, where SbNRT2 proteins did not contain signal peptides, but SbNRT3 proteins contained signal peptides. Further analysis revealed that the number of transmembrane domains of the SbNRT2s family members was greater than 10, while that of the SbNRT3s were 2. There was a close collinearity between NRT2/3s of S. bicolor and Zea mays. Protein domains analysis showed the presence of MFS_1 and NAR2 protein domains, which supported executing high affinity nitrate transport. Phylogenetic tree analysis showed that SbNRT2/3 were more closely related to those of Z. mays and Setaria italic. Analysis of gene promoter cis-acting elements indicated that the promoter region of SbNRT2/3 had several plant hormones and stress response elements, which might respond to growth and environmental cues. Gene expression heat map showed that SbNRT2-3 and SbNRT3-1 were induced by nitrate in the root and stem, respectively, and SbNRT2-4 and SbNRT2-3 were induced by low nitrogen in the root and stem. Non-synonymous SNP variants were found in SbNRT2-4 and SbNRT2-1a. Selection pressure analysis showed that the SbNRT2/3 were subject to purification and selection during evolution. The expression of SbNRT2/3 gene and the effect of aphid infection were consistent with the expression analysis results of genes in different tissues, and SbNRT2-1b and SbNRT3-1 were significantly expressed in the roots of aphid lines 5-27sug, and the expression levels of SbNRT2-3, SbNRT2-4 and SbNRT3-2 were significantly reduced in sorghum aphid infested leaves. Overall, genome-wide identification, expression and DNA variation analysis of NRT2/3 gene family of Sorghum bicolor provided a basis for elucidating the high efficiency of sorghum in nitrogen utilization.
Nitrate Transporters ; Nitrates/metabolism* ; Sorghum/metabolism* ; Anion Transport Proteins/metabolism* ; Phylogeny ; Protein Sorting Signals/genetics* ; Nitrogen/metabolism* ; DNA ; Gene Expression Regulation, Plant ; Plant Proteins/metabolism*

Objective:To assess the effectiveness of a model created using clinical features and preoperative chest CT imaging features in predicting the chronic obstructive pulmonary disease (COPD) among patients diagnosed with lung cancer.Methods:A retrospective analysis was conducted on clinical (age, gender, smoking history, smoking index, etc.) and imaging (lesion size, location, density, lobulation sign, etc.) data from 444 lung cancer patients confirmed by pathology at the Second Affiliated Hospital of Naval Medical University between June 2014 and March 2021. These patients were randomly divided into a training set (310 patients) and an internal test set (134 patients) using a 7∶3 ratio through the random function in Python. Based on the results of pulmonary function tests, the patients were further categorized into two groups: lung cancer combined with COPD and lung cancer non-COPD. Initially, univariate analysis was performed to identify statistically significant differences in clinical characteristics between the two groups. The variables showing significance were then included in the logistic regression analysis to determine the independent factors predicting lung cancer combined with COPD, thereby constructing the clinical model. The image features underwent a filtering process using the minimum absolute value convergence and selection operator. The reliability of these features was assessed through leave-P groups-out cross-validation repeated five times. Subsequently, a radiological model was developed. Finally, a combined model was established by combining the radiological signature with the clinical features. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) curves were plotted to evaluate the predictive capability and clinical applicability of the model. The area under the curve (AUC) for each model in predicting lung cancer combined with COPD was compared using the DeLong test.Results:In the training set, there were 182 cases in the lung cancer combined with COPD group and 128 cases in the lung cancer non-COPD group. The combined model demonstrated an AUC of 0.89 for predicting lung cancer combined with COPD, while the clinical model achieved an AUC of 0.82 and the radiological model had an AUC of 0.85. In the test set, there were 78 cases in the lung cancer combined with COPD group and 56 cases in the lung cancer non-COPD group. The combined model yielded an AUC of 0.85 for predicting lung cancer combined with COPD, compared to 0.77 for the clinical model and 0.83 for the radiological model. The difference in AUC between the radiological model and the clinical model was not statistically significant ( Z=1.40, P=0.163). However, there were statistically significant differences in the AUC values between the combined model and the clinical model ( Z=-4.01, P=0.010), as well as between the combined model and the radiological model ( Z=-2.57, P<0.001). DCA showed the maximum net benifit of the combined model. Conclusion:The developed synthetic diagnostic combined model, incorporating both radiological signature and clinical features, demonstrates the ability to predict COPD in patients with lung cancer.

Objective:To explore the differences of functional small airway and pulmonary vascular parameters in chronic obstructive pulmonary disease (COPD) of different imaging phenotypes.Methods:One hundred and thirty COPD patients underwent biphasic CT scanning in Shanghai Changzheng Hospital from August 2018 to August 2020 were analyzed retrospectively. The patients were classified into three phenotypes based on the presence of emphysema and bronchial wall thickening on CT images. Phenotype A: no emphysema or mild emphysema, with or without bronchial wall thickening; Phenotype E: obvious emphysema without bronchial wall thickening; phenotype M: significant emphysema and bronchial wall thickening were present. Parametric response map (PRM) and pulmonary vascular parameters were quantitatively measured at the whole lung level. PRM parameters included the volume of emphysema (PRMV Emphysema), the volume of functional small airway (PRMV fSAD), the volume of normal pulmonary parenchyma (PRMV Normal) and its volume percentage (%). Pulmonary vascular parameters included the number of vessels (N) and cross-sectional area vessels<5 mm 2 (N -CSA<5) at 6, 9, 12, 15, 18 21, 24 mm distance from the pleura. ANOVA or Kruskal-Wallis H tests were used to compare the differences for PRM and pulmonary vascular parameters among the three phenotypes, and LSD or Bonferroni tests were used for multiple comparisons. Results:There were significant differences among the three phenotypes for PRMV fSAD, PRMV Emphysema, PRMV fSAD%, PRMV Emphysema%, and PRMV Normal% at the whole lung level ( P<0.05). PRMV Emphysema, PRMV Emphysema%, PRMV Fsad, PRMV fSAD% of phenotype A were lower than those of phenotype E and M ( P<0.001), while there was no significant difference for PRMV Emphysema, PRMV Emphysema%, PRMV fSAD, PRMV fSAD% between phenotype E and phenotype M ( P>0.05). There were significant differences in N and N -CSA<5 that 6 mm distance from the pleura among the three groups( P<0.05). Among them, N and N -CSA<5 that 6 mm distance from pleura in phenotype M were significantly lower than those in phenotype A( P<0.001,0.002); No significant differences was found in N between phenotype M and phenotype E( P>0.05), while there was significant differences in N -CSA<5 between phenotype M and phenotype E( P=0.034). Conclusion:Biphasic quantitative CT analysis can reflect the heterogeneity of the functional small airways and pulmonary vascular abnormality in COPD with different phenotypes, and provide objective evidence for individualized diagnosis and treatment.

Hepatitis D (HD) is a serious disease. Traditionally, it is believed that the infection with hepatitis D virus (HDV) is closely related to hepatitis B virus (HBV). Recently, scholars have found the evidence that transmission of HDV does not rely on HBV, and have opened up δ virus a new chapter in virus research. This article reviews the origin of HDV, life cycle of HDV, HDV related to HBV infection, HDV unrelated to HBV infection, HDV-like virus, and the problems and prospect.

Objective:To explore the predictive value of random forest regression model for pulmonary function test.Methods:From August 2018 to December 2019, 615 subjects who underwent screening for three major chest diseases in Shanghai Changzheng Hospital were analyzed retrospectively. According to the ratio of forced expiratory volume in the first second to forced vital capacity (FEV 1/FVC) and the percentage of forced expiratory volume in the first second to the predicted value (FEV 1%), the subjects were divided into normal group, high risk group and chronic obstructive pulmonary disease (COPD) group. The CT quantitative parameter of small airway was parameter response mapping (PRM) parameters, including lung volume, the volume of functional small airways disease (PRMV fSAD), the volume of emphysema (PRMV Emph), the volume of normal lung tissue (PRMV Normal), the volume of uncategorized lung tissue (PRMV Uncategorized) and the percentage of the latter four volumes to the whole lung (%). ANOVA or Kruskal Wallis H was used to test the differences of basic clinical characteristics (age, sex, height, body mass), pulmonary function parameters and small airway CT quantitative parameters among the three groups; Spearman test was used to evaluate the correlation between PRM parameters and pulmonary function parameters. Finally, a random forest regression model based on PRM combined with four basic clinical characteristics was constructed to predict lung function. Results:There were significant differences in the parameters of whole lung PRM among the three groups ( P<0.001). Quantitative CT parameters PRMV Emph, PRMV Emph%, and PRMV Normal% showed a moderate correlation with FEV 1/FVC ( P<0.001). Whole lung volume, PRMV Normal,PRMV Uncategorized and PRMV Uncategorized% were strongly or moderately positively correlated with FVC ( P<0.001), other PRM parameters were weakly or very weakly correlated with pulmonary function parameters. Based on the above parameters, a random forest model for predicting FEV 1/FVC and a random forest model for predicting FEV 1% were established. The random forest model for predicting FEV 1/FVC predicted FEV 1/FVC and actual value was R 2=0.864 in the training set and R 2=0.749 in the validation set. The random forest model for predicting FEV 1% predicted FEV 1% and the actual value in the training set was R 2=0.888, and the validation set was R 2=0.792. The sensitivity, specificity and accuracy of predicting FEV 1% random forest model for the classification of normal group from high-risk group were 0.85(34/40), 0.90(65/72) and 0.88(99/112), respectively; and the sensitivity, specificity and accuracy of predicting FEV 1/FVC random forest model for differentiating non COPD group from COPD group were 0.89(8/9), 1.00 (112/112) and 0.99(120/121), respectively. While the accuracy of two models combination for subclassification of COPD [global initiative for chronic obstructive lung disease (GOLD) Ⅰ, GOLDⅡ and GOLD Ⅲ+Ⅳ] was only 0.44. Conclusions:Small airway CT quantitative parameter PRM can distinguish the normal population, high-risk and COPD population. The comprehensive regression prediction model combined with clinical characteristics based on PRM parameter show good performance differentiating normal group from high risk group, and differentiating non-COPD group from COPD group. Therefore, one-stop CT scan can evaluate the functional small airway and PFT simultaneously.

Objective:To investigate the value of CT features in predicting visceral pleural invasion (VPI) in clinical stage ⅠA peripheral lung adenocarcinoma under the pleura.Methods:The CT signs of 274 patients with clinical stage ⅠA peripheral lung adenocarcinoma under the pleura diagnosed in Changzheng Hospital of Naval Medical University from January 2015 to November 2021 were retrospectively analyzed. According to the ratio of 6∶4, 164 patients collected from January 2015 to August 2019 were used as the training group, and 110 patients collected from August 2019 to November 2021 were used as the validation group. The maximum diameter of the tumor (T), the maximum diameter of the consolidation part (C), and the minimum distance between the lesion and the pleura (DLP) were quantitatively measured, and the proportion of the consolidation part was calculated (C/T ratio, CTR). The CT signs of the tumor were analyzed, such as the relationship between the tumor and the pleura classification, the presence of a bridge tag sign, the location of the lesion, density type, shape, margin, boundary and so on. Variables with significant difference in the univariate analysis were entered into multivariate logistic regression analysis to explore predictors for VPI, and a binary logistic regression model was established. The predictive performance of the model was analyzed by receiver operating characteristic curve in the training and validation group.Results:There were 121 cases with VPI and 153 cases without VPI among the 274 patients with lung adenocarcinoma. There were 79 cases with VPI and 85 cases without VPI in the training group. Univariate analysis found that the maximum diameter of the consolidation part, CTR, density type, spiculation sign, vascular cluster sign, relationship of tumor and pleura and bridge tag sign between patients with VPI and those without VPI were significantly different in the training group( P<0.05). Multivariate logistic regression analysis found the relationship between tumor and pleura [taking type Ⅰ as reference, type Ⅱ (OR=6.662, 95%CI 2.364-18.571, P<0.001), type Ⅲ (OR=34.488, 95%CI 8.923-133.294, P<0.001)] and vascular cluster sign (OR=4.257, 95%CI 1.334-13.581, P=0.014) were independent risk factors for VPI in the training group. The sensitivity, specifcity, and area under curve (AUC) for the logistic model in the training group were 62.03%, 89.41% and 0.826, respectively, using the optimal cutoff value of 0.504. The validation group obtained an sensitivity, specifcity, and AUC of 92.86%, 47.06%, and 0.713, respectively, using the optimal cutoff value of 0.449. Conclusion:The relationship between the tumor and the pleura and the vascular cluster sign in the CT features can help to predict visceral pleural invasion in the clinical stage ⅠA peripheral lung adenocarcinoma under the pleura.

Objective:To explore the application effect of "blended learning + flipped classroom" in public elective courses for medical students, and provide reference for the blended construction of related courses.Methods:Totally 229 medical students were selected as research participants, who were taught by "blended learning + flipped classroom". After the courses, the curriculum evaluation questionnaires and focus group interview were used to collect students' evaluation of this course. SPSS 22.0 statistical software was used to make descriptive statistics on the questionnaire data.Results:Totally 98.5% students preferred "blended learning + flipped classroom" teaching mode, and more than 93% students thought this teaching method could improve their learning interest, empathy, understanding and application of knowledge. The results of the qualitative survey extracted two themes, namely "improving learning autonomy" and "expanding comprehensive quality".Conclusion:Perfecting the "blended learning + flipped classroom" teaching mode of the medical public elective courses plays a positive role in improving the learning autonomy and comprehensive quality of medical students and optimizing the learning effect.