Bovine rotavirus(BRV)is an important pathogen causing diarrhea in calves.To understand the genomic charac-teristics and genetic variations in bovine rotavirus,and to further enrich data on the biological characteristics of rotavirus,we aimed to amplify 11 gene segments of the isolated and cultured G6P[1]bovine rotavirus BLL strain,perform whole genome se-quencing,and analyze the molecular characteristics.MEGA7.0 and DNAMAN software were used for homology and typing a-nalysis,and the whole genome phylogenetic tree was constructed to analyze genetic evolution relationships.The complete geno-type of the BLL strain was G6-P[1]-I2-R2-C2-M2-A3-N2-T6-E2-H3.Phylogenetic analysis of the VP7 and VP4 genes of the BLL strain showed that the VP7 gene had the highest homology with RVA/Cow-wt/HB01/China/2021,and the VP4 gene of the BLL strain was in the same branch as RVA/Human-tc/ISR/Ro8059/1995.From the sequence alignment of VP8*amino acids,the sialic acid domain of the BLL strain was found to be similar to that in other P[1]strains,but different from those in other types of strains,except for residue 189,which was the same as that in Ro8059 but different from that in other strains.The results suggested that the BLL strain might potentially infect humans.Therefore,continued monitoring and study of the biological characteristics of this strain are necessary to provide more information and evidence supporting further research on the cross-species transmission of group A rotavirus in China.

Soy is a vital source of plant carbohydrates.However,it poses significant allergenic risks,particularly to young children and animals.Among the various proteins in soy,β-conglycinin,which con-stitutes approximately 30％of total soy carbohydrates,is a primary allergen.Undigested β-conglycinin can lead to intestinal damage by inhibiting cell growth,disrupting the cytoskeleton,and inducing apopto-sis.It can also enter the lymphatic and circulatory systems,triggering allergic reactions.Conventional ELISA methods for detecting β-conglycinin rely on polyclonal or monoclonal antibodies,which are limited by their large molecular weight,difficulty in accessing the protein core,and sensitivity to acidic and bas-ic conditions.To address these limitations,this study aimed to develop nanobodies(Nbs)against β-con-glycinin.Nbs,derived from the variable regions of heavy-chain antibodies found in camelids,have a mo-lecular weight approximately one-tenth that of conventional antibodies.They offer advantages such as small size,stable structure,high specificity,and strong affinity.A female alpacas was immunized five times using β-conglycinin,which showed a heavy chain antibody potency of 1∶16 000 by ELISA.Pe-ripheral blood lymphocytes were subsequently isolated and total RNA was extracted.The variable region of the heavy-chain antibody was amplified via PCR,and recombinant plasmids were constructed and transformed into the E.coli competency strain ER2738.The resulting library contained about 3.5×108 CFU/mL,which increased to 1.15×1012 PFU/mL after phage rescue,with a 100％Nbs gene insertion rate,indicating high diversity.Its Nbs phage output was significantly enriched by four rounds of solid-phase elution with an enrichment rate of 155.9.Four rounds of solid-phase panning yielded 35 positive clones,all of which shared the same amino acid sequence upon sequencing.The selected Nb was ex-pressed in a prokaryotic system,and its binding ability to β-conglycinin was confirmed using Western blotting and ELISA.The results demonstrated excellent specificity and affinity.This research lays the groundwork for developing a rapid and efficient detection method for β-conglycinin using Nbs,potentially enhancing food safety and allergen management.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

Enamel demineralization, the formation of white spot lesions, is a common issue in clinical orthodontic treatment. The appearance of white spot lesions not only affects the texture and health of dental hard tissues but also impacts the health and aesthetics of teeth after orthodontic treatment. The prevention, diagnosis, and treatment of white spot lesions that occur throughout the orthodontic treatment process involve multiple dental specialties. This expert consensus will focus on providing guiding opinions on the management and prevention of white spot lesions during orthodontic treatment, advocating for proactive prevention, early detection, timely treatment, scientific follow-up, and multidisciplinary management of white spot lesions throughout the orthodontic process, thereby maintaining the dental health of patients during orthodontic treatment.
Humans ; Consensus ; Dental Caries/etiology* ; Dental Enamel/pathology* ; Tooth Demineralization/etiology* ; Tooth Remineralization

Objective: To analyze the nucleic acid load of human parvovirus B19 in major commercially available blood products in China, including human albumin, human intravenous immunoglobulin, human rabies immunoglobulin and various coagulation factor products, aiming to provide evidence for improving blood product manufacturing processes and quality control of source plasma. Methods: A total of 98 batches of coagulation factor products were tested for human parvovirus B19 nucleic acid using real-time fluorescent quantitative PCR, including 42 batches of human prothrombin complex, 35 batches of human coagulation factor Ⅷ, and 21 batches of human fibrinogen. Additionally, 6 batches of human albumin, 6 batches of human intravenous immunoglobulin, and 38 batches of human rabies immunoglobulin were tested for human parvovirus B19 nucleic acid. Results: Human parvovirus B19 nucleic acid were undetectable in human albumin, human intravenous immunoglobulin and human rabies immunoglobulin. Among the 98 batches of coagulation factor products tested for human parvovirus B19 nucleic acid, B19 nucleic acid reactivity rate was 69.0% (29/42) for human prothrombin complex batches, but nucleic acid concentration were all significantly lower than 10 IU/mL. The reactivity rate of B19 nucleic acid in 35 batches of human coagulation factor Ⅷ was 48.6% (17/35), with nucleic acid concentration all below 10 IU/mL. The reactivity rate of B19 nucleic acid in 21 batches of human fibrinogen was 61.9% (13/21), with nucleic acid concentration all below 10 IU/mL. Conclusion: No human parvovirus B19 has been detected in human albumin, human intravenous immunoglobulin, or human rabies immunoglobulin. Human parvovirus B19 nucleic acid may exist in commercially available coagulation factor products, highlighting the need for enhanced screening of human parvovirus B19 nucleic acid in these products. It is also recommended that B19 viral nucleic acid testing be conducted on source plasma, particularly for coagulation factor products.

Objective: To analyze the nucleic acid load of human parvovirus B19 in major commercially available blood products in China, including human albumin, human intravenous immunoglobulin, human rabies immunoglobulin and various coagulation factor products, aiming to provide evidence for improving blood product manufacturing processes and quality control of source plasma. Methods: A total of 98 batches of coagulation factor products were tested for human parvovirus B19 nucleic acid using real-time fluorescent quantitative PCR, including 42 batches of human prothrombin complex, 35 batches of human coagulation factor Ⅷ, and 21 batches of human fibrinogen. Additionally, 6 batches of human albumin, 6 batches of human intravenous immunoglobulin, and 38 batches of human rabies immunoglobulin were tested for human parvovirus B19 nucleic acid. Results: Human parvovirus B19 nucleic acid were undetectable in human albumin, human intravenous immunoglobulin and human rabies immunoglobulin. Among the 98 batches of coagulation factor products tested for human parvovirus B19 nucleic acid, B19 nucleic acid reactivity rate was 69.0% (29/42) for human prothrombin complex batches, but nucleic acid concentration were all significantly lower than 10 IU/mL. The reactivity rate of B19 nucleic acid in 35 batches of human coagulation factor Ⅷ was 48.6% (17/35), with nucleic acid concentration all below 10 IU/mL. The reactivity rate of B19 nucleic acid in 21 batches of human fibrinogen was 61.9% (13/21), with nucleic acid concentration all below 10 IU/mL. Conclusion: No human parvovirus B19 has been detected in human albumin, human intravenous immunoglobulin, or human rabies immunoglobulin. Human parvovirus B19 nucleic acid may exist in commercially available coagulation factor products, highlighting the need for enhanced screening of human parvovirus B19 nucleic acid in these products. It is also recommended that B19 viral nucleic acid testing be conducted on source plasma, particularly for coagulation factor products.

Bovine rotavirus(BRV)is an important pathogen causing diarrhea in calves.To understand the genomic charac-teristics and genetic variations in bovine rotavirus,and to further enrich data on the biological characteristics of rotavirus,we aimed to amplify 11 gene segments of the isolated and cultured G6P[1]bovine rotavirus BLL strain,perform whole genome se-quencing,and analyze the molecular characteristics.MEGA7.0 and DNAMAN software were used for homology and typing a-nalysis,and the whole genome phylogenetic tree was constructed to analyze genetic evolution relationships.The complete geno-type of the BLL strain was G6-P[1]-I2-R2-C2-M2-A3-N2-T6-E2-H3.Phylogenetic analysis of the VP7 and VP4 genes of the BLL strain showed that the VP7 gene had the highest homology with RVA/Cow-wt/HB01/China/2021,and the VP4 gene of the BLL strain was in the same branch as RVA/Human-tc/ISR/Ro8059/1995.From the sequence alignment of VP8*amino acids,the sialic acid domain of the BLL strain was found to be similar to that in other P[1]strains,but different from those in other types of strains,except for residue 189,which was the same as that in Ro8059 but different from that in other strains.The results suggested that the BLL strain might potentially infect humans.Therefore,continued monitoring and study of the biological characteristics of this strain are necessary to provide more information and evidence supporting further research on the cross-species transmission of group A rotavirus in China.

Soy is a vital source of plant carbohydrates.However,it poses significant allergenic risks,particularly to young children and animals.Among the various proteins in soy,β-conglycinin,which con-stitutes approximately 30％of total soy carbohydrates,is a primary allergen.Undigested β-conglycinin can lead to intestinal damage by inhibiting cell growth,disrupting the cytoskeleton,and inducing apopto-sis.It can also enter the lymphatic and circulatory systems,triggering allergic reactions.Conventional ELISA methods for detecting β-conglycinin rely on polyclonal or monoclonal antibodies,which are limited by their large molecular weight,difficulty in accessing the protein core,and sensitivity to acidic and bas-ic conditions.To address these limitations,this study aimed to develop nanobodies(Nbs)against β-con-glycinin.Nbs,derived from the variable regions of heavy-chain antibodies found in camelids,have a mo-lecular weight approximately one-tenth that of conventional antibodies.They offer advantages such as small size,stable structure,high specificity,and strong affinity.A female alpacas was immunized five times using β-conglycinin,which showed a heavy chain antibody potency of 1∶16 000 by ELISA.Pe-ripheral blood lymphocytes were subsequently isolated and total RNA was extracted.The variable region of the heavy-chain antibody was amplified via PCR,and recombinant plasmids were constructed and transformed into the E.coli competency strain ER2738.The resulting library contained about 3.5×108 CFU/mL,which increased to 1.15×1012 PFU/mL after phage rescue,with a 100％Nbs gene insertion rate,indicating high diversity.Its Nbs phage output was significantly enriched by four rounds of solid-phase elution with an enrichment rate of 155.9.Four rounds of solid-phase panning yielded 35 positive clones,all of which shared the same amino acid sequence upon sequencing.The selected Nb was ex-pressed in a prokaryotic system,and its binding ability to β-conglycinin was confirmed using Western blotting and ELISA.The results demonstrated excellent specificity and affinity.This research lays the groundwork for developing a rapid and efficient detection method for β-conglycinin using Nbs,potentially enhancing food safety and allergen management.

To investigate the impact and underlying mechanism of NOP2/Sun RNA methyltransferase 2 (NSUN2) on gastric cancer progression, TCGA database was used and revealed a significant upregulation of NSUN2 expression in gastric cancer tissues. Western blot analysis revealed that NSUN2 was upregulated in gastric cancer cells compared with gastric mucosal epithelial cells. Colony formation assays demonstrated an enhanced colony-forming capacity in NSUN2-overexpressing cells. Furthermore, Transwell assays showed a marked increase in cell migration and invasion upon high NSUN2 expression. Moreover, TCGA database analysis suggested ARMC9 as a potential downstream target of NSUN2. Subsequently, MeRIP-qPCR analysis revealed that NSUN2 overexpression could increase m5C modification of ARMC9 mRNA, and reduce its degradation rate, thus enhancing protein expression. Additionally, ARMC9 overexpression augmented cellular colony formation and migratory and invasive capabilities. These findings indicate that NSUN2 promotes gastric cancer progression by elevating m5C modification of ARMC9 mRNA, increasing its stability and enhancing its expression, therefore, NSUN2 and ARMC9 may serve as potential therapeutic targets for gastric cancer.

ObjectiveThis study aims to develop and validate a novel multimodal predictive model， termed criss-cross network（CCNet）-directed graph neural network（DGNN）（CGN）， for accurate assessment of pulmonary nodule progression in high-risk individuals for lung cancer， by integrating longitudinal chest computed tomography（CT） imaging with both traditional Chinese and western clinical evaluation data. MethodsA cohort of 4 432 patients with pulmonary nodules was retrospectively analyzed. A twin CCNet was employed to extract spatiotemporal representations from paired sequential CT scans. Structured clinical assessment and imaging-derived features were encoded via a multilayer perceptron， and a similarity-based alignment strategy was adopted to harmonize multimodal imaging features across temporal dimensions. Subsequently， a DGNN was constructed to integrate heterogeneous features， where nodes represented modality-specific embeddings and edges denoted inter-modal information flow. Finally， model optimization was performed using a joint loss function combining cross-entropy and cosine similarity loss， facilitating robust classification of nodule progression status. ResultsThe proposed CGN model demonstrated superior predictive performance on the held-out test set， achieving an area under the receiver operating characteristic curve（AUC） of 0.830， accuracy of 0.843， sensitivity of 0.657， specificity of 0.712， Cohen's Kappa of 0.417， and F₁ score of 0.544. Compared with unimodal baselines， the CGN model yielded a 36%-48% relative improvement in AUC. Ablation studies revealed a 2%-22% increase in AUC when compared to simplified architectures lacking key components， substantiating the efficacy of the proposed multimodal fusion strategy and modular design. Incorporation of traditional Chinese medicine （TCM）-specific symptomatology led to an additional 5% improvement in AUC， underscoring the complementary value of integrating TCM and western clinical data. Through gradient-weighted activation mapping visualization analysis， it was found that the model's attention predominantly focused on nodule regions and effectively captured dynamic associations between clinical data and imaging-derived features. ConclusionThe CGN model， by synergistically combining cross-attention encoding with directed graph-based feature integration， enables effective alignment and fusion of heterogeneous multimodal data. The incorporation of both TCM and western clinical information facilitates complementary feature enrichment， thereby enhancing predictive accuracy for pulmonary nodule progression. This approach holds significant potential for supporting intelligent risk stratification and personalized surveillance strategies in lung cancer prevention.