Antibody (Ab) humanization is critical to reduce immunogenicity and enhance efficacy in the preclinical phase of the development of therapeutic Abs originated from animal models. Computational suggestions have long been desired, but available tools focused on immunogenicity calculation of whole Ab sequences and sequence segments, missing the individual residue sites. This study introduces Site-specific Immunogenicity for Therapeutic Antibody (SITA), a novel computational framework that predicts B-cell immunogenicity score for not only the overall antibody, but also individual residues, based on a comprehensive set of amino acid descriptors characterizing physicochemical and spatial features for antibody structures. A transfer-learning-inspired framework was purposely adopted to overcome the scarcity of Ab-Ab structural complexes. On an independent testing dataset derived from 13 Ab-Ab structural complexes, SITA successfully predicted the epitope sites for Ab-Ab structures with a receiver operating characteristic (ROC)-area unver the ROC curve (AUC) of 0.85 and a precision-recall (PR)-AUC of 0.305 at the residue level. Furthermore, the SITA score can significantly distinguish immunogenicity levels of whole human Abs, therapeutic Abs and non-human-derived Abs. More importantly, analysis of an additional 25 therapeutic Abs revealed that over 70% of them were detected with decreased immunogenicity after modification compared to their parent variants. Among these, nearly 66% Abs successfully identified actual modification sites from the top five sites with the highest SITA scores, suggesting the ability of SITA scores for guide the humanization of antibody. Overall, these findings highlight the potential of SITA in optimizing immunogenicity assessments during the process of therapeutic antibody design.

Antibody humanization is critical to reduce immunogenicity and enhance efficacy in the preclinical phase of the development of therapeutic antibodies originated from animal models.Computational suggestions have long been desired,but available tools focused on immunogenicity calculation of whole antibody sequences and sequence segments,missing the individual residue sites.This study introduces Site-specific Immunogenicity for Therapeutic Antibody(SITA),a novel computational framework that predicts B-cell immunogenicity score for not only the overall antibody,but also individual residues,based on a comprehensive set of amino acid descriptors characterizing physicochemical and spatial features for antibody structures.A transfer-learning-inspired framework was purposely adopted to overcome the scarcity of Antibody-Antibody structural complexes.On an independent testing dataset derived from 13 Antibody-Antibody structural complexes,SITA successfully predicted the epitope sites for Antibody-Antibody structures with a receiver operating characteristic(ROC)-area unver the ROC curve(AUC)of 0.85 and a precision-recall(PR)-AUC of 0.305 at the residue level.Furthermore,the SITA score can significantly distinguish immunogenicity levels of whole human antibodies,therapeutic antibodies and non-human-derived antibodies.More importantly,analysis of an additional 25 thera-peutic antibodies revealed that over 70％of them were detected with decreased immunogenicity after modification compared to their parent variants.Among these,nearly 66％antibodies successfully iden-tified actual modification sites from the top five sites with the highest SITA scores,suggesting the ability of SITA scores for guide the humanization of antibody.Overall,these findings highlight the potential of SITA in optimizing immunogenicity assessments during the process of therapeutic antibody design.

Objective:To analyze vaginal microecological changes in patients with vaginal infectious diseases and their correlation with human papillomavirus (HPV) infection.Methods:A case-control study was conducted involving 416 patients who visited the Gynecology Outpatient Department and the Cervical Disease Clinic at Yongkang Maternity and Child Care Hospital between December 2022 and December 2023. All patients underwent testing for vaginal microecology and HPV to evaluate the prevalence of vaginal infectious diseases and HPV infection. Vaginal microecological indicators were compared between patients with vaginal infections and those without identifiable pathogenic bacterial dysbiosis. The indicators included microbial density, lactobacilli levels, pH, hydrogen peroxide levels, abnormal leukocyte esterase, and the grading of vaginal lactobacilli. Additionally, the HPV infection status was compared among patients with different vaginal microecological environments, and the correlation between vaginal infections and HPV infections was analyzed.Results:In a study involving 416 participants, 216 were diagnosed with vaginal infections, with an incidence rate of 51.92% (216/416). Among these cases, 118 were classified as a single infection, accounting for 54.63% (118/216), while 98 were identified as mixed infections, accounting for 45.37% (98/216). The rate of HPV infection among the 216 patients with vaginal infectious diseases was 37.04% (80/216). This rate was significantly higher than the 15.31% (30/196) observed in patients without identifiable pathogenic bacterial dysbiosis ( χ2 = 24.79, P < 0.001). Patients with vaginal infectious diseases also displayed elevated rates of abnormal lactobacilli levels, abnormal pH, abnormal leukocyte esterase, and abnormal lactobacilli grading, with rates of 59.26%, 86.57%, 72.69%, and 57.41%, respectively. In comparison, patients without identifiable pathogenic dysbiosis had rates of 31.12%, 18.88%, 51.53%, and 34.18%, respectively. All differences were statistically significant ( χ2 = 32.76, 86.83, 19.64, 22.28, all P < 0.001). Additionally, significant differences in HPV infection rates were observed among patients who tested positive for bacterial vaginosis, vulvovaginal candidiasis, and trichomoniasis when compared to those who tested negative ( χ2 = 12.46, 4.04, 6.14, P < 0.001, 0.044, 0.013). Both bacterial vaginosis and vulvovaginal candidiasis were recognized as high-risk factors for HPV infection ( OR = 4.039, 2.902, both P < 0.05). Conclusions:Vaginal infectious diseases are significantly linked to HPV infection, particularly bacterial vaginosis and vulvovaginal candidiasis. Analyzing the characteristics of the vaginal microbiota can enhance the clinical management of HPV infection.

Objective:To analyze vaginal microecological changes in patients with vaginal infectious diseases and their correlation with human papillomavirus (HPV) infection.Methods:A case-control study was conducted involving 416 patients who visited the Gynecology Outpatient Department and the Cervical Disease Clinic at Yongkang Maternity and Child Care Hospital between December 2022 and December 2023. All patients underwent testing for vaginal microecology and HPV to evaluate the prevalence of vaginal infectious diseases and HPV infection. Vaginal microecological indicators were compared between patients with vaginal infections and those without identifiable pathogenic bacterial dysbiosis. The indicators included microbial density, lactobacilli levels, pH, hydrogen peroxide levels, abnormal leukocyte esterase, and the grading of vaginal lactobacilli. Additionally, the HPV infection status was compared among patients with different vaginal microecological environments, and the correlation between vaginal infections and HPV infections was analyzed.Results:In a study involving 416 participants, 216 were diagnosed with vaginal infections, with an incidence rate of 51.92% (216/416). Among these cases, 118 were classified as a single infection, accounting for 54.63% (118/216), while 98 were identified as mixed infections, accounting for 45.37% (98/216). The rate of HPV infection among the 216 patients with vaginal infectious diseases was 37.04% (80/216). This rate was significantly higher than the 15.31% (30/196) observed in patients without identifiable pathogenic bacterial dysbiosis ( χ2 = 24.79, P < 0.001). Patients with vaginal infectious diseases also displayed elevated rates of abnormal lactobacilli levels, abnormal pH, abnormal leukocyte esterase, and abnormal lactobacilli grading, with rates of 59.26%, 86.57%, 72.69%, and 57.41%, respectively. In comparison, patients without identifiable pathogenic dysbiosis had rates of 31.12%, 18.88%, 51.53%, and 34.18%, respectively. All differences were statistically significant ( χ2 = 32.76, 86.83, 19.64, 22.28, all P < 0.001). Additionally, significant differences in HPV infection rates were observed among patients who tested positive for bacterial vaginosis, vulvovaginal candidiasis, and trichomoniasis when compared to those who tested negative ( χ2 = 12.46, 4.04, 6.14, P < 0.001, 0.044, 0.013). Both bacterial vaginosis and vulvovaginal candidiasis were recognized as high-risk factors for HPV infection ( OR = 4.039, 2.902, both P < 0.05). Conclusions:Vaginal infectious diseases are significantly linked to HPV infection, particularly bacterial vaginosis and vulvovaginal candidiasis. Analyzing the characteristics of the vaginal microbiota can enhance the clinical management of HPV infection.