Immunotherapy has become a pivotal modality in clinical cancer treatment. However, its effectiveness is limited to a small subset of patients due to the low antigenicity, impaired innate response, and various adaptive immune resistance mechanisms of the tumor microenvironment (TME). Accumulating evidence reveals the critical roles of metal elements in shaping immunity against tumor progression and metastasis. The marriage of metalloimmunotherapy and nanotechnology further presents new opportunities to optimize the physicochemical and pharmacokinetic properties of metal ions in a precise spatiotemporal control manner. Several metallodrugs have demonstrated encouraging immunotherapeutic potential in preliminary studies and are currently undergoing clinical trials at different stages, yet challenges persist in scaling up production and addressing long-term biosafety concerns. This review delineates how metal materials modulate biological activities across diverse cell types to orchestrate antitumor immunity. Moreover, it summarizes recent progress in smart drug delivery-release systems integrating metal elements, either as cargo or vehicles, to enhance antitumor immune responses. Finally, the review introduces current clinical applications of nanomedicines in metalloimmunotherapy and discusses potential challenges that impede its widespread translation into clinical practice.

In recent years, with the rapid advancement of digital technologies, the application of intelligent medicine in the field of endocrine and metabolic diseases has been continuously expanding. This review focuses on the latest progress in intelligent medicine within this domain, aiming to provide valuable insights and references for promoting the integration of intelligent medicine with the diagnosis and treatment of endocrine and metabolic diseases.

Objective The Bayesian joint model was applied to predict conversion from mild cognitive impairment(MCI)to Alzheimer's disease(AD),and to compare time effect in longitudinal outcomes,and functional forms for the longitudinal outcomes that are included in the survival model.Methods The longitudinal sub-model used generalized linear mixed models to model the trajectory of longitudinal neuropsychological tests changes pattern,and the survival sub-model adopted a Cox proportional risk model.The longitudinal sub-model utilized two forms of effects,t and t2,and the link structures of longitudinal sub-model and survival sub-model adopted three functional forms(updated value,slope,and area).The data were divided into training and validation sets according to 7∶3,the model parameters were estimated based on Bayesian algorithm,and the dynamic AUC was used to evaluate model prediction performance.Results There were 374(54.20％)of 690 patients with MCI progressed to AD during the follow-up period.In training set,the results of Bayesian joint model with a time effect of t and area effect of three longitudinal neuropsychological tests were optimal,with a mean dynamic AUC of 0.8336.The APOEε4 gene and a low functional activities questionary were risk factors for MCI conversion to AD.The dynamic AUCs of the joint model with the t time effects and area effect for longitudinal data were above 0.75 in the validation sets.Conclusion The application of multivariate Bayesian joint model to MCI risk prediction may provide a theoretical basis for individualized interventions for cognitive impairment and inform statistical methods for survival modeling of chronic diseases.

Objective The Bayesian joint model was applied to predict conversion from mild cognitive impairment(MCI)to Alzheimer's disease(AD),and to compare time effect in longitudinal outcomes,and functional forms for the longitudinal outcomes that are included in the survival model.Methods The longitudinal sub-model used generalized linear mixed models to model the trajectory of longitudinal neuropsychological tests changes pattern,and the survival sub-model adopted a Cox proportional risk model.The longitudinal sub-model utilized two forms of effects,t and t2,and the link structures of longitudinal sub-model and survival sub-model adopted three functional forms(updated value,slope,and area).The data were divided into training and validation sets according to 7∶3,the model parameters were estimated based on Bayesian algorithm,and the dynamic AUC was used to evaluate model prediction performance.Results There were 374(54.20％)of 690 patients with MCI progressed to AD during the follow-up period.In training set,the results of Bayesian joint model with a time effect of t and area effect of three longitudinal neuropsychological tests were optimal,with a mean dynamic AUC of 0.8336.The APOEε4 gene and a low functional activities questionary were risk factors for MCI conversion to AD.The dynamic AUCs of the joint model with the t time effects and area effect for longitudinal data were above 0.75 in the validation sets.Conclusion The application of multivariate Bayesian joint model to MCI risk prediction may provide a theoretical basis for individualized interventions for cognitive impairment and inform statistical methods for survival modeling of chronic diseases.

In recent years, with the rapid advancement of digital technologies, the application of intelligent medicine in the field of endocrine and metabolic diseases has been continuously expanding. This review focuses on the latest progress in intelligent medicine within this domain, aiming to provide valuable insights and references for promoting the integration of intelligent medicine with the diagnosis and treatment of endocrine and metabolic diseases.

Objective:To accurately ascertain the whole genome sequencing and the composition of open reading frames (ORFs) of non-replicating Tiantan strain of vaccinia virus (NTV) using next-generation long-read sequencing technology.Methods:NTV, obtained from our laboratory stock, was amplified and purified on chicken embryo fibroblast cells(CEFs), and the full-length genomic nucleic acid of NTV was extracted. The PacBio HiFi sequencing platform was utilized for de novo assembly to obtain the complete genomic sequence of NTV. Using a homology annotation strategy, we identified its ORF composition and compared it with known non-replicating vaccinia virus strains. Results:The total length of NTV′s genome was 171 729 bp, with a GC content of 33%. Its unique inverted terminal repeat (ITR) region comprised hairpin structures, two tandem repeat regions, and three non-repeat regions. NTV contained 166 ORFs, with major differences observed in the ITR and its surrounding regions when compared to MVA-BN and NYVAC. These three strains shared a common set of 138 ORFs. NTV encoded six unique ORFs related to virus evasion of host antiviral response.Conclusions:This study accurately determines the whole genome sequencing and ORFs composition of NTV, and reveals its similarities and differences with other replication-deficient vaccinia virus strains, which pave a way for the development and application of the next generation of monkeypox vaccines and novel viral vectors.

Objective:To analyze the effect of Iron deficiency anemia (IDA) and Black stain (BS) on the microbial community of dental plaque.Methods:A total of 136 preschool children aged 3 to 6 years old from 12 kindergartens in Shinan District and Shibei District of Qingdao City were investigated by using a cluster sampling method from April to May 2019. They were divided into two groups based on oral examination: the early childhood caries (ECC) group and the caries-free (CF) group. According to whether they had IDA and BS, they were further divided into four groups: the IDA with caries (IDA-ECC) group, the non-IDA with caries (NIDA-ECC) group, the BS without caries (BS-CF) group and the non-BS without caries (NBS-CF) group. The gingival plaque of the study subjects was collected. The 16S rRNA gene was sequenced by using Illumina MiSeq high-throughput sequencing technology. The composition, community structure and different bacteria genera of the microbial communities between the groups were compared and analyzed. Potential biomarkers within each group were further identified by linear discriminant analysis of effect size (LEfSe).Results:The 136 children were aged (5.11±0.87) years old, with 80 boys (58.82%). There were statistically significant differences in the microbial composition, structure and function of oral plaque between the ECC and CF groups ( P<0.05). There were statistically significant differences in the microbial richness and diversity of oral plaque between the IDA-ECC and NIDA-ECC groups ( P<0.05). There was no significant difference in microbial diversity index between the BS-CF and NBS-CF groups ( P>0.05). The LEfSe analysis results showed that 41, 31 and 9 taxa with different relative abundance were identified between the ECC and CF groups, IDA-ECC and NIDA-ECC groups, and BS-CF and NBS-CF groups, respectively. Conclusion:IDA and BS have an effect on the microecological diversity and microbial community function of oral plaque in young children with early childhood caries.

Purpose: Total neoadjuvant therapy (TNT) is becoming the standard of care for locally advanced rectal cancer. However, surgery is deferred for months after completion, which may lead to fibrosis and increased surgical difficulty. The aim of this study was to assess whether TNT (TNT-RAPIDO) is associated with increased difficulty of total mesorectal excision (TME) compared with long-course chemoradiotherapy (LCRT) and upfront surgery. Methods: Twelve laparoscopic videos of low anterior resection with TME for rectal cancer were prospectively collected from January 2020 to October 2021, with 4 videos in each arm. Seven colorectal surgeons assessed the videos independently, graded the difficulty of TME using a visual analog scale and attempted to identify which category the videos belonged to. Results: The median age was 67 years, and 10 patients were male. The median interval to surgery from radiotherapy was 13 weeks in the LCRT group and 24 weeks in the TNT-RAPIDO group. There was no significant difference in the visual analog scale for difficulty in TME between the 3 groups (LCRT, 3.2; TNT-RAPIDO, 4.6; upfront, 4.1; P=0.12). A subgroup analysis showed similar difficulty between groups (LCRT 3.2 vs. TNT-RAPIDO 4.6, P=0.05; TNT-RAPIDO 4.6 vs. upfront 4.1, P=0.54). During video assessments, surgeons correctly identified the prior treatment modality in 42% of the cases. TNT-RAPIDO videos had the highest recognition rate (71%), significantly outperforming both LCRT (29%) and upfront surgery (25%, P=0.01). Conclusion TNT does not appear to increase the surgical difficulty of TME.

Objective:To analyze the effect of Iron deficiency anemia (IDA) and Black stain (BS) on the microbial community of dental plaque.Methods:A total of 136 preschool children aged 3 to 6 years old from 12 kindergartens in Shinan District and Shibei District of Qingdao City were investigated by using a cluster sampling method from April to May 2019. They were divided into two groups based on oral examination: the early childhood caries (ECC) group and the caries-free (CF) group. According to whether they had IDA and BS, they were further divided into four groups: the IDA with caries (IDA-ECC) group, the non-IDA with caries (NIDA-ECC) group, the BS without caries (BS-CF) group and the non-BS without caries (NBS-CF) group. The gingival plaque of the study subjects was collected. The 16S rRNA gene was sequenced by using Illumina MiSeq high-throughput sequencing technology. The composition, community structure and different bacteria genera of the microbial communities between the groups were compared and analyzed. Potential biomarkers within each group were further identified by linear discriminant analysis of effect size (LEfSe).Results:The 136 children were aged (5.11±0.87) years old, with 80 boys (58.82%). There were statistically significant differences in the microbial composition, structure and function of oral plaque between the ECC and CF groups ( P<0.05). There were statistically significant differences in the microbial richness and diversity of oral plaque between the IDA-ECC and NIDA-ECC groups ( P<0.05). There was no significant difference in microbial diversity index between the BS-CF and NBS-CF groups ( P>0.05). The LEfSe analysis results showed that 41, 31 and 9 taxa with different relative abundance were identified between the ECC and CF groups, IDA-ECC and NIDA-ECC groups, and BS-CF and NBS-CF groups, respectively. Conclusion:IDA and BS have an effect on the microecological diversity and microbial community function of oral plaque in young children with early childhood caries.

Humans ; COVID-19 ; Neoplasms/complications* ; Lung Diseases ; Medical Oncology