Objective:To develop a deep learning model based on 3D super-resolution reconstruction technology and to analyze its feasibility and effectiveness in predicting paraglottic space invasion in hypopharyngeal cancer.Methods:A retrospective study was conducted involving 382 patients with hypopharyngeal squamous cell carcinoma treated at Qilu Hospital of Shandong University between January 2014 and December 2020. The cohort included 364 males and 18 females, with a mean age of 62±7 years. Patients were divided into a training set ( n=300) and a test set ( n=82) based on enrollment time. A generative adversarial network was used to perform 3D super-resolution reconstruction on contrast-enhanced CT images, improving spatial resolution by 16 times. A 2.5D deep learning strategy was employed to construct Resnet-NR and Resnet-SR models based on conventional and super-resolution images, respectively, to predict whether the paraglottic space was invaded. Model performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). A multi-reader multi-case study was conducted to assess the impact of the artificial intelligence (AI) model on clinicians′ diagnostic capabilities. Results:The super-resolution model Resnet-SR achieved the highest accuracy in both the training set (AUC=0.87, 95% CI: 0.84-0.90) and the test set (AUC=0.88, 95% CI: 0.81-0.96), significantly outperforming traditional clinical indicators (T stage, N stage, tumor diameter, and pathological differentiation degree) (AUC range: 0.55-0.70, all P<0.05). In comparison, the conventional-resolution model Resnet-NR achieved AUCs of 0.81 (95% CI: 0.77-0.84, P=0.005) and 0.80 (95% CI: 0.71-0.89, P=0.184) in the training and test sets, respectively. Using Resnet-SR to assist clinical decision-making improved the diagnostic accuracy of junior physicians (AUC=0.793 without AI assistance vs. AUC=0.871 with AI assistance, P=0.012) and significantly reduced diagnosis time for clinicians of all experience levels (86.5 s without AI assistance vs. 82.5 s with AI assistance, t=2.01, P=0.032). Conclusion:This study successfully develops a deep learning model based on 3D super-resolution reconstruction technology, which can assist in preoperative prediction of paraglottic space invasion in hypopharyngeal cancer. The AI-assisted tool improves diagnostic accuracy for junior physicians and enhances diagnostic efficiency for clinicians across all experience levels.

In this comprehensive review, we delve into the evolution of drug delivery systems in reproductive medicine with a focus on the emerging role of exosomes, a class of extracellular vesicles. Exosomes offer unique advantages in overcoming these challenges due to their inherent biocompatibility, stability, and ability to facilitate targeted delivery. This review provides a detailed examination of exosome biogenesis and their function in cellular communication, setting the stage for understanding their potential as drug delivery vehicles. We explore the mechanisms through which exosomes can be loaded with small molecule drugs and the benefits they offer over synthetic nanoparticles. The review highlights groundbreaking case studies that illustrate the successful application of exosome-mediated drug delivery in reproductive health, including enhancing fertility treatments, supporting gamete and embryo development, and facilitating maternal-fetal communication. This study aims to provide a precise understanding of how exosomal drug delivery can revolutionize treatments for reproductive health disorders, paving the way for future therapeutic applications. Lastly, we touch upon the promising therapeutic implications of exosomal delivery for proteins and genes, offering a window into future treatments for reproductive health disorders.

Background and Aims:In recent years,with the continuous progress of systemic therapy,hepatic arterial infusion chemotherapy(HAIC)combined with immune checkpoint inhibitors and anti-angiogenic agents has demonstrated significant efficacy in the treatment of advanced hepatocellular carcinoma(HCC).However,direct comparisons between different immunotherapeutic targets,such as PD-1 and PD-L1 inhibitors,in terms of clinical benefit and safety remain limited.This study aimed to compare the efficacy and safety of HAIC plus bevacizumab and sintilimab(HAIC-BP1)versus HAIC plus bevacizumab and atezolizumab(HAIC-BPL)in advanced HCC.Methods:A retrospective analysis was conducted on 88 patients with advanced HCC who received first-line HAIC-BP1or HAIC-BPL at Sun Yat-sen University Cancer Center between January 2020 and December 2022.Progression-free survival(PFS),overall survival(OS),objective response rate(ORR),disease control rate(DCR),and adverse events(AEs)were compared between the two groups.Cox regression analysis was performed to identify prognostic factors affecting PFS.Results:A total of 47 patients were included in the HAIC-BP1 group and 41 patients in the HAIC-BPL group,with no statistically significant differences in baseline characteristics between the two groups(all P>0.05).The ORR(59.6%vs.65.9%)and DCR(72.3%vs.80.5%)did not significantly differ between the HAIC-BP1 group and the HAIC-BPL group(both P>0.05).After a median follow-up of 16.3 months,there were no significant differences in median OS(21.3 months vs.22.4 months)or median PFS(6.7 months vs.6.2 months)between the HAIC-BP1 group and the HAIC-BPL group(both P>0.05).The incidence of AEs was similar,and no treatment-related deaths occurred.Multivariate Cox regression analysis identified tumor diameter>10 cm as an independent adverse prognostic factor for PFS(HR=0.48,95%CI=0.27-0.83,P=0.009).Conclusion:Both HAIC-BP1 and HAIC-BPL demonstrated comparable efficacy and favorable safety profiles as first-line treatment options for advanced HCC.Tumor diameter>10 cm was an independent unfavorable prognostic factor for PFS,underscoring the importance of patient stratification in clinical decision-making.

Objective:To develop a deep learning model based on 3D super-resolution reconstruction technology and to analyze its feasibility and effectiveness in predicting paraglottic space invasion in hypopharyngeal cancer.Methods:A retrospective study was conducted involving 382 patients with hypopharyngeal squamous cell carcinoma treated at Qilu Hospital of Shandong University between January 2014 and December 2020. The cohort included 364 males and 18 females, with a mean age of 62±7 years. Patients were divided into a training set ( n=300) and a test set ( n=82) based on enrollment time. A generative adversarial network was used to perform 3D super-resolution reconstruction on contrast-enhanced CT images, improving spatial resolution by 16 times. A 2.5D deep learning strategy was employed to construct Resnet-NR and Resnet-SR models based on conventional and super-resolution images, respectively, to predict whether the paraglottic space was invaded. Model performance was evaluated using receiver operating characteristic (ROC) curves and area under the curve (AUC). A multi-reader multi-case study was conducted to assess the impact of the artificial intelligence (AI) model on clinicians′ diagnostic capabilities. Results:The super-resolution model Resnet-SR achieved the highest accuracy in both the training set (AUC=0.87, 95% CI: 0.84-0.90) and the test set (AUC=0.88, 95% CI: 0.81-0.96), significantly outperforming traditional clinical indicators (T stage, N stage, tumor diameter, and pathological differentiation degree) (AUC range: 0.55-0.70, all P<0.05). In comparison, the conventional-resolution model Resnet-NR achieved AUCs of 0.81 (95% CI: 0.77-0.84, P=0.005) and 0.80 (95% CI: 0.71-0.89, P=0.184) in the training and test sets, respectively. Using Resnet-SR to assist clinical decision-making improved the diagnostic accuracy of junior physicians (AUC=0.793 without AI assistance vs. AUC=0.871 with AI assistance, P=0.012) and significantly reduced diagnosis time for clinicians of all experience levels (86.5 s without AI assistance vs. 82.5 s with AI assistance, t=2.01, P=0.032). Conclusion:This study successfully develops a deep learning model based on 3D super-resolution reconstruction technology, which can assist in preoperative prediction of paraglottic space invasion in hypopharyngeal cancer. The AI-assisted tool improves diagnostic accuracy for junior physicians and enhances diagnostic efficiency for clinicians across all experience levels.

Objective:To explore the effects of age and gender on the sagittal spinal-pelvic parameters during the natural aging process of healthy adults.Methods:A total of 647 Chinese healthy adults who underwent health check-ups at the Second Affiliated Hospital of Zhejiang University School of Medicine and Songyang County People's Hospital, from January 2017 to September 2024 were collected. There were 277 males and 370 females, aged 18-93 years. Anteroposterior and lateral X-ray films of the whole spine were taken to evaluate the spinal-pelvic sagittal morphology. The following parameters were measured: thoracic kyphosis (TK), lumbar lordosis(LL), sacral slope (SS), pelvic incidence (PI), pelvic tilt (PT), global tilt (GT), T 1-pelvic angle (TPA), sagittal vertical axis (SVA), thoracic Cobb angle (T-Cobb), lower end vertebra of thoracic Cobb angle (T-LEV), apex vertebra of thoracic Cobb angle (T-Apex), lumbar Cobb angle (L-Cobb). Compare the differences in spine-pelvis parameters among patients of different genders and age groups (in this study, the subjects were subdivided into the 18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80-93 years groups according to the age range). Results:The results showed that GT, SVA, TPA, and PT increased with age ( P<0.05). For males aged 18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80-93 years, PT values were 8.58°±6.47°, 9.60°±5.63°, 12.65°±7.13°, 11.00°±6.99°, 13.01°±8.63°, 15.77°±8.02°, and 18.47°±10.03° respectively; for females in the same age groups, the PT values were 8.44°±6.83°, 9.00°±6.44°, 11.84°±7.35°, 12.07°±7.51°, 15.44°±9.39°, 19.26°±8.28°, and 18.17°±9.43° respectively. For males in these age groups, the global tilt (GT) values were 6.37°±7.20°, 8.77°±6.51°, 10.38°±9.07°, 8.80°±7.49°, 10.80°±8.62°, 16.07°±10.42°, and 21.99°±12.65° respectively; for females, the GT values were 4.46°±8.09°, 5.96°±7.83°, 8.17°±6.88°, 9.41°±8.03°, 9.96°±1.39°, 17.89°±9.39°, and 19.55°±12.34° respectively. The sagittal vertical axis (SVA) values for males in the age groups were -7.94±25.57 mm, -2.98±25.69 mm, -4.63±20.90 mm, -6.43±32.81 mm, 7.85±43.39 mm, 36.49±53.89 mm, and 55.57±51.10 mm respectively; for females, they were -24.12±31.35 mm, -17.49±25.12 mm, -17.88±22.72 mm, -8.25±30.91 mm, 8.80±27.45 mm, 28.67±38.22 mm, and 23.23±35.19 mm respectively. For males, the thoracic pelvic angle (TPA) values across the age groups were 4.46°±5.94°, 6.05°±5.38°, 9.58°±9.35°, 7.52°±7.64°, 11.23°±9.59°, 16.32°±12.38°, and 18.49°±11.70° respectively; for females, the TPA values were 2.72°±6.88°, 3.68°±6.26°, 7.30°±6.11°, 7.44°±6.75°, 12.64°±9.79°, 19.08°±10.39°, and 16.79°±13.19° respectively. T-Cobb, T-LEV, and T-Apex increased slowly with age ( P<0.05). The pelvic incidence (PI) remained relatively constant in males ( P>0.05), while it increased slowly with age in females ( P<0.05). Conclusions:Sagittal anteversion of the spinal-pelvis increases with age. Gender differences are reflected in specific changes in the fluctuation amplitude of certain parameters (such as PI), and the fluctuations of indicators like T-Cobb, T-LEV, and T-Apex are closely related to the natural aging process of the spine.

Background and Aims:In recent years,with the continuous progress of systemic therapy,hepatic arterial infusion chemotherapy(HAIC)combined with immune checkpoint inhibitors and anti-angiogenic agents has demonstrated significant efficacy in the treatment of advanced hepatocellular carcinoma(HCC).However,direct comparisons between different immunotherapeutic targets,such as PD-1 and PD-L1 inhibitors,in terms of clinical benefit and safety remain limited.This study aimed to compare the efficacy and safety of HAIC plus bevacizumab and sintilimab(HAIC-BP1)versus HAIC plus bevacizumab and atezolizumab(HAIC-BPL)in advanced HCC.Methods:A retrospective analysis was conducted on 88 patients with advanced HCC who received first-line HAIC-BP1or HAIC-BPL at Sun Yat-sen University Cancer Center between January 2020 and December 2022.Progression-free survival(PFS),overall survival(OS),objective response rate(ORR),disease control rate(DCR),and adverse events(AEs)were compared between the two groups.Cox regression analysis was performed to identify prognostic factors affecting PFS.Results:A total of 47 patients were included in the HAIC-BP1 group and 41 patients in the HAIC-BPL group,with no statistically significant differences in baseline characteristics between the two groups(all P>0.05).The ORR(59.6%vs.65.9%)and DCR(72.3%vs.80.5%)did not significantly differ between the HAIC-BP1 group and the HAIC-BPL group(both P>0.05).After a median follow-up of 16.3 months,there were no significant differences in median OS(21.3 months vs.22.4 months)or median PFS(6.7 months vs.6.2 months)between the HAIC-BP1 group and the HAIC-BPL group(both P>0.05).The incidence of AEs was similar,and no treatment-related deaths occurred.Multivariate Cox regression analysis identified tumor diameter>10 cm as an independent adverse prognostic factor for PFS(HR=0.48,95%CI=0.27-0.83,P=0.009).Conclusion:Both HAIC-BP1 and HAIC-BPL demonstrated comparable efficacy and favorable safety profiles as first-line treatment options for advanced HCC.Tumor diameter>10 cm was an independent unfavorable prognostic factor for PFS,underscoring the importance of patient stratification in clinical decision-making.

Objective:To explore the effects of age and gender on the sagittal spinal-pelvic parameters during the natural aging process of healthy adults.Methods:A total of 647 Chinese healthy adults who underwent health check-ups at the Second Affiliated Hospital of Zhejiang University School of Medicine and Songyang County People's Hospital, from January 2017 to September 2024 were collected. There were 277 males and 370 females, aged 18-93 years. Anteroposterior and lateral X-ray films of the whole spine were taken to evaluate the spinal-pelvic sagittal morphology. The following parameters were measured: thoracic kyphosis (TK), lumbar lordosis(LL), sacral slope (SS), pelvic incidence (PI), pelvic tilt (PT), global tilt (GT), T 1-pelvic angle (TPA), sagittal vertical axis (SVA), thoracic Cobb angle (T-Cobb), lower end vertebra of thoracic Cobb angle (T-LEV), apex vertebra of thoracic Cobb angle (T-Apex), lumbar Cobb angle (L-Cobb). Compare the differences in spine-pelvis parameters among patients of different genders and age groups (in this study, the subjects were subdivided into the 18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80-93 years groups according to the age range). Results:The results showed that GT, SVA, TPA, and PT increased with age ( P<0.05). For males aged 18-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80-93 years, PT values were 8.58°±6.47°, 9.60°±5.63°, 12.65°±7.13°, 11.00°±6.99°, 13.01°±8.63°, 15.77°±8.02°, and 18.47°±10.03° respectively; for females in the same age groups, the PT values were 8.44°±6.83°, 9.00°±6.44°, 11.84°±7.35°, 12.07°±7.51°, 15.44°±9.39°, 19.26°±8.28°, and 18.17°±9.43° respectively. For males in these age groups, the global tilt (GT) values were 6.37°±7.20°, 8.77°±6.51°, 10.38°±9.07°, 8.80°±7.49°, 10.80°±8.62°, 16.07°±10.42°, and 21.99°±12.65° respectively; for females, the GT values were 4.46°±8.09°, 5.96°±7.83°, 8.17°±6.88°, 9.41°±8.03°, 9.96°±1.39°, 17.89°±9.39°, and 19.55°±12.34° respectively. The sagittal vertical axis (SVA) values for males in the age groups were -7.94±25.57 mm, -2.98±25.69 mm, -4.63±20.90 mm, -6.43±32.81 mm, 7.85±43.39 mm, 36.49±53.89 mm, and 55.57±51.10 mm respectively; for females, they were -24.12±31.35 mm, -17.49±25.12 mm, -17.88±22.72 mm, -8.25±30.91 mm, 8.80±27.45 mm, 28.67±38.22 mm, and 23.23±35.19 mm respectively. For males, the thoracic pelvic angle (TPA) values across the age groups were 4.46°±5.94°, 6.05°±5.38°, 9.58°±9.35°, 7.52°±7.64°, 11.23°±9.59°, 16.32°±12.38°, and 18.49°±11.70° respectively; for females, the TPA values were 2.72°±6.88°, 3.68°±6.26°, 7.30°±6.11°, 7.44°±6.75°, 12.64°±9.79°, 19.08°±10.39°, and 16.79°±13.19° respectively. T-Cobb, T-LEV, and T-Apex increased slowly with age ( P<0.05). The pelvic incidence (PI) remained relatively constant in males ( P>0.05), while it increased slowly with age in females ( P<0.05). Conclusions:Sagittal anteversion of the spinal-pelvis increases with age. Gender differences are reflected in specific changes in the fluctuation amplitude of certain parameters (such as PI), and the fluctuations of indicators like T-Cobb, T-LEV, and T-Apex are closely related to the natural aging process of the spine.

The incidence of orthopedic trauma-related diseases keeps rising annually, which brings an urgent need to optimize the diagnostic and treatment processes to enhance treatment efficiency and improve patients′ prognosis. Traditional diagnostic methods in traumatic orthopedics primarily rely on manual film interpretation and classification, resulting in a substantial workload for physicians and consequently a low efficiency. Furthermore, during multidisciplinary consultations and cross-hospital referrals for patients with orthopedic trauma, accessing medical records and facilitating information exchange can be challenging, leading to delays in surgical intervention. The rapid advancement of artificial intelligence (AI) technology, characterized by feature engineering, artificial neural networks, and deep learning, has transformed the landscape of rapid diagnosis and precision treatment for orthopedic trauma. Nonetheless, centralized storage during task training poses risks of privacy disclosure and security concerns that impede the widespread application of AI models. In contrast, the decentralized nature of blockchain technology offers a secure operational environment for AI-driven diagnostics and treatments and the integration of blockchain and AI can deliver more accurate, efficient, and safe services for patients with orthopedic trauma. Currently, challenges remain in the inter-institutional sharing of data, constant phenomenon of data silos and absence of standardized protocols for developing collaborative models in clinical settings. To address these challenges, the authors reviewed the research advancements in integrated application of blockchain technology and artificial intelligence in diagnosing and treating orthopedic trauma, aiming to provide insights into the development of a digital diagnostic system tailored to this field in China.

Dynamic tracking analysis of monoclonal antibodies (mAbs) biotransformation in vivo is crucial, as certain modifications could inactivate the protein and reduce drug efficacy. However, a particular challenge (i.e. immune recognition deficiencies) in biotransformation studies may arise when modifications occur at the paratope recognized by the antigen. To address this limitation, a multi-epitope affinity technology utilizing the metal organic framework (MOF)@Au@peptide@aptamer composite material was proposed and developed by simultaneously immobilizing complementarity determining region (CDR) mimotope peptide (HH24) and non-CDR mimotope aptamer (CH1S-6T) onto the surface of MOF@Au nanocomposite. Comparative studies demonstrated that MOF@Au@peptide@aptamer exhibited significantly enhanced enrichment capabilities for trastuzumab variants in comparison to mono-epitope affinity technology. Moreover, the higher deamidation ratio for LC-Asn-30 and isomerization ratio for HC-Asn-55 can only be monitored by the novel bioanalytical platform based on MOF@Au@peptide@aptamer and liquid chromatography-quadrupole time of flight-mass spectrometry (LC-QTOF-MS). Therefore, multi-epitope affinity technology could effectively overcome the biases of traditional affinity materials for key sites modification analysis of mAb. Particularly, the novel bioanalytical platform can be successfully used for the tracking analysis of trastuzumab modifications in different biological fluids. Compared to the spiked phosphate buffer (PB) model, faster modification trends were monitored in the spiked serum and patients' sera due to the catalytic effect of plasma proteins and relevant proteases. Differences in peptide modification levels of trastuzumab in patients' sera were also monitored. In summary, the novel bioanalytical platform based on the multi-epitope affinity technology holds great potentials for in vivo biotransformation analysis of mAb, contributing to improved understanding and paving the way for future research and clinical applications.

Dynamic tracking analysis of monoclonal antibodies(mAbs)biotransformation in vivo is crucial,as certain modifications could inactivate the protein and reduce drug efficacy.However,a particular chal-lenge(i.e.immune recognition deficiencies)in biotransformation studies may arise when modifications occur at the paratope recognized by the antigen.To address this limitation,a multi-epitope affinity technology utilizing the metal organic framework(MOF)@Au@peptide@aptamer composite material was proposed and developed by simultaneously immobilizing complementarity determining region(CDR)mimotope peptide(HH24)and non-CDR mimotope aptamer(CH1S-6T)onto the surface of MOF@Au nanocomposite.Comparative studies demonstrated that MOF@Au@peptide@aptamer exhibited signifi-cantly enhanced enrichment capabilities for trastuzumab variants in comparison to mono-epitope af-finity technology.Moreover,the higher deamidation ratio for LC-Asn-30 and isomerization ratio for HC-Asn-55 can only be monitored by the novel bioanalytical platform based on MOF@Au@peptide@aptamer and liquid chromatography-quadrupole time of flight-mass spectrometry(LC-QTOF-MS).Therefore,multi-epitope affinity technology could effectively overcome the biases of traditional affinity materials for key sites modification analysis of mAb.Particularly,the novel bioanalytical platform can be suc-cessfully used for the tracking analysis of trastuzumab modifications in different biological fluids.Compared to the spiked phosphate buffer(PB)model,faster modification trends were monitored in the spiked serum and patients'sera due to the catalytic effect of plasma proteins and relevant proteases.Differences in peptide modification levels of trastuzumab in patients'sera were also monitored.In summary,the novel bioanalytical platform based on the multi-epitope affinity technology holds great potentials for in vivo biotransformation analysis of mAb,contributing to improved understanding and paving the way for future research and clinical applications.