Automatic and robust estimation of sex and chronological age from panoramic radiographs using a multi-task deep learning network: a study on a South Korean population.

Sex and chronological age estimation are crucial in forensic investigations and research on individual identification. Although manual methods for sex and age estimation have been proposed, these processes are labor-intensive, time-consuming, and error-prone. The purpose of this study was to estimate sex and chronological age from panoramic radiographs automatically and robustly using a multi-task deep learning network (ForensicNet). ForensicNet consists of a backbone and both sex and age attention branches to learn anatomical context features of sex and chronological age from panoramic radiographs and enables the multi-task estimation of sex and chronological age in an end-to-end manner. To mitigate bias in the data distribution, our dataset was built using 13,200 images with 100 images for each sex and age range of 15-80 years. The ForensicNet with EfficientNet-B3 exhibited superior estimation performance with mean absolute errors of 2.93 ± 2.61 years and a coefficient of determination of 0.957 for chronological age, and achieved accuracy, specificity, and sensitivity values of 0.992, 0.993, and 0.990, respectively, for sex prediction. The network demonstrated that the proposed sex and age attention branches with a convolutional block attention module significantly improved the estimation performance for both sex and chronological age from panoramic radiographs of elderly patients. Consequently, we expect that ForensicNet will contribute to the automatic and accurate estimation of both sex and chronological age from panoramic radiographs.

Blockchain-Based Caching Architecture for DApp Data Security and Delivery.

Decentralized applications (DApps) built on blockchain technology offer a promising solution to issues caused by centralization. However, traditional DApps leveraging off-chain storage face performance challenges due to factors such as storage location, network speed, and hardware conditions. For example, decentralized storage solutions such as IPFS suffer from diminished download performance due to I/O constraints influenced by data access patterns. Aiming to enhance the Quality of Service (QoS) in DApps built on blockchain technology, this paper proposes a blockchain node-based distributed caching architecture that guarantees real-time responsiveness for users. The proposed architecture ensures data integrity and user data ownership through blockchain while maintaining cache data consistency through local blockchain data. By implementing local cache clusters on blockchain nodes, our system achieves rapid response times. Additionally, attribute-based encryption is applied to stored content, enabling secure content sharing and access control, which prevents data leakage and unauthorized access in unreliable off-chain storage environments. Comparative analysis shows that our proposed system achieves a reduction in request processing latency of over 89% compared to existing off-chain solutions, maintaining cache data consistency and achieving response times within 65 ms. This demonstrates the model's effectiveness in providing secure and high-performance DApp solutions.

Novel Enhanced Mammalian Cell Transient Expression Vector via Promoter Combination.

During the emergence of infectious diseases, evaluating the efficacy of newly developed vaccines requires antigen proteins. Available methods enhance antigen protein productivity; however, structural modifications may occur. Therefore, we aimed to construct a novel transient overexpression vector capable of rapidly producing large quantities of antigenic proteins in mammalian cell lines. This involved expanding beyond the exclusive use of the human cytomegalovirus (CMV) promoter, and was achieved by incorporating a transcriptional enhancer (CMV enhancer), a translational enhancer (woodchuck hepatitis virus post-transcriptional regulatory element), and a promoter based on the CMV promoter. Twenty novel transient expression vectors were constructed, with the vector containing the human elongation factor 1-alpha (EF-1a) promoter showing the highest efficiency in expressing foreign proteins. This vector exhibited an approximately 27-fold higher expression of enhanced green fluorescent protein than the control vector containing only the CMV promoter. It also expressed the highest level of severe acute respiratory syndrome coronavirus 2 receptor-binding domain protein. These observations possibly result from the simultaneous enhancement of the transcriptional activity of the CMV promoter and the human EF-1a promoter by the CMV enhancer. Additionally, the synergistic effect between the CMV and human EF-1a promoters likely contributed to the further enhancement of protein expression.

Exploring the Relationship Between Avatar Ego Types and Communication: A Comparative Study of South Korea and the United States Based on the Expectation Confirmation Model.

This research explores the significance of avatar communication in the virtual world, where individuals can create new identities and establish relationships beyond real-world limitations. Avatar users engage in virtual interactions to fulfill their desires, enjoy entertainment, and experience surrogate satisfaction. This study integrates the Expectation Confirmation Model (ECM) and Impression Management Theory (IMT) to investigate the impact of various avatar ego types on communication satisfaction and continued intention to use. Two surveys (n = 600) were administered using South Korean and American samples. The results suggest a significant relationship between expectancy confirmation and perceived usefulness. Specifically, high perceived usefulness leads to increased communication satisfaction. Also, when pre-experience expectancy confirmation is low, it positively affects communication satisfaction. In addition, the study highlights differences between Western and Eastern cultural contexts in avatar ego type's expression. This study contributes to the understanding of virtual interactions, offering theoretical insights through the integration of ECM and IMT. Theoretical and practical implications are discussed.

Integrated drug response prediction models pinpoint repurposed drugs with effectiveness against rhabdomyosarcoma.

Targeted therapies for inhibiting the growth of cancer cells or inducing apoptosis are urgently needed for effective rhabdomyosarcoma (RMS) treatment. However, identifying cancer-targeting compounds with few side effects, among the many potential compounds, is expensive and time-consuming. A computational approach to reduce the number of potential candidate drugs can facilitate the discovery of attractive lead compounds. To address this and obtain reliable predictions of novel cell-line-specific drugs, we apply prediction models that have the potential to improve drug discovery approaches for RMS treatment. The results of two prediction models were ensemble and validated via in vitro experiments. The computational models were trained using data extracted from the Genomics of Drug Sensitivity in Cancer database and tested on two RMS cell lines to select potential RMS drug candidates. Among 235 candidate drugs, 22 were selected following the result of the computational approach, and three candidate drugs were identified (NSC207895, vorinostat, and belinostat) that showed selective effectiveness in RMS cell lines in vitro via the induction of apoptosis. Our in vitro experiments have demonstrated that our proposed methods can effectively identify and repurpose drugs for treating RMS.

Scientific Publication Speed of Korean Medical Journals during the COVID-19 Era.

OBJECTIVES: This study compared the scientific publication speeds of Korean medical journals before and during the coronavirus disease 2019 (COVID-19) era. METHODS: We analyzed 2,064 papers from 43 international Korean medical journals, selecting 12 papers annually from 2019 to 2022. We assessed publication speed indicators, including the time from submission to revision and from submission to publication. Additionally, we examined variations in publication speed based on journal and paper characteristics, including whether the studies were related to COVID-19. RESULTS: Among the 43 journals analyzed, 39.5% disclosed the peer review duration from submission to the first decision, and 11.6% reported their acceptance rates. The average time from submission to acceptance was 127.0 days in 2019, 126.1 days in 2020, 124.6 days in 2021, and 126.4 days in 2022. For COVID-19-related studies, the average time from submission to revision was 61.4 days, compared to 105.1 days for non-COVID-19 studies; from submission to acceptance, it was 87.4 days for COVID-19-related studies and 127.1 days for non-COVID-19 studies. All indicators for COVID-19-related studies showed shorter durations than those for non-COVID-19 studies, and the proportion of studies accepted within 30 or 60 days was significantly higher for COVID-19-related studies. CONCLUSIONS: This study investigated the publication speed of Korean international medical journals before and during the COVID-19 pandemic. The pandemic influenced journals' review and publication processes, potentially impacting the quality of academic papers. These findings provide insights into publication speeds during the COVID-19 era, suggesting that journals should focus on maintaining the integrity of their publication and review processes.

Long-term humoral and cellular immunity against vaccine strains and Omicron subvariants (BQ.1.1, BN.1, XBB.1, and EG.5) after bivalent COVID-19 vaccination.

Background: The assessment of long-term humoral and cellular immunity post-vaccination is crucial for establishing an optimal vaccination strategy. Methods: This prospective cohort study evaluated adults (≥18 years) who received a BA.4/5 bivalent vaccine. We measured the anti-receptor binding domain immunoglobulin G antibody and neutralizing antibodies (NAb) against wild-type and Omicron subvariants (BA.5, BQ.1.1, BN.1, XBB.1 and EG.5) up to 9 months post-vaccination. T-cell immune responses were measured before and 4 weeks after vaccination. Results: A total of 108 (28 SARS-CoV-2-naïve and 80 previously infected) participants were enrolled. Anti-receptor binding domain immunoglobulin G (U/mL) levels were higher at 9 months post-vaccination than baseline in SAR-CoV-2-naïve individuals (8,339 vs. 1,834, p<0.001). NAb titers against BQ.1.1, BN.1, and XBB.1 were significantly higher at 9 months post-vaccination than baseline in both groups, whereas NAb against EG.5 was negligible at all time points. The T-cell immune response (median spot forming unit/106 cells) was highly cross-reactive at both baseline (wild-type/BA.5/XBB.1.5, 38.3/52.5/45.0 in SARS-CoV-2-naïve individuals; 51.6/54.9/54.9 in SARS-CoV-2-infected individuals) and 4 weeks post-vaccination, with insignificant boosting post-vaccination. Conclusion: Remarkable cross-reactive neutralization was observed against BQ.1.1, BN.1, and XBB.1 up to 9 months after BA.4/5 bivalent vaccination, but not against EG.5. The T-cell immune response was highly cross-reactive.

Immunogenicity and safety of concomitant bivalent COVID-19 and quadrivalent influenza vaccination: implications of immune imprinting and interference.

OBJECTIVES: Concomitant COVID-19 and influenza vaccination would be an efficient strategy. Although the co-administration of monovalent COVID-19 and influenza vaccinations showed acceptable immunogenicity, it remains unknown whether the bivalent COVID-19 vaccine could intensify immune interference. We aimed to evaluate the immunogenicity and safety of concomitant BA.5-based bivalent COVID-19 and influenza vaccination. METHODS: An open-label, nonrandomized clinical trial was conducted for 154 age-matched and sex-matched healthy adults between October 2022 and December 2022. Participants received either a concomitant bivalent COVID-19 mRNA booster and quadrivalent influenza vaccination (group C) or separate vaccinations (group S) at least 4 weeks apart. Solicited and unsolicited adverse events were reported up to 6 months postvaccination. Immunogenicity was evaluated by anti-spike (S) IgG electrochemiluminescence immunoassay, focus reduction neutralization test, and hemagglutination inhibition assay. RESULTS: Group C did not meet the noninferiority criteria for the seroconversion rates of anti-S IgG and neutralizing antibodies against the wild-type SARS-CoV-2 strain compared with group S (44.2% vs. 46.8%, difference of -2.6% [95% CI, -18 to 13.4]; 44.2% vs. 57.1%, difference of -13.0% [95% CI to -28.9 to 2.9]). However, group C showed a stronger postvaccination neutralizing antibody response against Omicron BA.5 (72.7% vs. 64.9%). Postvaccination geometric mean titers for SARS-CoV-2 and influenza strains were similar between groups, except for influenza B/Victoria. Most adverse events were mild and comparable between the study groups. DISCUSSION: Concomitant administration of bivalent COVID-19 mRNA and quadrivalent influenza vaccines showed tolerable safety profiles and sufficient immunogenicity, particularly attenuating immune imprinting induced by previous ancestral vaccine strains.