Osaka Prefectural Government

Limited information has been shown quantitatively assessed factors associated with the risk of secondary transmission in measles index cases. We collected data on measles index cases reported in Osaka Prefecture between November 2018 and March 2019, along with their close contacts. Secondary attack rates (SARs) in contacts of index cases were calculated and compared depending on the vaccination status, classical or modified measles and other risk factors in index cases. For the multivariate analyses, we used binary logistic regression to adjust for these potential confounding factors on the secondary transmission and calculated the adjusted odds ratio (aOR) for the SARs. A total of 105 index cases were included, involving 9,846 close contacts, with 72 secondary cases identified. A significant negative association between the number of vaccinations received by index cases and the risk of secondary infection in his/her close contacts (p < 0.01). Index cases who had received one vaccine dose had an aOR of 0.22 (95% CI: 0.08-0.65), while those with two or more doses had an aOR of 0.25 (95% CI: 0.07-0.85). Index cases who did not exhibit all three classic measles symptoms had a significantly lower risk of causing secondary infections compared to those who presented with all three symptoms (aOR: 0.12, 95% CI: 0.03-0.39). The indirect protective effect of measles vaccination would present important evidence supporting the further strengthening of vaccination policies.

Early diagnosis of oral and systemic diseases remains a major challenge due to limitations in conventional invasive procedures. This review addresses the critical need for non-invasive, accessible diagnostics by examining the potential of saliva as an alternative diagnostic fluid. The main objective is to synthesize current knowledge on salivary biomarkers and technological innovations that enhance early detection capabilities. Methodologically, the review integrates evidence from proteomic, genomic, and metabolomic studies, as well as recent advances in microfluidic point-of-care devices. Key findings highlight that saliva contains a rich array of biomarkers, including cytokines, microRNAs, and extracellular vesicles, that can accurately reflect both local oral pathologies, such as dental caries and oral cancer, and systemic conditions, including diabetes, cardiovascular diseases, autoimmune disorders, and neurodegenerative diseases. The analysis further emphasizes that portable biosensors and lab-on-chip platforms are rapidly improving diagnostic sensitivity and enabling decentralized testing. Notwithstanding these encouraging advancements, issues with biological variability, standardization, and regulatory validation still exist. This review underscores the significance of interdisciplinary collaboration to overcome these barriers and fully integrate salivary diagnostics into routine healthcare. The implications are profound: widespread adoption could transform preventive medicine by providing patient-friendly, real-time monitoring tools that improve health outcomes globally.

Abstract Artificial intelligence (AI) has emerged as a transformative force in biomedical engineering, catalyzing a shift toward data‐driven, intelligent research paradigms. With its advanced capabilities in computation, pattern recognition, and large‐scale data analysis, AI significantly enhances the efficiency, precision, and reproducibility of biomedical research. In particular, the convergence of AI with biomedical engineering has given rise to the emerging field of Digital Biomedical Engineering, which emphasizes the integration of AI technologies, big data analytics, and computational modeling to enable smart, predictive, and personalized solutions across life sciences. This review provides a comprehensive overview of the current landscape of AI applications in biomedical engineering, highlighting advances in medical image analysis, biosignal processing, biomaterials design, and drug development. It also emphasizes how AI improves diagnostic precision, accelerates material and drug discovery, and fosters personalized and predictive medicine. Additionally, it discusses the limitations and regulatory challenges of AI adoption, while outlining future directions to guide research innovation and clinical translation in the era of digital biomedicine.

Abstract Preschool teacher training (TT) about children's neurodevelopmental concerns consisted of six monthly workshops and one booster session 3 months after the sixth session that lasted 90–105 min each. Each teacher was responsible for one child and provided different interventions between sessions. A questionnaire was administered pre‐ and post‐workshop. Of the 46 participants, we analyzed the results of 44. The Total Deviance/Difficulties score on the Strengths and Difficulties Questionnaire (SDQ) for children decreased significantly post‐training, with a large effect size. The SDQ subscale scores revealed larger effect sizes for Peer Problems and Prosocial Behavior and medium effect sizes for Hyperactivity and Emotional Symptoms. Teachers' Rosenberg Self‐Esteem Scale scores increased significantly with a medium effect size. The Pre‐School Teacher Efficacy Scale showed no significant differences with a small effect size. Thus, TT may benefit both children's behavior and teacher's self‐esteem. However, it is unclear whether these changes are attributable to actual changes in the children's or teachers' understanding of their growth and development, or to both. Further studies are required to confirm these findings.

ABSTRACT The pandemic, from 2020, was expected to be a catalyst for telework to permeate. Our study empirically examines the relationship between a firm’s digitalization and telework stickiness, utilizing the unique data from our firm survey conducted in Osaka, Japan. Our results show amongst the four digital technologies, online sharing of internal information impacts telework stickiness. This tendency is also true for firms that hastily adopted telework after the pandemic.

We assessed case fatality rates (CFRs) in adults aged ≥70 years in 10 prefectures in Japan (14.8 million residents) diagnosed between January 2022 and March 2023, when the Omicron variant was dominant in Japan. We selected incident reports on 283,052 cases from participating public health centers reported according to the Infectious Diseases Control Law. Patients were passively followed up until the end of their isolation, date of death, or 28 days after COVID-19 diagnosis, whichever occurred first. We calculated age-standardized CFRs with 95% confidence intervals (CIs) using the Japanese population aged 70-79, 80-89 and ≥90 years in 2022, divided into 16 subgroups according to the period of COVID-19 diagnosis. The overall CFR was 1.59% (95% CI: 1.55-1.64%); ranging between 0.67% (95% CI: 0.38-0.96%, from May 23 to June 19, 2022) and 2.58% (95% CI: 2.36-2.80%, from January 31 to February 27, 2022). The age-standardized CFRs had three peaks, (2.2% from January 31 to February 27, 2022; 1.0% from July 18 to August 14, 2022; and 1.6% from December 26, 2022 to January 22, 2023) coinciding with the 6th, 7th, and 8th COVID-19 waves in Japan caused by the Omicron variant. Population-based CFRs for Omicron variant COVID-19 in adults aged ≥70 years remained <3% throughout the period January 2022 to March 2023, including during three large waves in Japan.

Background Young-onset type 2 diabetes mellitus (T2DM), defined as a diagnosis before the age of 45, is an increasingly common and aggressive form of diabetes. This population is at a heightened risk of developing complications earlier in life due to longer disease duration and often suboptimal glycemic control. Complications such as diabetic neuropathy, retinopathy, and nephropathy are significant concerns, leading to reduced quality of life and increased morbidity. Objective To investigate the clinical profile and risk factors associated with complications of young-onset T2DM and to analyze the correlation between the age of onset and other parameters and the development of these complications. Methods We conducted a cross-sectional study on young-onset T2DM patients (<45 years) to investigate the prevalence and associated factors of diabetic complications. Variables analyzed included age, gender, BMI, waist-hip ratio, duration of diabetes, age at diagnosis, proteinuria, and glycosuria, along with biochemical markers such as HbA1C (glycated hemoglobin), serum cholesterol, triglycerides, and C-peptide levels. Results The average age of participants in our study was 34.76 ± 6.91 years. The mean BMI was 26.68 ± 3.35, with a mean cholesterol level of 169.84 ± 55.64 and a mean triglyceride level of 205.79 ± 67.49. The average HbA1c level was 9.82 ± 2.44. Diabetic neuropathy was found to increase significantly with advancing age (p < 0.001), longer duration of diabetes (p < 0.001), higher mean levels of HbA1C (p < 0.001), serum cholesterol (p = 0.006), and serum triglycerides (p = 0.010), as well as with lower levels of serum C-peptide (p = 0.025). The severity of kidney damage showed a significant association with older age (p = 0.049), longer diabetes duration (p < 0.01), elevated mean levels of HbA1C (p = 0.0002), and serum cholesterol (p = 0.0310). Diabetic retinopathy increased significantly with advancing age (p < 0.001), longer diabetes duration (p < 0.001), higher mean levels of HbA1C (p < 0.001), and serum triglycerides (p = 0.013). Conclusion Young-onset T2DM is associated with significant risks for neuropathy, retinopathy, and nephropathy, particularly with increasing age and longer disease duration. Higher HbA1C, serum cholesterol, and triglyceride levels are prevalent among those with complications. These findings underscore the need for early intervention and targeted management strategies to mitigate complications in this high-risk population.

Background: In Japan, notifiable infectious disease surveillance ended and was replaced by sentinel surveillance following the COVID-19 reclassification in May 2023. Since COVID-19 sentinel surveillance is integrated into seasonal influenza surveillance, the number of reported cases varies depending on the extent to which sentinel facilities provide COVID-19 care. Therefore, we compared COVID-19 sentinel surveillance with school absentee surveillance, which is limited to high school equivalent age or younger, but provides reliable information on absences in the target population. Method: The 17-week period from week 23 (June 5 to June 11) to week 39 (September 25 to October 1) of 2023 was used as the target period. The number of weekly COVID-19 reports from 72 sentinel sites in Mie Prefecture (Population 1.7 million) as for sentinel surveillance and the number of COVID-19 absentees at a total of 998 facilities (401 kindergartens and nursery schools, and 597 elementary, junior high, and senior high schools) registered for school absentee surveillance in Mie Prefecture as for school absentee surveillance were compared across Mie Prefecture and eight health centers (Fig 1). Result: Except for the summer vacation period from week 29 to 35, sentinel surveillance and school absentee surveillance showed a significant positive correlation. During the summer vacation period, a decrease in the number of COVID-19 absentees was observed, especially in the elementary, junior high, and senior high school groups of the school absentee surveillance, compared to the sentinel surveillance (Fig 2 and 3). When compared by health center, no regional differences were observed in school absentee surveillance, but in sentinel surveillance, some health centers reported significantly more cases than others. Conclusion: The results of this study suggest that although COVID-19-based school absentee surveillance has some drawbacks, such as the limited number of subjects and the difficulty of evaluation during the summer vacation when schools are closed, it has the advantage of being able to evaluate the entire community without being affected by medical institution practice bias, and can be used to monitor trends in infectious diseases. It was considered important to combine and evaluate multiple surveillance indicators in order to accurately monitor epidemiologic trends of infectious disease over time.

Objectives The primary aim of this study was to clarify the relationship between the number of public health nurses (PHNs) and the total number of people who received home-visit nursing services for mental health or intractable diseases. The secondary aim was to clarify the extent of regional differences in the number of PNHs and mental health or intractable diseases.Methods This study used the total number of people who received home-visit nursing services for mental health or intractable diseases in 2019 from the Portal Site of Official Statistics of Japan (e-Stat) and population and area data in January 2020. Single and multiple regression analyses (covariates: population and area) were performed on the relationship between the number of PHNs per 100,000 population (abbreviated as "ratios of PHNs") and the total number of people who received home-visit nursing services for mental health or intractable diseases per 100,000 population (abbreviated as "mental health/intractable disease achievements"). Regional differences in ratios of PHNs and mental health/intractable disease achievement were examined using mean, standard deviation, maximum/minimum values, and Gini coefficients. Analyses were performed for each of the five units: the prefectures as a whole, prefectural public health centers, municipalities within the jurisdiction of prefectural public health centers, and cities in which public health centers are established (including or not including special wards).Results Regression analyses indicated a positive relationship between the ratios of PHNs and mental health/intractable disease achievements. Multiple regression analysis indicated that both achievements were positively associated with population size and negatively associated with area size. The largest regression coefficients between the ratios of PHNs and achievements were 34.07 and 5.48 regarding mental health achievements and intractable disease achievements, respectively. For regional differences, the smallest Gini coefficient was the ratios of PHNs, and the largest was intractable disease achievements. The smallest and largest coefficient of the prefectures as a whole was 0.15 and 0.34, respectively. The maximum/minimum values of the prefectures as a whole also indicated that the smallest was 3.8 in the ratio of PHNs and the largest was 30.0 in intractable disease achievement.Conclusions Increasing number of PHNs is needed to provide more home-visit nursing services for mental health and intractable diseases. It is particularly important to fill up the larger number of PHNs in smaller populations or larger area prefectures. Due to regional differences in the home-visit nursing service, it is important to promote the increase in the level of these activities.

The association between serum uric acid levels and the risk of diabetes mellitus in women stratified by menopausal status is not well-established. Therefore, we investigated this association among a cohort of Japanese urban women. We conducted a prospective cohort study on 3,304 women (1,252 premenopausal and 2,052 postmenopausal), aged 30 to 79 years, with no prior cardiovascular disease or diabetes mellitus, and enrolled from a general urban population. Cox proportional hazard model was used to calculate hazard ratios and 95% confidence intervals (CIs) for incident diabetes mellitus according to serum uric acid quartiles. During 13.8 years of median follow-up, 219 incident diabetes mellitus cases were diagnosed. The incidence rate per 1,000 person-years was 3.42 in premenopausal women and 6.19 in postmenopausal women. After adjustment for potential risk factors, the multivariable hazard ratios (95% CIs) of the highest versus lowest serum uric acid quartiles were 1.56 (0.77-3.16) in premenopausal women, 2.00 (1.19-3.34) in postmenopausal women, and 1.81 (1.21-2.73) in all women. The interaction based on menopausal status was not significant ( P = 0.872). The corresponding population attributable fractions (95% CIs) were 13.3% (-8.9% to 31.1%), 19.1% (5.3%-30.9%), and 17.0% (5.6%-27.0%), respectively. Serum uric acid levels were positively associated with the risk of diabetes mellitus in postmenopausal women, but not in premenopausal women. However, the lack of an association in premenopausal women may have been due to limited power, so further research is required to confirm this menopausal status-specific association.