The incidences and clinical outcomes of cryptococcosis in Taiwan: A nationwide, population-based study, 2002-2015.

Large-scale epidemiological data on cryptococcosis other than cryptococcal meningitis (CM), human immunodeficiency virus (HIV)- or solid organ transplantation (SOT)-associated cryptococcosis are limited. This study investigated the disease burden of cryptococcosis in Taiwan over 14 years. Incident episodes of cryptococcosis, comorbidities, treatment, and outcomes were captured from Taiwan's National Health Insurance Research Database and National Death Registry between 2002 and 2015. Of 6647 episodes analyzed, the crude incidence rate per 100 000 population increased from 1.48 in 2002 to 2.76 in 2015, which was driven by the growing trend in the non-CM group (0.86-2.12) but not in the CM group (0.62-0.64). The leading three comorbidities were diabetes mellitus (23.62%), malignancy (22.81%), and liver disease (17.42%). HIV accounted for 6.14% of all episodes and was associated with the highest disease-specific incidence rate (269/100 000 population), but the value dropped 16.20% biennially. Within 90 days prior to cohort entry, 30.22% of episodes had systemic corticosteroid use. The in-hospital mortality of all episodes was 10.80%, which varied from 32.64% for cirrhosis and 13.22% for HIV to 6.90% for SOT. CM was associated with a higher in-hospital mortality rate than non-CM (19.15% vs. 6.33%). At diagnosis, only 48.53% of CM episodes were prescribed an amphotericin-based regimen. The incidence rate of cryptococcosis was increasing, especially that other than meningitis and in the non-HIV population. A high index of clinical suspicion is paramount to promptly diagnose, treat, and improve cryptococcosis-related mortality in populations other than those with HIV infection or SOT.

This nationwide study showed that the incidence rate of cryptococcosis doubled from 2002 to 2015. Non-meningeal cryptococcosis and non-HIV/nontransplant (NHNT)-associated cryptococcosis contributed to this increase. Our study highlighted the underestimated burden of cryptococcosis in the NHNT hosts.

Omnidirectional Sensor Design for Distributed Laser Measurement Systems.

Distributed laser measurement systems, widely used in high-end equipment such as airplanes, ships, and other manufacturing fields, face challenges in large spatial measurements due to laser plane obstructions and weak intersections. This paper introduces a novel omnidirectional sensor with enhanced adaptability to complex environments and improved measurement accuracy. Initially, an integrated omnidirectional measurement model is established, followed by the analysis of the optical path of the front-end detector, and the design of a signal-conditioning circuit for the photoelectric conversion of the front-end laser signal, Subsequently, a circuit testing platform is established to validate the detection functionality, and the corresponding results indicate that the symmetry of the output waveform is under 10 ns, the response time is under 100 ns, and the maximum detection distance is 22 m. Further, experimental results demonstrate the superiority of omnidirectional sensors over planar ones in complex environments, successfully receiving 360° laser signals. The positional accuracy of the common point to be measured on the top of the omnidirectional sensor is confirmed to exceed 0.05 mm, and the accuracy of the angle of attitude exceeds 0.04°. Using the laser tracker, the measurement accuracy of the system is verified to be better than 0.3 mm. When rotating in the horizontal and pitch directions, the measurement accuracy is better than 0.35 mm and 0.47 mm, respectively, fulfilling the sub-millimeter precision requirement and expanding the application scope of distributed laser measurement systems.

Multimodal feature fusion in deep learning for comprehensive dental condition classification.

BACKGROUND: Dental health issues are on the rise, necessitating prompt and precise diagnosis. Automated dental condition classification can support this need. OBJECTIVE: The study aims to evaluate the effectiveness of deep learning methods and multimodal feature fusion techniques in advancing the field of automated dental condition classification. METHODS AND MATERIALS: A dataset of 11,653 clinically sourced images representing six prevalent dental conditions-caries, calculus, gingivitis, tooth discoloration, ulcers, and hypodontia-was utilized. Features were extracted using five Convolutional Neural Network (CNN) models, then fused into a matrix. Classification models were constructed using Support Vector Machines (SVM) and Naive Bayes classifiers. Evaluation metrics included accuracy, recall rate, precision, and Kappa index. RESULTS: The SVM classifier integrated with feature fusion demonstrated superior performance with a Kappa index of 0.909 and accuracy of 0.925. This significantly surpassed individual CNN models such as EfficientNetB0, which achieved a Kappa of 0.814 and accuracy of 0.847. CONCLUSIONS: The amalgamation of feature fusion with advanced machine learning algorithms can significantly bolster the precision and robustness of dental condition classification systems. Such a method presents a valuable tool for dental professionals, facilitating enhanced diagnostic accuracy and subsequently improved patient outcomes.

Silk Fibroin-Laponite Porous Microspheres as Cell Microcarriers for Osteogenic Differentiation.

Silk fibroin (SF) has garnered significant attention as a natural polymer for fabricating porous scaffolds in various engineering applications. However, the limited osteoinductive property of SF has hindered its efficacy in bone repair applications. In this study, we constructed an SF-based injectable porous microcarrier that is doped with laponite (LAP), containing magnesium ions (Mg2+). The influence of freezing temperatures and concentrations of SF and LAP on the structural parameters of SF-LAP microcarriers was investigated. The SF-LAP microcarrier exhibited a porosity of 76.7 ± 1.2% and a controlled pore size of 24.6 ± 4.0 µm. At the 6 weeks of in vitro degradation test, a mild alkaline level in culture medium containing SF-LAP microcarriers was detected. The release of Mg2+ from the SF-LAP microcarrier was maintained at a concentration within the range of 1.2-2.3 mM during the 6 weeks. The seeded human adipose-derived stem cells in the SF-LAP microcarrier demonstrated a significant enhancement in osteogenic differentiation compared with cells seeded in the pure SF microcarrier, as evidenced by quantitative alkaline phosphatase activity and the expression of osteogenic marker genes. These findings underscore the potential of the SF-LAP microcarrier as an ideal cell carrier in the treatment of bone defects.

Effect of Hashimoto's thyroiditis on the dual-energy CT quantitative parameters and performance in diagnosing metastatic cervical lymph nodes in patients with papillary thyroid cancer.

BACKGROUND: To evaluate the effect of Hashimoto's thyroiditis (HT) on dual-energy computed tomography (DECT) quantitative parameters of cervical lymph nodes (LNs) in patients with papillary thyroid cancer (PTC), and its effect on the diagnostic performance and threshold of DECT in preoperatively identifying metastatic cervical LNs. METHODS: A total of 479 LNs from 233 PTC patients were classified into four groups: HT+/LN+, HT+/LN-, HT-/LN + and HT-/LN - group. DECT quantitative parameters including iodine concentration (IC), normalized IC (NIC), effective atomic number (Zeff), and slope of the spectral Hounsfield unit curve (λHU) in the arterial phase (AP) and venous phase were compared. Receiver operating characteristic curve analyses were performed to evaluate DECT parameters' diagnostic performance in differentiating metastatic from nonmetastatic LNs in the HT - and HT + groups. RESULTS: The HT+/LN + group exhibited lower values of DECT parameters than the HT-/LN + group (all p < 0.05). Conversely, the HT+/LN - group exhibited higher values of DECT parameters than the HT-/LN - group (all p < 0.05). In the HT + group, if an AP-IC of 1.850 mg/mL was used as the threshold value, then the optimal diagnostic performance (area under the curve, 0.757; sensitivity, 69.4%; specificity, 71.0%) could be obtained. The optimal threshold value of AP-IC in the HT - group was 2.050 mg/mL. In contrast, in the HT - group, AP-NIC demonstrated the highest area under the curve of 0.988, when an optimal threshold of 0.243 was used. The optimal threshold value of AP-NIC was 0.188 in the HT + group. CONCLUSIONS: HT affected DECT quantitative parameters of LNs and subsequent the diagnostic thresholds. When using DECT to diagnose metastatic LNs in patients with PTC, whether HT is coexistent should be clarified considering the different diagnostic thresholds.

Advancing nutrition risk assessment in middle-aged and older individuals with diverse food cultures: A data-driven personalized approach to predict incident hypertension, diabetes and mortality.

BACKGROUND: Personalized nutrition risk assessment is crucial in addressing the association between healthy dietary habits across the life course and the development of disease, functional capacity, and healthy aging, as specific dietary pattern recommendations may not be suitable for diverse food cultures. OBJECTIVE: To develop a data-driven, personalized nutrition risk assessment algorithm linked to incident hypertension, diabetes, and all-cause mortality utilizing the food frequency questionnaire among middle-aged and older individuals. METHODS: A retrospective, population-based cohort study conducted between 1999 and 2015 utilized the nationally representative Taiwan Longitudinal Study on Aging (TLSA) survey to examine personalized dietary risk clusters and their associations with health outcomes. Latent class analysis was performed to derive the dietary diversity clusters among community-dwelling middle-aged and older individuals. Outcomes were defined as new-onset hypertension, diabetes mellitus and all-cause mortality at 4-, 8-, 12- and 16-year follow-ups. RESULTS: Data from 1,811 participants (58.14% males, 43.90% aged 50-64 years) showed that around one-third of participants reported being illiterate, 21.98% widowed, and 51.46% engaging in regular physical exercise. Four dietary diversity clusters were identified: "least diverse", "fish and meat", "dairy, fruit, and vegetable", and "most diverse". The "most diverse" cluster was characterized by a high consumption of protein-rich foods, while the "dairy, fruit, and vegetable" cluster had the highest consumption of dairy products and beans/legumes. The "least diverse" cluster had the lowest intake of protein-rich foods, and dark-colored vegetables and fruits. The "most diverse" cluster had a significantly lower risk of hypertension development at the 4-year (aOR 0.58; p < 0.02) and 8-year (aOR 0.57; p < 0.01) follow-up and diabetes at the 4-year (aOR 0.44; p < 0.03) follow-up. Participants in the "most diverse" clusters exhibited lower risks of 8-year, 12-year, and 16-year mortality than those in the "least diverse" cluster (aOR 0.67, p < 0.05; 0.67, p < 0.03; and 0.50, p < 0.01, respectively). CONCLUSION: The personalized nutrition risk assessment algorithm from the food frequency questionnaire can effectively stratify personal health risks among diverse middle-aged and older individuals, making it a valuable tool in lifestyle modification and intervention studies.

Ten-year epidemiology and risk factors of cytomegalovirus infection in hematopoietic stem cell transplantation patients in Taiwan.

BACKGROUND: Cytomegalovirus (CMV) can cause infection and critical diseases in hematopoietic stem cell transplantation (HSCT) recipients. This study aimed to explore the cumulative incidence and risk factors for CMV infection and disease among HSCT recipients in Taiwan. METHODS: This retrospective cohort study using the Taiwan Blood and Marrow Transplantation Registry (TBMTR) included HSCT recipients between 2009 and 2018 in Taiwan. The primary outcome was cumulative incidence of CMV infection or disease at day 100 after HSCT. Secondary outcomes included day 180 cumulative incidence of CMV infection or disease, infection sites, risk factors for CMV infection or disease, survival analysis, and overall survival after CMV infection and disease. RESULTS: There were 4394 HSCT recipients included in the study (2044 auto-HSCT and 2350 allo-HSCT). The cumulative incidence of CMV infection and disease was significantly higher in allo-HSCT than in auto-HSCT patients at day 100 (53.7% vs. 6.0%, P < 0.0001 and 6.1% vs. 0.9%, P < 0.0001). Use of ATG (HR 1.819, p < 0.0001), recipient CMV serostatus positive (HR 2.631, p < 0.0001) and acute GVHD grades ≥ II (HR 1.563, p < 0.0001) were risk factors for CMV infection, while matched donor (HR 0.856, p = 0.0180) and myeloablative conditioning (MAC) (HR 0.674, p < 0.0001) were protective factors. CONCLUSION: The study revealed a significant disparity in terms of the incidence, risk factors, and clinical outcomes of CMV infection and disease between auto and allo-HSCT patients. These findings underscore the importance of considering these factors in the management of HSCT recipients to improve outcomes related to CMV infections.