Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

Thyroid scanning using technetium-99m ( 99mTc) is the gold standard for diagnosing feline hyperthyroidism. In cats with an overactive thyroid, a thyroid scan is the most appropriate imaging technique to detect and localize any hyperfunctional adenomatous thyroid tissue. In this study, the pharmacological properties of the Technekitty injection (Tc-99m), developed as a diagnostic agent for feline hyperthyroidism using 99mTc as an active ingredient, were tested in FRTL-5 thyroid follicular cell line and ICR mice. The percentage of cell uptake of the Tc-99m in FRTL-5 thyroid cells was 0.182 ± 0.018%, which was about 6 times higher compared to Clone 9 hepatocytes. This uptake decreased by 38.2% due to competitive inhibition by iodine (sodium iodide). In tissue distribution tests by using ICR mice, the highest distribution was observed in the liver, kidneys, spleen, lungs, and femur at 0.083 hours after administration, and this distribution decreased as the compound was excreted through the kidneys, the pri-mary excretory organ. Maximum distribution was confirmed at 1 hour in the small intestine, 6hours in the large intestine, and 2 hours in the thyroid gland. Additionally, the total amount excreted through urine and feces over 48 hours (2 days) was 78.80% of the injected dose, with 37.70% (47.84% of the total excretion) excreted through urine and 41.10% (52.16% of the total excretion) through feces. In conclusion, the Tc-99m has the same mechanism of action, potency, absorption, distribution, metabolism, and excretion characteristics as 99mTc used for feline hyperthyroidism in the United States, Europe, and other countries, because the Technekitty injection (Tc-99m) contains 99mTc as its sole active ingredient. Based on these results, the Technekitty injection (Tc-99m) is expected to be safely used in the clinical diagnosis of feline hyperthyroidism.

Background: Hypertrophic scarring represents an aberrant response to wounds in certain individuals, manifesting with symptoms such as itching, tenderness, pain, and pigmentation. This study aimed to investigate the impact of a silicone-based gel on the healing of hypertrophic scars, particularly those originating from deep tissue wounds. Methods: A rat model of wound healing and scarring was established, and 12 rats were randomly assigned to three groups: Dermatix Ultra group, SFG-100 silicone-gel group, and non-treated group. Rats in the treated groups (Dermatix Ultra and SFG-100 silicone-gel) received twice-daily applications for 8 weeks. Histologic analysis, including biopsy, was conducted to evaluate the scar elevation index, epidermis thickness, and the number of granulation veins. Results: Overall, both the Dermatix Ultra and SFG-100 silicone-gel groups exhibited improvements in hypertrophic scar healing, accompanied by a significant reduction in skin pigmentation. Histopathologically, scars in both treated groups displayed a notable decrease in scar elevation index, epithelial thickness, and collagen disorganization compared to the non-treated group. However, no significant difference was observed between the Dermatix Ultra and SFG-100 silicone-gel groups. Conclusion The results suggest that SFG-100 silicone-gel is an effective therapeutic agent for hypertrophic scars. Further research is warranted to elucidate the mechanisms underlying its efficacy and to optimize its application for clinical use.

Thyroid scanning using technetium-99m ( 99mTc) is the gold standard for diagnosing feline hyperthyroidism. In cats with an overactive thyroid, a thyroid scan is the most appropriate imaging technique to detect and localize any hyperfunctional adenomatous thyroid tissue. In this study, the pharmacological properties of the Technekitty injection (Tc-99m), developed as a diagnostic agent for feline hyperthyroidism using 99mTc as an active ingredient, were tested in FRTL-5 thyroid follicular cell line and ICR mice. The percentage of cell uptake of the Tc-99m in FRTL-5 thyroid cells was 0.182 ± 0.018%, which was about 6 times higher compared to Clone 9 hepatocytes. This uptake decreased by 38.2% due to competitive inhibition by iodine (sodium iodide). In tissue distribution tests by using ICR mice, the highest distribution was observed in the liver, kidneys, spleen, lungs, and femur at 0.083 hours after administration, and this distribution decreased as the compound was excreted through the kidneys, the pri-mary excretory organ. Maximum distribution was confirmed at 1 hour in the small intestine, 6hours in the large intestine, and 2 hours in the thyroid gland. Additionally, the total amount excreted through urine and feces over 48 hours (2 days) was 78.80% of the injected dose, with 37.70% (47.84% of the total excretion) excreted through urine and 41.10% (52.16% of the total excretion) through feces. In conclusion, the Tc-99m has the same mechanism of action, potency, absorption, distribution, metabolism, and excretion characteristics as 99mTc used for feline hyperthyroidism in the United States, Europe, and other countries, because the Technekitty injection (Tc-99m) contains 99mTc as its sole active ingredient. Based on these results, the Technekitty injection (Tc-99m) is expected to be safely used in the clinical diagnosis of feline hyperthyroidism.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Novel strategies are required to reduce the risk of developing diabetes and/or clinical outcomes and complications of diabetes. In this regard, the role of the circadian system may be a potential candidate for the prevention of diabetes. We reviewed evidence from animal, clinical, and epidemiological studies linking the circadian system to various aspects of the pathophysiology and clinical outcomes of diabetes. The circadian clock governs genetic, metabolic, hormonal, and behavioral signals in anticipation of cyclic 24-hour events through interactions between a “central clock” in the suprachiasmatic nucleus and “peripheral clocks” in the whole body. Currently, circadian rhythmicity in humans can be subjectively or objectively assessed by measuring melatonin and glucocorticoid levels, core body temperature, peripheral blood, oral mucosa, hair follicles, rest-activity cycles, sleep diaries, and circadian chronotypes. In this review, we summarized various circadian misalignments, such as altered light-dark, sleep-wake, rest-activity, fasting-feeding, shift work, evening chronotype, and social jetlag, as well as mutations in clock genes that could contribute to the development of diabetes and poor glycemic status in patients with diabetes. Targeting critical components of the circadian system could deliver potential candidates for the treatment and prevention of type 2 diabetes mellitus in the future.

Background: A healthcare system’s collapse due to a pandemic, such as the coronavirus disease 2019 (COVID-19), can expose healthcare workers (HCWs) to various mental health problems. This study aimed to investigate the impact of the COVID-19 pandemic on the depression and anxiety of HCWs. Methods: A nationwide questionnaire-based survey was conducted on HCWs who worked in healthcare facilities and public health centers in Korea in December 2020. Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7) were used to measure depression and anxiety. To investigate factors associated with depression and anxiety, stepwise multiple logistic regression analysis was performed. Results: A total of 1,425 participating HCWs were included. The mean depression score (PHQ-9) of HCWs before and after COVID-19 increased from 2.37 to 5.39, and the mean anxiety score (GAD-7) increased from 1.41 to 3.41. The proportion of HCWs with moderate to severe depression (PHQ-9 ≥ 10) increased from 3.8% before COVID-19 to 19.5% after COVID-19, whereas that of HCWs with moderate to severe anxiety (GAD-7 ≥ 10) increased from 2.0% to 10.1%. In our study, insomnia, chronic fatigue symptoms and physical symptoms after COVID-19, anxiety score (GAD-7) after COVID-19, living alone, and exhaustion were positively correlated with depression. Furthermore, post-traumatic stress symptoms, stress score (Global Assessment of Recent Stress), depression score (PHQ-9) after COVID-19, and exhaustion were positively correlated with anxiety. Conclusion In Korea, during the COVID-19 pandemic, HCWs commonly suffered from mental health problems, including depression and anxiety. Regularly checking the physical and mental health problems of HCWs during the COVID-19 pandemic is crucial, and social support and strategy are needed to reduce the heavy workload and psychological distress of HCWs.

In recent years, next-generation sequencing (NGS)–based genetic testing has become crucial in cancer care. While its primary objective is to identify actionable genetic alterations to guide treatment decisions, its scope has broadened to encompass aiding in pathological diagnosis and exploring resistance mechanisms. With the ongoing expansion in NGS application and reliance, a compelling necessity arises for expert consensus on its application in solid cancers. To address this demand, the forthcoming recommendations not only provide pragmatic guidance for the clinical use of NGS but also systematically classify actionable genes based on specific cancer types. Additionally, these recommendations will incorporate expert perspectives on crucial biomarkers, ensuring informed decisions regarding circulating tumor DNA panel testing.

Objective: The rapid societal changes have underscored the importance of effective stress detection and management. Chronic mental stress significantly contributes to both physical and psychological illnesses. However, many individuals often remain unaware of their stress levels until they face physical health issues, highlighting the necessity for regular stress monitoring. This study aimed to investigate the effectiveness of vocal biomarkers in detecting stress levels among healthy Korean employees and to contribute to digital healthcare solutions. Methods: We conducted a multi-center clinical study by collecting voice recordings from 115 healthy Korean employees under both relaxed and stress-induced conditions. Stress was induced using the socially evaluated cold pressor test. The Emphasized Channel Attention, Propagation and Aggregation in Time delay neural network (ECAPA-TDNN) deep learning architecture, renowned for its advanced capabilities in analyzing person-specific voice features, was employed to develop stress prediction scores. Results: The proposed model achieved a 70% accuracy rate in detecting stress. This performance underscores the potential of vocal biomarkers as a convenient and effective tool for individuals to self-monitor and manage their stress levels within digital healthcare frameworks. Conclusion The findings emphasize the promise of voice-based mental stress assessments within the Korean population and the importance of continued research on vocal biomarkers across diverse linguistic demographics.