The trend toward miniaturization and multi-functionalization of implantable medical devices is shifting the paradigm of medicine from treatment to prevention and precision management; however, it faces a bottleneck due to the energy density limits of batteries. Existing power transfer technologies based on electromagnetic induction or radio frequency cause rapid efficiency degradation and electromagnetic interference issues in micro-scale devices. This paper reviews laser-based optical wireless power transfer technology as an innovative alternative to these issues, with particular emphasis on its potential medical applications. We provide an in-depth analysis of strategies to maximize penetration depth using near-infrared windows and light propagation characteristics within biological tissue, optimization of conversion efficiency through bandgap engineering of silicon (Si) and gallium arsenide (GaAs) based photovoltaic cells, and the latest wavefront shaping and optical phased array technologies to overcome dynamic scattering. Furthermore, by chronologically organizing research trends over the past 20 years, we discuss the paradigm shift from passive devices to active intelligent systems and present the technical and regulatory challenges for clinical adoption based on international safety standards (IEC 60825-1, ISO 14708-1), ultimately providing a technical roadmap for the energy autonomy of next-generation bio-electronic medicine.

Older adults living alone face challenges in managing diabetes, yet research on glycemic control in this group is limited. This study analyzed data from the Korean National Health and Nutrition Examination Survey (2016~2021) to identify factors associated with glycemic control in 453 older adults with diabetes living alone. Methods: Glycemic control was categorized as good (glycated hemoglobin [HbA1c]<7.0%) or poor (HbA1c≥7.0%). Complex sample logistic regression examined demographic, disease and health-related, behavioral, and psychological factors associated with glycemic control. Results: Older adults aged ≥80 years had better glycemic control than those aged 65~69 years, while a diabetes duration of ≥15 years and higher body mass index were linked to poorer control. Strength training 5~7 days per week was associated with better control, whereas non-adherence to a healthy diet was unexpectedly linked to better outcomes. Conclusion: These findings highlight the need for tailored interventions to improve diabetes self-management and support healthy aging among older adults living alone. They also offer practical insights into shaping community-based health programs and social support systems for this population.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Darier’s disease is characterized by greasy and scaly papules that primarily affect seborrheic and intertriginous areas which is caused by a mutation in the ATP2A2 gene. Histopathologically, the disease is characterized by acantholysis and dyskeratosis. Among the diverse presentations, the segmental type follows a linear distribution along the lines of Blaschko. Herein, we present a case of a 54-year-old male with generalized erythematous papules that had been linearly distributed across his body for two decades. Lesions on his trunk and extremities were confined to the right side, whereas those on the scalp and face exhibited multiple segmental presentations. Histopathological examination revealed acantholysis and dyskeratosis in the epidermis, confirming the diagnosis of type 1 segmental Darier’s disease. This case underscores the rarity of type 1 segmental Darier’s disease, particularly with multiple segmental involvement and highlights the complexity and variability of this dermatological condition.

Darier’s disease is characterized by greasy and scaly papules that primarily affect seborrheic and intertriginous areas which is caused by a mutation in the ATP2A2 gene. Histopathologically, the disease is characterized by acantholysis and dyskeratosis. Among the diverse presentations, the segmental type follows a linear distribution along the lines of Blaschko. Herein, we present a case of a 54-year-old male with generalized erythematous papules that had been linearly distributed across his body for two decades. Lesions on his trunk and extremities were confined to the right side, whereas those on the scalp and face exhibited multiple segmental presentations. Histopathological examination revealed acantholysis and dyskeratosis in the epidermis, confirming the diagnosis of type 1 segmental Darier’s disease. This case underscores the rarity of type 1 segmental Darier’s disease, particularly with multiple segmental involvement and highlights the complexity and variability of this dermatological condition.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Objective: : Hemifacial spasm (HFS) is treated by a surgical procedure called microvascular decompression (MVD). However, HFS re-appearing phenomenon after surgery, presenting as early recurrence, is experienced by some patients after MVD. Dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging (MRI) and two analytical methods : receiver operating characteristic (ROC) curve and machine learning, were used to predict early recurrence in this study. Methods: : This study enrolled 60 patients who underwent MVD for HFS. They were divided into two groups : group A consisted of 32 patients who had early recurrence and group B consisted of 28 patients who had no early recurrence of HFS. DSC perfusion MRI was undergone by all patients before the surgery to obtain the several parameters. ROC curve and machine learning methods were used to predict early recurrence using these parameters. Results: : Group A had significantly lower relative cerebral blood flow than group B in most of the selected brain regions, as shown by the region-of-interest-based analysis. By combining three extraction fraction (EF) values at middle temporal gyrus, posterior cingulate, and brainstem, with age, using naive Bayes machine learning method, the best prediction model for early recurrence was obtained. This model had an area under the curve value of 0.845. Conclusion : By combining EF values with age or sex using machine learning methods, DSC perfusion MRI can be used to predict early recurrence before MVD surgery. This may help neurosurgeons to identify patients who are at risk of HFS recurrence and provide appropriate postoperative care.

Purpose: This study aimed to compare the wound cosmesis of a single-incision approach on scar assessment after laparoscopic surgery for colon cancer. Methods: This study included 32 patients undergoing single-port laparoscopic surgery (SPLS) and 61 patients undergoing multiport laparoscopic surgery (MPLS) for colon cancer at 3 tertiary referral hospitals between September 2011 and December 2019. We modified and applied the Korean version of the Patient and Observer Scar Assessment Scale (POSAS) to assess cosmetic outcomes. To assess the interobserver reliability using intraclass correlation coefficient values for the Observer Scar Assessment Scale (OSAS), the surgeons evaluated 5 images of postoperative scars. Results: No significant differences were observed in the time before the return of normal bowel function, time to sips of water and soft diet initiation, length of in-hospital stay, and postoperative complication rate. The SPLS group had a shorter total incision length than the MPLS group. The POSAS favored the SPLS approach, revealing significant differences in the Patient Scar Assessment Scale (PSAS), OSAS, and overall scores. The SPLS approach was an independent factor influencing the POSAS, PSAS, and OSAS scores. Eleven colorectal surgeons had a significantly substantial intraclass coefficient. Conclusion The cosmetic outcomes of SPLS as assessed by the patients and surgeons were superior to those of MPLS in colon cancer. Reducing the number of ports is an independent factor affecting scar assessment by patients and observers.