Defining "High Recurrence" of Depressive Episodes for Predicting Diagnostic Conversion from Major Depressive Disorder to Bipolar Disorder: A 5-year Retrospective Study.

Objective: This study determined the threshold for recurrent depressive episodes that predicted conversion from major depressive disorder (MDD) to bipolar disorder (BD). Methods: We retrospectively reviewed the medical records of 296 patients diagnosed with MDD for a minimum of 5 years in two university hospitals. We examined their the Diagnostic and Statistical Manual of Mental Disorders, 5th edition diagnoses and detailed clinical information at the initial admission and yearly assessments after discharge to establish the threshold for recurrent depressive episodes indicating a risk of diagnostic conversion from MDD to BD. Optimal cut-offs were derived using receiver operating characteristic (ROC) curves. Results: ROC curve analysis revealed that more than four recurrent depressive episodes was indicative of potential diagnostic conversion from MDD to BD (area under the curve, 0.604; sensitivity, 0.353; specificity, 0.855; positive predictive value, 0.421; negative predictive value, 0.816). Conclusion: These findings suggest that the best predictor of conversion from MDD to BD is more than four recurrent depressive episodes. Our findings have the potential to enhance diagnostic accuracy and treatment efficiency. To validate our results, longitudinal prospective studies are necessary.

Plasma neurofilament light levels show elevation two years prior to diagnosis of amyotrophic lateral sclerosis in the UK Biobank.

OBJECTIVE: Amyotrophic lateral sclerosis (ALS) is a debilitating neurodegenerative disease with profound unmet need. In patients carrying genetic mutations, elevations in neurofilament light (NfL) have been shown to precede symptom onset, however, the natural history of NfL in general ALS patients is less characterized. METHODS: We performed a secondary analysis of the UK Biobank Pharma Proteomics Project (UKB-PPP), a subset of the UK Biobank, a population-based cohort study in the United Kingdom, to examine plasma NfL levels in 237 participants subsequently diagnosed with ALS. We applied logistic and Cox proportional hazards regression to compare cases to 42,752 population-based and 948 age and sex-matched controls. Genetic information was obtained from exome and genotype array data.Results and Conclusions: We observed that NfL was 1.42-fold higher in cases vs population-based controls. At two to three years pre-diagnosis, NfL levels in patients exceeded the 95th percentile of age and sex-matched controls. A time-to-diagnosis analysis showed that a 2-fold increase in NfL levels was associated with a 3.4-fold risk of diagnosis per year, with NfL being most predictive of case status at two years (AUC = 0.96). Participants with genetic variation that might put them at risk for familial disease (N = 46) did not show a different pattern of association than those without (N = 191). DISCUSSION: Our findings show that NfL is elevated and discriminative of future ALS diagnosis up to two years prior to diagnosis in patients with and without genetic risk variants.

Kinetics of Shear-Induced Structural Ordering in Dense Colloids.

The macroscopic rheological response of a colloidal solution is highly correlated with the local microscopic structure, as revealed by an in situ Rheo-SAXS experiment with a high temporal resolution. Oscillatory shear can induce a strain-controlled ordering-to-disorder transition, resulting in a shear-thickening process that is different from the normal shear-thickening behavior that is driven by hydrodynamics and particle friction. We reveal that there is a complex time-dependent kinetics toward structural ordering under different applied strains. When the strain amplitude reaches a critical value that starts to induce disordering in the system, the pathway toward the dynamic equilibrium can also become highly non-monotonic. Within the same oscillatory cycle, there is a strong correlation of ordering with different phases of the oscillation, with the system oscillating between two dynamic metastable states.

Visual assessment and rheological characterization of shape retention of products on a surface.

A device to measure the height loss of a sample extruded from a syringe on a surface is described thus emulating toothpaste extrusion from a tube with the goal to predict shape retention of the extruded ribbon. Correlations with rheological tests are considered with a special focus on experiments more likely to be implementable in an industrial environment. In agreement with previous studies, the instantaneous viscosity maximum measured in a stress ramp test is a good predictor of ribbon height loss. Up- and down-shear flow curves of the thixotropic loop were fitted with a generalized Casson equation and the correlations of the fitting parameters with the height loss were also considered. Yield stress extracted from the up-shear flow curve as well as the shape of the curve is found to define the ribbon height loss as well as the degree of thixotropy which may be quantified by the width of the loop or simply as the ratio of viscosities at low shear rate.

Panoramic volumetric clinical handheld photoacoustic and ultrasound imaging.

Photoacoustic (PA) imaging has gained much attention, providing structural and functional information in combination with clinical ultrasound (US) imaging systems. 2D PA and US imaging is easily implemented, but its heavy dependence on operator skills makes 3D imaging preferable. In this study, we propose a panoramic volumetric clinical PA and US imaging system equipping a handheld imaging scanner weighing 600 g and measuring 70 × 62 × 110 mm3. Multiple PA/US scans were performed to cover a large field-of-view (FOV), and the acquired PA/US volumes were mosaic-stitched after manually correcting the positions and rotations in a total of 6 degrees of freedom. PA and US maximum amplitude projection images were visualized online, while spectral unmixed data was quantified offline. The performance of the system was tested via tissue-mimicking phantom experiments. The system's potential was confirmed in vivo by panoramically imaging vascular networks in human arms and necks, with FOVs of 331 × 38 and 129 × 120 mm2, respectively. Further, we quantified hemoglobin oxygen saturation levels in the radial artery, brachial artery, carotid artery, and jugular vein. We hope that this system can be applied for various clinical fields such as cardiovascular imaging, dermatology, vascular surgery, internal medicine, and oncology.

Psychometric Properties of the Korean Version of Functioning Assessment Short Test in Bipolar Disorder.

Objective: The Functioning Assessment Short Test (FAST) is a relatively specific test for bipolar disorders designed to assess the main functioning problems experienced by patients. This brief instrument includes 24 items assessing impairment or disability in 6 domains of functioning: autonomy, occupational functioning, cognitive functioning, financial issues, interpersonal relationships, and leisure time. It has already been translated into standardized versions in several languages. The aim of this study is to measure the validity and reliability of the Korean version of FAST (K-FAST). Methods: A total of 209 bipolar disorder patients were recruited from 14 centers in Korea. K-FAST, Young Mania Rating Scale (YMRS), Bipolar Depression Rating Scale (BDRS), Global Assessment of Functioning (GAF) and the World Health Organization Quality of Life Assessment Instrument Brief Form (WHOQOL-BREF) were administered, and psychometric analysis of the K-FAST was conducted. Results: The internal consistency (Cronbach's alpha) of the K-FAST was 0.95. Test-retest reliability analysis showed a strong correlation between the two measures assessed at a 1-week interval (ICC = 0.97; p < 0.001). The K-FAST exhibited significant correlations with GAF (r = -0.771), WHOQOL-BREF (r = -0.326), YMRS (r = 0.509) and BDRS (r = 0.598). A strong negative correlation with GAF pointed to a reasonable degree of concurrent validity. Although the exploratory factor analysis showed four factors, the confirmatory factor analysis of questionnaires had a good fit for a six factors model (CFI = 0.925; TLI = 0.912; RMSEA = 0.078). Conclusion: The K-FAST has good psychometric properties, good internal consistency, and can be applicable and acceptable to the Korean context.

Characteristics of Attention-Deficit/Hyperactivity Disorder Subtypes in Children Classified Using Quantitative Electroencephalography.

Purpose: This study used quantitative electroencephalography (QEEG) to investigate the characteristics of attention-deficit/hyperactivity disorder (ADHD) subtypes in children. Patients and Methods: There were 69 subjects (42 with ADHD and 27 neurotypical (NT)) in this study. A semi-structured interview was conducted with each participant for psychiatric diagnostic evaluation. We measured the absolute and relative power in 19 channels and analyzed QEEG using the following frequency ranges: delta (1-4 Hz), theta (4-8 Hz), alpha 1 (8-10 Hz), alpha 2 (10-12 Hz), beta 1 (12-15 Hz), beta 2 (15-20 Hz), beta 3 (20-30 Hz), and gamma (30-45 Hz). Group analyses and EEG noise preprocessing were conducted using iSyncBrain, a cloud-based, artificial intelligence EEG analysis platform. Analysis of covariance adjusted for IQ, age, and sex was used. Results: QEEG analysis revealed three ADHD subtypes, characterized by (A) elevated relative fast alpha and beta power, (B) elevated absolute slow frequency (delta and theta power), or (C) elevated absolute and relative beta power. A significant difference was found in the Korean ADHD Rating Scale (K-ARS) among the four groups (df=3, F=8.004, p<0.001); group C had the highest score (25.31±11.16), followed by group A (21.67±13.18). The score of group B (12.64±7.84) was similar to that of the NT group (11.07±6.12) and did not reach the cut-off point of the K-ARS. In the Wender-Utah Rating Scale (WURS), group B score (55.82±23.17) was significantly higher than the NT group score (42.81±13.26). Conclusion: These results indicate that children with ADHD do not constitute a neurophysiologically homogenous group. Children with QEEG subtype B (elevated slow frequency) may be difficult to distinguish from normal children using the K-ARS, which is the most common screening tool for ADHD. Moreover, parents of children with this subtype may be less sensitive to observing ADHD symptoms.

Genetically-informed prediction of short-term Parkinson's disease progression.

Parkinson's disease (PD) treatments modify disease symptoms but have not been shown to slow progression, characterized by gradual and varied motor and non-motor changes overtime. Variation in PD progression hampers clinical research, resulting in long and expensive clinical trials prone to failure. Development of models for short-term PD progression prediction could be useful for shortening the time required to detect disease-modifying drug effects in clinical studies. PD progressors were defined by an increase in MDS-UPDRS scores at 12-, 24-, and 36-months post-baseline. Using only baseline features, PD progression was separately predicted across all timepoints and MDS-UPDRS subparts in independent, optimized, XGBoost models. These predictions plus baseline features were combined into a meta-predictor for 12-month MDS UPDRS Total progression. Data from the Parkinson's Progression Markers Initiative (PPMI) were used for training with independent testing on the Parkinson's Disease Biomarkers Program (PDBP) cohort. 12-month PD total progression was predicted with an F-measure 0.77, ROC AUC of 0.77, and PR AUC of 0.76 when tested on a hold-out PPMI set. When tested on PDBP we achieve a F-measure 0.75, ROC AUC of 0.74, and PR AUC of 0.73. Exclusion of genetic predictors led to the greatest loss in predictive accuracy; ROC AUC of 0.66, PR AUC of 0.66-0.68 for both PPMI and PDBP testing. Short-term PD progression can be predicted with a combination of survey-based, neuroimaging, physician examination, and genetic predictors. Dissection of the interplay between genetic risk, motor symptoms, non-motor symptoms, and longer-term expected rates of progression enable generalizable predictions.

Bioactive Compounds and Quality Evaluation of Red-Pigmented Rice Processed by Germination and Roasting.

Red-pigmented rice was germinated and processed to develop germinated red rice tea, and the changes in physicochemical, bioactive, and microbial properties due to germination and roasting were investigated. The moisture and crude ash contents of red rice decreased after germination and roasting. Crude protein and crude fat contents increased after germination but slightly decreased after roasting. Total phenolics, flavonoids, and antioxidant activities (DPPH and ABTS radical scavenging activities) increased following germination and heat treatment. However, the increased levels of γ-amino butyric acid after germination significantly decreased during the subsequent roasting step. In addition, total bacteria, yeast, and mold counts increased during the germination process but decreased after heat treatment as compared to those in the original grain; Escherichia coli was not detected. Therefore, germination and subsequent roasting could effectively enhance the contents of the most bioactive compounds and maintain microbial stability in red-pigmented rice.

Corrosion Resistance of Laser Powder Bed Fused AISI 316L Stainless Steel and Effect of Direct Annealing.

Alloy parts produced by an additive manufacturing method with rapid heat transfer from fast melting and solidification have different microstructures, characteristics, and performances compared with materials made by the conventional process. In this study, the corrosion and oxidation resistance of SS316L, which was prepared by the powder bed fusion process, was compared with those of cold-rolled SS316L. Additionally, the surface oxide film on stainless steel was thoroughly assessed since the film has the greatest influence on the corrosion and oxidation resistance. The effect of heat treatment on corrosion and oxidation resistance of SS316L fabricated by additive manufacturing was investigated. The SS316L has a microstructure formed by sub-grain cells, in which locally concentrated alloying elements form a stable passive film. As a result, it has a higher level of corrosion resistance and oxidation resistance than conventional cold-rolled materials. However, it was confirmed that the sub-grain cell was removed by heat treatment, which resulted in the degradation of corrosion and oxidation resistance.

Application time and persistence of transcranial direct current stimulation (tDCS) against neuronal death resulting from transient cerebral ischemia.

BACKGROUND: Transcranial direct current stimulation (tDCS) has been studied as a tool to stimulate the functional recovery of neurons after stroke. Although this device has recently begun to be utilized for providing neuroprotection in stroke, research on its application conditions is lacking. This study aimed to examine the effects of various tDCS application conditions on cerebral ischemia. Ischemia was induced for 5 min in a gerbil model. The application of tDCS comprised a 20 min stimulation-20 min rest-20 min stimulation protocol, which was implemented simultaneously with the induction of cerebral ischemia. Application time of the tDCS effect on ischemia was confirmed by sampling brain tissues after stimulation using 0.2 mA tDCS at 0, 5, 10 and 60 min after ischemia. RESULTS: Persistence of the tDCS effect on ischemia was confirmed by sampling brain tissues 5, 7, and 10 days post stimulation, with 0.2 mA tDCS after ischemia. Furthermore, the tissues were stained with cresyl violet and Fluoro-Jade C so as to determine the reduction in neuronal death under all application conditions. CONCLUSIONS: The application of tDCS can be used as a useful intervention for acute phase stroke due to its sustained neuroprotective effect.

Status and future trends of hollow fiber biogas separation membrane fabrication and modification techniques.

With the increasing global demand for energy, renewable and sustainable biogas has attracted considerable attention. However, the presence of various gases such as methane, carbon dioxide (CO2), nitrogen, and hydrogen sulfide in biogas, and the potential emission of acid gases, which may adversely influence the environment, limits the efficient application of biogas in many fields. Consequently, researchers have focused on the upgrade and purification of biogas to eliminate impurities and obtain high-quality and high-purity biomethane with an increased combustion efficiency. In this context, the removal of CO2 gas, which is the most abundant contaminant in biogas, is of significance. Compared to conventional biogas purification processes such as water scrubbing, chemical absorption, pressure swing adsorption, and cryogenic separation, advanced membrane separation technologies are simpler to implement, easier to scale, and incur lower costs. Notably, hollow fiber membranes enhance the gas separation efficiency and decrease costs because their large specific surface area provides a greater range of gas transport. Several reviews have described biogas upgrading technologies and gas separation membranes composed of different materials. In this review, five commonly used commercial biogas upgrading technologies, as well as biological microalgae-based techniques are compared, the advantages and limitations of polymeric and mixed matrix hollow fiber membranes are highlighted, and methods to fabricate and modify hollow fiber membranes are described. This will provide more ideas and methods for future low-cost, large-scale industrial biogas upgrading using membrane technology.

Effects of COVID-19-related stress and fear on depression in schizophrenia patients and the general population.

This study compared the coronavirus disease 2019 (COVID-19)-related stress, fear of infection, loneliness, and depression between patients with schizophrenia and the general population. A face-to-face survey was administered to 1340 patients with a schizophrenia spectrum disorder and online survey of the general population (n = 2000) was conducted. The information gathered included the level of COVID-19-related stress, fear of infection, the Patient Health Questionnaire-9 score, and the three-item UCLA Loneliness Scale score. Structural equation modeling revealed a significant effect of fear of COVID-19 infection on depression among the general population and on loneliness among patients with schizophrenia. Loneliness experienced during COVID-19 exacerbated depression in both groups. In the COVID-19-related stress-loneliness-depression pathway, the partial mediating effect of loneliness was significant in both groups. Conversely, in the COVID-19-related fear-loneliness-depression pathway, the full mediating effect of loneliness was only significant in patients with schizophrenia. In conclusion, the loneliness associated with COVID-19-related stress and fear of infection was an important factor influencing depression, and the impact was greater in patients with schizophrenia compared with the general population. Thus, different mental health intervention plans are needed for patients with schizophrenia during the COVID-19 pandemic. During the long-lasting COVID-19 pandemic, social support and provision of mental health services to prevent loneliness and consequent depression are required in patients with schizophrenia.

FMCW Radar Estimation Algorithm with High Resolution and Low Complexity Based on Reduced Search Area.

We propose a frequency-modulated continuous wave (FMCW) radar estimation algorithm with high resolution and low complexity. The fast Fourier transform (FFT)-based algorithms and multiple signal classification (MUSIC) algorithms are used as algorithms for estimating target parameters in the FMCW radar systems. FFT-based and MUSIC algorithms have tradeoff characteristics between resolution performance and complexity. While FFT-based algorithms have the advantage of very low complexity, they have the disadvantage of a low-resolution performance; that is, estimating multiple targets with similar parameters as a single target. On the other hand, subspace-based algorithms have the advantage of a high-resolution performance, but have a problem of very high complexity. In this paper, we propose an algorithm with reduced complexity, while achieving the high-resolution performance of the subspace-based algorithm by utilizing the advantages of the two algorithms; namely, the low-complexity advantage of FFT-based algorithms and the high-resolution performance of the MUSIC algorithms. The proposed algorithm first reduces the amount of data used as input to the subspace-based algorithm by using the estimation results obtained by FFT. Secondly, it significantly reduces the range of search regions considered for pseudo-spectrum calculations in the subspace-based algorithm. The simulation and experiment results show that the proposed algorithm achieves a similar performance compared with the conventional and low complexity MUSIC algorithms, despite its considerably lower complexity.

Comparison between Atomoxetine and OROS Methylphenidate as an Adjunctive to SSRIs in Attention-deficit/Hyperactivity Disorder Adults with Comorbid Partially Responsive Major Depressive Disorder: A Head-to-head, 12-week, Randomized, Rater-blinded Clinical Trial.

OBJECTIVE: This study aimed to compare the efficacy and safety of atomoxetine (ATX) and OROS methylphenidate (MPH) as adjunctive to selective serotonin reuptake inhibitors (SSRIs) in adults with attention-deficit hyperactivity disorder (ADHD) with comorbid partially responsive major depressive disorder (MDD). METHODS: Sixty Korean adults with ADHD and comorbid partially responsive MDD were recruited in a 12-week, randomized, rater-blinded, active-controlled trial and were evenly randomized to ATX or OROS MPH treatment. RESULTS: Depressive symptoms measured using the Hamilton Depression Rating Scale and Clinically Useful Depression Outcome Scale, and ADHD symptoms measured using the Adult ADHD Self-Report Scale, as well as the Clinical Global Impression-Severity, Clinical Global Impression-Improvement, and the Sheehan Disability Scale scores were significantly improved in both groups during the 12 weeks of treatment. The changes in all outcome measures during the 12-week treatment were not significantly different between the two groups (all p > 0.05). No serious adverse events were reported and there were no significant differences in systolic and diastolic blood pressure, pulse rate, weight, or body mass index between the ATX and MPH groups. CONCLUSION: Our findings suggest that ATX and MPH can be used as adjunctive treatments in adults with ADHD and comorbid partially responsive MDD. The efficacy and tolerability of ATX and MPH in adults with ADHD did not differ significantly. Further studies should be conducted to draw a definitive conclusion.

Reduced TREM2 activation in microglia of patients with Alzheimer's disease.

Loss-of-function variants of triggering receptor expressed on myeloid cells 2 (TREM2) increase the risk of developing Alzheimer's disease (AD). The mechanism through which TREM2 contributes to the disease (TREM2 activation vs inactivation) is largely unknown. Here, we analyzed changes in a gene set downstream of TREM2 to determine whether TREM2 signaling is modified by AD progression. We generated an anti-human TREM2 agonistic antibody and defined TREM2 activation in terms of the downstream expression changes induced by this antibody in microglia developed from human induced pluripotent stem cells (iPSC). Differentially expressed genes (DEGs) following TREM2 activation were compared with the gene set extracted from microglial single nuclear RNA sequencing data of patients with AD, using gene set enrichment analysis. We isolated an anti-TREM2-specific agonistic antibody, Hyb87, from anti-human TREM2 antibodies generated using binding and agonism assays, which helped us identify 300 upregulated and 251 downregulated DEGs. Pathway enrichment analysis suggested that TREM2 activation may be associated with Th2-related pathways. TREM2 activation was lower in AD microglia than in microglia from healthy subjects or patients with mild cognitive impairment. TREM2 activation also showed a significant negative correlation with disease progression. Pathway enrichment analysis of DEGs controlled by TREM2 activity indicated that TREM2 activation in AD may lead to anti-apoptotic signaling, immune response, and cytoskeletal changes in the microglia. We showed that TREM2 activation decreases with AD progression, in support of a protective role of TREM2 activation in AD. In addition, the agonistic anti-TREM2 antibody can be used to identify TREM2 activation state in AD microglia.

Effects of Neohesperidin Dihydrochalcone (NHDC) on Oxidative Phosphorylation, Cytokine Production, and Lipid Deposition.

The sweetener neohesperidin dihydrochalcone (NHDC) is a precursor for anthocyanins and has been reported to have various bioactivities, including antioxidant and hepatitis inhibitory effects. However, its inflammatory functions and mechanisms of action are poorly understood. In this study, RAW 264.7 murine macrophages were treated with NHDC and its metabolite dihydrocaffeic acid (DHCA), after which cytokine production and mitochondrial respiration were assessed. DHCA significantly down-regulated the secretion of pro-inflammatory cytokines. In contrast, NHDC had a marginal effect, suggesting that the biological metabolism of NHDC to DHCA is required for its anti-inflammatory function. However, both NHDC and DHCA rescued LPS-induced suppression of oxidative phosphorylation, which is a hallmark of anti-inflammatory M2 macrophages. 3T3-L1 adipocytes showed lower fat deposition in the presence of DHCA, while sugar-containing NHDC showed a slight increase in fat deposition. In high-fat diet-induced obese mice, treatment with NHDC successfully down-regulated body weight gain in a dose-dependent manner. Furthermore, M2 polarized bone-marrow-derived macrophages (BMDM) from NHDC-fed mice secreted an increased amount of the anti-inflammatory cytokine IL-10. Overall, these results indicate that NHDC and its physiological metabolite DHCA have the potential to suppress the inflammatory response and obese status.

Foot Gesture Recognition Using High-Compression Radar Signature Image and Deep Learning.

Recently, Doppler radar-based foot gesture recognition has attracted attention as a hands-free tool. Doppler radar-based recognition for various foot gestures is still very challenging. So far, no studies have yet dealt deeply with recognition of various foot gestures based on Doppler radar and a deep learning model. In this paper, we propose a method of foot gesture recognition using a new high-compression radar signature image and deep learning. By means of a deep learning AlexNet model, a new high-compression radar signature is created by extracting dominant features via Singular Value Decomposition (SVD) processing; four different foot gestures including kicking, swinging, sliding, and tapping are recognized. Instead of using an original radar signature, the proposed method improves the memory efficiency required for deep learning training by using a high-compression radar signature. Original and reconstructed radar images with high compression values of 90%, 95%, and 99% were applied for the deep learning AlexNet model. As experimental results, movements of all four different foot gestures and of a rolling baseball were recognized with an accuracy of approximately 98.64%. In the future, due to the radar's inherent robustness to the surrounding environment, this foot gesture recognition sensor using Doppler radar and deep learning will be widely useful in future automotive and smart home industry fields.

High-Efficiency Super-Resolution FMCW Radar Algorithm Based on FFT Estimation.

This paper proposes a high-efficiency super-resolution frequency-modulated continuous-wave (FMCW) radar algorithm based on estimation by fast Fourier transform (FFT). In FMCW radar systems, the maximum number of samples is generally determined by the maximum detectable distance. However, targets are often closer than the maximum detectable distance. In this case, even if the number of samples is reduced, the ranges of targets can be estimated without degrading the performance. Based on this property, the proposed algorithm adaptively selects the number of samples used as input to the super-resolution algorithm depends on the coarsely estimated ranges of targets using the FFT. The proposed algorithm employs the reduced samples by the estimated distance by FFT as input to the super resolution algorithm instead of the maximum number of samples set by the maximum detectable distance. By doing so, the proposed algorithm achieves the similar performance of the conventional multiple signal classification algorithm (MUSIC), which is a representative of the super resolution algorithms while the performance does not degrade. Simulation results demonstrate the feasibility and performance improvement provided by the proposed algorithm; that is, the proposed algorithm achieves average complexity reduction of 88% compared to the conventional MUSIC algorithm while achieving its similar performance. Moreover, the improvement provided by the proposed algorithm was verified in practical conditions, as evidenced by our experimental results.

Wireless Power Transfer and Telemetry for Implantable Bioelectronics.

Implantable bioelectronic devices are becoming useful and prospective solutions for various diseases owing to their ability to monitor or manipulate body functions. However, conventional implantable devices (e.g., pacemaker and neurostimulator) are still bulky and rigid, which is mostly due to the energy storage component. In addition to mechanical mismatch between the bulky and rigid implantable device and the soft human tissue, another significant drawback is that the entire device should be surgically replaced once the initially stored energy is exhausted. Besides, retrieving physiological information across a closed epidermis is a tricky procedure. However, wireless interfaces for power and data transfer utilizing radio frequency (RF) microwave offer a promising solution for resolving such issues. While the RF interfacing devices for power and data transfer are extensively investigated and developed using conventional electronics, their application to implantable bioelectronics is still a challenge owing to the constraints and requirements of in vivo environments, such as mechanical softness, small module size, tissue attenuation, and biocompatibility. This work elucidates the recent advances in RF-based power transfer and telemetry for implantable bioelectronics to tackle such challenges.