Global, Regional, and National Epidemiology of Alopecia Areata: A Systematic Review and Modelling Study.

BACKGROUND: Alopecia areata (AA) is a chronic autoimmune disease that leads to a high psychiatric, economic, and systemic disease burden. A comprehensive understanding of AA epidemiology is essential for evaluating healthcare source utilization; however, there is a lack of systematic approach for summarizing epidemiologic data on AA. OBJECTIVES: To systematically investigate the global, regional, and national incidence and prevalence of AA. METHODS: A structured search was conducted using the Ovid MEDLINE, EMBASE, Cochrane Library, Web of Science, SciELO, and Korean journal databases from their inception date to October 4, 2023. Studies that reported the prevalence or incidence of AA were included. We used a Bayesian hierarchical linear mixed model to analyse the prevalence estimates. The primary outcomes of our study were the global, regional, and national prevalence of physician-diagnosed AA for overall population, adults, and children. The incidence data were summarised descriptively. RESULTS: In total, 88 studies from 28 countries were included in the analysis. The reported incidence of alopecia areata tended to be higher in adults aged 19-50 years, and this trend was consistent with its estimated prevalence. The reported prevalence in overall population tended to be higher in men compared to in women. The estimated lifetime prevalence of AA was 0.10% (95% credible intervals, 0.03%-0.39%) in the general population worldwide, 0.12% (95% credible intervals, 0.02%-0.52%) in adults, and 0.03% (95% credible intervals, 0.01%-0.12%) in children. The estimated prevalence was highest in the Asian region and lowest in the African region. CONCLUSIONS: In this study, 48% of the total Global Burden of Disease regions had insufficient data reporting the prevalence or incidence of AA. Further studies are needed to provide epidemiological information on middle- and low-income countries. Our study can serve as a crucial reference in terms of healthcare policy decisions.

Triptycene Branched Poly(aryl-co-aryl piperidinium) Electrolytes for Alkaline Anion Exchange Membrane Fuel Cells and Water Electrolyzers.

Alkaline polymer electrolytes (APEs) are essential materials for alkaline energy conversion devices such as anion exchange membrane fuel cells (AEMFCs) and water electrolyzers (AEMWEs). Here, we report a series of branched poly(aryl-co-aryl piperidinium) with different branching agents (triptycene: highly-rigid, three-dimensional structure; triphenylbenzene: planar, two-dimensional structure) for high-performance APEs. Among them, triptycene branched APEs showed excellent hydroxide conductivity (193.5 mS cm-1 @80 °C), alkaline stability, mechanical properties, and dimensional stability due to the formation of branched network structures, and increased free volume. AEMFCs based on triptycene-branched APEs reached promising peak power densities of 2.503 and 1.705 W cm-2 at 75/100 % and 30/30 % (anode/cathode) relative humidity, respectively. In addition, the fuel cells can run stably at a current density of 0.6 A cm-2 for 500 h with a low voltage decay rate of 46 µV h-1 . Importantly, the related AEMWE achieved unprecedented current densities of 16 A cm-2 and 14.17 A cm-2 (@2 V, 80 °C, 1 M NaOH) using precious and non-precious metal catalysts, respectively. Moreover, the AEMWE can be stably operated under 1.5 A cm-2 at 60 °C for 2000 h. The excellent results suggest that the triptycene-branched APEs are promising candidates for future AEMFC and AEMWE applications.

Monocular depth estimation network with single-pixel depth guidance.

Due to the scale ambiguity problem, the performance of monocular depth estimation (MDE) is inherently restricted. Multi-camera systems, especially those equipped with active depth cameras, have addressed this problem at the expense of increased hardware costs and space. In this Letter, we adopt a similar but cost-effective solution using only single-pixel depth guidance with a single-photon avalanche diode. To this end, we design a single-pixel guidance module (SPGM) that combines the global information from the single-pixel depth guidance with the spatial information from the image at the feature level. By integrating SPGMs into an MDE network, we introduce PhoMoNet, the first, to the best of our knowledge, end-to-end MDE network with single-pixel depth guidance. Experimental results show the effectiveness and superiority of PhoMoNet over state-of-the-art MDE networks on synthetic and real-world datasets.

Deep Learning-Based Evaluation of Ultrasound Images for Benign Skin Tumors.

In this study, a combined convolutional neural network for the diagnosis of three benign skin tumors was designed, and its effectiveness was verified through quantitative and statistical analysis. To this end, 698 sonographic images were taken and diagnosed at the Department of Dermatology at Severance Hospital in Seoul, Korea, between 10 November 2017 and 17 January 2020. Through an empirical process, a convolutional neural network combining two structures, which consist of a residual structure and an attention-gated structure, was designed. Five-fold cross-validation was applied, and the train set for each fold was augmented by the Fast AutoAugment technique. As a result of training, for three benign skin tumors, an average accuracy of 95.87%, an average sensitivity of 90.10%, and an average specificity of 96.23% were derived. Also, through statistical analysis using a class activation map and physicians' findings, it was found that the judgment criteria of physicians and the trained combined convolutional neural network were similar. This study suggests that the model designed and trained in this study can be a diagnostic aid to assist physicians and enable more efficient and accurate diagnoses.

Marine Bacterioplankton Community Dynamics and Potentially Pathogenic Bacteria in Seawater around Jeju Island, South Korea, via Metabarcoding.

Understanding marine bacterioplankton composition and distribution is necessary for improving predictions of ecosystem responses to environmental change. Here, we used 16S rRNA metabarcoding to investigate marine bacterioplankton diversity and identify potential pathogenic bacteria in seawater samples collected in March, May, September, and December 2013 from two sites near Jeju Island, South Korea. We identified 1343 operational taxonomic units (OTUs) and observed that community diversity varied between months. Alpha- and Gamma-proteobacteria were the most abundant classes, and in all months, the predominant genera were Candidatus Pelagibacter, Leisingera, and Citromicrobium. The highest number of OTUs was observed in September, and Vibrio (7.80%), Pseudoalteromonas (6.53%), and Citromicrobium (6.16%) showed higher relative abundances or were detected only in this month. Water temperature and salinity significantly affected bacterial distribution, and these conditions, characteristic of September, were adverse for Aestuariibacter but favored Citromicrobium. Potentially pathogenic bacteria, among which Vibrio (28 OTUs) and Pseudoalteromonas (six OTUs) were the most abundant in September, were detected in 49 OTUs, and their abundances were significantly correlated with water temperature, increasing rapidly in September, the warmest month. These findings suggest that monthly temperature and salinity variations affect marine bacterioplankton diversity and potential pathogen abundance.

Rosmarinic Acid, as an NHE1 Activator, Decreases Skin Surface pH and Improves the Skin Barrier Function.

Stratum corneum (SC) pH regulates skin barrier functions and elevated SC pH is an important factor in various inflammatory skin diseases. Acidic topical formulas have emerged as treatments for impaired skin barriers. Sodium proton exchanger 1 (NHE1) is an important factor in SC acidification. We investigated whether topical applications containing an NHE1 activator could improve skin barrier functions. We screened plant extracts to identify NHE1 activators in vitro and found Melissa officinalis leaf extract. Rosmarinic acid, a component of Melissa officinalis leaf extract, significantly increased NHE1 mRNA expression levels and NHE1 production. Immunofluorescence staining of NHE1 in 3D-cultured skin revealed greater upregulation of NHE1 expression by NHE1 activator cream, compared to vehicle cream. Epidermal lipid analysis revealed that the ceramide level was significantly higher upon application of the NHE1 activator cream on 3D-cultured skin, compared to application of a vehicle cream. In a clinical study of 50-60-year-old adult females (n = 21), application of the NHE1 activator-containing cream significantly improved skin barrier functions by reducing skin surface pH and transepidermal water loss and increasing skin hydration, compared to patients who applied vehicle cream and those receiving no treatment. Thus, creams containing NHE1 activators, such as rosmarinic acid, could help maintain or recover skin barrier functions.

Zooming on dynamics of marine microbial communities in the phycosphere of Akashiwo sanguinea (Dinophyta) blooms.

Characterizing ecological relationships between viruses, bacteria and phytoplankton in the ocean is critical to understanding the ecosystem; however, these relationships are infrequently investigated together. To understand the dynamics of microbial communities and environmental factors in harmful algal blooms (HABs), we examined the environmental factors and microbial communities during Akashiwo sanguinea HABs in the Jangmok coastal waters of South Korea by metagenomics. Specific bacterial species showed complex synergistic and antagonistic relationships with the A. sanguinea bloom. The endoparasitic dinoflagellate Amoebophrya sp. 1 controlled the bloom dynamics and correlated with HAB decline. Among nucleocytoplasmic large DNA viruses (NCLDVs), two Pandoraviruses and six Phycodnaviruses were strongly and positively correlated with the HABs. Operational taxonomic units of microbial communities and environmental factors associated with A. sanguinea were visualized by network analysis: A. sanguinea-Amoebophrya sp. 1 (r = .59, time lag: 2 days) and A. sanguinea-Ectocarpus siliculosus virus 1 in Phycodnaviridae (0.50, 4 days) relationships showed close associations. The relationship between A. sanguinea and dissolved inorganic phosphorus relationship also showed a very close correlation (0.74, 0 day). Microbial communities and the environment changed dynamically during the A. sanguinea bloom, and the rapid turnover of microorganisms responded to ecological interactions. A. sanguinea bloom dramatically changes the environments by exuding dissolved carbohydrates via autotrophic processes, followed by changes in microbial communities involving host-specific viruses, bacteria and parasitoids. Thus, the microbial communities in HAB are composed of various organisms that interact in a complex manner.

Antarctic freshwater microalga, Chloromonas reticulata, suppresses inflammation and carcinogenesis.

Inflammation triggered by the innate immune system is a strategy to protect organisms from the risk of environmental infection. However, it has recently become clear that inflammation can cause a variety of human diseases, including cancer. In this study, we investigated the effects of an ethanol extract of the Antarctic freshwater microalgae, Chloromonas reticulata (ETCH), on inflammation and carcinogenesis in RAW 264.7 macrophages and HCT116 human colon cancer cells, respectively. ETCH exhibited significant anti-inflammatory activity through the dose-dependent modulation of major inflammatory markers such as COX-2, IL-6, iNOS, TNF-α, and NO production. For example, ETCH reduced LPS-induced upregulation of COX-2, IL-6, iNOS, and TNF- alpha mRNA levels, leading to a significant decrease in the levels of LPS-stimulated NO and IL-6 as well as TNF-alpha products. In contract, ETCH exhibited dose-dependent cytotoxic activity against HCT116 cells, yielding a profound reduction in the proliferation of the cancer cells. Furthermore, ETCH induced G2 phase cell cycle arrest by transcriptionally regulating of genes involved in G2 / M transition including p21 (CDKN1A), cyclin B1 (CCNB1), and CDK1; CDKN1A mRNA levels were upregulated in response to ETCH, whereas CCNB1 and CDK1 were downregulated. This study reports for the first time anti-inflammatory and anti-cancer effects of, C. reticulata and provides new insights into the molecular mechanisms of the linkage between inflammation and cancer.

Graph Cut-Based Human Body Segmentation in Color Images Using Skeleton Information from the Depth Sensor.

Segmentation of human bodies in images is useful for a variety of applications, including background substitution, human activity recognition, security, and video surveillance applications. However, human body segmentation has been a challenging problem, due to the complicated shape and motion of a non-rigid human body. Meanwhile, depth sensors with advanced pattern recognition algorithms provide human body skeletons in real time with reasonable accuracy. In this study, we propose an algorithm that projects the human body skeleton from a depth image to a color image, where the human body region is segmented in the color image by using the projected skeleton as a segmentation cue. Experimental results using the Kinect sensor demonstrate that the proposed method provides high quality segmentation results and outperforms the conventional methods.

Microdevice-based solid-phase polymerase chain reaction for rapid detection of pathogenic microorganisms.

We demonstrate the integration of DNA amplification and detection functionalities developed on a lab-on-a-chip microdevice utilizing solid-phase polymerase chain reaction (SP-PCR) for point-of-need (PON) DNA analyses. First, the polycarbonate microdevice was fabricated by thermal bonding  to contain microchambers as reservoirs for performing SP-PCR. Next, the microchambers were subsequently modified with polyethyleneimine and glutaraldehyde for immobilizing amine-modified forward primers. During SP-PCR, the immobilized forward primers and freely diffusing fluorescence-labeled reverse primers cooperated to generate target amplicons, which remained covalently attached to the microchambers for the fluorescence detection. The SP-PCR microdevice was used for the direct identifications of two widely detected foodborne pathogens, namely Salmonella spp. and Staphylococcus aureus, and an alga causing harmful algal blooms annually in South Korea, Cochlodinium polykrikoides. The SP-PCR microdevice would be versatilely applied in PON testing as a universal platform for the fast identification of foodborne pathogens and environmentally threatening biogenic targets.

Anti-inflammation and Anti-Cancer Activity of Ethanol Extract of Antarctic Freshwater Microalga, Micractinium sp.

Inflammation mediated by the innate immune system is an organism's protective mechanism against infectious environmental risk factors. It is also a driver of the pathogeneses of various human diseases, including cancer development and progression. Microalgae are increasingly being focused on as sources of bioactive molecules with therapeutic potential against various diseases. Furthermore, the antioxidant, anti-inflammatory, and anticancer potentials of microalgae and their secondary metabolites have been widely reported. However, the underlying mechanisms remain to be elucidated. Therefore, in this study, we investigated the molecular mechanisms underlying the anti-inflammatory and anticancer activities of the ethanol extract of the Antarctic freshwater microalga Micractinium sp. (ETMI) by several in vitro assays using RAW 264.7 macrophages and HCT116 human colon cancer cells. ETMI exerted its anti-inflammatory activity by modulating the main inflammatory indicators such as cyclooxygenase (COX)-2, interleukin (IL)-6, inducible nitric oxide synthase (iNOS), tumor necrosis factor (TNF)-α, and nitric oxide (NO) in a dose-dependent manner. In addition, ETMI exerted cytotoxic activity against HCT116 cells in a dose-dependent manner, leading to significantly reduced cancer cell proliferation. Further, it induced cell cycle arrest in the G1 phase through the regulation of hallmark genes of the G1/S phase transition, including CDKN1A, and cyclin-dependent kinase 4 and 6 (CDK4 and CDK6, respectively). At the transcriptional level, the expression of CDKN1A gradually increased in response to ETMI treatment while that of CDK4 and CDK6 decreased. Taken together, our findings suggest that the anti-inflammatory and anticancer activities of the Antarctic freshwater microalga, Micractinium sp., and ETMI may provide a new clue for understanding the molecular link between inflammation and cancer and that ETMI may be a potential anticancer agent for targeted therapy of colorectal cancer.

Combined Effects of UV Exposure Duration and Mechanical Abrasion on Microplastic Fragmentation by Polymer Type.

It is important to understand the fragmentation processes and mechanisms of plastic litter to predict microplastic production in the marine environment. In this study, accelerated weathering experiments were performed in the laboratory, with ultraviolet (UV) exposure for up to 12 months followed by mechanical abrasion (MA) with sand for 2 months. Fragmentation of low-density polyethylene (PE), polypropylene (PP), and expanded polystyrene (EPS) was evaluated under conditions that simulated a beach environment. PE and PP were minimally fragmented by MA without photooxidation by UV (8.7 ± 2.5 and 10.7 ± 0.7 particles/pellet, respectively). The rate of fragmentation by UV exposure duration increased more for PP than PE. A 12-month UV exposure and 2-month MA of PP and PE produced 6084 ± 1061 and 20 ± 8.3 particles/pellet, respectively. EPS pellets were susceptible to MA alone (4220 ± 33 particles/pellet), while the combination of 6 months of UV exposure followed by 2 months of MA produced 12,152 ± 3276 particles/pellet. The number of fragmented polymer particles produced by UV exposure and mechanical abrasion increased with decreasing size in all polymer types. The size-normalized abundance of the fragmented PE, PP, and EPS particles according to particle size after UV exposure and MA was predictable. Up to 76.5% of the initial EPS volume was unaccounted for in the final volume of pellet produced particle fragments, indicating that a large proportion of the particles had fragmented into undetectable submicron particles.

Stereo Vision-Based High Dynamic Range Imaging Using Differently-Exposed Image Pair.

In this paper, a high dynamic range (HDR) imaging method based on the stereo vision system is presented. The proposed method uses differently exposed low dynamic range (LDR) images captured from a stereo camera. The stereo LDR images are first converted to initial stereo HDR images using the inverse camera response function estimated from the LDR images. However, due to the limited dynamic range of the stereo LDR camera, the radiance values in under/over-exposed regions of the initial main-view (MV) HDR image can be lost. To restore these radiance values, the proposed stereo matching and hole-filling algorithms are applied to the stereo HDR images. Specifically, the auxiliary-view (AV) HDR image is warped by using the estimated disparity between initial the stereo HDR images and then effective hole-filling is applied to the warped AV HDR image. To reconstruct the final MV HDR, the warped and hole-filled AV HDR image is fused with the initial MV HDR image using the weight map. The experimental results demonstrate objectively and subjectively that the proposed stereo HDR imaging method provides better performance compared to the conventional method.

Effects of the algicide, thiazolidinedione derivative TD49, on microbial communities in a mesocosm experiment.

We investigated the effects of the algicide thiazolidinedione derivative TD49 on microbial community in mesocosm experiments. The TD49 concentration exponentially decreased over time, with half-life of 3.5 h, following addition in the seawater (R2=0.98, P<0.001). Among microbial communities, heterotrophic bacteria and heterotrophic nanoflagellates (HNFs) grew well in all treatments following the addition of TD49. The abundance of HNFs lagged behind the increase in heterotrophic bacteria by 24 h in the 0.2 and 0.4 µM TD49 concentrations (R2=0.28, P<0.05), and by 48 h in the 0.6 and 1.0 µM TD49 concentrations (R2=0.30, P<0.05). This implies a strong concentration-dependent top-down effect of TD49 on microbial communities, with indications that the degradation of planktonic organisms, including the target alga, led to high heterotrophic bacteria concentrations, which in turn stimulated the population growth of predatory HNF. However, total ciliate numbers remained relatively low in the TD49 treatments relative to the control and blank groups, suggesting limited carbon flow from bacteria to these grazers even though the abundance of aloricate ciliates gradually increased toward the end of the experimental period, particularly at the high TD49 concentrations. TD49 appears to provide an environmentally safe approach to the control of harmful algal blooms (HABs) in aquatic ecosystems.

Photometric stereo-based single time-of-flight camera.

We present a method to enhance depth quality of a time-of-flight (ToF) camera without additional devices or hardware modifications. By controlling the turn-off patterns of the LEDs of the camera, we obtain depth and normal maps simultaneously. Sixteen subphase images are acquired with variations in gate-pulse timing and light emission pattern of the camera. The subphase images allow us to obtain a normal map, which are combined with depth maps for improved depth details. These details typically cannot be captured by conventional ToF cameras. By the proposed method, the average of absolute differences between the measured and laser-scanned depth maps has decreased from 4.57 to 3.77 mm.

Nonuniform video size reduction for moving objects.

Moving objects of interest (MOOIs) in surveillance videos are detected and encapsulated by bounding boxes. Since moving objects are defined by temporal activities through the consecutive video frames, it is necessary to examine a group of frames (GoF) to detect the moving objects. To do that, the traces of moving objects in the GoF are quantified by forming a spatiotemporal gradient map (STGM) through the GoF. Each pixel value in the STGM corresponds to the maximum temporal gradient of the spatial gradients at the same pixel location for all frames in the GoF. Therefore, the STGM highlights boundaries of the MOOI in the GoF and the optimal bounding box encapsulating the MOOI can be determined as the local areas with the peak average STGM energy. Once an MOOI and its bounding box are identified, the inside and outside of it can be treated differently for object-aware size reduction. Our optimal encapsulation method for the MOOI in the surveillance videos makes it possible to recognize the moving objects even after the low bitrate video compressions.

Directional joint bilateral filter for depth images.

Depth maps taken by the low cost Kinect sensor are often noisy and incomplete. Thus, post-processing for obtaining reliable depth maps is necessary for advanced image and video applications such as object recognition and multi-view rendering. In this paper, we propose adaptive directional filters that fill the holes and suppress the noise in depth maps. Specifically, novel filters whose window shapes are adaptively adjusted based on the edge direction of the color image are presented. Experimental results show that our method yields higher quality filtered depth maps than other existing methods, especially at the edge boundaries.

A new human perception-based over-exposure detection method for color images.

To correct an over-exposure within an image, the over-exposed region (OER) must first be detected. Detecting the OER accurately has a significant effect on the performance of the over-exposure correction. However, the results of conventional OER detection methods, which generally use the brightness and color information of each pixel, often deviate from the actual OER perceived by the human eye. To overcome this problem, in this paper, we propose a novel method for detecting the perceived OER more accurately. Based on the observation that recognizing the OER in an image is dependent on the saturation sensitivity of the human visual system (HVS), we detect the OER by thresholding the saturation value of each pixel. Here, a function of the proposed method, which is designed based on the results of a subjective evaluation on the saturation sensitivity of the HVS, adaptively determines the saturation threshold value using the color and the perceived brightness of each pixel. Experimental results demonstrate that the proposed method accurately detects the perceived OER, and furthermore, the over-exposure correction can be improved by adopting the proposed OER detection method.

Reversed domain adaptation for nuclei segmentation-based pathological image classification.

Despite the fact that digital pathology has provided a new paradigm for modern medicine, the insufficiency of annotations for training remains a significant challenge. Due to the weak generalization abilities of deep-learning models, their performance is notably constrained in domains without sufficient annotations. Our research aims to enhance the model's generalization ability through domain adaptation, increasing the prediction ability for the target domain data while only using the source domain labels for training. To further enhance classification performance, we introduce nuclei segmentation to provide the classifier with more diagnostically valuable nuclei information. In contrast to the general domain adaptation that generates source-like results in the target domain, we propose a reversed domain adaptation strategy that generates target-like results in the source domain, enabling the classification model to be more robust to inaccurate segmentation results. The proposed reversed unsupervised domain adaptation can effectively reduce the disparities in nuclei segmentation between the source and target domains without any target domain labels, leading to improved image classification performance in the target domain. The whole framework is designed in a unified manner so that the segmentation and classification modules can be trained jointly. Extensive experiments demonstrate that the proposed method significantly improves the classification performance in the target domain and outperforms existing general domain adaptation methods.