The complete chloroplast genome sequence and phylogenetic analysis of Asplenium antiquum Makino 1929, an Endangered species in Korea.

Asplenium antiquum Makino 1929 is one of the Endangered endemic species on the Korean Peninsula. The complete chloroplast of A. antiquum is 150,690 bp in length with typical quadripartite structure comprised of large single-copy region of (83,166 bp), a small single copy region (21,932 bp), and two inverted repeat regions, each 22,796 bp in length. 114 genes were detected in the chloroplast genome of A. antiquum, comprising 84 protein-encoding genes, 26 tRNA genes, and 4 rRNA genes. The phylogenetic analysis revealed a monophyletic relationship, placing A. antiquum as a sister to voth A. Prolongatum and A. nidus, forming a subclade of Asplenium species within the Aspleniaceae family. The genomic data obtained from this study will serve as valuable information for the species' genetic classification of Asplenium.

Effects of extracorporeal shockwave therapy for mild knee osteoarthritis: A pilot study.

BACKGROUND: Extracorporeal shockwave therapy (ESWT) has been widely used for various musculoskeletal disorders, including knee osteoarthritis (OA), and has been shown in several studies to be a safe treatment. Although some studies have confirmed the pain-relieving effect of ESWT for knee OA, research on objectivity for structural changes in knee OA is lacking. The aim of this study was to evaluate the ESWT treatment mechanisms in patients with knee OA by means of clinical symptoms and ultrasound techniques as objective measures. METHODS: Eighteen patients with mild knee OA were enrolled and randomized to 1 of 2 treatment groups: active or sham. Patients in the experimental group received 0.05 mJ/mm² total energy with 1000 pulses weekly for 3 weeks. We then assessed them before, immediately after, and 1-month after the last treatment using the following measurements: pain on a visual analog scale, Western Ontario and McMaster Universities Osteoarthritis Index, Lequesne index, knee joint range of motion, and ultrasonographic features (articular cartilage thickness, Doppler activity, and joint effusion height). RESULTS: All 18 patients completed the 3 treatment sessions without any complication. Both the experimental and control groups improved in terms of OA symptoms, as measured by the visual analog scale, Western Ontario and McMaster Universities Osteoarthritis Index score, and Lequesne index (P < .05). The height of the suprapatellar effusion decreased with time course in the experimental group (P < .05) and showed significant differences with control group at 1-month follow-up (P < .05). The experimental group showed an increase in knee flexion range of motion and Doppler activity immediately following the last treatment session (P < .05), but the effect was not sustained at the 1-month follow-up. CONCLUSIONS: Although the therapeutic activity itself could improve OA symptoms, objective improvements were only observed after ESWT. Suprapatellar effusion height was reduced after ESWT and the effect was maintained after 1-month. Our results suggest that ESWT may be effective in reducing suprapatellar effusion and improving symptoms in mild knee OA. However, studies with a larger sample size are required.

2023 TAMIS/TSOC/TACVPR Consensus Statement for Patients with Acute Myocardial Infarction Rehabilitation.

Cardiac rehabilitation is a comprehensive intervention recommended in international and Taiwanese guidelines for patients with acute myocardial infarction. Evidence supports that cardiac rehabilitation improves the health-related quality of life, enhances exercise capacity, reduces readmission rates, and promotes survival in patients with cardiovascular disease. The cardiac rehabilitation team is comprehensive and multidisciplinary. The inpatient, outpatient, and maintenance phases are included in cardiac rehabilitation. All patients admitted with acute myocardial infarction should be referred to the rehabilitation department as soon as clinically feasible. Pre-exercise evaluation, including exercise testing, helps physicians identify the risks of cardiac rehabilitation and organize appropriate exercise prescriptions. Therefore, the Taiwan Myocardial Infarction Society (TAMIS), Taiwan Society of Cardiology (TSOC), and Taiwan Academy of Cardiovascular and Pulmonary Rehabilitation (TACVPR) address this consensus statement to assist healthcare practitioners in performing cardiac rehabilitation in patients with acute myocardial infarction.

Age-dependent effect of vitamin D supplementation on musculoskeletal health in chronic spinal cord injury patients: A pilot study.

OBJECTIVE: To determine the effect of vitamin D supplementation on changes in body composition associated with musculoskeletal health status in patients with chronic SCI and vitamin D deficiency as a response to age. DESIGN: Prospective drug-intervention study. SETTING: Department of rehabilitation medicine, Veterans Health Service Medical Center. PARTICIPANTS: Seventeen patients with vitamin D insufficiency/deficiency (<30 ng/mL) and chronic SCI were divided into two groups: groups A <65 years (n = 8) and B ≥65 years of age (n = 9). INTERVENTIONS: Both groups received 800 IU/day cholecalciferol for 12 weeks. OUTCOME MEASURES: We used blood samples to evaluate metabolites related to vitamin D, testosterone (T), lipid profiles, and sex hormone-binding globulin (SHBG). Bioelectrical impedance analysis (BIA) was used to evaluate body composition. RESULTS: Group A had significantly better baseline clinical characteristics for all BIA measurements. SHGB was significantly higher in Group B (P = 0.003) and albumin was significantly higher in Group A (P = 0.000). When comparing pre- to post-treatment, Group A showed a significant improvement in T (P = 0.042), total cholesterol (P = 0.035), and triglyceride (P = 0.025) levels, whereas Group B significantly increased vitamin D (P = 0.038) and protein mass (PM) (P = 0.034) levels. CONCLUSION: This study suggested that addressing vitamin D deficiency in patients with SCI had different effects in young and older adults, with both groups showing positive changes in body composition. Particularly, the increase in PM on BIA measurements in elderly patients at high risk of sarcopenia was encouraging.

Psoriasis severity classification based on adaptive multi-scale features for multi-severity disease.

Psoriasis is a skin disease that causes lesions of various sizes across the body and can persist for years with cyclic deterioration and improvement. During treatment, and a multiple-severity disease, with irregular severity within the observation area may be found. The current psoriasis evaluation is based on the subjective evaluation criteria of the clinician using the psoriasis area and severity index (PASI). We proposed a novel psoriasis evaluation method that detects representative regions as evaluation criteria, and extracts severity features to improve the evaluation performance of various types of psoriasis, including multiple-severity diseases. We generated multiple-severity disease images using CutMix and proposed a hierarchical multi-scale deformable attention module (MS-DAM) that can adaptively detect representative regions of irregular and complex patterns in multiple-severity disease analyses. EfficientNet B1 with MS-DAM exhibited the best classification performance with an F1-score of 0.93. Compared with the performance of the six existing self-attention methods, the proposed MS-DAM showed more than 5% higher accuracy than that of multiscale channel attention module (MS-CAM). Using the gradient-weighted activation mapping method, we confirmed that the proposed method works at par with human visual perception. We performed a more objective, effective, and accurate analysis of psoriasis severity using the proposed method.

Clinical characteristics and outcomes of Clostridioides difficile infection in the intensive care unit: a KASID multi-centre study.

BACKGROUND: Despite the growing clinical and economic burden of Clostridioides difficile infection (CDI), data on CDI in the intensive care unit (ICU) in the Asia-Pacific region are lacking. METHODS: This retrospective study analysed 191 patients who were treated with CDI in the ICUs of three hospitals in South Korea from January 2017 to May 2021. Backward-stepwise multiple logistic regression was used to identify factors influencing the treatment response and mortality. RESULTS: Fifty-eight patients (30.4%) were considered immunocompromised. The mean Charlson comorbidity index was 5.65 ± 2.39 (10-year survival rate: 21%), the APACHE II score was 20.86 ± 7.78 (mortality rate: 40%), the ATLAS score was 5.45 ± 1.59 (cure rate: 75%), and the SOFA score was 7.97 ± 4.03 (mortality rate: 21.5%). Fifty-eight (30.4%) of the CDI cases were severe and 40 (20.9%) were fulminant. Oral vancomycin or oral metronidazole was the most frequently first-line treatments (N = 57; 32.6%). The 10-day response rate was 59.7% and the eight-week overall mortality rate was 41.4%. Fulminant CDI (OR 0.230; 95% CI 0.085-0.623) and each one-unit increment in the SOFA score (OR 0.848; 95% CI 0.759-0.947) were associated with treatment failure. High APACHE II (OR 0.355; 95% CI 0.143-0.880) and SOFA (OR 0.164; 95% CI 0.061-0.441) scores were associated with higher mortality. CONCLUSIONS: High-risk patients in the ICU had a higher mortality rate and a lower cure rate of CDI. Further research is required to provide more accurate prediction scoring systems and better clinical outcomes.

Measurement of Direct-Photon Cross Section and Double-Helicity Asymmetry at sqrt[s]=510 GeV in p[over →]+p[over →] Collisions.

We present measurements of the cross section and double-helicity asymmetry A_{LL} of direct-photon production in p[over →]+p[over →] collisions at sqrt[s]=510 GeV. The measurements have been performed at midrapidity (|η|<0.25) with the PHENIX detector at the Relativistic Heavy Ion Collider. At relativistic energies, direct photons are dominantly produced from the initial quark-gluon hard scattering and do not interact via the strong force at leading order. Therefore, at sqrt[s]=510 GeV, where leading-order-effects dominate, these measurements provide clean and direct access to the gluon helicity in the polarized proton in the gluon-momentum-fraction range 0.02

Transformer-based multi-task learning for classification and segmentation of gastrointestinal tract endoscopic images.

Despite being widely utilized to help endoscopists identify gastrointestinal (GI) tract diseases using classification and segmentation, models based on convolutional neural network (CNN) have difficulties in distinguishing the similarities among some ambiguous types of lesions presented in endoscopic images, and in the training when lacking labeled datasets. Those will prevent CNN from further improving the accuracy of diagnosis. To address these challenges, we first proposed a Multi-task Network (TransMT-Net) capable of simultaneously learning two tasks (classification and segmentation), which has the transformer designed to learn global features and can combine the advantages of CNN in learning local features so that to achieve a more accurate prediction in identifying the lesion types and regions in GI tract endoscopic images. We further adopted the active learning in TransMT-Net to tackle the labeled image-hungry problem. A dataset was created from the CVC-ClinicDB dataset, Macau Kiang Wu Hospital, and Zhongshan Hospital to evaluate the model performance. Then, the experimental results show that our model not only achieved 96.94% accuracy in the classification task and 77.76% Dice Similarity Coefficient in the segmentation task but also outperformed those of other models on our test set. Meanwhile, active learning also produced positive results for the performance of our model with a small-scale initial training set, and even its performance with 30% of the initial training set was comparable to that of most comparable models with the full training set. Consequently, the proposed TransMT-Net has demonstrated its potential performance in GI tract endoscopic images and it through active learning can alleviate the shortage of labeled images.

CLELNet: A continual learning network for esophageal lesion analysis on endoscopic images.

BACKGROUND AND OBJECTIVE: A deep learning-based intelligent diagnosis system can significantly reduce the burden of endoscopists in the daily analysis of esophageal lesions. Considering the need to add new tasks in the diagnosis system, a deep learning model that can train a series of tasks incrementally using endoscopic images is essential for identifying the types and regions of esophageal lesions. METHOD: In this paper, we proposed a continual learning-based esophageal lesion network (CLELNet), in which a convolutional autoencoder was designed to extract representation features of endoscopic images among different esophageal lesions. The proposed CLELNet consists of shared layers and task-specific layers. Shared layers are used to extract common features among different lesions while task-specific layers can complete different tasks. The first two tasks trained by the CLELNet are the classification (task 1) and the segmentation (task 2). We collected a dataset of esophageal endoscopic images from Macau Kiang Wu Hospital for training and testing the CLELNet. RESULTS: The experimental results showed that the classification accuracy of task 1 was 95.96%, and the Intersection Over Union and the Dice Similarity Coefficient of task 2 were 65.66% and 78.08%, respectively. CONCLUSIONS: The proposed CLELNet can realize task-incremental learning without forgetting the previous tasks and thus become a useful computer-aided diagnosis system in esophageal lesions analysis.

Robust skin microrelief depth estimation using a mobile stereo system.

BACKGROUND: The skin surface becomes wrinkled and rough due to various internal and external factors. A three-dimensional (3D) analysis of the skin is required to improve skin conditions. Stereophotogrammetry, a noninvasive 3D analysis method, is easy to install and use, but most stereo systems have a fixed baseline and scale. Previous stereo systems are not suitable for observing micro-range skin features. Therefore, we suggest the optimal conditions and methods for the 3D analysis of skin microrelief using a multi-conditioned stereo system. METHODS: We constructed a nonconvergence model using a mobile device and acquired stereo images under multiscale and multi-baseline conditions. We extracted 3D information of the skin through our process: preprocessing, skin feature extraction, feature matching, and actual depth mapping. We improved the accuracy of the 3D analysis of the skin by using disparity values instead of disparity maps. We compared and analyzed the performances of six local feature detector and descriptor algorithms. In addition, we suggested depth-mapping formulas to estimate the actual depth of the skin microrelief. RESULTS: We confirmed that stereo images with a working distance of 70-75 mm and a baseline of 4-8 mm are effective for the 3D analysis of skin microrelief. In addition, accelerated KAZE exhibited the best performance for features extraction and stereo matching. Finally, the extracted 3D information was converted to the actual depth, and the performance of the 3D analysis was verified. CONCLUSION: The proposed system and method that provide texture information are effective for 3D skin disease analysis and evaluation.

Automatic analysis system for abnormal red blood cells in peripheral blood smears.

The type and ratio of abnormal red blood cells (RBCs) in blood can be identified through peripheral blood smear test. Accurate classification is important because the accompanying diseases indicated by abnormal RBCs vary. In clinical practice, this task is time-consuming because the RBCs are manually classified. In addition, because the classification depends on the subjective criteria of pathologists, objective classification is difficult to achieve. In this paper, an automatic classification method that is solely based on images of RBCs captured under a microscope and processed using machine learning (ML) is proposed. The size and hemoglobin abnormalities of RBCs were classified by optimizing the criteria used in clinical practice. For morphologically abnormal RBCs classification, used seven geometric features information (major axis, minor axis, ratio of major and minor axis, perimeter, circularity, number of convex hulls, difference between area and convex area) and five types of multiple classifiers (Support Vector Machine, Decision Tree, K-Nearest Neighbor, Random Forest, and Adaboost models). Among was categorized using SVM, highly accurate results (99.9%) were obtained. The classification is performed simultaneously, and results are provided to the user through a graphical user interface (GUI).

In vitro mitochondrial apoptosis of melanoma cells via immature Poncirus trifoliata fruit extract.

OBJECTIVE: Poncirus trifoliata (P. trifoliata) fruits exert phytotherapeutic effects, depending on their maturity level. However, the mechanism by which these phytotherapeutic effects are exerted remains undefined - especially in cancers. Therefore, in this study, we investigated the effects of the immature fruit extract of P. trifoliata on a B16 melanoma cell line. MATERIALS AND METHODS: The effect of immature P. trifoliata extract on B16 cells was evaluated by MTT assay, cell proliferation, FACScan analysis of cell cycles, confocal imaging analysis, nuclear (Hoechst) staining, apoptosis assay (Annexin V-fluorescein isothiocyanate/propidium iodide staining), and Western blot assay. The capacity of immature P. trifoliata extract to inhibit the invasion and migration of B16 cells was assessed using the scratch-wound assay and Matrigel migration assay. The effect of immature P. trifoliata extract on mitochondrial function was determined via the mitochondrial membrane potential assay, activity, and fraction and cytosol proteins. RESULTS: Treating B16 cells with a methanol extract of immature P. trifoliata (MEPT) significantly inhibited cell viability, migration, and invasiveness in a dose- (p<0.01) and time (p<0.01)- dependent manner. MEPT arrested the cells in the G1 phase of the cell cycle and led to the activation of the PI3K/AKT/p21 pathway. Furthermore, MEPT dose-dependently induced apoptosis in B16 cells by increasing the expression of the pro-apoptotic proteins Bax and Apaf-1, while decreasing the expression of the anti-apoptotic protein, Bcl-2. MEPT treatment also decreased mitochondrial membrane potential. CONCLUSIONS: Immature P. trifoliata extract inhibited the growth of melanoma cells by inducing cell apoptosis through mitochondrial pathways. Therefore, further research into immature P. trifoliata extract as a potential therapeutic compound for melanoma treatment is warranted.

Low-shear modeled microgravity affects metabolic networks of Escherichia coli O157:H7 EDL933: Further insights into space-microbiology consequences.

Escherichia coli O157:H7 EDL933 exposed to low-shear modeled microgravity (LSMMG) and normal gravity (NG) was used for a transcriptomic analysis. The modified Gompertz model (R2 = 0.81-0.99) showed an increased growth rate of E. coli O157:H7 under LSMMG. The mechanism of this active growth was associated with highly upregulated genes in nutrient and energy metabolism, including the TCA cycle, glycolysis, and pyruvate metabolism. Green fluorescent protein-labeled E. coli O157:H7 also formed significantly thick biofilms (fluorescent unit: NG, 1,263; LSMMG, 1,533; P = 0.0473) under LSMMG, whereas bacterial mobility decreased slightly (P = 0.0310). The transcriptomic analysis revealed that genes encoding glycogen biosynthesis (glgCAP operon) were upregulated (1.40 to 1.82 of log fold change [FC]) due to the downregulation of csrA (2.17 of log FC), which is the global regulator of biofilm formation of E. coli. We also identified 52 genes in E. coli O157:H7 EDL933 that were involved in the secretion pathway, 32 of which showed ≥2-fold significant changes in transcription levels after cultivation under LSMMG. Notably, all downregulated genes belonged to the type III and VI secretion systems, indicating that host cell contact secretion was dysregulated in the LSMMG cultures compared to the NG cultures. LSMMG also stimulates the pathogenicity of E. coli O157:H7 via transcriptional upregulation of Shiga toxin 1 (1.36 to 2.81 log FC) and toxin HokB (6.1 log FC). Our results suggest LSMMG affects bacterial growth, biofilm formation, and E. coli O157:H7 pathogenicity at some transcriptional levels, which indicates the importance of understanding biological consequences.

Diagnosis of Esophageal Lesions by Multi-Classification and Segmentation Using an Improved Multi-Task Deep Learning Model.

It is challenging for endoscopists to accurately detect esophageal lesions during gastrointestinal endoscopic screening due to visual similarities among different lesions in terms of shape, size, and texture among patients. Additionally, endoscopists are busy fighting esophageal lesions every day, hence the need to develop a computer-aided diagnostic tool to classify and segment the lesions at endoscopic images to reduce their burden. Therefore, we propose a multi-task classification and segmentation (MTCS) model, including the Esophageal Lesions Classification Network (ELCNet) and Esophageal Lesions Segmentation Network (ELSNet). The ELCNet was used to classify types of esophageal lesions, and the ELSNet was used to identify lesion regions. We created a dataset by collecting 805 esophageal images from 255 patients and 198 images from 64 patients to train and evaluate the MTCS model. Compared with other methods, the proposed not only achieved a high accuracy (93.43%) in classification but achieved a dice similarity coefficient (77.84%) in segmentation. In conclusion, the MTCS model can boost the performance of endoscopists in the detection of esophageal lesions as it can accurately multi-classify and segment the lesions and is a potential assistant for endoscopists to reduce the risk of oversight.

Communicating Personal Risk Profiles of Alzheimer's Disease to Older Adults: A Pilot Trial.

Communicating personal Alzheimer's disease risk profiles based on validated risk algorithms may improve public knowledge about risk reduction, and initiate action. This proof of concept pilot trial aimed to test whether this is feasible and potentially effective and/or harmful. Older at-risk adults (N=24) were provided with their personal Alzheimer's disease risk profile online, which contained information on their personal risk level, scores and tailored recommendations to manage modifiable risk factors. After receiving the risk profile, participants were significantly more accurate in identifying risk and protective factors, and revised their perceived risk to be lower than their initial estimate. There was no apparent harm seen in psychological distress or dementia-related worry. This shows preliminary support for the feasibility of delivering personal dementia risk profiles to low risk, help-seeking older adults in an online format. A definitive trial examining behavioural outcomes and testing in groups with higher risk profiles is now warranted.

Probing Gluon Spin-Momentum Correlations in Transversely Polarized Protons through Midrapidity Isolated Direct Photons in p

Studying spin-momentum correlations in hadronic collisions offers a glimpse into a three-dimensional picture of proton structure. The transverse single-spin asymmetry for midrapidity isolated direct photons in p^{↑}+p collisions at sqrt[s]=200 GeV is measured with the PHENIX detector at the Relativistic Heavy Ion Collider (RHIC). Because direct photons in particular are produced from the hard scattering and do not interact via the strong force, this measurement is a clean probe of initial-state spin-momentum correlations inside the proton and is in particular sensitive to gluon interference effects within the proton. This is the first time direct photons have been used as a probe of spin-momentum correlations at RHIC. The uncertainties on the results are a 50-fold improvement with respect to those of the one prior measurement for the same observable, from the Fermilab E704 experiment. These results constrain gluon spin-momentum correlations in transversely polarized protons.

Optimization of psoriasis assessment system based on patch images.

Psoriasis is a chronic inflammatory skin disease that occurs in various forms throughout the body and is associated with certain conditions such as heart disease, diabetes, and depression. The psoriasis area severity index (PASI) score, a tool used to evaluate the severity of psoriasis, is currently used in clinical trials and clinical research. The determination of severity is based on the subjective judgment of the clinician. Thus, the disease evaluation deviations are induced. Therefore, we propose optimal algorithms that can effectively segment the lesion area and classify the severity. In addition, a new dataset on psoriasis was built, including patch images of erythema and scaling. We performed psoriasis lesion segmentation and classified the disease severity. In addition, we evaluated the best-performing segmentation method and classifier and analyzed features that are highly related to the severity of psoriasis. In conclusion, we presented the optimal techniques for evaluating the severity of psoriasis. Our newly constructed dataset improved the generalization performance of psoriasis diagnosis and evaluation. It proposed an optimal system for specific evaluation indicators of the disease and a quantitative PASI scoring method. The proposed system can help to evaluate the severity of localized psoriasis more accurately.

Immune response to hepatitis B vaccination and factors associated with poor immune response among healthcare workers.

BACKGROUND: Hepatitis B virus (HBV) infection is a major global health problem, and healthcare workers (HCWs) are at high risk for HBV infection. Current guidelines strongly recommend immunization and screening for high-risk groups. AIMS: We evaluated immunization and screening for HBV vaccination, assessed post-vaccination immune status of HCW's and characterized potential risk factors associated with poor immune response. MATERIALS AND METHODS: From January 2010 to December 2018, we retrospectively analyzed comprehensive health checkup data for a total of 303 HCWs who received an HBV vaccination. After vaccination, HBV surface antibody (anti-HBs) titers were collected and the distribution of immune response types was determined. Risk factors for poor immune responses were identified using logistic regression. RESULTS: A total of 213 HCWs were analyzed after exclusion based on the exclusion criteria. In total, 28 (13.2%) HCWs had anti-HBs titers <100 mIU/mL (hyporesponsive/nonresponsive groups), and 185 (86.8%) had anti-HBs titers ≥100 mIU/mL (hyperresponsive group). Follow-up observations found that 75% (21/28) of the hyporesponsive/nonresponsive groups did not have increased anti-HBs titers or did not maintain an increased response. A multivariate analysis showed that HBV antibody titers at the time of employment were a significant risk factor (OR, 6.12; CI, 1.34-27.93; P = 0.019). CONCLUSIONS: More attention should be paid to groups that are hyporesponsive/nonresponsive after vaccination and to those with low anti-HBs titers at the beginning of employment. HCWs can be further protected from HBV if their results are discussed at postvaccination follow-ups.