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Abstract In patients with gastroesophageal reflux disease (GERD) whose symptoms improve with acid-suppression therapy, on-demand treatment could constitute maintenance therapy. This study investigated the comparative efficacy and safety of on-demand tegoprazan and proton-pump inhibitor (PPI) therapy in GERD. From six university hospitals in the Daejeon-Chungcheong region, we enrolled patients with GERD who had experienced symptomatic improvement with acid-suppressive therapy and, using a randomization table, randomly allocated these participants to two groups: to receive either tegoprazan 50 mg + esomeprazole placebo or tegoprazan placebo + esomeprazole 20 mg, respectively. The primary endpoint of this study was the intergroup difference in patient satisfaction with on-demand therapy. Among the 69 participants who completed 8 weeks of on-demand therapy and rated patient satisfaction on a 5-point Likert scale, the tegoprazan and esomeprazole groups scored an average of 4.31 and 4.15 points, respectively, without any significant intergroup difference. In the tegoprazan group, 26.2% (182/694) of those with episodes experienced symptom improvement within 30 min, which is a significantly higher proportion compared to 16.1% (104/646) in the esomeprazole group. Compared to the esomeprazole group, the tegoprazan group had a significantly shorter time to symptom improvement overall and a significantly higher proportion of patients who improved within 30 min. No serious treatment-emergent adverse events were reported. Tegoprazan is effective as on-demand therapy for GERD and offers the expectation of faster symptom improvement than with PPIs. Clinical trial KCT0009296, registered at cris.nih.go.kr.

The natural circulation system has been widely studied for use in various applications because of its inherent advantage. However, it has a key weakness called flow instability that makes the system unstable. Through massive previous research, the mechanisms of flow instability were analyzed, but there was an ambiguous aspect related to the effect of experimental parameters on the phenomenon. Particularly, there has been no report on the heat transfer performance of the system when flow instability phenomena were present. In this study, thermal-hydraulic phenomena of a two-phase natural circulation system that functions as a passive containment cooling system (PCCS) was investigated according to experimental parameters, namely, the temperature boundary (120–158 °C) and exit loss coefficient (0–34.5) under atmospheric pressure conditions. The experimental results showed five different flow types in the loop. The flow modes that occurred by the interaction between flashing and boiling were classified by referring to the mass flow rate, void fraction, and visualization data. The system was more unstable when the temperature boundary conditions increased, but it was more stable when the exit loss coefficient increased. These results have only been confirmed in our research. The reason for the results is that the flow conditions are located on the boundary between Density Wave Oscillation I and the stable flow region, and that boundary does not have clear criteria. In addition, comparing the heat transfer performance of a system by heat rate can confirm the effect of flow instability on the thermal performance of the passive cooling system. As a result, the high exit loss coefficient stabilizes the system better than the low case and has similar heat removal performance.

Abstract Background An estimated 30% of patients with epilepsy experience drug-resistant epilepsy, which is the failure to control seizures despite the use of two or more antiseizure medications. Although other treatment options are considered, these alternatives often prove ineffective. Case presentation A 60-year-old East Asian male patient diagnosed with drug-resistant epilepsy experienced several seizures daily despite being on eight different antiseizure medications. Seizures began at age 15. He underwent epilepsy surgery at age 34, yet the seizures persisted. An electroencephalogram revealed multifocal sharp waves in the left hemisphere. Cerebral hemorrhages at ages 47, 50, and 56 were caused by head trauma during seizures. The patient became wheelchair-bound and now resides in a nursing home. At age 58, after suffering an acute cerebral infarction due to occlusion of the left internal carotid artery, his daily seizures ceased entirely. Despite remaining wheelchair-bound, he did not experience a significant decline in his quality of life. The cessation of seizures has reduced his risk of further trauma, and he has remained seizure-free for 3 years on just one antiseizure medication. Conclusion Surgical treatments for epilepsy often fail, with insufficient resection being a leading cause of these failures. In some cases, extensive destruction from an ischemic stroke may be beneficial. Furthermore, this case suggests that infarction therapy could be a potential treatment for patients with drug-resistant epilepsy.

Purpose Mastering the skill of smashing in a game can be quite challenging. Unfortunately, it’s not always easy to control the distance of the smash. The present study investigated the impact of different smashing distances on muscle activation patterns and kinematics of the upper limbs. Material and methods Ten collegiate athletes from a top-ranked team in Korea participated in the present study with a mean age, weight, and height of 21 ± 1 years, 71.9 ± 9.1 kg, and 1.78 ± 2.24 m, respectively. Three valid data points for each subject at three different distances were analyzed using a one-way analysis of variance (ANOVA). Results The results demonstrated that with increasing smashing distance, the internal rotation angle of the elbow and wrist joints decreased, while the angular velocity of flexion and internal rotation of the shoulder, elbow, and wrist joints increased. Muscle activation increased for all muscles except the biceps brachii (BICLO) with increasing distance. The greatest changes in activation levels were observed in the anterior deltoid (DELTA), extensor carpi radialis (ECR), and flexor carpi ulnaris (FCU). Conclusions During tasks with different smashing distances, muscle activation in the upper limbs (except the biceps) increased with increasing distances. Additionally, the internal rotation angle of the upper limbs decreased with increased distances, while the angular velocity of flexion and internal rotation of the shoulder, elbow, and wrist joints increased.

Obstructed hemivagina and ipsilateral renal agenesis (OHVIRA), also called Herlyn–Werner–Wunderlich syndrome, is an extremely rare Müllerian duct anomaly accompanied by Wolffian duct anomalies. A 10-year-old intact female Yorkshire Terrier weighing 3.35 kg was presented with anorexia, depression, vomiting, and abdominal pain. Radiography, ultrasonography, and computed tomography revealed uterine didelphys, obstructed hemivagina, a cystic structure around the right uterus, and right renal agenesis, leading to the diagnosis of OHVIRA syndrome. An ovariohysterectomy and decompression of the obstructed right hemivagina were performed, and the cystic structure near the right uterine horn was removed by en bloc resection, along with the right uterus and ovary. After the surgical intervention, the patient’s symptoms including abdominal pain, anorexia, and depression were immediately resolved. The patient was followed up for 1 month postoperatively with ultrasonography at 2-week intervals, which revealed the progression of mild fluid retention in the right hemivagina. However, no additional urogenital findings were identified, and the patient continued to exhibit no overt clinical symptoms. This case report describes the diagnosis and surgical treatment of the first documented case of OHVIRA syndrome in an animal. Unlike in human medicine, where vaginal septectomy is performed to prevent dilatation of the obstructed hemivagina and thereby resolve clinical symptoms, performing ovariohysterectomy combined with fluid aspiration from the obstructed hemivagina showed a favorable postoperative prognosis in the dog.

Huanglongbing (HLB; citrus greening) and citrus canker are invasive diseases afflicting Florida citrus groves, causing financial losses through yield loss, smaller fruit, blemishes, premature fruit drop and/or eventual tree death. Often, symptoms of these diseases resemble those of other disease or disorders. Early detection of HLB and canker via in-grove leaf inspection can permit more effective mitigation tactics and management of groves. Autonomous, vision-based disease scouting in a grove offers a financial benefit to the Florida citrus industry. This study investigates the potential of hyperspectral reflectance imagery (HSI) for detecting and classifying these conditions in the presence of other, less consequential leaf defects. Leaves with visible symptoms of HLB, canker, zinc deficiency, scab, melanose, greasy spot, and a control set were collected and both sides were imaged with a line-scan hyperspectral camera. Spectral bands from this imagery were selected using two methods: an unsupervised method based on principal component analysis (PCA), a supervised method based on linear discriminant analysis (LDA), which were compared with randomly selected bands as a control. The YOLOv8 network architecture was trained to classify each side of these leaves with each band combination. LDA-selected bands from the front of the leaves yielded an overall classification accuracy of 87.09 %, with higher recall of melanose and precision of control than any other model tested. Leaves with HLB and zinc deficiency were classified most accurately, with both band selection methods yielding F1 scores of at least 0.955 and 0.934, respectively. These findings favor the use of supervised band selection for HSI-based in-grove disease detection.

Citrus Black Spot (CBS), caused by the pathogenic fungus Phyllosticta citricarpa, is a quarantine citrus disease, that has the potential to spread on nursery tress especially in regions like Florida and beyond. The early detection of this disease assumes paramount importance, especially during the asymptomatic phase of tree infection. This critical stage offers a window of opportunity for grove managers to implement preemptive measures, thereby mitigating the potential dissemination of the infection within orchards. In the present study, we elucidate the robust capabilities of the Contamination Sanitization Inspection-Disinfection Plus (CSI-D+) system, which integrates state-of-the-art fluorescence imaging technology, in tandem with the YOLOv8 deep learning framework. Our investigation is centered on the direct detection of conidia of the CBS-causing fungus P. citricarpa (Gc12) and its non-pathogenic counterpart P. capitalensis (Gm33), both prevalent on surfaces of infected citrus leaves across varying concentration gradients. Impressively, the CSI-D+ system (which is a new, handheld fluorescence-based imaging device developed to detect microbial contamination and disinfect surfaces rapidly) exhibits remarkable discriminatory acumen, achieving a noteworthy mean classification accuracy of 96.97 % for Gc12 fungus classification. This precision is complemented by an impressive F1-score of 96.35 %, coupled with a commendable mAP@50 score of 97.82 %. Furthermore, our inquiry extends to encompass the Gm33 variant, wherein the system maintains a commendable average classification accuracy of 96.17 %, alongside an F1-score of 88.76 %, and a mAP@50 of 91.64 %. Such pioneering systems bear substantial promise, serving as a rapid, non-invasive instrument for the early identification of incipient CBS infestations within citrus arboreal landscapes. In equipping grove managers with timely insights, these advancements stand to empower effective and timely intervention strategies, fortifying orchard resilience against the progression of this pathogenic menace.

BackgroundFHIR (Fast Healthcare Interoperability Resources) has been proposed to enable health data interoperability. So far, its applicability has been demonstrated for selected research projects with limited data. ObjectiveThis study aimed to design and implement a conceptual medical intelligence framework to leverage real-world care data for clinical decision-making. MethodsA Python package for the use of multimodal FHIR data (FHIRPACK [FHIR Python Analysis Conversion Kit]) was developed and pioneered in 5 real-world clinical use cases, that is, myocardial infarction, stroke, diabetes, sepsis, and prostate cancer. Patients were identified based on the ICD-10 (International Classification of Diseases, Tenth Revision) codes, and outcomes were derived from laboratory tests, prescriptions, procedures, and diagnostic reports. Results were provided as browser-based dashboards. ResultsFor 2022, a total of 1,302,988 patient encounters were analyzed. (1) Myocardial infarction: in 72.7% (261/359) of cases, medication regimens fulfilled guideline recommendations. (2) Stroke: out of 1277 patients, 165 received thrombolysis and 108 thrombectomy. (3) Diabetes: in 443,866 serum glucose and 16,180 glycated hemoglobin A1c measurements from 35,494 unique patients, the prevalence of dysglycemic findings was 39% (13,887/35,494). Among those with dysglycemia, diagnosis was coded in 44.2% (6138/13,887) of the patients. (4) Sepsis: In 1803 patients, Staphylococcus epidermidis was the primarily isolated pathogen (773/2672, 28.9%) and piperacillin and tazobactam was the primarily prescribed antibiotic (593/1593, 37.2%). (5) PC: out of 54, three patients who received radical prostatectomy were identified as cases with prostate-specific antigen persistence or biochemical recurrence. ConclusionsLeveraging FHIR data through large-scale analytics can enhance health care quality and improve patient outcomes across 5 clinical specialties. We identified (1) patients with sepsis requiring less broad antibiotic therapy, (2) patients with myocardial infarction who could benefit from statin and antiplatelet therapy, (3) patients who had a stroke with longer than recommended times to intervention, (4) patients with hyperglycemia who could benefit from specialist referral, and (5) patients with PC with early increases in cancer markers.

Abstract The Sparsely Annotated Region and Organ Segmentation (SAROS) dataset was created using data from The Cancer Imaging Archive (TCIA) to provide a large open-access CT dataset with high-quality annotations of body landmarks. In-house segmentation models were employed to generate annotation proposals on randomly selected cases from TCIA. The dataset includes 13 semantic body region labels (abdominal/thoracic cavity, bones, brain, breast implant, mediastinum, muscle, parotid/submandibular/thyroid glands, pericardium, spinal cord, subcutaneous tissue) and six body part labels (left/right arm/leg, head, torso). Case selection was based on the DICOM series description, gender, and imaging protocol, resulting in 882 patients (438 female) for a total of 900 CTs. Manual review and correction of proposals were conducted in a continuous quality control cycle. Only every fifth axial slice was annotated, yielding 20150 annotated slices from 28 data collections. For the reproducibility on downstream tasks, five cross-validation folds and a test set were pre-defined. The SAROS dataset serves as an open-access resource for training and evaluating novel segmentation models, covering various scanner vendors and diseases.

Background/Aims: Papillary adenocarcinoma is classified to differentiated-type gastric cancer and is indicated for endoscopic submucosal dissection. However, due to its rare nature, there are limited studies on it. The purpose of this study was to determine the outcome of endoscopic submucosal dissection in patients with papillary-type early gastric cancer and to find the risk factors of lymph node metastasis.Methods: Patients diagnosed with papillary-type early gastric cancer at eight medical centers, who underwent endoscopic submucosal dissection or surgical treatment, were retrospectively reviewed. The clinical results and long-term outcomes of post-endoscopic submucosal dissection were evaluated, and the risk factors of lymph node metastasis in the surgery group were analyzed.Results: One-hundred and seventy-six patients with papillary-type early gastric cancer were enrolled: 44.9% (n=79) in the surgery group and 55.1% (n=97) in the endoscopic submucosal dissection group. As a result of endoscopic submucosal dissection, the en bloc resection and curative resection rates were 91.8% and 86.6%, respectively. The procedure-related complication rate was 4.1%, and local recurrence occurred in 3.1% of patients. Submucosal invasion (odds ratio, 3.735; 95% confidence interval, 1.026 to 12.177; p=0.047) and lymphovascular invasion (odds ratio, 7.636; 95% confidence interval, 1.730 to 22.857; p=0.004) were the risk factors of lymph node metastasis in papillary-type early gastric cancer patients.Conclusions: The clinical results of endoscopic submucosal dissection in papillary-type early gastric cancer were relatively favorable, and endoscopic submucosal dissection is considered safe if appropriate indications are confirmed by considering the risk of lymph node metastasis.

Abstract The effect of arterial tortuosity on intracranial atherosclerosis (ICAS) is not well understood. This study aimed to evaluate the effect of global intracranial arterial tortuosity on intracranial atherosclerotic burden in patients with ischemic stroke. We included patients with acute ischemic stroke who underwent magnetic resonance angiography (MRA) and classified them into three groups according to the ICAS burden. Global tortuosity index (GTI) was defined as the standardized mean curvature of the entire intracranial arteries, measured by in-house vessel analysis software. Of the 516 patients included, 274 patients had no ICAS, 140 patients had a low ICAS burden, and 102 patients had a high ICAS burden. GTI increased with higher ICAS burden. After adjustment for age, sex, vascular risk factors, and standardized mean arterial area, GTI was independently associated with ICAS burden (adjusted odds ratio [adjusted OR] 1.33; 95% confidence interval [CI] 1.09–1.62). The degree of association increased when the arterial tortuosity was analyzed limited to the basal arteries (adjusted OR 1.48; 95% CI 1.22–1.81). We demonstrated that GTI is associated with ICAS burden in patients with ischemic stroke, suggesting a role for global arterial tortuosity in ICAS.

Abstract Metalenses are instruments that manipulate waves and have exhibited remarkable capabilities to date. However, an important hurdle arises due to the severe hampering of the angular response originating from coma and field curvature aberrations, which result in a loss of focusing ability. Herein, we provide a blueprint by introducing the notion of a wide field-of-hearing (FOH) metalens, designed particularly for capturing and focusing sound with decreased aberrations. Employing an aberration-free planar-thin metalens that leverages perfect acoustic symmetry conversion, we experimentally realize a robust wide FOH capability of approximately 140∘ in angular range. Moreover, our metalens features a relatively short focal length, enabling compact implementation by reducing the aperture-to-hearing plane distance. This is beneficial for space-efficient source-tracking sound sensing. Our strategy can be used across various platforms, potentially including energy harvesting, monitoring, imaging, and communication in auditory, ultrasonic, and submerged environments.

Citrus greening disease (HLB) and citrus canker cause financial losses in Florida citrus groves via smaller fruits, blemishes, premature fruit drop, and/or eventual tree death. Management of these two diseases requires early detection and distinction from other leaf defects and infections. Automated leaf inspection with hyperspectral imagery (HSI) is tested in this study. Citrus leaves bearing visible symptoms of HLB, canker, scab, melanose, greasy spot, zinc deficiency, and a control class were collected, and images were taken with a line-scan HSI camera. YOLOv8 was trained to classify multispectral images from this image dataset, created by selecting bands with a novel variance-based method. The ‘small’ network using an intensity-based band combination yielded an overall weighted F1 score of 0.8959, classifying HLB and canker with F1 scores of 0.788 and 0.941, respectively. The network size appeared to exert greater influence on performance than the HSI bands selected. These findings suggest that YOLOv8 relies more heavily on intensity differences than on the texture properties of citrus leaves and is less sensitive to the choice of wavelengths than traditional machine vision classifiers.

Background: Botulinum neurotoxin type A (BoNTA) is widely used in aesthetic facial rejuvenation medicine. The exponential growth in using BoNTA for cosmetic purposes in Korea necessitates an update to the existing practice guidelines, building upon the consensus established by Korean experts in 2013. Aims: This work aims to provide an updated Korean consensus guideline for the safe and effective use of a novel BoNTA product (NEWLUX) for facial expression muscles. Methods: A panel of ten Korean experts in dermatology, plastic surgery, aesthetic medicine, and clinical anatomy convened in February 2024. They reviewed prior guidelines, including the 2013 Korean consensus, and shared their expertise on dosage, injection techniques, and potential complications associated with the use of the novel BoNTA product for facial expression muscles. The recommendations aimed to guide the best practices of the average aesthetic healthcare professional. Results: The panel reached a consensus on various aspects of using the BoNTA product, including recommended injection sites, dosages, and techniques for different aesthetic conditions caused by facial expression muscles. The resulting guideline emphasizes safety and efficacy, with recommendations based on the collective experience of the expert panel. Conclusion: This updated consensus guideline provides practical recommendations from Korean experts on the use of the novel BoNTA product for facial expression muscles. The guidelines will ensure safe and effective treatments while reflecting the latest advancements in the field.

This study compares the compression force of cortical screws used in lag fashion with partially threaded cannulated screws and fully threaded headless cannulated screws as fixation methods for humeral condylar fractures in dogs. Cadavers of eleven dogs weighing an average of 10.99 ± 2.51 kg (6.1–14.4 kg) were used. The humeri were subjected to simulated fracture by performing an osteotomy at the trochlea of humerus and classified into three groups: Group 1 applied a 3.0 mm cortical screw applied in a lag fashion, Group 2 applied a 3.0 mm partially threaded cannulated screw, and Group 3 applied a 3.5 mm fully threaded headless cannulated screw. The samples were then placed in a material testing machine, and a compression force was applied vertically to the lateral condyle until failure. There were statistically significant differences in failure load between the groups (p = 0.009). The maximum failure load in Group 3 was significantly higher than in Group 2 (p = 0.014), while there were no statistically significant differences between Group 1 and Group 2) or between Group 1 and Group 3. Partially threaded cannulated screws and fully threaded headless cannulated screws can be alternatives to traditional stabilization methods, offering simpler procedures and additional advantages.

The potential of Raman hyperspectral imaging with a 785 nm excitation line laser was examined for the detection of aflatoxin contamination in corn kernels. Nine-hundred kernels were artificially inoculated in the laboratory, with 300 kernels each inoculated with AF13 (aflatoxigenic) fungus, AF36 (nonaflatoxigenic) fungus, and sterile distilled water (control). One-hundred kernels from each treatment were subsequently incubated for 3, 5, and 8 days. The mean spectra of single kernels were extracted from the endosperm side and the embryo area of the germ side, and local Raman peaks were identified based upon the calculated reference spectra of aflatoxin-negative and -positive categories separately. The principal component analysis-linear discriminant analysis models were established using different types of variable inputs including original full spectra, preprocessed full spectra, and identified local peaks over kernel endosperm-side, germ-side, and both sides. The results of the established discriminant models showed that the germ-side spectra performed better than the endosperm-side spectra. Based upon the 20 ppb-threshold, the best mean prediction accuracy of 82.6% was achieved for the aflatoxin-negative category using the original spectra in the combined form of both kernel sides, and the best mean prediction accuracy of 86.7% was obtained for the -positive category using the preprocessed germ-side spectra. Based upon the 100 ppb-threshold, the best mean prediction accuracies of 85.0% and 89.6% were achieved for the aflatoxin-negative and -positive categories separately, using the same type of variable inputs for the 20 ppb-threshold. In terms of overall prediction accuracy, the models established upon the original spectra in the combined form of both kernel sides achieved the best predictive performance, regardless of the threshold. The mean overall prediction accuracies of 81.8% and 84.5% were achieved with the 20 ppb- and 100 ppb-thresholds, respectively.

Citrus diseases are significant threats to citrus groves, causing financial losses through reduced fruit size, blemishes, premature fruit drop, and tree death. The detection of citrus diseases via leaf inspection can improve grove management and mitigation efforts. This study explores the potential of a portable reflectance and fluorescence hyperspectral imaging (HSI) system for detecting and classifying a control group and citrus leaf diseases, including canker, Huanglongbing (HLB), greasy spot, melanose, scab, and zinc deficiency. The HSI system was used to simultaneously collect reflectance and fluorescence images from the front and back sides of the leaves. Nine machine learning classifiers were trained using full spectra and spectral bands selected through principal component analysis (PCA) from the HSI with pixel-based and leaf-based spectra. A support vector machine (SVM) classifier achieved the highest overall classification accuracy of 90.7% when employing the full spectra of combined reflectance and fluorescence data and pixel-based analysis from the back side of the leaves, whereas a discriminant analysis classifier yielded the best accuracy of 94.5% with the full spectra of combined reflectance and fluorescence data and leaf-based analysis. Among the diseases, control, scab, and melanose were classified most accurately, each with over 90% accuracy. Therefore, the integration of the reflectance and fluorescence HSI with advanced machine learning techniques demonstrated the capability to accurately detect and classify these citrus leaf diseases with high precision.

Abstract This study investigated the prognostic performance of combination strategies using a multimodal approach in patients treated after cardiac arrest. Prospectively collected registry data were used for this retrospective analysis. Poor outcome was defined as a cerebral performance category of 3–5 at 6 months. Predictors of poor outcome were absence of ocular reflexes (PR/CR) without confounding factors, a highly malignant pattern on the most recent electroencephalography, defined as suppressed background with or without periodic discharges and burst-suppression, high neuron-specific enolase (NSE) after 48 h, and diffuse injury on imaging studies (computed tomography or diffusion-weighted imaging [DWI]) at 72–96 h. The prognostic performances for poor outcomes were analyzed for sensitivity and specificity. A total of 130 patients were included in the analysis. Of these, 68 (52.3%) patients had poor outcomes. The best prognostic performance was observed with the combination of absent PR/CR, high NSE, and diffuse injury on DWI [91.2%, 95% confidence interval (CI) 80.7–97.1], whereas the combination strategy of all available predictors did not improve prognostic performance (87.8%, 95% CI 73.8–95.9). Combining three of the predictors may improve prognostic performance and be more efficient than adding all tests indiscriminately, given limited medical resources.

Abstract The availability of computational hardware and developments in (medical) machine learning (MML) increases medical mixed realities’ (MMR) clinical usability. Medical instruments have played a vital role in surgery for ages. To further accelerate the implementation of MML and MMR, three-dimensional (3D) datasets of instruments should be publicly available. The proposed data collection consists of 103, 3D-scanned medical instruments from the clinical routine, scanned with structured light scanners. The collection consists, for example, of instruments, like retractors, forceps, and clamps. The collection can be augmented by generating likewise models using 3D software, resulting in an inflated dataset for analysis. The collection can be used for general instrument detection and tracking in operating room settings, or a freeform marker-less instrument registration for tool tracking in augmented reality. Furthermore, for medical simulation or training scenarios in virtual reality and medical diminishing reality in mixed reality. We hope to ease research in the field of MMR and MML, but also to motivate the release of a wider variety of needed surgical instrument datasets.

Aging manifests as many phenotypes, among which age-related changes in brain vessels are important, but underexplored. Thus, in the present study, we constructed a model to predict age using cerebrovascular morphological features, further assessing their clinical relevance using a novel pipeline.Age prediction models were first developed using data from a normal cohort (n = 1181), after which their relevance was tested in two stroke cohorts (n = 564 and n = 455). Our novel pipeline adapted an existing framework to compute generic vessel features for brain vessels, resulting in 126 morphological features. We further built various machine learning models to predict age using only clinical factors, only brain vessel features, and a combination of both. We further assessed deviation from healthy aging using the age gap and explored its clinical relevance by correlating the predicted age and age gap with various risk factors.The models constructed using only brain vessel features and those combining clinical factors with vessel features were better predictors of age than the clinical factor-only model (r = 0.37, 0.48, and 0.26, respectively). Predicted age was associated with many known clinical factors, and the associations were stronger for the age gap in the normal cohort. The age gap was also associated with important factors in the pooled cohort atherosclerotic cardiovascular disease risk score and white matter hyperintensity measurements.Cerebrovascular age, computed using the morphological features of brain vessels, could serve as a potential individualized marker for the early detection of various cerebrovascular diseases.

The Contamination Sanitization Inspection and Disinfection (CSI-D) device is a handheld fluorescence-based imaging system designed to disinfect food contact surfaces using ultraviolet-C (UVC) illumination. This study aimed to determine the optimal CSI-D parameters (i.e., UVC exposure time and intensity) for the inactivation of the following foodborne bacteria plated on non-selective media: generic Escherichia coli (indicator organism) and the pathogens enterohemorrhagic E. coli, enterotoxigenic E. coli, Salmonella enterica, and Listeria monocytogenes. Each bacterial strain was spread-plated on non-selective agar and exposed to high-intensity (10 mW/cm2) or low-intensity (5 mW/cm2) UVC for 1–5 s. Control plates were not exposed to UVC. The plates were incubated overnight at 37 °C and then enumerated. Three trials for each bacterial strain were conducted. Statistical analysis was carried out to determine if there were significant differences in bacterial growth between UVC intensities and exposure times. Overall, exposure to low or high intensity for 3–5 s resulted in consistent inhibition of bacterial growth, with reductions of 99.9–100 % for E. coli, 96.8–100 % for S. enterica, and 99.2–100 % for L. monocytogenes. The 1 s exposure time showed inconsistent results, with a 66.0–100 % reduction in growth depending on the intensity and bacterial strain. When the results for all strains within each species were combined, the 3–5 s exposure times showed significantly greater (p 0.05) in growth inhibition between the high and low UVC intensities. The results of this study show that, in pure culture conditions, exposure to UVC with the CSI-D device for ≥3 s is required to achieve consistent reduction of E. coli, S. enterica, and L. monocytogenes.

Abstract Introduction Visual field defects (VFDs) represent a debilitating poststroke complication, characterized by unseen parts of the visual field. Visual perceptual learning (VPL), involving repetitive visual training in blind visual fields, may effectively restore visual field sensitivity in cortical blindness. This current multicenter, double‐blind, randomized, controlled clinical trial investigated the efficacy and safety of VPL‐based digital therapeutics (Nunap Vision [NV]) for treating poststroke VFDs. Methods Stroke outpatients with VFDs (>6 months after stroke onset) were randomized into NV (defective field training) or Nunap Vision‐Control (NV‐C, central field training) groups. Both interventions provided visual perceptual training, consisting of orientation, rotation, and depth discrimination, through a virtual reality head‐mounted display device 5 days a week for 12 weeks. The two groups received VFD assessments using Humphrey visual field (HVF) tests at baseline and 12‐week follow‐up. The final analysis included those completed the study (NV, n = 40; NV‐C, n = 35). Efficacy measures included improved visual area (sensitivity ≥6 dB) and changes in the HVF scores during the 12‐week period. Results With a high compliance rate, NV and NV‐C training improved the visual areas in the defective hemifield (>72 degrees2) and the whole field (>108 degrees2), which are clinically meaningful improvements despite no significant between‐group differences. According to within‐group analyses, mean total deviation scores in the defective hemifield improved after NV training (p = .03) but not after NV‐C training (p = .12). Conclusions The current trial suggests that VPL‐based digital therapeutics may induce clinically meaningful visual improvements in patients with poststroke VFDs. Yet, between‐group differences in therapeutic efficacy were not found as NV‐C training exhibited unexpected improvement comparable to NV training, possibly due to learning transfer effects.

Maximum likelihood estimation is a classical method with useful properties like efficiency, consistency, and asymptotic normality. However, the maximum likelihood estimator (MLE) cannot be in closed form in many distributions. Therefore, it is obtained by iterative methods, such as the Newton–Raphson algorithm, which is time consuming and unrobust. For three multivariate distributions (bivariate Weibull, bivariate gamma and multivariate Dirichlet distributions) where the corresponding MLEs are not in closed forms, the R package MLEce is developed to provide new efficient estimators with asymptotic normality and efficiency like the MLE. Along with MLE and method of moment estimator (MME), MLEce package conducts point estimation (closed-form efficient estimator), random sample generation, goodness-of-fit test, and confidence interval estimation. Simulations and real data examples are provided to help us understand how to use MLEce.

Summary: Homologous recombination (HR) protects replication forks (RFs) and repairs DNA double-strand breaks (DSBs). Within HR, BRCA2 regulates RAD51 via two interaction regions: the BRC repeats to form filaments on single-stranded DNA and exon 27 (Ex27) to stabilize the filament. Here, we identified a RAD51 S181P mutant that selectively disrupted the RAD51-Ex27 association while maintaining interaction with BRC repeat and proficiently forming filaments capable of DNA binding and strand invasion. Interestingly, RAD51 S181P was defective for RF protection/restart but proficient for DSB repair. Our data suggest that Ex27-mediated stabilization of RAD51 filaments is required for the protection of RFs, while it seems dispensable for the repair of DSBs.

Abstract Thus far, attempts to develop drugs that target corticotropin-releasing hormone receptor 1 (CRF1R), a drug target in stress-related therapy, have been unsuccessful. Studies have focused on using high-resolution G protein-coupled receptor (GPCR) structures to develop drugs. X-ray free-electron lasers (XFELs), which prevent radiation damage and provide access to high-resolution compositions, have helped accelerate GPCR structural studies. We elucidated the crystal structure of CRF1R complexed with a BMK-I-152 antagonist at 2.75 Å using fixed-target serial femtosecond crystallography. The results revealed that two unique hydrogen bonds are present in the hydrogen bond network, the stalk region forms an alpha helix and the hydrophobic network contains an antagonist binding site. We then developed two antagonists—BMK-C203 and BMK-C205—and determined the CRF1R/BMK-C203 and CRF1R/BMK-C205 complex structures at 2.6 and 2.2 Å, respectively. BMK-C205 exerted significant antidepressant effects in mice and, thus, may be utilized to effectively identify structure-based drugs against CRF1R.

bis-Phenol A (BPA), bis-Phenol S (BPS), and bis-Phenol F (BPF) are important polymer industry plasticizers. Regulatory measures have restricted the use of BPA in plastic formulations, especially for those which come in contact with food products. Rapid, accurate spectroscopic measurements are required for distinguishing which of the three are present. The bis-phenol groups are structurally identical. The second set of bis-groups (CH3-C-CH3, O=S=O, and H-C-H, respectively) are discretely different chemically, but vibrational modes corresponding to these groups are not unique identifiers, routinely overlapping with wavenumbers present in other members of the set. The dual modality method identifies the specific wavenumbers in which the Infrared (IR) signal is near zero and the Raman relative intensity is maximum, and those in which the Raman signal is minimum and the IR signal is maximum. The normalized intensity ratio between IR and Raman enhances the signal [BPA 10.6 (1508 cm−1); BPS 7.4 (751 cm−1); BPF 5.1 (1100 cm−1)]. The ratio between Raman and IR in BPF is also enhanced: 6.3 (845 cm−1). Discerning which specific wavenumbers are most enhanced is experimentally feasible, though not necessarily at present theoretically predictable. This study demonstrates that IR and Raman spectra are not just complimentary, but together they are confirmatory even when the normalized intensity ratios of corresponding wavenumbers are most different.

Abstract Air pollution by particulate matter (PM) in the air including PM1.0, PM2.5, and PM10, which are categorized by particle size, is a critical global environmental issue, harming the climate, ecosystems, and human health. Especially, ultrafine dust including PM1.0 and PM2.5 poses significant human health risks. Commercial fabric‐based filters effectively trap PMs but cause high‐pressure drop and limited filter capacity and reusability. Electrospun nanofiber filters address some issues but have low mechanical strength, toxic exposure risks, long fabrication times, and restrained reusability. Herein, a reusable and transparent impaction‐based PM filter using a UV‐curable polymeric stencil with micro apertures is proposed. The polymeric stencil filters achieve high filter efficiency (68–94%), superior filter capacity, and low‐pressure drop (

Background and Purpose This study aimed to evaluate whether extracellular-vesicle-incorporated microRNAs (miRNAs) are potential biomarkers for cancer-related stroke. Methods This cohort study compared patients with active cancer who had embolic stroke of unknown sources (cancer-stroke group) with patients with only cancer, patients with only stroke, and healthy individuals (control groups). The expression profiles of miRNAs encapsulated in plasma exosomes and microvesicles were evaluated using microarray and validated using quantitative real-time polymerase chain reaction. The XENO-QTM miRNA assay technology was used to determine the absolute copy numbers of individual miRNAs in an external validation cohort. Results This study recruited 220 patients, of which 45 had cancer-stroke, 76 were healthy controls, 39 were cancer controls, and 60 were stroke controls. Three miRNAs (miR-205-5p, miR-645, and miR-646) were specifically incorporated into microvesicles in patients with cancer-related stroke, cancer controls, and stroke controls. The area under the receiver operating characteristic curves of these three miRNAs were 0.7692–0.8510 for the differentiation of patients with cancer-stroke from cancer-controls and 0.8077–0.8846 for the differentiation of patients with cancer-stroke from stroke controls. The levels of several miRNAs were elevated in the plasma exosomes of patients with cancer, but were lower than those in plasma microvesicles. An in vivo study showed that systemic injection of miR-205-5p promoted the development of arterial thrombosis and elevation of D-dimer levels Conclusion Stroke due to cancer-related coagulopathy was associated with deregulated expression of miRNAs, particularly microvesicle-incorporated miR-205-5p, miR-645, and miR-646. Further prospective studies of extracellular-vesicle-incorporated miRNAs are required to confirm the diagnostic role of miRNAs in patients with stroke and to screen the roles of miRNAs in patients with cancer.

Abstract Repetitive transcranial magnetic stimulation (rTMS) is attracting attention as a new treatment technique for brain lesions, and many animal studies showing its effects have been reported. However, the findings of animal application researches cannot directly represent the effects of rTMS in human, mainly due to size difference and mechanistic characteristics of rTMS. Therefore, the authors purposed to develop a mouse rTMS to simulate clinical application and to confirm. Firstly, a virtual head model was created according to magnetic resonance images of murine head. Then, simulations of rTMS stimulation with different coils were performed on the murine head phantom, and an rTMS device for mice was fabricated based on the optimal voltage conditions. Lastly, strengths of magnetic fields generated by the two rTMS devices, for human (conventional clinical use) and mouse (newly fabricated), were measured in air and on mouse head and compared. Resultantly, the magnetic field intensity generated by coil of mouse was lower than human’s (p 0.05). Further in vivo researches using miniaturized rTMS devices for murine head should be followed to be more meaningful for human.

Abstract Identifying the cerebral arterial branches is essential for undertaking a computational approach to cerebrovascular imaging. However, the complexity and inter-individual differences involved in this process have not been thoroughly studied. We used machine learning to examine the anatomical profile of the cerebral arterial tree. The method is less sensitive to inter-subject and cohort-wise anatomical variations and exhibits robust performance with an unprecedented in-depth vessel range. We applied machine learning algorithms to disease-free healthy control subjects (n = 42), patients with stroke with intracranial atherosclerosis (ICAS) (n = 46), and patients with stroke mixed with the existing controls (n = 69). We trained and tested 70% and 30% of each study cohort, respectively, incorporating spatial coordinates and geometric vessel feature vectors. Cerebral arterial images were analyzed based on the ‘segmentation-stacking’ method using magnetic resonance angiography. We precisely classified the cerebral arteries across the exhaustive scope of vessel components using advanced geometric characterization, redefinition of vessel unit conception, and post-processing algorithms. We verified that the neural network ensemble, with multiple joint models as the combined predictor, classified all vessel component types independent of inter-subject variations in cerebral arterial anatomy. The validity of the categorization performance of the model was tested, considering the control, ICAS, and control-blended stroke cohorts, using the area under the receiver operating characteristic (ROC) curve and precision-recall curve. The classification accuracy rarely fell outside each image’s 90–99% scope, independent of cohort-dependent cerebrovascular structural variations. The classification ensemble was calibrated with high overall area rates under the ROC curve of 0.99–1.00 [0.97–1.00] in the test set across various study cohorts. Identifying an all-inclusive range of vessel components across controls, ICAS, and stroke patients, the accuracy rates of the prediction were: internal carotid arteries, 91–100%; middle cerebral arteries, 82–98%; anterior cerebral arteries, 88–100%; posterior cerebral arteries, 87–100%; and collections of superior, anterior inferior, and posterior inferior cerebellar arteries, 90–99% in the chunk-level classification. Using a voting algorithm on the queued classified vessel factors and anatomically post-processing the automatically classified results intensified quantitative prediction performance. We employed stochastic clustering and deep neural network ensembles. Ma-chine intelligence-assisted prediction of vessel structure allowed us to personalize quantitative predictions of various types of cerebral arterial structures, contributing to precise and efficient decisions regarding the cerebrovascular disease.

Citrus Black Spot (CBS) causes considerable damage to the Florida citrus industry. Early detection of CBS, especially in the presence of other peel blemishes, would enable better mapping and control of CBS spread, reduce wasted fruit, and permit early removal of culls from the packing stream. Oranges whose peels bore the symptoms of four defects/disease (CBS, greasy spot, melanose, and wind scar), as well as a normal control group, were imaged with a hyperspectral imaging system. Principal Component Analysis- (PCA) and Linear Discriminant Analysis (LDA) -based methods were employed to select bands from these images, and a custom convolutional neural network (CNN) for feature extraction was trained with these bands. The extracted features permitted classification of the peel conditions with four classifiers: SoftMax, Support Vector Machines (SVM), Random Forest Classifier (RFC), and K-Nearest Neighbors (KNN). A mean overall accuracy of 94.9 % was achieved using an SVM classifier on five bands selected with PCA, and 90.2 % with LDA-selected bands. These results show the potential of CNNs to extract features for automated postharvest citrus inspection.

This article presents a modeling method for the uncorrelated measurement error of the ultra-short baseline (USBL) acoustic positioning system for aiding navigation of underwater vehicles. The Mahalanobis distance (MD) and principal component analysis are applied to decorrelate the errors of USBL measurements, which are correlated in the x- and y-directions and vary according to the relative direction and distance between a reference station and the underwater vehicles. The proposed method can decouple the radial-direction error and angular direction error from each USBL measurement, where the former and latter are independent and dependent, respectively, of the distance between the reference station and the vehicle. With the decorrelation of the USBL errors along the trajectory of the vehicles in every time step, the proposed method can reduce the threshold of the outlier decision level. To demonstrate the effectiveness of the proposed method, simulation studies were performed with motion data obtained from a field experiment involving an autonomous underwater vehicle and USBL signals generated numerically by matching the specifications of a specific USBL with the data of a global positioning system. The simulations indicated that the navigation system is more robust in rejecting outliers of the USBL measurements than conventional ones. In addition, it was shown that the erroneous estimation of the navigation system after a long USBL blackout can converge to the true states using the MD of the USBL measurements. The navigation systems using the uncorrelated error model of the USBL, therefore, can effectively eliminate USBL outliers without loss of uncontaminated signals.

BackgroundConstipation symptoms are highly prevalent in acute ischemic stroke, but the clinical and neuroimaging predictors are unknown. This study aimed to identify lesions and clinical features associated with acute constipation.MethodsData from patients with acute ischemic stroke registered in a hospital-based stroke registry between January 2018 and December 2019 were analyzed. Clinical, laboratory, and imaging features were examined for associations with acute constipation. Using the topographic lesion on diffusion-weighted images, multivariate support vector regression-based lesion-symptom mapping (SVR-LSM) was conducted and compared between the non-constipation and acute constipation groups.ResultsA total of 256 patients (mean age 67 years, men: 64%) were included. Acute constipation was noted in 81 patients (32%). Initial stroke severity, represented by initial National Institutes of Health and Stroke Scale (NIHSS) scores, was associated with acute constipation. Laboratory parameters, including fibrin degradation products (FDP), fibrinogen, D-dimer, lipoprotein (a), and free fatty acid levels, also showed statistically significant differences between the non-constipation and constipation groups. FDP, D-dimer, and free fatty acid levels were independently associated with acute constipation in the logistic regression model after adjusting for initial NIHSS scores and potassium levels. SVR-LSM revealed that bilateral lesions in the precentral gyrus, insula, opercular part of the inferior frontal gyrus, the inferior parietal lobule, and lesions in the right middle frontal gyrus were significantly associated with acute constipation. The results were consistent after controlling for the initial NIHSS scores and poststroke potassium levels. When cardioembolic stroke subjects were excluded, the right insular and prefrontal cortex lesions lost their association with acute constipation.ConclusionAcute constipation symptoms after acute ischemic stroke are mainly related to bilateral lesions in the insula, precentral gyrus, postcentral gyrus, and inferior parietal lobule. Clinically important predictors of acute constipation include initial neurological severity and thromboembolic markers of stroke.

Background Although it is well known that the disordered brain provokes cardiac autonomic dysfunction, the detailed location of brain lesions related to cardiac function warrants further investigation. We aimed to elucidate the brain lesions topographically associated with left ventricular (LV) systolic function measured by myocardial strain in patients with acute ischemic stroke without preexisting primary cardiac dysfunction by using support vector regression lesion‐symptom mapping. Methods and Results Subjects were those with LV ejection fraction of 50% or more among patients with acute ischemic stroke registered in the Samsung Medical Center stroke registry between 2016 and 2017. To evaluate LV systolic performance and contractility, we measured LV ejection fraction and LV global and regional longitudinal strain using 2‐dimensional speckle‐tracking echocardiography. The association between stroke lesion location and cardiac strain was assessed using support vector regression lesion‐symptom mapping. Of a total of 776 patients, 286 subjects (mean age of 67.0 years, 65.4% men) were finally enrolled in this study. The mean global longitudinal strain was −17.0±3.4%, and the mean LV ejection fraction was 64.7±5.7%. The support vector regression lesion‐symptom mapping analysis revealed that the right insula and peri‐insular regions and left parietal cortex were associated with impaired LV global longitudinal strain in patients with acute ischemic stroke. In addition, impaired regional longitudinal strain showed topographical associations with these regions. Conclusions This study suggests that brain lesions in the right insula and peri‐insular regions and left parietal cortex are topographically associated with impaired LV strain in patients with acute ischemic stroke without preexisting cardiac dysfunction.

We present a deep learning model based on an autoencoder for the reconstruction of cranial and facial defects using the Medical Open Network for Artificial Intelligence (MONAI) framework, which has been pre-trained on the MUG500+ and SkullFix dataset. The implementation follows the MONAI contribution guidelines, hence, it can be easily tried out and used, and extended by MONAI users. The primary goal of this paper lies in the investigation of open-sourcing codes and pre-trained deep learning models under the MONAI framework. The pre-trained models generated in this work deliver reasonable results on the cranial and facial reconstruction task and provide an ideal starting-point for other researchers interested in further investigating the topic. We released the codes and the pre-trained model at the official MONAI ‘research contributions’ GitHub repository: https://github.com/Project-MONAI/research-contributions/tree/master/SkullRec. This contribution has two novelties: 1. Pre-training an autoencoder on the MUG500+ and SkullFix dataset for cranial and facial reconstruction using MONAI, and open-sourcing the codes and weights for other MONAI users; 2. Demonstrating that existing MONAI tutorials can be easily adapted to new use cases, such as skull (cranial and facial) reconstruction.

Risk for transmission of monkeypox virus (MPXV) (clade IIb) to healthcare workers (HCWs) is low. Although many cases have been reported among HCW, only a few have been occupationally acquired. We report a case of non–needle stick MPXV transmission to an HCW in the United States.

The genus Philadelphus (Hydrangeaceae) in South Korea is critically revised based on macro- and micro-morphological characteristics from over 1,000 herbarium specimens, and fresh material from wild populations. Findings show that: (1) The presence/absence and the density of the hairs on the disk, pistil, calyx, leaves, and petiole and the degree of division of the style are insufficient characters for recognizing species in Philadelphus. (2) Philadelphus koreanus, P. robustus, P. scaber, and P. seoulensis were confirmed to be synonyms of P. tenuifolius. (3) Philadelphus lasiogynus is newly synonymized into P. tenuifolius based on the type material. (4) Philadelphus pekinensis has been excluded from the Korean flora because of prior misidentifications of herbarium specimens, whose identity is very sparsely pubescent P. tenuifolius. It is therefore confirmed that only P. tenuifolius has been recorded in South Korea. Detailed morphological descriptions, photographs, illustrations, distribution maps, and information on the herbarium materials of P. tenuifolius in South Korea are provided.

A flow diverter (FD) is an effective method for treating wide-necked intracranial aneurysms by inducing hemodynamic changes in aneurysms. However, the procedural technique remains challenging, and it is often not performed properly in many cases of deployment or placements. In this study, three types of FDs that changed the material of the wire were prepared within the same structure. Differences in physical properties, such as before and after delivery loading stent size, radial force, and radiopacity, were evaluated. The performances in terms of deployment and trackability force were also evaluated in a simulated model using these FDs. Furthermore, changes of deployment patterns when these FDs were applied to a 3D-printed aneurysm model were determined. The NiTi FD using only nitinol (NiTi) wire showed 100% size recovery and 42% to 45% metal coverage after loading. The low trackability force (10.9 to 22.9 gf) allows smooth movement within the delivery system. However, NiTi FD cannot be used in actual surgeries due to difficulties in X-ray identification. NiTi-Pt/W FD, a combination of NiTi wire and platinum/tungsten (Pt/W) wire, had the highest radiopacity and compression force (6.03 ± 0.29 gf) among the three FDs. However, it suffered from high trackability force (22.4 to 39.9 gf) and the end part braiding mesh tended to loosen easily, so the procedure became more challenging. The NiTi(Pt) FD using a platinum core nitinol (NiTi(Pt)) wire had similar trackability force (11.3 to 22.1 gf) to NiTi FD and uniform deployment, enhancing procedural convenience. However, concerns about low expansion force (1.79 ± 0.30 gf) and the potential for migration remained. This comparative analysis contributes to a comprehensive understanding of how different wire materials influence the performance of FDs. While this study is still in its early stages and requires further research, its development has the potential to guide clinicians and researchers in optimizing the selection and development of FDs for the effective treatment of intracranial aneurysms.