Barriers and future improvements of workplace-based learning in Korean medicine clinical clerkship: perspectives of graduates.

BACKGROUND: Workplace-based learning (WPBL) has emerged as an essential practice in healthcare education. However, WPBL is rarely implemented in Korean medicine (KM) due to the passive attitude of teachers and possible violation of medical laws that limit the participation of trainees in medical treatment. In this study, we implemented WPBL in the clinical clerkship of Acupuncture and Moxibustion Medicine at a single College of KM and explored the barriers and future improvements of WPBL. METHODS: The WPBL was implemented from January to July 2019. During the clerkship, each senior student was assigned an inpatient at the university hospital. WPBL was conducted as follows: patient presentation by the supervisor, interaction with the patient at the bedside, preparation of medical records, oral case presentation, and discussion with feedback. The student performed a physical examination and review of systems as a clinical task. In addition, six doctors of KM who are currently practicing after three years of WPBL were interviewed in September 2022 to investigate the real-world effects and unmet needs of WPBL in their workplaces. RESULTS: Two major themes identified from the interview were: "the experience of novice doctors of KM with KM practice" and "Current state of KM clinical education." The five subcategories were: "Clinical competency priorities vary according to the KM workplace," "Difficulties faced by doctors of KM immediately after graduation," "WPBL experience of the interviewees," "Necessary but difficult to implement real patient learning," and "Unmet needs for clinical clerkship in KM." CONCLUSION: It is essential to consider the unique characteristics of KM practice and the duties required in various workplaces for successful WPBL. We anticipate our study to be a starting point for improving the WPBL and addressing the unmet needs in KM clinical education.

Reappraisal of Malignant Risk Assessment for Small (≤20 mm) Non-functioning Pancreatic Neuroendocrine Tumors.

BACKGROUND: Optimal management of non-functioning pancreatic neuroendocrine tumors (PanNETs) ≤20 mm is controversial. The biological heterogeneity of these tumors poses challenges when deciding between resection and observation. METHODS: In this multicenter, retrospective cohort study, we analyzed all patients (n = 78) who underwent resection of non-functioning PanNETs ≤20 mm at three tertiary medical centers from 2004 to 2020 to assess the utility of preoperatively available radiological features and serological biomarkers of non-functioning PanNETs in choosing an optimal surgical indication. The radiological features included non-hyper-attenuation pattern on enhancement computed tomography (CT; hetero/hypo-attenuation) and main pancreatic duct (MPD) involvement, and serological biomarkers included elevation of serum elastase 1 and plasma chromogranin A (CgA) levels. RESULTS: Of all small non-functioning PanNETs, 5/78 (6%) had lymph node metastasis, 11/76 (14%) were WHO grade II, and 9/66 (14%) had microvascular invasion; 20/78 (26%) had at least one of these high-risk pathological factors. In the preoperative assessment, hetero/hypo-attenuation and MPD involvement were observed in 25/69 (36%) and 8/76 (11%), respectively. Elevated serum elastase 1 and plasma CgA levels were observed in 1/33 (3%) and 0/11 (0%) patients, respectively. On multivariate logistic regression analysis, hetero/hypo-attenuation (odds ratio [OR] 6.1, 95% confidence interval [CI] 1.7-22.2) and MPD involvement (OR 16.8, 95% CI 1.6-174.3) were significantly associated with the high-risk pathological factors. The combination of the two radiological worrisome features correctly predicted non-functioning PanNETs with high-risk pathological factors, with about 75% sensitivity, 79% specificity, and 78% accuracy. CONCLUSIONS: This combination of radiological worrisome features can accurately predict non-functioning PanNETs that may require resection.

Chronic allergic asthma induces T-cell exhaustion and impairs virus clearance in mice.

BACKGROUND: Allergic asthma, one of the most common types of asthma, is thought to be highly susceptible to respiratory viral infections; however, its pathological mechanism needs to be elucidated. Recent studies have found impaired T-cell function in asthmatic mice. Therefore, we aimed to investigate the way by which asthma induction affects T-cell exhaustion in the lungs and assess the relationship between T-cell exhaustion and influenza viral infection. METHODS: Chronic allergic asthma mice were induced by intranasal injection of ovalbumin for 6 weeks and asthmatic features and T cell populations in lung or airway were assessed. To determine the influenza virus susceptibility, control and asthma mice were challenged with the human influenza virus strain A/Puerto Rico/8/1934 H1N1 and evaluated the survival rate, lung damage, and virus titer. RESULTS: Six weeks of OVA sensitization and challenge successfully induced chronic allergic asthma in a mouse model showing significant increase of sera IgE level and broncho-pathological features. A significant decrease in interferon-γ-producing T-cell populations and an increase in exhausted T-cell populations in the lungs of OVA-induced asthmatic mice were observed. Asthmatic mice were more susceptible to influenza virus infection than control mice showing lower survival rate and higher virus titer in lung, and a positive correlation existed between T-cell exhaustion in the lung and virus titer. CONCLUSIONS: Asthma induction in mice results in the exhaustion of T-cell immunity, which may contribute to the defective capacity of viral protection. This study demonstrates a correlation between asthma conditions and viral susceptibility by investigating the functional characteristics of T-cells in asthma. Our results provide insights into the development of strategies to overcome the dangers of respiratory viral disease in patients with asthma.

Comparative study of lumbar bone mineral content using DXA and CT Hounsfield unit values in chest CT.

BACKGROUND: Bone mineral content (BMC) values in certain bones and changes in BMC over time are key features for diagnosing osteoporosis. This study examined those features using morphometric texture analysis in chest computational tomography (CT) by comparing a dual-energy X-ray absorptiometry (DXA)-based BMC. An accessible approach for screening osteoporosis was suggested by accessing BMC using only Hounsfield units (HU). METHODOLOGY: The study included a total of 510 cases (255 patients) acquired between May 6, 2012, and June 30, 2020, at a single institution. Two cases were associated with two chest CT scans from one patient with a scan interval of over two years, and each scan was followed soon after by a DXA scan. Axial cuts of the first lumbar vertebra in CT and DXA-based L1 BMC values were corrected for each case. The maximum trabecular area was selected from the L1 spine body, and 45 texture features were extracted from the region using gray-level co-occurrence matrices. A regression model was employed to estimate the absolute BMC value in each case using 45 features. Also, an additional regression model was used to estimate the change in BMC between two scans for each patient using 90 features from the corresponding cases. RESULTS: The correlation coefficient (CC) and mean absolute error (MAE) between estimates and DXA references were obtained for the evaluation of regressors. In the case of the BMC estimation, CC and MAE were 0.754 and 1.641 (g). In the case of the estimation of change in BMC, CC and MAE were 0.680 and 0.528 (g). CONCLUSION: The modality using morphometric texture analysis with CT HUs can indirectly help screening osteoporosis because it provides estimates of BMC and BMC change that show moderate positive correlations with DXA measures.

A populational connection distribution map for the whole brain white matter reveals ordered cortical wiring in the space of white matter.

The white matter in the brain is composed of neural fibers that wire the cortical and subcortical brain systems. Considering the complexity in terms of interconnections of many neural populations within the narrow space surrounded by the folding walls of the gray matter, the brain requires a certain way of structured wiring. To explore the three-dimensional organization of wiring in an accessible manner, we focused on voxel-level wiring patterns in the white matter according to cortical distributions in which each voxel mediates the wiring. We constructed a voxel-wise connection distribution map from the whole white matter voxels to 360 cortical regions using probabilistic tractography of the 100 diffusion imaging data in the Human Connectome Project. We then explored the spatial organization of the fiber bundles at the white matter voxels in terms of the maximal and second maximal cortical connection labels and the local gradient and entropy of cortical connection density using the population connection distribution map. We presented dominant cortical connection labels, local gradient, and connection entropy for the most representative white matter regions, including the internal capsule, external capsule, corpus callosum, cingulum bundle, and uncinate fascicles, most of which were introduced in the current study. Those major tracts showed a gradient organization of connection distributions for individual voxels. This organized pattern, as reflected in the whole brain connection distribution map, could be established to optimize wiring in the entire brain within the physical space of the white matter.

The impact of obesity on the accuracy of DXA BMD for DXA-equivalent BMD estimation.

INTRODUCTION: As the radiomics technique using texture features in CT is adopted for accessing DXA-equivalent bone mineral density (BMD), this study aims to compare BMD by DXA and predicted BMD to investigate the impact of obesity and central obesity in general patients. MATERIALS AND METHODS: A total of 710 cases (621 patients) obtained from May 6, 2012, to June 30, 2021, were used in the study. We focused both their abdomen & pelvis CT's first lumbar vertebrae axial cuts to predict estimated BMD and bone mineral content (BMC). In each patient's CT, we extracted the largest trabecular region of the L1 vertebral body as a region of interest (ROI) using the gray-level co-occurrence matrices (GLCM) technique, and linear regression was applied to predict the indices. Cases were divided by central obesity/overall obesity and normal group by body mass index (BMI), waist circumference (WC), or index of central obesity (ICO) standard. RESULTS: The coefficients were all above 0.73, respectively. P-values from ICO were over 0.05 when the measures were Hip BMD and Hip BMC. In contrast, those from ICO were 0.0131 and 0.0351 when the measures were L1 BMD and L1 BMC, respectively, which show a difference between the two groups. CONCLUSIONS: The CT HU texture analysis method was an effective and economical method for measuring estimated BMD and BMC and evaluating the impact of obesity. We found that central obesity especially exerted an effect on the disturbance of the clinical BMD measurements since groups were significantly different under the ICO standard.

Anti-Thrombotic Effects of Artesunate through Regulation of cAMP and PI3K/MAPK Pathway on Human Platelets.

Normal activation of platelets and their aggregation are crucial for proper hemostasis. It appears that excessive or abnormal aggregation of platelets may bring about cardiovascular diseases such as stroke, atherosclerosis, and thrombosis. For this reason, finding a substance that can regulate platelet aggregation or suppress aggregation will aid in the prevention and treatment of cardiovascular diseases. Artesunate is a compound extracted from the plant roots of Artemisia or Scopolia, and its effects have shown to be promising in areas of anticancer and Alzheimer's disease. However, the role and mechanisms by which artesunate affects the aggregation of platelets and the formation of a thrombus are currently not understood. This study examines the ways artesunate affects the aggregation of platelets and the formation of a thrombus on platelets induced by U46619. As a result, cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) production were increased significantly by artesunate relative to the doses, as well as phosphorylated vasodilator-stimulated phosphoprotein (VASP) and inositol 1,4,5-trisphosphate receptor (IP3R), substrates to cAMP-dependent kinase and cGMP-dependent kinase, in a significant manner. The Ca2+, normally mobilized from the dense tubular system, was inhibited due to IP3R phosphorylation from artesunate, and phosphorylated VASP aided in inhibiting platelet activity via αIIb/ß3 platelet membrane inactivation and inhibiting fibrinogen binding. In addition, MAPK and PI3K/Akt phosphorylation was inhibited via artesunate in a significant manner, causing the production of TXA2 and intracellular granular secretion (serotonin and ATP release) to be reduced. Therefore, we suggest that artesunate has value as a substance that inhibits platelet aggregation and thrombus formation through an antiplatelet mechanism.

Conversion to open laparotomy during laparoscopic distal pancreatectomy: lessons from a single-center experience in 70 consecutive patients.

PURPOSE: The purpose of this study was to determine the factors influencing conversion from laparoscopic distal pancreatectomy (LDP) to open surgery, and the effect of such conversion on the outcome. METHODS: This retrospective single-center study included 70 consecutive patients undergoing LDP. The primary endpoint was the rate of conversion to open surgery during LDP. The secondary endpoints were determining the reasons for conversion to open surgery, with detailed analyses of these cases and a comparison of the surgical outcome with and without conversion. RESULTS: Seven patients (10%) required conversion to open surgery during LDP. Pancreatic ductal adenocarcinoma (PDAC) was identified as a risk factor for conversion (p = 0.010). The reasons for conversion included technical difficulty (two bleeding, one severe adhesion) and pancreatic stump-related issues (two margin-positive, two stapling failures). Although the overall morbidity rate (29 vs. 11%, p = 0.48) and the rate of clinically relevant postoperative pancreatic fistula (14 vs. 5%, p = 0.82) were no different for the patients with or without open conversion, the postoperative hospital stay was significantly longer in the former (median 15 vs. 10 days, p = 0.03). CONCLUSIONS: Careful preoperative assessment is required when planning LDP for PDAC. Although conversion to open surgery does not result in failure of LDP, efforts to reduce the duration of postoperative hospital stay and the occurrence of complications are desirable to improve the outcome of LDP.

Which deep learning model can best explain object representations of within-category exemplars?

Deep neural network (DNN) models realize human-equivalent performance in tasks such as object recognition. Recent developments in the field have enabled testing the hierarchical similarity of object representation between the human brain and DNNs. However, the representational geometry of object exemplars within a single category using DNNs is unclear. In this study, we investigate which DNN model has the greatest ability to explain invariant within-category object representations by computing the similarity between representational geometries of visual features extracted at the high-level layers of different DNN models. We also test for the invariability of within-category object representations of these models by identifying object exemplars. Our results show that transfer learning models based on ResNet50 best explained both within-category object representation and object identification. These results suggest that the invariability of object representations in deep learning depends not on deepening the neural network but on building a better transfer learning model.

Pharmacokinetic and pharmacodynamic integration for optimal dosage of cefquinome against Streptococcus equi subsp. equi in foals.

Cefquinome is administered in horses for the treatment of respiratory infection caused by Streptococcus equi subsp. zooepidemicus, and septicemia caused by Escherichia coli. However, there have been no attempts to use cefquinome against Streptococcus equi subsp. equi (S. equi), the causative agent of strangles. Hence the objective of this study was to calculate an optimal dosage of cefquinome against S. equi based on pharmacokinetics and pharmacodynamics integration. Cefquinome (1.0 mg/kg) was administered by intravenous and intramuscular routes to six healthy thoroughbred foals. Serum cefquinome concentrations were determined by high-performance liquid chromatography. The in vitro and ex vivo antibacterial activity were determined from minimum inhibitory concentrations (MIC) and bacterial killing curves. The optimal dosage was calculated from the integration of pharmacokinetic parameters and area under the curve (AUC24h/MIC) values. Total body clearance and volume of distribution of cefquinome after intravenous administration were 0.06 L/h/kg and 0.09 L/kg, respectively. Following intramuscular administration, a maximum concentration of 0.73 µg/mL at 1.52 h (Tmax) and a systemic bioavailability of 37.45% were observed. The MIC of cefquinome against S. equi was 0.016 µg/mL. The ex vivo AUC24h/MIC values representing bacteriostatic, and bactericidal activity were 113.11, and 143.14 h, respectively. Whereas the %T > MIC for bactericidal activity was 153.34%. In conclusion, based on AUC24h/MIC values and pharmacokinetic parameters, cefquinome when administered by intramuscularly at a dosage of 0.53 mg/kg every 24 h, would be effective against infection caused by S. equi in foals. Further studies may be necessary to confirm its therapeutic efficacy in a clinical environment.

Harmonized representation learning on dynamic EHR graphs.

With the rise of deep learning, several recent studies on deep learning-based methods for electronic health records (EHR) successfully address real-world clinical challenges by utilizing effective representations of medical entities. However, existing EHR representation learning methods that focus on only diagnosis codes have limited clinical value, because such structured codes cannot concretely describe patients' medical conditions, and furthermore, some of the codes assigned to patients contain errors and inconsistency; this is one of the well-known caveats in the EHR. To overcome this limitation, in this paper, we fuse more detailed and accurate information in the form of natural language provided by unstructured clinical data sources (i.e., clinical notes). We propose HORDE, a unified graph representation learning framework to embed heterogeneous medical entities into a harmonized space for further downstream analyses as well as robustness to inconsistency in structured codes. Our extensive experiments demonstrate that HORDE significantly improves the performances of conventional clinical tasks such as subsequent code prediction and patient severity classification compared to existing methods, and also show the promising results of a novel EHR analysis about the consistency of each diagnosis code assignment.

Identification of the Female-Produced Sex Pheromone of the Dotted White Geometrid Naxa seriaria (Lepidoptera: Geometridae).

The dotted white geometrid moth, Naxa seriaria Motschulsky (Lepidoptera: Geometridae), is a pest of Oleaceae in Korea, Japan, and China. In this study, we identified (3Z,6Z,9Z,12Z,15Z)-heneicosapentaene (C-21 pentaene) as the only compound in extracts of the pheromone glands of female N. seriaria causing a response from receptors on the antennae of males in analyses by gas chromatography with electroantennographic detection. The synthetic sex pheromone elicited dose-dependent electrophysiological responses from antennae of male N. seriaria. In field tests, more male moths were captured in traps baited with synthetic C-21 pentaene than in unbaited traps, and increasing the loading of C-21 pentaene in the lure increased catches of male moths. Significantly more male N. seriaria moths were caught in delta traps than in bucket traps. Based on these results, C-21 pentaene is proposed to be the major, if not the only, component of the sex pheromone of N. seriaria.

Neurofeedback learning for mental practice rather than repetitive practice improves neural pattern consistency and functional network efficiency in the subsequent mental motor execution.

During brain modulation, repeated mental practice may not always result in efficient learning. Particularly, the effectiveness of mental motor practice depends on how well one induces neural activity in a desired state consistently across mental trials, which calls for feedbacks to adjust one's performance. We hypothesized that even a brief experience of neurofeedback learning enhances trial-by-trial neural pattern consistency during subsequent mental motor execution and that this experience would change recruitment of functional connectivity in the motor imagery and default mode networks. To test this hypothesis, we conducted an experiment with two sessions of mental motor practice before and after a neurofeedback training session, in which participants conducted four types of first-person mental motor execution tasks (walking forward, turning left, turning right, and touching a tree). During the neurofeedback training session, in which participants conducted a virtual navigation game, 10 experimental participants received real-time fMRI neuro-feedbacks, while 10 control participants simply repeated the same mental task according to given cues without feedbacks. The experimental group showed significantly higher effects of neuro-feedback training on trial-by-trial consistencies and classification accuracies of activated neural patterns than the control group. Task-performing global node strength and network efficiency were increased in the motor imagery network but decreased in the default mode network only in the experimental group. These results demonstrate that even a brief experience of feedback learning is more effective than simple practice repetitions without evaluation, which was reflected in increased neural pattern consistency and task-dependent functional connectivity during a mental motor execution task.

Gintonin modulates platelet function and inhibits thrombus formation via impaired glycoprotein VI signaling.

Panax ginseng (P. ginseng), one of the most valuable medicinal plants, is known for its healing and immunobooster properties and has been widely used in folk medicine against cardiovascular diseases, including stroke and heart attack. In this study, we explored the anti-platelet activity of gintonin (a recently discovered non-saponin fraction of ginseng) against agonist-induced platelet activation. In vitro effects of gintonin on agonist-induced human and rat platelet aggregation, granule secretion, integrin αIIbß3 activation, and intracellular calcium ion ([Ca2+]i) mobilization were examined. Western blot analysis and immunoprecipitation techniques were used to estimate the expression of mitogen-activated protein kinases (MAPKs) and phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt) and interaction of glycoprotein VI (GPVI) signaling pathway molecules such as Src family kinases (SFK), tyrosine kinase Syk, and PLCγ2. In vivo effects were studied using acute pulmonary thromboembolism model in mice. Gintonin remarkably inhibited collagen-induced platelet aggregation and suppressed granule secretion, [Ca2+]i mobilization, and fibrinogen binding to integrin αIIbß3 in a dose-dependent manner and clot retraction. Gintonin attenuated the activation of MAPK molecules and PI3K/Akt pathway. It also inhibited SFK, Syk, and PLCγ2 activation and protected mice from thrombosis. Gintonin inhibited agonist-induced platelet activation and thrombus formation through impairment in GPVI signaling molecules, including activation of SFK, Syk, PLCγ2, MAPK, and PI3K/Akt; suggesting its therapeutic potential against platelet related CVD.

[A Patient with Multiple Pancreatic Metastases Undergoing Total Pancreatectomy 18 Years after Renal Cell Carcinoma Resection].

A 71-year-old woman underwent right nephrectomy for the treatment of clear cell renal cell carcinoma at the age of 53. After 15 years, surgical removal of a solitary tumor was performed in the right adrenal gland and thyroid gland; both were diagnosed as metastases of renal cell carcinoma. Eighteen years after the initial resection, computed tomography(CT) showed multiple hypervascular tumors spreading across the entire area of the pancreas. She was referred to our hospital, and endoscopic ultrasound-guided fine needle aspiration biopsy(EUS-FNA)revealed that they were metastases from the renal cell carcinoma. Total pancreatectomy and splenectomy were performed, and the patient remains alive and well with no evidence of recurrent disease 7 months after the pancreatectomy. Furthermore, her blood glucose level is well controlled with insulin therapy.

Analysis of structure-function network decoupling in the brain systems of spastic diplegic cerebral palsy.

Manifestation of the functionalities from the structural brain network is becoming increasingly important to understand a brain disease. With the aim of investigating the differential structure-function couplings according to network systems, we investigated the structural and functional brain networks of patients with spastic diplegic cerebral palsy with periventricular leukomalacia compared to healthy controls. The structural and functional networks of the whole brain and motor system, constructed using deterministic and probabilistic tractography of diffusion tensor magnetic resonance images and Pearson and partial correlation analyses of resting-state functional magnetic resonance images, showed differential embedding of functional networks in the structural networks in patients. In the whole-brain network of patients, significantly reduced global network efficiency compared to healthy controls were found in the structural networks but not in the functional networks, resulting in reduced structural-functional coupling. On the contrary, the motor network of patients had a significantly lower functional network efficiency over the intact structural network and a lower structure-function coupling than the control group. This reduced coupling but reverse directionality in the whole-brain and motor networks of patients was prominent particularly between the probabilistic structural and partial correlation-based functional networks. Intact (or less deficient) functional network over impaired structural networks of the whole brain and highly impaired functional network topology over the intact structural motor network might subserve relatively preserved cognitions and impaired motor functions in cerebral palsy. This study suggests that the structure-function relationship, evaluated specifically using sparse functional connectivity, may reveal important clues to functional reorganization in cerebral palsy. Hum Brain Mapp 38:5292-5306, 2017. © 2017 Wiley Periodicals, Inc.

[A Surgical Resected Case of VIPoma with Para-Aortic Lymph Node Involvement].

A 72-year-old woman had severe watery diarrhea and weight loss. Computed tomography demonstrated a 55mm tumor in pancreatic tail with enlargement of para-aortic lymph nodes. There was no apparent liver metastasis. Endoscopic ultrasound demonstrated a well-circumscribed heterogenous tumor, which was diagnosed neuroendocrine tumor by endoscopic ultrasound-guided fine needle aspiration biopsy. For suspected VIPoma with para-aortic lymph node involvement, distal pancreatectomy and para-aortic lymphadenectomy was performed. The tumor was diagnosed as VIPoma by immunohistochemistry. The diarrhea improved after surgery. No evidence of recurrence was detected after a follow-up of 11 months.

Multivariate detrending of fMRI signal drifts for real-time multiclass pattern classification.

Signal drift in functional magnetic resonance imaging (fMRI) is an unavoidable artifact that limits classification performance in multi-voxel pattern analysis of fMRI. As conventional methods to reduce signal drift, global demeaning or proportional scaling disregards regional variations of drift, whereas voxel-wise univariate detrending is too sensitive to noisy fluctuations. To overcome these drawbacks, we propose a multivariate real-time detrending method for multiclass classification that involves spatial demeaning at each scan and the recursive detrending of drifts in the classifier outputs driven by a multiclass linear support vector machine. Experiments using binary and multiclass data showed that the linear trend estimation of the classifier output drift for each class (a weighted sum of drifts in the class-specific voxels) was more robust against voxel-wise artifacts that lead to inconsistent spatial patterns and the effect of online processing than voxel-wise detrending. The classification performance of the proposed method was significantly better, especially for multiclass data, than that of voxel-wise linear detrending, global demeaning, and classifier output detrending without demeaning. We concluded that the multivariate approach using classifier output detrending of fMRI signals with spatial demeaning preserves spatial patterns, is less sensitive than conventional methods to sample size, and increases classification performance, which is a useful feature for real-time fMRI classification.