Purpose
Drug reaction with eosinophilia and systemic symptoms (DRESS) syndrome is a rare but serious condition that systematically damages various internal organs through T‐cell–mediated ...immunological drug reactions. We aimed to investigate whether clinical manifestations of DRESS syndrome differ according to culprit drugs.
Methods
We retrospectively analyzed data from 123 patients with probable/definite DRESS syndrome based on the RegiSCAR criteria (January 2011 to July 2016). The data were obtained from the Korean Severe Cutaneous Adverse Reaction Registry. Causality was assessed using the World Health Organization‐Uppsala Monitoring Centre criteria. The culprit drugs were categorized as allopurinol, carbamazepine, anti‐tuberculosis drug, vancomycin, cephalosporins, dapsone, and nonsteroidal anti‐inflammatory drugs.
Results
Differences were observed among culprit drugs regarding the frequencies of hepatitis (P < 0.01), renal dysfunction (P < 0.0001), lymphadenopathy (P < 0.01), and atypical lymphocyte (P < 0.01). Latency period differed among culprit drugs (P < 0.0001), being shorter in vancomycin and cephalosporin. In terms of clinical severity, admission duration (P < 0.01) and treatment duration (P < 0.05) differed among culprit drugs, being longer in vancomycin and anti‐tuberculosis drugs, respectively.
Conclusions
Based on the findings, clinical manifestations, including latency period and clinical severity, may differ according to culprit drugs in DRESS syndrome.
To assess the utility of machine learning (ML) algorithms in predicting clinically relevant atrial high-rate episodes (AHREs), which can be recorded by a pacemaker. We aimed to develop ML-based ...models to predict clinically relevant AHREs based on the clinical parameters of patients with implanted pacemakers in comparison to logistic regression (LR). We included 721 patients without known atrial fibrillation or atrial flutter from a prospective multicenter (11 tertiary hospitals) registry comprising all geographical regions of Korea from September 2017 to July 2020. Predictive models of clinically relevant AHREs were developed using the random forest (RF) algorithm, support vector machine (SVM) algorithm, and extreme gradient boosting (XGB) algorithm. Model prediction training was conducted by seven hospitals, and model performance was evaluated using data from four hospitals. During a median follow-up of 18 months, clinically relevant AHREs were noted in 104 patients (14.4%). The three ML-based models improved the discrimination of the AHREs (area under the receiver operating characteristic curve: RF: 0.742, SVM: 0.675, and XGB: 0.745 vs. LR: 0.669). The XGB model had a greater resolution in the Brier score (RF: 0.008, SVM: 0.008, and XGB: 0.021 vs. LR: 0.013) than the other models. The use of the ML-based models in patient classification was associated with improved prediction of clinically relevant AHREs after pacemaker implantation.
The aim was to determine whether various clinical specimens obtained from COVID-19 patients contain the infectious virus.
To demonstrate whether various clinical specimens contain the viable virus, ...we collected naso/oropharyngeal swabs and saliva, urine and stool samples from five COVID-19 patients and performed a quantitative polymerase chain reaction (qPCR) to assess viral load. Specimens positive with qPCR were subjected to virus isolation in Vero cells. We also used urine and stool samples to intranasally inoculate ferrets and evaluated the virus titres in nasal washes on 2, 4, 6 and 8 days post infection.
SARS-CoV-2 RNA was detected in all naso/oropharyngeal swabs and saliva, urine and stool samples collected between days 8 and 30 of the clinical course. Notably, viral loads in urine, saliva and stool samples were almost equal to or higher than those in naso/oropharyngeal swabs (urine 1.08 ± 0.16–2.09 ± 0.85 log10 copies/mL, saliva 1.07 ± 0.34–1.65 ± 0.46 log10 copies/mL, stool 1.17 ± 0.32 log10 copies/mL, naso/oropharyngeal swabs 1.18 ± 0.12–1.34 ± 0.30 log10 copies/mL). Further, viable SARS-CoV-2 was isolated from naso/oropharyngeal swabs and saliva of COVID-19 patients, as well as nasal washes of ferrets inoculated with patient urine or stool.
Viable SARS-CoV-2 was demonstrated in saliva, urine and stool samples from COVID-19 patients up to days 11–15 of the clinical course. This result suggests that viable SARS-CoV-2 can be secreted in various clinical samples and respiratory specimens.
Background
We aimed to assess the clinical characteristics of sarcopenia by the original and revised European Working Group on Sarcopenia in Older People (EWGSOP 1 and 2), and to propose a new ...sarcopenia phenotype score (SPS) to improve relevance of clinical outcomes.
Methods
Analyses were performed in 1408 older adults of the Aging Study of PyeongChang Rural Area, a community‐based cohort in Korea. For sarcopenia definitions, we used EWGSOP 1, EWGSOP 2, and SPS, a new index counting number of abnormal domains among components of grip strength, gait speed, or muscle mass. Frailty status by the frailty index and the Cardiovascular Health Study frailty score was compared with sarcopenia measures. Prediction ability for composite outcome combining death and institutionalization due to functional decline was assessed among sarcopenia measures.
Results
Generally, sarcopenia spectrum by both EWGSOP 1 and 2 was associated with worse functional status in parameters of geriatric assessments. However, population who were considered as sarcopenic by EWGSOP 1, but not by EWGSOP 2, showed increased risk of composite outcome and worse frailty status, compared with people who were classified as not sarcopenic by both EWGSOP 1 and 2. With SPS, dose–response relationship was observed with both frailty status and outcome prediction. Prediction for composite outcome was better in SPS than in EWGSOP 2 classification.
Conclusions
A new SPS might be used to classify sarcopenic burden in older adults to resolve possible inconsistencies in phenotype correlation and outcome prediction of EWGSOP 2 criteria.
Background
The effects of obesity on prognosis in gastric cancer are controversial.
Aims
To evaluate the association between body mass index (BMI) and mortality in patients with gastric cancer.
...Methods
A single-institution cohort of 7765 patients with gastric cancer undergoing curative gastrectomy between October 2000 and June 2016 was categorized into six groups based on BMI: underweight (< 18.5 kg/m
2
), normal (18.5 to < 23 kg/m
2
), overweight (23 to < 25 kg/m
2
), mildly obese (25 to < 28 kg/m
2
), moderately obese (28 to < 30 kg/m
2
), and severely obese (≥ 30 kg/m
2
). Hazard ratios (HRs) for overall survival (OS) and disease-specific survival (DSS) were calculated using Cox proportional hazard models.
Results
We identified 1279 (16.5%) all-cause and 763 (9.8%) disease-specific deaths among 7765 patients over 83.05 months (range 1.02–186.97) median follow-up. In multivariable analyses adjusted for statistically significant clinicopathological characteristics, preoperative BMI was associated with OS in a non-linear pattern. Compared with normal-weight patients, underweight patients had worse OS HR 1.42; 95% confidence interval (CI) 1.15–1.77, whereas overweight (HR 0.84; 95% CI 0.73–0.97), mildly obese (HR 0.77; 95% CI 0.66–0.90), and moderately obese (HR 0.77; 95% CI 0.59–1.01) patients had better OS. DSS exhibited a similar pattern, with lowest mortality in moderately obese patients (HR 0.58; 95% CI 0.39–0.85). Spline analysis showed the lowest all-cause mortality risk at a BMI of 26.67 kg/m
2
.
Conclusion
In patients undergoing curative gastric cancer surgery, those who were overweight or mildly-to-moderately obese (BMI 23 to < 30 kg/m
2
) preoperatively had better OS and DSS than normal-weight patients.
Background
This study aimed to investigate risk factors for lymph node (LN) or distant metastasis after non-curative endoscopic resection (ER) of undifferentiated-type early gastric cancer (EGC).
...Methods
Of 1124 patients who underwent ER for undifferentiated-type gastric cancer at 18 tertiary hospitals across six geographic areas in Korea between 2005 and 2014, 634 with non-curative ER beyond the expanded criteria were retrospectively enrolled. According to the treatment after ER, patients were divided into additional surgery (
n
= 270) and follow-up (
n
= 364) groups. The median follow-up duration was 59 months for recurrence and 84 months for mortality.
Results
LN metastasis was found in 6.7% (18/270) of patients at surgery. Ulcer odds ratio (OR) 3.83; 95% confidence interval (CI) 1.21–12.13;
p
= 0.022 and submucosal invasion (OR 10.35; 95% CI 1.35–79.48;
p
= 0.025) were independent risk factors. In the follow-up group, seven patients (1.9%) developed LN or distant recurrence. Ulcer hazard ratio (HR) 7.60; 95% CI 1.39–35.74;
p
= 0.018, LVI (HR 6.80; 95% CI 1.07–42.99;
p
= 0.042), and positive vertical margin (HR 6.71; 95% CI 1.28–35.19;
p
= 0.024) were independent risk factors. In the overall cohort, LN metastasis rates were 9.6% in patients with two or more risk factors and 1.2% in those with no or one risk factor.
Conclusions
LVI, ulcer, submucosal invasion, and positive vertical margin are independently associated with LN or distant metastasis after non-curative ER of undifferentiated-type EGC. Surgical resection is strongly recommended for patients with two or more risk factors.
The aim of this two-center randomized controlled trial was to assess the outcomes and relative factors associated with pulpotomies performed using a premixed injectable calcium silicate cement, as ...compared to mineral trioxide aggregate in mature permanent premolar and molar teeth with reversible pulpitis. Included teeth were randomly divided into two groups according to pulpotomy material (ProRoot MTA PMTA group, Endocem MTA Premixed EPM group). After pulp exposure, the superficial pulp was either removed to a depth of 2 mm (partial pulpotomy) or completely amputated to the level of the root canal orifice (full pulpotomy). A 3-mm layer of either material was randomly placed over the pulp wound, followed by the application of a thin layer of a light-cured glass ionomer composite liner. The restoration procedure was then carried out during the same visit. After one year of treatment, the pulpotomy success rate was 94.4% (67/71), with no significant difference between the PMTA and EPM groups. The success rate was 93.9% in the PMTA group and 97.1% in the EPM group. There were no significant factors related to the procedures. EPM is a viable alternative to PMTA for single-visit pulpotomies of permanent premolars and molars.
Organisms must be able to respond to low oxygen in a number of homeostatic and pathological contexts. Regulation of hypoxic responses via the hypoxia-inducible factor (HIF) is well established, but ...evidence indicates that other, HIF-independent mechanisms are also involved. Here, we report a hypoxic response that depends on the accumulation of lactate, a metabolite whose production increases in hypoxic conditions. We find that the NDRG3 protein is degraded in a PHD2/VHL-dependent manner in normoxia but is protected from destruction by binding to lactate that accumulates under hypoxia. The stabilized NDRG3 protein binds c-Raf to mediate hypoxia-induced activation of Raf-ERK pathway, promoting angiogenesis and cell growth. Inhibiting cellular lactate production abolishes the NDRG3-mediated hypoxia responses. Our study, therefore, elucidates the molecular basis for lactate-induced hypoxia signaling, which can be exploited for the development of therapies targeting hypoxia-induced diseases.
Recent geophysical studies have highlighted the potential utility of integrating both seismic and infrasound data to improve source characterization and event discrimination efforts. However, the ...influence of each of these data types within an integrated framework is not yet well‐understood by the geophysical community. To help elucidate the role of each data type within a merged structure, we develop a neural network which fuses seismic and infrasound array data via a gated multimodal unit for earthquake‐explosion discrimination within the Korean Peninsula. Model performance is compared before and after adding the infrasound branch. We find that the seismoacoustic model outperforms the seismic model, with the majority of the improvements stemming from the explosions class. The influence of infrasound is quantified by analyzing gated multimodal activations. Results indicate that the model relies comparatively more on the infrasound branch to correct seismic predictions.
Plain Language Summary
Earthquakes and explosions can produce energy that travel as waves through the ground, seismic, and the air, infrasound. As these waves travel to the station where they are detected, they can be changed so drastically by the medium that it makes it difficult to determine what caused them. In these instances, it has been shown that using both seismic and infrasound data works better to characterize an event than using them independent of one another. However, due to the differences in how the air and ground influence the movement of energy, it is not well‐known how these types of data work in unison to give us more information about an event. In this study, we use a machine learning model trained on both seismic and infrasound data to help us better understand how they can be used together to determine their source.
Key Points
Discrimination performance within the Korean Peninsula is improved after fusing seismoacoustic data within a deep learning architecture
Neural network framework provides insight into how information in multimodal data combine to distinguish between different event types
•Exceptionally high zT in p-type (zTmax = 1.45) and n-type (zTmax = 1.4) compounds.•We controlled small grain size and anisotropic texture.•High spin orbit coupling enhances the Seebeck ...coefficient.•Suppression of bipolar diffusion and phonon scattering enhance zT values.•Low power consumption (38% reduction) and fast cooling performance (1.7 times) in TE module.
Thermoelectric technologies can be used for waste heat power generation, and for solid-state cooling without environmentally hazardous refrigerants or moving parts. Thermoelectric cooling materials like the Bismuth Tellurides have been intensively investigated for several decades, but to date, thermoelectric cooling device applications have been limited to niche markets, because of their low cooling efficiency and high power consumption. Here, we demonstrate a thermoelectric module with significantly enhanced cooling performance and low power consumption, with fast cooling, using state-of-the-art p-/n-type Bi2Te3 based thermoelectric materials. Small grain size and anisotropic texture were achieved an exceptional high performance in the p-type Ag0.0006Bi0.46Sb1.5Te3.07 and n-type (CuI)0.002Bi2Te2.7Se0.3 compounds through rapid solidification and hot extrusion processes, resulting in significantly improved thermoelectric performance over a wide temperature range (zTmax = 1.45 for the p-type and 1.40 for the n-type compounds). The observed temperature-dependent thermoelectric properties in the n-type (CuI)0.002Bi2Te2.7Se0.3 compound could be explained in terms of Rashba band splitting rather than the multiband Boltzmann transport equations. We suggest that the enhancement of thermoelectric performance is due to the increase in chemical potential by Ag- (p-type) and CuI-doping (n-type) which suppresses bipolar diffusion, while the anisotropic texture and micro grains decreases lattice thermal conductivity. The thermoelectric module using these state-of-the-art thermoelectric materials demonstrated a reduction in power consumption by 38% and an increase of cooling speed by 170% compared with commercial single crystal-based TE devices, which is promising for practical applications.
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