Soil properties of cultivation sites for mountain-cultivated ginseng at local level

AbstractBackgroundIdentifying suitable site for growing mountain-cultivated ginseng is a concern for ginseng producers. This study was conducted to evaluate the soil properties of cultivation sites for mountain-cultivated ginseng in Hamyang-gun, which is one of the most well-known areas for mountain-cultivated ginseng in Korea.MethodsThe sampling plots from 30 sites were randomly selected on or near the center of the ginseng growing sites in July and August 2009. Soil samples for the soil properties analysis were collected from the top 20 cm at five randomly selected points.ResultsMountain-cultivated ginseng was grown in soils that varied greatly in soil properties on coniferous, mixed, and deciduous broad-leaved stand sites of elevations between > 200 m and < 1,000 m. The soil bulk density was higher in Pinus densiflora than in Larix leptolepis stand sites and higher in the < 700-m sites than in > 700-m sites. Soil pH was unaffected by the type of stand sites (pH 4.35–4.55), whereas the high-elevation sites of > 700 m were strongly acidified, with pH 4.19. The organic carbon and total nitrogen content were lower in the P. densiflora stand sites than in the deciduous broad-leaved stand sites. Available phosphorus was low in all of the stand sites. The exchangeable cation was generally higher in the mixed and low-elevation sites than in the P. densiflora and high-elevation sites, respectively.ConclusionThese results indicate that mountain-cultivated ginseng in Korea is able to grow in very acidic, nutrient-depleted forest soils

Convolution channel separation and frequency sub-bands aggregation for music genre classification

In music, short-term features such as pitch and tempo constitute long-term semantic features such as melody and narrative. A music genre classification (MGC) system should be able to analyze these features. In this research, we propose a novel framework that can extract and aggregate both short- and long-term features hierarchically. Our framework is based on ECAPA-TDNN, where all the layers that extract short-term features are affected by the layers that extract long-term features because of the back-propagation training. To prevent the distortion of short-term features, we devised the convolution channel separation technique that separates short-term features from long-term feature extraction paths. To extract more diverse features from our framework, we incorporated the frequency sub-bands aggregation method, which divides the input spectrogram along frequency bandwidths and processes each segment. We evaluated our framework using the Melon Playlist dataset which is a large-scale dataset containing 600 times more data than GTZAN which is a widely used dataset in MGC studies. As the result, our framework achieved 70.4% accuracy, which was improved by 16.9% compared to a conventional framework

One-Step Knowledge Distillation and Fine-Tuning in Using Large Pre-Trained Self-Supervised Learning Models for Speaker Verification

The application of speech self-supervised learning (SSL) models has achieved remarkable performance in speaker verification (SV). However, there is a computational cost hurdle in employing them, which makes development and deployment difficult. Several studies have simply compressed SSL models through knowledge distillation (KD) without considering the target task. Consequently, these methods could not extract SV-tailored features. This paper suggests One-Step Knowledge Distillation and Fine-Tuning (OS-KDFT), which incorporates KD and fine-tuning (FT). We optimize a student model for SV during KD training to avert the distillation of inappropriate information for the SV. OS-KDFT could downsize Wav2Vec 2.0 based ECAPA-TDNN size by approximately 76.2%, and reduce the SSL model's inference time by 79% while presenting an EER of 0.98%. The proposed OS-KDFT is validated across VoxCeleb1 and VoxCeleb2 datasets and W2V2 and HuBERT SSL models. Experiments are available on our GitHub

Prevalence of sarcopenia and sarcopenic obesity in Korean adults: The Korean Sarcopenic Obesity Study (KSOS)

*Context:* Sarcopenic obesity (SO), a combination of excess weight and reduced muscle mass and/or strength, is suggested to be associated with an increased risk of adverse health outcomes. &#xd;&#xa;*Objectives:* To examine the prevalence and characteristics of Sarcopenic and SO defined by using different indices such as Appendicular Skeletal muscle Mass (ASM)/height^2^ and Skeletal Muscle Index (SMI (%): skeletal muscle mass (kg)/weight (kg) &#xd7; 100) for Korean adults. &#xd;&#xa;*Methods:* 591 participants were recruited from the Korean Sarcopenic Obesity Study (KSOS) which is an ongoing prospective observational cohort study. Analysis was conducted in 526 participants (328 women, 198 men) who had complete data on body composition using Dual X-ray absorptiometry and computed tomography. &#xd;&#xa;*Results:* The prevalence of sarcopenia and SO increases with aging. Using two or more standard deviations (SD) of ASM/height^2^ below reference values from young, healthy adults as a definition of sarcopenia, the prevalence of sarcopenia and SO was 6.3% and 1.3% in men and 4.1% and 1.7% in women over 60 years of age. However, using two or more SD of SMI, the prevalence of sarcopenia and SO was 5.1% and 5.1% respectively in men and 14.2% and 12.5% respectively in women. As defined by SMI, subjects with SO had 3 times the risk of metabolic syndrome (OR = 3.03, 95% confidence interval (CI) = 1.26-7.26) and subjects with non-sarcopenic obesity had approximately 2 times the risk of metabolic syndrome (OR = 1.89, 95% CI = 1.18-3.02) compared with normal subjects. &#xd;&#xa;*Conclusion:* Obese subjects with relative sarcopenia were associated with a greater likelihood for metabolic syndrome. As Koreans were more obese and aging, the prevalence of SO and its impact on health outcomes are estimated to be rapidly grow. Further research is requested to establish the definition, cause and consequences of SO.&#xd;&#xa

Blood neurofilament light chain as a biomarker for monitoring and predicting paclitaxel-induced peripheral neuropathy in patients with gynecological cancers

ObjectiveWe aimed to evaluate the potential of serum neurofilament light chain (sNfL) and serum brain-derived neurotrophic factor (sBDNF) as reliable biomarkers for paclitaxel-induced peripheral neuropathy (PIPN).MethodsForty-eight patients with gynecologic cancer scheduled to undergo six cycles of paclitaxel-based chemotherapy at the National Cancer Center of Korea between September 2020 and January 2022 were prospectively assessed during and after chemotherapy.ResultsAt the end of the chemotherapy, 12 (25%) patients were classified as having grade 3 PIPN according to the National Cancer Institute-Common Toxicity Criteria. The sNfL levels increased during paclitaxel treatment in all patients. After two, four, and six cycles, patients with grade 3 PIPN exhibited higher mean sNfL levels than those in the 0–2 grade range (p = 0.004, p = 001, and p &lt; 0.001, respectively). For sNfL levels ≥ 124 pg/mL, after two cycles of chemotherapy, the sensitivity and specificity for predicting grade 3 PIPN at the end of treatment were 80% and 79%, respectively. Over the course of paclitaxel-based treatment, sBDNF levels continued to decrease regardless of the severity of PIPN. At the end of treatment and six months after chemotherapy, patients with grade 3 PIPN had lower sBDNF levels than those within the 0–2 grade range (p =0.037 and 0.02, respectively), and the patients in the latter group had better clinical symptoms six months after the end of treatment.ConclusionsThe sNfL levels during paclitaxel-based chemotherapy reflect ongoing neuroaxonal injury and serve as reliable biomarkers of PIPN severity. The sNfL levels during early treatment with paclitaxel might be prognostic indicators for PIPN progression. Low sBDNF levels 6 months after chemotherapy might adversely affect PIPN recovery

The comparison of the impact of arterial stiffness and central pressure on left ventricular geometry and diastolic function

Background This study was performed to compare the associations of brachial-ankle pulse wave velocity (baPWV) and central blood pressure (CBP) measurements with left ventricular (LV) geometry and diastolic function. Methods A total of 77 subjects (64.5 ± 10.8 years, 67.5% females) without documented cardiovascular disease were prospectively recruited. All subjects underwent transthoracic echocardiography, baPWV and noninvasive measurement of CBP on the same day. Results In simple linear correlation analyses, neither baPWV nor CBP was associated with LV mass index or relative wall thickness (P > 0.05 for each). Although baPWV significantly correlated with septal e´ velocity in simple linear correlation analyses (r = 0.258, P = 0.025), the significance was lost after controlling for potential confounder (P = 0.881). In simple linear correlation analyses, central systolic blood pressure (CSBP) and central pulse pressure (CPP) significantly correlated with both septal e´ velocity or E/e´ (P  0.05 for each). After controlling for confounders, including age, sex and body mass index, CSBP correlated with septal e´ velocity (β = − 0.258, P = 0.025), but not with E/e´ (P = 0.074). CPP correlated with both septal e´ velocity (β = − 0.300, P = 0.014) and E/e´ (β = 0.428, P = 0.002) in the same multivariable model. Conclusions In subjects without documented cardiovascular disease, CSBP and CPP may be more strongly associated with LV diastolic function than baPWV. Further studies with a larger sample size are needed to confirm our results.This study was supported by a research grant from the Korean Society of Hypertension

Serotype-Independent Protection Against Invasive Pneumococcal Infections Conferred by Live Vaccine With lgt Deletion

Streptococcus pneumoniae is the most common respiratory bacterial pathogen among cases of community-acquired infection in young children, older adults, and individuals with underlying medical conditions. Although capsular polysaccharide-based pneumococcal vaccines have contributed to significant decrease in invasive pneumococcal infections, these vaccines have some limitations, including limited serotype coverage, lack of effective mucosal antibody responses, and high costs. In this study, we investigated the safety and immunogenicity of a live, whole-cell pneumococcal vaccine constructed by deleting the gene for prolipoprotein diacylglyceryl transferase (lgt) from the encapsulated pneumococcal strain TIGR4 (TIGR4Δlgt) for protection against heterologous pneumococcal strains. Pneumococcal strain TIGR4 was successfully attenuated by deletion of lgt, resulting in the loss of inflammatory activity and virulence. TIGR4Δlgt colonized the nasopharynx long enough to induce strong mucosal IgA and IgG2b-dominant systemic antibody responses that were cross-reactive to heterologous pneumococcal serotypes. Finally, intranasal immunization with TIGR4Δlgt provided serotype-independent protection against pneumococcal challenge in mice. Taken together, our results suggest that TIGR4Δlgt is an avirulent and attractive broad-spectrum pneumococcal vaccine candidate. More broadly, we assert that modulation of such “master” metabolic genes represents an emerging strategy for developing more effective vaccines against numerous infectious agents

다변량 기법을 이용한 혼합치열기 분석법

Objective: To develop a mixed dentition analysis method in consideration of the normal variation of tooth sizes. Methods: According to the tooth-size of the maxillary central incisor, maxillary 1st molar, mandibular central incisor, mandibular lateral incisor, and mandibular 1st molar, 307 normal occlusion subjects were clustered into the smaller and larger tooth-size groups. Multiple regression analyses were then performed to predict the sizes of the canine and premolars; for the 2 groups and both genders separately. For a cross validation dataset, 504 malocclusion patients were assigned into the 2 groups. Then multiple regression equations were applied. Results: Our results show that the maximum errors of the predicted space for the canine, 1st and 2nd premolars were 0.71 and 0.82 mm residual standard deviation for the normal occlusion and malocclusion groups, respectively. For malocclusion patients, the prediction errors did not imply a statistically significant difference depending on the types of malocclusion nor the types of tooth-size groups. The frequency of prediction error more than 1 mm and 2 mm were 17.3% and 1.8%, respectively. The overall prediction accuracy was dramatically improved in this study compared to that of previous studies. Conclusions: The computer aided calculation method used in this study appeared to be more efficient. (Korean J Orthod 2009;39(2):112-119)본 연구는 서울대학교 치과병원 연구비(04-2007-0013) 지원을 받아 시행되었음.