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Abstract Background Lymphovascular invasion (LVI) has been identified as a prognostic factor in various cancers, but its significance in node-negative gastric cancer remains unclear. Gastric cancer prognosis is notably affected by lymph node metastasis, with LVI potentially indicating metastatic spread. Methods A retrospective review was conducted on 5,699 patients who underwent curative radical gastrectomy for gastric cancer between 1989 and 2018. The median follow-up duration was 62 months (0–362 months). Overall, disease-specific, and disease-free survival were compared based on LVI status and stratified by T stage. Additionally, patients with stage IIA or T2N0 were further evaluated to clarify the clinical significance of LVI in the T2N0 group. Results The T2N0 LVI-positive group exhibited significantly poor prognosis than those in the T2N0 LVI-negative group, with no significant differences observed on comparing the T2N0 LVI-positive group with the T2N1 LVI-negative or LVI-positive groups. Furthermore, although the T2N0 LVI-negative group demonstrated better prognosis compared to the IIA group, the T2N0 LVI-positive group exhibited worse survival. In addition, LVI positivity was an independent risk factor for overall survival in T2N0 patients. Conclusions LVI in node-negative gastric cancer has clinical significance as a prognostic indicator, indicating an increased risk of disease recurrence and poor survival especially in T2 cohort. This indicates an increased likelihood of lymph node involvement and may influence treatment decisions and follow-up strategies.

Abstract Non-suicidal self-injury (NSSI) among adolescents continues to be a significant public health concern worldwide. A recent systematic review and meta-analysis found that the global prevalence of NSSI in adolescents aged 12–18 years was 17.2%, with higher rates reported among females (19.7%) than males (14.8%). This behavior has been linked to several negative outcomes, such as depression, anxiety, substance abuse, and suicidal ideation. The present study aimed to classify adolescents based on intrapersonal and interpersonal factors associated with NSSI proposed in Nock’s (2009) integrated model of NSSI, to identify distinct clusters targeting specific risk factors. This encompassed negative cognition, emotional vulnerability, poor coping skill, peer-victimization, family adaptability, and perceived stress. A total of 881 adolescents aged 11–16 years in South Korea completed self-reported questionnaires on automatic thoughts, depression, emotional regulation, peer victimization, family adaptability and perceived stress. Latent profile analysis (LPA) revealed three distinct classes: “the severe group”, “the moderate group”, “the mild group”. Class 3 (“severe group”: N = 127) exhibited greater severity related to NSSI, including negative cognition, emotional vulnerability, poor coping skills, peer victimization, and perceived stress, with weaker levels of factors that can prevent NSSI compared to class 1 (“mild group”: N = 416) and class 2 (“moderated group”: N = 338). The present study emphasizes the importance of considering both intrapersonal (e.g., negative automatic thoughts & emotional dysregulation) and interpersonal factors (i.e., peer victimization) when understanding NSSI - among adolescents. These findings can be utilized to develop interventions aimed at reducing the prevalence and severity of NSSI among adolescents.

Abstract Background Astrocytes, one of the most resilient cells in the brain, transform into reactive astrocytes in response to toxic proteins such as amyloid beta (Aβ) in Alzheimer’s disease (AD). However, reactive astrocyte-mediated non-cell autonomous neuropathological mechanism is not fully understood yet. We aimed our study to find out whether Aβ-induced proteotoxic stress affects the expression of autophagy genes and the modulation of autophagic flux in astrocytes, and if yes, how Aβ-induced autophagy-associated genes are involved Aβ clearance in astrocytes of animal model of AD. Methods Whole RNA sequencing (RNA-seq) was performed to detect gene expression patterns in Aβ-treated human astrocytes in a time-dependent manner. To verify the role of astrocytic autophagy in an AD mouse model, we developed AAVs expressing shRNAs for MAP1LC3B/LC3B (LC3B) and Sequestosome1 (SQSTM1) based on AAV-R-CREon vector, which is a Cre recombinase-dependent gene-silencing system. Also, the effect of astrocyte-specific overexpression of LC3B on the neuropathology in AD (APP/PS1) mice was determined. Neuropathological alterations of AD mice with astrocytic autophagy dysfunction were observed by confocal microscopy and transmission electron microscope (TEM). Behavioral changes of mice were examined through novel object recognition test (NOR) and novel object place recognition test (NOPR). Results Here, we show that astrocytes, unlike neurons, undergo plastic changes in autophagic processes to remove Aβ. Aβ transiently induces expression of LC3B gene and turns on a prolonged transcription of SQSTM1 gene. The Aβ-induced astrocytic autophagy accelerates urea cycle and putrescine degradation pathway. Pharmacological inhibition of autophagy exacerbates mitochondrial dysfunction and oxidative stress in astrocytes. Astrocyte-specific knockdown of LC3B and SQSTM1 significantly increases Aβ plaque formation and GFAP-positive astrocytes in APP/PS1 mice, along with a significant reduction of neuronal marker and cognitive function. In contrast, astrocyte-specific overexpression of LC3B reduced Aβ aggregates in the brain of APP/PS1 mice. An increase of LC3B and SQSTM1 protein is found in astrocytes of the hippocampus in AD patients. Conclusions Taken together, our data indicates that Aβ-induced astrocytic autophagic plasticity is an important cellular event to modulate Aβ clearance and maintain cognitive function in AD mice.

Abstract Background Nonsuicidal self-injury (NSSI) combined with suicide ideation increases the risk of suicidal behaviors. Depression and posttraumatic stress disorder (PTSD) are comorbidities of NSSI compounding this relationship. The present study compared diagnostic subgroups of NSSI based on current depression and PTSD on psychological correlates (i.e., vulnerabilities and impairment) and suicidal presentations (i.e., suicidal cognitions and behaviors) in a psychiatric sample of adolescents. Methods Eighty-seven adolescents meeting DSM-5 criteria for NSSI and 104 age-range-matched nonclinical controls (NC) participated. Participants completed self-report measures on psychological vulnerabilities and impairment (e.g., emotion regulation difficulties, negative cognitions). Adolescents with NSSI also completed clinical interviews on psychiatric diagnoses and a recent self-injurious behavior (SIB). Scores on the psychological correlates of NSSI were compared between adolescents with NSSI and NC, and across three diagnostic subgroups of NSSI (A: NSSI+/depression-/PTSD-, n = 14; B: NSSI+/depression+/PTSD-, n = 57; C: NSSI+/depression+/PTSD+, n = 14). Differences between NSSI diagnostic subgroups were tested on the motives for SIB and accompanying suicidal presentations (e.g., desire, intent, motive, lethality). Results Common comorbidities of NSSI included depression, panic disorder, generalized anxiety disorder, and PTSD. The NSSI subgroup classification was significantly associated with panic disorder, which was controlled for in the subsequent group comparisons. Overall, adolescents who engage in NSSI with vs. without depression reported more psychological vulnerabilities and impairment and a greater degree of suicidal thoughts/desire in SIB (i.e., groups B, C >A), which remained significant after controlling for panic disorder. An increased odds of the suicidal motive for SIB was found in adolescents with all three conditions (i.e., group C: NSSI+/depression+/PTSD+) compared to those with NSSI but neither depression nor PTSD (i.e., group A: NSSI+/depression-/PTSD-); however, this was not significant after controlling for panic disorder. Conclusions Psychological underpinnings of adolescent NSSI in clinical contexts may be largely associated with concurrent depression. Suicidal motives in adolescents who engage in NSSI in the presence of depression and PTSD may be confounded by the co-occurrence of panic disorder. This study warrants the importance of attending to the comorbid depression with NSSI in adolescents as it is related to an increase in suicidal desire accompanying SIB.

Biofuel has received worldwide attention as one of the most promising renewable energy sources. Particularly, in many countries such as the U.S. and Brazil, first-generation ethanol from corn and sugar cane has been used as automobile fuel after blending with gasoline. Nevertheless, in order to continuously increase the use of biofuels, efforts are needed to reduce the cost of biofuel production and increase its profitability. This can be achieved by increasing the efficiency of a sequential biofuel production process consisting of multiple operations such as feedstock supply, pretreatment, fermentation, distillation, and biofuel transportation. This study aims at investigating methodologies for predicting feedstock yields, which is the earliest step for stable and sustainable biofuel production. Particularly, this study reviews feedstock yield estimation approaches using machine learning technologies that focus on gradually improving estimation accuracy by using big data and computer algorithms from traditional statistical approaches. Given that it is becoming increasingly difficult to stably produce biofuel feedstocks as climate change worsens, research on developing predictive modeling for raw material supply using the latest ML techniques is very important. As a result, this study will help researchers and engineers predict feedstock yields using various machine learning techniques, and contribute to efficient and stable biofuel production and supply chain design based on accurate predictions of feedstocks.

Onion (Allium cepa) is a major field vegetable in South Korea and has been produced for a long time along with cabbage, radish, garlic, and dried peppers. However, as field vegetables, including onions, have recently been imported at low prices, the profitability of onion production in South Korea is beginning to be at risk. In order to maximize farmers’ profits through onion production, this study develops onion yield prediction models via an ensemble learning-based framework involving linear regression, polynomial regression, support vector regression, decision tree, ridge regression, and lasso regression. The use of nitrogen fertilizers is considered an independent variable in the development of the yield prediction model. This is because the use of nitrogen fertilizers accounts for the highest production cost (13.47%) after labor cost (41.21%) and seed cost (17.42%), and it also directly affects onions yields. For the model development, five research datasets on changes in onion yield according to changes in the use of existing nitrogen fertilizers were used. In addition, a non-linear optimization model was devised using onion yield prediction models for the profit maximization of onion production. As a result, the developed non-linear optimization model using polynomial regression enables an increase in profits from onion production by 67.28%.

Abstract Background Weight changes after gastrectomy affect not only quality of life but also prognosis and survival. However, it remains challenging to predict the weight changes of individual patients. Using clinicopathological variables, we built a user-friendly tool to predict weight change after curative gastrectomy for gastric cancer. Methods The clinical data of 984 patients who underwent curative gastrectomy between 2009 and 2013 were retrospectively reviewed and analyzed. Multivariate logistic regression was performed to identify variables predictive of postoperative weight change. A nomogram was developed and verified via bootstrap resampling. Results Age, sex, performance status, body mass index, extent of resection, pathological stage, and postoperative weight change significantly influenced postoperative weight recovery. Postoperative levels of hemoglobin, albumin, ferritin and total iron-binding capacity were significant covariates. The nomogram performed well (concordance index = 0.637); calibration curves indicated appropriate levels of agreement. We developed an online weight prediction calculator based on the nomogram ( http://gc-weightchange.com/en/front/ ). Conclusions The novel, Web-calculator based on the predictive model allows surgeons to explore patient weight patterns quickly. The model identifies patients at high risk for weight loss after gastrectomy; such patients require multidisciplinary medical support.

The global healthcare market is expanding, with a particular focus on personalized care for individuals who are unable to leave their homes due to the COVID-19 pandemic. However, the implementation of personalized care is challenging due to the need for additional devices, such as smartwatches and wearable trackers. This study aims to develop a human body simulation that predicts and visualizes an individual’s 3D body changes based on 2D images taken by a portable device. The simulation proposed in this study uses semantic segmentation and image-based reconstruction techniques to preprocess 2D images and construct 3D body models. It also considers the user’s exercise plan to enable the visualization of 3D body changes. The proposed simulation was developed based on human-in-the-loop experimental results and literature data. The experiment shows that there is no statistical difference between the simulated body and actual anthropometric measurement with a p-value of 0.3483 in the paired t-test. The proposed simulation provides an accurate and efficient estimation of the human body in a 3D environment, without the need for expensive equipment such as a 3D scanner or scanning uniform, unlike the existing anthropometry approach. This can promote preventive treatment for individuals who lack access to healthcare.

Abstract Background Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive paralysis due to motor neuron degeneration. It has been proposed that epigenetic modification and transcriptional dysregulation may contribute to motor neuron death. In this study, we investigate the basis for therapeutic approaches to target lysine-specific histone demethylase 1 (LSD1) and elucidate the mechanistic role of LSD1-histone H3K4 signaling pathway in ALS pathogenesis. Methods In order to examine the role of spermidine (SD), we administered SD to an animal model of ALS (G93A) and performed neuropathological analysis, body weight, and survival evaluation. Results Herein, we found that LSD1 activity is increased while levels of H3K4me2, a substrate of LSD1, is decreased in cellular and animal models of ALS. SD administration modulated the LSD1 activity and restored H3K4me2 levels in ChAT-positive motor neurons in the lumbar spinal cord of ALS mice. SD prevented cellular damage by improving the number and size of motor neurons in ALS mice. SD administration also reduced GFAP-positive astrogliogenesis in the white and gray matter of the lumbar spinal cord, improving the neuropathology of ALS mice. Moreover, SD administration improved the rotarod performance and gait analysis of ALS mice. Finally, SD administration delayed disease onset and prolonged the lifespan of ALS (G93A) transgenic mice. Conclusion Together, modulating epigenetic targets such as LSD1 by small compounds may be a useful therapeutic strategy for treating ALS.

Biodiesel has received worldwide attention as a renewable energy resource that reduces greenhouse gas (GHG) emissions. Unlike traditional fossil fuels, such as coal, oil, and natural gas, biodiesel made of vegetable oils, animal fats, or recycled restaurant grease incurs higher production costs, so its supply chain should be managed efficiently for operational cost reduction. To this end, multiple machine learning technologies have recently been applied to estimate feedstock yield, biodiesel productivity, and biodiesel quality. This study aims to identify the machine learning technologies useful in particular areas of supply chain management by review of the scientific literature. As a result, nine machine learning algorithms, the Gaussian process model (GPM), random forest (RF), artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor (KNN), AdaBoost regression, multiple linear regression (MLR), linear regression (LR). and multilayer perceptron (MLP), are used for feedstock yield estimation, biodiesel productivity prediction, and biodiesel quality prediction. Among these, RF and ANN were identified as the most appropriate algorithms, providing high prediction accuracy. This finding will help engineers and managers understand concepts of machine learning technologies so they can use appropriate technology to solve operational problems in supply chain management.

Building-integrated photovoltaics (BIPVs) entail the use of photovoltaics as building materials, such as windows, roofs, and walls. Owing to their electricity-generation ability, BIPVs have become popular building materials for green buildings. This study involves an economic feasibility analysis of BIPVs for an agricultural research and development center in Fiji. The computerized relative allocation of facilities technique (CRAFT) is extended for cost-efficient facility design, and the levelized cost of electricity (LCOE) of BIPVs is evaluated to identify feasible alternatives from among three options, namely roof-integrated, window, and rooftop BIPVs. From the experiments, the LCOE values of the roof-integrated, window, and rooftop BIPVs were USD 0.13/kWh, 0.17/kWh, and 0.09/kWh, respectively. Moreover, the profit for the window BIPV was negative when the discount rate was greater than 0.08 due to its inefficient productivity. Contrarily, the roof-integrated BIPV showed a reasonable LCOE even though it required the highest investment cost. Nevertheless, further efforts are needed to reduce the cost of BIPVs for practical implementation.

Background/Objective: Physical inactivity is one of the major cardiovascular disease risk factors; however, not much is known regarding lifetime bone-specific physical activity and arterial stiffness. The aim of this cross-sectional study was to determine whether total bone-specific physical activity score (tBPAQ) was related to arterial stiffness and body composition in healthy young adults. Methods: Healthy young women (n = 56, 20.3 ± 1.3 years) and men (n = 52, 21.0 ± 1.2 years) between 18 and 25 years were recruited for this study. The tBPAQ was used to obtain a comprehensive account of lifetime bone-loading physical activity. We measured the carotid to femoral pulse wave velocity (cfPWV) to evaluate arterial stiffness using the novel oscillometric device (SphygmoCor XCEL). Dual energy X-ray absorptiometry was used to measure bone free lean body mass (BFLBM, kg) and % total body fat. Results: Partial correlations analyses showed a significant inverse relationship between tBPAQ and cfPWV (r = - 0.371, p = 0.007) in young women; however, this relationship was not found in young men (p > 0.05). There were significant negative correlations between tBPAQ and % total body fat in both young women (r = - 0.265, p = 0.048) and men (r = - 0.327, p = 0.018). No significant relationships were found between tBPAQ and BFLBM (p > 0.05). Conclusion: Our study provides preliminary evidence of sex-specificity of negative relationships of tBPAQ with i) cfPWV (women only) and ii) % total body fat (men and women). Whether bone-loading physical activity can lead to better cardiometabolic outcomes needs to be examined.

In addition to complications of acute diseases, chronic viral infections are linked to both malignancies and autoimmune disorders. Lack of adequate treatment options for Epstein-Barr virus (EBV), Human T-lymphotropic virus type 1 (HTLV-1), and human papillomavirus (HPV) remains. The NexImmune Artificial Immune Modulation (AIM) nanoparticle platform can be used to direct T cell responses by mimicking the dendritic cell function. In one application, AIM nanoparticles are used ex vivo to enrich and expand (E+E) rare populations of multi-antigen-specific CD8+ T cells for use of these cells as an AIM adoptive cell therapy. This study has demonstrated using E+E CD8+ T cells, the functional relevance of targeting EBV, HTLV-1, and HPV. Expanded T cells consist primarily of effector memory, central memory, and self-renewing stem-like memory T cells directed at selected viral antigen peptides presented by the AIM nanoparticle. T cells expanded against either EBV- or HPV-antigens were highly polyfunctional and displayed substantial in vitro cytotoxic activity against cell lines expressing the respective antigens. Our initial work was in the context of exploring T cells expanded from healthy donors and restricted to human leukocyte antigen (HLA)-A*02:01 serotype. AIM Adoptive Cell Therapies (ACT) are also being developed for other HLA class I serotypes. AIM adoptive cell therapies of autologous or allogeneic T cells specific to antigens associated with acute myeloid leukemia and multiple myeloma are currently in the clinic. The utility and flexibility of the AIM nanoparticle platform will be expanded as we advance the second application, an AIM injectable off-the-shelf nanoparticle, which targets multiple antigen-specific T cell populations to either activate, tolerize, or destroy these targeted CD8+ T cells directly in vivo, leaving non-target cells alone. The AIM injectable platform offers the potential to develop new multi-antigen specific therapies for treating infectious diseases, cancer, and autoimmune diseases.

Ethanol, a common renewable energy resource, can reduce greenhouse gas (GHG) emissions to resolve the problem of global warming worldwide. Various feedstocks such as corn, sugarcane, maize stover, and wheat straw can be utilized for ethanol production. They determine production operations and relevant costs. Although there are monetary incentives and government policies in different countries to increase ethanal use, it is still challenging to make its sales price competitive due to the inefficient supply chain of ethanol. Unlike fossil fuels such as coal, oil, and natural gas using a well-designed supply chain in the long history of mankind, additional efforts are needed to organize and stabilize the supply chain of ethanol efficiently. The goal of this study is to investigate how simulation modeling techniques can be applied to various supply chain management issues of ethanol. Particularly, application cases of three major simulation paradigms such as discrete-event simulation, system dynamics, and agent-based simulation are investigated by conducting a scientific literature review. The findings of this study will contribute to the expansion of simulation use in the field of biofuel supply chain management.

Building integrated photovoltaics (BIPVs) are becoming popular as building elements such as windows, roofs, and outer walls. Because BIPVs have both a construction material function and an electricity generation function, they are a promising alternative to sustainable buildings. This study aims to propose a novel agrivoltaic system design that produces crops underneath photovoltaic (PV) modules. Regarding the fact that crop growth is significantly influenced by shading from PV modules, roof BIPVs with different shading ratios can lead to increased crop productivity. Thus, BIPV design should be investigated based on the performance estimation and feasibility evaluation of different shading ratios in an agrivoltaic system. To this end, electricity generation and crop production models are devised by polynomial regression (PR) based on field experiment data collected from the agrivoltaic system at the Agricultural Research Service Center in Naju-si, South Korea. The experiment shows that a shading ratio of 30% allows for the maximization of the profitability of electricity and soybean production in an agrivoltaic system equipped with BIPVs. As a result, this research will contribute to implementing an agrivoltaic system with various BIPVs.

In the Architecture, Engineering, and Construction (AEC) industry, virtual environments are being utilized to enhance communication among stakeholders and improve visual comprehension. However, stakeholders possess diverse personal characteristics which can affect their spatial recognition ability in virtual spaces. Despite the potential impact of these individual traits, related research still needs to be more comprehensive. Therefore, this study analyzed how each individual’s characteristics influence spatial recognition in a Building Information Model (BIM)-based virtual environment. A quantitative methodology via a survey was employed to investigate the influence of personal factors such as age, gender, education level, and gaming experience on spatial recognition. In a 3D virtual corridor using BIM software, 76 participants were asked to navigate the corridor using a controller and count 23 sprinklers. Of the 76 participants, 30 responses were selected for the statistical analysis. The results demonstrate that age, gender, and education level did not significantly affect spatial recognition in the virtual environment. Conversely, participants with gaming experience tended to perceive spaces in the virtual environment more accurately and realistically, showing a statistically significant difference. This outcome suggests that gaming experience is crucial in enhancing spatial recognition ability in virtual environments. The findings from this study offer critical insights into the impact of individual characteristics on spatial recognition, providing valuable information for the future practical use of BIM-based virtual environments, and can subsequently assist in discovering efficient communication methods among stakeholders.

Various types of photovoltaic (PV) modules have been developed to exploit solar energy, a major renewable energy resource. One of the popular types of PV modules is building-integrated photovoltaics (BIPV), which are PV modules used as building materials. The goal of this study is to conduct an economic feasibility analysis of BIPV on the rooftop of the Keith D. McFarland Science Building at Texas A&M University, Commerce, Texas. To this end, a polynomial regression (PR) model is developed to estimate the electricity generation quantity of solar energy in the subject area, where the maximum temperature is 104 °F (40 °C) in summer. The developed PR models are used to estimate the potential profit of BIPV on the rooftop of the subject building, and the results are compared with the profit of a green roof system at the subject building. The economic feasibility analyses show that the levelized cost of electricity (LCOE) of the green roof system is approximately 39.77% higher than that of the BIPV system at a discount rate of 5%. Thus, the BIPV system is more profitable than the green roof system; consequently, this research will contribute to the implementation of BIPV on building rooftops and the expansion of renewable energy use in preference to fossil fuel.

Abstract Background Accumulated evidence suggests that individuals with social anxiety disorder (SAD) are at particular risk of developing alcohol use disorder (AUD). Yet, little is known about the mechanisms under this high comorbidity. This study aimed to elucidate the process of the development of alcohol related problems among individuals with elevated social anxiety. We investigated the moderation effect of difficulties in emotion regulation on the relationship between symptoms of social anxiety, coping and conformity motives and alcohol related problems. Methods In a sample of university students (N = 647) in South Korea, we examined whether cognitive (fear of negative evaluation), behavioral (social avoidance), and physiological symptoms (concerns over physiological symptoms) of social anxiety affect alcohol related problems with the mediation of coping and conformity motives. Furthermore, difficulties in emotion regulation were hypothesized to moderate each mediational path. Results Results showed that the fear of negative evaluation and concerns over physiological symptoms were associated with alcohol related problems with the mediation of conformity and coping motives, respectively. As hypothesized, each path was moderated by difficulties in emotion regulation. Conclusions Findings suggest that coping and conformity motives to cope with cognitive and physiological symptoms of social anxiety were related to alcohol related problems. In addition, individuals with high levels of difficulties in emotion regulation were prone to exhibit more alcohol related problems.

In this study, we compared acute and chronic bone marker and hormone responses to 6 weeks of low intensity (20% 1RM) blood flow restriction (BFR20) resistance training to high intensity (70% 1RM) traditional resistance training (TR70) and moderate intensity (45% 1RM) traditional resistance training (TR45) in young men (18–35 years). Participants were randomized to one of the training groups or to a control group (CON). The following training programs were performed 3 days per week for 6 weeks for knee extension and knee flexion exercises: BFR20, 20%1RM, 4 sets (30, 15, 15, 15 reps) wearing blood flow restriction cuffs around the proximal thighs; TR70, 70% 1RM 3 sets 10 reps; and TR45, 45% 1RM 3 sets 15 reps. Muscle strength and thigh cross-sectional area were assessed at baseline, between week 3 and 6 of training. Acute bone marker (Bone ALP, CTX-I) and hormone (testosterone, IGF-1, IGFBP-3, cortisol) responses were assessed at weeks 1 and 6, with blood collection done in the morning after an overnight fast. The main findings were that the acute bone formation marker (Bone ALP) showed significant changes for TR70 and BFR20 but there was no difference between weeks 1 and 6. TR70 had acute increases in testosterone, IGF-1, and IGFBP-3 (weeks 1 and 6). BFR20 had significant acute increases in testosterone (weeks 1 and 6) and in IGF-1 at week 6, while TR45 had significant acute increases in testosterone (week 1), IGF-1 (week 6), and IGFBP-3 (week 6). Strength and muscle size gains were similar for the training groups. In conclusion, low intensity BFR resistance training was effective for stimulating acute bone formation marker and hormone responses, although TR70 showed the more consistent hormone responses than the other training groups.

This study examined the perceived contingent factors that affect South Korean citizens’ image of the city they reside in. The respondents in this study perceived the image of their city through two dimensions––leading and safe––during the COVID-19 era. When respondents perceived the openness and expertise of the local government, the transformational and transactional leadership of the government leader, liberal political orientation of the leader, lower degree of law compliance of the mayor, high degree of citizenship, and high level of living infrastructure and competitiveness as attributes of the city, they were more likely to perceive the city as having a “leading” image. The perceived cultural characteristics of the local government, specifically the factor of hierarchy and regulation, the perceptions of citizenship, and all three variables regarding the perceptions related to city attributes (i.e., environmental, cultural, and living infrastructures and competitiveness) positively influenced the perception of a “safe” city image. Based on the results, various theoretical and practical implications were discussed in this study.

Despite the rapidly increasing rate of non-suicidal self-injury (NSSI) among adolescents, there is a dearth of culturally appropriate psychological measures screening for NSSI among the adolescents in the Asian countries. This study aimed to develop and validate the Self-Harm Screening Inventory (SHSI), a culturally sensitive and suitable scale for screening adolescents for NSSI. In total, 514 Korean adolescents (aged 12-16 years) were recruited nationwide. All participants gave informed consent and completed the online self-report measures on NSSI, depression, anxiety, and self-esteem. Thereafter, preliminary items were developed through a series of steps: literature review, ratings of experts on self-harm and suicide, and statistical analyses. Ten of the 20 preliminary items were eliminated after exploratory factor analysis due to low endorsement and factor loading (less than .70). The final version of the SHSI comprised 10 binary items relating to self-harm behaviors within the past year (e.g., cut my body with sharp objects, hit my body). A confirmatory factor analysis supported a one-factor structure, as hypothesized. The one-factor model had a good model fit (x2(35) = 84.958, p < .001, RMSEA = .053, CFI = .981, TLI = .975, SRMR = .124). The SHSI also had good internal consistency (Cronbach's alpha = .795) and 4-week test-retest reliability (r = .786, p < .01). The SHSI had high correlations with another self-harm related scale, the Self-Harm Inventory (r = .773, p < .01), and moderate correlations with the Child Depression Inventory (r = .484, p < .01) and Revised Children's Manifest Anxiety Scale (r = .433, p < .01). Additionally, the SHSI was negatively correlated with the Rosenberg Self-Esteem Scale (r = -.399, p < .01). The findings indicate that the SHSI is a reliable and valid measure for the screening of self-harm behaviors among adolescents.

Since Chinese cabbage is consumed fresh, its wholesale price varies with the total amount supplied on the market. However, in these days, climate variability presents a large threat to sustainable Chinese cabbage production in South Korea. To manage Chinese cabbage production well under unexpected weather conditions, it is important to study the impacts of climate variability on Chinese cabbage economic yields in South Korea. In this study, 2-year field trials were conducted in multiple locations across seven provinces in South Korea. The collected morphological data from 24 different varieties were used to develop a yield prediction model using a machine learning technique. Three Chinese cabbage groups were carried out through the clustering analysis, and a yield model was developed for each cluster group. The developed model was used to predict the cabbage economic yields under different combinations of climate change and cropping management plans. According to simulation results, Group 1 had the shortest growing degree days and produced higher yields than the other two groups. However, the overproduction of Group 1 led to a price reduction in the market of (USD(0.04–0.08) per kg), which suggested that producing Group 2 of (USD(0.31–0.96) per kg) is more beneficial to farmers. Based on the production results of the groups, their revenue varied by location and cropping management. The results of this study provide farmers with a better understanding of the relationship between production and economic benefits in future climate change scenarios.

APV systems producing both crops and electricity are becoming popular as an alternative way of producing renewable energy in many countries with land shortage issues (e.g., South Korea). This study aims at developing a hybrid performance model of an Agrophotovoltaic (APV) system that produces crops underneath the PV modules. In this study, the physical model used to estimate solar radiation is integrated with a polynomial regression approach to forecast the amount of electricity generation and crop production in the APV system. The model takes into account not only the environmental factors (i.e., daily temperature, precipitation, humidity, and wind speed) but also physical factors (i.e., shading ratio of the APV system) related to the performance of the APV system. For more accurate modelling, the proposed approach is validated based on field experiment data collected from the APV system at Jeollanam-do Agricultural Research and Extension Services in South Korea. As a result, the proposed approach can predict the electricity generation quantity in the APV system with an R2 of 80.4%. This will contribute to the distribution of the APV system, which will increase farmers’ income as well as the sustainability of our society.

A close link has been established between self-harm and suicide risk in adolescents, and increasing attention is given to social media as possibly involved in this relationship. It is important to identify indicators of suicidality (i.e., suicide ideation or attempt) including aspects related to contagion in online and offline social networks and explore the role of social media in the relationship between social circumstances and suicidality in young adolescents with self-harm. This study explored characteristics of Korean adolescents with a recent history of self-harm and identified how behavioral and social features explain lifetime suicidality with emphasis on the impact of social media. Data came from a nationwide online survey among sixth- to ninth-graders with self-harm during the past 12 months (n = 906). We used χ2 tests of independence to explore potential concomitants of lifetime suicidality and employed a multivariate logistic regression model to examine the relationship between the explanatory variables and suicidality. Sensitivity analyses were performed with lifetime suicide attempt in place of lifetime suicidality. 33.9% (n = 306) and 71.2% (n = 642) reported to have started self-harm by the time they were fourth- and six-graders, respectively; 44.3% (n = 400) reported that they have friends who self-harm. Having endorsed moderate/severe forms and multiple forms of self-harm (OR 5.36, p < 0.001; OR 3.13, p < 0.001), having engaged in self-harm for two years or more (OR 2.42, p = 0.001), having friends who self-harm (OR 1.92, p = 0.013), and having been bullied at school were associated with an increased odds of lifetime suicidality (OR 2.08, p = 0.004). Notably, having posted content about one’s self-harm on social media during the past 12 months was associated with an increased odds of lifetime suicidality (OR 3.15, p < 0.001), whereas having seen related content in the same period was not. Sensitivity analyses yielded similar results with lifetime suicide attempt, supporting our findings from the logistic regression. The current study suggests that self-harm may be prevalent from early adolescence in South Korea with assortative gathering. The relationship of vulnerable adolescents’ social circumstances to suicide risk may be compounded by the role of social media. As the role of social media can be linked to both risk (i.e., contagion) and benefit (i.e., social connection and support), pre-existing vulnerabilities alongside SH and what online communication centers on should be a focus of clinical attention.

The effects of the initial pulse of tert-butyl iodide as a surfactant in atomic layer deposition of HfO2 using cyclopentadienyl tris(dimethylamino) hafnium, CpHf(NMe2)3, and ozone, O3, are investigated at 320, 300, and 250 °C. The formation of 2-methylpropene and hydrogen iodide from tert-butyl iodide via elimination reactions is the key idea of our effective approach for improving film conformality, film quality, and leakage current simultaneously. Our predicted growth mechanisms, supported by experimental results, suggest that different blocking probabilities by 2-methylpropene and hydrogen iodide on the top and bottom sides of the trench feature with an aspect ratio of 22.6:1 lead to 10% improvement in film conformality. In addition, ligand exchanges between the Hf precursor and hydrogen iodide lead to effective removal of large portions of carbon-containing ligands, resulting in a significant reduction in carbon residues, 76% at 320 °C and 40% at 250 °C, as evidenced by secondary ion mass spectrometry results. An increase in film density is also observed partly due to better completion of surface reactions between –I of Hf–I and O3. In terms of electrical properties, a significant improvement of 95% in leakage current is achieved due to the improvement in the film quality when tert-butyl iodide is employed. The deposited HfO2 film has superior leakage properties of 5.18 × 10−8 A/cm2 at 3 MV/cm, which is below the dynamic random access memory leakage current limit.

A novel atomic layer deposition (ALD) that utilizes tertiary alkyl (tert-alkyl) halides as both growth activator and inhibitor is introduced and demonstrated for the deposition of a low resistive TiN film using TiCl4 and NH3. Among the alkyl halides, tert-butyl iodide is identified as a suitable material for both growth inhibition and growth activation without any incorporation of C impurity in the film. The electrical resistivity values of TiN thin films in activator-type and inhibitor-type ALD were significantly improved by 55% and 49%, respectively. The mechanism of the reduction in electrical resistivity is elucidated by means of theoretical approach and characterizations of TiN films. For activator-type ALD, tert-butyl iodide induces in situ ligand exchange with an adsorbed Ti precursor to form Ti–I bonds, leading to an increase in the reactivity with a NH3 reactant. For inhibitor-type ALD, the improvement of film conformality in a high aspect ratio (>22:1) substrate is exhibited. This study demonstrates that the effectiveness on the use of tert-alkyl halides in ALD deposition can serve as an important guideline for future studies of the growth activator and growth inhibitor to improve film properties, making the method widely applicable.

Understanding the risks of bystander and off-target editing is essential for genome engineering applications. Here, the authors analyze the fidelity of adenine and cytosine base editors in vivo.

Abstract Background Inappropriate use of antibiotics increases resistance and reduces their effectiveness. Despite evidence-based guidelines, antibiotics are still commonly used to treat infections likely caused by respiratory viruses. In this study, we examined the temporal relationships between antibiotic usage and respiratory infections in the Republic of Korea. Methods The number of monthly antibiotic prescriptions and the incidence of acute respiratory tract infections between 2010 and 2015 at all primary care clinics were obtained from the Korean Health Insurance Review and Assessment Service. The monthly detection rates of respiratory viruses, including adenovirus, respiratory syncytial virus, influenza virus, human coronavirus, and human rhinovirus, were collected from Korea Centers for Disease Control and Prevention. Cross-correlation analysis was conducted to quantify the temporal relationship between antibiotic use and respiratory virus activities as well as respiratory infections in primary clinics. Results The monthly use of different classes of antibiotic, including penicillins, other beta-lactam antibacterials, macrolides and quinolones, was significantly correlated with influenza virus activity. These correlations peaked at the 0-month lag with cross-correlation coefficients of 0.45 (p

The Agrophotovoltaic (APV) system is a novel concept in the field of Renewable Energy Systems. This system enables the generation of solar energy via photo-voltaic (PV) modules above crops, to mitigate harmful impact on food production. This study aims to develop a performance evaluation model for an APV system in a temperate climate region, such as South Korea. To this end, both traditional electricity generation models (solar radiation-based model and climate-based model) of PV modules and two major machine learning (ML) techniques (i.e., polynomial regression and deep learning) have been considered. Electricity generation data was collected via remote sensors installed in the APV system at Jeollanam-do Agricultural Research and Extension Services in South Korea. Moreover, economic analysis in terms of cost and benefit of the subject APV system was conducted to provide information about the return on investment to farmers and government agencies. As a result, farmers, agronomists, and agricultural engineers can easily estimate performance and profit of their APV systems via the proposed performance model.

This study aims at introducing a modeling and simulation approach for a green roof system which can reduce energy cost of a building exposed to high temperatures throughout the summer season. First, to understand thermal impact of a green roof system on a building surface, a field-based study has been conducted in Commerce, Texas, U.S., where the average maximum temperature in summer is 104 °F (40 °C). Two types of analyses were conducted: (1) comparison of temperature between different plant type via Analysis of variance (ANOVA) and (2) polynomial regression analysis to develop thermal impact estimation model based on air temperature and presence of a green roof. In addition, an agent-based simulation (ABS) model was developed via AnyLogic® University 8.6.0 simulation software, Chicago, IL, U.S., in order to accurately estimate energy cost and benefits of a building with a photovoltaic-green roof system. The proposed approach was applied to estimate energy reduction cost of the Keith D. McFarland Science Building at Texas A&M University, Commerce, Texas (33.2410° N, 95.9104° W). As a result, the proposed approach was able to save $740,325.44 in energy cost of a heating, ventilation, and air conditioning (HAVC) system in the subject building. The proposed approach will contribute to the implementation of a sustainable building and urban agriculture.

Abstract We report that engineered Cas9 variants with improved specificity—eCas9-1.1 and Cas9-HF1—are often poorly active in human cells, when complexed with single guide RNAs (sgRNAs) with a mismatch at the 5’ terminus, relative to target DNA sequences. Because the nucleotide at the 5’ end of sgRNAs, expressed under the control of the commonly-used U6 promoter, is fixed to a guanine, these attenuated Cas9 variants are not useful at many target sites. By using sgRNAs with matched 5’ nucleotides, produced by linking them to a self-cleaving ribozyme, the editing activity of Cas9 variants can be rescued without sacrificing high specificity.

The aim of this study was to identify an efficient agrophotovoltaic (APV) system structure for generating electricity from solar radiation without causing an adverse impact on crop growth. In a temperate climate region, it is critical to design an APV system with appropriate structure with the maximum amount of electricity generation because, unlike in desert areas, strong solar radiation is only available for a few hours a day. In this study, APV systems with three different shading ratios (i.e., 32%, 25.6%, and 21.3%) were considered, and the optimum structure in terms of electricity efficiency and profitability was investigated via nonlinear programming. Moreover, an estimation model of electricity generation was developed via a polynomial regression model based on remote sensing data given by the APV system located at Jeollanamdo Agricultural Research and Extension Services in South Korea. To evaluate the impact of the APV on crop production, five different grain crops—sesame (Sesamum indicum), mung bean (Vigna radiata), red bean (Vigna angularis), corn (Zea mays), and soybean (Glycine max)—were cultivated in the system. As a result, the proposed optimization model successfully identified the best APV system structure without reducing existing crop production.

Soybean sprout is an important food ingredient in East Asian cuisine. Soybean growth is highly sensitive to temperature and photoperiod. Thus, it is important to determine the optimal base temperature for an accurate yield prediction. The optimal base temperature can be varied by cultivars. In this study, six soybean sprout cultivars that are commonly grown in Korea were planted in South Jeolla province, South Korea between 2003 and 2018. Data on phenology were collected from the field and used to determine the optimal base temperature for each cultivar. As a result, variations of optimal base temperatures of cultivars ranged from 0 °C to 15 °C. In simulation, three plant parameter sets, including Soy15, Soy6, and Soy0, were created. Soy15, Soy6, and Soy0 represented soybean cultivars with base temperatures of 15 °C, 6 °C, and 0 °C, respectively. In simulation results, the values of percent bias were under 15%, indicating that the Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) could reasonably simulate soybean yields. Among these three cultivars, Soy15 had the smallest yield, while Soy6 had the highest yield. In climate change scenarios (SSP245 and SSP585), both maximum and minimum temperatures were increased by 1–3.3 °C. With increasing temperatures in the future period, grain yields for all cultivars decreased. The yield reduction might be because the high temperature shortened the length of growth period of the soybeans. Among the three cultivars, Soy6 was a promising cultivar that could have a high yield under climate change scenarios.

Exercise-induced rhabdomyolysis (exRML), a pathophysiological condition of skeletal muscle cell damage that may cause acute renal failure and in some cases death. Increased Ca2+ level in cells along with functional degradation of cell signaling system and cell matrix have been suggested as the major pathological mechanisms associated with exRML. The onset of exRML may be exhibited in athletes as well as in general population. Previous studies have reported that possible causes of exRML were associated with excessive eccentric contractions in high temperature, abnormal electrolytes balance, and nutritional deficiencies possible genetic defects. However, the underlying mechanisms of exRML have not been clearly established among health professionals or sports medicine personnel. Therefore, we reviewed the possible mechanisms and correlated prevention of exRML, while providing useful and practical information for the athlete and general exercising population.

Background: Various training schemes have sought to improve golf-related athletic ability. In the golf swing motion, the muscle strengths of the core and arms play important roles, where a difference typically exists in the power of arm muscles between the dominant and non-dominant sides. The purposes of this study were to determine the effects of exercises strengthening the core and non-dominant arm muscles of elite golf players (handicap

Planning for optimized farming with the aim of providing ideal site and cultivar selection is critical for a stable and sustainable supply of rice with sufficient quantity and quality to customers. In this study, a range of morphological characteristics and yield of eight rice cultivars that are commonly cultivated in Korea were investigated from 2005 to 2020. All morphological characteristics were significantly different among the eight rice cultivars. The dataset of morphological characteristics and yield was used to isolate groups of similar rice cultivars. The k-means clustering method was used to group the rice cultivars. Three groups (Group 1, Group 2, and Group 3) were created. Most cultivars were in Group 1. High-yielding rice cultivars were in Group 2, while the rice cultivars in Group 3 had the lowest rice grain yield. After grouping these rice cultivars, ideal farming locations for all three rice cultivar groups were identified to reduce transportation cost using an optimized location–allocation model. Simulation results suggested the following: (1) Group 1 should be produced in Jellanam-do (south west region), (2) Group 2 should be produced in Chungcheongnam-do (central west region), and (3) Group 3 should be mainly produced in the central west region of South Korea. Simulation results showed the potential to reduce transportation cost by around 0.014%. This can also reduce 21.04 tons of CO2 emission from a freight truck. Because these eight cultivars only make up 19.76% of the total rice production in South Korea, the cost reduction proportion was only 0.014% of total revenue. In future studies, more rice cultivars should be investigated to increase the efficiency of the model performance.

The reduction in the operational cost of a biofuel refinery is vitally important to make biofuel competitive with fossil fuels. The aim of this paper is to find a cost-efficient and sustainable refinery capacity for grain-based ethanol (i.e., corn-based ethanol) production, which will play an important role in promoting the widespread adoption and sustainable use of ethanol, by improving the productivity of the overall refining process. Continuous-event simulation was utilized in this study to model complex operations of a refinery such as the loading, unloading and treatment of feedstock over nine major phases (e.g., feedstock storage and handling, pretreatment and conditioning, fermentation and hydrolysis, and enzyme production) to produce ethanol. To improve the model prediction, the real data of corn yield produced in Tazewell County, Illinois, U.S. were used. The proposed simulation model is implemented in AnyLogic® University 8.6.0 simulation software, Chicago, IL, USA, and the (near) optimal number of reactors for the hydrolysis and fermentation is found via optimization software known as OptQuest®, Boulder, CO, USA, As a result, the proposed approach found that six reactors showed the optimal daily profit from USD 67,500 to 82,217. This information will help engineers and policy makers to modify the capacity of a biofuel refinery for enhancement of the system efficiency and ethanol production.

Given a rising demand for quality assurance, rather than solely yield, supplemental irrigation plays an important role to ensure the viability and profitability of vegetable crops from unpredictable changes in weather. However, under drought conditions, agricultural irrigation is often given low priority for water allocation. This reduced water availability for agriculture calls for techniques with greater irrigation efficiency, that do not compromise crop quality and yield, and that provide economic benefit for producers. This study developed vegetable growing models for eight different vegetable crops (bush bean, green bean, cabbage, peppermint, spearmint, yellow straight neck squash, zucchini, and bell pepper) based on data from several years of field research. The ALMANAC model accurately simulated yields and water use efficiency (WUE) of all eight vegetables. The developed vegetable models were used to evaluate the effects of various irrigation regimes on vegetable growth and production in several locations in the Winter Garden Region of Texas, under variable weather conditions. Based on our simulation results from 960 scenarios, optimal irrigation amounts that produce high yield as well as reasonable economic profit to producers were determined for each vegetable crop. Overall, yields for all vegetables increased as irrigation amounts increased. However, irrigation amounts did not have a sustainable impact on vegetable yield at high irrigation treatments, and the WUEs of most vegetables were not significantly different among various irrigation regimes. When vegetable yields were compared with water cost, the rate decreased as irrigation amounts increased. Thus, producers will not receive economic benefits when vegetable irrigation water demand is too high.

Transcranial direct current stimulation (tDCS) is a technique used to modulate neuronal excitability through non-invasive brain stimulation that can enhance exercise performance. We hypothesize that tDCS would improve submaximal running time to exhaustion (TTE) and delay the increase in the rating of perceived exertion (RPE) over time. We also hypothesize that tDCS would not lead to difference in cardiorespiratory responses. We employed a randomized, single-blinded, and counterbalanced design in which 10 trained men participated. After receiving either 20 min of 1.98 mA anodal tDCS applied over the primary motor cortex (M1) or sham-operated control on separate days, participants completed a constant-load test involving running at a speed equivalent to 80% of their own maximum oxygen consumption (VO2max). During this constant-load test, RPE, heart rate (HR), VO2, pulmonary ventilation (VE), respiratory exchange ratio (RER), and ventilatory threshold (VT) were continuously monitored. TTE was recorded at the end of the test. TTEs were significantly longer in the tDCS than in the sham conditions (21.18 ± 7.13 min; 18.44 ± 6.32 min; p = 0.011). For TTE, no significant differences were found in RPE between conditions at isotime. In addition, no significant differences in HR, VO2, VE, RER, and VT were found during TTE between the two stimulation conditions at any time point. These results indicate that the application of tDCS does not induce a change of the exercise performance-related index; however, it can affect the increase of the exercise duration due to the stimuli in the M1 area.

Switchgrass (Panicum virgatum L.) is a C4, warm season, perennial native grass that has been strongly recommended as an ideal biofuel feedstock. Accurate forecasting of switchgrass yield across a geographically diverse region and under future climate conditions is essential for determining realistic future ethanol production from switchgrass. This study compiled a switchgrass database through reviewing the existing literature from field trials across the U.S. Using observed switchgrass data, a process-based model (ALMANAC) was developed. The ALMANAC simulation results showed that crop management had more effect on yield than location. The ALMANAC model consists of functional relationships that provide a better understanding of interactions among plant physiological processes and environmental factors (water, soil, climate, and nutrients) giving realistic predictions in different climate conditions. This model was used to quantify the impacts of climate change on switchgrass yields. Simulated lowland switchgrass would have more yield increases between Illinois and Ohio in future (2021–2050) under both Representative Concentration Pathway (RCP) 4.5 and 8.5 pathways with low N fertilizer inputs than high N fertilizer inputs. There was no significant effect of climate variability on upland simulated yields, which means that N fertilization is a key factor in controlling upland switchgrass yields under future climate conditions.

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Background: Limited data exist on problematic sexual behaviour (PSB) in youth with developmental disabilities in South Korea. Method: Sixty-one parents of children with intellectual disabilities or autism spectrum disorder (aged 13-30) reported children's PSB and emotional, behavioural, cognitive, and interpersonal factors. The frequency of PSB in children with developmental disabilities was verified, and various factors' effects on PSB were examined through multiple linear regression analysis. Results: There were no significant differences in PSB levels between children based on sex and age group. The externalising tendency and a history of family conflict predicted higher PSB. In contrast, protective factors had no significant predictive effects. Conclusions: PSB may vary depending on emotional and interpersonal factors, as well as cognitive deficits. Our findings emphasise the importance of interventions for PSB that consider both intrapersonal and interpersonal aspects.

OBJECTIVE:The purpose of this cross-sectional study was to investigate the relationship between bone-specific physical activity (BPAQ) scores, body composition, and bone mineral density (BMD) in healthy young college women. METHODS:Seventy-three college women (21.7 ± 1.8 years; 162.1 ± 4.6 cm; 53.9 ± 5.8 kg) between the ages of 19 and 26 years were recruited from the universities in Seoul and Gyeonggi province, South Korea. We used dual energy X-ray absorptiometry to measure the lumbar spine (L2-L4) and proximal femur BMD (left side; total hip, femoral neck). The BPAQ scores (past, pBPAQ; current, cBPAQ; total, tBPAQ) were used to obtain a comprehensive account of lifetime physical activity related to bone health. We used X-scan plus II instrumentation to measure height (cm), weight (kg), fat free mass (FFM, kg), percent body fat (%), and body mass index (BMI). Participants were asked to record their 24-hour food intake in a questionnaire. RESULTS:There were positive correlations between BPAQ scores and total hip (pBPAQ r = 0.308, p = 0.008; tBPAQ, r = 0.286, p = 0.014) and FN BMD (pBPAQ r = 0.309, p = 0.008; tBPAQ, r = 0.311, p = 0.007), while no significant relationships were found in cBPAQ (p > 0.05). When FFM, Vitamin D intake, cBPAQ, pBPAQ, and tBPAQ were included in a stepwise multiple linear regression analysis, FFM and pBPAQ were predictors of total hip, accounting for 16% (p = 0.024), while FFM and tBPAQ predicted 14% of the variance in FN (p = 0.015). Only FFM predicted 15% of the variance in L2-L4 (p = 0.004). There was a positive correlation between Vitamin D intake and L2-L4 (p = 0.025), but other dietary intakes variables were not significant (p > 0.05). CONCLUSIONS:BPAQ-derived physical activity scores and FFM were positively associated with total hip and FN BMD in healthy young college women. Our study suggests that osteoporosis awareness and effective bone healthy behaviors for college women are required to prevent serious bone diseases later in life.

One strategy in cancer immunotherapy is to capitalize on the key immunoregulatory and antigen presenting capabilities of dendritic cells (DCs). This approach is dependent on efficient delivery of tumor specific antigens to DCs, which subsequently induce an anti-tumor T-cell mediated immune response. Human adenovirus serotype 5 (HAdV5) has been used in human studies for gene delivery, but has limited infection in DCs, which lack the proper receptors. Addition of the porcine fiber knob (PK) from porcine adenovirus type 4 to HAdV5 allows the virus to deliver genetic material via binding to glycosylated surface proteins and bypasses the coxsackie-and-adenovirus receptor required by wild-type HAdV5. In this study we explored the potential therapeutic applications of an adenovirus with PK-based tropism against cancers expressing mesothelin. Infectivity and gene transfer assays were used to compare Ad5-PK to wild-type HAdV5. Mouse models were used to demonstrate peptide specificity and T-cell responses. We show that the PK modification highly augmented infection of DCs, including the CD141+ DC subset, a key subset for activation of naïve CD8+ T-cells. We also show that Ad5-PK increases DC infectivity and tumor specific antigen expression. Finally, vaccination of mice with the Ad5-PK vector resulted in enhanced T-cell-mediated interferon gamma (IFN-γ) release in response to both mesothelin peptide and a tumor line expressing mesothelin. Ad5-PK is a promising tool for cancer immunotherapy as it improves infectivity, gene transfer, protein expression, and subsequent T-cell activation in DCs compared to wild-type HAdV5 viruses.