Chromosome-scale reference genome of broccoli (Brassica oleracea var. italica Plenck) provides insights into glucosinolate biosynthesis.

Broccoli (Brassica oleracea var. italica Plenck) is an important vegetable crop, as it is rich in health-beneficial glucosinolates (GSLs). However, the genetic basis of the GSL diversity in Brassicaceae remains unclear. Here we report a chromosome-level genome assembly of broccoli generated using PacBio HiFi reads and Hi-C technology. The final genome assembly is 613.79 Mb in size, with a contig N50 of 14.70 Mb. The GSL profile and content analysis of different B. oleracea varieties, combined with a phylogenetic tree analysis, sequence alignment, and the construction of a 3D model of the methylthioalkylmalate synthase 1 (MAM1) protein, revealed that the gene copy number and amino acid sequence variation both contributed to the diversity of GSL biosynthesis in B. oleracea. The overexpression of BoMAM1 (BolI0108790) in broccoli resulted in high accumulation and a high ratio of C4-GSLs, demonstrating that BoMAM1 is the key enzyme in C4-GSL biosynthesis. These results provide valuable insights for future genetic studies and nutritive component applications of Brassica crops.

A Glove-Wearing Detection Algorithm Based on Improved YOLOv8.

Wearing gloves during machinery operation in workshops is essential for preventing accidental injuries, such as mechanical damage and burns. Ensuring that workers are wearing gloves is a key strategy for accident prevention. Consequently, this study proposes a glove detection algorithm called YOLOv8-AFPN-M-C2f based on YOLOv8, offering swifter detection speeds, lower computational demands, and enhanced accuracy for workshop scenarios. This research innovates by substituting the head of YOLOv8 with the AFPN-M-C2f network, amplifying the pathways for feature vector propagation, and mitigating semantic discrepancies between non-adjacent feature layers. Additionally, the introduction of a superficial feature layer enriches surface feature information, augmenting the model's sensitivity to smaller objects. To assess the performance of the YOLOv8-AFPN-M-C2f model, this study conducted multiple experiments using a factory glove detection dataset compiled for this study. The results indicate that the enhanced YOLOv8 model surpasses other network models. Compared to the baseline YOLOv8 model, the refined version shows a 2.6% increase in mAP@50%, a 63.8% rise in FPS, and a 13% reduction in the number of parameters. This research contributes an effective solution for the detection of glove adherence.

Spatiotemporal variations and its driving factors of NDVI in Northwest China during 2000-2021.

Northwest China (WTL) is an essential ecological barrier zone of China, an important node of the "Silk Road Economic Belt," and a crucial bearing area for China's execution of the "One Road and One Belt" and "Going Global" strategies. However, its ecology is exceedingly fragile and particularly vulnerable to climate change and human interference. This study explored the spatiotemporal evolution characteristics of vegetation in WTL using NDVI data and investigated its drive mechanisms by geodetector, partial correlation analysis, and residual trend analysis methods. As well as forecasting the trend for vegetation changes. The findings demonstrated that (1) the change in NDVI manifested an overall improvement trend and the distribution in space of NDVI rose from the center to the periphery. 57.07% of the area had a sparse cover of vegetation (NDVI between 0 and 0.2). In addition, about 49% of regions had deterioration tendencies, which were mainly aggregated in HX, QCXDB, QCXDN, and the eastern of QCXQN and QCXXB. (2) The NDVI's shifting trend was unsustainability, and the region of uncertain future accounted for 57.45% of the total, with apparent unsustainability features. (3) The key parameters influencing NDVI spatial distribution were Pre (precipitation), vegetation type, land use type, and soil type. The interaction between two factors enhanced the influence of any single element, which appeared as bivariate and nonlinear enhancements. (4) Both climate variations and human activities have been recognized as key variables affecting NDVI growth. NDVI variance in 73.02% of areas was influenced by the combined effects of climate variations and human activities. However, human activities were the most influential element in NDVI growth, with the relative contributions of 80.28% (19.72% of which was caused by climate variations). These results can be conducive to deepening insights into the local vegetation status, identifying the mechanisms driving vegetation change, and providing scientific recommendations for WTL's ecosystem restoration measures based on actual situations.

Interactive effect between sleep and exercise on depressive symptoms in Chinese adolescents.

Objectives: The study aimed to investigate the effects of sleep and exercise, individually and jointly, on depressive symptoms in Chinese adolescents. Methods: Cluster sampling was used to conduct a cross-sectional, electronic survey among 11,563 students from five primary and high schools in Sichuan Province in Western China. The questionnaire contained custom-designed items concerning sleep and exercise, while it used the Center for Epidemiologic Studies Depression Scale to assess depressive symptoms and the Core Self-Evaluations Scale to assess core self-evaluation. Data were analyzed using descriptive statistics and multivariate linear regression. Results: A total of 10,185 valid questionnaires were collected, corresponding to an effective response rate of 88.1%. Among the respondents in the final analysis, 5,555 (54.5%) were boys and 4,630 (45.5%) were girls, and the average age was 15.20 ± 1.72 years (range, 11-18 years). Only less than half of the respondents (4,914, 48.2%) reported insufficient sleep, while the remainder (5,271, 51.8%) had adequate sleep. Nearly one-quarter (2,250, 22.1%) reported insufficient exercise, while the remainder (7,935, 77.9%) reported adequate exercise. More than half of the respondents (5,681, 55.7%) were from vocational high school, 3,368 (33.1%) were from junior high school, 945 (9.3%) were from senior high school, and 191 (1.9%) were from primary school. The prevalence of depressive symptoms among all respondents was 29.5% (95% CI 28.7%-30.4%). When other variables were controlled, the depression score did not vary significantly with gender (B = -0.244, SE = 0.127, P = 0.054), but it decreased by 0.194 points per 1-year increase in age (B = -0.194, SE = 0.037, P < 0.001). Students getting adequate sleep had depression scores 2.614 points lower than those getting insufficient sleep (B = -2.614, SE = 0.577, P < 0.001), while students who engaged in adequate exercise had depression scores 1.779 points lower than those not exercising enough (B = -1.779, SE = 0.461, P < 0.001). The depression score decreased by 0.919 points per 1-point increase in the core self-evaluation score (B = -0.919, SE = 0.008, P < 0.001). In regression controlling for gender, age, and core self-evaluation, sleep and exercise were found to be related significantly to influence depressive symptoms (B = 0.821, SE = 0.315, P = 0.009). Conclusion: Adequate sleep and adequate exercise are individually associated with milder depressive symptoms in Chinese adolescents. Our results further highlight the need for researchers and clinicians to take into account not only the individual but also the joint effects of sleep and exercise on depression in adolescents when conducting research and designing interventions. If sleep or physical exercise has substantially reduced the risk of depressive symptoms, further reductions by improving sleep and exercise become difficult and may even have opposite effects.

Predicting busulfan exposure in patients undergoing hematopoietic stem cell transplantation using machine learning techniques.

PURPOSE: This study aimed to establish an optimal model to predict the busulfan (BU) area under the curve at steady state (AUCss) by using machine learning (ML). PATIENTS AND METHODS: Seventy-nine adult patients (age ≥18 years) who received BU intravenously and underwent therapeutic drug monitoring from 2013 to 2021 at Fujian Medical University Union Hospital were enrolled in this retrospective study. The whole dataset was divided into a training group and test group at the ratio of 8:2. BU AUCss were considered as the target variable. Nine different ML algorithms and one population pharmacokinetic (pop PK) model were developed and validated, and their predictive performance was compared. RESULTS: All ML models were superior to the pop PK model (R2 = 0.751, MSE = 0.722, 14 and RMSE = 0.830) in model fitting and had better predictive accuracy. The ML model of BU AUCss established through support vector regression (SVR) and gradient boosted regression trees (GBRT) had the best predictive ability (R2 = 0.953 and 0.953, MSE = 0.323 and 0.326, and RMSE = 0.423 and 0.425). CONCLUSION: All the ML models can potentially be used to estimate BU AUCss with the aim of facilitating rational use of BU on the individualized level, especially models built by SVR and GBRT algorithms.

Population Pharmacokinetic Modeling Using Polymyxin B Free Plasma Concentrations From Published Reports and Evaluation of Dosage Regimens Based on Monte Carlo Simulation in Critically Ill Patients.

A population pharmacokinetic (pop PK) model of polymyxin B was developed using nonlinear mixed-effects (NONMEM) modeling based on free plasma concentrations to determine whether dose adjustment is required in critically ill patients. One thousand pharmacokinetic profiles for virtual patients with a body weight of 70 kg were simulated using Monte Carlo simulation at different dose scenarios, and area under the concentration-time curve of free drug (fAUC) was computed. The probability of target attainment (PTA) at each minimum inhibitory concentration (MIC) was calculated using fAUC/MIC as a pharmacokinetic/pharmacodynamic (PK/PD) index. The final population PK model was a 2-compartment model. PTA showed that 3.5 mg/kg/day regimens of polymyxin B effectively achieved the fAUC/MIC target of 10 (one log10 kill) against Pseudomonas aeruginosa strains with MIC of 1 mg/L or less (PTA,  90.7% or greater), while the dose regimen were ineffective against strains with an MIC of 2 mg/L or greater (PTA, 56.9% or less). For Klebsiella pneumoniae, the fAUC/MIC target of 17.4 (one log10 kill) was achieved in more than 90.4% of cases for MIC of 0.5 mg/L or less with 3 mg/kg/day regimens. However, the PTA decreased dramatically as MICs increased above 1 mg/L (PTA, 56.1% or less). The polymyxin B dosage regimen of 3.5 mg/kg/day and 3 mg/kg/day are sufficient to treat P. aeruginosa infections with an MIC of 1 mg/L or less and K. pneumoniae infections with an MIC of 0.5 mg/L or less, respectively. The current recommended dose (1.5-3 mg/kg/day) of polymyxin B appears inadequate to attain the PK/PD target for therapeutic efficacy against infections caused by P. aeruginosa and K. pneumoniae isolates when MIC is above the values.

Impact assessment of urbanization on vegetation net primary productivity: A case study of the core development area in central plains urban agglomeration, China.

Rapid urbanization process has a negative or positive impact on vegetation growth. Net primary productivity (NPP) is an effective indicator to characterize vegetation growth status. Taking the core development area of the Central Plains urban agglomeration as the study area, we estimated the NPP and its change trend in the past four decades using the Carnegie-Ames-Stanford Approach (CASA) model and statistical analysis based on meteorological and multi-source remote sensing data. Meanwhile, combined with the urbanization impact framework, we further analyzed urbanization's direct and indirect impact on NPP. The results showed that the urban area increased by 2688 km2 during a high-speed urbanization process from 1983 to 2019. As a result of the intense urbanization process, a continuous NPP decrease (direct impact) can be seen, which aggravated along with the acceleration of the urban expansion, and the mean value of direct impact was 130.84 g C·m-2·a-1. Meanwhile, urbanization also had a positive impact on NPP (indirect impact). The indirect impact showed an increasing trend during urbanization with a mean value of 10.91 g C·m-2·a-1. The indirect impact was mainly related to temperature in climatic factors. The indirect impact has a seasonal heterogeneity, and high-temperature environments of urban areas are more effective in promoting vegetation growth in autumn and winter than in summer. Among different cities, high-speed development cities have higher indirect impact values than medium's and low's because of better ecological construction. This study is of great significance for understanding the impact of urbanization on vegetation growth in the Central Plains urban agglomeration area, supporting urban greening plans, and building sustainable and resilient urban agglomerations.

Spatiotemporal variation of irrigation water requirements for grain crops under climate change in Northwest China.

Clarifying the spatiotemporal variation of crop irrigation water requirement (IWR) under the background of climate change is an essential basis for water resource management, determining the irrigation quota and adjusting the planting structure. Using 61 years of climate data from 205 stations in Northwest China, this study investigated the spatiotemporal variations of climatic factors and IWR during the growth period of five main grain crops (spring wheat, winter wheat, spring maize, summer maize, and rice) and explored the dominant climatic driving factors of IWR variation. Results showed that (1) the IWR of grain crops showed distinct differences. Rice was the highest water consumption crop (mean of 753.78 mm), and summer maize was the lowest (mean of 452.90 mm). (2) The variation trends and average values of IWR of different grain crops have spatial heterogeneity across Northwest China. For most crops, high values and increasing trends of IWR were mainly located in eastern Xinjiang, western Gansu, and western Inner Mongolia. (3) Tmax (maximum temperature), Tmin (minimum temperature), and Peff (effective precipitation) showed an increasing trend during the growth period of each grain crop, while U10 (wind speed at 10 m height), SD (solar radiation), and RH (relative humidity) presented decreasing trends. (4) SD, Tmax, and U10 promoted the increase of grain crops' IWR, while Peff and RH inhibited it. The impacts of climatic factors on the grain crop IWR differed among different regions. Peff was the most influential factor to the IWR of all grain crops in most areas. Therefore, under the premise of a significant increase in T and uncertain precipitation mode in the future, it is urgent to take effective water-saving measures according to the irrigation needs of the region. To cope with the adverse impact of climate change on the sustainable development of agriculture in the northwest dry area, to ensure regional and national food security.

A physiologically based pharmacokinetic analysis to predict the pharmacokinetics of intravenous isavuconazole in patients with or without hepatic impairment.

Isavuconazole (ISA) is an azole antifungal used in the treatment of invasive aspergillosis and mucormycosis. Patients with mild and moderate hepatic impairment have lower clearance (CL) as compared to the healthy population. Currently, there is no data on ISA in patients with severe hepatic impairment (Child-Pugh Class C). The purpose of this study was to build a physiologically based pharmacokinetic (PBPK) model to describe the pharmacokinetics (PK) of intravenous ISA, and to predict changes in ISA disposition in different patient populations and in patients with hepatic impairment to guide personalized dosing. By incorporating the systemic and drug specific parameters of ISA, the model was initially developed in healthy population and validated with 10 independent PK profiles obtained from healthy subjects and from patients with normal liver function. The results showed a satisfactory predictive capacity, with most of the relative predictive errors being between ±30% for area under the curve (AUC) and Cmax The observed plasma concentration-time profiles of ISA were well described by the model predicted profiles. The model adequately predicted the reduced CL of ISA in patients with mild and moderate hepatic impairment. Furthermore, the model predicted a decrease in CL of about 60% in patients with severe hepatic impairment. Therefore, we recommend reducing the dose by 50% in patients with severe hepatic impairment. The model also predicted differences in the PK of ISA between Caucasian and Asian population, with the CL ratio of 0.67 in Chinese vs Caucasian population. The developed PBPK model of ISA provides a reasonable approach for optimizing the dosage regimen in different ethnic populations and in patients with severe hepatic impairment.

Case Report: A novel KNCH2 variant-induced fetal heart block and the advantages of fetal genomic sequencing in prenatal long-term dexamethasone exposure.

Background: Fetal bradycardia is a common but severe condition. In addition to autoimmune-mediated fetal heart block, several types of channelopathies induce high-degree atrioventricular block (AVB). Long QT syndrome (LQTS) is a major cause of non-autoimmune-mediated fetal heart block. Due to the limitations of prenatal diagnostic technologies, LQTS is seldom identified unless fetal genetic screening is performed. Thus, long-term prenatal dexamethasone (DEX) exposure can become a challenge for these patients. We report on a rare case of a novel KCNH2 variant related to LQTS and associated with high-degree fetal AVB with long-term DEX exposure. This case led us to review our prenatal administration strategy for such patients. Case Presentation: A fetus was identified with high-degree AVB (2:1 transduction at 28 + 2 gestational weeks). Typical tests of immune function in the pregnant woman were conducted including tests for thyroid function, rheumatic screening, autoimmune antibodies (such as anti-Ro/SSA and anti-La/SSB), and anti-nuclear antibodies (anti-ANA). Following the recommended protocol, the pregnant patient received DEX (0.75 mg/day) during pregnancy. Subsequently, the fetal AVB changed from 2:1 to prolonged AV intervals with ventricular tachycardia, which suggested a therapeutic benefit of DEX in some respects. However, a high-degree AVB with a significantly prolonged QTc interval was identified in the neonate following birth. Genetic testing revealed that a KCNH2 c.1868C>A variant induced LQTS. The body length remained approximately -3.2 SD from the reference value after prenatal long-term DEX exposure, which indicated a developmental restriction. Additionally, the functional validation experiments were performed to demonstrate the prolonged duration of calcium transit both in depolarization and repolarization with the KCNH2 c.1868C>A variant. Conclusion: Genetic screening should be recommended in fetuses with autoimmune antibody negative high-degree AVB, especially for 2:1 transduction AVB and in fetuses with changes in fetal heart rhythm following initial DEX treatment. Genetic screening may help identify genetic variant-related channelopathies and avoid unexpected prenatal exposure of DEX and its possible long-term adverse postnatal complications.

The clinical relevance of neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio in chronic obstructive pulmonary disease with lung cancer.

Background: Chronic obstructive pulmonary disease (COPD) coexisting with lung cancer is associated with severe mortality and a worse prognosis. Inflammation plays an important role in common pathogenic pathways and disease progression. However, a few studies have identified the clinical value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in COPD with lung cancer, which are systemic inflammatory response markers in the blood. This study aimed to determine the association of the NLR or PLR with clinical characteristics and whether NLR or PLR can be diagnostic markers for COPD with lung cancer. Methods: Between 2015 and 2021, we conducted a retrospective analysis of 236 COPD patients with lung cancer and 500 patients without lung cancer (control group). Clinical information, blood routine examination, and spirometry results were collected and analyzed. The receiver operating characteristic (ROC) curve was used to identify the best cutoff point of NLR or PLR. Multivariate logistic regression analysis was performed to evaluate the association of NLR or PLR with the diagnosis and prognosis of COPD with lung cancer. Results: Compared to patients in the COPD-only group, patients in the lung cancer group had a higher percentage of current smoking and emphysema, and it was found that NLR or PLR was significantly higher in the lung cancer group. Multivariate analysis showed that age, smoking status, FEV1%pred, emphysema, NLR, and PLR were independent risk factors for lung cancer development in COPD. Furthermore, the high level of NLR or PLR was associated with age over 70 years old, current smoking status, and ineligible surgery treatment. The level of PLR or NLR markedly increased with hypercoagulation status, the severity of airflow limitation, and advanced progression of lung cancer. Additionally, the ROC analysis also revealed that elevated NLR or PLR was an independent predictor of COPD in lung cancer patients, TNM stages IIIB-IV at first diagnosis in lung cancer, and ineligible surgery in lung cancer patients. Conclusion: Increased NLR or PLR values might be an important and easily measurable inflammation biomarker to predict the diagnosis and severity of lung cancer with COPD.

Effect of posaconazole on the concentration of intravenous and oral cyclosporine in patients undergoing hematopoietic stem cell transplantation.

PURPOSE: This study aimed to investigate the interactions between posaconazole (POS) and intravenously/orally administered cyclosporine A (CsA) in allogeneic hematopoietic stem cell transplant (HSCT) recipients. METHODS: We included 118 allogeneic HSCT patients who received CsA and POS simultaneously between January 2017 and June 2020 in this study. The ratio of CsA blood concentration (ng/mL) to dosage (mg/day) (C/D) before and after POS initiation was compared. RESULTS: After the initiation of POS, the level of CsA increased 1 to 2 times in 66% (78/118) of patients compared to those without POS. However, the CsA C/D ratio increased by more than threefold in 6% (7/118) of patients after POS initiation, with an increase of more than fourfold in two patients. The median C/D ratio of CsA increased from 0.89 to 1.23 (P < 0.001) and 0.78 to 1.22 (P < 0.001) after POS initiation when CsA was administered intravenously and orally, respectively. In patients who received POS at the time of transition from intravenous to oral CsA, the value increased from 1.01 to 1.38 (P = 0.001). The route of administration had no significant effect on the change in the CsA C/D ratio (P = 0.615). Additionally, we observed the time required for the C/D ratio to reach a plateau after POS initiation was similar on days 13, 8, and 15 under various scenarios. CONCLUSION: POS treatment increased blood CsA levels. A large variability was found in the fold-change in the CsA C/D ratio. Therefore, CsA doses should be adjusted by closely monitoring the blood levels of CsA after POS initiation.

External Evaluation of Population Pharmacokinetic Models of Busulfan in Chinese Adult Hematopoietic Stem Cell Transplantation Recipients.

Objective: Busulfan (BU) is a bi-functional DNA-alkylating agent used in patients undergoing hematopoietic stem cell transplantation (HSCT). Over the last decades, several population pharmacokinetic (pop PK) models of BU have been established, but external evaluation has not been performed for almost all models. The purpose of the study was to evaluate the predictive performance of published pop PK models of intravenous BU in adults using an independent dataset from Chinese HSCT patients, and to identify the best model to guide personalized dosing. Methods: The external evaluation methods included prediction-based diagnostics, simulation-based diagnostics, and Bayesian forecasting. In prediction-based diagnostics, the relative prediction error (PE%) was calculated by comparing the population predicted concentration (PRED) with the observations. Simulation-based diagnostics included the prediction- and variability-corrected visual predictive check (pvcVPC) and the normalized prediction distribution error (NPDE). Bayesian forecasting was executed by giving prior one to four observations. The factors influencing the model predictability, including the impact of structural models, were assessed. Results: A total of 440 concentrations (110 patients) were obtained for analysis. Based on prediction-based diagnostics and Bayesian forecasting, preferable predictive performance was observed in the model developed by Huang et al. The median PE% was -1.44% which was closest to 0, and the maximum F20 of 57.27% and F30 of 72.73% were achieved. Bayesian forecasting demonstrated that prior concentrations remarkably improved the prediction precision and accuracy of all models, even with only one prior concentration. Conclusion: This is the first study to comprehensively evaluate published pop PK models of BU. The model built by Huang et al. had satisfactory predictive performance, which can be used to guide individualized dosage adjustment of BU in Chinese patients.

Impact of the Grain for Green Project on water resources and ecological water stress in the Yanhe River Basin.

The Grain for Green project (GGP), initialized by the Chinese government in 1999, has achieved substantial achievements accompanied by a decrease in surface runoff on the Loess Plateau, but the impacts of large-scale afforestation on regional water resources are uncertain. Hence, the objective of this study was to explore the impact of land use change on generalized water resources and ecological water stress using the blue and green water concepts, taking the Yanhe River Basin as the case study. The Soil and Water Assessment Tool (SWAT) was applied to quantify the green water and blue water, which are defined as generalized water resources. The ecological water requirement of vegetation (forest and grass), agricultural water footprint and virtual water flow are considered regional water requirements. The land use types of 1980 (Scenario I) and 2017 (Scenario II) were entered into the SWAT model while keeping the other parameters constant to isolate the influence of land use changes. The results show that the average annual differences in blue, green and generalized water resources were -72.08 million m3, 24.34 million m3, and -47.74 million m3, respectively, when the simulation results of Scenario II were subtracted from those of Scenario I, which shows that land use change caused by the GGP led to a decrease in blue and generalized water resources and an increase in green water resources. Surface runoff in Scenario I was more than that in Scenario II in all of the years of the study period from 1980-2017, and green water storage in Scenario I was more than that in Scenario II in all of the years of the study period except in 1998; although lateral flow in Scenario I was less than that in Scenario II except in 2000 and 2015, as was groundwater runoff in 1992, 2000 and 2015, and green water flow in 1998. Blue water flow, green water storage and green water flow in Scenario II were less than those in Scenario I in the whole basin, 12.89 percent of the basin and 99.21 percent of the basin, respectively. The total water footprint increased from 1995 to 2010 because the forest water footprint increased significantly in this period, although the agricultural water footprint and grass water footprint decreased. The ecological water stress index values had no obvious temporal change trends in either land use scenario, but the ecological water stress index in Scenario II was greater than that in Scenario I, which illustrates that the GGP led to an increase in ecological water stress from the perspective of generalized water resources.

External evaluation of population pharmacokinetic models for voriconazole in Chinese adult patients with hematological malignancy.

OBJECTIVES: Patients with hematological malignancies are prone to invasive fungal disease due to long-term chemotherapy or radiotherapy. Voriconazole is a second-generation triazole broad-spectrum antibiotic used to prevent or treat invasive fungal infections. Many population pharmacokinetic (pop PK) models have been published for voriconazole, and various diagnostic methods are available to validate the performance of these pop PK models. However, most of the published models have not been strictly evaluated externally. The purpose of this study is to evaluate these models externally and assess their predictive capabilities. METHODS: The external dataset consists of adults receiving voriconazole treatment at Fujian Medical University Union Hospital. We re-established the published models based on their final estimated values in the literature and used our external dataset for initial screening. Each model was evaluated based on the following outcomes: prediction-based diagnostics, prediction- and variability-corrected visual predictive check (pvcVPC), normalized prediction distribution errors (NPDE), and Bayesian simulation results with one to two prior observations. RESULTS: A total of 237 samples from 166 patients were collected as an external dataset. After screening, six candidate models suitable for the external dataset were finally obtained for comparison. Among the models, none demonstrated excellent predictive performance. Bayesian simulation shows that all models' prediction precision and accuracy were significantly improved when one or two prior concentrations were given. CONCLUSIONS: The published pop PK models of voriconazole have significant differences in prediction performance, and none of the models could perfectly predict the concentrations of voriconazole for our data. Therefore, extensive evaluation should precede the adoption of any model in clinical practice.

Two Innovative Approaches to Optimize Vancomycin Dosing Using Estimated AUC after First Dose: Validation Using Data Generated from Population PK Model Coupled with Monte-Carlo Simulation and Comparison with the First-Order PK Equation Approach.

The revised consensus guidelines for optimizing vancomycin doses suggest that maintaining the area under the concentration-time curve to minimal inhibitory concentration ratio (AUC/MIC) of 400-600 mg·h/L is the target pharmacokinetic/pharmacodynamic (PK/PD) index for efficacy. AUC-guided dosing approach uses a first-order pharmacokinetics (PK) equation to estimate AUC using two samples obtained at steady state and one-compartment model, which can cause inaccurate AUC estimation and fail to achieve the effective PK/PD target early in therapy (days 1 and 2). To achieve an efficacy target from the third or fourth dose, two innovative approaches (Method 1 and Method 2) to estimate vancomycin AUC at steady state (AUCSS) using two-compartment model and three or four levels after the first dose are proposed. The feasibility of the proposed methods was evaluated and compared with another published dosing algorithm (Method 3), which uses two samples and a one-compartment approach. Monte Carlo simulation was performed using a well-established population PK model, and concentration-time profiles for virtual patients with various degrees of renal function were generated, with 1000 subjects per group. AUC extrapolated to infinity (AUC0-∞) after the first dose was estimated using the three methods, whereas reference AUC (AUCref) was calculated using the linear-trapezoidal method at steady state after repeated doses. The ratio of AUC0-∞: AUCref and % bias were selected as the indicators to evaluate the accuracy of three methods. Sensitivity analysis was performed to examine the influence of change in each sampling time on the estimated AUC0-∞ using the two proposed approaches. For simulated patients with various creatinine clearance, the mean of AUC0-∞: AUCref obtained from Method 1, Method 2 and Method 3 ranged between 0.98 to 1, 0.96 to 0.99, and 0.44 to 0.69, respectively. The mean bias observed with the three methods was -0.10% to -2.09%, -1.30% to -3.59% and -30.75% to -55.53%, respectively. The largest mean bias observed by changing sampling time while using Method 1 and Method 2 were -4.30% and -10.50%, respectively. Three user-friendly and easy-to-use excel calculators were built based on the two proposed methods. The results showed that our approaches ensured sufficient accuracy and achieved target PK/PD index early and were superior to the published methodologies. Our methodology has the potential to be used for vancomycin dose optimization and can be easily implemented in clinical practice.

Kidins220/ARMS modulates brain morphology and anxiety-like traits in adult mice.

Kinase D interacting substrate of 220 kDa (Kidins220), also known as ankyrin repeat-rich membrane spanning (ARMS), is a transmembrane scaffold protein that participates in fundamental aspects of neuronal physiology including cell survival, differentiation, and synaptic plasticity. The Kidins220 constitutive knockout line displays developmental defects in the nervous and cardiovascular systems that lead to embryonic lethality, which has so far precluded the study of this protein in the adult. Moreover, Kidins220 mRNA is tightly regulated by alternative splicing, whose impact on nervous system physiology has not yet been addressed in vivo. Here, we have asked to what extent the absence of Kidins220 splicing and the selective knockout of Kidins220 impact on adult brain homeostasis. To answer this question, we used a floxed line that expresses only the full-length, non-spliced Kidins220 mRNA, and a forebrain-specific, CaMKII-Cre driven Kidins220 conditional knockout (cKO) line. Kidins220 cKO brains are characterized by enlarged ventricles in the absence of cell death, and by deficient dendritic arborization in several cortical regions. The deletion of Kidins220 leads to behavioral changes, such as reduced anxiety-like traits linked to alterations in TrkB-BDNF signaling and sex-dependent alterations of hippocampal-dependent spatial memory. Kidins220 floxed mice present similarly enlarged brain ventricles and increased associative memory. Thus, both the absolute levels of Kidins220 expression and its splicing pattern are required for the correct brain development and related expression of behavioral phenotypes. These findings are relevant in light of the increasing evidence linking mutations in the human KIDINS220 gene to the onset of severe neurodevelopmental disorders.

Core self-evaluation as mediator between depressive symptoms and suicidal ideation in adolescents.

OBJECTIVES: To explore the role of core self-evaluation in mediating between depressive symptoms and suicidal ideation in Chinese adolescents. METHODS: We used the cluster sampling method to analyze 11,563 students from five primary and secondary schools in China for depressive symptoms, core self-evaluation, and suicidal ideation using the following scoring scales: Core Self-Evaluation Scale (CSES), Center for Epidemiologic Survey Depression Scale (CES-D), the Second Edition of the Beck Depression Inventory (BDI- II), Screen for Child Anxiety Related Emotional Disorders (SCARED), and Adolescent Self-Rating Life Events Checklist (ASLEC). RESULTS: The incidence of depression was 29.7%; anxiety, 34.2%; and suicidal ideation, 28.0%. Core self-evaluation was a protective factor for suicidal ideation [OR 0.947, 95% CI 0.937-0.959, p<0.001]. Conversely, depression as measured by the CSES score was a risk factor for suicidal ideation (OR 1.084, 95% CI 1.073-1.096, p<0.001), as were anxiety as measured by the SCARED score (OR 1.011, 95% CI 1.006-1.016, p<0.001) and adolescent life events according to ASLEC score groups (OR 1.524, 95% CI 1.434-1.621, p<0.001). Core self-evaluation mediated the relationship between depression and suicidal ideation with an effect size of 13.9%. CONCLUSIONS: Better core self-evaluation is a protective factor against suicidal ideation and mediates the relationship between depression and suicidal ideation. We may be able to reduce the risk of suicidal ideation and therefore suicide among adolescents by improving their core self-evaluation.

Can Published Population Pharmacokinetic Models of Busulfan Be Used for Individualized Dosing in Chinese Pediatric Patients Undergoing Hematopoietic Stem Cell Transplantation? An External Evaluation.

Busulfan is a bifunctional alkylating agent that is widely used before hematopoietic stem cell transplantation (HSCT), in combination with other chemotherapeutic drugs. As of 2020, there is no population pharmacokinetic (popPK) model for busulfan in Chinese pediatric patients. A systemic external evaluation of 11 published popPK models was conducted in Chinese pediatric patients undergoing HSCT. Forty pediatric patients were enrolled in this study, with a total of 183 blood concentrations. The relative prediction error (PE%), median PE%, median absolute PE%, and percentage of PE% within ±20% and ±30% were calculated in prediction-based diagnostics. Simulation-based diagnostics were conducted through a prediction- and variability-corrected visual predictive check and the normalized prediction distribution error. The relative individual prediction error was calculated using Bayesian forecasting with 1 to 3 concentration points. The 1-compartment open linear popPK model, which was built by Su-jin Rhee et al (model H), incorporating the patient's body surface area, age, dosing day, and aspartate aminotransferase as significant covariates had preferable predictability than other popPK models. In prediction-based diagnostics, the median PE%, percentage of PE% within ±20%, and percentage of PE% within ±30% of model H were 8.48%, 45.35%, and 59.56%, respectively. The normalized prediction distribution error of model H showed that it followed the normal distribution. Based on Bayesian forecasting, model H showed good predictive performance. Thus, model H was the most appropriate model that can be used clinically for individualized dosage adjustments in Chinese pediatric HSCT patients.

Association of treatments for acute appendicitis with pregnancy outcomes in the United States from 2000 to 2016: Results from a multi-level analysis.

BACKGROUND: Open appendectomy, laparoscopic appendectomy, and non-surgical treatment are three options to treat acute appendicitis during pregnancy. Previous studies on the association of different treatment methods for acute appendicitis with pregnancy outcomes have been limited by small sample sizes and residual confounding, especially with respect to hospital-level factors. This study aimed to investigate the association of treatment method for acute appendicitis with pregnancy outcomes using a multi-level analysis. METHODS: A retrospective cohort study was conducted based on a large electronic health records database in the United States during the period 2000 to 2016. All pregnancies diagnosed with acute appendicitis and treated in participating hospitals during the study period were included. We conducted multi-level hierarchical logistic regression to analyze both individual- and hospital-level factors for abortion, preterm labor, and cesarean section. RESULTS: A total of 10,271 acute appendicitis during pregnancy were identified during the study period. Of them, 5,872 (57.2%) were treated by laparoscopic appendectomy, 1,403 (13.7%) by open appendectomy, and 2,996 (29.2%) by non-surgical treatment. Compared with open appendectomy, both laparoscopic appendectomy (adjusted OR, 0.6, 95% CI, 0.4, 0.9) and non-surgical treatment (adjusted OR, 0.4; 95% CI, 0.3-0.7) showed a decreased risk of preterm labor. Other important individual-level determinants of adverse pregnancy outcomes included maternal age, gestational hypertension, and anemia during pregnancy, the hospital-level determinant included the number of beds. CONCLUSIONS: Compared with open appendectomy, both laparoscopic appendectomy and non-surgical treatment may be associated with a lower risk of preterm labor, without increased risks of abortion and cesarean section.