The Impact of Academic Achievement and Parental Practices on Depressive Symptom Trajectories Among Chinese Adolescents

Though depressive symptoms tend to increase in early adolescence, the trajectories of these symptoms may vary strongly. This longitudinal study investigated the extent to which the distinct developmental trajectories of depressive symptoms were predicted by adolescents' academic achievement and perceived parental practices in a sample of Chinese young adolescents (N = 2,576). The results showed four trajectory profiles of depressive symptoms: low-stable (75%), low-increasing (11%), high-stable (9%), and high-decreasing (5%). Adolescents with high academic achievement were more likely to be classified into the low-stable, low-increasing, and high-decreasing profiles than into the high-stable depressive symptom profile. Moreover, students who perceived greater parental autonomy support were more likely to be in the low-stable and low-increasing profiles than the high-stable profile, whereas adolescents perceiving more parental psychological control had higher odds of being in the low-increasing rather than the low-stable profile. Parental educational involvement was unrelated to students' depressive symptom trajectories. In sum, Chinese adolescents with higher academic achievement and who perceived more parental autonomy support, and less psychological control, were at lower risk of experiencing depressive symptoms. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10802-021-00826-9

The Effect of Mindfulness Training on Proactive and Reactive Cognitive Control

Previous studies have demonstrated that mindfulness practice can improve general cognitive control. However, little research has examined whether mindfulness practices affect different cognitive control strategies. According to the dual mechanisms of control (DMC) model, different cognitive control strategies may play distinct roles in individuals’ lives. Proactive control allows people to maintain and prepare for goals, whereas reactive control allows them to respond flexibly to a changing environment. Thus, this study investigates the influences of mindfulness training on proactive and reactive control measured by the AX version of the Continuous Performance Test (AX-CPT). Thirty participants completed AX-CPT and the Five Facet Mindfulness Questionnaire (FFMQ) before and after random assignment to either an 8-week mindfulness training group or a control group. The results showed no interaction between group and test time for AY or BX trial type, but the training group had fewer post-test errors on the BX trial and a higher Behavior Shift Index (BSI) of reaction time (RT) compared with the control group. This finding indicates enhanced trend of proactive control with mindfulness training. A positive correlation between the BSI of RT and observing scores on the FFMQ confirmed the connection between attentional components in mindfulness and proactive control. Errors on the AY trial in the post-test decreased in both groups, reflecting reactive control that did not differ between groups. The 8-week mindfulness training demonstrates a potential improvement effect on proactive control and could be helpful in overcoming interference

The incidence and risk factors of acute pain after preoperative needle localization of pulmonary nodules: a cross-sectional study

Background: The incidence, severity and associated risk factors of acute pain after preoperative needle localization of pulmonary nodules are poorly characterized. We therefore conducted a cross-sectional study to quantify the acute pain induced by preoperative needle localization of small pulmonary nodules before video-assisted thoracoscopic surgery (VATS). Methods: We conducted this study at Shanghai Chest Hospital from September 2021 through December 2021. Eligible patients were between 18 and 75 years old and had small pulmonary nodules requiring preoperative CT-guided needle localization. The intensity of acute pain was assessed using the visual analogue scale (VAS) after preoperative needle localization. A VAS score ≥4 cm indicated moderate to severe pain. Patient demographics and CT-guided localization factors were collected to identify significant predictors associated with moderate to severe pain. Results: A total of 300 patients were included in the final analysis, with a mean (SD) age of 51 (SD =12) years old; 63% were female. Moderate to severe pain occurred in 50.8% of patients during deep breathing and 45.7% of patients during movement. Multivariate logistic regression analysis showed that multiple localization needles [multiple needle localizations vs. single needle localization, odds ratio (OR): 2.363, 95% confidence interval (CI): 1.157–4.825, P=0.018] and the specific location of needle puncture on the chest wall were significant predictors of moderate to severe pain after CT-guided needle localization (lateral chest wall vs. anterior chest wall OR: 2.235, 95% CI: 1.106–4.518, P=0.025; posterior chest wall vs. anterior chest wall OR: 1.198, 95% CI: 0.611–2.349, P=0.599). Conclusions: In adult patients receiving hookwire CT-guided localization, moderate to severe pain was common. Avoiding the localization route through lateral chest wall may be helpful and pharmacological medications or regional blockade is necessitated in high-risk population

An Updated Genome Assembly Improves Understanding of the Transcriptional Regulation of Coloration in Midas Cichlid

Midas cichlid (Amphilophus citrinellus), a popular aquarium fish, attracts extensive attention from worldwide biologists mainly due to its morphological polymorphism (dark versus gold). Continuous efforts have therefore been paid to address mechanisms of its coloration variants, while it is far away from the detailed illustration of a clear regulatory network. Some limits may come from the absence of a high-quality genome assembly and a relatively accurate gene set. In this study, we sequenced about 149 Gb of nucleotide sequences of Midas cichlid, generating a genome assembly with a total size of 933.5 Mb, which exhibits a good genome continuity with a contig N50 of 10.5 Mb. A total of 25,911 protein-coding genes were annotated and about 90% completeness was achieved, which helps to build a good gene pool for understanding expressional differences of color variation. With the assistance of the final gene set, we identified a total of 277 differential expressional genes (DEGs), of which 97 up- and 180 downregulated were determined in dark-vs-gold comparisons. Two protein-protein interaction (PPI) networks were constructed from these DEGs, and three key functional modules were classified. Hub genes within each module were evaluated, and we found that the third key module contains tyrp1b, oca2, pmela, tyr, and slc24a5, which were previously proven to be associated with melanin formation. Two downregulated DEGs (myl1 and pgam2) in the first key module may be involved in muscle movement and spermatogenesis, implying that certain side effects could result from the morphological polymorphism. The first key module, consisting of proteins encoded by upregulated DEGs that were associated with MAPK signaling, Toll-like receptor signaling, and gonadotropin-releasing hormone pathways, may contribute to a negative upstream regulation or downstream influence on melanin biosynthesis. Taken together, our new genome assembly and gene annotation of Midas cichlid provide a high-quality genetic resource for biological studies on this species, and the newly identified key networks and hub genes in dark-vs-gold comparisons enhance our understanding of the transcriptional regulatory mechanisms underlying coloration changes not only in Midas cichlid but also in other fishes from freshwater to marine ecosystems

Atmospheric deposition and river runoff stimulate the utilization of dissolved organic phosphorus in coastal seas

In coastal seas, the role of atmospheric deposition and river runoff in dissolved organic phosphorus (DOP) utilization is not well understood. Here, we address this knowledge gap by combining microcosm experiments with a global approach considering the relationship between the activity of alkaline phosphatases and changes in phytoplankton biomass in relation to the concentration of dissolved inorganic phosphorus (DIP). Our results suggest that the addition of aerosols and riverine water stimulate the biological utilization of DOP in coastal seas primarily by depleting DIP due to increasing nitrogen concentrations, which enhances phytoplankton growth. This “Anthropogenic Nitrogen Pump” was therefore identified to make DOP an important source of phosphorus for phytoplankton in coastal seas but only when the ratio of chlorophyll a to DIP [Log10 (Chl a / DIP)] is larger than 1.20. Our study therefore suggests that anthropogenic nitrogen input might contribute to the phosphorus cycle in coastal seas

Learning-based Nonlinear Model Predictive Control

© 2017 This paper presents stabilizing Model Predictive Controllers (MPC) in which prediction models are inferred from experimental data of the inputs and outputs of the plant. Using a nonparametric machine learning technique called LACKI, the estimated (possibly nonlinear) model function together with an estimation of Holder constant is provided. Based on these, a number of predictive controllers with stability guaranteed by design are proposed. Firstly, the case when the prediction model is estimated offline is considered and robust stability and recursive feasibility is ensured by using tightened constraints in the optimisation problem. This controller has been extended to the more interesting and complex case: the online learning of the model, where the new data collected from feedback is added to enhance the prediction model. An on-line learning MPC based on a double sequence of predictions is proposed.Spanish MINECO Grant PRX15-00300 and projects DPI2013-48243-C2-2-R and DPI2016-76493-C3-1-R. UK Engineering and Physical Research Council, grant no.EP/J012300/1

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Median Filter Based Compressed Sensing Model with Application to MR Image Reconstruction

Magnetic resonance imaging (MRI) has become a helpful technique and developed rapidly in clinical medicine and diagnosis. Magnetic resonance (MR) images can display more clearly soft tissue structures and are important for doctors to diagnose diseases. However, the long acquisition and transformation time of MR images may limit their application in clinical diagnosis. Compressed sensing methods have been widely used in faithfully reconstructing MR images and greatly shorten the scanning and transforming time. In this paper we present a compressed sensing model based on median filter for MR image reconstruction. By combining a total variation term, a median filter term, and a data fitting term together, we first propose a minimization problem for image reconstruction. The median filter term makes our method eliminate additional noise from the reconstruction process and obtain much clearer reconstruction results. One key point of the proposed method lies in the fact that both the total variation term and the median filter term are presented in the L1 norm formulation. We then apply the split Bregman technique for fast minimization and give an efficient algorithm. Finally, we apply our method to numbers of MR images and compare it with a related method. Reconstruction results and comparisons demonstrate the accuracy and efficiency of the proposed model