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

Parental Emotion Socialization and Child Psychological Adjustment among Chinese Urban Families: Mediation through Child Emotion Regulation and Moderation through Dyadic Collaboration

The theoretical model of emotion regulation and many empirical findings have suggested that children’s emotion regulation may mediate the association between parents’ emotion socialization and children’s psychological adjustment. However, limited research has been conducted on moderators of these relations, despite the argument that the associations between parenting practices and children’s psychological adjustment are probabilistic rather than deterministic. This study examined the mediating role of children’s emotion regulation in linking parents’ emotion socialization and children’s psychological adjustment, and whether dyadic collaboration could moderate the proposed mediation model in a sample of Chinese parents and their children in their middle childhood. Participants were 150 Chinese children (87 boys and 63 girls, Mage = 8.54, SD = 1.67) and their parents (Mage = 39.22, SD = 4.07). Parent–child dyadic collaboration was videotaped and coded from an interaction task. Parents reported on their emotion socialization, children’s emotion regulation and psychopathological symptoms. Results indicated that child emotion regulation mediated the links between parental emotion socialization and child’s psychopathological symptoms. Evidence of moderated mediation was also found: supportive emotion socialization and child emotion regulation were positively correlated only at high and medium levels of dyadic collaboration, with child’s psychopathological symptoms as the dependent variables. Our findings suggested that higher-level parent–child collaboration might further potentiate the protective effect of parental supportive emotion socialization practices against child psychopathological symptoms

The Heart of Parenting: Parent HR Dynamics and Negative Parenting While Resolving Conflict With Child

The current study examined parent heart rate (HR) dynamic changing patterns and their links to observed negative parenting (i.e., emotional unavailability and psychological control) during a parent–child conflict resolution task among 150 parent–child dyads (child age ranged from 6 to 12 years, Mage = 8.54 ± 1.67). Parent HR was obtained from electrocardiogram (ECG) data collected during the parent–child conflict resolution task. Negative parenting was coded offline based on the video recording of the same task. Results revealed that emotionally sensitive parents during the task showed greater HR increases while discussing a conflict and greater HR decreases while resolving the conflict, whereas emotionally unavailable parents showed no changes in HR. However, parent psychological control was not associated with HR dynamics during the task. These findings indicated the physiological underpinnings of parent emotional sensitivity and responsiveness during parent–child interactions. The potential association between HR baseline levels and parenting behaviors was also discussed

Multi-UAV Path Planning Algorithm Based on BINN-HHO

Multi-UAV (multiple unmanned aerial vehicles) flying in three-dimensional (3D) mountain environments suffer from low stability, long-planned path, and low dynamic obstacle avoidance efficiency. Spurred by these constraints, this paper proposes a multi-UAV path planning algorithm that consists of a bioinspired neural network and improved Harris hawks optimization with a periodic energy decline regulation mechanism (BINN-HHO) to solve the multi-UAV path planning problem in a 3D space. Specifically, in the procession of global path planning, an energy cycle decline mechanism is introduced into HHO and embed it into the energy function, which balances the algorithm’s multi-round dynamic iteration between global exploration and local search. Additionally, when the onboard sensors detect a dynamic obstacle during the flight, the improved BINN algorithm conducts a local path replanning for dynamic obstacle avoidance. Once the dynamic obstacles in the sensor detection area disappear, the local path planning is completed, and the UAV returns to the trajectory determined by the global planning. The simulation results show that the proposed Harris hawks algorithm has apparent superiorities in path planning and dynamic obstacle avoidance efficiency compared with the basic Harris hawks optimization, particle swarm optimization (PSO), and the sparrow search algorithm (SSA)

Quaternized chitosan nanoparticles loaded with the combined attenuated live vaccine against Newcastle disease and infectious bronchitis elicit immune response in chicken after intranasal administration

<p>Newcastle disease (ND) and infectious bronchitis (IB) are important diseases, which cause respiratory diseases in chickens, resulting in severely economic losses in the poultry industry. In this study, <i>N</i>-2-hydroxypropyl trimethyl ammonium chloride chitosan (N-2-HACC) and <i>N,O</i>-carboxymethyl chitosan (CMC) were synthesized as adjuvant and delivery carrier for vaccine antigens. N-2-HACC-CMC/NDV/IBV nanoparticles (NPs) (NDV/La Sota and IBV/H120 encapsulated in N-2-HACC-CMC NPs) and N-2-HACC-CMC/NDV-IBV NPs (the mixing of N-2-HACC-CMC/NDV NPs and N-2-HACC-CMC/IBV NPs in a ratio of 1:1) were prepared by the polyelectrolyte composite method, respectively. Both nanoparticles exhibited lower cytotoxicity and higher stability. Their bioactivities were maintained when they were stored at 37 °C for three weeks. Release assay <i>in vitro</i> showed that both NDV and IBV could be sustainably released from the nanoparticles after an initial burst release. <i>In vivo</i> immunization of chickens showed that N-2-HACC-CMC/NDV/IBV NPs or N-2-HACC-CMC/NDV-IBV NPs intranasally induced higher titers of IgG and IgA antibodies, significantly promoted proliferation of lymphocytes and induced higher levels of interleukine-2 (IL-2), IL-4 and interferon-γ (IFN-γ) than the commercially combined attenuated live vaccine did. This is the first study in the field of animal vaccines demonstrating that intranasal administration of chickens with antigens (NDV and IBV) encapsulated with chitosan derivative could induce humoral, cellular, and mucosal immune responses, which protected chickens from the infection of highly virulent NDV and IBV. This study indicated that N-2-HACC-CMC could be used as an efficient adjuvant and delivery carrier for further development of mucosal vaccines and drugs and could have an immense application potential in medicine.</p

The accuracy of artificial intelligence in predicting COVID-19 patient mortality: a systematic review and meta-analysis

Abstract Background The purpose of this paper was to systematically evaluate the application value of artificial intelligence in predicting mortality among COVID-19 patients. Methods The PubMed, Embase, Web of Science, CNKI, Wanfang, China Biomedical Literature, and VIP databases were systematically searched from inception to October 2022 to identify studies that evaluated the predictive effects of artificial intelligence on mortality among COVID-19 patients. The retrieved literature was screened according to the inclusion and exclusion criteria. The quality of the included studies was assessed using the QUADAS-2 tools. Statistical analysis of the included studies was performed using Review Manager 5.3, Stata 16.0, and Meta-DiSc 1.4 statistical software. This meta-analysis was registered in PROSPERO (CRD42022315158). Findings Of 2193 studies, 23 studies involving a total of 25 AI models met the inclusion criteria. Among them, 18 studies explicitly mentioned training and test sets, and 5 studies did not explicitly mention grouping. In the training set, the pooled sensitivity was 0.93 [0.87, 0.96], the pooled specificity was 0.94 [0.87, 0.97], and the area under the ROC curve was 0.98 [0.96, 0.99]. In the validation set, the pooled sensitivity was 0.84 [0.78, 0.88], the pooled specificity was 0.89 [0.85, 0.92], and the area under the ROC curve was 0.93 [1.00, 0.00]. In the subgroup analysis, the areas under the summary receiver operating characteristic (SROC) curves of the artificial intelligence models KNN, SVM, ANN, RF and XGBoost were 0.98, 0.98, 0.94, 0.92, and 0.91, respectively. The Deeks funnel plot indicated that there was no significant publication bias in this study (P > 0.05). Interpretation Artificial intelligence models have high accuracy in predicting mortality among COVID-19 patients and have high prognostic value. Among them, the KNN, SVM, ANN, RF, XGBoost, and other models have the highest levels of accuracy

Integration of eQTL and machine learning to dissect causal genes with pleiotropic effects in genetic regulation networks of seed cotton yield

Summary: The dissection of a gene regulatory network (GRN) that complements the genome-wide association study (GWAS) locus and the crosstalk underlying multiple agronomical traits remains a major challenge. In this study, we generate 558 transcriptional profiles of lint-bearing ovules at one day post-anthesis from a selective core cotton germplasm, from which 12,207 expression quantitative trait loci (eQTLs) are identified. Sixty-six known phenotypic GWAS loci are colocalized with 1,090 eQTLs, forming 38 functional GRNs associated predominantly with seed yield. Of the eGenes, 34 exhibit pleiotropic effects. Combining the eQTLs within the seed yield GRNs significantly increases the portion of narrow-sense heritability. The extreme gradient boosting (XGBoost) machine learning approach is applied to predict seed cotton yield phenotypes on the basis of gene expression. Top-ranking eGenes (NF-YB3, FLA2, and GRDP1) derived with pleiotropic effects on yield traits are validated, along with their potential roles by correlation analysis, domestication selection analysis, and transgenic plants

Endothelin-1 Induces a Glycolytic Switch in Pulmonary Arterial Endothelial Cells via the Mitochondrial Translocation of Endothelial Nitric Oxide Synthase

Recent studies have indicated that, during the development of pulmonary hypertension (PH), there is a switch from oxidative phosphorylation to glycolysis in the pulmonary endothelium. However, the mechanisms underlying this phenomenon have not been elucidated. Endothelin (ET)-1, an endothelial-derived vasoconstrictor peptide, is increased in PH, and has been shown to play an important role in the oxidative stress associated with PH. Thus, in this study, we investigated whether there was a potential link between increases in ET-1 and mitochondrial remodeling. Our data indicate that ET-1 induces the redistribution of endothelial nitric oxide synthase (eNOS) from the plasma membrane to the mitochondria in pulmonary arterial endothelial cells, and that this was dependent on eNOS uncoupling. We also found that ET-1 disturbed carnitine metabolism, resulting in the attenuation of mitochondrial bioenergetics. However, ATP levels were unchanged due to a compensatory increase in glycolysis. Further mechanistic investigations demonstrated that ET-1 mediated the redistribution of eNOS via the phosphorylation of eNOS at Thr495 by protein kinase C δ. In addition, the glycolytic switch appeared to be dependent on mitochondrial-derived reactive oxygen species that led to the activation of hypoxia-inducible factor signaling. Finally, the cell culture data were confirmed in vivo using the monocrotaline rat model of PH. Thus, we conclude that ET-1 induces a glycolytic switch in pulmonary arterial endothelial cells via the redistribution of uncoupled eNOS to the mitochondria, and that preventing this event may be an approach for the treatment of PH