The N-terminal domain of Lhcb proteins is critical for recognition of the LHCII kinase

AbstractThe light-harvesting chlorophyll (Chl) a/b complex of photosystem (PS) II (LHCII) plays important roles in the distribution of the excitation energy between the two PSs in the thylakoid membrane during state transitions. In this process, LHCII, homo- or heterotrimers composed of Lhcb1–3, migrate between PSII and PSI depending on the phosphorylation status of Lhcb1 and Lhcb2. We have studied the mechanisms of the substrate recognition of a thylakoid threonine kinase using reconstituted site-directed trimeric Lhcb protein–pigment complex mutants. Mutants lacking the positively charged residues R/K upstream of phosphorylation site (Thr) in the N-terminal domain of Lhcb1 were no longer phosphorylated. Besides, the length of the peptide upstream of the phosphorylated site (Thr) is also crucial for Lhcb phosphorylation in vitro. Furthermore, the two N-terminal residues of Lhcb appear to play a key role in the phosphorylation kinetics because Lhcb with N-terminal RR was phosphorylated much faster than with RK. Therefore, we conclude that the substrate recognition of the LHCII kinase is determined to a large extent by the N-terminal sequence of the Lhcb proteins. The study provides new insights into the interactions of the Lhcb proteins with the LHCII kinase

High psychological stress levels related to delivery can increase the occurrence of postpartum mental disorders

ObjectiveThe study sought to explore the relationship between high psychological stress levels related to delivery and postpartum mental disorders.MethodsA total of 284 parturients were included in the study from July 2021 to January 2022. The stress level at 1 month postpartum was assessed by the Impact of Event Scale-Revised (IES-R). Parturients with an IES-R score ≤ 9 were included in the low psychological stress level group, and those with an IES-R score > 9 were included in the high psychological stress level group. The Edinburgh Postnatal Depression Scale (EPDS), Union Physio-Psycho-Social Assessment Questionnaire (UPPSAQ-70), Symptom Checklist-90 (SCL-90) and Mini-International Neuropsychiatric Interview (M.I.N.I.) were conducted at 42 ± 7 days postpartum to assess the mental health of parturients.The parturients’ mental health after birth was assessed by the EPDS, UPPSAQ-70, and SCL-90. Semi-structured diagnostic interviews were conducted at 42 ± 7 days postpartum by using the M.I.N.I.ResultsThe incidence rate of postpartum mental disorders was 20.42% (58/284), the incidence rates of postpartum depression, anxiety disorders, obsessive-compulsive disorder and posttraumatic stress disorder were 17.96% (51/284), 11.97% (34/284), 4.58% (13/284) and 1.41% (4/284), respectively, and the comorbidity rate was 58.62% (34/58). A history of mental disorders and pregnancy complications were risk factors for postpartum depression (p = 0.028, p = 0.040, respectively); a history of mental disorders, a lack of physical exercise, partner violence and pregnancy complications were risk factors for postpartum anxiety disorders (p = 0.003, p = 0.007, p = 0.031, p = 0.048, respectively); and the delivery of female infants was a risk factor for postpartum obsessive-compulsive disorder (p = 0.022).The risk of postpartum depression, anxiety disorders and obsessive-compulsive disorder was 9.125 times (95% CI = 3.900 ~ 21.349, p < 0.01), 7.310 times (95% CI = 2.588 ~ 20.649, p < 0.01) and 6.259 times (95% CI = 1.347 ~ 29.093, p < 0.01) higher in postpartum women with high psychological stress levels related to delivery than in those with low psychological stress levels, respectively.ConclusionThe incidence of postpartum mental disorders is high and has a positive correlation with the level of psychological stress. This may lead to a new perspective of the effect of psychological stress on postpartum mental disorders and attract more attention to other mental disorders in addition to postpartum depression

A method for estimating particulate organic carbon at the sea surface based on geodetector and machine learning

Particulate organic carbon (POC) is an essential component of the carbon pump within marine organisms. Exploring estimation methods for POC holds substantial significance for understanding the marine carbon cycle. In this study, we investigated the spatial heterogeneity of 30 factors and POC concentrations using geodetector to account for nonlinearity, diversity, and complexity. Ultimately, 20 factors including sea surface temperature, sea surface salinity, and chlorophyll-a were selected as modeling variables. Six machine learning models—backpropagation neural network, convolutional neural network, attention-based neural network, random forest (RF), adaptive boosting, and extreme gradient boosting were used to compare their performance. The results indicate that among the six machine learning algorithms, RF exhibits the strongest performance, with a root mean square error of 0.11 [log(mg/m3)] and an average percentage deviation of 2.73%. Global annual average sea surface POC concentrations were estimated for 2007 and compared to NASA’s POC product. The outcomes indicate that the RF model-based estimation method displays enhanced accuracy in estimating POC concentrations within intricate coastal environments, while the backpropagation neural network performed better in estimating POC concentrations in open ocean areas. Leveraging the RF model, global sea surface POC concentrations were estimated for the years 2007 through 2016, enabling a spatiotemporal analysis. The analysis unveils heightened POC concentrations in coastal regions and lower levels in open ocean areas. Furthermore, POC concentrations were greater in high-latitude regions compared to mid and low latitude counterparts. In conclusion, the global sea surface POC product in this study exhibits heightened spatial resolution and improved data completeness in contrast to other products. It enhances the accuracy of conventional POC estimation methods, particularly within coastal regions

Effect of GARP on osteogenic differentiation of bone marrow mesenchymal stem cells via the regulation of TGFβ1 in vitro

Mesenchymal stem cells (MSCs), which have multipotential differentiation and self-renewal potential, are possible cells for tissue engineering. Transforming growth factor β1 (TGFβ1) can be produced by MSCs in an inactive form, and the activation of TGFβ1 functions as an important regulator of osteogenic differentiation in MSCs. Recently, studies showed that Glycoprotein A repetitions predominant (GARP) participated in the activation of latent TGFβ1, but the interaction between GARP and TGFβ1 is still undefined. In our study, we successfully isolated the MSCs from bone marrow of rats, and showed that GARP was detected in bone mesenchymal stem cells (BMSCs). During the osteogenic differentiation of BMSCs, GARP expression was increased over time. To elucidate the interaction between GARP and TGFβ1, we downregulated GARP expression in BMSCs to examine the level of active TGFβ1. We then verified that the downregulation of GARP decreased the secretion of active TGFβ1. Furthermore, osteogenic differentiation experiments, alkaline phosphatase (ALP) activity analyses and Alizarin Red S staining experiments were performed to evaluate the osteogenic capacity. After the downregulation of GARP, ALP activity and Alizarin Red S staining significantly declined and the osteogenic indicators, ALP, Runx2, and OPN, also decreased, both at the mRNA and protein levels. These results demonstrated that downregulated GARP expression resulted in the reduction of TGFβ1 and the attenuation of osteoblast differentiation of BMSCs in vitro

The association and dose–response relationship between dietary intake of α-linolenic acid and risk of CHD: a systematic review and meta-analysis of cohort studies

Abstract Previous studies show inconsistent associations between α -linolenic acid (ALA) and risk of CHD. We aimed to examine an aggregate association between ALA intake and risk of CHD, and assess for any dose–response relationship. We searched the PubMed, EMBASE and Web of Science databases for prospective cohort studies examining associations between ALA intake and CHD, including composite CHD and fatal CHD. Data were pooled using random-effects meta-analysis models, comparing the highest category of ALA intake with the lowest across studies. Subgroup analysis was conducted based on study design, geographic region, age and sex. For dose–response analyses, we used two-stage random-effects dose–response models. In all, fourteen studies of thirteen cohorts were identified and included in the meta-analysis. The pooled results showed that higher ALA intake was associated with modest reduced risk of composite CHD (risk ratios (RR)=0·91; 95 % CI 0·85, 0·97) and fatal CHD (RR=0·85; 95 % CI 0·75, 0·96). The analysis showed a J-shaped relationship between ALA intake and relative risk of composite CHD ( χ 2 =21·95, P <0·001). Compared with people without ALA intake, only people with ALA intake <1·4 g/d showed reduced risk of composite CHD. ALA intake was linearly associated with fatal CHD – every 1 g/d increase in ALA intake was associated with a 12 % decrease in fatal CHD risk (95 % CI −0·21, −0·04). Though a higher dietary ALA intake was associated with reduced risk of composite and fatal CHD, the excess composite CHD risk at higher ALA intakes warrants further investigation, especially through randomised controlled trials

Pickering emulsion-enhanced interfacial biocatalysis: tailored alginate microparticles act as particulate emulsifier and enzyme carrier

A robust Pickering emulsion stabilized by lipase-immobilized alginate gel microparticles with a coating of silanized titania nanoparticles is developed for biphasic biocatalysis. The good recyclability and high stability of the proposed interfacial catalysis system have been verified, retaining about 90% of relative enzyme activity in 10 catalytic cycles with operation for 240 h. Meanwhile the Pickering emulsions remain stable during a storage time of one year. The green system can be widely applied to construct powerful platforms for enzyme or microorganism-driven interfacial catalysis

Chromosome-Level Genome Assembly for Acer pseudosieboldianum and Highlights to Mechanisms for Leaf Color and Shape Change

Acer pseudosieboldianum (Pax) Komarov is an ornamental plant with prominent potential and is naturally distributed in Northeast China. Here, we obtained a chromosome-scale genome assembly of A. pseudosieboldianum combining HiFi and Hi-C data, and the final assembled genome size was 690.24 Mb and consisted of 287 contigs, with a contig N50 value of 5.7 Mb and a BUSCO complete gene percentage of 98.4%. Genome evolution analysis showed that an ancient duplication occurred in A. pseudosieboldianum. Phylogenetic analyses revealed that Aceraceae family could be incorporated into Sapindaceae, consistent with the present Angiosperm Phylogeny Group system. We further construct a gene-to-metabolite correlation network and identified key genes and metabolites that might be involved in anthocyanin biosynthesis pathways during leaf color change. Additionally, we identified crucial teosinte branched1, cycloidea, and proliferating cell factors (TCP) transcription factors that might be involved in leaf morphology regulation of A. pseudosieboldianum, Acer yangbiense and Acer truncatum. Overall, this reference genome is a valuable resource for evolutionary history studies of A. pseudosieboldianum and lays a fundamental foundation for its molecular breeding

COVID-19 causes record decline in global CO2 emissions

The considerable cessation of human activities during the COVID-19 pandemic has affected global energy use and CO2 emissions. Here we show the unprecedented decrease in global fossil CO2 emissions from January to April 2020 was of 7.8% (938 Mt CO2 with a +6.8% of 2-{\sigma} uncertainty) when compared with the period last year. In addition other emerging estimates of COVID impacts based on monthly energy supply or estimated parameters, this study contributes to another step that constructed the near-real-time daily CO2 emission inventories based on activity from power generation (for 29 countries), industry (for 73 countries), road transportation (for 406 cities), aviation and maritime transportation and commercial and residential sectors emissions (for 206 countries). The estimates distinguished the decline of CO2 due to COVID-19 from the daily, weekly and seasonal variations as well as the holiday events. The COVID-related decreases in CO2 emissions in road transportation (340.4 Mt CO2, -15.5%), power (292.5 Mt CO2, -6.4% compared to 2019), industry (136.2 Mt CO2, -4.4%), aviation (92.8 Mt CO2, -28.9%), residential (43.4 Mt CO2, -2.7%), and international shipping (35.9Mt CO2, -15%). Regionally, decreases in China were the largest and earliest (234.5 Mt CO2,-6.9%), followed by Europe (EU-27 & UK) (138.3 Mt CO2, -12.0%) and the U.S. (162.4 Mt CO2, -9.5%). The declines of CO2 are consistent with regional nitrogen oxides concentrations observed by satellites and ground-based networks, but the calculated signal of emissions decreases (about 1Gt CO2) will have little impacts (less than 0.13ppm by April 30, 2020) on the overserved global CO2 concertation. However, with observed fast CO2 recovery in China and partial re-opening globally, our findings suggest the longer-term effects on CO2 emissions are unknown and should be carefully monitored using multiple measures