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Purpose To analyze health-related quality of life (HRQoL) and related factors among elderly persons receiving community-based home care and institutional care in Guangzhou, a large city of mainland China. Methods A representative sample of 1600 subjects aged 60 years and over residing in communities and nursing homes was randomly selected through stratified sampling. The 12-item Short Form Health Survey version 2 (SF-12v2) was used to assess HRQoL. Results In total, 1014 elderly persons under different aged care models responded to the survey (response rate 63.4%) and 1000 were eligible for data analyses. Compared with the elderly receiving community-based home care or private institutional care, those in public institutional care had the lowest scores on the physical component summary (PCS, 36.89 ± 10.44) and the mental component summary (MCS, 47.16 ± 11.14). Number of chronic diseases, loneliness, and age were the most common significant factors ( P  < 0.05) affecting PCS and MCS. The interaction term between aged care model and number of chronic diseases significantly affected PCS ( β  = − 0.165, P  < 0.05), indicating a stronger association between these factors for participants receiving community-based home care than institutional care. The interaction term between aged care model and loneliness had a significant effect on MCS ( β  = 0.189, P  < 0.05), indicating a weaker association between loneliness and MCS for participants receiving community-based home care. Conclusions This study found poor HRQoL among the elderly in Guangzhou. The main factors associated with the physical and mental HRQoL of elderly persons included number of chronic diseases, loneliness, age, and education level. It also revealed the moderating effects of aged care model on HRQoL, suggesting specific health management strategies for elderly in community-based home care and institutional care, respectively.

Background: We assessed the information regarding the psychometric properties of the Short Form-12 Health Survey Version 2 (SF-12v2) among older adults in China Methods: A cross-sectional study was conducted on a stratified representative sample of older adults (≥60 years) residing in community and nursing home settings in 2017-18. Reliability was estimated using the internal consistency method. Validity was assessed using convergent and discriminant validity checks, factor analyses (including both exploratory and confirmatory factor analyses [EFA and CFA]), and “known groups” construct validity. Results: The final sample comprised 1000 older adults (451 community-dwelling and 549 institutional). Cronbach’s α was 0.81 for the Physical Component Summary (PCS) and 0.83 for the Mental Component Summary (MCS), showing satisfactory internal consistency for both. Most items were strongly correlated with their represented component (Spearman’s correlation coefficient: 0.62–0.87), although the correlation of SF items with PCS was a bit stronger than that with MCS. A two-factor structure (physical and mental health) indicated by EFA jointly accounted for 68.50% of the variance and presented adequate goodness-of-fit indices (GFI=0.98, AGFI=0.92, RMSEA=0.08, 90% Cl RMSEA=0.06 to 0.11, NFI=0.98, and CFI=0.98) in CFA. Known-groups comparison showed that SF-12v2 summary scores did well in differentiating subgroups of older adults by age, marital status, and self-reported health problems (P≤0.05). Conclusion: SF-12v2 is a reliable and valid health-related quality of life instrument for Chinese older adults that works equally well with older adults under institutional care and community-based home care models.

This paper introduces a novel method to recognize the facial micro-expressions by directly adopting state-of-the-arts deep learning algorithms. Specifically, genetic algorithm (GA) is applied based on the principles of evolution in searching an optimal solution to generate discriminant features. Prior to that, the feature vectors of each video are first encoded using existing apex-based feature descriptors, viz, Bi-WOOF, OFF-ApexNet and STSTNet. Then, GA is utilized to enrich the features by eliminating irrelevant information that do not contribute to the expression prediction. It is acknowledged that the overfitting phenomena can be avoided in the feature selection process, as GA employs tournament selection and deterministic mutation procedures during the evolution procedure. As a result, Genetic Algorithm in Apex Frame Network (GA-ApexNet) is introduced and significant improvement of the recognition performance has been achieved. A standard experimental configuration is designed to evaluate the robustness of the proposed framework. Following the suggestion in Facial Micro-Expressions Grand Challenge (MEGC 2019), the UF1 and UAR obtained are 78.85% and 78.28%, for the composite dataset that comprises CASME II, SMIC and SAMM. We also note that this is the first work that fuses GA in micro-expression recognition system.

Value co-creation focuses on customer participation and co-creates value with suppliers. Patients' support and cooperation can improve the quality of medical care. Value creation is closely related to participants' behavior. The DART (Dialogue, Access, Risk assessment, Transparency) model is widely used in commercial research because it defines and classifies value co-creation behavior clearly and systematically. However, there is little research using the DART model in the field of health care. This study aimed to develop and evaluate the psychometric properties of a scale measuring patient value co-creation behavior based on the DART model.OBJECTIVESValue co-creation focuses on customer participation and co-creates value with suppliers. Patients' support and cooperation can improve the quality of medical care. Value creation is closely related to participants' behavior. The DART (Dialogue, Access, Risk assessment, Transparency) model is widely used in commercial research because it defines and classifies value co-creation behavior clearly and systematically. However, there is little research using the DART model in the field of health care. This study aimed to develop and evaluate the psychometric properties of a scale measuring patient value co-creation behavior based on the DART model.The Delphi technique was used to determine the scale content with a panel of 17 experts. A cross-sectional survey was administered to 356 outpatients and inpatients of a hospital in Guangzhou, China.STUDY DESIGNThe Delphi technique was used to determine the scale content with a panel of 17 experts. A cross-sectional survey was administered to 356 outpatients and inpatients of a hospital in Guangzhou, China.Internal consistency reliability and composite reliability (CR) were used to estimate the scale's reliability. Validity was assessed using convergent and discriminant validity.METHODSInternal consistency reliability and composite reliability (CR) were used to estimate the scale's reliability. Validity was assessed using convergent and discriminant validity.Three rounds of expert consultation were completed before a final consensus was reached regarding scale content. The patient value co-creation behavior scale was composed of 23 items and 4 dimensions. The overall Cronbach's α was 0.934, and the CRs of the 4 DART dimensions were 0.843, 0.872, 0.911, and 0.884, respectively, showing satisfactory reliability. The average variance extracted ranged from 0.473 to 0.659, and the χ2 difference between constrained and free models was significant, indicating convergent and discriminant validity.RESULTSThree rounds of expert consultation were completed before a final consensus was reached regarding scale content. The patient value co-creation behavior scale was composed of 23 items and 4 dimensions. The overall Cronbach's α was 0.934, and the CRs of the 4 DART dimensions were 0.843, 0.872, 0.911, and 0.884, respectively, showing satisfactory reliability. The average variance extracted ranged from 0.473 to 0.659, and the χ2 difference between constrained and free models was significant, indicating convergent and discriminant validity.The scale exhibited acceptable reliability and validity and could serve as an evaluation tool for patient value co-creation behavior.CONCLUSIONSThe scale exhibited acceptable reliability and validity and could serve as an evaluation tool for patient value co-creation behavior.

This experiment was conducted to evaluate the effect of seed priming on the germination and physiology of Pinus bungeana seeds. Seeds were treated by hydropriming with distilled water, halopriming with potassium nitrate (KNO3) at -0.3, -0.6, -1.2 MPa respectively (untreated dry seeds were taken as control). Properties of seed germination and physiology were determined and the effect of hydro- and halopriming on germination and physiology of P. bungeana seeds were investigated. The results showed that, compared with control, each priming treatment had increased the ge rmination percentage (GP) and germination index (GI), shortened the mean germination time (MGT) and the time required for 50% of the seeds to germinate (G ^sub 50^). Primed P. bungeana seeds significantly decreased the relative conductivity and the amount of malondialdehyde (MDA). Of all the treatments applied to seeds of P. bungeana, halopriming at -0.3 MPa KNO3 produced the highest GP (65.0%) and the shortest MGT (18.8 d) and G ^sub 50^ (18.2 d).

Starch accounts for up to 90% of the dry weight of rice endosperm and is a key determinant of grain quality. Although starch biosynthesis enzymes have been comprehensively studied, transcriptional regulation of starch‐synthesis enzyme‐coding genes (SECGs) is largely unknown. In this study, we explored the role of a NAC transcription factor, OsNAC24, in regulating starch biosynthesis in rice. OsNAC24 is highly expressed in developing endosperm. The endosperm of osnac24 mutants is normal in appearance as is starch granule morphology, while total starch content, amylose content, chain length distribution of amylopectin and the physicochemical properties of the starch are changed. In addition, the expression of several SECGs was altered in osnac24 mutant plants. OsNAC24 is a transcriptional activator that targets the promoters of six SECGs; OsGBSSI , OsSBEI , OsAGPS2 , OsSSI , OsSSIIIa and OsSSIVb . Since both the mRNA and protein abundances of OsGBSSI and OsSBEI were decreased in the mutants, OsNAC24 functions to regulate starch synthesis mainly through OsGBSSI and OsSBEI. Furthermore, OsNAC24 binds to the newly identified motifs TTGACAA, AGAAGA and ACAAGA as well as the core NAC‐binding motif CACG. Another NAC family member, OsNAP, interacts with OsNAC24 and coactivates target gene expression. Loss‐of‐function of OsNAP led to altered expression in all tested SECGs and reduced the starch content. These results demonstrate that the OsNAC24‐OsNAP complex plays key roles in fine‐tuning starch synthesis in rice endosperm and further suggest that manipulating the OsNAC24‐OsNAP complex regulatory network could be a potential strategy for breeding rice cultivars with improved cooking and eating quality.

Mining is among the human activities with widest environmental impacts, and mining-impacted environments are characterized by high levels of metals that can co-select for antibiotic resistance genes (ARGs) in microorganisms. However, ARGs in mining-impacted environments are still poorly understood. Here, we conducted a comprehensive study of ARGs in such environments worldwide, taking advantage of 272 metagenomes generated from a global-scale data collection and two national sampling efforts in China. The average total abundance of the ARGs in globally distributed studied mine sites was 1572 times per gigabase, being rivaling that of urban sewage but much higher than that of freshwater sediments. Multidrug resistance genes accounted for 40% of the total ARG abundance, tended to co-occur with multimetal resistance genes, and were highly mobile (e.g. on average 16% occurring on plasmids). Among the 1848 high-quality metagenome-assembled genomes (MAGs), 85% carried at least one multidrug resistance gene plus one multimetal resistance gene. These high-quality ARG-carrying MAGs considerably expanded the phylogenetic diversity of ARG hosts, providing the first representatives of ARG-carrying MAGs for the Archaea domain and three bacterial phyla. Moreover, 54 high-quality ARG-carrying MAGs were identified as potential pathogens. Our findings suggest that mining-impacted environments worldwide are underexplored hotspots of multidrug resistance genes.

As a result of the escalating number of new cancer treatments being developed and competition among pharmaceutical companies, decisions regarding how to proceed with phase III trials are frequently based on findings from either single‐arm phase I expansion cohorts or phase II studies that compare the efficacy of the study drug to a standard‐of‐care benchmark derived from historical data. However, even when eligibility criteria are matched, differences in the distribution of baseline patient features may influence the outcome of single‐arm trials in real‐world scenarios. Therefore, novel methods are needed to enhance the accuracy of efficacy prediction from current cohorts relative to historical data. In this study, we demonstrated the feasibility of using the propensity score matching (PSM) method to improve decision making by matching relevant baseline features between current and historical cohorts. According to our findings, utilizing the PSM method may provide a less biased means of comparing outcomes between current and historical cohorts relative to a naïve approach, which relies solely on differences in average outcomes between the cohorts.

Grain size and the endosperm starch content determine grain yield and quality in rice. Although these yield components have been intensively studied, their regulatory mechanisms are still largely unknown. In this study, we show that loss-of-function of OsNAC129 , a member of the NAC transcription factor gene family that has its highest expression in the immature seed, greatly increased grain length, grain weight, apparent amylose content (AAC), and plant height. Overexpression of OsNAC129 had the opposite effect, significantly decreasing grain width, grain weight, AAC, and plant height. Cytological observation of the outer epidermal cells of the lemma using a scanning electron microscope (SEM) revealed that increased grain length in the osnac129 mutant was due to increased cell length compared with wild-type (WT) plants. The expression of OsPGL1 and OsPGL2 , two positive grain-size regulators that control cell elongation, was consistently upregulated in osnac129 mutant plants but downregulated in OsNAC129 overexpression plants. Furthermore, we also found that several starch synthase-encoding genes, including OsGBSSI , were upregulated in the osnac129 mutant and downregulated in the overexpression plants compared with WT plants, implying a negative regulatory role for OsNAC129 both in grain size and starch biosynthesis. Additionally, we found that the expression of OsNAC129 was induced exclusively by abscisic acid (ABA) in seedlings, but OsNAC129 -overexpressing plants displayed reduced sensitivity to exogenous brassinolide (BR). Therefore, the results of our study demonstrate that OsNAC129 negatively regulates seed development and plant growth, and further suggest that OsNAC129 participates in the BR signaling pathway.

Rice is a major food crop that sustains approximately half of the world population. Recent worldwide improvements in the standard of living have increased the demand for high-quality rice. Accurate identification of quantitative trait loci (QTLs) for rice grain quality traits will facilitate rice quality breeding and improvement. In the present study, we performed high-resolution QTL mapping for rice grain quality traits using a genotyping-by-sequencing approach. An F 2 population derived from a cross between an elite japonica variety, Koshihikari, and an indica variety, Nona Bokra, was used to construct a high-density genetic map. A total of 3,830 single nucleotide polymorphism markers were mapped to 12 linkage groups spanning a total length of 2,456.4 cM, with an average genetic distance of 0.82 cM. Seven grain quality traits—the percentage of whole grain, percentage of head rice, percentage of area of head rice, transparency, percentage of chalky rice, percentage of chalkiness area, and degree of chalkiness—of the F 2 population were investigated. In total, 15 QTLs with logarithm of the odds (LOD) scores >4 were identified, which mapped to chromosomes 6, 7, and 9. These loci include four QTLs for transparency, four for percentage of chalky rice, four for percentage of chalkiness area, and three for degree of chalkiness, accounting for 0.01%–61.64% of the total phenotypic variation. Of these QTLs, only one overlapped with previously reported QTLs, and the others were novel. By comparing the major QTL regions in the rice genome, several key candidate genes reported to play crucial roles in grain quality traits were identified. These findings will expedite the fine mapping of these QTLs and QTL pyramiding, which will facilitate the genetic improvement of rice grain quality.