Prevention of Periprosthetic Infection After Orthopedic Knee Replacement Based on 5E Rehabilitation Nursing Model.

Context: Periprosthetic joint infections (PJIs) are a rare but highly destructive complication after total knee arthroplasty (TKA). Nursing plays an important role in preventing postoperative infections in patients, but different nursing modes have different rates of postoperative infections. Objective: The study intended to explore the effects of "encouragement, education, exercise, employment, and evaluation" (5E) rehabilitation nursing on the prevention of periprosthetic joint infections (PJIs) after TKA. Design: The research team conducted a randomized controlled trial. Setting: The study took place at the First People's Hospital of Huzhou in Huzhou, China. Participants: Participants were 80 TKA postoperative patients at the hospital between January 2023 and July 2023. Interventions: The research randomly divided participants into two groups: (1) the intervention group, the 5E group, with 40 participants and (2) the control group, with 40 participants. The control group received routine nursing, while the 5E group received 5E rehabilitation nursing. Outcome Measures: The research team examined: (1) the prosthesis' location; (2) wound healing; (3) score for knee joint function, using the Berg Balance Scale (BBS) and the Hospital Score for Special Surgery (HSS) of the knee joint; (4) postoperative level of inflammatory factors, using levels of C-reactive protein (CRP); (5) infection occurrence; (6) length of hospital stay; and (7) nursing satisfaction. Results: The prosthesis was well positioned in both groups. Compared to the control group, the 5E group's: (1) wound healing was significantly better (P < .001); (2) at 7 days after surgery, HSS score (P < .001) and BBS score (P < .001) were significantly higher; (3) C-reactive protein (CRP) levels were significantly lower (P < .001); (4) at 90 days after surgery, incidence of postoperative periprosthetic joint infection (PJI) was significantly lower (P < .001); (5) length of hospital stay was significantly shorter (P = .0013); and (7) nursing satisfaction was significantly higher (P = .0338). Conclusions: The 5E rehabilitation nursing for patients after TKA was helpful in promoting wound recovery, supporting the recovery of knee-joint function, reducing the incidence of PJIs, shortening the length of hospital stay, and improving patients' nursing satisfaction.

Grass-specific ABERRANT MICROSPORE DEVELOPMENT 1 is required for maintaining pollen fertility in rice.

Pollen development includes a series of biological events that require precise gene regulation. Although several transcription factors (TFs) have been shown to play roles in maintaining pollen fertility, the major regulatory networks underlying tapetum development and pollen wall formation are largely unknown. Herein, we report that ABERRANT MICROSPORE DEVELOPMENT1 (AMD1), a protein annotated previously as unknown protein, is required for tapetum development and pollen exine patterning in rice (Oryza sativa L.). AMD1 encodes a grass-specific protein exhibiting transactivation activity in the nucleus and is spatiotemporally expressed in the tapetum and microspores during pollen development. Further biochemical assays indicate that AMD1 directly activates the transcription of DEFECTIVE POLLEN WALL (DPW) and POLYKETIDE SYNTHASE2 (OsPKS2), which are both implicated in sporopollenin biosynthesis during exine formation. Additionally, AMD1 directly interacts with TAPETUM DEGENERATION RETARDATION (TDR), a key TF involved in the regulation of tapetum degradation and exine formation. Taken together, we demonstrate that AMD1 is an important regulatory component involved in the TDR-mediated regulatory pathway to regulate sporopollenin biosynthesis, tapetum degradation, and exine formation for pollen development. Our work provides insights into the regulatory network of rice sexual reproduction and a useful target for genetic engineering of new male-sterile lines for hybrid rice breeding.

SWOLLEN TAPETUM AND STERILITY 1 is required for tapetum degeneration and pollen wall formation in rice.

The pollen wall is important for protecting the male gametophyte and for fertilization. The lipid components of the pollen wall are mainly synthesized and transported from the sporophytic tapetum. Although several factors related to lipid biosynthesis have been characterized, the molecular mechanisms underlying lipid biosynthesis during pollen development in rice (Oryza sativa L.) remain elusive. Here, we showed that mutation in the SWOLLEN TAPETUM AND STERILITY 1 (STS1) gene causes delayed tapetum degradation and aborted pollen wall formation in rice. STS1 encodes an endoplasmic reticulum (ER)-localized protein that contains domain of unknown function (DUF) 726 and exhibits lipase activity. Lipidomic and transcriptomic analyses showed that STS1 is involved in anther lipid homeostasis. Moreover, STS1 interacts with Polyketide Synthase 2 (OsPKS2) and Acyl-CoA Synthetase 12 (OsACOS12), two enzymes crucial in lipidic sporopollenin biosynthesis in pollen wall formation, suggesting a potentially lipidic metabolon for sporopollenin biosynthesis in rice. Collectively, our results indicate that STS1 is an important factor for lipid biosynthesis in reproduction, providing a target for the artificial control of male fertility in hybrid rice breeding and insight into the function of DUF726-containing protein in plants.

Secretory lipid transfer protein OsLTPL94 acts as a target of EAT1 and is required for rice pollen wall development.

The plant pollen wall protects the male gametophyte from various biotic and abiotic stresses. The formation of a unique pollen wall structure and elaborate exine pattern is a well-organized process, which needs coordination between reproductive cells and the neighboring somatic cells. However, molecular mechanisms underlying this process remain largely unknown. Here, we report a rice male-sterile mutant (l94) that exhibits defective pollen exine patterning and abnormal tapetal cell development. MutMap and knockout analyses demonstrated that the causal gene encodes a type-G non-specific lipid transfer protein (OsLTPL94). Histological and cellular analyses established that OsLTPL94 is strongly expressed in the developing microspores and tapetal cells, and its protein is secreted to the plasma membrane. The l94 mutation impeded the secretory ability of OsLTPL94 protein. Further in vivo and in vitro investigations supported the hypothesis that ETERNAL TAPETUM 1 (EAT1), a basic helix-loop-helix transcription factor (bHLH TF), activated OsLTPL94 expression through direct binding to the E-box motif of the OsLTPL94 promoter, which was supported by the positive correlation between the expression of EAT1 and OsLTPL94 in two independent eat1 mutants. Our findings suggest that the secretory OsLTPL94 plays a key role in the coordinated development of tapetum and microspores with the regulation of EAT1.

DEAP1 encodes a fasciclin-like arabinogalactan protein required for male fertility in rice.

Arabinogalactan proteins (AGPs) are widely distributed in plant cells. Fasciclin-like AGPs (FLAs) belong to a subclass of AGPs that play important roles in plant growth and development. However, little is known about the biological functions of rice FLA. Herein, we report the identification of a male-sterile mutant of DEFECTIVE EXINE AND APERTURE PATTERNING1 (DEAP1) in rice. The deap1 mutant anthers produced aberrant pollen grains with defective exine formation and a flattened aperture annulus and exhibited slightly delayed tapetum degradation. DEAP1 encodes a plasma membrane-associated member of group III plant FLAs and is specifically and temporally expressed in reproductive cells and the tapetum layer during male development. Gene expression studies revealed reduced transcript accumulation of genes related to exine formation, aperture patterning, and tapetum development in deap1 mutants. Moreover, DEAP1 may interact with two rice D6 PROTEIN KINASE-LIKE3s (OsD6PKL3s), homologs of a known Arabidopsis aperture protein, to affect rice pollen aperture development. Our findings suggested that DEAP1 is involved in male reproductive development and may affect exine formation and aperture patterning, thereby providing new insights into the molecular functions of plant FLAs in male fertility.

Building a novel multivariate nonlinear MGM(1,m,N|γ) model to forecast carbon emissions.

With the proposal of the carbon neutrality target, China's attention to carbon emissions has been further enhanced. Effective prediction of future carbon emissions is important for the formulation of carbon neutralization target and action plans in the region. Many factors affecting carbon emissions, cause their development trends may be nonlinear. To forecast the carbon emissions of coal and natural gas in the industrial sector more accurately, a new MGM(1,m,N|γ) model considering nonlinear characteristics is proposed in this paper. The new model introduces power function γ as nonlinear parameter, and the γ value is solved by nonlinear constraint function. We further deduce the simulation and prediction formula and then apply the improved model to the carbon emission forecast. The comparisons show that the nonlinear parameters can modify the trend of sequences and improve the prediction accuracy, which verifies the validity of the model. Finally, according to the influencing factors and forecast results, this paper analyzes the causes of high carbon emissions and puts forward reasonable suggestions for China's carbon governance.

Forecasting carbon emissions using MGM(1,m|λ,γ) model with the similar meteorological condition.

Carbon emission is a common concern of the international community and effectively predicting its future trend is necessary for emission reduction planning. Considering that the change trend of carbon emissions is unstable, more attention should be paid to the correction effect of new information on the development trend. Therefore, based on the traditional MGM(1,m) model, this paper introduces the new information priority operator λ and nonlinear parameter γ to strengthen the role of new information, further constructs three comparison models of MGM(1,m|λ), MGM(1,m|γ) and MGM(1,m|λ,γ).Then we apply the new model to the carbon emission prediction of different regions (cities, countries and continents) and different trends (fluctuating, rising and declining). The results illustrate that the new model has higher prediction accuracy, and adding dynamic parameters is a scientific and practical method to improve the forecasting ability of the grey forecasting model. Finally, we analyze the current situation and future development trend of carbon emissions, and put forward reasonable suggestions.

Forecasting greenhouse gas emissions with the new information priority generalized accumulative grey model.

Air pollution and other environmental problems caused by excessive emissions of greenhouse gases have become a comprehensive problem requiring joint global treatment. To consider the characteristics of different regions and different countries in terms of greenhouse gas emissions for accurate prediction, a new information priority generalized accumulative grey model (NIPGAGM(1,1,k)) is proposed. The new model maintains the structure of the traditional grey model and the basic result characteristics of its features. This research further deduces the calculation formulas of the model's time response sequence and parameter estimation. Furthermore, an optimization model is established to search the parameters using a detailed optimization algorithm. The optimization value of the new model is determined by the intelligent optimization algorithm. Then, the new model is applied to the greenhouse gas emission prediction of the Shanghai Cooperation Organization (SCO) member states. The numerical results are compared with those of existing models. Finally, according to the forecast results of greenhouse gas emissions in these regions, reasonable suggestions for clean energy production are proposed.

Forecast of carbon emissions in China based on time lag MGM(1,m,N|τ) grey model.

Global climate issues have been gaining international attention in recent years. As the largest developing country and the prime carbon emitter, the Chinese government has proposed a strategic 'double carbon' target for carbon emissions. To predict carbon emissions more accurately, clarify the future supply situation and optimise resource allocation, based on the grey MGM(1,m,N|τ) model, we introduced and applied the particle swarm algorithm to determine the time lag parameter τ and proposed a new MGM(1,m,N|τ) grey model. We give a detailed modelling procedure, including calculation steps and intelligent optimisation algorithms, by fully considering the effect of time lag. In this study, this new model is used to simulate and forecast China's carbon emissions from 2010 to 2019 and compare it with other traditional grey models and their improved time-lagged forms. The results show that the new model has significant advantages in prediction accuracy and validity, plus good prediction performance for carbon emissions, which can be extended to more macro and micro energy consumption prediction problems.