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ObjectiveAfter fully lifting coronavirus disease 2019 (COVID-19) pandemic control measures in mainland China in 12/2022, the incidence of COVID-19 has increased markedly, making it difficult to meet the general time-in-range (TIR) requirement. We investigated a more clinically practical TIR threshold and examined its association with the prognosis of COVID-19 patients with type 2 diabetes(T2D).Research design and methods63 T2D patients complicated with COVID-19 were evaluated. Patients were divided into favorable outcome group and adverse outcome group according to whether achieving composite endpoint (a >20-day length of stay, intensive care unit admission, mechanical ventilation use, or death). TIR, the time-below-range (TBR) and the time-above-range (TAR) were calculated from intermittently scanned continuous glucose monitoring. Logistic regression analysis and other statistical methods were used to analyze the correlation between glucose variability and prognosis to establish the appropriate reference range of TIR.ResultsTIR with thresholds of 80 to 190 mg/dL was significantly associated with favorable outcomes. An increase of 1% in TIR is connected with a reduction of 3.70% in the risk of adverse outcomes. The Youden index was highest when the TIR was 54.73%, and the sensitivity and specificity were 58.30% and 77.80%, respectively. After accounting for confounding variables, our analysis revealed that threshold target ranges (TARs) ranging from 200 mg/dL to 230 mg/dL significantly augmented the likelihood of adverse outcomes.ConclusionThe TIR threshold of 80 to 190 mg/dL has a comparatively high predictive value of the prognosis of COVID-19. TIR >54.73% was associated with a decreased risk of adverse outcomes. These findings provide clinically critical insights into possible avenues to improve outcomes for COVID-19 patients with T2D.

Both genetic and environmental factors affect the morphology of oysters. Molecular identification is currently the primary means of species identification, but it is inconvenient and costly. In this research, we evaluated the effectiveness of geometric morphometric (GM) techniques in distinguishing between two oyster species, Crassostrea gigas and C. ariakensis. We used traditional morphometric and GM methods, including principal component analysis (PCA), thin-plate spline analysis (TPS) and canonical variable analysis (CVA), to identify specific features that distinguish the two species. We found that differences in shape can be visualised using GM methods. The Procrustes analysis revealed significant differences in shell morphology between C. gigas and C. ariakensis. The shells of C. ariakensis are more prominent at the widest point and are more scattered and have a greater variety of shapes. The shells of C. gigas are more oval in shape. PCA results indicated that PC1 explained 45.22%, PC2 explained 22.09% and PC3 explained 10.98% of the variation between the two species, which suggests that the main morphological differences are concentrated in these three principal components. Combining the TPS analysis function plots showed that the shell shape of C. ariakensis is mainly elongated and spindle-shaped, whereas the shell shape of C. gigas is more oval. The CVA results showed that the classification rate for the two species reached 100% which means that C. ariakensis and C. gigas have distinct differences in shell morphology and can be completely separated, based on morphological characteristics. Through these methods, a more comprehensive understanding of the morphological characteristics of different oyster populations can be obtained, providing a reference for oyster classification and identification.

The influence of different environmental factors on the infectivity of H1N1 influenza virus was measured. We found less than 1-log reduction when viruses were exposed to NaCl solutions up to 5 M or solutions with pH = 4 through 11 for one hour. The infectivity of the virus was sensitive to the solution temperature. A log reduction ranging from 2 to more than 6 was observed starting at 50 °C and spanning just 3 or 5 for 10- or 30 min exposures, respectively. Drying the virus in media on aluminum or polymer coupons for 48 h resulted in a log reduction of 4 when kept at room temperature, but less than one when kept at 4 °C or -20 °C. Log reduction greater than 6 occurred at room temperature after 3 days, but only 1-log reduction occurred at 4 and -20 °C after 6 days. Drying on different coinage achieved similar results, except for pennies, where more than 6-log reduction was observed after 24 h. HOCl was used to fog the aluminum and polymer surfaces, placed vertically, for 5 and 7.5 min to achieve a log reduction of 4 and for 6.5 respectively. Storage of opened solution containers for 9 months at ambient resulted in a decrease in chlorine concentration from 550 ppm to 240 ppm. Fogging with the old solution was still able to achieve a log reduction of 6.5 after 7.5 min fogging. The study indicates that exposure to common environmental conditions such as a wide pH range, high salinity, and low temperatures has only a minor effect on infectivity. which can persist for more than 5 days when dried on commonly encountered surfaces, allowing accumulation of infectious viral titre. Fogging with HOCl is an effective method of delivering disinfectants to large areas, achieving complete reduction of the viral titer on both horizontal and vertical surfaces.

Panax notoginseng saponins (PNSs) are used as industrial raw materials to produce many drugs to treat cardio-cerebrovascular diseases. However, it is a heat-sensitive plant, and its large-scale artificial cultivation is impeded by high temperature stress, leading to decreases in productivity and PNSs yield. Here, we examined exogenous foliar leucine to alleviate heat stress and explored the underlying mechanism using metabolomics. The results indicated that 3 and 5 mM exogenous foliar leucine significantly alleviated heat stress in one-year- and two-year-old P. notoginseng in pots and field trials. Exogenous foliar leucine enhanced the antioxidant capacity by increasing the activities of antioxidant enzymes (POD, SOD) and the contents of antioxidant metabolites (amino acids). Moreover, exogenous foliar leucine enhanced carbohydrate metabolism, including sugars (sucrose, maltose) and TCA cycle metabolites (citric acid, aconitic acid, succinic acid and fumaric acid), in P. notoginseng leaves, stems, and fibrous roots to improve the energy supply of plants and further alleviate heat stress. Field experiments further verified that exogenous foliar leucine increased the productivity and PNSs accumulation in P. notoginseng. These results suggest that leucine application is beneficial for improving the growth and quality of P. notoginseng under heat stress. It is therefore possible to develop plant growth regulators based on leucine to improve the heat resistance of P. notoginseng and other crops.

Green agriculture can minimize the negative impact of agriculture on the environment. As countries around the world strongly advocate green production and green life style, not only is consumers' awareness about green consumption rising, but the demand for green agricultural products at home and abroad is gradually increasing as well. Brand image has been a crucial factor for consumers to make their final purchasing decisions, thus playing a critical role in influencing the purchasing decisions of consumers. Based on the theory of the brand image, this paper undergoes a comprehensive theoretical and positive analysis and explores the influence mechanism of brand image of green agricultural products on consumers' purchasing intention. A hypothetical model with perceived value as mediators is constructed by us to examine the influence of brand image of green agricultural products on consumers' purchasing intention. A quantitative study was conducted for a random sample of 341 consumers who purchased green agricultural products in China according to a questionnaire-based survey using a cluster random sampling technique. The study showed that the overall image of agribusiness, the image of agricultural products, the social image of agribusiness, and the image of consumers are all positively related to consumption intention. The overall image of agribusiness, the image of agricultural products, the social image of agribusiness, and the image of consumers have a positive influence on perceived value. Moreover, perceived value plays a part in the mediating role in the influence of the overall image of agribusiness, the image of agricultural products, the social image of agribusiness, and the image of consumers on consumption intention. These findings shed lights on enterprises in establishing a scientific and effective brand strategy and building an excellent brand image. The research conclusion can provide new insight into how to enhance the consumption willingness for green agricultural products and promote sustainable development.

The Bay of Bengal (BoB) is conventionally believed to be a low productive, oligotrophic marine ecosystem, where the diazotroph communities presumed to play a vital role in adding “new” nitrogen through the nitrogen fixation process. However, the diazotroph communities in the oceanic region of the BoB are still poorly understood though it represents most of the seawater volume. The present study investigated a detailed account of the bacterioplankton community structure and distribution in the oceanic BoB during the winter monsoon using high throughput sequencing targeting the 16S rRNA and nifH genes. Our study observed diverse groups of bacterioplankton communities in the BoB including both cyanobacterial and non-cyanobacterial phylotypes. Cyanobacteria (Prochlorococcus spp. and Synechococcus spp.) and Proteobacteria (mainly α-, γ-, and δ-Proteobacteria) were the most abundant groups within the bacterial communities, possessing differential vertical distribution patterns. Cyanobacteria were more abundant in the surface waters, whereas Proteobacteria dominated the deeper layers (75 m). However, within the diazotroph communities, Proteobacteria (mainly γ-Proteobacteria) were the most dominant groups than Cyanobacteria. Function prediction based on PICRUSt revealed that nitrogen fixation might more active to add fixed nitrogen in the surface waters, while nitrogen removal pathways (denitrification and anammox) might stronger in deeper layers. Canonical correspondence analysis (CCA) indicated that temperature, salinity, and silicate were major environmental factors driving the distribution of bacterial communities. Additionally, phosphate was also an important factor in regulating the diazotroph communities in the surface water. Overall, this study provided detailed information on bacterial communities and their vital role in the nitrogen cycles in oligotrophic ecosystems.

Marine picocyanobacteria Synechococcus exhibit highly diverse pigment types (PTs) and hence possess great advantage to utilize different spectrum of light effectively and to occupy a wide range of light niches. In this study, we explored the diversity of Synechococcus PTs in the eastern Indian Ocean (EIO), surface water of Strait of Malacca (SSM), and coastal waters of Sri Lanka (SSL). All the detected PTs were phycourobilin (PUB) containing PT 3 and showed distinct distribution patterns. Low PUB PT 3a and partial chromatic acclimater PT 3eA dominated in coastal and shallow waters (SSM and SSL). In contrast, high PUB and chromatic acclimaters PT 3dA and PT 3c/3dB were mainly distributed in open ocean (EIO). PT 3dA and PT 3c/3dB occurred at similar depths of the lower euphotic layers but showed distinct distribution pattern that are partially exclusive, indicating that they compete with each other for the same light niche. Interestingly, the newly described PT 3f was detected with high relative abundances at all stations and particularly dominated in the upper euphotic layer in EIO, which was confirmed with PT-specific quantitative polymerase chain reaction (qPCR). The relative abundance of PT 3f was negatively correlated with nutrient level, implying that PT 3f is adapted to oligotrophic waters. Pronounced niche partition of different PTs was observed in the upper and lower layers of euphotic zone in EIO and SSM/SSL. Light, nutrients, and strong stratification may play important roles in the niche partition of different PTs. Further analysis about ecologically significant taxonomic units revealed high diversity within each PT at different locations, which provided insights for understanding specific PT with wide range of niches.

Na+ is the most abundant ion in living organisms and plays essential roles in regulating nutrient uptake, muscle contraction, and neurotransmission. The identification of Na+ in protein structures is crucial for gaining a deeper understanding of protein function in a physiological context. LeuT, a bacterial homolog of the neurotransmitter:sodium symporter family, uses the Na+ gradient to power the uptake of amino acids into cells and has been used as a paradigm for the study of Na+-dependent transport systems. We have devised a low-energy multi-crystal approach for characterizing low-Z (Z ≤ 20) anomalous scattering ions such as Na+, Mg2+, K+, and Ca2+ by combining Bijvoet-difference Fourier syntheses for ion detection and f” refinements for ion speciation. Using the approach, we experimentally identify two Na+ bound near the central leucine binding site in LeuT. Using LeuT microcrystals, we also demonstrate that Na+ may be depleted to study conformational changes in the LeuT transport cycle.

To examine the spatial pattern and controlling factors of the primary productivity (PP) of phytoplankton in the eastern Indian Ocean (EIO), deck-incubation carbon fixation (a 14C tracer technique) and the related hydrographic properties were measured at 15 locations during the pre-summer monsoon season (February–April 2017). There are knowledge gaps in the field observations of PP in the EIO. The estimated daily carbon production rates integrated over the photic zone ranged from 113 to 817 mgC m–2 d–1, with a mean of 522 mgC m–2 d–1. The mixed-layer integrated primary production (MLD-PP) ranged from 29.0 to 303.7 mgC m–2 d–1 (mean: 177.2 mgC m–2 d–1). The contribution of MLD-PP to the photic zone-integrated PP (PZI-PP) varied between 19 and 51% (mean: 36%). Strong spatial variability in the carbon fixation rates was found in the study region. Specifically, the surface primary production rates were relatively higher in the Bay of Bengal domain affected by riverine flux and lower in the equatorial domain owing to the presence of intermonsoonal Wyrtki jets, which were characterized by a depression of thermocline and nitracline. The PZI-PP exhibited a linear (positive) relationship with nutrient values, but with no significance, indicating a partial control of macronutrients and a light limitation of carbon fixation. As evident from the vertical profiles, the primary production process mainly occurred above the nitracline depth and at high photosynthetic efficiency. Phytoplankton (>5 μm), including dinoflagellates, Trichodesmium, coccolithophores, and dissolved nutrients, are thought to have been correlated with primary production during the study period. The measured on-deck biological data of our study allow for a general understanding of the trends in PP in the survey area of the EIO and can be incorporated into global primary production models.

ABSTRACT Management of crop root rot disease is one of the key factors in ensuring sustainable development in agricultural production. The accumulation of autotoxins and pathogens in soil has been reported as a primary driver of root rot diseases; however, less is known about the correlation of plants, their associated pathogens and microbiome mediated by autotoxins as well as the contributions autotoxins make to the occurrence of root rot disease. Here, we integrated metabolomic, transcriptomic, and rhizosphere microbiome analyses to identify the root cell wall degradants cellobiose and d-galacturonic acid as being induced by the autotoxic ginsenoside Rg1 of Panax notoginseng, and we found that exogenous cellobiose and d-galacturonic acid in addition to Rg1 could aggravate root rot disease by modifying the rhizosphere microbiome. Microorganisms that correlated positively with root rot disease were enriched and those that correlated negatively were suppressed by exogenous cellobiose, d-galacturonic acid, and Rg1. In particular, they promoted the growth and infection of the soilborne pathogen Ilyonectria destructans by upregulating pathogenicity-related genes. Cellobiose showed the highest ability to modify the microbiome and enhance pathogenicity, followed by Rg1 and then d-galacturonic acid. Collectively, autotoxins damaged root systems to release a series of cell wall degradants, some of which modified the rhizosphere microbiome so that the host plant became more susceptible to root rot disease. IMPORTANCE The accumulation of autotoxins and pathogens in soil has been reported as a primary driver of root rot disease and one of the key factors limiting sustainable development in agricultural production. However, less is known about the correlation of plants, their associated pathogens, and the microbiome mediated by autotoxins, as well as the contributions autotoxins make to the occurrence of root rot disease. In our study, we found that autotoxins can damage root systems, thus releasing a series of cell wall degradants, and both autotoxins and the cell wall degradants they induce could aggravate root rot disease by reassembling the rhizosphere microbiome, resulting in the enrichment of pathogens and microorganisms positively related to the disease but the suppression of beneficial microorganisms. Deciphering this mechanism among plants, their associated pathogens, and the microbiome mediated by autotoxins will advance our fundamental knowledge of and ability to degrade autotoxins or employ microbiome to alleviate root rot disease in agricultural systems.

Longitudinal data on patient-reported outcomes (PROs), such as quality of life of patients, are frequently collected in clinical trials and other medical studies. Joint analysis of these data with survival times may improve the accuracy of statistical inferences, especially when PRO measurements may be missing after the death of patients. Classical linear mixed models are often used as the models for the longitudinal measurements in a joint analysis, but it may not be suitable for longitudinal PRO measurements with potential ceiling and floor effects caused by a large portion of patients who report either a maximum or minimum score. In this paper, we introduce a new joint model that uses a longitudinal Tobit model for the longitudinal outcomes with potential ceiling and floor effects and a Cox proportional hazard model for survival time with a random effect connecting these two models. An estimation procedure based on the partial likelihood and Laplace approximation is developed to estimate the parameters in both models, and a random weighting method is proposed to calculate the variances of these parameter estimators. Performances of the proposed procedures are evaluated through simulation studies and an application to the analysis of quality of life data from a clinical trial. [ABSTRACT FROM AUTHOR]