Two cytosolic glutamine synthetase isoforms play specific roles for seed germination and seed yield structure in <i>Arabidopsis</i>

Nitrogen (N) remobilization from reserves to sinks is essential for seedling establishment and seed production. Cytosolic glutamine synthetase (GS1) is up-regulated during both seed germination and seed filling in plants. However, the specific roles of the individual GS1 isogenes with respect to N remobilization, early seedling vigour, and final seed productivity are not known. In this study, impairment of seed germination and seedling establishment is demonstrated in the single knockout mutant gln1;2, and the double knockout mutant gln1;1:gln1;2. The negative effect of Gln1;2 deficiency was associated with reduced N remobilization from the cotyledons and could be fully alleviated by exogenous N supply. Following reproductive growth, both the single and double Gln1;2-knockout mutants showed decreased seed yield due to fewer siliques, less seeds per silique, and lower dry weight per seed. The gln1;1 single mutant had normal seed yield structure but primary root development during seed germination was reduced in the presence of external N. Gln1;2 promoter–green fluorescent protein constructs showed that Gln1;2 localizes to the vascular cells of roots, petals, and stamens. It is concluded that Gln1;2 plays an important role in N remobilization for both seedling establishment and seed production in Arabidopsis

Lung cancer gene expression database analysis incorporating prior knowledge with support vector machine-based classification method

<p>Abstract</p> <p>Background</p> <p>A reliable and precise classification is essential for successful diagnosis and treatment of cancer. Gene expression microarrays have provided the high-throughput platform to discover genomic biomarkers for cancer diagnosis and prognosis. Rational use of the available bioinformation can not only effectively remove or suppress noise in gene chips, but also avoid one-sided results of separate experiment. However, only some studies have been aware of the importance of prior information in cancer classification.</p> <p>Methods</p> <p>Together with the application of support vector machine as the discriminant approach, we proposed one modified method that incorporated prior knowledge into cancer classification based on gene expression data to improve accuracy. A public well-known dataset, Malignant pleural mesothelioma and lung adenocarcinoma gene expression database, was used in this study. Prior knowledge is viewed here as a means of directing the classifier using known lung adenocarcinoma related genes. The procedures were performed by software R 2.80.</p> <p>Results</p> <p>The modified method performed better after incorporating prior knowledge. Accuracy of the modified method improved from 98.86% to 100% in training set and from 98.51% to 99.06% in test set. The standard deviations of the modified method decreased from 0.26% to 0 in training set and from 3.04% to 2.10% in test set.</p> <p>Conclusion</p> <p>The method that incorporates prior knowledge into discriminant analysis could effectively improve the capacity and reduce the impact of noise. This idea may have good future not only in practice but also in methodology.</p

Language Embedded 3D Gaussians for Open-Vocabulary Scene Understanding

Open-vocabulary querying in 3D space is challenging but essential for scene understanding tasks such as object localization and segmentation. Language-embedded scene representations have made progress by incorporating language features into 3D spaces. However, their efficacy heavily depends on neural networks that are resource-intensive in training and rendering. Although recent 3D Gaussians offer efficient and high-quality novel view synthesis, directly embedding language features in them leads to prohibitive memory usage and decreased performance. In this work, we introduce Language Embedded 3D Gaussians, a novel scene representation for open-vocabulary query tasks. Instead of embedding high-dimensional raw semantic features on 3D Gaussians, we propose a dedicated quantization scheme that drastically alleviates the memory requirement, and a novel embedding procedure that achieves smoother yet high accuracy query, countering the multi-view feature inconsistencies and the high-frequency inductive bias in point-based representations. Our comprehensive experiments show that our representation achieves the best visual quality and language querying accuracy across current language-embedded representations, while maintaining real-time rendering frame rates on a single desktop GPU

Effects of domestic cooking process on the chemical and biological properties of dietary phytochemicals

peer-reviewedFoods are good sources of vitamins, minerals and dietary fibers as well as phytochemicals, which are beneficial for the human body as nutritional supplements. The nutritional value (crude fibers, crude proteins, crude fats, flavonols, carotenoids, polyphenols, glucosinolate, chlorophyll, and ascorbic acid) and biological or functional properties (antioxidant activity, anticancer activity, or anti-mutagenic activity) of foods can be well retained and protected with the appropriate cooking methods. The chemical, physical and enzyme modifications that occur during cooking will alter the dietary phytochemical antioxidant capacity and digestibility. This paper reviewed the recent advances on the effects of domestic cooking process on the chemical and biological properties of dietary phytochemicals. Furthermore, the possible mechanisms underlying these changes were discussed, and additional implications and future research goals were suggested. The domestic cooking process for improving the palatability of foods and increasing the bioavailability of nutrients and bioactive phytochemicals has been well supported

Efficacy and safety of teneligliptin in patients with type 2 diabetes mellitus: a Bayesian network meta-analysis

BackgroundAs a popular antidiabetic drug, teneligliptin has been used for over 10 years, but its efficacy and safety have rarely been systematically evaluated. Therefore, a Bayesian network meta-analysis was conducted to evaluate the efficacy and safety of teneligliptin in patients with type 2 diabetes mellitus (T2DM).MethodsWe systematically searched PubMed, Web of Science, Embase, Cochrane Central Register of Controlled Trials, and ClinicalTrials.gov. Randomized controlled trials (RCTs) comparing teneligliptin with placebo or active comparators in T2DM patients for at least 12 weeks were included in the study. Data analysis was performed using R 4.2.3 and Stata 17.0 software. Each outcome was presented as a mean difference (MD) or an odds ratio (OR) along with 95% confidence interval (CI) and the surface under the cumulative ranking curve value (SUCRA).ResultsA total of 18 RCTs with 3,290 participants with T2DM were included in this study. Generally, compared to placebo, sitagliptin, vildagliptin, metformin, and bromocriptine, 20 mg of teneligliptin showed better efficacy in reducing HbA1c (MD [95% CI], −0.78 [−0.86 to −0.70], −0.08 [−0.36 to 0.19], −0.04 [−0.72 to 0.60], −0.12 [−0.65 to 0.42], and −0.50 [−0.74 to −0.26], respectively) and fasting plasma glucose (FPG) (MD [95% CI], −18.02 [−20.64 to −15.13], 1.17 [−9.39 to 11.70], −8.06 [−30.95 to 14.35], −2.75 [−18.89 to 13.01], and −34.23 [−45.93 to −22.96], respectively), and 40 mg of teneligliptin also showed better efficacy in reducing HbA1c (MD [95% CI], −0.84 [−1.03 to −0.65], −0.15 [−0.49 to 0.19], −0.10 [−0.81 to 0.57], −0.18 [−0.76 to 0.39], and −0.56 [−0.88 to −0.26], respectively) and FPG (MD [95% CI], −20.40 [−26.07 to −14.57], −1.20 [−13.21 to 10.38], −10.43 [−34.16 to 12.65], −5.13 [−22.21 to 11.66], and −36.61 [−49.33 to −24.01], respectively). Compared to placebo, 20 mg of teneligliptin showed no significant difference in incidences of hypoglycemia and gastrointestinal adverse events (OR [95% CI], 1.30 [0.70 to 2.19] and 1.48 [0.78 to 2.98], respectively), and 40 mg of teneligliptin showed no significant difference in incidence of hypoglycemia (OR [95% CI], 2.63 [0.46 to 8.10]). Generally, antidiabetic effect and hypoglycemia risk of teneligliptin gradually increased as its dose increased from 5 mg to 40 mg. Compared to 20 mg of teneligliptin, 40 mg of teneligliptin showed superior efficacy and no-inferior safety, which was considered as the best option in reducing HbA1c, FPG, and 2h PPG and increasing proportion of the patients achieving HbA1c &lt; 7% (SUCRA, 85.51%, 84.24%, 79.06%, and 85.81%, respectively) among all the included interventions.ConclusionCompared to sitagliptin, vildagliptin, metformin, bromocriptine, and placebo, teneligliptin displayed favorable efficacy and acceptable safety in treating T2DM. Twenty milligrams or 40 mg per day was the optimal dosage regimen of teneligliptin. The results of this study will provide important evidence-based basis for rational use of teneligliptin and clinical decision-making of T2DM medication