Floral adaptation to local pollinator guilds in a terrestrial orchid

Background and Aims Studies of local floral adaptation in response to geographically divergent pollinators are essential for understanding floral evolution. This study investigated local pollinator adaptation and variation in floral traits in the rewarding orchid Gymnadenia odoratissima, which spans a large altitudinal gradient and thus may depend on different pollinator guilds along this gradient. Methods Pollinator communities were assessed and reciprocal transfer experiments were performed between lowland and mountain populations. Differences in floral traits were characterized by measuring floral morphology traits, scent composition, colour and nectar sugar content in lowland and mountain populations. Key Results The composition of pollinator communities differed considerably between lowland and mountain populations; flies were only found as pollinators in mountain populations. The reciprocal transfer experiments showed that when lowland plants were transferred to mountain habitats, their reproductive success did not change significantly. However, when mountain plants were moved to the lowlands, their reproductive success decreased significantly. Transfers between populations of the same altitude did not lead to significant changes in reproductive success, disproving the potential for population-specific adaptations. Flower size of lowland plants was greater than for mountain flowers. Lowland plants also had significantly higher relative amounts of aromatic floral volatiles, while the mountain plants had higher relative amounts of other floral volatiles. The floral colour of mountain flowers was significantly lighter compared with the lowland flowers. Conclusions Local pollinator adaptation through pollinator attraction was shown in the mountain populations, possibly due to adaptation to pollinating flies. The mountain plants were also observed to receive pollination from a greater diversity of pollinators than the lowland plants. The different floral phenotypes of the altitudinal regions are likely to be the consequence of adaptations to local pollinator guild

Investigation of relaxation factor in landweber iterative algorithm for electrical capacitance tomography

It is crucial to select a suitable relaxation factor in iterative image reconstruction algorithms (e.g. Landweber iterative algorithm) for electrical capacitance tomography (ECT) because it affects the convergence. By simulation, it is found notably that the relaxation factor should be selected adaptively according to the sensor structure (e.g. the number of electrodes) and the permittivity distribution in capacitance measurements. With different number of electrodes and four typical permittivity distributions, the relaxation factor and the related convergence are investigated in consideration of the change in relative image error. It is shown that the relaxation factor can be chosen based on the upper boundary of all relaxation factors. The conclusions in this paper can be used for practical industrial processes, regarding the adaptive selection of relaxation factor and the number of iterations needed

Dynamic Sparse Training via Balancing the Exploration-Exploitation Trade-off

Over-parameterization of deep neural networks (DNNs) has shown high prediction accuracy for many applications. Although effective, the large number of parameters hinders its popularity on resource-limited devices and has an outsize environmental impact. Sparse training (using a fixed number of nonzero weights in each iteration) could significantly mitigate the training costs by reducing the model size. However, existing sparse training methods mainly use either random-based or greedy-based drop-and-grow strategies, resulting in local minimal and low accuracy. In this work, we consider the dynamic sparse training as a sparse connectivity search problem and design an exploitation and exploration acquisition function to escape from local optima and saddle points. We further design an acquisition function and provide the theoretical guarantees for the proposed method and clarify its convergence property. Experimental results show that sparse models (up to 98\% sparsity) obtained by our proposed method outperform the SOTA sparse training methods on a wide variety of deep learning tasks. On VGG-19 / CIFAR-100, ResNet-50 / CIFAR-10, ResNet-50 / CIFAR-100, our method has even higher accuracy than dense models. On ResNet-50 / ImageNet, the proposed method has up to 8.2\% accuracy improvement compared to SOTA sparse training methods

Dense Feature Memory Augmented Transformers for COVID-19 Vaccination Search Classification

With the devastating outbreak of COVID-19, vaccines are one of the crucial lines of defense against mass infection in this global pandemic. Given the protection they provide, vaccines are becoming mandatory in certain social and professional settings. This paper presents a classification model for detecting COVID-19 vaccination related search queries, a machine learning model that is used to generate search insights for COVID-19 vaccinations. The proposed method combines and leverages advancements from modern state-of-the-art (SOTA) natural language understanding (NLU) techniques such as pretrained Transformers with traditional dense features. We propose a novel approach of considering dense features as memory tokens that the model can attend to. We show that this new modeling approach enables a significant improvement to the Vaccine Search Insights (VSI) task, improving a strong well-established gradient-boosting baseline by relative +15% improvement in F1 score and +14% in precision.Comment: EMNLP 202

The effect of cyclin D1 (CCND1) G870A-polymorphism on breast cancer risk is modified by oxidative stress among Chinese women in Singapore

Cyclin D1 (CCND1), an intracellular cell-cycle regulatory protein with checkpoint function, can promote cell proliferation or induce growth arrest and apoptosis depending on the cellular context. We hypothesized that the direction of the association between the (CCND1) G870A-polymorphism and breast cancer risk may be modified by dietary and genetic factors influencing the oxidant-antioxidant balance, such as a dietary pattern with a high intake of n-6 fatty acids and a low intake of n-3 fatty acids, or a genetic profile that is deficient in glutathione S-transferases. We tested our hypothesis in a case-control study nested into the Singapore Chinese Health Study, a prospective investigation of diet and cancer in 63 000 Chinese men and women. Genomic DNA collected from 258 incident cases of breast cancer and 670 female cohort controls was examined for CCND1, GSTM1, GSTT1 and GSTP1 genes using fluorogenic 5′-nuclease assay. Unconditional logistic regression models were used to assess the effects with adjustment for potential confounders. All statistical tests were two-sided. The heterozygous CCND1 GA genotype significantly reduced the breast cancer risk in all subjects (OR = 0.67, 95% CI 0.45-0.99) when compared with the GG genotype. The association was restricted to women with a high (above median value) intake level of n-6 fatty acids (OR = 0.51, 95% CI 0.30-0.87), a low (below median value) intake level of the antagonistic marine n-3 fatty acids (OR = 0.54, 95% CI 0.32-0.93) or a total lack of the antioxidative GSTM1 (OR = 0.44, 95% CI 0.25-0.80) or GSTT1 genes (OR = 0.46, 95% CI 0.24-0.87). The effects were consistently stronger in cases with advanced disease. The AA genotype did not affect breast cancer risk. The results of this study are compatible with the hypothesis that the oxidant-antioxidant balance in cells is an important determinant of the direction of the cyclin D1 effect, leading either to cell proliferation or cell deat

The effect of the cyclin D1 (CCND1) A870G polymorphism on colorectal cancer risk is modified by glutathione-S-transferase polymorphisms and isothiocyanate intake in the Singapore Chinese Health Study

Cyclin D1 (CCND1) regulates cellular decision between proliferation and growth arrest. Despite the functional relevance of the CCND1 A870G single nucleotide polymorphism (SNP) published results on its association with colorectal cancer (CRC) were inconsistent. We examined the association between this CCND1 genotype and CRC in the Singapore Chinese Health Study, a prospective investigation of diet and cancer in 63 000 Chinese men and women. We explored the hypothesis that inconsistency regarding the CCND1/CRC association may be attributable to the modifying effect of additional CRC risk factors. Since GSTM1/GSTT1 genotype and dietary isothiocyanate (ITC) intake had previously been identified as CRC risk factors in this cohort, we now explored if they influenced the CCND1/CRC association. In a nested case-control study within the Singapore Cohort, genomic DNA collected from 300 incident CRC cases and 1169 controls was examined for CCND1, GSTM1, GSTT1 and GSTP1 polymorphisms. Unconditional logistic regression was used to assess genotype effects on cancer risk. No main effect of CCND1 was observed, yet the CCND1 effect was influenced by ITC intake and GST genotypes. The presence of at least one CCND1 A-allele was associated with increased risk among low dietary ITC consumers (intake below median value for the cohort) with a high-activity GST profile (≥2 of the 3 GST genotypes classified non-null or high-activity) [odds ratio (OR) = 2.05; 95% confidence interval (CI), 1.10-3.82]. In contrast, the presence of at least one A-allele was associated with a decreased risk among all remaining subjects (OR = 0.56; 0.36-0.86) (P for interaction = 0.01). Recent studies indicate that ITCs inhibit cell proliferation and cause apoptosis through pro-oxidant properties. The results of our current study on CRC and those of our previous breast cancer study are compatible with the notion of oxidative stress in target cells as important determinant of direction and magnitude of the CCND1 effec

Sustained Release of IGF-1 by 3D Mesoporous Scaffolds Promoting Cardiac Stem Cell Migration and Proliferation

Background/Aims: C-kit-positive cardiac stem cells (CSCs) may have potential as a treatment for cardiovascular disease. However, the low survival rates of c-kit-positive CSCs present a major challenge during the transplantation process. Methods: The hierarchical structure of the 3D cell scaffold was characterized by scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), and N2 adsorption-desorption isotherms. Analyses of the proliferation and migration performances of the IGF-1 scaffold on c-kit-positive CSCs were conducted by experiments including QuantiT PicoGreen dsDNA and transwell assays. Results: In this study, we synthesized for the first time a novel hierarchical macro-mesoporous silica material (denoted MS15-c) in a one-pot procedure for the release of insulin-like growth factor-1 (IGF-1) and a three-dimensional (3D) cell scaffold. Both macropores and mesopores were visible in MS15-c and enabled the sustained release of IGF-1, extending its half-life and enhancing CSC proliferation and migration. Proliferation and migration were detected by QuantiT PicoGreen dsDNA and transwell assays, respectively. Moreover, an in vivo experiment was conducted to detect heart function with the addition of MS15-c. The new strategy proposed in this paper may extend the bio-applications of 3D cell scaffolds, thus permitting the sustained release of growth factors and efficient promotion of cell proliferation. Conclusion: This work successfully demonstrated an effective strategy for the construction of MS15-c cell scaffolds with hierarchical macro-mesoporous structures. The macro-mesoporous structures gave cell scaffolds the ability to release a growth factor to facilitate cell growth, while the scaffold structure promoted cell proliferation

Insulin-Like Growth Factor Axis and Risk of Type 2 Diabetes in Women

IGF-I shares structural homology and in vitro metabolic activity with insulin. Laboratory models suggest that IGF-I and its binding proteins IGFBP-1 and IGFBP-2 have potentially beneficial effects on diabetes risk, whereas IGFBP-3 may have adverse effects. We therefore conducted a prospective nested case-control investigation of incident diabetes (n = 742 case subjects matched 1:1 to control subjects) and its associations with IGF-axis protein levels in the Nurses’ Health Study, a cohort of middle-aged women. The median time to diabetes was 9 years. Statistical analyses were adjusted for multiple risk factors, including insulin and C-reactive protein. Diabetes risk was fivefold lower among women with baseline IGFBP-2 levels in the top versus bottom quintile (odds ratio [OR]q5–q1 = 0.17 [95% CI 0.08–0.35]; P trend < 0.0001) and was also negatively associated with IGFBP-1 levels (ORq5–q1 = 0.37 [0.18–0.73]; P trend = 0.0009). IGFBP-3 was positively associated with diabetes (ORq5–q1 = 2.05 [1.20–3.51]; P trend = 0.002). Diabetes was not associated with total IGF-I levels, but free IGF-I and diabetes had a significant association that varied (P interaction = 0.003) by insulin levels above the median (ORq5–q1 = 0.48 [0.26–0.90]; P trend = 0.0001) versus below the median (ORq5–q1 = 2.52 [1.05–6.06]; P trend < 0.05). Thus, this prospective study found strong associations of incident diabetes with baseline levels of three IGFBPs and free IGF-I, consistent with hypotheses that the IGF axis might influence diabetes risk