Stochastic Optimization of Areas UnderPrecision-Recall Curves with Provable Convergence

Areas under ROC (AUROC) and precision-recall curves (AUPRC) are common metrics for evaluating classification performance for imbalanced problems. Compared with AUROC, AUPRC is a more appropriate metric for highly imbalanced datasets. While stochastic optimization of AUROC has been studied extensively, principled stochastic optimization of AUPRC has been rarely explored. In this work, we propose a principled technical method to optimize AUPRC for deep learning. Our approach is based on maximizing the averaged precision (AP), which is an unbiased point estimator of AUPRC. We cast the objective into a sum of {\it dependent compositional functions} with inner functions dependent on random variables of the outer level. We propose efficient adaptive and non-adaptive stochastic algorithms named SOAP with {\it provable convergence guarantee under mild conditions} by leveraging recent advances in stochastic compositional optimization. Extensive experimental results on image and graph datasets demonstrate that our proposed method outperforms prior methods on imbalanced problems in terms of AUPRC. To the best of our knowledge, our work represents the first attempt to optimize AUPRC with provable convergence. The SOAP has been implemented in the libAUC library at~\url{https://libauc.org/}.Comment: 24 pages, 10 figure

Detecting the Thermal Properties of Bone Cement by Temperature Sensor

Polymethylmethacrylate-based (PMMA) bone cements containing functionalized carbon nanotubes (CNTs) were prepared, and the thermal properties of the resultant nanocomposite cements were characterized in accordance with the international standard for acrylic resin cements. The aim of this study was to determine the peak temperatures during the polymerization reaction in PMMA bone cement by thermocouple (temperature sensor). The CNTs were uniformly dispersed in the cement matrix. The setting time of the cement increased and the maximum temperature during exothermic polymerization reaction was effectively reduced by the incorporation of functionalized CNTs. This reduction decreased thermal necrosis of the respective nanocomposite cements, which probably could reduce the hyperthermia experienced in vivo

Design and application of a novel 3D printing digital navigation template for cubitus varus deformity in children

BackgroundThis study was aimed to assess the feasibility and efficacy of 3D printing digital template for treatment of cubitus varus deformity.Methods32 patients who underwent lateral closing osteotomy were evaluated between January 2018 and January 2020 in this retrospective study. Navigation templates were used in 17 cases, while conventional surgery in 15 cases. The carrying angles before and after surgery, operation time and elbow joint function were compared.ResultsNavigation templates matched well with the anatomical markers of the lateral humerus. More accurate osteotomy degrees, shorter operation time and less radiation exposure were achieved in the navigation template group (p < 0.05). At the last follow-up time, significant difference was found based on the Bellemore criteria (p = 0.0288).ConclusionsThe novel navigation template can shorten operation time, improve the lateral closing osteotomy accuracy and improve postoperative elbow joint function

Highly strained, radially π-conjugated porphyrinylene nanohoops

Small π-conjugated nanohoops are difficult to prepare, but offer an excellent platform for studying the interplay between strain and optoelectronic properties, and, increasingly, these shape-persistent macrocycles find uses in host-guest chemistry and self-assembly. We report the synthesis of a new family of radially π-conjugated porphyrinylene/phenylene nanohoops. The strain energy in the smallest nanohoop [2]CPT is approximately 54 kcal mol⁻¹, which results in a narrowed HOMO-LUMO gap and a red shift in the visible part of the absorption spectrum. Because of its high degree of preorganization and a diameter of ca. 13 Å, [2]CPT was found to accommodate C₆₀ with a binding affinity exceeding 10⁸ M⁻¹ despite the fullerene not fully entering the cavity of the host (X-ray crystallography). Moreover, the ?-extended nanohoops [2]CPTN, [3]CPTN, and [3]CPTA (N for 1,4-naphthyl; A for 9,10-anthracenyl) have been prepared using the same strategy, and [2]CPTN has been shown to bind C₇₀ 5 times more strongly than [2]CPT. Our failed synthesis of [2]CPTA highlights a limitation of the experimental approach most commonly used to prepare strained nanohoops, because in this particular case the sum of aromatization energies no longer outweighs the buildup of ring strain in the final reaction step (DFT calculations). These results indicate that forcing ring strain onto organic semiconductors is a viable strategy to fundamentally influence both optoelectronic and supramolecular properties

Integration of cognitive tasks into artificial general intelligence test for large models

During the evolution of large models, performance evaluation is necessarily performed to assess their capabilities and ensure safety before practical application. However, current model evaluations mainly rely on specific tasks and datasets, lacking a united framework for assessing the multidimensional intelligence of large models. In this perspective, we advocate for a comprehensive framework of cognitive science-inspired artificial general intelligence (AGI) tests, aimed at fulfilling the testing needs of large models with enhanced capabilities. The cognitive science-inspired AGI tests encompass the full spectrum of intelligence facets, including crystallized intelligence, fluid intelligence, social intelligence, and embodied intelligence. To assess the multidimensional intelligence of large models, the AGI tests consist of a battery of well-designed cognitive tests adopted from human intelligence tests, and then naturally encapsulates into an immersive virtual community. We propose increasing the complexity of AGI testing tasks commensurate with advancements in large models and emphasizing the necessity for the interpretation of test results to avoid false negatives and false positives. We believe that cognitive science-inspired AGI tests will effectively guide the targeted improvement of large models in specific dimensions of intelligence and accelerate the integration of large models into human society

KARR-seq reveals cellular higher-order RNA structures and RNA–RNA interactions

RNA fate and function are affected by their structures and interactomes. However, how RNA and RNA-binding proteins (RBPs) assemble into higher-order structures and how RNA molecules may interact with each other to facilitate functions remain largely unknown. Here we present KARR-seq, which uses N3-kethoxal labeling and multifunctional chemical crosslinkers to covalently trap and determine RNA–RNA interactions and higher-order RNA structures inside cells, independent of local protein binding to RNA. KARR-seq depicts higher-order RNA structure and detects widespread intermolecular RNA–RNA interactions with high sensitivity and accuracy. Using KARR-seq, we show that translation represses mRNA compaction under native and stress conditions. We determined the higher-order RNA structures of respiratory syncytial virus (RSV) and vesicular stomatitis virus (VSV) and identified RNA–RNA interactions between the viruses and the host RNAs that potentially regulate viral replication

H+-pyrophosphatases enhance low nitrogen stress tolerance in transgenic Arabidopsis and wheat by interacting with a receptor-like protein kinase

IntroductionNitrogen is a major abiotic stress that affects plant productivity. Previous studies have shown that plant H+-pyrophosphatases (H+-PPases) enhance plant resistance to low nitrogen stress. However, the molecular mechanism underlying H+-PPase-mediated regulation of plant responses to low nitrogen stress is still unknown. In this study, we aimed to investigate the regulatory mechanism of AtAVP1 in response to low nitrogen stress.Methods and ResultsAtAVP1 in Arabidopsis thaliana and EdVP1 in Elymus dahuricus belong to the H+-PPase gene family. In this study, we found that AtAVP1 overexpression was more tolerant to low nitrogen stress than was wild type (WT), whereas the avp1-1 mutant was less tolerant to low nitrogen stress than WT. Plant height, root length, aboveground fresh and dry weights, and underground fresh and dry weights of EdVP1 overexpression wheat were considerably higher than those of SHI366 under low nitrogen treatment during the seedling stage. Two consecutive years of low nitrogen tolerance experiments in the field showed that grain yield and number of grains per spike of EdVP1 overexpression wheat were increased compared to those in SHI366, which indicated that EdVP1 conferred low nitrogen stress tolerance in the field. Furthermore, we screened interaction proteins in Arabidopsis; subcellular localization analysis demonstrated that AtAVP1 and Arabidopsis thaliana receptor-like protein kinase (AtRLK) were located on the plasma membrane. Yeast two-hybrid and luciferase complementary imaging assays showed that the AtRLK interacted with AtAVP1. Under low nitrogen stress, the Arabidopsis mutants rlk and avp1-1 had the same phenotypes.DiscussionThese results indicate that AtAVP1 regulates low nitrogen stress responses by interacting with AtRLK, which provides a novel insight into the regulatory pathway related to H+-pyrophosphatase function in plants

An Experimental Study on the Establishment of Pulmonary Hypertension Model in Rats induced by Monocrotaline

Pulmonary hypertension is called PH for short. It is caused by the pulmonary artery vascular disease leading to pulmonary vascular resistance, and the increase right lung compartment load, which resulting in weakening or even collapse of the right ventricular function. The establishment of rat PH model under the action of monocrotaline is a repeatable, simple and accessible operation technique, which has been widely used in the treatment of pulmonary hypertension. This paper discusses the principle and properties of the PH model on rats under the monocrotaline action

Hedyotis diffusa Willd Inhibits Colorectal Cancer Growth in Vivo via Inhibition of STAT3 Signaling Pathway

Signal Transducer and Activator of Transcription 3 (STAT3), a common oncogenic mediator, is constitutively activated in many types of human cancers; therefore it is a major focus in the development of novel anti-cancer agents. Hedyotis diffusa Willd has been used as a major component in several Chinese medicine formulas for the clinical treatment of colorectal cancer (CRC). However, the precise mechanism of its anti-tumor activity remains largely unclear. Using a CRC mouse xenograft model, in the present study we evaluated the effect of the ethanol extract of Hedyotis diffusa Willd (EEHDW) on tumor growth in vivo and investigated the underlying molecular mechanisms. We found that EEHDW reduced tumor volume and tumor weight, but had no effect on body weight gain in CRC mice, demonstrating that EEHDW can inhibit CRC growth in vivo without apparent adverse effect. In addition, EEHDW treatment suppressed STAT3 phosphorylation in tumor tissues, which in turn resulted in the promotion of cancer cell apoptosis and inhibition of proliferation. Moreover, EEHDW treatment altered the expression pattern of several important target genes of the STAT3 signaling pathway, i.e., decreased expression of Cyclin D1, CDK4 and Bcl-2 as well as up-regulated p21 and Bax. These results suggest that suppression of the STAT3 pathway might be one of the mechanisms by which EEHDW treats colorectal cancer