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Abstract: The application of privileged structures in drug design is an effective strategy, which usually leads to innovative hits/leads and successful structural optimization. Pyrrolo[2, 3- d]pyrimidine are such a scaffold which are frequently used in many clinical drugs. The biocompounds bearing pyrrolo[2, 3-d]pyrimidine skeleton show different pharmacological effects such as anti-neurodegenerative, anti-inflammatory, antibacterial, and antitumor activities. In this article, we reviewed the representative structures and biological characteristics of reported synthetic pyrrolo[2, 3-d]pyrimidine compounds from 2017 to 2021. The linked diseases and targets were also mentioned briefly. This work might provide a reference for the subsequent drug discovery based on pyrrolo[2, 3-d]pyrimidine scaffold.

As a tissue conductivity imaging method, magneto-acousto-electric tomography (MAET) has the advantage of high axial spatial resolution compared with traditional electrical impedance imaging methods. However, it has the problems of difficulty in imaging targets with irregular conductivity distribution and poor lateral spatial resolution. Although the rotation-based MAET method can partly solve the irregular target problem, there is still a poor imaging signal-to-noise ratio (SNR) problem. Our previous study established a framework of an innovative MAET method, which has a very similar imaging theory and reconstruction algorithm to those of computed tomography (CT). Therefore, we name the method magneto-acoustic-electric computed tomography (MAE-CT). This paper proposes an improved implementation of MAE-CT based on multi-angle plane wave excitation. This method combines the electronic steering of the linear array transducer with the mechanical rotation to increase the number of projection angles while keeping the imaging complexity. In this study, we first established a finite element simulation model to verify the method's feasibility. Then phantom experiments were conducted to systematically investigate the performance of the proposed method. Finally, in vitro liver tissue experiment was conducted to further explore the feasibility of the method. The experimental results show that our method improves both the SNR and spatial resolution of the reconstructed image. For the phantom results, this method can detect conductivity of 0.67 S/m in an area with a size of 2 mm. To the best of our knowledge, this is the best result of spatial resolution available for MAET.

Cell-free DNA (cfDNA) analysis holds promise for early detection of lung cancer and benefits patients with higher survival. However, the detection sensitivity of previous cfDNA-based studies was still low to suffice the clinical use, especially for early-stage tumors.Establish an accurate and affordable approach for early-stage lung cancer detection by integrating cfDNA fragmentomics and machine learning models.This study included 350 non-cancer and 432 cancer participants. The participants' plasma cfDNA samples were profiled by whole-genome sequencing. Multiple cfDNA features and machine learning models were compared in the training cohort to achieve an optimal model. Model performance was evaluated in three validation cohorts.A stacked ensemble model integrating five cfDNA features and five machine learning algorithms constructed in the training cohort (cancer: 113, healthy: 113) outperformed all the models built on individual feature-algorithm combinations. This integrated model yielded superior sensitivities of 91.4% at 95.7% specificity for Cohort Validation I [Area Under the Curve (AUC): 0.984], 84.7% at 98.6% specificity for Validation II (AUC: 0.987), and 92.5% at 94.2% specificity for Additional Validation (AUC: 0.974), respectively. The model's high performance remained consistent when sequencing depth was down to 0.5× (AUC: 0.966-0.971). Furthermore, our model is sensitive to identifying early pathological features (83.2% sensitivity for stage I, 85.0% sensitivity for1cm tumor at the 0.66 cutoff).We have established a stacked ensemble model using cfDNA fragmentomics features and achieved superior sensitivity for detecting early-stage lung cancer, which could promote early diagnosis and benefit more patients. This article is open access and distributed under the terms of the Creative Commons Attribution Non-Commercial No Derivatives License 4.0 (http://creativecommons.org/licenses/by-nc-nd/4.0/).

This work gives a blind beamforming strategy for intelligent reflecting surface (IRS), aiming to boost the received signal-to-noise ratio (SNR) by coordinating phase shifts across reflective elements in the absence of channel information. While the existing methods of IRS beamforming typically first estimate channels and then optimize phase shifts, we propose a conditional sample mean based statistical approach that explores the wireless environment via random sampling without performing any channel estimation. Remarkably, the new method just requires a polynomial number of random samples to yield an SNR boost that is quadratic in the number of reflective elements, whereas the standard random-max sampling algorithm can only achieve a linear boost under the same condition. Moreover, we gain additional insight into blind beamforming by interpreting it as a least squares problem. Field tests demonstrate the significant advantages of the proposed blind beamforming algorithm over the benchmark algorithms in enhancing wireless transmission., Comment: 16 pages, 15 figures

Guiding enterprises to carry out green innovation and accelerating the forging of new competitive advantages in green industry has become an important direction of national innovation after the top 20. Based on the panel data of A-share non-financial listed companies from 2015 to 2020, this paper empirically examines the impact of vertical concurrent executive positions on corporate green innovation. The results show that the vertical concurrent position of senior executives significantly improves the degree of green innovation of enterprises. The vertical concurrent position of senior executives can effectively play the supervision function of major shareholders, improve the efficiency of resource allocation, and promote the green innovation behavior of enterprises. This result held up after a series of robustness tests. Therefore, more explicit regulations should be introduced for the vertical part-time system of senior executives of listed companies, so as to guide enterprises to establish a reasonable and efficient vertical part-time system of senior executives and improve the degree of green innovation of enterprises.

The past decades have witnessed a mounting research attention on the authorial stance in academic discourse. Examining the use of stance features has become a key focus to explore the interactive and persuasive nature of academic writing. This review article aims to sort out the research development of authorial stance to figure out the important factors in stance making, which has some academic reference value for future research on how EFL writers project themselves in academic writing.

Type 2 diabetes mellitus (T2DM) is a chronic progressive metabolic disease that has become a growing health problem worldwide, and the dangers of hyperglycemia and its chronic complications have long been considered a goal of diabetes treatment. In recent years, tirzepatide has become the first dual GIP/GLP-1R agonist approved for the treatment of diabetes mellitus in the United States as a new hypoglycemic medicine. Its hypoglycaemic and weight loss effects have been demonstrated in several large clinical trials, and there is also evidence that it has great potential for cardiovascular protection. In addition, the very concept of synthetic peptides opens up many unknown possibilities for tirzepatide. Ongoing trials (NCT04166773) and evidence suggest that it appears to be a promising drug in the areas of NAFLD, renal, and neuroprotection. Based on preclinical studies and clinical trials, the aim of this article is to discuss the latest clinical developments in tirzepatide, to focus on its differences with other incretin therapies, and to suggest future possibilities and mechanisms of tirzepatide therapy.

BACKGROUND: Abdominal or back pain is a common symptom in pancreatic diseases. However, the role of pain in pancreatic neuroendocrine neoplasm (PNENs) has not been clarified. OBJECTIVE: In this study, we aimed to show the association between the pain and the grade of PNENs. METHODS: A total of 186 patients with pathologically confirmed PNENs were included in this study. Clinical features and histological or radiological findings (size, location, and vascular invasion and local organs invasion and distal metastasis) were collected. Logistic regression analyses were used to show the association between pain and grade of PNENs. Nomogram was developed based on associated factors to predict the higher grade of PNENs. Receiver operating characteristic (ROC) curve was used to evaluate the diagnostic performance of size and nomogram model. RESULTS: The prevalence of pain in the cohort was 30.6% (n= 57). The vascular invasion and G3 PNENs were more common in the pain group (P= 0.02, P< 0.01). The tumor size was larger and incident of higher grade of PNENs was higher in the pain group than the non-pain group (p< 0.01). Age, pain and size were independent risk factors for G2/G3 or G3 PNENs. The odds ratio was 3.03 (95% CI: 1.67–7.91) and 3.32 (95% CI: 1.42–7.79) for pain, respectively. The nomogram model was developed to predict the G2/G3 or G3 PNENs. The area under the curve (AUC) of the nomogram model was 0.84 (95% CI, 0.77–0.91) in predicting the G2/G3 PNENs, and was 0.84 (95% CI, 0.78–0.91) in predicting the G3 PNENs. CONCLUSION: Abdominal or back pain is associated with the grade of PNENs. The nomograms based on clinical features may be a powerful numerical tool for predicting the grade of PNENs.

Compound-specific hydrogen isotopes have increasingly been used as a powerful proxy for investigating biogeochemical cycles and climate change over the past 2 decades. Understanding the hydrogen isotope in extant organisms is fundamental for us to interpret such isotope signals preserved in natural environmental samples. Here, we studied the controls on hydrogen isotope fractionation between fatty acids and growth water by an Fe-reducing heterotrophic marine bacterium Shewanella piezotolerans WP3 growing on different organic substrates, including N-acetyl-D-glucosamine (GlcNac), glucose, acetate, pyruvate, L-alanine, and L-glutamate. Meanwhile, we also evaluated the impact of growth temperature on the hydrogen isotope composition of fatty acids using GlcNac as the sole organic substrate. Our results show that the abundance-weighted mean fatty-acid / water fractionations (εFA/water) display considerable variations for cultures grown on different substrates. Specifically, WP3 yielded the most 2H-enriched fatty acids growing on L-glutamate and pyruvate with an εFA/water of 52 ± 14 ‰ and 44 ± 4 ‰, respectively, and exhibited 2H depletion using GlcNac (−76 ± 1 ‰) and glucose (−67 ± 35 ‰) as sole carbon sources and relatively small fractionations on acetate (23 ± 3 ‰) and L-alanine (−4 ± 9 ‰). Combined with metabolic model analysis, our results indicate that the central metabolic pathways exert a fundamental effect on the hydrogen isotope composition of fatty acids in heterotrophs. Temperature also has an obvious influence on the δ2H values of fatty acids, with strong 2H depletion at an optimal growth temperature (−23 ± 2 ‰ and −23 ‰ growing at 15 and 20 ∘C, respectively) and relatively small fractionations at non-optimal temperatures (4 ± 5 ‰, −4 ± 12 ‰, and 15 ± 41 ‰ at 4, 10, and 25 ∘C, respectively). We hypothesized that this may be associated with temperature-induced enzyme activity for nicotinamide adenine dinucleotide phosphate (NADPH) production. This study helps understand the controlling factors of hydrogen isotope fractionation by marine bacteria, laying the foundation for further interpreting the hydrogen isotope signatures of lipids as an important proxy to decode the biogeochemical cycles and ecological changes in marine sediments.