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Abstract Nucleotide-binding leucine-rich repeat (NLR) disease resistance genes typically confer resistance against races of a single pathogen. Here, we report that Yr87/Lr85, an NLR gene from Aegilops sharonensis and Aegilops longissima, confers resistance against both P. striiformis tritici (Pst) and Puccinia triticina (Pt) that cause stripe and leaf rust, respectively. Yr87/Lr85 confers resistance against Pst and Pt in wheat introgression as well as transgenic lines. Comparative analysis of Yr87/Lr85 and the cloned Triticeae NLR disease resistance genes shows that Yr87/Lr85 contains two distinct LRR domains and that the gene is only found in Ae. sharonensis and Ae. longissima. Allele mining and phylogenetic analysis indicate multiple events of Yr87/Lr85 gene flow between the two species and presence/absence variation explaining the majority of resistance to wheat leaf rust in both species. The confinement of Yr87/Lr85 to Ae. sharonensis and Ae. longissima and the resistance in wheat against Pst and Pt highlight the potential of these species as valuable sources of disease resistance genes for wheat improvement.

Abstract Most C–H bond activations of natural gas alkanes rely on transition metal complexes. Activations by using main-group systems have been reported but required heating or photo-irradiation under high atmospheric pressure with rather low regioselectivity. Here we report that Lewis acid-carbene adducts facilely undergo oxidative additions to C–H bonds of ethane, propane and n-butane with high selectivity under room temperature and atmospheric pressure. The Lewis acids can be moved by the addition of a base and the carbene-derived products can be easily converted into aldehydes. This work offers a route for main-group element compounds to selectively functionalise C–H bonds of natural gas alkanes and other small molecules.

Abstract Recently, multi-modal vision-language foundation models have gained significant attention in the medical field. While these models offer great opportunities, they still face crucial challenges, such as the requirement for fine-grained knowledge understanding in computer-aided diagnosis and the capability of utilizing very limited or even no task-specific labeled data in real-world clinical applications. In this study, we present MaCo, a masked contrastive chest X-ray foundation model that tackles these challenges. MaCo explores masked contrastive learning to simultaneously achieve fine-grained image understanding and zero-shot learning for a variety of medical imaging tasks. It designs a correlation weighting mechanism to adjust the correlation between masked chest X-ray image patches and their corresponding reports, thereby enhancing the model’s representation learning capabilities. To evaluate the performance of MaCo, we conducted extensive experiments using 6 well-known open-source X-ray datasets. The experimental results demonstrate the superiority of MaCo over 10 state-of-the-art approaches across tasks such as classification, segmentation, detection, and phrase grounding. These findings highlight the significant potential of MaCo in advancing a wide range of medical image analysis tasks.

Abstract Type I interferons have been well recognized for their roles in various types of immune cells during tumor immunotherapy. However, their direct effects on tumor cells are less understood. Oxidative phosphorylation is typically latent in tumor cells. Whether oxidative phosphorylation can be targeted for immunotherapy remains unclear. Here, we find that tumor cell responsiveness to type I, but not type II interferons, is essential for CD47-SIRPα blockade immunotherapy in female mice. Mechanistically, type I interferons directly reprogram tumor cell metabolism by activating oxidative phosphorylation for ATP production in an ISG15-dependent manner. ATP extracellular release is also promoted by type I interferons due to enhanced secretory autophagy. Functionally, tumor cells with genetic deficiency in oxidative phosphorylation or autophagy are resistant to CD47-SIRPα blockade. ATP released upon CD47-SIRPα blockade is required for antitumor T cell response induction via P2X7 receptor-mediated dendritic cell activation. Based on this mechanism, combinations with inhibitors of ATP-degrading ectoenzymes, CD39 and CD73, are designed and show synergistic antitumor effects with CD47-SIRPα blockade. Together, these data reveal an important role of type I interferons on tumor cell metabolic reprograming for tumor immunotherapy and provide rational strategies harnessing this mechanism for enhanced efficacy of CD47-SIRPα blockade.

This paper investigates the speed selection mechanism for traveling wave fronts of a reaction-diffusion-advection lattice stream-population model with the Allee effect. First, the asymptotic behaviors of the traveling wave solutions are given. Then, sufficient conditions for the speed determinacy of the traveling wave are successfully obtained by constructing appropriate upper and lower solutions. We examine the model with the reaction term $ f (\psi) = \psi(1-\psi)(1+\rho\psi) $, with $ \rho $ being a nonnegative constant, as a specific example. We give a novel conjecture that there exists a critical value $ \rho_c > 1 $, such that the minimal wave speed is linearly selected if and only if $ \rho\leq\rho_c $. Finally, our speculation is verified by numerical calculations.

SPC25 is associated with unfavorable outcomes in various cancers, but its role in prostate cancer (PRAD) is unclear. More research is needed on glycolysis and ferroptosis targets in PRAD. Bioinformatics tools were used to analyze SPC25 expression disparities. Gene set enrichment analysis (GSEA) identified pathways enriched by SPC25 and its correlation with glycolytic proteins. SPC25 mRNA transcriptional activity was analyzed by quantitative polymerase chain reaction (qPCR), while protein levels of SPC25, glycolytic markers, and ferroptosis markers were assessed using Western blot. CCK-8 was used to evaluate the effects of SPC25 on cell survival. Ferroptosis levels were measured by flow cytometry and assays for Fe 2+ and malondialdehyde (MDA) content. Glycolytic capacity was assessed using glucose uptake assays, lactate tests, and a Seahorse XF analyzer. In PRAD tissues and cells, SPC25 was notably upregulated and correlated with adverse outcomes. It enhanced cancer cell vitality. GSEA showed SPC25’s strong association with ferroptosis and glycolytic pathways, while Pearson correlation analysis indicated a positive relationship between SPC25 and glycolytic proteins. Overexpression of SPC25 in cell lines noticeably curbed the accumulation of lipid reactive oxygen species, MDA formation, and Fe 2+ content, while it augmented the protein expression of ferroptosis markers. SPC25 stimulated an increase in cellular extracellular acidification rate, glucose uptake, and lactate secretion, while it dampened oxygen consumption rate, and this effect could be counteracted by 2-deoxy- d -glucose (2-DG). Conversely, 2-DG mitigated the ferroptosis indicators that were diminished by SPC25 downregulation, including the reduction of ferroptosis marker protein expression. By upregulating glycolysis in PRAD cells, SPC25 suppresses the occurrence of ferroptosis.

Environmental pollution is closely linked to the occurrence and development of cancer. Chemical carcinogens are the most important environmental factors causing cancer in humans. Among them, persistent organic pollutants (POPs) are characterized by their widespread distribution, persistence, and bioaccumulation. Research on the carcinogenic effects of POPs has received considerable attention in recent years. This article reviewed the internal exposure, association with cancer risk, and potential carcinogenic mechanisms of five typical classes of POPs in the environment, including polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), per- and poly-fluoroalkyl substances (PFAS), brominated flame retardants (BFRs), and short-chain chlorinated paraffins (SCCPs). These five types of POPs have distinct carcinogenic mechanisms, including interfering with cell proliferation cycle, altering epigenetic inheritance, promoting oxidative stress, altering energy metabolism, and affecting immune function. The development of cancer is the result of interaction between intrinsic genetic factors and external environmental factors. In addition to focusing on how environmental POPs affect the genetic material of organisms, it is also important to consider their effects on the tumor microenvironment, including tumor immunity and angiogenesis. Understanding these effects is crucial for guiding future efforts in pollution control and precision medicine in cancer treatment.

IntroductionOutcome-based education (OBE) leads to revolutionary change in medical education, but each medical school is acknowledged to develop suited framework based on specific positioning, educational philosophy and expected outcomes.MethodsBased on the graduate outcomes of basic medical education in China released by Working Committee for the Accreditation of Medical Education (WCAME) which officially recognized by World Federation for Medical Education (WFME), Taizhou University re-documented the overall organization of the curriculum and classified the courses as “Crucial, Supporting and Associated (CSA)” categories to connect the graduate outcomes and course objectives.ResultsWe redefined the standard for graduates in Taizhou University Medical School including 34 items in four domains and redesigned the curriculum with 76 courses classified as CSA. Empirical data reveals a substantial improvement in students’ performance on Standardized Competence Test for Clinical Medicine Undergraduates in China (SCTCMU) by implementing the CSA system between 2022 and 2023. Notably, in 2023, Taizhou University’s students achieved pass rates more than 20 percentage points higher than the national average, demonstrating a profound and unprecedented impact.ConclusionThe CSA classification system provides a notably clear and structured framework for categorizing courses based on their direct or indirect relevance to educational objectives, which provides clarity to educators and empowers students with a more purposeful approach to their studies.

Abstract Primary angle closure disease (PACD) is a major cause of blindness worldwide. It has a high prevalence in East Asia, especially in China, which leads to a higher incidence of blindness than open-angle glaucoma. The aim of this study was to directly observe the circumlental space (CLS) in laser peripheral iridotomized eyes with PACD and to determine whether this structure plays a role in the pathogenesis of PACD. Fifty eyes of 50 patients with PACD, who had received laser peripheral iridotomy performed with neodymium:yttrium–aluminum-garnet were recruited from glaucoma clinics from March 2021 to May 2022, including 17 primary angle closure suspect (PACS), 16 primary angle closure (PAC) and 17 primary angle closure glaucoma (PACG). They were classified into two groups based on whether the ciliary process and the crystalline lens equator were in contact using slit-lamp photograph: the attached group and the unattached group. The demographic, clinical characteristics and anterior segment parameters measured from ultrasound biomicroscopy were compared between the attached group and the unattached group. Thirty-three eyes were assigned to the attached group and 17 eyes belonged to the unattached group. In the unattached group, the mean CLS was 0.10 ± 0.07 mm. No significant differences were identified between the different diagnosis groups in age, sex, best-corrected visual acuity, intraocular pressure, white-to-white, axial length, central corneal thickness, anterior chamber depth, flat keratometry, steep keratometry or iridotomy diameter (p > 0.05). The unattached group had shorter trabecular-ciliary process distance (p = 0.021) and larger ciliary process area (p = 0.001) compared with the attached group. Small CLS and its potential effect (partial ciliary block) might be considered as one of the mechanisms of PACD.

Stereo vision technology, as a significant branch of computer vision, has been widely applied in fields such as robot navigation, autonomous driving, and 3D reconstruction. Achieving embodied intelligence through edge hardware platforms remains challenging in balancing power consumption, real-time performance, and accuracy. Although the semi-global stereo matching algorithm has proven effective in balancing disparity map accuracy and computational complexity, its matching accuracy is often limited by weak textures, disparity discontinuities, lighting variations, and noise. To address the limitations of existing semi-global stereo matching algorithms and the power constraints of hardware platforms, this paper proposes a stereo matching algorithm based on FPGA that integrates the Sum of Absolute Differences (SAD) with adaptive Census transform. The goal is to enhance image and edge information and design a compact and efficient stereo vision hardware accelerator. During the hardware implementation phase, a pixel-level pipelined parallel matching cost computation structure is proposed. This structure significantly reduces data buffer requirements through multi-step parallel computation. Additionally, a two-stage four-layer parallel pipelined semi-global cost aggregation architecture is adopted, which effectively balances hardware resource utilization while maintaining accuracy. Evaluations of the Middlebury dataset show that compared to traditional SAD and Census algorithms, the proposed algorithm improves matching accuracy by 15.67% and 15.1%, respectively. On the Xilinx Zynq-7 platform, for images with resolutions of $1280\times 720$ and $640\times 480$ , the processing speeds reach 54.24fps and 81.34fps, respectively.

In this paper, a space-time line code (STLC) is combined with offset spatial modulation (OSM) for reaping both their advantages toward efficient multiple-input multiple-output (MIMO) transmission. Specifically, the spatial diversity offered by STLC increases the resilience against fading channels, while the simplified radio frequency (RF) switching processing merits of OSM inherently are preserved. As a further advancement in the pursuit of enhancing the performance of index detection, angle rotation is conceived and optimized for various transmit conditions. Subsequently, based on the approximation of the Q-function, an upper bound for the average bit error rate (BER) of STLC-OSM is derived in the context of an equispaced (ES) angle arrangement. Eventually, we demonstrate that STLC-OSM achieves considerable BER performance while achieving a unique single RF structure with a low implementation cost. Simulation results confirm the tightness of the derived BER bound and the advantages of the proposed scheme.

Reconfigurable metasurface, also known as Reconfigurable Intelligent Surfaces (RIS), with its flexible beamforming, low-cost, and easy industrial deployment characteristics, presents many interesting solutions in wireless application scenarios. This paper presents a sophisticated reconfigurable metasurface architecture that introduces an advanced concept of flexible full-array space-time wavefront manipulation with enhanced dynamic capabilities. The practical 2-bit phase-shifting unit cell on the RIS is distinguished by its ability to maintain four stable phase states, each with 90° differences, and features an insertion loss of less than 0.6 dB across a bandwidth of 200 MHz. All reconfigurable unit cells are equipped with meticulously designed control circuits, governed by an intelligent core composed of multiple Micro-Controller Units (MCUs), enabling rapid control response across the entire RIS array. Owing to the capability of each unit cell on the metasurface to independently switch states, the entire RIS is not limited to controlling general beams with specific directional patterns but also generates beams with more complex structures, including multi-focus 3D spot beams and vortex beams. This development substantially broadens its applicability across various industrial wireless transmission scenarios. Moreover, by leveraging the rapid-respond space-time coding and the full-array independent programmability of the RIS prototyping operating at 10.7 GHz, we have demonstrated that: 1) The implementation of 3D spot beams scanning facilitates dynamic beam tracking and real-time communication under the indoor near-field scenario; 2) The rapid wavefront rotation of vortex beams enables precise modulation of signals within the Doppler domain, showcasing an innovative approach to wireless signal manipulation; 3) The beam steering experiments for blocking users under outdoor far-field scenarios, verifying the beamforming capability of the RIS board.

Abstract Increasing evidence has shown that the expression of circular RNAs (circRNAs) can affect the drug sensitivity of cells and significantly influence drug efficacy. Therefore, research into the relationships between circRNAs and drugs can be of great significance in increasing the comprehension of circRNAs function, as well as contributing to the discovery of new drugs and the repurposing of existing drugs. However, it is time-consuming and costly to validate the function of circRNA with traditional medical research methods. Therefore, the development of efficient and accurate computational models that can assist in discovering the potential interactions between circRNAs and drugs is urgently needed. In this study, a novel method is proposed, called DHANMKF , that aims to predict potential circRNA-drug sensitivity interactions for further biomedical screening and validation. Firstly, multimodal networks were constructed by DHANMKF using multiple sources of information on circRNAs and drugs. Secondly, comprehensive intra-type and inter-type node representations were learned using bi-typed multi-relational heterogeneous graphs, which are attention-based encoders utilizing a hierarchical process. Thirdly, the multi-kernel fusion method was used to fuse intra-type embedding and inter-type embedding. Finally, the Dual Laplacian Regularized Least Squares method (DLapRLS) was used to predict the potential circRNA-drug sensitivity associations using the combined kernel in circRNA and drug spaces. Compared with the other methods, DHANMKF obtained the highest AUC value on two datasets. Code is available at https://github.com/cuntjx/DHANMKF .

Abstract Prized for their ability to generate chemical complexity rapidly, catalytic carbon–hydrogen (C–H) activation and functionalization reactions have enabled a paradigm shift in the standard logic of synthetic chemistry. Directing group strategies have been used extensively in C–H activation reactions to control regio- and enantioselectivity with transition metal catalysts. However, current methods rely heavily on coordination with nitrogen and/or oxygen atoms in molecules and have therefore been found to exhibit limited generality in asymmetric syntheses. Here, we report enantioselective C–H activation with unsaturated hydrocarbons directed by phosphorus centres to rapidly construct libraries of axially chiral phosphines through dynamic kinetic resolution. High reactivity and enantioselectivity are derived from modular assembly of an iridium catalyst with an endogenous phosphorus atom and an exogenous chiral phosphorus ligand, as confirmed by detailed experimental and computational studies. This reaction mode significantly expands the pool of enantiomerically enriched functional phosphines, some of which have shown excellent efficiency for asymmetric catalysis.

Abstract The increasing body of research has consistently demonstrated the intricate correlation between the human microbiome and human well-being. Microbes can impact the efficacy and toxicity of drugs through various pathways, as well as influence the occurrence and metastasis of tumors. In clinical practice, it is crucial to elucidate the association between microbes and diseases. Although traditional biological experiments accurately identify this association, they are time-consuming, expensive, and susceptible to experimental conditions. Consequently, conducting extensive biological experiments to screen potential microbe-disease associations becomes challenging. The computational methods can solve the above problems well, but the previous computational methods still have the problems of low utilization of node features and the prediction accuracy needs to be improved. To address this issue, we propose the DAEGCNDF model predicting potential associations between microbes and diseases. Our model calculates four similar features for each microbe and disease. These features are fused to obtain a comprehensive feature matrix representing microbes and diseases. Our model first uses the graph convolutional network module to extract low-rank features with graph information of microbes and diseases, and then uses a deep sparse Auto-Encoder to extract high-rank features of microbe-disease pairs, after which the low-rank and high-rank features are spliced to improve the utilization of node features. Finally, Deep Forest was used for microbe-disease potential relationship prediction. The experimental results show that combining low-rank and high-rank features helps to improve the model performance and Deep Forest has better classification performance than the baseline model.

Abstract Background Multidrug resistance in Enterobacteriaceae including resistance to quinolones is rising worldwide. The development of resistance may lead to the emergence of new transmission mechanisms. In this study, the collection of different E. coli was performed from animals and subjected to subsequent procedures including pulsed-field gel electrophoresis, micro-broth dilution method, polymerase chain reaction. Whole genome sequencing of E. coli C3 was performed to detect the affinity, antimicrobial resistance and major carriers of the isolates. Results A total of 66 E. coli were isolated and their antibiotic resistance genes, frequency of horizontal transfer and genetic environment of E. coli C3 were determined. The results showed there were both different and same types in PFGE typing, indicating clonal transmission of E. coli among different animals. The detection of antimicrobial resistance and major antibiotic resistance genes and the plasmid transfer results showed that strains from different sources had high levels of resistance to commonly used clinical antibiotics and could be spread horizontally. Whole-genome sequencing discovered a novel ICE mobile element. Conclusion In summary, the antimicrobial resistance of E. coli in northeast China is a serious issue and there is a risk of antimicrobial resistance transmission. Meanwhile, a novel ICE mobile element appeared in the process of antimicrobial resistance formation.

The residues from selenium-enriched Cardamine violifolia after the extraction of protein were still rich in polysaccharides. Thus, the recovery of selenium polysaccharides (SePSs) was compared using hot water extraction and ultrasonic-assisted extraction techniques. The yield, extraction rate, purity, specific energy consumption, and content of total and organic selenium from different SePS extracts were determined. The results indicated that at conditions of 250 W (ultrasonic power), 30 °C, and a liquid-to-material ratio of 30:1 extracted for 60 min, the yield of SePSs was 3.97 ± 0.07%, the extraction rate was 22.76 ± 0.40%, and the purity was 65.56 ± 0.35%, while the total and organic selenium content was 749.16 ± 6.91 mg/kg and 628.37 ± 5.93 mg/kg, respectively. Compared to traditional hot water extraction, ultrasonic-assisted extraction significantly improves efficiency, reduces energy use, and boosts both total and organic selenium content in the extract. Measurements of particle size, molecular weight, and monosaccharide composition, along with infrared and ultraviolet spectroscopy, revealed that ultrasonic-assisted extraction breaks down long-chain structures, decreases particle size, and changes monosaccharide composition in SePSs, leading to lower molecular weight and reduced dispersity. The unique structure of SePSs, which integrates selenium with polysaccharide groups, results in markedly improved antioxidant activity and reducing power, even at low concentrations, due to the synergistic effects of selenium and polysaccharides. This study establishes a basis for using SePSs in functional foods.

Decoy oligodeoxynucleotides (ODNs) allow targeting undruggable transcription factors, such as STAT3, but their limited potency and lack of delivery methods hampered translation. To overcome these challenges, we conjugated a STAT3-specific decoy to thalidomide, a ligand to cereblon in E3 ubiquitin ligase complex, to generate a proteolysis-targeting chimera (STAT3DPROTAC). STAT3DPROTAC downregulated STAT3 in target cells, but not STAT1 or STAT5. Computational modeling of the STAT3DPROTAC ternary complex predicted two surface lysines, K601 and K626, in STAT3 as potential ubiquitination sites. Accordingly, K601/K626 point mutations in STAT3, as well as proteasome inhibition or cereblon deletion, alleviated STAT3DPROTAC effect. Next, we conjugated STAT3DPROTAC to a CpG oligonucleotide targeting Toll-like receptor 9 (TLR9) to generate myeloid/B cell-selective C-STAT3DPROTAC. Naked C-STAT3DPROTAC was spontaneously internalized by TLR9+ myeloid cells, B cells, and human and mouse lymphoma cells but not by T cells. C-STAT3DPROTAC effectively decreased STAT3 protein levels and also STAT3-regulated target genes critical for lymphoma cell proliferation and/or survival (BCL2L1, CCND2, and MYC). Finally, local C-STAT3DPROTAC administration to human Ly3 lymphoma-bearing mice triggered tumor regression, while control C-STAT3D and C-SCR treatments had limited effects. Our results underscore the feasibility of using a PROTAC strategy for cell-selective, decoy oligonucleotide-based STAT3 targeting of and potentially other tumorigenic transcription factors for cancer therapy.

Background and objective The relationship between quality of life at three months after lung cancer surgery and different surgical approaches is remains unclear. This study aimed to compare the quality of life of patients three months after uniportal and multiportal thoracoscopic lobectomy. Methods Data from patients who underwent lung surgery at the Department of Thoracic Surgery, Sichuan Cancer Hospital between April 2021 and October 2021 were collected. The European Organization for Research and Treatment of Quality of Life Questionnaire-Core 30 (EORTC QLQ-C30) and Quality of Life Questionnaire-Lung Cancer 29 (EORTC QLQ-LC29) were used to collect quality of life data of the patients. Potential confounding factors in the baseline data were included in a multivariate regression model for adjustment, and the quality of life of the two groups three months postoperatively was compared with traditional clinical outcomes. Results A total of 130 lung cancer patients were included, with 57 males (43.8%) and 73 females (56.2%), and an average age of (57.1±9.5) yr. In the baseline data of the two groups, there was a statistical difference in the number of chest drainage tubes placed (P0.05). The multiportal group had longer surgery time (120.0 min vs 85.0 min, P=0.001), postoperative hospital stay (6.0 d vs 4.0 d, P=0.020), and a higher incidence of early ≥ grade 2 complications (39.0% vs 10.1%, P=0.011) compared to the uniportal group. Conclusion Patients undergoing uniportal and multiportal thoracoscopic lobectomy have similar quality of life at three months postoperatively. The uniportal group may have certain advantages in terms of traditional clinical outcome indicators such as operation time, postoperative hospital stay, and early postoperative complications.

Abstract Remote meta selective C–H functionalization of aromatic compounds remains a challenging problem in chemical synthesis. Here, we report an iridium catalyst bearing a bidentate pyridine-pyridone (PY-PYRI) ligand framework that efficiently catalyzes this meta selective borylation reaction. We demonstrate that the developed concept can be employed to introduce a boron functionality at the remote meta position of phenols, phenol containing bioactive and drug molecules, which was an extraordinary challenge. Moreover, we have demonstrated that the method can also be applied for the remote C6 borylation of indole derivatives including tryptophan that was the key synthetic precursor for the total synthesis of Verruculogen and Fumitremorgin A alkaloids. The inspiration of this catalytic concept was started from the O–Si secondary interaction, which by means of several more detailed control experiments and detailed computational investigations revealed that an unprecedented Bpin shift occurs during the transformation of iridium bis(boryl) complex to iridium tris(boryl) complex, which eventually control the remote meta selectivity by means of the dispersion between the designed ligand and steering silane group.

Abstract Oral tongue squamous cell carcinoma (OTSCC) is a malignant tumor. Recently, studies have found that adenylate cyclase 6 (ADCY6) plays a pivotal role in many lethal tumors formation processes. The role of ADCY6 in OTSCC remains unknown. The expression of ADCY6 in OTSCC tissue samples was detected. The clinical significance of ADCY6 in OTSCC was analyzed by statistical methods. OTSCC cell lines were selected to analyze the biological function of ADCY6. Meanwhile, the effect of ADCY6 on the growth of OTSCC in vivo was explored using subcutaneous tumorigenesis assay. WB assay was used to detect the underlying signaling pathway. Cell function recovery test used to investigate the mechanism of ADCY6‐promoting OTSCC malignant biological behavior via Hippo signaling pathway. We report that ADCY6 was obviously downregulated in OTSCC tissue samples and cell lines. Importantly, lower expression of ADCY6 indicates a poorer prognosis in patients with OTSCC, and its expression is significantly correlated with TNM stage and tumor size. Functionally, forced expression of ADCY6 can significantly inhibit the proliferation, migration, invasion, and promote apoptosis of OTSCC cells. Mechanistically, we demonstrated that ADCY6 upregulation impaired Hippo signaling pathway to reduce the malignant biological behavior of OTSCC. Generally, our findings suggest that ADCY6 suppressed Hippo signaling pathway to regulate malignant biological behavior in OTSCC, which provide new cues for further exploring the mechanism of occurrence and development of OTSCC.

Abstract The mechanisms underlying the transformation of chronic myeloid leukemia (CML) from chronic phase (CP) to blast crisis (BC) are not fully elucidated. Here, we show lower levels of miR-142 in CD34+CD38− blasts from BC CML patients than in those from CP CML patients, suggesting that miR-142 deficit is implicated in BC evolution. Thus, we create miR-142 knockout CML (i.e., miR-142 −/− BCR-ABL) mice, which develop BC and die sooner than miR-142 wt CML (i.e., miR-142 +/+ BCR-ABL) mice, which instead remain in CP CML. Leukemic stem cells (LSCs) from miR-142 −/− BCR-ABL mice recapitulate the BC phenotype in congenic recipients, supporting LSC transformation by miR-142 deficit. State-transition and mutual information analyses of “bulk” and single cell RNA-seq data, metabolomic profiling and functional metabolic assays identify enhanced fatty acid β-oxidation, oxidative phosphorylation and mitochondrial fusion in LSCs as key steps in miR-142-driven BC evolution. A synthetic CpG-miR-142 mimic oligodeoxynucleotide rescues the BC phenotype in miR-142 −/− BCR-ABL mice and patient-derived xenografts.

Sulfide organics and phenols are ubiquitous in freshwater lakes all over the world. As two taste and odor (T and O) compounds, they are harmful to the environment and human body. The existing detection methods for T and O compounds mainly include sensory analysis and gas-phase mass spectrometry, which are cumbersome and time-consuming. Herein, a method for the simultaneous and rapid detection of two T and O compounds (methyl sulfide and 2,4-di-tert-butylphenol) based on surface-enhanced Raman spectroscopy (SERS) is firstly developed. The SERS substrate was prepared by coating Ag nanoparticles (Ag NPs), layered double hydroxide (LDH), and graphene oxide (GO) on the surface of an Ag-coated Au nanoparticle (Au@Ag NP) substrate. Under optimal conditions, this SERS substrate possessed low detection limits of 1.53 ppm for methyl sulfide and 0.39 ppm for 2,4-di-tert-butylphenol. In addition, it took only 20 min to complete the detection using this method, without complex sample pretreatment. Furthermore, it was successfully applied to simultaneously detect methyl sulfide and 2,4-di-tert-butylphenol in actual water samples and had good application prospects for the rapid detection of T and O compounds in water.

This paper delves into enhancing the performance of ScAlN-based Piezoelectric Micromachined Ultrasonic Transducers (PMUTs) through the implementation of Polydimethylsiloxane (PDMS) acoustic lenses. The PMUT, encapsulated in PDMS, underwent thorough characterization through the utilization of an industry-standard hydrophone calibration instrument. The experimental results showed that the ScAlN-based PMUT with the PDMS lenses achieved an impressive sensitivity of −160 dB (re: 1 V/μPa), an improvement of more than 8 dB compared to the PMUT with an equivalent PDMS film. There was a noticeable improvement in the −3 dB main lobe width within the frequency response when comparing the PMUT with PDMS encapsulation, both with and without lenses. The successful fabrication of high-performance PDMS lenses proved instrumental in significantly boosting the sensitivity of the PMUT. Comprehensive performance evaluations underscored that the designed PMUT in this investigation surpassed its counterparts reported in the literature and commercially available transducers. This encouraging outcome emphasizes its substantial potential for commercial applications.

Systemic lupus erythematosus (SLE) is a debilitating autoimmune disorder characterized by unknown pathogenesis and heterogeneous clinical manifestations. The current existing serum biomarkers for SLE have limited sensitivity or specificity, making early and precise diagnosis difficult. Here, we identified two N-glycans on serum immunoglobulin G (IgG) as excellent diagnostic biomarkers for SLE based on in-depth glycomic analyses of 389 SLE patients and 304 healthy controls. These two N-glycan biomarkers are specific for diagnosing SLE, as no significant changes in these biomarkers were observed in other systemic autoimmune diseases that are easily confused with SLE, such as rheumatoid arthritis, primary Sjögren’s syndrome, or systemic sclerosis. Notably, the two N-glycan biomarkers proved to be autoantibody-independent and all-stage patient suitable. The two N-glycan biomarkers are demonstrated to be located on the Fc region based on fragment-specific glycan analysis and glycopeptide analysis, suggesting their close correlation with disease activity. Enzyme analyses revealed dysregulation of a series of glycotransferases in SLE, which might be responsible for the observed glycan alteration. Our findings provide insights into efficient population screening based on serum IgG glycosylation and potential new pathogenic factors of SLE.

Abstract Non-coding RNAs (ncRNAs) draw much attention from studies widely in recent years because they play vital roles in life activities. As a good complement to wet experiment methods, computational prediction methods can greatly save experimental costs. However, high false-negative data and insufficient use of multi-source information can affect the performance of computational prediction methods. Furthermore, many computational methods do not have good robustness and generalization on different datasets. In this work, we propose an effective end-to-end computing framework, called GDCL-NcDA, of deep graph learning and deep matrix factorization (DMF) with contrastive learning, which identifies the latent ncRNA-disease association on diverse multi-source heterogeneous networks (MHNs). The diverse MHNs include different similarity networks and proven associations among ncRNAs (miRNAs, circRNAs, and lncRNAs), genes, and diseases. Firstly, GDCL-NcDA employs deep graph convolutional network and multiple attention mechanisms to adaptively integrate multi-source of MHNs and reconstruct the ncRNA-disease association graph. Then, GDCL-NcDA utilizes DMF to predict the latent disease-associated ncRNAs based on the reconstructed graphs to reduce the impact of the false-negatives from the original associations. Finally, GDCL-NcDA uses contrastive learning (CL) to generate a contrastive loss on the reconstructed graphs and the predicted graphs to improve the generalization and robustness of our GDCL-NcDA framework. The experimental results show that GDCL-NcDA outperforms highly related computational methods. Moreover, case studies demonstrate the effectiveness of GDCL-NcDA in identifying the associations among diversiform ncRNAs and diseases.

Abstract The precise activation of C–H bonds will eventually provide chemists with transformative methods to access complex molecular architectures. Current approaches to selective C–H activation relying on directing groups are effective for the generation of five-membered, six-membered and even larger ring metallacycles but show narrow applicability to generate three- and four-membered rings bearing high ring strain. Furthermore, the identification of distinct small intermediates remains unsolved. Here, we developed a strategy to control the size of strained metallacycles in the rhodium-catalysed C−H activation of aza-arenes and applied this discovery to tunably incorporate the alkynes into their azine and benzene skeletons. By merging the rhodium catalyst with a bipyridine-type ligand, a three-membered metallacycle was obtained in the catalytic cycle, while utilizing an NHC ligand favours the generation of the four-membered metallacycle. The generality of this method was demonstrated with a range of aza-arenes, such as quinoline, benzo[f]quinolone, phenanthridine, 4,7-phenanthroline, 1,7-phenanthroline and acridine. Mechanistic studies revealed the origin of the ligand-controlled regiodivergence in the strained metallacycles.

There are numerous issues in the mainstream process of alkali decomposition of tungsten ores, such as large water consumption, large amounts of wastewater, and high processing costs, which add the dual pressure of economic and environmental protection on smelting enterprises and prevent them from meeting the industry’s development needs. As a result of a series of studies on scheelite roasting and decomposition processes, our team innovatively proposed the use of acid roasting to develop the process of sulfate decomposition of scheelite so that CaWO4 in the scheelite could be transformed directly into WO3. In addition to WO3, the roasting products contained soluble Na2SO4 and insoluble CaSO4. Because CaSO4 can be dissolved in hydrochloric acid, it can be separated from WO3 via hydrochloric acid leaching to further enrich WO3, resulting in a higher-grade material for subsequent procedures. In the presence of Na2SO4, its effect on the dissolution of WO3 or CaSO4 in hydrochloric acid will directly determine the separation effect of calcium and tungsten in the roasting products. Thus, using pure substances such as WO3, CaSO4, and Na2SO4 as raw materials, the dissolution behaviors of WO3, CaSO4, and WO3–CaSO4 in HCl–Na2SO4 solution were investigated separately via isothermal equilibrium dissolution to investigate the effects of hydrochloric acid concentration, sodium sulfate concentration, dissolution time, and dissolution temperature on the solubility of WO3, CaSO4, and WO3–CasO4 in HCl–Na2SO4 solution. The analysis shows that WO3 and CaSO4 have very different solubilities in hydrochloric acid. The solubility of CaSO4 in hydrochloric acid increases with temperature and hydrochloric acid concentration when the dissolution time is 0.5–2.5 h, the hydrochloric acid concentration is 1–5 mol·L−1, the molar ratio of HCl and Na2SO4 is 1∶2–2∶1, and the dissolution temperature is 40–80 ℃. The solubility of calcium sulfate in hydrochloric acid increases with the increase in temperature and hydrochloric acid concentration. When the temperature is 80 ℃ and the concentration of hydrochloric acid is 3 mol·L−1, the solubility of calcium sulfate in hydrochloric acid reaches a peak of 55 g·L−1. Due to the same ion effect, Na2SO4 can significantly reduce the solubility of CaSO4 and narrow the solubility difference between CaSO4 and WO3 in hydrochloric acid. CaSO4 has the highest solubility in HCl–Na2SO4 solution at 17.04 g·L−1. The dissolved WO3, whose solubility is maintained at 0.3–3 g·L−1, can be effectively recovered by using the current mature low-tungsten recovery process. Therefore, when CaSO4 and WO3 coexist in hydrochloric acid, increasing the concentration of hydrochloric acid and the dissolution temperature while decreasing the concentration of Na2SO4 can increase the solubility difference between them and achieve separation.

Abstract Super-resolution structured illumination microscopy (SR-SIM) has become a widely used nanoscopy technique for rapid, long-term, and multi-color imaging of live cells. Precise but troublesome determination of the illumination pattern parameters is a prerequisite for Wiener-deconvolution-based SR-SIM image reconstruction. Here, we present a direct reconstruction SIM algorithm (direct-SIM) with an initial spatial-domain reconstruction followed by frequency-domain spectrum optimization. Without any prior knowledge of illumination patterns and bypassing the artifact-sensitive Wiener deconvolution procedures, resolution-doubled SR images could be reconstructed by direct-SIM free of common artifacts, even for the raw images with large pattern variance in the field of view (FOV). Direct-SIM can be applied to previously difficult scenarios such as very sparse samples, periodic samples, very small FOV imaging, and stitched large FOV imaging.

Photocatalysis technology based on solar-powered semiconductors is widely recognized as a promising approach for achieving eco-friendly, secure, and sustainable degradation of organic contaminants. Nevertheless, conventional photocatalysts exhibit drawbacks such as a wide bandgap, and rapid recombination of photoinduced electron/hole pairs, in addition to complicated separation and recovery procedures. In this research, we cultivated BiOBr in situ on the surface of copper foam to fabricate a functional photocatalyst (denoted as BiOBr/Cu foam), which was subsequently employed for the photodegradation of Methylene Blue. Based on photodegradation experiments, the 0.3 BiOBr/Cu foam demonstrates superior photocatalytic efficacy compared to other photocatalysts under solar light irradiation. Furthermore, its ease of separation from the solution enhances its potential for reuse. The analysis of charge transfer revealed that the copper foam functions as an effective electron scavenger within the BiOBr/Cu foam, thereby facilitating charge separation and the generation of photo-induced holes. This phenomenon contributes to a significantly enhanced production of hydroxyl radicals. This study provides a valuable perspective on the design and synthesis of photocatalysts with heightened practicality, employing a conductive substrate.

Abstract Adipose tissues are essential for actively regulating systemic energy balance, glucose homeostasis, immune responses, reproduction, and longevity. Adipocytes maintain dynamic metabolic needs and possess heterogeneity in energy storage and supply. Overexpansion of adipose tissue, especially the visceral type, is a high risk for diabetes and other metabolic diseases. Changes in adipocytes, hypertrophy or hyperplasia, contribute to the remodeling of obese adipose tissues, accompanied by abundant immune cell accumulation, decreased angiogenesis, and aberrant extracellular matrix deposition. The process and mechanism of adipogenesis are well known, however, adipose precursors and their fate decision are only being defined with recent information available to decipher how adipose tissues generate, maintain, and remodel. Here, we discuss the key findings that identify adipose precursors phenotypically, with special emphasis on the intrinsic and extrinsic signals in instructing and regulating the fate of adipose precursors under pathophysiological conditions. We hope that the information in this review lead to novel therapeutic strategies to combat obesity and related metabolic diseases.

In this study, electrochemical corrosion and wear experiments were conducted to clarify the role of cryogenic treatment on the microstructural morphology and resistance to corrosion and wear of high-manganese austenitic steel. Heat treatment of the solution (950 °C) and annealing (500 °C and 600 °C) were performed on the hot-rolled specimens. Cryogenic treatment was applied to hot-rolled, hot-rolled + heat treated specimens. Cryogenic treatment is a practical technology for eliminating the strip morphology of hot-rolled specimens and improves the wear resistance of heat-treated specimens. However, it plays different role on the corrosion resistance of tested specimens related with production process. The wear mechanism differs due to the cryogenic treatment. A schematic model of the wear mechanism is proposed based on the experimental results. Cryogenic treatment coarsens the grain size regardless of the production process.

Bacteria in the genus Vibrio are ubiquitous in estuarine and coastal waters. Some species (including Vibrio cholerae and Vibrio vulnificus) are known human pathogens causing ailments like cholera, diarrhea, or septicemia. Notably, V. vulnificus can also cause a severe systemic infection (known as vibriosis) in eels raised in aquaculture facilities. Water samples were periodically collected from the estuary of the Asahi River, located in the southern part of Okayama City, Japan. These samples were directly plated onto CHROMagar Vibrio plates, and colonies displaying turquoise-blue coloration were selected. Thereafter, polymerase chain reaction was used to identify V. cholerae and V. vulnificus. A total of 30 V. cholerae strains and 194 V. vulnificus strains were isolated during the warm season when the water temperature (WT) was higher than 20 °C. Concurrently, an increase in coliforms was observed during this period. Notably, V. vulnificus has two genotypes, designated as genotype 1 and genotype 2. Genotype 1 is pathogenic to humans, while genotype 2 is pathogenic to both humans and eels. The loop-mediated isothermal amplification method was developed to rapidly determine genotypes at a low cost. Of the 194 strains isolated, 80 (41.2%) were identified as genotype 1 strains. Among the 41 strains isolated when the WTs were higher than 28 °C, 25 strains (61.0%) belonged to genotype 1. In contrast, of the 32 strains isolated when the WTs were lower than 24 °C, 27 strains (84.4%) belonged to genotype 2. These results suggest that the distribution of the two genotypes was influenced by WT.

This study aimed to investigate the potential effects of Gomisin B, a natural compound known for its inhibition of CYP3A4, on cognitive dysfunction in APP/PS1 transgenic mice with Alzheimer's disease (AD). Additionally, the study explored the combined effects of Gomisin B and Osthole (OST). The research involved male wild-type (WT) mice and 7-month-old APP/PS1 transgenic AD mice. The assessment of behavioral changes included the use of the open field test (OFT) and the Morris water maze (MWM). OST levels in brain tissue were quantified using LC-MS/MS, while levels of oxidative stress were measured through an assay kit. Neuronal apoptosis was studied using Nissl staining, RT-qPCR, and immunofluorescence. Amyloid plaque clearance was assessed using thioflavine-S (Th-S) staining, RT-qPCR, and ELISA. The results of the study revealed that Gomisin B led to a significant improvement in cognitive dysfunction in APP/PS1 mice. Moreover, the simultaneous administration of OST and Gomisin B demonstrated enhanced therapeutic effects. These effects were attributed to the inhibition of β-site APP-Cleaving Enzyme 1 (BACE1) and oxidative stress by Gomisin B, along with its anti-apoptotic properties. The combined use of OST and Gomisin B exhibited a synergistic impact, resulting in more pronounced anti-oxidant and anti-apoptotic effects. In summary, this study pioneers the exploration of Gomisin B's multifunctional anti-AD properties in APP/PS1 mice. The findings provide a solid groundwork for the development of anti-Alzheimer's drugs based on natural active ingredients.

Alzheimer's Disease (AD) is a global public health priority characterized by high mortality rates in adults and an increasing prevalence in aging populations worldwide. Despite significant advancements in comprehending the pathogenesis of AD since its initial report in 1907, there remains a lack of effective curative or preventive measures for the disease. In recent years, natural compounds sourced from diverse origins have garnered considerable attention as potential therapeutic agents for AD, owing to their anti-inflammatory, antioxidant, and neuroprotective properties. This review aims to consolidate the therapeutic effects of natural compounds on AD, specifically targeting the reduction of β-amyloid (Aβ) overproduction, anti-apoptosis, autophagy, neuroinflammation, oxidative stress, endoplasmic reticulum (ER) stress, and mitochondrial dysfunction. Notably, the identified compounds exhibiting these effects predominantly originate from plants. This review provides valuable insights into the potential of natural compounds as a reservoir of novel therapeutic agents for AD, thereby stimulating further research and contributing to the development of efficacious treatments for this devastating disease.

Mitochondrial dysfunction, especially in terms of mitochondrial dynamics, has been reported to be closely associated with neuronal outcomes and neurological impairment in cerebral ischemia/hypoxia injury. Dynamin-related protein 1 (Drp1) is a cytoplasmic GTPase that mediates mitochondrial fission and participates in neuronal cell death, calcium signaling, and oxidative stress. The neuroprotective role of Drp1 inhibition has been confirmed in several central nervous system disease models, demonstrating that targeting Drp1 may shed light on novel approaches for the treatment of cerebral ischemia/hypoxia injury. In this review, we aimed to highlight the roles of Drp1 in programmed cell death, oxidative stress, mitophagy, and mitochondrial function to provide a better understanding of mitochondrial disturbances in cerebral ischemia/hypoxia injury, and we also summarize the advances in novel chemical compounds targeting Drp1 to provide new insights into potential therapies for cerebral ischemia/hypoxia injury.

High heat flux generated by quartz lamps can be employed to provide a simulated aerodynamic heating environment for thermal-structural tests on spacecraft. To provide a general numerical solution for radiant heating problems and to investigate the properties of radiation heat flux distributions generated by quartz lamp heaters, a quartz lamp array radiation model is proposed based on Monte Carlo method (MCM). The performance of this numerical model, including result uncertainty and computation time, has been examined. The model is validated through the design and execution of experiments under various radiation intensities. Good agreements between the numerical and experimental results indicates the accuracy and stability of the numerical model for predicting radiation heat flux over a target plane. Then, the impact of various factors on the uniformity and efficiency of radiation dispersal are explored. The results indicate that increasing heater-receiver distance is an efficient strategy for improving radiation uniformity. The reflector is a crucial device for increasing heater efficiency. The edge effect reduces the heat flux within a 10 cm radius of filament ends. A neighboring lamp interval of less than 5 cm is an excellent choice for avoiding radiation troughs and increasing the heater's efficiency.

The main challenge of few-shot learning lies in the limited labeled sample of data. In addition, since image-level labels are usually not accurate in describing the features of images, it leads to difficulty for the model to have good generalization ability and robustness. This problem has not been well solved yet, and existing metric-based methods still have room for improvement. To address this issue, we propose a few-shot learning method based on a three-dimension attention mechanism and self-supervised learning. The attention module is used to extract more representative features by focusing on more semantically informative features through spatial and channel attention. Self-supervised learning mainly adopts a proxy task of rotation transformation, which increases semantic information without requiring additional manual labeling, and uses this information for training in combination with supervised learning loss function to improve model robustness. We have conducted extensive experiments on four popular few-shot datasets and achieved state-of-the-art performance in both 5-shot and 1-shot scenarios. Experiment results show that our work provides a novel and remarkable approach to few-shot learning.

The interception of one chemical intermediate with another intermediate is very challenging, as intermediates may be incompatible or too reactive, but could result in a streamlined method of organic synthesis. Here, the authors demonstrate enantioselective four-component reactions via the coupling of two intermediates.

Alzheimer’s disease (AD) poses a significant threat to the global elderly population. Traditional Chinese medicine (TCM) has been widely utilized in the treatment of AD. Osthole, a bioactive ingredient classified as an “emperor” in many TCM formulas, has been demonstrated to effectively alleviate AD symptoms. However, its low bioavailability in the brain has limited its clinical application. This study aimed to increase the intracerebral bioavailability of osthole by using borneol as a “courier,” based on the classical “Emperor–Minister–Assistant–Courier” model, and to investigate the enhanced pharmacological performance of osthole on AD. Results indicated that a suitable in situ thermosensitive gel matrix for intranasal administration mixed with osthole and borneol consists of P407 at 20%, P188 at 7%, and PEG300 at 6%. The concentration of osthole in the cerebrospinal fluid increased almost tenfold after intranasal administration of osthole/borneol compared to oral administration. Mechanisms showed that borneol as a “courier” opened up intercellular space and loosened the tight junctions of the nasal mucosa by suppressing ZO-1 and occludin expression, thereby expediting the nose-to-brain route and guiding osthole as “emperor” to its target in the brain. Osthole assisted by borneol demonstrated significantly improved efficiency in suppressing cleaved caspase-3 expression, increasing the Bcl-2/Bax ratio, improving T-SOD and catalase expression, reducing malondialdehyde levels, inhibiting neuron apoptosis, and decreasing Aβ levels by inhibiting BACE1 expression to alleviate cognitive impairment in APP/PS1 mice compared to osthole alone. Overall, our study demonstrated that the intracerebral bioavailability of osthole profoundly improved with intranasal administration of osthole/borneol and provided a wider application of TCM for AD treatment with higher intracerebral bioavailability.

This study addressed the critical need for non-invasive monitoring of diabetes by proposing an acetone gas sensor based on hierarchical In _2 O _3 with atomic layer deposition (ALD)-deposited WO _3 nanoparticles. The sensor fabrication involved a carefully designed process, leveraging ALD to control WO _3 deposition, ensuring uniform distribution, and mitigating agglomeration. The resulting composite exhibited enhanced sensitivity, making it promising for detecting acetone, a key biomarker for diabetes. Material synthesis, including hydrothermal formation of In _2 O _3 hierarchy particles and ALD of WO _3 , was meticulously conducted. Comprehensive characterizations, involving SEM, TEM, EDX, XRD, XPS, and BET, validated the successful synthesis and deposition. The sensor’s response to varying acetone concentrations (50–2000 ppb) was systematically investigated, revealing a positive correlation. The In _2 O _3 /WO _3 –2 sensor exhibited the highest sensitivity, attributed to the catalytic properties of WO _3 . The proposed sensor presented a cost-effective, sensitive, and selective solution, paving the way for non-invasive diabetes monitoring.

We have experimentally created perfect vortex beams (PVBs) by Fourier transformation of Bessel–Gaussian vortex beams, which are generated by modulating the fundamental Gaussian beam with the spiral phase plates and the axicons, respectively. Although the method has been used many times by other authors, as far as we know, few people pay attention to the quantitative relationship between the control parameters of the PVB and ring width. The effects of the waist radius of the fundamental Gaussian beam wg, base angle of the axicon γ, and focal length of the lens f on the spot parameters (ring radius ρ, and ring half-width Δ) of PVB are systematically studied. The beam pattern of the generated Bessel–Gaussian beam for different propagation distances behind the axicon and the fundamental Gaussian beam wg is presented. We showed experimentally that the ring radius ρ increases linearly with the increase of the base angle γ and focal length f, while the ring half-width Δ decreases with the increase of the fundamental beam waist radius wg, and increases with enlarging the focal length f. We confirmed the topological charge (TC) of the PVB by the interferogram between the PVB and the reference fundamental Gaussian beam. We also studied experimentally that the size of the generated PVB in the Fourier plane is independent of the TCs. Our approach to generate the PVB has the advantages of high-power tolerance and high efficiency.

In recent years, edge intelligence (EI) has emerged, combining edge computing with AI, and specifically deep learning, to run AI algorithms directly on edge devices. In practical applications, EI faces challenges related to computational power, power consumption, size, and cost, with the primary challenge being the trade-off between computational power and power consumption. This has rendered traditional computing platforms unsustainable, making heterogeneous parallel computing platforms a crucial pathway for implementing EI. In our research, we leveraged the Xilinx Zynq 7000 heterogeneous computing platform, employed high-level synthesis (HLS) for design, and implemented two different accelerators for LeNet-5 using loop unrolling and pipelining optimization techniques. The experimental results show that when running at a clock speed of 100 MHz, the PIPELINE accelerator, compared to the UNROLL accelerator, experiences an 8.09% increase in power consumption but speeds up by 14.972 times, making the PIPELINE accelerator superior in performance. Compared to the CPU, the PIPELINE accelerator reduces power consumption by 91.37% and speeds up by 70.387 times, while compared to the GPU, it reduces power consumption by 93.35%. This study provides two different optimization schemes for edge intelligence applications through design and experimentation and demonstrates the impact of different quantization methods on FPGA resource consumption. These experimental results can provide a reference for practical applications, thereby providing a reference hardware acceleration scheme for edge intelligence applications.

Abstract Background The purpose of this study was to determine how the drain fluid volume on the first day after surgery (DFV 1) can be used to predict clinically relevant post-operative pancreatic fistula following distal pancreatectomy (DP). Method A retrospective analysis of 175 patients who underwent distal pancreatectomy in hepatobiliary surgery at Chengdu 363 Hospital (China) from January 2015 to January 2021 has been performed. Depending on the presence of pancreatic fistula, all patients were divided into two groups: POPF and non-POPF. The clinical factors were analyzed using SPSS 17.0 and Medcalc software. In order to assess the effectiveness of DFV 1 in predicting POPF after surgery, ROC curves were used to calculate its cut-off point,, which yielded sensitivity and negative predictive value of 100% for excluding POPF. Result Of the 175 patients who underwent distal pancreatectomy, the incidence of overall pancreatic fistula was 36%, but the rate of clinically significant (grade B and C) fistula, as defined by the International Study Group on Pancreatic Fistula, 30 was only 17.1% (28 grade B and 2 grade C fistula). The results from univariate and multivariate logistic regression analysis showed that drain fluid volume on the first postoperative day (OR = 0.95, P = 0.03), drainage fluid amylase level on POD1 (OR = 0.99, P = 0.01) and the preoperative ALT level (OR = 0.73, P = 0.02) were independent risk factors associated with CR-POPF. Receiver operating characteristic (ROC) curve analysis revealed that a drainage volume of 156 mL within 24 h and an amylase greater than 3219.2 U/L on the first postoperative day were the optimal thresholds associated with complications. Conclusion After distal pancreatectomy, the drainage volume on the first postoperative day can predict the presence of a clinically relevant pancreatic fistula.

Macrocyclization is an important process in bioactive natural product synthesis. Here, the authors report on the study of a macrocyclic ring constructing enzyme in the biosynthesis of alchivemycin A and using gene deletion, biochemical assays and isotope labelling show the enzyme catalyses tandem dehydration and Michael-type addition.

Abstract Background Gene expression analysis can provide useful information for analyzing complex biological mechanisms. However, many reported findings are unrepeatable due to small sample sizes relative to a large number of genes and the low signal-to-noise ratios of most gene expression datasets. Results Meta-analysis of multi-data sets is an efficient method for tackling the above problem. To improve the performance of meta-analysis, we propose a novel meta-analysis framework. It consists of two parts: (1) a novel data augmentation strategy. Various cross-platform normalization methods exist, which can preserve original biological information of gene expression datasets from different angles and add different “perturbations” to the dataset. Using such perturbation, we provide a feasible means for gene expression data augmentation; (2) elastic data shared lasso (DSL- $${{\varvec{L}}}_{\mathbf{2}}$$ L 2 ). The DSL- $${\mathbf{L}}_{\mathbf{2}}$$ L 2 method spans the continuum between individual models for each dataset and one model for all datasets. It also overcomes the shortcomings of the data shared lasso method when dealing with highly correlated features. Comprehensive simulation experiment results show that the proposed method has high prediction and gene selection performance. We then apply the proposed method to non-small cell lung cancer (NSCLC) blood gene expression data in order to identify key tumor-related genes. The outcomes of our experiment indicate that the method could be used for identifying a set of robust disease-related gene signatures that may be used for NSCLC early diagnosis or prognosis or even targeting. Conclusion We propose a novel and effective meta-analysis method for biological research, extrapolating and integrating information from multiple gene expression datasets.

Abstract Detecting changes is an important issue for ophthalmology to compare longitudinal fundus images at different stages and obtain change regions. Illumination variations bring distractions on the change regions by the pixel-by-pixel comparison. In this paper, a new unsupervised change detection method based on sparse representation classification (SRC) is proposed for the fundus image pair. First, the local neighborhood patches are extracted from the reference image to build a dictionary of the local background. Then the current image patch is represented sparsely and its background is reconstructed by the obtained dictionary. Finally, change regions are given through background subtracting. The SRC method can correct automatically illumination variations through the representation coefficients and filter local contrast and global intensity effectively. In experiments of this paper, the AUC and mAP values of SRC method are 0.9858 and 0.8647 respectively for the image pair with small lesions; the AUC and mAP values of the fusion method of IRHSF and SRC are 0.9892 and 0.9692 separately for the image pair with the big change region. Experiments show that the proposed method in this paper is more robust than RPCA for the illumination variations and can detect change regions more effectively than pixel-wised image differencing.