The roles of DNA methylation on pH dependent i-motif (iM) formation in rice.

I-motifs (iMs) are four-stranded non-B DNA structures containing C-rich DNA sequences. The formation of iMs is sensitive to pH conditions and DNA methylation, although the extent of which is still unknown in both humans and plants. To investigate this, we here conducted iMab antibody-based immunoprecipitation and sequencing (iM-IP-seq) along with bisulfite sequencing using CK (original genomic DNA without methylation-related treatments) and hypermethylated or demethylated DNA at both pH 5.5 and 7.0 in rice, establishing a link between pH, DNA methylation and iM formation on a genome-wide scale. We found that iMs folded at pH 7.0 displayed higher methylation levels than those formed at pH 5.5. DNA demethylation and hypermethylation differently influenced iM formation at pH 7.0 and 5.5. Importantly, CG hypo-DMRs (differentially methylated regions) and CHH (H = A, C and T) hyper-DMRs alone or coordinated with CG/CHG hyper-DMRs may play determinant roles in the regulation of pH dependent iM formation. Thus, our study shows that the nature of DNA sequences alone or combined with their methylation status plays critical roles in determining pH-dependent formation of iMs. It therefore deepens the understanding of the pH and methylation dependent modulation of iM formation, which has important biological implications and practical applications.

Chemical Micromotors Move Faster at Oil-Water Interfaces.

Many real-world scenarios involve interfaces, particularly liquid-liquid interfaces, that can fundamentally alter the dynamics of colloids. This is poorly understood for chemically active colloids that release chemicals into their environment. We report here the surprising discovery that chemical micromotors─colloids that convert chemical fuels into self-propulsion─move significantly faster at an oil-water interface than on a glass substrate. Typical speed increases ranged from 3 to 6 times up to an order of magnitude and were observed for different types of chemical motors and interfaces made with different oils. Such speed increases are likely caused by faster chemical reactions at an oil-water interface than at a glass-water interface, but the exact mechanism remains unknown. Our results provide valuable insights into the complex interactions between chemical micromotors and their environments, which are important for applications in the human body or in the removal of organic pollutants from water. In addition, this study also suggests that chemical reactions occur faster at an oil-water interface and that micromotors can serve as a probe for such an effect.

Afterglow Nanoprobe-Enabled Quantitative Lateral Flow Immunoassay by a Palm-Size Device for Household Healthcare.

Lateral flow immunoassay (LFIA), a classical point-of-care testing (POCT) technique, plays an important role in disease screening and healthcare monitoring. However, traditional LFIA is either designed for qualitative analysis or requires expensive equipment for quantification, limiting its use in household diagnosis. In this study, we proposed a new generation of LFIA for household health monitoring by using ultralong organic phosphorescence (UOP) nanomaterials as afterglow nanoprobes with a self-developed palm-size sensing device. The UOP nanoprobes exhibit a phosphorescence signal with a second-level lifetime, which completely avoids the interference from excitation light and biological background fluorescence. Therefore, an ultraminiaturized and low-cost UOP nanosensor was successfully designed by eliminating the complex optical path and filtering systems. We chose an inflammatory factor, C-reactive protein (CRP), for household POCT validation. The whole analysis was completed within 9 min. A limit of detection (LOD) of 0.54 ng/mL of CRP antigen was achieved with high stability and good specificity, which is comparable to laboratory instruments and fully satisfying the clinical diagnosis requirement.

Enzymatic Nanomotors Surviving Harsh Conditions Enabled by Metal Organic Frameworks Encapsulation.

Enzyme-driven micro/nanomotors (MNMs) have demonstrated potentials in the biomedical field because of their excellent biocompatibility, versatility, and fuel bioavailability. However, the fragility of enzymes limits their practical application, because of their susceptibility to denaturation and degradation in realistic scenarios. Herein, a simple yet versatile and effective approach is reported to preserve the enzymatic activity and propulsion capability of enzymatic MNMs under various harsh conditions using metal organic frameworks (MOFs) as a protective shell. Urease can be encapsulated within the exoskeleton of zeolitic imidazolate framework-8 (ZIF-8) via biomimetic mineralization to form ZIF-8@urease (ZU-I) nanomotors that exhibit self-propulsion in the presence of urea. When exposed to harsh conditions, including high temperature, presence of proteases, and organic solvents, the ZU-I nanomotors still maintained their activity and mobility, whereas ZIF-8 with externally modified urease (ZU-O) nanomotors with externally modified urease as a control rapidly lost their motion capabilities owing to the inactivation of urease. Furthermore, ZU-I nanomotors exhibit effectively enhanced diffusion within the small intestine fluid, achieving a fourfold higher mucus penetration than the ZU-O nanomotors. The results highlight the effectiveness of using MOFs as protective shells for enzyme nano-engines, which can greatly advance the practical applications of enzymatic MNMs under realistic conditions, especially for biomedical purpose.

Enzymatic Reaction Enhanced Diffusion Accelerates Cargo Transport through Micro/Nano-Channels.

Energy conversion and transfer of enzyme-catalyzed reactions at molecular level are an interesting and challenging scientific topic that helps understanding biological processes in nature. In this study, it is demonstrated that enzyme-catalyzed reactions can enhance diffusion of surrounding molecules and thus accelerate cargo transport within 1D micro/nanochannels. Specifically, urease is immobilized on the inner walls of silica micro/nano-tubes to construct bio-catalytically active micro/nanochannels. The catalytic reaction inside the channels drives a variety of cargoes, including small dye molecules, polymers, and rigid nanoparticles (e.g., quantum dots, QDs), to pass through these micro/nanochannels much faster than they will by free diffusion. The enhanced diffusion of molecular species inside the channels is validated by direct observation of the Brownian motion of tracer particles, and further confirmed by significantly enhanced Raman intensity of reporter molecules. Finite element and Brownian dynamics simulations provide a theoretical understanding of these experimental observations. Furthermore, the effect of the channels' size on the diffusion enhancement is examined. The acceleration effect of the cargo transport through these enzymatically active micro/nanochannels can be turned on or off via chemical activators or inhibitors. This study provides valuable insights on the design of biomimetic channels capable of controlled and efficient transmembrane transport.

Physical exercise ameliorates age-related deterioration of skeletal muscle and mortality by activating Pten-related pathways in Drosophila on a high-salt diet.

The phosphatase and tensin congeners (Pten) gene affects cell growth, cell proliferation, and rearrangement of connections, and it is closely related to cellular senescence, but it remains unclear the role of muscle-Pten gene in exercise against age-related deterioration in skeletal muscle and mortality induced by a high-salt diet (HSD). In here, overexpression and knockdown of muscle Pten gene were constructed by building MhcGAL4 /PtenUAS-overexpression and MhcGAL4 /PtenUAS-RNAi system in flies, and flies were given exercise training and a HSD for 2 weeks. The results showed that muscle Pten knockdown significantly reduced the climbing speed, climbing endurance, GPX activity, and the expression of Pten, Sirt1, PGC-1α genes, and it significantly increased the expression of Akt and ROS level, and impaired myofibril and mitochondria of aged skeletal muscle. Pten knockdown prevented exercise from countering the HSD-induced age-related deterioration of skeletal muscle. Pten overexpression has the opposite effect on skeletal muscle aging when compared to it knockdown, and it promoted exercise against HSD-induced age-related deterioration of skeletal muscle. Pten overexpression significantly increased lifespan, but its knockdown significantly decreased lifespan of flies. Thus, current results confirmed that differential expression of muscle Pten gene played an important role in regulating skeletal muscle aging and lifespan, and it also affected the adaptability of aging skeletal muscle to physical exercise since it determined the activity of muscle Pten/Akt pathway and Pten/Sirt1/PGC-1α pathway.

Tumour necrosis factor α regulates the miR-27a-3p-Sfrp1 axis in a mouse model of osteoporosis.

Osteoporosis is a metabolic bone disease that involves gradual loss of bone density and mass, thus resulting in increased fragility and risk of fracture. Inflammatory cytokines, such as tumour necrosis factor α (TNF-α), inhibit osteogenic differentiation of bone marrow mesenchymal stem cells (BMSCs), and several microRNAs are implicated in osteoporosis development. This study aimed to explore the correlation between TNF-α treatment and miR-27a-3p expression in BMSC osteogenesis and further understand their roles in osteoporosis. An osteoporosis animal model was established using ovariectomized (OVX) mice. Compared with Sham mice, the OVX mice had a significantly elevated level of serum TNF-α and decreased level of bone miR-27a-3p, and in vitro TNF-α treatment inhibited miR-27a-3p expression in BMSCs. In addition, miR-27a-3p promoted osteogenic differentiation of mouse BMSCs in vitro, as evidenced by alkaline phosphatase staining and Alizarin Red-S staining, as well as enhanced expression of the osteogenic markers Runx2 and Osterix. Subsequent bioinformatics analysis combined with experimental validation identified secreted frizzled-related protein 1 (Sfrp1) as a downstream target of miR-27a-3p. Sfrp1 overexpression significantly inhibited the osteogenic differentiation of BMSCs in vitro and additional TNF-α treatment augmented this inhibition. Moreover, Sfrp1 overexpression abrogated the promotive effect of miR-27a-3p on the osteogenic differentiation of BMSCs. Furthermore, the miR-27a-3p-Sfrp1 axis was found to exert its regulatory function in BMSC osteogenic differentiation via regulating Wnt3a-ß-catenin signalling. In summary, this study revealed that TNF-α regulated a novel miR-27a-3p-Sfrp1 axis in osteogenic differentiation of BMSCs. The data provide new insights into the development of novel therapeutic strategies for osteoporosis.

A fundamental study on postmortem submersion interval estimation by metabolomics analyzing of gastrocnemius muscle from submersed rat models in freshwater.

In forensic practice, determining the postmortem submersion interval (PMSI) and cause-of-death of cadavers in aquatic ecosystems has always been challenging task. Traditional approaches are not yet able to address these issues effectively and adequately. Our previous study proposed novel models to predict the PMSI and cause-of-death based on metabolites of blood from rats immersed in freshwater. However, with the advance of putrefaction, it is hardly to obtain blood samples beyond 3 days postmortem. To further assess the feasibility of PMSI estimation and drowning diagnosis in the later postmortem phase, gastrocnemius, the more degradation-resistant tissue, was collected from drowned rats and postmortem submersion model in freshwater immediately after death, and at 1 day, 3 days, 5 days, 7 days, and 10 days postmortem respectively. Then the samples were analyzed with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to investigate the dynamic changes of the metabolites. A total of 924 metabolites were identified. Similar chronological changes of gastrocnemius metabolites were observed in the drowning and postmortem submersion groups. The difference in metabolic profiles between drowning and postmortem submersion groups was only evident in the initial 1 day postmortem, which was faded as the PMSI extension. Nineteen metabolites representing temporally-dynamic patterns were selected as biomarkers for PMSI estimation. A regression model was built based on these biomarkers with random forest algorithm, which yielded a mean absolute error (± SE) of 5.856 (± 1.296) h on validation samples from an independent experiment. These findings added to our knowledge of chronological changes in muscle metabolites from submerged vertebrate remains during decomposition, which provided a new perspective for PMSI estimation.

Broad environmental adaptation of abundant microbial taxa in Robinia pseudoacacia forests during long-term vegetation restoration.

Vegetation restoration has significant impacts on ecosystems, and a comprehensive understanding of microbial environmental adaptability could facilitate coping with ecological challenges such as environmental change and biodiversity loss. Here, abundant and rare soil bacterial and fungal communities were characterized along a 15-45-year chronosequence of forest vegetation restoration in the Loess Plateau region. Phylogenetic-bin-based null model analysis (iCAMP), niche breadth index, and co-occurrence network analysis were used to assess microbial community assembly and environmental adaptation of a Robinia pseudoacacia plantation under long-term vegetation restoration. The drift process governed community assembly of abundant and rare soil fungi and bacteria. With increasing soil total phosphorus content, the relative importance of drift increased, while dispersal limitation and heterogeneous selection exhibited opposite trends for abundant and rare fungi. Rare soil fungal composition dissimilarities were dominated by species replacement processes. Abundant microbial taxa had higher ecological niche width and contribution to ecosystem multifunctionality than rare taxa. Node property values (e.g., degree and betweenness) of abundant microbial taxa were substantially higher than those of rare microbial taxa, indicating abundant species occupied a central position in the network. This study provides insights into the diversity and stability of microbial communities during vegetation restoration in Loess Plateau. The findings highlight that abundant soil fungi and bacteria have broad environmental adaptation and major implications for soil multifunctionality under long-term vegetation restoration.

Reproducible Quantitative Trait Loci for Resistance to Soft Rot Caused by Dickeya dianthicola Derived from the Wild Potato Solanum microdontum (PI 458355) Are Located on Chromosomes 1, 3, and 5.

The potato wild relative Solanum microdontum is a breeder-friendly source of genetic resistance to soft rot. Our objectives were to (i) identify loci associated with soft rot resistance in S. microdontum germplasm and (ii) develop bi-parental populations in a self-compatible S. tuberosum genetic background to recover segregating F2 progenies, construct a linkage map, and identify quantitative trait loci (QTLs). Under objective (i), tubers from 103 S. microdontum genotypes from the United States Potato Genebank were inoculated with a high virulence strain of Dickeya dianthicola, and lesion size was measured after a 24-h incubation period at 30°C. Association analysis using 3,490 polymorphic Infinium array SNP markers identified soft rot resistance loci on chromosomes 1, 2, 3, 5, 7, 8, 11, and 12. Under objective (ii), a resistant S. microdontum accession PI 458355 was crossed with a highly fertile, self-compatible, diploid S. tuberosum pollen parent (PI 654351) to generate segregating F2 populations. Composite interval mapping was conducted using a genetic linkage map with 970 GBS-based SNP markers. Reproducible QTLs were detected on chromosomes 1, 3, and 5, explaining 11, 13, and 23% of the phenotypic variation, respectively. Homozygous S. microdontum alleles at the QTL on chromosome 5 and heterozygous or homozygous S. microdontum alleles at QTLs on chromosomes 1 and 3 significantly decrease lesion size compared with the homozygous S. tuberosum parent. The germplasm created in these studies provides a resource for studying traits from S. microdontum, and we can use the advanced F2 selections for future potato improvement. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Genome-wide characterization of i-motifs and their potential roles in the stability and evolution of transposable elements in rice.

I-motifs (iMs) are non-canonical DNA secondary structures that fold from cytosine (C)-rich genomic DNA regions termed putative i-motif forming sequences (PiMFSs). The structure of iMs is stabilized by hemiprotonated C-C base pairs, and their functions are now suspected in key cellular processes in human cells such as genome stability and regulation of gene transcription. In plants, their biological relevance is still largely unknown. Here, we characterized PiMFSs with high potential for i-motif formation in the rice genome by developing and applying a protocol hinging on an iMab antibody-based immunoprecipitation (IP) coupled with high-throughput sequencing (seq), consequently termed iM-IP-seq. We found that PiMFSs had intrinsic subgenomic distributions, cis-regulatory functions and an intricate relationship with DNA methylation. We indeed found that the coordination of PiMFSs with DNA methylation may affect dynamics of transposable elements (TEs) among different cultivated Oryza subpopulations or during evolution of wild rice species. Collectively, our study provides first and unique insights into the biology of iMs in plants, with potential applications in plant biotechnology for improving important agronomic rice traits.

Application of artificial intelligence-assisted image diagnosis software based on volume data reconstruction technique in medical imaging practice teaching.

BACKGROUND: In medical imaging courses, due to the complexity of anatomical relationships, limited number of practical course hours and instructors, how to improve the teaching quality of practical skills and self-directed learning ability has always been a challenge for higher medical education. Artificial intelligence-assisted diagnostic (AISD) software based on volume data reconstruction (VDR) technique is gradually entering radiology. It converts two-dimensional images into three-dimensional images, and AI can assist in image diagnosis. However, the application of artificial intelligence in medical education is still in its early stages. The purpose of this study is to explore the application value of AISD software based on VDR technique in medical imaging practical teaching, and to provide a basis for improving medical imaging practical teaching. METHODS: Totally 41 students majoring in clinical medicine in 2017 were enrolled as the experiment group. AISD software based on VDR was used in practical teaching of medical imaging to display 3D images and mark lesions with AISD. Then annotations were provided and diagnostic suggestions were given. Also 43 students majoring in clinical medicine from 2016 were chosen as the control group, who were taught with the conventional film and multimedia teaching methods. The exam results and evaluation scales were compared statistically between groups. RESULTS: The total skill scores of the test group were significantly higher compared with the control group (84.51 ± 3.81 vs. 80.67 ± 5.43). The scores of computed tomography (CT) diagnosis (49.93 ± 3.59 vs. 46.60 ± 4.89) and magnetic resonance (MR) diagnosis (17.41 ± 1.00 vs. 16.93 ± 1.14) of the experiment group were both significantly higher. The scores of academic self-efficacy (82.17 ± 4.67) and self-directed learning ability (235.56 ± 13.50) of the group were significantly higher compared with the control group (78.93 ± 6.29, 226.35 ± 13.90). CONCLUSIONS: Applying AISD software based on VDR to medical imaging practice teaching can enable students to timely obtain AI annotated lesion information and 3D images, which may help improve their image reading skills and enhance their academic self-efficacy and self-directed learning abilities.

Promotion of self-directed learning abilities among Chinese medical students through preparing for career calling and enhancing teaching competencies in medical education: a cross-sectional study.

BACKGROUND: Medical students face a heavy burden as they are tasked with acquiring a vast amount of medical knowledge within a limited time frame. Self-directed learning (SDL) has become crucial for efficient and ongoing learning among medical students. However, effective ways to foster SDL ability among Chinese medical students are lacking, and limited studies have identified factors that impact the SDL ability of medical students. This makes it challenging for educators to develop targeted strategies to improve students' SDL ability. This study aims to assess SDL ability among Chinese medical students and examine the effects of career calling and teaching competencies on SDL ability, as well as the possible mechanisms linking them. METHODS: Data were collected from 3614 respondents (effective response rate = 60.11%) using cross-sectional online questionnaires and analyzed using IBM SPSS Statistics 22.0. The questionnaire comprised a Demographic Characteristics Questionnaire, Self-directed Learning Ability Scale (Cronbach's alpha = 0.962), Teaching Competencies Scale, and Career Calling Scale. RESULTS: The average SDL ability score of Chinese medical students was 3.68 ± 0.56, indicating a moderate level of SDL ability. The six factors of the Self-directed Learning Ability Scale-self-reflection, ability to use learning methods, ability to set study plans, ability to set studying objectives, ability to adjust psychological state, and willpower in studying-accounted for 12.90%, 12.89%, 12.39%, 11.94%, 11.34%, and 8.67% of the variance, respectively. Furthermore, career calling was positively associated with SDL learning ability (ß = 0.295, p < 0.001), and SDL learning ability was positively associated with teaching competencies (ß = 0.191, p < 0.01). Simple slope analysis showed that when the level of teaching competencies was higher, the influence of career calling on SDL ability was stronger. CONCLUSIONS: Chinese medical students' SDL ability has room for improvement. Medical students could strengthen their willpower in studying by setting milestones goals with rewards, which could inspire their motivation for the next goals. Teachers should guide students to learn experience to improve students' reflective ability. Educators play a crucial role in bridging the gap between career calling education and SDL ability enhancement, highlighting the significance of optimal teaching competencies. Colleges should focus on strengthening teachers' sense of career calling and teaching competencies.

The Role of Bismuth in Suppressing the CO Poisoning in Alkaline Methanol Electrooxidation: Switching the Reaction from the CO to Formate Pathway.

While tuning the electronic structure of Pt can thermodynamically alleviate CO poisoning in direct methanol fuel cells, the impact of interactions between intermediates on the reaction pathway is seldom studied. Herein, we contrive a PtBi model catalyst and realize a complete inhibition of the CO pathway and concurrent enhancement of the formate pathway in the alkaline methanol electrooxidation. The key role of Bi is enriching OH adsorbates (OHad) on the catalyst surface. The competitive adsorption of CO adsorbates (COad) and OHad at Pt sites, complementing the thermodynamic contribution from alloying Bi with Pt, switches the intermediate from COad to formate that circumvents CO poisoning. Hence, 8% Bi brings an approximately 6-fold increase in activity compared to pure Pt nanoparticles. This notion can be generalized to modify commercially available Pt/C catalysts by a microwave-assisted method, offering opportunities for the design and practical production of CO-tolerance electrocatalysts in an industrial setting.

Supramolecular Modular Assembly of Imaging-Trackable Enzymatic Nanomotors.

Self-propelled micro/nanomotors (MNMs) have shown great application potential in biomedicine, sensing, environmental remediation, etc. In the past decade, various strategies or technologies have been used to prepare and functionalize MNMs. However, the current preparation strategies of the MNMs were mainly following the pre-designed methods based on specific tasks to introduce expected functional parts on the various micro/nanocarriers, which lacks a universal platform and common features, making it difficult to apply to different application scenarios. Here, we have developed a modular assembly strategy based on host-guest chemistry, which enables the on-demand construction of imaging-trackable nanomotors mounted with suitable driving and imaging modules using a universal assembly platform, according to different application scenarios. These assembled nanomotors exhibited enhanced diffusion behavior driven by enzymatic reactions. The loaded imaging functions were used to dynamically trace the swarm motion behavior of assembled nanomotors with corresponding fuel conditions both in vitro and in vivo. The modular assembly strategy endowed with host-guest interaction provides a universal approach to producing multifunctional MNMs in a facile and controllable manner, which paves the way for the future development of MNMs systems with programmable functions.

Polyoxometalate-Nanozyme-Integrated Nanomotors (POMotors) for Self-Propulsion-Promoted Synergistic Photothermal-Catalytic Tumor Therapy.

Enzyme-powered nanomotors have demonstrated promising potential in biomedical applications, especially for catalytic tumor therapy, owing to their ability of self-propulsion and bio-catalysis. However, the fragility of natural enzymes limits their environmental adaptability and also therapeutic efficacy in catalysis-enabled tumor therapy. Herein, polyoxometalate-nanozyme-based light-driven nanomotors were designed and synthesized for targeted synergistic photothermal-catalytic tumor therapy. In this construct, the peroxidase-like activity of the P2 W18 Fe4 polyoxometalates-based nanomotors can provide self-propulsion and facilitate their production of reactive oxygen species thus killing tumor cells, even in the weakly acidic tumor microenvironment. Conjugated polydopamine endows the nanomotors with the capability of light-driven self-propulsion behavior. After 10 min of NIR (808 nm) irradiation, along with the help of epidermal growth factor receptor antibody, the targeted accumulation and penetration of nanomotors in the tumor enabled highly efficient synergistic photothermal-catalytic therapy. This approach overcomes the disadvantages of the intrinsically fragile nature of enzyme-powered nanomotors in physiological environments and, more importantly, provides a motility-behavior promoted synergistic anti-tumor strategy.

Endowing Porphyrinic Metal-Organic Frameworks with High Stability by a Linker Desymmetrization Strategy.

The fabricating of metal-organic frameworks (MOFs) that integrate high stability and functionality remains a long-term pursuit yet a great challenge. Herein, we develop a linker desymmetrization strategy to construct highly stable porphyrinic MOFs, namely, USTC-9 (USTC represents the University of Science and Technology of China), presenting the same topological structure as the well-known PCN-600 that readily loses crystallinity in air or upon conventional activation. For USTC-9, the involved porphyrinic linker (TmCPP-M) with carboxylate groups located in the meta-position presents a chair-shaped conformation with lower C2h symmetry than that (D4h) of the common porphyrinic carboxylate (TCPP) linker in PCN-600. As a result, the wrinkled and interlocked linker arrangements collectively contribute to the remarkable stability of USTC-9. Given the high stability and porosity as well as Lewis acidity, USTC-9(Fe) demonstrates its excellent performance toward catalytic CO2 cycloaddition with diverse epoxides at moderate temperature and atmospheric pressure.

Pd/Co Catalyst with High Pd Atom Utilization Efficiency for Nitrobenzene Hydrogenation at Room Temperature: Experimental and DFT Studies.

Enhancing catalytic performance as well as reducing catalyst cost are the eternal pursuit for the catalysis community. Herein, a simple and effective palladium-doped cobalt (Pd/Co) catalyst with high Pd atom utilization efficiency was synthesized via galvanic replacement reaction for the selective hydrogenation of nitrobenzene with H2 at room temperature, delivering >99 % yield of aniline with up to 158 times higher catalytic activity than commercial palladium powder. Detailed characterizations and DFT calculations revealed that Co-Pd interaction leads to a decrease in electron density of Pd and the distance between Pd atoms that results in the enhanced catalytic performance. Further experiments indicated that the Pd/Co catalyst serves as a highly efficient, selective, and recyclable catalyst for a range of nitroarene substrates. This work might provide a green and sustainable methodology to design and synthesize highly active catalysts with high utilization efficiency of the noble metals in fundamental and applied research.

Analysis of controlled ovarian hyperstimulation protocols in women over 35 years old with poor ovarian response: a real-world study.

The objective of this study was to investigate the optimal controlled ovarian hyperstimulation (COH) protocol for patients aged 35 and above with poor ovarian response (POR), utilizing real-world data. This retrospective cohort study examined clinical information from a total of 4256 patients between January 2017 and November 2022. The patients were categorized into three groups: modified GnRH agonist protocol (2116 patients), GnRH antagonist protocol (1628 patients), and Mild stimulation protocol (512 patients). Comparative analysis was conducted on clinical variables and pregnancy outcomes across the three groups. The GnRH agonist protocol was associated with a higher number of oocyte number (4.02 ± 2.25 vs. 3.15 ± 1.52 vs. 2.40 ± 1.26, p < 0.001), higher number of transferable embryos (1.73 ± 1.02 vs. 1.35 ± 1.22 vs. 1.10 ± 0.86, p = 0.016), higher cumulative live birth rate 28.50(603/2116) vs. 24.94(406/1628) vs. 20.51(105/512), p < 0.001) than GnRH antagonist protocol and Mild stimulation protocol, the Mild stimulation protocol was associated with a higher miscarriage rates 16.27(62/381) vs. 16.61(48/289) vs. 32.22(29/90), p = 0.001) than the other two groups. Therefore, it can be concluded that all three protocols can be used in patients over 35 years old with poor ovarian response. However, if patients require more frozen-thawed embryo transfers to achieve better cumulative live birth rates, the modified GnRH agonist protocol may be the preferable option.

Inverse lithography physics-informed deep neural level set for mask optimization.

As the feature size of integrated circuits continues to decrease, optical proximity correction (OPC) has emerged as a crucial resolution enhancement technology for ensuring high printability in the lithography process. Recently, level set-based inverse lithography technology (ILT) has drawn considerable attention as a promising OPC solution, showcasing its powerful pattern fidelity, especially in advanced processing. However, the massive computational time consumption of ILT limits its applicability to mainly correcting partial layers and hotspot regions. Deep learning (DL) methods have shown great potential in accelerating ILT. However, the lack of domain knowledge of inverse lithography limits the ability of DL-based algorithms in process window (PW) enhancement, etc. In this paper, we propose an inverse lithography physics-informed deep neural level set (ILDLS) approach for mask optimization. This approach utilizes level set-based ILT as a layer within the DL framework and iteratively conducts mask prediction and correction to significantly enhance printability and PW in comparison with results from pure DL and ILT. With this approach, the computational efficiency is significantly improved compared with ILT. By gearing up DL with the knowledge of inverse lithography physics, ILDLS provides a new and efficient mask optimization solution.