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Hesperidin is a dihydroflavonoids, accounting for more than 50% of the total flavonoids in Citri Reticulatae Pericarpium (CRP) of traditional Chinese medicine. It is an effective antioxidant and free radical scavenger that has anti-inflammatory, antiviral and hypoglycemic properties. The latest studies reported that hesperidin has a potential for novel coronavirus resistance. However, little is known about the synthesis regulation and accumulation site of hesperidin in plants. In this study, hesperidin synthase gene Crc1,6RhaT was cloned, and the protein can be completely transformed flavanone-7-O-glucoside into hesperidin in vitro and in vivo. Studies on biological characteristics of ovary walls and exocarps showed that the relative expression levels of the Crc1,6RhaT gene and protein decreased gradually with the development of citrus fruits, and the relative content of hesperidin firstly increased, then sequentially decreased. In situ hybridization results further revealed that Crc1,6RhaT transcription was mainly concentrated in the secretory cavity cells, which are revealed to be the site of flavonoid synthesis. Immunocytochemistry localization results showed that the Crc1,6RhaT was mainly located in the endoplasmic reticulum, nucleus and vacuole of secretory cells. We inferred that the Crc1,6RhaT was synthesized in the endoplasmic reticulum, then was transported into the vacuoles through enlarged vesicles at the end of the endoplasmic reticulum. Our results not only revealed that Crc1,6RhaT may be involved in the synthesis of hesperidin of the main bioactive substance in the medicinal plant Citrus reticulata ‘Chachi’ fruit, but also provided novel insights into the main subcellular sites of hesperidin biosynthesis in vacuoles.

Abstract Due to the rapid development of stem cell technology, there have been tremendous advances in molecular biological and pathological research, cell therapy as well as organoid technologies over the past decades. Advances in genome editing technology, particularly the discovery of clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-related protein 9 (Cas9), have further facilitated the rapid development of stem cell researches. The CRISPR-Cas9 technology now goes beyond creating single gene editing to enable the inhibition or activation of endogenous gene loci by fusing inhibitory (CRISPRi) or activating (CRISPRa) domains with deactivated Cas9 proteins (dCas9). These tools have been utilized in genome-scale CRISPRi/a screen to recognize hereditary modifiers that are synergistic or opposing to malady mutations in an orderly and fair manner, thereby identifying illness mechanisms and discovering novel restorative targets to accelerate medicinal discovery investigation. However, the application of this technique is still relatively rare in stem cell research. There are numerous specialized challenges in applying large-scale useful genomics approaches to differentiated stem cell populations. Here, we present the first comprehensive review on CRISPR-based functional genomics screening in the field of stem cells, as well as practical considerations implemented in a range of scenarios, and exploration of the insights of CRISPR-based screen into cell fates, disease mechanisms and cell treatments in stem cell models. This review will broadly benefit scientists, engineers and medical practitioners in the areas of stem cell research.

Abstract Background Continuous peripheral nerve blocks are widely used for anesthesia and postoperative analgesia in lower limb surgeries. The authors aimed to develop a novel continuous sacral plexus block procedure for analgesia during total knee arthroplasty. Methods The study comprised two stages. In Stage I, the authors built upon previous theories and technological innovations to develop a novel continuous sacral plexus block method, ultrasound-guided continuous parasacral ischial plane block (UGCPIPB) and subsequently conducted a proof-of-concept study to assess its effectiveness and feasibility. Stage II involved a historical control study to compare clinical outcomes between patients undergoing this new procedure and those receiving the conventional procedure. Results The study observed a 90% success rate in catheter placement. On postoperative day (POD) 1, POD2, and POD3, the median visual analog scale (VAS) scores were 3 (range, 1.5–3.5), 2.5 (1.6–3.2), and 2.7 (1.3–3.4), respectively. Furthermore, 96.3% of the catheters remained in place until POD3, as confirmed by ultrasound. The study revealed a significant increase in skin temperature and peak systolic velocity of the anterior tibial artery on the blocked side compared with those on the non-blocked side. Complications included catheter clogging in one patient and leakage at the insertion site in two patients. In Stage II, the novel technique was found to be more successful than conventional techniques, with a lower catheter displacement rate than the conventional procedure for continuous sciatic nerve block. Conclusion UGCPIPB proved to be an effective procedure and safe for analgesia in total knee arthroplasty. Chinese Clinical Trial Registry Number ChiCTR2300068902.

BackgroundThe aim of this study was to investigate the accuracy of self-tested SARS-CoV-2 rapid antigen tests.MethodsDatabases of Pubmed, Embase, and Cochrane Library were searched for original studies investigating accuracy of self-tested SARS-CoV-2 rapid antigen tests, with RT-PCR as “gold standard.”ResultsForty-five eligible studies were found after database searching and screening using pre-defined criteria. The accuracy results from 50,897 suspected COVID-19 patients were pooled, and the overall sensitivity, specificity and diagnostic odds ratio were 0.77, 1.00, and 625.95, respectively. Subgroup analysis showed higher sensitivity of rapid antigen tests in subgroups of Abbott Panbio, self-collected nasal swab samples, and use of nasopharyngeal or oropharyngeal swab and lower Ct cutoff value in RT-PCR.ConclusionFully self-performed SARS-CoV-2 rapid antigen tests showed overall high accuracy compared to “gold standard,” and are reliable surrogates for the standard test of COVID-19 using nasopharyngeal or oropharyngeal samples and RT-PCR.

Ambient air pollution has been reported to be a risk factor for hypertensive disorders of pregnancy (HDP). Past studies have reported supportive evidence, but evidence from China is scarce and does not integrate the different periods of the pregnancy course. In this study, 1945 pregnant women with HDP and healthy pregnancies between 2016 and 2022 from the Renmin Hospital of Wuhan University registry network database were analysed. The geographic information, biological information and demographic information of the case were fused in the analysis. Machine learning methods were used to obtain the weight of the variable. Then, we used the generalized linear mixed model to evaluate the relationship between increased exposure to each pollutant at different periods of HDP and examined it in different groups. The results showed that SO2 had the predominate impact (12.65 %) on HDP compared with other air pollutants. SO2 exposure was associated with an increased risk of HDP. Increased unit SO2 concentrations were accompanied by an increased risk of HDP (OR = 1.33, 95 % CI: 1.13, 1.566), and the susceptible window for this effect was mainly in the first trimester (OR = 1.242, 95 % CI: 1.092, 1.412). In addition, SO2 exposure was associated with an increased risk of HDP in urban maternity (OR = 1.356, 95 % CI: 1.112, 1.653), obese maternity (OR = 3.58, 95 % CI: 1.608, 7.971), no higher education maternity (OR = 1.348, 95 % CI: 1.065, 1.706), nonzero delivery maternity (OR = 1.981, 95 % CI: 1.439, 2.725), maternal with first time maternity (OR = 1.247, 95 % CI: 1.007, 1.544) and other groups. In summary, SO2 exposure in early pregnancy is one of the risk factors for HDP, and the increased risk of HDP due to increased SO2 exposure may be more pronounced in obese, urban, low-education, and nonzero delivery populations.

Abstract The Yangtze River is one of the largest riverine ecosystems in the world and is a biodiversity hotspot. In recent years, this river ecosystem has undergone rapid habitat deterioration due to anthropogenic disturbances, leading to a decrease in freshwater biodiversity. Owing to these anthropogenic impacts, the Chinese government imposed a “Ten‐year fishing ban” (TYFB) in the Yangtze River and its tributaries. Ecological changes associated with this decision have not been documented to evaluate the level of success. This study evaluates the success of the TYFB by analyzing the changes in phytoplankton communities and comparing them to periods before the TYFB was imposed. A total of 325 phytoplankton species belonging to 7 phyla and 103 genera dominated by Chlorophyceae and Bacillariophyceae were identified. Species diversity according to the Shannon–Wiener ranged between 1.19 and 3.00. The results indicated that phytoplankton diversity increased, while both density and biomass decreased after the TYFB. The health of the aquatic ecosystem appeared to have improved after the TYFB, as indicated by the phytoplankton‐based index of biotic integrity. Significant seasonal and spatial differences were found among the number of species, density, and biomass of phytoplankton, where these differences were correlated with pH, water depth, chlorophyll‐a, permanganate index, transparency, copper, ammonia nitrogen, and total phosphorus based on redundancy analysis. Results from this study indicate that the TYFB played an important role in the restoration of freshwater ecosystem in the Yangtze River and its tributaries.

BackgroundIn recent years, the prevalence of childhood obesity has escalated alarmingly, posing significant threats to the physical and mental well-being of children, with an elevated likelihood of persisting into adulthood. Notably, recent investigations have uncovered a profound association between intestinal microbiota, a crucial component of the internal milieu, and childhood obesity. Disturbances in intestinal microbiota and their by-products are now understood to be profoundly intertwined with the evolutionary pathway of childhood obesity. Bibliometric analysis offers a deep understanding of the current research landscape, so we apply it to a review of the emerging trends and patterns between childhood obesity and gut microbiota.Materials and methodsWe conducted a rigorous and extensive search of the Web of Science (WoS) Core Collection database, spanning the years from 1900 to 2023, to analyze scholarly articles pertaining to childhood obesity and gut microbiota. Utilizing VOSviewer, CiteSpace, the R package “bibliometrix,” and the online bibliometric analysis platform (https://bibliometric.com/), we delved into the intricate details of research hotspots, academic collaborations, and emerging trends within this domain.ResultsThe exhaustive search encompassed the globe, uncovering a cumulative total of 1,384 pertinent studies originating from 429 nations. The results were compelling, revealing a profound influence exerted by the United States and China in this specific field of research. Furthermore, it was observed that the volume of scholarly works pertaining to childhood obesity and gut microbiota is steadily growing year on year. The current hot topics in this field include “abuse,” “maltreatment,” “adverse childhood experiences,” “students,” and “food addiction”.ConclusionThis comprehensive review offers a meticulous exploration of the evolving trends and emerging research agendas pertaining to childhood obesity and gut microbiota over the past two decades. It strives to equip researchers with a thorough understanding of the key nations, institutions, journals, and potential collaborators in these specialized fields. Additionally, it sheds light on the current frontiers of research and strategic avenues for further exploration, thus serving as an invaluable resource for scholars delving deeper into the intricacies of childhood obesity and the gut microbiome.

Abstract Typhoon disasters undergo a complex evolutionary process influenced by temporal changes, and investigating this process constitutes the central focus of geographical research. As a key node within the typhoon disaster process, the state serves as the foundation for gauging the dynamics of the disaster. The majority of current approaches to disaster information extraction rely on event extraction methods to acquire fundamental elements, including disaster-causing factors, disaster-bearing bodies, disaster-pregnant environment and the extent of damage. Due to the dispersion of various disaster information and the diversity of time and space, it is a challenge for supporting the analysis of the typhoon disaster process. In this paper, a typhoon disaster state information extraction (TDSIE) method for Chinese texts is proposed, which aims to facilitate the systematic integration of fragmented typhoon disaster information. First, the integration of part-of-speech tagging with spatio-temporal information extraction is employed to achieve the tagging of typhoon disaster texts. Second, within the framework of spatio-temporal semantic units, the typhoon disaster semantic vector is constructed to facilitate the identification of information elements of typhoon disaster states. Third, co-referential state information fusion is performed based on spatio-temporal cues. Experimental analysis, conducted using online news as the data source, reveals that the TDSIE achieves precision and recall rates consistently surpassing 85%. The typhoon disaster state information derived from the TDSIE allows for the analysis of spatio-temporal patterns, evolutionary characteristics, and activity modes of typhoon disasters across various scales. Therefore, TDSIE serves as valuable support for investigating the inherent process properties of typhoon disasters.

Abstract. Background:. Pulmonary arterial hypertension (PAH) is characterized by excessive proliferation of small pulmonary arterial vascular smooth muscle cells (PASMCs), endothelial dysfunction, and extracellular matrix remodeling. G protein-coupled receptor kinase 2 (GRK2) plays an important role in the maintenance of vascular tone and blood flow. However, the role of GRK2 in the pathogenesis of PAH is unknown. Methods:. GRK2 levels were detected in lung tissues from healthy people and PAH patients. C57BL/6 mice, vascular smooth muscle cell-specific Grk2-knockout mice (Grk2ΔSM22), and littermate controls (Grk2flox/flox) were grouped into control and hypoxia mice (n = 8). Pulmonary hypertension (PH) was induced by exposure to chronic hypoxia (10%) combined with injection of the SU5416 (cHx/SU). The expression levels of GRK2 and Yes-associated protein (YAP) in pulmonary arteries and PASMCs were detected by Western blotting and immunofluorescence staining. The mRNA expression levels of Grk2 and Yes-associated protein (YAP) in PASMCs were quantified with real-time polymerase chain reaction (RT-PCR). Wound-healing assay, 3-(4,5)-dimethylthiahiazo (-z-y1)-3,5-di-phenytetrazoliumromide (MTT) assay, and 5-Ethynyl-2′-deoxyuridine (EdU) staining were performed to evaluate the proliferation and migration of PASMCs. Meanwhile, the interaction among proteins was detected by immunoprecipitation assays. Results:. The expression levels of GRK2 were upregulated in the pulmonary arteries of patients with PAH and the lungs of PH mice. Moreover, cHx/SU-induced PH was attenuated in Grk2ΔSM22 mice compared with littermate controls. The amelioration of PH in Grk2ΔSM22 mice was accompanied by reduced pulmonary vascular remodeling. In vitro study further confirmed that GRK2 knock-down significantly altered hypoxia-induced PASMCs proliferation and migration, whereas this effect was severely intensified by overexpression of GRK2. We also identified that GRK2 promoted YAP expression and nuclear translocation in PASMCs, resulting in excessive PASMCs proliferation and migration. Furthermore, GRK2 is stabilized by inhibiting phosphorylating GRK2 on Tyr86 and subsequently activating ubiquitylation under hypoxic conditions. Conclusion:. Our findings suggest that GRK2 plays a critical role in the pathogenesis of PAH, via regulating YAP expression and nuclear translocation. Therefore, GRK2 serves as a novel therapeutic target for PAH treatment.

Background: Although genome-wide association studies (GWAS) have identified 14 loci associated with frailty index (FI) susceptibility, the underlying causative genes and biological mechanisms remain elusive.Methods: A cross-tissue transcriptome-wide association study (TWAS) was conducted utilizing the Unified Test for Molecular Markers (UTMOST), which integrates GWAS summary statistics from 164,610 individuals of European ancestry and 10,616 Swedish participants, alongside gene expression matrices from the Genotype-Tissue Expression (GTEx) Project. Validation of the significant genes was performed through three distinct methods: FUSION, FOCUS, and Multiple Marker Analysis of Genome-wide Annotation (MAGMA). Exploration of tissue and functional enrichment for FI-associated SNPs was conducted using MAGMA. Conditional and joint analyses, along with fine mapping, were employed to enhance our understanding of FI’s genetic architecture. Mendelian randomization was employed to ascertain causal relationships between significant genes and FI, and co-localization analysis was utilized to investigate shared SNPs between significant genes and FI.Results: In this study, two novel susceptibility genes associated with the risk of FI were identified through the application of four TWAS methods. Mendelian randomization demonstrated that HTT may elevate the risk of developing frailty, whereas LRPPRC could offer protection against the onset of frailty. Additionally, co-localization analysis identified a shared SNP between LRPPRC and FI. Tissue enrichment analyses revealed that genomic regions linked to SNPs associated with frailty were predominantly enriched in various brain regions, including the frontal cortex, cerebral cortex, and cerebellar hemispheres. Conditional, combined analyses, and fine mapping collectively identified two genetic regions associated with frailty: 2p21 and 4q16.3. Functional enrichment analyses revealed that the pathways associated with frailty were primarily related to the MHC complex, PD-1 signaling, cognition, inflammatory response to antigenic stimuli, and the production of second messenger molecules.Conclusion: This investigation uncovers two newly identified genes with forecasted expression levels associated with the risk of FI, offering new perspectives on the genetic architecture underlying FI.

ObjectivePseudomonas aeruginosa has strong drug resistance and can tolerate a variety of antibiotics, which is a major problem in the management of antibiotic-resistant infections. Direct prediction of multi-drug resistance (MDR) resistance phenotypes of P. aeruginosa isolates and clinical samples by genotype is helpful for timely antibiotic treatment.MethodsIn the study, whole genome sequencing (WGS) data of 494 P. aeruginosa isolates were used to screen key anti-microbial resistance (AMR)-associated genes related to imipenem (IPM), meropenem (MEM), piperacillin/tazobactam (TZP), and levofloxacin (LVFX) resistance in P. aeruginosa by comparing genes with copy number differences between resistance and sensitive strains. Subsequently, for the direct prediction of the resistance of P. aeruginosa to four antibiotics by the AMR-associated features screened, we collected 74 P. aeruginosa positive sputum samples to sequence by metagenomics next-generation sequencing (mNGS), of which 1 sample with low quality was eliminated. Then, we constructed the resistance prediction model.ResultsWe identified 93, 88, 80, 140 AMR-associated features for IPM, MEM, TZP, and LVFX resistance in P. aeruginosa. The relative abundance of AMR-associated genes was obtained by matching mNGS and WGS data. The top 20 features with importance degree for IPM, MEM, TZP, and LVFX resistance were used to model, respectively. Then, we used the random forest algorithm to construct resistance prediction models of P. aeruginosa, in which the areas under the curves of the IPM, MEM, TZP, and LVFX resistance prediction models were all greater than 0.8, suggesting these resistance prediction models had good performance.ConclusionIn summary, mNGS can predict the resistance of P. aeruginosa by directly detecting AMR-associated genes, which provides a reference for rapid clinical detection of drug resistance of pathogenic bacteria.

Abstract Entanglement entropy is a fundamental concept with rising importance in various fields ranging from quantum information science, black holes to materials science. In complex materials and systems, entanglement entropy provides insight into the collective degrees of freedom that underlie the systems’ complex behaviours. As well-known predictions, the entanglement entropy exhibits area laws for systems with gapped excitations, whereas it follows the Gioev-Klich-Widom scaling law in gapless fermion systems. However, many of these fundamental predictions have not yet been confirmed in experiments due to the difficulties in measuring entanglement entropy in physical systems. Here, we report the experimental verification of the above predictions by probing the nonlocal correlations in phononic systems. We obtain the entanglement entropy and entanglement spectrum for phononic systems with the fermion filling analog. With these measurements, we verify the Gioev-Klich-Widom scaling law. We further observe the salient signatures of topological phases in entanglement entropy and entanglement spectrum.

The carrying-soil effect is an important factor affecting the success or failure of rectangular pipe jacking construction. Because it is difficult to explore the dynamic evolution process of the carrying-soil effect in the field test, this paper relies on the pipe jacking project of a comprehensive pipe gallery in Suzhou City, and uses ABAQUS 2021 finite element software to simulate the jacking process of rectangular pipe jacking. Based on the theory of plastic mechanics of rock and soil and the related research and application status, the equivalent plastic strain index is introduced as the basis for judging the failure boundary of soil in the numerical simulation results, and the boundary between the carrying-soil area and the surrounding soil is determined, that is, the shear fracture surface. According to the principle of plastic potential energy, the development direction of the fracture surface is consistent with the direction of plastic flow, so as to predict the development direction of the boundary of the carrying-soil area. According to the change in the equivalent plastic strain cloud map with the jacking mileage, the evolution process of the carrying-soil effect is clarified, and the dynamic evolution law of the carrying-soil area is revealed, which is of great significance for predicting the disturbance of the surrounding soil during the construction of rectangular pipe jacking and accurately evaluating the environmental effect of the construction.

Abstract Physisorption relying on crystalline porous materials offers prospective avenues for sustainable separation processes, greenhouse gas capture, and energy storage. However, the lack of end-to-end deep learning model for adsorption prediction confines the rapid and precise screen of crystalline porous materials. Here, we present DeepSorption, a spatial atom interaction learning network that realizes accurate, fast, and direct structure-adsorption prediction with only information of atomic coordinate and chemical element types. The breakthrough in prediction is attributed to the awareness of global structure and local spatial atom interactions endowed by the developed Matformer, which provides the intuitive visualization of atomic-level thinking and executing trajectory in crystalline porous materials prediction. Complete adsorption curves prediction could be performed using DeepSorption with a higher accuracy than Grand canonical Monte Carlo simulation and other machine learning models, a 20-35% decline in the mean absolute error compared to graph neural network CGCNN and machine learning models based on descriptors. Since the established direct associations between raw structure and target functions are based on the understanding of the fundamental chemistry of interatomic interactions, the deep learning network is rationally universal in predicting the different physicochemical properties of various crystalline materials.

Abstract As a series of work about 5D (spacetime) topological orders, here we employ the path-integral formalism of 5D topological quantum field theory (TQFT) established in Zhang and Ye, JHEP 04 (2022) 138 to explore non-Abelian fusion rules, hierarchical shrinking rules and quantum dimensions of particle-like, loop-like and membrane-like topological excitations in 5D topological orders. To illustrate, we focus on a prototypical example of twisted BF theories that comprise the twisted topological terms of the BBA type. First, we classify topological excitations by establishing equivalence classes among all gauge-invariant Wilson operators. Then, we compute fusion rules from the path-integral and find that fusion rules may be non-Abelian; that is, the fusion outcome can be a direct sum of distinct excitations. We further compute shrinking rules. Especially, we discover exotic hierarchical structures hidden in shrinking processes of 5D or higher: a membrane is shrunk into particles and loops, and the loops are subsequently shrunk into a direct sum of particles. We obtain the algebraic structure of shrinking coefficients and fusion coefficients. We compute the quantum dimensions of all excitations and find that sphere-like membranes and torus-like membranes differ not only by their shapes but also by their quantum dimensions. We further study the algebraic structure that determines anomaly-free conditions on fusion coefficients and shrinking coefficients. Besides BBA, we explore general properties of all twisted terms in 5D. Together with braiding statistics reported before, the theoretical progress here paves the way toward characterizing and classifying topological orders in higher dimensions where topological excitations consist of both particles and spatially extended objects.

Abstract Background Intraspinal anesthesia poses significant teaching challenges and inadequate teaching resources, which ultimately limit students’ opportunities for practice. To address this issue, we aimed to develop a virtual platform for combined spinal-epidural anesthesia that merges virtual reality technology with haptic feedback technology, while assessing its educational impact and learning outcomes. Methods We utilized MIMICS, 3Ds MAX, and UNITY 3D software to perform 3D reconstruction based on lumbar CT/MRI data from a standard male volunteer. The haptic coefficients were configured on each layer by 20 experienced anesthesiologists in accordance with the Geomagic Touch X force feedback device. A total of 20 anesthesiology interns completed 30 virtual puncture training sessions. Two experienced anesthetists evaluated the efficacy of the platform and the level of mastery achieved using the Global Rating Scale (GRS) and a Checklist score, respectively. Finally, a questionnaire survey was conducted to gather feedback on the virtual platform. Results After the 10th session, the puncture time stabilized at 2.4 min. As the number of sessions increased, the Global Rating Scale (GRS) score stabilized by the 8th session, and the Checklist scores tended to stabilize by the 10th session. Results from questionnaires indicated that over half of the anesthesiology interns (70%) believed that the platform, which exhibited strong repeatability, improved their anatomical recognition and provided a strong sense of breakthrough in identifying the ligamentum flavum. The majority of them (80%) expressed satisfaction with the virtual platform. Conclusions The platform effectively facilitated the acquisition of basic and accurate puncture skills on a virtual patient.

In computer and system sciences, higher-order cellular automata (HOCA) are a type of cellular automata that evolve over multiple time steps and generate complex patterns, which have various applications, such as secret-sharing schemes, data compression, and image encryption. In this paper, we introduce HOCA to quantum many-body physics and construct a series of symmetry-protected topological (SPT) phases of matter, in which symmetries are supported on a great variety of subsystems embbeded in the SPT bulk. We call these phases HOCA-generated SPT (HGSPT) phases. Specifically, we show that HOCA can generate not only well-understood SPTs with symmetries supported on either regular (e.g., linelike subsystems in the two-dimensional cluster model) or fractal subsystems, but also a large class of unexplored SPTs with symmetries supported on more choices of subsystems. One example is mixed-subsystem SPT that has either fractal and linelike subsystem symmetries simultaneously or two distinct types of fractal symmetries simultaneously. Another example is chaotic-subsystem SPT in which chaotic-looking symmetries are significantly different from and thus cannot reduce to fractal or regular subsystem symmetries. We also introduce a new notation system to characterize HGSPTs. We prove that all possible subsystem symmetries in a square lattice can be locally simulated by an HOCA-generated symmetry. As the usual two-point strange correlators are trivial in most HGSPTs, we find that the nontrivial SPT orders can be detected by what we call multi point strange correlators. We propose a universal procedure to design the spatial configuration of the multi point strange correlators for a given HGSPT phase. Specifically, we find deep connections between multi point strange correlators and the spurious topological entanglement entropy (STEE), both exhibiting long-range behavior in a short-range entangled state. Our HOCA approaches and multi point strange correlators pave the way for a unified paradigm to design, classify, and detect phases of matter with symmetries supported on a great variety of subsystems, and also provide potential useful perspective in surpassing the computational irreducibility of HOCA in a quantum mechanical way.

Background: This study aimed to examine the differential variations in the metabolic composition of follicular fluid (FF) among normal-weight patients with polycystic ovary syndrome (PCOS) and controls and to identify potential biomarkers that may offer insights into the early identification and management of these patients. Methods: We collected FF samples from 45 normal-weight women with PCOS and 36 normal-weight controls without PCOS who were undergoing in vitro fertilization–embryo transfer. An untargeted metabolomic study of collected FF from infertile women was performed using high-performance liquid chromatography–tandem spectrometry (LC-MS). The tendency of the two groups to separate was demonstrated through multivariate analysis. Univariate analysis and variable importance in projection were used to screen out differential metabolites. Metabolic pathway analysis was conducted using the Kyoto Encyclopedia of Genes and Genomes (KEGG), and a diagnostic model was established using the random forest algorithm. Results: The metabolomics analysis revealed an increase in the expression of 23 metabolites and a decrease in that of 10 metabolites in the FF of normal-weight women with PCOS. According to the KEGG pathway analysis, these differential metabolites primarily participated in the metabolism of glycerophospholipids and the biosynthesis of steroid hormones. Based on the biomarker combination of the top 10 metabolites, the area under the curve value was 0.805. The concentrations of prostaglandin E2 in the FF of individuals with PCOS exhibited an inverse association with the proportion of high-quality embryos (p < 0.05). Conclusions: Our research identified a distinct metabolic profile of the FF from normal-weight women with PCOS. The results offer a broader comprehension of the pathogenesis and advancement of PCOS, and the detected differential metabolites could be potential biomarkers and targets for the treatment of PCOS.

Visual object tracking is an important technology in camera-based sensor networks, which has a wide range of practicability in auto-drive systems. A transformer is a deep learning model that adopts the mechanism of self-attention, and it differentially weights the significance of each part of the input data. It has been widely applied in the field of visual tracking. Unfortunately, the security of the transformer model is unclear. It causes such transformer-based applications to be exposed to security threats. In this work, the security of the transformer model was investigated with an important component of autonomous driving, i.e., visual tracking. Such deep-learning-based visual tracking is vulnerable to adversarial attacks, and thus, adversarial attacks were implemented as the security threats to conduct the investigation. First, adversarial examples were generated on top of video sequences to degrade the tracking performance, and the frame-by-frame temporal motion was taken into consideration when generating perturbations over the depicted tracking results. Then, the influence of perturbations on performance was sequentially investigated and analyzed. Finally, numerous experiments on OTB100, VOT2018, and GOT-10k data sets demonstrated that the executed adversarial examples were effective on the performance drops of the transformer-based visual tracking. White-box attacks showed the highest effectiveness, where the attack success rates exceeded 90% against transformer-based trackers.

Abstract Background Marine Lenhart syndrome is a rare disease and causes refractory hyperthyroidism. So far, little evidence on the combination of both Marine Lenhart syndrome and Hashimoto's thyroiditis is available. We suspect that Marine Lenhart syndrome when combined with Hashimoto's thyroiditis might have its particular features, which are not exactly the same as those of the isolated Marine Lenhart syndrome. Case presentation A 56-year-old middle-aged man presented with recurrent hyperthyroidism, and Graves' disease combined with Hashimoto's thyroiditis was considered. Radionuclide imaging showed a hot nodule, but ultrasonography suggested the possibility of malignancy with a category of 4B according to the Chinese-Thyroid Imaging-Reporting and Data System (C-TIRADS) model. Fine needle aspiration cytology (FNAC) revealed eosinophilic follicular lesions with papillary features, and prompted that papillary thyroid carcinoma could not be excluded. Partial thyroidectomy was performed and the nodule was proven to be benign by histopathology. The final diagnosis was atypical Marine Lenhart syndrome with Hashimoto's thyroiditis. Conclusions Marine Lenhart syndrome combined with Hashimoto's thyroiditis has its particular characteristics, showing some signs mimicking malignancy. Limitations of ultrasonography and FNAC in diagnosis should be noted in these scenarios.

Highlights Cerium methacrylate was prepared and ingeniously used as curing agent for epoxy, surface modifier for BN, and effective corrosion inhibitor. The coating integrates high thermal conductivity (4.29 W m−1 K−1), corrosion resistance (low-frequency impedance is 5.1 × 1011 Ω cm2 at 181 day), hydrophobicity (WCA: ~ 148.35° and WSA: ~ 20°), temperature resistance and adhesion. The coating can extend service life of metal materials without sacrificing their inherent heat conduction property.

BackgroundLockdowns in COVID-19 pandemic led to less physical activity and more intake of unhealthy food in children. The aim of this study was to investigate the negative impact of major lockdowns on the growth of children aged 3-6 years during COVID-19 pandemic period.MethodsPhysical examination results in 2019 to 2022 from 5834 eligible children (2972 males and 2862 females) from Southwestern China who were 3 years old in 2019 were retrospectively collected. Height and weight data points were extracted from the results, and percentiles of height (height%), weight (weight%), and BMI (BMI%), and rates of overweight and obesity were calculated and compared between different years during the pandemic.ResultsAfter analyzing the 15404 growth data points from 5834 children, a slowly increasing trend of height% from 2019 to 2022 was observed. Weight%, BMI%, overweight rate, obesity rate, and combined overweight and obesity rate had two peaks in 2020 and 2022 when major lockdowns were adopted and a drop in between (year 2021), except for obesity rate which did not drop in 2021. Similar results were shown after stratification by gender.ConclusionThe lockdowns in COVID-19 pandemic promoted obesity of kindergarten children, but did not show any negative impact on their height growth possibly due to over-nutrition of children during lockdowns. More efforts need to be made to limit the increase of obesity rate in kindergarten children during possible future lockdowns.

The rapid advancement of modern technology has significantly driven progress in various IT-related activities, resulting in a substantial increase in internet penetration rates, particularly among college students. The utilization of the internet has become one of the most essential tools in our modern society. However, internet addiction (IA) has emerged as a serious concern, particularly among college students, adversely affecting academic performance and having significant psychological and psychiatric implications. The aim of the current study was to determine the impact of physical exercise, gender and academic year on IA among college students. In the present study, we investigated internet usage, engagement in sports activities, and academic performance among college students from Western, Middle, and Eastern regions of Chinese universities. It’s noteworthy that most of the respondents were freshmen. Our findings indicate that freshmen students were more susceptible to experiencing IA. Approximately 75% of students engaged in leisure sports activities, revealing an inverse correlation between sports activity and IA. This correlation aligns with the level of sports involvement, emphasizing the potential benefits of physical activity in mitigating IA. However, our study did not uncover any correlation between geographic location and the occurrence of IA, nor did it find differences between medical and non-medical students. Furthermore, our study revealed no significant variations in IA among students from different ethnic backgrounds. The underlying mechanism of IA is being currently determined. Our data suggest that physical exercise, gender, and academic year have a significant impact on IA among college students.

ABSTRACTSpatial relation extraction is the process of identifying geographic entities from text and determining their corresponding spatial relations. Traditional spatial relation extraction mainly uses rule-based pattern matching, supervised learning-based or unsupervised learning-based methods. However, these methods suffer from poor time-sensitive, high labor cost and high dependence on large-scale data. With the development of pre-trained language models greatly alleviating the shortcomings of traditional methods, supervised learning methods incorporating pre-trained language models have become the mainstream relation extraction methods. Pipeline extraction and joint extraction, as the two most dominant ideas of relation extraction, both have obtained good performance on different datasets, and whether to share the contextual information of entities and relations is the main differences between the two ideas. In this paper, we compare the performance of two ideas oriented to spatial relation extraction based on Chinese corpus data in the field of geography and verify which method based on pre-trained language models is more suitable for Chinese spatial relation extraction. We fine-tuned the hyperparameters of the two models to optimize the extraction accuracy before the comparison experiments. The results of the comparison experiments show that pipeline extraction performs better than joint extraction of spatial relation extraction for Chinese text data with sentence granularity, because different tasks have different focus on contextual information, and it is difficult to take account into the needs of both tasks by sharing contextual information. In addition, we further compare the performance of the two models with the rule-based template approach in extracting topological, directional and distance relations, summarize the shortcomings of this experiment and provide an outlook for future work.

Abstract Background Rheumatoid arthritis, metabolic syndrome (MS) and cardiovascular disease (CVD) are mutually connected. We aim to investigate the association between rheumatoid factor (RF) and MS in general population, explore the potential value of RF for assessment of metabolic status, and further provide a reference to the establishment of CVD primary prevention for this population. Methods We assessed the health check-up subjects, accordance with the inclusive criteria, from 1 January 2015 to 31 October 2021 in a large refereed general hospital, in this retrospective study. Subjects were categorized into four groups according to their levels of RF. Multivariate logistic regression models along with the Odds ratio (OR) and Confidence interval (CI) values were used to measure the association between RF and MS. Results A total of 13,690 subjects were analyzed. Prevalence of MS increased with RF level (P for trend

The development of temperature control load is inevitable for people to improve the quality of life, but it has the same characteristics as the output of wind power generation, that is, randomness and intermittence. Therefore, the continuous access of temperature control load has an unprecedented challenge to the stability of power grid. However, the instability of the power grid caused by the input of wind power can be balanced by the temperature control load acting on the power grid. The research direction of this paper is the regulation of temperature controlled load household air source heat pump equipment on the power grid on the load side, which is constrained by meeting the user’s comfort. It is intended to achieve the goal of cutting peak and filling valley for the power grid side and reducing the wind rejection rate. The user side gets the economic compensation to cooperate with the power grid dispatching. At the same time, the power grid side improves the economic benefits by reducing the peak valley difference and reducing the occurrence of fan suspension. The main research contents are as follows: the thermodynamic equivalent model of single air source heat pump is established, and the aggregation model is established combined with Monte Carlo method. The simulation analysis shows that the air source heat pump group can participate in the regulation of load side; Using the prediction model of wind power based on meta learning, combined with single time series model and single linear regression model, the wind power is reasonably predicted; The multi-dimensional state queue method is used to improve the load characteristics and reduce the air rejection rate on the premise of meeting the user comfort; This paper expounds the distribution network level load regulation system, establishes the hierarchical load control structure, and makes the two-way interaction between the family compliance control system and the power grid a reality. In order to study the influence of user selection on regulation effect, according to the differences of user needs, we established three regulation strategies. Scheme A can achieve the most ideal regulation effect, and scheme B is slightly worse than scheme A. The most ideal control effect parameters can be obtained by scheme A, and the worst control effect parameters can be obtained by scheme C. Comparing the regulation effect parameters after scheme a and scheme C, based on the parameters of scheme C, the peak valley difference of scheme A is reduced by 18.30%, the peak to average ratio is reduced by 17.61% and the load variance is reduced by 18.12%. It is proved that the user can reduce the peak valley difference by using scheme A. Comparing the regulation effect parameters after scheme B and scheme C, compared with scheme C, the peak valley difference of scheme B is reduced by 11.80%, the peak to average ratio is reduced by 11.81%, and the load variance is reduced by 14.77%. It is proved that the regulation effect of scheme B can be reduced, but the effect is not as good as scheme A.

After the large-scale wind power airport is connected to the power grid, the wind farm cannot actively provide inertia support to the system, resulting in a significant decline in the inertia of the power system and weakening the frequency regulation ability of the power system. In order to explore the measurement and evaluation of inertia constant after large-scale wind farm is connected to the power grid. This paper first introduces the composition of inertia of power system at the present stage, then expounds the response process of inertia to disturbance after large disturbance of power system, and then deduces the power system model with large-scale wind power access through the analysis of traditional inertia measurement. Finally, the simulation model is used to compare the traditional measurement estimation with this paper. The maximum error is 9.18%, the minimum error can reach 2.4%, and the minimum error of the traditional estimation method can also reach 18%. Compared with traditional methods, it can be concluded that the error between the theoretical value of inertial time constant and the estimation of inertial time constant of the method described in this paper is significantly reduced.

To improve the accuracy of the evaluation of the equivalent inertia of a power system, a method for evaluating the equivalent inertia level of a power system based on an intelligent optimization algorithm is proposed. The proposed method constructs the objective function based on different degrees of system perturbation, ignores the frequency characteristics of the load, constructs the objective function with the generator swing equation, solves the inertia time constant of each generator using the intelligent optimization algorithm, and then evaluates the equivalent inertia of the whole system, eliminates the influence of inconsistent frequency change rate under perturbation on the system equivalent inertia evaluation, and thus obtains a more accurate system equivalent inertia evaluation, experimental result shows the evaluation accuracy can be improved by 10.79% and 3.48% respectively compared with other two comparison method.

The “carbon peaking and carbon neutralization” scheme formulated to solve the power energy shortage makes the new energy units incorporated into the power grid on a large scale. The randomness and volatility caused by the high proportion of new energy access have a certain impact on the dynamic stability of the power grid. Based on the dynamic stability theory, this paper applies the dual-stream CNN algorithm in the deep learning technology to model, takes the power of each node and line as the input and the key eigenvalue as the output, quickly identifies the main oscillation modes of the power system, makes a qualitative evaluation. Combined with the actual power grid analysis, the interval oscillation frequencies of the system are 0.57 Hz and 0.53 Hz respectively, which belong to strongly damped oscillation and can be quickly subsided after being excited. It can be concluded that the dual-stream CNN algorithm can provide reliable technical support for subsequent dispatching operation, and is conducive to improving the safe and stable operation level of power system.

Abstract Demyelinating disorders are among the most common and debilitating diseases in neurology. Canavan disease (CD) is a lethal demyelinating disease caused by mutation of the aspartoacylase (ASPA) gene, which leads to the accumulation of its substrate N‐acetyl‐l‐aspartate (NAA), and consequently demyelination and vacuolation in the brain. In this study, hypoimmunogenic human induced pluripotent stem cell (iPSC)‐derived oligodendrocyte progenitor cells (OPC) are developed from a healthy donor as an “off‐the‐shelf” cell therapy. Hypoimmunogenic iPSCs are generated through CRISPR/Cas9 editing of the human leukocyte antigen (HLA) molecules in healthy donor‐derived iPSCs and differentiated into OPCs. The OPCs are engrafted into the brains of CD (nur7) mice and exhibit widespread distribution in the brain. The engrafted OPCs mature into oligodendrocytes that express the endogenous wildtype ASPA gene. Consequently, the transplanted mice exhibit elevated human ASPA expression and enzymatic activity and reduced NAA level in the brain. The transplanted OPCs are able to rescue major pathological features of CD, including defective myelination, extensive vacuolation, and motor function deficits. Moreover, the hypoimmunogenic OPCs exhibit low immunogenicity both in vitro and in vivo. The hypoimmunogenic OPCs can be used as “off‐the‐shelf” universal donor cells to treat various CD patients and many other demyelinating disorders, especially autoimmune demyelinating diseases, such as multiple sclerosis.

BackgroundThe aim of this study was to investigate the diagnostic accuracy of KRAS mutation detection using plasma sample of patients with non-small cell lung cancer (NSCLC).MethodsDatabases of Pubmed, Embase, Cochrane Library, and Web of Science were searched for studies detecting KRAS mutation in paired tissue and plasma samples of patients with NSCLC. Data were extracted from each eligible study and analyzed using MetaDiSc and STATA.ResultsAfter database searching and screening of the studies with pre-defined criteria, 43 eligible studies were identified and relevant data were extracted. After pooling the accuracy data from 3341 patients, the pooled sensitivity, specificity and diagnostic odds ratio were 71%, 94%, and 59.28, respectively. Area under curve of summary receiver operating characteristic curve was 0.8883. Subgroup analysis revealed that next-generation sequencing outperformed PCR-based techniques in detecting KRAS mutation using plasma sample of patients with NSCLC, with sensitivity, specificity, and diagnostic odds ratio of 73%, 94%, and 82.60, respectively.ConclusionCompared to paired tumor tissue sample, plasma sample showed overall good performance in detecting KRAS mutation in patients with NSCLC, which could serve as good surrogate when tissue samples are not available.

An economically feasible integrated navigation algorithm is designed for deep-sea human-occupied vehicles(HOV) operating near the seafloor. The algorithm utilizes the Doppler velocity log and a strapped-down compass carried by the HOV to form a dead reckoning(DR) system. A four-dimensional Kalman filter is designed to integrate DR with the position information provided by an ultra-short baseline(USBL) acoustic positioning system to constitute a DR/USBL integrated navigation system. Considering that the actual measurements of the USBL usually contain a large number of outliers with few missing values, an online data-cleaning scheme using DR is designed. This design is robust and can provide continuous and consistent measurements for DR/USBL. Finally, semi-physical simulation results based on sea trial data show that the DR/USBL integrated navigation system can effectively integrate the advantages of the two systems to provide smoother and more accurate positioning information; the positioning error is within 25 m.

Targeting cancer-associated metabolism is evolving as a promising approach for cancer therapy. Here, the authors generate cancer cell-membrane encapsulated nanoparticles to induce cell cycle arrest and cytotoxicity in lactate-high cancer cells, reducing tumourigensis in glioblastoma cell-line and patient-derived models.

Abstract Due to the difficulty in sampling of metastatic tumors, patient selection is commonly based on results of primary tumor samples when metastatic samples are not available. However, due to tumor heterogeneity, metastatic tumors may be different from primary tumors in their phenotypes. The aim of this study was to investigate the expression of EGFR, HER2, and HER3 between primary and lymph node metastatic lesions of colorectal cancer. Paired primary tumors and lymph node metastases from 79 patients with colorectal cancer were retrospectively collected and analyzed for EGFR, HER2, and HER3 expression. High EGFR, HER2, and HER3 expression (2+ and 3+) was found in 64.2%, 66.0%, and 85.0% of primary tumors, and 56.8%, 46.0%, and 76.0% of lymph node metastases, respectively. Correlation rates between primary and metastatic lesions were 67.1%, 63.3%, and 74.7% for EGFR, HER2, and HER3, respectively. Stage IV tumors (with distant metastasis) had higher correlation rates of HER2 expression compared to stage III tumors (without distant metastasis) (P = 0.050). Moderate correlation rates in EGFR, HER2, and HER3 expression were observed between primary and metastatic lesions of colorectal cancer. Tumor stage or existence of distant metastasis could serve as potential predictive markers for the correlation of HER2 expression between primary tumors and lymph node metastases of colorectal cancer.

We present the experimental realization of spectrally tunable, ultrashort, quasi-monochromatic extreme ultraviolet (XUV) pulses generated at 100 kHz repetition rate in a user-oriented gas high harmonic generation beamline of the Extreme Light Infrastructure—Attosecond Light Pulse Source facility. Versatile spectral and temporal shaping of the XUV pulses is accomplished with a double-grating, time-delay compensated monochromator accommodating the two composing stages in a novel, asymmetrical geometry. This configuration supports the achievement of high monochromatic XUV flux (2.8 ± 0.9 × 1010 photons/s at 39.7 eV selected with 700 meV full width at half maximum bandwidth) combined with ultrashort pulse duration (4.0 ± 0.2 fs using 12.1 ± 0.6 fs driving pulses) and small spot size (sub-100 µm). Focusability, spectral bandwidth, and overall photon flux of the produced radiation were investigated, covering a wide range of instrumental configurations. Moreover, complete temporal (intensity and phase) characterization of the few-femtosecond monochromatic XUV pulses—a goal that is difficult to achieve by conventional reconstruction techniques—has been realized using a ptychographic algorithm on experimentally recorded XUV-infrared pump–probe traces. The presented results contribute to in situ, time-resolved experiments, accessing direct information on the electronic structure dynamics of novel target materials.

Tea consumption has been linked to a decreased risk of cardiovascular disease (CVD) mortality, which imposes a heavy burden on the healthcare system; however, which components in tea cause this beneficial effect is not fully understood. Here we uncovered a cystatin (namely CsCPI1), which is a cysteine proteinase inhibitor (CPI) of the tea plant (Camellia sinensis) that promotes antithrombotic activity. Since thrombosis is a common pathogenesis of fatal CVDs, we investigated the effects of CsCPI1, which showed good therapeutic effects in mouse models of thrombotic disease and ischemic stroke. CsCPI1 significantly increases endothelial cell production of nitric oxide (NO) and inhibits platelet aggregation. Notably, CsCPI1 exhibited no cytotoxicity or resistance to pH and temperature changes, which indicates that CsCPI1 might be a potent antithrombotic agent that contributes to the therapeutic effects of tea consumption against CVD. Specifically, the antithrombotic effects of CsCPI1 are distinct from the classical function of plant cystatins against herbivorous insects. Therefore, our study proposes a new potential role of cystatins in CVD prevention and treatment, which requires further study.

Abstract Background Gastric cancer (GC) is a highly heterogeneous disease with many different histological and molecular subtypes. Due to their reduced systemic adverse effects, nanoformulation agents have attracted increasing attention for use in the treatment of GC patients in the clinic. To improve therapeutic outcomes, it is vitally necessary to provide individual medication references and guidance for use of these nanoformulations, and patient-derived organoids (PDOs) are promising models through which to achieve this goal. Results Using an improved enzymatic digestion process, we succeeded in constructing GC PDOs from surgically resected tumor tissues and endoscopic biopsies from GC patients; these PDOs closely recapitulated the histopathological and genomic features of the corresponding primary tumors. Next, we chose two representative paclitaxel (PTX) nanoformulations for comparative study and found that liposomal PTX outperformed albumin-bound PTX in killing GC PDOs at both the transcriptome and cellular levels. Our results further showed that the different distributions of liposomal PTX and albumin-bound PTX in PDOs played an essential role in the distinct mechanisms through which they kill PDOs. Finally, we constructed patient-derived xenografts model in which we verified the above distinct therapeutic outcomes via an intratumoral administration route. Conclusions This study demonstrates that GC PDOs are reliable tools for predicting nanoformulation efficacy. Graphical Abstract

Abstract Topological orders are a prominent paradigm for describing quantum many-body systems without symmetry-breaking orders. We present a topological quantum field theoretical (TQFT) study on topological orders in five-dimensional spacetime (5D) in which topological excitations include not only point-like particles, but also two types of spatially extended objects: closed string-like loops and two-dimensional closed membranes. Especially, membranes have been rarely explored in the literature of topological orders. By introducing higher-form gauge fields, we construct exotic TQFT actions that include mixture of two distinct types of BF topological terms and many twisted topological terms. The gauge transformations are properly defined and utilized to compute level quantization and classification of TQFTs. Among all TQFTs, some are not in Dijkgraaf-Witten cohomological classification. To characterize topological orders, we concretely construct all braiding processes among topological excitations, which leads to very exotic links formed by closed spacetime trajectories of particles, loops, and membranes. For each braiding process, we construct gauge-invariant Wilson operators and calculate the associated braiding statistical phases. As a result, we obtain expressions of link invariants all of which have manifest geometric interpretation. Following Wen’s definition, the boundary theory of a topological order exhibits gravitational anomaly. We expect that the characterization and classification of 5D topological orders in this paper encode information of 4D gravitational anomaly. Further consideration, e.g., putting TQFTs on 5D manifolds with boundaries, is left to future work.

Universal topological data of topologically ordered phases can be captured by topological quantum field theory in continuous space time by taking the limit of low energies and long wavelengths. While previous continuum field-theoretical studies of topological orders in three-dimensional (3D) real space focused on either self-statistics, braiding statistics, shrinking rules, fusion rules, or quantum dimensions, it has yet to systematically put all topological data together in a unified continuum field-theoretical framework. Here, we construct the topological BF field theory with twisted terms (e.g., AAdA and AAB) as well as a K-matrix BB term to simultaneously explore all such topological data and reach anomaly-free topological orders. Following the spirit of the famous K-matrix Chern-Simons theory of two-dimensional topological orders, we present general formulas and systematically show how the K-matrix BB term confines topological excitations, and how self-statistics of particles is transmuted between bosonic one and fermionic one. To reach anomaly-free topological orders, we explore, within the present continuum field-theoretical framework, how the principle of gauge invariance fundamentally influences possible realizations of topological data. More concretely, we present the topological actions of (i) particle-loop braidings with emergent fermions, (ii) multiloop braidings with emergent fermions, and (iii) Borromean rings braidings with emergent fermions, and calculate their universal topological data. Together with previous efforts, our paper paves the way toward a more systematic and complete continuum field-theoretical analysis of exotic topological properties of 3D topological orders. Several interesting future directions are also discussed.

Natural products are a main source of new chemical entities for use in drug and pesticide discovery. In order to discover lead compounds with high herbicidal activity, a series of new pyrido[2,3-d] pyrimidine derivatives were designed and synthesized using 2-chloronicotinic acid as the starting material. Their structures were characterized with 1H NMR, 13C NMR and HRMS, and the herbicidal activities against dicotyledonous lettuce (Lactuca sativa), field mustard (Brassica campestris), monocotyledonous bentgrass (Agrostis stolonifera) and wheat (Triticum aestivum) were determined. The results indicated that most of the pyrido[2,3-d] pyrimidine derivatives had no marked inhibitory effect on lettuce at 1 mM. However, most of the pyrido[2,3-d] pyrimidine derivatives possessed good activity against bentgrass at 1 mM. Among them, the most active compound, 3-methyl-1-(2,3,4-trifluorophenyl)pyrido[2,3-d]pyrimidine-2,4(1H,3H)-dione (2o), was as active as the positive controls, the commercial herbicides clomazone and flumioxazin. Molecular simulation was performed with molecular docking and DFT calculations. The docking studies provided strong evidence that 2o acts as an herbicide by inhibition of protoporphyrinogen oxidase. However, the physiological results indicate that it does not act on this target in vivo, implying that it could be metabolically converted to a compound with a different molecular target.

Vaccines have significant potential in treating and/or preventing diseases, yet there remain challenges in developing effective vaccines against some diseases, such as AIDS and certain tumors. Mesenchymal stem cells (MSCs), a subset of cells with low immunogenicity, high proliferation potential, and an abundant source of extracellular vesicles (EVs), represent one of the novel and promising vaccine platforms. This review describes the unique features and potential mechanisms of MSCs as a novel vaccine platform. We also cover aspects such as the safety and stability of MSCs that warrant future in-depth studies.

Based on the real-time environmental constraints in urban regional construction, this paper constructed a bi-level decentralized low-carbon optimal dispatching model of the urban regional integrated energy system (RIES), including the park integrated energy systems (IESs). In this model, a bi-level optimal allocation model of carbon emission constraints between the urban and the park is proposed for the first time. The upper urban will formulate the real-time carbon emission constraints based on real-time environmental monitoring, decomposing the historical carbon emissions to the lower park IESs; the lower park will meet the real-time carbon emission constraints during optimization. We through the upper urban with the lower park between the bi-level decentralized optimization to ensure that the objective function’s upper urban power, natural gas, and heat distribution network system is minimum total network loss. In addition, it is necessary to ensure the minimum operating cost of each park IESs and focus on how to meet the requirements of the overall environment of urban RIES. Furthermore, we study the influence of optimal allocation strategy of carbon emission constraints on network loss, and operating cost of urban RIES under different scenarios. Then, an improved analytical target cascading (ATC) method is applied to solve the bi-level decentralized optimal dispatching model of urban RIES. Finally, an example under three different scenarios is given to verify the superiority and effectiveness of the proposed model and the improved method.

T cells play a crucial role in the regulation of immune response and are integral to the efficacy of cancer immunotherapy. Because immunotherapy has emerged as a promising treatment for cancer, increasing attention has been focused on the differentiation and function of T cells in immune response. In this review, we describe the research progress on T-cell exhaustion and stemness in the field of cancer immunotherapy and summarize advances in potential strategies to intervene and treat chronic infection and cancer by reversing T-cell exhaustion and maintaining and increasing T-cell stemness. Moreover, we discuss therapeutic strategies to overcome T-cell immunodeficiency in the tumor microenvironment and promote continuous breakthroughs in the anticancer activity of T cells.

Ionic liquids (ILs) have garnered increasing attention in the biomedical field due to their unique properties. Although significant research has been conducted in recent years, there is still a lack of understanding of the potential applications of ILs in the biomedical field and the underlying principles. To identify the antibacterial activity and mechanism of ILs on bacteria, we evaluated the antimicrobial potency of imidazole chloride ILs (CnMIMCl) on Staphylococcus aureus (S. aureus). The toxicity of ILs was positively correlated to the length of the imidazolidinyl side chain. We selected C12MIMCl to study the mechanism of S. aureus. Through the simultaneous change in the internal and external parts of S. aureus, C12MIMCl caused the death of the bacteria. The production of large amounts of reactive oxygen species (ROS) within the internal parts stimulated oxidative stress, inhibited bacterial metabolism, and led to bacterial death. The external cell membrane could be destroyed, causing the cytoplasm to flow out and the whole cell to be fragmented. The antibacterial effect of C12MIMCl on skin abscesses was further verified in vivo in mice.

To control COVID-19 pandemic, complete lockdown was initiated in 2020. We investigated the impact of lockdown on tertiary-level academic performance, by comparing educational outcomes amongst first-year students during second semester of their medical course prior to and during lockdown. Evidence: The demographics, including educational outcomes of the two groups were not significantly different during semester one (prior to the lockdown). The academic performance amongst women was better than men prior to lockdown. However, the scores were improved significantly for both sexes during lockdown in 2020, following the complete online teaching, compared to that in 2019, showing no significant difference between men and women in 2020, for English and Chinese History. There were significant different scores between men and women in lab-based Histology Practice in 2019 (in-person tuition) and 2020 (online digital tuition), although only a significant improvement in women was observed between 2019 and 2020. Implication: the forced change to online delivery of the second semester of the first-year medical program in 2020 due to the COVID-19 pandemic did not result in any decline in assessment outcomes in any of the subjects undertaken. We believe extensive online digital media should continue to be available to students in future.

IntroductionThe purpose of this study was to compare short and mid-term outcomes in esophageal squamous cell carcinoma (ESCC) patients undergoing open or minimally invasive McKeown esophagectomy (MIE) after neoadjuvant PD-1 inhibitor plus chemotherapy.MethodsPatients with locally advanced ESCC underwent open or minimally invasive McKeown esophagectomy after neoadjuvant PD-1 inhibitor plus chemotherapy were retrospectively included from June 2019 to June 2021. The baseline characteristics, pathological data, short-and mid-term outcomes were collected and compared based on the surgical approach.ResultsA total of 35 patients were included in the study. An open procedure was performed for 13 patients (37.1%), and 22 (62.9%) patients underwent MIE after neoadjuvant therapy. Compared with open group, MIE group had shorter operative times (350.8± 117.8 vs. 277.9 ± 30.2 min, P = 0.009). The total number of resected lymph nodes was not significantly different, but more left recurrent laryngeal lymph nodes were harvested from the Open group (2.6 ± 3.2 vs. 0.9 ± 1.7, P = 0.047). The median follow-up time was 1.42 years (range, 0.35–2.59 years) from the first day of treatment. Three patients (8.6%) died during follow-up, one in the open surgery group and two in the MIE group. There were six (17.1%) patients developed recurrence, three in each group. The 2-year cumulative survival rates were 92.3 ± 7.4% and 89.5 ± 7.1% for the open and MIE groups, respectively. Overall survival was not different between the two surgical approaches.ConclusionsMIE might be safe and feasible for patients with locally advanced ESCC undergoing neoadjuvant PD-1 inhibitor plus chemotherapy.

Tenofovir disoproxil fumarate is the first-line antiviral therapy for chronic viral hepatitis B, but long-term use is associated with renal failure and hypophosphatemic osteomalacia. Tenofovir disoproxil fumarate-induced osteoporosis and secondary hyperparathyroidism are less commonly reported. Herein, we describe the case of a patient with bone and multijoint pain who was initially misdiagnosed as having normocalcemic primary hyperparathyroidism associated with prolonged exposure to tenofovir disoproxil fumarate. The patient’s 24-h urinary calcium and phosphorus excretion levels and serum calcium levels were at the lower end of the normal range. After reviewing these findings, the diagnosis was amended to osteoporosis and secondary hyperparathyroidism caused by tenofovir disoproxil fumarate. In this report, we describe the differences in clinical and laboratory manifestations of hyperparathyroidism induced by tenofovir disoproxil fumarate and normocalcemic primary hyperparathyroidism. We also discuss relevant pathophysiological mechanisms and propose a feasible treatment strategy.

The spacing of PVDs is an essential factor affecting the consolidation effect of vacuum preloading. For exploring the influence of spacing of PVDs on the impact of sludge drainage consolidation, FeCl3, a commonly used inorganic coagulant, was used to pretreat the sludge. In the experiment a vacuum filtration test was carried out to determine the optimal addition amount of FeCl3, and then the landfill sludge was pretreated according to the FeCl3 optimal addition amount. And two different spacing of PVDs were used to carry out a vacuum preloading contrast test. Then, the drainage and settlement were recorded, and water content and vane shear strength (VSS) were measured after the experiment. Finally, Mercury intrusion porosimetry (MIP) was carried out to explore the pore characteristics of the sludge further. The main conclusions are as follows: After conditioning by FeCl3, the sludge’s flocculent structure was destroyed, the intracellular water was released, and the effect of drainage capacity was significantly improved. After the spacing of PVDs is halved, the average volume reduction ratio and shear strength increases, and the effect of advanced dewatering and volume reduction of sludge improved significantly, leading to a better consolidation effect. In the progress of vacuum drainage consolidation, halving the spacing of PVDs results in large pores transformation into small pores, and the range of drainage consolidation is greatly expanded.

To ensure the necessary technical support for the long-term operation of the space vehicle, this paper studies the optimization technology of thermal emitter design in thermophotovoltaic technology. Because of the unsatisfactory experimental results of the traditional DBR cavity physical model, this paper uses the simplified DBR structure model to design multiple multi-layer composite structures named “simplified DBR cavity” and the absorption rate A value exceeds 99.5%, achieving a higher thermoelectric conversion efficiency.