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Abstract Quantum metrology promises unprecedented precision of parameter estimation, but it is often vulnerable to noise. While significant efforts have been devoted to improving the metrology performance in Markovian environments, practical control schemes specifically designed for non-Markovian noises are much less investigated. Here, we propose two control-enhanced quantum metrology schemes that are suitable for tackling general non-Markovian noises described by noise channels or noise spectra. We conduct experiments to verify the efficacy of these schemes on a nuclear magnetic resonance system. The experimental results involving multiqubit probes show that the parameter estimation precision can be greatly improved, significantly surpassing the standard quantum limit, with our schemes. At present, non-Markovian noises are widely encountered on diverse quantum devices, the proposed schemes are relevant for realistic metrology applications on these platforms.

To investigate the effect of the interaction between protocatechuic acid (PCA) and gelatin on the functional properties and stability of gelatin-PCA complexes. Gelatin-PCA complexes were prepared by non-covalent and covalent binding. Afterward, the interaction between PCA and gelatin was analyzed using UV-Vis spectroscopy, fluorescence spectroscopy, and Fourier transform infrared spectroscopy. Meanwhile, an analysis was also performed on the antioxidant activity, antibacterial activity, and stability of the complexes. The findings showed a higher PCA binding rate for the covalent complexes than the non-covalent complexes. Additionally, the interaction between PCA and gelatin resulted in the fluorescence quenching of gelatin, with a higher level of fluorescence quenching observed for the covalent binding. Moreover, in addition to excellent DPPH and ABTS+ radical scavenging abilities. Compared with GPCA-2，the non-covalent complex GPCA-1 showed more significant (P

The mucosal barrier is crucial for intestinal homeostasis, and goblet cells are essential for maintaining the mucosal barrier integrity. The proviral integration site for Moloney murine leukemia virus-1 (PIM1) kinase regulates multiple cellular functions, but its role in intestinal homeostasis during colitis is unknown. Here, we demonstrate that PIM1 is prominently elevated in the colonic epithelia of both ulcerative colitis patients and murine models, in the presence of intestinal microbiota. Epithelial PIM1 leads to decreased goblet cells, thus impairing resistance to colitis and colitis-associated colorectal cancer (CAC) in mice. Mechanistically, PIM1 modulates goblet cell differentiation through the Wnt and Notch signaling pathways. Interestingly, PIM1 interacts with histone deacetylase 2 (HDAC2) and downregulates its level via phosphorylation, thereby altering the epigenetic profiles of Wnt signaling pathway genes. Collectively, these findings investigate the unknown function of the PIM1–HDAC2 axis in goblet cell differentiation and ulcerative colitis/CAC pathogenesis, which points to the potential for PIM1-targeted therapies of ulcerative colitis and CAC.

Spinosad, a potent broad-spectrum bioinsecticide produced by Saccharopolyspora spinosa, has significant market potential. Despite its effectiveness, the regulatory mechanisms of spinosad biosynthesis remain unclear. Our investigation identified the crucial role of the LysR family transcriptional regulator ORF-L16, located upstream of spinosad biosynthetic genes, in spinosad biosynthesis. Through reverse transcription PCR (RT-PCR) and 5′-rapid amplification of cDNA ends (5′-Race), we unveiled that the spinosad biosynthetic gene cluster (BGC) contains six transcription units and seven promoters. Electrophoretic mobility shift assays (EMSAs) demonstrated that ORF-L16 bound to seven promoters within the spinosad BGC, indicating its involvement in regulating spinosad biosynthesis. Notably, deletion of ORF-L16 led to a drastic reduction in spinosad production from 1818.73 mg/L to 1.69 mg/L, accompanied by decreased transcription levels of spinosad biosynthetic genes, confirming its positive regulatory function. Additionally, isothermal titration calorimetry (ITC) and EMSA confirmed that spinosyn A, the main product of the spinosad BGC, served as an effector of ORF-L16. Specifically, it decreased the binding affinity between ORF-L16 and spinosad BGC promoters, thus exerting negative feedback regulation on spinosad biosynthesis. This research enhances our comprehension of spinosad biosynthesis regulation and lays the groundwork for future investigations on transcriptional regulators in S. spinosa.

Abstract Previous studies have indicated a link between neutrophil to lymphocyte ratio (NLR) and impaired fasting glucose (IFG), but the findings have been disputed. By conducting a real-world follow-up study, we can monitor the development of diseases and confirm the connection between NLR and IFG. A total of 1168 patients without IFG or T2DM were followed up for six years. At baseline, participants' NLR levels, fasting plasma glucose and other clinical characteristics were recorded. During the follow-up period, NLR levels and the prevalence of IFG were recorded. Ultimately, 45 individuals were lost to follow-up, leaving 1,123 participants for analysis. Using Group-Based Trajectory Modeling (GBTM), the sample was divided into three groups. The prevalence of IFG in the three groups was 12.1%, 19.4%, and 20.85%, respectively. Compared with the low-level NLR group, the hazard ratio of IFG in the moderate-level NLR group and high-level NLR group were 1.628 (1.109–2.390) and 1.575 (1.001–2.497), respectively. There was a significant interaction effect of BMI and NLR on the risk of IFG (P

Abstract Background The cancer microbiota was considered the main risk factor for cancer progression. We had proved that Fusobacterium periodonticum (F.p) was higher abundance in Esophageal cancer(EC)tissues. Bioinformation analysis found that BCT was a key virulence protein of F.p. However, little is known about the role and mechanism of BCT in EC. This study aimed to recognize the key virulence protein of F.p and explore the mechanism of BCT in promoting EC. Methods We constructed a eukaryotic expression vector and purified the recombinant protein BCT. CCK8 used to analyzed the activity of EC after treated by different concentration of BCT. UPLC-MS/MS and ELISA used to detect the metabonomics and metabolites. The ability of migration and invasion was completed by transwell assay. RT-QPCR, WB used to analyze the expression of relevant genes. Results Our data showed that BCT was higher expression in EC tumor tissues (p

Abstract Polyethers play a crucial role in the development of anticancer drugs. To enhance the anticancer efficacy and reduce the toxicity of these compounds, thereby advancing their application in cancer treatment, herein, guided by the structure‐activity relationships of aglycone polyethers, novel aglycone polyethers are rationally redesigned with potentially improved efficacy and reduced toxicity against tumors. To realize the biosynthesis of the novel aglycone polyethers, the gene clusters and the post‐polyketide synthase tailoring pathways for aglycone polyethers endusamycin and lenoremycin are identified and subjected to combinatorial biosynthesis studies, resulting in the creation of a novel aglycone polyether termed End‐16, which demonstrates significant potential for treating bladder cancer (BLCA). End‐16 demonstrates the ability to suppress the proliferation, migration, invasion, and cellular protrusions formation of BLCA cells, as well as induce cell cycle arrest in the G1 phase in vitro. Notably, End‐16 exhibits superior inhibitory activity and fewer side effects against BLCA compared to the frontline anti‐BLCA drug cisplatin in vivo, thereby warranting further preclinical studies. This study highlights the significant potential of integrating combinatorial biosynthesis strategies with rational design to create unnatural products with enhanced pharmacological properties.

Abstract Targeted delivery of glutamine metabolism inhibitors holds promise for cholangiocarcinoma therapy, yet effective delivery vehicles remain a challenge. This study reports the development of a biomimetic nanosystem, termed R‐CM@MSN@BC, integrating mesoporous organosilicon nanoparticles with reactive oxygen species‐responsive diselenide bonds for controlled release of the glutamine metabolism inhibitor bis‐2‐(5‐phenylacetamido‐1,3,4‐thiadiazol‐2‐yl) ethyl sulfide (BPTES) and the photosensitizer Ce6. Erythrocyte membrane coating, engineered with Arg‐Gly‐Asp (RGD) peptides, not only enhanced biocompatibility but also improved tumor targeting and tissue penetration. Upon laser irradiation, R‐CM@MSN@BC executed both photodynamic and glutamine‐metabolic therapies, inducing necroptosis in tumor cells and triggering significant immunogenic cell death. Time‐of‐flight mass cytometry analysis revealed that R‐CM@MSN@BC can remodel the immunosuppressive tumor microenvironment by polarizing M1‐type macrophages, reducing infiltration of M2‐type and CX3CR1+ macrophages, and decreasing T cell exhaustion, thereby increasing the effectiveness of anti‐programmed cell death ligand 1 immunotherapy. This strategy proposed in this study presents a viable and promising approach for the treatment of cholangiocarcinoma.

For the study of the applicability of polyurethane concrete (PUC) in the anchorage zone of expansion joints, the construction process of PUC was summarized through the on-site construction of the anchorage zone of bridge expansion joints. The mechanical response of anchorage zones with different materials under vehicle loading was also analyzed by finite element modeling. The linear fatigue cumulative damage of expansion joint anchorage zone materials PUC, steel fiber concrete (SFC), and silicate cement concrete (PCC) were analyzed respectively by traffic investigation of bridge sections under construction and Miner's linear fatigue damage accumulation theory. The results show that the vertical displacement of PUC is 13 times that of SFC and PCC, the stress is reduced by 36%, and the annual cumulative fatigue damage value of PUC is 1.06E-07, which is only 1/10 of that of SFC, and PUC has excellent load cushioning capacity and fatigue performance, which can effectively improve the service life of the anchorage zone of expansion joints.

Abstract Amidst the escalating impacts of global warming, the occurrence and severity of compound extreme weather events have risen significantly, presenting substantial threats to both lives and property. Existing response strategies predominantly focus on individual events, often overlooking the cumulative effects rising from their inherent complexity. To address this critical gap, we conducted a thorough examination of sequential extreme precipitation–heatwave compound events (SEPHCE) in China from 1975 to 2020, utilizing data from 1929 meteorological stations. Our investigation revealed a consistent rise in the frequency and duration of SEPHCE, with a particularly notable surge since 1993. Furthermore, shorter interval events disproportionately affected the regions of southwestern and southeast coastal China. Furthermore, SEPHCE onset times exhibited advancement, and the endings were delayed, thereby intensifying the overall trend. These findings underscore the pressing need to prioritize effective planning and adaptation strategies to mitigate the impact of these compound event, while also addressing the potential exacerbation of inequality resulting from climate change.

This is an essay in the field of environmental engineering. The experiment adopts the impregnation method, and uses FeCl3 as the modifier to modify the activated carbon to study its desulfurization ability. The effects of modifier concentration, roasting temperature, and reaction temperature on the desulfurization performance of modified activated carbon were experimentally studied. Studies have shown that as the concentration of the modified solution increases, the Fe2O3 attached to the surface of the activated carbon increases, the specific surface area and total pore volume of the modified activated carbon decrease, and the average pore size increases; as the roasting temperature increases, the amount of Fe2O3 attached to the surface of the activated carbon continues. When the roasting temperature exceeds 300 ℃, the pore structure of the activated carbon surface will be sintered, which will reduce the desulfurization performance of the modified activated carbon; as the reaction temperature increases, the adsorption performance of FeCl3/AC-0.15 first increases and then decreases. When the concentration of FeCl3 modified solution is 0.15 mol/L, the calcination temperature is 300 ℃, and the reaction temperature is 60 ℃, the desulfurization efficiency of modified activated carbon is the highest.

Abstract Background The emergence of the COVID-19 pandemic towards the end of 2019 triggered a relentless spread of online misinformation, which significantly impacted societal stability, public perception, and the effectiveness of measures to prevent and control the epidemic. Understanding the complex dynamics and characteristics that determine the duration of rumors is crucial for their effective management. In response to this urgent requirement, our study takes survival analysis method to analyze COVID-19 rumors comprehensively and rigorously. Our primary aim is to clarify the distribution patterns and key determinants of their persistence. Through this exploration, we aim to contribute to the development of robust rumor management strategies, thereby reducing the adverse effects of misinformation during the ongoing pandemic. Methods The dataset utilized in this research was sourced from Tencent's “Jiao Zhen” Verification Platform's “Real-Time Debunking of Novel Coronavirus Pneumonia” system. We gathered a total of 754 instances of rumors from January 18, 2020, to January 17, 2023. The duration of each rumor was ascertained using the Baidu search engine. To analyze these rumors, survival analysis techniques were applied. The study focused on examining various factors that might influence the rumors' longevity, including the theme of the content, emotional appeal, the credibility of the source, and the mode of presentation. Results Our study's results indicate that a rumor's lifecycle post-emergence typically progresses through three distinct phases: an initial rapid decline phase (0–25 days), followed by a stable phase (25–1000 days), and ultimately, an extinction phase (beyond 1000 days). It is observed that half of the rumors fade within the first 25 days, with an average duration of approximately 260.15 days. When compared to the baseline category of prevention and treatment rumors, the risk of dissipation is markedly higher in other categories: policy measures rumors are 3.58 times more likely to perish, virus information rumors have a 0.52 times higher risk, epidemic situation rumors are 4.86 times more likely to die out, and social current affairs rumors face a 2.02 times increased risk. Additionally, in comparison to wish rumors, bogie rumors and aggression rumors have 0.26 and 0.27 times higher risks of dying, respectively. In terms of presentation, graphical and video rumors share similar dissolution risks, whereas textual rumors tend to have a longer survival time. Interestingly, the credibility of the rumor's source does not significantly impact its longevity. Conclusion The survival time of rumors is strongly linked to their content theme and emotional appeal, whereas the credibility of the source and the format of presentation have a more auxiliary influence. This study recommends that government agencies should adopt specific strategies to counter rumors. Experts and scholars are encouraged to take an active role in spreading health knowledge. It's important for the public to proactively seek trustworthy sources for accurate information. Media platforms are advised to maintain journalistic integrity, verify the accuracy of information, and guide the public towards improved media literacy. These actions, collectively, can foster a collaborative alliance between the government and the media, effectively combating misinformation.

AIM: To explore the usage of choroidal thickness measured by swept-source optical coherence tomography (SS-OCT) to detect myopic macular degeneration (MMD) in high myopic participants. METHODS: Participants with bilateral high myopia (≤−6 diopters) were recruited from a subset of the Guangzhou Zhongshan Ophthalmic Center-Brien Holden Vision Institute High Myopia Cohort Study. SS-OCT was performed to determine the choroidal thickness, and myopic maculopathy was graded by the International Meta-Analysis for Pathologic Myopia (META-PM) Classi?cation. Presence of MMD was defined as META-PM category 2 or above. RESULTS: A total of 568 right eyes were included for analysis. Eyes with MMD (n=106, 18.7%) were found to have older age, longer axial lengths (AL), higher myopic spherical equivalents (SE), and reduced choroidal thickness in each Early Treatment Diabetic Retinopathy Study (ETDRS) grid sector (P

Abstract Skeletal stem/progenitor cell (SSPC) senescence is a major cause of decreased bone regenerative potential with aging, but the causes of SSPC senescence remain unclear. In this study, we revealed that macrophages in calluses secrete prosenescent factors, including grancalcin (GCA), during aging, which triggers SSPC senescence and impairs fracture healing. Local injection of human rGCA in young mice induced SSPC senescence and delayed fracture repair. Genetic deletion of Gca in monocytes/macrophages was sufficient to rejuvenate fracture repair in aged mice and alleviate SSPC senescence. Mechanistically, GCA binds to the plexin-B2 receptor and activates Arg2-mediated mitochondrial dysfunction, resulting in cellular senescence. Depletion of Plxnb2 in SSPCs impaired fracture healing. Administration of GCA-neutralizing antibody enhanced fracture healing in aged mice. Thus, our study revealed that senescent macrophages within calluses secrete GCA to trigger SSPC secondary senescence, and GCA neutralization represents a promising therapy for nonunion or delayed union in elderly individuals.

Genetic risk factors have been shown to contribute to the development of sexual dysfunction. However, the role of methylenetetrahydrofolate reductase (MTHFR) gene variants in the risk of erectile dysfunction (ED) remains unclear. In this study, we recruited 1254 participants who underwent ED assessed by the International Index of Erectile Function-5. The MTHFR c.677C>T variant was also measured by fluorescence polymerase chain reaction (PCR). No significant difference in the genotypic frequency of the MTHFR C677T polymorphism (CC, CT, and TT) was observed between men from the ED and non-ED groups. In addition, on binary logistic regression analysis, both crude and adjusted models showed that the risk of ED was not significantly associated with the C677T polymorphism. Interestingly, a significantly higher frequency of the 677TT polymorphism was found in severe and moderate ED (P = 0.02). The positive correlation between the MTHFR 677TT polymorphism and severe ED was confirmed by logistic regression analysis, even after adjusting for potential confounders (odds ratio [OR] = 2.46, 95% confidence interval [CI]: 1.15–5.50, P = 0.02). These findings suggest a positive correlation between the MTHFR 677TT polymorphism and the risk of severe ED. Identification of MTHFR gene polymorphisms may provide complementary information for ED patients during routine clinical diagnosis.

N-Nitrosamine disinfection by-products (NAs-DBPs) have been well proven for its role in esophageal carcinogenesis. However, the role of intratumoral microorganisms in esophageal squamous cell carcinoma (ESCC) has not yet been well explored in the context of exposure to NAs-DBPs. Here, the multi-omics integration reveals F. periodonticum (Fp) as “facilitators” is highly enriched in cancer tissues and promotes the epithelial mesenchymal transition (EMT)-like subtype formation of ESCC. We demonstrate that Fp potently drives de novo synthesis of fatty acids, migration, invasion and EMT phenotype through its unique FadAL adhesin. However, N-nitrosomethylbenzylamine upregulates the transcription level of FadAL. Mechanistically, co-immunoprecipitation coupled to mass spectrometry shows that FadAL interacts with FLOT1. Furthermore, FLOT1 activates PI3K-AKT/FASN signaling pathway, leading to triglyceride and palmitic acid (PA) accumulation. Innovatively, the results from the acyl-biotin exchange demonstrate that FadAL-mediated PA accumulation enhances Wnt3A palmitoylation on a conserved cysteine residue, Cys-77, and promotes Wnt3A membrane localization and the translocation of β-catenin into the nucleus, further activating Wnt3A/β-catenin axis and inducing EMT phenotype. We therefore propose a “microbiota-cancer cell subpopulation” interaction model in the highly heterogeneous tumor microenvironment. This study unveils a mechanism by which Fp can drive ESCC and identifies FadAL as a potential diagnostic and therapeutic target for ESCC.

Nontuberculous mycobacteria (NTM) are exceedingly rare etiological agents of intracranial infections. Among them, Mycobacterium rhodesiae stands out as an even less common pathogen. In this paper, we report the first documented case of a central nervous system (CNS) infection in humans caused by Mycobacterium rhodesiae, which has specific imaging findings and good response to the therapy by using Linezolid, Clarithromycin, and Minocycline. The diagnosis was facilitated by a comprehensive multimodal approach, incorporating multisite imaging, cerebrospinal fluid analysis via next-generation sequencing (NGS), and targeted genetic testing. Furthermore, this paper provides a derivation of the clinical characteristics observed in other documented instances of CNS infections attributable to NTM and based on a review of the current literature. Our experience contributes to the evidence that is needed to understand the full spectrum of NTM-related CNS pathologies and underscores the importance of a multidisciplinary diagnostic process in atypical presentations of intracranial infections.

BackgroundStomolophus meleagris envenomation causes severe cutaneous symptoms known as jellyfish dermatitis. The potential molecule mechanisms and treatment efficiency of dermatitis remain elusive because of the complicated venom components. The biological activity and molecular regulation mechanism of Troxerutin (TRX) was firstly examined as a potential treatment for jellyfish dermatitis. MethodsWe examined the inhibit effects of the TRX on tentacle extract (TE) obtained from S. meleagris in vivo and in vitro using the mice paw swelling models and corresponding assays for Enzyme-Linked Immunosorbent Assay (ELISA) Analysis, cell counting kit-8 assay, flow cytometry, respectively. The mechanism of TRX on HaCaT cells probed the altered activity of relevant signaling pathways by RNA sequencing and verified by RT-qPCR, Western blot to further confirm protective effects of TRX against the inflammation and oxidative damage caused by TE. ResultsTE significantly induced the mice paw skin toxicity and accumulation of inflammatory cytokines and reactive oxygen species in vivo and vitro. Moreover, a robust increase in the phosphorylation of mitogen-activated protein kinase (MAPKs) and nuclear factor-kappa B (NF-κB) signaling pathways was observed. While, the acute cutaneous inflammation and oxidative stress induced by TE were significantly ameliorated by TRX treatment. Notablly, TRX suppressed the phosphorylation of MAPK and NF-κB by initiating the nuclear factor erythroid 2-related factor 2 signaling pathway, which result in decreasing inflammatory cytokine release. ConclusionTRX inhibits the major signaling pathway responsible for inducing inflammatory and oxidative damage of jellyfish dermatitis, offering a novel therapy in clinical applications.

Abstract The Southern Ocean's eddy response to changing climate remains unclear, with observations suggesting non‐monotonic changes in eddy kinetic energy (EKE) across scales. Here simulations reappear that smaller‐mesoscale EKE is suppressed while larger‐mesoscale EKE increases with strengthened winds. This change was linked to scale‐wise changes in the kinetic energy cycle, where a sensitive balance between the dominant mesoscale energy sinks—inverse KE cascade, and source—baroclinic energization. Such balance induced a strong (weak) mesoscale suppression in the flat (ridge) channel. Mechanistically, this mesoscale suppression is attributed to stronger zonal jets weakening smaller mesoscale eddies and promoting larger‐scale waves. These EKE multiscale changes lead to multiscale changes in meridional and vertical eddy transport, which can be parameterized using a scale‐dependent diffusivity linked to the EKE spectrum. This multiscale eddy response may have significant implications for understanding and modeling the Southern Ocean eddy activity and transport under a changing climate.

The Middle Permian Qixia Formation in the Shuangyushi area, northwestern Sichuan Basin, develops shoal-facies dolomite reservoirs. To pinpoint promising reservoirs in the Qixia Formation, deep thin shoal-facies dolomite reservoirs were predicted using the techniques of pre-stack Kirchhoff-Q compensation for absorption, inverse Q filtering, low-to high-frequency compensation, forward modeling, and facies-controlled seismic meme inversion. The results are obtained in six aspects. First, the dolomite reservoirs mainly exist in the middle and lower parts of the second member of Qixia Formation (Qi2 Member), which coincide with the zones shoal cores are developed. Second, the forward modeling shows that the trough energy at the top and bottom of shoal core increases with increasing shoal-core thickness, and weak peak reflections are associated in the middle of shoal core. Third, five types of seismic waveform are identified through waveform analysis of seismic facies. Type-I and Type-II waveforms correspond to promising facies (shoal core microfacies). Fourth, vertically, two packages of thin dolomite reservoirs turn up in the sedimentary cycle of intraplatform shoal in the Qi2 Member, and the lower package is superior to the upper package in dolomite thickness, scale and lateral connectivity. Fifth, in plane, significantly controlled by sedimentary facies, dolomite reservoirs laterally distribute with consistent thickness in shoal cores at topographical highs and extend toward the break. Sixth, the promising prospects are the zones with thick dolomite reservoirs and superimposition of horst–graben structural traps.

This study investigates the portrayal of China in Kazakhstani media, focusing on changes in perceptions before and during the Belt and Road Initiative (BRI). Through comparative discourse analysis, the research reveals a shift in media narratives from primarily economic and political aspects to a growing emphasis on fostering friendly relations between Kazakhstan and China. The paper also explores how diplomatic relations between the two countries influence media reports about China. Although the findings are specific to Kazakhstan, the study contributes to understanding Central Asian views on China, especially in the context of the BRI and the region's changing geopolitical dynamics. The research suggests a trend toward more positive and neutral coverage of China in Kazakhstani news outlets.

Energy transition has brought widespread attentions to the concept of coupled utilization of the geothermal and solar energy. This paper provides an integrated assessment on developing a nanofluid geothermal-photovoltaic hybrid system that addresses the multi-objective optimization and multi-criteria evaluation difficulties. The coupling system design and dispatch are optimized by considering the multiple objectives from the microscopic particles to the system. The life cycle cost, levelized cost of energy, levelized cost of heat, and the irreversibility are introduced in the optimization stage. The optimization parameters include the pipe arrangement, type of nanoparticles, and the concentration of the nanoparticles in nanofluids. A combined analysis including the energy, exergy, economy, and the environment is proposed to evaluate the various objectives and cases. The results show that the combination of 2% Al2O3 nanofluid and spiral pipe has the optimum performance. The monocrystalline solar panels with the nanofluids-aided heat pump create the least CO2 emissions (550 kg/year), the least LCOE (198.18 $), and the highest exergy efficiency. However, the LCOH (211.78 $/MWh) is still much high. Only when the electricity cost is higher than 0.11$/kWh, the proposed coupling system would show competitiveness. In summary, these results effectively prove the robustness and superiority of the hybrid system.

Abstract Preoperative knowledge of expected postoperative pain can help guide perioperative pain management and focus interventions on patients with the greatest risk of acute pain. However, current methods for predicting postoperative pain require patient and clinician input or laborious manual chart review and often do not achieve sufficient performance. We use routinely collected electronic health record data from a multicenter dataset of 234,274 adult non-cardiac surgical patients to develop a machine learning method which predicts maximum pain scores on the day of surgery and four subsequent days and validate this method in a prospective cohort. Our method, POPS, is fully automated and relies only on data available prior to surgery, allowing application in all patients scheduled for or considering surgery. Here we report that POPS achieves state-of-the-art performance and outperforms clinician predictions on all postoperative days when predicting maximum pain on the 0–10 NRS in prospective validation, though with degraded calibration. POPS is interpretable, identifying comorbidities that significantly contribute to postoperative pain based on patient-specific context, which can assist clinicians in mitigating cases of acute pain.

Abstract Background Cell‐cell communication by carcinoma‐derived exosomes can influence the tumor microenvironment (TME) and regulate cancer progression. Based on the overexpression of microRNA‐21‐5p (miR‐21) in plasma from patients diagnosed with esophageal squamous cell carcinoma (ESCC) and exosomes from ESCC cell lines identified earlier, this study aimed to explore the influence of exosomal miR‐21 within the TME. Method ScRNA‐Seq and Bulk RNA‐Seq were integrated to elucidate the communication between cancer and endothelial cells. The functionality and mechanisms by which exo‐miR‐21 derived from carcinoma regulate endothelial cell‐mediated angiogenesis were assessed using a cocultivation model of EC9706 cells and recipient human umbilical vein endothelial cells (HUVECs), through blood vessel formation experiments, luciferase reporter assays, RT‐qPCR, and western blot analysis. Result A total of 3842 endothelial cells were extracted from the scRNA‐seq data of ESCC samples and reclustered into five cell subtype. Cell‐cell communication analysis revealed cancer cells presented a strong interaction with angiogenesis‐like endothelial cells in secreted signaling. MiR‐21 was unregulated in ESCC and the carcinoma‐derived exo‐miR‐21 was significantly raised in HUVECs. The exo‐miR‐21 promoted the proliferation and migration of HUVECs while also enhancing, closed mesh count, and junction number in HUVECs. Mechanistically, dual‐luciferase reporter assay revealed that PTEN was the target of miR‐21. Meanwhile, p‐Akt was significantly increased and suppressed by inhibition of miR‐21 and PI3K inhibitor LY294002. Conclusion Exo‐miR‐21‐mediated communication between endothelial and cancer cells plays a pivotal role in promoting the angiogenesis of ESCC. Therefore, controlling exo‐miR‐21 could serve as a novel therapeutic strategy for ESCC by targeting angiogenesis.

Abstract Background Nuclear respiratory factor 1 (NRF1) is a transcription factor that participates in several kinds of tumor, but its role in hepatocellular carcinoma (HCC) remains elusive. This study aims to explore the role of NRF1 in HCC progression and investigate the underlying mechanisms. Results NRF1 was overexpressed and hyperactive in HCC tissue and cell lines and high expression of NRF1 indicated unfavorable prognosis of HCC patients. NRF1 promoted proliferation, migration and invasion of HCC cells both in vitro and in vivo. Mechanistically, NRF1 activated ERK1/2-CREB signaling pathway by transactivating lysophosphatidylcholine acyltransferase 1 (LPCAT1), thus promoting cell cycle progression and epithelial mesenchymal transition (EMT) of HCC cells. Meanwhile, LPCAT1 upregulated the expression of NRF1 by activating ERK1/2-CREB signaling pathway, forming a positive feedback loop. Conclusions NRF1 is overexpressed in HCC and promotes HCC progression by activating LPCAT1-ERK1/2-CREB axis. NRF1 is a promising therapeutic target for HCC patients.

Abstract Recognizing cashmere and wool fibers has been a challenging problem in the textile industry due to their similar morphological structure, chemical composition, and physicochemical properties. Traditional manual methods for identifying these fibers are inefficient, labor-intensive, and inaccurate. To address these issues, we present a novel method for recognizing cashmere and wool fibers using an improved version of ShuffleNetV2 and Transfer Learning, which we implement as a new cashmere and wool classification network (CWCNet).The approach leverages depthwise separable dilated convolution to extract more feature information for fiber classification. We also introduce a new activation function that enhances the nonlinear representation of the model and allows it to more fully extract negative feature information. Experimental results demonstrate that CWCNet achieves an accuracy rate of up to 98.438% on our self-built dataset, which is a 2.084% improvement over the original ShuffleNetV2 model. Furthermore, our proposed method outperforms classical models such as EfficientNetB0, MobileNetV2, Wide-ResNet50, and ShuffleNetV2 in terms of recognition accuracy while remaining lightweight.The method is capable of extracting more information on fiber characteristics and has the potential to replace manual labor as technological advancements continue to be made. This will greatly benefit engineering applications in the textile industry by providing more efficient and accurate fiber classification.

Typical satellite component detection is an application-valuable and challenging research field. Currently, there are many algorithms for detecting typical satellite components, but due to the limited storage space and computational resources in the space environment, these algorithms generally have the problem of excessive parameter count and computational load, which hinders their effective application in space environments. Furthermore, the scale of datasets used by these algorithms is not large enough to train the algorithm models well. To address the above issues, this paper first applies YOLOv8 to the detection of typical satellite components and proposes a Lightweight Typical Satellite Components Detection algorithm based on improved YOLOv8 (LTSCD-YOLO). Firstly, it adopts the lightweight network EfficientNet-B0 as the backbone network to reduce the model’s parameter count and computational load; secondly, it uses a Cross-Scale Feature-Fusion Module (CCFM) at the Neck to enhance the model’s adaptability to scale changes; then, it integrates Partial Convolution (PConv) into the C2f (Faster Implementation of CSP Bottleneck with two convolutions) module and Re-parameterized Convolution (RepConv) into the detection head to further achieve model lightweighting; finally, the Focal-Efficient Intersection over Union (Focal-EIoU) is used as the loss function to enhance the model’s detection accuracy and detection speed. Additionally, a larger-scale Typical Satellite Components Dataset (TSC-Dataset) is also constructed. Our experimental results show that LTSCD-YOLO can maintain high detection accuracy with minimal parameter count and computational load. Compared to YOLOv8s, LTSCD-YOLO improved the mean average precision (mAP50) by 1.50% on the TSC-Dataset, reaching 94.5%. Meanwhile, the model’s parameter count decreased by 78.46%, the computational load decreased by 65.97%, and the detection speed increased by 17.66%. This algorithm achieves a balance between accuracy and light weight, and its generalization ability has been validated on real images, making it effectively applicable to detection tasks of typical satellite components in space environments.

The quality of molten iron not only has a significant impact on the strength, toughness, smelting cost and service life of cast iron but also directly affects the satisfaction of users. The establishment of timely and accurate blast furnace molten iron quality prediction models is of great significance for the improvement of the production efficiency of blast furnace. In this paper, Si, S and P content in molten iron is taken as the important index to measure the quality of molten iron, and the 989 sets of production data from a No.1 blast furnace from August to October 2020 are selected as the experimental data source, predicting the quality of molten iron by the I-GWO-CNN-BiLSTM model. First of all, on the basis of the traditional data processing method, the missing data values are classified into correlation data, temporal data, periodic data and manual input data, and random forest, the Lagrangian interpolation method, the KNN algorithm and the SVD algorithm are used to complete them, so as to obtain a more practical data set. Secondly, CNN and BiLSTM models are integrated and I-GWO optimized hyperparameters are used to form the I-GWO-CNN-BiLSTM model, which is used to predict Si, S and P content in molten iron. Then, it is concluded that using the I-GWO-CNN-BiLSTM model to predict the molten iron quality can obtain high prediction accuracy, which can provide data support for the regulation of blast furnace parameters. Finally, the MCMC algorithm is used to analyze the influence of the input variables on the Si, S and P content in molten iron, which helps the steel staff control the quality of molten iron in a timely manner, which is conducive to the smooth running of blast furnace production.

Metal contamination in drinking water is well known; however, detailed insights into the metals/metalloids in finished water and their health effects are lacking. Water samples collected over four seasons from August 2022 to April 2023 from three locations in the Yangtze River basin in Nanjing were analyzed using inductively coupled plasma mass spectrometry to detect 33 metal/metalloid types. This study assessed seasonal and spatial variations and evaluated the removal efficiencies of advanced treatment processes. Health risks from metal/metalloid ingestion were calculated using a risk assessment model from the United States Environmental Protection Agency (USEPA). No significant regional differences in total metal/metalloid concentrations were found between the source and finished waters. Metals such as Cr, Ga, Hg, Pb, and Rb varied seasonally, peaking in winter. The advanced treatment process outperformed the conventional process for As removal. However, the removal efficiencies were lower for Mn, Cd, Hg, Se, and Zn than those of the conventional process. Positive correlations were observed among several metals, suggesting that metals may have similar sources of contamination. The main carcinogenic risk exceeded the acceptable levels in children according to the USEPA. Non-carcinogenic risks were below the threshold values, but As, Tl, and V were highlighted as key risk elements. Seasonal changes markedly influenced metal/metalloid concentrations and distributions in water, necessitating risk management focused on arsenic.

Blast furnace ironmaking plays an important role in modern industry and the development of the economy. A reasonable ingredient scheme is crucial for energy efficiency and emission reduction in blast furnace production. Determining the right blast furnace ingredients is a complicated process; therefore, this study examines the optimization of the ingredient ratio. In this paper a model of the blast furnace ingredients is established by considering cost of per ton iron, CO2 emissions, and the theoretical coke ratio as the objective functions; ingredient parameters, process parameters, main and by-product parameters as variables; and the blast furnace smelting theory and equilibrium equation as constraints. Then, the model is solved by using an improved grey wolf optimization algorithm and an improved multi-objective grey wolf optimization algorithm. Using the data collected from the steel mill, the conclusion is that multi-objective optimization can consider the indexes of each target, so that the values of all the targets are excellent; we also compared the multi-objective solution results with the original production scheme of the steel mill, and we found that using the blast furnace ingredient scheme optimized in this study can reduce the cost of iron per ton, CO2 emissions per ton, and the theoretical coke ratio in blast furnace production by 350 CNY/t, 1000 kg/t, and 20 kg/t, respectively, compared with the original production plan. Thus, steel mill decision makers can choose the blast furnace ingredients according to different business strategies and the actual needs of steel mills can be better met.

Testosterone (T), an environmental androgen, significantly disrupts endocrine systems in wildlife and ecosystems. Despite growing concern over its high levels in aquatic environments, the reproductive toxicity of testosterone and its mechanisms are not well understood. In this study, we investigated the reproductive toxicity and mechanisms of testosterone using Caenorhabditis elegans (C. elegans) and assessed its ecological toxicity through the benchmark dose (BMD) method. Our results indicate that T concentrations exceeding 0.01 μg/L significantly reduce the brood size, decrease germ cell counts, and prolong the generation time in C. elegans as T concentrations increase. Furthermore, to elucidate the specific mechanisms, we analyzed the expression of nhr-69, mpk-1, and other genes involved in sex determination. These findings suggest that the nhr-69-mediated reproductive toxicity of T primarily affects sperm formation and the offspring number by influencing its downstream targets, mpk-1 and fog-1/3, which are critical in the germ cell sex-determining pathway. Additionally, this study determined that the 10% lower boundary of the baseline dose (BMDL10) is 1.160 ng/L, offering a more protective reference dose for the ecological risk assessment of T. The present study suggests that nhr-69 mediates the reproductive toxicity of T by influencing mpk-1 and fog-1/3, critical genes at the end of the germ cell sex-determining pathway, thereby providing a basis for establishing reproductive toxicity thresholds for T.

The functional performance of immune cells relies on a complex transcriptional regulatory network. The three-dimensional structure of chromatin can affect chromatin status and gene expression patterns, and plays an important regulatory role in gene transcription. Currently available techniques for studying chromatin spatial structure include chromatin conformation capture techniques and their derivatives, chromatin accessibility sequencing techniques, and others. Additionally, the recently emerged deep learning technology can be utilized as a tool to enhance the analysis of data. In this review, we elucidate the definition and significance of the three-dimensional chromatin structure, summarize the technologies available for studying it, and describe the research progress on the chromatin spatial structure of dendritic cells, macrophages, T cells, B cells, and neutrophils.

Purpose: The pathophysiological mechanisms underlying migraine remain elusive, with oxidative stress hypothesized as a potential etiological factor. The Oxidative Balance Score (OBS) is a comprehensive tool for assessing the impact of diet and lifestyle on oxidative stress, thereby gauging an individual's overall antioxidant capacity. In this cross-sectional study, we explored the correlation between OBS and migraine prevalence among a cohort of US adults. Methods: We analyzed data from 6195 participants aged 20 years and above, drawn from the National Health and Nutrition Examination Survey (NHANES) conducted between 1999 and 2004. We employed multiple logistic regression, coupled with sensitivity analyses, to investigate the relationship between OBS and migraine. Subsequent subgroup analyses and interaction tests were performed to assess the consistency of this association across the population. Results: Multiple logistic regression revealed an inverse relationship between OBS and the likelihood of experiencing migraines. Specifically, individuals in the highest OBS quartile exhibited a significantly reduced migraine risk compared to those in the lowest quartile (OR = 0.98, 95% Confidence Interval (CI): 0.97–0.99, P = 0.0001). Furthermore, restricted cubic spline curves indicated a non-linear association between dietary OBS and migraine incidence (non-linear P = 0.0258). Discussion: Our findings suggest that adherence to an antioxidant-rich diet may be an effective strategy for mitigating migraine, potentially by influencing oxidative balance.

As the “blood vessels” and “nerves” of the power grid, cables are important carriers for transmitting electric energy, and their failures will affect the safe and stable operation of the power grid. In this paper, a digital twin model of thermal characteristics is constructed for 10 kV YJV×400 cluster cable and its joint model. Based on the multi-physical field coupling analysis method, the fluid field, temperature field and current-carrying capacity of the cluster cable are analyzed. The temperature rise and airflow distribution characteristics of the joint and its external insulation when the defect of joint false connection occurs are analyzed. Based on the fuzzy analytic hierarchy process (FAHP), weights are assigned to the locations of multiple measurement points of the cable external insulation, and the temperature distribution of each measurement point is combined with the digital twin technology to calculate the hot spot temperature of the cable, so as to assess the defects of the joints of the cables. The digital twin platform is used for real-time monitoring of cable status and assessment of defects. The temperature rise experiments of cables under different carrying capacity and joint defects show that this method can accurately and efficiently calculate hot spot temperatures and assess defects of joints in cluster cables.

With the rapid progress of intelligent vision of the Internet of Things, the gap between the resultant high-level demands and conventional silicon-based hardware architectures is continuously widening. Biomimetic artificial neural networks (ANNs) have recently been proposed to solve this problem. However, they still face the predicaments in uniformity, heterogeneous integration, and hardware implementation, etc. Here we demonstrate an intelligent vision ANN with two-dimensional material (2DM)/molecular ferroelectric (MF) bilayer electronic/optoelectronic memristors. In contrast to conventional ferroelectric transistors, in-plane ferroelectric polarization was also found to enable a simpler two-terminal structure with a lateral p/n-type doping in the adjacent 2DM layer. After a demonstration of fabricated array and board-level driving circuits, an image recognition and classification task is proposed, reaching an accuracy of 85.2%, which implies great potential towards multi-modal artificial intelligent vision systems.

Objective. To explore associations of combined exposure to metabolic/inflammatory indicators with thyroid nodules. Methods. We reviewed personal data for health screenings from 2020 to 2021. A propensity score matching method was used to match 931 adults recently diagnosed with thyroid nodules in a 1 : 4 ratio based on age and gender. Conditional logistic regression and Bayesian kernel machine regression (BKMR) were used to explore the associations of single metabolic/inflammatory indicators and the mixture with thyroid nodules, respectively. Results. In the adjusted models, five indicators (ORQ4 vs. Q1: 1.30, 95% CI: 1.07–1.58 for fasting blood glucose; ORQ4 vs. Q1: 1.30, 95% CI: 1.08–1.57 for systolic blood pressure; ORQ4 vs. Q1: 1.26, 95% CI: 1.04–1.53 for diastolic blood pressure; ORQ4 vs. Q1: 1.23, 95% CI: 1.02–1.48 for white blood cell; ORQ4 vs. Q1: 1.28, 95% CI: 1.07–1.55 for neutrophil) were positively associated with the risk of thyroid nodules, while high-density lipoproteins (ORQ3 vs. Q1: 0.75, 95% CI: 0.61–0.91) were negatively associated with the risk of thyroid nodules. Univariate exposure-response functions from BKMR models showed similar results. Moreover, the metabolic and inflammatory mixture exhibited a significant positive association with thyroid nodules in a dose-response pattern, with systolic blood pressure being the greatest contributor within the mixture (conditional posterior inclusion probability of 0.82). No interaction effects were found among the five indicators. These associations were more prominent in males, participants with higher age (≥40 years old), and individuals with abnormal body mass index status. Conclusions. Levels of the metabolic and inflammatory mixture have a linear dose-response relationship with the risk of developing thyroid nodules, with systolic blood pressure levels being the most important contributor.

Background: To exploit hepatocellular carcinoma (HCC) diagnostic substances, we identify potential predictive markers based on machine learning and to explore the significance of immune cell infiltration in this pathology. Method: Three HCC gene expression datasets were used for weighted gene co-expression network analysis (WGCNA) and differential expression analysis. Least Absolute Shrinkage and Selection Operator (LASSO) and Random Forest were applied to identify candidate biomarkers. The diagnostic value of HCC diagnostic gene biomarkers was further assessed by the area under the ROC curve observed in the validation dataset. CIBERSORT was used to analyze 22 immune cell fractions from HCC patients and to analyze their correlation with diagnostic markers. In addition, the prognostic value of the markers and the sensitivity of the drugs were analyzed. Result: WGCNA and differential expression analysis were used to screen 396 distinct gene signatures in HCC tissues. They were mostly engaged in cytoplasmic fusion and the cell division cycle, according to gene enrichment analyses. Five genes were shown to have a high diagnostic value for use as diagnostic biomarkers for HCC, including EFHD1 (AUC = 0.77), KIF4A (AUC = 0.97), UBE2C (AUC = 0.96), SMYD3 (AUC = 0.91), and MCM7 (AUC = 0.93). T cells, NK cells, macrophages, and dendritic cells were found to be related to diagnostic markers in HCC tissues by immune cell infiltration analysis, indicating that these cells are intimately linked to the onset and spread of HCC. Concurrently, these five genes and their constructed models have considerable prognostic value. Conclusion: These five genes (EFHD1, KIF4A, UBE2C, SMYD3, and MCM7) may serve as new candidate molecular markers for HCC, providing new insights for future diagnosis, prognosis, and molecular therapy of HCC.

In this study, we evaluated the permeability damage and throughput potential of shale cores, focusing particularly on the damage water inflicts on shale permeability and the potential for hydrocarbon extraction using various injection media. Nuclear magnetic resonance (NMR) was utilized to analyze the distribution of crude oil across different pore sizes and to determine the limits of their utilization under varied media injection cycles. The results indicate that the Shengli Oilfield FY shale possesses abundant inorganic pores, primarily composed of intergranular and intragranular pores. Organic matter is dispersed and contains numerous micro-fractures. While formation water has only a minor impact on the permeability of fractured cores, it significantly impairs matrix permeability. Moreover, when the formation water content exceeds 10%, the degree of damage will decrease. In contrast to formation water, distilled water causes serious damage to both matrix and fractured cores. Therefore, anti-swelling measures are essential to ensure effective development in subsequent stages. After five injection cycles, the final recovery rates for brine, surfactant, and CO2 injection are 11.5%, 29.3%, and 45.9%, respectively. CO2 injection demonstrates the best production enhancement, followed by surfactant injection. CO2 is particularly effective in each cycle, primarily due to its expansion and extraction mechanism. Surfactants enhance production mainly by reducing interfacial tension and altering wettability, resulting in significant improvement in the first cycle. Meanwhile, brine injection primarily augments production through improved wettability and capillary pressure, resulting in a moderate production improvement. Based on NMR experiments, the minimum pore size for CO2 injection is estimated to be around 10–15 nm, Surfactant injection necessitates pore sizes with a minimum of 30–40 nm and brine injection requires pore sizes of approximately 60–70 nm. This research provides valuable experimental data for on-site shale oil development and deepens our understanding of the mechanisms involved in hydrocarbon recovery from shale using different injection media.

Aims: Previous studies have related heat waves to morbidity and mortality of cardiovascular diseases; however, potential mechanisms remained limited. Our aims were to investigate the short-term effects of heat waves on a series of clinical/subclinical indicators associated with cardiovascular health. Methods: Our study used 80,574 health examination records from the Health Management Center of Nanjing Zhongda Hospital during the warm seasons of 2019–2021, including 62,128 participants. A total of 11 recognized indicators of cardiovascular risk or injury were assessed. Air pollution and meteorological data were obtained from the Nanjing Ecological Environment Bureau and the China Meteorological Data Network, respectively. Heat waves were defined as a daily average temperature over the 95th percentile for three or more consecutive days from May to September. We used a combination of linear mixed effects models and distributed lag nonlinear models to assess the lagged effects of heat waves on clinical and subclinical cardiovascular indicators. Stratified analyses based on individuals' characteristics, including gender, age, body mass index (BMI), diabetes, and hypertension, were also performed. Results: Heat waves were related to significant changes in most indicators, with the magnitude of effects generally peaking at a lag of 0 to 3 days. Moreover, the cumulative percentage changes over lag 0–7 days were –0.82 % to –2.55 % in blood pressure, 1.32 % in heart rate, 0.20 % to 2.66 % in systemic inflammation markers, 0.36 % in a blood viscosity parameter, 9.36 % in homocysteine, and 1.35 % to 3.25 % in injuring myocardial enzymes. Interestingly, females and males showed distinct susceptibilities in different indicators. Stronger effects were also found in participants aged 50 years or over, individuals with abnormal BMI status, and patients with diabetes. Conclusion: Short-term exposure to heat waves could significantly alter clinical/subclinical cardiovascular indicator profiles, including blood pressure changes, increased heart rate, acute systemic inflammation, elevated blood viscosity, and myocardial injury.

Abstract Non-targeted metabonomic techniques were used to explore changes in metabolic profiles of patients with early onset and late onset T2DM. Newly diagnosed early onset T2DM (EarT2DM) and late onset T2DM (LatT2DM) patients were recruited, and the matched age, sex, and low-risk population of diabetes mellitus were selected as the control group. 117 adults were recruited in the study, including 21 in EarT2DM group with 25 in corresponding control group (heaCG1), and 48 in LatT2DM group with 23 in corresponding control group (heaCG2). There were 15 relatively distinctive metabolic variants in EarT2DM group and 10 distinctive metabolic variants in LatT2DM group. The same changing pathways mainly involved protein, aminoacyl-tRNA biosynthesis, fatty acid biosynthesis, taurine metabolism, arginine biosynthesis, lysosome and mTOR signaling pathway. The independent disturbed pathways in EarT2DM included branched chain amino acids, alanine, aspartate and glutamate metabolism. The independent disturbed pathways in LatT2DM involved linoleic acid metabolism, biosynthesis of unsaturated fatty acids, arginine, proline metabolism and FoxO signaling pathway. T2DM patients at different diagnosed ages may have different metabolite profiles. These metabolic differences need to be further verified.

Abstract Background Menopause is a specific physical and psychological transition period for women, during which they experience a series of menopausal symptoms. Menopausal hormone therapy is an important treatment for improving menopausal symptoms. Helping women correctly understand menopausal hormone therapy is a prerequisite for increasing the acceptance and utilization of menopausal hormone therapy by women. Physical examinations are an important method for women to master their own health status and detect potential health problems, and in recent years, an increasing number of women have actively participated in physical examinations. Therefore, this study aims to comprehend the prevalence of menopausal symptoms and attitudes towards menopausal hormone therapy among women aged 40–60 who underwent physical examinations, which would provide a useful reference to reduce the prevalence of menopausal symptoms and improve acceptance of menopausal hormone therapy. Methods This cross-sectional study was conducted at the Health Management Centre of the Affiliated Hospital of Southwest Medical University in Luzhou City, Sichuan Province. The data were collected from 295 women aged between 40 and 60 using convenience sampling. Information on all participants was collected through face-to-face interviews. Participants completed a demographic questionnaire and an attitude towards menopausal hormone therapy questionnaire, and the modified Kupperman index was used to assess the prevalence and severity of participants' menopausal symptoms. The collected data were processed using SPSS and Excel software and analysed using descriptive statistics and logistic regression. Results The top 5 menopausal symptoms were insomnia, fatigue, bone and joint pain, sexual dysfunction and emotional instability. Multiple linear regression analysis showed that residence, sexual intercourse frequency, mentality, and physical exercise were the influencing factors of menopausal symptoms. The study showed that 77% of women said they were still reluctant to receive menopausal hormone therapy after experiencing menopause-related symptoms. The main source of menopausal hormone therapy-related knowledge among women was from surrounding menopausal women (62%), and 54% wanted to gain menopausal hormone therapy-related knowledge through a web-based approach. Conclusion The incidence of menopausal symptoms is higher in women aged 40–60 years, which is related to women’s mentality, exercise, and sexual intercourse frequency. In addition, the results of this study indicate that women’s knowledge of menopausal hormone therapy is insufficient, which suggests that we need to strengthen health education to improve the acceptance rate of menopausal hormone therapy.

Abstract Glioblastoma (GBM) is notorious for malignant neovascularization that contributes to undesirable outcome. However, its mechanisms remain unclear. This study aimed to identify prognostic angiogenesis‐related genes and the potential regulatory mechanisms in GBM. RNA‐sequencing data of 173 GBM patients were obtained from the Cancer Genome Atlas (TCGA) database for screening differentially expressed genes (DEGs), differentially transcription factors (DETFs), and reverse phase protein array (RPPA) chips. Differentially expressed genes from angiogenesis‐related gene set were extracted for univariate Cox regression analysis to identify prognostic differentially expressed angiogenesis‐related genes (PDEARGs). A risk predicting model was constructed based on 9 PDEARGs, namely MARK1, ITGA5, NMD3, HEY1, COL6A1, DKK3, SERPINA5, NRP1, PLK2, ANXA1, SLIT2, and PDPN. Glioblastoma patients were stratified into high‐risk and low‐risk groups according to their risk scores. GSEA and GSVA were applied to explore the possible underlying GBM angiogenesis‐related pathways. CIBERSORT was employed to identify immune infiltrates in GBM. The Pearson's correlation analysis was performed to evaluate the correlations among DETFs, PDEARGs, immune cells/functions, RPPA chips, and pathways. A regulatory network centered by three PDEARGs (ANXA1, COL6A1, and PDPN) was constructed to show the potential regulatory mechanisms. External cohort of 95 GBM patients by immunohistochemistry (IHC) assay demonstrated that ANXA1, COL6A1, and PDPN were significantly upregulated in tumor tissues of high‐risk GBM patients. Single‐cell RNA sequencing also validated malignant cells expressed high levels of the ANXA1, COL6A1, PDPN, and key DETF (WWTR1). Our PDEARG‐based risk prediction model and regulatory network identified prognostic biomarkers and provided valuable insight into future studies on angiogenesis in GBM.

Abstract Based on the staggered difference-in-difference (DID) model, this paper uses Chinese listed firms between 2012 and 2020 to investigate the impact of green bond issuance on corporate environmental, social and governance (ESG) performance. We provide evidence that green bond issuance positively enhances corporate ESG performance. Green bond issuance mainly promotes corporate ESG performance through the internal attention effect and the external supervision effect. Moreover, the positive correlation between green bond issuance and corporate ESG performance is more prominent among companies with larger size, higher government subsidies and executives with environmental experience. The extended analysis shows that green bond issuance can promote the enhancement of firm valuation. This study provides theoretical guidance for the use of green financial systems to promote corporate ESG performance.

Abstract Despite that in-sensor processing has been proposed to remove the latency and energy consumption during the inevitable data transfer between spatial-separated sensors, memories and processors in traditional computer vision, its hardware implementation for artificial neural networks (ANNs) with all-in-one device arrays remains a challenge, especially for organic-based ANNs. With the advantages of biocompatibility, low cost, easy fabrication and flexibility, here we implement a self-powered in-sensor ANN using molecular ferroelectric (MF)-based photomemristor arrays. Tunable ferroelectric depolarization was intentionally introduced into the ANN, which enables reconfigurable conductance and photoresponse. Treating photoresponsivity as synaptic weight, the MF-based in-sensor ANN can operate analog convolutional computation, and successfully conduct perception and recognition of white-light letter images in experiments, with low processing energy consumption. Handwritten Chinese digits are also recognized and regressed by a large-scale array, demonstrating its scalability and potential for low-power processing and the applications in MF-based in-situ artificial retina.

The tiller angle, which is an important agronomic trait, determines plant architecture and greatly influences the grain yield of rice. In this study, a population of chromosome segment substitution lines derived from a cross between a japonica variety with a compact plant architecture—Koshihikari—and an indica variety with a spread-out plant architecture—Nona Bokra—was used to investigate the genetic basis of the tiller angle. Five quantitative trait loci (qTA1, qTA5, qTA9-1, qTA9-2, and qTA11) for the tiller angle were detected on chromosomes 1, 5, 9, 9, and 11 in two different environments. The phenotypic variation in these QTLs ranged from 3.78% to 8.22%. Two pairs of digenic epistatic QTLs were detected in Lingshui. The epistatic interaction explained 15.19% and 13.60% of the phenotypic variance, respectively. Among the five QTLs, qTA9-2 was detected in both environments. An F2 mapping population containing the qTA9-2 QTL was established. The location of qTA9-2 was narrowed down to a 187 kb region between InDel markers M9 and M10 on chromosome 9. Thirty open reading frames (ORFs), including TAC1, a gene known to regulate the tiller angle, were identified in this region. The gene sequencing results suggested that a base substitution from G to A at position 1557 in the 3′-untranslated region led to a difference in the expression of qTA9-2 in Koshihikari and Nona Bokra. These findings provide a potential gene resource for the improvement of rice plant architecture.

The main objective of our study is to explore the associations between combined exposure to urinary heavy metals and high remnant cholesterol (HRC), a known cardiovascular risk factor. Utilizing data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, we conducted a cross-sectional analysis of 5690 participants, assessing urinary concentrations of ten heavy metals. Ten heavy metals in urine were measured by inductively coupled plasma mass spectrometry (ICP-MS). Fasting residual cholesterol ≥0.8 mmol/L was defined as HRC (using blood samples). Statistical analyses included weighted multivariable logistic regression, weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) to evaluate the associations of heavy metal exposure with HRC. Stratified analyses based on individual characteristics were also conducted. Multivariable logistic regression found that the four metals (OR Q4 vs. Q1: 1.33, 95% CI: 1.01–1.75 for barium (Ba); OR Q4 vs. Q1: 1.50, 95% CI: 1.16–1.94 for cadmium (Cd); OR Q4 vs. Q1: 1.52, 95% CI: 1.15–2.01 for mercury (Hg); OR Q4 vs. Q1: 1.35, 95% CI: 1.06–1.73 for lead (Pb)) were positively correlated with the elevated risk of HRC after adjusting for covariates. In addition, all three mixed models, including WQS (OR: 1.25; 95% CI: 1.07–1.46), qgcomp (OR: 1.17; 95% CI: 1.03–1.34), and BKMR, consistently showed a significant positive correlation between co-exposure to heavy metal mixtures and HRC, with Ba and Cd being the main contributors within the mixture. These associations were more pronounced in younger adults (20 to 59 years), males, and those with a higher body mass index status (≥25 kg/m2). Our findings reveal a significant relationship between exposure to the mixture of heavy metals and HRC among US adults, with Ba and Cd being the major contributors to the mixture’s overall effect. Public health efforts aimed at reducing heavy metal exposure can help prevent HRC and, in turn, cardiovascular disease.

In this paper, the gas–liquid two-phase flow within a Tesla valve under zero-gravity conditions is numerically studied. Based on the VOF model and the inlet two-phase separation method, the forward and reverse flow patterns and pressure drop changes in a Tesla valve at different inlet velocities were analyzed. At an inlet velocity of 0.1–0.2 m/s, the flow pattern was slug flow, the bubbles were evenly distributed in different positions in the Tesla valve, and the velocity difference between the main pipe and the arc branch pipe was small. When the inlet velocity was 0.4 m/s, the main flow pattern was annular flow, and there was a phenomenon of gas–liquid phase separation through different flow channels, which was related to centrifugal force. At an inlet velocity of 0.6–0.8 m/s, bubbly flow and slug flow coexisted, which was related to the uneven velocity. In the study range, the difference in the forward and reverse pressure drops of two-phase flow was smaller than that of single-phase flow, and the two-phase diodicity decreased first and then increased with the change in inlet velocity, reaching minimum values of 0.78 at 0.2 m/s and 1.44 at 0.8 m/s.

Abstract Alzheimer’s disease (AD) is a major subtype of neurodegenerative dementia caused by long-term interactions and accumulation of multiple adverse factors, accompanied by dysregulation of numerous intracellular signaling and molecular pathways in the brain. At the cellular and molecular levels, the neuronal cellular milieu of the AD brain exhibits metabolic abnormalities, compromised bioenergetics, impaired lipid metabolism, and reduced overall metabolic capacity, which lead to abnormal neural network activity and impaired neuroplasticity, thus accelerating the formation of extracellular senile plaques and intracellular neurofibrillary tangles. The current absence of effective pharmacological therapies for AD points to the urgent need to investigate the benefits of non-pharmacological approaches such as physical exercise. Despite the evidence that regular physical activity can improve metabolic dysfunction in the AD state, inhibit different pathophysiological molecular pathways associated with AD, influence the pathological process of AD, and exert a protective effect, there is no clear consensus on the specific biological and molecular mechanisms underlying the advantages of physical exercise. Here, we review how physical exercise improves crucial molecular pathways and biological processes associated with metabolic disorders in AD, including glucose metabolism, lipid metabolism, Aβ metabolism and transport, iron metabolism and tau pathology. How metabolic states influence brain health is also presented. A better knowledge on the neurophysiological mechanisms by which exercise improves AD metabolism can contribute to the development of novel drugs and improvement of non-pharmacological interventions.

AbstractPenicillium oxalicum strain can be isolated from the Bletilla striata (Thunb.) Reichb. f. tubers. Its solid-state fermentation products are concentrated by percolation extraction. Separation and purification have been conducted to the ethyl acetate extracts by preparative HPLC. Based on the use of spectrometry, we have determined 17 known compounds, 12,13-dihydroxy-fumitremorgin C (1), pseurotin A (2), tyrosol (3), cyclo-(L-Pro-L-Val) (4), cis-4-hydroxy-8-O-methylmellein (5), uracil (6), cyclo-(L-Pro-L-Ala) (7), 1,2,3,4-tetrahydro-4-hydroxy-4-quinolin carboxylic acid (8), cyclo-(Gly-L-Pro) (9), 2'-deoxyuridine (10), 1-(β-D-ribofuranosyl)thymine (11), cyclo-(L-Val-Gly) (12), 2'-deoxythymidine (13), cyclo-(Gly-D-Phe) (14), cyclo-L-(4-hydroxyprolinyl)-D-leucine (15), cyclo-(L)-4-hydroxy-Pro-(L)-Phe (16), uridine (17). Here, we report compounds 1–3, 5, 7–8, 11–12, 14–17 are first found and isolated from this endophyte.

Abstract To describe the clinical spectrum and prognosis of atypical tumefactive demyelinating lesions (TDLs), which were confirmed by pathology. A total of 11 patients were diagnosed with atypical TDLs confirmed by brain biopsy and surgery between January 2006 and December 2017. The clinical spectrum and prognosis in these patients were analyzed. The patients’ ages ranged from 29 to 62 years, with a mean age of 48.9 years; 72.7% were males. The Expanded Disability Status Scale (EDSS) of the patients with first onset was 2.36. Most of the patients started with limb numbness and weakness (45.5%) or alalia (27.2%). The mean time from symptom onset to biopsy or surgery was 12.9 days (3–30 days). Most of the patients had solitary lesions (72.7%), supratentorial lesions (90.9%, particularly predominant in the frontal, temporal, and parietal lobes), moderate edema (63.6%), mild mass effect (54.5%), and patchy lesions (54.5%). Among them, three patients were positive for myelin basic protein (MBP) and one patient was positive for myelin oligodendrocyte glycoprotein (MOG). The patients were followed up for an average of 6.9 years (2–14 years), and recurrent TDLs were observed in 2 patients. Except for the 2 patients who relapsed, only 1 of the 9 patients died; the other 8 patients improved or maintained the status quo (the EDSS scores were lower or unchanged). The patients did not have any serious nervous system injury at onset, and the main presentation included extremity weakness, headache or dizziness, and alalia. The most common form was patchy on MRI enhancement. Cerebrospinal fluid and demyelination test can be an indicator of TDLs, and seizures may be a poor prognostic indicator. Most atypical TDLs have monophasic courses and good outcomes. The effect of neurosurgery alone was good in our group, and the effect of surgery on atypical TDLs can be further studied.