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In order to study the effect of typical transition metal ions on coal spontaneous combustion under low temperature oxidation conditions, the transition metal ions of lignite (HM), gas coal (QM) and fertilizer coal (FM) were determined, and Fe (Ⅲ), Mn (Ⅲ) and Cu (Ⅱ), which are abundant in transition metal ions and have strong oxidation, were selected as the research objects. The charge distribution, frontier orbitals and Laplacian bond levels were analyzed by the quantum chemistry calculation method, and the existence of active sites was proved. Two reaction processes of Ar—CH2—CH3 to Ar—CO—CH3 with or without transition metal ions were investigated, and the thermodynamic parameters were obtained by model optimization, transition state calculation and IRC verification. The calculation results show that the activation energy barrier is 164.18 kJ/mol without transition metal ion and 158.72 kJ/mol with transition metal ion. The effect of transition metal ion on the total reaction rate is not significant. With the participation of Fe (Ⅲ), Mn (Ⅲ) and Cu (Ⅱ), the total heat releases of the reaction are 1535.52, 1834.97 and 365.93 kJ/mol, respectively, which are higher than the heat release from the oxidation of aliphatic hydrocarbons by oxygen molecules (319.93 kJ/mol). The free energy barriers of C—H in oxidized aliphatic hydrocarbons are 42.79, 4.30 and 117.29 kJ/mol, respectively, which are all lower than the activation energies of C—H oxidation by oxygen molecules (146.38 kJ/mol). The order of C—H oxidation capacity of transition metal ions from high to low is Mn (Ⅲ), Fe (Ⅲ) and Cu (Ⅱ). During the reaction process, the formation of ·OH and H+ is accompanied by further reaction with the coal structure to accelerate the spontaneous combustion process of coal. In order to verify the accuracy of the simulation results, the time and concentration of CO gas products in four different coal samples were measured by temperature programmed gas chromatography. It was found that the temperature points of CO gas products in four coal samples were similar. The coal samples with manganese ion added produced CO gas products at 90 ℃, while the other three coal samples produced CO gas products at 100 ℃. The concentration of CO gas products from large to small is Mn (Ⅲ), Fe (Ⅲ), Cu (Ⅱ) and raw coal sample, which is consistent with the calculated results. With the increase of temperature, the effect of Mn (Ⅲ) on increasing the rate of CO production gradually weakens, and the effect of iron and copper ions on catalytic coal spontaneous combustion is gradually significant. The experimental results have a certain correlation with the simulation results. Compared with oxygen molecules, transition metal ions in coal are more likely to oxidize C—H, which not only causes the free radical chain reaction to occur earlier, but also increases the heat release of the reaction and the production of ·OH and H+, thus promoting spontaneous combustion of coal. This has reference significance for the mechanism of spontaneous combustion of transition metal catalyzed coal.

Abstract The Crumbs protein (CRB) family plays a crucial role in maintaining the apical–basal polarity and integrity of embryonic epithelia. The family comprises different isoforms in different animals and possesses diverse structural, localization, and functional characteristics. Mutations in the human CRB1 or CRB2 gene may lead to a broad spectrum of retinal dystrophies. Various CRB-associated experimental models have recently provided mechanistic insights into human CRB-associated retinopathies. The knowledge obtained from these models corroborates the importance of CRB in retinal development and maintenance. Therefore, complete elucidation of these models can provide excellent therapeutic prospects for human CRB-associated retinopathies. In this review, we summarize the current animal models and human-derived models of different CRB family members and describe the main characteristics of their retinal phenotypes.

The environmental stability of infectious viruses in the laboratory setting is crucial to the transmission potential of human respiratory viruses. Different experimental techniques or conditions used in studies over the past decades have led to diverse understandings and predictions for the stability of viral infectivity in the atmospheric environment. In this paper, we review the current knowledge on the effect of simulated atmospheric conditions on the infectivity of respiratory viruses, mainly focusing on influenza viruses and coronaviruses, including severe acute respiratory syndrome coronavirus 2 and Middle East respiratory syndrome coronavirus. First, we summarize the impact of the experimental conditions on viral stability; these involve the methods of viral aerosol generation, storage during aging and collection, the virus types and strains, the suspension matrixes, the initial inoculum volumes and concentrations, and the drying process. Second, we summarize and discuss the detection methods of viral infectivity and their disadvantages. Finally, we integrate the results from the reviewed studies to obtain an overall understanding of the effects of atmospheric environmental conditions on the decay of infectious viruses, especially aerosolized viruses. Overall, this review highlights the knowledge gaps in predicting the ability of viruses to maintain infectivity during airborne transmission.

Abstract Background Few studies have assessed the burden of mental disorders among children and adolescents considering the impact of co-morbidities and suicide on disability adjusted life years (DALYs). Methods This was a multicenter cross-sectional study. Our survey data in Liaoning Province (LN) were used to estimate the burden of six mental disorders, supplemented with data from other investigative studies conducted in China to assess four other disorders. DALYs were derived from the sum of years lived with a disability (YLDs) adjusted for co-morbidities, and the years of life lost (YLLs) adjusted for suicide. The changes in DALYs, YLDs, and YLLs were compared with and without adjustment for co-morbidities and suicide. Results The DALYs rate of mental disorders among children and adolescents in LN decreased from 1579.6/105 to 1391.4/105, after adjusting for both co-morbidities and suicide (-11.9%). The DALYs rate for major depression, anxiety disorder, and conduct disorder (-80.8/105, -75.0/105 and -30.2/105, respectively) were the top three contributors to the DALYs reduction (-188.2/105). The YLDs decreased from 72724.8 to 62478.5 after co-morbidity adjustment (-17.8%), mainly due to the reduction by major depression (-35.3%) and attention deficit/hyperactivity disorder [ADHD] (-34.2%). The YLLs increased from 130 to 1697.8 after adjusting for suicides (+ 56.9% of all suicide YLLs), mainly due to the contribution of major depression (+ 32.4%) and anxiety disorder (+ 10.4%). Compared to GBD 2010, the estimated DALY rate for mental disorders in LN was to be about 80%, with the proportion of DALYs and DALY rates explained by major depressive disorder accounted for only approximately one-third (14.6% vs. 41.9% and 202.6 vs. 759.9, respectively). But the proportion and absolute level of DALY rates explained by anxiety disorders were approximately 2-fold higher (39.7% vs. 19.6% and 552.2 vs. 323.3, respectively). Conclusions The DALYs of mental disorders among Chinese children and adolescents were approximately 80% of the global level, with anxiety disorders imposing about 2 times the global level. Co-morbidity and suicide must be adjusted when calculating DALYs.

Abstract Background The prospective phase III multi-centre L-MOCA trial (NCT03534453) has demonstrated the encouraging efficacy and manageable safety profile of olaparib maintenance therapy in the Asian (mainly Chinese) patients with platinum-sensitive relapsed ovarian cancer (PSROC). In this study, we report the preplanned exploratory biomarker analysis of the L-MOCA trial, which investigated the effects of homologous recombination deficiency (HRD) and programmed cell death ligand 1 (PD-L1) expression on olaparib efficacy. Methods HRD status was determined using the ACTHRD assay, an enrichment-based targeted next-generation sequencing assay. PD-L1 expression was assessed by SP263 immunohistochemistry assay. PD-L1 expression positivity was defined by the PD-L1 expression on ≥ 1% of immune cells. Kaplan–Meier method was utilised to analyse progression-free survival (PFS). Results This exploratory biomarker analysis included 225 patients and tested HRD status [N = 190; positive, N = 125 (65.8%)], PD-L1 expression [N = 196; positive, N = 56 (28.6%)], and BRCA1/2 mutation status (N = 219). The HRD-positive patients displayed greater median PFS than the HRD-negative patients [17.9 months (95% CI: 14.5–22.1) versus 9.2 months (95% CI: 7.5–13.8)]. PD-L1 was predominantly expressed on immune cells. Positive PD-L1 expression on immune cells was associated with shortened median PFS in the patients with germline BRCA1/2 mutations [14.5 months (95% CI: 7.4–18.2) versus 22.2 months (95% CI: 18.3–NA)]. Conversely, positive PD-L1 expression on immune cells was associated with prolonged median PFS in the patients with wild-type BRCA1/2 [20.9 months (95% CI: 13.9–NA) versus 8.3 months (95% CI: 6.7–13.8)]. Conclusions HRD remained an effective biomarker for enhanced olaparib efficacy in the Asian patients with PSROC. Positive PD-L1 expression was associated with decreased olaparib efficacy in the patients with germline BRCA1/2 mutations but associated with improved olaparib efficacy in the patients with wild-type BRCA1/2. Trial registration NCT03534453. Registered at May 23, 2018.

Abstract Purpose The purpose of this study was to compare the learning in the implant dentistry hands-on course to that of the flipped classroom (FC) and the traditional lecture cohorts (control). Materials and methods In this study,80 students were enrolled for the first time in an implant dentistry program. Subsequently, they were divided into two groups. The first, the FC group, which had free access to a video with a PowerPoint presentation on the Chaoxing-WHU-MOOC platform about the implant placement on first molar sites before class. The second, the control group, which attended a didactic lecture describing implant practice on the first molar site via a bidirectional multimedia interactive teaching demonstration and then operated on a simulation model. Cone beam computed tomography (CBCT) and the deviation gauge were utilized to analyze the accuracy of the implant placement in the students’ models. An online satisfaction questionnaire was distributed to both groups one week after the class. Results The linear deviation of the CBCT examination did not show any statistical difference between the two groups concerning cervical, apex, and angular. A significant buccal deviation was observed in the control group compared with the FC group (mean: 0.7436 mm vs. 0.2875 mm, p = 0.0035), according to the restoration-level deviation gauge. A total of 74.36% of students in the FC group placed implant within 0.5 mm buccal-to-lingual deviations, but only 41.03% of students in the control group reached within 0.5 mm buccal-to-lingual deviation ranges. Additionally, 91.67% of the students in the FC group and 97.5% of the students in the control group were satisfied with the practical implant class. Conclusion FC was more effective than a didactic lecture for implant dentistry practical skill acquisition.

Abstract Background Sleep disturbances are a common occurrence in patients with schizophrenia, yet the underlying pathogenesis remain poorly understood. Here, we performed a targeted metabolomics-based approach to explore the potential biological mechanisms contributing to sleep disturbances in schizophrenia. Methods Plasma samples from 59 drug-naïve patients with schizophrenia and 36 healthy controls were subjected to liquid chromatography-mass spectrometry (LC-MS) targeted metabolomics analysis, allowing for the quantification and profiling of 271 metabolites. Sleep quality and clinical symptoms were assessed using the Pittsburgh Sleep Quality Index (PSQI) and the Positive and Negative Symptom Scale (PANSS), respectively. Partial correlation analysis and orthogonal partial least squares discriminant analysis (OPLS-DA) model were used to identify metabolites specifically associated with sleep disturbances in drug-naïve schizophrenia. Results 16 characteristic metabolites were observed significantly associated with sleep disturbances in drug-naïve patients with schizophrenia. Furthermore, the glycerophospholipid metabolism (Impact: 0.138, p

Abstract The study of progressive failure of reservoir rocks is very important for the stability analysis of ultra-deep boreholes. The progressive failure can be characterized by the crack initiation stress (CI), crack damage stress (CD) and peak stress (Peak), which is controlled by the evolution of cracks in rock and is significantly affected by confining pressure. To explore the effect of high confining pressure and initial crack on the progressive failure, the initial crack density of 121 sedimentary rock samples was characterized by acoustic waves, and the progressive failure under different confining pressures was analyzed. Experiments show that the ratios of CI to Peak (CI/Peak) and CD to Peak (CD/Peak) increase significantly with confining pressure, which is agreement with the existing conclusion from low confining pressure (0–52 MPa), but those decrease for high confining pressure (68–85 MPa) above critical point of sandstone. The CI/Peak and CD/Peak decrease with increase of initial crack density, which is sensitive to confining pressure but independent of rock type and grain size. The CD of sandstone is pertinent to the friction coefficient of cracks. These results laid a foundation for analyzing the evolution mechanism of wellbore damage and predicting the timing of wellbore instability in ultra-deep wells.

Background: Retinoblastoma (RB) is a rare primary malignant tumor primarily affecting children. Our study aims to compare the overall survival (OS) between pediatric and adult RB patients and establish a predictive model for adult RB patients' OS to assist clinical decision-making. Methods: This study retrospectively analyzed data from 1938 RB patients in the Surveillance, Epidemiology, and End Results (SEER) database, covering the period from 2000 to 2015. Propensity score matching (PSM) ensured balanced characteristics between pediatric and adult groups. A Cox proportional hazards regression model was used to assess prognostic factors, and selected variables were utilized to construct a predictive survival model. The Nomogram model's performance was evaluated through the C-index, time-dependent ROC curves, calibration curves, and decision curve analysis (DCA). Results: Following PSM, adult RB patients had lower OS compared to pediatric RB patients. Independent prognostic factors for adult RB OS included age, gender, disease stage, radiation therapy, income, and diagnosis confirmation. In the training cohort, the Nomogram achieved a C-index for OS of 0.686 and accurately predicted 2-year, 3-year, and 5-year OS with AUC values of 0.672, 0.680, and 0.660, respectively. The C-index, time-dependent ROC curves, calibration curves, and DCA in both training and validation cohorts confirmed the Nomogram's excellent performance. Conclusion: In this study, adult RB patients have worse OS than pediatric RB patients. Consequently, we constructed a Nomogram to predict the risk for adult RB patients. The Nomogram demonstrated good accuracy and reliability, making it suitable for widespread application in clinical practice to assist healthcare professionals in assessing patients’ prognoses.

This study aims to improve the accuracy of predicting the severity of traffic accidents by developing an innovative traffic accident risk prediction model—StackTrafficRiskPrediction. The model combines multidimensional data analysis including environmental factors, human factors, roadway characteristics, and accident-related meta-features. In the model comparison, the StackTrafficRiskPrediction model achieves an accuracy of 0.9613, 0.9069, and 0.7508 in predicting fatal, serious, and minor accidents, respectively, which significantly outperforms the traditional logistic regression model. In the experimental part, we analyzed the severity of traffic accidents under different age groups of drivers, driving experience, road conditions, light and weather conditions. The results showed that drivers between 31 and 50 years of age with 2 to 5 years of driving experience were more likely to be involved in serious crashes. In addition, it was found that drivers tend to adopt a more cautious driving style in poor road and weather conditions, which increases the margin of safety. In terms of model evaluation, the StackTrafficRiskPrediction model performs best in terms of accuracy, recall, and ROC–AUC values, but performs poorly in predicting small-sample categories. Our study also revealed limitations of the current methodology, such as the sample imbalance problem and the limitations of environmental and human factors in the study. Future research can overcome these limitations by collecting more diverse data, exploring a wider range of influencing factors, and applying more advanced data analysis techniques.

Abstract It is known that the heterogeneity caused by thermally induced micro-cracks and thermal stress can affect the mechanical behavior of granite. The laboratory-scale tests have the intrinsic limitation of non-repeatability and lack of effective methods to characterize the interaction effect between thermal micro-cracks and thermal stresses. In this study, we demonstrate how advancements in particle bonded model and moment tensor can help better understand the roles of high temperature in weakening granite and thermally induced cracking process in Brazilian test. Our results show that the types of micro-cracks (intergranular, intragranular, and transcrystalline ones) are related to their thermal expansion coefficients of mineralogical compositions. The intergranular tensile micro-cracks are predominant during the heating and heating–cooling processes. An obvious weakening of granite and non-central initiation is associated with the heterogeneity caused by the thermal damage and thermal stress. We also quantitatively evaluate the thermal damage based on orientation distribution, b-value, and nature of the sources, which gives a new microcracking perspective on tensile characteristics subjected to high temperature.

Abstract Age-related cataract and hearing difficulties are major sensory disorders that often co-exist in the global-wide elderly and have a tangible influence on the quality of life. However, the epidemiologic association between cataract and hearing difficulties remains unexplored, while little is known about whether the two share their genetic etiology. We first investigated the clinical association between cataract and hearing difficulties using the UK Biobank covering 502,543 individuals. Both unmatched analysis (adjusted for confounders) and a matched analysis (one control matched for each patient with cataract according to confounding factors) were undertaken and confirmed that cataract was associated with hearing difficulties (OR, 2.12; 95% CI, 1.98–2.27; OR, 2.03; 95% CI, 1.86–2.23, respectively). Furthermore, we explored and quantified the shared genetic architecture of these two complex sensory disorders at the common variant level using the bivariate causal mixture model (MiXeR) and conditional/conjunctional false discovery rate method based on the largest available genome-wide association studies of cataract (N = 585,243) and hearing difficulties (N = 323,978). Despite detecting only a negligible genetic correlation, we observe polygenic overlap between cataract and hearing difficulties and identify 6 shared loci with mixed directions of effects. Follow-up analysis of the shared loci implicates candidate genes QKI, STK17A, TYR, NSF, and TCF4 likely contribute to the pathophysiology of cataracts and hearing difficulties. In conclusion, this study demonstrates the presence of epidemiologic association between cataract and hearing difficulties and provides new insights into the shared genetic architecture of these two disorders at the common variant level.

Abstract Objective Restless legs syndrome (RLS) stands as a prevalent neurological complication within maintenance hemodialysis (MHD) patients. However, the alterations in cerebral blood flow (CBF) among MHD-RLS patients remain uncharted. Through the utilization of the arterial spin labeling (ASL) technique, we evaluated the fluctuations in CBF within distinct brain regions and analyzed the risk factors for the development of RLS in MHD patients in the context of the clinic. Methods Thirty-one MHD patients with concomitant RLS (MHD-RLS group) and thirty-one non-RLS patients matched based on age, gender, as well as cognitive function (MHD-nRLS group) were included. Through image preprocessing and data analysis, the changes in CBF values in distinct brain regions were obtained, and the CBF values of brain regions with substantial differences between the two groups were correlated with the RLS scores. Furthermore, the differences in baseline data were compared, and through the utilization of multifactorial logistic regression, the independent risk factors for the development of RLS were examined. Results Compared with the MHD-nRLS group, the MHD-RLS group had increased CBF in the right superior temporal gyrus, reduced CBF in the right hippocampus, left middle frontal gyrus, inferior frontal gyrus of right triangle, middle frontal gyrus of left orbit, left precentral gyrus, and left precuneus. Only left precentral gyrus CBF were negatively correlated with RLS scores after correction for dialysis duration(r = -0.436, P = 0.016). Accordingly, multifactorial regression analysis by stepwise method yielded that the left precentral gyrus CBF values(OR: 0.968, 95%CI: 0.944–0.993, P = 0.012) remained an independent risk factor for RLS in MHD patients. In addition, the results showed that hemodialysis duration (OR: 1.055, 95%CI: 1.014–1.098, P = 0.008) and serum iron levels (OR: 0.685, 95%CI: 0.551–0.852, P = 0.001) were also risk factors for the development of RLS. Conclusion Patients afflicted with MHD-RLS exhibit alterations in CBF across several brain regions. Notably, the left precentral gyrus might serve as a pivotal region influencing the onset of RLS among MHD patients. Furthermore, extended hemodialysis duration and a relative insufficiency in serum iron levels independently contribute as risk factors for RLS development within the MHD patient population.

Abstract Background Patients with disorders of consciousness (DoC) exhibit varied revival outcomes based on different etiologies and diagnoses, the mechanisms of which remain largely unknown. The fluctuating clinical presentations in DoC pose challenges in accurately assessing consciousness levels and prognoses, often leading to misdiagnoses. There is an urgent need for a deeper understanding of the physiological changes in DoC and the development of objective diagnostic and prognostic biomarkers to improve treatment guidance. Methods To explore biomarkers and understand the biological processes, we conducted a comprehensive untargeted metabolomic analysis on serum samples from 48 patients with DoC. Patients were categorized based on etiology (TBI vs. non-TBI), CRS-R scores, and prognosis. Advanced analytical techniques, including PCA and OPLS-DA models, were employed to identify differential metabolites. Results Our analysis revealed a distinct separation in metabolomic profiles among the different groups. The primary differential metabolites distinguishing patients with varying etiologies were predominantly phospholipids, with a notable decrease in glycerophospholipids observed in the TBI group. Patients with higher CRS-R scores exhibited a pattern of impaired carbohydrate metabolism coupled with enhanced lipid metabolism. Notably, serum concentrations of both LysoPE and PE were reduced in patients with improved outcomes, suggesting their potential as prognostic biomarkers. Conclusions Our study underscores the critical role of phospholipid metabolism in the brain’s metabolic alterations in patients with DoC. It identifies key biomarkers for diagnosis and prognosis, offering insights that could lead to novel therapeutic targets. These findings highlight the value of metabolomic profiling in understanding and potentially treating DoC.

Abstract Background Climate change is expected to alter the factors that drive changes in adaptive variation. This is especially true for species with long life spans and limited dispersal capabilities. Rapid climate changes may disrupt the migration of beneficial genetic variations, making it challenging for them to keep up with changing environments. Understanding adaptive genetic variations in tree species is crucial for conservation and effective forest management. Our study used landscape genomic analyses and phenotypic traits from a thorough sampling across the entire range of Quercus longinux, an oak species native to Taiwan, to investigate the signals of adaptation within this species. Results Using ecological data, phenotypic traits, and 1,933 single-nucleotide polymorphisms (SNPs) from 205 individuals, we classified three genetic groups, which were also phenotypically and ecologically divergent. Thirty-five genes related to drought and freeze resistance displayed signatures of natural selection. The adaptive variation was driven by diverse environmental pressures such as low spring precipitation, low annual temperature, and soil grid sizes. Using linear-regression-based methods, we identified isolation by environment (IBE) as the optimal model for adaptive SNPs. Redundancy analysis (RDA) further revealed a substantial joint influence of demography, geology, and environments, suggesting a covariation between environmental gradients and colonization history. Lastly, we utilized adaptive signals to estimate the genetic offset for each individual under diverse climate change scenarios. The required genetic changes and migration distance are larger in severe climates. Our prediction also reveals potential threats to edge populations in northern and southeastern Taiwan due to escalating temperatures and precipitation reallocation. Conclusions We demonstrate the intricate influence of ecological heterogeneity on genetic and phenotypic adaptation of an oak species. The adaptation is also driven by some rarely studied environmental factors, including wind speed and soil features. Furthermore, the genetic offset analysis predicted that the edge populations of Q. longinux in lower elevations might face higher risks of local extinctions under climate change.

Abstract To investigate the associations between corneal curvature (CC) and other anterior segment biometrics in young myopic adults. In this retrospective multi-center study, 7893 young myopic adults were included. CC and other anterior segment biometrics were measured by Scheimpflug imaging (Pentacam). CC was defined as SimK at central 3 mm area, and other anterior segment biometrics included white-to-white corneal diameter (WTW), central corneal thickness (CCT), corneal volume (CV) at 3 mm, 5 mm, and 7 mm area, anterior corneal astigmatism (ACA), posterior corneal astigmatism (PCA), anterior corneal eccentricity (ACE) and asphericity (ACAP), posterior corneal eccentricity (PCE) and asphericity (PCAP), anterior chamber depth (ACD), and anterior chamber volume (ACV). Univariate regression analyses were used to assess the associations between CC and other anterior segment biometrics, and multivariate regression analyses were further performed to adjusted for age, gender and spherical equivalent. CC was higher in patients of female gender and higher myopia (all P

Abstract The analysis of optical spectra—emission or absorption—has been arguably the most powerful approach for discovering and understanding matter. The invention and development of many kinds of spectrometers have equipped us with versatile yet ultra-sensitive diagnostic tools for trace gas detection, isotope analysis, and resolving hyperfine structures of atoms and molecules. With proliferating data and information, urgent and demanding requirements have been placed today on spectrum analysis with ever-increasing spectral bandwidth and frequency resolution. These requirements are especially stringent for broadband laser sources that carry massive information and for dispersive devices used in information processing systems. In addition, spectrum analyzers are expected to probe the device’s phase response where extra information is encoded. Here we demonstrate a novel vector spectrum analyzer (VSA) that is capable of characterizing passive devices and active laser sources in one setup. Such a dual-mode VSA can measure loss, phase response, and dispersion properties of passive devices. It also can coherently map a broadband laser spectrum into the RF domain. The VSA features a bandwidth of 55.1 THz (1260–1640 nm), a frequency resolution of 471 kHz, and a dynamic range of 56 dB. Meanwhile, our fiber-based VSA is compact and robust. It requires neither high-speed modulators and photodetectors nor any active feedback control. Finally, we employ our VSA for applications including characterization of integrated dispersive waveguides, mapping frequency comb spectra, and coherent light detection and ranging (LiDAR). Our VSA presents an innovative approach for device analysis and laser spectroscopy, and can play a critical role in future photonic systems and applications for sensing, communication, imaging, and quantum information processing.

Rapidly expanding studies investigate the effects of e-commerce on company operations in the retail market. However, the interaction between agri-food e-commerce (AEC) and the traditional agri-food wholesale industry (AWI) has not received enough attention in the existing literature. Based on the provincial panel data from 2013 to 2020 in China, this paper examines the effect of AEC on AWI, comprising three dimensions: digitalization (DIGITAL), agri-food e-commerce infrastructure and supporting services (AECI), and agri-food e-commerce economy (AECE). First, AWI and AEC are measured using an entropy-based combination of indicators. The results indicate that for China as a whole, AWI has remained practically unchanged, whereas AEC exhibits a significant rising trend. Second, the findings of the fixed-effect regression reveal that DIGITAL and AECE tend to raise AWI, whereas AECI negatively affects AWI. Third, threshold regression results indicate that AECI tends to diminish AWI with three-stage inhibitory intensity, which manifests as a first increase and then a drop in the inhibition degree. These results suggest that with the introduction of e-commerce for agricultural product circulation, digital development will have catfish effects that tend to stimulate the vitality of the conventional wholesale industry and promote technical progress. Furthermore, the traditional wholesale industry benefits financially from e-commerce even while it diverts part of the traditional wholesale circulation for agricultural products.

Crocus sativus (saffron) is a globally autumn-flowering plant, and its stigmas are the most expensive spice and valuable herb medicine. Crocus specialized metabolites, crocins, are biosynthesized in distant species, Gardenia (eudicot) and Crocus (monocot), and the evolution of crocin biosynthesis remains poorly understood. With the chromosome-level Crocus genome assembly, we revealed that two rounds of lineage-specific whole genome triplication occurred, contributing important roles in the production of carotenoids and apocarotenoids. According to the kingdom-wide identification, phylogenetic analysis, and functional assays of carotenoid cleavage dioxygenases (CCDs), we deduced that the duplication, site positive selection, and neofunctionalization of Crocus-specific CCD2 from CCD1 members are responsible for the crocin biosynthesis. In addition, site mutation of CsCCD2 revealed the key amino acids, including I143, L146, R161, E181, T259, and S292 related to the catalytic activity of zeaxanthin cleavage. Our study provides important insights into the origin and evolution of plant specialized metabolites, which are derived by duplication events of biosynthetic genes.

Objective: To investigate the effect of a 16-week Tai Chi practice on strength, tactile sensation, kinesthesia, and static postural control among older adults of different age groups. Methods: This is a quasi-experimental study. Thirteen participants aged 60–69 years (60–69yr), 11 aged 70–79 years (70–79yr), and 13 aged 80–89 years (80–89yr) completed 16 weeks of 24-form Tai Chi practice. Their ankle and hip peak torque, tactile sensation, ankle and knee kinesthesia, and the root mean square of the center of pressure (Cop-RMS) were measured before (week 0) and after (week 17) practice. Results: 80–89yr showed less ankle plantar/dorsiflexion and hip abduction peak torques (p = 0.003, p

Aiming at the development problems of deep coal reservoirs, such as deep burial, low permeability and complex stress field, this paper clarifies that the resource enrichment conditions, effective fracturing volume, effective horizontal section length, and good reservoir conditions are the key factors for high productivity on the basis of summarizing the exploration and development practice of the Daning-Jixian Block in the past five years. Under the guidance of the theory of “artificial gas reservoir” development, a technical system for the efficient development of deep coalbed methane was preliminarily established as follows. ① According to the reservoir resource conditions, structural preservation conditions and engineering fracturing conditions, a total of 11 indicators in three categories established the geological-engineering “dessert” evaluation standards of deep coalbed methane. ② Based on the techniques such as microstructural characterization, multi-scale fracture prediction, and 3D geological model construction, the quantitative and visual characterization of all elements of “geology + engineering” of deep coal seam was achieved. ③ Based on the guiding idea of “geological small scale, three-dimensional seismic microscale, drill along the target, less adjustment and fast drilling”, a three-stage geological-engineering geo-steering technology with an excellent design of pre-drilling trajectory, precise target entry and post-target fine-tuning as the core was developed.④ The optimization design of the five-in-one well network based on “in-situ stress field, natural fracture field, artificial fracture field, well type and orientation, well network and well spacing” realized the maximization of resource utilization and the maximization of gas field recovery. ⑤ According to the occurrence characteristics, seepage mechanism and production characteristics of deep coalbed methane, a reasonable production capacity evaluation and EUR prediction technology based on the rate-transient analysis method, the empirical production decline method, the numerical simulation method, and the empirical analogy method was formed. ⑥ Following to the design principle of “four-in-one” precision fracturing section and “fracture staggering + differentiation between fracturing segments”, a large-scale volumetric fracturing technology aimed at constructing artificial gas reservoirs was proposed.⑦ According to the characteristics of gas-water variation in gas wells, the optimal control technology of drainage and production in different production stages through the whole life cycle of wells was put forwarded. ⑧ Combined with the current progress of AI technology, and the characteristics of deep coalbed methane development law, gathering and transportation, the technology of gathering, transportation and digital intelligence integrating geological, engineering, and ground aspects was explored. Under the guidance of this achievement, 29 horizontal wells that have been put into production，with an initial production of 5×104−16×104 m3/d, an average of 10.2×104 m3/d, and the daily gas production of the block has exceeded 3 million cubic meters, which has important guiding significance for accelerating the large-scale production of deep coalbed methane in the eastern margin of the Ordos basin. Also the study establishes a reference and standard for the efficient development of similar resources.

Abstract Despite orientationally variant tears of the meniscus, suture repair is the current clinical gold treatment. However, inaccessible tears in company with re-tears susceptibility remain unresolved. To extend meniscal repair tools from the perspective of adhesion and regeneration, we design a dual functional biologic-released bioadhesive (S-PIL10) comprised of methacrylated silk fibroin crosslinked with phenylboronic acid-ionic liquid loading with growth factor TGF-β1, which integrates chemo-mechanical restoration with inner meniscal regeneration. Supramolecular interactions of β-sheets and hydrogen bonds richened by phenylboronic acid-ionic liquid (PIL) result in enhanced wet adhesion, swelling resistance, and anti-fatigue capabilities, compared to neat silk fibroin gel. Besides, elimination of reactive oxygen species (ROS) by S-PIL10 further fortifies localized meniscus tear repair by affecting inflammatory microenvironment with dynamic borate ester bonds, and S-PIL10 continuously releases TGF-β1 for cell recruitment and bridging of defect edge. In vivo rabbit models functionally evidence the seamless and dense reconstruction of torn meniscus, verifying that the concept of meniscus adhesive is feasible and providing a promising revolutionary strategy for preclinical research to repair meniscus tears.

Abstract Large‐scale underground hydrogen storage (UHS) provides a promising method for increasing the role of hydrogen in the process of carbon neutrality and energy transition. Of all the existing storage deposits, salt caverns are recognized as ideal sites for pure hydrogen storage. Evaluation and optimization of site selection for hydrogen storage facilities in salt caverns have become significant issues. In this article, the software CiteSpace is used to analyze and filter hot topics in published research. Based on a detailed classification and analysis, a “four‐factor” model for the site selection of salt cavern hydrogen storage is proposed, encompassing the dynamic demands of hydrogen energy, geological, hydrological, and ground factors of salt mines. Subsequently, 20 basic indicators for comprehensive suitability grading of the target site were screened using the analytic hierarchy process and expert survey methods were adopted, which provided a preliminary site selection system for salt cavern hydrogen storage. Ultimately, the developed system was applied for the evaluation of salt cavern hydrogen storage sites in the salt mines of Pingdingshan City, Henan Province, thereby confirming its rationality and effectiveness. This research provides a feasible method and theoretical basis for the site selection of UHS in salt caverns in China.

Abstract Exercise is a potential treatment to improve sleep quality in middle-aged and elderly individuals. Understanding exercise-induced changes in functional plasticity of brain circuits that underlie improvements in sleep among middle-aged and older adults can inform treatment of sleep problems. The aim of the study is to identify the effects of a 12-week exercise program on sleep quality and brain functional connectivity in middle-aged and older adults with insomnia. The trial was registered with Chinese Clinical Trial Register (ChiCTR2000033652). We recruited 84 healthy sleepers and 85 individuals with insomnia. Participants with insomnia were assigned to receive either a 12-week exercise intervention or were placed in a 12-week waitlist control condition. Thirty-seven middle-aged and older adults in the exercise group and 30 in the waitlist group completed both baseline and week 12 assessments. We found that middle-aged and older adults with insomnia showed significantly worse sleep quality than healthy sleepers. At the brain circuit level, insomnia patients showed decreased connectivity in the widespread motor network. After exercise intervention, self-reported sleep was increased in the exercise group (P

Abstract Greenspaces are important for sustaining healthy urban environments and their human populations. Yet their capacity to support multiple ecosystem services simultaneously (multiservices) compared with nearby natural ecosystems remains virtually unknown. We conducted a global field survey in 56 urban areas to investigate the influence of urban greenspaces on 23 soil and plant attributes and compared them with nearby natural environments. We show that, in general, urban greenspaces and nearby natural areas support similar levels of soil multiservices, with only six of 23 attributes (available phosphorus, water holding capacity, water respiration, plant cover, arbuscular mycorrhizal fungi (AMF), and arachnid richness) significantly greater in greenspaces, and one (available ammonium) greater in natural areas. Further analyses showed that, although natural areas and urban greenspaces delivered a similar number of services at low (>25% threshold) and moderate (>50%) levels of functioning, natural systems supported significantly more functions at high (>75%) levels of functioning. Management practices (mowing) played an important role in explaining urban ecosystem services, but there were no effects of fertilisation or irrigation. Some services declined with increasing site size, for both greenspaces and natural areas. Our work highlights the fact that urban greenspaces are more similar to natural environments than previously reported and underscores the importance of managing urban greenspaces not only for their social and recreational values, but for supporting multiple ecosystem services on which soils and human well-being depends.

Abstract Background The study aimed to investigate the association between nonalcoholic fatty liver disease (NAFLD) and ischemic stroke events after revascularization in patients with Moyamoya disease (MMD). Methods This study prospectively enrolled 275 MMD patients from September 2020 to December 2021. Patients with alcoholism and other liver diseases were excluded. NAFLD was confirmed by CT imaging or abdominal ultrasonography. Stroke events and modified Rankin Scale (mRS) scores at the latest follow-up were compared between the two groups. Results A total of 275 patients were enrolled in the study, among which 65 were diagnosed with NAFLD. Univariate logistic regression analysis showed that NAFLD (P = 0.029) was related to stroke events. Multivariate logistic regression analysis showed that NAFLD is a predictor of postoperative stroke in MMD patients (OR = 27.145, 95% CI = 2.031–362.81, P = 0.013). Kaplan-Meier analysis showed that compared with MMD patients with NAFLD, patients in the control group had a longer stroke-free time (P = 0.004). Univariate Cox analysis showed that NAFLD (P = 0.016) was associated with ischemic stroke during follow-up in patients with MMD. Multivariate Cox analysis showed that NAFLD was an independent risk factor for stroke in patients with MMD (HR = 10.815, 95% CI = 1.259–92.881, P = 0.030). Furthermore, fewer patients in the NAFLD group had good neurologic status (mRS score ≤ 2) than the control group (P = 0.005). Conclusion NAFLD was an independent risk factor for stroke in patients with MMD after revascularization and worse neurological function outcomes.

Abstract Liver injury is a core pathological process in the majority of liver diseases, yet the genetic factors predisposing individuals to its initiation and progression remain poorly understood. Here we show that asialoglycoprotein receptor 1 (ASGR1), a lectin specifically expressed in the liver, is downregulated in patients with liver fibrosis or cirrhosis and male mice with liver injury. ASGR1 deficiency exacerbates while its overexpression mitigates acetaminophen-induced acute and CCl4-induced chronic liver injuries in male mice. Mechanistically, ASGR1 binds to an endoplasmic reticulum stress mediator GP73 and facilitates its lysosomal degradation. ASGR1 depletion increases circulating GP73 levels and promotes the interaction between GP73 and BIP to activate endoplasmic reticulum stress, leading to liver injury. Neutralization of GP73 not only attenuates ASGR1 deficiency-induced liver injuries but also improves survival in mice received a lethal dose of acetaminophen. Collectively, these findings identify ASGR1 as a potential genetic determinant of susceptibility to liver injury and propose it as a therapeutic target for the treatment of liver injury.

Abstract Background Bone implant infections pose a critical challenge in orthopedic surgery, often leading to implant failure. The potential of implant coatings to deter infections by hindering biofilm formation is promising. However, a shortage of cost-effective, efficient, and clinically suitable coatings persists. Polyvinyl alcohol (PVA), a prevalent biomaterial, possesses inherent hydrophilicity, offering potential antibacterial properties. Methods This study investigates the PVA solution's capacity to shield implants from bacterial adhesion, suppress bacterial proliferation, and thwart biofilm development. PVA solutions at concentrations of 5%, 10%, 15%, and 20% were prepared. In vitro assessments evaluated PVA's ability to impede bacterial growth and biofilm formation. The interaction between PVA and mCherry-labeled Escherichia coli (E. coli) was scrutinized, along with PVA’s therapeutic effects in a rat osteomyelitis model. Results The PVA solution effectively restrained bacterial proliferation and biofilm formation on titanium implants. PVA solution had no substantial impact on the activity or osteogenic potential of MC3T3-E1 cells. Post-operatively, the PVA solution markedly reduced the number of Staphylococcus aureus and E. coli colonies surrounding the implant. Imaging and histological scores exhibited significant improvements 2 weeks post-operation. Additionally, no abnormalities were detected in the internal organs of PVA-treated rats. Conclusions PVA solution emerges as an economical, uncomplicated, and effective coating material for inhibiting bacterial replication and biofilm formation on implant surfaces, even in high-contamination surgical environments.

Abstract Background Currently, noninvasive imaging techniques and circulating biomarkers are still insufficient to accurately assess carotid plaque stability, and an in-depth understanding of the molecular mechanisms that contribute to plaque instability is still lacking. Methods We established a clinical study cohort containing 182 patients with carotid artery stenosis. After screening, 39 stable and 49 unstable plaques were included in the discovery group, and quantitative proteomics analysis based on data independent acquisition was performed for these plaque samples. Additionally, 35 plaques were included in the validation group to validate the proteomics results by immunohistochemistry analysis. Results A total of 397 differentially expressed proteins were identified in stable and unstable plaques. These proteins are primarily involved in ferroptosis and lipid metabolism-related functions and pathways. Plaque validation results showed that ferroptosis- and lipid metabolism-related proteins had different expression trends in stable plaques versus unstable fibrous cap regions and lipid core regions. Ferroptosis- and lipid metabolism-related mechanisms in plaque stability were discussed. Conclusions Our results may provide a valuable strategy for revealing the mechanisms affecting plaque stability and will facilitate the discovery of specific biomarkers to broaden the therapeutic scope.

Abstract Automatic and accurate recognition of abnormal working conditions of fused magnesia furnace is of great significance to the safe and reliable production of fused magnesia. Aiming at the defects of manual judgment of abnormal working conditions in the production process of fused magnesium furnace and the existing recognition method of abnormal working conditions based on machine learning, this paper proposes a working condition recognition model for fused magnesium furnace based on stochastic configuration networks and reinforcement learning. Firstly, a hybrid data augmentation method of generative and non-generative is used to obtain high-quality sample data with salient features. Secondly, based on ResNeXt, multi-scale local features are extracted under the condition of limited parameter quantity by controlling the cardinality. Combining a mixed model that enjoys the benefit of both self-attention and convolution (ACmix) and bidirectional feature pyramid network (BiFPN), the extracted local feature maps of different scales are cross-scale fused and focused, and more differentiated detailed feature information of the region of interest is retained. Thirdly, based on Transformer, the working condition recognition network of fused magnesium furnace is constructed to improve the global correlation between adjacent local features in the spatial dimension. The fused features are sent to stochastic configuration networks to establish a classification criterion for working condition recognition of fused magnesium furnace with generalization ability. Finally, reinforcement learning is used to evaluate the credibility of uncertain recognition results of samples in real time, and a self-optimizing adjustment action strategy at the Transformer encoding layer is defined. Build a library of Transformer models with different encoding layers, which is adapt to the different feature extraction requirements of multi-modal working samples. The experimental results show that the method in this paper has better recognition performance and generalization ability than other algorithms.

A systematic analytical approach has been developed to comprehensively characterize the creep damage material properties of coatings on thin-layer substrates. This involves conducting creep tests using a compound, two-material, miniaturized thin plate specimen (MTPS) with an inverse approach. For demonstration, independent creep tests were performed on miniature specimens of the substrate (P91 steel) and the coating (CoNiCrAlY) at 650 °C, as well as on compound substrate-coating specimens. The reference stress method, coupled with finite element analysis, was utilized to obtain conversion parameters for strain data from the miniature specimen tests. Analytical solutions for the Kachanov creep damage model specific to the two-material substrate-coating system were adopted for inverse optimization. The MTPS testing method and the associated inverse approach have proven effective in accurately determining the complete three-stage creep constants within the coating-substrate system. Results obtained for the P91–CoNiCrAlY coated system have shown a clear demonstration of the accuracy and capability of the method in identifying the full sets of uniaxial creep damage properties, i.e. A, n, m, B, χ, and φ, provided the feasible experimental data are available.

In vitro assessments for the prediction of pharmacokinetic (PK) behavior of biotherapeutics can help identify corresponding liabilities significantly earlier in the discovery timeline. This can minimize the need for extensive early in vivo PK characterization, thereby reducing animal usage and optimizing resources. In this study, we recommend bolstering classical developability workflows with in vitro measures correlated with PK. In agreement with current literature, in vitro measures assessing nonspecific interactions, self-interaction, and FcRn interaction are demonstrated to have the highest correlations to clearance in hFcRn Tg32 mice. Crucially, the dataset used in this study has broad sequence diversity and a range of physicochemical properties, adding robustness to our recommendations. Finally, we demonstrate a computational approach that combines multiple in vitro measurements with a multivariate regression model to improve the correlation to PK compared to any individual assessment. Our work demonstrates that a judicious choice of high throughput in vitro measurements and computational predictions enables the prioritization of candidate molecules with desired PK properties.

The diagnostic criteria for preeclampsia do not accurately reflect the pathophysiological characteristics of patients with preeclampsia. Conventional biomarkers and diagnostic approaches have proven insufficient to fully comprehend the intricacies of preeclampsia. This study aimed to screen differentially abundant metabolites as candidate biomarkers for preeclampsia. A propensity score matching method was used to perform a 1:1 match between preeclampsia patients (n = 70) and healthy control individuals (n = 70). Based on univariate and multivariate statistical analysis methods, the different characteristic metabolites were screened and identified. Least absolute shrinkage and selection operator (LASSO) regression analysis was subsequently used to further screen for differentially abundant metabolites. A receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic efficacy of the metabolites. A total of 1,630 metabolites were identified and quantified in maternal serum samples. Fifty-three metabolites were significantly increased, and two were significantly decreased in preeclampsia patients. The area under the curve (AUC) of the model composed of isobutyryl-L-carnitine and acetyl-leucine was 0.878, and the sensitivity and specificity in detecting preeclampsia were 81.4% and 87.1%, respectively. There are significant differences in metabolism between preeclampsia patients and healthy pregnant women, and a range of novel biomarkers have been identified. These findings lay the foundation for the use of metabolomic biomarkers for the diagnosis of preeclampsia.

This study assesses sediment erosion rates in the Zhoukou River Basin in southern Taiwan over the past three decades, focusing on the impact of extreme rainfall events. While various established methods determine erosion rates over different temporal scales, we employ an independent approach for decadal-scale erosion rate calculation by utilizing open-source global and regional digital elevation models (DEMs) data for two distinct periods. We introduce a new method that applies Fourier analysis to vertically register the DEMs, significantly minimizing their vertical bias. Through spectral analysis, we identify long wavelength topography crucial for correcting vertical offsets. Erosion rates, computed through DEMs of Difference (DoD), exhibit a similar trend of significant reduction in sediment export rates from 1990–2010 to 2011–2020 due to decreased extreme rainfall events, aligning with erosion rate estimates derived from mean suspended load data at gauge stations. Over the entire period from 1990 to 2020, the calculated denudation rate was 14.19 mm/yr, whereas in the recent decade (2011–2020), it decreased to 10.46 mm/yr. Our study suggests that the improved DoD method can effectively estimate sediment transport rates by leveraging underutilized DEMs captured at distinct points in time, especially when the erosional signal dominates data noise.

ABSTRACTThe gut commensal bacteria Christensenellaceae species are negatively associated with many metabolic diseases, and have been seen as promising next-generation probiotics. However, the cultured Christensenellaceae strain resources were limited, and their beneficial mechanisms for improving metabolic diseases have yet to be explored. In this study, we developed a method that enabled the enrichment and cultivation of Christensenellaceae strains from fecal samples. Using this method, a collection of Christensenellaceae Gut Microbial Biobank (ChrisGMB) was established, composed of 87 strains and genomes that represent 14 species of 8 genera. Seven species were first described and the cultured Christensenellaceae resources have been significantly expanded at species and strain levels. Christensenella strains exerted different abilities in utilization of various complex polysaccharides and other carbon sources, exhibited host-adaptation capabilities such as acid tolerance and bile tolerance, produced a wide range of volatile probiotic metabolites and secondary bile acids. Cohort analyses demonstrated that Christensenellaceae and Christensenella were prevalent in various cohorts and the abundances were significantly reduced in T2D and OB cohorts. At species level, Christensenellaceae showed different changes among healthy and disease cohorts. C. faecalis, F. tenuis, L. tenuis, and Guo. tenuis significantly reduced in all the metabolic disease cohorts. The relative abundances of C. minuta, C. hongkongensis and C. massiliensis showed no significant change in NAFLD and ACVD. and C. tenuis and C. acetigenes showed no significant change in ACVD, and Q. tenuis and Geh. tenuis showed no significant change in NAFLD, when compared with the HC cohort. So far as we know, this is the largest collection of cultured resource and first exploration of Christensenellaceae prevalences and abundances at species level.

ABSTRACTBackground The atherogenic index of plasma (AIP) is a novel metabolic biomarker of atherosclerosis. Nevertheless, the association between the AIP and new-onset hypertension has not been elucidated in the Chinese population.Methods Prospective data were obtained from 3150 participants aged ≥ 18 years in the China Health and Nutrition Survey from 2009 to 2015. The AIP is a logarithmically transformed ratio of triglycerides to high-density lipoprotein cholesterol in molar concentration. Cox regression analysis was used to determine the association of AIP index with new-onset hypertension.Results After the six-year follow-up, 1054 (33.4%) participants developed new-onset hypertension. The participants were divided into AIP quartile groups (Q1-Q4). Compared with those in Q1, subjects in Q3–4 had nearly 1.35 times the risk of new-onset hypertension after full adjustment [Q3: hazard ratio (HR): 1.35, 95% confidence interval (CI): 1.13–1.62; Q4: HR: 1.35, 95% CI: 1.13–1.64]. The risks of new-onset hypertension were nearly 1.30 times higher in subjects in Q2–4 than in subjects in Q1 (p

Renal fibrosis is a common feature of various chronic kidney diseases. However, the underlying mechanism remains poorly understood. The CXC chemokine receptor (CXCR) family plays a role in renal fibrosis; however, the detailed mechanisms have not been elucidated. In this study, we investigated the potential role of CXCR7 in mediating renal fibrosis. CXCR7 expression is decreased in unilateral ischemia–reperfusion injury (UIRI) and unilateral ureteral obstruction mouse models. Furthermore, CXCR7 was specifically expressed primarily in the Lotus Tetragonolobus Lectin-expressing segment of tubules, was slightly expressed in the peanut agglutinin-expressing segment, and was barely expressed in the Dolichos biflorus agglutinin-expressing segment. Administration of pFlag-CXCR7, an overexpression plasmid for CXCR7, significantly inhibited the activation of β-catenin signaling and protected against the progression of epithelial-to-mesenchymal transition (EMT) and renal fibrosis in a UIRI mouse model. Using cultured HKC-8 cells, we found that CXCR7 significantly downregulated the expression of active β-catenin and fibrosis-related markers, including fibronectin, Collagen I, and α-SMA. Furthermore, CXCR7 significantly attenuated TGF-β1-induced changes in β-catenin signaling, EMT and fibrosis. These results suggest that CXCR7 plays a crucial role in inhibiting the activation of β-catenin signaling and the progression of EMT and renal fibrosis. Thus, CXCR7 could be a novel therapeutic target for renal fibrosis.

Due to sanctions, more Chinese high-tech SMEs are turning to rent AI computing power through cloud service providers. Therefore, it is necessary to give a variety of suggestions for China's high-tech SMEs to better develop AI applications through computing power leasing. Because traditional theories are difficult to explain this new technology adoption behavior, this research combines and extends TTF and UTAUT2 theories to take an empirical research. A total of 387 questionnaires were received, of which incomplete questionnaires and invalid questionnaires were issued, leaving 281 valid questionnaires. The results indicate that SME innovativeness, perceived risk, performance expectancy, price value and task technology fit are all significantly related to usage, whereas task technology fit moderates the other relationships significantly. Results give a variety of suggestions for China's high-tech SMEs to better develop AI applications through computing power leasing in the context of sanctions. This study not only suggests ways to increase the competitiveness of SMEs by optimizing leasing services but also give directions in investors' investment decisions. The findings are also applicable to the large-scale application of China's domestic AI chips in computing power leasing scenarios in the future.

BackgroundHead and neck paragangliomas (HNPGLs) are rare neuroendocrine tumors that pose significant challenges in both diagnosis and treatment. The pathogenic mechanism remains unclear, and there is no proteomic analysis-based molecular classification. Therefore, gaining a deeper understanding of this disease from the protein level is crucial because proteins play a fundamental role in the occurrence and development of tumors.MethodsWe collected 44 tumor samples from patients diagnosed with HNPGL. The adrenal paraganglioma tissue (N = 46) was used as the disease control group and the chorda tympani nerves (N = 18) were used as the control group. High-pH reversed-phase liquid chromatography and liquid chromatography with tandem mass spectrometry analyses were used to build an integrated protein database of tumor samples. We then obtained two sets of differentially expressed proteins between the tumor group and the control group to identify the unique proteomic signatures of HNPGLs. Ingenuity pathway analysis annotations were used to perform the functional analysis. Subsequently, we developed a clinically relevant molecular classification for HNPGLs that connected the clinical characteristics with meaningful proteins and pathways to explain the varied clinical manifestations.ResultsWe identified 6,640 proteins in the HNPGL group, and 314 differentially expressed proteins unique to HNPGL were discovered via inter-group comparison. We identified two HNPGL subgroups that significantly differed in clinical manifestation and proteomic characteristics. On the basis of the proteomic results, we proposed a pathogenic mechanism underlying HNPGL.ConclusionWe conducted a comprehensive analysis of the molecular mechanisms of HNPGL to build, for the first time, a clinically relevant molecular classification. By focusing on differential proteomic analyses between different types of paragangliomas, we were able to obtain a comprehensive description of the proteomic characteristics of HNPGL, which will be valuable for the search for significant biomarkers as a new treatment method for HNPGL.