Construction of metal interpretable scoring system and identification of tungsten as a novel risk factor in COPD.

Numerous studies have highlighted the correlation between metal intake and deteriorated pulmonary function, emphasizing its pivotal role in the progression of Chronic Obstructive Pulmonary Disease (COPD). However, the efficacy of traditional models is often compromised due to overfitting and high bias in datasets with low-level exposure, rendering them ineffective in delineating the contemporary risk trends associated with pulmonary diseases. To address these limitations, we embarked on developing advanced, interpretable models, crucial for elucidating the intricate mechanisms of metal toxicity and enriching the domain knowledge embedded in toxicity models. In this endeavor, we scrutinized extensive, long-term metal exposure datasets from NHANES to explore the interplay between metal and pulmonary functionality. Employing a variety of machine-learning approaches, we opted for the "Mixer of Experts" model for its proficiency in identifying a myriad of toxicological trends and sensitivities. We conceptualized and illustrated the TSAP (Toxicity Score at Population-level), a metal interpretable scoring system offering performance nearly equivalent to the amalgamation of standard interpretable methods addressing the "black box" conundrum. This streamlined, bifurcated procedural analysis proved instrumental in discerning established risk factors, thereby uncovering Tungsten as a novel contributor to COPD risk. SYNOPSIS: TSAP achieved satisfied performance with transparent interpretability, suggesting tungsten intake need further action for COPD prevention.

Comparing the effectiveness of mind-body practices (MBPs) and various psychological methods on occupational stress among healthcare workers: a network meta-analysis of randomized controlled trials.

OBJECTIVES: The purpose of this study is to compare the efficacy of mind-body practices (MBPs) and multiple psychological methods, and identify the optimal method for relieving work-related stress among healthcare workers (HCWs) by network meta-analysis (NMA). METHODS: We applied six electronic databases, namely PubMed, Web of Science, Embase, PsycINFO, Cochrane, and Chinese National Knowledge Infrastructure to identify relevant RCTs from inception to September 16, 2023, and implemented a search strategy based on the PICOS principles. Data selection, extraction, and analysis of bias were carried out independently and in duplicate by separate researchers. State 16.0 was used to conduct NMA for comparing the effectiveness of various therapies. RESULTS: We identified 23 studies including MBPs and three different psychological therapies, namely mindfulness-related therapy (MRT), psychoeducational therapy (PT), and comprehensive therapy (CT), which were divided into eleven specific techniques, namely yoga, meditation techniques (MT), Qigong, muscle relaxation(MR), biofeedback therapy (BT), mindfulness-based interventions (MBIs), modified mindfulness-based stress reduction (MBSR-M), mindfulness-based interventions combined with others (MBIs-C), mindfulness-based awareness(MBA), PT and CT. Our NMA results of MBPs and three psychological therapies showed MBPs (SMD = -0.90, CrI:-1.26, -0.05, SUCRA = 99%) were effective for occupational stress in HCWs, followed by MRT(SMD = -0.48, CrI:-0.87, -0.08, SUCRA = 66.5%). NMA results of eleven specific techniques showed yoga (SMD = 1.36, CrI:0.91, 1.81, SUCRA = 97.5%) was the most effective technique in relieving the stress of HCWs, followed by MR (SMD = 1.36, CrI:0.91, 1.81, SUCRA = 87.3%). CONCLUSIONS: Our study suggested MBPs may be the most effective intervention to improve the occupational stress of HCWs. Furthermore, yoga is likely to be the most optimal of MBPs. Hospital managers should attach importance to yoga in addressing occupational stress among medical workers.

[Rapid Start-up of Continuous Autotrophic Nitrogen Removal Reactor by Hybrid-inoculating PN and PN/A Granular Sludges].

The rapid cultivation of partial nitritation/ANAMMOX （PN/A） granular sludge in a continuous-flow mode is one of the key technologies for efficient biological nitrogen removal in domestic wastewater treatment. Compared with that in PN/A granular sludge, PN granular sludge demonstrates a shorter incubation period and suitability for batch culture. It is also a good carrier for enriching ANAMMOX （AMX） bacteria. In this study, we established a continuous-flow autotrophic nitrogen removal process in three continuously stirred tank reactors （CSTR） （R1-R3） by hybrid-inoculating PN/A and PN granular sludge at the mass ratios of 3∶1, 1∶1, and 1∶3, respectively. By implementing high ammonium nitrogen loading and short hydraulic retention time, continuous autotrophic nitrogen removal processes were successfully started up in the three CSTRs. The results showed that compared with that of R1 and R2, R3 had a longer start-up time but a similar steady-state nitrogen removal performance. The total nitrogen removal load of R3 could be more than 2.6 kg·ï¼ˆm3·d）-1. Intriguingly, the inoculated PN granular sludge served as a precursor for PN/A granular sludge cultivation. This approach facilitated the enrichment of anaerobic ammonia-oxidizing bacteria （AMX） by introducing abundant ammonium-oxidizing bacteria （AOB） and nitrite nitrogen substrates into the CSTR. According to the results of high-throughput sequencing, the microbial abundance and diversity of the mature granules in R1-R3 were significantly higher than those of the inoculation sludge. AOB （genus Nitrosomonas）, AMX （genera Candidatus Kuenenia and Candidatus Brocadia）, and symbiotic heterotrophs, such as Chloroflexi, Bacteroidetes, and Chlorobi, drove the autotrophic nitrogen removal process and maintained the stability of the granular structure. In summary, a novel start-up strategy of hybrid-inoculating granular sludge was provided for a continuous-flow autotrophic nitrogen removal in engineering application.

Apoptotic Extracellular Vesicles from Supernumerary Tooth-Derived Pulp Stem Cells Transfer COL1A1 to Promote Angiogenesis via PI3K/Akt/VEGF Pathway.

Purpose: Angiogenesis is a tightly controlled process that initiates the formation of new vessels and its dysfunction can lead to life-threatening diseases. Apoptotic extracellular vesicles (ApoEVs) have emerged as a proangiogenic agent with high safety and isolation efficiency profile, and ApoEVs from supernumerary tooth-derived pulp stem cells (SNTSC-ApoEVs) have their unique advantages with an easily accessible parental cell source and non-invasive cell harvesting. However, the detailed characteristics of SNTSC-ApoEVs are largely unknown. This study aimed to investigate the proangiogenic capacity and function molecule of SNTSC-ApoEVs. Methods: SNTSC-ApoEVs were isolated and characterized. In vitro effects of SNTSC-ApoEVs on the proliferation, migration, and tube formation of human umbilical vein endothelial cells (HUVECs) were evaluated by CCK-8, wound healing, transwell, and tube formation assays. The mRNA and protein levels of proangiogenic genes were quantified by qRT-PCR, Western blot, and immunofluorescence analysis. A Matrigel plug model was established in 6-week-old male nu/nu mice for one week, and the in vivo impact of SNTSC-ApoEVs on micro-vessel formation was assessed by histological analysis. Proteomic analysis and RNA sequencing were performed to explore the active ingredients and underlying mechanisms. Results: SNTSC-ApoEVs enhanced the proliferation, migration, and angiogenesis of HUVECs in vitro. In the Matrigel plug model in vivo, SNTSC-ApoEVs promoted CD31-positive luminal structure formation. Apart from expressing general ApoEV markers, SNTSC-ApoEVs were enriched with multiple proteins related to extracellular matrix-cell interactions. Mechanistically, SNTSC-ApoEVs transferred COL1A1 to HUVECs and promoted endothelial functions by activating the PI3K/Akt/VEGF cascade. Conclusion: SNTSC-ApoEVs can promote angiogenesis by transferring the functional molecule COL1A1 and activating the PI3K/Akt/VEGF pathway, making SNTSC-ApoEVs a promising strategy for the treatment of angiogenesis-related diseases.

Initial experience using ultrasound, automated breast volume scanner, and elastography for primary leiomyosarcoma of the breast: A rare case report.

Background: Primary leiomyosarcoma of the breast was a rare malignant tumor. Due to the extremely low morbidity and insufficient understanding of its imageological characteristics, there was a risk of misdiagnosis. In this case report, we presented the features of conventional US, elastography, automated breast volume scanner (ABVS), computed tomography (CT), and pathological findings of a case of primary leiomyosarcoma of the breast. Case presentation: A 74-year-old woman detected a mass of the left breast by palpation. Both ultrasound and CT revealed a solid mass in the outer quadrant of the left breast. After admission, she underwent a modified radical unilateral mastectomy under general anesthesia (resection of the lesion with left breast reserved). Furthermore, the intraoperative frozen section revealed malignant spindle cells, and the postoperative histopathology revealed primary leiomyosarcoma of the breast. After discharge, the patient was generally in good condition after the procedure and was asked to seek medical treatment in the oncology department. Findings on various imaging examinations and clinical data were carefully evaluated. Additionally, we also reviewed the associated kinds of literature. Conclusion: We reported the features of conventional US, elastography, ABVS, CT, and pathological findings of a rare case of primary leiomyosarcoma of the breast. Overall, our findings indicated that the above-mentioned features generally predict malignancy. However, compared to other malignant breast lesions, the features of this case were not specific enough.

AANAT1 regulates insect midgut detoxification through the ROS/CncC pathway.

Insecticide resistance has been a problem in both the agricultural pests and vectors. Revealing the detoxification mechanisms may help to better manage insect pests. Here, we showed that arylalkylamine N-acetyltransferase 1 (AANAT1) regulates intestinal detoxification process through modulation of reactive oxygen species (ROS)-activated transcription factors cap"n"collar isoform-C (CncC): muscle aponeurosis fibromatosis (Maf) pathway in both the oriental fruit fly, Bactrocera dorsalis, and the arbovirus vector, Aedes aegypti. Knockout/knockdown of AANAT1 led to accumulation of biogenic amines, which induced a decreased in the gut ROS level. The reduced midgut ROS levels resulted in decreased expression of CncC and Maf, leading to lower expression level of detoxification genes. AANAT1 knockout/knockdown insects were more susceptible to insecticide treatments. Our study reveals that normal functionality of AANAT1 is important for the regulation of gut detoxification pathways, providing insights into the mechanism underlying the gut defense against xenobiotics in metazoans.

Nitrogen-Mediated Promotion of Cobalt-Based Oxygen Evolution Catalyst for Practical Anion-Exchange Membrane Electrolysis.

Scarce and expensive iridium oxide is still the cornerstone catalyst of polymer-electrolyte membrane electrolyzers for green hydrogen production because of its exceptional stability under industrially relevant oxygen evolution reaction (OER) conditions. Earth-abundant transition metal oxides used for this task, however, show poor long-term stability. We demonstrate here the use of nitrogen-doped cobalt oxide as an effective iridium substitute. The catalyst exhibits a low overpotential of 240 mV at 10 mA cm-2 and negligible activity decay after 1000 h of operation in an alkaline electrolyte. Incorporation of nitrogen dopants not only triggers the OER mechanism switched from the traditional adsorbate evolution route to the lattice oxygen oxidation route but also achieves oxygen nonbonding (ONB) states as electron donors, thereby preventing structural destabilization. In a practical anion-exchange membrane water electrolyzer, this catalyst at anode delivers a current density of 1000 mA cm-2 at 1.78 V and an electrical efficiency of 47.8 kW-hours per kilogram hydrogen.

A phase 1, randomized, double-blind, placebo-controlled, dose escalation study to evaluate the safety, tolerability, pharmacokinetics and immunogenicity of SHR-1905, a long-acting anti-thymic stromal lymphopoietin antibody, in healthy subjects.

Introduction: Thymic stromal lymphopoietin (TSLP) is integral to inducing innate and T helper two cell inflammation that leads to clinical symptoms of asthma. SHR-1905 is a humanized immunoglobulin G1 kappa monoclonal antibody that inhibits TSLP bioactivity, developed for the treatment of severe uncontrolled asthma. This phase 1, randomized, double-blind, placebo-controlled single ascending dose study assessed the safety, tolerability, pharmacokinetics (PK), and immunogenicity of subcutaneous SHR-1905 in healthy subjects. Methods: Five dose cohorts were planned (50, 100, 200, 400, and 600 mg) and subjects were randomized (8:2) in each cohort to receive SHR-1905 or placebo with a follow-up period up to Day 253. Results: The majority of treatment-emergent adverse events (TEAEs) were mild and the incidence of TEAEs was comparable between the SHR-1905 and the placebo groups. The maximum serum concentration was reached 7.0-17.6 days after injection. The serum concentration of SHR-1905 increased with increasing dose level, and SHR-1905 exposure exhibited in a slightly greater-than-dose-proportional manner from 50 to 600 mg. SHR-1905 had a prolonged serum half-life around 80 days supporting every 6-month dosing. In SHR-1905 treated subjects, 15% tested positive for anti-drug antibodies post-dose with no apparent effect on corresponding PK profiles or safety. Conclusion: SHR-1905 demonstrated a good safety and tolerability profile with a long half-life in healthy subjects after a single administration in the dose range of 50-600 mg. Clinical Trial Registration: clinicaltrials.gov, identifier NCT04800263.

Ultra-high pressure treatment improve the content of characteristic aromatic components of melon juice from the view of physical changes.

Introduction: The effectiveness of ultra-high pressure (UHP) technology in retaining the flavor of fresh fruit and vegetable juices has been acknowledged in recent years. Along with previously hypothesized conclusions, the improvement in melon juice flavor may be linked to the reduction of its surface tension through UHP. Methods: In this paper, the particle size, free-water percentage, and related thermodynamic parameters of melon juice were evaluated in a physical point for a deeper insight. Results: The results showed that the UHP treatment of P2-2 (200 MPa for 20 min) raised the free water percentage by 7,000 times than the other treatments and both the melting enthalpy, binding constant and Gibbs free energy of P2-2 were minimized. This significantly increased the volatility of characteristic aromatic compounds in melon juice, resulting in a 1.2-5 times increase in the content of aromatic compounds in the gas phase of the P2-2 group compared to fresh melon juice.

Improving resistant starch content of cassava starch by pulsed electric field-assisted esterification.

This study aims to investigate the effect of pulsed electric field (PEF) assisted OSA esterification treatment on the multi-scale structure and digestive properties of cassava starch and structure-digestion relationships. The degree of substitution (DS) of starch dually modified at 1.5-4.5 kV/cm was 37.6-55.3 % higher than that of starch modified by the conventional method. Compared with native starch, the resistant starch (RS) content of esterified starch treated with 3 kV/cm significantly increased by 17.13 %, whereas that of starch produced by the conventional method increased by only 5.91 %. Furthermore, assisted esterification at low electric fields (1.5-3 kV/cm) promotes ester carbonyl grafting on the surface of starch granules, increases steric hindrance and promotes the rearrangement of the amorphous regions of starch, which increases the density of the double-helical structure. These structural changes slow down starch digestion and increase the RS content. Therefore, this study presents a potential method for increasing the RS content of starch products using PEF to achieve the desired digestibility.

Development and validation of a predictive model for severe white matter hyperintensity with obesity.

Purpose: The purpose of the present study was to identify predictors of severe white matter hyperintensity (WMH) with obesity (SWO), and to build a prediction model for screening obese people with severe WMH without Nuclear Magnetic Resonance Imaging (MRI) examination. Patients subjects and methods: From September 2020 to October 2021, 650 patients with WMH were recruited consecutively. The subjects were divided into two groups, SWO group and non-SWO group. Univariate and Logistic regression analysis were was applied to explore the potential predictors of SWO. The Youden index method was adopted to determine the best cut-off value in the establishment of the prediction model of SWO. Each parameter had two options, low and high. The score table of the prediction model and nomogram based on the logistic regression were constructed. Of the 650 subjects, 487 subjects (75%) were randomly assigned to the training group and 163 subjects (25%) to the validation group. By resampling the area under the curve (AUC) of the subject's operating characteristics and calibration curves 1,000 times, nomogram performance was verified. A decision curve analysis (DCA) was used to evaluate the nomogram's clinical usefulness. By resampling the area under the curve (AUC) of the subject's operating characteristics and calibration curves 1,000 times, nomogram performance was verified. A decision curve analysis (DCA) was used to evaluate the nomogram's clinical usefulness. Results: Logistic regression demonstrated that hypertension, uric acid (UA), complement 3 (C3) and Interleukin 8 (IL-8) were independent risk factors for SWO. Hypertension, UA, C3, IL-8, folic acid (FA), fasting C-peptide (FCP) and eosinophil could be used to predict the occurrence of SWO in the prediction models, with a good diagnostic performance, Areas Under Curves (AUC) of Total score was 0.823 (95% CI: 0.760-0.885, p < 0.001), sensitivity of 60.0%, specificity of 91.4%. In the development group, the nomogram's AUC (C statistic) was 0.829 (95% CI: 0.760-0.899), while in the validation group, it was 0.835 (95% CI: 0.696, 0.975). In both the development and validation groups, the calibration curves following 1,000 bootstraps showed a satisfactory fit between the observed and predicted probabilities. DCA showed that the nomogram had great clinical utility. Conclusion: Hypertension, UA, C3, IL-8, FA, FCP and eosinophil models had the potential to predict the incidence of SWO. When the total score of the model exceeded 9 points, the risk of SWO would increase significantly, and the nomogram enabled visualization of the patient's WMH risk. The application prospect of our models mainly lied in the convenient screening of SWO without MRI examination in order to detect SWO and control the WMH hazards early.

A Novel Parallel Control Method for Optimal Consensus of Nonlinear Multiagent Systems.

This work concentrates on the initial introduction of parallel control to investigate an optimal consensus control strategy for continuous-time nonlinear multiagent systems (MASs) via adaptive dynamic programming (ADP). First, the control input is integrated into the feedback system for parallel control, facilitating an augmented system's optimal consensus control with an appropriate augmented performance index function to be established, which is identical to the original system's suboptimal control with a conventional performance index. Second, the feasibility of the proposed control scheme is evaluated based on the policy iteration algorithm, and the convergence of the algorithm is demonstrated. Then, an online learning algorithm becomes available to implement the ADP-based optimal parallel consensus control protocol without prior knowledge of the system. The Lyapunov approach is employed to indicate that the signals are convergent. Ultimately, the experimental data support the theoretical results.

Facet-switching of rate-determining step on copper in CO2-to-ethylene electroreduction.

Reduction of carbon dioxide (CO2) by renewable electricity to produce multicarbon chemicals, such as ethylene (C2H4), continues to be a challenge because of insufficient Faradaic efficiency, low production rates, and complex mechanistic pathways. Here, we report that the rate-determining steps (RDS) on common copper (Cu) surfaces diverge in CO2 electroreduction, leading to distinct catalytic performances. Through a combination of experimental and computational studies, we reveal that C─C bond-making is the RDS on Cu(100), whereas the protonation of *CO with adsorbed water becomes rate-limiting on Cu(111) with a higher energy barrier. On an oxide-derived Cu(100)-dominant Cu catalyst, we reach a high C2H4 Faradaic efficiency of 72%, partial current density of 359 mA cm-2, and long-term stability exceeding 100 h at 500 mA cm-2, greatly outperforming its Cu(111)-rich counterpart. We further demonstrate constant C2H4 selectivity of >60% over 70 h in a membrane electrode assembly electrolyzer with a full-cell energy efficiency of 23.4%.

Construction of a nomogram model to predict technical difficulty in performing laparoscopic sphincter-preserving radical resection for rectal cancer.

BACKGROUND: Colorectal surgeons are well aware that performing surgery for rectal cancer becomes more challenging in obese patients with narrow and deep pelvic cavities. Therefore, it is essential for colorectal surgeons to have a comprehensive understanding of pelvic structure prior to surgery and anticipate potential surgical difficulties. AIM: To evaluate predictive parameters for technical challenges encountered during laparoscopic radical sphincter-preserving surgery for rectal cancer. METHODS: We retrospectively gathered data from 162 consecutive patients who underwent laparoscopic radical sphincter-preserving surgery for rectal cancer. Three-dimensional reconstruction of pelvic bone and soft tissue parameters was conducted using computed tomography (CT) scans. Operative difficulty was categorized as either high or low, and multivariate logistic regression analysis was employed to identify predictors of operative difficulty, ultimately creating a nomogram. RESULTS: Out of 162 patients, 21 (13.0%) were classified in the high surgical difficulty group, while 141 (87.0%) were in the low surgical difficulty group. Multivariate logistic regression analysis showed that the surgical approach using laparoscopic intersphincteric dissection, intraoperative preventive ostomy, and the sacrococcygeal distance were independent risk factors for highly difficult laparoscopic radical sphincter-sparing surgery for rectal cancer (P < 0.05). Conversely, the anterior-posterior diameter of pelvic inlet/sacrococcygeal distance was identified as a protective factor (P < 0.05). A nomogram was subsequently constructed, demonstrating good predictive accuracy (C-index = 0.834). CONCLUSION: The surgical approach, intraoperative preventive ostomy, the sacrococcygeal distance, and the anterior-posterior diameter of pelvic inlet/sacrococcygeal distance could help to predict the difficulty of laparoscopic radical sphincter-preserving surgery.

Unraveling Stoichiometry Effect in Nickel-Tungsten Alloys for Efficient Hydrogen Oxidation Catalysis in Alkaline Electrolytes.

Anion-exchange membrane fuel cells provide the possibility to use platinum group metal-free catalysts, but the anodic hydrogen oxidation reaction (HOR) suffers from sluggish kinetics and its source is still debated. Here, over nickel-tungsten (Ni-W) alloy catalysts, we show that the Ni : W ratio greatly governs the HOR performance in alkaline electrolyte. Experimental and theoretical studies unravel that alloying with W can tune the unpaired electrons in Ni, tailoring the potential of zero charge and the catalytic surface to favor hydroxyl adsorption (OHad). The OHad species coordinately interact with potassium (K+) ions, which break the K+ solvation sheath to leave free water molecules, yielding an improved connectivity of hydrogen-bond networks. Consequently, the optimal Ni17W3 alloy exhibits alkaline HOR activity superior to the state-of-the-art platinum on carbon (Pt/C) catalyst and operates steadily with negligible decay after 10,000 cycles. Our findings offer new understandings of alloyed HOR catalysts and will guide rational design of next-generation catalysts for fuel cells.

Metabolic pathway-based subtyping reveals distinct microenvironmental states associated with diffuse large B-cell lymphoma outcomes.

Diffuse large B-cell lymphoma (DLBCL) is a biologically and clinically heterogeneous disease that requires personalized clinical treatment. Assigning patients to different risk categories and cytogenetic abnormality and genetic mutation groups has been widely applied for prognostic stratification of DLBCL. Increasing evidence has demonstrated that dysregulated metabolic processes contribute to the initiation and progression of DLBCL. Metabolic competition within the tumor microenvironment is also known to influence immune cell metabolism. However, metabolism- and immune-related stratification has not been established. Here, 1660 genes involved in 84 metabolic pathways were selected and tested to establish metabolic clusters (MECs) of DLBCL. MECs established based on independent lymphoma datasets distinguished different survival outcomes. The CIBERSORT algorithm and EcoTyper were applied to quantify the relative abundance of immune cell types and identify variation in cell states for 13 lineages comprising the tumor micro environment among different MECs, respectively. Functional characterization showed that MECs were an indicator of the immune microenvironment and correlated with distinctive mutational characteristics and oncogenic signaling pathways. The novel immune-related MECs exhibited promising clinical prognostic value and potential for informing DLBCL treatment decisions.

Characterization of an agmatine N-acetyltransferase from Bactrocera dorsalis that modulates ovary development.

Agmatine N-acetyltransferase (AgmNAT), which catalyzes the formation of N-acetylagmatine from acetyl-CoA and agmatine, is a member of the GCN5-related N-acetyltransferase family. So far, knowledge of the physiological roles of AgmNAT in insects is limited. Here, we identified one gene encoding protein homologous to that of Drosophila AgmNAT using sequence information from an activity-verified Drosophila AgmNAT in a BLAST search of the Bactrocera dorsalis genome. We expressed and purified B. dorsalis AgmNAT in Escherichia coli and used the purified enzyme to define the substrate specificity for acyl-CoA and amine substrates. Our application of the screening strategy to BdorAgmNAT led to the identification of agmatine as the best amine substrate for this enzyme, with the highest kcat/Km value. We successfully obtained a BdorAgmNAT knockout strain based on a wild-type strain (WT) using the CRISPR/Cas9 technique. The ovary development of the BdorAgmNAT knockout mutants was delayed for 10 days compared with the WT specimens. Moreover, mutants had a much smaller mature ovary size and laid far fewer eggs than WT. Loss of function of BdorAgmNAT caused by RNAi with mature WT females did not affect their fecundity. These findings indicate that BdorAgmNAT is critical for oogenesis. Our data provide the first evidence for AgmNAT in regulating ovary development.

Parallel Driving with Big Models and Foundation Intelligence in Cyber-Physical-Social Spaces.

Recent years have witnessed numerous technical breakthroughs in connected and autonomous vehicles (CAVs). On the one hand, these breakthroughs have significantly advanced the development of intelligent transportation systems (ITSs); on the other hand, these new traffic participants introduce more complex and uncertain elements to ITSs from the social space. Digital twins (DTs) provide real-time, data-driven, precise modeling for constructing the digital mapping of physical-world ITSs. Meanwhile, the metaverse integrates emerging technologies such as virtual reality/mixed reality, artificial intelligence, and DTs to model and explore how to realize improved sustainability, increased efficiency, and enhanced safety. More recently, as a leading effort toward general artificial intelligence, the concept of foundation model was proposed and has achieved significant success, showing great potential to lay the cornerstone for diverse artificial intelligence applications across different domains. In this article, we explore the big models embodied foundation intelligence for parallel driving in cyber-physical-social spaces, which integrate metaverse and DTs to construct a parallel training space for CAVs, and present a comprehensive elucidation of the crucial characteristics and operational mechanisms. Beyond providing the infrastructure and foundation intelligence of big models for parallel driving, this article also discusses future trends and potential research directions, and the "6S" goals of parallel driving.

Proficiency testing for event-specific quantification of genetically modified maize MON87427: Performance assessment based on the metrologically traceable reference values as assigned values.

The Asia Pacific Metrology Program and the Accreditation Cooperation joint Proficiency Testing (PT) program for the quantification of genetically modified maize MON87427 was organized by the National Institute of Metrology, China, to enhance the measurement accuracy and metrological traceability in the region. Certified reference materials were employed as test samples; metrologically traceable certified reference values served as PT reference values (PTRVs) for evaluating the participants results. The consensus values obtained from the participants were higher than the assigned values, potentially due to the systematic effects of DNA extraction process. The participants' relatively poor overall performance by the ζ-score compared with z-score demonstrates their need to thoroughly investigate quantification bias to elevate the measurement capability of genetically modified (GM) content and deepen their understanding of uncertainty estimation. This program confirmed the importance of using metrologically traceable reference values instead of consensus values as PTRV for reliable performance assessment.