Targeting neuropilin-1 abolishes anti-PD-1-upregulated regulatory T cells and synergizes with 4-1BB agonist for liver cancer treatment.

BACKGROUND AIMS: Regulatory T cells (Tregs) are an obstacle to PD-1 blockade-mediated antitumor efficacy. However, the behaviors of Tregs response to anti-PD-1 in HCC and the characteristics of Tregs tissue adaptation from peripheral lymphoid tissues to the tumor are still unclear. APPROACH RESULTS: Here, we determine that PD-1 monotherapy potentially augments the accumulation of tumor CD4 + Tregs. Mechanistically, anti-PD-1 mediates Tregs proliferation in lymphoid tissues rather than in the tumor. Increased peripheral Tregs burden replenishes intratumoral Tregs, raising the ratio of intratumoral CD4 + Tregs to CD8 + T cells. Subsequently, single-cell transcriptomics revealed that neuropilin-1 (Nrp-1) supports Tregs migration behavior, and the genes of Crem and Tnfrsf9 regulate the behaviors of the terminal suppressive Tregs. Nrp-1 + 4-1BB - Tregs stepwise develop to the Nrp-1 - 4-1BB + Tregs from lymphoid tissues into the tumor. Moreover, Treg-restricted Nrp1 depletion abolishes anti-PD-1-upregulated intratumoral Tregs burden and synergizes with the 4-1BB agonist to enhance the antitumor response. Finally, a combination of the Nrp-1 inhibitor and the 4-1BB agonist in humanized HCC models showed a favorable and safe outcome and evoked the antitumor effect of the PD-1 blockade. CONCLUSION: Our findings elucidate the potential mechanism of anti-PD-1-mediated intratumoral Tregs accumulation in HCC and uncover the tissue adaptation characteristics of Tregs and identify the therapeutic potential of targeting Nrp-1 and 4-1BB for reprogramming the HCC microenvironment.

Bibliometric Analysis of Brain Stimulation Technologies in Sleep Disorders.

BACKGROUND Sleep disorders are a common disease faced by people today and can lead to fatigue, lack of concentration, impaired memory, and even death. In recent years, the development of brain stimulation techniques has provided a new perspective for the treatment of sleep disorders. However, there is a lack of bibliometric analyses related to sleep disorders and brain stimulation techniques. Therefore, this study analyzed the application status and trend of brain stimulation technology in sleep disorder research. MATERIAL AND METHODS Articles and reviews published between 1999 and 2023 were retrieved from the Web of Science. CiteSpace was used to visually analyze the publications, countries, institutions, journals, authors, references, and keywords. RESULTS A total of 459 publications were obtained. The number of studies was shown to be on a general upward trend. The country with the largest number of publications was the United States; UDICE-French Research Universities had the highest number of publications; Neurology had the highest citation frequency; 90% of the top 10 references cited were from Journal Citation Reports Q1; Brigo was the author with the highest number of publications; and the most frequent keywords were "transcranial magnetic stimulation", "deep brain stimulation", and "Parkinson disease". CONCLUSIONS Our study used CiteSpace software to analyze 459 studies published since 1999 on brain stimulation techniques for the treatment of sleep disorders, revealing research trends and the current state of the field. Our results will help researchers to understand the existing research quickly and provide direction for future research.

Distortion measurement of a lithography projection lens based on multichannel grating lateral shearing interferometry.

The optical distortion of the lithographic projection lens can reduce imaging quality and cause overlay errors in lithography, thus preventing the miniaturization of printed patterns. In this paper, we propose a technique to measure the optical distortion of a lithographic projection lens by sensing the wavefront aberrations of the lens. A multichannel dual-grating lateral shearing interferometer is used to measure the wavefront aberrations at several field points in the pupil plane simultaneously. Then, the distortion at these field points is derived according to the proportional relationship between the Z 2 and Z 3 Zernike terms (the tilt terms) and the image position shifts. Without the need for additional devices, our approach can simultaneously retrieve both the wavefront aberrations and the image distortion information. Consequently, it improves not only measurement speed and accuracy but also enables accounting for displacement stage positioning error. Experiments were conducted on a lithographic projection lens with a numerical aperture of 0.57 to verify the feasibility of the proposed method.

Effects of Blood Collection Tubes on the Quantification of Catecholamines and Their O-Methylated Metabolites by Liquid Chromatography Coupled With Tandem Mass Spectrometry.

BACKGROUND: Catecholamines (epinephrine; norepinephrine; and dopamine) and their O-methylated metabolites (metanephrine; normetanephrine; and 3-methoxytyramine) are biomarkers for pheochromocytoma and paraganglioma. Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) was recommended by Endocrine Society for detecting these compounds. The influence of blood collection tubes on the analysis of the six analytes by LC-MS/MS was not thoroughly investigated, which we want to clarify in our study. METHODS: Blood samples of healthy individuals were collected into serum, lithium heparin, and K2EDTA plasma tubes separately. Samples were subjected to solid phase extraction and then analyzed by LC-MS/MS. The retention behavior and assay performance of the six analytes were assessed for samples from different collection containers. The impacts of potassium and sodium as the counter ions of EDTA on the retention time and matrix effect were also studied. RESULTS: Compared with O-methylated metabolites, the results for catecholamines were more affected by the collection tubes, especially for norepinephrine, which displayed severely suppressed signal and very low extraction efficiency in K2EDTA plasma. Changing the counter ion of EDTA from potassium to sodium dramatically changed the retention behavior and matrix effect of norepinephrine. CONCLUSIONS: It is necessary to evaluate blood collection tubes for catecholamines and their O-methylated metabolites analyzed by LC-MS/MS. In addition, attention should also be paid when the anticoagulant counter ion was changed.

Revealing the optimal traditional processing methods and its protective effects against febrile seizures of Arisaema cum bile.

Arisaema cum bile (known as Dan Nanxing in Chinese, DNX) is a herbal medicine used for treating febrile seizure (FS), which commonly prepared by using Arisaematis Rhizoma and animal bile. This study was designed to explore the optimal processing time of DNX and its potential mechanism on the anti-FS effect. A total of 17 volatile organic compounds (VOCs) were the characteristic ones to distinguish different fermentation stages of DNX by using gas chromatography-ion mobility spectrometry (GC-IMS), such as 2-heptanone monomer, and heptanal monomer. DNX with fermentation for 3 months had an obvious pattern of VOCs with others, which could be regarded as the optimal fermentation time. The Enterococcus and Staphylococcus might be the core bacteria on the production of VOCs. Additionally, DNX (2.8 g/kg, p.o.) reversed hot water bath-induced FSs of rats, as indicated by increased seizure latency and decreased seizure duration time. It also prevented hippocampal neuronal loss, increased GABAAR, and decreased GRIA1 expression. At the genus level, relative abundance of Enterococcus and Akkermansia were enriched after DNX treatment. These findings suggested that fermentation for 3 months might be the optimal process time for DNX, and DNX possess an anti-FS effect through regulating neurotransmitter disorder and gut microbiota.

Carvacrol ameliorates skin allograft rejection through modulating macrophage polarization by activating the Wnt signalling pathway.

Post-transplantation immune rejection remains an important factor for transplant patients. However, conventional immunosuppressants are associated with substantial adverse effects. Natural immunosuppressants present a promising alternative to conventional counterparts, boasting exceptional biological activity, minimal toxicity and reduced side effects. We identified carvacrol as a prospective immunosuppressive agent following T cell proliferation experiment and validated carvacrol's immunosuppressive efficacy in the murine allogeneic skin graft model. T cell proliferation assay was used to screen natural small molecule compounds and the immunosuppressive effect of compounds was evaluated in MHC-mismatched murine allogeneic skin graft model. H&E and immunohistochemical staining were applied to evaluate the pathological grade. Furthermore, flow cytometry was uitlized to analyse the immunophenotype changes of immune cells. Western blotting and q-PCR were used to detect the expression of key molecules in macrophages. In vitro, carvacrol demonstrates significant inhibition of the proliferation of CD4+ T and CD8+ T cells. It notably reduces inflammatory factor expression within the allografts, suppresses T cell differentiation toward Th1 phenotype and expansion. Furthermore, carvacrol prominently hinders M1-type macrophages polarization by activating Wnt signaling. Notably, the anti-rejection efficacy of carvacrol was significantly weakened upon the removal of macrophages in mice using chlorophosphate liposomes. Carvacrol could significantly inhibit T cell proliferation, alleviate graft rejection and has outstanding toxicological safety. The molecular mechanism of the anti-rejection effect of carvacrol is closely related to its mediating activation of macrophage Wnt pathway, inhibiting M1 polarization and inducing T cell differentiation.

Graph Attention Informer for Long-Term Traffic Flow Prediction under the Impact of Sports Events.

Traffic flow prediction is one of the challenges in the development of an Intelligent Transportation System (ITS). Accurate traffic flow prediction helps to alleviate urban traffic congestion and improve urban traffic efficiency, which is crucial for promoting the synergistic development of smart transportation and smart cities. With the development of deep learning, many deep neural networks have been proposed to address this problem. However, due to the complexity of traffic maps and external factors, such as sports events, these models cannot perform well in long-term prediction. In order to enhance the accuracy and robustness of the model on long-term time series prediction, a Graph Attention Informer (GAT-Informer) structure is proposed by combining the graph attention layer and informer layer to capture the intrinsic features and external factors in spatial-temporal correlation. The external factors are represented as sports events impact factors. The GAT-Informer model was tested on real-world data collected in London, and the experimental results showed that our model has better performance in long-term traffic flow prediction compared to other baseline models.

Kaempferol inhibited invasion and metastasis of gastric cancer cells by targeting AKT/GSK3ß pathway based on network pharmacology and molecular docking.

This study aims to explore the mechanisms of the inhibitory effect of kaempferol on the invasion and metastasis of gastric cancer (GC) cells through network pharmacology prediction and experimental verification. It identifies core targets via PPI network analysis and finds that kaempferol binds to these targets well. In vitro experiments showed that kaempferol could inhibit the proliferation, colony formation, migration and invasion of GC cells. Western blotting indicated kaempferol may reduce AKT and GSK3ß phosphorylation, leading to lower expression of invasion-related genes SRC, MMP9, CXCR4, KDR, and MMP2. Overall, kaempferol may prevent migration and invasion of GC cells via the AKT/GSK3ß signaling pathway.

PANI/GO and Sm co-modified Ti/PbO2 dimensionally stable anode for highly efficient amoxicillin degradation: Performance assessment, impact parameters and degradation mechanism.

The abuse and uncontrolled discharge of antibiotics present a severe threat to environment and human health, necessitating the development of efficient and sustainable treatment technology. In this work, we employ a facile one-step electrodeposition method to prepare polyaniline/graphite oxide (PANI/GO) and samarium (Sm) co-modified Ti/PbO2 (Ti/PbO2-PANI/GO-Sm) electrode for the degradation of amoxicillin (AMX). Compared with traditional Ti/PbO2 electrode, Ti/PbO2-PANI/GO-Sm electrode exhibits more excellent oxygen evolution potential (2.63 V) and longer service life (56 h). In degradation experiment, under optimized conditions (50 mg L-1 AMX, 20 mA cm-2, pH 3, 0.050 M Na2SO4, 25 °C), Ti/PbO2-PANI/GO-Sm electrode achieves remarkable removal efficiencies of 88.76% for AMX and 79.92% for chemical oxygen demand at 90 min. In addition, trapping experiment confirms that ·OH plays a major role in the degradation process. Based on theoretical calculation and liquid chromatography-mass spectrometer results, the heterocyclic portion of AMX molecule is more susceptible to ·OH attacks. Thus, this novel electrode offers a sustainable and efficient solution to address environmental challenges posed by antibiotic-contaminated wastewater.

Endogenous Plasma Peptides Modulated by Protease in a Time-Dependent Manner as Effective Biomarkers for Preanalytical Quality Control.

Non-cryopreservation temperature exposure (NCE) is a vital preanalytical factor for assessing plasma quality. NCE can introduce undesirable errors in clinical diagnosis or when developing biomarkers of diseases. Biomarkers that can effectively indicate the changes in sample quality caused by long-term NCE (0-several days) are limited. Low-molecular-weight (LMW) peptides in the plasma are modulated by endogenous proteases. These protease activities are significantly correlated with NCE temperatures and duration, indicating a potential link of these protease reactions with the preanalytical quality of plasma samples. In this study, two groups of plasma samples were aged at room temperature (RT, 57 samples) and 4 °C (69 samples) for different durations (0, 1, 2, 5, and 10 days), and LMW peptidomics were analyzed through nanopore-assisted matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The analysis revealed 10 peptides that consistently exhibited time-dependent changes, which were used to develop multiple-variable models for predicting the changes in sample quality resulting from extended NCE. These biomarker models exhibited outstanding performance in distinguishing poor-quality samples aged at both RT and 4 °C. To validate the findings, tests on samples from validation sets were conducted by analysts who were blinded to the detailed conditions, which revealed a high specificity (94.3-96.9%) and sensitivity (90.5-99.3%). These results indicate the potential of these peptides as novel biomarkers of quality control.

Simulation-driven machine learning approach for high-speed correction of slope-dependent error in coherence scanning interferometry.

Slope-dependent error often occurs in the coherence scanning interferometry (CSI) measurement of functional engineering surfaces with complex geometries. Previous studies have shown that these errors can be corrected through the characterization and phase inversion of the instrument's three-dimensional (3D) surface transfer function. However, since CSI instrument is usually not completely shift-invariant, the 3D surface transfer function characterization and correction must be repeated for different regions of the full field of view, resulting in a long computational process and a reduction of measurement efficiency. In this work, we introduce a machine learning approach based on a deep neural network that is trainable for slope-dependent error correction in CSI. Our method leverages a deep neural network to directly learn errors characteristics from simulated surface measurements provided by a previously validated physics-based virtual CSI method. The experimental results demonstrate that the trained network is capable of correcting the surface height map with 1024 × 1024 sampling points within 0.1 seconds, covering a 178 µm field of view. The accuracy is comparable to the previous phase inversion approach while the new method is two orders of magnitude faster under the same computational condition.

Quality inspection of cube beam splitters by a white light interferometric approach.

Beam splitters have a wide range of applications as a key component in optical systems. Adopting beam splitters with geometric defects in an optical system, e.g., an interferometric measurement system, may cause additional optical path difference and degrade the measurement accuracy. The quality inspection of beam splitters is essential to meet the accuracy requirements for modern optical systems. Most of the current quality inspection methods rely on inefficient and inaccurate manual observation. Therefore, for commonly used cube beam splitters (CBSs), we propose a digital method to quantify the geometric quality based on the white light interferometric principle. A Fourier domain analysis is used to calculate the CBS misalignment error and perpendicularity error. This method is verified by inspecting six different CBS samples. The experimental results show that all samples have varying degrees of misalignment and perpendicularity errors. The maximum perpendicularity error is 0.93°, and three of the six samples have misalignment errors larger than 50 µm. Nanometer level precision of the misalignment measurement can be achieved.

The relationship between vitamin D receptor gene polymorphisms and ankylosing spondylitis: a systematic review, meta-analysis and trial sequential analysis.

The relation between vitamin D receptor (VDR) gene polymorphisms and ankylosing spondylitis (AS) remains unclear. A systematic review and meta-analysis were conducted using six databases, including PubMed, Web of Science, EMBASE, CNKI, Wanfang and Cochrane Library. The selection of each study was based on inclusion and exclusion criteria. The Newcastle-Ottawa Scale was applied to assess the quality of the included studies, while the strength was evaluated by odds ratios and 95% confidence intervals. The following contrasts were used: allele contrast (H vs h), homozygous contrast (HH vs hh), heterozygous contrast (Hh vs hh), dominant contrast (HH + Hh vs hh) and recessive contrast (HH vs Hh + hh). For the BsmI-rs1544410 polymorphism, three studies were included of 782 cases and 863 controls. The data showed a significant relationship under allele contrast H vs h (OR = 1.66, 95% CI 1.20-2.30 (P = 0.002)). For the TaqI-rs731236 polymorphism, 675 cases and 697 controls were included in two studies. The data showed a significant relationship under allele contrast H vs h (OR = 1.57, 95% CI 1.11-2.21 (P < 0.05)), homozygous contrast Hh vs hh (OR = 1.65, 95% CI 1.12-2.43 (P < 0.05)), and recessive contrast HH + Hh vs hh (OR = 1.66, 95% CI 1.13-2.43 (P < 0.05)). There were significant relationships between VDR gene BsmI-rs1544410 and TaqI-rs731236 polymorphisms and AS, while no associations were found between FokI-rs2228570 and ApaI-rs7975232 polymorphisms and AS. In the future, additional studies with larger case numbers are need.

AST-GIN: Attribute-Augmented Spatiotemporal Graph Informer Network for Electric Vehicle Charging Station Availability Forecasting.

Electric Vehicle (EV) charging demand and charging station availability forecasting is one of the challenges in the intelligent transportation system. With accurate EV station availability prediction, suitable charging behaviors can be scheduled in advance to relieve range anxiety. Many existing deep learning methods have been proposed to address this issue; however, due to the complex road network structure and complex external factors, such as points of interest (POIs) and weather effects, many commonly used algorithms can only extract the historical usage information and do not consider the comprehensive influence of external factors. To enhance the prediction accuracy and interpretability, the Attribute-Augmented Spatiotemporal Graph Informer (AST-GIN) structure is proposed in this study by combining the Graph Convolutional Network (GCN) layer and the Informer layer to extract both the external and internal spatiotemporal dependence of relevant transportation data. The external factors are modeled as dynamic attributes by the attributeaugmented encoder for training. The AST-GIN model was tested on the data collected in Dundee City, and the experimental results showed the effectiveness of our model considering external factors' influence on various horizon settings compared with other baselines.

Blocking CD47 promotes antitumour immunity through CD103+ dendritic cell-NK cell axis in murine hepatocellular carcinoma model.

BACKGROUND & AIMS: The CD47-signal regulatory protein α (SIRPα) axis inhibits dendritic cell (DC) phagocytosis and contributes to immune evasion. However, the behaviour of DCs and the potential crosstalk between DCs and natural killer (NK) cells in the hepatocellular carcinoma (HCC) microenvironment after CD47 blockade remain unclear. METHODS: The infiltration of CD103+ DCs and NK cells were analysed by immunohistochemistry and immunofluorescence in both human and murine HCC specimens. An orthotopic liver tumour model was used to evaluate the function of the CD103+ DC-NK cell axis after CD47 blockade in vivo in wild-type, Rag1-/-, Batf3-/-, and STING1-/- mice. Phagocytosis assays were performed in CD103+ DC and HCC cell lines. CD103+ DC-derived cytokines were analysed by chemokine array. Spleen-derived NK cells in C57BL/6J mice were used to evaluate cytotoxic functions in vitro. RESULTS: Higher CD47 expression was associated with worse prognosis in patients with HCC. CD47 blockade enhanced antitumour efficacy by stimulating the CD103+ DC-NK cell axis. The hypoxic microenvironment promoted CD47 blockade-induced tumour DNA phagocytosis by CD103+ DCs. By releasing IL-12 and CXCL9, activated CD103+ DCs induced the recruitment of NK cells with upregulated expression of granzyme B, NKG2D, interferon-γ, and tumour necrosis factor-α and downregulated expression of NKG2A. The antitumour effects of CD47 blockade could be abolished by cyclic GMP-AMP synthase (cGAS)-STING pathway inhibition. CONCLUSIONS: In addition to the classical DC-T cell axis, CD47 blockade significantly enhanced the ability of CD103+ DCs to take up tumour DNA, resulting in the stimulation of the cGAS-STING pathway, which promoted the infiltration and activation of NK cells in liver cancer. LAY SUMMARY: Hypoxia (low oxygen levels) is prevalent in the hepatocellular carcinoma microenvironment and promotes the phagocytosis (ingestion and elimination) of tumour DNA by CD103+ dendritic cells (a type of immune cell). Blockade of the cell surface protein CD47 resulted in activation of CD103+ dendritic cells which led to the recruitment and activation of natural killer cells (a different immune cell). When activated, these cells exhibit an antitumour effect.

Measurement and correction of lateral distortion in a Fizeau interferometer based on the self-calibration technique.

The lateral distortion of a surface measuring Fizeau interferometer may cause distorted image features in the lateral direction, as well as the surface form error in the axial direction (which is a source of the retrace error). Traditional method for lateral distortion measurement requires a high-accuracy calibration plate featuring a grid pattern. Such a calibration plate is not always available, especially when the required accuracy of the grid pattern comes to the order of sub-micrometer or even nanometer level. To remove the dependence on the plate accuracy, we propose a self-calibration method for the measurement and correction of lateral distortion in Fizeau interferometer. The self-calibration technique may separate the lateral distortion and the geometric error of the calibration plate. This method is verified using a 108-mm-aperture Fizeau interferometer. The experiments show that the form measurement error of a surface tilted at approximately 5° and 16° can be reduced from 92 nm to 43 nm and from 251 nm to 144 nm (peak-to-valley value), respectively, after the distortion correction.

Proteomics and post-translational modifications analysis of umbilical mesenchymal stem cells aging.

Mesenchymal stem cells (MSCs) are considered to be critical for regenerative medicine. However, long-term culturing of MSCs will induce aging of MSCs, and thereafter impair cellular function. Changes in proteomics have been reported to be involved in cell aging, and therefore investigations on cell aging of MSCs at levels of proteomics and post-translational protein modifications (PTM) are ultimately important. In the present study, human umbilical cord mesenchymal stem cells (hUMSCs) were exposed to different culture conditions for either 7 or 30 days. Proteins changes during cell culture were investigated using tandem mass tag (TMT) labeling quantitative approach, and N-glycosylation patterns were analyzed using multistage mass spectrometry. We identified 66 proteins (fold change >1.50) that were differentially expressed in long-term culture. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that aging exerts a side effect on hUMSCs by affecting various molecular functions and biological processes, such as lysosome, autophagy and post-translational protein modification. Glycosylation analysis indicates that cell N-glycan patterns are associated with aging of MSCs. Our results presented here should contribute to future studies on cell aging and cellular quality controls related to MSCs as regenerative medicine.

Effects of illumination non-uniformity on the double-Ronchi lateral shearing interference field.

Double-Ronchi shearing interferometry is a promising technique for insitu wavefront aberration measurement of the projection lens in photolithography systems. In practice, the non-uniformity of illumination is an important issue affecting the interference field, which has not been systematically researched. In this work, the interference field errors caused by non-uniform illumination distributions are analyzed utilizing the theories of scalar diffraction. The theoretical analysis has been verified by simulation and fundamental experiments. Results show that the uniformity requirements for the abrupt annular, Gaussian, and uniform random illumination distribution (RD) are 0.9434, 0.8439, and 0.2751, respectively, with a shear ratio of 5% and a relative wavefront reconstruction error of 1%. The uniformity of the three distributions is reduced to 0.6513, 0.5864, and 0.1234, respectively, with the shear ratio shrunk to 3%. When the shear ratio is less than 1%, there is no specific requirement for illumination uniformity.

Secure Vehicular Platoon Management against Sybil Attacks.

The capacity of highways has been an ever-present constraint in the 21st century, bringing about the issue of safety with greater likelihoods of traffic accidents occurring. Furthermore, recent global oil prices have inflated to record levels. A potential solution lies in vehicular platooning, which has been garnering attention, but its deployment is uncommon due to cyber security concerns. One particular concern is a Sybil attack, by which the admission of fake virtual vehicles into the platoon allows malicious actors to wreak havoc on the platoon itself. In this paper, we propose a secure management scheme for platoons that can protect major events that occur in the platoon operations against Sybil attacks. Both vehicle identity and message exchanged are authenticated by adopting key exchange, digital signature and encryption schemes based on elliptic curve cryptography (ECC). Noteworthy features of the scheme include providing perfect forward secrecy and both group forward and backward secrecy to preserve the privacy of vehicles and platoons. Typical malicious attacks such as replay and man-in-the-middle attacks for example can also be resisted. A formal evaluation of the security functionality of the scheme by the Canetti-Krawczyk (CK) adversary and the random oracle model as well as a brief computational verification by CryptoVerif were conducted. Finally, the performance of the proposed scheme was evaluated to show its time and space efficiency.

Missing Traffic Data Imputation with a Linear Generative Model Based on Probabilistic Principal Component Analysis.

Even with the ubiquitous sensing data in intelligent transportation systems, such as the mobile sensing of vehicle trajectories, traffic estimation is still faced with the data missing problem due to the detector faults or limited number of probe vehicles as mobile sensors. Such data missing issue poses an obstacle for many further explorations, e.g., the link-based traffic status modeling. Although many studies have focused on tackling this kind of problem, existing studies mainly focus on the situation in which data are missing at random and ignore the distinction between links of missing data. In the practical scenario, traffic speed data are always missing not at random (MNAR). The distinction for recovering missing data on different links has not been studied yet. In this paper, we propose a general linear model based on probabilistic principal component analysis (PPCA) for solving MNAR traffic speed data imputation. Furthermore, we propose a metric, i.e., Pearson score (p-score), for distinguishing links and investigate how the model performs on links with different p-score values. Experimental results show that the new model outperforms the typically used PPCA model, and missing data on links with higher p-score values can be better recovered.