D3EGFR: a webserver for deep learning-guided drug sensitivity prediction and drug response information retrieval for EGFR mutation-driven lung cancer.

As key oncogenic drivers in non-small-cell lung cancer (NSCLC), various mutations in the epidermal growth factor receptor (EGFR) with variable drug sensitivities have been a major obstacle for precision medicine. To achieve clinical-level drug recommendations, a platform for clinical patient case retrieval and reliable drug sensitivity prediction is highly expected. Therefore, we built a database, D3EGFRdb, with the clinicopathologic characteristics and drug responses of 1339 patients with EGFR mutations via literature mining. On the basis of D3EGFRdb, we developed a deep learning-based prediction model, D3EGFRAI, for drug sensitivity prediction of new EGFR mutation-driven NSCLC. Model validations of D3EGFRAI showed a prediction accuracy of 0.81 and 0.85 for patients from D3EGFRdb and our hospitals, respectively. Furthermore, mutation scanning of the crucial residues inside drug-binding pockets, which may occur in the future, was performed to explore their drug sensitivity changes. D3EGFR is the first platform to achieve clinical-level drug response prediction of all approved small molecule drugs for EGFR mutation-driven lung cancer and is freely accessible at https://www.d3pharma.com/D3EGFR/index.php.

Data-independent acquisition in metaproteomics.

INTRODUCTION: Metaproteomics offers insights into the function of complex microbial communities, while it is also capable of revealing microbe-microbe and host-microbe interactions. Data-independent acquisition (DIA) mass spectrometry is an emerging technology, which holds great potential to achieve deep and accurate metaproteomics with higher reproducibility yet still facing a series of challenges due to the inherent complexity of metaproteomics and DIA data. AREAS COVERED: This review offers an overview of the DIA metaproteomics approaches, covering aspects such as database construction, search strategy, and data analysis tools. Several cases of current DIA metaproteomics studies are presented to illustrate the procedures. Important ongoing challenges are also highlighted. Future perspectives of DIA methods for metaproteomics analysis are further discussed. Cited references are searched through and collected from Google Scholar and PubMed. EXPERT OPINION: Considering the inherent complexity of DIA metaproteomics data, data analysis strategies specifically designed for interpretation are imperative. From this point of view, we anticipate that deep learning methods and de novo sequencing methods will become more prevalent in the future, potentially improving protein coverage in metaproteomics. Moreover, the advancement of metaproteomics also depends on the development of sample preparation methods, data analysis strategies, etc. These factors are key to unlocking the full potential of metaproteomics.

PET/CT-based deep learning grading signature to optimize surgical decisions for clinical stage I invasive lung adenocarcinoma and biologic basis under its prediction: a multicenter study.

PURPOSE: No consensus on a grading system for invasive lung adenocarcinoma had been built over a long period of time. Until October 2020, a novel grading system was proposed to quantify the whole landscape of histologic subtypes and proportions of pulmonary adenocarcinomas. This study aims to develop a deep learning grading signature (DLGS) based on positron emission tomography/computed tomography (PET/CT) to personalize surgical treatments for clinical stage I invasive lung adenocarcinoma and explore the biologic basis under its prediction. METHODS: A total of 2638 patients with clinical stage I invasive lung adenocarcinoma from 4 medical centers were retrospectively included to construct and validate the DLGS. The predictive performance of the DLGS was evaluated by the area under the receiver operating characteristic curve (AUC), its potential to optimize surgical treatments was investigated via survival analyses in risk groups defined by the DLGS, and its biological basis was explored by comparing histologic patterns, genotypic alternations, genetic pathways, and infiltration of immune cells in microenvironments between risk groups. RESULTS: The DLGS to predict grade 3 achieved AUCs of 0.862, 0.844, and 0.851 in the validation set (n = 497), external cohort (n = 382), and prospective cohort (n = 600), respectively, which were significantly better than 0.814, 0.810, and 0.806 of the PET model, 0.813, 0.795, and 0.824 of the CT model, and 0.762, 0.734, and 0.751 of the clinical model. Additionally, for DLGS-defined high-risk population, lobectomy yielded an improved prognosis compared to sublobectomy p = 0.085 for overall survival [OS] and p = 0.038 for recurrence-free survival [RFS]) and systematic nodal dissection conferred a superior prognosis to limited nodal dissection (p = 0.001 for OS and p = 0.041 for RFS). CONCLUSION: The DLGS harbors the potential to predict the histologic grade and personalize the surgical treatments for clinical stage I invasive lung adenocarcinoma. Its applicability to other territories should be further validated by a larger international study.

New Phenanthro[9,10-d]oxazole-Based Fluorophores with Hybridized Local and Charge-Transfer Characteristics for Highly Efficient Blue Non-Doped OLEDs with Negligible Efficiency Roll-Off.

It is vital to develop highly efficient non-doped blue organic light-emitting diodes (OLEDs) with high color purity and low-efficiency roll-off for applications in display and lighting. Herein, two blue D-A fluorophores TPA-PO and TPA-DPO are designed and synthesized, in which phenanthro[9,10-d]oxazole (PO) acts as the acceptor and triphenylamine as the donor. TPA-PO and TPA-DPO display good thermal stability and efficient luminescence efficiency in neat film. Results based on photophysical property and theoretical calculation demonstrate that TPA-PO and TPA-DPO possess the hybridized local and charge-transfer (HLCT) feature, which can utilize the triplet exciton to achieve highly efficient electroluminance (EL). The non-doped OLEDs with TPA-PO/TPA-DPO as pure emissive layer show the uniform EL emission peak at 468 nm, corresponding to CIE coordinates of (0.168, 0.187) and (0.167, 0.167), respectively. The TPA-DPO-based non-doped OLEDs provide the maximum external quantum efficiency (EQE) of 7.99 % and high exciton utility efficiency of 48.4 %~72.6 %. Moreover, the TPA-DPO-based device exhibits low-efficiency roll-off, still maintaining the EQE of 6.03 % at the high luminance of 5000 cd m-2. Those findings state clearly that PO is a promising building block of blue fluorophore with a potential HLCT feature to be applied in non-doped OLEDs.

LinguaPhylo: A probabilistic model specification language for reproducible phylogenetic analyses.

Phylogenetic models have become increasingly complex, and phylogenetic data sets have expanded in both size and richness. However, current inference tools lack a model specification language that can concisely describe a complete phylogenetic analysis while remaining independent of implementation details. We introduce a new lightweight and concise model specification language, 'LPhy', which is designed to be both human and machine-readable. A graphical user interface accompanies 'LPhy', allowing users to build models, simulate data, and create natural language narratives describing the models. These narratives can serve as the foundation for manuscript method sections. Additionally, we present a command-line interface for converting LPhy-specified models into analysis specification files (in XML format) compatible with the BEAST2 software platform. Collectively, these tools aim to enhance the clarity of descriptions and reporting of probabilistic models in phylogenetic studies, ultimately promoting reproducibility of results.

Mechanism and origin of enantioselectivity for organocatalyzed asymmetric heteroannulation of alkynes in the construction of axially chiral C2-arylquinoline.

Axially chiral C2-arylquinoline has been successfully constructed via asymmetric heteroannulation of alkynes catalyzed by chiral phosphoric acid with high yield and high enantioselectivity. Inspired by this intriguing work, theoretical calculations have been carried out, and the detailed reaction mechanism has been elaborated, in which the whole reaction can be divided into steps including hydrogen transfer, C-N bonding, annulation reaction and the final dehydration processes. The initial hydrogen-transfer reaction has two possible pathways, while the subsequent C-N bonding process has eight possible pathways. Then, after the annulation reaction and the final dehydration processes, the major product and byproduct were formed. QTAIM and IGMH analyses were used to illustrate the role of weak intermolecular interactions in the catalytic process, and the distortion/interaction and EDA analyses provided a deeper understanding of the origin of enantioselectivity. The calculated results are consistent with the experimental results. This work would provide valuable insights into asymmetric reactions catalyzed by chiral phosphoric acid.

Effects of oxygen adsorption on the corrosion behavior of the Ti(0001) surface: a DFT investigation.

The electrochemical corrosion of Ti surfaces is significantly affected by O adsorption, yet the underlying mechanisms remain unexplored. Herein, density functional theory calculations are employed to examine the adsorption energies, structural properties, electronic structures, and thermodynamic stability of atomic O on Ti(0001) surfaces during initial oxidation. Additionally, the impact of O adsorption on Ti dissolution is assessed by introducing a Ti vacancy on the Ti(0001) surface. The passivation of the Ti(0001) surface is predominantly ascribed to the robust adsorption of O atoms. The thermodynamic results reveal that bulk TiO2 easily forms at 300 K, which explains the spontaneous passivation of the Ti(0001) surface. The formation of an O monolayer on the Ti(0001) surface increases the work function (Φ), positively shifting the equilibrium potential and reducing the corrosion rate. The surface vacancy formation energy of Ti on the Ti(0001)/O surface surpasses that on the clean surface. The electrode potential shift for a Ti atom dissolving from the Ti(0001)/O surface is positive, indicating that oxidation impedes the formation of Ti vacancies, rendering Ti atoms less soluble. This study enhances our comprehension of the corrosion mechanism in Ti metal.

Arenarialins A-F, Anti-inflammatory Meroterpenoids with Rearranged Skeletons from the Marine Sponge Dysidea arenaria.

Six new sesquiterpene quinone/hydroquinone meroterpenoids, arenarialins A-F (1-6), were isolated from the marine sponge Dysidea arenaria collected from the South China Sea. Their chemical structures and absolute configurations were determined by HRMS and NMR data analyses coupled with DP4+ and ECD calculations. Arenarialin A (1) features an unprecedented tetracyclic 6/6/5/6 carbon skeleton, whereas arenarialins B-D (2-4) possess two rare secomeroterpene scaffolds. Arenarialins A-F showed inhibitory activity on the production of inflammatory cytokines TNF-α and IL-6 in LPS-induced RAW264.7 macrophages with arenarialin D regulating the NF-κB/MAPK signaling pathway.

Proteomics analysis of histone deacetylase inhibitor-resistant solid tumors reveals resistant signatures and potential drug combinations.

Histone deacetylase inhibitors (HDACis) are important drugs for cancer therapy, but the indistinct resistant mechanisms of solid tumor therapy greatly limit their clinical application. In this study we conducted HDACi-perturbated proteomics and phosphoproteomics analyses in HDACi-sensitive and -resistant cell lines using a tandem mass tag (TMT)-based quantitative proteomic strategy. We found that the ribosome biogenesis proteins MRTO4, PES1, WDR74 and NOP16 vital to tumorigenesis might regulate the tumor sensitivity to HDACi. By integrating HDACi-perturbated protein signature with previously reported proteomics and drug sensitivity data, we predicted and validated a series of drug combination pairs potentially to enhance the sensitivity of HDACi in diverse solid tumor. Functional phosphoproteomic analysis further identified the kinase PDK1 and ROCK as potential HDACi-resistant signatures. Overall, this study reveals the potential HDACi-resistant signatures and may provide promising drug combination strategies to attenuate the resistance of solid tumor to HDACi.

Multiparameter MRI-based radiomics nomogram for preoperative prediction of brain invasion in atypical meningioma:a multicentre study.

OBJECTIVE: To develop a nomogram based on tumor and peritumoral edema (PE) radiomics features extracted from preoperative multiparameter MRI for predicting brain invasion (BI) in atypical meningioma (AM). METHODS: In this retrospective study, according to the 2021 WHO classification criteria, a total of 469 patients with pathologically confirmed AM from three medical centres were enrolled and divided into training (n = 273), internal validation (n = 117) and external validation (n = 79) cohorts. BI was diagnosed based on the histopathological examination. Preoperative contrast-enhanced T1-weighted MR images (T1C) and T2-weighted MR images (T2) for extracting meningioma features and T2-fluid attenuated inversion recovery (FLAIR) sequences for extracting meningioma and PE features were obtained. The multiple logistic regression was applied to develop separate multiparameter radiomics models for comparison. A nomogram was developed by combining radiomics features and clinical risk factors, and the clinical usefulness of the nomogram was verified using decision curve analysis. RESULTS: Among the clinical factors, PE volume and PE/tumor volume ratio are the risk of BI in AM. The combined nomogram based on multiparameter MRI radiomics features of meningioma and PE and clinical indicators achieved the best performance in predicting BI in AM, with area under the curve values of 0.862 (95% CI, 0.819-0.905) in the training cohort, 0.834 (95% CI, 0.780-0.908) in the internal validation cohort and 0.867 (95% CI, 0.785-0.950) in the external validation cohort, respectively. CONCLUSIONS: The nomogram based on tumor and PE radiomics features extracted from preoperative multiparameter MRI and clinical factors can predict the risk of BI in patients with AM.

Limited resection is comparable to lobectomy for tumor size ≤ 2 cm pulmonary invasive mucinous adenocarcinoma.

OBJECTIVES: Invasive mucinous adenocarcinoma (IMA) has a rare incidence with better prognosis than nonmucinous adenocarcinoma. We aimed to investigate the prognosis between limited resection and lobectomy for patients with clinical stage IA IMA ≤ 2 cm. METHODS: Data were taken from two cohorts: In Shanghai Pulmonary Hospital (SPH) corhort, we identified 403 patients with clinical stage IA IMA who underwent surgery. In the SEER corhort, 480 patients with stage T1 IMA who after surgery were included. Recurrence-free survival (RFS) for SPH corhort, lung cancer-specific survival (LCSS) for the SEER corhort and overall survival (OS) for both corhort were compared between patients undergoing lobectomy and limited resection by Log-rank and Cox proportional hazard regression model. RESULTS: In SPH corhort, patients who underwent limited resection had equivalent prognosis than those underwent lobectomy (5-year RFS: 79.3% versus. 82.6%, p = 0.116; 5-year OS: 86.2% versus. 88.3%, p = 0.235). However, patients with IMA > 2 to 3 cm had worse prognosis than those with IMA ≤ 2 cm (5-year RFS: 73.7% versus. 86.1%, p = 0.007). In the analysis of IMA > 2 to 3 cm subgroup, multivariate analysis showed that limited resection was an independent risk factor of RFS (hazard ratio, 2.417; 95% confidence interval, 1.157-5.049; p = 0.019), while OS (p = 0.122) was not significantly different between two groups. For IMA ≤ 2 cm, limited resection was not a risk factor of RFS (p = 0. 953) and OS (p = 0.552). In the SEER corhort, IMA ≤ 2 cm subgroup, limited resection was equivalent prognosis in LCSS (p = 0.703) and OS (p = 0.830). CONCLUSIONS: Limited resection could be a potential surgical option which comparable to lobectomy in patients with clinical stage IA IMA ≤ 2 cm.

A rare case of intervertebral disc calcification combined with ossification of the posterior longitudinal ligament in a child: a case report and literature review.

BACKGROUND: Intervertebral disc calcification (IDC) combined with calcification in children has been sporadically reported, while ossification of the posterior longitudinal ligament (OPLL) in the cervical spine in pediatric patients is exceedingly rare. The aim of this study is to investigate the potential prognosis and outcomes associated with this condition. CASE PRESENTATION: We present an unusual case involving a 10-year-old Chinese child diagnosed with calcified cervical disc herniation and ossification of the posterior longitudinal ligament. Conservative treatment measures were implemented, and at the 1-month and 6-month follow-up, the patient's pain exhibited significant improvement. Subsequent cervical MRI and CT scans revealed the complete disappearance of OPLL and substantial absorption of the calcified disc. During the three-month follow-up, CT demonstrated slight residual disc calcification, however, the patient remained asymptomatic with no discernible limitation in cervical motion. CONCLUSIONS: We conducted a comprehensive review of several cases presenting with the same diagnosis. It is noteworthy that IDC combined with OPLL in children constitutes a rare clinical entity. Despite imaging indications of potential spinal canal occupation, the majority of such cases demonstrate complete absorption following conservative treatment, with OPLL exhibiting a faster absorption rate than calcified discs.

Chronic Alcohol Exposure Alters the Levels and Assembly of the Actin Cytoskeleton and Microtubules in the Adult Mouse Hippocampus.

BACKGROUND: Alcohol abuse, a prevalent global health issue, is associated with the onset of cognitive impairment and neurodegeneration. Actin filaments (F-actin) and microtubules (MTs) polymerized from monomeric globular actin (G-actin) and tubulin form the structural basis of the neuronal cytoskeleton. Precise regulation of the assembly and disassembly of these cytoskeletal proteins, and their dynamic balance, play a pivotal role in regulating neuronal morphology and function. Nevertheless, the effect of prolonged alcohol exposure on cytoskeleton dynamics is not fully understood. This study investigates the chronic effects of alcohol on cognitive ability, neuronal morphology and cytoskeleton dynamics in the mouse hippocampus. METHODS: Mice were provided ad libitum access to 5% (v/v) alcohol in drinking water and were intragastrically administered 30% (v/v, 6.0 g/kg/day) alcohol for six weeks during adulthood. Cognitive functions were then evaluated using the Y maze, novel object recognition and Morris water maze tests. Hippocampal histomorphology was assessed through hematoxylin-eosin (HE) and Nissl staining. The polymerized and depolymerized states of actin cytoskeleton and microtubules were separated using two commercial assay kits and quantified by Western blot analysis. RESULTS: Mice chronically exposed to alcohol exhibited significant deficits in spatial and recognition memory as evidenced by behavioral tests. Histological analysis revealed notable hippocampal damage and neuronal loss. Decreased ratios of F-actin/G-actin and MT/tubulin, along with reduced levels of polymerized F-actin and MTs, were found in the hippocampus of alcohol-treated mice. CONCLUSIONS: Our findings suggest that chronic alcohol consumption disrupted the assembly of the actin cytoskeleton and MTs in the hippocampus, potentially contributing to the cognitive deficits and pathological injury induced by chronic alcohol intoxication.

Molecularly imprinted polymer photoelectrochemical sensor for the detection of triazophos in water based on carbon quantum dot-modified titanium dioxide.

Widely used organophosphorus pesticide triazophos (TAP) can easily cumulate in aquatic system due to its high stability chemically and photochemically and thus posing significant threat to aquatic creatures and humans' health. Urging demand for rapid determining TAP in water has risen. Photoelectrochemical (PEC) sensing turns out to be a good candidate for its simplicity in fabrication and swiftness in detection. Nevertheless, traditional PEC sensors often lack selectivity as their signal generation primarily relies on the oxidation of organic compounds in the electrolyte by photo-induced holes. To address this limitation, molecularly imprinted polymers (MIPs) can be in combined with PEC sensors to significantly enhance the selectivity. Here, we present a novel approach utilizing a PEC sensor enhanced by carbon-modified titanium dioxide molecularly imprinted polymers (MIP/C/TiO2 NTs). Carbon quantum dot (CQD) modification of titanium dioxide nanotube arrays (C/TiO2 NTs) was achieved through a one-step anodization process, effectively enhancing visible light absorption by narrowing the band gap of TiO2, and CQDs also function as sensitizer accelerating charge transfer for improved and stable photocurrent signals during detection. Our method further incorporates MIPs to heighten the selectivity of the PEC sensor. Electro-polymerization using cyclic voltammetry was employed to polymerize MIPs with pyrrole as the functional monomer and triazophos as the target molecule. The resultant MIP/C/TiO2 NT sensor exhibited remarkable sensitivity, with a detection limit of 0.03 nM (S/N = 3), alongside exceptional selectivity and stability for triazophos detection in water. This offers a promising avenue for efficient, cost-effective, and rapid monitoring of pesticide contaminants in aquatic environments, contributing to the broader goals of environmental preservation and public health.

Distributed Drive Electric Vehicle Handling Stability Coordination Control Framework Based on Adaptive Model Predictive Control.

Distributed drive electric vehicles improve steering response and enhance overall vehicle stability by independently controlling each motor. This paper introduces a control framework based on Adaptive Model Predictive Control (AMPC) for coordinating handling stability, consisting of three layers: the dynamic supervision layer, online optimization layer, and low-level control layer. The dynamic supervision layer considers the yaw rate and maneuverability limits when establishing the ß-ß˙ phase plane stability boundary and designs variable weight factors based on this stability boundary. The online optimization layer constructs the target weight-adaptive AMPC strategy, which can adjust the control weights for maneuverability and lateral stability in real time based on the variable weight factors provided by the dynamic supervision layer. The low-level control layer precisely allocates the driver's requested driving force and additional yaw moment by using torque distribution error and tire utilization as the cost function. Finally, experiments are conducted on a Simulink-CarSim co-simulation platform to assess the performance of AMPC. Simulation results show that, compared to the traditional MPC strategy, this control strategy not only enhances maneuverability under normal conditions but also improves lateral stability control under extreme conditions.

Spatio-Temporal Joint Optimization-Based Trajectory Planning Method for Autonomous Vehicles in Complex Urban Environments.

Providing safe, smooth, and efficient trajectories for autonomous vehicles has long been a question of great interest in the field of autopiloting. In dynamic and ever-changing urban environments, safe and efficient trajectory planning is fundamental to achieving autonomous driving. Nevertheless, the complexity of environments with multiple constraints poses challenges for trajectory planning. It is possible that behavior planners may not successfully obtain collision-free trajectories in complex urban environments. Herein, this paper introduces spatio-temporal joint optimization-based trajectory planning (SJOTP) with multi-constraints for complex urban environments. The behavior planner generates initial trajectory clusters based on the current state of the vehicle, and a topology-guided hybrid A* algorithm applied to an inflated map is utilized to address the risk of collisions between the initial trajectories and static obstacles. Taking into consideration obstacles, road surface adhesion coefficients, and vehicle dynamics constraints, multi-constraint multi-objective coordinated trajectory planning is conducted, using both differential-flatness vehicle models and point-mass vehicle models. Taking into consideration longitudinal and lateral coupling in trajectory optimization, a spatio-temporal joint optimization solver is used to obtain the optimal trajectory. The simulation verification was conducted on a multi-agent simulation platform. The results demonstrate that this methodology can obtain optimal trajectories safely and efficiently in complex urban environments.

6'-O-Caffeoylarbutin from Quezui Tea: A Highly Effective and Safe Tyrosinase Inhibitor.

Tyrosinase is vital in fruit and vegetable browning and melanin synthesis, crucial for food preservation and pharmaceuticals. We investigated 6'-O-caffeoylarbutin's inhibition, safety, and preservation on tyrosinase. Using HPLC, we analyzed its effect on mushroom tyrosinase and confirmed reversible competitive inhibition. UV_vis and fluorescence spectroscopy revealed a stable complex formation with specific binding, causing enzyme conformational changes. Molecular docking and simulations highlighted strong binding, enabled by hydrogen bonds and hydrophobic interactions. Cellular tests showed growth reduction of A375 cells with mild HaCaT cell toxicity, indicating favorable safety. Animal experiments demonstrated slight toxicity within safe doses. Preservation trials on apple juice showcased 6'-O-caffeoylarbutin's potential in reducing browning. In essence, this study reveals intricate mechanisms and applications of 6'-O-caffeoylarbutin as an effective tyrosinase inhibitor, emphasizing its importance in food preservation and pharmaceuticals. Our research enhances understanding in this field, laying a solid foundation for future exploration.

Short-term postmortem interval estimation by detection of apoptosis-related protein in skin.

Time-of-death extrapolation has always been one of the most important issues in forensic practice. For a complicated case in which a corpse is destroyed with little evidence, judging the time of death of the deceased is a major challenge, which also enables criminals to escape legal sanctions. To find a method to roughly judge the time of death of a corpse with only a small amount of skin tissue, in this study, we established an early death model by using mice; furthermore, the postmortem interval was estimated by determining the protein and mRNA levels of Bax and Bcl-2 in the skin. In this process, 0 h after death was used as the control group, and the expression levels of Bax and Caspase-3 reached the maximum value at 8-12 h, while Bcl-2, as an inhibitor of apoptosis protein, peaked after 24 h. The mRNA expression levels of related proteins in postmortem skin tissues were also different. The results of these data indicate that the protein and mRNA levels of Bax and Bcl-2 in the skin have potential application in early time-of-death estimation.

Omic horizon expression: a database of gene expression based on RNA sequencing data.

BACKGROUND: Gene expression profiles have important significance for gene expression characteristics and further functional studies. More attention has been given to the expression databases in humans and mice, but less attention has been given to rats, while rat models also play an irreplaceable role in biomedical experiments. RESULTS: To depict the rat gene expression profiles in mRNA expression levels, we analyzed over 2,700 RNA sequencing (RNA-Seq) samples from 48 tissues, 40 primary cell types and 25 cell lines; and then mapped them to the latest version of the rat genome reference, mRatBN7.2. Based on these datasets and reanalysis, we constructed a new database, the Omic Horizon Expression Database ( http://immudb.bjmu.edu.cn/expression.html ), which allows expressional profile query of over 25,000 rat genes based on non-redundant gene symbols. The database supports requests using gene symbols (or alias), Ensemble and Entrez gene IDs. Gene expression profiles can be queried in three categories: tissues, primary cells and cell lines. Application examples including expression profiling and comparison, as well as identification of novel rat genes, were illustrated to show the utility of the database. CONCLUSIONS: As an omic resource, the Omic Horizon Expression Database provides horizons of gene expression profiles across various tissues and cells, which greatly facilitates the identification of rat genes as well as functional clues.

The predictive value of inflammatory biomarkers for major pathological response in non-small cell lung cancer patients receiving neoadjuvant chemoimmunotherapy and its association with the immune-related tumor microenvironment: a multi-center study.

BACKGROUND: Inflammatory biomarkers in the peripheral blood have been established as predictors for immunotherapeutic efficacy in advanced non-small cell lung cancer (NSCLC). Whether they can also predict major pathological response (MPR) in neoadjuvant setting remains unclear. METHODS: In this multi-center retrospective study, 122 and 92 stage I-IIIB NSCLC patients from six hospitals who received neoadjuvant chemoimmunotherapy followed by surgery were included in the discovery and external validation cohort, respectively. Baseline and on-treatment neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII) were calculated and associated with MPR. Furthermore, resected tumor samples from 37 patients were collected for RNA-sequencing to investigate the immune-related tumor microenvironment. RESULTS: In both the discovery and validation cohorts, the on-treatment NLR, dNLR, PLR, and SII levels were significantly lower in the patients with MPR versus non-MPR. On-treatment SII remained an independent predictor of MPR in multivariate logistic regression analysis. The area under the curve (AUC) of on-treatment SII for predicting MPR was 0.75 (95%CI, 0.67-0.84) in the discovery cohort. Moreover, the predictive value was further improved by combining the on-treatment SII and radiological tumor regression data, demonstrating an AUC of 0.82 (95%CI, 0.74-0.90). The predictive accuracy was validated in the external cohort. Compared with the SII-high group, patients with SII-Low were associated with the activated B cell receptor signaling pathway and a higher intratumoral immune cell infiltration level. CONCLUSIONS: On-treatment SII was independently associated with MPR in NSCLC patients receiving neoadjuvant chemoimmunotherapy. Further prospective studies are warranted.