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This paper is a continuation and an extension of our recent work (Deng et al. in Arch Ration Mech Anal 231(1):153–187, 2019) on the identification of magnetized anomalies using geomagnetic monitoring, which aims to establish a rigorous mathematical theory for the geomagnetic detection technology. Suppose a collection of magnetized anomalies is present in the shell of the Earth. By monitoring the variation of the magnetic field of the Earth due to the presence of the anomalies, we establish sufficient conditions for the unique recovery of these unknown anomalies. Deng et al. (2019), the geomagnetic model was described by a linear Maxwell system. In this paper, we consider a much more sophisticated and complicated magnetohydrodynamic model, which stems from the widely accepted dynamo theory of geomagnetics.

It is recognized by academia and industry that second‐life batteries retired from electric vehicles still have use values and can be effectively used for supporting less demanding applications. At present, there lacks investigation on the applications of re‐using retired batteries on serving residential sector's energy management. Motivated by this, this paper studies the scenario of assembling retired batteries to be second‐life battery energy storage systems (SL‐BESSs) and using them to serve the energy demand of residential communities in an affordable manner. Based on an established SL‐BESS model, a two‐level community energy management framework is proposed, which optimizes the schedules of a SL‐BESS and other energy resources in a community subjected to a variety of short‐term operational objectives. In the upper level, a many‐objective optimization model is formulated, which comprehensively integrates four objectives covering the community's multi‐scale operational considerations. A NSGA‐III‐based solving approach is developed to find the non‐dominated solutions of the model. In the lower level, the optimal community scale load reshaping decisions and energy costs obtained from the upper level are allocated to individual houses. Extensive numerical case studies are conducted, and the results show that the proposed system can realize better trade‐off among the different operational considerations with less computational cost.

Car sharing has become an increasingly popular mode of travel. This paper provides a comprehensive literature survey on relocation optimization for shared electric vehicles. The literature is reviewed and categorized based on two types of relocation: static and dynamic relocation. Static relocation is analyzed in terms of operator-based relocation and user-based relocation, while dynamic relocation is analyzed in terms of four methodologies: optimization models, simulations, multi-stage methods, and deep reinforcement learning. The paper finally provides some interesting future research topics, such as considering the nonlinear charging process of electric vehicles in the process of constructing relocation optimization models and designing algorithms for shared electric vehicles.

Carcinogenic aflatoxins can be inactivated by smectites (e.g., montmorillonite) through adsorption and degradation. Proteins in gastric fluids can reduce smectite’s adsorption capacity for aflatoxins. The objective of this study was to evaluate the efficiency of smectites modified with organic nutrients in restricting the influence of proteins on aflatoxin adsorption. Arginine, histidine, choline, lysine, and vitamin B1 were selected to occupy part of the interlayer space of montmorillonite to achieve a smectite structure more selective for aflatoxin adsorption, but not for the large protein molecules. The unmodified montmorillonite had a maximum adsorption capacity of 0.2 mol/kg in the presence of pepsin. The vitamin B1-montmorillonite showed significant improvements in the aflatoxin affinity constant from 0.065 to 0.201 μ M − 1 and the aflatoxin adsorption to 0.56 mol/kg. Choline-montmorillonite and histidine-montmorillonite showed a moderate increase in AfB1 adsorption. Arginine-montmorillonite and lysine-montmorillonite showed a slight increase in the adsorption capacity, but did not improve the affinity constant. The XRD results indicated that pepsin could still access the interlayer of nutrient-montmorillonite complexes. The intercalation of organic nutrients into the interlayer space of montmorillonite improved the AfB1 adsorption by restricting the adsorption of pepsin.

Background Lung adenocarcinoma (LUAD) is a refractory tumor with high incidence, high mortality, and easy development of drug resistance. Represented by PD-L1, the rise of immunotherapy and multidrug combinations offers a reliable approach to treating LUAD. However, there are still some patients with immunoresistance or insensitivity, and new combination therapies are still needed. Methods In this study, cyclic arginine-glycine-aspartate (cRGD)/erythrocyte membrane (RBCM) double-head nanocarriers were designed. This nanocarrier platform targets CTRP6 in tumors and delivers gemcitabine to block the progression of lung cancer. PD-L1 monoclonal antibodies were used as a codelivery platform to explore the effect of the codelivery platform on immunotherapy. Results CTRP6 expression was negatively correlated with the prognosis of patients with lung adenocarcinoma. The codelivery platform @RBCM/cRGD-PhLips effectively targeted tumor cells. Co-carrying gemcitabine and targeting CTRP6 expression, it amplified ferroptosis of tumor cells through the NRF2/STAT3 signaling pathway, activated intratumoral immunity, and promoted M1-like macrophage transformation and CD8 + T-cell recruitment. This platform amplified the immune effect of PD-L1 monoclonal antibodies to play an anti-lung cancer role. Conclusions The synergistic delivery of the targeted tumor cell-intrinsic CTRP6 biomimetic nanocarrier provides a new approach to the combined immunotherapy of lung cancer. Graphical Abstract

Background Tumor-associated macrophages (TAMs) play pivotal roles in innate immunity and contribute to the advancement of lung cancer. We aimed to identify novel TAM-related biomarkers and significance of macrophage infiltration in lung adenocarcinoma (LUAD) through an integrative analysis of single-cell RNA-sequencing (scRNA-seq) data. To describe the cell atlas and construct a novel prognostic signature in LUAD. Methods The gene signature linked to TAMs was identified utilizing Scanpy from the scRNA-seq dataset GSE131907. Subsequent analysis involved evaluating the expression levels of these genes, their potential molecular mechanisms, and prognostic significance in LUAD using data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We also constructed a risk score models through LASSO Cox regression for these genes. The underlying mechanism was further elucidated through the application of GSEA, ESTIMATE, TIDE, and other bioinformatic algorithms. Results Single-cell atlas was described by analyze 29 scRNA-seq samples from 19 LUAD patients. The TAMs-related gene signature (TGS) was identified as an independent prognostic factor by LASSO Cox regression analysis using differential expression genes (DEGs) derived from pro- and anti-inflammatory macrophage cells. Risk score model including nine TAMs-related genes ( FOSL1 , ZNF697 , ADM , UBE2S , TICAM1 , S100P , BIRC3 , TLE1 , and DEFB1 ) were obtained for prognosis construction. Moreover, the risk model underwent additional validation in four external GEO cohorts: GSE31210, GSE72094, GSE26939, and GSE30219. Interestingly, TGS-high tumors revealed enrichments in TGF-β signaling and hypoxia pathways, which shown low immune infiltration and immunosuppression by ESTIMATE and TIDE algorithm. The TGS-high risk group exhibited lower richness and diversity in the T-cell receptor (TCR) repertoire. Conclusion This study introduces a novel TGS score developed through LASSO Cox regression analysis, utilizing DEGs in pro- and anti-inflammatory macrophage cells. High TGS tumors exhibited enrichment in TGF-β signaling and hypoxia pathways, suggesting their potential utility in predicting prognosis and immune responses in patients with LUAD. These results offer promising implications for the development of therapeutic strategies for LUAD.

Angiogenesis is the process of capillary sprouting from pre-existing vessels and it plays a critical role in the carcinogenic process of lung adenocarcinoma (LUAD). However, the association of angiogenesis regulators with the prognosis and progression of LUAD needs to be further elucidated. In this study, we adopted differential expression analysis, Cox proportional hazards (PH) regression analysis and experimental validation to identify angiogenesis regulators correlated with a poor prognosis, immune infiltration and cancer progression in LUAD. These results showed that the diagnostic and prognostic models based on COL5A2 and EPHB2 served as independent biomarkers with superior predictive ability. The patients in the high-risk group exhibited a worse prognosis in the TCGA cohort (P < 0.001, HR = 1.72, 95% CI 1.28–2.30), GSE310210 cohort (P = 0.005, HR = 2.87, 95% CI 1.46–5.61), and GSE31019 cohort (P = 0.01, HR = 2.14, 95% CI 1.19–3.86) than patients in the low-risk group. The high prognostic risk patients had a higher TMB (P < 0.001); higher fractions of M0 macrophages, neutrophils, NK cells resting, and T cells CD4 memory activated (P < 0.05); and higher expression of immune checkpoints PD-1, PDL-1, PDL-2, and B7H3 (P < 0.001). Patients in the high-risk group were more sensitive to chemotherapeutic drugs and molecular targeted drugs such as cisplatin, doxorubicin, gefitinib, and bosutinib (P < 0.0001). In addition, inhibition of COL5A2 and EPHB2 effectively suppressed the proliferation and migration of LUAD cells. The current study identified angiogenesis regulators as potential biomarkers and therapeutic targets for LUAD and may help to further optimize cancer therapy.

Neoadjuvant chemoimmunotherapy is increasingly employed in resectable non-small cell lung cancer (NSCLC), with variable pathological complete response (pCR) rates. Currently, no reliable preoperative tool is available for predicting pCR. This study develops a nomogram based on clinical variables to predict pCR and guide individualized surgical decisions. We retrospectively analyzed data from 179 NSCLC patients (stages IIB-IIIB) who received neoadjuvant chemoimmunotherapy followed by resection (2019-2022). Variables included demographics, smoking history, comorbidities, treatment details, and pathology. Univariate and multivariate logistic regression identified pCR predictors, which were incorporated to build a nomogram. Performance was assessed via area under the curve (AUC), calibration, and decision curve analysis (DCA). Of 179 patients, 92 (51.4%) achieved pCR. Multivariate analysis identified independent predictors: non-squamous histology (OR 0.344 (non-squamous vs. squamous), 95% CI 0.151-0.707, p = 0.006), positive family history (OR 10.76 (positive vs. negative), 95% CI 1.903-203.3, p = 0.027), shorter smoking cessation duration (defined as time in days from last cigarette to treatment start) (OR 0.999 (per day), 95% CI 0.999-0.999, p = 0.033), older age (OR 1.053 (per year), 95% CI 1.005-1.106, p = 0.032), and more treatment cycles (OR 1.621 (per cycle), 95% CI 1.007-2.661, p = 0.049). The nomogram showed modest discrimination (AUC 0.709, 95% CI 0.633-0.785), good calibration, and net benefit on DCA, though it has not been externally validated and is limited by single-center data, small sample size, high pCR rate, and skewed demographics (95.5% male, 92.7% smokers), potentially limiting generalizability to diverse populations such as females or non-smokers. This nomogram, derived from routine clinical data, predicts pCR after neoadjuvant chemoimmunotherapy in NSCLC, offering a tool for thoracic surgeons to optimize treatment and surgical planning, despite its modest discriminative power, by serving as a complementary aid in resource-limited settings where biomarkers may not be readily available. External validation in larger, multi-center cohorts is essential.

Background The increasing prevalence of multiple primarylung cancers (MPLCs) presents challenges to current diagnostic and clinicalmanagement approaches. However, the molecular mechanisms driving MPLCdevelopment and distinguishing it from solitary primary lung cancers (SPLCs)remain largely unexplored. Methods We performed a comparative single‐cell RNAsequencing (scRNA‐seq) analysis on tumour and adjacent para‐tumour tissues fromMPLC and SPLC patients to comparatively evaluate their immunological landscapes.Additionally, multiplex immunofluorescence (mIF) staining and independentvalidation datasets were used to confirm findings. Results MPLCs and SPLCs share significant similarities in genetic, transcriptomic and immune profiles, suggesting common therapeutic strategies such as EGFR‐TKIs andICIs. Notably, an immunosuppressive macrophage subtype, F13A1+ Macrophage (Mϕ), is specifically enriched in MPLCs. This subtype overexpresses M2 macrophagemarkers and exhibits up‐regulation of SPP1‐CD44/CCL13‐ACKR1 interactions, indicatingits role in shaping the immunosuppressive tumour microenvironment and promotingtumour growth in MPLCs. Conclusions This study unveils shared molecular mechanismsbetween MPLCs and SPLCs, while identifying MPLC‐specific cellular and molecularfeatures, such as the role of F13A1+ macrophages. The findings provide novelinsights into MPLC pathogenesis, supporting the development of targetedtherapeutic strategies. Key points Comparative scRNA‐seq analysis reveals significant similarities in genetic, transcriptomicand immune profiles between MPLCs and SPLCs. Identification of a unique immunosuppressive F13A1+ macrophage subtype, preferentially enriched in MPLCs, linked to immune evasion and tumourprogression. SPP1‐CD44/CCL13‐ACKR1 interactions are crucial in MPLC tumour microenvironment, indicating potential targets for therapeutic intervention. Comparative single‐cell RNA sequencing (scRNA‐seq) analysis reveals significant similarities in genetic, transcriptomic and immune profiles between multiple primary lung cancers (MPLCs) and solitary primary lung cancers (SPLCs). Identification of a unique F13A1+ macrophage subtype, preferentially enriched in MPLCs, linked to immune evasion and tumour progression. SPP1‐CD44/CCL13‐ACKR1 interactions are crucial in MPLC tumour microenvironment, indicating potential targets for therapeutic intervention.

Mycotoxins in feed and food are highly toxic and pose a serious danger even at very low concentrations. The use of bentonites in animal diet can reduce toxin bioavailability. However, some mycotoxins like fumonisin B1 (FB1) form anionic species which excludes the use of negatively charged clays. Layered double hydroxides (LDH) with anion-exchange properties, in theory, can be perfect candidates to adsorb FB1. However, fundamental research on the use of LDH for mycotoxins removal is scarce and incomplete. Thus, the presented study was designed to explore such a possibility. The LDH materials with differing chemistry and layer charge were synthesized by co-precipitation both from metal nitrates and chlorides and were then tested for FB1 removal. XRD, FTIR, XPS, and chemical analysis were used for the LDH characterization and to obtain insight into the removal mechanisms. A higher adsorption capacity was observed for the Mg/Al LDH samples (~0.08–0.15 mol/kg) in comparison to the Mg/Fe LDH samples (~0.05–0.09 mol/kg) with no difference in removal efficiency between Cl and NO3 intercalated LDH. The adsorption capacity increased along with lower layer charge of Mg/Al and was attributed to the lower content of bonded carbonates and the increase of non-polar sites which led to matching between the adsorption domains of LDH with FB1. The FTIR analysis confirmed the negative effect of carbonates which hampered the adsorption at pH 7 and led to the highest adsorption at pH 5 (FB1 content ~15.8 ± 0.75 wt.%). The fast surface adsorption (1–2 min) was dominant and XRD analysis of the basal spacing indicated that no FB1 intercalation occurred in the LDH. The XPS confirmed a strong interaction of FB1 with Mg sites of LDH at pH 5 where the interaction with FB1 carboxylate moieties COO− was confirmed. The research confirmed a high affinity and selectivity of LDH structures towards anionic forms of FB1 mycotoxin.