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Lupus nephritis (LN) is a severe and common manifestation of systemic lupus erythematosus (SLE) that is frequently identified with a poor prognosis. Macrophages play an important role in its pathogenesis. Different macrophage subtypes have different effects on lupus-affected kidneys. Based on their origin, macrophages can be divided into monocyte-derived macrophages (MoMacs) and tissue-resident macrophages (TrMacs). During nephritis, TrMacs develop a hybrid pro-inflammatory and anti-inflammatory functional phenotype, as they do not secrete arginase or nitric oxide (NO) when stimulated by cytokines. The infiltration of these mixed-phenotype macrophages is related to the continuous damage caused by immune complexes and exposure to circulating inflammatory mediators, which is an indication of the failure to resolve inflammation. On the other hand, MoMacs differentiate into M1 or M2 cells under cytokine stimulation. M1 macrophages are pro-inflammatory and secrete pro-inflammatory cytokines, while the M2 main phenotype is essentially anti-inflammatory and promotes tissue repair. Conversely, MoMacs undergo differentiation into M1 or M2 cells in response to cytokine stimulation. M1 macrophages are considered pro-inflammatory cells and secrete pro-inflammatory mediators, whereas the M2 main phenotype is primarily anti-inflammatory and promotes tissue repair. Moreover, based on cytokine expression, M2 macrophages can be further divided into M2a, M2b, and M2c phenotypes. M2a and M2c have anti-inflammatory effects and participate in tissue repair, while M2b cells have immunoregulatory and pro-inflammatory properties. Further, memory macrophages also have a role in the advancement of LN. Studies have demonstrated that the polarization of macrophages is controlled by multiple metabolic pathways, such as glycolysis, the pentose phosphate pathway, fatty acid oxidation, sphingolipid metabolism, the tricarboxylic acid cycle, and arginine metabolism. The changes in these metabolic pathways can be regulated by substances such as fish oil, polyenylphosphatidylcholine, taurine, fumaric acid, metformin, and salbutamol, which inhibit M1 polarization of macrophages and promote M2 polarization, thereby alleviating LN. Highlights Macrophages are the main infiltrating cells in lupus nephritis (LN) kidneys. Different macrophage subtypes have different effects on the development and progression of LN. M1-type macrophages possess pro-inflammatory functions, participating in the onset and progression of LN. In contrast, M2-type macrophages primarily exhibit anti-inflammatory and tissue repair-promoting functions, which are beneficial for the remission of LN. The infiltration of mixed phenotype macrophages reflects a failure in the resolution of inflammation and correlates with poor prognostic outcomes in LN. Multiple metabolic pathways, such as glycolysis, pentose phosphate pathway, amino sugar and nucleotide sugar metabolism, fatty acid oxidation, sphingolipid metabolism, tricarboxylic acid cycle, arginine metabolism, and tryptophan metabolism, regulate macrophage polarization. Compounds such as omega-3 fatty acids, polyunsaturated phospholipids, taurine, fumarate, metformin, salbutamol, and others can modulate metabolic pathways, suppressing M1 polarization and promoting M2 polarization in macrophages, thereby ameliorating LN symptoms.

Background Comprehensive genomic analysis and optimal treatment for non-small cell lung cancer (NSCLC) patients with epidermal growth factor receptor ( EGFR ) G719X + S768I co-mutations remain limited. This study aimed to elucidate the genetic landscape and the clinical effectiveness of EGFR tyrosine kinase inhibitors (EGFR-TKIs) in this subset. Methods A total of 645 EGFR -mutant NSCLC patients were retrospectively screened, with 142 patients harbored EGFR G719X + S768I co-mutations. Among these patients, next-generation sequencing was performed in 126 patients, and the efficacy of first-line EGFR-TKIs was evaluated in 96 patients with stage IV disease. Impacts of variant allele frequency (VAF) and concurrent TP53 mutations were also analyzed. Results Among G719X variants, G719C was most prevalent (69.8%), followed by G719A (19.0%) and G719S (8.7%). The most common co-existing mutation was TP53 (38.0%), followed by ALK and PIK3CA (6.3% each). For first-line EGFR-TKIs, the overall objective response rate (ORR) reached 68.8%, with a median progression-free survival (mPFS) of 21.4 months (95% CI: 18.2–24.6). Afatinib showed a significantly better response compared to both first- and third-generation EGFR-TKIs (1st vs. 2nd vs. 3rd generations, ORR: 35.7% vs. 76.8% vs. 61.5%, P  = 0.01; mPFS: 17.2 vs. 23.4 vs. 17.4 months, P  = 0.008). VAF and TP53 mutation status did not affect outcomes ( P  > 0.05), but patients with metastases in the brain and liver experienced notably shorter mPFS. Brain metastases patients had an ORR of 70.5% without additional benefit from third-generation TKIs. Conclusions This study delineates the genomic profile of EGFR G719X + S768I co-mutated NSCLC and highlights the superior effectiveness of second-generation EGFR-TKIs, particularly afatinib. These findings provided valuable insights to guide clinical decision-making and facilitate the development of tailored therapeutic strategies for this subset.

Reliable fault line selection technology is crucial for preventing fault range expansion and ensuring the reliable operation of distribution networks. Modern distribution systems with neutral earthing via arc extinguishing coil face challenges during single-phase ground faults due to indistinct fault characteristics and system sequence networks influenced by the grounding methods on the distributed generation side. These factors increase the difficulty of fault line selection. By analyzing the differences between the zero-sequence currents of feeder lines and neutral lines in active distribution networks with neutral earthing via arc extinguishing coil, a method for single-phase ground fault line selection has been proposed in this paper. This method involves switching from a neutral point ungrounded mode to a low-resistance neutral grounding mode using distributed generation grid-connected transformers under permanent fault conditions. Criteria based on the differences in zero-sequence current ratios before and after the grounding mode switch are established. Simulation validation using the Power Systems Computer Aided Design (PSCAD) platform has been conducted. The proposed method demonstrates strong tolerance to transition resistance, simple extraction of fault characteristic signals, and accurate fault line selection results.

As the demand for power supply stability and reliability in the active distribution network (ADN) increases, the primary and secondary integrated intelligent switch (PSIIS) has become the primary choice for smart grid transformation in many weak infrastructure areas. However, the number of PSIISs that can be configured is often limited. It is necessary to comprehensively utilize the measurement data and sectional capabilities of PSIISs through the optimal configuration method to find the optimal configuration scheme. Therefore, fault observability-related indexes (FORIs) are proposed based on the functional characteristics of PSIISs. These indexes include fault type observability, fault location observability, fault current distribution characteristics observability, transition resistance observability, and weak infrastructure area observability. An optimization configuration model of PSIISs considering the comprehensive fault observability (CFO) is constructed. The adaptive genetic algorithm (AGA) is selected as the model-solving method. Subsequently, an optimal configuration method of PSIISs considering CFO is proposed. Finally, an example analysis is conducted in MATLAB to verify the effectiveness and feasibility of the proposed method. This optimal configuration method aims to maximize the use of a limited number of PSIISs by considering CFO, and the AGA proves to be an effective tool in solving the optimal configuration scheme.

This paper presents a comprehensive comparison study on the dynamic performances of three planar 3-DOF parallel manipulators (PPMs): 3-RRR, 3-PRR, and 3-RPR. In this research work, the discrete time transfer matrix method (DT-TMM) is employed for developing dynamic models of the planar parallel manipulators. Numerical simulations using the virtual work principle and ADAMS 2016 software are performed to verify the DT-TMM dynamic model of PPMs. Numerous dynamic performance indices, including dynamic dexterity, the power requirement, energy transmission efficiency, and the joint force/torque margin, are proposed to compare the dynamic performance of three PPMs under the general circular and linear trajectories. The comprehensive analyses and comparisons show that: (1) the 3-RRR PPM has advantages in terms of a circular trajectory, offering the best dynamic dexterity performance, the smallest power requirement, and the second-highest energy transfer efficiency; (2) the 3-PRR PPM performs best in terms of a linear trajectory, offering the best dynamic dexterity, the smallest power requirement range, and the best drive performance; and (3) the 3-RPR PPM has the highest energy transfer efficiency and demonstrates better dynamic performance in a circular trajectory compared to a linear trajectory.

Background The combined prognostic role of skeletal muscle index (SMI), subcutaneous fat index (SFI), and visceral fat index (VFI) in non-metastatic non-small cell lung cancer (NSCLC) remains unclear. Methods Consecutive non-metastatic NSCLC patients who underwent radical pulmonary resection at Yunnan Cancer Hospital from January 2013 to December 2018 were analyzed. Preoperative CT-derived SMI, SFI, and VFI at the third lumbar vertebra level (L3) were stratified into sex-specific high and low groups. A composite index was created based on the count of low-value measures among the three indices. Cox regression evaluated associations with overall survival (OS) and relapse-free survival (RFS). Results A total of 1661 patients (mean age 58.9 ± 9.5 years; 911 men [54.8%] and 750 women [45.2%]) were enrolled, with a median follow-up of 73.97 months (95% CI: 72.80–75.10). Low SMI (HR = 1.49, 95% CI: 1.16–1.92, p  = 0.002), low SFI (HR = 1.54, 95% CI: 1.22–1.94, p  < 0.001), and low VFI (HR = 1.69, 95% CI: 1.32–2.17, p  < 0.001) were associated with poorer OS. The composite index demonstrated poorer OS with an increasing number of low indices (SMI, SFI, and VFI) ( p for trend < 0.001): one-low (HR = 1.50, 95% CI: 1.16–1.94, p  = 0.002), two-low (HR = 1.71, 95% CI: 1.29–2.28, p  < 0.001), and all-low (HR = 2.99, 95% CI: 1.89–4.71, p  < 0.001). Similar trend occurred for RFS (all p  < 0.05). Conclusion Preoperative SMI, SFI, and VFI were independently associated with prognosis in patients with NSCLC, and a composite index integrating these measures may provide valuable complementary information for risk stratification.

Prehistoric human history on the Tibetan Plateau is a hotly debated topic. Archaeological research on the plateau during the past few decades has enormously improved our understanding of the topic and makes it possible for us to consider the processes and mechanisms of prehistoric human migration to the region. By reviewing the published archaeological research on the Tibetan Plateau, we propose that the first people on the plateau initially spread into the He-Huang region from the Chinese Loess Plateau, and then moved to the low elevation Northeastern Tibetan Plateau and perhaps subsequently to the entire plateau. This process consisted of four stages. （1） During the climatic amelioration of the Last Deglacial period （15-11.6 ka BP）, Upper Paleolithic hunter-gatherers with a developed microlithic technology first spread into the Northeastern Tibetan Plateau. （2） In the early-mid Holocene （11.6-6 ka BP）, Epipaleolithic microlithic hunter-gatherers were widely distributed on the northeastern plateau and spread southwards to the interior plateau, possibly with millet agriculture developed in the neigh- boring low elevation regions. （3） In the mid-late Holocene （6-4 ka BP）, Neolithic millet farmers spread into low elevation river valleys in the northeastern and southeastern plateau areas. （4） In the late Holocene （4-2.3 ka BP）, Bronze Age barley and wheat farmers further settled on the high elevation regions of the Tibetan Plateau, especially after 3.6 ka BP. Finally, we sug- gest that all of the reported Paleolithic sites earlier than the LGM on the Tibetan Plateau need further examination.

Porous materials are very promising for the development of cost- and energy-efficient separation processes, such as for the purification of ethylene from ethylene/ethane mixture—an important but currently challenging industrial process. Here we report a microporous hydrogen-bonded organic framework that takes up ethylene with very good selectivity over ethane through a gating mechanism. The material consists of tetracyano-bicarbazole building blocks held together through intermolecular CN···H–C hydrogen bonding interactions, and forms as a threefold-interpenetrated framework with pores of suitable size for the selective capture of ethylene. The hydrogen-bonded organic framework exhibits a gating mechanism in which the threshold pressure required for guest uptake varies with the temperature. Ethylene/ethane separation is validated by breakthrough experiments with high purity of ethylene (99.1%) at 333 K. Hydrogen-bonded organic frameworks are usually not robust, yet this material was stable under harsh conditions, including exposure to strong acidity, basicity and a variety of highly polar solvents.Porous materials are promising candidates for the cost- and energy-efficient separation of ethylene and ethane from gas mixtures: an important but challenging industrial process. Now, a hydrogen-bonded organic framework has been reported that is stable under harsh conditions and can take up ethylene at practical temperatures—with very high selectivity over ethane—through a gating mechanism.

The heterogeneity of tumor immune microenvironments is a major factor in poor prognosis among hepatocellular carcinoma (HCC) patients. Neutrophils have been identified as playing a critical role in the immune microenvironment of HCC based on recent single-cell studies. However, there is still a need to stratify HCC patients based on neutrophil heterogeneity. Therefore, developing an approach that efficiently describes \"neutrophil characteristics\" in HCC patients is crucial to guide clinical decision-making. We stratified two cohorts of HCC patients into molecular subtypes associated with neutrophils using bulk-sequencing and single-cell sequencing data. Additionally, we constructed a new risk model by integrating machine learning analysis from 101 prediction models. We compared the biological and molecular features among patient subgroups to assess the model's effectiveness. Furthermore, an essential gene identified in this study was validated through molecular biology experiments. We stratified patients with HCC into subtypes that exhibited significant differences in prognosis, clinical pathological characteristics, inflammation-related pathways, levels of immune infiltration, and expression levels of immune genes. Furthermore, A risk model called the \"neutrophil-derived signature\" (NDS) was constructed using machine learning, consisting of 10 essential genes. The NDS's RiskScore demonstrated superior accuracy to clinical variables and correlated with higher malignancy degrees. RiskScore was an independent prognostic factor for overall survival and showed predictive value for HCC patient prognosis. Additionally, we observed associations between RiskScore and the efficacy of immune therapy and chemotherapy drugs. Our study highlights the critical role of neutrophils in the tumor microenvironment of HCC. The developed NDS is a powerful tool for assessing the risk and clinical treatment of HCC. Furthermore, we identified and analyzed the feasibility of the critical gene in NDS as a molecular marker for HCC.

Background: Fractional Flow Reserve (FFR) has been widely utilized in clinical practice for decades,however, the comparative clinical outcomes of FFR-guided versus coronary angiography (CAG)-guided percutaneous coronary intervention (PCI) still warrant further evaluation. Methods and materials: Randomized controlled trials (RCTs) comparing FFR-guided and CAG-guided PCI were systematically searched in PubMed, Embase and the Cochrane library databases from their respective inception to December 31, 2023. Primary endpoints included the incidence of major adverse cardiovascular events (MACE), all cause mortality, myocardial infarction (MI) and target vessel revascularization(TVR). Stratified analyses were performed to evaluate the effects of FFR-guided versus CAG-guided PCI across different follow-up periods (short-term and long-term) and patient cohorts (acute coronary syndrome (ACS) and non-ACS patients). Results: This meta-analysis included eight RCTs involving 4,433 patients, with four studies reporting 1-year outcomes and four reporting outcomes beyond one year. Among these, 5 studies focused on non-ACS patients, and three included ACS patients, with a significant male predominance (3,437 vs. 996 females). By follow-up duration, FFR-guided PCI demonstrated significant long-term reductions in MACE (OR: 0.76, 95% CI: 0.60-0.96, P = 0.022) and MI (OR: 0.65, 95% CI: 0.45-0.93, P = 0.018), but no significant short-term benefits were observed for MACE (OR: 0.85, 95% CI: 0.67-1.08, P = 0.194), MI (OR: 0.85, 95% CI: 0.63-1.16, P = 0.307), or all-cause mortality (short-term: OR: 0.77, 95% CI: 0.47-1.26, P = 0.296; long-term: OR: 0.74, 95% CI: 0.50-1.09, P = 0.123). By patient type, FFR-guided PCI significantly reduced MACE (OR: 0.82, 95% CI: 0.68-0.99, P = 0.038), MI (OR: 0.76, 95% CI: 0.58-0.99, P = 0.039), and TVR (OR: 0.78, 95% CI: 0.61-0.99, P = 0.036) in non-ACS patients, but no significant differences were observed in ACS patients for MACE (OR: 0.76, 95% CI: 0.53-1.08, P = 0.127), all-cause mortality (OR: 0.60, 95% CI: 0.35-1.02, P = 0.060), MI (OR: 0.77, 95% CI: 0.47-1.25, P = 0.294), or TVR (OR: 0.98, 95% CI: 0.48-2.02, P = 0.315). Sensitivity analysis confirmed the robustness of these findings. Conclusions: FFR-guided PCI is superior to CAG-guided PCI in reducing MACE and MI in long-term and non-ACS patients but shows no advantage in short-term or ACS populations. FFR should be avoided in patients presenting with ACS in routine clinical practice.