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Abstract Three-dimensional solar steam evaporators with efficient water purification performance have received increasing attention recently. Herein, elastic polymer covalent organic frameworks (PP-PEG) containing PEG chains with intriguing adaptability to guests are prepared by forming porphyrin rings. PP-PEG foams demonstrate full spectrum absorbance and excellent photothermal conversion properties. Through well-designed thermal management and optimization of the hydrophilicity and PEG chain length, we obtain a highly efficient solar evaporator with an evaporation rate of 4.89 kg m−2 h−1 under 1 sun in self-contained mode. The optimized solar evaporation rate is increased to 18.88 kg m−2 h−1 under 1 sun with a facile truncated cone reflector, exceeding all known solar steam evaporators. This innovative design holds immense promise for desalination and water purification owing to its simple preparation, high efficiency and durability.

Abstract Presenilin-associated protein (PSAP) is a mitochondrial proapoptotic protein as established in cell biology studies. It remains unknown whether it involves in neurodegenerative diseases. Here, we explored PASP expression in adult and aged human brains and its alteration relative to Alzheimer-disease (AD)-type neuropathology. In pathology-free brains, light PASP immunoreactivity (IR) occurred among largely principal neurons in the cerebrum and subcortical structures. In the brains with AD pathology, enhanced PSAP IR occurred in neuronal and neuritic profiles with a tangle-like appearance, with PSAP and pTau protein levels elevated in neocortical lysates relative to control. Neuronal/neuritic profiles with enhanced PSAP IR partially colocalized with pTau, but invariably with Amylo-Glo labelled tangles. The neuronal somata with enhanced PASP IR also showed diminished IR for casein kinase 1 delta (Ck1δ), a marker of granulovacuolar degeneration; and diminished IR for sortilin, which is normally expressed in membrane and intracellular protein sorting/trafficking organelles. In old 3xTg-AD mice with β-amyloid and pTau pathologies developed in the brain, PSAP IR in the cerebral sections exhibited no difference relative to wildtype mice. These findings indicate that PSAP upregulation is involved in the course of tangle formation especially in the human brain during aging and in AD pathogenesis.

Abstract Background Multiple studies have shown that tumor-associated macrophages (TAMs) promote cancer initiation and progression. However, the reprogramming of macrophages in the tumor microenvironment (TME) and the cross-talk between TAMs and malignant subclones in intrahepatic cholangiocarcinoma (iCCA) has not been fully characterized, especially in a spatially resolved manner. Deciphering the spatial architecture of variable tissue cellular components in iCCA could contribute to the positional context of gene expression containing information pathological changes and cellular variability. Methods Here, we applied spatial transcriptomics (ST) and digital spatial profiler (DSP) technologies with tumor sections from patients with iCCA. Results The results reveal that spatial inter- and intra-tumor heterogeneities feature iCCA malignancy, and tumor subclones are mainly driven by physical proximity. Tumor cells with TME components shaped the intra-sectional heterogenetic spatial architecture. Macrophages are the most infiltrated TME component in iCCA. The protein trefoil factor 3 (TFF3) secreted by the malignant subclone can induce macrophages to reprogram to a tumor-promoting state, which in turn contributes to an immune-suppressive environment and boosts tumor progression. Conclusions In conclusion, our description of the iCCA ecosystem in a spatially resolved manner provides novel insights into the spatial features and the immune suppressive landscapes of TME for iCCA.

Objective: This study aims to elucidate and quantify the composition of Jiangtang Qingre formula (JQF), delineate the absorbed components in the bloodstream, predict the major biologically active components, and identify potential targets for the treatment of diabetes mellitus (DM). Materials and Methods: The chemical composition and metabolites of JQF were elucidated using ultra-high-performance liquid chromatography (UHPLC)-linear ion trap quadrupole-orbitrap high-resolution mass spectrometry (MS). The various components of JQF were concurrently determined using UHPLC-triple–quadrupole MS. Network pharmacological analysis was employed to explore the bioactive components and potential therapeutic targets in DM. Results: A total of 63 compounds were identified and provisionally characterized, with flavones, organic acids, and alkaloids emerging as the major chemical constituents. A robust analytical method that enables the simultaneous quantification of 24 representative components was successfully developed. The contents of 11 batches of samples were assessed. Ten prototype components were identified in rat plasma. The pathways associated with the efficacy of JQF in DM treatment were linked to signal transduction, endocrine and immune systems, lipid metabolism, and amino acid metabolism. Conclusion: This study systematically and comprehensively characterized the major chemical components and patterns in JQF, laying the groundwork for understanding its pharmacodynamic mechanisms and clinical applications.

Abstract Background Retroperitoneal liposarcoma (RPLPS) is a relatively rare disease. Liposarcomas vary in size, but sizeable RPLPS larger than 30 cm in diameter are very rare, and their diagnosis and treatment present significant challenges. Case presentation We report a 58-year-old male patient who was admitted to the hospital with an increased abdominal circumference and was later diagnosed with a giant RPLPS. The liposarcoma was found to adhere to the right kidney and the entire ureter, invading the ascending colon. The patient underwent complete combined surgical resection. The tumor was removed intact, measured 55.0 cm × 30.0 cm × 18.0 cm, and weighed 19.8 kg. Histopathologic analysis revealed well-differentiated liposarcoma (WDLPS). The patient was successfully discharged from the hospital and followed up for 6 months with no signs of recurrence. Conclusion RPLPS is a rare tumor with atypical clinical presentation. Surgery remains the most effective method of treatment for retroperitoneal sarcomas, with complete removal if there is local invasion. Preoperative examination, including three-dimensional (3D) reconstruction, is essential for surgical success. The role of adjuvant radiotherapy or chemotherapy remains controversial. However, clinicians should not rule them out as viable options.

Abstract Endometrial cancer (EC) is associated with significant risk factors such as polycystic ovarian syndrome (PCOS) and sedentary behavior. In our study, we aim to employ machine learning algorithms to investigate the potential molecular processes that underlie their interaction and explore their respective roles in the diagnosis and immunotherapy of EC. The GEO database provides access to microarray data, which was utilized in this study to identify gene expression modules associated with PCOS and sedentary behavior, using weighted gene expression network analysis (WGCNA). Cluego software was then employed to investigate the energy enrichment of shared pathways in both PCOS and sedentary individuals, and differential gene analysis was used to confirm another two databases. The miRNAs–mRNAs controlled network was constructed to verify the pathway. The immune-related factors of the shared pathway in EC were then analyzed. Finally, to validate our findings, we conducted cell experiments using EC cell lines (AN3CA, KLE, Ishikawa, RL95-2, and HEC-1A). We found that increased intracellular aromatic compound anabolism is a common feature of both PCOS and sedentary individuals. We then developed a disease pathway model that was based on the common genetic characteristics of PCOS and sedentary behavior. We utilized pathway typing in EC samples and found a significant survival difference between the two subgroups, with the upregulated expression type exhibiting an immune-hot phenotype. Finally, the experimental results confirmed the expression of the hub gene (NAA15) in EC. The findings of our study suggest that genes related to the intracellular aromatic compound metabolic pathway can be used for immunotherapy of EC.

An inductively coupled plasma triple quadrupole mass spectrometric (ICP-QQQ-MS) method was established for the determination of cadmium (Cd) in cereal-based complementary foods for infants and young children. In different collision/reaction modes, namely single quadrupole-helium collision (SQ-He), double quadrupole-helium collision (QQQ-He) and double quadrupole-oxygen reaction (QQQ-O2), various possible interferences in the MS measurement process were analyzed and several methods to eliminate them were proposed. The results showed that the decreasing order of the ability to resist matrix, oxide and multiatomic ion interferences was QQQ-O2 > QQQ-He > SQ-He. QQQ-O2 combined with the standard addition method showed a better ability to eliminate interference. By introducing interference correction equations, the problem of inconsistency between Cd isotope abundance ratio and natural abundance ratio caused by interference from stannum (Sn) isotopes was effectively solved. The results of Cd determination by isotope dilution mass spectrometry (IDMS) in the QQQ-O2 mode were consistent with those obtained using the standard addition method, indicating effective elimination of both matrix effect and MS interference. The proposed ICP-QQQ-MS method allows the accuracy determination of Cd in complex matrix samples.

The subspecies Abrus pulchellus subsp. mollis exhibits pharmacological properties akin to the traditional Chinese medicinal plant Abri Herba (A. pulchellus subsp. cantoniensis (Hance) Verdc.). In this report, we unveil the plastid genome of A. pulchellus subsp. mollis. The genome spans 156,322 base pairs (bp), comprising a large single-copy (LSC) region of 86,633 bp, a small single-copy (SSC) region of 18,219 bp, and two distinct inverted repeat regions (IRs) of 25,735 bp each. Annotation process cataloged a total of 111 genes within this genome, including 77 protein-coding genes, 30 transfer RNA (tRNA) genes, and four ribosomal RNA (rRNA) genes. The overall guanine-cytosine (GC) content of the plastome is 35.5%. Phylogenetic analysis utilizing maximum-likelihood (ML) based on 16 complete plastid genomes reveals a close clustering of three Abrus taxa, namely A. pulchellus subsp. mollis, A. pulchellus subsp. cantoniensis, and A. precatorius. Notably, A. pulchellus subsp. cantoniensis clusters with A. precatorius as a sister group, distinct from A. pulchellus subsp. mollis. These findings highlight significant differences between the plastid genomes of the two subspecies, laying the foundation for future research on the identification of medicinal herbs and germplasm resources related to these subspecies.

Highlights The capacity fading mechanism of the conventional Na3V2(PO4)3//Na3V2(PO4)3 (NVP//NVP) cell has been investigated. All-solid-state ferroelectric-engineered composite electrolyte could improve the electrolyte–electrode interfacial stability as well as the interfacial ion conduction of the Na-ion battery using the NVP anode. Outstanding cyclic stability has been achieved in the all-solid-state Na-ion battery using the NVP anode, with a capacity fading rate as low as 0.005% per cycle.

Abstract Federated learning (FL) has emerged as a significant method for developing machine learning models across multiple devices without centralized data collection. Candidemia, a critical but rare disease in ICUs, poses challenges in early detection and treatment. The goal of this study is to develop a privacy-preserving federated learning framework for predicting candidemia in ICU patients. This approach aims to enhance the accuracy of antifungal drug prescriptions and patient outcomes. This study involved the creation of four predictive FL models for candidemia using data from ICU patients across three hospitals in China. The models were designed to prioritize patient privacy while aggregating learnings across different sites. A unique ensemble feature selection strategy was implemented, combining the strengths of XGBoost’s feature importance and statistical test p values. This strategy aimed to optimize the selection of relevant features for accurate predictions. The federated learning models demonstrated significant improvements over locally trained models, with a 9% increase in the area under the curve (AUC) and a 24% rise in true positive ratio (TPR). Notably, the FL models excelled in the combined TPR + TNR metric, which is critical for feature selection in candidemia prediction. The ensemble feature selection method proved more efficient than previous approaches, achieving comparable performance. The study successfully developed a set of federated learning models that significantly enhance the prediction of candidemia in ICU patients. By leveraging a novel feature selection method and maintaining patient privacy, the models provide a robust framework for improved clinical decision-making in the treatment of candidemia.

Objective To examine the levels of systemic inflammatory response index (SIRI) and serum lipoprotein-associated phospholipase A2 (Lp-PLA2) in patients with acute carbon monoxide poisoning (ACOP), and to explore the predictive value of SIRI, Lp - PLA2 and their combination for delayed encephalopathy after acute carbon monoxide poisoning (DEACMP). Methods Total 265 patients with ACOP diagnosed and treated in Harrison International Peace Hospital of Hebei Medical University, The Second People's Hospital of Hengshui and The No.4 People's Hospital of Hengshui from March 2020 to March 2023 were included. SIRI and serum Lp-PLA2 levels were measured. According to the occurrence of DEACMP, they were divided into DEACMP group (n = 32) and non -DEACMP group (n = 233), while according to the degree of poisoning, they were divided into mild poisoning group (n = 20), moderate poisoning group (n = 107) and severe poisoning group (n = 138). Univariate and multivariate Logistic regression analyses were used to screen the risk factors of DEACMP in patients with ACOP, and the receiver operating characteristic (ROC) curve was drawn to evaluate the predictive efficacy of SIRI, Lp - PLA2 and their combination for DEACMP. Results The levels of SIRI (t = 13.068, P = 0.000) and serum Lp-PLA2 (t = 8.208, P = 0.000) in DEACMP group were higher than those in non-DEACMP group, and their levels gradually increased with the severity of poisoning, the levels of SIRI (t = 8.764, P = 0.000; t = 4.586, P = 0.000) and Lp-PLA2 (t = 3.726, P = 0.000; t = 2.038, P = 0.044) in the severe poisoning group and moderate poisoning group were higher than those in the mild poisoning group, and the levels of SIRI and serum Lp-PLA2 in the severe poisoning group were also higher than those in the moderate poisoning group (t = 10.294, P = 0.000; t = 2.700, P = 0.007). Logistic regression analysis showed the severe poisoning (OR = 11.695, 95%CI: 4.893-39.994; P = 0.000), SIRI increased (OR = 1.600, 95%CI: 1.033-2.476; P = 0.001) and Lp - PLA2 increased (OR = 11.302, 95%CI: 1.486-38.933; P = 0.000) were risk factors of DEACMP in patients with ACOP. ROC curve showed that area under the curve (AUC) predicted by Lp-PLA2, SIRI and their combination were 0.82 (95%CI: 0.754-0.894, P = 0.000), 0.82 (95%CI: 0.739-0.895, P = 0.000) and 0.87 (95%CI: 0.805-0.934, P = 0.000), sensitivity were 0.66, 0.72 and 0.84, specificity were 0.85, 0.88 and 0.90, respectively. The prediction efficiency of Lp-PLA2 combined with SIRI was better than that of Lp- PLA2 (t = 2.198, P = 0.027) or SIRI (t = 2.268, P = 0.023) alone. Conclusions DEACMP is easy to occur when SIRI and serum Lp-PLA2 were high in patients with ACOP. The combined detection of Lp-PLA2 and SIRI can be used for early screening of DEACMP.

Harmonics and three-phase imbalance are two common disturbances in power systems that interact with and affect each other, leading to more complex impacts on power system performance. To comprehensively and accurately analyze the distribution and interaction mechanisms of harmonics and three-phase imbalance, this study investigated the joint emission level of harmonic and three-phase unbalanced disturbance sources (H-TU-DS). This paper proposes a joint probabilistic emission level modeling approach. The power, harmonic, and three-phase unbalanced data of H-TU-DS are multidimensional, and the feature dataset is filtered by calculating multiple correlation coefficients to achieve dimensionality reduction without losing data information. Considering the different operating characteristics of the H-TU-DS, an improved fuzzy C-means (FCM) algorithm is applied to classify operating conditions, enabling a comprehensive and accurate analysis of the joint emission level. Based on the nonparametric kernel density function, joint probability modeling of H-TU-DS is performed using an adaptive bandwidth improvement method, effectively enhancing the accuracy of the modeling process. Finally, the effectiveness and accuracy of the proposed methods for feature dataset filtering, operating condition classification, and joint probability modeling are demonstrated through comparisons with both simulated and actual data. The proposed model facilitates the prediction and assessment of the impact of H-TU-DS on power quality after grid connection, enabling the effective prevention of power-quality problems through advanced treatment.

BackgroundThe relationship of systolic blood pressure variability (SBPV) with Alzheimer’s disease (AD) remains controversial. We aimed to explore the roles of SBPV in predicting AD incidence and to test the pathways that mediated the relationship of SBPV with cognitive functions.MethodsLongitudinal data across 96 months (T0 to T4) were derived from the Alzheimer’s disease Neuroimaging Initiative cohort. SBPV for each participant was calculated based on the four measurements of SBP across 24 months (T0 to T3). At T3, logistic regression models were used to test the SBPV difference between 86 new-onset AD and 743 controls. Linear regression models were used to test the associations of SBPV with cognition and AD imaging endophenotypes for 743 non-demented participants (median age = 77.0, female = 42%). Causal mediation analyses were conducted to explore the effects of imaging endophenotypes in mediating the relationships of SBPV with cognitive function. Finally, Cox proportional hazard model was utilized to explore the association of SBPV with incident risk of AD (T3 to T4, mean follow-up = 3.5 years).ResultsParticipants with new-onset AD at T3 had significantly higher SBPV compared to their controls (p = 0.018). Higher SBPV was associated with lower scores of cognitive function (p = 0.005 for general cognition, p = 0.029 for memory, and p = 0.016 for executive function), higher cerebral burden of amyloid deposition by AV45 PET (p = 0.044), lower brain metabolism by FDG PET (p = 0.052), and higher burden of white matter hyperintensities (WMH) (p = 0.012). Amyloid pathology, brain metabolism, and WMH partially (ranging from 17.44% to 36.10%) mediated the associations of SBPV with cognition. Higher SBPV was significantly associated with elevated risk of developing AD (hazard ratio = 1.29, 95% confidence interval = 1.07 to 1.57, p = 0.008).ConclusionThese findings supported that maintaining stable SBP in late life helped lower the risk of AD, partially by modulating amyloid pathology, cerebral metabolism, and cerebrovascular health.

Abstract The large uncertainties in estimating CH4 emissions from wetland ecosystems, the leading natural source to the atmosphere, substantially hinder the quantification of the global CH4 budget. This study used the IBIS‐CH4 (Integrated BIosphere Simulator‐Methane) model, a process‐based model integrating microbial mechanisms associated with CH4 production and oxidation processes, to simulate global wetland CH4 emissions from 2001 to 2020. Initially, we employed the IBIS‐CH4 model to evaluate its performance across 26 diverse wetland sites worldwide. The results showed that the magnitude and seasonality of observed CH4 fluxes over various wetland sites were well reproduced. We then used this model to estimate the annual global wetland CH4 emissions from 2001 to 2020, averaging 152.67 Tg CH4 yr−1, with a range of 135.72–167.57 Tg CH4 yr−1. The estimated global wetland CH4 emissions are generally in agreement with the current bottom‐up estimates (117–256 Tg CH4 yr−1) and closely overlap with independent top‐down estimates (139–183 Tg CH4 yr−1). During 2001–2020, the estimated global wetland CH4 emissions initially showed an increasing trend, followed by a decline. The peak of CH4 emissions reached in 2010, coinciding with the peak of wetland area. The majority of global wetland CH4 emissions were concentrated in tropical regions, which exhibited a clear seasonality and had a peak in July. The impact of meteorological factors on wetland CH4 emissions was greater than that of leaf area index, indicating the importance of soil hydrothermal conditions on wetland CH4 emissions.