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Personal care products (PCPs) are a class of emerging pollutants that have attracted public concern owing to their harmful effects on humans and the environment. Biomonitoring data is valuable for insight the levels of PCPs in the human body and can be crucial for identifying potential health hazards. To gain a better understanding of timely exposure profiles and health risk of reproductive-age population to PCPs, we determined six parabens, six benzophenone-type ultraviolet filters, and three disinfectants in 256 urine samples collected from young adults aged 18-44 years in Beijing, China. The urinary levels of benzophenone-3 (BP-3) and 4-hydroxybenzophenone (4-OHBP) were significantly higher in summer compared to winter, suggesting these compounds have different seasonal usage patterns. Moreover, the total concentration of 15 PCPs in female was 430 ng/mL, approximately two times higher than that in male. P­chloro-m-xylenol (PCMX), as a new type of antibacterial agent, has the greatest level among all target analytes, indicating the increasingly use of this antibacterial alternative recently. Five potential influencing factors that lead to the elevated exposure level of PCPs were identified. Over 19% of the target population had a high hazard index value (greater than 1) which was attributed to exposure to propyl paraben (PrP), benzophenone-1 (BP-1), BP-3 and PCMX, indicating that PCPs may pose a relatively high exposure risk at environmental levels that should be a cause for concern.

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Single-cell technology depicts integrated tumor profiles including both tumor cells and tumor microenvironments, which theoretically enables more robust diagnosis than traditional diagnostic standards based on only pathology. However, the inherent challenges of single-cell RNA sequencing (scRNA-seq) data, such as high dimensionality, low signal-to-noise ratio (SNR), sparse and non-Euclidean nature, pose significant obstacles for traditional diagnostic approaches. The diagnostic value of single-cell technology has been largely unexplored despite the potential advantages. Here, we present a graph neural network-based framework tailored for molecular diagnosis of primary liver tumors using scRNA-seq data. Our approach capitalizes on the biological plausibility inherent in the intercellular communication networks within tumor samples. By integrating pathway activation features within cell clusters and modeling unidirectional inter-cellular communication, we achieve robust discrimination between malignant tumors (including hepatocellular carcinoma, HCC, and intrahepatic cholangiocarcinoma, iCCA) and benign tumors (focal nodular hyperplasia, FNH) by scRNA data of all tissue cells and immunocytes only. The efficacy to distinguish iCCA from HCC was further validated on public datasets. Through extending the application of high-throughput scRNA-seq data into diagnosis approaches focusing on integrated tumor microenvironment profiles rather than a few tumor markers, this framework also sheds light on minimal-invasive diagnostic methods based on migrating/circulating immunocytes.

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In the rat, the activity of laryngeal adductor muscles, the crural diaphragm, and sympathetic vasomotor neurons is entrained to the post-inspiratory (post-I) phase of the respiratory cycle, a mechanism thought to enhance cardiorespiratory efficiency. The identity of the central neurons responsible for transmitting respiratory activity to these outputs remains unresolved. Here we explore the contribution of the Kölliker-Fuse/Parabrachial nuclei (KF-PBN) in the generation of post-I activity in vagal and sympathetic outputs under steady-state conditions and during acute hypoxemia, a condition that potently recruits post-I activity. In artificially ventilated, vagotomised and urethane-anesthetised rats, bilateral KF-PBN inhibition by microinjection of the GABAA receptor agonist isoguvacine evoked stereotypical responses on respiratory pattern, characterised by a reduction in phrenic nerve burst amplitude, a modest lengthening of inspiratory time, and an increase in breath-to-breath variability, while post-I vagal nerve activity was abolished and post-I sympathetic nerve activity diminished. During acute hypoxemia, KF-PBN inhibition attenuated tachypnoeic responses and completely abolished post-I vagal activity while preserving respiratory-sympathetic coupling. Furthermore, KF-PBN inhibition disrupted the decline in respiratory frequency that normally follows resumption of oxygenation. These findings suggest that the KF-PBN is a critical hub for the distribution of post-I activities to vagal and sympathetic outputs and is an important contributor to the dynamic adjustments to respiratory patterns that occur in response to acute hypoxia. While KF-PBN appears essential for post-I vagal activity, it only partially contributes to post-I sympathetic nerve activity, suggesting the contribution of multiple neural pathways to respiratory-sympathetic coupling.

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We present a 60-year-old maintenance hemodialysis patient who initially presented with neck swelling, which was diagnosed as a thyroid issue. Following a hemodialysis session, the swelling in the neck progressively enlarged, leading to respiratory distress and eventual cardiac arrest. During a life-saving tracheotomy, dark red blood was observed, and endotracheal intubation was urgently performed. Subsequent computed tomography examination identified multiple areas of slight high-density images in the nasopharyngeal cavity, oropharyngeal cavity, and esophagus. As time passed, the patient's hematoma underwent spontaneous absorption, but signs of recovery were absent. We discuss the rarity, etiology, diagnosis, and management of spontaneous neck hematoma in maintenance hemodialysis patients.

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BACKGROUND AND AIMS: Erythritol, a sugar alcohol (polyol), has recently been linked to the risks of major adverse cardiovascular events. We investigated whether plasma erythritol and other polyols (mannitol/sorbitol) were associated with the risk of incident coronary heart disease (CHD). METHODS: This prospective nested case-control study included 762 incident cases of CHD and 762 controls from the Nurses' Health Study. Plasma concentrations of polyols were measured at baseline (1989-90 or 2000-02). Associations of erythritol with cardiometabolic risk factors were also analyzed in the Women's Lifestyle Validation Study (n=728; blood collected in 2010-12). RESULTS: Higher erythritol levels were related to more adverse cardiometabolic risk factor status. The relative risk (RR) for CHD per 1-SD increment was 1.15 [95% CI: 1.04, 1.28] for erythritol and 1.16 [1.05, 1.28] for mannitol/sorbitol, after adjusting for diet quality, lifestyles, and adiposity. Compared with women in the lowest quartile, those in the highest quartile (Q4) of erythritol had a RR 1.55 [1.13, 2.14] for CHD. The RR in Q4 of erythritol was 1.61 [1.15, 2.24; p=0.006] when hypertension and dyslipidemia were further added to the model; the RR was 1.21 [0.86, 1.70] after adjustment for diabetes. For mannitol/sorbitol, the RR in the Q4 was 1.42 [1.05, 1.91; p=0.022] for CHD in the multivariable-adjusted model including diabetes. CONCLUSIONS: Higher plasma erythritol and mannitol/sorbitol were related to elevated risks of CHD even after adjustment for diet, lifestyles, adiposity, and other risk factors. The unfavorable association of mannitol/sorbitol, but not erythritol, with CHD risk remained significant independently of diabetes/hyperglycemia.

The present study shows unfavorable associations of circulating erythritol and mannitol/sorbitol with long-term coronary heart disease (CHD) risk even after adjustments for overall diet quality, lifestyle factors, and several other traditional CHD risk factors among women at usual risk. In contrast to mannitol/sorbitol, the association between high erythritol levels and increased CHD risk was no longer significant upon additional inclusion of diabetes in the multivariable-adjusted model. Our findings from the two independent study populations of women without prior CHD suggest endogenous and exogenous erythritol levels are related to unfavorable cardiometabolic risk factor status.

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Virtual/augmented reality (VR/AR) devices offer both immersive imagery and sound. With those wide-field cues, we can simultaneously acquire and process visual and auditory signals to quickly identify objects, make decisions, and take action. While vision often takes precedence in perception, our visual sensitivity degrades in the periphery. In contrast, auditory sensitivity can exhibit an opposite trend due to the elevated interaural time difference. What occurs when these senses are simultaneously integrated, as is common in VR applications such as 360° video watching and immersive gaming? We present a computational and probabilistic model to predict VR users' reaction latency to visual-auditory multisensory targets. To this aim, we first conducted a psychophysical experiment in VR to measure the reaction latency by tracking the onset of eye movements. Experiments with numerical metrics and user studies with naturalistic scenarios showcase the model's accuracy and generalizability. Lastly, we discuss the potential applications, such as measuring the sufficiency of target appearance duration in immersive video playback, and suggesting the optimal spatial layouts for AR interface design.

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The concept of an intelligent augmented reality (AR) assistant has significant, wide-ranging applications, with potential uses in medicine, military, and mechanics domains. Such an assistant must be able to perceive the environment and actions, reason about the environment state in relation to a given task, and seamlessly interact with the task performer. These interactions typically involve an AR headset equipped with sensors which capture video, audio, and haptic feedback. Previous works have sought to facilitate the development of intelligent AR assistants by visualizing these sensor data streams in conjunction with the assistant's perception and reasoning model outputs. However, existing visual analytics systems do not focus on user modeling or include biometric data, and are only capable of visualizing a single task session for a single performer at a time. Moreover, they typically assume a task involves linear progression from one step to the next. We propose a visual analytics system that allows users to compare performance during multiple task sessions, focusing on non-linear tasks where different step sequences can lead to success. In particular, we design visualizations for understanding user behavior through functional near-infrared spectroscopy (fNIRS) data as a proxy for perception, attention, and memory as well as corresponding motion data (acceleration, angular velocity, and gaze). We distill these insights into embedding representations that allow users to easily select groups of sessions with similar behaviors. We provide two case studies that demonstrate how to use these visualizations to gain insights about task performance using data collected during helicopter copilot training tasks. Finally, we evaluate our approach by conducting an in-depth examination of a think-aloud experiment with five domain experts.

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Objective: Hypertension (HTN) is a prevalent global health concern. From the standpoint of preventive and personalized medicine (PPPM/3PM), early detection of HTN offers a crucial opportunity for targeted prevention and personalized treatment. This study aimed to evaluate the association between the weight-adjusted waist index (WWI) and HTN risk. Methods: A case-control study using data from the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018 was conducted. Logistic regression models assessed the association between WWI and HTN. Subgroup analyses explored differences in age, sex, ethnicity, and diabetes status. Restricted cubic spline (RCS) analyses examined potential nonlinear relationships. Results: A total of 32,116 participants, with an average age of 49.28 ± 17.56 years, were included in the study. A significant positive association between WWI and the risk of HTN was identified (odds ratio [OR], 2.49; 95% CI, 2.39-2.59; P < 0.001). When WWI was categorized into quartiles (Q1-Q4), the highest quartile (Q4) exhibited a stronger association compared to Q1 (OR, 2.94; 95% CI, 2.65-3.27; P < 0.001). Subgroup analyses indicated that WWI was a risk factor for HTN across different populations, although variations in the magnitude of effect were observed. Furthermore, the findings from the RCS elucidated a nonlinear positive correlation between WWI and HTN. Conclusion: WWI is independently associated with HTN risk, highlighting its potential as a risk assessment tool in clinical practice. Incorporating WWI into early detection strategies enhances targeted prevention and personalized management of HTN. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-024-00375-3.

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Background: Seed hypocotyl germination signifies the initiation of the life cycle for plants and represents a critical stage that heavily influences subsequent plant growth and development. While previous studies have established the melatonin (MEL; N-acetyl-5-methoxytrytamine) effect to stimulate seed germination of some plants, its specific role in peony germination and underlying physiological mechanism have yet to be determined. This study aims to evaluate the MEL effect for the hypocotyl germination of peony seeds, further ascertain its physiological regulation factors. Methods: In this work, seeds of Paeonia ostia 'Fengdan' were soaked into MEL solution at concentrations of 50, 100, 200, and 400 µM for 48 h and then germinated in darkness in incubators. Seeds immersed in distilled water without MEL for the same time were served as the control group. Results: At concentrations of 100 and 200 µM, MEL treatments improved the rooting rate of peony seeds, while 400 µM inhibited the process. During seed germination, the 100 and 200 µM MEL treatments significantly reduced the starch concentration, and α-amylase was the primary amylase involved in the action of melatonin. Additionally, compared to the control group, 100 µM MEL treatment significantly increased the GA3 concentration and radicle thickness of seeds, but decreased ABA concentration. The promotion effect of 200 µM MEL pretreatment on GA1 and GA7 was the most pronounced, while GA4 concentration was most significantly impacted by 50 µM and 100 µM MEL. Conclusion: Correlation analysis established that 100 µM MEL pretreatment most effectively improved the rooting rate characterized by increasing α-amylase activity to facilitate starch decomposition, boosting GA3 levels, inhibiting ABA production to increase the relative ratio of GA3 to ABA. Moreover, MEL increased radicle thickness of peony seeds correlating with promoting starch decomposition and enhancing the synthesis of GA1 and GA7.

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N6-Methyladenosine (m6A) is the most prevalent mRNA modification. Its biological function primarily relies on its "Reader" protein, such as YTHDC2. Previous studies have shown that YTHDC2 downregulation is a pro-carcinogenic phenomenon in lung adenocarcinoma (LUAD). However, further investigation is needed to understand the molecular mechanisms of downstream genes and the associated biological phenomena following YTHDC2 downregulation. Here, we found that YTHDC2 knockout upregulated exosome content in LUAD. Following YTHDC2 knockout, the mRNA levels of OAS family members (OASs) and IFIT family members (IFITs) also decreased; and inhibition of OASs and IFITs could promote exosome content. Several m6A modification sites on the NT domain of OASs and the TPR12 domain of IFITs were found to increase the stability of OASs and IFITs in a YTHDC2-dependent manner. OASs and IFITs affected exosome content through target genes including RAB5A, RAB7 and RAB11A, and three arginine (R) amino acids on IFITs were critical for combination IFITs with targeted RAB mRNAs and subsequent degradation. Simultaneously, OASs degraded targeted RABs through RNAseL. Additionally, mutual bindings between OASs and IFITs were critical for their target gene degradation. Collectively, the above findings might provide a theoretical basis for the treatment of LUAD patients with low YTHDC2 expression.

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Background: Phosphorylation is a critical post-translational modification (PTM) type contributing to colorectal cancer (CRC). The study aimed to construct a nomogram model to predict colon adenocarcinoma (COAD) prognosis based on PTM signatures. Methods: The Cancer Genome Atlas (TCGA) database has been indexed for COAD patients' RNA sequencing, proteomic data, and clinical details. To find potential PTM prognostic signatures, the least absolute shrinkage and selection operator (LASSO) was deployed. Model validation procedures included the use of the Kaplan-Meier (K-M) method, the receiver operating characteristic (ROC) curve, the area under the curve (AUC), and the decision curve analysis (DCA). Additionally, biological enrichment, tumor immune microenvironment, and chemotherapy were also assessed. To validate the model, CRC cells were used in in vitro experiments using western blotting, proliferation assay, colony formation assay, and flow cytometry. Results: The LASSO regression analysis identified 8 PTM sites. Based on the median PTM score, patients were classified into low- and high-risk groups. K-M results showed that high-risk patients had worse prognoses (P<0.001). Our model demonstrated powerful effectiveness and predictive value (TCGA whole group: 1-year AUC =0.611, 2-year AUC =0.574, 3-year AUC =0.627). Additionally, high-risk CRC patients were enriched in KRAS signaling pathways (P=0.01), possessed more robust immune escape capacity (P=0.001, and induced cell-cycle arrest of CRC cells (P<0.01). Conclusions: We established and validated a novel nomogram model related to PTM that can predict prognosis and guide the treatment of COAD.

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This study evaluates the impact of environmentally relevant, low-concentration deltamethrin exposure to Eriocheir sinensis ovaries. Our findings revealed that even at a concentration of 0.05 µg/L, deltamethrin exposure can induce significant ovarian toxicity through a 5-day exposure, with gradual amplification detected with time, demonstrating the toxicity amplification effect. Hematoxylin and Eosin staining revealed that low-concentration deltamethrin exposure produces pathological damage consistent with acute toxicity-yolk granules were dissolved and oocyte membranes were ruptured. High-throughput RNA-sequencing data indicated that the acute and low-concentration exposure groups involved completely different pathways and molecular functions, suggesting distinct mechanisms for their toxic effects. Following the identification of phospholipase D (PLD) as a potential core factor regulating the toxicity amplification effect of low concentration deltamethrin, we delved into subsequent mechanism studies using quantitative real-time PCR, immunofluorescence and enzyme-linked immunosorbent assay. Through the GnRH signaling pathway, increased PLD indirectly stimulates augmented estradiol secretion, subsequently inducing apoptosis by upregulating Cathepsin D, which can activate the key executioners of apoptosis-caspases (CASP3 and CASP7). In conclusion, low-concentration deltamethrin exposures can induce significant ovarian damage through apoptosis mediated by the upregulation of PLD in the ovaries of Eriocheir sinensis at environmentally relevant concentrations, which lays the preliminary theoretical groundwork for further elucidating the mechanism of toxicity amplification effect of pesticide exposure at low concentrations.

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It has been demonstrated that observers can accurately estimate their self-motion direction (i.e., heading) from optic flow, which can be affected by attention. However, it remains unclear how attention affects the serial dependence in the estimation. In the current study, participants conducted two experiments. The results showed that the estimation accuracy decreased when attentional resources allocated to the heading estimation task were reduced. Additionally, the estimates of currently presented headings were biased toward the headings of previously seen headings, showing serial dependence. Especially, this effect decreased (increased) when the attentional resources allocated to the previously (currently) seen headings were reduced. Furthermore, importantly, we developed a Bayesian inference model, which incorporated attention-modulated likelihoods and qualitatively predicted changes in the estimation accuracy and serial dependence. In summary, the current study shows that attention affects the serial dependence in heading estimation from optic flow and reveals the Bayesian computational mechanism behind the heading estimation.

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Although total carbon (TC) is an important component of fine particulate matter (PM2.5: particulate matter with aerodynamic diameter of <2.5 µm); its sources remain partially unidentified, especially in coastal urban areas. With ongoing development of the global economy and maritime activities, ship-generated TC emissions in port areas cannot be neglected. In this study, from September 11, 2017 to August 31, 2018, we collected 355 p.m.2.5 samples in Qingdao, China, to determine the water-soluble ion concentrations, TC concentrations, and stable carbon isotopes (δ13CTC). During the open fishing season (OFS; September 11, 2017 to April 30, 2018) and the closed fishing season (CFS; May 1, 2018 to August 31, 2018), the TC concentrations were 9.30 ± 5.38 µg/m3 and 3.36 ± 2.10 µg/m3 respectively, and the corresponding δ13CTC values were -24.53‰ ± 1.17‰ and -27.03‰ ± 0.91‰, respectively, indicating significant differences (p < 0.05) between the two periods. The differences in TC concentrations and the δ13CTC values between the OFS and CFS reflect changes in the source of contamination. Bayesian model was used to quantify the contributions of different TC sources, revealing that ship emissions accounted for approximately 35.3% of the total, which was close to the contribution from the largest source, i.e., motor vehicles (39%). Using the ship emission inventory, Qingdao's ship emissions were further quantified at 455 metric tons, representing 35%-40% of the total TC emissions around Qingdao. Notably, fishing ships contributed approximately 40% of the total ship emissions. These findings underscore the considerable impact of ship emissions, particularly those from fishing ships, on TC concentrations in coastal urban areas.

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Ferroptosis, as a unique form of cell death caused by iron overload and lipid peroxidation, is involved in the pathogenesis of various inflammatory diseases of the airways. Inhibition of ferroptosis has become a novel strategy for reducing airway epithelial cell death and improving airway inflammation. The aim of the present study was to analyze and validate the key genes and signaling pathways associated with ferroptosis by bioinformatic methods combined with experimental analyzes in vitro and in vivo to aid the diagnosis and treatment of neutrophilic asthma. A total of 1,639 differentially expressed genes (DEGs) were identified in the transcriptome dataset. After overlapping with ferroptosis-related genes, 11 differentially expressed ferroptosis-related genes (DE-FRGs) were obtained. A new diagnostic model was constructed by these DE-FRGs from the transcriptome dataset with those from the GSE108417 dataset. The receiver operating characteristic curve analysis indicated that the area under the curve had good diagnostic performance (>0.8). As a result, four key DE-FRGs (CXCL2, HMOX1, IL-6 and SLC7A5) and biological pathway [hypoxia-inducible factor 1 (HIF-1) signaling pathway] associated with ferroptosis in neutrophilic asthma were identified by the bioinformatics analysis combined with experimental validation. The upstream regulatory network of key DE-FRGs and target drugs were predicted and the molecular docking results from screened 37 potential therapeutic drugs revealed that the 13 small-molecule drugs exhibited a higher stable binding to the primary proteins of key DE-FRGs. The results suggested that four key DE-FRGs and the HIF-1α/heme oxygenase 1 pathway associated with ferroptosis have potential as novel markers or targets for the diagnosis or treatment of neutrophilic asthma.

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Advancing membranes with enhanced solute-solute selectivity is essential for expanding membrane technology applications, yet it presents a notable challenge. Drawing inspiration from the unparalleled selectivity of biological systems, which benefit from the sophisticated spatial organization of functionalities, we posit that manipulating the arrangement of the membrane's building blocks, an aspect previously given limited attention, can address this challenge. We demonstrate that optimizing the face-to-face orientation of building blocks during the assembly of covalent-organic-framework (COF) membranes improves ion-π interactions with multivalent ions. This optimization leads to extraordinary selectivity in differentiating between monovalent cations and anions from their multivalent counterparts, achieving selectivity factors of 214 for K+/Al3+ and 451 for NO3-/PO43-. Leveraging this attribute, the COF membrane facilitates the direct extraction of NaCl from seawater with a purity of 99.57%. These findings offer an alternative approach for designing highly selective membrane materials, offering promising prospects for advancing membrane-based technologies.

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Kidney fibrosis marks a critical phase in chronic kidney disease with its molecular intricacies yet to be fully understood. This study's deep dive into single-cell sequencing data of renal tissue during fibrosis pinpoints the pivotal role of fibroblasts and myofibroblasts in the fibrotic transformation. Through identifying distinct cell populations and conducting transcriptomic analysis, Spp1 emerged as a key gene associated with renal fibrosis. The study's experimental findings further confirm Spp1's vital function in promoting fibroblast to myofibroblast differentiation via the TGF-ß/Smad signaling pathway, underscoring its contribution to fibrosis progression. The suppression of Spp1 expression notably hindered this differentiation process, spotlighting Spp1 as a promising therapeutic target for halting renal fibrosis. This condensed summary encapsulates the essence and findings of the original research within the specified word limit.

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Despite the synthesis of numerous cationic metal-organic frameworks (CMOFs), their counter anions have been primarily limited to inorganic Cl-, NO3 -, ClO4 -, BF4 -, and Cr2O7 2-, which have weak coordination abilities. In this study, a series of new CMOFs is synthesized using azolates with strong coordination abilities as counter anions, which are exclusively employed as ligands for coordinating with metals. Owing to the unique nitrogen-rich composition of azolates, the CMOFs demonstrate significant potential as high-energy-density materials. Notably, CMOF(CuTNPO) has an exceptionally high heat of detonation of 7375 kJ kg-1, surpassing even that of the state-of-art CL-20 (6536 kJ kg-1). To further validate the advantages of employing azolates as counter anions, analogues with azolates serving as ligands are also synthesized. The comparison study indicates that encapsulating azolates within the cationic frameworks confers both high energy and safety properties. X-ray data and quantum calculations indicate that their enhanced performance stems from stronger H─bonds and π-π interactions. This study introduces new roles for azolates in MOFs and expands possibilities for structural diversity and potential applications of framework materials.

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Solvent system selection based on polarity is a common strategy in a countercurrent chromatography (CCC) analysis. However, the solvent selectivity of solvent system is often ignored, despite its significant impact on the separation efficiency of CCC. In this study, the role of solvent in the overall properties of solvent system and the selective classification of solvent system were discussed to improve the solvent system selection based on polarity. Firstly, the mathematical relationship between logarithm of the partition coefficient (log K) of the template molecule and solvent composition of n-hexane/ethyl acetate/alcohol solvents (methanol, ethanol, and isopropanol)/water (HEAwat) system was analyzed and the optimal solvent system (K = 1) of the template molecules was determined. Then, the actual methanol concentration at the column inlet when the analyte peak in a HPLC analysis (B%) and the clustering results of the average polarity (P') of the optimal CCC solvent system were analyzed. Finally, the classification of HEAWat system in terms of its overall solvent properties by deducing equations of selectivity parameters (χe, χd, and χn) to explain the P' values clustering results. The results showed that HEAWat system was suitable for the separation of analytes with 55 % < B% < 100 %. However, the n-hexane/ethyl acetate/isopropanol/water (HEIWat) system proved more suitable for the separation of large polar compounds to other HEAWat system when the P' value decreased due to the change of alcohol solvents. The selected solvent systems were classified into group III and IV by Snyder's method. The solvent systems in group III were suitable for the separation of analytes with 85 % < B% < 100 %, and the distribution behavior of analytes was mainly influenced by the ratio of each solvent. The solvent systems in group IV were suitable for the separation of analytes with 55 % < B% < 85 %, and the distribution behavior of analytes was mainly influenced by the type of alcohol solvents.