Cross-Linking CdSO4-Type Nets with Hexafluorosilicate Anions to Form an Ultramicroporous Material for Efficient C2H2/CO2 and C2H2/C2H4 Separation.

A 44.610.8 topology hybrid ultramicroporous material (HUM), {[Cu1.5F(SiF6)(L)2.5]·G}n, (L = 4,4'-bisimidazolylbiphenyl, G = guest molecules), 1, formed by cross-linking interpenetrated 3D four-connected CdSO4-type nets with hexafluorosilicate anions is synthesized and evaluated in the context of gas sorption and separation herein. 1 is the first HUM functionalized with two different types of fluorinated sites (SiF6 2- and F- anions) lining along the pore surface. The optimal pore size (≈5 Å) combining mixed and high-density electronegative fluorinated sites enable 1 to preferentially adsorb C2H2 over CO2 and C2H4 by hydrogen bonding interactions with a high C2H2 isosteric heat of adsorption (Qst) of ≈42.3 kJ mol-1 at zero loading. The pronounced discriminatory sorption behaviors lead to excellent separation performance for C2H2/CO2 and C2H2/C2H4 that surpasses many well-known sorbents. Dynamic breakthrough experiments are conducted to confirm the practical separation capability of 1, which reveal an impressive separation factor of 6.1 for equimolar C2H2/CO2 mixture. Furthermore, molecular simulation and density functional theory (DFT) calculations validate the strong binding of C2H2 stems from the chelating fix of C2H2 between SiF6 2- anion and coordinated F- anion.

In-depth organic mass cytometry reveals differential contents of 3-hydroxybutanoic acid at the single-cell level.

Comprehensive single-cell metabolic profiling is critical for revealing phenotypic heterogeneity and elucidating the molecular mechanisms underlying biological processes. However, single-cell metabolomics remains challenging because of the limited metabolite coverage and inability to discriminate isomers. Herein, we establish a single-cell metabolomics platform for in-depth organic mass cytometry. Extended single-cell analysis time guarantees sufficient MS/MS acquisition for metabolite identification and the isomers discrimination while online sampling ensures the high-throughput of the method. The largest number of identified metabolites (approximately 600) are achieved in single cells and fine subtyping of MCF-7 cells is first demonstrated by an investigation on the differential levels of 3-hydroxybutanoic acid among clusters. Single-cell transcriptome analysis reveals differences in the expression of 3-hydroxybutanoic acid downstream antioxidative stress genes, such as metallothionein 2 (MT2A), while a fluorescence-activated cell sorting assay confirms the positive relationship between 3-hydroxybutanoic acid and target proteins; these results suggest that the heterogeneity of 3-hydroxybutanoic acid provides cancer cells with different ability to resist surrounding oxidative stress. Our method paves the way for deep single-cell metabolome profiling and investigations on the physiological and pathological processes that occur during cancer.

D-arabinose induces cell cycle arrest by promoting autophagy via p38 MAPK signaling pathway in breast cancer.

Breast cancer patients often have a poor prognosis largely due to lack of effective targeted therapy. It is now well established that monosaccharide enhances growth retardation and chemotherapy sensitivity in tumor cells. We investigated whether D-arabinose has capability to restrict the proliferation of tumor cells and its mechanism. Here, we report that D-arabinose induced cytotoxicity is modulated by autophagy and p38 MAPK signaling pathway in breast cancer cell lines. The proliferation of cells was evaluated by CCK-8 and Colony formation assay. The distribution of cells in cell cycle phases was analyzed by flow cytometry. Cell cycle, autophagy and MAPK signaling related proteins were detected by western blotting. Mouse xenograft model was used to evaluate the efficacy of D-arabinose in vivo. The proliferation of cells was dramatically inhibited by D-arabinose exposure in a dose-dependent manner, which was relevant to cell cycle arrest, as demonstrated by G2/M cell cycle restriction and ectopic expression of cell cycle related proteins. Mechanistically, we further identified that D-arabinose is positively associated with autophagy and the activation of the p38 MAPK signaling in breast cancer. In contrast, 3-Ma or SB203580, the inhibitor of autophagy or p38 MAPK, reversed the efficacy of D-arabinose. Additionally, D-arabinose in vivo treatment could significantly inhibit xenograft growth of breast cancer cells. Our findings were the first to reveal that D-arabinose triggered cell cycle arrest by inducing autophagy through the activation of p38 MAPK signaling pathway in breast cancer cells.

Pharmacological inhibition of the ACE/Ang-2/AT1 axis alleviates mechanical ventilation-induced pulmonary fibrosis.

Mechanical ventilation (MV) is an essential therapy for acute respiratory distress syndrome (ARDS) and pulmonary fibrosis. However, it can also induce mechanical ventilation-induced pulmonary fibrosis (MVPF) and the underlying mechanism remains unknown. Based on a mouse model of MVPF, the present study aimed to explore the role of the angiotensin-converting enzyme/angiotensin II/angiotensin type 1 receptor (ACE/Ang-2/AT1R) axis in the process of MVPF. In addition, recombinant angiotensin-converting enzyme 2(rACE2), AT1R inhibitor valsartan, AGTR1-directed shRNA and ACE inhibitor perindopril were applied to verify the effect of inhibiting ACE/Ang-2/AT1R axis in the treatment of MVPF. Our study found MV induced an inflammatory reaction and collagen deposition in mouse lung tissue accompanied by the activation of ACE in lung tissue, increased concentration of Ang-2 in bronchoalveolar lavage fluid (BALF), and upregulation of AT1R in alveolar epithelial cells. The process of pulmonary fibrosis could be alleviated by the application of the ACE inhibitor perindopril, ATIR inhibitor valsartan and AGTR1-directed shRNA. Meanwhile, rACE2 could also alleviate MVPF through the degradation of Ang-2. Our finding indicated the ACE/Ang-2/AT1R axis played an essential role in the pathogenesis of MVPF. Pharmacological inhibition of the ACE/Ang-2/AT1R axis might be a promising strategy for the treatment of MVPF.

Fibrotic extracellular vesicles contribute to mechanical ventilation-induced pulmonary fibrosis development by activating lung fibroblasts via JNK signalling pathway: an experimental study.

Recent research has revealed that mechanical ventilation (MV) could initiate ventilator-induced lung injury along with the initiation of the process of pulmonary fibrosis (PF), leading to MV-induced PF (MVPF). However, the underlying mechanism remains unclear. This study aimed to explore the role of MV-induced extracellular vesicles (MV-EVs) and the c-Jun N-terminal kinase (JNK) signalling pathway in the pathogenesis of MVPF in vivo and in vitro. The process of MV is accompanied by the secretion of MV-EVs, which could induce lung fibroblast activation. Furthermore, single-cell RNA-sequencing analysis revealed that the JNK pathway in lung fibroblasts was activated after MV initiation. Inhibiting the JNK pathway could both restrain MV-EV-induced lung fibroblast activation in vitro or reduce the severity of MVPF in vivo. In conclusion, this study demonstrated that MV-EVs contribute to MVPF progression by activating lung fibroblasts via the JNK signalling pathway and that inhibiting the secretion of EV and the activation of the JNK signalling pathway is a promising strategy for treating MVPF.

A deep learning model for predicting COVID-19 ARDS in critically ill patients.

Background: The coronavirus disease 2019 (COVID-19) is an acute infectious pneumonia caused by a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection previously unknown to humans. However, predictive studies of acute respiratory distress syndrome (ARDS) in patients with COVID-19 are limited. In this study, we attempted to establish predictive models to predict ARDS caused by COVID-19 via a thorough analysis of patients' clinical data and CT images. Method: The data of included patients were retrospectively collected from the intensive care unit in our hospital from April 2022 to June 2022. The primary outcome was the development of ARDS after ICU admission. We first established two individual predictive models based on extreme gradient boosting (XGBoost) and convolutional neural network (CNN), respectively; then, an integrated model was developed by combining the two individual models. The performance of all the predictive models was evaluated using the area under receiver operating characteristic curve (AUC), confusion matrix, and calibration plot. Results: A total of 103 critically ill COVID-19 patients were included in this research, of which 23 patients (22.3%) developed ARDS after admission; five predictive variables were selected and further used to establish the machine learning models, and the XGBoost model yielded the most accurate predictions with the highest AUC (0.94, 95% CI: 0.91-0.96). The AUC of the CT-based convolutional neural network predictive model and the integrated model was 0.96 (95% CI: 0.93-0.98) and 0.97 (95% CI: 0.95-0.99), respectively. Conclusion: An integrated deep learning model could be used to predict COVID-19 ARDS in critically ill patients.

Research Trends and Hotspots of Medical Electrical Impedance Tomography Algorithms: A Bibliometric Analysis From 1987 to 2021.

Electrical impedance tomography (EIT) is a gradually maturing medical imaging technique that relies on computational algorithms for reconstructing and visualizing internal conductivity distributions within the human body. To provide a comprehensive and objective understanding of the current state and trends in the EIT algorithm research, we conducted bibliometric analysis on a 25-year EIT algorithm research dataset sourced from Web of Science Core Collections. We visualized publication characteristics, collaboration patterns, keywords, and co-cited references. The results indicate a steady increase in annual publications over recent decades. The United States, United Kingdom, China, and South Korea contributed 60% of the articles collaboratively. Keyword analysis unveiled three distinct stages in the evolution of EIT algorithm research: the establishment of fundamental algorithm frameworks, optimization for improved imaging performance, and the development of algorithms for clinical applications. Additionally, there has been a shift in research focus from traditional theories to the incorporation of new methods, such as artificial intelligence. Co-cited references suggest that integrating EIT with other established imaging techniques may emerge as a new trend in EIT algorithm research. In summary, EIT algorithms have been a consistent research focus, with current efforts centered on optimizing algorithms to enhance imaging performance. The emerging research trend involves utilizing more diverse and intersecting algorithms.

Bibliometric analysis of research trends in stem cell therapy for knee osteoarthritis over the period 2001-2021.

Stem cell therapy is a promising treatment for knee osteoarthritis, but few bibliometric studies have been performed on the subject. Bibliometric analysis is helpful for identifying the most influential studies in a specific field and can evaluate the global research trends in stem cell therapy for knee osteoarthritis. The Web of Science Core Collection was searched for publications from 2001 to 2021. Publication performance was analyzed using several bibliometric parameters, including VOSviewer, to identify the research landscape of trends in topics, and CiteSpace was investigated to identify the keywords that have the strongest citation bursts. From 2001 to 2021, in total, 1,345 publications explored the research on stem cells in knee osteoarthritis. The United States contributed the largest number of publications and at the top list of international collaborations. Tokyo Medical and Dental University ranked first among institutions in the overall number of articles and citations. The journal of Osteoarthritis and Cartilage had the largest number of publications. Sekiya Ichiro was the most cited author, with 32 articles. The keywords with the most frequent occurrence were "osteoarthritis," "mesenchymal stem cells," and "cartilage," in descending order of frequency. "fibroblast growth factor" and "extracellular vesicle" were the first and last searched theme terms, respectively. The number of publications on stem cells for knee osteoarthritis stays growing. Cartilage repair and paracrine function are current research hotspots for the stem cell therapy mechanism. Stem cell therapy has gradually advanced from basic research to the clinical application stage.

Characteristics and topic trends on electrical impedance tomography hardware publications.

Objective: Electrical impedance tomography (EIT) is a technique to measure electrical properties of tissue. With the progress of modern integrated circuits and microchips, EIT instrumentation becomes an active research area to improve all aspects of device performance. Plenty of studies on EIT hardware have been presented in prestigious journals. This study explores publications on EIT hardware to identify the developing hotspots and trends. Method: Publications covering EIT hardware on the Web of Science Core Collection (WoSCC) database from 1989 to 2021 were collected for bibliometric analysis. CiteSpace and VOS viewer were used to study the characteristics of the publications. Main results: A total of 592 publications were analyzed, showing that the number of annual publications steadily increased. China, England, and South Korea were the most prolific countries on EIT hardware publications with productive native institutions and authors. Research topics spread out in "bio-electrical impedance imaging", "hardware optimization", "algorithms" and "clinical applications" (e.g., tissue, lung, brain, and oncology). Hardware research in "pulmonary" and "hemodynamic" applications focused on monitoring and were represented by silhouette recognition and dynamic imaging while research in "tumor and tissue" and "brain" applications focused on diagnosis and were represented by optimization of precision. Electrode development was a research focus through the years. Imaging precision and bioavailability of hardware optimization may be the future trend. Conclusion: Overall, system performance, particularly in the areas of system bandwidth and precision in applications may be the future directions of hardware research.

Emerging trends and hot spots on electrical impedance tomography extrapulmonary applications.

Objective: Electrical impedance tomography (EIT) develops rapidly in technology and applications. Nowadays EIT is used in multiple clinical and experimental scenarios including pulmonary, brain, and tissue monitoring, etc. The present study explores the research trends and hotspots on EIT extrapulmonary application research by bibliometrics analysis. Approach: Publications on EIT extrapulmonary applications between 1987 and 2021 were retrieved from the Web of Science Core Collection database. For precise screening, search strategy "electrical impedance tomography" plus "hemodynamic" or "brain" or "nerve" or "cancer" or "venous" or "vessel" or "tumor" or "veterinary" or "tissue" or "cell" or "wearable" or "application" and excluding "lung", "ventilation" "respiratory", "pulmonary", "algorithm", "current", "voltage" or "electrode" were used. CiteSpace and VOSviewer were used to analyze the publication features, collaboration, keywords co-occurrence, and co-cited reference. Main results: A total of 506 articles were finally identified. The global publication numbers on extrapulmonary applications gradually increased yearly in the past 30 years. The US, UK, and China contributed most three publications concerning EIT extrapulmonary applications. "tissues", "conductivity", "model" were research hotspots, and "cutaneous melanoma", "microstructure", "diagnosis" were recent topics (Portions of this research have previously been presented in poster form). Significance: Overall, EIT extrapulmonary applications bibliometrics analysis provides a unique insight into research focus, current trends, and future directions.

First Attempt at Using Electrical Impedance Tomography to Predict High Flow Nasal Cannula Therapy Outcomes at an Early Phase.

Objective: Spatial and temporal ventilation distributions in patients with acute respiratory failure during high flow nasal cannula (HFNC) therapy were previously studied with electrical impedance tomography (EIT). The aim of the study was to explore the possibility of predicting HFNC failure based on various EIT-derived parameters. Methods: High flow nasal cannula failure was defined reintubation within 48 h after HFNC. EIT was performed with the patients spontaneously breathing in the supine position at the start of HFNC. EIT-based indices (comprising the global inhomogeneity index, center of ventilation, ventilation delay, rapid shallow breathing index, minute volume, and inspiration to expiration time) were explored and evaluated at three time points (prior to HFNC, T1; 30 min after HFNC started, T2; and 1 h after, T3). Results: A total of 46 subjects were included in the final analysis. Eleven subjects had failed HFNC. The time to failure was 27.8 ± 12.4 h. The ROX index (defined as SpO2/FiO2/respiratory rate) for HFNC success patients was 8.3 ± 2.7 and for HFNC failure patients, 6.2 ± 1.8 (p = 0.23). None of the investigated EIT-based parameters showed significant differences between subjects with HFNC failure and success. Further subgroup analysis indicated that a significant difference in ventilation inhomogeneity was found between ARDS and non-ARDS [0.54 (0.37) vs. 0.46 (0.28) as evaluated with GI, p < 0.01]. Ventilation homogeneity significantly improved in ARDS after 60-min HFNC treatment [0.59 (0.20) vs 0.57 (0.19), T1 vs. T3, p < 0.05]. Conclusion: Spatial and temporal ventilation distributions were slightly but insignificantly different between the HFNC success and failure groups. HFNC failure could not be predicted by changes in EIT temporal and spatial indexes of ventilation distribution within the first hour. Further studies are required to predict the outcomes of HFNC.

Knockdown of long non-coding RNA CDKN2B-AS1 suppresses the progression of breast cancer by miR-122-5p/STK39 axis.

The lncRNAs have been made certain to take part in the development of most cancers in multiple ways. Here, our purpose is to making observation of the biological role and function of lncRNA CDKN2B-AS1 in human breast cancer. Twenty-eight pairs of breast cancer tissue and adjacent normal tissue from breast cancer patients were used to investigate the expression of CDKN2B-AS1 by qRT-PCR. And a lentivirus-shRNA guided CDKN2B-AS1 were to reduce its expression. The function of CDKN2B-AS1 was analyzed using a series of in vitro assays. Meanwhile, the xenograft model was used to further explicate the role of CDKN2B-AS1 in breast cancer. As for the results, there is a relative rich expression of CDKN2B-AS1 in breast cancer tissues compared with the corresponding adjacent normal tissues. Compared with the human breast epithelial cell line, the abundant expression of CDKN2B-AS1 in breast cancer cells were revealed as well. Then, knockdown CDKN2B-AS1 inhibited the malignant biological behaviors of MCF7 and T47D cells. In mechanism, CDKN2B-AS1 sponged the miR-122-5p to regulate STK39 expression. Furthermore, the inhibition effect with sh-CDKN2B-AS1 on breast cancer cells was alleviated by miR-122-5p inhibitor. Last, an in vivo model also confirmed that knockdown CDKN2B-AS1 retarded the growth of breast cancer. Our data concluded that knockdown of CDKN2B-AS1 suppresses the progression of breast cancer by miR-122-5p/STK39 axis.

[Methods and applications of single-cell proteomics analysis based on mass spectrometry].

The cell is the smallest unit of living organisms. Although cells often assemble to serve a common function, intercellular heterogeneity often exists due to different genetic and environmental effects. Therefore, single-cell analysis has been regarded as an indispensable means to investigate cell heterogeneity, especially when researching cell differentiation, disease diagnosis, and therapy. As the chief factors influencing cell and biological activities, proteins have long been a major concern in biochemistry. However, due to their intrinsic lack of amplification characteristics, wide species variety, low abundance, and wide dynamic range, proteins are scarcely studied in single-cell research when compared with other biological macromolecules. Therefore, ultra-sensitive single-cell proteomics analysis methods are urgently required. Among all general measurement techniques, fluorescence methods possess high sensitivity and a capability of dynamic tracing, but low target numbers impose restrictions on their broad application in real "proteomic" studies. Similarly, electrochemical methods adapt to electrochemically active molecules, which miss the majority of proteins. Mass spectrometry (MS), as the core approach of proteomic studies, provides high-sensitivity and high-throughput analysis of proteins together with abundant structural information, which is unique in all the analytical instruments and has made great progress in single-cell proteomic research. Herein, the representative research methods for single-cell proteomics based on MS are reviewed. According to the different protein separation methods used prior to MS analysis, they are divided into three categories, including capillary electrophoresis (CE), liquid chromatography (LC), and direct infusion without the need for separation. First, CE has been widely used in the separation and analysis of complex biological samples owing to its low cost, high analysis speed, and high separation efficiency. Its unique feature is the extraction and transfer of contents from cellular or subcellular regions using capillaries smaller than a single cell size. This sampling method also offers less substrate interference and negligible oxidative damage to the cells. Nonetheless, single-cell analysis based on CE-MS mainly focuses on proteomic studies of large cells because of the considerable sample loss, interface instability, and reproducibility issues. Compared with CE, LC, especially nanoLC, is more widely used in single-cell proteomic research, which mainly depends on its good reproducibility, nanoliter injection volume, low flow rate, low sample loss, and good compatibility with mass spectrometry. In recent years, it has been increasingly applied in the study of large-volume embryos, germ cells, and even somatic cells. More than 1000 proteins have been identified in single HeLa cells using this state-of-the-art single-cell proteomics method. It is worth noting that the single-cell sampling volume based on LC gradually reduces to the nanoliter level, and that the sample loss can be reduced by integrating a series of proteomic sampling processes into small volumes, setting sealing conditions, and reducing washing steps. However, the adequacy of cell lysis, the completeness and efficiency of protein pretreatment, and the labeling of peptide segments are important factors affecting the number and types of protein identification. Compared with protein separation using CE or LC prior to MS analysis, the direct MS analysis, assisted by labelling and signal transformation, eliminates complicated sample pretreatment and simplifies the operation by reducing enzymatic hydrolysis and separation. It also renders higher resolution as well as multi-omics compatibility. So far, the number of proteins detected using this method is limited due to the complexity of the samples. In conclusion, the aspects of throughput, sensitivity, identified protein species, and applications are summarized for each method mentioned above, and the prospect of single-cell proteomic research based on MS in the future is also discussed.

The research on minimizing the induction between the transmitting and receiving coils in close range transient electromagnetic inspection of groundwater-related defects in the operating tunnels.

The striking dominance of groundwater-related defects in the operational high-speed railway tunnels in China calls for swift and accurate detection and identification. Thus, it is a new attempt to detect the water-bearing defects at 5 to 10 meters via train-borne transient electromagnetic method in operating tunnels. Due to the short detection distance, the interaction between transmitting and receiving coils is more important than those normally used coils. Thus, numerical and experimental methods are combined to investigate the mutual induction. The influence of turns, current and coil size on the mutual induction and the impact of damping coefficient on the receiving system are manifested. To further verify these findings, full-scale model experiments are conducted. During these physical experiments, the detection results of different coil parameters including coil size, number of turns, and emission current are compared and analyzed. Then, a special effort to minimize the induction between transmitting and receiving coils is expended to acquire the suitable coils for close range detection in the tunnel context. Finally, in order to verify the availability of the detection system, different detection distances are conducted. It turns out that different detection distances have slight difference at the detection results, but they are still within the measuring range of the detection instrument. Obviously, these findings can provide theoretical support for the detection of water-bearing anomalies in operating tunnels and it also has reference significance for the detection of anomalies at close distance.

LncRNA AFAP-AS1 promotes anaplastic thyroid cancer progression by sponging miR-155-5p through ETS1/ERK pathway.

Anaplastic thyroid cancer (ATC) is the most common malignant endocrine tumors which resist to majority treatment. Thus, there is impelling need to figure out the mechanism of progress of ATC. In this study, we explored the function and mechanism of lncRNA actin filamentin-1 antisense RNA (AFAP-AS1) which provided a new biomarker for ATC. Viabilities and apoptosis were tested by CCK-8, colony formation and flow cytometry. The interactions between miR-155-5p and AFAP-AS1 or ETS1 was detected by luciferase reporter assays. ETS proto-oncogene1/mitogen-activated protein kinase1 (ETS1/ERK) pathway was assessed by Western blot. Xenograft models were built to confirm the function of AFAP-AS1 in vivo. Firstly, we showed that relative RNA expression of AFAP-AS1 in ATC cells was higher than in immortalized thyroid cells. Next, AFAP-AS1 was verified as an oncogene in ATC since knock-down of AFAP-AS1 inhibited cell proliferation and accelerated apoptosis. In addition, miR-155-5p was negatively regulated by AFAP-AS1. Moreover, AFAP-AS1 regulated ETS1/ERK pathway by sponging miR-155-5p. Finally, we confirmed knock-down of AFAP-AS1 significantly suppressed tumor proliferation in vivo. Our research proved that AFAP-AS1 could facilitate progression of thyroid cancer sponging miR-155-5p through ETS1/ERK pathway.

Emerging Trends and Hot Spots of Electrical Impedance Tomography Applications in Clinical Lung Monitoring.

OBJECTIVE: This study explores the emerging trends and hot topics concerning applications on electrical impedance tomography (EIT) in clinical lung monitoring. METHODS: Publications on EIT applications in clinical lung monitoring in 2001-2021 were extracted from the Web of Science Core Collection (WoSCC). The search strategy was "electrical impedance tomography" and "lung." CiteSpace, a VOS viewer was used to study the citation characteristics, cooperation, and keyword co-occurrence. Moreover, co-cited reference clustering, structural variation analysis (SVA), and future research trends were presented. RESULTS: Six hundred and thirty-six publications were included for the final analysis. The global annual publications on clinical lung monitoring gradually increased in the last two decades. Germany contributes 32.2% of total global publications. University Medical Center Schleswig-Holstein (84 publications, cited frequency 2,205), Physiological Measurement (105 publications, cited frequency 2,056), and Inéz Frerichs (116 articles, cited frequency 3,609) were the institution, journal, and author with the largest number of article citations in the research field. "Electrical impedance tomography" (occurrences, 304), "mechanical ventilation" (occurrences, 99), and "acute respiratory distress syndrome" (occurrences, 67) were the top most three frequent keywords, "noninvasive monitoring" (Avg, pub, year: 2008.17), and "extracorporeal membrane oxygenation" (Avg, pub, year: 2019.60) were the earliest and latest keywords. The keywords "electrical impedance tomography" (strength 7.88) and co-cited reference "Frerichs I, 2017, THORAX" (strength 47.45) had the highest burst value. "Driving pressure," "respiratory failure," and "titration" are the three keywords still maintaining a high brush value until now. The largest and smallest cluster of the co-cited references are "obstructive lung diseases" (#0, size: 97) and "lung perfusion" (#20, size: 5). Co-cited reference "Frerichs I, 2017, THORAX" (modularity change rate: 98.49) has the highest structural variability. Categories with most and least interdisciplinary crossing are "ENGINEERING" and "CRITICAL CARE MEDICINE." CONCLUSIONS: EIT is a valuable technology for clinical lung monitoring, gradually converting from imaging techniques to the clinic. Research hot spots may continue monitoring techniques, the ventilation distribution of acute respiratory distress syndrome (ARDS), and respiratory therapy strategies. More diversified lung function monitoring studies, such as lung perfusion and interdisciplinary crossing, are potentially emerging research trends.

Construction of High-Nuclearity Manganese-Cluster-Organic Frameworks by Using a Tripodal Alcohol Ligand.

Two novel cluster-organic frameworks based on the 12-nuclearity manganese-cluster secondary building unit (SBU), [MnIII4MnII8(L)4(Ac)8(MeO)2(µ5-O)2(H2O)4](Ac)2·16H2O (1) and [MnIII4MnII8(L)4(Ac)8(MeO)2(µ5-O)2(H2O)4](Ac)2·12H2O (2), where Ac = CH3COO- and MeO = CH3O, have been constructed from solvothermal reactions of the 3-nuclearity manganese cluster [Mn3(µ3-O)(Ac)6(py)3](ClO4) (Mn3, where py = pyridine) with a tripodal alcohol ligand containing a 4-pyridyl group. 1 and 2 represent the first examples of metal-organic frameworks containing 12-nuclearity manganese-cluster SBUs. In addition, 1 exhibits an integration of the porosity and magnetic properties from both the framework and cluster in a porous material.