Relay Adsorption in Metal-Organic Frameworks for One-Step Helium Purification at Ambient Temperature.

One-step He purification from natural gas represents a crucial solution for addressing the global He shortages. The prevailing method to produce high-grade He involves cryogenic distillation and ultralow temperature adsorption processes, which is highly cost- and energy-intensive. Separating and purifying He at ambient temperature is a great challenge because the fundamental limitation lies in the boiling point, polarizability, and kinetic diameters of CH4/N2/He gases. In this study, we seek to implement a relay adsorption strategy using Ni(ina)2 and MIL-100(Cr) metal-organic frameworks (MOFs) to produce high-purity He from ternary mixtures (CH4, N2, and He) at ambient temperature. The CH4/He selectivity in Ni(ina)2 and N2/He selectivity in MIL-100(Cr) both reach record 15.39 and 128.49, respectively, making the relay adsorption for helium purification highly efficient. The breakthrough experiments show that the two MOFs can sequentially adsorb CH4 and N2 in ternary mixtures, producing He with a purity of up to 99.99% in one step. The remarkable separation performance and stability of these MOFs underscore the industrial potential in purifying He at ambient temperature.

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.

A Rhombic 2D Conjugated Metal-Organic Framework as Cathode for High-Performance Sodium-Ion Battery.

2D conjugated metal-organic frameworks (2D c-MOFs) have garnered significant attention as promising electroactive materials for energy storage. However, their further applications are hindered by low capacity, limited cycling life, and underutilization of the active sites. Herein, Cu-TBA (TBA = octahydroxyltetrabenzoanthracene) with large conjugation units (narrow energy gap) and a unique rhombus topology is introduced as the cathode material for sodium-ion batteries (SIBs). Notably, Cu-TBA with a rhombus topology exhibits a high specific surface area (613 m2 g-1) and metallic band structure. Additionally, Cu-TBA outperforms its hexagonal counterpart, Cu-HHTP (HHTP = 2,3,6,7,10,11-hexahydroxyltriphenylene), demonstrating superior reversible capacity (153.6 mAh g-1 at 50 mA g-1) and outstanding cyclability with minimal capacity decay even after 3000 cycles at 1 A g-1. This work elucidates a new strategy to enhance the electrochemical performance of 2D c-MOFs cathode materials by narrowing the energy gap of organic linkers, effectively expanding the utilization of 2D c-MOFs for SIBs.

WY-14643, a novel antiplatelet and antithrombotic agent targeting the GPIbα receptor.

BACKGROUND AND PURPOSE: Hypolipidemia and platelet activation play key roles in atherosclerotic diseases. Pirinixic acid (WY-14643) was originally developed as a lipid-lowering drug. Here we focused on its antiplatelet and antithrombotic abilities and the underlying mechanism. EXPERIMENTAL APPROACH: The effects of WY-14643 on platelet aggregation was measured using a lumi-aggregometer. Clot retraction and spreading on fibrinogen were also assayed. PPARα-/- platelets were used to identify the target of WY-14643. The interaction between WY-14643 and glycoprotein Ibα (GPIbα) was detected using cellular thermal shift assay (CETSA), surface plasmon resonance (SPR) spectroscopy and molecular docking. GPIbα downstream signaling was examined by Western blot. The antithrombotic effect was investigated using mouse mesenteric arteriole thrombosis model. Mouse tail bleeding model was used to study its effect on bleeding side effects. KEY RESULTS: WY-14643 concentration-dependently inhibits human washed platelet aggregation, clot retraction, and spreading. Significantly, WY-14643 inhibits thrombin-induced activation of human washed platelets with an IC50 of 7.026 µM. The antiplatelet effect of WY-14643 is mainly dependent of GPIbα. CESTA, SPR and molecular docking results indicate that WY-14643 directly interacts with GPIbα and acts as a GPIbα antagonist. WY-14643 also inhibits phosphorylation of PLCγ2, Akt, p38, and Erk1/2 induced by thrombin. Noteworthily, 20 mg/kg oral administration of WY-14643 inhibits FeCl3-induced thrombosis of mesenteric arteries in mice similarly to clopidogrel without increasing bleeding. CONCLUSION AND IMPLICATIONS: WY-14643 is not only a PPARα agonist with lipid-lowering effect, but also an antiplatelet agent as a GPIbα antagonist. It may have more significant therapeutic advantages than current antiplatelet agents for the treatment of atherosclerotic thrombosis, which have lipid-lowering effects without bleeding side effects.

PANoptosis, an indicator of COVID-19 severity and outcomes.

Coronavirus disease 2019 (COVID-19) has been wreaking havoc for 3 years. PANoptosis, a distinct and physiologically relevant inflammatory programmed cell death, perpetuates cytokine storm and multi-organ injuries in COVID-19. Although PANoptosis performs indispensable roles in host defense, further investigation is needed to elucidate the exact processes through which PANoptosis modulates immunological responses and prognosis in COVID-19. This study conducted a bioinformatics analysis of online single-cell RNA sequence (scRNA-seq) and bulk RNA-seq datasets to explore the potential of PANoptosis as an indicator of COVID-19 severity. The degree of PANoptosis in bronchoalveolar lavage fluid (BALF) and peripheral blood mononuclear cells (PBMC) indicated the severity of COVID-19. Single-cell transcriptomics identified pro-inflammatory monocytes as one of the primary sites of PANoptosis in COVID-19. The study subsequently demonstrated the immune and metabolic characteristics of this group of pro-inflammatory monocytes. In addition, the analysis illustrated that dexamethasone was likely to alleviate inflammation in COVID-19 by mitigating PANoptosis. Finally, the study showed that the PANoptosis-related genes could predict the intensive care unit admission (ICU) and outcomes of COVID-19 patients who are hospitalized.

STING is significantly increased in high-grade glioma with high risk of recurrence.

In this study, we aimed to comprehensively characterize the potential relationships among the frequently mutated genes, well-known homologous recombination repair (HRR) proteins, and immune proteins in glioma from a clinical perspective. A total of 126 surgical tissues from patients initially diagnosed with glioma were included. The genetic alterations were tested using the targeted next-generation sequencing technique. The expression of HRR proteins, immune proteins, and genetic alteration-related proteins were detected using immunostaining. Integrated analysis showed that ATRX is positively correlated with STING in high-grade glioma (HGG) with wild-type ATRX and IDH1. Then, a relapse predictive risk-scoring model was established using the least absolute shrinkage and selection operator regression algorithms. The scores based on the expression of ATRX and STING significantly predict the recurrence for glioma patients, which further predict the survival for specific subgroups, characterized with high expression of RAD51 and wild-type TERT. Moreover, STING is significantly higher in patients with high relapse risk. Interestingly, STING inhibitors and agonists both suppress the growth of HGG cells, regardless of their STING levels and STING pathway activity, whereas RAD51 inhibitor B02 is found to exclusively sensitize HGG cells with high expression of STING to temozolomide in vitro and in vivo. Overall, findings in the study not only reveal that ATRX is closely correlated with STING to drive the relapse of HGG, but also provide a STING-guided combined strategy to treat patients with aggressive gliomas. Translation of these findings will ultimately improve the outcomes for ATRX and IDH1 genomically stratified subgroups in HGG.

Ethane/Ethylene Separations in Flexible Diamondoid Coordination Networks via an Ethane-Induced Gate-Opening Mechanism.

Separating ethane (C2H6) from ethylene (C2H4) is an essential and energy-intensive process in the chemical industry. Here, we report two flexible diamondoid coordination networks, X-dia-1-Ni and X-dia-1-Ni0.89Co0.11, that exhibit gate-opening between narrow-pore (NP) and large-pore (LP) phases for C2H6, but not for C2H4. X-dia-1-Ni0.89Co0.11 thereby exhibited a type F-IV isotherm at 273 K with no C2H6 uptake and a high uptake (111 cm3 g-1, 1 atm) for the NP and LP phases, respectively. Conversely, the LP phase exhibited a low uptake of C2H4 (12.2 cm3 g-1). This C2H6/C2H4 uptake ratio of 9.1 for X-dia-1-Ni0.89Co0.11 far surpassed those of previously reported physisorbents, many of which are C2H4-selective. In situ variable-pressure X-ray diffraction and modeling studies provided insight into the abrupt C2H6-induced structural NP to LP transformation. The promise of pure gas isotherms and, more generally, flexible coordination networks for gas separations was validated by dynamic breakthrough studies, which afforded high-purity (99.9%) C2H4 in one step.

Insight into the Gas-Induced Phase Transformations in a 2D Switching Coordination Network via Coincident Gas Sorption and In Situ PXRD.

Switching coordination networks (CNs) that reversibly transform between narrow or closed pore (cp) and large pore (lp) phases, though fewer than their rigid counterparts, offer opportunities for sorption-related applications. However, their structural transformations and switching mechanisms remain underexplored at the molecular level. In this study, we conducted a systematic investigation into a 2D switching CN, [Ni(bpy)2(NCS)2]n, sql-1-Ni-NCS (1 = bpy = 4,4'-bipyridine), using coincident gas sorption and in situ powder X-ray diffraction (PXRD) under low-temperature conditions. Gas adsorption measurements revealed that C2H4 (169 K) and C2H6 (185 K) exhibited single-step type F-IVs sorption isotherms with sorption uptakes of around 180-185 cm3 g-1, equivalent to four sorbate molecules per formula unit. Furthermore, parallel in situ PXRD experiments provided insight into sorbate-dependent phase switching during the sorption process. Specifically, CO2 sorption induced single-step phase switching (path I) solely between cp and lp phases consistent with the observed single-step type F-IVs sorption isotherm. By contrast, intermediate pore (ip) phases emerged during C2H4 and C2H6 desorption as well as C3H6 adsorption, although they remained undetectable in the sorption isotherms. To our knowledge, such a cp-lp-ip-cp transformation (path II) induced by C2H4/6 and accompanied by single-step type F-IVs sorption isotherms represents a novel type of phase transition mechanism in switching CNs. By virtue of Rietveld refinements and molecular simulations, we elucidated that the phase transformations are governed by cooperative local and global structural changes involving NCS- ligand reorientation, bpy ligand twist and rotation, cavity edge (Ni-bpy-Ni) deformation, and interlayer expansion and sliding.

Spatiotemporal variation in heatwaves and elderly population exposure across China.

Heatwaves have been intensified worldwide due to climate change, posing great health risks, especially to elderly populations. However, in China, limited studies have employed the heat index to decipher the spatiotemporal trends of heatwaves and their impacts on the elderly population. By comparing the three heatwave definitions, this study aimed to evaluate the long-term spatiotemporal variations in heatwaves from 1964 to 2022 across China using the Excess Heat Factor (EHF). We took advantage of high-resolution reanalysis temperature data on the Google Earth Engine (GEE) platform to efficiently calculate the heatwaves. Our results revealed that the frequency and duration of heatwaves increased significantly in approximately 77 % of China's total area, with South China experiencing the most frequent and prolonged heatwaves. Conversely, in most areas, no significant trend was discerned in the growth of the maximum and average heatwave intensities. The total number of elderly people affected by heatwaves surged from approximately 11.96 million in 2001 to over 30.31 million in 2020, with an estimated additional 1.12 million older adults exposed to heatwaves annually across the nation (R2 = 0.60, p < 0.05). The population factor exhibited largest effect on the exposure of heatwaves, followed by climate effects and combined factors, with the corresponding explanatory power about 42.84 %, 34.85 % and 22.31 %, respectively. These individuals predominantly resided in the Northeast China, Southwest China, and South China. We also found geographical variations in heatwave exposure along elevations and land use types. These insights underscore the pressing necessity for formulating strategic interventions to mitigate the health threats presented by mounting heatwave exposure, especially for susceptible groups like the elderly in China.

Clinical Features and Immunogenetic Risk Factors Associated With Additional Autoantibodies in Anti-Transcriptional Intermediary Factor 1γ Juvenile-Onset Dermatomyositis.

OBJECTIVE: Novel autoantibody specificities including anti-CCAR1 were recently discovered in adult patients with anti-transcriptional intermediary factor (TIF1)-positive dermatomyositis (DM) and were associated with attenuated cancer emergence. The aims of the present study were to examine whether these autoantibodies occur in patients with juvenile-onset DM (JDM) and to determine their associated features. METHODS: Sera from 150 patients with anti-TIF1γ autoantibody-positive JDM in a cross-sectional cohort and 90 juvenile healthy controls were assayed for anti-CCAR1, anti-C1Z1, anti-IMMT, anti-TBL1XR1, and anti-Sp4 autoantibodies. Demographics, myositis autoantibodies, clinical features, medications, outcomes, and HLA-DRB1 and HLA-DQA1 alleles were compared between those with and without these autoantibodies. RESULTS: Any one of the anti-TIF1γ-associated autoantibodies was present in 44 patients (29%) overall, including 25 (17%) with anti-Sp4, 22 (15%) with anti-TBL1XR1, 14 (9%) with anti-CCAR1, 2 (1%) with anti-C1Z1, and 2 (1%) with anti-IMMT autoantibodies. These anti-TIF1γ-associated autoantibodies frequently co-occurred. Patients with any of the anti-TIF1γ-associated autoantibodies had less frequent falling (34% [15] vs. 53% [56], P = 0.032) and lower peak muscle enzymes. None of the patients had cancer. Among White patients, HLA-DRB1*03 was protective against an anti-TIF1γ-associated autoantibody (odds ratio 0.20, 95% confidence interval 0.07-0.52). CONCLUSION: Autoantibodies associated with anti-TIF1γ were found in isolation and in combination among a subset of patients with JDM. Patients with these autoantibodies had less severe muscle disease and were not enriched for HLA-DRB1*03. Additional autoantibodies among patients with positive anti-TIF1γ with JDM likely contribute to the heterogeneity of the anti-TIF1γ serologic subgroup.

Ligand Defect-Induced Active Sites in Ni-MOF-74 for Efficient Photocatalytic CO2 Reduction to CO.

The conversion of CO2 into valuable carbon-based products using clean and renewable solar energy has been a significant challenge in photocatalysis. It is of paramount importance to develop efficient photocatalysts for the catalytic conversion of CO2 using visible light. In this study, the Ni-MOF-74 material is successfully modified to achieve a highly porous structure (Ni-74-Am) through temperature and solvent modulation. Compared to the original Ni-MOF-74, Ni-74-Am contains more unsaturated Ni active sites resulting from defects, thereby enhancing the performance of CO2 photocatalytic conversion. Remarkably, Ni-74-Am exhibits outstanding photocatalytic performance, with a CO generation rate of 1380 µmol g-1 h-1 and 94% CO selectivity under visible light, significantly surpassing the majority of MOF-based photocatalysts reported to date. Furthermore, experimental characterizations reveal that Ni-74-Am has significantly higher efficiency of photogenerated electron-hole separation and faster carrier migration rate for photocatalytic CO2 reduction. This work enriches the design and application of defective MOFs and provides new insights into the design of MOF-based photocatalysts for renewable energy and environmental sustainability. The findings of this study hold significant promise for developing efficient photocatalysts for CO2 reduction under visible-light conditions.

How well do concentric radii approximate population exposure to volcanic hazards?

Effective risk management requires accurate assessment of population exposure to volcanic hazards. Assessment of this exposure at the large-scale has often relied on circular footprints of various sizes around a volcano to simplify challenges associated with estimating the directionality and distribution of the intensity of volcanic hazards. However, to date, exposure values obtained from circular footprints have never been compared with modelled hazard footprints. Here, we compare hazard and population exposure estimates calculated from concentric radii of 10, 30 and 100 km with those calculated from the simulation of dome- and column-collapse pyroclastic density currents (PDCs), large clasts, and tephra fall across Volcanic Explosivity Index (VEI) 3, 4 and 5 scenarios for 40 volcanoes in Indonesia and the Philippines. We found that a 10 km radius-considered by previous studies to capture hazard footprints and populations exposed for VEI ≤ 3 eruptions-generally overestimates the extent for most simulated hazards, except for column collapse PDCs. A 30 km radius - considered representative of life-threatening VEI ≤ 4 hazards-overestimates the extent of PDCs and large clasts but underestimates the extent of tephra fall. A 100 km radius encapsulates most simulated life-threatening hazards, although there are exceptions for certain combinations of scenario, source parameters, and volcano. In general, we observed a positive correlation between radii- and model-derived population exposure estimates in southeast Asia for all hazards except dome collapse PDC, which is very dependent upon topography. This study shows, for the first time, how and why concentric radii under- or over-estimate hazard extent and population exposure, providing a benchmark for interpreting radii-derived hazard and exposure estimates. Supplementary information: The online version contains supplementary material available at 10.1007/s00445-023-01686-5.

MOF-GRU: A MOFid-Aided Deep Learning Model for Predicting the Gas Separation Performance of Metal-Organic Frameworks.

The remarkable versatility of metal-organic frameworks (MOFs) stems from their rich chemical information, leading to numerous successful applications. However, identifying optimal MOFs for specific tasks necessitates a thorough assessment of their chemical attributes. Conventional machine learning approaches for MOF prediction have relied on intricate chemical and structural details, hampering rapid evaluations. Drawing inspiration from recent advancements exemplified by Snurr et al., wherein a text string was used to represent a MOF (MOFid), we introduce a MOFid-aided deep learning model, named the MOF-GRU model. This model, founded on natural language processing principles and utilizing the gated recurrent unit architecture, leverages the serialized text string representation of metal-organic frameworks (MOFs) to forecast gas separation performance. Through a focused study on CH4/N2 separation, we substantiate the efficacy of this approach. Comparative assessments against traditional machine learning techniques underscore our model's superior predictive accuracy and its capacity to handle extensive data sets adeptly. The MOF-GRU model remarkably uncovers latent structure-performance relationships with only MOF sequences, obviating the necessity for intricate three-dimensional (3D) structural information. Overall, this model's judicious design empowers efficient data utilization, thereby hastening the discovery of high-performance materials tailored for gas separation applications.

Expression of IDO1 in Tumor Microenvironment Significantly Predicts the Risk of Recurrence/Distant Metastasis for Patients With Esophageal Squamous Cell Carcinoma.

In this study, we aimed to explore immune markers predicting locoregional recurrence/distant metastasis (R/M) for patients with esophageal squamous cell carcinoma (ESCC) post-surgical intervention by using a novel high-throughput spatial tool to quantify multiple immune proteins expressed in ESCC and lymphocytes in tumor microenvironment (TME-L). First, formalin-fixed paraffin-embedded tissues from surgical patients with ESCC (n = 94) were constructed on a microarray, which was then divided into discovery (n = 36) and validation cohorts (n = 58). Using a newly developed GeoMx digital spatial profiling tool, 31 immune proteins in paired ESCC and TME-L, morphologically segmented by PANCK and CD45, respectively, from the discovery cohort were quantified, releasing 2,232 variables. Next, the correlation matrix was analyzed using the Corrplot package in R Studio, resulting in 6 closely correlated clusters. The Least Absolute Shrinkage and Selection Operator regression scoring model predictive of R/M risk with superior specificity was successfully established based on the 3 following hierarchically clustered immune proteins: ARG1 in ESCC/PANCK+, STING, and IDO1 in TME-L/CD45+. Moreover, the expression of IDO1 in TME-L, rather than in ESCC, significantly predicted the R/M risk score with an area under curve of 0.9598. In addition, its correlation with R/M status was further validated by dual immunohistochemistry staining of IDO1 and CD45 in discovery and validation cohorts. Above all, our findings not only provide a more accurate scoring approach based on quantitative immune proteins for the prediction of R/M risk, but also propose that IDO1 in TME-L potentially plays a driving role in mediating R/M in ESCC.

Non-heme Iron Single-Atom Nanozymes as Peroxidase Mimics for Tumor Catalytic Therapy.

Single-atom nanozymes (SAzymes) open new possibilities for the development of artificial enzymes that have catalytic activity comparable to that of natural peroxidase (POD). So far, most efforts have focused on the structural modulation of the Fe-N4 moiety to mimic the metalloprotein heme center. However, non-heme-iron POD with much higher activity, for example, HppE, has not been mimicked successfully due to its structural complexity. Herein, carbon dots (CDs)-supported SAzymes with twisted, nonplanar Fe-O3N2 active sites, highly similar to the non-heme iron center of HppE, was synthesized by exploiting disordered and subnanoscale domains in CDs. The Fe-CDs exhibit an excellent POD activity of 750 units/mg, surpassing the values of conventional SAzymes with planar Fe-N4. We further fabricated an activatable Fe-CDs-based therapeutic agent with near-infrared enhanced POD activity, a photothermal effect, and tumor-targeting ability. Our results represent a big step in the design of high-performance SAzymes and provide guidance for future applications for synergistic tumor therapy.

Co-treatment of diamond-wire-saw silicon kerf and spent automotive catalysts for simultaneous recovery of PGMs, REEs, Zr, and high-purity Si.

Spent automotive catalysts (SACs) and diamond-wire-saw silicon kerf (DWSSK) are classified as hazardous wastes. Currently, the two wastes are treated separately using unrelated approaches. More than two independent approaches are required to recover platinum group metals (PGMs), Zr and rare earth elements (REEs) from SACs, and recover Si from DWSSK, which is time-consuming and laborious. In this study, a new approach was proposed to co-treat the two wastes based on the concept of using waste treats waste: using DWSSK (∼89.85 wt% Si) as a new metal collector to extract PGMs, REEs, and Zr simultaneously from SACs to obtain a Si-VM alloy (VM: valuable metal); meanwhile, using the carrier of SACs to form molten slag to eliminate the main impurity, O, from DWSSK. The largest recovery ratios of Pd, Rh, Zr, Ce, La, and Nd from SACs were 99.50 ± 0.10%, 99.14 ± 0.14 %, 96.19 ± 0.76%, 67.18 ± 4.57%, 61.24 ± 4.93% and 47.65 ± 7.27%, respectively, and the largest removal ratio of O from DWSSK was 99.96%. After smelting, the Si-VM alloy was separated into high-purity Si and VM-containing acid solutions via acid leaching. The leaching ratios of Pd, Rh, Ce, La, Nd, and Zr were 99.78%, 98.15%, 99.93%, ∼100%, 99.76% and 99.98%, respectively. The purity of Si was upgraded from 89.85 wt% (in DWSSK) to 99.98 wt% after acid leaching. The new approach proposed in this study is considered more environmentally friendly and cost-effective than the regular approaches that treat the two wastes separately.

Shape-Memory Effect Enabled by Ligand Substitution and CO2 Affinity in a Flexible SIFSIX Coordination Network.

We report that linker ligand substitution involving just one atom induces a shape-memory effect in a flexible coordination network. Specifically, whereas SIFSIX-23-Cu, [Cu(SiF6 )(L)2 ]n , (L=1,4-bis(1-imidazolyl)benzene, SiF6 2- =SIFSIX) has been previously reported to exhibit reversible switching between closed and open phases, the activated phase of SIFSIX-23-CuN , [Cu(SiF6 )(LN )2 ]n (LN =2,5-bis(1-imidazolyl)pyridine), transformed to a kinetically stable porous phase with strong affinity for CO2 . As-synthesized SIFSIX-23-CuN , α, transformed to less open, γ, and closed, ß, phases during activation. ß did not adsorb N2 (77 K), rather it reverted to α induced by CO2 at 195, 273 and 298 K. CO2 desorption resulted in α', a shape-memory phase which subsequently exhibited type-I isotherms for N2 (77 K) and CO2 as well as strong performance for separation of CO2 /N2 (15/85) at 298 K and 1 bar driven by strong binding (Qst =45-51 kJ/mol) and excellent CO2 /N2 selectivity (up to 700). Interestingly, α' reverted to ß after re-solvation/desolvation. Molecular simulations and density functional theory (DFT) calculations provide insight into the properties of SIFSIX-23-CuN .

Novel applications of histopathological markers to distinguish prognostic subgroups in colorectal adenocarcinoma.

OBJECTIVE: To explore the novel applications of histological factors by stratifying the prognostic markers of the overall CRC patients in subgroups. MATERIALS AND METHODS: A total of 17 histopathological and molecular factors were retrospectively collected and systematically analyzed for the prediction of CRC prognosis in the overall and stratified subgroups by using the Kaplan-Meier curve analysis as well as the Cox regression test. The χ2 test was used to analyze the correlation of the prognostic markers with other factors. RESULTS: The histopathological markers including the lymph node metastasis (LNM), perineural/venous invasion (PVI), TNM stage, the local recurrence or distant metastasis after surgery (R/M) and the molecular markers Ki-67 expression as well as KRAS mutation were identified to be the independent prognostic biomarkers in the overall CRC. The differential prognosis of LNM was found to be significant in age, tumor site, histological classification (histo_classification), cell differentiation, and KRAS/NRAS/BRAF (KNB) mutation stratified subgroups. The PVI was discovered to differently predict survival for patients in age, histo_classification, differentiation, and R/M stratified subgroups. Same as LNM and PVI, TNM was also found to demonstrate differential prognosis in age, tumor site, histo_classification, differentiation, R/M status and KRAS/KNB mutation stratified subgroups. More importantly, R/M was firstly identified not to be terrible for patients in age, histo_classification, LNM, TNM, Ki-67, and KRAS/KNB stratified subgroups. Besides, KRAS mutation was innovatively found to show differential prognosis in age, differentiation, and LNM stratified subgroups. CONCLUSIONS: The stratification analyses of prognostic markers in CRC patients indicate novel applications of the above histopathological and molecular markers in clinic and the findings provide new insights into future investigations of precision pathology.

The pathological markers LNM, PVI, TNM stage, R/M, the histological marker Ki-67 expression and the molecular marker KRAS mutation are all the early biomarkers capable of independently predicting the 2-year survival rate for CRC.Differential prognosis of the histopathological and molecular markers is commonly found in age, tumor site, differentiation, histological type, LNM, TNM, and R/M stratified CRC subgroups.

Efficient and Reversible Separation of Chloroform from Chlorinated Hydrocarbons and Water Utilizing a Two-Dimensional Coordination Network.

Chloroform is a volatile organic solvent and a contaminant that is slightly soluble in water, making the reversible separation of chloroform from water a critical and challenging task within the chemical and environmental industries. In this study, we present a newly developed coordination framework, [Zn(4-pmntd)(opa)] [4-pmntd, N,N'-bis(4-pyridylmethyl)naphthalene diimide; opa, o-phthalic acid], which demonstrates a high adsorption capacity for chloroform (2.5 mmol/g) and an excellent ability to separate chloroform from water. The effectiveness of chloroform extraction by Zn(4-pmntd)(opa) was confirmed through vapor sorption, grand canonical Monte Carlo simulation, and 1H nuclear magnetic resonance spectroscopy. The porous framework was also utilized to create a filtration film using natural rubber, which successfully separated chloroform from water with a minimum test concentration of approximately 1 × 10-6 mol/L and a chloroform purity of 99.2%. [Zn(4-pmntd)(opa)] therefore has significant potential for low-energy separation and recycling of chloroform from water under ambient conditions.

Efficient Visible-Light Photocatalytic Hydrogen Evolution over the In2O3@Ni2P Heterojunction of an In-Based Metal-Organic Framework.

Although the engineering of visible-light-driven photocatalysts with appropriate bandgap structures is beneficial for generating hydrogen (H2), the construction of heterojunctions and energy band matching are extremely challenging. In this study, In2O3@Ni2P (IO@NP) heterojunctions are attained by annealing MIL-68(In) and combining the resulting material with NP via a simple hydrothermal method. Visible-light photocatalysis experiments validate that the optimized IO@NP heterojunction exhibits a dramatically improved H2 release rate of 2485.5 µmol g-1 h-1 of 92.4 times higher than that of IO. Optical characterization reveals that the doping of IO with an NP component promotes the rapid separation of photo-induced carriers and enables the capture of visible light. Moreover, the interfacial effects of the IO@NP heterojunction and synergistic interaction between IO and NP that arises through their close contact mean that plentiful active centers are available to reactants. Notably, eosin Y (EY) acts as a sacrificial photosensitizer and has a significant effect on the rate of H2 generation under visible light irradiation, which is an aspect that needs further improvement. Overall, this study describes a feasible approach for synthesizing promising IO-based heterojunctions for use in practical photocatalysis.