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[Display omitted] • Brønsted acidity in the MOF UiO-66 was investigated computationally. • μ 1 -OH protons were found to be more acidic than μ 3 -OH. • Explicit solvation and electrostatics analysis provided additional insights. UiO-66 is one of the most popular metal–organic framework materials for catalysis. The Brønsted acidity of its Zr 6 -node is often critical to its catalytic power, but the acidity of each individual proton is difficult to measure directly in experiments. Here, we used density functional theory calculations to quantify the Brønsted acidity of different protons on both pristine and defective Zr 6 -nodes. The calculated acidities were in a different order than the previously reported results that were indirectly assigned from titration. Additional computational analyses were performed to help explain the results and reveal the underlying factors that could affect the acidity. [ABSTRACT FROM AUTHOR]

• Paper studies relationship between land cover (LC) and urban heat island (UHI). • Land surface temperature is retrieved using mono-window algorithm. • LC classification was retrieved via random forest classifier to explore LC result. • The LST of each land change is retrieved to study its effect to UHI intensity. • Relationship between greenness degree and LST is revealed using NDVI index. In this study, the relationship between land cover (LC) characteristics and urban heat island (UHI) intensity in the main urban area of Wuhan City are investigated. The effects of LC change on green space and land surface temperature (LST) was investigated, along with the relationship among LST, LC, and normalised differential vegetation index (NDVI). The land was divided into five categories, namely, built-up area, agricultural land, water, forest, and bare land. LST was determined using the infrared band image from the same period. The area of built-up areas accounted for only 32.81% in 2007, and it increased to 46.01% in 2020, while agricultural land decreased by 12.14%, which is the primary reason for the increase in built-up areas. The average LST in the study area increased from 25.92℃ to 31.71℃, and the range of LST moved forward to high-temperature range. The high-temperature areas (>32℃) expanded from point distribution to plane distribution and its expansion direction was consistent with the urbanisation direction. The water and forest have the strongest mitigation capacity for UHI and should be protected. Urban managers should avoid the increase of bare land due to the degradation of agricultural land and forest because the increase in LST caused by this type of LC change is obvious. LST was negatively correlated with NDVI, indicating that fewer vegetation resulted in higher LST. [ABSTRACT FROM AUTHOR]

Under the Air Pollution Prevention and Control Action Plan (APPCAP) implemented, China has witnessed an air quality change during the past five years, yet the main influence factors remain relatively unexplored. Taking the Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD) regions as typical cluster cities, the Weather Research Forecasting (WRF) and Comprehensive Air Quality Model with Extension (CAMx) were introduced to demonstrate the meteorological and emission contribution and PM2.5 flux distribution. The results showed that the PM2.5 concentration in BTH and YRD significantly declined with a descend ratio of −39.6% and −28.1%, respectively. For the meteorological contribution, those regions had a similar tendency with unfavorable conditions in 2013–2015 (contribution concentration 1.6–3.8 μg/m3 and 1.1–3.6 μg/m3) and favorable in 2016 (contribution concentration −1.5 μg/m3 and −0.2 μg/m3). Further, the absolute value of the net flux's intensity was positively correlated with the degree of the favorable/unfavorable weather conditions. When it came to emission intensity, the total net inflow flux increased, and the outflow flux decreased significantly across the border with the emission increasing. In short: the aforementioned results confirmed the effectiveness of the regional joint emission control and provided scientific support for the proposed effective joint control measures. [ABSTRACT FROM AUTHOR]

• BrdU immunofluorescence double labeling to detect cell proliferation. • Tan promotes the proliferation and differentiation of endogenous hepatic stem cells. • Tan can alleviate liver cirrhosis. Liver cirrhosis (LC), the major pathway for the progression and development of chronic liver disease, is an advanced stage of liver disease. It is the third most common chronic noncommunicable disease after cardiovascular diseases and malignant tumors. Tanshinone IIA (Tan), an extract of Salvia miltiorrhiza (S. miltiorrhiza), has been proven to promote the proliferation and differentiation of stem cells. Moreover, its protective effect in liver injury has received widespread attention. The present study investigated whether Tan plays a therapeutic role in LC by promoting endogenous stem cell proliferation and differentiation. LC models were established by intraperitoneal injection of an olive oil solution containing 50 % carbon tetrachloride (CCL 4) combined with 10 % alcohol in the drinking water. After successful model establishment, the animals were randomly divided into four groups and injected with physiological saline or low-, medium-, or high-dose (10, 20, or 40 mg/kg) Tan for seven consecutive days. The protective effect of Tan on LC was observed by western blotting, serological examination and histopathological staining. Furthermore, immunofluorescence double-labeling of 5-bromo-2-deoxyuridine (BrdU) and the liver cell markers albumin and CK-18 or the liver stem cell markers EPCAM and OV-6 was used to evaluate the proliferation and differentiation of endogenous liver stem cells. We confirmed successful establishment of the LC model by observing transaminase levels and hematoxylin-eosin (HE) and Masson staining of liver sections in CCL 4 -treated and healthy rats. After Tan treatment, HE and Masson staining of paraffin sections of liver tissue showed that Tan treatment significantly improved histological injury to the liver. Serological tests showed that albumin-bilirubin (ALBI) scores and models for end-stage liver disease (MELD) were lower. Immunofluorescence and immunohistochemical staining showed that the newly proliferated cells were colocalized with ALB, OV-6, EPCAM, and CK-18, indicating that new expression of these markers occurred after Tan injection. All results were most significant in the medium-dose treatment group. Tan can alleviate liver injury induced by CCL 4 combined with alcohol in rats and plays a therapeutic role in LC by promoting the proliferation and differentiation of endogenous liver stem cells. [ABSTRACT FROM AUTHOR]

Background: Endoscopic examination is a popular and routine procedure for the diagnosis and treatment of gastrointestinal (GI) diseases. Skilled endoscopists are in great demand in clinical practice, but the training process for beginners to become endoscopy specialists is fairly long. Convenience and a self-paced, learner-centered approach make electronic learning (e-learning) an excellent instructional prospect.Objective: This study aimed to develop and apply an e-learning system in gastroscopy teaching and learning and to evaluate its effectiveness and user satisfaction.Methods: The e-learning software Gastroscope Roaming System was developed for primary learners. The system simulates the real structure of the upper gastrointestinal (UGI) tract to teach the main characteristics of gastroscopy under both normal conditions and conditions of common UGI tract diseases. A randomized controlled trial was conducted. Participants were randomly allocated to an e-learning group (EG)or a non-e-learning control group after a pretest. On completing the training, participants undertook a posttest and gastroscopy examination. In addition, the EG completed a satisfaction questionnaire.Results: Of the 44 volunteers, 41 (93%) completed the gastroscopy learning and testing components. No significant pretest differences were found between the intervention and control groups (mean 50.86, SD 6.12 vs mean 50.76, SD 6.88; P=.96). After 1 month of learning, the EG's posttest scores were higher (mean 83.70, SD 5.99 vs mean 78.76, SD 7.58; P=.03) and improved more (P=.01) than those of the control group, with better performance in the gastroscopy examination (mean 91.05, SD 4.58 vs mean 84.38, SD 5.19; P<.001). Overall, 85% (17/20) of the participants were satisfied with the e-learning system, and 95% (19/20) of the participants considered it successful.Conclusions: E-learning is an effective educational strategy for primary learners to acquire skills in gastroscopy examination and endoscopic imaging of the GI tract.Trial Registration: Chinese Clinical Trial Registry ChiCTR-IOR-17013091; http://www.chictr.org.cn/showproj.aspx?proj=22142. [ABSTRACT FROM AUTHOR]

Addresses the role of kinase and oxidase interconversions in vitamin B-6 metabolism. Molecular characteristics of the enzymes involved; Findings on the purifications of pyridoxine and pyridoxamine; Analysis of an amino acid sequence.

Ionic liquid surfactant (ILS) shows potential application in surfactant foam enhancing oil recovery (SFEOR). The structure–activity relationship between structural characteristics and foam feature is vital for the design and selection of favorable ILS for SFEOR. In this paper, the effect of structural substituent groups of anionic ILSs on foam features was established from experimental methods and Density functional theory (DFT) simulations. Physicochemical features of two anionic ILSs, 3-butyl-1-ethoxycarbonylimidazolium dodecyl benzene sulfonate ([Etbim][DBS]) and 1-butyl-3-butylcarbonylimidazolium dodecyl benzene sulfonate ([Btbim][DBS]) was determined. By surface tensiometry, the critical micelle concentration (CMC) values of [Etbim][DBS] and [Btbim][DBS] were 0.324 mmol/L and 0.211 mmol/L respectively. Foam characteristic of two ILSs were studied, whose tendency followed: [Etbim][DBS] > [Btbim][DBS]. ILS hydrates showed tendency: [Etbim][DBS] (H2O)n < [Btbim][DBS] (H2O)n. Binding energy (D0) values followed the tendency: [Etbim][DBS] (H2O)n > [Btbim][DBS] (H2O)n. Experimental and DFT results verified the introduction of longer ester alkyl chain length in imidazolium cation was adverse to foam features of ILSs. This information will help to screen new foam surfactants for SFEOR. [ABSTRACT FROM AUTHOR]

The artificial intelligence technology of computer science is widely used in digital pathology and develops rapidly, which is a milestone in the era of accurate diagnosis and treatment of tumors. As the gold standard of tumor diagnosis, traditional pathology is highly subjective and unrepeatable, and the work is cumbersome. Feature extraction and quantitative analysis of digital pathological images based on artificial intelligence technology are transformed into data with high fidelity and high-throughput that can be mined and analyzed. It shows unique advantages in early diagnosis, grading, and constructing the prognostic model of tumors. The development of artificial intelligence in digital pathology has brought a unique opportunity for pathology, and it is also the trend of the development of precise diagnosis and treatment in the future. In order to provide reference for clinical diagnosis and treatment, we review the current status and the value of potential application of artificial intelligence in digital pathological image analysis of colorectal cancer.

Solvent D2O and 18O kinetic isotope effects on RNA 2′-O-transphosphorylation catalyzed by Zn2+ demonstrate an altered transition state relative to specific base catalysis. A recent model from DFT calculations involving inner sphere coordination to the non-bridging and leaving group oxygens is consistent with the data. [ABSTRACT FROM AUTHOR]

One functional hydroxyl group-containing anionic surface active ionic liquids (SAILs), 1-(3-hydroxypropyl)-3-methylimidazolium dodecyl sulfate ([MPmim][DS]) and 1-(3-hydroxypropyl)-3-butylimidazolium dodecyl sulfate ([MPbim][DS]) were synthesized and characterized with 1HNMR, 13CNMR, FT-IR spectroscopy, thermogravimetric analysis (TGA), and elemental analysis. The critical micellar concentration (CMC) values of [MPmim][DS] and [MPbim][DS] were obtained through measurements of surface tension and electrical conductivity. The capability of [MPmim][DS] and [MPbim][DS] to form microemulsions was assessed. The influence of the hydroxyl group of imidazolium cation on microemulsion formulation was elucidated using Density functional theory (DFT) simulations. Critical micellar concentration (CMC) values for [MPbim][DS] and [MPmim][DS] are 0.51 mmol/L and 0.99 mmol/L, respectively. The micellization processes of [MPbim][DS] and [MPmim][DS] are spontaneous, endothermic, and entropy-driven. [MPmim][DS] or [MPbim][DS] as surfactant, ethyl laurate microemulsions are formulated. The single-phase region area (S ME) percent of ethyl laurate microemulsions are 60% and 66%. The single-phase region area percent of different microemulsions follows the trend: [MPbim][DS] > [MPmim][DS]. Introducing the functional hydroxyl group into the imidazolium cation significantly expands the S ME area of microemulsions. DFT simulations are employed to analyze hydrogen bonding and electronic energy interactions among cations, DS anion, [MPmim][DS], [MPbim][DS], and ethyl laurate. Two types of hydrogen bonds are formed in [MPmim][DS] or [MPbim][DS], as C-H...O, and O-H...O. In [MPmim][DS], the hydroxyl group of imidazolium cation participates in the formation of a strong hydrogen bond with DS anion, exemplified by strong hydrogen bond O18-H19...O64 (1.972 Å). These advancements offer critical insights into the design of surface active ionic liquids, enhancing their functional properties and broadening the potential for innovative microemulsion applications in various industries. [Display omitted] • Two anionic SAILs ([MPmim][DS] and [MPbim][DS]) with functional hydroxyl group were prepared for microemulsion formulations. • Critical micelle concentration values of SAILs were evaluated with surface tension and electrical conductivity measurements. • Hydrogen bond and electronic energy analysis of cation, anion, SAILs, and ethyl laurate were determined with DFT simulations. • The introduction of hydroxyl group into imidazolium cation greatly increased the single-phase region area of microemulsions. [ABSTRACT FROM AUTHOR]

To gauge the utility of multiparametric MRI in characterizing pathologic changes after iodinated contrast-induced acute kidney injury (CI-AKI) in rats. We randomly grouped 24 rats injected with 8 g iodine/kg of body weight (n = 6 each) and 6 rats injected with saline as controls. All rats underwent T1, T2 mapping and diffusion kurtosis imaging (DKI) after contrast injection at 0 (control), 1, 3, 7, 13 days. T1, T2, and mean kurtosis (MK) values were performed in renal outer/inner stripes of outer medulla (OSOM and ISOM) and cortex (CO), and their diagnosis performance for CI-AKI also been evaluated. Serum creatinine (SCr), insulin-like growth factor-binding protein 7 (IGFBP7), tissue inhibitor metalloproteinase 2 (TIMP-2), aquaporin-1 (AQP1), α-smooth muscle actin (α-SMA), and histologic indices were examined. Compared with controls, urinary concentrations of both TIMP-2 and IGFBP7 were obviously elevated from Day 1 to Day 13 (all p < 0.05). T2 values were significantly higher than control group for Days 1 and 3, and T1 and MK increased were more remarkable at all time points (Days 1–13) in CI-AKI (all p < 0.05) than control group. Changes in T1 and MK strongly correlated with renal injury scores of all anatomical compartments and with expression levels of AQP1 and moderately correlated with α-SMA. Changes in T2 values correlating moderately with renal scores of CO, ISOM and OSOM and AQP1. The MK obtained the highest area under the receiver operating characteristic (ROC) curve of 0.846 with a sensitivity of 70.8 % and specificity of 88.9 %. Combined use of multiparametric MRI could be a valid noninvasive method for comprehensive monitoring of CI-AKI. Among these parameters, MK may achieve the best diagnostic performance for CI-AKI. • Combined use of multiparametric MRI could give one opportunity to comprehensively monitor CI-AKI. • Alterations of renal MK, T1, and T2 values after CI-AKI were useful to detect renal impairment. • T1, T2 and MK values at early time points after CI-AKI induction displayed significant correlations with renal microstructure alterations. [ABSTRACT FROM AUTHOR]

Background: Ulcerative colitis (UC) is a chronic and recurrent disease without satisfactory treatment strategies. Dental pulp stem cell (DPSC) transplantation has been proposed as a potential therapy for UC. This study aimed to investigate the therapeutic effects of the rat hepatocyte growth factor (HGF) gene transduced into DPSCs for UC. Methods: The therapeutic effects of HGF-DPSCs transplanted intravenously into a rat model of UC induced by 5% dextran sulphate sodium (DSS) were compared with the other treatment groups (LV-HGF group, DPSCs group and GFP-DPSCs group). Immunofluorescence and immunohistochemistry were used to observe the localization and proliferation of HGF-DPSCs at the site of colon injury. The expression levels of inflammatory factors were detected by real-time quantitative PCR (RT-PCR) and western blotting. The oxidative stress markers were detected by ELISA. DAI scores and body weight changes were used to macroscopically evaluate the treatment of rats in each group. Results: Immunofluorescence and immunohistochemistry assays showed that HGF-DPSCs homed to colon injury sites and colocalized with intestinal stem cell (ISC) markers (Bmi1, Musashi1 and Sox9) and significantly promoted protein expression (Bmi1, Musashi1, Sox9 and PCNA). Anti-inflammatory cytokine (TGF-β and IL-10) expression was the highest in the HGF-DPSCs group compared with the other treatment groups, while the expression of pro-inflammatory cytokines (TNF-α and INF-γ) was the lowest. Additionally, the oxidative stress response results showed that malondialdehyde (MDA) and myeloperoxidase (MPO) expression decreased while superoxide dismutase (SOD) expression increased, especially in the HGF-DPSCs group. The DAI scores showed a downward trend with time in the five treatment groups, whereas body weight increased, and the changes were most prominent in the HGF-DPSCs group. Conclusions: The study indicated that HGF-DPSCs can alleviate injuries to the intestinal mucosa by transdifferentiating into ISC-like cells, promoting ISC-like cell proliferation, suppressing inflammatory responses and reducing oxidative stress damage, which provides new ideas for the clinical treatment of UC. [ABSTRACT FROM AUTHOR]

[Display omitted] • [DPmim]Cl and [DPbim]Cl with dihydroxyl group was prepared for MCC dissolution. • The viscosity, density, electrical conductivity, and Kamlet-Taft parameters (β and π*) of ILs were evaluated. • Density functional theory (DFT) simulations were used to investigate the interactions between ILs and cellobiose. • The introduction of hydroxyl groups favored disruption of intermolecular hydrogen bonds of MCC. Ionic liquids (ILs) have emerged as a promising class of green solvents suitable for cellulose dissolution. In this study, two dihydroxyl-functionalized ionic liquids, 1-methyl-3-(2,3-dihydroxypropyl)-imidazolium chloride ([DPmim]Cl) and 1-butyl-3-(2,3-dihydroxypropyl)-imidazolium chloride ([DPbim]Cl), were prepared for microcrystalline cellulose (MCC) dissolution. The physical properties of [DPmim]Cl and [DPbim]Cl, such as relative viscosity, density, electrical conductivity, and Kamlet-Taft parameters (β and π*), were evaluated. The dissolution and regeneration properties of MCC in [DPmim]Cl and [DPbim]Cl were investigated. The regenerated MCC was characterized by Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), and X-ray diffraction (XRD). Density functional theory (DFT) simulations were used to investigate the interactions between ionic liquid and cellobiose. [DPmim]Cl and [DPbim]Cl, with higher β-values (0.975 and 1.098) respectively, exhibited stronger hydrogen bonding alkalinity. This increased alkalinity enhanced their ability to accept hydrogen bonds from cellulose, which in turn weakened the inter- and intra-molecular hydrogen bonds within cellulose. As a result, the dissolution of MCC was promoted. The dissolution of MCC in [DPmim]Cl was faster than [DPbim]Cl at same temperature. FTIR, TGA, and XRD characterizations showed that the hydrogen bonding network of microcrystalline cellulose was disrupted during ionic liquid dissolution. DFT simulations unveiled the formation of strong hydrogen bonds between the hydroxyl groups of ILs and the hydroxyl or ether linkages in cellulose. These hydrogen bonds have been identified as a potential crucial factor in facilitating the dissolution of cellulose. [ABSTRACT FROM AUTHOR]

Chitosan-gelatin-flavonoid functional composite films were prepared with chitosan, gelatin, and three flavonoids (Naringenin, Apigenin, and Luteolin). The effect of three flavonoids on physical, antioxidant, and antibacterial properties of functional composite film was investigated from experimental and Density functional theory (DFT) simulations. The tensile strength, thermal stability, water solubility, water vapor permeability, antioxidant activity, and antibacterial activity of chitosan-gelatin-flavonoid functional composite films were improved with flavonoid (Naringenin, Apigenin, and Luteolin) incorporation. The release behavior of Apigenin from functional composite film was much lower than that of Naringenin or Luteolin. ABTS + radical scavenging ability values of functional composite films followed: Luteolin (69.53 %) > Naringenin (41.39 %) > Apigenin (36.13 %). The antibacterial activities of functional composite films against Staphylococcus aureus followed: Luteolin (52.03 mm) > Apigenin (49.34 mm) > Naringenin (43.15 mm). The total number, location of hydroxyl groups on ring-B, and the unsaturation degree on pyrone ring of flavonoids influenced antioxidant and antibacterial activities of functional composite films. The minimum bond dissociation enthalpy values of flavonoids followed: Luteolin < Apigenin < Naringenin. The interaction energy of Apigenin-chitobiose was stronger than that of Naringenin or Luteolin. These results will shed light on flavonoid selection for functional composite films of food packaging., Competing Interests: Declaration of competing interest The authors declare that they have no competing interest., (Copyright © 2024. Published by Elsevier B.V.)

Heterometallic hydride complexes are of growing interest due to their potential to contribute to highly active insertion-based catalysis; however, methods to modulate electron density within this class of molecules are underexplored. Addition of ancillary ligands to heterotrimetallic NiAl 2 H 2 species (1) results in the formation of heterobimetallic NiAl-hydride complexes with varying phosphine donors (2-(L)2). Incorporation of sigma donating ancillary ligands of increasing strength led to contractions of the Ni-Al distances correlated to a strengthening of a back donation interaction to the Al-H sigma antibonding orbital, most prominently present in 2-(PMe3)2. Demethylation of the aryl ether from 2-(PMe3)2 provides access to a novel anionic nickel-aluminum complex (3) with a maintained bridged hydride moiety between Ni and Al. Increased negative charge in complex 3 results in an elongation of the Ni-Al interaction. Combined crystallographic, spectroscopic, and computational studies support a 3-center interaction within the Al-H-Ni subunits and were used to map the degree of Ni-H character of the series within the Al-H-Ni bonding continuum.

Introduction: Online question-and-answer (Q&A) platforms are frequently replete with extensive human resource support. This study proposes a novel methodology of a customized large language model (LLM) called Chaotic LLM-based Educational Q&A System (CHAQS) to navigate the complexities associated with intelligent Q&A systems for the educational sector., Methods: It uses an expansive dataset comprising over 383,000 educational data pairs, an intricate fine-tuning process encompassing p-tuning v2, low-rank adaptation (LRA), and strategies for parameter freezing at an open-source large language model ChatGLM as a baseline model. In addition, Fuzzy Logic is implemented to regulate parameters and the system's adaptability with the Lee Oscillator to refine the model's response variability and precision., Results: Experiment results showed a 5.12% improvement in precision score, an 11% increase in recall metric, and an 8% improvement in the F1 score as compared to other models., Discussion: These results suggest that the CHAQS methodology significantly enhances the performance of educational Q&A systems, demonstrating the effectiveness of combining advanced tuning techniques and fuzzy logic for improved model precision and adaptability., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Chen, Shi, Chen and Lee.)

This study introduces recommendations for conducting molecular simulations of vapor adsorption, with an emphasis on enhancing the accuracy, reproducibility, and comparability of results. The first aspect we address is consistency in the implementation of some details of typical molecular models, including tail corrections and cutoff distances, due to their significant influence on generated data. We highlight the importance of explicitly calculating the saturation pressures at relevant temperatures using methods such as Gibbs ensemble Monte Carlo simulations and illustrate some pitfalls in extrapolating saturation pressures using this method. For grand canonical Monte Carlo (GCMC) simulations, the input fugacity is usually calculated using an equation of state, which often requires the critical parameters of the fluid. We show the importance of using critical parameters derived from the simulation with the same model to ensure internal consistency between the simulated explicit adsorbate phase and the implicit bulk phase in GCMC. We show the advantages of presenting isotherms on a relative pressure scale to facilitate easier comparison among models and with experiment. Extending these guidelines to a practical case study, we evaluate the performance of various isoreticular metal-organic frameworks (MOFs) in adsorption cooling applications. This includes examining the advantages of using propane and isobutane as working fluids and identifying MOFs with a superior performance., (© 2024 Author(s). Published under an exclusive license by AIP Publishing.)

Undergraduate research experiences are an instrumental component of student development, increasing conceptual understanding, promoting inquiry-based learning, and guiding potential career aspirations. Moving one step further, as research continues to become more interdisciplinary, there exists potential to accelerate student growth by granting additional perspectives through collaborative research. This study demonstrates the utilization of a model collaborative research project, specifically investigating the development of sorbent technologies for efficient CO 2 capture, which is an important research area for improving environmental sustainability. A model CO 2 sorbent system of heteroatom-doped porous carbon is utilized to enable students to gain knowledge of adsorption processes, through combined experimental and computational investigations and learnings. A particular emphasis is placed on creating interdisciplinary learning experiences, exemplified by using density functional theory (DFT) to understand molecular interactions between doped carbon surfaces and CO 2 molecules as well as explain underlying physical mechanisms that govern experimental results. The experimental observations about CO 2 sorption performance of doped ordered mesoporous carbons (OMCs) can be correlated with simulation results, which can explain how the presence of heteroatom functional groups impact the ability of porous carbon to selectively adsorb CO 2 molecules. Through an inquiry-focused approach, students were observed to couple interdisciplinary results to construct holistic explanations, while developing skills in independent research and scientific communications. This collaborative research project allows students to obtain a deeper understanding of sustainability challenges, cultivate confidence in independent research, prepare for future career paths, and most importantly, be exposed to strategies employing interdisciplinary research approaches to address scientific challenges., Competing Interests: The authors declare no competing financial interest., (© 2024 The Authors. Published by American Chemical Society and Division of Chemical Education, Inc.)

Yes-associated protein1 (YAP1), a downstream effector of the Hippo pathway, is over-expressed in several types of malignancies. We analyzed retrospectively the TCGA database using 447 colorectal cancer (CRC) samples to determine the correlation between YAP1 expression level and CRC patient prognosis. YAP1-enforced expressed CRC cell lines were constructed using the lentivirus particles containing a YAP1 insert. YAP1 was highly expressed in CRC cancerous tissues and is associated with distant metastasis of CRC patients. Kaplan - Meier analysis indicated that CRC patients with a higher YAP1 expression group ( n  = 104) had worse disease-free survival (DFS) and overall survival (OS) than lower YAP1 expression group ( n  = 343) ( p  = 0.008 and p  = 0.022). Univariate and multivariate analysis indicated that the elevated YAP1 expression predicted the aggressive phenotype and was an independent indicator for OS and DFS of CRC patients. YAP1 over-expression in CRC cells enhanced their migration and invasion significantly which can be reversed by AXL, CTGF, or CYR61 interference. The study suggested that YAP1 affected the prognosis of CRC patients and controlled the abilities of invasion and migration of CRC cells via its target genes AXL, CTGF, and CYR61.

In recent years, there is been a growing reliance on image analysis methods to bolster dentistry practices, such as image classification, segmentation and object detection. However, the availability of related benchmark datasets remains limited. Hence, we spent six years to prepare and test a bench Oral Implant Image Dataset (OII-DS) to support the work in this research domain. OII-DS is a benchmark oral image dataset consisting of 3834 oral CT imaging images and 15240 oral implant images. It serves the purpose of object detection and image classification. To demonstrate the validity of the OII-DS, for each function, the most representative algorithms and metrics are selected for testing and evaluation. For object detection, five object detection algorithms are adopted to test and four evaluation criteria are used to assess the detection of each of the five objects. Additionally, mean average precision serves as the evaluation metric for multi-objective detection. For image classification, 13 classifiers are used for testing and evaluating each of the five categories by meeting four evaluation criteria. Experimental results affirm the high quality of our data in OII-DS, rendering it suitable for evaluating object detection and image classification methods. Furthermore, OII-DS is openly available at the URL for non-commercial purpose: https://doi.org/10.6084/m9.figshare.22608790., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Cervical cancer is the fourth most common cancer among women, and cytopathological images are often used to screen for this cancer. However, manual examination is very troublesome and the misdiagnosis rate is high. In addition, cervical cancer nest cells are denser and more complex, with high overlap and opacity, increasing the difficulty of identification. The appearance of the computer aided automatic diagnosis system solves this problem. In this paper, a weakly supervised cervical cancer nest image identification approach using Conjugated Attention Mechanism and Visual Transformer (CAM-VT), which can analyze pap slides quickly and accurately. CAM-VT proposes conjugated attention mechanism and visual transformer modules for local and global feature extraction respectively, and then designs an ensemble learning module to further improve the identification capability. In order to determine a reasonable interpretation, comparative experiments are conducted on our datasets. The average accuracy of the validation set of three repeated experiments using CAM-VT framework is 88.92%, which is higher than the optimal result of 22 well-known deep learning models. Moreover, we conduct ablation experiments and extended experiments on Hematoxylin and Eosin stained gastric histopathological image datasets to verify the ability and generalization ability of the framework. Finally, the top 5 and top 10 positive probability values of cervical nests are 97.36% and 96.84%, which have important clinical and practical significance. The experimental results show that the proposed CAM-VT framework has excellent performance in potential cervical cancer nest image identification tasks for practical clinical work., Competing Interests: Declaration of Competing Interest We state that there is no Conflict of Interest in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Background and Purpose: Colorectal cancer has become the third most common cancer worldwide, accounting for approximately 10% of cancer patients. Early detection of the disease is important for the treatment of colorectal cancer patients. Histopathological examination is the gold standard for screening colorectal cancer. However, the current lack of histopathological image datasets of colorectal cancer, especially enteroscope biopsies, hinders the accurate evaluation of computer-aided diagnosis techniques. Therefore, a multi-category colorectal cancer dataset is needed to test various medical image classification methods to find high classification accuracy and strong robustness., Methods: A new publicly available Enteroscope Biopsy Histopathological H&E Image Dataset (EBHI) is published in this paper. To demonstrate the effectiveness of the EBHI dataset, we have utilized several machine learning, convolutional neural networks and novel transformer-based classifiers for experimentation and evaluation, using an image with a magnification of 200×., Results: Experimental results show that the deep learning method performs well on the EBHI dataset. Classical machine learning methods achieve maximum accuracy of 76.02% and deep learning method achieves a maximum accuracy of 95.37%., Conclusion: To the best of our knowledge, EBHI is the first publicly available colorectal histopathology enteroscope biopsy dataset with four magnifications and five types of images of tumor differentiation stages, totaling 5532 images. We believe that EBHI could attract researchers to explore new classification algorithms for the automated diagnosis of colorectal cancer, which could help physicians and patients in clinical settings., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Associazione Italiana di Fisica Medica e Sanitaria. Published by Elsevier Ltd. All rights reserved.)

Background and Purpose: Colorectal cancer is a common fatal malignancy, the fourth most common cancer in men, and the third most common cancer in women worldwide. Timely detection of cancer in its early stages is essential for treating the disease. Currently, there is a lack of datasets for histopathological image segmentation of colorectal cancer, which often hampers the assessment accuracy when computer technology is used to aid in diagnosis., Methods: This present study provided a new publicly available Enteroscope Biopsy Histopathological Hematoxylin and Eosin Image Dataset for Image Segmentation Tasks (EBHI-Seg). To demonstrate the validity and extensiveness of EBHI-Seg, the experimental results for EBHI-Seg are evaluated using classical machine learning methods and deep learning methods., Results: The experimental results showed that deep learning methods had a better image segmentation performance when utilizing EBHI-Seg. The maximum accuracy of the Dice evaluation metric for the classical machine learning method is 0.948, while the Dice evaluation metric for the deep learning method is 0.965., Conclusion: This publicly available dataset contained 4,456 images of six types of tumor differentiation stages and the corresponding ground truth images. The dataset can provide researchers with new segmentation algorithms for medical diagnosis of colorectal cancer, which can be used in the clinical setting to help doctors and patients. EBHI-Seg is publicly available at: https://figshare.com/articles/dataset/EBHI-SEG/21540159/1., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Shi, Li, Hu, Chen, Chen, Fan, Gao, Jing, Lu, Ma, Ma, Meng, Tang, Sun, Grzegorzek, Qi, Teng and Li.)

Background and Objective: Gastric cancer is the fifth most common cancer globally, and early detection of gastric cancer is essential to save lives. Histopathological examination of gastric cancer is the gold standard for the diagnosis of gastric cancer. However, computer-aided diagnostic techniques are challenging to evaluate due to the scarcity of publicly available gastric histopathology image datasets., Methods: In this paper, a noble publicly available Gastric Histopathology Sub-size Image Database (GasHisSDB) is published to identify classifiers' performance. Specifically, two types of data are included: normal and abnormal, with a total of 245,196 tissue case images. In order to prove that the methods of different periods in the field of image classification have discrepancies on GasHisSDB, we select a variety of classifiers for evaluation. Seven classical machine learning classifiers, three Convolutional Neural Network classifiers, and a novel transformer-based classifier are selected for testing on image classification tasks., Results: This study performed extensive experiments using traditional machine learning and deep learning methods to prove that the methods of different periods have discrepancies on GasHisSDB. Traditional machine learning achieved the best accuracy rate of 86.08% and a minimum of just 41.12%. The best accuracy of deep learning reached 96.47% and the lowest was 86.21%. Accuracy rates vary significantly across classifiers., Conclusions: To the best of our knowledge, it is the first publicly available gastric cancer histopathology dataset containing a large number of images for weakly supervised learning. We believe that GasHisSDB can attract researchers to explore new algorithms for the automated diagnosis of gastric cancer, which can help physicians and patients in the clinical setting., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

A machine learning (ML) methodology that uses a histogram of interaction energies has been applied to predict gas adsorption in metal-organic frameworks (MOFs) using results from atomistic grand canonical Monte Carlo (GCMC) simulations as training and test data. In this work, the method is first extended to binary mixtures of spherical species, in particular, Xe and Kr. In addition, it is shown that single-component adsorption of ethane and propane can be predicted in good agreement with GCMC simulation using a histogram of the adsorption energies felt by a methyl probe in conjunction with the random forest ML method. The results for propane can be improved by including a small number of MOF textural properties as descriptors. We also discuss the most significant features, which provides physical insight into the most beneficial adsorption energy sites for a given application.

Acute pancreatitis (AP) is commonly accompanied by intense pain and is associated with high mortality rates. However, the effectiveness of existing therapeutic approaches remains unsatisfactory. Stem cell therapy, which can promote the regeneration of damaged tissue and alleviate systemic inflammatory responses, has brought new possibility for patients suffering from AP. In particular, hair follicle-derived mesenchymal stem cells (HF-MSCs) are proposed as a suitable cell source for treating pancreatic diseases, but further research on their effectiveness, safety, and underlying mechanisms is warranted for clinical implementation. In this work, the therapeutic potential of HF-MSC transplantation was studied in an L-arginine-induced AP rat model. HF-MSCs were extracted from infant Sprague-Dawley (SD) rats, expanded in vitro , and detected by flow cytometry. HF-MSCs were labeled by PKH67 and transplanted into rats with AP via tail vein injection. Serum specimens were collected at 24 h, 48 h, and 72 h after transplantation, and the levels of amylase, lipase, and anti-inflammatory factors, namely interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-α), were analyzed. Pancreas samples were collected and assayed by immunofluorescence and immunohistochemistry 1 week after transplantation to monitor the differentiation of HF-MSCs and the functional recovery of the damaged pancreas. Intravenously delivered rat HF-MSCs spontaneously homed to the damaged pancreas and expressed pancreatic progenitor cell markers, relieved inflammation, and boosted pancreatic regeneration. These findings indicate that HF-MSC transplantation is a potentially effective treatment for AP., Competing Interests: None., (AJTR Copyright © 2021.)

Background: Metal-organic frameworks (MOFs) possess adjustable aperture, high load capacities, tailorable structures, and excellent biocompatibilities for their use as drug delivery carries in cancer therapy. Until now, Zr-MOFs, in particular, combine optimal stability towards hydrolysis and post synthetic modification with low toxicity, and are widely studied for their excellentbiological performance., Introduction: This review comprises the exploration of Zr-MOFs as drug delivery devices (DDSs) with a focus on various new methods, including chemotherapy (CT), photodynamic therapy (PDT), photothermal therapy (PTT), sonodynamic therapy (SDT), radiotherapy, immunotherapy, gene therapy and related combined therapies, which all generate reactive oxygen species (ROS) to achieve high efficiency of tumor therapy., Conclusion: We described and summarized these pertinent examples of the therapeutic mechanisms and highlighted the antitumor effects of their biological application both in vitro and in vivo. The perspectives on their future applications and the analogous challenge of the Zr-MOFs materials are given., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Metal-organic frameworks (MOFs) with coordinatively unsaturated metal sites are appealing as adsorbent materials due to their tunable functionality and ability to selectively bind small molecules. Through the use of computational screening methods based on periodic density functional theory, we investigate O 2 and N 2 adsorption at the coordinatively unsaturated metal sites of several MOF families. A variety of design handles are identified that can be used to modify the redox activity of the metal centers, including changing the functionalization of the linkers (replacing oxido donors with sulfido donors), anion exchange of bridging ligands (considering μ-Br - , μ-Cl - , μ-F - , μ-SH - , or μ-OH - groups), and altering the formal oxidation state of the metal. As a result, we show that it is possible to tune the O 2 affinity at the open metal sites of MOFs for applications involving the strong and/or selective binding of O 2 . In contrast with O 2 adsorption, N 2 adsorption at open metal sites is predicted to be relatively weak across the MOF dataset, with the exception of MOFs containing synthetically elusive V 2+ open metal sites. As one example from the screening study, we predicted that exchanging the μ-Cl - ligands of M 2 Cl 2 (BBTA) (H 2 BBTA = 1 H ,5 H -benzo(1,2- d :4,5- d ')bistriazole) with μ-OH - groups would significantly enhance the strength of O 2 adsorption at the open metal sites without a corresponding increase in the N 2 affinity. Experimental investigation of Co 2 Cl 2 (BBTA) and Co 2 (OH) 2 (BBTA) confirms that the former exhibits weak physisorption of both N 2 and O 2 , whereas the latter is capable of chemisorbing O 2 at room temperature in a highly selective manner. The O 2 chemisorption behavior is attributed to the greater electron-donating character of the μ-OH - ligands and the presence of H-bonding interactions between the μ-OH - bridging ligands and the reduced O 2 adsorbate.

RNA catalysis is of fundamental importance to biology and yet remains ill-understood due to its complex nature. The multidimensional "problem space" of RNA catalysis includes both local and global conformational rearrangements, changes in the ion atmosphere around nucleic acids and metal ion binding, dependence on potentially correlated protonation states of key residues, and bond breaking/forming in the chemical steps of the reaction. The goal of this chapter is to summarize and apply multiscale modeling methods in an effort to target the different parts of the RNA catalysis problem space while also addressing the limitations and pitfalls of these methods. Classical molecular dynamics simulations, reference interaction site model calculations, constant pH molecular dynamics (CpHMD) simulations, Hamiltonian replica exchange molecular dynamics, and quantum mechanical/molecular mechanical simulations will be discussed in the context of the study of RNA backbone cleavage transesterification. This reaction is catalyzed by both RNA and protein enzymes, and here we examine the different mechanistic strategies taken by the hepatitis delta virus ribozyme and RNase A., (© 2015 Elsevier Inc. All rights reserved.)