To identify important MRI features to differentiate hepatic mucinous cystic neoplasms from septated hepatic cysts based on random forest.

OBJECTIVE: To identify important MRI features to differentiate hepatic mucinous cystic neoplasms (MCN) from septated hepatic cysts (HC) using random forest and compared with logistic regression algorithm. METHODS: Pathologically diagnosed hepatic cysts and hepatic MCNs with pre-operative contrast-enhanced MRI in our hospital from 2010 to 2023 were collected and only septated lesions on enhanced MRI were enrolled. A total of 21 septated HC and 18 MCNs were included in this study. Eighteen MRI features were analyzed and top important features were identified based on random forest (RF) algorithm. The results were evaluated by the prediction performance of a RF model combining the important features and compared with the performance of the logistic regression (LR) algorithm. Finally, for each identified feature, diagnostic probability, sensitivity, and specificity were calculated and compared. RESULTS: Four variables, i.e., the septation arising from wall without indentation, multiseptate, intracapsular cyst sign, and solitary lesion were extracted as top important features with significance for MCNs by the random forest algorithm. The RF model using these variables had an AUC of 0.982 (0.95CI, 0.950-1.000), compared with the LR model based on two identified features with AUC of 0.931 (0.95CI, 0.846-1.000), p = 0.202. Among the four important features, multiseptate had the highest specificity (95.2%) and good sensitivity (72.2%, lower than the septation from wall without indentation, 94.4%) to diagnose MCNs. CONCLUSION: Four out of 18 MRI features were extracted as reliably important factors to differ hepatic MCNs from septated HC. The combination of these four features in a RF model could achieve satisfactory diagnostic efficacy.

Facile synthesis of porphyrin-MOFs with high photo-Fenton activity to efficiently degrade ciprofloxacin.

The slow conversion of Fe(Ⅱ)/Fe(III) cycle was largely limited the degradation efficiency of many photo-Fenton systems. Herein, four Fe-MOFs nanorods (namely Fe-TCPP-1, Fe-TCPP-2, Fe-TCPP-3, Fe-TCPP-4) with decreasing length-diameter ratios were synthesized in a household microwave oven, using photosensitizer porphyrin and iron ions with Fenton activity as building blocks. Among them, the Fe-TCPP-3 exhibited high photogenerated electron-hole (e--h+) separation efficiency and largest pore structure, endowing Fe-TCPP-3 with superior photo-Fenton property. In addition, Fe-TCPP-3 based photo-Fenton system was applied to efficiently degrade antibiotic ciprofloxacin (CIP) under neutral condition, due to the continuously generated reactive species (h+, e-, OH·, O2·-, 1O2) in Fe-TCPP-3 under visible-light irradiation. With irradiation for 30 min, the degradation efficiency of the system could reach about 73 %, which was about 26-fold towards the system without light irradiation. This study paved a way to modulating the photo-Fenton activity of MOF-based catalysts.

A catalyst-free co-reaction system of long-lasting and intensive chemiluminescence applied to the detection of alkaline phosphatase.

A catalyst-free co-reaction luminol-H2O2-K2S2O8 chemiluminescence (CL) system was developed, with long-life and high-intensity emission, and CL emission lasting for 6 h. A possible mechanism of persistent and intense emission in this CL system was discussed in the context of CL spectra, cyclic voltammetry, electron spin resonance (ESR), and the effects of radical scavengers on luminol-H2O2-K2S2O8 system. H2O2 and K2S2O8 co-reactants can promote each other to continuously generate corresponding radicals (OH•, 1O2, O2•-, SO4•-) that trigger the CL emission of luminol. H2O2 can also be constantly produced by the reaction of K2S2O8 and H2O to further extend the persistence of this CL system. CL emission can be quenched via ascorbic acid (AA), which can be generated through hydrolysis reaction of L-ascorbic acid 2-phosphate trisodium salt (AAP) and alkaline phosphatase (ALP). Next, a CL-based method was established for the detection of ALP with good linearity from 0.08 to 5 U·L-1 and a limit of detection of 0.049 U·L-1. The proposed method was used to detect ALP in human serum samples.

An ultrathin 2D Yb(III) metal-organic frameworks with strong electrochemiluminescence as a "on-off-on" platform for detection of picric acid and berberine chloride form.

To investigate the strong electrochemiluminescence (ECL) of ultrathin two dimensional metal-organic frameworks (2D MOFs) is crucial. In this work, we reported the strong ECL behavior of 2D Yb-MOFs, which exhibited thickness-dependent ECL. The thinner the 2D Yb-MOFs, the stronger the ECL signals. The corresponding ECL emission mechanism was investigated in detail, which was ascribed to the thinner 2D Yb-MOF with larger specific surface area, provided more luminophores, better electronic conductivity and superior fluorescence quantum yield, which yielded a higher ECL intensity. Considering the excellent ECL performances above, the ultrathin 2D Yb-MOF-1 was selected as new ECL emitter so that a sensor could be fabricated to realize the "on-off-on" detection of picric acid (PA) and berberine chloride form (BCF). The proposed sensor strategy exhibited a good analytical performance, where the linear range for PA detection was from 0.1 µM to 1 µM with a limit of 81.3 nM, and that for BCF detection from 0.05 µM to 1 µM with a limit of 36.5 nM. This study carves out a novel avenue for exploiting excellent ECL materials.

Ultrasensitive ratiometric electrochemiluminescence for detecting atxA mRNA using luminol-encapsulated liposome as effectively amplified signal labels.

It is an advantageous way to quickly identify the toxicity of Bacillus anthracis (B. anthracis) by detecting the transcription product of the atxA gene. Herein, a novel ultrasensitive ratiometric electrochemiluminescence (ECL) biosensor with competitive mechanism and double amplified signal ways was proposed for detecting the atxA mRNA. The K2S2O8 was used as cathodic emitter and silver metal-organic gels (AgMOG) was used as ECL enhancer. The AgMOG could accelerate the electro-catalytic reduction of S2O82- to SO4˙-, which reacted with dissolved oxygen, resulting in strong cathodic ECL. Meanwhile, luminol was encapsulated in liposome as anodic amplified signal labels and the luminol anion radical also reacted with dissolved oxygen to create the anodic ECL emission. We immobilized luminol-encapsulated liposomes on the surface of AgMOG through the hybridization of DNA and mRNA. This would provide a competitive mechanism involving dissolved oxygen between K2S2O8 and luminol. Benefiting from the competitive mechanism and amplified signal ways, this ratiometric biosensor achieved a wide linear relationship range from 10 to 300 fM with a low limit of detection (8.13 fM). Considering the accessible operation, favorable performance, and high universality of this strategy, this work may be used to analyze other mRNAs of bacteria.

Prediction of COVID-19 Severity Using Chest Computed Tomography and Laboratory Measurements: Evaluation Using a Machine Learning Approach.

BACKGROUND: Most of the mortality resulting from COVID-19 has been associated with severe disease. Effective treatment of severe cases remains a challenge due to the lack of early detection of the infection. OBJECTIVE: This study aimed to develop an effective prediction model for COVID-19 severity by combining radiological outcome with clinical biochemical indexes. METHODS: A total of 46 patients with COVID-19 (10 severe, 36 nonsevere) were examined. To build the prediction model, a set of 27 severe and 151 nonsevere clinical laboratory records and computerized tomography (CT) records were collected from these patients. We managed to extract specific features from the patients' CT images by using a recently published convolutional neural network. We also trained a machine learning model combining these features with clinical laboratory results. RESULTS: We present a prediction model combining patients' radiological outcomes with their clinical biochemical indexes to identify severe COVID-19 cases. The prediction model yielded a cross-validated area under the receiver operating characteristic (AUROC) score of 0.93 and an F1 score of 0.89, which showed a 6% and 15% improvement, respectively, compared to the models based on laboratory test features only. In addition, we developed a statistical model for forecasting COVID-19 severity based on the results of patients' laboratory tests performed before they were classified as severe cases; this model yielded an AUROC score of 0.81. CONCLUSIONS: To our knowledge, this is the first report predicting the clinical progression of COVID-19, as well as forecasting severity, based on a combined analysis using laboratory tests and CT images.

Meningitic Escherichia coli-induced upregulation of PDGF-B and ICAM-1 aggravates blood-brain barrier disruption and neuroinflammatory response.

BACKGROUND: Blood-brain barrier (BBB) disruption and neuroinflammation are considered key mechanisms of pathogenic Escherichia coli invasion of the brain. However, the specific molecules involved in meningitic E. coli-induced BBB breakdown and neuroinflammatory response remain unclear. Our previous RNA-sequencing data from human brain microvascular endothelial cells (hBMECs) revealed two important host factors: platelet-derived growth factor-B (PDGF-B) and intercellular adhesion molecule-1 (ICAM-1), which were significantly upregulated in hBMECs after meningitic E. coli infection. Whether and how PDGF-B and ICAM-1 contribute to the development of E. coli meningitis are still unclear. METHODS: The western blot, real-time PCR, enzyme-linked immunosorbent assay, immunohistochemistry, and immunofluorescence were applied to verify the significant induction of PDGF-B and ICAM-1 by meningitic E. coli in vivo and in vitro. Evan's blue assay and electric cell-substrate impedance sensing assay were combined to identify the effects of PDGF-B on BBB permeability. The CRISPR/Cas9 technology, cell-cell adhesion assay, and electrochemiluminescence assay were used to investigate the role of ICAM-1 in neuroinflammation subversion. RESULTS: We verified the significant induction of PDGF-B and ICAM-1 by meningitic E. coli in mouse as well as monolayer hBMECs models. Functionally, we showed that the increase of PDGF-B may directly enhance the BBB permeability by decreasing the expression of tight junction proteins, and the upregulation of ICAM-1 contributed to neutrophils or monocytes recruitment as well as neuroinflammation subversion in response to meningitic E. coli infection. CONCLUSIONS: Our findings demonstrated the roles of PDGF-B and ICAM-1 in mediating bacterial-induced BBB damage as well as neuroinflammation, providing new concepts and potential targets for future prevention and treatment of bacterial meningitis.

Terbium(III) Organic Gels: Novel Antenna Effect-Induced Enhanced Electrochemiluminescence Emitters.

Metal organic gels (MOGs) have emerged as a new class of smart soft materials with superb luminescence properties and have attracted tremendous attention in various aspects. However, the electrochemiluminescence (ECL) behavior of MOGs has not been reported yet. In this work, cathode electrochemiluminescence (ECL) emission of terbium(III) organic gels (TOGs) was reported for the first time with potassium persulfate (K2S2O8) as an efficient coreactant. TOGs were synthesized by a facile one-step strategy, mixing terbium ions (Tb3+) and the ligand 4'-(4-carboxyphenyl)-2,2':6',2''-terpyridine (Hcptpy) at room temperature. The possible strong green ECL emission mechanism was discussed in detail and ascribed to the external coreactant enhancement and internal antenna effect enhancement. Moreover, the promising application of TOGs in analytical chemistry was clarified by the ECL on-off detection of tetracycline. This remarkable discovery of ECL emission of TOGs may pioneer the application of MOGs in ECL fields.

Chronic lung disease, lung regeneration and future therapeutic strategies.

Chronic lung diseases have been recognized as one of the world's leading causes of death in recent decades. Lacking effective treatments brings the patients not only bad quality of life but also higher risk for lung cancer development. By increasing the understanding of deeper mechanism of how lung develops and regenerates, researchers now focus on studying lung regenerative medicine, aiming to apply different and more efficient therapies to treat chronic lung diseases. This review will provide a wide picture of both basic lung developmental, regeneration mechanism and different designed strategies for treating chronic lung diseases in the future decades.

1,4-Benzoxazine-3(4H)-ones as potent inhibitors of platelet aggregation: design, synthesis and structure-activity relations.

A series of novel potentially platelet aggregation-inhibiting 1,4-benzoxazine-3(4H)-one derivatives was designed and synthesized through Smiles rearrangement, reduction and acetylation reactions. The antiaggregatory activities of the target molecules on arterial blood samples from rabbits, expressed by IC50 values (µM), were then evaluated in vitro against ADP induced platelet aggregation. The favorable IC50 values of compound 8c (IC50=8.99 µM) and 8d (IC50=8.94 µM) indicated that these two compounds were the most potent molecules among all the synthesized compounds. A detailed molecular docking study to explore the interaction of compounds 8c and 8d with GP IIb/IIIa receptor showed that they these two compounds were docked into the active site of GPIIb/IIIa receptor. These results suggest that the 1,4-benzoxazine-3(4H)-one derivatives are promising lead compounds to develop new platelet aggregation inhibitors.