Development and validation of a deep learning model for multicategory pneumonia classification on chest computed tomography: a multicenter and multireader study.

Background: Accurate diagnosis of pneumonia is vital for effective disease management and mortality reduction, but it can be easily confused with other conditions on chest computed tomography (CT) due to an overlap in imaging features. We aimed to develop and validate a deep learning (DL) model based on chest CT for accurate classification of viral pneumonia (VP), bacterial pneumonia (BP), fungal pneumonia (FP), pulmonary tuberculosis (PTB), and no pneumonia (NP) conditions. Methods: In total, 1,776 cases from five hospitals in different regions were retrospectively collected from September 2019 to June 2023. All cases were enrolled according to inclusion and exclusion criteria, and ultimately 1,611 cases were used to develop the DL model with 5-fold cross-validation, with 165 cases being used as the external test set. Five radiologists blindly reviewed the images from the internal and external test sets first without and then with DL model assistance. Precision, recall, F1-score, weighted F1-average, and area under the curve (AUC) were used to evaluate the model performance. Results: The F1-scores of the DL model on the internal and external test sets were, respectively, 0.947 [95% confidence interval (CI): 0.936-0.958] and 0.933 (95% CI: 0.916-0.950) for VP, 0.511 (95% CI: 0.487-0.536) and 0.591 (95% CI: 0.557-0.624) for BP, 0.842 (95% CI: 0.824-0.860) and 0.848 (95% CI: 0.824-0.873) for FP, 0.843 (95% CI: 0.826-0.861) and 0.795 (95% CI: 0.767-0.822) for PTB, and 0.975 (95% CI: 0.968-0.983) and 0.976 (95% CI: 0.965-0.986) for NP, with a weighted F1-average of 0.883 (95% CI: 0.867-0.898) and 0.846 (95% CI: 0.822-0.871), respectively. The model performed well and showed comparable performance in both the internal and external test sets. The F1-score of the DL model was higher than that of radiologists, and with DL model assistance, radiologists achieved a higher F1-score. On the external test set, the F1-score of the DL model (F1-score 0.848; 95% CI: 0.824-0.873) was higher than that of the radiologists (F1-score 0.541; 95% CI: 0.507-0.575) as was its precision for the other three pneumonia conditions (all P values <0.001). With DL model assistance, the F1-score for FP (F1-score 0.541; 95% CI: 0.507-0.575) was higher than that achieved without assistance (F1-score 0.778; 95% CI: 0.750-0.807) as was its precision for the other three pneumonia conditions (all P values <0.001). Conclusions: The DL approach can effectively classify pneumonia and can help improve radiologists' performance, supporting the full integration of DL results into the routine workflow of clinicians.

Systemic chemical characterization of Lemna minor by UHPLC-Q-Exactive Orbitrap MS coupled with parallel reaction monitoring.

Lemna minor L. (LM) has been used for measles opacity, rubella itching, edema, and oliguria, and the main active ingredients were flavonoids, namely, apigenin, apigenin-7-O-glucoside, and luteolin-7-O-glucoside. However, few systematic analyses of their constituents have been performed; thus, it was necessary to establish a fast and efficient method to identify the chemical composition of LM. In this study, the UHPLC-Q-Exactive Orbitrap mass spectrometry coupled with parallel reaction monitoring was established. Finally, a total of 112 constituents, including 30 dipeptides, 28 nucleosides, 11 amino acids, 10 organic acids, 10 flavonoids, and 23 other compounds, were identified by MS, diagnostic fragment ions, and retention time. One hundred one of those chemicals were first found in LM, which was very beneficial for the further development and utilization of nutriments and the medicinal use of LM.

Regional homogeneity alterations in multifrequency bands in patients with extracranial multi-organ tuberculosis: a prospective cross-sectional study.

Background: This study aimed to clarify the spontaneous neural activity in the conventional frequency band (0.01-0.08 Hz) and 2 subfrequency bands (slow-4: 0.027-0.073 Hz; slow-5: 0.01-0.027 Hz) in patients with extracranial multi-organ tuberculosis (EMTB) through regional homogeneity (ReHo) analysis. Methods: In all, 32 patients with EMTB and 31 healthy controls (HCs) were assessed by resting-state functional magnetic resonance imaging (rs-fMRI) scans to clarify the abnormal spontaneous neural activity through ReHo analysis in the conventional frequency band and 2 subfrequency bands. Results: Compared with the HCs, the patients with EMTB exhibited decreased ReHo in the left postcentral gyrus [t=-4.79; 95% confidence interval (CI): -0.79 to -0.31] and the left superior cerebellum (t=-4.45; 95% CI: -0.54 to -0.21) in the conventional band. Conversely, increased ReHo was observed in the right middle occipital gyrus (t=3.94; 95% CI: 0.18-0.53). In the slow-4 band, patients with EMTB only exhibited decreased ReHo in the superior cerebellum (t=-4.69; 95% CI: -0.54 to -0.22); meanwhile, in the slow-5 band, these patients exhibited decreased ReHo in the right postcentral gyrus (t=-3.76; 95% CI: -0.74 to -0.21) and the left superior cerebellum (t=-5.20, 95% CI: -0.72 to -0.31). After Bonferroni correction, no significant correlation was observed between the ReHo values in clusters showing significant between-group differences and cognitive test scores. Conclusions: ReHo showed abnormal synchronous neural activity in patients with EMTB in different frequency bands, which provides a novel understanding of the pathological mechanism of EMTB.

A Systematic Method for the Identification of Aporphine Alkaloid Constituents in Sabia schumanniana Diels Using UHPLC-Q-Exactive Orbitrap/Mass Spectrometry

Sabia schumanniana Diels (SSD) is a plant whose stems are used in traditional folk medicine for the treatment of lumbago and arthralgia. Previous studies have revealed chemical constituents of SSD, including triterpenoids and aporphine alkaloids. Aporphine alkaloids contain a variety of active components, which might facilitate the effective treatment of lumbago and arthralgia. However, only 5-oxoaporphine (fuseine) has been discovered in SSD to date. In this study, we sought to systematically identify the aporphine alkaloids in SSD. We established a fast and reliable method for the detection and identification of these aporphine alkaloids based on ultra-high-performance liquid chromatography (UHPLC)-Q-Exactive-Orbitrap/mass spectrometry combined with parallel reaction monitoring (PRM). We separated all of the analyzed samples using a Thermo Scientific Hypersil GOLD™ aQ C18 column (100 mm × 2.1 mm, 1.9 µm). Finally, we identified a total of 70 compounds by using data such as retention times and diagnostic ions. No fewer than 69 of these SSD aporphine alkaloids have been reported here for the first time. These findings may assist in future studies concerning this plant and will ultimately contribute to the research and development of new drugs.

Low serum calcium and phosphorus and their clinical performance in detecting COVID-19 patients.

BACKGROUND: This study aimed to evaluate the clinical performance of low serum calcium and phosphorus in discriminative diagnosis of the severity of patients with coronavirus disease 2019 (COVID-19). We conducted a single-center hospital-based study and consecutively recruited 122 suspected and 104 confirmed patients with COVID-19 during January 24 to April 25, 2020. Clinical risk factors of COVID-19 were identified. The discriminative power of low calcium and phosphorus regarding the disease severity was evaluated. Low calcium and low phosphorus are more prevalent in severe or critical COVID-19 patients than moderate COVID-19 patients (odds ratio [OR], 15.07; 95% confidence interval [CI], 1.59-143.18 for calcium; OR, 6.90; 95% CI, 2.43-19.64 for phosphorus). The specificity in detecting the severe or critical patients among COVID-19 patients reached 98.5% (95% CI, 92.0%-99.7%) and 84.8% (95% CI, 74.3%-91.6%) by low calcium and low phosphorus, respectively, albeit with suboptimal sensitivity. Calcium and phosphorus combined with lymphocyte count could obtain the best discriminative performance for the severe COVID-19 patients (area under the curve [AUC] = 0.80), and combined with oxygenation index was promising (AUC = 0.71). Similar discriminative performances of low calcium and low phosphorus were found between suspected and confirmed COVID-19 patient. Low calcium and low phosphorus could indicate the severity of COVID-19 patients, and may be utilized as promising clinical biomarkers for discriminative diagnosis.

New and Efficient Electrocatalyst for Hydrogen Production from Water Splitting: Inexpensive, Robust Metallic Glassy Ribbons Based on Iron and Cobalt.

Efficient, stable electrocatalysts are required to promote the hydrogen evolution reaction (HER) to obtain hydrogen as a clean, sustainable fuel via water splitting. In the present work, ribbons of the metallic glass Fe40Co40P13C7 were produced using a conventional melt-spinning technique and assessed as electrocatalysts for HER. In 0.5 M H2SO4, these ribbons generated an overpotential of 118 mV at a current density of 10 mA cm-2. This overpotential remained essentially constant over 20 h under these conditions. On the basis of the excellent properties, these glassy ribbons represent a new type of highly active, robust HER catalyst suitable for practical applications.

Efficient degradation of rhodamine B using Fe-based metallic glass catalyst by Fenton-like process.

An efficient heterogeneous catalyst, Fe-based metallic glass (Fe­Si­B amorphous ribbon), was successfully prepared for Fenton-like degradation of rhodamine B (RhB) by a melt-spinning method. The catalyst was characterized using XRD and SEM. The effects of various reaction parameters such as H2O2 dosage, temperature, initial pH value, Fe­Si­B dosage and initial RhB concentration on the degradation of RhB were studied. Almost complete degradation of RhB (20 mg L−1) was achieved within only 10 min by 0.5 g L−1 Fe­Si­B catalyst and 1.6 mM H2O2 at pH 3.0 at 295 K. Kinetic analyses showed that the degradation process could be described by a pseudo-first-order kinetic model. The catalytic stability was also investigated and it was found that the Fe­Si­B catalyst exhibited good structural stability and no loss of performance even after three cycles. It was concluded that the Fe­Si­B amorphous ribbon was a potential heterogeneous Fenton-like catalyst for industrial wastewater treatment.

Stable aqueous dispersions of graphene prepared with hexamethylenetetramine as a reductant.

Highly stable graphene aqueous dispersions were achieved by chemical reduction of graphene oxide with an environmentally friendly reagent of hexamethylenetetramine (HMTA). By this method, chemical reduction as well as dispersion of graphene can be carried out in one step without the need of organic stabilizers or pH control. The as-synthesized products were characterized by Fourier transform infrared spectroscopy, ultraviolet-visible spectroscopy, X-ray diffraction, Raman spectroscopy, atomic force microscopy, scanning and transmission electron microscopy, and thermogravimetry and differential scanning calorimetry. It is revealed that the bulk of the oxygen-containing functional groups were removed from graphene oxide via HMTA reduction, and stable aqueous colloidal dispersions of graphene have a concentration up to ca. 0.65mg/mL. Moreover, it is found that the freshly precipitated graphene nanosheets can be re-dispersed in water with simple ultrasonic treatment. A mechanism for the formation of stable graphene colloidal dispersions is proposed. This simple and green approach should find practical applications in the preparation of graphene-based nanocomposites with a facile and low-cost solution processing technique.