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Dopamine modified peanut husks (PH/DA), a novel adsorbent, were investigated to enhance the adsorption capacity of dyes (neutral red, NR and crystal violet, CV) and fluoroquinolone antibiotics (ofloxacin, OFLX and enoxacin, ENO). Scanning electron microscopy (SEM), X-ray diffraction (XRD), Fourier transform infrared (FT-IR), thermo-gravimetric analysis and differential scanning calorimetry (TG-DSC) and Brunauer-Emmett-Teller (BET) method were used to characterize PH and PH/DA. The findings demonstrated that the physical and chemical properties of the peanut husks were changed after dopamine-modification. As for adsorption kinetics, NR adsorption properties were satisfactorily explained by the Elovich model, whereas CV adsorption processes suited to the pseudo-second order model. Both OFLX and ENO followed the pseudo-first order model. Isotherm data showed that CV and ENO conform to the Temkin model while NR and OFLX fitted better to the Langmuir model. The qmax of NR, CV, OFLX and ENO by PH/DA were 52.37, 45.92, 46.57 and 58.40 mg/g at 290 K, respectively, according to Langmuir model. The adsorbent maintained an adsorption efficiency of above 70% even after three adsorption-desorption cycles. These findings proved that PH/DA's successful development offers important insights into the production of sorbents for water treatment based on biomass. The adsorption of dyes and antibiotics on dopamine-modified peanut husk was investigated. The adsorbent was characterized by SEM, FTIR, XRD, XPS, BET and TG-DSC. Adsorption isotherm and kinetics models were fitted with the experimental data. Mechanism for the adsorption of dyes and antibiotics were elucidated. [ABSTRACT FROM AUTHOR]

Plastic greenhouses play an important role in vegetable cultivation in China. While evaluations have attributed perfluoroalkyl acid contamination in greenhouse vegetables primarily to irrigation water, the potential contribution from greenhouse plastic films has consistently been overlooked, despite PFAAs' long-standing use as anti-fogging agents. In this study, a comprehensive assessment of PFAA contamination was conducted in greenhouses at the Shouguang vegetable base in China, based on extensive environmental and crop sample collection, followed by analysis using LC-MS/MS. PFAAs are still used in greenhouse plastic film, and their migration to the surface water mist and the air inside the greenhouse was also observed. Elevated levels of PFAA pollution were found near the corner areas of greenhouses with longer service times, leading to further pollution of the soil and nearby vegetables. This is considered as the primary source which may have been caused by PFAAs migrating with condensation from the plastic film and accumulating for decades. However, polluted irrigation water still remains the dominate source of PFAAs in other areas inside the greenhouse. Based on our analysis, we conclude that PFAAs present in plastic films could be the primary contaminant source for vegetables in specific zones. This underscores the urgent need for heightened vigilance towards environmental pollution within agricultural facilities, which currently represent the most prevalent mode of intensive vegetable cultivation in China. [ABSTRACT FROM AUTHOR]

A study published in the journal Clinical & Translational Medicine suggests that analyzing microbial communities could be a useful tool for diagnosing and predicting the prognosis of pancreatic tumors. The researchers examined fecal and intratumor microbial samples from patients with pancreatic tumors and healthy volunteers. They discovered that specific bacteria in fecal samples could potentially serve as non-invasive biomarkers for early detection of pancreatic tumors. Furthermore, they observed differences in the microbial composition of pancreatic tissues between malignant and non-malignant tumors. These findings indicate that microbial profiling may offer a promising approach for improving the early detection and treatment of pancreatic tumors. [Extracted from the article]

Background: The status of the hypothalamic‐pituitary‐gonadal (HPG) axis is important for assessing the onset of physiological or pathological puberty. The reference standard gonadotropin‐releasing hormone (GnRH) stimulation test requires hospital admission and repeated blood samples. A simple noninvasive method would be beneficial. Objectives: To explore a noninvasive method for evaluating HPG axis activation in children using an MRI radiomics model. Study Type: Retrospective. Population: Two hundred thirty‐nine children (83 male; 3.6–14.6 years) with hypophysial MRI and GnRH stimulation tests, randomly divided a training set (168 children) and a test set (71 children). Field Strength/Sequence: 3.0 T, 3D isotropic fast spin echo (CUBE) T1‐weighted imaging (T1WI) sequences. Assessment: Radiomics features were extracted from sagittal 3D CUBE T1WI, and imaging signatures were generated using the least absolute shrinkage and selection operator (LASSO) with 10‐fold cross‐validation. Diagnostic performance for differential diagnosis of HPG status was compared between a radiomics model and MRI features (adenohypophyseal height [aPH] and volume [aPV]). Statistical Tests: Receiver operating characteristic (ROC) and decision curve analysis (DCA). A P value <0.05 was considered statistically significant. Results: Eight hundred fifty‐one radiomics features were extracted and reduced to 10 by the LASSO method in the training cohort. The radiomics model based on CUBE T1WI showed good performance in assessment of HPG axis activation with an area under the ROC curve (AUC) of 0.81 (95% CI: 0.71, 0.91) in the test set. The AUC of the radiomics model was significantly higher than that of aPH (0.81 vs. 0.65) but there was no significant difference compared to aPV (0.81 vs. 0.78, P = 0.58). In DCA analysis, the radiomics signature showed higher net benefit over the aPV and aPH models. Data Conclusions: The MRI radiomics model has potential to assess HPG axis activation status noninvasively, potentially providing valuable information in the diagnosis of patients with pathological puberty onset. Evidence Level: 4 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

With the major needs of rural revitalization and building industrialization, focusing on the pain points of rural architectural design, based on architectural computational design thinking, and the context of the era of AI, this research integrates the text-to-image and BIM technologies, proposes a computational design method for cloud-based rural architectural design, and builds a cloud computing design platform for rural buildings. It establishes an industrial win-win model from the data chain ecosystem, takes advantage of AI technology, coordinates the process of design, construction, operation and maintenance, and introduces the practice of research results with a case study, in order to promote the informatization upgrade and industrialization transformation of rural architectural design. [ABSTRACT FROM AUTHOR]

BACKGROUND. The coronavirus disease 2019 (COVID-19) rapidly progressed to a global pandemic. Although some patients totally recover from COVID-19 pneumonia, the disease's long-term effects on the brain still need to be explored. METHODS. We recruited 51 patients with 2 subtypes of COVID-19 (19 mild and 32 severe) with no specific neurological manifestations at the acute stage and no obvious lesions on the conventional MRI 3 months after discharge. Changes in gray matter morphometry, cerebral blood flow (CBF), and white matter (WM) microstructure were investigated using MRI. The relationship between brain imaging measurements and inflammation markers was further analyzed. RESULTS. Compared with healthy controls, the decrease in cortical thickness/CBF and the changes in WM microstructure were more severe in patients with severe disease than in those with mild disease, especially in the frontal and limbic systems. Furthermore, changes in brain microstructure, CBF, and tract parameters were significantly correlated (P < 0.05) with the inflammatory markers C-reactive protein, procalcitonin, and interleukin 6. CONCLUSION. Indirect injury related to inflammatory storm may damage the brain, altering cerebral volume, CBF, and WM tracts. COVID-19-related hypoxemia and dysfunction of vascular endothelium may also contribute to neurological changes. The abnormalities in these brain areas need to be monitored during recovery, which could help clinicians understand the potential neurological sequelae of COVID-19. FUNDING. Natural Science Foundation of China., Introduction The highly infectious coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) rapidly progressed to a global pandemic and unleashed widespread concern around the world [...]

Wavefront encoding (WFC) is a depth-of-field (DOF) extension technology that combines optical encoding and digital decoding. The system extends DOF at the expense of intermediate image quality and then decodes it through an image restoration algorithm to obtain a clear image. Affected by point spread differences, traditional decoding methods are often accompanied by artifacts and noise amplification problems. In this paper, based on lens-combined modulated wavefront coding (LM-WFC), we simulate the imaging process under different object distances, generate a simulation data set of WFC, and train a multi-scale convolutional neural network. The simulation experiment proves that this method can effectively reduce artifacts and improve image clarity. In addition, we used the LM-WFC camera to obtain real scene images with different target distances for experiments. The decoding results showed that the network model can enhance the quality of image restoration and generate clear images that are more in line with human vision, which is conducive to the improvement and practical application of wavefront coding systems. [ABSTRACT FROM AUTHOR]