Diffusion tensor magnetic resonance imaging in the gradingof liver fibrosis associated with congenital ductal plate malformations

Purpose: Liver biopsy is still the standard method for the diagnosis of ductal plate malformations (DPM). However, it is an invasive tool. Magnetic resonance imaging (MRI) has shown its accuracy in the diagnosis of this pathology. Herein, a study was conducted to elucidate the role of diffusion MRI parameters in predicting the degree of hepatic fibrosis. Material and methods: This prospective study included 29 patients with DPM and 20 healthy controls. Both groups underwent diffusion tensor magnetic resonance imaging (DT-MRI), and its parameters were compared between patients and controls, and then they were correlated with the degree of liver fibrosis in the patient group. Results: All patients with DPM, whatever its type, expressed a significantly lower hepatic apparent diffusion coefficient (ADC) compared to controls. However, fractional anisotropy (FA) showed no significant difference between them. The ADC value of 1.65 × 10-3 mm2/s had sensitivity and specificity of 82.1% and 90%, respectively, in differentiating DPM patients from healthy controls. It was evident that patients with higher fibrosis grades had significantly lower hepatic ADC, indicating a negative correlation between ADC and the grade of hepatic fibrosis; rs = -0.901, p < 0.001. Conclusions: DT-MRI showed good efficacy in the diagnosis of congenital DPM. Moreover, ADC could be applied to monitor the degree of liver fibrosis rather than the invasive liver biopsy. No significant correlation was noted between the FA and the grades of liver fibrosis

The additive value of diffusion tensor imaging in the determination of perianal fistula activity

Abstract Background Although the activity of the perianal fistula has been evaluated before by MRI in the literature, limited diffusion tensor magnetic resonance imaging (DT-MRI) studies are reported to date. Our study aimed to elucidate the role of DT-MRI in evaluating the activity state of the perianal fistula and the prediction of postoperative complications. We reviewed the data of 30 patients diagnosed with perianal fistula and referred them for an MRI diffusion study before the surgical intervention. Apparent diffusion coefficient (ADC) and fractional anisotropy (FA) were calculated for the fistulous area and the normal surrounding puborectalis as a control area. Results According to the presence of pus intraoperatively, patients were allocated into two groups: the active group (10 patients) and the inactive group (20 patients). FA and ADC measurements showed a significant decrease in association with the active disease when measured at the fistula site, and this was not observed in the normal surrounding tissues. The area under the curve (AUC) was 0.985 and 0.730 for the ADC and FA, respectively, when cutoff values of 1 × 10–3 mm2/s and 0.621 were applied, respectively. Adding the FA to the ADC increased the DT-MRI specificity to 95% in the determination of the active fistula. The combination between both FA and ADC increased the AUC to 0.785 with a sensitivity of 73.7% and specificity of 63.6% in the detection of postoperative complications. Conclusions DT-MRI could be used as a reliable diagnostic tool to differentiate patients with active perianal fistula disease from inactive ones and to predict the postoperative outcome

Neuroradiological value of high resolution magnetic resonance neurography (MRN) in the diagnosis of sciatic neuropathy presumably related to COVID-19

Background: In the context of sciatic neuropathy, there have been many etiologies and the need for differentiating between the possible underlying causes is an important matter for early diagnosis and management. COVID-19 has been associated with many peripheral neuropathies and sciatic neuropathy could be potentially a complication. Although, very rare with limited cases published in the literature to date. Methods: We investigated the role of MR neurography in evaluating sciatic neuropathy presumably post- COVID-19 infection in one of our cases after exclusion of other possible causes of sciatic neuropathy using STIR MR neurography. Results: Our STIR MR neurography demonstrated increased signal and size of the left sciatic nerve with 2ry muscular edema in the biceps femoris muscle in keeping radiologically with sciatic neuropathy. Conclusion: MR neurography has proven to be valuable in narrowing the differential diagnosis of the reported imaging findings and showed a very good correlation to the NCVs, laboratory investigations, and sural nerve biopsy. Although a very rare complication, COVID-19 could be a potential direct cause of sciatic neuropathy

Artificial neural network approach for prediction of AuNPs biosynthesis by Streptomyces flavolimosus, characterization, antitumor potency in-vitro and in-vivo against Ehrlich ascites carcinoma

Abstract Gold nanoparticles (AuNPs) have emerged as promising and versatile nanoparticles for cancer therapy and are widely used in drug and gene delivery, biomedical imaging, diagnosis, and biosensors. The current study describes a biological-based strategy for AuNPs biosynthesis using the cell-free supernatant of Streptomyces flavolimosus. The biosynthesized AuNPs have an absorption peak at 530–535 nm. The TEM images indicate that AuNPs were spherical and ranged in size from 4 to 20 nm. The surface capping molecules of AuNPs are negatively charged, having a Zeta potential of − 10.9 mV. FTIR analysis revealed that the AuNPs surface composition contains a variety of functional groups as –OH, C–H, N–, C=O, NH3 +, amine hydrochloride, amide group of proteins, C–C and C–N. The bioprocess variables affecting AuNPs biosynthesis were optimized by using the central composite design (CCD) in order to maximize the AuNPs biosynthesis. The maximum yield of AuNPs (866.29 µg AuNPs/mL) was obtained using temperature (35 °C), incubation period (4 days), HAuCl4 concentration (1000 µg/mL) and initial pH level 6. Comparison was made between the fitness of CCD versus Artificial neural network (ANN) approach based on their prediction and the corresponding experimental results. AuNPs biosynthesis values predicted by ANN exhibit a more reasonable agreement with the experimental result. The anticancer activities of AuNPs were assessed under both in vitro and in vivo conditions. The results revealed a significant inhibitory effect on the proliferation of the MCF-7 and Hela carcinoma cell lines treated with AuNPs with IC50 value of 13.4 ± 0.44 μg/mL and 13.8 ± 0.45 μg/mL for MCF-7 and Hela cells; respectively. Further, AuNPs showed potential inhibitory effect against tumor growth in tumor-bearing mice models. AuNPs significantly reduced the tumor volume, tumor weight, and decreased number of viable tumor cells in EAC bearing mice

Process optimization for gold nanoparticles biosynthesis by Streptomyces albogriseolus using artificial neural network, characterization and antitumor activities

Abstract Gold nanoparticles (GNPs) are highly promising in cancer therapy, wound healing, drug delivery, biosensing, and biomedical imaging. Furthermore, GNPs have anti-inflammatory, anti-angiogenic, antioxidants, anti-proliferative and anti-diabetic effects. The present study presents an eco-friendly approach for GNPs biosynthesis using the cell-free supernatant of Streptomyces albogriseolus as a reducing and stabilizing agent. The biosynthesized GNPs have a maximum absorption peak at 540 nm. The TEM images showed that GNPs ranged in size from 5.42 to 13.34 nm and had a spherical shape. GNPs have a negatively charged surface with a Zeta potential of − 24.8 mV. FTIR analysis identified several functional groups including C–H, –OH, C–N, amines and amide groups. The crystalline structure of GNPs was verified by X-ray diffraction and the well-defined and distinct diffraction rings observed by the selected area electron diffraction analysis. To optimize the biosynthesis of GNPs using the cell-free supernatant of S. albogriseolus, 30 experimental runs were conducted using central composite design (CCD). The artificial neural network (ANN) was employed to analyze, validate, and predict GNPs biosynthesis compared to CCD. The maximum experimental yield of GNPs (778.74 μg/mL) was obtained with a cell-free supernatant concentration of 70%, a HAuCl4 concentration of 800 μg/mL, an initial pH of 7, and a 96-h incubation time. The theoretically predicted yields of GNPs by CCD and ANN were 809.89 and 777.32 μg/mL, respectively, which indicates that ANN has stronger prediction potential compared to the CCD. The anticancer activity of GNPs was compared to that of doxorubicin (Dox) in vitro against the HeP-G2 human cancer cell line. The IC50 values of Dox and GNPs-based treatments were 7.26 ± 0.4 and 22.13 ± 1.3 µg/mL, respectively. Interestingly, treatments combining Dox and GNPs together showed an IC50 value of 3.52 ± 0.1 µg/mL, indicating that they targeted cancer cells more efficiently