Ultrasound features and differential diagnosis for superficial nodular fasciitis.

BACKGROUND: Nodular fasciitis (NF) has nonspecific clinical manifestations and is often misdiagnosed as sarcoma. The investigations of imaging methods for NF were limited. OBJECTIVE: To analyze the ultrasound (US) features of NF, and to evaluate the diagnostic value of US for NF. MATERIALS AND METHODS: A total of 61 NF patients were recruited retrospectively, and 551 lesions in the subcutaneous fat layer were included for comparison. We evaluated the ultrasound features of the patients and divided the NF cases into three types. Chi-square test or Fisher exact test were conducted to detect the potential difference in the distributions of three types in the two groups. RESULTS: Among the 61 NF cases, 65.6% were in the upper extremities (n = 40). The proportion of type 1, 2, and 3 were 57.4%, 24.6%, and 18.0%, respectively. NF were significantly more likely locating in the upper extremities than the other soft tissue tumors (p < 0.001). Type 1 and type 2 of sonographic features were significantly more commonly observed in NF than other soft tissue tumors among the three types (p < 0.001). CONCLUSION: The type 1 and type 2 of US features can help to distinguish NF from other lesions. US has great potential to improve the diagnostic accuracy and reduce the unnecessary surgery.

Effect of dissolved oxygen on L-methionine production from glycerol by Escherichia coli W3110BL using metabolic flux analysis method.

L-Methionine is an essential amino acid in humans, which plays an important role in the synthesis of some important amino acids and proteins. In this work, metabolic flux of batch fermentation of L-methionine with recombinant Escherichia coli W3110BL was analyzed using the flux balance analysis method, which estimated the intracellular flux distributions under different dissolved oxygen conditions. The results revealed the producing L-methionine flux of 4.8 mmol/(g cell·h) [based on the glycerol uptake flux of 100 mmol/(g cell·h)] was obtained at 30% dissolved oxygen level which was higher than that of other dissolved oxygen levels. The carbon fluxes for synthesizing L-methionine were mainly obtained from the pathway of phosphoenolpyruvate to oxaloacetic acid [15.6 mmol/(g cell·h)] but not from the TCA cycle. Hence, increasing the flow from phosphoenolpyruvate to oxaloacetic acid by enhancing the enzyme activity of phosphoenolpyruvate carboxylase might be conducive to the production of L-methionine. Additionally, pentose phosphate pathway could provide a large amount of reducing power NADPH for the synthesis of amino acids and the flux could increase from 41 mmol/(g cell·h) to 51 mmol/(g cell·h) when changing the dissolved oxygen levels, thus meeting the requirement of NADPH for L-methionine production and biomass synthesis. Therefore, the following modification of the strains should based on the improvement of the key pathway and the NAD(P)/NAD(P)H metabolism.

Deep learning driven diagnosis of malignant soft tissue tumors based on dual-modal ultrasound images and clinical indexes.

Background: Soft tissue tumors (STTs) are benign or malignant superficial neoplasms arising from soft tissues throughout the body with versatile pathological types. Although Ultrasonography (US) is one of the most common imaging tools to diagnose malignant STTs, it still has several drawbacks in STT diagnosis that need improving. Objectives: The study aims to establish this deep learning (DL) driven Artificial intelligence (AI) system for predicting malignant STTs based on US images and clinical indexes of the patients. Methods: We retrospectively enrolled 271 malignant and 462 benign masses to build the AI system using 5-fold validation. A prospective dataset of 44 malignant masses and 101 benign masses was used to validate the accuracy of system. A multi-data fusion convolutional neural network, named ultrasound clinical soft tissue tumor net (UC-STTNet), was developed to combine gray scale and color Doppler US images and clinic features for malignant STTs diagnosis. Six radiologists (R1-R6) with three experience levels were invited for reader study. Results: The AI system achieved an area under receiver operating curve (AUC) value of 0.89 in the retrospective dataset. The diagnostic performance of the AI system was higher than that of one of the senior radiologists (AUC of AI vs R2: 0.89 vs. 0.84, p=0.022) and all of the intermediate and junior radiologists (AUC of AI vs R3, R4, R5, R6: 0.89 vs 0.75, 0.81, 0.80, 0.63; p <0.01). The AI system also achieved an AUC of 0.85 in the prospective dataset. With the assistance of the system, the diagnostic performances and inter-observer agreement of the radiologists was improved (AUC of R3, R5, R6: 0.75 to 0.83, 0.80 to 0.85, 0.63 to 0.69; p<0.01). Conclusion: The AI system could be a useful tool in diagnosing malignant STTs, and could also help radiologists improve diagnostic performance.

Benefit of Using Both Ultrasound Imaging and Clinical Information for Predicting Malignant Soft Tissue Tumors.

OBJECTIVE: Ultrasonography (US) is the primary imaging method for soft tissue tumors (STTs), the diagnostic performance of which still requires improvement. To achieve an accurate evaluation of STTs, we built the diagnostic nomogram for STTs using the clinical and US features of patients with STTs. METHODS: A total of 613 patients with 195 malignant and 418 benign STTs were retrospectively recruited. We used a blend of clinical and ultrasonic features, as well as exclusively US features, to develop two distinct diagnostic models for STTs: the clinical-US model and the US-only model, respectively. The two models were evaluated and compared by measuring their areas under the receiver operating characteristic curve (AUC), calibration, integrated discrimination improvement (IDI) and decision curve analysis. The performance of the clinical-US model was also compared with that of two radiologists. RESULTS: The clinical-US model had better diagnostic performance than the model based on US imaging features alone (AUCs of the clinical-US and US-only models: 0.95 [0.93-0.97] vs. 0.89 [0.87-0.92], p < 0.001; IDI of the two models: 0.15 ± 0.03, p < 0.001). The clinical-US model was also superior to the two radiologists in diagnosing STTs (AUCs of clinical-US model and two radiologists: 0.95 [0.93-0.97] vs. 0.79 [0.75-0.82] and 0.83 [0.80-0.85], p < 0.001). CONCLUSION: The diagnostic model based on clinical and US imaging features had high diagnostic performance in STTs, which could help identify malignant STTs for radiologists.

Viscoelastic Behavior and Phase Structure of High-Content SBS-Modified Asphalt.

To investigate the effect of styrene-butadiene-styrene (SBS) modifier content on the viscoelastic behavior of SBS-modified asphalt (SBSMA) at different temperatures and phase structures, the star SBS modifier was chosen to fabricate seven types of SBSMA with different contents. Multiple stress creep recovery (MSCR), linear amplitude sweep (LAS), and low-temperature frequency sweep tests were adopted to study the influence of SBS modifier content on the viscoelastic performance of SBSMA at high to low temperatures. The SBSMA's microstructure with different contents was investigated using a fluorescence microscope. The results indicated that the change in non-recoverable creep compliance and creep recovery rate was bounded by 4.5% content at high temperatures, with an apparent turning point. The changing slope of content at less than 4.5% was much higher than that of the content greater than 4.5%. At medium temperatures, the fatigue life of SBSMA increased exponentially with the rising modifier content. The rate of increase in fatigue life was the largest as the content increased from 4.5% to 6.0%. At low temperatures, the low-temperature viscoelastic property index G (60 s) of SBSMA decreased logarithmically as the modifier content increased. In terms of the microscopic phase structure, the SBS modifier gradually changed from the dispersed to the continuous phase state with the increasing SBS modifier content.

Calcium Carbonate Addition Improves L-Methionine Biosynthesis by Metabolically Engineered Escherichia coli W3110-BL.

L-Methionine (L-Met) is a sulfur-containing amino acid, which is one of the eight essential amino acids to human body. In this work, the fermentative production of L-Met with genetically engineered Escherichia coli W3110-BL in a 5-L fermentor was enhanced through supplement of Ca2+ into the fermentation medium. With the addition of 30 g/L calcium carbonate (CaCO3), the titer of L-Met and yield against glucose reached 1.48 g/L and 0.09 mol/mol glucose, 57.45% higher than those of the control, respectively. The flux balance analysis (FBA) revealed that addition of CaCO3 strengthened the tricarboxylic acid cycle and increased the intracellular ATP concentration by 39.28%. The re-distribution of carbon, ATP, and cofactors flux may collaborate to improve L-Met biosynthesis with E. coli W3110-BL. The regulation of citrate synthase and oxidative phosphorylation pathway was proposed to be important for overproduction of L-Met. These foundations provide helpful reference in the following metabolic modification or fermentation control for further improvement of L-Met biosynthesis.

Enhanced L-methionine production by genetically engineered Escherichia coli through fermentation optimization.

Microbial fermentation for L-methionine (L-Met) production based on natural renewable resources is attractive and challenging. In this work, the effects of medium composition and fermentation conditions were investigated to improve L-Met production by genetically engineered Escherichia coli MET-3. Statistical optimization techniques including Plackett-Burman (PB) design and Box-Behnken design (BBD) were adopted first to optimize the culture medium. Results of PB-designed experiments indicated that the culture medium components including glucose, yeast extract, KH2PO4, and MgSO4.7H2O had significant effects on L-Met biosynthesis. With their best-predicted concentration established by BBD (glucose 37.43 g/L, yeast extract 0.95 g/L, KH2PO4 1.82 g/L, and MgSO4.7H2O 4.51 g/L), L-Met titer was increased to 3.04 g/L from less than 2.0 g/L. For further enhancement of L-Met biosynthesis, the fermentation conditions of batch cultivation carried out in a 5-L fermentor were optimized, and the optimum results were obtained at an agitation rate of 300 rpm, medium pH of 7.0, and induction temperature of 28 °C. Based on the optimization parameters, fed-batch fermentation with the modified medium was conducted. As a result, great improvement of L-Met titer (12.80 g/L) and yield (0.13 mol/mol) were achieved, with an increase of 38.53% and 30.0% compared with those of the basal medium, respectively. Furthermore, higher L-Met productivity of 0.261 g/L/h was obtained, representing 2.13-fold higher in comparison to the original medium. The results may provide a helpful reference for further study on strain improvement and fermentation control.