[Study on the total flavonoid content and antioxidant activity of Morus nigra Linn. from different origins in Xinjiang].

OBJECTIVE: Optimization of the extraction process of total flavonoids from Morus nigra Linn. based on response surface design, to compare the differences in total flavonoid content of Morus nigra Linn. from different origins in Xinjiang and its relationship with antioxidant activity. METHODS: A one-way test was used to investigate the effects of ethanol volume fraction, material-liquid ratio, ultrasonic power and ultrasonic time on total flavonoid content analysis of Morus nigra Linn. , Box-Behnken response surface design optimisation was used to derive the optimal extraction process parameters. Meanwhile, the in vitro antioxidant activity of Morus nigra Linn. was evaluated by antioxidant activity indexes such as hydroxyl radical scavenging capacity and ferric ion reducing capacity. RESULTS: The optimal extraction condition was 45% ethanol by volume, 1∶20 g/mL material-liquid ratio, 300W ultrasound power and 60 min ultrasound time. The total flavonoid content of Morus nigra Linn. s from six origins was detected and the result showed that Kuche >Kashgar >Kuche Wuqia Town>Hetian >Ying jisha >Yutian, in which the total flavonoid content of mulberry in Kucha city was(27.159±0.091)mg/g. The difference in the total flavonoid content of Morus nigra Linn. s in different origicns was statistically significant(P<0.05). In vitro antioxidant activity analysis showed that the antioxidant activity of mulberry from Kuche and Hetian was stronger, and the hydroxyl radical scavenging capacity, ferric ion reducing capacity, and total antioxidant capacity of mulberry from various origins were statistically significant(P<0.05). The correlation analysis showed that the total flavonoid content of Morus nigra Linn. was correlated with the antioxidant capacity to improve the scavenging of hydroxyl radicals. CONCLUSION: The ultrasonic-assisted method of extracting total flavonoids from Morus nigra Linn. is simple, and the model constructed has a high degree of fit, which can better compare the total flavonoids content of Morus nigra Linn. from different origins in Xinjiang.

Dual-domain mean-reverting diffusion model-enhanced temporal compressive coherent diffraction imaging.

Temporal compressive coherent diffraction imaging is a lensless imaging technique with the capability to capture fast-moving small objects. However, the accuracy of imaging reconstruction is often hindered by the loss of frequency domain information, a critical factor limiting the quality of the reconstructed images. To improve the quality of these reconstructed images, a method dual-domain mean-reverting diffusion model-enhanced temporal compressive coherent diffraction imaging (DMDTC) has been introduced. DMDTC leverages the mean-reverting diffusion model to acquire prior information in both frequency and spatial domain through sample learning. The frequency domain mean-reverting diffusion model is employed to recover missing information, while hybrid input-output algorithm is carried out to reconstruct the spatial domain image. The spatial domain mean-reverting diffusion model is utilized for denoising and image restoration. DMDTC has demonstrated a significant enhancement in the quality of the reconstructed images. The results indicate that the structural similarity and peak signal-to-noise ratio of images reconstructed by DMDTC surpass those obtained through conventional methods. DMDTC enables high temporal frame rates and high spatial resolution in coherent diffraction imaging.

Characterization of phospholipidome in milk, yogurt and cream, and phospholipid differences related to various dairy processing methods.

Milk phospholipids have multiple health benefits, but the deficiency of detailed phospholipid profiles in dairy products brings obstacles to intake calculation and function evaluation of dairy phospholipids. In present study, 306 phospholipid molecular species were identified and quantified among 207 milk, yogurt and cream products using a HILIC-ESI-Q-TOF MS and a HILIC-ESI-QQQ MS. The phospholipid profiles of five mammals' milk show that camel milk contains the most abundant phosphatidylethanolamine, phosphatidylserine and sphingomyelin; cow, yak and goat milk have similar phospholipidomes, while buffalo milk contains abundant phosphatidylinositol. Fewer plasmalogens but more lyso-glycerolphospholipids were found in ultra-high-temperature (UHT) sterilized milk than in pasteurized milk, and higher proportions of lyso-glycerolphospholipid/total phospholipid were observed in both cream and skimmed/semi-skimmed milk than whole milk, indicating that UHT and skimming processes improve glycerolphospholipid degradation and phospholipid nutrition loss. Meanwhile, more diacyl-glycerolphospholipids and less of their degradation products make yogurt a better phospholipid resource than whole milk.

A Combined UWB/IMU Localization Method with Improved CKF.

Aiming at the problem that ultra-wide band (UWB) cannot be accurately localized in environments with large noise variations and unknown statistical properties, a combinatorial localization method based on improved cubature (CKF) is proposed. First, in order to overcome the problem of inaccurate local approximation or even the inability to converge due to the initial value not being set near the optimal solution in the process of solving the UWB position by the least-squares method, the Levenberg-Marquardt algorithm (L-M) is adopted to optimally solve the UWB position. Secondly, because UWB and IMU information are centrally fused, an adaptive factor is introduced to update the measurement noise covariance matrix in real time to update the observation noise, and the fading factor is added to suppress the filtering divergence to achieve an improvement for the traditional CKF algorithm. Finally, the performance of the proposed combined localization method is verified by field experiments in line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios, respectively. The results show that the proposed method can maintain high localization accuracy in both LOS and NLOS scenarios. Compared with the Extended Kalman filter (EKF), unbiased Kalman filter (UKF), and CKF algorithms, the localization accuracies of the proposed method in NLOS scenarios are improved by 25.2%, 18.3%, and 11.3%, respectively.

[Analysis on vitamin B_1 and vitamin B_2 proficiency testing assessment in China disease control and prevention system].

OBJECTIVE: To evaluate the detection ability of vitamin B_1 and vitamin B_(2 )in rice flour in the laboratories of disease control and prevention system, by conducting the proficiency testing(PT)activity. METHODS: Before the vitamin B_1 and vitamin B_2 quality control samples were distributed to the laboratories of disease control and prevention system, the uniformity and stability of samples were analyzed by one-way ANOVO respectively. High performance liquid chromatography(HPLC) method was required to determine vitamin B_1(GB 5009.84-2016: determination of vitamin B_1 in food, first method as reference). HPLC method was also required to determine vitamin B_2(GB 5009.85-2016: determination of vitamin B_2 in food, first method as reference). Robust statistics analysis of proficiency testing result was conducted to evaluate laboratory testing ability through Z score. RESULTS: A total of 43 laboratories completed the proficiency testing. In all of the laboratories participated in the determination of vitamin B_(1 )and vitamin B_2, the total satisfactory rate of vitamin B_1 was 88.4%, while vitamin B_2 was 86.0%. CONCLUSION: The ability of vitamin B_1 and vitamin B_2 detection in disease control and prevention system in China is better than expected, and the testing ability of a few laboratory needs to be improved.

Formate Might Be a Novel Potential Serum Metabolic Biomarker for Type 2 Diabetic Peripheral Neuropathy.

Background: As one of the most frequent complications of type 2 diabetes mellitus (T2DM), diabetic peripheral neuropathy (DPN) shows a profound impact on 50% of patients with symptoms of neuropathic pain, numbness and other paresthesia. No valid serum biomarkers for the prediction of DPN have been identified in the clinic so far. This study is to investigate the potential serum biomarkers for DPN firstly based on 1H-Nuclear Magnetic Resonance (1H-NMR)-based metabolomics technique. Methods: Thirty-six patients enrolled in this study were divided into two groups: 18 T2DM patients without DPN (T2DM group) and 18 T2DM patients with DPN (DPN group). Serum metabolites were measured via 1H-NMR spectroscopy. Bioinformatic approaches including principal component analysis (PCA), orthogonal partial least squares-discriminant analysis (OPLS-DA), independent sample t-test, Fisher's test, Pearson and Spearman correlation analysis, Stepwise multiple linear regression analysis and receiver operating characteristic (ROC) curve analysis were used to identify the potential altered serum biomarkers. Results: A total of 20 metabolites were obtained and further analyzed. Formate was identified as the only potential biomarker that decreased in the DPN group with statistical significance after multiple comparisons (p<0.05). Formate also displayed a negative relationship with some elevated clinical markers in DPN. ROC curve analysis showed a good discriminative ability for formate in DPN with an area under the curve (AUC) value of 0.981. Conclusion: Formate could be considered a potential serum metabolic biomarker for DPN. The reduced level of formate in DPN may be associated with mitochondrial dysfunction and gut microbiota alteration. Monitoring the level of serum formate would be an important strategy for the early diagnosis of DPN and a supplement of formate may be a promising treatment for DPN in the future.

Analysis of metabolites of bactrain camel milk in Alxa of China before and after fermentation with fermenting agent TR1 based on untargeted LC-MS/MS based metabolomics.

Camel milk produces many beneficial functional compounds and affects body health through metabolism. The differential metabolites of bactrain camel milk in Alxa before and after fermentation were identified by liquid chromatography-tandem mass spectrometry based metabolomics (LC-MS/MS). The differential metabolite pathway types were also identified in this paper. We obtained the following results that 148 and 82 differential metabolites were detected in positive and negative ion mode respectively, 85 differential metabolites were shown a significant upward trend and 63 with downward trend after fermentation in positive ion mode. Meanwhile, 32 differential metabolites characterized upward trend and 50 characterized downward trend in negative ion mode. The differential metabolites were mainly organic acids, amino acids, esters, vitamins and other substances contained in camel milk. Among them, most up-regulated substances had the functions of lowering blood pressure, lowering blood sugar, treatment of inflammation, antibiosis and other effects. Many harmful substances were significantly down-regulated after camel milk fermentation. However, there were also some metabolites whose prebiotic functions have been weakened by camel milk fermentation, which may provide reference values for healthcare function, exploitation and application of camel milk.

[Determination of 21 polyphenols in fruits by high performance liquid chromatography].

OBJECTIVE: To establish a high performance liquid chromatography(HPLC) method for simultaneous determination of flavonoids(epicatechin, isoorientin, eriocitrin, hyperoside, narirutin, naringin, hesperidin, neohesperidin, quercetin, didymin, naringenin and hesperetin), phenolic acids(gallic acid, chlorogenic acid, caffeic acid, ferulic acid, sinapic acid and p-coumaric acid), terpenoids(limonin), stilbenes(piceatannol and resveratrol) in fruits. METHODS: Add ethanol-water(4∶1, V/V) solution to the fruit pulp sample, ultrasonic extraction at 55 ℃ for 10 min, after centrifugation, the supernatant was dried and re-dissolved, and then eluted with ZORBAX Eclipse XDB-C_(18)(4.6 mm×100 mm, 3.5 µm) as chromatographic column, polyphenols are determined by HPLC under switching wavelength, and quantified by external standard method. RESULTS: The 21 polyphenols can be detected within 45 min and well separated from baseline, with linear correlation coefficients greater than 0.999, the detection limit of the method was 0.03-0.31 µg/g, and the limit of quantitation of the method was 0.09-1.03 µg/g. The intra-day precision was 0.5%-9.3%, the inter-day precision was 2.0%-9.6%. The recoveries of more than 90% polyphenols in the three fruits at three levels were between 80.0% and 119.8%. The relative standard deviation of spiked recoveries of three samples was less than 10.8%. The detection result of citrus, mango, blueberry, persimmon and other samples proved that the composition of polyphenols in different fruits was different. CONCLUSION: The method is sensitive, accurate and reproducible, and is suitable for the determination of polyphenols in fruits.

MBFQuant: A Multiplier-Bitwidth-Fixed, Mixed-Precision Quantization Method for Mobile CNN-Based Applications.

Deploying Convolutional Neural Network (CNN)-based applications to mobile platforms can be challenging due to the conflict between the restricted computing capacity of mobile devices and the heavy computational overhead of running a CNN. Network quantization is a promising way of alleviating this problem. However, network quantization can result in accuracy degradation and this is especially the case with the compact CNN architectures that are designed for mobile applications. This paper presents a novel and efficient mixed-precision quantization pipeline, called MBFQuant. It redefines the design space for mixed-precision quantization by keeping the bitwidth of the multiplier fixed, unlike other existing methods, because we have found that the quantized model can maintain almost the same running efficiency, so long as the sum of the quantization bitwidth of the weight and the input activation of a layer is a constant. To maximize the accuracy of a quantized CNN model, we have developed a Simulated Annealing (SA)-based optimizer that can automatically explore the design space, and rapidly find the optimal bitwidth assignment. Comprehensive evaluations applying ten CNN architectures to four datasets have served to demonstrate that MBFQuant can achieve improvements in accuracy of up to 19.34% for image classification and 1.12% for object detection, with respect to a corresponding uniform bitwidth quantized model.

[Determination of vitamin A, D and E in dishes by two-dimensional liquid chromatography].

OBJECTIVE: To establish a method for the simultaneous determination of vitamins A, D and E in dishes by two-dimensional liquid chromatography. METHODS: The samples were saponified and extracted with a mixture of ethyl acetate and n-hexane(3∶2, V/V)under the protection of antioxidants, and determined by two-dimensional liquid chromatography. The baseline separation of retinol, α-tocopherol, ß-tocopherol, γ-tocopherol, δ-tocopherol, and α-tocotrienols was achieved by using Alphasil pentafluorophenyl column(PFP, 150 mm×4.6 mm, 5 µm) as the one-dimensional column, and using water and methanol as mobile phases for gradient elution under the fluorescence detector. The separation detection of ergocalciferol and cholecalciferol from other impurities was achieved on the UV detector by Alphasil VC-C_(18) column(150 mm×4.6 mm, 3.5 µm) as the two-dimensional column. RESULTS: The baseline separation detection of retinol, ergocalciferol, cholecalciferol and five tocopherols was achieved. The compounds were linearly correlated within the set range, and the correlation coefficients were >0.999. The recovery rate of the method was between 85.4% and 106.4%. The detection limit of all-trans retinol was 0.7 µg/100 g, and the limit of quantitation was 2.4 µg/100 g. The limits of detection and quantification of tocopherols ranged from 1.1 to 2.5 µg/100 g and 3.6 to 8.3 µg/100 g. The detection limit of ergocalciferol and cholecalciferol was 0.3 µg/100 g, and the limit of quantification was 1.0 µg/100 g. In the end, finished dishes such as dry fried hairtail, braised mushroom, steamed egg with soy sauce, sweet and sour ribs were repeatedly measured by this method for six times, and the relative standard deviation was less than 10%. CONCLUSION: The method has the characteristics of simple operation, good repeatability, high accuracy and friendly to operators and ecological environment. It can realize the simultaneous typing detection of vitamins A, D and E in finished dishes.

Design of an Efficient CNN-based Cough Detection System on Lightweight FPGA.

Precisely and automatically detecting the cough sound is of vital clinical importance. Nevertheless, due to privacy protection considerations, transmitting the raw audio data to the cloud is not permitted, and therefore there is a great demand for an efficient, accurate, and low-cost solution at the edge device. To address this challenge, we propose a semi-custom software-hardware co-design methodology to help build the cough detection system. Specifically, we first design a scalable and compact convolutional neural network (CNN) structure that generates many network instances. Second, we develop a dedicated hardware accelerator to perform the inference computation efficiently, and then we find the optimal network instance by applying network design space exploration. Finally, we compile the optimal network and let it run on the hardware accelerator. The experimental results demonstrate that our model achieves 88.8% classification accuracy, 91.2% sensitivity, 86.5% specificity, and 86.5% precision, while the computation complexity is only 1.09M multiply-accumulation (MAC). Additionally, when implemented on a lightweight field programmable gate array (FPGA), the complete cough detection system only occupies 7.9K lookup tables (LUTs), 12.9K flip-flops (FFs), and 41 digital signal processing (DSP) slices, providing 8.3 GOP/s actual inference throughput and total power dissipation of 0.93 W. This framework meets the needs of partial application and can be easily extended or integrated into other healthcare applications.

A simple and versatile strategy for sensitive SIDA-UHPLC-MS/MS analysis of Alternaria toxins in olive oil.

Alternaria toxins are naturally occurring contaminants found in natural products. Given the prevalence of Alternaria toxins and the complexity of oil-rich matrices, achieving ultra-trace analysis has become a daunting task. A new sample pretreatment technique, i.e., cold-induced liquid-liquid microextraction combined with serially-coupled-columns for SIDA-UHPLC-MS/MS, was developed and reported for the first time. Theoretical and experimental investigations on the mechanism and key parameters revealed that the proposed method achieved simultaneous purification and enrichment in one-step sample extraction with a superior limit of quantitation (0.15-1.5 µg kg-1), without further sample manipulation, such as fat removal or solvent exchange procedures prior to LC-MS. The method was validated taking into consideration EU guidelines and showed acceptable linearity (r ≥ 0.9991), accuracy with recoveries between 75 and 114% and precision with RSD≤9.7% for all of the analytes studied. It was successfully applied to the analysis of twenty samples sourced from the Mediterranean region in order to gain first insights into Alternaria toxins contaminations in olive oils. This technical approach is well suited for large-scale studies in a high-throughput and cost-effective quality assurance laboratory environments, and it has the potential to detect ultra-trace levels of toxins in complex samples, which may lead to the development of new and sustainable sample preparation procedures.

[Development of nutrient profiling model include nutrients and food groups evaluation].

OBJECTIVE: To develop the nutrient profiling model based on the nutrition and health status of Chinese residents, and comprehensively evaluate the nutritional quality of food and dietary pattern. METHODS: Nutrient-and food group-indexes closely related to the main health problems of Chinese residents were screened and determined based on the level of evidence. Different food and dietary patterns were taken as examples to calculate the nutrient dense score. RESULTS: The nutrient indexes of this model included protein, dietary fiber, vitamin D, sodium, potassium, calcium, saturated fatty acid and sugar. Food group indexes included whole grain and legume, fruit, vegetable, soybean and nut. CONCLUSION: Nutrient profiling model included both nutrient-and food group-indexes could provide a more comprehensive evaluation on nutrient density of food and diet, and the rationality of diet align with dietary guidelines.

The Role of Campus Data in Representing Depression Among College Students: Exploratory Research.

BACKGROUND: Depression is a predominant feature of many psychological problems leading to extreme behaviors and, in some cases, suicide. Campus information systems keep detailed and reliable student behavioral data; however, whether these data can reflect depression and we know the differences in behavior between depressive and nondepressive students are still research problems. OBJECTIVE: The purpose of this paper is to investigate the behavioral patterns of depressed students by using multisource campus data and exploring the link between behavioral preferences and depressive symptoms. The campus data described in this paper include basic personal information, academic performance, poverty subsidy, consumption habit, daily routine, library behavior, and meal habit, totaling 121 features. METHODS: To identify potentially depressive students, we developed an online questionnaire system based on a standard psychometric instrument, the Zung Self-Rating Depression Scale (SDS). To explore the differences in behavior of depressive and nondepressive students, the Mann-Whitney U test was applied. In order to investigate the behavioral features of different depressive symptoms, factor analysis was used to divide the questionnaire items into different symptom groups and then correlation analysis was employed to study the extrinsic characteristics of each depressive symptom. RESULTS: The correlation between these factors and the features were computed. The results indicated that there were 25 features correlated with either 4 factors or SDS score. The statistical results indicated that depressive students were more likely to fail exams, have poor meal habits, have increased night activities and decreased morning activities, and engage less in social activities (eg, avoiding meal times with friends). Correlation analysis showed that the somatic factor 2 (F4) was negatively correlated with the number of library visits (r=-.179, P<.001), and, compared with other factors, had the greatest impact on students' daily schedule, eating and social habits. The biggest influencing factor to poor academic performance was cognitive factor F1, and its score was found to be significantly positively correlated with fail rate (r=.185, P=.02). CONCLUSIONS: The results presented in this study indicate that campus data can reflect depression and its symptoms. By collecting a large amount of questionnaire data and combining machine learning algorithms, it is possible to realize an identification method of depression and depressive symptoms based on campus data.

Physical Fitness with Regular Lifestyle Is Positively Related to Academic Performance among Chinese Medical and Dental Students.

OBJECTIVE: The purpose of this study was to examine the relationship between physical fitness, lifestyle, and academic performance of Chinese college students and investigate the differences among medical and dental students on their lifestyle. METHODS: This study was conducted with 316 students enrolled from 2012 to 2014 at Tongji University. Scores from the college physical test were used to represent the students' physical fitness condition. Lifestyle was measured by some variables extracted from the students' behavior data provided by the university's information center. Academic performance was measured by the average score of basic courses and the average score of professional courses. Demographic information, including age, gender, nation, and family background, was also obtained. Separate multiple linear regression analysis was performed for modeling academic performance and physical fitness with a p value threshold of 0.05. RESULTS: A total of 212 (45.97% females) medical students and 104 (58.65% females) dental students participated in this study. Physical fitness score (medical: r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. r = 0.34, p value threshold of 0.05. CONCLUSION: Physical fitness, library usage, and the regularity of lifestyle are significant contributors to academic performance among Chinese medical and dental students. Moreover, medical students are shown to have less rest time compared to dental students.

Corrigendum to "A Trial of Student Self-Sponsored Peer-to-Peer Lending Based on Credit Evaluation Using Big Data Analysis".

[This corrects the article DOI: 10.1155/2019/9898251.].

A Trial of Student Self-Sponsored Peer-to-Peer Lending Based on Credit Evaluation Using Big Data Analysis.

There is still no effective approach to overcome the problem of credit evaluation for Chinese students. In absence of a reliable credit evaluation system for students, the university students have to only apply through online peer-to-peer (P2P) loan platforms because Chinese financial institutions typically reject students' loan applications. Lack of students' financial records hinders financial institutes and banks to routinely evaluate the students' credit status and assign loans to them. Hence, this paper attempted to benefit from university students' diversified daily behavior data, and logistic regression (LR) and gradient boosting decision tree (GBDT) algorithms were also used to develop robust credit evaluation models for university students, in which the validation of the proposed models was assessed by a real-time P2P lending platform. In this study, the students' overdue behavior in returning books to university library was used as an index. With training 17838 samples, the proposed models performed well, while GBDT-based model outperformed in identification of "bad borrowers." Based on the proposed models, a self-sponsored peer-to-peer loan platform was established and developed in a Chinese university for ten months, and the achieved findings demonstrated that adopting such credit evaluation models can effectively reduce the default ratio.

[Determination of vitamin K in animal foods].

OBJECTIVE: To establish a high performance liquid chromatography method with fluorescence detection for a variety of vitamin K and to assess the content of vitamin K in animal foods. METHODS: Animal foods were hydrolyzed by 0.2 g lipase and 0.1 g protease in pH 8 for 4 hours, extracted with isooctane followed by rotary evaporation and reconstitution. The mobile phase was 900 mL methanol and 100 mL tetrahydrofuran which contained 5 mmol glacial acetic acid, 11 mmol zinc chloride and 6 mmol anhydrous sodium acetate. The content of vitamin K_1, menaquinone-4(MK-4), and menaquinone-7(MK-7)were separated on Atlantis T3 column(4.6 mm×250 mm, 5 µm)by high-performance liquid chromatography. The fluorescence detector was set at a wavelength of 320 nm for excitation and 410.3 nm for emission. RESULTS: The linear range of the method was 0.01-0.40 µg/mL, and coefficient of determination was > 0.999. The spiked recoveries were 84.4%-124.2% with relative standard deviation was <6%(n=6). MK-4 was the main form of vitamin K in pork and chicken. The highest content of vitamin K_1 was found in beef, and MK-7 could be detected in aquatic products. CONCLUSION: The proposed method is successfully applied for the determination of vitamin K in animal foods. A variety of vitamin K are distributed differently in distinct animals.

Destaining of Diff-Quik stained cytologic smears is not necessary for the detection of anaplastic lymphoma kinase gene rearrangement in lung adenocarcinoma by fluorescence in situ hybridization.

BACKGROUND: Anaplastic lymphoma kinase (ALK) gene rearrangement analysis by fluorescence in situ hybridization (FISH) is one of the standard molecular tests for targeted therapy of lung adenocarcinoma. However, insufficient cell block cellularity may impede molecular testing. A recent study showed that Diff-Quik (DQ) stained cytology smear is suitable for ALK by FISH. AIMS: The aim of our study was to observe the impact of destaining intervals on the quality of FISH signals and determine if DQ smears without destaining would allow FISH analysis. MATERIALS AND METHODS: Thirty-five DQ smears from 27 cases of lung adenocarcinoma were analyzed for ALK gene rearrangement by FISH. Twenty three DQ smears were destained for different intervals, including 30 s (13 cases), 1 min (6 cases), or 2 min (4 cases). Twelve DQ smears were not subjected to destaining. For further validation, FISH signals in 8 smears and 6 cell blocks were compared with the paired destained DQ smears. The signal quality was semi-quantified and analyzed with Chi-squared test. RESULTS: Of the total 27 selected cases, three (11%) were positive for ALK gene rearrangement, whereas 24 (89%) were negative. FISH signal was satisfactory in all DQ smears. There was no significant difference in the quality of signal among smears with different destaining intervals (P = 0.55) or between smears with and without destaining (P = 0.41). DQ smears without destaining showed identical FISH results and similar or better signals as compared with paired destained smears and cell blocks in all cases. CONCLUSIONS: Duration of destaining intervals does not impact the quality of FISH signal on DQ smears. Destaining of DQ smears is not necessary for ALK by FISH.

Bioremediation of heavy metal contaminated aqueous solution by using red algae Porphyra leucosticta.

Bioremediation is an effective process for the removal and recovery of heavy metal ions from aqueous solutions. In this study, red algae Porphyra leucosticta was examined to remove Cd(II) and Pb(II) ions from wastewater through biological enrichment and biological precipitation. The experimental parameters that affect the bioremediation process such as pH, contact time and biomass dosage were studied. The maximum bioremediation capacity of metal ions was 31.45 mg/g for Cd(II) and 36.63 mg/g for Pb(II) at biomass dosage 15 g/L, pH 8.0 and contact time 120 minutes containing initial 10.0 mg/L of Cd(II) and 10.0 mg/L of Pb(II) solution. Red algae Porphyra leucosticta biomass was efficient at removing metal ions of 10.0 mg/L of Cd(II) and 10.0 mg/L of Pb(II) solution with bioremediation efficiency of 70% for Cd(II) and 90% for Pb(II) in optimal conditions. At the same time, the removal capacity for real industrial effluent was gained at 75% for 7.6 mg/L Cd(II) and 95% for 8.9 mg/L Pb(II). In conclusion, it is demonstrated that red algae Porphyra leucosticta is a promising, efficient, cheap and biodegradable sorbent biomaterial for reducing heavy metal pollution in the environment and wastewater.