Epidemiological Data Mining for Assisting with Foodborne Outbreak Investigation.

Diseases caused by the consumption of food are a significant but avoidable public health issue, and identifying the source of contamination is a key step in an outbreak investigation to prevent foodborne illnesses. Historical foodborne outbreaks provide rich data on critical attributes such as outbreak factors, food vehicles, and etiologies, and an improved understanding of the relationships between these attributes could provide insights for developing effective food safety interventions. The purpose of this study was to identify hidden patterns underlying the relations between the critical attributes involved in historical foodborne outbreaks through data mining approaches. A statistical analysis was used to identify the associations between outbreak factors and food sources, and the factors that were strongly significant were selected as predictive factors for food vehicles. A multinomial prediction model was built based on factors selected for predicting "simple" foods (beef, dairy, and vegetables) as sources of outbreaks. In addition, the relations between the food vehicles and common etiologies were investigated through text mining approaches (support vector machines, logistic regression, random forest, and naïve Bayes). A support vector machine model was identified as the optimal model to predict etiologies from the occurrence of food vehicles. Association rules also indicated the specific food vehicles that have strong relations to the etiologies. Meanwhile, a food ingredient network describing the relationships between foods and ingredients was constructed and used with Monte Carlo simulation to predict possible ingredients from foods that cause an outbreak. The simulated results were confirmed with foods and ingredients that are already known to cause historical foodborne outbreaks. The method could provide insights into the prediction of the possible ingredient sources of contamination when given the name of a food. The results could provide insights into the early identification of food sources of contamination and assist in future outbreak investigations. The data-driven approach will provide a new perspective and strategies for discovering hidden knowledge from massive data.

A Novel Foodborne Illness Detection and Web Application Tool Based on Social Media.

Foodborne diseases and outbreaks are significant threats to public health, resulting in millions of illnesses and deaths worldwide each year. Traditional foodborne disease surveillance systems rely on data from healthcare facilities, laboratories, and government agencies to monitor and control outbreaks. Recently, there is a growing recognition of the potential value of incorporating social media data into surveillance systems. This paper explores the use of social media data as an alternative surveillance tool for foodborne diseases by collecting large-scale Twitter data, building food safety data storage models, and developing a novel frontend foodborne illness surveillance system. Descriptive and predictive analyses of the collected data were conducted in comparison with ground truth data reported by the U.S. Centers for Disease Control and Prevention (CDC). The results indicate that the most implicated food categories and the distributions from both Twitter and the CDC were similar. The system developed with Twitter data could complement traditional foodborne disease surveillance systems by providing near-real-time information on foodborne illnesses, implicated foods, symptoms, locations, and other information critical for detecting a potential foodborne outbreak.

Amyloid peptide hydrogels via formation of coordination polymers with Ag+ by its core peptide equipped with a C-cysteine.

We report that the core sequence of amyloid ß (Aß) peptide, KLVFF, when equipped with a C-terminal cysteine residue, exhibited an extremely low minimum hydrogelation concentration of 0.05 wt% in the presence of Ag+ in pH 5 buffer, with this concentration 2 orders of magnitude lower than that of the pentapeptide itself. The CD signal of the Ag+-L-KLVFFC hydrogel was observed to be sensitive to the early-stage aggregation of amyloid ß peptide.

Dynamics and Predictability of Tropical Cyclone Rapid Intensification in Ensemble Simulations of Hurricane Patricia (2015).

Hurricane Patricia (2015) over the eastern Pacific was a record-breaking tropical cyclone (TC) under a very favorable environment during its rapid intensification (RI) period, which makes it an optimal real case for studying RI dynamics and predictability. In this study, we performed ensemble Kalman filter analyses at Patricia's early development stage using both traditional observations and the Office of Naval Research Tropical Cyclone Intensity (TCI) field campaign data. It is shown that assimilating the inner-core TCI observations produces a stronger initial vortex and significantly improves the prediction of RI. Analysis of observation sensitivity experiments shows that the deep-layer dropsonde observations have high impact on both the primary and secondary circulations for the entire troposphere while the radar observations have the most impact on the primary circulations near aircraft flight level. A wide range of intensification scenarios are obtained through two sets of ensemble forecasts initialized with and without assimilating the TCI data prior to the RI onset. Verification of the ensemble forecasts against the TCI observations during the RI period shows that forecast errors toward later stages can originate from two different error sources at early stages of the vortex structure: One is a timing error from a delayed vortex development such that the TC evolution is the same but shifted in time; the other is due to a totally different storm such that there is no moment in time the simulated storm can obtain a correct TC structure.

Long non-coding RNA (lncRNA) nuclear enriched abundant transcript 1 (NEAT1) promotes the inflammation and apoptosis of otitis media with effusion through targeting microRNA (miR)-495 and activation of p38 MAPK signaling pathway.

Long non-coding RNA (lncRNA) plays a vital role in human inflammatory diseases. Our study aimed to investigate the function of lncRNA nuclear-enriched abundant transcript 1 (NEAT1) in otitis media with effusion (OME). The mRNA levels of NEAT1 and miR-495 were measured by RT-qPCR. The protein levels of p38 MAPK were detected by western blot. The levels of inflammatory cytokines were examined by ELISA. CCK-8 and flow cytometry assays were used to evaluate the cell viability and apoptosis, respectively. The interaction between NEAT1 and miR-495 was determined by luciferase reporter and RIP assays. NEAT1 was highly expressed in OME, and silencing of NEAT1 facilitated the cell proliferation and suppressed levels of inflammatory cytokines and cell apoptosis in LPS-induced HMEECs. Moreover, miR-495 was confirmed as a downstream target of NEAT1. Functional assays revealed that NEAT1 promoted the OME by targeting miR-495. It was further demonstrated that NEAT1 could activate the p38 MAPK signaling pathway by regulating miR-495, and the p38 MAPK inhibitor restored the effects of NEAT1 overexpression on the inflammation levels, cell proliferation, and apoptosis. Our study revealed that lncRNA NEAT1 served as a ceRNA to activate p38 MAPK signaling by targeting miR-495 in OME, which may offer a new target for OME treatment.

Crowdsourcing and machine learning approaches for extracting entities indicating potential foodborne outbreaks from social media.

Foodborne outbreaks are a serious but preventable threat to public health that often lead to illness, loss of life, significant economic loss, and the erosion of consumer confidence. Understanding how consumers respond when interacting with foods, as well as extracting information from posts on social media may provide new means of reducing the risks and curtailing the outbreaks. In recent years, Twitter has been employed as a new tool for identifying unreported foodborne illnesses. However, there is a huge gap between the identification of sporadic illnesses and the early detection of a potential outbreak. In this work, the dual-task BERTweet model was developed to identify unreported foodborne illnesses and extract foodborne-illness-related entities from Twitter. Unlike previous methods, our model leveraged the mutually beneficial relationships between the two tasks. The results showed that the F1-score of relevance prediction was 0.87, and the F1-score of entity extraction was 0.61. Key elements such as time, location, and food detected from sentences indicating foodborne illnesses were used to analyze potential foodborne outbreaks in massive historical tweets. A case study on tweets indicating foodborne illnesses showed that the discovered trend is consistent with the true outbreaks that occurred during the same period.

Effectiveness of Ginkgo biloba diterpene lactone in the treatment of sudden sensorineural hearing loss.

PURPOSE: To evaluate the effectiveness of systemic Ginkgo biloba diterpene lactone therapy for sudden sensorineural hearing loss. METHODS: This retrospective review investigated 56 patients with unilateral sudden sensorineural hearing loss. Among them, 26 patients received conventional therapy (group C, intravenous methylprednisolone), and 30 received conventional therapy supplemented with Ginkgo biloba diterpene lactone (group G). Pure tone audiometry was measured before treatment and 1 month after treatment. The average pure tone audiometry gain, pure tone audiometry gain at each frequency, pure tone audiometry gain according to initial hearing loss, and rate of effectiveness were defined as functionally relevant recovery of hearing and compared between the two groups. RESULTS: The average pure tone audiometry gain was significantly greater in group G (20.6 ± 15.1 dB) than in group C (11.9 ± 13.3 dB) (p = 0.025), with similar trends at 250, 1 k, and 8 k Hz. In the subgroup of patients with profound hearing loss (initial pure tone audiometry >70 dB), hearing gain was significantly higher in group G (26.7 ± 14.4 dB) than in C (5.5 ± 9.0 dB) (p = 0.034). In the mild-moderate hearing loss subgroup (initial pure tone audiometry ≤70 dB), the pure tone audiometry gain did not differ significantly (group G: 18.4 ± 14.3 dB; group C: 13.0 ± 13.4 dB) (p = 0.209). The overall rate of effectiveness was 73.3% and 57.7% in groups G and C, respectively; however, the difference was statistically insignificant (p = 0.218). CONCLUSIONS: Compared with conventional therapy alone, supplementary systemic administration of Ginkgo biloba diterpene lactone to treat sudden sensorineural hearing loss could improve hearing recovery, especially, in patients with profound hearing loss.

Utilization of text mining as a big data analysis tool for food science and nutrition.

Big data analysis has found applications in many industries due to its ability to turn huge amounts of data into insights for informed business and operational decisions. Advanced data mining techniques have been applied in many sectors of supply chains in the food industry. However, the previous work has mainly focused on the analysis of instrument-generated data such as those from hyperspectral imaging, spectroscopy, and biometric receptors. The importance of digital text data in the food and nutrition has only recently gained attention due to advancements in big data analytics. The purpose of this review is to provide an overview of the data sources, computational methods, and applications of text data in the food industry. Text mining techniques such as word-level analysis (e.g., frequency analysis), word association analysis (e.g., network analysis), and advanced techniques (e.g., text classification, text clustering, topic modeling, information retrieval, and sentiment analysis) will be discussed. Applications of text data analysis will be illustrated with respect to food safety and food fraud surveillance, dietary pattern characterization, consumer-opinion mining, new-product development, food knowledge discovery, food supply-chain management, and online food services. The goal is to provide insights for intelligent decision-making to improve food production, food safety, and human nutrition.

Helical nanofibers of N-(perfluorooctanoyl)cysteine ethyl ester in coordination polymers of Ag.

We propose using the formation of coordination polymers of Ag+ to probe differences between the perfluorinated alkyl chain and the alkyl chain by deriving a thiol ligand, N-(perfluoroalkanoyl)cysteine. Rapid formation in EtOH of P-/M-helical nanofibrils of high thermostability was found for N-(perfluorooctanoyl)-l-/d-cysteine ethyl esters at the µM level upon mixing with Ag+, but not for the octanoyl counterpart. This difference was also observed in terms of circular dichroism-enantiomeric excess dependence.

Quality comparison of "Laba" garlic processed by High Hydrostatic Pressure and High Pressure Carbon Dioxide.

The production of "Laba" garlic is limited to the homemade method with long processing time and non-uniform color quality. Innovative food processing technologies including high hydrostatic pressure (HHP) and high pressure carbon dioxide (HPCD) were applied to the processing of "Laba" garlic. Products prepared at different treatment pressures (200, 350 and 500 MPa of HHP; 4, 7 and 10 MPa of HPCD) were compared by evaluating the texture, color, flavor and sensory qualities. The results indicated that HHP treatment at 200 MPa was optimal for retaining the textural quality of "Laba" garlic, which was mainly attributed to the compacted cells and the increased Ca2+-cross linked cell-cell adhesion. HHP had greater effect on facilitating the formation of the attractive green color of "Laba" garlic than HPCD. The flavor profiles of "Laba" garlic were modified after treatments, with pungent compounds decreased to non-detectable. The results from sensory study confirmed that "Laba" garlic treated by HHP at 200 MPa was most acceptable to consumers. Moreover, considering the treatment capacity and feasibility of commercialization, HHP would be a promising technology in production of "Laba" garlic with improved quality and efficiency.

Early-life Programming of Type 2 Diabetes Mellitus: Understanding the Association between Epigenetics/Genetics and Environmental Factors.

Type 2 Diabetes Mellitus is an increasing public health problem that poses a severe social and economic burden affecting both developed and developing countries. Defects in insulin signaling itself are among the earliest indications that an individual is predisposed to the development of insulin resistance and subsequently Type 2 Diabetes Mellitus. To date, however, the underlying molecular mechanisms which result in resistance to the actions of insulin are poorly understood. Furthermore, it has been shown that maternal obesity is associated with an increased risk of obesity and insulin resistance in the offspring. However, the genetic and/or epigenetic modifications within insulin-sensitive tissues such as the liver and skeletal muscle, which contribute to the insulin-resistant phenotype, still remain unknown. More importantly, a lack of in-depth understanding of how the early life environment can have long-lasting effects on health and increased risk of Type 2 Diabetes Mellitus in adulthood poses a major limitation to such efforts. The focus of the current review is thus to discuss recent experimental and human evidence of an epigenetic component associated with components of nutritional programming of Type 2 Diabetes Mellitus, including altered feeding behavior, adipose tissue, and pancreatic beta-cell dysfunction, and transgenerational risk transmission.

A Facile Pathway to Modify Cellulose Composite Film by Reducing Wettability and Improving Barrier towards Moisture.

The hydrophilic property of cellulose is a key limiting factor for its wide application. Here, a novel solution impregnation pathway was developed to increase the hydrophobic properties of cellulose. When compared with the regenerated cellulose (RC), the composite films showed a decrease in water uptake ability towards water vapor, and an increase of the water contact angle from 29° to 65° with increasing resin content in the composites, with only a slight change in the transmittance. Furthermore, the Young's modulus value increased from 3.2 GPa (RC film) to 5.1 GPa (RCBEA50 film). The results indicated that the composites had combined the advantages of cellulose and biphenyl A epoxy acrylate prepolymer (BEA) resin. The presented method has great potential for the preparation of biocomposites with improved properties. The overall results suggest that composite films can be used as high-performance packaging materials.

Ag+ coordination polymers of a chiral thiol ligand bearing an AIE fluorophore.

We report that in the Ag+ coordination polymers of a chiral thiol ligand containing an AIE fluorophore, tetraphenylethene (TPE), the TPE chromophores experience H-type aggregation, and yet a substantial enhancement of the fluorescence is observed, though to a lesser extent than that in the aggregates of the thiol ligand itself, which undergoes J-type aggregation. We show that this is not due to the difference in the freedom of the rotation of the fluorophore in the two types of aggregate, but is due to a small increase in the radiation rate constant in the coordination polymers while the much higher radiationless rate constant remains more or less unchanged.

Supramolecular aggregates as sensory ensembles.

As a new emerging area in chemical sensing, sensing using supramolecular aggregates exhibits unique advantages over that using conventional small-molecule chemical sensors, in terms of high sensitivity and selectivity, and the simplicity of the sensory building blocks. This Feature Article outlines the recent research progress made in sensing based on induced supramolecular aggregation-disaggregation. The reviewed sensory building blocks, in general, in the form of a small molecular sensor, yet with a much simpler structure, which form aggregates, are those of perylene derivatives, pyrene derivatives, tetraphenylethylene derivatives, metallophilic species and metal-organic frameworks.

'Laba' garlic processed by dense phase carbon dioxide: the relation between green colour generation and cellular structure, alliin consumption and alliinase activity.

BACKGROUND: 'Laba' garlic is usually processed by soaking garlic in vinegar for more than 1 week during winter. It is popular for its unique green colour and tasty flavour. Greening is desirable and required for this product as its characteristic. Dense phase carbon dioxide (DPCD) had a significant effect on the greening of intact garlic (Allium sativum L.) cloves. The relation between green colour generation and alliin consumption, alliinase activity and the cellular structure of garlic, respectively, were investigated in this work. The effects of treatment time, pressure and temperature of DPCD were also analysed and discussed. RESULTS: DPCD had a significant effect on the cellular structure of garlic cells. Garlic protoplast underwent greater morphological change after DPCD treatments at higher temperatures while the amount of precipitate increased with greater treatment time and temperature. Common trends on garlic greening and alliin consumption were observed except for DPCD treatment at 10 MPa and 65 °C. The alliinase activity decreased with increasing treatment time, pressure and temperature. It reached the lowest level at 13 MPa and 55 °C. CONCLUSION: The formation of the green colour was a comprehensive result of DPCD on changing cellular structure, alliin consumption and alliinase activity. DPCD treatment at 10 MPa and 55 °C was the optimum condition for the greening of 'Laba' garlic. This work further facilitated the application of DPCD in the industrial production of 'Laba' garlic. © 2015 Society of Chemical Industry.

Chirality sensing using Ag⁺-thiol coordination polymers.

We report here chirality sensing using achiral Ag(+)-thiol coordination polymers as the framework which becomes CD active upon interaction with chiral species, taking p-mercaptophenylboronic acid as a thiol ligand that bears a binding group for monosaccharides.

[Results of low-dose computed tomography (LDCT) screening for early lung cancer: prevalence in 4 690 asymptomatic participants].

OBJECTIVE: To report the results of low-dose computed tomography (LDCT) screening for early lung cancer in 4 690 asymptomatic participants at the Cancer Hospital, Chinese Academy of Medical Sciences between July 2007 and June 2012. METHODS: After informed consent and questionnaire forms were obtained, 4 690 asymptomatic participants ≥ 40 years underwent chest low dose spiral CT scanning. According to the National Comprehensive Cancer Network (NCCN) guideline for lung cancer screening (version 1.1, 2012), all participants were assigned to three groups, namely high-risk, moderate-risk and low-risk groups. In terms of gender, smoking history and second-hand tobacco smoking exposure history, two other groups named male and female never-smoker groups who were exposed to second-hand tobacco smoking were designated. The positive results were identified as at least one solid or part-solid nodule measuring ≥ 5 mm, or non-solid nodule ≥ 8 mm in diameter. LDCT scanning protocol, criteria of management according to the size and consistency of pulmonary nodules were compliant with the International Early Lung Cancer Active Program (I-ELCAP). TNM staging of all lung cancers were based on the clinical evidence and pathological findings. RESULTS: In various risk status group of the participants, the percentage of positive results of baseline CT were 27.0% (86/319), 19.3% (199/1 029) and 11.3% (377/3 342), respectively. A total of 26 participants (27 lesions) were diagnosed as lung cancer (11 in men, 15 in women). The detection rate of lung cancer was 0.6% (26/4 690). Besides a SCLC (limited-disease, LD), 25 cases (76.0%) were stage I including 24 NSCLC and one cacinoid on baseline LDCT and the surgical resection rate was 88.5% (23/26). The diameter of resected cancers was 6.9-29.5 mm (median, 16.3 mm). For female never smokers aged 40 years or older who were exposed to second-hand smoking, the detection rate of lung cancer was higher than that of the high-risk and male never smokers who were exposed to second-hand smoking (1.4% vs. 0.9%, 0.4%). CONCLUSIONS: The results indicate that LDCT can detect small lung cancers and most of the cancers are detected at an early stage. Emphasis should be placed on the non-smoking female individuals who are exposed to second-hand smoking in China.

Highly flexible magnetic composite aerogels prepared by using cellulose nanofibril networks as templates.

Nanostructured cellulose nanofibrils can form ductile or tough networks that are suitable templates for the creation of materials with functional properties. In this work, a facile method has been developed for the preparation of magnetic hybrid cellulose aerogels. The preparation processes followed by two steps, firstly, preparation of cellulose hydrogel films from LiOH/urea solvent, then CoFe2O4 nanoparticles were synthesized in the porous structured cellulose scaffolds. After being freeze-dried, CoFe2O4/cellulose magnetic aerogels were obtained. The porosity of the composite aerogels ranged from 78 to 52% with pore size distribution in a few tens of nanometers. The internal specific surface areas were around 300-320 m2/g, and the densities were in the range of 0.25-0.39 g/cm3. The hybrid aerogels showed improved mechanical strength, superparamagnetic properties. Unlike solvent-swollen gels and ferrogels, the magnetic composite aerogels were lightweight, flexibility, high porosity and with large specific surface area and could be expected to be used in many fields.

[Detection of EBV-LMP1 antibodies in sera and clinical significance in the patients with nasopharyngeal carcinoma].

OBJECTIVE: To detect the levels of Epstein-Barr virus (EBV) latent membrane protein 1 Antibodies (LMP1-Ab) in nasopharyngeal carcinoma (NPC)sera and discuss the clinical significance of this test in diagnosis, prognosis, and immune-targeted therapy of NPC. METHOD: Enzyme-linked immunosorbent assay (ELISA) and Western blot method were used to detect the LMP1-Ab levels in 61 NPC sera, 30 nasopharyngitis sera, and 55 normal sera. The relationship between the LMP1-Ab level and clinical and pathological features of NPC was analyzed. RESULT: ELISA test showed that LMP1 antibodies level was significantly higher in nasopharyngeal carcinoma group than those in nasopharyngitis group and in healthy group and there were statistical significances (all P<0.05). In SNPC group, the LMP1-Ab level was not related to the pathological grade and cervical lymph node metastases (P>0.05). Western blot test revealed that the expression of LMP1 antibodies was higher in NPC sera than in nasopharyngitis sera and in normal sera. CONCLUSION: LMP1-Ab level was higher in nasopharyngeal carcinoma group than in nasopharyngitis group and in normal group. Therefore, LMP1 may be considered as a tumor correlated antigen to help the diagnosis and immune-targeted therapy of NPC.

Performance of electromyography recorded using textile electrodes in classifying arm movements.

Electromyography (EMG) signals are commonly recorded using the Ag/AgCl gel electrodes in myoelectric prosthetic control. While a gelled electrode may provide high-quality EMG recordings, it is inconvenient in clinical application of a myoelectric prosthesis. A novel type of signal sensors-textile electrodes should be ideal in control of myoelectric prostheses. However, it is unknown whether the performance of textile electrodes is comparable to commonly used electrodes in classifying arm movements. In this study, the custom-made bipolar textile electrodes were fabricated using copper-based nickel-plated conductive fabric and were used to record EMG signals. The performance of EMG signals recorded with textile electrodes in identifying nine arm and hand movements were investigated. Our pilot results showed that the average classification accuracy across six able-bodied subjects was 94.05% when using textile electrodes and 94.26% when using conventional electrodes, with no significant difference between the two types of electrodes (p=0.81). The pilot results suggest that the textile electrodes could achieve similar performance in classifying arm movements in control of myoelectric prostheses as the gelled metal electrodes.