INORGANIC ELEMENTS IN COW AND SHEEP RAW MILK SAMPLES FROM NATIONAL PARK OF GARGANO

A study about cow and sheep raw milk collected from different farms in the National Park of Gargano was carried out. A number of 93 raw milk samples (50 cow milk and 43 sheep milk) were analysed for the detection of several trace element (As, Cd, Co, Cr, Cu, Fe, Mo, Mn, Pb, Se, Zn) and artificial gamma radionuclide (Cs-134, Cs-137) content. Data analysis shows a significant statistical difference between the two species. Cow milk mean values are always lower than sheep ones for Cu, Fe, Mn and Pb. Artificial longterm gamma radionuclide activity was not detected in all samples, resulting lower than the minimum detectable concentration (MDC). All inorganic contaminant concentration levels actually don’t represent a primary health concern. This research is also a contribution in the risk assessment related to the consumption of these products and confirm both sheep and cow milk as a good environmental pollution indicator. Furthermore, this investigation is a contribution to enhance safety and quality of typical dairy products from National Park of Gargano

INORGANIC ELEMENTS IN COW AND SHEEP RAW MILK SAMPLES FROM NATIONAL PARK OF GARGANO

A study about cow and sheep raw milk collected from different farms in the National Park of Gargano was carried out. A number of 93 raw milk samples (50 cow milk and 43 sheep milk) were analysed for the detection of several trace element (As, Cd, Co, Cr, Cu, Fe, Mo, Mn, Pb, Se, Zn) and artificial gamma radionuclide (Cs-134, Cs-137) content. Data analysis shows a significant statistical difference between the two species. Cow milk mean values are always lower than sheep ones for Cu, Fe, Mn and Pb. Artificial longterm gamma radionuclide activity was not detected in all samples, resulting lower than the minimum detectable concentration (MDC). All inorganic contaminant concentration levels actually don't represent a primary health concern. This research is also a contribution in the risk assessment related to the consumption of these products and confirm both sheep and cow milk as a good environmental pollution indicator. Furthermore, this investigation is a contribution to enhance safety and quality of typical dairy products from National Park of Gargano

ACRYLAMIDE, FOOD AND EUROPEAN COMMUNITIES RECOMMENDATION

The exposure, often deceitful, to the acrylamide has determined notable apprehension in many consumers, so much that the Committee of the European Communities has financed the project HEATOX and has emanated the recommendation 2007/331. It is ascertained that proposed strategies have not brought to great changes in the food process chains, and neither in the traditional catering and housewife, for which more incisive measures are wished

Verocytotoxin-Producing Escherichia coli O26 in raw water buffalo (Bubalus bubalis) milk products in Italy

Escherichia coli 026 is known as a verocytotoxin-producing E. coli (VTEC) organism that causes severe foodborne diseases such as hemorrhagic colitis and hemolytic uremic syndrome. Although cattle are the most important reservoir of VTEC, only a few reports on the role of water buffalo (Bubalus bubalis) as a reservoir of VTEC and on the presence of these organisms in their milk are available. However, in Southern Italy, where water buffalo are intensively reared, an outbreak of hemolytic uremic syndrome due to E. coli 026 has recently been reported, in which the consumption of typical dairy products was considered to be a common risk factor. The aims of this work were to assess the prevalence of E. coli 026 in raw water buffalo milk, to characterize the virulence gene profiles of the isolates, and to evaluate their phenotypic antimicrobial resistance pattern. Of 160 analyzed samples, 1 (0.6%) tested positive for E. coli 026, and the isolate showed the stx1+ lstx2+leae-lhlyA+ genotypic profile. The strain showed resistance against glycopeptides, macrolides, and penicillins. The presence of VTEC organisms in raw water buffalo milk could be considered to be a potential threat to consumers; however, the strict adherence to the processes used in the preparation of the most common buffalo dairy products could strongly mitigate the foodborne risk. To our knowledge, this article reports the first isolation and characterization of E. coli 026 VTEC in raw water buffalo milk. Copyright ©, International Association for Food Protectio

Escherichia coli O26 IN RAW BUFFALO MILK: PRELIMINARY RESULTS

Escherichia coli O26 is considered to be one of the most important food-borne pathogen. In this study, 120 buffalo milk samples collected in Lazio and in Apulia regions were tested for the presence of E. coli O26. One buffalo milk sample (0,8%) tested positive for E. coli O26; the isolate was positive at the verocytotoxicity test and it showed resistance properties to different antimicrobial classes. These preliminary results highlight the need to monitor the foods of animal origin used for production and eaten by a wide range of persons, respect VTEC organism

DETECTING MALICIOUS USE WITH UNLABELLED DATA USING CLUSTERING AND OUTLIER ANALYSIS

Abstract: Most commercial intrusion detection systems (IDSs) presently available are signature-based network IDSs. Organisations using these IDSs are still experiencing difficulties in detecting intrusive activity on their networks since novel new attacks are consistently being encountered, and analysts can miss legitimate alarms when reviewing large alarm logs that contain a high number of false positives. There has been research investigating the use of data mining techniques to effectively detect malicious activity in an enterprise network. The results of many of these projects have demonstrated that these techniques can be effective when trained/calibrated using labelled datasets. Labelled datasets identify and characterize normal and malicious traffic for use in training/calibrating the detection sensor. However, the creation of labelled datasets is resource intensive. It requires a significant effort by security analysts to create a data set that characterises the traffic in a specific enterprise network environment. This research simulates and analyses malicious activity on an enterprise network to explore the detection of malicious activity with data mining techniques using unlabelled datasets. Semi-discrete decomposition (SDD) is used as a clustering and outlier analysis technique to characterize network traffic as either normal or anomalous. 1