Artificial neural networks for diagnosis and survival prediction in colon cancer

ANNs are nonlinear regression computational devices that have been used for over 45 years in classification and survival prediction in several biomedical systems, including colon cancer. Described in this article is the theory behind the three-layer free forward artificial neural networks with backpropagation error, which is widely used in biomedical fields, and a methodological approach to its application for cancer research, as exemplified by colon cancer. Review of the literature shows that applications of these networks have improved the accuracy of colon cancer classification and survival prediction when compared to other statistical or clinicopathological methods. Accuracy, however, must be exercised when designing, using and publishing biomedical results employing machine-learning devices such as ANNs in worldwide literature in order to enhance confidence in the quality and reliability of reported data

Modeling survival in colon cancer: a methodological review

The Cox proportional hazards model is the most widely used model for survival analysis because of its simplicity. The fundamental assumption in this model is the proportionality of the hazard function. When this condition is not met, other modifications or other models must be used for analysis of survival data. We illustrate in this review several methodological approaches to deal with the violation of the proportionality assumption, using survival in colon cancer as an illustrative example

EFFECT OF RE-MATING INTERVAL AFTER THE FIRST PARTURITION ON THE LITTER PARAMETERS, MILK YIELD AND REPRODUCTION TRAITS OF RABBIT DOES

A total number of 120 nulliparous APRI and Baladi Black does (60 does for each breed) were mated at 5 months of age at the beginning of the breeding season (during September) to study the effect of re-mating interval after the first parturition on the litter parameters, milk yield per day and reproduction traits. All does were randomly divided into three equal groups according to reproductive rhythm: The 1st group: post partum (PP), the 2nd group: 11 days after parturition (P11), and the 3rd group: Post weaning (PW) .The body weight of P11 does were slightly higher than that of PP or PW groups. The re- mating interval groups during second parity had significant (P<0.05) effects on litter traits at weaning. Litter size and Litter weight at weaning age in PW group were higher significantly (P<0.05) than those in PP and P11 groups. Litter weight at 21 days of age in PW and P11 groups were higher significantly (P<0.05) than those in PP group. The PW group had significant higher litter size at weaning than those in PP group. Daily milk yield (DMY) after second parity was affected significantly by re-mating interval groups in the third and fourth week of suckling period. GL in PP group was higher significantly (P<0.05) comparing with P11 or PW groups. The values of litter size and weight traits were better for APRI does comparing with BB except litter weight at 21 days. The difference in results between the two breeds in daily milk yield showed generally higher trend of daily milk yield for APRI over BB. The Kindling interval and the gestation period were significantly (P<0.05) affected by interaction of re-mating interval group and breed. In conclusion, applying a lengthened period after the first kindling (by more than 10 days or after weaning) had a favorable effect on the does’ production

Molecular mechanisms of increased cerebral vulnerability after repeated mild blast-induced traumatic brain injury

AbstractThe consequences of a mild traumatic brain injury can be especially severe if it is repeated within the period of increased cerebral vulnerability (ICV) that follows the initial insult. To better understand the molecular mechanisms that contribute to ICV, we exposed rats to different levels of mild blast overpressure (5 exposures; total pressure range: 15.54–19.41psi or 107.14–133.83kPa) at a rate of 1 per 30min, monitored select physiological parameters, and assessed behavior. Two days post-injury or sham, we determined changes in protein biomarkers related to various pathologies in behaviorally relevant brain regions and in plasma. We found that oxygen saturation and heart rate were transiently depressed following mild blast exposure and that injured rats exhibited significantly increased anxiety- and depression-related behaviors. Proteomic analyses of the selected brain regions showed evidence of substantial oxidative stress and vascular changes, altered cell adhesion, and inflammation predominantly in the prefrontal cortex. Importantly, these pathological changes as well as indications of neuronal and glial cell loss/damage were also detected in the plasma of injured rats. Our findings illustrate some of the complex molecular changes that contribute to the period of ICV in repeated mild blast-induced traumatic brain injury. Further studies are needed to determine the functional and temporal relationship between the various pathomechanisms. The validation of these and other markers can help to diagnose individuals with ICV using a minimally invasive procedure and to develop evidence-based treatments for chronic neuropsychiatric conditions

Dynamics of PEGylated-dextran-spermine nanoparticles for gene delivery to leukemic cells.

Leukemic cells are hard-to-transfect cell lines. Many transfection reagents which can provide high gene transfer efficiency in common adherent cell lines are not effective to transfect established blood cell lines or primary leukemic cells. This study aims to examine a new class of cationic polymer non-viral vector, PEGylated-dextran-spermine (PEG-D-SPM), to determine its ability to transfect the leukemic cells. Here, the optimal conditions of the complex preparation (PEG-D-SPM/plasmid DNA (pDNA)) were examined. Different weight-mixing (w/w) ratios of PEG-D-SPM/pDNA complex were prepared to obtain an ideal mixing ratio to protect encapsulated pDNA from DNase degradation and to determine the optimal transfection efficiency of the complex. Strong complexation between polymer and pDNA in agarose gel electrophoresis and protection of pDNA from DNase were detected at ratios from 25 to 15. Highest gene expression was detected at w/w ratio of 18 in HL60 and K562 cells. However, gene expression from both leukemic cell lines was lower than the control MCF-7 cells. The cytotoxicity of PEG-D-SPM/pDNA complex at the most optimal mixing ratios was tested in HL60 and K562 cells using MTS assay and the results showed that the PEG-D-SPM/pDNA complex had no cytotoxic effect on these cell lines. Spherical shape and nano-nature of PEG-D-SPM/pDNA complex at ratio 18 was observed using transmission electron microscopy. As PEG-D-SPM showed modest transfection efficiency in the leukemic cell lines, we conclude that further work is needed to improve the delivery efficiency of the PEG-D-SPM

Seasonal Effect on Biomarkers of Exposure to Petroleum Hydrocarbons in the Coasts of North Western Suez Gulf, Egypt

Petroleum hydrocarbons of surface water were collected from eight locations of from the coasts of north western Suez Gulf, Egypt. The extracted petroleum hydrocarbons were determined by gas chromatography–flame ionization detector and quantified by integrating the areas of both the resolved and unresolved components. The results confirm that the concentration is relatively higher than the recommended in the regulations of the Egyptian low of Environment of No.4/1994 of petroleum products. At various locations, The dissolved petroleum hydrocarbons ranged from 5.639 to 74.8 and 1.868 to 65.698 mg/ml for summer and winter seasons, respectively. This indicates that chronic oil pollution, in addition to hydrocarbon concentrations, the diagnostic indices used shows that the hydrocarbons in the area were comes from biogenic, petrogenic and anthropogenic sources. FT-IR spectrometric analysis confirms the petrogenic nature of pollutants

Study of atmospheric pollution and health risk assessment: A case study for the sharjah and ajman emirates (uae)

Dust is a significant pollution source in the United Arab Emirates (UAE) that impacts population health. Therefore, the present study aims to determine the concentration of heavy metals (Cd, Pb, Cr, Cu, Ni, and Zn) in the air in the Sharjah and Ajman emirates’ urban areas and assesses the health risk. Three indicators were used for this purpose: the average daily dose (ADD), the hazard quotient (HQ), and the health index (HI). Data were collected during the period April–August 2020. Moreover, the observation sites were clustered based on the pollutants’ concentration, given that the greater the heavy metal concentration is, the greater is the risk for the population health. The most abundant heavy metal found in the atmosphere was Zn, with a mean concentration of 160.30 mg/kg, the concentrations of other metals being in the following order: Ni \u3e Cr \u3e Cu \u3e Pb \u3e Cd. The mean concentrations of Cd, Pb, and Cr were within the range of background values, while those of Cu, Ni, and Zn were higher than the background values, indicating anthropogenic pollution. For adults, the mean ADD values of heavy metals decreased from Zn to Cd (Zn \u3e Ni \u3e Cr \u3e Cu \u3e Pb \u3e Cd). The HQ (HI) suggested an acceptable (negligible) level of non-carcinogenic harmful health risk to residents’ health. The sites were grouped in three clusters, one of them containing a single location, where the highest concentrations of heavy metals were found

Chemical Profile of Cyperus laevigatus and Its Protective Effects against Thioacetamide-Induced Hepatorenal Toxicity in Rats

Cyperus species represent a group of cosmopolitan plants used in folk medicine to treat several diseases. In the current study, the phytochemical profile of Cyperus laevigatus ethanolic extract (CLEE) was assessed using UPLC-QTOF–MS/MS. The protective effect of CLEE at 50 and 100 mg /kg body weight (b.w.) was evaluated on hepatorenal injuries induced by thioacetamide (100 mg/kg) via investigation of the extract’s effects on oxidative stress, inflammatory markers and histopathological changes in the liver and kidney. UPLC-QTOF–MS/MS analysis of CLEE resulted in the identification of 94 compounds, including organic and phenolic acids, flavones, aurones, and fatty acids. CLEE improved the antioxidant status in the liver and kidney, as manifested by enhancement of reduced glutathione (GSH) and coenzyme Q10 (CoQ10), in addition to the reduction in malondialdehyde (MDA), nitric oxide (NO), and 8-hydroxy-2′-deoxyguanosine (8OHdG). Moreover, CLEE positively affected oxidative stress parameters in plasma and thwarted the depletion of hepatorenal ATP content by thioacetamide (TAA). Furthermore, treatment of rats with CLEE alleviated the significant increase in plasma liver enzymes, kidney function parameters, and inflammatory markers. The protective effect of CLEE was confirmed by a histopathological study of the liver and kidney. Our results proposed that CLEE may reduce TAA-hepatorenal toxicity via its antioxidant and anti-inflammatory properties suppressing oxidative stress

Support vector machine model for diagnosis of lymph node metastasis in gastric cancer with multidetector computed tomography: a preliminary study

<p>Abstract</p> <p>Background</p> <p>Lymph node metastasis (LNM) of gastric cancer is an important prognostic factor regarding long-term survival. But several imaging techniques which are commonly used in stomach cannot satisfactorily assess the gastric cancer lymph node status. They can not achieve both high sensitivity and specificity. As a kind of machine-learning methods, Support Vector Machine has the potential to solve this complex issue.</p> <p>Methods</p> <p>The institutional review board approved this retrospective study. 175 consecutive patients with gastric cancer who underwent MDCT before surgery were included. We evaluated the tumor and lymph node indicators on CT images including serosal invasion, tumor classification, tumor maximum diameter, number of lymph nodes, maximum lymph node size and lymph nodes station, which reflected the biological behavior of gastric cancer. Univariate analysis was used to analyze the relationship between the six image indicators with LNM. A SVM model was built with these indicators above as input index. The output index was that lymph node metastasis of the patient was positive or negative. It was confirmed by the surgery and histopathology. A standard machine-learning technique called k-fold cross-validation (5-fold in our study) was used to train and test SVM models. We evaluated the diagnostic capability of the SVM models in lymph node metastasis with the receiver operating characteristic (ROC) curves. And the radiologist classified the lymph node metastasis of patients by using maximum lymph node size on CT images as criterion. We compared the areas under ROC curves (AUC) of the radiologist and SVM models.</p> <p>Results</p> <p>In 175 cases, the cases of lymph node metastasis were 134 and 41 cases were not. The six image indicators all had statistically significant differences between the LNM negative and positive groups. The means of the sensitivity, specificity and AUC of SVM models with 5-fold cross-validation were 88.5%, 78.5% and 0.876, respectively. While the diagnostic power of the radiologist classifying lymph node metastasis by maximum lymph node size were only 63.4%, 75.6% and 0.757. Each SVM model of the 5-fold cross-validation performed significantly better than the radiologist.</p> <p>Conclusions</p> <p>Based on biological behavior information of gastric cancer on MDCT images, SVM model can help diagnose the lymph node metastasis preoperatively.</p

Perspective Chapter: The Toxic Silver (Hg)

In the late 1950s, residents of a Japanese fishing village known as “Minamata” began falling ill and dying at an alarming rate. The Japanese authorities stated that methyl-mercury-rich seafood and shellfish caused the sickness. Burning fossil fuels represent ≈52.7% of Hg emissions. The majorities of mercury’s compounds are volatile and thus travel hundreds of miles with wind before being deposited on the earth’s surface. High acidity and dissolved organic carbon increase Hg-mobility in soil to enter the food chain. Additionally, Hg is taken up by areal plant parts via gas exchange. Mercury has no identified role in plants while exhibiting high affinity to form complexes with soft ligands such as sulfur and this consequently inactivates amino acids and sulfur-containing antioxidants. Long-term human exposure to Hg leads to neurotoxicity in children and adults, immunological, cardiac, and motor reproductive and genetic disorders. Accordingly, remediating contaminated soils has become an obligation. Mercury, like other potentially toxic elements, is not biodegradable, and therefore, its remediation should encompass either removal of Hg from soils or even its immobilization. This chapter discusses Hg’s chemical behavior, sources, health dangers, and soil remediation methods to lower Hg levels