Determination of Carboplatin Dose by Area Under the Curve in Combination Chemotherapy for Senile Non-small Cell Lung Cancer

To preliminarily determine the appropriate dosage of carboplatin （CBP） at AUC of 5 mg-M1^-1·min^-1 in the combination chemotherapy for Chinese senile patients with non-small cell lung cancer （NSCLC）. Thirty-five Chinese senile patients with NSCLC in advanced stage （Ⅲ/Ⅳ） were given 96 cycles of combination chemotherapy. Chemotherapy schedules included Taxol＋CBP, Gemzar＋CBP and NVB＋CBE The dose of CBP was at 5 mg.mL^-1·min^-1 of area under the concentration-time curve （AUC）. Side effects and quality of life were observed before and after the chemotherapy. Myelosuppression was severe and commonly observed. Grade 3/4 of granulocytopenia was found in 47.9% （46/96） of the patients and grade 3/4 of thrombocytopenia was noted in 28.1% （27/96） of the subjects. However, other side effects were slight. The mean score of quality of life （QOL）, according to the criteria of QOL for Chinese cancer patients had reduced 6.8. At 5 mg.mL^-1·min^-1 by AUC, the hematological toxicity of CBP was severe and it had some negative effects on the QOL. The administration of CBP at 5 mg.mL^-1·min^-1 by AUC may be too high for Chinese senile patients with non-small cell lung cancer.

Area under the curve of methotrexate and creatinine clearance are outcome - determining factors in primary CNS lymphomas

Although high-dose methotrexate(HD-MTX)is the most effective drug against primary CNS lymphomas(PCNSL),outcome-de-termining variables related to its administration schedule have not been defined.The impact on toxicity and outcome of the area under thecurve(AUC(MTX)),dose intensity(DI(MTX))and infusion rate(IR(MTX))of MTX and plsamatic creatinine clearance(CL(crea))was investigated in a retrospective series of 45 PCNSL patients treated with three different HD-MTX-basedcombinations.Anticon-vulsants were administered in 31 pts(69%).Age>60 years,anticonvulsant therapy,slow IR(MTX)(

Predicting potential invasion risks of Leucaena leucocephala(Lam.)de Wit in the arid area of Saudi Arabia

The presence of invasive plant species poses a substantial ecological impact,thus comprehensive evaluation of their potential range and risk under the influence of climate change is necessary.This study uses maximum entropy(MaxEnt)modeling to forecast the likelihood of Leucaena leucocephala(Lam.)de Wit invasion in Saudi Arabia under present and future climate change scenarios.Utilizing the MaxEnt modeling,we integrated climatic and soil data to predict habitat suitability for the invasive species.We conducted a detailed analysis of the distribution patterns of the species,using climate variables and ecological factors.We focused on the important influence of temperature seasonality,temperature annual range,and precipitation seasonality.The distribution modeling used robust measures of area under the curve(AUC)and receiver-operator characteristic(ROC)curves,to map the invasion extent,which has a high level of accuracy in identifying appropriate habitats.The complex interaction that influenced the invasion of L.leucocephala was highlighted by the environmental parameters using Jackknife test.Presently,the actual geographic area where L.leucocephala was found in Saudi Arabia was considerably smaller than the theoretical maximum range,suggesting that it had the capacity to expand further.The MaxEnt model exhibited excellent prediction accuracy and produced reliable results based on the data from the ROC curve.Precipitation and temperature were the primary factors influencing the potential distribution of L.leucocephala.Currently,an estimated area of 216,342 km^(2)in Saudi Arabia was at a high probability of invasion by L.leucocephala.We investigated the potential for increased invasion hazards in the future due to climate change scenarios(Shared Socioeconomic Pathways(SSPs)245 and 585).The analysis of key climatic variables,including temperature seasonality and annual range,along with soil properties such as clay composition and nitrogen content,unveiled their substantial influence on the distribution dynamic of L.leucocephala.Our findings indicated a significant expansion of high risk zones.High-risk zones for L.leucocephala invasion in the current climate conditions had notable expansions projected under future climate scenarios,particularly evident in southern Makkah,Al Bahah,Madina,and Asir areas.The results,backed by thorough spatial studies,emphasize the need to reduce the possible ecological impacts of climate change on the spread of L.leucocephala.Moreover,the study provides valuable strategic insights for the management of invasion,highlighting the intricate relationship between climate change,habitat appropriateness,and the risks associated with invasive species.Proactive techniques are suggested to avoid and manage the spread of L.leucocephala,considering its high potential for future spread.This study enhances the overall comprehension of the dynamics of invasive species by combining modeling techniques with ecological knowledge.It also provides valuable information for decision-making to implement efficient conservation and management strategies in response to changing environmental conditions.

Deep Learning-Based ECG Classification for Arterial Fibrillation Detection

The application of deep learning techniques in the medical field,specifically for Atrial Fibrillation(AFib)detection through Electrocardiogram(ECG)signals,has witnessed significant interest.Accurate and timely diagnosis increases the patient’s chances of recovery.However,issues like overfitting and inconsistent accuracy across datasets remain challenges.In a quest to address these challenges,a study presents two prominent deep learning architectures,ResNet-50 and DenseNet-121,to evaluate their effectiveness in AFib detection.The aim was to create a robust detection mechanism that consistently performs well.Metrics such as loss,accuracy,precision,sensitivity,and Area Under the Curve(AUC)were utilized for evaluation.The findings revealed that ResNet-50 surpassed DenseNet-121 in all evaluated categories.It demonstrated lower loss rate 0.0315 and 0.0305 superior accuracy of 98.77%and 98.88%,precision of 98.78%and 98.89%and sensitivity of 98.76%and 98.86%for training and validation,hinting at its advanced capability for AFib detection.These insights offer a substantial contribution to the existing literature on deep learning applications for AFib detection from ECG signals.The comparative performance data assists future researchers in selecting suitable deep-learning architectures for AFib detection.Moreover,the outcomes of this study are anticipated to stimulate the development of more advanced and efficient ECG-based AFib detection methodologies,for more accurate and early detection of AFib,thereby fostering improved patient care and outcomes.

Efficacy of a Diabetes Specific Nutritional Supplement (DSNS) on Glycemic Response in Prediabetic Adults: A Two-Armed, Open-Labelled Randomized Controlled Study

It is well known that Diabetes Specific Nutritional Supplements (DSNSs) are linked to improved glycemic control in individuals with diabetes. However, data on efficacy of DSNSs in prediabetics is limited. This was a two-armed, open-labelled, randomized controlled six-week study on 199 prediabetics [30 - 65 years;Glycosylated Hemoglobin (HbA1c) 5.7% - 6.4% and/or Fasting Blood Glucose (FBG) 100-125 mg/dl]. Two parallel phases were conducted: Acute Blood Glucose Response (ABGR) and Intervention phase. Prediabetic participants were randomized into test (n = 100) and control (n = 99). The primary objective was to assess the ABGR of DSNS versus an isocaloric snack, measured by incremental Area under the Curve (iAUC). Test and control received 60 g of DSNS and 56 g of isocaloric snack (cornflakes) respectively, both in 250 ml double-toned milk on visit days 1, 15, 29 and 43. Postprandial Blood Glucose (PPG) was estimated at 30, 60, 90, 120, 150 and 180 minutes. During the 4 weeks intervention phase, the test group received DSNS with lifestyle counselling (DSNS + LC) and was compared with the control receiving lifestyle counselling alone (LC alone). Impact was studied on FBG, HbA1C, anthropometry, body composition, blood pressure, nutrient intake, and physical activity. The impact of DSNS was also studied using CGM between two 14-day phases: CGM1 baseline (days 1 - 14) and CGM2 endline (days 28 - 42). DSNS showed significantly lower PPG versus isocaloric snack at 30 (p 12, and chromium were reported by DSNS + LC versus LC alone. No other significant changes were reported between groups. It may be concluded that DSNS may be considered as a snack for prediabetic or hyperglycemic individuals requiring nutritional support for improved glycemic control.

Preoperative prediction of hepatocellular carcinoma microvascular invasion based on magnetic resonance imaging feature extraction artificial neural network

BACKGROUND Hepatocellular carcinoma(HCC)recurrence is highly correlated with increased mortality.Microvascular invasion(MVI)is indicative of aggressive tumor biology in HCC.AIM To construct an artificial neural network(ANN)capable of accurately predicting MVI presence in HCC using magnetic resonance imaging.METHODS This study included 255 patients with HCC with tumors<3 cm.Radiologists annotated the tumors on the T1-weighted plain MR images.Subsequently,a three-layer ANN was constructed using image features as inputs to predict MVI status in patients with HCC.Postoperative pathological examination is considered the gold standard for determining MVI.Receiver operating characteristic analysis was used to evaluate the effectiveness of the algorithm.RESULTS Using the bagging strategy to vote for 50 classifier classification results,a prediction model yielded an area under the curve(AUC)of 0.79.Moreover,correlation analysis revealed that alpha-fetoprotein values and tumor volume were not significantly correlated with the occurrence of MVI,whereas tumor sphericity was significantly correlated with MVI(P<0.01).CONCLUSION Analysis of variable correlations regarding MVI in tumors with diameters<3 cm should prioritize tumor sphericity.The ANN model demonstrated strong predictive MVI for patients with HCC(AUC=0.79).

Gut microbiota predicts the diagnosis of ulcerative colitis in Saudi children

BACKGROUND Ulcerative colitis(UC)is an immune-mediated chronic inflammatory condition with a worldwide distribution.Although the etiology of this disease is still unknown,the understanding of the role of the microbiota is becoming increasingly strong.AIM To investigate the predictive power of the gut microbiota for the diagnosis of UC in a cohort of newly diagnosed treatment-naïve Saudi children with UC.METHODS The study population included 20 children with a confirmed diagnosis of UC and 20 healthy controls.Microbial DNA was extracted and sequenced,and shotgun metagenomic analysis was performed for bacteria and bacteriophages.Biostatistics and bioinformatics demonstrated significant dysbiosis in the form of reduced alpha diversity,beta diversity,and significant difference of abundance of taxa between children with UC and control groups.The receiver operating characteristic curve,a probability curve,was used to determine the difference between the UC and control groups.The area under the curve(AUC)represents the degree of separability between the UC group and the control group.The AUC was calculated for all identified bacterial species and for bacterial species identified by the random forest classification algorithm as important potential biomarkers of UC.A similar method of AUC calculation for all bacteriophages and important species was used.RESULTS The median age and range were 14(0.5-21)and 12.9(6.8-16.3)years for children with UC and controls,respectively,and 40%and 35%were male for children with UC and controls,respectively.The AUC for all identified bacterial species was 89.5%.However,when using the bacterial species identified as important by random forest classification algorithm analysis, the accuracy increased to 97.6%. Similarly, the AUC for all theidentified bacteriophages was 87.4%, but this value increased to 94.5% when the important bacteriophagebiomarkers were used.CONCLUSIONThe very high to excellent AUCs of fecal bacterial and viral species suggest the potential use of noninvasivemicrobiota-based tests for the diagnosis of unusual cases of UC in children. In addition, the identification ofimportant bacteria and bacteriophages whose abundance is reduced in children with UC suggests the potential ofpreventive and adjuvant microbial therapy for UC.

Reduced hemoglobin and increased C-reactive protein are associated with upper gastrointestinal bleeding

AIM: To investigate the early upper gastrointestinal endoscopy (endoscopy) significantly reduces mortality resulting from upper gastrointestinal (GI) bleeding.

Integrating vegetation indices and geo-environmental factors in GIS-based landslide-susceptibility mapping:using logistic regression

This study aimed to assess the potential of in-situ measured soil and vegetation characteristics in landslide susceptibility analyses.First,data for eight independent variables,i.e.,soil moisture content,soil organic content,compaction of soil(soil toughness),plant root strength,crop biomass,tree diameter at knee height,Shannon Wiener Index(SWI)for trees and herbs was assembled from field tests at two historic landslide locations:Aranayaka and Kurukudegama,Sri Lanka.An economical,finer resolution database was obtained as the field tests were not cost-prohibitive.The logistic regression(LR)analysis showed that soil moisture content,compaction of soil,SWI for trees and herbs were statistically significant at P<0.05.The variance inflation factors(VIFs)were computed to test for multicollinearity.VIF values(<2)confirmed the absence of multicollinearity between four independent variables in the LR model.Receiver Operating Characteristics(ROC)curve and Confusion Metrix(CM)methods were used to validate the model.In ROC analysis,areas under the curve of Success Rate Curve and Prediction Rate Curve were 84.5% and 96.6%,respectively,demonstrating the model’s excellent compatibility and predictability.According to the CM,the model demonstrated a 79.6% accuracy,63.6% precision,100% recall,and a F-measure of 77.8%.The model coefficients revealed that the vegetation cover has a more significant contribution to landslide susceptibility than soil characteristics.Finally,the susceptibility map,which was then classified as low,medium,and highly susceptible areas based on the natural breaks(Jenks)method,was generated using geographical information systems(GIS)techniques.All the historic landslide locations fell into the high susceptibility areas.Thus,validation of the model and inspection of the susceptibility map indicated that the in-situ soil and vegetation characteristics used in the model could be employed to demarcate historical landslide patches and identify landslide susceptible locations with high confidence.

Angiopoietin-2/angiopoietin-1 as non-invasive biomarker of cirrhosis in chronic hepatitis C

AIM To evaluate the efficacy of peripheral blood concentrations of angiopoietins(Ang) as cirrhosis biomarkers of chronic hepatitis C(CHC).METHODS Ang1 and Ang2 serum levels were measured by enzyme-linked immunosorbent assays(ELISA) in samples from 179 cirrhotic and non-cirrhotic CHC patients, classified according to the METAVIR system.Groups were compared by non-parametric MannWhitney U test. Subsequently, the association of peripheral concentrations of angiopoietins with the stage of fibrosis was analyzed using Spearman correlation test. Finally, the accuracy, sensitivity and specificity of circulating angiopoietins for cirrhosis diagnosis were determined by the study of the respective area under the curve of receiver operator characteristics(AUC-ROC).RESULTS Peripheral blood concentrations of Ang1 and Ang2 in CHC patients were significantly related to fibrosis. While Ang1 was decreased in cirrhotic subjects compared to non-cirrhotic(P < 0.0001), Ang2 was significantly increased as CHC progressed to the end stage of liver disease(P < 0.0001). Consequently, Ang2/Ang1 ratio was notably amplified and significantly correlated with fibrosis(P < 0.0001). Interestingly, the individual performance of each angiopoietin for the diagnosis of cirrhosis reached notable AUC-ROC values(above 0.7, both), but the Ang2/Ang1 ratio was much better(AUC-ROC = 0.810) and displayed outstanding values of sensitivity(71%), specificity(84%) and accuracy(82.1%) at the optimal cut-off(10.33). Furthermore, Ang2/Ang1 ratio improved the performance of many other previously described biomarkers or scores of liver cirrhosis in CHC.CONCLUSION Ang2/Ang1 ratio might constitute a useful tool for monitoring the progression of chronic liver disease towards cirrhosis and play an important role as therapeutic target.

Mapping favorable groundwater potential recharge zones using a GIS-based analytical hierarchical process and probability frequency ratio model:A case study from an agro-urban region of Pakistan

In Punjab(Pakistan),the increasing population and expansion of land use for agriculture have severely exploited the regional groundwater resources.Intensive pumping has resulted in a rapid decline in the level of the water table as well as its quality.Better management practices and artificial recharge are needed for the development of sustainable groundwater resources.This study proposes a methodology to delineate favorable groundwater potential recharge zones(FPRI)by integrating maps of groundwater potential recharge index(PRI)with the DRASTIC-based groundwater vulnerability index(VI).In order to evaluate both indexes,different thematic layers corresponding to each index were overlaid in ArcGIS.In the overlay analysis,the weights(for various thematic layers)and rating values(for sub-classes)were allocated based on a review of published literature.Both were then normalized and modified using the analytical hierarchical process(AHP)and a frequency ratio model respectively.After evaluating PRI and FPRI,these maps were validated using the area under the curve(AUC)method.The PRI map indicates that 53%of the area assessed exists in very low to low recharge zones,22%in moderate,and 25%in high to excellent potential recharge zones.The VI map indicates that 38%of the area assessed exists in very low to low vulnerability,33%in moderate,and 29%in high to very high vulnerability zones.The FPRI map shows that the central region of Punjab is moderately-to-highly favorable for recharge due to its low vulnerability and high recharge potential.During the validation process,it was found that the AUC estimated with modified weights and rating values was 79%and 67%,for PRI and VI indexes,respectively.The AUC was less when evaluated using original weights and rating values taken from published literature.Maps of favorable groundwater potential recharge zones are helpful for planning and implementation of wells and hydraulic structures in this region.

Oral glucose tolerance test in diabetes,the old method revisited

The oral glucose tolerance test(OGTT)has been widely used both in clinics and in basic research for a long time.It is applied to diagnose impaired glucose tolerance and/or type 2 diabetes mellitus in individuals.Additionally,it has been employed in research to investigate glucose utilization and insulin sensitivity in animals.The main aim of each was quite different,and the details are also somewhat varied.However,the time or duration of the OGTT was the same,using the 2-h post-glucose load glycemia in both,following the suggestions of the American Diabetes Association.Recently,the use of 30-min or 1-h post-glucose load glycemia in clinical practice has been recommended by several studies.In this review article,we describe this new view and suggest perspectives for the OGTT.Additionally,quantification of the glucose curve in basic research is also discussed.Unlike in clinical practice,the incremental area under the curve is not suitable for use in the studies involving animals receiving repeated treatments or chronic treatment.We discuss the potential mechanisms in detail.Moreover,variations between bench and bedside in the application of the OGTT are introduced.Finally,the newly identified method for the OGTT must achieve a recommendation from the American Diabetes Association or another official unit soon.In conclusion,we summarize the recent reports regarding the OGTT and add some of our own perspectives,including machine learning and others.

Comparative research on the prognostic ability of improved early warning and APACHE Ⅱ evaluation for hospitalized patients in the emergency department

Objective： To compare the feasibility and applicability of predicting the prognosis of patients using the Early Warning Score（MEWS） system and the Acute Physiology and Chronic Health Evaluation（APACHE Ⅱ） system in the Emergency Department.Methods： Using a prospective study method, the APACHE Ⅱ and MEWS data for 640 patients hospitalized in the Emergency Internal Medicine Department were collected. The prognoses, two scores to predict the corresponding prediction index of sensitivity, specificity and positive predictive value for the prognosis,the negative predictive value and the ROC curve for predicting the prognosis were analyzed for all patients.Results： In the prediction of the risk of mortality, the MEWS system had a high resolution. The MEWS area under the ROC curve was 0.93. The area under the ROC curve for the APACHE score was 0.79, and the difference was statistically significant（Z =4.348, P 〈 0.01）.Conclusions： Both the MEWS and APACHE Ⅱ systems can be used to determine the severity of emergency patients and have a certain predictive value for the patient＇s mortality risk. However, the MEWS system is simple and quick to operate, making it a useful supplement for APACHE Ⅱ score.

Development of a drill energy utilization index for aiding selection of drill machines in surface mines

Drill machines used in surface mines, particularly in coal, is characterized by a very poor utilization （around 40%） and low availability （around 60%）. The main purpose of this study is to develop a drill selec- tion methodology and simultaneously a performance evaluation technique based on drill cuttings produced and drilling rate achieved. In all 28 blast drilled through were investigated. The drilling was accomplished by 5 different drill machines of Ingersoll-Rand and Revathi working in coal mines of Sonepur Bazari （SECL） and Block-II （BCCL）. The drills are Rotary and Rotary Percussive type using tri- cone rock roller bits. Drill cuttings were collected and sieve analysis was done in the laboratory. Using Rosin Ramler Diagram, coarseness index （CI）, mean chip size （d）, specific-st trace area （SSA） and charac- teristic particle size distribution curves for all the holes drilled were plotted. The predictor equation for drill penetration rate established through multiple regressions was found to have a very good correlation with an index of determination of 0.85. A comparative analysis of particle size distribution curves was used to evaluate the drill efficiency. The suggested approach utilises the area under the curve, after the point of trend reversal and brittleness ratio of the respective bench to arrive at drill energy utilization index （DEUI）, for mapping of drill machine to bench, The developed DEU1 can aid in selecting or mapping a right machine to right bench for achieving higher penetration rate and utilizations.

Predicting the invasion of a southern African savannah by the black wattle (Acacia mearnsii)

Understanding the drivers of biological invasions in landscapes is a major goal in invasion ecology.The control of biological invasions has increasingly become critical in the past few decades because invasive species are thought to be a major threat to endemism.In this study,by examining the key variables that influence Acacia mearnsii,we sought to understand its potential invasion in eastern Zimbabwe.We used the maximum entropy(MaxEnt)method against a set of environmental variables to predict the potential invasion front of A.mearnsii.Our study showed that the predictor variables,i.e.,aspect,elevation,distance from streams,soil type and distance from the nearest A.mearnsii plantation adequately explained(training AUC=0.96 and test AUC=0.93)variability in the spatial distribution of invading A.mearnsii.The front of invasion by A.mearnsii seemed also to occur next to existing A.mearnsii plantations.Results from our study could be useful in identifying priority areas that could be targeted for controlling the spread of A.mearnsii in Zimbabwe and other areas under threat from A.mearnsii invasion.We recommend that the plantation owners pay for the control of A.mearnsii invasion about their plantations.

Machine Learning-Based Threatened Species Translocation Under Climate Vulnerability

Climate change is the most serious causes and has a direct impact on biodiversity.According to the world’s biodiversity conservation organization,rep-tile species are most affected since their biological and ecological qualities are directly linked to climate.Due to a lack of time frame in existing works,conser-vation adoption affects the performance of existing works.The proposed research presents a knowledge-driven Decision Support System(DSS)including the assisted translocation to adapt to future climate change to conserving from its extinction.The Dynamic approach is used to develop a knowledge-driven DSS using machine learning by applying an ecological and biological variable that characterizes the model and mitigation processes for species.However,the frame-work demonstrates the huge difference in the estimated significance of climate change,the model strategy helps to recognize the probable risk of threatened spe-cies translocation to future climate change.The proposed system is evaluated using various performance metrics and this framework can comfortably adapt to the decisions support to reintroduce the species for conservation in the future.

Responses to oral glucose challenge differ by physical activity volume and intensity: A pilot study

Background:One-hour postprandial hyperglycemia is associated with increased risk of type 2 diabetes and cardiovascular disease.Physical activity(PA)has short-term beneficial effects on post-meal glucose response.This study compared the oral glucose tolerance test results of 3 groups of people with habitually different levels of PA.Methods:Thirty-one adults without diabetes(age 25.9±6.6 years;body mass index 23.8±3.8 kg/m^2;mean±SD)were recruited and divided into 3 groups based on self-reported PA volume and intensity:low activity<30 min/day of moderate-intensity activity(n=11),moderately active≥30 min/day of moderate-intensity PA(n=10),and very active≥60 min/day of PA at high intensity(n=10).Participants completed an oral glucose tolerance test(50 g glucose)with capillary blood samples obtained at baseline,15 min,30 min,45 min,60 min,90 min,and 120 min post-ingestion.Results:There were no significant differences between groups for age or body fat percentage or glycated hemoglobin(p>0.05).The groups were significantly different in terms of baseline glucose level(p=0.003)and,marginally,for gender(p=0.053)and BMI(p=0.050).There was a statistically significant effect of PA on the 1-h postprandial glucose results(p=0.029),with differences between very active and low activity groups(p=0.008)but not between the moderately active and low activity groups(p=0.360),even when baseline glucose level and gender differences were accounted for.For incremental area under the curve there was no significant effect of activity group once gender and body fat percentage had been accounted for(p=0.401).Those in the low activity group took 15 min longer to reach peak glucose level than those in the very active group(p=0.012).Conclusion:The results suggest that high levels of PA have a beneficial effect on postprandial blood glucose profiles when compared to low and moderate levels of activity.

Glycemic Indices of Multiple Oral Nutritional Supplements: A Randomized Cross-Over Study in Indian Adults

Background: A randomized cross-over study was conducted to assess the glycemic index (GI) of seven Oral Nutritional Supplements (ONSs). These ONSs are designed to support the nutritional requirements of different age-groups, physiological states, or health conditions among Indian adults. Methods: The study had two phases viz., phase1 (n = 18) studied two ONSs: A1 and B1 and phase 2 (n = 20) studied five ONSs: A2, B2, C2, D2 & E2. The subjects were healthy, non-diabetic adults, aged between 20 - 44 years with a mean Body Mass Index of 21.2 ± 1.52 kg/m2 (Phase 1) and 21.0 ± 1.45 kg/m2 (Phase 2). All these ONSs were compared with reference drinks (glucose). The carbohydrates in one serving of each ONS were matched to carbohydrates from 25 grams of glucose following ISO 2010 guidelines. Capillary blood was assessed for blood glucose response at baseline, 15, 30, 45, 60, 90 and 120 minutes. GI was calculated as the incremental area under the curve (iAUC) for the test drinks and expressed as a percentage of the average iAUC from glucose. Results: Phase 1 indicated that the high fiber diabetes-specific nutrition supplement A1 with higher protein (23% energy), higher fat (25% energy) and reduced carbohydrates (40% energy) had a significantly (p = 0.002) lower GI [34 (±6)] as compared to B1 [63 (±7)] (protein 19%, fat 7% and carbohydrates 60% energy) even with similar amount (22%) and type of fiber. Phase 2 reported that all test products [A2 (32 ± 5), B2 (37 ± 4), C2 (31 ± 5), D2 (31 ± 5) and E2 (55 ± 4)] had a low GI. As compared to phase 1, ONSs in phase 2 had lower fiber content (1.6% - 4.6% energy). Conclusion: The glycemic index of oral nutrition supplements is influenced not only by their fiber content, but also by the overall macronutrient composition including protein (≥17% energy), fat (≥10% - 27% energy) and carbohydrates (40% - 57.5% energy).

Pharmacokinetic comparison between ultraselection of uterine artery and peripheral vein chemotherapy of carboplatin in cervical cancer

Objective:The present study is to compare pharmacokinetics difference of carboplatin by using ultraselection uterine artery with by using peripheral vein in cervical cancer.Methods:Thirteen patients with locally advanced cervical cancer who had been proved by pathobiology were randomly divided into two groups:the ultraselection uterine artery group(group A, n = 6) and the peripheral vein(group B, n = 7).Carboplatin was administered by infusing into artery or vein in both groups at the dosage of 300 mg/m2.Tissues from the cervical tumor were collected at different times after infusion in both groups and then analyzed.Results:The peak concentration of platinum in tumor tissue was about 2.79 times higher in group A than that of group B(P < 0.05).The platinum concentrations in tumor in group A reached its peak levels immediately after infusion.But, group B had delayed time.While, for the time point of 0 min, when the administration finished immediately, the platinum concentration in tumor was significantly higher when compared with group B(P < 0.05).The tumor tissue area under the concentration(AUC) of carboplatin was about 2 times higher in group A than that of group B(P < 0.05).Conclusion:We observed the pharmacological advantages of chemotherapy by using ultraselection uterine artery administration of chemotherapeutic agent carboplatin in tumor tissue which provided theoretical basis and laboratory parameters of the intra-arterial chemotherapy for gynecologic malignancy.

Mapping of Freshwater Snails’ Habitat—A Source of Transmitting Bilharzia in Mwea Sub-County, Kenya

Bilharzia is vector-borne disease carried by a parasite that is hosted by fresh water snails. The distribution of the disease is concurrent with the existence of the freshwater snails and is dependent on certain suitable environmental conditions. It is difficult to identify the specific habitats of the snails as they are often inaccessible on the ground, the snails also migrate by means of flowing water, making it difficult to keep a track of the freshwater snails’ habitat. This paper aimed at using GIS, Remote Sensing and Species Distribution Modelling techniques to model the suitable habitats for the freshwater snails and to prove that the snails migrate when there are sudden changes in water levels whilst showing the population at risk of bilharzia. The SDM used is the Maximum Entropy (MAXENT) for its ability to make right predictions even with small presence sites. The AUC value of the model was 0.951. The research results showed that the environmental variables;brightness Index, elevation, temperatures were negatively correlated with the snails’ presence while the wetness index, MSAVI, greenness index and soil pH were positively correlated. The snails are observed to favor clay soils of the montmorillonite type and the crop-lands land cover. Areas consistently submerged by water especially after flooding are shown to be the most suitable areas where snails migrate by means of river or canal water. The research proves that Mwea is not the source habitat of the freshwater snails. The neighboring sub-counties within Kirinyaga County should be investigated using such models as a likely source-habitat of the freshwater snails. Destroying the source habitats will lead to complete eradication of the freshwater snails within Mwea.