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.

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.

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.

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).

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.

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.

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.

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).