Discriminatory Efficiency Research Articles

A new diatom-based multimetric index (MMI-D) for ecological health monitoring in the Tropical Rift Valley Lake (Lake Hawassa, Ethiopia)

Multimetric assessment is one of the important tools for diagnosing, detecting and measuring impairment in ecosystem function in lentic ecosystems. It enhances detection capabilities across a broader variety of stressors and offers a more complete picture of ecological conditions than single metrics or biological indicators. In this context, a diatom-based multimetric index (MMI-D) has been developed to evaluate the ecological health of Lake Hawassa. Physicochemical and benthic diatom sampling was conducted at nine sites along the lakeshore, representing varying levels of human disturbance, from February to November in2015 and 2016. The sampling sites were classified a priori into three categories: minimally disturbed (three sites), moderately disturbed (three sites) and highly disturbed (three sites). This classification, was based on a clustering analysis using the percent disturbance score (PDS). Of the 24-diatom candidate metrics, only ten were chosen as core metrics for the development of MMI-D, based on redundancy analysis, reaction to environmental conditions, percent discriminatory efficiency (%DE) and box plots. The newly established MMI-D clearly distinguished between reference and non-reference sites, and between the lake’s three clusters. The MMI-D’s performance was validated using independent data sets from lakes Hawassa and Ziway and it demonstrated the best capability for discrimination between different disturbance levels. MMI-D 2-stage Least Squares (2SLS) regression analysis revealed an inverse but robust connection with the PDS, indicating its responsiveness to Lake Hawassa habitat quality degradation (n = 9, R 2 = 0.921, p < 0.001). The MMI-D revealed a high %DE (95.1%) and a negative but significant connection with nutrients, total suspended solids (TSS), and turbidity (R 2 > 0.6; p < 0.05). Generally, it can be concluded that this index is a powerful tool that could assist endusers by providing a practical method for measuring the ecological quality of Lake Hawassa.

Comparison of an interpretable extreme gradient boosting model and an artificial neural network model for prediction of severe acute pancreatitis.

Acute pancreatitis (AP) that progresses to persistent organ failure is referred to as severe acute pancreatitis (SAP). It is a condition associated with a relatively high mortality. A prediction model that would facilitate early recognition of patients at risk for SAP is crucial for improvement of patient prognosis. The aim of this study was to evaluate the accuracy of extreme gradient boosting (XGBoost) and artificial neural network (ANN) models for predicting SAP. A total of 648 patients with AP were enrolled. XGBoost and ANN models were developed and validated in the training (519 patients) and test sets (129 patients). The accuracy and predictive performance of the XGBoost and ANN models were evaluated using both the area under the receiver operating characteristic curves (AUCs) and the area under the precision‑recall curves (AUC‑PRs). A total of 15 variables were selected for model construction through a univariable analysis. The AUCs of the XGBoost and ANN models in 5‑fold cross‑validation of the training set were 0.92 (95% CI, 0.87-0.97) and 0.86 (95% CI, 0.78-0.92), respectively, whereas the AUCs for the test set were 0.93 (95% CI, 0.85-1) and 0.87 (95% CI, 0.79-0.96), respectively. The XGBoost model outperformed the ANN model in terms of both diagnostic accuracy and AUC‑PR. Individual predictions of the XGBoost model were explained using a local interpretable model‑agnostic explanation plot. An interpretable XGBoost model showed better discriminatory efficiency for predicting SAP than the ANN model, and could be used in clinical practice to identify patients at risk for SAP.

Molecular tracking of Acidovorax citrulli: Unveiling pathogen dynamics and blotch disease outbreaks through specific markers

Acidovorax citrulli (Ac), a gram-negative bacterium, is the causal agent of bacterial fruit blotch (BFB), which poses a significant threat to cucurbit crop production worldwide. Understanding the genetic diversity of Ac is crucial for identifying sources of resistance and implementing effective disease management strategies. In this study, we conducted the first genetic characterization of Ac strains collected in Turkey using Inter-Simple Sequence Repeat (ISSR) markers. These markers were selected based on repetitive domains mapped on the complete reference genome sequence of Acidovorax citrulli strain NWB SC196. The identity of the Turkish strains was confirmed through molecular (PCR) and serological (Immunofluorescence test and ELISA) methods, while the selected ISSRs, which exhibited similarity to flanked regions in the pathogen's whole genome sequence, were employed to assess the genetic diversity among Ac strains. We compared the profiles of Turkish strains with those of a collection of Ac strains from various countries, including the US, to explore a possible common origin. Specifically, we considered the dissemination of these strains through rootstocks used for grafted seedling production (Cucurbita maxima ? Cucurbita moschata). The results demonstrated a shared genetic profile, suggesting a potential link between Ac strains collected in Turkey and foreign strains. The Mauve analysis, utilizing whole genome sequences of various Ac strains available in the NCBI database, displayed similar clustering patterns to those obtained using our selected molecular markers, confirming the discriminatory efficiency of our method. Based on the high discriminatory power of the selected markers, our proposed method offers a rapid and straightforward approach for genetic analysis of intraspecific variation and monitoring Ac gene flow across countries. The characterized strains and markers presented in this study serve as valuable resources and reference materials for further genetic investigations and tracking contamination sources associated with Ac.

Significance of serum sestrin2 as a biomarker of severity and functional outcome in acute intracerebral hemorrhage: a prospective observational longitudinal study

BackgroundSestrin2 is a highly conserved stress-inducible protein with neuroprotective properties. Herein, we investigated the prognostic significance of serum sestrin2 in human intracerebral hemorrhage (ICH).MethodsIn this prospective observational longitudinal study, we enrolled 126 patients with supratentorial ICH as cases together with 126 healthy individuals as controls. Severity indicators were National Institutes of Health Stroke Scale (NIHSS) and hematoma volume. Prognostic parameters were early neurologic deterioration (END) and post-stroke 6-month poor prognosis [modified Rankin Scale (mRS) scores of 3–6]. Multivariate analysis was performed to assess relations of serum sestrin2 levels to severity and prognosis.ResultsPatients had statistically significantly higher serum sestrin2 levels than controls. Serum sestrin2 levels of patients were independently correlated with NIHSS scores and hematoma volume, as well as were substantially elevated in order of mRS scores from 0 to 6. Serum sestrin2 was identified as an independent predictor of END and poor prognosis. Based on the receiver operating characteristic curve, serum sestrin2 had a similar predictive ability for END and poor prognosis, as compared to NIHSS scores and hematoma volume. Prediction models of END and poor prognosis, in which serum sestrin2, NIHSS scores and hematoma volume were integrated, were visually described via nomogram, were reliable and stable under calibration curve and were of clinical benefit using decision curve analysis. Also, prediction model of poor prognosis showed dramatically higher discriminatory efficiency than any of NIHSS scores, hematoma volume and serum sestrin2.ConclusionSerum sestrin2 levels, which are obviously increased following acute ICH, are independently related to illness severity and poor clinical outcomes, substantializing serum sestrin2 as a clinically valuable prognostic biomarker of ICH.

MOLECULAR ASSESSMENT OF GENETIC DIVERGENCE AMONG MAIZE GENOTYPES

Research carried out in 2021 at the Jeser Al-Musayyab Company, Baghdad, Iraq, determined the molecular variations among 10 inbred lines of maize (Zea mays L.), for use in the future production of promising F1 hybrids. DNA sequencing random polymorphism technology using Inter Simple Sequence Repeats (ISSR) with five primers (UBC 834, UBC 835, UBC 856, UBC 866, and UBC 897) assessed the genetic variations among the 10 inbred lines of maize. All five primers produced 29 bands, averaging 5.8 strips each primer. The four primers, UBC 834, UBC 835, UBC 866, and UBC 897, had produced the same and highest number of proliferators with molecular weights ranging from 100 to 2000 bp. The primer UBC 856 showed the lowest number, with a molecular weight of 100–500 bp. The total number of polymorphs was 24, with a percentage of 82.4%, with the lowest (80%) polymorphs recorded in the primer UBC 856. The least discriminatory efficiency and ability values were 17.24% and 16.66%, respectively. Relying on binary data and genetic divergence using the UPGMA method to create a genetic kinship tree, the maize lines were separated into two groups, i.e., A, B, secondary, and sub-secondary groups. The highest genetic similarity (with the lowest genetic divergence) was estimated according to the Nei and Li coefficient of 0.23 between the two lines HS and S-10. The presented findings can provide further guidance and help analyze the genetic diversity among the maize populations.

Development of macroinvertebrate based multimetric index for ecological health monitoring in Lake Hawassa, Ethiopia

Little information is available on the use and applicability of biotic indices in aquatic resource conservation and management in Eastern Africa, especially in lentic ecosystems. The aim of this study was to develop a macroinvertebrate multimetric index (MMIH) to assess the ecological condition of Lake Hawassa. Sampling sites were clustered based on percentage disturbance score (PDS) and categorized into minimally (three sites), moderately (three sites) and highly disturbed (three sites). Physicochemical and invertebrate sampling was done at these clustered sites along the lakeshore area from February to November 2015 and 2016. Out of a total of 35 macroinvertebrate candidate metrics, ten core metrics were selected based on redundancy analysis, metrics response to environmental parameters, percent discriminatory efficiency (%DE) and box and whisker plots, and incorporated in the development of MMIH. The developed MMIH index performed well and showed a clear demarcation between the reference and non-reference sites and between the three-disturbance levels. The validation of the MMIH index performed well in discriminating the independent data sets taken from Lake Hawassa and L. Ziway. Besides, it also showed a strong but inverse relation with PDS (R2 = 0.91, P = 0.0003). Hence, in a lentic ecosystem, this index should be considered as a starting point in terms of lake bio-assessment in Ethiopia, but additional data in all ecoregions of the country are necessary to determine the long-term reliability and usefulness of the MMIH. In the short-term, this index will provide resource managers and aquatic environmentalists with a tool to assess the ecological condition of freshwater lakes.

The combined use of D-dimer testing and the neutrophil-to-lymphocyte ratio in the early differential diagnosis of aortic dissection

ABSTRACT Background The study aimed to ascertain whether a diagnostic strategy combining D-dimer with the neutrophil-to-lymphocyte ratio (NLR) could improve the discriminative performance for aortic dissection (AD). Research design and methods Baseline levels of D-dimer and NLR were measured in patients suspected of AD. The diagnostic performance and clinical usefulness of D-dimer, NLR, and their combination were assessed and compared using receiver operating characteristics (ROC) curve analysis, logistic regression analysis, net reclassification improvement (NRI), integrated discrimination improvement (IDI), and decision curve analysis (DCA). Results The levels of D-dimer and NLR were both significantly higher in AD patients. The combined use displayed good discriminatory performance with an area under ROC curve (AUC) of 0.869, which was preferable to that of D-dimer. Although no meaningful improvement was found in the AUC by comparison with NLR alone, the combined use could significantly improve the discrimination power with a continuous NRI of 60.0% and an IDI of 4.9%. DCA demonstrated that the net benefit of the combined use was preferred over that of either single test. Conclusions The combined use of D-dimer and NLR could improve the discriminatory efficiency for AD with the potential in clinical application. This study may provide a novel diagnostic strategy for AD. More studies need to be done to confirm the findings of this study.

MRI-Based Radiomics Nomogram for Preoperative Differentiation Between Ocular Adnexal Lymphoma and Idiopathic Orbital Inflammation.

Ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI) are malignant and benign lesions for which radiotherapy and corticosteroids are indicated, but similar clinical manifestations make their differentiation difficult. To develop and validate an MRI-based radiomics nomogram for individual diagnosis of OAL vs. IOI. Retrospective. A total of 103 patients (46.6% female) with mean age of 56.4 ± 16.3 years having OAL (n=58) or IOI (n=45) were divided into an independent training (n=82) and a testing dataset (n=21). A 3-T, precontrast T1-weighted imaging (T1WI), T2-weighted imaging (T2WI), and postcontrast T1WI (T1 + C). Radiomics features were extracted and selected from segmented tumors and peritumoral regions in MRI before-and-after filtering. These features, alone or combined with clinical characteristics, were used to construct a radiomics or joint signature to differentiate OAL from IOI, respectively. A joint nomogram was built to show the impact of the radiomics signature and clinical characteristics on individual risk of developing OAL. Area under the curve (AUC) and accuracy (ACC) were used for performance evaluation. Mann-Whitney U and Chi-square tests were used to analyze continuous and categorical variables. Decision curve analysis, kappa statistics, DeLong and Hosmer-Lemeshow tests were also conducted. P < 0.05 was considered statistically significant. The joint signature achieved an AUC of 0.833 (95% confidence interval [CI]: 0.806-0.870), slightly better than the radiomics signature with an AUC of 0.806 (95% CI: 0.767-0.838) (P=0.778). The joint and radiomics signatures were comparable to experienced radiologists referencing to clinical characteristics (ACC=0.810 vs. 0.796-0.806, P > 0.05) or not (AUC=0.806 vs. 0.753-0.791, P > 0.05), respectively. The joint nomogram gained more net benefits than the radiomics nomogram, despite both showing good calibration and discriminatory efficiency (P > 0.05). The developed radiomics-based analysis might help to improve the diagnostic performance and reveal the association between radiomics features and individual risk of developing OAL. 3 TECHNICAL EFFICACY: 3.

Species discrimination of novel chloroplast DNA barcodes and their application for identification of Panax (Aralioideae, Araliaceae).

Certain species within the genus Panax L. (Araliaceae) contain pharmacological precious ginsenosides, also known as ginseng saponins. Species containing these compounds are of high commercial value and are thus of particular urgency for conservation. However, within this genus, identifying the particular species that contain these compounds by morphological means is challenging. DNA barcoding is one method that is considered promising for species level identification. However, in an evolutionarily complex genus such as Panax, commonly used DNA barcodes such as nrITS, matK, psbA-trnH, rbcL do not provide species-level resolution. A recent in silico study proposed a set of novel chloroplast markers, trnQ-rps16, trnS-trnG, petB, and trnE-trnT for species level identification within Panax. In the current study, the discriminatory efficiency of these molecular markers is assessed and validated using 91 reference barcoding sequences and 38 complete chloroplast genomes for seven species, one unidentified species and one sub-species of Panax, and two outgroup species of Aralia L. along with empirical data of Panax taxa present in Vietnam via both distance-based and tree-based methods. The obtained results show that trnQ-rps16 can classify with species level resolution every clade tested here, including the highly valuable Panaxvietnamensis Ha et Grushv. We thus propose that this molecular marker to be used for identification of the species within Panax to support both its conservation and commercial trade.

Unlocking Kautsky’s dark box: Development of an optical toxicity classification tool (OPTOX index) with marine diatoms exposed to emerging contaminants

Chlorophyll a induction curves, or Kautsky curves, have been extensively used to study physiological stress conditions in phototrophic organisms, with the analysis of several derived parameters. Nevertheless, these variables use only about 10 % of the information comprised in the complete Kautsky curve dataset, leaving 90 % of the photochemical data within an underutilized dark box, that is not translated into photochemically relevant variables. By observing the variable fluorescence profiles from marine diatoms exposed to a myriad of emerging and classical contaminants, several fluorescence profile alterations were detected, with significant deviations from the control conditions concomitant with the degree of growth inhibition imposed by the chemical stressor. The Linear Discriminant Analysis (LDA) analysis based on the normalized variable chlorophyll a fluorescence profiles revealed a high discriminatory efficiency of the type of contaminant to which the cultures were exposed, indicating that the exposure to different chemical stressors (contaminants) results in specific fluorescence profiles that can be used as descriptors of these exposure conditions. Analysing the individual contaminant LDA analysis, a very low overlap between samples exposed to different concentrations was observed, indicating a high discriminatory power of the variable fluorescence profiles. When evaluating the blind-test classification efficiencies, provided by this contaminant-specific LDA approach, it was possible to observe a high degree of efficiency in almost all contaminants tested, and for most of the concentrations applied. With this in mind, the produced linear discriminants and proportion of traces was used to compute an optical toxicity classification tool - the OPTOX index. The index revealed a high degree of correlation with the growth inhibition observed and/or with the exogenous dose of contaminant applied. The developed OPTOX index, a unifying tool enclosing all the fluorescence data provided by the chlorophyll a induction curve, proved to be an efficient tool to apply in ecotoxicological assays using marine model diatoms with a high degree of reliability for classifying the exposure of the cells to emerging contaminants. Additionally, the data analysis pipeline, as well as the index development methodology here proposed, can be easily transposed to other autotrophic organisms subjected to different ecotoxicological test conditions calibrated and validated against known biochemical or morphological descriptors of stress, integrating this way a large amount of data that was until know completely overlooked and left within an underutilized and undervalued dark box.

Whole-Genome Sequencing-Based Characterization of a Listeria monocytogenes Strain from an Aborted Water Buffalo in Southern Italy.

Listeria monocytogenes is a Gram-positive pathogen causing life-threatening infections both in humans and animals. In livestock farms, it can persist for a long time and primarily causes uterine infections and encephalitis in farmed animals. Whole genome sequencing (WGS) is currently becoming the best method for molecular typing of this pathogen due to its high discriminatory power and efficiency of characterization. This study describes the WGS-based characterization of an L. monocytogenes strain from an aborted water buffalo fetus in southern Italy. The strain under study was classified as molecular serogroup IVb, phylogenetic lineage I, MLST sequence type 6, Clonal Complex 6, and cgMLST type CT3331, sublineage 6. Molecular analysis indicated the presence of 61 virulence genes and 4 antibiotic resistance genes. Phylogenetic analysis, including all the publicly available European L. monocytogenes serogroup IVb isolates, indicated that our strain clusterized with all the other CC6 strains and that different CCs were variably distributed within countries and isolation sources. This study contributes to the current understanding of the genetic diversity of L. monocytogenes from animal sources and highlights how the WGS strategy can provide insights into the pathogenic potential of this microorganism, acting as an important tool for epidemiological studies.

Discrimination of Iron Deficiency, Alpha and Beta Thalassemia on the Basis of Red Cell Distribution Width and Reticulocyte Indices.

The two major causes of microcytic anemia are iron deficiency and thalassemia. In clinical practice, in some cases, differentiation of microcytic and hypochromic anemia become difficult on the basis of traditional red cell parameters. This study primarily aimed to evaluate the usefulness of red cell distribution width (RDW), immature reticulocyte fraction (IRF), and reticulocyte hemoglobin equivalent (Ret-He) in the discrimination of alpha thalassemia, beta thalassemia, and latent iron deficiency. In this retrospective study laboratory data including complete blood counts of females diagnosed with alpha thalassemia, beta thalassemia, and latent iron deficiency were retrospectively reviewed. Receiver operating characteristic (ROC) curve was constructed to evaluate the applicability and discriminatory efficiency of RDW, IRF, and Ret-He. Sensitivity and specificity of RDW-CV and RDW-SD was lower in the alpha thalassemia and beta thalassemia groups. Immature reticulocyte fraction (IRF) and reticulocyte hemoglobin equivalent (Ret-He) were significantly higher in the iron deficient group as compared to alpha and beta thalassemia. In alpha and beta thalassemia, RDW-SD and RDW-CV were found to be poor discriminators. Sig-nificantly reduced levels of Ret-He were observed in alpha thalassemia and beta thalassemia in comparison to iron deficient group. While iron deficient group was characterized by increased values of RDW-SD, RDW-CV, IRF, and Ret-He.

Sulcus and otolith outline analyses: complementary tools for stock discrimination in white croaker Pennahia argentata in northern Chinese coastal waters

This study analyzed and compared variations of the sulcus and otolith outlines of three geographic stocks (Huanghe (Yellow) River estuary (HHE), Jiaozhou Bay (JZB), and Changjiang (Yangtze) River estuary (CJE)) of white croaker Pennahia argentata in northern Chinese coastal waters. The sulcus and otolith outline analyses via elliptical Fourier transform (EFT, i.e., outline analysis) achieved an overall classification rate of 80.4% and 87.2%, respectively. Based on a combination of sulcus and otolith shape indices (SIs) and two derivative ratios, a moderate discriminatory efficiency of 64.7% was obtained. The results indicate that sulcus outline analysis could be used alone to discriminate white croaker stocks, and that both sulcus and otolith outline analyses discriminated the fish stocks at a higher classification rate than the shape indices. The sulcus outline analysis provided complementary information to the whole otolith outline analysis for stock discrimination. Both the sulcus and otolith outline analyses efficiently discriminated between the most geographically separated CJE and HHE stocks, indicating that they could be considered discrete stocks for fishery management.

Comparison of otolith shape descriptors and morphometrics for stock discrimination of yellow croaker along the Chinese coast

This study compared and evaluated the efficiency of two otolith shape descriptors (i.e., the elliptic Fourier transform (EFT) and discrete wavelet transform (DWT)) and morphometrics for stock discrimination. To accomplish this, sample fish from three stocks of yellow croaker Larimichthys polyactis along the Chinese coast (LDB stock from the Liaodong Bay of the Bohai Sea, JZB stock from the Jiaozhou Bay of the Yellow Sea and CJE stock from the Changjiang River estuary of the East China Sea) were used for otolith morphology analyses. The results showed that morphometrics produced an overall classification success rate of 70.8% in contrast with success rates of 80.0% or 82.0% obtained using EFT or DWT, respectively. This suggests that the two shape descriptors comparably discriminated among the stocks and performed more efficiently than morphometrics. During data adjustment and acquisition, some size variables were excluded from the subsequent discriminant analysis for stock discrimination because they were statistically “ineffective,” which could reduce the efficiency of morphometrics and lead to relatively low overall classification success. Both EFT and DWT retain the contour coefficients and thus provide a detailed description of otolith shape, which could improve discriminatory efficiency compared with morphometrics.

Field scale temporal and spatial variability of δ13C, δ15N, TC and TN soil properties: Implications for sediment source tracing

Use of natural tracers (in particular, δ13C and δ15N, total carbon and nitrogen) for discriminating and apportioning soil sources of eroded sediment has increased. Some critical issues, however, including the variability of such tracers over time and space, merit further investigation. This study used a 25 m grid in a 1.78 ha hydrologically-isolated permanent pasture field in SW England to assess temporal and spatial variability in the discrimination (using Kruskal-Wallis H-tests) of top (0–2 cm) and subsoil (2–10 cm) samples afforded by these tracers. Grid sampling was repeated four times (twice in each of June and July 2015) to assess the impact of temporal variability and Monte Carlo random sub-sampling of the 25 m grid was used to assess the significance of spatial variability for discriminatory efficiency. Using grouped (combining all time-periods) data, all tracers were statistically significant (p ≤ 0.05) for discriminating soil samples by depth. For the repeat sample collection campaigns, δ13C discriminated samples by soil depth in three out of four, δ15N in one and both TC and TN in all periods. Grouped data (all time-periods, both soil depths) yielded statistically significant results for all tracers. All tracers apart from δ15N yielded statistically significant tests for the comparison of topsoil tracers across the four time periods, whilst all tracers except δ13C were significantly different in the subsoil samples across the sampling campaigns. All tracers therefore exhibited some statistically significant temporal variation. δ13C and δ15N exhibited less temporal dependence than TC and TN. Random sub-sampling (n = 10) with 100 iterations of the tracer data grid sampling points did not alter the discriminatory efficiency of the properties. The spatial nature of the tracer data, therefore, did not compromise or confound discrimination between the soil source samples by depth or across time. Un-mixing modelling with virtual sediment mixtures based on equal proportions of the field soil source tracers from each time period and using the field soil source data from each individual period, revealed sensitivity to the temporal dependence of the tracers. Overall, the findings suggest that the temporal variation in the tracers tested requires more consideration than the spatial dimension at the scale of an individual field, which in a conventional erosion source tracing study, would represent one location of many within the target landscape or catchment.

Ordering adjectives in referential communication

• Speakers vary adjective order to facilitate early referent identification. • Adjectives that rule out more referential alternatives are placed earlier. • Adjective ordering is also affected by a production-centered availability effect. • Discriminability and availability affect ordering differently from semantic effects. • Competition in the speaker’s message determines adjective selection and ordering. We contrasted two hypotheses concerning how speakers determine adjective order during referential communication. The discriminatory efficiency hypotheses claims that speakers place the most discriminating adjective early to facilitate referent identification. By contrast, the availability-based ordering hypothesis assumes that speakers produce most available adjectives early to ease production. Experiment 1 showed that speakers use more pattern-before-color modifier orders (than the reversed) when pattern, not color, distinguished the referent from alternatives, providing support for the discriminatory efficiency hypothesis. Participants also overspecified color more often than pattern, and they generally favored color-before-pattern orders, in support of the availability-based ordering hypothesis. Experiments 2 and 3 replicated both effects in a dialogue setting, where speakers’ adjective ordering was also primed by their partner’s ordering, using conjoined and non-conjoined constructions. We propose a novel model ( PASS ) that explains how discriminability and availability simultaneously influence adjective selection and ordering via competition in the speaker’s message representation.

Sediment contribution from different geologic formations and land uses in an Iranian small watershed, case study

Many intra and extra problems occurred due to unsustainable human use of natural resources leading to increasing sediment loads in the watersheds. However, few studies have been comprehensively conducted in progressing countries to prioritize sediment sources from different points of views, particularly in some countries like Iran where such valuable information is essential for proper watershed resources management. The present study was therefore planned to assess the importance of potential sediment sources viz., spatial sources (geologic units) and source types (land use units) in sediment yield in Idelo watershed as one of the important sub-watersheds of Sefidrood large Watershed in Zanjan Province, Iran, using composite fingerprinting. In addition, the results of the sediment fingerprinting approach were compared with those of field measurement data obtained from studying soil erosion types (viz., sheet, rill and gully erosion). Toward this attempt, 16 tracers were detected in different geologic units and land uses and the sediment yielded at the watershed outlet. The results showed that the composite fingerprints of the different geologic units comprising As, N, Cu, Zn, OC and Co tracers could correctly distinguish 86% of the sediment source samples. The red gypsiferous marl contributed 85 percent in sediment yield. In regard to source types, the optimum composite fingerprint encompassed only N and Cu and provided a discriminatory efficiency of 90%. Besides that, the rangelands with 48.8% study area coverage had a significant contribution of 88% in sediment yield. The field measurements confirmed the reliability of results of fingerprinting approach in apportioning watershed scale sediment sources on the base of consistency of the two sets of results. It was also understood from the results, besides successful applicability of composite fingerprinting in assessing the provenance of the sediment yielded at the watershed outlet that the geologic formations and land use types played different roles in sediment yield. Such information helps managers and decision makers to properly regulate appropriate and adaptive management approaches in the study watershed.

Application of phylogenetic information of ITS2 secondary structure in DNA barcoding of Solanum medicinal plant

Internal transcript spacer 2 (ITS2) is one of the broadly used standard core barcodes and also the only nuclear barcode in identification of Chinese traditional medicine. Although the DNA barcode method based on ITS2 is popular and has been used in Chinese Pharmacopoeia, its low discriminatory efficiency is still a problem to its extensive application. Therefore, further study is still necessary to explore its phylogenetic information for medicinal plants identification. In cells, ITS2 activity is based on its secondary structure. The secondary structures are particularly useful in phylogenetic analysis because they include information not found in the primary sequence. In this study ITS2 secondary structure of 40 samples from 26 species were predicted and used to explore their utility in addressing the identification problems of Chinese traditional medicine in Solanum. The secondary structures were predicted and aligned, and their consensus models were generated using the three different software of LocARNA, MASTR and PicXAA-R. RNAstat software was used to transform the secondary structures into 28 symbol code data for maximum parsimony (MP) analysis. The results showed that the phylogenetic information increased 88.57% after ITS2 secondary structure information has been added, and then the support values above 50%, 75% and 90% in the tree increased 19.05%, 66.67% and 66.67%, respectively, indicating that the identification of Solanum medical plants has been well resolved. Thus, our analysis suggests that ITS2 secondary structure information should be incorporated into the current DNA barcoding analysis as a beneficial supplement of phylogenetic information.

Sediment sources in a small agricultural catchment: A composite fingerprinting approach based on the selection of potential sources

Fingerprinting techniques have been widely used as a reasonable and reliable means for investigating sediment sources, especially in relatively large catchments in which there are significant differences in surface materials. However, the discrimination power of fingerprint properties for small catchments, in which the surface materials are relatively homogeneous and human interference is marked, may be affected by fragmentary or confused source information. Using fingerprinting techniques can be difficult, and there is still a need for further studies to verify the effectiveness of such techniques in these small catchments. A composite fingerprinting approach was used in this study to investigate the main sources of sediment output, as well as their relative contributions, from a small catchment (30km2) with high levels of farming and mining activities. The impact of the selection of different potential sediment sources on the derivation of composite fingerprints and its discrimination power were also investigated by comparing the results from different combinations of potential source types. The initial source types and several samples that could cause confusion were adjusted. These adjustments improved the discrimination power of the composite fingerprints. The results showed that the composite fingerprinting approach used in this study had a discriminatory efficiency of 89.2% for different sediment sources and that the model had a mean goodness of fit of 0.90. Cultivated lands were the main sediment source. The sediment contribution of the studied cultivated lands ranged from 39.9% to 87.8%, with a mean of 76.6%, for multiple deposited sediment samples. The mean contribution of woodlands was 21.7%. Overall, the sediment contribution from mining and road areas was relatively low. The selection of potential sources is an important factor in the application of fingerprinting techniques and warrants more attention in future studies, as is the case with other uncertainty factors.

Cyclodextrin based ternary system of modafinil: Effect of trimethyl chitosan and polyvinylpyrrolidone as complexing agents

Modafinil is an approved drug for the treatment of narcolepsy and have a strong market presence in many countries. The drug is widely consumed for off-label uses and currently listed as a restricted drug. Modafinil has very low water solubility. To enhance the aqueous solubility of modafinil by the formation of a ternary complex with Hydroxypropyl-β-cyclodextrin and two hydrophilic polymers was the main objective of the present study. Pyrrolidone (PVP K30) and a water soluble chitosan derivative, trimethyl chitosan (TMC) were studied by solution state and solid state characterization methods for their discriminatory efficiency in solubility enhancement of modafinil. Phase solubility study depicted the highest complexation efficiency (2.22) of cyclodextrin derivative in the presence of TMC compared to the same in the presence of PVP K30 (0.08) and in the absence of any polymer (0.92). FT-IR analysis of binary and ternary complex expressed comparable contribution of both polymers in formation of inclusion complex. The thermal behaviour of binary and ternary complex, involving individual polymers disclosed the influence of TMC on polymorphism of the drug. DSC study revealed efficiency of TMC to prevent conversion of metastable polymorphic form to stable polymorphic form. Ternary complex, involving TMC enhanced water solubility of the drug 1.5 times more compared to the binary complex of the drug whereas PVP K30 reduced the Solubility.