What are the Andean Colombian anurans? Empirical regionalization proposals vs. observed patterns of compositional dissimilarity

Background

Defining Andean anurans through their altitudinal limits has been a common practice in species lists, studies of responses to climate change among others, especially in the northern Andes. At least three proposals to differentiate Andean anurans from lowland anurans through elevation and at least one to differentiate Andean anurans from high mountain anurans have been formulated. However, the most frequently used altitudinal limits are not based on theoretical or numerical support, but on observations or practical definitions. Additionally, these proposals have been applied equally to different portions of the Andes, ignoring the fact that even between slopes of the same mountain, environmental conditions (and therefore the distribution of species) may differ. The objective of this work was to evaluate the concordance between the altitudinal distribution of anurans in the Colombian Andes and four different altitudinal delimitation proposals.

Methods

We constructed our study area in a manner that allowed us to include species from the Andean region (as traditionally defined) and adjacent lowlands, because if the boundaries criteria were applied they would separate the species of the latter by themselves. We divided the study area into eight entities according to the watershed and the course of the most important rivers. We conducted a bibliographic search for all anurans in the cordilleras and inter-Andean valleys of Colombia and complemented the search with information on anurans for the region available in the GBIF. After curing the species distribution points, we generated elevation bands of 200 m amplitude for both the study area and for each Andean entity. Subsequently, we performed a cluster analysis to evaluate the grouping of the elevation bands according to their species composition.

Results

In none of the cases (neither for the entire study area nor for any of the entities) we found a correspondence of any of the traditionally used boundaries and the altitudinal distribution of Anurans in the Andean region of Colombia. Instead, on average, the altitudinal delimitation proposals arbitrarily spanned the altitudinal distribution of about one third of the species distributed in the study area.

Conclusions

We suggest that, although, based on our results, some Andean entities can be divided according to the altitudinal composition of the species that occur in them, we did not find any results that support the idea of a generalizable altitudinal limit for the Colombian Andes. Thus, to avoid biases in studies that may later be used by decision makers, the selection of anuran species in studies in the Colombian Andes should be based on biogeographic, phylogenetic or natural history criteria and not on altitudinal limits as they have been used.

Comparison of swept-source OCTA and indocyanine green angiography in central serous chorioretinopathy

Background

To compare swept-source optical coherence tomography angiography (SS-OCTA) and indocyanine green angiography (ICGA) in patients with central serous chorioretinopathy (CSC).

Methods

SS-OCTA and ICGA images of 39 eyes with symptomatic CSC were collected and aligned. Spatial overlap of the annotations of the coarse granulated high reflective area on choriocapillary OCTA and the hyperfluorescence area on mid-phase ICGA was calculated according to the Jaccard index (JI). SS-OCTA findings of fellow eyes and changes in SS-OCTA abnormalities during the follow-up were also analyzed.

Results

Three main types of abnormalities in choriocapillaris SS-OCTA images were found: type A, coarse granulated high reflective area (39 eyes [100%]); type B, roundish dark halo around Type A (32 eyes [82.1%]); and type C, coarse granulated low reflective area (39 eyes [100%]). The mean JI of type A on SS-OCTA and the hyperfluorescence area on ICGA were 0.55 ± 0.15 for grader 1 and 0.49 ± 0.15 for grader 2. The mean area of type A abnormalities on SS-OCTA and hyperfluorescence on ICGA was 3.976 (IQR, 2.139–8.168) and 3.043 (IQR, 1.408–4.909) mm² (P = 0.199). The areas of type A, B and C abnormalities on SS-OCTA after laser treatment or observation were 3.36mm² (IQR, 2.399–9.312), 2.9mm² (IQR, 2.15–3.7), and 0.19mm² (IQR, 0.08–0.23), respectively, which was smaller than those in the baseline (7.311mm² (IQR 3.788–11.209), P < 0.001; 4.3mm² (IQR, 2.8–9.8), P = 0.002;0.33mm² (IQR, 0.23–0.38), P < 0.001). The change in the type A, B or C area was not significantly different between the two groups (P = 0.679, 0.732, and 0.892).

Conclusion

The coarse granulated high reflective area in SS-OCTA corresponded well with the hyperpermeability area in ICGA. SS-OCTA promotes noninvasive visualization and follow-up quantifications of the choroidal vasculature in CSC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12886-022-02607-4.

Hierarchical cluster analysis of herbicide modes of action reveals distinct classes of multiple resistance in weeds

BACKGROUND

The number of weed species resistant to multiple herbicide modes of action (MoAs) has increased over the last 30 years and may in the future render existing herbicide MoAs obsolete for many cropping systems. Yet few predictive tools exist to manage this risk. Using a worldwide dataset of weed species resistant to multiple herbicide MoAs, hierarchical clustering was used to classify MoAs into similar groups in relation to the suite of resistant weed species they have in common. Network analyses then were used to explore the relative importance of species prevalence and similarity in cluster patterns.

RESULTS

Hierarchical clustering identified three similarly sized clusters of herbicide MoAs that were linked by the co-occurrence of resistant weeds: Herbicide Resistance Action Committee (HRAC) groups 2, 4, 5 and 9; HRAC groups 12, 14 and 15; and HRAC groups 1, 3 and 22. Cluster membership was consistent with similarities in the physiological or biochemical target of the herbicide MoAs. Network analyses revealed that the number of weed species resistant to two different MoAs was related to the number of weeds known to be resistant to each individual herbicide MoA.

CONCLUSIONS

Hierarchical cluster analysis provided new insights into the risk of weeds becoming resistant to more than one herbicide MoA. By clustering herbicide MoAs into three distinct groups, the potential exists for farmers to manage resistance by rotating herbicides between rather than within clusters, as far as crop, weed and environmental conditions allow.

Automatic Lung Segmentation and Quantification of Aeration in Computed Tomography of the Chest Using 3D Transfer Learning

BACKGROUND

Identification of lung parenchyma on computer tomographic (CT) scans in the research setting is done semi-automatically and requires cumbersome manual correction. This is especially true in pathological conditions, hindering the clinical application of aeration compartment (AC) analysis. Deep learning based algorithms have lately been shown to be reliable and time-efficient in segmenting pathologic lungs. In this contribution, we thus propose a novel 3D transfer learning based approach to quantify lung volumes, aeration compartments and lung recruitability.

METHODS

Two convolutional neural networks developed for biomedical image segmentation (uNet), with different resolutions and fields of view, were implemented using Matlab. Training and evaluation was done on 180 scans of 18 pigs in experimental ARDS (u2Net Pig ) and on a clinical data set of 150 scans from 58 ICU patients with lung conditions varying from healthy, to COPD, to ARDS and COVID-19 (u2Net Human ). One manual segmentations (MS) was available for each scan, being a consensus by two experts. Transfer learning was then applied to train u2Net Pig on the clinical data set generating u2Net Transfer . General segmentation quality was quantified using the Jaccard index (JI) and the Boundary Function score (BF). The slope between JI or BF and relative volume of non-aerated compartment (S JI and S BF , respectively) was calculated over data sets to assess robustness toward non-aerated lung regions. Additionally, the relative volume of ACs and lung volumes (LV) were compared between automatic and MS.

RESULTS

On the experimental data set, u2Net Pig resulted in JI = 0.892 [0.88 : 091] (median [inter-quartile range]), BF = 0.995 [0.98 : 1.0] and slopes S JI = -0.2 {95% conf. int. -0.23 : -0.16} and S BF = -0.1 {-0.5 : -0.06}. u2Net Human showed similar performance compared to u2Net Pig in JI, BF but with reduced robustness S JI = -0.29 {-0.36 : -0.22} and S BF = -0.43 {-0.54 : -0.31}. Transfer learning improved overall JI = 0.92 [0.88 : 0.94], P < 0.001, but reduced robustness S JI = -0.46 {-0.52 : -0.40}, and affected neither BF = 0.96 [0.91 : 0.98] nor S BF = -0.48 {-0.59 : -0.36}. u2Net Transfer improved JI compared to u2Net Human in segmenting healthy (P = 0.008), ARDS (P < 0.001) and COPD (P = 0.004) patients but not in COVID-19 patients (P = 0.298). ACs and LV determined using u2Net Transfer segmentations exhibited < 5% volume difference compared to MS.

CONCLUSION

Compared to manual segmentations, automatic uNet based 3D lung segmentation provides acceptable quality for both clinical and scientific purposes in the quantification of lung volumes, aeration compartments, and recruitability.

Exploring reported genes of microglia RNA-sequencing data: Uses and considerations

The advent of RNA‐sequencing techniques has made it possible to generate large, unbiased gene expression datasets of tissues and cell types. Several studies describing gene expression data of microglia from Alzheimer's disease or multiple sclerosis have been published, aiming to generate more insight into the role of microglia in these neurological diseases. Though the raw sequencing data are often deposited in open access databases, the most accessible source of data for scientists is what is reported in published manuscripts. We observed a relatively limited overlap in reported differentially expressed genes between various microglia RNA‐sequencing studies from multiple sclerosis or Alzheimer's diseases. It was clear that differences in experimental set up influenced the number of overlapping reported genes. However, even when the experimental set up was very similar, we observed that overlap in reported genes could be low. We identified that papers reporting large numbers of differentially expressed microglial genes generally showed higher overlap with other papers. In addition, though the pathology present within the tissue used for sequencing can greatly influence microglia gene expression, often the pathology present in samples used for sequencing was underreported, leaving it difficult to assess the data. Whereas reanalyzing every raw dataset could reduce the variation that contributes to the observed limited overlap in reported genes, this is not feasible for labs without (access to) bioinformatic expertise. In this study, we thus provide an overview of data present in manuscripts and their supplementary files and how these data can be interpreted.

Termite Assemblage and Damage on Tree Trunks in Fast-Growing Teak Plantations of Different Age: A Case Study in West Java, Indonesia

We conducted surveys of termite assemblages and tree trunks damaged by termites in teakwood (Tectona grandis L.f.) plantations. The surveys were conducted in five-, six-, and nine-year-old plantations. We used a standardized belt-transect to collect termites and build tree inventories. Data of collected termites at the genus and functional-group levels and termites' diversity between plantations were compared with their attack rate. The results showed that four genera of soil recycler termites belonging to groups IIf and III were present across the plantations. Distribution analysis suggested that termite communities might develop from a stochastic distribution to a nonrandom co-occurrence distribution over time. Diversity analysis showed an increased nestedness-resultant diversity contribution to the total dissimilarity over time. Observed attacks on tree trunks were superficial and limited to the outer bark, with group IIf as the main contributor. Furthermore, the level of damage done by termites to tree trunks was positively correlated with increases in the group IIf occupancy area and overgrown understory vegetation. Plantation management by maintaining an adequate understory might suppress termite attacks on fast-growing teakwood, although in the case of our study, termite attacks are inevitable when termites from group IIf were already present.

Large-scale Prediction of Drug-Protein Interactions Based on Network Information

BACKGROUND

The prediction of drug-protein interaction (DPI) plays an important role in drug discovery and re-positioning. Unfortunately, traditional experimental validation of DPIs is expensive and time-consuming. Therefore, it is necessary to develop in silico methods for the identification of potential DPIs.

METHOD

In this work, the identification of DPIs was performed by the generated recommendation of the unexplored interaction of the drug-protein bipartite graph. Three kinds of recommenders were proposed to predict the potential DPIs.

RESULTS

The simulation results showed that the proposed models obtained good performance in cross validation and independent test.

CONCLUSION

Our recommendation strategy based on collaborative filtering can effectively improve the DPI identification performance, especially for certain DPIs lacking chemical structure similarity or genomic sequence similarity.

Invertebrate turnover along gradients of anthropogenic salinisation in rivers of two German regions

Rising salinity in freshwater ecosystems can affect community composition. Previous studies mainly focused on changes in freshwater communities along gradients of absolute levels of electrical conductivity (EC). However, both geogenic and anthropogenic drivers contribute to the EC level and taxa may regionally be adapted to geogenic EC levels. Therefore, we examined the turnover in freshwater invertebrates along gradients of anthropogenic EC change in two regions of Germany. The anthropogenic change of EC was estimated as the difference between the measured EC and the modeled background EC driven by geochemical and climate variables. Turnover in freshwater invertebrates (β-diversity) was estimated using the Jaccard index (JI). We found that invertebrate turnover between EC gradient categories is generally greater than 47%, with a maximum of approximately 70% in sites with a more than 0.4 mS cm^-1 change compared to the baseline (i.e. no difference between predicted and measured EC). The invertebrates Amphinemura sp., Anomalopterygella chauviniana and Leuctra sp. were reliable indicators of low EC change, whereas Potamopyrgus antipodarum indicated sites with the highest EC change. Variability within categories of EC change was slightly lower than within categories of absolute EC. Elevated nutrient concentrations that are often linked to land use may have contributed to the observed change of the invertebrate richness and can exacerbate effects of EC on communities in water. Overall, our study suggests that the change in EC, quantified as the difference between measured EC and modeled background EC, can be used to examine the response of invertebrate communities to increasing anthropogenic salinity concentrations in rivers. However, due to the strong correlation between EC change and observed EC in our study regions, the response to these two variables was very similar. Further studies in areas where EC change and observed EC are less correlated are required. In addition, such studies should consider the change in specific ions.

Bioinformatics analysis of correlation between protein function and intrinsic disorder

The correlation of molecular function and protein intrinsic disorder is an important aspect of understanding the relationship between function, sequence and structure. This research was inspired by statistical correlation evaluation method described by Xie et al. (J Proteome Res 6 (2007) 1882-1898, reference study), where the authors analyzed the relationship between structure and function of proteins from Swiss-Prot database and where these functions were described with Swiss-Prot function keywords. In this research, we investigated whether the conclusions from the reference study stand for another dataset with richer functional annotation. We used CAFA3 challenge training dataset where the function was described with terms from Gene Ontology (GO terms). In order to compare the results with the previous work, we associated the GO terms with the corresponding Swiss-Prot function keywords. The results were compared with the reference study by first repeating the analysis with Swiss-Prot function keywords and then by GO terms. We used PONDR VSL2b disorder predictor to label over 66,000 CAFA3 proteins as putatively disordered or ordered. Out of 186 Swiss-Prot keywords (belonging to molecular function type) with more than 20 annotated proteins, we found 47 to be highly order related and 44 highly disorder related. Using the same dataset and annotation constraints, out of 1781 GO term (belonging to molecular function type), we found 746 to be highly order related and 564 highly disorder related. GO term results are presented as interactive graphs displaying complex hierarchical structure of Gene Ontology. Comparison of two functional annotations, GO and Swiss-Prot keywords, showed consistent results in cases when it was possible to map a Swiss-Prot keyword to a corresponding GO term. Because of the small number of such cases, we propose a new method for deriving the missing mappings between Swiss-Prot keywords and GO terms with the highest likelihood by measuring similarity (Jaccard index) between sets of protein annotated by different functions. Comparison with results from the reference study revealed prevalence of binding related functions (disorder related) in the current dataset even though the same functions were not present in previous results.

Triple Alignment: Congruency of Perceived Preschool Classroom Social Networks Among Teachers, Children, and Researchers

Classroom social networks are influential to young children's cognitive, social-emotional, and language development, but assessment and analyses of social networks are complex. Findings have been mixed regarding whether different informants (teachers, children, researchers) are congruent in perceiving classroom social networks. There is also a lack of discussion about the roles of network transformation (converting value networks into binary networks), a required data step for widely used statistical network analyses. This study addressed these issues based on network data of 16 preschool children containing 240 potential dyadic interactions collected from teacher ratings, child nominations, and researcher observations across 44 observation cycles over four school days. Results showed that the three informants were congruent in perceiving the classroom social network, whereas the level of congruency between the teacher-report and the researcher-report networks was the highest. Binary transformation of social networks tended to decrease the level of congruency across informants, although the level of congruency tended to be higher when more stringent binary transformation thresholds were selected.

Segmentation and Modelling of the Nuclear Envelope of HeLa Cells Imaged with Serial Block Face Scanning Electron Microscopy

This paper describes an unsupervised algorithm, which segments the nuclear envelope of HeLa cells imaged by Serial Block Face Scanning Electron Microscopy. The algorithm exploits the variations of pixel intensity in different cellular regions by calculating edges, which are then used to generate superpixels. The superpixels are morphologically processed and those that correspond to the nuclear region are selected through the analysis of size, position, and correspondence with regions detected in neighbouring slices. The nuclear envelope is segmented from the nuclear region. The three-dimensional segmented nuclear envelope is then modelled against a spheroid to create a two-dimensional (2D) surface. The 2D surface summarises the complex 3D shape of the nuclear envelope and allows the extraction of metrics that may be relevant to characterise the nature of cells. The algorithm was developed and validated on a single cell and tested in six separate cells, each with 300 slices of 2000 × 2000 pixels. Ground truth was available for two of these cells, i.e., 600 hand-segmented slices. The accuracy of the algorithm was evaluated with two similarity metrics: Jaccard Similarity Index and Mean Hausdorff distance. Jaccard values of the first/second segmentation were 93%/90% for the whole cell, and 98%/94% between slices 75 and 225, as the central slices of the nucleus are more regular than those on the extremes. Mean Hausdorff distances were 9/17 pixels for the whole cells and 4/13 pixels for central slices. One slice was processed in approximately 8 s and a whole cell in 40 min. The algorithm outperformed active contours in both accuracy and time.

Segmentation and Boundary Detection of Fetal Kidney Images in Second and Third Trimesters Using Kernel-Based Fuzzy Clustering

Organ segmentation is an important step in Ultrasound fetal images for early prediction of congenital abnormalities and to estimate delivery date. In many applications of 2D medical imaging, they face problems with speckle noise and object contours. Frequent scanning of fetal leads to clinical disturbances to the fetal growth and the quantitative interpretation of Ultrasonic images also a difficult task compared to other image modalities. In the present work a three-stage hybrid algorithm has been developed to segment the US fetal kidney images for the detection of shape and contour. At the first stage the hybrid Mean Median (Hybrid MM) filter is applied to reduce the speckle noise. Then a kernel based Fuzzy C - means clustering is used to detect the shape and contour. Finally, the texture features are obtained from the segmented images. Based on the obtained texture features, the abnormalities are detected. The Gaussian Radial basis function provides an accuracy of 80% at the second and third trimesters with weighted constant ranging from 4 to 8, compared to other global kernel functions. Similarly the proposed method has an accuracy of 86% with compared to other FCM techniques.

Implementation of a Pipeline Using Disease-Disease Associations for Computational Drug Repurposing

Drug repurposing is a powerful technique which has been recently employed in both industry and academia to discover and validate previously approved drugs for new indications. It provides the quickest possible transition from bench to bedside. In essence, computational strategies are appealing because they putatively nominate the most encouraging candidate for a given indication. A wide range of computational methods exist for repositioning. In this chapter we present the guidelines for performing integrated drug repurposing strategy by combining disease-disease association and molecular simulation analysis.

Ethnopharmacological studies of indigenous plants in Kel village, Neelum Valley, Azad Kashmir, Pakistan

BACKGROUND

This explorative study was undertaken for the first time in Kel village located in the Upper Neelum Valley, Azad Kashmir, Pakistan. The purpose was to document the indigenous knowledge of the native people used in the preparation of herbal medicines.

METHODS

To get the data on traditional uses of medicinal plants, 20 informants were interviewed. Quantitative ethnobotanical indices, i.e., use value (UV), relative frequencies of citation (RFC), informant consensus factor (Fic), fidelity level (FL), data matrix ranking (DMR), preference ranking (PR), and jaccard index (JI), were calculated for the recorded medicinal plants.

RESULTS

A total of 50 medicinal plants belonging to 33 families used in 13 disease categories were documented. Leaves were the frequently used plant parts, and decoction was the commonly used method for herbal medicine. Plants with high use value were Berberis lycium (2.05), Impatiens glandulifera (1.95), Artemisia scoparia (1.75), Ageratum conozoides (1.75), and Achillea millefolium (1.7). The highest RFC value was calculated for Berberis lycium (0.75), Cynoglossum lanceolatum (0.65), and Impatiens glandulifera and Achillea millefolium (0.60 each). The maximum informant consensus factor was for urinary system, cardiac diseases, baldness, and abortion and miscarriage (1.00). Berberis lyceum (95%) used in jaundice, hepatitis, typhoid, fever, and tuberculosis disorders. Plants with maximum fidelity level (FL) were Berberis lycium (95%) followed by Dioscorea bulbifera, Impatiens glandulifera, and Artemisia vulgaris (90%). Olea ferruginea was the most multipurpose plant and exports (21.2%) was the leading threat in the area. The pearson correlation coefficient (0.500) showed a positive correlation between the use value and relative frequency of citation.

CONCLUSION

The present study provides useful information about traditional uses of medicinal plants used by local communities in different ailments. The plants with the highest use values could be employed in pharmacological research and biotechnological approaches in order to achieve adequate revenue. Some of the plants in the study area are facing high threats of becoming rare, and conservation initiatives are needed to conserve them for sustainable management in the region.

Comparing the natural variation of oribatid mite communities with their changes associated with anthropogenic disturbance

Several organism communities serve as ecological and environmental indicators to detect changes in human-impacted habitats. However, the composition of indicator communities may vary because of natural variation in addition to the changes associated with human disturbances. This meta-analysis compared the natural variation of oribatid mite assemblages, a good indicator model group in soil ecosystems, with their deviations associated with disturbance using diversity and dissimilarity indices and three human disturbance types. Literature data were collected about oribatid mite assemblages from natural and disturbed habitats. Human disturbances consisted of agriculture, heavy metal pollution and forest management. Biodiversity indices (Shannon and Berger-Parker) and dissimilarity indices (Jaccard and Bray-Curtis) were calculated among natural habitats and between disturbed and control habitats at the species and genus level. We considered oribatid mite assemblages as effective community-level indicators when the methods separated the differences of assemblages between disturbed and control habitats from their varieties among natural habitats. In addition, the study analysed the correlation between these indices and environmental variables of the study sites. Oribatid mite assemblages performed high indication strength with Bray-Curtis index for agricultural disturbances since dissimilarity values between disturbed and control habitats were as high as between different natural habitats and higher than among the same types of natural habitats. Genus-level values showed similar results to the species level. This approach may be useful to test the effectiveness of other indicator groups and methods.

A Segmentation Framework of Pulmonary Nodules in Lung CT Images

Accurate segmentation of pulmonary nodules is a prerequisite for acceptable performance of computer-aided detection (CAD) system designed for diagnosis of lung cancer from lung CT images. Accurate segmentation helps to improve the quality of machine level features which could improve the performance of the CAD system. The well-circumscribed solid nodules can be segmented using thresholding, but segmentation becomes difficult for part-solid, non-solid, and solid nodules attached with pleura or vessels. We proposed a segmentation framework for all types of pulmonary nodules based on internal texture (solid/part-solid and non-solid) and external attachment (juxta-pleural and juxta-vascular). In the proposed framework, first pulmonary nodules are categorized into solid/part-solid and non-solid category by analyzing intensity distribution in the core of the nodule. Two separate segmentation methods are developed for solid/part-solid and non-solid nodules, respectively. After determining the category of nodule, the particular algorithm is set to remove attached pleural surface and vessels from the nodule body. The result of segmentation is evaluated in terms of four contour-based metrics and six region-based metrics for 891 pulmonary nodules from Lung Image Database Consortium and Image Database Resource Initiative (LIDC/IDRI) public database. The experimental result shows that the proposed segmentation framework is reliable for segmentation of various types of pulmonary nodules with improved accuracy compared to existing segmentation methods.

Investigation of traditional medicinal floral knowledge of Sarban Hills, Abbottabad, KP, Pakistan

ETHNO PHARMACOLOGICAL RELEVANCE

Ethno medicinal traditional knowledge regarding the uses of indigenous medicinal plants for treating various human infectious diseases is totally in hold of the elder community members. The young generation is not much aware about such vital traditional medicinal practices.

AIM OF STUDY

To document, accumulate and widely disseminate the massive indigenous knowledge of century's practiced therapeutic uses of medicinal plants by the local people living in this area.

MATERIALS AND METHODS

A total of 134 local inhabitants (78 male and 56 female) were interviewed through questionnaire method. The data obtained were quantitatively analyzed through the use value, fidelity level index and relative frequency citation. Plants specimen were preserved and mounted on herbarium sheets and labeled, cataloged and deposited with voucher numbers in Hazara University Herbarium, Mansehra, Pakistan (HUP).

RESULTS

74 plant species belonging to 70 genera and 42 families were documented in the current study. These medicinal plant species are used commonly as an ethno medicine against 56 various diseases such as digestive disorder, cough, pain and skin diseases etc. Herbaceous plant species were the dominant among plants studied which were 57% of the total plants, followed by shrubs (23%) and trees (20%). Asteraceae was the leading family among collected medicinal plant species (10.81%). Maximum medicinal plant species were used for treatment of digestive disorders (9.09%) and cough (7.44%). Most widely part used is leaf (27.9%), followed by fruit (13.5%) and seed (13.5%) for the treatment of different ailments by the traditional healers. The medicinal plant species with greater use values were Berberis lycium (0.91) and Cannabis sativa (0.81). The medicinal plant species with maximum fidelity level were Ziziphus jujuba (100%) and Lonicera caprifolium (92.31%) whereas the medicinal with most relative frequency citation were B. lycium (0.313), Ziziphus nummularia (0.276). The comparative result reveals that 36% of medicinal plant species were reported for the first time from Abbottabad regarding their uses, whereas 26% of plant species were reported with different medicinal uses. Brugmansia suaveolens and Allium griffithianum were recorded for the first time from Pakistan as well as from other countries across the globe for currently reported medicinal uses.

CONCLUSION

The current study revealed the importance to document and launch list of all possible plants that are used in ethno medicinal practices in the study area. Future antimicrobial, antivirals, and pharmacological studies are required to ratify the efficacy and safety of the medicinal plants species.

Host range and community structure of avian nest parasites in the genus Philornis (Diptera: Muscidae) on the island of Trinidad

Parasite host range can be influenced by physiological, behavioral, and ecological factors. Combining data sets on host-parasite associations with phylogenetic information of the hosts and the parasites involved can generate evolutionary hypotheses about the selective forces shaping host range. Here, we analyzed associations between the nest-parasitic flies in the genus Philornis and their host birds on Trinidad. Four of ten Philornis species were only reared from one species of bird. Of the parasite species with more than one host bird species, P. falsificus was the least specific and P. deceptivus the most specific attacking only Passeriformes. Philornis flies in Trinidad thus include both specialists and generalists, with varying degrees of specificity within the generalists. We used three quantities to more formally compare the host range of Philornis flies: the number of bird species attacked by each species of Philornis, a phylogenetically informed host specificity index (Poulin and Mouillot's S TD), and a branch length-based S TD. We then assessed the phylogenetic signal of these measures of host range for 29 bird species. None of these measures showed significant phylogenetic signal, suggesting that clades of Philornis did not differ significantly in their ability to exploit hosts. We also calculated two quantities of parasite species load for the birds - the parasite species richness, and a variant of the S TD index based on nodes rather than on taxonomic levels - and assessed the signal of these measures on the bird phylogeny. We did not find significant phylogenetic signal for the parasite species load or the node-based S TD index. Finally, we calculated the parasite associations for all bird pairs using the Jaccard index and regressed these similarity values against the number of nodes in the phylogeny separating bird pairs. This analysis showed that Philornis on Trinidad tend to feed on closely related bird species more often than expected by chance.

Community ecology of the metazoan parasites of freshwater fishes of Kerala

The prevalence and mean intensity of metazoan parasite infection, the community characteristics (richness index, dominance index, evenness index and Shannon index of diversity) and the qualitative similarity of the metazoan parasite fauna among the species and families of the fishes were determined of 13 fish species of freshwater fishes of Kerala belonging to seven families. The metazoan parasite fauna of this geographical area is very diverse; it consisted of 33 species of parasites belonging to seven major taxa: ten species of Monogenea, nine Digenea, two Cestoda, six Nematoda, three Acanthocephala, two Copepoda and one Isopoda. Prevalence of infection ranged from 32.9% (Puntius vittatus) to 87.1% (Mystus oculatus) and mean intensity from 3.8 (Puntius vittatus) to 27.6 (Aplocheilus lineatus). The infra- and component communities of parasites were somewhat characteristic. The dominance pattern of the major taxa was in the order Digenea > Nematoda > Monogenea = Acanthocephala > Cestoda = Copepoda > Isopoda. Macropodus cupanus harboured the richest fauna and Puntius vittatus had the least rich fauna. The parasite fauna of A. lineatus was the most heterogeneous and that of M. cavasius, the most homogeneous. The diversity of the parasite fauna was the greatest in M. cavasius and the least in A. lineatus. The parasite faunas of A. lineatus and M. cupanus and of M. cavasius and M. oculatus were similar. However, in spite of the taxonomic nearness and the similarity of the habits and habitats of the four species of cyprinids (P. amphibius, P. filamentosus, P. sarana and P. vittatus), their parasite fauna were qualitatively very dissimilar-of the seven species of parasites encountered in them only one was shared by the four host species. The cyprinid, Rasbora daniconius, had its own characteristic component community of parasites consisting of six species none of which was shared by the other four cyprinids. The richest parasite fauna was that of the family Cyprinidae followed by that of Channidae and the poorest of Belonidae. The most homogeneous parasite fauna was that of Bagridae and the most heterogeneous that of Cyprinodontidae. The parasite fauna of Cyprinodontidae and Belontidae were qualitatively very similar. The results indicate that the freshwater fishes of the southwest cost of India harbour a rich and diverse metazoan parasite fauna, which is as rich and diverse as that of the marine fishes of this area. The results also suggest that carnivorous/omnivorous fish species harbour richer and more heterogeneous component communities of parasites than herbivorous species implying that the feeding habits of fishes is a major factor deciding their parasite faunas.

A topological similarity measure for proteins

We introduce a new measure for assessing similarity among chemical structures, based on well-established computational-topology algorithms. We argue that although the method considers geometry, it is more than a mere geometric similarity measure, as it takes into account, on different geometric scales, the important topological features of the compared structures. We prove that our measure is rigorous and complies with the proper mathematical requirements. We validate the method through comparing different configurations of simple zinc finger proteins and present an application on ligands binding to membrane-proteINS extracted from the Directory of Useful Decoys: Enhanced database and corresponding decoys. This article is part of a Special Issue entitled: Viral membrane proteins - Channels for cellular networking.

Two-Dimensional Tomography from Noisy Projections Taken at Unknown Random Directions

Computerized tomography is a standard method for obtaining internal structure of objects from their projection images. While CT reconstruction requires the knowledge of the imaging directions, there are some situations in which the imaging directions are unknown, for example, when imaging a moving object. It is therefore desirable to design a reconstruction method from projection images taken at unknown directions. Another difficulty arises from the fact that the projections are often contaminated by noise, practically limiting all current methods, including the recently proposed diffusion map approach. In this paper, we introduce two denoising steps that allow reconstructions at much lower signal-to-noise ratios (SNRs) when combined with the diffusion map framework. In the first denoising step we use principal component analysis (PCA) together with classical Wiener filtering to derive an asymptotically optimal linear filter. In the second step, we denoise the graph of similarities between the filtered projections using a network analysis measure such as the Jaccard index. Using this combination of PCA, Wiener filtering, graph denoising, and diffusion maps, we are able to reconstruct the two-dimensional (2-D) Shepp-Logan phantom from simulative noisy projections at SNRs well below their currently reported threshold values. We also report the results of a numerical experiment corresponding to an abdominal CT. Although the focus of this paper is the 2-D CT reconstruction problem, we believe that the combination of PCA, Wiener filtering, graph denoising, and diffusion maps is potentially useful in other signal processing and image analysis applications.