In vivo evaluation & safety profile evaluation of Arctostaphylos uva-ursi (L.) Spreng. extract in rabbits.

The aim of our research work was to investigate the effects of low dose of Arctostaphylos uva-ursi (L.) Spreng. on rabbits. Crude extract was administered for 90 days in rabbits and hematology, biochemistry parameters and histopathology changes were analyzed. In result of it gender-based variations were observed in hematological, kidney function, liver function, cardiac enzymes and lipid profile. Urine analysis revealed same results as that of standard and control drug. No significant pathology was observed in heart, stomach, liver and kidney tissues of rabbits, treated with A.uva-ursi in a dose of 25 mg/kg/day. Our results justify the use of A. uva-ursi in medicine for treatment of variable pathologies.

Analgesic, Anti-inflammatory and neuropharmacological effects of Atropa belladonna.

The present study was carried out to investigate, in vivo, analgesic, anti-inflammatory and neuro-pharmacological activities of the methanolic extract of Atropa belladonna. The analgesic activity was measured by acetic acid induced writhing inhibition test. The neuro-pharmacological activities were evaluated by open field, rearing test, cage cross, swim test, head dip and traction tests. The anti-inflammatory activity was assessed by formalin induce inflammation on hind paw. The extract showed highly significant (p<0.001) analgesic activity with % inhibitions of writhing response at doses 100 and 300mg/kg body weight were 28.5% and 57.1%, respectively. The extract at both doses showed significant (p<0.05) sedative effect in-cage cross test and highly significance value (p<0.001) in high dose. In-open field test, the extract showed significant (P<0.05) anxiolytic activity at higher dose whereas in rearing test activity shows significant p-value at both doses. The extract also showed significant value for anti-inflammatory activity. The findings of the study clearly indicated the presence of significant analgesic, neuro-pharmacological and anti-inflammatory properties of the plant, which demands further investigation including, compounds isolation.

Anti-nociceptive activity of seed extract of Vernonia anthelmintica willd.

Vernonia anthelmintica is commonly known as kali ziri. Its seeds are used for several therapeutical purposes. Its seeds contain many constituents of medicinal importance as vernodlin, vernodalol, and vernolic acid. It is commonly used psoriasis and leucoderma or white leprosy. It is potent wormicidal agent. The present study was conducted on seed's extract of V. anthelmintica to determine its analgesic potency. The activity was conducted on mice by using acetic acid induced writhes,hot plate method and by tail flick method using water bath. The results of the writhing test were highly significant and comparable with Aspirin, which produced 26 and 20 writhes. The percentage of inhibition of writhes with the two doses of crude extract was 65.45% and 64.28% at 300mg/kg, while 83.63% and 71.42% at 500mg/kg, where as with Aspirin it was 52.72% and 28.57% in first and second phase respectively. Hot plate and tail flick method also indicated that vernonia has potent analgesic activity. The drug can be utilized as anti-nociceptive agent.

Effects of pulsed Nd:YAG laser kernel irradiation on maize (Zea mays L.): Insights into germination, gas exchange, photosynthetic pigments, and morphological modifications.

Energy has always been the most concerned topic worldwide due to its large consumption. Among various types of energies, light has amazing characteristics and have interesting effects on living organisms. Interest is increasing in the use of laser kernel treatment as an environment friendly physical technique for better results in agronomic crops, but the work is still in progress. The present study was conducted with the aim to examine the application of range of Neodymium-doped Yttrium Aluminum Garnet (Nd:YAG) pulsed laser exposures (200, 400, 600, 800, 1000, 1200, 1400 J/cm2) as pre-sowing kernel treatment on seedling survival rate, leaf photosynthetic activity in relation with photosynthetic pigments and visual morphological effects at seedling to maturity stage. Results showed that the low laser exposure (200, 400 and 600 J/cm2) improved the photosynthetic activity in parallel with improvement in chlorophyll a, chlorophyll b, total chlorophyll, carotenoids as well as morphological traits. Kernel treatments with higher laser fluences (800, 1000, 1200 and 1400 J/cm2) showed irregular responses in studied attributes examined at the individual plant level. At 800 and 1000 J/cm2 improvements were found in some plants but at higher doses clear negative impacts were recorded on studied attributes. In conclusion, the lower doses of Nd:YAG pulsed laser fluences are found beneficial for induction of improvement in maize plants for better growth but higher doses were found toxic ones. In future further studies are needed to check the impacts of low laser doses on yield related attributes under field conditions and the high doses might also be used to create variants with beneficial characteristics if possible.

Cotton plant part 3D segmentation and architectural trait extraction using point voxel convolutional neural networks.

BACKGROUND: Plant architecture can influence crop yield and quality. Manual extraction of architectural traits is, however, time-consuming, tedious, and error prone. The trait estimation from 3D data addresses occlusion issues with the availability of depth information while deep learning approaches enable learning features without manual design. The goal of this study was to develop a data processing workflow by leveraging 3D deep learning models and a novel 3D data annotation tool to segment cotton plant parts and derive important architectural traits. RESULTS: The Point Voxel Convolutional Neural Network (PVCNN) combining both point- and voxel-based representations of 3D data shows less time consumption and better segmentation performance than point-based networks. Results indicate that the best mIoU (89.12%) and accuracy (96.19%) with average inference time of 0.88 s were achieved through PVCNN, compared to Pointnet and Pointnet++. On the seven derived architectural traits from segmented parts, an R2 value of more than 0.8 and mean absolute percentage error of less than 10% were attained. CONCLUSION: This plant part segmentation method based on 3D deep learning enables effective and efficient architectural trait measurement from point clouds, which could be useful to advance plant breeding programs and characterization of in-season developmental traits. The plant part segmentation code is available at https://github.com/UGA-BSAIL/plant_3d_deep_learning .

Birth weight estimation--a sonographic model for Pakistani population.

OBJECTIVE: To develop a sonographic birth weight estimation model for Pakistani population and to validate the published models in the same population. METHODS: Data was collected for pregnant women who presented to Radiology Department of Aga Khan University Hospital Karachi from January 2007 to July 2008 and had undergone ultrasound estimation of foetal weight within 4 days prior to a term delivery (37-42 weeks gestation). The neonate's actual birth weight was used to validate the published foetal weight estimation models and modified sonographic birth weight estimation model was derived for our population by using linear regression. RESULTS: Modified sonographic birth weight estimation model for our population was derived by using foetal parameters. No significant difference (p-value > 0.05) of actual and predicted birth weight derived from Our regression model, Campbell and Woo models was noted, however least difference (p = 0.7) was identified between our predicted model (Mean difference 14 +/- 37.7 g). CONCLUSION: Our sonographic modified regression model of foetal weight estimation gave the least difference with actual neonatal birth weight and can be reliably used in our population. Hadlock1, Hadlock2 and Woo2 models are not appropriate in our setting or should be used carefully while predicting foetal weight in our population.

Infectivity of okra enation leaf curl virus and the role of its V2 protein in pathogenicity.

Cotton crop has been severely affected by multiple begomoviruses in Pakistan and India. In our previous study, we found okra enation leaf curl virus (OELCuV), cotton leaf curl Multan betasatellite (CLCuMuB) and cotton leaf curl Multan alphasatellite (CLCuMuA) infecting cotton in Pakistan. The current study was designed to investigate the infectivity of OELCuV and its ability to trans-replicate non-cognate CLCuMuB. Agro-infectious clones containing the partial tandem repeats of OELCuV and CLCuMuB were constructed and the infectivity assays were carried out through Agrobacterium mediated transformation in the model host species Nicotiana benthamiana under controlled conditions. The results showed that in the inoculated plants OELCuV alone can cause downward curling and yellowing of leaves with thickened veins. However, when co-inoculated with the non-cognate CLCuMuB it could functionally trans-replicate CLCuMuB resulting in a more severe phenotype. The expression of Pre-coat/V2 protein in the N. benthamiana plants through the potato virus X (PVX) system caused localized cell death after severe leaf curling in the infiltrated leaves. The tissue tropism of the virus was associated with the systemic development of a hypersensitive response (HR), which ultimately lead to the plant death. The results indicated the involvement of V2 protein in the pathogenicity of OELCuV and its ability to trigger the host defense machinery. This study also demonstrated the ability of OELCuV to trans-replicate CLCuMuB resulting in typical leaf curl disease symptoms in N. benthamiana.