Improving diagnosis and prognosis of lung cancer using vision transformers: a scoping review.

BACKGROUND: Vision transformer-based methods are advancing the field of medical artificial intelligence and cancer imaging, including lung cancer applications. Recently, many researchers have developed vision transformer-based AI methods for lung cancer diagnosis and prognosis. OBJECTIVE: This scoping review aims to identify the recent developments on vision transformer-based AI methods for lung cancer imaging applications. It provides key insights into how vision transformers complemented the performance of AI and deep learning methods for lung cancer. Furthermore, the review also identifies the datasets that contributed to advancing the field. METHODS: In this review, we searched Pubmed, Scopus, IEEEXplore, and Google Scholar online databases. The search terms included intervention terms (vision transformers) and the task (i.e., lung cancer, adenocarcinoma, etc.). Two reviewers independently screened the title and abstract to select relevant studies and performed the data extraction. A third reviewer was consulted to validate the inclusion and exclusion. Finally, the narrative approach was used to synthesize the data. RESULTS: Of the 314 retrieved studies, this review included 34 studies published from 2020 to 2022. The most commonly addressed task in these studies was the classification of lung cancer types, such as lung squamous cell carcinoma versus lung adenocarcinoma, and identifying benign versus malignant pulmonary nodules. Other applications included survival prediction of lung cancer patients and segmentation of lungs. The studies lacked clear strategies for clinical transformation. SWIN transformer was a popular choice of the researchers; however, many other architectures were also reported where vision transformer was combined with convolutional neural networks or UNet model. Researchers have used the publicly available lung cancer datasets of the lung imaging database consortium and the cancer genome atlas. One study used a cluster of 48 GPUs, while other studies used one, two, or four GPUs. CONCLUSION: It can be concluded that vision transformer-based models are increasingly in popularity for developing AI methods for lung cancer applications. However, their computational complexity and clinical relevance are important factors to be considered for future research work. This review provides valuable insights for researchers in the field of AI and healthcare to advance the state-of-the-art in lung cancer diagnosis and prognosis. We provide an interactive dashboard on lung-cancer.onrender.com/ .

Shaped Microwave Field in a Three-Level Closed Loop Dense Atomic System.

In this work, we investigate the atomic properties of a three-level system under the effect of a shaped microwave field. The system is simultaneously driven by a powerful laser pulse and a weak constant probe that drives the ground state to an upper level. Meanwhile, an external microwave field drives the upper state to the middle transition with shaped waveforms. Hence, two situations are considered: one in which the atomic system is controlled by a strong laser pump and a classical constant microwave field, and another in which both the microwave and pump laser fields are shaped. Finally, for sake of comparison, we investigate the tanh-hyperbolic, the Gaussian and the power of the exponential microwave form in the system. Our results reveal that shaping the external microwave field has a significant impact on the absorption and dispersion coefficient dynamics. In comparison with the classical scenario, where usually the strong pump laser is considered to have a major role in controlling the absorption spectrum, we show that shaping the microwave field leads to distinct results.

Modelling intra-muscular contraction dynamics using in silico to in vivo domain translation.

BACKGROUND: Advances in sports medicine, rehabilitation applications and diagnostics of neuromuscular disorders are based on the analysis of skeletal muscle contractions. Recently, medical imaging techniques have transformed the study of muscle contractions, by allowing identification of individual motor units' activity, within the whole studied muscle. However, appropriate image-based simulation models, which would assist the continued development of these new imaging methods are missing. This is mainly due to a lack of models that describe the complex interaction between tissues within a muscle and its surroundings, e.g., muscle fibres, fascia, vasculature, bone, skin, and subcutaneous fat. Herein, we propose a new approach to overcome this limitation. METHODS: In this work, we propose to use deep learning to model the authentic intra-muscular skeletal muscle contraction pattern using domain-to-domain translation between in silico (simulated) and in vivo (experimental) image sequences of skeletal muscle contraction dynamics. For this purpose, the 3D cycle generative adversarial network (cycleGAN) models were evaluated on several hyperparameter settings and modifications. The results show that there were large differences between the spatial features of in silico and in vivo data, and that a model could be trained to generate authentic spatio-temporal features similar to those obtained from in vivo experimental data. In addition, we used difference maps between input and output of the trained model generator to study the translated characteristics of in vivo data. RESULTS: This work provides a model to generate authentic intra-muscular skeletal muscle contraction dynamics that could be used to gain further and much needed physiological and pathological insights and assess and overcome limitations within the newly developed research field of neuromuscular imaging.

A Deep Sequence Learning Framework for Action Recognition in Small-Scale Depth Video Dataset.

Depth video sequence-based deep models for recognizing human actions are scarce compared to RGB and skeleton video sequences-based models. This scarcity limits the research advancements based on depth data, as training deep models with small-scale data is challenging. In this work, we propose a sequence classification deep model using depth video data for scenarios when the video data are limited. Unlike summarizing the frame contents of each frame into a single class, our method can directly classify a depth video, i.e., a sequence of depth frames. Firstly, the proposed system transforms an input depth video into three sequences of multi-view temporal motion frames. Together with the three temporal motion sequences, the input depth frame sequence offers a four-stream representation of the input depth action video. Next, the DenseNet121 architecture is employed along with ImageNet pre-trained weights to extract the discriminating frame-level action features of depth and temporal motion frames. The extracted four sets of feature vectors about frames of four streams are fed into four bi-directional (BLSTM) networks. The temporal features are further analyzed through multi-head self-attention (MHSA) to capture multi-view sequence correlations. Finally, the concatenated genre of their outputs is processed through dense layers to classify the input depth video. The experimental results on two small-scale benchmark depth datasets, MSRAction3D and DHA, demonstrate that the proposed framework is efficacious even for insufficient training samples and superior to the existing depth data-based action recognition methods.

The Antibacterial and Larvicidal Potential of Bis-(2-Ethylhexyl) Phthalate from Lactiplantibacillus plantarum.

Lactic acid bacteria produce a variety of antibacterial and larvicidal metabolites, which could be used to cure diseases caused by pathogenic bacteria and to efficiently overcome issues regarding insecticide resistance. In the current study, the antibacterial and larvicidal potential of Bis-(2-ethylhexyl) phthalate isolated from Lactiplantibacillus plantarum BCH-1 has been evaluated. Bioactive compounds were extracted by ethyl acetate and were fractionated by gradient column chromatography from crude extract. Based on FT-IR analysis followed by GC-MS and ESI-MS/MS, the active compound was identified to be Bis-(2-ethylhexyl) phthalate. Antibacterial potential was evaluated by disk diffusion against E. coli (12.33 ± 0.56 mm inhibition zone) and S. aureus (5.66 ± 1.00 mm inhibition zone). Larvicidal potency was performed against Culex quinquefasciatus Say larvae, where Bis-(2-ethylhexyl) phthalate showed 100% mortality at 250 ppm after 72 h with LC50 of 67.03 ppm. Furthermore, after 72 h the acetylcholinesterase inhibition was observed as 29.00, 40.33, 53.00, 64.00, and 75.33 (%) at 50, 100, 150, 200, and 250 ppm, respectively. In comet assay, mean comet tail length (14.18 ± 0.28 µm), tail DNA percent damage (18.23 ± 0.06%), tail movement (14.68 ± 0.56 µm), comet length (20.62 ± 0.64 µm), head length (23.75 ± 0.27 µm), and head DNA percentage (39.19 ± 0.92%) were observed at 250 ppm as compared to the control. The current study for the first time describes the promising antibacterial and larvicidal potential of Bis-(2-ethylhexyl) phthalate from Lactiplantibacillus plantarum that would have potential pharmaceutical applications.

Exploring 3D Human Action Recognition Using STACOG on Multi-View Depth Motion Maps Sequences.

This paper proposes an action recognition framework for depth map sequences using the 3D Space-Time Auto-Correlation of Gradients (STACOG) algorithm. First, each depth map sequence is split into two sets of sub-sequences of two different frame lengths individually. Second, a number of Depth Motion Maps (DMMs) sequences from every set are generated and are fed into STACOG to find an auto-correlation feature vector. For two distinct sets of sub-sequences, two auto-correlation feature vectors are obtained and applied gradually to L2-regularized Collaborative Representation Classifier (L2-CRC) for computing a pair of sets of residual values. Next, the Logarithmic Opinion Pool (LOGP) rule is used to combine the two different outcomes of L2-CRC and to allocate an action label of the depth map sequence. Finally, our proposed framework is evaluated on three benchmark datasets named MSR-action 3D dataset, DHA dataset, and UTD-MHAD dataset. We compare the experimental results of our proposed framework with state-of-the-art approaches to prove the effectiveness of the proposed framework. The computational efficiency of the framework is also analyzed for all the datasets to check whether it is suitable for real-time operation or not.

A Deep Learning Based Approach for Localization and Recognition of Pakistani Vehicle License Plates.

License plate localization is the process of finding the license plate area and drawing a bounding box around it, while recognition is the process of identifying the text within the bounding box. The current state-of-the-art license plate localization and recognition approaches require license plates of standard size, style, fonts, and colors. Unfortunately, in Pakistan, license plates are non-standard and vary in terms of the characteristics mentioned above. This paper presents a deep-learning-based approach to localize and recognize Pakistani license plates with non-uniform and non-standardized sizes, fonts, and styles. We developed a new Pakistani license plate dataset (PLPD) to train and evaluate the proposed model. We conducted extensive experiments to compare the accuracy of the proposed approach with existing techniques. The results show that the proposed method outperformed the other methods to localize and recognize non-standard license plates.

Coherent Surface Plasmon Hole Burning via Spontaneously Generated Coherence.

Surface plasmon (SP)-induced spectral hole burning (SHB) at the silver-dielectric interface is investigated theoretically. We notice a typical lamb dip at a selective frequency, which abruptly reduces the absorption spectrum of the surface plasmons polaritons (SPP). Introducing the spontaneous generated coherence (SGC) in the atomic medium, the slope of dispersion becomes normal. Additionally, slow SPP propagation is also noticed at the interface. The spectral hole burning dip is enhanced with the SGC effect and can be modified and controlled with the frequency and intensity of the driving fields. The SPP propagation length at the hole-burning region is greatly enhanced under the effect of SGC. A propagation length of the order of 600 µm is achieved for the modes, which is a remarkable result. The enhancement of plasmon hole burning under SGC will find significant applications in sensing technology, optical communication, optical tweezers and nano-photonics.

Growth Inhibition of Common Enteric Pathogens in the Intestine of Broilers by Microbially Produced Dextran and Levan Exopolysaccharides.

Antibiotics are generally applied for treatment or as subtherapeutic agents to overcome diseases caused by pathogenic bacteria including Escherichia coli, Salmonella and Enterococcus species in poultry. However, due to their possible adverse effects on animal health and to maintain food safety, probiotics, prebiotics, and synbiotics have been proposed as alternatives to antibiotic growth promoters (AGPs) in poultry production. In this study, the effects of prebiotics on the augmentation of broiler's indigenous gut microbiology were studied. Day old 180 broilers chicks were divided into four treatment groups: G, L, C1, and C2. The groups G and L were fed with basal diet containing 3% dextran and 3% levan, respectively. Control groups were fed with basal diets without antibiotic (C1) and with antibiotics (C2). The experimental groups showed decreased mortality as compared to control groups. After 35 days, the chickens were euthanized and intestinal fluid was analyzed for enteric pathogens on chromogenic agar plates and by 16S rRNA gene sequencing. Inhibition of the growth of E. coli and Enterococcus was observed in groups G and L, respectively, whereas Salmonella was only present in group C1. Also, high populations of lactic acid bacteria were detected in the intestine of prebiotic fed birds as compared to controls. These results depict that dextran and levan have the potential to replace the use of antibiotics in poultry feed for inhibiting the growth of common enteric pathogens. To the best of our knowledge, this is the first study where effects of dextran and levan on intestinal microbiota of broilers have been reported.

Barriers in access to healthcare services for individuals with disorders of sex differentiation in Bangladesh: an analysis of regional representative cross-sectional data.

BACKGROUND: Worldwide people in disorder of sex development (DSD) faces multiple barriers while seeking their social rights, particularly healthcare services. We aimed to explore the healthcare opportunities available to them, using patterns of healthcare utilization and difficulties faced by DSD population in accessing healthcare services in Bangladesh. METHODS: Data from a total of 945 DSD population and 71 medical staff were analyzed, collected from three major divisions (Dhaka, Chittagong, and Rajshahi) in Bangladesh during the period of January to December of 2017. A structured questionnaire was used to collect data via face-to-face interviews. Descriptive statistic was used to determine the frequencies of the visit by the DSD population in healthcare facilities as well as to analyze difficulties experienced by the DSD population in getting healthcare services. Multivariate regression analysis was used to explore the association between perceived barriers in getting healthcare services and failures of the DSD population to receive the healthcare services. RESULTS: Present data revealed that around 80% of DSD population sought healthcare services from government healthcare facilities, where the overall success rate in getting healthcare services was less than 50%. The DSD population reported a number of reasons for failures in getting healthcare services, including non-friendly interaction by non-clinical hospital's staff, non-friendly interaction by physicians, public fright as general people do not want to mingle with a DSD person, undesirable excess public interest in DSD individuals, and limitation of the treatment opportunities of hospitals to merely male or female patients. Among the stated reasons, the most frequently reported reason was non-friendly interaction by physicians (50.27%), followed by undesirable excess public interest in DSD individuals (50.16%). CONCLUSION: DSD population in Bangladesh have limited access to healthcare facilities and facing multiple barriers to get healthcare services. Initiatives from the government and social organizations are important to ensure their access to healthcare services.

Plant growth promotion and enhanced uptake of Cd by combinatorial application of Bacillus pumilus and EDTA on Zea mays L.

In developing countries, Cd contamination is ubiquitous which limits agriculture productivity. The current study was designed to investigate the efficacy of plant-Bacillus pumilus-ethylene diamine tetraacetic acid (EDTA) and plant-microbe-chelator (PMC) synergy for enhanced plant growth and Cd-uptake potential of Zea mays in industrially contaminated and cadmium (Cd) spiked soil. A pot experiment was conducted by growing Z. mays seedlings either inoculated with B. pumilus or un-inoculated along with the application of 5 mM EDTA. Plants were exposed to two levels of Cd contamination for 45 days. An increase in Cd uptake was observed in Z. mays inoculated with B. pumilus followed by EDTA treatment as compared to non-inoculated and un-treated ones. Zea mays showed improved values with PMC approach for different growth parameters including root length (41%), shoot length (40%), fresh weight (59%), dry weight (49%), chlorophyll contents (49%), and relative water contents (30%). Higher tolerance index (117%) was observed for plants grown in soil spiked with 300 mg kg-1 Cd (S2). PMC application markedly enhanced Cd uptake potential of Z. mays up to 12% and 68.8%, respectively, in S1 and S2 soil. While the PMC application increased Cd accumulation capacity of Z. mays by 71.2% and 52.5% in S1 and S2 soil. The calculated bioaccumulation and translocation factor revealed that Z. mays possess Cd uptake potential, and this ability can be significantly enhanced with PMC application.

Drought tolerance improvement in plants: an endophytic bacterial approach.

Climate change is a crucial issue among the serious emerging problems which got a global attention in the last few decades. With the climate change, worldwide crop production has been seriously affected by drought stress. In this regard, various technologies including traditional breeding and genetic engineering are used to cope with drought stress. However, the interactions between plants and endophytic bacteria emerged as an interesting era of knowledge that can be used for novel agriculture practices. Endophytic bacteria which survive within plant tissues are among the most appropriate technologies improving plant growth and yield under drought conditions. These endophytic bacteria live within plant tissues and release various phytochemicals that assist plant to withstand in harsh environmental conditions, i.e., drought stress. Their plant growth-promoting characteristics include nitrogen fixation, phosphate solubilization, mineral uptake, and the production of siderophore, 1-aminocyclopropane-1-carboxylate (ACC) deaminase, and various phytohormones. These plant growth promoting characteristics of endophytic bacteria improve root length and density, which lead to the enhance drought tolerance. In addition, plant-endophytic bacteria assist plant to withstand against drought stress by producing drought-tolerant substances, for instance, abscisic acid, indole-3-acetic acid, ACC deaminase, and various volatile compounds. Indirectly, endophytic bacteria also improve osmotic adjustment, relative water content, and antioxidant activity of inoculated plants. Altogether, these bacterial-mediated drought tolerance and plant growth-promoting processes continue even under severe drought conditions which lead to enhanced plant growth promotion and yield. The present review highlights a natural and environment-friendly strategy in the form of drought-tolerant and plant growth-promoting endophytic bacteria to improve drought tolerance in plants.

Integrating fuzzy logic with Pearson correlation to optimize contaminant detection in water distribution system with uncertainty analyses.

An effective detection algorithm, supervising an online water system, is expected to monitor changes in water quality due to any contamination. However, contemporary event detection methods are often criticized for their high false detection rates as well as for their low true detection rates. This study proposes two new event detection methods for contamination that use multi-objective optimization by investigating the correlation between multiple types of conventional water quality sensors. While the first method incorporates non-dominated sorting genetic algorithm II (NSGA-II) with the Pearson correlation Euclidean distance (PE) method in order to maximize the probability of detection (PD) and to minimize the false alarm rate (FAR), the second method introduces fuzzy logic in order to establish a degree of correlations ranking that replaces the correlation relationship indicator threshold. Optimization is performed by using NSGA-II in the second method. The results of this study show that the incorporation of fuzzy logic with NSGA-II in event detection method have produced better results in event detection. The results also show that both methods detect all true events without producing any false alarm rates. Moreover, an uncertainty analysis on input sensor signals is performed to test the robustness of the fuzzy logic-based event detection method by employing the widely used Monte Carlo simulation (MCS) technique. Four different scenarios of uncertainty are analyzed, in particular, and the findings suggest that the proposed method is very effective in minimizing false alarm rates and maximizing true events detection, and hence, it can be regarded as one of the novel approaches to demonstrate its application in the development of an event detection algorithm.

Bioaccumulation of Cr, Ni, Cd and Pb in the Economically Important Freshwater Fish Schizothorax plagiostomus from Three Rivers of Malakand Division, Pakistan: Risk Assessment for Human Health.

Contamination of freshwater ecosystems such as rivers with hazardous heavy metals is an environmental problem of public health concern. Accumulation of potentially toxic heavy metals in freshwater fish causes a potential health threat to their consumers including humans. The present research aimed to (1) investigate the accumulation of four potentially toxic heavy metals viz. Cr, Ni, Cd and Pb in muscle tissue of the commercially important freshwater fish Schizothorax plagiostomus at different sites of River Swat, River Panjkora and River Barandu in northern Pakistan (2) to compare gross metal accumulation in the fish samples by calculating metal pollution index (MPI) and (3) to assess potential risk to the health of the fish consumers. Samples were analyzed for the heavy metals by flame atomic absorption spectrophotometry (FAAS). Risk analysis showed that Ni risk was higher at River Panjkora and River Barandu, Pb risk was higher at River Swat and River Panjkora while Cd risk was quite low at all the three rivers.

Hepaotoprotective and nephroprotective activities of Pistacia integerrima fruit extract in paracetamol intoxicated male rabbits with effect on blood cells count.

The beneficial effects of Pistacia integerrima (PI) fruit methanol extract on some liver and kidney related parameters and blood cells count of paracetamol (PCM) intoxicated male rabbits were studied. Paracetamol intoxication caused remarkable increase in the serum ALT, AST and ALP levels. The PCM intoxicated rabbits that received PI extract orally at doses of 200 mg and 400 mg/kg b.w. /oral/day for 16 days showed significant reduction in serum ALT, AST and ALP levels (P<0.05). Liver microsections from PCM intoxicated rabbits treated with PI fruit methanol extract showed improvement in the liver histoarchitecture. The urine output of PCM intoxicated control rabbits group was significantly lower (P<0.05). The PCM intoxicated rabbits that received PI extract showed significant increase in urine output (P<0.05). The PCM intoxicated rabbits treated with PI extract also showed significant reduction in the levels of serum urea and creatinine (P<0.05). The renal creatinine clearance of PCM rabbits treated with PI extract improved significantly (P<0.05). Microsections of kidneys from PCM intoxicated rabbits treated with PI fruit methanol extract showed improvement in renal histoarchitecture. During this study, PI extract caused no improvement in the RBC count of PCM intoxicated rabbits. However, the extract caused significant increase in WBC and platelets count (P < 0.05) of PCM intoxicated rabbits. From the findings of the present research, it was concluded that oral administration of P. integerrima fruit methanol extract is beneficial for the liver and kidney related biochemical parameters and blood cells count of paracetamol intoxicated male rabbits.

Pathway for the Biosynthesis of the Pigment Chrysogine by Penicillium chrysogenum.

Chrysogine is a yellow pigment produced by Penicillium chrysogenum and other filamentous fungi. Although the pigment was first isolated in 1973, its biosynthetic pathway has so far not been resolved. Here, we show that deletion of the highly expressed nonribosomal peptide synthetase (NRPS) gene Pc21g12630 (chyA) resulted in a decrease in the production of chrysogine and 13 related compounds in the culture broth of P. chrysogenum Each of the genes of the chyA-containing gene cluster was individually deleted, and corresponding mutants were examined by metabolic profiling in order to elucidate their function. The data suggest that the NRPS ChyA mediates the condensation of anthranilic acid and alanine into the intermediate 2-(2-aminopropanamido)benzoic acid, which was verified by feeding experiments of a ΔchyA strain with the chemically synthesized product. The remainder of the pathway is highly branched, yielding at least 13 chrysogine-related compounds.IMPORTANCEPenicillium chrysogenum is used in industry for the production of ß-lactams, but also produces several other secondary metabolites. The yellow pigment chrysogine is one of the most abundant metabolites in the culture broth, next to ß-lactams. Here, we have characterized the biosynthetic gene cluster involved in chrysogine production and elucidated a complex and highly branched biosynthetic pathway, assigning each of the chrysogine cluster genes to biosynthetic steps and metabolic intermediates. The work further unlocks the metabolic potential of filamentous fungi and the complexity of secondary metabolite pathways.

Random mutagenesis of super Koji (Aspergillus oryzae): improvement in production and thermal stability of α-amylases for maltose syrup production.

BACKGROUND: Alpha-amylases hydrolyze 1,4 α-glycosidic bonds of starch and produce malto-oligosaccharides. It is an important enzyme generally applied in textile, food and brewing industries. Enhancement in thermal stability and productivity of enzymes are the two most sought after properties for industrial use. The Aspergillus oryzae (Koji) has Generally Recognized as Safe (GRAS) status and safe for use in food industry. Hence, Koji strain's development for the screening of potent mutants, hyper producer of thermostable α-amylases, with desired attributes is the need of the time. RESULTS: A process has been developed to improve super Koji (A. oryzae cmc1) strain through γ-rays treatment. The doses i.e. 0.60, 0.80, 1.00, 1.20 & 1.40 KGy gave more than 3.0 log kill. Initially, 52 Koji mutants resistant to 1% (w/v) Triton X-100 were selected. 2nd screening was based on α-amylases hyper production and 23 mutants were sorted out by measuring clearing zones index (CI). Afterwards nine potent mutants, resistant to 2-deoxy D-glucose, were screened based on CI. These were further analyzed for thermal stability and productivity of α-amylase under submerged conditions. The mutants' M-80(10), M-100(6) & M-120(5) gave about four fold increases in α-amylases productivity. The half life of M-100(6) α-amylase at 55 °C was 52 min and was highest among the mutants. Liquid Chromatography-Mass Spectrometry (LC-MS) analysis confirmed that mutants did not produce aflatoxins. Field Emission Scanning Electron Microscopy (FESEM) of Koji mycelia depicted that exposure to gamma rays increased rigidity of the mycelium. The potent Koji mutant M-100(6) was grown on soluble starch in 10L fermenter and produced 40.0 IU ml-1 of α-amylases with specific activity of 2461 IU mg-1 protein. Growth kinetic parameters were: µ = Specific growth rate= 0.069 h-1, td = Biomass doubling time= 10.0 h, Yp/x = Product yield coefficient with respect to cell mass = 482 U g-1; qp= Specific rate of product formation= 33.29 U g-1 h-1. CONCLUSION: It was concluded that the developed five step screening process has great potential to generate potent mutants for the hyper production of thermostable enzymes through γ-rays mediated physical mutagenesis. The developed thermostable α-amylases of super Koji mutantM-100(6) has immense potential for application in saccharification process for maltose syrup production. Moreover, the developed five step strain's development process may be used for the simultaneous improvement in productivity and thermal stability of other microbial enzymes.

Generative Adversarial Network for Medical Images (MI-GAN).

Deep learning algorithms produces state-of-the-art results for different machine learning and computer vision tasks. To perform well on a given task, these algorithms require large dataset for training. However, deep learning algorithms lack generalization and suffer from over-fitting whenever trained on small dataset, especially when one is dealing with medical images. For supervised image analysis in medical imaging, having image data along with their corresponding annotated ground-truths is costly as well as time consuming since annotations of the data is done by medical experts manually. In this paper, we propose a new Generative Adversarial Network for Medical Imaging (MI-GAN). The MI-GAN generates synthetic medical images and their segmented masks, which can then be used for the application of supervised analysis of medical images. Particularly, we present MI-GAN for synthesis of retinal images. The proposed method generates precise segmented images better than the existing techniques. The proposed model achieves a dice coefficient of 0.837 on STARE dataset and 0.832 on DRIVE dataset which is state-of-the-art performance on both the datasets.

Effect of long term exposure to sublethal concentration of imidacloprid on some biochemical and haematological parameters of Grass carp and Goldfish.

During the present research, C. idella and C. auratus fish were exposed to 2 ppm concentration of imidacloprid for 28 and 24 days, respectively, and the effect on biochemical and haematological parameters was investigated. During the study of biochemical parameters, there occurred significant increase (P<0.05) in the serum levels of ALT and creatinine of imidacloprid exposed groups of both species of fish. The level of serum albumin of imidacloprid exposed groups of both fish species was significantly lower as compared to control group (P<0.05). Serum globulin level in imidacloprid exposed group of C. idella was insignificantly lower as compared to control group, however the serum globulin level of C. auratus was significantly lower than the control group (P < 0.05). The level of total proteins in serum of imidacloprid exposed groups of both fish species was insignificantly lower as compared to control groups (P>0.05). During the study of haematological parameters, TLC of C. idella was insignificantly (P>0.05) higher than control group but the TLC of C. auratus was significantly (P<0.05) higher than control. There was also observed increasing trend in the percentage of neutrophils and lymphocytes of imidacloprid exposed group of each fish species. The platelets count of imidacloprid exposed group of each fish species was significantly (P<0.05) lower than control group. The haemoglobin concentration of imidacloprid exposed group of C. idella was significantly lower than control group (P<0.05). In case of C. auratus, the haemoglobin level of imidacloprid exposed group was insignificantly lower than control group (P>0.05). From the finding of the present research it was concluded that 28 days exposure of C. idella and 24 days exposure of C. auratus to 2 ppm concentration of imidacloprid does not cause mortality however the exposure causes alteration in the normal level of biochemical and haematological parameters.

Influence of endophytic Bacillus pumilus and EDTA on the phytoextraction of Cu from soil by using Cicer arietinum.

In developing countries, soil contamination with metals is ubiquitous, which poses a serious threat to the ecosystem. The current study was designed to screen out the nested belongings of Cicer arietinum plants and Bacillus pumilus (KF 875447) in extracting copper (Cu) from contaminated soils. A pot experiment was executed by growing C. arietinum seedlings either inoculated with B. pumilus or uninoculated along with the application of 5 mM ethylenediaminetetraacetic acid (EDTA). Plants were subjected to three different concentrations of Cu (250, 350, and 500 ppm) for 48 days. An increase in Cu uptake was observed in C. arietinum plants inoculated with B. pumilus as compared to uninoculated ones. C. arietinum exhibited improved values for different growth parameters in the presence of B. pumilus, that is, root length (37%), shoot length (31%), whole plant fresh as well as (45%) dry weight (27%), and chlorophyll contents (32%). More than 70% of tolerance index (TI) was observed for plants at 500 ppm Cu treatment. Addition of B. pumilus and EDTA significantly increased metal uptake by C. arietinum up to 19 and 36%, respectively, while the application of B. pumilus and EDTA in combination increased metal accumulation by 41%. The calculated bioaccumulation and translocation factor (TF) revealed that C. arietinum possess phytoextraction potential for Cu, and this ability is significantly improved with application of B. pumilus and EDTA amendments.