One-shot image semantic segmentation poses a challenging task of recognizing the object regions from unseen categories with only one annotated example as supervision. In this article, we propose a simple yet effective similarity guidance network to tackle the one-shot (SG-One) segmentation problem. We aim at predicting the segmentation mask of a query image with the reference to one densely labeled support image of the same category. To obtain the robust representative feature of the support image, we first adopt a masked average pooling strategy for producing the guidance features by only taking the pixels belonging to the support image into account. We then leverage the cosine similarity to build the relationship between the guidance features and features of pixels from the query image. In this way, the possibilities embedded in the produced similarity maps can be adopted to guide the process of segmenting objects. Furthermore, our SG-One is a unified framework that can efficiently process both support and query images within one network and be learned in an end-to-end manner. We conduct extensive experiments on Pascal VOC 2012. In particular, our SG-One achieves the mIoU score of 46.3%, surpassing the baseline methods.In applications of domain adaptation, there may exist multiple source domains, which can provide more or less complementary knowledge for pattern classification in the target domain. In order to improve the classification accuracy, a decision-level combination method is proposed for the multisource domain adaptation based on evidential reasoning. The classification results obtained from different source domains usually have different reliabilities/weights, which are calculated according to domain consistency. Therefore, the multiple classification results are discounted by the corresponding weights under belief functions framework, and then, Dempster’s rule is employed to combine these discounted results. In order to reduce errors, a neighborhood-based cautious decision-making rule is developed to make the class decision depending on the combination result. The object is assigned to a singleton class if its neighborhoods can be (almost) correctly classified. Otherwise, it is cautiously committed to the disjunction of several possible classes. By doing this, we can well characterize the partial imprecision of classification and reduce the error risk as well. A unified utility value is defined here to reflect the benefit of such classification. This cautious decision-making rule can achieve the maximum unified utility value because partial imprecision is considered better than an error. Several real data sets are used to test the performance of the proposed method, and the experimental results show that our new method can efficiently improve the classification accuracy with respect to other related combination methods.This article is concerned with the issue of l₂-l∞ state estimation for nonlinear coupled networks, where the variation of coupling mode is governed by a set of switching signals satisfying a persistent dwell-time property. To solve the problem of data collisions in a constrained communication network, the round-robin protocol, as an important scheduling strategy for orchestrating the transmission order of sensor nodes, is introduced. Redundant channels with signal quantization are used to improve the reliability of data transmission. The main purpose is to determine an estimator that can guarantee the exponential stability in mean square sense and an l₂-l∞ performance level of the estimation error system. Based on the Lyapunov method, sufficient conditions for the addressed problem are established. The desired estimator gains can be obtained by addressing a convex optimization case. The correctness and availability of the developed approach are finally explained via two illustrative examples.Unsupervised domain adaptation (UDA) aims at reducing the distribution discrepancy when transferring knowledge from a labeled source domain to an unlabeled target domain. Previous UDA methods assume that the source and target domains share an identical label space, which is unrealistic in practice since the label information of the target domain is agnostic. This article focuses on a more realistic UDA scenario, i.e., partial domain adaptation (PDA), where the target label space is subsumed to the source label space. In the PDA scenario, the source outliers that are absent in the target domain may be wrongly matched to the target domain (technically named negative transfer), leading to performance degradation of UDA methods. This article proposes a novel target-domain-specific classifier learning-based domain adaptation (TSCDA) method. TSCDA presents a soft-weighed maximum mean discrepancy criterion to partially align feature distributions and alleviate negative transfer. Also, it learns a target-specific classifier for the target domain with pseudolabels and multiple auxiliary classifiers to further address the classifier shift. A module named peers-assisted learning is used to minimize the prediction difference between multiple target-specific classifiers, which makes the classifiers more discriminant for the target domain. Extensive experiments conducted on three PDA benchmark data sets show that TSCDA outperforms other state-of-the-art methods with a large margin, e.g., 4% and 5.6% averagely on Office-31 and Office-Home, respectively.This article considers the problem of finite-time consensus for nonlinear multiagent systems (MASs), where the nonlinear dynamics are completely unknown and the output saturation exists. First, the mapping relationship between the output of each agent at the terminal time and the control input is established along the iteration domain. By using the terminal iterative learning control method, two novel distributed data-driven consensus protocols are proposed depending on the input and output saturated data of agents and its neighbors. Then, the convergence conditions independent of agents’ dynamics are developed for the MASs with fixed communication topology. It is shown that the proposed data-driven protocol can guarantee the system to achieve two different finite-time consensus objectives. Meanwhile, the design is also extended to the case of switching topologies. Finally, the effectiveness of the data-driven protocol is validated by a simulation example.Network embedding is a highly effective method to learn low-dimensional node vector representations with original network structures being well preserved. However, existing network embedding algorithms are mostly developed for a single network, which fails to learn generalized feature representations across different networks. In this article, we study a cross-network node classification problem, which aims at leveraging the abundant labeled information from a source network to help classify the unlabeled nodes in a target network. To succeed in such a task, transferable features should be learned for nodes across different networks. To this end, a novel cross-network deep network embedding (CDNE) model is proposed to incorporate domain adaptation into deep network embedding in order to learn label-discriminative and network-invariant node vector representations. On the one hand, CDNE leverages network structures to capture the proximities between nodes within a network, by mapping more strongly connected nodes to have more similar latent vector representations. On the other hand, node attributes and labels are leveraged to capture the proximities between nodes across different networks by making the same labeled nodes across networks have aligned latent vector representations. Extensive experiments have been conducted, demonstrating that the proposed CDNE model significantly outperforms the state-of-the-art network embedding algorithms in cross-network node classification.Online learning methods are designed to establish timely predictive models for machine learning problems. The methods for online learning of nonlinear systems are usually developed in the reproducing kernel Hilbert space (RKHS) associated with Gaussian kernel in which the kernel bandwidth is manually selected and remains steady during the entire modeling process in most cases. This setting may make the learning model rigid and inappropriate for complex data streams. Since the bandwidth appears in a nonlinear term of the kernel model, it raises substantial challenges in the development of learning methods with an adaptive bandwidth. In this article, we propose a novel approach to address this important open issue. By a carefully casted linearization scheme, the nonlinear learning problem is reasonably transformed into a state feedback control problem for a series of controllable systems. Then, by employing optimal control techniques, an effective algorithm is developed, and the parameters in the learning model including kernel bandwidth can be efficiently updated in a real-time manner. By taking advantage of the particular structure of the Gaussian kernel model, a theoretical analysis on the convergence and rationality of the proposed method is also provided. Compared with the kernel algorithms with a fixed bandwidth, our novel learning framework can not only achieve adaptive learning results with a better prediction accuracy but also show performance that is more robust with a faster convergence speed. Encouraging numerical results are provided to demonstrate the advantages of our new method.In this article, we study the generalization performance of multitask learning (MTL) by considering MTL as a learning process of vector-valued functions (VFs). We will answer two theoretical questions, given a small size training sample 1) under what conditions does MTL perform better than single-task learning (STL)? And 2) under what conditions does MTL guarantee the consistency of all tasks during learning? In contrast to the conventional task-summation based MTL, the introduction of VF form enables us to detect the behavior of each task and the task-group relatedness in MTL. Specifically, the task-group relatedness examines how the success (or failure) of some tasks affects the performance of the other tasks. By deriving the specific deviation and symmetrization inequalities for VFs, we obtain a generalization bound for MTL to the upper bound of the joint probability that there is at least one task with a large generalization gap. To answer the first question, we discuss how the synergic relatedness between task groups affects the generalization performance of MTL and shows that MTL outperforms STL if almost any pair of complementary task groups is predominantly synergic. Moreover, to answer the second question, we present a sufficient condition to guarantee the consistency of each task in MTL, which requires that the function class of each task should not have high complexity. In addition, our findings provide a strategy to examine whether the task settings will enjoy the advantages of MTL.Nontechnical losses (NTLs) are estimated to be considerable and increasing every year. Recently, high-resolution measurements from globally laid smart meters have brought deeper insights on users’ consumption patterns that can be exploited potentially by NTL detection. However, consumption-pattern-based NTL detection is now facing two major challenges the inefficiency of harnessing high dimensionality and the severe lack of fraudulent samples. To overcome them, an NTL detection model based on deep learning and anomaly detection is proposed in this article, namely bidirectional Wasserstein GAN and support vector data description-based NTL detector (BSBND). Motivated by the powerful ability of generative adversarial networks (GANs) to learn deep representation from high-dimensional distributions of data, in the BSBND, we utilized a BiWGAN for feature extraction from high-dimensional raw consumption records, and a one-class classifier trained only on benign samples–SVDD–is adopted to map features into judgments. Moreover, a novel alternate coordinating algorithm is proposed to optimize the cooperation between the upstream BiWGAN and the downstream SVDD, and also, an interpreting algorithm is proposed to visualize the basis of each fraudulent judgment. Case studies have demonstrated the superiority of the BSBND over the state of the arts, the powerful feature extraction ability of BiWGAN, and also the effectiveness of the proposed coordinating and interpreting algorithms.A powerful feature of adaptive memory is its inherent flexibility. Alcohol and other addictive substances can remold neural circuits important for memory to reduce this flexibility. However, the mechanism through which pertinent circuits are selected and shaped remains unclear. We show that circuits required for alcohol-associated preference shift from population level dopaminergic activation to select dopamine neurons that predict behavioral choice in Drosophila melanogaster. During memory expression, subsets of dopamine neurons directly and indirectly modulate the activity of interconnected glutamatergic and cholinergic mushroom body output neurons (MBON). Transsynaptic tracing of neurons important for memory expression revealed a convergent center of memory consolidation within the mushroom body (MB) implicated in arousal, and a structure outside the MB implicated in integration of naïve and learned responses. These findings provide a circuit framework through which dopamine neuronal activation shifts from reward delivery to cue onset, and provide insight into the maladaptive nature of memory.Objective To present our initial experience with double-face augmentation urethroplasty for near-obliterative bulbar urethral strictures and analyze the short-term outcomes. Material and methods We retrospectively evaluated a prospectively maintained database of patients with near-obliterative bulbar urethral strictures (>2 cm), who underwent double-face augmentation urethroplasty. The patients’ demographic characteristics, clinical data, and data regarding the investigations conducted were analyzed. Near-obliterative urethral stricture was defined as lumen less then 6 Fr. Double-face urethroplasty was performed using a ventral approach, during which dorsal inlay and ventral onlay buccal mucosal graft (BMG) augmentation were performed. A successful outcome was defined as normal voiding without the need for any instrumentation to improve the urinary flow rate. Results A total of 37 patients with a mean age of 50±11.7 years, who underwent this procedure were included in the study. The mean stricture length was 5.2±0.95 cm. The mean length of the dorsal inlay BMG augmentation was 3.1±0.5 cm and that of the ventral onlay BMG augmentation was 6.3±1.2 cm. Post-void dribbling (18.9%) was the most commonly reported complication. The maximum flow rates and symptom scores significantly improved in both groups compared with the preoperative parameters (p less then 0.001). The incidence of both erectile dysfunction and ejaculatory failure was reported in 6 (16.2%) patients; respectively. The overall success rate was 86.5% at a median follow-up period of 36 months (IQR 26.5-43). Conclusion Double-face augmentation urethroplasty is a safe and feasible option for near-obliterative bulbar urethral strictures, and our study showed satisfactory short-term outcomes for the same.Objective Urothelial carcinoma (UC) is heterogeneous, and variant histologies (VH) are more frequent than initially reported. Reporting VH is recommended by several guidelines because of prognostic and therapeutic implications. We evaluated the concordance of VH between the first transurethral resections of the bladder (TURBs) and the following radical cystectomy (RC). This paper is the first to compare VH with a central pathology review between TURB and RC. Material and methods In this retrospective study, we only included those patients who underwent TURB with VH and then RC between 01/2010 and 12/2013 at our institution. The presence of VH in both TURB and RC was assessed and compared according to the 2016 World Health Organization (WHO) classification by a central pathology review. Results Among 110 patients who had the initial TURB/RC, 54 (49.1%) were diagnosed with VH, 48 (43%) had a single pattern, and six had (5%) multiple histological patterns. Squamous differentiation was the most common single VH (31%). Twenty patients with UC (18%) showed discordance between TURB and RC, especially in micropapillary versus nested (n=3) cases. Concordant histology between TURB/RC was seen in 82% of the cases. Conclusion Discrepancies can be seen between TURB and RC when reporting VH, which can be problematic for selection of therapy and management. TURB alone might be insufficient to evaluate the presence of VH, especially in VH with heavy therapeutic implications, such as micropapillary carcinomas. Nevertheless, concordance with a central review by an experienced uropathologist when applying the WHO 2016 classification is 82%.Along with positive SARS-CoV-2 RNA in nasopharyngeal swabs, viral RNA was detectable at high concentration for >3 weeks in fecal samples from 12 mildly symptomatic and asymptomatic children with COVID-19. Saliva also tested positive during the early phase of infection. If proven infectious, feces and saliva could serve as transmission sources.Purpose The aim of this study was to develop 99mTc-[HYNIC-X-D-Phe13]-BBN(7-14)NH2 derivatives using two different tripeptidic spacer groups (X=GGG and X=SSS) in order to improve its pharmacokinetic, in vitro stability, specific binding and affinity. Background Bombesin (BBN), a 14-aminoacid amphibian peptide homologue of mammalian gastrin-releasing peptide (GRP), has demonstrated the ability to bind with high affinity and specificity to GRP receptor, which are overexpressed on a variety of human cancers. Methods Peptide conjugates labeled with 99mTc using tricine-EDDA and radiochemical purity was assessed by TLC and HPLC. The stability of radioconjugates was evaluated in the presence of saline and human serum. Affinity, internalization and also dissociation Constant was evaluated using MDA-MB-231 and PC-3 cell line. Biodistribution study was performed in BALB/C mice. Results Labeling yield of ˃95% was obtained. The change introduced in the BBN sequence increased plasma stability. In vitro blocking studies showed that, binding and internalization of both radiolabeled peptides are mediated by their receptors on the surface of MDA-MB-231 and PC-3 cells. Biodistribution results demonstrated a rapid blood clearance, with predominantly renal excretion. Specific binding in GRP receptor-positive tissues such as pancreas was confirmed with blocking study. Conclusions The introduction of spacer sequence between chelator and BBN(7-14) led to improved bidistribution. Analogue with tri-Gly spacer is the more promising radiopeptide for targeting GRP receptor than Ser conjugate. Therefore, these analogs can be considered as a candidate for the identification of bombesin-positive tumors.Background Poor bioavailability and poor solubility of drugs in aqueous phase are the most important problems of newly developed chemical entities that can be improved by nanoemulsion. Objectives BCS class II and IV which are poorly soluble in water demonstrate various problems in conventional dosage forms. For the improvement of solubility, bioavailability and getting best therapeutic effect of poorly soluble drugs nanoemulsion is the best solution. Method Nanoemulsion are thermodynamically unstable isotropic system with droplet size 1- 100 nm in which two immiscible fluids are combined together to form one phase by using an emulsifying agent. Nanoemulsion can be designed to promote the bioavailability of API by trapping them inside. Results Nanoemulsion can be developed in many dosage forms such as oral, parenteral, topical, ophthalmic dosage form in large scale using common operation at a very low cost. Large range of lipophilic drugs can be easily incorporated in nanoemulsion. Conclusion In this review, attention is focused on the type of nanoemulsion, their advantages over other dosage form, method for their preparation, characterization, applications and patents in various fields.Background and objective Psoriasis is an autoimmune skin disease involving cascading release of cytokines activated by the innate and acquired immune system. The increasing prevalence rate of psoriasis demands for more appropriate therapy. The existing chemical moiety is promising for the better therapeutic outcome but the selection of a proper channel for administration has to be reviewed. Hence there is a need to select the most appropriate dosage form and route of administration for improving the curative rate of psoriasis. Results A total of 108 systematic reviews of research and review articles was carried to make the manuscript comprehensible. The role of inflammatory mediators in the pathogenesis of the disease is discussed for a better understanding of the selection of pharmacotherapy. The older and newer therapeutic moiety with its mode of administration for psoriasis treatment has been discussed. With a comparative review on topical and oral administration of first-line drugs such as methotrexate (MTX), cyclosporine (CsA), and betamethasone, its benefits-liabilities in the selected routes were accounted for. Emphasis has also been given towards advanced nanocarriers for dermatologic applications. Conclusion For better therapeutic outcome, proper selection of drug moiety with its appropriate administration is the major requisite. With the advent of nanotechnology, the development of nanocarrier for dermatologic application has been successfully demonstrated in positioning the systemically administrated drug into topical targeted delivery. In a nutshell, to achieve successful treatment strategies towards psoriasis, there is a need to focus on the development of stable, non-toxic nanocarrier for topical delivery. Inclusion of the existing orally administered drug moiety into nanocarriers for topical delivery is proposed, in order to enhance therapeutics payload with reduced side effects which serves as a better treatment approach for relief of the psoriasis condition.Introduction Gasdermin A (GSDMA) and Gasdermin B (GSDMB) have been associated with childhood and to a lesser extent with adult asthma in many populations. In this study, investigate whether there is an association between GSDMA (rs7212938, T/G) and GSDMB (rs7216389, T/C) at locus 17q21.2 and risk of Allergic Rhinitis among Jordanians. Also we aimed to determine if there is an association between such polymorphisms and the IgE level. Methods The study included 112 rhinitis patients and 111 Healthy controls. Gasdermin A (GSDMA) (rs7212938, T/G) and Gasdermin B (rs7216389, T/C) polymorphisms were genotyped using the PCR-RFLP method. Results On the genotype level, three analysis models were applied namely co-dominant, dominant and recessive genotypes. GSDMB CC genotype was found to be significant protective effect against of allergic Rhinitis ( less then 0.05). cc genotype was also significantly associated with higher IGE level among the studied population. Conclusion The GSDMB CC of homozygous minor genotype showed a protective effect against Allergic rhinitis. It also was found to be significantly associated with lower IGE level among the studied population. No association was found between GSDMA with the risk of allergic Rhinitis.Osteoporosis is one of the major health issues associated with menopause-related estrogen deficiency. Various reports suggest that the hormonal changes related to menopausal transition may lead to derangement of redox homeostasis and ultimately oxidative stress. Estrogen deficiency and oxidative stress may enhance the expression of genes involved in inflammation. All these factors may contribute, in synergy, to the development of postmenopausal osteoporosis. Previous studies suggest that estrogen may act as an antioxidant to protect the bone against oxidative stress, and as an antiinflammatory agent in suppressing pro-inflammatory and pro-osteoclastic cytokines. Thus, the focus of the current review is to examine the relationship between estrogen deficiency, oxidative stress and inflammation, and the impacts of these phenomena on skeletal health in postmenopausal women.Objective Lipemia is one of the causes of interference in immunoassay and LC-MS/MS methods. Increased prevalence of vitamin D deficiency in the US, where obesity is gradually increasing, raises the suspicion that high levels of fat diet and blood lipid levels interfere with vitamin D measurement results. The focus of this study was to investigate the effect of blood lipid profiles on vitamin D results and prevent the matrix effect. Material and methods In this study, 25OH vitamin D3 (25OHD3) levels of 100 samples consecutively accepted to biochemistry laboratory regardless of age and sex were measured by the LC-MS/MS method, and each sample was restudied after 1/10 dilution. After dilution restudy, two groups were obtained-group 1 (results deviating below 20%) and group 2 (results deviating above 20%)-and the difference between the groups was investigated. There were 79 patients in group 1 and 21 patients in group 2. In our study, lipid profiles (triglyceride, total cholesterol, HDL, LDL) from the same samples of consecutive vitamin D patients were studied. Results It was observed that the triglyceride, total cholesterol HDL, LDL, and 25OHD3 measurements of group 1 and group 2 were similar (p > 0.05). While the mean vitamin D value in the second group was 9.94 ± 7.85, the mean vitamin D value after dilution was measured as 39.23 ± 18.13 and was statistically significant. 25OHD3 concentrations of 21 patients out of 100 were found to be falsely low. Measurements were repeated to confirm the results. Conclusion The matrix effect caused by exogenous and endogenous interferences in the blood could be a hidden factor increasing the prevalence of vitamin D deficiency by causing falsely low 25OHD3 values. Suspicious results should be remeasured by a dilution study.The nuclear erythroid 2-related factor 2 (Nrf2) signaling pathway has a main role against oxidative stress and inflammation. Spinal cord injury (SCI) leads to the high secretion of inflammatory cytokines and reactive oxygen species, which disturbs nervous system function and regeneration. Several studies have indicated that the activation of the Nrf2 signaling pathway may be effective against inflammation after SCI. The experimental studies have indicated that many chemical and natural agents act as Nrf2 inducer, which inhibits the SCI progression. Thus, the finding of novel Nrf2-inducer anti-inflammatory agents may be a valuable approach in drug discovery. In the present review, we discussed the Nrf2 signal pathway and crosstalk with the NF-κB pathway and also the impact of this pathway on inflammation in animal models of SCI. Furthermore, we discussed the regulation of Nrf2 by several phytochemicals and drugs, as well as their effects on the SCI inhibition. Therefore, the current study presented a new hypothesis of the development of anti-inflammatory agents that mediate the Nrf2 signaling pathway for treating the SCI outcomes.Background Studies have found that autophagy could promote the clearance of Aβ. To promote and maintain the occurrence of autophagy in Alzheimer’s disease (AD) might be a potential way to reduce neuronal loss and improve the learning and memory of AD. Objective To investigate the possible mechanisms of Yishen Huazhuo Decoction (YHD) against AD model. Methods Forty 7-month-old male SAMP8 mice were randomly divided into model (P8) group and YHD group, 20 in each group, with 20 SAMR1 mice as control (R1) group. All mice were intragastrically administered for 4 weeks, YHD at the dosage of 6.24g/kg for YHD group, and distilled water for P8 group and R1 group. Morris water maze (MWM) test, Nissl’s staining, TEM, TUNEL staining, immunofluorescence double staining, and western blot analysis were applied to learning and memory, structure and ultrastructure of neurons, autophagosome, apoptosis index, Aβ, LAMP1, and autophagy related proteins. Results The escape latency time of YHD group was significantly shorter on the 4th and 5th day during MWM test than those in P8 group (P=0.011, 0.0080.05), while Caspase3 expression in YHD group was significantly lower (P=0.044 less then 0.05). YHD could promote the clearance of Aβ1-42 protein, improve the expression of Beclin-1 and p-Bcl2 proteins, reduce mTOR and p62 proteins. Conclusions YHD could induce autophagy initiation, increase the formation of autophagosomes and autolysosome, promote the degradation of autophagy substrates, thereby to regulate autophagy, thereby to promote the clearance of Aβ1-42 to improve memory impairment in SAMP8 mice.Background Mammalian central neurons regulate their intracellular pH (pHi) strongly and even slight pHi-fluctuations can influence inter-/intracellular signaling, synaptic plasticity and excitability. Objective For the first time, we investigated topiramate´s (TPM) influence on pHi- behavior of human central neurons representing a promising target for anticonvulsants and antimigraine drugs. Methods In slice-preparations of tissue resected from the middle temporal gyrus of five adults with intractable temporal lobe epilepsy, BCECF-AM-loaded neocortical pyramidal-cells were investigated fluometrically. The pHi-regulation was estimated by using the recovery-slope from intracellular acidification after an ammonium-prepulse (APP). Results Among 17 pyramidal neurons exposed to 50 µM TPM, seven (41.24%) responded with an altered resting-pHi (7.02±0.12), i.e. acidification of 0.01-0.03 pH- units. The more alkaline the neurons, the greater the TPM-related acidifications (r=0.7, p=0.001, n=17). The recovery from APP-ac conclusions.”Background Drug repositioning is becoming popular due to the development of resistance to almost all the recommended antimalarials. Pregabalin and gabapentin are chemical analogs of gamma-aminobutyric acid (GABA) approved for the treatment of epilepsy and neuropathic pain. Objective This study investigates acute toxicities and antimalarial activities of pregabalin and gabapentin in the murine malarial model. Method Acute toxicities were assessed using the method of Lorke, while curative activities were assessed by administration of serial doses of pregabalin and gabapentin to Plasmodium berghei infected mice. Pregabalin was further investigated for its prophylactic activity, and curative potential when combined with either artesunate or amodiaquine. All drugs were freshly prepared and administered orally. Thin films were collected, stained, and observed under the microscope for estimation of parasitemia and calculation of percentage chemoinhibition or chemoprevention. In pregabalin -artesunate or -amodiaquine combination aspect of this study, survival day post-infection (SDPI) was recorded, while parasitemia was re-estimated for animals that survived till day 28. Results The oral LD50 of gabapentin, as well as pregabalin, was >5,000 mg/kg. Gabapentin at 100 and 200 mg/Kg demonstrated 35.64% and -12.78% chemoinhibition, respectively while pregabalin demonstrated 75.60% and 100.00% chemoinhibition at doses of 12.5 and 25 mg/Kg respectively. Also, pregabalin at individual doses of 25, 50 mg/Kg, and in combination with either artesunate or amodiaquine demonstrated 100.00% chemoinhibition. In its prophylactic study, pregabalin was found to be 100% chemopreventive at individual doses of 12.5 and 25 mg/Kg. Conclusion Both GABA analogs have antimalarial properties, but pregabalin proved to be more efficacious.Background and objective Indoleamine-2,3-dioxygenase 1 (IDO1) which catalyzes degradation of L-tryptophan (L-Trp) to N-formyl kynurenine (NFK) in the first and rate-limiting step of Kynurenine (KYN) pathway has been identified as a promising therapeutic target for cancer immunotherapy. The small molecule Epacadostat developed by Incyte Corp is the most advanced IDO1 inhibitor in clinical trials. Methods In this study, various amidine derivatives were individually installed as the polar capping group onto the amino ethylene side chain to replace the sulfamoylamino moiety of Epacadostat to develop novel IDO1 inhibitors. A series of novel 1,2,5-oxadiazol3-carboximidamide derivatives were designed, prepared, and evaluated for their inhibitory activities against human IDO1 enzyme and cellular IDO1. Results In vitro human IDO1 enzyme and cellular IDO1 assay results demonstrate that the inhibitory activities of compound 13a and 13b were comparable to Epacadostat, with the enzymatic IC50 values of 49.37nM and 52.12nM and cellular IC50 values of 12.34nM and 14.34nM respectively. The anti-tumor efficacy of 13b is slightly better than Epacadosta in Lewis Lung Cancer (LLC) tumorbearing mice model. Conclusion 13b is a potent IDO1 inhibitor with therapeutic potential in tumor immunotherapy.Background Studies showed that biogenic selenium nanoparticles (SeNPs) have a number of pharmacological properties such as antimicrobial ones. Objective The present investigation assesses the efficacy of biogenic selenium nanoparticles (SeNPs) as a new patent against latent toxoplasmosis in mice model. Methods Male BALB/c mice were orally treated with SeNPs at the doses of 2.5, 5, 10 mg/kg once a day for 14 days. On the 15th day, the mice were infected with the intraperitoneal inoculation of 20-25 tissue cysts from the Tehran strain of Toxoplasma gondii. The mean numbers of brain tissue cysts and the mRNA levels of TNF-α, IL-12, IL-10, IFN-γ, and inducible nitric oxide synthase (iNOS) in mice of each tested group were measured. Moreover, serum clinical chemistry factors in treated mice were examined to determine the safety of SeNPs. Results The mean number of the brain tissue cysts was significantly (P0.05) was observed in the clinical chemistry parametrs among the mice in the control subgroups compared with groups treated with SeNPs. Conclusion The results of the present study showed a new patent in the treatment of toxoplasmosis; so that taking the biogenic selenium nanoparticles in concentrations of 2.5-10 mg/kg for 2 weeks was able to prevent severe symptoms of the toxoplasmosis in mice model. This indicated the prophylactic effects of SeNPs with no considerable toxicity against latent toxoplasmosis. However, more studies are required to elucidate the correct anti-Toxoplasma mechanisms of SeNPs.Background Scanning patient’s lungs to detect a Coronavirus 2019 (COVID-19) may lead to similar imaging with other chest diseases that strongly requires a multidisciplinary approach to confirm the diagnosis. There are only few works targeted pathological x-ray images. Most of the works targeted only single disease detection which is not good enough. Some works have provided for all classes however the results suffer due to lack of data for rare classes and data unbalancing problem. Methods Due to arise of COVID-19 virus medical facilities of many countries are overwhelmed and there is a need of intelligent system to detect it. There have been few works regarding detection of the coronavirus but there are many cases where it can be misclassified as some techniques do not provide any goodness if it can only identify type of diseases and ignore the rest. This work is a deep learning-based model to distinguish between cases of COVID-19 from other chest diseases which is need of today. Results A Deep Neural Network model provides a significant contribution in terms of detecting COVID-19 and provide effective analysis of chest related diseases with respect to age and gender. Our model achieves 87% accuracy in terms of Gan based synthetic data and four different types of deep learning- based models which provided state of the art comparable results. Conclusion If the gap in identifying of all viral pneumonias is not filled with effective automation of chest disease detection the healthcare industry may have to bear unfavorable circumstances.Diabetes mellitus (DM) is recognized as the most common and the world’s fastestgrowing chronic disease with severe complications leading to increased mortality. Many strategies exist for the management of DM and its control including treatment with insulin and insulin analogs, oral hypoglycemic therapy such as insulin secretion stimulators and insulin sensitizers, and diet and physical training. Over the years, many types of drugs and molecules with an interesting pharmacological diversity have been developed and proposed for their anti-diabetic potential. Such molecules target diverse key receptors, enzymes, and regulatory/signaling proteins known to be directly or indirectly involved in the pathophysiology of DM. Among them, insulin receptor (IR) is undoubtedly the target of choice for its central role in insulin-mediated glucose homeostasis and its utilization by the major insulin-sensitive tissues such as skeletal muscles, adipose tissue, and liver. In this review, we focus on the implication of antibodies targeting IR in the pathology of DM as well as the recent advances in the development of IR antibodies as promising antidiabetic drugs. The challenge still consists to develop more powerful, highly selective, and safer anti-diabetic drugs.Background Imaging agents are crucial in diagnosing diseases. Ultrasmall lanthanide oxide (Ln2O3) nanoparticles (NPs) (Ln = Eu, Gd, and Dy) are promising materials as high-performance imaging agents because of their excellent magnetic, optical, and X-ray attenuation properties which can be applied as magnetic resonance imaging (MRI), fluorescence imaging (FI), and X-ray computed tomography (CT) agents, respectively. Ultrasmall Ln2O3 NPs (Ln = Eu, Gd, and Dy) are reviewed here. Method The reviewed topics include polyol synthesis, characterization, properties, and biomedical imaging applications of ultrasmall Ln2O3 NPs. Recently published papers were used as bibliographic databases. Results A polyol method is a simple and efficient one-pot synthesis for preparing ultrasmall Ln2O3 NPs. Ligand-coated ultrasmall Ln2O3 NPs have good colloidal stability, biocompatibility, and renal excretion ability suitable for in vivo imaging applications. Ultrasmall Eu2O3 NPs display photoluminescence in the red region suitable for use as FI agents. Ultrasmall Gd2O3 NPs have r1 values higher than those of commercial molecular contrast agents and r2/r1 ratios close to 1, which make them eligible for use as T1 MRI contrast agents. Ultrasmall Dy2O3 NPs exhibit high r2 and negligible r1 values, which make them suitable for use as T2 MRI contrast agents. All ultrasmall Ln2O3 NPs have high X-ray attenuation powers which make them suitable for use as CT contrast agents. Conclusion Unmixed, mixed, or doped ultrasmall Ln2O3 NPs with different Ln are extremely useful for in vivo imaging applications in MRI, CT, FI, MRI-CT, MRI-FI, CT-FI, and MRI-CT-FI.Background Naringin (NAR) is a flavonoid enriched in several medicinal plants and fruits. An increasing interest in this molecule has been emerging because it has the potential to contribute to alleviating many health problems. Objective This review briefly describes the NAR pharmacokinetics and it mainly focus on in vitro and in vivo animal studies showing NAR beneficial effects on cardiovascular, metabolic, neurological and pulmonary disorders and cancer. The anabolic effects of NAR on different models of bone and dental diseases are also analyzed. In addition, the evidence of the NAR action on the gastrointestinal tract is reported as well as its influence on the microbiota composition and activity. Finally, current research on NAR formulations and clinical applications are discussed. Methods The PubMed database was searched until 2019, using the keywords NAR, naringenin, cardiovascular and metabolic disorders, neurological and pulmonary disorders, cancer, bone and dental diseases, gastrointestinal tract, microbiota, NAR formulations, clinical trials. Results The number of studies related to the bioavailability and pharmacokinetics of NAR is limited. Positive effects of NAR have been reported on cardiovascular diseases, type 2 Diabetes mellitus (T2DM), metabolic syndrome, pulmonary disorders, neurodegenerative diseases, cancer and gastrointestinal pathologies. Current NAR formulations seem to improve its bioavailability, which would allow its clinical application. Conclusion NAR is endowed with broad biological effects that could improve human health. Since a scarce number of clinical studies have been performed, the use of them requires more investigation in order to know better their safety, efficacy, delivery and bioavailability in humans.Colon-targeted oral delivery has recently attracted a substantial number of studies on both systemic and local treatments. Among approaches for colonic delivery, film coatings have been demonstrated as effective elements of the drug delivery systems because they can integrate multiple release strategies, such as pH-controlled release, time-controlled release and enzyme-triggered release. Moreover, coating layer modulations, natural film materials and nanoparticle coatings have been vigorously investigated with promising applications. This review aims to describe the primary approaches for improving drug delivery to the colon in the last decade. The outstanding importance of current developments in film coatings will advance dosage form designs and lead to the development of efficient colon-targeted oral delivery systems.The imbalance between increased oxidative agents and antioxidant defence mechanisms is central in the pathogenesis of obstructive lung diseases such as asthma and COPD. In these patients, there are increased levels of reactive oxygen species. Superoxide anions (O2 – ), hydrogen peroxide (H2O2) and hydroxyl radicals (.OH) are critical for the formation of further cytotoxic radicals in the bronchi and lung parenchyma. Chronic inflammation, partly induced by oxidative stress, can further increase the oxidant burden through activated phagocytic cells (neutrophils, eosinophils, macrophages), particularly in severer disease states. Antioxidants and anti-inflammatory genes are, in fact, frequently downregulated in diseased patients. Nrf2, which activates the antioxidant response element (ARE) leading to up-regulation of GPx, thiol metabolism-associated detoxifying enzymes (GSTs) and stress-response genes (HO-1) are all downregulated in animal models and patients with asthma and COPD. An exaggerated production of nithese chronic disabling obstructive lung diseases.Significance The prevalence of chronic wounds is increasing worldwide. The most recent estimates suggest that up to 2% of the population in the industrialized countries are affected.1 Recent Advances During the past few decades, bacterial biofilms have been elucidated as one of the primary reasons why chronic wounds fail to heal.2,3 Critical Issues There is a lack of direct causation and evidence of the role that biofilms play in persistent wounds, which complicates research on new treatment options, since it is still unknown which factors dominate. For this reason, several different in vitro wound models have been created, that mimic the biofilm infections observed in chronic wounds and other chronic infections. These different models are, amongst other purposes, used to test a variety of wound care products. However, chronic wounds are highly complex, and several different factors must be taken into consideration along with the infection, including physiochemical and human-supplemented factors. Furthermore, the limitations of using in vitro models, such as the lack of a responsive immune system should always be given due consideration. Future directions Present understandings of all the elements and interactions that take place within chronic wounds are incomplete. As our insight of in vivo chronic wounds continues to expand, so too must the in vitro models used to mimic these infections evolve and adapt to new knowledge.Objective The goal of any topical formulation is efficient transdermal delivery of its active components. However, delivery of compounds can be problematic with penetration through tough layers of fibrotic dermal scar tissue. Approach We propose a new combined approach using high performance liquid chromatography (HPLC) and Raman spectroscopy (RS) in assessment of penetration of topicals used in scar management. Results Positive detection of compounds within the treatment topical using both techniques was validated with mass spectrometry. RS detected conformational structural changes; the 1655/1446 cm-1 ratio estimating collagen content significantly decreased (p less then 0.05) over weeks (W) 4, 12, and 16 compared to Day (D) 0. The amide I band, known to represent collagen and protein in skin, shifted from 1667 cm-1 to 1656 cm-1 which may represent a change from β-sheets in elastin to α-helices in collagen. Confirmatory elastin immunohistochemistry decreased compared to D0, conversely the collagen I/III ratio increased in the same samples by W12 (p less then 0.05, and p less then 0.0001 respectively), in keeping with normal scar formation. OCT attenuation coefficient representing collagen deposition was significantly decreased at W4 compared to D0 and increased at W16 (p less then 0.05). Innovation This study provides a platform for further research on the simultaneous evaluation of the effects of compounds in cutaneous scarring by RS, and a role for RS in the therapeutic evaluation and theranostic management of skin scarring. Conclusions RS can provide non-invasive information on the effects of topicals on scar pathogenesis and structural composition, validated by other analytical techniques such as HPLC.Significance Biofilms in vivo are small densely packed aggregations of microbes that are highly resistant to host immune responses and treatment. They attach to each other and to nearby surfaces. Biofilms are difficult to study and identify in a clinical setting as their quantification necessitates the use of advanced microscopy techniques such as confocal laser scanning microscopy. Nonetheless, it is likely that biofilms contribute to the pathophysiology of chronic skin wounds. Reducing, removing, or preventing biofilms is thus a logical approach to help clinicians heal chronic wounds. Recent Advances Wound care products have demonstrated varying degrees of efficacy in destroying biofilms in in vitro and preclinical models, as well as in some clinical studies. Critical Issues Controlled studies exploring the beneficial role of biofilm eradication and its relationship to healing in patients with chronic wounds are limited. This review aims to discuss the mode of action and clinical significance of currently available antibiofilm products, including surfactants, dressings, and others, with a focus on levels of evidence for efficacy in disrupting biofilms and ability to improve wound healing outcomes. Future Directions Few available products have good evidence to support antibiofilm activity and wound healing benefits. Novel therapeutic strategies are on the horizon. More high-quality clinical studies are needed. The development of noninvasive techniques to quantify biofilms will facilitate increased ease of research about biofilms in wounds and how to combat them.Objective Ischemic heart disease accounts for over 20% of all deaths worldwide. As the global population faces a rising burden of chronic diseases, such as hypertension, hyperlipidemia, and diabetes, the prevalence of heart failure due to ischemic heart disease is estimated to increase. We sought to develop a model that may more accurately identify therapeutic targets to mitigate the development of heart failure following MI. Approach Having utilized fetal large mammalian models of scarless wound healing, we proposed a fetal ovine model of myocardial regeneration after myocardial ischemia (MI). Results Use of this model has identified critical pathways in the mammalian response to MI that are differentially activated in the regenerative, fetal mammalian response to MI when compared to the reparative, scar-forming, adult mammalian response to MI. Innovation While the foundation of myocardial regeneration research has been built on zebrafish and rodent models, effective therapies derived from these disease models have been lacking; therefore, we sought to develop a more representative ovine model of myocardial regeneration after MI to improve the identification of therapeutic targets designed to mitigate the development of heart failure following MI. Conclusions In order to develop therapies aimed at mitigating this rising burden of disease, it is critical that the animal models we utilize closely reflect the physiology and pathology we observe in human disease. We encourage use of this ovine large mammalian model in order to facilitate identification of therapies designed to mitigate the growing burden of heart failure.Significance Non-healing wounds have been the subject of decades of basic and clinical research. Despite new knowledge about the biology of impaired wound healing, little progress has been made in treating chronic wounds, leaving patients with few therapeutic options. Diabetic ulcers are a particularly common form of non-healing wound. Recent Advances Recently, investigation of therapeutic nucleic acids (TNAs) including plasmid DNA, small-interfering RNA (siRNA), microRNA (miRNA) mimics, anti-microRNA oligonucleotides (anti-miR oligos, or AMO), messenger RNA (mRNA), and antisense oligonucleotides (ASOs) has created a new treatment strategy for chronic wounds. TNAs can modulate the wound towards a pro-healing environment by targeting gene pathways associated with inflammation, proteases, cell motility, angiogenesis, epithelialization, and oxidative stress. A variety of delivery systems have been investigated for TNAs, including dendrimers, lipid nanoparticles, polymeric micelles, polyplexes, metal nanoparticles, and hydrogels. The present review summarizes recent developments in TNA delivery for therapeutic targets associated with chronic wounds, with an emphasis on diabetic ulcers. Critical issues Translational potential of TNAs remains a key challenge; we highlight some drug delivery approaches for TNAs that may hold promise. We also describe current commercial efforts to locally deliver nucleic acids to modulate the wound environment. Future directions Localized nucleic acid delivery holds promise for the treatment of non-healing chronic wounds. Future efforts to improve targeting of these nucleic acid therapies in the wound with both spatial and temporal control through drug delivery systems will be crucial to successful clinical translation.Significance Infections can significantly delay the healing process in chronic wounds placing an enormous economic burden on health care resources. Identification of infection biomarkers and imaging modalities to observe and quantify them has seen progress over the years. Recent Advances Traditionally, clinicians determine the presence of infection through visual observation of wounds and confirm their diagnosis through wound culture. Many laboratory markers including white blood cell count, erythrocyte sedimentation rate, C-reactive protein, procalcitonin, presepsin, and bacterial protease activity have been quantified to assist diagnosis of infection. Moreover, imaging modalities like plain radiography, computed tomography, magnetic resonance imaging, ultrasound imaging, spatial frequency domain imaging, thermography, autofluorescence imaging, and biosensors, have emerged for real-time wound infection diagnosis and showed their unique advantages in deeper wound infection diagnosis. Critical issues While traditional diagnostic approaches provide valuable information, they are time-consuming and depend on clinicians’ experience.