Perturbative Analysis of Spectral Singularities and Their Optical Realizations

We develop a perturbative method of computing spectral singularities of a Schreodinger operator defined by a general complex potential that vanishes outside a closed interval. These can be realized as zero-width resonances in optical gain media and correspond to a lasing effect that occurs at the threshold gain. Their time-reversed copies yield coherent perfect absorption of light that is also known as an antilaser. We use our general results to establish the exactness of the n-th order perturbation theory for an arbitrary complex potential consisting of n delta-functions, obtain an exact expression for the transfer matrix of these potentials, and examine spectral singularities of complex barrier potentials of arbitrary shape. In the context of optical spectral singularities, these correspond to inhomogeneous gain media.Comment: 13 pages, 2 figures, one table, a reference added, typos correcte

Adjuvant Migraine Medications in the Treatment of Sudden Sensorineural Hearing Loss.

Objectives/hypothesisTo examine the hearing outcomes of patients with sudden sensorineural hearing loss (SSNHL) treated with oral and intratympanic (IT) steroid only or a combination of steroid and migraine treatment. Our hypothesis was that adjuvant migraine medications may improve outcomes in SSNHL.MethodsA retrospective chart review at a tertiary otology center was conducted to identify patients with SSNHL who received oral steroid and IT dexamethasone injection(s) with or without migraine medications (a combination of nortriptyline and topiramate).ResultsA total of 47 patients received oral steroid and IT dexamethasone injection(s) only, and 46 patients received oral steroid and IT dexamethasone injection(s) as well as migraine lifestyle changes plus a combination of nortriptyline and topiramate. There were no significant differences in demographics and baseline audiometric data between the two groups. Both groups demonstrated improvements in pure tone average (PTA) and hearing thresholds at 250 Hz and 8000 Hz posttreatment. However, compared to steroid-only group, the adjuvant migraine medications group had significantly greater improvements in hearing thresholds at the lower frequencies (250 Hz, 500 Hz, 1000 Hz). Patients in the latter cohort also had greater improvement in PTA (P = .01) and received fewer IT injections (P = .04) PTA improvement of ≥ 10 dB was observed in 36 patients (78%) in the adjuvant migraine medications group and 22 patients (46%) in the control group (P < .001).ConclusionIn multimodal treatment of SSNHL, supplementing oral and IT steroid with migraine medications may result in greater improvements in lower frequency hearing thresholds and PTA. Furthermore, adjuvant migraine treatment can lead to decrease in number of IT injections, thus reducing procedure-related risks and complications.Level of evidence3 Laryngoscope, 131:E283-E288, 2021

A new framework for consensus for discrete-time directed networks of multi-agents with distributed delays

Copyright @ 2012 Taylor & FrancisIn this article, the distributed consensus problem is considered for discrete-time delayed networks of dynamic agents with fixed topologies, where the networks under investigation are directed and the time-delays involved are distributed time delays including a single or multiple time delay(s) as special cases. By using the invariance principle of delay difference systems, a new unified framework is established to deal with the consensus for the discrete-time delayed multi-agent system. It is shown that the addressed discrete-time network with arbitrary distributed time delays reaches consensus provided that it is strongly connected. A numerical example is presented to illustrate the proposed methods.This work was supported in part by City University of Hong Kong under Grant 7008114, the Royal Society of the UK, the National Natural Science Foundation of China under Grants 60774073 and 61074129, and the Natural Science Foundation of Jiangsu Province of China under Grant BK2010313

In Vitro Screening of Seed Extracts of Medicinal Plants for Protease Inhibitory Activity

Protease inhibitors (PIs) are deployed in the plant kingdom as storage proteins or peptides, regulators of endogenous proteases, and plant protection agents against insect pests and pathogen attack. In humans, they are identified as chemopreventive agents against a range of cancers and have potential as drug to treat an array of disease associated with aberrant activity of proteases. The present investigation reports PIs activity data from 30 medicinal plants. The screening for PIs activity was done by dot blot assay using X-ray film coated with gelatin. Among screened seed extracts, Albizia lebbeck, Raphanus sativus, Mucuna pruriens, Achyranthes aspera, and Coffea arabica showed high inhibitory activities with trypsin protease. Most of seed extracts exhibited moderate activity, whereas Ocimum sanctum showed moderate to low activity against trypsin. The presence of varied protein content is reported from all seed extracts with highest in A. lebbeck (50.0 ± 3.4 mg/ml). The data produced in the present investigation could be helpful for further exploration of PIs as therapeutic agent

Traditional Methods for Treatment and Management of Measles in Northern Nigeria: Medicinal plants and their molecular docking

Background: Measles is one of the major causes of death among young children worldwide. According to the World Health Organization, measles affects more than 20 million people globally each year, with around 17 millions of them being children. In Nigeria, traditional herbal medicine has long been employed to treat this disease. Methods: Purposive sampling was used with the aid of an open-ended interview guide, from March–December 2021. In addition, a literature search was carried out on the reported plants. Molecular docking-based virtual screening was employed to identify possible compounds with higher affinity to the target enzyme. Results: Twenty-four medicinal plants and three traditional methods were documented for the treatment and management of measles in Northern Nigeria. Cow dung and fermented Sorghum had the highest Fidelity Level at 100 %, respectively. Leaves were the most common plant part used for the treatment of measles, likely due to the presence of secondary metabolites. Decoction and oral application were the most effective methods of preparation and administration, respectively. The binding affinities of the investigated compounds ranged from -1.3 Kcal/mol to -9.3 Kcal/mol, respectively. From the molecular docking, Quinoline and Amyrin were identified to have the highest binding affinity of -9.3 Kcal/mol, respectively. Conclusion: This study adds to our understanding of the plants utilized by Northern Nigerians in the prevention and treatment of measles. These data may be used to further pharmacological research on these therapeutic plants, with a focus on safety, standardization, and effective dose

Predicting clinical outcomes in neuroblastoma with genomic data integration

Background: Neuroblastoma is a heterogeneous disease with diverse clinical outcomes. Current risk group models require improvement as patients within the same risk group can still show variable prognosis. Recently collected genome-wide datasets provide opportunities to infer neuroblastoma subtypes in a more unified way. Within this context, data integration is critical as different molecular characteristics can contain complementary signals. To this end, we utilized the genomic datasets available for the SEQC cohort patients to develop supervised and unsupervised models that can predict disease prognosis. Results: Our supervised model trained on the SEQC cohort can accurately predict overall survival and event-free survival profiles of patients in two independent cohorts. We also performed extensive experiments to assess the prediction accuracy of high risk patients and patients without MYCN amplification. Our results from this part suggest that clinical endpoints can be predicted accurately across multiple cohorts. To explore the data in an unsupervised manner, we used an integrative clustering strategy named multi-view kernel k-means (MVKKM) that can effectively integrate multiple high-dimensional datasets with varying weights. We observed that integrating different gene expression datasets results in a better patient stratification compared to using these datasets individually. Also, our identified subgroups provide a better Cox regression model fit compared to the existing risk group definitions. Conclusion: Altogether, our results indicate that integration of multiple genomic characterizations enables the discovery of subtypes that improve over existing definitions of risk groups. Effective prediction of survival times will have a direct impact on choosing the right therapies for patients.No sponso

Low-dimensional Representations of Hyperspectral Data for Use in CRF-based Classification

Probabilistic graphical models have strong potential for use in hyperspectral image classification. One important class of probabilisitic graphical models is the Conditional Random Field (CRF), which has distinct advantages over traditional Markov Random Fields (MRF), including: no independence assumption is made over the observation, and local and pairwise potential features can be defined with flexibility. Conventional methods for hyperspectral image classification utilize all spectral bands and assign the corresponding raw intensity values into the feature functions in CRFs. These methods, however, require significant computational efforts and yield an ambiguous summary from the data. To mitigate these problems, we propose a novel processing method for hyperspectral image classification by incorporating a lower dimensional representation into the CRFs. In this paper, we use representations based on three types of graph-based dimensionality reduction algorithms: Laplacian Eigemaps (LE), Spatial-Spectral Schroedinger Eigenmaps (SSSE), and Local Linear Embedding (LLE), and we investigate the impact of choice of representation on the subsequent CRF-based classifications

Medicinal Plants Traditionally Used in the Management of COVID-19 in Kurdistan Region of Iraq

Coronaviruses are infectious respiratory tract illnesses, but they can also affect the digestive tract and infect both humans and animals. The new coronavirus results in complicated health problems all over the world. The most urgent concern of all researchers around the world has been the treatment of the virus. The following study aimed to use quantitative ethnobotany to help scientist in addressing the deadly virus. Expert sampling method was adopted with the aid of an in-depth interview guide. Thirty-nine respondents were interviewed. Eighty-one medicinal plant species from 35 families were documented. Males 25 (64.1%) constitute the greater percentage of the total respondents. Majority of the respondents had formal education. Eighty-one medicinal plant species from 35 families were documented. Leaves are the most utilized 25.8 followed by seed 17.7 and fruits 12.1%, respectively. Relative frequency of citation ranged from 0.5 to 0.9, whereas the FL value ranged from 0.4 to 0.85, revealing how effective the documented plant species are in the management of COVID-19 in the region. A greater amount of research into documented medicinal plants is warranted because of the high likelihood that they contain many active ingredients

Physiological Fluid Specific Agglomeration Patterns Diminish Gold Nanorod Photothermal Characteristics

Investigations into the use of gold nanorods (Au-NRs) for biological applications are growing exponentially due to their distinctive physicochemical properties, which make them advantageous over other nanomaterials. Au-NRs are particularly renowned for their plasmonic characteristics, which generate a robust photothermal response when stimulated with light at a wavelength matching their surface plasmon resonance. Numerous reports have explored this nanophotonic phenomenon for temperature driven therapies; however, to date there is a significant knowledge gap pertaining to the kinetic heating profile of Au-NRs within a controlled physiological setting. In the present study, the impact of environmental composition on Au-NR behavior and degree of laser actuated thermal production was assessed. Through acellular evaluation, we identified a loss of photothermal efficiency in biologically relevant fluids and linked this response to excessive particle aggregation and an altered Au-NR spectral profile. Furthermore, to evaluate the potential impact of solution composition on the efficacy of nano-based biological applications, the degree of targeted cellular destruction was ascertained in vitro and was found to be susceptible to fluid-dependent modifications. In summary, this study identified a diminution of Au-NR nanophotonic response in artificial physiological fluids that translated to a loss of application efficiency, pinpointing a critical concern that must be considered to advance in vivo, nano-based bio-applications