Design, optimization, and evaluation of methotrexate loaded and albumin coated polymeric nanoparticles.

Methotrexate is a potent anticancer drug whose strong efflux is facilitated by the brain's efflux transporter. As an efflux transporter blocker, albumin increased the drug's concentration in the brain. Methotrexate-loaded nanoparticles were produced by evaporating the emulsification fluid. Improvements and analyses were made to the following aspects of the generated nanoparticles: size, polydispersity, zeta potential, entrapment efficiency, percentage yield, scanning electron microscopy, in vitro drug release studies, and sterilization. The particle size was determined to be in the nano range, and homogeneity of particle size was suggested by a low polydispersity index result. Particle diameters of 168 nm were observed in the F5 preparation, and zeta potential values of -1.5 mV suggested that the preparation produced adequate repulsive interactions between the nanoparticles. Albumin and dopamine HCl were employed to coat the methotrexate-loaded nanoparticles to guarantee that the brain received an adequate amount of them. The homogeneity of albumin coated nanoparticles was demonstrated by the low% PDI values of 0.129 and 0.122 for albumin coated nanoparticles (MNPs-Alb) and polymerized dopamine HCl and albumin coated nanoparticles (MNPs-PMD-Alb), respectively. After 48 h of incubation, the cell viability measured at the same drug concentration (5 mg) decreased for the F5, albumin coated nanoparticles, polymerized dopamine HCl coated nanoparticles, and polymerized dopamine HCl and albumin coated nanoparticles, respectively. Our primary findings demonstrate that the albumin nanoparticles containing methotrexate are designed to deliver the drug gradually. With minimal cytotoxicity, the intended preparation might give the brain an appropriate dosage of methotrexate.

Potential role of oxytocin in the regulation of memories and treatment of memory disorders.

Oxytocin (OXT) is an "affiliative" hormone or neurohormone or neuropeptide consists of nine amino acids, synthesized in magnocellular neurons of paraventricular (PVN) and supraoptic nuclei (SON) of hypothalamus. OXT receptors are widely distributed in various region of brain and OXT has been shown to regulate various social and nonsocial behavior. Hippocampus is the main region which regulates the learning and memory. Hippocampus particularly regulates the acquisition of new memories and retention of acquired memories. OXT has been shown to regulate the synaptic plasticity, neurogenesis, and consolidation of memories. Further, findings from both preclinical and clinical studies have suggested that the OXT treatment improves performance in memory related task. Various trials have suggested the positive impact of intranasal OXT in the dementia patients. However, these studies are limited in number. In the present study authors have highlighted the role of OXT in the formation and retrieval of memories. Further, the study demonstrated the outcome of OXT treatment in various memory and related disorders.

Stimulated Emission of Signal Photons from Dark Matter Waves.

The manipulation of quantum states of light has resulted in significant advancements in both dark matter searches and gravitational wave detectors. Current dark matter searches operating in the microwave frequency range use nearly quantum-limited amplifiers. Future high frequency searches will use photon counting techniques to evade the standard quantum limit. We present a signal enhancement technique that utilizes a superconducting qubit to prepare a superconducting microwave cavity in a nonclassical Fock state and stimulate the emission of a photon from a dark matter wave. By initializing the cavity in an |n=4⟩ Fock state, we demonstrate a quantum enhancement technique that increases the signal photon rate and hence also the dark matter scan rate each by a factor of 2.78. Using this technique, we conduct a dark photon search in a band around 5.965 GHz (24.67 µeV), where the kinetic mixing angle ε≥4.35×10^{-13} is excluded at the 90% confidence level.

Current Landscape of Gene Therapy for the Treatment of Cardiovascular Disorders.

Cardiovascular disorders (CVD) are the primary cause of death worldwide. Multiple factors have been accepted to cause cardiovascular diseases; among them, smoking, physical inactivity, unhealthy eating habits, age, and family history are flag-bearers. Individuals at risk of developing CVD are suggested to make drastic habitual changes as the primary intervention to prevent CVD; however, over time, the disease is bound to worsen. This is when secondary interventions come into play, including antihypertensive, anti-lipidemic, anti-anginal, and inotropic drugs. These drugs usually undergo surgical intervention in patients with a much higher risk of heart failure. These therapeutic agents increase the survival rate, decrease the severity of symptoms and the discomfort that comes with them, and increase the overall quality of life. However, most individuals succumb to this disease. None of these treatments address the molecular mechanism of the disease and hence are unable to halt the pathological worsening of the disease. Gene therapy offers a more efficient, potent, and important novel approach to counter the disease, as it has the potential to permanently eradicate the disease from the patients and even in the upcoming generations. However, this therapy is associated with significant risks and ethical considerations that pose noteworthy resistance. In this review, we discuss various methods of gene therapy for cardiovascular disorders and address the ethical conundrum surrounding it.

Reactive oxygen species mediated apoptotic death of colon cancer cells: therapeutic potential of plant derived alkaloids.

Colorectal cancer (CRC) is one of the most deaths causing diseases worldwide. Several risk factors including hormones like insulin and insulin like growth factors (e.g., IGF-1) have been considered responsible for growth and progression of colon cancer. Though there is a huge advancement in the available screening as well as treatment techniques for CRC. There is no significant decrease in the mortality of cancer patients. Moreover, the current treatment approaches for CRC are associated with serious challenges like drug resistance and cancer re-growth. Given the severity of the disease, there is an urgent need for novel therapeutic agents with ideal characteristics. Several pieces of evidence suggested that natural products, specifically medicinal plants, and derived phytochemicals may serve as potential sources for novel drug discovery for various diseases including cancer. On the other hand, cancer cells like colon cancer require a high basal level of reactive oxygen species (ROS) to maintain its own cellular functions. However, excess production of intracellular ROS leads to cancer cell death via disturbing cellular redox homeostasis. Therefore, medicinal plants and derived phytocompounds that can enhance the intracellular ROS and induce apoptotic cell death in cancer cells via modulating various molecular targets including IGF-1 could be potential therapeutic agents. Alkaloids form a major class of such phytoconstituents that can play a key role in cancer prevention. Moreover, several preclinical and clinical studies have also evidenced that these compounds show potent anti-colon cancer effects and exhibit negligible toxicity towards the normal cells. Hence, the present evidence-based study aimed to provide an update on various alkaloids that have been reported to induce ROS-mediated apoptosis in colon cancer cells via targeting various cellular components including hormones and growth factors, which play a role in metastasis, angiogenesis, proliferation, and invasion. This study also provides an individual account on each such alkaloid that underwent clinical trials either alone or in combination with other clinical drugs. In addition, various classes of phytochemicals that induce ROS-mediated cell death in different kinds of cancers including colon cancer are discussed.

Assessing the prospect of XAFS experiments of metalloproteins under in vivo conditions at Indus-2 synchrotron facility, India.

The feasibility of X-ray absorption fine-structure (XAFS) experiments of ultra-dilute metalloproteins under in vivo conditions (T = 300 K, pH = 7) at the BL-9 bending-magnet beamline (Indus-2) is reported, using as an example analogous synthetic Zn (0.1 mM) M1dr solution. The (Zn K-edge) XAFS of M1dr solution was measured with a four-element silicon drift detector. The first-shell fit was tested and found to be robust against statistical noise, generating reliable nearest-neighbor bond results. The results are found to be invariant between physiological and non-physiological conditions, which confirms the robust coordination chemistry of Zn with important biological implications. The scope of improving spectral quality for accommodation of higher-shell analysis is addressed.

The QICK (Quantum Instrumentation Control Kit): Readout and control for qubits and detectors.

We introduce a Xilinx RF System-on-Chip (RFSoC)-based qubit controller (called the Quantum Instrumentation Control Kit, or QICK for short), which supports the direct synthesis of control pulses with carrier frequencies of up to 6 GHz. The QICK can control multiple qubits or other quantum devices. The QICK consists of a digital board hosting an RFSoC field-programmable gate array, custom firmware, and software and an optional companion custom-designed analog front-end board. We characterize the analog performance of the system as well as its digital latency, important for quantum error correction and feedback protocols. We benchmark the controller by performing standard characterizations of a transmon qubit. We achieve an average gate fidelity of Favg=99.93%. All of the schematics, firmware, and software are open-source.

Exploring Kid Space in the wild: a preliminary study of multimodal and immersive collaborative play-based learning experiences.

Parents recognize the potential benefits of technology for their young children but are wary of too much screen time and its potential deficits in terms of social engagement and physical activity. To address these concerns, related literature suggests technology usages with a blend of digital and physical learning experiences. Towards this end, we developed Kid Space, incorporating immersive computing experiences designed to engage children more actively in physical movement and social collaboration during play-based learning. The technology features an animated peer learner, Oscar, who aims to understand and respond to children's actions and utterances using extensive multimodal sensing and sensemaking technologies. To investigate student engagement during Kid Space learning experiences, an exploratory case study was designed using a formative research method with eight first-grade students. Multimodal data (audio and video) along with observational, interview, and questionnaire data were collected and analyzed. The results show that the students demonstrated high levels of engagement, less attention focused on the screen (projected wall), and more physical activity. In addition to these promising results, the study also enabled us to understand actionable insights to improve Kid Space for future deployments (e.g., the need for real-time personalization). We plan to incorporate the lessons learned from this preliminary study and deploy Kid Space with real-time personalization features for longer periods with more students.

Seamless High-Q Microwave Cavities for Multimode Circuit Quantum Electrodynamics.

Multimode cavity quantum electrodynamics-where a two-level system interacts simultaneously with many cavity modes-provides a versatile framework for quantum information processing and quantum optics. Because of the combination of long coherence times and large interaction strengths, one of the leading experimental platforms for cavity QED involves coupling a superconducting circuit to a 3D microwave cavity. In this work, we realize a 3D multimode circuit QED system with single photon lifetimes of 2 ms across 9 modes of a novel seamless cavity. We demonstrate a variety of protocols for universal single-mode quantum control applicable across all cavity modes, using only a single drive line. We achieve this by developing a straightforward flute method for creating monolithic superconducting microwave cavities that reduces loss while simultaneously allowing control of the mode spectrum and mode-qubit interaction. We highlight the flexibility and ease of implementation of this technique by using it to fabricate a variety of 3D cavity geometries, providing a template for engineering multimode quantum systems with exceptionally low dissipation. This work is an important step towards realizing hardware efficient random access quantum memories and processors, and for exploring quantum many-body physics with photons.

Searching for Dark Matter with a Superconducting Qubit.

Detection mechanisms for low mass bosonic dark matter candidates, such as the axion or hidden photon, leverage potential interactions with electromagnetic fields, whereby the dark matter (of unknown mass) on rare occasion converts into a single photon. Current dark matter searches operating at microwave frequencies use a resonant cavity to coherently accumulate the field sourced by the dark matter and a near standard quantum limited (SQL) linear amplifier to read out the cavity signal. To further increase sensitivity to the dark matter signal, sub-SQL detection techniques are required. Here we report the development of a novel microwave photon counting technique and a new exclusion limit on hidden photon dark matter. We operate a superconducting qubit to make repeated quantum nondemolition measurements of cavity photons and apply a hidden Markov model analysis to reduce the noise to 15.7 dB below the quantum limit, with overall detector performance limited by a residual background of real photons. With the present device, we perform a hidden photon search and constrain the kinetic mixing angle to ε≤1.68×10^{-15} in a band around 6.011 GHz (24.86 µeV) with an integration time of 8.33 s. This demonstrated noise reduction technique enables future dark matter searches to be sped up by a factor of 1,300. By coupling a qubit to an arbitrary quantum sensor, more general sub-SQL metrology is possible with the techniques presented in this Letter.

Quality assurance and enrichment of biological and biomedical ontologies and terminologies.

Biological and biomedical ontologies and terminologies are used to organize and store various domain-specific knowledge to provide standardization of terminology usage and to improve interoperability. The growing number of such ontologies and terminologies and their increasing adoption in clinical, research and healthcare settings call for effective and efficient quality assurance and semantic enrichment techniques of these ontologies and terminologies. In this editorial, we provide an introductory summary of nine articles included in this supplement issue for quality assurance and enrichment of biological and biomedical ontologies and terminologies. The articles cover a range of standards including SNOMED CT, National Cancer Institute Thesaurus, Unified Medical Language System, North American Association of Central Cancer Registries and OBO Foundry Ontologies.

Detecting modeling inconsistencies in SNOMED CT using a machine learning technique.

SNOMED CT is a comprehensive and evolving clinical reference terminology that has been widely adopted as a common vocabulary to promote interoperability between Electronic Health Records. Owing to its importance in healthcare, quality assurance becomes an integral part of the lifecycle of SNOMED CT. While, manual auditing of every concept in SNOMED CT is difficult and labor intensive, identifying inconsistencies in the modeling of concepts without any context can be challenging. Algorithmic techniques are needed to identify modeling inconsistencies, if any, in SNOMED CT. This study proposes a context-based, machine learning quality assurance technique to identify concepts in SNOMED CT that may be in need of auditing. The Clinical Finding and the Procedure hierarchies are used as a testbed to check the efficacy of the method. Results of auditing show that the method identified inconsistencies in 72% of the concept pairs that were deemed inconsistent by the algorithm. The method is shown to be effective in both maximizing the yield of correction, as well as providing a context to identify the inconsistencies. Such methods, along with SNOMED International's own efforts, can greatly help reduce inconsistencies in SNOMED CT.

Evaluating lexical similarity and modeling discrepancies in the procedure hierarchy of SNOMED CT.

BACKGROUND: SNOMED CT is a standardized and comprehensive clinical terminology that is used in Electronic Health Records to capture, store and access clinical data of patients. Studies have, however, shown that there are inconsistencies inherent in the modeling of concepts in SNOMED CT that can have an impact on its usage to record clinical data and in clinical decision-making tools. METHODS: An effective lexical approach to identifying inconsistencies with high likelihood in the structural modeling of the concepts of SNOMED CT is discussed and assessed. The approach uses the two or more concepts in the context of their lexical similarity to compare their modeling in order to identify inconsistencies. A sample of 50 sets is randomly picked from the Procedure hierarchy of SNOMED CT and evaluated for inconsistencies. RESULTS: Of the 50 randomly picked sets, 58% are found to exhibit one or more concepts with inconsistencies. In terms of concepts, 29% of the 146 concepts are found to exhibit one or more inconsistencies. CONCLUSIONS: The assessment of the sample concepts shows that SNOMED CT is not free from inconsistencies which may affect its use in clinical care and decision support systems. The proposed methodology is found to be effective in identifying areas of SNOMED CT that may be in need of quality assessment.

Augmentation of the step-by-step Energy-Scanning EXAFS beamline BL-09 to continuous-scan EXAFS mode at INDUS-2 SRS.

An innovative scheme to carry out continuous-scan X-ray absorption spectroscopy (XAS) measurements similar to quick-EXAFS mode at the Energy-Scanning EXAFS beamline BL-09 at INDUS-2 synchrotron source (Indore, India), which is generally operated in step-by-step scanning mode, is presented. The continuous XAS mode has been implemented by adopting a continuous-scan scheme of the double-crystal monochromator and on-the-fly measurement of incident and transmitted intensities. This enabled a high signal-to-noise ratio to be maintained and the acquisition time was reduced to a few seconds from tens of minutes or hours. The quality of the spectra (signal-to-noise level, resolution and energy calibration) was checked by measuring and analysing XAS spectra of standard metal foils. To demonstrate the energy range covered in a single scan, a continuous-mode XAS spectrum of copper nickel alloy covering both Cu and Ni K-edges was recorded. The implementation of continuous-scan XAS mode at BL-09 would expand the use of this beamline in in situ time-resolved XAS studies of various important systems of current technological importance. The feasibility of employing this mode of measurement for time-resolved probing of reaction kinetics has been demonstrated by in situ XAS measurement on the growth of Ag nanoparticles from a solution phase.

A tribal abstraction network for SNOMED CT target hierarchies without attribute relationships.

OBJECTIVE: Large and complex terminologies, such as Systematized Nomenclature of Medicine-Clinical Terms (SNOMED CT), are prone to errors and inconsistencies. Abstraction networks are compact summarizations of the content and structure of a terminology. Abstraction networks have been shown to support terminology quality assurance. In this paper, we introduce an abstraction network derivation methodology which can be applied to SNOMED CT target hierarchies whose classes are defined using only hierarchical relationships (ie, without attribute relationships) and similar description-logic-based terminologies. METHODS: We introduce the tribal abstraction network (TAN), based on the notion of a tribe-a subhierarchy rooted at a child of a hierarchy root, assuming only the existence of concepts with multiple parents. The TAN summarizes a hierarchy that does not have attribute relationships using sets of concepts, called tribal units that belong to exactly the same multiple tribes. Tribal units are further divided into refined tribal units which contain closely related concepts. A quality assurance methodology that utilizes TAN summarizations is introduced. RESULTS: A TAN is derived for the Observable entity hierarchy of SNOMED CT, summarizing its content. A TAN-based quality assurance review of the concepts of the hierarchy is performed, and erroneous concepts are shown to appear more frequently in large refined tribal units than in small refined tribal units. Furthermore, more erroneous concepts appear in large refined tribal units of more tribes than of fewer tribes. CONCLUSIONS: In this paper we introduce the TAN for summarizing SNOMED CT target hierarchies. A TAN was derived for the Observable entity hierarchy of SNOMED CT. A quality assurance methodology utilizing the TAN was introduced and demonstrated.

Contrasting lexical similarity and formal definitions in SNOMED CT: consistency and implications.

OBJECTIVE: To quantify the presence of and evaluate an approach for detection of inconsistencies in the formal definitions of SNOMED CT (SCT) concepts utilizing a lexical method. MATERIAL AND METHOD: Utilizing SCT's Procedure hierarchy, we algorithmically formulated similarity sets: groups of concepts with similar lexical structure of their fully specified name. We formulated five random samples, each with 50 similarity sets, based on the same parameter: number of parents, attributes, groups, all the former as well as a randomly selected control sample. All samples' sets were reviewed for types of formal definition inconsistencies: hierarchical, attribute assignment, attribute target values, groups, and definitional. RESULTS: For the Procedure hierarchy, 2111 similarity sets were formulated, covering 18.1% of eligible concepts. The evaluation revealed that 38 (Control) to 70% (Different relationships) of similarity sets within the samples exhibited significant inconsistencies. The rate of inconsistencies for the sample with different relationships was highly significant compared to Control, as well as the number of attribute assignment and hierarchical inconsistencies within their respective samples. DISCUSSION AND CONCLUSION: While, at this time of the HITECH initiative, the formal definitions of SCT are only a minor consideration, in the grand scheme of sophisticated, meaningful use of captured clinical data, they are essential. However, significant portion of the concepts in the most semantically complex hierarchy of SCT, the Procedure hierarchy, are modeled inconsistently in a manner that affects their computability. Lexical methods can efficiently identify such inconsistencies and possibly allow for their algorithmic resolution.

Identifying problematic concepts in SNOMED CT using a lexical approach.

SNOMED CT (SCT) has been endorsed as a premier clinical terminology by many organizations with a perceived use within electronic health records and clinical information systems. However, there are indications that, at the moment, SCT is not optimally structured for its intended use by healthcare practitioners. A study is conducted to investigate the extent of inconsistencies among the concepts in SCT. A group auditing technique to improve the quality of SCT is introduced that can help identify problematic concepts with a high probability. Positional similarity sets are defined, which are groups of concepts that are lexically similar and the position of the differing word in the fully specified name of the concepts of a set that correspond to each other. A manual auditing of a sample of such sets found 38% of the sets exhibiting one or more inconsistent concepts. Group auditing techniques such as this can thus be very helpful to assure the quality of SCT, which will help expedite its adoption as a reference terminology for clinical purposes.

The readiness of SNOMED problem list concepts for meaningful use of electronic health records.

OBJECTIVE: By 2015, SNOMED CT (SCT) will become the USA's standard for encoding diagnoses and problem lists in electronic health records (EHRs). To facilitate this effort, the National Library of Medicine has published the "SCT Clinical Observations Recording and Encoding" and the "Veterans Health Administration and Kaiser Permanente" problem lists (collectively, the "PL"). The PL is studied in regard to its readiness to support meaningful use of EHRs. In particular, we wish to determine if inconsistencies appearing in SCT, in general, occur as frequently in the PL, and whether further quality-assurance (QA) efforts on the PL are required. METHODS AND MATERIALS: A study is conducted where two random samples of SCT concepts are compared. The first consists of concepts strictly from the PL and the second contains general SCT concepts distributed proportionally to the PL's in terms of their hierarchies. Each sample is analyzed for its percentage of primitive concepts and for frequency of modeling errors of various severity levels as quality measures. A simple structural indicator, namely, the number of parents, is suggested to locate high likelihood inconsistencies in hierarchical relationships. The effectiveness of this indicator is evaluated. RESULTS: PL concepts are found to be slightly better than other concepts in the respective SCT hierarchies with regards to the quality measure of the percentage of primitive concepts and the frequency of modeling errors. There were 58% primitive concepts in the PL sample versus 62% in the control sample. The structural indicator of number of parents is shown to be statistically significant in its ability to identify concepts having a higher likelihood of inconsistencies in their hierarchical relationships. The absolute number of errors in the group of concepts having 1-3 parents was shown to be significantly lower than that for concepts with 4-6 parents and those with 7 or more parents based on Chi-squared analyses. CONCLUSION: PL concepts suffer from the same issues as general SCT concepts, although to a slightly lesser extent, and do require further QA efforts to promote meaningful use of EHRs. To support such efforts, a structural indicator is shown to effectively ferret out potentially problematic concepts where those QA efforts should be focused.

Identifying inconsistencies in SNOMED CT problem lists using structural indicators.

The National Library of Medicine has published the CORE and the VA/KP problem lists to facilitate the usage of SNOMED CT for encoding diagnoses and clinical data of patients in electronic health records. Therefore, it is essential for the content of the problem lists to be as accurate and consistent as possible. This study assesses the effectiveness of using a concept's word length and number of parents, two structural indicators for measuring concept complexity, to identify inconsistencies with high probability. The method is able to isolate concepts with over 40% expected of being erroneous. A structural indicator for concepts which is able to identify 52% of the examined concepts as having errors in synonyms is also presented. The results demonstrate that the concepts in problem lists are not free of inconsistencies and further quality assurance is needed to improve the quality of these concepts.

A family-based framework for supporting quality assurance of biomedical ontologies in BioPortal.

BioPortal contains over 300 ontologies, for which quality assurance (QA) is critical. Abstraction networks (ANs), compact summarizations of ontology structure and content, have been used in such QA efforts, typically in a "one-off" manner for a single ontology. Ontologies can be characterized-independently of knowledge-content focus-from a structural standpoint leading to the formulation of ontology families. A family is defined as a set of ontologies satisfying some overarching condition regarding their structural features. Seven such families, comprising 186 ontologies, are identified. To increase efficiency, a new family-based QA framework is introduced in which an automated, uniform AN derivation technique and accompanying semi-automated, uniform QA regimen are applicable to the ontologies of a given family. Specifically, across an entire family, the QA efforts exploit family-wide AN features in the characterization of sets of classes that are more likely to harbor errors. The approach is demonstrated on the Cancer Chemoprevention BioPortal ontology.