Abstract: A compact tunable optical true time delay consists of an optical subassembly to apply dispersion-free time delay to the input optical signal, and a mechanical subassembly to facilitate tuning the delay using a linear actuator. The deployment of a precision optical ferrule sliding in a precision split sleeve offers a self-contained and inexpensive method to minimize optical misalignment during the tuning process, which releases the burden of the mechanical subassembly and is also advantageous in keeping the device compact. The exterior dimension remains unchanged at any moment despite the interior motion. Both reflection-type and transmission-type optical time delays are introduced, driven either manually or electrically.

Abstract: A compact tunable optical true time delay consists of an optical subassembly to apply dispersion-free time delay to the input optical signal, and a mechanical subassembly to facilitate tuning the delay using a linear actuator. The deployment of a precision optical ferrule sliding in a precision split sleeve offers a self-contained and inexpensive method to minimize optical misalignment during the tuning process, which releases the burden of the mechanical subassembly and is also advantageous in keeping the device compact. The exterior dimension remains unchanged at any moment despite the interior motion. Both reflection-type and transmission-type optical time delays are introduced, driven either manually or electrically.

Abstract: A patient-trial matching system (100) includes a structuralizer (102) configured to convert input non-structured patient health data and input non-structured clinical trial eligibility criteria into structured patient health data and structured clinical trial eligibility criteria by organizing a content of the non-structured data as known data elements. The patient-trial matching system further includes a semantic matcher (122) configured to match the structured patient health data and the structured clinical trial eligibility criteria based on user input matching criteria and outputs matched results. The patient-trial matching system further includes a ranking engine (126) configured to rank the matched results using ranking criteria (128), which include ranking patients matched to a clinical trial of interest in response to matching to find a group of trial patients and ranking clinical trials matched to a particular patient in response to matching to find a clinical trial.

Abstract: Disclosed are composite materials comprising a porous, carbonated, calcium silicate ceramic having a microstructure comprising interconnected open pores; where the calcium silicate surface defining the pores is partially or completely coated with an amorphous silica layer, and the silica coating comprises an overlayer of calcium carbonate crystals; where the silica coating and calcium carbonate overlayer form a network that interconnects throughout the ceramic microstructure, but do not completely occlude the pores. Also disclosed are methods of forming such composite materials.

Abstract: A method (100) for standardizing gene nomenclature, comprising: (i) receiving (110) a source; (ii) tokenizing (120) the source; (iii) comparing (130) a first token to a prefix tree structure with a root node, edges, and leaf nodes; (iv) determining (140) which edge extending from the root node to associated first leaf nodes the first token matches; (v) updating (150) an identification pointer with the location of the first leaf node; (vi) determining (160) which of one or more edges that a second token matches; (vii) updating (170) the identification pointer with the location of the second leaf node; (viii) repeating (172) the determining (160) and updating (170) steps with subsequent tokens until a subsequent token fails to match an edge extending from a leaf node or there is no edge extending from the leaf node; and (ix) providing (180) an identification of a canonical gene name.

Abstract: A method (100) for standardizing gene nomenclature, comprising: (i) receiving (110) a source; (ii) tokenizing (120) the source; (iii) comparing (130) a first token to a prefix tree structure with a root node, edges, and leaf nodes; (iv) determining (140) which edge extending from the root node to associated first leaf nodes the first token matches; (v) updating (150) an identification pointer with the location of the first leaf node; (vi) determining (160) which of one or more edges that a second token matches; (vii) updating (170) the identification pointer with the location of the second leaf node; (viii) repeating (172) the determining (160) and updating (170) steps with subsequent tokens until a subsequent token fails to match an edge extending from a leaf node or there is no edge extending from the leaf node; and (ix) providing (180) an identification of a canonical gene name.

Abstract: A method for assessing risk associated with a request from an inquirer for allele frequency from a database of genetic data, comprising: (i) generating an allele database comprising allele frequency information and request frequency information for each of a plurality of alleles; (ii) generating an inquirer database comprising allele request information about a plurality of inquirers; (iii) receiving a request for genetic data from an inquirer, comprising a request for allele frequency for one or more alleles and an identifier of the inquirer; (iv) updating the request frequency information based on the received request; (v) updating the allele request information for the requesting inquirer; (vi) calculating an allele risk score; (vii) calculating an inquirer risk score; and (viii) assessing, based on the allele risk score and the inquirer risk score, a risk associated with the received request.

Abstract: A method (100) for generating a graph-based reference genome, comprising: (i) receiving (120) one or more older versions of a current reference genome, each comprising a plurality of nodes identifying the version of the reference genome and a location within that version for the respective node; (ii) aligning (130) each older version of the reference genome to the current reference genome to generate a graph-based reference genome, wherein the alignment is based on the location information; (iii) extracting (140), from a corpus of references, an allele and contextual information associated with the allele, wherein the respective reference identifies the version of the reference genome and a location of the allele within the version; and (iv) mapping (150) the allele and associated contextual information onto a node of the graph-based reference genome, based on the identified version of the reference genome and the location of the extracted allele within that version.

Abstract: The present disclosure pertains to a system, a method of using such a system, and a non-transitory computer-readable medium containing instructions to such a system for generating annotated gene fusion data from processing both a patient's DNA and RNA sequence information thereby filtering out weak candidate gene fusions. Thus the annotated gene fusion data contains clinically relevant information and accurate gene fusion detections (low false-positives) for use in clinical and/or R&D settings. The system, method and computer-readable medium allows a user to generate gene fusion data by detecting breakpoints from a patient's DNA-SEQ and RNA-SEQ, creating candidate breakpoint data by combining matching breakpoints from the DNA-SEQ and RNA-SEQ breakpoint data, determining confidence levels of the candidate breakpoint, identifying corresponding gene fusions, and annotating clinically relevant information about the gene fusions.

Abstract: The application discloses five polymorph forms B, P, F, J, O of (4-((R)-((2S,5R)-4-(3-fluorobenzyl)-(2,5-dimethylpiperazine-1-yl)(3-hydroxyphenyl)methyl)phenyl)(4-methylpiperidine-1-yl)methanone dihydrochloride, preparation methods thereof and application thereof in the manufacture of a medicament for preventing or treating a mood disorder or a disease related to a ? opioid receptor.

Abstract: A method (100) for recruiting a patient for a clinical trial, comprising: receiving (110) a dataset comprising information about one or more clinical trials each including patient eligibility criteria; extracting (120) the patient eligibility criteria from each of the clinical trials; converting (130) the patient eligibility criteria to a standardized patient eligibility criterion using a structured clinical trial mark-up language; storing (140) the patient eligibility criterion in a database (862), each of the criterion associated with one or more clinical trials; receiving (150) patient-specific data values about a patient; querying (160) the clinical trial eligibility criteria database using the patient-specific data values to identify eligibility criterion satisfied by the patient-specific data value; identifying (170) a clinical trial associated with the one or more standardized patient eligibility criterion satisfied by a received patient-specific data value; and providing (180) a report of the identifi

Abstract: A method and a system for interpreting data between two quantitative genomic datasets are described, wherein datasets are associated with the same disease or condition, for example, samples from the same patient obtained on different genomic platforms with varying data acquisition parameters. The data samples in each of the first and second datasets are rank ordered and the relative distances among the data samples are determined. The value ranks and relative distances are then used to correlate to data samples in the first and second quantitative genomic datasets, with the output provided to a user, such as a clinician or a patient.

Abstract: A system and method for providing a prioritized list of clinical trials that are relevant to a patient suffering from an illness or disease, such as cancer, are disclosed. Specifically, a method for conducting an automated, real time clinical trial search and a prioritization analysis is described. The method comprises the steps of conducting an automated full-text clinical trial search based on structuralization of clinical trial eligibility data and knowledge-based inference, initiating a query from the patient's side, and providing a prioritized list of all accessible clinical trials fulfilling a particular query. The system provides better sensitivity, precision and negative predictive value than the current most known clinical trial matching tool: clinicaltrials.gov.

Abstract: The application discloses five polymorph forms B, P, F, J, O of (4-((R)-((2S,5R)-4-(3-fluorobenzyl)-(2,5-dimethylpiperazine-1-yl)(3-hydroxyphenyl)methyl)phenyl)(4-methylpiperidine-1-yl)methanone dihydrochloride, preparation methods thereof and application thereof in the manufacture of a medicament for preventing or treating a mood disorder or a disease related to a ? opioid receptor.

Abstract: Methods, systems and apparatus for detecting subpopulations of constituents of at least one biological organism are disclosed. In accordance with exemplary embodiments, cluster partitions of biological data samples compiled from constituents of at least one biological organism are evaluated (114) by computing inconsistency scores for the partitions based on an inconsistency measure. In addition, for at least one of the plurality of partitions, a non-zero value is allocated to the inconsistency measure of at least one cluster that has only one biological data sample. Further, the subpopulations are identified by selecting the partition of having the minimum inconsistency score as the subpopulations.

Abstract: A method for assessing risk associated with a request from an inquirer for allele frequency from a database of genetic data, comprising: (i) generating an allele database comprising allele frequency information and request frequency information for each of a plurality of alleles; (ii) generating an inquirer database comprising allele request information about a plurality of inquirers; (iii) receiving a request for genetic data from an inquirer, comprising a request for allele frequency for one or more alleles and an identifier of the inquirer; (iv) updating the request frequency information based on the received request; (v) updating the allele request information for the requesting inquirer; (vi) calculating an allele risk score; (vii) calculating an inquirer risk score; and (viii) assessing, based on the allele risk score and the inquirer risk score, a risk associated with the received request.

Abstract: The present disclosure pertains to a system, a method of using such a system, and a non-transitory computer-readable medium containing instructions to such a system for generating annotated gene fusion data from processing both a patient's DNA and RNA sequence information thereby filtering out weak candidate gene fusions. Thus the annotated gene fusion data contains clinically relevant information and accurate gene fusion detections (low false-positives) for use in clinical and/or R&D settings. The system, method and computer-readable medium allows a user to generate gene fusion data by detecting breakpoints from a patient's DNA-SEQ and RNA-SEQ, creating candidate breakpoint data by combining matching breakpoints from the DNA-SEQ and RNA-SEQ breakpoint data, determining confidence levels of the candidate breakpoint, identifying corresponding gene fusions, and annotating clinically relevant information about the gene fusions.

Abstract: A data-driven integrative visualization system and a method for visualization and exploration of the multi-modal features of a cohort of samples, is disclosed Specifically, a method for providing an interactive computation and visualization front-end of a genomics platform for presenting the complex multiparametric and high dimensional, multi-omic data of a patient with respect to a cohort of samples, that assists the user in understanding the similarities and differences across individual or groups of samples, identify correlation among different features and improve treatment planning and long term patient care, is described. The method may include obtaining and inputting multi-omic data of a patient and/or cohorts, identifying multi-modal feature variations and their relationships, and displaying this information in an interactive circular format on a GUI, from which the user can access further information.

Abstract: A patient-trial matching system (100) includes a structuralizer (102) configured to convert input non-structured patient health data and input non-structured clinical trial eligibility criteria into structured patient health data and structured clinical trial eligibility criteria by organizing a content of the non-structured data as known data elements. The patient-trial matching system further includes a semantic matcher (122) configured to match the structured patient health data and the structured clinical trial eligibility criteria based on user input matching criteria and outputs matched results. The patient-trial matching system further includes a ranking engine (126) configured to rank the matched results using ranking criteria (128), which include ranking patients matched to a clinical trial of interest in response to matching to find a group of trial patients and ranking clinical trials matched to a particular patient in response to matching to find a clinical trial.

Abstract: Tissue matrices having anti-microbial properties are provided. In certain embodiments, the tissue matrices include cationic anti-microbial agents that form a stable bond with the tissue matrices without adversely affecting the biologic properties of the tissue matrices.