The human auditory system extracts meaning from the environment by transforming acoustic input signals into semantic categories. Specific acoustic features give rise to distinct categorical percepts, such as speech or music, and to spatially distinct preferential responses in the auditory cortex. These responses contain category-relevant information, yet their representational level and role within the acoustic-to-semantic transformation process remain unclear. We combined neuroimaging, a deep neural network, a brain-based sound synthesis, and psychophysics to identify the sound features that are internally represented in the speech- and music-selective human auditory cortex and test their functional role in sound categorization. We found that the synthetized sounds exhibit unnatural features distinct from those normally associated with speech and music, yet they elicit categorical cortical and behavioral responses resembling those of natural speech and music. Our findings provide new insights into the fundamental sound features underlying speech and music categorization in the human auditory cortex.

The objective was to identify innovative strategies that may increase recruitment and/or retention of groups less represented in chronic disease clinical research. A systematic review was conducted. Inclusion criteria were: (a) NIH-defined racial and ethnic minority groups and clinical research; (b) evidence-based, clinical research recruitment and/or retention strategies involving the leading causes of mortality and morbidity in the United States; (c) conducted in the United States; and (d) qualitative design. Data exploring the strategies were extracted and thematically analyzed. Twenty-seven studies were included. Studies focused on cancer (70%), recruitment (93%), and perspectives from clinicians (63%). The most referenced strategies were education (44%), communication (48%), and community-based participatory research (63%). Critical themes include empowerment, transparency, trust, and sustainability. Strategies must prioritize the community and be implemented sustainably, where cultural humility and community-based participatory research are foundational. Methods We adhered to and adapted the Enhancing Transparency in Reporting the Synthesis of Qualitative Research (ENTREQ) guidelines, Enhancing the Quality and Transparency of Health Research (EQUATOR) guidelines, and The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist to report this completed systematic review and meta-synthesis. Eligibility criteria Briefly, we included studies with qualitative or mixed methods research designs, were conducted in the U.S., published in English or Spanish in a peer-reviewed journal between 2009 and 2024, and that demonstrated evidence-based recruitment and/or retention strategies for clinical research focused on the leading causes of morbidity and mortality in the U.S. as determined by the Centers for Disease Control and Prevention (CDC). Studies spanning ten years from 2009 were initially selected; this was later updated to include fifteen years from 2009 to reflect the increasing significance and importance of this work during this period. Eligible studies targeted ethnic and racial minorities defined by the NIH. Studies included all ages and used the NIH definition of clinical research. Information sources and search strategy The literature search strategy was developed in collaboration with the review team and trained biomedical librarians (NT and AL) at the National Institutes of Health (NIH). The search strategy was created using a combination of text words and the controlled vocabulary terms in the following databases: (PubMed (MeSH) Medical Subject Headings, Embase - EMTREE, and CINAHL subject headings. The search was refined using an iterative process and finalized by the review team members and librarians. For each search strategy, the search terms included these text words and controlled vocabulary when available: underrepresented, minority, racial and ethnic groups, clinical research, and disparities. The following databases were searched: PubMed (National Library of Medicine), Embase (Elsevier), CINAHL Plus (Cumulative Index to Nursing and Allied Health Literature - EBSCOhost), and Web of Science Core Collection (Clarivate Analytics). The following limits were applied using the filters available in each database. The search was limited to human studies only and was limited to studies conducted in the United States. The final search strategy can be found in the S2 Appendix. Selection process Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia; www.covidence.org) imported studies and automatically excluded duplicates. All stages of the screening, data extraction, and quality assessment were independently conducted by members of the review team (CJP, JMG, AK, MW, LA, and JGG). The review team was composed of six members. The review team first screened titles and abstracts to identify studies that met the inclusion criteria. Next, the full texts of studies included during the title and abstract were screened using the same eligibility criteria. Each article was screened by two reviewers and conflicts between reviewers were resolved by consensus discussion with the review team. Data collection process & data items Data from each included study were collected by two reviewers using Covidence. The following outcomes of interest were extracted: focus on recruitment, retention, or both; and a description of the evidence-based strategies. We extracted data on study characteristics, including year of publication and condition of interest, including subtype for cancer. Additionally, we extracted characteristics including race and ethnicity, sex assigned at birth if applicable, geography (urban or rural), and role in clinical research (e.g., participant, clinician (i.e., medical or research staff), community leader, etc.). Study risk of bias assessment For the quality assessment, we evaluated the following domains: (a) role of the researcher; (b) sampling method; (c) data collection method; and (d) analysis method, which were identified as all criteria met or criteria partially met. We followed the adapted guidelines and conceptual domains of the Critical Appraisal Skills Programme (CASP) quality assessment tool to assess the quality of studies. Two reviewers assessed the risk of bias for each included study and resolved disagreements by consensus discussion with the review team. Synthesis methods A thematic synthesis was operationalized for the data analysis, where we analyzed the findings and developed inductive and deductive codes using qualitative synthesis methodologies and established guidelines. The thematic synthesis utilized an iterative process grounded in qualitative thematic analysis methodologies. We initially developed a deductive coding scheme, focusing on direct meaning and content that highlighted evidence-based strategies and direct quotations from study participants. The team discussed and created the codebook, and then each code was defined. Discrepancies or additional deductive codes were added and discussed by the team for consensus. Each study was coded independently by reviewers. Inductive codes were later added to describe high-level interpretation and themes. Both deductive and inductive codes existed in our codebook using this iterative process. Further analysis was conducted where strategies and themes were summarized into a conceptual model emphasizing key elements for the recruitment and retention of racial and ethnic groups historically underrepresented in clinical research.

Efficiency is a key organizing principle in modern natural product synthesis. Practical criteria include time, cost, and effort expended to synthesize the target, which tracks with step-count and scale. The execution of a natural product synthesis, that is, the sum and identity of each reaction employed therein, falls along a continuum of chemical (abiotic) synthesis on one extreme, followed by the hybrid chemoenzymatic approach, and ultimately biological (biosynthesis) on the other, acknowledging the first synthesis belongs to Nature. Starting materials also span a continuum of structural complexity approaching the target with constituent elements on one extreme, followed by petroleum-derived and “chiral pool” building blocks, and complex natural products (i.e., semisynthesis) on the other. Herein, we detail our approach toward realizing the first synthesis of (−)-melodinine K, a complex bis-indole alkaloid. The total syntheses of monomers (−)-tabersonine and (−)-16-methoxytabersonine employing our domino Michael/Mannich annulation is described. Isolation of (−)-tabersonine from Voacanga africana and strategic biotransformation with tabersonine 16-hydroxylase for site-specific C–H oxidation enabled a scalable route. The Polonovski–Potier reaction was employed in biomimetic fragment coupling. Subsequent manipulations delivered the target. We conclude with a discussion of efficiency in natural products synthesis and how chemical and biological technologies define the synthetic frontier.

We report a methodology using machine learning to capture chemical intuition from a set of (partially) failed attempts to synthesize a metal organic framework. We define chemical intuition as the collection of unwritten guidelines used by synthetic chemists to find the right synthesis conditions. As (partially) failed experiments usually remain unreported, we have reconstructed a typical track of failed experiments in a successful search for finding the optimal synthesis conditions that yields HKUST-1 with the highest surface area reported to date. We illustrate the importance of quantifying this chemical intuition for the synthesis of novel materials.

IntroductionFoundational to a well-functioning health system is a strong routine health information system (RHIS) that informs decisions and actions at all levels of the health system. In the context of decentralization across low- and middle-income countries, RHIS has the promise of supporting sub-national health staff to take data-informed actions to improve health system performance. However, there is wide variation in how “RHIS data use” is defined and measured in the literature, impeding the development and evaluation of interventions that effectively promote RHIS data use.MethodsAn integrative review methodology was used to: (1) synthesize the state of the literature on how RHIS data use in low- and middle-income countries is conceptualized and measured; (2) propose a refined RHIS data use framework and develop a common definition for RHIS data use; and (3) propose improved approaches to measure RHIS data use. Four electronic databases were searched for peer-reviewed articles published between 2009 and 2021 investigating RHIS data use.ResultsA total of 45 articles, including 24 articles measuring RHIS data use, met the inclusion criteria. Less than half of included articles (42%) explicitly defined RHIS data use. There were differences across the literature whether RHIS data tasks such as data analysis preceded or were a part of RHIS data use; there was broad consensus that data-informed decisions and actions were essential steps within the RHIS data use process. Based on the synthesis, the Performance of Routine Information System Management (PRISM) framework was refined to specify the steps of the RHIS data use process.ConclusionConceptualizing RHIS data use as a process that includes data-informed actions emphasizes the importance of actions in improving health system performance. Future studies and implementation strategies should be designed with consideration for the different support needs for each step of the RHIS data use process.

Data synthesis measurement summary.

Under the direction and funding of the National Cooperative Mapping Program with guidance and encouragement from the United States Geological Survey (USGS), a digital database of three-dimensional (3D) vector data, displayed as two-dimensional (2D) data-extent bounding polygons. This geodatabase is to act as a virtual and digital inventory of 3D structure contour and isopach vector data for the USGS National Geologic Synthesis (NGS) team. This data will be available visually through a USGS web application and can be queried using complimentary nonspatial tables associated with each data harboring polygon. This initial publication contains 60 datasets collected directly from USGS specific publications and federal repositories. Further publications of dataset collections in versioned releases will be annotated in additional appendices, respectfully. These datasets can be identified from their specific version through their nonspatial tables. This digital dataset contains spatial extents of the 2D geologic vector data as polygon features that are attributed with unique identifiers that link the spatial data to nonspatial tables that define the data sources used and describe various aspects of each published model. The nonspatial DataSources table includes full citation and URL address for both published model reports, any digital model data released as a separate publication, and input type of vector data, using several classification schemes. A tabular glossary defines terms used in the dataset. A tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and the accompanying nonspatial tables.

Logic synthesis is a challenging and widely-researched combinatorial optimization problem during integrated circuit (IC) design. It transforms a high-level description of hardware in a programming language like Verilog into an optimized digital circuit netlist, a network of interconnected Boolean logic gates, that implements the function. Spurred by the success of ML in solving combinatorial and graph problems in other domains, there is growing interest in the design of ML-guided logic synthesis tools. Yet, there are no standard datasets or prototypical learning tasks defined for this problem domain. Here, we describe OpenABC-D,a large-scale, labeled dataset produced by synthesizing open source designs with a leading open-source logic synthesis tool and illustrate its use in developing, evaluating and benchmarking ML-guided logic synthesis. OpenABC-D has intermediate and final outputs in the form of 870,000 And-Inverter-Graphs (AIGs) produced from 1500 synthesis runs plus labels such as the optimized node counts, and de-lay. We define a generic learning problem on this dataset and benchmark existing solutions for it. The codes related to dataset creation and benchmark models are available athttps://github.com/NYU-MLDA/OpenABC.git.

To cope with hypoxia, tumor cells have developed a number of adaptive mechanisms mediated by hypoxia-inducible factor 1 (HIF-1) to promote angiogenesis and cell survival. Due to significant roles of HIF-1 in the initiation, progression, metastasis, and resistance to treatment of most solid tumors, a considerable amount of effort has been made to identify HIF-1 inhibitors for treatment of cancer. Isolated from Saururus cernuus, manassantins A (1) and B (2) are potent inhibitors of HIF-1 activity. To define the structural requirements of manassantins for HIF-1 inhibition, we prepared and evaluated a series of manassantin analogues. Our SAR studies examined key regions of manassantin’s structure in order to understand the impact of these regions on biological activity and to define modifications that can lead to improved performance and drug-like properties. Our efforts identified several manassantin analogues with reduced structural complexity as potential lead compounds for further development. Analogues MA04, MA07, and MA11 down-regulated hypoxia-induced expression of the HIF-1α protein and reduced the levels of HIF-1 target genes, including cyclin-dependent kinase 6 (Cdk6) and vascular endothelial growth factor (VEGF). These findings provide an important framework to design potent and selective HIF-1α inhibitors, which is necessary to aid translation of manassantin-derived natural products to the clinic as novel therapeutics for cancers.

This digital GIS dataset and accompanying nonspatial files synthesize the model outputs from a regional-scale volumetric 3-D geologic model that portrays the generalized subsurface geology of western South Dakota from a wide variety of input data sources.The study area includes all of western South Dakota from west of the Missouri River to the Black Hills uplift and Wyoming border. The model data released here consist of the stratigraphic contact elevation of major Phanerozoic sedimentary units that broadly define the geometry of the subsurface, the elevation of Tertiary intrusive and Precambrian basement rocks, and point data representing the three-dimensional geometry of fault surfaces. the presence of folds and unconformities are implied by the 3D geometry of the stratigraphic units, but these are not included as discrete features in this data release. The 3D geologic model was constructed from a wide variety of publicly available surface and subsurface geologic data; none of these input data are part of this Data Release, but data sources are thoroughly documented such that a user could obtain these data from other sources if desired. This model was created as part of the U.S. Geological Survey’s (USGS) National Geologic Synthesis (NGS) project—a part of the National Cooperative Geologic Mapping Program (NCGMP). The WSouthDakota3D geodatabase contains twenty-five (25) subsurface horizons in raster format that represent the tops of modeled subsurface units, and a feature dataset “GeologicModel”. The GeologicModel feature dataset contains a feature class of thirty-five (35) faults served in elevation grid format (FaultPoints). The feature class “ModelBoundary” describes the footprint of the geologic model, and was included to meet the NCGMP’s GeMS data schema. Nonspatial tables define the data sources used (DataSources), define terms used in the dataset (Glossary), and provide a description of the modeled surfaces (DescriptionOfModelUnits). Separate file folders contain the vector data in shapefile format, the raster data in ASCII format, and the nonspatial tables as comma-separated values. In addition, a tabular data dictionary describes the entity and attribute information for all attributes of the geospatial data and the accompanying nonspatial tables (EntityAndAttributes). An included READ_ME file documents the process of manipulating and interpreting publicly available surface and subsurface geologic data to create the model. It additionally contains critical information about model units, and uncertainty regarding their ability to predict true ground conditions. Accompanying this data release is the “WSouthDakotaInputSummaryTable.csv”, which tabulates the global settings for each fault block, the stratigraphic horizons modeled in each fault block, the types and quantity of data inputs for each stratigraphic horizon, and then the settings associated with each data input.

IntroductionFoundational to a well-functioning health system is a strong routine health information system (RHIS) that informs decisions and actions at all levels of the health system. In the context of decentralization across low- and middle-income countries, RHIS has the promise of supporting sub-national health staff to take data-informed actions to improve health system performance. However, there is wide variation in how “RHIS data use” is defined and measured in the literature, impeding the development and evaluation of interventions that effectively promote RHIS data use.MethodsAn integrative review methodology was used to: (1) synthesize the state of the literature on how RHIS data use in low- and middle-income countries is conceptualized and measured; (2) propose a refined RHIS data use framework and develop a common definition for RHIS data use; and (3) propose improved approaches to measure RHIS data use. Four electronic databases were searched for peer-reviewed articles published between 2009 and 2021 investigating RHIS data use.ResultsA total of 45 articles, including 24 articles measuring RHIS data use, met the inclusion criteria. Less than half of included articles (42%) explicitly defined RHIS data use. There were differences across the literature whether RHIS data tasks such as data analysis preceded or were a part of RHIS data use; there was broad consensus that data-informed decisions and actions were essential steps within the RHIS data use process. Based on the synthesis, the Performance of Routine Information System Management (PRISM) framework was refined to specify the steps of the RHIS data use process.ConclusionConceptualizing RHIS data use as a process that includes data-informed actions emphasizes the importance of actions in improving health system performance. Future studies and implementation strategies should be designed with consideration for the different support needs for each step of the RHIS data use process.

Context

• We would like to have good open source speech recognition
• Commercial companies try to solve a hard problem: map arbitrary, open-ended speech to text and identify meaning
• The easier problem should be: detect a predefined sequence of sounds and map it to a predefined action.
• Lets tackle the simplest problem first: Classifying single, short words (commands)
• Audio training data is difficult to obtain.

Approaches

• The parent project (spoken verbs) created synthetic speech datasets using text-to-speech programs. The focus there is on single-syllable verbs (commands).
• The Speech Commands dataset (by Pete Warden, see the TensorFlow Speech Recognition Challenge) asked volunteers to pronounce a small set of words: (yes, no, up, down, left, right, on, off, stop, go, and 0-9).
• This data set provides synthetic counterparts to this real world dataset.

Open questions

One can use these two datasets in various ways. Here are some things I am interested in seeing answered:

1. What is it in an audio sample that makes it "sound similar"? Our ears can easily classify both synthetic and real speech, but for algorithms this is still hard. Extending the real dataset with the synthetic data yields a larger training sample and more diversity.
2. How well does an algorithm trained on one data set perform on the other? (transfer learning) If it works poorly, the algorithm probably has not found the key to audio similarity.
3. Are synthetic data sufficient for classifying real datasets? If this is the case, the implications are huge. You would not need to ask thousands of volunteers for hours of time. Instead, you could easily create arbitrary synthetic datasets for your target words.

A interesting challenge (idea for competition) would be to train on this data set and evaluate on the real dataset.

Synthetic data creation

Here I describe how the synthetic audio samples were created. Code is available at https://github.com/JohannesBuchner/spoken-command-recognition, in the "tensorflow-speech-words" folder.

1. The list of words is in "inputwords". "marvin" was changed to "marvel", because "marvin" does not have a pronounciation coding yet.
2. Pronounciations were taken from the British English Example Pronciation dictionary (BEEP, http://svr-www.eng.cam.ac.uk/comp.speech/Section1/Lexical/beep.html ). The phonemes were translated for the next step with a translation table (see compile.py for details). This creates the file "words". There are multiple pronounciations and stresses for each word.
3. A text-to-speech program (espeak) was used to pronounce these words (see generatetfspeech.sh for details). The pronounciation, stress, pitch, speed and speaker were varied. This gives >1000 clean examples for each word.
4. Noise samples were obtained. Noise samples (airport babble car exhibition restaurant street subway train) come from AURORA (https://www.ee.columbia.edu/~dpwe/sounds/noise/), and additional noise samples were synthetically created (ocean white brown pink). (see ../generatenoise.sh for details)
5. Noise and speech were mixed. The speech volume and offset were varied. The noise source, volume was also varied. See addnoise.py for details. addnoise2.py is the same, but with lower speech volume and higher noise volume. All audio files are one second (1s) long and are in wav format (16 bit, mono, 16000 Hz).
6. Finally, the data was compressed into an archive and uploaded to kaggle.

Acknowledgements

This work built upon

• Pronounciation dictionary: BEEP: http://svr-www.eng.cam.ac.uk/comp.speech/Section1/Lexical/beep.html
• Noise samples: AURORA: https://www.ee.columbia.edu/~dpwe/sounds/noise/
• eSPEAK: http://espeak.sourceforge.net/ and mbrola voices http://www.tcts.fpms.ac.be/synthesis/mbrola/mbrcopybin.html

Please provide appropriate citations to the above when using this work.

To cite the resulting dataset, you can use:

APA-style citation: "Buchner J. Synthetic Speech Commands: A public dataset for single-word speech recognition, 2017. Available from https://www.kaggle.com/jbuchner/synthetic-speech-commands-dataset/".

BibTeX @article{speechcommands, title={Synthetic Speech Commands: A public dataset for single-word speech recognition.}, author={Buchner, Johannes}, journal={Dataset available from https://www.kaggle.com/jbuchner/synthetic-speech-commands-dataset/}, year={2017} }

Thanks to everyone trying to improve open source voice detection and speech recognition.

Links

• https://www.kaggle.com/jbuchner/spokenverbs
• https://www.kaggle.com/c/tensorflow-speech-recognition-challenge
• https://github.com/JohannesBuchner/spoken-command-recognition/

Video abstractPurpose: Multimodal therapy is a frequent term in aphasia literature, but it has no agreed upon definition. Phrases such as “multimodal therapy” and “multimodal treatment” are applied to a range of aphasia interventions as if mutually understood, and yet, the interventions reported in the literature differ significantly in methodology, approach, and aims. This inconsistency can be problematic for researchers, policy makers, and clinicians accessing the literature and potentially compromises data synthesis and meta-analysis. A literature review was conducted to examine what types of aphasia treatment are labeled multimodal and determine whether any patterns are present.Method: A systematic search was conducted to identify literature pertaining to aphasia that included the term multimodal therapy (and variants). Sources included literature databases, dissertation databases, textbooks, professional association websites, and Google Scholar.Results: Thirty-three original review articles were identified, as well as another 31 sources referring to multimodal research, all of which used a variant of the term multimodal therapy. Treatments had heterogeneous aims, underlying theories, and methods. The rationale for using more than 1 modality was not always clear, nor was the reason each therapy was considered to be multimodal when similar treatments had not used the title. Treatments were noted to differ across 2 key features. The 1st was whether the ultimate aim of intervention was to improve total communication, as in augmentative and alternative communication approaches, or to improve 1 specific modality, as when gesture is used to improve word retrieval. The 2nd was the point in the treatment that the nonspeech modalities were employed.Discussion: Our review demonstrated that references to “multimodal” treatments represent very different therapies with little consistency. We propose a framework to define and categorize multimodal treatments, which is based both on our results and on current terminology in speech-language pathology.Supplemental Material S1. Secondary sources referring to multimodal treatments. Supplemental Material S2. Data extraction table for original research on "multimodal therapy."Pierce, J. E., O'Halloran, R., Togher, L., & Rose, M. L. (2019). What is meant by "multimodal therapy" for aphasia? American Journal of Speech-Language Pathology, 28, 706–716. https://doi.org/10.1044/2018_AJSLP-18-0157

A lack of selectivity of classical agonists for the nicotinic acetylcholine receptors (nAChR) has prompted us to identify and develop a distinct scaffold of α7 nAChR-selective ligands. Noncanonical 2,4,6-substituted pyrimidine analogues were framed around compound 40 for a structure–activity relationship study. The new lead compounds activate selectively the α7 nAChRs with EC50’s between 30 and 140 nM in a PNU-120596-dependent, cell-based calcium influx assay. After characterizing the expanded lead landscape, we ranked the compounds for rapid activation using Xenopus oocytes expressing human α7 nAChR with a two-electrode voltage clamp. This approach enabled us to define the molecular determinants governing rapid activation, agonist potency, and desensitization of α7 nAChRs after exposure to pyrimidine analogues, thereby distinguishing this subclass of noncanonical agonists from previously defined types of agonists (agonists, partial agonists, silent agonists, and ago-PAMs). By NMR, we analyzed pKa values for ionization of lead candidates, demonstrating distinctive modes of interaction for this landscape of ligands.

1. Applied ecological research is increasingly inspired by the Open Science movement. However, new challenges about how we define our science when biodiversity data is being shared and re-used are not solved. Among these challenges is the risk associated with blurring the distinction between research that mainly seeks to explore patterns with no a-priori articulated hypotheses (exploratory research), and research that explicitly tests a-priori formulated hypotheses (confirmatory research).

2. A rapid screening of a random selection of peer-reviewed articles suggests that neither experimental protocols nor hypothesis-testing sensu stricto are common in applied ecological research. In addition, most experiments are carried out on small spatial scales, which contrast with current global policy needs and research trends towards addressing large spatial and temporal scales. This latter trend make it unfeasible for policy to rely mainly on insights gained from experimental research.

3. To solve fundamental local, regional and global societal challenges, we need both exploratory and confirmatory research, and the fundamental (but different) role that hypothesis-testing and prediction play in applied ecological research should be revaluated.

4. A clearer distinction between exploratory and confirmatory research could be facilitated by allocating journal sections to different types of research; embracing new tools offered by the open science era, such as pre-registration of hypothesis; establishing new systems where post-hoc hypotheses emerging through exploration can also be registered for later testing; and more broad adoption of causal inference methods that foster more structured testing of hypotheses about causal mechanisms from observational biodiversity data.

5. Synthesis and applications. To gain the full benefits from the open science era, researchers, funding bodies and journal editors should explicitly consider incentives that encourage openness about methods and approaches, as well as value the full plurality of scientific approaches needed to address questions in conservation science.

Methods A full description of the dataset, including data collection and the procedures for random selection of papers to include, is given in Appendix 1 accompanying in the paper. There is also additional suppelementary information available at the OSF registration located at https://doi.org/10.17605/OSF.IO/W3S49.

IntroductionWomen at increased risk of developing pre-eclampsia are advised to take a daily low-dose of aspirin from 12 weeks of pregnancy to reduce their risks. Despite the well-established prophylactic effect of aspirin, adherence to this therapy is low. This systematic review aimed to summarise evidence on the barriers and facilitators of adherence to low-dose aspirin to inform intervention development to support decision making and persistence with aspirin use for pre-eclampsia prevention.Materials and methodsA systematic review and meta-synthesis of qualitative research was co-produced by representatives from charities, and public, clinical and academic members. Eight electronic databases (MEDLINE, PsycINFO, CINAHL, Web of Science, Scopus, EMBASE, Prospero, OpenGrey), archives of charities and professional organisations were searched (between October and November 2023 and re-run in August 2023) using predefined search terms. Studies containing qualitative components related to barriers and facilitators of adherence to low-dose aspirin during pregnancy were included. Quality assessment was performed using the Critical Appraisal Skills Programme checklist for qualitative research. A combination of the COM-B framework with phases of adherence process as defined by international taxonomy was used as the coding framework. Co-production activities were facilitated by use of ‘Zoom’ and ‘Linoit’.ResultsFrom a total of 3377 papers identified through our searches, five published studies and one dissertation met our inclusion criteria. Studies were published from 2019 to 2022 covering research conducted in the USA, Canada, UK, Netherlands and Australia. Barriers and facilitators to adherence were mapped to six categories of the COM-B for three phases of adherence: initiation, implementation, and discontinuation. The discontinuation phase of adherence was only mentioned by one author. Four key themes were identified relating to pregnancy: ‘Insufficient knowledge’, ‘Necessity concerns balance’, ‘Access to medicine’, ‘Social influences’, and ‘Lack of Habit’.ConclusionsThe COM-B framework allowed for detailed mapping of key factors shaping different phases of adherence in behavioural change terms and now provides a solid foundation for the development of a behavioural intervention. Although potential intervention elements could be suggested based on the results of this synthesis, additional co-production work is needed to define elements and plan for the delivery of the future intervention.Trial registrationPROSPERO CRD42022359718. https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022359718.

Previous work has shown a strong correlation between zeolite framework flexibility and the nature of structural symmetry and phase transitions. However, there is little experimental data regarding this relationship, in addition to how flexibility can be connected to the synthesis of these open framework materials. This is of interest for the synthesis of novel zeolites, which require organic additives to permutate the resulting geometry and symmetry of the framework. Here, we have used high pressure powder X-ray diffraction to study the three zeolites: Na-X, RHO and ZK-5, which can all be prepared using 18-crown-6 ether as an organic additive. We observe significant differences in how the occluded 18-crown-6 ether influences the framework flexibility – this being dependant on the geometry of the framework. We use these differences as an indicator to define the role of 18-crown-6 ether during zeolite crystallisation. Furthermore, in conjunction with previous work we predict that pressure-induced symmetry transitions are intrinsic to body-centred cubic zeolites. The high symmetry yields fewer degrees of freedom, meaning it is energetically favourable to lower the symmetry to facilitate further compression.

Early assessment of infectious disease outbreaks is key to implementing timely and effective control measures. In particular, rapidly recognising whether infected individuals stem from a single outbreak sustained by local transmission, or from repeated introductions, is crucial to adopt effective interventions. In this study, we introduce a new framework for combining several data streams, e.g. temporal, spatial and genetic data, to identify clusters of related cases of an infectious disease. Our method explicitly accounts for underreporting, and allows incorporating preexisting information about the disease, such as its serial interval, spatial kernel, and mutation rate. We define, for each data stream, a graph connecting all cases, with edges weighted by the corresponding pairwise distance between cases. Each graph is then pruned by removing distances greater than a given cutoff, defined based on preexisting information on the disease and assumptions on the reporting rate. The pruned graphs corresponding to different data streams are then merged by intersection to combine all data types; connected components define clusters of cases related for all types of data. Estimates of the reproduction number (the average number of secondary cases infected by an infectious individual in a large population), and the rate of importation of the disease into the population, are also derived. We test our approach on simulated data and illustrate it using data on dog rabies in Central African Republic. We show that the outbreak clusters identified using our method are consistent with structures previously identified by more complex, computationally intensive approaches.

Macrocyclic peptides are considered large enough to inhibit “undruggable” targets, but the design of passively cell-permeable molecules in this space remains a challenge due to the poorly understood role of molecular size on passive membrane permeability. Using split-pool combinatorial synthesis, we constructed a library of cyclic, per-N-methlyated peptides spanning a wide range of calculated lipohilicities (0 < AlogP < 8) and molecular weights (∼800 Da < MW < ∼1200 Da). Analysis by the parallel artificial membrane permeability assay revealed a steep drop-off in apparent passive permeability with increasing size in stark disagreement with current permeation models. This observation, corroborated by a set of natural products, helps define criteria for achieving permeability in larger molecular size regimes and suggests an operational cutoff, beyond which passive permeability is constrained by a sharply increasing penalty on membrane permeation.

In this study, the hydrogel formulations based on polysaccharide sodium alginate were investigated for further development of intercalated nanocomposite hydrogels, for purposes of future applications in the areas of health as a carrier in drug delivery systems. Thus, the objective of the work dealt with in the optimization of hydrogels synthesis and obtaining nanostructured hydrogels with clay in an intercalated conformation. The optimization of the hydrogel synthesis was successful, and it is possible to define the materials and / or solutions to be used and concentrations of these solutions to the best formulations of hydrogels. The choice of the concentration of the polysaccharide, the type of crosslinking agent and nanofiller to continued development work, it was determined following criteria as the degree of swelling, and in some cases the physical properties, contributed to determine the best hydrogels. The development of intercalated nanocomposites hydrogel beads was confirmed by the X-ray diffraction technique, which thus could be used to observe evidence of effective incorporation or intercalation of the nanoclay in the hydrogel matrix.