GaSI: A Wide-Gap Non-centrosymmetric Helical Crystal.

The complex non-centrosymmetric and chiral nature of helical structures endow materials that possess such motifs with unusual properties. However, despite their ubiquity in biological and organic systems, there is a severe lack of inorganic crystals that display helicity in extended lattices, where these unusual properties are expected to be most pronounced. Here, we report a new inorganic helical structure, gallium sulfur iodide (GaSI), within the exfoliable class of III-VI-VII (1:1:1) one-dimensional (1D) van der Waals (vdW) crystals. Through detailed structural analyses, including single-crystal X-ray diffraction, electron microscopy, and density functional theory (DFT), we elucidate the apparent noncrystallographic screw axis and the first example of an atomic scale helical structure bearing a "squircular" cross-section in GaSI. Crystallizing in the non-centrosymmetric P4̅ space group, we found that GaSI crystals exhibit pronounced second-harmonic generation. From diffuse reflectance spectroscopy, GaSI displays a sizeable bandgap of 3.69 eV, owing tostrong covalent interactions arising from the smaller sulfur atoms within the helix core. These results position GaSI as a promising exfoliable nonlinear optical material across a broad optical window.

Encapsulation of crystalline and amorphous Sb2S3 within carbon and boron nitride nanotubes.

The recent rediscovery of 1D and quasi-1D (q-1D) van der Waals (vdW) crystals has laid foundation for the realization of emergent electronic, optical, and quantum-confined physical phenomena in both bulk and at the nanoscale. Of these, the highly anisotropic q-1D vdW crystal structure and the visible-light optical/optoelectronic properties of antimony trisulfide (Sb2S3) have led to its widespread consideration as a promising building block for photovoltaic and non-volatile phase change devices. However, while these applications will greatly benefit from well-defined and sub-nanometer-thick q-1D structures, little has been known about feasible synthetic routes that can access single covalent chains of Sb2S3. In this work, we explore how encapsulation in single or multi-walled carbon nanotubes (SWCNTs or MWCNTs) and visible-range transparent boron nitride nanotubes (BNNTs) influences the growth and phase of Sb2S3 nanostructures. We demonstrate that nanotubes with smaller diameters had a more pronounced effect in the crystallographic growth direction and orientation of Sb2S3 nanostructures, promoting the crystallization of the guest structures along the long-axis [010]-direction. As such, we were able to reliably access well-ordered few to single covalent chains of Sb2S3 when synthesized within defect-free SWCNTs with sub-2 nm inner diameters. Intriguingly, we found that the degree of crystalline order of Sb2S3 nanostructures was strongly influenced by the presence of defects and discontinuities along the Sb2S3-nanotube interface. We show that amorphous nanowire domains of Sb2S3 form around defect sites in larger, multi-walled nanotubes that manifest inner wall defects and discontinuities, suggesting a means to manipulate the crystallization dynamics of confined sub-10 nm-thick Sb2S3 nanostructures within nanotubes. Lastly, we show that ultranarrow amorphous Sb2S3 can impart functionality onto isolable BNNTs with photocurrent generation in the pA range which, alongside the dispersibility of the Sb2S3@BNNTs, could be leveraged to easily fabricate photoresistors only a few nm in width. Altogether, our results serve to solidify the understanding of how q-1D vdW pnictogen chalcogenides crystallize within confined synthetic platforms and are a step towards realizing functional materials from ensembles of encapsulated heterostructures.

A Randomised Phase II Trial of Hippocampal Sparing Versus Conventional Whole Brain Radiotherapy After Surgical Resection or Radiosurgery in Favourable Prognosis Patients With 1-10 Brain Metastases.

AIMS: To assess in patients with 1-10 brain metastases, each of which has been treated by neurosurgery or stereotactic radiosurgery, whether hippocampal sparing whole brain radiotherapy (HS-WBRT) better spares neurocognitive function (NCF) than standard WBRT. Further, to assess whether a phase III randomised trial of HS-WBRT would be feasible in the UK. MATERIALS AND METHODS: A multicentre, randomised, open label phase II trial was undertaken, randomising patients to 30Gy in 10 fractions of WBRT or HS-WBRT. The primary endpoint was decline in Total recall using Hopkins Verbal Learning Test Revised (HVLT-R) at 4 months post treatment. To assess this, we aimed to recruit 84 patients over 3 years. Secondary endpoints included further measures of NCF, quality of life, duration of functional independence, local control of treated metastases, development of new metastases, disease control within the hippocampal regions, overall survival, steroid and antiepileptic medication requirements, and toxicity. RESULTS: The trial closed prematurely due to slower than anticipated recruitment. From April 2016 to January 2018, 23 patients were randomised. Follow up was a median of 25 months. Fifteen patients (6 WBRT, 9 HS-WBRT) were assessed for the primary endpoint; of these, 1 in each arm experienced significant decline in the 4-month HVLT-R Total recall score (p = 0.8). Patients in the HS-WBRT arm experienced less insomnia (p < 0.01) and drowsiness (p < 0.01). There were no differences in other secondary endpoints. CONCLUSION: A phase III randomised trial of HS-WBRT was shown not to be feasible at this time in the UK. As most randomised trials of HS-WBRT reported to date share common endpoints, including NCF, an individual patient data meta-analysis should be undertaken.

SlowMoMan: a web app for discovery of important features along user-drawn trajectories in 2D embeddings.

Motivation: Nonlinear low-dimensional embeddings allow humans to visualize high-dimensional data, as is often seen in bioinformatics, where datasets may have tens of thousands of dimensions. However, relating the axes of a nonlinear embedding to the original dimensions is a nontrivial problem. In particular, humans may identify patterns or interesting subsections in the embedding, but cannot easily identify what those patterns correspond to in the original data. Results: Thus, we present SlowMoMan (SLOW Motions on MANifolds), a web application which allows the user to draw a one-dimensional path onto a 2D embedding. Then, by back-projecting the manifold to the original, high-dimensional space, we sort the original features such that those most discriminative along the manifold are ranked highly. We show a number of pertinent use cases for our tool, including trajectory inference, spatial transcriptomics, and automatic cell classification. Availability and implementation: Software: https://yunwilliamyu.github.io/SlowMoMan/; Code: https://github.com/yunwilliamyu/SlowMoMan.

Lattice-guided assembly of optoelectronically active π-conjugated peptides on 1D van der Waals single crystals.

The deployment of organic molecules in high-performance devices strongly relies on the formation of well-ordered domains, which is often complicated by the dynamic and sensitive nature of supramolecular interactions. Here, we engineered the assembly of water-processable, optoelectronic π-conjugated peptides into well-defined organic-inorganic heterointerfaced assemblies by leveraging the long-range anisotropic ordering of 1D van der Waals (vdW) crystals composed of subnanometer-thick transition metal sulfide chains (MS3; M = Nb, Ta) as assembly templates. We found that the monomers can readily form 1D supramolecular assemblies onto the underlying crystal surface, owing to the structural correspondence between the π-π interactions of the quaterthiophene (4T)-based peptide units (DDD-4T) and sulfur atom ordering along the NbS3 (100) surface. The heterointerfaced assemblies exhibited substantially red-shifted photoluminescence and enhanced visible-range photocurrent generation compared to solution-assembled films. Our results underscore the role of lattice matching in forming ordered supramolecular assemblies, offering an emergent approach to assembling organic building blocks endowed with improved physical properties.

Functionalization and Structural Evolution of Conducting Quasi-One-Dimensional Chevrel-Type Telluride Nanocrystals.

Interfacing organic molecular groups with well-defined inorganic lattices, especially in low dimensions, enables synthetic routes for the rational manipulation of both their local or extended lattice structures and physical properties. While appreciably studied in two-dimensional systems, the influence of surface organic substituents on many known and emergent one-dimensional (1D) and quasi-1D (q-1D) crystals has remained underexplored. Herein, we demonstrate the surface functionalization of bulk and nanoscale Chevrel-like q-1D ionic crystals using In2Mo6Te6, a predicted q-1D Dirac semimetal, as the model phase. Using a series of alkyl ammonium (-NR4+; R = H, methyl, ethyl, butyl, and octyl) substituents with varying chain lengths, we demonstrate the systematic expansion of the intrachain c-axis direction and the contraction of the interchain a/b-axis direction with longer chain substituents. Additionally, we demonstrate the systematic expansion of the intrachain c-axis direction and the contraction of the interchain a/b-axis direction as the alkyl chain substituents become longer using a combination of powder X-ray diffraction and Raman experiments. Beyond the structural modulation that the substituted groups can impose on the lattice, we also found that the substitution of ammonium-based groups on the surface of the nanocrystals resulted in selective suspension in aqueous (NH4+-functionalized) or organic solvents (NOc4+-functionalized), imparted fluorescent character (Rhodamine B-functionalized), and modulated the electrical conductivity of the nanocrystal ensemble. Altogether, our results underscore the potential of organic-inorganic interfacing strategies to tune the structural and physical properties of rediscovered Chevrel-type q-1D ionic solids and open opportunities for the development of surface-addressable building blocks for hybrid electronic and optoelectronic devices at the nanoscale.

Sensitive Thermochromic Behavior of InSeI, a Highly Anisotropic and Tubular 1D van der Waals Crystal.

Thermochromism, the change in color of a material with temperature, is the fundamental basis of optical thermometry. A longstanding challenge in realizing sensitive optical thermometers for widespread use is identifying materials with pronounced thermometric optical performance in the visible range. Herein, it is demonstrated that single crystals of indium selenium iodide (InSeI), a 1D van der Waals (vdW) solid consisting of weakly bound helical chains, exhibit considerable visible range thermochromism. A strong temperature-dependent optical band edge absorption shift ranging from 450 to 530 nm (2.8 to 2.3 eV) over a 380 K temperature range with an experimental (dEg/dT)max value extracted to be 1.26 × 10-3 eV K-1 is shown. This value lies appreciably above most dense conventional semiconductors in the visible range and is comparable to soft lattice solids. The authors further seek to understand the origin of this unusually sensitive thermochromic behavior and find that it arises from strong electron-phonon interactions and anharmonic phonons that significantly broaden band edges and lower the Eg with increasing temperature. The identification of structural signatures resulting in sensitive thermochromism in 1D vdW crystals opens avenues in discovering low-dimensional solids with strong temperature-dependent optical responses across broad spectral windows, dimensionalities, and size regimes.

Acute, but not repeated, cocaine exposure alters allopregnanolone levels in the midbrain of male and female rats.

RATIONALE: Multiple psychiatric disorders are associated with altered brain and serum levels of neuroactive steroids, including the endogenous GABAergic steroid, allopregnanolone. Clinically, chronic cocaine use was correlated with decreased levels of pregnenolone. Preclinically, the effect of acute cocaine on allopregnanolone levels in rodents has had mixed results, showing an increase or no change in allopregnanolone levels in some brain regions. OBJECTIVE: We hypothesized that cocaine acutely increases allopregnanolone levels, but repeated cocaine exposure decreases allopregnanolone levels compared to controls. METHODS: We performed two separate studies to determine how systemic administration of 15 mg/kg cocaine (1) acutely or (2) chronically alters brain (olfactory bulb, frontal cortex, dorsal striatum, and midbrain) and serum allopregnanolone levels in adult male and female Sprague-Dawley rats. RESULTS: Cocaine acutely increased allopregnanolone levels in the midbrain, but not in olfactory bulb, frontal cortex, or dorsal striatum. Repeated cocaine did not persistently (24 h later) alter allopregnanolone levels in any region in either sex. However, allopregnanolone levels varied by sex across brain regions. In the acute study, we found that females had significantly higher allopregnanolone levels in serum and olfactory bulb relative to males. In the repeated cocaine study, females had significantly higher allopregnanolone levels in olfactory bulb, frontal cortex, and serum. Finally, acute cocaine increased allopregnanolone levels in the frontal cortex of females in proestrus, relative to non-proestrus stages. CONCLUSION: Collectively these results suggest that allopregnanolone levels vary across brain regions and by sex, which may play a part in differential responses to cocaine by sex.

Single Quasi-1D Chains of Sb2Se3 Encapsulated within Carbon Nanotubes.

The realization of stable monolayers from 2D van der Waals (vdW) solids has fueled the search for exfoliable crystals with even lower dimensionalities. To this end, 1D and quasi-1D (q-1D) vdW crystals comprising weakly bound subnanometer-thick chains have been discovered and demonstrated to exhibit nascent physics in the bulk. Although established micromechanical and liquid-phase exfoliation methods have been applied to access single isolated chains from bulk crystals, interchain vdW interactions with nonequivalent strengths have greatly hindered the ability to achieve uniform single isolated chains. Here, we report that encapsulation of the model q-1D vdW crystal, Sb2Se3, within single-walled carbon nanotubes (CNTs) circumvents the relatively stronger c-axis vdW interactions between the chains and allows for the isolation of single chains with structural integrity. High-resolution transmission electron microscopy and selected area electron diffraction studies of the Sb2Se3@CNT heterostructure revealed that the structure of the [Sb4Se6]n chain is preserved, enabling us to systematically probe the size-dependent properties of Sb2Se3 from the bulk down to a single chain. We show that ensembles of the [Sb4Se6]n chains within CNTs display Raman confinement effects and an emergent band-like absorption onset around 600 nm, suggesting a strong blue shift of the near-infrared band gap of Sb2Se3 into the visible range upon encapsulation. First-principles density functional theory calculations further provided qualitative insight into the structures and interactions that could manifest in the Sb2Se3@CNT heterostructure. Spatial visualization of the calculated electron density difference map of the heterostructure indicated a minimal degree of electron donation from the host CNT to the guest [Sb4Se6]n chain. Altogether, this model system demonstrates that 1D and q-1D vdW crystals with strongly anisotropic vdW interactions can be precisely studied by encapsulation within CNTs with suitable diameters, thereby opening opportunities in understanding dimension-dependent properties of a plethora of emergent vdW solids at or approaching the subnanometer regime.

An analysis of iris pattern as a risk factor for skin cancer development in immunosuppressed renal transplant recipients.

INTRODUCTION: Renal transplant recipients are at increased risk of keratinocyte skin cancers with a tendency to have multiple, aggressive and difficult to treat tumours. The eye and the skin share the same embryological ectoderm. Iris pattern has recently been reported as a predictive risk factor for skin cancer in non-immunosuppressed Southern European (Grigore et al., J Eur Acad Dermatol Venereol, 2018, 1662) and Irish populations (Ridge et al., J Eur Acad Dermatol Venereol, 2022, e542). AIMS: To analyse if an individual's iris pattern is an independent risk factor for the development of keratinocyte skin cancers in renal transplant recipients. METHODS: Iris patterns of 110 renal transplant recipients were evaluated using the Simionescu visual three-step technique (iris periphery, colarette and iris freckling [Simionescu et al., Ann Res Rev Biol, 2014, 2525]). Established risk factors for skin cancer in transplant patients were recorded as confounding factors. RESULTS: Observational cross-sectional study including 110 renal transplant population. Thirty-one participants had skin cancer. In the skin cancer group, iris periphery was blue/grey in 74.3% (p = 0.053, OR 2.5), the colarette was light brown in 57.1% (p < 0.0043) and iris freckles were present in 55%(p = 0.044). Dark brown and blue colarettes were observed in controls. Binary Logistic Regression analysis showed light brown colarette is a significant independent risk factor for skin cancer (OR 4.54, p < 0.02, CI 1.56-10.57). CONCLUSION: Within this renal transplant population a blue iris periphery, light brown colarette and presence of freckling confers an independent risk for keratinocyte skin cancer. Iris pattern is a useful tool for identification of transplant patients at risk of keratinocyte skin cancer and an easy-to-use technique for risk evaluation in this cohort. This is the first study looking at iris pattern and keratinocyte skin cancer risk in renal transplant population.

Comparative assessment of radiation therapy-induced vasculitis using [18F]FDG-PET/CT in patients with non-small cell lung cancer treated with proton versus photon radiotherapy.

PURPOSE: To assess radiation therapy (RT)-induced vasculitis in patients with non-small cell lung cancer (NSCLC) by examining changes in the uptake of 18F-fluoro-D-deoxyglucose ([18F]FDG) by positron emission tomography/computed tomography (PET/CT) images of the ascending aorta (AA), descending aorta (DA), and aortic arch (AoA) before and after proton and photon RT. METHOD: Thirty-five consecutive locally advanced NSCLC patients were definitively treated with proton (n = 27) or photon (n = 8) RT and concurrent chemotherapy. The patients were prospectively enrolled to undergo [18F]FDG-PET/CT imaging before and 3 months after RT. An adaptive contrast-oriented thresholding algorithm was applied to generate mean standardized uptake values (SUVmean) for regions of interest (ROIs) 3 mm outside and 3 mm inside the outer perimeter of the AA, DA, and AoA. These ROIs were employed to exclusively select the aortic wall and remove the influence of blood pool activity. SUVmeans before and after RT were compared using two-tailed paired t-tests. RESULTS: RT treatments were associated with increased SUVmeans in the AA, DA, and AoA-1.9%, 0.3%, and 1.3% for proton and 15.8%, 9.5%, and 15.5% for photon, respectively. There was a statistically significant difference in the ∆SUVmean (post-RT SUVmean - pre-RT SUVmean) in patients treated with photon RT when compared to ∆SUVmean in patients treated with proton RT in the AA (p = 0.043) and AoA (p = 0.015). There was an average increase in SUVmean that was related to dose for photon patients (across structures), but that was not seen for proton patients, although the increase was not statistically significant. CONCLUSION: Our results suggest that patients treated with photon RT for NSCLC may exhibit significantly more RT-induced inflammation (measured as ∆SUVmean) in the AA and AoA when compared to patients who received proton RT. Knowledge gained from further analyses in larger cohorts could aid in treatment planning and help prevent the significant morbidity and mortality associated with RT-induced vascular complications. TRIAL REGISTRATION: NCT02135679.

The power of partnership: Exploring collaboration dynamics in U.S. transplant research.

INTRODUCTION: Collaboration is one of the hallmarks of academic research. This study analyzes collaboration patterns in U.S. transplant research, examining publication trends, productive institutions, co-authorship networks, and citation patterns in high-impact transplant journals. METHODS: 4,265 articles published between 2012 and 2021 were analyzed using scientometric tools, logistic regression, VantagePoint software, and Gephi software for network visualization. RESULTS: 16,003 authors from 1,011 institutions and 59 countries were identified, with Harvard, Johns Hopkins, and University of Pennsylvania contributing the most papers. Odds of international collaboration significantly increased over time (OR 1.03; p â€‹= â€‹0.040), while odds of citation in single-institution collaborations decreased (OR 0.99; p â€‹= â€‹0.016). Five major scientific communities and central institutions (Harvard University and University of Pittsburgh) connecting them were identified, revealing interconnected research clusters. CONCLUSIONS: Collaboration enhances knowledge exchange and research productivity, with an increasing trend of institutional and international collaboration in U.S. transplant research. Understanding this community is essential for promoting research impact and forming strategic partnerships.

Improving integrated depression and non-communicable disease care in Malawi through engaged leadership and supportive implementation climate.

BACKGROUND: Low- and middle-income countries often lack access to mental health services, leading to calls for integration within other primary care systems. In sub-Saharan Africa, integration of depression treatment in non-communicable disease (NCD) settings is feasible, acceptable, and effective. However, leadership and implementation climate challenges often hinder effective integration and quality of services. The aim of this study was to identify discrete leadership strategies that facilitate overcoming barriers to the integration of depression care in NCD clinics in Malawi and to understand how clinic leadership shapes the implementation climate. METHODS: We conducted 39 in-depth interviews with the District Medical Officer, the NCD coordinator, one NCD provider, and the research assistant from each of the ten Malawian NCD clinics (note one District Medical Officer served two clinics). Based on semi-structured interview guides, participants were asked their perspectives on the impact of leadership and implementation climate on overcoming barriers to integrating depression care into existing NCD services. Thematic analysis used both inductive and deductive approaches to identify emerging themes and compare among participant type. RESULTS: The results revealed how engaged leadership can fuel a positive implementation climate where clinics had heightened capacity to overcome implementation barriers. Effective leaders were approachable and engaged in daily operations of the clinic and problem-solving. They held direct involvement with and mentorship during the intervention, providing assistance in patient screening and consultation with treatment plans. Different levels of leadership utilized their respective standings and power dynamics to influence provider attitudes and perceptions surrounding the intervention. Leaders acted by informing providers about the intervention source and educating them on the importance of mental healthcare, as it was often undervalued. Lastly, they prioritized teamwork and collective ownership for the intervention, increasing provider responsibility. CONCLUSION: Training that prioritizes leadership visibility and open communication will facilitate ongoing Malawi Ministry of Health efforts to scale up evidence-based depression treatment within NCD clinics. This proves useful where extensive and external monitoring may be limited. Ultimately, these results can inform successful strategies to close implementation gaps to achieve integration of mental health services in low-resource settings through improved leadership and implementation climate. TRIAL REGISTRATION: These findings are reported from ClinicalTrials.gov, NCT03711786. Registered on 18/10/2018. https://clinicaltrials.gov/ct2/show/NCT03711786 .

Structure and function analysis of a type III preQ1-I riboswitch from Escherichia coli reveals direct metabolite sensing by the Shine-Dalgarno sequence.

Riboswitches are small noncoding RNAs found primarily in the 5' leader regions of bacterial messenger RNAs where they regulate expression of downstream genes in response to binding one or more cellular metabolites. Such noncoding RNAs are often regulated at the translation level, which is thought to be mediated by the accessibility of the Shine-Dalgarno sequence (SDS) ribosome-binding site. Three classes (I-III) of prequeuosine1 (preQ1)-sensing riboswitches are known that control translation. Class I is divided into three subtypes (types I-III) that have diverse mechanisms of sensing preQ1, which is involved in queuosine biosynthesis. To provide insight into translation control, we determined a 2.30 Å-resolution cocrystal structure of a class I type III preQ1-sensing riboswitch identified in Escherichia coli (Eco) by bioinformatic searches. The Eco riboswitch structure differs from previous preQ1 riboswitch structures because it has the smallest naturally occurring aptamer and the SDS directly contacts the preQ1 metabolite. We validated structural observations using surface plasmon resonance and in vivo gene-expression assays, which showed strong switching in live E. coli. Our results demonstrate that the Eco riboswitch is relatively sensitive to mutations that disrupt noncanonical interactions that form the pseudoknot. In contrast to type II preQ1 riboswitches, a kinetic analysis showed that the type III Eco riboswitch strongly prefers preQ1 over the chemically similar metabolic precursor preQ0. Our results reveal the importance of noncanonical interactions in riboswitch-driven gene regulation and the versatility of the class I preQ1 riboswitch pseudoknot as a metabolite-sensing platform that supports SDS sequestration.

A broadly applicable approach to enrich electronic-health-record cohorts by identifying patients with complete data: a multisite evaluation.

OBJECTIVE: Patients who receive most care within a single healthcare system (colloquially called a "loyalty cohort" since they typically return to the same providers) have mostly complete data within that organization's electronic health record (EHR). Loyalty cohorts have low data missingness, which can unintentionally bias research results. Using proxies of routine care and healthcare utilization metrics, we compute a per-patient score that identifies a loyalty cohort. MATERIALS AND METHODS: We implemented a computable program for the widely adopted i2b2 platform that identifies loyalty cohorts in EHRs based on a machine-learning model, which was previously validated using linked claims data. We developed a novel validation approach, which tests, using only EHR data, whether patients returned to the same healthcare system after the training period. We evaluated these tools at 3 institutions using data from 2017 to 2019. RESULTS: Loyalty cohort calculations to identify patients who returned during a 1-year follow-up yielded a mean area under the receiver operating characteristic curve of 0.77 using the original model and 0.80 after calibrating the model at individual sites. Factors such as multiple medications or visits contributed significantly at all sites. Screening tests' contributions (eg, colonoscopy) varied across sites, likely due to coding and population differences. DISCUSSION: This open-source implementation of a "loyalty score" algorithm had good predictive power. Enriching research cohorts by utilizing these low-missingness patients is a way to obtain the data completeness necessary for accurate causal analysis. CONCLUSION: i2b2 sites can use this approach to select cohorts with mostly complete EHR data.

Anatomical structures, cell types, and biomarkers of the healthy human blood vasculature.

More than 150 scientists from 17 consortia are collaborating on an international project to build a Human Reference Atlas, which maps all 37 trillion cells in the healthy adult human body. The initial release of this atlas provided hierarchical lists of the anatomical structures, cell types, and biomarkers in 11 organs. Here, we describe the methods we used as part of this initiative to build the first open, computer-readable, and comprehensive database of the adult human blood vasculature, called the Human Reference Atlas-Vasculature Common Coordinate Framework (HRA-VCCF). It includes 993 vessels and their branching connections, 10 cell types, and 10 biomarkers. With this paper we are releasing additional details on vessel types and subtypes, branching sequence, anastomoses, portal systems, microvasculature, functional tissue units, mappings to regions vessels supply or drain, geometric properties of vessels, and links to 3D reference objects. Future versions will add variants and connections to the lymph vasculature; and, it will iteratively expand and improve the database as additional experimental data become available through the participating consortia.

RNA target highlights in CASP15: Evaluation of predicted models by structure providers.

The first RNA category of the Critical Assessment of Techniques for Structure Prediction competition was only made possible because of the scientists who provided experimental structures to challenge the predictors. In this article, these scientists offer a unique and valuable analysis of both the successes and areas for improvement in the predicted models. All 10 RNA-only targets yielded predictions topologically similar to experimentally determined structures. For one target, experimentalists were able to phase their x-ray diffraction data by molecular replacement, showing a potential application of structure predictions for RNA structural biologists. Recommended areas for improvement include: enhancing the accuracy in local interaction predictions and increased consideration of the experimental conditions such as multimerization, structure determination method, and time along folding pathways. The prediction of RNA-protein complexes remains the most significant challenge. Finally, given the intrinsic flexibility of many RNAs, we propose the consideration of ensemble models.

Generate Analysis-Ready Data for Real-world Evidence: Tutorial for Harnessing Electronic Health Records With Advanced Informatic Technologies.

Although randomized controlled trials (RCTs) are the gold standard for establishing the efficacy and safety of a medical treatment, real-world evidence (RWE) generated from real-world data has been vital in postapproval monitoring and is being promoted for the regulatory process of experimental therapies. An emerging source of real-world data is electronic health records (EHRs), which contain detailed information on patient care in both structured (eg, diagnosis codes) and unstructured (eg, clinical notes and images) forms. Despite the granularity of the data available in EHRs, the critical variables required to reliably assess the relationship between a treatment and clinical outcome are challenging to extract. To address this fundamental challenge and accelerate the reliable use of EHRs for RWE, we introduce an integrated data curation and modeling pipeline consisting of 4 modules that leverage recent advances in natural language processing, computational phenotyping, and causal modeling techniques with noisy data. Module 1 consists of techniques for data harmonization. We use natural language processing to recognize clinical variables from RCT design documents and map the extracted variables to EHR features with description matching and knowledge networks. Module 2 then develops techniques for cohort construction using advanced phenotyping algorithms to both identify patients with diseases of interest and define the treatment arms. Module 3 introduces methods for variable curation, including a list of existing tools to extract baseline variables from different sources (eg, codified, free text, and medical imaging) and end points of various types (eg, death, binary, temporal, and numerical). Finally, module 4 presents validation and robust modeling methods, and we propose a strategy to create gold-standard labels for EHR variables of interest to validate data curation quality and perform subsequent causal modeling for RWE. In addition to the workflow proposed in our pipeline, we also develop a reporting guideline for RWE that covers the necessary information to facilitate transparent reporting and reproducibility of results. Moreover, our pipeline is highly data driven, enhancing study data with a rich variety of publicly available information and knowledge sources. We also showcase our pipeline and provide guidance on the deployment of relevant tools by revisiting the emulation of the Clinical Outcomes of Surgical Therapy Study Group Trial on laparoscopy-assisted colectomy versus open colectomy in patients with early-stage colon cancer. We also draw on existing literature on EHR emulation of RCTs together with our own studies with the Mass General Brigham EHR.

Informative missingness: What can we learn from patterns in missing laboratory data in the electronic health record?

BACKGROUND: In electronic health records, patterns of missing laboratory test results could capture patients' course of disease as well as ​​reflect clinician's concerns or worries for possible conditions. These patterns are often understudied and overlooked. This study aims to identify informative patterns of missingness among laboratory data collected across 15 healthcare system sites in three countries for COVID-19 inpatients. METHODS: We collected and analyzed demographic, diagnosis, and laboratory data for 69,939 patients with positive COVID-19 PCR tests across three countries from 1 January 2020 through 30 September 2021. We analyzed missing laboratory measurements across sites, missingness stratification by demographic variables, temporal trends of missingness, correlations between labs based on missingness indicators over time, and clustering of groups of labs based on their missingness/ordering pattern. RESULTS: With these analyses, we identified mapping issues faced in seven out of 15 sites. We also identified nuances in data collection and variable definition for the various sites. Temporal trend analyses may support the use of laboratory test result missingness patterns in identifying severe COVID-19 patients. Lastly, using missingness patterns, we determined relationships between various labs that reflect clinical behaviors. CONCLUSION: In this work, we use computational approaches to relate missingness patterns to hospital treatment capacity and highlight the heterogeneity of looking at COVID-19 over time and at multiple sites, where there might be different phases, policies, etc. Changes in missingness could suggest a change in a patient's condition, and patterns of missingness among laboratory measurements could potentially identify clinical outcomes. This allows sites to consider missing data as informative to analyses and help researchers identify which sites are better poised to study particular questions.