Methanol-to-Olefins Studied by UV Raman Spectroscopy as Compared to Visible Wavelength: Capitalization on Resonance Enhancement.

Resonance Raman spectroscopy can provide insights into complex reaction mechanisms by selectively enhancing the signals of specific molecular species. In this work, we demonstrate that, by changing the excitation wavelength, Raman bands of different intermediates in the methanol-to-hydrocarbons reactions can be identified. We show in particular how UV excitation enhances signals from short-chain olefins and cyclopentadienyl cations during the induction period, while visible excitation better detects later-stage aromatics. However, visible excitation is prone to fluorescence that can obscure Raman signals, and hence, we show how fast fluorescence rejection techniques like Kerr gating are necessary for extracting useful information from visible excitation measurements.

Chimeric Protein Switch Biosensors.

Rapid detection of protein and small-molecule analytes is a valuable technique across multiple disciplines, but most in vitro testing of biological or environmental samples requires long, laborious processes and trained personnel in laboratory settings, leading to long wait times for results and high expenses. Fusion of recognition with reporter elements has been introduced to detection methods such as enzyme-linked immunoassays (ELISA), with enzyme-conjugated secondary antibodies removing one of the many incubation and wash steps. Chimeric protein switch biosensors go further and provide a platform for homogenous mix-and-read assays where long wash and incubation steps are eradicated from the process. Chimeric protein switch biosensors consist of an enzyme switch (the reporter) coupled to a recognition element, where binding of the analyte results in switching the activity of the reporter enzyme on or off. Several chimeric protein switch biosensors have successfully been developed for analytes ranging from small molecule drugs to large protein biomarkers. There are two main formats of chimeric protein switch biosensor developed, one-component and multi-component, and these formats exhibit unique advantages and disadvantages. Genetically fusing a recognition protein to the enzyme switch has many advantages in the production and performance of the biosensor. A range of immune and synthetic binding proteins have been developed as alternatives to antibodies, including antibody mimetics or antibody fragments. These are mainly small, easily manipulated proteins and can be genetically fused to a reporter for recombinant expression or manipulated to allow chemical fusion. Here, aspects of chimeric protein switch biosensors will be reviewed with a comparison of different classes of recognition elements and switching mechanisms.

Therapeutic drug monitoring of immunotherapies with novel Affimer-NanoBiT sensor construct.

Concentration-therapeutic efficacy relationships have been observed for several therapeutic monoclonal antibodies (TmAb), where low circulating levels can result in ineffective treatment and high concentrations can cause adverse reactions. Rapid therapeutic drug monitoring (TDM) of TmAb drugs would provide the opportunity to adjust an individual patient's dosing regimen to improve treatment results. However, TDM for immunotherapies is currently limited to centralised testing methods with long sample-collection to result timeframes. Here, we show four point-of-care (PoC) TmAb biosensors by combining anti-idiotypic Affimer proteins and NanoBiT split luciferase technology at a molecular level to provide a platform for rapid quantification (<10 minutes) for four clinically relevant TmAb (rituximab, adalimumab, ipilimumab and trastuzumab). The rituximab sensor performed best with 4 pM limit of detection (LoD) and a quantifiable range between 8 pM-2 nM with neglectable matrix effects in serum up to 1%. After dilution of serum samples, the resulting quantifiable range for all four sensors falls within the clinically relevant range and compares favourably with the sensitivity and/or time-to-result of current ELISA standards. Further development of these sensors into a PoC test may improve treatment outcome and quality of life for patients receiving immunotherapy.

Applications of Surface Plasmon Resonance (SPR) to the Study of Diverse Protein-Ligand Interactions.

Functional characterization of enzymes/proteins requires determination of the binding affinity of small molecules or other biomolecules with the target proteins. Several available techniques, such as proteomics and drug discovery strategies, require a precise and high-throughput assay for rapid and reliable screening of potential candidates for further testing. Surface plasmon resonance (SPR), a well-established label-free technique, directly measures biomolecular affinities. SPR assays require immobilization of one interacting component (ligand) on a conductive metal (mostly gold or silver) and a continuous flow of solution containing potential binding partner (analyte) across the surface. The SPR phenomenon occurs when polarized light excites the electrons at the interface of the metal and the dielectric medium to generate electromagnetic waves that propagate parallel to the surface. Changes in the refractive index due to interaction between the ligand and analyte are measured by detecting the reflected light, providing real-time data on kinetics and specificity. A prominent use of SPR is identifying compounds in crude plant extracts that bind to specific molecules. Procedures that utilize SPR are becoming increasingly applicable outside the laboratory setting, and SPR imaging and localized SPR (LSPR) are cheaper and more portable alternative for in situ detection of plant or mammalian pathogens and drug discovery studies. LSPR, in particular, has the advantage of direct attachment to test tissues in live-plant studies. Here, we describe three protocols utilizing SPR-based assays for precise analysis of protein-ligand interactions. © 2024 Wiley Periodicals LLC. Basic Protocol 1: SPR comparison of binding affinities of viral reverse transcriptase polymorphisms Basic Protocol 2: SPR screening of crude plant extract for protein-binding agents Basic Protocol 3: Localized SPR-based antigen detection using antibody-conjugated gold nanoparticles.

A Critical Assessment on Calculating Vibrational Spectra in Nanostructured Materials.

Vibrational spectroscopy is an omnipresent spectroscopic technique to characterize functional nanostructured materials such as zeolites, metal-organic frameworks (MOFs), and metal-halide perovskites (MHPs). The resulting experimental spectra are usually complex, with both low-frequency framework modes and high-frequency functional group vibrations. Therefore, theoretically calculated spectra are often an essential element to elucidate the vibrational fingerprint. In principle, there are two possible approaches to calculate vibrational spectra: (i) a static approach that approximates the potential energy surface (PES) as a set of independent harmonic oscillators and (ii) a dynamic approach that explicitly samples the PES around equilibrium by integrating Newton's equations of motions. The dynamic approach considers anharmonic and temperature effects and provides a more genuine representation of materials at true operating conditions; however, such simulations come at a substantially increased computational cost. This is certainly true when forces and energy evaluations are performed at the quantum mechanical level. Molecular dynamics (MD) techniques have become more established within the field of computational chemistry. Yet, for the prediction of infrared (IR) and Raman spectra of nanostructured materials, their usage has been less explored and remain restricted to some isolated successes. Therefore, it is currently not a priori clear which methodology should be used to accurately predict vibrational spectra for a given system. A comprehensive comparative study between various theoretical methods and experimental spectra for a broad set of nanostructured materials is so far lacking. To fill this gap, we herein present a concise overview on which methodology is suited to accurately predict vibrational spectra for a broad range of nanostructured materials and formulate a series of theoretical guidelines to this purpose. To this end, four different case studies are considered, each treating a particular material aspect, namely breathing in flexible MOFs, characterization of defects in the rigid MOF UiO-66, anharmonic vibrations in the metal-halide perovskite CsPbBr3, and guest adsorption on the pores of the zeolite H-SSZ-13. For all four materials, in their guest- and defect-free state and at sufficiently low temperatures, both the static and dynamic approach yield qualitatively similar spectra in agreement with experimental results. When the temperature is increased, the harmonic approximation starts to fail for CsPbBr3 due to the presence of anharmonic phonon modes. Also, the spectroscopic fingerprints of defects and guest species are insufficiently well predicted by a simple harmonic model. Both phenomena flatten the potential energy surface (PES), which facilitates the transitions between metastable states, necessitating dynamic sampling. On the basis of the four case studies treated in this Review, we can propose the following theoretical guidelines to simulate accurate vibrational spectra of functional solid-state materials: (i) For nanostructured crystalline framework materials at low temperature, insights into the lattice dynamics can be obtained using a static approach relying on a few points on the PES and an independent set of harmonic oscillators. (ii) When the material is evaluated at higher temperatures or when additional complexity enters the system, e.g., strong anharmonicity, defects, or guest species, the harmonic regime breaks down and dynamic sampling is required for a correct prediction of the phonon spectrum. These guidelines and their illustrations for prototype material classes can help experimental and theoretical researchers to enhance the knowledge obtained from a lattice dynamics study.

Progressive remodeling of structural networks following surgery for operculo-insular epilepsy.

Introduction: Operculo-insular epilepsy (OIE) is a rare condition amenable to surgery in well-selected cases. Despite the high rate of neurological complications associated with OIE surgery, most postoperative deficits recover fully and rapidly. We provide insights into this peculiar pattern of functional recovery by investigating the longitudinal reorganization of structural networks after surgery for OIE in 10 patients. Methods: Structural T1 and diffusion-weighted MRIs were performed before surgery (t0) and at 6 months (t1) and 12 months (t2) postoperatively. These images were processed with an original, comprehensive structural connectivity pipeline. Using our method, we performed comparisons between the t0 and t1 timepoints and between the t1 and t2 timepoints to characterize the progressive structural remodeling. Results: We found a widespread pattern of postoperative changes primarily in the surgical hemisphere, most of which consisted of reductions in connectivity strength (CS) and regional graph theoretic measures (rGTM) that reflect local connectivity. We also observed increases in CS and rGTMs predominantly in regions located near the resection cavity and in the contralateral healthy hemisphere. Finally, most structural changes arose in the first six months following surgery (i.e., between t0 and t1). Discussion: To our knowledge, this study provides the first description of postoperative structural connectivity changes following surgery for OIE. The ipsilateral reductions in connectivity unveiled by our analysis may result from the reversal of seizure-related structural alterations following postoperative seizure control. Moreover, the strengthening of connections in peri-resection areas and in the contralateral hemisphere may be compatible with compensatory structural plasticity, a process that could contribute to the recovery of functions seen following operculo-insular resections for focal epilepsy.

The Global Impact of Multisystemic Vulnerabilities on Criminal Variety: A Cross-Continental Study in Young Adults.

Previous research has shown a robust association between different childhood and adolescent vulnerabilities and youth offending. However, these investigations have primarily focused on youths from high-income Western countries. Consequently, the generalizability of these findings to better inform global justice policies remains uncertain. This study aimed to address this gap by examining the relationship between individual, familial, and contextual vulnerabilities and criminal versatility during young adulthood, accounting for sociodemographic factors and cross-national differences. Data were derived from a diverse sample of 4,182 young adults (67% female; mean age = 18.96; SD = 0.81) residing in 10 countries across 5 continents who participated in the International Study of Pro/Antisocial Behavior in Young Adults. The Psychosocial and Family Vulnerability Questionnaire and the Adverse Childhood Experiences questionnaire were used to assess social and family adversity, and past-year criminal diversity was measured with the Criminal Variety Index. Results indicate that child maltreatment, substance abuse, and delinquent peers are global risk factors for criminal variety. Moreover, they are independent across males and females and among youths living in countries that are ranked differently on the Human Development Index (HDI). In addition, some childhood vulnerabilities showed different predictive ability across sexes (e.g., school failure), and across countries ranked differently on the HDI (e.g., family dysfunction). These findings suggest that certain childhood factors contribute to criminal behavior through transcultural mechanisms. Moreover, they highlight the importance of developing evidence-based policies that focus on transcultural risk factors to globally prevent criminal behavior.

Sociodemographic and health-related differences in undiagnosed hypertension in the health survey for England 2015-2019: a cross-sectional cohort study.

Background: Hypertension is a leading cause of morbidity and mortality worldwide, yet a substantial proportion of cases are undiagnosed. Understanding the scale of undiagnosed hypertension and identifying groups most at risk is important to inform approaches to detection. Methods: In this cross-sectional cohort study, we used data from the 2015 to 2019 Health Survey for England, an annual, cross-sectional, nationally representative survey. The survey follows a multi-stage stratified probability sampling design, involving a random sample of primary sampling units based on postcode sectors, followed by a random sample of postal addresses within these units. Within each selected household, all adults (aged ≥16 years) and up to four children, were eligible for participation. For the current study, individuals aged 16 years and over who were not pregnant and had valid blood pressure data were included in the analysis. The primary outcome was undiagnosed hypertension, defined by a measured blood pressure of 140/90 mmHg or above but no history of diagnosis. Age-adjusted prevalence of undiagnosed hypertension was estimated across sociodemographic and health-related characteristics, including ethnicity, region, rural-urban classification, relationship status, highest educational qualification, National Statistics Socio-Economic Classification (NS-SEC), Body Mass Index (BMI), self-reported general health, and smoking status. To assess the independent association between undiagnosed hypertension and each characteristic, we fitted a logistic regression model adjusted for sociodemographic factors. Findings: The sample included 21,476 individuals, of whom 55.8% were female and 89.3% reported a White ethnic background. An estimated 30.7% (95% confidence interval 29.0-32.4) of men with hypertension and 27.6% (26.1-29.1) of women with hypertension were undiagnosed. Younger age, lower BMI, and better self-reported general health were associated with an increased likelihood of hypertension being undiagnosed for men and women. Living in rural areas and in regions outside of London and the East of England were also associated with an increased likelihood of hypertension being undiagnosed for men, as were being married or in a civil partnership and having higher educational qualifications for women. Interpretation: Hypertension is commonly undiagnosed, and some of the groups that are at the lowest risk of hypertension are the most likely to be undiagnosed. Given the high lifetime risk of hypertension and its strong links with morbidity and mortality, our findings suggest a need for greater awareness of the potential for undiagnosed hypertension, including among those typically considered 'low risk'. Further research is needed to assess the impact of extending hypertension screening to lower-risk groups. Funding: None.