University of Strathclyde

Reactive fragment (RF) screening has emerged as an efficient method for ligand discovery across the proteome, irrespective of a target's perceived tractability. To date, however, the efficiency of subsequent optimisation campaigns has largely been low‐throughput, constrained by the need for synthesis and purification of target compounds. We report an efficient platform for ‘direct‐to‐biology’ (D2B) screening of cysteine‐targeting chloroacetamide RFs, wherein synthesis is performed in 384‐well plates allowing direct assessment in downstream biological assays without purification. Here, the developed platform was used to optimise inhibitors of SARS‐CoV‐2 main protease (MPro), an established drug target for the treatment of COVID‐19. An initial RF hit was developed into a series of potent inhibitors, and further exploration using D2B screening enabled a ‘switch’ to a reversible inhibitor series. This example of ligand discovery for MPro illustrates the acceleration that D2B chemistry can offer for optimising RFs towards covalent inhibitor candidates, as well as providing future impetus to explore the evolution of RFs into non‐covalent ligands.

Accurate soil stratification is essential for geotechnical engineering design. Owing to its effectiveness and efficiency, the cone penetration test (CPT) has been widely applied for subsurface stratigraphy, which relies heavily on empiricism for correlations to soil type. Recently, deep learning techniques have shown great promise in learning the relationship between CPT data and soil boundaries automatically. However, the segmentation of soil boundaries is fraught with model and measurement uncertainty. This paper introduces an uncertainty‐guided U((‐Net (UGU‐Net) for improved soil boundary segmentation. The UGU‐Net consists of three parts: (a) a Bayesian U‐Net to predict a pixel‐level uncertainty map, (b) reinforcement of original labels on the basis of the predicted uncertainty map, and (c) a traditional deterministic U‐Net, which is applied to the reinforced labels for final soil boundary segmentation. The results show that the proposed UGU‐Net outperforms the existing methods in terms of both high accuracy and low uncertainty. A sensitivity study is also conducted to explore the influence of key model parameters on model performance. The proposed method is validated by comparing the predicted subsurface profile with benchmark profiles. The code for this project is available at github.com/Xiaoqi‐Zhou‐suda/UGU‐Net.

This paper proposes an energy-efficient optimization technique for downlink indoor visible light communication (VLC) systems using hybrid non-orthogonal multiple access (NOMA) and reconfigurable intelligent surfaces (RIS). The approach considers a hybrid time division multiple access-NOMA (TDMA-NOMA) to provide massive connectivity to multi-clusters. Clusters of users are formed using NOMA while TDMA is used to allocate a specific time slot within a communication frame. The proposed technique optimizes the precoding at the multi-LED transmitter, RIS tuning parameters, and time-slot allocation parameters for each cluster to maximize the system’s energy efficiency (EE). The EE optimization problem is solved through the block coordinate descent (BCD) framework, which splits the optimization problem into two blocks. An alternating optimization (AO) framework is used in the first block to optimize the transmit precoding through conic quadratic programming (CQP) and RIS tuning parameters through a semidefinite programming (SDP) technique based on the surrogate optimization method. The second block allocates energy-efficient time-slot for each cluster through linear programming (LP) approach to further improve the EE of the system. The simulation results indicate that the proposed BCD framework achieves fast convergence and excellent performance in terms of the EE of the system while maintaining low computational complexity.

Purpose Antimicrobial resistance is a global health crisis exacerbated by excessive and inappropriate use of antibiotics, especially among low- and middle-income countries including Pakistan. The paediatric population is a key area in view of their vulnerability and excessive prescribing of antibiotics in Pakistan. Consequently, there is an urgent need to robustly assess antimicrobial use among hospitalized neonates and children in tertiary hospitals in Pakistan as they are generally the training centres for new physicians subsequently treating children. Patients and Methods A point prevalence survey (PPS) was conducted in the children’s wards of 14 tertiary care hospitals in Punjab Province, covering over 50% of the population of Pakistan. This builds on a previous PPS among tertiary care hospitals treating exclusively neonates and children. Results A total of 1811 neonates and children were surveyed with 1744 patients prescribed antibiotics, a prevalence of 96.3%. A total of 2747 antibiotics were prescribed to these 1744 neonates and children, averaging 1.57 antibiotics per patient. Overall, 57.7% of the patients were prescribed one antibiotic and 27.2% two antibiotics, with 85.6% of antibiotics administered parenterally. Over a third (34.4%) of the antibiotics were prescribed prophylactically, with 44.7% of them for surgical procedures. Among those prescribed antibiotics for surgical procedures, 75.2% were prescribed for more than one day. Overall, 92.2% of antibiotics were prescribed empirically, with 86.2% prescribed without mentioning the rationale for their choice in the notes, with 77.6% having no stop date. Respiratory tract infections were the most common indication (43.4%). Staphylococcus species (36.0%) were the most common pathogen with limited Culture and Sensitivity Testing performed. Three quarters (75.2%) of antibiotics were from the Watch list, and 24.4% were Access antibiotics. Conclusion A very high prevalence of antibiotic use among neonates and children in tertiary hospitals in Pakistan, including Watch antibiotics, mirroring previous studies. Consequently, initiatives including antimicrobial stewardship programmes are urgently needed to address current inappropriate prescribing.

Coffee silver skin, an organic residue from coffee production, demonstrates low solid fuel characteristics such as low bulk density and heating value, necessitating enhancements for solid fuel applications. Torrefaction in a flue gas environment (5% O2, 15% CO2, and a balance of N2, v/v) is more energy-efficient than inert torrefaction, using recovered flue gas to improve fuel quality and process efficiency. Three input factors were assessed: temperature (200, 250, and 300 °C), residence time (30, 45, and 60 min), and gas media (N2 and flue gas). Four performance metrics were evaluated: energy yield, upgrading energy index, specific energy consumption, and energy-mass co-benefit. Temperature significantly influenced most outcomes, except for energy-mass co-benefit, which was medium-dependent. Optimal torrefaction conditions achieving maximum energy yield (71.48%) and energy-mass co-benefit (5.30%) were identified at 200 °C for 30 min with flue gas. The torrefied material’s properties include moisture content, volatile matter, fixed carbon, and ash content of 3.03%, 69.24%, 27.04%, and 1.01%, respectively. Furthermore, the hydrophobicity of pelletized coffee silver skin notably increased under flue gas conditions, evident by a contact angle greater than 100°, indicating that flue gas torrefaction is a feasible approach for producing high-grade solid fuel.

Currently 2.29% of deaths worldwide are caused by antimicrobial resistance (AMR), compared to 1.16% from malaria, and 1.55% from human immunodeficiency virus and acquired immunodeficiency syndrome (HIV/AIDs). Furthermore, deaths resulting from AMR are projected to increase to more than 10 million per annum by 2050. Biofilms are common in hospital settings, such as medical implants and pose a particular problem as they have shown resistance to antibiotics up to 1000-fold higher than planktonic cells because of dormant states and reduced growth rates. This is compounded by the fact that many antibiotics target mechanisms of active metabolism and are therefore less effective. The work presented here aimed to develop a method for biofilm quantification which could be translated into the clinical setting, as well as used in the screening of antibiofilm agents. This was carried out alongside crystal violet staining, as a published point of reference. Using electrochemical impedance spectroscopy and square wave voltammetry, P. aeruginosa biofilm formation was detected within an hour after seeding P. aeruginosa on the sensor. A 40% decrease in impedance modulus was shown when P. aeruginosa biofilm had formed, compared to the media only control. As such, this work offers a starting point for the development of real-time biofilm sensing technologies, which can be translated into implantable materials.

The accountability interview in which a public figure is held to account for their statements or actions is a well-established armature in the delivery of broadcast news. In its broadcast canonical form it relies on questioning as an instrument for addressing issues of knowledge, responsibility, and the rightness of actions of those with public standing. However, shifts in questioning techniques have accelerated a movement towards argument in the context of the broadcast accountability interview and a corresponding loosening of its interview structure. Indeed, there are signs of a growing tendency for the interview framework itself to be questioned by interviewees. This article examines what is at stake in these changes and asks if the accountability interview in an era of heightened conflict remains fit for purpose or is facing a kind of legitimation crisis.

Nitrogen‐containing drug molecules and pharmaceuticals are ubiquitous, rendering the construction of C−N bonds a crucial target in methodology development. The Ritter reaction is a well‐established method for accessing C−N bonds by generating amide functionality through the reaction of carbocations and nitriles. Since its discovery back in 1948, the Ritter reaction has progressively advanced towards milder and more sustainable conditions for carbocation generation. In this regard, notable contributions have been made by means of single electron transfer (SET) chemistry. Nowadays, photo‐ and electrochemistry are established methods of choice for the generation of reactive radical intermediates and their subsequent oxidation via radical‐polar crossover (RPC) mechanism. We review recent examples of tandem RPC and Ritter‐type protocols, demonstrating how photo‐ and electrochemical energies have been effectively harvested to expand the precursor pool for the Ritter reaction as well as reimagining the process with novel mechanisms and additives.

Objectives The elderly are particularly prone to complications from a number of vaccine-preventable diseases. However, there are limited data on vaccine uptake for this vulnerable population in South Africa. Consequently, this study investigated influenza, pneumococcal and shingles vaccine uptake among elderly people in South Africa; reasons for their vaccination status; and factors associated with their uptake. Methods Cross-sectional study using an interviewer-administered questionnaire to survey 985 consenting adults aged ≥65 years in 2018. Participants were recruited from across South Africa. Bivariate analysis was used to identify socio-demographic variables associated with vaccine uptake, with multivariate logistic regression analysis used to identify key factors associated with vaccine uptake. Results Influenza vaccine uptake was 32.3% (318/985), with uptake highest in those aged 85–90 years. Pneumococcal and shingles vaccine uptake was 3.8% (37/985) and 0.4% (4/985) respectively, being highest among those aged >90 years. The strongest statistically significant predictors for influenza vaccination were previous influenza vaccination (OR: 8.42 [5.61–12.64]); identifying as ‘Coloured’ (OR: 8.39 [3.98–17.69]); and residing in Gauteng Province (OR: 5.44 [3.30–9.02]). The strongest statistically significant predictors of receiving pneumococcal vaccination included receiving influenza vaccination (OR = 10.67 [3.27–37.83]); residing in the Western Cape Province (OR: 7.34 [1.49–36.22]); identifying as ‘Indian’ (OR: 5.85 [2.53–13.55]); and having a university education (OR: 5.56 [1.25–24.77]). Statistically significant barriers to receiving influenza vaccination included following the Traditional African religion (OR: 0.08 [0.01–0.62]) and residing in Limpopo Province (OR: 0.16 [0.04–0.71]). The main reasons for non-vaccination were considering influenza as a mild illness (36.6%; 242/661), and lack of knowledge about the pneumococcal (93.4%; 886/948) and shingles (95.2%; 934/981) vaccines. Conclusion Vaccine uptake for all vaccines was sub-optimal, with multiple non-modifiable factors predicting vaccine uptake. These pre-COVID-19 data provide a baseline for measuring the effectiveness of future interventions to increase vaccine uptake and safeguard the health of the elderly.

We present numerical simulations used to interpret laser-driven plasma experiments at the GSI Helmholtz Centre for Heavy Ion Research. The mechanisms by which non-thermal particles are accelerated in astrophysical environments, e.g., the solar wind, supernova remnants, and gamma ray bursts, is a topic of intense study. When shocks are present, the primary acceleration mechanism is believed to be first-order Fermi, which accelerates particles as they cross a shock. Second-order Fermi acceleration can also contribute, utilizing magnetic mirrors for particle energization. Despite this mechanism being less efficient, the ubiquity of magnetized turbulence in the universe necessitates its consideration. Another acceleration mechanism is the lower-hybrid drift instability, arising from gradients of both density and magnetic field, which produce lower-hybrid waves with an electric field that energizes particles as they cross these waves. With the combination of high-powered laser systems and particle accelerators, it is possible to study the mechanisms behind cosmic-ray acceleration in the laboratory. In this work, we combine experimental results and high-fidelity three-dimensional simulations to estimate the efficiency of ion acceleration in a weakly magnetized interaction region. We validate the FLASH magneto-hydrodynamic code with experimental results and use OSIRIS particle-in-cell code to verify the initial formation of the interaction region, showing good agreement between codes and experimental results. We find that the plasma conditions in the experiment are conducive to the lower-hybrid drift instability, yielding an increase in energy ΔE of ∼ 264 keV for 242 MeV calcium ions.

Effective waste management techniques are required due to the serious environmental risks posed by the increase in the production of solid waste. This study addresses two important research questions regarding Turkey’s management of municipal solid waste (MSW). First, it fills a gap in the literature by identifying the optimal MSW treatment option using combined Pythagorean fuzzy Analytic Hierarchy Process (AHP) and Weighted Aggregated Sum Product Assessment (WASPAS) approach. Second, it applies a novel method called Environmental Failure Mode and Effect Analysis (E-FMEA), designed for practical application, to conduct a comprehensive environmental impact assessment based on ISO 14001 standards. The results demonstrate the effectiveness of the integrated AHP-WASPAS approach in decision-making, highlighting the optimal MSW treatment option. Additionally, E-FMEA systematically examines environmental risks associated with MSW management in Turkey, offering crucial insights for practice and policy formation. At the core of this study lies the integration of all methods as robust and holistic approach, comprehensively addressing key aspects of MSW management. Landfills emerge as the preferred option for waste management due to their versatility, affordability, long-term storage capacity, and integration of modern technologies to reduce environmental impacts. Numerical results reveal that both landfills and incinerators exhibit moderate to high Risk Priority Number (RPN) values across various environmental components, highlighting their significant potential environmental impacts. Furthermore, a risk analysis through sensitivity testing reveals that landfilling is the most favorable municipal solid waste management option in Turkey. These findings highlight the need for policies that prioritize sustainable waste treatment while addressing environmental risks.

Reactive fragment (RF) screening has emerged as an efficient method for ligand discovery across the proteome, irrespective of a target’s perceived tractability. To date, however, the efficiency of subsequent optimisation campaigns has largely been low‐throughput, constrained by the need for synthesis and purification of target compounds. We report a high‐throughput platform for ‘direct‐to‐biology’ (D2B) screening of cysteine‐targeting chloroacetamide RFs, wherein synthesis is performed in 384‐well plates allowing direct assessment in downstream biological assays without purification. Here, the developed platform was used to optimise inhibitors of SARS‐CoV‐2 main protease (MPro), an established drug target for the treatment of COVID‐19. An initial RF hit was developed into a series of potent inhibitors, and further exploration using D2B screening enabled a ‘switch’ to a reversible inhibitor series. This example of ligand discovery for MPro illustrates the acceleration that D2B chemistry can offer for optimising RFs towards covalent inhibitor candidates, as well as providing future impetus to explore the evolution of RFs into non‐covalent ligands.

Introduction Despite the well-established efficacy of thiazolidinediones (TZDs), including pioglitazone and rosiglitazone, in type II diabetes management, their potential contribution to heart failure risk remains a significant area of uncertainty. This incomplete understanding, which persists despite decades of clinical use of TZDs, has generated ongoing controversy and unanswered questions regarding their safety profiles, ultimately limiting their broader clinical application. Objective and methods This study presented a multi-omics approach, integrating toxicoproteomics and toxicometabolomics data with the goal of uncovering novel mechanistic insights into TZD cardiotoxicity and identifying molecular signatures predictive of side effect progression. Results Network analysis of proteo-metabolomic data revealed a distinct fingerprint of disrupted biochemical pathways, which were primarily related to energy metabolism. Downregulation of oxidative phosphorylation and fatty acid synthesis was coupled with increased activity in anaerobic glycolysis, the pentose phosphate pathway, and amino acid and purine metabolism. This suggests a potential metabolic shift in AC16 cells from fatty acid oxidation towards anaerobic glycolysis, potentially contributing to observed cardiotoxicity. Additionally, the study identified a marked disruption in the glutathione system, indicating an imbalanced redox state triggered by TZD exposure. Importantly, our analysis identified key molecular signatures across omics datasets, including prominent signatures of amino acids like L-ornithine, L-tyrosine and glutamine, which are evidently associated with heart failure, supporting their potential use for the early prediction of cardiotoxicity progression. Conclusion By uncovering a novel mechanistic explanation for TZD cardiotoxicity, this study simultaneously illuminates potential therapeutic interventions, opening avenues for future research to improve the safety profile of TZD agents. (250 words) Graphical abstracts

Next generation high-power laser facilities are expected to generate hundreds-of-MeV proton beams and operate at multi-Hz repetition rates, presenting opportunities for medical, industrial and scientific applications requiring bright pulses of energetic ions. Characterizing the spectro-spatial profile of these ions at high repetition rates in the harsh radiation environments created by laser-plasma interactions remains challenging but is paramount for further source development. To address this, we present a compact scintillating fiber imaging spectrometer based on the tomographic reconstruction of proton energy deposition in a layered fiber array. Modeling indicates that spatial resolution of approximately 1 mm and energy resolution of less than 10% at proton energies of more than 20 MeV are readily achievable with existing 100 µm diameter fibers. Measurements with a prototype beam-profile monitor using 500 µm fibers demonstrate active readouts with invulnerability to electromagnetic pulses, and less than 100 Gy sensitivity. The performance of the full instrument concept is explored with Monte Carlo simulations, accurately reconstructing a proton beam with a multiple-component spectro-spatial profile.

Solid oxide cells (SOCs) are promising energy‐conversion devices due to their high efficiency under flexible operational modes. Yet, the sluggish kinetics of fuel electrodes remain a major obstacle to their practical applications. Since the electrochemically active region only extends a few micrometers, manipulating surface architecture is vital to endow highly efficient and stable fuel electrodes for SOCs. Herein, a simple selective etching method of nanosurface reconstruction is reported to achieve catalytically optimized hierarchical morphology for boosting the SOCs under different operational modes simultaneously. The selective etching can create many corrosion pits and exposure of more B‐site active atoms in Sr2Co0.4Fe1.2Mo0.4O6‐δ fuel electrode, as well as promote the exsolution of CoFe alloy nanoparticles. An outstanding electrochemical performance of the fabricated cell with the power density increased by 1.47 times to 1.31 W cm⁻² at fuel cell mode is demonstrated, while the current density reaches 1.85 A cm⁻² under 1.6 V at CO2 electrolysis mode (800 °C). This novel selective etching method in perovskite oxides provides an appealing strategy to fabricate hierarchical electrocatalysts for highly efficient and stable SOCs with broad implications for clean energy systems and CO2 utilization.

Literature on Group One organoelement chemistry is dominated by lithium, though sodium and potassium also feature prominently, whereas rubidium and caesium are rarely mentioned. With recent breakthroughs hinting that organoelement compounds of these two heavier metals can perform better than their lighter congeners in particular applications, important advantages could be missed unless complete sets of alkali metals are included in studies. Here, we report the synthesis and characterisation of a complete set of multi‐alkali‐metallated molecular compounds of the 1,3,5‐tris[(4,6‐dimethylpyridin‐2‐yl)aminomethyl]‐2,4,6‐triethylbenzene framework. Made by deprotonating the framework N‐H bonds by a suitable base, the set comprises six THF‐solvated compounds, four of which are homometallic, either containing Li in a trinuclear structure or Na, K, and Rb in hexanuclear structures. Since deprotonation was incomplete with Cs, its homometallic compound is tetranuclear containing two un‐metallated N‐H bonds. A heterobimetallic trilithium‐tricaesium hexanuclear compound was also obtained by using a bimetallic Li‐Cs base for deprotonation. Such alkali‐metallated frameworks are often precursors to other multimetallic frameworks with unique properties across different fields of science.