Global disparities in surgeons’ workloads, academic engagement and rest periods: the on-calL shIft fOr geNEral SurgeonS (LIONESS) study

: The workload of general surgeons is multifaceted, encompassing not only surgical procedures but also a myriad of other responsibilities. From April to May 2023, we conducted a CHERRIES-compliant internet-based survey analyzing clinical practice, academic engagement, and post-on-call rest. The questionnaire featured six sections with 35 questions. Statistical analysis used Chi-square tests, ANOVA, and logistic regression (SPSS® v. 28). The survey received a total of 1.046 responses (65.4%). Over 78.0% of responders came from Europe, 65.1% came from a general surgery unit; 92.8% of European and 87.5% of North American respondents were involved in research, compared to 71.7% in Africa. Europe led in publishing research studies (6.6 ± 8.6 yearly). Teaching involvement was high in North America (100%) and Africa (91.7%). Surgeons reported an average of 6.7 ± 4.9 on-call shifts per month, with European and North American surgeons experiencing 6.5 ± 4.9 and 7.8 ± 4.1 on-calls monthly, respectively. African surgeons had the highest on-call frequency (8.7 ± 6.1). Post-on-call, only 35.1% of respondents received a day off. Europeans were most likely (40%) to have a day off, while African surgeons were least likely (6.7%). On the adjusted multivariable analysis HDI (Human Development Index) (aOR 1.993) hospital capacity > 400 beds (aOR 2.423), working in a specialty surgery unit (aOR 2.087), and making the on-call in-house (aOR 5.446), significantly predicted the likelihood of having a day off after an on-call shift. Our study revealed critical insights into the disparities in workload, access to research, and professional opportunities for surgeons across different continents, underscored by the HDI

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly

Novel Nanozeolitic Imidazolate Framework (ZIF-8)–Luciferase Biocomposite for Nanosensing Applications

The identification of new strategies to improve the stability of proteins is of utmost importance for a number of applications, from biosensing to biocatalysis. Metal-organic frameworks (MOFs) have been shown as a versatile host platform for the immobilization of proteins, with the potential to protect proteins in harsh conditions. In this work, a new thermostable luciferase mutant has been selected as a bioluminescent protein model to investigate the suitability of MOFs to improve its stability and prompt its applications in real-world applications, for example, ATP detection in portable systems. The luciferase has been immobilized onto zeolitic imidazolate framework-8 (ZIF-8) to obtain a bioluminescent biocomposite with enhanced performance. The biocomposite ZIF-8@luc has been characterized in harsh conditions (e.g., high temperature, non-native pH, etc.). Bioluminescence properties confirmed that MOF enhanced the luciferase stability at acidic pH, in the presence of organic solvents, and at -20 degrees C. To assess the feasibility of this approach, the recyclability, storage stability, precision, and Michaelis-Menten constants (Km) for ATP and D-luciferin have been also evaluated. As a proof of principle, the suitability for ATP detection was investigated and the biocomposite outperformed the free enzyme in the same experimental conditions, achieving a limit of detection for ATP down to 0.2 fmol

A Bayesian Approach to Run-to-Run Optimization of Animal Cell Bioreactors Using Probabilistic Tendency Models

Increasing demand for recombinant proteins (including monoclonal antibodies) where time to market is critical could benefit from the use of model-based optimization of cell viability and productivity. Owing to the complexity of metabolic regulation, unstructured models of animal cell cultures typically have built-in errors (structural and parametric uncertainty) which give rise to the need for obtaining relevant data through experimental design in modeling for optimization. A Bayesian optimization strategy which integrates tendency models with iterative policy learning is proposed. Parameter distributions in a probabilistic model of bioreactor performance are re-estimated using data from experiments designed for maximizing information content and productivity. Results obtained highlight that experimental design for run-to-run optimization using a probabilistic tendency model is effective to maximize biomass growth even though significant model uncertainty is present. A hybrid cybernetic model of a myeloma cell culture coconsuming glucose and glutamine is used to simulate data to demonstrate the efficacy of the proposed approach

Theoretical Study of Novel Azo-Tetraphenylporphyrins: Potential Photovoltaic Materials

A density functional theory study was performed to analyze the electron donor–acceptor properties of the cis and trans isomers of a novel azobenzene-containing tetraphenylporphyrin (TPPN₂PhC₁₄H₂₉) with different substituents (Br or TMS). In general, the trans isomers are better electron acceptors than the correspondent cis homologues. Their UV–vis spectra were also obtained and a comparison with available experimental results is included. According to these results, the azo compounds reported here are promising materials for the elaboration of dye-sensitized solar cells because their HOMO–LUMO gaps are close to 2 eV. Moreover, the energy of the high intensity absorption bands also fulfills the requirements needed for the operation of a solar cell built with TiO₂ and the I^–/I₃^– pair

New In-Depth Analytical Approach of the Porcine Seminal Plasma Proteome Reveals Potential Fertility Biomarkers

A complete characterization of the proteome of seminal plasma (SP) is an essential step to understand how SP influences sperm function and fertility after artificial insemination (AI). The purpose of this study was to identify which among characterized proteins in boar SP were differently expressed among AI boars with significantly different fertility outcomes. A total of 872 SP proteins, 390 of them belonging specifically to <i>Sus Scrofa</i> taxonomy, were identified (Experiment 1) by using a novel proteomic approach that combined size exclusion chromatography and solid-phase extraction as prefractionation steps prior to Nano LC–ESI–MS/MS analysis. The SP proteomes of 26 boars showing significant differences in farrowing rate (<i>n</i> = 13) and litter size (<i>n</i> = 13) after the AI of 10 526 sows were further analyzed (Experiment 2). A total of 679 SP proteins were then quantified by the SWATH approach, where the penalized linear regression LASSO revealed differentially expressed SP proteins for farrowing rate (FURIN, AKR1B1, UBA1, PIN1, SPAM1, BLMH, SMPDL3A, KRT17, KRT10, TTC23, and AGT) and litter size (PN-1, THBS1, DSC1, and CAT). This study extended our knowledge of the SP proteome and revealed some SP proteins as potential biomarkers of fertility in AI boars