Introduction

Pre- and post-exposure prophylaxis (PrEP and PEP) are important pillars of the HIV prevention portfolio to reduce the risk of acquisition just before or after HIV exposure. While PrEP efficacy has been elucidated in many randomized clinical trials, corresponding data for PEP is extremely difficult to obtain in a controlled setting. Consequently, it is almost impossible to study the impact of PEP initiation delay and duration on HIV risk reduction clinically, which would inform recommendations on PEP use.

Methods

We employ pharmacokinetics, pharmacodynamics and viral dynamics models, along with individual factors, such as drug adherence to investigate the impact of initiation delay and PEP duration on HIV risk reduction. We evaluated PEP using two- and three-drug regimens with a TDF/FTC backbone. Moreover, we study PEP efficacy in the context of PrEP-to-PEP transitions.

Results

In our simulations, early initiation of PEP emerged as a pivotal factor for HIV risk reduction. We found that 2-drug (TDF/FTC) PEP may insufficiently protect when initiated > 1 hour post-exposure. When adding a third drug, early initiation was still a critical factor; however, over 90% efficacy could be achieved when PEP was initiated 48 hours post-exposure and taken for at least 14–28 days, depending on the efficacy of the third-drug component. When investigating PrEP-PEP transitions, we observed that preceding PrEP can (1) contribute directly to prophylactic efficacy, and (2) boost subsequent PEP efficacy by delaying initial viral dynamics and building-up drug concentrations, overall facilitating self-managed transitioning between PrEP and PEP.

Conclusions

Our study confirms the critical role of early (< 48 hours) PEP initiation, preferably with three drugs taken for 28 days. Self-start with TDF/FTC and later addition of a third drug is better than not self-starting. Furthermore, our study highlights the synergy between recent PrEP intake and PEP and may help to inform recommendations on PEP use.

Dihydroorotate dehydrogenase (DHODH) is a key enzyme in the pyrimidine biosynthesis pathway, playing a critical role in cellular processes and offering therapeutic potential for antiviral, antineoplastic, and autoimmune treatments. Human DHODH (HsDHODH) utilizes ubiquinone as a second substrate, positioning its quinone-binding site as a promising target for inhibitor development. Lapachol, a natural naphthoquinone, has gained prominence as a valuable natural product for the discovery of novel therapeutic agents, thanks to its wide range of biological activities. In this study, we present the first crystal structure of HsDHODH in complex with lapachol, providing valuable insights into the interactions between this natural product and the enzyme. The structure reveals key binding interactions that mediate lapachol’s affinity for HsDHODH and validates previously proposed computational models. Complementary molecular dynamics simulations further highlight the stability of the complex and the importance of water-mediated interactions in ligand binding. These findings enhance our understanding of how naphthoquinone derivatives, such as lapachol, interact with class 2 DHODHs, offering a foundation for the design of optimized inhibitors for therapeutic applications. By integration of structural and computational data, this study contributes to the rational design of novel HsDHODH inhibitors, paving the way for future exploration of lapachol and its derivatives in drug discovery.

We study a stroboscopic quantum Ising model with Fibonacci dynamics. We use its boundary spin correlation functions in long but finite chains to identify regions in the phase diagram which exhibit Majorana zero modes (MZM) as well as Majorana golden-ratio modes (MGM). We find that these regions evolve in a self-similar manner with increasing simulation time and identify the self-similarity transform which governs this evolution of the phase diagram. Integrability-breaking perturbations lead to a temporal decay of the boundary spin correlations, ultimately limiting the self-similarity of the phase diagram. Our predictions are testable with current quantum information processors.

Most studies on residential segregation in China have primarily relied on decennial population census data, which lacks the granularity and timeliness needed to capture segregation dynamics with higher frequency. Drawing on georeferenced housing market transaction data between 2012 and 2023 in Shanghai and Beijing, and employing fine-grained spatial segregation analysis techniques, including k-nearest neighbor approaches (k−NN) and modifiable grids, we find that housing segregation by price and size increased between 2012 and 2018, followed by a decline thereafter, particularly in the larger-sized and higher-priced market segments. While segregation levels are generally comparable between the two cities, Shanghai exhibits higher segregation for the top 20 % of apartments, while Beijing shows greater segregation for the bottom 20 %. Segregation is highest for prices, followed by rents, with housing size showing the lowest segregation. Expanding the analysis to 11 major Chinese cities, we suggest that high and rising housing prices are associated with increasing segregation, particularly in cities with lower initial segregation. Methodologically, this paper demonstrates that leveraging big transaction and listing data, alongside utilizing fine-grained spatial analysis, can advance our understanding of urban inequalities.

The interconversion between spin and charge currents is vital for developing spintronics technologies, which require materials with high spin-to-charge-current conversion efficiency (SCC). The alloy IrAl was shown to exhibit a large spin Hall angle at gigahertz frequencies. Here, we use spintronic terahertz emission spectroscopy to investigate terahertz SCC in IrxAl1-x|FM heterostructures with a ferromagnetic layer FM of CoFeB and Ni as a function of the composition ratio x. We observe a strongly x-dependent terahertz-signal amplitude, whereas no change in the dynamics of the ultrafast in-plane charge current is seen. For x=0.48, we find that the SCC efficiency in IrxAl1-x reaches up to 65% of that of Pt. Signals from IrxAl1-x|Ni suggest that orbital contributions to the signal are minor. This study highlights the potential of IrAl alloys for SCC in ultrafast spintronic applications.

Studying wooden objects from ancient Egypt provides valuable insights into past economies, craftsmanship, and trade networks. However, traditional wood identification methods are often invasive, restricting research on fragile and museum-conserved items. Here, we present WoodScope, an interdisciplinary approach combining visual, macroscopic, and microscopic techniques to enhance the identification accuracy of ancient Egyptian wooden objects while preserving their integrity. Applied to 187 nearly 4000-year-old objects from diverse funerary contexts, WoodScope revealed significant links between material choices and cultural practices, including the first documented use of grape wood in a funerary cow model. This approach bridges preservation ethics, scientific precision and challenges related to object accessibility, offering a transformative framework for studying ancient wooden objects, advancing archaeological research, and informing conservation strategies for ancient Egypt’s cultural heritage.

Measurement of Anti-Müllerian hormone (AMH) in female dogs is becoming increasingly important in clinical practice. It has been shown earlier that concentrations vary throughout the estrous cycle. AMH concentrations are known to be high during proestrus and estrus, then decrease during the luteal phase and anestrus. Aim of this study was to investigate variations during pregnancy and lactation. Therefore, blood samples were analyzed from 40 pregnant and 19 non-pregnant privately owned dogs of various breeds. One sample was collected from each dog during estrus, three samples during pregnancy, one at three weeks in lactation, and one after weaning. The measured concentrations were compared with those from the non-pregnant dogs, from which samples were collected at the same corresponding time points. AMH concentration in pregnant dogs was highest in estrus (0.63 ng/ml, quartiles 0.40 and 0.87) and remained relatively high during pregnancy. At sampling during lactation the median concentration was significantly lower compared with all other time points (median 0.19 ng/ml, quartiles 0.14 and 0.26). After weaning, AMH increased again to 0.30 ng/ml (quartiles 0.24 and 0.50). During late pregnancy, lactation and after weaning, the AMH concentration was lower in the pregnant dogs compared with the non-pregnant ones. In addition, the significant decline of AMH concentration in pregnant dogs during lactation was not present in the non-pregnant dogs. It can be hypothesized that higher prolactin concentrations may reduce AMH synthesis by inhibiting the secretion of GnRH, FSH, and LH in mammals. In our study we found moderate negative correlation between bodyweight or the number of suckling puppies and AMH concentration. However, since no assay was available, prolactin concentrations were not measured. These findings indicate that pregnancy and lactation status should be considered when interpreting AMH concentrations in clinical practice.

Controlling protein–protein interactions is critical for dissecting signaling pathways, especially those initiated by ligand-receptor interactions, which alter receptor oligomerization and drive downstream signaling cascades. Traditional methods for driving protein–protein complexes use antibodies that face limitations in terms of stoichiometry, geometric rigidity, and antibody specificity. Chemical inducers of dimerization (CIDs) for fusion proteins such as HaloTag (Halo) and SNAP-Tags (SNAP) offer precise and covalent control of protein proximities, overcoming limitations of antibody-dependent methods. In this study, we expand the toolkit of Halo and SNAP CIDs with (1) benzylguanine (BG) and HaloTag ligand (HTL) crosslinkers featuring varying polyethylene glycol linker lengths and update this kit with (2) a FRET-based dimerizing sensor to induce and verify protein proximity. Here we establish our CIDs on extracellularly Halo- and SNAP-tagged TGFβ, BMP, neurotrophic factor, and metabotropic glutamate receptors, thereby elucidating the signaling potential of ligand-independent dimerization in a heteromeric fashion.

In this study, we report our recent findings on the synthesis and reactivity of a novel 1,2,3-triazolin-5-imine type mesoionic imine-carbodiimide (MII-CDI) adduct. Unlike reported NHC-CDI adducts, formed by the reactions of N-heterocyclic carbene (NHC) with CDI, these zwitterionic compounds undergo a spontaneous 1,3 H-shift, resulting in guanidine-type compounds. The mechanism of this 1,3-H shift has been investigated through quantum chemical calculations. The MII-CDI adduct serves as a valuable synthon for the synthesis of mesoionic carbene-acyclic diamino carbene (MIC-ADC)-based nitreone (N(I)) compounds. We have conducted a detailed investigation into the electronic properties, chemical reactivity, and electrochemical behaviour of these nitreone (N(I)) compounds. Additionally, the potential of these MII-CDI adducts as guanidinate ligands is explored. Our investigations here display the distinct reactivities of MII in contrast to their N-heterocyclic imine (NHI) congeners.

We construct exact ground states of the J1-J3b classical Heisenberg model on the pyrochlore lattice in the presence of a magnetic field. They are noncoplanar multi-Q spin configurations with a large magnetic unit cell that generalize the previously found coplanar sublattice pairing states. Using linear spin-wave theory, we show that entropy favors these multi-Q states at low temperatures in high magnetic fields. This is confirmed by Monte Carlo simulations, and a phase diagram is constructed. We also calculate the zero-temperature dynamical structure factor. Besides the usual Goldstone modes associated with the ordering Qs, we find high intensity gapless modes at momenta where there are no Bragg peaks.

Recent years have witnessed a surge of experimental and theoretical interest in controlling the properties of matter, such as its chemical reactivity, by confining it in optical cavities, where the enhancement of the light–matter coupling strength leads to the creation of hybrid light–matter states known as polaritons. However, ab initio calculations that account for the quantum nature of both the electromagnetic field and matter are challenging and have only started to be developed in recent years. We introduce a deep learning variational quantum Monte Carlo method to solve the electronic and photonic Schrödinger equations of molecules trapped in optical cavities. We extend typical electronic neural network wave function ansätze to describe joint fermionic and bosonic systems, i.e., electron–photon systems, in a quantum Monte Carlo framework. We apply our method to hydrogen molecules in a cavity, computing both ground and excited states. We assess their energy, dipole moment, charge density shift due to the cavity, the state of the photonic field, and the entanglement developed between the electrons and photons. Where possible, we compare our results with more conventional quantum chemistry methods proposed in the literature, finding good qualitative agreement, thus extending the range of scientific problems that can be tackled using machine learning techniques.

Cemeteries, traditionally reserved for mourning, are also valuable urban green spaces contributing to ecosystem services, wildlife habitats, and human well-being. This study focuses on London’s Magnificent Seven cemeteries, which vary in habitat and usage, from semi-wild nature reserves to active burial sites. In autumn 2023, we conducted non-participatory observations of human activities and wildlife presence, and surveyed visitors (n = 176) regarding their perceptions of birds (crows, magpies, parakeets, robins, owls, blackbirds), mammals (fox, grey squirrel, bats, rats, cats, hedgehogs, rabbits, deer) and activities (e.g. biking, dog walking, picnicking). Our observations showed that visitors primarily engaged in solitary or accompanied walks. Observed animals included crows (Corvus spp.) and pigeons (Columba spp.), as well as grey squirrels (Sciurus carolinensis) and foxes (Vulpes vulpes). Regarding visitor perceptions, wildlife was generally perceived positively, with invasive ring-necked parakeets (Psittacula krameri) as well as non-native grey squirrels occasionally evoking negative perceptions. Activities like grave visiting and solitary walks are widely accepted, while picnicking, biking and sports are less favored, with younger participants and locals generally being more accepting to more lively activities. Urban cemeteries play multifunctional roles beyond mourning, offering green spaces for recreation and wildlife habitats. This study highlights the importance of recognizing cemeteries as critical urban refuges for both people and wildlife, demonstrating that sacred grounds and urban wilderness can coexist to create restorative green spaces in busy cities. The future survival of inner-city cemeteries depends on their rejuvenation and integration into local communities, enabling them to act as nature-based solutions to withstand development pressures.

In this article, we explore reproductive decision-making among adults with a rare genetic chronic disease: Cystic Fibrosis (CF). CF is hereditary and can be tested for at various moments in prospective parent's reproductive trajectory, namely before, during or after pregnancy. Based on 15 interviews with persons with CF in Germany who at the time of the interviews were considering having a child, were pregnant, already had a child, or had decided against having a child, we show that people with rare genetic chronic diseases face challenges that go far beyond those all young parents have to deal with. Persons with a rare and chronic disease are forced to anticipate the future beyond the common imagination of what kind of person their child will become. On the one hand, they must take into consideration their own future, that is the state and progress of their own disease. This may limit their ability to actively parent at all and in addition may be negatively impacted by the everyday efforts and struggles of parenting. On the other, as they potentially pass on their disease to their child, they also have to take into account their child's future, its wellbeing and future life. This includes considerations regarding what constitutes a good and liveable life.

This paper examines the evolving role of German Performing Rights Organizations (PROs) in the context of technological advancements and societal shifts, focusing on the tensions and transformations. Employing an interdisciplinary approach encompassing history, sociology, and computer science, the study analyzes three case studies spanning from the early 20th century to the present day. These cases explore tensions arising from monitoring practices in the 1930s, conflicts between the German PRO GEMA and actors of the underground electronic dance music scene, and the challenges posed by artificial intelligence (AI) to collective copyright management. The analysis highlights how PROs must adapt their core tasks – licensing, revenue collection, royalty distribution, and usage monitoring – to address technological disruptions and maintain cultural diversity. The paper concludes by advocating for increased transparency, technological openness, and interdisciplinary research to guide the future development of PRO business models in a rapidly changing media landscape.

Automobiles depend on fossil resources – both to create the device and to power it. The automotive industry has decreased this dependency on fossil fuels by developing more fuel-efficient combustion engines, lightweight designs, and biofuels. The rise of battery electric vehicles (BEVs) offers the chance to reduce the fossil footprint by avoiding fuel combustion and exhaust emission. Disruptive approaches toward a truly sustainable car are far from being market-ready. To reach a completely sustainable car, the automotive industry must address the carbon footprint of material production, which is based in the chemical sector. The automotive and chemical industries have to adopt closed-loop thinking, utilize renewable resources for biodegradables, as well as develop novel materials and designs for efficient recycling. Disruptive approaches can arise from predictive models that can accelerate chemical research and enable the discovery of sustainable materials with desirable recycling properties. Integrating generative artificial intelligence (AI) with high-throughput experimental validation will shorten material development cycles and advance the transition to more sustainable products. Moving toward a fully recyclable car is aligning research and development efforts from the chemical sector to the automotive industry and beyond, presenting a giant leap toward a circular economy.

Amyloid aggregation intermediates are metastable protein species linked to toxicity and disease pathology and are emerging as therapeutic targets. These oligomeric aggregates are ill-characterized and their low concentration, low stability, and high polydispersity pose complex analytical challenges. We here present the use of mass spectrometry (MS)-based approaches to capture and isolate specific protein aggregates, effectively performing gas-phase purification, prior to structural characterization. This allows for studies of individual oligomeric states separated in high resolution according to assembly state and conformation, which is unattainable using condensed-phase techniques. We describe how intact protein assemblies can be separated, manipulated, and spectroscopically analyzed in the gas phase and highlight how this has recently been used to gain unique structural insights into oligomeric aggregates.

Revisamos ejemplares de herbario y bibliografía referente al ají de páramo, Drimys granadensis, para Bogotá, con el fin de realizar una descripción de la especie para el área y sintetizar la información conocida sobre su morfología, taxonomía, distribución, ecología y usos reportados. Buscamos actualizar la información disponible para esta especie en Bogotá a fin de promover nuevas investigaciones y acciones para su manejo y conservación.

Chemically stable, lanthanide-based photon upconversion micro- and nanoparticles (UCNPs) with their characteristic multicolor emission bands in the ultraviolet (UV), visible (vis), near-infrared (NIR), and short-wave infrared (SWIR) are promising optical reporters and barcoding tags. To assess the applicability of UCNPs for the monitoring of early stage cement hydration processes and as authentication tags for cementitious materials, we screened the evolution of the luminescence of self-made core-only NaYF4:Yb,Er UCNPs and commercial μm-sized Y2O2S:Yb,Er particles during the first stages of cement hydration, which largely determines the future properties of the hardened material. Parameters explored from the UCNP side included particle size, morphology, surface chemistry or coating, luminescence properties, and concentration in different cement mixtures. From the cement side, the influence of the mineral composition of the cement matrix was representatively examined for ordinary Portland cement (OPC) and its constituents tricalcium aluminate (C3A), tricalcium silicate (C3S), and gypsum at different water to cement ratios. Based on reflection and luminescence measurements, enabling online monitoring, which were complemented by XRD and isothermal heat-flow calorimetric measurements to determine whether the incorporation of these particles could impair cement hydration processes, well suited lanthanide particle reporters could be identified as well as application conditions. In addition, thereby the reporter influence on cement hydration kinetics could be minimized while still preserving a high level of information content. The best performance for the luminescence probing of changes during early stage cement hydration processes was observed for 25 nm-sized oleate (OA)-coated UCNPs added in a concentration of 0.1 wt %. Higher UCNP amounts of 1.0 wt % delayed cement hydration processes size- and surface coating-specifically in the first 24 h. Subsequent luminescence stability screening studies performed over a period of about one year support the applicability of UCNPs as optical authentication tags for construction materials.

In this paper, we introduce a class of highly entangled real quantum states that cannot be approximated by circuits with log -many non-Clifford gates and prove that Bell sampling enables efficient cross-device verification (or distributed inner product estimation) for these states. That is, two remote parties can estimate the inner product tr⁡(𝜌⁢𝜎) , each having black-box access to copies of a state 𝜌 (or respectively 𝜎 ) in this class. This is significant because it is clear that this task can be achieved in those cases (such as low entanglement or low non-Clifford gate count) where one can independently learn efficient classical descriptions of each state using established techniques and share the description to compute the overlap. Instead, our results demonstrate that this is possible even in more complex scenarios where these “learn and share” methods are insufficient. Our proposal is scalable, as it just requires a number of two-copy Bell measurements and single-copy Pauli measurements that grows polynomially with both the number of qubits and the desired inverse error, and can be implemented in the near term. Moreover, the required number of samples can be efficiently experimentally determined by the parties in advance, and our findings are robust against preparation errors. We anticipate that these results could have applications in quantum cryptography and verification.

After the magma ocean state, secondary atmospheres build up via early volcanic degassing of planetary interiors. The terrestrial planets Venus, Earth, and Mars are believed to have originated from similar source material but reveal distinct present-day atmospheric compositions, pressures, and temperatures. To investigate how such diverse atmospheres emerge, we have built a three-step model coupling mantle and atmospheric composition. The model incorporates mantle melting, melt ascent, and volcanic degassing. Additionally, it includes atmospheric equilibrium chemistry, taking into account processes such as water condensation and hydrogen escape. Key parameters such as mantle oxygen fugacity, melt production rates, surface temperature, and volatile abundance in the mantle, were varied to understand their impact on atmospheric composition and pressure. For reduced mantles with redox states below IW +1, atmospheric pressures remain strongly limited to a maximum of 2 bar due to the outgassing of predominantly light species that are prone to atmospheric escape or condensation. Above IW +1, atmospheric pressure can reach several tens of bars depending on the outgassing efficiency. For high-pressure atmospheres, CO2 is the main atmospheric species observed in our models. For oxidized low-pressure atmospheres, depending on temperature, atmospheres can be either waterrich or also CO2-dominated. For reducing atmospheres, nitrogen species tend to dominate the atmospheres, with NH3 for colder atmospheres and N2 for warmer atmospheres. CH4 becomes dominant only in a narrow parameter space at redox states around IW +0.5 to IW +2 and is favored by lower atmospheric temperatures.