Abstract This perspective offers a personal reflection on the evolution, current status, and open challenges of quantum chemistry in the context of large molecular systems. Beginning with Dirac’s famous 1929 prophecy, I revisit the historical trajectory of our discipline, from the development of early conceptual models to the emergence of density functional theory and correlated wavefunction methods. While enormous progress has been made in algorithmic sophistication, enabling accurate calculations on systems with thousands of atoms, I argue that accurate energies alone do not solve the entirety of chemical problems. Real-world applications demand more than electronic structure: solvation, entropy, conformational complexity, and the sheer complexity of large molecules challenge our methods and our assumptions. Equally important are the conceptual and philosophical tensions that continue to shape the field, especially the difficult balance between prediction and understanding. I advocate for a more integrative approach that values models, insight, and falsifiability alongside numerical precision. Finally, I briefly consider the emerging role of machine learning and the implications of automation for the future of theory. This article is not a review but a dialogue – with the field, with its history, and with its practitioners.

The vertebrate brain must balance internally generated predictions with constraints of environmental affordances. This balance constitutes a fundamental principle of neural organization that underwrites cortical computation. Using the prosomeric model of the neuraxis, we show how dorsalizing and ventralizing morphogenetic gradients specify excitatory and inhibitory lineages during development, establishing the functional architecture of active affordance. These developmental asymmetries are elaborated through telencephalic expansion, pallial-subpallial integration, and laminar differentiation of the neocortex, as described by the structural model. We demonstrate that motor control emerges within a sensory-predictive architecture due to the alar origin of the telencephalon and that increasing excitatory-inhibitory complementarity within the mammalian neocortex enables selective, context-sensitive action. Subpallial and diencephalic systems provide inhibitory governance over cortical action tendencies, supporting policy evaluation and selection in the framework of active inference. At the base of this hierarchy, the hypothalamus integrates homeostatic and allostatic signals to bias the landscape of affordances, shaping the likelihood of action policies. Together, these findings establish active affordance as a developmental and evolutionary framework linking prosomeric neurodevelopment, cortical architecture, subcortical control, and adaptive behavior. Active inference is thereby situated as the mature cortical expression of a conserved biological solution to acting in an uncertain world.

We aim to investigate the spatial experience of patients with chronic scotomas caused by lesion to early visual cortex, including primary visual cortex (V1) and adjacent extrastriate visual areas. These experiments are conducted as part of an adversarial collaboration testing contrasting theories of consciousness: Integrated Information Theory (IIT) and two Predictive Processing accounts, Active Inference (AI) and Neurorepresentationalism (NREP). The central question is whether lesions to early visual cortex alter the experienced extent of visual space itself, or instead primarily disrupt stimulus content within an otherwise preserved visual space. To address this, we use paradigms in which patients estimate distances or spatial extents that either span a scotomatous region or fall entirely within intact visual field locations. Psychometric functions relating perceived and physical extent are modeled to estimate shifts in the point of subjective equality (PSE). According to IIT, lesions to early visual cortex, including V1 and occipital exstrastriate cortex, should lead to systematic reductions in perceived spatial extent across the scotoma (negative PSE shifts), reflecting a contraction of experienced space. In contrast, Predictive Processing accounts posit that higher-level predictive mechanisms preserve spatial structure despite loss of early input, predicting little or no systematic contraction (with NREP allowing limited context-dependent effects). By quantifying distortions in perceived spatial extent, this protocol aims to distinguish between these competing theoretical predictions.

Objetivos: El presente estudio describe las características clínicas y epidemiológicas de las pacientes con cáncer de mama a quienes se les aplicó la técnica del ganglio centinela en el Servicio de Seno y Tejidos Blandos del Instituto Nacional de Cancerología (INC), en 10 años de experiencia.Métodos:Serie de casos de pacientes con diagnóstico de cáncer de mama temprano en estadios 0-IIB (T3N0M0), a quienes se les realizó la técnica. A partir de registros de los servicios de Patología, Medicina Nuclear y Cirugía de Seno y Tejidos Blandos del INC, se realizó la captura de datos aplicando un cuestionario previamente elaborado. Resultados: Se tomaron en cuenta 289 casos; las técnicas usadas incluyeron: radio coloides (Tecnecio 99) en 256 casos; colorante, en 5; y ambas técnicas, en los 28 restantes. El ganglio centinela fue identificado en 283 casos, con una tasa de detección del 98,0%. En carcinoma invasor, el tamaño tumoral promedio fue 2,2 cm (DE 1,1). En promedio, fueron resecados 1,5 ganglios (0,99 DE); de estos casos, 85 (30%) fueron metastásicos. Hubo 24 eventos adversos; el más común fue la formación de seroma. La media de seguimiento fue de 647 días (DE 693 días); el porcentaje de pacientes libres de enfermedad al seguimiento, del 94,4%; hubo recaída axilar en 1 paciente.Conclusiones: Según los autores de la experiencia descrita, la técnica de ganglio centinela es segura, pues permite una estadificación adecuada de la axila. Las características tumorales del ganglio centinela en la población objeto de estudio guardan similitud con las reportadas en la literatura mundial.

We developed an in vitro methodology to study trained immunity using murine bone-marrow-derived macrophages stimulated with β-glucan and lipopolysaccharide (LPS). Longitudinal analysis of interleukin (IL)-6 and tumor necrosis factor (TNF) production demonstrates that trained macrophages secrete higher cytokine levels following primary stimulation with β-glucan compared to unstimulated macrophages (step 1). After a resting period, trained macrophages return to basal levels of cytokine production (step 2) but rapidly produce enhanced levels of IL-6 and TNF after secondary stimulation with LPS, compared to macrophages individually stimulated with either β-glucan (step 3) or LPS (step 4) alone. The combined cytokine production of macrophages after single stimulation with β-glucan (stimulus 1) and LPS (stimulus 2) is significantly lower than the cytokine levels produced by trained macrophages sequentially stimulated with both β-glucan and LPS (stimulus 1 + 2) (step 5). These results experimentally reproduce the distinctive functional stages that macrophages undergo during the training process.

Coastal wetlands are critical blue carbon reservoirs, yet the depth-resolved impacts of warming on belowground carbon dynamics remain poorly understood. Over the course of an 8-year in situ experiment, we investigated plant-derived carbon inputs, soil carbon losses via respiration, and microbially mediated carbon fixation across a 60 cm soil profile under a projected 2°C atmospheric warming scenario. Plant carbon fixation (above- and belowground net primary productivity) and soil respiration exhibited synchronized responses to warming, with an initial increase, followed by a decline in the mid-term, and no significant response in the later stages. Soil and microbial respiration stabilized after prolonged exposure to elevated temperatures, as these processes were constrained by substrate availability. In contrast, phospholipid fatty acid profiling, amino sugar biomarkers, and metagenome-assembled genomes consistently indicated a greater than one-third reduction in microbial carbon fixation within subsoils (40-60 cm). Our fully factorial, depth-stratified warming design reveals the particular vulnerability of deep soil microbial carbon retention to long-term climate warming, independent of shifts in plant input or respiratory carbon loss. This work highlights underappreciated pathways influencing soil blue carbon dynamics in a changing world.

Metal–organic frameworks (MOFs), composed of metal nodes coordinated with organic ligands, have emerged as a versatile class of functional materials for next‐generation smart textile systems. Their high surface area, tunable pore chemistry, and modular structural diversity enable multifunctional textile platforms. When integrated into textile substrates, MOFs can retain the properties, breathability, and comfort of fabrics while imparting advanced functionalities significant for sensing, environmental protection, biomedical interfaces, and energy‐related applications. This review provides a comprehensive overview of recent advances in MOF‐integrated smart textiles, focusing on material design principles, integration strategies, and application‐driven performance. Key fabrication approaches including surface coating, in situ growth, post‐synthetic modification, hydrothermal assembly, and emerging printing techniques such as inkjet and electrohydrodynamic jet are critically examined with respect to scalability, durability, and textile compatibility. Representative applications spanning gas and chemical sensing, detoxification, antimicrobial and biomedical functions, energy harvesting, and flexible energy storage are systematically discussed. Finally, current challenges and future opportunities are outlined, highlighting pathways toward scalable, durable, and application‐oriented MOF‐based smart textiles for real‐world applications.

Benthic prokaryotic communities in deep-sea sediments remain poorly studied. They are constrained by organic matter availability and oxygenation in warm deep-sea ecosystems. Here, we investigated benthic prokaryotic communities and carbon uptake in deep Red Sea sediments (218–2415 m seafloor depth), where persistently warm (~21.5 °C) waters and a strong south–north productivity gradient co-occur. Sediment particulate organic carbon (POC), prokaryotic abundance (PA), and [13C]-D-glucose-based carbon uptake and uptake kinetics were examined in two sediment layers (0–1 and 4–5 cm), while bacterial communities were characterized using 16S rRNA gene sequencing of the 0–1 cm layer. Sediment POC, PA, and carbon uptake declined northward, consistent with reduced organic-carbon supply to the seafloor. Bacterial community composition differed significantly across the ~500 m depth associated with the Red Sea oxygen minimum zone (OMZ). Sediments from the relatively low-oxygen upper OMZ-range (200–500 m) had higher sediment POC and PA, and were enriched in putatively anaerobe-associated taxa, whereas deeper sediments (>500 m) below the OMZ exhibited more fragmented co-occurrence networks. These results suggest that organic-carbon availability defines the basin-scale metabolic backdrop, whereas bacterial community differentiation was more clearly resolved between upper OMZ-range and below-OMZ sediments than along latitude alone.

Protonatable nitroxides are electron paramagnetic resonance (EPR) molecular probes employed for pH measurements in bulk aqueous media. The change in the protonation state of the molecule induces a measurable change in the <i>g</i>- and hyperfine (<i>A</i>) parameters used as pH indicators. The quantitative understanding of the origin of the change of the EPR parameters in terms of electronic structure and different solvation patterns is still lacking. Here, we delve into the origins of the changes in the <i>g</i>- and hyperfine (<i>A</i>) parameters of ¹⁴N upon protonation of the heterocyclic nitrogen of the pH-sensitive nitroxide probe HMI (2,2,3,4,5,5-hexamethylimidazolidin-1-oxyl, C₉H₁₉N₂O) by means of combined experimental and theoretical techniques that have been developed and extensively validated in previous works. To establish a molecular-level understanding of the dependency of EPR parameters on the pH of the medium, we considered two limiting cases of deprotonated (pH ≫ p<i>K</i>_a) and protonated (pH ≪ p<i>K</i>_a) states of HMI. We found that, upon protonation of the heterocyclic nitrogen, the change in the electronic structure dominates the pH dependency of isotropic <i>g</i> and <i>A</i> values. Supporting this prominent role of electronic structure modulation, the average shift of EPR observables between the corresponding hydrogen-bonding states of the protonated and unprotonated forms remains constant. Furthermore, the results establish that the hydrogen bonding network structures around the nucleus of interest only marginally change upon protonation, although the populations of corresponding states with given H-bond numbers strongly do. This feature entails an additional, smaller contribution to the relative pH dependency of <i>g</i>^iso and <i>A</i>^iso values over electronic structure modulation upon protonation in a given H-bond state. The findings of this study pave the way to investigating HMI-based labels in peptides and other pH-sensitive EPR probes in protic polar solvents.

Background The overuse and misuse of antibiotics significantly contributes to antimicrobial resistance (AMR). Adverse reactions to antibiotics are well documented, but their impact on patients’ behaviours requires further exploration. Aim To explore how side effects and allergies influence patients’ behaviours to prescribed antibiotic use. Design &amp; setting A mixed-methods explanatory sequential study in England. Method A survey of 1059 adults with prior experience of antibiotic side effects was conducted. Descriptive statistics identified common side effects and behavioural responses, while chi-squared tests explored demographic differences. Focus groups were held with 21 participants, recruited through a research panel. Thematic analysis captured deeper insight into participants’ personal experiences. Results Many antibiotic side effects were identified, presenting shortly after consumption and affecting several aspects of patients’ lives. One-third of respondents (31%, n =325; 95% CI: 28-34%) were unaware of potential side effects beforehand, citing inaccessible patient information leaflets and limited communication from healthcare professionals as barriers. Almost half (42%, n =440; 95% CI: 37-47%) did not complete their antibiotic course following the side effects, with 32% ( n =142; 95% CI: 28-37%) stopping without medical advice. Many allergy diagnoses were made in childhood without follow-up assessments. Conclusion Antibiotic side effects can significantly disrupt patients’ lives and discourage appropriate use of antibiotics. Providing accessible information before prescribing may help manage expectations and support self-management of side effects. Patients with longstanding allergy labels should be encouraged to undergo reassessment to ensure that they are not contributing to AMR by unnecessarily avoiding the use of first-line antibiotics.