Biodiversity loss reduces global terrestrial carbon storage.

Natural ecosystems store large amounts of carbon globally, as organisms absorb carbon from the atmosphere to build large, long-lasting, or slow-decaying structures such as tree bark or root systems. An ecosystem's carbon sequestration potential is tightly linked to its biological diversity. Yet when considering future projections, many carbon sequestration models fail to account for the role biodiversity plays in carbon storage. Here, we assess the consequences of plant biodiversity loss for carbon storage under multiple climate and land-use change scenarios. We link a macroecological model projecting changes in vascular plant richness under different scenarios with empirical data on relationships between biodiversity and biomass. We find that biodiversity declines from climate and land use change could lead to a global loss of between 7.44-103.14 PgC (global sustainability scenario) and 10.87-145.95 PgC (fossil-fueled development scenario). This indicates a self-reinforcing feedback loop, where higher levels of climate change lead to greater biodiversity loss, which in turn leads to greater carbon emissions and ultimately more climate change. Conversely, biodiversity conservation and restoration can help achieve climate change mitigation goals.

Revealing the Singlet Fission Mechanism for a Silane-Bridged Thienotetracene Dimer.

Tetraceno[2,3-b]thiophene is regarded as a strong candidate for singlet fission-based solar cell applications due to its mixed characteristics of tetracene and pentacene that balance exothermicity and triplet energy. An electronically weakly coupled tetraceno[2,3-b]thiophene dimer (Et2Si(TIPSTT)2) with a single silicon atom bridge has been synthesized, providing a new platform to investigate the singlet fission mechanism involving the two acene chromophores. We study the excited state dynamics of Et2Si(TIPSTT)2 by monitoring the evolution of multiexciton coupled triplet states, 1TT to 5TT to 3TT to T1 + S0, upon photoexcitation with transient absorption, temperature-dependent transient absorption, and transient/pulsed electron paramagnetic resonance spectroscopies. We find that the photoexcited singlet lifetime is 107 ps, with 90% evolving to form the TT state, and the complicated evolution between the multiexciton states is unraveled, which can be an important reference for future efforts toward tetraceno[2,3-b]thiophene-based singlet fission solar cells.

Body Composition in Advanced Non-Small Cell Lung Cancer Treated With Immunotherapy.

Importance: The association between body composition (BC) and cancer outcomes is complex and incompletely understood. Previous research in non-small-cell lung cancer (NSCLC) has been limited to small, single-institution studies and yielded promising, albeit heterogeneous, results. Objectives: To evaluate the association of BC with oncologic outcomes in patients receiving immunotherapy for advanced or metastatic NSCLC. Design, Setting, and Participants: This comprehensive multicohort analysis included clinical data from cohorts receiving treatment at the Dana-Farber Brigham Cancer Center (DFBCC) who received immunotherapy given alone or in combination with chemotherapy and prospectively collected data from the phase 1/2 Study 1108 and the chemotherapy arm of the phase 3 MYSTIC trial. Baseline and follow-up computed tomography (CT) scans were collected and analyzed using deep neural networks for automatic L3 slice selection and body compartment segmentation (skeletal muscle [SM], subcutaneous adipose tissue [SAT], and visceral adipose tissue). Outcomes were compared based on baseline BC measures or their change at the first follow-up scan. The data were analyzed between July 2022 and April 2023. Main Outcomes and Measures: Hazard ratios (HRs) for the association of BC measurements with overall survival (OS) and progression-free survival (PFS). Results: A total of 1791 patients (878 women [49%]) with NSCLC were analyzed, of whom 487 (27.2%) received chemoimmunotherapy at DFBCC (DFBCC-CIO), 825 (46.1%) received ICI monotherapy at DFBCC (DFBCC-IO), 222 (12.4%) were treated with durvalumab monotherapy on Study 1108, and 257 (14.3%) were treated with chemotherapy on MYSTIC; median (IQR) ages were 65 (58-74), 66 (57-71), 65 (26-87), and 63 (30-84) years, respectively. A loss in SM mass, as indicated by a change in the L3 SM area, was associated with worse oncologic outcome across patient groups (HR, 0.59 [95% CI, 0.43-0.81] and 0.61 [95% CI, 0.47-0.79] for OS and PFS, respectively, in DFBCC-CIO; HR, 0.74 [95% CI, 0.60-0.91] for OS in DFBCC-IO; HR, 0.46 [95% CI, 0.33-0.64] and 0.47 [95% CI, 0.34-0.64] for OS and PFS, respectively, in Study 1108; HR, 0.76 [95% CI, 0.61-0.96] for PFS in the MYSTIC trial). This association was most prominent among male patients, with a nonsignificant association among female patients in the MYSTIC trial and DFBCC-CIO cohorts on Kaplan-Meier analysis. An increase of more than 5% in SAT density, as quantified by the average CT attenuation in Hounsfield units of the SAT compartment, was associated with poorer OS in 3 patient cohorts (HR, 0.61 [95% CI, 0.43-0.86] for DFBCC-CIO; HR, 0.62 [95% CI, 0.49-0.79] for DFBCC-IO; and HR, 0.56 [95% CI, 0.40-0.77] for Study 1108). The change in SAT density was also associated with PFS for DFBCC-CIO (HR, 0.73; 95% CI, 0.54-0.97). This was primarily observed in female patients on Kaplan-Meier analysis. Conclusions and Relevance: The results of this multicohort study suggest that loss in SM mass during systemic therapy for NSCLC is a marker of poor outcomes, especially in male patients. SAT density changes are also associated with prognosis, particularly in female patients. Automated CT-derived BC measurements should be considered in determining NSCLC prognosis.

Tetracene Diacid Aggregates for Directing Energy Flow toward Triplet Pairs.

A comprehensive investigation of the solution-phase photophysics of tetracene bis-carboxylic acid [5,12-tetracenepropiolic acid (Tc-DA)] and its related methyl ester [5,12-tetracenepropynoate (Tc-DE)], a non-hydrogen-bonding counterpart, reveals the role of the carboxylic acid moiety in driving molecular aggregation and concomitant excited-state behavior. Low-concentration solutions of Tc-DA exhibit similar properties to the popular 5,12-bis((triisopropylsilyl)ethynl)tetracene, but as the concentration increases, evidence for aggregates that form excimers and a new mixed-state species with charge-transfer (CT) and correlated triplet pair (TT) character is revealed by transient absorption and fluorescence experiments. Aggregates of Tc-DA evolve further with concentration toward an additional phase that is dominated by the mixed CT/TT state which is the only state present in Tc-DE aggregates and can be modulated with the solvent polarity. Computational modeling finds that cofacial arrangement of Tc-DA and Tc-DE subunits is the most stable aggregate structure and this agrees with results from 1H NMR spectroscopy. The calculated spectra of these cofacial dimers replicate the observed broadening in ground-state absorption as well as accurately predict the formation of a near-UV transition associated with a CT between molecular subunits that is unique to the specific aggregate structure. Taken together, the results suggest that the hydrogen bonding between Tc-DA molecules and the associated disruption of hydrogen bonding with solvent produce a regime of dimer-like behavior, absent in Tc-DE, that favors excimers rather than CT/TT mixed states. The control of aggregate size and structure using distinct functional groups, solute concentration, and solvent in tetracene promises new avenues for its use in light-harvesting schemes.

Global trends and scenarios for terrestrial biodiversity and ecosystem services from 1900 to 2050.

Based on an extensive model intercomparison, we assessed trends in biodiversity and ecosystem services from historical reconstructions and future scenarios of land-use and climate change. During the 20th century, biodiversity declined globally by 2 to 11%, as estimated by a range of indicators. Provisioning ecosystem services increased several fold, and regulating services decreased moderately. Going forward, policies toward sustainability have the potential to slow biodiversity loss resulting from land-use change and the demand for provisioning services while reducing or reversing declines in regulating services. However, negative impacts on biodiversity due to climate change appear poised to increase, particularly in the higher-emissions scenarios. Our assessment identifies remaining modeling uncertainties but also robustly shows that renewed policy efforts are needed to meet the goals of the Convention on Biological Diversity.

Ultrafast Charge Transfer Cascade in a Mixed-Dimensionality Nanoscale Trilayer.

Innovation in optoelectronic semiconductor devices is driven by a fundamental understanding of how to move charges and/or excitons (electron-hole pairs) in specified directions for doing useful work, e.g., for making fuels or electricity. The diverse and tunable electronic and optical properties of two-dimensional (2D) transition metal dichalcogenides (TMDCs) and one-dimensional (1D) semiconducting single-walled carbon nanotubes (s-SWCNTs) make them good quantum confined model systems for fundamental studies of charge and exciton transfer across heterointerfaces. Here we demonstrate a mixed-dimensionality 2D/1D/2D MoS2/SWCNT/WSe2 heterotrilayer that enables ultrafast photoinduced exciton dissociation, followed by charge diffusion and slow recombination. Importantly, the heterotrilayer serves to double charge carrier yield relative to a MoS2/SWCNT heterobilayer and also demonstrates the ability of the separated charges to overcome interlayer exciton binding energies to diffuse from one TMDC/SWCNT interface to the other 2D/1D interface, resulting in Coulombically unbound charges. Interestingly, the heterotrilayer also appears to enable efficient hole transfer from SWCNTs to WSe2, which is not observed in the identically prepared WSe2/SWCNT heterobilayer, suggesting that increasing the complexity of nanoscale trilayers may modify dynamic pathways. Our work suggests "mixed-dimensionality" TMDC/SWCNT based heterotrilayers as both interesting model systems for mechanistic studies of carrier dynamics at nanoscale heterointerfaces and for potential applications in advanced optoelectronic systems.

Mapping the planet's critical areas for biodiversity and nature's contributions to people.

Meeting global commitments to conservation, climate, and sustainable development requires consideration of synergies and tradeoffs among targets. We evaluate the spatial congruence of ecosystems providing globally high levels of nature's contributions to people, biodiversity, and areas with high development potential across several sectors. We find that conserving approximately half of global land area through protection or sustainable management could provide 90% of the current levels of ten of nature's contributions to people and meet minimum representation targets for 26,709 terrestrial vertebrate species. This finding supports recent commitments by national governments under the Global Biodiversity Framework to conserve at least 30% of global lands and waters, and proposals to conserve half of the Earth. More than one-third of areas required for conserving nature's contributions to people and species are also highly suitable for agriculture, renewable energy, oil and gas, mining, or urban expansion. This indicates potential conflicts among conservation, climate and development goals.

Mapping microarchitectural degeneration in the dilated ascending aorta with ex vivo diffusion tensor imaging.

Aims: Thoracic aortic aneurysms (TAAs) carry a risk of catastrophic dissection. Current strategies to evaluate this risk entail measuring aortic diameter but do not image medial degeneration, the cause of TAAs. We sought to determine if the advanced magnetic resonance imaging (MRI) acquisition strategy, diffusion tensor imaging (DTI), could delineate medial degeneration in the ascending thoracic aorta. Methods and results: Porcine ascending aortas were subjected to enzyme microinjection, which yielded local aortic medial degeneration. These lesions were detected by DTI, using a 9.4 T MRI scanner, based on tensor disorientation, disrupted diffusion tracts, and altered DTI metrics. High-resolution spatial analysis revealed that fractional anisotropy positively correlated, and mean and radial diffusivity inversely correlated, with smooth muscle cell (SMC) and elastin content (P < 0.001 for all). Ten operatively harvested human ascending aorta samples (mean subject age 61.6 ± 13.3 years, diameter range 29-64 mm) showed medial pathology that was more diffuse and more complex. Nonetheless, DTI metrics within an aorta spatially correlated with SMC, elastin, and, especially, glycosaminoglycan (GAG) content. Moreover, there were inter-individual differences in slice-averaged DTI metrics. Glycosaminoglycan accumulation and elastin degradation were captured by reduced fractional anisotropy (R2 = 0.47, P = 0.043; R2 = 0.76, P = 0.002), with GAG accumulation also captured by increased mean diffusivity (R2 = 0.46, P = 0.045) and increased radial diffusivity (R2 = 0.60, P = 0.015). Conclusion: Ex vivo high-field DTI can detect ascending aorta medial degeneration and can differentiate TAAs in accordance with their histopathology, especially elastin and GAG changes. This non-destructive window into aortic medial microstructure raises prospects for probing the risks of TAAs beyond lumen dimensions.

Global spatially explicit yield gap time trends reveal regions at risk of future crop yield stagnation.

Yield gaps, here defined as the difference between actual and attainable yields, provide a framework for assessing opportunities to increase agricultural productivity. Previous global assessments, centred on a single year, were unable to identify temporal variation. Here we provide a spatially and temporally comprehensive analysis of yield gaps for ten major crops from 1975 to 2010. Yield gaps have widened steadily over most areas for the eight annual crops and remained static for sugar cane and oil palm. We developed a three-category typology to differentiate regions of 'steady growth' in actual and attainable yields, 'stalled floor' where yield is stagnated and 'ceiling pressure' where yield gaps are closing. Over 60% of maize area is experiencing 'steady growth', in contrast to ∼12% for rice. Rice and wheat have 84% and 56% of area, respectively, experiencing 'ceiling pressure'. We show that 'ceiling pressure' correlates with subsequent yield stagnation, signalling risks for multiple countries currently realizing gains from yield growth.

DAMM for the detection and tracking of multiple animals within complex social and environmental settings.

Accurate detection and tracking of animals across diverse environments are crucial for behavioral studies in various disciplines, including neuroscience. Recently, machine learning and computer vision techniques have become integral to the neuroscientist's toolkit, enabling high-throughput behavioral studies. Despite advancements in localizing individual animals in simple environments, the task remains challenging in complex conditions due to intra-class visual variability and environmental diversity. These limitations hinder studies in ethologically-relevant conditions, such as when animals are concealed within nests or in obscured environments. Moreover, current tools are laborious and time-consuming to employ, requiring extensive, setup-specific annotation and model training/validation procedures. To address these challenges, we introduce the 'Detect Any Mouse Model' (DAMM), a pretrained object detector for localizing mice in complex environments, capable of robust performance with zero to minimal additional training on new experimental setups. Our approach involves collecting and annotating a diverse dataset that encompasses single and multi-housed mice in various lighting conditions, experimental setups, and occlusion levels. We utilize the Mask R-CNN architecture for instance segmentation and validate DAMM's performance with no additional training data (zero-shot inference) and with few examples for fine-tuning (few-shot inference). DAMM excels in zero-shot inference, detecting mice, and even rats, in entirely unseen scenarios and further improves with minimal additional training. By integrating DAMM with the SORT algorithm, we demonstrate robust tracking, competitively performing with keypoint-estimation-based methods. Finally, to advance and simplify behavioral studies, we made DAMM accessible to the scientific community with a user-friendly Python API, shared model weights, and a Google Colab implementation.

Land-Use Decisions Have Substantial Air Quality Health Effects.

Understanding how best to use limited land without compromising food security, health, and beneficial ecosystem functions is a critical challenge of our time. Ecosystem service assessments increasingly inform land-use decisions but seldom include the effects of land use on air quality, the largest environmental health risk. Here, we estimate and value the air quality health effects of potential land-use policies and projected trends in the United States, alongside carbon sequestration and economic returns to land, until 2051. We show that air quality health effects are of first-order importance in land-use decisions, often larger in value than carbon sequestration and economic returns combined. When air quality is properly accounted for, policies that appeared beneficial are shown to be detrimental and vice versa. Land-use-driven air quality impacts are largely from agricultural emissions and biogenic forest emissions, although incentives for reduced deforestation remain beneficial overall. Without evaluating air quality, we are unable to determine whether land-use decisions make us better or worse off.

Molecular Control of Triplet-Pair Spin Polarization and Its Optoelectronic Magnetic Resonance Probes.

ConspectusPreparing and manipulating pure magnetic states in molecular systems are the key initial requirements for harnessing the power of synthetic chemistry to drive practical quantum sensing and computing technologies. One route for achieving the requisite higher spin states in organic systems exploits the phenomenon of singlet fission, which produces pairs of triplet excited states from initially photoexcited singlets in molecular assemblies with multiple chromophores. The resulting spin states are characterized by total spin (quintet, triplet, or singlet) and its projection onto a specified molecular or magnetic field axis. These excited states are typically highly polarized but exhibit an impure spin population pattern. Herein, we report the prediction and experimental verification of molecular design rules that drive the population of a single pure magnetic state and describe the progress toward its experimental realization.A vital feature of this work is the close partnership among theory, chemical synthesis, and spectroscopy. We begin by presenting our theoretical framework for understanding spin manifold interconversion in singlet fission systems. This theory makes specific testable predictions about the intermolecular structure and orientation relative to an external magnetic field that should lead to pure magnetic state preparation and provides a powerful tool for interpreting magnetic spectra. We then test these predictions through detailed magnetic spectroscopy experiments on a series of new molecular architectures that meet one or more of the identified structural criteria. Many of these architectures rely on the synthesis of molecules with features unique to this effort: rigid bridges between chromophores in dimers, heteroacenes with tailored singlet/triplet-pair energy level matching, or side-group engineering to produce specific crystal structures. The spin evolution of these systems is revealed through our application and development of several magnetic resonance methods, each of which has different sensitivities and relevance in environments relevant to quantum applications.Our theoretical predictions prove to be remarkably consistent with our experimental results, though experimentally meeting all the structural prescriptions demanded by theory for true pure-state preparation remains a challenge. Our magnetic spectra agree with our model of triplet-pair behavior, including funneling of the population to the ms = 0 magnetic sublevel of the quintet under specified conditions in dimers and crystals, showing that this phenomenon is subject to control through molecular design. Moreover, our demonstration of novel and/or highly sensitive detection mechanisms of spin states in singlet fission systems, including photoluminescence (PL), photoinduced absorption (PA), and magnetoconductance (MC), points the way toward both a deeper understanding of how these systems evolve and technologically feasible routes toward experiments at the single-molecule quantum limit that are desirable for computational applications.

Vaxign-DL: A Deep Learning-based Method for Vaccine Design and its Evaluation.

Reverse vaccinology (RV) provides a systematic approach to identifying potential vaccine candidates based on protein sequences. The integration of machine learning (ML) into this process has greatly enhanced our ability to predict viable vaccine candidates from these sequences. We have previously developed a Vaxign-ML program based on the eXtreme Gradient Boosting (XGBoost). In this study, we further extend our work to develop a Vaxign-DL program based on deep learning techniques. Deep neural networks assemble non-linear models and learn multilevel abstraction of data using hierarchically structured layers, offering a data-driven approach in computational design models. Vaxign-DL uses a three-layer fully connected neural network model. Using the same bacterial vaccine candidate training data as used in Vaxign-ML development, Vaxign-DL was able to achieve an Area Under the Receiver Operating Characteristic of 0.94, specificity of 0.99, sensitivity of 0.74, and accuracy of 0.96. Using the Leave-One-Pathogen-Out Validation (LOPOV) method, Vaxign-DL was able to predict vaccine candidates for 10 pathogens. Our benchmark study shows that Vaxign-DL achieved comparable results with Vaxign-ML in most cases, and our method outperforms Vaxi-DL in the accurate prediction of bacterial protective antigens.

Optically Addressing Exciton Spin and Pseudospin in Nanomaterials for Spintronics Applications.

Oriented exciton spins that can be generated and manipulated optically are of interest for a range of applications, including spintronics, quantum information science, and neuromorphic computing architectures. Although materials that host such excitons often lack practical coherence times for use on their own, strategic transduction of the magnetic information across interfaces can combine fast modulation with longer-term storage and readout. Several nanostructure systems have been put forward due to their interesting magneto-optical properties and their possible manipulation using circularly polarized light. These material systems are presented here, namely two-dimensional (2D) systems due to the unique spin-valley coupling properties and quantum dots for their exciton fine structure. 2D magnets are also discussed for their anisotropic spin behavior and extensive 2D magnetic states that are not yet fully understood but could pave the way for emergent techniques of magnetic control. This review also details the experimental and theoretical tools to measure and understand these systems along with a discussion on the progress of optical manipulation of spins and magnetic order transitions.

Multiexciton quintet state populations in a rigid pyrene-bridged parallel tetracene dimer.

The multiexciton quintet state, 5TT, generated as a singlet fission intermediate in pairs of molecular chromophores, is a promising candidate as a qubit or qudit in future quantum information science schemes. In this work, we synthesize a pyrene-bridged parallel tetracene dimer, TPT, with an optimized interchromophore coupling strength to prevent the dissociation of 5TT to two decorrelated triplet (T1) states, which would contaminate the spin-state mixture. Long-lived and strongly spin-polarized pure 5TT state population is observed via transient absorption spectroscopy and transient/pulsed electron paramagnetic resonance spectroscopy, and its lifetime is estimated to be >35 µs, with the dephasing time (T2) for the 5TT-based qubit measured to be 726 ns at 10 K. Direct relaxation from 1TT to the ground state does diminish the overall excited state population, but the exclusive 5TT population at large enough persistent density for pulsed echo determination of spin coherence time is consistent with recent theoretical models that predict such behavior for strict parallel chromophore alignment and large exchange coupling.

Mediating Photochemical Reaction Rates at Lewis Acidic Rare Earths by Selective Energy Loss to 4f-Electron States.

Manifesting chemical differences in individual rare earth (RE) element complexes is challenging due to the similar sizes of the tripositive cations and the corelike 4f shell. We disclose a new strategy for differentiating between similarly sized Dy3+ and Y3+ ions through a tailored photochemical reaction of their isostructural complexes in which the f-electron states of Dy3+ act as an energy sink. Complexes RE(hfac)3(NMMO)2 (RE = Dy (2-Dy) and Y (2-Y), hfac = hexafluoroacetylacetonate, and NMMO = N-methylmorpholine-N-oxide) showed variable rates of oxygen atom transfer (OAT) to triphenylphosphine under ultraviolet (UV) irradiation, as monitored by 1H and 19F NMR spectroscopies. Ultrafast transient absorption spectroscopy (TAS) identified the excited state(s) responsible for the photochemical OAT reaction or lack thereof. Competing sensitization pathways leading to excited-state deactivation in 2-Dy through energy transfer to the 4f electron manifold ultimately slows the OAT reaction at this metal cation. The measured rate differences between the open-shell Dy3+ and closed-shell Y3+ complexes demonstrate that using established principles of 4f ion sensitization may deliver new, selective modalities for differentiating the RE elements that do not depend on cation size.

Controlling Electronic Coupling of Acene Chromophores on Quantum Dot Surfaces through Variable-Concentration Ligand Exchange.

Controlling the binding of functional organic molecules on quantum dot (QD) surfaces and the resulting ligand/QD interfacial structure determines the resulting organic-inorganic hybrid behavior. In this study, we vary the binding of tetracenedicarboxylate ligands bound to PbS QDs cast in thin films by performing solid-state ligand exchange of as-produced bound oleate ligands. We employ comprehensive Fourier-transform infrared (FTIR) analysis coupled with ultraviolet-visible (UV-vis) spectrophotometric measurements, transient absorption, and Density Functional Theory (DFT) simulations to study the QD/ligand surface structure and resulting optoelectronic properties. We find that there are three primary QD/diacid structures, each with a distinct binding mode dictated by the QD-ligand and ligand-ligand intermolecular and steric interactions. They can be accessed nearly independently of one another via different input ligand concentrations. Low concentrations produce mixed oleate/tetracene ligand structures where the tetracene carboxylates tilt toward QD surfaces. Intermediate concentrations produce mixed oleate/tetracene ligand structures with ligand-ligand interactions through intramolecular hydrogen bonding with the ligands perpendicular to the QD surface and weaker QD/ligand electronic interactions. High concentrations result in full ligand exchange, and the ligands tilt toward the surface while the QD film compacts. When the tetracene ligands tilt or lie flat on the QD surface, the benzene ring π-system interacts strongly with the p-orbitals at the PbS surface and produces strong QD-ligand interactions evidenced through QD/ligand state mixing, with a coupling energy of ≈700 meV.

Projecting global oil palm expansion under zero-deforestation commitments: Direct and indirect land use change impacts.

In the last three decades, global production of oil palm has boomed, which has partly come at the expense of tropical rainforests. Recognizing this, many companies operating in the palm oil industry have committed to eliminate deforestation from their operations, often referred to as zero-deforestation commitments (ZDCs). Here, we estimate that if ZDCs are fully adopted and enforced across all sectors and geographies, the global extent of oil palm plantations may be 11 M ha or 40% smaller in 2030 than in a business-as-usual (BAU) scenario that assumes no compliance with ZDCs. As a result of such land-sparing effects, we estimate that 96 M ha of forests are saved from conversion, of which, 17% would otherwise have been converted (directly or indirectly) due to expanding oil palm plantations. Overall, these figures suggest that ZDCs have the potential to deliver major environmental benefits if they are fully adopted and enforced.