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Achieving a net-zero-carbon economy requires significant structural changes in the financial system, driving a substantial shift in investment towards low-carbon assets. This transformation of finance is necessary beyond the aim of climate stabilization but is more broadly required to foster sustainably thriving economies. In this paper, we offer a critical discussion of the positive tipping points that can be activated in the financial system to accelerate a fast, sustainable transition. Identifying and leveraging these critical and positive tipping points can amplify sustainable investments and foster transformative changes in the practices of the financial sector. By aligning expectations, steering herding behaviour, mobilizing public finance, reducing capital costs, reaching low-carbon investment thresholds in developing nations, and enforcing robust financial regulations and policies, the financial system can assume a central role in re-orienting economies onto a net-zero and sustainable course. Taken together, such mechanisms highlight the positive tipping points that can be triggered within sustainable finance and emphasize the necessity of policy interventions to activate and capitalize on these dynamics.

Abstract A timely and well-managed phase-out of bank lending to the fossil fuel sector is critical if Paris climate targets are to remain within reach. Using a systems lens to explore over $7 trillion of syndicated fossil fuel debt, we show that syndicated debt markets are resilient to uncoordinated phase-out scenarios without regulatory limits on banks’ fossil fuel lending. However, with regulation in place, a tipping point emerges as banks sequentially exit the sector and phase-out becomes efficient. The timing of this tipping point depends critically on the stringency of regulatory rules. It is reached sooner in scenarios where systemically important banks lead the phase-out and is delayed without regional coordination, particularly between US, Canadian and Japanese banks.

The raw datasets of oxysterol quantifications from whole cell and mitochondrial fractions of THP-1 monocytes and macrophages, neuronal-like SH-SH5Y cells and human peripheral blood mononuclear cells are presented. Oxysterols were quantified using a new liquid chromatography-mass spectrometry (LC-MS) and multiple reaction monitoring analysis published in the article “A quantitative LC-MS/MS method for analysis of mitochondrial-specific oxysterol metabolism” in Redox Biology [1]. This method showed improved extraction efficiency and recovery of mono and dihydroxycholesterols from cellular matrix. The datasets derived from the three cell lines are included in the appendix. These datasets provide new information about the oxysterol distribution in THP-1 monocytes and macrophages, SH-SY5Y cells and peripheral blood mononuclear cells. These datasets can be used as a guide for oxysterol distribution in the three cell lines for future studies, and can used for future method optimization, and for comparison of oxysterol recovery with other analytical techniques.

Oxysterols are critical regulators of inflammation and cholesterol metabolism in cells. They are oxidation products of cholesterol and may be differentially metabolised in subcellular compartments and in biological fluids. New analytical methods are needed to improve our understanding of oxysterol trafficking and the molecular interplay between the cellular compartments required to maintain cholesterol/oxysterol homeostasis. Here we describe a method for isolation of oxysterols using solid phase extraction and quantification by liquid chromatography-mass spectrometry, applied to tissue, cells and mitochondria.We analysed five monohydroxysterols; 24(S)-hydroxycholesterol, 25-hydroxycholesterol, 27-hydroxycholesterol, 7α-hydroxycholesterol, 7 ketocholesterol and three dihydroxysterols 7α-24(S)dihydroxycholesterol, 7α-25dihydroxycholesterol, 7α-27dihydroxycholesterol by LC-MS/MS following reverse phase chromatography. Our new method, using Triton and DMSO extraction, shows improved extraction efficiency and recovery of oxysterols from cellular matrix. We validated our method by reproducibly measuring oxysterols in mouse brain tissue and showed that mice fed a high fat diet had significantly lower levels of 24S/25diOHC, 27diOHC and 7ketoOHC. We measured oxysterols in mitochondria from peripheral blood mononuclear cells and highlight the importance of rapid cell isolation to minimise effects of handling and storage conditions on oxysterol composition in clinical samples. In addition, in vitro cell culture systems, of THP-1 monocytes and neuronal-like SH-SH5Y cells, showed mitochondrial-specific oxysterol metabolism and profiles were lineage specific. In summary, we describe a robust and reproducible method validated for improved recovery, quantitative linearity and detection, reproducibility and selectivity for cellular oxysterol analysis. This method enables subcellular oxysterol metabolism to be monitored and is versatile in its application to various biological and clinical samples.

Competing Interests: Declaration of interests Thirteen of the authors (ZA, S-CH, LJ, AM, CO, MO, JP, YP-S, DS, LB-V, MRo, MW, and HW) were compensated for their time while drafting and developing the Lancet Countdown's report. LC was supported by a grant from the National Heart, Lung, and Blood Institute of the National Institutes of Health. CD received funding from the European Research Council (FLORA, grant number 101039402). RD was supported by a grant from the High Tide Foundation and subcontracts on funds from the Wellcome Trust and US Centers for Disease Control and Prevention. GG-S received funding from the UK National Institute for Health and Care Research for the Global Health Research Group on Diet and Activity (NIHR133205, with sub-award contract number G109900-SJ1/171 with the University of Cambridge). SHG's research was supported by the National Research Foundation, Prime Minister's Office, Singapore, under its Campus for Research Excellence and Technological Enterprise programme (grant number NRF2019-THE001-0006). JJH was supported by two grants from the Wellcome Trust and a grant from the US National Science Foundation. RH, RK, and MSo acknowledge funding from Academy of Finland projects HEATCOST (grant 334798) and VFSP-WASE (grant 359421), together with EU Horizon projects FirEUrisk (grant number 101003890) and EXHAUSTION (grant number 820655). OJ was supported by grants from the National Health Medical Research Council (Heat and Health: building resilience to extreme heat in a warming world, GNT1147789); Wellcome Trust (Heat stress in ready-made garment factories in Bangladesh and the Heat inform pregnant study); and Resilience New South Wales (A new heat stress scale for general public); holds a patent for the Environmental Measurement Unit; and has received consulting fees from the National Institutes of Health. HM received funding from the Oak Foundation to support work on climate change through RealZero, is partly funded by the National Institute for Health Research's Comprehensive Biomedical Research Centre at University College London Hospitals, and received fees from Bayer Pharmaceuticals and Chiesl for sustainability consulting. JM-U was supported by grants PID2021-127107NB-I00 from Ministerio de Ciencia e Innovación (Spain) and 2021 SGR 00526 from Generalitat de Catalunya (Spain). JRo's work is supported by the Alexander von Humboldt foundation. RL, JRo, and MRo were supported by Horizon Europe through the IDAlert project (101057554) and UK Research and Innovation (reference number 10056533). RNS reports a contract with Massachusetts General Hospital. MSo and AU were supported by the Finnish Foreign Ministry project IBA-ILMA (grant number VN/13798/2023). MSp was supported by funding from the Wellcome Trust, through Our Planet Our Health (Livestock, Environment and People, award number 205212/Z/16/Z) and a Wellcome Career Development Award (Towards the full cost of diets, award number 225318/Z/22/Z). JDSh was supported by the Canadian Institutes of Health Research, the Commonwealth Fund, and the Emergency Care Research Institute and has received consulting fees from the Institute for Healthcare Research. JT was supported by the Research Council of Finland (T-Winning Spaces 2035 project), the UK Medical Research Council (PICNIC project), and the Finnish Ministry of the Environment (SEASON project). JB is employed as a consultant by the Global Climate and Health Alliance. ML received consulting fees from YarCom for advisory services and was supported by general use gifts awarded to the Center on Global Energy Policy at Columbia University, USA. JMil acknowledges consulting fees from the C40 Climate Leadership Group. CZ-C received a consultancy from the University of Alberta and was supported by contracts with her university (Universidad Peruana Cayetano Heredia), University of Leeds, WHO, and the Wellcome Trust; she was also supported by a letter of agreement between her university and the Food and Agriculture Organization's Indigenous Peoples Unit. MD was supported by the Wellcome Trust via the Complex Urban Systems for Sustainability and Health project (grants 205207/Z/16/Z and 209387/Z/17/Z). IH, S-CH, MRo, CT, and RL were supported by the Horizon Europe CATALYSE project (CATALYSE grant number 101057131, HORIZON-HLTH-2021-ENVHLTH-02, with UK Research and Innovation reference number 10041512). The work of YH, YL, DT, and QZ was supported by the National Aeronautics and Space Administration's Earth Action programme (grant number 80NSSC21K0507). AJP was supported by the Bezos Earth Fund and the Schmidt Family Foundation. ER and SD were supported by a Process-based models for climate impact attribution across sectors (PROCLIAS) grant (COST Action PROCLIAS grant CA19139), funded by European Cooperation in Science and Technology. All other authors declare no competing interests.

Competing Interests: Declaration of interests 14 of the authors (MRo, MWa, LJ, MBO'H, CO, HW, CdN, HK, PL, DS, CG, ZA, MY-G, and KRvD) were compensated for their time while drafting and developing the Lancet Countdown's report. OG was supported by the EU Horizon Grant: Climate Action To Advance Healthy Societies in Europe (Project 101057131–CATALYSE), for which there is overlap of data collection and preprocessing with the materials submitted in this report. MSp was supported by the Wellcome Trust Livestock, Environment and People (grant number 205212/Z/16/Z) and Wellcome Trust (grant number 225318/Z/22/Z). JT was supported by the Academy of Finland grants for the T-Winning (grant number 353327). CD was supported by the UK Natural Environment Research Council Independent Research Fellowship (grant number NE/N01524X/1), which ended in 2021, and by the European Research Council starting grant FLORA (grant number 101039402). OJ was supported by the NHMRC Investigator Grant entitled Heat and Health: Building resilience to extreme heat in a warming world (GNT20009507), the Wellcome Trust grant Heat stress in ready-made garment factories in Bangladesh (216059/Z/19/Z), and the Resilience New South Wales grant A new heat stress scale for general public (PJ-0000850). YL was supported by funding from the National Aeronautics and Space Administration (grant number: 80NSSC21K0507) for the wildfire population exposure and fire danger indicators. TO and IH were supported by the UK Research and Innovation Engineering and Physical Sciences Research Council Centre for Research in Energy Demand Solutions (grant number EP/R035288/1). MRo was supported by funding from IDAlert project (UK Research and Innovation project reference number 10056533). KB was supported by funding from the National Institute for Health and Care Research (NIHR) Centre on Non-communicable Diseases and Environmental Change (NIHR203247). All other authors declare no competing interests. The authors alone are responsible for the views expressed in this Commission, and they do not necessarily represent the views, decisions, or policies of the institutions with which they are affiliated.

Decarbonisation plans across the globe require zero-carbon energy sources to be widely deployed by 2050 or 2060. Solar energy is the most widely available energy resource on Earth, and its economic attractiveness is improving fast in a cycle of increasing investments. Here we use data-driven conditional technology and economic forecasting modelling to establish which zero carbon power sources could become dominant worldwide. We find that, due to technological trajectories set in motion by past policy, a global irreversible solar tipping point may have passed where solar energy gradually comes to dominate global electricity markets, without any further climate policies. Uncertainties arise, however, over grid stability in a renewables-dominated power system, the availability of sufficient finance in underdeveloped economies, the capacity of supply chains and political resistance from regions that lose employment. Policies resolving these barriers may be more effective than price instruments to accelerate the transition to clean energy., (© 2023. Springer Nature Limited.)

Mammals exhibit a diverse range of limb morphologies that are associated with different locomotor ecologies and structural mechanics. Much remains to be investigated, however, about the combined effects of locomotor modes and scaling on the external shape and structural properties of limb bones. Here, we used squirrels (Sciuridae) as a model clade to examine the effects of locomotor mode and scaling on the external shape and structure of the two major limb bones, the humerus and femur. We quantified humeral and femoral morphologies using 3D geometric morphometrics and bone structure analyses on a sample of 76 squirrel species across their four major ecotypes. We then used phylogenetic generalized linear models to test how locomotor ecology, size, and their interaction influenced morphological traits. We found that size and locomotor mode exhibit different relationships with the external shape and structure of the limb bones, and that these relationships differ between the humerus and femur. External shapes of the humerus and, to a lesser extent, the femur are best explained by locomotor ecology rather than by size, whereas structures of both bones are best explained by interactions between locomotor ecology and scaling. Interestingly, the statistical relationships between limb morphologies and ecotype were lost when accounting for phylogenetic relationships among species under Brownian motion. That assuming Brownian motion confounded these relationships is not surprising considering squirrel ecotypes are phylogenetically clustered; our results suggest that humeral and femoral variation partitioned early between clades and their ecomorphologies were maintained to the present. Overall, our results show how mechanical constraints, locomotor ecology, and evolutionary history may enact different pressures on the shape and structure of limb bones in mammals., (© The Author(s) 2023. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology.)

Body size is often hypothesized to facilitate or constrain morphological diversity in the cranial, appendicular, and axial skeletons. However, how overall body shape scales with body size ( i.e. , body shape allometry) and whether these scaling patterns differ between ecological groups remains poorly investigated. Here, we test whether and how the relationships between body shape, body size, and limb lengths differ among species with different locomotor specializations, and describe the underlying morphological components that contribute to body shape evolution among squirrel (Sciuridae) ecotypes. We quantified the body size and shape of 87 squirrel species from osteological specimens held at museum collections. Using phylogenetic comparative methods, we first found that body shape and its underlying morphological components scale allometrically with body size, but these allometric patterns differ among squirrel ecotypes: chipmunks and gliding squirrels exhibited more elongate bodies with increasing body sizes whereas ground squirrels exhibited more robust bodies with increasing body size. Second, we found that only ground squirrels exhibit a relationship between forelimb length and body shape, where more elongate species exhibit relatively shorter forelimbs. Third, we found that the relative length of the ribs and elongation or shortening of the thoracic region contributes the most to body shape evolution across squirrels. Overall, our work contributes to the growing understanding of mammalian body shape evolution and how it is influenced by body size and locomotor ecology, in this case from robust subterranean to gracile gliding squirrels., Competing Interests: The authors declare there are no competing interests., (©2023 Linden et al.)

Purpose: Clinicians rely on imaging features to calculate complexity of renal masses based on validated scoring systems. These scoring methods are labor-intensive and are subjected to interobserver variability. Artificial intelligence has been increasingly utilized by the medical community to solve such issues. However, developing reliable algorithms is usually time-consuming and costly. We created an international community-driven competition (KiTS19) to develop and identify the best system for automatic segmentation of kidneys and kidney tumors in contrast CT and report the results. Methods: A training and test set of CT scans that was manually annotated by trained individuals were generated from consecutive patients undergoing renal surgery for whom demographic, clinical and outcome data were available. The KiTS19 Challenge was a machine learning competition hosted on grand-challenge.org in conjunction with an international conference. Teams were given 3 months to develop their algorithm using a full-annotated training set of images and an unannotated test set was released for 2 weeks from which average Sørensen-Dice coefficient between kidney and tumor regions were calculated across all 90 test cases. Results: There were 100 valid submissions that were based on deep neural networks but there were differences in pre-processing strategies, architectural details, and training procedures. The winning team scored a 0.974 kidney Dice and a 0.851 tumor Dice resulting in 0.912 composite score. Automatic segmentation of the kidney by the participating teams performed comparably to expert manual segmentation but was less reliable when segmenting the tumor. Conclusion: Rapid advancement in automated semantic segmentation of kidney lesions is possible with relatively high accuracy when the data is released publicly, and participation is incentivized. We hope that our findings will encourage further research that would enable the potential of adopting AI into the medical field., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Sathianathen, Heller, Tejpaul, Stai, Kalapara, Rickman, Dean, Oestreich, Blake, Kaluzniak, Raza, Rosenberg, Moore, Walczak, Rengel, Edgerton, Vasdev, Peterson, McSweeney, Peterson, Papanikolopoulos and Weight.)

As the quantity and quality of cross-sectional imaging data increase, it is important to be able to make efficient use of the information. Semantic segmentation is an emerging technology that promises to improve the speed, reproducibility, and accuracy of analysis of medical imaging, and to allow visualization methods that were previously impossible. Manual image segmentation often requires expert knowledge and is both time- and cost-prohibitive in many clinical situations. However, automated methods, especially those using deep learning, show promise in alleviating this burden to make segmentation a standard tool for clinical intervention in the future. It is therefore important for clinicians to have a functional understanding of what segmentation is and to be aware of its uses. Here we include a number of examples of ways in which semantic segmentation has been put into practice in urology. PATIENT SUMMARY: This mini-review highlights the growing role of segmentation methods for medical images in urology to inform clinical practice. Segmentation methods show promise in improving the reliability of diagnosis and aiding in visualization, which may become a tool for patient education., (Copyright © 2021 European Association of Urology. Published by Elsevier B.V. All rights reserved.)

There is a large body of literature linking anatomic and geometric characteristics of kidney tumors to perioperative and oncologic outcomes. Semantic segmentation of these tumors and their host kidneys is a promising tool for quantitatively characterizing these lesions, but its adoption is limited due to the manual effort required to produce high-quality 3D segmentations of these structures. Recently, methods based on deep learning have shown excellent results in automatic 3D segmentation, but they require large datasets for training, and there remains little consensus on which methods perform best. The 2019 Kidney and Kidney Tumor Segmentation challenge (KiTS19) was a competition held in conjunction with the 2019 International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) which sought to address these issues and stimulate progress on this automatic segmentation problem. A training set of 210 cross sectional CT images with kidney tumors was publicly released with corresponding semantic segmentation masks. 106 teams from five continents used this data to develop automated systems to predict the true segmentation masks on a test set of 90 CT images for which the corresponding ground truth segmentations were kept private. These predictions were scored and ranked according to their average Sørensen-Dice coefficient between the kidney and tumor across all 90 cases. The winning team achieved a Dice of 0.974 for kidney and 0.851 for tumor, approaching the inter-annotator performance on kidney (0.983) but falling short on tumor (0.923). This challenge has now entered an "open leaderboard" phase where it serves as a challenging benchmark in 3D semantic segmentation., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020. Published by Elsevier B.V.)

Objective: To understand better the public perception and comprehension of medical technology such as artificial intelligence (AI) and robotic surgery. In addition to this, to identify sensitivity to their use to ensure acceptability and quality of counseling. Subjects and Methods: A survey was conducted on a convenience sample of visitors to the MN Minnesota State Fair ( n  = 264). Participants were randomized to receive one of two similar surveys. In the first, a diagnosis was made by a physician and in the second by an AI application to compare confidence in human and computer-based diagnosis. Results: The median age of participants was 45 (interquartile range 28-59), 58% were female ( n  = 154) vs 42% male ( n  = 110), 69% had completed at least a bachelor's degree, 88% were Caucasian ( n  = 233) vs 12% ethnic minorities ( n  = 31) and were from 12 states, mostly from the Upper Midwest. Participants had nearly equal trust in AI vs physician diagnoses. However, they were significantly more likely to trust an AI diagnosis of cancer over a doctor's diagnosis when responding to the version of the survey that suggested that an AI could make medical diagnoses ( p  = 9.32e-06). Though 55% of respondents ( n  = 145) reported that they were uncomfortable with automated robotic surgery, the majority of the individuals surveyed (88%) mistakenly believed that partially autonomous surgery was already happening. Almost all (94%, n  = 249) stated that they would be willing to pay for a review of medical imaging by an AI if available. Conclusion: Most participants express confidence in AI providing medical diagnoses, sometimes even over human physicians. Participants generally express concern with surgical AI, but they mistakenly believe that it is already being performed. As AI applications increase in medical practice, health care providers should be cognizant of the potential amount of misinformation and sensitivity that patients have to how such technology is represented.

Active networks composed of filaments and motor proteins can self-organize into a variety of architectures. Computer simulations in two or three spatial dimensions and including or omitting steric interactions between filaments can be used to model active networks. Here we examine how these modelling choices affect the state space of network self-organization. We compare the networks generated by different models of a system of dynamic microtubules and microtubule-crosslinking motors. We find that a thin 3D model that includes steric interactions between filaments is the most versatile, capturing a variety of network states observed in recent experiments. In contrast, 2D models either with or without steric interactions which prohibit microtubule crossings can produce some, but not all, observed network states. Our results provide guidelines for the most appropriate choice of model for the study of different network types and elucidate mechanisms of active network organization.

During cell division, mitotic motors organize microtubules in the bipolar spindle into either polar arrays at the spindle poles or a "nematic" network of aligned microtubules at the spindle center. The reasons for the distinct self-organizing capacities of dynamic microtubules and different motors are not understood. Using in vitro reconstitution experiments and computer simulations, we show that the human mitotic motors kinesin-5 KIF11 and kinesin-14 HSET, despite opposite directionalities, can both organize dynamic microtubules into either polar or nematic networks. We show that in addition to the motor properties the natural asymmetry between microtubule plus- and minus-end growth critically contributes to the organizational potential of the motors. We identify two control parameters that capture system composition and kinetic properties and predict the outcome of microtubule network organization. These results elucidate a fundamental design principle of spindle bipolarity and establish general rules for active filament network organization., (Copyright © 2018 The Francis Crick Institute. Published by Elsevier Inc. All rights reserved.)

Growing microtubules are protected from depolymerization by the presence of a GTP or GDP/Pi cap. End-binding proteins of the EB1 family bind to the stabilizing cap, allowing monitoring of its size in real time. The cap size has been shown to correlate with instantaneous microtubule stability. Here we have quantitatively characterized the properties of cap size fluctuations during steady-state growth and have developed a theory predicting their timescale and amplitude from the kinetics of microtubule growth and cap maturation. In contrast to growth speed fluctuations, cap size fluctuations show a characteristic timescale, which is defined by the lifetime of the cap sites. Growth fluctuations affect the amplitude of cap size fluctuations; however, cap size does not affect growth speed, indicating that microtubules are far from instability during most of their time of growth. Our theory provides the basis for a quantitative understanding of microtubule stability fluctuations during steady-state growth.

Recent years have seen steady improvements in the recognition and interpretation of violence related injuries in human skeletal remains. Such work has at times benefited from the involvement of biological anthropologists in forensic casework and has often relied upon comparison of documented examples with trauma observed in skeletal remains. In cases where no such example exists investigators must turn to experimentation. The selection of experimental samples is problematic as animal proxies may be too dissimilar to humans and human cadavers may be undesirable for a raft of reasons. The current article examines a third alternative in the form of polyurethane plates and spheres marketed as viable proxies for human bone in ballistic experiments. Through subjecting these samples to a range of impacts from both modern and archaic missile weapons it was established that such material generally responds similarly to bone on a broad, macroscopic scale but when examined in closer detail exhibits a range of dissimilarities that call for caution in extrapolating such results to real bone., (Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.)