Taken in Algeria, 'Last Fireworks' is this year's first place category and open competition overall winner. Breakthroughs, discoveries, and DIY tips sent every weekday. The winners of the 2025 Epson International Pano awards have been announced, showcasing photographs of our great, big, beautiful world in ultra-wide glory. Italy's Alex Wides (Alessandro Cantarelli) won the Open Photographer of the Year and the Nature/Landscape category for his fine-art landscapes (seen above and below). Among this year's 3,423 entries, there were more photographs of the Northern Lights than usual, coinciding with the 11-year solar cycle maximum .

What a wonderful world for all to see. Photographers from around the globe highlighted the best of our planet as part of the open competition for the Sony World Photography Awards 2023. The World Photography Organisation announced last week the best single shots, all taken in 2022, chosen from more than 415,000 submissions from over 200 countries and territories, according to a press release. The competition was split into 10 categories: Architecture, creative, landscape, lifestyle, motion, natural world & wildlife, object, portraiture, street photography and travel. While 10 individual category winners were named -- and they will be awarded Sony digital imaging equipment and the ability to compete for the Open Photographer of the Year title -- finalists were also given honorable mentions.

Images of lounging elephants, treefrog embryos and a parasitic fungus erupting from the body of a fly have all won prizes at an ecology photo competition. The doomed fly was captured by evolutionary biologist Roberto García-Roa in the Tambopata National Reserve, Peru, and took the overall win at the second ever BMC Ecology and Evolution Image Competition. The contest aims to showcase the wonder of the natural world and emphasise the growing need to protect it from human activity. Mr García-Roa, from the University of Valencia, Spain, said: 'The image depicts a conquest that has been shaped by thousands of years of evolution. 'The spores of the so-called'zombie' fungus have infiltrated the exoskeleton and mind of the fly and compelled it to migrate to a location that is more favourable for the fungus's growth.

We each developed from a single cell—a fertilized egg—that divided and divided and eventually gave rise to the trillions of cells, of hundreds of types, that constitute the tissues and organs of our adult bodies. Advancing our understanding of the molecular programs underlying the emergence and differentiation of these diverse cell types is of fundamental interest and will affect almost every aspect of biology and medicine. Recently, technological advances have made it possible to directly measure the gene expression patterns of individual cells ([ 1 ][1]). Such methods can be used to clarify cell types and to determine the developmental stage of individual cells ([ 2 ][2]). Single-cell transcriptional profiling of successive developmental stages has the potential to be particularly informative, as the data can be used to reconstruct developmental processes, as well as characterize the underlying genetic programs ([ 3 ][3], [ 4 ][4]). ![Figure][5] A genomic technique for tracking cellular development High-throughput single-cell genomic methods enable a global view of cell type diversifcation by transcriptome and epigenome CREDIT: N. DESAI/ SCIENCE FROM CAO ET AL. ([7][6]) AND BIORENDER When I began my doctoral studies in Jay Shendure's lab at the University of Washington, available single-cell sequencing techniques relied on the isolation of individual cells within physical compartments and thus were limited in terms of both throughput and cost. As a graduate student, I developed four high-throughput single-cell genomic techniques to overcome these limitations ([ 5 ][7]–[ 8 ][8]). Leveraging these methods, I profiled millions of single-cell transcriptomes from organisms, in species that included worms, mice, and humans. By quantifying the dynamics of embryonic development at single-cell resolution, I was able to map out the global genetic programs that control cell proliferation and differentiation at the whole-organism scale. By the 1980s, biologists had documented every developmental step in the nematode Caenorhabditis elegans , from a single-cell embryo to the adult worm, and mapped the connections of all of the worm's neurons ([ 9 ][9]). However, although the nematode worm has a relatively small cell number (558 cells at hatching), a comprehensive understanding of the molecular basis for the specification of these cell types remains difficult. To resolve cellular heterogeneity, I first developed a method to specifically label the transcriptomes of large numbers of single cells, which we called sci-RNA-seq (single-cell combinatorial indexing RNA sequencing) ([ 5 ][7]). This method is based on combinatorial indexing, a strategy using split-pool barcoding of nucleic acids to label vast numbers of single cells within a single experiment ([ 9 ][9]). In this study, I profiled nearly 50,000 cells from C. elegans at the L2 stage, which is more than 50-fold “shotgun cellular coverage” of its somatic cell composition. We further defined consensus expression profiles for 27 cell types and identified rare neuronal cell types corresponding to as few as one or two cells in the L2 worm. This was the first study to show that single-cell transcriptional profiling is sufficient to separate all major cell types from an entire animal. C. elegans development follows a tightly controlled genetic program. Other multicellular organisms, such as mice and humans, have much more developmental flexibility. However, conventional approaches for mammalian single-cell profiling lack the throughput and resolution to obtain a global view of the molecular states and trajectories of the rapidly diversifying and expanding cell types. To investigate cell state dynamics in mammalian development, I developed an even more scalable single-cell profiling technique, sci-RNA-seq3 ([ 7 ][6]), and used it to trace the development path of 2 million mouse cells as they traversed diverse paths in a 4-day window of development corresponding to organogenesis (embryonic day 9.5 to embryonic day 13.5). From these data, we characterized the dynamics of cell proliferation and key regulators for each cell lineage, a potentially foundational resource for understanding how the hundreds of cell types forming a mammalian body are generated in development. This was, and remains, the largest publicly available single-cell transcriptional dataset. The sci-RNA-seq3 method enabled this dataset to be generated rapidly, within a few weeks, by a single individual. A major challenge regarding current single-cell assays is that nearly all such methods capture just one aspect of cellular biology (typically mRNA expression), limiting the ability to relate different components to one another and to infer causal relationships. Another technique that I developed, sci-CAR (single-cell combinatorial indexing chromatin accessibility and mRNA) ([ 6 ][10]), was created with the goal of overcoming this limitation, allowing the user to jointly profile the epigenome (chromatin accessibility) and transcriptome (mRNA). I applied sci-CAR to the mouse whole kidneys, recovering all major cell types and linking cis-regulatory sites to their target genes on the basis of the covariance of chromatin accessibility and transcription across large numbers of single cells. To further explore the gene regulatory mechanisms, I invented sci-fate ([ 8 ][8]), a new method that identifies the temporal dynamics of transcription by distinguishing newly synthesized mRNA transcripts from “older” mRNA transcripts in thousands of individual cells. Applying the strategy to cancer cell state dynamics in response to glucocorticoids, we were able to link transcription factors (TFs) with their target genes on the basis of the covariance between TF expression and the amount of newly synthesized RNA across thousands of cells. In summary, my dissertation involved developing the technical framework for quantifying gene expression and chromatin dynamics across thousands to millions of single cells and applying these technologies to profile complex, developing organisms. The methods that I developed enable such projects to be achievable by a single individual, rather than requiring large consortia. Looking ahead, I anticipate that the integration of single-cell views of the transcriptome, epigenome, proteome, and spatial-temporal information throughout development will enable an increasingly complete view of how life is formed. GRAND PRIZE WINNER Junyue Cao Junyue Cao received his undergraduate degree from Peking University and a Ph.D. from the University of Washington. After completing his postdoctoral fellowship at the University of Washington, Junyue Cao started his lab as an assistant professor and lab head of single-cell genomics and population dynamics at the Rockefeller University in 2020. His current research focuses on studying how a cell population in our body maintains homeostasis by developing genomic techniques to profile and perturb cell dynamics at single-cell resolution. CATEGORY WINNER: ECOLOGY AND EVOLUTION Orsi Decker Orsi Decker completed her undergraduate degree at Eötvös Loránd University in Budapest, Hungary. She went on to receive her master's degree in Ecology and Evolution at the University of Amsterdam. Decker completed her doctoral research at La Trobe University in Melbourne, Australia, where she investigated the extinctions of native digging mammals and their context-dependent impacts on soil processes. She is currently a postdoctoral researcher at La Trobe University, where she is examining how land restoration efforts could be improved to regain soil functions through the introduction of soil fauna to degraded areas. [www.sciencemag.org/content/370/6519/925.1][11] CATEGORY WINNER: MOLECULAR MEDICINE Dasha Nelidova Dasha Nelidova completed her undergraduate degrees at the University of Auckland, New Zealand. She completed her Ph.D. in neurobiology at the Friedrich Miescher Institute for Biomedical Research in Basel, Switzerland. Nelidova is currently a postdoctoral researcher at the Institute of Molecular and Clinical Ophthalmology Basel, where she is working to develop new translational technologies for treating retinal diseases that lead to blindness. [www.sciencemag.org/content/370/6519/925.2][12] CATEGORY WINNER: CELL AND MOLECULAR BIOLOGY William E. Allen William E. Allen received his undergraduate degree from Brown University in 2012, M.Phil. in Computational Biology from the University of Cambridge in 2013, and Ph.D. in Neurosciences from Stanford University in 2019. At Stanford, he worked to develop new tools for the large-scale characterization of neural circuit structure and function, which he applied to understand the neural basis of thirst. After completing his Ph.D., William started as an independent Junior Fellow in the Society of Fellows at Harvard University, where he is developing and applying new approaches to map mammalian brain function and dysfunction over an animal's life span. [www.sciencemag.org/content/370/6519/925.3][13] 1. [↵][14]1. D. Ramsköld et al ., Nat. Biotechnol. 30, 777 (2012). [OpenUrl][15][CrossRef][16][PubMed][17] 2. [↵][18]1. C. Trapnell , Genome Res. 25, 1491 (2015). [OpenUrl][19][Abstract/FREE Full Text][20] 3. [↵][21]1. D. E. Wagner et al ., Science 360, 981 (2018). [OpenUrl][22][Abstract/FREE Full Text][23] 4. [↵][24]1. K. Davie et al ., Cell 174, 982 (2018). [OpenUrl][25][CrossRef][26][PubMed][27] 5. [↵][28]1. J. Cao et al ., Science 357, 661 (2017). [OpenUrl][29][Abstract/FREE Full Text][30] 6. [↵][31]1. J. Cao et al ., Science 361, 1380 (2018). [OpenUrl][32][Abstract/FREE Full Text][33] 7. [↵][34]1. J. Cao et al ., Nature 566, 496 (2019). [OpenUrl][35][CrossRef][36][PubMed][37] 8. [↵][38]1. J. Cao, 2. W. Zhou, 3. F. Steemers, 4. C. Trapnell, 5. J. Shendure , Nat. Biotechnol. 38, 980 (2020). [OpenUrl][39][CrossRef][40][PubMed][41] 9. [↵][42]1. D. A. Cusanovich et al ., Science 348, 910 (2015). 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Our challenge to bot builders; design, develop, and market the best bots you can that utilise the Hu:toma API. There will be hurdles to jump along the way, which is why we've scouted the bot community and brought together some of the smartest, most experienced minds to coach & provide feedback to our teams. Over a period of 16 weeks, that's right someone will be getting a rather large christmas present, competition entrants will have six categories of bots to compete in building. Category deadlines are spaced every two weeks, with the six category winners and six wildcards making it to the final round. These categories are closely aligned with Amir Shevat's book "Designing Bots".