Two Moraea species were used as outgroups. All 21 newly assembled chloroplast genomes had the typical quadripartite structure, comprising large and small single-copy regions and two inverted repeats. They ranged from 150,596 to 157,200 base pairs, and each contained 113 genes: 79 protein-coding genes, 30 tRNA genes and four rRNA genes.

Gene order was otherwise highly conserved across the sampled members of the series. Comparative analysis identified an approximately 17,000-base-pair inversion in the small single-copy region of seven samples: Iris ventricosa, I. bungei, I. cathayensis, two I. kobayashii samples and two unidentified specimens. The rearrangement reversed eight genes: rps15, ndhH, ndhA, ndhI, ndhG, ndhE, psaC and ndhD.

It was identified as a distinctive structural feature of the series’ second major clade and as evidence for that clade’s monophyly independent of sequence data. The study distinguished four configurations at the inverted-repeat and single-copy boundaries, based on the positions of rps19 and ycf1. Most samples shared the fourth configuration.

I. liupanshanensis and I. qinghainica showed boundary contraction, while I. anguifuga showed expansion that placed ycf1 wholly within the inverted repeat. The series was recovered as sister to the clade containing I. ser. Foetidissimae and I. ser.

Spuriae, while the three newly described species and two unidentified taxa were incorporated into the strongly supported series. Three new species were formally described: Iris liupanshanensis, I. helanshanensis and I. coeruleoviridis. I. liupanshanensis has unusually broad leaves, 10–12 mm wide, and an above-ground flowering stem.

I. helanshanensis differs from I. farreri in its shorter bracts, lack of an elongated ovary neck and beakless fruit. I. coeruleoviridis resembles I. anguifuga but has broader leaves and smaller flowers, measuring 6–6.5 cm in diameter rather than about 10 cm. All three new species were documented in China.

I. liupanshanensis occurs in montane grasslands of the Liupan Mountains, while I. helanshanensis is recorded from the Helan and Luo Mountains. I. coeruleoviridis is known only from the Caolianling area of the western Qinling Mountains. Preliminary conservation assessments placed I. liupanshanensis and I. coeruleoviridis in the Data Deficient category.

I. helanshanensis was assessed as Vulnerable based on an estimated population of fewer than 1,000 mature individuals, an occupied area of less than 20 km² and a limited number of locations. The authors noted potential habitat degradation and fragmentation associated with tourism development, while stating that systematic surveys are needed to verify the assessment. The analysis had several limitations.

No I. songarica sample was available, leaving its phylogenetic position unresolved. Detailed morphological data were also unavailable for the two unidentified taxa, so their status as independent species could not be established. The known range of I. coeruleoviridis remains limited, and some records used to assess distribution were sparse.

Subject of Research: Phylogeny, chloroplast-genome structure and taxonomy of Iris series Tenuifoliae

Article Title: Phylogeny and taxonomy of Iris ( Iridaceae ) series Tenuifoliae : Discovery of a clade with chloroplast genome inversion and description of three new species

Article References: Zhang, Z., Li, H., Zhang, G., & Zuo, T. (2026). Phylogeny and taxonomy of Iris (Iridaceae) series Tenuifoliae: Discovery of a clade with chloroplast genome inversion and description of three new species. PhytoKeys, 275, 299-320. https://doi.org/10.3897/phytokeys.275.184036

Image Credits: AI Generated

DOI: 10.3897/phytokeys.275.184036

Keywords: Iris, Tenuifoliae, phylogenetics, chloroplast genomes, plant taxonomy, species description, genome inversion, Iridaceae, conservation status, Phylogeny, taxonomy, series

For decades, researchers studying amphibian populations have faced an uncomfortable trade-off. Estimating survival, population size, and life-history traits through capture-recapture analyses requires recognising the same individual across repeated encounters. In large mammals, genetic identification from faecal samples can accomplish this with minimal disturbance. In amphibians, however, the standard approach has long been toe clipping, the surgical removal of one or more toes to create a permanent marking code. Studies cited by the research team show that toe clipping can affect survival, physiology, and behaviour in frogs, undermining both animal welfare and the integrity of the data collected. Biometric techniques, which identify individuals using measurable phenotypic features, offer a promising alternative, but they depend on finding a trait that is both unique to each individual and stable over time.

Animal biometrics has an impressive track record across the tree of life. Eyespots on butterfly wings, injury marks in white sharks, stripe arrangements in zebras and tigers, and even nose prints in cattle have all been used to distinguish individuals without handling. In amphibians, photographic identification based on skin patterns has been applied successfully in many species. The problem is that this approach fails entirely for species in which some or all individuals lack distinct dorsal markings, and Osteocephalus oophagus is precisely such a species. Although the frog exhibits some dorsal patterns, these are often very limited, inconsistently present across individuals, or restricted to specific body regions, making systematic comparisons difficult.

The eyes, however, told a different story. Osteocephalus oophagus possesses complex golden irises crossed by thin, black, radial lines around the pupil, whose arrangement appears to create a unique, fingerprint-like pattern in each individual. Iris recognition was originally developed for human identification, where iris texture is sufficiently complex to serve as a lifelong biometric signature, and it has since been tested in geckos, cattle, goats, and tigers. A recent study even demonstrated that iris characteristics can be used to distinguish amphibian species. What had never been tested before was whether iris patterns could identify individual frogs, and whether those patterns remain stable across encounters.

To answer these questions, the research team conducted a capture-recapture study on an approximately five-hectare river island in lowland rainforest within the Les Nouragues nature reserve in French Guiana, near the Saut Pararé field camp of the CNRS Nouragues Ecological Research Station. The study ran during the rainy seasons of March through May in 2021, 2022, and 2023. Sampling focused on an array of 39 artificial pool sites spaced every 20 metres along the trails covering the island, each consisting of three flower pots of different capacities, 0.1 litres, 0.3 litres, and 1 litre, installed at a height of 130 centimetres to mimic the natural breeding pools used by treefrogs. Natural breeding sites such as tree hollows were also surveyed throughout the island.

The field protocol was designed to minimise disturbance from the very first encounter. Frogs were systematically searched for in and around artificial and natural pools between 18:40 and 02:00, with the aim of sampling all adult males and females present on the island during each study period. Upon first capture, a frog was caught by hand and photographed with Olympus TG-620 and TG-630 cameras, including both eyes, the dorsal and ventral sides, and the hind legs, before being released at the capture site. The eye photographs were later cropped to isolate the iris and compiled into a reference library on rugged Windows 10 tablets carried into the field. During subsequent encounters, both eyes were photographed without any direct contact. If the frog could be identified using the reference library on the tablet, it was left undisturbed entirely. Only frogs that could not be matched were processed following the first-encounter protocol. Notably, frogs encountered in amplexus typically resumed mating within an hour, and eye photographs could be obtained while frogs perched on natural structures, whether alone or paired.

Manual in-field identifications were independently verified using Wild-ID 1.0.0, a pattern-matching software originally developed for photographic identification in wildlife studies. The software was run twice, once using only left-eye images and once using only right-eye images, allowing each iris pattern to serve as its own independent verification. The results were striking. Over the three study seasons, 103 individuals were sampled across 392 capture events: 128 captures in 2021, 217 in 2022, and 47 in 2023. For most identifications, a single eye was sufficient to reliably identify the individual, with the second eye serving only as confirmation. Iris patterns proved highly distinctive among individuals, and the diversity of patterns across the sampled population was visually unmistakable.

Within-season recapture rates demonstrated that iris patterns remain sufficiently stable for short-term monitoring. In 2021, the study area was sampled for 22 days and 24 individuals were encountered, of which 16, or 66.7 percent, were recaptured during the same season, with individuals captured an average of 5.8 plus or minus 5.3 times. In 2022, after 24 days of sampling, 59 individuals were encountered and 47, or 79.7 percent, were recaptured within the season, averaging 9.0 plus or minus 6.2 captures per individual. In 2023, 17 days of sampling yielded 23 individuals, none of which had been captured during the previous two years, and 13 of them, or 56.5 percent, were recaptured within the season. Across all three years, more than half of the identified individuals were consistently re-identified based on their iris patterns, indicating that these patterns do not change appreciably over the course of a breeding season.

The long-term picture was more complicated. Only three individuals first captured in 2021 were recaptured in 2022, and none of the 23 individuals encountered in 2023 had been captured during the previous two years. Because no additional marking or identification technique was used, the researchers could not determine whether previously identified frogs remained in the population but were no longer identifiable, or whether they were genuinely absent. The three cross-year recaptures showed no substantial alteration in their iris patterns, and identification within and across seasons was generally unambiguous. The team therefore interprets the scarcity of interannual recaptures as more likely reflecting population turnover and emigration than changes in iris morphology rendering individuals unidentifiable. Evidence from other poikilothermic vertebrates is mixed on this point: iris patterns in Atlantic salmon remain stable only over several months, whereas long-term stability has been demonstrated in geckos. Comparable data for amphibians are lacking, and human iris patterns are known to remain stable throughout life.

The study concludes that iris patterns in Osteocephalus oophagus are individually distinct and enable reliable short-term individual identification, and the authors recommend the approach as a non-invasive method for individual recognition within a single reproductive season. The method is readily compatible with ethical research guidelines such as the 3Rs, reducing the need for repeated handling of study animals. Further research is needed to evaluate the potential of iris patterns for long-term identification, ideally through studies on captive individuals or field studies combining iris photography with an independent identification method such as genetic identification or permanent marking. The approach may also extend to other anuran species with complex irises, including Osteocephalus taurinus, Hyloscirtus tigrinus, Trachycephalus resinifictrix, and Sachatamia ilex, though the authors caution that suitability will vary among species. Highly complex iris patterns may hinder rapid field identification, as potentially occurs in Trachycephalus hadroceps, whereas uniform or patternless irises may provide insufficient interindividual variation, as potentially observed in the red-eyed treefrog Agalychnis callidryas. The reliability of iris patterns for individual re-identification should therefore be evaluated species by species before the method is applied more broadly. If those evaluations succeed, iris pattern identification could become a powerful, non-invasive tool for rapid field-based individual recognition, opening new opportunities for individual-level studies in amphibians while keeping the frogs themselves untouched.

Subject of Research: Iris pattern recognition as a non-invasive method for individual identification in the treefrog Osteocephalus oophagus

Article Title: Iris pattern recognition as a non-invasive method for individual identification in Osteocephalus oophagus ( Hylidae )

Article References: Bégué, L., Petel, F., Premel, V., Raboisson, G., Ringler, E., Ringler, M., Toszeghi, M., Vacher, V., & Peignier, M. (2026). Iris pattern recognition as a non-invasive method for individual identification in Osteocephalus oophagus (Hylidae). Herpetozoa, 39, 381-387. https://doi.org/10.3897/herpetozoa.39.e208000

Image Credits: AI Generated

DOI: 10.3897/herpetozoa.39.e208000

Keywords: iris recognition, Osteocephalus oophagus, amphibian biometrics, capture-recapture, non-invasive identification, French Guiana, treefrog, Wild-ID, animal welfare, herpetology, Iris, pattern

The central message of the collection is that coronal rain and prominences, long treated as separate phenomena, are in fact closely related expressions of the same underlying physics: coronal condensation. Whether a cooling clump of plasma falls back to the solar surface as rain or hangs suspended for days as a prominence depends largely on the magnetic topology in which it forms. Condensations that form in closed, steeply curved loops tend to drain rapidly along field lines as rain, while those that settle into magnetic dips can remain buoyantly supported as prominences. Their different lifetimes and appearances are therefore not arbitrary but are dictated by the interplay of radiative losses, heating, gravity, flows, and magnetic forces, all acting on plasma that spans several orders of magnitude in temperature and density.

The theoretical foundation is revisited by Thomas Waters and Andrew Stricklan, who re-examine the radiative cooling of optically thin plasma and identify a catastrophic cooling mode distinct from the classical thermal instability. This mode is governed by the isochoric instability criterion, which applies to plasma compressed at constant volume, and crucially it cannot be stabilized by thermal conduction. That means condensations can form under conditions where conventional thermal-instability arguments would predict a stable equilibrium. The result widens the theoretical window within which rapid cooling in hot, low-density plasmas should be interpreted, and it may explain observations of abrupt, near-catastrophic temperature drops in coronal loops that standard theory has struggled to accommodate.

A sweeping theoretical and numerical perspective comes from Rony Keppens, Yuhang Zhou, and Chengcai Xia, whose review places prominences and coronal rain within a unified framework of multiphase coronal plasma. They trace how gravity, flows, heating prescriptions, and magnetic topology shape both the linear growth of instabilities and their full nonlinear magnetohydrodynamic evolution. Their assessment is candid about what remains unsolved: the fine structure of prominences, their internal dynamics, and their complete life cycle from birth to eruption remain major challenges for numerical studies. Complementing this, Valeriia Liakh and Jack Jenkins review a decade and a half of prominence and coronal rain modeling with the open-source MPI-AMRVAC code, following the progression from simplified one-dimensional setups to multidimensional simulations that self-consistently produce cool condensations, and charting a path toward three-dimensional models that include partial ionization, realistic radiative transfer, and the full mass cycle between chromosphere and corona.

Radiation becomes a formidable complication once plasma cools enough to become optically thick, because photons can then be absorbed as well as emitted. Petr Heinzel and colleagues demonstrate through non-local thermodynamic equilibrium, or non-LTE, radiative transfer calculations that the optically thin loss functions commonly used in simulations break down for cool, dense condensations. Realistic net radiative rates must include both losses and gains from the absorption of incident radiation, and their models quantify how condensations relax toward radiative equilibrium on timescales that depend on plasma pressure and geometric thickness. In a companion review, Heinzel and Stanislav Gunár survey five decades of non-LTE prominence modeling, from one-dimensional slabs to two-dimensional and emerging three-dimensional multi-thread structures, and argue that coupling dynamic MHD models with multidimensional radiative transfer is now essential for interpreting rapidly moving eruptive prominences captured by modern instruments.

On the observational side, disentangling emission from plasma at wildly different temperatures along the same line of sight is the central challenge. Paolo Antolin and colleagues extend a technique called Response Fitting to separate cool, warm, and hot contributions within several passbands of the Atmospheric Imaging Assembly on the Solar Dynamics Observatory and the slit-jaw imager of the Interface Region Imaging Spectrograph. The method improves the decomposition of the AIA 94 and 304 angstrom channels and allows the hot Fe XXI flare emission contaminating the IRIS 1330 and 1400 angstrom passbands to be estimated. Applied to a joint AIA-IRIS observation, it reveals an approximately seven-fold increase in cool plasma associated with flare-driven coronal rain, and because it is computationally efficient it opens the door to near-real-time thermal diagnostics of the solar atmosphere.

That diagnostic power is already yielding surprises. Seray Şahin and Paolo Antolin used IRIS and SDO/AIA observations of coronal-rain showers neighboring a modest C7.5 flare to test whether a flare can influence loops that are not themselves flaring. They compared the amount, intensity, and velocity of rain across the pre-flare, impulsive, and gradual phases, finding that the number of detected rain events rose by roughly 27 percent from the pre-flare to the impulsive phase, while average intensity and downflow velocity increased by about 17 and 18 percent respectively by the gradual phase. The implication is striking: a flare can alter the thermodynamic conditions of neighboring, apparently quiescent loops, and the tidy distinction between quiescent and flare-driven coronal rain is not always clear-cut.

Thermal non-equilibrium, in which plasma on closed loops undergoes repeated cycles of heating, cooling, and condensation, has also now been caught operating far beyond its usual habitat. Clara Froment and Sophie Masson report long-period extreme-ultraviolet pulsations and recurring coronal-rain showers in a non-eruptive pseudo-streamer observed over roughly two and a half days with SDO/AIA. The ordering of the EUV emission peaks and the appearance of rain near the end of each cooling cycle provide strong evidence for thermal non-equilibrium cycles occurring both beneath the pseudo-streamer dome and in regions dominated by open or large-scale magnetic fields. Continuous interchange reconnection accompanied the evolution, suggesting that the interaction between reconnection and thermal non-equilibrium may govern how condensations are released and transported near open-closed magnetic boundaries, with possible consequences for the solar wind itself.

Two further studies round out the physical picture. Pengfei Chen introduces the evocatively named concept of solar filament physiognomy, the practice of inferring magnetic properties from the appearance and fine structure of filaments in imaging observations, a valuable complement in an era when direct measurements of the coronal magnetic field remain difficult. Lorenzo Melis and Roberto Soler analyze the Kelvin-Helmholtz instability at the interface between partially ionized prominence plasma and the fully ionized corona, showing that compressibility and acoustic effects matter at observed flow speeds and that ambipolar diffusion generally destabilizes the interface, lowering the threshold velocity and broadening the unstable parameter range. And Yuhong Fan’s review of MHD simulations of prominence-forming flux ropes demonstrates that prominence material is no passive tracer: its weight modifies the equilibrium, stability, and eruptive evolution of the flux rope that hosts it, ultimately shaping coronal mass ejections.

Taken together, the collection sketches a field in transition, where observers, theorists, and modelers converge on a single coupled system. Future models must move toward fully three-dimensional treatments that combine MHD with non-LTE radiative transfer, non-equilibrium ionization, and multi-fluid effects, while synthetic observables will be essential for meaningful comparison with the rapidly improving data from the Daniel K. Inouye Solar Telescope, Solar Orbiter, and Proba-3. The ultimate goal is to follow condensations continuously, from their thermodynamic formation through their drainage, suspension, or eruption, and thereby assemble a comprehensive picture of the coronal mass and energy cycle. In that picture, the rain that falls through the Sun’s corona and the great crimson prominences that arch above its limb are not curiosities but signposts pointing to the same fundamental physics.

Subject of Research: Coronal cooling and the formation, evolution, and eruption of cool plasma in the solar corona

Article Title: Coronal Cooling: Rain, Prominences, and Eruptions – Editorial

Article References: Şahin, S., Druett, M. K., Liakh, V., Popescu Braileanu, B., & Rees-Crockford, T. (2026). Coronal Cooling: Rain, Prominences, and Eruptions – Editorial. Solar Physics, 301(10), Article 151. https://doi.org/10.1007/s11207-026-02746-7

Image Credits: AI Generated

DOI: 10.1007/s11207-026-02746-7

Keywords: solar physics, coronal rain, prominences, solar filaments, thermal instability, radiative transfer, MHD simulations, coronal mass ejections, SDO/AIA, IRIS, thermal non-equilibrium, solar corona

The central obstacle the researchers confronted is a familiar one in modern biology. The richest data on cellular signaling come from perturbation screens performed in controlled in vitro settings, where scientists can apply defined stimuli — a dose of interferon, a jolt of EGF, a targeted kinase inhibitor — and observe, often at the protein level, how signaling networks respond within minutes. These experiments are clean, interpretable and information-dense. But cells in a dish are not cells in a body. In vivo contexts are shaped by tissue architecture, immune interactions, developmental cues and a constantly shifting microenvironment, and perturbation data of comparable quality simply cannot be gathered there. The question was whether the deep mechanistic knowledge embedded in in vitro screens could be transferred to the messy, heterogeneous world of living organisms.

IRIS — the framework’s name reflects its role as an interpreter of signaling — answers that question affirmatively by learning what its developers call conserved signaling representations. The method is trained on large collections of perturbation screening data, spanning many stimuli, many cell types and many experimental conditions. From this corpus it distills a shared mathematical space in which the essential features of signaling activity are encoded: which pathways are active, in what combinations, and with what intensity. Crucially, the representation is designed to be context-invariant. It abstracts away from the particulars of any single experiment and captures the recurring logic of signal transduction itself — the way receptor activation cascades into kinase activity, transcription factor engagement and downstream gene expression. Once this conserved space has been learned, the framework can map cells from an entirely different setting, such as an in vivo tissue atlas, into the same coordinate system and read off their signaling states.

Technically, the approach draws on transfer learning, one of the most consequential ideas in contemporary machine learning. Rather than training a model from scratch on scarce in vivo data, IRIS transfers knowledge acquired in the data-rich in vitro domain to the data-poor in vivo domain. The perturbation screens serve as a kind of ground-truth curriculum: because the stimuli are known, the model can learn the explicit correspondence between an applied perturbation and the resulting signaling response. That supervised grounding is what distinguishes IRIS from purely unsupervised approaches, which can cluster cells by similarity but cannot attribute those similarities to specific signaling events. With the transfer learned, the model performs what is effectively computational inference across domains — taking the gene expression profile of a single cell from a tumor, an embryo or an inflamed organ and reconstructing the signaling activity that most plausibly produced it.

The implications of reconstructing signaling histories extend well beyond technical elegance. Many of the most important decisions a cell makes are driven by transient signals that leave subtle traces in gene expression. An immune cell that encountered its antigen hours ago, a stem cell that received a morphogen pulse during development, a cancer cell that survived a burst of chemotherapy-induced stress — all of these carry records of their past exposures in their present molecular state, but those records are encrypted. By decoding them, IRIS allows researchers to ask retrospective questions that were previously unanswerable: which cells in a tissue recently received a particular signal, which pathways were engaged in sequence, and how the history of stimulation differs between neighboring cells that look superficially identical.

In disease research, this capability is especially potent. Tumor microenvironments are theaters of continuous signaling crosstalk, with malignant cells, immune infiltrates and stromal cells exchanging signals that determine immune evasion, therapy resistance and metastatic potential. Bulk genomic methods average away this complexity, and even single-cell atlases typically report endpoint states. A framework that infers signaling histories cell by cell can reveal, for example, which subpopulations of tumor cells have been receiving survival signals from their surroundings, or which immune cells show the signaling signature of recent activation versus chronic exhaustion. Such information could sharpen the design of combination therapies, identifying not just which pathways are active in a tumor but which were active in the events leading to the observed cellular landscape.

The method also addresses a persistent reproducibility problem in single-cell biology. Signaling measurements are notoriously difficult to standardize across laboratories, platforms and tissue types, which has slowed the accumulation of comparable in vivo signaling data. By anchoring interpretation in a conserved representation learned from perturbation data, IRIS provides a common reference frame. Two studies of different tissues, generated with different protocols, can be projected into the same signaling space and compared directly. This harmonizing function may prove as valuable as the reconstruction itself, because it converts fragmented, experiment-specific observations into a cumulative, comparable body of knowledge about how signaling operates across the body.

Like any ambitious computational method, IRIS rests on assumptions that will require continued scrutiny. Transfer learning works best when the source and target domains genuinely share underlying structure, and while core signaling circuits are indeed conserved, in vivo contexts introduce regulatory layers — mechanical forces, metabolic gradients, three-dimensional tissue organization — that in vitro screens cannot fully represent. The framework’s predictions are inferences, not direct measurements, and experimental validation in specific biological systems remains essential. The authors position the tool as a hypothesis-generating engine: it nominates the signaling events most likely to have shaped a cell, which experimentalists can then test with targeted perturbations, phosphoproteomics or lineage tracing. In this sense, IRIS does not replace laboratory investigation but directs it, concentrating experimental effort on the most informative hypotheses.

The broader significance of the work lies in what it signals about the trajectory of computational biology. The field is moving from descriptive cataloguing — enumerating the cell types present in a tissue — toward mechanistic reconstruction, in which algorithms infer the dynamic processes that generated the observed states. Perturbation screens supply the causal grammar; transfer learning supplies the bridge from controlled experiments to natural contexts. Together they suggest a future in which a routine single-cell dataset can be reinterpreted not as a static census but as a record of conversations between cells and their environments. For a discipline built on snapshots, the ability to reconstruct history from a single frame is a genuinely transformative shift, and IRIS offers a concrete, testable route toward that goal.

Subject of Research: Reconstructing single-cell signaling states and histories using perturbation screens and transfer learning.

Article Title: Reconstructing signaling histories of single cells via perturbation screens and transfer learning

Article References: Hutchins, N. T., Meziane, M., Lu, C., Mitalipova, M., Fischer, D. S., & Li, P. (2026). Reconstructing signaling histories of single cells via perturbation screens and transfer learning. Nature Methods. https://doi.org/10.1038/s41592-026-03213-8

Image Credits: AI Generated

DOI: 10.1038/s41592-026-03213-8

Keywords: single-cell sequencing, signaling pathways, perturbation screens, transfer learning, IRIS, in vivo cellular contexts, computational biology, tumor microenvironment, signaling history reconstruction, Nature Methods, Reconstructing, signaling