Incorporating plant phenological responses into species distribution models reduces estimates of future species loss and turnover.

Anthropogenetic climate change has caused range shifts among many species. Species distribution models (SDMs) are used to predict how species ranges may change in the future. However, most SDMs rarely consider how climate-sensitive traits, such as phenology, which affect individuals' demography and fitness, may influence species' ranges. Using > 120 000 herbarium specimens representing 360 plant species distributed across the eastern United States, we developed a novel 'phenology-informed' SDM that integrates phenological responses to changing climates. We compared the ranges of each species forecast by the phenology-informed SDM with those from conventional SDMs. We further validated the modeling approach using hindcasting. When examining the range changes of all species, our phenology-informed SDMs forecast less species loss and turnover under climate change than conventional SDMs. These results suggest that dynamic phenological responses of species may help them adjust their ecological niches and persist in their habitats as the climate changes. Plant phenology can modulate species' responses to climate change, mitigating its negative effects on species persistence. Further application of our framework will contribute to a generalized understanding of how traits affect species distributions along environmental gradients and facilitate the use of trait-based SDMs across spatial and taxonomic scales.

Plasticity and not adaptation is the primary source of temperature-mediated variation in flowering phenology in North America.

Phenology varies widely over space and time because of its sensitivity to climate. However, whether phenological variation is primarily generated by rapid organismal responses (plasticity) or local adaptation remains unresolved. Here we used 1,038,027 herbarium specimens representing 1,605 species from the continental United States to measure flowering-time sensitivity to temperature over time (Stime) and space (Sspace). By comparing these estimates, we inferred how adaptation and plasticity historically influenced phenology along temperature gradients and how their contributions vary among species with different phenology and native climates and among ecoregions differing in species composition. Parameters Sspace and Stime were positively correlated (r = 0.87), of similar magnitude and more frequently consistent with plasticity than adaptation. Apparent plasticity and adaptation generated earlier flowering in spring, limited responsiveness in late summer and delayed flowering in autumn in response to temperature increases. Nonetheless, ecoregions differed in the relative contributions of adaptation and plasticity, from consistently greater importance of plasticity (for example, southeastern United States plains) to their nearly equal importance throughout the season (for example, Western Sierra Madre Piedmont). Our results support the hypothesis that plasticity is the primary driver of flowering-time variation along temperature gradients, with local adaptation having a widespread but comparatively limited role.

Mitochondrial matrix RTN4IP1/OPA10 is an oxidoreductase for coenzyme Q synthesis.

Targeting proximity-labeling enzymes to specific cellular locations is a viable strategy for profiling subcellular proteomes. Here, we generated transgenic mice (MAX-Tg) expressing a mitochondrial matrix-targeted ascorbate peroxidase. Comparative analysis of matrix proteomes from the muscle tissues showed differential enrichment of mitochondrial proteins. We found that reticulon 4-interacting protein 1 (RTN4IP1), also known as optic atrophy-10, is enriched in the mitochondrial matrix of muscle tissues and is an NADPH oxidoreductase. Interactome analysis and in vitro enzymatic assays revealed an essential role for RTN4IP1 in coenzyme Q (CoQ) biosynthesis by regulating the O-methylation activity of COQ3. Rtn4ip1-knockout myoblasts had markedly decreased CoQ9 levels and impaired cellular respiration. Furthermore, muscle-specific knockdown of dRtn4ip1 in flies resulted in impaired muscle function, which was reversed by dietary supplementation with soluble CoQ. Collectively, these results demonstrate that RTN4IP1 is a mitochondrial NAD(P)H oxidoreductase essential for supporting mitochondrial respiration activity in the muscle tissue.

Mitochondrial matrix protein LETMD1 maintains thermogenic capacity of brown adipose tissue in male mice.

Brown adipose tissue (BAT) has abundant mitochondria with the unique capability of generating heat via uncoupled respiration. Mitochondrial uncoupling protein 1 (UCP1) is activated in BAT during cold stress and dissipates mitochondrial proton motive force generated by the electron transport chain to generate heat. However, other mitochondrial factors required for brown adipocyte respiration and thermogenesis under cold stress are largely unknown. Here, we show LETM1 domain-containing protein 1 (LETMD1) is a BAT-enriched and cold-induced protein required for cold-stimulated respiration and thermogenesis of BAT. Proximity labeling studies reveal that LETMD1 is a mitochondrial matrix protein. Letmd1 knockout male mice display aberrant BAT mitochondria and fail to carry out adaptive thermogenesis under cold stress. Letmd1 knockout BAT is deficient in oxidative phosphorylation (OXPHOS) complex proteins and has impaired mitochondrial respiration. In addition, BAT-specific Letmd1 deficient mice exhibit phenotypes identical to those observed in Letmd1 knockout mice. Collectively, we demonstrate that the BAT-enriched mitochondrial matrix protein LETMD1 plays a tissue-autonomous role that is essential for BAT mitochondrial function and thermogenesis.

Augmented Reality Navigation Can Achieve Accurate Coronal Component Alignment During Total Knee Arthroplasty.

Background Computer-navigated knee arthroplasty has been shown to improve accuracy over conventional instruments. The next generation of computer assistance is being developed using augmented reality. The accuracy of augmented reality navigation has not been established. Methods From April 2021 to October 2021, a prospective, consecutive series of 20 patients underwent total knee arthroplasty utilising an augmented reality-assisted navigation system (ARAN). The coronal and sagittal alignment of the femoral and tibial bone cuts was measured using the ARAN and the final position of the components was measured on postoperative CT scans. The absolute difference between the measurements was recorded to determine the accuracy of the ARAN. Results Two cases were excluded due to segmentation errors, leaving 18 cases for analysis. The ARAN produced a mean absolute error of 1.4°, 2.0°, 1.1° and 1.6° for the femoral coronal, femoral sagittal, tibial coronal and tibial sagittal alignments, respectively. No outliers (absolute error of >3°) were identified in femoral coronal or tibial coronal alignment measurements. Three outliers were identified in tibial sagittal alignment, with all cases demonstrating less tibial slope (by 3.1°, 3.3° and 4°). Five outliers were identified in femoral sagittal alignment and in all cases, the component was more extended (3.1°, 3.2°, 3.2°, 3.4° and 3.9°). The mean operative time significantly decreased from the first nine augmented reality cases to the final nine cases by 11 minutes (p<0.05). There was no difference in the accuracy between the early and late ARAN cases. Conclusion Augmented reality navigation can achieve accurate alignment of total knee arthroplasty with a low rate of component malposition in the coronal plane. Acceptable and consistent accuracy can be achieved from the initial adoption of this technique, however, some sagittal outliers were identified and there is a clear learning curve with respect to operating time. The level of evidence was IV.

Relationships of climate, human activity, and fire history to spatiotemporal variation in annual fire probability across California.

In the face of recent wildfires across the Western United States, it is essential that we understand both the dynamics that drive the spatial distribution of wildfire, and the major obstacles to modeling the probability of wildfire over space and time. However, it is well documented that the precise relationships of local vegetation, climate, and ignitions, and how they influence fire dynamics, may vary over space and among local climate, vegetation, and land use regimes. This raises questions not only as to the nature of the potentially nonlinear relationships between local conditions and the fire, but also the possibility that the scale at which such models are developed may be critical to their predictive power and to the apparent relationship of local conditions to wildfire. In this study we demonstrate that both local climate-through limitations posed by fuel dryness (CWD) and availability (AET)-and human activity-through housing density, roads, electrical infrastructure, and agriculture, play important roles in determining the annual probabilities of fire throughout California. We also document the importance of previous burn events as potential barriers to fire in some environments, until enough time has passed for vegetation to regenerate sufficiently to sustain subsequent wildfires. We also demonstrate that long-term and short-term climate variations exhibit different effects on annual fire probability, with short-term climate variations primarily impacting fire probability during periods of extreme climate anomaly. Further, we show that, when using nonlinear modeling techniques, broad-scale fire probability models can outperform localized models at predicting annual fire probability. Finally, this study represents a powerful tool for mapping local fire probability across the state of California under a variety of historical climate regimes, which is essential to avoided emissions modeling, carbon accounting, and hazard severity mapping for the application of fire-resistant building codes across the state of California.

Novel Molecular Mechanism of Lenalidomide in Myeloid Malignancies Independent of Deletion of Chromosome 5q.

Lenalidomide as well as other immunomodulatory drugs (IMiDs) have achieved clinical efficacies in certain sub-types of hematologic malignancies, such as multiple myeloma, lower-risk myelodysplastic syndromes (MDS) with a single deletion of chromosome 5q (del(5q)) and others. Despite superior clinical response to lenalidomide in hematologic malignancies, relapse and resistance remains a problem in IMiD-based therapy. The last ten years have witnessed the discovery of novel molecular mechanism of IMiD-based anti-tumor therapy. IMiDs bind human cereblon (CRBN), the substrate receptor of the CRL4 E3 ubiquitin ligase complex. Binding of CRBN with IMiDs leads to degradation of the Ikaros family zinc finger proteins 1 and 3 (IKZF1 and IKZF3) and casein kinase 1 alpha. We have found that lenalidomide-mediated degradation of IKZF1 leads to activation of the G protein-coupled receptor 68 (GPR68)/calcium/calpain pro-apoptotic pathway and inhibition of the regulator of calcineurin 1 (RCAN1)/calcineurin pro-survival pathway in MDS and acute myeloid leukemia (AML). Calcineurin inhibitor Cyclosporin-A potentiates the anti-leukemia activity of lenalidomide in MDS/AML with or without del(5q). These findings broaden the therapeutic potential of IMiDs. This review summarizes novel molecular mechanism of lenalidomide in myeloid malignancies, especially without del(5q), in the hope to highlight novel therapeutic targets.

Spatial Regulation of Reactive Oxygen Species via G6PD in Brown Adipocytes Supports Thermogenic Function.

Reactive oxygen species (ROS) are associated with various roles of brown adipocytes. Glucose-6-phosphate dehydrogenase (G6PD) controls cellular redox potentials by producing NADPH. Although G6PD upregulates cellular ROS levels in white adipocytes, the roles of G6PD in brown adipocytes remain elusive. Here, we found that G6PD defect in brown adipocytes impaired thermogenic function through excessive cytosolic ROS accumulation. Upon cold exposure, G6PD-deficient mutant (G6PDmut) mice exhibited cold intolerance and downregulated thermogenic gene expression in brown adipose tissue (BAT). In addition, G6PD-deficient brown adipocytes had increased cytosolic ROS levels, leading to extracellular signal-regulated kinase (ERK) activation. In BAT of G6PDmut mice, administration of antioxidant restored the thermogenic activity by potentiating thermogenic gene expression and relieving ERK activation. Consistently, body temperature and thermogenic execution were rescued by ERK inhibition in cold-exposed G6PDmut mice. Taken together, these data suggest that G6PD in brown adipocytes would protect against cytosolic oxidative stress, leading to cold-induced thermogenesis.

Dynamic tracking and identification of tissue-specific secretory proteins in the circulation of live mice.

Secretory proteins are an essential component of interorgan communication networks that regulate animal physiology. Current approaches for identifying secretory proteins from specific cell and tissue types are largely limited to in vitro or ex vivo models which often fail to recapitulate in vivo biology. As such, there is mounting interest in developing in vivo analytical tools that can provide accurate information on the origin, identity, and spatiotemporal dynamics of secretory proteins. Here, we describe iSLET (in situ Secretory protein Labeling via ER-anchored TurboID) which selectively labels proteins that transit through the classical secretory pathway via catalytic actions of Sec61b-TurboID, a proximity labeling enzyme anchored in the ER lumen. To validate iSLET in a whole-body system, we express iSLET in the mouse liver and demonstrate efficient labeling of liver secretory proteins which could be tracked and identified within circulating blood plasma. Furthermore, proteomic analysis of the labeled liver secretome enriched from liver iSLET mouse plasma is highly consistent with previous reports of liver secretory protein profiles. Taken together, iSLET is a versatile and powerful tool for studying spatiotemporal dynamics of secretory proteins, a valuable class of biomarkers and therapeutic targets.

Advancing frost dates have reduced frost risk among most North American angiosperms since 1980.

In recent decades, the final frost dates of winter have advanced throughout North America, and many angiosperm taxa have simultaneously advanced their flowering times as the climate has warmed. Phenological advancement may reduce plant fitness, as flowering prior to the final frost date of the winter/spring transition may damage flower buds or open flowers, limiting fruit and seed production. The risk of floral exposure to frost in the recent past and in the future, however, also depends on whether the last day of winter frost is advancing more rapidly, or less rapidly, than the date of onset of flowering in response to climate warming. This study presents the first continental-scale assessment of recent changes in frost risk to floral tissues, using digital records of 475,694 herbarium specimens representing 1,653 angiosperm species collected across North America from 1920 to 2015. For most species, among sites from which they have been collected, dates of last frost have advanced much more rapidly than flowering dates. As a result, frost risk has declined in 66% of sampled species. Moreover, exotic species consistently exhibit lower frost risk than native species, primarily because the former occupy warmer habitats where the annual frost-free period begins earlier. While reducing the probability of exposure to frost has clear benefits for the survival of flower buds and flowers, such phenological advancement may disrupt other ecological processes across North America, including pollination, herbivory, and disease transmission.

A new phenological metric for use in pheno-climatic models: A case study using herbarium specimens of Streptanthus tortuosus.

PREMISE: Herbarium specimens have been used to detect climate-induced shifts in flowering time by using the day of year of collection (DOY) as a proxy for first or peak flowering date. Variation among herbarium sheets in their phenological status, however, undermines the assumption that DOY accurately represents any particular phenophase. Ignoring this variation can reduce the explanatory power of pheno-climatic models (PCMs) designed to predict the effects of climate on flowering date. METHODS: Here we present a protocol for the phenological scoring of imaged herbarium specimens using an ImageJ plugin, and we introduce a quantitative metric of a specimen's phenological status, the phenological index (PI), which we use in PCMs to control for phenological variation among specimens of Streptanthus tortuosus (Brassicaceeae) when testing for the effects of climate on DOY. We demonstrate that including PI as an independent variable improves model fit. RESULTS: Including PI in PCMs increased the model R 2 relative to PCMs that excluded PI; regression coefficients for climatic parameters, however, remained constant. DISCUSSION: Our protocol provides a simple, quantitative phenological metric for any observed plant. Including PI in PCMs increases R 2 and enables predictions of the DOY of any phenophase under any specified climatic conditions.

PhenoForecaster: A software package for the prediction of flowering phenology.

PREMISE OF THE STUDY: Predicting the flowering times of angiosperm taxa is a goal of mounting importance in the face of future climate change, with applications not only in plant biology and ecology, but also horticulture, agriculture, and invasive species management. To date, no tool is available to facilitate predictions of flowering phenology using multivariate phenoclimatic models. Such a tool is needed by researchers and other stakeholders who need to predict phenological activity, but are unfamiliar with phenoclimate modeling techniques. PhenoForecaster allows users of any background to conduct species-specific phenological predictions using an intuitive graphical interface and provides an estimate of each prediction's accuracy. METHODS AND RESULTS: Elastic net regression techniques were used to develop species-specific models capable of predicting the flowering dates of 2320 angiosperm species. CONCLUSIONS: PhenoForecaster is the first stand-alone package to make phenological modeling directly accessible to users without the need for in-depth phenological observations.

Overlooked climate parameters best predict flowering onset: Assessing phenological models using the elastic net.

Determining the manner in which plant species shift their flowering times in response to climatic conditions is essential to understanding and forecasting the impacts of climate change on the world's flora. The limited taxonomic diversity and duration of most phenological datasets, however, have impeded a comprehensive, systematic determination of the best predictors of flowering phenology. Additionally, many studies of the relationship between climate conditions and plant phenology have included only a limited set of climate parameters that are often chosen a priori and may therefore overlook those parameters to which plants are most phenologically sensitive. This study harnesses 894,392 digital herbarium records and 1,959 in situ observations to produce the first assessment of the effects of a large number (25) of climate parameters on the flowering time of a very large number (2,468) of angiosperm taxa throughout North America. In addition, we compare the predictive capacity of phenological models constructed from the collection dates of herbarium specimens vs. repeated in situ observations of individual plants using a regression approach-elastic net regularization-that has not previously been used in phenological modeling, but exhibits several advantages over ordinary least squares and stepwise regression. When herbarium-derived data and in situ phenological observations were used to predict flowering onset, the multivariate models based on each of these data sources had similar predictive capacity (R2  = 0.27). Further, apart from mean maximum temperature (TMAX), the two best predictors of flowering time have not commonly been included in phenological models: the number of frost-free days (NFFD) and the quantity of precipitation as snow (PAS) in the seasons preceding flowering. By vetting these models across an unprecedented number of taxa, this work demonstrates a new approach to phenological modeling.

Surgical management of negative dysphotopsia.

PURPOSE: To evaluate curative and preventative surgical strategies for negative dysphotopsia. SETTING: Private practice, Los Angeles, California, USA. DESIGN: Retrospective case series. METHODS: Patients with self-reported chronic negative dysphotopsia had corrective surgery as the therapeutic group. Second eye surgery, in cases with negative dysphotopsia in the previously operated eye, comprised the preventative group. Chronologically, several surgical strategies were used, including bag-to-bag intraocular lens (IOL) exchange, reducing posterior chamber depth, piggyback secondary IOL placement, bag-to-sulcus IOL exchange, and reverse optic capture. The primary outcome measure was improvement of negative dysphotopsia by 3 months postoperatively. RESULTS: The therapeutic group comprised 40 eyes of 37 patients; 76.6% of causative IOLs were acrylic and 23.4% were silicone and all were bag-fixated. There were 21 eyes in the preventative group of which 11 were second eyes from the therapeutic group; the remaining 10 did not require surgery for the symptomatic eye. Successful outcomes for each surgical strategy were as follows: bag-to-bag IOL exchange (0/5), a reduction in posterior chamber depth with iris suture fixation of the bag-haptic complex (0/1), piggyback secondary IOL (8/11), secondary reverse optic capture (21/22), ciliary sulcus posterior chamber IOL exchange (7/8), and primary reverse optic capture (21/21). CONCLUSIONS: Negative dysphotopsia was associated with acrylic or silicone IOLs of either square- or round-edge design. Negative dysphotopsia was reduced, eliminated, or prevented when the IOL optic overlaid the anterior capsulotomy rather than when the capsule edge overlaid the optic. Bag-to-sulcus IOL exchange and reverse optic capture were highly successful in managing or preventing negative dysphotopsia.

Long-term herbarium records reveal temperature-dependent changes in flowering phenology in the southeastern USA.

In recent years, a growing body of evidence has emerged indicating that the relationship between flowering phenology and climate may differ throughout various portions of the growing season. These differences have resulted in long-term changes in flowering synchrony that may alter the quantity and diversity of pollinator attention to many species, as well as altering food availability to pollenivorous and nectarivorous animal species. However, long-term multi-season records of past flowering timing have primarily focused on temperate environments. In contrast, changes in flowering phenology within humid subtropical environments such as the southeastern USA remain poorly documented. This research uses herbarium-based methods to examine changes in flowering time across 19,328 samples of spring-, summer-, and autumn-flowering plants in the southeastern USA from the years 1951 to 2009. In this study, species that flower near the onset of the growing season were found to advance under increasing mean March temperatures (-3.391 days/°C, p = 0.022). No long-term advances in early spring flowering or spring temperature were detected during this period, corroborating previous phenological assessments for the southeastern USA. However, late spring through mid-summer flowering exhibited delays in response to higher February temperatures (over 0.1.85 days/°C, p ≤ 0.041 in all cases). Thus, it appears that flowering synchrony may undergo significant restructuring in response to warming spring temperatures, even in humid subtropical environments.

Digital herbarium archives as a spatially extensive, taxonomically discriminate phenological record; a comparison to MODIS satellite imagery.

This study demonstrates that phenological information included in digital herbarium archives can produce annual phenological estimates correlated to satellite-derived green wave phenology at a regional scale (R = 0.183, P = 0.03). Thus, such records may be utilized in a fashion similar to other annual phenological records and, due to their longer duration and ability to discriminate among the various components of the plant community, hold significant potential for use in future research to supplement the deficiencies of other data sources as well as address a wide array of important issues in ecology and bioclimatology that cannot be addressed easily using more traditional methods.