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At least 253 records · Page 14

A simplified protocol for the automated production of 2‐[ 18 F]fluoro‐3‐[2‐((S)‐3‐pyrrolinyl)methoxy]pyridine ([ 18 F]nifene) on an IBA Synthera® module

The α4β2 nicotinic acetylcholine receptor (nAChR) ligand 2‐[18F]fluoro‐3‐[2‐((S)‐3‐pyrrolinyl)methoxy]pyridine ([18F]nifene) has been synthesized in 10% decay‐corrected radiochemical yield using the IBA Synthera® platform (IBA Cyclotron Solutions, Louvain‐la‐Neuve, Belgium) with an integrated fluidic processor (IFP). Boc‐nitronifene served as the precursor, and 20% trifluoroacetic acid (TFA) was used to deprotect the Boc‐group after radiolabeling. By omitting the solvent extraction step after radiolabeling, the process was simplified to a single step with no manual intervention. [18F]Nifene was obtained in decay‐corrected radiochemical yields of 10 ± 2% (n = 20) and radiochemical purity >99%. Typical specific radioactivities of 2700–4865 mCi/μmole (100–180 GBq/μmol) were measured at the end of synthesis; total synthesis times were about 1 h 40 min.

IBA Synthera®↗

Flaxseed oil ameliorates aging in d ‐galactose induced rats via altering gut microbiota and mitigating oxidative damage

Abstract BACKGROUND Aging causes decreased antioxidant capacity and chronic inflammation and may even elevate cancer risks. Previous studies reported that flaxseed oil (FO) can alleviate age‐related diseases, including improving alcoholic liver disease, atherosclerosis and diabetes. However, whether the intestinal microbiota accountable for this alleviation is still unknown. This study aims to study the antioxidant effects of FO in an aging rat model and the underlying mechanism between the intestinal microbiota and aging. RESULTS Our results presented that serum and liver antioxidant capacities in FO group were up‐regulated, and liver inflammation in FO group was reduced. The 16S rDNA sequencing showed that FO regulated the microbial community, including up‐regulation of four families of Lactobacillus and six families of Clostridium. In addition, FO had also adjusted the relative abundance of several genera such as Ruminococcaceae_UCG‐005 and Prevotella_9 , which may be the key bacteria associated with the aging process. Colonic transcriptome analysis showed that there were 1679 differentially expressed genes (DEGs) in the Model group and the FO group (134 up‐regulated and 1545 down‐regulated). Gene set enrichment analysis (GSEA) revealed FO down‐regulates the expression of the upstream genes Ptprc , Lck , Zap70 , Lat and Lcp2 in the T cell receptor signaling pathway. CONCLUSION In conclusion, FO improved antioxidant capacity and reduced intestinal microbial disturbances caused by aging damage, indicating that dietary FO has the potential to fight aging damage. This study provides a more comprehensive view of dietary intervention to improve aging. © 2022 Society of Chemical Industry.

Sun, Xiaoyan↗

Neuroprotectin D1 Attenuates Blast Overpressure Induced Reactive Microglial Cells in the Cochlea

Objective/Hypothesis We examined a neuroinflammatory response associated with glial activation in the cochlea exposed to blast overpressure and evaluated the potential therapeutic efficacy of specialized pro‐resolving mediators such as neuroprotectin D1, NPD1; (10R, 17S‐dihydroxy‐4Z, 7Z, 11E, 13E, 15Z, 19Z‐docosahexaenoic acid) in a rodent blast‐induced auditory injury model. Study Design Animal Research. Methods A compressed‐air driven shock tube was used to expose anesthetized adult male Long‐Evan rats to shock waves simulating an open‐field blast exposure. Approximately 30 minutes after blast exposure, rats were treated with NPD1 (100 ng/kg body wt.) or vehicle delivered intravenously via tail vein injection. Rats were then euthanized 48 hours after blast exposure. Unexposed rats were included as controls. Tissue sections containing both middle and inner ear were prepared with hematoxylin–eosin staining to elucidate histopathological changes associated with blast exposure. Cochlear tissues were evaluated for relative expression of ionized calcium‐binding adaptor 1 (Iba1), as an indicator of microglial activation by immunohistochemistry and western blot analyses. Results Our animal model resulted in an acute injury mechanism manifested by damage to the tympanic membrane, hemorrhage, infiltration of inflammatory cells, and increased expression of Iba1 protein. Moreover, therapeutic intervention with NPD1 significantly reduced Iba1 expression in the cochlea, suggesting a reduction of a neuroinflammatory response caused by blast overpressure. Conclusions Blast overpressure resulted in an increased expression of proteins involved in gliosis within the auditory system, which were reduced by NPD1. Treatment of NPD1 suggests an effective strategy to reduce or halt auditory microglial cell activation due to primary blast exposure. Level of Evidence NA Laryngoscope , 131:E2018–E2025, 2021

Ríos, José David↗

Gender gap in perspectives of the impacts of degradation and restoration on ecosystem services in Ethiopia

Abstract The importance of land restoration has garnered increasing attention on the global stage through large‐scale initiatives such as the Bonn Challenge. However, policies and strategies are often gender‐blind and designed in compliance with entrenched social hierarchies, exacerbating pre‐existing social inequalities that affect restoration initiatives. The challenge of developing gender‐responsive policies and initiatives is accentuated by a persistent lack of sex‐disaggregated data concerning men's and women's differing perceptions and experiences. This study aims to help fill this gap by capturing the differences in men and women's perceptions of ecosystem services before and after restoration interventions in Ethiopia. Towards that end, in October 2021, we collected data from fifty‐nine (59) paired husband‐wife households and six gender‐segregated focus group discussions in two regions of Ethiopia: Amhara and Southern Nations, and Nationalities and Peoples (SNNP). Kendall's concordance analysis established a strong degree of disagreement between men's and women's ratings of restoration outcomes for most indicators. Men attributed degradation to landscape conditions and natural forces, while women considered the lack of appropriate restoration strategies as a precursor for accelerated degradation. The study also reveals that men tended to benefit more than women from enhanced ecosystem services post‐restoration, with increased labour and land management burdens often falling on the shoulders of women. Based on these findings, we argue that including men's and women's perspectives from the earliest planning phases of restoration initiatives is essential to ensure greater equity in benefit‐sharing, mitigate trade‐offs for women, and build more nuanced, just and successful approaches to restoration.

Mponela, Powell↗

Development and cross‐validation of a circumference‐based predictive equation to estimate body fat in an active population

Abstract Objective The U.S. Army uses sex‐specific circumference‐based prediction equations to estimate percent body fat (%BF) to evaluate adherence to body composition standards. The equations are periodically evaluated to ensure that they continue to accurately assess %BF in a diverse population. The objective of this study was to develop and validate alternative field expedient equations that may improve upon the current Army Regulation (AR) body fat (%BF) equations. Methods Body size and composition were evaluated in a representatively sampled cohort of 1904 active‐duty Soldiers (1261 Males, 643 Females), using dual‐energy X‐ray absorptiometry (%BF DXA ), and circumferences obtained with 3D imaging and manual measurements. Sex stratified linear prediction equations for %BF were constructed using internal cross validation with %BF DXA as the criterion measure. Prediction equations were evaluated for accuracy and precision using root mean squared error, bias, and intraclass correlations. Equations were externally validated in a convenient sample of 1073 Soldiers. Results Three new equations were developed using one to three circumference sites. The predictive values of waist, abdomen, hip circumference, weight and height were evaluated. Changing from a 3‐site model to a 1‐site model had minimal impact on measurements of model accuracy and performance. Male‐specific equations demonstrated larger gains in accuracy, whereas female‐specific equations resulted in minor improvements in accuracy compared to existing AR equations. Equations performed similarly in the second external validation cohort. Conclusions The equations developed improved upon the current AR equation while demonstrating robust and consistent results within an external population. The 1‐site waist circumference‐based equation utilized the abdominal measurement, which aligns with associated obesity related health outcomes. This could be used to identify individuals at risk for negative health outcomes for earlier intervention.

Taylor, Kathryn M.↗

Characterization of Cytokine Treatment on Human Pancreatic Islets by Top‐Down Proteomics

Type 1 diabetes (T1D) results from autoimmune-mediated destruction of insulin-producing β cells in the pancreatic islet. This process is modulated by pro-inflammatory cytokine signaling, which has been previously shown to alter protein expression in ex vivo islets. Herein, we applied top-down proteomics to globally evaluate proteoforms from human islets treated with proinflammatory cytokines (interferon-γ and interleukin-1β). We measured 1636 unique proteoforms across six donors and two time points (control and 24 h post-treatment) and observed consistent changes in abundance across the glicentin-related pancreatic polypeptide (GRPP) and major proglucagon fragment regions of glucagon, as well as the LF-19/catestatin and vasostatin-1/2 region of chromogranin-A. We also observe several proteoforms that increase after cytokine-treatment or are exclusively observed after cytokine-treatment, including forms of beta-2 microglobulin (B2M), high-mobility group N2 protein (HMGN2), and chemokine (C-X-C motif) ligands (CXCL). Together, our quantitative results provide a baseline proteoform profile for human islets and identify several proteoforms that may serve as interesting candidate markers for T1D progression or therapeutic intervention.

glucagon↗

Haze–cloud correlations mediated by supersaturation fluctuations

Atmospheric aerosol particles that contain water-soluble components can absorb water vapor in humid environments and form either haze particles or cloud droplets, depending on supersaturation conditions. Laboratory and in situ measurements have shown that haze particles and cloud droplets often coexist and compete for available water vapor in shallow clouds and fogs, especially under polluted conditions. It is expected that more aerosol particles can form more haze particles and cloud droplets, so that the haze and cloud number concentrations are positively correlated. However, recent large-eddy simulations show that haze and cloud number concentration can be negatively correlated under extremely polluted conditions. Haze–cloud interactions across different environmental settings remain poorly understood. In this study, experiments in a convection cloud chamber with the same aerosol injection rate show that, as supersaturation forcing increases (i.e., changing from polluted to clean conditions), the covariance between haze and cloud droplet number concentration changes from negative to positive and finally to zero. Large-eddy simulations (LES) of the cloud chamber with a fixed supersaturation forcing but varying aerosol injection rates show a similar result for the haze–cloud correlation: near zero in clean, mean-supersaturation-dominated activation conditions; positive in moderate, supersaturation-fluctuation-influenced activation conditions; and negative in polluted, supersaturation-fluctuation-dominated activation conditions. A theoretical covariance framework was developed to interpret this behavior based on the relative magnitude and signs of the correlations between supersaturation and the populations of haze and cloud droplets. Significantly, experiments, LES, and theory all yield the same three-regime behavior for the sign of the haze–cloud covariance. Furthermore, our results show that the haze–cloud covariance remains robust and easily measurable, thereby providing a useful metric for regime identification in the atmosphere, improving regime-aware parameterizations, and informing aerosol interventions such as fog dispersion, rainfall enhancement, and albedo modification.

54 ENVIRONMENTAL SCIENCES↗

Bayesian Calibration of Stochastic Agent Based Model via Random Forest

Agent-based models (ABM) provide an excellent framework for modeling outbreaks and interventions in epidemiology by explicitly accounting for diverse individual interactions and environments. However, these models are usually stochastic and highly parametrized, requiring precise calibration for predictive performance. When considering realistic numbers of agents and properly accounting for stochasticity, this high-dimensional calibration can be computationally prohibitive. This paper presents a random forest-based surrogate modeling technique to accelerate the evaluation of ABMs and demonstrates its use to calibrate an epidemiological ABM named CityCOVID via Markov chain Monte Carlo (MCMC). The technique is first outlined in the context of CityCOVID's quantities of interest, namely hospitalizations and deaths, by exploring dimensionality reduction via temporal decomposition with principal component analysis (PCA) and via sensitivity analysis. The calibration problem is then presented, and samples are generated to best match COVID-19 hospitalization and death numbers in Chicago from March to June in 2020. Further, these results are compared with previous approximate Bayesian calibration (IMABC) results, and their predictive performance is analyzed, showing improved performance with a reduction in computation.

60 APPLIED LIFE SCIENCES↗

Ultrafast Early Warning of Heart Attacks through Plasmon‐Enhanced Raman Spectroscopy using Collapsible Nanofingers and Machine Learning

Abstract As the leading cause of death, heart attacks result in millions of deaths annually, with no end in sight. Early intervention is the only strategy for rescuing lives threatened by heart disease. However, the detection time of the fastest heart‐attack detection system is >15 min, which is too long considering the rapid passage of life. In this study, a machine learning (ML)‐driven system with a simple process, low‐cost, short detection time (only 10 s), and high precision is developed. By utilizing a functionalized nanofinger structure, even a trace amount of biomarker leaked before a heart attack can be captured. Additionally, enhanced Raman profiles are constructed for predictive analytics. Five ML models are developed to harness the useful characteristics of each Raman spectrum and provide early warnings of heart attacks with >98% accuracy. Through the strategic combination of nanofingers and ML algorithms, the proposed warning system accurately provides alerts on silent heart‐attack attempts seconds ahead of actual attacks.

60 APPLIED LIFE SCIENCES↗

Unraveling the Hsp70-ROS-autophagy axis in pentachlorophenol-challenged lung and liver epithelial cells

Pentachlorophenol (PCP) was extensively utilized as an organochlorine pesticide and wood preservative in the United States from the 1930s until the Environmental Protection Agency (EPA) imposed restrictions due to concerns about its toxicity and potential carcinogenic properties. Although it is no longer widely used, PCP remains a concern due to its environmental persistence and potential for long-term health effects. Significant occupational and environmental exposures have likely occurred, with the health and economic costs of PCP exposure potentially being substantial given its known toxicity. Notably, PCP exhibits rapid absorption through both the skin and respiratory system and has been shown to cause hepatotoxicity, developmental toxicity, immunotoxicity, irritation, and carcinogenicity in laboratory animal studies. PCP exposure induces oxidative stress, a key mechanism underlying its inflammatory and toxic effects, which can activate cellular stress responses including upregulation of heat shock protein 70 (Hsp70). Previous studies in lung and liver epithelial cells have shown that Hsp70 and oxidative stress play pivotal roles in triggering autophagy. This study establishes the critical role of the Hsp70-reactive oxygen species (ROS)-autophagy axis in regulating cellular responses to PCP exposure in human alveolar (A549) and liver carcinoma (HepG2) epithelial cells. Our research elucidated the molecular mechanisms underlying PCP's cellular effects, demonstrating that its exposure resulted in increased expression of autophagy-related proteins (Beclin-1, LC3B, ATG12, and ATG16), subunits of NADPH oxidase (NCF-1, NCF-2, NOX2, and Rac), and antioxidant proteins (SOD and GPx) in both lung and liver cell types. Notably, PCP augmented the interaction between Hsp70 and the autophagy regulator Beclin-1. Pretreatment with the ROS inhibitor N-acetylcysteine or Hsp70 knockdown markedly reversed PCP-induced responses. Our in-silico protein–protein docking analysis and molecular dynamics simulation studies revealed enhanced interactions and/or stable confirmations maintained throughout the simulations for TLR4-Hsp70 and Hsp70-Beclin-1 complexes in the presence of PCP. These findings provide a strong foundation for future studies, employing in vivo experimental models and human populations to identify promising targets for PCP-induced toxicity and cellular injury. As a result, these findings may have far-reaching implications for public health and environmental policy, ultimately leading to the identification of biomarkers and the development of more effective interventions for environmentally induced toxicity and diseases.

97 MATHEMATICS AND COMPUTING↗

Glycosylation of SARS-CoV-2: structural and functional insights

The COVID-19 pandemic is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Similar to other coronaviruses, its particles are composed of four structural proteins: spike (S), envelope (E), membrane (M), and nucleocapsid (N) proteins. S, E, and M proteins are glycosylated, and the N protein is phosphorylated. The S protein is involved in the interaction with the host receptor human angiotensin-converting enzyme 2 (hACE2), which is also heavily glycosylated. Recent studies have revealed several other potential host receptors or factors that can increase or modulate the SARS-CoV-2 infection. Interestingly, most of these molecules bear carbohydrate residues. While glycans acquired by the viruses through the hijacking of the host machinery help the viruses in their infectivity, they also play roles in immune evasion or modulation. Here, glycans play complex roles in viral pathobiology, both on their own and in association with carrier biomolecules, such as proteins or glycosaminoglycans (GAGs). Understanding these roles in detail can help in developing suitable strategies for prevention and therapy of COVID-19. In this review, we sought to emphasize the interplay of SARS-CoV-2 glycosylated proteins and their host receptors in viral attachment, entry, replication, and infection. Moreover, the implications for future therapeutic interventions targeting these glycosylated biomolecules are also discussed in detail.

59 BASIC BIOLOGICAL SCIENCES↗

A framework for detection and attribution of regional precipitation change: Application to the United States historical record

Abstract Despite the emerging influence of anthropogenic climate change on the global water cycle, at regional scales the combination of observational uncertainty, large internal variability, and modeling uncertainty undermine robust statements regarding the human influence on precipitation. Here, we use output from global climate models in a perfect-data sense to develop a framework for conducting regional detection and attribution (D&A) for precipitation, starting with the contiguous United States (CONUS) where observational uncertainty is lower than in other regions. Our unified approach can simultaneously detect systematic trends in mean and extreme precipitation, attribute trends to anthropogenic forcings, compute the effects of forcings as a function of time, and map the effects of individual forcings. Model output is used to conduct a set of tests that yield a parsimonious representation for characterizing seasonal precipitation over the CONUS for the historical record (1900 to present day), which ensures our D&A is insensitive to structural uncertainty. Our framework is developed using synthetic data in a Pearl-causal perspective wherein causality can be identified using intervention-based simulations. While the hypothesis-based framework and accompanying generalized D&A formula we develop should be widely applicable, we include a strong caution that the hypothesis-guided simplification of the formula for the historical climatic record of CONUS as described in this paper will likely fail to hold in other geographic regions and under future warming.

54 ENVIRONMENTAL SCIENCES↗

Sediment transport and morphodynamic changes due to upstream variation and sea level rise on the Western Mekong Delta, Vietnam

The hydrological and morphological dynamics across the Vietnam Mekong Delta (VMD) coastline are increasingly shaped by human interventions and climate change, affecting the sustainability of socio-economic environments. This study employs the TELEMAC-MASCARET modeling system (TELEMAC-2D, TOMAWAC, and SISYPHE modules) to simulate hydrodynamics, sediment transport, and morphological changes for a 10-year period under baseline (SC1) and future climate (SC2) scenarios, considering wave climatology of Northeast (NEM) and Southwest monsoons (SWM). The results of sedimentation and erosion were analyzed across five key coastal zones from Ca Mau Cape (KV1) to Ha Tien (KV5). Model results highlight distinct seasonal patterns of sediment redistribution shaped by monsoonal flows, wave action, and seabed morphology. During the NEM, sediment deposition is concentrated near estuarine zones, while the SWM favors offshore sediment accumulation due to perpendicular wave actions, and shallow, gently sloping bathymetry that dissipates wave energy. Coastal erosion predominantly occurs at convex shoreline features subjected to stronger coastal currents, particularly in fine-grained sediment areas. Under future sea level rise and land subsidence scenarios, reduced flow velocities lead to lower bottom shear stress, promoting deposition and mitigating erosion problems despite increased wave energy. Besides that, sediment transport analyses across 14 cross-sections (C-S) reveal a southward trend during the NEM and a northward reversal during the SWM, with upstream sediment reductions primarily influencing near-estuarine zones and exerting minimal impact beyond the mid-coastal regions. Furthermore, these findings advance the understanding of sediment redistribution processes under climate change and seasonal change, and provide a scientific basis for adaptive coastal management and sustainable development.

Climate change↗

Synthetic microbial communities: Bridging research and application in second-generation bioenergy feedstock microbiomes

The sustainable production of purpose-grown bioenergy feedstocks is essential in transitioning away from fossil fuels. Synthetic communities (SynComs) are consortia of microorganisms that can be used as biological interventions to support objectives like plant growth and stress tolerance. This review examines the state of knowledge regarding microbiomes and SynComs of second-generation bioenergy feedstocks, focusing on the rhizosphere. We first provide an overview of second-generation feedstocks, including switchgrass (Panicum virgatum), miscanthus (Miscanthus × giganteus), sorghum (Sorghum spp.), sugarcane (Saccharum spp.), and poplar (Populus spp.), and summarize our current understanding of their plant-soil-microbiome ecology. We next discuss considerations in the objectives, design, and evaluation of SynComs to enhance feedstock production, and then critically review the literature around their use. Our literature analysis revealed that SynCom performance varied substantially between controlled pilot experiments and field trials, possibly due to system complexity that could not be fully considered in their design and pilot evaluation. We identified a gap in the use of SynComs to support the unique sustainability objectives of biofuel feedstock agriculture, presenting an opportunity to leverage these additional microbial traits in SynCom designs. Finally, we emphasize the importance of targeted research to identify the ecological principles that govern the assembly, activation, and persistence of microbes in the feedstock rhizosphere, thereby enhancing our capacity to manage microbiomes under diverse environmental conditions and ensure their functionality. Beyond biofuels, SynComs are a promising microbiome management strategy for crop production; however, an ecologically informed design and evaluation of SynComs are advised.

SynCom↗

Impacts of Vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 Variants Alpha and Delta on Coronavirus Disease 2019 Transmission Dynamics in Four Metropolitan Areas of the United States

To characterize Coronavirus Disease 2019 (COVID-19) transmission dynamics in each of the metropolitan statistical areas (MSAs) surrounding Dallas, Houston, New York City, and Phoenix in 2020 and 2021, we extended a previously reported compartmental model accounting for effects of multiple distinct periods of non-pharmaceutical interventions by adding consideration of vaccination and Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants Alpha (lineage B.1.1.7) and Delta (lineage B.1.617.2). For each MSA, we found region-specific parameterizations of the model using daily reports of new COVID-19 cases available from January 21, 2020 to October 31, 2021. In the process, we obtained estimates of the relative infectiousness of Alpha and Delta as well as their takeoff times in each MSA (the times at which sustained transmission began). The estimated infectiousness of Alpha ranged from 1.1x to 1.4x that of viral strains circulating in 2020 and early 2021. The estimated relative infectiousness of Delta was higher in all cases, ranging from 1.6x to 2.1x. The estimated Alpha takeoff times ranged from February 1 to February 28, 2021. The estimated Delta takeoff times ranged from June 2 to June 26, 2021. In conclusion, estimated takeoff times are consistent with genomic surveillance data.

60 APPLIED LIFE SCIENCES↗

Adoption of image-driven machine learning for microstructure characterization and materials design: A Perspective

Microstructure characterization enables the development of structure-processing-property relationships critical to several research areas within the broad field of materials science, from alloy design to the assessment of corrosion resistance, and failure analysis. Conventional approaches to material characterization have relied on either qualitative inference by the human ex-pert or software applications that can extract high-level features from images, such as boundary segmentation, average grain diameter, etc. Such approaches rely heavily on subject matter expert user intervention and knowledge of what phases or more generally, what microstructural features, are of interest. The recent surge in the adoption of machine learning techniques to address problems in materials engineering has brought with it an increased interest and application of Image Driven Machine Learning (IDML) approaches. In this work, we review the applications of IDML to the field of materials characterization. A canonical hierarchy of stages is defined, which when put sequentially together completes an IDML study: problem definition, dataset building, model selection and training, model evaluation, and integration with existing instrumentation or simulation workflow. The studies reviewed in this work are analyzed from the perspective of each of these stages. Such a review permits agranular assessment of the field, for example the impact of IDML on materials characterization at the nanoscale, the size of a typical dataset required to train a semantic segmentation model on electron microscopy images, ubiquitousness of transfer learning in the domain, etc. Finally, we discuss the importance of interpretability and explainability in the field of IDML for materials characterization, and provide an overview of two emerging techniques in the field: semantic segmentation and generative adversarial networks.

Baskaran, Arun↗

A Framework for Closed-Loop Optimization of an Automated Mechanical Serial-Sectioning System via Run-to-Run Control as Applied to a Robo-Met.3D

Optimization of automated data collection is gaining increased interest for the purposes of enabling closed-loop self-correcting systems that inherently maximize operational efficiencies and reduce waste. Many data collection systems have several variables which influence data accuracy or consistency and which can require frequent user interaction to be monitored and maintained. Operating upon a Robo-MET.3D™ automated mechanical serial-sectioning system, a run-to-run control algorithm has been developed to accelerate data collection and reduce data inconsistency. Here, using historical data amassed over a decade of experiments, a linear regression model of the deterministic system dynamics is created and used to employ a run-to-run control algorithm that optimizes selected system inputs to reduce operator intervention and increase efficacy while reducing variance of system output.

42 ENGINEERING↗