Feedback Cycle Research Articles

IP3R-Mediated Calcium Release Promotes Ferroptotic Death in SH-SY5Y Neuroblastoma Cells.

Ferroptosis is an iron-dependent cell death pathway that involves the depletion of intracellular glutathione (GSH) levels and iron-mediated lipid peroxidation. Ferroptosis is experimentally caused by the inhibition of the cystine/glutamate antiporter xCT, which depletes cells of GSH, or by inhibition of glutathione peroxidase 4 (GPx4), a key regulator of lipid peroxidation. The events that occur between GPx4 inhibition and the execution of ferroptotic cell death are currently a matter of active research. Previous work has shown that calcium release from the endoplasmic reticulum (ER) mediated by ryanodine receptor (RyR) channels contributes to ferroptosis-induced cell death in primary hippocampal neurons. Here, we used SH-SY5Y neuroblastoma cells, which do not express RyR channels, to test if calcium release mediated by the inositol 1,4,5-trisphosphate receptor (IP3R) channel plays a role in this process. We show that treatment with RAS Selective Lethal Compound 3 (RSL3), a GPx4 inhibitor, enhanced reactive oxygen species (ROS) generation, increased cytoplasmic and mitochondrial calcium levels, increased lipid peroxidation, and caused cell death. The RSL3-induced calcium signals were inhibited by Xestospongin B, a specific inhibitor of the ER-resident IP3R calcium channel, by decreasing IP3R levels with carbachol and by IP3R1 knockdown, which also prevented the changes in cell morphology toward roundness induced by RSL3. Intracellular calcium chelation by incubation with BAPTA-AM inhibited RSL3-induced calcium signals, which were not affected by extracellular calcium depletion. We propose that GPx4 inhibition activates IP3R-mediated calcium release in SH-SY5Y cells, leading to increased cytoplasmic and mitochondrial calcium levels, which, in turn, stimulate ROS production and induce lipid peroxidation and cell death in a noxious positive feedback cycle.

Sox9 Accelerates Vascular Aging by Regulating Extracellular Matrix Composition and Stiffness.

Vascular calcification and increased extracellular matrix (ECM) stiffness are hallmarks of vascular aging. Sox9 (SRY-box transcription factor 9) has been implicated in vascular smooth muscle cell (VSMC) osteo/chondrogenic conversion; however, its relationship with aging and calcification has not been studied. Immunohistochemistry was performed on human aortic samples from young and aged patients. Young and senescent primary human VSMCs were induced to produce ECM, and Sox9 expression was manipulated using adenoviral overexpression and depletion. ECM properties were characterized using atomic force microscopy and proteomics, and VSMC phenotype on hydrogels and the ECM were examined using confocal microscopy. In vivo, Sox9 was not spatially associated with vascular calcification but correlated with the senescence marker p16 (cyclin-dependent kinase inhibitor 2A). In vitro Sox9 showed mechanosensitive responses with increased expression and nuclear translocation in senescent cells and on stiff matrices. Sox9 was found to regulate ECM stiffness and organization by orchestrating changes in collagen (Col) expression and reducing VSMC contractility, leading to the formation of an ECM that mirrored that of senescent cells. These ECM changes promoted phenotypic modulation of VSMCs, whereby senescent cells plated on ECM synthesized from cells depleted of Sox9 returned to a proliferative state, while proliferating cells on a matrix produced by Sox9 expressing cells showed reduced proliferation and increased DNA damage, reiterating features of senescent cells. LH3 (procollagen-lysine, 2-oxoglutarate 5-dioxygenase 3) was identified as an Sox9 target and key regulator of ECM stiffness. LH3 is packaged into extracellular vesicles and Sox9 promotes extracellular vesicle secretion, leading to increased LH3 deposition within the ECM. These findings highlight the crucial role of ECM structure and composition in regulating VSMC phenotype. We identify a positive feedback cycle, whereby cellular senescence and increased ECM stiffening promote Sox9 expression, which, in turn, drives further ECM modifications to further accelerate stiffening and senescence.

Direct T e-based Metallicities of z = 2–9 Galaxies with JWST/NIRSpec: Empirical Metallicity Calibrations Applicable from Reionization to Cosmic Noon

We report detections of the [O iii]λ4364 auroral emission line for 16 galaxies at z = 2.1–8.7, measured from JWST/NIRSpec observations obtained as part of the Cosmic Evolution Early Release Science (CEERS) survey program. We combine this CEERS sample with 9 objects from the literature at z = 4−9 with auroral-line detections from JWST/NIRSpec and 21 galaxies at z = 1.4−3.7 with auroral-line detections from ground-based spectroscopy. We derive electron temperature (T e) and direct-method oxygen abundances for the combined sample of 46 star-forming galaxies at z = 1.4−8.7. We use these measurements to construct the first high-redshift empirical T e-based metallicity calibrations for the strong-line ratios [O iii]/Hβ, [O ii]/Hβ, R23 = ([O iii]+[O ii])/Hβ, [O iii]/[O ii], and [Ne iii]/[O ii]. These new calibrations are valid over 12+log(O/H) = 7.4−8.3 and can be applied to samples of star-forming galaxies at z = 2−9, leading to an improvement in the accuracy of metallicity determinations at Cosmic Noon and in the Epoch of Reionization. The high-redshift strong-line relations are offset from calibrations based on typical z ∼ 0 galaxies or H ii regions, reflecting the known evolution of ionization conditions between z ∼ 0 and z ∼ 2. Deep spectroscopic programs with JWST/NIRSpec promise to improve statistics at the low and high ends of the metallicity range covered by the current sample, as well as to improve the detection rate of [N ii]λ6585 and thus allow the future assessment of N-based indicators. These new high-redshift calibrations will enable accurate characterizations of metallicity scaling relations at high redshift, improving our understanding of feedback and baryon cycling in the early Universe.

Implementing mainstream genetic counseling within the area-wide network of the German Consortium Hereditary Breast and Ovarian Cancer (GC-HBOC): Satisfaction of primary care providers with the provided state-of-the-art training by the Cologne Center.

The German Cancer Society (Deutsche Krebsgesellschaft DKG) has published a position paper to address the challenges of cancer patient care in the era of genomic medicine. The German Consortium Hereditary Breast and Ovarian Cancer (GC-HBOC) has implemented this recommendation in its care concept for families at risk. Core elements are the outcome-oriented evaluation of structured and standardized clinical measures and reporting recommendations derived therefrom to primary care providers and patients. A cross-sector network with certified breast cancer and gynecological cancer centers was founded in 2015, starting from the Cologne Center of the GC-HBOC. To guarantee the knowledge transfer for mainstream genetic counseling, the Cologne center has established an educational program for physicians and specialized nurses in order to pilot trans-sectoral knowledge transfer on risk assessment and risk-stratified care. It consists of face-to-face lectures with written knowledge test, attending a genetic case conference and genetic counseling sessions with the opportunity to counsel under supervision. The lectures were accompanied by a structured evaluation of the participants' satisfaction and feedback of the needs in mainstream genetic counseling. Thereby, the network ensures that genetic counseling and testing is provided according to state-of-the-art knowledge and allows physicians to participate in knowledge-generating care outside the university setting and patients to receive care close to home. After multiple feedback cycles to improve the educational program, the GC-HBOC, in cooperation with the German Cancer Society, has now adopted this concept and developed a common and uniform online curriculum funded by the Federal Ministry of Health. https://www.krebsgesellschaft.de/fortbildung-familiaerer-krebs.html.

Carbon cycle feedbacks in an idealized simulation and a scenario simulation of negative emissions in CMIP6 Earth system models

Abstract. Limiting global warming to well below 2 ∘C by the end of the century is an ambitious target that requires immediate and unprecedented emission reductions. In the absence of sufficient near-term mitigation, this target will only be achieved by carbon dioxide removal (CDR) from the atmosphere later during this century, which would entail a period of temperature overshoot. Aside from the socio-economic feasibility of large-scale CDR, which remains unclear, the effects on biogeochemical cycles and climate are key to assessing CDR as a mitigation option. Changes in atmospheric CO2 concentration and climate alter the CO2 exchange between the atmosphere and the underlying carbon reservoirs of the land and the ocean. Here, we investigate carbon cycle feedbacks under idealized and more realistic overshoot scenarios in an ensemble of Earth system models. The responses of oceanic and terrestrial carbon stocks to changes in atmospheric CO2 concentration and changes in surface climate (the carbon–concentration feedback and the carbon–climate feedback, quantified by the feedback metrics β and γ, respectively) show a large hysteresis. This hysteresis leads to growing absolute values of β and γ during phases of negative emissions. We find that this growth over time occurs such that the spatial patterns of feedbacks do not change significantly for individual models. We confirm that the β and γ feedback metrics are a relatively robust tool to characterize inter-model differences in feedback strength since the relative feedback strength remains largely stable between phases of positive and negative emissions and between different simulations, although exceptions exist. When the emissions become negative, we find that the model uncertainty (model disagreement) in β and γ increases more strongly than expected from the assumption that the uncertainties would accumulate linearly with time. This indicates that the model response to a change from increasing to decreasing forcing introduces an additional layer of uncertainty, at least in idealized simulations with a strong signal. We also briefly discuss the existing alternative definition of feedback metrics based on instantaneous carbon fluxes instead of carbon stocks and provide recommendations for the way forward and future model intercomparison projects.

Toward generalized Milankovitch theory (GMT)

Abstract. In recent decades, numerous paleoclimate records and results of model simulations have provided strong support for the astronomical theory of Quaternary glacial cycles formulated in its modern form by Milutin Milankovitch. At the same time, new findings have revealed that the classical Milankovitch theory is unable to explain a number of important facts, such as the change in the dominant periodicity of glacial cycles from 41 to 100 kyr about 1 million years ago. This transition was also accompanied by an increase in the amplitude and asymmetry of the glacial cycles. Here, based on the results of a hierarchy of models and data analysis, a framework of the extended (generalized) version of the Milankovitch theory is presented. To illustrate the main elements of this theory, a simple conceptual model of glacial cycles was developed using the results of an Earth system model, CLIMBER-2. This conceptual model explicitly assumes the multistability of the climate–cryosphere system and the instability of the “supercritical” ice sheets. Using this model, it is shown that Quaternary glacial cycles can be successfully reproduced as the strongly nonlinear response of the Earth system to the orbital forcing, where 100 kyr cyclicity originates from the phase locking of the precession and obliquity-forced glacial cycles to the corresponding eccentricity cycle. The eccentricity influences glacial cycles solely through its amplitude modulation of the precession component of orbital forcing, while the long timescale of the late Quaternary glacial cycles is determined by the time required for ice sheets to reach their critical size. The postulates used to construct this conceptual model were justified using analysis of relevant physical and biogeochemical processes and feedbacks. In particular, the role of climate–ice sheet–carbon cycle feedback in shaping and globalization of glacial cycles is discussed. The reasons for the instability of the large northern ice sheets and the mechanisms of the Earth system escape from the “glacial trap” via a set of strongly nonlinear processes are presented. It is also shown that the transition from the 41 to the 100 kyr world about 1 million years ago can be explained by a gradual increase in the critical size of ice sheets, which in turn is related to the gradual removal of terrestrial sediments from the northern continents. The implications of this nonlinear paradigm for understanding Quaternary climate dynamics and the remaining knowledge gaps are finally discussed.

An Overview of Anthropogenic Changes in Land Use and Land Cover, with Specific Attention to Climate Change and Unsustainable Agriculture

The worldwide need for food and the alterations in bioenergy demands associated with shifts in land use and land cover changes (LULCC) have given rise to environmental apprehensions, including global warming and climate change. There is substantial evidence indicating that we are currently witnessing human-induced transformations that could potentially result in a sixth mass extinction event. This study seeks to explore the connections between land use and land cover change (LULCC), forests, biodiversity, the carbon cycle, hydrology, climate, and various biogeochemical feedback mechanisms. These interrelationships play a crucial role in shaping future environmental outcomes and influencing climate change. Additionally, the review critically assesses existing research on the correlation between LULCC and climate, along with associated processes. The paper delves into ongoing investigations surrounding LULCC, its ecological repercussions, and its influence on the regulatory mechanisms of terrestrial ecosystems, ecosystem services, atmospheric chemistry, and the climate. It underscores the importance of developing land-use strategies rooted in a scientific evaluation of LULCC to promote sustainability and wider economic development, with a particular emphasis on addressing climate change. Global agreements and protocols also call for land use strategies that consider the implications of environmental degradation.

Metagenomic insights into inhibition of soil microbial carbon metabolism by phosphorus limitation during vegetation succession.

There is growing awareness of the need for regenerative practices in the fight against biodiversity loss and climate change. Yet, we lack a mechanistic understanding of how microbial community composition and functioning are likely to change alongside transition from high-density tillage to large-scale vegetation restoration. Here, we investigated the functional dynamics of microbial communities following a complete vegetation successional chronosequence in a subtropical zone, Southwestern China, using shotgun metagenomics approaches. The contents of total soil phosphorus (P), available P, litter P, and microbial biomass P decreased significantly during vegetation succession, indicating that P is the most critical limiting nutrient. The abundance of genes related to P-uptake and transport, inorganic P-solubilization, organic P-mineralization, and P-starvation response regulation significantly increased with successional time, indicating an increased microbial "mining" for P under P limitation. Multi-analysis demonstrated microbial P limitation strongly inhibits carbon (C) catabolism potential, resulting in a significant decrease in carbohydrate-active enzyme family gene abundances. Nevertheless, over successional time, microorganisms increased investment in genes involved in degradation-resistant compounds (lignin and its aromatic compounds) to acquire P resources in the litter. Our study provides functional gene-level insights into how P limitation during vegetation succession in subtropical regions inhibits soil microbial C metabolic processes, thereby advancing our understanding of belowground C cycling and microbial metabolic feedback during forest restoration.

The biological basis for using optical signals to track evergreen needleleaf photosynthesis

Abstract Evergreen needleleaf forests (ENFs) play a sizable role in the global carbon cycle, but the biological and physical controls on ENF carbon cycle feedback loops are poorly understood and difficult to measure. To address this challenge, a growing appreciation for the stress physiology of photosynthesis has inspired emerging techniques designed to detect ENF photosynthetic activity with optical signals. This Overview summarizes how fundamental plant biological and biophysical processes control the fate of photons from leaf to globe, ultimately enabling remote estimates of ENF photosynthesis. We demonstrate this using data across four ENF sites spanning a broad range of environmental conditions and link leaf- and stand-scale observations of photosynthesis (i.e., needle biochemistry and flux towers) with tower- and satellite-based remote sensing. The multidisciplinary nature of this work can serve as a model for the coordination and integration of observations made at multiple scales.

Creating Stronger Design Systems for Collaboration: Skills, Resources, and Practices Needed to Support an Effective Co-Design Experience

This paper describes a design case that addressed a healthcare training need for clinicians and administrators about Value-Based Care (VBC) through the design, development, implementation, and evaluation of seven massive open online courses (MOOCs). The context was an industry-academic partnership that linked subject matter experts in VBC with university faculty and designers. Courses were developed using a co-design approach to provide multiple perspectives on the issues involved, ensure the accuracy of the content, and enhance the alignment between the design and stakeholders’ needs. The team worked collaboratively to define the opportunity, brainstorm ideas, prototype solutions, evaluate prototypes based on identified needs, and ultimately design online educational experiences for a wide variety of learners in different healthcare contexts. This paper shares lessons learned about creating stronger design systems for collaboration in the areas of selecting and supporting co-design teams, fostering collaborative learning environments, and modeling collaboration in the instructional design process. Reflections about this design case underscored the importance of forming relationships among team members, which was a key outcome of the co-design structure and, facilitated the communication and psychological safety needed to support the iterative cycles of feedback during course development.

Machine learning algorithm for ventilator mode selection, pressure and volume control.

Mechanical ventilation techniques are vital for preserving individuals with a serious condition lives in the prolonged hospitalization unit. Nevertheless, an imbalance amid the hospitalized people demands and the respiratory structure could cause to inconsistencies in the patient's inhalation. To tackle this problem, this study presents an Iterative Learning PID Controller (ILC-PID), a unique current cycle feedback type controller that helps in gaining the correct pressure and volume. The paper also offers a clear and complete examination of the primarily efficient neural approach for generating optimal inhalation strategies. Moreover, machine learning-based classifiers are used to evaluate the precision and performance of the ILC-PID controller. These classifiers able to forecast and choose the perfect type for various inhalation modes, eliminating the likelihood that patients will require mechanical ventilation. In pressure control, the suggested accurate neural categorization exhibited an average accuracy rate of 88.2% in continuous positive airway pressure (CPAP) mode and 91.7% in proportional assist ventilation (PAV) mode while comparing with the other classifiers like ensemble classifier has reduced accuracy rate of 69.5% in CPAP mode and also 71.7% in PAV mode. An average accuracy of 78.9% rate in other classifiers compared to neutral network in CPAP. The neural model had an typical range of 81.6% in CPAP mode and 84.59% in PAV mode for 20 cm H2O of volume created by the neural network classifier in the volume investigation. Compared to the other classifiers, an average of 72.17% was in CPAP mode, and 77.83% was in PAV mode in volume control. Different approaches, such as decision trees, optimizable Bayes trees, naive Bayes trees, nearest neighbour trees, and an ensemble of trees, were also evaluated regarding the accuracy by confusion matrix concept, training duration, specificity, sensitivity, and F1 score.

Increasing the delivery of upper limb constraint-induced movement therapy programs for stroke and brain injury survivors: evaluation of the ACTIveARM project

Purpose To increase the number of constraint-induced movement therapy (CIMT) programs provided by rehabilitation services. Methods A before-and-after implementation study involving nine rehabilitation services. The implementation package to help change practice included file audit–feedback cycles, 2-day workshops, poster reminders, a community-of-practice and drop-in support. File audits were conducted at baseline, every three months for 1.5 years, and once after support ceased to evaluate maintenance of change. CIMT participant outcomes were collected to evaluate CIMT effectiveness and maintenance (Action Research Arm Test and Motor Activity Log). Staff focus groups explored factors influencing CIMT delivery. Results CIMT adoption improved from baseline where only 2% of eligible people were offered and/or received CIMT (n = 408 files) to more than 50% over 1.5 years post-implementation (n = 792 files, 52% to 73% offered CIMT, 27%–46% received CIMT). Changes were maintained at 6-month follow-up (n = 172 files, 56% offered CIMT, 40% received CIMT). CIMT participants (n = 74) demonstrated clinically significant improvements in arm function and occupational performance. Factors influencing adoption included interdisciplinary collaboration, patient support needs, intervention adaptations, a need for continued training, and clinician support. Conclusions The implementation package helped therapists overcome an evidence-practice gap and deliver CIMT more routinely.

Development of a behaviour change intervention to increase the delivery of upper limb constraint-induced movement therapy programs to people with stroke and traumatic brain injury

Purpose Constraint-induced movement therapy (CIMT) is a recommended intervention for arm recovery after acquired brain injury but is underutilised in practice. The purpose of this study is to describe the development of a behaviour change intervention targeted at therapists, to increase delivery of CIMT. Methods A theoretically-informed approach for designing behaviour change interventions was used including identification of which behaviours needed to change (Step 1), barriers and enablers that needed to be addressed (Step 2), and intervention components to target those barriers and enablers (Step 3). Data collection methods included file audits and therapist interviews. Quantitative data (file audits) were analysed using descriptive statistics. Qualitative data analysis (interviews) was informed by the Theoretical Domains Framework (TDF) and Behaviour Change Wheel. Results Fifty two occupational therapists, physiotherapists and allied health assistants participated in focus groups (n = 7) or individual interviews (n = 6). Key barriers (n = 20) and enablers (n = 10) were identified across 11 domains of the TDF and perceived to influence CIMT implementation. The subsequent behaviour change intervention included training workshops, nominated team champions, community of practice meetings, three-monthly file audit feedback cycles, poster reminders and drop-in support during CIMT. Conclusion This study describes the development of a behaviour change intervention to increase CIMT delivery by clinicians. Trial registration Australian New Zealand Clinical Trials Registry, Trial ID: ACTRN12617001147370.

DESIGNING COLLABORATIVE AUGMENTED REALITY ACTIVITIES WITH OLDER ADULTS IN LONG TERM CARE

Abstract Loneliness is common among older adults in long term care (LTC) settings. Interactive communication technologies hold great promise in reducing loneliness but require design and evaluation studies. As part of a larger study on use of head mounted display augmented reality (HMD-AR) to connect older LTC adults with family members, we conducted a participatory design study to a) identify and design HMD-AR multi-user activities and b) address barriers found with LTC residents when interacting with HMD-AR. Results: Laboratory testing was conducted with 23 older adults with normal cognition (ages 65 to 93, 6 men) and field testing with iterative feedback cycles with 8 older adults with impaired mobility and cognition (ages 54 to 87, 2 men, 4 with stroke) that resulted in prototype development and testing of three activities: playing checkers, decorating a fireplace, and eating a meal. Challenges successfully addressed through technological innovations included: 1) enhancing perceptions and ease of interacting with photorealistic avatars, 2) providing various techniques to allow older adults to view and move AR objects despite cognitive and functional impairments (e.g., visual-perceptual impairments; limited dexterity), 3) using visual aids and voice commands, 4) developing visual adaptations for central vision and color detection impairments, and 5) creating tutorials and help guides for learnability and remembrance. Sessions lasted for 30 minutes and no adverse effects were noted with prolonged or repeated HMD-AR use. All enjoyed the HMD-AR activities. Conclusion: HMD-AR can be successfully adapted for use by older adults with multiple cognitive and physical impairments.

Writing experiences of neurodiverse students in graduate STEM programs

BackgroundDespite efforts to increase the participation of marginalized students, neurodivergent students remain underrepresented in graduate STEM programs. Prior research shows that these students often experience challenges related to key aspects of writing. The objective of this qualitative study is to deepen understanding of the writing experiences, strengths, and challenges of neurodivergent students pursuing graduate degrees in STEM fields. In this analysis, we consider the factors that influence the writing-specific challenges faced by neurodivergent students in graduate STEM programs. This work also explores how neurodivergent students leverage strengths and strategies for success in graduate-level writing tasks.ResultsThis qualitative study draws on Social Cognitive Theory (SCT) to consider the ways cognitive, behavioral, and environmental factors impact writing experiences. We used thematic analysis of the transcripts from 13 focus groups and 1 interview to examine the writing experiences of 31 students who identify as neurodivergent in graduate STEM programs. The findings suggest that many writing challenges faced by neurodivergent graduate students are behaviors and beliefs that emerge in response to environmental factors such as the culture of STEM fields, prior experiences with writing assignments, anxiety driven by intensive feedback cycles, and perceived and experienced stigma. Study participants employed a range of collaborative and situational strategies to support and enhance their writing productivity.ConclusionThese findings may provide insight for current and future neurodivergent graduate students as they adjust to the intense writing demands of graduate degree programs and for graduate program administrators and faculty advisors as they consider new ways to support the academic success of neurodivergent graduate students.

Structured, nurse-led ward rounds to improve interprofessional communication and optimize care of vascular surgery patients: a best practice implementation project.

Ward rounds are crucial inpatient activities during which patients' conditions are discussed. Team-based models such as nurse-led ward rounds (NLWRs) have been conceptualized and trialled, with positive results. An evidence-based quality improvement pilot project to introduce NLWRs was implemented at a cardiovascular medical-surgical unit in a Singapore tertiary hospital. The JBI Evidence Implementation Framework was used to guide the project. The evidence-based NLWR format incorporated stakeholder feedback on NLWR frequency, preparation, coordination, and content. Baseline and 6-month post-implementation audits were carried out. The 4 audit criteria improved from baseline, reaching 100% compliance for criteria 1, 2, and 3 associated with interprofessional communication and collaboration. An improvement from baseline (30% to 46.7%) was also observed for criterion 4 on patient involvement during medical ward rounds. Moreover, there were improvements in clinical outcome data such as patient hospitalization length, "best medical therapy" rates, and inpatient complications. A statistically significant improvement in nurses' confidence to lead discussions during medical rounds was also observed ( p = 0.026). This project promoted greater compliance with NLWR criteria through audit and feedback cycles and the contextualization of implementation strategies. A well-supported program that prepares nurses for interprofessional communication also improves nurses' confidence in team communication, bolstering their ability to provide high-quality patient care.

Large-Scale Features of the CON Galaxy NGC4418 with MUSE

AbstractCompact obscured nuclei (CONs) are relatively common in the centers of local (U)LIRGs, yet their nature remains unknown. Both AGN activity and extreme nuclear starbursts have been suggested as plausible nuclear power sources. The prevalence of outflows in these systems suggest that CONs represent a key phase in the nuclear feedback cycle, in which material is ejected from the central regions of the galaxy. Here, we present results from MUSE for the confirmed local CON galaxy NGC4418. For the first time we spatially map the spectral features and kinematics of the galaxy in the optical, revealing several previously unknown structures. In particular, we discover a bilateral outflow along the minor axis, an outflowing bubble, several knot structures and a receding outflow partially obscured by the galactic disk. Based on the properties of these features, we conclude that the CON in NGC4418 is most likely powered by an AGN.

Formation of the Siberian Yamal gas emission crater via accumulation and explosive release of gas within permafrost

AbstractThe Arctic landscape has experienced many dramatic forms of change due to anthropogenic warming. Large crater‐like forms surrounded by fragmented blocks scattered outward to great distances with precursor mounds appeared in the continuous permafrost zone of the Yamal and Gydan peninsulas of Western Siberia. The morphologies of these craters, in addition to the abundant evidence of active and intense gas emissions across the region, indicate that they formed due the subsurface accumulation, pressurization, and explosive release of gasses trapped within the permafrost. Therefore, these craters were termed “gas emission craters” (GEC). However, some have suggested that in addition to gas accumulation, these features form in a manner similar to ice‐cored pingos and require pressurization due to the freezing of subsurface ice. This is despite the fact that not all GECs form in areas conducive to pingo‐like ice accumulation. Here, we test whether the pressurization and explosive release of methane gas alone can reproduce the observed morphology of the first‐discovered and most intensely studied GEC, Yamal crater. We use the available field and satellite data to constrain the initial dimension parameters of a model of the explosion process and consider several plausible configurations for the unknown interior cavity shape, the overlying permafrost cap thickness, and gas chamber volume. The explosion process is modeled in phases: gas migrates upward and accumulates in the subsurface until the gas pressure fractures the overlying cap, the expanding gas and cap blocks are initially accelerated outward together, and then the blocks are launched as projectiles. The sizes and locations of the ejected blocks found at Yamal crater are used to determine the initial gas pressures required to launch those projectiles to the observed locations. Finally, we estimate the amount of gas released in each of the multiple model runs testing different plausible internal cavity geometries. For the range of plausible block sizes and densities, and a subset of gas chamber volumes considered, we find that the gas pressure (0.6–2.6 MPa) required to launch the Yamal crater blocks to their observed distances was within the range of the sum of the ice/permafrost tensile strength and the lithostatic pressure (0.22–2.87 MPa). Thus, the observed blocks could have been launched by the energy required to fracture and displace the overlying permafrost cap. We show that the mechanism of formation of this GEC does not require pressure from the freezing of ice in the subsurface to crack and explode the overlying permafrost—gas pressure alone can produce these GECs. We expect that as our planet warms, the Siberian permafrost will continue to warm, weaken, and release gasses such as the greenhouse gas methane, and contribute to a permafrost carbon‐positive feedback cycle that would lead to the formation of even more explosive GECs.

Feedback as a key factor in business development

This article explores how to effectively foster a feedback culture within an organization. It outlines key principles for providing constructive, motivating, and impactful feedback, including timeliness, an unbiased approach, the use of «I–messages», a positive orientation, openness, and dialogue. Additionally, the article delves into methods of integrating feedback into the organization’s culture, such as one–on–one meetings, feedback cycles, performance evaluations, and cultivating a growth mindset. Furthermore, ethical principles such as confidentiality, objectivity, honesty, and an individualized approach are discussed. By adhering to these approaches and principles and implementing a feedback system within the organization’s culture, companies can create an atmosphere of continuous improvement, trust, and collaboration. A feedback culture rooted in these principles contributes to both the personal growth of employees and motivates them to align their actions with the organization’s goals, ultimately enhancing overall business effectiveness.

Assessing carbon cycle projections from complex and simple models under SSP scenarios

Both full-fledged Earth system models (ESMs) and simple climate models (SCMs) have been used to investigate climate change for future representative CO2 concentration pathways under the sixth phase of the Coupled Model Intercomparison Project. Here, we explore to what extent complex and simple models are consistent in their carbon cycle response in concentration-driven simulations. Although ESMs and SCMs exhibit similar compatible fossil fuel CO2 emissions, ESMs systematically estimate a lower ocean carbon uptake than SCMs in the historical period and future scenarios. The ESM and SCM differences are especially large under low-concentration and overshoot scenarios. Furthermore, ESMs and SCMs deviate in their land carbon uptake estimates, but the differences are scenario-dependent. These differences are partly driven by a few model outliers (ESMs and SCMs) and the procedure of observational constraining that is present in the majority of SCMs but not applied in ESMs. The differences in land uptake arise from the difference in the way land-use change (LUC) emissions are calculated and different assumptions on how the carbon cycle feedbacks are defined, possibly reflecting the treatment of nitrogen limitation of biomass growth and historical calibration of SCMs. The differences in ocean uptake, which are especially large in overshoot scenarios, may arise from the faster mixing of carbon from the surface to the deep ocean in SCMs than in ESMs. We also discuss the inconsistencies that arise when converting CO2 emissions from integrated assessment models (IAMs) to CO2 concentrations inputs for ESMs, which typically rely on a single SCM. We further highlight the discrepancies in LUC emission estimates between models of different complexity, particularly ESMs and IAMs, and encourage climate modeling groups to address these potential areas for model improvement.