Projected future climatic forcing on the global distribution of vegetation types.

Most emissions scenarios suggest temperature and precipitation regimes will change dramatically across the globe over the next 500 years. These changes will have large impacts on the biosphere, with species forced to migrate to follow their preferred environmental conditions, therefore moving and fragmenting ecosystems. However, most projections of the impacts of climate change only reach 2100, limiting our understanding of the temporal scope of climate impacts, and potentially impeding suitable adaptive action. To address this data gap, we model future climate change every 20 years from 2000 to 2500 CE, under different CO2 emissions scenarios, using a general circulation model. We then apply a biome model to these modelled climate futures, to investigate shifts in climatic forcing on vegetation worldwide, the feasibility of the migration required to enact these modelled vegetation changes, and potential overlap with human land use based on modern-day anthromes. Under a business-as-usual scenario, up to 40% of terrestrial area is expected to be suited to a different biome by 2500. Cold-adapted biomes, particularly boreal forest and dry tundra, are predicted to experience the greatest losses of suitable area. Without mitigation, these changes could have severe consequences both for global biodiversity and the provision of ecosystem services. This article is part of the theme issue 'Ecological novelty and planetary stewardship: biodiversity dynamics in a transforming biosphere'.

Image processing and supervised machine learning for retinal microglia characterization in senescence.

The process of senescence impairs the function of cells and can ultimately be a key factor in the development of disease. With an aging population, senescence-related diseases are increasing in prevalence. Therefore, understanding the mechanisms of cellular senescence within the central nervous system (CNS), including the retina, may yield new therapeutic pathways to slow or even prevent the development of neuro- and retinal degenerative diseases. One method of probing the changing functions of senescent retinal cells is to observe retinal microglial cells. Their morphological structure may change in response to their surrounding cellular environment. In this chapter, we show how microglial cells in the retina, which are implicated in aging and diseases of the CNS, can be identified, quantified, and classified into five distinct morphotypes using image processing and supervised machine learning algorithms. The process involves dissecting, staining, and mounting mouse retinas, before image capture via fluorescence microscopy. The resulting images can then be classified by morphotype using a support vector machine (SVM) we have recently described showing high accuracy. This SVM model uses shape metrics found to correspond with qualitative descriptions of the shape of each morphotype taken from existing literature. We encourage more objective and widespread use of methods of quantification such as this. We believe automatic delineation of the population of microglial cells in the retina, could potentially lead to their use as retinal imaging biomarkers for disease prediction in the future.

In Vivo Detection of Retinal Ganglion Cell Stress in Rodents with DARC.

DARC (detection of apoptosing retinal cells) uses fluorescently tagged Annexin A5 to identify retinal apoptosis non-invasively in vivo using a confocal laser scanning ophthalmoscope (cSLO). This can provide insights into the presence and progression of disease pathology and the efficacy of neuroprotective intervention. The methods of administration, imaging, and quantification of DARC, including the operation of the cSLO, are described here.

The "Crossing Collection Sign": A Diagnostic Tool on Spine Magnetic Resonance Imaging For Localizing Cerebrospinal Fluid Leak.

OBJECTIVE: The aim of the study is to determine whether the site of "cross" between ventral and dorsal spinal longitudinal extradural CSF collections (SLECs) seen on magnetic resonance imaging during initial workup of patients with suspected CSF leaks can predict the subsequently confirmed leakage site on computed tomography myelography or surgical repair. METHODS: This was an institutional review board-approved, retrospective study performed from 2006 to 2021. Patients with SLECs who underwent total spine magnetic resonance imaging at our institution, followed by myelography and/or surgical repair for CSF leak, were included. Patients with incomplete workup including lack of computed tomography myelography and/or surgical repair and patients severely motion degraded imaging were excluded from our study. The site of cross between ventral and dorsal SLECs was defined as the "crossing collection sign" and was compared with the anatomically confirmed site of leak on myelography and/or at surgical repair. RESULTS: Thirthy-eight patients met inclusion criteria with 18 females and 11 males ranging in age from 27 to 60 years (median, 40 years; interquartile range, 14 years). The crossing collection sign was seen in 76% of patients (n = 29). The distributions of confirmed CSF leak were as follows: cervical (n = 9), thoracic (n = 17), and lumbar spine (n = 3). The crossing collection sign predicted the site of CSF leak in 14 of 29 patients (48%) and was within 3-vertebral segments in 26 of 29 cases (90%). CONCLUSIONS: The crossing collection sign can help prospectively identify spinal regions with highest likelihood for CSF leak in patients with SLECs. This can potentially help optimize the more invasive subsequent steps in the workup for these patients, including dynamic myelography and surgical exploration for repair.

Structure-Based Design of Potent Iminosugar Inhibitors of Endoplasmic Reticulum α-Glucosidase I with Anti-SARS-CoV-2 Activity.

Enveloped viruses depend on the host endoplasmic reticulum (ER) quality control (QC) machinery for proper glycoprotein folding. The endoplasmic reticulum quality control (ERQC) enzyme α-glucosidase I (α-GluI) is an attractive target for developing broad-spectrum antivirals. We synthesized 28 inhibitors designed to interact with all four subsites of the α-GluI active site. These inhibitors are derivatives of the iminosugars 1-deoxynojirimycin (1-DNJ) and valiolamine. Crystal structures of ER α-GluI bound to 25 1-DNJ and three valiolamine derivatives revealed the basis for inhibitory potency. We established the structure-activity relationship (SAR) and used the Site Identification by Ligand Competitive Saturation (SILCS) method to develop a model for predicting α-GluI inhibition. We screened the compounds against SARS-CoV-2 in vitro to identify those with greater antiviral activity than the benchmark α-glucosidase inhibitor UV-4. These host-targeting compounds are candidates for investigation in animal models of SARS-CoV-2 and for testing against other viruses that rely on ERQC for correct glycoprotein folding.

Dopamine signals encode internally determined subjective value regardless of externally indicated reward attributes.

The dopamine reward prediction error signal is known to be subjective but has so far only been related to explicit external stimuli and rewards. However, personal choices are based on private internal values of the rewards at stake. Without indications of an agent's private internal value, we do not know whether dopamine neurons, or any reward neurons, encode the internal value. The well-established Becker-DeGroot-Marschak (BDM) auction-like mechanism allows participants to place bids for freely stating their private internal value for a good. BDM bids are known to reflect the agent's true internal valuation, as inaccurate bidding results in suboptimal reward ('incentive compatibility'). In our experiment rhesus monkeys placed BDM bids for juice rewards without specific external constraints. Their bids for physically identical rewards varied trial by trial and increased overall for larger rewards. Responses of midbrain dopamine neurons followed the trial-by-trial variation of bids despite constant, explicitly predicted reward amounts; correspondingly, the dopamine responses were similar when the animal placed similar bids for different reward amounts. Support Vector Regression demonstrated accurate prediction of the animal's bids by as few as twenty dopamine neurons, demonstrating the validity of the dopamine code for internal reward value. Thus, dopamine responses reflect the instantaneous internal subjective reward value rather than the value imposed by external stimuli.

Key Elements and Mechanisms of a Peer-Support Intervention to Reduce Loneliness and Isolation among Low-Income Older Adults: A Qualitative Implementation Science Study.

This paper describes the evaluation of a longitudinal peer-support program developed to address loneliness and isolation among low-income, urban community-dwelling older adults in San Francisco. Our objective was to determine barriers, challenges, and successful strategies in implementation of the program. In-depth qualitative interviews with clients (n = 15) and peers (n = 6) were conducted and analyzed thematically by program component. We identified barriers and challenges to engagement and outlined strategies used to identify clients, match them with peers, and provide support to both peers and clients. We found that peers played a flexible, non-clinical role and were perceived as friends. Connections to community resources helped when clients needed additional support. We also documented creative strategies used to maintain inter-personal connections during the COVID-19 pandemic. This study fills a gap in understanding how a peer-support program can be designed to address loneliness and social isolation, particularly in low-income, urban settings.

A proposed theoretical framework for retinal biomarkers.

Objective: Propose a theoretical framework for retinal biomarkers of Alzheimer's disease (AD). Background: The retina and brain share important biological features that are relevant to AD. Developing retinal biomarkers of AD is a strategic priority but as yet none have been validated for clinical use. Part of the reason may be that fundamental inferential assumptions have been overlooked. Failing to recognize these assumptions will disadvantage biomarker discovery and validation, but incorporating them into analyses could facilitate translation. New theory: The biological assumption that a disease causes analogous effects in the brain and retina can be expressed within a Bayesian network. This allows inferences about abstract theory and individual events, and provides an opportunity to falsify the foundational hypothesis of retina-brain analogy. Graphical representation of the relationships between variables simplifies comparison between studies and facilitates judgements about whether key assumptions are valid given the current state of knowledge. Major challenges: The framework provides a visual approach to retinal biomarkers and may help to rationalize analysis of future studies. It suggests possible reasons for inconsistent results in existing literature on AD biomarkers. Linkage to other theories: The framework can be modified to describe alternative theories of retinal biomarker biology, such as retrograde degeneration resulting from brain disease, and can incorporate confounding factors such as co-existent glaucoma or macular degeneration. Parallels with analogue confirmation theory and surrogate marker validation suggest strengths and weaknesses of the framework that can be anticipated when developing analysis plans. Highlights: Retinal biomarkers hold great promise for Alzheimer's disease (AD), but none are currently used clinically.Assumptions about the cause of retinal and brain changes are often overlooked, and this may disadvantage biomarker discovery and validation.We present a new approach to retinal biomarkers that describes cause and effect graphically in a Bayesian network.We show how this allows a more complete assessment of how well a biomarker might reflect the brain, and how data from right and left eyes can be used to rule out poor biomarker candidates.

Did perceptions of supportive work-life culture change during the COVID-19 pandemic?

Objective: This article examines whether perceptions of supportive work-life culture changed during the COVID-19 pandemic-and if that depended on (1) working from home; (2) children in the household; and (3) professional status. We test for gender differences across the analyses. Background: During normal times, the "ideal worker" is expected to prioritize the demands of their job and is penalized for attending to family/personal needs while on company time. But the organization and expectations of roles might have changed due to the COVID-19 pandemic. Organizations could have become more empathic or reinforced norms about single-minded devotion to work. Method: In September 2019, we collected data from a national sample of Canadian workers. Then, during a pivotal period of shocks to the economy and social life, we re-interviewed these participants in June 2020. Results: We discovered that overall perceptions of work-life culture became more positive. However, subgroup differences revealed this positive change was muted among employees: (1) who worked from home; (2) with children under age 6 at home; and (3) in professional occupations. We found no subgroup differences by gender. Conclusion: Our findings address speculation about whether employees perceived their employers as becoming more supportive of work-life fit early in the pandemic. Future research should determine (a) longer-term change in work-life culture during and after the pandemic; and (b) whether the actual benefits of supportive work-life culture also changed or if it was "window dressing." This direction suggests it should have more strongly reduced work-life conflict as the pandemic unfolded.

Automated characterisation of microglia in ageing mice using image processing and supervised machine learning algorithms.

The resident macrophages of the central nervous system, microglia, are becoming increasingly implicated as active participants in neuropathology and ageing. Their diverse and changeable morphology is tightly linked with functions they perform, enabling assessment of their activity through image analysis. To better understand the contributions of microglia in health, senescence, and disease, it is necessary to measure morphology with both speed and reliability. A machine learning approach was developed to facilitate automatic classification of images of retinal microglial cells as one of five morphotypes, using a support vector machine (SVM). The area under the receiver operating characteristic curve for this SVM was between 0.99 and 1, indicating strong performance. The densities of the different microglial morphologies were automatically assessed (using the SVM) within wholemount retinal images. Retinas used in the study were sourced from 28 healthy C57/BL6 mice split over three age points (2, 6, and 28-months). The prevalence of 'activated' microglial morphology was significantly higher at 6- and 28-months compared to 2-months (p < .05 and p < .01 respectively), and 'rod' significantly higher at 6-months than 28-months (p < 0.01). The results of the present study propose a robust cell classification SVM, and further evidence of the dynamic role microglia play in ageing.

New QSPRs for Liquid Heat Capacity.

Quantitative Structure-Property Relationships (QSPRs) have found applications in many areas of chemistry and engineering as effective prediction methods. QSPRs use molecular descriptors to simplify complex molecular properties to a single value and have been used extensively for constant value properties. Liquid heat capacity ( cpl ) is another property where QSPRs can be helpful prediction tools. Researchers have shown strong correlation between the cpl and various molecular descriptors, but these predictions are limited to a single temperature, usually 298.15 K. Additionally, other QSPRs have had problems with oxygen-containing functional groups. In this work, QSPRs for cpl at various temperatures were developed using data selected from the DIPPR database using a novel search method. This method improves on existing QSPRs for cpl by using unique descriptors but does not overcome the issue of oxygen-containing species.

Climate change research and action must look beyond 2100.

Anthropogenic activity is changing Earth's climate and ecosystems in ways that are potentially dangerous and disruptive to humans. Greenhouse gas concentrations in the atmosphere continue to rise, ensuring that these changes will be felt for centuries beyond 2100, the current benchmark for projection. Estimating the effects of past, current, and potential future emissions to only 2100 is therefore short-sighted. Critical problems for food production and climate-forced human migration are projected to arise well before 2100, raising questions regarding the habitability of some regions of the Earth after the turn of the century. To highlight the need for more distant horizon scanning, we model climate change to 2500 under a suite of emission scenarios and quantify associated projections of crop viability and heat stress. Together, our projections show global climate impacts increase significantly after 2100 without rapid mitigation. As a result, we argue that projections of climate and its effects on human well-being and associated governance and policy must be framed beyond 2100.

Detecting retinal cell stress and apoptosis with DARC: Progression from lab to clinic.

DARC (Detection of Apoptosing Retinal Cells) is a retinal imaging technology that has been developed within the last 2 decades from basic laboratory science to Phase 2 clinical trials. It uses ANX776 (fluorescently labelled Annexin A5) to identify stressed and apoptotic cells in the living eye. During its development, DARC has undergone biochemistry optimisation, scale-up and GMP manufacture and extensive preclinical evaluation. Initially tested in preclinical glaucoma and optic neuropathy models, it has also been investigated in AMD, Alzheimer's, Parkinson's and Diabetic models, and used to assess efficacy of therapies. Progression to clinical trials has not been speedy. Intravenous ANX776 has to date been found to be safe and well-tolerated in 129 patients, including 16 from Phase 1 and 113 from Phase 2. Results on glaucoma and AMD patients have been recently published, and suggest DARC with an AI-aided algorithm can be used to predict disease activity. New analyses of DARC in GA (Geographic Atrophy) prediction are reported here. Although further studies are needed to validate these findings, it appears there is potential for the technology to be used as a biomarker. Much larger clinical studies will be needed before it can be considered as a diagnostic, although the relatively non-invasive nature of the nasal as opposed to intravenous administration would widen its acceptability in the future as a screening tool. This review describes DARC development and its progression into Phase 2 clinical trials from lab-based research. It discusses hypotheses, potential challenges, and regulatory hurdles in translating technology.

A peer intervention reduces loneliness and improves social well-being in low-income older adults: A mixed-methods study.

BACKGROUND: Evidence-based interventions addressing loneliness and social isolation are needed, including among low-income, community-dwelling older adults of diverse racial and ethnic backgrounds. Our objective was to assess the effect of a peer intervention in addressing loneliness, isolation, and behavioral health needs in this population. METHODS: We conducted a mixed-method, two-year longitudinal study of a peer-outreach intervention in 74 low-income older adults recruited via an urban senior center in San Francisco. Structured participant surveys were conducted at baseline and every 6 months for up to 2 years. Outcomes included loneliness (3-item UCLA loneliness scale), social interaction (10-item Duke index), self-perceived socializing barriers (range: 0-10), and depression (PHQ-2 screen). Data were analyzed using mixed-effects linear and logistic regression adjusted for age and gender. Qualitative, semi-structured interviews with participants (N = 15) and peers (N = 6) were conducted in English and Spanish and analyzed thematically. RESULTS: Participants were on average 71 years old (range: 59-96 years), with 58% male, 15% LGBT, 18% African American, 19% Latinx, 8% Asian, 86% living alone, and 36% with an ADL impairment. On average, 43 contact visits (IQR: 31-97 visits) between participants and peers occurred over the first year. Loneliness scores decreased by, on average, 0.8 points over 24 months (p = 0.015). Participants reported reduced depression (38%-16%, p < 0.001) and fewer barriers to socializing (1.5 fewer, p < 0.001). Because of the longitudinal relationship and matching of characteristics of peers to participants, participants reported strong feelings of kinship, motivations to reach out in other areas of life, and improved mood. CONCLUSION: Diverse older adults in an urban setting participating in a longitudinal peer program experienced reduced loneliness, depression, and barriers to socializing. Matching by shared backgrounds facilitated rapport and bonding between participants and peers.

Retinal Changes in Transgenic Mouse Models of Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative disorder, the most common form of dementia. AD is characterised by amyloid-ß (Aß) plaques and neurofibrillary tangles (NFT) in the brain, in association with neuronal loss and synaptic failure, causing cognitive deficits. Accurate and early diagnosis is currently unavailable in lifespan, hampering early intervention of potential new treatments. Visual deficits have been well documented in AD patients, and the pathological changes identified in the brain are also believed to be found in the retina, an integral part of the central nervous system. Retinal changes can be detected by real-time non-invasive imaging, due to the transparent nature of the ocular media, potentially allowing an earlier diagnosis as well as monitoring disease progression and treatment outcome. Animal models are essential for AD research, and this review has a focus on retinal changes in various transgenic AD mouse models with retinal imaging and immunohistochemical analysis as well as therapeutic effects in those models. We also discuss the limitations of transgenic AD models in clinical translations.

Investigational neuroprotective compounds in clinical trials for retinal disease.

INTRODUCTION: Retinal neurodegeneration causes irreversible vision loss, impairing quality of life. By targeting neurotoxic conditions, such as oxidative stress and ischemia, neuroprotectants can slow or stop sight loss resulting from eye disease. Despite limimted clinical use of neuroprotectants, there are several promising compounds in early clinical trials (pre-phase III) which may fulfil new therapeutic roles. Search terms relating to neuroprotection and eye disease were used on ClinicalTrials.gov to identify neuroprotective candidates. AREAS COVERED: Research supporting neuroprotection in eye diseases is focused on, ranging from preclinical to phase II, according to the ClinicalTrials.gov database. The compounds discussed are explored in terms of future clinical applications. EXPERT OPINION: The major challenge in neuroprotection research is translation from basic research to the clinic. A number of potential neuroprotectants have progressed to ophthalmology clinical trials in recent years, with defined mechanisms of action - saffron and CoQ10 - targeting mitochondria, and both CNTF and NGF showing anti-apoptotic effects. Enhancements in trial design and patient cohorts in proof-of-concept trials with enriched patient populations and surrogate endpoints should accelerate drug development. A further important consideration is optimising drug delivery to improve individualised management and patient compliance. Progress in these areas means that neuroprotective strategies have a much improved chance of translational success.

Naturally occurring neuroprotectants in glaucoma.

With the increasing global burden of glaucoma-caused blindness there is a significant need to develop therapies that both enable early detection of retinal neurodegeneration, and help protect cells from the neurodegenerative processes of glaucoma. In this chapter, we discuss potential neuroprotective agents that are present naturally and examine their role and suitability as therapies in glaucoma. These agents have been found to have anti-apoptotic and anti-inflammatory mechanisms of action which may aid the resilience of retinal ganglion cells and enable them to withstand potential insults that trigger cell death. We highlight how these properties could be translated into clinical practice and the barriers needing to be overcome in order to achieve this.

The latitudinal diversity gradient of tetrapods across the Permo-Triassic mass extinction and recovery interval.

The decline in species richness from the equator to the poles is referred to as the latitudinal diversity gradient (LDG). Higher equatorial diversity has been recognized for over 200 years, but the consistency of this pattern in deep time remains uncertain. Examination of spatial biodiversity patterns in the past across different global climate regimes and continental configurations can reveal how LDGs have varied over Earth history and potentially differentiate between suggested causal mechanisms. The Late Permian-Middle Triassic represents an ideal time interval for study, because it is characterized by large-scale volcanic episodes, extreme greenhouse temperatures and the most severe mass extinction event in Earth history. We examined terrestrial and marine tetrapod spatial biodiversity patterns using a database of global tetrapod occurrences. Terrestrial tetrapods exhibit a bimodal richness distribution throughout the Late Permian-Middle Triassic, with peaks in the northern low latitudes and southern mid-latitudes around 20-40° N and 60° S, respectively. Marine reptile fossils are known almost exclusively from the Northern Hemisphere in the Early and Middle Triassic, with highest diversity around 20° N. Reconstructed terrestrial LDGs contrast strongly with the generally unimodal gradients of today, potentially reflecting high global temperatures and prevailing Pangaean super-monsoonal climate system during the Permo-Triassic.

Moving Fast-Scan Cyclic Voltammetry toward FDA Compliance with Capacitive Decoupling Patient Protection.

Carbon-fiber microelectrodes allow for high spatial and temporal measurements of electroactive neurotransmitter measurements in vivo using fast-scan cyclic voltammetry (FSCV). However, common instrumentation for such measurements systems lack patient safety precautions. To add safety precautions as well as to overcome chemical and electrical noise, a two-electrode FSCV headstage was modified to introduce an active bandpass filter on the electrode side of the measurement amplifier. This modification reduced the measured noise and ac-coupled the voltammetric measurement and moved it from a classical direct current response measurement. ac-coupling not only reduces the measured noise, but also moves FSCV toward compliance with IEC-60601-1, enabling future human trials. Here, we develop a novel ac-coupled voltammetric measurement method of electroactive neurotransmitters. Our method allows for the modeling of a system to then calculate a waveform to compensate for added impedance and capacitance for the system. We describe how first by measuring the frequency response of the system and modeling the analogue response as a digital filter we can then calculate a predicted waveform. The predicted waveform, when applied to the bandpass filter, is modulated to create a desired voltage sweep at the electrode interface. Further, we describe how this modified FSCV waveform is stable, allowing for the measurement of electroactive neurotransmitters. We later describe a 32.7% sensitivity enhancement for dopamine with this new measurement as well as maintaining a calibration curve for dopamine, 3,4-dihydroxyphenylacetic acid, ascorbic acid, and serotonin in vitro. We then validate dopamine in vivo with stimulated release. Our developed measurement method overcame the added capacitance that would traditionally make a voltammetric measurement impossible, and it has wider applications in electrode sensor development, allowing for measurement with capacitive systems, which previously would not have been possible.

Mitigating the Effects of Electrode Biofouling-Induced Impedance for Improved Long-Term Electrochemical Measurements In Vivo.

Biofouling is a prevalent issue in studies that involve prolonged implantation of electrochemical probes in the brain. In long-term fast-scan cyclic voltammetry (FSCV) studies, biofouling manifests as a shift in the peak oxidative potential of the background signal that worsens over days to weeks, diminishing sensitivity and selectivity to neurotransmitters such as dopamine. Using open circuit potential (OCP) measurements, scanning electron microscopy/energy-dispersive X-ray spectroscopy (SEM/EDX), and electrochemical impedance spectroscopy (EIS), we examined the biofouling-induced events that occur due to electrode implantation. We determined that the FSCV background signal shift results from cathodic polarization of the Ag/AgCl-wire reference electrode and increased electrochemical impedance of both the Ag/AgCl-wire reference electrode and carbon-fiber working electrode. These events are likely caused collectively by immune response-induced electrode encapsulation. A headstage utilizing a three-electrode configuration, designed to compensate for the impedance component of biofouling, reduced the FSCV background signal shift in vivo and preserved dopamine sensitivity at artificially increased impedance levels in vitro. In conjunction with a stable reference electrode, this three-electrode configuration will be critical in achieving reliable neurotransmitter detection for the duration of long-term FSCV studies.