Progress (Ireland)

PurposeRetinitis pigmentosa (RP) is the most common and genetically heterogenous inherited retinal degeneration described. Although vascular attenuation is a notable phenotype in later stages of the disease, the temporal nature of this attenuation and its contribution to disease are not well understood. Despite a growing body of research suggesting that blood-brain barrier (BBB) disruption can drive neurological deficits across a wide range of conditions, there is a paucity of data related to the contribution of inner blood-retina barrier (iBRB) disruption in RP.MethodsHere, we sought to examine retinal vascular changes in three established mouse models of RP, Rho–/–, Rd10, and Rpe65D477G. Each model was also established on a claudin-5 heterozygous (Cldn5+/−) background to examine retinal pathology in the context of a “leaky” iBRB. Additionally, we quantitatively examined iBRB integrity in patients with RP (n = 14) harboring autosomal dominant variants in either the RHO or RPE65 genes.ResultsOur results show decreased perfusion capacity and disruptions to retinal vascular plexuses within these models, highlighting a perturbed vascular state across Rho–/–, Rd10, and Rpe65D477G models. We highlight a specific loss of the deeper vascular plexus in more rapidly degenerating Rho–/– and Rd10 models, while still observing a global loss of CLDN5 vascular coverage in Rpe65D477G models despite lack of deep plexus degeneration. Moreover, our novel retinal degenerative models on a background of Cldn5 heterozygosity allow us to investigate retinal pathology of these models in the context of a “leaky” iBRB and highlight a specific sensitivity of the larger retinal macrovessels in these models. Furthermore, we find similar phenotypic patterns in a cohort of patients with RP with temporal iBRB changes that phenocopy these preclinical models.ConclusionsCumulatively, these findings represent the first quantitative profiling of iBRB disruption in RP and suggest that retinal vascular stabilization may represent a gene agnostic approach to treating this devastating form of blindness.

This study assesses India’s climate finance requirement from 2022-2030 to decarbonise its four major carbon-emitting sectors—cement, steel, power, and road transport. Climate finance or additional capital expenditure (capex) for transitioning to a low-carbon economy, i.e., over and above the capex already planned in the business-as-usual (BAU) scenario, has been estimated at US$467 billion for 2022-2030 or 1.3 per cent of India’s gross domestic product (GDP) annually. This comprises US$251 billion for the steel sector, followed by US$141 billion for cement, US$57 billion for power and US$18 billion for road transport. The estimated investment in the four sectors will reduce the use of 291 million tonnes of coal and 72 billion litres of petrol and diesel, mitigating 6.9 billion tonnes of CO2 emissions (excluding road transport). The study also evaluated the macroeconomic consistency of India’s estimated climate finance requirement. Overall, capital and financial flows net of the projected current account deficit (CAD) for India are estimated at US$530 billion during 2023–2030 as against the projected expansion of US$474 billion in monetary base. Thus, India would need to skilfully manage both (i) capital flows in the BAU; and (ii) climate finance from external sources. India may have to strategically widen its CAD, subject to a maximum of 2.5 per cent of GDP.

This paper looks at reported subsidy spending in India, in light of ongoing central initiatives to build transparency and accessibility of information related to financial operations and decisions of public expenditure. Subsidies have become a prominent policy tool for public resource allocation in India. However, without a clear definition and reporting of ‘subsidy’, the term tends to be loosely used to encompass many schemes and programs of the Union and state governments, including the recent rise in ‘freebies’, which need to be clearly differentiated. Moreover, many forms of financing through special securities and extra-budgetary resources have been used to finance subsidy spending, making it difficult to comprehensively define and measure subsidy expenditure in the budget and other annual accounts. These issues relate to the existence of data gaps in India’s fiscal reporting and accounts, which are a critical area of concern due to the large financial implications of subsidy expenditures. This paper identifies how subsidy spending has been accounted in India and explains the resultant data gaps that render such fiscal data inconsistent and incomparable across levels of government. The paper seeks to understand whether the present reporting of subsidy spending in the finance accounts and budget documents provide clear and comprehensive information about budget allocations, revenue sources, expenditures, and other related financial matters. It then proposes steps in the way forward to improve their transparency.

A diagnosis and an illustrated description of Mongolicosa uvs Esyunin et Ustinova sp. n. from the Uvs Province of Mongolia is provided, based on both sexes. The new species belongs to the pseudoferruginea group and appears to be especially similar to M. glupovi Marusik, Azarkina et Koponen 2004, yet differing in having a wide septal stem of the epigyne and an elongated terminal apophysis of the male palp.


 The true trend in tax revenues has been obscured by pandemic-related effects, inflation, and discretionary policy changes in recent years. These hinder accurate assessment of the state of the economy, a correct picture of which can only be had by stripping out these effects. In particular, the increasing deployment of additional revenue measures in succession for several years has masked information on the economy’s health that is observed from the automatic movement of tax revenues along with the GDP. This paper focuses upon tax buoyancy, which includes discretionary policy changes, to examine how the historical relationship of tax revenues with income may have been disturbed by exceptional shocks. Using early data and other evidence, it illustrates probable impacts of non-linear and asymmetric normalisation, the extraordinary price growth and uneven distribution thereof, and fiscal policy responses in the pandemic. It further compiles additional revenue mobilization measures for a longer period from 2011-12 to highlight how newer and fresher fiscal efforts have been used to complement a stagnant or shrinking tax base and how these can be distortionary in aspects beyond the diffusion of important macroeconomic signals.

Forests are a substantial terrestrial carbon sink, but anthropogenic changes in land use and climate have considerably reduced the scale of this system1. Remote-sensing estimates to quantify carbon losses from global forests2–5 are characterized by considerable uncertainty and we lack a comprehensive ground-sourced evaluation to benchmark these estimates. Here we combine several ground-sourced6 and satellite-derived approaches2,7,8 to evaluate the scale of the global forest carbon potential outside agricultural and urban lands. Despite regional variation, the predictions demonstrated remarkable consistency at a global scale, with only a 12% difference between the ground-sourced and satellite-derived estimates. At present, global forest carbon storage is markedly under the natural potential, with a total deficit of 226 Gt (model range = 151–363 Gt) in areas with low human footprint. Most (61%, 139 Gt C) of this potential is in areas with existing forests, in which ecosystem protection can allow forests to recover to maturity. The remaining 39% (87 Gt C) of potential lies in regions in which forests have been removed or fragmented. Although forests cannot be a substitute for emissions reductions, our results support the idea2,3,9 that the conservation, restoration and sustainable management of diverse forests offer valuable contributions to meeting global climate and biodiversity targets.

The article presents an attempt to solve the plane problem on the impact of an elastic Timoshenko shell on an elastic half-space using the method of reducing problems of dynamics to the solution of a Volterra's infinite system of integral equations (ISIE) of the second kind. It is shown that such an approach is not acceptable. When discretizing the reduced Volterra's ISIE of the second kind, a poorly defined system of linear algebraic equations is obtained: as the reduction order increases, the determinant of such a system tends to infinity. This circumstance shows the limitations of this approach.

Data sharing not applicable to this article as no datasets were generated or analysed during the current study.

Screening, brief intervention and referral to treatment (SBIRT) is an evidence-based approach to the treatment of a wide variety of medical conditions (e.g., alcohol, tobacco, cannabis and opioid use, treatment engagement and adherence, asthma control, elder abuse disclosure, and exercise, among many others). While SBIRT is efficacious, it is not widely adopted or implemented. Some of the reasons for this are lack of training, time, expert providers, and funding. Thus, there is a critical need to develop effective, standardized, acceptable and time-and cost-efficient ways of implementing SBIRT, such as technology-enabled solutions, including those that do not rely on human interventionists. This symposium will present a series of papers that will each describe the current and ongoing development of such technology enabled SBIRT, focusing specifically on the Brief Negotiation Interview (BNI), one of the most robustly efficacious approaches to SBIRT. Each of the papers will also describe their efforts at incorporating artificial intelligence (e.g., machine learning, natural language processing) into this work, which spans such diverse populations as individuals with high-risk drinking, uncontrolled asthma, elder abuse, and opioid use disorder, as well as medical trainees who are using a web-based application to learn to implement the BNI with their patients. Special attention will be paid by each presenter to the potential ethical issues posed by AI.