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The majority of pathogenic mutations in the neurofibromatosis type I (NF1) gene reduce total neurofibromin protein expression through premature truncation or microdeletion, but it is less well understood how loss-of-function missense variants drive NF1 disease. We have found that patient variants in codons 844 to 848, which correlate with a severe phenotype, cause protein instability and exert an additional dominant-negative action whereby wild-type neurofibromin also becomes destabilized through protein dimerization. We have used our neurofibromin cryogenic electron microscopy structure to predict and validate other patient variants that act through a similar mechanism. This provides a foundation for understanding genotype-phenotype correlations and has important implications for patient counseling, disease management, and therapeutics.

Abstrak – Konstruksi Net Farm Income untuk Kesejahteraan Petani Gula Tujuan Utama - Penelitian ini mencoba untuk menyusun formula Net Farm Income (NFI) yang berpihak pada petani. Metode - Penelitian ini menggunakan metode Islamic Anthropological Assumptions (IAA). Informan penelitian ini adalah beberapa pihak yang terlibat dalam pengembangan pertanian tebu. Temuan Utama – Penelitian ini menunjukkan bahwa meskipun hegemoni pemegang kekuasaan sangat kuat, terdapat nilai persatuan, budaya dan religiusitas di kalangan petani. Di sisi lain, petani tetap berada pada posisi yang terpinggirkan meskipun menyumbang penyerapan terbesar tenaga kerja dan pasokan tebu. Selain itu, penelitian ini menangkap nilai budaya lokal yang diwujudkan dalam ijtihad (kesungguhan) dan syukur. Implikasi Teori dan Kebijakan - Kajian ini berinisiatif untuk mentransformasikan dan mendemonstrasikan dimensi lokalitas dan religiusitas ke dalam konsep baru NFI. Bagi pengambil kebijakan, konsep NFI baru ini dapat menjadi dasar pemikiran dan pertimbangan baru untuk restrukturisasi regulasi yang menyangkut kesejahteraan petani tebu. Kebaruan Penelitian - Konstruksi baru NFI mengubah makna kesejahteraan dalam akuntansi pertanian syariah. Abstract – Net Farm Income Construction for Sugar Farmers' Welfare Main Purpose - This study attempts to develop a Net Farm Income (NFI) formula that is pro-sugar farmers. Method - This study uses the Islamic Anthropological Assumptions (IAA) method. The informants are several parties involved in developing sugarcane farming. Main Findings – This study shows that although the hegemony of the power holders is very strong, there are values of unity, culture and religiosity among the farmers. On the other hand, they are marginalised even though they are the biggest contributor to employment and sugarcane suppliers. In addition, this research captures local cultural values embodied in “ijtihad” (seriousness) and gratitude. Theory and Practical Implications - This study takes the initiative to transform and demonstrate the NFI concept with locality and religiosity dimensions. For policymakers, this concept can become a basis for new thoughts and considerations for restructuring regulations concerning the welfare of sugar farmers. Novelty - The new construction of NFI changes the meaning of welfare in Islamic farm accounting.

National forest inventory (NFI) programs provide vital information on forest parameters’ status, trend, and change. Most NFI designs and estimation methods are tailored to estimate status over large areas but are not well suited to estimate trend and change, especially over small spatial areas and/or over short time periods (e.g. annual estimates). Fine-scale space-time indexed estimates are critical to a variety of environmental, ecological, and economic monitoring efforts. In the United States, for example, NFI data are used to estimate forest carbon status, trend, and change to support national, state, and local user group needs. Increasingly, these users seek finer spatial and temporal scale estimates to evaluate existing land use policies and management practices, and inform future activities. Here we propose a spatio-temporal Bayesian small area estimation modeling framework that delivers statistically valid estimates with complete uncertainty quantification for status, trend, and change. The framework accommodates a variety of space and time dependency structures, and we detail model configurations for different settings. The proposed framework is used to quantify forest carbon dynamics at an annual county-level across a 14 year period for the contiguous United States. Also, using an analysis of simulated data, we compare the proposed framework with traditional NFI estimators and offer computationally efficient algorithms, software, and data to reproduce results for benchmarking.

Abstract Background The Norwegian forest resource map (SR16) maps forest attributes by combining national forest inventory (NFI), airborne laser scanning (ALS) and other remotely sensed data. While the ALS data were acquired over a time interval of 10 years using various sensors and settings, the NFI data are continuously collected. Aims of this study were to analyze the effects of stratification on models linking remotely sensed and field data, and assess the accuracy overall and at the ALS project level. Materials and methods The model dataset consisted of 9203 NFI field plots and data from 367 ALS projects, covering 17 Mha and 2/3 of the productive forest in Norway. Mixed-effects regression models were used to account for differences among ALS projects. Two types of stratification were used to fit models: 1) stratification by the three main tree species groups spruce, pine and deciduous resulted in species-specific models that can utilize a satellite-based species map for improving predictions, and 2) stratification by species and maturity class resulted in stratum-specific models that can be used in forest management inventories where each stand regularly is visually stratified accordingly. Stratified models were compared to general models that were fit without stratifying the data. Results The species-specific models had relative root-mean-squared errors (RMSEs) of 35%, 34%, 31%, and 12% for volume, aboveground biomass, basal area, and Lorey’s height, respectively. These RMSEs were 2–7 percentage points (pp) smaller than those of general models. When validating using predicted species, RMSEs were 0–4 pp. smaller than those of general models. Models stratified by main species and maturity class further improved RMSEs compared to species-specific models by up to 1.8 pp. Using mixed-effects models over ordinary least squares models resulted in a decrease of RMSE for timber volume of 1.0–3.9 pp., depending on the main tree species. RMSEs for timber volume ranged between 19%–59% among individual ALS projects. Conclusions The stratification by tree species considerably improved models of forest structural variables. A further stratification by maturity class improved these models only moderately. The accuracy of the models utilized in SR16 were within the range reported from other ALS-based forest inventories, but local variations are apparent.

Abstract Background Forest carbon models are recognized as suitable tools for the reporting and verification of forest carbon stock and stock change, as well as for evaluating the forest management options to enhance the carbon sink provided by sustainable forestry. However, given their increased complexity and data availability, different models may simulate different estimates. Here, we compare carbon estimates for Romanian forests as simulated by two models (CBM and EFISCEN) that are often used for evaluating the mitigation options given the forest-management choices. Results The models, calibrated and parameterized with identical or harmonized data, derived from two successive national forest inventories, produced similar estimates of carbon accumulation in tree biomass. According to CBM simulations of carbon stocks in Romanian forests, by 2060, the merchantable standing stock volume will reach an average of 377 m3 ha−1, while the carbon stock in tree biomass will reach 76.5 tC ha−1. The EFISCEN simulations produced estimates that are about 5% and 10%, respectively, lower. In addition, 10% stronger biomass sink was simulated by CBM, whereby the difference reduced over time, amounting to only 3% toward 2060. Conclusions This model comparison provided valuable insights on both the conceptual and modelling algorithms, as well as how the quality of the input data may affect calibration and projections of the stock and stock change in the living biomass pool. In our judgement, both models performed well, providing internally consistent results. Therefore, we underline the importance of the input data quality and the need for further data sampling and model improvements, while the preference for one model or the other should be based on the availability and suitability of the required data, on preferred output variables and ease of use.

Forest fragmentation is a widespread phenomenon that directly or indirectly affects the processes that take place both in forest ecosystems and in their immediate surroundings. So far, many studies confirm its negative effects, especially on biodiversity. On the other hand, there are few studies that address the effects of forest fragmentation on the amount of accumulated biomass or carbon, as well as on the characteristics of wood resources in managed forests. Therefore, issues related to timber production, which are important from the point of view of multifunctional forest management, are omitted. The aim of our research was to add to the knowledge in this area. In particular, we focused on assessing the impact of forest fragmentation on wood resources based on an analysis of edge effects in forest patches (units formed by combining forest fragments characterized by structural connectivity). Vector data describing the topography of forest fragments in Poland and the results of the National Forest Inventory (NFI) from 2015–2019 were used as material for solving this problem. The results of our research showed that the effects of fragmentation on managed pine stands depend on the age of the stand and the fertility of the habitat. In young stands growing on barren or strongly barren habitats, growing stock volume turned out to be significantly higher in the edge zone. In older stands, especially on moderately fertile habitats, significantly higher resources were found in the interior zone of forest patches. Habitat quality also had a significant effect on the amount of carbon accumulated. In strongly barren habitats, higher carbon mass was found in edge zones, while in moderately fertile habitats, stands had higher carbon volume in the interior zone. Our results illustrate that forest fragmentation is a very complex process that can increase or reduce wood resources, depending on the age of the stand and the quality of the habitat. From the standpoint of measurable benefits, it was concluded that protection from the negative effects of fragmentation should focus primarily on older stands and more fertile habitats. [ABSTRACT FROM AUTHOR]

Abstract Background The aim of this study was to construct a nationwide stand age model by using National Forest Inventory (NFI) data and nationwide airborne laser scanning (ALS) data. In plantation forestry, age is usually known. While this is not the case in boreal managed forests, age is still seldom predicted in forest management inventories. Measuring age accurately in situ is also very laborious. On the other hand, tree age is one of the accurately measured sample tree attributes in NFI field data. Many countries also have a nationwide coverage of airborne laser scanning (ALS) data. In this study, we merged these data sources and constructed a nationwide, area-based model for stand age. Results While constructing the model, we omitted old forests from the data, since the correlation between ALS height metrics and stand age diminished at stands with age > 100 years. Additionally, the effect of growth conditions was considerable, so we also utilized different geographical and NFI variables such as site fertility and soil type in the modeling. The resultant nationwide model for the stand age of managed forests yielded a root mean square error (RMSE) of about 14 years. The model could be improved further by additional forest structure variables, but such information may not be available in practice. Conclusions The results showed that the prediction of stand age by ALS, geographical and NFI information was challenging, but still possible with moderate success. This study is an example of the joint use of NFI and nationwide ALS data and re-use of NFI data in research.

Background: The Norwegian forest resource map (SR16) maps forest attributes by combining national forest inventory (NFI), airborne laser scanning (ALS) and other remotely sensed data. While the ALS data were acquired over a time interval of 10 years using various sensors and settings, the NFI data are continuously collected. Aims of this study were to analyze the effects of stratification on models linking remotely sensed and field data, and assess the accuracy overall and at the ALS project level. Materials and methods: The model dataset consisted of 9203 NFI field plots and data from 367 ALS projects, covering 17 Mha and 2/3 of the productive forest in Norway. Mixed-effects regression models were used to account for differences among ALS projects. Two types of stratification were used to fit models: 1) stratification by the three main tree species groups spruce, pine and deciduous resulted in species-specific models that can utilize a satellite-based species map for improving predictions, and 2) stratification by species and maturity class resulted in stratum-specific models that can be used in forest management inventories where each stand regularly is visually stratified accordingly. Stratified models were compared to general models that were fit without stratifying the data. Results: The species-specific models had relative root-mean-squared errors (RMSEs) of 35%, 34%, 31%, and 12% for volume, aboveground biomass, basal area, and Lorey's height, respectively. These RMSEs were 2–7 percentage points (pp) smaller than those of general models. When validating using predicted species, RMSEs were 0–4 pp. smaller than those of general models. Models stratified by main species and maturity class further improved RMSEs compared to species-specific models by up to 1.8 pp. Using mixed-effects models over ordinary least squares models resulted in a decrease of RMSE for timber volume of 1.0–3.9 pp., depending on the main tree species. RMSEs for timber volume ranged between 19%–59% among individual ALS projects. Conclusions: The stratification by tree species considerably improved models of forest structural variables. A further stratification by maturity class improved these models only moderately. The accuracy of the models utilized in SR16 were within the range reported from other ALS-based forest inventories, but local variations are apparent. [ABSTRACT FROM AUTHOR]

Mongolia’s first Multipurpose National Forest Inventory, 2014-2017, was implemented by the Forest Research and Development Centre, in collaboration with international expertise and the country’s main forestry institutions, universities and research organisations.The long-term objective of the multipurpose NFI is to promote sustainable management of forestry resources in Mongolia, to enhance their social, economic and environmental functions.The NFI findings show that there are 11.3 million hectares of Boreal Forest in Mongolia. 9.5 million hectares are Stocked Boreal Forest Area, of which 69 percent is located outside of protected areas, 4 percent are designated for green-wood utilisation through forest enterprise concessions, and another 16 percent designated for fallen dead-wood collection through forest user group concessions. The non-protected stocked forests (i.e. production forest) have an average growing stock volume of 115 m3 per hectare, compared with an optimal growing stock volume of 237 m3 per hectare, and there is an additional 46.5 m3 of dead wood per hectare. The growing stock age distribution shows that 24 m3 per hectare are over 200 years (i.e. economically over-aged). The main tree species in stocked forest are Larix sibirica (81%), Pinus sibirica (7%), Betula platyphylla (6%) and Pinus sylvestris (5%), of which all, except for P. sibirica, are classified as legally harvestable tree species. Wild fire is the current main environmental factor decreasing the forest tree biomass.The NFI helped identifying priority areas for the forestry sector, and to guide the implementation of sustainable forest management at the local level. The main forest management challenges of Mongolia’s boreal forest will be to address that they are a) under-stocked (less than 50% of production potential), b) over-aged (31% of growing stock volume in stocked production forest is above optimal production age), and c) under-utilised (4% of forest area designated to green-wood utilisation).

Background: Forest carbon models are recognized as suitable tools for the reporting and verification of forest carbon stock and stock change, as well as for evaluating the forest management options to enhance the carbon sink provided by sustainable forestry. However, given their increased complexity and data availability, different models may simulate different estimates. Here, we compare carbon estimates for Romanian forests as simulated by two models (CBM and EFISCEN) that are often used for evaluating the mitigation options given the forest-management choices. Results: The models, calibrated and parameterized with identical or harmonized data, derived from two successive national forest inventories, produced similar estimates of carbon accumulation in tree biomass. According to CBM simulations of carbon stocks in Romanian forests, by 2060, the merchantable standing stock volume will reach an average of 377 m3 ha−1, while the carbon stock in tree biomass will reach 76.5 tC ha−1. The EFISCEN simulations produced estimates that are about 5% and 10%, respectively, lower. In addition, 10% stronger biomass sink was simulated by CBM, whereby the difference reduced over time, amounting to only 3% toward 2060. Conclusions: This model comparison provided valuable insights on both the conceptual and modelling algorithms, as well as how the quality of the input data may affect calibration and projections of the stock and stock change in the living biomass pool. In our judgement, both models performed well, providing internally consistent results. Therefore, we underline the importance of the input data quality and the need for further data sampling and model improvements, while the preference for one model or the other should be based on the availability and suitability of the required data, on preferred output variables and ease of use. [ABSTRACT FROM AUTHOR]

This is a case of a pediatric patient with a history of neurofibromatosis I (NFI) presenting to the emergency department secondary to a suicide attempt via self-strangulation after being verbally and physically bullied at school. Upon hospital admission, the 10-year-old patient was found to have significant auditory and visual perceptual hallucinations in addition to suicidal ideations, for which psychiatry was consulted. The patient underwent magnetic resonance imaging (MRI) of the brain to evaluate for intracranial neurofibromas as a potential etiology of his behavior. There is evidence that the growth of neurofibromas in the brain can be associated with psychosis. His brain MRI was significant for multiple foci of non-enhancing lesions seen in the cerebellum, white matter, supratentorial white matter, and bilateral hippocampi that can be seen in NFI, highlighting a medical etiology for the patient's auditory and visual perceptual disturbances. The objective of this case report is to explore medical causes of psychosis including metabolic disorders, neurodegenerative diseases, metabolic disturbances, parathyroid diseases, genetic disorders (Fragile X, Prader-Willi, etc.), autoimmune disorders, multiple sclerosis, temporal lobe epilepsy, infections, and brain tumors., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Sanzone et al.)

Background The nuclear factor I (NFI) is a family of transcription factors consisting of four distinct but closely related genes, NFIA, NFIB, NFIC and NFIX, which are important in the development of various tissues and organs in mammals. Recent study results have shown that NFI family may play a critical role in the progression of various human tumors and have been identified as key tumor suppressors and oncogenes for many cancers. However, the expression levels and distinctive prognostic values of the NFI family remain poorly explored in most cancers. Materials and Methods In the present study, the differences in mRNA expression of the NFI family in various cancers were investigated using the Oncomine and TCGA databases, and the mRNA expression, genetic alteration and DNA methylation of the NFI family members in various cancers were examined using cBioPortal for Cancer Genomics. In addition, the prognostic significance of the NFI family was assessed in multiple cancers using the Kaplan–Meier plotter (KM plotter) and SurvExpress databases. Results The mRNA expression levels in the NFI family were significantly downregulated in most cancers compared with normal tissues and DNA hypermethylation might downregulate the NFI family expression. Although NFIX expression was not downregulated in kidney, colorectal and prostate cancers. Furthermore, NFIB expression was upregulated in gastric cancer. Further survival analyses based on the KM plotter and SurvExpress databases showed dysregulations of the NFI genes were significantly correlated with survival outcomes in breast, lung, and head and neck cancers. Decreased expression levels of NFIA, NFIB and NFIC were associated with poor overall survival (OS) in head and neck cancer. Low mRNA expression of NFIA and NFIB was significantly associated with OS and first progression in lung adenocarcinoma, but not in lung squamous cell carcinoma. In addition, potential correlations between NFI family members and survival outcomes were also observed in liver, esophageal, kidney and cervical cancer. Conclusion The results from the present study indicated certain members of the NFI family could be promising therapeutic targets and novel prognostic biomarkers for human cancers.

In a Europe shaped by centuries of forest management, the task of today's scientists in characterising, understanding and modelling natural forests is highly challenging. Although numerous forest reserves exist, most remain hardly comparable case studies. Contrarily, National Forest Inventories (NFIs) consist of systematically distributed sample plots with varying time since last intervention and provide representative data. These characteristics make NFIs a unique opportunity to investigate hidden natural forests.Here we propose using NFI plots free of human influence for >40 to >70 years ('latent reserves') to conduct large‐scale studies on near‐natural forests. We tested this original concept in Swiss forests. We characterised compositional and structural attributes of 'latent reserves' and compared them with those of managed forests to assess whether the former demonstrated more signs of naturalness than the latter. As an example of an application, we analysed the tree‐ and stand‐level factors affecting natural tree mortality in 'latent reserves'.Up to 15.3% of Swiss NFI plots fulfilled the criteria of 'latent reserves', and most of these plots were distributed at mid‐ to high elevations where accessibility and management opportunities are limited. 'Latent reserves' showed more signs of naturalness than managed forests—a higher proportion of broadleaves, higher mortality rates, higher stand density and more deadwood. However, their size structure and basal area did not differ from those of managed forests, most likely because of a lower site productivity. Although 'latent reserves' were transitioning towards a natural state, more time without management might be required for these forests to become fully detached from the effects of past management, especially at high elevations. Mortality analyses in 'latent reserves' showed that species‐specific tree mortality had a U‐shaped response to tree size, was negatively related to tree growth and was higher when competition was stronger.Synthesis. Our findings demonstrate the potential of 'latent reserves' to study near‐natural forests at the country level, and point to further opportunities for larger‐scale collaborations. Investigating 'latent reserves' represents a first step towards a deeper understanding of such forests using existing long‐term data and shows promise for further research in Europe. [ABSTRACT FROM AUTHOR]

Background: The aim of this study was to construct a nationwide stand age model by using National Forest Inventory (NFI) data and nationwide airborne laser scanning (ALS) data. In plantation forestry, age is usually known. While this is not the case in boreal managed forests, age is still seldom predicted in forest management inventories. Measuring age accurately in situ is also very laborious. On the other hand, tree age is one of the accurately measured sample tree attributes in NFI field data. Many countries also have a nationwide coverage of airborne laser scanning (ALS) data. In this study, we merged these data sources and constructed a nationwide, area-based model for stand age. Results: While constructing the model, we omitted old forests from the data, since the correlation between ALS height metrics and stand age diminished at stands with age > 100 years. Additionally, the effect of growth conditions was considerable, so we also utilized different geographical and NFI variables such as site fertility and soil type in the modeling. The resultant nationwide model for the stand age of managed forests yielded a root mean square error (RMSE) of about 14 years. The model could be improved further by additional forest structure variables, but such information may not be available in practice. Conclusions: The results showed that the prediction of stand age by ALS, geographical and NFI information was challenging, but still possible with moderate success. This study is an example of the joint use of NFI and nationwide ALS data and re-use of NFI data in research. [ABSTRACT FROM AUTHOR]

Regulation of the epigenome during in vivo specification of brain stem cells is still poorly understood. Here, we report DNA methylome analyses of directly sampled cortical neural stem and progenitor cells (NS/PCs) at different development stages, as well as those of terminally differentiated cortical neurons, astrocytes, and oligodendrocytes. We found that sequential specification of cortical NS/PCs is regulated by two successive waves of demethylation at early and late development stages, which are responsible for the establishment of neuron- and glia-specific low-methylated regions (LMRs), respectively. The regulatory role of demethylation of the gliogenic genes was substantiated by the enrichment of nuclear factor I (NFI)-binding sites. We provide evidence that de novo DNA methylation of neuron-specific LMRs establishes glia-specific epigenotypes, essentially by silencing neuronal genes. Our data highlight the in vivo implications of DNA methylation dynamics in shaping epigenomic features that confer the differentiation potential of NS/PCs sequentially during development.

Forests are an important component of the global carbon (C) cycle: they can capture and retain large amounts of C annually, depending on stand characteristics, climate, and disturbance regimes. With climate and disturbance regimes shifting, it is important to be able to accurately represent the corresponding changes in forest C dynamics with well-calibrated models. The Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3) is a widely used model for simulating C dynamics in managed forests at stand, regional, and national levels. Here, we use a Bayesian Markov Chain Monte Carlo (MCMC) technique to calibrate the parameters in the CBM-CFS3 by assimilating C stocks of six deadwood and soil pools estimated from data collected from 635 plots within the Canadian National Forest Inventory. Calibration led to most improvement in the simulation of C stocks in small and fine woody debris, reducing RMSE by 54.3%, followed by the snag stems (RMSE reduced by 23.2%), and coarse woody debris (13%). The calibrated parameters resulted in increased rates of C cycling in fine and coarse woody debris and the soil organic layer, distinct C dynamics in hardwood and softwood dominated stands, and increased temperature sensitivity of the C contained in the mineral soil. While parameter calibration considerably improved the simulation of the small and fine woody debris and snags stem pools, model representation of the branch snag, coarse woody debris, soil organic layer, and mineral soil pools were not substantially improved. Lack of substantial improvements in the calibrated model performance indicated the need for including additional processes in C dynamics simulation or a change in the modelling paradigm. We illustrate the potential need to include a lignin effect on deadwood decay and suggest further exploration of the effects of tree species, soil types, and mosses on performance of the CBM-CFS3. [ABSTRACT FROM AUTHOR]

National and international carbon reporting systems require information on forest carbon stocks. This information can be derived from national forest inventory data and remote sensing. Here we present the conceptual challenges in assessing forest resources across Europe by combining MODIS satellite versus terrestrial driven NPP estimates calculated from 13 national forest inventory (NFI) data covering 200.000 sampling plots. The results suggest that MODIS NPP predictions using local daily climate data and addressing stand desnsity effects, provide realistic forest productivity estimates. Ignoring these effects leads to an overestimation in the estimated carbon storage of European forests derived from satellite data. [ABSTRACT FROM AUTHOR]

Although wall-to-wall, accurate, and up-to-date forest composition maps at the stand level are a fundamental input for many applications, ranging from global environmental issues to local forest management planning, countrywide mapping approaches on the tree type level remain rare. This paper presents and validates an innovative remote sensing based approach for a countrywide mapping of broadleaved and coniferous trees in Switzerland with a spatial resolution of 3 m. The classification approach incorporates a random forest classifier, explanatory variables from multispectral aerial imagery and a Digital Terrain Model (DTM) from Airborne Laser Scanning (ALS) data, digitized training polygons and independent validation data from the National Forest Inventory (NFI). The methodological workflow was optimized for an area of 41,285 km² that is characterized by temperate forests within a complex topography. Whereas high model overall accuracies (0.99) and kappa (0.98) were achieved, the comparison of the tree type map with independent NFI data revealed significant deviations that are related to underestimations of broadleaved trees (median of -3.17%). Constraints of the tree type mapping approach are mostly related to the acquisition date and time of the imagery and the topographic (negative) effects on the prediction. A comparison with the most recent High Resolution Layers (HRL) forest 2012 from the European Environmental Agency revealed that the tree type map is superior regarding spatial resolution, level of detail and accuracy. The high-quality map achieved with the approach presented here is of great value for optimizing forest management and planning activities and is also an important information source for applications outside the forestry sector. [ABSTRACT FROM AUTHOR]

The paper shows difficulties in the evaluation of the forest status when considering forests with different height structure (uneven-aged forests). It is the main problem in categorizing such forests. Concerning the actual forest management conception in Slovakia, it is assumed that the area of forests with close-to-nature management system will increase. It leads to more structured forests, as for the tree species, age, height, as well as the spatial structure. The typical vertically homogeneous forests account for only 50% of all Slovak forests, according to results from the National Forest Inventory in Slovakia (NFI SR). During the processing of NFI data the stands were divided into 2 classes as follows: (i) vertically homogeneous stands, which are classified into nine growth stages; (ii) vertically heterogeneous stands, which are classified into two growth stages (lower and advanced), and stands in the process of regeneration. New approaches are not based on the visual subjective estimation of forest homogeneity, but on objective analyses of measured values from inventory plots (tree heights, diameters, and age). The paper shows a new approach to the classification of forest stands on an example of the variability of measured heights on inventory plots from NFI.

A climate change mitigation mechanism for emissions reduction from reduced deforestation and forest degradation, plus forest conservation, sustainable management of forest, and enhancement of carbon stocks (REDD+), has received an international political support in the climate change negotiations. The mechanism will require, among others, an unprecedented technical capacity for monitoring, reporting and verification of carbon emissions from the forest sector. A functional monitoring, reporting and verification requires inventories of forest area, carbon stock and changes, both for the construction of forest reference emissions level and compiling the report on the actual emissions, which are essentially lacking in developing countries, particularly in Africa. The purpose of this essay is to contribute to a better understanding of the state and prospects of forest monitoring and reporting in the context of REDD+ in Africa. We argue that monitoring and reporting capacities in Africa fall short of the stringent requirements of the methodological guidance for monitoring, reporting and verification for REDD+, and this may weaken the prospects for successfully implementing REDD+ in the continent. We presented the challenges and prospects in the national forest inventory, remote sensing and reporting infrastructures. A North-South, South-South collaboration as well as governments own investments in monitoring, reporting and verification system could help Africa leapfrog in monitoring and reporting. These could be delivered through negotiations for the transfer of technology, technical capacities, and experiences that exist among developed countries that traditionally compile forest carbon reports in the context of the Kyoto protocol. [ABSTRACT FROM AUTHOR]

Spatially explicit knowledge of aboveground biomass (AGB) in large areas is important for accurate carbon accounting and quantifying the effect of forest disturbance on the terrestrial carbon cycle. We estimated AGB from 1990 to 2011 in northern Guangdong, China, based on a spatially explicit dataset derived from six years of national forest inventory (NFI) plots, Landsat time series imagery (1986-2011) and Advanced Land Observing Satellite (ALOS) Phased Array L-band Synthetic Aperture Radars (PALSAR) 25 m mosaic data (2007-2010). Four types of variables were derived for modeling and assessment. The random forest approach was used to seek the optimal variables for mapping and validation. The root mean square error (RMSE) of plot-level validation was between 6.44 and 39.49 (t/ha), the normalized root-mean-square error (NRMSE) was between 7.49% and 19.01% and mean absolute error (MAE) was between 5.06 and 23.84 t/ha. The highest coefficient of determination R² of 0.8 and the lowest NRMSE of 7.49% were reported in 2006. A clear increasing trend of mean AGB from the lowest value of 13.58 t/ha to the highest value of 66.25 t/ha was witnessed between 1988 and 2000, while after 2000 there was a fluctuating ascending change, with a peak mean AGB of 67.13 t/ha in 2004. By integrating AGB change with forest disturbance, the trend in disturbance area closely corresponded with the trend in AGB decrease. To determine the driving forces of these changes, the correlation analysis was adopted and exploratory factor analysis (EFA) method was used to find a factor rotation that maximizes this variance and represents the dominant factors of nine climate elements and nine human activities elements affecting the AGB dynamics. Overall, human activities contributed more to short-term AGB dynamics than climate data. Harvesting and human-induced fire in combination with rock desertification and global warming made a strong contribution to AGB changes. This study provides valuable information for the relationships between forest AGB and climate as well as forest disturbance in subtropical zones. [ABSTRACT FROM AUTHOR]

Net primary production (NPP) is an important ecological metric for studying forest ecosystems and their carbon sequestration, for assessing the potential supply of food or timber and quantifying the impacts of climate change on ecosystems. The global MODIS NPP dataset using the MOD17 algorithm provides valuable information for monitoring NPP at 1-km resolution. Since coarse-resolution global climate data are used, the global dataset may contain uncertainties for Europe. We used a 1-km daily gridded European climate data set with the MOD17 algorithm to create the regional NPP dataset MODIS EURO. For evaluation of this new dataset, we compare MODIS EURO with terrestrial driven NPP from analyzing and harmonizing forest inventory data (NFI) from 196,434 plots in 12 European countries as well as the global MODIS NPP dataset for the years 2000 to 2012. Comparing these three NPP datasets, we found that the global MODIS NPP dataset differs from NFI NPP by 26%, while MODIS EURO only differs by 7%. MODIS EURO also agrees with NFI NPP across scales (from continental, regional to country) and gradients (elevation, location, tree age, dominant species, etc.). The agreement is particularly good for elevation, dominant species or tree height. This suggests that using improved climate data allows the MOD17 algorithm to provide realistic NPP estimates for Europe. Local discrepancies between MODIS EURO and NFI NPP can be related to differences in stand density due to forest management and the national carbon estimation methods. With this study, we provide a consistent, temporally continuous and spatially explicit productivity dataset for the years 2000 to 2012 on a 1-km resolution, which can be used to assess climate change impacts on ecosystems or the potential biomass supply of the European forests for an increasing bio-based economy. MODIS EURO data are made freely available at ftp://palantir.boku.ac.at/Public/MODIS_EURO. [ABSTRACT FROM AUTHOR]

Here, we identify a role for the matrilin-2 (Matn2) extracellular matrix protein in controlling the early stages of myogenic differentiation. We observed Matn2 deposition around proliferating, differentiating and fusing myoblasts in culture and during muscle regeneration in vivo. Silencing of Matn2 delayed the expression of the Cdk inhibitor p21 and of the myogenic genes Nfix, MyoD and Myog, explaining the retarded cell cycle exit and myoblast differentiation. Rescue of Matn2 expression restored differentiation and the expression of p21 and of the myogenic genes. TGF-β1 inhibited myogenic differentiation at least in part by repressing Matn2 expression, which inhibited the onset of a positive-feedback loop whereby Matn2 and Nfix activate the expression of one another and activate myoblast differentiation. In vivo, myoblast cell cycle arrest and muscle regeneration was delayed in Matn2[sup -/-] relative to wild-type mice. The expression levels of Trf3 and myogenic genes were robustly reduced in Matn2[sup -/-] fetal limbs and in differentiating primary myoblast cultures, establishing Matn2 as a key modulator of the regulatory cascade that initiates terminal myogenic differentiation. Our data thus identify Matn2 as a crucial component of a genetic switch that modulates the onset of tissue repair. [ABSTRACT FROM AUTHOR]

Background Sulfotransferase 1A1 (SULT1A1) gene expression is tissue specific, with little to no expression in normal breast epithelia. Expression in breast tumors has been documented, but the transcriptional regulation of SULT1A1 in human breast tissue is poorly understood. We identified Nuclear Factor I (NFI) as a transcription factor family involved in the regulation of SULT1A1 expression. Methods Transcription Factor Activation Profiling Plate Array assay was used to identify the possible transcription factors that regulate the gene expression of SULT1A1in normal breast MCF-10A cells and breast cancer ZR-75-1 cells. Expression levels of NFI-C and SULT1A1 were determined by real-time RT-PCR using total RNA isolated from 84 human liver samples. Expression levels of SULT1A1, NFI-A, NFI-B, NFI-C, and NFI-X were also determined in different human breast cancer cell lines (MCF-7, T-47D, ZR-75-1, and MDA-MB-231), in the transformed human epithelial cell line MCF-10A, and in ZR-75-1 cells that were transfected with siRNAs directed against NFI-A, NFI-B, NFI-C, or NFI-X for 48 h. The copy numbers of SULT1A1 in cell lines ZR-75-1, MCF-7, T-47D, MDA-MB-231, and MCF-10A were determined using a pre-designed Custom Plus TaqMan® Copy Number kit from Life Technologies. Results In normal human liver samples, SULT1A1 mRNA level was positively associated with NFIC. In different human breast cancer and normal epithelial cell lines, SULT1A1 expression was positively correlated with NFI-B and NFI-C. SULT1A1 expression was decreased 41% and 61% in ZR-75-1 cells treated with siRNAs against NFI-A and NFI-C respectively. SULT1A1 gene expression was higher in cells containing more than one SULT1A1 copy numbers. Conclusions Our data suggests that SULT1A1 expression is regulated by NFI, as well as SULT1A1 copy number variation in human breast cancer cell lines. These data provide a mechanistic basis for the differential expression of SULT1A1 in different tissues and different physiological states of disease. [ABSTRACT FROM AUTHOR]

Context: Old-growth trees play a very important role in the maintenance of biodiversity in forests. However, no clear definition is yet available to help identify them since tree age is usually not recorded in National Forest Inventories. Aims: To develop and test a new method to identify old-growth trees using a species-specific threshold for tree diameter in National Forest Inventories. Methods: Different nonlinear mixed models for diameter-age were generated using data from the Spanish Forest Inventory in order to identify the most appropriate one for Aleppo pine in its South-western distribution area. The asymptote of the optimal model indicates the threshold diameter for defining an old-growth tree. Additionally, five site index curves were examined to analyze the influence of site quality on these models. Results: The Hossfled III mixed model was found to be the most appropriate to fit diameter-age curves for Aleppo pine trees. The overall diameter at breast height threshold for old-growth trees was 40.6 cm, although over a range of sites with increasing site quality, the threshold figure was 36.0, 38.0, 40.4, 43.1, and 46.3 cm, respectively. Conclusions: This method allows the identification of old-growth trees and therefore of biodiversity hotspots, thus providing decision makers with a useful tool for management purposes. [ABSTRACT FROM AUTHOR]

Abstract: Indicators for sustainable forest management are considered to be key tools for the implementation of regional, national and international forest policies. The Montreal process identified the “maintenance of forest contribution to global carbon cycles” as an essential component in sustainable management of forest ecosystems. Carbon sink evaluations provide reference information to policy-makers, stakeholders, resource managers and concerned citizens about the sustainable use of our forests for present and future generations. Two forest areas in northern and central Spain (‘Páramos y Valles’ and Central Mountain Range) were chosen as pilot areas to test the use of the National Forest Inventory to calculate carbon biomass forest sink at operational level. Data from the Second and Third National Forest Inventory (2NFI and 3NFI, respectively), together with biomass equations were used. Total carbon biomass sink was calculated as a balance between carbon dioxide inputs and outputs in forest biomass. Tree growth between 2NFI and 3NFI, new plots and ingrowth (recruitment and upgrowth) biomass were considered as inputs, while forest harvesting and natural mortality were considered as outputs. In ‘Páramos y Valles’, 2.46MgCO2 ha−1 year−1 was fixed in the tree biomass of forest ecosystems from 2NFI to 3NFI, whereas in the Central Mountain Range the fixation was 0.72MgCO2 ha−1 year−1 in the period between inventories. The balance of CO2 in the two areas was positive in 3NFI, with more than four million Mg of CO2 accumulated in ‘Páramos y Valles’ and more than 72 million Mg of CO2 fixed in the Central Mountain Range. Forest ecosystems are carbon sinks in the tree biomass in the two areas considered. [Copyright &y& Elsevier]

Even though astrocytes are critical for both normal brain functions and the development and progression of neuropathological states, including neuroinflammation associated with neurodegenerative diseases, the mechanisms controlling gene expression during astrocyte differentiation are poorly understood. Thus far, several signaling pathways were shown to regulate astrocyte differentiation, including JAK-STAT, bone morphogenic protein-2/Smads, and Notch. More recently, a family of nuclear factor-1 (NFI-A, -B, -C, and -X) was implicated in the regulation of vertebral neocortex development, with NFI-A and -B controlling the onset of gliogenesis. Here, we developed an in vitro model of differentiation of stem cells towards neural progenitors (NP) and subsequently astrocytes. The transition from stem cells to progenitors was accompanied by an expected change in the expression profile of markers, including Sox-2, Musashi-1, and Oct4. Subsequently, generated astrocytes were characterized by proper morphology, increased glutamate uptake, and marker gene expression. We used this in vitro differentiation model to study the expression and functions of NFIs. Interestingly, stem cells expressed only background levels of NFIs, while differentiation to NP activated the expression of NFI-A. More importantly, NFI-X expression was induced during the later stages of differentiation towards astrocytes. In addition, NFI-X and -C were required for the expression of glial fibrillary acidic protein and secreted protein acidic and rich in cystein-like protein 1, which are the markers of astrocytes at the later stages of differentiation. We conclude that an expression program of NFIs is executed during the differentiation of astrocytes, with NFI-X and -C controlling the expression of astrocytic markers at late stages of differentiation. [ABSTRACT FROM AUTHOR]

Members of the nuclear factor I (NFI) family are key regulators of stem cell biology during development, with well-documented roles for NFIA, NFIB, and NFIX in a variety of developing tissues, including brain, muscle, and lung. Given the central role these factors play in stem cell biology, we posited that they may be pivotal for spermatogonial stem cells or further developing spermatogonia during testicular development. Surprisingly, in stark contrast to other developing organ systems where NFI members are co-expressed, these NFI family members show discrete patterns of expression within the seminiferous tubules. Sertoli cells (spermatogenic supporting cells) express NFIA, spermatocytes express NFIX, round spermatids express NFIB, and peritubular myoid cells express each of these three family members. Further analysis of NFIX expression during the cycle of the seminiferous epithelium revealed expression not in spermatogonia, as we anticipated, but in spermatocytes. These data suggested a potential role for NFIX in spermatogenesis. To investigate, we analyzed mice with constitutive deletion of Nfix (Nfix-null). Assessment of germ cells in the postnatal day 20 (P20) testes of Nfix-null mice revealed that spermatocytes initiate meiosis, but zygotene stage spermatocytes display structural defects in the synaptonemal complex, and increased instances of unrepaired DNA double-strand breaks. Many developing spermatocytes in the Nfix-null testis exhibited multinucleation. As a result of these defects, spermatogenesis is blocked at early diplotene and very few round spermatids are produced. Collectively, these novel data establish the global requirement for NFIX in correct meiotic progression during the first wave of spermatogenesis., (© The Author(s) 2022. Published by Oxford University Press on behalf of Society for the Study of Reproduction. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Nuclear Factor One (NFI) family of transcription factors regulate proliferation and multiple aspects of differentiation, playing analogous roles in embryonic development and various types of cancer. While all NFI family members are expressed in the developing brain and are involved in progression of brain cancers, their role in neuroblastoma has not been studied. Here we show that NFIB is required for the survival and proliferation of SH-SY5Y neuroblastoma cells, assessed by viability and colony formation assays. Cdon, an Ig superfamily member, is a SHH dependence receptor that acts as a tumor suppressor in neuroblastoma. In the absence of NFI, Cdon is upregulated in the developing mouse brain, however the mechanisms by which its transcription is regulated remains unknown. We report CDON as a downstream target of NFIs in SH-SY5Y cells. There are three putative NFI binding sites within the one kb CDON promoter, two of which are occupied by NFIs in SH-SY5Y cells and human neural stem cells. In dual-luciferase assays, Nfib directly represses CDON proximal promoter activity. Moreover, silencing NFIB leads to upregulation of CDON in SH-SY5Y cells, however, decreased cell proliferation in NFIB silenced cells could not be rescued by concomitantly silencing CDON , suggesting other molecular players are involved. For instance, p21, an NFI target in glioblastoma and breast cancer cells, is also upregulated upon NFIB knock-down. We propose that NFIB is indispensable for SH-SY5Y cells which may involve regulation of apoptosis inducer proteins CDON and p21. • CDON is a downstream target of NFIB in SH-SY5Y neuroblastoma cells. • NFIs occupy two of identified NFI binding sites on CDON promoter in SH-SY5Y. • NFIB directly represses CDON proximal promoter activity. • NFIB is required for the survival and proliferation of SH-SY5Y cells. [ABSTRACT FROM AUTHOR]

Nuclear Factor One (NFI) family of transcription factors regulate proliferation and multiple aspects of differentiation, playing analogous roles in embryonic development and various types of cancer. While all NFI family members are expressed in the developing brain and are involved in progression of brain cancers, their role in neuroblastoma has not been studied. Here we show that NFIB is required for the survival and proliferation of SH-SY5Y neuroblastoma cells, assessed by viability and colony formation assays. Cdon, an Ig superfamily member, is a SHH dependence receptor that acts as a tumor suppressor in neuroblastoma. In the absence of NFI, Cdon is upregulated in the developing mouse brain, however the mechanisms by which its transcription is regulated remains unknown. We report CDON as a downstream target of NFIs in SH-SY5Y cells. There are three putative NFI binding sites within the one kb CDON promoter, two of which are occupied by NFIs in SH-SY5Y cells and human neural stem cells. In dual-luciferase assays, Nfib directly represses CDON proximal promoter activity. Moreover, silencing NFIB leads to upregulation of CDON in SH-SY5Y cells, however, decreased cell proliferation in NFIB silenced cells could not be rescued by concomitantly silencing CDON, suggesting other molecular players are involved. For instance, p21, an NFI target in glioblastoma and breast cancer cells, is also upregulated upon NFIB knock-down. We propose that NFIB is indispensable for SH-SY5Y cells which may involve regulation of apoptosis inducer proteins CDON and p21., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Gene regulatory networks (GRNs), consisting of transcription factors and their target sites, control neurogenesis and cell-fate specification in the developing central nervous system. In this study, we use integrated single-cell RNA and single-cell ATAC sequencing (scATAC-seq) analysis in developing mouse and human retina to identify multiple interconnected, evolutionarily conserved GRNs composed of cell-type-specific transcription factors that both activate genes within their own network and inhibit genes in other networks. These GRNs control temporal patterning in primary progenitors, regulate transition from primary to neurogenic progenitors, and drive specification of each major retinal cell type. We confirm that NFI transcription factors selectively activate expression of genes promoting late-stage temporal identity in primary retinal progenitors and identify other transcription factors that regulate rod photoreceptor specification in postnatal retina. This study inventories cis- and trans-acting factors that control retinal development and can guide cell-based therapies aimed at replacing retinal neurons lost to disease., Competing Interests: Declaration of interests S.B. co-founded and is a shareholder of CDI Labs, LLC. S.B. is also a consultant for Third Rock Ventures, LLC., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)