Wood pellets are an important fuel for bioenergy production, with demand expected to increase as renewable energy production expands globally. Common feedstock sources include in-woods chips or pulpwood-sized roundwood harvested from both thinnings and final harvests in pine (Pinus spp.) stands. Wood pellet production may result in more intensive harvesting and less downed woody debris (DWD) retained post-harvest, which could affect site sustainability. To examine this, we conducted a field-based study comparing the retention and distribution of DWD material across wood pellet and conventional pulpwood harvests (n = 75). Wood pellet clearcuts had lower coarse and fine DWD for total treatment area (P = 0.06) and a reduction in fine DWD on landings (P = 0.06) compared to conventional harvests. Additionally, operations incorporating in-woods chipping for pellet feedstock decreased coarse DWD in clearcut harvest areas by 2.74 Mg ha-1 compared to conventional harvesting sites (P = 0.05). Conversely, thinning treatments showed no significant differences in DWD retention on landings (P = 0.40), harvest areas (P = 0.79), or total area (P = 0.61). Pellet harvests with in-woods chipping reduced DWD nutrient retention, particularly fine and coarse debris carbon content on landings (P = 0.02), and fine debris nitrogen content in harvest areas (P = 0.07). Our study suggests that wood pellet clearcut harvests using in-woods chipping reduces DWD. However, remaining amounts are within acceptable ranges suggested by Biomass Harvesting Guidelines (BHGs). Findings suggest a need for complementary research in the southeastern US to assess threshold levels of DWD required for maintaining site sustainability, water quality, and wildlife habitat.
Downed woody debris (DWD) plays an important role as regulator of nutrient and carbon (C) cycling in forests, accounting for up to the 20 % of the total C stocks in primary forests. DWD persistence is highly influenced by microbial decomposition, which is determined by various environmental factors, including fluctuations in temperature and moisture, as well as in intrinsic DWD properties determined by species, diameter, or decay classes (DCs). The relative importance of these different drivers, as well as their interactions, remains largely unknown. Moreover, the importance of DWD for C cycling in virgin forests remains poorly understood, due to their scarcity and poor accessibility. To address this research gap, we conducted a study on DWD respiration (RDWD), in a temperate virgin forest dominated by European beech and silver fir. Our investigation analysed the correlation between RDWD of these two dominant tree species and the seasonal changes in climate (temperature and moisture), considering other intrinsic DWD traits such as DCs (1, 2 and 4) and diameters (1, 10 and 25 cm). As anticipated, RDWD (normalized per gram of dry DWD) increased with air temperature. Surprisingly, DWD diameter also had a strong positive correlation with RDWD. Nonetheless, the sensitivity to both variables and other intrinsic traits (DC and density) was greatly modulated by the species. On the contrary, water content, which exhibited a considerable spatial variation, had an overall negative effect on RDWD. Virgin forests are generally seen as ineffective C sinks due to their lack of net productivity and high respiration and nutrient turnover. However, the rates of RDWD in this virgin forest were significantly lower than those previously estimated for managed forests. This suggests that DWD in virgin forests may be buffering forest CO2 emissions to the atmosphere more than previously thought.
In a conifer forest in Central Italy burnt by wildfire in 2017, shallow sub-surface (topmost 5 cm) soil temperature and soil moisture (% volumetric water content) were measured during summer 2022. Various distances from downed trees (natural barriers) and log erosion barriers (artificial barriers) were sampled. Additional data on the hour of sampling, barriers characteristics, and barriers location were collected.
Downed woody material (DWM) is a unique part of the forest carbon cycle serving as a pool between living biomass and subsequent atmospheric emission or transference to other forest pools. Thus, DWM is an individually defined pool in national greenhouse gas inventories. The diversity of DWM carbon drivers (e.g., decay, tree mortality, or wildfire) and associated high spatial variability make this a difficult-to-predict component of forest ecosystems. Using the now fully established nationwide inventory of DWM across the United States (US), we developed models, which substantially improved predictions of stand-level DWM carbon density relative to the current national-reporting model ('previous' model, here). The previous model was developed from published DWM carbon densities prior to the NFI DWM inventory. Those predictions were tested using NFI DWM carbon densities resulting in a poor fit to the data (coefficient of determination, or R2 = 0.03). We present new random forest (RF) and stochastic gradient boosted (SGB) regression models to prediction DWM carbon density on all NFI plots and spatially on all forest land pixels. We evaluated various biotic and abiotic regression predictors, and the most important were standing dead trees, long-term annual precipitation, and long-term maximum summer temperature. A RF model scored best for expanding predictions to NFI plots (R2 = 0.31), while an SGB model was identified for DWM carbon predictions based on purely spatial data (i.e., NFI-plot-independent, with R2 = 0.23). The new RF model predicts conterminous US DWM carbon stocks to be 15% lower than the previous model and 2% higher than NFI data expanded according to inventory design-based inference. The new NFI data-driven models not only improve the predictions of DWM carbon density on all plots, they also provide flexibility in extending these predictions beyond the NFI to make spatially explicit and spatially continuous estimates of DWM carbon on all forest land in the US.
Current guidelines, rarely if at all, address decision-making for revascularization when bypass surgery is not a possibility for high-risk cases. Patients who are surgically turned down are routinely excluded from clinical trials, even though they remain symptomatic. Furthermore, the reasons for surgical ineligibility are often times not captured in standardized risk models. There is no data regarding health status outcomes following PCI procedures in these patients and the ultimate question remains whether the benefits of PCI outweigh its risks in this controversial subpopulation. When CHIP (Complex High risk Indicated Percutaneous coronary interventions) is selected for these very complex individuals, there is no unanimity regarding the goals for interventional revascularization (for instance, the ambition to achieve completeness of revascularization vs. more targeted or selective PCI). The recognition that, worldwide, these patients are becoming increasingly prevalent and increasingly commonplace in the cardiac catheterization labs, along with the momentum for more complex interventional procedures and expanding skillsets, gives us a timely opportunity to better examine the outcomes for these patients and inform clinical decision-making.
High rates of migration and invasiveness are crucial factors contributing to the elevated mortality associated with liver cancer. Peptidyl-prolyl isomerase A (PPIA) has emerged as a key player in the progression of various human cancers, although its specific role in the advancement of liver cancer has not been fully elucidated. Previous research revealed that PPIA dictated nuclear factor E2-related factor 2 (Nrf2) stability to promote cancer progression. To clarify this by exploring the biological effects of PPIA and Nrf2 in liver cancer. First, PPIA and Nrf2 expression in normal hepatocyte cells and human hepatoma cells were quantitatively analyzed using RT-qPCR and western blot. Then, to assess effects of PPIA on migration and invasion of hepatoma cells, the study employed the scratch assay and the transwell invasion assay. Further, PPIA and Nrf2 were knock-downed, and ferroptotic cell death was assessed in erastin-treated hepatoma cells to clarify effect mechanism of PPIA in liver cancer progression. The interaction between PPIA and Nrf2 by conducting Co-IP experiments. The findings of our research indicate that PPIA is overexpressed, and promotes proliferation, migration and invasion in human hepatoma cells. The knockdown of PPIA and Nrf2 significantly enhances ferroptosis, which subsequently leads to a marked decrease in both migration and invasion of human hepatoma cells. Furthermore, our investigation revealed that PPIA interacts with Nrf2 in hepatoma cells, suggesting a complex relationship between these two proteins in the progression of liver cancer. This study highlights the potential role of PPIA as a critical oncogenic driver in liver cancer, suggesting that targeting PPIA could offer therapeutic advantages in the treatment of this malignancy.
This dataset compiles detailed representative forest stand structure data from a European hemiboreal forest region; it spans multiple forest types, successional stages, and forest management contexts. It integrates measurements of live trees and dead wood, including fallen trunks, snags (standing dead trees), stumps and fine woody debris (down to 3 mm diameter), together with tree species identity, dimensional attributes, and decay stages. A subset of stands has been surveyed repeatedly, capturing temporal changes in forest structure. Estonia, hemiboreal forest zone. Field sampling was conducted between 2006 and 2024. The dataset comprises detailed stand-structure measurements from >600 forest stands, mostly represented by 2-ha plots. It includes most common hemiboreal forest types along gradients of dominant tree species and soil moisture. These range from low-productivity, dry Scots pine-dominated forests to black alder-dominated mobile-water swamps, with particularly strong representation of productive Norway spruce-deciduous mixed forests and drained peatland forests. Stand ages range from a few years post clearcutting to old stands with the dominant tree layer >200 years old. Old stands without signs of management are well represented (98 study stands) and constitute a substantial reference set for naturally developing and old-growth forest conditions in the region. The stands encompass a broad range of silvicultural treatments, including post-clearcut and post retention-cut succession, mature forests with sanitary cutting history, stands subject to precommercial and commercial thinning, and shelterwood cutting. In addition, a subset of stands includes repeated measurements of forest structure following ditch closure (rewetting) as part of a peatland forest restoration experiment. Live trees, standing dead trunks and stumps were recorded along strip plots (area-based sampling), while downed dead wood items were measured along transects (line-intersect method). The dataset enables modelling above-ground tree carbon, quantitative assessment of habitat conditions for biodiversity, and analyses of their relationships with forest characteristics. It enables analyses of how specific forest management practices (clearcutting, retention forestry, shelterwood harvest, thinning) affect the stand structure, habitat quality, and carbon stocks. Because the dataset includes geopositioned measurements collected starting from the early 2000s onward, it can be combined with time-matched or contemporary remote sensing data, or with newly collected field data from stands of comparable ages, to assess structural changes in similar forest types over time. Given that hemiboreal forest types share structural features with closed-canopy boreal and northern temperate forests dominated by spruce-pine-deciduous mixtures, the dataset is applicable for regional modelling across approximately ten degrees of latitude, spanning from the Fennoscandian middle-boreal zone to the northern limit of the beech region in mid-Lithuania.
Knowledge of fuel characteristics and their spatial and temporal distribution is increasingly important as fire managers rely on this information to quantify fire risk, plan prescribed burning activities, forecast fire danger and predict wildland fire behaviour and effects. Current fuel inventory approaches used in Australia largely rely on visual assessment methods that are subjective and lack the consistency and accuracy required for fire management applications. We describe a protocol to quantify characteristics for various fuel strata considered in Australian fire modelling applications, namely: litter and suspended dead fuels; downed wood debris; live understorey; bark; and overstorey canopy. The method provides information about:•Cover and height (or depth) of each strata;•Mass of fine fuels of litter, dead suspended and live understorey layers (dead fuel diameter (d) ≤ 0.6 cm, live fuel d ≤ 0.4 cm); and•Mass and size class distribution of downed woody fuels (d>0.6 cm). The protocol integrates a variety of sampling methods including destructive sampling for fine fuel particles, line intersect method for downed woody fuel, and indirect approaches relying on double sampling techniques to estimate live understorey, bark and overstorey canopy fuels. The protocol can be adapted to enable application to situations with distinct accuracy requirements. Data collected using the protocol will have direct use in developing models of forest fuel dynamics and evaluating outputs from remote sensing approaches to describe these fuels.
Saproxylic beetles, as primary decomposers in forest ecosystems, play a crucial role in the decomposition of dead wood. However, there is a significant gap in understanding the extent of assemblages and damage caused by these insects, which is essential for managing the quality and utilization of dead wood resources in natural forests. This study employed the Bevan damage classification system to quantify the severity of saproxylic beetle damage to fallen trees, focusing on the boreal forest in the Green zone of Ulaanbaatar, the capital of Mongolia. A factorial design was used to assess the influence of forest landscape (north vs. south mixed forest), tree species (Siberian spruce Picea obovata and Siberian pine Pinus sibirica), and decay class (1-4) on beetle damage indices, abundance and feeding guilds (cambium consumers, wood borers, predators, parasitoids, and detritivores). Our findings reveal that decay class significantly affects beetle abundance and damage severity with early stages showing the highest values. Cambium consumers and wood borers were more abundant in decay class 1 (DC1) for downed spruce, with Ips typographus (24.7%) and Tetropium castaneum (15%) causing the most damage. For the Siberian pine, Monochamus galloprovincialis (9.8%) and Judolia sexmaculata (13.3%) were the most damaging in DC1 followed by Pityogenes conjunctus (10%). The results suggest that Siberian spruce may be more susceptible to saproxylic beetle damage than the Siberian pine, with structural features such as bark cover branch size and wood moisture playing a critical role, especially in early decay stages. Based on our findings, we recommend decay-stage-specific management approaches, particularly targeting early decay stages (DC1-DC2) where beetle damage is most severe. Practical strategies include early detection of freshly downed trees, bark removal to reduce suitable habitat for cambium consumers, and on-site processing techniques such as bark gouging or mechanical debarking. These methods allow deadwood biomass to be retained in the forest while reducing pest pressure, offering a viable alternative to salvage logging. Such approaches are especially relevant in protected areas, where they can support both pest control and biodiversity conservation objectives. However, given the geographic scope limited to boreal forests of Ulaanbaatar, caution should be exercised in extrapolating these recommendations to other regions without further study.
Conventional protective devices cannot reliably detect series faults at the far end of the distribution feeder, such as open-conductor faults, downed conductor faults from the load side, and downed conductor faults from the source side when associated with high-impedance conditions. This limitation is especially challenging in the presence of distributed generation units. This paper introduces an innovative scheme for detecting series faults using traveling wave voltage measurements. This scheme identifies faults by comparing the polarities of the first-arriving voltage waves at the lateral ends. During such faults, the polarity at the lateral end downstream of the fault differs from the others. Building on this principle, a fault management scheme is proposed that combines polarity differences with a two-terminal traveling-wave scheme to both locate the fault and restore service. The scheme is validated on the IEEE 33-bus system using PSCAD simulations. The results confirm that the proposed scheme is sensitive to all types of series faults, whether or not distributed generation (DG) units are connected, and remains secure under normal operating conditions such as load switching and capacitor bank connection. Furthermore, the scheme accommodates the uncertainty inherent in renewable energy sources, making it effective across the full range of power contributions-from zero (when disconnected from the grid) to full output. The results confirm that proposed scheme provides high reliability in detecting the open-conductor faults and identifying faulted laterals regardless of synchronization misalignment between measurement points. It accurately determines the faulted section for synchronization deviations up to 3 µs, while deviations exceeding 1 µs may affect accuracy under busbar fault conditions. A verification step using fault indicators at secondary substations ensures correct section isolation even under significant synchronization deviations. Overall, the proposed algorithm outperforms existing methods, particularly in networks with DG units.
Renal cell carcinoma (RCC) is considered as a "metabolic disease" due to various perturbations in metabolic pathways that could drive cancer development. Glycine decarboxylase (GLDC) is a mitochondrial enzyme that takes part in the oxidation of glycine to support nucleotide biosynthesis via transfer of one-carbon units. Herein, we aimed to investigate the potential role of GLDC in RCC development. We found that GLDC depletion diminished nucleotide synthesis and promoted reactive oxygen species (ROS) generation to repress RCC progression, which was reversed by repletion of deoxynucleosides. Additionally, in vitro and in vivo studies revealed that GLDC plays an important role in regulation of proliferation and tumor growth via interferon stimulated gene factor 3 (ISGF3)-mediated pathway. Expressions of interferon regulatory factor 9 (IRF9) and signal transducer and activator of transcription 2 (STAT2) were elevated in GLDC knock-downed cells and decreased in GLDC over-expressed cells. Double knock-down of STAT2 and IRF9 in GLDC-deficient cells rescued GLDC depletion-induced decrease in cell proliferation. Furthermore, GLDC depletion increased cisplatin-and doxorubicin-induced DNA damage through ISGF3 pathway, leading to cell cycle dysregulation and increased mitotic catastrophe. These findings reveal that GLDC regulates RCC progression via ISFG3-mediated pathway and offers a promising strategy for RCC treatment.
Forests in the Eastern and Midwestern U.S. have been profoundly affected by human use over the last 150 years, with few old growth forests remaining. Such mature forests may harbor distinct communities and high biodiversity, particularly detritivores and their associated food webs. These communities, however, have been surveyed only rarely in comparisons of diversity and community composition between old and young forests. Here, we compare the mycophilous beetle communities of young and old deciduous forest stands in Southwestern Ohio (U.S.A.). We assess how the abundance and diversity of beetles associated with fungal sporocarps varies with forest age, downed woody debris, and invasive honeysuckle density. We surveyed fungus-associated beetles with baited traps at eight wooded parklands centered around Dayton, Ohio, conducting sampling three times over a growing season. In contrast to expectation, we found no clear effect of forest age on mycophilous beetle communities, but infestation by invasive honeysuckle (Lonicera maackii) negatively affected beetle abundance and diversity. Beetle abundance, richness, and community composition also strongly varied across seasonal sampling periods. Our surveys of mycophilous beetles in a Midwestern U.S. forest represent an initial step toward understanding how these communities are shaped by forest age and invasive species. Such information is crucial in managing forests to preserve biodiversity and ecosystem services.
This database provides accessible and georeferenced information on forest structure, tree-related microhabitats, and deadwood of 12 urban forests located in 12 different urban parks across three Italian cities, Florence, Rome, and Campobasso. Four urban parks - varying in size, forest type, and history - were selected following an urban-periurban gradient in each city. Inner city parks are typically ancient, with native and non-native trees planted for aesthetic and cultural purposes, and scarce semi-natural vegetation remains. Periurban parks usually host native and semi-natural vegetation and may include agricultural areas. 15 plots were placed to survey a selected urban forest located in each of the 12 urban parks, using a systematic aligned sampling scheme and then visited in the field, for a total of 180 plots. The collected data contributed to the construction of three different datasets. Two tree-level datasets present information on tree-related microhabitats and dendrometric variables including tree species, diameter at breast height, tree height, height-to-base of the live crown, tree volume, and tree basal area. The deadwood dataset presents information on five categories of deadwood, particularly snags, standing dead trees, coarse woody debris, stumps, and dead downed trees, where height, diameter, and decay status were sampled. Other research can employ these data to integrate and compare databases from different cities and forest types. Additionally, data can be linked to future analyses of urban forest fauna (e.g., beetle and bird communities) and updated to assess variability over time as well as employed in landscape analysis to guide improved management actions.
Aberrant activation/overexpression of RNF126 is implicated as a driving event in tumor progression. However, although some functions of RNF126 in prostate cancer (PCa) cell lines has been reported, more biological functions and in-depth mechanisms should be further clarified in PCa. Here, we provide evidence that RNF126 expression is elevated in human PCa tissues and cell lines, which is associated with tumor grades and prognosis. Cell proliferation was measured by the CCK8 and colony-formation assays. Cell migration was performed by Transwell and wound-healing assays. RNF126 target proteins were investigated via proteomic, co-immunoprecipitation and western blot methods. Additionally, we knock-downed MBNL1 expression to perform rescue experiments. In vivo, xenograft mice assay was used to verify the effect of RNF126 on the growth of PCa cell. Here, we showed that RNF126 was highly expressed in PCa and its higher expression was associated with worse patients' prognosis. Expression modulation of RNF126 affects PCa cells proliferation, migration, EMT and docetaxel (DTX) resistance in vitro or in vivo. Additionally, RNF126 involves in the regulation of PI3K/AKT, MEK/ERK and EMT pathways. Mechanistically, immunoprecipitation (IP) and coimmunoprecipitation (co-IP) assays indicated that RNF126 could bind to MBNL1 directly. Our data also suggested that MBNL1 was a critical downstream event in RNF126-mediated tumorigenesis and chemo-resistance and played a crucial role in driving the PI3K/AKT, MEK/ERK and EMT pathways. Taken together, our findings reveal a novel biological and molecular functions of RNF126 and may provide a new treatment option for PCa patients.
Retention harvests are promoted as an alternative to clearcuts to enhance ecological values in managed forests. Understanding how retention affects carbon (C) dynamics over time and in various forest types is important for balancing objectives like timber production and C storage. This is particularly crucial now, as the climate mitigating effects of boreal forests are weakening due to both forest harvests and natural disturbances. Using data from a relatively long-term experiment (pre-harvest to 18-years post-harvest) in previously unharvested boreal mixedwood forest, we compared C pools (mature trees, regenerating trees and shrubs, deadwood, and soil) among harvest levels (clearcuts, 10%, 20%, 50%, 75% retention, and unharvested reference). Soil C appeared to be invariant at the scale of this study, so we focused our analyses on biomass in living and dead vegetation. Total pre-harvest C storage was greater in conifer-dominated and mixed stands than in deciduous (broadleaf)-dominated stands, reflecting mainly greater biomass in live trees but also in downed deadwood. Net loss of C from the forest up to 3-years post-harvest scaled with harvest intensity in all forest types. At 3- and 18-years post-harvest in deciduous and 3-years post-harvest in conifer stands, all retention harvests resulted in larger C stocks than clearcuts; only higher retention levels provided this benefit at 3- and 18-years post-harvest in mixed (75% retention) and at 18 years in conifer stands (50%, 75% retention). In some forest types, the highest retention levels (75% for deciduous and mixed stands, 50% and 75% for conifer stands) maintained total C stocks statistically equivalent to unharvested forest at both 3- and 18-years post-harvest. Deciduous stands became net C sinks by 3-7 years post-harvest, likely due to prolific aspen regeneration and growth. Mixed and conifer stands, however, were nearly C-neutral or were C sources until 12-18 years post-harvest. This reflected persistent effects of pre-harvest forest type, including less aspen regeneration, slower growth of conifer seedlings, and mortality of retained conifers. Our results suggest that strategic retention harvesting could serve as a practical option to couple C storage options to other management considerations.
Understanding the distribution and dynamics of species is central to ecology and important for managing biodiversity. The distributions of species in metacommunities are determined by many factors, including environmental conditions and interactions between species. Yet, it is difficult to quantify the effect of species interactions on metacommunity dynamics from observational data. We present an approach to estimate the importance of species interactions that combines data from two observational presence-absence inventories (providing colonization-extinction data) with data from species interaction experiments (providing informative prior distributions in the Bayesian framework). We further illustrate the approach on wood-decay fungi that interact within a downed log through competition for resources and space, and facilitate the succession of other species by decomposing the wood. Specifically, we estimated the relative importance of species interactions by examining how the presence of a species influenced the colonization and extinction probability of other species. Temporal data on fruit body occurrence of 12 species inventoried twice were jointly analyzed with experimental data from two laboratory experiments that aimed to estimate competitive interactions. Both environmental variables and species interactions affected colonization and extinction dynamics. Late-successional fungi had more colonization interactions with predecessor species than early-successional species. We identified several species interactions, and the presence of certain species changed the probability that later-successional species colonized by -81% to 512%. The presence of certain species increased the probability that other species went extinct from a log by 14%-61%. Including the informative priors from experimental data added two colonization interactions and one extinction interaction for which the observational field data was inconclusive. However, most species had no detectable interactions, either because they did not interact or because of low species occupancy, meaning data limitation. We show how temporal presence-absence data can be combined with experimental data to identify which species influence the colonization-extinction dynamics of others. Accounting for species interactions in metacommunity models, in addition to environmental drivers, is important because interactions can have cascading effects on other species.
The elemental dynamics and interactions within deadwood profoundly influence carbon sequestration and nutrient cycling in forest ecosystems. Recent studies have investigated macronutrient cycling during deadwood decay of specific plants, yet the dynamics and interactions of micronutrients, trace elements, and the elementome across species and decay stages remain unexplored. Here, we investigated the elementome and their coupling relationships across five decay stages of downed deadwood (DDW) from four dominant species (Hippophae rhamnoides, Populus purdomii, Abies fabri, and Picea brachytyla) along the Hailuogou Glacier primary successional chronosequence. Element coupling was evaluated following the framework of mean correlation of all elements in absolute value and null modeling. We observed species-specific elementome differentiation during DDW decay, with interspecific distances greater in the initial and later decay stages and lower in the intermediate stage. Notably, shrub H. rhamnoides exhibited distinct initial elementomes and remained robust multi-element coupling throughout decay. Conversely, element couplings for tree species declined with decay, particularly for P. purdomii and A. fabri, reaching decoupling from Stage III. Non-essential elements of Al, V, and Ti remained robust coupling, while key nutrients of N, P, and Ca decoupled as decay progressed. The individual element coupling was negatively correlated with their enrichment levels, with lower coupling observed for anthropogenically enriched metals. Our results reveal the importance of plant species in elementome differentiation and element coupling during deadwood decay, while atmospheric heavy metal deposition mediates individual element coupling, underscoring species-specific deadwood management strategies and monitoring of heavy metal deposition to optimize forest ecosystem functions and stability.
Recent studies have showed that 5-methylcytosine (m5C) can be utilized to assess the prognosis of tumors. However, the role of clinical implications of m5C modification remains unclear. The mRNA expression profiles and clinical features were downed from GEO and ICGC databases.In order to screen out m5C regulators,Univariate and multivariate Cox regression were performed. The survival rate was determined using K-M survival analysis. Then the risk model was validated in ICGC and GSE63156 two external datasets. A nomogram was created using risk level and clinical features, well validated by calibration curve. ESTIMATE, MCP-counter and GSVA algorithms were applied to assess tumor microenvironment, immune cell, and immune function. Several drugs exhibited sensitivity for potential therapy of ES. Five m5C regulators (YBX1, TET2, NOP2, DNMT3A, DNMT1) were screened out as risk signatures. The Kaplan-Meier survival analysis demonstrated that the high-risk group had a lower survival rate compared to the low-risk group(p = 0.0026). The AUC of ROC curves in 1, 3, 5 years ranged from 0.752 to 0.829. Based on the amount of risk and clinical characteristics, a nomogram was created and well validated by calibration curve.ESTIMATE, MCP-counter and GSVA algorithms were applied to assess tumor mircoenvironment, immune cell, and immune function. Several drugs exhibited sensitivity for potential therapy of ES. The present research indicated that m5C regulators (YBX1, TET2, NOP2, DNMT3A, DNMT1) play critical roles in ES progression, and provide new insight in ES prognosis prediction.
Downer cow syndrome, or secondary recumbency, is a condition primarily affecting dairy cows, where the animal is unable to rise and stand, due to unknown cause. It is usually associated with poor prognosis. Terminal downers are euthanized in most countries. A four-year old Kasarkode dwarf-cow, post-calving was brought up laterally recumbent with heavy nasal discharge, labored breathing, loss of appetite and signs of dehydration on 6th day of its recumbency. Before this, the patient was diagnosed with milk fever and standard treatment with calcium borogluconate was administered intravenously. The animal was left to succumb under unprotected conditions, due to various constraints on euthanasia. After adopting the cow, Nasya was started immediately to avoid death due to sepsis and shock. The animal was drenched with Ayurvedic fluids containing deepana-pacana herbs. Sternal recumbency, warm and moistened muzzle was observed on the fourth day of commencing ayurvedic treatment. Respiratory distress was minimal. Drastic prognostic shift from "no hope" to "good" was possible within 6 days thanks to Nasya, and the animal was stable. Thereafter, integrative care comprising of antibiotics, rehydrating IV fluids, and supplementations, along with ayurvedic medicines was initiated. Ruminal-fluid obtained from slaughterhouse was used for ruminal-flora replacement. Rumination on 14th day, cow on its feet by 19th day and complete healing of decubital ulcers by approximately 40 days was recorded. A downed cow which did not respond to standard veterinary care was managed with Ayurveda-integrated veterinary care. Ayurveda herbs like bamboo leaves (Bambusa vulgaris), green chiretta (Andrographis paniculata) that cattle prefer eating during certain illness, turn out to be useful for Ayurvedic management. Hence, Ayurveda veterinary medicine might be, a good choice for integrative management of terminal downers, preventing early death in downed dairy cows.
Nature-based climate solutions (NCS) are championed as a primary tool to mitigate climate change, especially in forested regions capable of storing and sequestering vast amounts of carbon. New England is one of the most heavily forested regions in the United States (>75% forested by land area), and forest carbon is a significant component of climate mitigation policies. Large infrequent disturbances, such as hurricanes, are a major source of uncertainty and risk for policies relying on forest carbon for climate mitigation, especially as climate change is projected to alter the intensity and extent of hurricanes. To date, most research into disturbance impacts on forest carbon stocks has focused on fire. Here, we show that a single hurricane in the region can down between 121 and 250 MMTCO2e or 4.6%-9.4% of the total aboveground forest carbon, much greater than the carbon sequestered annually by New England's forests (16 MMTCO2e year-1). However, emissions from hurricanes are not instantaneous; it takes approximately 19 years for downed carbon to become a net emission and 100 years for 90% of the downed carbon to be emitted. Reconstructing hurricanes with the HURRECON and EXPOS models across a range of historical and projected wind speeds, we find that an 8% and 16% increase in hurricane wind speeds leads to a 10.7- and 24.8-fold increase in the extent of high-severity damaged areas (widespread tree mortality). Increased wind speed also leads to unprecedented geographical shifts in damage, both inland and northward, into heavily forested regions traditionally less affected by hurricanes. Given that a single hurricane can emit the equivalent of 10+ years of carbon sequestered by forests in New England, the status of these forests as a durable carbon sink is uncertain. Understanding the risks to forest carbon stocks from disturbances is necessary for decision-makers relying on forests as a NCS.