Global Reduction Research Articles

Low-carbon oriented planning of shared photovoltaics and energy storage systems in distribution networks via carbon emission flow tracing

With the targets of carbon peaking and carbon neutrality, carbon emission reduction measures have become significant issues in new-type power systems. Distribution networks (DNs), which multiple power sources and flexible loads access to, play an essential role in exploiting the potential of reducing carbon emissions on the demand side. To achieve a global carbon emission reduction considering the carbon quota of each customer, shared photovoltaics (PVs) and energy storage systems (ESSs) are allocated with a centralized calculation and optimization conducted by DNs. To solve two key points in demand-side planning of shared PVs and ESSs in distribution networks, i.e., the accuracy of carbon emission flow (CEF) calculation and carbon quota-oriented optimization planning, this paper proposes a low-carbon oriented planning method for shared PVs and ESSs via CEF tracing. Firstly, a novel CEF calculation method is proposed based on the forward current sweep and backward voltage sweep algorithm, which considers the tracing of reactive power and power losses. Next, carbon emission index and economic index of allocating shared PVs and ESSs are defined. Subsequently, a bi-level optimization model is presented, considering the excess carbon emissions of each load based on carbon accounting and carbon quotas. Finally, the superiority of the proposed method is verified through a modified IEEE 33-node distribution network, and the effects of various investment constraints and carbon quotas are discussed.

First-Come-First-Served as a Separate Principle

A lock is a mechanism to guarantee mutual exclusion with eventual progress, i.e., some degree of fairness. First-come-first-served (FCFS) progress is perfectly fair. FCFS progress can be offered by a locking algorithm or added by wrapping a non-FCFS lock with a separate FCFS algorithm. A new separate FCFS algorithm is presented that creates FCFS progress by wrapping a lock’s entry protocol (acquire). The algorithm addresses an important safety issue in locking, called barging, where arriving threads proceed before waiting threads or waiting threads are serviced with some bias. Barging increases latency for waiting threads and is non-intuitive to concurrent programmers, even though it is inherent to non-deterministic concurrent execution. A correctness proof is presented for the new FCFS algorithm and verified with the proof assistant PVS. Experimental tests are performed to ensure the presented wrapper provides FCFS progress when used to transform non-FCFS software and hardware locks. The performance of the non-FCFS and transformed FCFS counterparts is compared, and contrasted with locks using inherent FCFS progress. The results show the FCFS transforms are performant for most algorithms, providing an additional tool for application developers to achieve correctness without a significant global performance reduction.

In-Person and Teleconsultation Services at a National Hospital in Peru: Time Series Analysis of General and Psychiatric Care Amid the COVID-19 Pandemic.

The COVID-19 pandemic led to a global reduction in health care accessibility for both infected and noninfected patients, posing a particular burden on those with chronic conditions, including mental health issues. Peru experienced significant devastation from the pandemic, resulting in a collapsed health care system and leading to the world's highest per capita mortality rate as a result of COVID-19. Understanding the trends in health care utilization, particularly in mental health care, is crucial for informing pandemic response efforts and guiding future recovery strategies. This study aims to analyze the trends of outpatient medical and psychiatric consultations during the COVID-19 pandemic in a national hospital in Peru. This observational study was conducted at a national hospital in Lima, Peru. We analyzed data on user care across all services, including psychiatric services, from May 2019 to December 2022. The data were calculated for users served per month, including the number of users seen monthly in mental health services. Sociodemographic variables such as sex (female or male), age (≥0 years), type of medical appointment (regular or additional), and modality of care (in-person or teleconsultations) were taken into account. An interrupted time series regression model was conducted to assess the number of outpatient medical and psychiatric consultations. Subgroup analyses were performed based on service modality, including overall consultations, telemonitoring/teleconsultations only, or face-to-face only, for all service users and for mental health service users. A total of 1,515,439 participants were included, with females comprising 275,444/484,994 (56.80%) of the samples. Only 345,605/1,515,439 (22.81%) visits involved telemedicine. The total monthly outpatient visits were significantly reduced compared with the expected projection (P<.001) at the beginning of the pandemic, followed by a later monthly increment of 298.7 users. Face-to-face interventions experienced a significant reduction at the beginning of the pandemic (P<.001), gradually recovering in the following months. By contrast, telemedicine use initially increased but subsequently declined toward the end of the pandemic. A similar trend was observed in mental health units. During the pandemic years, health care utilization in both general and psychiatric services experienced a significant decrease, particularly at the beginning of the pandemic (March 2020). However, no significant trends were observed in either case throughout the pandemic period. Telemedicine consultations witnessed a significant increase overall during this period, particularly among mental health users.

Genetically-Based Active Flow Control And PIV Measurements Of A Circular Cylinder Wake

In the field of flow manipulation, considerable attention is devoted to controlling the wake of bluff bodies, which are characterized by the phenomenon of vortex shedding. Specifically, the control of the wake behind a single circular cylinder has garnered substantial research interest due to its engineering applications, such as reducing aerodynamic drag in the automotive and aerospace industries. Therefore, in the current work, through the application of the planar PIV technique, the fluid dynamic behavior of a circular cylinder wake controlled via synthetic jets (SJ) and Machine Learning (ML) methods is analyzed and discussed. ML algorithms are used to determine the optimal voltage signal for the loudspeaker, which effectively minimizes the aerodynamic drag of the cylinder. This approach overcomes the limitations associated with the a priori assumption of a parametric waveshape. In particular, the gradient-enriched machine learning control (gMLC) algorithm is chosen as optimization tool to search the best open-loop control policy for aerodynamic drag reduction. The cost function for this problem has been defined considering both the drag reduction contribution and the electrical power spent for the actuation. Initial optimization tests are performed by minimizing a cost function considering only the reduction in aerodynamic drag. Subsequently, a term related to the electrical power consumption for actuation is incorporated into the cost function. Once obtained the optimal control policies for these cases (hereinafter renamed CC1 and CC2, respectively), the physical mechanism responsible for reducing the aerodynamic drag is investigated more closely by analyzing the effect of the control laws on the turbulent flow statistics. Figure 1 reports a comparative assessment of the CC1 and CC2 with the baseline configuration and the configuration controlled by a sinusoidal law (CCS). The baseline configuration is characterized by an extended region of localized turbulent fluctuations in the far wake, where the time-averaged signature of von Kármán vortices is found. In contrast, all the controlled configurations show a global reduction in wake turbulence, with a peak of turbulent energy at the rear stagnation point due to the momentum injection from the SJ actuator. Notably, the CCS and CC2 configurations share similar flow field morphologies, while the CC1 configuration shows a greater reduction in turbulent fluctuations compared to the other controlled cases. This control law also achieves the largest drag reduction among all configurations studied reporting a 9.7% of drag reduction, compared to CCS and CC2, which exhibit similar reductions of 8.4% and 8.5%, respectively. Therefore, the optimization procedure has proven the capability of finding control policies able to outperform the traditional sinusoidal control widely studied in literature.

Microglia depletion leads to increased susceptibility to ocular hypertension-dependent glaucoma.

In recent years, microglia have been highlighted for playing integral roles in neurodegenerative diseases, like glaucoma. To better understand the role of microglia during chronic ocular hypertension, we depleted microglia from aged (9-12 months old) DBA/2 J (D2) mice, which exhibit age-related increases in intraocular pressure, using a dietary CSF1R antagonist, PLX5622. Retinal ganglion cell (RGC) somas were counted, and optic nerve cross-sections stained and assessed for glaucomatous damage. Sustained administration of dietary PLX5622 significantly reduced the numbers of retinal microglia. Dietary PLX5622 did not lead to changes in intraocular pressure in D2 or normotensive DBA/2 J-Gpnmb+ (D2-Gpnmb+ ) control mice. While PLX5622-treated D2-Gpnmb+ did not develop optic nerve damage, PLX5622-treated D2 mice showed a significant increase in moderate-to-severe optic nerve damage compared to D2 mice fed a control diet. In conclusion, global reduction of microglia exacerbated glaucomatous neurodegeneration in D2 mice suggesting microglia play an overall beneficial role in protecting from ocular hypertension associated RGC loss.

Molecular basis of neurodegeneration in a mouse model of Polr3-related disease.

Pathogenic variants in subunits of RNA polymerase (Pol) III cause a spectrum of Polr3-related neurodegenerative diseases including 4H leukodystrophy. Disease onset occurs from infancy to early adulthood and is associated with a variable range and severity of neurological and non-neurological features. The molecular basis of Polr3-related disease pathogenesis is unknown. We developed a postnatal whole-body mouse model expressing pathogenic Polr3a mutations to examine the molecular mechanisms by which reduced Pol III transcription results primarily in central nervous system phenotypes. Polr3a mutant mice exhibit behavioral deficits, cerebral pathology and exocrine pancreatic atrophy. Transcriptome and immunohistochemistry analyses of cerebra during disease progression show a reduction in most Pol III transcripts, induction of innate immune and integrated stress responses and cell type-specific gene expression changes reflecting neuron and oligodendrocyte loss and microglial activation. Earlier in the disease when integrated stress and innate immune responses are minimally induced, mature tRNA sequencing revealed a global reduction in tRNA levels and an altered tRNA profile but no changes in other Pol III transcripts. Thus, changes in the size and/or composition of the tRNA pool have a causal role in disease initiation. Our findings reveal different tissue- and brain region-specific sensitivities to a defect in Pol III transcription.

Visual analysis of changes in European air transport during the COVID-19 pandemic from interactive maps

Abstract The paper explores the substantial decline in European air transport during 2020, while employing interactive maps for visual analysis. According to the International Civil Aviation Organization’s (2020) economic analysis, there was a sharp 60% global reduction in passenger traffic during the combined second, third, and fourth quarters, equivalent to about 2.7 billion fewer passengers than in 2019. The established air traffic flow, which developed over decades, faced partial disruption due to COVID-19 restrictions. Consequently, the aviation industry strategically focused on restructuring to ensure the sustained operation of major air transport routes. Using OpenSky Network data and a Google Sheets environment for storage, our study utilizes the FlowmapBlue interactive platform to visualize the 2020 European airspace, and to define key air traffic corridors. Despite the substantial decline, the visualization reveals resilient routes and crucial connections, underscoring the imperative of preserving these links for effective crisis response in the future.

Evaluating Climate Change Mitigation Strategies of G20 Countries: Policies, Actions, and Progress Towards Global Emission Reduction Goals

The G20 countries are responsible for over 75% of the greenhouse gas (GHG) emissions at a global level. The research summarises the role of G20 countries in combating Climate Change. This research study explores the comprehensive assessment of the G20 nations’ policies and the impacts of climate change across the globe. The paper studies the policies of the G20 countries’ governments to meet the Nationally Determined Contribution (NDC) target and achieve the global goal of the Paris Agreement (or COP28) and Net Zero Emissions Target of limiting the level of global temperature increase to well below 2 degrees C while pursuing efforts aligning to a global threshold objective of 1.5-degree C. Through the review of existing literature, the researchers aim to provide a better understanding of climate change and the biodiversity and ecosystem. In addition to this, the study provides various strengths and opportunities for the countries to explore soon, reducing the emission levels in the ecosystem and thus, promoting a sustainable future, through an interlinked phenomenon.

How Volcanic Aerosols Globally Inhibit Precipitation

AbstractVolcanic aerosols reduce global mean precipitation in the years after major eruptions, yet the mechanisms that produce this response have not been rigorously identified. Volcanic aerosols alter the atmosphere's energy balance, with precipitation changes being one pathway by which the atmosphere acts to return toward equilibrium. By examining the atmosphere's energy budget in climate model simulations using radiative kernels, we explain the global precipitation reduction as largely a consequence of Earth's surface cooling in response to volcanic aerosols reflecting incoming sunlight. These aerosols also directly add energy to the atmosphere by absorbing outgoing longwave radiation, which is a major cause of precipitation decline in the first post‐eruption year. We additionally identify factors limiting the post‐eruption precipitation decline, and provide evidence that our results are robust across climate models.

The roots of carbon emission differences between China and USA: A quantitative study based on global value chains

China and the USA, as preeminent contributors to global carbon emissions, demonstrate discernible differentials in both magnitude and trajectories of their respective carbon outputs. This article employed two methods, Structural Decomposition Analysis (SDA) and Quantitative Structural Modeling, to scrutinize the underpinnings of these disparities through the lens of the global value chain. Drawing upon data from the World Input-Output Database (WIOD), our analysis revealed that the compounded influences of output composition, input intensity, input composition and input origin collectively elevated China's aggregate carbon footprint from 2000 to 2014, while the scale effect made China's carbon emissions lower than of the USA. Notably, China's carbon emissions surpassed those of USA, with the gap accentuating over time. The quantitative results of the structural model showed that the difference in carbon emissions between China and USA predominantly stem from disparities in productivity, production technology, factor intensity, factor endowment and direct carbon intensity. Differences in trade costs exhibited some discernible impact, their influence remains relatively marginal, whereas distinctions in consumption behaviors and trade imbalances minimally contribute to the observed differentials. These findings have important policy implications for global carbon reduction efforts and China's trajectory towards a low-carbon economic paradigm.

Mechanisms of well iron clogging in groundwater heat pump systems: Insights from video imaging, hydrogeochemical analysis, and geochemical modeling

Groundwater heat pump (GWHP) systems are increasingly popular as low-carbon and environmentally friendly technologies, but well clogging induced by iron remains a significant issue. This study investigated the clogging characteristics and biogeochemistry of three typical wells (pumping, injection, and observation wells) in an operating GWHP system using video imaging, sampling, and analysis of hydrogeochemical and microbial data. The results revealed that iron-induced well clogging is a complex process involving physical, chemical, and microbial factors. Pumping wells experience clogging due to water mixing with varying redox conditions, resulting in hematite-based iron oxide deposits. Injection wells exhibit higher clogging severity, with transformed oxidation and accumulation of reduced iron minerals at the solid-liquid interface, resulting in darker colored clogs with magnetite. Clogging in both extraction and injection wells is closely related to iron-rich aquifer sections, where severe clogging occurs. Shallow clogging due to iron oxide is limited and attributed to the oxidation of zero-valent iron in well casing material. Iron-oxidizing bacteria and iron-reducing bacteria were detected in the consolidated deposits of clogged wells, indicating their involvement in the clogging formation process. Moreover, a strong correlation was observed between the presence of nitrate-reducing bacteria in the water phase and the severity of clogging, suggesting a possible link between iron oxidation and nitrate reduction in the system. Geochemical modeling results further supported the observed clogging severity in GWHP systems and confirmed varying clogging mechanisms in different wells and depths. These findings contribute to the understanding of clogging in GWHP operations, aiding in robust water utilization and energy-saving efforts, and supporting global carbon reduction initiatives.

Nailfold capillary measurements correlated to NOTCH3 R544C mutation in preclinical CADASIL patients

BackgroundCerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is a hereditary disease caused by NOTCH3 mutation. Nailfold capillaroscopy is a non-invasive technique typically used for rheumatic diseases. It has potential in other conditions linked to vascular pathology. However, capillaroscopy in CADASIL has not been explored. This study aims to investigate whether capillaroscopy measurements can correlate with brain vascular changes in preclinical CADASIL patients, specifically those with NOTCH3 mutation. MethodsThis study included 69 participants from the Taiwan Precision Medicine Initiative (TPMI) dataset who visited Taichung Veterans General Hospital from January to December 2022. All individuals underwent genetic studies, brain imaging and nailfold capillaroscopy. The Mann-Whitney U test was used to compare results of brain imaging between carriers and controls. It was also used to compare measurements in nailfold capillaroscopy within each group. Spearman Rank Correlation Analysis was used to explore the relationship between capillary measurements and brain MRI results. ResultsWhite matter hyperintensities (WMH) expression was positively correlated with capillary dimension and negatively correlated with density. Our results presented that R544C carriers exhibited a diffuse increase in WMH (p < 0.001) and a global reduction in gray matter volume but preserved in specific areas. The white matter lesion scores in all brain regions were higher in the mutation carriers than the controls. (p < 0.001). ConclusionThis research highlights the association of nailfold capillaroscopy findings with white matter lesions in preclinical CADASIL patients. Capillaroscopy guides an effective screening strategy in individuals with NOTCH3 mutations.

Strain dynamics of contaminating bacteria modulate the yield of ethanol biorefineries

Bioethanol is a sustainable energy alternative and can contribute to global greenhouse-gas emission reductions by over 60%. Its industrial production faces various bottlenecks, including sub-optimal efficiency resulting from bacteria. Broad-spectrum removal of these contaminants results in negligible gains, suggesting that the process is shaped by ecological interactions within the microbial community. Here, we survey the microbiome across all process steps at two biorefineries, over three timepoints in a production season. Leveraging shotgun metagenomics and cultivation-based approaches, we identify beneficial bacteria and find improved outcome when yeast-to-bacteria ratios increase during fermentation. We provide a microbial gene catalogue which reveals bacteria-specific pathways associated with performance. We also show that Limosilactobacillus fermentum overgrowth lowers production, with one strain reducing yield by ~5% in laboratory fermentations, potentially due to its metabolite profile. Temperature is found to be a major driver for strain-level dynamics. Improved microbial management strategies could unlock environmental and economic gains in this US $ 60 billion industry enabling its wider adoption.

Heterogeneous technology-induced global CO2 emission reduction and emission forecasting since the Kyoto era

While identifying the drivers of global CO2 emission is crucial for climate change mitigation, the heterogeneous technology-related drivers (e.g., technological change and efficiency of energy and CO2 emission) were ignored to a large extent at a global scale, hindering to formulate heterogenous climate policies. Moreover, the projection of CO2 emission was also not well compared for countries. Here, the study investigated the heterogeneous technology-related drivers of CO2 emissions in time and space simultaneously in 42 major emitter countries over 1998–2020 by extending the spatiotemporal production-theoretical decomposition models, and compared the different performances for forecasting CO2 emission by traditional time-series models and several machine learning models. Key findings as follows: first, drivers of CO2 emissions exhibit significant heterogeneity across countries where the effects of energy usage technology gap and CO2 emission technology gap were negative drivers for USA, South Korea, and the Czech Republic and potential energy intensity effect was the negative driver in countries like China, Russia, Japan, and India. Second, the effects of within-GDP per capita and within- population size were the important drivers affecting global CO2 emission difference. Third, general regression neural network achieved the best forecasting performance on average compared with other models in the study. The study highlights the importance of formulating climate policies based on heterogeneous technology and emission forecast modeling.

Global brain connectivity: Test-retest stability and association with biological and neurocognitive variables

BackgroundGlobal brain connectivity (GBC) enables measuring brain regions’ functional connectivity strength at rest by computing the average correlation between each brain voxel’s time-series and that of all other voxels. New methodWe used resting-state fMRI (rs-fMRI) data of young adult participants from the Human Connectome Project (HCP) dataset to explore the test-retest stability of GBC, the brain regions with higher or lower GBC, as well as the associations of this measure with age, sex, and fluid intelligence. GBC was computed by considering separately the positive and negative correlation coefficients (positive GBC and negative GBC). ResultsTest-retest stability was higher for positive compared to negative GBC. Areas with higher GBC were located in the default mode network, insula, and visual areas, while regions with lower GBC were in subcortical regions, temporal cortex, and cerebellum. Higher age was related to global reduction of positive GBC. Males displayed higher positive GBC in the whole brain. Fluid intelligence was associated to increased positive GBC in fronto-parietal, occipital and temporal regions. Comparison with Existing MethodCompared to previous works, this study adopted a larger sample size and tested GBC stability using data from different rs-fMRI sessions. Moreover, these associations were examined by testing positive and negative GBC separately. ConclusionsLower stability for negative compared to positive GBC suggests that negative correlations may reflect less stable couplings between brain regions. Our findings indicate a greater importance of positive compared to negative GBC for the associations of functional connectivity strength with biological and neurocognitive variables.

Change in water column total chlorophyll-a in the Mediterranean revealed by satellite observation

Chlorophyll-a (Chl-a) is a crucial pigment in algae and macrophytes, which makes the concentration of total Chl-a in the water column (total Chl-a) an essential indicator for estimating the primary productivity and carbon cycle of the ocean. Integrating the Chl-a concentration at different depths (Chl-a profile) is an important way to obtain the total Chl-a. However, due to limited cost and technology, it is difficult to measure Chl-a profiles directly in a spatially continuous and high-resolution way. In this study, we proposed an integrated strategy model that combines three different machine learning methods (PSO-BP, random forest and gradient boosting) to predict the Chl-a profile in the Mediterranean by using several sea surface variables (photosynthetically active radiation, spectral irradiance, sea surface temperature, wind speed, euphotic depth and KD490) and subsurface variables (mixed layer depth) observed by or estimated from satellite and BGC-Argo float observations. After accuracy estimation, the integrated model was utilized to generate the time series total Chl-a in the Mediterranean from 2003 to 2021. By analysing the time series results, it was found that seasonal fluctuation contributed the most to the variation in total Chl-a. In addition, there was an overall decreasing trend in the Mediterranean phytoplankton biomass, with the total Chl- decreasing at a rate of 0.048 mg/m2 per year, which was inferred to be related to global warming and precipitation reduction based on comprehensive analysis with sea surface temperature and precipitation data.

Life cycle costing analysis of a retrofitted hydrogen-powered locomotive: Canadian context

The transportation sector must adopt cleaner alternatives to meet global emission reduction goals and attain net-zero emissions by 2050. Hydrogen stands out as a promising solution for decarbonizing the railway sector. This study conducts an economic assessment of hydrogen locomotives, considering their entire life cycle. Life cycle costs are analyzed across various travel scenarios and life stages. For shorter distances, the operational phase and capital costs of retrofitting components contribute 64% and 21% to the total life cycle costs, respectively. In contrast, longer distances are dominated by the operational phase, representing nearly 90% of the total costs. Clean hydrogen must reduce costs to compete with diesel locomotives, as only non-sustainable hydrogen currently matches diesel operational expenses. Anticipated advancements in hydrogen technology are expected to make clean hydrogen more accessible, leading to a significant reduction in the life cycle costs of hydrogen locomotives.

EPEN-11. CHARACTERIZING EPIGENETIC MODULATIONS AND EZHIP DOWNSTREAM TARGETS IN PFA EPENDYMOMA

Abstract BACKGROUND Ependymomas can arise from all compartments of the central nervous system and ten distinct molecular groups have been identified in children and adults. In children, the most aggressive group is posterior fossa group A ependymoma (PFA). In PFA ependymomas, the aberrant overexpression of EZHIP (EZH inhibitory protein) has been implicated as a relevant driver of the disease. EZHIP suppresses the installing and spreading of the repressive epigenetic mark H3K27me3 via disturbing PRC2 (polycomb repressive complex 2) activity through inhibiting EZH2 (enhancer of zeste 2), which causes overall low levels of H3K27me3 in PFA. METHODS To get a better understanding how EZHIP may drive the disease, how it affects the epigenetic landscape and what the downstream targets of EZHIP are, we performed DNA sequencing, RNA expression profiling and ChIP-seq experiments of H3K27me3, H3K27ac, EZH2, and EZHIP in PFA, PFB, and ST-ZFTA ependymomas (n = 3 tumor cases each). RESULTS After validating the high levels of EZHIP and global reduction of H3K27me3 in PFA, we characterized the epigenetic landscape and EZHIP chromatin binding characteristics in PFA compared to PFB and ST-ZFTA ependymoma. Transcriptome analysis showed that overall more genes are up-regulated in PFA compared with PFB and ZFTA, which might be caused by its relatively high accessibility with a global loss of H3K27me3. EZHIP knockdown experiments confirmed direct changes on H3K27me3, H3K27ac and gene expression. We also found that PLAG1 (pleomorphic adenoma gene 1) expression linearly correlated with EZHIP expression in PFA tumors. ChIP-seq data indeed showed the PLAG1 locus to be bound by EZHIP and marked with increased H3K27ac and decreased H3K27me3 signals in PFA. CONCLUSIONS We identified PLAG1 as a potential downstream target of EZHIP in PFA tumors. Currently, more experiments on PLAG1 are being performed to further explore its role as a potential vulnerability in PFA ependymoma.

EPEN-26. DRUG SCREENING IN PATIENT-DERIVED MODELS OF POSTERIOR FOSSA A EPENDYMOMA REVEALS NOVEL PHARMACOLOGICAL VULNERABILITIES

Abstract Ependymoma (EPN) is the third most common malignant intracranial pediatric brain tumor. The most common and aggressive EPN subgroup, posterior fossa ependymoma group A (PFA-EPN), occurs predominantly in younger children and has a 5-year progression free survival of only 33%. Despite progress in the molecular characterization and subtyping of EPN, the standard treatment remains surgery with adjuvant radiation therapy. There is currently no approved role for chemotherapy in PFA-EPN. As such, identifying novel therapies for PFA-EPN is an important unmet medical need. To define therapeutic sensitivities for PFA-EPN, we performed a drug screen on three patient-derived PFA-EPN cell lines. We found that PFA-EPN cell lines were sensitive to several clinically relevant drugs, most notably those targeting epigenetic regulators. This is of a particular interest as a common molecular feature of PFA-EPN is the global reduction of the repressive post-translational histone modification H3K27me3 due to transcriptional EZHIP overexpression or H3 K27M mutations. To further characterize our PFA-EPN cell lines, we performed optical genome mapping analysis, revealing previously undescribed structural variants affecting genes encoding proteins responsible for signaling and transcription. One PFA-EPN sample that showed profound sensitivity to EGFR inhibitors, also had a duplication of a genomic region containing the EGFR ligand encoding genes, AREG, BTC, EREG, and EPGN. We are currently working to validate these results in larger cohorts of PFA-EPN models. Collectively, these findings provide new clues on drugs, signaling and putative therapeutic targets in these rare yet aggressive tumors.

Assessing the impact of rural E-commerce on regional poverty alleviation: A spatial spillover analysis

China's innovative and sustainable e-commerce poverty alleviation model has not only generated significant social and economic value but also serves as an effective practical case for global poverty reduction. This study employed 611 counties in contiguous poverty-affected areas in China from 2011 to 2022 as valid research samples. It adopted the Spatial Autoregression Model, Spatial Error Model, and Spatial Durbin Model to examine the impact of rural e-commerce on the quality of poverty alleviation, spatial spillover effects, and regional heterogeneity in contiguous poverty-affected areas. The results indicate that rural e-commerce improves the quality of poverty alleviation in local regions and has a spatial spillover effect on the quality of poverty alleviation in adjacent regions. Moreover, significant regional heterogeneity exists in the direct promotion and spatial spillover effects of rural e-commerce on the quality of poverty alleviation in contiguously poor areas. Specifically, in the impoverished areas of eastern, central, and northeastern China, rural e-commerce not only enhances the quality of poverty alleviation in the local region but also has a positive spillover effect on the poverty alleviation quality of neighboring regions. The findings of this study provide valuable insights for rural e-commerce to consolidate the achievements of poverty alleviation and align them with rural revitalization efforts.