Activity In Region Research Articles

Abstract LB422: Specific activation of the Epstein-Barr Virus BGLF4 locus via lowered DNA methylation in EBV-associated CNS lymphoproliferative disease

Abstract Introduction: Epstein-Barr virus positive (EBV+) central nervous system lymphoproliferative diseases (CNS-LPD) are aggressive clinical conditions with poor prognosis. We have previously reported use of a ganciclovir (GCV), zidovudine (AZT), rituximab and dexamethasone regimen (GARD) that induced complete and durable responses in patients with primary CNS post-transplant lymphoproliferative disease (PTLD). Responses were associated with detection of two GCV/AZT viral drug targets, the EBV protein kinases BGLF4 and BXLF1. These viral proteins are normally expressed in lytic phase EBV, and the molecular basis for expression in latently infected EBV+ CNS-LPD is unknown. Methods: RNA expression of EBV genes LMP1, BZLF1, BXLF1, and BGLF4 was measured in 12 CNS-LPD biopsies (n=8/12 DLBCL-type) via qRT-PCR. Mass spectrometry-based EpiTYPER assay was used to quantify DNA methylation in EBV gene promoters. Biopsies from 25 patients with systemic PTLD were used for comparison. The BGLF4 locus was investigated in detail using luciferase reporters and 5’RACE mapping of transcription start sites in 3 EBV-infected cell lines and 4 CNS-LPD biopsy samples. Overall EBV methylation was assessed in a screening assay covering 31 EBV loci. Mechanistic involvement of active demethylation via TET2 was studied in a HEK293 CRISPR-Cas9 gene knockout model under EBV (strain M81) infection. Results: Gene expression analysis of biopsy specimens showed expression of LMP1, BXLF1, and BGLF4, but not BZLF1. Expression of BXLF1 and BGLF4 was significantly higher in CNS-LPD when compared to systemic EBV+ PTLD (p=0.043 and p=0.00022, respectively). EpiTYPER data showed significantly decreased promoter methylation at BGLF4 (p=0.00013). Luciferase reporter analysis of the BGLF4 upstream sequence revealed 3 regions of promoter activity which were silenced by in vitro methylation of reporters. 5’RACE identified transcription start sites at all 3 BGLF4 promoters and detected their activity in EBV+ cell lines and CNS-LPD biopsies. By overlaying transcriptional activity, 5’RACE and DNA methylation data, we identified DNA methylation loss at single CpG dinucleotides correlated with BGLF4 expression (r2=0.73). These sites were specifically demethylated in CNS-LPD, while surrounding EBV methylation remained high. Knockout of TET2 followed by EBV infection revealed that active demethylation is required for demethylation at BGLF4 promoters. Conclusions: The molecular determinant for success of the GARD regimen in CNS-LPD has remained poorly understood, with immunohistochemical detection of BGLF4/BXLF1 as the only predictor of treatment response. Our results provide the molecular basis for expression of BGLF4 in CNS-LPD by showing decreased promotor DNA methylation. We identified specific BGLF4 methylation sites that hold promise as potential DNA biomarkers for EBV+ CNS-LPD. Citation Format: Christoph Weigel, Haley L. Klimaszewski, Selamawit Addissie, Sarah Schlotter, Fode Tounkara, James P. Dugan, Bradley M. Haverkos, Lynda Villagomez, Mark Lustberg, Pierluigi Porcu, Timothy Voorhees, Michael A. Caligiuri, Ginny Bumgardner, Christopher C. Oakes, Robert Baiocchi. Specific activation of the Epstein-Barr Virus BGLF4 locus via lowered DNA methylation in EBV-associated CNS lymphoproliferative disease [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB422.

Multi-parameters monitoring of geological disasters around the Taihang Mountains-Yanshan area, Hebei Province

The Hebei Taihang Mountains-Yanshan region marks North China’s natural boundary between plains and plateaus. The unique geological and geographical conditions have led to a hazardous environment with frequent geological events. Hence, conducting a comparative analysis of regional geological hazard drivers is necessary. A geological hazard driver analysis model using multiparameter preferential Geodetectors was developed, focusing on the Taihang Mountains-Yanshan region in Hebei. It was divided into zones: Taihang Mountains, Yanshan Mountains and Dam Plateau. The results showed significant differences in the explanatory power of geohazard drivers in various zones, varying with the softening of the natural geological environment and increased human activities. In the Taihang Mountains, the primary geohazard factor is average annual rainfall, whereas in the Yanshan Mountains, it is average annual rainfall and geomorphology. Interactions among factors reveal that annual average rainfall holds the highest explanatory power for geological hazard spatial differences, notably interacting with geomorphological, geological and human activity regions, yielding an escalating effect. The study findings can be crucial references for disaster prevention, mitigation, national land resource development, economic planning and the ‘six belts’ construction in Beijing, Tianjin and Hebei.

Gray matter volume associations in youth with ADHD features of inattention and hyperactivity/impulsivity.

Prior research has shown smaller cortical and subcortical gray matter volumes among individuals with attention-deficit/hyperactivity disorder (ADHD). However, neuroimaging studies often do not differentiate between inattention and hyperactivity/impulsivity, which are distinct core features of ADHD. The present study uses an approach to disentangle overlapping variance to examine the neurostructural heterogeneity of inattention and hyperactivity/impulsivity dimensions. We analyzed data from 10,692 9- to 10-year-old children from the Adolescent Brain Cognitive Development (ABCD) Study. Confirmatory factor analysis was used to derive factors representing inattentive and hyperactive/impulsive traits. We employed structural equation modeling to examine these factors' associations with gray matter volume while controlling for the shared variance between factors. Greater endorsement of inattentive traits was associated with smaller bilateral caudal anterior cingulate and left parahippocampal volumes. Greater endorsement of hyperactivity/impulsivity traits was associated with smaller bilateral caudate and left parahippocampal volumes. The results were similar when accounting for socioeconomic status, medication, and in-scanner motion. The magnitude of these findings increased when accounting for overall volume and intracranial volume, supporting a focal effect in our results. Inattentive and hyperactivity/impulsivity traits show common volume deficits in regions associated with visuospatial processing and memory while at the same time showing dissociable differences, with inattention showing differences in areas associated with attention and emotion regulation and hyperactivity/impulsivity associated with volume differences in motor activity regions. Uncovering such biological underpinnings within the broader disorder of ADHD allows us to refine our understanding of ADHD presentations.

Semi-supervised Active Learning for Video Action Detection

In this work, we focus on label efficient learning for video action detection. We develop a novel semi-supervised active learning approach which utilizes both labeled as well as un- labeled data along with informative sample selection for ac- tion detection. Video action detection requires spatio-temporal localization along with classification, which poses several challenges for both active learning (informative sample se- lection) as well as semi-supervised learning (pseudo label generation). First, we propose NoiseAug, a simple augmenta- tion strategy which effectively selects informative samples for video action detection. Next, we propose fft-attention, a novel technique based on high-pass filtering which enables effective utilization of pseudo label for SSL in video action detection by emphasizing on relevant activity region within a video. We evaluate the proposed approach on three different bench- mark datasets, UCF-101-24, JHMDB-21, and Youtube-VOS. First, we demonstrate its effectiveness on video action detec- tion where the proposed approach outperforms prior works in semi-supervised and weakly-supervised learning along with several baseline approaches in both UCF101-24 and JHMDB- 21. Next, we also show its effectiveness on Youtube-VOS for video object segmentation demonstrating its generalization capability for other dense prediction tasks in videos.

Vulnerable brain regions in adolescent major depressive disorder: A resting-state functional magnetic resonance imaging activation likelihood estimation meta-analysis.

Adolescent major depressive disorder (MDD) is a significant mental health concern that often leads to recurrent depression in adulthood. Resting-state functional magnetic resonance imaging (rs-fMRI) offers unique insights into the neural mechanisms underlying this condition. However, despite previous research, the specific vulnerable brain regions affected in adolescent MDD patients have not been fully elucidated. To identify consistent vulnerable brain regions in adolescent MDD patients using rs-fMRI and activation likelihood estimation (ALE) meta-analysis. We performed a comprehensive literature search through July 12, 2023, for studies investigating brain functional changes in adolescent MDD patients. We utilized regional homogeneity (ReHo), amplitude of low-frequency fluctuations (ALFF) and fractional ALFF (fALFF) analyses. We compared the regions of aberrant spontaneous neural activity in adolescents with MDD vs healthy controls (HCs) using ALE. Ten studies (369 adolescent MDD patients and 313 HCs) were included. Combining the ReHo and ALFF/fALFF data, the results revealed that the activity in the right cuneus and left precuneus was lower in the adolescent MDD patients than in the HCs (voxel size: 648 mm3, P < 0.05), and no brain region exhibited increased activity. Based on the ALFF data, we found decreased activity in the right cuneus and left precuneus in adolescent MDD patients (voxel size: 736 mm3, P < 0.05), with no regions exhibiting increased activity. Through ALE meta-analysis, we consistently identified the right cuneus and left precuneus as vulnerable brain regions in adolescent MDD patients, increasing our understanding of the neuropathology of affected adolescents.

Physical, Chemical and Compaction Characteristics of Slightly Weathered Tephras of New Zealand

AbstractThe North Island of New Zealand is a region of high volcanic activity, with significant eruptions over the past. Analogous to past events, future volcanic eruptions would produce a considerable volume of ash and granular soils, covering widespread areas and raising concerns for their disposal and storage. Such deposits, primarily airfall tephra, could be potentially used in geotechnical engineering applications such as foundations, roadway embankments and land reclamations. However, before their use as structural fills can be recommended, detailed laboratory investigations of their physical, chemical, compaction, and geotechnical engineering properties (strength, compressibility, collapsibility, liquefaction potential, etc.) must be conducted. Different tephra deposits can be products of different eruptions, so chemical composition analyses can be combined with the physical, compaction, and engineering properties to characterize such deposits. Accordingly, this paper provides useful insights from physical (grain size, specific gravity, and morphology), chemical (elemental and mineralogy using X-ray fluorescence and X-ray diffraction), and compaction tests (maximum dry density, optimum water content, and particle breakage) for eleven selected volcanic tephra samples sourced from the North Island of New Zealand in the Rotorua, Taupo, and Auckland regions.

Spatial correspondence of cortical activity measured with whole head fNIRS and fMRI: Toward clinical use within subject

Functional near infrared spectroscopy (fNIRS) and functional magnetic resonance imaging (fMRI) both measure the hemodynamic response, and so both imaging modalities are expected to have a strong correspondence in regions of cortex adjacent to the scalp. To assess whether fNIRS can be used clinically in a manner similar to fMRI, 22 healthy adult participants underwent same-day fMRI and whole-head fNIRS testing while they performed separate motor (finger tapping) and visual (flashing checkerboard) tasks. Analyses were conducted within and across subjects for each imaging approach, and regions of significant task-related activity were compared on the cortical surface. The spatial correspondence between fNIRS and fMRI detection of task-related activity was good in terms of true positive rate, with fNIRS overlap of up to 68 % of the fMRI for analyses across subjects (group analysis) and an average overlap of up to 47.25 % for individual analyses within subject. At the group level, the positive predictive value of fNIRS was 51 % relative to fMRI. The positive predictive value for within subject analyses was lower (41.5 %), reflecting the presence of significant fNIRS activity in regions without significant fMRI activity. This could reflect task-correlated sources of physiologic noise and/or differences in the sensitivity of fNIRS and fMRI measures to changes in separate (vs. combined) measures of oxy and de-oxyhemoglobin. The results suggest whole-head fNIRS as a noninvasive imaging modality with promising clinical utility for the functional assessment of brain activity in superficial regions of cortex physically adjacent to the skull.

Behaviors analysis of on-coming cluster based on knowledge under cluster security requirements

Analysis of cluster behaviors of the on-coming cluster is an essential measure for high value locations on the battlefield. Unlike target tracking and clustering analysis, cluster behaviors analysis under cluster security requirements remains an open issue, which is a joint analysis of clustering, intent reasoning and activity regions. To address this issue, a framework for cluster behaviors analysis is proposed by incorporating expert knowledge and domain knowledge, and a knowledge-assisted score function with is designed to improve the accuracy of intent reasoning network, overcoming the effects of possible knowledge errors. The framework consists of three modules for cluster analysis, intent reasoning and activity region analysis for typical tasks, in which an intent reasoning network is constructed to obtain cluster intents by using a hybrid knowledge and data driven approach. Furthermore, considering the complexity of the battlefield environment, different tasks and corresponding activity region optimization functions are designed for cluster activity region analysis, which are vital elements of cluster behaviors analysis. Simulations demonstrate the effectiveness of the proposed cluster behaviors analysis framework.

Enzymatic properties of UDP-glycosyltransferase 89B1 from radish and modulation of enzyme catalytic activity via loop region mutation.

Glycosyltransferases (GTs), crucial enzymes in plants, alter natural substances through glycosylation, a process with extensive applications in pharmaceuticals, food, and cosmetics. This study narrows its focus to GT family 1, specifically UDP-glycosyltransferases (UGTs), which are known for glycosylating small phenolic compounds, especially hydroxybenzoates. We delve into the workings of Raphanus sativus glucosyltransferase (Rs89B1), a homolog of Arabidopsis thaliana UGT89B1, and its mutant to explore their glycosyltransferase activities toward hydroxybenzoates. Our findings reveal that Rs89B1 glycosylates primarily the para-position of mono-, di-, trihydroxy benzoic acids, and its substrate affinity is swayed by the presence and position of the hydroxyl group on the benzene ring of hydroxybenzoate. Moreover, mutations in the loop region of Rs89B1 impact both substrate affinity and catalytic activity. The study demonstrates that insertional/deletional mutations in non-conserved regions, which are distant from the UGT's recognition site, can have an effect on the UGT's substrate recognition site, which in turn affects acceptor substrate selectivity and glycosyltransferase activity. This research uncovers new insights suggesting that mutations in the loop region could potentially fine-tune enzyme properties and enhance its catalytic activity. These findings not only have significant implications for enzyme engineering in biotechnological applications but also contribute to a more profound understanding of this field.

Assessment of the energy saving potential by regions of Ukraine (methodology and predictive assessment)

The purpose of the research is the develop methods and tools for long-term forecasting of electricity consumption based on the improved comprehensive method of demand for energy resources, taking into account the peculiarities of electricity use in the regions of Ukraine and their impact on the country's electricity consumption. The scientific novelty of the obtained results is the consideration of the technological potential of regional electricity conservation by means of electricity conservation measures typical for the regions. Thus, a complex method, a mathematical model, and a methodology for determining the forecast demand for electricity for three hierarchical levels of the economy were further developed. In these levels, the following groups of indicators are distinguished for forecasting electricity consumption: country, region, local level, or types of economic activity in the region. The formed three-level model (level I, level II, level III) takes into account both the general potential of electricity conservation (from structural and technological changes) in the country as a whole, and peculiarities at the regional level (region, city, village, settlement, territorial community) in certain (selected) types of economic activity in production (service provision). In the course of the work, material was collected on energy-saving measures in energy-intensive industries and forecasts of the development of certain types of production and service provision. These estimates determined the technological potential of energy saving in the regions. The 12 regions with the largest electricity consumption are highlighted, and the other regions are combined. In the region, the potential of electricity saving was distributed according to the structure of electricity consumption according to the types of economic activity inherent in this region. The technological potential of electricity conservation in the country will reach 10.35 billion kWh. Keywords: region, electricity-saving, electricity-saving potential, forecasting, energy efficiency, electricity.

Influence of new dimethylaminoethanol derivatives, butanoic and trans-butenedioic acids, on the tolerability of hypoxia, hyperthermia, and hypothermia

BACKGROUND: The need to increase the tolerance of various extreme effects is associated not only with the expansion of human professional activity regions but also with the need to assist victims of natural and man-made disasters. The use of pharmacological agents for individual adverse effects is a well-known method; however, considering the combined effects of several physical or chemical factors, only a few references are found in the literature.&#x0D; AIM: This preclinical study aimed to examine the effectiveness of a new derivative of aminoethanol and intermediates of the Krebs cycle in relation to the isolated and combined effects of hypoxia and temperature (hyperthermia and hypothermia).&#x0D; MATERIALS AND METHODS: The fumaric salt of the amber ether of diethylaminoethanol was synthesized at St. Petersburg State University of Chemistry and Pharmacy, Department of Organic Chemistry (Head Professor I.P. Yakovlev). The study was conducted on small laboratory animals. Resistance to hypoxia was assessed by the dynamics of the altitude threshold of animals, tolerance to hyperthermia by survival in a thermal chamber at 40°C, and tolerance to hypothermia by the time of maximum swimming in water at 10–12°C. Under combined exposure, the condition of the animals was assessed by the dynamics of physical performance, hypoxia was induced by preliminary administration of the methemoglobin former sodium nitrite at a dose of 50 mg/kg, and thermal exposure was induced by placing the animal in water at 40°C (hyperthermia) or 9–11°C (hypothermia).&#x0D; RESULTS: After a single intragastric administration in a wide range of doses, the test compound stimulated the physical performance of animals and exhibited a protective effect under the isolated effects of hypobaric hypoxia, hyperthermia, and hypothermia. With combined exposure to hemic hypoxia and hyperthermia, the compound was effective at a dose of 250 mg/kg. With combined exposure to hemic hypoxia and hypothermia, efficiency was also noted at lower doses (25 and 50 mg/kg).&#x0D; CONCLUSION: Fumaric salt of dimethylaminoethanol amber ether, a new derivative of dimethylaminoethanol, butenedioic, and trans-butenedioic acids, is promising for further study as a means of increasing the body’s resistance to extreme influences.

Abstract A024: DCE-MRI-based biophysical simulation to forecast NAT response in HER2+ breast cancer patients, with glucose characterization and orthogonal validation using FDG-PET and 64Cu studies

Abstract Background Regions of high metabolic activity within a tumor can increase tumor perfusion. Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) and 18Fluorodeoxyglucose (FDG) positron emission tomography (PET) are imaging methods used in cancer diagnosis; the former identifies perfusion of the tumor microenvironment and the latter provides a coarse readout of glucose metabolic activity. Here, we perform a pilot analysis in a unique cohort of patients who underwent DCE-MRI, 18FDG-PET and 64Cu-DOTA-Traztuzumab. We characterize the performance of our perfusion model SimBioSys-Microvasculature (SBS-MV). We use this model in 3D simulations of individual HER2+ breast cancer patients to forecast response to neoadjuvant chemotherapy (NAT). Methods SBS-MV is a modified Tofts model for pharmacokinetic modeling of DCE-MRI data, utilizing a tissue segmentation model developed in-house to inform parameter fits and ensure that the derived parameters fall within acceptable values on a tissue-by-tissue level. We evaluated the stability of the SBS-MV model by analyzing a separate cohort of 10 patients who underwent ultrafast DCE-MRI. By undersampling the original high temporal resolution data, we mimicked possible variation in standard-of-care (SoC) DCE studies and accessed the variability of our fits with respect to different subsets. Next, we analyzed data from a different cohort of 18 patients, each of whom underwent a pre-NAT SoC DCE-MRI study, a mid-treatment FDG PET study, and a mid-treatment 64Cu-DOTA-Trastuzumab study during treatment. Tissue segmentation and SBS-MV fits were performed on the pre-NAT DCE-MRI. Tightly cropped boxes encompassing the tumor in the 3D SBS-MV volumes and the PET volumes were created. Using these identified regions, all summary statistics were calculated and cross-correlated between imaging modalities. Results SBS-MV was stable to SoC-mimicking temporally undersampled ultrafast DCE-MRI series, demonstrating relatively little variability in the output parameters (a voxel wise median deviation of approximately 0.005 min−1). Further, we demonstrate that SBS-MV parameters (Ktrans, ve) are correlated with FDG SUVSA and 64Cu SUVSA. The glucose concentrations used in the biophysical simulations, which are derived from SBS-MV fits, were correlated with FDG SUVSA, indicating that downstream applications of the SBS-MV models still carry this perfusion information. Finally, using SBS-MV, our biophysical simulations of HER2-targeted therapy accurately predict patient response. In this small cohort, our biophysical simulations performed well, yielding predictive accuracy of 0.83 (sensitivity=0.83, specificity=0.83). Conclusion Our MV model extracts biologically meaningful perfusion parameters from standard clinical DCE-MRI time series, providing the same benefits of a comprehensive kinetic analysis without impacting clinical workflow. This approach could be used in research and clinical settings, offering actionable information on what drives individual patient therapeutic response for a more personalized care. Citation Format: John Whitman, Vikram Adhikarla, Russell Rockne, Lusine Tumyan, Joanne Mortimer, Wei Huang, Dorys Lopez Ramos, Joseph R. Peterson, John A. Cole. DCE-MRI-based biophysical simulation to forecast NAT response in HER2+ breast cancer patients, with glucose characterization and orthogonal validation using FDG-PET and 64Cu studies [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Breast Cancer Research; 2023 Oct 19-22; San Diego, California. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_1):Abstract nr A024.

Search for interacting galaxy clusters from SDSS DR-17 employing optimized friends-of-friends algorithm and multimessenger tracers

ABSTRACT In the theoretical framework of hierarchical structure formation, galaxy clusters evolve through continuous accretion and mergers of substructures. Cosmological simulations have revealed the best picture of the universe as a 3D filamentary network of dark-matter distribution called the cosmic web. Galaxy clusters are found to form at the nodes of this network and are the regions of high merging activity. Such mergers being highly energetic, contain a wealth of information about the dynamical evolution of structures in the Universe. Observational validation of this scenario needs a colossal effort to identify numerous events from all-sky surveys. Therefore, such efforts are sparse in literature and tend to focus on individual systems. In this work, we present an improved search algorithm for identifying interacting galaxy clusters and have successfully produced a comprehensive list of systems from SDSS DR-17. By proposing a set of physically motivated criteria, we classified these interacting clusters into two broad classes, ‘merging’ and ‘pre-merging/postmerging’ systems. Interestingly, as predicted by simulations, we found that most cases show cluster interaction along the prominent cosmic filaments of galaxy distribution (i.e. the proxy for dark matter filaments), with the most violent ones at their nodes. Moreover, we traced the imprint of interactions through multiband signatures, such as diffuse cluster emissions in radio or X-rays. Although we could not find direct evidence of diffuse emission from connecting filaments and ridges; our catalogue of interacting clusters will ease locating such faintest emissions as data from sensitive telescopes such as eROSITA or SKA, becomes accessible.

18F-FDG PET/CT anatomic and metabolic guidance in CT-guided lung biopsies

PurposeTo evaluate the role of Fluorine-18 fluorodeoxyglucose (18F-FDG) PET/CT as a metabolic guide in increasing the accuracy, diagnostic yield and safety of CT-guided percutaneous needle lung biopsy (PNB). Methods and MaterialsRetrospective analysis of 340 consecutive patients with suspicious lung nodules, masses or extensive disease that underwent lung biopsy over a 3-year period. Patients were divided into three groups; those that had PET/CT prior to the biopsy, those that had PET-CT following the biopsy and those who did not undergo PET-CT. Correlation was made with the histopathological result. Results353 PNBs were performed (median lesion size 30 mm, 7–120 mm) with overall diagnostic rate of 83.9 % (95.8 % malignant). Biopsy success rate was 88.8 % with PET-CT pre-PNB, versus 78.9 % of 175 PNB without PET-CT upfront (p < 0.01 Fisher exact test). Correct targeting to PET-CT-maximum activity area (MAA) was present in 87.1 %. Biopsy success rate was 88.8 % for PNBs targeting the PET-CT-MAA region and only 52.8 % for PNBs not targeting the PET-CT-MAA (p < 0.0001). PET-CT pre-PNB had higher rates of PET-CT-MAA targeting compared to PET-CT post PNB (91.0 % v 80.0 %, p = 0.01). The availability of PET-CT before the PNB lead to significantly increased biopsy success rates in patients with a mass (OR:7.01p = 0.004), compared to a nodule (p = 0.498) or multiple nodules (p = 0.163). Patients with a PET-CT pre-PNB underwent fewer PNB passes (mean 2.6 v 3.1, p < 0.0001 Mann Whitney U). Serious complications were less common in PET-CT pre-PNB group (4.5 % v 10.9 %, p < 0.05). Pre-PNB PET-CT performance improvement applied to all 3 radiologists and was greatest for masses and infiltrative abnormalities. ConclusionMetabolic information provided by 18F-FDG PET/CT and PNB localisation to the PET-CT maximum activity region is associated with higher diagnostic biopsy rates especially in masses and appears to account for improved performance, less needle passes and complications when available pre-biopsy.

LC-FLD Determination of Glyphosate, AMPA and Glufosinate in Surface Water from the Paraná River Basin

Natural waters from the Paraná River hydrographic basin in the Brazil-Paraguay cross-border region were analyzed by liquid chromatography coupled to a fluorescence detector (LC-FLD) after extraction of the analytes in anion exchange resin IRA-900. The method allowed good recovery (91 to 113%) of the studied species (glyphosate, (aminomethyl)phosphonic acid (AMPA) and glufosinate) precision compatible with the requirements of the National Metrology Institute (relative standard deviation &lt; 18%) and limit of quantification (LOQ) values between 0.2 and 0.8 mg L-1. In most of the samples collected between January and September 2022, it was impossible to detect the presence of herbicides, even in regions of intense agricultural activity, probably due to the high adsorption capacity of the soils of the region and due to the higher LOQ of the method. Under these conditions, the main transport route is estimated to be associated with surface runoff, which is only favored by heavy rainfall events.

Effects of Eddies on the Formation and Subduction of North Pacific Subtropical Mode Water Based on Argo Observations

AbstractNorth Pacific subtropical mode water (NPSTMW) is formed in the winter deep mixed layer (ML), due to ocean‐to‐atmosphere interactions, south of the Kuroshio Extension (KE), one of the most energetic eddy activity regions. The large‐scale effects of eddies on the formation and subduction of NPSTMW are investigated on updated Argo observations via kinematic and thermodynamic parameterization approaches. The climatological annual mean eddy‐induced subduction of NPSTMW can reach 4.51 Sv, which accounts for nearly 56% of the total subduction. The local enhancement of the eddy‐induced subduction rate can reach 90 m yr−1 in the high eddy kinetic energy (EKE) zone. Moreover, the spatial distributions of the large eddy‐induced subduction are mostly generated in a zone of steep isopycnals near the KE front area via the parameterization. The diagnosis of the thermodynamic relationship indicates that the eddy‐induced buoyancy flux broadens the area of ocean surface buoyancy loss and then fosters the formation of NPSTMW in winter. The eddy‐induced buoyancy loss due to diapycnal mixing is likely to occur in the relatively steep isopycnals near the KE region, which accounts for 21.2% of the net NPSTMW formation. The contribution of eddy‐induced subduction has the same order as that of lateral induction in each year. The eddy‐induced subduction and lateral induction show similar interannual variations related to the KE variable state.

Radiological risk estimation from the terrestrial gamma dose rate in the seismically active Kopili Fault Zone, India

ABSTRACT Anomalies in terrestrial gamma radiation have been reported in regions of seismic activity. The Kopili Fault in India is well-known for being extremely seismically active. Several mild to moderate-magnitude earthquakes with epicentres along the Kopili Fault Zone have recently been recorded. This necessitates a measurement of variations in gamma radiation and its associated radiological risks to the population in the region in relation to seismic activities. In this work, a portable gamma survey metre was used to measure terrestrial gamma radiations in the earthquake-prone Dhekiajuli area of Sonitpur district, India, which is located in the Kopili Fault Zone. Indoor and outdoor gamma dose rates were found to be 99.4 ± 5.1–195.9 ± 5.1 nGy h−1 (geometric mean: 159.0 ± 8.8 nGy h−1) and 99.4 ± 5.1–198.8 ± 5.1 nGy h−1 (geometric mean: 132 ± 6.5 nGy h−1), respectively. The estimated total annual effective dose equivalents (geometric mean: 0.94 ± 0.05 mSv y−1) were found to be higher than the recommended global average of 0.48 mSv y−1. The excess lifetime cancer risk was also estimated by considering the life span of an individual as 70 years, which ranged from 2.4 × 10−3 to 4.8 × 10−3.

Investigation of altered spontaneous brain activity in patients with bronchial asthma using the percent amplitude of fluctuation method: a resting-state functional MRI study

PurposeTo explore the regions of aberrant spontaneous brain activity in asthma patients and their potential impacts using the Percent amplitude of fluctuation (PerAF) analysis method.Patients and methodsIn this study, a total of 31 bronchial asthma (BA) patients were ultimately included, comprising 17 males and 14 females. Subsequently, 31 healthy control subjects (HCS) were recruited, consisting of 17 males and 14 females, and they were matched with the BA group based on age, sex, and educational status. The PerAF analysis technique was employed to study the differences in spontaneous brain activity between the two groups. The SPM12 toolkit was used to carry out a two sample t-test on the collected fMRI data, in order to examine the differences in PerAF values between the asthma patients and the healthy controls. We employed the Montreal Cognitive Assessment (MoCA) scale and the Hamilton Depression Scale (HAMD) to evaluate the cognitive and emotional states of the two groups. Pearson correlation analysis was utilized to ascertain the relationship between changes in the PerAF values within specific brain regions and cognitive as well as emotional conditions.ResultsCompared with the healthy control group, areas of the brain with reduced PerAF in asthma patients included the inferior cerebellum, fusiform gyrus, right inferior orbital frontal gyrus, left middle orbital frontal gyrus, left/right middle frontal gyrus (MFG), dorsal lateral superior frontal gyrus (SFGdl), left superior temporal gyrus (STG), precuneus, right inferior parietal lobule (IPL), and left/right angular gyrus. BA patients exhibit mild cognitive impairments and a propensity for emotional disturbances. Furthermore, the perAF values of the SFGdl region are significantly positively correlated with the results of the MoCA cognitive assessment, while negatively correlated with the HAMD evaluation.ConclusionThrough the application of PerAF analysis methods, we discovered that several brain regions in asthma patients that control the amplitude of respiration, vision, memory, language, attention, and emotional control display abnormal changes in intrinsic brain activity. This helps characterize the neural mechanisms behind cognitive, sensory, and motor function impairments in asthma patients, providing valuable insights for potential therapeutic targets and disease management strategies.

Regional Multifractal Variability of the Overall Seismic Activity in Pakistan from 1820 to 2020 via the Application of MDFA on Earthquake Catalogs

The overall seismicity of Pakistan from 1820 to 2020 is analysed in terms of its multifractal behaviour. Seismic events of magnitude ML = 3.0 and above are spatially clustered into four distinct groups, each one corresponding to a different region of high seismic activity. The Multifractal Detrended Fluctuation Analysis (MFDA) method applied on each cluster reveals pronounced inter-cluster heterogeneity in terms of the resulting generalised Hurst exponent and fractality spectrum, possibly due to the particular tectonic characteristics of the regions under investigation. Additional results on the variability of the Gutenberg–Richter b-value across the defined clusters further corroborate the uniqueness of the seismic profile of each region.

Neuroimaging Genomics a Predictor of Major Depressive Disorder (MDD).

Depression is a complex psychiatric disorder influenced by various genetic and environmental factors. Strong evidence has established the contribution of genetic factors in depression through twin studies and the heritability rate for depression has been reported to be 37%. Genetic studies have identified genetic variations associated with an increased risk of developing depression. Imaging genetics is an integrated approach where imaging measures are combined with genetic information to explore how specific genetic variants contribute to brain abnormalities. Neuroimaging studies allow us to examine both structural and functional abnormalities in individuals with depression. This review has been designed to study the correlation of the significant genetic variants with different regions of neural activity, connectivity, and structural alteration in the brain as detected by imaging techniques to understand the scope of biomarkers in depression. This might help in developing novel therapeutic interventions targeting specific genetic pathways or brain circuits and the underlying pathophysiology of depression based on this integrated approach can be established at length.