Significant Variation Research Articles

Quantification of eosinophils in the lower gastrointestinal tract of adults: a review of surgical specimens with normal histology from the Free State province, South Africa.

Eosinophils are normal residents of the gastrointestinal tract (GIT). They are noted in small numbers with significant variation between anatomic locations. An idiopathic increase of eosinophils is known as eosinophilic gastrointestinal disease (EGID). EGIDs are a heterologous group of disorders that produce a range of enteric and colonic syndromes. Their incidence has been increasing worldwide. Our study aimed to quantify eosinophils in each segment of the GIT in surgical specimens with normal histology to facilitate the histological diagnosis of EGID. Similarly, we aimed to describe the effect of race and gender on gastrointestinal eosinophil numbers. A retrospective, quantitative comparative study was performed. We assessed 360 surgical specimens with normal histology from the lower gastrointestinal tract of African and Caucasian adults from the Free State Province, South Africa. The number of eosinophils per mm² was counted. Overall, comparable eosinophil values were noted for both males and females, and African and Caucasian South Africans. However, Caucasians recorded a higher concentration of eosinophils in the appendix and the left colon. Eosinophils were most numerous in the lamina propria, with only small numbers present in the epithelium. Our results show that the South African population has similar eosinophil distribution trends to international studies. However, South Africans had far fewer eosinophils than Japanese and North American adults in each segment. Specific eosinophil reference ranges were formulated to quantify reference ranges of eosinophils in the lower GIT, allowing for the accurate diagnosis of EGIDs in our population in future.

Architectural Design for Data Security in Cloud-based Big Data Systems

التصميم المعماري للنظام هو عملية إبداعية بعد كل شيء. المتطلبات غير الوظيفية وبنية البرامج لها علاقة قوية. يعد أمن النظام أحد الشواغل الكبيرة وهو حاجة ومتطلب غير وظيفي. يجب أن يعتمد الأسلوب والهيكل المعماري المختاران للنظام على متطلبات النظام غير الوظيفية. تُستخدم تقنيات البيانات الضخمة لتخزين كميات هائلة من البيانات التشغيلية في المجال العام. تم اقتراح مخططات هيكل وسلوك النظام التي تستخدم تصميمًا معماريًا آمنًا لنظام يعمل عبر السحابة. تم التحقيق في مكونات مختلفة من البيانات الضخمة في هذا العمل البحثي نظرًا لخطورة القضايا الأمنية التي تركز على الخصوصية والسرية. يعد تأمين البيانات عبر السحابة التي يتم الاستعانة بمصادر خارجية لها مصدر قلق متزايد. هناك مسؤولو قواعد بيانات ضارة من الخارج ومن الداخل يمكنهم الوصول إلى البيانات الخاصة والحساسة وتعديلها ، وبالتالي يمكن أن يكون مزود خدمة قاعدة البيانات مخادعًا. آليات الأمان مطلوبة بالضرورة لحماية البيانات الحساسة الموجودة على السحابات العامة. على مستوى التطبيق ، يضمن الحل المقترح خصوصية وسرية البيانات الموجودة على السحابة. تم إجراء اختبارات مكثفة ، وكانت نتائج هذا البحث كما يلي: كشفت النتائج المسجلة عن اختلافات ذات دلالة إحصائية في النص العادي ومحتويات الوسائط المتعددة (أي الصوت والفيديو) مع قياس الوقت بالمللي ثانية لمجموعات البيانات الصغيرة والمتوسطة والكبيرة.

Obesity Does Not Negatively Affect Patient-perceived Outcomes After Cervical Disc Replacement for Disc Herniation.

Retrospective review. To assess the impact of Body Mass Index (BMI) on patient-reported outcome measures (PROMs) after cervical disc replacement (CDR). BMI may affect PROMs after spine surgery. Primary CDR recipients for herniated disc(s) with BMI <40 were retrospectively selected from a single-surgeon registry. Cohorts were divided into non-obese (BMI <30) and obese (BMI ≥30). Intercohort in-hospital complication rates were compared through independent samples t tests. Pre/postoperative PROMs were compared between cohorts through multivariable regression accounting for demographic differences. Final follow-up dates between patients averaged 11.8 ± 9.3 months. PROMs assessed included Patient-reported Outcomes Measurement Information System-Physical Function, Neck Disability Index, Visual Analog Scale-Neck, Visual Analog Scale-Arm, and the 9-item Patient Health Questionnaire. Improvements in PROMs were evaluated and compared at each follow-up within cohorts through paired t tests. The magnitude of improvement in PROMs from preoperative baseline at 6-week follow-up (∆PROM-6W) and final follow-up (∆PROM-FF) along with achievement rates of minimum clinically important differences were compared between cohorts through multivariable regression accounting for demographic differences. Of 153 patients, 53 patients were noted as obese. Demographic differences included age, prevalence of hypertension and diabetes, and comorbidity burden scores ( P ≤ 0.011, all). No significant variations in in-hospital complications were found. The non-obese cohort demonstrated improvements in all PROMs at 6 weeks and final follow-up periods ( P ≤ 0.005, all). The obese cohort demonstrated improvements in all postoperative PROMs besides 9-item Patient Health Questionnaire at 6 weeks ( P ≤ 0.015, all). After accounting for age and comorbidity variations, there were no significant intercohort differences in raw PROM scores, ∆PROM-6W, ∆PROM-FF, or minimum clinically important difference achievement rates. Regardless of BMI, patients experience significant improvements in physical function, disability, pain, and mental health after CDR for disc herniation. Patients with obesity do not suffer inferior patient-perceived outcomes after CDR. These findings may help surgeons counsel patients in the preoperative period.

Soil Microbial Community Structure and Its Contribution to Carbon Cycling in the Yalu River Estuary Wetland

Wetland microbial communities play a vital role in ecosystem functioning, particularly in the intricate processes of carbon cycling. This study employed metagenomic sequencing to investigate the diversity, composition, structural differences, carbon cycling functional gene, and microbial species of soil microbial communities in five distinct soil types of the Yalu River estuary wetland, including shoal soil, bog soil, paddy soil, meadow soil, and brown forest soil. We further explored the influence of environmental factors on both the microbial community structure and carbon cycling functional genes. Our results revealed a bacterial-dominated soil microbial community, constituting about 97.6%. Archaea and fungi represented relatively minor fractions, at 1.9% and 0.4%, respectively. While no significant differences were observed in Chao1 indices between bacterial and fungal communities, the Shannon index revealed notable differences. Both Chao1 and Shannon indices exhibited significant variations within the archaeal communities. The dominant bacterial phyla were Proteobacteria, Actinobacteria, Acidobacteria, Bacteroidetes, and Nitrospirae. Thaumarchaeota, Crenarchaeota, and Euryarchaeota formed the major archaeal phyla, while Ascomycota, Mucoromycota, and Basidiomycota were the dominant fungal phyla. Non-metric multidimensional scaling (NMDS) analysis based on Bray-Curtis distance revealed notable differences in the bacterial, archaeal, and fungal community structures across the samples. Redundancy analysis (RDA) identified key environmental factors for the major phyla. Soil pH, soil organic carbon (SOC), electrical conductivity (EC), and total phosphorus (TP) were the main influencing factors for bacteria, while soil TP, EC, total sulfur (TS), and SOC were the primary drivers for archaeal phyla. Soil total nitrogen (TN) and EC were the main influencing factors for fungal phyla. Analysis of key carbon cycling pathway genes utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG) database and clustering heatmap revealed some variations in functional gene composition across different soil types. Mantel test indicated that pH, TN, and SOC were the primary environmental factors influencing microbial functional genes associated with soil carbon cycling. Stratified bar chart analysis further demonstrated that the major contributors to carbon cycling originated from corresponding dominatnt phyla and genera of Proteobacteria, Thaumarchaeota, Actinomycetota, Euryarchaeota, and Bacteroidota. The species and relative abundance of microorganisms associated with carbon cycling pathways varied among the samples. These findings provide a crucial reference for informing the conservation and sustainable management of wetland ecosystems in the Yalu River estuary.

Absence of Monotony and Strain Effects on Referees' Physical Performance During International Basketball Federation World Cup Basketball Competition.

The study aimed to conduct a comparative analysis of physical performance indicators and assess the levels of performance monotony and strain experienced by basketball referees. The study involved the participation of 12 basketball referees (mean age: 40.0 [4.9]y) affiliated with the International Basketball Federation. The investigation was carried out throughout 2 density tournaments, wherein the maximum heart rate, average heart rate, performance monotony, and performance strain were documented for 3 variables. The findings indicated significant variations in the mean heart rate, maximum heart rate, total distance monotony, total distance strain, the total number of sprints monotony, the total number of sprints strain, calories monotony, and calories strain (P < .05). Decreasing the density of elite-level basketball competitions has been observed to reduce the monotony and strain experienced by referees. However, this action does not increase motion distance or speed zones. The environmental stressors experienced by senior-level athletes (World Cup) differ from those encountered by younger athletes (World Cup Under 19). Further investigation is required to ascertain the potential effects of competition monotony and strain on decision-making processes and the overall quality of refereeing.

Can critical care transport be safely reduced in children intubated during emergency management of status epilepticus in the United Kingdom: a national audit with case–control analysis

ObjectiveThis study describes the baseline clinical characteristics, predictors of successful extubation at referring hospitals and short-term outcomes of children intubated for status epilepticus and referred to United Kingdom (UK) paediatric...

Injection rate, scanning position, and values of parameters on pulmonary computed tomography perfusion in normal Beagles.

This study evaluated the effects of scanning position and contrast medium injection rate on pulmonary CT perfusion (CTP) images in healthy dogs. 7 healthy Beagles. Experiments involved 4 conditions: dorsal and sternal recumbency at 2.5 mL/s (first) and sternal recumbency with additional rates of 1.5 and 3.5 mL/s (second). Various parameters, including the initial time of venous enhancement (Tv), peak time of arterial enhancement (PTa), and peak enhancement values of the artery, were measured. The PTa to Tv interval was calculated. Perfusion mapping parameters (pulmonary blood flow, pulmonary blood volume, mean transit time, time to maximum, and time to peak) were determined in different lung regions (left and right dorsal, middle, and ventral). There are significant variations in most perfusion mapping parameters based on the pulmonary parenchymal location. Dorsal recumbency had a lower peak value of arterial enhancement than sternal recumbency. Pulmonary blood flow in the dorsal region and mean transit time and time to maximum in all regions showed no significant differences based on position. Pulmonary blood volume and time to peak varied with scanning position. The PTa to Tv interval did not differ based on the injection rate, but the injection time at 1.5 mL/s was longer than at other rates. All perfusion mapping parameters of the ventral region increased with higher injection rates. The recommended CTP imaging approach in dogs is a low injection rate of 1.5 mL/s in the sternal recumbency. This study provides reference ranges for perfusion parameters based on the pulmonary parenchymal location, contributing to the acquisition and application of pulmonary CTP images for differential diagnosis in small-breed dogs.

Association of serum CTRP4 levels with vascular endothelial function in patients with type 2 diabetes mellitus: CTRP4 ameliorating inflammation, proliferation and migration in human umbilical vein endothelial cells.

We investigated the correlation between serum C1q/TNF-related protein 4 (CTRP4) level and flow-mediated dilation (FMD) in patients with type 2 diabetes mellitus (T2DM), and evaluated the biological effects of CTRP4 on human umbilical vein endothelial cells (HUVECs). A group of 165 patients diagnosed with T2DM were included in this study. Endothelial function was measured with the examination of brachial artery FMD. ELISA kit was used to measure the levels of CTRP4 in serum. HUVECs were stimulated with recombinant CTRP4 protein to assess its biological functions. The levels of CTRP4 showed a significant variation among three groups based on FMD tertiles (p = 0.001). What's more, FMD had a significant difference among three CTRP4 tertile groups (p < 0.05) and was negatively related to serum CTRP4 levels (r = -0.270, p < 0.001). In T2DM patients, logistic regression analysis demonstrated that CTRP4 was the primary influence factor of low FMD (p < 0.01). In receiver operating characteristic curve analysis, the area under the curve of CTRP4 for predicting low FMD was 0.66 (95%CI 0.58-0.75). When stimulated HUVECs with recombinant CTRP4 protein, we found that CTRP4 could concentration-dependently ameliorate proliferation and migration of HUVECs in wounding healing and transwell assay. This protein could also decrease the expression of IL-6 and TNF-α and promote the release of NO in HUVEC supernatants, with suppression of NF-κB and STAT3 phosphorylation. Serum CTRP4 concentrations were negatively associated with FMD. CTRP4 alleviated proliferation, migration and inflammation in HUVECs through the suppression of NF-κB and STAT3 signaling pathways.

CASTNet: A Context-Aware, Spatio-Temporal Dynamic Motion Prediction Ensemble for Autonomous Driving

Autonomous vehicles are cyber-physical systems that combine embedded computing and deep learning with physical systems to perceive the world, predict future states, and safely control the vehicle through changing environments. The ability of an autonomous vehicle to accurately predict the motion of other road users across a wide range of diverse scenarios is critical for both motion planning and safety. However, existing motion prediction methods do not explicitly model contextual information about the environment, which can cause significant variations in performance across diverse driving scenarios. To address this limitation, we propose CASTNet : a dynamic, context-aware approach for motion prediction that (i) identifies the current driving context using a spatio-temporal model, (ii) adapts an ensemble of motion prediction models to fit the current context, and (iii) applies novel trajectory fusion methods to combine predictions output by the ensemble. This approach enables CASTNet to improve robustness by minimizing motion prediction error across diverse driving scenarios. CASTNet is highly modular and can be used with various existing image processing backbones and motion predictors. We demonstrate how CASTNet can improve both CNN-based and graph-learning-based motion prediction approaches and conduct ablation studies on the performance, latency, and model size for various ensemble architecture choices. In addition, we propose and evaluate several attention-based spatio-temporal models for context identification and ensemble selection. We also propose a modular trajectory fusion algorithm that effectively filters, clusters, and fuses the predicted trajectories output by the ensemble. On the nuScenes dataset, our approach demonstrates more robust and consistent performance across diverse, real-world driving contexts than state-of-the-art techniques.

RDGT-GAN: Robust Distribution Generalization of Transformers for COVID-19 Fake News Detection

Social media platforms have become a vital source of information during the outbreak of the pandemic (COVID-19). The phenomena of fake information or news spread through social media have become increasingly prevalent and a powerful tool for information proliferation. Detecting fake news is crucial for the betterment of society. Existing fake news detection models focus on increasing the performance which leads to overfitting and lag generalizability. Hence, these models require training for various datasets of the same domain with significant variations in the distribution. In our work, we have addressed this overfitting issue by designing a robust distribution generalization of transformers-based generative adversarial network (RDGT-GAN) architecture, which can generalize the model for COVID-19 fake news datasets with different distributions without retraining. Based on our experimental findings, it is evident that the proposed model outperforms the current state-of-the-art (SOTA) models in terms of performance.

1239 Trends in Geospatial Availability of Neuro-oncology Clinical Trials in the United States Over Two Decades

INTRODUCTION: Advances in brain tumors treatments rely on successful neuro-oncology (NO) clinical trials. To date, data on NO trials completion in the US is scarce. Understanding these factors could help improve access to and the design of future clinical trials. METHODS: NO clinical trials registered in the US were analyzed (2000-2019). Univariate and multivariate analysis were used to compare success rates among trials. Geospatial analysis was performed to determine the trial density and failure rates across different states. Trial density was estimated by the number of trials/state population. RESULTS: A total of 2,610 neuro-oncology clinical trials were registered in the US during the study period, of which 1,257 met a primary endpoint – completion or trial failure. North Dakota had the highest trial density (6.03 trials/100,000 residents), followed by South Dakota (5.83) and several Northeastern states (3.90-5.60). The change in trial failure rates did not correlate with trial density by state (p = 0.777). The states with the greatest increase in trial failure rates were Nevada (23.1%), West Virginia, Alaska, and Idaho (all three at 20.0%). Florida showed a trend towards a statistically significant increase in failure rates to 10.9% (p = 0.09). CONCLUSIONS: The results of this study highlight the variations in success rates and geographic distribution of neuro-oncology clinical trials in the United States. Factors beyond trial density may be critical to trial success. The significant geographic variations in trial density and failure rates across states emphasize the need for targeted efforts to improve access participation to trials in certain regions. Further studies aimed at identifying the factors contributing to the increase in trial failure rates are needed to develop strategies to improve trial enrollment.

UniRecSys: A unified framework for personalized, group, package, and package-to-group recommendations

Recommender systems aim to enhance the overall user experience by providing tailored recommendations for a variety of products and services. These systems help users make more informed decisions, leading to greater user engagement with the platform. However, the implementation of these systems largely depends on the context, which can vary from recommending an item or package to a user or a group. This requires careful exploration of several models during the deployment, as there is no comprehensive and unified approach that deals with recommendations at different levels. Furthermore, these individual models must be closely attuned to their generated recommendations depending on the context to prevent significant variation in their generated recommendations. In this paper, we propose a novel unified recommendation framework that addresses all four recommendation tasks, namely, personalized, group, package, and package-to-group recommendation, filling the gap in the current research landscape. The proposed framework can be integrated with most of the traditional matrix factorization-based collaborative filtering (CF) models. This research underscores the significance of including group and package information while learning latent representations of users and items for personalized recommendations. These components help in exploiting a rich latent representation of the user/item by enforcing them to align closely with their corresponding group/package representation. We consider two prominent CF techniques, namely Regularized Matrix Factorization and Maximum Margin Matrix factorization, as the baseline models and demonstrate their customization to various recommendation tasks. Experimental results on two publicly available datasets are reported, comparing them to other baseline approaches for various recommendation tasks.

Comparative Analysis of Chemical Composition and Antibacterial Activities of Essential Oils from Two Ocimum Species

Background: The species of the genus Ocimum has been used since ancient times in the Indian subcontinent to cure various illnesses. Essential oil from Ocimum species has antimicrobial activity. Objective: The main objective of this study was to extract essential oils from different parts of two Ocimum species and test their antimicrobial activity Methods: Hydrodistillation was used to extract essential oils from various parts of two basil species, CG_MS was used to identify the chemical compounds, and disk diffusion method was used to assess their antimicrobial activity. Results: A total of sixty-seven chemical compounds from Ocimum sanctum L. and Ocimum gratissimum L. were identified using GC-MS. Among them, eugenol (1.00-27.66%), methyl eugenol (0.78-28.52%), β-elemene (5.10-20.98%), caryophyllene (0.94-43.18%), caryophyllene oxide (1.1-10.81%), palmitic acid methyl ester (3.20-21.38%), oleic acid methyl ester (2.91-40.7%) and linoleic acid methyl ester (1.55-74.71%) comprised the majority of the makeup of essential oils, due to diverse plant species and body sections, the percentage differed significantly. The essential oils contained monoterpenes, sesquiterpenes, and aldehydes/ketonic derivatives in the flower and leaf parts of O. sanctum and the leaf part of O. gratissimum. The essential oils of these Ocimum species showed good antibacterial activities against the bacteria, methicillin-resistant Staphylococcus aureus (MRSA), Klebsiella pneumoniae, Pseudomonas aeruginosa, Escherichia coli, and Enterococcus faecalis with inhibition zones ranging from 10-36 mm. Conclusion: These two species of Ocimum showed significant variation in chemical composition and antibacterial activity.

Land use and topographic controls on soil chemical properties in some selected sites of the North West Region of Cameroon

ABSTRACT Land use change affects soil forming processes and modifies site conditioning factors. This paper evaluates land use and topographic controls on soil chemical properties in selected sites of the North West Region of Cameroon. Three topographic zones comprising; low altitude (<1200m), mid-altitude (1200-1500m), and high altitude (˃1500m), under four land use types were studied. 60 soil samples were collected on plots of 30m2, at 0-20cm depth and subjected to chemical analyses. Significant relationships between variables were established via ANOVA and Pearson’s correlation tests. The results revealed significant correlation between soil properties at (P<0.05) and (P<0.01) confident intervals between soil properties with land use and elevation classes. A significant decline (P< 0.01) was observed in the concentrations of pH, Base Saturation (BS), Cation Exchange Capacity (CEC), Total Nitrogen (TN), Soil Organic Carbon (SOC), Soil Organic Matter (SOM), Phosphorus (P) and exchangeable bases in farmlands. Soil chemical properties showed variations across land uses and elevation classes. Soil pH, BS, CEC, SOC, SOM, P, and Ca2+ were statistically significant with topographic variations, while BS, CEC, TN, and Mg2+ varied significantly with land use. Exchangeable potassium (K+) and exchangeable sodium (Na+) showed no significant variations with land use and topographic position.

Study of physico-chemical parameters and zooplanktons diversity of Bhīma River from Solapur district (m. s.) India

The present study is on "Physico-chemical parameters of Bhima river of Solapur District (Maharashtra)".The Study was carried on from Jan'2022 to Des'2022 atfour selected sampling stations. Monthly variation of Physico-chemical Characteristics of water of Bhima River were studied and it revealed that the water quality is fairly homogeneous and suitable for drinking .Study of zooplankton showed 90 species of zooplankton belonging to 4 different classes.Rotifera 21 species ( 23%) , Cladocera 20 species ( 22%) , Copepoda 22 species ( 24%) , Protozoa 27 species ( 30%).The investigation on Physico-chemical characteristics at different sites revealed it's alkaline Nature , suitable for aquaculture practices. Significant site variations have been recorded due to the interference of sewage and agricultural wastes. All the Zooplankton groups, Rotifera , Protozoans , Copepoda recorded dominance.

Classification of acoustic survey data: A comparison between seven teams of experts

Acoustic surveys of mixed fish aggregations often rely on manual allocation of acoustic energy to target species, with auxiliary information such as trawl catches and target strength distributions aiding interpretation. However, different teams of experts may use the same auxiliary data differently. In this experiment, seven teams of experts interpreted the same acoustic data, and we compared their classification to target categories to quantify uncertainty in the manual classification process. The teams largely agreed on the total acoustic energy attributable to organisms, but there was significant variation in how the teams split this energy on different target categories. This was caused by differences in applied thresholds for separating plankton and fish, as well as disagreements in species classification. For all target categories, the variation due to teams was lower than the overall variability across acoustic segments, but when scaled up to the number of segments in a typical survey, the team effect either dominated or was of similar magnitude as the segment variability. These results imply a need for further standardisation and uncertainty estimation of expert evaluations in acoustic surveys involving manual interpretation of echo sounder data.

Development of a Follow-Up Measure to Ensure Complete Screening for Colorectal Cancer

The current quality performance measure for colorectal cancer (CRC) screening is limited to initial screening. Despite low rates, there is no measure for appropriate follow-up with colonoscopy after receipt of an abnormal result of a stool-based screening test (SBT) for CRC. A quality performance measure is needed. To develop and test a quality performance measure for follow-up colonoscopy within 6 months of an abnormal result of an SBT for CRC. This retrospective quality improvement study examined data from January 1, 2016, to December 31, 2020, with 2018 plus 6 months of follow-up as the primary measurement period to verify performance rates, specify a potential measure, and test for validity, reliability, and feasibility. The Optum Labs Data Warehouse (OLDW), a deidentified database of health care claims and clinical data, was accessed. The OLDW contains longitudinal health information on enrollees and patients, representing a diverse mixture of ages and geographic regions across the US. For the database study, adults from 38 health care organizations (HCOs) aged 50 to 75 years who completed an initial CRC SBT with an abnormal result were observed to determine follow-up colonoscopy rates within 6 months. Rates were stratified by race, ethnicity, sex, insurance, and test modality. Three HCOs participated in the feasibility field testing. Data were analyzed from June 1, 2022, to May 31, 2023. The primary outcome consisted of follow-up colonoscopy rates following an abnormal SBT result for CRC. Reliability statistics were also calculated across HCOs, race, ethnicity, and measurement year. Among 20 581 adults (48.6% men and 51.4% women; 307 [1.5%] Asian, 492 [7.2%] Black, 644 [3.1%] Hispanic, and 17 705 [86.0%] White; mean [SD] age, 63.6 [7.1] years) in 38 health systems, 47.9% had a follow-up colonoscopy following an abnormal SBT result for CRC within 6 months. There was significant variation between HCOs. Notably, significantly fewer Black patients (37.1% [95% CI, 34.6%-39.5%]) and patients with Medicare (49.2% [95% CI, 47.7%-50.6%]) or Medicaid (39.2% [95% CI, 36.3%-42.1%]) insurance received a follow-up colonoscopy. A quality performance measure that tracks rates of follow-up within 6 months of an abnormal SBT result was observed to be feasible, valid, and reliable, with a median reliability statistic between HCOs of 94.5% (range, 74.3%-99.7%). The findings of this observational study of 20 581 adults suggest that a measure of follow-up colonoscopy within defined periods after an abnormal result of an SBT test for CRC is warranted based on low current performance rates and would be feasible to collect by health systems and produce valid, reliable results.

Frequency-Adaptive Pan-Sharpening with Mixture of Experts

Pan-sharpening involves reconstructing missing high-frequency information in multi-spectral images with low spatial resolution, using a higher-resolution panchromatic image as guidance. Although the inborn connection with frequency domain, existing pan-sharpening research has not almost investigated the potential solution upon frequency domain. To this end, we propose a novel Frequency Adaptive Mixture of Experts (FAME) learning framework for pan-sharpening, which consists of three key components: the Adaptive Frequency Separation Prediction Module, the Sub-Frequency Learning Expert Module, and the Expert Mixture Module. In detail, the first leverages the discrete cosine transform to perform frequency separation by predicting the frequency mask. On the basis of generated mask, the second with low-frequency MOE and high-frequency MOE takes account for enabling the effective low-frequency and high-frequency information reconstruction. Followed by, the final fusion module dynamically weights high frequency and low-frequency MOE knowledge to adapt to remote sensing images with significant content variations. Quantitative and qualitative experiments over multiple datasets demonstrate that our method performs the best against other state-of-the-art ones and comprises a strong generalization ability for real-world scenes. Code will be made publicly at https://github.com/alexhe101/FAME-Net.

Abstract 6682: Bile acid profiles and racial disparities in colorectal cancer: Exploring the protective role of secondary bile acid derivatives

Abstract Background: Colorectal cancer (CRC) is the third leading cause of cancer death in the United States, with diet and gut microbiota-derived bile acids implicated as long-term risk factors. The interplay between bile acids and immune cell differentiation, particularly of macrophages and T-cells, is a crucial aspect of the CRC microenvironment. Given the high-animal-fat diets' influence on the microbiome’s production of hydrophobic secondary bile acids such as deoxycholic acid (DCA) and lithocholic acid (LCA), this study investigates the potential immunomodulatory effects of their lower concentrations and their isomers in possibly fostering M2-like macrophage expansion. Methods: Clinical samples were obtained during colonoscopies with no tumor findings at Rush University Medical Center, Chicago. RNA was extracted from colonoscopy biopsies for NanoString RNA expression analysis, while bile acids were isolated from both lyophilized stool and frozen serum samples. To explore the immunological effects of secondary bile acids, the macrophage RAW 264.7 cell line, alongside peritoneal macrophages and bone marrow-derived macrophages (BMDMs) from C57BL/6J mice, were treated with LCA and LCA isomers. Following the bile acid treatment, LPS (100 ng/mL) or IL-4 (40 ng/ml) was added to elicit pro-inflammatory or anti-inflammatory states, respectively. After 48 hours, conditioned media were collected for enzyme-linked immunosorbent assay (ELISA), while cells were analyzed by flow cytometry and rt-qPCR. Results: Contrary to initial hypotheses, the levels of DCA and LCA levels were not significantly different between African American and non-Hispanic White subjects. Notably, allo-isomers and oxo-derivatives of these bile acids, which may promote Treg and M2-like macrophage expansion, were substantially lower in African American subjects. Ex vivo treatments with isoalloLCA and IsoLCA led to notable changes in the M2 macrophage differentiation and shifts in PGE2 production upon exposure to inflammatory or anti-inflammatory stimuli, suggesting a nuanced alteration in the macrophage-mediated inflammatory response. Conclusion: This study highlights a significant ethnic variation in bile acid profiles, with a potential impact on immune modulation and CRC risk. The reduced presence of certain bile acid isomers in African American subjects may influence the risk of CRC through altered macrophage differentiation and function. These findings emphasize the need for personalized dietary and therapeutic strategies to modulate the bile acid metabolome, potentially reducing CRC disparities. Citation Format: Hanchu Dai, Patricia G. Wolf, Lisa Tussing-Humphreys, Ece Mutlu, Jason M. Ridlon, Rex Gaskins. Bile acid profiles and racial disparities in colorectal cancer: Exploring the protective role of secondary bile acid derivatives [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6682.

Accounting for Greenhouse Gas Emissions in the Agricultural System of China Based on the Life Cycle Assessment Method

Agricultural systems contribute nearly one-third of global anthropogenic GHG emissions and are an important source of GHGs globally. The clarification of the GHG emission pattern from agriculture is of paramount importance in the establishment of an agricultural emission reduction mechanism and the realization of China’s dual-carbon target. Based on the life cycle assessment method (LCA), this paper comprehensively quantifies the greenhouse gas emissions from the agricultural system in China, encompassing rice, wheat, and corn cultivation as well as animal husbandry including cows, horses, donkeys, mules, camels, pigs, and sheep. The analysis covers the period 2000–2020 and examines the spatial distribution, temporal trends, and structural changes in the greenhouse gas emissions within China’s agriculture sector. The main results are as follows: (1) from 2000 to 2020, China witnessed a consistent upward trajectory in its total agricultural GHG emissions, exhibiting an average annual growth rate of 0.73%. Notably, methane (CH4) emissions emerged as the largest contributor, displaying an overall fluctuating pattern. Carbon dioxide (CO2) emissions demonstrated intermittent increases with a noteworthy annual growth rate of 3%, signifying the most rapid expansion within this context. Conversely, nitrous oxide (N2O) emissions experienced decline over the specified period. (2) GHG emissions from cultivation demonstrate an upward trajectory, primarily driven by the CH4 emissions originating from rice cultivation and CO2 resulting from straw incineration. Conversely, GHG emissions stemming from animal husbandry declined, with the primary source being CH4 emissions arising from animal enteric fermentation. Agricultural N2O emissions predominantly arise due to manure management and nitrogen fertilizer application. (3) Agricultural greenhouse gas emissions exhibit significant variations in spatial distribution, gradually concentrating towards the North China Plain, the middle and lower reaches of the Yangtze River, and the northeast. Specifically, agricultural CH4 emissions are progressively concentrated in China’s pivotal rice-growing regions, encompassing the middle and lower reaches of the Yangtze River Plain, as well as livestock breeding areas like Inner Mongolia. Agricultural CO2 emissions primarily concentrate in dryland crop production zones such as North China and Northeast China. Meanwhile, Agricultural N2O emissions predominantly occur in Inner Mongolia and the North China Plain. China’s agricultural greenhouse gas emissions in 2020 show a significant spatial clustering effect, with hotspots primarily concentrated in Shandong, Anhui, Henan, and other regions and cold spots focused in the western and southern areas. The emission patterns of agricultural GHGs are closely intertwined with farming practices, regional development levels, and national policy; hence, tailored measures for emission reduction should be formulated based on specific crop types, livestock categories, agricultural production activities, and regional development characteristics.