Distribution Patterns Research Articles

Inversion Model for Permeability Coefficient Based on Random Forest–Secretary Bird Optimization Algorithm: Case Study of Lower Reservoir of C-Pumped Storage Power Station

The geological complexity of the karst regions presents significant challenges, with the permeability coefficient being a critical parameter for accurately analyzing seepage behavior in hydraulic engineering projects. To overcome the limitations of traditional inversion methods, which often exhibit low computational efficiency, poor accuracy, and instability, this study utilizes a finite-element forward model and orthogonal experimental design to establish a sample set for permeability-coefficient inversion. A surrogate model for seepage calculation based on the Random Forest (RF) algorithm is subsequently developed. Furthermore, the Secretary Bird Optimization Algorithm (SBOA) is incorporated to propose an intelligent RF–SBOA inversion method for permeability-coefficient estimation, which is validated through a case study of the C-pumped storage power station. The results demonstrate that the RF model’s predictions for water levels at four boreholes closely align with the measured data, outperforming models such as CART, BP, and SVR. The SBOA effectively identifies the optimal geological permeability coefficient, with the borehole water-level inversion achieving a maximum relative error of only 0.128%, which meets the accuracy requirements for engineering applications. Additionally, the computed distribution of the natural seepage field is consistent with the typical distribution patterns observed in mountain seepage systems. During the normal water-storage phase, both the calculated seepage flow and gradient comply with engineering standards, while the seepage-field distribution aligns with empirical observations. This inversion model provides a rapid and accurate method for estimating the permeability coefficient of strata in the project area, with potential applicability to permeability inversion in other engineering geology contexts, thus demonstrating considerable practical value for engineering applications.

Topological differentiation of vegetation of the Lublin-Volyn geobotanical district

The position of the Lublin and Volyn (Volhynian) uplands within the geobotanical zonation system is ambiguous and disputable. An analysis of the syntaxonomical diversity and landscape distribution of the egetation of the Lublin and Volyn uplands revealed their similarity, and we consider this whole territory as the Lublin-Volyn geobotanical district of hornbeam-oak, oak forests, and steppe meadows. This district differs from the adjacent territories and is classified within the Central European mixed forests ecoregion. Typical and diagnostic syntaxa have been identified, and ecological-coenotic profiles have been constructed to characterize the distribution patterns of shrub-forest and herbaceous vegetation within the landscape. Based on calculations of phytosociological indicators for the main ecological factors, graphical patterns of their variation were developed. It was determined that the characteristic forests of the district, Tilieto-Carpinetum (Carpinion betulis), are represented by four variants (T.-C. var. galeobdolosum; T.-C. var. hepaticosum; T.-C. var. caricosum pilosae; T.-C. var. isopyrosum). The district is also characterized by the presence of syntaxa associated with carbonate soils, both of the marsh type (Caricion davallianae) and the meadow-steppe type (Cirsio-Brachypodion, Festucion valesiacae), with the dominance of Carex humilis and Stipa capillata. Using DCA-analysis, the correlation between ecological factor indicators and the distribution of plant communities within the ecological space has been established, forming six fields distributed along three vectors: by moisture (aquatic and marsh communities), xerophytism, and chemical properties of soils (meadow-steppe communities), as well as the structure of coenoses with a specific ombroregime (forest communities).

Surplus or deficit? Quantification of carbon sources and sinks and analysis of driving mechanisms of typical oasis urban agglomeration ecosystems

The relationship between carbon sources and sinks, along with their balance, is a crucial indicator for assessing ecosystem health. Ecosystem protection mitigates climate change and promotes the carbon cycle balance. Consequently, to effectively assess the status of carbon sources and sinks in an oasis ecosystem, this study utilized remote sensing and statistical data to estimate the natural carbon sources and sinks, energy carbon emissions(ECE), and carbon surpluses or deficits in the urban agglomeration of the northern slopes of the Tianshan Mountains(UANSTM) for a period 2000–2022 from a perspective of the natural-social-economic system. The driving mechanisms were analyzed using the optimal geodetector model (OPGD) and generalized divisia index method (GDIM). The results show(1) throughout the study period, natural carbon sources and sinks in the UANSTM exhibited a distribution pattern that diminished from the Tianshan Mountains axis northward and southward, accompanied by a fluctuating increase over time. ECE predominantly occurred in urban built-up areas and adjacent cultivated lands, totaling an increase of 88.48 × 104 TgC. (2) The change trend showed an overall predominance of carbon sources, with the rate of increase of carbon sources being greater than that of carbon sinks. Grassland-cultivated land and construction land interaction area exhibited significant changes in carbon sources and sinks. (3) During the study period, the UANSTM experienced a consistent carbon deficit, averaging −68.11 TgC annually. Spatially, this deficit evolved from discrete points to linear and then to areal patterns. (4) Precipitation and elevation were the primary determinants of natural carbon sources and sinks. Whereas GDP with a contribution of 50.4%,was the predominant driver of ECE across each prefecture-level city. Development of policies that synergize regional natural and socioeconomic systems is an important means of achieving a carbon balance. The results of this study provide a reference for adding a research paradigm on carbon sources and sinks in oasis urban agglomerations and for low-carbon development.

Mathematics Education Research Trends in the Philippines: A Bibliometric Analysis using Scopus Database

The investigation of research trends in mathematics education in the global landscape has been prominent in the recent years. However, there is a dearth of literature in investigating research trends in mathematics education in the Philippine setting. Thus, this bibliometric analysis on the research in mathematics education in the Philippines from 2013 to 2023 was conducted. This paper aimed to present scientific information about the distribution pattern of research on mathematics education in terms of discipline, the profile of prominent authors, the key subject areas which given emphasis, and the direction of research. A total of 993 articles were obtained from the Scopus database and were analyzed using the VOSviewer software application to see the research trends in mathematics education in the Philippines. Research articles emerged as the predominant document type, followed by conference papers. The pinnacle of mathematics education research in the Philippines was in 2014. Notably, the research trend in the Philippines for the last five years have observable decrease in mathematics education. Results show that in terms of discipline, problem solving, teacher professional development, and curriculum were typically the key areas of emphasis. Moreover, the top author with the greatest number of citations since 2013-2023 is a female researcher from Mindanao. Furthermore, the mathematics subjects that have the most attention are algebra, proof, calculus, technology, geometry, and modeling. Finally, this paper foresees continued growth in mathematics education research in the Philippines, particularly in the realms of professional development and problem-solving.

Associations between temporal eating patterns and energy distribution patterns with gallstones: a cross-sectional study based on NHANES 2017–2018

BackgroundGallstones are strongly associated with eating occasion (EO) and energy distribution, but few studies have addressed this aspect. Therefore, we utilize the data from 2017 to 2018 National Health and Nutrition Examination Survey (NHANES) to explore the association between temporal eating patterns and energy distribution patterns with the incidence of gallstones.MethodsOur study comprised participants who completed the NHANES dietary intake interview and self-reported health questionnaire at age 20 or older. The self-report method for gallstones (have you ever been told by a doctor) was used. We use the latent class analysis (LCA) identified temporal eating patterns, and identified energy distribution patterns through latent profile analysis (LPA). The association between temporal eating patterns, energy distribution patterns, and gallstones was examined using logistic regression modeling.ResultsThe study included a total of 4,692 participants. LCA identified four temporal eating patterns labeled as “Conventional,” “Early breakfast,” “Later breakfast,” and “Grazing.” Compared to the “Conventional” pattern, the “Early breakfast” pattern (OR 0.809, 95%CI 0.808–0.811) was associated with a reduced risk of gallstones, while the “Later breakfast” (OR 1.435, 95%CI 1.432–1.438) and “Grazing” (OR 1.147, 95%CI 1.145–1.148) patterns were associated with an increased risk of gallstones. LPA identified four energy distribution patterns labeled as “Guideline,” “High carbohydrates,” “Carbs-fat balance,” and “High fat.” The “High carbohydrates” pattern (OR 1.329, 95%CI 1.326–1.331) was associated with an increased risk of gallstones compared to the “Guideline” pattern. The “Carbs-fat balance” pattern (OR 0.877, 95%CI 0.876–0.879) and the “High fat” pattern (OR 0.848, 95%CI 0.846-0.850) were significantly and negatively associated with the risk of gallstones.ConclusionsTo summarize, inappropriate timing of eating and energy sources are associated with gallstones. As a dietary prevention measure for gallstones, we suggest adhering to a regular eating routine and avoiding overly casual and frequent food consumption. If the main EO routine occurs in the morning, this time should not exceed 9:00 a.m. Additionally, reducing carbohydrate intake and maintaining a moderate level of fat intake is believed to contribute to a lower risk of gallstones.

Research on the Synergistic Development of China’s Pension Industry and Pension Career

To adapt to the new demographic trends and foster high-quality and sustainable population growth, this study analyzes the synergistic development of the pension industry and pension career based on the data of 31 provinces in China from 2016 to 2022, using a distance coordination model, the latest Vague set similarity measure method, new grey relational analysis, kernel density estimation, and Markov chain. The findings indicate that (1) the development levels of China’s pension industry and pension career have shown a steady upward trend, with the gap between them gradually narrowing, though the overall development of the pension career remains higher than that of the pension industry. (2) The synergistic degree of China’s pension industry and pension career is high, with the degree of synergy fluctuating but generally increasing. (3) The synergistic development degree of the pension industry and pension career has continued to rise. The increase in the synergistic development degree shows a spatial distribution pattern of “Central > East > West”. (4) The spatial distribution of synergistic development of China’s pension industry and pension career is uneven, and in the long term, regions with higher synergistic development levels tend to positively influence less developed regions.

Light attenuation parameterization in a highly turbid mega estuary and its impact on the coastal planktonic ecosystem

Light is essential for phytoplankton photosynthesis and many other biogeochemical processes in the aquatic system. However, light regimes vary greatly in the estuaries and coasts due to the optical complexity of the Case-2 waters. In this study, observed vertical profiles of photosynthetically active radiation (PAR; 400-700 nm) in a highly turbid mega estuary, the Changjiang (Yangtze River) Estuary, are used to quantify the effects of sedimentary and biogeochemical components on PAR attenuation in the water column and associated ecological impacts. The in-situ data suggest suspended sediment plays the most crucial role in light diffuse attenuation coefficient (Kd) distribution, followed by salinity (i.e., an index for colored dissolved organic matter) and phytoplankton chlorophyll-a. A new parameterization of Kd, based on suspended sediment, chlorophyll-a concentration, and salinity, is fitted using multiple linear regression. The previous and new Kd parameterizations are further applied to a coupled hydrodynamics-sediment-ecosystem model to simulate spring phytoplankton blooms. Comparative model runs reveal that the new Kd parameterization resulted in a better representation of the spring bloom patterns in magnitude, horizontal distribution, and vertical thickness of the high chlorophyll-a band offshore the turbidity maximum zone during the spring bloom. In summary, accurate representations of underwater light fields in the optically complex Case-2 water are critical in understanding biophysical processes that control planktonic ecosystem dynamics in the estuaries and coastal seas.

Stereological study of organelle distribution in human mature oocytes

The ultrastructure of human oocytes has been described only qualitatively. To offer a precise organelle spatial distribution and organelle volume during the main maturation stages, we previously conducted stereological studies on prophase-I (GV) and metaphase-I (MI) oocytes, and here we present results on metaphase-II (MII) oocytes. Five donor oocytes from different donors were processed for transmission electron microscopy, and quantification of organelle distribution was performed using point-counting stereology. Statistical tests compared the means of the relative volumes occupied by organelles among oocyte regions. The most abundant organelles were elements of the smooth endoplasmic reticulum (SER), such as SER small vesicles, SER medium vesicles, SER large vesicles and SER isolated tubules, along with mitochondria, followed by SER tubular aggregates, cortical vesicles and lysosomes. Significant differences between oocyte regions were found for lysosomes, cortical vesicles and SER large vesicles. Comparisons of MII oocytes to previous findings in GV and MI oocytes evidenced specific patterns of organelle distribution and relative volumes. This final evaluation thus enables to track organelle spatial reorganization across oocyte stages, which, in addition to gathered knowledge, may be useful to assist in improvements of stimulation protocols, in-vitro maturation media and cryopreservation techniques.

Neurotrophic extracellular matrix proteins promote neuronal and iPSC astrocyte progenitor cell- and nano-scale process extension for neural repair applications.

The extracellular matrix plays a critical role in modulating cell behaviour in the developing and adult central nervous system influencing neural cell morphology, function and growth. Neurons and astrocytes, play vital roles in neural signalling and support respectively and respond to cues from the surrounding matrix environment. However, a better understanding of the impact of specific individual extracellular matrix proteins on both neurons and astrocytes is critical for advancing the development of matrix-based scaffolds for neural repair applications. This study aimed to provide an in-depth analysis of how different commonly used extracellular matrix proteins- laminin-1, Fn, collagen IV, and collagen I-affect the morphology and growth of trophic induced pluripotent stem cell (iPSC)-derived astrocyte progenitors and mouse motor neuron-like cells. Following a 7-day culture period, morphological assessments revealed that laminin-1, fibronectin, and collagen-IV, but not collagen I, promoted increased process extension and a stellate morphology in astrocytes, with collagen-IV yielding the greatest increases. Subsequent analysis of neurons grown on the different extracellular matrix proteins revealed a similar pattern with laminin-1, fibronectin, and collagen-IV supporting robust neurite outgrowth. fibronectin promoted the greatest increase in neurite extension, while collagen-I did not enhance neurite growth compared to poly-L-lysine controls. Super-resolution microscopy highlighted extracellular matrix-specific nanoscale changes in cytoskeletal organization, with distinct patterns of actin filament distribution where the three basement membrane-associated proteins (laminin-1, fibronectin, and collagen-IV) promoted the extension of fine cellular processes. Overall, this study demonstrates the potent effect of laminin-1, fibronectin and collagen-IV to promote both iPSC-derived astrocyte progenitor and neuronal growth, yielding detailed insights into the effect of extracellular matrix proteins on neural cell morphology at both the whole cell and nanoscale levels. The ability of laminin-1, collagen-IV and fibronectin to elicit strong growth-promoting effects highlight their suitability as optimal extracellular matrix proteins to incorporate into neurotrophic biomaterial scaffolds for the delivery of cell cargoes for neural repair.

Personalized prediction model specific for sudden cardiac death in the population: a machine learning study based on EHR

Abstract Background Predicting sudden cardiac death (SCD) in the general population remains a significant challenge, particularly at the individual level. SCD and myocardial infarction (MI) share similar pattern of characteristics and risk factors, making their specific prediction highly difficult. As a result, the current prediction models exhibit low specificity. Methods To estimate the specific risk of SCD over three months, we trained a machine learning model on electronic health record (EHR) data representing 8,566,229 drug prescriptions and 801,352 of hospital diagnoses up to five years prior to SCD. The data were obtained from a French cohort of 12,338 SCD and from a cohort of 12,338 controls from 2011 to 2015. We then validated the results on two external cohorts: one temporal cohort in the same area between 2016 and 2020 with 11,620 SCD cases and 11,620 controls and one geographical cohort from the USA with 892 SCD cases and 892 controls from 2013 to 2021. In order to address the specificity of our prediction model for SCD, SCD cases collected between 2016 and 2020 were also matched with a group of 35 000 controls who had myocardial infarction, with no SCD, following the same protocol as for the controls issued from the general population. Findings: The analysis reveals three distinct patterns of distribution for SCD cases, controls, and MI cases. We observed a semi linear increase of SCD cases over the deciles of predicted risk, and our model detected 24% (2,908) of SCD cases with a predicted risk exceeding 90% (highest decile). We observed the opposite among the controls that decreased linearly with increasing deciles of predicted risk: most of the controls were accurately identified in the lowest deciles, and there were only 214 controls (2%) in the highest decile. Interestingly, we observed a relatively stable distribution of MI cases across the deciles, with 10% of MI cases in the highest decile (Figure 1). Interpretation: We developed and validated a personalized prediction model that is able to identify subjects at high-risk for SCD specifically. Figure 1: Histogram of predicted risks for sudden cardiac death cases, controls and myocardial infarction cases in the validation cohort.Figure 1

Heparin does not improve myocardial glucose metabolism suppression in patients with low betahydroxybutyrate level

Abstract Background/introduction Inadequate myocardial glucose metabolism suppression (GMS) can hamper diagnostic PET/CT imaging with [18F]FDG. β-hydroxybutyrate level (BHB) measurement prior to [18F]FDG injection is a newly proposed method of pre-evaluation of adequate GMS. However, more knowledge is needed, if BHB can be used to guide the preparation protocol (diet, fasting or premedication). Purpose The aim of our study was to evaluate if point-of-care measured BHB can be used to guide use of heparin premedication for cardiac [18F]FDG-PET/CT. Methods 139 patients [78 male, median age 58 (19-78) years] with clinical indication for cardiac [18F]FDG PET/CT were recruited. All patients had followed a high fat, low carbohydrate diet for one day and fasted for at least twelve hours. For the first 64 patients, BHB was measured, but it was not used to guide premedication. For the next 75 patients, iv. heparin 50 IU/kg was injected 15-20 minutes before FDG injection, if BHB was low (less than 0.35 mmol/l), whereas those with high BHB (more than 0.35 mmol/l) continued without heparin. [18F]FDG uptake pattern was evaluated visually using grades "no uptake", "focal uptake", "isolated lateral wall uptake", "basal ring", "diffuse uptake" and "focal on diffuse". "No uptake" and "focal uptake" were considered as adequate GMS. Statistical significance of the difference in uptake patterns was evaluated using the Pearson’s chi-square test. Results Median BHB was 0.4 (0.1-5.8) mmol/l. Half of the patients (76, 55 %) reached BHB higher than 0.35 mmol/l. Still, 102 patients (74 %) had adequate GMS. In high BHB group, 65 patients (86 %) had adequate GMS, whereas of those with low BHB, only 37 patients (59 %) had adequate GMS (p<0.001). In low BHB group prevalence of inadequate GMS was comparable in patients with and without heparin (42 % vs. 41 %, p=0.941) Results for the whole scale of visual distribution patterns can be seen in figure 1. Conclusion(s) Patients with high BHB have a high percentage of adequate GMS, whereas in patients with low BHB the probability of adequate GMS is significantly lower. Unfractionated heparin does not seem to improve myocardial GMS in patients with low BHB. Thus, high BHB should be pursued, and a longer diet might be needed for those with low initial BHB.

Invasive quantitative assessment of coronary microvascular dysfunction in patients with hypertrophic cardiomyopathy

Abstract Background Patients (P) with hypertrophic cardiomyopathy (HCM) commonly suffer from coronary microvascular dysfunction (CMD) - the affection of function/structure of the coronary microvasculature. Invasive assessment of CMD through thermodilution methods allows for the calculation of coronary flow reserve (CFR) and index of microvascular resistance (IMR). These methods, while extensively studied in the context of non-obstructive coronary artery disease and myocardial infarction, have not been thoroughly validated in HCM P. Objectives To invasively assess the presence of CMD in P with HCM and to determine clinical predictors of invasively assessed CMD. Methods In a prospective single-centre study, we opportunistically recruited consecutive adult P with an established diagnosis of HCM with or without LVOTO that had an indication to pursue elective coronarography – such as pre-procedural evaluation for alcoholic septal ablation (ASA) or exclusion of epicardial coronary artery disease. P characteristics and coronary hemodynamic invasive assessment data were extracted. CFR was calculated as the ratio between resting and hyperemia mean transit times (TmnRest;TmnHyper). IMR was calculated as the ratio between distal coronary pressure (Pd) and the inverse of TmnHyper (IMR=Pd/TmnHyper-1). A cutoff of ≤22.0 in IMR, an ≥d 2 in CFR was used. We excluded P with end-stage HCM (LV EF <50% and/or or left ventricular wall thinning), or with epicardial coronary artery disease. Continuous variables were reported as mean ± SD or median and IQR depending on data distribution pattern and categorical data as frequencies and percentages. A linear regression model was used to test predictors of IMR and CFR involvement. Results 25 HCM P with a mean age of 63±10 years were included, 14 (56%) were female. In 20 (80%) of the P the cause for coronary angiography was ASA. All P referred for ASA had LVOTO and were on beta-blocker therapy (Table 1.). Median CFR was 2.5 [1.5-3] and median IMR was 19 [14-22], both within normal range. A total of 13 (44%) P had a reduced CFR and 5 (20%) of P had an increased IMR. 14 P (56%) had an altered CFR or IMR value, with the presence of a functional CMD phenotype in 10 P (40%) (Table 2). Angina was associated with a higher IMR (5.3, 95% CI - 0.05-10, p=0.053) and for each +1 increase in CCS a larger increase in the likelihood of a higher IMR was observed (CCS 1, +7 (95%CI 0.68 – 14); CCS 2, +9 (95%CI 4 – 14); CCS 3, 10 (95%CI 2 – 18)). A similar but non significant trend was observed for higher CCS correlating with lower CFR (Table 3). Conclusion In a prospective cohort of HCM P submited to invasive angiographic evaluation 56% had at least one invasive measure compatible with CMD. Angina, and a higher degree of anginal symptoms correlated positively with the presence of higher IMR and therefore with a higher level of CMD. In the future, we intend to correlate these findings with multimodality imaging/clinical outcomes.Patient characteristics and LR results

Impact of land-use change on coupling coordination degree of regional water–food–carbon system

IntroductionThe objective of this study is to investigate the impact of land use changes on the coupling coordination of the regional water-food-carbon system in Hebei Province. Moreover, the findings aim to offer insights for achieving comprehensive and coordinated development of regional resources.MethodsBy constructing an evaluation index system of the coupled coordinated development of the water-food-carbon system, using the coupled coordination model to study the coupled coordination of the water-food-carbon (WFC) system in Hebei Province from 2010 to 2020, and applying the Pearson correlation coefficient and ArcGIS to analyze the impacts of land-use changes on the degree of coupled coordination.ResultsThe results show that: (1) The most notable characteristics of land type changes include a decrease in cropland and an increase in construction land, primarily driven by the conversion of cropland to construction sites. The total area converted amounts to 8207.20 km2. (2) The degree of coupled coordination of the water-food-carbon system in the study area as a whole shows an upward and then downward trend, and shows a spatial distribution pattern of “high in the north-east and low in the south-west”; (3) In Hebei Province, the degree of coupling coordination within the water-food-carbon system exhibits a stable positive correlation with forest land, grassland, and water area. Additionally, the transfer of forest land and grassland are significant factors influencing the delineation of cold and hot spots within the region.DiscussionTherefore, in addressing the coordinated development of the water-food-carbon system, it is essential to consider the influence of land. Resources should be allocated judiciously based on regional advantages to promote sustainable development effectively.

Resilience Assessment and Influencing Factors Analysis of Water Security System in the Yellow River Basin

The assessment and regulation of water security system resilience (WSSR) are important ways to alleviate water resource crises. On the basis of the three characteristics of resilience, namely, resistance, restoration, and adaptability, an evaluation index system of the WSSR was built for the Yellow River Basin (YRB). A projection pursuit model based on the sparrow search algorithm (SSA-PP model) was constructed to assess the WSSR at the overall and provincial scales from 2009 to 2022. The factors influencing the spatial distribution patterns of WSSR was identified through factor detector and interactive detector techniques. The results revealed that: (1) From 2009 to 2022, the YRB exhibited a rising trend in WSSR, with the western region attaining the peak level, and the eastern region recording the lowest magnitude. (2) the adaptability capacity of most provinces and regions in the YRB tended to decrease to about 1.0, whereas the resistance and restoration capacities tended to increase towards 2.0. (3) Factors relevant to the restoration and adaptability subsystems, such as the development and utilization ratio of water resources and surface water resources (B2 and B3), water resource load index (C1), water consumption per 10,000 yuan of GDP (C8), and total precipitation (A1), significantly affected the WSSR. The interaction between factors exhibited significant enhancement effects on explanatory. Therefore, targeted countermeasures and recommendations were provided to improve the WSSR in the YRB.

Characteristics of Microbial Diversity and Metabolic Versatility in Dynamic Mid-Okinawa Trough Subsurface Sediments

Large-scale and multi-sample datasets have revealed that microbial diversity and geographic distribution patterns are distinct across various habitats, particularly between hydrothermal vent and cold seep ecosystems. To date, our understanding of the effects of spatial and geochemical gradients on marine microbial communities remains limited. Here, we report the microbial diversity and metabolic versatility of a remote seafloor sediment ecosystem at different sites (GC-2, -4, -5, -6, -8) in the Mid-Okinawa Trough (Mid-OT) using high-throughput metagenomic sequencing technology. Desulfobacteraceae (3.1%) were detected in a high abundance at GC-2 with intense methane concentrations (353 μL/L), which showed a clear correlation with cold seeping. Whereas Candidatus Brocadiaceae (1.7%), Rhodobacteraceae (0.9%), and Rhodospirillaceae (0.7%), which are commonly involved in denitrification and sulfur oxidation, were enriched at GC-8. Concurrently investigating the potential of deep-sea microbial metabolism, we gained insights into the adaptive capabilities and metabolic mechanisms of microorganisms within seafloor environments. Utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, the analysis of functional modules revealed a significant enrichment (71–74%) of genes associated with metabolic pathways. These results expand our knowledge of the relationship between microbial biodiversity and metabolic versatility in deep-sea extreme environments.

Identification of new instances of white matter hyperintensities in patients following TAVI (from the CAPITA study)

Abstract A third of patients diagnosed with symptomatic severe aortic valve stenosis and scheduled for transcatheter aortic valve implantation (TAVI) exhibit some level of cognitive impairment. The prospective CAPITA study aimed to systematically evaluate the impact of TAVI on cerebral and cognitive outcomes in patients undergoing the procedure. In this report, we focus on the identification of new incidence of white matter hyperintensities (WMH) and the correlation with changes in cognitive functioning. The CAPITA (CArdiac OutPut, Cerebral Blood Flow and Cognition In Patients With Severe Aortic Valve Stenosis Undergoing Transcatheter Aortic Valve Implantation) study is a prospective study of cerebral and cognitive outcomes following TAVI. Patients underwent magnetic resonance imaging (MRI) and extensive neuropsychological testing at baseline and three month follow-up. New cerebral infarcts were defined according to NeuroARC criteria. We examined the incidence of new WMH in terms of volume (Δ mL) and number on FLAIR MRI, and explored the correlation between new WMH and cognitive functioning. A total of 148 patients were included who underwent TAVI between August 2020 and October 2022. Mean age was 80.5±5.7 years, of whom 43% female with a median STS-PROM of 2.0% (IQR 1.4%-2.9%). Median baseline WMH comprised 127 (IQR 32-216) lesions, with a total volume of 13.1 (IQR 7.0-24.6) mL. At 3 months follow-up, the number of lesions increased to 164 (IQR 121-301) lesions, with a total volume of 13.3 (IQR 5.8-21.5) mL. Median WMH volume increase was 0.1 (IQR 0.0-0.3) ml (p=0.02). A total of 9 patients (9.5%) had an increase of 1 mL of WMH or more. At follow-up, 12% of patients exhibited cognitive decline of >0.5SD. These patient tended to have a greater increase in white matter hyperintensity volume (1.26±2.96 ml), compared to the 53% of patients with stable cognition (0.29±0.45 ml) and the 36% of patients with improved cognition (0.31±0.91 ml), (p=0.06). WMH lesions did not exhibit distribution patterns across various locations within the groups characterized by declined, stable, or improved cognition (Figure 1). WMH volumes were higher in patients who experienced postprocedural delirium than in patients without delirium (27.1±14.0 vs 15.0±12.5 mL, p<0.001). In this study, patients with severe symptomatic aortic valve stenosis undergoing TAVI, there was an overall increase of white matter hyperintensity volume between baseline and 3-month follow-up. Up to 12% of patients had cognitive decline, which was associated with new white matter hyperintensities on MRI.

Prevalance and impact of concomitant atrial fibrillation in patients undergoing percutaneous coronary intervention for acute myocardial infarction

Abstract Introduction Atrial fibrillation (AF) is a common cardiac arrhythmia associated with coronary artery disease (CAD) and myocardial infarction (MI). The prevalence of AF in patients following acute MI varies, with conflicting evidence on its impact on outcomes. Concomitant atrial fibrillation is associated with an adverse prognosis in patients with acute myocardial infarction (MI). However, it remains unclear whether this is due to a causal effect of AF, or whether AF acts as a surrogate marker for comorbidities in this population Also, there are limited data on whether coronary artery disease distribution impacts the risk of developing AF. Purpose This large cohort study aims to determine the prevalence of AF in acute MI patients treated with PCI, assess its independent prognostic value for MACCE, investigate the association of AF with CAD distribution patterns, and provide insights into the long-term outcomes of AF in this patient population. Methods A cohort of 1000 consecutive MI patients treated with PCI was retrospectively analyzed. Data on demographics, medical history, presentation, treatment, and outcomes was collected. Propensity score matching was used to adjust for baseline differences between AF and non-AF groups. CAD distribution, major adverse events, and MACCE were assessed using statistical analyses. Results Amongst the studied population, 6.5% people had AF (65/1000) and it was noted that those with AF had a worse outcome. However, on statistical analyses (both on multivariable cox and propensity matching) accounting for risk factors, outcomes were not significantly different between those with and without AF. Hence, this negated key baseline differences between AF and non-AF groups, with no significant differences in demographics or presentation. Patients with AF had a higher prevalence of severe CAD in the left main stem (LMS) and left circumflex artery (LCx). The association of AF with MACCE was not significant in the matched groups. Long-term follow-up revealed similar rates of MACCE between AF and non-AF groups. Discussion AF in acute MI patients undergoing PCI is associated with a higher prevalence of severe CAD in the LMS and LCx. AF appears to be a surrogate marker of other risk factors, rather than an independent risk factor for MACCE. The study highlights the need for tailored aggressive treatment for risk factor modification in AF patients with MI. Conclusions AF is associated with an increased risk of MACCE in acute MI patients undergoing PCI. However, this association is primarily driven by the burden of comorbidities associated with AF, emphasizing the importance of tailored treatment strategies for AF patients. Prospective studies with routine ambulatory monitoring are recommended to validate these findings and guide future practice.

Seroprevalence and associated factors of toxoplasmosis in female children and adolescents in Germany

Abstract Background Toxoplasmosis is a parasitic disease that causes a high burden of disease worldwide. Infections occur mainly through the consumption of undercooked meat or the ingestion of contaminated cat feces from the environment. In Germany, seroprevalence in adults is exceptionally high by international comparison (50%), which could be due to the frequent consumption of raw pork products. Comparable analyses for children and adolescents are missing but are needed to estimate the public health problem and to suggest countermeasures. Methods As part of the second wave of the representative German Health Interview and Examination Survey for Children and Adolescents (2014-2017), serum of 1,453 girls aged 3 to 17 years was tested for the presence of T. gondii IgG antibodies using enzyme linked fluorescence assay (ELFA). We calculated overall and stratified seroprevalence and used multivariable logistic regression models based on Directed Acyclic Graphs to identify associated factors. Adjusted odds ratios (aOR) with 95% confidence intervals (CI) are being reported. Results Overall, 94 out of 1,453 girls tested positive for T. gondii resulting in a seroprevalence of 6.3% (95% CI: 4.7-8.0). With each year of life, the chance of being seropositive increased significantly by 1.2 (95% CI 1.1-1.3). A low social status (aOr 2.7; 95% CI 1.3-5.9) and living in rural (aOR 2.6; 95% CI 1.1-5.7) or urban (aOR 2.2; 95% CI 1.1-4.4) areas were found to be associated with seropositivity. No regional distribution patterns or differences between vegetarians and non-vegetarians were seen. Conclusions Six out of 100 girls become infected with T. gondii during the first 18 years of life. Independent risk factors identified in our study have also been associated with seropositivity in other countries. Meat consumption appears to have a reduced impact on the risk of infection in children and adolescents compared to adults, calling for different prevention strategies in this population. Key messages • Toxoplasmosis causes a high infection pressure for girls and young women in Germany. • Transmission pathways might differ between age groups with more environmentally associated infections in children and adolescents.

MSMTRIU-Net: Deep Learning-Based Method for Identifying Rice Cultivation Areas Using Multi-Source and Multi-Temporal Remote Sensing Images.

Identifying rice cultivation areas in a timely and accurate manner holds great significance in comprehending the overall distribution pattern of rice and formulating agricultural policies. The remote sensing observation technique provides a convenient means to monitor the distribution of rice cultivation areas on a large scale. Single-source or single-temporal remote sensing images are often used in many studies, which makes the information of rice in different types of images and different growth stages hard to be utilized, leading to unsatisfactory identification results. This paper presents a rice cultivation area identification method based on a deep learning model using multi-source and multi-temporal remote sensing images. Specifically, a U-Net based model is employed to identify the rice planting areas using both the Landsat-8 optical dataset and Sentinel-1 Polarimetric Synthetic Aperture Radar (PolSAR) dataset; to take full into account of the spectral reflectance traits and polarimetric scattering traits of rice in different periods, multiple image features from multi-temporal Landsat-8 and Sentinel-1 images are fed into the network to train the model. The experimental results on China's Sanjiang Plain demonstrate the high classification precisions of the proposed Multi-Source and Multi-Temporal Rice Identification U-Net (MSMTRIU-NET) and that inputting more information from multi-source and multi-temporal images into the network can indeed improve the classification performance; further, the classification map exhibits greater continuity, and the demarcations between rice cultivation regions and surrounding environments reflect reality more accurately.

Deep learning modeling of RNA ac4C deposition reveals the importance of plant alternative splicing.

The N4-acetylcytidine (ac4C) modification has recently been characterized as a noncanonical RNA marker in plants. While the precise installation of ac4C sites in individual plant transcripts continues to present challenges, the biological roles of ac4C in specific plant species are gradually being deciphered. Herein, we utilized a deep learning technique called iac4C (intelligent ac4C) to predict ac4C sites in mRNA. ac4C deposition was effectively forecasted by the iac4C model (AUROC = 0.948), revealing a reliable distribution pattern primarily situated in the transcribing area as opposed to regions that are not translated. The iac4C deep learning approach using a combination of BiGRU and self-attention mechanisms both validates previous studies showing a positive correlation between ac4C and RNA splicing in plant species and reveals new examples of other splicing events associated with ac4C. Our advanced deep learning algorithm for analyzing ac4C enables swift identification of important biological phenomena that would otherwise be challenging to uncover through traditional experimental approaches. These findings provide insight into the essential regulatory function of site-specific ac4C deposition in alternative splicing processes. The source code and datasets for iac4C are available at https://github.com/xlwei507/iac4C .