Variation In Diversity Research Articles

Integrated machine learning reveals aquatic biological integrity patterns in semi-arid watersheds

Semi-arid regions present unique challenges for maintaining aquatic biological integrity due to their complex evolutionary mechanisms. Uncovering the spatial patterns of aquatic biological integrity in these areas is a challenging research task, especially under the compound environmental stress. Our goal is to address this issue with a scientifically rigorous approach. This study aims to explore the spatial analysis and diagnosis method of aquatic biological based on the combination of machine learning and statistical analysis, so as to reveal the spatial differentiation patterns and causes of changes of aquatic biological integrity in semi-arid regions. To this end, we have introduced an innovative approach that combines XGBoost-SHAP and Fuzzy C-means clustering (FCM), we successfully identified and diagnosed the spatial variations of aquatic biological integrity in the Wei River Basin (WRB). The study reveals significant spatial variations in species number, diversity, and aquatic biological integrity of phytoplankton, serving as a testament to the multifaceted responses of biological communities under the intricate tapestry of environmental gradients. Delving into the depths of the XGBoost-SHAP algorithm, we discerned that Annual average Temperature (AT) stands as the pivotal driver steering the spatial divergence of the Phytoplankton Integrity Index (P-IBI), casting a positive influence on P-IBI when AT is below 11.8 °C. The intricate interactions between hydrological variables (VF and RW) and AT, as well as between water quality parameters (WT, NO3–N, TP, COD) and AT, collectively sculpt the spatial distribution of P-IBI. The fusion of XGBoost-SHAP with FCM unveils pronounced north-south gradient disparities in aquatic biological integrity across the watershed, segmenting the region into four distinct zones. This establishes scientific boundary conditions for the conservation strategies and management practices of aquatic ecosystems in the region, and its flexibility is applicable to the analysis of spatial heterogeneity in other complex environmental contexts.

Global patterns of nuclear and mitochondrial genetic diversity in marine fishes.

Genetic diversity is a fundamental component of biodiversity. Examination of global patterns of genetic diversity can help highlight mechanisms underlying species diversity, though a recurring challenge has been that patterns may vary by molecular marker. Here, we compiled 6862 observations of genetic diversity from 492 species of marine fish and tested among hypotheses for diversity gradients: the founder effect hypothesis, the kinetic energy hypothesis, and the productivity-diversity hypothesis. We fit generalized linear mixed effect models (GLMMs) and explored the extent to which various macroecological drivers (latitude, longitude, temperature (SST), and chlorophyll-a concentration) explained variation in genetic diversity. We found that mitochondrial genetic diversity followed geographic gradients similar to those of species diversity, being highest near the Equator, particularly in the Coral Triangle, while nuclear genetic diversity did not follow clear geographic patterns. Despite these differences, all genetic diversity metrics were correlated with chlorophyll-a concentration, while mitochondrial diversity was also positively associated with SST. Our results provide support for the kinetic energy hypothesis, which predicts that elevated mutation rates at higher temperatures increase mitochondrial but not necessarily nuclear diversity, and the productivity-diversity hypothesis, which posits that resource-rich regions support larger populations with greater genetic diversity. Overall, these findings reveal how environmental variables can influence mutation rates and genetic drift in the ocean, caution against using mitochondrial macrogenetic patterns as proxies for whole-genome diversity, and aid in defining global gradients of genetic diversity.

Plant and soil microbial community assembly processes across urban vacant lots

AbstractQuestionsNumerous studies on community assembly processes have been conducted in natural ecosystems. However, we know little about community assembly processes in human‐dominated urban ecosystems. Here, we asked: (1) how are the composition and functional diversity of native and exotic plant species shaped by local environment and landscape factors across urban vacant lots; and (2) how is microbial (bacterial and fungal) community composition influenced by the local environment, landscape factors, and plant species composition across urban vacant lots?LocationWe investigated 69 urban vacant lots in Yokohama, Japan.MethodsBy using a variation partitioning approach, we examined the relative importance of local environmental and landscape factors (including land use and spatial structure) in explaining variation in plant species composition and functional diversity of native or exotic species. We also explored the relative importance of local environmental and landscape factors, and plant species composition in explaining variation in microbial community composition.ResultsThe spatial structure of vacant lots determined the species composition and functional diversity of plant communities, suggesting that plant community assembly is determined by dispersal limitation. However, the functional diversity of the exotic species varied randomly, which reduced the relative importance of the spatial structure of vacant lots. Plant species composition as well as the spatial structure of vacant lots were the important drivers of the composition of soil microbial communities, despite a higher proportion of unexplained variation in their composition. Finally, we found an essential contribution of earthmoving methods in explaining the variations in both plant and microbial community composition.ConclusionPlant and microbial community composition would be largely determined by dispersal limitation across urban vacant lots. Understanding urban community assembly is critical for predicting plant and microbial communities that play an essential role in regulating urban ecosystem functioning and services.

Altitudinal Variation in Species Diversity, Distribution, and Regeneration Status of a Secondary Picea Forest in Guandi Mountain, Northern China

Altitude plays a crucial role in shaping the diversity and distribution of species in forest landscapes in mountainous regions. However, existing studies often lack comprehensive analysis of the intricate relationships among environmental factors, disturbances, and species diversity. This study aims to address this gap by thoroughly analyzing major species’ diversity, distribution, and regeneration status, along with their influencing factors, across different altitudinal gradients (1850 to 2350 m). Field surveys were conducted to examine the major species in different vegetation layers of the secondary Picea forest in Guandi Mountain. The key findings from the study include the following: (1) the study area recorded a total of nine species of adult trees, belonging to eight genera in five families, fourteen species of shrubs from eight genera in five families, and fifty-two herb species representing forty-eight genera in twenty-six families. Dominant species varied across layers, with Picea asperata Mast. and Larix principis-rupprechtii Mayr. dominating the arborous layer, Lonicera ferdinandii Franch. and Cotoneaster acutifolius Turcz. in the shrub layer, and Poa pratensis L. and Duchesnea indica (Andrews.) Focke in the herb layer. (2) Altitude significantly influenced species diversity, with the most pronounced effects observed in the shrub and herb layers. (3) Tree species regeneration varied with altitude, with Picea asperata exhibiting the highest regeneration performance, particularly in the high-altitude zone (2250–2350 m). Regeneration parameters were significantly correlated with species diversity indices in both tree and shrub layers. (4) Redundancy analysis revealed that, apart from altitude, cutting (p = 0.015) influenced the species diversity of the tree layer, while annual precipitation (p = 0.006) and temperature (p = 0.01) determined the diversity of the shrub layer. Grazing (p = 0.042) was identified as a determining factor for species diversity in the herb layer. Overall, these findings provide valuable insights into the sustainable management of forest ecosystems in the study area and offer practical guidance for forest management in similar mountainous landscapes worldwide.

ADAR Family Proteins: A Structural Review.

This review aims to highlight the structures of ADAR proteins that have been crucial in the discernment of their functions and are relevant to future therapeutic development. ADAR proteins can correct or diversify genetic information, underscoring their pivotal contribution to protein diversity and the sophistication of neuronal networks. ADAR proteins have numerous functions in RNA editing independent roles and through the mechanisms of A-I RNA editing that continue to be revealed. Provided is a detailed examination of the ADAR family members-ADAR1, ADAR2, and ADAR3-each characterized by distinct isoforms that offer both structural diversity and functional variability, significantly affecting RNA editing mechanisms and exhibiting tissue-specific regulatory patterns, highlighting their shared features, such as double-stranded RNA binding domains (dsRBD) and a catalytic deaminase domain (CDD). Moreover, it explores ADARs' extensive roles in immunity, RNA interference, and disease modulation, demonstrating their ambivalent nature in both the advancement and inhibition of diseases. Through this comprehensive analysis, the review seeks to underline the potential of targeting ADAR proteins in therapeutic strategies, urging continued investigation into their biological mechanisms and health implications.

Spatiotemporal analysis in brown seaweed diversity and abundance at selected coastal locations on the Southern coast of Tamil Nadu, India: A way forward for conservation and sustainable utilization

Tamil Nadu and its southern coast are well-known for seaweed diversity and abundant resources in India. Brown seaweeds are primary habitat producers in reef environments. The objective of this study was to assess the spatiotemporal variation in diversity and abundance of brown seaweed species along the intertidal region at selected coastal locations on the southern coast of Tamil Nadu, India. The sampling was performed monthly at six coastal locations, namely Hare Island (HI), Tuticorin Harbour (TH), Chinna Muttom (CM), Arockiapuram (AP), Vedhalai (VD), and Mandapam (MP), along the intertidal region during low tides between January 2021 and December 2021. A total of 36 brown seaweed species were identified at six locations, namely Sargassum (9 species), followed by Padina (5 species), Turbinaria (3 species), Dictyota (3 species) and 16 species each of others. In the context of different locations, the highest species diversity was observed at HI (35) and the lowest at CM (21) during the study period. The highest abundance was recorded at CM (19.80 kg wt m−2), while the lowest was reported at AP (9.51 kg wt m−2). Sargassum and Turbinaria exhibited the highest prevalence across all the locations. Among different seasons, the maximum species diversity was recorded during PoMoN (26), whereas the minimum species diversity was recorded during PrMoN (11). Similarly, the highest abundance was seen during PoMoN, whereas the lowest abundance was reported during PrMoN. These findings offer crucial foundational data for the preservation and exploitation of brown seaweeds.

Spatial and diel variations of bacterioplankton and pico-nanoeukaryote communities and potential biotic interactions during macroalgal blooms

We investigated spatial heterogeneity and diel variations in bacterioplankton and pico-nanoeukaryote communities, and potential biotic interactions at the extinction stage of the Ulva prolifera bloom in the Jiaozhou Bay, Yellow Sea. It was found that the presence of Ulva canopies significantly promoted the cell abundance of heterotrophic bacteria, raised evenness, and altered the community structure of bacterioplankton. A diel pattern was solely significant for pico-nanoeukaryote community structure. >50 % of variation in the heterotrophic bacterial abundance was accounted for by the ratio of Bacteroidota to Firmicutes, and dissolved organic nitrogen effectively explained the variations in cell abundances of phytoplankton populations. The factors representing biotic interactions frequently contributed substantially more than environmental factors in explaining the variations in diversity and community structure of both bacterioplankton and pico-nanoeukaryotes. There were higher proportions of eukaryotic pathogens compared to other marine systems, suggesting a higher ecological risk associated with the Ulva blooms.

Variations in Genetic Diversity of Invasive Species Lithobates catesbeianus in China.

The introduction and subsequent range expansion of the American bullfrog (Lithobates catesbeianus) is part of a rising trend of troublesome biological invasions happening in China. This detrimental amphibious invasive species has strong adaptability. After its introduction and spread, it established its own ecological niche in many provinces of China, and its range has continued to expand to more areas. Previous studies recorded the introduction time of bullfrogs and calculated the changes in their genetic diversity in China using mitochondria, but the specific introduction route in China is still unknown. Expanding upon previous research, we employed whole-genome scans (utilizing 2b-RAD genomic sequencing) to examine single nucleotide polymorphisms (SNPs) and microsatellites within Lithobates catesbeianus to screen the genomes of these invasive amphibian species from eight Chinese provinces and two U.S. states, including Kansas, where bullfrogs originate. A total of 1,336,475 single nucleotide polymorphic loci and 17 microsatellite loci were used to calculate the genetic diversity of bullfrogs and their migration pathways. Our results suggest that the population in Hunan was the first to be introduced and to spread, and there may have been multiple introductions of subpopulations. Additionally, the genetic diversity of both the SNP and microsatellite loci in the Chinese bullfrog population was lower than that of the US population due to bottleneck effects, but the bullfrogs can adapt and spread rapidly. This study will offer crucial insights for preventing and controlling future introductions into the natural habitats in China. Additionally, it will assist in devising more precise strategies to manage the existing populations and curtail their continued expansion, as well as aim to improve clarity and originality while mitigating plagiarism risk.

Gut microbiome is associated with personality traits of free-ranging Tibetan macaques (Macaca thibetana).

Recent studies have emphasized that there is a strong link between the gut microbiome and the brain that affects social behavior and personality in animals. However, the interface between personality and the gut microbiome in wild primates remains poorly understood. Here, we used high-throughput sequencing and ethological methods in primate behavioral ecology to investigate the relationship between gut microbiome and personality in Tibetan macaques (Macaca thibetana). The behavioral assessment results indicated three personality dimensions including socialization, shyness, and anxiety. There was significant variation in alpha diversity only for shyness, with a significantly lower alpha diversity indices (including Shannon, Chao1, and PD) for bold individuals than for shy individuals. Using regression models to control for possible confounding factors, we found that the relative abundance of three genera, Akkermansia, Dialister, and Asteroleplasma, was significantly and positively correlated with the sociability scores in the macaques. In addition, Oscillospiraceae exhibited a positive correlation with scores for Shy Dimension. Furthermore, we found that the predicted functional genes for propionate and pyruvate, porphyrin and chlorophyll metabolic pathways related to animal behavior, were significant enriched in shyness group. We propose that the gut microbiome may play an important role in the formation of personality of Tibetan macaques.

Vegetation communities and soil properties along the restoration process of the Jinqianghe mine site in the Qilian Mountains, China.

The study explores the impact of mine grassland restoration on plant communities and soil properties in alpine grasslands, a subject of significant interest due to the observed relationship between grassland changes, plant communities, and soil properties. While prior research has mainly focused on the consequences of grassland degradation on plant diversity and soil characteristics, the specific effects of varying restoration degrees in alpine mining grasslands at the regional scale remain poorly understood. To address this knowledge gap, we established 15 sampling plots (0.5m×0.5m) across five different restoration degrees within alpine mining grasslands in the Qilian Mountains, China. Our objective was to assess the variations in plant diversity and soil properties along these restoration gradients. We conducted comprehensive analyses, encompassing soil properties [soil water content (SWC), available nitrogen (AN), total phosphorus (TP), nitrate nitrogen (NO3-N), ammonium nitrogen (NH4-N), total nitrogen (TN), available phosphorus (AP), soil organic carbon (SOC), nitrate nitrogen, soil pH, and electrical conductivity (EC)], plant characteristics (height, density, frequency, coverage, and aboveground biomass), and plant diversity indices (Simpson, Shannon-Wiener, Margalef, Dominance, and Evenness indexes). Our findings included the identification and collection of 18 plant species from 11 families and 16 genera across the five restoration degrees: Very Low Restoration Degree (VLRD), Low Restoration Degree (LRD), Moderate Restoration Degree (MRD), High Restoration Degree (HRD), and Natural Grassland (NGL). Notably, species like Carex duriuscula, Cyperus rotundus, and Polygonum viviparum showed signs of recovery. Principal component analysis and Pearson correlation analysis revealed that soil pH, SWC, SOC, NO3-N, and AN were the primary environmental factors influencing plant communities. Specifically, soil pH and EC decreased as restoration levels increased, while SWC, AN, TP, NH4-N, TN, AP, SOC, and NO3-N exhibited a gradual increase with greater restoration efforts. Furthermore, the HRD plant community demonstrated similarities to the NGL, indicating the most effective natural recovery. In conclusion, our study provides valuable insights into the responses of plant community characteristics, plant diversity, and soil properties across varying restoration degrees to environmental factors. It also elucidates the characteristics of plant communities along recovery gradients in alpine grasslands.

Examining leisure constraints and motivations within the psychological continuum model: a study among recreational video gamers

ABSTRACT This study investigates perceived leisure constraints and motivations among Iranian gamers, employing the Psychological Continuum Model (PCM). Targeting recreational gamers under 30 years old, dedicating 1 to 6 hours per week to gaming, we utilised (D. Funk et al. 2008) PCM stages questionnaire, Crawford’s et al. (1991) perceived hierarchical leisure constraints questionnaire, and Cianfrone et al. (2011) motivations questionnaire. Our analysis, featuring One-way analysis of variance (ANOVA) for constraints and motivations across PCM stages and Multiple Discriminant Analysis (MDA) for psychological communication, revealed compelling insights. Results indicate a noteworthy increase in perceived constraints with PCM progression (p < 0.05), highlighting significant differences in dimensions such as interest, time involvement, facilities, cost, and interpersonal aspects (p < 0.05). Concurrently, motivations progressively rise with PCM advancement, showcasing significant variations in competition, diversion, fantasy, and social interaction dimensions (p < 0.01). This study’s significant findings illuminate the evolving landscape of constraints and motivations across distinct PCM stages, offering valuable implications for comprehending gaming behaviours within this demographic.

Patterns of Tadpole β Diversity in Temperate Montane Streams.

Understanding the spatial variation and formation mechanism of biological diversity is a hot topic in ecological studies. Comparing with α diversity, β diversity is more accurate in reflecting community dynamics. During the past decades, β diversity studies usually focused on plants, mammals, and birds. Studies of amphibian β diversity in montane ecosystems, in particular, tadpoles, are still rare. In this study, Mount Emei, located in southwestern China, was selected as the study area. We explored the tadpole β diversity in 18 streams, based on a two-year survey (2018-2019). Our results indicated a high total β diversity in tadpole assemblages, which was determined by both turnover and nestedness processes, and the dominant component was turnover. Both the total β diversity and turnover component were significantly and positively correlated with geographical, elevational, and environmental distances, but no significant relationship was detected between these and the nestedness component. Moreover, the independent contributions of river width, current velocity, and chlorophyll α were larger than that of geographical and elevational distance. Overall, tadpole β diversity was determined by both spatial and environmental factors, while the contribution of environmental factors was larger. Future studies can focus on functional and phylogenetic structures, to better understand the tadpole assembly process.

Synthetic Leaves Based on Crystalline Olefin-Linked Covalent Organic Frameworks for Efficient CO2 Photoreduction with Water.

We report, for the first time, a new synthetic strategy for the preparation of crystalline two-dimensional olefin-linked covalent organic frameworks (COFs) based on aldol condensation between benzodifurandione and aromatic aldehydes. Olefin-linked COFs can be facilely crystallized through either a pyridine-promoted solvothermal process or a benzoic anhydride-mediated organic flux synthesis. The resultant COF leaf with high in-plane π-conjugation exhibits efficient visible-light-driven photoreduction of carbon dioxide (CO2) with water (H2O) in the absence of any photosensitizer, sacrificial agents, or cocatalysts. The production rate of carbon monoxide (CO) reaches as high as 158.1 μmol g-1 h-1 with near 100% CO selectivity, which is accompanied by the oxidation of H2O to oxygen. Both theoretical and experimental results confirm that the key lies in achieving exceptional photoinduced charge separation and low exciton binding. We anticipate that our findings will facilitate new possibilities for the development of semiconducting COFs with structural diversity and functional variability.

Microbiome mapping in beef processing reveals safety-relevant variations in microbial diversity and genomic features

The microbiome of surfaces along the beef processing chain represents a critical nexus where microbial ecosystems play a pivotal role in meat quality and safety of end products. This study offers a comprehensive analysis of the microbiome along beef processing using whole metagenomics with a particular focus on antimicrobial resistance and virulence-associated genes distribution. Our findings highlighted that microbial communities change dynamically in the different steps along beef processing chain, influenced by the specific conditions of each micro-environment. Brochothrix thermosphacta, Carnobacterium maltaromaticum, Pseudomonas fragi, Psychrobacter cryohalolentis and Psychrobacter immobilis were identified as the key species that characterize beef processing environments. Carcass samples and slaughterhouse surfaces exhibited a high abundance of antibiotic resistance genes (ARGs), mainly belonging to aminoglycosides, β-lactams, amphenicols, sulfonamides and tetracyclines antibiotic classes, also localized on mobile elements, suggesting the possibility to be transmitted to human pathogens.We also evaluated how the initial microbial contamination of raw beef changes in response to storage conditions, showing different species prevailing according to the type of packaging employed. We identified several genes leading to the production of spoilage-associated compounds, and highlighted the different genomic potential selected by the storage conditions.Our results suggested that surfaces in beef processing environments represent a hotspot for beef contamination and evidenced that mapping the resident microbiome in these environments may help in reducing meat microbial contamination, increasing shelf-life, and finally contributing to food waste restraint.

Bacterial community shifts of commercial apples, oranges, and peaches at different harvest points across multiple growing seasons.

Assessing the microbes present on tree fruit carpospheres as the fruit enters postharvest processing could have useful applications, as these microbes could have a major influence on spoilage, food safety, verification of packing process controls, or other aspects of processing. The goal of this study was to establish a baseline profile of bacterial communities associated with apple (pome fruit), peach (stone fruit), and Navel orange (citrus fruit) at harvest. We found that commercial peaches had the greatest bacterial richness followed by oranges then apples. Time of harvest significantly changed bacterial diversity in oranges and peaches, but not apples. Shifts in diversity varied by fruit type, where 70% of the variability in beta diversity on the apple carposphere was driven by the gain and loss of species (i.e., nestedness). The peach and orange carposphere bacterial community shifts were driven by nearly an even split between turnover (species replacement) and nestedness. We identified a small core microbiome for apples across and between growing seasons that included only Methylobacteriaceae and Sphingomonadaceae among the samples, while peaches had a larger core microbiome composed of five bacterial families: Bacillaceae, Geodermtophilaceae, Nocardioidaceae, Micrococcaeceae, and Trueperaceae. There was a relatively diverse core microbiome for oranges that shared all the families present on apples and peaches, except for Trueperaceae, but also included an additional nine bacterial families not shared including Oxalobacteraceae, Cytophagaceae, and Comamonadaceae. Overall, our findings illustrate the important temporal dynamics of bacterial communities found on major commercial tree fruit, but also the core bacterial families that constantly remain with both implications being important entering postharvest packing and processing.

Physicochemical Variation of Water, Diversity, and Bacterial Community Structure in Post-coal Mining Ponds of Different Ages in Samarinda, East Kalimantan, Indonesia

&lt;p&gt;This study aims to determine physicochemical variation of water, diversity, and community structure of bacteria at post-coal mining ponds of various ages located in Samarinda, East Kalimantan, Indonesia. Bacteria species were identified using a metagenomic approach on the Next-Generation Sequencing (NGS) nanopore platform and analyzed using the QIIME2 pipeline. The result showed that ponds aged &amp;gt; 20 years old had better water quality compared to others &amp;lt; 5 years old. In addition, ponds &amp;gt; 20 years old had lower conductivity values (0,21-0,40 mS/cm), water temperature (29,1-30,1oC), and sulfur content (2,35-6,44 mg/L), as well as higher pH (6,57-7,61) and abundance of sulfur-oxidizing bacteria (SOB) (217-364 CFU/mL). Based on the results, ponds &amp;lt; 5 years old had water quality characterized by higher conductivity (0,27-1,29 mS/cm), water temperature (30,1-31,4 oC), and sulfur content (6,56-15,03 mg/L), lower pH (2,93-3,72), and abundance of SOB (0-38 CFU/mL). Diversity and structure of bacteria community showed that the Operational Taxonomic Unit (OTU) in post-coal mining ponds &amp;gt; 20 years old was 3819 compared to 2027 in those &amp;lt; 5 years old. Bacteria community in post-coal mining ponds &amp;gt; 20 years old consisted of 11 phyla and 45 classes, while those &amp;lt; 5 years old had 9 phyla and 38 classes. Moreover, the relative abundance of families, genera, and species at ponds &amp;gt; 20 years old was also higher. The high water quality, diversity, and community structure of bacteria at ponds &amp;gt; 20 years old showed the successful remediation of ponds water by SOB.&lt;/p&gt;

Modified Adaptive CNN for Deep Learning based Histopathological Image Analysis for Cancer Diagnosis

This research on cancer diagnosis is motivated by the need for more accurate and efficient diagnostic tools in the field of oncology. Traditional methods of histopathological examination are time-consuming and can be subject to human error. The adoption of deep learning techniques, particularly Convolutional Neural Networks (CNNs), presents an opportunity to significantly improve the precision and speed of cancer diagnosis through automated analysis of tissue samples. This research addresses current challenges, including variability in samples and limited dataset diversity, with the goal of enhancing the reliability and applicability of the developed models. The ultimate aim is to contribute to the advancement of diagnostic methodologies, providing clinicians with more reliable tools for early and accurate cancer detection and ultimately improving patient outcomes and treatment strategies. Using a modified adaptive CNN algorithm, trained on extensive pathology image datasets, the approach enhances the precision and speed of cancer cell detection in tissue samples. By utilizing these artificial intelligence tools, the diagnostic process becomes not only more accurate but also significantly expeditious. Despite the promising strides, certain challenges persist. Variability in tissue samples, limited availability of diverse datasets, and interpretability of deep learning models pose hurdles to widespread adoption. To address these challenges, this research focuses on developing robust models that can generalize well across diverse datasets. Additionally, efforts are being made to create more comprehensive and diverse datasets to improve model training. Results show accuracy exceeding 97%, sensitivity and specificity at 97% and 95%, F1 score reaching 96%, and precision at 96%.

Modified Adaptive CNN for Deep Learning based Histopathological Image Analysis for Cancer Diagnosis

This research on cancer diagnosis is motivated by the need for more accurate and efficient diagnostic tools in the field of oncology. Traditional methods of histopathological examination are time-consuming and can be subject to human error. The adoption of deep learning techniques, particularly Convolutional Neural Networks (CNNs), presents an opportunity to significantly improve the precision and speed of cancer diagnosis through automated analysis of tissue samples. This research addresses current challenges, including variability in samples and limited dataset diversity, with the goal of enhancing the reliability and applicability of the developed models. The ultimate aim is to contribute to the advancement of diagnostic methodologies, providing clinicians with more reliable tools for early and accurate cancer detection and ultimately improving patient outcomes and treatment strategies. Using a modified adaptive CNN algorithm, trained on extensive pathology image datasets, the approach enhances the precision and speed of cancer cell detection in tissue samples. By utilizing these artificial intelligence tools, the diagnostic process becomes not only more accurate but also significantly expeditious. Despite the promising strides, certain challenges persist. Variability in tissue samples, limited availability of diverse datasets, and interpretability of deep learning models pose hurdles to widespread adoption. To address these challenges, this research focuses on developing robust models that can generalize well across diverse datasets. Additionally, efforts are being made to create more comprehensive and diverse datasets to improve model training. Results show accuracy exceeding 97%, sensitivity and specificity at 97% and 95%, F1 score reaching 96%, and precision at 96%.

Synergistic variation of rhizosphere soil phosphorus availability and microbial diversity with stand age in plantations of the endangered tree species Parashorea chinensis.

Soil physicochemical properties and nutrient composition play a significant role in shaping microbial communities, and facilitating soil phosphorus (P) transformation. However, studies on the mechanisms of interactions between P transformation characteristics and rhizosphere microbial diversity in P-deficient soils on longer time scales are still limited. In this study, rhizosphere soils were collected from a pure plantation of Parashorea chinensis (P. chinensis) at six stand ages in the subtropical China, and the dynamic transformation characteristics of microbial diversity and P fractions were analyzed to reveal the variation of their interactions with age. Our findings revealed that the rhizosphere soils across stand ages were in a strongly acidic and P-deficient state, with pH values ranging from 3.4 to 4.6, and available P contents ranging from 2.6 to 7.9 mg·kg-1. The adsorption of P by Fe3+ and presence of high levels of steady-state organic P highly restricted the availability of P in soil. On long time scales, acid phosphatase activity and microbial biomass P were the main drivers of P activation. Moreover, pH, available P, and ammonium nitrogen were identified as key factors driving microbial community diversity. As stand age increased, most of the nutrient content indicators firstly increased and then decreased, the conversion of other forms of P to bio-available P became difficult, P availability and soil fertility began to decline. However, bacteria were still able to maintain stable species abundance and diversity. In contrast, stand age had a greater effect on the diversity of the fungal community than on the bacteria. The Shannon and Simpson indices varied by 4.81 and 0.70 for the fungi, respectively, compared to only 1.91 and 0.06 for the bacteria. Microorganisms play a dominant role in the development of their relationship with soil P. In conclusion, rhizosphere microorganisms in P. chinensis plantations gradually adapt to the acidic, low P environment over time. This adaptation is conducive to maintaining P bioeffectiveness and alleviating P limitation.

Impact of nitrogen fertilizer application on soil fungal diversity and maize yield variation in Shandong Province, China

Maize is one of the major crops cultivated in northern Shandong Province and contributes significantly to China's maize production, and nitrogen (N) application to the soil can have a marked impact on maize yield and soil microbial productivity. The current environmental challenge, which needs urgently to be addressed, is to effectively utilize fertilizer nitrogen to improve crop production without causing environmental stress in sustainable agroecosystems. Soil fungi can improve plant health and crop performance through improved nutrient uptake and reducing plant stress levels. How soil N influences fungal diversity and maize yield at spatial patterns remains unclear. In this study, the influences of different soil N treatments on maize yields and fungal diversity were investigated in maize fields at five N rates (from 0 to 120 kg ha−1). High-throughput sequencing of the internal transcribed spacer (ITS) region revealed that α- and β-diversities of fungi significantly increased at 80 kg N ha−1 (N80) but decreased significantly in the control (N0) and other N treatments. Variations in the NC model predicted strong fungal distribution patterns (R2 = 0.60) among all the treatments. The highest proportion of operational taxonomic units (OTUs) (68.99 %) was observed at N80. The study also found that the complexity of the co-occurrence network significantly stabilized at N80, but a decrease in network complexity was observed at N120. The study showed that, relative to the control, the addition of N to the soil significantly increased the abundance of Ascomycota at the phylum level and Chaetomium, Fusarium, and Mortierella at the genus levels, with average abundances of 5.82 %, 1.67 %, and 19.58 %, respectively. Functional ecology analysis indicated that soil N upregulated the composition of ecological fungal communities by stochastic processes. The composition of major fungal sub-communities was positively correlated with nitrogen/carbon cycling at N80. Moreover, results also indicated that the yields (3.14 t ha−1) and other agronomic effects at N80 were significantly higher than those in the other treatments. This study demonstrates that optimal nitrogen application achieves increases in both fungal diversity and yield, contributing to improved crop production and sustainability at spatial scales.