Variability In Size Research Articles

The relationship between body size and diet breadth in non‐web building spiders

Abstract The handling hypothesis assumes that large animals have broader diets than small animals because small animals are restricted to small prey while large animals can handle both small and large prey. On the other hand, the optimal foraging hypothesis assumes no relationship between predator body size and diet breadth because large predators should shift from small prey to large prey to maximize the net energy intake. Using the diets and body sizes of 89 non‐web building spider species obtained from public databases (World Spider Trait database, Spiders of Europe and World Spider Catalogue), we investigated the relationship between body size and diet breadth in this group of terrestrial arthropod predators. We found that the taxonomic niche diet breadth measured by Hill numbers (i.e., prey richness, Shannon index of diversity and Simpson index of equitability) had no significant relationship with spider body size. The minimum prey size did not show any relationship with spider body size. On the other hand, mean, maximum, range and variability in prey size increased with spider body size. The results provide support for both hypotheses. The pattern in prey taxonomic dimension supports the optimal foraging hypothesis, while the pattern in prey size dimension supports the handling hypothesis. Overall, the observed distinct patterns between the taxonomic and prey size niche axes can be caused by the fact that the non‐web building spiders utilize similar prey types that are however highly size‐structured.

Comparative analysis of vision transformers and fine-tuned transfer learning models for brain tumor classification

Brain tumors are a primary factor causing cancer-related deaths globally, and their classification remains a significant research challenge due to the variability in tumor intensity, size, and shape, as well as the similar appearances of different tumor types. Accurate differentiation is further complicated by these factors, making diagnosis difficult even with advanced imaging techniques such as magnetic resonance imaging (MRI). Recent techniques in artificial intelligence (AI), in particular deep learning (DL), have improved the speed and accuracy of medical image analysis, but they still face challenges like overfitting and the need for large annotated datasets. This study addresses these challenges by presenting two approaches for brain tumor classification using MRI images. The first approach involves fine-tuning transfer learning cutting-edge models, including SEResNet, ConvNeXtBase, and ResNet101V2, with global average pooling 2D and dropout layers to minimize overfitting and reduce the need for extensive preprocessing. The second approach leverages the Vision Transformer (ViT), optimized with the AdamW optimizer and extensive data augmentation. Experiments on the BT-Large-4C dataset demonstrate that SEResNet achieves the highest accuracy of 97.96%, surpassing ViT’s 95.4%. These results suggest that fine-tuning and transfer learning models are more effective at addressing the challenges of overfitting and dataset limitations, ultimately outperforming the Vision Transformer and existing state-of-the-art techniques in brain tumor classification.

Morphological and Optical Profiling of Melanocytes and SK-MEL-28 Melanoma Cells Via Digital Holographic Microscopy and Quantitative Phase Imaging.

Melanoma, which originates from pigment-producing melanocytes, is an aggressive and deadly skin cancer. Despite extensive research, its mechanisms of progression and metastasis remain unclear. This study uses quantitative phase imaging via digital holographic microscopy, Principal Component Analysis (PCA), and t-distributed Stochastic Neighbor Embedding (t-SNE) to identify the morphological, optical, and behavioral differences between normal melanocytes and SK-MEL-28 melanoma cells. Our findings reveal significant differences in cell shape, size, and internal organization, with SK-MEL-28 cells displaying greater size variability, more polygonal shapes, and higher optical thickness. Phase shift parameters and surface roughness analyses underscore melanoma cells' uniform and predictable textures. Violin plots highlight the dynamic and varied migration of SK-MEL-28 cells, contrasting with the localized movement of melanocytes. Hierarchical clustering of correlation matrices provides further insights into complex morphological and optical relationships. Integrating label-free imaging with robust analytical methods enhances understanding of melanoma's aggressive behavior, supporting targeted therapies and highlighting potential biomarkers for precise melanoma diagnostics and treatment.

Comparison of magnification corrected optic disc size by slit-lamp biomicroscopy, fundus photography, and optical coherence tomography

Abstract PURPOSE: Optic disc size measurement is essential for determining landmarks, lesions, and distances of the retina. Due to the size variability in nature and when measured with different instruments, newer methods to compare sizes between different instruments are needed. We aimed to determine the comparability of slit lamp, fundus photography, and optical coherence tomography (OCT) measurements of optic disc size after correcting for both ocular and instrument magnification. MATERIALS AND METHODS: In this prospective, observational study, optic disc size was measured by slit-lamp biomicroscopy, fundus photography, and OCT. Instrument and ocular magnification was calculated, and the measured size was corrected for both using the Littman formula. The corrected values were analyzed using Bland–Altman plots and intra-class correlation (ICC) for agreeability and correlation, respectively. Linear regression analysis was conducted to estimate the systematic errors and interconvertibility in cases of high correlation. RESULTS: Fifty-six eyes were included for the analysis. Uncorrected and corrected values for each method had excellent correlation and agreeability (ICC absolute agreement >0.75, P < 0.01). Among magnification corrected values, slit lamp and OCT had excellent correlation and agreement (ICC consistency = 0.846, confidence interval 0.75–0.91, P < 0.01). This pair had R 2 = 0.73 on linear regression (P < 0.01). Linear regression formulas for interconverting uncorrected and corrected values for the three methods had variable accuracy (R 2 from 0.47 to 0.66). CONCLUSION: Uncorrected values of different methods for disc size measurement cannot be compared directly; they need ocular and instrument magnification correction. Among the three methods compared, the best interconvertible pairs of measurement were magnification corrected slit lamp and OCT values.

Differentiating Postural and Kinetic Tremor Responses to Deep Brain Stimulation in Essential Tremor.

While deep brain stimulation (DBS) targeting the ventral intermediate nucleus (VIM) of thalamus or posterior subthalamic area (PSA) can suppress forms of action tremor in people with Essential Tremor, previous studies have suggested postural tremor may respond more robustly than kinetic tremor to DBS. In this study, we aimed to more precisely quantify the (1) onset/offset dynamics and (2) steady-state effects of VIM/PSA-DBS on postural and kinetic tremor. Tremor data from wireless inertial measurement units were collected from 11 participants with ET (20 unilaterally assessed DBS leads). Three postural hold tasks and one kinetic task were performed with stimulation turned off, in 2-min intervals after enabling unilateral DBS at the clinician-optimized DBS setting (15 min), and in 2-min intervals following cessation of DBS (5 min). At baseline, kinetic tremor had significantly higher amplitudes, standard deviation, and frequency than postural tremor (P < 0.001). DBS had a more robust acute effect on postural tremors (54% decrease, P < 0.001), with near immediate tremor suppression in amplitude and standard deviation, but had non-significant improvement of kinetic tremor on the population-level across the wash-in period (34% decrease). Tremor response was not equivalent between wash-in and wash-out timepoints and involved substantial individual variability including task-specific rebound or long wash-out effects. Programming strategies for VIM/PSA-DBS should consider the individual temporal and effect size variability in postural versus kinetic tremor improvement. Improved targeting and programming strategies around VIM and PSA may be necessary to equivalently suppress both postural and kinetic tremors.

Variability and temporal stability of throughfall along a hillslope

Tree species composition, tree size, and microclimate can vary along hillslopes in forest ecosystems. This will affect the amount of throughfall (TF) that reaches the ground. However, few studies have focused on the effects of topography on the spatio-temporal variability of throughfall. We therefore, measured throughfall on a steep hillslope roughly 110 m long covered by European beech trees (Fagus sylvatica) in the Re della Pietra experimental catchment, Tuscany Apennines, Central Italy. Although the trees all have a similar age, the basal area, Plant Area Index (PAI), and canopy cover are higher on the lower part of the hillslope than the upper part of the hillslope. We installed 49 throughfall collectors in two 144 m2 square grids: one on the lower hillslope and one on the upper hillslope. In addition, we installed 29 collectors on a transect connecting the lower and upper grid. Throughfall was measured from all collectors at an approximately monthly interval and compared with gross precipitation (GP) measured in a nearby open area. The overall a TF/GP ratio for the 61 manual measurements during the period from July 2020 to September 2023 study period was 70 ± 3.4 %. It was higher for the growing season (71 ± 4.0 %) characterised by higher rainfall intensities than the dormant season (69 ± 2.7 %). TF/GP was lower for the lower grid than the upper grid (61 ± 5.1 vs 73 ± 6.0 % of GP, respectively). The differences between the measurements at the lower and upper grid were significant for almost all measurement days and reflect the differences in tree size and stand density. Temporal stability analysis indicated a high persistence of the spatial TF pattern for both grids, especially in the dormant season. The higher temporal stability for in the upper grid seems to be related to the lower variability in tree size. Although these results need to be confirmed by larger-scale studies at different hillslopes, they suggest that topographic differences in stand characteristics should be taken into account when determining the water balance for forested catchments.

Association between perioperative platelet distribution width changes and postoperative acute kidney injury in patients with renal insufficiency: a retrospective study

BackgroundAcute kidney injury (AKI) is a major complication following cardiac surgery with a high incidence in those with existing kidney dysfunction. Platelet distribution width (PDW) reflects variability in platelet size and serves as an indicator of platelet activation. Recent investigations linked PDW changes to kidney pathology, suggesting its utility in identifying individuals at risk for AKI, thus necessitating exploration of its predictive value.MethodsPatients with preoperative renal dysfunction [15 ≤ estimated glomerular filtration rate (eGFR) < 60 ml/min/1.73m2] who underwent cardiac surgery from January 2018 to December 2021 were retrospectively enrolled. PDW values were measured preoperatively and again upon admission to the ICU immediately after cardiac surgery, with the change in PDW (dPDW) defined as the difference between these two measurements. The primary outcome was postoperative AKI, defined base on the Kidney Disease: Improving Global Outcomes (KDIGO) definition and staging criteria. Multivariate regression models were performed to identify the association between dPDW and AKI and its potential trend. Restricted cubic spline analysis assessed non-linear associations between dPDW and AKI. The Youden index identified an optimal dPDW cut-off for AKI prediction. Subgroup analysis was performed to elucidate the consistency of these associations across the various subgroups.ResultsAKI occurred in 53.10% (513/966) of patients, accompanied by significant PDW increases in cases of AKI (P < 0.001). After adjusting confounders, dPDW was identified as a significant risk factor for AKI [odds ratio (OR) = 1.09, 95% confidence interval (CI): (1.02 ~ 1.16), P = 0.012]. Patients in the highest dPDW quartile (Q4) had a 195% higher AKI risk compared to those in the lowest quartile (Q1) (OR = 2.95, 95% CI:1.78 ∼ 4.90, P < 0.001). Trend analysis indicates that the risk of AKI increased with higher dPDW quartiles (P for trend < 0.001). Youden index showed that dRDW = 1.1 was identified as the optimal diagnostic cut-off value for AKI. Subgroup analyses and interaction tests showed a robust association between dPDW and AKI in all subgroups (P for interaction > 0.05).ConclusionsThis study underscored perioperative PDW changes as a significant predictor of postoperative AKI in patients with renal insufficiency, highlighting its potential in refining risk stratification and management strategies.Clinical trial numberNot applicable for this observational retrospective study.

Clinical Outcomes and Applicability of Serratus Anterior Muscle Flap With Split Thickness Skin Graft in Thin Resurfacing Reconstructive Surgeries: A Retrospective Analysis.

This retrospective study evaluates the efficacy of the serratus anterior muscle (SAm) free flap combined with a split thickness skin graft (STSG) for thin resurfacing in reconstructive surgery, presenting an alternative to pure skin perforator flaps. It analyzes 14 SAm free flap procedures performed between January 2015 and December 2023. The study cohort comprised 5 women and 9 men, aged 31-80 years, addressing defects caused by infection, malignancy, burn, and trauma, located in various body parts.The study involves harvesting the SAm flap while focusing on anatomical features such as the distinct direction of muscle fibers and the surface location of the vascular pedicle for efficient dissection. It emphasizes the anatomical advantages of the SAm flap, such as robust vascular supply, controlled flap thickness, and preservation of the long thoracic nerve, making it suitable for a range of surgical needs. Complications included STSG loss, partial necrosis, and infection, all managed effectively. Postoperative shoulder function assessment showed no significant impairment.Results demonstrated the successful application of the SAm flap in all cases, with an average flap dimension of 38.21 cm2 and pedicle length of 7.3 cm. The average operation time was 122.1 minutes. The study underscores the SAm flap's adaptability, versatility, and minimal donor site morbidity.It concludes that the SAm flap, in conjunction with STSG, is a viable alternative for thin resurfacing in reconstructive surgery. However, limitations such as the small sample size and procedural variability suggest the need for further research to fully establish the flap's potential in diverse surgical contexts.

Physiological Predictors of Operator Performance: The Role of Mental Effort and Its Link to Task Performance.

The present study investigated how pupil size and heart rate variability (HRV) can contribute to the prediction of operator performance. We illustrate how focusing on mental effort as the conceptual link between physiological measures and task performance can align relevant empirical findings across research domains. Physiological measures are often treated as indicators of operators' mental state. Thereby, they could enable a continuous and unobtrusive assessment of operators' current ability to perform the task. Fifty participants performed a process monitoring task consisting of ten 9-minute task blocks. Blocks alternated between low and high task demands, and the last two blocks introduced a task reward manipulation. We measured response times as primary performance indicator, pupil size and HRV as physiological measures, and mental fatigue, task engagement, and perceived effort as subjective ratings. Both increased pupil size and increased HRV significantly predicted better task performance. However, the underlying associations between physiological measures and performance were influenced by task demands and time on task. Pupil size, but not HRV, results were consistent with subjective ratings. The empirical findings suggest that, by capturing variance in operators' mental effort, physiological measures, specifically pupil size, can contribute to the prediction of task performance. Their predictive value is limited by confounding effects that alter the amount of effort required to achieve a given level of performance. The outlined conceptual approach and empirical results can guide study designs and performance prediction models that examine physiological measures as the basis for dynamic operator assistance.

Wood Anatomical and Demographic Similarities Between Self-Standing Liana and Tree Seedlings in Tropical Dry Forests of Colombia.

Canopy lianas differ considerably from trees in terms of wood anatomical structure, and they are suggested to have a demographic advantage-faster growth and higher survival-than trees. However, it remains unclear whether these anatomical and demographic differences persist at the seedling stage, when most liana species are self-standing and, consequently, might be ecologically similar to trees. We assessed how self-standing liana and tree seedlings differ in relation to wood anatomy, growth, and survival. We measured 12 wood traits and monitored seedling growth and survival over one year for 10 self-supporting liana and 10 tree seedling species from three tropical dry forests in Colombia. Liana and tree seedlings exhibited similar survival rates and wood anatomies for traits related to water storage and mechanical support. Yet, for traits associated with water transport, liana seedlings showed greater variability in vessel lumen size, while tree seedlings had higher vessel density. Also, the liana relative growth rate was significantly higher than for trees. These results indicate that, while self-supporting liana and tree seedlings are anatomically similar in terms of mechanical support and water storage-likely contributing to their similar survival rates-liana seedlings have a growth advantage, possibly due to more efficient water transport. These findings suggest that the well-documented anatomical and demographic differences between adult lianas and trees may depend on the liana's developmental stage, with more efficient water transport emerging as a key trait from early stages.

FPGA-Based Design of a Ready-to-Use and Configurable Soft IP Core for Frame Blocking Time-Sampled Digital Speech Signals

‘Frame blocking’ or ‘Framing’ is a technique that divides a time-sampled speech or audio signal into consecutive and equi-sized short-time frames, either overlapped or non-overlapped, for analysis. The framing hardware architectures (FHA) in the literature support framing speech or audio samples of specific word size with specific frame size and frame overlap size. However, speech and audio applications often require framing signal samples of varied word sizes with varied frame sizes and frame overlap sizes. Therefore, the existing FHAs must be redesigned appropriately to keep up with the variability in word size, frame size and frame overlap size, as demanded across multiple applications. Redesigning the existing FHAs for each specific application is laborious, prompting the need for a configurable intellectual property (IP) core. The existing FHAs are inappropriate for creating configurable IP cores as they lack adaptability to accommodate variability in frame size and frame overlap size. Therefore, to address these issues, a novel FHA, adaptable to accommodate the desired variability, is proposed. Furthermore, the proposed FHA is transformed into a field-programmable gate array-based soft, ready-to-use and configurable frame blocking IP core using the Xilinx® Vivado™ tool. The resulting IP core is versatile, offering configurability for framing in numerous applications incorporating real-time digital speech and audio systems. This research article discusses the proposed FHA and frame blocking IP core in detail.

Highlighted Diffusion Model as Plug-in Priors for Polyp Segmentation.

Automated polyp segmentation from colonoscopy images is crucial for colorectal cancer diagnosis. The accuracy of such segmentation, however, is challenged by two main factors. First, the variability in polyps' size, shape, and color, coupled with the scarcity of well-annotated data due to the need for specialized manual annotation, hampers the efficacy of existing deep learning methods. Second, concealed polyps often blend with adjacent intestinal tissues, leading to poor contrast that challenges segmentation models. Recently, diffusion models have been explored and adapted for polyp segmentation tasks. However, the significant domain gap between RGB-colonoscopy images and grayscale segmentation masks, along with the low efficiency of the diffusion generation process, hinders the practical implementation of these models. To mitigate these challenges, we introduce the Highlighted Diffusion Model Plus (HDM+), a two-stage polyp segmentation framework. This framework incorporates the Highlighted Diffusion Model (HDM) to provide explicit semantic guidance, thereby enhancing segmentation accuracy. In the initial stage, the HDM is trained using highlighted ground-truth data, which emphasizes polyp regions while suppressing the background in the images. This approach reduces the domain gap by focusing on the image itself rather than on the segmentation mask. In the subsequent second stage, we employ the highlighted features from the trained HDM's U-Net model as plug-in priors for polyp segmentation, rather than generating highlighted images, thereby increasing efficiency. Extensive experiments conducted on six polyp segmentation benchmarks demonstrate the effectiveness of our approach.

Advancements in Digital Forensics: A Quantitative Analysis of Cell Tower Triangulation Techniques

This study delves into the accuracy and reliability of Cell Tower Triangulation (CTT) in digital forensics, employing a diverse sample of mobile devices across various real-world scenarios—criminal investigations, missing persons, and corporate security breaches. By simulating these situations, the research aims to provide a comprehensive understanding of CTT’s effectiveness in urban and rural settings. Data was meticulously collected on signal strength, tower locations, and timestamps, and analyzed using statistical methods to assess CTT accuracy and reliability. Findings from descriptive statistics, comparative analyses, precision metrics, and correlation analyses reveal significant insights into CTT’s application in digital forensics. Despite certain limitations in precision, indicated by the variability in virtual triangle sizes, the study underscores the potential of CTT in supporting investigations while also highlighting the importance of ethical considerations and legal compliance. This research contributes to the advancement of digital forensics, offering a nuanced understanding of CTT’s capabilities and limitations.

Impact of pupil size and corneal spherical aberrations on the performance of monofocal intraocular lenses: an experimental model

In this study, an in vitro comparison of the optical performances of three models (spherical, aberration-neutral, and aberration-correcting) of monofocal intraocular lenses (IOLs) is proposed. A comprehensive model is employed, encompassing a wide range of corneal models and aperture sizes, reflecting the high variability of corneal spherical aberrations (SA) and pupil sizes in both normal and postoperative refractive corneal surgery populations. Analysis of average through-focus modulation transfer function (MTF) curves reveals significant differences in optical performance attributable to pupil size and corneal SA. These differences depend on the IOL model and affects MTFmax (representing contrast at best focus), depth of focus, refractive error tolerance, and the effective power of the lens.

Maintenance of inflorescence size variability within common buckwheat (Fagopyrum esculentum Moench) cultivars of various origin: the phenomenon and its possible causes

Background. Intrapopulation polymorphism usually can be interpreted as a result of balancing selection, but the basic mechanisms of such selection are not always clear. Earlier we documented a wide variation in the inflorescence size within one of the most genetically uniform common buckwheat (Fagopyrum esculentum Moench) cultivar ‘Skorospelaya 86’, with larger sizes controlled by recessive alleles of multiple genes. The objective of the present work was to analyze the variation within a set of buckwheat cultivars representing different morphological types of the crop, and try to make out possible mechanisms that underlie it. Material and methods. A set of buckwheat cultivars of various origin and belonging to different morphological types were analyzed. The size of inflorescences was assessed as a number of their iterative subunits, i.e., partial floret clusters (PFCs). The number of mature seeds in the entire inflorescence and various PFCs was also counted. Results and conclusions. All the cultivars were variable, with the range at the species level from 6 to 24 PFCs. Accumulation of the genes determining a larger inflorescence seems to be simply explained: larger inflorescences tended to produce more seeds than smaller ones. However, it is not so easy to explain the maintenance of the inflorescence size variability, i.e., why the alleles determining small inflorescences were not lost during the artificial selection for higher seed productivity. Probably, such polymorphism may be useful for maintaining heterosis at the population level.

LesionNet: an automated approach for skin lesion classification using SIFT features with customized convolutional neural network.

Accurate detection of skin lesions through computer-aided diagnosis has emerged as a critical advancement in dermatology, addressing the inefficiencies and errors inherent in manual visual analysis. Despite the promise of automated diagnostic approaches, challenges such as image size variability, hair artifacts, color inconsistencies, ruler markers, low contrast, lesion dimension differences, and gel bubbles must be overcome. Researchers have made significant strides in binary classification problems, particularly in distinguishing melanocytic lesions from normal skin conditions. Leveraging the "MNIST HAM10000" dataset from the International Skin Image Collaboration, this study integrates Scale-Invariant Feature Transform (SIFT) features with a custom convolutional neural network model called LesionNet. The experimental results reveal the model's robustness, achieving an impressive accuracy of 99.28%. This high accuracy underscores the effectiveness of combining feature extraction techniques with advanced neural network models in enhancing the precision of skin lesion detection.

Inheritance of signs of parent species by hybrids of Russet, Yellow and Speckled ground squirrels (&lt;i&gt;Spermophilus&lt;/i&gt;, Sciuridae, Rodentia)

The inheritance of size, color and bioacoustic characteristics of Russet (Spermophilus major), Yellow (S. fulvus) and Speckled (S. suslicus) ground squirrels in hybrids differing in their genetic status were studied. In a hybrid population of Russet and Yellow ground squirrels, 10 individuals of S. major, 10 individuals of S. fulvus and 40 hybrids of S. major × S. fulvus were analyzed; in a hybrid population of Russet and Speckled ground squirrels, 11 individuals of S. major, 11 individuals of S. suslicus and 24 hybrids of S. major × S. suslicus were analyzed. Hybrid individuals different in genetic status have been shown to demonstrate differentiation in the vector space of the variability range of the parental species. At the same time, both a shift in some categories of hybrids towards one of the hybridizing species and a significant deviation are noted. The results obtained indicate an increase in the level of variability in size, color and bioacoustic characters in hybrid populations, associated with the erosion of the divergent hiatus of specific features of the parental forms due to the formation of a differentiated hybrid population. As hybrid individuals with different combinations of parental traits accumulate in the population, the situation arises when a sufficient number of hybrids with an overall combination of parental traits (Hcomb) appear in the hybridogenic population. In the hybrid population of the Russet and Yellow ground squirrels, the proportion of such hybrids, according to our data, is 22.5% (n = 40), and in the hybrid population of the Russet and Speckled ground squirrels it is 12.5% (n = 24). This category of hybrid individuals can be considered as possible material for further microevolutionary events and the process of speciation.

Machine learning and deep learning models for the diagnosis of apical periodontitis: a scoping review.

To assess the existing literature on the use of machine learning (ML) and deep learning (DL) models for diagnosing apical periodontitis (AP) in humans. A scoping review was conducted following the Arksey and O'Malley framework. The PubMed, SCOPUS, and Web of Science databases were searched, focusing on articles using ML/DL approaches for AP diagnosis. No restrictions were applied. Two independent reviewers screened publications and charted data in predefined Excel tables for analysis. Nineteen publications focused on diagnosing AP by identifying periapical radiolucent lesions (PRLs) in dental radiographs were included. The average sensitivity and specificity for reviewed models were 83% and 90%, respectively. Only three studies explored the direct impact of artificial intelligence (AI) assistance on clinicians' diagnostic performance. Both consistently showed improved sensitivity without compromising specificity. Significant variability in dataset sizes, labeling techniques, and algorithm configurations was noticed. Findings affirm AI models' effectiveness and transformative potential in diagnosing AP by improving the accurate detection of periapical radiolucencies using dental radiographs. However, the lack of standardized reporting on crucial aspects of methodology and performance metrics prevents establishing a definitive diagnostic approach using AI. Further studies are needed to expand AI applications in AP diagnosis beyond radiographic analysis. AI can potentially improve diagnostic accuracy in AP diagnosis by enhancing the sensitivity of PRL detection in dental radiographs without compromising specificity.

A First-Passage Model of Intravitreal Drug Delivery and Residence Time-Influence of Ocular Geometry, Individual Variability, and Injection Location.

Standard of care for various retinal diseases involves recurrent intravitreal injections. This motivates mathematical modeling efforts to identify influential factors for ocular drug residence time, aiming to minimize administration frequency. We sought to describe the vitreal diffusion of therapeutics in nonclinical species frequently used during drug development assessments. In human eyes, we investigated the impact of variability in vitreous cavity size and eccentricity, and in injection location, on drug disposition. Using a first-passage time approach, we modeled the transport-controlled distribution of two standard therapeutic protein formats (Fab and IgG) and elimination through anterior and posterior pathways. Anatomical three-dimensional geometries of mouse, rat, rabbit, cynomolgus monkey, and human eyes were constructed using ocular images and biometry datasets. A scaling relationship was derived for comparison with experimental ocular half-lives. Model simulations revealed a dependence of residence time on ocular size and injection location. Delivery to the posterior vitreous resulted in increased vitreal half-life and retinal permeation. Interindividual variability in human eyes had a significant influence on residence time (half-life range of 5-7days), showing a strong correlation to axial length and vitreal volume. Anterior exit was the predominant route of drug elimination. Contribution of the posterior pathway displayed a 3% difference between protein formats but varied between species (10%-30%). The modeling results suggest that experimental variability in ocular half-life is partially attributed to anatomical differences and injection site location. Simulations further suggest a potential role of the posterior pathway permeability in determining species differences in ocular pharmacokinetics.

Light Microscopic and Scanning Electron Microscopic Techniques to Characterize Nutlets of Some Indian Cyperoideae (Cyperaceae) and Their Taxonomic Significance.

In the present investigation, nutlet morphological and micro-morphological characters were analyzed using Light Microscope (LM) and Scanning Electron Microscope (SEM) in 38 taxa under 13 genera from the sub-family Cyperoideae of Cyperaceae to find out whether these characters are taxonomically important or not. Nutlet morphology and surface characters of the representative taxa from all the possible tribes under the sub-family Cyperoideae namely, Fuireneae, Cypereae, Cariceae, Abildgaardieae, Eleocharideae, Pseudoschoeneae, Schoenoplecteae, and Sclerieae were evaluated for their taxonomic significance. Cluster analysis was employed considering nutlet morphological characters to determine the overall similarity among the taxa based on 153 character states. Except in few specified cases, grouping of the taxa in the clusters is in accordance to the taxonomic treatments made by recent Cyperologists. Nutlets in the tribe Abildgaardieae showed maximum level of variability in size, shape, and surface ornamentation at the level of higher taxon, but showed specificity at the species level. Tuberculate, striate-reticulate, and transversely wavy ridged surface ornamentations were found in different species of Fimbristylis. Previously described cryptic variation, and effect of different ploidy level were not reflected in nutlet surface morphology and micromorphology in Fimbristylis dichotoma and F. ovata complexes which was previously made the taxa taxonomically very difficult. Serrulate anticlinal wall in F. bisumbellata was the most unique in Fimbristylis. Species under the megadiverse genus Carex representing the tribe Cariceae showed very unique type of surface ornamentation. Surface walls of all the studied species of Carex were characterized by polygonal epidermal cells with single conical silica body (2-3 per cell in C. speciosa) of variable length and sizes. Most interestingly, in C. nubigena, presence of the central silica body and peripheral satellites was not consistent. Based on the presence and absence, two different variants under the species were identified. In C. nubigena, when silica body was present, epidermal cells were characterized by central conical silica body surrounded by variable number of satellites. The present investigation first time reports this novel nutlet surface character in C. nubigena. Among the studied characters, length and height of conical, height of apex, and width of apex are variable among Carex species. On the other hand, exclusion of the genera Schoenoplectiella and Schoenoplectus from tribe Scirpeae s.l. and placement under the tribes Pseudoschoeneae and Schoenoplecteae (respectively) was also supported by the present investigation. The present study also confirms that nutlet morphological and micro-morphological characters are useful in identification and arrangement of different taxa under the subfamily Cyperoideae of Cyperaceae. Result of the present investigation was correlated and discussed in comparative manner with the treatments of the recent past.