Browse Articles

Inner pace: A dynamic exploration and analysis of basketball game pace

This study aims to investigate the dynamics of basketball game pace and its influence on game outcomes through a novel intra-game segmentation approach. By employing K-means clustering on possession duration, we categorized possessions from 1,141 NBA games in the 2019–2020 season into high-frequency (HFS), low-frequency (LFS), and normal-frequency segments (NFS). A sliding window method was utilized to identify these segments, revealing distinct temporal patterns within games. To analyze the predictive value of these segments, we applied machine learning models, including Random Forest and Light Gradient Boosting Machine (LightGBM), complemented by SHapley Additive exPlanations (SHAP) for interpretability. Our findings demonstrate that HFS segments increase toward the end of each quarter, driven by rapid transitions and tactical urgency, whereas LFS segments dominate the middle phases, reflecting strategic tempo control. NFS accounts for the majority of game time but decreases as the game progresses. The LightGBM analysis highlighted the importance ranking of key performance indicators (KPIs) across different segments and revealed differences in the importance of these indicators within each segment. Compared to traditional methods, our approach provides a finer-grained analysis of game pace dynamics and offers actionable insights for optimizing coaching strategies. This study not only advances the understanding of basketball game rhythm but also establishes a robust framework for integrating machine learning and statistical models in sports analysis.

Impact of the non-ideal condition in the analysis of high voltage gain switched impedance inverter with cost perspectives

Terahertz spectroscopy for analysis of vaterite-to-calcite crystal phase transition induced by distilled water

Vaterite is a crystalline polymorph of anhydrous calcium carbonate (CaCO3), which exhibits relatively low stability compared to other two polymorphs, calcite and aragonite. Vaterite particles have properties such as large specific surface area, high porosity, and high solubility; hence, research has been made in wide range of applications from material additive to drug delivery. X-ray diffractometry (XRD) is capable of identifying polymorphs of calcium carbonate. However, depending on the base material and the installed state, it may not always be suitable for non-destructive observation. This study reveals that vaterite-to-calcite crystal phase transition degree can be quantified by the absorption spectrum in terahertz range. The vaterite concentration and the terahertz absorption peak intensity near 3.3 THz showed linearity with correlation coefficient of R2 = 0.934 in our experiment. The findings allow us to quantitatively evaluate vaterite-to-calcite crystal phase transition in non-destructive and non-invasive way.

Retraction Note: Prophylactic treatment with transdermal deferoxamine mitigates radiation-induced skin fibrosis

Drug delivery process simulation—Quantifying the conformation dynamics of paclitaxel and cremophor EL

Paclitaxel is a highly successful anti-neoplastic cancer drug. The first clinically successful paclitaxl-delivery method is a mixture with cremophor EL and ethanol, here termed the taxol micelle. Until now, molecular dynamics analysis has not been presented to quantify the structural and conformation properties of these drug molecules when interacting with each other to create this nonstandard micelle. Here we apply systematic molecular simulation and statistical analysis of paclitaxel and cremophor EL conformations based on all atom and coarse-grained approaches. The cremophor EL in the taxol micelle showed a clustering network in a 3D landscape where paclitaxel can be loaded at much higher than standard concentration with no aggregation. Paclitaxel particles within the cremophor EL cavities showed some oscillatory behaviour due to a repeated adsorption/desorption with the surrounding network. Paclitaxel conformations at the lowest energy state can be described when the side-chain phenyl rings are closer relative to the immobile core. Cremophor EL molecules reached the highest energy state when wings were fully spread and at the lowest energy state when wings were fully closed. The spiral shapes were observed to be the dominant species in the cremophor EL population. We then established reliable statistical correlations between molecular conformations and the energy states. Our reliable all atom and coarse-grained modelling approach can also be applied for effective drug design analysis using different drug delivery systems.

Impact of canny edge detection preprocessing on performance of machine learning models for Parkinson’s disease classification

Abstract This study investigates the classification of individuals as healthy or at risk of Parkinson’s disease using machine learning (ML) models, focusing on the impact of dataset size and preprocessing techniques on model performance. Four datasets are created from an original dataset: $$DS_0$$ (normal dataset), $$DS_1$$ ( $$DS_0$$ subjected to Canny edge detection and Hessian filtering), $$DS_2$$ (augmented $$DS_0$$ ), and $$DS_3$$ (augmented $$DS_1$$ ). We evaluate a range of ML models-Logistic Regression (LR), Decision Tree (DT), Random Forest (RF), Gradient Boosting (GB), XGBoost (XBG), Naive Bayes (NB), Support Vector Machine (SVM), and AdaBoost (AdB)-on these datasets, analyzing prediction accuracy, model size, and prediction latency. The results show that while larger datasets lead to increased model memory footprints and prediction latencies, the Canny edge detection preprocessing supplemented by Hessian filtering (used in $$DS_1$$ and $$DS_3$$ ) degrades the performance of most models. In our experiment, we observe that Random Forest (RF) maintains a stable memory footprint of 61 KB across all datasets, while models like KNN and SVM show significant increases in memory usage, from 5.7-7 KB on $$DS_0$$ to 102-220 KB on $$DS_2$$ , and similar increases in prediction time. Logistic Regression, Decision Tree, and Naive Bayes show stable memory footprints and fast prediction times across all datasets. XGBoost’s prediction time increases from 180-200 ms on $$DS_0$$ to 700-3000 ms on $$DS_2$$ . Statistical analysis using the Mann-Whitney U test with 100 prediction accuracy observations per model (98 degrees of freedom) reveals significant differences in performance between models trained on $$DS_0$$ and $$DS_2$$ (p-values < 1e-34 for most models), while the effect sizes measured by estimating Cliff’s delta values (approaching $$-1$$ ) indicate large shifts in performance, especially for SVM and XGBoost. These findings highlight the importance of selecting lightweight models like LR and DT for deployment in resource-constrained healthcare applications, as models like KNN, SVM, and XGBoost show significant increases in resource demands with larger datasets, particularly when Canny preprocessing is applied.

Heated-balloon ablation as a novel less invasive local treatment for bile duct strictures: A first experimental study

Background Endobiliary radiofrequency ablation (RF-A) is a promising therapeutic option for bile duct strictures. However, conventional catheter RF-A has several limitations, and its usefulness and application remain debated. This study aimed to examine the feasibility of a novel heated-balloon ablation (HB-A). Methods A prototype HB-A catheter, along with an assembly created from freshly resected porcine liver and a specific jig, was used in this study. The test HB-A setting was set in six patterns: 70°C in the target temperature with 2.5 min in the target temperature maintenance time, 70°C with 5 min, 75°C with 2.5 min, 75°C with 5 min, 80°C with 2.5 min, and 80°C with 5 min. The study outcomes included the ablation range and temperature propagation associated with HB-A. Results The lengths and depths of the ablation area were 15.8 ± 1.3 and 1.5 ± 0.1, 18.0 ± 0.7 and 2.1 ± 0.1, 18.8 ± 0.4 and 2.3 ± 0.2, 18.5 ± 0.9 and 2.5 ± 0.1, 19.8 ± 0.8 and 2.5 ± 0.1, and 20.5 ± 0.5 and 3.4 ± 0.1 mm in 70°C for 2.5 min, 70°C for 5 min, 75°C for 2.5 min, 75°C for 5 min, 80°C for 2.5 min, and 80°C for 5 min, respectively. Excessive ablation was not observed during any procedure. The temperature cutoff for achieving or not achieving the ablation effect was between 55 and 60°C for every setting. Conclusions The novel HB-A treatment has good temperature and ablation range control with high reproducibility under the same settings while preventing excessive ablation. This study paves the way for further evaluation of this procedure and its early clinical application.

Synthesis of novel spiro[chromeno[2,3-d][1,3,4]thiadiazolo[3,2-a] pyrimidines via an isatin-based three-component reaction

DNA extraction protocols for animal fecal material on blood spot cards

Background Collecting fecal samples using dry preservatives is an attractive option in large epidemiological studies as they are easy to use, cheap and independent of cold chain logistics. Here, we test four DNA extraction methods with the aim of identifying an efficient procedure to extract high-quality DNA from fecal material of canine, sheep, equine, bovine, and pig collected on dry blood spot cards, with the goal of generating good quality shotgun metagenomics datasets. Further, the suitability of Illumina shotgun metagenomic sequencing at 20 million paired-end (PE) read depth per sample was assessed on its ability to successfully characterize the taxonomic and functional aspects of the resulting fecal microbiome. Methods DNA was extracted from pig feces and mock communities collected on blood spot cards using four DNA extraction methods; two different methods of the QIAsymphony® PowerFecal® Pro DNA Kit, the ZymoBIOMICS™ DNA Miniprep Kit, and the MagNA Pure 96 DNA and Viral NA Small Volume Kit. Possible extraction bias was controlled by amplicon sequencing of mock communities. Fecal samples from canine, sheep, equine, bovine, and pig were thereafter subjected to the best performing DNA extraction method and shotgun metagenomic sequencing to determine sequencing efforts for functional and taxonomic analysis. Results The four DNA extraction methods demonstrated similar community composition in the sequenced bacterial mock community. The QIAsymphony® PowerFecal® Pro DNA Kit was identified as the DNA extraction method of choice, and the resulting DNA was subjected to shotgun metagenomic sequencing with 20million PE reads. We found that higher number of reads increased the richness of observed genera between 100,000 and 5 million reads, after which higher sequencing effort did not increase the richness of the metagenomes. As for functional analysis, the number of low abundance functions in the metagenomes of the animals’ feces increased with sequencing depth above 20 million PE reads. Conclusion Our experiments identified several methods suitable for extracting DNA from feces collected on blood spot cards. The QIAGEN’s Blood and Tissue kit on the QiaSymphony platform fulfilled the criteria of high yield, quality, and unbiased DNA, while maintaining high throughput for shotgun metagenomic sequencing. A sequencing depth of 20 million PE reads proved adequate for taxonomic estimations and identifying common functional pathways. Detecting rarer traits, however, requires more sequencing effort.

Baicalin prevents experimental autoimmune uveitis by promoting macrophage polarization balance through inhibiting the HIF-1α signaling pathway

Pacing and placing in 161-km ultramarathons: Effects of sex and age

Ultramarathons are growing in popularity, owing especially to the participation of women and masters athletes. Pacing strategy, which can vary by sex and age, is a critical variable in determining finishing place in races up to the marathon distance. Whether this is true in 161-km ultramarathons is unclear. We tested the hypotheses that pacing is a determining factor in finishing place and that pacing differs by sex and age in 161-km ultramarathons. Publicly available data from 161-km races (n = 6) were analyzed for years 2012–2022 (n = 56). Linear regression was used to analyze the proportion of time in each segment (between timing checkpoints) by place, sex, and age. In general, runners used the same percentage of their total race time in each segment independent of finishing place, sex, or age. The exception was that later finishers often ran proportionally faster at the start compared to earlier finishers. Finishing times increased with age but pacing was unaffected by age or sex. We conclude that slower finishers paced the same as faster finishers following a relatively quick start in these ultramarathons, and pacing was not consistently affected by sex or age. These findings should inform training decisions and racing strategy in 161-km ultramarathons.

Latent profiles of job demands and job resources and their association with work wellbeing among nurses in South Korea

Understanding young adults’ perceptions regarding human papillomavirus vaccination: A qualitative study

Background Over 47,000 human papillomavirus (HPV) related cancers are newly diagnosed every year in the United States, yet HPV vaccination rates are below desirable levels. Young adulthood is critical for catch-up HPV vaccination. Previous research on HPV vaccine-seeking behavior among young adults is limited, particularly in Tennessee. This study aimed to understand HPV vaccine perceptions and experiences of young adults. Methods Virtual semi-structured interviews were conducted among 18–26-year-olds at a university in Tennessee from April to May 2022 (N = 25). Interview questions were based on the Health Belief Model and previous literature with a focus on gaining in-depth insights into young adults’ perspectives regarding HPV vaccination. Inductive and deductive thematic analysis approaches were used for data analysis. Results Five major themes were identified: (1) perceptions about HPV and HPV vaccination, (2) factors that may prevent HPV vaccination, (3) role of health care providers, (4) role of family and friends, and (5) HPV vaccine promotion strategies. Participants commonly discussed lack of knowledge and awareness as a factor preventing HPV vaccine uptake. Participants described some facilitators of HPV vaccination, including healthcare provider recommendations and family support, and perceived future benefits of receiving the HPV vaccine. Suggestions for promotion strategies included promotion through college health centers, community education, and awareness campaigns. Conclusions Young adults’ perceptions about the HPV vaccine and inadequate knowledge may influence uptake. Findings from this study showed that healthcare provider recommendations and parental support were facilitators for getting vaccinated. Future efforts may consider increasing awareness among young adults, exploring barriers to recommendation, and addressing parental concerns.

Correction: Development of a novel complex inflammatory bowel disease mouse model: Reproducing human inflammatory bowel disease etiologies in mice

Exploring breast cancer awareness and screening practices amongst rural women in The Gambia: Community-based cross-sectional study

Background Breast cancer is a significant public health challenge in The Gambia, where it ranks as the second most commonly diagnosed cancer among women. Rural women face unique challenges in accessing screening services; however, evidence about their breast cancer awareness and screening uptake remains limited. This study aimed to assess breast cancer awareness and identify associated factors influencing screening uptake among rural women in The Gambia. Methods A community-based cross-sectional study was conducted among rural women in The Gambia. Using multistage sampling, we recruited 985 women from two local government authorities (response rate: 90.2%). Data were collected using a structured questionnaire administered in Kobo Toolbox. Descriptive statistics were used to summarize participant characteristics, while associations between predictors and breast cancer screening uptake were assessed using Chi-squared or Fisher’s exact test. Multivariable logistic regression was used to identify factors associated with screening uptake. Statistical significance was set at p<0.05 and adjusted odds ratios (aOR) with 95% confidence intervals were reported. Results The mean age of the study population was 32 years (standard deviation [SD]: ±12.6), with 34% aged 18–24 years. Although breast cancer awareness was high (87.7%), screening uptake was low (12.6%), primarily due to limited knowledge (58.7%), service unavailability (13.5%) and financial constraints (13.1%). Clinical breast examination was the most common screening method used (62.6%). Multivariable analysis revealed that Students (aOR=3.111, 95% CI: 1.453–6.663) and civil servants (aOR=2.778, 95% CI: 1.174–6.573) were more likely to undergo screening compared to unemployed women. Conversely, women with two (aOR=0.061, 95% CI: 0.005–0.791), three (aOR=0.075, 95% CI: 0.006–0.967), and five children (aOR=0.065, 95% CI: 0.005–0.877) were less likely to participate in screening compared to nulliparous women. Conclusion Despite the high awareness of breast cancer, screening uptake among rural women in The Gambia was notably low, primarily due to limited knowledge, service unavailability and financial constraints. There is an urgent need for targeted interventions to improve screening uptake, particularly among multiparous women in rural communities.

DASNeRF: depth consistency optimization, adaptive sampling, and hierarchical structural fusion for sparse view neural radiance fields

To address the challenges of significant detail loss in Neural Radiance Fields (NeRF) under sparse-view input conditions, this paper proposes the DASNeRF framework. DASNeRF aims to generate high-detail novel views from a limited number of input viewpoints. To address the limitations of few-shot NeRF, including insufficient depth information and detail loss, DASNeRF introduces accurate depth priors and employs a depth constraint strategy combining relative depth ordering fidelity regularization and depth structural consistency regularization. These methods ensure reconstruction accuracy even with sparse input views. The depth priors provide high-quality depth data through a more accurate monocular depth estimation model, enhancing the reconstruction capability and stability of the model. The depth ordering fidelity regularization guides the network to learn relative relationships using local depth ranking priors, reducing blurring caused by inaccurate depth estimation. Depth structural consistency regularization maintains global depth consistency by enforcing continuity across neighboring depth pixels. These depth constraint strategies enhance DASNeRF’s performance in complex scenes, making 3D reconstruction under sparse views more accurate and natural. In addition, we utilize a three-layer optimal sampling strategy, consisting of coarse sampling, optimized sampling, and fine sampling during the three-layer sampling process to better capture details in key regions. In the optimized sampling phase, the sampling point density in key regions is adaptively increased while reducing sampling in low-priority regions, enhancing detail capture accuracy. To alleviate overfitting, we proposed an MLP structure with per-layer input fusion. This design preserves the model’s detail perception ability while effectively avoids overfitting. Specifically, each layer’s input includes the output features from the previous layer and incorporates processed five-dimensional information, further enhancing fine detail reconstruction. Experimental results show that DASNeRF outperforms state-of-the-art methods on the LLFF and DTU dataset, achieving better performance in metrics such as PSNR, SSIM, and LPIPS. The reconstructed details and visual quality are significantly improved, demonstrating DASNeRF’s potential in 3D reconstruction under sparse-view conditions.

GRIN lens implantation strategies for in vivo calcium imaging using miniature microscopy

Miniature microscopy (Miniscope) has become one of the most popular and valuable neuroscience tools in the last decade. Miniscope in vivo calcium imaging during freely moving behavior has led to a number of transformative discoveries about neural coding across a large range of behaviors. The UCLA Miniscope Project is an open-source miniaturized microscopy platform that has greatly benefited the neuroscience community and led to the release of a number of different miniaturized microscopes with extended capabilities. While researchers can record from essentially any brain region through a cranial window or a gradient index of refraction (GRIN) lens, there is still a need for comprehensive protocols which describe detailed surgical procedures for successful miniaturized microscopy applications across different brain regions. Here, we provide step-by-step surgical procedures for implantation of GRIN lenses to record from a number of different brain regions including subregions in the medial prefrontal cortex (PrL, IL, DP), subregions in the hippocampus (dCA1, CA2 and vCA1), and the ventral striatum (nucleus accumbens, NAc). Moreover, we also provide surgical methods of new multi-brain regions imaging techniques developed by our group to record bilateral medial prefrontal cortex (mPFCs) or simultaneously record mPFC and NAc. Taken together, this protocol details easy and reproducible techniques for GRIN lens implantation and miniaturized microscopy in multiple structures.

Spatio-temporal distribution of Crimean-Congo Hemorrhagic Fever and its relationship with climate factors in Pakistan: A decade-long experience from tertiary care laboratory network

Pakistan is at high-risk for Crimean-Congo Hemorrhagic Fever (CCHF) outbreaks due to its geographic location and disease burden in bordering countries. We aimed to study the spatio-temporal distribution of human CCHF cases in Pakistan and to observe its correlation with temperature, precipitation and seasonal variation. Retrospective data of test requests generated for CCHF at country-wide patient sample collection points (n = 307) across Pakistan from 2012 to 2023 was extracted for analysis. Average monthly temperature and precipitation data was used in the Poisson regression method to examine the effect on the number of cases. A total of 2,559 patients were clinically suspected of CCHF in 39 cities with 547 confirmed positive for CCHF in 10 cities using real-time PCR assay, with a positivity rate of 21.37% and a male predominance (84.6%). Most of the confirmed cases (57.6%, n = 315) were detected between 2016 and 2019 while 97.4% (n = 533) detected in 3 cities. Highest number of cases were reported during summer (p < 0.001) with 41.13% of confirmed cases reported in the months of August and September. A positive correlation of suspected cases with temperature was observed in Karachi and Quetta with a lag of zero months (p = 0.000), and a negative correlation was observed with precipitation for Karachi and Peshawar with a lag of 2 months (p = 0.000). Case fatality rate for CCHF patients admitted at Aga Khan University Hospital was 45.8%. CCHF is on the rise in Pakistan. Positive cases are concentrated within 3 cities where human and animal migration rates are high. Outbreak situations occur when multiple factors coincide. Seasonal and climatic patterns can be used as predictors of disease by policymakers for strict implementation on animal regulation, transport, and surveillance of animal migration to curtail outbreak situations in Pakistan.

Impact of cardiosphere-derived cells on the maladapted right ventricular muscle in a rat sugen/hypoxia model of pulmonary hypertension with right ventricular dysfunction

Background and aims With pulmonary arterial hypertension (PAH), right ventricular (RV) function is a major determinant of survival. Despite current therapies, maladaptive changes ensue in the RV muscle of PAH patients, culminating in RV dysfunction and failure. The aims of the study were to evaluate the impact of intra-coronary (IC) cardiosphere-derived cells (CDCs) in attenuating the maladaptive pathobiology in the RV muscle and evaluating mechanisms underlying improvements in RV function. Methods Two groups of the Sugen/Hypoxia rat model of PAH, exhibiting significantly reduced RV function, via TAPSE measurements, received either intracoronary infusion of CDCs or PBS placebo. Immunohistochemistry methods were used to assess RV pathobiological changes. Additionally, advanced proteomics were employed to examine protein signaling pathways and upstream regulators. Results RV muscle capillarity was significantly reduced in the PAH rats while RV muscle fibrosis was increased. IC CDCs significantly increased RV muscle capillarity back to levels noted in healthy rats and reduced RV free wall fibrosis. Further, a significant reduction in iNOS+ (M1) macrophages was also observed within the RV free wall in CDC-treated animals. Proteomic analysis of RV muscle in CDC- or PBS-treated PAH rats showed alterations in protein pathways related to inflammation, fibrosis, autophagy, cell vitality, and angiogenesis. These changes were consistent with putative coordination by a small number of key upstream regulators (MYC, TP53, HNF4A, TGFB1, and KRAS). TAPSE was significantly reduced in PBS-treated animals but was maintained at or above baseline levels in CDC-treated animals. Conclusions CDC therapy can significantly impact the maladaptive milieu of the RV myocardium in advanced PAH, by altering several pathobiological pathways. Such adjunctive therapy, in addition to those employed to reduce pulmonary vascular resistance, would be a great advance in managing RV failure, for which no effective current approved therapies exist.

Impact of artificial feeding on the developmental cycle of two triatomine species

Background Live animals are the preferred food source for rearing and keeping triatomines in insectaries. However, there is an increasing demand for artificial feeding as an alternative method to using live animals. Despite this demand, scientific studies showing the viability of rearing triatomine colonies in insectaries with artificial feeding are still lacking. In this regard, we tested whether feeding triatomines with an artificial system affects different physiological and biological parameters during the insects’ development. Methodology/principal findings Three experimental groups were established for the species Triatoma infestans and Panstrongylus megistus. The insects were fed weekly and individually, with each group receiving different treatments, as follows: A) artificial feeding system with rabbit blood, B) live animal host, and C) alternating feeding (one week A and the next B). The groups were kept under the same environmental conditions and monitored daily. The parameters evaluated per instar and total cycle were the effect of the blood supply method on the insects’ developmental time, the association between feeding method and insect mortality, weight gain, and the number of feedings needed to trigger molting. The latter two were evaluated only in P. megistus. Conclusions/significance Sex did not influence the insects’ survival or weight gain. The biological cycle duration was shortest in insects fed on a live animal host, followed by the group fed alternately, and longest in those fed artificially. Panstrongylus megistus fed on an artificial system required more feedings to complete molting and gained less weight. The insect mortality rate was not influenced by the feeding method. This is the first study showing that artificial feeding conditions affect different physiological parameters in two triatomine species, questioning the viability of exclusive artificial feeding as a sustainable strategy in a laboratory environment.