bluuebunny/crossref_metadata_2025_split huggingface dataset:
Retinal microglia-derived S100A9 incite NLRP3 inflammasome in a Western diet fed Ossabaw pig retina
Authors: Lim Rayne R , Thomas Anju , Ramasubramanian Aparna , Chaurasia Shyam S. 
Published: October 2024

AbstractPurposeWe established S100A9 as a myeloid-derived damage-associated molecular pattern (DAMPs) protein associated with increasing severity of diabetic retinopathy (DR) in type 2 diabetic subjects. The present study investigates the retinal localization, expression, and mechanisms of action for S100A9 in the young obese Ossabaw pig retina.MethodsRetinae from Ossabaw pigs fed a Western diet for 10 weeks were evaluated for S100 and inflammatory mediator expression using quantitative PCR and Western blot. Double immunohistochemistry was performed to identify the cellular sources of S100A9 in the pig retina. Primary pig retinal microglial cells (pMicroglia) were examined for S100A9 production. S100A9-induced responses were also investigated, and inhibitor studies elucidated the mechanism of action via the NLRP3 inflammasome. A specific inhibitor, Paquinimod (ABR-215757), was administeredin vitroto assess the rescue of S100A9-induced NLRP3 inflammasome activation in pMicroglia.ResultsThe expression of the S100 family in the obese Ossabaw pig retina showed a significant elevation of S100A9, consistent with increased levels of circulating S100A9. Moreover, the retina had elevated levels of inflammatory mediators IL-6, IL-8, MCP-1, IL-1β and NLRP3. Retinal microglia in obese Ossabaw were activated and accompanied by an increased expression of intracellular S100A9. pMicroglia isolated from pig retina transformed from ramified to amoeboid state when activated with LPS and produced high S100A9 transcript and protein levels. The S100A9 protein, in turn, further activated pMicroglia by heightened production of S100A9 transcripts and secretion of pro-inflammatory IL-1β protein. Inhibition of TLR4 with TAK242 and NLRP3 with MCC950 attenuated the production of IL-1β during S100A9 stimulus. Finally, pre-treatment with Paquinimod successfully reduced S100A9-driven increases of glycosylated-TLR4, NLRP3, ASC, Caspase-1, and IL-1β production.ConclusionWe demonstrated that microglial-derived S100A9 perpetuates pro-inflammatory responses via the NLRP3 inflammasome in the retina of young Western-diet-fed Ossabaw pigs exhibiting diabetic retinopathy.
Massively parallel experimental interrogation of natural variants in ancient signaling pathways reveals both purifying selection and local adaptation
Authors: Aguilar-Rodríguez José , Vila Jean , Chen Shi-An A. , Razo-Mejia Manuel , Ghosh Olivia , Fraser Hunter B. , Jarosz Dan F. , Petrov Dmitri A. 
Published: October 2024

AbstractThe nature of standing genetic variation remains a central debate in population genetics, with differing perspectives on whether common variants are mostly neutral or have functional effects. We address this question by directly mapping the fitness effects of over 9,000 natural variants in the Ras/PKA and TOR/Sch9 pathways—key regulators of cell proliferation in eukaryotes—across four conditions inSaccharomyces cerevisiae. While many variants are neutral in our assay, on the order of 3,500 exhibited significant fitness effects. These non-neutral variants tend to be missense and affect conserved, more densely packed, and less solvent-exposed protein regions. They are also typically younger, occur at lower frequencies, and more often found in heterozygous states, suggesting they are subject to purifying selection. A substantial fraction of non-neutral variants showing strong fitness effects in our experiments, however, is present at high frequencies in the population. These variants show signs of local adaptation as they tend to be found specifically in domesticated strains adapted to human-made environments. Our findings support the view that while common variants are often neutral, a significant proportion have adaptive functional consequences and are driven into the population by local positive selection. This study highlights the potential to explore the functional effects of natural genetic variation on a genome scale with quantitative fitness measurements in the laboratory, bridging the gap between population genetics and functional genomics to understand evolutionary dynamics in the wild.
Contrasting macroevolutionary patterns in the human N-glycosylation pathway
Authors: Kifer Domagoj , Čorak Nina , Domazet-Lošo Mirjana , Kasalo Niko , Lauc Gordan , Klobučar Göran , Domazet-Lošo Tomislav 
Published: October 2024

AbstractBuilding on coding mutations and splicing variants, post-translational modifications add a final layer to protein diversity that operates at developmental and physiological timescales. Although protein glycosylation is one of the most common post-translational modifications, its evolutionary origin remains largely unexplored. Here, we performed a phylostratigraphic tracking of glycosylation machinery genes and their targets — glycosylated proteins — in a broad phylogenetic context. Our results show that the vast majority of human glycosylation machinery genes trace back to two evolutionary periods: the origin of all cellular organisms and the origin of all eukaryotes. This indicates that protein glycosylation is an ancient process likely common to all life, further elaborated in early eukaryotes. In contrast, human glycoproteins exhibited prominent enrichment signals in more recent evolutionary periods, suggesting an important role in the transition from metazoans to vertebrates. Focusing specifically on the N-glycosylation pathway, we noted that the majority of N-glycosylation genes acting on the cytoplasmic side of the endoplasmic reticulum (ER) trace back to the origin of cellular organisms. This sharply contrasts with the rest of the N-glycosylation pathway, which is oriented toward the ER lumen, where genes of eukaryotic origin predominate. In the Golgi, we also identified an analogous binary evolutionary origin of glycosylation machinery genes. We discuss these findings in the context of the evolutionary emergence of the eukaryotic endomembrane system and propose that the ER evolved through the invagination of a prokaryotic cell membrane containing an N-glycosylation pathway.
Single-cell profiling of cortical tubers in tuberous sclerosis complex shows molecular structure preservation and massive reorganization of metabolism
Authors: Friis Sørensen Frederik Nørby , Petanjek Tin Luka , Scheper Mirte , Rydbirk Rasmus , Korshunova Irina , Anink Jasper , Mühlebner Angelika , Mills James D. , Petanjek Zdravko , Aronica Eleonora , Khodosevich Konstantin 
Published: October 2024

AbstractTuberous sclerosis complex (TSC) is a multisystemic genetic disorder associated with loss-of-function mutations in theTSC1orTSC2gene, which lead mTOR pathway hyperactivation and epileptogenesis. Cortical tubers are the hallmark of TSC and represent disorganized cortical structure underlying the generation of focal seizures. Here, we report single-nucleus RNA sequencing in resected cortical tubers vs matched pediatric controls. Strikingly, in spite of severe cortical disorganization, we found that cortical tubers preserve all neuronal subtypes, even the rarest ones. Moreover, we showed that principal neurons largely preserve spatial position based on transcriptional signatures. Principal neurons and layer 1-2 GABAergic neurons that modulate upper cortical circuits exhibited the largest gene expression changes. Interestingly, multiple mTOR pathway gene expression changes in TSC counteracted mTOR hyperactivation. TSC neuronal, but not glial, networks exhibited massive metabolic reorganization with a reduction in mitochondrial respiration and a concomitant switch to fatty acid metabolism. Finally, we show that neuron-specific AMPA receptor signaling might underlie epileptogenesis in TSC and could represent a potential candidate for therapeutic targeting.
Sleep Deprivation in Mice: Looking Beyond the Slow Wave Rebound
Authors: Magyar Tárek Zoltán , Szalárdy Orsolya , Bódizs Róbert 
Published: October 2024

AbstractSleep is a fundamental process by which the brain achieves an optimal computational regime; it has been suggested that criticality is an appropriate theoretical framework in which such a process can be understood. Studying the critical and fractal dynamics of the brain involves modelling the nonlinearity of brain signals (such as EEG or ECoG) yielding, among others, the following metrics: spectral slope, spectral intercept, spectral knee, and normalized spectral entropy. Therefore, the present study investigates the nonlinear and critical dynamics of the brain in relation to sleep deprivation in mice, by comparing the sensitivity of the above-mentioned metrics to classical band- limited spectral indices. Mice were exposed to a 9 day-long sleep deprivation paradigm with baseline, sleep deprivation, and recovery phases. Spectral parameters were computed using the FOOOF algorithm. The results suggest that the classical approach (slow wave activity; 0.75-4.5 Hz) to neural signal processing differentiates between baseline sleep and rebound sleep only during the NREM phase. In contrast, the spectral slope and the spectral intercept both capture sleep deprivation related effects during REM and NREM episodes as well. This is particularly notable considering that the spectral knee is shifted towards higher frequencies, essentially rendering the spectral slope unreflective of slow wave activity – traditionally considered the biomarker of sleep homeostasis.Lastly, normalized spectral entropy fails to differentiate between baseline sleep and sleep following sleep deprivation in mice. These results support the sensitivity of fractal spectral parameters indexing the intricate balance between sleep and wake states.
Infrared finite scattering theory: Amplitudes and soft theorems
Authors: Prabhu Kartik , Satishchandran Gautam 
Published: October 2024

Any nontrivial scattering with massless fields in four spacetime dimensions will generically produce an out-state with memory. Scattering with any massless fields violates the standard assumption of asymptotic completeness—that all “in” and “out” states lie in the standard (zero-memory) Fock space—and therefore leads to infrared divergences in the standard S-matrix amplitudes. In this paper, we define an infrared finite scattering theory which assumes only (1) the existence of in-/out-algebras and (2) that Heisenberg evolution is an automorphism of these algebras. The resulting “superscattering” map $ allows for transitions between different in/out memory states and agrees with the standard S matrix when it is defined. We construct $ amplitudes by defining (3) a “generalized asymptotic completeness” which accommodates states with memory in the space of asymptotic states and (4) a complete basis of improper states that generalize the usual n-particle momentum basis to account for states with memory. Using only general properties of $, we prove an analog of the Weinberg soft theorems in quantum gravity and QED which imply that all $ amplitudes are well defined in the infrared. We comment on how one must generalize this framework to consider $ amplitudes for theories with collinear divergences (e.g., massless QED and Yang-Mills theories).

Published by the American Physical Society
2024
Enhancing hydrologic LiDAR digital elevation models: Bridging hydrographic gaps at fine scales
Authors: Wu Di , Li Ruopu , Edidem Michael , Wang Guangxing 
Published: October 2024

AbstractHigh‐resolution digital elevation models (HRDEMs), derived from LiDAR, are widely used for mapping hydrographic details in flat terrains. However, artificial flow barriers, particularly from roads, elevate terrain and prematurely end flowlines. Drainage barrier processing (DBP), such as HRDEM excavation, is employed to address this issue. However, there is a gap in quantitatively assessing the impact of DBP on HRDEM‐derived flowlines, especially at finer scales. This study fills that gap by quantitatively assessing how DBP improves flowline quality at finer scales. We evaluated HRDEM‐derived flowlines that were generated using different flow direction algorithms, developing a framework to measure the effects of flow barrier removal. The results show that the primary factor influencing flowline quality is the presence of flow accumulation artifacts. Quality issues also stem from differences between natural and artificial flow paths, unrealistic flowlines in flat areas, complex canal networks, and ephemeral drainage ways. Notably, the improvement achieved by DBP is demonstrated to be more than 6%, showcasing its efficacy in reducing the impact of flow barriers on hydrologic connectivity.
Quantitative analysis of imaging characteristics in lung adenocarcinoma in situ using artificial intelligence
Authors: Shi Wensong , Hu Yuzhui , Yang Yulun , Song Yinsen , Chang Guotao , Qian He , Wei Zhengpan , Gao Liang , Sun Yingli , Li Ming , Yi Hang , Wu Sikai , Wang Kun , Mao Yousheng , Ai Siyuan , Zhao Liang , Zheng Huiyu , Li Xiangnan 
Published: October 2024

AbstractBackgroundWith the rising incidence of pulmonary nodules (PNs), lung adenocarcinoma in situ (AIS) is a critical early stage of lung cancer, necessitating accurate diagnosis for early intervention. This study applies artificial intelligence (AI) for quantitative imaging analysis to differentiate AIS from atypical adenomatous hyperplasia (AAH) and minimally invasive adenocarcinoma (MIA), aiming to enhance clinical diagnosis and prevent misdiagnosis.MethodsThe study analyzed 1215 PNs with confirmed AAH, AIS, and MIA from six centers using the Shukun AI diagnostic module. Parameters evaluated included demographic data and various CT imaging metrics to identify indicators for clinical application, focusing on the mean CT value's predictive value.ResultsSignificant differences were found in several parameters between AAH and AIS, with nodule mass showing the highest predictive value. When comparing AIS to MIA, total nodule volume was the best predictor, followed by the maximum CT value.ConclusionThe mean CT value has limited discriminative power for AIS diagnosis. Instead, the maximum CT value and maximum 3D diameter are recommended for clinical differentiation. Nodule mass and volume of solid components are strong indicators for differentiating AIS from AAH and MIA, respectively.
Application of machine learning in predicting health perception through military personnel's sense of empowerment
Authors: Chen Kun‐Huang , Chiu Pao‐Lung , Chen Ming‐Hsuan 
Published: October 2024

AbstractThe promotion of health and provision of care services for new recruits are issues of constant concern for military leaders and healthcare providers, as they are crucial to maintaining and operating military forces. The enhancement of military personnel's empowerment has been recognized as a core value in promoting health perception. However, the pathways between military personnel's sense of empowerment and health perception have not been thoroughly explored. The primary aim of this study is to examine the predictive power of different dimensions of empowerment (personal, interpersonal, and socio‐political) on new recruits' health perception, and to further observe differences among subgroups, which will help us grasp the nuances of future health intervention measures. The research data were extracted from the “Military Career Development Study,” analyzing personal empowerment data from Wave 1 (W1) and perceived health data from Wave 2 (W2) (N = 2,232). In terms of analytical methods, five ML classifiers, including Decision Tree, Random Forest, Support Vector Machine, AdaBoost, and k‐Nearest Neighbors (KNN) algorithms, were used for prediction in both the full sample and subsamples (gender and socioeconomic status). Results show that among the five ML classifiers, the Decision Tree performed best overall, achieving a prediction accuracy of 95.4%. The results by gender show that the ML models perform best for both males and females with the Decision Tree and Random Forest methods. For the Decision Tree, the accuracy rates were 94.9% for males and 95.1% for females; the F1 scores were 92.9% for males and 93.2% for females. For the Random Forest, the accuracy rates were 94.9% for males and 95.4% for females; the F1 scores were 92.7% for males and 93.2% for females. Regarding SES, the Decision Tree and Random Forest methods performed best. In the SES Low group, both methods achieved a prediction accuracy of 95.6% and an F1 score of 93.7%; in the SES high group, they achieved a prediction accuracy of 95.4% and an F1 score of 93.3%. However, the contribution of different dimensions of empowerment features varied significantly among subgroups. These findings can provide important information on the differences in health perception among military personnel.
Distal preservation and retrograde resection of the anterior vaginal wall in female robot‐assisted radical cystectomy
Authors: Iguchi Ryo , Inoue Koji 
Published: October 2024

AbstractIntroductionIn many cases of female radical cystectomy for bladder cancer, the procedure involves simultaneous removal of the uterus, fallopian tubes, ovaries, anterior vaginal wall, and urethra. After this procedure, rare complications like vaginal dehiscence and evisceration may occur. We herein describe this article surgical technique involving preservation of the distal anterior vaginal wall to maintain pelvic floor strength and retrograde resection of the proximal anterior vaginal wall.Materials and Surgical TechniqueThe presented case was a 61‐year‐old woman who had a bladder tumor. After undergoing a transurethral resection, the pathology revealed muscle‐invasive squamous cell bladder cancer. Consequently, she received a robot‐assisted radical cystectomy (RARC) without neoadjuvant chemotherapy. Before opening the vaginal wall, the urethra, including the external urethral meatus, was dissected along its entire length. Next, a transverse incision was made in the anterior vaginal wall at the level of bladder neck, and the wall was resected retrogradely toward the anterior vaginal fornix while preserving the distal anterior vaginal wall. The opened vaginal wall was closed in a tubular shape.DiscussionPreservation of the distal anterior vaginal wall and retrograde anterior vaginal wall resection can be safely performed in female RARC and may reduce the risk of vaginal dehiscence by minimizing the vaginal wall defect.
Isolated esophageal hiatal hernia of the colon: A case report and review of literature
Authors: Maeda Shinsuke , Ito Shunichi , Hosoda Kei 
Published: October 2024

AbstractEsophageal hiatal hernias, most of which are transhiatal migrations of the gastric cardia into the mediastinum, include a minor category called paraesophageal hernias. Herniation of organs other than the stomach belongs to this category. A 75‐year‐old man who developed esophageal hiatal hernia of an isolated transverse colon underwent elective laparoscopic surgery. Intraoperative findings revealed a preserved phrenoesophageal attachment on the patient's left dorsal side. Sac excision, sutured cruroplasty, and Toupet fundoplication were performed. The postoperative course was uneventful, and the patient's stooping‐induced dyspnea was relieved after surgery. Our literature review indicated that hiatal hernia of the isolated colon has the unique characteristic of causing secondary gastroduodenal outlet obstruction and shares a mutual nature with Type II hiatal hernia. Although rare, this uncommon type of hiatal hernia may be recognized as a distinct subtype of paraesophageal hernia.
Research on the P‐S‐N Curve Fitting Method of Notched Specimens Considering Small Sample Properties
Authors: Zhang Ziyang , Liu Jianhui , Hu Juntai , Wu Qingjun , Wu Shenglei 
Published: October 2024

ABSTRACTAiming at the issue of fatigue test data for large‐scale mechanical components of building steel are very limited, a method for fitting P‐S‐N curves under small sample data of notched specimens is proposed to predict fatigue life. First, a fatigue life subsample augmented and its reliability assessment method are established, based on Bayesian hierarchical modeling and modified Monte Carlo method. Second, a clustering combination weighting method is proposed, to define weights of hidden variables of the binomial mixture Weibull distribution, and the expectation–maximization algorithm is used to determine probability density function of the distribution. Finally, the P‐S‐N curves under various failure probabilities are fitted with Weibull distributed life models, and the convergence and prediction accuracy of the different models are compared. The results show that the fatigue data of small samples can be predicted better by using mixed Weibull distribution, and the fitting P‐S‐N curve is more reliable and accurate.
Ki‐67 evaluation using deep‐learning model‐assisted digital image analysis in breast cancer
Authors: Matsumoto Hirofumi , Miyata Ryota , Tsuruta Yuma , Nakada Norihiro , Koki Ayako , Unesoko Mikiko , Abe Norie , Zaha Hisamitsu 
Published: October 2024

AimsTo test the efficacy of artificial intelligence (AI)‐assisted Ki‐67 digital image analysis in invasive breast carcinoma (IBC) with quantitative assessment of AI model performance.Methods and ResultsThis study used 494 cases of Ki‐67 slide images of IBC core needle biopsies. The methods were divided into two steps: (i) construction of a deep‐learning model (DL); and (ii) DL implementation for Ki‐67 analysis. First, a DL tissue classifier model (DL‐TC) and a DL nuclear detection model (DL‐ND) were constructed using HALO AI DenseNet V2 algorithm with 31,924 annotations in 300 Ki‐67 digital slide images. Whether the class predicted by DL‐TC in the test set was correct compared with the annotation of ground truth at the pixel level was evaluated. Second, DL‐TC‐ and DL‐ND‐assisted digital image analysis (DL‐DIA) was performed in the other 194 luminal‐type cases and correlations with manual counting and clinical outcome were investigated to confirm the accuracy and prognostic potential of DL‐DIA. The performance of DL‐TC was excellent and invasive carcinoma nests were well segmented from other elements (average precision: 0.851; recall: 0.878; F1‐score: 0.858). Ki‐67 index data and the number of nuclei from DL‐DIA were positively correlated with data from manual counting (ρ = 0.961, and 0.928, respectively). High Ki‐67 index (cutoff 20%) cases showed significantly worse recurrence‐free survival and breast cancer‐specific survival (P = 0.024, and 0.032, respectively).ConclusionThe performances of DL‐TC and DL‐ND were excellent. DL‐DIA demonstrated a high degree of concordance with manual counting of Ki‐67 and the results of this approach have prognostic potential.
Analytic mappings of the unit disk which almost preserve hyperbolic area
Authors: Ivrii Oleg , Nicolau Artur 
Published: October 2024

AbstractIn this paper, we study analytic self‐maps of the unit disk which distort hyperbolic areas of large hyperbolic disks by a bounded amount. We give a number of characterizations involving angular derivatives, Lipschitz extensions, Möbius distortion, the distribution of critical points and Aleksandrov–Clark measures. We also examine the Lyapunov exponents of their Aleksandrov–Clark measures.