bluuebunny/crossref_metadata_2025_split huggingface dataset:
A novel tumor-associated neutrophil gene signature for predicting prognosis, tumor immune microenvironment, and therapeutic response in breast cancer
Authors: Zhang Jianyou , Wang Xinbo , Zhang Zhonglai , Ma Fuyi , Wang Feng 
Published: March 2024

AbstractTumor-associated neutrophils (TANs) can promote tumor progression. This study aimed to investigate the molecular signature that predict the prognosis and immune response of breast cancer (BRCA) based on TAN-related gene (TANRG) expression data. The RNA-seq data of BRCA were gathered from The Cancer Genome Atlas (TCGA) and gene expression omnibus (GEO) datasets. Univariate Cox regression analysis and the least absolute shrinkage and selection operator for selecting prognostic genes. A neo-TAN-related risk signature was constructed by multivariate Cox regression analysis. Time-dependent receiver operating characteristic (ROC) curve analyses and Kaplan–Meier analyses were performed to validate the signature in GEO cohorts and the triple-negative breast cancer (TNBC) subtype. We constructed an independent prognostic factor model with 11 TANRGs. The areas under the ROC curve (AUCs) of the TCGA training cohorts for 3-, 5-, and 7-year overall survival were 0.72, 0.73, and 0.73, respectively. The AUCs of the GEO test cohorts for 3-, 5-, and 7-year overall survival were 0.83, 0.89, and 0.94 (GSE25066) and 0.67, 0.69, and 0.73 (GSE58812), respectively. The proportion of immune subtypes differed among the different risk groups. The IC50 values differed significantly between risk groups and can be used as a guide for systemic therapy. The prognostic model developed by TANRGs has excellent predictive performance in BRCA patients. In addition, this feature is closely related to the prediction of survival, immune activity and treatment response in BRCA patients.
Secular trend in age at menarche among Indian women
Authors: Meher Trupti , Sahoo Harihar 
Published: March 2024

AbstractAge at menarche is not only a parameter that signifies biological characteristics for women but is also considered as an indicator to measure the quality of life of a population. Moreover, menarche has significant implications on women’s health and information about menarcheal age is crucial for health policymakers. However, little is known about the trends in menarcheal age in India. Thus, in order to fill this research gap, the present study aimed to explore the age at menarche, its trend and regional heterogeneity among Indian women. A birth cohort approach was used by polling data from the 1st (1992–93), 4th (2015–16) and 5th (2019–21) rounds of NFHS. Descriptive statistics and bivariate analyses were performed to present the distribution of age at menarche and mean age at menarche across birth cohorts and each category of covariates. A multiple linear regression model was fitted to examine the trend in age at menarche and further to investigate the association of covariates with menarcheal age among Indian women. The analysis demonstrated that a majority of women (66.2%) attained menarche between the ages of 13–14 years. Moreover, about 17.2% of women experienced an early age at menarche, whereas 16.7% of women had a late age at menarche. The mean age at menarche for the sampled women was 13.49 years. The analysis also observed a secular declining trend in menarcheal age among Indian women and a significant variation in the mean age at menarche across birth cohorts. It also highlighted significant socio-economic patterning in menarcheal age among women.
Long-term outcome of uniport vs. multiport video-assisted thoracoscopic lobectomy for lung cancer
Authors: Ruan Yingding , Cao Wenjun , Xue Hongsheng , You Maoduan , Zhao Zhilong 
Published: March 2024

AbstractThis study aims to compare the perioperative outcomes and long-term survival of U-VATS lobectomy for NSCLC with multiportal VATS (M-VATS, involving two ports or more) lobectomy. A total of 339 patients who underwent intentional VATS lobectomy for lung cancer between 2012 and 2017 were included in the analysis. Perioperative outcomes and long-term survival were evaluated. Propensity score matching was utilized to minimize baseline characteristic differences between the two groups. Out of the total cases, 17 (5.01%) were converted to open thoracotomy. The conversion rates were 4.96% (7/141) in the U-VATS group and 5.05% (10/198) in the M-VATS group. A total of 322 consecutive patients underwent VATS lobectomy and mediastinal lymphadenectomy. After propensity matching, 106 pairs were obtained, consisting of 83 males and 129 females. Intraoperative bleeding volume, number of retrieved lymph nodes, explored nodal stations, drainage time and volume, and postoperative hospital stay were similar between the two groups. Both groups exhibited comparable morbidity and mortality rates. From the multivariable analysis, there was no significant difference observed in terms of overall survival (OS) and disease-free survival (DFS) between the two patient cohorts. U-VATS demonstrated comparable perioperative outcomes and long-term efficacy to M-VATS. However, further confirmation of these findings is required.
Comparison of the CASA and InVEST models’ effects for estimating spatiotemporal differences in carbon storage of green spaces in megacities
Authors: Wang Ruei-Yuan , Mo Xueying , Ji Hong , Zhu Zhe , Wang Yun-Shang , Bao Zhilin , Li Taohui 
Published: March 2024

AbstractUrban green space is a direct way to improve the carbon sink capacity of urban ecosystems. The carbon storage assessment of megacity green spaces is of great significance to the service function of urban ecosystems and the management of urban carbon zoning in the future. Based on multi-period remote sensing image data, this paper used the CASA model and the InVEST model to analyze the spatio-temporal variation and driving mechanism of carbon storage in Shenzhen green space and discussed the applicability of the two models to the estimation of carbon storage in urban green space. The research results showed that, from 2008 to 2022, in addition to the rapid expansion of construction land, the area of green space and other land types in Shenzhen showed a significant decrease trend. The estimation results of the carbon storage model showed that the carbon storage of green space shows a significant trend of reduction from 2008 to 2022, and the reduction amounts are 0.8 × 106 t (CASA model) and 0.64 × 106 t (InVEST model), respectively. The evaluation results of the model show that, in megacities, the spatial applicability of InVEST model is lower than that of CASA model, and the CASA model is more accurate in estimating the carbon storage of urban green space. The research results can provide a scientific basis for the assessment of the carbon sink capacity of megacity ecosystems with the goal of "dual carbon".
Effects of acute phase intensive electrical muscle stimulation in COVID-19 patients requiring invasive mechanical ventilation: an observational case-control study
Authors: Tsuchikawa Yohei , Tanaka Shinya , Kasugai Daisuke , Nakagawa Riko , Shimizu Miho , Inoue Takayuki , Nagaya Motoki , Nasu Takafumi , Omote Norihito , Higashi Michiko , Yamamoto Takanori , Jingushi Naruhiro , Numaguchi Atsushi , Nishida Yoshihiro 
Published: March 2024

AbstractWe investigated the effects of acute-phase intensive electrical muscle stimulation (EMS) on physical function in COVID-19 patients with respiratory failure requiring invasive mechanical ventilation (IMV) in the intensive care unit (ICU). Consecutive COVID-19 patients requiring IMV admitted to a university hospital ICU between January and April 2022 (EMS therapy group) or between March and September 2021 (age-matched historical control group) were included in this retrospective observational case–control study. EMS was applied to both upper and lower limb muscles for up to 2 weeks in the EMS therapy group. The study population consisted of 16 patients undergoing EMS therapy and 16 age-matched historical controls (median age, 71 years; 81.2% male). The mean period until initiation of EMS therapy after ICU admission was 3.2 ± 1.4 days. The EMS therapy group completed a mean of 6.2 ± 3.7 EMS sessions, and no adverse events occurred. There were no significant differences between the two groups in Medical Research Council sum score (51 vs. 53 points, respectively; P = 0.439) or ICU mobility scale at ICU discharge. Addition of upper and lower limb muscle EMS therapy to an early rehabilitation program did not result in improved physical function at ICU discharge in severe COVID-19 patients.
Relative contributions of taxonomic and functional diversity to the assembly of plant communities hosting endemic Dianthus species in a mountain steppe
Authors: Behroozian Maryam , Pierce Simon , Ejtehadi Hamid , Memariani Farshid , Rafiee Fahime , Joharchi Mohammad Reza 
Published: March 2024

AbstractPlant community assembly is the outcome of long-term evolutionary events (evident as taxonomic diversity; TD) and immediate adaptive fitness (functional diversity; FD); a balance expected to shift in favour of FD in ‘harsh’ habitats under intense selection pressures. We compared TD and FD responses along climatic and edaphic gradients for communities of two species (Dianthus pseudocrinitus and D. polylepis) endemic to the montane steppes of the Khorassan-Kopet Dagh floristic province, NE Iran. 75 plots at 15 sites were used to relate TD and FD to environmental gradients. In general, greater TD was associated with variation in soil factors (potassium, lime, organic matter contents), whereas FD was constrained by aridity (drought adaptation). Crucially, even plant communities hosting different subspecies of D. polylepis responded differently to aridity: D. polylepis subsp. binaludensis communities included a variety of broadly stress-tolerant taxa with no clear environmental response, but TD of D. polylepis subsp. polylepis communities was directly related to precipitation, with consistently low FD reflecting a few highly specialized stress-tolerators. Integrating taxonomic and functional diversity metrics is essential to understand the communities hosting even extremely closely related taxa, which respond idiosyncratically to climate and soil gradients.
Hazardous heat exposure among incarcerated people in the United States
Authors: Tuholske Cascade , Lynch Victoria D. , Spriggs Raenita , Ahn Yoonjung , Raymond Colin , Nigra Anne E. , Parks Robbie M. 
Published: March 2024

AbstractClimate change is predicted to increase the frequency of potentially hazardous heat conditions across the United States, putting the incarcerated population of 2 million at risk for heat-related health conditions. We evaluate the exposure to potentially hazardous heat for 4,078 continental US carceral facilities during 1982–2020. Results show that the number of hot days per year increased during 1982–2020 for 1,739 carceral facilities, primarily located in the southern United States. State-run carceral facilities in Texas and Florida accounted for 52% of total exposure, despite holding 12% of all incarcerated people. This highlights the urgency for enhanced infrastructure, health system interventions and treatment of incarcerated people, especially under climate change.
Genetic algorithm-enhanced microcomb state generation
Authors: Mazoukh Celine , Di Lauro Luigi , Alamgir Imtiaz , Fischer Bennet , Perron Nicolas , Aadhi A. , Eshaghi Armaghan , Little Brent E. , Chu Sai T. , Moss David J. , Morandotti Roberto 
Published: March 2024

AbstractMicrocavities enable the generation of highly efficient microcombs, which find applications in various domains, such as high-precision metrology, sensing, and telecommunications. Such applications generally require precise control over the spectral features of the microcombs, such as free spectral range, spectral envelope, and bandwidth. Most existing methods for customizing microcomb still rely on manual exploration of a large parameter space, often lacking practicality and versatility. In this work, we propose a smart approach that employs genetic algorithms to autonomously optimize the parameters for generating and tailoring stable microcombs. Our scheme controls optical parametric oscillation in a microring resonator to achieve broadband microcombs spanning the entire telecommunication C-band. The high flexibility of our approach allows us to obtain complex microcomb spectral envelopes corresponding to various operation regimes, with the potential to be directly adapted to different microcavity geometries and materials. Our work provides a robust and effective solution for targeted soliton crystal and multi-soliton state generation, with future potential for next-generation telecommunication applications and artificial intelligence-assisted data processing.
A phase diagram structure determines the optimal sensitivity-precision trade-off in signaling systems
Authors: Kong Ka Kit , Luo Chunxiong , Liu Feng 
Published: March 2024

AbstractSignal transduction is crucial for many biological functions. However, it is still unclear how signaling systems function accurately under noisy situations. More specifically, such systems operate in a regime of low response noise, while maintaining high sensitivity to signals. To gain further insight on this regime, here we derive a fundamental trade-off between response sensitivity and precision in biological signaling processes under the static noise condition. We find that the optimal trade-off in signaling networks can be better characterized by a phase diagram structure rather than topological structures. We confirm that the patterning network of early Drosophila embryos agrees with our derived relationship, and apply the optimal phase diagram structure to quantitatively predict the patterning position shifts of the downstream genes, including hunchback, Krüppel, giant, knirps and even-skipped, upon the dosage perturbation of the morphogen Bicoid.
Neuron–astrocyte metabolic coupling facilitates spinal plasticity and maintenance of inflammatory pain
Authors: Marty-Lombardi Sebastián , Lu Shiying , Ambroziak Wojciech , Schrenk-Siemens Katrin , Wang Jialin , DePaoli-Roach Anna A. , Hagenston Anna M. , Wende Hagen , Tappe-Theodor Anke , Simonetti Manuela , Bading Hilmar , Okun Jürgen G. , Kuner Rohini , Fleming Thomas , Siemens Jan 
Published: March 2024

AbstractLong-lasting pain stimuli can trigger maladaptive changes in the spinal cord, reminiscent of plasticity associated with memory formation. Metabolic coupling between astrocytes and neurons has been implicated in neuronal plasticity and memory formation in the central nervous system, but neither its involvement in pathological pain nor in spinal plasticity has been tested. Here we report a form of neuroglia signalling involving spinal astrocytic glycogen dynamics triggered by persistent noxious stimulation via upregulation of the Protein Targeting to Glycogen (PTG) in spinal astrocytes. PTG drove glycogen build-up in astrocytes, and blunting glycogen accumulation and turnover by Ptg gene deletion reduced pain-related behaviours and promoted faster recovery by shortening pain maintenance in mice. Furthermore, mechanistic analyses revealed that glycogen dynamics is a critically required process for maintenance of pain by facilitating neuronal plasticity in spinal lamina 1 neurons. In summary, our study describes a previously unappreciated mechanism of astrocyte–neuron metabolic communication through glycogen breakdown in the spinal cord that fuels spinal neuron hyperexcitability.
A systematic review of the methodology of trade-off analysis in agriculture
Authors: Breure Timo S. , Estrada-Carmona Natalia , Petsakos Athanasios , Gotor Elisabetta , Jansen Boris , Groot Jeroen C. J. 
Published: March 2024

AbstractTrade-off analysis (TOA) is central to policy and decision-making aimed at promoting sustainable agricultural landscapes. Yet, a generic methodological framework to assess trade-offs in agriculture is absent, largely due to the wide range of research disciplines and objectives for which TOA is used. In this study, we systematically reviewed 119 studies that have implemented TOAs in landscapes and regions dominated by agricultural systems around the world. Our results highlight that TOAs tend to be unbalanced, with a strong emphasis on productivity rather than environmental and socio-cultural services. TOAs have mostly been performed at farm or regional scales, rarely considering multiple spatial scales simultaneously. Mostly, TOAs fail to include stakeholders at study development stage, disregard recommendation uncertainty due to outcome variability and overlook risks associated with the TOA outcomes. Increased attention to these aspects is critical for TOAs to guide agricultural landscapes towards sustainability.
A deep learning model of tumor cell architecture elucidates response and resistance to CDK4/6 inhibitors
Authors: Park Sungjoon , Silva Erica , Singhal Akshat , Kelly Marcus R. , Licon Kate , Panagiotou Isabella , Fogg Catalina , Fong Samson , Lee John J. Y. , Zhao Xiaoyu , Bachelder Robin , Parker Barbara A. , Yeung Kay T. , Ideker Trey 
Published: March 2024

AbstractCyclin-dependent kinase 4 and 6 inhibitors (CDK4/6is) have revolutionized breast cancer therapy. However, <50% of patients have an objective response, and nearly all patients develop resistance during therapy. To elucidate the underlying mechanisms, we constructed an interpretable deep learning model of the response to palbociclib, a CDK4/6i, based on a reference map of multiprotein assemblies in cancer. The model identifies eight core assemblies that integrate rare and common alterations across 90 genes to stratify palbociclib-sensitive versus palbociclib-resistant cell lines. Predictions translate to patients and patient-derived xenografts, whereas single-gene biomarkers do not. Most predictive assemblies can be shown by CRISPR–Cas9 genetic disruption to regulate the CDK4/6i response. Validated assemblies relate to cell-cycle control, growth factor signaling and a histone regulatory complex that we show promotes S-phase entry through the activation of the histone modifiers KAT6A and TBL1XR1 and the transcription factor RUNX1. This study enables an integrated assessment of how a tumor’s genetic profile modulates CDK4/6i resistance.
Description of an activity-based enzyme biosensor for lung cancer detection
Authors: Dempsey Paul W. , Sandu Cristina-Mihaela , Gonzalezirias Ricardo , Hantula Spencer , Covarrubias-Zambrano Obdulia , Bossmann Stefan H. , Nagji Alykhan S. , Veeramachaneni Nirmal K. , Ermerak Nezih O. , Kocakaya Derya , Lacin Tunc , Yildizeli Bedrittin , Lilley Patrick , Wen Sara W. C. , Nederby Line , Hansen Torben F. , Hilberg Ole 
Published: March 2024

Abstract
Background
Lung cancer is associated with the greatest cancer mortality as it typically presents with incurable distributed disease. Biomarkers relevant to risk assessment for the detection of lung cancer continue to be a challenge because they are often not detectable during the asymptomatic curable stage of the disease. A solution to population-scale testing for lung cancer will require a combination of performance, scalability, cost-effectiveness, and simplicity.

Methods
One solution is to measure the activity of serum available enzymes that contribute to the transformation process rather than counting biomarkers. Protease enzymes modify the environment during tumor growth and present an attractive target for detection. An activity based sensor platform sensitive to active protease enzymes is presented. A panel of 18 sensors was used to measure 750 sera samples from participants at increased risk for lung cancer with or without the disease.

Results
A machine learning approach is applied to generate algorithms that detect 90% of cancer patients overall with a specificity of 82% including 90% sensitivity in Stage I when disease intervention is most effective and detection more challenging.

Conclusion
This approach is promising as a scalable, clinically useful platform to help detect patients who have lung cancer using a simple blood sample. The performance and cost profile is being pursued in studies as a platform for population wide screening.
Transcriptomics-driven metabolic pathway analysis reveals similar alterations in lipid metabolism in mouse MASH model and human
Authors: Tsouka Sofia , Kumar Pavitra , Seubnooch Patcharamon , Freiburghaus Katrin , St-Pierre Marie , Dufour Jean-François , Masoodi Mojgan 
Published: March 2024

AbstractBackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) is a prevalent chronic liver disease worldwide, and can rapidly progress to metabolic dysfunction-associated steatohepatitis (MASH). Accurate preclinical models and methodologies are needed to understand underlying metabolic mechanisms and develop treatment strategies. Through meta-analysis of currently proposed mouse models, we hypothesized that a diet- and chemical-induced MASH model closely resembles the observed lipid metabolism alterations in humans.MethodsWe developed transcriptomics-driven metabolic pathway analysis (TDMPA), a method to aid in the evaluation of metabolic resemblance. TDMPA uses genome-scale metabolic models to calculate enzymatic reaction perturbations from gene expression data. We performed TDMPA to score and compare metabolic pathway alterations in MASH mouse models to human MASH signatures. We used an already-established WD+CCl4-induced MASH model and performed functional assays and lipidomics to confirm TDMPA findings.ResultsBoth human MASH and mouse models exhibit numerous altered metabolic pathways, including triglyceride biosynthesis, fatty acid beta-oxidation, bile acid biosynthesis, cholesterol metabolism, and oxidative phosphorylation. We confirm a significant reduction in mitochondrial functions and bioenergetics, as well as in acylcarnitines for the mouse model. We identify a wide range of lipid species within the most perturbed pathways predicted by TDMPA. Triglycerides, phospholipids, and bile acids are increased significantly in mouse MASH liver, confirming our initial observations.ConclusionsWe introduce TDMPA, a methodology for evaluating metabolic pathway alterations in metabolic disorders. By comparing metabolic signatures that typify human MASH, we show a good metabolic resemblance of the WD+CCl4 mouse model. Our presented approach provides a valuable tool for defining metabolic space to aid experimental design for assessing metabolism.