bluuebunny/crossref_metadata_2025_split huggingface dataset:
Harvesting insect pests for animal feed: potential to capture an unexploited resource
Authors: Cohnstaedt Lee W , Lado Paula , Ewing Robert , Cherico Jason , Brabec Daniel , Shults Phillip , Arsi Komala , Donoghue Ann M , Wagner Roy , Chaskopoulou Alexandra 
Published: July 2024

Abstract
The demand for animal protein grows as the human population increases. Technological and genetic advances in traditional animal agriculture will not produce enough protein to meet future needs without significant innovations such as the use of insects as protein sources. Insect farming is growing insects, whereas insect harvesting is collecting insects from their natural habitats to produce high-quality protein for animal feed or human food. Intensive agricultural environments produce tremendous quantities of pestiferous insects and with the right harvest technologies these insects can be used as a protein supplement in traditional animal daily rations. An avenue to exploit these insects is to use traps such as the United States Department of Agriculture-Biomass Harvest Trap (USDA-BHT) to efficiently attract, harvest, and store insects from naturally abundant agricultural settings. The modular design allows for a low cost, easy to build and fix device that is user friendly and has customizable attractants to target various pest species. Although insect harvesting faces substantial challenges, including insect biomass quantity, seasonal abundance and preservation, food safety, and economic and nutritional evaluation, the potential for utilizing these pests for protein shows tremendous promise. In this forum, insect harvesting is discussed, including its potential, limitations, challenges, and research needs. In addition, the use of a mass trapping device is discussed as a tool to increase the biomass of insects collected from the environment.
A cargo sorting receptor mediates chloroplast protein trafficking through the secretory pathway
Authors: Liu Jinling , Chen Hong , Liu Li , Meng Xiangzhao , Liu Qianwen , Ye Qinyi , Wen Jiangqi , Wang Tao , Dong Jiangli 
Published: July 2024

Abstract
Nucleus-encoded chloroplast proteins can be transported via the secretory pathway. The molecular mechanisms underlying the trafficking of chloroplast proteins between the intracellular compartments are largely unclear, and a cargo sorting receptor has not previously been identified in the secretory pathway. Here, we report a cargo sorting receptor that is specifically present in Viridiplantae and mediates the transport of cargo proteins to the chloroplast. Using a forward genetic analysis, we identified a gene encoding a transmembrane protein (MtTP930) in barrel medic (Medicago truncatula). Mutation of MtTP930 resulted in impaired chloroplast function and a dwarf phenotype. MtTP930 is highly expressed in the aerial parts of the plant and is localized to the endoplasmic reticulum (ER) exit sites and Golgi. MtTP930 contains typical cargo sorting receptor motifs, interacts with Sar1, Sec12, and Sec24, and participates in coat protein complex II vesicular transport. Importantly, MtTP930 can recognize the cargo proteins plastidial N-glycosylated nucleotide pyrophosphatase/phosphodiesterase (MtNPP) and α-carbonic anhydrase (MtCAH) in the ER and then transport them to the chloroplast via the secretory pathway. Mutation of a homolog of MtTP930 in Arabidopsis (Arabidopsis thaliana) resulted in a similar dwarf phenotype. Furthermore, MtNPP-GFP failed to localize to chloroplasts when transgenically expressed in Attp930 protoplasts, implying that these cargo sorting receptors are conserved in plants. These findings fill a gap in our understanding of the mechanism by which chloroplast proteins are sorted and transported via the secretory pathway.
Impaired myoblast differentiation and muscle IGF‐1 receptor signaling pathway activation after N‐glycosylation inhibition
Authors: Annibalini Giosuè , Di Patria Laura , Valli Giacomo , Bocconcelli Matteo , Saltarelli Roberta , Ferri Lorenzo , Barberi Laura , Fanelli Fabiana , Morrone Amelia , Barone Rita , Guerrini Renzo , Musarò Antonio , Stocchi Vilberto , Barbieri Elena 
Published: July 2024

AbstractThe role of N‐glycosylation in the myogenic process remains poorly understood. Here, we evaluated the impact of N‐glycosylation inhibition by Tunicamycin (TUN) or by phosphomannomutase 2 (PMM2) gene knockdown, which encodes an enzyme essential for catalyzing an early step of the N‐glycosylation pathway, on C2C12 myoblast differentiation. The effect of chronic treatment with TUN on tibialis anterior (TA) and extensor digitorum longus (EDL) muscles of WT and MLC/mIgf‐1 transgenic mice, which overexpress muscle Igf‐1Ea mRNA isoform, was also investigated. TUN‐treated and PMM2 knockdown C2C12 cells showed reduced ConA, PHA‐L, and AAL lectin binding and increased ER‐stress‐related gene expression (Chop and Hspa5 mRNAs and s/uXbp1 ratio) compared to controls. Myogenic markers (MyoD, myogenin, and Mrf4 mRNAs and MF20 protein) and myotube formation were reduced in both TUN‐treated and PMM2 knockdown C2C12 cells. Body and TA weight of WT and MLC/mIgf‐1 mice were not modified by TUN treatment, while lectin binding slightly decreased in the TA muscle of WT (ConA and AAL) and MLC/mIgf‐1 (ConA) mice. The ER‐stress‐related gene expression did not change in the TA muscle of WT and MLC/mIgf‐1 mice after TUN treatment. TUN treatment decreased myogenin mRNA and increased atrogen‐1 mRNA, particularly in the TA muscle of WT mice. Finally, the IGF‐1 production and IGF1R signaling pathways activation were reduced due to N‐glycosylation inhibition in TA and EDL muscles. Decreased IGF1R expression was found in TUN‐treated C2C12 myoblasts which was associated with lower IGF‐1‐induced IGF1R, AKT, and ERK1/2 phosphorylation compared to CTR cells. Chronic TUN‐challenge models can help to elucidate the molecular mechanisms through which diseases associated with aberrant N‐glycosylation, such as Congenital Disorders of Glycosylation (CDG), affect muscle and other tissue functions.
Case Study on Analysing the Early Disease Detection of Pancreatic Ductal Adenocarcinoma in Korean Association for Clinical Oncology
Authors: Ponnarassery Chandran Sijithra , Santhi N. 
Published: July 2024

Objectives:
Pancreatic ductal adenocarcinoma (PDAC) is the most pervasive sort of pancreatic malignant growth. Due to the lack of early symptoms and effective methods for early detection and screening, the majority of patients (80% to 85%) are diagnosed with advanced metastatic or locally advanced disease, resulting in a low 5-year survival rate of 12%. The case study represents a comprehensive investigation into the intricate landscape of pancreatic cancer diagnosis within the Korean population.

Methods:
Grounded in epidemiological bits of knowledge, the review plans to disentangle the particular examples, commonness, and segment attributes of PDAC in Korea. By scrutinizing current diagnostic modalities, including conventional imaging techniques, molecular markers, and emerging technologies, the research seeks to evaluate the strengths and limitations of existing approaches within the Korean clinical context. Central to the study is an exploration of the collaborative initiatives spearheaded by the Association of Clinical Oncology in Korea in the domain of PDAC early detection. Analysing research projects, clinical trials, and interdisciplinary collaborations, the case study sheds light on the association’s pivotal role in driving innovation and progress in oncology.

Results:
The goal is to offer a detailed analysis of how the association helps in furthering knowledge and enhancing results in the management of PDAC. The case study delves into the implications of early PDAC detection for patient outcomes, emphasizing the significance of timely interventions and tailored treatment strategies. By outlining the potential benefits and challenges associated with early diagnosis, the study aims to inform health care policies, shape clinical guidelines, and guide future research priorities.

Conclusion:
Through a holistic approach, the case study endeavours to offer important experiences into the multifaceted landscape of PDAC early detection within the Korean health care system, contributing to the broader discourse on effective oncological practices and patient care.
An Investigation of Moxibustion Treatment for Abscesses in the Song Dynasty: Focusing on the "Jiu Ai Tu"
Authors: Wang Li 
Published: July 2024

Abstract:

Jiu Ai Tu（灸艾图 The Moxa Treatment）from the Song dynasty is the earliest surviving painting that focuses on the subject of acupuncture and moxibustion. This paper takes the medical activities depicted in the artwork as its research object and systematically analyzes the external treatment methods for abscesses during the Song dynasty reflected in Jiu Ai Tu. By examining the understanding of abscesses during that period, the paper explores the level of development in external medicine techniques. By analyzing the medical awareness and behaviors of patients when facing such severe illnesses, it aims to explore the societal cognition and experiences regarding health and disease. The paper attempts to present the folk medical ecology of the Song dynasty represented by Jiu Ai Tu.
Assessing cachexia in obesity: contradiction or perfectly possible?
Authors: Baracos Vickie E. 
Published: July 2024

Purpose of review
Existing definitions of clinically important weight loss in patients with cancer do not specifically address weight loss in patients who are obese at presentation. This review explores the clinical impact of weight loss and depletion of the skeletal muscle mass (i.e., criteria defining cancer cachexia), in patients with obesity.

Recent findings
Overweight and obese BMI values are shown by many recent studies to pose a survival advantage in patients with cancers of advanced stage, when compared with BMI in normal and underweight ranges. The classification of cancer-associated weight loss has evolved, and current grading schemes evaluate the impact of weight across the range of BMI values. Weight loss is associated with mortality in patients with BMI more than 30 kg/m2, however this is to a much lesser degree than in patients with lower BMI values. Diagnostic imaging permits the precise assessment of skeletal muscle index (SMI) in patients with cancer, and it has been clearly shown that while usually quite muscular, obese patients can have profound muscle depletion (i.e., sarcopenia), independent of the presence of weight loss. Muscle depletion associates strongly with mortality in obese patients, as well as with complications of cancer surgery and systemic therapy.

Summary
It would seem contradictory to diagnose concurrent obesity and cachexia, as these terms represent opposite ends of the weight spectrum. Weight loss can occur in anyone with cancer, however its priority for clinical management may be lesser in obese versus low body weight individuals. Sarcopenic obesity is strongly associated with a poor clinical outcome and deserves further research, diagnosis in clinical practice, and new strategies for mitigation.
Internal dosimetry and biodistribution of indigenously prepared 177Lu-DOTA-rituximab in lymphoma and other hematological malignancies treated with rituximab
Authors: Edamadaka Yeshwanth , Parghane Rahul V. , Sahu Sudeep , Lad Sangita , Kamaldeep  , Wanage Gaurav , Shanmukhaiah Chandrakala , Kulkarni Vrinda , Basu Sandip 
Published: July 2024

Objective
The aim of this study was to evaluate the biodistribution and dosimetry of lutetium-177-1,4,7,10-tetraazacyclododecane-1,4,7,10-tetraacetic acid (177Lu-DOTA)-rituximab in CD20+ non-Hodgkin’s lymphoma and other hematological malignancies treated with rituximab.

Methods
The standard dosimetry protocol was used, with cold rituximab infusion, then a diagnostic activity of 177Lu-DOTA-rituximab. Planar images were acquired at multiple time points. Normal organs and tumor dosimetry were performed by using organ and tumor-specific regions of interest and whole-body counts were obtained serially after pixel matched, background, scatter, and attenuation correction. The mean radiation absorbed doses were obtained from OLINDA/EXM v2.1.1 and ORIGIN software.

Results
A total of 22 patients were included in this study. Prolonged blood pool clearance of 177Lu-DOTA-rituximab with long residence time in the blood pool and normal organs were observed. The whole body effective half-life was 104.5 ± 22 h. The mean total body radiation absorbed dose was 0.208 ± 0.03 mGy/MBq and the mean total body effective dose was 0.196 ± 0.05 mGy/MBq of 177Lu-DOTA-rituximab. The mean radiation absorbed doses of 0.613 ± 0.21, 1.68 ± 2, 1.01 ± 0.42, and 0.136 ± 0.02mGy/MBq were seen for the liver, spleen, kidneys, and bone marrow, respectively. Tumor lesion uptake was noticed in two patients with tumor radiation absorbed doses were 0.842 mGy/MBq in one and 9.9 mGy/MBq in the other patient. A strong correlation was obtained between the cumulative activities of radiation-absorbed doses derived from ORIGIN and OLINDA software methods at a significant P value less than 0.001.

Conclusion
The results of our study demonstrated favorable biodistribution and dosimetry of indigenously produced 177Lu-DOTA-rituximab in patients with CD20+ lymphoma. These results can be used for future studies of radioimmunotherapy employing 177Lu-DOTA-rituximab.
Are maximum magnitudes of induced earthquakes controlled by pressure diffusion?
Authors: Langenbruch Cornelius , Moein Mohammad J. A. , Shapiro Serge A. 
Published: June 2024

There is an ongoing discussion about how to forecast the maximum magnitudes of induced earthquakes based on operational parameters, subsurface conditions and physical process understanding. Although the occurrence of damage caused by induced earthquakes is rare, some cases have caused significant economic loss, injuries and even loss of life. We analysed a global compilation of earthquakes induced by hydraulic fracturing, geothermal reservoir stimulation, water disposal, gas storage and reservoir impoundment. Our analysis showed that maximum magnitudes scale with the characteristic length of pressure diffusion in the brittle Earth’s crust. We observed an increase in the nucleation potential of larger-magnitude earthquakes with time and explained it by diffusion-controlled growth of the pressure-perturbed part of faults. Numerical and analytical fault size modelling supported our findings. Finally, we derived magnitude scaling laws to manage induced seismic hazard of upcoming energy projects prior to operation.
This article is part of the theme issue ‘Induced seismicity in coupled subsurface systems’.
STAN, a computational framework for inferring spatially informed transcription factor activity
Authors: Zhang Linan , Sagan April , Qin Bin , Kim Elena , Hu Baoli , Osmanbeyoglu Hatice Ulku 
Published: June 2024

AbstractTranscription factors (TFs) drive significant cellular changes in response to environmental cues and intercellular signaling. Neighboring cells influence TF activity and, consequently, cellular fate and function. Spatial transcriptomics (ST) captures mRNA expression patterns across tissue samples, enabling characterization of the local microenvironment. However, these datasets have not been fully leveraged to systematically estimate TF activity governing cell identity. Here, we present STAN (Spatially informedTranscription factorActivityNetwork), a linear mixed-effects computational method that predicts spot-specific, spatially informed TF activities by integrating curated TF-target gene priors, mRNA expression, spatial coordinates, and morphological features from corresponding imaging data. We tested STAN using lymph node, breast cancer, and glioblastoma ST datasets to demonstrate its applicability by identifying TFs associated with specific cell types, spatial domains, pathological regions, and ligand‒receptor pairs. STAN augments the utility of STs to reveal the intricate interplay between TFs and spatial organization across a spectrum of cellular contexts.
Graph neural networks best guide phenotypic virtual screening on cancer cell lines
Authors: Vishwakarma Sachin , Hernandez-Hernandez Saiveth , Ballester Pedro J. 
Published: June 2024

AbstractArtificial intelligence is increasingly driving early drug design, offering novel approaches to virtual screening. Phenotypic virtual screening (PVS) aims to predict how cancer cell lines respond to different compounds by focusing on observable characteristics rather than specific molecular targets. Some studies have suggested that deep learning may not be the best approach for PVS. However, these studies are limited by the small number of tested molecules as well as not employing suitable performance metrics and dissimilar-molecules splits better mimicking the challenging chemical diversity of real-world screening libraries. Here we prepared 60 datasets, each containing approximately 30,000 to 50000 molecules tested for their growth inhibitory activities on one of the NCI-60 cancer cell lines. We evaluated the performance of five machine learning algorithms for PVS on these 60 problem instances. To provide a comprehensive evaluation, we employed two model validation types: the random split and the dissimilar-molecules split. The models were primarily evaluated using hit rate, a more suitable metric in VS contexts. The results show that all models are more challenged by test molecules that are substantially different from those in the training data. In both validation types, the D-MPNN algorithm, a graph-based deep neural network, was found to be the most suitable for building predictive models for this PVS problem.
InterLabelGO+: Unraveling label correlations in protein function prediction
Authors: Liu Quancheng , Zhang Chengxin , Freddolino Lydia 
Published: June 2024

ABSTRACTMotivationAccurate protein function prediction is crucial for understanding biological processes and advancing biomedical research. However, the rapid growth of protein sequences far outpaces the experimental characterization of their functions, necessitating the development of automated computational methods.ResultsWe present InterLabelGO+, a hybrid approach that integrates a deep learning-based method with an alignment-based method for improved protein function prediction. InterLabelGO+ incorporates a novel loss function that addresses label dependency and imbalance and further enhances performance through dynamic weighting of the alignment-based component. A preliminary version of InterLabelGO+ achieved a strong performance in the CAFA5 challenge, ranking 6th out of 1,625 participating teams. Comprehensive evaluations on large-scale protein function prediction tasks demonstrate InterLabelGO+’s ability to accurately predict Gene Ontology terms across various functional categories and evaluation metrics.Availability and ImplementationThe source code and datasets for InterLabelGO+ are freely available on GitHub athttps://github.com/QuanEvans/InterLabelGO. The software is implemented in Python and PyTorch, and is supported on Linux and macOS.Contactlydsf@umich.edu(LF) andzcx@umich.edu(CZ)
Origin and evolution of Auxin Efflux Carrier family: PIN, PILS, GPR155 and the others
Authors: Vosolsobě Stanislav , Kurtović Katarina , Schmidt Vojtěch , Skokan Roman , Petrášek Jan 
Published: June 2024

AbstractThe resolution of the 3D structure of PIN proteins and the ability to universally predict protein structures using AlphaFold allowed us to reconsider the classification of Auxin efflux carriers within the BART superfamily, and we propose to merge members of this superfamily, possessing a characteristic fold with a helical crossover, with other families carrying this fold (BASS, NhaA, CPA and others) into a newly proposed superfamily named X-Helices Carriers (XHC). We further demonstrate a profound divergence between PIN and PILS proteins and monophyly of eukaryotic PINs with the animal cholesterol receptor GPR155/LYCHOS. We hypothesise that its signalling capacity is derived from a general feature of PIN proteins to interact with membrane lipids within the core membrane fold. Finally, we discuss the auxin-transport ability of PIN and PILS proteins in the context of the described properties of bacterial homologs that act as organic acid permeases.DisclaimerThis version is a draft and it will be updated during the next few weeks.HighlightsPINs are in plants and fragmentary in many algae and protists, but never in fungiEukaryotic PINs are monophyletic together with animal cholesterol receptor GPR155PILS are frequently present in protists and in all fungi, but not in animalsPINs/PILS split is occurred very early in ProkaryotaAECs belongs to proposed superfamily of transporter with helical crossover
Cell-type-specific alternative splicing in the cerebral cortex of a Schinzel-Giedion Syndrome patient variant mouse model
Authors: Jones Emma F. , Howton Timothy C. , Soelter Tabea M. , Crumley Anthony B. , Lasseigne Brittany N. 
Published: June 2024

AbstractSchinzel-Giedion Syndrome (SGS) is an ultra-rare Mendelian disorder caused by gain-of-function mutations in theSETBP1gene. While previous studies determined multiple roles for howSETBP1and associated pathways may cause disease manifestation, they have not assessed whether cell-type-specific alternative splicing (AS) plays a role in SGS. We used STARsolo to quantify gene and splice junction (SJ) expression for 51,465 nuclei previously generated from the cerebral cortex of atypicalSetbp1S858RSGS patient variant mice (n = 3) and wild-type control mice (n = 3). After cell type annotation, we performed pseudobulk differential gene expression and SJ usage (SJU) analyses across cell types and conditions. We identified 34 genes with statistically significant alterations in SJU. Oligodendrocytes had the most genes with changes in SJU, followed by astrocytes, excitatory, and inhibitory neurons. One gene,Son, a splicing cofactor known to cause the neurodevelopmental disorder ZTTK Syndrome, had SJU changes in all six non-vascular cell types we measured inSetbp1S858Rcompared to controls. This is the first research to report AS changes in the cerebral cortex of an SGS model and the first study to link SGS to perturbations inSon.
Barking Up the Right Tree: Immune Checkpoint Signatures of Human and Dog Cancers
Authors: Kocikowski Mikolaj , Yébenes Mayordomo Marcos , Alfaro Javier , Parys Maciej 
Published: June 2024

AbstractIn the quest for improved therapeutics targeting immune checkpoints (ICs), we turn to spontaneously developing dog (canine) cancers, which are unique models that genetically and clinically mirror human equivalents. Despite its potential, canine cancer immunology remains largely unexplored. Here, we examine the RNA-seq-based expression of 44 ICs across 14 canine cancer types and an extensive human dataset. We unveil diverse canine IC expression patterns and unique human IC signatures that reflect the histological type and primary site of cancer. We uncover a striking similarity between canine brain cancers, osteosarcoma, and their human counterparts, identifying them as prospective immunotherapy models. Four ICs—CD160, A2AR, NKG2A, and OX40—are key to the differences observed between species. Moreover, individual patient IC signatures exhibit varying alignment with their respective cancer types, a finding with profound implications for personalized human therapy. This exploration illuminates new aspects of canine and human cancer immunology, setting the stage for discoveries at their crossroads.