bluuebunny/crossref_metadata_2025_split huggingface dataset:
Nutrient loading from a sustainably certified aquaculture operation dwarfs annual nutrient inputs from a large multi-use watershed, Lake Yojoa, Honduras
Authors: Fadum J.M. , Ross M.V.R. , Tenorio E. A. , Barby C.A. , Hall E.K. 
Published: March 2024

AbstractNet-pen aquaculture is a popular and increasingly prevalent method for producing large quantities of low-fat protein in freshwater ecosystems across the tropics. While there are numerable social and economic advantages associated with aquaculture, there are also challenges related to the environmental sustainability of aquaculture. Chief among these risks is excessive nutrient loading which can drive rapid eutrophication in aquatic ecosystems. In this study, we compare the estimated annual nutrient loads from the six principal tributaries that contribute to Lake Yojoa to the estimated nutrient load of a large net-pen Tilapia operation located in the central region of the lake. We estimated that the Tilapia farm was responsible for ~ 86% of nitrogen (N) and ~95% of the phosphorus (P) annual contributions to Lake Yojoa. This disproportionate nutrient loading of both N and P suggests that this single aquaculture operation, more so than changes in nutrients inputs from the watershed, was responsible for the previously documented deterioration of the Lake Yojoa ecosystem. This study shows the potential for net-pen aquaculture to have disproportionately negative impacts on freshwater ecosystems, even when operations meet all standards for the current state-of-the-art sustainability certifications. We suggest shifts in metrics that could improve the impact of the certification process so that best practices can reduce the impact of net-pen aquaculture on freshwater ecosystems and arrive at the intended goal of long-term environmental sustainability.
Temporal interference electrical neurostimulation yields fMRI BOLD activation in humans
Authors: Modak Priyamvada , Fine Justin , Colon Brayden , Need Ella , Hulvershorn Leslie , Finn Peter , Brown Joshua W 
Published: March 2024

AbstractTemporal interference electrical neurostimulation (TI) is a relatively new method of non-invasive neurostimulation that may be able to stimulate deep brain regions without stimulating the overlying superficial regions. Despite studies in rodents, almost no studies have investigated its effects on human brain activity along with safety and tolerability profiles. We performed simultaneous TI stimulation and fMRI to investigate the effects of TI on human BOLD signals. Here we show that TI can induce increased BOLD activation in humans, with good safety and tolerability profiles. We also show the limits of spatial precision and explore the nature and causes of additional off target effects. TI may be a promising approach for addressing questions about the causal role of deep brain structures in human cognition and may also afford new clinical treatments.
Investigating the mode of action for wasting produced by tetrachlorodibenzo-p-dioxin (TCDD) in rats using transcriptomics: Evidence for roles of AHR and ARNT in circadian cycling
Authors: Andersen Melvin E. , Barutcu A. Rasim , Black Michael B. , Harrill Joshua A. 
Published: March 2024

AbstractSingle, high doses of TCDD in rats caused wasting, a progressive loss of 30 to 50% body weight and death within several weeks. To identify pathway perturbations at or near doses causing wasting, we examined differentially gene expression (DGE) and pathway enrichment in centrilobular (CL) and periportal (PP) regions of female rat livers following 6 dose levels of TCDD – 0, 3, 22, 100, 300, and 1000 ng/kg/day, 5 days/week for 4 weeks. At the higher doses, rats lost weight, had increased liver/body weight ratios and nearly complete cessation of liver cell proliferation, signs consistent with wasting. DGE curves were left shifted for the CL versus the PP regions. Canonical Phase I and Phase II genes were maximally increased at lower doses and remained elevated at all doses. At lower doses,<22 ng/kg/day in the CL and<100 ng/kg/day, upregulated genes showed transcription factor (TF) enrichment for AHR and ARNT. At the mid- and hi-dose doses, there was a large number of downregulated genes and pathway enrichment for DEGs showed downregulation of many cellular metabolism processes including those for steroids, fatty acid metabolism, pyruvate metabolism and citric acid cycle. There was significant TF enrichment of the hi-dose downregulated genes for RXR, ESR1, LXR, PPARalpha. At the highest dose, there was also pathway enrichment with upregulated genes for extracellular matrix organization, collagen formation, hemostasis and innate immune system. TCDD demonstrates most of its effects through binding the aryl hydrocarbon receptor (AHR) while the downregulation of metabolism genes at higher TCDD doses is known to be independent of AHR binding to DREs. Based on our results with DEG, we provide a hypothesis for wasting in which high doses of TCDD shifts circadian processes away from the resting state leading to greatly reduced synthesis of steroids and complex lipids needed for cell growth and producing gene expression signals consistent with an epithelial-to-mesenchymal transition in hepatocytes.
Rectal Swab DNA Collection Protocol for PCR Genotyping in Rats
Authors: Kaye Audrey E. , Proctor-Bonbright Jacob W. , Yu Jai Y. 
Published: March 2024

AbstractDNA collection is essential for genotyping laboratory animals. However, common collection methods require tissue amputation, causing discomfort and injury. Rectal swabbing has been proposed as an effective non-invasive alternative, but an evidence-backed protocol for the technique remains unavailable. We evaluate the effect of collection parameters on PCR result quality and present a genotyping protocol that can yield results for a litter of rats within 3-5 hours. We found that samples with 2-8 scrapes produced enough DNA to amplify targets up to ∼1800bp long using PCR. Rectal swabbing produced PCR results with similar quality to ear clip samples, and results were unaffected by residual fecal matter or cell debris. Our protocol enables fast, non-invasive, and repeatable genotyping using commercial PCR reagents.
Transformer-Based Deep Learning Model with Latent Space Regularization for CRISPR-Cas Protein Sequence Classification
Authors: Nammi Bharani , Madugula Sita Sirisha , Pujar Pranav , Arachchige Vindi Mahesha Jayasinghe , Liu Jin , Wang Shouyi 
Published: March 2024

AbstractThe discovery of the CRISPR-Cas system has significantly advanced genome editing, offering vast applications in medical treatments and life sciences research. Despite their immense potential, the existing CRISPR-Cas proteins still face challenges concerning size, delivery efficiency, and cleavage specificity. Addressing these challenges necessitates a deeper understanding of CRISPR-Cas proteins to enhance the design and discovery of novel Cas proteins for precision gene editing. In this study, we performed extensive deep-learning research on CRISPR-Cas proteins, aiming to develop a classification model capable of distinguishing CAS from non-CAS proteins, as well as discriminating sub-categories of CAS proteins, specifically CAS9 and CAS12. We developed two types of deep learning models: 1) a transformer encoder-based classification model, trained from scratch; and 2) a large protein language model fine-tuned on ProtBert, pre-trained on more than 200 million proteins. To boost learning efficiency for the model trained from scratch, we introduced a novel margin-based loss function to maximize inter-class separability and intra-class compactness in protein sequence embedding latent space of a transformer encoder. The experimental results show that the Fine-Tuned ProtBert-based (FTPB) classification model achieved accuracies of 99.06%, 94.42%, 96.80%, 97.57% for CAS9 vs. Non-CAS, CAS12 vs. Non-CAS, CAS9 vs. CAS12, and multi-class classification of CAS9 vs. CAS12 vs. Non-CAS, respectively. The Latent Space Regularized Max-Margin Transformer (LSRMT) model achieved classification accuracies of 99.81%, 99.81%, 99.06%, 99.27% for the same tasks, respectively. These results demonstrate the effectiveness of the proposed Max-Margin-based latent space regularization in enhancing model robustness and generalization capabilities. Remarkably, the LSRMT model, even when trained on a significantly smaller dataset, outperformed the fine-tuned state-of-the-art large protein model. The high classification accuracies achieved by the LSRMT model demonstrate its proficiency in identifying discriminative features of CAS proteins, marking a significant step towards advancing our understanding of CAS protein structures in future research endeavors.
Thymic dendritic cell-derived IL-27p28 promotes the establishment of functional bias against IFN-γ production in newly generated CD4+T cells through STAT1-related epigenetic mechanisms
Authors: Zhang Jie , Tang Hui , Wu Haoming , Pang Xuewen , Jin Rong , Zhang Yu 
Published: March 2024

AbstractThe newly generated CD4 single-positive (SP) T lymphocytes are featured by enhanced IL-4 but repressed IFN-γ production. The mechanisms underlying this functional bias remain elusive. Previous studies have reported that CD4+T cells from mice harboring DC-specific deletion of IL-27p28 display an increased capacity of IFN-γ production upon TCR stimulation. Here we demonstrated that similarly altered functionality occurred in CD4SP thymocytes, recent thymic emigrants (RTEs), as well as naive T cells from eitherCd11c-p28f/fmice or mice deficient in the α subunit of IL-27 receptor. Therefore, DC-derived IL-27p28-triggered, IL-27Rα-mediated signal is critically involved in the establishment of functional bias against IFN-γ production during their development in the thymus. Epigenetic analyses indicated reduced DNA methylation of theIfnglocus and increased trimethylation of H3K4 at bothIfngandTbx21loci in CD4SP thymocytes fromCd11c-p28f/fmice. Transcriptome profiling demonstrated thatIl27p28ablation resulted in the coordinated up-regulation of STAT1-activated genes. Concurrently, STAT1 was found to be constitutively activated. Moreover, we observed increased accumulation of STAT1 at theIfngandTbx21loci and a strong correlation between STAT1 binding and H3K4me3 modification of these loci. Of note,Il27p28deficiency exacerbated the autoimmune phenotype ofAire-/-mice. Collectively, this study reveals a novel mechanism underlying the functional bias of newly generated CD4+T cells and the potential relevance of such a bias in autoimmunity.Graphical abstract
Unsupervised generative AI discovers pan-leukocyte dysregulated pathways in single-cell lupus data
Authors: Bolouri Hamid , Cerosaletti Karen , Lacy-Hulbert Adam 
Published: March 2024

AbstractComparisons of single-cell RNA-sequencing (scRNA-seq) data from healthy and diseased tissues are widely used to identify cell-type-specific dysregulated genes, pathways, and processes. Accordingly, many sophisticated methods have been developed for this purpose. However, such tools generally require considerable user expertise for optimal performance. Here, we show that unsupervised application of a linearly-decoded Variational Auto Encoder (a generative AI model) to scRNA-seq data recapitulates and extends findings from a seminal recent lupus study and leads to new insights. Thanks to existing software libraries, our approach is straightforward to implement, computationally efficient, methodologically robust, and produces consistent and reproducible results.
Conformational landscape of soluble α-klotho revealed by cryogenic electron microscopy
Authors: Schnicker Nicholas J. , Xu Zhen , Amir Mohammad , Gakhar Lokesh , Huang Chou-Long 
Published: March 2024

ABSTRACTα-Klotho (KLA) is a type-1 membranous protein that can associate with fibroblast growth factor receptor (FGFR) to form co-receptor for FGF23. The ectodomain of unassociated KLA is shed as soluble KLA (sKLA) to exert FGFR/FGF23-independent pleiotropic functions. The previously determined X-ray crystal structure of the extracellular region of sKLA in complex with FGF23 and FGFR1c suggests that sKLA functions solely as an on-demand coreceptor for FGF23. To understand the FGFR/FGF23-independent pleiotropic functions of sKLA, we investigated biophysical properties and structure of apo-sKLA. Mass photometry revealed that sKLA can form a stable structure with FGFR and/or FGF23 as well as sKLA dimer in solution. Single particle cryogenic electron microscopy (cryo-EM) supported the dimeric structure of sKLA. Cryo-EM further revealed a 3.3Å resolution structure of apo-sKLA that overlays well with its counterpart in the ternary complex with several distinct features. Compared to the ternary complex, the KL2 domain of apo-sKLA is more flexible. 3D variability analysis revealed that apo-sKLA adopts conformations with different KL1-KL2 interdomain bending and rotational angles. The potential multiple forms and shapes of sKLA support its role as FGFR-independent hormone with pleiotropic functions. A comprehensive understanding of the sKLA conformational landscape will provide the foundation for developing klotho-related therapies for diseases.
Integration of pH control into Chi.Bio reactors and demonstration with small-scale enzymatic poly(ethylene terephthalate) hydrolysis
Authors: Denton Mackenzie C.R. , Murphy Natasha P. , Norton-Baker Brenna , Lua Mauro , Steel Harrison , Beckham Gregg T. 
Published: March 2024

AbstractSmall-scale bioreactors that are affordable and accessible would be of major benefit to the research community. In previous work, an open-source, automated bioreactor system was designed to operate up to the 30 mL scale with online optical monitoring, stirring, and temperature control, and this system, dubbed Chi.Bio, is now commercially available at a cost that is typically 1-2 orders of magnitude less than commercial bioreactors. In this work, we further expand the capabilities of the Chi.Bio system by enabling continuous pH monitoring and control through hardware and software modifications. For hardware modifications, we sourced low-cost, commercial pH circuits and made straightforward modifications to the Chi.Bio head plate to enable continuous pH monitoring. For software integration, we introduced closed-loop feedback control of the pH measured inside the Chi.Bio reactors and integrated a pH-control module into the existing Chi.Bio user interface. We demonstrated the utility of pH control through the small-scale depolymerization of the synthetic polyester, poly(ethylene terephthalate) (PET), using a benchmark cutinase enzyme, and compared this to 250 mL bioreactor hydrolysis reactions. The results in terms of PET conversion and rate, measured both by base addition and product release profiles, are statistically equivalent, with the Chi.Bio system allowing for a 20-fold reduction of purified enzyme required relative to the 250 mL bioreactor setup. Through inexpensive modifications, the ability to conduct pH control in Chi.Bio reactors widens the potential slate of biochemical reactions and biological cultivations for study in this system, and may also be adapted for use in other bioreactor platforms.
Vegetative stage and soil horizon determine direction and magnitude of rhizosphere priming effects in contrasting treeline soils
Authors: Michel Jennifer , Fontaine Sébastien , Revaillot Sandrine , Piccon-Cochard Catherine , Whitaker Jeanette 
Published: March 2024

AbstractTreelines in high latitudes and high altitudes are considered sentinels of global change. This manifests in accelerated encroachment of trees and shrubs and enhanced plant productivity, with currently unknown implications for the carbon balance of these biomes. Given the large soil organic carbon stocks in many treeline soils, we here wondered whether introducing highly productive plants would accelerate carbon cycling through rhizosphere priming effects and if certain soils would be more vulnerable to carbon loss from positive priming than others.To test this, organic and mineral soils were sampled above and below treelines in the Swedish sub-arctic and the Peruvian Andes. A greenhouse experiment was then performed to quantify plant-induced changes in soil mineralisation rates (rhizosphere priming effect) and new C formation using natural abundance labelling and the C4-species Cynodon dactylon. Several environmental, plant, soil and microbial parameter were monitored during the experiment to complement the observations on soil C cycling.Priming was predominantly positive at the beginning of the experiment, then systematically decreased in all soils during the plant growth season to be mostly negative at the end of the experiment at plant senescence. Independent of direction of priming, the magnitude of priming was always greater in organic than in corresponding mineral soils, which was best explained by the higher C contents of these soils. Integrated over the entire study period, the overall impact of priming (positive and negative) on the soil C balance was mostly negligible. Though, net soil C loss was observed in organic soils from the sub-arctic tundra in Sweden.Most notably, positive and negative priming effects were not mutually exclusive, rather omnipresent across ecosystems, depending on sampling time. The direction of priming seems to be fluctuating with plant productivity, rhizosphere carbon inputs and nutrient uptake. This highlights the need for integrative long-term studies if we aim to understand priming effects at ecosystem scale and greenhouse and laboratory studies must be validated in situ to enable reliable ecological upscaling.
Causal Brain Network Evaluates Surgical Outcomes in Patients with Drug-Resistant Epilepsy
Authors: Wang Yalin , Liu Minghui , Lin Wentao , Zheng Weihao , Wang Tiancheng , Liu Yaqing , Peng Hong , Chen Wei , Hu Bin 
Published: March 2024

AbstractNetwork neuroscience has greatly facilitated epilepsy studies; meanwhile, drug-resistant epilepsy (DRE) is increasingly recognized as a brain network disorder. Unfortunately, surgical success rates in patients with DRE are still very limited, varying 30% ∼ 70%. At present, there is almost no systematic exploration of intracranial electrophysiological brain network closely related to surgical outcomes, and it is not clear which brain network methodologies can effectively promote DRE precision medicine. In this retrospective comparative study, we included multicenter datasets, containing electrocorticogram (ECoG) data from 17 DRE patients with 55 seizures. Ictal ECoG within clinically-annotated epileptogenic zone (EZ) and non-epileptogenic zone (NEZ) were separately computed using six different algorithms to construct causal brain networks. All the brain network results were divided into two groups, successful and failed surgery. Statistical results based on the Mann-Whitney-U-test show that: causal connectivity of α-frequency band (8 ∼ 13 Hz) in EZ calculated by convergent cross mapping (CCM) gains the most significant differences between the surgical success and failure groups, with aPvalue of 7.85e-08 and Cohen’s d effect size of 0.77. CCM-defined EZ brain network can also distinguish the successful and failed surgeries considering clinical covariates (clinical centers, DRE types) withP< 0. 001. Based on the brain network features, machine learning models are established to predict the surgical outcomes. Among them, SVM classifier with Gaussian kernel function and Bayesian Optimization demonstrates the highest average accuracy of 84.48% through 5-fold cross validation, further indicating that the CCM-defined EZ brain network is a reliable biomarker for predicting DRE’s surgical outcomes.
Distinct prelimbic cortex neuronal responses to emotional states of others drive emotion recognition in adult male mice
Authors: Jabarin Renad , Mohapatra Alok Nath , Ray Natali , Netser Shai , Wagner Shlomo 
Published: March 2024

SummaryThe ability to perceive the emotional states of others, termed emotion recognition, allows individuals to adapt their conduct to the social environment. The brain mechanisms underlying this capacity, known to be impaired in individuals with autism spectrum disorder (ASD), remain, however, elusive. Using the emotional state preference paradigm, we show that adult mice can discern emotional states of conspecifics in a sex-specific manner, behavior impaired in an ASD mouse model. Fiber photometry revealed inhibition of pyramidal neurons in the prelimbic medial prefrontal cortex (PrL) during investigation of aroused individuals, as opposed to transient excitation towards non-aroused conspecifics. Augmenting this differential neuronal response enhanced emotion recognition, while abolishing this response eliminated such behavior, as demonstrated via optogenetic stimulation. Chronic electrophysiological recordings at the single-cell level indicated social stimulus-specific responses in PrL neurons at the onset and conclusion of social investigation bouts, potentially regulating the initiation and termination of social interactions. The dysregulated activity of these neurons may thus contribute to deficits in social behavior observed in ASD.
Combining function and structure in a single macro-scale connectivity model of the human brain
Authors: Sairanen Viljami 
Published: March 2024

AbstractCombining the macro-scale functional and structural connectivity matrices of the human brain could provide useful information on how various diseases and conditions affect the brain. However, it is not a simple task to combine such information as they are derived usually in very different ways with functional information typically gathered using fMRI, EEG, or MEG whereas structural information relies on robust diffusion-weighted MRI tractography methods. This work proposes a solution to this problem using an analogy to an electric circuit with the functional information being the voltage sources and the structural information resistance of the elements in the circuit. The voltage sources and resistances can be used to solve the current in the circuit using Modified Nodal Analysis, for example. In the proposed analogy, the solved electric current represents how the functional information flows in the structural brain network. This work demonstrates a connection-specific example of such analysis as well as whole-brain analysis using data from the Human Connectome Project. Another dataset of functional and structural data from healthy brains is used to demonstrate that the proposed method can be used to study the aging of the human brain. The main motivation for the proposed analysis method is that it could provide new information on various conditions and diseases such as Alzheimer’s that affect the human brain. In a sense, the proposed functio-structural current (FSC) analysis is a macro-scale version of the classical Hodkin-Huxley model.