Beef Cattle Genome Project: Advances in Genome Sequencing, Assembly, and Functional Genes Discovery.

Beef is a major global source of protein, playing an essential role in the human diet. The worldwide production and consumption of beef continue to rise, reflecting a significant trend. However, despite the critical importance of beef cattle resources in agriculture, the diversity of cattle breeds faces severe challenges, with many breeds at risk of extinction. The initiation of the Beef Cattle Genome Project is crucial. By constructing a high-precision functional annotation map of their genome, it becomes possible to analyze the genetic mechanisms underlying important traits in beef cattle, laying a solid foundation for breeding more efficient and productive cattle breeds. This review details advances in genome sequencing and assembly technologies, iterative upgrades of the beef cattle reference genome, and its application in pan-genome research. Additionally, it summarizes relevant studies on the discovery of functional genes associated with key traits in beef cattle, such as growth, meat quality, reproduction, polled traits, disease resistance, and environmental adaptability. Finally, the review explores the potential of telomere-to-telomere (T2T) genome assembly, structural variations (SVs), and multi-omics techniques in future beef cattle genetic breeding. These advancements collectively offer promising avenues for enhancing beef cattle breeding and improving genetic traits.

The diagnostic value of CT-based radiomics nomogram for solitary indeterminate smoothly marginated solid pulmonary nodules.

Objectives: This study aimed to explore the value of radiomics nomogram based on computed tomography (CT) on the diagnosis of benign and malignant solitary indeterminate smoothly marginated solid pulmonary nodules (SMSPNs). Methods: This study retrospectively reviewed 205 cases with solitary indeterminate SMSPNs on CT, including 112 cases of benign nodules and 93 cases of malignant nodules. They were divided into training (n=143) and validation (n=62) cohorts based on different CT scanners. Radiomics features of the nodules were extracted from the lung window CT images. The variance threshold method, SelectKBest, and least absolute shrinkage and selection operator were used to select the key radiomics features to construct the rad-score. Through multivariate logistic regression analysis, a nomogram was built by combining rad-score, clinical factors, and CT features. The nomogram performance was evaluated by the area under the receiver operating characteristic curve (AUC). Results: A total of 19 radiomics features were selected to construct the rad-score, and the nomogram was constructed by the rad-score, one clinical factor (history of malignant tumor), and three CT features (including calcification, pleural retraction, and lobulation). The nomogram performed better than the radiomics model, clinical model, and experienced radiologists who specialized in thoracic radiology for nodule diagnosis. The AUC values of the nomogram were 0.942 in the training cohort and 0.933 in the validation cohort. The calibration curve and decision curve showed that the nomogram demonstrated good consistency and clinical applicability. Conclusion: The CT-based radiomics nomogram achieved high efficiency in the preoperative diagnosis of solitary indeterminate SMSPNs, and it is of great significance in guiding clinical decision-making.

The Preparation and Evaluation of a Hydrochloride Hydrogel Patch with an Iontophoresis-Assisted Release of Terbinafine for Transdermal Delivery.

Background: Terbinafine hydrochloride (TEB) is a broad-spectrum antifungal medication commonly used to treat fungal infections of the skin. This study designed a hydrogel patch assisted by an iontophoresis system to enhance the transdermal permeability of TEB, enabling deeper penetration into the skin layers. Methods: The influences of current intensity, pH levels, and drug concentration on the TEB hydrogel patch's permeability were explored using an adaptive ion electroosmosis system. The pharmacokinetic profile, facilitated by iontophoresis for transdermal permeation, was analyzed through the application of microdialysis technology. Scanning electron microscopy and transmission electron microscopy were employed to assess the impact of ion electroosmotic systems on skin integrity. Results: The cumulative drug accumulation within 8 h of the TEB hydrogel patches, assisted by iontophoresis, was 2.9 and 7.9 times higher than without iontophoresis assistance and TEB cream in the control group, respectively. TEB hydrogel patches assisted by iontophoresis can significantly increase the permeability of TEB, and the AUC(0-8 h) was 3.4 and 5.4 times higher, while the Cmax was 4.2 and 7.3 times higher than the TEB hydrogel patches without iontophoresis, respectively. This system has no significant impact on deep-layer cells. Conclusions: This system may offer a safe and effective clinical strategy for the local treatment of deep antifungal infections.

TMPRSS2 and glycan receptors synergistically facilitate coronavirus entry.

The entry of coronaviruses is initiated by spike recognition of host cellular receptors, involving proteinaceous and/or glycan receptors. Recently, TMPRSS2 was identified as the proteinaceous receptor for HCoV-HKU1 alongside sialoglycan as a glycan receptor. However, the underlying mechanisms for viral entry remain unknown. Here, we investigated the HCoV-HKU1C spike in the inactive, glycan-activated, and functionally anchored states, revealing that sialoglycan binding induces a conformational change of the NTD and promotes the neighboring RBD of the spike to open for TMPRSS2 recognition, exhibiting a synergistic mechanism for the entry of HCoV-HKU1. The RBD of HCoV-HKU1 features an insertion subdomain that recognizes TMPRSS2 through three previously undiscovered interfaces. Furthermore, structural investigation of HCoV-HKU1A in combination with mutagenesis and binding assays confirms a conserved receptor recognition pattern adopted by HCoV-HKU1. These studies advance our understanding of the complex viral-host interactions during entry, laying the groundwork for developing new therapeutics against coronavirus-associated diseases.

Transcriptome Profiling Reveals the Response of Seed Germination of Peganum harmala to Drought Stress.

Peganum harmala L. is a perennial herbaceous plant that plays critical roles in protecting the ecological environment in arid, semi-arid, and desert areas. Although the seed germination characteristics of P. harmala in response to environmental factors (i.e., drought, temperature, and salt) have been investigated, the response mechanism of seed germination to drought conditions has not yet been revealed. In this study, the changes in the physiological characteristics and transcriptional profiles in seed germination were examined under different polyethylene glycol (PEG) concentrations (0-25%). The results show that the seed germination rate was significantly inhibited with an increase in the PEG concentration. Totals of 3726 and 10,481 differentially expressed genes (DEGs) were, respectively, generated at 5% and 25% PEG vs. the control (C), with 1642 co-expressed DEGs, such as drought stress (15), stress response (175), and primary metabolism (261). The relative expression levels (RELs) of the key genes regulating seed germination in response to drought stress were in accordance with the physiological changes. These findings will pave the way to increase the seed germination rate of P. harmala in drought conditions.

Transcriptomic annotation of the Chungtien schizothoracin (Ptychobarbus chungtienensis) using Iso-seq and RNA-seq data.

The Chungtien schizothoracin (Ptychobarbus chungtienensis), an endangered fish species endemic to the Zhongdian Plateau, remains underexplored in terms of transcriptomic sequencing. This investigation used tissues from five distinct organs (heart, liver, spleen, kidney, and brain) of the Chungtien schizothoracin for PacBio Iso-seq and RNA-seq analyses, yielding a repertoire of 16,598 full-length transcripts spanning lengths from 363 bp to 7,157 bp. Gene family clustering and phylogenetic analysis encompassed a comprehensive set of 13 fish species, all of which were cyprinids, including the zebrafish and the examined species Ptychobarbus chungtienensis. Moreover, the identification of long non-coding RNAs (lncRNAs) and coding sequences was accomplished across all five tissues. Comprehensive analyses of gene expression profiles and differentially expressed genes among the above five tissues were performed. In summary, the obtained full-length transcripts and detailed gene expression profiles of the Chungtien schizothoracin tissues furnish crucial expression data and genetic sequences, laying the groundwork for future investigations and fostering a holistic comprehension of the adaptive mechanisms inherent in the Chungtien schizothoracin under various conditions.

NIN-LIKE PROTEIN3.2 inhibits repressor Aux/IAA14 expression and enhances root biomass in maize seedlings under low nitrogen.

Plants generally enhance their root growth in the form of greater biomass and/or root length to boost nutrient uptake in response to short-term low nitrogen (LN). However, the underlying mechanisms of short-term LN-mediated root growth remain largely elusive. Our genome-wide association study, haplotype analysis, and phenotyping of transgenic plants showed that the crucial nitrate signaling component NIN-LIKE PROTEIN3.2 (ZmNLP3.2), a positive regulator of root biomass, is associated with natural variations in root biomass of maize (Zea mays L.) seedlings under LN. The monocot-specific gene AUXIN/INDOLE-3-ACETIC ACID14 (ZmAux/IAA14) exhibited opposite expression patterns to ZmNLP3.2 in ZmNLP3.2 knockout and overexpression lines, suggesting that ZmNLP3.2 hampers ZmAux/IAA14 transcription. Importantly, ZmAux/IAA14 knockout seedlings showed a greater root dry weight (RDW), whereas ZmAux/IAA14 overexpression reduced RDW under LN compared with wild-type plants, indicating that ZmAux/IAA14 negatively regulates the RDW of LN-grown seedlings. Moreover, in vitro and vivo assays indicated that AUXIN RESPONSE FACTOR19 (ZmARF19) binds to and transcriptionally activates ZmAux/IAA14, which was weakened by the ZmNLP3.2-ZmARF19 interaction. The zmnlp3.2 ZmAux/IAA14-OE seedlings exhibited further reduced RDW compared to ZmAux/IAA14 overexpression lines when subjected to LN treatment, corroborating the ZmNLP3.2-ZmAux/IAA14 interaction. Thus, our study reveals a ZmNLP3.2-ZmARF19-ZmAux/IAA14 module regulating root biomass in response to nitrogen limitation in maize.

[Research progress on bioactive constituents and pharmacological effects of Tibetan medicine Sinopodophylli Fructus].

Sinopodophylli Fructus is a traditional medicine used by the Tibetan people. It is known for its ability to regulate menstruation and promote blood circulation. Presently, bioactive constituents that have been isolated and identified from Sinopodophylli Fructus mainly include 15 lignans(e.g., podophyllotoxin, deoxypodophyllotoxin, and 4'-demethylpodophyllotoxin) and 20 flavonoids(e.g., quercetin, kaempferol, and rutin). These components exhibit pharmacological effects such as anticancer, antibacterial, and lipid-lowering activities. Additionally, Sinopodophylli Fructus contains other components such as proteins, fatty acids, polysaccharides, vitamins, amino acids, and trace elements. According to the relevant literature reports in China and abroad, this article reviewed the chemical constituents and pharmacological effects of Sinopodophylli Fructus, aiming to provide references for the development and rational clinical application of this medicinal resource.

The Efficacy of Neuromodulation Interventions for Chemotherapy-Induced Peripheral Neuropathy: A Systematic Review and Meta-Analysis.

Purpose: To determine the efficacy and safety of a neuromodulation intervention regimen in the treatment of chemotherapy-induced peripheral neuropathy (CIPN). Patients and Methods: Systematic searches were conducted in seven English databases. Randomized controlled trials of all neuromodulation interventions (both invasive and non-invasive) for the treatment of CIPN were selected. Group comparisons of differences between interventions and controls were also made. We divided the outcomes into immediate-term effect (≤3 weeks), short-term effect (3 weeks to ≤3 months), and long-term effect (>3 months). Results: Sixteen studies and 946 patients with CIPN were included. Among immediate-term effects, neuromodulation interventions were superior to usual care for improving pain (SMD=-0.77, 95% CI -1.07~ 0.47), FACT-Ntx (MD = 5.35, 95% CI 2.84~ 7.87), and QOL (SMD = 0.44, 95% CI 0.09~ 0.79) (moderate certainty); neuromodulation loaded with usual care was superior to usual care for improving pain (SMD=-0.47, 95% CI -0.71 ~ -0.23), and QOL (SMD = 0.40, 95% CI 0.12 ~ 0.69) (moderate certainty). There were no statistically significant differences between the neuromodulation interventions regimen vs usual care in short- and long-term outcomes and neuromodulation vs sham stimulation from any outcome measure. There were mild adverse events such as pain at the site of stimulation and bruising, and no serious adverse events were reported. Conclusion: Neuromodulation interventions had significant immediate-term efficacy in CIPN but had not been shown to be superior to sham stimulation; short-term and long-term efficacy could not be determined because there were too few original RCTs. Moreover, there are no serious adverse effects of this therapy.

NIR-II nanoprobes for investigating the glymphatic system function under anesthesia and stroke injury.

The glymphatic system plays an important role in the transportation of cerebrospinal fluid (CSF) and the clearance of metabolite waste in brain. However, current imaging modalities for studying the glymphatic system are limited. Herein, we apply NIR-II nanoprobes with non-invasive and high-contrast advantages to comprehensively explore the function of glymphatic system in mice under anesthesia and cerebral ischemia-reperfusion injury conditions. Our results show that the supplement drug dexmedetomidine (Dex) enhances CSF influx in the brain, decreases its outflow to mandibular lymph nodes, and leads to significant differences in CSF accumulation pattern in the spine compared to isoflurane (ISO) alone, while both ISO and Dex do not affect the clearance of tracer-filled CSF into blood circulation. Notably, we confirm the compromised glymphatic function after cerebral ischemia-reperfusion injury, leading to impaired glymphatic influx and reduced glymphatic efflux. This technique has great potential to elucidate the underlying mechanisms between the glymphatic system and central nervous system diseases.

Expansion and improvement of ChinaMu by MuT-seq and chromosome-level assembly of the Mu-starter genome.

ChinaMu is the largest sequence-indexed Mutator (Mu) transposon insertional library in maize (Zea mays). In this study, we made significant improvements to the size and quality of the ChinaMu library. We developed a new Mu-tag isolation method Mu-Tn5-seq (MuT-seq). Compared to the previous method used by ChinaMu, MuT-seq recovered 1/3 more germinal insertions, while requiring only about 1/14 of the sequencing volume and 1/5 of the experimental time. Using MuT-seq, we identified 113,879 germinal insertions from 3,168 Mu-active F1 families. We also assembled a high-quality genome for the Mu-active line Mu-starter, which harbors the initial active MuDR element and was used as the pollen donor for the mutation population. Using the Mu-starter genome, we recovered 33,662 (15.6%) additional germinal insertions in 3,244 (7.4%) genes in the Mu-starter line. The Mu-starter genome also improved the assignment of 117,689 (54.5%) germinal insertions. The newly upgraded ChinaMu dataset currently contains 215,889 high-quality germinal insertions. These insertions cover 32,224 pan-genes in the Mu-starter and B73Ref5 genomes, including 23,006 (80.4%) core genes shared by the two genomes. As a test model, we investigated Mu insertions in the pentatricopeptide repeat (PPR) superfamily, discovering insertions for 92% (449/487) of PPR genes in ChinaMu, demonstrating the usefulness of ChinaMu as a functional genomics resource for maize.

NIa-Pro of sugarcane mosaic virus targets Corn Cysteine Protease 1 (CCP1) to undermine salicylic acid-mediated defense in maize.

Papain-like cysteine proteases (PLCPs) play pivotal roles in plant defense against pathogen invasions. While pathogens can secrete effectors to target and inhibit PLCP activities, the roles of PLCPs in plant-virus interactions and the mechanisms through which viruses neutralize PLCP activities remain largely uncharted. Here, we demonstrate that the expression and activity of a maize PLCP CCP1 (Corn Cysteine Protease), is upregulated following sugarcane mosaic virus (SCMV) infection. Transient silencing of CCP1 led to a reduction in PLCP activities, thereby promoting SCMV infection in maize. Furthermore, the knockdown of CCP1 resulted in diminished salicylic acid (SA) levels and suppressed expression of SA-responsive pathogenesis-related genes. This suggests that CCP1 plays a role in modulating the SA signaling pathway. Interestingly, NIa-Pro, the primary protease of SCMV, was found to interact with CCP1, subsequently inhibiting its protease activity. A specific motif within NIa-Pro termed the inhibitor motif was identified as essential for its interaction with CCP1 and the suppression of its activity. We have also discovered that the key amino acids responsible for the interaction between NIa-Pro and CCP1 are crucial for the virulence of SCMV. In conclusion, our findings offer compelling evidence that SCMV undermines maize defense mechanisms through the interaction of NIa-Pro with CCP1. Together, these findings shed a new light on the mechanism(s) controlling the arms races between virus and plant.

NIR-II Ratiometric Fluorescence Probes Enable Precise Determination of the Metastatic Status of Sentinel Lymph Nodes.

Accurately determining the metastatic status of sentinel lymph nodes (SLNs) through noninvasive imaging with high imaging resolution and sensitivity is crucial for cancer therapy. Herein, we report a dual-tracer-based NIR-II ratiometric fluorescence nanoplatform combining targeted and nontargeted moieties to determine the metastatic status of SLNs through the recording of ratio signals. Ratiometric fluorescence imaging revealed approximately 2-fold increases in signals in tumor-draining SLNs compared to inflamed and normal SLNs. Additionally, inflamed SLNs were diagnosed by combining the ratio value with the enlarged size outputted by NIR-II fluorescence imaging. The metastatic status diagnostic results obtained through NIR-II ratiometric fluorescence signals were further confirmed by standard H&E staining, indicating that the ratiometric fluorescence strategy could achieve distant metastases detection. Furthermore, the superior imaging quality of ratiometric probes enables visualization of the detailed change in the lymphatic network accompanying tumor growth. Compared to clinically available and state-of-the-art NIR contrast agents, our dual-tracer-based NIR-II ratiometric fluorescence probes provide significantly improved performance, allowing for the quick assessment of lymphatic function and guiding the removal of tumor-infiltrating SLNs during cancer surgery.

Multiparametric MRI model to predict molecular subtypes of breast cancer using Shapley additive explanations interpretability analysis.

PURPOSE: The purpose of this study was to assess the predictive performance of multiparametric magnetic resonance imaging (MRI) for molecular subtypes and interpret features using SHapley Additive exPlanations (SHAP) analysis. MATERIAL AND METHODS: Patients with breast cancer who underwent pre-treatment MRI (including ultrafast dynamic contrast-enhanced MRI, magnetic resonance spectroscopy, diffusion kurtosis imaging and intravoxel incoherent motion) were recruited between February 2019 and January 2022. Thirteen semantic and thirteen multiparametric features were collected and the key features were selected to develop machine-learning models for predicting molecular subtypes of breast cancers (luminal A, luminal B, triple-negative and HER2-enriched) by using stepwise logistic regression. Semantic model and multiparametric model were built and compared based on five machine-learning classifiers. Model decision-making was interpreted using SHAP analysis. RESULTS: A total of 188 women (mean age, 53 ± 11 [standard deviation] years; age range: 25-75 years) were enrolled and further divided into training cohort (131 women) and validation cohort (57 women). XGBoost demonstrated good predictive performance among five machine-learning classifiers. Within the validation cohort, the areas under the receiver operating characteristic curves (AUCs) for the semantic models ranged from 0.693 (95% confidence interval [CI]: 0.478-0.839) for HER2-enriched subtype to 0.764 (95% CI: 0.681-0.908) for luminal A subtype, inferior to multiparametric models that yielded AUCs ranging from 0.771 (95% CI: 0.630-0.888) for HER2-enriched subtype to 0.857 (95% CI: 0.717-0.957) for triple-negative subtype. The AUCs between the semantic and the multiparametric models did not show significant differences (P range: 0.217-0.640). SHAP analysis revealed that lower iAUC, higher kurtosis, lower D*, and lower kurtosis were distinctive features for luminal A, luminal B, triple-negative breast cancer, and HER2-enriched subtypes, respectively. CONCLUSION: Multiparametric MRI is superior to semantic models to effectively predict the molecular subtypes of breast cancer.

Pan-Omics in Sheep: Unveiling Genetic Landscapes.

Multi-omics-integrated analysis, known as panomics, represents an advanced methodology that harnesses various high-throughput technologies encompassing genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Sheep, playing a pivotal role in agricultural sectors due to their substantial economic importance, have witnessed remarkable advancements in genetic breeding through the amalgamation of multiomics analyses, particularly with the evolution of high-throughput technologies. This integrative approach has established a robust theoretical foundation, enabling a deeper understanding of sheep genetics and fostering improvements in breeding strategies. The comprehensive insights obtained through this approach shed light on diverse facets of sheep development, including growth, reproduction, disease resistance, and the quality of livestock products. This review primarily focuses on the application of principal omics analysis technologies in sheep, emphasizing correlation studies between multiomics data and specific traits such as meat quality, wool characteristics, and reproductive features. Additionally, this paper anticipates forthcoming trends and potential developments in this field.

Aggregation-induced signal amplification strategy based on peptide self-assembly for ultrasensitive electrochemical detection of melanoma biomarker.

The detection of melanoma circulating biomarker in liquid biopsies is current under evaluation for being potentially utilized for earlier cancer diagnosis and its metastasis. Herein, we developed a non-invasive electrochemical approach for ultrasensitive detection of the S100B, serving as a potential promising blood circulating biomarker of melanoma, based on an aggregation-induced signal amplification (AISA) strategy via in-situ peptide self-assembly. The fundamental principle of this assay is that the designed amphiphilic peptides (C16-Pep-Fc), fulfilling multiple functions, feature both a recognition region for specific binding to S100B and an aggregation (self-assembly) region for the formation of peptide nanomicelles under mild conditions. The C16 tails were encapsulated within the hydrophobic core of the aggregates, while the relatively hydrophilic recognition fragment Pep and Fc tag were exposed on the outer surface for subsequent recognition of S100B and signal output. AISA provided remarkable accumulation of electroactive Fc moieties that enabled ultrasensitive S100B detection of as low as 0.02 nM, which was 10-fold lower than un-amplified approach and better than previously reported assays. As a proof-of-concept study, further experiments also highlighted the good reproducibility and stability of AISA and demonstrated its usability when applied to simulated serum samples. Hence, this work not only presented a valuable assay tool for ultrasensitive detecting protein biomarker, but also advocated for the utilization of aggregation-induced signal amplification in electrochemical biosensing system, given its considerable potential for future practical applications.

Intensive vision-guided network for radiology report generation.

Objective.Automatic radiology report generation is booming due to its huge application potential for the healthcare industry. However, existing computer vision and natural language processing approaches to tackle this problem are limited in two aspects. First, when extracting image features, most of them neglect multi-view reasoning in vision and model single-view structure of medical images, such as space-view or channel-view. However, clinicians rely on multi-view imaging information for comprehensive judgment in daily clinical diagnosis. Second, when generating reports, they overlook context reasoning with multi-modal information and focus on pure textual optimization utilizing retrieval-based methods. We aim to address these two issues by proposing a model that better simulates clinicians perspectives and generates more accurate reports.Approach.Given the above limitation in feature extraction, we propose a globally-intensive attention (GIA) module in the medical image encoder to simulate and integrate multi-view vision perception. GIA aims to learn three types of vision perception: depth view, space view, and pixel view. On the other hand, to address the above problem in report generation, we explore how to involve multi-modal signals to generate precisely matched reports, i.e. how to integrate previously predicted words with region-aware visual content in next word prediction. Specifically, we design a visual knowledge-guided decoder (VKGD), which can adaptively consider how much the model needs to rely on visual information and previously predicted text to assist next word prediction. Hence, our final intensive vision-guided network framework includes a GIA-guided visual encoder and the VKGD.Main results.Experiments on two commonly-used datasets IU X-RAY and MIMIC-CXR demonstrate the superior ability of our method compared with other state-of-the-art approaches.Significance.Our model explores the potential of simulating clinicians perspectives and automatically generates more accurate reports, which promotes the exploration of medical automation and intelligence.

High-precision detection and navigation surgery of colorectal cancer micrometastases.

Surgical resection is an effective treatment for colorectal cancer (CRC) patients, whereas occult metastases hinder the curative effect. Currently, there is no effective method to achieve intraoperatively diagnosis of tumor-positive lymph nodes (LNs). Herein, we adopt a near-infrared-II (NIR-II) organic donor-pi-acceptor-pi-donor probe FE-2PEG, which exhibits bright fluorescence over 1100 nm, excellent photostability, blood circulation time, and biocompatibility, to achieve high-performance bioimaging with improved temporal and spatial resolution. Importantly, the FE-2PEG shows efficient passive enrichment in orthotopic CRC, metastatic mesenteric LNs, and peritoneal metastases by enhanced permeability and retention effect. Under NIR-II fluorescence-guided surgery (FGS), the peritoneal micrometastases were resected with a sensitivity of 94.51%, specificity of 86.59%, positive predictive value (PPV) of 96.57%, and negative predictive value of 79.78%. The PPV still achieves 96.07% even for micrometastases less than 3 mm. Pathological staining and NIR-II microscopy imaging proved that FE-2PEG could successfully delineate the boundary between the tumor and normal tissues. Dual-color NIR-II imaging strategy with FE-2PEG (1100 ~ 1300 nm) and PbS@CdS quantum dots (> 1500 nm) successfully protects both blood supply and normal tissues during surgery. The NIR-II-based FGS provides a promising prospect for precise intraoperative diagnosis and minimally invasive surgery of CRC.

A new method for examining the co-occurrence network of fossil assemblages.

Currently, studies of ancient faunal community networks have been based mostly on uniformitarian and functional morphological evidence. As an important source of data, taphonomic evidence offers the opportunity to provide a broader scope for understanding palaeoecology. However, palaeoecological research methods based on taphonomic evidence are relatively rare, especially for body fossils in lacustrine sediments. Such fossil communities are not only affected by complex transportation and selective destruction in the sedimentation process, they also are strongly affected by time averaging. Historically, it has been believed that it is difficult to study lacustrine entombed fauna by a small-scale quadrat survey. Herein, we developed a software, the TaphonomeAnalyst, to study the associational network of lacustrine entombed fauna, or taphocoenosis. TaphonomeAnalyst allows researchers to easily perform exploratory analyses on common abundance profiles from taphocoenosis data. The dataset for these investigations resulted from fieldwork of the latest Middle Jurassic Jiulongshan Formation near Daohugou Village, in Ningcheng County of Inner Mongolia, China, spotlighting the core assemblage of the Yanliao Fauna. Our data included 27,000 fossil specimens of animals from this deposit, the Yanliao Fauna, whose analyses reveal sedimentary environments, taphonomic conditions, and co-occurrence networks of this highly studied assemblage, providing empirically robust and statistically significant evidence for multiple Yanliao habitats.

Dye-Triplet-Sensitized Downshifting Nanoprobes with Ratiometric Dual-NIR-IIb Emission for Accurate In Vivo Detection.

Despite the emerging near-infrared-IIb (NIR-IIb, 1500-1700 nm) bioimaging significantly improving the in vivo penetration depth and resolution, quantitative detection with accuracy remains challenging due to its inhomogeneous fluorescence signal attenuation in biological tissue. Here, ratiometric dual-NIR-IIb in vivo detection with excitation wavelengths of 808 and 980 nm is presented using analyte-responsive dye-triplet-sensitized downshifting nanoprobes (DSNPs). NIR cyanine dye IR-808, a recognizer of biomarker hypochlorite (ClO-), is introduced to trigger a triplet energy transfer process from the dye to Er3+ ions of DSNPs under 808 nm excitation, facilitating the formation of an analyte-responsive 1525 nm NIR-IIb assay channel. Meanwhile, DSNPs also enable emitting intrinsic nonanalyte-dependent downshifting fluorescence at the same NIR-IIb window under 980 nm excitation, serving as a self-calibrated signal to alleviate the interference from the probe amount and depth. Due to the two detected emissions sharing identical light propagation and scattering, the ratiometric NIR-IIb signal is demonstrated to ignore the depth of penetration in biotissue. The arthritis lesions are distinguished from normal tissue using ratiometric probes, and the amount of ClO- can be accurately output by the established detection curves.