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.

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.

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.

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.

Liposomal nanostructures for Gemcitabine and Paclitaxel delivery in pancreatic cancer.

Pancreatic cancer (PC) is an incurable disease with a high death rate in the world nowadays. Gemcitabine (GEM) and Paclitaxel (PTX) are considered as references of chemotherapeutic treatments and are commonly used in clinical applications. Factors related to the tumor microenvironment such as insufficient tumor penetration, toxicity, and drug resistance can limit the effectiveness of these therapeutic anticancer drugs. The use of different liposomal nanostructures is a way that can optimize the drug's effectiveness and reduce toxicity. Given the development of PC therapy, this review focuses on advances in Nano-formulation, characterization, and delivery systems of loaded GEM and PTX liposomes using chemotherapy, nucleic acid delivery, and stroma remodeling therapy. As a result, the review covers the literature dealing with the applications of liposomes in PC therapy.

Plant immunity suppression by an exo-ß-1,3-glucanase and an elongation factor 1α of the rice blast fungus.

Fungal cell walls undergo continual remodeling that generates ß-1,3-glucan fragments as products of endo-glycosyl hydrolases (GHs), which can be recognized as pathogen-associated molecular patterns (PAMPs) and trigger plant immune responses. How fungal pathogens suppress those responses is often poorly understood. Here, we study mechanisms underlying the suppression of ß-1,3-glucan-triggered plant immunity by the blast fungus Magnaporthe oryzae. We show that an exo-ß-1,3-glucanase of the GH17 family, named Ebg1, is important for fungal cell wall integrity and virulence of M. oryzae. Ebg1 can hydrolyze ß-1,3-glucan and laminarin into glucose, thus suppressing ß-1,3-glucan-triggered plant immunity. However, in addition, Ebg1 seems to act as a PAMP, independent of its hydrolase activity. This Ebg1-induced immunity appears to be dampened by the secretion of an elongation factor 1 alpha protein (EF1α), which interacts and co-localizes with Ebg1 in the apoplast. Future work is needed to understand the mechanisms behind Ebg1-induced immunity and its suppression by EF1α.

Folium crataegi boosts skin regeneration for burn injury in rats through multiple ways.

Appropriate topical dressings for burn treatments are important to accelerate skin wound recovery and prevent external infections. This study aimed to evaluate the effect and investigate the mechanism of folium crataegi (Crataegus pinnatifida Bge.) for the treatment of burn wounds, as well as to compare the therapeutic effects of aqueous extracts (HLW) and alcoholic extracts (HLE) from folium crataegi. The results demonstrated that both HLW and HLE groups exhibited a higher wound contraction rate than the silver sulfadiazine (SSD) ointment group. Moreover, HLW showed more significant wound repair effects than HLE. HLW significantly increased levels of EGF and FGF-2 in wound tissue, as well as TGF-ß1, VEGF, CAT and IL-10 in serum. Folium crataegi extract, especially aqueous extracts, exerted good anti-inflammatory, anti-oxidant and anti-bacterial effects by upregulating the expression of lag3, txn1 and slpi, respectively. Folium crataegi extract significantly inhibits the expression of npas2, a key gene in the circadian rhythm pathway. In conclusion, this research illustrated that the folium crataegi extract, especially aqueous extracts, had better therapeutic effects on skin burns through multiple ways, possibly including a novel mechanism related to circadian rhythm pathway. These findings suggest that folium crataegi could be a valuable source of compounds for enhancing skin regeneration through multiple ways.

An Ultrastable Bifunctional Electrocatalyst Derived from a Co2+-Anchored Covalent-Organic Framework for High-Efficiency ORR/OER and Rechargeable Zinc-Air Battery.

It remains a great challenge to develop alternative electrocatalysts with high stability for the oxygen reduction reaction (ORR) and oxygen evolution reaction (OER). Herein, a bifunctional electrocatalyst composed of hollow CoOx (Co3O4/CoO) nanoparticles embedded in lamellar carbon nanofibers is derived from a Co2+-anchored covalent-organic framework. The as-fabricated electrocatalyst (CoOx@NC-800) exhibits a half-wave potential (E1/2) of 0.89 V with ultrahigh long-term stability (100% current retention after 3000 CV cycles). Together with promising OER performance, the CoOx@NC-800 based reversible Zn-air battery displays a small potential gap (0.70 V), superior to that of the commercial 20% Pt/C + RuO2. The density functional theory (DFT) calculations reveal that the remarkable electrocatalytic performance and stability of CoOx@NC-800 are attributed to the optimized adsorption of the *OOH intermediate and reduced free energy of the potential-limiting step. This study establishes the functionalization of COF structure for fabrication of high-performance carbon-based electrocatalysts.

Biosynthesis and Pharmacological Activities of Flavonoids, Triterpene Saponins and Polysaccharides Derived from Astragalus membranaceus.

Astragalus membranaceus (A. membranaceus), a well-known traditional herbal medicine, has been widely used in ailments for more than 2000 years. The main bioactive compounds including flavonoids, triterpene saponins and polysaccharides obtained from A. membranaceus have shown a wide range of biological activities and pharmacological effects. These bioactive compounds have a significant role in protecting the liver, immunomodulation, anticancer, antidiabetic, antiviral, antiinflammatory, antioxidant and anti-cardiovascular activities. The flavonoids are initially synthesized through the phenylpropanoid pathway, followed by catalysis with corresponding enzymes, while the triterpenoid saponins, especially astragalosides, are synthesized through the universal upstream pathways of mevalonate (MVA) and methylerythritol phosphate (MEP), and the downstream pathway of triterpenoid skeleton formation and modification. Moreover, the Astragalus polysaccharide (APS) possesses multiple pharmacological activities. In this review, we comprehensively discussed the biosynthesis pathway of flavonoids and triterpenoid saponins, and the structural features of polysaccharides in A. membranaceus. We further systematically summarized the pharmacological effects of bioactive ingredients in A. membranaceus, which laid the foundation for the development of clinical candidate agents. Finally, we proposed potential strategies of heterologous biosynthesis to improve the industrialized production and sustainable supply of natural products with pharmacological activities from A. membranaceus, thereby providing an important guide for their future development trend.

Apiaceae Medicinal Plants in China: A Review of Traditional Uses, Phytochemistry, Bolting and Flowering (BF), and BF Control Methods.

Apiaceae plants have been widely used in traditional Chinese medicine (TCM) for the removing dampness, relieving superficies, and dispelling cold, etc. In order to exploit potential applications as well as improve the yield and quality of Apiaceae medicinal plants (AMPs), the traditional use, modern pharmacological use, phytochemistry, effect of bolting and flowering (BF), and approaches for controlling BF were summarized. Currently, about 228 AMPs have been recorded as TCMs, with 6 medicinal parts, 79 traditional uses, 62 modern pharmacological uses, and 5 main kinds of metabolites. Three different degrees (i.e., significantly affected, affected to some extent, and not significantly affected) could be classed based on the yield and quality. Although the BF of some plants (e.g., Angelica sinensis) could be effectively controlled by standard cultivation techniques, the mechanism of BF has not yet been systemically revealed. This review will provide useful references for the reasonable exploration and high-quality production of AMPs.

A Deep Learning Model for the Diagnosis and Discrimination of Gram-Positive and Gram-Negative Bacterial Pneumonia for Children Using Chest Radiography Images and Clinical Information.

Purpose: This study aimed to develop a deep learning model based on chest radiography (CXR) images and clinical data to accurately classify gram-positive and gram-negative bacterial pneumonia in children to guide the use of antibiotics. Methods: We retrospectively collected CXR images along with clinical information for gram-positive (n=447) and gram-negative (n=395) bacterial pneumonia in children from January 1, 2016, to June 30, 2021. Four types of machine learning models based on clinical data and six types of deep learning algorithm models based on image data were constructed, and multi-modal decision fusion was performed. Results: In the machine learning models, CatBoost, which only used clinical data, had the best performance; its area under the receiver operating characteristic curve (AUC) was significantly higher than that of the other models (P<0.05). The incorporation of clinical information improved the performance of deep learning models that relied solely on image-based classification. Consequently, AUC and F1 increased by 5.6% and 10.2% on average, respectively. The best quality was achieved with ResNet101 (model accuracy: 0.75, recall rate: 0.84, AUC: 0.803, F1: 0.782). Conclusion: Our study established a pediatric bacterial pneumonia model that utilizes CXR and clinical data to accurately classify cases of gram-negative and gram-positive bacterial pneumonia. The results confirmed that the addition of image data to the convolutional neural network model significantly improved its performance. While the CatBoost-based classifier had greater advantages owing to a smaller dataset, the quality of the Resnet101 model trained using multi-modal data was comparable to that of the CatBoost model, even with a limited number of samples.

Furan Donor for NIR-II Molecular Fluorophores with Enhanced Bioimaging Performance.

The second near-infrared (NIR-II, 1,000 to 1,700 nm) molecular fluorophores containing donor-acceptor-donor conjugated backbone have attracted substantial attention due to their outstanding advantages, such as stable emission and facilely tuned photophysical properties. However, it is still challenging for them to simultaneously achieve high brightness and red-shifted absorption and emission. Herein, furan is adopted as the D unit to construct NIR-II fluorophores, demonstrating red shift of absorption, enhanced absorption coefficient, and fluorescent quantum yield when compared with the generally used thiophene counterparts. The high brightness and desirable pharmacokinetics of the optimized fluorophore, IR-FFCHP, endows improved performance for angiography and tumor-targeting imaging. Furthermore, dual-NIR-II imaging of tumor and sentinel lymph nodes (LNs) has been achieved with IR-FFCHP and PbS/CdS quantum dots, enabling the in vivo imaging navigated LN surgery in tumor-bearing mice. This work demonstrates the potential of furan for constructing bright NIR-II fluorophores for biological imaging.