STAB2: an updated spatio-temporal cell atlas of the human and mouse brain.

The brain is constituted of heterogeneous types of neuronal and non-neuronal cells, which are organized into distinct anatomical regions, and show precise regulation of gene expression during development, aging and function. In the current database release, STAB2 provides a systematic cellular map of the human and mouse brain by integrating recently published large-scale single-cell and single-nucleus RNA-sequencing datasets from diverse regions and across lifespan. We applied a hierarchical strategy of unsupervised clustering on the integrated single-cell transcriptomic datasets to precisely annotate the cell types and subtypes in the human and mouse brain. Currently, STAB2 includes 71 and 61 different cell subtypes defined in the human and mouse brain, respectively. It covers 63 subregions and 15 developmental stages of human brain, and 38 subregions and 30 developmental stages of mouse brain, generating a comprehensive atlas for exploring spatiotemporal transcriptomic dynamics in the mammalian brain. We also augmented web interfaces for querying and visualizing the gene expression in specific cell types. STAB2 is freely available at https://mai.fudan.edu.cn/stab2.

E-value: a superior alternative to P-value and its adjustments in DNA methylation studies.

DNA methylation plays a crucial role in transcriptional regulation. Reduced representation bisulfite sequencing (RRBS) is a technique of increasing use for analyzing genome-wide methylation profiles. Many computational tools such as Metilene, MethylKit, BiSeq and DMRfinder have been developed to use RRBS data for the detection of the differentially methylated regions (DMRs) potentially involved in epigenetic regulations of gene expression. For DMR detection tools, as for countless other medical applications, P-values and their adjustments are among the most standard reporting statistics used to assess the statistical significance of biological findings. However, P-values are coming under increasing criticism relating to their questionable accuracy and relatively high levels of false positive or negative indications. Here, we propose a method to calculate E-values, as likelihood ratios falling into the null hypothesis over the entire parameter space, for DMR detection in RRBS data. We also provide the R package 'metevalue' as a user-friendly interface to implement E-value calculations into various DMR detection tools. To evaluate the performance of E-values, we generated various RRBS benchmarking datasets using our simulator 'RRBSsim' with eight samples in each experimental group. Our comprehensive benchmarking analyses showed that using E-values not only significantly improved accuracy, area under ROC curve and power, over that of P-values or adjusted P-values, but also reduced false discovery rates and type I errors. In applications using real RRBS data of CRL rats and a clinical trial on low-salt diet, the use of E-values detected biologically more relevant DMRs and also improved the negative association between DNA methylation and gene expression.

Opportunities and challenges for ChatGPT and large language models in biomedicine and health.

ChatGPT has drawn considerable attention from both the general public and domain experts with its remarkable text generation capabilities. This has subsequently led to the emergence of diverse applications in the field of biomedicine and health. In this work, we examine the diverse applications of large language models (LLMs), such as ChatGPT, in biomedicine and health. Specifically, we explore the areas of biomedical information retrieval, question answering, medical text summarization, information extraction and medical education and investigate whether LLMs possess the transformative power to revolutionize these tasks or whether the distinct complexities of biomedical domain presents unique challenges. Following an extensive literature survey, we find that significant advances have been made in the field of text generation tasks, surpassing the previous state-of-the-art methods. For other applications, the advances have been modest. Overall, LLMs have not yet revolutionized biomedicine, but recent rapid progress indicates that such methods hold great potential to provide valuable means for accelerating discovery and improving health. We also find that the use of LLMs, like ChatGPT, in the fields of biomedicine and health entails various risks and challenges, including fabricated information in its generated responses, as well as legal and privacy concerns associated with sensitive patient data. We believe this survey can provide a comprehensive and timely overview to biomedical researchers and healthcare practitioners on the opportunities and challenges associated with using ChatGPT and other LLMs for transforming biomedicine and health.

GeneGPT: augmenting large language models with domain tools for improved access to biomedical information.

MOTIVATION: While large language models (LLMs) have been successfully applied to various tasks, they still face challenges with hallucinations. Augmenting LLMs with domain-specific tools such as database utilities can facilitate easier and more precise access to specialized knowledge. In this article, we present GeneGPT, a novel method for teaching LLMs to use the Web APIs of the National Center for Biotechnology Information (NCBI) for answering genomics questions. Specifically, we prompt Codex to solve the GeneTuring tests with NCBI Web APIs by in-context learning and an augmented decoding algorithm that can detect and execute API calls. RESULTS: Experimental results show that GeneGPT achieves state-of-the-art performance on eight tasks in the GeneTuring benchmark with an average score of 0.83, largely surpassing retrieval-augmented LLMs such as the new Bing (0.44), biomedical LLMs such as BioMedLM (0.08) and BioGPT (0.04), as well as GPT-3 (0.16) and ChatGPT (0.12). Our further analyses suggest that: First, API demonstrations have good cross-task generalizability and are more useful than documentations for in-context learning; second, GeneGPT can generalize to longer chains of API calls and answer multi-hop questions in GeneHop, a novel dataset introduced in this work; finally, different types of errors are enriched in different tasks, providing valuable insights for future improvements. AVAILABILITY AND IMPLEMENTATION: The GeneGPT code and data are publicly available at https://github.com/ncbi/GeneGPT.

Human umbilical cord mesenchymal stem cell-derived exosomes ameliorate renal fibrosis in diabetic nephropathy by targeting Hedgehog/SMO signaling.

Diabetic nephropathy (DN) is the leading cause of end-stage renal disease globally. Currently, there are no effective drugs for the treatment of DN. Although several studies have reported the therapeutic potential of mesenchymal stem cells, the underlying mechanisms remain largely unknown. Here, we report that both human umbilical cord MSCs (UC-MSCs) and UC-MSC-derived exosomes (UC-MSC-exo) attenuate kidney damage, and inhibit epithelial-mesenchymal transition (EMT) and renal fibrosis in streptozotocin-induced DN rats. Strikingly, the Hedgehog receptor, smoothened (SMO), was significantly upregulated in the kidney tissues of DN patients and rats, and positively correlated with EMT and renal fibrosis. UC-MSC and UC-MSC-exo treatment resulted in decrease of SMO expression. In vitro co-culture experiments revealed that UC-MSC-exo reduced EMT of tubular epithelial cells through inhibiting Hedgehog/SMO pathway. Collectively, UC-MSCs inhibit EMT and renal fibrosis by delivering exosomes and targeting Hedgehog/SMO signaling, suggesting that UC-MSCs and their exosomes are novel anti-fibrotic therapeutics for treating DN.

Increasingly amplified stimulation mediated by TaNAC69-B is crucial for the leaf senescence in wheat.

Leaf senescence involves massive multidimensional alterations, such as nutrient redistribution, and is closely related to crop yield and quality. No apical meristem, Arabidopsis transcription activation factor, and Cup-shaped cotyledon (NAC)-type transcription factors integrate various signals and modulate an enormous number of target genes to ensure the appropriate progression of leaf senescence. However, few leaf senescence-related NACs have been functionally characterized in wheat. Based on our previous RNA-sequencing (RNA-seq) data, we focused on a NAC family member, TaNAC69-B, which is increasingly expressed during leaf senescence in wheat. Overexpression of TaNAC69-B led to precocious leaf senescence in wheat and Arabidopsis, and affected several agricultural traits in transgenic wheat. Moreover, impaired expression of TaNAC69-B by virus-induced gene silencing retarded the leaf senescence in wheat. By RNA-seq and quantitative real-time polymerase chain reaction analysis, we confirmed that some abscisic acid (ABA) biosynthesis genes, including AAO3 and its ortholog in wheat, TraesCS2B02G270600 (TaAO3-B), were elevated by the overexpression of TaNAC69-B. Consistently, we observed more severe ABA-induced leaf senescence in TaNAC69-B-OE wheat and Arabidopsis plants. Furthermore, we determined that TaNAC69-B bound to the NAC binding site core (CGT) on the promoter regions of AAO3 and TaAO3-B. Moreover, we confirmed elevated ABA levels in TaNAC69-B-OE wheat lines. Although TaNAC69-B shares 39.83% identity (amino acid) with AtNAP, TaNAC69-B did not completely restore the delayed leaf senescence in the atnap mutant. Collectively, our results revealed a positive feedback loop, consisting of TaNAC69-B, ABA biosynthesis and leaf senescence, that is essential for the regulation of leaf senescence in wheat.

Decreased spermatogonial numbers in boys with severe haematological diseases.

This study examines spermatogonial numbers in testicular samples from 43 prepubertal patients undergoing haematopoietic stem cell transplantation (HSCT). High-dose chemotherapy and/or radiation during HSCT can impact spermatogenesis requiring fertility preservation. Results show that 49% of patients have decreased and 19% severely depleted spermatogonial pool prior to HSCT. Patients with Fanconi anaemia exhibit significantly reduced spermatogonial numbers. Patients with immunodeficiency or aplastic anaemia generally present within the normal range, while results in patients with myelodysplastic syndrome or myeloproliferative neoplasm vary. The study emphasizes the importance of assessing spermatogonial numbers in patients with severe haematological diseases for informed fertility preservation decisions.

Plasmonic Gold Nanostar-Based Probes with Distance-Dependent Plasmon-Enhanced Fluorescence for Ultrasensitive DNA Methyltransferase Assay.

The ultrasensitive DNA methyltransferase (Dam MTase) assay is of high significance for biomedical research and clinical diagnosis because of its profound effect on gene regulation. However, detection sensitivity is still limited by shortcomings, including photobleaching and weak signal intensities of conventional fluorophores at low concentrations. Plasmonic nanostructures with ultrastrong electromagnetic fields and fluorescence enhancement capability that can overcome these intrinsic defects hold great potential for ultrasensitive bioanalysis. Herein, a silica-coated gold nanostars (Au NSTs@SiO2)-based plasmon-enhanced fluorescence (PEF) probe with 20 "hot spots" was developed for ultrasensitive detection of Dam MTase. Here, the Dam Mtase assay was achieved by detecting the byproduct PPi of the rolling circle amplification reaction. It is worth noting that, benefiting from the excellent fluorescence enhancement capability of Au NSTs originating from their 20 "hot spots", the detection limit of Dam Mtase was reduced by nearly 105 times. Moreover, the proposed Au NST-based PEF probe enabled versatile evaluation of Dam MTase inhibitors as well as endogenous Dam MTase detection in GW5100 and JM110 Escherichia coli cell lysates, demonstrating its potential in biomedical analysis.

Electrodeposited Poly(5-Amino-2-Naphthalenesulfonic Acid-co-o-Aminophenol) as the Electrode Material for Flexible Supercapacitor.

Copolymers of 5-amino-2-naphthalenesulfonic acid (ANS) and o-aminophenol (oAP) are electropolymerized on carbon cloth substrate from aqueous solutions, and the electropolymerization process is investigated using electrochemical quartz-crystal microbalance. The surface of the copolymer (PANS-co-oAP) appears rough and is capable to store charge as the battery-type electrode in 1 m H2 SO4 (102.9 mAh g-1 at 1 A g-1 ) or in 1 m ZnSO4 (79.75 mAh g-1 at 1 A g-1 ) aqueous solutions. Compared with PANS and PoAP, the high specific capacity of the PANS-co-oAP is originated from the increased number of electrochemically active sites and increased diffusion rates of ions. Evidence of amino/imino and hydroxyl/carbonyl groups redox processes and cation insertion and extraction are given by ex situ X-ray photoelectron spectroscopy. When used as the electrode material in the flexible solid-state supercapacitors, the specific capacitance is at 37.9 F g-1 which does not significantly alter with the bending angle. The flexible solid-state supercapacitor shows a specific energy of 5.4 Wh kg-1 and a power density of 250.3 W kg-1 at 0.5 A g-1 , and a high capacitance retention (88.2%) after 3000 cycles at 5 A g-1 is achieved.

γδ T cells and the PD-1/PD-L1 axis: a love-hate relationship in the tumor microenvironment.

Gamma delta (γδ) T cells demonstrate strong cytotoxicity against diverse cancer cell types in an MHC-independent manner, rendering them promising contenders for cancer therapy. Although amplification and adoptive transfer of γδ T cells are being evaluated in the clinic, their therapeutic efficacy remains unsatisfactory, primarily due to the influence of the immunosuppressive tumor microenvironment (TME). Currently, the utilization of targeted therapeutic antibodies against inhibitory immune checkpoint (ICP) molecules is a viable approach to counteract the immunosuppressive consequences of the TME. Notably, PD-1/PD-L1 checkpoint inhibitors are considered primary treatment options for diverse malignancies, with the objective of preserving the response of αß T cells. However, γδ T cells also infiltrate various human cancers and are important participants in cancer immunity, thereby influencing patient prognosis. Hence, it is imperative to comprehend the reciprocal impact of the PD-1/PD-L1 axis on γδ T cells. This understanding can serve as a therapeutic foundation for improving γδ T cells adoptive transfer therapy and may offer a novel avenue for future combined immunotherapeutic approaches.

Serum matrix metalloproteinase-7 for discriminating biliary atresia: a diagnostic accuracy and validation study.

BACKGROUND: Prompt and precise differential diagnosis of biliary atresia (BA) among cholestatic patients is of great importance. Matrix metalloproteinase-7 (MMP-7) holds great promise as a diagnostic marker for BA. This study aimed to investigate the accuracy of age-specific serum MMP-7 for discriminating BA from other cholestatic pediatric patients. METHODS: This was a single center diagnostic accuracy and validation study including both retrospective and prospective cohorts. Serum MMP-7 concentrations were measured using an ELISA kit, the trajectory of which with age was investigated in a healthy infants cohort aged 0 to 365 days without hepatobiliary diseases (n = 284). Clinical BA diagnosis was based on intraoperative cholangiography and subsequent histological examinations. The diagnostic accuracy of age-specific cutoffs of serum MMP-7 were assessed in a retrospective cohort of cholestatic patients (n = 318, with 172 BA) and validated in a prospective cohort (n = 687, including 395 BA). RESULTS: The MMP-7 concentration declines non-linearly with age, showing higher levels in healthy neonates as well as higher cutoff value in neonatal cholestasis. The area under the ROC curve (AUROC) was 0.967 (95% confidence interval [CI]: 0.946-0.988) for the retrospective cohort, and the cutoff of 18 ng/mL yielded 93.0% (95%CI: 88.1-96.3%), 93.8% (95%CI: 88.6-97.1%), 94.7% (95%CI: 90.1-97.5%), and 91.9% (95%CI: 86.4-95.8%) for sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), respectively. The performance of MMP-7 was successfully validated in the larger prospective cohort, resulting in a diagnostic sensitivity of 95.9% (379/395; 95% CI: 93.5-97.7%), a specificity of 87.3% (255/292; 95% CI: 83.0-90.9%), a PPV of 91.1% (379/416; 95% CI: 87.9-93.7%), and a NPV of 94.1% (255/271; 95% CI: 90.6-96.6%), respectively. Besides, higher cutoff value of 28.1 ng/mL achieved the best sensitivity, specificity, PPV, and NPV for infants aged 0-30 days, which was 86.4% (95% CI: 75.0-94.0%), 95.5% (95% CI: 77.2-99.9%), 98.1% (95% CI: 89.7-100%), and 72.4% (95% CI: 52.8-87.3%), respectively. CONCLUSIONS: The serum MMP-7 is accurate and reliable in differentiating BA from non-BA cholestasis, showing its potential application in the diagnostic algorithm for BA and significant role in the future research regarding pathogenesis of BA.

Impact of Hepatic Pedicle Clamping on Long-Term Survival Following Hepatectomy for Hepatocellular Carcinoma: Stratified Analysis Based on Intraoperative Blood Transfusion Status.

BACKGROUND: Hepatic pedicle clamping (HPC) is frequently utilized during hepatectomy to reduce intraoperative bleeding and diminish the need for intraoperative blood transfusion (IBT). The long-term prognostic implications of HPC following hepatectomy for hepatocellular carcinoma (HCC) remain under debate. This study aims to elucidate the association between HPC and oncologic outcomes after HCC resection, stratified by whether IBT was administered. PATIENTS AND METHODS: Prospectively collected data on patients with HCC who underwent curative resection from a multicenter database was studied. Patients were stratified into two cohorts on the basis of whether IBT was administered. The impact of HPC on long-term overall survival (OS) and recurrence-free survival (RFS) between the two cohorts was assessed by univariable and multivariable Cox regression analyses. RESULTS: Of 3362 patients, 535 received IBT. In the IBT cohort, using or not using HPC showed no significant difference in OS and RFS outcomes (5-year OS and RFS rates 27.9% vs. 24.6% and 13.8% vs. 12.0%, P = 0.810 and 0.530). However, in the non-IBT cohort of 2827 patients, the HPC subgroup demonstrated significantly decreased OS (5-year 45.9% vs. 56.5%, P < 0.001) and RFS (5-year 24.7% vs. 33.3%, P < 0.001) when compared with the subgroup without HPC. Multivariable Cox regression analysis identified HPC as an independent risk factor of OS and RFS [hazard ratios (HR) 1.16 and 1.12, P = 0.024 and 0.044, respectively] among patients who did not receive IBT. CONCLUSIONS: The impact of HPC on the oncological outcomes following hepatectomy for patients with HCC differed significantly whether IBT was administered, and HPC adversely impacted on long-term survival for patients without receiving IBT during hepatectomy.

Development of a Dual Fluorescence Signal-Enhancement Immunosensor Based on Substrate Modification for Simultaneous Detection of Interleukin-6 and Procalcitonin.

High-sensitivity detection of biomarkers is of great significance to improve the accuracy of disease diagnosis and the rate of occult disease diagnosis. Using a substrate modification and two-color quantum dot (QD) nanobeads (QBs), we have developed a dual fluorescence signal-enhancement immunosensor for sensitive, simultaneous detection of interleukin 6 (IL-6) and procalcitonin (PCT) at low volumes (∼20 µL). First, the QBs compatible with QDs with different surface ligands were prepared by optimizing surfactants based on the microemulsion method. Through the use of a fluorescence-linked immunosorbent assay (FLISA), the feasibility of a dual signal-enhancement immunosensor was verified, and a 5-fold enhancement of fluorescence intensity was achieved after the directional coating of the antibodies on sulfhydryl functionalization (-SH) substrates and the preparation of QBs by using a polymer and silica double-protection method. Next, a simple polydimethylsiloxane (HS-PDMS) immunosensor with a low volume consumption was prepared. Under optimal conditions, we achieved the simultaneous detection of IL-6 and PCT with a linear range of 0.05-50 ng/mL, and the limit of detection (LOD) was 24 and 32 pg/mL, respectively. The result is comparable to two-color QBs-FLISA with a sulfhydryl microplate, even though only 20% of its volume was used. Thus, the dual fluorescence signal-enhancement HS-PDMS immunosensor offers the capability of early microvolume diagnosis of diseases, while the detection of inflammatory factors is clinically important for assisting disease diagnosis and determining disease progression.

Ribosomal protein L17 functions as an antimicrobial protein in amphioxus.

Antimicrobial peptides (AMPs), characterized by their cationic nature and amphiphilic properties, play a pivotal role in inhibiting the biological activity of microbes. Currently, only a fraction of the antimicrobial potential within the ribosomal protein family has been explored, despite its extensive membership and resemblance to AMPs. Herein we demonstrated that amphioxus RPL17 (BjRPL17) exhibited not only upregulated expression upon bacterial stimulation but also possessed bactericidal capabilities against both Gram-negative and -positive bacteria through combined action mechanisms including interaction with cell surface molecules LPS, LTA, and PGN, disruption of cell membrane integrity, promotion of membrane depolarization, and induction of intracellular ROS production. Furthermore, a peptide derived from residues 127-141 of BjRPL17 (termed BjRPL17-1) showed antibacterial activity against Staphylococcus aureus and its methicillin-resistant strain via the same mechanism observed for the full-length protein. Additionally, the rpl17 gene was highly conserved in Metazoa, hinting it may play a universal role in the antibacterial defense system in different animals. Importantly, neither BjRPL17 nor peptide BjRPL17-1 exhibited toxicity towards mammalian cells thereby offering prospects for designing novel AMP agents based on these findings. Collectively, our results establish RPL17 as a novel member of AMPs with remarkable evolutionary conservation.

miR-126a-5p inhibits H1N1-induced inflammation and matrix protease secretion in lung fibroblasts by targeting ADAMTS-4.

Upregulation of ADAMTS-4 has been reported to have an important role in lung injury, and ADAMTS-4 expression is regulated by miR-126a-5p in abdominal aortic aneurysms. The aim of this study was to investigate whether miR-126a-5p/ADAMTS-4 plays a role in influenza-virus-induced lung injury. Lung fibroblasts were infected with H1N1 influenza virus to detect changes in miR-126a-5p and ADAMTS-4 expression, and cell viability was measured by CCK-8 assay. Inflammatory factors and matrix protease levels were examined using ELISA kits, and cell apoptosis was assessed by measuring the levels of apoptosis-related proteins. A dual luciferase assay was used to verify the regulatory relationship between miR-126a-5p and ADAMTS-4. H1N1 influenza virus reduced fibroblast viability, inhibited miR-126a-5p expression, and promoted ADAMTS-4 expression. Overexpression of miR-126a-5p attenuated the cellular inflammatory response, apoptosis, matrix protease secretion, and virus replication. Luciferase reporter assays revealed that miR-126a-5p inhibited ADAMTS-4 expression by targeting ADAMTS-4 mRNA. Further experiments showed that overexpression of ADAMTS-4 significantly reversed the inhibitory effects of miR-126a-5p on fibroblast inflammation, apoptosis, matrix protease secretion, and virus replication. Upregulation of miR-126a-5p inhibits H1N1-induced apoptosis, inflammatory factors, and matrix protease secretion, as well as virus replication in lung fibroblasts.

A survey of recent methods for addressing AI fairness and bias in biomedicine.

OBJECTIVES: Artificial intelligence (AI) systems have the potential to revolutionize clinical practices, including improving diagnostic accuracy and surgical decision-making, while also reducing costs and manpower. However, it is important to recognize that these systems may perpetuate social inequities or demonstrate biases, such as those based on race or gender. Such biases can occur before, during, or after the development of AI models, making it critical to understand and address potential biases to enable the accurate and reliable application of AI models in clinical settings. To mitigate bias concerns during model development, we surveyed recent publications on different debiasing methods in the fields of biomedical natural language processing (NLP) or computer vision (CV). Then we discussed the methods, such as data perturbation and adversarial learning, that have been applied in the biomedical domain to address bias. METHODS: We performed our literature search on PubMed, ACM digital library, and IEEE Xplore of relevant articles published between January 2018 and December 2023 using multiple combinations of keywords. We then filtered the result of 10,041 articles automatically with loose constraints, and manually inspected the abstracts of the remaining 890 articles to identify the 55 articles included in this review. Additional articles in the references are also included in this review. We discuss each method and compare its strengths and weaknesses. Finally, we review other potential methods from the general domain that could be applied to biomedicine to address bias and improve fairness. RESULTS: The bias of AIs in biomedicine can originate from multiple sources such as insufficient data, sampling bias and the use of health-irrelevant features or race-adjusted algorithms. Existing debiasing methods that focus on algorithms can be categorized into distributional or algorithmic. Distributional methods include data augmentation, data perturbation, data reweighting methods, and federated learning. Algorithmic approaches include unsupervised representation learning, adversarial learning, disentangled representation learning, loss-based methods and causality-based methods.

Prognostic Value of a Combined Nomogram Model Integrating 3-Dimensional Deep Learning and Radiomics for Head and Neck Cancer.

OBJECTIVE: The preoperative prediction of the overall survival (OS) status of patients with head and neck cancer (HNC) is significant value for their individualized treatment and prognosis. This study aims to evaluate the impact of adding 3D deep learning features to radiomics models for predicting 5-year OS status. METHODS: Two hundred twenty cases from The Cancer Imaging Archive public dataset were included in this study; 2212 radiomics features and 304 deep features were extracted from each case. The features were selected by univariate analysis and the least absolute shrinkage and selection operator, and then grouped into a radiomics model containing Positron Emission Tomography /Computed Tomography (PET/CT) radiomics features score, a deep model containing deep features score, and a combined model containing PET/CT radiomics features score +3D deep features score. TumorStage model was also constructed using initial patient tumor node metastasis stage to compare the performance of the combined model. A nomogram was constructed to analyze the influence of deep features on the performance of the model. The 10-fold cross-validation of the average area under the receiver operating characteristic curve and calibration curve were used to evaluate performance, and Shapley Additive exPlanations (SHAP) was developed for interpretation. RESULTS: The TumorStage model, radiomics model, deep model, and the combined model achieved areas under the receiver operating characteristic curve of 0.604, 0.851, 0.840, and 0.895 on the train set and 0.571, 0.849, 0.832, and 0.900 on the test set. The combined model showed better performance of predicting the 5-year OS status of HNC patients than the radiomics model and deep model. The combined model was shown to provide a favorable fit in calibration curves and be clinically useful in decision curve analysis. SHAP summary plot and SHAP The SHAP summary plot and SHAP force plot visually interpreted the influence of deep features and radiomics features on the model results. CONCLUSIONS: In predicting 5-year OS status in patients with HNC, 3D deep features could provide richer features for combined model, which showed outperformance compared with the radiomics model and deep model.

Efficacy of transauricular vagus nerve stimulation for the treatment of chemotherapy-induced painful peripheral neuropathy: a randomized controlled exploratory study.

BACKGROUND: Chemotherapy-induced painful peripheral neuropathy (CIPN) is a common adverse event in cancer patients, and there is still a lack of effective treatment. Transauricular vagal nerve stimulation (taVNS) is a minimally invasive treatment, but there are few reports regarding its efficacy for CIPN. OBJECTIVE: To investigate the efficacy and possible mechanism of taVNS in patients with CIPN. METHODS: Twenty-seven patients with CIPN were randomly divided into a taVNS group (n = 14) and a sham stimulation (SS) group (n = 13). A numerical rating scale (NRS) for pain, NCICTCAE 4.0 (neurotoxicity classification), quantitative sensory test (QST), Short-Form-Health Survey-12 (SF-12), and Athens Insomnia Scale (AIS) were administered before the intervention (D-10) and on the day after the intervention (D0), and the inflammatory cytokines in plasma were also measured. The NRS, NCI-CTCAE 4.0, SF-12, and AIS were administered again at D30 and D90. RESULTS: Compared with the SS group, the NRS and AIS in the taVNS group were significantly lower at D0. The impact lasted until D30. There were no statistically significant differences in the NRS and AIS between the 2 groups at D90. On D30, the mental component score of the SF-12 was significantly higher in the taVNS group than in the SS group. No adverse events were found. There was no significant difference in QST and plasma inflammatory cytokines between the 2 groups. CONCLUSION: taVNS can relieve chemotherapy-induced neuropathic pain in the short term, can improve sleep status and quality of life, and is expected to become a novel clinical treatment method for CIPN.

Utilizing rubidium chloride as an effective and stable interface modification layer for high-efficiency solar cells.

The presence of interface defects between the perovskite layer and the underlying substrate has a significant impact on the power conversion efficiency (PCE) and stability of perovskite solar cells (PSCs). S n O 2 thin films are employed in PSCs as electron transport layers to achieve high PCE. However, the significant lattice mismatch between S n O 2 and the perovskite material leads to a large number of uncoordinated defects at the interface between perovskite and substrate, resulting in recombination losses at the interface. In this study, rubidium chloride (RbCl) was introduced as the interface modification layer between the perovskite layer and the S n O 2 electron transport layer to enhance the PCE of PSCs. The research showed that the RbCl interface modification layer effectively passivated the under-coordinated defects of Sn ions and optimized the energy level alignment between the perovskite layer and the S n O 2 film. Moreover, the fabricated PSCs exhibited an open-circuit voltage of 1.11 V and a power conversion efficiency of 21.64%. Furthermore, the device maintained 80% of initial efficiency after storage for 30 days in an inert gas environment and 60% of the value after storage for 30 days in ambient air.

Single-neuron firing cascades underlie global spontaneous brain events.

The resting brain consumes enormous energy and shows highly organized spontaneous activity. To investigate how this activity is manifest among single neurons, we analyzed spiking discharges of ∼10,000 isolated cells recorded from multiple cortical and subcortical regions of the mouse brain during immobile rest. We found that firing of a significant proportion (∼70%) of neurons conformed to a ubiquitous, temporally sequenced cascade of spiking that was synchronized with global events and elapsed over timescales of 5 to 10 s. Across the brain, two intermixed populations of neurons supported orthogonal cascades. The relative phases of these cascades determined, at each moment, the response magnitude evoked by an external visual stimulus. Furthermore, the spiking of individual neurons embedded in these cascades was time locked to physiological indicators of arousal, including local field potential power, pupil diameter, and hippocampal ripples. These findings demonstrate that the large-scale coordination of low-frequency spontaneous activity, which is commonly observed in brain imaging and linked to arousal, sensory processing, and memory, is underpinned by sequential, large-scale temporal cascades of neuronal spiking across the brain.