Prediction of testicular histology in azoospermia patients through deep learning-enabled two-dimensional grayscale ultrasound.

Testicular histology based on testicular biopsy is an important factor for determining appropriate testicular sperm extraction surgery and predicting sperm retrieval outcomes in patients with azoospermia. Therefore, we developed a deep learning (DL) model to establish the associations between testicular grayscale ultrasound images and testicular histology. We retrospectively included two-dimensional testicular grayscale ultrasound from patients with azoospermia (353 men with 4357 images between July 2017 and December 2021 in The First Affiliated Hospital of Sun Yat-sen University, Guangzhou, China) to develop a DL model. We obtained testicular histology during conventional testicular sperm extraction. Our DL model was trained based on ultrasound images or fusion data (ultrasound images fused with the corresponding testicular volume) to distinguish spermatozoa presence in pathology (SPP) and spermatozoa absence in pathology (SAP) and to classify maturation arrest (MA) and Sertoli cell-only syndrome (SCOS) in patients with SAP. Areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were used to analyze model performance. DL based on images achieved an AUC of 0.922 (95% confidence interval [CI]: 0.908-0.935), a sensitivity of 80.9%, a specificity of 84.6%, and an accuracy of 83.5% in predicting SPP (including normal spermatogenesis and hypospermatogenesis) and SAP (including MA and SCOS). In the identification of SCOS and MA, DL on fusion data yielded better diagnostic performance with an AUC of 0.979 (95% CI: 0.969-0.989), a sensitivity of 89.7%, a specificity of 97.1%, and an accuracy of 92.1%. Our study provides a noninvasive method to predict testicular histology for patients with azoospermia, which would avoid unnecessary testicular biopsy.

Prediction of allograft function in pre-transplant kidneys using sound touch elastography (STE): an ex vivo study.

BACKGROUND: The purpose of the study was to evaluate renal quality and predict posttransplant graft function using ex vivo sound touch elastography (STE). METHODS: In this prospective study, 106 donor kidneys underwent ex vivo STE examination and biopsy from March 2022 to August 2023. The mean stiffness of the superficial cortex (STEsc), deep cortex (STEdc), and medulla (STEme) was obtained and synthesized into one index (STE) through the factor analysis method. Additionally, 100 recipients were followed up for 6 months. A random forest algorithm was employed to explore significant predictive factors associated with the Remuzzi score and allograft function. The performance of parameters was evaluated by using the area under the receiver operating characteristic curve (AUC). RESULTS: STE had AUC values of 0.803 for diagnosing low Remuzzi and 0.943 for diagnosing high Remuzzi. Meanwhile, STE had an AUC of 0.723 for diagnosing moderate to severe ATI. Random forest algorithm identified STE and Remuzzi score as significant predictors for 6-month renal function. The AUC for STE in predicting postoperative allograft function was 0.717, which was comparable with that of the Remuzzi score (AUC = 0.756). Nevertheless, the specificity of STE was significantly higher than that of Remuzzi (0.913 vs 0.652, p < 0.001). Given these promising results, donor kidneys can be transplanted directly without the need for biopsy when STE ≤ 11.741. CONCLUSIONS: The assessment of kidney quality using ex vivo STE demonstrated significant predictive value for the Remuzzi score and allograft function, which could help avoid unnecessary biopsy. CRITICAL RELEVANCE STATEMENT: Pre-transplant kidney quality measured with ex vivo STE can be used to assess donor kidney quality and avoid unnecessary biopsy. KEY POINTS: STE has significant value for diagnosing low Remuzzi and high Remuzzi scores. STE achieved good performance in predicting posttransplant allograft function. Assessment of kidney quality using ex vivo STE could avoid unnecessary biopsies.

Investigating PPT2's role in ovarian cancer prognosis and immunotherapy outcomes.

Ovarian cancer (OC) remains the primary cause of mortality among gynecological malignancies, and the identification of reliable molecular biomarkers to prognosticate OC outcomes is yet to be achieved. The gene palmitoyl protein thioesterase 2 (PPT2), which has been sparsely studied in OC, was closely associated with metabolism. This study aimed to determine the association between PPT2 expression, prognosis, immune infiltration, and potential molecular mechanisms in OC. We obtained the RNA-seq and clinical data from The Cancer Genome Atlas (TCGA), The Genotype-Tissue Expression (GTEx) and Gene Expression Omnibus (GEO) databases, then Kaplan-Meier analysis, univariate Cox regression, multivariate Cox regression, nomogram, and calibration were conducted to assess and verify the role of PPT2. Gene set enrichment analysis (GSEA) was used to figure out the closely correlated pathways with PPT2. Overexpression experiment was performed to explore the function of PPT2. Our findings showed that PPT2 mRNA expression was apparent down-regulation in OC tissue compared to normal ovarian tissues in TCGA, GTEx datasets, and GEO datasets. This differential expression was also confirmed in our in-house datasets at both the mRNA and protein levels. Decreased PPT2 expression correlated with lower survival rates in TCGA, several GEO datasets, and our in-house datasets. Multivariate analysis revealed that PPT2 was an independent factor in predicting better outcomes for OC patients in TCGA and GEO. A negative correlation was revealed between immune infiltration and PPT2 expression through Single-sample GSEA (ssGSEA). Additionally, PPT2 was negatively correlated with an up-regulated immune score, stromal score, and estimate score, suggesting that patients with low PPT2 expression might benefit more from immunotherapy. Numerous chemical agents showed lower IC50 in patients with high PPT2 expression. In single-cell RNA sequencing (scRNA-seq) analysis of several OC datasets, we found PPT2 was mainly expressed in endothelial cells. Furthermore, we found that PPT2 inhibited OC cell proliferation in vitro. Our results demonstrated that PPT2 was considered a favorable prognostic biomarker for OC and may be vital in predicting response to immunotherapy and chemotherapy. Further research was needed to fully understand the relationship between PPT2 and immunotherapy efficacy in OC patients.

2-Ethylhexyl diphenyl phosphate aggravates colitis-induced neuroinflammation and behavioral abnormalities by inhibiting the PI3K-AKT-NF-κB and Wnt/GSK3ß signaling pathways.

2-Ethylhexyl diphenyl phosphate (EHDPHP), a widely used organophosphorus flame retardant (OPFR), is ubiquitous in daily life because of its extensive application in plastic production. EHDPHPs, which are only superficially applied and not chemically bonded to products, are released into the environment, posing potential health risks. With increasing environmental concentrations, EHDPHP is a growing threat, particularly to individuals with preexisting health conditions who are more susceptible to environmental pollutants. This study examined the effects of EHDPHP exposure in a colitis model, reflecting a rising chronic health issue, by assessing changes in neuroinflammation and neurobehavioral abnormalities. Healthy and dextran sulfate sodium (DSS)-induced colitis C57BL/6 J mice were treated with either 0.2 % Tween or EHDPHP solution (10 mg/kg body weight/day) for 28 days. The study revealed significant increases in the serum and expression levels of TNFα and IL-1ß, accompanied by depressive and anxiety-like behaviors. Coexposure to EHDPHP and DSS exacerbated these neurobehavioral impairments. RNA sequencing confirmed that EHDPHP triggered inflammation via the PI3K-Akt-NF-κB and Wnt/GSK3ß signaling pathways, as confirmed by Western blot analysis. These findings suggest that EHDPHP aggravates colitis-induced neuroinflammation and neurobehavioral abnormalities, highlighting the harmful impact of EHDPHP, particularly in individuals with preexisting inflammatory conditions.

Learning Motor Cues in Brain-Muscle Modulation.

Current studies for brain-muscle modulation often analyze selected properties in electrophysiological signals, leading to a partial understanding. This article proposes a cross-modal generative model that converts brain activities measured by electroencephalography (EEG) to corresponding muscular responses recorded by electromyography (EMG). Examining the generation process in the model highlights how the motor cue, representing implicit motor information hidden within brain activities, modulates the interaction between brain and muscle systems. The proposed model employs a two-stage generation process to bridge the semantic gap in cross-modal signals. Initially, the shared movement-related information between EEG and EMG signals is extracted using a contrastive learning framework. These shared representations act as conditional vectors in the subsequent EMG generation stage based on generative adversarial networks (GANs). Experiments on a self-collected multimodal electrophysiological signal data set show the algorithm's superiority over existing time series generative methods in cross-modal EMG generation. Further insights derived from the model's inference process underscore the brain's strategy for muscle control during movements. This research provides a data-driven approach for the neuroscience community, offering a comprehensive perspective of brain-muscular modulation.

Inhibition of HIF-2α expression in cardiomyocytes attenuates PCB126-induced cardiotoxicity associated with decreased apoptosis through the PI3K/Akt and p53 signaling pathways.

PCB126, a type of polychlorinated biphenyl (PCB), is a persistent pollutant found in both biotic and abiotic environments and poses significant public health risks due to its potential to cause cardiac damage with prolonged exposure. Hypoxia-inducible factor-2α (HIF-2α) is part of the hypoxia-inducible factor (HIF) transcription complex family. Previous studies have shown that knocking out or inhibiting HIF-2α expression can ameliorate pulmonary hypertension and right ventricular dysfunction. This study aimed to investigate whether cardiac-specific knockout of HIF-2α can alleviate the cardiotoxicity caused by PCB126. In this study, cardiac-specific knockout mice and wild-type mice were orally administered PCB126 or corn oil (50 µg/kg/week) for eight weeks. Our findings indicated that PCB126 induces cardiotoxicity and myocardial injury, as evidenced by elevated cardiac enzyme levels and increased cardiac collagen fibers. RNA sequencing revealed that PCB126-induced cardiotoxicity involves the PI3K/Akt and p53 signaling pathways, which was confirmed by western blot analysis. Notably, cardiac-specific knockout of HIF-2α mitigated the damage caused by PCB126, reducing the expression of cardiac enzymes, inflammatory cytokines, and myocardial collagen fibers. Under normal conditions, conditional knockout (CKO) of the HIF-2α gene in cardiomyocytes did not affect the morphology or function of the mouse heart. However, HIF-2α CKO in the heart reduced the cardiotoxic effects of PCB126 by decreasing apoptosis through the PI3K/Akt and p53 signaling pathways. In conclusion, inhibiting HIF-2α expression in cardiomyocytes attenuated PCB126-induced cardiotoxicity by modulating apoptosis through these signaling pathways.

The association between FLAIR vascular hyperintensities and outcomes in patients with border zone infarcts treated with medical therapy may vary with the infarct subtype.

RATIONALE AND OBJECTIVES: Fluid-attenuated inversion recovery vessel hyperintensities (FVHs) reflect the haemodynamic state and may aid in predicting the prognosis of border zone (BZ) infarct patients. This study was to explore the relationship between FVHs and functional outcomes for different BZ infarct subtypes following medical therapy administration. MATERIALS AND METHODS: Consecutive patients with ischemic stroke were retrospectively enrolled and classified into internal BZ (IBZ) infarct, cortical BZ (CBZ) infarct and mixed-type infarct patients. FVHs were quantified using the FVH-Alberta Stroke Program Early CT Score (ASPECTS) system, and the scores were used to divide the patients into low-FVH (0-3) and high-FVH (4-7) groups. The FVH location and the cerebrovascular stenotic degree were recorded. Logistic regression was performed to identify risk factors for poor outcomes (modified Rankin scale score ≥3). RESULTS: A total of 207 BZ infarct patients (IBZ, n = 130; CBZ, n = 52; mixed-type, n = 25) were included. The FVH score was positively correlated with cerebrovascular stenosis (r = 0.332, P < 0.001) in all patients. A high FVH score was associated with poor outcomes in all (OR 2.568, 95% CI (1.147 to 5.753), P = 0.022) and in CBZ infarct patients (OR 9.258, 95% CI 1.113 to 77.035), P = 0.040). FVH-diffusion-weighted imaging (DWI) mismatch was not significantly associated with outcomes in the entire patient group or in any subgroup. CONCLUSIONS: A high FVH score is associated with poor long-term outcomes in patients with CBZ infarcts but not in those with IBZ or mixed-type infarcts.

C23 ameliorates carbon tetrachloride-induced liver fibrosis in mice.

BACKGROUND: C23, an oligo-peptide derived from cold-inducible RNA-binding protein (CIRP), has been reported to inhibit tissue inflammation, apoptosis and fibrosis by binding to the CIRP receptor; however, there are few reports on its role in liver fibrosis and the underlying mechanism is unknown. AIM: To explore whether C23 plays a significant role in carbon tetrachloride (CCl4)-induced liver fibrosis. METHODS: CCl4 was injected for 6 weeks to induce liver fibrosis and C23 was used beginning in the second week. Masson and Sirius red staining were used to examine changes in fiber levels. Inflammatory factors in the liver were detected and changes in α-smooth muscle actin (α-SMA) and collagen I expression were detected via immunohistochemical staining to evaluate the activation of hematopoietic stellate cells (HSCs). Western blotting was used to detect the activation status of the transforming growth factor-beta (TGF-ß)/Smad3 axis after C23 treatment. RESULTS: CCl4 successfully induced liver fibrosis in mice, while tumor necrosis factor-alpha (TNF-α), IL (interleukin)-1ß, and IL-6 levels increased significantly and the IL-10 level decreased significantly. Interestingly, C23 inhibited this process. On the other hand, C23 significantly inhibited the activation of HSCs induced by CCl4, which inhibited the expression of α-SMA and the synthesis of collagen I. In terms of mechanism, C23 can block Smad3 phosphorylation significantly and inhibits TGF-ß/Smad3 pathway activation, thereby improving liver injury caused by CCl4. CONCLUSION: C23 may block TGF-ß/Smad3 axis activation, inhibit the expression of inflammatory factors, and inhibit the activation of HSCs induced by CCl4, alleviating liver fibrosis.

Acinetobacter corruptisaponis sp. nov., Isolated from a Spoiled Bath Lotion.

Strain DM2021935T representing a novel Acinetobacter species was isolated from a spoiled bath lotion in Guangdong, China. Based on 16S rRNA gene phylogenetic analysis, strain DM2021935T was closely related to 'Acinetobacter thutiue' VNH17T, Acinetobacter junii CIP 64.5 T, and Acinetobacter tibetensis Y-23 T. Cells of strain DM2021935T were Gram-stain-negative, non-spore-forming, strictly aerobic, catalase-positive, oxidase-negative, α-hemolytic, and non-motile. Strain DM2021935T exhibited growth in 1-3% (w/v) NaCl at temperatures ranging from 4 to 37 °C and tolerated pH levels from 6.0 to 8.0. The predominant fatty acids in strain DM2021935T are C12:0, C16:0, C18:1 ω9c, and summed feature 3. Polar lipid profiles included glycolipids, phospholipids, phosphatidylethanolamine, and phosphatidyl-N-methylethanolamine. The identified respiratory quinones were ubiquinone Q-8 and Q-9. The genomic size of DM2021935T comprised 4.15 Mb, consisting of one chromosome (3,827,633 bp) and two plasmids (241,357 and 83,010 bp). The G + C content was 41.8%. The average nucleotide identity, average amino acid identity, and digital DNA-DNA hybridization values between strain DM2021935T and phylogenetically related type strains were below the species delineation thresholds (72.2-95.4, 53.1-87.0, and 20.4-66.4%, respectively). AntiSMASH analysis identified four gene clusters: non-ribosomal peptide synthetase, non-alpha poly-amino group acids, YcaO cyclodehydratase, and aryl polyene biosynthesis. Based on genotypic data, strain DM2021935T represents a novel species within the genus Acinetobacter. The proposed name for the novel species is Acinetobacter corruptisaponis sp. nov. (type strain DM2021935T = KCTC 92772 T = GDMCC 1.3703 T).

Artificial Intelligence-Assisted Perfusion Density as Biomarker for Screening Diabetic Nephropathy.

Purpose: To identify a reliable biomarker for screening diabetic nephropathy (DN) using artificial intelligence (AI)-assisted ultra-widefield swept-source optical coherence tomography angiography (UWF SS-OCTA). Methods: This study analyzed data from 169 patients (287 eyes) with type 2 diabetes mellitus (T2DM), resulting in 15,211 individual data points. These data points included basic demographic information, clinical data, and retinal and choroidal data obtained through UWF SS-OCTA for each eye. Statistical analysis, 10-fold cross-validation, and the random forest approach were employed for data processing. Results: The degree of retinal microvascular damage in the diabetic retinopathy (DR) with the DN group was significantly greater than in the DR without DN group, as measured by SS-OCTA parameters. There were strong associations between perfusion density (PD) and DN diagnosis in both the T2DM population (r = -0.562 to -0.481, P < 0.001) and the DR population (r = -0.397 to -0.357, P < 0.001). The random forest model showed an average classification accuracy of 85.8442% for identifying DN patients based on perfusion density in the T2DM population and 82.5739% in the DR population. Conclusions: Quantitative analysis of microvasculature reveals a correlation between DR and DN. UWF PD may serve as a significant and noninvasive biomarker for evaluating DN in patients through deep learning. AI-assisted SS-OCTA could be a rapid and reliable tool for screening DN. Translational Relevance: We aim to study the pathological processes of DR and DN and determine the correspondence between their clinical and pathological manifestations to further clarify the potential of screening DN using AI-assisted UWF PD.

Seed Priming with Dynamically Transformed Selenium Nanoparticles to Enhance Salt Tolerance in Rice.

Seed priming with nanomaterials is an emerging approach for improving plant stress tolerance. Here, we demonstrated a mechanism for enhancing salt tolerance in rice under salt stress via priming with nonstimulatory nanoparticles such as selenium nanoparticles (SeNPs), distinct from stimulatory nanomaterials. Due to the dynamic transformation ability of SeNPs, SeNP priming could enhance rice salt tolerance by mediating the glutathione cycle to eliminate excess reactive oxygen species (ROS). During priming, SeNPs penetrated rice seeds and transitioned into a soluble form (99.9%) within the embryo endosperm. Subsequently, the soluble selenium (Se) was transported to rice roots and metabolized into various Se-related derivatives, including selenomethionine (SeMet), Na2SeO3 (Se IV), selenocysteine (SeCys2), and methylselenocysteine (MeSeCys). These derivatives significantly enhanced the root activities of key enzymes such as glutathione peroxidase (GSH-PX), glutathione reductase (GR), catalase (CAT), peroxidase (POD), and superoxide dismutase (SOD) by 24.97%, 47.98%, 16.23%, 16.81%, and 14.82%, respectively, thus reinforcing the glutathione cycle and ROS scavenging pathways. Moreover, these alterations induced transcriptional changes in rice seedlings, with genes involved in signal transduction, transcription factors (TFs), ROS scavenging, and protein folding being upregulated, activating signal perception and self-repair mechanisms. These findings offer valuable insights for the agricultural application of nanomaterials.

Field test and numerical research on explosion crater in calcareous sand.

The explosion in foundation poses a significant threat to people and buildings. Currently, a unified empirical prediction formula for crater in calcareous foundation has not been established. In this paper, analyzed the types and sizes of explosion crater with different scaled burial depths through field tests and numerical simulation. In field tests, revealed the influence of scaled burial depth on the type and size of explosion crater and obtained the critical scaled burial depth for three different types of explosion craters, namely ejecta-type crater, collapse-type crater and covert explosion. Through the Smooth Particle Hydrodynamic-Finite Element Method (SPH-FEM) coupling algorithm, studied the movement trajectory of sand particles around the explosive at the moment of explosion in detail. Based on the field tests and numerical simulation results, it was found that calcareous sand has a smaller specific gravity due to its own characteristics, and the size of the explosion crater is larger than that of quartz sand at the same scaled burial depth. Obtained an empirical formula for crater in calcareous sand. Which can quickly predict the size of explosion crater and provide calculation basis for explosion resistant design in calcareous sand foundations.

Surface Chemistry Regulation in Cu4I4-Triazolate Metal-Organic Frameworks for One-Step C3H6 Purification from Quaternary C3 Mixtures.

C3H6 is a crucial building block for many chemicals, yet separating it from other C3 hydrocarbons presents a significant challenge. Herein, we report a hydrolytically stable Cu4I4-triazolate metal-organic framework (MOF) (JNU-9-CH3) featuring 1D channels decorated with readily accessible iodine and nitrogen atoms from Cu4I4 clusters and triazolate linkers, respectively. The exposed iodine and nitrogen atoms allow for cooperative binding of C3 hydrocarbons, as evidenced by in situ single-crystal crystallography and Raman spectroscopy studies. As a result, JNU-9-CH3 exhibits substantially stronger binding affinity for C3H4, CH2═C═CH2, and C3H8 than that for C3H6. Breakthrough experiments confirm its ability to directly separate C3H6 (≥99.99%) from C3H4/CH2═C═CH2/C3H8/C3H6 mixtures at varying ratios and flow rates. Overall, we illustrate the cooperative binding of C3 hydrocarbons in a Cu4I4-triazolate MOF and its highly efficient C3H6 purification from quaternary C3 mixtures. The study highlights the potential of MOF adsorbents with metal-iodide clusters for cooperative bindings and hydrocarbon separations.

Photoinduced Nonadiabatic Dynamics of a Single-Walled Carbon Nanotube-Porphyrin Complex.

Single-walled carbon nanotubes (SWCNTs) have gained a lot of attention in the past few decades due to their promising optoelectronic properties. In addition, SWCNTs can form complexes that have good chemical stability and transport properties with other optical functional materials through noncovalent interactions. Elucidating the detailed mechanism of these complexes is of great significance for improving their optoelectronic properties. Nevertheless, simulating the photoinduced dynamics of these complexes accurately is rather challenging since they usually contain hundreds of atoms. To save computational efforts, most of the previous works have ignored the excitonic effects by employing nonadiabatic carrier (electron and hole) dynamics simulations. To properly consider the influence of excitonic effects on the photoinduced ultrafast processes of the SWCNT-tetraphenyl porphyrin (H2TPP) complex and to further improve the computational efficiency, we developed the nonadiabatic molecular dynamics (NAMD) method based on the extended tight binding-based simplified Tamm-Dancoff approximation (sTDA-xTB), which is applied to study the ultrafast photoinduced dynamics of the noncovalent SWCNT-porphyrin complex. In combination with statically electronic structure calculations, the present work successfully reveals the detailed microscopic mechanism of the ultrafast excitation energy transfer process of the complex. Upon local excitation on the H2TPP molecule, an ultrafast energy transfer process occurs from H2TPP (SWCNT-H2TPP*) to SWCNT (SWCNT*-H2TPP) within 10 fs. Then, two slower processes corresponding to the energy transfer from H2TPP to SWCNT and hole transfer from H2TPP to SWCNT take place in the 1 ps time scale. The sTDA-xTB-based electronic structure calculation and NAMD simulation results not only match the previous experimental observations from static and transient spectra but also provide more insights into the detailed information on the complex's photoinduced dynamics. Therefore, the sTDA-xTB-based NAMD method is a powerful theoretical tool for studying the ultrafast photoinduced dynamics in large extended systems with a large number of electronically excited states, which could be helpful for the subsequent design of SWCNT-based functional materials.

Dual immunostimulatory CD73 antibody-polymeric cytotoxic drug complex for triple negative breast cancer therapy.

Treatment of triple-negative breast cancer (TNBC) poses significant challenges due to its propensity for metastasis. A key impediment lies in the suppressive immune microenvironment, which fosters tumor progression. This study introduces an approach employing a dual immune-stimulatory CD73 antibody-polymeric cytotoxic drug complex (αCD73-PLG-MMAE). This complex is designed for targeted eradication of TNBC while modulating tumor immunity through mechanisms such as immunogenic cell death (ICD) and interference with the adenosine signaling pathway. By enhancing antitumor immune responses, this strategy offers a highly effective means of treating TNBC and mitigating metastasis. The complex is synthesized by combining αCD73 with poly(L-glutamic acid) (PLG) grafted Fc binding peptides (Fc-III-4C) and Val-Cit-PAB-monomethyl auristatin E (MMAE), exploiting the affinity between αCD73 and Fc-III-4C. αCD73 selectively targets CD73 molecules on both tumor and immune suppressive cells, thereby inhibiting the adenosine pathway. Meanwhile, Val-Cit-PAB-MMAE, activated by cathepsin B, triggers selective release of MMAE, inducing ICD in tumor cells. In a 4T1 tumor model, αCD73-PLG-MMAE significantly enhances drug accumulation in tumors by 4.13-fold compared to IgG-PLG-MMAE, leading to suppression of tumor growth and metastasis. Furthermore, it synergistically augments the antitumor effects of αPD-1, resulting in a tumor inhibition rate of 92 % as compared to 21 % with αPD-1 alone. This study thus presents a pioneering therapeutic strategy for TNBC, emphasizing the potential of targeted immunomodulation in cancer treatment. STATEMENT OF SIGNIFICANCE: Antibody-drug conjugate (ADC) therapy holds promise for treating triple-negative breast cancer (TNBC). However, the current ADC, sacituzumab govitecan, fails to overcome the crucial role of adenosine in the suppressive immune microenvironment characteristic of this "cold tumor". Here, we present a dual immune-stimulatory complex, αCD73-PLG-MMAE, which targets TNBC specifically and modulates tumor immunity through mechanisms such as immunogenic cell death (ICD) and interference with the adenosine signaling pathway. Thus, it kills tumor cells with cytotoxic drugs, comprehensively regulates immunosuppression, and restores a durable immune response. This study proposes an antibody-polymeric drug complex with immunomodulatory and immunoagonist roles, offering new insights into TNBC treatment.

Ultrasomics differentiation of malignant and benign focal liver lesions based on contrast-enhanced ultrasound.

OBJECTIVES: To establish a nomogram for differentiating malignant and benign focal liver lesions (FLLs) using ultrasomics features derived from contrast-enhanced ultrasound (CEUS). METHODS: 527 patients were retrospectively enrolled. On the training cohort, ultrasomics features were extracted from CEUS and b-mode ultrasound (BUS). Automatic feature selection and model development were performed using the Ultrasomics-Platform software, outputting the corresponding ultrasomics scores. A nomogram based on the ultrasomics scores from artery phase (AP), portal venous phase (PVP) and delayed phase (DP) of CEUS, and clinical factors were established. On the validation cohort, the diagnostic performance of the nomogram was assessed and compared with seniorexpert and resident radiologists. RESULTS: In the training cohort, the AP, PVP and DP scores exhibited better differential performance than BUS score, with area under the curve (AUC) of 84.1-85.1% compared with the BUS (74.6%, P < 0.05). In the validation cohort, the AUC of combined nomogram and expert was significantly higher than that of the resident (91.4% vs. 89.5% vs. 79.3%, P < 0.05). The combined nomogram had a comparable sensitivity with the expert and resident (95.2% vs. 98.4% vs. 97.6%), while the expert had a higher specificity than the nomogram and the resident (80.6% vs. 72.2% vs. 61.1%, P = 0.205). CONCLUSIONS: A CEUS ultrasomics based nomogram had an expert level performance in FLL characterization.

Team-Scouter: Simulative Visual Analytics of Soccer Player Scouting.

In soccer, player scouting aims to find players suitable for a team to increase the winning chance in future matches. To scout suitable players, coaches and analysts need to consider whether the players will perform well in a new team, which is hard to learn directly from their historical performances. Match simulation methods have been introduced to scout players by estimating their expected contributions to a new team. However, they usually focus on the simulation of match results and hardly support interactive analysis to navigate potential target players and compare them in fine-grained simulated behaviors. In this work, we propose a visual analytics method to assist soccer player scouting based on match simulation. We construct a two-level match simulation framework for estimating both match results and player behaviors when a player comes to a new team. Based on the framework, we develop a visual analytics system, Team-Scouter, to facilitate the simulative-based soccer player scouting process through player navigation, comparison, and investigation. With our system, coaches and analysts can find potential players suitable for the team and compare them on historical and expected performances. For an in-depth investigation of the players' expected performances, the system provides a visual comparison between the simulated behaviors of the player and the actual ones. The usefulness and effectiveness of the system are demonstrated by two case studies on a real-world dataset and an expert interview.

Smartboard: Visual Exploration of Team Tactics with LLM Agent.

Tactics play an important role in team sports by guiding how players interact on the field. Both sports fans and experts have a demand for analyzing sports tactics. Existing approaches allow users to visually perceive the multivariate tactical effects. However, these approaches require users to experience a complex reasoning process to connect the multiple interactions within each tactic to the final tactical effect. In this work, we collaborate with basketball experts and propose a progressive approach to help users gain a deeper understanding of how each tactic works and customize tactics on demand. Users can progressively sketch on a tactic board, and a coach agent will simulate the possible actions in each step and present the simulation to users with facet visualizations. We develop an extensible framework that integrates large language models (LLMs) and visualizations to help users communicate with the coach agent with multimodal inputs. Based on the framework, we design and develop Smartboard, an agent-based interactive visualization system for fine-grained tactical analysis, especially for play design. Smartboard provides users with a structured process of setup, simulation, and evolution, allowing for iterative exploration of tactics based on specific personalized scenarios. We conduct case studies based on real-world basketball datasets to demonstrate the effectiveness and usefulness of our system.