LD-CSNet: A latent diffusion-based architecture for perceptual Compressed Sensing.

Compressed Sensing (CS) is a groundbreaking paradigm in image acquisition, challenging the constraints of the Nyquist-Shannon sampling theorem. This enables high-quality image reconstruction using a minimal number of measurements. Neural Networks' potent feature induction capabilities enable advanced data-driven CS methods to achieve high-fidelity image reconstruction. However, achieving satisfactory reconstruction performance, particularly in terms of perceptual quality, remains challenging at extremely low sampling rates. To tackle this challenge, we introduce a novel two-stage image CS framework based on latent diffusion, named LD-CSNet. In the first stage, we utilize an autoencoder pre-trained on a large dataset to represent natural images as low-dimensional latent vectors, establishing prior knowledge distinct from sparsity and effectively reducing the dimensionality of the solution space. In the second stage, we employ a conditional diffusion model for maximum likelihood estimates in the latent space. This is supported by a measurement embedding module designed to encode measurements, making them suitable for a denoising network. This guides the generation process in reconstructing low-dimensional latent vectors. Finally, the image is reconstructed using a pre-trained decoder. Experimental results across multiple public datasets demonstrate LD-CSNet's superior perceptual quality and robustness to noise. It maintains fidelity and visual quality at lower sampling rates. Research findings suggest the promising application of diffusion models in image CS. Future research can focus on developing more appropriate models for the first stage.

Gßγ dimers mediate low K+ stress-inhibited root growth via modulating auxin redistribution in Arabidopsis.

In the investigation of heterotrimeric G protein-mediated signal transduction in planta, their roles in the transmittance of low K+ stimuli remain to be elucidated. Here, we found that the primary root growth of wild-type Arabidopsis was gradually inhibited with the decrease of external K+ concentrations, while the primary root of the mutants for G protein ß subunit AGB1 and γ subunits AGG1, AGG2 and AGG3 could still grow under low K+ conditions (LK). Exogenous NAA application attenuated primary root elongation in agb1 and agg1/2/3 but promoted the growth in wild-type seedlings under LK stress. Using ProDR5:GFP, ProPIN1:PIN1-GFP and ProPIN2:PIN2-GFP reporter lines, a diminishment in auxin concentration at the radicle apex and a reduction in PIN1and PIN2 efflux carrier abundance were observed in wild-type roots under LK, a phenomenon not recorded in the agb1 and agg1/2/3. Further proteolytic and transcriptional assessments revealed an enhanced degradation of PIN1 and a suppressed expression of PIN2 in the wild-type background under LK, contrasting with the stability observed in the agb1 and agg1/2/3 mutants. Our results indicate that the G protein ß and γ subunits play pivotal roles in suppressing of Arabidopsis root growth under LK by modulating auxin redistribution via alterations in PIN1 degradation and PIN2 biosynthesis.

The Core-Shell Microneedle with Probiotic Extracellular Vesicles for Infected Wound Healing and Microbial Homeostasis Restoration.

Wound healing is a dynamic process involving the timely transition of organized phases. However, infected wounds often experience prolonged inflammation due to microbial overload. Thus, addressing the viable treatment needs across different healing stages is a critical challenge in wound management. Herein, a novel core-shell microneedle (CSMN) patch is designed for the sequential delivery of tannic acid-magnesium (TA-Mg) complexes and extracellular vesicles from Lactobacillus druckerii (LDEVs). Upon application to infected sites, CSMN@TA-Mg/LDEV releases TA-Mg first to counteract pathogenic overload and reduce reactive oxygen species (ROS), aiding the transition to proliferative phase. Subsequently, the sustained release of LDEVs enhances the activities of keratinocytes and fibroblasts, promotes vascularization, and modulates the collagen deposition. Notably, dynamic track of microbial composition demonstrates that CSMN@TA-Mg/LDEV can both inhibit the aggressive pathogen and increase the microbial diversity at wound sites. Functional analysis further highlights the potential of CSMN@TA-Mg/LDEV in facilitating wound healing and skin barrier restoration. Moreover, it is confirmed that CSMN@TA-Mg/LDEV can accelerate wound closure and improve post-recovery skin quality in the murine infected wound. Conclusively, this innovative CSMN patch offers a rapid and high-quality alternative treatment for infected wounds and emphasizes the significance of microbial homeostasis.

Win-win integration: A mitochondria targeted AIE photosensitizer for hypochlorite detection and type I & type II photodynamic therapy.

BACKGROUND: Photodynamic therapy (PDT) is a pioneering and effective anticancer modality with low adverse effects and high selectivity. Hypochlorous acid or hypochlorite (HClO/ClO-) is a type of inflammatory cytokine. The abnormal increase of ClO- in tumor cells is related to tumor pathogenesis and may be a "friend" for the design and synthesis of responsive phototherapy agents. However, preparing responsive phototherapy agents for all-in-one noninvasive diagnosis and simultaneous in situ therapy in a complex tumor environment is highly desirable but still remains an enormously demanding task. RESULTS: An acceptor-π bridge-donor-π bridge-acceptor (A-π-D-π-A) type photosensitizer TPTPy was designed and synthesized based on the phenothiazine structure which was used as the donor moiety as well as a ClO- responsive group. TPTPy was a multifunctional mitochondria targeted aggregation-induced emission (AIE) photosensitizer which could quickly and sensitively respond to ClO- with fluorescence "turn on" performance (19-fold fluorescence enhancement) and enhanced type I reactive oxygen species (ROS) generation to effectively ablate hypoxic tumor cells. The detection limit of TPTPy to ClO- was calculated to be 185.38 nM. The well-tailored TPTPy anchoring to mitochondria and producing ROS in situ could disrupt mitochondria and promote cell apoptosis. TPTPy was able to image inflammatory cells and tumor cells through ClO- response. In vivo results revealed that TPTPy was successfully utilized for PDT in tumor bearing nude mice and exhibited excellent biological safety for major organs. SIGNIFICANCE AND NOVELTY: A win-win integration strategy was proposed to design a tumor intracellular ClO- responsive photosensitizer TPTPy capable of both type I and type II ROS production to achieve photodynamic therapy of tumor. This work sheds light on the win-win integration design by taking full advantage of the characteristics of tumor microenvironment to build up responsive photosensitizer for in situ PDT of tumor.

Accurate de novo design of heterochiral protein-protein interactions.

Abiotic D-proteins that selectively bind to natural L-proteins have gained significant biotechnological interest. However, the underlying structural principles governing such heterochiral protein-protein interactions remain largely unknown. In this study, we present the de novo design of D-proteins consisting of 50-65 residues, aiming to target specific surface regions of L-proteins or L-peptides. Our designer D-protein binders exhibit nanomolar affinity toward an artificial L-peptide, as well as two naturally occurring proteins of therapeutic significance: the D5 domain of human tropomyosin receptor kinase A (TrkA) and human interleukin-6 (IL-6). Notably, these D-protein binders demonstrate high enantiomeric specificity and target specificity. In cell-based experiments, designer D-protein binders effectively inhibited the downstream signaling of TrkA and IL-6 with high potency. Moreover, these binders exhibited remarkable thermal stability and resistance to protease degradation. Crystal structure of the designed heterochiral D-protein-L-peptide complex, obtained at a resolution of 2.0 Å, closely resembled the design model, indicating that the computational method employed is highly accurate. Furthermore, the crystal structure provides valuable information regarding the interactions between helical L-peptides and D-proteins, particularly elucidating a novel mode of heterochiral helix-helix interactions. Leveraging the design of D-proteins specifically targeting L-peptides or L-proteins opens up avenues for systematic exploration of the mirror-image protein universe, paving the way for a diverse range of applications.

Blade-Coated Porous 3D Carbon Composite Electrodes Coupled with Multiscale Interfaces for Highly Sensitive All-Paper Pressure Sensors.

Flexible and wearable pressure sensors hold immense promise for health monitoring, covering disease detection and postoperative rehabilitation. Developing pressure sensors with high sensitivity, wide detection range, and cost-effectiveness is paramount. By leveraging paper for its sustainability, biocompatibility, and inherent porous structure, herein, a solution-processed all-paper resistive pressure sensor is designed with outstanding performance. A ternary composite paste, comprising a compressible 3D carbon skeleton, conductive polymer poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate), and cohesive carbon nanotubes, is blade-coated on paper and naturally dried to form the porous composite electrode with hierachical micro- and nano-structured surface. Combined with screen-printed Cu electrodes in submillimeter finger widths on rough paper, this creates a multiscale hierarchical contact interface between electrodes, significantly enhancing sensitivity (1014 kPa-1) and expanding the detection range (up to 300 kPa) of as-resulted all-paper pressure sensor with low detection limit and power consumption. Its versatility ranges from subtle wrist pulses, robust finger taps, to large-area spatial force detection, highlighting its intricate submillimeter-micrometer-nanometer hierarchical interface and nanometer porosity in the composite electrode. Ultimately, this all-paper resistive pressure sensor, with its superior sensing capabilities, large-scale fabrication potential, and cost-effectiveness, paves the way for next-generation wearable electronics, ushering in an era of advanced, sustainable technological solutions.

Machine learning-driven source identification and ecological risk prediction of heavy metal pollution in cultivated soils.

To overcome challenges in assessing the impact of environmental factors on heavy metal accumulation in soil due to limited comprehensive data, our study in Yangxin County, Hubei Province, China, analyzed 577 soil samples in combination with extensive big data. We used machine learning techniques, the potential ecological risk index, and the bivariate local Moran's index (BLMI) to predict Cr, Pb, Cd, As, and Hg concentrations in cultivated soil to assess ecological risks and identify pollution sources. The random forest model was selected for its superior performance among various machine learning models, and results indicated that heavy metal accumulation was substantially influenced by environmental factors such as climate, elevation, industrial activities, soil properties, railways, and population. Our ecological risk assessment highlighted areas of concern, where Cd and Hg were identified as the primary threats. BLMI was used to analyze spatial clustering and autocorrelation patterns between ecological risk and environmental factors, pinpointing areas that require targeted interventions. Additionally, redundancy analysis revealed the dynamics of heavy metal transfer to crops. This detailed approach mapped the spatial distribution of heavy metals, highlighted the ecological risks, identified their sources, and provided essential data for effective land management and pollution mitigation.

Regulation and mechanistic insights into tensile strain in mesenchymal stem cell osteogenic differentiation.

Bone marrow mesenchymal stem cells (BMSCs) are integral to bone remodeling and homeostasis, as they are capable of differentiating into osteogenic and adipogenic lineages. This differentiation is substantially influenced by mechanosensitivity, particularly to tensile strain, which is a prevalent mechanical stimulus known to enhance osteogenic differentiation. This review specifically examines the effects of various cyclic tensile stress (CTS) conditions on BMSC osteogenesis. It delves into the effects of different loading devices, magnitudes, frequencies, elongation levels, dimensionalities, and coculture conditions, providing a comparative analysis that aids identification of the most conducive parameters for the osteogenic differentiation of BMSCs. Subsequently, this review delineates the signaling pathways activated by CTS, such as Wnt/ß-catenin, BMP, Notch, MAPK, PI3K/Akt, and Hedgehog, which are instrumental in mediating the osteogenic differentiation of BMSCs. Through a detailed examination of these pathways, this study elucidates the intricate mechanisms whereby tensile strain promotes osteogenic differentiation, offering valuable guidance for optimizing therapeutic strategies aimed at enhancing bone regeneration.

Is Type 2 Diabetes Mellitus Associated with Spinal Degenerative Disorders?: Evidence from Observational and 2-Sample Mendelian Randomization Analyses.

BACKGROUND: Type 2 diabetes mellitus (T2DM) and spinal degenerative disorders (SDD) are common diseases that frequently coexist. However, both traditional observational studies and recent Mendelian randomization (MR) studies have demonstrated conflicting evidence on the association between T2DM and SDD. This comparative study explored and compared the association between T2DM and SDD using observational and MR analyses. METHODS: For observational analyses, cross-sectional studies (44,972 participants with T2DM and 403,095 participants without T2DM), case-control studies (38,234 participants with SDD and 409,833 participants without SDD), and prospective studies (35,550 participants with T2DM and 392,046 participants without T2DM with follow-up information until 2022) were performed to test the relationship between T2DM and SDD using individual-level data from the U.K. Biobank from 2006 to 2022. For MR analyses, the associations between single-nucleotide polymorphisms with SDD susceptibility obtained using participant data from the U.K. Biobank, which had 407,938 participants from 2006 to 2022, and the FinnGen Consortium, which had 227,388 participants from 2017 to 2022, and genetic predisposition to T2DM obtained using summary statistics from a pooled genome-wide association study involving 1,407,282 individuals were examined. The onset and severity of T2DM are not available in the databases being used. RESULTS: Participants with T2DM were more likely to have SDD than their counterparts. Logistic regression analysis identified T2DM as an independent risk factor for SDD, which was confirmed by the Cox proportional hazard model results. However, using single-nucleotide polymorphisms as instruments, the MR analyses demonstrated no causal relationship between T2DM and SDD. The lack of such an association was robust in the sensitivity analysis, and no pleiotropy was seen. CONCLUSIONS: Our results suggest that the association between T2DM and SDD may be method-dependent. Researchers and clinicians should be cautious in interpreting the association, especially the causal association, between T2DM and SDD. Our findings provide fresh insights into the association between T2DM and SDD by various analysis methods and guide future research and clinical efforts in the effective prevention and management of T2DM and SDD. LEVEL OF EVIDENCE: Prognostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Correlation between the three-dimensional hyoid bone parameters and pharyngeal airway dimensions in different sagittal and vertical malocclusions.

OBJECTIVE: This study aimed to explore the relationship between three-dimensional (3D) measurements of the hyoid bone (HB) and pharyngeal airway space (PAS) in relation to sagittal and vertical malocclusion. METHODS: A total of 368 cone-beam computed tomography (CBCT) scans were classified into three skeletal groups (Class I, II, and III) and subdivided by vertical growth patterns (hypodivergent, normodivergent, and hyperdivergent). PAS dimensions, including nasopharyngeal, oropharyngeal, hypopharyngeal, and total airway spaces, were measured in surface area, volume, minimum constricted area (MCA), length, and width, HB position and dimension were analyzed in 3D using InVivo 6.0.3 and Dolphin 11.8 software. Data were analyzed using two-way ANOVA, and Bonferroni post-hoc tests, with P ≤ 0.05 considered significant. RESULTS: The study found that patients with skeletal Class III and hypodivergent growth pattern had the highest sagittal position of the hyoid bone, while those with skeletal Class II and hyperdivergent pattern had the lowest hyoid length. Nasopharyngeal airway space width was significantly lower in skeletal Class III patients, while volume and area were lower in hyperdivergent patients. Oropharyngeal and hypopharyngeal dimensions were also affected by skeletal class and growth pattern, with hyperdivergent patients having the lowest values. Total pharyngeal volume, area, and minimum constricted area were also affected, with hyperdivergent patients having the lowest values and skeletal Class II patients having the lowest minimum constricted area. CONCLUSION: Pharyngeal airway dimensions and hyoid bone parameters vary with malocclusions. The hyoid bone's position influences the airway, identifying patients at risk for airway obstruction and sleep-disordered breathing.

Aqueous Grown Quantum Dots with Robust Near-Infrared Fluorescence for Integrated Traumatic Brain Injury Diagnosis and Surgical Monitoring.

Surgical intervention is the most common first-line treatment for severe traumatic brain injuries (TBIs) associated with high intracranial pressure, while the complexity of these surgical procedures often results in complications. Surgeons often struggle to comprehensively evaluate the TBI status, making it difficult to select the optimal intervention strategy. Here, we introduce a fluorescence imaging-based technology that uses high-quality silver indium selenide-based quantum dots (QDs) for integrated TBI diagnosis and surgical guidance. These engineered, poly(ethylene glycol)-capped QDs emit in the near-infrared region, are resistant to phagocytosis, and importantly, are ultrastable after the epitaxial growth of an aluminum-doped zinc sulfide shell in the aqueous phase that renders the QDs resistant to long-term light irradiation and complex physiological environments. We found that intravenous injection of QDs enabled both the precise diagnosis of TBI in a mouse model and, more importantly, the comprehensive evaluation of the TBI status before, during, and after an operation to distinguish intracranial from superficial hemorrhages, provide real-time monitoring of the secondary hemorrhage, and guide the decision making on the evacuation of intracranial hematomas. This QD-based diagnostic and monitoring system could ultimately complement existing clinical tools for treating TBI, which may help surgeons improve patient outcomes and avoid unnecessary procedures.

The tumor-stroma ratio in giant cell tumor of bone: associations with the immune microenvironment and responsiveness to denosumab treatment.

BACKGROUND: Currently, there is limited understanding regarding the clinical significance of the tumor-stroma ratio (TSR) in giant cell tumor of bone (GCTB). Hence, we aimed to investigate the distribution of TSR in GCTB and explore its correlation with various clinicopathologic factors, immune microenvironment, survival prognosis, and denosumab treatment responsiveness. METHODS: We conducted a multicenter cohort study comprising 426 GCTB patients treated at four centers. TSR was evaluated on hematoxylin and eosin-stained and immunofluorescent sections of tumor specimens. Immunohistochemistry was performed to assess CD3+, CD4+, CD8+, CD20+, PD-1+, PD-L1+, and FoxP3+ TIL subtypes as well as Ki-67 expression levels in 426 tissue specimens. These parameters were then analyzed for their correlations with patient outcomes [local recurrence-free survival (LRFS) and overall survival (OS)], clinicopathological features, and denosumab treatment responsiveness. RESULTS: Low TSR was significantly associated with poor LRFS and OS in both cohorts. Furthermore, TSR was also correlated with multiple clinicopathological features, TIL subtype expression, and denosumab treatment responsiveness. TSR demonstrated similar predictive capabilities as the conventional Campanacci staging system for predicting patients' LRFS and OS. CONCLUSION: The results of this study provide evidence supporting the use of TSR as a reliable prognostic tool in GCTB and as a predictor of denosumab treatment responsiveness. These findings may aid in developing individualized treatment strategies for GCTB patients in the future.

Comparative safety of monoclonal antibodies in chronic inflammatory airway diseases (chronic sinusitis with nasal polyposis and asthma): A network meta-analysis.

OBJECTIVE: Several monoclonal antibodies (MoAbs) targeting specific type 2 immune reactions have been developed as innovative therapeutic approaches for chronic inflammatory airway diseases, such as chronic sinusitis with nasal polyps (CRSwNP) and asthma. However, the clinical safety of these MoAbs and how to choose them are not clear. Therefore, we aimed to assess the systemic drug- and dose-based safety of MoAbs in chronic airway inflammation using network meta-analysis (NMA). METHODS: Electronic databases were systematically searched for relevant studies published in English between January 2009 and December 2022. Eligible studies must have clearly reported adverse events (AEs) among the MoAbs' safety data. RESULTS: 1). Regarding serious AEs, mepolizumab was significantly safer than placebo; in terms of permanent treatment discontinuation, reslizumab and dupilumab were significantly safer than benralizumab. 2). Regarding asthma worsening, dupilumab was associated with the best safety profile; was safer than dupilumab/300 mg/q2-4w. 3). In terms of injection-site reactions, dupilumab posed a higher risk than placebo; dupilumab/300 mg/qw posed a higher risk than dupilumab/300 mg/q2w and dupilumab/300 mg/q2-4w; lebrikizumab/250 mg/q4w posed a higher risk than lebrikizumab/37.5 mg/q4w; mepolizumab/100 mg/q4w posed a higher risk than mepolizumab/75 mg/q4w; benralizumab/30 mg/q4-8w posed a higher risk than benralizumab/20 mg/q4-8w. 4) In CRSwNP patients combined with asthma, the risks of experiencing AEs were not increased. CONCLUSION: Overall, biologics are safe and well tolerated in chronic inflammatory airway disease. This drug- and dose-based NMA provides further evidence on the different safety profiles of different emerging MoAbs. This information may help guide rational drug use and provide clinical recommendations for choosing MoAbs. TRIAL REGISTRATION: SYSTEMATIC REVIEW REGISTRATION (PROSPERO #CRD42023387610).

Targeted delivery of type I TGF-ß receptor-mimicking peptide to fibrotic kidney for improving kidney fibrosis therapy via enhancing the inhibition of TGF-ß1/Smad and p38 MAPK pathways.

Renal fibrosis is a representative pathological feature of various chronic kidney diseases, and efficient treatment is needed. Interstitial myofibroblasts are a key driver of kidney fibrosis, which is dependent on the binding of TGF-ß1 to type I TGF-ß receptor (TßRI) and TGF-ß1-related signaling pathways. Therefore, attenuating TGF-ß1 activity by competing with TGF-ß1 in myofibroblasts is an ideal strategy for treating kidney fibrosis. Recently, a novel TßRI-mimicking peptide RIPΔ demonstrated a high affinity for TGF-ß1. Thus, it could be speculated that RIPΔ may be used for anti-fibrosis therapy. Platelet-derived growth factor ß receptor (PDGFßR) is highly expressed in fibrotic kidney. In this study, we found that target peptide Z-RIPΔ, which is RIPΔ modified with PDGFßR-specific affibody ZPDGFßR, was specifically and highly taken up by TGF-ß1-activated NIH3T3 fibroblasts. Moreover, Z-RIPΔ effectively inhibited the myofibroblast proliferation, migration and fibrosis response in vitro. In vivo and ex vivo experiments showed that Z-RIPΔ specifically targeted fibrotic kidney, improved the damaged renal function, and ameliorated kidney histopathology and renal fibrosis in UUO mice. Mechanistic studies showed that Z-RIPΔ hold the stronger inhibition of the TGF-ß1/Smad and TGF-ß1/p38 pathways than unmodified RIPΔ in vitro and in vivo. Furthermore, systemic administration of Z-RIPΔ to UUO mice led to minimal toxicity to major organs. Taken together, RIPΔ modified with ZPDGFßR increased its therapeutic efficacy and reduced its systemic toxicity, making it a potential candidate for targeted therapy for kidney fibrosis.

Neddylation activated TRIM25 desensitizes triple-negative breast cancer to paclitaxel via TFEB-mediated autophagy.

BACKGROUND: Paclitaxel (PTX) treatment resistance is an important factor leading to poor prognosis in triple-negative breast cancer (TNBC), therefore there is an urgent need to identify new target for combination therapy. Neddylation is a post-translational process that introduces a ubiquitin-like protein called neural precursor cell expressed developmentally downregulated protein 8 (NEDD8). Previous studies have found that neddylation is activated in multiple tumors, but its relationship with PTX chemotherapy sensitivity has not been reported. METHODS: Differences in UBC12 and NEDD8 expression levels between PTX-sensitive and PTX-insensitive TNBC tissues were validated using public databases and immunohistochemistry. The in vitro and in vivo functional experiments were used to observe the effect of neddylation inhibition combined with PTX therapy on tumor progression. Co-IP, western blot and PCR assays were used to investigate the molecular mechanisms. Molecular docking was used to simulate the protein binding of UBC12 and TRIM25. Molecular dynamics simulation was used to observe the changes in TRIM25 protein conformation. RESULTS: We found that in TNBC that is insensitive to PTX, NEDD8 and NEDD8 conjugating enzyme UBC12 are highly expressed. Treatment with the NEDD8-activating enzyme (NAE) inhibitor mln4924 or knockdown of UBC12 significantly increased the sensitivity of the tumor to PTX, and this increase in sensitivity is related to UBC12-mediated autophagy activation. Mechanistically, UBC12 can transfer NEDD8 to E3 ubiquitin ligase tripartite motif containing 25 (TRIM25) at K117. Molecular dynamics simulations indicate that the neddylation modification of TRIM25 reduces steric hindrance in its RING domain, facilitating the binding of TRIM25 and ubiquitylated substrates. Subsequently, TRIM25 promotes the nuclear translocation of transcription factor EB (TFEB) and transcription of autophagy related genes by increasing K63-polyubiquitination of TFEB, thereby reducing tumor sensitivity to PTX. CONCLUSIONS: Neddylation is activated in PTX-insensitive TNBC. Specifically, autophagy gene transcriptional activation mediated by the UBC12/TRIM25/TFEB axis reduces TNBC sensitivity to PTX. Neddylation suppression combination with PTX treatment shows a synergistic anti-tumor effect.

Eigendecomposition-free inverse design of meta-optics devices.

The inverse design of meta-optics has received much attention in recent years. In this paper, we propose a GPU-friendly inverse design framework based on improved eigendecomposition-free rigorous diffraction interface theory, which offers up to 16.2 × speedup over the traditional inverse design based on rigorous coupled-wave analysis. We further improve the framework's flexibility by introducing a hybrid parameterization combining neural-implicit and traditional shape optimization. We demonstrate the effectiveness of our framework through intricate tasks, including the inverse design of reconfigurable free-form meta-atoms.

Potential of digital chest radiography-based deep learning in screening and diagnosing pneumoconiosis: An observational study.

The diagnosis of pneumoconiosis is complex and subjective, leading to inevitable variability in readings. This is especially true for inexperienced doctors. To improve accuracy, a computer-assisted diagnosis system is used for more effective pneumoconiosis diagnoses. Three models (Resnet50, Resnet101, and DenseNet) were used for pneumoconiosis classification based on 1250 chest X-ray images. Three experienced and highly qualified physicians read the collected digital radiography images and classified them from category 0 to category III in a double-blinded manner. The results of the 3 physicians in agreement were considered the relative gold standards. Subsequently, 3 models were used to train and test these images and their performance was evaluated using multi-class classification metrics. We used kappa values and accuracy to evaluate the consistency and reliability of the optimal model with clinical typing. The results showed that ResNet101 was the optimal model among the 3 convolutional neural networks. The AUC of ResNet101 was 1.0, 0.9, 0.89, and 0.94 for detecting pneumoconiosis categories 0, I, II, and III, respectively. The micro-average and macro-average mean AUC values were 0.93 and 0.94, respectively. The accuracy and Kappa values of ResNet101 were 0.72 and 0.7111 for quadruple classification and 0.98 and 0.955 for dichotomous classification, respectively, compared with the relative standard classification of the clinic. This study develops a deep learning based model for screening and staging of pneumoconiosis is using chest radiographs. The ResNet101 model performed relatively better in classifying pneumoconiosis than radiologists. The dichotomous classification displayed outstanding performance, thereby indicating the feasibility of deep learning techniques in pneumoconiosis screening.

Complex immune microenvironment of chordoma: a road map for future treatment.

BACKGROUND: Chordoma, a rare bone tumor, presents limited treatment options and patients typically exhibit poor survival outcomes. While immunotherapy has shown promising results in treating various tumors, research on the immune microenvironment of chordomas is still in its early stages. Therefore, understanding how the immune microenvironment of chordomas influences the outcomes of immunotherapy is crucial. METHODS: We employed single-cell RNA sequencing (scRNA-seq), bulk RNA-seq, CellChat, gene set variation analysis, as well as calculation of immune features to further dissect the complex immune microenvironment of chordoma. RESULTS: Previous research by van Oost et al argued that compared with other sarcomas, chordomas typically exhibit an immunologically "hot" microenvironment, a conclusion with which we concur based on their research findings. Additionally, the authors suggest that T cell-mediated immunotherapy is feasible for the majority of chordomas. However, we are inclined to categorize them as an immune-excluded phenotype according to the latest classification methods, rather than persisting with the concepts of "cold" and "hot". Unlike them, we explored immune infiltration scores (IS), T lymphocyte scoring (TLS), and human leucocyte antigen class I (HLA-I) using Bulk RNA-seq data from 126 chordoma patients and found that higher IS, TLS, and higher HLA-I expression were associated with poorer patient prognosis. Additionally, CellChat analysis of scRNA-seq results from six chordoma patients revealed no direct interaction between T cells and tumor cells. CONCLUSIONS: These findings suggested that the efficacy of T cell-based immunotherapy may be limited or even ineffective for patients with chordoma.

Development of a predictive nomogram for in-hospital death risk in multimorbid patients with hepatocellular carcinoma undergoing Palliative Locoregional Therapy.

Patients diagnosed with hepatocellular carcinoma (HCC) often present with multimorbidity, significantly contributing to adverse outcomes, particularly in-hospital mortality. This study aimed to develop a predictive nomogram to assess the impact of comorbidities on in-hospital mortality risk in HCC patients undergoing palliative locoregional therapy. We retrospectively analyzed data from 345 hospitalized HCC patients who underwent palliative locoregional therapy between January 2015 and December 2022. The nomogram was constructed using independent risk factors such as length of stay (LOS), hepatitis B virus (HBV) infection, hypertension, chronic obstructive pulmonary disease (COPD), anemia, thrombocytopenia, liver cirrhosis, hepatic encephalopathy (HE), N stage, and microvascular invasion. The model demonstrated high predictive accuracy with an AUC of 0.908 (95% CI: 0.859-0.956) for the overall dataset, 0.926 (95% CI: 0.883-0.968) for the training set, and 0.862 (95% CI: 0.728-0.994) for the validation set. Calibration curves indicated a strong correlation between predicted and observed outcomes, validated by statistical tests. Decision curve analysis (DCA) and clinical impact curves (CIC) confirmed the model's clinical utility in predicting in-hospital mortality. This nomogram offers a practical tool for personalized risk assessment in HCC patients undergoing palliative locoregional therapy, facilitating informed clinical decision-making and improving patient management.