Generalized modality responses in primary sensory neurons of awake mice during the development of neuropathic pain.

Introduction: Peripheral sensory neurons serve as the initial responders to the external environment. How these neurons react to different sensory stimuli, such as mechanical or thermal forces applied to the skin, remains unclear. Methods: Using in vivo two-photon Ca2+ imaging in the lumbar 4 dorsal root ganglion (DRG) of awake Thy1.2-GCaMP6s mice, we assessed neuronal responses to various mechanical (punctate or dynamic) and thermal forces (heat or cold) sequentially applied to the paw plantar surface. Results: Our data indicate that in normal awake male mice, approximately 14 and 38% of DRG neurons respond to either single or multiple modalities of stimulation. Anesthesia substantially reduces the number of responsive neurons but does not alter the ratio of cells exhibiting single-modal responses versus multi-modal responses. Following peripheral nerve injury, DRG cells exhibit a more than 5.1-fold increase in spontaneous neuronal activity and a 1.5-fold increase in sensory stimulus-evoked activity. As neuropathic pain resulting from nerve injury progresses, the polymodal nature of sensory neurons intensifies. The polymodal population increases from 39.1 to 56.9%, while the modality-specific population decreases from 14.7 to 5.0% within a period of 5 days. Discussion: Our study underscores polymodality as a significant characteristic of primary sensory neurons, which becomes more pronounced during the development of neuropathic pain.

Rapid Diagnosis of Pneumocystis jirovecii Pneumonia and Respiratory Tract Colonization by Next-Generation Sequencing.

OBJECTIVES: To describe the epidemiology of Pneumocystis jirovecii pneumonia and colonization diagnosed by next-generation sequencing (NGS) and explore the usefulness of the number of P. jirovecii sequence reads for the diagnosis of P. jirovecii pneumonia. METHODS: We examined the NGS results for P. jirovecii in respiratory samples collected from patients and analysed their clinical, radiological and microbiological characteristics. RESULTS: Among 285 respiratory samples collected over a 12-month period (January to December 2022), P. jirovecii sequences were detected in 56 samples from 53 patients. Fifty (94.3%) of the 53 patients were HIV-negative. Following our case definitions, 37 (69.8%) and 16 (30.2%) of the 53 patients had P. jirovecii infection and colonization respectively. P. jirovecii infection was associated with presence of underlying disease with immunosuppression (94.6% vs 18.8%, P < 0.05), positive serum 1,3-ß-D-glucan (41.2% vs 0%, P < 0.01) and higher number of P. jirovecii sequence reads (P < 0.005). In contrast, P. jirovecii colonization was associated with the male sex (93.8% vs 54.1%, P < 0.01), another definitive infectious disease diagnosis of the respiratory tract (43.8% vs 2.7%, P < 0.001) and higher survival (100% vs 67.6%, P < 0.01). Although P. jirovecii pneumonia was associated with higher number of P. jirovecii reads in respiratory samples, only a sensitivity of 82.14% and a specificity of 68.75% could be achieved. CONCLUSION: Detection of P. jirovecii sequences in respiratory samples has to be interpreted discreetly. A combination of clinical, radiological and laboratory findings is still the most crucial in determining whether a particular case is genuine P. jirovecii pneumonia.

Nontyphoidal salmonella septic arthritis in A patient with systemic lupus erythematosus: A case report.

We report a case of septic arthritis in a 43-year-old female patient. Despite initial treatment with ceftriaxone for Nontyphoidal Salmonella based on blood and joint fluid culture results, the shoulder joint pain worsened. Suspected systemic lupus erythematosus associated synovitis did not respond to immunosuppressive therapy including methylprednisolone, hydroxychloroquine and methotrexate. Subsequent radiograph revealed a shoulder joint abscess, leading to arthroscopic joint debridement. Ceftriaxone was administered post-operatively until analgesic efficacy was attained. This case highlights the significance of accurate diagnosis and appropriate treatment for nontyphoidal Salmonella septic arthritis.

Single cell analysis reveals the roles and regulatory mechanisms of type-I interferons in Parkinson's disease.

The pathogenesis of Parkinson's disease (PD) is strongly associated with neuroinflammation, and type I interferons (IFN-I) play a crucial role in regulating immune and inflammatory responses. However, the specific features of IFN in different cell types and the underlying mechanisms of PD have yet to be fully described. In this study, we analyzed the GSE157783 dataset, which includes 39,024 single-cell RNA sequencing results for five PD patients and six healthy controls from the Gene Expression Omnibus database. After cell type annotation, we intersected differentially expressed genes in each cell subcluster with genes collected in The Interferome database to generate an IFN-I-stimulated gene set (ISGs). Based on this gene set, we used the R package AUCell to score each cell, representing the IFN-I activity. Additionally, we performed monocle trajectory analysis, and single-cell regulatory network inference and clustering (SCENIC) to uncover the underlying mechanisms. In silico gene perturbation and subsequent experiments confirm NFATc2 regulation of type I interferon response and neuroinflammation. Our analysis revealed that microglia, endothelial cells, and pericytes exhibited the highest activity of IFN-I. Furthermore, single-cell trajectory detection demonstrated that microglia in the midbrain of PD patients were in a pro-inflammatory activation state, which was validated in the 1-Methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced PD mouse model as well. We identified transcription factors NFATc2, which was significantly up-regulated and involved in the expression of ISGs and activation of microglia in PD. In the 1-Methyl-4-phenylpyridinium (MPP+)-induced BV2 cell model, the suppression of NFATc2 resulted in a reduction in IFN-ß levels, impeding the phosphorylation of STAT1, and attenuating the activation of the NF-κB pathway. Furthermore, the downregulation of NFATc2 mitigated the detrimental effects on SH-SY5Y cells co-cultured in conditioned medium. Our study highlights the critical role of microglia in type I interferon responses in PD. Additionally, we identified transcription factors NFATc2 as key regulators of aberrant type I interferon responses and microglial pro-inflammatory activation in PD. These findings provide new insights into the pathogenesis of PD and may have implications for the development of novel therapeutic strategies.

Macrophage hitchhiking for systematic suppression in postablative multifocal hepatocellular carcinoma.

BACKGROUND AIMS: Hepatocellular carcinoma (HCC), particularly the multifocal HCC, features aggressive invasion and dismal prognosis. Locoregional treatments were often refractory to eliminate tumor tissue, resulting in residual tumor cells persisting and subsequent progression. Owing to problematic delivery to the tumor tissue, systemic therapies, such as lenvatinib (LEN) therapy, show limited clinical benefit in preventing residual tumor progression. Therefore, more advanced strategies for postablative multifocal HCC are urgently needed. APPROACH RESULTS: Motivated by the chemotaxis in tumor penetration of macrophages, we report a strategy named microinvasive ablation-guided macrophage hitchhiking (MAMH) for the targeted therapy toward HCC. In this study, the strategy leverages the natural inflammatory gradient induced by ablation to guide LEN-loaded macrophages toward tumor targeting, which increased by ~10-fold the delivery efficiency of LEN in postablative HCC in vivo. MAMH has demonstrated significant antitumor activity in various HCC models, including the hydrodynamic tail vein injection multifocal HCC mouse model and the orthotopic xenograft HCC rabbit model, systematically inhibiting residual tumor progression after ablation and prolonging the median survival of tumor-bearing mice. The potential antitumor mechanism was explored using techniques such as flow cytometry, enzyme-linked immunosorbent assay, and immunohistochemistry. We found that the strategy significantly suppressed tumor cell proliferation and neovascularization, and such enhanced delivery of LEN stimulated systemic immune responses and induced durable immune memory. CONCLUSIONS: The macrophage hitchhiking strategy demonstrates exceptional therapeutic efficacy and biosafety across various species, offering promising prospects for clinical translation in controlling residual tumor progression and improving outcomes following HCC ablation.

Dihydromyricetin regulates RIPK3-CaMKII to prevent necroptosis in high glucose-stimulated cardiomyocytes.

Background: Diabetic cardiomyopathy is one common cardiovascular complication without effective treatments. Dihydromyricetin (DHY), a natural dihydroflavonol compound extracted from Ampelopsis grossedentata, possesses versatile pharmacologically important effects. In our current research, we planned to evaluate the impact and probable DHY mechanisms in high glucose (HG)-induced cardiomyocytes. Methods: Primary cardiomyocytes were pretreated with different concentrations of DHY (0, 20, 40, 80, 160, and 320 µM) for various time (0, 1, 2, 4, 12, and 24 h). They were then stimulated for 48 h with 5.5 mmol/L normal glucose (NG) and 33.3 mmol/L high glucose (HG). Cell viability, adenosine-triphosphate (ATP) levels, and lactate dehydrogenase (LDH) release of cardiomyocytes were detected. JC-1 staining was employed to measure the mitochondrial membrane potential. MitoSOX staining and dihydroethidium (DHE) staining were applied to evaluate the oxidative stress levels. TDT mediated dUTP nick end labeling (TUNEL) was used to measure apoptotic levels. Expressions of calcium/calmodulin-dependent protein kinase II (CaMKII), phospholamban (PLB), optic atrophy 1 (OPA1), dynamin-related protein 1 (DRP1), caspase 3, mixed kinase lineage domain like protein (MLKL), receptor interacting protein kinase 3 (RIPK3), and receptor interacting protein kinase 1 (RIPK1) were detected by immunofluorescence and/or Western blot. Results: DHY improved cell viability, enhanced ATP level, and decreased LDH content in HG-stimulated cardiomyocytes, suggesting DHY attenuating cell injury. DHY reduced number of TUNEL positive cells, inhibited RIPK3 and cleaved-caspase 3 expression, implying DHY alleviated necroptosis in HG-stimulated cardiomyocytes. DHY diminished JC-1 monomers, DHE and MitoSOX fluorescence intensity as well as DRP1 expression but increased JC-1 aggregates intensity and OPA1 expression, indicating that DHY attenuated oxidative stress in HG-stimulated cardiomyocytes. DHY also attenuated CaMKII activity by suppressed PLB phosphorylation and inhibited CaMKII oxidation in HG-stimulated cardiomyocytes. Conclusions: HG-induced cardiomyocytes injury was alleviated wherein DHY attenuated necroptosis, repressed ROS production, and inhibited CaMKII oxidation, suggesting that DHY may serve as potential agent to prevent and treat diabetic cardiomyopathy.

Inhibition of USP7 enhances CD8+ T cell activity in liver cancer by suppressing PRDM1-mediated FGL1 upregulation.

Lymphocyte activation gene 3 (LAG3), an immune checkpoint molecule expressed on activated T cells, functions as a negative regulator of immune responses. Persistent antigen exposure in the tumor microenvironment results in sustained LAG3 expression on T cells, contributing to T cell dysfunction. Fibrinogen-like protein 1 (FGL1) has been identified as a major ligand of LAG3, and FGL1/LAG3 interaction forms a novel immune checkpoint pathway that results in tumor immune evasion. In addition, ubiquitin-specific peptidase 7 (USP7) plays a crucial role in cancer development. In this study we investigated the role of USP7 in modulation of FGL1-mediated liver cancer immune evasion. We showed that knockdown of USP7 or treatment with USP7 inhibitor P5091 suppressed liver cancer growth by promoting CD8+ T cell activity in Hepa1-6 xenograft mice and in HepG2 or Huh7 cells co-cultured with T cells, whereas USP7 overexpression produced the opposite effect. We found that USP7 upregulated FGL1 in HepG2 and Huh7 cells by deubiquitination of transcriptional factor PR domain zinc finger protein 1 (PRDM1), which transcriptionally activated FGL1, and attenuated the CD8+ T cell activity, leading to the liver cancer growth. Interestingly, USP7 could be transcriptionally stimulated by PRDM1 as well in a positive feedback loop. P5091, an inhibitor of USP7, was able to downregulate FGL1 expression, thus enhancing CD8+ T cell activity. In an immunocompetent liver cancer mouse model, the dual blockade of USP7 and LAG3 resulted in a superior antitumor activity compared with anti-LAG3 therapy alone. We conclude that USP7 diminishes CD8+ T cell activity by a USP7/PRDM1 positive feedback loop on FGL1 production in liver cancer; USP7 might be a promising target for liver cancer immunotherapy.

Post-COVID-19 Pandemic Rebound of Macrolide-Resistant Mycoplasma pneumoniae Infection: A Descriptive Study.

The rebound characteristics of respiratory infections after lifting pandemic control measures were uncertain. From January to November 2023, patients presenting at a teaching hospital were tested for common respiratory viruses and Mycoplasma pneumoniae using a combination of antigen, nucleic acid amplification, and targeted next-generation sequencing (tNGS) tests. The number and rate of positive tests per month, clinical and microbiological characteristics were analyzed. A rapid rebound of SARS-CoV-2 was followed by a slower rebound of M. pneumoniae, with an interval of 5 months between their peaks. The hospitalization rate was higher, with infections caused by respiratory viruses compared to M. pneumoniae. Though the pediatric hospitalization rate of respiratory viruses (66.1%) was higher than that of M. pneumoniae (34.0%), the 4094 cases of M. pneumoniae within 6 months posed a huge burden on healthcare services. Multivariate analysis revealed that M. pneumoniae-infected adults had more fatigue, comorbidities, and higher serum C-reactive protein, whereas children had a higher incidence of other respiratory pathogens detected by tNGS or pathogen-specific PCR, fever, and were more likely to be female. A total of 85% of M. pneumoniae-positive specimens had mutations detected at the 23rRNA gene, with 99.7% showing A2063G mutation. Days to defervescence were longer in those not treated by effective antibiotics and those requiring a change in antibiotic treatment. A delayed but significant rebound of M. pneumoniae was observed after the complete relaxation of pandemic control measures. No unusual, unexplained, or unresponsive cases of respiratory infections which warrant further investigation were identified.

Targeting optimal power consumption: Optimizing operational parameters for orchard furrowing and fertilizing machine.

In response to the problem of excessive power consumption during the furrowing operation of orchard furrowing fertilizer machines, an optimization experiment of furrowing operation parameters for orchard furrowing fertilizer machine was conducted based on discrete element simulations. This research focused on the impact of furrowing device operation parameters on furrowing power consumption under full machine operating conditions. Firstly, a kinematics analysis of the soil granules during cutting was done. The mathematical model of soil granules through three movement processes of rising, detachment, and falling was established to determine the main factors affecting the power consumption of furrowing. Secondly, in assessing the furrowing power consumption, the stability coefficient of the furrowing depth, and the percentage of soil cover, alongside the key parameters of furrowing depth, forward propulsion velocity, and furrowing blade rotation speed, a comprehensive quadratic orthogonal rotation regression experiment was meticulously conducted. It was established that test metrics and test parameters regress. Finally, the test parameters were comprehensively optimized after analyzing each factor's impact on the test metrics. The orchard furrowing fertilizer machine's optimal operating parameters were determined, and the verification test was performed. According to the field test findings, the forward propulsion velocity was 785 m/h, and the furrowing blade rotation speed was 190 r/min when the furrowing depth was 275 mm. At this point, the furrowing power consumption was 2.39 kW, the soil cover percentage was 69.06%, and the furrowing depth stability coefficient was 95.08%. These results were in line with the requirements of orchard furrowing operation. The findings of the study can be utilized as a guide for structural changes to orchard furrowing equipment and the management of furrowing operation parameters.

Combination of Contrast-enhanced FlAIR and Contrast-enhanced T1WI: A Quick and Efficient Method in Detecting Brain Metastases of Lung Cancers.

BACKGROUND: Some patients with suspected brain metastases (BM) could not tolerate longer scanning examinations according to the standardized MRI protocol. OBJECTIVE: The purpose of this study was to evaluate the clinical value of contrast-enhanced fast fluid-attenuated inversion recovery (CE FLAIR) imaging in combination with contrast-enhanced T1 weighted imaging (CE T1WI) in detecting BM of lung cancer and explore a quick and effective MRI protocol. MATERIAL AND METHODS: In 201 patients with lung cancers and suspected BM, T1WI and FLAIR were performed before and after administration of gadopentetate dimeglumine. Two radiologists reviewed pre- and post-contrast images to determine the presence of abnormal contrast enhancement or signal intensity and decided whether it was metastatic or not on CE T1WI (Group 1) and CE FLAIR (Group 2). The number, locations and features of abnormal findings in two groups were recorded. Receiver Operating Characteristic (ROC) analyses were conducted in three groups: Group 1, 2 and 3(combination of CE FLAIR and CE T1WI). RESULTS: A total of 714 abnormal findings were revealed, of which 672 were considered as BM and 42 nonmetastatic. Superficial and small metastases(≤10mm) in parenchyma and ependyma, leptomeningeal and non-expansive skull metastases were typically better seen on CE FLAIR. The areas under ROC in the three groups were 0.720,0.887 and 0.973, respectively. Group 3 was significantly better in diagnostic efficiency of BMs than Group 1 (p<0.0001) or Group 2 (p=0.0006). CONCLUSION: The combination of CE T1WI and CE FLAIR promotes diagnostic performance and results in better observation and characterization of BM in patients with lung cancers. It provides a quick and efficient way of detecting BM.

Identification of autism spectrum disorder based on electroencephalography: A systematic review.

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by difficulties in social communication and repetitive and stereotyped behaviors. According to the World Health Organization, about 1 in 100 children worldwide has autism. With the global prevalence of ASD, timely and accurate diagnosis has been essential in enhancing the intervention effectiveness for ASD children. Traditional ASD diagnostic methods rely on clinical observations and behavioral assessment, with the disadvantages of time-consuming and lack of objective biological indicators. Therefore, automated diagnostic methods based on machine learning and deep learning technologies have emerged and become significant since they can achieve more objective, efficient, and accurate ASD diagnosis. Electroencephalography (EEG) is an electrophysiological monitoring method that records changes in brain spontaneous potential activity, which is of great significance for identifying ASD children. By analyzing EEG data, it is possible to detect abnormal synchronous neuronal activity of ASD children. This paper gives a comprehensive review of the EEG-based ASD identification using traditional machine learning methods and deep learning approaches, including their merits and potential pitfalls. Additionally, it highlights the challenges and the opportunities ahead in search of more effective and efficient methods to automatically diagnose autism based on EEG signals, which aims to facilitate automated ASD identification.

Exploring the resistance mechanism of triple-negative breast cancer to paclitaxel through the scRNA-seq analysis.

BACKGROUND: The triple negative breast cancer (TNBC) is the most malignant subtype of breast cancer with high aggressiveness. Although paclitaxel-based chemotherapy scenario present the mainstay in TNBC treatment, paclitaxel resistance is still a striking obstacle for cancer cure. So it is imperative to probe new therapeutic targets through illustrating the mechanisms underlying paclitaxel chemoresistance. METHODS: The Single cell RNA sequencing (scRNA-seq) data of TNBC cells treated with paclitaxel at different points were downloaded from the Gene Expression Omnibus (GEO) database. The Seurat R package was used to filter and integrate the scRNA-seq expression matrix. Cells were further clustered by the FindClusters function, and the gene marker of each subset was defined by FindAllMarkers function. Then, the hallmark score of each cell was calculated by AUCell R package, the biological function of the highly expressed interest genes was analyzed by the DAVID database. Subsequently, we performed pseudotime analysis to explore the change patterns of drug resistance genes and SCENIC analysis to identify the key transcription factors (TFs). Finally, the inhibitors of which were also analyzed by the CTD database. RESULTS: We finally obtained 6 cell subsets from 2798 cells, which were marked as AKR1C3+, WNT7A+, FAM72B+, RERG+, IDO1+ and HEY1+HCC1143 cell subsets, among which the AKR1C3+, IDO1+ and HEY1+ cell subsets proportions increased with increasing treatment time, and then were regarded as paclitaxel resistance subsets. Hallmark score and pseudotime analysis showed that these paclitaxel resistance subsets were associated with the inflammatory response, virus and interferon response activation. In addition, the gene regulatory networks (GRNs) indicated that 3 key TFs (STAT1, CEBPB and IRF7) played vital role in promoting resistance development, and five common inhibitors targeted these TFs as potential combination therapies of paclitaxel were identified. CONCLUSION: In this study, we identified 3 paclitaxel resistance relevant IFs and their inhibitors, which offers essential molecular basis for paclitaxel resistance and beneficial guidance for the combination of paclitaxel in clinical TNBC therapy.

The microRNA-211-5p/P2RX7/ERK/GPX4 axis regulates epilepsy-associated neuronal ferroptosis and oxidative stress.

Ferroptosis is an iron-dependent cell death mechanism involving the accumulation of lipid peroxides. As a critical regulator, glutathione peroxidase 4 (GPX4) has been demonstrated to be downregulated in epilepsy. However, the mechanism of ferroptosis in epilepsy remains unclear. In this study, bioinformatics analysis, analysis of epilepsy patient blood samples and cell and mouse experiments revealed strong associations among epilepsy, ferroptosis, microRNA-211-5p and purinergic receptor P2X 7 (P2RX7). P2RX7 is a nonselective ligand-gated homotrimeric cation channel, and its activation mainly increases neuronal activity during epileptic seizures. In our study, the upregulation of P2RX7 in epilepsy was attributed to the downregulation of microRNA (miR)-211-5p. Furthermore, P2RX7 has been found to regulate GPX4/HO-1 by alleviating lipid peroxidation induced by suppression of the MAPK/ERK signaling pathway in murine models. The dynamic decrease in miR-211-5p expression induces hypersynchronization and both nonconvulsive and convulsive seizures, and forebrain miR-211-5p suppression exacerbates long-lasting pentylenetetrazole-induced seizures. Additionally, in this study, induction of miR-211-5p expression or genetic-silencing of P2RX7 significantly reduced the seizure score and duration in murine models through the abovementioned pathways. These results suggest that the miR-211-5p/P2RX7 axis is a novel target for suppressing both ferroptosis and epilepsy.

Potassium deficiency diagnosis method of apple leaves based on MLR-LDA-SVM.

Introduction: At present, machine learning and image processing technology are widely used in plant disease diagnosis. In order to address the challenges of subjectivity, cost, and timeliness associated with traditional methods of diagnosing potassium deficiency in apple tree leaves. Methods: The study proposes a model that utilizes image processing technology and machine learning techniques to enhance the accuracy of detection during each growth period. Leaf images were collected at different growth stages and processed through denoising and segmentation. Color and shape features of the leaves were extracted and a multiple regression analysis model was used to screen for key features. Linear discriminant analysis was then employed to optimize the data and obtain the optimal shape and color feature factors of apple tree leaves during each growth period. Various machine-learning methods, including SVM, DT, and KNN, were used for the diagnosis of potassium deficiency. Results: The MLR-LDA-SVM model was found to be the optimal model based on comprehensive evaluation indicators. Field experiments were conducted to verify the accuracy of the diagnostic model, achieving high diagnostic accuracy during different growth periods. Discussion: The model can accurately diagnose whether potassium deficiency exists in apple tree leaves during each growth period. This provides theoretical guidance for intelligent and precise water and fertilizer management in orchards.

Parishin treatment alleviates cardiac aging in naturally aged mice.

Background: Cardiac aging progressively decreases physiological function and drives chronic/degenerative aging-related heart diseases. Therefore, it is crucial to postpone the aging process of heart and create products that combat aging. Aims & methods: The objective of this study is to examine the effects of parishin, a phenolic glucoside isolated from traditional Chinese medicine Gastrodia elata, on anti-aging and its underlying mechanism. To assess the senescent biomarkers, cardiac function, cardiac weight/body weight ratio, cardiac transcriptomic changes, and cardiac histopathological features, heart tissue samples were obtained from young mice (12 weeks), aged mice (19 months) treated with parishin, and aged mice that were not treated. Results: Parishin treatment improved cardiac function, ameliorated aging-induced cardiac injury, hypertrophy, and fibrosis, decreased cardiac senescence biomarkers p16Ink4a, p21Cip1, and IL-6, and increased the "longevity factor" SIRT1 expression in heart tissue. Furthermore, the transcriptomic analysis demonstrated that parishin treatment alleviated the cardiac aging-related Gja1 downregulation and Cyp2e1, Ccna2, Cdca3, and Fgf12 upregulation in the heart tissues. The correlation analysis suggested a strong connection between the anti-aging effect of parishin and its regulation of gut microbiota and metabolism in the aged intestine. Conclusion: The present study demonstrates the protective role and underlying mechanism of parishin against cardiac aging in naturally aged mice.

A brain tumor computer-aided diagnosis method with automatic lesion segmentation and ensemble decision strategy.

Objectives: Gliomas and brain metastases (Mets) are the most common brain malignancies. The treatment strategy and clinical prognosis of patients are different, requiring accurate diagnosis of tumor types. However, the traditional radiomics diagnostic pipeline requires manual annotation and lacks integrated methods for segmentation and classification. To improve the diagnosis process, a gliomas and Mets computer-aided diagnosis method with automatic lesion segmentation and ensemble decision strategy on multi-center datasets was proposed. Methods: Overall, 1,022 high-grade gliomas and 775 Mets patients' preoperative MR images were adopted in the study, including contrast-enhanced T1-weighted (T1-CE) and T2-fluid attenuated inversion recovery (T2-flair) sequences from three hospitals. Two segmentation models trained on the gliomas and Mets datasets, respectively, were used to automatically segment tumors. Multiple radiomics features were extracted after automatic segmentation. Several machine learning classifiers were used to measure the impact of feature selection methods. A weight soft voting (RSV) model and ensemble decision strategy based on prior knowledge (EDPK) were introduced in the radiomics pipeline. Accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC) were used to evaluate the classification performance. Results: The proposed pipeline improved the diagnosis of gliomas and Mets with ACC reaching 0.8950 and AUC reaching 0.9585 after automatic lesion segmentation, which was higher than those of the traditional radiomics pipeline (ACC:0.8850, AUC:0.9450). Conclusion: The proposed model accurately classified gliomas and Mets patients using MRI radiomics. The novel pipeline showed great potential in diagnosing gliomas and Mets with high generalizability and interpretability.

Inhibition of Galectin-9 sensitizes tumors to anthracycline treatment via inducing antitumor immunity.

Anthracyclines are a class of conventionally and routinely used first-line chemotherapy drugs for cancer treatment. In addition to the direct cytotoxic effects, increasing evidence indicates that the efficacy of the drugs also depends on immunomodulatory effects with unknown mechanisms. Galectin-9 (Gal-9), a member of the ß-galactoside-binding protein family, has been demonstrated to induce T-cell death and promote immunosuppression in the tumor microenvironment. Here, we asked whether anthracycline-mediated immunomodulatory activity might be related to Gal-9. We found that combining doxorubicin with anti-Gal-9 therapy significantly inhibited tumor growth and prolonged overall survival in immune-competent syngeneic mouse models. Moreover, Gal-9 expression was increased in response to doxorubicin in various human and murine cancer cell lines. Mechanistically, doxorubicin induced tumoral Gal-9 by activating the STING/interferon ß pathway. Clinically, Gal-9 and p-STING levels were elevated in the tumor tissues of breast cancer patients treated with anthracyclines. Our study demonstrates Gal-9 upregulation in response to anthracyclines as a novel mechanism mediating immune escape and suggests targeting Gal-9 in combination with anthracyclines as a promising therapeutic strategy for cancer treatment.

Long non­coding RNA L13Rik promotes high glucose-induced mesangial cell hypertrophy and matrix protein expression by regulating miR-2861/CDKN1B axis.

Background: Diabetic nephropathy (DN) is a frequent microvascular complication of diabetes. Glomerular mesangial cell (MC) hypertrophy occurs at the initial phase of DN and plays a critical role in the pathogenesis of DN. Given the role of long non coding RNA (lncRNA) in regulating MC hypertrophy and extracellular matrix (ECM) accumulation, our aim was to identify functional lncRNAs during MC hypertrophy. Methods: Here, an lncRNA, C920021L13Rik (L13Rik for short), was identified to be up-regulated in DN progression. The expression of L13Rik in DN patients and diabetic mice was assessed using quantitative real-time PCR (qRT-PCR), and the function of L13Rik in regulating HG-induced MC hypertrophy and ECM accumulation was assessed through flow cytometry and western blotting analysis. Results: The L13Rik levels were significantly increased while the miR-2861 levels were decreased in the peripheral blood of DN patients, the renal tissues of diabetic mice, and HG-treated MCs. Functionally, both L13Rik depletion and miR-2861 overexpression effectively reduced HG-induced cell hypertrophy and ECM accumulation. Mechanistically, L13Rik functioned as a competing endogenous RNA (ceRNA) to sponge miR-2861, resulting in the de-repression of cyclin-dependent kinase inhibitor 1B (CDKN1B), a gene known to regulate cell cycle and MC hypertrophy. Conclusions: Collectively, the current results demonstrate that up-regulated L13Rik is correlated with DN and may be a hopeful therapeutic target for DN.

Rapid Diagnosis of Urinary Tract Cancers on a LEGO-Inspired Detection Platform via Chemiresistive Profiling of Volatile Metabolites.

Rapid and in situ profiling of volatile metabolites from body fluids represents a new trend in cancer diagnosis and classification in the early stages. We report herein an on-chip strategy that combines an array of conductive nanosensors with a chaotic gas micromixer for real-time monitoring of volatiles from urine and for accurate diagnosis and classification of urinary tract cancers. By integrating a class of LEGO-inspired microchambers immobilized with MXene-based sensing nanofilms and zigzag microfluidic gas channels, it enables the intensive intermingling of volatile organic chemicals with sensor elements that tremendously facilitate their ion-dipole interactions for molecular recognition. Aided with an all-in-one, point-of-care platform and an effective machine-learning algorithm, healthy or diseased samples from subpopulations (i.e., tumor subtypes, staging, lymph node metastasis, and distant metastasis) of urinary tract cancers can be reliably fingerprinted in a few minutes with high sensitivity and specificity. The developed detection platform has proven to be a noninvasive supplement to the liquid biopsies available for facile screening of urinary tract cancers, which holds great potential for large-scale personalized healthcare in low-resource areas.

A CT-based radiomics integrated model for discriminating pulmonary cryptococcosis granuloma from lung adenocarcinoma-a diagnostic test.

Background: Chest computed tomography (CT) is a critical tool in the diagnosis of pulmonary cryptococcosis as approximately 30% of normal immunity individuals may not exhibit any significant symptoms or laboratory findings. Pulmonary cryptococcosis granuloma and lung adenocarcinoma can appear similar on noncontrast chest CT. This study evaluates the use of an integrated model that was developed based on radiomic features combined with demographic and radiological features to differentiate pulmonary cryptococcosis nodules from lung adenocarcinomas. Methods: Preoperative chest CT images for 215 patients with solid pulmonary nodules with histopathologically confirmed lung adenocarcinoma and cryptococcosis infection were collected from two clinical centers (108 cases in the training set and 107 cases in the test set divided by the different hospitals). Radiomics models were constructed based on nodular lesion volume (LV), 5-mm extended lesion volume (ELV), and perilesion volume (PLV). A demoradiological model was constructed using logistic regression based on demographic information (age, sex) and 12 radiological features (location, number, shape and specific imaging signs). Both models were used to build an integrated model, the performance of which was assessed using the test set. A junior and a senior radiologist evaluated the nodules. Receiver operating characteristic (ROC) curve analysis was conducted, and areas under the curve (AUCs), sensitivity (SEN), and specificity (SPE) of the models were calculated and compared. Results: Among the radiomics models, AUCs of the LV, ELV, and PLV were 0.558, 0.757, and 0.470, respectively. Age, lesion number, and lobular sign were identified as independent discriminative features providing an AUC of 0.77 in the demoradiological model (SEN 0.815, SPE 0.642). The integrated model achieved the highest AUC of 0.801 (SEN 0.759, SPE 0.755), which was significantly higher than that obtained by a junior radiologist (AUC =0.689, P=0.024) but showed no significant difference from that of the senior radiologist (AUC =0.784, P=0.388). Conclusions: An integrated model with radiomics and demoradiological features improves discrimination of cryptococcosis granulomas from solid adenocarcinomas on noncontrast CT. This model may be an effective strategy for machine complementation to discrimination by radiologists, and whole-lung automated recognition methods might dominate in the future.