Integrating molecular dynamics simulation with small- and wide-angle X-ray scattering to unravel the flexibility, antigen-blocking, and protease-restoring functions in a hindrance-based pro-antibody.

Spatial hindrance-based pro-antibodies (pro-Abs) are engineered antibodies to reduce monoclonal antibodies' (mAbs) on-target toxicity using universal designed blocking segments that mask mAb antigen-binding sites through spatial hindrance. By linking through protease substrates and linkers, these blocking segments can be removed site-specifically. Although many types of blocking segments have been developed, such as coiled-coil and hinge-based Ab locks, the molecular structure of the pro-Ab, particularly the region showing how the blocking fragment blocks the mAb, has not been elucidated by X-ray crystallography or cryo-EM. To achieve maximal effect, a pro-Ab must have high antigen-blocking and protease-restoring efficiencies, but the unclear structure limits its further optimization. Here, we utilized molecular dynamics (MD) simulations to study the dynamic structures of a hinge-based Ab lock pro-Ab, pro-Nivolumab, and validated the simulated structures with small- and wide-angle X-ray scattering (SWAXS). The MD results were closely consistent with SWAXS data (χ2 best-fit = 1.845, χ2 allMD = 3.080). The further analysis shows a pronounced flexibility of the Ab lock (root-mean-square deviation = 10.90 Å), yet it still masks the important antigen-binding residues by 57.3%-88.4%, explaining its 250-folded antigen-blocking efficiency. The introduced protease accessible surface area method affirmed better protease efficiency for light chain (33.03 Å2) over heavy chain (5.06 Å2), which aligns with the experiments. Overall, we developed MD-SWAXS validation method to study the dynamics of flexible blocking segments and introduced methodologies to estimate their antigen-blocking and protease-restoring efficiencies, which would potentially be advancing the clinical applications of any spatial hindrance-based pro-Ab.

Clustering one million molecular structures on GPU within seconds.

Structure clustering is a general but time-consuming work in the study of life science. Up to now, most published tools do not support the clustering analysis on graphics processing unit (GPU) with root mean square deviation metric. In this work, we specially write codes to do the work. It supports multiple threads on multiple GPUs. To show the performance, we apply the program to a 33-residue fragment in protein Pin1 WW domain mutant. The dataset contains 1,400,000 snapshots, which are extracted from an enhanced sampling simulation and distribute widely in the conformational space. Various testing results present that our program is quite efficient. Particularly, with two NVIDIA RTX4090 GPUs and single precision data type, the clustering calculation on 1 million snapshots is completed in a few seconds (including the uploading time of data from memory to GPU and neglecting the reading time from hard disk). This is hundreds of times faster than central processing unit. Our program could be a powerful tool for fast extraction of representative states of a molecule among its thousands to millions of candidate structures.

Microparticle Mediated Delivery of Apelin Improves Heart Function in Post Myocardial Infarction Mice.

BACKGROUND: Apelin is an endogenous prepropeptide that regulates cardiac homeostasis and various physiological processes. Intravenous injection has been shown to improve cardiac contractility in patients with heart failure. However, its short half-life prevents studying its impact on left ventricular remodeling in the long term. Here, we aim to study whether microparticle-mediated slow release of apelin improves heart function and left ventricular remodeling in mice with myocardial infarction (MI). METHODS: A cardiac patch was fabricated by embedding apelin-containing microparticles in a fibrin gel scaffold. MI was induced via permanent ligation of the left anterior descending coronary artery in adult C57BL/6J mice followed by epicardial patch placement immediately after (acute MI) or 28 days (chronic MI) post-MI. Four groups were included in this study, namely sham, MI, MI plus empty microparticle-embedded patch treatment, and MI plus apelin-containing microparticle-embedded patch treatment. Cardiac function was assessed by transthoracic echocardiography. Cardiomyocyte morphology, apoptosis, and cardiac fibrosis were evaluated by histology. Cardioprotective pathways were determined by RNA sequencing, quantitative polymerase chain reaction, and Western blot. RESULTS: The level of endogenous apelin was largely reduced in the first 7 days after MI induction and it was normalized by day 28. Apelin-13 encapsulated in poly(lactic-co-glycolic acid) microparticles displayed a sustained release pattern for up to 28 days. Treatment with apelin-containing microparticle-embedded patch inhibited cardiac hypertrophy and reduced scar size in both acute and chronic MI models, which is associated with improved cardiac function. Data from cellular and molecular analyses showed that apelin inhibits the activation and proliferation of cardiac fibroblasts by preventing transforming growth factor-ß-mediated activation of Smad2/3 and downstream profibrotic gene expression. CONCLUSIONS: Poly(lactic-co-glycolic acid) microparticles prolonged the apelin release time in the mouse hearts. Epicardial delivery of the apelin-containing microparticle-embedded patch protects mice from both acute and chronic MI-induced cardiac dysfunction, inhibits cardiac fibrosis, and improves left ventricular remodeling.

LVPocket: integrated 3D global-local information to protein binding pockets prediction with transfer learning of protein structure classification.

BACKGROUND: Previous deep learning methods for predicting protein binding pockets mainly employed 3D convolution, yet an abundance of convolution operations may lead the model to excessively prioritize local information, thus overlooking global information. Moreover, it is essential for us to account for the influence of diverse protein folding structural classes. Because proteins classified differently structurally exhibit varying biological functions, whereas those within the same structural class share similar functional attributes. RESULTS: We proposed LVPocket, a novel method that synergistically captures both local and global information of protein structure through the integration of Transformer encoders, which help the model achieve better performance in binding pockets prediction. And then we tailored prediction models for data of four distinct structural classes of proteins using the transfer learning. The four fine-tuned models were trained on the baseline LVPocket model which was trained on the sc-PDB dataset. LVPocket exhibits superior performance on three independent datasets compared to current state-of-the-art methods. Additionally, the fine-tuned model outperforms the baseline model in terms of performance. SCIENTIFIC CONTRIBUTION: We present a novel model structure for predicting protein binding pockets that provides a solution for relying on extensive convolutional computation while neglecting global information about protein structures. Furthermore, we tackle the impact of different protein folding structures on binding pocket prediction tasks through the application of transfer learning methods.

Oral mucosal lesions triage via YOLOv7 models.

BACKGROUND/PURPOSE: The global incidence of lip and oral cavity cancer continues to rise, necessitating improved early detection methods. This study leverages the capabilities of computer vision and deep learning to enhance the early detection and classification of oral mucosal lesions. METHODS: A dataset initially consisting of 6903 white-light macroscopic images collected from 2006 to 2013 was expanded to over 50,000 images to train the YOLOv7 deep learning model. Lesions were categorized into three referral grades: benign (green), potentially malignant (yellow), and malignant (red), facilitating efficient triage. RESULTS: The YOLOv7 models, particularly the YOLOv7-E6, demonstrated high precision and recall across all lesion categories. The YOLOv7-D6 model excelled at identifying malignant lesions with notable precision, recall, and F1 scores. Enhancements, including the integration of coordinate attention in the YOLOv7-D6-CA model, significantly improved the accuracy of lesion classification. CONCLUSION: The study underscores the robust comparison of various YOLOv7 model configurations in the classification to triage oral lesions. The overall results highlight the potential of deep learning models to contribute to the early detection of oral cancers, offering valuable tools for both clinical settings and remote screening applications.

Decoding frontotemporal and cell-type-specific vulnerabilities to neuropsychiatric disorders and psychoactive drugs.

Frontotemporal lobe abnormalities are linked to neuropsychiatric disorders and cognition, but the role of cellular heterogeneity between temporal lobe (TL) and frontal lobe (FL) in the vulnerability to genetic risk factors remains to be elucidated. We integrated single-nucleus transcriptome analysis in 'fresh' human FL and TL with genetic susceptibility, gene dysregulation in neuropsychiatric disease and psychoactive drug response data. We show how intrinsic differences between TL and FL contribute to the vulnerability of specific cell types to both genetic risk factors and psychoactive drugs. Neuronal populations, specifically PVALB neurons, were most highly vulnerable to genetic risk factors for psychiatric disease. These psychiatric disease-associated genes were mostly upregulated in the TL, and dysregulated in the brain of patients with obsessive-compulsive disorder, bipolar disorder and schizophrenia. Among these genes, GRIN2A and SLC12A5, implicated in schizophrenia and bipolar disorder, were significantly upregulated in TL PVALB neurons and in psychiatric disease patients' brain. PVALB neurons from the TL were twofold more vulnerable to psychoactive drugs than to genetic risk factors, showing the influence and specificity of frontotemporal lobe differences on cell vulnerabilities. These studies provide a cell type resolved map of the impact of brain regional differences on cell type vulnerabilities in neuropsychiatric disorders.

Reduced Graphene-Oxide-Doped Elastic Biodegradable Polyurethane Fibers for Cardiomyocyte Maturation.

Conductive biomaterials offer promising solutions to enhance the maturity of cultured cardiomyocytes. While the conventional culture of cardiomyocytes on nonconductive materials leads to more immature characteristics, conductive microenvironments have the potential to support sarcomere development, gap junction formation, and beating of cardiomyocytes in vitro. In this study, we systematically investigated the behaviors of cardiomyocytes on aligned electrospun fibrous membranes composed of elastic and biodegradable polyurethane (PU) doped with varying concentrations of reduced graphene oxide (rGO). Compared to PU and PU-4%rGO membranes, the PU-10%rGO membrane exhibited the highest conductivity, approaching levels close to those of native heart tissue. The PU-rGO membranes retained anisotropic viscoelastic behavior similar to that of the porcine left ventricle and a superior tensile strength. Neonatal rat cardiomyocytes (NRCMs) and human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) on the PU-rGO membranes displayed enhanced maturation with cell alignment and enhanced sarcomere structure and gap junction formation with PU-10%rGO having the most improved sarcomere structure and CX-43 presence. hiPSC-CMs on the PU-rGO membranes exhibited a uniform and synchronous beating pattern compared with that on PU membranes. Overall, PU-10%rGO exhibited the best performance for cardiomyocyte maturation. The conductive PU-rGO membranes provide a promising matrix for in vitro cardiomyocyte culture with promoted cell maturation/functionality and the potential for cardiac disease treatment.

Traditional, complementary and integrative medicine for fatigue post COVID-19 infection: A systematic review of randomized controlled trials.

Background: Chronic fatigue is a predominant symptom of post COVID-19 condition, or long COVID. We aimed to evaluate the efficacy and safety of Traditional, Complementary and Integrative Medicine (TCIM) for fatigue post COVID-19 infection. Methods: Ten English and Chinese language databases and grey literature were searched up to 12 April 2023 for randomized controlled trials (RCTs). Cochrane "Risk of bias" (RoB) tool was applied. Evidence certainty was assessed using Grading of Recommendations Assessment, Development, and Evaluation (GRADE). Effect estimates were presented as risk ratio (RR) or mean difference (MD) with 95% confidence interval (CI). Results: Thirteen RCTs with 1632 participants were included. One RCT showed that Bufei Huoxue herbal capsules reduced fatigue (n=129, MD -14.90, 95%CI -24.53 to -5.27), one RCT reported that Ludangshen herbal liquid lowered fatigue (n=184, MD -1.90, 95%CI -2.38 to -1.42), and the other one RCT shown that fatigue disappearance rate was higher with Ludangshen herbal liquid (n=184, RR 4.19, 95%CI 2.06 to 8.53). Compared to traditional Chinese medicine rehabilitation (TCM-rahab) alone, one RCT showed that fatigue symptoms were lower following Qingjin Yiqi granules plus TCM-rehab (n=388, MD -0.48, 95%CI -0.50 to -0.46). Due to concerns with RoB and/or imprecision, the certainty in this evidence was low to very low. No serious adverse events was reported. Conclusions: Limited evidence suggests that various TCIM interventions might reduce post COVID-19 fatigue. Larger, high quality RCTs of longer duration are required to confirm these preliminary findings. Study Registration: The protocol of this review has been registered at PROSPERO: CRD42022384136.

Revolutionizing Neurocare: Biomimetic Nanodelivery Via Cell Membranes.

Brain disorders represent a significant challenge in medical science due to the formidable blood-brain barrier (BBB), which severely limits the penetration of conventional therapeutics, hindering effective treatment strategies. This review delves into the innovative realm of biomimetic nanodelivery systems, including stem cell-derived nanoghosts, tumor cell membrane-coated nanoparticles, and erythrocyte membrane-based carriers, highlighting their potential to circumvent the BBB's restrictions. By mimicking native cell properties, these nanocarriers emerge as a promising solution for enhancing drug delivery to the brain, offering a strategic advantage in overcoming the barrier's selective permeability. The unique benefits of leveraging cell membranes from various sources is evaluated and advanced technologies for fabricating cell membrane-encapsulated nanoparticles capable of masquerading as endogenous cells are examined. This enables the targeted delivery of a broad spectrum of therapeutic agents, ranging from small molecule drugs to proteins, thereby providing an innovative approach to neurocare. Further, the review contrasts the capabilities and limitations of these biomimetic nanocarriers with traditional delivery methods, underlining their potential to enable targeted, sustained, and minimally invasive treatment modalities. This review is concluded with a perspective on the clinical translation of these biomimetic systems, underscoring their transformative impact on the therapeutic landscape for intractable brain diseases.

Co-occurring EGFR p.E709X Mutation Mediates Primary Resistance to the Third-Generation EGFR-TKIs in EGFR p.G719X-Mutant Patients with Advanced NSCLC.

PURPOSE: The current National Comprehensive Cancer Network (NCCN) guidelines recommend afatinib or osimertinib as the preferred first-line treatment strategy for patients with advanced NSCLC harboring EGFR p.G719X mutation. However, in the absence of head-to-head trials comparing afatinib with osimertinib in EGFR p.G719X-mutant patients, it is unclear which regimen is the preferred treatment option. EXPERIMENTAL DESIGN: A large cohort of 4,228 treatment-naïve patients with lung cancer who underwent targeted next-generation sequencing (NGS) testing was screened for EGFR p.G719X mutation. A multicenter cohort involving 68 EGFR p.G719X-mutant patients with advanced NSCLC and NGS profiling was retrospectively enrolled to evaluate clinical responses to afatinib (n = 37) and the third-generation EGFR-TKIs (n = 31). Ba/F3 cells stably expressing the EGFR p.G719A mutation were created to investigate the response to EGFR-TKIs in vitro. RESULTS: Concurrent EGFR p.E709X mutations, being the most frequent co-occurring EGFR mutation in EGFR p.G719X-mutant NSCLC (∼30%), exerted a detrimental effect on outcomes in patients treated with third-generation EGFR-TKI [G719X/E709X vs. G719X; objective response rate (ORR): 0.00% vs. 47.62%, P < 0.001; mPFS: 7.18 vs. 14.2 months, P = 0.04, respectively]. Conversely, no significant difference was found in the treatment efficacy of afatinib between EGFR p.G719X/E709X and EGFR p.G719X patients (G719X/E709X vs. G719X; ORR: 71.43% vs. 56.67%, P = 0.99; mPFS: 14.7 vs. 15.8 months, P = 0.69, respectively). In vitro experiments elucidated a resistant drug sensitivity and poor inhibition of EGFR phosphorylation in Ba/F3 cells expressing EGFR p.G719A/E709K mutation upon the third-generation EGFR-TKI treatment. CONCLUSIONS: Co-occurring EGFR p.E709X mutation mediated primary resistance to the third-generation EGFR-TKIs in EGFR p.G719X-mutant patients but remained sensitive to afatinib. A personalized treatment strategy should be undertaken based on the coexisting EGFR p.E709X mutation status.

A preliminary study of optimal treatment response rates in patients undergoing hepatic arterial infusion chemotherapy combined with molecular targeting and immunotherapy.

Objectives: This study aimed to examine the effectiveness of the best response rate (BRR) as a surrogate for overall survival (OS), using the modified Response Evaluation Criteria in Solid Tumors (mRECIST), in patients with unresectable hepatocellular carcinoma (HCC) undergoing hepatic arterial infusion chemotherapy (HAIC) with fluorouracil, leucovorin, and oxaliplatin (FOLFOX) combined with molecular targeting and immunotherapy. Methods: This study enrolled 111 consecutive patients who had complete imaging data. The median age of patients was 58 years (IQR 50.5-65.0). Among the patients, those with Barcelona Clinic Liver Cancer (BCLC) stage A, BCLC stage B, and BCLC stage C comprised 6.4%, 19.1%, and 73.6%, respectively. The optimal threshold of BRR can be determined using restricted cubic splines (RCS) and the rank sum statistics of maximum selection. Survival curves of patients in the high rating and low rating groups were plotted. We then used the change-in-estimate (CIE) method to filter out confounders and the inverse probability of treatment weighting (IPTW) to balance confounders between the two groups to assess the robustness of the results. Results: The median frequency of the combination treatment regimens administered in the overall population was 3 times (IQR 2.0-3.0). The optimal BRR truncation value calculated was -0.2. Based on this value, 77 patients were categorized as the low rating group and 34 as the high rating group. The differences in the OS between the high and low rating groups were statistically significant (7 months [95%CI 6.0-14.0] vs. 30 months [95%CI 30.0-]; p< 0.001). Using the absolute 10% cut-off value, the CIE method was used to screen out the following confounding factors affecting prognosis: successful conversion surgery, baseline tumor size, BCLC stage, serum total bilirubin level, number of interventional treatments, alpha-fetoprotein level, presence of inferior vena cava tumor thrombus, and partial thrombin activation time. The survival curve was then plotted again using IPTW for confounding factors, and it was found that the low rating group continued to have better OS than the high rating group. Finally, the relationship between BRR and baseline factors was analyzed, and inferior vena cava tumor thrombus and baseline tumor size correlated significantly with BRR. Conclusions: BRR can be used as a surrogate endpoint for OS in unresectable HCC patients undergoing FOLFOX-HAIC in combination with molecular targeting and immunotherapy. Thus, by calculating the BRR, the prognosis of HCC patients after combination therapy can be predicted. Inferior vena cava tumor thrombus and baseline tumor size were closely associated with the BRR.

[Effect of Naotaifang on microglial polarization and glial scar following cerebral ischemia reperfusion injury].

This study aims to investigate the effect of Naotaifang(NTF) on the proteins associated with microglial polarization and glial scar in the rat model of cerebral ischemia reperfusion injury(CIRI). The CIRI model was established by middle cerebral artery occlusion/reperfusion. The 48 successfully modeled rats were randomized into model 7 d, model 14 d, NTF 7 d, and NTF 14 d groups(n=12). In addition, 12 SD rats were selected as the sham group. The NTF group was administrated with NTF suspension at 27 g·kg~(-1)·d~(-1) by gavage, and the sham, model 7 d, and model 14 d groups were administrated with the same volume of normal saline every day by gavage for 7 and 14 days, respectively. After the intervention, Longa score was evaluated. The infarct volume was measured by 2,3,5-triphenyl-2H-tetrazolium chloride(TTC) staining. Morris water maze and open field tests were carried out to evaluate the spatial learning, memory, cognitive function, and anxiety degree of rats. Hematoxylin-eosin(HE) staining was employed to observe the morphological structure and damage of the brain tissue. The immunofluorescence assay was employed to measure the expression of glial fibrillary acidic protein(GFAP) and glial scar. Western blot was employed to determine the protein levels of GFAP, neurocan, phosphacan, CD206, arginase-1(Arg-1), interleukin(IL)-1ß, IL-6, and IL-4. Compared with the sham, model 7 d and model 14 d groups showed cerebral infarction of different degrees, severe pathological injury of cerebral cortex and hippocampus, neurological impairment, reduced spatial learning and memory, cognitive dysfunction, severe anxiety, astrocyte hyperplasia, thickening penumbra glial scar, and up-regulated protein levels of IL-1ß, IL-6, GFAP, neurocan, phosphacan, CD206, and Arg-1(P<0.01). Compared with the model group, NTF 7 d and NTF 14 d groups improved spatial learning, memory, and cognitive function, reduced anxiety, improved nerve function, reduced cerebral infarction volume, reduced astrocyte hyperplasia, thinned penumbra glial scar, down-regulated the protein levels of GFAP, neurocan, phosphacan, IL-6, and IL-1ß, and up-regulated the protein levels of IL-4, CD206, and Arg-1(P<0.05 or P<0.01). NTF exerts a neuroprotective effect on CIRI by inducing the M2 polarization of microglia, inhibiting inflammatory response, and reducing the formation of glial scar.

Clinical study on the prediction of ALN metastasis based on intratumoral and peritumoral DCE-MRI radiomics and clinico-radiological characteristics in breast cancer.

Objective: To investigate the value of predicting axillary lymph node (ALN) metastasis based on intratumoral and peritumoral dynamic contrast-enhanced MRI (DCE-MRI) radiomics and clinico-radiological characteristics in breast cancer. Methods: A total of 473 breast cancer patients who underwent preoperative DCE-MRI from Jan 2017 to Dec 2020 were enrolled. These patients were randomly divided into training (n=378) and testing sets (n=95) at 8:2 ratio. Intratumoral regions (ITRs) of interest were manually delineated, and peritumoral regions of 3 mm (3 mmPTRs) were automatically obtained by morphologically dilating the ITR. Radiomics features were extracted, and ALN metastasis-related radiomics features were selected by the Mann-Whitney U test, Z score normalization, variance thresholding, K-best algorithm and least absolute shrinkage and selection operator (LASSO) algorithm. Clinico-radiological risk factors were selected by logistic regression and were also used to construct predictive models combined with radiomics features. Then, 5 models were constructed, including ITR, 3 mmPTR, ITR+3 mmPTR, clinico-radiological and combined (ITR+3 mmPTR+ clinico-radiological) models. The performance of models was assessed by sensitivity, specificity, accuracy, F1 score and area under the curve (AUC) of receiver operating characteristic (ROC), calibration curves and decision curve analysis (DCA). Results: A total of 2264 radiomics features were extracted from each region of interest (ROI), 3 and 10 radiomics features were selected for the ITR and 3 mmPTR, respectively. 5 clinico-radiological risk factors were selected, including lesion size, human epidermal growth factor receptor 2 (HER2) expression, vascular cancer thrombus status, MR-reported ALN status, and time-signal intensity curve (TIC) type. In the testing set, the combined model showed the highest AUC (0.839), specificity (74.2%), accuracy (75.8%) and F1 Score (69.3%) among the 5 models. DCA showed that it had the greatest net clinical benefit compared to the other models. Conclusion: The intra- and peritumoral radiomics models based on DCE-MRI could be used to predict ALN metastasis in breast cancer, especially for the combined model with clinico-radiological characteristics showing promising clinical application value.

A real-time augmented reality system integrated with artificial intelligence for skin tumor surgery: experimental study and case series.

BACKGROUND: Skin tumors affect many people worldwide, and surgery is the first treatment choice. Achieving precise preoperative planning and navigation of intraoperative sampling remains a problem and is excessively reliant on the experience of surgeons, especially for Mohs surgery for malignant tumors. MATERIALS AND METHODS: To achieve precise preoperative planning and navigation of intraoperative sampling, we developed a real-time augmented reality (AR) surgical system integrated with artificial intelligence (AI) to enhance three functions: AI-assisted tumor boundary segmentation, surgical margin design, and navigation in intraoperative tissue sampling. Non-randomized controlled trials were conducted on manikin, tumor-simulated rabbits, and human volunteers in Hunan Engineering Research Center of Skin Health and Disease Laboratory to evaluate the surgical system. RESULTS: The results showed that the accuracy of the benign and malignant tumor segmentation was 0.9556 and 0.9548, respectively, and the average AR navigation mapping error was 0.644 mm. The proposed surgical system was applied in 106 skin tumor surgeries, including intraoperative navigation of sampling in 16 Mohs surgery cases. Surgeons who have used this system highly recognize it. CONCLUSIONS: The surgical system highlighted the potential to achieve accurate treatment of skin tumors and to fill the gap in global research on skin tumor surgery systems.

EGFR Oncogenic Mutations in NSCLC Impair Macrophage Phagocytosis and Mediate Innate Immune Evasion Through Up-Regulation of CD47.

INTRODUCTION: EGFR-mutated NSCLC is characterized by an immunosuppressive microenvironment that confers limited clinical effectiveness to anti-PD-1 or PD-L1 antibodies. Despite the discouraging outcomes of immunotherapy, novel immune checkpoints are constantly emerging, among which the specific vulnerability for therapeutic intervention in the context of EGFR-mutated NSCLC remains unresolved. METHODS: Data sets of patient- and cell line-levels were used for screening and mutual validation of association between EGFR mutation and a panel of immune checkpoint-related genes. Regulatory mechanism was elucidated through in vitro manipulation of EGFR signaling pathway and evaluated by immunoblot analysis, quantitative polymerase chain reaction, flow cytometry, immunofluorescence staining, and chromatin immunoprecipitation. In vivo investigation of different therapeutic strategies were conducted using both immunocompetent and immunodeficient mouse models. RESULTS: Among all screened immune checkpoints, CD47 emerged as the candidate most relevant to EGFR activation. Mechanistically, EGFR mutation constitutively activated downstream ERK and AKT pathways to respectively up-regulate the transcriptional factors c-Myc and NF-κB, both of which structurally bound to the promotor region of CD47 and actively transcribed this "don't eat me" signal. Impaired macrophage phagocytosis was observed on introduction of EGFR-sensitizing mutations in NSCLC cell line models, whereas CD47 blockade restored the phagocytic capacity and augmented tumor cell killing in both in vitro and in vivo models. Remarkably, the combination of anti-CD47 antibody with EGFR tyrosine kinase inhibitor revealed an additive antitumor activity compared with monotherapy of either antitumor agent in both immunocompetent and adaptive immunity-deficient mouse models. CONCLUSIONS: EGFR-sensitizing mutation facilitates NSCLC's escape from innate immune attack through up-regulating CD47. Combination therapy incorporating CD47 blockade holds substantial promise for clinical translation in developing more effective therapeutic approaches against EGFR-mutant NSCLC.

A sodium alginate gel bead adsorbent doping with amidoxime-modified hydroxyapatite for the efficient adsorption of uranium.

In this work, the modified­sodium alginate gel beads were prepared by sol-gel method. Due to the presence of water channels in the sodium alginate gel bead, amidoxime groups and PO43- were exposed to the surface of the adsorbent to the maximum extent, resulting in the excellent adsorption capacity of modified­sodium alginate gel beads. The introduction of amidoxime-modified hydroxyapatite significantly improved the adsorption capacity and the adsorption rate of the gel beads. The adsorption capacity increased from 308.7 to 466.0 mg/g and the adsorption equilibrium time was shortened from 300 min to 120 min. The modified­sodium alginate gel bead possessed the advantages of short adsorption time, high adsorption efficiency and large adsorption capacity, which could be regarded as a potential adsorbent for uranium. Moreover, the uranium removal ability on the modified gel beads was mainly attributed to the Coulomb force between PO43- and uranium and the complexation between uranium and amidoxime groups. In summary, this work would provide a new idea for the modification and application of sodium alginate-based materials.

Uncommon de novo EGFRT790M-Mutant NSCLC characterized with unique genetic Features: Clinical response and acquired resistance to the third-generation EGFR-TKIs treatment.

INTRODUCTION: The literature on de novo EGFRT790M-mutant patients diagnosed with lung cancer is limited, and there is currently no consensus concerning the most effective treatment protocols. This study aimed to investigate the genomic characteristics of de novoEGFRT790M-mutant non-small cell lung cancer (NSCLC) and provide insights into its clinical response and resistance mechanism to third-generation EGFR-TKIs. METHODS: Next-generation sequencing was utilized to screen a substantial cohort of 4,228 treatment-naïve patients from the Mygene genomic database to identifythe de novo EGFR-T790M mutation. Meanwhile, we recruited 83 individuals diagnosed with lung cancer who harbored de novo EGFRT790M mutation in the real world. In addition, 166 patients who acquired EGFR-T790M mutation after becoming resistant to first- or second-generation EGFR-TKIs were included as a comparison cohort. RESULTS: De novo EGFRT790M mutation identified by next-generation sequencing is rare (∼1.3 %) in Chinese lung cancer patients. The relative variant allele frequency (VAF) of de novo EGFRT790M mutation was either comparable to or significantly lower than those of EGFR-activating mutations. Patients with de novo-T790M mutations exhibited less favorable clinical outcomes when administered third-generation EGFR-TKIs as first-line therapy thanthose with 19del mutationsdue to a high overlap rate in EGFR p.L858R mutation. In patients with a de novo EGFRT790M mutation, no correlation was observed between T790M clonality and treatment outcomes with third-generation EGFR-TKIs. In contrast, the sub-clonality of the T790M mutation detrimentally affected the third-generation EGFR-TKI treatment efficacy in patients with acquired T790M mutation. Potential resistance mechanisms of third-generation EGFR TKIs in NSCLC patients with de novo or acquired EGFRT790M mutations included EGFR p.C797S in cis or EGFR p.E709X mutation, as well as activation of bypass pathways. CONCLUSIONS: The present study characterized the uncommon but unique de novo EGFRT790M-mutant NSCLC and laid a foundation for designing future clinical trials in the setting of uncommon EGFR mutation.

Calculation of solvation force in molecular dynamics simulation by deep-learning method.

Electrostatic calculations are generally used in studying the thermodynamics and kinetics of biomolecules in solvent. Generally, this is performed by solving the Poisson-Boltzmann equation on a large grid system, a process known to be time consuming. In this study, we developed a deep neural network to predict the decomposed solvation free energies and forces of all atoms in a molecule. To train the network, the internal coordinates of the molecule were used as the input data, and the solvation free energies along with transformed atomic forces from the Poisson-Boltzmann equation were used as labels. Both the training and prediction tasks were accelerated on GPU. Formal tests demonstrated that our method can provide reasonable predictions for small molecules when the network is well-trained with its simulation data. This method is suitable for processing lots of snapshots of molecules in a long trajectory. Moreover, we applied this method in the molecular dynamics simulation with enhanced sampling. The calculated free energy landscape closely resembled that obtained from explicit solvent simulations.

Analysis of drug-induced interstitial lung disease caused by herbal medicine using the Japanese Adverse Drug Event Report database.

BACKGROUND: Drug-induced interstitial lung disease (DIILD) is a severe adverse event leading to morbidity and mortality. This study evaluated the adverse event indicators of DIILD and time-to-onset profiles following the daily intake of herbal drugs (Scutellariae radix ["ogon" in Japanese], Bupleuri radix ["saiko" in Japanese], and Pinelliae tuber ["hange" in Japanese]) using the Japanese Adverse Drug Event Report database. DIILD was defined in accordance with the Medical Dictionary for Regulatory Activities. METHODS: The Japanese Adverse Drug Event Report database contained 830,079 reports published between April 2004 and April 2023. The association between herbal medicines and DILLD was evaluated using the pharmacovigilance index as the reporting odds ratio (ROR), logistic regression models, propensity score-matching techniques, and Weibull shape parameters. RESULTS: The adjusted RORs using multivariate logistic regression models for Scutellariae radix (daily intake), Pinelliae tuber (daily intake), sex (male), age (≥ 60 years), Scutellariae radix (daily intake)*age (≥ 60 years), and Scutellariae radix (daily intake)* Pinelliae tuber (daily intake) were 1.47 (1.36 - 1.59), 1.05 (1.01 - 1.10), 1.45 (1.34 - 1.57), 1.92 (1.74 - 2.11), 3.35 (3.12 - 3.60), and 1.49 (1.46 - 1.53), respectively. DIILD onset profiles were evaluated using the Weibull shape parameter. A logistic plot of daily intake and onset of DIILD was drawn. ROR signals were detected in 32 of 54 herbal medicines, including Scutellariae radix, Bupleuri radix, and Pinelliae tuber. The median duration (days) (interquartile range) to DIILD onset was 36.0 (27.0-63.0) for Saikokaryukotsuboreito, 35.0 (21.0-55.0) for Saireito, and 31.0 (13.5-67.5) for Shosaikoto. The Weibull shape parameter beta (95% confidence interval) values for Saikokaryukotsuboreito, Saireito, and Shosaikoto were 1.36 (1.08-1.67), 1.36 (1.20-1.52), and 1.31 (0.98-1.68), respectively. CONCLUSIONS: DIILD demonstrated a dose-dependent to crude drugs. Clinicians should strive for the early detection of DIILD and avoid the inadvertent administration of herbal medicines.