Analysis on the pathogenesis and treatment progress of NRG1 fusion-positive non-small cell lung cancer.

Lung cancer persistently leads as the primary cause of morbidity and mortality among malignancies. A notable increase in the prevalence of lung adenocarcinoma has become evident in recent years. Although targeted therapies have shown in treating certain subsets of non-small cell lung cancers (NSCLC), a significant proportion of patients still face suboptimal therapeutic outcomes. Neuregulin-1 (NRG1), a critical member of the NRG gene family, initially drew interest due to its distribution within the nascent ventricular endocardium, showcasing an exclusive presence in the endocardium and myocardial microvessels. Recent research has highlighted NRG1's pivotal role in the genesis and progression across a spectrum of tumors, influencing molecular perturbations across various tumor-associated signaling pathways. This review provides a concise overview of NRG1, including its expression patterns, configuration, and fusion partners. Additionally, we explore the unique features and potential therapeutic strategies for NRG1 fusion-positive occurrences within the context of NSCLC.

Mitigation of gestational diabetes-induced endothelial dysfunction through FGF21-NRF2 pathway activation involving L-Cystine.

Gestational diabetes mellitus (GDM) disrupts glucolipid metabolism, endangering maternal and fetal health. Despite limited research on its pathogenesis and treatments, we conducted a study using serum samples from GDM-diagnosed pregnant women. We performed metabolic sequencing to identify key small molecule metabolites and explored their molecular interactions with FGF21. We also investigated FGF21's impact on GDM using blood samples from affected women. Our analysis revealed a novel finding: elevated levels of L-Cystine in GDM patients. Furthermore, we observed a positive correlation between L-Cystine and FGF21 levels, and found that L-Cystine induces NRF2 expression via FGF21 for a period of 96 h. Under high glucose (HG) conditions, FGF21 upregulates NRF2 and downstream genes NQO1 and EPHX1 via AKT phosphorylation induced by activation of IRS1, enhancing endothelial function. Additionally, we confirmed that levels of FGF21, L-Cystine, and endothelial function at the third trimester were effectively enhanced through appropriate exercise and diet during pregnancy in GDM patients (GDM + ED). These findings suggest FGF21 as a potential therapeutic agent for GDM, particularly in protecting endothelial cells. Moreover, elevated L-Cystine via appropriate exercise and diet might be a potential strategy to enhance FGF21's efficacy.

Choroid plexus volume as a novel candidate neuroimaging marker of the Alzheimer's continuum.

BACKGROUND: Enlarged choroid plexus (ChP) volume has been reported in patients with Alzheimer's disease (AD) and inversely correlated with cognitive performance. However, its clinical diagnostic and predictive value, and mechanisms by which ChP impacts the AD continuum remain unclear. METHODS: This prospective cohort study enrolled 607 participants [healthy control (HC): 110, mild cognitive impairment (MCI): 269, AD dementia: 228] from the Chinese Imaging, Biomarkers, and Lifestyle study between January 1, 2021, and December 31, 2022. Of the 497 patients on the AD continuum, 138 underwent lumbar puncture for cerebrospinal fluid (CSF) hallmark testing. The relationships between ChP volume and CSF pathological hallmarks (Aß42, Aß40, Aß42/40, tTau, and pTau181), neuropsychological tests [Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Neuropsychiatric Inventory (NPI), and Activities of Daily Living (ADL) scores], and multimodal neuroimaging measures [gray matter volume, cortical thickness, and corrected cerebral blood flow (cCBF)] were analyzed using partial Spearman's correlation. The mediating effects of four neuroimaging measures [ChP volume, hippocampal volume, lateral ventricular volume (LVV), and entorhinal cortical thickness (ECT)] on the relationship between CSF hallmarks and neuropsychological tests were examined. The ability of the four neuroimaging measures to identify cerebral Aß42 changes or differentiate among patients with AD dementia, MCI and HCs was determined using receiver operating characteristic analysis, and their associations with neuropsychological test scores at baseline were evaluated by linear regression. Longitudinal associations between the rate of change in the four neuroimaging measures and neuropsychological tests scores were evaluated on the AD continuum using generalized linear mixed-effects models. RESULTS: The participants' mean age was 65.99 ± 8.79 years. Patients with AD dementia exhibited the largest baseline ChP volume than the other groups (P < 0.05). ChP volume enlargement correlated with decreased Aß42 and Aß40 levels; lower MMSE and MoCA and higher NPI and ADL scores; and lower volume, cortical thickness, and cCBF in other cognition-related regions (all P < 0.05). ChP volume mediated the association of Aß42 and Aß40 levels with MMSE scores (19.08% and 36.57%), and Aß42 levels mediated the association of ChP volume and MMSE or MoCA scores (39.49% and 34.36%). ChP volume alone better identified cerebral Aß42 changes than LVV alone (AUC = 0.81 vs. 0.67, P = 0.04) and EC thickness alone (AUC = 0.81 vs.0.63, P = 0.01) and better differentiated patients with MCI from HCs than hippocampal volume alone (AUC = 0.85 vs. 0.81, P = 0.01), and LVV alone (AUC = 0.85 vs.0.82, P = 0.03). Combined ChP and hippocampal volumes significantly increased the ability to differentiate cerebral Aß42 changes and patients among AD dementia, MCI, and HCs groups compared with hippocampal volume alone (all P < 0.05). After correcting for age, sex, years of education, APOE ε4 status, eTIV, and hippocampal volume, ChP volume was associated with MMSE, MoCA, NPI, and ADL score at baseline, and rapid ChP volume enlargement was associated with faster deterioration in NPI scores with an average follow-up of 10.03 ± 4.45 months (all P < 0.05). CONCLUSIONS: ChP volume may be a novel neuroimaging marker associated with neurodegenerative changes and clinical AD manifestations. It could better detect the early stages of the AD and predict prognosis, and significantly enhance the differential diagnostic ability of hippocampus on the AD continuum.

Clinical applications of telemedicine services using a regional telemedicine platform for cancer treatment: a cross-sectional study.

BACKGROUND: Telemedicine is beneficial for improving treatment efficiency and reducing medical expenses of cancer patients. This study focuses on cancer patients participating in teleconsultations through a regional telemedicine platform in China, analyzes the consultation process, and provides references for the clinical application of telemedicine. METHODS: We collected information on teleconsultations of cancer patients conducted from 2015 to 2022 through the regional telemedicine platform. Utilizing SPSS 23.0 software, we conducted descriptive analysis to summarize the distribution of patient gender, age, region, and disease types. The ordinal logistic regression analysis was adopted to analyze the factors influencing the waiting time and consultation duration for teleconsultations. RESULTS: From 2015 to 2022, a total of 23,060 teleconsultations were conducted for cancer patients via regional telemedicine platform, with an average growth rate of 11.09%. The main types of consultations were for lung cancer, liver cancer, and breast cancer, accounting for 18.14%, 10.49%, and 9.46% respectively. 57.05% of teleconsultations had a waiting time of less than 24 h, while patient age, consultation expert level, and disease type were the main factors influencing the waiting time. 50.06% of teleconsultations had a duration of more than 20 min, and the inviting hospital level and the title of invited consultant were the main factors influencing the consultation duration. CONCLUSIONS: In China, telemedicine has been widely employed in the clinical diagnosis and treatment of cancers, covering various types of oncological diseases. However, the waiting time for teleconsultations was generally more than 12 h, indicating the need to enhance consultation scheduling and allocate more expert resources to further optimize the efficiency of teleconsultations. Additionally, further exploration is required for remote health management of outpatients with cancers outside the hospital.

Spatiotemporal Regulation of Cell Fate in Living Systems Using Photoactivatable Artificial DNA Membraneless Organelles.

Coacervates formed by liquid-liquid phase separation emerge as important biomimetic models for studying the dynamic behaviors of membraneless organelles and synchronously motivating the creation of smart architectures with the regulation of cell fate. Despite continuous progress, it remains challenging to balance the trade-offs among structural stability, versatility, and molecular communication for regulation of cell fate and systemic investigation in a complex physiological system. Herein, we present a self-stabilizing and fastener-bound gain-of-function methodology to create a new type of synthetic DNA membraneless organelle (MO) with high stability and controlled bioactivity on the basis of DNA coacervates. Specifically, long single-strand DNA generated by rolling circle amplification (RCA) is selected as the scaffold that assembles into membraneless coacervates via phase separation. Intriguingly, the as-formed DNA MO can recruit RCA byproducts and other components to achieve self-stabilization, nanoscale condensation, and function encoding. As a proof of concept, photoactivatable DNA MO is constructed and successfully employed for time-dependent accumulation and spatiotemporal management of cancer in a mouse model. This study offers new, important insights into synthetic membraneless organelles for the basic understanding and manipulation of important life processes.

Charge adaptive phytochemical-based nanoparticles for eradication of methicillin-resistant staphylococcus aureus biofilms.

The intrinsic resistance of MRSA coupled with biofilm antibiotic tolerance challenges the antibiotic treatment of MRSA biofilm infections. Phytochemical-based nanoplatform is a promising emerging approach for treatment of biofilm infection. However, their therapeutic efficacy was restricted by the low drug loading capacity and lack of selectivity. Herein, we constructed a surface charge adaptive phytochemical-based nanoparticle with high isoliquiritigenin (ISL) loading content for effective treatment of MRSA biofilm. A dimeric ISL prodrug (ISL-G2) bearing a lipase responsive ester bond was synthesized, and then encapsulated into the amphiphilic quaternized oligochitosan. The obtained ISL-G2 loaded NPs possessed positively charged surface, which allowed cis-aconityl-d-tyrosine (CA-Tyr) binding via electrostatic interaction to obtain ISL-G2@TMDCOS-Tyr NPs. The NPs maintained their negatively charged surface, thus prolonging the blood circulation time. In response to low pH in the biofilms, the fast removal of CA-Tyr led to a shift in their surface charge from negative to positive, which enhanced the accumulation and penetration of NPs in the biofilms. Sequentially, the pH-triggered release of d-tyrosine dispersed the biofilm and lipase-triggered released of ISL effectively kill biofilm MRSA. An in vivo study was performed on a MRSA biofilm infected wound model. This phytochemical-based system led to ∼2 log CFU (>99 %) reduction of biofilm MRSA as compared to untreated wound (P < 0.001) with negligible biotoxicity in mice. This phytochemical dimer nanoplatform shows great potential for long-term treatment of resistant bacterial infections.

LACC1 deficiency leading to juvenile arthritis and anemia.

OBJECTIVE: Juvenile arthritis caused by loss-of-function LACC1 mutations is characterized by early onset of symmetric and chronic arthritis, associated with an elevation of inflammatory markers. We aimed to describe serum cytokine levels, explore the type I interferon pathway, and evaluate the efficacy of treatment in a patient presenting with polyarthritis and anemia caused by novel compound heterozygous variations in LACC1. METHODS: Clinical data of a patient with compound heterozygous variations in LACC1 was collected. Serum cytokine levels and IFN-stimulated cytokine genes were analyzed at diagnosis, at disease flare, and after treatment. Full-length cDNA of LACC1 was checked by RNA analysis. Single-cell RNA sequencing was performed in PBMCs. RESULTS: Two novel variants in the LACC1 gene were identified in a patient presenting with polyarthritis and anemia. LACC1-cDNA was normally expressed in the healthy control, the target production at 1384 bp was not observed in the patient. Compared to nine patient controls with non-systemic juvenile idiopathic arthritis, serum interleukin(IL)-6 level was significantly elevated in the affected patient. The median IFN score for the patient, her mother, and controls were 118, 8, and 4.9, respectively. The combined treatment of JAK inhibitors with prednisone or tocilizumab led to a complete response, including remission of joint symptoms, resolution of anemia, reduced expression of IFN-stimulated cytokine genes, and normalized levels of inflammatory markers, including CRP, ESR, SAA, and serum IL-6. CONCLUSION: LACC1 may play a crucial role in multiple inflammatory signaling pathways. The combination therapy of JAK inhibitors and tocilizumab may be effective for a subset of refractory patients.

Polyelectrolyte complex formation of alginate and chito oligosaccharide is influenced by their proportion and alginate molecular weight.

Sodium alginate (SA) and chito oligosaccharide (COS) are widely used food additives in the food industry, and exploring their interaction to form polyelectrolyte complexes (PECs) may provide insights into food development. In the present study, the effects of viscosity-average molecular weight (Mv) and relative amounts of SA on the formation of sodium alginate/chito oligosaccharide polyelectrolyte (SCP) complexes were investigated. The results showed that the electrostatic interaction between -COOH and -NH2 and the hydrogen bonding between OH, were attributed to the formation of the SCP complexes. Then the formation and properties of SCP complexes were greatly dependent on the Mv and the relative amount of SA. SA with Mv of ≥2.16 × 106 Da could form spherical SCP complexes, while the SA/COS ratio (w/w) ≥ 0.8 was not conducive to the formation of SCP complexes. Moreover, the SCP complexes were more stable in the gastric environment than in the intestinal condition. In addition, 1.73 × 107 Da was the optimal Mv of SA for SCP complexes formation. This study contributed to a comprehensive understanding of the interaction between SA and COS, and shed light on the potential application of SA and COS formulation to develop new food products.

Growth hormone releasing peptide-6 (GHRP-6) prevents doxorubicin-induced myocardial and extra-myocardial damages by activating prosurvival mechanisms.

Introduction: Dilated cardiomyopathy (DCM) is a fatal myocardial condition with ventricular structural changes and functional deficits, leading to systolic dysfunction and heart failure (HF). DCM is a frequent complication in oncologic patients receiving Doxorubicin (Dox). Dox is a highly cardiotoxic drug, whereas its damaging spectrum affects most of the organs by multiple pathogenic cascades. Experimentally reproduced DCM/HF through Dox administrations has shed light on the pathogenic drivers of cardiotoxicity. Growth hormone (GH) releasing peptide 6 (GHRP-6) is a GH secretagogue with expanding and promising cardioprotective pharmacological properties. Here we examined whether GHRP-6 administration concomitant to Dox prevented the onset of DCM/HF and multiple organs damages in otherwise healthy rats. Methods: Myocardial changes were sequentially evaluated by transthoracic echocardiography. Autopsy was conducted at the end of the administration period when ventricular dilation was established. Semiquantitative histopathologic study included heart and other internal organs samples. Myocardial tissue fragments were also addressed for electron microscopy study, and characterization of the transcriptional expression ratio between Bcl-2 and Bax. Serum samples were destined for REDOX system balance assessment. Results and discussion: GHRP-6 administration in parallel to Dox prevented myocardial fibers consumption and ventricular dilation, accounting for an effective preservation of the LV systolic function. GHRP-6 also attenuated extracardiac toxicity preserving epithelial organs integrity, inhibiting interstitial fibrosis, and ultimately reducing morbidity and mortality. Mechanistically, GHRP-6 proved to sustain cellular antioxidant defense, upregulate prosurvival gene Bcl-2, and preserve cardiomyocyte mitochondrial integrity. These evidences contribute to pave potential avenues for the clinical use of GHRP-6 in Dox-treated subjects.

The casein in sheep milk processed by cold plasma technology: Phosphorylation degree, functional properties, oxidation characteristics, and structure.

Cold plasma is a nonthermal process used for modification of proteins. The objective of this study was to investigate the effect of cold plasma technology on the phosphorylation degree, functional and oxidation properties, and structure of casein in sheep milk. Cold plasma treatment for 3-4 min significantly increased the phosphorylation degree and enhanced functional properties, including water-holding capacity, solubility, foaming capacity and stability. Besides, plasma treatment time profoundly influenced protein oxidation, and treatment for 2 and 3 min could be the preferred conditions to minimize protein change. The protein conformation became unstable with the extension of treatment time. Particle size, polymer dispersity index, and microscopy images confirmed alterations in the protein structure following 3 min of processing. Consequently, using cold plasma treatment at 10 kHz 20 kV for 3 min could be suggested for milk protein modification, providing a basis for the application of high-quality caseins in food processing.

Repairing Exposed Tendon Wounds with Absorbable Gelatin Sponges and Autologous Split-Thickness Skin Grafts: A Case Series.

ABSTRACT: Conventional flap repair surgery has several drawbacks, including operational complexity, donor site damage, and high risk. In this case series, the authors explored an alternative approach for repairing exposed tendon wounds caused by trauma using absorbable gelatin sponges (AGSs) and autologous thigh skin grafts. This report presents two cases of lower-extremity skin necrosis with tendon exposure following wound debridement. The treatment approach involved early debridement, negative-pressure wound therapy, and wound irrigation with 0.9% sodium chloride. Upon achieving controlled wound infection, AGSs were applied to the exposed tendon to prevent degeneration and promote wound healing. Subsequently, areas where granulation tissue failed to cover the tendon were repaired using AGSs and 0.25-mm-thick autologous mesh skin grafts harvested from the thigh. Complete wound healing was achieved in both cases, on the 20th and 12th day after skin grafting, respectively. The proposed method proved successful in repairing exposed tendon wounds, effectively preventing infection and necrosis.

Multi-view attribute learning and context relationship encoding enhanced segmentation of lung tumors from CT images.

Graph convolutional neural networks (GCN) have shown the promise in medical image segmentation due to the flexibility of representing diverse range of image regions using graph nodes and propagating knowledge via graph edges. However, existing methods did not fully exploit the various attributes of image nodes and the context relationship among their attributes. We propose a new segmentation method with multi-similarity view enhancement and node attribute context learning (MNSeg). First, multiple views were formed by measuring the similarities among the image nodes, and MNSeg has a GCN based multi-view image node attribute learning (MAL) module to integrate various node attributes learnt from multiple similarity views. Each similarity view contains the specific similarities among all the image nodes, and it was integrated with the node attributes from all the channels to form the enhanced attributes of image nodes. Second, the context relationships among the attributes of image nodes are formulated by a transformer-based context relationship encoding (CRE) strategy to propagate these relationships across all the image nodes. During the transformer-based learning, the relationships were estimated based on the self-attention on all the image nodes, and then they were encoded into the learned node features. Finally, we design an attention at attribute category level (ACA) to discriminate and fuse the learnt diverse information from MAL, CRE, and the original node attributes. ACA identifies the more informative attribute categories by adaptively learn their importance. We validate the performance of MNSeg on a public lung tumor CT dataset and an in-house non-small cell lung cancer (NSCLC) dataset collected from the hospital. The segmentation results show that MNSeg outperformed the compared segmentation methods in terms of spatial overlap and the shape similarities. The ablation studies demonstrated the effectiveness of MAL, CRE, and ACA. The generalization ability of MNSeg was proved by the consistent improved segmentation performances using different 3D segmentation backbones.

Rainbow connections of bioriented graphs.

For a directed graph D, it's deemed rainbow connected if each arc is assigned a different color, so that all paths from the vertex u to the vertex v are rainbow connected. Rainbow connection number refers to how many colors are needed in D to achieve rainbow connectivity. Among ordered vertex pair (u,v) with arc coloring, if both arcs and internal vertices exhibit unique colors, it is referred to as a total colored graph. As the total rainbow connection number indicates, the smallest number of colors are required to total-color D. This paper focuses on investigating the rainbow connection number of the biorientation of a connected graph, as well as the total rainbow connection number.

Ecological restoration for eutrophication mitigation in urban interconnected water bodies: Evaluation, variability and strategy.

Many urban water bodies grapple with low flow flux and weak hydrodynamics. To address these issues, projects have been implemented to form integrated urban water bodies via interconnecting artificial lake or ponds with rivers, but causing pollution accumulation downstream and eutrophication. Despite it is crucial to assess eutrophication, research on this topic in urban interconnected water bodies is limited, particularly regarding variability and feasible strategies for remediation. This study focused on the Loucun river in Shenzhen, comprising an pond, river and artificial lake, evaluating water quality changes pre-(post-)ecological remediation and establishing a new method for evaluating the water quality index (WQI). The underwater forest project, involving basement improvement, vegetation restoration, and aquatic augmentation, in the artificial lake significantly reduced total nitrogen (by 43.58%), total phosphorus (by 79.17%) and algae density (by 36.90%) compared to pre-remediation, effectively controlling algal bloom. Rainfall, acting as a variable factor, exacerbated downstream nutrient accumulation, increasing total phosphorus by 4.56 times and ammonia nitrogen by 1.30 times compared to the dry season, and leading to algal blooms in the non-restoration pond. The improved WQI method effectively assesses water quality status. The interconnected water body exhibits obvious nutrient accumulation in downstream regions. A combined strategy that reducing nutrient and augmenting flux was verified to alleviate accumulation of nutrients downstream. This study provides valuable insights into pollution management strategies for interconnected pond-river-lake water bodies, offering significant reference for nutrient mitigation in such urban water bodies.

The causal relationship between 5 serum lipid parameters and diabetic nephropathy: a Mendelian randomization study.

Background: Serum lipids were found to be correlated with chronic kidney disease and cardiovascular disease. Here, we aimed to research the potential causal associations between five serum lipid parameters and the risk of diabetic nephropathy using several Mendelian Randomization methods. Methods: Genetic data was obtained from the UK Biobank datasets. Causal effects were estimated using multiple MR methods. Heterogeneity and pleiotropy tests were performed. Results: MR analysis revealed that HDL-C and TG exhibited causal associations with diabetic nephropathy (P<0.05). Similar trends were not observed for other lipid parameters. Conclusions: Our research has suggested links between HDL-C, TG and diabetic nephropathy. The findings could contribute to further elucidation of the disease etiology. Strengths and limitations of this study: This article only uses Mendel randomization method to analyze the relationship between blood lipids and diabetes nephropathy, which is more convincing when combined with population data.

Incidence and risk factors of post-operative delirium in glioma patients: A prospective cohort study in general wards.

AIMS: Glioma patients are at high risk for postoperative delirium (POD), yet studies focusing on this population in general neurosurgical ward settings are limited. This paper investigates the incidence of POD and related risk factors in glioma patients hospitalized in general wards. DESIGN: Prospective observational study. METHODS: This prospective study included 133 adult glioma patients hospitalized in the general neurosurgery ward. In addition to collecting routine perioperative general clinical data, patients' psychological status was assessed preoperatively using the Hospital Anxiety and Depression Scale (HADS). POD was assessed within 3 days postoperatively using the Confusion of Consciousness Assessment method, twice daily. The incidence of POD was calculated, and risk factors were identified using logistic regression analysis. RESULTS: The incidence of POD in glioma patients admitted to the general ward was 31.6% (40/133). Multivariate regression revealed advanced age (age > 50 years), frontal lobe tumour, presence of preoperative anxiety or depression, retention of a luminal drain, postoperative pain, indwelling catheter these six factors were independent risk factors for the development of delirium in patients after surgery. CONCLUSION: In general ward settings, supratentorial glioma patients exhibit a high risk of POD. Critical risk factors include preoperative psychological conditions, as well as postoperative pain, drainage and catheterization. Rigorous preoperative evaluations, effective pain management strategies and the integration of humanistic care principles are essential in mitigating the risk of POD for glioma patients. RELEVANCE TO CLINICAL PRACTICE: In general ward settings, this study reveals the high occurrence of POD in glioma patients and identifies preoperative psychological states, age, tumour location and several postoperative factors as significant risk factors for POD, which provides a framework for targeted interventions. By integrating these insights into clinical practice, healthcare teams can better identify glioma patients at risk for POD and implement preventive measures, thereby enhancing recovery and overall care quality for glioma patients in general neurosurgical wards. REPORTING METHOD: This study adheres to the STROBE guidelines, ensuring a transparent and comprehensive reporting of the observational research methodology and results. PATIENT OR PUBLIC CONTRIBUTION: Patients involvement was limited to the provision of data through their participation in the study's assessments and the collection of clinical information. The study did not involve a direct patient or public contribution in the design, conduct, analysis, or interpretation of the data, nor in the preparation of the manuscript.

Studies on invariant measures of fractional stochastic delay Ginzburg-Landau equations on Rn.

This paper is concerned with invariant measures of fractional stochastic delay Ginzburg-Landau equations on the entire space $ \mathbb{R}^n $. We first derive the uniform estimates and the mean-square uniform smallness of the tails of solutions in corresponding space. Then we deduce the weak compactness of a set of probability distributions of the solutions applying the Ascoli-Arzel$ \grave{a} $. We finally prove the existence of invariant measures by applying Krylov-Bogolyubov's method.

Nuclease-assisted selection of slow-off rate aptamers.

Conventional directed evolution methods offer the ability to select bioreceptors with high binding affinity for a specific target in terms of thermodynamic properties. However, there is a lack of analogous approaches for kinetic selection, which could yield affinity reagents that exhibit slow off-rates and thus remain tightly bound to targets for extended periods. Here, we describe an in vitro directed evolution methodology that uses the nuclease flap endonuclease 1 to achieve the efficient discovery of aptamers that have slow dissociation rates. Our nuclease-assisted selection strategy can yield specific aptamers for both small molecules and proteins with off-rates that are an order of magnitude slower relative to those obtained with conventional selection methods while still retaining excellent overall target affinity in terms of thermodynamics. This new methodology provides a generalizable approach for generating slow off-rate aptamers for diverse targets, which could, in turn, prove valuable for applications including molecular devices, bioimaging, and therapy.

Development and Validation of Nomograms for Predicting Pneumonia in Patients with COVID-19 and Lung Cancer.

Background: COVID-19 has spread worldwide, becoming a global threat to public health and can lead to complications, especially pneumonia, which can be life-threatening. However, in lung cancer patients, the prediction of pneumonia and severe pneumonia has not been studied. We aimed to develop effective models to assess pneumonia after SARS-CoV-2 infection in lung cancer patients to guide COVID-19 management. Methods: We retrospectively recruited 621 lung cancer patients diagnosed with COVID-19 via SARS-CoV-2 RT-PCR analysis in two medical centers and divided into training and validation group, respectively. Univariate and multivariate logistic regression analysis were used to identify independent risk factors of all-grade pneumonia and ≥ grade 2 pneumonia in the training group. Nomograms were established based on independent predictors and verified in the validation group. C-index, ROC curves, calibration curve, and DCA were used to evaluate the nomograms. Subgroup analyses in immunotherapy or thoracic radiotherapy patients were then conducted. Results: Among 621 lung cancer patients infected with SARS-CoV-2, 203 (32.7%) developed pneumonia, and 66 (10.6%) were ≥ grade 2. Multivariate logistic regression analysis showed that diabetes, thoracic radiotherapy, low platelet and low albumin at diagnosis of COVID-19 were significantly associated with all-grade pneumonia. The C-indices of the prediction nomograms in the training group and validation group were 0.702 and 0.673, respectively. Independent predictors of ≥ grade 2 pneumonia were age, KPS, thoracic radiotherapy, platelet and albumin at COVID 19 diagnosis, with C-indices of 0.811 and 0.799 in the training and validation groups. In the thoracic radiotherapy subgroup, 40.8% and 11% patients developed all-grade and ≥grade 2 pneumonia, respectively. The rates in the immunotherapy subgroup were 31.3% and 6.6%, respectively. Conclusion: We developed nomograms predicting the probability of pneumonia in lung cancer patients infected with SARS-CoV-2. The models showed good performance and can be used in the clinical management of COVID-19 in lung cancer patients. Higher-risk patients should be managed with enhanced protective measures and appropriate intervention.

Comparing the accuracy of four machine learning models in predicting type 2 diabetes onset within the Chinese population: a retrospective study.

OBJECTIVE: To evaluate the effectiveness of machine learning (ML) models in predicting 5-year type 2 diabetes mellitus (T2DM) risk within the Chinese population by retrospectively analyzing annual health checkup records. METHODS: We included 46,247 patients (32,372 and 13,875 in training and validation sets, respectively) from a national health checkup center database. Univariate and multivariate Cox analyses were performed to identify factors influencing T2DM risk. Extreme Gradient Boosting (XGBoost), support vector machine (SVM), logistic regression (LR), and random forest (RF) models were trained to predict 5-year T2DM risk. Model performances were analyzed using receiver operating characteristic (ROC) curves for discrimination and calibration plots for prediction accuracy. RESULTS: Key variables included fasting plasma glucose, age, and sedentary time. The LR model showed good accuracy with respective areas under the ROC (AUCs) of 0.914 and 0.913 in training and validation sets; the RF model exhibited favorable AUCs of 0.998 and 0.838. In calibration analysis, the LR model displayed good fit for low-risk patients; the RF model exhibited satisfactory fit for low- and high-risk patients. CONCLUSIONS: LR and RF models can effectively predict T2DM risk in the Chinese population. These models may help identify high-risk patients and guide interventions to prevent complications and disabilities.