Mechanism Switch in Surface-Enhanced Raman Scattering: The Role of Nanoparticle Dimensions.

Surface-enhanced Raman scattering (SERS) is renowned for amplifying Raman signals, with electromagnetic mechanism (EM) enhancement arising from localized surface plasmon resonances and chemical mechanism (CM) enhancement as a result of charge transfer interactions. Despite the conventional emphasis on EM as a result of plasmonic effects, recent findings highlight the significance of CM when noble metals appear as smaller entities. However, the threshold size of the noble metal clusters/particles corresponding to the switch in SERS mechanisms is not clear at present. In this work, the VSe2-xOx/Au composites with different Au sizes are employed, in which a clear view of the SERS mechanism switch is observed at the Au size range of 16-21 nm. Our findings not only provide insight into the impact of noble metal size on SERS efficiency but also offer quantitative data to assist researchers in making informed judgments when analyzing SERS mechanisms.

VirRep: a hybrid language representation learning framework for identifying viruses from human gut metagenomes.

Identifying viruses from metagenomes is a common step to explore the virus composition in the human gut. Here, we introduce VirRep, a hybrid language representation learning framework, for identifying viruses from human gut metagenomes. VirRep combines a context-aware encoder and an evolution-aware encoder to improve sequence representation by incorporating k-mer patterns and sequence homologies. Benchmarking on both simulated and real datasets with varying viral proportions demonstrates that VirRep outperforms state-of-the-art methods. When applied to fecal metagenomes from a colorectal cancer cohort, VirRep identifies 39 high-quality viral species associated with the disease, many of which cannot be detected by existing methods.

Cross-sectional study of hepatitis B virus infection in female breast cancer patients in China for the first time diagnosed.

BACKGROUND: The correlation between breast cancer and hepatitis B virus (HBV) remains inconclusive. This study aims to explore the serological status of HBV infection and past infection in different age groups of female breast cancer patients, patients with benign breast diseases, and individuals undergoing routine physical examinations. METHODS: Serum data on HBV serological markers were collected and analyzed from 6072 female breast cancer patients first diagnosed from September 2012 to July 2020 at the First Affiliated Hospital of Chongqing Medical University, along with 4019 women with benign breast diseases and 54,740 healthy females undergoing routine physical examinations in the same period. The data were stratified by age for comparison between groups. RESULTS: The prevalence of HBV infection and past infection in the breast cancer group (7.9%, 55.1%) was higher than that in the benign breast disease group (6.5%, 39.1%) and the healthy females group(5.0%, 17.6%);the rate of only HBV surface antibody positivity (HBsAb ( +)) in the breast cancer group (10.3%) was lower than that in the benign breast disease group (26.9%) and the healthy females group (49.2%), with significant differences between the three groups (p < 0.05). Stratified by age, the prevalence of HBV infection in the breast cancer group (8%, 8.9%) and benign breast disease group (7.75%, 8.1%)was higher than that in the healthy females group (4.5%, 6.3%) in the 30-39 and 40-49 age group, respectively. The past infection rate of HBV in the breast cancer group (24.8%, 45.0%) was higher than that in the benign breast disease group (16.1%, 35.4%) in the ≤ 29 and 30-39 age group, respectively.. The past infection rate of HBV in the breast cancer group was higher than that in the healthy females group in all age groups, while the rate of only HBsAb ( +) in the breast cancer group was lower than that in the benign breast disease group and the routine physical examination group in all age groups. CONCLUSIONS: Breast cancer women and women with benign breast diseases have higher rates of hepatitis B virus infection and previous infections, with more significant differences among middle-aged women. Breast cancer women and women with benign breast diseases have lower rates of only HBsAb ( +) for HBV.

Population coding for figure-ground texture segregation in macaque V1 and V4.

Object recognition often involves the brain segregating objects from their surroundings. Neurophysiological studies of figure-ground texture segregation have yielded inconsistent results, particularly on whether V1 neurons can perform figure-ground texture segregation or just detect texture borders. To address this issue from a population perspective, we utilized two-photon calcium imaging to simultaneously record the responses of large samples of V1 and V4 neurons to figure-ground texture stimuli in awake, fixating macaques. The average response changes indicate that V1 neurons mainly detect texture borders, while V4 neurons are involved in figure-ground segregation. However, population analysis (SVM decoding of PCA-transformed neuronal responses) reveal that V1 neurons not only detect figure-ground borders, but also contribute to figure-ground texture segregation, although requiring substantially more principal components than V4 neurons to reach a 75 % decoding accuracy. Individually, V1/V4 neurons showing larger (negative/positive) figure-ground response differences contribute more to figure-ground segregation. But for V1 neurons, the contribution becomes significant only when many principal components are considered. We conclude that V1 neurons participate in figure-ground segregation primarily by defining the figure borders, and the poorly structured figure-ground information V1 neurons carry could be further utilized by V4 neurons to accomplish figure-ground segregation.

Plasmonic trimers designed as SERS-active chemical traps for subtyping of lung tumors.

Plasmonic materials can generate strong electromagnetic fields to boost the Raman scattering of surrounding molecules, known as surface-enhanced Raman scattering. However, these electromagnetic fields are heterogeneous, with only molecules located at the 'hotspots', which account for ≈ 1% of the surface area, experiencing efficient enhancement. Herein, we propose patterned plasmonic trimers, consisting of a pair of plasmonic dimers at the bilateral sides and a trap particle positioned in between, to address this challenge. The trimer configuration selectively directs probe molecules to the central traps where 'hotspots' are located through chemical affinity, ensuring a precise spatial overlap between the probes and the location of maximum field enhancement. We investigate the Raman enhancement of the Au@Al2O3-Au-Au@Al2O3 trimers, achieving a detection limit of 10-14 M of 4-methylbenzenethiol, 4-mercaptopyridine, and 4-aminothiophenol. Moreover, single-molecule SERS sensitivity is demonstrated by a bi-analyte method. Benefiting from this sensitivity, our approach is employed for the early detection of lung tumors using fresh tissues. Our findings suggest that this approach is sensitive to adenocarcinoma but not to squamous carcinoma or benign cases, offering insights into the differentiation between lung tumor subtypes.

Temporal relationship between hepatic steatosis and fasting blood glucose elevation: a longitudinal analysis from China and UK.

BACKGROUND: The link between nonalcoholic fatty liver disease and type 2 diabetes has not been fully established. We investigated the temporal relationship between nonalcoholic fatty liver disease (NAFLD) and type 2 diabetes (T2D), quantitatively assessed the impact, and evaluated the related mediation effect. METHODS: This study involved participants from the China Multi-Ethnic Cohort Study and the UK Biobank. We performed cross-lagged path analysis to compare the relative magnitude of the effects between NAFLD and T2D using two-period biochemical data. Hepatic steatosis and fasting blood glucose elevation (FBG) represented NAFLD and T2D respectively. We fitted two separate Cox proportional-hazards models to evaluate the influence of hepatic steatosis on T2D. Furthermore, we applied the difference method to assess mediation effects. RESULTS: In cross-lagged path analyses, the path coefficients from baseline hepatic steatosis to first repeat FBG (ßCMEC = 0.068, ßUK-Biobank = 0.033) were significantly greater than the path coefficients from baseline FBG to first repeat hepatic steatosis (ßCMEC = 0.027, ßUK-Biobank = -0.01). Individuals with hepatic steatosis have a risk of T2D that is roughly three times higher than those without the condition (HR = 3.478 [3.314, 3.650]). Hepatic steatosis mediated approximately 69.514% of the total effect between obesity and follow-up T2D. CONCLUSIONS: Our findings contribute to determining the sequential relationship between NAFLD and T2D in the causal pathway, highlighting that the dominant pathway in the relationship between these two early stages of diseases was the one from hepatic steatosis to fasting blood glucose elevation. Individuals having NAFLD face a significantly increased risk of T2D and require long-term monitoring of their glucose status as well.

In Situ Preparation of Metallic Copper Nanosheets/Carbon Paper Sensitive Electrodes for Low-Potential Electrochemical Detection of Nitrite.

In the realm of electrochemical nitrite detection, the potent oxidizing nature of nitrite typically necessitates operation at high detection potentials. However, this study introduces a novel approach to address this challenge by developing a highly sensitive electrochemical sensor with a low reduction detection potential. Specifically, a copper metal nanosheet/carbon paper sensitive electrode (Cu/CP) was fabricated using a one-step electrodeposition method, leveraging the catalytic reduction properties of copper's high occupancy d-orbital. The Cu/CP sensor exhibited remarkable performance in nitrite detection, featuring a low detection potential of -0.05 V vs. Hg/HgO, a wide linear range of 10~1000 µM, an impressive detection limit of 0.079 µM (S/N = 3), and a high sensitivity of 2140 µA mM-1cm-2. These findings underscore the efficacy of electrochemical nitrite detection through catalytic reduction as a means to reduce the operational voltage of the sensor. By showcasing the successful implementation of this strategy, this work sets a valuable precedent for the advancement of electrochemical low-potential nitrite detection methodologies.

[Deep transfer learning radiomics model based on temporal bone CT for assisting in the diagnosis of inner ear malformations].

Objective:To evaluate the diagnostic efficacy of traditional radiomics, deep learning, and deep learning radiomics in differentiating normal and inner ear malformations on temporal bone computed tomography（CT）. Methods:A total of 572 temporal bone CT data were retrospectively collected, including 201 cases of inner ear malformation and 371 cases of normal inner ear, and randomly divided into a training cohort（n=458） and a test cohort（n=114） in a ratio of 4∶1. Deep transfer learning features and radiomics features were extracted from the CT images and feature fusion was performed to establish the least absolute shrinkage and selection operator. The CT results interpretated by two chief otologists from the National Clinical Research Center for Otorhinolaryngological Diseases served as the gold standard for diagnosis. The model performance was evaluated using receiver operating characteristic（ROC）, and the accuracy, sensitivity, specificity, and other indicators of the models were calculated. The predictive power of each model was compared using the Delong test. Results:1 179 radiomics features were obtained from traditional radiomics, 2 048 deep learning features were obtained from deep learning, and 137 features fusion were obtained after feature screening and fusion of the two. The area under the curve（AUC） of the deep learning radiomics model on the test cohort was 0.964 0（95%CI 0.931 4-0.996 8）, with an accuracy of 0.922, sensitivity of 0.881, and specificity of 0.945. The AUC of the radiomics features alone on the test cohort was 0.929 0（95%CI 0.882 2-0.974 9）, with an accuracy of 0.878, sensitivity of 0.881, and specificity of 0.877. The AUC of the deep learning features alone on the test cohort was 0.947 0（95%CI 0.898 2-0.994 8）, with an accuracy of 0.913, sensitivity of 0.810, and specificity of 0.973. The results indicated that the prediction accuracy and AUC of the deep learning radiomics model are the highest. The Delong test showed that the differences between any two models did not reach statistical significance. Conclusion:The feature fusion model can be used for the differential diagnosis of normal and inner ear malformations, and its diagnostic performance is superior to radiomics or deep learning models alone.

High performance few-mode fiber-based light field direction sensing system using deep convolutional neural network: fiber speckle demodulation network (FSDNET).

Precisely sensing the light field direction information plays the essential role in the fields of three-dimensional (3D) imaging, light field sensing, target positioning and tracking, remote sensing, etc. It is thrilling to find that the optical fiber can be used as a sensing component due to its high sensitivity, compact size, and strong resistance to electromagnetic interference. According to the core principle that the few-mode fiber output speckle pattern is sensitive to the change of incident light field direction, the variation characteristics is further investigated in this research study. Based on the simulation and analysis of the fiber transmission characteristics, the output speckle corresponding to the incident light field with the direction in the range of ±6° horizontally and vertically are calculated. Furthermore, a deep convolutional neural network (CNN): fiber speckle demodulation network (FSDNET) is proposed and constructed to establish what we believe to be a novel way to reveal and identify the mapping relationship between the light field direction and the output speckle. The theoretical simulation shows that the mean absolute error (MAE) between the perceived light field directions and the true directions is 0.01°. Then, a light field direction sensing system based on the few-mode fiber is developed. Regarding to the performance of the sensing system, the MAE of the FSDNET for the light field directions that have appeared in the training set is 0.0389°, and for testing set of the unknown directions that have not appeared in the training set, the MAE is 0.0570°. Therefore, the simulation and experimental results prove that high performance sensing of light field direction can be achieved by the proposed few-mode fiber sensing system and the FSDNET.

Biological functions and biomedical applications of extracellular vesicles derived from blood cells.

There is a growing interest in using extracellular vesicles (EVs) for therapeutic applications. EVs are composed of cytoplasmic proteins and nucleic acids and an external lipid bilayer containing transmembrane proteins on their surfaces. EVs can alter the state of the target cells by interacting with the receptor ligand of the target cell or by being internalised by the target cell. Blood cells are the primary source of EVs, and 1 µL of plasma contains approximately 1.5 × 107 EVs. Owing to their easy acquisition and the avoidance of cell amplification in vitro, using blood cells as a source of therapeutic EVs has promising clinical application prospects. This review summarises the characteristics and biological functions of EVs derived from different blood cell types (platelets, erythrocytes, and leukocytes) and analyses the prospects and challenges of using them for clinical therapeutic applications. In summary, blood cell-derived EVs can regulate different cell types such as immune cells (macrophages, T cells, and dendritic cells), stem cells, and somatic cells, and play a role in intercellular communication, immune regulation, and cell proliferation. Overall, blood cell-derived EVs have the potential for use in vascular diseases, inflammatory diseases, degenerative diseases, and injuries. To promote the clinical translation of blood cell-derived EVs, researchers need to perform further studies on EVs in terms of scalable and reproducible isolation technology, quality control, safety, stability and storage, regulatory issues, cost-effectiveness, and long-term efficacy.

Injectable Oxygen-Carrying Microsphere Hydrogel for Dynamic Regulation of Redox Microenvironment of Wounds.

The delayed healing of infected wounds can be attributed to the increased production of reactive oxygen species (ROS) and consequent damages to vascellum and tissue, resulting in a hypoxic wound environment that further exacerbates inflammation. Current clinical treatments including hyperbaric oxygen therapy and antibiotic treatment fail to provide sustained oxygenation and drug-free resistance to infection. To propose a dynamic oxygen regulation strategy, this study develops a composite hydrogel with ROS-scavenging system and oxygen-releasing microspheres in the wound dressing. The hydrogel itself reduces cellular damage by removing ROS derived from immune cells. Simultaneously, the sustained release of oxygen from microspheres improves cell survival and migration in hypoxic environments, promoting angiogenesis and collagen regeneration. The combination of ROS scavenging and oxygenation enables the wound dressing to achieve drug-free anti-infection through activating immune modulation, inhibiting the secretion of pro-inflammatory cytokines interleukin-6, and promoting tissue regeneration in both acute and infected wounds of rat skins. Thus, the composite hydrogel dressing proposed in this work shows great potential for dynamic redox regulation of infected wounds and accelerates wound healing without drugs.

Epigenetic regulation of immune cells in systemic lupus erythematosus: insight from chromatin accessibility.

INTRODUCTION: Systemic Lupus Erythematosus (SLE) is a multi-dimensional autoimmune disease involving numerous tissues throughout the body. The chromatin accessibility landscapes in immune cells play a pivotal role in governing their activation, function, and differentiation. Aberrant modulation of chromatin accessibility in immune cells is intimately associated with the onset and progression of SLE. AREAS COVERED: In this review, we described the chromatin accessibility landscapes in immune cells, summarized the recent evidence of chromatin accessibility related to the pathogenesis of SLE, and discussed the potential of chromatin accessibility as a valuable option to identify novel therapeutic targets for this disease. EXPERT OPINION: Dynamic changes in chromatin accessibility are intimately related to the pathogenesis of SLE and have emerged as a new direction for exploring its epigenetic mechanisms. The differently accessible chromatin regions in immune cells often contain binding sites for transcription factors (TFs) and cis-regulatory elements such as enhancers and promoters, which may be potential therapeutic targets for SLE. Larger scale cohort studies and integrating epigenomic, transcriptomic, and metabolomic data can provide deeper insights into SLE chromatin biology in the future.

Recently, there has been a growing body of studies that explore the influence of epigenetic factors including DNA methylation, histone post-translational modifications, and non-coding RNA regulation on Systemic Lupus Erythematosus (SLE). Unusual regulation of these common epigenetic modifications would change the chromatin accessibility landscapes in SLE immune cells. Many studies have mapped the chromatin accessibility of various immune cells in SLE patients to uncover potential regulators like transcription factors (TFs) and cis-regulatory elements. Higher chromatin accessibility of immune cells in SLE patients compared to healthy individuals provides new avenues for diagnosing this disease. TFs identified in differentially accessible chromatin regions and their regulated genes might serve as novel targets for therapies, where the phenotypes affected by these genes, like inflammatory cytokine release and immune activation, are reliable bases for evaluating the prognosis of such targeted therapies.In this review, we described the chromatin accessibility landscape in immune cells, summarized the recent evidence of chromatin accessibility related to the process by which SLE develops, and discussed the potential of chromatin accessibility as a valuable option to identify novel therapeutic targets for this disease. Larger scale studies and combining epigenomic, transcriptomic, and metabolomic data can provide deeper insights into SLE chromatin biology in the future.

Discovery of antimicrobial peptides in the global microbiome with machine learning.

Novel antibiotics are urgently needed to combat the antibiotic-resistance crisis. We present a machine-learning-based approach to predict antimicrobial peptides (AMPs) within the global microbiome and leverage a vast dataset of 63,410 metagenomes and 87,920 prokaryotic genomes from environmental and host-associated habitats to create the AMPSphere, a comprehensive catalog comprising 863,498 non-redundant peptides, few of which match existing databases. AMPSphere provides insights into the evolutionary origins of peptides, including by duplication or gene truncation of longer sequences, and we observed that AMP production varies by habitat. To validate our predictions, we synthesized and tested 100 AMPs against clinically relevant drug-resistant pathogens and human gut commensals both in vitro and in vivo. A total of 79 peptides were active, with 63 targeting pathogens. These active AMPs exhibited antibacterial activity by disrupting bacterial membranes. In conclusion, our approach identified nearly one million prokaryotic AMP sequences, an open-access resource for antibiotic discovery.

Self-Assembled Nanocomposite DOX/TPOR4@CB[7]4 for Enhanced Synergistic Photodynamic Therapy and Chemotherapy in Neuroblastoma.

DOX/TPOR4@CB[7]4 was synthesized via self-assembly, and its physicochemical properties and ability to generate reactive oxygen species (ROS) were evaluated. The impact of photodynamic therapy on SH-SY5Y cells was assessed using the MTT assay, while flow cytometry analysis was employed to detect cell apoptosis. Confocal laser scanning microscopy was utilized to observe the intracellular distribution of DOX/TPOR4@CB[7]4 in SH-SY5Y cells. Additionally, fluorescence imaging of DOX/TPOR4@CB[7]4 in nude mice bearing SH-SY5Y tumors and examination of the combined effects of photodynamic and chemical therapies were conducted. The incorporation of CB[7] significantly enhanced the optical properties of DOX/TPOR4@CB[7]4, resulting in increased ROS production and pronounced toxicity towards SH-SY5Y cells. Moreover, both the apoptotic and mortality rates exhibited significant elevation. In vivo experiments demonstrated that tumor growth inhibition was most prominent in the DOX/TPOR4@CB[7]4 group. π-π interactions facilitated the binding between DOX and photosensitizer TPOR, with TPOR's naphthalene hydrophilic groups encapsulated within CB[7]'s cavity through host-guest interactions with CB[7]. Therefore, CB[7] can serve as a nanocarrier to enhance the combined application of chemical therapy and photodynamic therapy, thereby significantly improving treatment efficacy against neuroblastoma tumors.

Optical fiber bundle differential compressive imaging.

We present a differential compressive imaging method for an optical fiber bundle (OFB), which provides a solution for an ultrathin bend-resistant endoscope with high resolution. This method uses an OFB and a diffuser to generate speckle illumination patterns. Differential operation is additionally applied to the speckle patterns to produce sensing matrices, by which the correlation between the matrices is greatly reduced from 0.875 to 0.0275, which ensures the high quality of image reconstruction. Pixilation artifacts from the fiber core arrangement are also effectively eliminated with this configuration. We demonstrate high-resolution reconstruction of images of 132 × 132 pixels with a compression rate of 12% using 77 fiber cores, the total diameter of which is only about 91 µm. An experimental verification proves that this method is tolerant to a limited degree of fiber bending, which provides a potential approach for robust high-resolution fiber endoscopy.

Nomogram prediction of vessels encapsulating tumor clusters in small hepatocellular carcinoma ≤ 3 cm based on enhanced magnetic resonance imaging.

BACKGROUND: Vessels encapsulating tumor clusters (VETC) represent a recently discovered vascular pattern associated with novel metastasis mechanisms in hepatocellular carcinoma (HCC). However, it seems that no one have focused on predicting VETC status in small HCC (sHCC). This study aimed to develop a new nomogram for predicting VETC positivity using preoperative clinical data and image features in sHCC (≤ 3 cm) patients. AIM: To construct a nomogram that combines preoperative clinical parameters and image features to predict patterns of VETC and evaluate the prognosis of sHCC patients. METHODS: A total of 309 patients with sHCC, who underwent segmental resection and had their VETC status confirmed, were included in the study. These patients were recruited from three different hospitals: Hospital 1 contributed 177 patients for the training set, Hospital 2 provided 78 patients for the test set, and Hospital 3 provided 54 patients for the validation set. Independent predictors of VETC were identified through univariate and multivariate logistic analyses. These independent predictors were then used to construct a VETC prediction model for sHCC. The model's performance was evaluated using the area under the curve (AUC), calibration curve, and clinical decision curve. Additionally, Kaplan-Meier survival analysis was performed to confirm whether the predicted VETC status by the model is associated with early recurrence, just as it is with the actual VETC status and early recurrence. RESULTS: Alpha-fetoprotein_lg10, carbohydrate antigen 199, irregular shape, non-smooth margin, and arterial peritumoral enhancement were identified as independent predictors of VETC. The model incorporating these predictors demonstrated strong predictive performance. The AUC was 0.811 for the training set, 0.800 for the test set, and 0.791 for the validation set. The calibration curve indicated that the predicted probability was consistent with the actual VETC status in all three sets. Furthermore, the decision curve analysis demonstrated the clinical benefits of our model for patients with sHCC. Finally, early recurrence was more likely to occur in the VETC-positive group compared to the VETC-negative group, regardless of whether considering the actual or predicted VETC status. CONCLUSION: Our novel prediction model demonstrates strong performance in predicting VETC positivity in sHCC (≤ 3 cm) patients, and it holds potential for predicting early recurrence. This model equips clinicians with valuable information to make informed clinical treatment decisions.

Dihydroartemisinin suppresses the tumorigenesis of esophageal carcinoma by elevating DAB2IP expression in a NFIC-dependent manner.

Dihydroartemisinin (DHA) has been identified to have the anticancer and anti-inflammatory activities. Disabled homolog 2 interacting protein (DAB2IP) is a well-recognized tumor suppressor. Both DHA and DAB2IP were proven to have suppressing effects on esophageal carcinoma (ESCA) tumorigenesis. However, whether DHA regulated ESCA cells via DAB2IP and its mechanism are still vague. Functional analyses were conducted using MTT, tube formation, sphere formation, and transwell assays in vitro as well as Tumor formation experiments in mice. Levels of genes and proteins were assayed by qRT-PCR and western blotting analyses. The interaction between DAB2IP and Nuclear Factor I C (NFIC) was confirmed using bioinformatics analysis and dual-luciferase reporter assay. DHA treatment suppressed ESCA cell angiogenesis, stemmess, migration, and invasion. DAB2IP level was decreased in ESCA tissues and cells, and DHA elevated DAB2IP expression in ESCA cells. Functionally, DAB2IP overexpression impaired ESCA cell angiogenesis, stemmess, migration and invasion. Mechanistically, NFIC had binding sites on the promoter region and directly targeted DAB2IP. DHA could up-regulate DAB2IP expression via NFIC. Moreover, NFIC was also decreased in ESCA tissues and cells, and its overexpression had anticancer activity in ESCA cells. In addition, DAB2IP knockdown reversed the anticancer effects of NFIC or DHA on ESCA cells. In further in vivo analysis, DHA also suppressed ESCA growth by regulating DAB2IP expression. DHA suppressed the tumorigenesis of ESCA by elevating DAB2IP expression in an NFIC-dependent manner, suggesting the potential clinical application of DHA in ESCA treatment.

Optimal Glycated Hemoglobin Cutoff for Diagnosis of Diabetes and Prediabetes in Chinese Breast Cancer Women.

Purpose: Glycated hemoglobin (HbA1c) is widely used in diabetes management and now recommended for diagnosis and risk assessment. Our research focused on investigating the optimal cutoff points of HbA1c for diagnosis of diabetes and prediabetes in Chinese breast cancer women, aiming to enhance early detection and tailor treatment strategies. Patients and Methods: This study involved 309 breast cancer women without diabetes history in China. Patients were categorized into groups of newly diagnosed diabetes, prediabetes, and normal glucose tolerance using oral glucose tolerance test (OGTT) according to the 2010 ADA criteria. HbA1c data were collected from all patients. Receiver operating characteristic (ROC) curve analysis was used to assess the effectiveness of the HbA1c screening. Results: Among the 309 breast cancer women without diabetes history, 96 (31.0%) were identified with diabetes and 130 (42.1%) had prediabetes according to OGTT, and the incidence of normal glucose tolerance was only 26.9% (83). ROC curve analysis, using OGTT as a reference, revealed that the area under the curve of 0.903 (P<0.001, 95% CI, 0.867-0.938) for HbA1c alone, indicating high accuracy. The optimal HbA1c cutoff for identifying diabetes was determined to be 6.0%, with a sensitivity of 78.1% and specificity of 86.4%. For prediabetes, the ROC curve for HbA1c alone showed that the area under the ROC curve of 0.703 (P<0.001, 95% CI, 0.632-0.774), with an optimal cutoff of 5.5% (sensitivity of 76.9% and specificity of 51.8%). Conclusion: The prevalence of undiagnosed diabetes is very high in breast cancer women without diabetes history in China. The optimal cutoff points of HbA1c for identifying diabetes and prediabetes are 6.0% and 5.5% in Chinese breast cancer women, respectively.

The FAITHS2 Model Predicts Functional Disability in Patients With Acute Ischemic Stroke.

The present study aimed to develop a model to predict functional disability at 3 months in patients with acute ischemic stroke (AIS) (n = 5,406). The primary outcome was functional disability (modified Rankin Scale [mRS] >2) at 3 months. A prediction model including blood biomarkers was developed based on a multivariable logistic regression model, which was internally validated by the 100-time bootstrap method. A nomogram and a web-based calculator were developed for usage in clinical practice. At 3 months, 11% (638/5,406) of the patients had functional disability. Seven independent predictors of functional disability at 3 months were incorporated into the FAITHS2 model (fasting plasma glucose, age, interleukin-6, stroke history, National Institute of Health Stroke Scale [NIHSS] at admission, sex, and systolic blood pressure). The Area Under Curves (AUCs) were 0.814 (95% confidence interval [CI] 0.796-0.832) and 0.808 (95% CI 0.806-0.810), and the Brier scores were 0.088 ± 0.214 and 0.089 ± 0.003 for the derivation cohort and internal validation, respectively, showing optimal performance of the model. The FAITHS2 model has excellent potential to be a dependable application for individualized clinical decision making.