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ObjectiveCurrently, distinct use of clinical data, routine laboratory indicators or the detection of diabetic autoantibodies in the diagnosis and management of diabetes mellitus is limited. Hence, this study was aimed to screen the indicators, and to establish and validate a multifactorial logistic regression model nomogram for the non-invasive differential prediction of type 1 diabetes mellitus.MethodsClinical data, routine laboratory indicators, and diabetes autoantibody profiles of diabetic patients admitted between September 2018 and December 2022 were retrospectively analyzed. Logistic regression was used to select the independent influencing factors, and a prediction nomogram based on the multiple logistic regression model was constructed using these independent factors. Moreover, the predictive accuracy and clinical application value of the nomogram were evaluated using Receiver Operating Characteristic (ROC) curves, calibration curves, decision curve analysis (DCA), and clinical impact curves (CIC).ResultsA total of 522 diabetic patients were included in this study. These patients were randomized into training and validation sets in a 7:3 ratio. The predictors screened included age, prealbumin (PA), high-density lipoprotein cholesterol (HDL-C), islet cells autoantibodies (ICA), islets antigen 2 autoantibodies (IA-2A), glutamic acid decarboxylase antibody (GADA), and C-peptide levels. Based on these factors, a multivariate model nomogram was constructed, which had an Area Under Curve (AUC) of 0.966 and 0.961 for the training set and validation set, respectively. Subsequently, the calibration curves demonstrated a strong accuracy of the graph; the DCA and CIC results indicated that the graph could be used as a non-invasive valid predictive tool for the differential diagnosis of type 1 diabetes mellitus, clinically.ConclusionThe established prediction model combining patient’s age, PA, HDL-C, ICA, IA-2A, GADA, and C-peptide can assist in differential diagnosis of type 1 diabetes mellitus and type 2 diabetes mellitus and provides a basis for the clinical as well as therapeutic management of the disease.

Abstract Background Luminal breast cancer (BC) is the predominant subtype of breast cancer with a sustained risk of late recurrence and death. Understanding the molecular mechanisms for the oncogenesis of luminal BC would improve the prognosis for this large subset of patients. SPDEF was reported to be dysregulated in breast cancers. However, the biological functions and underlying molecular mechanism of SPDEF in luminal BC remains largely unknown. The aim of the present study was to elucidate the potential roles of SPDEF underlying subtype-specific functions in BC, especially in luminal subtypes. Methods The expressions and clinicopathological characteristics of SPDEF in luminal BC patients were evaluated bioinformatically. In vitro and in vivo assays were performed to investigate the oncogenic function and stemness maintenance of SPDEF in luminal BC. Chromatin immunoprecipitation (ChIP) and dual luciferase reporter assays were conducted to determine the transcription regulation of GALNT7 by SPDEF. GALNT7 levels in serum from luminal BC patients were further detected by enzyme-linked immunosorbent assay (ELISA). Results SPDEF is markedly upregulated in luminal BC and positively associated with tumor progression and poor prognosis. Furthermore, we confirmed that SPDEF enhanced the proliferation, migration, invasion and stemness of luminal BC cells in vitro as well the tumorigenicity in vivo. Mechanistically, we demonstrated the stimulative effect of SPDEF on the progression and stemness of luminal BC, which is mediated by its directly transcriptional target GALNT7. Clinically, we verified that the GALNT7 can be used as a noninvasive diagnostic marker. Noteworthy, the combined detection of serum GALNT7 and traditional tumor markers can enhance diagnostic accuracy thus is of vital importance in the early diagnosis of luminal BC. Conclusions Our study reveals a novel mechanism by which SPDEF transcriptionally activates GALNT7 via directly binding to its promoter to promote cell proliferation, motility and stemness, and led to luminal BC tumorigenesis and poor prognosis.

The late embryonic mouse lens requires the transcription factor ATF4 for its survival although the underlying mechanisms were unknown. Here, RNAseq analysis revealed that E16.5 Atf4 null mouse lenses downregulate the mRNA levels of lens epithelial markers as well as known markers of late lens fiber cell differentiation. However, a comparison of this list of differentially expressed genes (DEGs) with other known transcriptional regulators of lens development indicated that ATF4 expression is not directly controlled by the previously described lens gene regulatory network. Pathway analysis revealed that the Atf4 DEG list was enriched in numerous genes involved in nutrient transport, amino acid biosynthesis, and tRNA charging. These changes in gene expression likely result in the observed reductions in lens free amino acid and glutathione levels, which would result in the observed low levels of extractable lens protein, finally leading to perinatal lens disintegration. These data demonstrate that ATF4, via its function in the integrated stress response, is likely to play a crucial role in mediating the adaption of the lens to the avascularity needed to maintain lens transparency.

We have fabricated junctionless N-type silicon-on-insulator (SOI) ferroelectric-HfO2 field effect transistors (FeFETs) with overlap and underlap structures between gate and drain/source regions to investigate the role of gate-induced-drain-leakage (GIDL) current in erase operation of FeFETs with a floating body. We also introduced a novel gate stack process for low voltage operation by inserting a Ti layer in the metal gate. The Ti layer insertion can suppress the growth of an interfacial layer (IL) by controlling oxygen intrusion into the IL during the rapid thermal anneal (RTA) process. We demonstrated an efficient erase operation at shorter and lower pulse voltage with GIDL current in the overlap structure than in the underlap structure. A compact FeFET retention model is developed based on the surface-potential based FET model, the nucleation-limited-switching (NLS) model, and the retention model of ferroelectric (FE) capacitor. Faster degradation of the program state observed in the experiment can be explained by electron detrapping according to the modeling and simulation.

We have experimentally demonstrated memory operation of a HfO2-based ferroelectric FET (FeFET) with an ultrathin MoS2 channel and bottom-gate structure. ZrO2 seed layer enhances ferroelectricity in HfZrO2 by post deposition anneal process. Surface passivation of a MoS2 layer reduces the instability of the transistor characteristics. An additional top gate effectively controls the body potential instead of floating body. Thereby, FeFET memory operation was realized with enhanced ferroelectricity and body-potential control. By using pulse write operation, the ultrathin MoS2 channel FeFET showed the memory window of 0.22V, the retention time >5000 seconds, and the endurance cycles were $> 10^{6}$ times. This work highlights the applicability of the device for high-density memory such as 3D FeFET.

This study aims to explore the construction of an evaluation index system for undergraduate engineering majors based on the Context, Input, Process, Product (CIPP) model under the Outcome-based Education (OBE) approach employing the Delphi method and Analytic Hierarchy Process. The trial of the evaluation index system involved 986 entrepreneurs, engineering technicians and teachers majoring in the field of electronic-information, who were recruited and selected for participation on the Internet. Data were collected from the consultation questionnaire developed in accordance with the indicators at all levels. Subsequently, Principal Component Analysis was used to verify the rationality of the indicator design, and the corresponding weights were adjusted. The results found that the index system includes 4 first-level, 11 second-level, and 42 third-level indicators, and different weights are assigned according to the extent of influence each of these indicators has on the quality of undergraduate training. Furthermore, the evaluation system can reflect the actual relationship among the indicators to some extent, which provides reference for the quality evaluation of engineering education.

Traces of mercury ions in environmental water can harm humans and animals. Paper-based visual detection methods have been widely developed for the rapid detection of mercury ions; however, existing methods are not sensitive enough to be used in real environments. Here, we developed a novel, simple and effective visual fluorescent sensing paper-based chip for the ultrasensitive detection of mercury ions in environmental water. CdTe-quantum-dots-modified silica nanospheres were firmly absorbed by and anchored to the fiber interspaces on the paper’s surface to effectively avoid the unevenness caused by liquid evaporation. The fluorescence of quantum dots emitted at 525 nm can be selectively and efficiently quenched with mercury ions, and the ultrasensitive visual fluorescence sensing results attained using this principle can be captured using a smartphone camera. This method has a detection limit of 2.83 µg/L and a fast response time (90 s). We successfully achieved the trace spiking detection of seawater (from three regions), lake water, river water and tap water with recoveries in the range of 96.8–105.4% using this method. This method is effective, low-cost, user-friendly and has good prospects for commercial application. Additionally, the work is expected to be utilized in the automated big data collection of large numbers of environmental samples.