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In this paper, a dielectric modulated double source trench gate tunnel FET (DM-DSTGTFET) based on biosensor is proposed for the detection of biomolecules. DM-DSTGTFET adopts double source and trench gate to enhance the on-state current and to generate bidirectional current. In the proposed structure, two cavities are etched over 1 nm gate oxide for biomolecules filling. A 2D simulation in the Technology Computer-Aided Design (TCAD) is adopted for the analysis of sensitivity study. The results show that under low supply voltage, the current sensitivity of the DM-DSTGTFET is as high as 1.38 × 105, and the threshold voltage sensitivity can reach 1.2 V. Therefore, the DM-DSTGTFET biosensor has good application prospects due to its low power consumption and high sensitivity.

This article comprehensively analyzes the new developments and challenges faced by several typical prediction models in the field of radiation effects in recent years. The models discussed include the RPP model, the extended RPP (rectangular parallelepiped) model, and the IRPP (integral rectangular parallelepiped) model. The article conducts a comprehensive analysis of the limitations of the assumption that uses the linear energy transfer (LET) of incident particles and the SEU (single-particle upset) cross-section (without considering the energy and type of ions) to predict the rate of single-particle effects (SEUs). Additionally, the article points out that with the continuous progress of integrated circuit technology, the geometric shape of the target circuit, the energy of the incident particles, the type of particles, and more precise physical models corresponding to the interaction between radiation and matter have become increasingly important in evaluating the sensitivity to single-particle effects (SEEs). Subsequently, based on the probability characteristics of SEE, a series of general estimation equations for the SEE rate are derived, considering particle energy, particle type, and the probability of influence at a specific moment. Then, by introducing the concept of interaction volume, the concept of sensitive volume is further expanded, and using these general equations, the relationship between the SEE rate cross-section and the SEE projected area is derived, simplifying the SEU rate prediction equation to a form that can be directly used in engineering applications. Finally, the article emphasizes a complete method of applying the general prediction equation to engineering to estimate the radiation disturbance performance of two typical verification circuits, and provides the corresponding prediction results.

The development of an integrated circuit faces the challenge of the physical limit of Moore’s Law. One of the most important “Beyond Moore” challenges is the scaling down of Metal-Oxide-Semiconductor Field-Effect Transistors (MOSFETs) versus their increasing static power consumption. This is because, at room temperature, the thermal emission transportation mechanism will cause a physical limitation on subthreshold swing (SS), which is fundamentally limited to a minimum value of 60 mV/decade for MOSFETs, and accompanied by an increase in off-state leakage current with the process of scaling down. Moreover, the impacts of short-channel effects on device performance also become an increasingly severe problem with channel length scaling down. Due to the band-to-band tunneling mechanism, Tunnel Field-Effect Transistors (TFETs) can reach a far lower SS than MOSFETs. Recent research works indicated that TFETs are already becoming some of the promising candidates of conventional MOSFETs for ultra-low-power applications. This paper provides a review of some advances in materials and structures along the evolutionary process of TFETs. An in-depth discussion of both experimental works and simulation works is conducted. Furthermore, the performance of TFETs with different structures and materials is explored in detail as well, covering Si, Ge, III-V compounds and 2D materials, alongside different innovative device structures. Additionally, this work provides an outlook on the prospects of TFETs in future ultra-low-power electronics and biosensor applications.

Background Chemotherapy is a widely used treatment for cancer. However, the development of acquired multidrug resistance (MDR) is a serious issue. Emerging evidence has shown that the extracellular vesicles (EVs) mediate MDR, but the underlying mechanism remains unclear, especially the effects of chemotherapeutic agents on this process. Methods Extracellular vesicles isolation was performed by differential centrifugation. The recipient cells that acquired ATP-binding cassette sub-family B member 1 (ABCB1) proteins were sorted out from co-cultures according to a stringent multi-parameter gating strategy by fluorescence-activated cell sorting (FACS). The transfer rate of ABCB1 was measured by flow cytometry. The xenograft tumor models in mice were established to evaluate the transfer of ABCB1 in vivo. Gene expression was detected by real-time PCR and Western blotting. Results Herein, we show that a transient exposure to chemotherapeutic agents can strikingly increase Rab8B-mediated release of extracellular vesicles (EVs) containing ABCB1 from drug-resistant cells, and accelerate these EVs to circulate back onto plasma membrane of sensitive tumor cells via the down-regulation of Rab5. Therefore, intercellular ABCB1 transfer is significantly enhanced; sensitive recipient cells acquire a rapid but unsustainable resistance to evade the cytotoxicity of chemotherapeutic agents. More fascinatingly, in the xenograft tumor models, chemotherapeutical drugs also locally or distantly increase the transfer of ABCB1 molecules. Furthermore, some Non-small-cell lung carcinoma (NSCLC) patients who are undergoing primary chemotherapy have a rapid increase of ABCB1 protein in their monocytes, and this is obviously associated with poor chemotherapeutic efficacy. Conclusions Chemotherapeutic agents stimulate the secretion and recycling of ABCB1-enriched EVs through the dysregulation of Rab8B and Rab5, leading to a significant increase of ABCB1 intercellular transfer, thus assisting sensitive cancer cells to develop an urgent resistant phenotype. Our findings provide a new molecular mechanism of how chemotherapeutic drugs assist sensitive cancer cells in acquiring an urgent resistance.

Due to their high carrier mobility, thermal conductivity, and exceptional foldability, transition metal dichalcogenides (TMDs) present promising prospects in the realm of flexible semiconductor devices. Concurrently, tunneling field-effect transistors (TFETs) have garnered significant attention owing to their low energy consumption. This study investigates a TMD van der Waals heterojunction (VdWH) TFET, specifically by fabricating MoS2 field-effect transistors (FETs), WSe2 FETs, and MoS2/WSe2 VdWH TFETs. The N-type characteristics of the MoS2 and P-type characteristics of WSe2 are established through an analysis of the electrical characteristics of the respective FETs. Finally, we analyze the energy band and electrical characteristics of the MoS2/WSe2 VdWH TFET, which exhibits a drain current switching ratio of 105. This study provides valuable insights for the development of novel low-power devices.

Spatial metabolomics has revolutionized cancer research by offering unprecedented insights into the metabolic heterogeneity of the tumor microenvironment (TME). Unlike conventional metabolomics, which lacks spatial resolution, spatial metabolomics enables the visualization of metabolic interactions among cancer cells, stromal components, and immune cells within their native tissue context. Despite its growing significance, a systematic and visualized analysis of spatial metabolomics in cancer research remains lacking, particularly in the integration of multi-omics data and the standardization of methodologies for comprehensive tumor metabolic mapping. This study aims to conduct a bibliometric analysis to systematically evaluate the development trends, key contributors, research hotspots, and future directions of spatial metabolomics in cancer research. A bibliometric approach was employed using data retrieved from the Web of Science Core Collection. Analytical tools such as VOSviewer and CiteSpace were utilized to visualize and assess co-citation networks, keyword co-occurrence, and institutional collaborations. Key metrics, including publication trends, authorship influence, country contributions, and journal impact, were analyzed to map the research landscape in this domain. A total of 182 publications on spatial metabolomics in cancer research were identified over the past two decades, with a notable surge in research output beginning in 2018. The field has experienced accelerated growth, with an annual average of 40 publications since 2021, reflecting its increasing relevance in cancer studies. Among 28 contributing countries, China (n=53), the United States (n=35), Germany (n=18), and the United Kingdom (n=13) have been the most active contributors. China leads in publication volume, while the United States exhibits the highest citation impact, indicating significant research influence. International collaboration networks are particularly strong among the United States, Germany, and China, underscoring the global interest in this emerging field. Analysis of key authors and institutions identifies He Jiuming as the most prolific author and Song Xiaowei as the researcher with the highest average citations. Other influential authors include Abliz Zeper and Sun Chenglong. Leading research institutions driving advancements in this field include the Chinese Academy of Medical Sciences, Peking Union Medical College, Harvard Medical School, and Stanford University. Regarding journal impact, Nature Communications (n=11), Journal of Pharmaceutical Analysis (n=9), and Nature Methods (n=8) are the most active publishing platforms in this domain. Citation analysis reveals that Cell, BioEssays, and Genome Medicine are among the most highly cited journals, reflecting the interdisciplinary nature of spatial metabolomics research.

In this paper, a dopingless fin-shaped SiGe channel TFET (DF-TFET) is proposed and studied. To form a high-efficiency dopingless line tunneling junction, a fin-shaped SiGe channel and a gate/source overlap are induced. Through these methods, the DF-TFET with high on-state current, switching ratio of 12 orders of magnitude and no obvious ambipolar effect can be obtained. High κ material stack gate dielectric is induced to improve the off-state leakage, interface characteristics and the reliability of DF-TFET. Moreover, by using the dopingless channel and fin structure, the difficulties of doping process and asymmetric gate overlap formation can be resolved. As a result, the structure of DF-TFET can possess good manufacture applicability and remarkably reduce footprint. The physical mechanism of device and the effect of parameters on performance are studied in this work. Finally, on-state current (ION) of 58.8 μA/μm, minimum subthreshold swing of 2.8 mV/dec (SSmin), average subthreshold swing (SSavg) of 18.2 mV/dec can be obtained. With improved capacitance characteristics, cutoff frequency of 5.04 GHz and gain bandwidth product of 1.29 GHz can be obtained. With improved performance and robustness, DF-TFET can be a very attractive candidate for ultra-low-power applications.

Background Natural killer (NK) cell immunotherapy has shown promising therapeutic potential for acute myeloid leukemia (AML), especially with advancements in chimeric antigen receptor-engineered NK cells (CAR-NK) and artificial intelligence (AI). Despite these developments, the field lacks comprehensive bibliometric analyses to identify research hotspots and trends, which could guide future precision treatments. Methods A bibliometric analysis of NK cell immunotherapy for AML was conducted using literature from 2000 to 2023 retrieved from the Web of Science Core Collection database. Data visualization tools like CiteSpace, VOSviewer, and RStudio were employed to analyze publication trends, country contributions, institutional collaborations, influential authors, and research themes. Results The analysis identified 1513 studies, with the United States and China leading global contributions. Notable institutions include the University of Minnesota and MD Anderson Cancer Center. Hot topics include allogeneic NK therapy, CAR-NK cell therapy, and memory-like NK cells. Emerging trends highlight the integration of intelligent NK cells and combinatory therapies, offering promising avenues for AML treatment. Despite progress, challenges such as NK cell expansion, activation, and resistance mechanisms remain critical areas for research. Conclusion This study provides a comprehensive overview of the research landscape, highlighting the transformative potential of NK cell immunotherapy in AML. It underscores the need for international collaboration and continued innovation to overcome existing challenges and advance precision therapies.

Introduction Drug-induced myelosuppression (DIM) is a serious side effect of several medications, particularly chemotherapy, immunosuppressants, and targeted therapies, which can lead to infections, anemia, and bleeding. While these drugs are effective, their adverse effects can disrupt treatment plans and reduce quality of life. However, early identification of DIM remains challenging, as many associated drugs do not explicitly list this risk, complicating clinical monitoring. Methods This study utilized the FDA Adverse Event Reporting System (FAERS) database to perform signal mining and assess the risks of DIM. Reports from the first quarter of 2004 to the third quarter of 2024 were analyzed using signal detection algorithms such as Reporting Odds Ratio (ROR), Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Empirical Bayesian Geometric Mean (EBGM). These methods helped identify drug signals related to DIM and explore risk factors and occurrence patterns. Results The study analyzed 21 380 adverse event reports related to DIM, showing a significant increase in the number of reports since 2019, peaking at 3501 in 2021. Among patients, 50.2% were female, 35.5% were male, and the majority (44.42%) were aged between 18 and 65. Breast cancer patients had the highest DIM incidence (10.6%). Geographically, China reported the most cases (57.4%), followed by Japan (12.4%), and the United States (6.76%). The drugs most frequently linked to DIM included trastuzumab, bevacizumab, venetoclax, methotrexate, and pertuzumab. Additionally, 12 new drug signals were identified that were not labeled for DIM risk, including PERTUZUMAB, SODIUM CHLORIDE, and MESNA, which showed particularly strong or unexpected associations. Conclusion This study identifies new DIM-related drug signals and emphasizes the need for early detection to improve clinical management and optimize treatment regimens. The findings provide valuable evidence for drug safety monitoring and can help reduce DIM-related risks in cancer treatment. Plain Language Summary Drug-induced myelosuppression (DIM) is a condition where certain medications cause a decrease in blood cells, which can lead to serious health problems like infections, anemia, and bleeding. This is especially a concern for cancer patients who are treated with chemotherapy, targeted therapies, and immunotherapy. However, it is often difficult to predict which drugs might cause this side effect, especially once the drugs are already on the market. In this study, we used real-world data from the FDA’s Adverse Event Reporting System (FAERS) to find out which drugs are most likely to cause DIM. By analyzing over 21,000 reports from patients between 2004 and 2024, we identified several drugs that are strongly linked to DIM, including some that hadn’t been officially labeled for this risk. Our findings help improve the understanding of DIM, allowing doctors to better monitor patients and reduce the chances of severe complications. This research provides important information that can help doctors choose safer treatment options for cancer patients, and it can also guide regulatory agencies in improving drug safety warnings.

In this paper, a silicon-based T-shape gate dual-source tunnel field-effect transistor (TGTFET) is proposed and investigated by TCAD simulation. As a contrastive study, the structure, characteristic, and analog/RF performance of TGTFET, LTFET, and UTFET are discussed. The gate overlap introduced by T-shape gate can enhance the efficiency of tunneling junction. The dual-source regions in TGTFET can increase the on-state current ( I ON ) by offering a doubled tunneling junction area. In order to further improve the device performance, the n+ pocket is introduced in TGTFET to further increase the band-to-band tunneling rate. Simulation results reveal that the TGTFET’s I ON and switching ratio ( I ON / I OFF ) reach 81 μA/μm and 6.7 × 10 10 at 1 V gate to source voltage ( V g ). The average subthreshold swing of TGTFET (SS avg , from 0 to 0.5 V V g ) reaches 51.5 mV/dec, and the minimum subthreshold swing of TGTFET (SS min , at 0.1 V V g ) reaches 24.4 mV/dec. Moreover, it is found that TGTFET have strong robustness on drain-induced barrier lowering (DIBL) effect. The effects of doping concentration, geometric dimension, and applied voltage on device performance are investigated in order to create the TGTFET design guideline. Furthermore, the transconductance ( g m ), output conductance ( g ds ), gate to source capacitance ( C gs ), gate to drain capacitance ( C gd ), cut-off frequency ( f T ), and gain bandwidth (GBW) of TGTFET reach 232 μS/μm, 214 μS/μm, 0.7 fF/μm, 3.7 fF/μm, 11.9 GHz, and 2.3 GHz at 0.5 V drain to source voltage ( V d ), respectively. Benefiting from the structural advantage, TGTFET obtains better DC/AC characteristics compared to UTFET and LTFET. In conclusion, the considerable good performance makes TGTFET turn into a very attractive choice for the next generation of low-power and analog/RF applications.