An inorganic-blended p-type semiconductor with robust electrical and mechanical properties.

Inorganic semiconductors typically have limited p-type behavior due to the scarcity of holes and the localized valence band maximum, hindering the progress of complementary devices and circuits. In this work, we propose an inorganic blending strategy to activate the hole-transporting character in an inorganic semiconductor compound, namely tellurium-selenium-oxygen (TeSeO). By rationally combining intrinsic p-type semimetal, semiconductor, and wide-bandgap semiconductor into a single compound, the TeSeO system displays tunable bandgaps ranging from 0.7 to 2.2 eV. Wafer-scale ultrathin TeSeO films, which can be deposited at room temperature, display high hole field-effect mobility of 48.5 cm2/(Vs) and robust hole transport properties, facilitated by Te-Te (Se) portions and O-Te-O portions, respectively. The nanosphere lithography process is employed to create nanopatterned honeycomb TeSeO broadband photodetectors, demonstrating a high responsibility of 603 A/W, an ultrafast response of 5 µs, and superior mechanical flexibility. The p-type TeSeO system is highly adaptable, scalable, and reliable, which can address emerging technological needs that current semiconductor solutions may not fulfill.

Arsenic trioxide augments immunogenic cell death and induces cGAS-STING-IFN pathway activation in hepatocellular carcinoma.

The treatment of hepatocellular carcinoma (HCC) is particularly challenging due to the inherent tumoral heterogeneity and easy resistance towards chemotherapy and immunotherapy. Arsenic trioxide (ATO) has emerged as a cytotoxic agent effective for treating solid tumors, including advanced HCC. However, its effectiveness in HCC treatment remains limited, and the underlying mechanisms are still uncertain. Therefore, this study aimed to characterize the effects and mechanisms of ATO in HCC. By evaluating the susceptibilities of human and murine HCC cell lines to ATO treatment, we discovered that HCC cells exhibited a range of sensitivity to ATO treatment, highlighting their inherent heterogeneity. A gene signature comprising 265 genes was identified to distinguish ATO-sensitive from ATO-insensitive cells. According to this signature, HCC patients have also been classified and exhibited differential features of ATO response. Our results showed that ATO treatment induced reactive oxygen species (ROS) accumulation and the activation of multiple cell death modalities, including necroptosis and ferroptosis, in ATO-sensitive HCC cells. Meanwhile, elevated tumoral immunogenicity was also observed in ATO-sensitive HCC cells. Similar effects were not observed in ATO-insensitive cells. We reported that ATO treatment induced mitochondrial injury and mtDNA release into the cytoplasm in ATO-sensitive HCC tumors. This subsequently activated the cGAS-STING-IFN axis, facilitating CD8+ T cell infiltration and activation. However, we found that the IFN pathway also induced tumoral PD-L1 expression, potentially antagonizing ATO-mediated immune attack. Additional anti-PD1 therapy promoted the anti-tumor response of ATO in ATO-sensitive HCC tumors. In summary, our data indicate that heterogeneous ATO responses exist in HCC tumors, and ATO treatment significantly induces immunogenic cell death (ICD) and activates the tumor-derived mtDNA-STING-IFN axis. These findings may offer a new perspective on the clinical treatment of HCC and warrant further study.

Nicotine downregulates miR-375-3p via neurotrophic tyrosine receptor kinase 2 to enhance the malignant behaviors of laryngopharyngeal squamous epithelial cells.

Nicotine exposure from smoking constitutes a significant global public health concern. Furthermore, smoking represents a pivotal risk factor for head and neck squamous cell carcinoma (HNSCC). However, the influence of nicotine on HNSCC remains relatively underexplored. Our aim was to unravel the molecular mechanisms that underlie the effect of nicotine on the metastatic cascade of HNSCC. In this study, we discovered a significant association between smoking and HNSCC metastasis and prognosis. Nicotine significantly enhanced HNSCC cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in vitro. Analysis of TCGA-HNSCC and FDEENT-HNSCC cohorts revealed reduced miR-375-3p levels in HNSCC tumor tissues, particularly among current smokers. Additionally, miR-375-3p level was strongly correlated with both lymph node metastasis and tumor stage. By downregulating miR-375-3p, nicotine promotes HNSCC cell metastasis in vitro and hematogenous metastatic capacity in vivo. Utilizing transcriptomic sequencing, molecular docking, dual-luciferase reporter assay, and fluorescence in situ hybridization (FISH), we demonstrated that miR-375-3p specifically binds to 3' untranslated region (3'UTR) of NTRK2 mRNA. Thus, this study uncovers a novel nicotine-induced mechanism involving miR-375-3p-mediated NTRK2 targeting, which promotes HNSCC metastasis. These findings have implications for improving the prognosis of patients with HNSCC, especially in smokers.

Diffusion-Dominated Luminescence Dynamics of CsPbBr3 Studied Using Cathodoluminescence and Microphotoluminescence Spectroscopy.

Time-resolved or time-correlation measurements using cathodoluminescence (CL) reveal the electronic and optical properties of semiconductors, such as their carrier lifetimes, at the nanoscale. However, halide perovskites, which are promising optoelectronic materials, exhibit significantly different decay dynamics in their CL and photoluminescence (PL). We conducted time-correlation CL measurements of CsPbBr3 using Hanbury Brown-Twiss interferometry and compared them with time-resolved PL. The measured CL decay time was on the order of subnanoseconds and was faster than PL decay at an excited carrier density of 2.1 × 1018 cm-3. Our experiment and analytical model revealed the CL dynamics induced by individual electron incidences, which are characterized by highly localized carrier generation followed by a rapid decrease in carrier density due to diffusion. This carrier diffusion can play a dominant role in the CL decay time for undoped semiconductors, in general, when the diffusion dynamics are faster than the carrier recombination.

A new 4-gene-based prognostic model accurately predicts breast cancer prognosis and immunotherapy response by integrating WGCNA and bioinformatics analysis.

Background: Breast cancer (BRCA) is a common malignancy in women, and its resistance to immunotherapy is a major challenge. Abnormal expression of genes is important in the occurrence and development of BRCA and may also affect the prognosis of patients. Although many BRCA prognosis model scores have been developed, they are only applicable to a limited number of disease subtypes. Our goal is to develop a new prognostic score that is more accurate and applicable to a wider range of BRCA patients. Methods: BRCA patient data from The Cancer Genome Atlas database was used to identify breast cancer-related genes (BRGs). Differential expression analysis of BRGs was performed using the 'limma' package in R. Prognostic BRGs were identified using co-expression and univariate Cox analysis. A predictive model of four BRGs was established using Cox regression and the LASSO algorithm. Model performance was evaluated using K-M survival and receiver operating characteristic curve analysis. The predictive ability of the signature in immune microenvironment and immunotherapy was investigated. In vitro experiments validated POLQ function. Results: Our study identified a four-BRG prognostic signature that outperformed conventional clinicopathological characteristics in predicting survival outcomes in BRCA patients. The signature effectively stratified BRCA patients into high- and low-risk groups and showed potential in predicting the response to immunotherapy. Notably, significant differences were observed in immune cell abundance between the two groups. In vitro experiments demonstrated that POLQ knockdown significantly reduced the viability, proliferation, and invasion capacity of MDA-MB-231 or HCC1806 cells. Conclusion: Our 4-BRG signature has the potential as an independent biomarker for predicting prognosis and treatment response in BRCA patients, complementing existing clinicopathological characteristics.

Pulse irradiation synthesis of metal chalcogenides on flexible substrates for enhanced photothermoelectric performance.

High synthesis temperatures and specific growth substrates are typically required to obtain crystalline or oriented inorganic functional thin films, posing a significant challenge for their utilization in large-scale, low-cost (opto-)electronic applications on conventional flexible substrates. Here, we explore a pulse irradiation synthesis (PIS) to prepare thermoelectric metal chalcogenide (e.g., Bi2Se3, SnSe2, and Bi2Te3) films on multiple polymeric substrates. The self-propagating combustion process enables PIS to achieve a synthesis temperature as low as 150 °C, with an ultrafast reaction completed within one second. Beyond the photothermoelectric (PTE) property, the thermal coupling between polymeric substrates and bismuth selenide films is also examined to enhance the PTE performance, resulting in a responsivity of 71.9 V/W and a response time of less than 50 ms at 1550 nm, surpassing most of its counterparts. This PIS platform offers a promising route for realizing flexible PTE or thermoelectric devices in an energy-, time-, and cost-efficient manner.

A 2D Heterostructure-Based Multifunctional Floating Gate Memory Device for Multimodal Reservoir Computing.

The demand for economical and efficient data processing has led to a surge of interest in neuromorphic computing based on emerging two-dimensional (2D) materials in recent years. As a rising van der Waals (vdW) p-type Weyl semiconductor with many intriguing properties, tellurium (Te) has been widely used in advanced electronics/optoelectronics. However, its application in floating gate (FG) memory devices for information processing has never been explored. Herein, an electronic/optoelectronic FG memory device enabled by Te-based 2D vdW heterostructure for multimodal reservoir computing (RC) is reported. When subjected to intense electrical/optical stimuli, the device exhibits impressive nonvolatile electronic memory behaviors including ≈108 extinction ratio, ≈100 ns switching speed, >4000 cycles, >4000-s retention stability, and nonvolatile multibit optoelectronic programmable characteristics. When the input stimuli weaken, the nonvolatile memory degrades into volatile memory. Leveraging these rich nonlinear dynamics, a multimodal RC system with high recognition accuracy of 90.77% for event-type multimodal handwritten digit-recognition is demonstrated.

Lattice-mismatch-free construction of III-V/chalcogenide core-shell heterostructure nanowires.

Growing high-quality core-shell heterostructure nanowires is still challenging due to the lattice mismatch issue at the radial interface. Herein, a versatile strategy is exploited for the lattice-mismatch-free construction of III-V/chalcogenide core-shell heterostructure nanowires by simply utilizing the surfactant and amorphous natures of chalcogenide semiconductors. Specifically, a variety of III-V/chalcogenide core-shell heterostructure nanowires are successfully constructed with controlled shell thicknesses, compositions, and smooth surfaces. Due to the conformal properties of obtained heterostructure nanowires, the wavelength-dependent bi-directional photoresponse and visible light-assisted infrared photodetection are realized in the type-I GaSb/GeS core-shell heterostructure nanowires. Also, the enhanced infrared photodetection is found in the type-II InGaAs/GeS core-shell heterostructure nanowires compared with the pristine InGaAs nanowires, in which both responsivity and detectivity are improved by more than 2 orders of magnitude. Evidently, this work paves the way for the lattice-mismatch-free construction of core-shell heterostructure nanowires by chemical vapor deposition for next-generation high-performance nanowire optoelectronics.

Anti-Ambipolar Heterojunctions: Materials, Devices, and Circuits.

Anti-ambipolar heterojunctions are vital in constructing high-frequency oscillators, fast switches, and multivalued logic (MVL) devices, which hold promising potential for next-generation integrated circuit chips and telecommunication technologies. Thanks to the strategic material design and device integration, anti-ambipolar heterojunctions have demonstrated unparalleled device and circuit performance that surpasses other semiconducting material systems. This review aims to provide a comprehensive summary of the achievements in the field of anti-ambipolar heterojunctions. First, the fundamental operating mechanisms of anti-ambipolar devices are discussed. After that, potential materials used in anti-ambipolar devices are discussed with particular attention to 2D-based, 1D-based, and organic-based heterojunctions. Next, the primary device applications employing anti-ambipolar heterojunctions, including anti-ambipolar transistors (AATs), photodetectors, frequency doublers, and synaptic devices, are summarized. Furthermore, alongside the advancements in individual devices, the practical integration of these devices at the circuit level, including topics such as MVL circuits, complex logic gates, and spiking neuron circuits, is also discussed. Lastly, the present key challenges and future research directions concerning anti-ambipolar heterojunctions and their applications are also emphasized.

Multislip-enabled morphing of all-inorganic perovskites.

All-inorganic lead halide perovskites (CsPbX3, X = Cl, Br or I) are becoming increasingly important for energy conversion and optoelectronics because of their outstanding performance and enhanced environmental stability. Morphing perovskites into specific shapes and geometries without damaging their intrinsic functional properties is attractive for designing devices and manufacturing. However, inorganic semiconductors are often intrinsically brittle at room temperature, except for some recently reported layered or van der Waals semiconductors. Here, by in situ compression, we demonstrate that single-crystal CsPbX3 micropillars can be substantially morphed into distinct shapes (cubic, L and Z shapes, rectangular arches and so on) without localized cleavage or cracks. Such exceptional plasticity is enabled by successive slips of partial dislocations on multiple [Formula: see text] systems, as evidenced by atomic-resolution transmission electron microscopy and first-principles and atomistic simulations. The optoelectronic performance and bandgap of the devices were unchanged. Thus, our results suggest that CsPbX3 perovskites, as potential deformable inorganic semiconductors, may have profound implications for the manufacture of advanced optoelectronics and energy systems.

Contact Engineering of Halide Perovskites: Gold is Not Good Enough; Metalloid is Better.

The operation stability of halide perovskite devices is the critical issue that impedes their commercialization. The main reasons are that the ambient H2 O molecules can easily deteriorate the perovskites, while the metal electrodes react in different degrees with the perovskites. Herein, one kind of new electrode, the metalloids, is reported, which are much more stable than the conventional noble metals as electrical contacts for halide perovskites. The degradation mechanism of halide perovskites with noble metal electrodes is carefully studied and compared with the metalloid electrodes. It is found that the iodide ions can easily halogenate Cu and Ag in halide perovskites. Although Au is almost not halogenated, it can also decompose the perovskite film. On the contrary, after long-term storage, the metalloid electrodes remain intact on the perovskite film without any degradation. In addition, the long-time operation stability of the perovskite devices with metalloid electrodes is much higher than that of noble metals. First-principles calculations confirm the exceptional stability of the metalloid electrodes.This work explores the ultra-stable electrodes for halide perovskites, paving the way to the large-scale deployment of perovskite-based electronic devices.

Van der Waals nanomesh electronics on arbitrary surfaces.

Chemical bonds, including covalent and ionic bonds, endow semiconductors with stable electronic configurations but also impose constraints on their synthesis and lattice-mismatched heteroepitaxy. Here, the unique multi-scale van der Waals (vdWs) interactions are explored in one-dimensional tellurium (Te) systems to overcome these restrictions, enabled by the vdWs bonds between Te atomic chains and the spontaneous misfit relaxation at quasi-vdWs interfaces. Wafer-scale Te vdWs nanomeshes composed of self-welding Te nanowires are laterally vapor grown on arbitrary surfaces at a low temperature of 100 °C, bringing greater integration freedoms for enhanced device functionality and broad applicability. The prepared Te vdWs nanomeshes can be patterned at the microscale and exhibit high field-effect hole mobility of 145 cm2/Vs, ultrafast photoresponse below 3 µs in paper-based infrared photodetectors, as well as controllable electronic structure in mixed-dimensional heterojunctions. All these device metrics of Te vdWs nanomesh electronics are promising to meet emerging technological demands.

Automatic Classification of Mass Shape and Margin on Mammography with Artificial Intelligence: Deep CNN Versus Radiomics.

The purpose of this study is to test the feasibility for deep CNN-based artificial intelligence methods for automatic classification of the mass margin and shape, while radiomic feature-based machine learning methods were also implemented in this study as baseline and for comparison study. In this retrospective study, 596 patients with breast mass that underwent mammography from 4 hospitals were enrolled from January 2012 to October 2019. Margin and shape of each mass were annotated according to BI-RADS by 2 experienced radiologists. Deep CNN-based AI was implemented for the classification task based on Resnet50. Balanced sampler and CBAM were also used to improve the performance of the Deep CNNs. As comparison, image texture features were extracted and then dimensionality reduction methods (such as PCA, ICA) and classical classifiers (such as SVM, DT, KNN) were used for classification task. Based on Python programming software, accuracy (ACC) was used to evaluate the performance of the model, and the model with the highest ACC value was selected. Deep CNN based on Resnet50 with balanced sampler and CBAM achieved the best performance for both margin and shape classification, with ACC of 0.838 and 0.874, respectively. For the radiomics-based machine learning, the best performance for margin was achieved as 0.676 by the combination of FA + RF, while the best performance for shape was 0.802 by the combination of PCA + MLP. The feasibility for automatic classification with coarse labeling of the mass shape and margin was testified with the deep CNN-based AI methods, while radiomic feature-based machine learning methods achieved inferior classification results.

Electrically Switchable Polarization in Bi2 O2 Se Ferroelectric Semiconductors.

Atomically 2D layered ferroelectric semiconductors, in which the polarization switching process occurs within the channel material itself, offer a new material platform that can drive electronic components toward structural simplification and high-density integration. Here, a room-temperature 2D layered ferroelectric semiconductor, bismuth oxychalcogenides (Bi2 O2 Se), is investigated with a thickness down to 7.3 nm (≈12 layers) and piezoelectric coefficient (d33 ) of 4.4 ± 0.1 pm V-1 . The random orientations and electrically dependent polarization of the dipoles in Bi2 O2 Se are separately uncovered owing to the structural symmetry-breaking at room temperature. Specifically, the interplay between ferroelectricity and semiconducting characteristics of Bi2 O2 Se is explored on device-level operation, revealing the hysteresis behavior and memory window (MW) formation. Leveraging the ferroelectric polarization originating from Bi2 O2 Se, the fabricated device exhibits "smart" photoresponse tunability and excellent electronic characteristics, e.g., a high on/off current ratio > 104 and a large MW to the sweeping range of 47% at VGS  = ±5 V. These results demonstrate the synergistic combination of ferroelectricity with semiconducting characteristics in Bi2 O2 Se, laying the foundation for integrating sensing, logic, and memory functions into a single material system that can overcome the bottlenecks in von Neumann architecture.

Au-Seeded CsPbI3 Nanowire Optoelectronics via Exothermic Nucleation.

Converting vapor precursors to solid nanostructures via a liquid noble-metal seed is a common vapor deposition principle. However, such a noble-metal-seeded process is excluded from the crystalline halide perovskite synthesis, mainly hindered by the growth mechanism shortness. Herein, powered by a spontaneous exothermic nucleation process (ΔH < 0), the Au-seeded CsPbI3 nanowires (NWs) growth is realized based on a vapor-liquid-solid (VLS) growth mode. It is energetically favored that the Au seeds are reacted with a Pb vapor precursor to form molten Au-Pb droplets at temperatures down to 212 °C, further triggering the low-temperature VLS growth of CsPbI3 NWs. More importantly, this Au-seeded process reduces in-bandgap trap states and consequently avoids Shockley-Read-Hall recombination, contributing to outstanding photodetector performances. Our work extends the powerful Au-seeded VLS growth mode to the emerging halide perovskites, which will facilitate their nanostructures with tailored material properties.

SAH-NET: Structure-Aware Hierarchical Network for Clustered Microcalcification Classification in Digital Breast Tomosynthesis.

Benign and malignant classification of clustered microcalcifications (MCs) in digital breast tomosynthesis (DBT) is an essential task in computer-aided diagnosis. However, due to the anisotropic resolution of DBT, three-dimensional (3-D) convolutional neural network (CNN)-based methods cannot extract hierarchical features efficiently. Moreover, the sparse distribution of MC points in the cluster makes it difficult for the CNN to extract discriminative structural information for classification. To comprehensively address these challenges, we propose a novel structure-aware hierarchical network (SAH-Net) for benign and malignant classification of clustered MC in a DBT volume. Specifically, the two-dimensional (2-D) group convolution is used to extract intraslice features. The one-to-one correspondence between group convolutions and slices ensures the independence of hierarchical feature extraction. Then, a partial deformable Transformer-based 3-D structural feature learning module is proposed to capture the long-range dependency between MC points in the cluster. We evaluate the proposed method on an in-house dataset with 495 clustered MCs collected from 462 DBT images. Experimental results confirm the validity of our proposed modules. The results also show that the proposed SAH-Net outperforms several other representative methods on this topic, and achieves the best classification result, with an area under the receiver operation curve (AUC) of 86.87%. The implementation of the proposed model is available at https://github.com/sunhaotian130911/SAHNet.

Correlation between Ferroptosis-Related Gene Signature and Immune Landscape, Prognosis in Breast Cancer.

Breast cancer (BC) is the most commonly diagnosed cancer and second leading cause of cancer-related death in women worldwide. Ferroptosis, an iron-dependent newly discovered mode of cell death, can be induced by lenaltinib and plays an important role in the biological behaviors of BC. Therefore, the prognostic value of ferroptosis-related genes (FRGs) in BC warrants further investigation. FRG expression profiles and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database and Gene Expression Omnibus (GEO). Immune-related pathways were found in the functional analysis. Significant differences in enrichment scores for immune cells were observed. Some patients from TCGA-BRCA were included as the training cohort. A six-gene prediction signature was constructed with the least absolute shrinkage and selection operator Cox regression. This model was validated in the rest of the TCGA-BRCA and GEO cohort. The expressions of the six FRGs were verified with real-time quantitative polymerase chain reaction and immunohistochemistry in the Human Protein Atlas. Relapse or metastasis was more likely in the high-risk group. Risk score was an independent predictor of disease-free survival. Collectively, the ferroptosis-related risk model established in this study may serve as an effective tool to predict the prognosis in BC.

One-Dimensional Atomic Chains for Ultimate-Scaled Electronics.

The continuous downscaling of semiconducting channels in transistors has driven the development of modern electronics. However, with the component transistors becoming smaller and denser on a single chip, the continued downscaling progress has touched the physical limits. In this Perspective, we suggest that the emerging one-dimensional (1D) material system involving inorganic atomic chains (ACs) that are packed by van der Waals (vdW) interactions may tackle this issue. Stemming from their 1D crystal structures and naturally terminated surfaces, 1D ACs could potentially shrink transistors to atomic-scale diameters. Also, we argue that 1D ACs with few-atom widths allow us to revisit 1D materials and uncover physical properties distinct from conventional materials. These ultrathin 1D AC materials demand substantive attention. They may bring opportunities to develop ultimate-scaled AC-based electronic, optoelectronic, thermoelectric, spintronic, memory devices, etc.

LMA-Net: A lesion morphology aware network for medical image segmentation towards breast tumors.

Breast tumor segmentation plays a critical role in the diagnosis and treatment of breast diseases. Current breast tumor segmentation methods are mainly deep learning (DL) based methods, which exacted the contrast information between tumors and backgrounds, and produced tumor candidates. However, all these methods were developed based on traditional standard convolutions, which may not be able to model various tumor shapes and extract pure information of tumors (the extracted information usually contain non-tumor information). Besides, the loss functions used in these methods mainly aimed to minimize the intra-class distances, while ignoring the influence of inter-class distances upon segmentation. In this paper, we propose a novel lesion morphology aware network to segment breast tumors in 2D magnetic resonance images (MRI). The proposed network employs a hierarchical structure that contains two stages: breast segmentation stage and tumor segmentation stage. In the tumor segmentation stage, we devise a tumor morphology aware network to incorporate pure tumor characteristics, which facilitates contrastive information extraction. Further, we propose a hybrid intra- and inter-class distance optimization loss to supervise the network, which can minimize intra-class distances meanwhile maximizing inter-class distances, hence reducing the potential false positive/negative pixels in segmentation results. Verified on a clinical 2D MRI breast tumor dataset, our proposed method achieves eminent segmentation results and outperforms state-of-the-art methods, implying that the proposed method has a good prospect for clinical use.

Mixed-Dimensional Anti-ambipolar Phototransistors Based on 1D GaAsSb/2D MoS2 Heterojunctions.

The incapability of modulating the photoresponse of assembled heterostructure devices has remained a challenge for the development of optoelectronics with multifunctionality. Here, a gate-tunable and anti-ambipolar phototransistor is reported based on 1D GaAsSb nanowire/2D MoS2 nanoflake mixed-dimensional van der Waals heterojunctions. The resulting heterojunction shows apparently asymmetric control over the anti-ambipolar transfer characteristics, possessing potential to implement electronic functions in logic circuits. Meanwhile, such an anti-ambipolar device allows the synchronous adjustment of band slope and depletion regions by gating in both components, thereby giving rise to the gate-tunability of the photoresponse. Coupled with the synergistic effect of the materials in different dimensionality, the hybrid heterojunction can be readily modulated by the external gate to achieve a high-performance photodetector exhibiting a large on/off current ratio of 4 × 104, fast response of 50 µs, and high detectivity of 1.64 × 1011 Jones. Due to the formation of type-II band alignment and strong interfacial coupling, a prominent photovoltaic response is explored in the heterojunction as well. Finally, a visible image sensor based on this hybrid device is demonstrated with good imaging capability, suggesting the promising application prospect in future optoelectronic systems.