Search

Summary: Genomics studies have detected numerous genetic alterations in esophageal squamous cell carcinoma (ESCC). However, the functions of these mutations largely remain elusive, partially due to a lack of feasible animal models. Here, we report a convenient platform with CRISPR-Cas9-mediated introduction of genetic alterations and orthotopic transplantation to generate a series of primary ESCC models in mice. With this platform, we validate multiple frequently mutated genes, including EP300, FAT1/2/4, KMT2D, NOTCH2, and TGFBR2, as tumor-suppressor genes in ESCC. Among them, TGFBR2 loss dramatically promotes tumorigenesis and multi-organ metastasis. Paradoxically, TGFBR2 deficiency leads to Smad3 activation, and disruption of Smad3 partially restrains the progression of Tgfbr2-mutated tumors. Drug screening with tumor organoids identifies that pinaverium bromide represses Smad3 activity and restrains Tgfbr2-deficient ESCC. Our studies provide a highly efficient platform to investigate the in vivo functions of ESCC-associated mutations and develop potential treatments for this miserable malignancy.

This paper presents a high-efficiency piezoelectric energy harvesting and management circuit utilizing a full-bridge rectifier (FBR) designed for powering wireless sensor nodes. The circuit comprises a rectifier bridge, a fully CMOS-based reference source, and an energy management system. The rectifier bridge uses a PMOS cross-coupled structure to greatly reduce the conduction voltage drop. The CMOS reference source provides the necessary reference voltage and current. The energy management system delivers a stable 1.8 V to the load and controls its operation in intermittent bursts. Fabricated with a 110 nm CMOS process, the circuit occupies an area of 0.6 mm2, and is housed in a QFN32 package. Test results indicate that under 40 Hz frequency and 4 g acceleration vibrations, the chip’s energy extraction power reaches 234 μW, with the load operating every 3 s at a supply voltage of 1.8 V. Thus, this FBR interface circuit efficiently harnesses the energy output from the piezoelectric energy harvester.

Objective The Early Cambrian superlarge rare earth-rich phosphate deposit in Xinhua, Zhijin County, Guizhou Province, is a typical marine sedimentary deposit. There have long been controversial on the mineralisation environment and mineralisation mechanism. Methods In this paper, the sedimentary environment and formation mechanism of the phosphorus-bearing rock series in the Gezhongwu Formation are verified, through the study of the microscopic characteristics of phosphorus-bearing rock series rocks or ores and the evidence of elemental geochemistry. Results This study reveal the regular changes in the structure of phosphorite from the bottom up of the phosphorous-bearing rock series: the grain sizes decreasing; the interstitial materials between grains vary from bright dolomite cement to micritic matrix, such as siliceous and collophanite, followed by bright dolomite cement and finally micrite collophanite and siliceous. The cementation mode has mainly converted from pore cementation to pore-based cementation, and the supports change from grain to grain-matrix supports. Moreover, the single layers of the rocks become thinner and darker, and the development of staggered bedding was decreased. Conclusion These characteristics reflect that the sedimentary environment of the phosphorus-bearing rock series is a subtidal zone with strong hydrodynamic forces, and of the upper section has sedimentary depths higher and hydrodynamic conditions slightly weaker than those of the lower section. The significant negative Ce anomalies (δCe between 0.32-0.39) and low Ni/Co (0.98-6.07) and V/Cr ratios (0.57-12.50) of the phosphorus-bearing rock series show that the sedimentary water had oxidation characteristics similar to those of a modern marine environment. The lower 103·Sr/Ca(2.00-3.38) and 1/Σ(Al2O3+TiO2) ratios (0.57-3.45) indicate that the ancient water depth was generally shallow, but the relative depth changed frequently. The distribution characteristics of Fe, Cu and Ba contents indicate that the palaeoproductivity of carbonate in the lower section is higher than that in the upper section. In the palaeoenvironment where various conditions are coupled, the phosphorite was finally enriched and formed by precipitation-stirring-subdivision-cementation-solidification.

Objective A set of black rock series rich in organic matter developed in the Yangtze Plate of China in the Early Cambrian. Methods To explore the main controlling factors affecting the enrichment of organic matter, the samples of the Niutitang Formation in Bahuang, Tongren Guizhou Province were tested for total organic carbon (TOC), major, trace and rare earth elements. Results The results show that the organic carbon content of the black rock series show a trend of high→low→high from bottom→lower middle→upper. The redox indexes Ni/Co, V/Cr, V/(V+Ni) and U/Th and the index Mo/TOC for determining the retention degree of water in the basin indicate that the carbonaceous shale and polymetallic element shale rich in organic matter at the bottom and upper part of the Niutitang Formation are formed in oxygen-poor to anoxic, medium to strong limited retention environments. The lower middle phosphate rock layer is formed in oxygen-poor to oxygen-rich, medium retention sedimentary environment. The δCe shows that the study area experienced a process of transgression regression in the Early Cambrian. Babio reveals the high paleoproductivity at the bottom and upper part of the Niutitang Formation and the medium to high paleoproductivity at the lower-middle part. The Ti/Al indicates weak terrigenous input as a whole. Rare earth distribution mode, δEu anomaly and La/Yb-REE diagram show that the phosphorus ore bed and metal-rich shale are affected by hydrothermal activity, which brings rich nutrients and reducing sedimentary environment for the enrichment of organic matter in metal rich shale. The phosphorus ore bed was formed in the period of sea level rise, and the upwelling of ocean currents led to the oxygenation of the sedimentary environment, which was not conducive to the preservation of organic matter. Therefore, the content of organic matter in the lower middle phosphorus-bearing formation is low. Conclusion The key factor restricting the enrichment of organic matter in the black rock series of the Niutitang Formation is the generally reducing and retained sedimentary environment, and the medium-high paleoproductivity is an important basis for the enrichment of organic matter. Hydrothermal activity creates favorable conditions for the enrichment of organic matter in local strata (polymetallic enrichment layer), and terrigenous clastic input has little impact on the enrichment of organic matter. The rise in sea level is an unfavorable factor for the enrichment of organic matter. It is the "comprehensive model" under the joint action of multiple factors that control the enrichment of organic matter in the black rock series of the Niutitang Formation.

A novel low-power MOS-only voltage reference is presented. The Enz–Krummenacher–Vittoz (EKV) model is adopted to provide a new perspective on the operating principle. The normalized charge density, introduced as a new variable, serves as an indicator when trimming the output temperature coefficient. The proposed voltage reference consists of a specific current generator and a 5-bit trimmable load. Thanks to the good match between the current source stage and the output stage, the nonlinear temperature dependence of carrier mobility is automatically canceled out. The circuit is designed using 55 nm COMS technology. The operating temperature ranges from −40 °C to 120 °C. The average temperature coefficient of the output voltage can be reduced to 21.7 ppm/°C by trimming. The power consumption is only 23.2 nW with a supply voltage of 0.8 V. The line sensitivity and the power supply rejection ratio at 100 Hz are 0.011 %/V and −89 dB, respectively.

In this paper, an event-driven wireless sensor node is proposed and demonstrated. The primary design objective is to devise a wireless sensor node with miniaturization, integration, and high-accuracy recognition ability. The proposed wireless sensor node integrates two vibration-threshold-triggered energy harvesters that sense and power a threshold voltage control circuit for power management, a microcontroller unit (MCU) for system control, a one-dimensional convolutional neural network (1D-CNN) environment data analysis and vibration events distribution, and a radio frequency (RF) digital baseband transmitter with IEEE 802.15.4-/.6 protocols. The dimensions of the wireless sensor node are 4 × 2 × 1 cm3. Finally, the proposed wireless sensor node was fabricated and tested. The alarming time for detecting the vibration event is less than 6 s. The measured recognition accuracy of three events (knock, shake, and heat) is over 97.5%. The experimental results showed that the proposed integrated wireless sensor node is very suitable for wireless environmental monitoring systems.

Efficient and effective radar emitter recognition is critical for electronic support measurement (ESM) systems. However, in complex electromagnetic environments, intercepted pulse trains generally contain substantial data noise, including spurious and missing pulses. Currently, radar emitter recognition methods utilizing traditional artificial neural networks (ANNs) like CNNs and RNNs are susceptible to data noise and require intensive computations, posing challenges to meeting the performance demands of modern ESM systems. Spiking neural networks (SNNs) exhibit stronger representational capabilities compared to traditional ANNs due to the temporal dynamics of spiking neurons and richer information encoded in precise spike timing. Furthermore, SNNs achieve higher computational efficiency by performing event-driven sparse addition calculations. In this paper, a lightweight spiking neural network is proposed by combining direct coding, leaky integrate-and-fire (LIF) neurons, and surrogate gradients to recognize radar emitters. Additionally, an improved SNN for radar emitter recognition is proposed, leveraging the local timing structure of pulses to enhance adaptability to data noise. Simulation results demonstrate the superior performance of the proposed method over existing methods.