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Cystic lymphangioma (CL) is a rare benign tumor of the lymphatic system, most commonly found in the neck, head, and armpits. The incidence of lymphangiomas in the abdominal cavity is less than 5%, and the incidence of retroperitoneal tumors is even lower. We report here a case of recurrent giant CL that recurred 20 years after the first complete surgical resection. Pelvic MRI at 6 months follow-up after the second complete surgical resection indicated a recurrence of the tumor. The main purpose of this article is to explore the treatment and follow-up strategies for recurrent lymphangioma.

Abstract Neural circuits with specific structures and diverse neuronal firing features are the foundation for supporting intelligent tasks in biology and are regarded as the driver for catalyzing next-generation artificial intelligence. Emulating neural circuits in hardware underpins engineering highly efficient neuromorphic chips, however, implementing a firing features-driven functional neural circuit is still an open question. In this work, inspired by avoidance neural circuits of crickets, we construct a spiking feature-driven sensorimotor control neural circuit consisting of three memristive Hodgkin-Huxley neurons. The ascending neurons exhibit mixed tonic spiking and bursting features, which are used for encoding sensing input. Additionally, we innovatively introduce a selective communication scheme in biology to decode mixed firing features using two descending neurons. We proceed to integrate such a neural circuit with a robot for avoidance control and achieve lower latency than conventional platforms. These results provide a foundation for implementing real brain-like systems driven by firing features with memristive neurons and put constructing high-order intelligent machines on the agenda.

BackgroundCancer is widely recognized as a prominent contributor to global mortality due to factors such as delayed diagnosis, unfavorable prognosis, and high likelihood of recurrence. FGD5 transcription factor G antisense RNA 1(FGD5-AS1), a newly identified long non-coding RNA, has emerged as a promising prognostic biomarker, for malignancy prognosis. This meta-analysis aimed to assess the prognostic significance of FGD5-AS1 in various carcinomas.MethodsA systematic search was performed through five electronic databases to identify studies that investigating the role of FGD5-AS1 expression as a prognostic factor in carcinomas. The value of FGD5-AS1 in malignancies was estimated by odds ratios (ORs) and hazard ratios (HRs) with a corresponding 95% confidence intervals (CIs). Furthermore, the GEPIA database was used to further supplement our results.ResultsThis analysis included 12 studies with 642 cases covering eight cancer types. High FGD5-AS1 expression exhibited a significant correlation with poor overall survival(OS) (HR = 2.04, 95%CI [1.72, 2.42], P < 0.00001), advanced tumor stage (OR = 3.47, 95%CI [2.34, 5.14], P < 0.00001), lymph node metastasis(LNM) (OR = 1.79, 95% CI [1.20,2.67], P = 0.004), and larger tumor size (OR= 5.25, 95%CI [2.68, 10.30], P < 0.00001). Furthermore, the FGD5-AS1 expression was notably upregulated in six types of malignancies as verified using the GEPIA online gene analysis tool.ConclusionsThe findings of this meta-analysis indicated that high FGD5-AS1 expression was significantly associated with poor prognosis in diverse cancer types, suggesting that FGD5-AS1 may be a promising biomarker for predicting cancer prognosis.Systematic review registrationhttps://www.york.ac.uk/inst/crd, identifier CRD42024552582.

The scalability of neuromorphic devices depends on the dismissal of capacitors and additional circuits. Here Liu et al. report an artificial neuron based on the polarization and depolarization of an anti-ferroelectric film, avoiding additional elements and reaching 37 fJ/spike of power consumption.

Background: With the increasing number of new cancer cases and mortality rates, cancer has become a serious global health problem, but there are no ideal cancer biomarkers for effective diagnosis. Currently, mounting evidence demonstrates that lncRNAs play a fundamental role in cancer progression. BBOX1 anti-sense RNA 1 (BBOX1-AS1) is a recently clarified lncRNA and has been identified as dysregulated in various carcinomas, and it contributes to poor survival in cancer patients.Methods: We thoroughly searched six databases for eligible articles published as of 27, April 2023. The association of BBOX1-AS1 expression levels with prognostic and clinicopathological parameters was assessed by odds ratios (OR) and hazard ratios with 95% CIs. Additionally, we further validated our results utilizing the GEPIA online database.Results: Eight studies comprising 602 patients were included in this analysis. High BBOX1-AS1 expression indicated poor overall survival (OS) (hazard ratios = 2.30, 95% Cl [1.99, 2.67], p < 0.00001) when compared with low BBOX1-AS1 expression. Furthermore, BBOX1-AS1 expression was positively correlated with lymph node metastasis (OR = 3.00, 95% CI [1.71–5.28], p = 0.0001) and advanced tumor stage (OR = 3.74, 95% CI [2.63–5.32], p < 0.00001) for cancer patients. Moreover, BBOX1-AS1 was remarkably upregulated in 12 malignancies, and the elevated BBOX1-AS1 expression predicted poorer OS and worse disease-free survival (DFS) confirmed through the GEPIA online gene analysis tool.Conclusion: The findings highlight that BBOX1-AS1 was significantly associated with detrimental overall survival, disease-free survival, lymph node metastasis and tumor stage; thus, it could act as a novel promising biomarker to predict the clinicopathological characteristics and prognosis for various cancers.

Peripheral nerve compression or permanent damage of central nervous system (CNS) can trigger severe neuralgia to patients. Analgesic medicine or even surgery to remove nerve compression is commonly used for pain relief. But these treatments either are ineffective, have side-effect or can cause subsequent complications. Acupuncture, a technique that has been widely used in China and other Asian countries for thousands of years, is an alternative to relieve pain, although the mechanism of action is not fully understood. In this study, two patients who had symptoms of severe neuralgia associated with peripheral nerve compression or permanent damage/dysfunction of CNS and analgesic medicines are ineffective, underwent cheek acupuncture, a new technique established recent years by the author with the features of painless, standardization, simplicity, and precision. An immediate analgesic effect of the cheek acupuncture was observed without any side effects, and clinical remission was achieved after several sessions of treatments. It suggests that this new approach is an efficient alternative for pain relief induced by nerve impairment. The authors proposed a biological holographic model of triplet homunculi existing at the level of the local cheek, spinal cord, and cerebral cortex, to explain the immediate and accurate analgesic effect of the cheek acupuncture. These homunculi have the same structure, and synchronized sensations and actions that are mediated by afferent and efferent neurons, as the integrated human body. Therefore, the nociception and needling signals are sensed, transmitted, analyzed, and manipulated cooperatively and simultaneously among these homunculi with the subsequent pain relief in the body.

Conventional machine vision systems suffer from great data latency and energy consumption in cognitive tasks due to the separated vision sensors, memory units, and processors. In‐sensor computing based on optoelectronic synapses allows efficient computation by directly sensing and processing optical signals. Herein, an optoelectronic synapse based on Au/ZnO:N/IGZO/TiN structure is proposed. It shows uniform optical SET and electrical RESET behaviors, with various light‐tunable plasticity. Furthermore, a 4‐bit reservoir is experimentally implemented on the device, which is ideal to construct in‐sensor reservoir computing (RC) system. By converting spatiotemporal optical signals to higher dimensional feature space, in‐sensor RC has a great advantage in processing sequential visual information. Simulation results demonstrate that the in‐sensor RC system based on the proposed synapse achieves a considerable recognition accuracy (90.45%) for the MNIST dataset with very limited 36‐30‐10 perceptron network, and a 97.14% accuracy for human action classification from sequential vision data based on the Weizmann dataset. This work proves the low training cost and great efficiency for processing spatiotemporal and sequential optical signals, which may pave a new way for future machine vision applications.

The human visual system plays the most important role in information perception. Inspired by its structure and processing mechanism, novel optoelectronic memristor‐based artificial visual systems have emerged, thanks to the advantages of time latency and energy efficiency. However, the established systems lack a complete hardware supporting system to demonstrate the potential of large‐scale integration. Herein for the first time, a gate multiplexing architecture for optical signal sensor and memory integration is proposed, which can achieve multivalue storage of 3‐bit optical signal in the analog domain. Based on this novel structure, an artificial visual sensor and memory system (AVSMS) is implemented with a 5 × 6 photodiode array, an I/V conversion circuit, and a 32 × 32 1T1R memristor array for image sensor and memory integration. Furthermore, a parallel pipeline storage strategy is proposed to enable AVSMS to store 32 images with a size of 5 × 6 pixels and 3‐bit grayscale without erasing operation and achieve an ideal frame rate of more than 60 000 frames per second for high‐speed storage. Experimental results demonstrate that AVSMS can directly eliminate repeated background information in sequential images through peripheral hardware circuitry. The AVSMS provides a promising hardware solution for large‐scale image sensor and memory integration in artificial visual systems.

Brain computer interface (BCI) is a promising way for automatic driving and exploring brain functions. As the number of electrodes for electroencephalogram (EEG) acquisition continues to grow, the signal processing capabilities of BCI are facing challenges. Considering the bottlenecks of the Von Neumann architecture, it is increasingly difficult for the traditional digital computing pattern to meet the requirements of the EEG signal processing in terms of power consumption and efficiency. Here, we propose a 1T1R array-based EEG signal analysis system in which the biological likelihood of the memristor is used to efficiently analyze signals in the simulated domain. The identification and classification of EEG signals are achieved experimentally using the memristor array with an average recognition rate of 89.83%. The support vector machine classification implemented by the memristor crossbar array provides a 34.4 times improvement in power efficiency compared to the complementary metal oxide semiconductor-based support vector machine classifier. This work provides new ideas for the application of memristors in BCI.

Memristor is a potential basic unit for the in‐memory computing system, which is an approach to break the memory wall of the traditional computer. However, low switching speed, nonuniform device characteristics, and inefficient logic synthesis hinder the development of memristor‐based in‐memory computing. Herein, a novel Cu/α‐Si/α‐C/Pt memristor and direct resistance‐coupling logic synthesis scheme to construct high‐efficiency in‐memory computing is presented. The memristor shows excellent uniformity of low/high resistance (relative dispersion σ/μ = 4.68% and 3.28%) and SET/RESET voltage (relative dispersion σ/μ = 3.24% and 5.85%), fast switching speed (≈30 ns), good endurance (>108), and long retention (>105 s at 100 °C). Complete set of Boolean logic and some derived logic operators are efficiently implemented in the Cu/α‐Si/α‐C/Pt crossbar array. Furthermore, the reconfigurable and parallel logic synthesis is experimentally demonstrated by one‐bit full adder and parallel copy operation. This work can greatly improve the logic computing efficiency and flexibility in the memristor crossbar array.

True random number generator (TRNG) is a critical component in hardware security that is increasingly important in the era of mobile computing and internet of things. A memristor is a promising candidate to construct a TRNG due to its intrinsic variability of switching behavior and high-density integration. Here, we present a 1T1R oscillation structure with a TiN/NbOx/Pt memristor for constructing a rate-adjustable TRNG. The randomness of the oscillation comes from the stochastic switch latency of the memristor. The experimental results demonstrate that the oscillation rate can be modulated by changing the gate bias of the transistor in series. Furthermore, a TRNG circuit with adjustable rates is constructed based on the 1T1R oscillation, and the simulated results revealed that the proposed TRNG output can pass eight NIST tests, indicating the true randomness of the circuit. Finally, the randomness in the memristor, the adjustable rate of the 1T1R oscillation, and the NIST test result of RNG are proved in turn. These results demonstrate the feasibility of the circuit, which can minimize the power consumption by adjusting the random number generation rate to correct the frequency drift caused by extrinsic factors, such as environment temperature and humidity.

The excellent properties of nanomaterials have been confirmed in many fields, but their effects on plants are still unclear. In this study, different concentrations of bismuth vanadate (BV) were added to the growth medium to analyze the growth of seedlings, including taproots, lateral roots, leaf stomata, root activity, and superoxide anion O2.- generation. Gene expression levels related to root growth were determined by quantitative PCR in Arabidopsis thaliana. The results showed that BV promoted the growth of taproots and the development of lateral roots, enhanced the length of the extension zone in roots, increased the number and size of leaf stomata and root activity, reduced the accumulation of ROS in seedlings, and changed the expression levels of genes related to polyamines or hormones. At the same time, we investigated the antibacterial activity of BV against a variety of common pathogens causing crop diseases. The results showed that BV could effectively inhibit the growth of Fusarium wilt of cotton and rice sheath blight. These results provide a new prospect for the development of nanomaterial-assisted plants, which is expected to become one of the ways to solve the problem of controlling and promoting the development of plants. At the same time, it also provides a reference for the study of the effect of BV on plants.

In all organisms, splicing occurs through the formation of spliceosome complexes, and splicing auxiliary factors are essential during splicing. U2AF65 is a crucial splicing cofactor, and the two typical RNA-recognition motifs at its center recognize and bind the polypyrimidine sequence located between the intron branch site and the 3′-splice site. U2AF65A is a member of the U2AF65 gene family, with pivotal roles in diseases in mammals, specifically humans; however, few studies have investigated plant U2AF65A, and its specific functions are poorly understood. Therefore, in the present study, we systematically identified U2AF65A in plant species from algae to angiosperms. Based on 113 putative U2AF65A sequences from 33 plant species, phylogenetic analyses were performed, followed by basic bioinformatics, including the comparisons of gene structure, protein domains, promoter motifs, and gene expression levels. In addition, using rice as the model crop, we demonstrated that the OsU2AF65A protein is localized to the nucleus and cytoplasm, and it is involved in responses to various stresses, such as drought, high salinity, low temperature, and heavy metal exposure (e.g., cadmium). Using Arabidopsis thaliana and rice mutants, we demonstrated that U2AF65A is involved in the accumulation of plant biomass, growth of hypocotyl upon thermal stimulation, and reduction of tolerance of high temperature stress. These findings offer an overview of the U2AF65 gene family and its stress response functions, serving as the reference for further comprehensive functional studies of the essential specific splicing cofactor U2AF65A in the plant kingdom.

This essay explores the clinical application of cheek acupuncture in pain management, positioning it as a novel branch within acupuncture. Similar to established techniques like head, facial, hand, and foot acupuncture, cheek acupuncture operates as a micro-needle diagnostic and therapeutic system, projecting a holographic image of the human body around the cheeks and their vicinity. Over 10000 human trials have validated its efficacy, with clinical observations on 630 pain patients demonstrating rapid and reliable results. Remarkably, cheek acupuncture's effectiveness extends beyond East Asian populations to individuals of diverse racial backgrounds, suggesting broad applicability. Immediate pain relief efficacy reached 72.5%, with an overall effective rate of 86.9% in treating various pain types. Advantages such as easy point selection, rapid effects, and wide-ranging indications make cheek acupuncture a promising modality in pain management. Despite promising results, further exploration and documentation are needed to fully understand its potential across different diseases and populations. [ABSTRACT FROM AUTHOR]

To explore the restraining effect of baicalein and the mitogen-activation protein kinase kinase inhibitor, U0126, on human cervical cell line HeLa proliferation, apoptosis and migration. HeLa cells were treated by different concentrations of baicalein or U0126. A Cell Counting Kit (CCK)-8 assay was applied to examine cell viability. Flow cytometry was used to determine cell cycle and apoptosis. A wound healing assay was performed to detect cell migration. A terminal deoxynucleotidyl transferase dUTP nick end labeling assay was adopted to test cell apoptosis. Reverse transcription-quantitative polymerase chain reaction and western blot analysis was used to detect apoptosis gene and protein expression. CCK-8 assay demonstrated that baicalein and U0126 suppressed HeLa cell viability by dose dependence. TUNEL, Annexin V-fluorescein isothiocyanate/propidium iodide, and ratio of Bcl-2-associated X protein and B cell lymphoma 2 indicated that baicalein and U0126 induced HeLa cell apoptosis. Flow cytometry revealed that baicalein blocked the cell cycle of HeLa in G0/G1 phase. A wound healing assay demonstrated that baicalein significantly inhibited HeLa cell migration compared with control. Baicalein and U0126 markedly downregulated extracellular signal-regulated kinase 1/2, matrix metalloproteinase (MMP) 2 and MMP9 levels both in mRNA and protein. In the present study, the authors demonstrated that baicalein and U0126 may be used in cervical cancer treatment by inhibiting cell migration and inducing cell apoptosis. [ABSTRACT FROM AUTHOR]