Cyclo-farnesyl Diphosphate-Dependent Prenylation in Fungi.

A conserved two-gene cassette in fungi was discovered by genome mining, which encodes a UbiA family intramembrane prenyltansferase (VviA) and a haloacid dehalogenase-like hydrolase family terpene cyclase (VviB), respectively. A series of in vivo and in vitro investigations revealed that VviA exclusively uses VviB-synthesized drim-8-ene diphosphate (cyclo-farnesyl diphosphate) as the native prenyl donor to catalyze prenylation on d-mannitol, showcasing a previously unidentified function of UbiA-type prenyltransferases and a new prenylation manner in fungi.

Mental health concerns during pregnancy associated with the risk of preterm birth: A retrospective cohort study.

BACKGROUNDS: There are multiple risk factors for preterm birth (PTB), one of the most important of which is mood disorders during pregnancy. We aimed to comprehensively investigate the association of both total mental health concerns and ten specific psychiatric symptoms with PTB risk. METHODS: A cohort study was performed consisting of 25,175 pregnant women who participated in Women and Children's Hospital of Chongqing Medical University between 2020 and 2022. The Symptom Checklist 90 (SCL-90) was utilized to assess the psychiatric symptoms. Multivariable or multinomial logistic regression was applied to investigate mental health concerns associated with risk of PTB or its different clinical sub-categories, respectively. Sensitivity analyses were further performed to validate the results. RESULTS: 8336 women who met the inclusion criteria were included; of these, 547 (6.6 %) had preterm deliveries, and 2542 (30.5 %) had mental health concerns. Compared with women with healthy minds, women with total mental health concerns had a 29.0 % higher risk of overall PTB (OR = 1.28, 95%CI = 1.07-1.54), medical-induced PTB (OR = 1.49, 95%CI = 1.05-2.13) and spontaneous PTB with premature rupture of membranes (OR = 1.33, 95%CI = 1.01-1.74). As to the specific psychological symptoms, hostility pregnant women had a 55.0 % higher risk of PTB (OR = 1.55, 95%CI = 1.14-2.11). Similar results were observed in most of the sensitivity analyses. LIMITATIONS: This is a single-center study, thus the extrapolation of the results may be limited. CONCLUSIONS: Pregnant women with mental health symptoms, especially hostility, have an increased risk of PTB. The findings underscore that integrating mental health services into routine maternal care may be a strategy to prevent PTB.

An Active-Matrix Synaptic Phototransistor Array for In-Sensor Spectral Processing.

The human retina perceives and preprocesses the spectral information of incident light, enabling fast image recognition and efficient chromatic adaptation. In comparison, it is reluctant to implement parallel spectral preprocessing and temporal information fusion in current complementary metal-oxide-semiconductor (CMOS) image sensors, requiring intricate circuitry, frequent data transmission, and color filters. Herein, an active-matrix synaptic phototransistor array (AMSPA) is developed based on organic/inorganic semiconductor heterostructures. The AMSPA provides wavelength-dependent, bidirectional photoresponses, enabling dynamic imaging and in-sensor spectral preprocessing functions. Specifically, near-infrared light induces inhibitory photoresponse while UV light results in exhibitory photoresponse. With rational structural design of the organic/inorganic hybrid heterostructures, the current dynamic range of phototransistor is improved to over 90 dB. Finally, a 32 × 64 AMSPA (128 pixels per inch) is demonstrated with one-switch-transistor and one-synaptic phototransistor (1-T-1-PT) structure, achieving spatial chromatic enhancement and temporal trajectory imaging. These results reveal the feasibility of AMSPA for constructing artificial vision systems.

Application of radio frequency energy in processing of fruit and vegetable products.

Thermal processing is commonly employed to ensure the quality and extend the shelf-life of fruits and vegetables. Radio frequency (RF) heating has been used as a promising alternative treatment to replace conventional thermal processing methods with advantages of rapid, volumetric, and deep penetration heating characteristics. This article provides comprehensive information regarding RF heating uniformity and applications in processing of fruit and vegetable products, including disinfestation, blanching, drying, and pasteurization. The dielectric properties of fruits and vegetables and their products have also been summarized. In addition, recommendations for future research on RF heating are proposed to enhance practical applications for fruits and vegetables processing in future.

Wearable and Multiplexed Biosensors based on Oxide Field-Effect Transistors.

Wearable sensors designed for continuous, non-invasive monitoring of physicochemical signals are important for portable healthcare. Oxide field-effect transistor (FET)-type biosensors provide high sensitivity and scalability. However, they face challenges in mechanical flexibility, multiplexed sensing of different modules, and the absence of integrated on-site signal processing and wireless transmission functionalities for wearable sensing. In this work, a fully integrated wearable oxide FET-based biosensor array is developed to facilitate the multiplexed and simultaneous measurement of ion concentrations (H+, Na+, K+) and temperature. The FET-sensor array is achieved by utilizing a solution-processed ultrathin (≈6 nm thick) In2O3 active channel layer, exhibiting high compatibility with standard semiconductor technology, good mechanical flexibility, high uniformity, and low operational voltage of 0.005 V. This work provides an effective method to enable oxide FET-based biosensors for the fusion of multiplexed physicochemical information and wearable health monitoring applications.

An Ion-Mediated Spiking Chemical Neuron based on Mott Memristor.

Artificial spiking neurons capable of interpreting ionic information into electrical spikes are critical to mimic biological signaling systems. Mott memristors are attractive for constructing artificial spiking neurons due to their simple structure, low energy consumption, and rich neural dynamics. However, challenges remain in achieving ion-mediated spiking and biohybrid-interfacing in Mott neurons. Here, a biomimetic spiking chemical neuron (SCN) utilizing an NbOx Mott memristor and oxide field-effect transistor-type chemical sensor is introduced. The SCN exhibits both excitation and inhibition spiking behaviors toward ionic concentrations akin to biological neural systems. It demonstrates spiking responses across physiological and pathological Na+ concentrations (1-200 × 10-3 m). The Na+-mediated SCN enables both frequency encoding and time-to-first-spike coding schemes, illustrating the rich neural dynamics of Mott neuron. In addition, the SCN interfaced with L929 cells facilitates real-time modulation of ion-mediated spiking under both normal and salty cellular microenvironments.

An artificial visual neuron with multiplexed rate and time-to-first-spike coding.

Human visual neurons rely on event-driven, energy-efficient spikes for communication, while silicon image sensors do not. The energy-budget mismatch between biological systems and machine vision technology has inspired the development of artificial visual neurons for use in spiking neural network (SNN). However, the lack of multiplexed data coding schemes reduces the ability of artificial visual neurons in SNN to emulate the visual perception ability of biological systems. Here, we present an artificial visual spiking neuron that enables rate and temporal fusion (RTF) coding of external visual information. The artificial neuron can code visual information at different spiking frequencies (rate coding) and enables precise and energy-efficient time-to-first-spike (TTFS) coding. This multiplexed sensory coding scheme could improve the computing capability and efficacy of artificial visual neurons. A hardware-based SNN with the RTF coding scheme exhibits good consistency with real-world ground truth data and achieves highly accurate steering and speed predictions for self-driving vehicles in complex conditions. The multiplexed RTF coding scheme demonstrates the feasibility of developing highly efficient spike-based neuromorphic hardware.

Abnormal functional connectivity of white-matter networks and gray-white matter functional networks in patients with NMOSD.

Cognitive impairment (CI) has been reported in 29-70% of patients with neuromyelitis optica spectrum disorder (NMOSD). Abnormal white matter (WM) functional networks that correlate with cognitive functions have not been studied well in patients with NMOSD. The aim of the current study was to investigate functional connectivity (FC), spontaneous activity, and functional covariance connectivity (FCC) abnormalities of WM functional networks in patients with NMOSD and their correlation with cognitive performance. Twenty-four patients with NMOSD and 24 healthy controls (HCs) were included in the study. Participants underwent brain resting-state functional magnetic resonance imaging (fMRI) and the Montreal Cognitive Assessment (MoCA). Eight WM networks and nine gray matter (GM) networks were created. In patients, WM networks, including WM1-4, WM1-8, WM2-6, WM2-7, WM2-8, WM4-8, WM5-8 showed reduced FC (P < 0.05). All WM networks except WM1 showed decreased spontaneous activity (P < 0.05). The major GM networks demonstrated increased/decreased FC (P < 0.05), whereas GM7-WM7, GM8-WM4, GM8-WM6 and GM8-WM8 displayed decreased FC (P < 0.05). The MoCA results showed that two-thirds (16/24) of the patients had CI. FC and FCC in WM networks were correlated negatively with the MoCA scores (P < 0.05). WM functional networks are multi-layered. Abnormal FC of WM functional networks and GM functional networks may be responsible for CI.

MAFE-Net: retinal vessel segmentation based on a multiple attention-guided fusion mechanism and ensemble learning network.

The precise and automatic recognition of retinal vessels is of utmost importance in the prevention, diagnosis and assessment of certain eye diseases, yet it brings a nontrivial uncertainty for this challenging detection mission due to the presence of intricate factors, such as uneven and indistinct curvilinear shapes, unpredictable pathological deformations, and non-uniform contrast. Therefore, we propose a unique and practical approach based on a multiple attention-guided fusion mechanism and ensemble learning network (MAFE-Net) for retinal vessel segmentation. In conventional UNet-based models, long-distance dependencies are explicitly modeled, which may cause partial scene information loss. To compensate for the deficiency, various blood vessel features can be extracted from retinal images by using an attention-guided fusion module. In the skip connection part, a unique spatial attention module is applied to remove redundant and irrelevant information; this structure helps to better integrate low-level and high-level features. The final step involves a DropOut layer that removes some neurons randomly to prevent overfitting and improve generalization. Moreover, an ensemble learning framework is designed to detect retinal vessels by combining different deep learning models. To demonstrate the effectiveness of the proposed model, experimental results were verified in public datasets STARE, DRIVE, and CHASEDB1, which achieved F1 scores of 0.842, 0.825, and 0.814, and Accuracy values of 0.975, 0.969, and 0.975, respectively. Compared with eight state-of-the-art models, the designed model produces satisfactory results both visually and quantitatively.

Enabling low-drift flexible perovskite photodetectors by electrical modulation for wearable health monitoring and weak light imaging.

Metal halide perovskites are promising for next-generation flexible photodetectors owing to their low-temperature solution processability, mechanical flexibility, and excellent photoelectric properties. However, the defects and notorious ion migration in polycrystalline metal halide perovskites often lead to high and unstable dark current, thus deteriorating their detection limit and long-term operations. Here, we propose an electrical field modulation strategy to significantly reduce the dark current of metal halide perovskites-based flexible photodetector more than 1000 times (from ~5 nA to ~5 pA). Meanwhile, ion migration in metal halide perovskites is effectively suppressed, and the metal halide perovskites-based flexible photodetector shows a long-term continuous operational stability (~8000 s) with low signal drift (~4.2 × 10-4 pA per second) and ultralow dark current drift (~1.3 × 10-5 pA per second). Benefitting from the electrical modulation strategy, a high signal-to-noise ratio wearable photoplethysmography sensor and an active-matrix photodetector array for weak light imaging are successfully demonstrated. This work offers a universal strategy to improve the performance of metal halide perovskites for wearable flexible photodetector and image sensor applications.

Multitarget-Tracking Method Based on the Fusion of Millimeter-Wave Radar and LiDAR Sensor Information for Autonomous Vehicles.

Multitarget tracking based on multisensor fusion perception is one of the key technologies to realize the intelligent driving of automobiles and has become a research hotspot in the field of intelligent driving. However, most current autonomous-vehicle target-tracking methods based on the fusion of millimeter-wave radar and lidar information struggle to guarantee accuracy and reliability in the measured data, and cannot effectively solve the multitarget-tracking problem in complex scenes. In view of this, based on the distributed multisensor multitarget tracking (DMMT) system, this paper proposes a multitarget-tracking method for autonomous vehicles that comprehensively considers key technologies such as target tracking, sensor registration, track association, and data fusion based on millimeter-wave radar and lidar. First, a single-sensor multitarget-tracking method suitable for millimeter-wave radar and lidar is proposed to form the respective target tracks; second, the Kalman filter temporal registration method and the residual bias estimation spatial registration method are used to realize the temporal and spatial registration of millimeter-wave radar and lidar data; third, use the sequential m-best method based on the new target density to find the track the correlation of different sensors; and finally, the IF heterogeneous sensor fusion algorithm is used to optimally combine the track information provided by millimeter-wave radar and lidar, and finally form a stable and high-precision global track. In order to verify the proposed method, a multitarget-tracking simulation verification in a high-speed scene is carried out. The results show that the multitarget-tracking method proposed in this paper can realize the track tracking of multiple target vehicles in high-speed driving scenarios. Compared with a single-radar tracker, the position, velocity, size, and direction estimation errors of the track fusion tracker are reduced by 85.5%, 64.6%, 75.3%, and 9.5% respectively, and the average value of GOSPA indicators is reduced by 19.8%; more accurate target state information can be obtained than a single-radar tracker.

Functional Changes of White Matter Are Related to Human Pain Sensitivity during Sustained Nociception.

Pain is considered an unpleasant perceptual experience associated with actual or potential somatic and visceral harm. Human subjects have different sensitivity to painful stimulation, which may be related to different painful response pattern. Excellent studies using functional magnetic resonance imaging (fMRI) have found the effect of the functional organization of white matter (WM) on the descending pain modulatory system, which suggests that WM function is feasible during pain modulation. In this study, 26 pain sensitive (PS) subjects and 27 pain insensitive (PIS) subjects were recruited based on cold pressor test. Then, all subjects underwent the cold bottle test (CBT) in normal (26 degrees temperature stimulating) and cold (8 degrees temperature stimulating) conditions during fMRI scan, respectively. WM functional networks were obtained using K-means clustering, and the functional connectivity (FC) was assessed among WM networks, as well as gray matter (GM)-WM networks. Through repeated measures ANOVA, decreased FC was observed between the GM-cerebellum network and the WM-superior temporal network, as well as the WM-sensorimotor network in the PS group under the cold condition, while this difference was not found in PIS group. Importantly, the changed FC was positively correlated with the state and trait anxiety scores, respectively. This study highlighted that the WM functional network might play an integral part in pain processing, and an altered FC may be related to the descending pain modulatory system.

Bidirectional Synaptic Phototransistor Based on Two-Dimensional Ferroelectric Semiconductor for Mixed Color Pattern Recognition.

Optoelectronic synaptic devices capable of processing multiwavelength inputs are critical for neuromorphic vision hardware, which remains an important challenge. Here, we develop a bidirectional synaptic phototransistor based on a two-dimensional ferroelectric semiconductor of α-In2Se3, which exhibits bidirectional potentiated and depressed synaptic weight update under optical pulse stimulation. Importantly, the bidirectional optoelectronic synaptic behavior can be extended to multiwavelengths (blue, green, and red light), which could be used for color recognition. The mechanism underlying the bidirectional synaptic characteristics is attributed to the gate-configurable barrier heights as revealed by the Kelvin probe force microscopy measurement. The α-In2Se3 device exhibits versatile synaptic plasticity such as paired-pulse facilitation, short- and long-term potentiation, and long-term depression. The bidirectional optoelectronic synaptic weight updates under multiwavelength inputs enable a high accuracy of 97% for mixed color pattern recognition.

Realizing nearly-zero dark current and ultrahigh signal-to-noise ratio perovskite X-ray detector and image array by dark-current-shunting strategy.

Although perovskite X-ray detectors have revealed promising properties, their dark currents are usually hundreds of times larger than the practical requirements. Here, we report a detector architecture with a unique shunting electrode working as a blanking unit to suppress dark current, and it theoretically can be reduced to zero. We experimentally fabricate the dark-current-shunting X-ray detector, which exhibits a record-low dark current of 51.1 fA at 5 V mm-1, a detection limit of 7.84 nGyair s-1, and a sensitivity of 1.3 × 104 µC Gyair-1 cm-2. The signal-to-noise ratio of our polycrystalline perovskite-based detector is even outperforming many previously reported state-of-the-art single crystal-based X-ray detectors by serval orders of magnitude. Finally, the proof-of-concept X-ray imaging of a 64 × 64 pixels dark-current-shunting detector array is successfully demonstrated. This work provides a device strategy to fundamentally reduce dark current and enhance the signal-to-noise ratio of X-ray detectors and photodetectors in general.

The Efficacy of Scouting Technology in Pedicle Screw Placement in the Patients With Degenerative Scoliosis.

Objective: To investigate the curative effect of ball tip technology in pedicle screw placement in the patients with degenerative scoliosis (DS), as compared to traditional freehand technique. Methods: A total of 90 patients with degenerative scoliosis who were admitted to Affiliated Hospital of Hebei Engineering University from October 2019 to October 2021 were selected as the objects in this prospective study. They were randomly divided into an experimental group and a control group with 45 cases in each. The clinical indications, the accuracy of pedicle screw placement, the occurrence of surgical complications, the measurement of spinal and pelvic parameters, the recovery of spinal function and pain degree were recorded and compared within the two groups. Results: After treatment, the operation time, intraoperative blood loss, total number of screws, and time of screwing were compared between the two groups, and the difference was not significant (P > .05). However, the bedding time and the hospital stay were shorter in the experimental group than the control group with difference (P < .05). There was no significant difference in clinical standards and poor implantation in the Gertzbein-Robbins A-E classification between the two groups (P > .05). While the number of perfect placement of screws in the experimental group was higher (P < .05). Before treatment, the Cobbs angle and pelvic incidence-lumbar lordosis (PI-LL) levels of the two groups were comparable (P > .05); after treatment, the Cobbs angle and PI-LL levels of the two groups were lower than those before treatment, and the difference was significant (P < .05). There was no significant difference in Cobbs angle and PI-LL levels between groups (P > .05). Before treatment, the JOA and DOI scores of the two groups were comparable (P > .05); after treatment, the JOA and DOI scores of the two groups were improved (P < .05); the improvement of JOA and DOI scores of the experimental group were better than those in the control group (P < .05). Before treatment, there was no significant difference in the pain degree between the two groups (P > .05); after treatment, the pain of the two groups was improved compared with that before treatment, and the pain degree of the experimental group was lower than that of the control group (P < .05). The incidence of postoperative complications in the experimental group was lower than that in the control group, but there was no significant difference in the total incidence of postoperative complications between the two groups (P > .05). Conclusion: The scouting technique-assisted screw placement can effectively improve the spinal function of patients with degenerative scoliosis, with obvious curative effect and high safety.

Highly Linear and Symmetric Synaptic Memtransistors Based on Polarization Switching in Two-Dimensional Ferroelectric Semiconductors.

Brain-inspired neuromorphic computing hardware based on artificial synapses offers efficient solutions to perform computational tasks. However, the nonlinearity and asymmetry of synaptic weight updates in reported artificial synapses have impeded achieving high accuracy in neural networks. Here, this work develops a synaptic memtransistor based on polarization switching in a two-dimensional (2D) ferroelectric semiconductor (FES) of α-In2 Se3 for neuromorphic computing. The α-In2 Se3 memtransistor exhibits outstanding synaptic characteristics, including near-ideal linearity and symmetry and a large number of programmable conductance states, by taking the advantages of both memtransistor configuration and electrically configurable polarization states in the FES channel. As a result, the α-In2 Se3 memtransistor-type synapse reaches high accuracy of 97.76% for digit patterns recognition task in simulated artificial neural networks. This work opens new opportunities for using multiterminal FES memtransistors in advanced neuromorphic electronics.

Solution-Processed Perovskite/Metal-Oxide Hybrid X-Ray Detector and Array with Decoupled Electronic and Ionic Transport Pathways.

Lead halide perovskites possess heavy elements and excellent mobility-lifetime (µτ) product, becoming desirable candidates for X-ray detectors. However, current perovskite photoconduction detectors (PCDs) with vertical geometry, where electronic signals and mobile ions share the same conduction path, are facing with extremely challenging ion-migration issue. Herein, a hybrid X-ray detector device structure, in which perovskite is vertically stacked onto an indium oxide (In2 O3 ) transistor with lateral transport geometry is designed, perovskite mainly acts as X-ray sensitizer to activate In2 O3 conduction channel, the actual electrical signal is conducted and collected in the lateral metal-oxide device. With the decoupled ionic and electronic transportation, hybrid detectors are insensitive to the ionic motion of perovskite, hence demonstrating no hysteresis and almost no shifting of baseline that are often observed in PCDs, hybrid detectors also exhibit reduced dark current, improved response time, and four times higher photocurrent signals. Finally, array integration of hybrid detectors and preliminary X-ray imaging is realized. The work provides an effective device strategy in addition to the mere material alternations to attain high-performance perovskite-based X-ray detectors and arrays.

Inorganic-Organic Hybrid Phototransistor Array with Enhanced Photogating Effect for Dynamic Near-Infrared Light Sensing and Image Preprocessing.

Narrow-band-gap organic semiconductors have emerged as appealing near-infrared (NIR) sensing materials by virtue of their unique optoelectronic properties. However, their limited carrier mobility impedes the implementation of large-area, dynamic NIR sensor arrays. In this work, high-performance inorganic-organic hybrid phototransistor arrays are achieved for NIR sensing, by taking advantage of the high electron mobility of In2O3 and the strong NIR absorption of a BTPV-4F:PTB7-Th bulk heterojunction (BHJ) with an enhanced photogating effect. As a result, the hybrid phototransistors reach a high responsivity of 1393.0 A W-1, a high specific detectivity of 4.8 × 1012 jones, and a fast response of 0.72 ms to NIR light (900 nm). Meanwhile, an integrated 16 × 16 phototransistor array with a one-transistor-one-phototransistor (1T1PT) architecture is achieved. On the basis of the enhanced photogating effect, the phototransistor array can not only achieve real-time, dynamic NIR light mapping but also implement image preprocessing, which is promising for advanced NIR image sensors.

Correlation Analysis of Vaspin Gene Polymorphisms and Polycystic Ovary Syndrome Based on Intelligent Medicine.

Polycystic ovary syndrome (PCOS) is now a common gynecological endocrine disease, also known as Stein-Leventhal syndrome. Studies have found that Vaspin gene polymorphism is significantly associated with diabetes and cardiovascular disease, and PCOS has a clear glucose metabolism abnormality. So far, because the cause of PCOS is not clear, many problems such as the etiology, diagnostic criteria, prevention, and treatment of PCOS remain unsolved. Which also makes PCOS attract the attention of academic circles. Therefore, it is urgent to clarify the pathogenesis of PCOS, in order to explore the clinical correlation between the polymorphism of the Vaspin gene and polycystic ovary syndrome. This article introduces the correlation analysis study of Vaspin gene polymorphisms and polycystic ovary syndrome based on intelligent medicine. This article first selected 40 patients with PCOS as the experimental group and then selected 40 patients without PCOS as the control group. Secondly, through the detection methods of hs-CRP level detection and oil red O fat staining and passed two sets of control experiments. Finally, intelligent medical data analysis was used to analyze the location of the Vaspin gene in the experimental group and the control group. The final result showed that the correlation reached 75%.

Fully Printed Optoelectronic Synaptic Transistors Based on Quantum Dot-Metal Oxide Semiconductor Heterojunctions.

Optoelectronic synaptic transistors with hybrid heterostructure channels have been extensively developed to construct artificial visual systems, inspired by the human visual system. However, optoelectronic transistors taking full advantages of superior optoelectronic synaptic behaviors, low-cost processes, low-power consumption, and environmental benignity remained a challenge. Herein, we report a fully printed, high-performance optoelectronic synaptic transistor based on hybrid heterostructures of heavy-metal-free InP/ZnSe core/shell quantum dots (QDs) and n-type SnO2 amorphous oxide semiconductors (AOSs). The elaborately designed heterojunction improves the separation efficiency of photoexcited charges, leading to high photoresponsivity and tunable synaptic weight changes. Under the coordinated modulation of electrical and optical modes, important biological synaptic behaviors, including excitatory postsynaptic current, short/long-term plasticity, and paired-pulse facilitation, were demonstrated with a low power consumption (∼5.6 pJ per event). The InP/ZnSe QD/SnO2 based artificial vision system illustrated a significantly improved accuracy of 91% in image recognition, compared to that of bare SnO2 based counterparts (58%). Combining the outstanding synaptic characteristics of both AOS materials and heterojunction structures, this work provides a printable, low-cost, and high-efficiency strategy to achieve advanced optoelectronic synapses for neuromorphic electronics and artificial intelligence.