Sensitive subcellular scale and real-time detection of hydrogen peroxide by a W-doped Pt microelectrode.

A W-doped Pt modified graphene oxide (Pt-W-GO) electrochemical microelectrode was developed to detect hydrogen peroxide (H2O2) in real time at a subcellular scale. Interestingly, results showed that the concentration of H2O2 in the nucleus of HeLa cells was 2.68 times and 0.51 times that in the extracellular membrane and cytoplasm, respectively.

Co4+ in porous ZIF-67-derives intercalating-bridging adsorption of 2-reaction sites for simultaneous 2-electron transfer toward sensitive detection of uric acid.

Metal-organic frameworks (MOFs) have been used to detect uric acid (UA), but still very challenging to achieve a low detection limit due to the low inferior conductivity of MOFs. Herein, three different N-doped ZIF-67-derived carbons were synthesized for the first time by one-step co-pyrolysis of 2-methylimidazole with cobalt nitrate (CN), cobalt acetate (CA) or cobalt chloride (CC) toward UA sensing. Afterwards, the cobalt nitrate-derived Co particle (Co/CN) supported by N-doped ZIF-67-derived carbon displays extremely low detection limit and high sensitivity for UA, outperformed all reported MOFs-based UA sensors. More interestingly, it was discovered that the high valence Co4+ within the Co/CN sample produced in high-acidic environment can intercalate in the frame for a bridge adsorption between two reaction sites, which boosted simultaneous 2-electron transfer, while Co3+ only allows an end-adsorption structure for one-electron transfer being the rate determining step. Furthermore, the bridge adsorption mode of UA on Co4+ -based catalyst was also verified by theoretical DFT calculations and XPS experiment. This work holds great promise for a selective and sensitive UA sensor for practical bioscience and clinic diagnostic applications while shedding lights in fundamental research for innovative designs and developments of high-sensitive electrochemical sensors.

CircPKN2 promotes ferroptosis in bladder cancer by promoting the ubiquitination of Stearoyl-CoA Desaturase 1.

Bladder cancer (BC) is one of the most common malignancies in the male urinary system and currently lacks an optimal treatment strategy. To elucidate the pathogenic mechanisms of BC from the perspective of circular RNAs, we conducted this study. Building upon our previous research, a novel circRNA, circPKN2, captured our interest due to its significant downregulation in BC, and its close association with the prognosis of BC patients. Our research findings indicate that circPKN2 can inhibit the proliferation and migration of BC cells in vitro. Furthermore, we discovered that circPKN2 exerts its anti-cancer effects in BC by promoting ferroptosis. Mechanistic studies revealed that circPKN2 recruits STUB1 to facilitate the ubiquitination of SCD1, thereby suppressing the WNT pathway and promoting ferroptosis in BC. Additionally, our research unveiled the regulatory role of the splicing factor QKI in the biogenesis of circPKN2. Animal studies demonstrated that circPKN2 enhances ferroptosis in BC cells in vivo, inhibiting tumor growth and metastasis. The discovery of the anti-cancer factor circPKN2 holds promise for providing new therapeutic targets in the prevention and treatment of BC.

A Reconfigurable Near-Sensor Processor for Anomaly Detection in Limb Prostheses.

This paper presents a reconfigurable near-sensor anomaly detection processor to real-time monitor the potential anomalous behaviors of amputees with limb prostheses. The processor is low-power, low-latency, and suitable for equipment on the prostheses and comprises a reconfigurable Variational Autoencoder (VAE), a scalable Self-Organizing Map (SOM) Array, and a window-size-adjustable Markov Chain, which can implement an integrated miniaturized anomaly detection system. With the reconfigurable VAE, the proposed processor can support up to 64 sensor sampling channels programmable by global configuration, which can meet the anomaly detection requirements in different scenarios. A scalable SOM array allows for the selection of different sizes based on the complexity of the data. Unlike traditional time accumulation-based anomaly detection methods, the Markov Chain is utilized to detect time-series-based anomalous data. The processor is designed and fabricated in a UMC 40-nm LP technology with a core area of 1.49 mm2 and a power consumption of 1.81 mW. It achieves real-time detection performance with 0.933 average F1 Score for the FSP dataset within 24.22 µs, and 0.956 average F1 Score for the SFDLA-12 dataset within 30.48 µs, respectively. The energy dissipation of detection for each input feature is 43.84 nJ with the FSP dataset, and 55.17 nJ with the SFDLA-12 dataset. Compared with ARM Cortex-M4 and ARM Cortex-M33 microcontrollers, the processor achieves energy and area efficiency improvements ranging from 257×, 193× and 11×, 8×, respectively.

The Enhancement Mechanism of Different Single-Transition Metal Atomic Catalysts/Sulfur Cathode on High-Performance of Li-S Batteries.

Materials with various single-transition metal atoms dispersed in nitrogenated carbons (M─N─C, M = Fe, Co, and Ni) are synthesized as cathodes to investigate the electrocatalytic behaviors focusing on their enhancement mechanism for performance of Li-S batteries. Results indicate that the order of both electrocatalytic activity and rate capacity for the M─N─C catalysts is Co > Ni > Fe, and the Co─N─C delivers the highest capacity of 1100 mAh g-1 at 1 C and longtime stability at a decay rate of 0.05% per cycle for 1000 cycles, demonstrating excellent battery performance. Theoretical calculations for the first time reveal that M─N─N─C catalysts enable direct conversion of Li2 S6 to Li2 S rather than Li2 S4 to Li2 S by stronger adsorption with Li2 S6 , which also has an order of Co > Ni > Fe. And Co─N─C has the strongest adsorption energy, not only rendering the highest electrocatalytic activity, but also depressing the polysulfides' dissolution into electrolyte for the longest cycle life. This work offers an avenue to design the next generation of highly efficient sulfur cathodes for high-performance Li-S batteries, while shedding light on the fundamental insight of single metal atomic catalytic effects on Li-S batteries.

LUCAT1 inhibits ferroptosis in bladder cancer by regulating the mRNA stability of STAT3.

OBJECT: In this study, we aimed to elucidate the role of LUCAT1, a recently identified lncRNA, in ferroptosis within the context of bladder cancer (BC). METHODS: Through a comprehensive array of experimental techniques, including transmission electron microscopy (TEM), RNA pull-down assays, and fluorescence in situ hybridization (FISH), we investigated the molecular interactions and functional consequences associated with LUCAT1 in BC cells. RESULTS: Our findings indicate that LUCAT1 acts as a pivotal regulator in BC, fostering cell proliferation, migration, and invasion, while concurrently impeding ferroptosis. Mechanistically, we unveiled a direct binding between LUCAT1 and insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), which governs the mRNA stability of signal transducer and activator of transcription 3 (STAT3). Intriguingly, ectopic expression of STAT3 counteracted the suppressive effect of LUCAT1 on ferroptosis induction in BC cells. Notably, in an in vivo setting, LUCAT1 emerged as a crucial modulator of ferroptosis inhibition in BC by regulating STAT3 mRNA stability. CONCLUSION: Collectively, our study identifies LUCAT1 as a novel oncogenic player, repressing ferroptosis in BC. These findings shed light on the intricate interplay between lncRNAs and ferroptosis in cancer, implicating LUCAT1 as a promising therapeutic target for patients afflicted with BC. Further investigations into the underlying mechanisms governing LUCAT1-mediated ferroptosis resistance are warranted, with the potential to uncover novel strategies for combating BC progression and improving patient outcomes.

Enhanced Photovoltaic Properties of Y6 Derivatives with Asymmetric Terminal Groups: A Theoretical Insight.

Y6 derivatives with asymmetric terminal groups have attracted considerable attention in recent years. However, the effects of the asymmetric modification of terminal groups on the photovoltaic performance of Y6 derivatives are not well understood yet. Therefore, we designed a series of Y6-based acceptors with asymmetric terminal groups by endowing them with various electron-withdrawing abilities and different conjugated rings to conduct systematic research. The electron-withdrawing ability of the Y6-D1 terminal group (substituted by IC-2F and IC-2NO2 terminals) is strongest, followed by Y6 (substituted by two same IC-2F terminals), Y6-D2 (substituted by IC-2F and 2-(4-oxo-4,5-dihydro-6H-cyclopenta[b]thiophen-6-ylidene)malononitrile terminals), Y6-D4 (substituted by IC-2F and indene ring), and Y6-D3 (substituted by IC-2F and thiazole ring). Computed results show that A-A stacking is the main molecular packing mode of Y6 and four other asymmetric Y6 derivatives. The ratios of A-A stacking face-on configuration of Y6-D1, Y6-D2, Y6-D3, Y6-D4, and Y6 are 51.6%, 55.0%, 43.5%, 59.3%, and 62.4%, respectively. Except for Y6-D1 substituted by the IC-2F and IC-2NO2 (the strongest electron-withdrawing capacity) terminal groups, the other three asymmetric molecules are mainly electron-transporting and can therefore act as acceptors. The open-circuit voltages of organic solar cells (OSCs) based on Y6-D2, Y6-D3, and Y6-D4, except for Y6-D1, may be higher than those of OSCs based on the Y6 acceptor because of their higher energy levels of lowest unoccupied molecular orbital (LUMO). PM6/Y6-D3 and PM6/Y6-D4 have better light absorption properties than PM6/Y6 due to their higher total oscillator strength. These results indicate that Y6-D3 and Y6-D4 can be employed as good acceptors.

Exome sequencing identified novel variants in three Chinese patients with 5,10-methenyltetrahydrofolate synthetase deficiency.

5,10-methenyltetrahydrofolate synthetase (MTHFS) deficiency is a folate metabolism disorder known as a rare autosomal recessive neurodevelopmental disorder (MIM: #618367). With central nervous system involvements, it is mainly characterized by developmental delay, epilepsy, microcephaly, hypertonia, and cranial nerves involvement. Here, we report three new cases with MTHFS deficiency from two non-consanguineous Chinese families. All patients showed white matter dysplasia and global developmental delay, of which only patient 1 and 2 manifested tonic-clonic seizures. Moreover, patient 2 had severe eczema and patient 3 had recurrent diarrhea. Both phenotypic features are firstly found in MTHFS deficiency. Trio whole-exome sequencing and sanger sequencing were used to identify four novel variants, p.Y169Tfs*17, p.S53F, c.117+1delG, and p.E61G in the MTHFS gene. The identification of four novel pathogenic variants and varied clinical features in three affected patients expands the genotype and phenotype spectrum of MTHFS deficiency. We also reviewed all cases of MTHFS deficiency that had previously been reported. The experience of diagnosis and treatment from these cases provides us a more comprehensive understanding of this rare disease.

Efficacy and safety of combined Chinese and Western medicine in the treatment of knee osteoarthritis: a prospective, multicenter cohort study.

Purpose: To conduct a real-world evaluation of the efficacy and safety of combined Chinese and Western medicine in treating knee osteoarthritis (KOA). Methods: A multicenter, prospective cohort study design was employed, enrolling 450 KOA patients (Kellgren-Lawrence score of 3 or less). The patients were divided into a Western medicine treatment group (WM group) and a combined Western and traditional Chinese medicine treatment group (WM-CM group). A 6-week treatment plan was administered, and follow-up visits occurred at 2 weeks, 4 weeks, and 6 weeks after initiating treatment. The primary outcome indicator was the total Western Ontario and McMaster Universities Arthritis Index (WOMAC) score after 6 weeks of treatment. Secondary outcome indicators included WOMAC subscales for pain, stiffness, and joint function, visual analogue scale (VAS) score, physical component summary (PCS), mental component summary (MCS), and clinical effectiveness. The incidence of drug-related adverse events was used as a safety evaluation indicator. Results: A total of 419 patients were included in the final analysis: 98 in the WM group and 321 in the WM-CM group. The baseline characteristics of the two groups were comparable, except for the incidence of stiffness symptoms and stiffness scores. After 6 weeks of treatment, the WM-CM group exhibited superior results to the WM group in improving the total WOMAC score (24.71 ± 1.38 vs. 16.36 ± 0.62, p < 0.001). The WM-CM group also outperformed the WM group in WOMAC pain and joint function scores, VAS score, PCS score, MCS score, and clinical effectiveness (p < 0.05), which was consistent with the findings of the main evaluation index. Subgroup analysis indicated that the combined Chinese and Western medicine treatment showed more pronounced benefits in patients under 65 years of age and in those with a Kellgren-Lawrence (K-L) classification of 0-I. Throughout the study, no adverse effects were observed in either group. Conclusion: The combination of Chinese and Western medicine demonstrated superiority over Western medicine alone in relieving knee pain symptoms, improving knee function, and enhancing the quality of life for KOA patients with a K-L score of 3 or less. Moreover, the treatment exhibited a good safety profile. Clinical Trial Registration: (https://www.chictr.org.cn/), identifier (ChiCTR1900027175).

[Effects of blistering cupping combined with thunder-fire moxibustion on the efficacy and airway remodeling of cold-wheezing syndrome in bronchial asthma].

OBJECTIVE: To investigate the clinical efficacy of the combined application of blistering cupping with thunder-fire moxibustion in treating bronchial asthma of cold-wheezing syndrome, and its influences on airway remodeling, inflammatory factors, lung function, and quality of life on the base of conventional western medicine treatment. METHODS: A total of 76 patients with bronchial asthma of cold-wheezing syndrome were randomly divided into an observation group and a control group, 38 cases in each group. In the control group, the basic treatment was used, i.e. budesonide formoterol powder inhalation. In the observation group, on the basis of the treatment as the control group, blistering cupping combined with thunder-fire moxibustion was supplemented, Dazhui (GV 14), Danzhong (CV 17) and bilateral Feishu (BL 13), Gaohuang (BL 43), and Zhongfu (LU 1) were selected; blistering cupping was administered once a day and thunder-fire moxibustion was given twice a day. One course of treatment was composed of 7 days in both groups, and 2 courses of treatment were required. Before and after treatment, the airway remodeling indexes (matrix metalloproteinase-9 [MMP-9], tissue inhibitor of matrix metalloproteinase-1 [TIMP-1], and transforming growth factor-ß1 [TGF-ß1]) and inflammatory indexes (interleukin [IL] -1ß、IL-25) were detected by using radioimmunoassay in the patients of the two groups. The lung function, traditional Chinese medicine symptom score, and asthma quality of life questionnaire (AQLQ) score were observed in the patients of the two groups. RESULTS: After treatment, the serum levels of MMP-9, TIMP-1, TGF-ß1, IL-1ß, IL-25, peak expiratory flow (PEFR), traditional Chinese medicine symptom scores, and AQLQ scores were decreased compared with those before treatment in the patients of the two groups (P<0.05), and the results in the observation group were lower than those in the control group (P<0.05). After treatment, the first second forced expiratory volume (FEV1) and peak expiratory flow rate (PEF) were increased compared with those before treatment in the two groups (P<0.05), and the results in the observation group were higher than those in the control group (P<0.05). CONCLUSION: On the basis of the conventional western medicine treatment, the combination of blistering cupping with thunder-fire moxibustion can effectively ameliorate the clinical symptoms of patients, reduce inflammatory levels, inhibit airway remodeling and improve the lung function and quality of life in the patients with bronchial asthma.

A wearable group-synchronized EEG system for multi-subject brain-computer interfaces.

Objective: The multi-subject brain-computer interface (mBCI) is becoming a key tool for the analysis of group behaviors. It is necessary to adopt a neural recording system for collaborative brain signal acquisition, which is usually in the form of a fixed wire. Approach: In this study, we designed a wireless group-synchronized neural recording system that supports real-time mBCI and event-related potential (ERP) analysis. This system uses a wireless synchronizer to broadcast events to multiple wearable EEG amplifiers. The simultaneously received broadcast signals are marked in data packets to achieve real-time event correlation analysis of multiple targets in a group. Main results: To evaluate the performance of the proposed real-time group-synchronized neural recording system, we conducted collaborative signal sampling on 10 wireless mBCI devices. The average signal correlation reached 99.8%, the amplitude of average noise was 0.87 µV, and the average common mode rejection ratio (CMRR) reached 109.02 dB. The minimum synchronization error is 237 µs. We also tested the system in real-time processing of the steady-state visual-evoked potential (SSVEP) ranging from 8 to 15.8 Hz. Under 40 target stimulators, with 2 s data length, the average information transfer rate (ITR) reached 150 ± 20 bits/min, and the highest reached 260 bits/min, which was comparable to the marketing leading EEG system (the average: 150 ± 15 bits/min; the highest: 280 bits/min). The accuracy of target recognition in 2 s was 98%, similar to that of the Synamps2 (99%), but a higher signal-to-noise ratio (SNR) of 5.08 dB was achieved. We designed a group EEG cognitive experiment; to verify, this system can be used in noisy settings. Significance: The evaluation results revealed that the proposed real-time group-synchronized neural recording system is a high-performance tool for real-time mBCI research. It is an enabler for a wide range of future applications in collaborative intelligence, cognitive neurology, and rehabilitation.

A Memristor-Based Learning Engine for Synaptic Trace-Based Online Learning.

The memristor has been extensively used to facilitate the synaptic online learning of brain-inspired spiking neural networks (SNNs). However, the current memristor-based work can not support the widely used yet sophisticated trace-based learning rules, including the trace-based Spike-Timing-Dependent Plasticity (STDP) and the Bayesian Confidence Propagation Neural Network (BCPNN) learning rules. This paper proposes a learning engine to implement trace-based online learning, consisting of memristor-based blocks and analog computing blocks. The memristor is used to mimic the synaptic trace dynamics by exploiting the nonlinear physical property of the device. The analog computing blocks are used for the addition, multiplication, logarithmic and integral operations. By organizing these building blocks, a reconfigurable learning engine is architected and realized to simulate the STDP and BCPNN online learning rules, using memristors and 180 nm analog CMOS technology. The results show that the proposed learning engine can achieve energy consumption of 10.61 pJ and 51.49 pJ per synaptic update for the STDP and BCPNN learning rules, respectively, with a 147.03× and 93.61× reduction compared to the 180 nm ASIC counterparts, and also a 9.39× and 5.63× reduction compared to the 40 nm ASIC counterparts. Compared with the state-of-the-art work of Loihi and eBrainII, the learning engine can reduce the energy per synaptic update by 11.31× and 13.13× for trace-based STDP and BCPNN learning rules, respectively.

An IoT-Based Wearable Labor Progress Monitoring System for Remote Evaluation of Admission Time to Hospital.

Because contractions signal the approach of labor, pregnant women-especially primigravidas (i.e., women pregnant for the first time)-usually go to the hospital to seek medical intervention when they begin experiencing contractions, which is not conductive to good perinatal outcomes. Conventionally, uterine contraction monitoring requires specialized medical devices and relies on the doctor's clinical experience. Therefore, exploring an objective method to detect labor onset at home and avoid early hospital admission has essential importance. In this article, a labor progress monitoring system based on a sensing device, edge service, and Internet of things (IoT) platform is proposed, aiming to suggest suitable hospital admission times for low-risk primigravidas. The pregnant woman places the sensing device on her abdomen with the help of a belt to detect contraction activities. An intelligent edge service for contraction classification is deployed on a mobile phone. The system's artificial intelligence (AI)-assisted algorithm is lightweight, with 670 kB and 194 kB of memory dedicated to a convolutional neural network and long short-term memory, respectively. It classifies the pregnant woman as deferred admission, optional admission, or recommended admission according to different contraction states. An IoT platform connected to the hospital is implemented, providing professional suggestions from doctors. The test set collected in an emergency clinic shows that the proposed system can reach a classification accuracy of more than 96%. In conclusion, the proposed system enables remote labor progress monitoring at home and avoids early hospital admission.

A bean sprout-like cobalt selenium phosphorus nanosheet-composed anode toward fast and high sodium-ion storage.

A metal-organic framework (MOF) is used to thermally grow cobalt selenophosphide (CoSeP) nanoparticles on an N-doped 2-dimensional carbon matrix (CoSeP@N-C), resulting in an assembled unique 3-dimensional bean sprout-like nanosheet composite with massive defects as an advanced anode material of sodium ion batteries. The results indicate that the massive defects in the CoSeP@N-C sprout-like 3-D structure can offer high density of reaction sites and well accommodate the volume change during the sodiation/desodiation process, while rendering abundant channels for rapid transport of sodium ions, thereby synergistically making the CoSeP@N-C anode much more reversible for the sodium ion storage process and producing higher rate performance than those of CoP2 and CoSe2@N-C. The ex situ X-ray diffraction, ex situ Raman and ex situ TEM analyses further confirm the mechanism of sodium storage intercalation and transformation in CoSeP@N-C. This work vividly demonstrates a rational design of metal selenophosphide anodes as an effective strategy to accomplish fast and high sodium-ion storage.

Case report: Identification and clinical phenotypic analysis of novel mutation of the PPP1CB gene in NSLH2 syndrome.

Objective: To screen and analyze the genetic mutations in the PPP1CB gene in a patient with Noonan syndrome with loose anagen hair-2 (NSLH2) in Yunnan Province, China and explore the possible molecular pathogenesis. Methods: After obtaining informed consent, we collected the patient's medical history and carried out physical and laboratory examinations for the NSLH2 proband and the family members. Genomic DNA was extracted from the peripheral blood of all individuals. The coding regions including all pathogenic exons, parts of introns, and promoters of genes were sequenced by next-generation sequencing. Pathogenic mutations, which were detected in the probands and their parents, were verified by Sanger sequencing. Results: The clinical manifestations of NSLH2 included prominent forehead, yellowish hair, slightly wide eye distance, sparse eyebrows, bilateral auricle deformity, reduced muscle tension, and cardiac and visual abnormalities. The proband carried a c.371A>G mutation in exon 3 of PPP1CB, which is a missense mutation. This was a de novo mutation as the parents of the proband showed no mutation at this site. Conclusion: In this study, we identified a novel mutation of PPP1CB, which enriched the mutation spectrum of the PPP1CB gene and provided a basis for the diagnosis of NSLH2.

A Neuromorphic Processing System With Spike-Driven SNN Processor for Wearable ECG Classification.

This paper presents a neuromorphic processing system with a spike-driven spiking neural network (SNN) processor design for always-on wearable electrocardiogram (ECG) classification. In the proposed system, the ECG signal is captured by level crossing (LC) sampling, achieving native temporal coding with single-bit data representation, which is directly fed into an SNN in an event-driven manner. A hardware-aware spatio-temporal backpropagation (STBP) is suggested as the training scheme to adapt to the LC-based data representation and to generate lightweight SNN models. Such a training scheme diminishes the firing rate of the network with little plenty of classification accuracy loss, thus reducing the switching activity of the circuits for low-power operation. A specialized SNN processor is designed with the spike-driven processing flow and hierarchical memory access scheme. Validated with field programmable gate arrays (FPGA) and evaluated in 40 nm CMOS technology for application-specific integrated circuit (ASIC) design, the SNN processor can achieve 98.22% classification accuracy on the MIT-BIH database for 5-category classification, with an energy efficiency of 0.75 µJ/classification.

Single-Atom Iron Anchored on 2-D Graphene Carbon to Realize Bridge-Adsorption of O-O as Biomimetic Enzyme for Remarkably Sensitive Electrochemical Detection of H2O2.

Single-atom catalysis is mainly focused on its dispersed high-density catalytic sites, but delicate designs to realize a unique catalysis mechanism in terms of target reactions have been much less investigated. Herein an iron single atomic site catalyst anchored on 2-D N-doping graphene (Fe-SASC/G) was synthesized and further employed as a biomimetic sensor to electrochemically detect hydrogen peroxide, showing an extremely high sensitivity of 3214.28 µA mM-1 cm-2, which is much higher than that (6.5 µA mM-1 cm-2) of its dispersed on 1-D carbon nanowires (Fe-SASC/NW), ranking the best sensitivity among all reported Fe based catalyst at present. The sensor was also used to successfully in situ monitor H2O2 released from A549 living cells. The mechanism was further systematically investigated. Results interestingly indicate that the distance between adjacent single Fe atomic catalytic sites on 2-D graphene of Fe-SASC/G matches statistically well with the outer length of bioxygen of H2O2 to promote a bridge adsorption of -O-O- for simultaneous 2-electron transfer, while the single Fe atoms anchored on distant 1-D nanowires in Fe-SASC/NW only allow an end-adsorption of oxygen atoms for 1-electron transfer. These results demonstrate that Fe-SASC/G holds great promise as an advanced electrode material in selective and sensitive biomimetic sensor and other electrocatalytic applications, while offering scientific insights in deeper single atomic catalysis mechanisms, especially the effects of substrate dimensions on the mechanism.

Research Progress on the Role of Vitamin D in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder that can lead to severe social behavioral difficulties, which mainly manifests as social communication and interaction disorders; narrow interests; and repetitive, stereotyped behaviors. In recent years, the prevalence of ASD has increased annually, and it has evolved from a rare disease to one with a high incidence among childhood developmental disorders. The pathogenesis of ASD is considered to be the interaction of genetic and environmental factors. There is increasing evidence that vitamin D deficiency in pregnancy and early childhood can lead to the occurrence of ASD. Studies have demonstrated that vitamin D intervention can significantly improve the symptoms of ASD, but the underlying mechanism is still unclear. Therefore, exploring the neuroprotective mechanism of vitamin D against ASD is a huge challenge currently being worked on by current basic and clinical researchers, a task which is of great significance for the clinical promotion and optimization of vitamin D in the treatment of ASD. To further clarify the relationship between vitamin D and ASD, this review summarizes the correlation between vitamin D level and ASD, the effects of vitamin D supplementation on ASD, the possible mechanism of vitamin D involved in ASD, and insights from ASD animal models.

Assess heavy metals-induced oxidative stress of microalgae by Electro-Raman combined technique.

Oxidative stress of aquatic microorganisms under heavy metal stress is closely reflected by metabolite changes in cells but it is very difficult to study due to the fast metabolism process and severe in-situ measurements hurdle. Herein, the oxidative stress of cadmium on Euglena gracilis was systematically studied through multi-combined techniques. In particular, for the first time electrochemical approach was associated with Raman spectroscopy imaging to vividly to investigate temporal-spatially varied oxidative stress and its effects on cells metabolism, in which former real-time measured a volcanic relation of extracellular hydrogen peroxide versus the increase of cadmium stress, while the latter shows the corresponding metabolic changes by Raman imaging of single cells. This work builds a bridge to unravel the mechanism of cellular oxidative stress under harsh conditions in a more systematic and holistic approach, while holding a great promise to construct heavy metal biosensors precisely monitoring high heavy metal tolerance strains for environmental modification.

Backpropagation With Sparsity Regularization for Spiking Neural Network Learning.

The spiking neural network (SNN) is a possible pathway for low-power and energy-efficient processing and computing exploiting spiking-driven and sparsity features of biological systems. This article proposes a sparsity-driven SNN learning algorithm, namely backpropagation with sparsity regularization (BPSR), aiming to achieve improved spiking and synaptic sparsity. Backpropagation incorporating spiking regularization is utilized to minimize the spiking firing rate with guaranteed accuracy. Backpropagation realizes the temporal information capture and extends to the spiking recurrent layer to support brain-like structure learning. The rewiring mechanism with synaptic regularization is suggested to further mitigate the redundancy of the network structure. Rewiring based on weight and gradient regulates the pruning and growth of synapses. Experimental results demonstrate that the network learned by BPSR has synaptic sparsity and is highly similar to the biological system. It not only balances the accuracy and firing rate, but also facilitates SNN learning by suppressing the information redundancy. We evaluate the proposed BPSR on the visual dataset MNIST, N-MNIST, and CIFAR10, and further test it on the sensor dataset MIT-BIH and gas sensor. Results bespeak that our algorithm achieves comparable or superior accuracy compared to related works, with sparse spikes and synapses.