Electronically Reconfigurable Memristive Neuron Capable of Operating in Both Excitation and Inhibition Modes.

Threshold switching (TS) memristors are promising candidates for artificial neurons in neuromorphic systems. However, they often lack biological plausibility, typically functioning solely in an excitation mode. The absence of an inhibitory mode limits neurons' ability to synergistically process both excitatory and inhibitory synaptic signals. To address this limitation, we propose a novel memristive neuron capable of operating in both excitation and inhibition modes. The memristor's threshold voltage can be reversibly tuned using voltages of different polarities because of its bipolar TS behavior, enabling the device to function as an electronically reconfigurable bi-mode neuron. A variety of neuronal activities such as all-or-nothing behavior and tunable firing probability are mimicked under both excitatory and inhibitory stimuli. Furthermore, we develop a self-adaptive neuromorphic vision sensor based on bi-mode neurons, demonstrating effective object recognition in varied lighting conditions. Thus, our bi-mode neuron offers a versatile platform for constructing neuromorphic systems with rich functionality.

Causal associations between both psoriasis and psoriatic arthritis and multiple autoimmune diseases: a bidirectional two-sample Mendelian randomization study.

Background: Numerous observational studies have identified associations between both psoriasis (PsO) and psoriatic arthritis (PsA), and autoimmune diseases (AIDs); however, the causality of these associations remains undetermined. Methods: We conducted a bidirectional two-sample Mendelian Randomization study to identify causal associations and directions between both PsO and PsA and AIDs, such as systemic lupus erythematosus (SLE), Crohn's disease (CD), ulcerative colitis (UC), multiple sclerosis (MS), uveitis, bullous pemphigoid (BP), Hashimoto's thyroiditis (HT), rheumatoid arthritis (RA), vitiligo, and ankylosing spondylitis (AS). The causal inferences were drawn by integrating results from four regression models: Inverse Variance Weighting (IVW), MR-Egger, Weighted Median, and Maximum Likelihood. Furthermore, we performed sensitivity analyses to confirm the reliability of our findings. Results: The results showed that CD [IVW odds ratio (ORIVW), 1.11; 95% confidence interval (CI), 1.06-1.17; P = 8.40E-06], vitiligo (ORIVW, 1.16; 95% CI, 1.05-1.28; P = 2.45E-03) were risk factors for PsO, while BP may reduce the incidence of PsO (ORIVW, 0.91; 95% CI, 0.87-0.96; P = 1.26E-04). CD (ORIVW, 1.07; 95% CI, 1.02-1.12; P = 0.01), HT (ORIVW, 1.23; 95% CI, 1.08-1.40; P = 1.43E-03), RA (ORIVW, 1.11; 95% CI, 1.02-1.21, P = 2.05E-02), AS (ORIVW, 2.18; 95% CI, 1.46-3.27; P = 1.55E-04), SLE (ORIVW, 1.04; 95% CI, 1.01-1.08; P = 1.07E-02) and vitiligo (ORIVW, 1.27; 95% CI, 1.14-1.42; P = 2.67E-05) were risk factors for PsA. Sensitivity analyses had validated the reliability of the results. Conclusions: Our study provides evidence for potential causal relationships between certain AIDs and both PsO and PsA. Specifically, CD and vitiligo may increase the risk of developing PsO, while CD, HT, SLE, RA, AS, and vitiligo may elevate the risk for PsA. Additionally, it is crucial to closely monitor the condition of PsO patients with specific AIDs, as they have a higher likelihood of developing PsA than those without AIDs. Moving forward, greater attention should be paid to PsA and further exploration of other PsO subtypes is warranted.

Atroposelective Formal [2 + 5] Macrocyclization Synthesis for a Novel All-Hydrocarbon Cyclo[7] Meta-Benzene Macrocycle.

A novel axially chiral all-hydrocarbon cyclo[7] (1,3-(4,6-dimethyl)benzene (CDMB-7) was designed and synthesized using atroposelective[2 + 5] cyclization through Suzuki-Miyaura coupling. CDMB-7 adopts an irregular bowl-like shape with C2 symmetry and exhibits two diastereoisomers in its crystallographic structure. The conformational isomers of CDMB-7 racemates remain stable at high temperatures (393 K). High-performance liquid chromatography (HPLC) confirmed that a single chiral isomer will spontaneously undergo racemization within 30 min at room temperature. This finding opens up possibilities for achieving adaptive chirality in all-hydrocarbon cyclo[7] m-benzene macrocycles.

Optically driven intelligent computing with ZnO memristor.

Artificial vision is crucial for most artificial intelligence applications. Conventional artificial visual systems have been facing challenges in terms of real-time information processing due to the physical separation of sensors, memories, and processors, which results in the production of a large amount of redundant data as well as the data conversion and transfer between these three components consuming most of the time and energy. Emergent optoelectronic memristors with the ability to realize integrated sensing-computing-memory (ISCM) are key candidates for solving such challenges and therefore attract increasing attention. At present, the memristive ISCM devices can only perform primary-level computing with external light signals due to the fact that only monotonic increase of memconductance upon light irradiation is achieved in most of these devices. Here, we propose an all-optically controlled memristive ISCM device based on a simple structure of Au/ZnO/Pt with the ZnO thin film sputtered at pure Ar atmosphere. This device can perform advanced computing tasks such as nonvolatile neuromorphic computing and complete Boolean logic functions only by light irradiation, owing to its ability to reversibly tune the memconductance with light. Moreover, the device shows excellent operation stability ascribed to a purely electronic memconductance tuning mechanism. Hence, this study is an important step towards the next generation of artificial visual systems.

Association between polypharmacy and chronic kidney disease among community-dwelling older people: a longitudinal study in southern China.

BACKGROUND: Polypharmacy would increase the risk of adverse drug events and the burden of renal drug excretion among older people. Nevertheless, the association between the number of medication and the risk of chronic kidney disease (CKD) remains controversial. Therefore, this study aims to investigate the association between the number of medication and the incidence of CKD in older people. METHODS: This study investigates the association between the number of medications and CKD in 2672 elderly people (≥ 65 years older) of the community health service center in southern China between 2019 and 2022. Logistic regression analysis was used to evaluate the relationship between polypharmacy and CKD. RESULTS: At baseline, the average age of the study subjects was 71.86 ± 4.60, 61.2% were females, and 53 (2.0%) suffer from polypharmacy. During an average follow-up of 3 years, new-onset CKD developed in 413 (15.5%) participants. Logistic regression analysis revealed that taking a higher number of medications was associated with increase of CKD. Compared with people who didn't take medication, a higher risk of CKD was observed in the older people who taken more than five medications (OR 3.731, 95% CI 1.988, 7.003), followed by those who take four (OR 1.621, 95% CI 1.041, 2.525), three (OR 1.696, 95% CI 1.178, 2.441), two drugs (OR 1.585, 95% CI 1.167, 2.153), or one drug (OR 1.503, 95% CI 1.097, 2.053). Furthermore, age, systolic blood pressure (SBP), white blood cell (WBC), blood urea nitrogen (BUN) and triglyceride (TG) were also independent risk factors CKD (P < 0.05). CONCLUSION: The number of medications was associated with CKD in older people. As the number of medications taken increased, the risk of CKD was increased.

Machine learning for predicting halogen radical reactivity toward aqueous organic chemicals.

Rapid advances in machine learning (ML) provide fast, accurate, and widely applicable methods for predicting free radical-mediated organic pollutant reactivity. In this study, the rate constants (logk) of four halogen radicals were predicted using Morgan fingerprint (MF) and Mordred descriptor (MD) in combination with a series of ML models. The findings highlighted that making accurate predictions for various datasets depended on an effective combination of descriptors and algorithms. To further alleviate the challenge of limited sample size, we introduced a data combination strategy that improved prediction accuracy and mitigated overfitting by combining different datasets. The Light Gradient Boosting Machine (LightGBM) with MF and Random Forest (RF) with MD models based on the unified dataset were finally selected as the optimal models. The SHapley Additive exPlanations revealed insights: the MF-LightGBM model successfully captured the influence of electron-withdrawing/donating groups, while autocorrelation, walk count and information content descriptors in the MD-RF model were identified as key features. Furthermore, the important contribution of pH was emphasized. The results of the applicability domain analysis further supported that the developed model can make reliable predictions for query compounds across a broader range. Finally, a practical web application for logk calculations was built.

The novel small molecule E0924G dually regulates bone formation and bone resorption through activating the PPARδ signaling pathway to prevent bone loss in ovariectomized rats and senile mice.

Osteoporosis is particularly prevalent among postmenopausal women and the elderly. In the present study, we investigated the effect of the novel small molecule E0924G (N-(4-methoxy-pyridine-2-yl)-5-methylfuran-2-formamide) on osteoporosis. E0924G significantly increased the protein expression levels of osteoprotegerin (OPG) and runt-related transcription factor 2 (RUNX2), and thus significantly promoted osteogenesis in MC3T3-E1 cells. E0924G also significantly decreased osteoclast differentiation and inhibited bone resorption and F-actin ring formation in receptor activator of NF-κB ligand (RANKL)-induced osteoclasts from RAW264.7 macrophages. Importantly, oral administration of E0924G in both ovariectomized (OVX) rats and SAMP6 senile mice significantly increased bone mineral density and decreased bone loss compared to OVX controls or SAMR1 mice. Further mechanistic studies showed that E0924G could bind to and then activate peroxisome proliferator-activated receptor delta (PPARδ), and the pro-osteoblast effect and the inhibition of osteoclast differentiation induced by E0924G were significantly abolished when PPARδ was knocked down or inhibited. In conclusion, these data strongly suggest that E0924G has the potential to prevent OVX-induced and age-related osteoporosis by dual regulation of bone formation and bone resorption through activation of the PPARδ signaling pathway.

The application of machine learning methods for prediction of heavy metal by activated carbons, biochars, and carbon nanotubes.

Carbonaceous materials are commonly used as adsorbents for heavy metals. The determination of the adsorption capacity needs time and energy, and the key factors affecting the adsorption capacity have not been determined. Therefore, a new and efficient method is needed to predict the adsorption capacity and explore the decisive factors in the adsorption process. In this study, three tree-based machine learning models (i.e., random forest, gradient boosting decision tree, and extreme gradient boosting) were developed to predict the adsorption capacity of eight heavy metals (i.e., As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) on activated carbons, biochars, and carbon nanotubes using 3674 data points extracted from 151 journal articles. After a comprehensive comparison, the gradient boosting decision tree had the best performance for a combined model based on all data (R2 = 0.9707, RMSE = 0.1420). Moreover, independent models were developed for three datasets classified by the adsorbent and eight datasets classified by the heavy metals. In addition, a graphical user interface was built to predict the adsorption capacity of heavy metals. This study provides a novel strategy and convenient tool for the removal of heavy metals and can help to improve the removal efficiency of heavy metals to build a healthier world.

Targeting M2-like tumor-associated macrophages is a potential therapeutic approach to overcome antitumor drug resistance.

Tumor drug resistance emerges from the interaction of two critical factors: tumor cellular heterogeneity and the immunosuppressive nature of the tumor microenvironment (TME). Tumor-associated macrophages (TAMs) constitute essential components of the TME. M2-like TAMs are essential in facilitating tumor metastasis as well as augmenting the drug resistance of tumors. This review encapsulates the mechanisms that M2-like TAMs use to promote tumor drug resistance. We also describe the emerging therapeutic strategies that are currently targeting M2-like TAMs in combination with other antitumor drugs, with some still undergoing clinical trial evaluation. Furthermore, we summarize and analyze various existing approaches for developing novel drugs that target M2-like TAMs to overcome tumor resistance, highlighting how targeting M2-like TAMs can effectively stop tumor growth, metastasis, and overcome tumor drug resistance.

The jet-like chromatin structure defines active secondary metabolism in fungi.

Eukaryotic genomes are spatially organized within the nucleus in a nonrandom manner. However, fungal genome arrangement and its function in development and adaptation remain largely unexplored. Here, we show that the high-order chromosome structure of Fusarium graminearum is sculpted by both H3K27me3 modification and ancient genome rearrangements. Active secondary metabolic gene clusters form a structure resembling chromatin jets. We demonstrate that these jet-like domains, which can propagate symmetrically for 54 kb, are prevalent in the genome and correlate with active gene transcription and histone acetylation. Deletion of GCN5, which encodes a core and functionally conserved histone acetyltransferase, blocks the formation of the domains. Insertion of an exogenous gene within the jet-like domain significantly augments its transcription. These findings uncover an interesting link between alterations in chromatin structure and the activation of fungal secondary metabolism, which could be a general mechanism for fungi to rapidly respond to environmental cues, and highlight the utility of leveraging three-dimensional genome organization in improving gene transcription in eukaryotes.

Prediction of antibiotic sorption in soil with machine learning and analysis of global antibiotic resistance risk.

Although the sorption of antibiotics in soil has been extensively studied, their spatial distribution patterns and sorption mechanisms still need to be clarified, which hinders the assessment of antibiotic resistance risk. In this study, machine learning was employed to develop the models for predicting the soil sorption behavior of three classes of antibiotics (sulfonamides, tetracyclines, and fluoroquinolones) in 255 soils with 2203 data points. The optimal independent models obtained an accurate predictive performance with R2 of 0.942 to 0.977 and RMSE of 0.051 to 0.210 on test sets compared to combined models. Besides, a global map of the antibiotic sorption capacity of soil predicted with the optimal models revealed that the sorption potential of fluoroquinolones was the highest, followed by tetracyclines and sulfonamides. Additionally, 14.3% of regions had higher antibiotic sorption potential, mainly in East and South Asia, Central Siberia, Western Europe, South America, and Central North America. Moreover, a risk index calculated with the antibiotic sorption capacity of soil and population density indicated that about 3.6% of soils worldwide have a high risk of resistance, especially in South and East Asia with high population densities. This work has significant implications for assessing the antibiotic contamination potential and resistance risk.

Continuous directed evolution of a compact CjCas9 variant with broad PAM compatibility.

CRISPR-Cas9 genome engineering is a powerful technology for correcting genetic diseases. However, the targeting range of Cas9 proteins is limited by their requirement for a protospacer adjacent motif (PAM), and in vivo delivery is challenging due to their large size. Here, we use phage-assisted continuous directed evolution to broaden the PAM compatibility of Campylobacter jejuni Cas9 (CjCas9), the smallest Cas9 ortholog characterized to date. The identified variant, termed evoCjCas9, primarily recognizes N4AH and N5HA PAM sequences, which occur tenfold more frequently in the genome than the canonical N3VRYAC PAM site. Moreover, evoCjCas9 exhibits higher nuclease activity than wild-type CjCas9 on canonical PAMs, with editing rates comparable to commonly used PAM-relaxed SpCas9 variants. Combined with deaminases or reverse transcriptases, evoCjCas9 enables robust base and prime editing, with the small size of evoCjCas9 base editors allowing for tissue-specific installation of A-to-G or C-to-T transition mutations from single adeno-associated virus vector systems.

Transcriptional insights of citrus defense response against Diaporthe citri.

Citrus melanose, caused by Diaporthe citri, is one of the most important and widespread fungal diseases of citrus. Previous studies demonstrated that the citrus host was able to trigger the defense response to restrict the spread of D. citri. However, the molecular mechanism underlying this defense response has yet to be elucidated. Here, we used RNA-Seq to explore the gene expression pattern at the early (3 days post infection, dpi) and late (14 dpi) infection stages of citrus leaves in response to D. citri infection, and outlined the differences in transcriptional regulation associated with defense responses. The functional enrichment analysis indicated that the plant cell wall biogenesis was significantly induced at the early infection stage, while the callose deposition response was more active at the late infection stage. CYP83B1 genes of the cytochrome P450 family were extensively induced in the callus deposition-mediated defense response. Remarkably, the gene encoding pectin methylesterase showed the highest upregulation and was only found to be differentially expressed at the late infection stage. Genes involved in the synthesis and regulation of phytoalexin coumarin were effectively activated. F6'H1 and S8H, encoding key enzymes in the biosynthesis of coumarins and their derivatives, were more strongly expressed at the late infection stage than at the early infection stage. Collectively, our study profiled the response pattern of citrus leaves against D. citri infection and provided the transcriptional evidence to support the defense mechanism.

[Urine metabolomics study of intervention of Xihuang Pills in rats with hyperplasia of mammary gland].

This study aimed to investigate the mechanism of Xihuang Pills in improving hyperplasia of mammary gland(HMG) in rats based on urine metabolomics using ultra-performance liquid chromatography-quadrupole-Orbitrap mass spectrometry(UPLC-Q-Orbitrap-MS). The HMG rat model was established by intramuscular injection of estradiol benzoate solution(0.5 mg·kg~(-1), 25 days) followed by progesterone injection(5 mg·kg~(-1), 5 days). UPLC-Q-Orbitrap-MS technology was used to establish the endogenous small-molecule metabolic profiles in urine samples of rats in the blank group, the HMG model group, and Xihuang Pills group. Multivariate statistical analysis was performed for pattern recognition, t test and variable importance in the projection(VIP) were used to screen potential biomarkers. The significantly changed differential metabolites were identified using the online database Human Metabolome Database(HMDB). Metabolic pathway enrichment analysis was conducted using the MetaboAnalyst 5.0 database. The results showed that 90 differential metabolites with significant changes(P<0.05) were identified between the blank group and the HMG model group using the HMDB. Among them, 48 metabolites significantly reverted(P<0.05) after administration of Xihuang Pills, which may be related to the regulatory effect of Xihuang Pills. Thirteen metabolic pathways significantly associated with HMG were identified when the differential metabolites were imported into the MetaboAnalyst 5.0 database, and Xihuang Pills could modulate seven of these pathways. These metabolic pathways mainly involved histidine metabolism, arginine and proline metabolism, ß-alanine metabolism, glycine, serine and threonine metabolism, tryptophan metabolism, pyrimidine metabolism, and amino sugar and nucleotide sugar metabolism. This study utilized UPLC-Q-Orbitrap-MS and urine metabolomics technology to analyze the mechanism of Xihuang Pills in improving HMG, laying the foundation for further in-depth research.

HapX-mediated H2B deub1 and SreA-mediated H2A.Z deposition coordinate in fungal iron resistance.

Plant pathogens are challenged by host-derived iron starvation or excess during infection, but the mechanism through which pathogens counteract iron stress is unclear. Here, we found that Fusarium graminearum encounters iron excess during the colonization of wheat heads. Deletion of heme activator protein X (FgHapX), siderophore transcription factor A (FgSreA) or both attenuated virulence. Further, we found that FgHapX activates iron storage under iron excess by promoting histone H2B deubiquitination (H2B deub1) at the promoter of the responsible gene. Meanwhile, FgSreA is shown to inhibit genes mediating iron acquisition during iron excess by facilitating the deposition of histone variant H2A.Z and histone 3 lysine 27 trimethylation (H3K27 me3) at the first nucleosome after the transcription start site. In addition, the monothiol glutaredoxin FgGrx4 is responsible for iron sensing and control of the transcriptional activity of FgHapX and FgSreA via modulation of their enrichment at target genes and recruitment of epigenetic regulators, respectively. Taken together, our findings elucidated the molecular mechanisms for adaptation to iron excess mediated by FgHapX and FgSreA during infection in F. graminearum and provide novel insights into regulation of iron homeostasis at the chromatin level in eukaryotes.

Numerical Simulation Research on Partial Discharge of Particle Defects at Epoxy Interface Excited by High-Frequency Sinusoidal Voltage.

In order to improve the effectiveness of partial discharge detection in attached metal particle insulators, this paper proposes a partial discharge detection method for particle defects in insulators under high-frequency sinusoidal voltage excitation. In order to study the development process of partial discharge under high-frequency electrical stress, a two-dimensional plasma simulation model of partial discharge with particle defects at the epoxy interface is established under plate-plate electrode structure, which realizes the dynamic simulation of particulate defect partial discharge. By studying the microscopic mechanism of partial discharge, the spatial and temporal distribution characteristics of microscopic parameters such as electron density, electron temperature, and surface charge density are obtained. Based on this simulation model, this paper further studies the partial discharge characteristics of epoxy interface particle defects at different frequencies, and verifies the accuracy of the model from two aspects of discharge intensity and surface damages through experimental means. The results show that with the increase in the frequency of applied voltage, the amplitude of electron temperature shows an increasing trend. However, the surface charge density gradually decreases with the increase in frequency. These two factors make partial discharge severest when the frequency of the applied voltage is 15 kHz.

The sphinganine C4-hydroxylase FgSur2 regulates sensitivity to azole antifungal agents and virulence of Fusarium graminearum.

Lipid rafts consisting of ergosterol and sphingolipids in the lipid membrane of cells play important roles in various cellular processes. However, the functions of sphingolipids and their synthetic genes in phytopathogenic fungi have not been well understood yet. In this study, we conducted genome-wide searches and carried out systematic gene deletion analysis of the sphingolipid synthesis pathway in Fusarium graminearum, a causal agent of Fusarium head blight of wheat and other cereal crops worldwide. Mycelial growth assays showed that deletion of FgBAR1, FgLAC1, FgSUR2 or FgSCS7 resulted in markedly reduced hyphal growth. Fungicide sensitivity tests showed that the sphinganine C4-hydroxylase gene FgSUR2 deletion mutant (ΔFgSUR2) exhibited significantly increased susceptibility to azole fungicides. In addition, this mutant displayed a remarkable increase in cell membrane permeability. Importantly, ΔFgSUR2 was defective in deoxynivalenol (DON) toxisome formation, leading to dramatically decreased DON biosynthesis. Moreover, the deletion of FgSUR2 resulted in dramatically decreased virulence of the pathogen on host plants. Taken together, these results indicate that FgSUR2 plays an important role in regulating the susceptibility to azoles and virulence of F. graminearum.

The predictive value of the modified AFP model for liver transplantation outcomes in multinodular hepatocellular carcinoma patients.

BACKGROUND: There is a lack of studies focusing on the benefit of liver transplantation (LT) in hepatocellular carcinoma (HCC) patients with > 3 tumors. This study aims to establish a model to effectively predict overall survival in Chinese HCC patients with multiple tumors (> 3 tumors) who undergo LT. METHODS: This retrospective study included 434 HCC liver transplant recipients from the China Liver Transplant Registry. All HCC patients had more than 3 tumor nodules. Three selection criteria systems (i.e., AFP, Metroticket 2.0, and Up-to-7) were compared regarding the prediction of HCC recurrence. The modified AFP model was established by univariate and multivariate competing risk analyses. RESULTS: The AFP score 2 and the AFP score ≥ 3 groups had 5-year recurrence rates of 19.6% and 40.5% in our cohort. The prediction of HCC recurrence based on the AFP model was associated with a c-statistic of 0.606, which was superior to the Up-to-7 and Metroticket 2.0 models. AFP level > 1000 ng/mL, largest tumor size ≥ 8 cm, vascular invasion, and MELD score ≥ 15 were associated with overall survival. The 5-year survival rate in the modified AFP score 0 group was 71.7%. CONCLUSIONS: The AFP model is superior in predicting tumor recurrence in HCC patients with > 3 tumors prior to LT. With the modified AFP model, patients likely to derive sufficient benefit from LT can be identified.