Unleashing the potential of Li-O2 batteries with electronic modulation and lattice strain in pre-lithiated electrocatalysts.

Efficient catalysts are indispensable for overcoming the sluggish reaction kinetics and high overpotentials inherent in Li-O2 batteries. However, the lack of precise control over catalyst structures at the atomic level and limited understanding of the underlying catalytic mechanisms pose significant challenges to advancing catalyst technology. In this study, we propose the concept of precisely controlled pre-lithiated electrocatalysts, drawing inspiration from lithium electrochemistry. Our results demonstrate that Li+ intercalation induces lattice strain in RuO2 and modulates its electronic structure. These modifications promote electron transfer between catalysts and reaction intermediates, optimizing the adsorption behavior of Li-O intermediates. As a result, Li-O2 batteries employing Li0.52RuO2 exhibit ultrahigh energy efficiency, long lifespan, high discharge capacity, and excellent rate performance. This research offers valuable insights for the design and optimization of efficient electrocatalysts at the atomic level, paving the way for further advancements in Li-O2 battery technology.

Deep learning-assisted diagnosis of benign and malignant parotid gland tumors based on automatic segmentation of ultrasound images: a multicenter retrospective study.

Objectives: To construct deep learning-assisted diagnosis models based on automatic segmentation of ultrasound images to facilitate radiologists in differentiating benign and malignant parotid tumors. Methods: A total of 582 patients histopathologically diagnosed with PGTs were retrospectively recruited from 4 centers, and their data were collected for analysis. The radiomics features of six deep learning models (ResNet18, Inception_v3 etc) were analyzed based on the ultrasound images that were obtained under the best automatic segmentation model (Deeplabv3, UNet++, and UNet). The performance of three physicians was compared when the optimal model was used and not. The Net Reclassification Index (NRI) and Integrated Discrimination Improvement (IDI) were utilized to evaluate the clinical benefit of the optimal model. Results: The Deeplabv3 model performed optimally in terms of automatic segmentation. The ResNet18 deep learning model had the best prediction performance, with an area under the receiver-operating characteristic curve of 0.808 (0.694-0.923), 0.809 (0.712-0.906), and 0.812 (0.680-0.944) in the internal test set and external test sets 1 and 2, respectively. Meanwhile, the optimal model-assisted clinical and overall benefits were markedly enhanced for two out of three radiologists (in internal validation set, NRI: 0.259 and 0.213 [p = 0.002 and 0.017], IDI: 0.284 and 0.201 [p = 0.005 and 0.043], respectively; in external test set 1, NRI: 0.183 and 0.161 [p = 0.019 and 0.008], IDI: 0.205 and 0.184 [p = 0.031 and 0.045], respectively; in external test set 2, NRI: 0.297 and 0.297 [p = 0.038 and 0.047], IDI: 0.332 and 0.294 [p = 0.031 and 0.041], respectively). Conclusions: The deep learning model constructed for automatic segmentation of ultrasound images can improve the diagnostic performance of radiologists for PGTs.

Machine Learning Identify Ferroptosis-Related Genes as Potential Diagnostic Biomarkers for Gastric Intestinal Metaplasia.

BACKGROUND: Gastric intestinal metaplasia(GIM) is an independent risk factor for GC, however, its pathogenesis is still unclear. Ferroptosis is a new type of programmed cell death, which may be involved in the process of GIM. The purpose of this study was to analyze the expression of ferroptosis-related genes (FRGs) in GIM tissues and to explore the relationship between ferroptosis and GIM. METHOD: The results of GIM tissue full transcriptome sequencing were downloaded from Gene Expression Omnibus(GEO) database. R software (V4.2.0) and R packages were used for screening and enrichment analysis of differentially expressed genes(DEGs). The key genes were screened by least absolute shrinkage and selection operator(LASSO) and support vector machine-recursive feature elimination(SVM-RFE) algorithm. Receiver operating characteristic(ROC) curve was used to evaluate the diagnostic efficacy of key genes in GIM. Clinical samples were used to further validate hub genes. RESULTS: A total of 12 differentially expressed ferroptosis-related genes (DEFRGs) were identified. Using two machine learning algorithms, GOT1, ALDH3A2, ACSF2 and SESN2 were identified as key genes. The area under ROC curve (AUC) of GOT1, ALDH3A2, ACSF2 and SESN2 in the training set were 0.906, 0.955, 0.899 and 0.962 respectively, and the AUC in the verification set were 0.776, 0.676, 0.773 and 0.880, respectively. Clinical samples verified the differential expression of GOT1, ACSF2, and SESN2 in GIM. CONCLUSION: We found that there was a significant correlation between ferroptosis and GIM. GOT1, ACSF2 and SESN2 can be used as diagnostic markers to effectively identify GIM.

RNA-seq revealed the protective effect of Huangqi Guizhi Wuwu Decoction against cisplatin induced PC12 cell injury.

BACKGROUND: Chemotherapy-induced peripheral neuropathy not only affects the tolerability of chemotherapy, but also causes intolerable and prolonged neuropathic pain in cancer patients. Currently, duloxetine is the only drug used to treat chemotherapy-induced peripheral neuropathy. However, the clinical use of this drug still faces several challenges. Therefore, we focused on traditional Chinese medicine to find an effective and safe alternative medicine. Huangqi Guizhi Wuwu Decoction is a traditional Chinese medicine that has been clinically used for treating nerve pain for thousands of years. This study aimed to investigate the neuroprotective effect of Huangqi Guizhi Wuwu Decoction on cisplatin-induced nerve injury in PC12 cells and to elucidate its potential mechanism of action. METHODS: Huangqi Guizhi Wuwu Decoction-containing serum and blank serum were prepared from a rat model. The protective effects of Huangqi Guizhi Wuwu Decoction on cisplatin (10 µmol/L)-induced PC12 cell injury were assessed by a Cell Counting Kit-8 assay. RNA expression in Huangqi Guizhi Wuwu Decoction-protected PC12 cells was analyzed using RNA-seq, and subsequently, differentially expressed genes were further analyzed using Gene Ontology and Gene Set Enrichment Analysis. RESULTS: The Cell Counting Kit-8 results showed that pretreatment of PC12 cells with Huangqi Guizhi Wuwu Decoction-containing serum (5%, 10%, 15%) significantly increased cells' viability to 10 µmol/L cisplatin-induced cell death. RNA-seq analysis revealed 843 differentially expressed genes in the chemotherapy-induced peripheral neuropathy group and 249 in the Huangqi Guizhi Wuwu Decoction group. The gene set enrichment analysis results in this study suggest that Huangqi Guizhi Wuwu Decoction may treat chemotherapy-induced peripheral neuropathy by enhancing axon guidance. CONCLUSIONS: This study provides valuable evidence for using Huangqi Guizhi Wuwu Decoction in treating chemotherapy-induced peripheral neuropathy, partially achieved by improving axon guidance pathways.

Hearing Loss and Cognitive Impairment Among Community-Dwelling Older Adults - Liaoning, Henan, and Guangdong Provinces, China, 2019-2020.

What is already known about this topic?: Many studies have shown that hearing loss (HL) is a risk factor for cognitive decline and dementia, but there are still limited studies on this association among Chinese older adults. What is added by this report?: Based on the results of pure-tone audiometry tests, HL is associated with cognitive impairment in community-dwelling older adults. The odds ratios (ORs) were 1.23 (1.08-1.40) for mild HL, 1.55 (1.32-1.82) for moderate HL, and 1.87 (1.47-2.39) for severe or profound HL. What are the implications for public health practice?: Enhanced public awareness of hearing protection is important for preventing cognitive impairment. It is advocated to promote the screening of HL and cognitive function assessment in elderly health examinations or management in primary care services.

[Monitoring System of Medical Device Adverse Events in the US and Application of MAUDE Database in Medical Device Registration].

In order to achieve precise risk control of medical devices, it is necessary to establish a scientific evaluation system throughout the entire life cycle of medical devices that focuses on risk identification and risk control. This study summarizes the medical device adverse event monitoring system of the US on regulatory agencies and regulatory law, adverse events reporting forms and time limits, adverse event database, adverse event report analysis and evaluation, as well as adverse event feedback and control. Furthermore, some examples are provided to illustrate the application of the MAUDE database in risk analysis, physical and mechanical performance research, and clinical evaluation of medical device registration and application materials.

Differences in networks of alexithymia and cognitive emotion regulation strategies among older adults with different health statuses in eastern China-A network analysis and network comparison.

To identify core and bridge nodes in the network structure of alexithymia and cognitive emotion regulation strategies in community-dwelling older adults, and compare network differences among older adults with different health statuses, we recruited 677 participants and network analysis was performed in R 4.2.0. After including the covariates, the nodes Catastrophizing, Difficulty Identifying feelings, and Refocusing on Planning ranked as the top three. The nodes Externally Oriented Thoughts and Difficulty Identifying Feelings were identified as bridge nodes based on bridge strength values. Significant differences were observed between the healthy and comorbidity groups, and also between the single chronic disease and comorbidity groups (p < 0.05). Catastrophizing, Difficulty Identifying Feelings, and Refocusing on Planning were the core nodes, and Externally Oriented Thoughts and Difficulty Identifying Feelings were the key bridge nodes. The network structure of comorbidity in older adults was characterized by stronger ties to non-adaptive cognitive emotion regulation strategies.

Apoptosis mediated by crosstalk between mitochondria and endoplasmic reticulum: A possible cause of citrinin disruption of the intestinal barrier.

Citrinin (CTN) is a mycotoxin commonly found in contaminated foods and feed, posing health risks to both humans and animals. However, the mechanism by which CTN damages the intestine remains unclear. In this study, a model of intestinal injury was induced by administering 1.25 mg/kg and 5 mg/kg of CTN via gavage for 28 consecutive days in 6-week-old Kunming mice, aiming to explore the potential mechanisms underlying intestinal injury. The results demonstrate that CTN can cause structural damage to the mouse jejunum. Additionally, CTN reduces the protein expression of Claudin-1, Occludin, ZO-1, and MUC2, thereby disrupting the physical and chemical barriers of the intestine. Furthermore, exposure to CTN alters the structure of the intestinal microbiota in mice, thus compromising the intestinal microbial barrier. Meanwhile, the results showed that CTN exposure could induce excessive apoptosis in intestinal cells by altering the expression of proteins such as CHOP and GRP78 in the endoplasmic reticulum and Bax and Cyt c in mitochondria. The mitochondria and endoplasmic reticulum are connected through the mitochondria-associated endoplasmic reticulum membrane (MAM), which regulates the membrane. We found that the expression of bridging proteins Fis1 and BAP31 on the membrane was increased after CTN treatment, which would exacerbate the endoplasmic reticulum dysfunction, and could activate proteins such as Caspase-8 and Bid, thus further inducing apoptosis via the mitochondrial pathway. Taken together, these results suggest that CTN exposure can cause intestinal damage by disrupting the intestinal barrier and inducing excessive apoptosis in intestinal cells.

Spatial heterogeneity of per- and polyfluoroalkyl substances caused by glacial melting in Tibetan Lake Nam Co due to global warming.

Per- and polyfluoroalkyl substances (PFASs) in high-latitude polar regions and the Tibetan Plateau have received widespread international attention. Here, we measured 18 PFASs and 11 major isomers in the lake water, sediment, and surrounding runoff of Lake Nam Co in 2020. The concentrations of ultrashort-chain trifluoroacetic acid (TFA) and perfluoropropanoic acid (PFPrA) and major isomers of perfluoooctanoic acid (PFOA) and perfluoooctane sulfonate acid (PFOS) in water bodies in high-latitude polar regions and the Tibetan Plateau are reported for the first time. The results showed that the concentration of ∑PFASs in glacial runoff was approximately 139 % greater than that in nonglacial runoff. The concentrations of ∑PFASs in the lake water and sediment in the southern lake with multiple glacial runoff events were approximately 113 % and 108 % higher, respectively, than those in the northern lake. The concentrations of short-chain perfluorobutanoic acid (PFBA) and ultrashort-chain TFA and PFPrA, which may be indicators of ice and snow melt, exhibited significant spatial heterogeneity. Overall, the spatial heterogeneity of PFAS concentrations in the water, sediment and surrounding runoff of Lake Nam Co may be caused mainly by glacial melting.

Few-layer Bi2O2Se: A promising candidate for high-performance near-room-temperature thermoelectric applications.

Advancements in high-temperature thermoelectric materials have been substantial, yet identifying promising near-room-temperature candidates for efficient power generation from low-grade waste heat or thermoelectric cooling applications has become critical but proven exceedingly challenging. Bismuth oxyselenide (Bi2O2Se) emerges as an ideal candidate for near-room-temperature energy harvesting due to its low thermal conductivity, high carrier mobility and remarkable air-stability. In this study, the thermoelectric properties of few-layer Bi2O2Se over a wide temperature range (20 - 380 K) are investigated, where a charge transport mechanism transitioning from polar optical phonon (POP) to piezoelectric scattering at 140 K is observed. Moreover, the Seebeck coefficient (S) increases with temperature up to 280 K then stabilizes at ~-200 µV/K through 380 K. Bi2O2Se demonstrates high mobility (450 cm2V-1s-1) within the optimum power factor (PF) window, despite its T^(-1.25) dependence. The high mobility compensates the minor reduction in carrier density n2D hence contributes to maintain a robust electrical conductivity ~3x104 S/m. This results in a remarkable PF of 860 µW m-1K-2 at 280 K without the necessity for gating (Vg = 0 V), reflecting the innate performance of the as-grown material. These results underscore the considerable promise of Bi2O2Se for room temperature thermoelectric applications.

Decoding Micro-Electrocorticographic Signals by Using Explainable 3D Convolutional Neural Network to Predict Finger Movements.

BACKGROUND: Electroencephalography (EEG) and electrocorticography (ECoG) recordings have been used to decode finger movements by analyzing brain activity. Traditional methods focused on single bandpass power changes for movement decoding, utilizing machine learning models requiring manual feature extraction. NEW METHOD: This study introduces a 3D convolutional neural network (3D-CNN) model to decode finger movements using ECoG data. The model employs adaptive, explainable AI (xAI) techniques to interpret the physiological relevance of brain signals. ECoG signals from epilepsy patients during awake craniotomy were processed to extract power spectral density across multiple frequency bands. These data formed a 3D matrix used to train the 3D-CNN to predict finger trajectories. RESULTS: The 3D-CNN model showed significant accuracy in predicting finger movements, with root-mean-square error (RMSE) values of 0.26-0.38 for single finger movements and 0.20-0.24 for combined movements. Explainable AI techniques, Grad-CAM and SHAP, identified the high gamma (HG) band as crucial for movement prediction, showing specific cortical regions involved in different finger movements. These findings highlighted the physiological significance of the HG band in motor control. COMPARISON WITH EXISTING METHODS: The 3D-CNN model outperformed traditional machine learning approaches by effectively capturing spatial and temporal patterns in ECoG data. The use of xAI techniques provided clearer insights into the model's decision-making process, unlike the "black box" nature of standard deep learning models. CONCLUSIONS: The proposed 3D-CNN model, combined with xAI methods, enhances the decoding accuracy of finger movements from ECoG data. This approach offers a more efficient and interpretable solution for brain-computer interface (BCI) applications, emphasizing the HG band's role in motor control.

Atmospheric observation and emission estimation of HFC-125 and HFC-32 in China from four representative cities.

HFC-125 and HFC-32 are fluorinated greenhouse gases of great concern due to their high GWPs and increasing background atmospheric concentrations. Long-term atmospheric observations of HFC-125 and HFC-32 were carried out in four representative cities of China (Beijing, Guangzhou, Hangzhou, and Lanzhou) from January 2012 to October 2019. Overall, the annual mean atmospheric concentrations of HFC-125 and HFC-32 both showed increasing trends, with average rates of 4.8 ppt yr-1 and 7.9 ppt yr-1. The average concentrations of HFC-125 and HFC-32 in urban areas were significantly higher than those in suburban areas. Significant differences in atmospheric concentrations of the two HFCs were observed among the four cities. HFC-125 and HFC-32 emissions were estimated accordingly, averaging 6.2 Gg yr-1 (23.6 Mt. CO2-eq) and 5.7 Gg yr-1 (4.3 Mt. CO2-eq) during 2012 and 2019 and growing at rates of 0.8 Gg yr-1 (3.1 Mt. CO2-eq) and 0.8 Gg yr-1 (0.6 Mt. CO2-eq), respectively, with an increasing contribution to global radiative forcing. The bottom-up inventories of HFC-125 and HFC-32 in the four cities increased annually from 2012 to 2019, with the highest emissions in Beijing, while the top-down emissions fluctuated during the research period. SYNOPSIS: The atmospheric concentrations of HFC-125 and HFC-32 were measured from 2012 to 2019 in four representative cities of China. Both HFC emissions at national and city levels were estimated using observation-based and inventory methods.

Heterologous activation and metabolites identification of the pks7 gene cluster from Saccharopolyspora erythraea.

The microbial genome remains a huge treasure trove for the discovery of diverse natural products. Saccharopolyspora erythraea NRRL23338, the industry producer of erythromycin, has a dozen of biosynthetic gene clusters whose encoding products are unidentified. Heterologous expression of one of the polyketide clusters pks7 in Streptomyces albus B4 chassis resulted in the characterization of its function responsible for synthesizing both 6-methylsalicyclic acid and 6-ethylsalicyclic acid. Meanwhile, two new 6-ethylsalicyclic acid ester derivatives were isolated as shunt metabolites. Their structures were identified by comprehensive analysis of MS and NMR experiments. Putative functions of genes within the pks7 BGC were also discussed.

Does type 1 diabetes serve as a protective factor against inflammatory bowel disease: A Mendelian randomization study.

BACKGROUND: The impact of type 1 diabetes (T1D) on inflammatory bowel disease (IBD) remains unclear. AIM: To analyze the causal relationship between T1D and IBD using Mendelian ran-domization (MR). METHODS: Single nucleotide polymorphisms were sourced from FinnGen for T1D, IBD, ulcerative colitis (UC) and Crohn's disease (CD). Inverse variance-weighted, MR-Egger, and weighted median tests were used to assess exposure-outcome causality. The MR-Egger intercept was used to assess horizontal pleiotropy. Co-chran's Q and leave-one-out method were used to analyze heterogeneity and sensitivity, respectively. RESULTS: Our MR analysis indicated that T1D was associated with a reduced risk of IBD [odds ratio (OR): 0.959; 95% confidence interval (CI): 0.938-0.980; P < 0.001] and UC (OR: 0.960; 95%CI: 0.929-0.992; P = 0.015), with no significant association observed in terms of CD risk (OR: 0.966; 95%CI: 0.913-1.022; P = 0.227). The MR-Egger intercept showed no horizontal pleiotropy (P > 0.05). Cochran's Q and leave-one-out sensitivity analyses showed that the results were not heterogeneous (P > 0.05) and were robust. CONCLUSION: This MR analysis suggests that T1D serves as a potential protective factor against IBD and UC but is independent of CD.

Retrospective analysis based on a clinical grading system for patients with hepatic hemangioma: A single center experience.

BACKGROUND: The optimal approach for managing hepatic hemangioma is controversial. AIM: To evaluate a clinical grading system for management of hepatic hemangioma based on our 17-year of single institution experience. METHODS: A clinical grading system was retrospectively applied to 1171 patients with hepatic hemangioma from January 2002 to December 2018. Patients were classified into four groups based on the clinical grading system and treatment: (1) Observation group with score < 4 (Obs score < 4); (2) Surgical group with score < 4 (Sur score < 4); (3) Observation group with score ≥ 4 (Obs score ≥ 4); and (4) Surgical group with score ≥ 4 (Sur score ≥ 4). The clinico-pathological index and outcomes were evaluated. RESULTS: There were significantly fewer symptomatic patients in surgical groups (Sur score ≥ 4 vs Obs score ≥ 4, P < 0.001; Sur score < 4 vs Obs score < 4, χ² = 8.60, P = 0.004; Sur score ≥ 4 vs Obs score < 4, P < 0.001). The patients in Sur score ≥ 4 had a lower rate of in need for intervention and total patients with adverse event than in Obs score ≥ 4 (P < 0.001; P < 0.001). Nevertheless, there was no significant difference in need for intervention and total patients with adverse event between the Sur score < 4 and Obs score < 4 (P > 0.05; χ² = 1.68, P > 0.05). CONCLUSION: This clinical grading system appeared as a practical tool for hepatic hemangioma. Surgery can be suggested for patients with a score ≥ 4. For those with < 4, follow-up should be proposed.

Association Between Alcohol Consumption and Disability Accumulation in Multiple Sclerosis.

BACKGROUND AND OBJECTIVES: Previous studies have indicated that alcohol consumption is associated with multiple sclerosis (MS) disease progression. We aimed to study the influence of alcohol consumption habits on disease progression and health-related quality of life in MS. METHODS: We categorized patients from 2 population-based case-control studies by alcohol consumption habits at diagnosis and followed them up to 15 years after diagnosis through the Swedish MS registry regarding changes in the Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Impact Scale 29 (MSIS-29). We used Cox regression models with 95% confidence intervals (CIs) using 24-week confirmed disability worsening, EDSS 3, EDSS 4, and physical and psychological worsening from the patient's perspective as end points. RESULTS: Our study comprised 9,051 patients with MS, with a mean age of 37.5 years at baseline/diagnosis. Compared with nondrinking, low and moderate alcohol consumption was associated with reduced risk of EDSS-related unfavorable outcomes (hazard ratios between 0.81 and 0.90) and with reduced risk of physical worsening. The inverse association was confined to relapsing-remitting MS and was more pronounced among women. High alcohol consumption did not significantly affect disease progression. The inverse relationship between low-moderate alcohol consumption and disability progression became stronger when we only included those who had not changed their alcohol consumption during follow-up (hazard ratios between 0.63 and 0.71). There were no differences in measures of disability at baseline between drinkers who continued drinking alcohol after diagnosis and those who later discontinued. Our findings speak against bias due to reverse causation. DISCUSSION: Low and moderate alcohol consumption was associated with more favorable outcomes in relapsing-remitting MS, compared with nondrinking, while there was no significant influence of high alcohol consumption on disease outcomes.

Cobalt germanium hydroxides with asymmetric electron distribution and surface hydroxyl groups for superb catalytic degradation performances.

Peroxymonosulfate (PMS)-based advanced oxidation processes (AOPs) are attractive approaches for solving the global problem of water pollution, due to the generation of highly-active reactive oxygen species (ROS). Therefore, highly-efficient PMS activation is crucial for promoting the catalytic degradation of environmental pollutants. Here, bimetallic CoGeO2(OH)2 nanosheets with abundant surface hydroxyl groups (CGH) were synthesized via a simple hydrothermal route for PMS activation and degradation of various organic contaminants for the first time. The abundant surface hydroxyl groups (≡Co-OH/≡Ge-OH) could promptly initiate PMS to generate highly-active species: singlet oxygen (1O2), sulfate radicals (SO4·-) and hydroxyl radicals (HO•), while the asymmetric electron distribution among Co-O-Ge bonds derived from the higher electronegativity of Ge than Co further enhances the quick electron transfer to promote the redox cycle of Co2+/Co3+ and Ge2+/Ge4+, thereby achieving an outstanding catalytic capability. The optimal catalyst exhibits nearly 100 % catalytic degradation performance of dyes (Methylene blue, Rhodamine B, Methyl orange, Orange II, Methyl green) and antibiotics (Norfloxacin, Bisphenol A, Tetracycline) over a wide pH range of 3-11 and under different coexisting anion conditions (Cl-, HCO3-, NO3-, HA), suggesting the excellent adaptability for practical usage. This study could potentially lead to novel perspectives on the remediation of water areas such as groundwater and deep-water areas.

Based on machine learning, CDC20 has been identified as a biomarker for postoperative recurrence and progression in stage I & II lung adenocarcinoma patients.

Objective: By utilizing machine learning, we can identify genes that are associated with recurrence, invasion, and tumor stemness, thus uncovering new therapeutic targets. Methods: To begin, we obtained a gene set related to recurrence and invasion from the GEO database, a comprehensive gene expression database. We then employed the Weighted Gene Co-expression Network Analysis (WGCNA) to identify core gene modules and perform functional enrichment analysis on them. Next, we utilized the random forest and random survival forest algorithms to calculate the genes within the key modules, resulting in the identification of three crucial genes. Subsequently, one of these key genes was selected for prognosis analysis and potential drug screening using the Kaplan-Meier tool. Finally, in order to examine the role of CDC20 in lung adenocarcinoma (LUAD), we conducted a variety of in vitro and in vivo experiments, including wound healing assay, colony formation assays, Transwell migration assays, flow cytometric cell cycle analysis, western blotting, and a mouse tumor model experiment. Results: First, we collected a total of 279 samples from two datasets, GSE166722 and GSE31210, to identify 91 differentially expressed genes associated with recurrence, invasion, and stemness in lung adenocarcinoma. Functional enrichment analysis revealed that these key gene clusters were primarily involved in microtubule binding, spindle, chromosomal region, organelle fission, and nuclear division. Next, using machine learning, we identified and validated three hub genes (CDC45, CDC20, TPX2), with CDC20 showing the highest correlation with tumor stemness and limited previous research. Furthermore, we found a close association between CDC20 and clinical pathological features, poor overall survival (OS), progression-free interval (PFI), progression-free survival (PFS), and adverse prognosis in lung adenocarcinoma patients. Lastly, our functional research demonstrated that knocking down CDC20 could inhibit cancer cell migration, invasion, proliferation, cell cycle progression, and tumor growth possibly through the MAPK signaling pathway. Conclusion: CDC20 has emerged as a novel biomarker for monitoring treatment response, recurrence, and disease progression in patients with lung adenocarcinoma. Due to its significance, further research studying CDC20 as a potential therapeutic target is warranted. Investigating the role of CDC20 could lead to valuable insights for developing new treatments and improving patient outcomes.

Ultralow-Energy-Consumption Photosynaptic Transistor Utilizing Conjugated Polymers/Perovskite Quantum Dots Nanocomposites With Ligand Density Optimization.

The photosynaptic transistor stands as a promising contender for overcoming the von Neumann bottleneck in the realm of photo-communication. In this context, photonic synaptic transistors is developed through a straightforward solution process, employing an organic semiconducting polymer with pendant-naphthalene-containing side chains (PDPPNA) in combination with ligand-density-engineered CsPbBr3 perovskite quantum dots (PQDs). This fabrication approach allows the devices to emulate fundamental synaptic behaviors, encompassing excitatory postsynaptic current, paired-pulse facilitation, the transition from short-to-long-term memory, and the concept of "learning experience." Notably, the phototransistor, incorporating the blend of the PDPPNA and CsPbBr3 PQDs washed with ethyl acetate, achieved an exceptional memory ratio of 104. Simultaneously, the same device exhibited an impressive paired-pulse facilitation ratio of 223% at a moderate operating voltage of -4 V and an extraordinarily low energy consumption of 0.215 aJ at an ultralow operating voltage of -0.1 mV. Consequently, these low-voltage synaptic devices, constructed with a pendant side-chain engineering of organic semiconductors and a ligand density engineering of PQDs through a simple fabrication process, exhibit substantial potential for replicating the visual memory capabilities of the human brain.