Assessing the global distribution and risk of harmful microalgae: A focus on three toxic Alexandrium dinoflagellates.

Harmful dinoflagellates and their resulting blooms pose a threat to marine life and human health. However, to date, global maps of marine life often overlook harmful microorganisms. As harmful algal blooms (HABs) increase in frequency, severity, and extent, understanding the distribution of harmful dinoflagellates and their drivers is crucial for their management. We used MaxEnt, random forest, and ensemble models to map the habitats of the representative HABs species in the genus Alexandrium, including A. catenella, A. minutum, and A. pacificum. Since species occurrence records used in previous studies were solely morphology-based, potentially leading to misidentifications, we corrected these species' distribution records using molecular criteria. The results showed that the key environmental drivers included the distance to the coastline, bathymetry, sea surface temperature (SST), and dissolved oxygen. Alexandrium catenella thrives in temperate to cold zones and is driven by low SST and high oxygen levels. Alexandrium pacificum mainly inhabits the Temperate Northern Pacific and prefers warmer SST and lower oxygen levels. Alexandrium minutum thrives universally and adapts widely to SST and oxygen. By analyzing the habitat suitability of locations with recorded HAB occurrences, we found that high habitat suitability could serve as a reference indicator for bloom risk. Therefore, we have proposed a qualitative method to spatially assess the harmful algae risk according to the habitat suitability. On the global risk map, coastal temperate seas, such as the Mediterranean, Northwest Pacific, and Southern Australia, faced higher risks. Although HABs currently have restricted geographic distributions, our study found these harmful algae possess high environmental tolerance and can thrive across diverse habitats. HAB impacts could increase if climate changes or ocean conditions became more favorable. Marine transportation may also spread the harmful algae to new unaffected ecosystems. This study has pioneered the assessment of harmful algal risk based on habitat suitability.

Construction of Highly Accurate Machine Learning Potential Energy Surfaces for Excited-State Dynamics Simulations Based on Low-Level Data Sets.

Machine learning is capable of effectively predicting the potential energies of molecules in the presence of high-quality data sets. Its application in the construction of ground- and excited-state potential energy surfaces is attractive to accelerate nonadiabatic molecular dynamics simulations of photochemical reactions. Because of the huge computational cost of excited-state electronic structure calculations, the construction of a high-quality data set becomes a bottleneck. In the present work, we first built two data sets. One was obtained from surface hopping dynamics simulations at the semiempirical OM2/MRCI level. Another was extracted from the dynamics trajectories at the CASSCF level, which was reported previously. The ground- and excited-state potential energy surfaces of ethylene-bridged azobenzene at the CASSCF computational level were constructed based on the former low-level data set. Although non-neural network machine learning methods can achieve good or modest performance during the training process, only neural network models provide reliable predictions on the latter external test data set. The BPNN and SchNet combined with the Δ-ML scheme and the force term in the loss functions are recommended for dynamics simulations. Then, we performed excited-state dynamics simulations of the photoisomerization of ethylene-bridged azobenzene on machine learning potential energy surfaces. Compared with the lifetimes of the first excited state (S1) estimated at different computational levels, our results on the E isomer are in good agreement with the high-level estimation. However, the overestimation of the Z isomer is unimproved. It suggests that smaller errors during the training process do not necessarily translate to more accurate predictions on high-level potential energies or better performance on nonadiabatic dynamics simulations, at least in the present case.

Causal association between circulating blood cell traits and pulmonary embolism: a mendelian randomization study.

BACKGROUND: Pulmonary embolism (PE) is a life-threatening thromboembolic disease for which there is limited evidence for effective prevention and treatment. Our goal was to determine whether genetically predicted circulating blood cell traits could influence the incidence of PE. METHODS: Using single variable Mendelian randomization (SVMR) and multivariate Mendelian randomization (MVMR) analyses, we identified genetic associations between circulating blood cell counts and lymphocyte subsets and PE. GWAS blood cell characterization summary statistics were compiled from the Blood Cell Consortium. The lymphocyte subpopulation counts were extracted from summary GWAS statistics for samples from 3757 individuals that had been analyzed by flow cytometry. GWAS data related to PE were obtained from the FinnGen study. RESULTS: According to the SVMR and reverse MR, increased levels of circulating white blood cells (odds ratio [OR]: 0.88, 95% confidence interval [CI]: 0.81-0.95, p = 0.0079), lymphocytes (OR: 0.90, 95% CI: 0.84-0.97, p = 0.0115), and neutrophils (OR: 0.88, 95% CI: 0.81-0.96, p = 0.0108) were causally associated with PE susceptibility. MVMR analysis revealed that lower circulating lymphocyte counts (OR: 0.84, 95% CI: 0.75-0.94, p = 0.0139) were an independent predictor of PE. According to further MR results, this association may be primarily related to HLA-DR+ natural killer (NK) cells. CONCLUSIONS: Among European populations, there is a causal association between genetically predicted low circulating lymphocyte counts, particularly low HLA-DR+ NK cells, and an increased risk of PE. This finding supports observational studies that link peripheral blood cells to PE and provides recommendations for predicting and preventing this condition.

Comprehensive landscape of junctional genes and their association with overall survival of patients with lung adenocarcinoma.

Objectives: Junctional proteins are involved in tumorigenesis. Therefore, this study aimed to investigate the association between junctional genes and the prognosis of patients with lung adenocarcinoma (LUAD). Methods: Transcriptome, mutation, and clinical data were retrieved from The Cancer Genome Atlas (TCGA). "Limma" was used to screen differentially expressed genes. Moreover, Kaplan-Meier survival analysis was used to identify junctional genes associated with LUAD prognosis. The junctional gene-related risk score (JGRS) was generated based on multivariate Cox regression analysis. An overall survival (OS) prediction model combining the JGRS and clinicopathological properties was proposed using a nomogram and further validated in the Gene Expression Omnibus (GEO) LUAD cohort. Results: To our knowledge, this study is the first to demonstrate the correlation between the mRNA levels of 14 junctional genes (CDH15, CDH17, CDH24, CLDN6, CLDN12, CLDN18, CTNND2, DSG2, ITGA2, ITGA8, ITGA11, ITGAL, ITGB4, and PKP3) and clinical outcomes of patients with LUAD. The JGRS was generated based on these 14 genes, and a higher JGRS was associated with older age, higher stage levels, and lower immune scores. Thus, a prognostic prediction nomogram was proposed based on the JGRS. Internal and external validation showed the good performance of the prediction model. Mechanistically, JGRS was associated with cell proliferation and immune regulatory pathways. Mutational analysis revealed that more somatic mutations occurred in the high-JGRS group than in the low-JGRS group. Conclusion: The association between junctional genes and OS in patients with LUAD demonstrated by our "TCGA filtrating and GEO validating" model revealed a new function of junctional genes.

Potential molecular and cellular mechanisms of the effects of cuproptosis-related genes in the cardiomyocytes of patients with diabetic heart failure: a bioinformatics analysis.

Background: Diabetes mellitus is an independent risk factor for heart failure, and diabetes-induced heart failure severely affects patients' health and quality of life. Cuproptosis is a newly defined type of programmed cell death that is thought to be involved in the pathogenesis and progression of cardiovascular disease, but the molecular mechanisms involved are not well understood. Therefore, we aimed to identify biomarkers associated with cuproptosis in diabetes mellitus-associated heart failure and the potential pathological mechanisms in cardiomyocytes. Materials: Cuproptosis-associated genes were identified from the previous publication. The GSE26887 dataset was downloaded from the GEO database. Methods: The consistency clustering was performed according to the cuproptosis gene expression. Differentially expressed genes were identified using the limma package, key genes were identified using the weighted gene co-expression network analysis(WGCNA) method, and these were subjected to immune infiltration analysis, enrichment analysis, and prediction of the key associated transcription factors. Consistency clustering identified three cuproptosis clusters. The differentially expressed genes for each were identified using limma and the most critical MEantiquewhite4 module was obtained using WGCNA. We then evaluated the intersection of the MEantiquewhite4 output with the three clusters, and obtained the key genes. Results: There were four key genes: HSDL2, BCO2, CORIN, and SNORA80E. HSDL2, BCO2, and CORIN were negatively associated with multiple immune factors, while SNORA80E was positively associated, and T-cells accounted for a major proportion of this relationship with the immune system. Four enriched pathways were found to be associated: arachidonic acid metabolism, peroxisomes, fatty acid metabolism, and dorsoventral axis formation, which may be regulated by the transcription factor MECOM, through a change in protein structure. Conclusion: HSDL2, BCO2, CORIN, and SNORA80E may regulate cardiomyocyte cuproptosis in patients with diabetes mellitus-associated heart failure through effects on the immune system. The product of the cuproptosis-associated gene LOXL2 is probably involved in myocardial fibrosis in patients with diabetes, which leads to the development of cardiac insufficiency.

The New Delhi metallo-ß-lactamase-1 biosensor rapidly and accurately detected antibiotic plasma concentrations in cefuroxime-treated patients.

OBJECTIVES: Therapeutic drug monitoring (TDM) of ß-lactam antibiotics in critically ill patients may benefit dose optimisation, thus improving therapeutic outcomes. However, rapidly and accurately detecting these antibiotics in blood remains a challenge. This research group recently developed a thermometric biosensor called the New Delhi metallo-ß-lactamase-1 (NDM-1) biosensor, which detects multiple classes of ß-lactam antibiotics in spiked plasma samples. METHODS: This study assessed the NDM-1 biosensor's effectiveness in detecting plasma concentrations of ß-lactam antibiotics in treated patients. Seven patients receiving cefuroxime were studied. Plasma samples collected pre- and post-antibiotic treatment were analysed using the NDM-1 biosensor and compared with liquid chromatography coupled with ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). RESULTS: The biosensor detected plasma samples without dilution, and a brief pre-treatment using a polyvinylidene fluoride filter significantly lowered matrix effects, reducing the running time to 5-8 minutes per sample. The assay's linear range for cefuroxime (6.25-200 mg/L) covered target concentrations during the trough phase of pharmacokinetics in critically ill patients. The pharmacokinetic properties of cefuroxime in treated patients determined by the NDM-1 biosensor and the UPLC-MS/MS were comparable, and the cefuroxime plasma concentrations measured by the two methods showed statistically good consistency. CONCLUSION: These data demonstrate that the NDM-1 biosensor assay is a fast, sensitive, and accurate method for detecting cefuroxime plasma concentrations in treated patients and highlights the NDM-1 biosensor as a promising tool for on-site TDM of ß-lactam antibiotics in critically ill patients.

[Spatio-temporal Evolution of Drought and Its Impact on Key Resources in the Important Ecological Functional Area: A Case Study in the Yellow River Basin].

This study explored the characteristics of spatial and temporal changes in drought in the Yellow River Basin from 2001 to 2020 based on TVPDI, surface runoff, vegetation net primary productivity, and grain yield data. Further, the effects of drought on water resources, grain resources, and vegetation resources were also analyzed using data spatialization methods, slope trend analysis, and Pearson correlation analysis. The results showed that:① The spatial distribution of drought in the Yellow River basin was stepped from southeast to northwest, and 60.6 % of the basin was in drought. The overall trend of drought in the basin was decreasing annually, and 94 % of the basin was gradually changing from drought to wet conditions, and the trend of drought from spring to winter decreased first and then increased. ② From the spatial and temporal changes in important resources in the basin, 53 % of the key surface runoff areas showed an increasing trend and were mainly located in the southwest of the basin; the net primary productivity (NPP) of vegetation and grain yield of food resources also showed an increasing trend. ③ Drought and the three types of resources showed significant spatial correlations, and the higher the degree of drought, the more significant the effects on surface runoff, vegetation productivity, and grain yield. However, the important resources in areas that had become wetter in recent years had not increased significantly, which indicated that the effects of drought on the three types of important resources had a time lag, and their lags had significant differences in spatial distribution and geographical differentiation patterns. This study has important theoretical implications for agricultural production, drought mitigation, and ecological conservation in the Yellow River Basin.

Adolescent's explicit and implicit cigarette cognitions predict experimentation with both cigarettes and e-cigarettes.

Background: Past year, month, and lifetime adolescent e-cigarette use rates remain persistently high, despite falling cigarette use rates. Previous investigations have noted a strong relationship between an individual's positive and negative cognitions related to a behavior, and subsequent initiation of that behavior.Objective: This investigation was conducted to determine the impact positive and negative explicit and implicit cigarette-related cognitions may have on the use of cigarettes and e-cigarettes among at-risk, cigarette-naive adolescents.Methods: A three-year longitudinal investigation evaluated the relationship between cigarette-related cognitions and subsequent cigarette and e-cigarette use among 586 alternative high school students (female: 50.8%; mean age: 17.4 years; Hispanic/Latino: 75.0%) who had never smoked cigarettes at the baseline assessment. Multilevel logistic regression models were used to generate demographics-adjusted odds ratios (OR) and 95% confidence intervals (95% CI).Results: Students with higher positive explicit cigarette cognitions at the baseline had greater odds of subsequent cigarette use (OR = 1.72, 95% CI 1.11-2.68). If students also reported an increase over time in positive (OR = 3.45, 95% CI 2.10-5.68) or negative (OR = 1.93, 95% CI 1.03-3.61) explicit cigarette cognitions, the odds of cigarette use increased. The odds of dual use of cigarettes and e-cigarettes were greater among students who had higher negative implicit cigarette cognitions at the baseline (OR = 2.07, 95% CI 1.03-4.17) compared to those with lower levels of negative implicit cognitions.Conclusion: Prevention programming that focuses on decreasing positive cognitions related to nicotine and tobacco use may have greater overall effect on decreasing use compared to programs that only focus on increasing negative cognitions individuals form surrounding cigarette or e-cigarettes.

EP300 through upregulating the expression of vimentin to promote the progression of chordoma.

OBJECTIVE: There is a lack of effective drugs to treat the progression and recurrence of chordoma, which is widely resistant to treatment in chemotherapy. The authors investigated the functional and therapeutic relevance of the E1A-binding protein p300 (EP300) in chordoma. METHODS: The expression of EP300 and vimentin was examined in specimens from 9 patients with primary and recurrent chordoma with immunohistochemistry. The biological functions of EP300 were evaluated with Cell Counting Kit-8, clonogenic assays, and transwell assays. The effects of EP300 inhibitors (C646 and SGC-CBP30) on chordoma cell motility were assessed with these assays. The effect of the combination of EP300 inhibitors and cisplatin on chordoma cells was evaluated with clonogenic assays. Reverse transcription quantitative polymerase chain reaction and Western blot techniques were used to explore the potential mechanism of EP300 through upregulation of the expression of vimentin to promote the progression of chordoma. RESULTS: Immunohistochemistry analysis revealed a positive correlation between elevated EP300 expression levels and recurrence. The upregulation of EP300 stimulated the growth of and increased the migratory and invasive capabilities of chordoma cells, along with upregulating vimentin expression and consequently impacting their invasive properties. Conversely, EP300 inhibitors decreased cell proliferation and downregulated vimentin. Furthermore, the combination of EP300 inhibition and cisplatin exhibited an enhanced anticancer effect on chordoma cells, indicating that EP300 may influence chordoma sensitivity to chemotherapy. CONCLUSIONS: These findings indicate that EP300 functions as an oncogene in chordoma. Targeting EP300 offers a novel approach to the development and clinical treatment of chordoma.

Multi-fidelity machine learning for predicting bandgaps of nonlinear optical crystals.

Nonlinear optical (NLO) materials are of great importance in modern optics and industry because of their intrinsic capability of wavelength conversion. Bandgap is a key property of NLO crystals. In recent years, machine learning (ML) has become a powerful tool to predict the bandgaps of compounds before synthesis. However, the shortage of available experimental data of NLO crystals poses a significant challenge for the exploration of new NLO materials using ML. In this work, we proposed a new multi-fidelity ML approach based on the multilevel descriptors developed by us (Z.-Y. Zhang, X. Liu, L. Shen, L. Chen and W.-H. Fang, J. Phys. Chem. C, 2021, 125, 25175-25188) and the gradient boosting regression tree algorithm. The calculated and experimental bandgaps of NLO crystals were collected as the low- and high-fidelity labels, respectively. The experimental values were predicted based on chemical compositions of crystals without prior knowledge about crystal structures. The multi-fidelity ML model overcame the performance of single-fidelity predictor. Furthermore, it was observed that less accurate predictions on the low-fidelity label may result in more accurate prediction on the high-fidelity label, at least in the present case. Using the multi-fidelity ML model with the best performance in this work, the mean absolute error on the test set of experimental bandgaps was 0.293 eV, which is smaller than that using the single-fidelity model (0.355 eV). It is far from perfect but accurate enough as an effective computational tool in the first step to discover novel NLO materials.

Retinoschisin Is Required for Pineal Gland Calcification and Cellular Communication in Pinealocytes of Rats and Mice.

Retinoschisin (RS1) is a secretory protein specifically localized to the extracellular domains in both the lateral retina and the pineal gland (PG). However, the functions of RS1 in the pineal body are poorly understood. To address this knowledge gap, in this study, we undertook histochemical, ultrastructural, and Western blotting analyses of the PG in rats and RS1-knock-in transgenic. We found that RS1 plays a key role in pineal gland calcification (PGC) in mice through both extracellular and intracellular pathways. RS1 was clustered around the cell membrane or intracellularly in pinealocytes, actively participating in the exchange of calcium and thereby mediating PGC. Additionally, RS1 deposition is essential for maintaining PGC architecture in the intercellular space of the adult PG. In RS1-knock-in mice with a nonsense mutation (p.Y65X) in the Rs1-domain of RS1, the Rs1-domain is chaotically dispersed in pinealocytes and the intercellular region of the PG. This prevents RS1 from binding calcified spots and forming calcified nodules, ultimately leading to the accumulation of calcareous lamellae in microvesicles. Additionally, RS1 was observed to colocalize with connexin-36, thereby modulating intercellular communication in the PG of both rats and mice. Our study revealed for the first time that RS1 is essential for maintaining PGC architecture and that it colocalizes with connexin 36 to modulate intercellular communication in the PG. These findings provide novel insights into the function of the RS1 gene in the PG.

Histology and transcriptomic analysis reveal the inflammation and affected pathways under 2-methylisoborneol (2-MIB) exposure on grass carp.

2-Methylisoborneol (2-MIB) is a common and widely distributed off-flavor compound in water. However, the toxic mechanisms of 2-MIB on aquatic organisms remain largely unexplored. In this study, grass carp larvae were exposed to different concentrations (0, 5, and 20 µg L-1) of 2-MIB for 96 h. The accumulation of 2-MIB in the dorsal muscle was measured. Histological analysis, ultrastructure observations, and transcriptomic sequencing were conducted on the liver tissues. The results showed that 2-MIB accumulated significantly in the fish muscle, with the accumulation increasing as the exposure concentration increased through gas chromatography-mass spectrometry (GC-MS) detection. Histological and ultrastructure observations indicated that 2-MIB caused concentration-dependent inflammatory infiltration and mitochondrial damage in the liver. Transcriptomic analysis revealed lipid metabolism disorders induced by exposure to 2-MIB in grass carp. Additionally, 5 µg L-1 2-MIB affected the neurodevelopment and cardiovascular system of grass carp larvae through extracellular matrix (ECM)-receptor interaction and focal adhesion pathway. Furthermore, several pathways related to the digestive system were significantly enriched, implying that 2-MIB may impact pancreatic secretion function, protein digestion and absorption processes. These findings provide new insights into the potential toxicological mechanisms of 2-MIB.

Endoplasmic reticulum stress-related gene expression causes the progression of dilated cardiomyopathy by inducing apoptosis.

Background: Previous studies have shown that endoplasmic reticulum stress (ERS) -induced apoptosis is involved in the pathogenesis of dilated cardiomyopathy (DCM). However, the molecular mechanism involved has not been fully characterized. Results: In total, eight genes were obtained at the intersection of 1,068 differentially expressed genes (DEGs) from differential expression analysis between DCM and healthy control (HC) samples, 320 module genes from weighted gene co-expression network analysis (WGCNA), and 2,009 endoplasmic reticulum stress (ERGs). These eight genes were found to be associated with immunity and angiogenesis. Four of these genes were related to apoptosis. The upregulation of MX1 may represent an autocompensatory response to DCM caused by a virus that inhibits viral RNA and DNA synthesis, while acting as an autoimmune antigen and inducing apoptosis. The upregulation of TESPA1 would lead to the dysfunction of calcium release from the endoplasmic reticulum. The upregulation of THBS4 would affect macrophage differentiation and apoptosis, consistent with inflammation and fibrosis of cardiomyocytes in DCM. The downregulation of MYH6 would lead to dysfunction of the sarcomere, further explaining cardiac remodeling in DCM. Moreover, the expression of genes affecting the immune micro-environment was significantly altered, including TGF-ß family member. Analysis of the co-expression and competitive endogenous RNA (ceRNA) network identified XIST, which competitively binds seven target microRNAs (miRNAs) and regulates MX1 and THBS4 expression. Finally, bisphenol A and valproic acid were found to target MX1, MYH6, and THBS4. Conclusion: We have identified four ERS-related genes (MX1, MYH6, TESPA1, and THBS4) that are dysregulated in DCM and related to apoptosis. This finding should help deepen understanding of the role of endoplasmic reticulum stress-induced apoptosis in the development of DCM.

Analysis of drought and heat stress response genes in rice using co-expression network and differentially expressed gene analyses.

Studies on Oryza sativa (rice) are crucial for improving agricultural productivity and ensuring global sustenance security, especially considering the increasing drought and heat stress caused by extreme climate change. Currently, the genes and mechanisms underlying drought and heat resistance in rice are not fully understood, and the scope for enhancing the development of new strains remains considerable. To accurately identify the key genes related to drought and heat stress responses in rice, multiple datasets from the Gene Expression Omnibus (GEO) database were integrated in this study. A co-expression network was constructed using a Weighted Correlation Network Analysis (WGCNA) algorithm. We further distinguished the core network and intersected it with differentially expressed genes and multiple expression datasets for screening. Differences in gene expression levels were verified using quantitative real-time polymerase chain reaction (PCR). OsDjC53, MBF1C, BAG6, HSP23.2, and HSP21.9 were found to be associated with the heat stress response, and it is also possible that UGT83A1 and OsCPn60a1, although not directly related, are affected by drought stress. This study offers significant insights into the molecular mechanisms underlying stress responses in rice, which could promote the development of stress-tolerant rice breeds.

The Impact of Mobile Social Media Use on Depressive Mood Among College Students: A Chain Mediating Effect of Upward Social Comparison and Cognitive Overload.

Background: The 18-24 age group has a much higher rate of depression risk than other age groups, and this age group has the highest proportion among users of mobile social media. The relationship between the use of mobile social media and depressive mood is inconsistent and the mechanism of action is controversial. Purpose: This study explored the relationship among the intensity of social media use, upward social comparison, cognitive overload and depressive mood. Methods: In this research, we used the Brief Self-rating Depression Scale (PHQ-9), the Social Media Usage Intensity Questionnaire, the Social Comparison Scale on Social Networking Sites and the Social Networking Site Cognitive Overload Scale to investigate the depressive mood and mobile social media use of 568 college students. Results: The intensity of mobile social media use, social networking site upward social comparison, and social networking site cognitive overload are all positively correlated with depressive mood. The intensity of mobile social media use has a positive predictive effect on depressive mood, with upward social comparison and cognitive overload acting as independent mediators in the relationship between mobile social media use intensity and depressive symptoms, as well as exhibiting a chained mediating effect of upward social comparison-cognitive overload. Conclusion: The upward social comparison and cognitive load that occur during the use of mobile social media are important predictive factors for the occurrence of depressive mood. This study is a supplement to the mechanism of the relationship between mobile social media use and depression, providing more evidence-based evidence and intervention directions for university teachers, mobile social media developers, and psychologists.

Modulating solvated structure of Zn2+ and inducing surface crystallography by a simple organic molecule with abundant polar functional groups to synergistically stabilize zinc metal anodes for long-life aqueous zinc-ion batteries.

Aqueous zinc-ion batteries (AZIBs) have attracted significant attention owing to their inherent security, low cost, abundant zinc (Zn) resources and high energy density. Nevertheless, the growth of zinc dendrites and side reactions on the surface of Zn anodes during repeatedly plating/stripping shorten the cycle life of AZIBs. Herein, a simple organic molecule with abundant polar functional groups, 2,2,2-trifluoroether formate (TF), has been proposed as a high-efficient additive in the ZnSO4 electrolyte to suppress the growth of Zn dendrites and side reaction during cycling. It is found that TF molecules can infiltrate the solvated sheath layer of the hydrated Zn2+ to reduce the number of highly chemically active H2O molecules owing to their strong binding energy with Zn2+. Simultaneously, TF molecules can preferentially adsorb onto the Zn surface, guiding the uniform deposition of Zn2+ along the crystalline surface of Zn(002). This dual action significantly inhibits the formation of Zn dendrites and side reactions, thus greatly extending the cycling life of the batteries. Accordingly, the Zn//Cu asymmetric cell with 2 % TF exhibits stable cycling for more than 3,800 cycles, achieving an excellent average Columbic efficiency (CE) of 99.81 % at 2 mA cm-2/1 mAh cm-2. Meanwhile, the Zn||Zn symmetric cell with 2 % TF demonstrates a superlong cycle life exceeding 3,800 h and 2,400 h at 2 mA cm-2/1 mAh cm-2 and 5 mA cm-2/2.5 mAh cm-2, respectively. Simultaneously, the Zn//VO2 full cell with 2 % TF possesses high initial capacity (276.8 mAh/g) and capacity retention (72.5 %) at 5 A/g after 500 cycles. This investigation provides new insights into stabilizing Zn metal anodes for AZIBs through the co-regulation of Zn2+ solvated structure and surface crystallography.

New insights into immune cells in cancer immunotherapy: from epigenetic modification, metabolic modulation to cell communication.

Cancer is one of the leading causes of death worldwide, and more effective ways of attacking cancer are being sought. Cancer immunotherapy is a new and effective therapeutic method after surgery, radiotherapy, chemotherapy, and targeted therapy. Cancer immunotherapy aims to kill tumor cells by stimulating or rebuilding the body's immune system, with specific efficiency and high safety. However, only few tumor patients respond to immunotherapy and due to the complex and variable characters of cancer immune escape, the behavior and regulatory mechanisms of immune cells need to be deeply explored from more dimensions. Epigenetic modifications, metabolic modulation, and cell-to-cell communication are key factors in immune cell adaptation and response to the complex tumor microenvironment. They collectively determine the state and function of immune cells through modulating gene expression, changing in energy and nutrient demands. In addition, immune cells engage in complex communication networks with other immune components, which are mediated by exosomes, cytokines, and chemokines, and are pivotal in shaping the tumor progression and therapeutic response. Understanding the interactions and combined effects of such multidimensions mechanisms in immune cell modulation is important for revealing the mechanisms of immunotherapy failure and developing new therapeutic targets and strategies.

Lightweight and drift-free magnetically actuated millirobots via asymmetric laser-induced graphene.

Millirobots must have low cost, efficient locomotion, and the ability to track target trajectories precisely if they are to be widely deployed. With current materials and fabrication methods, achieving all of these features in one millirobot remains difficult. We develop a series of graphene-based helical millirobots by introducing asymmetric light pattern distortion to a laser-induced polymer-to-graphene conversion process; this distortion resulted in the spontaneous twisting and peeling off of graphene sheets from the polymer substrate. The lightweight nature of graphene in combine with the laser-induced porous microstructure provides a millirobot scaffold with a low density and high surface hydrophobicity. Magnetically driven nickel-coated graphene-based helical millirobots with rapid locomotion, excellent trajectory tracking, and precise drug delivery ability were fabricated from the scaffold. Importantly, such high-performance millirobots are fabricated at a speed of 77 scaffolds per second, demonstrating their potential in high-throughput and large-scale production. By using drug delivery for gastric cancer treatment as an example, we demonstrate the advantages of the graphene-based helical millirobots in terms of their long-distance locomotion and drug transport in a physiological environment. This study demonstrates the potential of the graphene-based helical millirobots to meet performance, versatility, scalability, and cost-effectiveness requirements simultaneously.

Comparative molecular dynamics simulations provided insights into the mechanisms of cold-adaption of alginate lyases from the PL7 family.

Alginate is an important polysaccharide that is abundant in the marine environments, including the Polar Regions, and bacterial alginate lyases play key roles in its degradation. Many reported alginate lyases show characteristics of cold-adapted enzymes, including relatively low temperature optimum of activities (Topt) and low thermal stabilities. However, the cold-adaption mechanisms of alginate lyases remain unclear. Here, we studied the cold-adaptation mechanisms of alginate lyases by comparing four members of the PL7 family from different environments: AlyC3 from the Arctic ocean (Psychromonas sp. C-3), AlyA1 from the temperate ocean (Zobellia galactanivorans), PA1167 from the human pathogen (Pseudomonas aeruginosa PAO1), and AlyQ from the tropic ocean (Persicobacter sp. CCB-QB2). Sequence comparison and comparative molecular dynamics (MD) simulations revealed two main strategies of cold adaptation. First, the Arctic AlyC3 and temperate AlyA1 increased the flexibility of the loops close to the catalytic center by introducing insertions at these loops. Second, the Arctic AlyC3 increased the electrostatic attractions with the negatively charged substrate by introducing a high portion of positively charged lysine at three of the insertions mentioned above. Furthermore, our study also revealed that the root mean square fluctuation (RMSF) increased greatly when the temperature was increased to Topt or higher, suggesting the RMSF increase temperature as a potential indicator of the cold adaptation level of the PL7 family. This study provided new insights into the cold-adaptation mechanisms of bacterial alginate lyases and the marine carbon cycling at low temperatures.