Earth-abundant Zn-dipyrrin chromophores for efficient CO2 photoreduction.

The development of strong sensitizing and Earth-abundant antenna molecules is highly desirable for CO2 reduction through artificial photosynthesis. Herein, a library of Zn-dipyrrin complexes (Z-1-Z-6) are rationally designed via precisely controlling their molecular configuration to optimize strong sensitizing Earth-abundant photosensitizers. Upon visible-light excitation, their special geometry enables intramolecular charge transfer to induce a charge-transfer state, which was first demonstrated to accept electrons from electron donors. The resulting long-lived reduced photosensitizer was confirmed to trigger consecutive intermolecular electron transfers for boosting CO2-to-CO conversion. Remarkably, the Earth-abundant catalytic system with Z-6 and Fe-catalyst exhibits outstanding performance with a turnover number of >20 000 and 29.7% quantum yield, representing excellent catalytic performance among the molecular catalytic systems and highly superior to that of noble-metal photosensitizer Ir(ppy)2(bpy)+ under similar conditions. Experimental and theoretical investigations comprehensively unveil the structure-activity relationship, opening up a new horizon for the development of Earth-abundant strong sensitizing chromophores for boosting artificial photosynthesis.

Understanding secondary particles in a regional site of Yangtze River Delta: Insights from mass spectrometric measurement.

Submicron particulate matter (PM1) poses significant risks to health risks and global climate. In this study, secondary organic aerosols (SOA) and inorganic compositions were examined for their physicochemical characteristics and evolution using high-resolution aerosol instruments in Changzhou over one-month period. The results showed that transport accompanied by regional static conditions leaded to the occurrence of heavy pollution. In addition, regional generation and local emissions also leaded to the occurrence of light and moderate pollution during the observation period in Changzhou. Organic aerosols (OA) and nitrate (NO3-) accounted for 45 % and 23 % of PM1, respectively. The increase in PM1 was dominated by the contribution of NO3- and OA. SOA was dominance in OA (63 % with 40 % MO-OOA), which was higher than primary organic aerosols (POA). Besides, photochemical reactions and the high oxidizing nature of the urban atmosphere promoted the production of OA, especially MO-OOA in Changzhou. Our results highlight that secondary particles contribute significantly to PM pollution in Changzhou, underlining the importance of controlling emissions of gaseous precursors, especially under high oxidation conditions.

Elucidating the unexpected importance of intermediate-volatility organic compounds (IVOCs) from refueling procedure.

Evaporative emissions release organic compounds comparable to gasoline exhaust in China. However, the measurement of intermediate volatility organic compounds (IVOCs) is lacking in studies focusing on gasoline evaporation. This study sampled organics from a real-world refueling procedure and analyzed the organic compounds using comprehensive two-dimensional gas chromatography coupled with a mass spectrometer (GC×GC-MS). The non-target analysis detected and quantified 279 organics containing 93 volatile organic compounds (VOCs, 64.9 ± 7.4 % in mass concentration), 182 IVOCs (34.9 ± 7.4 %), and 4 semivolatile organic compounds (SVOCs, 0.2 %). The refueling emission profile was distinct from that of gasoline exhaust. The b-alkanes in the B12 volatility bin are the most abundant IVOC species (1.9 ± 1.4 µg m-3) in refueling. A non-negligible contribution of 17.5 % to the ozone formation potential (OFP) from IVOCs was found. Although IVOCs are less in concentration, secondary organic aerosol potential (SOAP) from IVOCs (58.1 %) even exceeds SOAP from VOCs (41.6 %), mainly from b-alkane in the IVOC range. At the molecular level, the proportion of cyclic compounds in SOAP (12.1 %) indeed goes above its mass concentration (3.1 %), mainly contributed by cyclohexanes and cycloheptanes. As a result, the concentrations and SOAP of cyclic compounds (>50 %) could be overestimated in previous studies. Our study found an unexpected contribution of IVOCs from refueling procedures to both ozone and SOA formation, providing new insights into secondary pollution control policy.

Molecular strategies of the pygmy grasshopper Eucriotettix oculatus adapting to long-term heavy metal pollution.

To study the heavy metal accumulation and its impact on insect exterior and chromosome morphology, and reveal the molecular mechanism of insects adapting to long-term heavy metal compound pollution habitats, this study, in the Diaojiang river basin, which has been polluted by heavy metals(HMs) for nearly a thousand years, two Eucriotettix oculatus populations was collected from mining and non-mining areas. It was found that the contents of 7 heavy metals (As, Cd, Pb, Zn, Cu, Sn, Sb) in E. oculatus of the mining area were higher than that in the non-mining 1-11 times. The analysis of morphology shows that the external morphology, the hind wing type and the chromosomal morphology of E. oculatus are significant differences between the two populations. Based on the heavy metal accumulation，morphological change, and stable population density, it is inferred that the mining area population has been affected by heavy metals and has adapted to the environment of heavy metals pollution. Then, by analyzing the transcriptome of the two populations, it was found that the digestion, immunity, excretion, endocrine, nerve, circulation, reproductive and other systems and lysosomes, endoplasmic reticulum and other cell structure-related gene expression were suppressed. This shows that the functions of the above-mentioned related systems of E. oculatus are inhibited by heavy metal stress. However, it has also been found that through the significant up-regulation of genes related to the above system, such as ATP2B, pepsin A, ubiquitin, AQP1, ACOX, ATPeV0A, SEC61A, CANX, ALDH7A1, DLD, aceE, Hsp40, and catalase, etc., and the down-regulation of MAPK signalling pathway genes, can enhanced nutrient absorption, improve energy metabolism, repair damaged cells and degrade abnormal proteins, maintain the stability of cells and systems, and resist heavy metal damage so that E. oculatus can adapt to the environment of heavy metal pollution for a long time.

Approaches for the Treatment and Resource Utilization of Electroplating Sludge.

The disposal of electroplating sludge (ES) is a major challenge for the sustainable development of the electroplating industry. ESs have a significant environmental impact, occupying valuable land resources and incurring high treatment costs, which increases operational expenses for companies. Additionally, the high concentration of hazardous substances in ES poses a serious threat to both the environment and human health. Despite extensive scholarly research on the harmless treatment and resource utilization of ES, current technology and processes are still unable to fully harness its potential. This results in inefficient resource utilization and potential environmental hazards. This article analyzes the physicochemical properties of ES, discusses its ecological hazards, summarizes research progress in its treatment, and elaborates on methods such as solidification/stabilization, heat treatment, wet metallurgy, pyrometallurgy, biotechnology, and material utilization. It provides a comparative summary of different treatment processes while also discussing the challenges and future development directions for technologies aimed at effectively utilizing ES resources. The objective of this text is to provide useful information on how to address the issue of ES treatment and promote sustainable development in the electroplating industry.

Building Co16-N3-based UiO-MOF to Expand Design Parameters for MOF Photosensitization.

The construction of secondary building units (SBUs) in versatile metal-organic frameworks (MOFs) represents a promising method for developing multi-functional materials, especially for improving their sensitizing ability. Herein, we developed a dual small molecules auxiliary strategy to construct a high-nuclear transition-metal-based UiO-architecture Co16-MOF-BDC with visible-light-absorbing capacity. Remarkably, the N3- molecule in hexadecameric cobalt azide SBU offers novel modification sites to precise bonding of strong visible-light-absorbing chromophores via click reaction. The resulting Bodipy@Co16-MOF-BDC exhibits extremely high performance for oxidative coupling benzylamine (~100% yield) via both energy and electron transfer processes, which is much superior to that of Co16-MOF-BDC (31.5%) and Carboxyl Bodipy@Co16-MOF-BDC (37.5%). Systematic investigations reveal that the advantages of Bodipy@Co16-MOF-BDC in dual light-absorbing channels, robust bonding between Bodipy/Co16 clusters and efficient electron-hole separation can greatly boost photosynthesis. This work provides an ideal molecular platform for synergy between photosensitizing MOFs and chromophores by constructing high-nuclear transition-metal-based SBUs with surface-modifiable small molecules.

Global research hotspots, development trends and prospect discoveries of phase separation in cancer: a decade-long informatics investigation.

Liquid-liquid phase separation (LLPS) is a complex and subtle phenomenon whose formation and regulation take essential roles in cancer initiation, growth, progression, invasion, and metastasis. This domain holds a wealth of underutilized unstructured data that needs further excavation for potentially valuable information. Therefore, we retrospectively analyzed the global scientific knowledge in the field over the last decade by using informatics methods (such as hierarchical clustering, regression statistics, hotspot burst, and Walktrap algorithm analysis). Over the past decade, this area enjoyed a favorable development trend (Annual Growth Rate: 34.98%) and global collaboration (International Co-authorship: 27.31%). Through unsupervised hierarchical clustering based on machine learning, the global research hotspots were divided into five dominant research clusters: Cluster 1 (Effects and Mechanisms of Phase Separation in Drug Delivery), Cluster 2 (Phase Separation in Gene Expression Regulation), Cluster 3 (Phase Separation in RNA-Protein Interaction), Cluster 4 (Reference Value of Phase Separation in Neurodegenerative Diseases for Cancer Research), and Cluster 5 (Roles and Mechanisms of Phase Separation). And further time-series analysis revealed that Cluster 5 is the emerging research cluster. In addition, results from the regression curve and hotspot burst analysis point in unison to super-enhancer (a=0.5515, R2=0.6586, p=0.0044) and stress granule (a=0.8000, R2=0.6000, p=0.0085) as the most potential star molecule in this field. More interestingly, the Random-Walk-Strategy-based Walktrap algorithm further revealed that "phase separation, cancer, transcription, super-enhancer, epigenetics"(Relevance Percentage[RP]=100%, Development Percentage[DP]=29.2%), "stress granule, immunotherapy, tumor microenvironment, RNA binding protein"(RP=79.2%, DP=33.3%) and "nanoparticle, apoptosis"(RP=70.8%, DP=25.0%) are closely associated with this field, but are still under-developed and worthy of further exploration. In conclusion, this study profiled the global scientific landscape, discovered a crucial emerging research cluster, identified several pivotal research molecules, and predicted several crucial but still under-developed directions that deserve further research, providing an important reference value for subsequent basic and clinical research of phase separation in cancer.

Comparative investigation of neoadjuvant immunotherapy versus adjuvant immunotherapy in perioperative patients with cancer: a global-scale, cross-sectional, large-sample informatics study.

BACKGROUND: Neoadjuvant and adjuvant immunotherapies for cancer have evolved through a series of remarkable and critical research advances; however, addressing their similarities and differences is imperative in clinical practice. Therefore, this study aimed to examine their similarities and differences from the perspective of informatics analysis. METHODS: This cross-sectional study retrospectively analyzed extensive relevant studies published between 2014 and 2023 using stringent search criteria, excluding non-peer-reviewed and non-English documents. The main outcome variables are publication volume, citation volume, connection strength, occurrence frequency, relevance percentage, and development percentage. Furthermore, an integrated comparative analysis was conducted using unsupervised hierarchical clustering, spatiotemporal analysis, regression statistics, and Walktrap algorithm analysis. RESULTS: This analysis included 1,373 relevant studies. Advancements in neoadjuvant and adjuvant immunotherapies have been promising over the last decade, with an annual growth rate of 25.18% vs. 6.52% and global collaboration (International Co-authorships) of 19.93% vs. 19.84%. Respectively, five dominant research clusters were identified through unsupervised hierarchical clustering based on machine learning, among which Cluster 4 (Balance of neoadjuvant immunotherapy efficacy and safety) and Cluster 2 (Adjuvant immunotherapy clinical trials) (Average Publication Year [APY]: 2021.70±0.70 vs. 2017.54±4.59) are emerging research populations. Burst and regression curve analyses uncovered domain pivotal research signatures, including microsatellite instability (R2=0.7500, P=0.0025) and biomarkers (R2=0.6505, P=0.0086) in neoadjuvant scenarios, and the tumor microenvironment (R2=0.5571, P=0.0209) in adjuvant scenarios. The Walktrap algorithm further revealed that "neoadjuvant immunotherapy, non-small cell lung cancer (NSCLC), immune checkpoint inhibitors, melanoma" and "adjuvant immunotherapy, melanoma, hepatocellular carcinoma, dendritic cells" (Relevance Percentage: 100% vs. 100%, Development Percentage: 37.5% vs. 17.1%) are extremely relevant to this field but remain underdeveloped, highlighting the need for further investigation. CONCLUSION: This study identified pivotal research signatures and provided substantial predictions for neoadjuvant and adjuvant cancer immunotherapies. In addition, comprehensive quantitative comparisons revealed a notable shift in focus within this field, with neoadjuvant immunotherapy taking precedence over adjuvant immunotherapy after 2020; such a qualitative finding facilitate proper decision-making for subsequent research and mitigate the wastage of healthcare resources.

Pharmacology of PACAP and VIP receptors in the spinal cord highlights the importance of the PAC1 receptor.

BACKGROUND AND PURPOSE: The spinal cord is a key structure involved in the transmission and modulation of pain. Pituitary adenylate cyclase-activating peptide (PACAP) and vasoactive intestinal peptide (VIP), are expressed in the spinal cord. These peptides activate G protein-coupled receptors (PAC1, VPAC1 and VPAC2) that could provide targets for the development of novel pain treatments. However, it is not clear which of these receptors are expressed within the spinal cord and how these receptors signal. EXPERIMENTAL APPROACH: Dissociated rat spinal cord cultures were used to examine agonist and antagonist receptor pharmacology. Signalling profiles were determined for five signalling pathways. The expression of different PACAP and VIP receptors was then investigated in mouse, rat and human spinal cords using immunoblotting and immunofluorescence. KEY RESULTS: PACAP, but not VIP, potently stimulated cAMP, IP1 accumulation and ERK and cAMP response element-binding protein (CREB) but not Akt phosphorylation in spinal cord cultures. Signalling was antagonised by M65 and PACAP6-38. PACAP-27 was more effectively antagonised than either PACAP-38 or VIP. The patterns of PAC1 and VPAC2 receptor-like immunoreactivity appeared to be distinct in the spinal cord. CONCLUSIONS AND IMPLICATIONS: The pharmacological profile in the spinal cord suggested that a PAC1 receptor is the major functional receptor subtype present and thus likely mediates the nociceptive effects of the PACAP family of peptides in the spinal cord. However, the potential expression of both PAC1 and VPAC2 receptors in the spinal cord highlights that these receptors may play differential roles and are both possible therapeutic targets.

Enhancing the Performance of 2D Ni-Fe Layered Double Hydroxides by Cabbage-Inspired Carbon Conjunction for Oxygen Evolution Reactions.

Layered double hydroxide (LDH) nanosheets as one type of two-dimensional materials have garnered increasing attention in the field of oxygen evolution reaction (OER) in recent decades. To address the challenges associated with poor conductivity and limited electron and charge transfer capability in LDH materials, we have developed a straightforward one-pot synthesis method to successfully fabricate a composite material with a microstructure resembling cabbage, which encompasses NiFe-LDH and nanocarbon (referred as NiFe-LDH@C). Atomic force microscopy (AFM) and high-resolution transmission electron microscopy (HRTEM) revealed that the monolayer NiFe-LDH with a height of ~ 0.5-0.8 nm is uniformly distributed and closely bonded to the carbon support, leading to a significant enhancement in conductivity and facilitating faster electron and charge transfer. Moreover, the NiFe-LDH@C exhibits a substantial number of surface defect sites, which enhances the interaction with oxygen species. This dual enhancement in charge transfer and oxygen species-mediated transfer greatly improves the catalytic OER performance, which is further corroborated by theoretical calculations. Notably, the Ni10Fe6-LDH@C with the highest concentration of surface oxygen vacancies demonstrated superior water oxidation performance, surpassing commercially available RuO2 catalysts; an OER overpotential of 231 mV@10 mA cm-2 with a Tafel slope of 71 mV dec-1 was achieved.

Multimodal Dual-Embedding Networks for Malware Open-Set Recognition.

Malware open-set recognition (MOSR) is an emerging research domain that aims at jointly classifying malware samples from known families and detecting the ones from novel unknown families, respectively. Existing works mostly rely on a well-trained classifier considering the predicted probabilities of each known family with a threshold-based detection to achieve the MOSR. However, our observation reveals that the feature distributions of malware samples are extremely similar to each other even between known and unknown families. Thus, the obtained classifier may produce overly high probabilities of testing unknown samples toward known families and degrade the model performance. In this article, we propose the multi \ modal dual-embedding networks, dubbed MDENet, to take advantage of comprehensive malware features from different modalities to enhance the diversity of malware feature space, which is more representative and discriminative for down-stream recognition. Concretely, we first generate a malware image for each observed sample based on their numeric features using our proposed numeric encoder with a re-designed multiscale CNN structure, which can better explore their statistical and spatial correlations. Besides, we propose to organize tokenized malware features into a sentence for each sample considering its behaviors and dynamics, and utilize language models as the textual encoder to transform it into a representable and computable textual vector. Such parallel multimodal encoders can fuse the above two components to enhance the feature diversity. Last, to further guarantee the open-set recognition (OSR), we dually embed the fused multimodal representation into one primary space and an associated sub-space, i.e., discriminative and exclusive spaces, with contrastive sampling and ρ -bounded enclosing sphere regularizations, which resort to classification and detection, respectively. Moreover, we also enrich our previously proposed large-scaled malware dataset MAL-100 with multimodal characteristics and contribute an improved version dubbed MAL-100 + . Experimental results on the widely used malware dataset Mailing and the proposed MAL-100 + demonstrate the effectiveness of our method.

Abiotic Small Molecule Inhibitors and Activators of the LasR Quorum Sensing Receptor in Pseudomonas aeruginosa with Potencies Comparable or Surpassing N-Acyl Homoserine Lactones.

The opportunistic pathogen Pseudomonas aeruginosa controls almost 10% of its genome, including myriad virulence genes, via a cell-to-cell chemical communication system called quorum sensing (QS). Small molecules that either inhibit or activate QS in P. aeruginosa represent useful research tools to study the role of this signaling pathway in infection and interrogate its viability as an antivirulence target. However, despite active research in this area over the past 20+ years, there are relatively few synthetic compounds known to strongly inhibit or activate QS in P. aeruginosa. Most reported QS modulators in this pathogen are of low potency or have structural liabilities that limit their application in biologically relevant environments such as mimics of the native N-acyl l-homoserine lactone (AHL) signals. Here, we report the results of a high-throughput screen for abiotic small molecules that target LasR, a key QS regulator in P. aeruginosa. We screened a 25,000-compound library and discovered four new structural classes of abiotic LasR modulators. These compounds include antagonists that surpass the potency of all known AHL-type compounds and mimetics thereof, along with an agonist with potency approaching that of LasR's native ligand. The novel structures of this compound set, along with their anticipated robust physicochemical profiles, underscore their potential value as probe molecules to interrogate the roles of QS in this formidable pathogen.

Review on Layered Manganese-Based Metal Oxides Cathode Materials for Potassium-Ion Batteries: From Preparation to Modification.

Potassium-ion battery is rich in resources and cheap in price, in the era of lithium-ion battery commercialization, potassium-ion battery is the most likely to replace it. Based on the classification and summary of electrode materials for potassium-ion batteries, this paper focuses on the introduction of manganese-based oxide KxMnO2. The layered KxMnO2 has a large layer spacing and can be embedded with large size potassium-ions. This paper focuses on the preparation and doping of manganese-based cathode materials for potassium-ion batteries, summarizes the main challenges of KxMnO2-based cathode materials in the current stage of research and further looks into its future development direction.

Three new red neutral and ionic iridium(III) complexes based on the same main ligand and auxiliary ligand but with different counterions for solution-processed organic light-emitting diodes.

Three new neutral and ionic phosphorescent iridium(III) complexes were successfully prepared using 1-(6-methoxynaphthalen-2-yl)isoquinoline as the main ligand, while the auxiliary ligand was 2-(2-1H-imidazolyl)pyridine. Three complexes (Ir1, Ir2, Ir3) showed red emission, peaking at 610, 609, and 615 nm, respectively, and they exhibited good solubility and excellent photophysical properties in different solvents, which is suitable to prepare organic light-emitting diodes (OLEDs) by solution method. Among the three OLEDs prepared by iridium(III) complexes using the solution method, the device based on Ir2 possessed better electroluminescent properties, and its maximum brightness, current efficiency (CE), power efficiency (PE), and the maximum external quantum efficiency (EQE) were 507.2 cd m-2 , 0.14 cd A-1 , 0.06 lm W-1 , and 0.14%. respectively, proving that the three complexes have a certain of potential for OLEDs applications and are expected to expand the applications of iridium(III) complexes for OLEDs.

Reinstatement of the fission yeast species Schizosaccharomyces versatilis Wickerham et Duprat, a sibling species of Schizosaccharomyces japonicus.

Schizosaccharomyces japonicus Yukawa et Maki (1931) and Schizosaccharomyces versatilis Wickerham et Duprat (1945) have been treated as varieties of S. japonicus or as conspecific, based on various approaches including mating trials and nDNA/nDNA optical reassociation studies. However, the type strains of S. japonicus and S. versatilis differ by five substitutions (99.15% identity) and one 1-bp indel in the sequences of the D1/D2 domain of the 26S rRNA gene, and 23 substitutions (96.3% identity) and 31-bp indels in the sequences of internal transcribed spacer (ITS) of rRNA, suggesting that they may not be conspecific. To reassess their taxonomic status, we conducted mating trials and whole-genome analyses. Mating trials using the type strains showed a strong but incomplete prezygotic sterility barrier, yielding interspecies mating products at two orders of magnitude lower efficiency than intraspecies matings. These mating products, which were exclusively allodiploid hybrids, were unable to undergo the haplontic life cycle of the parents. We generated chromosome-level gap-less genome assemblies for both type strains. Whole genome sequences yielded an average nucleotide identity (ANI) of 86.4%, indicating clear separation of S. japonicus and S. versatilis. Based on these findings, we propose the reinstatement of S. versatilis as a distinct species (holotype strain: CBS 103T and ex-types: NRRL Y-1026, NBRC 1607, ATCC 9987, PYCC 7100; Mycobank no.: 847838).

Anion Photoelectron Spectroscopy and Quantum Chemistry Calculations of Gas-Phase TaSi17Ì and TaSi18Ì Clusters: Structural Determination, Bonding Characteristics, and Multiplicity of Structural Forms.

This study explores the structures and chemical bonding properties of TaSi17̅ and TaSi18̅ clusters by employing anion photoelectron spectroscopy and theoretical computations. Utilizing CALYPSO and ABCluster programs for initial structure prediction, B3LYP hybrid functional for optimization, and CCSD(T)/def2-TZVPPD level for energy calculations, the research identifies the most stable isomers of these clusters. Key findings include the identification of two coexisting low-energy isomers for TaSi17̅, exhibiting Ta-endohedral fullerene-like cage structures, and the lowest-energy structures of TaSi17̅ and TaSi18̅ anions can be considered as derived from the TaSi16̅ superatom cluster. The study enhances the understanding of group 14 element chemistry and guides the design of novel inorganic metallic compounds, potentially impacting materials science.

Secondary Organic Aerosol Formation Potential from Vehicular Non-tailpipe Emissions under Real-World Driving Conditions.

Traffic emissions are a dominant source of secondary organic aerosol (SOA) in urban environments. Though tailpipe exhaust has drawn extensive attention, the impact of non-tailpipe emissions on atmospheric SOA has not been well studied. Here, a closure study was performed combining urban tunnel experiments and dynamometer tests using an oxidation flow reactor in situ photo-oxidation. Results show a significant gap between field and laboratory research; the average SOA formation potential from real-world fleet is 639 ± 156 mg kg fuel-1, higher than the reconstructed result (188 mg kg fuel-1) based on dynamometer tests coupled with fleet composition inside the tunnel. Considering the minimal variation of SOA/CO in emission standards, we also reconstruct CO and find the critical role of high-emitting events in the real-world SOA burden. Different profiles of organic gases are detected inside the tunnel than tailpipe exhaust, such as more abundant C6-C9 aromatics, C11-C16 species, and benzothiazoles, denoting contributions from non-tailpipe emissions to SOA formation. Using these surrogate chemical compounds, we roughly estimate that high-emitting, evaporative emission, and asphalt-related and tire sublimation share 14, 20, and 10% of the SOA budget, respectively, partially explaining the gap between field and laboratory research. These experimental results highlight the importance of non-tailpipe emissions to atmospheric SOA.

The role of CEMIP in cancers and its transcriptional and post-transcriptional regulation.

CEMIP is a protein known for inducing cell migration and binding to hyaluronic acid. Functioning as a hyaluronidase, CEMIP primarily facilitates the breakdown of the extracellular matrix component, hyaluronic acid, thereby regulating various signaling pathways. Recent evidence has highlighted the significant role of CEMIP in different cancers, associating it with diverse pathological states. While identified as a biomarker for several diseases, CEMIP's mechanism in cancer seems distinct. Accumulating data suggests that CEMIP expression is triggered by chemical modifications to itself and other influencing factors. Transcriptionally, chemical alterations to the CEMIP promoter and involvement of transcription factors such as AP-1, HIF, and NF-κB regulate CEMIP levels. Similarly, specific miRNAs have been found to post-transcriptionally regulate CEMIP. This review provides a comprehensive summary of CEMIP's role in various cancers and explores how both transcriptional and post-transcriptional mechanisms control its expression.

Diverse modes of chromosome terminal deletion in spontaneous canavanine-resistant Schizosaccharomyces pombe mutants.

Canavanine resistance has been used to analyze mutation rates in the fission yeast Schizosaccharomyces pombe . However, the genetic basis of canavanine resistance in this organism remains incompletely understood. Here, we performed whole genome sequencing on five spontaneously arising canavanine-resistant S. pombe mutants, including the can2-1 mutant isolated in the 1970s. This analysis revealed that three mutants, including can2-1 , experienced terminal deletions of the left arm of chromosome II, leading to the loss of multiple amino acid transporter genes. Interestingly, these three mutants underwent chromosome terminal deletion through distinct mechanisms, including homology-driven translocation, homology-independent chromosome fusion, and de novo telomere addition. Our findings shed new light on the genetic basis of canavanine resistance and mechanisms underlying chromosome terminal deletions in fission yeast.

An assessment system for clinical and biological interpretability in ulcerative colitis.

Ulcerative colitis (UC) is a serious inflammatory bowel disease (IBD) with high morbidity and mortality worldwide. As the traditional diagnostic techniques have various limitations in the practice and diagnosis of early ulcerative colitis, it is necessary to develop new diagnostic models from molecular biology to supplement the existing methods. In this study, we developed a machine learning-based synthesis to construct an artificial intelligence diagnostic model for ulcerative colitis, and the correctness of the model is verified using an external independent dataset. According to the significantly expressed genes related to the occurrence of UC in the model, an unsupervised quantitative ulcerative colitis related score (UCRScore) based on principal coordinate analysis was established. The UCRScore is not only highly generalizable across UC bulk cohorts at different stages, but also highly generalizable across single-cell datasets, with the same effect in terms of cell numbers, activation pathways and mechanisms. As an important role of screening genes in disease occurrence, based on connectivity map analysis, 5 potential targeting molecular compounds were identified, which can be used as an additional supplement to the therapeutic of UC. Overall, this study provides a potential tool for differential diagnosis and assessment of bio-pathological changes in UC at the macroscopic level, providing an opportunity to optimize the diagnosis and treatment of UC.