Genome stability from the perspective of telomere length.

Telomeres and their associated proteins protect the ends of chromosomes to maintain genome stability. Telomeres undergo progressive shortening with each cell division in mammalian somatic cells without telomerase, resulting in genome instability. When telomeres reach a critically short length or are recognized as a damage signal, cells enter a state of senescence, followed by cell cycle arrest, programmed cell death, or immortalization. This review provides an overview of recent advances in the intricate relationship between telomeres and genome instability. Alongside well-established mechanisms such as chromosomal fusion and telomere fusion, we will delve into the perspective on genome stability by examining the role of retrotransposons. Retrotransposons represent an emerging pathway to regulate genome stability through their interactions with telomeres.

Dot1l cooperates with Npm1 to repress endogenous retrovirus MERVL in embryonic stem cells.

Dot1l is a histone methyltransferase without a SET domain and is responsible for H3K79 methylation, which marks active transcription. In contradiction, Dot1l also participates in silencing gene expression. The target regions and mechanism of Dot1l in repressing transcription remain enigmatic. Here, we show that Dot1l represses endogenous retroviruses in embryonic stem cells (ESCs). Specifically, the absence of Dot1l led to the activation of MERVL, which is a marker of 2-cell-like cells. In addition, Dot1l deletion activated the 2-cell-like state and predisposed ESCs to differentiate into trophectoderm lineage. Transcriptome analysis revealed activation of 2-cell genes and meiotic genes by Dot1l deletion. Mechanistically, Dot1l interacted with and co-localized with Npm1 on MERVL, and depletion of Npm1 similarly augmented MERVL expression. The catalytic activity and AT-hook domain of Dot1l are important to suppress MERVL. Notably, Dot1l-Npm1 restricts MERVL by regulating protein level and deposition of histone H1. Furthermore, Dot1l is critical for Npm1 to efficiently interact with histone H1 and inhibit ubiquitination of H1 whereas Npm1 is essential for Dot1l to interact with MERVL. Altogether, we discover that Dot1l represses MERVL through chaperoning H1 by collaborating with Npm1. Importantly, our findings shed light on the non-canonical transcriptional repressive role of Dot1l in ESCs.

Distinctive Lipid Characteristics of Colorectal Cancer Revealed through Non-targeted Lipidomics Analysis of Tongue Coating.

The metabolites and microbiota in tongue coating display distinct characteristics in certain digestive disorders, yet their relationship with colorectal cancer (CRC) remains unexplored. Here, we employed liquid chromatography coupled with tandem mass spectrometry to analyze the lipid composition of tongue coating using a nontargeted approach in 30 individuals with colorectal adenomas (CRA), 32 with CRC, and 30 healthy controls (HC). We identified 21 tongue coating lipids that effectively distinguished CRC from HC (AUC = 0.89), and 9 lipids that differentiated CRC from CRA (AUC = 0.9). Furthermore, we observed significant alterations in the tongue coating lipid composition in the CRC group compared to HC/CRA groups. As the adenoma-cancer sequence progressed, there was an increase in long-chain unsaturated triglycerides (TG) levels and a decrease in phosphatidylethanolamine plasmalogen (PE-P) levels. Furthermore, we noted a positive correlation between N-acyl ornithine (NAOrn), sphingomyelin (SM), and ceramide phosphoethanolamine (PE-Cer), potentially produced by members of the Bacteroidetes phylum. The levels of inflammatory lipid metabolite 12-HETE showed a decreasing trend with colorectal tumor progression, indicating the potential involvement of tongue coating microbiota and tumor immune regulation in early CRC development. Our findings highlight the potential utility of tongue coating lipid analysis as a noninvasive tool for CRC diagnosis.

A monomeric structure of human TMEM63A protein.

OSCA/TMEM63 is a newly identified family of mechanically activated (MA) ion channels in plants and animals, respectively, which convert physical forces into electrical signals or trigger intracellular cascades and are essential for eukaryotic physiology. OSCAs and related TMEM16s and transmembrane channel-like (TMC) proteins form homodimers with two pores. However, the molecular architecture of the mammalian TMEM63 proteins remains unclear. Here we elucidate the structure of human TMEM63A in the presence of calcium by single particle cryo-EM, revealing a distinct monomeric architecture containing eleven transmembrane helices. It has structural similarity to the single subunit of the Arabidopsis thaliana OSCA proteins. We locate the ion permeation pathway within the monomeric configuration and observe a nonprotein density resembling lipid. These results lay a foundation for understanding the structural organization of OSCA/TMEM63A family proteins.

Intelligent Cell Profiling and Precision Release: Multimolecular Marker-Activated Transmembrane DNA Computing Nanosystem.

Accurate classification of tumor cells is of importance for cancer diagnosis and further therapy. In this study, we develop multimolecular marker-activated transmembrane DNA computing systems (MTD). Employing the cell membrane as a native gate, the MTD system enables direct signal output following simple spatial events of "transmembrane" and "in-cell target encounter", bypassing the need of multistep signal conversion. The MTD system comprises two intelligent nanorobots capable of independently sensing three molecular markers (MUC1, EpCAM, and miR-21), resulting in comprehensive analysis. Our AND-AND logic-gated system (MTDAND-AND) demonstrates exceptional specificity, allowing targeted release of drug-DNA specifically in MCF-7 cells. Furthermore, the transformed OR-AND logic-gated system (MTDOR-AND) exhibits broader adaptability, facilitating the release of drug-DNA in three positive cancer cell lines (MCF-7, HeLa, and HepG2). Importantly, MTDAND-AND and MTDOR-AND, while possessing distinct personalized therapeutic potential, share the ability of outputting three imaging signals without any intermediate conversion steps. This feature ensures precise classification cross diverse cells (MCF-7, HeLa, HepG2, and MCF-10A), even in mixed populations. This study provides a straightforward yet effective solution to augment the versatility and precision of DNA computing systems, advancing their potential applications in biomedical diagnostic and therapeutic research.

Thiol-Ene Click Reaction in Constructing Liquid Separation Membranes for Water Treatment.

In the evolving landscape of water treatment, membrane technology has ascended to an instrumental role, underscored by its unmatched efficacy and ubiquity. Diverse synthesis and modification techniques are employed to fabricate state-of-the-art liquid separation membranes. Click reactions, distinguished by their rapid kinetics, minimal byproduct generation, and simple reaction condition, emerge as a potent paradigm for devising eco-functional materials. While the metal-free thiol-ene click reaction is acknowledged as a viable approach for membrane material innovation, a systematic elucidation of its applicability in liquid separation membrane development remains conspicuously absent. This review elucidates the pre-functionalization strategies of substrate materials tailored for thiol-ene reactions, notably highlighting thiolation and introducing unsaturated moieties. The consequential implications of thiol-ene reactions on membrane properties-including trade-off effect, surface wettability, and antifouling property-are discussed. The application of thiol-ene reaction in fabricating various liquid separation membranes for different water treatment processes, including wastewater treatment, oil/water separation, and ion separation, are reviewed. Finally, the prospects of thiol-ene reaction in designing novel liquid separation membrane, including pre-functionalization, products prediction, and solute-solute separation membrane, are proposed. This review endeavors to furnish invaluable insights, paving the way for expanding the horizons of thiol-ene reaction application in liquid separation membrane fabrication.

Spatial asynchrony and cross-scale climate interactions in populations of a coldwater stream fish.

Climate change affects populations over broad geographic ranges due to spatially autocorrelated abiotic conditions known as the Moran effect. However, populations do not always respond to broad-scale environmental changes synchronously across a landscape. We combined multiple datasets for a retrospective analysis of time-series count data (5-28 annual samples per segment) at 144 stream segments dispersed over nearly 1,000 linear kilometers of range to characterize the population structure and scale of spatial synchrony across the southern native range of a coldwater stream fish (brook trout, Salvelinus fontinalis), which is sensitive to stream temperature and flow variations. Spatial synchrony differed by life stage and geographic region: it was stronger in the juvenile life stage than in the adult life stage and in the northern sub-region than in the southern sub-region. Spatial synchrony of trout populations extended to 100-200 km but was much weaker than that of climate variables such as temperature, precipitation, and stream flow. Early life stage abundance changed over time due to annual variation in summer temperature and winter and spring stream flow conditions. Climate effects on abundance differed between sub-regions and among local populations within sub-regions, indicating multiple cross-scale interactions where climate interacted with local habitat to generate only a modest pattern of population synchrony over space. Overall, our analysis showed higher degrees of response heterogeneity of local populations to climate variation and consequently population asynchrony than previously shown based on analysis of individual, geographically restricted datasets. This response heterogeneity indicates that certain local segments characterized by population asynchrony and resistance to climate variation could represent unique populations of this iconic native coldwater fish that warrant targeted conservation. Advancing the conservation of this species can include actions that identify such priority populations and incorporate them into landscape-level conservation planning. Our approach is applicable to other widespread aquatic species sensitive to climate change.

Directed evolution of Baeyer-Villiger monooxygenase for highly secretory expressed in Pichia pastoris and efficient preparation of chiral pyrazole sulfoxide.

The methylotrophic yeast Pichia pastoris (Komagataella phaffii) is a highly distinguished expression platform for the excellent synthesis of various heterologous proteins in recent years. With the advantages of high-density fermentation, P. pastoris can produce gram amounts of recombinant proteins. While not every protein of interest can be expressed to such high titers, such as Baeyer-Villiger monooxygenase (BVMO) (AcPSMO) which is responsible for pyrazole sulfide asymmetric oxidation. In this work, an excellent yeast expression system was established to facilitate efficient AcPSMO expression, which exhibited 9.5-fold enhanced secretion. Subsequently, an ultrahigh throughput screening method based on fluorescence-activated cell sorting by fusing super folder green fluorescent protein (sfGFP) in the C-terminal of AcPSMO was developed, and directed evolution was performed. The protein expression level of the superior mutant AcPSMOP1 (S58T/T252P/E336N/H456D) reached 84.6 mg/L at 100 mL shaking flask, which was 4.7 times higher than the levels obtained with the wild-type. Finally, the optimized chassis cells were used for high-density fermentation on a 5-L scale, and AcPSMOP1 protein yield of 3.4 g/L was achieved, representing approximately 85% of the total protein secreted. By directly employing the pH-adjusted supernatant as a biocatalyst, 20 g/L pyrmetazole sulfide was completely transformed into the corresponding (S)-sulfoxide, with a 78.8% isolated yield. This work confers dramatic benefits for efficient secretion of other BVMOs in P. pastoris.

A Coupled Statistical and Deterministic Model for Forecasting Climate-Driven Dengue Incidence in Selangor, Malaysia.

The mosquito-borne dengue virus remains a major public health concern in Malaysia. Despite various control efforts and measures introduced by the Malaysian Government to combat dengue, the increasing trend of dengue cases persists and shows no sign of decreasing. Currently, early detection and vector control are the main methods employed to curb dengue outbreaks. In this study, a coupled model consisting of the statistical ARIMAX model and the deterministic SI-SIR model was developed and validated using the weekly reported dengue data from year 2014 to 2019 for Selangor, Malaysia. Previous studies have shown that climate variables, especially temperature, humidity, and precipitation, were able to influence dengue incidence and transmission dynamics through their effect on the vector. In this coupled model, climate is linked to dengue disease through mosquito biting rate, allowing real-time forecast of dengue cases using climate variables, namely temperature, rainfall and humidity. For the period chosen for model validation, the coupled model can forecast 1-2 weeks in advance with an average error of less than 6%, three weeks in advance with an average error of 7.06% and four weeks in advance with an average error of 8.01%. Further model simulation analysis suggests that the coupled model generally provides better forecast than the stand-alone ARIMAX model, especially at the onset of the outbreak. Moreover, the coupled model is more robust in the sense that it can be further adapted for investigating the effectiveness of various dengue mitigation measures subject to the changing climate.

The rat acute oral toxicity of trifluoromethyl compounds (TFMs): a computational toxicology study combining the 2D-QSTR, read-across and consensus modeling methods.

All areas of the modern society are affected by fluorine chemistry. In particular, fluorine plays an important role in medical, pharmaceutical and agrochemical sciences. Amongst various fluoro-organic compounds, trifluoromethyl (CF3) group is valuable in applications such as pharmaceuticals, agrochemicals and industrial chemicals. In the present study, following the strict OECD modelling principles, a quantitative structure-toxicity relationship (QSTR) modelling for the rat acute oral toxicity of trifluoromethyl compounds (TFMs) was established by genetic algorithm-multiple linear regression (GA-MLR) approach. All developed models were evaluated by various state-of-the-art validation metrics and the OECD principles. The best QSTR model included nine easily interpretable 2D molecular descriptors with clear physical and chemical significance. The mechanistic interpretation showed that the atom-type electro-topological state indices, molecular connectivity, ionization potential, lipophilicity and some autocorrelation coefficients are the main factors contributing to the acute oral toxicity of TFMs against rats. To validate that the selected 2D descriptors can effectively characterize the toxicity, we performed the chemical read-across analysis. We also compared the best QSTR model with public OPERA tool to demonstrate the reliability of the predictions. To further improve the prediction range of the QSTR model, we performed the consensus modelling. Finally, the optimum QSTR model was utilized to predict a true external set containing many untested/unknown TFMs for the first time. Overall, the developed model contributes to a more comprehensive safety assessment approach for novel CF3-containing pharmaceuticals or chemicals, reducing unnecessary chemical synthesis whilst saving the development cost of new drugs.

Semantic relatedness can impair memory for item locations.

While memory for semantically related items is improved over unrelated items in many cases, relatedness can also lead to memory costs. Here we examined how the semantic relatedness of words within a display influenced memory for their locations. Participants learned the locations of words inside grid displays; the words in a given display were either from a single category or were from different assorted categories. When a display containing words from a single category was compared to a scrambled display containing words from multiple categories, location memory performance was rendered worse, while word recall performance was significantly improved. Our results suggest that semantically structured spaces can both help and harm memory within the context of a location memory task. We hypothesize that relatedness can improve memory performance by increasing the likelihood that matching candidates will be retrieved, yet might worsen performance that requires distinguishing between similar target representations.

Semantic partitioning facilitates memory for object location through category-partition cueing.

In our lived environments, objects are often semantically organised (e.g., cookware and cutlery are placed close together in the kitchen). Across four experiments, we examined how semantic partitions (that group same-category objects in space) influenced memory for object locations. Participants learned the locations of items in a semantically partitioned display (where each partition contained objects from a single category) as well as a purely visually partitioned display (where each partition contained a scrambled assortment of objects from different categories). Semantic partitions significantly improved location memory accuracy compared to the scrambled display. However, when the correct partition was cued (highlighted) to participants during recall, performance on the semantically partitioned display was similar to the scrambled display. These results suggest that semantic partitions largely benefit memory for location by enhancing the ability to use the given category as a cue for a visually partitioned area (e.g., toys - top left). Our results demonstrate that semantically structured spaces help location memory across partitions, but not items within a partition, providing new insights into the interaction between meaning and memory.

Semantic partitioning facilitates memory for object location through category-partition cueing.

In our lived environments, objects are often semantically organised (e.g., cookware and cutlery are placed close together in the kitchen). Across four experiments, we examined how semantic partitions (that group same-category objects in space) influenced memory for object locations. Participants learned the locations of items in a semantically partitioned display (where each partition contained objects from a single category) as well as a purely visually partitioned display (where each partition contained a scrambled assortment of objects from different categories). Semantic partitions significantly improved location memory accuracy compared to the scrambled display. However, when the correct partition was cued (highlighted) to participants during recall, performance on the semantically partitioned display was similar to the scrambled display. These results suggest that semantic partitions largely benefit memory for location by enhancing the ability to use the given category as a cue for a visually partitioned area (e.g., toys - top left). Our results demonstrate that semantically structured spaces help location memory across partitions, but not items within a partition, providing new insights into the interaction between meaning and memory.

Exploring the neural mechanisms underlying achalasia: A study of functional connectivity and regional brain activity.

BACKGROUND AND AIMS: The pathophysiology of achalasia, which involves central nuclei abnormalities, remains unknown. We investigated the resting-state functional MRI (rs-fMRI) features of patients with achalasia. METHODS: We applied resting-state functional MRI (rs-fMRI) to investigate the brain features in patients with achalasia (n = 27), compared to healthy controls (n = 29). Focusing on three regions of interest (ROIs): the dorsal motor nucleus of the vagus (DMV), the nucleus ambiguus (NA), and the nucleus of the solitary tract (NTS), we analyzed variations in resting-state functional connectivity (rs-FC), fractional amplitude of low-frequency fluctuations (fALFF), and regional homogeneity (ReHo). RESULTS: Achalasia patients demonstrated stronger functional connectivity between the NA and the right precentral gyrus, left postcentral gyrus, and left insula. No significant changes were found in the DMV or NTS. The fMRI analysis showed higher rs-FC values for NA-DMV and NA-NTS connections in achalasia patients. Achalasia patients exhibited decreased fALFF values in the NA, DMV, and NTS regions, as well as increased ReHo values in the NA and DMV regions. A positive correlation was observed between fALFF values in all six ROIs and the width of the barium meal. The NTS fALFF value and NA ReHo value displayed a positive correlation with integrated relaxation pressure (IRP), while the ReHo value in the right precentral gyrus showed an inverse correlation with the height of the barium meal. CONCLUSIONS: Abnormal rs-FC and regional brain activity was found in patients with achalasia. Our study provides new insights into the pathophysiology of achalasia and highlights the potential of rs-fMRI in improving the diagnosis and treatment of this condition.

Identification of exosome protein panels as predictive biomarkers for non-small cell lung cancer.

BACKGROUND: Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related deaths worldwide, primarily due to its propensity for metastasis. Patients diagnosed with localized primary cancer have higher survival rates than those with metastasis. Thus, it is imperative to discover biomarkers for the early detection of NSCLC and the timely prediction of tumor metastasis to improve patient outcomes. METHODS: Here, we utilized an integrated approach to isolate and characterize plasma exosomes from NSCLC patients as well as healthy individuals. We then conducted proteomics analysis and parallel reaction monitoring to identify and validate the top-ranked proteins of plasma exosomes. RESULTS: Our study revealed that the proteome in exosomes from NSCLC patients with metastasis was distinctly different from that from healthy individuals. The former had larger diameters and lower concentrations of exosomes than the latter. Furthermore, among the 1220 identified exosomal proteins, we identified two distinct panels of biomarkers. The first panel of biomarkers (FGB, FGG, and VWF) showed potential for early NSCLC diagnosis and demonstrated a direct correlation with the survival duration of NSCLC patients. The second panel of biomarkers (CFHR5, C9, and MBL2) emerged as potential biomarkers for assessing NSCLC metastasis, of which CFHR5 alone was significantly associated with the overall survival of NSCLC patients. CONCLUSIONS: These findings underscore the potential of plasma exosomal biomarkers for early NSCLC diagnosis and metastasis prediction. Notably, CFHR5 stands out as a promising prognostic indicator for NSCLC patients. The clinical utility of exosomal biomarkers offers the potential to enhance the management of NSCLC.

InGaN micro-LED array with integrated emission and detection functions for color detection application.

InGaN-based micro-LEDs can detect and emit optical signals simultaneously, owing to their overlapping emission and absorption spectra, enabling color detection. In this paper, we fabricated a green InGaN-based micro-LED array with integrated emission and detection functions. On the back side of the integrated device, when the 80 µm micro-LED emitted light, the 200 µm LED could receive reflected light to accomplish color detection. The spacing between the 80 µm and the 200 µm micro-LEDs was optimized to be 1 mm to reduce the effect of the direct light transmitted through the n-GaN layer without reflection. The integrated device shows good detection performance for different colors and skin colors, even in a dark environment. In addition, light can be emitted from the top side of the device. Utilization of light from both sides of the integrated device provides the possibility of its application in display, communication, and detection on the different sides.

Long Noncoding RNA Lx8-SINE B2 Interacts with Eno1 to Regulate Self-Renewal and Metabolism of Embryonic Stem Cells.

Long noncoding RNAs (lncRNAs) emerge as important orchestrators of biological processes in embryonic stem cells (ESCs). LncRNA Lx8-SINE B2 was recently identified as an ESC-specific lncRNA that marks pluripotency. Here, we studied the function of lncRNA Lx8-SINE B2 in ESCs. Depletion of Lx8-SINE B2 disrupted ESC proliferation, repressed the expression of pluripotency genes, activated differentiation genes, and inhibited reprogramming to induced pluripotent stem cells. The reduction of the colony formation ability of ESCs upon Lx8-SINE B2 knockdown was accompanied by the elongation of the G1 phase and the shortening of the S phase. Transcriptome analysis revealed that Lx8-SINE B2 deficiency affected multiple metabolic pathways, particularly glycolysis. Mechanistically, Lx8-SINE B2 functions as a cytoplasmic lncRNA and interacts with the glycolytic enzyme Eno1 as shown by RNA pull-down and RNA localization analysis. Lx8-SINE B2 and Eno1 interact with and regulate each other's expression, hence promoting the expression of metabolic genes and influencing glycolysis. In conclusion, we have identified lncRNA Lx8-SINE B2 as a novel regulator of ESC proliferation, cell cycle, and metabolism through working with Eno1.

Lack of surgical resection is associated with increased early mortality in hematological patients complicated with rhino-orbital-cerebral mucormycosis.

Rhino-orbital-cerebral mucormycosis (ROCM), which is an acute fatal infectious disease with a high mortality rate, is increasingly being diagnosed in patients with hematological diseases worldwide. We aimed to investigate the clinical characteristics, treatment, and prognosis of hematological diseases complicated by ROCM. Our sample comprised a total of 60 ROCM patients with hematological diseases. The most common primary disease was acute lymphoblastic leukemia (ALL) (n=27, 45.0%), while 36 patients (60.0%) were diagnosed with a clear type of pathogen, all belonging to the Mucorales, most commonly Rhizopus (41.7%). Of the 32 patients (53.3%) who died, 19 (59.3%) died of mucormycosis, and 84.2% (n=16) of those died within 1 month. Forty-eight cases (80.0%) received antifungal treatment combined with surgical therapy, 12 of whom (25.0%) died of mucormycosis, amounting to a mortality rate that was significantly lower than in patients who received antifungal therapy alone (n=7, 58.3%) (P=0.012). The median neutrophil value of patients who underwent surgery was 0.58 (0.11-2.80) 103/µL, the median platelet value was 58.00 (17.00-93.00) 103/µL, and no surgery-related deaths were reported. Multivariate analysis showed that patient's advanced age (P=0.012, OR=1.035 (1.008-1.064)) and lack of surgical treatment (P=0.030, OR=4.971 (1.173-21.074)) were independent prognostic factors.In this study, hematological diseases associated with ROCM have a high mortality rate. Lack of surgical treatment is an independent prognostic factor for death from mucormycosis. Surgery may therefore be considered in patients with hematological disease even if their neutrophil and platelet values are lower than normal.

HP1c regulates development and gut homeostasis by suppressing Notch signaling through Su(H).

Notch signaling and epigenetic factors are known to play critical roles in regulating tissue homeostasis in most multicellular organisms, but how Notch signaling coordinates with epigenetic modulators to control differentiation remains poorly understood. Here, we identify heterochromatin protein 1c (HP1c) as an essential epigenetic regulator of gut homeostasis in Drosophila. Specifically, we observe that HP1c loss-of-function phenotypes resemble those observed after Notch signaling perturbation and that HP1c interacts genetically with components of the Notch pathway. HP1c represses the transcription of Notch target genes by directly interacting with Suppressor of Hairless (Su(H)), the key transcription factor of Notch signaling. Moreover, phenotypes caused by depletion of HP1c in Drosophila can be rescued by expressing human HP1γ, suggesting that HP1γ functions similar to HP1c in Drosophila. Taken together, our findings reveal an essential role of HP1c in normal development and gut homeostasis by suppressing Notch signaling.

Latent trajectory models for spatio-temporal dynamics in Alaskan ecosystems.

The Alaskan landscape has undergone substantial changes in recent decades, most notably the expansion of shrubs and trees across the Arctic. We developed a Bayesian hierarchical model to quantify the impact of climate change on the structural transformation of ecosystems using remotely sensed imagery. We used latent trajectory processes to model dynamic state probabilities that evolve annually, from which we derived transition probabilities between ecotypes. Our latent trajectory model accommodates temporal irregularity in survey intervals and uses spatio-temporally heterogeneous climate drivers to infer rates of land cover transitions. We characterized multi-scale spatial correlation induced by plot and subplot arrangements in our study system. We also developed a Pólya-Gamma sampling strategy to improve computation. Our model facilitates inference on the response of ecosystems to shifts in the climate and can be used to predict future land cover transitions under various climate scenarios.