Cycle Control Research Articles

Increased c-MYC Expression Associated with Active IGH Locus Rearrangement: An Emerging Role for c-MYC in Chronic Lymphocytic Leukemia

This review examines the pivotal role of c-MYC in Chronic Lymphocytic Leukemia (CLL), focusing on how its overexpression leads to increased genetic instability, thereby accelerating disease progression. MYC, a major oncogene, encodes a transcription factor that regulates essential cellular processes, including cell cycle control, proliferation, and apoptosis. In CLL cases enriched with unmutated immunoglobulin heavy chain variable (IGHV) genes, MYC is significantly overexpressed and associated with active rearrangements in the IGH immunoglobulin heavy chain locus. This overexpression results in substantial DNA damage, including double-strand breaks, chromosomal translocations, and an increase in abnormal repair events. Consequently, c-MYC plays a dual role in CLL: it promotes aggressive cell proliferation while concurrently driving genomic instability through its involvement in genetic recombination. This dynamic contributes not only to CLL progression but also to the overall aggressiveness of the disease. Additionally, the review suggests that c-MYC’s influence on genetic rearrangements makes it an attractive target for therapeutic strategies aimed at mitigating CLL malignancy. These findings underscore c-MYC’s critical importance in advancing CLL progression, highlighting the need for further research to explore its potential as a target in future treatment approaches.

BPDCN MYB fusions regulate cell cycle genes, impair differentiation and induce myeloid-dendritic cell leukemia.

MYB fusions are recurrently found in select cancers, including blastic plasmacytoid dendritic cell neoplasm (BPDCN), an acute leukemia with poor prognosis. They are markedly enriched in BPDCN compared to other blood cancers, and in some patients are the only obvious somatic mutation detected. This suggests they may alone be sufficient to drive dendritic cell transformation. MYB fusions are hypothesized to alter the normal transcription factor activity of MYB, but mechanistically how they promote leukemogenesis is poorly understood. Using CUT&RUN chromatin profiling, we found that in BPDCN leukemogenesis, MYB switches from being a regulator of dendritic cell lineage genes to aberrantly regulating G2/M cell cycle control genes. MYB fusions found in BPDCN patients increased the magnitude of DNA binding at these locations, and this was linked to BPDCN-associated gene expression changes. Furthermore, expression of MYB fusions in vivo impaired dendritic cell differentiation and induced transformation to generate a mouse model of myeloid-dendritic acute leukemia. Therapeutically, we present evidence that all-trans retinoic acid (ATRA) may cause loss of MYB protein and cell death in BPDCN.

Altered Endometrial Microbiota Profile Is Associated With Poor Endometrial Receptivity of Repeated Implantation Failure.

To gain insight into the endometrial pathophysiology of unexplained repeated implantation failure (RIF), we examined the characteristics of genital tract microbiota and explored the correlation between the microbiota and endometrial receptivity. Vaginal secretion (VS) and endometrial biopsy (EB) samples were collected from patients with RIF (RIF group, n=32) and those with infertility who had achieved pregnancy during their initial embryo transfer cycle (control group, n=18). 16S ribosomal RNA sequencing and quantitative PCR were performed to characterize the microbiota of the two groups. Spearman's correlation analysis was performed to determine the relationship between endometrial receptivity markers and endometrial microbiota. Endometrial microbiota exhibited distinct characteristics from vaginal microbiota, with a higher alpha-diversity. Alpha-diversity of the endometrial microbiota was higher in the RIF group than in the control group. Compared with the control group, the RIF group had a significant decrease in endometrial Lactobacillus abundance and an increase in Gardnerella and Acinetobacter abundances. The expression levels of endometrial receptivity markers, including homeobox A11, integrin αvβ3, leukemia inhibitor factor, matrix metalloproteinase-9, and vascular endothelial growth factor, were lower in the RIF group than in the control group. Moreover, the expression levels of these markers were correlated with endometrial Lactobacillus, Gardnerella, and Acinetobacter abundances. RIF is characterized by endometrial microbiota dysbiosis and poor endometrial receptivity. Moreover, abnormal endometrial microbiota is associated with impaired endometrial receptivity, which may be a potential cause of unexplained RIF.

Evaluation of BUBR1, MCM2, and GMNN as oral cancer biomarkers.

Oral cancer is a public health problem worldwide. Late diagnosis results in a low survival rate. However, this tumor can arise from oral precancerous lesions and identification of biomarkers in precursor lesions has the potential for early diagnosis, improving patient survival. In this context, proteins involved in the cell cycle control are potentially promising. This study aimed to evaluate the importance of immunohistochemical expression of BUBR1, MCM2, and GMNN as biomarkers of oral carcinogenesis considering different oral sites. Sixty-six samples of oral epithelial dysplasia (from 33 males and 33 females) and 63 samples of oral squamous cell carcinoma (from 44 males and 19 females) were subjected to immunohistochemistry to detect some human proteins. Ki67 expression was included as a marker of cell proliferation. Marker expression was quantified by manually counting at least 1000 cells, and the labeling index was used in all statistical analyses. GMNN, MCM2, BUBR1 (nuclear and cytoplasmic labeling), and Ki67 expression levels were higher in carcinomas than in dysplasia (P < 0.05). Cytoplasmic BUBR1 was a good marker of malignancy (AUC = 0.8525, P < 0.05), but Ki67 was not (AUC = 0.5943, P = 0.0713). GMNN, MCM2, BUBR1, and Ki67 had higher expression in carcinoma than in dysplasia, regardless of the site of the lesion. Cytoplasmic BUBR1 has the potential to be used as a marker of tumor progression.

Biogenesis and Regulation of the Freeze–Thaw Responsive microRNA Fingerprint in Hepatic Tissue of Rana sylvatica

Background: Freeze-tolerant animals undergo significant physiological and biochemical changes to overcome challenges associated with prolonged whole-body freezing. In wood frog Rana sylvatica (now Lithobates sylvaticus), up to 65% of total body water freezes in extracellular ice masses and, during this state of suspended animation, it is completely immobile and displays no detectable brain, heart, or respirometry activity. To survive such extensive freezing, frogs integrate various regulatory mechanisms to ensure quick and smooth transitions into or out of this hypometabolic state. One such rapid and reversible regulatory molecule capable of coordinating many aspects of biological functions is microRNA. Herein, we present a large-scale analysis of the biogenesis and regulation of microRNAs in wood frog liver over the course of a freeze–thaw cycle (control, 24 h frozen, and 8 h thawed). Methods/Results: Immunoblotting of key microRNA biogenesis factors showed an upregulation and enhancement of microRNA processing capacity during freezing and thawing. This was followed with RT-qPCR analysis of 109 microRNA species, of which 20 were significantly differentially expressed during freezing and thawing, with the majority being upregulated. Downstream bioinformatics analysis of miRNA/mRNA targeting coupled with in silico protein–protein interactions and functional clustering of biological processes suggested that these microRNAs were suppressing pro-growth functions, including DNA replication, mRNA processing and splicing, protein translation and turnover, and carbohydrate metabolism. Conclusions: Our findings suggest that this enhanced miRNA maturation capacity might be one key factor in the vital hepatic miRNA-mediated suppression of energy-expensive processes needed for long-term survival in a frozen state.

Modulation of p300 acetylation to protect against doxorubicin-induced cardiotoxicity

Abstract Background Doxorubicin (DOX) is a widely-used anti-neoplastic agent, but the most common adverse reaction to its use is cardiotoxicity(1). DOX acts by producing reactive oxygen species (ROSs) that cause DNA damage(1,2), which activates various proteins, including the tumour suppressor p53 and the acetyltransferase p300. When activated, p300 acetylates and increases the activity of p53 which leads to increased apoptotic activity(3). Cardiotoxicity results because the heart has limited mechanisms to dispose of ROSs(4), and because cardiomyocytes have a low turnover rate(5). Purpose We examined the p300 inhibitor Theracurmin (THR)(6,7) as a candidate to prevent DOX cardiotoxicity using an in-vivo mouse model, and sought to elucidate the underlying molecular mechanisms using in-vitro studies. Methods C57BL/6 mice were pre-treated with THR or vehicle (as control), then administered DOX or vehicle. Cardiac function was evaluated by echocardiography and cardiac catheterization. In vitro studies used cardiac fibroblasts (FBs) and cardiac endothelial cells (ECs) pre-treated with THR, then with DOX, as in the animal studies. Western blotting and rt-qPCR was used to quantify protein and mRNA levels of genes in the p53-p300 pathway or related to apoptosis, oxidative stress, and cell cycle control. Results DOX-treated mice showed significant decreases in left ventricular (LV) ejection fraction (LVEF, p=0.0004), fractional shortening (FS, p=0.0012), and a significant increase in end-systolic volume (ESV, p=0.0004). We also showed a significant decrease in anterior (LVAW;d, p=0.005) and posterior (LVPW;d, p=0.005) wall thickness of the LV in these mice. However, when mice were pre-treated with THR prior to DOX administration, we saw significant increases in LVEF (p=0.045) and LVPW;d (p=0.015), and a significant decrease in ESV (p=0.0047) compared to those that were not pre-treated. In-vitro analyses demonstrated a significant increase in cleaved caspase 3 protein expression in DOX-treated ECs (p=0.007), that was not prevented by THR pre-treatment. In DOX-treated FBs, we saw a reduction in AKT mRNA (p=0.017) and increases in BAX 9p=0.008), P21 (p=0.0001), and GADD45 (0.037) mRNA expression. In DOX-treated ECs, we also saw significant increases in BAX (p=0.015) and P21 (p=0.011) mRNA expression. These changes in mRNA expression were not reversed with THR pre-treatment in either cell type. Conclusion THR pre-treatment successfully mitigated functional deficits and structural deficits associated with DOX cardiotoxicity. In-vitro studies show that THR pre-treatment was not sufficient to significantly prevent changes in key molecular targets associated with apoptosis. Further studies are required to elucidate the mechanism behind the observed functional changes.Abstract OverviewAbstract Results

Amelanotic Melanoma—Biochemical and Molecular Induction Pathways

Amelanotic melanoma (AM) is a subtype of hypomelanotic or completely amelanotic melanoma. AM is a rare subtype of melanoma that exhibits a higher recurrence rate and aggressiveness as well as worse surveillance than typical melanoma. AM shows a dysregulation of melanin production, cell cycle control, and apoptosis pathways. Knowing these pathways has an application in medicine due to targeted therapies based on the inhibiting elements of the abovementioned pathways. Therefore, we summarized and discussed AM biochemical and molecular induction pathways and personalized medicine approaches, clinical management, and future directions due to the fact that AM is relatively rare. AM is commonly misdiagnosed. Hence, the role of biomarkers is becoming significant. Nonetheless, there is a shortage of biomarkers specific to AM. BRAF, NRAS, and c-KIT genes are the main targets of therapy. However, the role of BRAF and KIT in AM varied among studies. BRAF inhibitors combined with MAK inhibitors demonstrate better results. Immune checkpoint inhibitors targeting CTLA-4 combined with a programmed death receptor 1 (PD-1) show better outcomes than separately. Fecal microbiota transplantation may overcome resistance to immune checkpoint therapy of AM. Immune-modulatory vaccines against indoleamine 2,3-dioxygenase (IDO) and PD ligand (PD-L1) combined with nivolumab may be efficient in melanoma treatment.

An attractor state zone precedes neural crest fate in melanoma initiation.

The field cancerization theory suggests that a group of cells containing oncogenic mutations are predisposed to transformation 1, 2 . We previously identified single cells in BRAF V600E ;p53 -/- zebrafish that reactivate an embryonic neural crest state before initiating melanoma 3-5 . Here we show that single cells reactivate the neural crest fate from within large fields of adjacent abnormal melanocytes, which we term the "cancer precursor zone." These cancer precursor zone melanocytes have an aberrant morphology, dysplastic nuclei, and altered gene expression. Using single cell RNA-seq and ATAC-seq, we defined a distinct transcriptional cell attractor state for cancer precursor zones and validated the stage-specific gene expression initiation signatures in human melanoma. We identify the cancer precursor zone driver, ID1, which binds to TCF12 and inhibits downstream targets important for the maintenance of melanocyte morphology and cell cycle control. Examination of patient samples revealed precursor melanocytes expressing ID1, often surrounding invasive melanoma, indicating a role for ID1 in early melanomagenesis. This work reveals a surprising field effect of melanoma initiation in vivo in which tumors arise from within a zone of morphologically distinct, but clinically covert, precursors with altered transcriptional fate. Our studies identify novel targets that could improve early diagnosis and prevention of melanoma.

Deep predictive data representation model control for photovoltaic maximum power point tracking under partial shading conditions

As deep learning progresses in recent years, deep neural networks (DNNs) have penetrated applications in various industries. The global maximum power point (GMPP) tracking issue exists in photovoltaic (PV) systems. This study proposes a deep predictive data representation model control (PDRC)-based PV GMPP tracking method. The PDRC approach establishes a data representation control model centered on deep prediction by extracting the data features such as the current, voltage, and duty cycle of PV systems controllers on a time series basis. The proposed PDRC method can receive signals of voltage and current, then output duty cycle control signals. Thereby PDRC method can control PV output power to track GMPP efficiently. Finally, the proposed PDRC approach is evaluated with the perturbation observation method (P&O), the improved particle swarm algorithm (PSO-P&O), and the modified cuckoo algorithm (CS-P&O) to compare the PV GMPP tracking performance. In the simulation experiments, the PDRC approach increases the average tracking efficiency over the comparison algorithms by at least 7.729 % and decreases the average tracking time by at least 0.0155 s under partial shading conditions (PSCs). In the physical simulation validation, the proposed PDRC approach possesses minimal power perturbation and increases the average tracking efficiency over the comparison algorithms by at least 0.407 %.

Single-cell omics and machine learning integration to develop a polyamine metabolism-based risk score model in breast cancer patients

BackgroundBreast cancer remains the leading malignant neoplasm among women globally, posing significant challenges in terms of treatment and prognostic evaluation. The metabolic pathway of polyamines is crucial in breast cancer progression, with a strong association to the increased capabilities of tumor cells for proliferation, invasion, and metastasis.MethodsWe used a multi-omics approach combining bulk RNA sequencing and single-cell RNA sequencing (scRNA-seq) to study polyamine metabolism. Data from The Cancer Genome Atlas, Gene Expression Omnibus, and Genotype-Tissue Expression identified 286 differentially expressed genes linked to polyamine pathways in breast cancer. These genes were analyzed using univariate COX and machine learning algorithms to develop a prognostic scoring algorithm. Single-cell RNA sequencing validated the model by examining gene expression heterogeneity at the cellular level.ResultsOur single-cell analyses revealed distinct subpopulations with different expressions of genes related to polyamine metabolism, highlighting the heterogeneity of the tumor microenvironment. The SuperPC model (a constructed risk score) demonstrated high accuracy when predicting patient outcomes. The immune profiling and functional enrichment analyses revealed that the genes identified play a crucial role in cell cycle control and immune modulation. Single-cell validation confirmed that polyamine metabolism genes were present in specific cell clusters. This highlights their potential as therapeutic targets.ConclusionsThis study integrates single cell omics with machine-learning to develop a robust scoring model for breast cancer based on polyamine metabolic pathways. Our findings offer new insights into tumor heterogeneity, and a novel framework to personalize prognosis. Single-cell technologies are being used in this context to enhance our understanding of the complex molecular terrain of breast cancer and support more effective clinical management.

Modeling the effect of land-use change on runoff water quality in the urban watershed: a case study of Settat city, Morocco

ABSTRACT The purpose of this study is to create a model of the quantity and quality of runoff from the urban watershed. The modeling was performed using a personal computer stormwater management model (PCSWMM) tool and was based on washoff and buildup for total suspended solids (TSS), total nitrogen (TN), and total phosphorus (TP) measured in the field. In addition, low impact development (LID) was used under four different scenarios to improve runoff control of the urban hydrologic cycle and reduce pollutant concentrations. Model performance was analyzed using the R2 and NSE goodness-of-fit indices. Thus, three typical rainfall events, as well as field measurement parameters (TSS, TN, and TP), were used for the model's calibration and validation. The base scenario quantified the runoff volume and pollutant load without any intervention in the runoff process control. Scenarios S2 (BR: bioretention) and S3 (PP: permeable pavement) contributed, separately, in reducing runoff and pollutant load but with relatively small percentages. In addition, the results show that scenario S4 (BR and PP) has the most significant impact on flow reduction, by about 10% compared with the base scenario, as well as on the pollutant load reduction, by about 31, 29, and 40% for the parameters TSS, TN, and TP, respectively.

MicroRNAs as Promising Therapeutic Agents Against Prostate Cancer Resistant to Castration—Where Are We Now?

MicroRNAs are a conserved class of small, tissue-specific, non-coding RNAs that regulate gene expression to preserve cellular homeostasis. Proper miRNA expression is crucial for physiological balance because it affects numerous genetic pathways, including cell cycle control, proliferation, and apoptosis, through gene expression targeting. Deregulated miRNA expression has been implicated in several cancer types, including prostate cancer (PC), acting as tumor suppressors or oncogenes. Despite the availability of promising therapies to control tumor growth and progression, effective diagnostic and therapeutic strategies for different types of cancer are still lacking. PC continues to be a significant health challenge, particularly its castration-resistant (CRPC) form, which presents major therapeutic obstacles because of its resistance to conventional androgen deprivation treatments. This review explores miRNAs’ critical roles in gene regulation and cancer biology, as well as various miRNA delivery systems, highlighting their potential and the challenges in effectively targeting cancer cells. It aims to provide a comprehensive overview of the status of miRNA research in the fight against CRPC, summarizing miRNA-based therapies’ successes and limitations. It also highlights the promise of miRNAs as therapeutic agents for CRPC, underlining the need for further research to overcome existing challenges and move these therapies toward clinical applications.

Rate of Adriamycin Resistance Associated (ARA) long Noncoding RNA Expression in Sample of Hepatitis B Virus Iraqi Patients

Numerous biological processes, including epigenetics regulation, control of cell cycle, beside transcriptional, translational and regulation of genes expression, have been linked to long non-coding RNAs lncRNAs . the disruption of expression for lncRNAs are important early stages in in hepatitis B virus disease. Objectives: In order to investigate ARA lncRNA production in Hepatitis B patients, analyze its clinical importance, and examine the possible value as a predictive biomarker, Amplification of Adriamycin Resistance Associated Lnc-RNA and Glyceraldehyde 3-phosphate dehydrogenase (reference gene) was done by two steps reverase- transcriptase polymerase chain reaction ,No significant difference P = 0.566 was observed in the Adriamycin Resistance Associated lncRNA serum levels between chronic hepatitis B virus patient and control ,In the patients group with chronic HBV )infection, the expression of Adriamycin Resistance Associated lncRNAs was elevated to the 2 fold.

Stochastic Boolean model of normal and aberrant cell cycles in budding yeast

The cell cycle of budding yeast is governed by an intricate protein regulatory network whose dysregulation can lead to lethal mistakes or aberrant cell division cycles. In this work, we model this network in a Boolean framework for stochastic simulations. Our model is sufficiently detailed to account for the phenotypes of 40 mutant yeast strains (83% of the experimentally characterized strains that we simulated) and also to simulate an endoreplicating strain (multiple rounds of DNA synthesis without mitosis) and a strain that exhibits ‘Cdc14 endocycles’ (periodic transitions between metaphase and anaphase). Because our model successfully replicates the observed properties of both wild-type yeast cells and many mutant strains, it provides a reasonable, validated starting point for more comprehensive stochastic-Boolean models of cell cycle controls. Such models may provide a better understanding of cell cycle anomalies in budding yeast and ultimately in mammalian cells.

Ultraviolet radiation inhibits mitochondrial bioenergetics activity.

Mitochondria play an important role in cellular function, not only as a major site of adenosine triphosphate (ATP) production but also by regulating energy expenditure, apoptosis signaling, control of the cell cycle, cellular growth, cell differentiation, transportation of metabolites, and production of reactive oxygen species. Interaction with electromagnetic waves can lead to dysregulation or alterations in the patterns of energy activities in the mitochondria. Ultraviolet light (UV) can be found in sunlight and artificial sources, such as lamps. UV radiation can cause damage to DNA, proteins, and lipids. Besides that, UV radiation is largely used in microorganism disinfection. To establish possible alterations in mitochondrial bioenergetics, this study proposes to investigate the UV (at two distinct intervals) effects on isolated mitochondria from mice liver to obtain direct responses and selective permeability of the internal membrane information. UVA-371 and UVC-255 nm lamps were used to irradiate, at different doses varying from 22.5 to 756 mJ/cm2, isolated mitochondria samples. Mitochondrial respiration pathways were investigated by high-resolution respirometry, and possible mitochondrial membrane damages were evaluated by mitochondrial swelling by spectrophotometer analysis. UVC irradiation results (in the higher dose) indicate decrease in 75% of mitochondrial bioenergetics capacity, such as limitation of oxidative phosphorylation in 60% and increased energy dissipation in 30%. Mitochondrial swelling experiments (spectrophotometer) indicated inner membrane damage, and consequently a loss of selective permeability. Direct correlation between irradiation and effect responses was observed, mitochondrial bioenergetics is severely affected by UVC radiation, but (UVA) radiation did not present bioenergetic alterations. These alterations can contribute to improving the knowledge behind the cell death mechanism in disinfection UV light and UV therapy such as phototherapy.

Cell Cycle Complexity: Exploring the Structure of Persistent Subsystems in 414 Models.

Background: The regulation of cellular proliferation and genomic integrity is controlled by complex surveillance mechanisms known as cell cycle checkpoints. Disruptions in these checkpoints can lead to developmental defects and tumorigenesis. Methods: To better understand these mechanisms, computational modeling has been employed, resulting in a dataset of 414 mathematical models in the BioModels database. These models vary significantly in detail and simulated processes, necessitating a robust analytical approach. Results: In this study, we apply the chemical organization theory (COT) to these models to gain insights into their dynamic behaviors. COT, which handles both ordinary and partial differential equations (ODEs and PDEs), is utilized to analyze the compartmentalized structures of these models. COT's framework allows for the examination of persistent subsystems within these models, even when detailed kinetic parameters are unavailable. By computing and analyzing the lattice of organizations, we can compare and rank models based on their structural features and dynamic behavior. Conclusions: Our application of the COT reveals that models with compartmentalized organizations exhibit distinctive structural features that facilitate the understanding of phenomena such as periodicity in the cell cycle. This approach provides valuable insights into the dynamics of cell cycle control mechanisms, refining existing models and potentially guiding future research in this area.

Characterizing Genetic Susceptibility to Colorectal Cancer in Taiwan Through Genome-Wide Association Study.

We conducted the first genome-wide association study (GWAS) of colorectal cancer (CRC) in Taiwan with 5342 cases and 61,015 controls. Ninety-two SNPs in three genomic regions reached genome-wide significance (p < 5 × 10-8). The lead SNPs in these three regions were: rs12778523 (OR = 1.18, 95% CI, 1.15-1.23, p = 4.51 × 10-13), an intergenic SNP between RNA5SP299 and LINC02676 at chromosome 10p14; rs647161 (OR = 1.14, 95% CI, 1.09-1.19, p = 2.21 × 10-9), an intronic SNP in PITX1 at 5q31.1, and rs10427139 (OR = 1.20, 95% CI, 1.14-1.28, p = 3.62 × 10-9), an intronic SNP in GPATCH1 at 19q13.1. We further validated CRC susceptibility SNPs previously identified through GWAS in other populations. A total of 61 CRC susceptibility SNPs were confirmed in Taiwanese. The top validated putative CRC susceptibility genes included: POU2AF2, HAO1, LAMC1, EIF3H, BMP2, ZMIZ1, BMP4, POLD3, CDKN1A, PREX1, CDKN2B, CDH1, and LRIG1. The top enriched pathways included TGF-β signaling, BMP signaling, extracellular matrix organization, DNA repair, and cell cycle control. We could not validate SNPs in HLA-G at 6p22.1 and in NOTCH4 at 6p21.32. We generated a weighted genetic risk score (GRS) using the 61 SNPs and constructed receiver operating characteristic (ROC) curves using the GRS to predict CRC. The area under the ROC curve (AUC) was 0.589 for GRS alone and 0.645 for GRS, sex, and age. These susceptibility SNPs and genes provide important insights into the molecular mechanisms of CRC development and help identify high-risk individuals for CRC in Taiwan.

Performance Analysis and Prediction of 5G Round-Trip Time Based on the VMD-LSTM Method

With the increasing level of industrial informatization, massive industrial data require real-time and high-fidelity wireless transmission. Although some industrial wireless network protocols have been designed over the last few decades, most of them have limited coverage and narrow bandwidth. They cannot always ensure the certainty of information transmission, making it especially difficult to meet the requirements of low latency in industrial manufacturing fields. The 5G technology is characterized by a high transmission rate and low latency; therefore, it has good prospects in industrial applications. To apply 5G technology to factory environments with low latency requirements for data transmission, in this study, we analyze the statistical performance of the round-trip time (RTT) in a 5G-R15 communication system. The results indicate that the average value of 5G RTT is about 11 ms, which is less than the 25 ms of WIA-FA. We then consider 5G RTT data as a group of time series, utilizing the augmented Dickey–Fuller (ADF) test method to analyze the stability of the RTT data. We conclude that the RTT data are non-stationary. Therefore, firstly, the original 5G RTT series are subjected to first-order differencing to obtain differential sequences with stronger stationarity. Then, a time series analysis-based variational mode decomposition–long short-term memory (VMD-LSTM) method is proposed to separately predict each differential sequence. Finally, the predicted results are subjected to inverse difference to obtain the predicted value of 5G RTT, and a predictive error of 4.481% indicates that the method performs better than LSTM and other methods. The prediction results could be used to evaluate network performance based on business requirements, reduce the impact of instruction packet loss, and improve the robustness of control algorithms. The proposed early warning accuracy metrics for control issues can also be used to indicate when to retrain the model and to indicate the setting of the control cycle. The field of industrial control, especially in the manufacturing industry, which requires low latency, will benefit from this analysis. It should be noted that the above analysis and prediction methods are also applicable to the R16 and R17 versions.

Lifting the Profile of Deep Forest Soil Carbon

Forests are the reservoir for a vast amount of terrestrial soil organic carbon (SOC) globally. With increasing soil depth, the age of SOC reportedly increases, implying resistance to change. However, we know little about the processes that underpin deep SOC persistence and what deep SOC is vulnerable to climate change. This review summarizes the current knowledge of deep forest SOC, the processes regulating its cycling, and the impacts of climate change on the fate of deep forest SOC. Our understanding of the processes that influence deep SOC cycling and the extent of SOC stores is limited by available data. Accordingly, there is a large degree of uncertainty surrounding how much deep SOC there is, our understanding of the influencing factors of deep SOC cycling, and how these may be distinct from upper soil layers. To improve our ability to predict deep SOC change, we need to more accurately quantify the deep SOC pool and deepen our knowledge of how factors related to the tree root–soil–microbiome control deep SOC storage and cycling. Thereby, addressing the uncertainty of deep SOC contribution in the global C exchange with climate change and concomitant impacts on forest ecosystem function and resilience.

The Archaeal Cell Cycle.

Since first identified as a separate domain of life in the 1970s, it has become clear that archaea differ profoundly from both eukaryotes and bacteria. In this review, we look across the archaeal domain and discuss the diverse mechanisms by which archaea control cell cycle progression, DNA replication, and cell division. While the molecular and cellular processes archaea use to govern these critical cell biological processes often differ markedly from those described in bacteria and eukaryotes, there are also striking similarities that highlight both unique and common principles of cell cycle control across the different domains of life. Since much of the eukaryotic cell cycle machinery has its origins in archaea, exploration of the mechanisms of archaeal cell division also promises to illuminate the evolution of the eukaryotic cell cycle.