Doxorubicin resistance involves modulation of interferon signaling, transcriptional bursting, and gene co-expression patterns of U-ISGF3-related genes.

Chemotherapy, although effective in treating cancer, can induce various cellular responses, including senescence and drug resistance. Here, we investigate the transcriptomic alterations induced by doxorubicin (DOX), a commonly used chemotherapeutic agent, in human colon cancer cells. Using single-cell RNA sequencing, we identified distinct cell populations and their transcriptional profiles following subtoxic DOX treatment, revealing cell clusters characterized by differential expression of genes involved in cell cycle regulation and interferon (IFN) signaling. DOX-persisting proliferating cells exhibited upregulation of genes reported to be linked to the unphosphorylated form of ISGF3 (U-ISGF3) transcription factor. Furthermore, we found that HSH2D, a poor prognostic marker, was highly upregulated in doxorubicin-surviving proliferative cells, and its expression was correlated with U-ISGF3-related genes. Analysis of transcription kinetics via mathematical modeling revealed that the number of mRNA molecules produced per transcriptional burst was increased for U-ISGF3-related genes. We also observed altered gene co-expression patterns of U-ISGF3-related genes and others upon DOX treatment, which potentially contributes to chemoresistance of DOX-surviving proliferative cells and may influence cancer cell fate after chemotherapy. Our findings highlight U-ISGF3-related genes and the JAK/STAT pathway as potential therapeutic targets for overcoming chemoresistance in colon cancer.

Development of novel rectal/uterine clamping device.

We developed a novel clamping device for laparoscopic surgery, free from conventional pinch structure, capable of uniformly occluding any ductal organ. This study aimed to evaluate performance of the new clamper compared to the pinch-type clamper. The new clamper consists of two metal bars with ties at each end, which enables parallel clamping. A resected porcine stomach was used, with an infusion tube at the anal end to increase intra-luminal pressure. The oral side of the stomach was clamped with either the new clamper or the pinch-type clamper, and their performances were evaluated in qualitative and semi-quantitative manner. Qualitative evaluation involved imaging the clamping site at intra-gastric pressures from 0 to 15 mmHg using microfocus computed tomography. The new clamper showed no gap even under increased intra-luminal pressure, while the pinch-type clamper showed a gap on the distal side. Quantitative evaluation measured bursting pressure under continuous air insufflation. Air leakages were observed in the new clamper at higher intra-luminal pressures than in the pinch-type clamper (46.1 mmHg vs. 13.6 mmHg, P < 0.01). Our new clamping device showed superior performance in preclinical setting compared to the conventional pinch-type clamper. We are currently working on its design freezing and aiming for early commercialization.

Effect of growth hormone on colonic anastomosis after intraperitoneal administration of 5-fluorouracil, bleomycin and cisplatin: An experimental study.

BACKGROUND: Growth hormone (GH) plays a crucial role in wound healing and tissue repair in postoperative patients. In particular, colonic anastomosis healing following colorectal surgery is impaired by numerous chemotherapy agents. AIM: To investigate whether GH can improve the healing of a colonic anastomosis following the adverse effects of intraperitoneal administration of 5-fluorouracil (5-FU), bleomycin and cisplatin. METHODS: Eighty Wistar rats underwent laparotomy and a 1 cm-resection of the transverse colon, followed by an end-to-end anastomosis under general anesthesia. The rats were blindly allocated into four equal groups and administered a different daily intraperitoneal therapeutic regimen for 6 days. The control group (A) received normal saline. Group B received chemotherapy with 5-FU (20 mg/kg), bleomycin (4 mg/kg) and cisplatin (0.7 mg/kg). Group C received GH (2 mg/kg), and group D received the aforementioned combination chemotherapy and GH, as described. The rats were sacrificed on the 7th postoperative day and the anastomoses were macroscopically and microscopically examined. Body weight, bursting pressure, hydroxyproline levels and inflammation markers were measured. RESULTS: All rats survived until the day of sacrifice, with no infections or other complications. A decrease in the body weight of group D rats was observed, not statistically significant compared to group A (P = 1), but significantly different to groups C (P = 0.001) and B (P < 0.01). Anastomotic dehiscence rate was not statistically different between the groups. Bursting pressure was not significantly different between groups A and D (P = 1.0), whereas group B had a significantly lower bursting pressure compared to group D (P < 0.001). All groups had significantly more adhesions than group A. Hydroxyproline, as a measurement of collagen deposition, was significantly higher in group D compared to group B (P < 0.05), and higher, but not statistically significant, compared to group A. Significant changes in group D were recorded, compared to group A regarding inflammation (3.450 vs 2.900, P = 0.016) and fibroblast activity (2.75 vs 3.25, P = 0.021). Neoangiogenesis and collagen deposition were not significantly different between groups A and D. Collagen deposition was significantly increased in group D compared to group B (P < 0.001). CONCLUSION: Intraperitoneal administration of chemotherapy has an adverse effect on the healing process of colonic anastomosis. However, GH can inhibit the deleterious effect of administered chemotherapy agents and induce colonic healing in rats.

Transcriptional bursting dynamics in gene expression.

Gene transcription is a stochastic process that occurs in all organisms. Transcriptional bursting, a critical molecular dynamics mechanism, creates significant heterogeneity in mRNA and protein levels. This heterogeneity drives cellular phenotypic diversity. Currently, the lack of a comprehensive quantitative model limits the research on transcriptional bursting. This review examines various gene expression models and compares their strengths and weaknesses to guide researchers in selecting the most suitable model for their research context. We also provide a detailed summary of the key metrics related to transcriptional bursting. We compared the temporal dynamics of transcriptional bursting across species and the molecular mechanisms influencing these bursts, and highlighted the spatiotemporal patterns of gene expression differences by utilizing metrics such as burst size and burst frequency. We summarized the strategies for modeling gene expression from both biostatistical and biochemical reaction network perspectives. Single-cell sequencing data and integrated multiomics approaches drive our exploration of cutting-edge trends in transcriptional bursting mechanisms. Moreover, we examined classical methods for parameter estimation that help capture dynamic parameters in gene expression data, assessing their merits and limitations to facilitate optimal parameter estimation. Our comprehensive summary and review of the current transcriptional burst dynamics theories provide deeper insights for promoting research on the nature of cell processes, cell fate determination, and cancer diagnosis.

Exact burst-size distributions for gene-expression models with complex promoter structure.

In prokaryotic and eukaryotic cells, most genes are transcribed in a bursty fashion on one hand and complex gene regulations may lead to complex promoter structure on the other hand. This raises an unsolved issue: how does promoter structure shape transcriptional bursting kinetics characterized by burst size and frequency? Here we analyze stochastic models of gene transcription, which consider complex regulatory mechanisms. Notably, we develop an efficient method to derive exact burst-size distributions. The analytical results show that if the promoter of a gene contains only one active state, the burst size indeed follows a geometric distribution, in agreement with the previous result derived under certain limiting conditions. However, if it contains a multitude of active states, the burst size in general obeys a non-geometric distribution, which is a linearly weighted sum of geometric distributions. This superposition principle reveals the essential feature of bursting kinetics in complex cases of transcriptional regulation although it seems that there has been no direct experimental confirmation. The derived burst-size distributions not only highlight the importance of promoter structure in regulating bursting kinetics, but can be also used in the exact inference of this kinetics based on experimental data.

Enhancers: A Focus on Synthetic Biology and Correlated Gene Expression.

Enhancers are central for the regulation of metazoan transcription but have proven difficult to study, primarily due to a myriad of interdependent variables shaping their activity. Consequently, synthetic biology has emerged as the main approach for dissecting mechanisms of enhancer function. We start by reviewing simple but highly parallel reporter assays, which have been successful in quantifying the complexity of the activator/coactivator mechanisms at enhancers. We then describe studies that examine how enhancers function in the genomic context and in combination with other enhancers, revealing that they activate genes through a variety of different mechanisms, working together as a system. Here, we primarily focus on synthetic reporter genes that can quantify the dynamics of enhancer biology through time. We end by considering the consequences of having many genes and enhancers within a 'local environment', which we believe leads to correlated gene expression and likely reports on the general principles of enhancer biology.

Bursting gamma oscillations in neural mass models.

Gamma oscillations (30-120 Hz) in the brain are not periodic cycles, but they typically appear in short-time windows, often called oscillatory bursts. While the origin of this bursting phenomenon is still unclear, some recent studies hypothesize its origin in the external or endogenous noise of neural networks. We demonstrate that an exact neural mass model of excitatory and inhibitory quadratic-integrate and fire-spiking neurons theoretically predicts the emergence of a different regime of intrinsic bursting gamma (IBG) oscillations without any noise source, a phenomenon due to collective chaos. This regime is indeed observed in the direct simulation of spiking neurons, characterized by highly irregular spiking activity. IBG oscillations are distinguished by higher phase-amplitude coupling to slower theta oscillations concerning noise-induced bursting oscillations, thus indicating an increased capacity for information transfer between brain regions. We demonstrate that this phenomenon is present in both globally coupled and sparse networks of spiking neurons. These results propose a new mechanism for gamma oscillatory activity, suggesting deterministic collective chaos as a good candidate for the origin of gamma bursts.

Transcriptional noise, gene activation, and roles of SAGA and Mediator Tail measured using nucleotide recoding single-cell RNA-seq.

We describe a time-resolved nascent single-cell RNA sequencing (RNA-seq) approach that measures gene-specific transcriptional noise and the fraction of active genes in S. cerevisiae. Most genes are expressed with near-constitutive behavior, while a subset of genes show high mRNA variance suggestive of transcription bursting. Transcriptional noise is highest in the cofactor/coactivator-redundant (CR) gene class (dependent on both SAGA and TFIID) and strongest in TATA-containing CR genes. Using this approach, we also find that histone gene transcription switches from a low-level, low-noise constitutive mode during M and M/G1 to an activated state in S phase that shows both an increase in the fraction of active promoters and a switch to a noisy and bursty transcription mode. Rapid depletion of cofactors SAGA and MED Tail indicates that both factors play an important role in stimulating the fraction of active promoters at CR genes, with a more modest role in transcriptional noise.

Transcriptional bursting: from fundamentals to novel insights.

Transcription occurs as irregular bursts in a very wide range of systems, including numerous different species and many genes within these. In this review, we examine the underlying theories, discuss how these relate to experimental measurements, and explore some of the discrepancies that have emerged among various studies. Finally, we consider more recent works that integrate novel concepts, such as the involvement of biomolecular condensates in enhancer-promoter interactions and their effects on the dynamics of transcriptional bursting.

Global transcription regulation revealed from dynamical correlations in time-resolved single-cell RNA sequencing.

Single-cell transcriptomics reveals significant variations in transcriptional activity across cells. Yet, it remains challenging to identify mechanisms of transcription dynamics from static snapshots. It is thus still unknown what drives global transcription dynamics in single cells. We present a stochastic model of gene expression with cell size- and cell cycle-dependent rates in growing and dividing cells that harnesses temporal dimensions of single-cell RNA sequencing through metabolic labeling protocols and cel lcycle reporters. We develop a parallel and highly scalable approximate Bayesian computation method that corrects for technical variation and accurately quantifies absolute burst frequency, burst size, and degradation rate along the cell cycle at a transcriptome-wide scale. Using Bayesian model selection, we reveal scaling between transcription rates and cell size and unveil waves of gene regulation across the cell cycle-dependent transcriptome. Our study shows that stochastic modeling of dynamical correlations identifies global mechanisms of transcription regulation. A record of this paper's transparent peer review process is included in the supplemental information.

Experimental models of high-risk bowel anastomosis in rats: A systematic review.

BACKGROUND: Anastomotic leaks remain one of the most dreaded complications in gastrointestinal surgery causing significant morbidity, that negatively affect the patients' quality of life. Experimental studies play an important role in understanding the pathophysiological background of anastomotic healing and there are still many fields that require further investigation. Knowledge drawn from these studies can lead to interventions or techniques that can reduce the risk of anastomotic leak in patients with high-risk features. Despite the advances in experimental protocols and techniques, designing a high-quality study is still challenging for the investigators as there is a plethora of different models used. AIM: To review current state of the art for experimental protocols in high-risk anastomosis in rats. METHODS: This systematic review was performed according to The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. To identify eligible studies, a comprehensive literature search was performed in the electronic databases PubMed (MEDLINE) and Scopus, covering the period from conception until 18 October 2023. RESULTS: From our search strategy 102 studies were included and were categorized based on the mechanism used to create a high-risk anastomosis. Methods of assessing anastomotic healing were extracted and were individually appraised. CONCLUSION: Anastomotic healing studies have evolved over the last decades, but the findings are yet to be translated into human studies. There is a need for high-quality, well-designed studies that will help to the better understanding of the pathophysiology of anastomotic healing and the effects of various interventions.

Single Cell Transcriptome Analysis During Development in Dictyostelium.

Dictyostelium represents a stripped-down model for understanding how cells make decisions during development. The complete life cycle takes around a day and the fully differentiated structure is composed of only two major cell types. With this apparent reduction in "complexity," single cell transcriptomics has proven to be a valuable tool in defining the features of developmental transitions and cell fate separation events, even providing causal information on how mechanisms of gene expression can feed into cell decision-making. These scientific outputs have been strongly facilitated by the ease of non-disruptive single cell isolation-allowing access to more physiological measures of transcript levels. In addition, the limited number of cell states during development allows the use of more straightforward analysis tools for handling the ensuing large datasets, which provides enhanced confidence in inferences made from the data. In this chapter, we will outline the approaches we have used for handling Dictyostelium single cell transcriptomic data, illustrating how these approaches have contributed to our understanding of cell decision-making during development.

Linearly Amplified Single-Stranded RNA-Derived Transcriptome Sequencing (LAST-seq).

Single-cell RNA sequencing (scRNA-seq) stands as a cutting-edge technology widely used in biological and biomedical research. Existing scRNA-seq methods rely on reverse transcription (RT) and second-strand synthesis (SSS) to convert RNA to cDNA before amplification. However, these methods often suffer from limited RT/SSS efficiency, which compromises the sensitivity of RNA detection. Here, we develop a new method, linearly amplified single-stranded RNA-derived transcriptome sequencing (LAST-seq), which directly amplifies the original single-stranded RNA without prior RT and SSS and offers high-sensitivity RNA detection and a low level of technical noise in single-cell transcriptome analysis. LAST-seq has been applied to quantify transcriptional bursting kinetics in human cells, advancing our understanding of chromatin organization's role in regulating gene expression. Key features • An RNase H/DNA polymerase-based strategy to attach the T7 promoter to single-stranded RNA. • T7 promoter mediated IVT on single stranded RNA template at single cell level.

Classification of coal bursting liability of some chinese coals using machine learning methods.

The classification of coal bursting liability (CBL) is essential for the mitigation and management of coal bursts in mining operations. This study establishes an index system for CBL classification, incorporating dynamic fracture duration (DT), elastic strain energy index (WET), bursting energy index (KE), and uniaxial compressive strength (RC). Utilizing a dataset comprising 127 CBL measurement groups, the impacts of various optimization algorithms were assessed, and two prominent machine learning techniques, namely the back propagation neural network (BPNN) and the support vector machine (SVM), were employed to develop twelve distinct models. The models' efficacy was evaluated based on accuracy, F1-score, Kappa coefficient, and sensitivity analysis. Among these, the Levenberg-Marquardt back propagation neural network (LM-BPNN) model was identified as superior, achieving an accuracy of 96.85%, F1-score of 0.9113, and Kappa coefficient of 0.9417. Further validation in Wudong Coal Mine and Yvwu Coal Industry confirmed the model, achieving 100% accuracy. These findings underscore the LM-BPNN model's potential as a viable tool for enhancing coal burst prevention strategies in coal mining sectors.

Identification of molecular determinants of gene-specific bursting patterns by high-throughput imaging screens.

Stochastic transcriptional bursting is a universal property of active genes. While different genes exhibit distinct bursting patterns, the molecular mechanisms for gene-specific stochastic bursting are largely unknown. We have developed and applied a high-throughput-imaging based screening strategy to identify cellular factors and molecular mechanisms that determine the bursting behavior of human genes. Focusing on epigenetic regulators, we find that protein acetylation is a strong acute modulator of burst frequency, burst size and heterogeneity of bursting. Acetylation globally affects the Off-time of genes but has gene-specific effects on the On-time. Yet, these effects are not strongly linked to promoter acetylation, which do not correlate with bursting properties, and forced promoter acetylation has variable effects on bursting. Instead, we demonstrate acetylation of the Integrator complex as a key determinant of gene bursting. Specifically, we find that elevated Integrator acetylation decreases bursting frequency. Taken together our results suggest a prominent role of non-histone proteins in determining gene bursting properties, and they identify histone-independent acetylation of a transcription cofactor as an allosteric modulator of bursting via a far-downstream bursting checkpoint.

Astroglial gap junctions strengthen hippocampal network activity by sustaining afterhyperpolarization via KCNQ channels.

Throughout the brain, astrocytes form networks mediated by gap junction channels that promote the activity of neuronal ensembles. Although their inputs on neuronal information processing are well established, how molecular gap junction channels shape neuronal network patterns remains unclear. Here, using astroglial connexin-deficient mice, in which astrocytes are disconnected and neuronal bursting patterns are abnormal, we show that astrocyte networks strengthen bursting activity via dynamic regulation of extracellular potassium levels, independently of glutamate homeostasis or metabolic support. Using a facilitation-depression model, we identify neuronal afterhyperpolarization as the key parameter underlying bursting pattern regulation by extracellular potassium in mice with disconnected astrocytes. We confirm this prediction experimentally and reveal that astroglial network control of extracellular potassium sustains neuronal afterhyperpolarization via KCNQ voltage-gated K+ channels. Altogether, these data delineate how astroglial gap junctions mechanistically strengthen neuronal population bursts and point to approaches for controlling aberrant activity in neurological diseases.

Vagus nerve stimulation in bursts can efficiently modulate gastric contractions and contraction frequency at varying gastric pressures.

OBJECTIVE: There has been recent clinical interest in the use of vagus nerve stimulation (VNS) for treating gastrointestinal disorders as an alternative to drugs or gastric electrical stimulation. However, effectiveness of burst stimulation has not been demonstrated. We investigated the ability of bursting and continuous VNS to influence gastric and pyloric activity under a range of stimulation parameters and gastric pressures. The goals of this study were to determine which parameters could optimally excite or inhibit gastric activity. MATERIALS AND METHODS: Data were collected from 21 Sprague-Dawley rats. Under urethane anesthesia, a rubber balloon was implanted into the stomach, connected to a pressure transducer and a saline infusion pump. A pressure catheter was inserted at the pyloric sphincter and a bipolar nerve cuff was implanted onto the left cervical vagus nerve. The balloon was filled to 15 cmH2O. Stimulation trials were conducted in a consistent order; the protocol was then repeated at 25 and 35 cmH2O. The nerve was then transected and stimulation repeated to investigate directionality of effects. RESULTS: Bursting stimulation at the bradycardia threshold caused significant increases in gastric contraction amplitude with entrainment to the bursting frequency. Some continuous stimulation trials could also cause increased contractions but without frequency changes. Few significant changes were observed at the pylorus, except for frequency entrainment. These effects could not be uniquely attributed to afferent or efferent activity. SIGNIFICANCE: Our findings further elucidate the effects of different VNS parameters on the stomach and pylorus and provide a basis for future studies of bursting stimulation for gastric neuromodulation.

Memristor-coupled dual-neuron mapping model: initials-induced coexisting firing patterns and synchronization activities.

Synaptic plasticity makes memristors particularly suitable for simulating the connection synapses between neurons that describe magnetic induction coupling. By applying a memristor to the synaptic coupling between two map-based neuron models, a memristor-coupled dual-neuron mapping (MCDN) model is proposed in this article. The MCDN model has a line fixed point set associated with the memristor initial state, which is always unstable for the model parameters and memristor initial state of interest. Complex spiking/bursting firing patterns and their transitions are disclosed using some dynamical analysis means. The numerical results show that these spiking/bursting firings are significantly relied on the memristor initial state, demonstrating the coexistence of firing patterns. Moreover, the initial effects of complete synchronization are explored for the homogeneous MCDN model, and it is clarified that in addition to being related to the coupling strength, the synchronization activities are extremely dependent on the initial states of the memristor and neurons. Finally, these numerical results are confirmed by the FPGA-based hardware experiments.

Post-task responses following working memory and movement are driven by transient spectral bursts with similar characteristics.

The post-movement beta rebound has been studied extensively using magnetoencephalography (MEG) and is reliably modulated by various task parameters as well as illness. Our recent study showed that rebounds, which we generalise as "post-task responses" (PTRs), are a ubiquitous phenomenon in the brain, occurring across the cortex in theta, alpha, and beta bands. Currently, it is unknown whether PTRs following working memory are driven by transient bursts, which are moments of short-lived high amplitude activity, similar to those that drive the post-movement beta rebound. Here, we use three-state univariate hidden Markov models (HMMs), which can identify bursts without a priori knowledge of frequency content or response timings, to compare bursts that drive PTRs in working memory and visuomotor MEG datasets. Our results show that PTRs across working memory and visuomotor tasks are driven by pan-spectral transient bursts. These bursts have very similar spectral content variation over the cortex, correlating strongly between the two tasks in the alpha (R2 = .89) and beta (R2 = .53) bands. Bursts also have similar variation in duration over the cortex (e.g., long duration bursts occur in the motor cortex for both tasks), strongly correlating over cortical regions between tasks (R2 = .56), with a mean over all regions of around 300 ms in both datasets. Finally, we demonstrate the ability of HMMs to isolate signals of interest in MEG data, such that the HMM probability timecourse correlates more strongly with reaction times than frequency filtered power envelopes from the same brain regions. Overall, we show that induced PTRs across different tasks are driven by bursts with similar characteristics, which can be identified using HMMs. Given the similarity between bursts across tasks, we suggest that PTRs across the cortex may be driven by a common underlying neural phenomenon.

The mesenteric entry site as a potential weak point in gastrointestinal anastomoses - findings from an ex-vivo biomechanical analysis.

PURPOSE: Gastrointestinal disorders frequently necessitate surgery involving intestinal resection and anastomosis formation, potentially leading to severe complications like anastomotic leakage (AL) which is associated with increased morbidity, mortality, and adverse oncologic outcomes. While extensive research has explored the biology of anastomotic healing, there is limited understanding of the biomechanical properties of gastrointestinal anastomoses, which was aimed to be unraveled in this study. METHODS: An ex-vivo model was developed for the biomechanical analysis of 32 handsewn porcine end-to-end anastomoses, using interrupted and continuous suture techniques subjected to different flow models. While multiple cameras captured different angles of the anastomosis, comprehensive data recording of pressure, time, and temperature was performed simultaneously. Special focus was laid on monitoring time, location and pressure of anastomotic leakage (LP) and bursting pressures (BP) depending on suture techniques and flow models. RESULTS: Significant differences in LP, BP, and time intervals were observed based on the flow model but not on the suture techniques applied. Interestingly, anastomoses at the insertion site of the mesentery exhibited significantly higher rates of leakage and bursting compared to other sections of the anastomosis. CONCLUSION: The developed ex-vivo model facilitated comparable, reproducible, and user-independent biomechanical analyses. Assessing biomechanical properties of anastomoses offers an advantage in identifying technical weak points to refine surgical techniques, potentially reducing complications like AL. The results indicate that mesenteric insertion serves as a potential weak spot for AL, warranting further investigations and refinements in surgical techniques to optimize outcomes in this critical area of anastomotic procedures.