Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding the molecular mechanism responsible for developing therapeutic radiation-induced radioresistance of rectal cancer and improving the clinical outcomes of radiotherapy - A review

ABSTRACT Rectal cancer accounts for the second highest cancer-related mortality, which is predominant in Western civilizations. The treatment for rectal cancers includes surgery, radiotherapy, chemotherapy, and immunotherapy. Radiotherapy, specifically external beam radiation therapy, is the most common way to treat rectal cancer because radiation not only limits cancer progression but also significantly reduces the risk of local recurrence. However, therapeutic radiation-induced radioresistance to rectal cancer cells and toxicity to normal tissues are major drawbacks. Therefore, understanding the mechanistic basis of developing radioresistance during and after radiation therapy would provide crucial insight to improve clinical outcomes of radiation therapy for rectal cancer patients. Studies by various groups have shown that radiotherapy-mediated changes in the tumor microenvironment play a crucial role in developing radioresistance. Therapeutic radiation-induced hypoxia and functional alterations in the stromal cells, specifically tumor-associated macrophage (TAM) and cancer-associated fibroblasts (CAF), play a crucial role in developing radioresistance. In addition, signaling pathways, such as – the PI3K/AKT pathway, Wnt/β-catenin signaling, and the hippo pathway, modulate the radiation responsiveness of cancer cells. Different radiosensitizers, such as small molecules, microRNA, nanomaterials, and natural and chemical sensitizers, are being used to increase the effectiveness of radiotherapy. This review highlights the mechanism responsible for developing radioresistance of rectal cancer following radiotherapy and potential strategies to enhance the effectiveness of radiotherapy for better management of rectal cancer.
Formamide denaturation of double-stranded DNA for fluorescence in situ hybridization (FISH) distorts nanoscale chromatin structure

As imaging techniques rapidly evolve to probe nanoscale genome organization at higher resolution, it is critical to consider how the reagents and procedures involved in sample preparation affect chromatin at the relevant length scales. Here, we investigate the effects of fluorescent labeling of DNA sequences within chromatin using the gold standard technique of three-dimensional fluorescence in situ hybridization (3D FISH). The chemical reagents involved in the 3D FISH protocol, specifically formamide, cause significant alterations to the sub-200 nm (sub-Mbp) chromatin structure. Alternatively, two labeling methods that do not rely on formamide denaturation, resolution after single-strand exonuclease resection (RASER)-FISH and clustered regularly interspaced short palindromic repeats (CRISPR)-Sirius, had minimal impact on the three-dimensional organization of chromatin. We present a polymer physics-based analysis of these protocols with guidelines for their interpretation when assessing chromatin structure using currently available techniques.
Systematic computer-aided disulfide design as a general strategy to stabilize prefusion class I fusion proteins

Numerous enveloped viruses, such as coronaviruses, influenza, and respiratory syncytial virus (RSV), utilize class I fusion proteins for cell entry. During this process, the proteins transition from a prefusion to a postfusion state, undergoing substantial and irreversible conformational changes. The prefusion conformation has repeatedly shown significant potential in vaccine development. However, the instability of this state poses challenges for its practical application in vaccines. While non-native disulfides have been effective in maintaining the prefusion structure, identifying stabilizing disulfide bonds remains an intricated task. Here, we present a general computational approach to systematically identify prefusion-stabilizing disulfides. Our method assesses the geometric constraints of disulfide bonds and introduces a ranking system to estimate their potential in stabilizing the prefusion conformation. We found, for the RSV F protein, that disulfides restricting the initial stages of the conformational switch can offer higher stability to the prefusion state than those preventing unfolding at a later stage. The implementation of our algorithm on the RSV F protein led to the discovery of prefusion-stabilizing disulfides, providing evidence that supports our hypothesis. Furthermore, the evaluation of our top design as a vaccine candidate in a cotton rat model demonstrated robust protection against RSV infection, highlighting the potential of our approach for vaccine development. Significance statement Class I fusion proteins, pivotal for cellular entry, constitute primary targets for neutralizing antibodies across a wide range of highly pathogenic viruses. Notably, the prefusion conformation of these proteins has demonstrated to be a robust immunogen, presenting a promising avenue for vaccine development. Despite of this, the inherent structural instability of this conformation poses a substantial hurdle for vaccine formulations. To overcome this limitation and to optimize these proteins as vaccines candidates, we developed an automated computational approach to enhance the structural stability of the prefusion conformation without compromising its immunogenic properties. Given the clinical significance of class I fusion proteins, our computational tool offers a mechanism to accelerate the development of preventive measures against a multitude of viral infections.
Omissions of Threat Trigger Subjective Relief and Prediction Error-Like Signaling in the Human Reward and Salience Systems

The unexpected absence of danger constitutes a pleasurable event that is critical for the learning of safety. Accumulating evidence points to similarities between the processing of absent threat and the well-established reward prediction error (PE). However, clear-cut evidence for this analogy in humans is scarce. In line with recent animal data, we showed that the unexpected omission of (painful) electrical stimulation triggers activations within key regions of the reward and salience pathways and that these activations correlate with the pleasantness of the reported relief. Furthermore, by parametrically violating participants’ probability and intensity related expectations of the upcoming stimulation, we showed for the first time in humans that omission-related activations in the VTA/SN were stronger following omissions of more probable and intense stimulations, like a positive reward PE signal. Together, our findings provide additional support for an overlap in the neural processing of absent danger and rewards in humans.
Comparison of a novel potentiator of CFTR channel activity to ivacaftor in ameliorating mucostasis caused by cigarette smoke in primary human bronchial airway epithelial cells

Background Cystic Fibrosis causing mutations in the gene CFTR, reduce the activity of the CFTR channel protein, and leads to mucus aggregation, airway obstruction and poor lung function. A role for CFTR in the pathogenesis of other muco-obstructive airway diseases such as Chronic Obstructive Pulmonary Disease (COPD) has been well established. The CFTR modulatory compound, Ivacaftor (VX-770), potentiates channel activity of CFTR and certain CF-causing mutations and has been shown to ameliorate mucus obstruction and improve lung function in people harbouring these CF-causing mutations. A pilot trial of Ivacaftor supported its potential efficacy for the treatment of mucus obstruction in COPD. These findings prompted the search for CFTR potentiators that are more effective in ameliorating cigarette-smoke (CS) induced mucostasis. Methods A novel small molecule potentiator (SK-POT1), previously identified in CFTR binding studies, was tested for its activity in augmenting CFTR channel activity using patch clamp electrophysiology in HEK-293 cells, a fluorescence-based assay of membrane potential in Calu-3 cells and in Ussing chamber studies of primary bronchial epithelial cultures. Addition of cigarette smoke extract (CSE) to the solutions bathing the apical surface of Calu-3 cells and primary bronchial airway cultures was used to model COPD. Confocal studies of the velocity of fluorescent microsphere movement on the apical surface of CSE exposed airway epithelial cultures, were used to assess the effect of potentiators on CFTR-mediated mucociliary movement. Results We showed that SK-POT1, like VX-770, was effective in augmenting the cyclic AMP-dependent channel activity of CFTR. SK-POT-1 enhanced CFTR channel activity in airway epithelial cells previously exposed to CSE and ameliorated mucostasis on the surface of primary airway cultures. Conclusion Together, this evidence supports the further development of SK-POT1 as an intervention in the treatment of COPD.
Maternal behavior in Sumatran orangutans (Pongo abelii) is modulated by mother-offspring characteristics and socioecological factors

Mammalian mothers flexibly invest in their offspring to maximize their lifetime fitness. Flexible maternal investment may be particularly important in large-brained species with prolonged maternal care – e.g., in great apes. We investigated the effects of socioecological factors and mother-offspring characteristics on nine maternal behaviors in wild Sumatran orangutans (Pongo abelii; N=22 mother-offspring pairs; over 11,200 hours of focal data; collected from 2007-2022) using generalized linear mixed models. The behaviors fall under four maternal functions: locomotory support (carrying), skill acquisition support (feeding in proximity, food transfer), protective proximity maintenance (body contact and proximity initiation, following), and independence promotion (body contact and proximity termination, avoiding). Mother’s parity was not significantly associated with any maternal behavior. Mothers were more likely to show locomotory support, skill acquisition support, and protective proximity maintenance toward younger than older offspring; whereas they were more likely to promote independence in older than younger offspring. Mothers with male offspring were more likely to show skill acquisition support to their offspring than those with female offspring. With increasing food availability, skill acquisition support reduced. With increasing association size, mothers were more likely to show protective proximity maintenance and less likely to promote independence. When males were present, mothers were more likely to show locomotory support to their offspring. Sumatran orangutan mothers thus flexibly adjust offspring directed behavior in response to prevailing socioecological factors and mother-offspring characteristics. Our findings add support to the evolutionary theory that mammalian mothers flexibly invest in their offspring.
Impact of alternative splicing on Arabidopsis proteome

Alternative splicing is an important regulatory process in eukaryotes. In plants, the major form of alternative splicing is intron retention. Despite its importance, the global impact of AS on the Arabidopsis proteome has not been investigated. In this study, we address this gap by performing a comprehensive integrated analysis of how changes in AS can affect the Arabidopsis proteome using mutants that disrupt ACINUS and PININ, two evolutionarily conserved alternative splicing factors. We used tandem mass tagging (TMT) with real-time search MS3 (RTS-SPS-MS3) coupled with extensive sample fractionations to achieve very high coverage and accurate protein quantification. We then integrated our proteomic data with transcriptomic data to assess how transcript changes and increased intron retention (IIR) affect the proteome. For differentially expressed transcripts, we have observed a weak to moderate correlation between transcript changes and protein changes. Our studies revealed that some IIRs have no effect on either transcript or protein levels, while some IIRs can significantly affect protein levels. Surprisingly, we found that IIRs have a much smaller effect on increasing protein diversity. Notably, the increased intron retention events detected in the double mutant are also detected in the WT under various biotic or abiotic stresses. We further investigated the characteristics of the retained introns. Our extensive proteomic data help to guide the phenotypic analysis and reveal that collective protein changes contribute to the observed phenotypes of the increased anthocyanin, pale green, reduced growth, and short root observed in the acinus pnn double mutant. Overall, our study provides insight into the intricate regulatory mechanism of intron retention and its impact on protein abundance in plants.
Variations of floral temperature in changing weather conditions

Floral temperature is a flower characteristic that has the potential to impact the fitness of flowering plants and their pollinators. Likewise, the presence of floral temperature patterns, areas of contrasting temperature across the flower, can have similar impacts on the fitness of both mutualists. It is currently poorly understood how floral temperature changes under the influence of different weather conditions, and how floral traits may moderate these changes. Such weather dependency will impact how stable floral temperatures are over time and their utility to plant and pollinator. The stability of floral temperature cues is likely to facilitate effective plant-pollinator interactions and play a role in the plant’s reproductive success. We use thermal imaging to monitor how floral temperatures and temperature patterns of four plant species (Cistus ‘snow fire’ and ‘snow white’, Coreopsis verticillata and Geranium psilostemon) change with several weather variables (illumination, temperature; windspeed; cloud cover; humidity and pressure) during times that pollinators are active. All weather variables influenced floral temperature in one or more species. The directionality of these relationships were similar across species. In all species light conditions (illumination) had the greatest influence on floral temperature overall, and in generation of contrasting temperatures between parts of the flower, temperature patterns. The effect sizes of other weather variables were lower and more varied across the four species. Most likely, floral traits such as pigmentation and structure influence these relationships between weather conditions and generation of floral temperature. Synthesis: Floral temperature and the extent to which flowers showed contrasting temperature patterns were influenced predominantly by light conditions. However, several weather variables had additional, lesser, influences. Furthermore, differences in floral traits, pigmentation and structure, likely resulted in differences in temperature responses to given conditions between species and different parts of the same flower. However, floral temperatures and contrasting temperature patterns that are sufficiently elevated for detection by pollinators were maintained across most conditions if flowers received moderate illumination. This suggests the presence of elevated floral temperature and contrasting temperature patterns are fairly constant and may have potential to influence plant-pollinator interactions across weather conditions.
Explainable Deep Learning Framework: Decoding Brain Task and Prediction of Individual Performance in False-Belief Task at Early Childhood Stage

Decoding of brain tasks aims to identify individuals’ brain states and brain fingerprints to predict behavior. Deep learning provides an important platform for analyzing brain signals at different developmental stages to understand brain dynamics. Due to their internal architecture and feature extraction techniques, existing machine learning and deep-learning approaches for fMRI-based brain decoding must improve classification performance and explainability. The existing approaches also focus on something other than the behavioral traits that can tell about individuals’ variability in behavioral traits. In the current study, we hypothesized that even at the early childhood stage (as early as 3 years), connectivity between brain regions could decode brain tasks and predict behavioural performance in false-belief tasks. To this end, we proposed an explainable deep learning framework to decode brain states (Theory of Mind and Pain states) and predict individual performance on ToM-related false-belief tasks in a developmental dataset. We proposed an explainable spatiotemporal connectivity-based Graph Convolutional Neural Network (Ex-stGCNN) model for decoding brain tasks. Here, we consider a dataset (age range: 3-12 yrs and adults, samples: 155) in which participants were watching a short, soundless animated movie, ”Partly Cloudy,” that activated Theory-of-Mind (ToM) and pain networks. After scanning, the participants underwent a ToMrelated false-belief task, leading to categorization into the pass, fail, and inconsistent groups based on performance. We trained our proposed model using Static Functional Connectivity (SFC) and Inter-Subject Functional Correlations (ISFC) matrices separately. We observed that the stimulus-driven feature set (ISFC) could capture ToM and Pain brain states more accurately with an average accuracy of 94%, whereas it achieved 85% accuracy using SFC matrices. We also validated our results using five-fold cross-validation and achieved an average accuracy of 92%. Besides this study, we applied the SHAP approach to identify neurobiological brain fingerprints that contributed the most to predictions. We hypothesized that ToM network brain connectivity could predict individual performance on false-belief tasks. We proposed an Explainable Convolutional Variational Auto-Encoder model using functional connectivity (FC) to predict individual performance on false-belief tasks and achieved 90% accuracy.
The Impact of Digitisation Projects on the Work of Local Historians

Background: the methodology of historical research depends on a commitment to reporting and record keeping based on investigation of primary and secondary sources. This dependence on finding and assessing the reliability of information sources presents particular challenges to designers of information retrieval software intended to support historical research. Aim: this paper reports the results of a questionnaire distributed as the first phase of a research project intended to assess the information needs of historians working with original and/or digitised primary resources. We have been particularly interested in the work of “local” historians working with archives of local newspapers and with image collections that are in the process of being digitised. The primary aim at this stage was to discover whether these historians have a preference between original or digitised resources and to understand the reasons behind any preferences. In the longer term we aim to apply what we have learned to the development of a model of information seeking behaviour that can be used to guide the design of information retrieval applications supporting local historical research. Method: an online survey was distributed to historians in 43 universities in the UK. Results: The results show that historians make an interesting distinction between their preference for working with original documents and the greater “usefulness” of digitised resources. Conclusions: Historical research presents a number of unique challenges. Further research is needed into the unique aspects of the local historian’s information seeking behaviour. An important focus for this research will be the design of archival information retrieval systems that address these unique requirements.
Optimal Consumption and Investment Strategies with Stochastic Interest Rates

We characterize the solution to the consumption and investment problem of a power utility investor in a continuous-time dynamically complete market with stochastic changes in the opportunity set. Under stochastic interest rates the investor optimally hedges against changes in the term structure of interest rates by investing in a coupon bond, or portfolio of bonds, with a payment schedule that equals the forward-expected (i.e. certainty equivalent) consumption pattern. Numerical experiments with two different specifications of the term structure dynamics (the Vasicek model and a three-factor non-Markovian Heath-Jarrow-Morton model) suggest that the hedge portfolio is more sensitive to the form of the term structure than to the dynamics of interest rates.
The influence of selected demographic variables on the triple bottom line reporting of businesses in the Nelson Mandela Bay

Triple bottom line reporting is an important aspect of a business’s sustainability efforts. The compilation of these reports allows the stakeholders of a business to assess the impact that it has on the economy, society, and environment. This increased stakeholder scrutiny of triple bottom line reports has led businesses that report on the triple bottom line to gain a competitive advantage through increased levels of trust and loyalty from their stakeholders. Other benefits of triple bottom line reporting include employee satisfaction and the minimisation of risk through ethical conduct. The purpose of this article was to investigate the influence of selected demographic variables on the triple bottom line reporting of businesses in the Nelson Mandela Bay region. A quantitative approach was implemented, and a self-administered questionnaire was distributed to the respondents. An exploratory factor analysis was conducted, and Cronbach’s alpha coefficients were calculated to assess the validity and reliability of the measuring instrument. The empirical results showed that some demographic variables – the size of the business, the industry in which the business operates, and the management style of the business – had a significant influence on the business’s triple bottom line reporting. Corresponding author: Tony Matchaba-Hove Email addresses for corresponding author: Tony.Matchaba-hove@mandela.ac. za First submission received: 28th February 2018 Revised submission received: 14th May 2018 Accepted: 25th May 2018
Combined Effects of Unsteady River Discharges and Wave Conditions on River Mouth Bar Morphodynamics

River mouth bar formation, a key process in fluvial‐deltaic morphodynamics, is subject to both river discharge and waves. Given the increasing variability of both forcings under continuous climate change and human interventions, assessing their combined effects on mouth bar formation is an imperative issue. In this study, an extensive set of combined high and low river flows coupled with varying wave conditions and sediment grain sizes was assumed for numerical experiments conducted in Delft3D‐SWAN. The results suggested that three regimes existed for mouth bar formation, namely, stable, ephemeral, and absent. These regimes corresponded to consistently weak, initially‐weak‐then‐strong, and initially strong relative wave strengths, respectively, during the onset and reworking stages. Suppression of mouth bar formation further led to the inhibition of deltaic distributary networks. These findings have important implications for water and sediment management strategies, such as water diversion and dam regulation, in estuaries and deltas to prevent coastal erosion.
Pattern preserving quasi-isometries in lamplighter groups and other related groups

In this paper we explore the interplay between aspects of the geometry and algebra of three families of groups of the form B semidirect the integers Z, namely Lamplighter groups, solvable Baumslag-Solitar groups and lattices in SOL. In particular we examine what kind of maps are induced on B by quasi-isometries that coarsely permute cosets of the Z subgroup. By the results of Schwartz(1996) and Taback(2000) in the lattice in SOL and solvable Baumslag-Solitar cases respectively such quasi-isometries induce affine maps of B. We show that this is no longer true in the lamplighter case but the induced maps do share some features with affine maps.