bluuebunny/crossref_metadata_2025 huggingface dataset:
Mutational scanning reveals oncogenicCTNNB1mutations have diverse effects on signalling and clinical traits
Authors: Krishna Anagha , Meynert Alison , Kelder Martijn , Ewing Ailith , Sheraz Shahida , Ferrer-Vaquer Anna , Grimes Graeme , Becher Hannes , Silk Ryan , Semple Colin A , Kendall Timothy , Hadjantonakis Anna-Katerina , Bird Tom , Marsh Joseph A , Hohenstein Peter , Wood Andrew J , Ozdemir Derya D
Published: November 2023

CTNNB1, the gene encoding β-catenin, is a frequent target for oncogenic mutations activating the canonical Wnt signalling pathway, typically via missense mutations within a degron hotspot motif in exon 3. Here, we combine saturation genome editing with a fluorescent reporter assay to quantify signalling phenotypes for all 342 missense mutations in the mutation hotspot, including 74 recurrent mutations reported in over 6000 tumours. Our data define the genetic requirements for β-catenin degron function and reveal diverse levels of signal activation among known driver mutations. Tumorigenesis in different human tissues involves selection forCTNNB1mutations spanning distinct ranges of effect size. In hepatocellular carcinoma, mutations that activate β-catenin relatively weakly are associated with worse prognosis compared to stronger activating mutations, despite greater immune cell infiltration in the tumour microenvironment. Our work therefore provides a resource to understand mutational diversity within a pan-cancer mutation hotspot, with potential implications for targeted therapy.
Mesenchymal Stromal Cells regulate human Hematopoietic Stem Cell survival and regeneration via cAMP/PKA pathway
Authors: Muddineni Siva Sai Naga Anurag , Even Chen Katz , Zipin-Roitman Adi , Beider Katia , Raz Yael , Weizman Eviatar , Nagler Arnon , Milyavsky Michael
Published: November 2023

Ionizing radiation and chemotherapy suppress normal Hematopoietic Stem and Progenitor Cells (HSPCs) function and present an inherent risk of developing bone marrow failure and secondary leukemias. Mesenchymal Stromal Cells (MSCs) constitute an essential HSPC niche component by regulating HSPC quiescence, self-renewal, survival, and differentiation. Yet, the underlying pro-regenerative signaling pathways activated in HSPCs by MSCs remain poorly understood. Here, using co-culture system of bone marrow-derived MSCs and HSPCs we established that irradiated HSPCs co-cultured with MSCs underwent significantly less apoptosis and maintained theirin vivorepopulating ability. We reveal that MSCs mediate protection by preserving pro-survival MCL1 protein levels in human HSPCs. Moreover, using unbiased HSPC transcriptomic analysis complemented with ex vivo and in vivo validation studies we discovered that MSCs activate cAMP/PKA/CREB signaling pathway in HSPCs to prevent MCL1 decline and apoptosis onset upon irradiation. Pharmacological activation of cAMP signaling pathway in human HSPCs replicated MSC mediated protection of HSPC functionality. Collectively, our results highlight the role of cAMP/PKA/CREB signaling pathway in MSC-HSPC cross-talk and its critical role in the regulation of survival and self-renewal ability of human HSPCs. Furthermore, we also revealed pharmacological agents that can mitigate radiation-induced hematological sequelae.
Vault particles are common contaminants of extracellular vesicle preparations
Authors: Liu Xinming , Nizamudeen Zubair , Hill Christopher J , Parmenter Christopher , Arkill Kenton P , Lambert Daniel W. , Hunt Stuart
Published: November 2023

Extracellular vesicles (EVs) may contain a variety of molecular cargo including proteins and nucleic acids. Vault particle components have been repeatedly reported in the literature as EV cargo. Here, we demonstrated by small RNA sequencing that vault RNA (vtRNA) were highly abundant in EV pellets enriched by differential centrifugation. EVs were prepared by commonly used enrichment methods and biochemical assays used to determine whether vault particle components were bona fide EV cargo. EVs were isolated by differential centrifugation, size exclusion chromatography (SEC) and Dynabead immunocapture. RNase and proteinase treatment of EV preparations demonstrated that most vtRNA and major vault protein (MVP) were not enclosed and protected within the EV membrane. Vault-like particles were visualised in differential centrifugation pellets by cryo-transmission electron microscopy. EVs enriched by size exclusion chromatography and those isolated by immunocapture post-ultracentrifugation showed co-purification of MVP, whereas EVs isolated by direct immunocapture from conditioned medium were MVP-negative. Taken together, commonly used isolation techniques, such as differential centrifugation and SEC, can lead to contamination of EVs with vault particles. The current study highlights the importance of determining the topology of putative EV-associated components to determine if they are EV cargo or contaminants that have been co-purified.
External Validation of Machine Learning and EEG for Continuous Pain Intensity Prediction in Healthy Individuals
Authors: Mari Tyler , Henderson Jessica , Ali S. Hasan , Hewitt Danielle , Brown Christopher , Stancak Andrej , Fallon Nicholas
Published: November 2023

Previous research has predicted subjective pain intensity from electroencephalographic (EEG) data using machine learning (ML) models. However, there is a paucity of externally validated ML models for pain assessment, particularly for continuous pain prediction (e.g., decoding pain ratings on a 101-point scale). We aimed to conduct the first external validation paradigm for ML regression models for pain intensity prediction from EEG data. Ninety-one subjects were recruited across three samples. Sample one (n = 40) was used for model development, sample two (n = 51) was used as a cross-subject external validation set, whilst sample three (n = 25) was used as a within-subjects temporal external validation set. Pneumatic pressure stimuli were delivered to the left-hand index fingernail bed at 10 graded intensity levels. Single-trial time-frequency features of peri-stimulus EEG were used to train a Random Forest (RF) model and long short-term memory (LSTM) network to predict pain intensity responses. Results demonstrated that both the RF model and LSTM network predicted pain intensity significantly more accurately than a random prediction model, with the mean absolute error (MAE) of the RF (best performing model) at 19.59, 21.29, and 18.90 for internal validation, cross-subject external validation, and within-subject external validation, respectively. However, neither model was able to predict pain intensity better than a baseline dummy model, which predicted the mean behavioural rating of the training set and did not have access to neural data. Moreover, in a replication of our recent work, we developed a RF model for the classification of low and high-pain trials, which demonstrated internal and external validation accuracies up to 64% and 58%, respectively. Taken together, our results suggest that using ML and EEG to predict continuous pain ratings is not currently feasible. However, classification models demonstrate some potential, consistently outperforming chance across validation samples. Further improvements such as composite measures are required to elevate ML performance to a clinically meaningful level.
SPREd: A simulation-supervised neural network tool for gene regulatory network reconstruction
Authors: Wu Zijun , Sinha Saurabh
Published: November 2023

Reconstruction of gene regulatory networks (GRNs) from expression data is a significant open problem. Common approaches train a machine learning (ML) model to predict a gene’s expression using transcription factors’ (TFs’) expression as features and designate important features/TFs as regulators of the gene. Here, we present an entirely different paradigm, where GRN edges are directly predicted by the ML model. The new approach, named “SPREd” is a simulation-supervised neural network for GRN inference. Its inputs comprise expression relationships (e.g., correlation, mutual information) between the target gene and each TF and between pairs of TFs. The output includes binary labels indicating whether each TF regulates the target gene. We train the neural network model using synthetic expression data generated by a biophysics-inspired simulation model that incorporates linear as well as non-linear TF-gene relationships and diverse GRN configurations. We show SPREd to outperform state-of-the-art GRN reconstruction tools GENIE3, ENNET, PORTIA and TIGRESS on synthetic datasets with high co-expression among TFs, similar to that seen in real data. A key advantage of the new approach is its robustness to relatively small numbers of conditions (columns) in the expression matrix, which is a common problem faced by existing methods. Finally, we evaluate SPREd on real data sets in yeast that represent gold standard benchmarks of GRN reconstruction and show it to perform significantly better than or comparably to existing methods. In addition to its high accuracy and speed, SPREd marks a first step towards incorporating biophysics principles of gene regulation into ML-based approaches to GRN reconstruction.
Titin-based force regulates cardiac myofilament structures mediating length-dependent activation
Authors: Hessel Anthony L. , Kuehn Michel N. , Engels Nichlas M. , Nissen Devin L. , Freundt Johanna K. , Ma Weikang , Irving Thomas C. , Linke Wolfgang A
Published: November 2023

The Frank-Starling law states that the heart’s stroke volume increases with greater preload due to increased venous return, allowing the heart to adapt to varying circulatory demands. Molecularly, increasing preload increases sarcomere length (SL), which alters sarcomere structures that are correlated to increased calcium sensitivity upon activation. The titin protein, spanning the half-sarcomere, acts as a spring in the I-band, applying a SL-dependent force suggested to pull against and alter myofilaments in a way that supports the Frank-Starling effect. To evaluate this, we employed the titin cleavage (TC) model, where a tobacco-etch virus protease recognition site is inserted into distal I-band titin and allows for rapid, specific cleavage of titin in an otherwise-healthy sarcomere. Here, we evaluated the atomic-level structures of amyopathic cardiac myofilaments following 50% titin cleavage under passive stretch conditions using small-angle X-ray diffraction, which measures these structures under near-physiological (functional) conditions. We report that titin-based forces in permeabilized papillary muscle regulate both thick and thin myofilament structures clearly supporting titin’s role in the Frank-Starling mechanism.
Systems analysis of long-term heat stress responses in the C4grassSetaria viridis
Authors: Zhang Peng , Sharwood Robert , Carroll Adam , Estavillo Gonzalo M , von Caemmerer Susanne , Furbank Robert T.
Published: November 2023

A substantial number of C4plants are utilized as food and fodder crops and often display improved resource use efficiency compared to C3counterparts. However, their response to future extreme climates such as heatwaves is less understood.Setaria viridis, an emerging C4model grass closely related to important C4 crops, was grown under high temperature for two weeks (42°C as compared to 28°C). High temperature resulted in stunted growth, but surprisingly had little impact on leaf area based photosynthetic rates. Rates of dark respiration significantly increased and there were major alterations in carbon and nitrogen metabolism in the heat-stressed plants, including reduced starch levels, accumulation of soluble sugars and an increase in leaf nitrogen content. Measurements of major phytohormones revealed a dramatic increase in abscisic acid in the heat-stressed plants. Leaf transcriptomics, proteomics and metabolomics analyses were carried out and mapped onto metabolic pathways of photosynthesis, respiration, carbon/nitrogen metabolism and hormone synthesis and signaling. Overall, upregulation of a number of stress-signaling pathways was observed, consistent with multiple potent signals leading to reduced plant growth. A systems model of plant response is presented based on oxidative stress, hormone and sugar signaling pathways.
Genetic Discovery Enabled by A Large Language Model
Authors: Tu Tao , Fang Zhouqing , Cheng Zhuanfen , Spasic Svetolik , Palepu Anil , Stankovic Konstantina M. , Natarajan Vivek , Peltz Gary
Published: November 2023

Artificial intelligence (AI) has been used in many areas of medicine, and recently large language models (LLMs) have shown potential utility for clinical applications. However, since we do not know if the use of LLMs can accelerate the pace of genetic discovery, we used data generated from mouse genetic models to investigate this possibility. We examined whether a recently developed specialized LLM (Med-PaLM 2) could analyze sets of candidate genes generated from analysis of murine models of biomedical traits. In response to free-text input, Med-PaLM 2 correctly identified the murine genes that contained experimentally verified causative genetic factors for six biomedical traits, which included susceptibility to diabetes and cataracts. Med-PaLM 2 was also able to analyze a list of genes with high impact alleles, which were identified by comparative analysis of murine genomic sequence data, and it identified a causative murine genetic factor for spontaneous hearing loss. Based upon this Med-PaLM 2 finding, a novel bigenic model for susceptibility to spontaneous hearing loss was developed. These results demonstrate Med-PaLM 2 can analyze gene-phenotype relationships and generate novel hypotheses, which can facilitate genetic discovery.
High-fat diets promote peritoneal inflammation and augment endometriosis-associated abdominal hyperalgesia
Authors: Herup-Wheeler Tristin , Shi Mingxin , Harvey Madeleine E. , Talwar Chandni , Kommagani Ramakrishna , MacLean James A. , Hayashi Kanako
Published: November 2023

Immune dysfunction is one of the central components in the development and progression of endometriosis by establishing a chronic inflammatory environment. Western-style high-fat diets (HFD) have been linked to greater systemic inflammation to cause metabolic and chronic inflammatory diseases, and are also considered an environmental risk factor for gynecologic diseases. Here, we aimed to examine how HFD alter an inflammatory environment in endometriosis and discern their contribution to endometriotic-associated hyperalgesia. Our results showed that HFD-induced obesity enhanced abdominal mechanical allodynia that was induced by endometriotic lesions. Peritoneal inflammatory macrophages and cytokine levels increased by lesion induction were elevated by chronic exposure to HFD. Pain-related mediators in the dorsal root ganglia were further stimulated after lesion induction under the HFD condition. Although HFD did not affect inflammatory macrophages in the peritoneal cavity without lesion induction, the diversity and composition of the gut microbiota were clearly altered by HFD as a sign of low-grade systemic inflammation. Thus, HFD alone might not establish a local inflammatory environment in the pelvic cavity, but it can contribute to further enhancing chronic inflammation, leading to the exacerbation of endometriosis-associated abdominal hyperalgesia following the establishment and progression of the disease.
Synergistic Role of NK Cells and Monocytes in Promoting Atherogenesis in Severe COVID-19 Patients
Authors: Gunasena Manuja , Alles Mario , Wijewantha Yasasvi , Mulhern Will , Bowman Emily , Gabriel Janelle , Kettelhut Aaren , Kumar Amrendra , Weragalaarachchi Krishanthi , Kasturiratna Dhanuja , Horowitz Jeffrey C , Scrape Scott , Pannu Sonal R , Liu Shan-Lu , Vilgelm Anna , Wijeratne Saranga , Bednash Joseph S , Demberg Thorsten , Funderburg Nicholas T , Liyanage Namal P.M.
Published: November 2023

Clinical data demonstrate an increased predisposition to cardiovascular disease (CVD) following severe COVID-19 infection. This may be driven by a dysregulated immune response associated with severe disease. Monocytes and vascular tissue resident macrophages play a critical role in atherosclerosis, the main pathology leading to ischemic CVD. Natural killer (NK) cells are a heterogenous group of cells that are critical during viral pathogenesis and are known to be dysregulated during severe COVID-19 infection. Their role in atherosclerotic cardiovascular disease has recently been described. However, the contribution of their altered phenotypes to atherogenesis following severe COVID-19 infection is unknown. We demonstrate for the first time that during and after severe COVID-19, circulating proinflammatory monocytes and activated NK cells act synergistically to increase uptake of oxidized low-density lipoprotein (Ox-LDL) into vascular tissue with subsequent foam cell generation leading to atherogenesis despite recovery from acute infection. Our data provide new insights, revealing the roles of monocytes/macrophages, and NK cells in COVID-19-related atherogenesis.
Nucleus accumbens dopamine release reflects Bayesian inference during instrumental learning
Authors: Qü Albert J. , Tai Lung-Hao , Hall Christopher D. , Tu Emilie M. , Eckstein Maria K. , Mishchanchuk Karyna , Lin Wan Chen , Chase Juliana B. , MacAskill Andrew F. , Collins Anne G. E. , Gershman Samuel J. , Wilbrecht Linda
Published: November 2023

Dopamine release in the nucleus accumbens has been hypothesized to signal reward prediction error, the difference between observed and predicted reward, suggesting a biological implementation for reinforcement learning. Rigorous tests of this hypothesis require assumptions about how the brain maps sensory signals to reward predictions, yet this mapping is still poorly understood. In particular, the mapping is non-trivial when sensory signals provide ambiguous information about the hidden state of the environment. Previous work using classical conditioning tasks has suggested that reward predictions are generated conditional on probabilistic beliefs about the hidden state, such that dopamine implicitly reflects these beliefs. Here we test this hypothesis in the context of an instrumental task (a two-armed bandit), where the hidden state switches repeatedly. We measured choice behavior and recorded dLight signals reflecting dopamine release in the nucleus accumbens core. Model comparison among a wide set of cognitive models based on the behavioral data favored models that used Bayesian updating of probabilistic beliefs. These same models also quantitatively matched the dopamine measurements better than non-Bayesian alternatives. We conclude that probabilistic belief computation contributes to instrumental task performance in mice and is reflected in mesolimbic dopamine signaling.
Christianson Syndrome across the Lifespan: An International Longitudinal Study in Children, Adolescents, and Adults
Authors: Kavanaugh Brian C. , Elacio Jennifer , Best Carrie R. , St. Pierre Danielle G. , Pescosolido Matthew F. , Ouyang Qing , Caruso Paul , Buch Karen , Biedermann John , Bradley Rebecca S. , Liu Judy S. , Jones Richard N. , Morrow Eric M.
Published: November 2023

Mutations in the X-linked endosomal Na+/H+ Exchanger 6 (NHE6) causes Christianson Syndrome (CS). In the largest study to date, we examine genetic diversity and clinical progression, including cerebellar degeneration, in CS into adulthood. Data were collected as part of the International Christianson Syndrome and NHE6 (SLC9A6) Gene Network Study. Forty-four individuals with 31 unique NHE6 mutations, age 2 to 32 years, were followed prospectively, herein reporting baseline, 1-year follow-up, and retrospective natural history. We present data on the CS phenotype with regard to physical growth, adaptive and motor regression, and across the lifespan, including information on mortality. Longitudinal data on body weight and height were examined using a linear mixed model: the rate of growth across development was slow and resulted in prominently decreased age-normed height and weight by adulthood. Adaptive functioning was longitudinally examined: a majority of adult (18+ years) participants lost gross and fine motor skills over a 1-year follow-up. Previously defined core diagnostic criteria for CS (present in >85%) – namely nonverbal status, intellectual disability, epilepsy, postnatal microcephaly, ataxia, hyperkinesia – were universally present in age 6 to 16; however, an additional core feature of high pain tolerance was added (present in 91%), and furthermore, evolution of symptoms were noted across the lifespan, such that postnatal microcephaly, ataxia and high pain threshold were often not apparent prior to age 6, and hyperkinesis decreased after age 16. While neurologic exams were consistent with cerebellar dysfunction, importantly, a majority of individuals (>50% older than 10) also had corticospinal tract abnormalities. Three participants died during the period of the study. In this large and longitudinal study of CS, we begin to define the trajectory of symptoms and the adult phenotype, thereby identifying critical targets for treatment.
Disentangling heterogeneity in Substance Use Disorders: Insights from Genome-Wide Polygenic Scores
Authors: Vilar-Ribó Laura , Alemany Silvia , Cabana-Domínguez Judit , Llonga Natalia , Arribas Lorena , Grau-López Lara , Daigre Constanza , Cormand Bru , Fernàndez-Castillo Noèlia , Ramos-Quiroga Josep Antoni , Artigas María Soler , Ribasés Marta
Published: November 2023

Substance use disorder (SUD) is a global health problem with significant impact on individuals and society. The presentation of SUD is diverse, involving various substances, ages at onset, comorbid conditions, and disease trajectories. Current treatments for SUD struggle to address this heterogeneity, resulting in high relapse rates. SUD often co-occurs with other psychiatric and mental-health related conditions that contribute to the heterogeneity of the disorder and predispose to adverse disease trajectories. Family and genetic studies highlight the role of genetic and environmental factors in the course of SUD, and point to a shared genetic liability between SUDs and comorbid psychopathology. In this study, we aimed to disentangle SUD heterogeneity using a deeply phenotyped SUD cohort and polygenic scores (PGSs) for psychiatric disorders and related traits. We explored associations between PGSs and various SUD-related phenotypes, as well as PGS-environment interactions using information on lifetime emotional, physical and/or sexual abuse. Our results revealed different patterns of associations between the genetic liability for mental-health related traits and SUD-related phenotypes, which may help explain part of the heterogeneity observed in SUD. In our SUD sample, we found associations linking the genetic liability for ADHD with lower educational attainment, the genetic liability for PTSD with higher rates of unemployment, the genetic liability for educational attainment with lower rates of criminal records and unemployment and the genetic liability for well-being with lower rates of outpatient treatments and fewer problems related to family and social relationships. We also found evidence of PGS-environment interactions showing that genetic liability for suicide attempt worsened the psychiatric status in SUD individuals with a history of emotional physical and/or sexual abuse. Collectively, these data contribute to a better understanding of the role of the genetic liability for mental health-related conditions and adverse life experiences in SUD heterogeneity.
Urine proteomic analysis of patients with schizophrenia
Authors: Zhao Chenyang , Dong Fang , Zhou Fuchun , Huan Yuhang , Yang Jian , Gao Youhe
Published: November 2023

We tried to explore the difference of urinary proteome between unmedicated schizophrenia patients and normal people through a small number of cases. The results showed that a total of 35 differential proteins were screened in the schizophrenia group compared with the healthy control group. Through random grouping evaluation, it has 91.4 % credibility. Fifteen of the differentially expressed proteins were reported to be related to schizophrenia mechanism, drug target or nervous system regulation. Among them, the aromatic amino acid decarboxylase related to the pathogenesis of schizophrenia can distinguish all 10 patients and 9 normal people with 100 % accuracy in this study, and the AUC value of 17 proteins is greater than or equal to 0.9. The biological pathways enriched by differentially expressed proteins include ephrin receptor signaling pathway, positive regulation of long-term potentiation (LTP), etc. This study shows that urine proteomics can reflect the difference between schizophrenia and healthy controls, and has the potential as a diagnostic marker.
Prosthetic Visual Acuity with the PRIMA System in Patients with Atrophic Age-related Macular Degeneration at 4 years follow-up
Authors: Muqit MMK. , Le Mer Y. , Olmos de Koo L , Holz FG , Sahel JA , Palanker D.
Published: November 2023

Objective

To assess the efficacy and safety of the PRIMA subretinal neurostimulation system 48-months post-implantation for improving visual acuity (VA) in patients with geographic atrophy (GA) due to age-related macular degeneration (AMD) at 48-months post-implantation.

Design

First-in-human clinical trial of the PRIMA subretinal prosthesis in patients with atrophic AMD, measuring best-corrected ETDRS VA (Clinicaltrials.govNCT03333954).

Subjects

Five patients with GA, no foveal light perception and VA of logMAR 1.3 to 1.7 in their worse-seeing “study” eye.

Methods

In patients implanted with a subretinal photovoltaic neurostimulation array containing 378 pixels of 100 μm in size, the VA was measured with and without the PRIMA system using ETDRS charts at 1 meter. The system’s external components: augmented reality glasses and pocket computer, provide image processing capabilities, including zoom.

Main Outcome Measures

VA using ETDRS charts with and without the system. Light sensitivity in the central visual field, as measured by Octopus perimetry. Anatomical outcomes demonstrated by fundus photography and optical coherence tomography up to 48-months post- implantation.

Results

All five subjects met the primary endpoint of light perception elicited by the implant in the scotoma area. In one patient the implant was incorrectly inserted into the choroid. One subject died 18-months post-implantation due to study-unrelated reason. ETDRS VA results for the remaining three subjects are reported herein. Without zoom, VA closely matched the pixel size of the implant: 1.17 ± 0.13 pixels, corresponding to mean logMAR 1.39, or Snellen 20/500, ranging from 20/438 to 20/565. Using zoom at 48 months, subjects improved their VA by 32 ETDRS letters versus baseline (SE 5.1) 95% CI[13.4,49.9], p<0.0001. Natural peripheral visual function in the treated eye did not decline after surgery compared to the fellow eye (p=0.08) during the 48 months follow-up period.

Conclusions

Subretinal implantation of PRIMA in subjects with GA suffering from profound vision loss due to AMD is feasible and well tolerated, with no reduction of natural peripheral vision up to 48-months. Using prosthetic central vision through photovoltaic neurostimulation, patients reliably recognized letters and sequences of letters,and with zoom it provided a clinically meaningful improvement in VA of up to eight ETDRS lines.
Development of supramolecular anticoagulants with on-demand reversibility
Authors: Dockerill Millicent , Ford Daniel J. , Angerani Simona , Alwis Imala , Ripoll-Rozada Jorge , Smythe Rhyll E. , Liu Joanna S.T. , Barbosa Pereira Pedro José , Jackson Shaun P. , Payne Richard J. , Winssinger Nicolas
Published: November 2023

Drugs are administered at a dosing schedule set by their therapeutic index and termination of action is achieved by clearance and metabolism of the drug (hours to days for small molecules, weeks to months for biologics). In some cases, it is important to achieve a fast reversal of the drug’s action to overcome dangerous side effects or in response to unforeseen events. A case in point is for anticoagulant drugs. Here we report a general strategy to achieve on-demand reversibility by leveraging supramolecular assembly of drug fragments and showcase the approach with thrombin-inhibiting anticoagulants. In our supramolecular drug design, the action of the drug is reinforced by a dynamic hybridisation of peptide nucleic acids (PNAs) between drug fragments. We show that this design enables the generation of very potent bivalent direct thrombin inhibitors (Ki74 pM) and this inhibition can be reversed through the use of a PNA antidote. We demonstrate that these supramolecular inhibitors exhibit potent anticoagulant activityin vitroandin vivoand that this activity can also be reversed on demand.
How copper based grape pest management has impacted wine aroma
Authors: De Guidi Irene , Galeote Virginie , Blondin Bruno , Legras Jean-Luc
Published: November 2023

Despite the high energetic cost of the reduction of sulfate to H2S, required for the synthesis of sulfur-containing amino acids, some wineSaccharomyces cerevisiaestrains have been reported to produce excessive amounts of H2S during alcoholic fermentation, which is detrimental to wine quality. Surprisingly, in the presence of sulfite, used as a preservative, wine strains produce more H2S than wild (oak) or wine velum (flor) isolates during fermentation. Since copper resistance caused by the amplification of the sulfur rich protein Cup1p is a specific adaptation trait of wine strains, we analyzed the link between copper resistance mechanism and H2S production. We show that a higher content of copper in the must increases the production of H2S. Using a set of 51 strains we observed a positive and then negative relation between the number of copies ofCUP1and H2S production during fermentation. This complex pattern could be mimicked using a multicopy plasmid carryingCUP1, confirming the relation between copper resistance and H2S production. The massive use of copper for vine sanitary management has led to the selection of resistant strains at the cost of a metabolic tradeoff: the overproduction of H2S, resulting in a decrease in wine quality.
Impact of non-invasive ventilation on exacerbation frequency in COPD patients
Authors: Zimmermann Maximilian , Margalitadze Georgi , Kroppen Doreen , Windisch Wolfram , Majorski Daniel S , Berger Melanie , Stanzel Sarah B , Wollsching-Strobel Maximilian
Published: November 2023

BACKGROUND

Acute exacerbations of COPD are key events in the natural course of the patients illness, as they significantly impair the health condition, accelerate the deterioration of lung function, worsen the prognosis for the patient and account for the majority of the COPD-related healthcare costs. Particularly in patients with a pre-existing non-invasive ventilation (NIV) therapy, a reduction of exacerbation frequency is crucial, as they are at high risk for a lasting morbidity and increased mortality.

METHODOLOGY

A prospective cohort study was conducted. Data from adult patients with the diagnosis COPD and existing High-Intensity NIV (HINIV) therapy from August 2021 to September 2023 was analyzed. Exacerbation history of moderate and severe exacerbations of the past 12 months and blood gases at initiation and during HINIV therapy were analyzed.

RESULTS

20 patients were included (mean age 69.2±9 years; 70% female). After initiation of HINIV therapy the frequency of exacerbation displayed a significant reduction from 1.5±0.9 to 0.5±0.5 per year (p<0.001). In addition, improvements in pCO2(73.0±22.0 mmHg vs. 44.0±4.8 mmHg; p<0.001), the pH (7.33±0.1 vs. 7.42±0.0; p<0.001) and HCO3-(33.0±4.9 mmol/l vs. 27.9±3.2 mmol/l; p<0.001) were successfully demonstrated.

DISCUSSION

The present study demonstrates the positive effects of high-intensity NIV on exacerbation rate, measured by the number of moderate and severe exacerbations in one year. Most significant effects were observed when patients had a high number of exacerbations before the initiation of NIV therapy.

What are the main findings?

A significant reduction in the number of exacerbations was demonstrated with HINIV.

There was a strong reduction in the frequency of exacerbations, especially in patients with a high frequency of exacerbations before the HINIV therapy was initiated.

What are the implications of the main findings?

The exacerbation history should be a more important factor in determining the indication for NIV therapy.

Further studies on the pathophysiological causes must follow in order to comprehensively assess the therapeutic effects of NIV.
Psychometric properties of the Dutch London Measure of Unplanned Pregnancy for pregnant people and their partners
Authors: Sprenger Merel , Beumer Wieke Y. , van Ditzhuijzen Jenneke , Kiefte-de Jong Jessica C.
Published: November 2023

Context

It is often unclear what constitutes an unplanned or unintended pregnancy, and pregnancy intentions may be multidimensional dynamic. The London Measure of Unplanned Pregnancy (LMUP) measures pregnancy intentions in a manner close to the actual experience. The aim of this study is to establish a Dutch version of the LMUP (LMUP-NL) and to evaluate the reliability and validity of this version for both people who were pregnant and their partners, whatever the pregnancy outcome.

Methods

A psychometric evaluation of the LMUP using observational data from the BluePrInt study and the RISE UP study was conducted with 1201 people (839 people who were pregnant and 362 partners), aged between 16-55 years. The LMUP-NL was translated based using the Flemish LMUP and the UK 2020 update, resulting in a version for people who were pregnant and one for partners. Next, the acceptability, readability, reliability, construct and convergent validity were analyzed, combining Principal Component analysis, Confirmatory Factor analysis and Mokken scale analyses.

Results

The LMUP-NL demonstrated to be readable and reliable (Cronbach’s alpha >0.80 for both versions). Construct validity of both versions was acceptable (CFI>0.93) and Mokken scale analyses indicated a strong scale (H-coefficient:0.68).

Conclusions

The LMUP-NL is reliable and valid for people who were pregnant and their partners, regardless of the pregnancy outcome. It offers researchers and policy makers an instrument suitable to measure pregnancy intention in a multidimensional manner, constituting a closer reflection of the actual experience of pregnancy intentions.
Thermodynamically-consistent, reduced models of gene regulatory networks
Authors: Pan Michael , Gawthrop Peter J. , Faria Matthew , Johnston Stuart T.
Published: November 2023

Synthetic biology aims to engineer novel functionalities into biological systems. While the approach has to date been predominantly applied to single cells, a richer set of biological phenomena can be engineered by applying synthetic biology to cell populations. To rationally design cell populations, we require mathematical models that link between intracellular biochemistry and intercellular interactions. In this study, we develop a kinetic model of gene expression that is suitable for incorporation into agent-based models of cell populations. To be scalable to large cell populations, models of gene expression should be both computationally efficient and compliant with the laws of physics. We satisfy the first requirement by applying a model reduction scheme to translation, and the second requirement by formulating models using bond graphs. Our reduced model is significantly faster to simulate than the full model, and faithfully reproduces important behaviours of the full model. We couple separate models of gene expression to build models of the toggle switch and repressilator. With these models, we explore the effects of resource availability and cell-to-cell heterogeneity on circuit behaviour. The modelling approaches developed in this study are a bridge towards engineering collective cell behaviours such as synchronisation and division of labour.
In-vivodistributed multicellular control of gene expression in microbial consortia
Authors: Salzano Davide , Shannon Barbara , Grierson Claire , Marucci Lucia , Savery Nigel J , di Bernardo Mario
Published: November 2023

This paper presents an innovative approach in synthetic biology, focusing on the engineering of biomolecular feedback control systems within microbial consortia to achieve robust and precise regulation of desired phenotypes. Traditional biomolecular control strategies, while effective, are predominantly confined to single-cell applications, limiting their complexity and adaptability due to metabolic constraints. We propose a novel methodology that distributes control functionalities across different cell populations within a microbial consortium. This approach leverages the division of labor and cooperative interactions among microbial populations, significantly enhancing flexibility and robustness. We build on the foundation of synthetically engineered microbial consortia, known for their applications in complex compound production and advanced computational processes. However, the challenge of implementing a distributed feedback control loop for precise phenotype regulation in synthetic communities has remained unaddressed. Our work closes this gap by developing and validating an in-vivo feedback control loop distributed across a bacterial consortium, specifically designed using two Escherichia coli strains. These strains are engineered to perform the three essential control functions: computation, sensing, and actuation. We employ orthogonal quorum sensing signaling molecules for communication between the controller and target cell populations. Through in-vivo experiments, we compare closed-loop and open-loop configurations to demonstrate the effectiveness of our approach. The results show that our distributed control system can regulate gene expression levels in target populations with high precision and robustness, even in the presence of consortium composition variations. This feature is particularly vital for practical applications in synthetic biology where stability and adaptability are crucial. Our study not only addresses a significant gap in synthetic biology literature but also opens avenues for more complex and reliable synthetic biology applications.
Hierarchical topological analysis of crystal structures: the skeletal net concept
Authors: Blatova Olga A. , Blatov Vladislav A.
Published: November 2023

Topological analysis of crystal structures faces the problem of the `correct' or the `best' assignment of bonds to atoms, which is often ambiguous. A hierarchical scheme is used where any crystal structure is described as a set of topological representations, each of which corresponds to a particular assignment of bonds encoded by a periodic net. In this set, two limiting nets are distinguished, complete and skeletal, which contain, respectively, all possible bonds and the minimal number of bonds required to keep the structure periodicity. Special attention is paid to the skeletal net since it describes the connectivity of a crystal structure in the simplest way, thus enabling one to find unobvious relations between crystalline substances of different composition and architecture. The tools for the automated hierarchical topological analysis have been implemented in the program package ToposPro. Examples, which illustrate the advantages of such analysis, are considered for a number of classes of crystalline substances: elements, intermetallics, ionic and coordination compounds, and molecular crystals. General provisions of the application of the skeletal net concept are also discussed.
Reporting controversial issues in controversial industries
Authors: Marshall Donna , Rehme Jakob , O'Dochartaigh Aideen , Kelly Stephen , Boojihawon Roshan , Chicksand Daniel
Published: November 2023

Purpose

This article explores how companies in multiple controversial industries report their controversial issues. For the first time, the authors use a new conceptualization of controversial industries, focused on harm and solutions, to investigate the reports of 28 companies in seven controversial industries: Agricultural Chemicals, Alcohol, Armaments, Coal, Gambling, Oil and Tobacco.

Design/methodology/approach

The authors thematically analyzed company reports to determine if companies in controversial industries discuss their controversial issues in their reporting, if and how they communicate the harm caused by their products or services, and what solutions they provide.

Findings

From this study data the authors introduce a new legitimacy reporting method in the controversial industries literature: the solutions companies offer for the harm caused by their products and services. The authors find three solution reporting methods: no solution, misleading solution and less-harmful solution. The authors also develop a new typology of reporting strategies used by companies in controversial industries based on how they report their key controversial issue and the harm caused by their products or services, and the solutions they offer. The authors identify seven reporting strategies: Ignore, Deny, Decoy, Dazzle, Distort, Deflect and Adapt.

Research limitations/implications

Further research can test the typology and identify strategies used by companies in different institutional or regulatory settings, across different controversial industries or in larger populations.

Practical implications

Investors, consumers, managers, activists and other stakeholders of controversial companies can use this typology to identify the strategies that companies use to report controversial issues. They can assess if reports admit to the controversial issue and the harm caused by a company's products and services and if they provide solutions to that harm.

Originality/value

This paper develops a new typology of reporting strategies by companies in controversial industries and adds to the theory and discourse on social and environmental reporting (SER) as well as the literature on controversial industries.
Remittances and agricultural productivity: the effect of heterogeneity in economic activity of farming households in Ghana
Authors: Eghan Mark , Adjasi Charles
Published: November 2023

Purpose

This paper aims to test the impact of remittances receipt on agricultural productivity. The paper empirically assesses whether heterogeneity in economic activity of farming households affects the effects of remittances on productivity of tradable and nontradable crop farming households in Ghana.

Design/methodology/approach

The authors employ propensity score matching (PSM) methods to address potential endogeneity issues that could arise from the estimation due to selection bias. This paper uses the seventh round of Ghana living standard survey dataset for Ghana.

Findings

The authors find that, the involvement of farming households in other economic activities alters the impact of remittances on crop yield. This differential impact also varies according whether the crop is tradeable or not.

Practical implications

Policy can reduce the cost of sending remittances and include financial literacy modules in the farmer training modules to increase farmers' knowledge on investment of remittance in agricultural production.

Originality/value

The authors distinguish the paper from others by controlling for crop types (particularly tradeable or otherwise and gestation period), farming of a second or more crops and engagement of smallholder farmers in nonfarm economic activities.
Resolving power imbalances in construction payment using blockchain smart contracts
Authors: Wu Liupengfei , Lu Weisheng , Chen Chen
Published: November 2023

Purpose

This research aims to develop a blockchain smart contract–enabled framework to resolve power imbalance problems in construction payment.

Design/methodology/approach

This research adopts a design science research method to develop the blockchain smart contract–enabled framework. The authors then develop a prototype system. Finally, the authors evaluate its performance in solving power imbalance-induced payment problems.

Findings

The results show that the prototype system can resolve power imbalance problems in construction payment by allowing project participants to make transparent and decentralized decisions that are self-enforceable by blockchain smart contracts.

Research limitations/implications

This study provides theoretical explanations for how blockchain smart contracts can resolve power imbalances in construction payment; based on that, it proposes a novel blockchain smart contract–enabled method to rebalance the power of stakeholders in construction payment. Thus, it contributes to the body of knowledge on blockchain technology and construction payment.

Practical implications

This study moves beyond a conceptual framework and develops a practical blockchain smart contract system for resolving power imbalances in construction payment, strengthening construction project members' confidence in using blockchain technology.

Social implications

The proposed blockchain smart contract–enabled solution helps mitigate negative social impacts associated with late payment and non-payment. Furthermore, the research maximizes trust among participants in payment processes to inspire collaborative culture in the construction industry.

Originality/value

This paper introduces a novel blockchain smart contract integrated method, allowing project stakeholders to resolve power imbalance problems in construction payment through decentralized decision-making.
Improving the analysis of the judiciary performance - the use of data mining techniques to assess the timeliness of civil trials
Authors: Pernici Barbara , Bono Carlo Alberto , Piro Ludovica , Del Treste Mattia , Vecchi Giancarlo
Published: November 2023

Purpose

The purpose of this paper is to show how data mining techniques can improve the performance management of the judiciary, helping judges in steering position with specific and timely measures. It explores different approaches to analyse the length of trials, based on the case of an Italian judicial office.

Design/methodology/approach

The paper presents a temporal analysis to compare the timeliness of trials, using data and process mining approaches with the support of a specific software to represent graphically the results. Data were gathered directly from the office data base, improving precision and the opportunity to monitor specific phases of the trials.

Findings

The results highlight the progress that can be reached using data mining approaches to develop performance analyses helping courts to correct inefficiencies and to manage the personnel distribution, overcoming the critical comments arisen against traditional KPI (Raine, 2000). The work proposes a methodology to analyse cases deriving from different juridical matters useful to set up a performance monitoring system that could be diffused to different courts.

Research limitations/implications

The limitations of the research regard the analysis of a selected, limited number of cases in terms of judicial matters.

Practical implications

Data mining techniques can improve the performance management processes in providing more accurate feedback to the judicial offices leaders and increasing the organisational learning.

Social implications

The performance of the judiciary is one of the relevant issues that emerged in the recent decade in the field of public sector reforms. Several reasons explain this interest, which has gone beyond the specific legal disciplines to involve public policy, management, economics and ICT studies.

Originality/value

Considering the literature on the judiciary (Visser et al., 2019; Di Martino et al., 2021; Troisi and Alfano, 2023) the contribution differs as both the methodological approach and the predictive analysis considers the intrinsic differences that define cases belonging to different juridical matters performing a cross-sectional analysis, with a specific focus of process variants.