Cyclin-dependent kinase 4 drives cystic kidney disease in the absence of mTORC1 signaling activity.

Progression of cystic kidney disease has been linked to activation of the mTORC1 signaling pathway. Yet the utility of mTORC1 inhibitors to treat patients with polycystic kidney disease remains controversial despite promising preclinical data. To define the cell intrinsic role of mTORC1 for cyst development, the mTORC1 subunit gene Raptor was selectively inactivated in kidney tubular cells lacking cilia due to simultaneous deletion of the kinesin family member gene Kif3A. In contrast to a rapid onset of cyst formation and kidney failure in mice with defective ciliogenesis, both kidney function, cyst formation discerned by magnetic resonance imaging and overall survival were strikingly improved in mice additionally lacking Raptor. However, these mice eventually succumbed to cystic kidney disease despite mTORC1 inactivation. In-depth transcriptome analysis revealed the rapid activation of other growth-promoting signaling pathways, overriding the effects of mTORC1 deletion and identified cyclin-dependent kinase (CDK) 4 as an alternate driver of cyst growth. Additional inhibition of CDK4-dependent signaling by the CDK4/6 inhibitor Palbociclib markedly slowed disease progression in mice and human organoid models of polycystic kidney disease and potentiated the effects of mTORC1 deletion/inhibition. Our findings indicate that cystic kidneys rapidly adopt bypass mechanisms typically observed in drug resistant cancers. Thus, future clinical trials need to consider combinatorial or sequential therapies to improve therapeutic efficacy in patients with cystic kidney disease.

A deep learning approach to case prioritisation of colorectal biopsies.

AIMS: To create and validate a weakly supervised artificial intelligence (AI) model for detection of abnormal colorectal histology, including dysplasia and cancer, and prioritise biopsies according to clinical significance (severity of diagnosis). MATERIALS AND METHODS: Triagnexia Colorectal, a weakly supervised deep learning model, was developed for the classification of colorectal samples from haematoxylin and eosin (H&E)-stained whole slide images. The model was trained on 24 983 digitised images and assessed by multiple pathologists in a simulated digital pathology environment. The AI application was implemented as part of a point and click graphical user interface to streamline decision-making. Pathologists assessed the accuracy of the AI tool, its value, ease of use and integration into the digital pathology workflow. RESULTS: Validation of the model was conducted on two cohorts: the first, on 100 single-slide cases, achieved micro-average model specificity of 0.984, micro-average model sensitivity of 0.949 and micro-average model F1 score of 0.949 across all classes. A secondary multi-institutional validation cohort, of 101 single-slide cases, achieved micro-average model specificity of 0.978, micro-average model sensitivity of 0.931 and micro-average model F1 score of 0.931 across all classes. Pathologists reflected their positive impressions on the overall accuracy of the AI in detecting colorectal pathology abnormalities. CONCLUSIONS: We have developed a high-performing colorectal biopsy AI triage model that can be integrated into a routine digital pathology workflow to assist pathologists in prioritising cases and identifying cases with dysplasia/cancer versus non-neoplastic biopsies.

Molecular characterization of chronic cutaneous wounds reveals subregion- and wound type-specific differential gene expression.

A limited understanding of the pathology underlying chronic wounds has hindered the development of effective diagnostic markers and pharmaceutical interventions. This study aimed to elucidate the molecular composition of various common chronic ulcer types to facilitate drug discovery strategies. We conducted a comprehensive analysis of leg ulcers (LUs), encompassing venous and arterial ulcers, foot ulcers (FUs), pressure ulcers (PUs), and compared them with surgical wound healing complications (WHCs). To explore the pathophysiological mechanisms and identify similarities or differences within wounds, we dissected wounds into distinct subregions, including the wound bed, border, and peri-wound areas, and compared them against intact skin. By correlating histopathology, RNA sequencing (RNA-Seq), and immunohistochemistry (IHC), we identified unique genes, pathways, and cell type abundance patterns in each wound type and subregion. These correlations aim to aid clinicians in selecting targeted treatment options and informing the design of future preclinical and clinical studies in wound healing. Notably, specific genes, such as PITX1 and UPP1, exhibited exclusive upregulation in LUs and FUs, potentially offering significant benefits to specialists in limb preservation and clinical treatment decisions. In contrast, comparisons between different wound subregions, regardless of wound type, revealed distinct expression profiles. The pleiotropic chemokine-like ligand GPR15L (C10orf99) and transmembrane serine proteases TMPRSS11A/D were significantly upregulated in wound border subregions. Interestingly, WHCs exhibited a nearly identical transcriptome to PUs, indicating clinical relevance. Histological examination revealed blood vessel occlusions with impaired angiogenesis in chronic wounds, alongside elevated expression of genes and immunoreactive markers related to blood vessel and lymphatic epithelial cells in wound bed subregions. Additionally, inflammatory and epithelial markers indicated heightened inflammatory responses in wound bed and border subregions and reduced wound bed epithelialization. In summary, chronic wounds from diverse anatomical sites share common aspects of wound pathophysiology but also exhibit distinct molecular differences. These unique molecular characteristics present promising opportunities for drug discovery and treatment, particularly for patients suffering from chronic wounds. The identified diagnostic markers hold the potential to enhance preclinical and clinical trials in the field of wound healing.

Impact of deprivation on glycaemic control in youth with type 1 diabetes in the southwestern region of France.

OBJECTIVES: The objective of this multicenter cross-sectional study was to determine predictors of poor glycaemic control in children with type 1 diabetes mellitus (T1DM), particularly with respect to socioeconomic status (SES). METHODS: Our study population consisted of 1154 children who attended T1DM follow-up consultation with a pediatric diabetes specialist. Clinical and demographic data were retrieved retrospectively from patients' records. Individual deprivation was defined by an EPICES (Evaluation of the Deprivation and Inequalities of Health in Healthcare Centers) score ≥ 30. Patients were assigned to quintiles of the European Deprivation Index (EDI) based on their area deprivation scores. We used multivariable linear regression models to detect potential associations between glycaemic control and indicators of low SES. RESULTS: In total, 33% (n = 376) of patients had an EPICES score ≥ 30 and 23% (n = 268) were in the 5th EDI quintile. Multivariable linear regression analysis showed that poor glycaemic control was associated with both individual (ß 0.38; 95%CI 0.26-0.5; p < 0.001) and area deprivation (ß 0.26; 95%CI 0.08-0.43; p = 0.004). Demographic factors, body mass index (BMI) and insulin regimen were also independently associated with poor glycaemic control (p < 0.001). Interestingly, access to diabetes technologies was not related to SES or either glycaemic control. CONCLUSION: Low SES is associated with a higher risk of poor glycaemic control, independently of insulin regimen. BMI, age at the time of consultation, duration of diabetes, and insulin regimen. Also have an impact on HbA1c. These parameters need to be considered when developing novel treatment strategies for children with T1DM to better target at-risk patients.

IMI-Bigpicture: A Central Repository for Digital Pathology.

To address the challenges posed by large-scale development, validation, and adoption of artificial intelligence (AI) in pathology, we have constituted a consortium of academics, small enterprises, and pharmaceutical companies and proposed the BIGPICTURE project to the Innovative Medicines Initiative. Our vision is to become the catalyst in the digital transformation of pathology by creating the first European, ethically compliant, and quality-controlled whole slide imaging platform, in which both large-scale data and AI algorithms will exist. Our mission is to develop this platform in a sustainable and inclusive way, by connecting the community of pathologists, researchers, AI developers, patients, and industry parties based on creating value and reciprocity in use based on a community model as the mechanism for ensuring sustainability of the platform.

Biomarker-Based Classification and Localization of Renal Lesions Using Learned Representations of Histology-A Machine Learning Approach to Histopathology.

Several deep learning approaches have been proposed to address the challenges in computational pathology by learning structural details in an unbiased way. Transfer learning allows starting from a learned representation of a pretrained model to be directly used or fine-tuned for a new domain. However, in histopathology, the problem domain is tissue-specific and putting together a labelled data set is challenging. On the other hand, whole slide-level annotations, such as biomarker levels, are much easier to obtain. We compare two pretrained models, one histology-specific and one from ImageNet on various computational pathology tasks. We show that a domain-specific model (HistoNet) contains richer information for biomarker classification, localization of biomarker-relevant morphology within a slide, and the prediction of expert-graded features. We use a weakly supervised approach to discriminate slides based on biomarker level and simultaneously predict which regions contribute to that prediction. We employ multitask learning to show that learned representations correlate with morphological features graded by expert pathologists. All of these results are demonstrated in the context of renal toxicity in a mechanistic study of compound toxicity in rat models. Our results emphasize the importance of histology-specific models and their knowledge representations for solving a wide range of computational pathology tasks.

HistoNet: A Deep Learning-Based Model of Normal Histology.

We introduce HistoNet, a deep neural network trained on normal tissue. On 1690 slides with rat tissue samples from 6 preclinical toxicology studies, tissue regions were outlined and annotated by pathologists into 46 different tissue classes. From these annotated regions, we sampled small 224 × 224 pixels images (patches) at 6 different levels of magnification. Using 4 studies as training set and 2 studies as test set, we trained VGG-16, ResNet-50, and Inception-v3 networks separately at each magnification level. Among these model architectures, Inception-v3 and ResNet-50 outperformed VGG-16. Inception-v3 identified the tissue from query images, with an accuracy up to 83.4%. Most misclassifications occurred between histologically similar tissues. Investigation of the features learned by the model (embedding layer) using Uniform Manifold Approximation and Projection revealed not only coherent clusters associated with the individual tissues but also subclusters corresponding to histologically meaningful structures that had not been annotated or trained for. This suggests that the histological representation learned by HistoNet could be useful as the basis of other machine learning algorithms and data mining. Finally, we found that models trained on rat tissues can be used on non-human primate and minipig tissues with minimal retraining.

The Application, Challenges, and Advancement Toward Regulatory Acceptance of Digital Toxicologic Pathology: Results of the 7th ESTP International Expert Workshop (September 20-21, 2019).

With advancements in whole slide imaging technology and improved understanding of the features of pathologist workstations required for digital slide evaluation, many institutions are investigating broad digital pathology adoption. The benefits of digital pathology evaluation include remote access to study or diagnostic case materials and integration of analysis and reporting tools. Diagnosis based on whole slide images is established in human medical pathology, and the use of digital pathology in toxicologic pathology is increasing. However, there has not been broad adoption in toxicologic pathology, particularly in the context of regulatory studies, due to lack of precedence. To address this topic, as well as practical aspects, the European Society of Toxicologic Pathology coordinated an expert international workshop to assess current applications and challenges and outline a set of minimal requirements needed to gain future regulatory acceptance for the use of digital toxicologic pathology workflows in research and development, so that toxicologic pathologists can benefit from digital slide technology.

Resistance mechanisms to TP53-MDM2 inhibition identified by in vivo piggyBac transposon mutagenesis screen in an Arf-/- mouse model.

Inhibitors of double minute 2 protein (MDM2)-tumor protein 53 (TP53) interaction are predicted to be effective in tumors in which the TP53 gene is wild type, by preventing TP53 protein degradation. One such setting is represented by the frequent CDKN2A deletion in human cancer that, through inactivation of p14ARF, activates MDM2 protein, which in turn degrades TP53 tumor suppressor. Here we used piggyBac (PB) transposon insertional mutagenesis to anticipate resistance mechanisms occurring during treatment with the MDM2-TP53 inhibitor HDM201. Constitutive PB mutagenesis in Arf-/- mice provided a collection of spontaneous tumors with characterized insertional genetic landscapes. Tumors were allografted in large cohorts of mice to assess the pharmacologic effects of HDM201. Sixteen out of 21 allograft models were sensitive to HDM201 but ultimately relapsed under treatment. A comparison of tumors with acquired resistance to HDM201 and untreated tumors identified 87 genes that were differentially and significantly targeted by the PB transposon. Resistant tumors displayed a complex clonality pattern suggesting the emergence of several resistant subclones. Among the most frequent alterations conferring resistance, we observed somatic and insertional loss-of-function mutations in transformation-related protein 53 (Trp53) in 54% of tumors and transposon-mediated gain-of-function alterations in B-cell lymphoma-extra large (Bcl-xL), Mdm4, and two TP53 family members, resulting in expression of the TP53 dominant negative truncations ΔNTrp63 and ΔNTrp73. Enhanced BCL-xL and MDM4 protein expression was confirmed in resistant tumors, as well as in HDM201-resistant patient-derived tumor xenografts. Interestingly, concomitant inhibition of MDM2 and BCL-xL demonstrated significant synergy in p53 wild-type cell lines in vitro. Collectively, our findings identify several potential mechanisms by which TP53 wild-type tumors may escape MDM2-targeted therapy.

Lean body weight is the best scale for venous thromboprophylaxis algorithm in severely obese patients undergoing bariatric surgery.

Severely obese patients undergoing bariatric surgery (BS) are at increased risk for venous thromboembolism (VTE). How standard low molecular weight heparin (LMWH) regimen should be adapted to provide both sufficient efficacy and safety in this setting is unclear. We aimed to compare the influence of four body size descriptors (BSD) on peak anti-Xa levels in BS obese patients receiving LMWH fixed doses to identify which one had the greatest impact. One hundred and thirteen BS obese patients [median body mass index (BMI), 43.3 kg/m2 (IQR, 40.6-48.7 kg/m2)] receiving subcutaneous dalteparin 5000 IU twice daily were included in this prospective monocenter study. Peak steady-state anti-Xa levels were measured peri-operatively following thromboprophylaxis initiation. Only 48% of patients achieved target anti-Xa levels (0.2-0.5 IU/ml). In univariate analysis, age, gender, total body-weight (TBW), lean body-weight (LBW), ideal body-weight (IBW), BMI and estimated glomerural filtration rate (eGFR) were associated with anti-Xa levels. The strongest negative association was observed with LBW (r = -0.56, p < .0001). Receiver operating characteristic curves indicated that among BSD, LBW (cut-off >55.8 kg) had the highest sensitivity (73%) and specificity (69%) to predict sub-prophylactic anti-Xa levels. In multivariate analysis, LBW and eGFR remained associated with anti-Xa levels (ß = -0.47 ±â€¯0.08, p < .0001 and ß = -0.19 ±â€¯0.08; p = .02, respectively). In BS morbidly obese patients receiving LMWH for thromboprophylaxis after BS, LBW and eGFR are the main determinants of anti-Xa level, and could be proposed in LMWH-based thromboprophylaxis dosing algorithms. The efficacy of a LBW-scale based dosing algorithm for optimal VTE prevention deserves further prospective randomized trials.

mTORC1 maintains renal tubular homeostasis and is essential in response to ischemic stress.

Mammalian target of rapamycin complex 1 (mTORC1) is a key regulator of cell metabolism and autophagy. Despite widespread clinical use of mTORC1 inhibitors, the role of mTORC1 in renal tubular function and kidney homeostasis remains elusive. By using constitutive and inducible deletion of conditional Raptor alleles in renal tubular epithelial cells, we discovered that mTORC1 deficiency caused a marked concentrating defect, loss of tubular cells, and slowly progressive renal fibrosis. Transcriptional profiling revealed that mTORC1 maintains renal tubular homeostasis by controlling mitochondrial metabolism and biogenesis as well as transcellular transport processes involved in countercurrent multiplication and urine concentration. Although mTORC2 partially compensated for the loss of mTORC1, exposure to ischemia and reperfusion injury exaggerated the tubular damage in mTORC1-deficient mice and caused pronounced apoptosis, diminished proliferation rates, and delayed recovery. These findings identify mTORC1 as an important regulator of tubular energy metabolism and as a crucial component of ischemic stress responses.

Reduced Activity of Sphingosine-1-Phosphate Lyase Induces Podocyte-related Glomerular Proteinuria, Skin Irritation, and Platelet Activation.

Sphingosine-1-phosphate (S1P) lyase is considered as a drug target in autoimmune diseases based on the protective effect of reducing activity of the enzyme in animal models of inflammation. Since S1P lyase deficiency in mice causes a severe, lethal phenotype, it was of interest to investigate any pathological alterations associated with only partially reduced activity of S1P lyase as may be encountered upon pharmacological inhibition. Both genetic reduction of S1P lyase activity in mice and inhibition of S1P lyase with a low-molecular-weight compound in rats consistently resulted in podocyte-based kidney toxicity, which is the most severe finding. In addition, skin irritation and platelet activation were observed in both instances. The similarity of the findings in both the genetic model and the pharmacological study supports the value of analyzing inducible partially target-deficient mice for safety assessment. If the findings described in rodents translate to humans, target-related toxicity, particularly podocyte dysfunction, may limit chronic systemic treatment of autoimmune diseases with S1P lyase inhibitors. Furthermore, partial deficiency or inhibition of S1P lyase appears to provide an in vivo rodent model to enable studies on the mechanism of podocyte dysfunction.

Vascular origin of vildagliptin-induced skin effects in Cynomolgus monkeys: pathomechanistic role of peripheral sympathetic system and neuropeptide Y.

The purpose of this article is to characterize skin lesions in cynomolgus monkeys following vildagliptin (dipeptidyl peptidase-4 inhibitor) treatment. Oral vildagliptin administration caused dose-dependent and reversible blister formation, peeling and flaking skin, erosions, ulcerations, scabs, and sores involving the extremities at ≥5 mg/kg/day and necrosis of the tail and the pinnae at ≥80 mg/kg/day after 3 weeks of treatment. At the affected sites, the media and the endothelium of dermal arterioles showed hypertrophy/hyperplasia. Skin lesion formation was prevented by elevating ambient temperature. Vildagliptin treatment also produced an increase in blood pressure and heart rate likely via increased sympathetic tone. Following treatment with vildagliptin at 80 mg/kg/day, the recovery time after lowering the temperature in the feet of monkeys and inducing cold stress was prolonged. Ex vivo investigations showed that small digital arteries from skin biopsies of vildagliptin-treated monkeys exhibited an increase in neuropeptide Y-induced vasoconstriction. This finding correlated with a specific increase in NPY and in NPY1 receptors observed in the skin of vildagliptin-treated monkeys. Present data provide evidence that skin effects in monkeys are of vascular origin and that the effects on the NPY system in combination with increased peripheral sympathetic tone play an important pathomechanistic role in the pathogenesis of cutaneous toxicity.

Patients' characteristics and healthcare providers' perceived workload in French hospital emergency wards.

The aim of this research is to understand how patients' characteristics increase healthcare providers' perceived workload. Patients' characteristics and dependency, technical and relational complexities of care seem to increase healthcare providers' workload. As workload is multidimensional, we examine which dimensions are affected by patients' characteristics. Our methodology is based on 121 patients assessed with the NASA task load index (NASA-TLX) and a questionnaire filled in by 57 health providers in 2 emergency wards in French hospital settings, to evaluate their attitudes to different patients' characteristics. Our results show that physical demand is the dimension most affected by patients' behaviour and characteristics. Next, we observe that workload increases more due to patients' behaviour than their social characteristics. We propose that a regulation mechanism be taken into account in further research, using methodology based on observations to identify how healthcare providers might adapt their activities to compensate for workload variations caused by patients.

The transcription factor ZNF469 regulates collagen production in liver fibrosis.

Non-alcoholic fatty liver disease (NAFLD) - characterized by excess accumulation of fat in the liver - now affects one third of the world's population. As NAFLD progresses, extracellular matrix components including collagen accumulate in the liver causing tissue fibrosis, a major determinant of disease severity and mortality. To identify transcriptional regulators of fibrosis, we computationally inferred the activity of transcription factors (TFs) relevant to fibrosis by profiling the matched transcriptomes and epigenomes of 108 human liver biopsies from a deeply-characterized cohort of patients spanning the full histopathologic spectrum of NAFLD. CRISPR-based genetic knockout of the top 100 TFs identified ZNF469 as a regulator of collagen expression in primary human hepatic stellate cells (HSCs). Gain- and loss-of-function studies established that ZNF469 regulates collagen genes and genes involved in matrix homeostasis through direct binding to gene bodies and regulatory elements. By integrating multiomic large-scale profiling of human biopsies with extensive experimental validation we demonstrate that ZNF469 is a transcriptional regulator of collagen in HSCs. Overall, these data nominate ZNF469 as a previously unrecognized determinant of NAFLD-associated liver fibrosis.

Plant-herbivore interactions: Experimental demonstration of genetic variability in plant-plant signalling.

Plant-herbivore interactions mediated by plant-plant signalling have been documented in different species but its within-species variability has hardly been quantified. Here, we tested if herbivore foraging activity on plants was influenced by a prior contact with a damaged plant and if the effect of such plant-plant signalling was variable across 113 natural genotypes of Arabidopsis thaliana. We filmed the activity of the generalist herbivore Cornu aspersum during 1 h on two plants differing only in a prior contact with a damaged plant or not. We recorded each snails' first choice, and measured its first duration on a plant, the proportion of time spent on both plants and leaf consumption. Overall, plant-plant signalling modified the foraging activity of herbivores in A. thaliana. On average, snails spent more time and consumed more of plants that experienced a prior contact with a damaged plant. However, the effects of plant-plant signalling on snail behaviour was variable: depending on genotype identity, plant-plant signalling made undamaged plants more repellant or attractive to snails. Genome-wide associations revealed that genes related to stress coping ability and jasmonate pathway were associated to this variation. Together, our findings highlight the adaptive significance of plant-plant signalling for plant-herbivore interactions.

Legalised active assistance in dying: palliative care stakeholders' national e-consultation.

OBJECTIVES: There is a growing debate surrounding the legalisation of medical assistance in dying (MAID). MAID is currently prohibited by the French law; however, the debate has recently been reinvigorated in France. This study aims to collect opinions of palliative care stakeholders (PCS) regarding the legalisation of MAID and to identify the factors associated with their opinions. METHODS: We performed a transversal survey between 26 June 2021 and 25 July 2021, on PCS who were on the French national scientific society for palliative care. Participants were invited by email. RESULTS: 1439 PCS took part and expressed an opinion about the legalisation of MAID. 1053 (69.7%) were against the legalisation of MAID. When forced to choose which option should be privileged if the law had to change, 3.7% favoured euthanasia, 10.1% favoured assisted suicide with provision of lethal drug by a professional, 27.5% favoured assisted suicide with prescription of a lethal drug and 29.5% favoured assisted suicide with provision of a lethal drug by an association. The opinion regarding legalisation of MAID was statistically different depending on the participant profession (p<0.001) and when comparing clinical and non-clinical positions (p<0.001). A quarter of participants (26.7%) believe that legalising MAID might lead them to change their current position. CONCLUSIONS: Overall, French palliative care professionals are against a modification of the current legal framework for legalising MAID but some might change their current position if a law was voted. This might destabilise the PCS demography that is already worrying.

AraDiv: a dataset of functional traits and leaf hyperspectral reflectance of Arabidopsis thaliana.

Data from functional trait databases have been increasingly used to address questions related to plant diversity and trait-environment relationships. However, such databases provide intraspecific data that combine individual records obtained from distinct populations at different sites and, hence, environmental conditions. This prevents distinguishing sources of variation (e.g., genetic-based variation vs. phenotypic plasticity), a necessary condition to test for adaptive processes and other determinants of plant phenotypic diversity. Consequently, individual traits measured under common growing conditions and encompassing within-species variation across the occupied geographic range have the potential to leverage trait databases with valuable data for functional and evolutionary ecology. Here, we recorded 16 functional traits and leaf hyperspectral reflectance (NIRS) data for 721 widely distributed Arabidopsis thaliana natural accessions grown in a common garden experiment. These data records, together with meteorological variables obtained during the experiment, were assembled to create the AraDiv dataset. AraDiv is a comprehensive dataset of A. thaliana's intraspecific variability that can be explored to address questions at the interface of genetics and ecology.

Investigation of correlation among safety biomarkers in serum, histopathological examination, and toxicogenomics.

This article addresses the issue of miscorrelation between hepatic injury biomarkers and histopathological findings in the drug development context. Our studies indicate that the use of toxicogenomics can aid in the drug development decision-making process associated with such miscorrelated data. BLZ945 was developed as a Colony-Stimulating Factor 1 Receptor (CSF-1R) inhibitor. Treatment of BLZ945 in rats and monkeys increased serum alanine aminotransferase (ALT) and aspartate transaminase (AST). However, liver hypertrophy was the only histopathological liver finding in rats, and there was no change in the livers of monkeys. Longer treatment of BLZ945 in rats for 6 weeks caused up to 6-fold elevation of ALT, yet hepatocyte necrosis was not detected microscopically. Toxicogenomic profiling of liver samples demonstrated that the genes associated with early response to liver injury, apoptosis/necrosis, inflammation, oxidative stress, and metabolic enzymes were upregulated. Studies are ongoing to evaluate the mechanisms underlying BL945-induced ALT and AST elevations.