DARPP-32, Jack of All Trades… Master of Which?

DARPP-32 (PPP1R1B) was discovered as a substrate of cAMP-dependent protein kinase (PKA) enriched in dopamine-innervated brain areas. It is one of three related, PKA-regulated inhibitors of protein phosphatase-1 (PP1). These inhibitors seem to have appeared in early vertebrate ancestors, possibly Gnathostomes. DARPP-32 has additional important biochemical properties including inhibition of PKA when phosphorylated by Cdk5 and regulation by casein kinases 1 and 2. It is highly enriched in specific neuronal populations, especially striatal medium-size spiny neurons. As PP1 inhibitor DARPP-32 amplifies and/or mediates many actions of PKA at the plasma membrane and in the cytoplasm, with a broad spectrum of potential targets and functions. DARPP-32 also undergoes a continuous and tightly regulated cytonuclear shuttling. This trafficking is controlled by phosphorylation of Ser-97, which is necessary for nuclear export. When phosphorylated on Thr-34 and dephosphorylated on Ser-97, DARPP-32 can inhibit PP1 in the nucleus and modulate signaling pathways involved in the regulation of chromatin response. Recent work with multiple transgenic and knockout mutant mice has allowed the dissection of DARPP-32 function in striato-nigral and striato-pallidal neurons. It is implicated in the action of therapeutic and abused psychoactive drugs, in prefrontal cortex function, and in sexual behavior. However, the contribution of DARPP-32 in human behavior remains poorly understood. Post-mortem studies in humans suggest possible alterations of DARPP-32 levels in schizophrenia and bipolar disorder. Genetic studies have revealed a polymorphism with possible association with psychological and psychopathological traits. In addition, a short isoform of DARPP-32, t-DARPP, plays a role in cancer, indicating additional signaling properties. Thus, DARPP-32 is a non-essential but tightly regulated signaling hub molecule which may improve the general performance of the neuronal circuits in which it is expressed

DynaDom: structure-based prediction of T cell receptor inter-domain and T cell receptor-peptide-MHC (class I) association angles

Table S3. Per residue flip states using Reduce, Protoss and DynaDom comparing single domains and TCR complexes. (PDF 145 kb

Transcriptional Regulation of the Intestinal Cancer Stem Cell Phenotype

Colorectal cancer (CRC) is one of the most frequent cancers worldwide. Current treatments include surgery and chemotherapy, but disease recurrence occurs frequently. The continuous renewal of intestinal epithelium relies on the presence of intestinal stem cells that are also at the origin of CRC and contribute to therapy resistance and metastatic dissemination. Several nuclear signaling pathways and transcription factors regulate both intestinal cell homeostasis and tumorigenesis. However, the transcriptional events that govern the emergence of aggressive therapy-resistant cancer stem cells are still poorly defined. This review summarizes the relevance of transcription factors in intestinal stem cell biology and their involvement in colon cancer development and drug resistance

BetaSAC: A New Conditional Sampling For RANSAC

International audienceWe present a new strategy for RANSAC sampling named BetaSAC, in reference to the beta distribution. Our proposed sampler builds a hypothesis set incrementally, select- ing data points conditional on the previous data selected for the set. Such a sampling is shown to provide more suitable samples in terms of inlier ratio but also of consistency and potential to lead to an accurate parameters estimation. The algorithm is presented as a general framework, easily implemented and able to exploit any kind of prior infor- mation on the potential of a sample. As with PROSAC, BetaSAC converges towards RANSAC in the worst case. The benefits of the method are demonstrated on the homog- raphy estimation problem

Preserved subliminal processing and impaired conscious access in schizophrenia.

BACKGROUND: Studies of visual backward masking have frequently revealed an elevated masking threshold in schizophrenia. This finding has frequently been interpreted as indicating a low-level visual deficit. However, more recent models suggest that masking may also involve late and higher-level integrative processes, while leaving intact early bottom-up visual processing. OBJECTIVE: To test the hypothesis that the backward-masking deficit in schizophrenia corresponds to a deficit in the late stages of conscious perception, whereas the subliminal processing of masked stimuli is fully preserved. DESIGN: Twenty-eight patients with schizophrenia and 28 normal control subjects performed 2 backward-masking experiments. We used Arabic digits as stimuli and varied quasi-continuously the interval with a subsequent mask, thus allowing us to progressively unmask the stimuli. We finely quantified their degree of visibility using objective and subjective measures to evaluate the threshold duration for access to consciousness. We also studied the priming effect caused by the variably masked numbers in a comparison task performed on a subsequently presented and highly visible target number. RESULTS: The threshold delay between the digit and mask necessary for the conscious perception of the masked stimulus was longer in patients compared with controls. This higher consciousness threshold in patients was confirmed by an objective and a subjective measure, and both measures were highly correlated for the patients and controls. However, subliminal priming of masked numbers was effective and identical in patients and controls. CONCLUSIONS: Access to conscious report of masked stimuli is impaired in schizophrenia, whereas fast bottom-up processing of the same stimuli, as assessed by subliminal priming, is preserved. These findings suggest a high-level origin of the masking deficit in schizophrenia, although they leave open for further research its exact relation to previously identified bottom-up visual processing abnormalities

Development of a dynamic riparian vegetation model in TELEMAC-2D

Water Qualit

Can we Agree? On the Rash\=omon Effect and the Reliability of Post-Hoc Explainable AI

The Rash\=omon effect poses challenges for deriving reliable knowledge from machine learning models. This study examined the influence of sample size on explanations from models in a Rash\=omon set using SHAP. Experiments on 5 public datasets showed that explanations gradually converged as the sample size increased. Explanations from <128 samples exhibited high variability, limiting reliable knowledge extraction. However, agreement between models improved with more data, allowing for consensus. Bagging ensembles often had higher agreement. The results provide guidance on sufficient data to trust explanations. Variability at low samples suggests that conclusions may be unreliable without validation. Further work is needed with more model types, data domains, and explanation methods. Testing convergence in neural networks and with model-specific explanation methods would be impactful. The approaches explored here point towards principled techniques for eliciting knowledge from ambiguous models.Comment: 13 pages, 6 figures and 6 table