Unconventional machine learning of genome-wide human cancer data

Recent advances in high-throughput genomic technologies coupled with exponential increases in computer processing and memory have allowed us to interrogate the complex aberrant molecular underpinnings of human disease from a genome-wide perspective. While the deluge of genomic information is expected to increase, a bottleneck in conventional high-performance computing is rapidly approaching. Inspired in part by recent advances in physical quantum processors, we evaluated several unconventional machine learning (ML) strategies on actual human tumor data. Here we show for the first time the efficacy of multiple annealing-based ML algorithms for classification of high-dimensional, multi-omics human cancer data from the Cancer Genome Atlas. To assess algorithm performance, we compared these classifiers to a variety of standard ML methods. Our results indicate the feasibility of using annealing-based ML to provide competitive classification of human cancer types and associated molecular subtypes and superior performance with smaller training datasets, thus providing compelling empirical evidence for the potential future application of unconventional computing architectures in the biomedical sciences

FisHook -- An Optimized Approach to Marine Specie Classification using MobileNetV2

Marine ecosystems are vital for the planet's health, but human activities such as climate change, pollution, and overfishing pose a constant threat to marine species. Accurate classification and monitoring of these species can aid in understanding their distribution, population dynamics, and the impact of human activities on them. However, classifying marine species can be challenging due to their vast diversity and the complex underwater environment. With advancements in computer performance and GPU-based computing, deep-learning algorithms can now efficiently classify marine species, making it easier to monitor and manage marine ecosystems. In this paper, we propose an optimization to the MobileNetV2 model to achieve a 99.83% average validation accuracy by highlighting specific guidelines for creating a dataset and augmenting marine species images. This transfer learning algorithm can be deployed successfully on a mobile application for on-site classification at fisheries

Light acts as a stressor and influences abiotic and biotic stress responses in plants

Light is important for plants as an energy source and a developmental signal, but it can also cause stress to plants and modulates responses to stress. Excess and fluctuating light result in photoinhibition and reactive oxygen species (ROS) accumulation around photosystems II and I, respectively. Ultraviolet light causes photodamage to DNA and a prolongation of the light period initiates the photoperiod stress syndrome. Changes in light quality and quantity, as well as in light duration are also key factors impacting the outcome of diverse abiotic and biotic stresses. Short day or shady environments enhance thermotolerance and increase cold acclimation. Similarly, shade conditions improve drought stress tolerance in plants. Additionally, the light environment affects the plants' responses to biotic intruders, such as pathogens or insect herbivores, often reducing growth‐defence trade‐offs. Understanding how plants use light information to modulate stress responses will support breeding strategies to enhance crop stress resilience. This review summarizes the effect of light as a stressor and the impact of the light environment on abiotic and biotic stress responses. There is a special focus on the role of the different light receptors and the crosstalk between light signalling and stress response pathways

The heterodimeric structure of heterogeneous nuclear ribonucleoprotein C1/C2 dictates 1,25-dihydroxyvitamin D-directed transcriptional events in osteoblasts

Heterogeneous nuclear ribonucleoprotein (hnRNP) C plays a key role in RNA processing but also exerts a dominant negative effect on responses to 1,25-dihydroxyvitamin D (1,25(OH)(2)D) by functioning as a vitamin D response element-binding protein (VDRE-BP). hnRNPC acts a tetramer of hnRNPC1 (huC1) and hnRNPC2 (huC2), and organization of these subunits is critical to in vivo nucleic acid-binding. Overexpression of either huC1 or huC2 in human osteoblasts is sufficient to confer VDRE-BP suppression of 1,25(OH)(2)D-mediated transcription. However, huC1 or huC2 alone did not suppress 1,25(OH)(2)D-induced transcription in mouse osteoblastic cells. By contrast, overexpression of huC1 and huC2 in combination or transfection with a bone-specific polycistronic vector using a “self-cleaving” 2A peptide to co-express huC1/C2 suppressed 1,25D-mediated induction of osteoblast target gene expression. Structural diversity of hnRNPC between human/NWPs and mouse/rat/rabbit/dog was investigated by analysis of sequence variations within the hnRNP CLZ domain. The predicted loss of distal helical function in hnRNPC from lower species provides an explanation for the altered interaction between huC1/C2 and their mouse counterparts. These data provide new evidence of a role for hnRNPC1/C2 in 1,25(OH)(2)D-driven gene expression, and further suggest that species-specific tetramerization is a crucial determinant of its actions as a regulator of VDR-directed transactivation

Sodium hypochlorite concentration and post-endodontic pain - unveiling the optimal balance: a systematic review and meta-analysis

Introduction This study systematically reviewed literature regarding the effect of different concentrations of sodium hypochlorite (NaOCl) used during root canal treatment (RCT) on post-endodontic pain (PEP) and rescue analgesia. Methods Following registration with PROSPERO (CRD42023388916), a search was conducted using PubMed, Scopus, Web of Science, and Embase databases. Randomized controlled trials (RaCTs) of patients receiving RCT which assessed PEP at different time intervals were included. Following data extraction and Cochrane risk of bias assessment 2, meta-analyses were performed to evaluate PEP during the first 48h along with rescue analgesic intake. The certainty of the evidence was evaluated using the Grading of Recommendations, Assessment, Development and Evaluation approach. Results Five RaCTs with 674 patients were included. One study exhibited a low risk of bias, while four raised some concerns. Patients treated with low concentrations of NaOCl (≤3%) were significantly less likely to report PEP at 24h (OR=2.32; [95%CI, 1.63-3.31]; P<0.05) and 48h (OR=2.49; [95% CI,1.73-3.59]; P<0.05) as compared with high concentrations of NaOCl (≥5%). Furthermore, with low concentrations of NaOCl, significantly lesser moderate-severe PEP was reported at 24h (OR=2.32; [95%CI, 1.47-3.62]; P<0.05) and 48h (OR=2.35; [95%CI, 1.32-4.16]; P<0.05) and lesser analgesia was needed (OR=2.43; [95%CI, 1.48-4.00]; P<0.05). Conclusions While PEP can be influenced by several factors, low certainty evidence suggests that when NaOCl is used as an irrigant during RCT, PEP may be less likely with lower concentrations of NaOCl. Moderate certainty evidence indicates that lesser analgesia may be required with lower concentrations of NaOCl. These results should be cautiously interpreted

Computational reconstitution of spine calcium transients from individual proteins

We have built a stochastic model in the program MCell that simulates Ca^(2+) transients in spines from the principal molecular components believed to control Ca^(2+) entry and exit. Proteins, with their kinetic models, are located within two segments of dendrites containing 88 intact spines, centered in a fully reconstructed 6 × 6 × 5 μm^3 cube of hippocampal neuropil. Protein components include AMPA- and NMDA-type glutamate receptors, L- and R-type voltage-dependent Ca^(2+) channels, Na^+/Ca^(2+) exchangers, plasma membrane Ca^(2+) ATPases, smooth endoplasmic reticulum Ca^(2+) ATPases, immobile Ca2+ buffers, and calbindin. Kinetic models for each protein were taken from published studies of the isolated proteins in vitro. For simulation of electrical stimuli, the time course of voltage changes in the dendritic spine was generated with the desired stimulus in the program NEURON. Voltage-dependent parameters were then continuously re-adjusted during simulations in MCell to reproduce the effects of the stimulus. Nine parameters of the model were optimized within realistic experimental limits by a process that compared results of simulations to published data. We find that simulations in the optimized model reproduce the timing and amplitude of Ca^(2+) transients measured experimentally in intact neurons. Thus, we demonstrate that the characteristics of individual isolated proteins determined in vitro can accurately reproduce the dynamics of experimentally measured Ca^(2+) transients in spines. The model will provide a test bed for exploring the roles of additional proteins that regulate Ca^(2+) influx into spines and for studying the behavior of protein targets in the spine that are regulated by Ca^(2+) influx

Genetic addiction risk severity assessment identifies polymorphic reward genes as antecedents to reward deficiency syndrome (RDS) hypodopaminergia\u27s effect on addictive and non-addictive behaviors in a nuclear family

This case series presents the novel genetic addiction risk score (GARS), which shows a high prevalence of polymorphic risk alleles of reward genes in a nuclear family with multiple reward deficiency syndrome (RDS) behavioral issues expressing a hypodopaminergic antecedent. The family consists of a mother, father, son, and daughter. The mother experienced issues with focus, memory, anger, and amotivational syndrome. The father experienced weight issues and depression. The son experienced heavy drinking, along with some drug abuse and anxiety. The daughter experienced depression, lethargy, brain fog, focus issues, and anxiety, among others. A major clinical outcome of the results presented to the family members helped reduce personal guilt and augment potential hope for future healing. Our laboratory\u27s prior research established that carriers of four or more alleles measured by GARS