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ARID genes encode subunits of SWI/SNF chromatin remodeling complexes and are frequently mutated in human cancers. We investigated the correlation between ARID mutations, molecular features, and clinical outcomes in melanoma patients. Cutaneous melanoma samples (n = 1577) were analyzed by next-generation sequencing. Samples were stratified by pathogenic/likely pathogenic mutation in ARID genes (ARID1A/2/1B/5B). PD-L1 expression was assessed using IHC (SP142; positive (+): ≥ 1%). Tumor mutation burden (TMB)-high was defined as ≥ 10 mutations/Mb. Transcriptomic signatures predictive of response to immune checkpoint inhibitors-interferon gamma and T-cell inflamed score were calculated. Real-world overall survival (OS) information was obtained from insurance claims data, with Kaplan-Meier estimates calculated from time of tissue collection until last date of contact. Mann-Whitney U, Chi-square, and Fisher exact tests were applied where appropriate, with p values adjusted for multiple comparisons. ARID2 mutations were more prevalent in cutaneous melanoma compared to ARID1A (11.0%: n = 451 vs 2.8%: n = 113), with concurrent ARID1A/ARID2 mutation in 1.1% (n = 46) of samples. ARID mutations were associated with a high prevalence of RAS pathway mutations-NF1 (ARID1A, 52.6%; ARID2, 48.5%; ARID1A/2, 63.6%; and ARID-WT, 13.3%; p

Humans increasingly dominate Earth's natural freshwater ecosystems, but biomass production of modified ecosystems is rarely studied. We estimate potential fish total standing stock in USA reservoirs is 3.4 billion (B) kg, and approximate annual secondary production is 4.5 B kg y-1. We also observe varied and non-linear trends in reservoir fish biomass over time, thus previous assertions that reservoir fisheries decline over time are not universal. Reservoirs are globally relevant pools of freshwater fisheries, in part due to their immense limnetic footprint and spatial extent. This study further shows that reservoir ecosystems play major roles in food security and fisheries conservation. We encourage additional effort be expended to effectively manage reservoir environments for the good of humanity, biodiversity, and fish conservation.

Organisms must regulate their behavior flexibly in the face of environmental challenges. Failure can lead to a host of maladaptive behavioral traits associated with a range of neuropsychiatric disorders, including attention deficit hyperactivity disorder, autism, and substance use disorders. This maladaptive dysregulation of behavior is influenced by genetic and environmental factors. For example, environmental enrichment produces beneficial neurobehavioral effects in animal models of such disorders. The present study determined the effects of environmental enrichment on a range of measures related to behavioral regulation using a large cohort of male, outbred heterogeneous stock (HS) rats as subjects. Subjects were reared from late adolescence onwards either in pairs in standard housing with minimal enrichment (n = 200) or in groups of 16 in a highly enriched environment consisting of a large multi-level cage filled with toys, running wheels, and shelters (n = 64). Rats were subjected to a battery of tests, including: (i) locomotor response to novelty, (ii) light reinforcement, (iii) social reinforcement, (iv) reaction time, (v) a patch-depletion foraging test, (vi) Pavlovian conditioned approach, (vii) conditioned reinforcement, and (viii) cocaine conditioned cue preference. Results indicated that rats housed in the enriched environment were able to filter out irrelevant stimuli more effectively and thereby regulate their behavior more efficiently than standard-housing rats. The dramatic impact of environmental enrichment suggests that behavioral studies using standard housing conditions may not generalize to more complex environments that may be more ethologically relevant.

Abstract Two-dimensional (2D) graphene and graphene-related materials (GRMs) show great promise for future electronic devices. GRMs exhibit distinct properties under the influence of the substrate that serves as support through uneven compression/ elongation of GRMs surface atoms. Strain in GRM monolayers is the most common feature that alters the interatomic distances and band structure, providing a new degree of freedom that allows regulation of their electronic properties and introducing the field of straintronics. Having an all-optical and minimally invasive detection tool that rapidly probes strain in large areas of GRM monolayers, would be of great importance in the research and development of novel 2D devices. Here, we use Polarization-resolved Second Harmonic Generation (P-SHG) optical imaging to identify strain distribution, induced in a single layer of WS2 placed on a pre-patterned Si/SiO2 substrate with cylindrical wells. By fitting the P-SHG data pixel-by-pixel, we produce spatially resolved images of the crystal armchair direction. In regions where the WS2 monolayer conforms to the pattern topography, a distinct cross-shaped pattern is evident in the armchair image owing to strain. The presence of strain in these regions is independently confirmed using a combination of atomic force microscopy and Raman mapping.

Abstract Electron self-injection in laser wakefield accelerators (LWFAs) is an important determinator of electron beam parameters. Controllable and adjustable LWFA beams are essential for applications. Controlled injection by capturing sheath electrons can be achieved using plasma density down-ramps or bumps, which perturb the LWFA bubble phase velocity by varying the plasma frequency and by affecting relativistic self-focussing of the laser. We report on a comprehensive study, using particle-in-cell simulations, of the effect of laser pulse evolution on injection on density perturbations. We show how the LWFA can be optimised to make it suitable for use in a wide range of applications, in particular those requiring short duration, low slice-emittance and low energy spread, and high-charge electron bunches.

Abstract Segregation is a threat to the aspirations of producing a cohesive society and modelling its dynamics can be done in order to help design preventative measures. This work explores the question of whether the network topologies of urban spaces can affect the pace at which populations can become segregated. The simulation dynamics employed augment the canonical Schelling model in such a way that it also captures the affinity for agents to prefer denser regions which also offer sufficient local homogeneity. It is shown that different networks synthetically generated and from real city maps can alter the rate of segregation. The results also show that using the entropy trace on the distribution of agent edge degree across all agents correlates with the segregation reinforcing the relevance of physics inspired modeling of social systems. This investigation shows that it is possible to explore and select network arrangements which can be less conducive towards segregation movements during the stages of urban planning so that the rate is reduced. An additional finding is that the entropic measure is closely associated with the common statistic for such modeling efforts.

Abstract Microplastics are one of the concerning environmental pollutants because of their ubiquity. Their capability to adsorb other environmental pollutants increases the risk even further. Existing identification approaches for microplastic characterization for polymer class and their surface-adsorbed heavy metal detection require the utilization of multiple resources and expertise. The article discusses the applicability of a custom-made hyphenated Laser Induced Breakdown Spectroscopy (LIBS)—Raman spectroscopic system in characterizing microplastics by comparing the analytical performance with conventional methods such as Attenuated Total Reflectance- Fourier Transform Infrared (ATR-FTIR) spectroscopy, confocal Raman spectroscopy, and Scanning Electron Microscopy–Energy Dispersive X-ray Spectroscopy (SEM–EDS). Raman analysis identified polyethylene (PE), polypropylene (PP), and polyethylene terephthalate (PET) plastics, which is confirmed by confocal Raman and FTIR study of the same. LIBS study of microplastics detected heavy metals such as Al, Ni, Co, and Zn, along with Ca and Mg trace elements. The cross-examination with EDS validates these trace elements' presence on the microplastics' surface. The results of the reported LIBS-Raman analysis and its validity evaluated using conventional gold-standard methods show the applicability of the proposed methodology in characterizing microplastics from environmental resources with less or no sample preparation in short time.

Abstract Restoring motor function after stroke necessitates involvement of numerous cognitive systems. However, the impact of damage to motor and cognitive network organization on recovery is not well understood. To discover correlates of successful recovery, we explored imaging characteristics in chronic stroke subjects by combining noninvasive brain stimulation and fMRI. Twenty stroke survivors (6 months or more after stroke) were randomly assigned to a single session of transcranial direct current stimulation (tDCS) or sham during image acquisition. Twenty healthy subjects were included as controls. tDCS was limited to 10 min at 2 mA to serve as a mode of network modulation rather than therapeutic delivery. Fugl-Meyer Assessments (FMA) revealed significant motor improvement in the chronic stroke group receiving active stimulation (p = 0.0005). Motor changes in this group were correlated in a data-driven fashion with imaging features, including functional connectivity (FC), surface-based morphometry, electric field modeling and network topology, focusing on relevant regions of interest. We observed stimulation-related changes in FC in supplementary motor (p = 0.0029), inferior frontal gyrus (p = 0.0058), and temporo-occipital (p = 0.0095) areas, though these were not directly related to motor improvement. The feature most strongly associated with FMA improvement in the chronic stroke cohort was graph topology of the dorsal attention network (DAN), one of the regions surveyed and one with direct connections to each of the areas with FC changes. Chronic stroke subjects with a greater degree of motor improvement had lower signal transmission cost through the DAN (p = 0.029). While the study was limited by a small stroke cohort with moderate severity and variable lesion location, these results nevertheless suggest a top-down role for higher order areas such as attention in helping to orchestrate the stroke recovery process.

Abstract Aesthetic judgements are partly predicted by image statistics, although the extent to which they are calibrated to the statistics of real-world scenes and the ‘visual diet’ of daily life is unclear. Here, we investigated the extent to which the beauty ratings of Western oil paintings from the JenAesthetics dataset can be accounted for by real-world scene statistics. We computed spatial and chromatic image statistics for the paintings and a set of real-world scenes captured by a head-mounted camera as participants went about daily lives. Partial least squares regression (PLSR) indicated that 6–15% of the variance in beauty ratings of the art can be accounted for by the art’s image statistics. The luminance contrast of paintings made an important contribution to the PLSR models: paintings were perceived as more beautiful the greater the variation in luminance. PLSR models which expressed the art’s image statistics relative to real-world scene statistics explained a similar amount of variance to models using the art’s image statistics. The importance of an image statistic to perceived beauty was not related to how closely art reproduces the value from the real world. The findings suggest that beauty judgements of art are not strongly calibrated to the scene statistics of the real world.

Abstract The Proteus effect is a phenomenon found in over 60 studies where people tend to conform behaviorally to their avatars’ identity characteristics, especially in virtual reality. This study extends research on the Proteus effect to consider organization-representing avatars and misogynistic behavioral outcomes. Male participants (N = 141) in a lab experiment embodied a set of pretested avatars which varied in level of association with a university mascot (i.e., color and body type) in a bespoke virtual reality simulation designed to elicit misogynistic behavior. Namely, participants were directed to place a hand on virtual agents’ body parts, including the buttocks (i.e., a transgressive misogynistic act). Time delay in complying with directions to touch the agents’ buttocks served as an implicit measure of resistance to this misogynistic behavior. Results suggest that within moderately masculine body-size avatar users, those who embodied a university-color-associated avatar exhibited more misogynistic behaviors (i.e., faster buttocks-touching). Unexpectedly, this effect of avatar color was not apparent within the hypermasculine body-size avatars, and within the university-associated color condition, hypermasculine body-type was associated with less misogynistic behavior. These findings suggest that organization-representing avatars may induce behavioral conformity to implicit attitudes associated with the organization, such as misogyny.

Abstract There are currently no available FDA-cleared biodosimetry tools for rapid and accurate assessment of absorbed radiation dose following a radiation/nuclear incident. Previously we developed a protein biomarker-based FAST-DOSE bioassay system for biodosimetry. The aim of this study was to integrate an ELISA platform with two high-performing FAST-DOSE biomarkers, BAX and DDB2, and to construct machine learning models that employ a multiparametric biomarker strategy for enhancing the accuracy of exposure classification and radiation dose prediction. The bioassay showed 97.92% and 96% accuracy in classifying samples in human and non-human primate (NHP) blood samples exposed ex vivo to 0–5 Gy X-rays, respectively up to 48 h after exposure, and an adequate correlation between reconstructed and actual dose in the human samples (R2 = 0.79, RMSE = 0.80 Gy, and MAE = 0.63 Gy) and NHP (R2 = 0.80, RMSE = 0.78 Gy, and MAE = 0.61 Gy). Biomarker measurements in vivo from four NHPs exposed to a single 2.5 Gy total body dose showed a persistent upregulation in blood samples collected on days 2 and 5 after irradiation. The data indicates that using a combined approach of targeted proteins can increase bioassay sensitivity and provide a more accurate dose prediction.

Abstract Application of stable isotopically labelled (SIL) molecules in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI) over a series of time points allows the temporal and spatial dynamics of biochemical reactions to be tracked in a biological system. However, these large kinetic MSI datasets and the inherent variability of biological replicates presents significant challenges to the rapid analysis of the data. In addition, manual annotation of downstream SIL metabolites involves human input to carefully analyse the data based on prior knowledge and personal expertise. To overcome these challenges to the analysis of spatiotemporal MALDI-MSI data and improve the efficiency of SIL metabolite identification, a bioinformatics pipeline has been developed and demonstrated by analysing normal bovine lens glucose metabolism as a model system. The pipeline consists of spatial alignment to mitigate the impact of sample variability and ensure spatial comparability of the temporal data, dimensionality reduction to rapidly map regional metabolic distinctions within the tissue, and metabolite annotation coupled with pathway enrichment modules to summarise and display the metabolic pathways induced by the treatment. This pipeline will be valuable for the spatial metabolomics community to analyse kinetic MALDI-MSI datasets, enabling rapid characterisation of spatio-temporal metabolic patterns from tissues of interest.

Abstract Silica fiber under high pressure increases the risk of fiber breakage or permanent deformation, which may cause sensor failure due to mechanical strength limitations. High pressure can also induce birefringence in optical fiber. In this study, we present a simple design and low-cost high pressure sensor using polymer optical fiber (POF) based on the intensity-variation technique. A side-coupling mechanism in the sensor structure is adopted, which varies the intensity with applied pressure. Two POFs are twisted together to create a sensing region where the light is launched in the first fiber and measurement is taken from the second fiber. In sensing phenomena, cladding mode frustrated total internal reflection occurs when pressure increases. Silicone gel is used in the pressure chamber for sealing and preventing leakage. The sensor structure is able to detect high pressure in the MPa range, where we tested up to 4 MPa. For higher sensitivity, twisted and bend structure is analyzed, and sensitivity is achieved at about 432.21 nW/MPa. However, twisted helical structure is adopted to enhance sensing range which is about 50 cm. The proposed high-pressure sensor structure is easier to fabricate and has high stability because it doesn’t require any destructive method as compared to other conventional methods.

Abstract Fecal Microbiota Transplant (FMT) has shown some success in treating inflammatory bowel diseases (IBD). There is emerging evidence that host engraftment of donor taxa is a tenet of successful FMT. We undertook a double-blind, randomized, placebo-controlled pilot study to characterize the response to FMT in children and young adults with mild to moderate active Crohn’s disease (CD) and ulcerative colitis (UC). Subjects with CD or UC were randomized to receive antibiotics and weekly FMT or placebo in addition to baseline medications. We enrolled 15 subjects aged 14–29 years. Four subjects had CD, and 11 had UC. Subjects exhibited a wide range of microbial diversity and donor engraftment. Specifically, engraftment ranged from 26 to 90% at week 2 and 3–92% at 2 months. Consistent with the current literature, increases over time of both alpha diversity (p

Abstract Production of hard X-ray via inverse Compton scattering at photon energies below 100 keV range aimed at potential applications in medicine and material research is reported. Experiments have been performed at the Brookhaven National Laboratory, Accelerator Test Facility, employing the counter collision of a 70 MeV, 0.3 nC electron beam with a near infra-red Nd: YAG laser (1064 nm wavelength) pulse containing ~ 100 mJ in a single shot basis. The radiation distribution of the scattered photon beam is assessed to be sufficiently quasi monochromatic to produce clear contrast from the Au K- edge at 80.7 keV.

Abstract Low muscle mass is associated with numerous adverse outcomes independent of other associated comorbid diseases. We aimed to predict and understand an individual’s risk for developing low muscle mass using proteomics and machine learning. We identified eight biomarkers associated with low pectoralis muscle area (PMA). We built three random forest classification models that used either clinical measures, feature selected biomarkers, or both to predict development of low PMA. The area under the receiver operating characteristic curve for each model was: clinical-only = 0.646, biomarker-only = 0.740, and combined = 0.744. We displayed the heterogenetic nature of an individual’s risk for developing low PMA and identified two distinct subtypes of participants who developed low PMA. While additional validation is required, our methods for identifying and understanding individual and group risk for low muscle mass could be used to enable developments in the personalized prevention of low muscle mass.

Abstract The objective was to assess the impact of environmental complexity on affective state (anxiety) in fast- and slow-growing broilers (Gallus gallus domesticus) as they gain weight. Six hundred fast-growing broilers (Ross 708; “fast-growers”) and 600 slow-growing broilers (Hubbard Redbro Mini; “slow-growers”) were raised in 24 pens with simple (standard; SE) or complex (permanent and temporary enrichments; CE) environments. Six birds/pen underwent the attention bias test on day 23 (fast-growers only), 28–29, 35–36, 42–43, and 56–57 (slow-growers only), with individuals only tested once (n = 576). Proportion of birds feeding, time spent vigilant and latencies to eat and step were recorded. Greater vigilance and longer latencies indicate more anxiety. Slow-growers fed more (p = 0.001), were less vigilant (p = 0.003), and stepped sooner than fast-growers (p = 0.007). For both strains, likelihood of feeding was unrelated to weight in SE, but decreased with increasing weight in CE (p = 0.048). Birds in CE stepped sooner than birds in SE (p = 0.030). Vigilance increased with body weight (p = 0.024). These results indicate that affective state (anxiety) can change as birds gain weight, depending on environmental complexity and genetic strain. Overall, slow-growers showed reduced anxiety compared to fast-growers, across housing treatments or weights.

Abstract The combination of multi-omic techniques, such as genomics, transcriptomics, proteomics, metabolomics and epigenomics, has revolutionised studies in medical research. These techniques are employed to support biomarker discovery, better understand molecular pathways and identify novel drug targets. Despite concerted efforts in integrating omic datasets, there is an absence of protocols that integrate all four biomolecules in a single extraction process. Here, we demonstrate for the first time a minimally destructive integrated protocol for the simultaneous extraction of artificially degraded DNA, proteins, lipids and metabolites from pig brain samples. We used an MTBE-based approach to separate lipids and metabolites, followed by subsequent isolation of DNA and proteins. We have validated this protocol against standalone extraction protocols and show comparable or higher yields of all four biomolecules. This integrated protocol is key to facilitating the preservation of irreplaceable samples while promoting downstream analyses and successful data integration by removing bias from univariate dataset noise and varied distribution characteristics.

Abstract This study investigated the time course of gene expression changes during the progression of persistent painful neuropathy caused by paclitaxel (PTX) in male and female mouse hindpaws and dorsal root ganglia (DRG). Bulk RNA-seq was used to examine these gene expression changes at 1, 16, and 31 days post-last PTX. At these time points, differentially expressed genes (DEGs) were predominantly related to the reduction or increase in epithelial, skin, bone, and muscle development and to angiogenesis, myelination, axonogenesis, and neurogenesis. These processes are accompanied by the regulation of DEGs related to the cytoskeleton, extracellular matrix organization, and cellular energy production. This gene plasticity during the progression of persistent painful neuropathy could be interpreted as a biological process linked to tissue regeneration/degeneration. In contrast, gene plasticity related to immune processes was minimal at 1–31 days after PTX. It was also noted that despite similarities in biological processes and pain chronicity between males and females, specific DEGs differed dramatically according to sex. The main conclusions of this study are that gene expression plasticity in hindpaw and DRG during PTX neuropathy progression similar to tissue regeneration and degeneration, minimally affects immune system processes and is heavily sex-dependent at the individual gene level.

Abstract This research work aims at evaluating the geothermal energy potentials of the Rafin Rewa warm spring (RRWS) of the Precambrian Basement Complex in Nigeria as an alternative energy source using integrated aeromagnetic geophysical techniques. Four aeromagnetic dataset were acquired, assemblage, analyzed, and interpreted using integrated geophysical processing techniques of spectral analysis and Euler deconvolution. Qualitative interpretation of the residual anomalous map reveals a distribution of positive anomalies (> 53 nT) majorly in the central and southeastern regions, which are traced to the granitic rocks, while the low anomalies (

Abstract The aim of this study is to compare the diagnostic performance of magnetic resonance imaging (MRI) against computed tomography (CT) in various aspects of local staging in colon cancer patients. This study was a prospective single arm diagnostic accuracy study. All consecutive adult patients with confirmed colon cancer that met the current criteria for surgical resection were considered as eligible. Diagnostic performance assessment included T (T1/T2 vs T3/T4 and T3cd) and N (N positive) staging, serosa and retroperitoneal surgical margin (RSM) involvement and extramural vascular invasion (EMVI). Imaging was based on a 3 Tesla MRI system and the evaluation of all sequences (T1, T2 and diffusion-weighted imaging-DWI series) by two independent readers. CT scan was performed in a 128 row multidetector (MD) CT scanner (slice thickness: 1 mm) with intravenous contrast. Pathology report was considered as the gold standard for local staging. Sensitivity (SE), specificity (SP), and area under the curve (AUC) were calculated for both observers. MRI displayed a higher diagnostic performance over CT in terms of T1/T2 vs T3/T4 (SE: 100% vs 83.9%, SP: 96.6% vs 81%, AUC: 0.825 vs 0.983, p

Abstract Numerous studies have indicated that Morocco’s indigenous sheep breeds are genetically homogenous, posing a risk to their survival in the challenging harsh climate conditions where they predominantly inhabit. To understand the genetic behind genetic homogeneity through the lens of runs of homozygosity (ROH), we analyzed the whole genome sequences of five indigenous sheep breeds (Beni Guil, Ouled Djellal, D’man, Sardi, Timahdite and Admixed).The results from principal component, admixture, Fst, and neighbour joining tree analyses consistently showed a homogenous genetic structure. This structure was characterized by an average length of 1.83 Mb for runs of homozygosity (ROH) segments, with a limited number of long ROH segments (24–48 Mb and > 48 Mb). The most common ROH segments were those ranging from 1–6 Mb. The most significant regions of homozygosity (ROH Islands) were mostly observed in two chromosomes, namely Chr1 and Chr5. Specifically, ROH Islands were exclusively discovered in the Ouled Djellal breed on Chr1, whereas Chr5 exhibited ROH Islands in all breeds. The analysis of ROH Island and iHS technique was employed to detect signatures of selection on Chr1 and Chr5. The results indicate that Chr5 had a high level of homogeneity, with the same genes being discovered across all breeds. In contrast, Chr1 displays some genetic variances between breeds. Genes identified on Chr5 included SLC39A1, IL23A, CAST, IL5, IL13, and IL4 which are responsible for immune response while genes identified on Chr1 include SOD1, SLAMF9, RTP4, CLDN1, and PRKAA2. ROH segment profile and effective population sizes patterns suggests that the genetic uniformity of studied breeds is the outcome of events that transpired between 250 and 300 generations ago. This research not only contributes to the understanding of ROH distribution across breeds but helps design and implement native sheep breeding and conservation strategies in Morocco. Future research, incorporating a broader sample size and utilizing the pangenome for reference, is recommended to further elucidate these breeds’ genomic landscapes and adaptive mechanisms.

Abstract Indigenous goats are important to many livelihoods. Despite this, they are subjected to indiscriminate crossbreeding. This affects their genetic variability which is needed to survive in current regime of climate change. The study assessed population structure and genetic diversity of Galla and Small East African goats (SEA) using pedigree information. A total of 7384 animals, 5222 of the Galla and 2162 of the SEA breeds, born between the years 1983 and 2022, were utilized. Individuals with known parents were defined as reference population. From the results, the maximum generation traced for Galla and SEA populations was 14.6 and 14.5, respectively. However, only 6 and 5 generations for Galla and SEA were complete. Pedigree completeness increased with the increasing number of generations. The average generation interval (GI) for Galla and SEA was 3.84 ± 0.04 and 4.4 ± 0.13 years. The average increase in the rate of inbreeding per generation for Galla and SEA was 0.04 and 0.05, with the effective ancestors and founders (fa/fe) ratio being same (1.00) for both breeds. Fifty percent (50%) of the genetic variability in the populations was contributed by 3 and 1 ancestor for Galla SEA, respectively. The effective population size (Ne) was 5.19 and 4.77 for Galla and SEA. Therefore, the current breeding programs should be changed to avoid future genetic bottlenecks in this population. These findings offer an opportunity to enhance the current genetic status and management of Kenyan native goats and other regions with similar production systems.

Abstract Pancreatic adenocarcinoma is one of the most aggressive and lethal forms of cancer. Chemotherapy is the primary treatment for pancreatic cancer, but resistance to the drugs used remains a major challenge. A genome-wide CRISPR interference and knockout screen in the PANC-1 cell line with the drug nab-paclitaxel has identified a group of spindle assembly checkpoint (SAC) genes that enhance survival in nab-paclitaxel. Knockdown of these SAC genes (BUB1B, BUB3, and TTK) attenuates paclitaxel-induced cell death. Cells treated with the small molecule inhibitors BAY 1217389 or MPI 0479605, targeting the threonine tyrosine kinase (TTK), also enhance survival in paclitaxel. Overexpression of these SAC genes does not affect sensitivity to paclitaxel. These discoveries have helped to elucidate the mechanisms behind paclitaxel cytotoxicity. The outcomes of this investigation may pave the way for a deeper comprehension of the diverse responses of pancreatic cancer to therapies including paclitaxel. Additionally, they could facilitate the formulation of novel treatment approaches for pancreatic cancer.

Abstract Accumulation of α-synuclein (α-Syn) has been implicated in proteasome and autophagy dysfunction in Parkinson’s disease (PD). High frequency electrical stimulation (HFS) mimicking clinical parameters used for deep brain stimulation (DBS) in vitro or DBS in vivo in preclinical models of PD have been found to reduce levels of α-Syn and, in certain cases, provide possible neuroprotection. However, the mechanisms by which this reduction in α-Syn improves cellular dysfunction associated with α-Syn accumulation remains elusive. Using HFS parameters that recapitulate DBS in vitro, we found that HFS led to a reduction of mutant α-Syn and thereby limited proteasome and autophagy impairments due to α-Syn. Additionally, we observed that HFS modulates via the ATP6V0C subunit of V-ATPase and mitigates α-Syn mediated autophagic dysfunction. This study highlights a role for autophagy in reduction of α-Syn due to HFS which may prove to be a viable approach to decrease pathological protein accumulation in neurodegeneration.

Abstract AI-powered segmentation of hip and knee bony anatomy has revolutionized orthopedics, transforming pre-operative planning and post-operative assessment. Despite the remarkable advancements in AI algorithms for medical imaging, the potential for biases inherent within these models remains largely unexplored. This study tackles these concerns by thoroughly re-examining AI-driven segmentation for hip and knee bony anatomy. While advanced imaging modalities like CT and MRI offer comprehensive views, plain radiographs (X-rays) predominate the standard initial clinical assessment due to their widespread availability, low cost, and rapid acquisition. Hence, we focused on plain radiographs to ensure the utilization of our contribution in diverse healthcare settings, including those with limited access to advanced imaging technologies. This work provides insights into the underlying causes of biases in AI-based knee and hip image segmentation through an extensive evaluation, presenting targeted mitigation strategies to alleviate biases related to sex, race, and age, using an automatic segmentation that is fair, impartial, and safe in the context of AI. Our contribution can enhance inclusivity, ethical practices, equity, and an unbiased healthcare environment with advanced clinical outcomes, aiding decision-making and osteoarthritis research. Furthermore, we have made all the codes and datasets publicly and freely accessible to promote open scientific research.

Abstract Atherosclerosis is rare in internal thoracic arteries (ITA) even in patients with severe atherosclerotic coronary artery (ACA) disease. To explore cellular differences, ITA SMC from 3 distinct donors and ACA SMC from 3 distinct donors were grown to sub-confluence and growth arrested for 48 h. Proliferation and thrombospondin-1 (TSP1) production were determined using standard techniques. ITA SMC were larger, grew more slowly and survived more passages than ACA SMC. ACA SMC had a more pronounced proliferative response to 10% serum than ITA SMC. Both ACA SMC and ITA SMC proliferated in response to exogenous TSP1 (12.5 µg/ml and 25 µg/ml) and platelet derived growth factor-BB (PDGF-BB; 20 ng/ml) but TSP1- and PDGF-BB-induced proliferation were partially inhibited by anti-TSP1 antibody A4.1, microRNA-21(miR-21)-3p inhibitors and miR-21-5p inhibitors in each of the 3 ACA SMC lines, but not in any of the ITA SMC lines. PDGF-BB stimulated TSP1 production in ACA SMC but not in ITA SMC but there was no increase in TSP1 levels in conditioned media in either SMC type. In summary, there are significant differences in morphology, proliferative capacity and in responses to TSP1 and PDGF-BB in SMC derived from ITA compared to SMC derived from ACA.

Abstract We present the first machine learning-based autonomous hyperspectral neutron computed tomography experiment performed at the Spallation Neutron Source. Hyperspectral neutron computed tomography allows the characterization of samples by enabling the reconstruction of crystallographic information and elemental/isotopic composition of objects relevant to materials science. High quality reconstructions using traditional algorithms such as the filtered back projection require a high signal-to-noise ratio across a wide wavelength range combined with a large number of projections. This results in scan times of several days to acquire hundreds of hyperspectral projections, during which end users have minimal feedback. To address these challenges, a golden ratio scanning protocol combined with model-based image reconstruction algorithms have been proposed. This novel approach enables high quality real-time reconstructions from streaming experimental data, thus providing feedback to users, while requiring fewer yet a fixed number of projections compared to the filtered back projection method. In this paper, we propose a novel machine learning criterion that can terminate a streaming neutron tomography scan once sufficient information is obtained based on the current set of measurements. Our decision criterion uses a quality score which combines a reference-free image quality metric computed using a pre-trained deep neural network with a metric that measures differences between consecutive reconstructions. The results show that our method can reduce the measurement time by approximately a factor of five compared to a baseline method based on filtered back projection for the samples we studied while automatically terminating the scans.

Abstract The development of geopolymer concrete offers promising prospects for sustainable construction practices due to its reduced environmental impact compared to conventional Portland cement concrete. However, the complexity involved in geopolymer concrete mix design often poses challenges for engineers and practitioners. In response, this study proposes a simplified approach for designing geopolymer concrete mixtures, drawing upon principles from Portland cement concrete mix design standards and recommended molar ratios of oxides involved in geopolymer synthesis. The proposed methodology aims to streamline the mix design process while optimizing key factors such as chemical composition, alkali activation solution, water content, and curing conditions to achieve desired compressive strength and workability. By leveraging commonalities between Portland cement concrete and geopolymer concrete, this approach seeks to facilitate the adoption of geopolymer concrete in practical construction applications. The proposed mix design guidelines have been validated through examples for concrete cured under different conditions, including outdoor and oven curing. Future research should focus on validating the proposed methodology through experimental studies and exploring cost-effective alternatives for alkali activation solutions to enhance the feasibility and scalability of geopolymer concrete production. Overall, the proposed simplified approach holds promise for advancing the utilization of geopolymer concrete as a sustainable alternative in the construction industry.

Abstract A popular and widely suggested measure for assessing unilateral hand motor skills in stroke patients is the box and block test (BBT). Our study aimed to create an augmented reality enhanced version of the BBT (AR-BBT) and evaluate its correlation to the original BBT for stroke patients. Following G-power analysis, clinical examination, and inclusion–exclusion criteria, 31 stroke patients were included in this study. AR-BBT was developed using the Open Source Computer Vision Library (OpenCV). The MediaPipe's hand tracking library uses a palm and a hand landmark machine learning model to detect and track hands. A computer and a depth camera were employed in the clinical evaluation of AR-BBT following the principles of traditional BBT. A strong correlation was achieved between the number of blocks moved in the BBT and the AR-BBT on the hemiplegic side (Pearson correlation = 0.918) and a positive statistically significant correlation (p = 0.000008). The conventional BBT is currently the preferred assessment method. However, our approach offers an advantage, as it suggests that an AR-BBT solution could remotely monitor the assessment of a home-based rehabilitation program and provide additional hand kinematic information for hand dexterities in AR environment conditions. Furthermore, it employs minimal hardware equipment.

The term Solar Cell is commonly used for Photovoltaics that convert light into electrical energy. However, light can be harvested from various sources not limited to the Sun. This work considers the possibility of harvesting photons from different star types, including our closest neighbor star Proxima Centauri. The theoretical efficiency limits of single junction photovoltaic devices are calculated for different star types at a normalized light intensity corresponding to the AM0 spectrum intensity with AM0 = 1361 W/m2. An optimal bandgap of > 12 eV for the hottest O5V star type leads to 47% Shockley-Queisser photoconversion efficiency (SQ PCE), whereas a narrower optimal bandgap of 0.7 eV leads to 23% SQ PCE for the coldest red dwarf M0, M5.5Ve, and M8V type stars. Organic Photovoltaics (OPVs) are the most lightweight solar technology and have the potential to be employed in weight-restricted space applications, including foreseeable interstellar missions. With that in mind, the Suns G2V spectrum and Proxima Centauris M5.5Ve spectrum are considered in further detail in combination with two extreme bandgap OPV systems: one narrow bandgap system (PM2:COTIC-4F, Eg = 1.14 eV) and one wide bandgap system (PM6:o-IDTBR, Eg = 1.62 eV). Semi-empirically modeled JV-curves reveal that the absorption characteristics of the PM2:COTIC-4F blend match well with both the G2V and the M5.5Ve spectrum, yielding theoretical PCEs of 22.6% and 12.6%, respectively. In contrast, the PM6:o-IDTBR device shows a theoretical PCE of 18.2% under G2V illumination that drops sharply to 0.9% under M5.5Ve illumination.