Sampling Pattern Research Articles

Hydrocarbon biodegradation processes at a historic oil production site - A signature metabolite study.

Decades of research demonstrated that microbes can remediate petroleum-contaminated environments through biodegradation of hydrocarbons. Recent studies have applied signature metabolite analysis to investigate hydrocarbon-contaminated sites, focusing primarily on aquifer systems and metabolites of relatively water-soluble monoaromatic hydrocarbons. However, the number of studies involving non-targeted analysis and identification of individual metabolites in environmental samples is limited. In addition, metabolite patterns in crude oil-contaminated samples are rarely compared to those in the unaltered crude oils. In this study, we identified metabolites in complex environmental samples and crude oils from a former oil sands mining site using non-targeted gas chromatography-mass spectrometry. Based on these results, we suggest potential biodegradation processes that may account for the formation of the observed metabolites. The non-target results from water samples contaminated with crude oil showed that aromatic acids were the dominant metabolites. We observed that arylacetic acids were particularly abundant in the water samples when the metabolite patterns were compared with those found in crude oil and oil sands samples formerly produced at the site, as well as those found in oil-contaminated soil samples. The dominance of arylacetic acids is evidence that the microbial communities have a limited capacity for α-oxidation, i.e. an enzymatic attack on the methylene group, which is necessary to further degrade these compounds. Therefore, aromatic acids may be enriched at sites with long-term exposure to crude oil. Our study demonstrates that non-targeted metabolite analysis can provide an insight into the prevalent pattern of carboxylic acid metabolites and degradation processes in hydrocarbon-contaminated habitats.

Accelerated model-based T1, T2* and proton density mapping using a Bayesian approach with automatic hyperparameter estimation.

To achieve automatic hyperparameter estimation for the model-based recovery of quantitative MR maps from undersampled data, we propose a Bayesian formulation that incorporates the signal model and sparse priors among multiple image contrasts. We introduce a novel approximate message passing framework "AMP-PE" that enables the automatic and simultaneous recovery of hyperparameters and quantitative maps. We employed the variable-flip-angle method to acquire multi-echo measurements using gradient echo sequence. We explored undersampling schemes to incorporate complementary sampling patterns across different flip angles and echo times. We further compared AMP-PE with conventional compressed sensing approaches such as the -norm minimization, PICS and other model-based approaches such as GraSP, MOBA. Compared to conventional compressed sensing approaches such as the -norm minimization and PICS, AMP-PE achieved superior reconstruction performance with lower errors in mapping and comparable performance in and proton density mappings. When compared to other model-based approaches including GraSP and MOBA, AMP-PE exhibited greater robustness and outperformed GraSP in reconstruction error. AMP-PE offers faster speed than MOBA. AMP-PE performed better than MOBA at higher sampling rates and worse than MOBA at a lower sampling rate. Notably, AMP-PE eliminates the need for hyperparameter tuning, which is a requisite for all the other approaches. AMP-PE offers the benefits of model-based recovery with the additional key advantage of automatic hyperparameter estimation. It works adeptly in situations where ground-truth is difficult to obtain and in clinical environments where it is desirable to automatically adapt hyperparameters to individual protocol, scanner and patient.

Establishment and extension of a compact and robust binary feature descriptor for UAV image matching

Abstract Local feature description is a crucial challenge in unmanned aerial vehicle (UAV) images matching. Although scholars have explored a variety of methods for defining local feature descriptions, improving the matching accuracy of UAV images and reducing the memory consumption of descriptor remain worthwhile research issues. A compact and robust binary feature descriptor for UAV image matching is proposed. To achieve rotational invariance of the descriptor, a sampling pattern based on the region overlap error is employed to assign the dominant direction of the feature points. Additionally, a rotation invariant gradient computation method is proposed to reduce the dominant direction assignment errors. Then, the region around the feature point is divided into grids based on the region overlap error, and gradient orientation histogram and average intensity histogram are constructed. Finally, these histograms are binarized to generate a 30-byte binary descriptor. Results from the Oxford dataset, the Iguazu dataset, and a high-resolution UAV image dataset indicate that the proposed descriptor is compact and achieves the highest matching accuracy compared to nine commonly used feature descriptors, including scale-invariant feature transform, speeded up robust feature, binary robust invariant scalable keypoints, KAZE, oriented fast and rotated brief, fast retina keypoint, local intensity order pattern, boosted efficient binary local image descriptor, and triplet-based efficient binary local image descriptor. Notably, on the high-resolution UAV images with translational transformations, scale variations, salt-and-pepper noise, and Gaussian white noise, the accuracies of the proposed descriptor were 87.09%, 80.83%, 92.46%, and 87.42%, respectively. The improvements ranged from 6.95% to 53.20%, 9.32% to 55.90%, 10.39% to 44.29%, and 6.54% to 58.24%.

Interdependent roles for growth differentiation factor-15 (GDF15) and LIMS1 in regulating cell migration: Implications for colorectal cancer metastasis.

Colorectal cancer (CRC) ranks second in mortality worldwide while metastasis accounts for most CRC-related deaths. Thus, understanding cell migration, a crucial step in metastasis, is imperative for developing new therapies. Growth Differentiation Factor-15 (GDF15), a member of the Transforming Growth Factor β superfamily, is overexpressed in CRC and promotes metastasis with a so far unknown mechanism. LIMS1 is a cell-matrix adhesion prosurvival protein that is also overexpressed in CRC and localized at the tumor invasive front, while bioinformatics analysis shows that both genes exhibit the same expression pattern in metastatic CRC samples. In the present study, treatment of low-aggressiveness HT29 CRC cells with human recombinant GDF15 (hrGDF15) led to increased LIMS1 expression, increased mRNA level of RhoGTPases RAC1 and RHOA but not CDC42, and increased migration. Conversely, GDF15 or LIMS1-siRNA-mediated silencing in invasive HCT116 cells resulted in downregulation of LIMS1 and GDF15 respectively, decreased RAC1, and RHOA as well as reduced cell migration, which were fully restored by hrGDF15 treatment both in GDF15 and LIMS1-siRNA-treated cells. Our findings indicate that GDF15 and LIMS1 have an interdependent role in the migration process which renders them potent targets for the development of novel therapeutic strategies to inhibit metastatic spread.

Assessing the influence of land use change on soil quality across different ecosystems in Kolli hills, Eastern Ghats

Soil quality indices (SQIs) assess an ecosystem’s susceptibility to land-use change (LUC), highlighting the impacts on soil parameters. This study developed an SQI for six ecosystems in the Kolli Hills (KH), Eastern Ghats (EG), India: evergreen forest (EF), deciduous forest (DF), thorn forest (TF), agricultural system (AS), horticulture system (HS), and plantation system (PS). Soil samples were collected at two depths, surface (15 cm) and subsurface (30 cm), from 240 sites (40 samples per depth per ecosystem) and analyzed. LUC altered the soil physical and chemical properties. AS and HS had higher sand content (54.63%), bulk density (1.47 Mg m−3), and particle density (2.48 Mg m−3), whereas EF and DF had higher clay content (63.91%), porosity (52.03%), and available soil moisture (18.33%), all of which decreased with depth. The organic carbon and nutrient levels were greater in EF, DF, TF, and PS, with EF having the highest values (soil organic carbon: 60.70 g kg−1; nitrogen: 322.21 kg ha−1; phosphorus: 80.54 kg ha−1; potassium: 617.06 kg ha−1, iron—83.16 mg kg−1, manganese—60.16 mg kg−1, zinc—5.16 mg kg−1 and copper—5.35 mg kg−1) at 15 cm and decreasing with depth. In conclusion, the SQI for surface soil was the maximum in EF (2.50), followed by DF, TF, PS, HS, and AS, with a similar pattern in subsurface samples, suggesting an urgent need for land management strategies to improve soil quality in these ecosystems of the Eastern Ghats.

Metabolomics-Driven Insights into Biomarkers for Poor Ovarian Response: A Narrative Review.

Poor ovarian response (POR) remains a significant challenge in the field of assisted reproductive technology (ART), as the quantity and quality of oocytes retrieved directly influence embryo implantation, clinical pregnancy, and live birth rates. Metabolomics has become a valuable tool for elucidating the molecular mechanisms underlying diminished ovarian reserve (DOR) and POR. This review aims to synthesize findings from metabolomic studies examining metabolite expression patterns in serum and follicular fluid samples from women with POR. A literature search was performed using the Medline/PubMed and Scopus databases, employing keywords related to metabolomics and POR. In total, nine studies met the inclusion criteria for this review. These studies identified several metabolites with differential expression in serum and follicular fluid samples between women with normal ovarian response and those with POR. Although the metabolomic profiles varied significantly among studies, consistent alterations in prostaglandin related metabolites were observed in two of the nine studies reviewed. These findings suggest that, pending further validation, these metabolites may serve as potential biomarkers for ovarian response. Metabolomics has significantly advanced our understanding of the mechanisms underlying ovarian function and holds promise for identifying effective biomarkers that could improve the prediction and management of POR.

Common Isolates and Antibiotic Susceptibility Pattern of Urine Samples among Patients Attending a Tertiary Health Institution in South Nigeria

Aim: To identify the main isolates in Urinary Tract Infection (UTI) and their antibiotic susceptibility patterns in Federal Medical Centre Asaba as a guide to developing corresponding antibiogram to support empirical treatment of these infections. Study Design: A three - year retrospective cross-sectional study. Place and Duration of Study: Federal Medical Centre, Asaba, Delta State, Nigeria between 1st of January 2019 to 31st December 2022. Methodology: A three - year retrospective cross-sectional study carried out by reviewing laboratory records with a focus on identifying bacterial pathogens causing UTI as well as evaluating their antibiotics susceptibility in Federal Medical Centre, Asaba, Delta State, Nigeria. All Urine microscopy, culture and sensitivity results from the 1st of January 2019 to 31st December, 2022 were collected and reviewed. Results: A total number of 2113 results of subjects, 683 males and 1430 females, that attended the tertiary hospital from the 1st of January 2019 to 31st December 2022 were reviewed. The bacterial strains identified/isolated among the population studied were Staphylococcus aureus 907 (42.9%), Escherichia coli 866 (41.9%), Klebsiella spp 232 (11.0%), Pseudomonas aeruginosa 54 (2.6%), Proteus spp 31 (1.4%), Streptococcus spp 2 (0.1%) and Pantoea spp 1.The records revealed that the organisms were isolated more in female subjects (66.7%) than male subjects (33.3%), Staphylococcus aureus 285 males, 622 females, Escherichia coli 294 males, 592 females, Klebsiella spp 62 males, 170 females, Pseudomonas aeruginosa 29 males 25 females, Proteus spp 13 males, 18 females, Streptococcus spp 2 females. Pantoea spp 1 female as well. The highest percentages of resistance have been observed against tested antibiotics. Conclusion: Most of the isolates were extended spectrum β-lactamase producers and multidrug-resistant. We observed that Gram-negative bacteria were the main cause of UTIs where the predominant microorganism was E. coli.

Study on the Mechanism of Gas Diffusion in Coal Particles under the Coupled Effects of Gas Pressure and Temperature.

To investigate the gas diffusion mechanism in coal particles under the coupled effects of gas pressure and temperature, a low-temperature liquid nitrogen adsorption experiment was first conducted to obtain the pore structure characteristics and pore size distribution patterns of the coal samples. Subsequently, a methane diffusion experiment was performed on coal particles with simultaneous increases in gas pressure and temperature using a unipore model to solve the diffusion coefficient. Finally, models for the diffusion coefficient of free-state methane and adsorbed-state methane were established, with their applicability discussed. The results indicate that the pore structure of the coal samples exhibits an approximately unimodal distribution, predominantly consisting of mesopores. As the gas pressure and temperature increase, the tortuosity of the coal sample pores also increases. Both the desorption volume and desorption rate of gas rise with the simultaneous increase in gas pressure and temperature, and overall, the diffusion coefficient of coal particles tends to increase under these conditions. Methane diffusion in coal particles is primarily governed by the surface diffusion of adsorbed methane, with gas pressure exerting a greater influence on surface diffusion than temperature. The findings of this study contribute to the understanding of the gas diffusion mechanism in coal and are of significant importance for improving gas extraction rates and preventing gas-related disasters.

Longitudinal DNA methylation profiles in saliva of offspring from mothers with gestational diabetes: associations with early childhood growth patterns

BackgroundThe prevalence of obesity and type 2 diabetes mellitus (T2DM) is rising globally, particularly among children exposed to adverse intrauterine environments, such as those associated with gestational diabetes mellitus (GDM). Epigenetic modifications, specifically DNA methylation, have emerged as mechanisms by which early environmental exposures can predispose offspring to metabolic diseases. This study aimed to investigate DNA methylation differences in children born to mothers with GDM compared to non-GDM mothers, using saliva samples, and to assess the association of these epigenetic patterns with early growth measurements.MethodsThis study analyzed saliva DNA methylation patterns in 30 children (15 born to GDM mothers and 15 to non-GDM mothers) from the EPIDG cohort. Samples were collected at two time points: 8–10 weeks postpartum and at one year of age. Epigenome-wide analysis of over 850,000 CpG sites was conducted using the Illumina Methylation EPIC Bead Chip. Differential methylation positions (DMPs) were identified with the limma package, using a significance threshold of p < 0.01 and delta β ≥ 5%. Correlation analysis examined associations between methylation and growth variables (weight, height, BMI and annual growth) using Spearman tests.ResultsWe identified 6,968 DMPs at the postpartum stage and 5,132 after one year, with 50 sites remaining differentially methylated over time, 16 of which maintained consistent methylation directionality. Functional analysis linked several of these DMPs to genes involved in inflammation and metabolic processes, including CYTH3 and FARP2, both implicated in growth and metabolic pathways. Significant correlations were found between specific CpG sites and growth-related variables such as weight, head circumference, height, and BMI.ConclusionsThis study’s longitudinal design reveals stable DNA methylation patterns in saliva samples that differentiate GDM-exposed children from controls across the first year of life, highlighting the feasibility of saliva as a minimally invasive biomarker source. The persistence of these epigenetic signatures underscores their potential as early indicators of metabolic risk, offering valuable insights into the long-term impact of maternal GDM on child health. Although the use of saliva offers a practical and non-invasive tool for pediatric epigenetic research, further studies are necessary to validate these findings in larger populations.

Phenotypic Antibiotic Resistance Patterns of Escherichia coli Isolates from Clinical UTI Samples and Municipal Wastewater in a Grenadian Community.

Antimicrobial resistance (AMR) is a growing global health threat. This study investigated antibiotic resistance in E. coli isolates from municipal wastewater (86 isolates) and clinical urinary tract infection (UTI) cases (34 isolates) in a Grenadian community, using data from January 2022 to October 2023. Antibiogram data, assessed per WHO guidelines for Critically Important antimicrobials (CIA), showed the highest resistance levels in both clinical and wastewater samples for ampicillin, followed by amoxicillin/clavulanic acid and nalidixic acid, all classified as Critically Important. Similar resistance was observed for sulfamethoxazole-trimethoprim (highly important) in both groups, with nitrofurantoin showing resistance in the important category. According to the WHO AWaRe classification, ampicillin (ACCESS group) had the highest resistance, while nitrofurantoin had the lowest across all samples. The WATCH group antibiotics, cefuroxime and cefoxitin, showed comparable resistance levels, whereas aztreonam from the RESERVE group (tested only in wastewater) was 100% sensitive. Multiple Antibiotic Resistance (MAR) index analysis revealed that 7% of wastewater and 38.2% of clinical samples had MAR values over 0.2, indicating prior antibiotic exposure in clinical isolates. These parallel patterns in wastewater and clinical samples highlight wastewater monitoring as a valuable tool for AMR surveillance, supporting antibiotic stewardship through ongoing environmental and clinical assessment.

A distinct alternative mRNA splicing profile identifies the oncogenic CD44 transcript variant 3 in KMT2A-rearranged pediatric T-cell acute lymphoblastic leukemia cells.

T-cell acute lymphoblastic leukemia (T-ALL), which constitutes of 10-15% of all pediatric acute lymphoblastic leukemia (ALL) cases, is known for its complex pathology due to pervasive genetic and chromosomal abnormalities. Although most children are successfully cured, chromosomal rearrangements involving the KMT2A gene is considered a poor prognostic factor. In a cohort of 171 pediatric T-ALL samples, we have studied differences in gene and splice variant patterns in KMT2A-rearranged (KMT2A-r) T-ALL compared with KMT2A-negative (KMT2A-wt) T-ALL samples. Our results have identified a distinct gene expression and splice variant expression pattern in pediatric KMT2A-r patient samples including significant expression of splicing regulatory markers ESRP1 and MBNL3. Additionally, the prosurvival long transcript variant of BCL2 were upregulated in KMT2A-r compared with KMT2A-wt T-ALL samples. Lastly, increased levels of activating methylation in the promoter region of CD44 were identified followed by an upregulation of the oncogenic transcript variant CD44v3 in KMT2A-r T-ALL. Together, this suggests that CD44v3 could play a potential role as gene expression-based risk stratification of KMT2A-r T-ALL and could possibly serve as a therapeutic target using splicing modulators.

WTAP/IGF2BP3 Mediated m6A Modification of SOD2 mRNA Aggravates the Tumourigenesis of Colorectal Cancer

ABSTRACTWilms tumor 1‐associated protein (WTAP) has been validated to be a crucial regulator in the tumorigenesis and advancement of diverse malignancies. This study intended to probe the impacts of WTAP on colorectal cancer (CRC) progression from the perspective of N6‐methyladenosine (m6A) modification. The differential expression patterns of WTAP in clinical CRC samples and cultured cell lines were validated via qRT‐PCR and western blot. Cell function tests were conducted with colony formation, transwell, and CCK‐8. MeRIP‐qPCR was conducted to identify the WTAP‐mediated SOD2 (Superoxide dismutase 2) mRNA modification in CRC cells. Animal experiments were adopted to evaluate the function of WTAP in vivo. WTAP exhibited high expression pattern in CRC samples along with cells. Silencing of WTAP potently restrained the growth of CRC tumorigenesis in virto and in vivo. Mechanically, SOD2 was identified as an m6A target of WTAP. WTAP‐mediated m6A modification of SOD2 mRNA elevated its stability in an IGF2BP3‐dependent manner. Meanwhile, SOD2 overexpression could reverse the tumor suppressive effect induced by WTAP silencing. Molecular therapy targeting WTAP‐SOD2 may offer novel insights and perspectives for the treatment of CRC.

Infrared imaging with visible light in microfluidic devices: the water absorption barrier.

Infrared spectro-microscopy is a powerful technique for analysing chemical maps of cells and tissues for biomedical and clinical applications, yet the strong water absorption in the mid-infrared region is a challenge to overcome, as it overlaps with the spectral fingerprints of biological components. Microfluidic chips offer ultimate control over the water layer thickness and are increasingly used in infrared spectro-microscopy. However, the actual impact of the water layer thickness on the instrument's performance is often left to the experimentalist's intuition and the peculiarities of specific instruments. Aiming to experimentally test the amount of absorption introduced by water with varying layer thicknesses, we fabricated a set of microfluidic devices with three controlled chamber thicknesses, each comprising a simple test pattern made of a well-known photoresist SU-8. We employed two infrared spectro-microscopy methods for measurements. The first method involves using a standard FTIR microscope with a benchtop infrared light source. The second method is a quantum infrared microscopy technique, where infrared imaging is achieved by detecting correlated photons in the visible range. We demonstrated that both methods enable the measurement of the absorption spectrum in the mid-IR region, even in the presence of up to a 30 μm thick water layer on top of a sample pattern. Additionally, the Q-IR technique offers practical advantages over synchrotron-based FTIR, such as reduced complexity, cost, and ease of operation.

Immunogenic Cell Death Traits Emitted from Chronic Lymphocytic Leukemia Cells Following Treatment with a Novel Anti-Cancer Agent, SpiD3.

Background: Targeted therapies (e.g., ibrutinib) have markedly improved chronic lymphocytic leukemia (CLL) management; however, ~20% of patients experience disease relapse, suggesting the inadequate depth and durability of these front-line strategies. Moreover, immunotherapeutic success in CLL has been stifled by its pro-tumor microenvironment milieu and low mutational burden, cultivating poor antigenicity and limited ability to generate anti-tumor immunity through adaptive immune cell engagement. Previously, we have demonstrated how a three-carbon-linker spirocyclic dimer (SpiD3) promotes futile activation of the unfolded protein response (UPR) in CLL cells through immense misfolded-protein mimicry, culminating in insurmountable ER stress and programmed CLL cell death. Method: Herein, we used flow cytometry and cell-based assays to capture the kinetics and magnitude of SpiD3-induced damage-associated molecular patterns (DAMPs) in CLL cell lines and primary samples. Result: SpiD3 treatment, in vitro and in vivo, demonstrated the capacity to propagate immunogenic cell death through emissions of classically immunogenic DAMPs (CALR, ATP, HMGB1) and establish a chemotactic gradient for bone marrow-derived dendritic cells. Conclusions: Thus, this study supports future investigation into the relationship between novel therapeutics, manners of cancer cell death, and their contributions to adaptive immune cell engagement as a means for improving anti-cancer therapy in CLL.

Visual Sampling Patterns in a Naturalistic Setting for Toddlers with Autism

Visual Sampling Patterns in a Naturalistic Setting for Toddlers with Autism

An Epigenetic Locus Associated with Loss of Smell in COVID-19.

Loss of smell, also known as anosmia, is a prevalent and often prolonged symptom following infection with SARS-CoV-2. While many patients regain olfactory function within weeks, a significant portion experience persistent anosmia lasting over a year post-infection. The underlying mechanisms responsible for this sensory deficit remain largely uncharacterized. Previous studies, including genome-wide association studies (GWAS), have identified genetic variants near the UGT2A1 and UGT2A2 genes that are linked to anosmia in COVID-19 patients. However, the role of epigenetic changes in the development and persistence of smell loss has not been well explored. In this study, we aimed to investigate epigenetic alterations in the form of DNA methylation in the UGT1A1 gene, which is a locus associated with olfactory dysfunction in COVID-19 patients. We analysed DNA methylation patterns in blood samples from two carefully matched cohorts of 20 COVID-19 patients each, which are differentiated by their olfactory function-those with normal smell (normosmia) and those suffering from smell loss (anosmia). The cohorts were matched for age and sex to minimize potential confounding factors. Using quantitative analysis, we found significantly lower levels of DNA methylation in the UGT1A1 locus in the anosmia group compared to the normosmia group, with a 14% decrease in median methylation values in patients with smell loss (p < 0.0001). These findings highlight potential epigenomic alterations in the UGT1A1 gene that may contribute to the pathogenesis of anosmia following COVID-19 infection. Our results suggest that the methylation status at this locus could serve as a biomarker for olfactory dysfunction in affected individuals. This study is among the first to describe epigenetic changes associated with smell loss in COVID-19, providing a foundation for future research into targeted interventions and potential therapeutic strategies aimed at reversing persistent anosmia. Further investigations involving larger cohorts and additional loci may help elucidate the complex interaction between genetic, epigenetic, and environmental factors influencing long-term sensory impairment post-COVID-19.

Exploring G Protein-Coupled Receptors in Hematological Cancers.

Hematological cancers, such as lymphomas and leukemias, pose significant challenges in oncology, necessitating a deeper understanding of their molecular landscape to enhance therapeutic strategies. This article critically examines and discusses recent research on the roles of G protein-coupled receptors (GPCRs) in myeloma, lymphomas, and leukemias with a particular focus on pediatric acute lymphoblastic (lymphocytic) leukemia (ALL). By utilizing RNA sequencing (RNA-seq), we analyzed GPCR expression patterns in pediatric ALL samples (aged 3-12 years old), with a further focus on Class A orphan GPCRs. Our analysis revealed distinct GPCR expression profiles in pediatric ALL, identifying several candidates with aberrant upregulated expression compared with healthy counterparts. Among these GPCRs, GPR85, GPR65, and GPR183 have varying numbers of studies in the field of hematological cancers and pediatric ALL. Furthermore, we explored missense mutations of pediatric ALL in relation to the RNA gene expression findings, providing insights into the genetic underpinnings of this disease. By integrating both RNA-seq and missense mutation data, this article aims to provide an insightful and broader perspective on the potential correlations between specific GPCR and their roles in pediatric ALL.

An improved method for whole-mount in situ hybridization in regenerating tails of Xenopus laevis tadpoles

Whole-mount in situ hybridization (WISH) is a widely used method that supports the concept of “seeing is believing” by enabling the visualization of gene expression patterns in whole-mount multicellular samples or sections. This technique is essential in the study of epimorphic regeneration in cold-blooded vertebrates, where complex three-dimensional organs such as tails, limbs, and eyes are completely restored after loss. The tadpoles of the frog X. laevis serve as a convenient model for studying regeneration, as they can regenerate their tails within a week after amputation. Modern high-throughput sequencing methods have identified various cell populations involved in the regeneration process and determined the repertoire of genes activated during this time. Specifically, a population of reparative myeloid cells expressing mmp9 as a marker gene has been shown to be crucial for the initial stages of tail regeneration in X. laevis tadpoles. The validation of these data and further examination using WISH offers the advantage of providing detailed information on the spatial and temporal dynamics of target gene expression levels. However, detecting mRNA by WISH can be challenging when mRNA levels are very low, transcripts are localized in hard-to-access areas, or tissue samples are prone to background staining, as is the case with X. laevis regenerating tail samples. Here, we describe additional treatments for regenerating tail samples that minimize background staining and enhance the visualization of cells containing target RNA through in situ hybridization. Using an optimized WISH protocol on X. laevis tadpole tail regenerates, we obtained novel data on the mmp9 expression pattern during the first day post-amputation at the regeneration-competent stage 40 and the regeneration-incompetent stage 47 (refractory period). The significant differences in the expression patterns indicate that mmp9 activity is positively correlated with regeneration competence.

A feedback-driven brain organoid platform enables automated maintenance and high-resolution neural activity monitoring.

The analysis of tissue cultures, particularly brain organoids, requires a sophisticated integration and coordination of multiple technologies for monitoring and measuring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Our approach enables continuous, communicative, non-invasive interactions within an Internet of Things (IoT) architecture among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids while measuring their neuronal activity. The organoids are cultured in custom, 3D-printed chambers affixed to commercial microelectrode arrays. Periodic feeding is achieved using programmable microfluidic pumps. We developed a computer vision fluid volume estimator used as feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a set of 7-day studies of mouse cerebral cortex organoids, comparing manual and automated protocols. The automated protocols were validated in maintaining robust neural activity throughout the experiment. The automated system enabled hourly electrophysiology recordings for the 7-day studies. Median neural unit firing rates increased for every sample and dynamic patterns of organoid firing rates were revealed by high-frequency recordings. Surprisingly, feeding did not affect firing rate. Furthermore, performing media exchange during a recording showed no acute effects on firing rate, enabling the use of this automated platform for reagent screening studies.

Single-pixel imaging through scattering media employing a circular polarization multiplexing metasurface

We propose a scheme of single-pixel imaging through scattering media employing an all-dielectric metasurface, which provides the functions of circular polarization multiplexing and random sampling for single-pixel imaging simultaneously. The former and latter functions are implemented through focusing two orthogonal circular polarization lights with different focal lengths and relative displacements of the metasurface, respectively. Numerical simulations are performed to demonstrate the performance of the metasurface. Whereafter, we simulate the target images projected onto the metasurface and single-pixel imaging reconstructions with these simulated sampling patterns by using the Monte Carlo method, thereby verifying the proposed approach. This technology holds significant potential for applications in microscopic imaging and biological tissue recognition.