Biological Conditions Research Articles

Floristic composition and phenology of vegetation in district Dir Lower, Khyber Pakhtunkhwa, Pakistan

The present study explores the floristic composition and phenology of vegetation in district Dir Lower, Khyber Pakhtunkhwa, Pakistan. This district features diverse biological and climatic conditions, creating a unique environment for ecological studies. The research was conducted from May to November in 2018 and 2019, documenting 206 plant species across 182 genera and 82 families. The dominant families were Lamiaceae, Asteraceae, and Poaceae. Using Raunkaier’s life form classification, the study found a dominance of therophytes (41%) and nanophanerophytes (13%), indicating the local ecosystem’s adaptation to annual climatic changes. In terms of leaf size spectrum, microphylls were the most abundant (39%), followed by mesophylls (27%) and Nanophylls (22%). The distribution of plant species in the research area reflects the adaptation of the local flora to specific environmental conditions. Phenological observations revealed two distinct flowering seasons: the primary season from May to August and the secondary season from September to November. During the first season, the majority of plants (85%), predominantly herbs, were in bloom. In contrast, the second season showed a smaller diversity of blooming plants, including six fern species. Fruiting patterns mirrored the flowering trends, with a higher fruiting rate observed from May to August (106 species) compared to September to November (100 species). This research provides a comprehensive overview of the floristic diversity, biological spectrum, and phenological patterns in district Dir Lower, contributing valuable information to plant ecology and conservation in the region.

Taylor's law on abundance unravels the role of traits and environmental conditions on population dynamics.

The variance-mean scaling in population abundance or Taylor's power law (TPL) has been reported hundreds of times and is related to ecological processes such as competition, dispersal or territoriality. In this sense, the TPL was extensively validated to resume population variability and to show the action of ecological mechanisms. Baumgartner and Peláez (2024) combine databases of fish dynamics along the United States, species traits, species phylogeny and climatic conditions, estimating the TPL for 180 species along 972 populations. The observed scaling suggests that the variability of the population decreases with abundance. Notably, 68% of the variation in the variance-mean scaling was explained by species traits and environmental conditions. Specifically, the life history of the species, associated with its body size, was the main explanation for the TPL, also reporting that the variability of the population increased faster with mean abundance in the headwaters than in other river sections. Equally important, the diversity of the community in which the species were inserted did not affect the scaling. These results provide overwhelming evidence on the nature of TPL on large geographic scales and how they are affected by species biology and environmental conditions. A contribution that should motivate further empirical and theoretical analysis of the TPL and its determinants.

CLONAL HEMATOPOIESIS AND ITS ROLE IN THE DEVELOPMENT OF CARDIOVASCULAR DISEASES

Clonal hematopoiesis (CH) is the increase in somatic clones carrying mutations in hematopoietic stem cells. This biological condition can lead to cancer and is implicated in the development of atherosclerosis and cardiovascular diseases. CH of indeterminate potential (CHIP) refers to somatic mutations in genes that are associated with the development of Coronary heart disease (CHD) and leukemia. Now, with next-generation sequencing, we can detect mutations even if they are present in only a small number of cells in the tissue sample being studied. Consequently, numerous studies have shown that mutations in the DNMT3A, TET2, ASXL1, and JAK2 genes found in the blood are associated with coronary heart disease. The purpose of our study is to detect a genetic variant of genes in Kazakh patients with atherosclerosis, which will further allow us to study the role of CHIP in increasing the risk of developing coronary microvascular dysfunction and CHD. We perform high-throughput whole-exome sequencing in patients with atherosclerosis. The object of the study is samples delivered from the clinic “National Scientific Cardiac Surgery Center” in Astana. The study is carried out in accordance with the principles of the Declaration of Helsinki of the World Medical Association. Genomic DNA extraction was performed on 245 samples using the Illustra Blood Kit (Cytiva, USA). Qualitative and quantitative assessment of the extracted genomic DNA was conducted using the NanoDrop 2000 (Thermo Scientific) and Qubit 2.0 (Thermo Fisher Scientific). Subsequently, DNA library preparation was carried out using the Illumina DNA Prep with Exome 2.5 Enrichment kit. Quality control of the resulting DNA libraries was conducted on a 2100 Bioanalyzer system using the Agilent DNA 1000 Kit and High Sensitivity DNA kit (Agilent Technologies). Following assessment of the DNA library concentration on Qubit 2.0, they were loaded onto the high-performance sequencer NovaSeq 6000 (Illumina, USA) following the manufacturer’s protocol. We conducted human whole-exome sequencing on 245 samples to identify somatic clones in the peripheral blood of patients with atherosclerosis. Patients were divided into three groups – low risk, middle, and high risk of atherosclerotic complications. Bioinformatic analysis of sequence data were performed. We created list of genes associated with CH to deep analysis and to interpreter the data in patient groups. Subsequently, DNA extraction from the remaining samples is performed, followed by sequencing on the NovaSeq 6000 platform. Analysis of the resulting sequenced data is currently underway. Further research and monitoring of CHIP will enable us to understand the mechanisms underlying the development of cardiovascular diseases and to devise a comprehensive management plan for patients with this pathology. Supported by Committee of Science of the Ministry of Science and Higher Education of Republic of Kazakhstan (AP14869903), (BR21881970) and Nazarbayev University CRP (211123CRP1608).

Exploring Cannabis sativa L for Anti-Alzheimer Potential: An Extensive Computational Study including Molecular Docking, Molecular Dynamics, and ADMET Assessments

Introduction: Cholinesterase enzymes play a pivotal role in hydrolyzing acetylcholine, a neurotransmitter crucial for memory and cognition, into its components, acetic acid, and choline. A primary approach in addressing Alzheimer's disease symptoms is by inhibiting the action of these enzymes. Method: With this context, our study embarked on a mission to pinpoint potential Cholinesterase (ChE) inhibitors using a comprehensive computational methodology. A total of 49 phytoconstituents derived from Cannabis sativa L underwent in silico screening via molecular docking, pharmacokinetic and pharmacotoxicological analysis, to evaluate their ability to inhibit cholinesterase enzymes. Out of these, two specific compounds, namely tetrahydrocannabivarin and Δ-9- tetrahydrocannabinol, belonging to cannabinoids, stood out as prospective therapeutic agents against Alzheimer's due to their potential as cholinesterase inhibitors. These candidates showcased commendable binding affinities with the cholinesterase enzymes, highlighting their interaction with essential enzymatic residues. objective: Our study aims to pinpoint potential Cholinesterase (ChE) inhibitors derived from Cannabis sativa L using molecular docking, pharmacokinetic, and pharmacotoxicological analysis. Result: They were predicted to exhibit greater binding affinities than Rivastigmine and Galantamine. Their ADMET assessments further classified them as viable oral pharmaceutical drugs. They are not expected to induce any mutagenic or hepatotoxic effects and cannot produce skin sensitization. In addition, these phytoconstituents are predicted to be BBB permeable and can reach the central nervous system (CNS) and exert their therapeutic effects. To delve deeper, we explored molecular dynamics (MD) simulations to examine the stability of the complex formed between the best candidate (Δ-9-tetrahydrocannabinol) and the target proteins under simulated biological conditions. The MD study affirmed that the ligand-ChE recognition is a spontaneous reaction leading to stable complexes Conclusion: Our research outcomes provide valuable insights, offering a clear direction for the pharmaceutical sector in the pursuit of effective anti-Alzheimer treatments.

Integrating DIA Single-Cell Proteomics Data with the DiagnoMass Proteomic Hub for Biological Insights.

Single-cell proteomics has emerged as a powerful technology for unraveling the complexities of cellular heterogeneity, enabling insights into individual cell functions and pathologies. One of the primary challenges in single-cell proteomics is data generation, where low mass spectral signals often preclude the triggering of MS2 events. This challenge is addressed by Data Independent Acquisition (DIA), a data acquisition strategy that does not depend on peptide ion isotopic signatures to generate an MS2 event. In this study, we present data generated from the integration of DIA single-cell proteomics with a version of the DiagnoMass Proteomic Hub that was adapted to handle DIA data. DiagnoMass employs a hierarchical clustering methodology that enables the identification of tandem mass spectral clusters that are discriminative of biological conditions, thereby reducing the reliance on search engine biases for identifications. Nevertheless, a search engine (in this work, DIA-NN) can be integrated with DiagnoMass for spectral annotation. We used single-cell proteomic data from iPSC-derived neuroprogenitor cell cultures as a test study of this integrated approach. We were able to differentiate between control and Rett Syndrome patient cells to discern the proteomic variances potentially contributing to the disease's pathology. Our research confirms that the DiagnoMass-DIA synergy significantly enhances the identification of discriminative proteomic signatures, highlighting critical biological variations such as the presence of unique spectra that could be related to Rett Syndrome pathology.

Biomimetic synthetic test system based on hydroxyapatite cement for adhesive strength evaluation of experimental mineral-organic bone adhesive materials.

The development of bone adhesive materials is a research field of high relevance for the advancement of clinical procedures. Despite this, there are currently no material candidates meeting the full range of requirements placed on such a material, such as biocompatibility, sufficient mechanical properties and bond strength under biological conditions, practical applicability in a clinical setting, and no adverse effect on the healing process itself. A serious obstacle to the advancement of the field is a lack in standardized methodology leading to comparable results between experiments and different research groups. Natural bone samples are the current gold-standard material used to perform adhesive strength experiments, however they come with a number of drawbacks, including high sample variability due to unavoidable natural causes and the impossibility to reliably recreate test conditions to repeat experiments. This paper introduces a valuable auxiliary test method capable of producing large numbers of synthetic test specimens which are chemically similar to bone and can be produced in different laboratories so to repeat experiments under constant conditions across laboratories. The substrate is based on a hydroxyapatite forming cement with addition of gelatine as organic component. Crosslinking of the organic component is performed to improve mechanical properties. In order to demonstrate the performance of the developed method, various experimental and commercial bone/tissue adhesive materials were tested and compared with results obtained by established methods to highlight the potential of the test system.

Interference with Systemic Negative Feedback Regulation as a Potential Mechanism for Nonmonotonic Dose-Responses of Endocrine-Disrupting Chemicals.

Endocrine-disrupting chemicals (EDCs) often exhibit nonmonotonic dose-response (NMDR) relationships, posing significant challenges to health risk assessment and regulations. Several molecular mechanisms operating locally in cells have been proposed, including opposing actions via different receptors, mixed-ligand heterodimer formation, and receptor downregulation. Systemic negative feedback regulation of hormone homeostasis, which is a common feature of many endocrine systems, has also been invoked as a mechanism; however, whether and how exactly such global feedback structure may underpin NMDRs is poorly understood. We hypothesize that an EDC may compete with the endogenous hormone for receptors (i) at the central site to interfere with the feedback regulation thus altering the physiological hormone level, and (ii) at the peripheral site to disrupt the hormone action; this dual-action may oppose each other, producing nonmonotonic endocrine effects. The objective here is to explore - through computational modeling - how NMDRs may arise through this potential mechanism and the relevant biological variabilities that enable susceptibility to nonmonotonic effects. We constructed a dynamical model of a generic hypothalamic-pituitary-endocrine (HPE) axis with negative feedback regulation between a pituitary hormone and a terminal effector hormone (EH). The effects of model parameters, including receptor binding affinities and efficacies, on NMDR were examined for EDC agonists and antagonists. Monte Carlo human population simulations were then conducted to systemically explore biological parameter conditions that engender NMDR. When an EDC interferes sufficiently with the central feedback action of EH, the net endocrine effect at the peripheral target site can be opposite to what is expected of an agonist or antagonist at low concentrations. J/U or Bell-shaped NMDRs arise when the EDC has differential binding affinities and/or efficacies, relative to EH, for the peripheral and central receptors. Quantitative relationships between these biological variabilities and associated distributions were discovered, which can distinguish J/U and Bell-shaped NMDRs from monotonic responses. The ubiquitous negative feedback regulation in endocrine systems can act as a universal mechanism for counterintuitive and nonmonotonic effects of EDCs. Depending on key receptor kinetic and signaling properties of EDCs and endogenous hormones, some individuals may be more susceptible to these complex endocrine effects.

Long-term monitoring of water quality and phytoplankton community structure of Lake Manzala, Mediterranean Coast of Egypt

Coastal wetlands play a crucial role in supporting biodiversity, providing valuable ecosystem services, and contributing to the resilience of coastal ecosystems, making the preservation and restoration of these wetlands essential for sustainable development in coastal regions. This study focuses on Lake Manzala, a coastal wetland located on the Mediterranean Coast of Egypt, highlighting the significance of conserving and managing this unique environment. The objective of this research was to evaluate the water quality and phytoplankton structure of Lake Manzala and establish an updated long-term ecological database for the region, specifically evaluating the effectiveness of development plans that were carried out in 2017. Surface water samples were collected seasonally at eleven sites between 2010 to 2022. The findings revealed that prior to the development plans, the phytoplankton abundance in Lake Manzala exhibited high levels of eutrophication, characterized by increased abundance and species richness. The dominant phytoplankton classes in Lake Manzala were Bacillariophyceae, Chlorophyceae, and Cyanophyceae. Prior to development plans, they accounted for 46.5% and 45.0% respectively. Post-development, Bacillariophyceae increased to 62.8%, while Chlorophyceae decreased to 25.1%. Dinophyceae increased from 1.3% to 9.04%, while Cyanophyceae decreased from 6.1% to 1.6%. Based on the Trophic State Index for chlorophyll a, Lake Manzala underwent a shift from predominantly hypertrophic to eutrophic conditions. The study explored the relationship between biological factors and environmental conditions using principal component analysis, cluster analysis, and the modified water quality index (WQI). The results indicated positive signs of improvement in Lake Manzala during the post-development phase, as it transitioned from a poor to a moderate state. This research emphasizes the need for integrated land and water management approaches. By informing policy direction and development, this research underscores the importance of preserving and restoring ecosystems for the long-term well-being of both local communities and the global environment.

Evaluation of the Amount of Endophytic Bacteria Associated with Roots of Brachiaria Humidicola Cv. Humidicola (Rendle) Schweick in Relation to Ph Values, Organic Matter and Phosphorus Contents of Cattle Farm Soil

The objective of this study was to isolate endophytic bacteria from roots of Brachiaria humidicola cv. humidicola (Rendle) Schweick and to relate their presence to pH, organic matter and phosphorus contents of the soil of cattle farms located in the municipality of San Benito Abad. Soil sampling was carried out with roots of B. humicola for the isolation and counting of the population density of endophytic bacteria and soil samples were also collected for the determination of pH, organic matter and phosphorus parameters. The results found indicate that there is an amount of endophytic bacteria in roots of B. humidicola when the soil contains optimum pH values of (6.1 ± 6.98); low to moderate phosphorus content (10.8 ± 16.28 mg/kg) and low to moderate organic matter content (1.7 ± 2.31%). The presence of endophytic bacteria was observed in a range of 3.0 ± 8.0 X 106 CFU/g of roots. There is a worldwide need to establish a relationship between endophytic bacteria and soil physical-chemical quality indicator parameters to predict a change in functional diversity under physical, chemical and biological conditions of the soil ecosystem.

Species diversity of mosquitoes (Diptera: Culicidae), larval habitat characteristics, and potential as vectors for lymphatic filariasis in Central Bengkulu Regency, Indonesia.

Lymphatic filariasis (LF) is a vector-borne disease in various regions of Indonesia. The transmission dynamics within a locality are intricately linked to the presence of the pathogen (microfilaria), definitive host (humans), intermediate host (mosquitoes), reservoir, and environmental factors. The geographic landscape of Central Bengkulu Regency, which is characterized by plantations, marshlands, and forests, serves as a suitable habitat for mosquitoes. Understanding species diversity, vector behaviors, habitat characteristics, and microfilarial presence is crucial for devising effective and efficient control strategies. This study aimed to identify species diversity, assess biting patterns, characterize larval habitats, and detect microfilarial presence in mosquitoes. Mosquito collection was conducted using human landing collection (HLC) and resting collection indoors and outdoors for 6 months at a frequency of twice monthly from November 2022 to May 2023. The larvae were collected using dippers and pipettes. Adult mosquitoes and larvae were identified at the species level and analyzed using diversity indices. The measured larval bioecological parameters included physical, chemical, and biological conditions. The mosquito density obtained through HLC was calculated using the man-hour density (MHD) and man-biting rate (MBR) formulas. The presence of microfilaria was confirmed using a polymerase chain reaction. A total of 808 adult mosquitoes from five genera and 18 species were captured, along with 485 larvae from four genera and eight species. The mosquito diversity was moderate. The dominant adult species included Armigeres subalbatus (44.8%), whereas Aedes albopictus (25.4%) and Ar. subalbatus (22.3%) were abundant larvae. The highest larval density was observed in natural ponds. The average MBR was three mosquitoes per person per night, with fluctuating nightly activity (mean MHD of 1.8 mosquitoes per person per hour). Larval habitats had temperatures of 25.4°C-28.7°C, illumination of 224-674 lx, and pH of 7.1-7.9, with over half being turbid and nearly two-thirds lacking predators. Microfilariae were not detected in the tested mosquitoes. The presence of mosquitoes, their habitat, and the high density of Ar. subalbatus contributes to the transmission of LF in Central Bengkulu Regency, Indonesia.

Increased Growth of RED Jabon (Anthocephalus macrophyllus) Seedlings using Various Doses of Compost Fertiliser on Used Gold Mine Planting Media

Mining operations disrupt the equilibrium of terrestrial ecosystems, leading to a decline in soil fertility and overall environmental quality. The adverse effects of such activities can severely impact forest ecosystems, resulting in disturbances to physical, chemical, and biological conditions. Consequently, initiatives aimed at restoring soil health to its pre-mining state are essential, often involving revegetation efforts. The cultivation of red jabon trees in nutrient-deficient and less fertile soils necessitates the incorporation of organic matter to enhance soil quality, typically achieved through the application of compost. This study aimed to evaluate the effects and optimal ratios of compost mixed with ex-gold mining soil on the growth of red jabon seedlings. The experimental design included four treatment groups and five replications, yielding a total of 20 experimental units. The treatments for compost application were as follows: D1 = control (no compost), D2 = 10% compost + 90% ex-gold mining soil, D3 = 30% compost + 70% ex-gold mining soil, and D4 = 50% compost + 50% ex-gold mining soil. The parameters observed included survival rate, height growth, diameter growth, dry weight of the plants, and root-to-crown ratio. The findings indicated that the application of compost significantly influenced the growth of red jabon seedlings. Notably, treatment D4 (50% compost + 50% ex-gold mining soil) yielded the most favorable results, achieving a survival rate of 100%, a height increase of 16.56 cm, a diameter increase of 2.21 mm, a dry weight of 40.73 g, and a root-to-crown ratio of 4.84.

Metadata-guided feature disentanglement for functional genomics.

With the development of high-throughput technologies, genomics datasets rapidly grow in size, including functional genomics data. This has allowed the training of large Deep Learning (DL) models to predict epigenetic readouts, such as protein binding or histone modifications, from genome sequences. However, large dataset sizes come at a price of data consistency, often aggregating results from a large number of studies, conducted under varying experimental conditions. While data from large-scale consortia are useful as they allow studying the effects of different biological conditions, they can also contain unwanted biases from confounding experimental factors. Here, we introduce Metadata-guided Feature Disentanglement (MFD)-an approach that allows disentangling biologically relevant features from potential technical biases. MFD incorporates target metadata into model training, by conditioning weights of the model output layer on different experimental factors. It then separates the factors into disjoint groups and enforces independence of the corresponding feature subspaces with an adversarially learned penalty. We show that the metadata-driven disentanglement approach allows for better model introspection, by connecting latent features to experimental factors, without compromising, or even improving performance in downstream tasks, such as enhancer prediction, or genetic variant discovery. The code will be made available at https://github.com/HealthML/MFD.

Biological, Psychological, Social, and Spiritual Domains of Teachers in a Philippine University

Countries worldwide have experienced an unprecedented event that changed the educational systems and suddenly forced our teachers to adopt online classes. This greatly affected our teacher's mental health. This study aimed to determine the harmony of the biological, psychological, social, and spiritual domains and also looked into the challenges encountered among university teachers during the COVID-19 pandemic. The findings served as bases for the intervention plan. The data were treated using frequency, rank, simple percentage, mean, standard deviation, rank, Chi-square test of independence, and ANOVA. Results showed teachers have poor health habits in the physical domain. In the area of the psychological domain, it showed that teachers experienced severe depression. Results of the spiritual domain suggest that teachers lack spiritual enrichment. In addition, the teachers in the social domain have warm relationships. The biological domain of teachers reveals a meaningful relationship with gender. Also, teachers' civil status is related to the social domain. Results also show that teachers can cope with resourcefulness, adjusting one's mindset and patience. Results show that teachers have biological conditions, severe psychological depression, warm social relationships with people around them, and less spiritual life after the COVID-19 pandemic. Therefore, it is recommended that an intervention plan be implemented, monitored, and evaluated to improve their living conditions while doing their job as facilitators of learning.

Comprehensive Screening and Validation of Stable Internal Reference Genes for Accurate qRT-PCR Analysis in Holotrichia parallela under Diverse Biological Conditions and Environmental Stresses.

Holotrichia parallela is among the world's most destructive pests. For accurate qPCR and gene expression studies, the selection of stable and appropriate reference genes is crucial. However, a thorough evaluation of potential reference genes for use in H. parallela research is lacking. In this study, 11 reference genes (GAPDH, RPL32, RPL7A, RPS18, RPL13a, RPL18, Actin, RPS7, RPS3, VATB,and EF1A) were evaluated under different biological conditions and environmental stresses. The stability of 11 potential reference gene transcripts was evaluated through various computational tools, including geNorm, BestKeeper, NormFinder, theΔCt method, and the RefFinder program. Under various developmental stages and RNAi conditions, RPL18 and RPL13a exhibited the greatest stability. RPL13a, RPL18, and RPL32 were the most stable genes in both male and female adults. Under differing tissue conditions, RPL13a and RPS3 stood out as the most reliable. Moreover, under varying photoperiod conditions, RPL13a, RPS3 and RPL32 were the most stable genes. Lastly, Actin and RPL13a were the most stable genes across different temperatures. These findings offer essential criteria for selecting suitable reference genes across diverse experimental settings, thereby establishing a solid basis for accurate gene expression studies in H. parallela using RT-qPCR.

Chitosan based hydrogel for iron (III) chelation in biological conditions

In this study, a chitosan derivative with strong iron (III) chelating capabilities was developed by grafting the Deferoxamine (DFO) chelator to achieve a substitution degree of 3.8 ± 0.2 %. Through blending with ungrafted chitosan of low degree of acetylation (DA), a formulation able to form a physical hydrogels was formed in aqueous media, without the requirement of a cross-linking agent. The functionalization of chitosan with DFO led to xerogels exhibiting superior iron (III) chelation capacity and higher swelling when exposed to aqueous solutions, in comparison with to an unmodified chitosan xerogel. Notably, this material extracts iron (III) even against the strong iron chelator deferiprone. Furthermore, the material demonstrates selectivity for iron (III) chelation even in the presence of competing cations like copper (II) and zinc (II).

Correlations of Long Noncoding RNA HNF4A-AS1 Alternative Transcripts with Liver Diseases and Drug Metabolism.

Hepatocyte nuclear factor 4 alpha antisense 1 (HNF4A-AS1) is a long noncoding RNA (lncRNA) gene physically located next to the transcription factor HNF4A gene in the human genome. Its transcription products have been reported to inhibit the progression of hepatocellular carcinoma (HCC) and negatively regulate the expression of cytochrome P450s (CYPs), including CYP1A2, 2B6, 2C9, 2C19, 2E1, and 3A4. By altering CYP expression, lncRNA HNF4A-AS1 also contributes to the susceptibility of drug-induced liver injury. Thus, HNF4A-AS1 lncRNA is a promising target for controlling HCC and modulating drug metabolism. However, HNF4A-AS1 has four annotated alternative transcripts in the human genome browsers, and it is unclear which transcripts the small interfering RNAs or small hairpin RNAs used in the previous studies are silenced and which transcripts should be used as the target. In this study, four annotated and two newly identified transcripts were confirmed. These six transcripts showed different expression levels in different liver disease conditions, including metabolic dysfunction-associated steatotic liver disease, alcohol-associated liver disease, and obesity. The expression patterns of all HNF4A-AS1 transcripts were further investigated in liver cell growth from human embryonic stem cells to matured hepatocyte-like cells, HepaRG differentiation, and exposure to rifampicin treatment. Several HNF4A-AS1 transcripts highly displayed correlations with these situations. In addition, some of the HNF4A-AS1 transcripts also showed a strong correlation with CYP3A4 during HepaRG maturation and rifampicin exposure. Our findings provide valuable insights into the specific roles of HNF4A-AS1 transcripts, paving the way for more targeted therapeutic strategies for liver diseases and drug metabolism. SIGNIFICANCE STATEMENT: This study explores the alternative transcripts of HNF4A-AS1, showing how their expression changes in different biological conditions, from various liver diseases to the growth and differentiation of hepatocytes and drug metabolism. The generated knowledge is essential for understanding the independent roles of different transcripts from the same lncRNA in different liver diseases and drug metabolism situations.

A Numerical Investigation of the Effects of Wave-Induced Soil Deformation on Solute Release from Submarine Sediments

The sustainable development of marine environments requires a deep understanding of their chemical and biological conditions. These are significantly impacted by the exchange of substances such as contaminants, heavy metals, and nutrients between marine sediments and the water column. Although the existing literature has addressed the physics of enhanced solute migration in sediment due to sea waves, the role of coupled flow and soil deformation has often been neglected. This study investigates the effects of wave-induced soil deformation on solute release from the marine sediment using a coupled numerical model that incorporates the effect of soil deformation into the advection–diffusion equation. The results reveal that solute release is notably accelerated in deformable sediments with a smaller shear modulus, with the longitudinal dispersion coefficient increasing up to five times as the shear modulus decreases from 108 Pa to 106 Pa. This enhancement is more pronounced in shallow sediments as the sediment permeability decreases, where the longitudinal dispersion coefficient in deformable sediments can be 15 times higher than that in non-deformable sediments at a hydraulic conductivity of 1 × 10−5 m/s. Furthermore, the rate of solute release increases with decreasing sediment saturation due to the compressibility of pore water, although this rate of increase gradually diminishes.

ScParser: sparse representation learning for scalable single-cell RNA sequencing data analysis

The rapid rise in the availability and scale of scRNA-seq data needs scalable methods for integrative analysis. Though many methods for data integration have been developed, few focus on understanding the heterogeneous effects of biological conditions across different cell populations in integrative analysis. Our proposed scalable approach, scParser, models the heterogeneous effects from biological conditions, which unveils the key mechanisms by which gene expression contributes to phenotypes. Notably, the extended scParser pinpoints biological processes in cell subpopulations that contribute to disease pathogenesis. scParser achieves favorable performance in cell clustering compared to state-of-the-art methods and has a broad and diverse applicability.

Toward Fully Automated Personalized Orthopedic Treatments: Innovations and Interdisciplinary Gaps.

Personalized orthopedic devices are increasingly favored for their potential to enhance long-term treatment success. Despite significant advancements across various disciplines, the seamless integration and full automation of personalized orthopedic treatments remain elusive. This paper identifies key interdisciplinary gaps in integrating and automating advanced technologies for personalized orthopedic treatment. It begins by outlining the standard clinical practices in orthopedic treatments and the extent of personalization achievable. The paper then explores recent innovations in artificial intelligence, biomaterials, genomic and proteomic analyses, lab-on-a-chip, medical imaging, image-based biomechanical finite element modeling, biomimicry, 3D printing and bioprinting, and implantable sensors, emphasizing their contributions to personalized treatments. Tentative strategies or solutions are proposed to address the interdisciplinary gaps by utilizing innovative technologies. The key findings highlight the need for the non-invasive quantitative assessment of bone quality, patient-specific biocompatibility, and device designs that address individual biological and mechanical conditions. This comprehensive review underscores the transformative potential of these technologies and the importance of multidisciplinary collaboration to integrate and automate them into a cohesive, intelligent system for personalized orthopedic treatments.

Unrolling the Invisible: Socio-Cultural Grounds of Child Mortality in the Slums of Dhaka

According to World Health Organization, there is an 85% decline in the recorded child deaths from 1971 in Bangladesh from 371.3 to 22.6 per 1000 live births. However, the rate of child mortality is still quite significant considering the growing development of Bangladesh. In maximum literatures, the prevalent reasons behind child mortality are portrayed as complete biological phenomena and medical conditions (e.g., asphyxia, prematurity, and low birth weight) for the children under the age of 5 in Bangladesh. This research focused on the reasons behind child mortality beyond the biological and medical conditions while stressing on finding the preventable causes of child mortality, through a systematic method of death study named Social Autopsy. Social autopsy refers to a structured qualitative research tool that aims at identifying social, behavioral, and health systems contributors to child deaths. Using this tool, the research has identified that multiple socio-cultural, structural, and behavioral conditions along with medical conditions for child mortality. The research was done in two of the biggest slum areas of Dhaka city: Hazaribagh and Kamrangir Char. 15 families who lost children under 5 years and 5 health care providers were interviewed with a semi-structured method to draw an inclusive picture of socio-cultural dynamics of child mortality. The data was analyzed manually through thematic analysis and narrative analysis which showed the interconnection of all the broader underlying reasons and a detailed impacts of specific causes of child mortality.