Molecular functions of microRNAs in colorectal cancer: recent roles in proliferation, angiogenesis, apoptosis, and chemoresistance.

MiRNAs (microRNAs) constitute a group of diminutive molecules of non-coding RNA intricately involved in regulating gene expression. This regulation is primarily accomplished through the binding of miRNAs to complementary sequences situated in the 3'-UTR of the messenger RNA (mRNA) target; as a result, they are degraded or repressed. The multifaceted biogenesis of miRNAs is characterized by a meticulously orchestrated sequence of events encompassing transcription, processing, transportation, and decay. Colorectal cancer stands as a pervasive and formidable ailment, afflicting millions across the globe. Colorectal cancer is not well diagnosed early, and metastasis rates are high, which results in low survival rates in advanced stages. The genesis and progression of colorectal cancer are subject to the influence of genetic and epigenetic factors, among which miRNAs play a pivotal role. When it comes to colorectal cancer, miRNAs have a dual character, depending on the genes they target, functioning as either tumor suppressors or oncogenes and the prevailing cellular milieu. Their impact extends to modulating critical facets of colorectal cancer pathogenesis, including proliferation, angiogenesis, apoptosis, chemoresistance, and radiotherapy response. The discernible potential of miRNAs which are used as biomarkers to diagnose colorectal cancer, prognosis, and treatment response has come to the forefront. Notably, miRNAs are easily found and detected readily in a variety of biological fluids, including saliva, blood, urine, and feces. This prominence is attributed to the inherent advantages of miRNAs over conventional biomarkers, including heightened stability, specificity, sensitivity, and accessibility. Various investigations have pinpointed miRNA signatures or panels capable of differentiating colorectal cancer patients from their healthy counterparts, predicting colorectal cancer stage and survival, and monitoring colorectal cancer recurrence and therapy response. Although there has been research on miRNAs in various diseases, there has been less research on miRNAs in cancer. Moreover, updated results of preclinical and clinical studies on miRNA biomarkers and drugs are required. Nevertheless, the integration of miRNAs as biomarkers for colorectal cancer is not devoid of challenges and limitations. These encompass the heterogeneity prevalent among colorectal cancer subtypes and stages, the variability in miRNA expression across different tissues and individuals, the absence of standardized methodologies for miRNA detection and quantification, and the imperative for validation through extensive clinical trials. Consequently, further research is imperative to conclusively establish the clinical utility and reliability of miRNAs as colorectal cancer biomarkers. MiR-21 demonstrates carcinogenic characteristics by targeting several tumor suppressor genes, which encourages cell division, invasion, and metastasis. On the other hand, by controlling the Wnt/ß-catenin pathway, the tumor suppressor miRNA miR-34a prevents CRC cell proliferation, migration, and invasion. Furthermore, in colorectal cancer, the miR-200 family increases chemotherapy sensitivity while suppressing epithelial-mesenchymal transition (EMT). As an oncogene, the miR-17-92 cluster targets elements of the TGF-ß signaling pathway to encourage the growth of CRC cells. Finally, miR-143/145, which is downregulated in CRC, influences apoptosis and the progression of the cell cycle. These miRNAs affect pathways like Wnt, TGF-ß, PI3K-AKT, MAPK, and EMT, making them potential clinical biomarkers and therapeutic targets. This review summarizes recent research related to miRNAs, their role in tumor progression and metastasis, and their potential as biomarkers and therapeutic targets in colorectal cancer. In addition, we combined miRNAs' roles in tumorigenesis and development with the therapy of CRC patients, leading to novel perspectives on colorectal cancer diagnosis and treatment.

Detection of haptoglobin and serum amyloid A as biomarkers in naturally infected Mycoplasma bovis calves.

The livestock sector of Pakistan is increasing rapidly and it plays important role both for rural community and national economy. It is estimated that almost 8 million rural people are involved in livestock rearing and earning about 35-40 % of their income from the livestock sector. Mycoplasma bovis (M. bovis) infection causes significant economic losses in dairy animals especially young calf in the form of clinical illnesses such as pneumonia, poly-arthritis, respiratory distress and mortality. M. bovis is hard to diagnose and control because of uneven disease appearance and it is usually noticed in asymptomatic animals. For the identification of M. bovis in sub-clinical and clinical samples, determination of acute phase proteins i.e., haptoglobin (Hp) and serum amyloid A (SAA) are important tools for the timely diagnosis of disease. Therefore, early diagnosis of disease and hemato-biochemical changes are considered beneficial tools to control the infectious agent to uplift the economy of the dairy farmers. For this purpose, blood samples were collected from 200 calves of Bovidae family. Serum was separated from blood samples to determine the concentration of Hp and SAA, while blood samples were processed to determine hematological changes in blood from calves by using hematological analyzer. The blood plasma obtained from the blood samples was processed to measure oxidative stress factors. Lungs tissues from slaughterhouses/ morbid calves were collected to observe histopathological changes. The results of present study indicated that level of SAA and Hp remarkably increased (P < 0.05) in M. bovis infected calves in comparison to healthy calves. The oxidative stress markers indicated that nitric oxide and MDA levels in the infected calves increased significantly (P < 0.05), while infected claves had considerably lower levels of superoxide dismutase, catalase and glutathione. These findings indicate that oxidative stress play role to increase the level of APPs, while monitoring of APPs levels may serve as a valuable addition to the clinical evaluation of naturally infected calves with M. bovis. The hematological parameters were decreased significantly (P < 0.05). Altogether, this study suggests that Hp and SAA are proposed as promising biomarkers for detecting naturally occurring M. bovis infection in calves.

Extracorporeal Shockwave for Intermittent Claudication and Quality of Life: A Randomized Clinical Trial.

Importance: Intermittent lower limb claudication limits function and quality of life. Supervised exercise programs are not readily available, and a noninvasive alternative is needed. Objective: To assess extracorporeal corporeal shockwave therapy in improving quality of life in patients with claudication. Design, Setting, and Participants: In this double-blind, placebo-controlled randomized clinical trial, patients in the outpatient setting at a single tertiary center for vascular surgery were randomized in a 1:1 ratio to extracorporeal shockwave therapy or placebo therapy with no shockwaves delivered. Recruitment was between June 2015 and January 2020, with 12-week follow-up ending in March 2020. A convenience sample of patients with claudication and conservative treatment requirements who refused or were unable to participate in supervised exercise were eligible. Patients receiving anticoagulation therapy or with an active cancer were excluded. Of 522 patients screened, 389 were eligible, 138 were enrolled, and 110 completed follow-up and were included in the primary analysis. Statistical analysis was completed by May 2021. Intervention: In the intervention group, patients received 100 impulses of 0.1mJ/mm/cm2 in an area of the gastrocnemius muscle 3 times weekly for 3 weeks. The steps for treatment were replicated for the control group without delivering the treatment. Main Outcomes and Measures: The primary outcome was the Physical Functioning domain of the 36-item Short-Form Quality of Life Questionnaire at 12-week follow-up. Secondary outcomes included walking distances, ankle brachial pressure index, and other quality-of-life measures. Results: Of 138 patients recruited and randomized, 92 (67%) were male, and the mean (SD) age of the study population was 67 (9.6) years. The intervention group had a significantly higher physical function score at 12 weeks (estimated median difference 3.8; 95% CI, 0.0-7.7; P = .03). However, this significance did not remain when adjusting for covariates. At 12 weeks, the intervention group had significantly longer pain-free and maximum walking distances (pain-free estimated median difference, 34.1, 95% CI, 11.4-56.8; P = .004; maximum estimated median difference, 51.4; 95% CI, 10.7-86.5; P = .01). Conclusions and Relevance: To our knowledge, this is the first double-blind, placebo-controlled, randomized clinical trial to consider extracorporeal shockwave therapy for the management of intermittent claudication. It demonstrated efficacy for walking distances, may have a positive effect on quality of life, and may provide a safe, noninvasive alternative therapy for patients with intermittent claudication. Trial Registration: ClinicalTrials.gov Identifier: NCT02652078.

Fractional epidemic model of coronavirus disease with vaccination and crowding effects.

Most of the countries in the world are affected by the coronavirus epidemic that put people in danger, with many infected cases and deaths. The crowding factor plays a significant role in the transmission of coronavirus disease. On the other hand, the vaccines of the covid-19 played a decisive role in the control of coronavirus infection. In this paper, a fractional order epidemic model (SIVR) of coronavirus disease is proposed by considering the effects of crowding and vaccination because the transmission of this infection is highly influenced by these two factors. The nonlinear incidence rate with the inclusion of these effects is a better approach to understand and analyse the dynamics of the model. The positivity and boundedness of the fractional order model is ensured by applying some standard results of Mittag Leffler function and Laplace transformation. The equilibrium points are described analytically. The existence and uniqueness of the non-integer order model is also confirmed by using results of the fixed-point theory. Stability analysis is carried out for the system at both the steady states by using Jacobian matrix theory, Routh-Hurwitz criterion and Volterra-type Lyapunov functions. Basic reproductive number is calculated by using next generation matrix. It is verified that disease-free equilibrium is locally asymptotically stable if R 0 < 1 and endemic equilibrium is locally asymptotically stable if R 0 > 1 . Moreover, the disease-free equilibrium is globally asymptotically stable if R 0 < 1 and endemic equilibrium is globally asymptotically stable if R 0 > 1 . The non-standard finite difference (NSFD) scheme is developed to approximate the solutions of the system. The simulated graphs are presented to show the key features of the NSFD approach. It is proved that non-standard finite difference approach preserves the positivity and boundedness properties of model. The simulated graphs show that the implementation of control strategies reduced the infected population and increase the recovered population. The impact of fractional order parameter α is described by the graphical templates. The future trends of the virus transmission are predicted under some control measures. The current work will be a value addition in the literature. The article is closed by some useful concluding remarks.

Macrophage-enriched novel functional long noncoding RNAs LRRC75A-AS1 and GAPLINC regulate polarization and innate immune responses.

INTRODUCTION: Macrophages (Mφs) are functionally dynamic immune cells that bridge innate and adaptive immune responses; however, the underlying epigenetic mechanisms that control Mφ plasticity and innate immune functions are not well elucidated. OBJECTIVE: To identify novel functions of macrophage-enriched lncRNAs in regulating polarization and innate immune responses. METHODS: Total RNA isolated from differentiating monocyte-derived M1 and M2 Mφs was profiled for lncRNAs expression using RNAseq. Impact of LRRC75A-AS1, GAPLINC and AL139099.5 knockdown was examined on macrophage differentiation, polarization markers, phagocytosis, and antigen processing by flow cytometry and florescence microscopy. Cytokine profiles were examined by multiplex bead array and cytoskeletal signaling pathway genes were quantified by PCR-based array. Gingival biopsies were collected from periodontally healthy and diseased subjects to examine lncRNAs, M1/M2 marker expression. RESULTS: Transcriptome profiling of M1 and M2 Mφs identified thousands of differentially expressed known and novel lncRNAs. We characterized three Mφ-enriched lncRNAs LRRC75A-AS1, GAPLINC and AL139099.5 in polarization and innate immunity. Knockdown of LRRC75A-AS1 and GAPLINC downregulated the Mφ differentiation markers and skewed Mφ polarization by decreasing M1 markers without a significant impact on M2 markers. LRRC75A-AS1 and GAPLINC knockdown also attenuated bacterial phagocytosis, antigen processing and inflammatory cytokine secretion in Mφs, supporting their functional role in potentiating innate immune functions. Mechanistically, LRRC75A-AS1 and GAPLINC knockdown impaired Mφ migration by downregulating the expression of multiple cytoskeletal signaling pathways suggesting their critical role in regulating Mφ migration. Finally, we showed that LRRC75A-AS1 and GAPLINC were upregulated in periodontitis and their expression correlates with higher M1 markers suggesting their role in macrophage polarization in vivo. CONCLUSION: Our results show that polarized Mφs acquire a unique lncRNA repertoire and identified many previously unknown lncRNA sequences. LRRC75A-AS1 and GAPLINC, which are induced in periodontitis, regulate Mφ polarization and innate immune functions supporting their critical role in inflammation.

Correction: Facile fabrication of a graphene-based chemical sensor with ultrasensitivity for nitrobenzene.

[This corrects the article DOI: 10.1039/D3RA08794H.].

iAFPs-Mv-BiTCN: Predicting antifungal peptides using self-attention transformer embedding and transform evolutionary based multi-view features with bidirectional temporal convolutional networks.

Globally, fungal infections have become a major health concern in humans. Fungal diseases generally occur due to the invading fungus appearing on a specific portion of the body and becoming hard for the human immune system to resist. The recent emergence of COVID-19 has intensely increased different nosocomial fungal infections. The existing wet-laboratory-based medications are expensive, time-consuming, and may have adverse side effects on normal cells. In the last decade, peptide therapeutics have gained significant attention due to their high specificity in targeting affected cells without affecting healthy cells. Motivated by the significance of peptide-based therapies, we developed a highly discriminative prediction scheme called iAFPs-Mv-BiTCN to predict antifungal peptides correctly. The training peptides are encoded using word embedding methods such as skip-gram and attention mechanism-based bidirectional encoder representation using transformer. Additionally, transform-based evolutionary features are generated using the Pseduo position-specific scoring matrix using discrete wavelet transform (PsePSSM-DWT). The fused vector of word embedding and evolutionary descriptors is formed to compensate for the limitations of single encoding methods. A Shapley Additive exPlanations (SHAP) based global interpolation approach is applied to reduce training costs by choosing the optimal feature set. The selected feature set is trained using a bi-directional temporal convolutional network (BiTCN). The proposed iAFPs-Mv-BiTCN model achieved a predictive accuracy of 98.15 % and an AUC of 0.99 using training samples. In the case of the independent samples, our model obtained an accuracy of 94.11 % and an AUC of 0.98. Our iAFPs-Mv-BiTCN model outperformed existing models with a ~4 % and ~5 % higher accuracy using training and independent samples, respectively. The reliability and efficacy of the proposed iAFPs-Mv-BiTCN model make it a valuable tool for scientists and may perform a beneficial role in pharmaceutical design and research academia.

Surgical Interventions in Chronic Pancreatitis: A Systematic Review of Their Impact on Quality of Life.

This systematic review evaluates the efficacy of surgical interventions in improving the quality of life for patients with chronic pancreatitis (CP). A thorough literature search, following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, identified 11 studies that focused on patient-reported outcomes after surgical treatments, including pancreatic resections, drainage procedures, and duodenum-preserving head resections. The findings indicate that organ-preserving procedures, notably the Frey and Beger operations, significantly enhance pain control and overall quality of life while reducing analgesic dependency. This review provides crucial insights into the long-term efficacy and comparative benefits of different surgical approaches, highlighting the need for personalized surgical strategies in CP management. It emphasizes the necessity for standardized outcome measures and further comparative research to refine CP treatment protocols.

Designing future peanut: the power of genomics-assisted breeding.

KEY MESSAGE: Integrating GAB methods with high-throughput phenotyping, genome editing, and speed breeding hold great potential in designing future smart peanut cultivars to meet market and food supply demands. Cultivated peanut (Arachis hypogaea L.), a legume crop greatly valued for its nourishing food, cooking oil, and fodder, is extensively grown worldwide. Despite decades of classical breeding efforts, the actual on-farm yield of peanut remains below its potential productivity due to the complicated interplay of genotype, environment, and management factors, as well as their intricate interactions. Integrating modern genomics tools into crop breeding is necessary to fast-track breeding efficiency and rapid progress. When combined with speed breeding methods, this integration can substantially accelerate the breeding process, leading to faster access of improved varieties to farmers. Availability of high-quality reference genomes for wild diploid progenitors and cultivated peanuts has accelerated the process of gene/quantitative locus discovery, developing markers and genotyping assays as well as a few molecular breeding products with improved resistance and oil quality. The use of new breeding tools, e.g., genomic selection, haplotype-based breeding, speed breeding, high-throughput phenotyping, and genome editing, is probable to boost genetic gains in peanut. Moreover, renewed attention to efficient selection and exploitation of targeted genetic resources is also needed to design high-quality and high-yielding peanut cultivars with main adaptation attributes. In this context, the combination of genomics-assisted breeding (GAB), genome editing, and speed breeding hold great potential in designing future improved peanut cultivars to meet market and food supply demands.

Valency based novel quantitative structure property relationship (QSPR) approach for predicting physical properties of polycyclic chemical compounds.

In this study, we introduce a novel valency-based index, the neighborhood face index (NFI), designed to characterize the structural attributes of benzenoid hydrocarbons. To assess the practical applicability of NFI, we conducted a linear regression analysis utilizing numerous physiochemical properties associated with benzenoid hydrocarbons. Remarkably, the results revealed an extraordinary correlation exceeding 0.9991 between NFI and these properties, underscoring the robust predictive capability of the index. The NFI, identified as the best-performing descriptor, is subsequently investigated within certain infinite families of carbon nanotubes. This analysis demonstrates the index's exceptional predictive accuracy, suggesting its potential as a versatile tool for characterizing and predicting properties across diverse molecular structures, particularly in the context of carbon nanotubes.

Deepstacked-AVPs: predicting antiviral peptides using tri-segment evolutionary profile and word embedding based multi-perspective features with deep stacking model.

BACKGROUND: Viral infections have been the main health issue in the last decade. Antiviral peptides (AVPs) are a subclass of antimicrobial peptides (AMPs) with substantial potential to protect the human body against various viral diseases. However, there has been significant production of antiviral vaccines and medications. Recently, the development of AVPs as an antiviral agent suggests an effective way to treat virus-affected cells. Recently, the involvement of intelligent machine learning techniques for developing peptide-based therapeutic agents is becoming an increasing interest due to its significant outcomes. The existing wet-laboratory-based drugs are expensive, time-consuming, and cannot effectively perform in screening and predicting the targeted motif of antiviral peptides. METHODS: In this paper, we proposed a novel computational model called Deepstacked-AVPs to discriminate AVPs accurately. The training sequences are numerically encoded using a novel Tri-segmentation-based position-specific scoring matrix (PSSM-TS) and word2vec-based semantic features. Composition/Transition/Distribution-Transition (CTDT) is also employed to represent the physiochemical properties based on structural features. Apart from these, the fused vector is formed using PSSM-TS features, semantic information, and CTDT descriptors to compensate for the limitations of single encoding methods. Information gain (IG) is applied to choose the optimal feature set. The selected features are trained using a stacked-ensemble classifier. RESULTS: The proposed Deepstacked-AVPs model achieved a predictive accuracy of 96.60%%, an area under the curve (AUC) of 0.98, and a precision-recall (PR) value of 0.97 using training samples. In the case of the independent samples, our model obtained an accuracy of 95.15%, an AUC of 0.97, and a PR value of 0.97. CONCLUSION: Our Deepstacked-AVPs model outperformed existing models with a ~ 4% and ~ 2% higher accuracy using training and independent samples, respectively. The reliability and efficacy of the proposed Deepstacked-AVPs model make it a valuable tool for scientists and may perform a beneficial role in pharmaceutical design and research academia.

Synergistic effects of hybrid microfibers on mechanical, thermal, and microstructural characterization of nanocomposites.

The use of geopolymers (GP) in cementitious composites provides a solution to reduce the significant carbon emissions associated with conventional cement production, thereby advancing environmentally friendly concrete construction practices. The promise of hybrid fiber-reinforced fly ash (FA)-based GP (HFGP) composites that combine microfibers and nanoparticles has not yet been fully comprehended. This research aims to enhance the mechanical and microstructural properties of HFGP blends by varying the proportion of nano calcium carbonate ( n - C a C O 3 ). The production of HFGP involved the use of two types of fibers: 1% carbon fibers and 0.5% basalt fibers. To achieve HFGP blends with a consistent fiber ratio, we incorporated four different levels of n - C a C O 3 , comprising 1%, 2%, 3%, and 4% of the mixture. The analysis of fractured samples encompassed microstructural and mineralogical characterization, which was conducted using scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and X-ray diffraction (XRD) analysis. The results unveiled that the HFGP blend containing 3% n - C a C O 3 exhibited the highest levels of hardness, compressive strength, toughness modulus, and flexural strength while the use of 2% n - C a C O 3 produced the highest results for fracture toughness and impact strength. SEM analysis illustrated that n - C a C O 3 had a significant positive impact on the microstructure of GP. A considerable rise in hump intensity between 20 and 40 °C ( 2 θ ) was also seen in the XRD examination, indicating that calcium silicate hydrate (CSH) had formed after the primary binder, such as sodium aluminosilicate hydrate (NASH), had been present. The stretching of O-H bonds in water molecules was also seen in the HFGP spectra at 3399, 3436, 3436, and 3438 cm-1. Due to the higher water content in the HFGP network, which may influence the material's strength, these bands were more apparent and larger in specimens with additions of nanoparticles and hybrid fibers.

Facile fabrication of a graphene-based chemical sensor with ultrasensitivity for nitrobenzene.

Chemical sensors have a wide range of applications in a variety of industries, particularly for sensing volatile organic compounds. This work demonstrates the fabrication of a chemical sensor based on graphene deposited on Cu foils using low-pressure chemical vapor deposition, following its transfer on oxidized silicon through a wet etching method. Scanning electron microscopy, Raman spectroscopy and UV-vis spectroscopy of the transferred graphene were performed. A device was fabricated by simply connecting the strips of a Cu tape along the two opposite edges of graphene, which acted as a chemical sensor. The sensor was exposed to different analytes, namely acetone, propanol, benzyl chloride, nitrobenzene, carbon tetrachloride and acetic acid. A relative change in the resistance of the device was observed, which was attributed to the interaction of analytes with graphene as it changes charge concentrations in the graphene lattice. The fabricated sensor showed a notable sensitivity and response time for all analytes, particularly a sensitivity as high as 231.1 for nitrobenzene and a response time as short as 6.9 s for benzyl chloride. The sensor was also tested for analyte leakage from containers for domestic, laboratory and industrial applications.

Expression network analysis of bovine skin infested with Rhipicephalus australis identifies pro-inflammatory genes contributing to tick susceptibility.

The skin is the primary feeding site of ticks that infest livestock animals such as cattle. The highly specialised functions of skin at the molecular level may be a factor contributing to variation in susceptibility to tick infestation; but these remain to be well defined. The aim of this study was to investigate the bovine skin transcriptomic profiles of tick-naïve and tick-infested cattle and to uncover the gene expression networks that influence contrasting phenotypes of host resistance to ticks. RNA-Seq data was obtained from skin of Brangus cattle with high (n = 5) and low (n = 6) host resistance at 0 and 12 weeks following artificial tick challenge with Rhipicephalus australis larvae. No differentially expressed genes were detected pre-infestation between high and low resistance groups, but at 12-weeks there were 229 differentially expressed genes (DEGs; FDR < 0.05), of which 212 were the target of at least 1866 transcription factors (TFs) expressed in skin. Regulatory impact factor (RIF) analysis identified 158 significant TFs (P < 0.05) of which GRHL3, and DTX1 were also DEGs in the experiment. Gene term enrichment showed the significant TFs and DEGs were enriched in processes related to immune response and biological pathways related to host response to infectious diseases. Interferon Type 1-stimulated genes, including MX2, ISG15, MX1, OAS2 were upregulated in low host resistance steers after repeated tick challenge, suggesting dysregulated wound healing and chronic inflammatory skin processes contributing to host susceptibility to ticks. The present study provides an assessment of the bovine skin transcriptome before and after repeated tick challenge and shows that the up-regulation of pro-inflammatory genes is a prominent feature in the skin of tick-susceptible animals. In addition, the identification of transcription factors with high regulatory impact provides insights into the potentially meaningful gene-gene interactions involved in the variation of phenotypes of bovine host resistance to ticks.

Transcriptomics, proteomics, and metabolomics interventions prompt crop improvement against metal(loid) toxicity.

The escalating challenges posed by metal(loid) toxicity in agricultural ecosystems, exacerbated by rapid climate change and anthropogenic pressures, demand urgent attention. Soil contamination is a critical issue because it significantly impacts crop productivity. The widespread threat of metal(loid) toxicity can jeopardize global food security due to contaminated food supplies and pose environmental risks, contributing to soil and water pollution and thus impacting the whole ecosystem. In this context, plants have evolved complex mechanisms to combat metal(loid) stress. Amid the array of innovative approaches, omics, notably transcriptomics, proteomics, and metabolomics, have emerged as transformative tools, shedding light on the genes, proteins, and key metabolites involved in metal(loid) stress responses and tolerance mechanisms. These identified candidates hold promise for developing high-yielding crops with desirable agronomic traits. Computational biology tools like bioinformatics, biological databases, and analytical pipelines support these omics approaches by harnessing diverse information and facilitating the mapping of genotype-to-phenotype relationships under stress conditions. This review explores: (1) the multifaceted strategies that plants use to adapt to metal(loid) toxicity in their environment; (2) the latest findings in metal(loid)-mediated transcriptomics, proteomics, and metabolomics studies across various plant species; (3) the integration of omics data with artificial intelligence and high-throughput phenotyping; (4) the latest bioinformatics databases, tools and pipelines for single and/or multi-omics data integration; (5) the latest insights into stress adaptations and tolerance mechanisms for future outlooks; and (6) the capacity of omics advances for creating sustainable and resilient crop plants that can thrive in metal(loid)-contaminated environments.

Chloroplast gene control: unlocking RNA thermometer mechanisms in photosynthetic systems.

RNA thermometers offer straightforward, protein-independent methods to regulate gene expression at the post-transcriptional level. In this context, Chung and colleagues have discovered a revolutionary RNA thermometer in the chloroplast genome of Chlamydomonas reinhardtii. This will facilitate temperature-driven control of inducible transgene expression for biotechnology applications in plant and algal systems.

Structural performance of FRP composite bars reinforced rubberized concrete compressive members: Tests and numerical modeling.

Waste tyre rubber has become an environmental and health concern that needs to be sustainably managed to avoid fire hazards and save natural resources. This research work aims to study the structural behavior of glass fiber reinforced polymer (glass-FRP) reinforced rubberized concrete (GRC) compressive elements under monotonic axial compression loads. Nine GRC circular compressive elements with different axial and crosswise reinforcement ratios were fabricated. All the elements were 300 mm in diameter and 1200 mm in height. A 3D nonlinear finite element equation (FEM) was suggested for the GRC compressive elements using a commercial package ABAQUS. A parametric study has been done to examine the effect of various parameters of GRC elements. The test outcomes revealed that the ductility of GRC elements ameliorated with the lessening in the spaces of glass-FRP ties. The addition of rubberized concrete improved the ductility of GRC elements. The damage to GRC elements occurred due to the vertical cracking along the height of the elements. The estimates of FEM were in close agreement with the test outcomes. The suggested empirical equation depending on the 600 test elements, which considered the lateral confinement effect of FRP ties, presented higher accuracy than previous equations.

WO3-x nanorods/rGO/AgBiS2 Z-scheme heterojunction with comprehensive spectrum response and enhanced Fenton and photocatalytic activities.

Tetracycline (TC) antibiotics and dyes are the prevalent water contaminants, and their removal from the water through photocatalysis is a plausible approach. However, most semiconductors in their pristine form need to be improved to be exploited in photocatalysis owing to poor photoresponse, intense carrier recombination, and inertness without irradiation. Herein, we demonstrate the modification of defective WO3-x by rGO and AgBiS2 in the form of WO3-x/rGO/AgBiS2 (R2). It exploits the superior conductivity and synergism of rGO to inhibit carrier recombination; thereby, Z-scheme heterojunction with AgBiS2 provides high redox potential. Defects in WO3-x enable electron (e-) storage in R2, which decomposes H2O2 to generate ROS without irradiation. Owing to these essences and broad-spectrum response, it removed 93.72, 82.77, and 84.82% of TC during photo-Fenton (PFR), night-Fenton (NFR), and photocatalytic (PCR) reactions, respectively. Its removal rates reached 94.74, 81.54, and 87.50% against rhodamine B (RhB) during PFR, NFR, and PCR, respectively. It is superior to memory catalysis (MC) and conventional Fenton reactions (CFR) because it can perform without and with irradiation across a broader pH range. So, this work is conducive to designing WO3-x-based catalysts to combat environmental and energy crises.

A Rare Case of Uterine Blastomycosis and Its Management: A Case Report and Literature Review.

The report delineates the rare occurrence of uterine blastomycosis, an atypical systemic presentation of Blastomyces dermatitidis infection prevalent in North America. Focused on a 51-year-old immunocompetent female displaying abdominal pain and irregular vaginal bleeding, it underscores the intricate diagnostic hurdles posed by symptoms mirroring common gynecological conditions. Despite fewer than 10 recorded cases, the rarity of uterine involvement highlights the imperative for heightened clinical suspicion. The multifaceted diagnostic strategy integrates risk factors, travel history, imaging, and histopathological examinations. Emphasizing a multidisciplinary treatment helmed by gynecologists, pathologists, and infectious disease specialists, the utilization of antifungal agents, notably itraconazole, is pivotal. Addressing the scarcity of literature and the condition's clinical resemblance to prevalent ailments, further research becomes paramount in devising tailored diagnostic and treatment protocols for uterine blastomycosis. This study enriches the existing literature by providing critical insights into a scarcely documented condition, contributing novel perspectives essential for clinical understanding and management strategies.