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Background: Groundnut is mainly grown in the semi-arid tropic (SAT) regions worldwide, where abiotic stress like drought is persistent. However, a major research gap exists regarding exploring the genetic and genomic underpinnings of tolerance to drought. In this study, a multi-parent advanced generation inter-cross (MAGIC) population was developed and evaluated for five seasons at two locations for three consecutive years (2018–19, 2019–20 and 2020–21) under drought stress and normal environments. Results: Phenotyping data of drought tolerance related traits, combined with the high-quality 10,556 polymorphic SNPs, were used to perform multi-locus model genome-wide association study (GWAS) analysis. We identified 37 significant marker-trait associations (MTAs) (Bonferroni-corrected) accounting, 0.91- 9.82% of the phenotypic variance. Intriguingly, 26 significant MTAs overlap on four chromosomes (Ah03, Ah07, Ah10 and Ah18) (harboring 70% of MTAs), indicating genomic hotspot regions governing drought tolerance traits. Furthermore, important candidate genes associated with leaf senescence (NAC transcription factor), flowering (B3 domain-containing transcription factor, Ulp1 protease family, and Ankyrin repeat-containing protein), involved in chlorophyll biosynthesis (FAR1 DNA-binding domain protein), stomatal regulation (Rop guanine nucleotide exchange factor; Galacturonosyltransferases), and associated with yield traits (Fasciclin-like arabinogalactan protein 11 and Fasciclin-like arabinogalactan protein 21) were found in the vicinity of significant MTAs genomic regions. Conclusion: The findings of our investigation have the potential to provide a basis for significant MTAs validation, gene discovery and development of functional markers, which could be employed in genomics-assisted breeding to develop climate-resilient groundnut varieties. [ABSTRACT FROM AUTHOR]

Detection of tumor marker location in the breast and axilla using a less commonly utilized color Doppler ultrasound (CDUS) artifact. This prospective study was conducted between August and December 2023 and included consecutive patients with markers placed in the breast and axilla, both before and after neoadjuvant chemotherapy (NACT). Examinations were conducted using a 14 to 5 MHz linear array transducer with B-mode and Doppler capability. By reducing the velocity scale and increasing the color gain values, adjustments were made to create a bloom-like artifact. CDUS was performed with the ultrasound transmit frequency set between 14–5 MHz, color frequency between 6 and 7, color gain ranging from 58 to 80, and velocity scale within the range of 4.6–6.1 cm/s. Twenty patients, with a mean age of 55.50 years ± 12.04 SD (range, 31–72), were included in the study. 14 (70%) were pre-NACT, and six (30%) were post-NACT patients. A total of 20 breast lesions and six axillary lymph nodes were marked. The breast lesions and axillary lymph nodes where the biopsy marker was placed (14 breast lesions and five axillary lymph nodes before NACT, six breast lesions and one axillary lymph node after NACT) were localized with blooming-like artifact. The average size of breast lesions was 20.95 mm ± 6.56 SD (range, 15–40). For axillary lymph nodes, the average size was 20.63 mm ± 5.01 SD (range: 31–14). The blooming-like CDUS artifact is a novel and easily applicable method determining the location of metallic markers in the breast and axilla on diagnostic examinations. [ABSTRACT FROM AUTHOR]

Background and aim: The D-dimer to fibrinogen ratio (DFR) represents an emerging and significant clinical biomarker. However, its correlation with cerebral venous thrombosis (CVT) remains underexplored. This retrospective cohort study aims to elucidate the association between DFR values and the severity and prognosis of CVT. Methods: Severe CVT was defined as the presence of at least 1 of the following risk factors: mental status disorder, coma state, intracranial cerebral hemorrhage, or thrombosis of the deep cerebral venous system. The modified Rankin Scale was utilized to assess functional outcomes. DFR measurements were obtained within 24 h of hospital admission. Logistic regression analysis was employed to determine the prognostic significance of DFR. After Bonferroni correction, a two-tailed P value < 0.017 (0.05/3) was considered statistically significant. Result: A total of 196 patients were included in the study, among whom 85 patients were diagnosed with severe CVT, and 35 and 14 patients experienced short-term and long-term adverse outcomes, respectively. Receiver operating characteristic curve analysis demonstrated that DFR has predictive value for severe CVT, poor short-term and long-term outcomes, with area under the curve values of 0.690 [95% CI: 0.617–0.764, P <.001], 0.773 [95% CI: 0.701–0.845, P <.001], and 0.754 [95% CI: 0.619–0.886, P =.002], respectively. DFR ≥ 0.253 was identified as a significant predictor of severe CVT [adjusted odds ratio (aOR) (95% CI): 2.03 (1.10–3.75), P =.024]. Additionally, DFR ≥ 0.322 and DFR ≥ 0.754 were significantly associated with poor short-term outcomes at discharge [aOR (95% CI): 2.63 (1.43–4.76), P =.002] and poor long-term outcomes at 12 months [aOR (95% CI): 2.86 (1.32–6.25), P =.008], respectively. Conclusion: Elevated DFR is associated with increased severity of CVT. Additionally, higher DFR levels can predict poorer clinical outcomes in CVT. [ABSTRACT FROM AUTHOR]

Adrenomedullin has emerged as a promising biomarker in the field of viral diseases. Numerous studies have demonstrated its potential in assessing disease severity, predicting clinical outcomes, and monitoring treatment response. Adrenomedullin (AM) is a multifaceted peptide implicated in vasodilation, hormone secretion, antimicrobial defense, cellular growth, angiogenesis, and, importantly, chronic pain. AM and related peptides interface with cytoskeletal proteins within neuronal contexts, influencing microtubule dynamics. AM has primarily been utilized in diagnosing diseases of bacterial origin, including sepsis. Nevertheless, there are reports suggesting its utility in diseases of viral origin, and this is the focus of the present study. Furthermore, adrenomedullin has been shown to be elevated in various viral infections, suggesting its role in immune response modulation. Furthermore, AM may contribute to neuronal dysfunction through mechanisms involving immune and inflammatory responses, apoptosis, and disruptions in calcium homeostasis. This review aims to consolidate current knowledge regarding AM and its potential implications in viral diseases, elucidating its diverse roles in neurological pathophysiology. This review highlights the growing importance of adrenomedullin as a biomarker in viral diseases and the need for further functional studies to understand the underlying mechanisms involved. [ABSTRACT FROM AUTHOR]

One problem that has hampered the use of red fluorescent proteins in the fast-developing nematode Caenorhabditis elegans has been the substantial time delay in maturation of several generations of red fluorophores. The recently described mScarlet-I3 protein has properties that may overcome this limitation. We compare here the brightness and onset of expression of CRISPR/Cas9 genome-engineered mScarlet, mScarlet3, mScarlet-I3, and GFP reporter knock-ins. Comparing the onset and brightness of expression of reporter alleles of C. elegans golg-4 , encoding a broadly expressed Golgi resident protein, we found that the onset of detection of mScarlet-I3 in the embryo is several hours earlier than older versions of mScarlet and comparable to GFP. These findings were further supported by comparing mScarlet-I3 and GFP reporter alleles for pks-1 , a gene expressed in the CAN neuron and cells of the alimentary system, as well as reporter alleles for the pan-neuronal, nuclear marker unc-75. Hence, the relative properties of mScarlet-I3 and GFP do not depend on cellular or subcellular context. In all cases, mScarlet-I3 reporters also show improved signal-to-noise ratio compared to GFP. [ABSTRACT FROM AUTHOR]

Background: Peripheral inflammation is often associated with depressive disorders, and immunological biomarkers of depression remain a focus of investigation. Methods: We performed RNA-seq analysis of RNA transcripts of human peripheral blood mononuclear cells from a case-control study including subjects with self-reported depression in the pre-symptomatic state of major depressive disorder and analyzed differentially expressed genes (DEGs) and the frequency of intron retention (IR) using rMATS. Results: Among the statistically significant DEGs identified, the 651 upregulated DEGs were particularly enriched in the term "bacterial infection and phagocytosis", whereas the 820 downregulated DEGs were enriched in the terms "antigen presentation" and "T-cell proliferation and maturation". We also analyzed 158 genes for which the IR was increased (IncIR) and 211 genes for which the IR was decreased (DecIR) in the depressed subjects. Although the Gene Ontology terms associated with IncIR and DecIR were very similar to those of the up- and downregulated genes, respectively, IR genes appeared to be particularly enriched in genes with sensor functions, with a preponderance of the term "ciliary assembly and function". The observation that IR genes specifically interact with innate immunity genes suggests that immune-related genes, as well as cilia-related genes, may be excellent markers of depression. Re-analysis of previously published RNA-seq data from patients with MDD showed that common IR genes, particularly our predicted immune- and cilia-related genes, are commonly detected in populations with different levels of depression, providing validity for using IR to detect depression. Conclusion: Depression was found to be associated with activation of the innate immune response and relative inactivation of T-cell signaling. The DEGs we identified reflect physiological demands that are controlled at the transcriptional level, whereas the IR results reflect a more direct mechanism for monitoring protein homeostasis. Accordingly, an alteration in IR, namely IncIR or DecIR, is a stress response, and intron-retained transcripts are sensors of the physiological state of the cytoplasm. The results demonstrate the potential of relative IR as a biomarker for the immunological stratification of depressed patients and the utility of IR for the discovery of novel pathways involved in recovery from depression. [ABSTRACT FROM AUTHOR]

Marine invertebrate stem cells (MISCs) represent a distinct category of pluripotent and totipotent cells with remarkable abilities for self-renewal and differentiation into multiple germ layers, akin to their vertebrate counterparts. These unique cells persist throughout an organism's adult life and have been observed in various adult marine invertebrate phyla. MISCs play crucial roles in numerous biological processes, including developmental biology phenomena specific to marine invertebrates, such as senescence, delayed senescence, whole-body regeneration, and asexual reproduction. Furthermore, they serve as valuable models for studying stem cell biology. Despite their significance, information about MISCs remains scarce and scattered in the scientific literature. In this review, we have carefully collected and summarized valuable information about MISC detection by perusing the articles that study and detect MISCs in various marine invertebrate organisms. The review begins by defining MISCs and highlighting their unique features compared to vertebrates. It then discusses the common markers for MISC detection and in vitro techniques employed in invertebrate and vertebrates investigation. This comprehensive review provides researchers and scientists with a cohesive and succinct overview of MISC characteristics, detection methods, and associated biological phenomena in marine invertebrate organisms. We aim to offer a valuable resource to researchers and scientists interested in marine invertebrate stem cells, fostering a better understanding of their broader implications in biology. With ongoing advancements in scientific techniques and the continued exploration of marine invertebrate species, we anticipate that further discoveries will expand our knowledge of MISCs and their broader implications in biology. [ABSTRACT FROM AUTHOR]

The American cockroach, Periplaneta americana (Blattodea: Blattidae), is a prevalent urban pest with significant public health implications. This study aimed to develop and validate novel microsatellite markers to understand the genetic diversity and population genetic structure of P. americana. In this study, a total of 397,898 microsatellite markers were developed based on 24.6 million genomic DNA sequences. Twenty microsatellite markers were selected and amplified with varying numbers of alleles ranging from 0 to 35. Seven out of 20 markers were characterized for their polymorphism and amplification efficiency. The polymorphic information content (PIC) values of these markers were high (0.669 to 0.950) implying their effectiveness. These markers also revealed 7 to 35 alleles per locus across tested samples, highlighting their utility in assessing the extensive genetic variation within Periplaneta americana populations. These results provide insightful information that may be applied to the genetic analysis of the American cockroach population using the developed species-specific microsatellite marker. [ABSTRACT FROM AUTHOR]

Introduction Hemoglobin, albumin, lymphocyte, and platelet (HALP) score has been used to predict the prognosis in several types of cancers for the last few years. We aimed to reveal whether HALP score has high sensitivity and specificity in the detection of diabetic nephropathy. Methods A cross-sectional study developed in Abant Izzet Baysal University Hospital in Bolu, Türkiye. Patients with type 2 diabetes mellitus (DM) were enrolled in the study. Study cohort included patients with diabetic nephropathy and patients without diabetic nephropathy. Pregnant women, subjects with malignancy, active infections conditions, and rheumatologic or hematologic diseases were excluded. We retrospectively analyzed and compared the HALP scores of the type 2 DM patients with and without diabetic nephropathy. Moreover, we sought correlation between HALP score and fasting glucose, glycated hemoglobin (HbA1c), and estimated glomerular filtration rate (eGFR). Results A total of 356 DM patients, 162 with nephropathy and 194 without nephropathy were included in the study. The HALP score was 44.86 (4.5–119.9) in the nephropathic group, while it was 55.14 (13.2–173.7) in the nonnephropathic group (p < 0.001). HALP score was negatively correlated with HbA1c (r = –0.66, p = 0.003) and fasting glucose (r = –0.65, p = 0.002), while positive correlation was found between HALP score and eGFR (r = 0.13, p = 0.02). HALP score lower than 45.9% have 73% sensitivity and 52% specificity in detecting diabetic nephropathy (area under the curve: 0.64, p < 0.001, 95% confidence interval: 0.59–0.70). Conclusion We suggest that HALP score can become a simple and easy to assess marker for diabetic nephropathy in addition to standard tests. [ABSTRACT FROM AUTHOR]

Asian seabass (Lates calcarifer) is an important foodfish species. It has been cultured in Singapore since the 1980s. A selective breeding program to improve growth, meat quality and disease resistance has been ongoing in Singapore since 2004. In 2012, outbreaks of the big belly disease (BBD) occurred in two batches of offspring generated by a mass-cross among F1 brooders in a hatchery. After the outbreaks, only 437 survived in 6000 F2 juveniles. Molecular parentage analysis with 10 microsatellites revealed that four parents (F1) produced high percentage of offspring that survived the BBD outbreaks. Eighty-two BBD survivor offspring (F2) were selected based on their growth performance at 90 days post hatch (dph), family origin and allelic diversity. They were used as brooders to generate F3. In a period of five years, these F2 brooders produced six batches of offspring, where no outbreak of BBD occurred. In the same period, outbreaks of BBD occurred in 4 out of 18 batches produced by F2 brooders selected for growth, with mortality rates ranging from 85.1% to 95.4%. In F3, the average body weight (57.1 ± 1.09 g, n = 3068) of the line for BBD survival was slightly lower than that (60.6 ± 2.29 g, n = 4280) of the line for growth at 90 dph. In both lines, the body weight of F3 was much higher than that (46.90 ± 0.19 g, n = 12117) of F2. The genetic diversity in the line for BBD survival (F3) was much lower than that in F3 line for growth due to small founder population. These data indicate that the selection of BBD survival during BBD outbreaks using molecular parentage analysis is effective to reduce BBD outbreaks. Avoiding further reduction of genetic diversity is essential in the line selected for increased survival against BBD. [ABSTRACT FROM AUTHOR]

Small cell lung cancer (SCLC) is a type of lung cancer with high malignant degree, rapid transformation, rapid invasion and metastasis, which is prone to early metastasis and poor prognosis. Bone metastases of SCLC occur in three stages: cancer cells proliferate at the primary site, break through local tissues, enter the blood circulation to form circulating tumor cells (CTCs), reach bone tissue through blood circulation, and take root and germinate to form new tumor sites with the support of the bone microenvironment. However, traditional imaging and pathology examinations have disadvantages such as low sensitivity, high cost and difficulty in implementation. Exploratory studies based on blood marker detection as screening and efficacy evaluation of SCLC bone metastases have been reported in recent years. By reviewing the molecular biological mechanism of SCLC bone metastasis formation, this paper found that conventional diagnostic methods such as imaging and pathological biopsy were inadequate in SCLC bone metastasis. The changes in hyaluronic acid, protein biomarkers, non-coding RNA, and biomarkers in liquid biopsy were earlier than the changes in imaging, which had the advantages of simple operation and good repeatability. It provides a new idea and method for the early diagnosis of SCLC bone metastasis, which is worthy of clinical application. [ABSTRACT FROM AUTHOR]

Herein, we propose an analytical approach based on intermolecular fluorescent resonant energy transfer (FRET) pairs for the visualization of specific enzyme activity in model biomembranes and in living cells. Cell visualizations with fluorescent confocal laser microscopy usually rely on fluorescent probes, such as Fluorescein isothiocyanate (FITC), Alexa488, Tetramethylrhodamine isothiocyanate (TRITC) and many others. However, for more specific tasks, such as the detection of certain enzymatic activity inside the living cell, the toolbox is quite limited. In the case of enzyme-hydrolases for example, the choice is limited to organic molecules comprising a fluorescent dye (typically, 4-methylumbelliferone (MUmb) or 7-amino-4-methylcoumarin (AMC) derivatives) and a fluorescence quencher, bound via an enzyme-sensitive linker—so that when the linker is degraded, the fluorescent signal increases. Unfortunately, both MUmb and AMC are quenched and have a relatively low quantum yield in cells, and their excitation and emission ranges overlap with that of intracellular fluorophores, often producing a strong background noise. R6G, on the other hand, has excellent quantum yield apart from intracellular fluorophores, but there are no efficient quenchers that could be chemically linked to R6G. Herein, we show that R6G is able to form intermolecular FRET pairs with MUmb or AMC, with the latter serving as fluorescence donors. This yields a combination of R6G's excellent fluorescence properties with a possibility to use an enzyme-sensitive linker in MUTMAC or AMC derivatives. This phenomenon was initially discovered in a model system, reversed micelles, where the donor, the acceptor, and the enzyme are forced to be in close proximity to each other, so that proximity could serve as an explanation for the intermolecular FRET effect. Surprisingly enough, the phenomenon has been reproduced in living cells. Moreover, we were able to create working intermolecular donor–acceptor FRET pairs for several different enzymes, including chymotrypsin, phosphatase, and asparaginase. This appears counterintuitive, as besides the overlap of the emission spectra of the donor and the absorption spectra of the acceptor, there are other criteria for the FRET effect, including the convergence of two fluorophores at a distance of about 1–10 nm, and the orientation of their dipoles at a certain angle, which is difficult to imagine in a bulk system like a living cell. We hypothesize that FRET-enabling donor–acceptor interaction may be taking place at the inner surface of the lipid bilayer, to which both donor and acceptor molecules would likely have an affinity. This hypothesis would require a more detailed investigation. Therefore, we have shown that the method suggested has good potential in the visualization of enzyme functioning inside living cells, which is often a challenging task. Shifting of the fluorescence signal to the long-wavelength region would increase the signal selectivity, making it easily distinguishable from autofluorescence. [ABSTRACT FROM AUTHOR]

Enhancing the marker repository and the development of breeder-friendly markers in chickpeas is important in relation to chickpea genomics-assisted breeding applications. Insertion–deletion (InDel) markers are widely distributed across genomes and easily observed with specifically designed primers, leading to less time, cost, and labor requirements. In light of this, the present study focused on the identification and development of InDel markers through the use of double-digest restriction site-associated DNA sequencing (ddRADSeq) data from 20 chickpea accessions. Bioinformatic analysis identified 20,700 InDel sites, including 15,031 (72.61%) deletions and 5669 (27.39%) insertions, among the chickpea accessions. The InDel markers ranged from 1 to 25 bp in length, while single-nucleotide-length InDel markers were found to represent the majority of the InDel sites and account for 79% of the total InDel markers. However, we focused on InDel markers wherein the length was greater than a single nucleotide to avoid any read or alignment errors. Among all of the InDel markers, 96.1% were less than 10 bp, 3.6% were between 10 and 20 bp, and 0.3% were more than 20 bp in length. We examined the InDel markers that were 10 bp and longer for the development of InDel markers based on a consideration of the genomic distribution and low-cost genotyping with agarose gels. A total of 29 InDel regions were selected, and primers were successfully designed to evaluate their efficiency. Annotation analysis of the InDel markers revealed them to be found with the highest frequency in the intergenic regions (82.76%), followed by the introns (6.90%), coding sequences (6.90%), and exons (3.45%). Genetic diversity analysis demonstrated that the polymorphic information content of the markers varied from 0.09 to 0.37, with an average of 0.20. Taken together, these results showed the efficiency of InDel marker development for chickpea genetic and genomic studies using the ddRADSeq method. The identified markers might prove valuable for chickpea breeders. [ABSTRACT FROM AUTHOR]

Rice blast is one of the most devastating biotic stresses that limits rice productivity. The North Eastern Hill (NEH) region of India is considered to be one of the primary centres of diversity for both rice and pathotypes of Magnaporthe grisea. Therefore, the present study was carried out to elucidate the genetic basis of leaf and neck blast resistance under Meghalaya conditions. A set of 80 diverse genotypes (natural population) and 2 F2 populations involving resistant parent, a wildtype landrace, LR 5 (Lal Jangali) and susceptible genotypes Sambha Mahsuri SUB 1 (SMS) and LR 26 (Chakhao Poireiton) were used for association analysis of reported major gene-linked markers with leaf and neck blast resistance to identify major effective genes under local conditions. Genotyping using twenty-five gene-specific markers across diverse genotypes and F2 progenies revealed genes Pi5 and Pi54 to be associated with leaf blast resistance in all three populations. Genes Pib and qPbm showed an association with neck blast resistance in both natural and LR 5 × SMS populations. Additionally, a set of 184 genome-wide polymorphic markers (SSRs and SNPs), when applied to F2-resistant and F2-susceptible DNA bulks derived from LR 5 × LR 26, suggested that Pi20(t) on chromosome 12 is one of the major genes imparting disease resistance. Markers snpOS318, RM1337 and RM7102 and RM247 and snpOS316 were associated with leaf blast and neck blast resistance, respectively. The genotypes, markers and genes will help in marker-assisted selection and development of varieties with durable resistance. [ABSTRACT FROM AUTHOR]

Abstract Background and aim The D-dimer to fibrinogen ratio (DFR) represents an emerging and significant clinical biomarker. However, its correlation with cerebral venous thrombosis (CVT) remains underexplored. This retrospective cohort study aims to elucidate the association between DFR values and the severity and prognosis of CVT. Methods Severe CVT was defined as the presence of at least 1 of the following risk factors: mental status disorder, coma state, intracranial cerebral hemorrhage, or thrombosis of the deep cerebral venous system. The modified Rankin Scale was utilized to assess functional outcomes. DFR measurements were obtained within 24 h of hospital admission. Logistic regression analysis was employed to determine the prognostic significance of DFR. After Bonferroni correction, a two-tailed P value

Rationale: Long non-coding RNAs (lncRNAs) influence tumor cell properties during the onset and progression of lung malignancies; however, their diagnostic and prognostic significance has not been determined. We have previously shown that when non-small cell lung cancer (NSCLC) cells acquire a more malignant phenotype (under the influence of macrophagal cytotoxic activity) compared to the original cell lines, the expression of several lncRNAs, in particular PSMB8-AS1, MBNL1-AS1, and OLMALINC, is altered compared to the original cell lines. Aim: A comparative analysis of lncRNAs PSMB8-AS1, MBNL1-AS1, and OLMALINC expression in tissue samples from lung tumors and conditionally normal areas of the lungs and an assessment of the lncRNAs clinical significance. Methods: We have analyzed surgical samples of the tumor and conditionally normal tissue from 16 patients with a verified diagnosis of NSCLC. The expression level of lncRNAs PSMB8-AS1, MBNL1-AS1 and OLMALINC was assessed by real-time polymerase chain reaction. To analyze the long-term treatment results and clinical significance of the studied genes, the patients were divided into two comparison groups depending on the relative level of lncRNAs expression (above or below the median). Results: The expression of lncRNAs PSMB8-AS1, MBNL1-AS1 and OLMALINC in the lung tumor tissue was significantly reduced compared to the conditionally normal tissues (p = 0.0034; p = 0.002 and p = 0.0172, respectively). Analysis of the association between the expression of these lncRNAs with clinical and morphological characteristics, such as disease stage, tumor size, presence of regional and distant metastases was unable to identify any regular patterns. The expression of lncRNAs PSMB8-AS1, MBNL1-AS1 and OLMALINC was not a significant prognostic factor (p = 0.364; p = 0.759 and p = 0.184, respectively). However in the case of high OLMALINC and PSMB8-AS1 expression, median survival was 47 months, while in the case of their low expression, median survival was not achieved during the follow-up. The expression of lncRNA PSMB8-AS1 in NSCLC tumors positively correlated with the expression of lncRNA OLMALINC (r = 0.680, p = 0.007), which may indicate their functional interplay or the presence of common regulatory mechanisms. Conclusion: The NSCLC tumors demonstrated aberrant expression of PSMB8-AS1, MBNL1-AS1, and OLMALINC lncRNAs. A more detailed study of their expression in various cell types and their regulatory role would allow for validation of new therapeutic targets in NSCLC, as well as for development of alternative therapies.

The purpose of this study is to identify ethnopoetic markers in a translingual literary text. A translingual text is a text created by an author in a language that is not his or her native language and that transmits fragments of the author’s original culture. By ethnopoetic markers we mean such elements of the text that 1) are transferred into the fabric of the Russian-language text and have an exophonic sound, therefore, are semantically lacunary for the reader and require expansion; 2) are neutral from the point of view of the translator language, but reproduce foreign images of the world. The material for the study was selected poems by the Tatar poetess Albina Absalyamova. In the course of the work, it was possible to establish that the category of translingual text as a scientific problem is closely intertwined with the epistemological fields of ethnoand geopoetics.

Oral cancer became a very common condition. WHO estimates that there are 4 cases of lip and oral cavity cancer for every 100,000 people worldwide. The early diagnosis of cancers is currently a top focus in the health sector. Recent systematic reviews and meta-analyses have identified promising biomarkers for early detection in several original research investigations. However, it is still unclear the quality of these evidence and which biomarker performs the best in terms of early detection. Therefore, the objective was, to map the methodological and reporting quality of available oral squamous cell carcinoma (OSCC) or head/neck squamous cell carcinoma (HNSCC) systematic reviews and meta-analysis. Secondly, to evaluate diagnostic accuracy of salivary biomarkers for common craniofacial cancers and to compare the diagnostic value of different salivary biomarkers.PubMed, Scopus, Web of Science, Embase and Cochrane Library electronic databases were used to map the methodological and reporting quality of the systematic reviews and meta-analysis conducted on the HNSCC, OSCC using the AMSTAR-2 checklist. The inclusion criteria were systematic reviews and meta-analysis published in the topic of HNSCC and OSCC biomarkers. Exclusion criteria were no animal studies; original primary studies, due to limitation of competency in other languages articles with language other than English were excluded. The sensitivity and specificity were calculated for salivary biomarkers and ranked according to network meta-analysis principles.A total of N = 5893 patients were included from four meta-analysis studies. All together, these included n = 37 primary studies. n = 94 biomarkers were pooled from these four meta-analyses and categorised into the stages at which they were detected (I-IV). In OSCC, Chemerin and MMP-9 displayed the highest sensitivity, registering 0.94 (95% CI 0.78, 1.00) and a balanced accuracy of 0.93. Phytosphingosine closely followed, with a sensitivity of 0.91 (95% CI 0.68, 0.99) and a balanced accuracy of 0.87.For HNSCC, the top three biomarkers are Actin, IL-1β Singleplex, and IL-8 ELISA. Actin leads with a sensitivity of 0.91 (95% CI 0.68–0.99), a specificity of 0.67, and an overall accuracy of 0.79. Subsequently, IL-1β Singleplex exhibits a sensitivity of 0.62 (95% CI 0.30–0.88), a specificity of 0.89, and an accuracy of 0.75, followed by IL-8 ELISA with a sensitivity of 0.81 (95% CI 0.54–0.97), a specificity of 0.59, and an accuracy of 0.70.In conclusion, there was highest sensitivity for MMP-9 and chemerin salivary biomarkers. There is need of further more studies to identify biomarkers for HNSCC and OSCC.

Aim: study the dynamics of osteogenesis and bone resorption markers in elite biathlonists owing to the “compression” specifics of cyclic training aids, mainly used at the stages of the early season of the annual training cycle.Materials and methods: 23 elite biathlonists undergoing centralized training as the members of the Russian national team took part in the study.Results: no changes in the P1NP amounts reaching a reliable level were recorded throughout the early season. The average group osteocalcin amount at the precompetition stage significantly (p < 0,05) increased compared with that measured at the special preliminary stage. Dynamics of β-CrossLaps concentration showed significant (p < 0,05) decrease during the transition from the general preliminary to the special preliminary stage.Conclusion: the degree of intense training activity influence on the activity of bone cells and in turn the response of bone tissue to training loads depend on a set of exercise parameters performed by the athlete, such as duration, intensity, specificity, recovery time and mechanical stress. Optimizing the ratio of cyclic aids with different levels of compression loads during specialized training promotes adaptive changes which protect bone tissue from resorption affected by intense physical exercises. When analyzing the levels of bone metabolism markers for diagnosis and monitoring disorders associated with skeletal overload which could occur high-intensity training loads, an individual approach as well as recognition of the load specifics and parameters performed by an athlete at a specific stage of the training macrocycle are required.

Rice is an important food product for people. Milled white rice is mainly used or food purposes, but unpolished rice is also used. The cells of the aleurone layer and the embryo of the rice grain contain lipids, the presence of which strengthens the immune system and protects against heart disease and cancer, which has increased interest in them. The current paper has provided a review of the information on the study of quantitative trait loci connected with lipid content in rice grain. The study was conducted in China, Korea, and Japan from 1983 to 2021 using dihaploid lines from hybrids among rice varieties with contrasting lipid content. There was identified a correlation with QTL on 12 rice chromosomes with the help of a microsatellite marker map. Hu et al. (2004) found three QTLs for oil content located on chromosomes 1, 2, and 5. Yu et al. (2009) found four QTLs on chromosomes 3, 5, 6, and 8. Qin et al. (2010) mapped eight QTLs to chromosomes 1, 2, 3, 5, 6, 7 and 9. Kim et al. (2013) found a significant QTL, qRLC5, on chromosome 5. Yun et al. (2014) found that high lipid content was determined by three QTL on chromosomes 2, 3 and 6. Ying et al. (2012) identified 29 QTL on 10 chromosomes, several for seven fatty acids. Zhou and his colleagues (2021) conducted a genomic study of oil composition and concentration in different groups of 533 cultivated rice varieties and identified 99 QTL, 94 of which were associated with oil composition and five of them with oil concentration. These QTLs will allow developing pyramids of favorable alleles to improve rice quality using marker-assisted breeding.

Herein, we propose an analytical approach based on intermolecular fluorescent resonant energy transfer (FRET) pairs for the visualization of specific enzyme activity in model biomembranes and in living cells. Cell visualizations with fluorescent confocal laser microscopy usually rely on fluorescent probes, such as Fluorescein isothiocyanate (FITC), Alexa488, Tetramethylrhodamine isothiocyanate (TRITC) and many others. However, for more specific tasks, such as the detection of certain enzymatic activity inside the living cell, the toolbox is quite limited. In the case of enzyme-hydrolases for example, the choice is limited to organic molecules comprising a fluorescent dye (typically, 4-methylumbelliferone (MUmb) or 7-amino-4-methylcoumarin (AMC) derivatives) and a fluorescence quencher, bound via an enzyme-sensitive linker—so that when the linker is degraded, the fluorescent signal increases. Unfortunately, both MUmb and AMC are quenched and have a relatively low quantum yield in cells, and their excitation and emission ranges overlap with that of intracellular fluorophores, often producing a strong background noise. R6G, on the other hand, has excellent quantum yield apart from intracellular fluorophores, but there are no efficient quenchers that could be chemically linked to R6G. Herein, we show that R6G is able to form intermolecular FRET pairs with MUmb or AMC, with the latter serving as fluorescence donors. This yields a combination of R6G’s excellent fluorescence properties with a possibility to use an enzyme-sensitive linker in MUTMAC or AMC derivatives. This phenomenon was initially discovered in a model system, reversed micelles, where the donor, the acceptor, and the enzyme are forced to be in close proximity to each other, so that proximity could serve as an explanation for the intermolecular FRET effect. Surprisingly enough, the phenomenon has been reproduced in living cells. Moreover, we were able to create working intermolecular donor–acceptor FRET pairs for several different enzymes, including chymotrypsin, phosphatase, and asparaginase. This appears counterintuitive, as besides the overlap of the emission spectra of the donor and the absorption spectra of the acceptor, there are other criteria for the FRET effect, including the convergence of two fluorophores at a distance of about 1–10 nm, and the orientation of their dipoles at a certain angle, which is difficult to imagine in a bulk system like a living cell. We hypothesize that FRET-enabling donor–acceptor interaction may be taking place at the inner surface of the lipid bilayer, to which both donor and acceptor molecules would likely have an affinity. This hypothesis would require a more detailed investigation. Therefore, we have shown that the method suggested has good potential in the visualization of enzyme functioning inside living cells, which is often a challenging task. Shifting of the fluorescence signal to the long-wavelength region would increase the signal selectivity, making it easily distinguishable from autofluorescence.

Xuming Wang, Xiaoli Ji Department of Stomatology, The Affiliated Huaian No.1 People’s Hospital of Nanjing Medical University, Huaian, Jiangsu, People’s Republic of ChinaCorrespondence: Xiaoli Ji, Email jixiaoli214@163.comBackground: Several studies have investigated the relationship between serum lactate dehydrogenase-to-albumin ratio (LAR) and the prognosis of cancers. However, no studies have explored the association between serum LAR and the survival of oral cancer (OC). This study was aimed to determine the association of serum LAR with the overall survival (OS) of OC.Methods: One hundred and ninety patients with OC were included in this study between January 2018 and December 2019. Log rank test and Kaplan–Meier method were used to compare the survival rate of OC between the low LAR group and the high LAR group. The association between serum LAR and the survival of OC patients was determined via univariate and multivariate Cox regression analyses.Results: Kaplan-Meier analysis and Log rank test indicated that the OS rate in low LAR group was significantly higher than that in high LAR group (P < 0.05). Univariate cox analysis showed that TNM III-IV stage, serum LDH > 162 U/L, and serum LAR > 3.79 were significantly associated with the OS of OC patients. Multivariate Cox analysis suggested that the TNM III-IV stage (HR, 2.317; 95% CI, 1.423– 3.774, P = 0.001) and serum LAR > 3.79 (HR, 5.138; 95% CI, 2.245– 11.756, P = 0.000) were independently related with poor OS of OC patients.Conclusion: High serum LAR (> 3.79) is an independent predictor of adverse prognosis in OC patients. LAR could be used as a promising marker for predicting the OS of OC patients.Keywords: oral cancer, lactate dehydrogenase to albumin ratio, prognosis, marker

Brain-derived neurotrophic factor (BDNF) is a predominant neurotrophic factor in the brain, indispensable for neuronal growth, synaptic development, neuronal repair, and hippocampal neuroplasticity. Among its genetic variants, the BDNF Val66Met polymorphism is widespread in the population and has been associated with the onset and aggravation of diverse pathologies, including metabolic conditions like obesity and diabetes, cardiovascular ailments, cancer, and an array of psychiatric disorders. Psychiatric disorders constitute a broad category of mental health issues that influence mood, cognition, and behavior. Despite advances in research and treatment, challenges persist that hinder our understanding and effective intervention of these multifaceted conditions. Achieving and maintaining stable body weight is pivotal for overall health and well-being, and the relationship between psychiatric conditions and body weight is notably intricate and reciprocal. Both weight gain and loss have been linked to varying mental health challenges, making the disentanglement of this relationship critical for crafting holistic treatment strategies. The BDNF Val66Met polymorphism's connection to weight fluctuation in psychiatric patients has garnered attention. This review investigated the effects and underlying mechanisms by which the BDNF Val66Met polymorphism moderates body weight among individuals with psychiatric disorders. It posits the polymorphism as a potential biomarker, offering prospects for improved monitoring and therapeutic approaches for mental illnesses.

Persimmon is classified as either pollination-constant non-astringent (PCNA) or non-PCNA on the basis of the loss of astringency in fruit. PCNA trait of persimmon has attracted much research attention owing to its economical merit, as there is no cost in removing astringency. To efficiently develop new PCNA cultivars in crossbreeding, marker-assisted selection plays a crucial role. Here, we describe a cleaved amplified polymorphic sequence (CAPS) marker that can be used to select PCNA persimmon. A sequence-characterized amplified region (SCAR) marker used to screen for PCNA offspring is unsuitable for populations recently derived from two non-PCNA parents ('Yoshidagosho' and 'Toyoichi'), resulting in the selection of non-PCNA offspring as PCNA. To detect specific polymorphisms for these non-PCNA offspring, we analyzed fragment sizes of SCAR marker products by capillary DNA sequencing. A slightly lower-molecular-weight fragment at 353 bp was specifically detected in non-PCNA offspring but not in PCNA offspring. We treated the SCAR marker products with the StuI restriction enzyme and demonstrated that the smaller 353-bp fragment corresponded to allele a353-1, one of four previously identified sequence polymorphisms at the 353-bp peak, and a353-1 is linked to non-PCNA trait. Comprehensive analysis of 130 germplasms by the CAPS marker, detecting the truncated fragment after StuI treatment, indicated the presence of a353-1 in 38 non-PCNA cultivars. Our findings suggest the potential use of the CAPS marker for selecting PCNA offspring derived from these 38 non-PCNA cultivars. [ABSTRACT FROM AUTHOR]

Background/aim: Aging, a multifaceted biological process, leads to diminished physical performance, especially in older adults with diabetes, where a mismatch between biological and chronological age is noticeable. Numerous studies have demonstrated that diabetes accelerates aging at the cellular and organ levels. Notable aging markers are telomerase reverse transcriptase (TERT), related to telomere length, and type 1 chain collagen (COL1A1), a key component of skin collagen. Additionally, age-related methylation increases, as revealed through methylation analysis, augmenting aspects of aging. However, the detailed interplay between aging and diabetes, particularly regarding methylation, remains underexplored and warrants further study to elucidate the biological links between the two. Materials and methods: In this study, we elucidate the modulatory influence of diabetes on the aging process, focusing specifically on the modifications in TERT in the kidney and COL1A1 in the skin using mice of Swiss Webster strain as the diabetes model. Specimens were categorized into three distinct chronological cohorts: chronologically young (16 weeks; n = 5), chronologically old (40 weeks; n = 5), and a periodically assessed group (16 weeks; n = 30), from which five mice were systematically sacrificed on a weekly basis. Results: Our findings reveal a marked impact of diabetes on the methylation statuses of TERT and COL1A1, characterized by an elevation in methylation levels within the periodic group (1st-6th week) and a simultaneous, progressive attenuation in the expression of TERT and COL1A1 genes. Conclusion: The observed alterations in the methylation levels of TERT and COL1A1 propound the hypothesis that diabetes potentially expedites the aging process, concomitantly impinging on the production of TERT and COL1A, ostensibly through the mechanism of promoter gene hypermethylation. [ABSTRACT FROM AUTHOR]

One hundred eighty pairs of tissues of esophageal squamous cell carcinoma (ESCC) were tested by the transcriptome sequencing in order to explore etiology factors. The chi‐square test and correlation analysis demonstrated that the relative expression levels of keratin 17 (KRT17) and collagen type I α1 chain (COL1A1) were significantly higher in EC with diabetes. Expression of KRT17 was correlated with blood glucose (r = 0.204, p = 0.001) and tumor size (r = −0.177, p = 0.038) in patients. COL1A1 correlated with age (r = −0.170, p = 0.029) and blood glucose levels (r = 0.190, p = 0.015). Experimental results of qRT‐PCR: KRT17 and COL1A1 genes were highly expressed in ESCC (p < 0.05). When the two genes were used as a combination test, the positive detection rate of EC was 90.6%, and the ROC curve had greater power. The KRT17 and COL1A1 genes had the potential to be biomarkers for the diagnosis of ESCC. [ABSTRACT FROM AUTHOR]

Mining exploration programmes are being expensive and risky due to the limitations of conventional prospecting methods in identifying desired mineralisation. Worldwide, mining exploration programmes have a success rate of approximately 0.7%. Bio-geochemical methods, a sub-branch of geochemical prospecting, are used to identify potential mineralisation areas by studying the distribution of plants containing certain metals. Turkey's leading position in the world in terms of boron reserves increases the strategic importance of boron. On the other hand, metagenome analysis is an important tool in scientific research for detecting microorganisms. Our study aims to develop a cost-effective and efficient biological alternative method for detecting boron mines. Metagenome analysis output showed correlation with the presence of Calothrix sp. NIES-3974, Snodgrassella alvi , Xanthomonas citri , X. citri pv. Fuscans, Pseudomonas viciae , and Aphanothecaceae bacteria and detecting of the potential boron traces in soil. Modelling studies were also conducted on aquaporin z protein, related to the boron uptake, that can be used for utilising from boron detection. [ABSTRACT FROM AUTHOR]

Background: Aneurysmal subarachnoid hemorrhage (aSAH) patients typically have poor prognoses. The anion gap (AG) has been proven to correlate with mortality in various critically ill patients. However, hypoalbuminemia can lead to underestimations of the true anion gap levels. This study was conducted to verify the prognostic value of single AG and albumin-corrected anion gap (ACAG) among aSAH patients. Methods: Significant factors in the univariate logistic regression analysis were included in the multivariate logistic regression analysis to explore the risk factors for mortality in aSAH patients and to confirm the independent relationship between ACAG and mortality. The restricted cubic spline (RCS) was used to visually show the relationship between ACAG level and mortality risk of aSAH patients. The predictive model for mortality was developed by incorporating significant factors into the multivariate logistic regression analysis. The prognostic value of ACAG and the developed model was evaluated by calculating the area under the receiver operating characteristics curve (AUC). Results: Among 710 aSAH patients, a 30-day mortality was observed in 20.3% of the cases. A positive relationship was demonstrated between the ACAG level and mortality in aSAH patients using the RCS curve. The multivariate logistic regression analysis helped discover that only six factors were finally and independently related to mortality of aSAH patients after adjusting for confounding effects, including the Hunt-Hess scale score (p = 0.006), surgical options (p < 0.001), white blood cell count (p < 0.001), serum chloride levels (p = 0.023), ACAG (p = 0.039), and delayed cerebral ischemia (p < 0.001). The AUC values for the AG, albumin, and ACAG in predicting mortality among aSAH patients were 0.606, 0.536, and 0.617, respectively. A logistic regression model, which includes the Hunt-Hess scale score, surgical options, white blood cell count, serum chloride levels, ACAG, and delayed cerebral ischemia, achieved an AUC of 0.911 for predicting mortality. Conclusion: The ACAG is an effective prognostic marker for aSAH patients. A prognostic model incorporating ACAG could help clinicians evaluate the risk of poor outcomes among aSAH patients, thereby facilitating the development of personalized therapeutic strategies. [ABSTRACT FROM AUTHOR]

Objectives: To ascertain the prevalence of transfusion transmissible infections )TTIs( across diverse donor groups in the Najran province. Additionally, to establish a potential association between the development of TTI and the donors' blood group, as determined by the ABO/Rh blood grouping system. Methods: Blood donation data of 4120 donors, spanning from January to December 2020, were retrospectively reviewed. The blood were screened for TTI markers, including hepatitis B surface antigen )HBsAg(, anti-hepatitis B core )anti-HBc(, antihepatitis C virus )anti-HCV(, anti-human immunodeficiency Original Article viruses 1 and 2 )anti-HIV1&2(, anti-human T-lymphotropic virus types 1 and 2 )anti-HTLV-1&2(, and syphilis antigen. Results: Positive TTI markers were detected in 10.9% of the donors. The most detected TTI marker was anti-HBc )8.9%(, followed by HBsAg )0.7%(. Other markers were individually detected in <1% of the donors. Anti-HBc-positive was significantly elevated among non-Saudi blood donors. There was an association between age groups and anti-HCV )p=0.002(, anti-HTLV )p=0.004( and syphilis antigen )p=0.02( markers positivity. The AB positive blood group exhibited the most positivity for TTI markers, followed by O positive blood group. Similarly, association was found between ABO group and HBsAg )p=0.01(, anti-HBc )p=0.001(, and anti-HCV )p<0.001( markers positivity. Conclusion: Emphasis on implementing robust screening measures for donated blood is underscored by this study. There is the need for future study to extensively evaluate TTI status to enhance our understanding of the trend in TTI. [ABSTRACT FROM AUTHOR]

Background: Intensive care unit admissions are largely attributed to sepsis in pediatrics. It is essential to diagnose an infection correctly and monitor it closely to optimize treatment and outcomes. Aim: This research was conducted to estimate the diagnostic utility of serum progranulin in pediatric sepsis. Patients and methods: This case-control study included 50 pediatric sepsis patients and 40 healthy matched controls. A peripheral blood sample was taken from the patients and controls then progranulin levels were measured using ELISA. Results: Serum progranulin values were significantly greater in pediatric sepsis patients than in controls (median 180.15 vs. 96.0 ng/ml, respectively: Mann-Whitney p < 0.001). Serum progranulin had good diagnostic power and was the best of laboratory parameters in the diagnosis of pediatric sepsis after CRP with ROC area under the curve (AUC) = 0.998. Using a cutoff value of 116.3 ng/ml PGRN had a sensitivity of 86.0% and a specificity of 100% with a positive predictive value of 100% and a negative predictive value of 85.1%. Serum progranulin levels were positively correlated with body weight and CRP levels and negatively correlated with platelets and hemoglobin levels. Progranulin levels in survivors were not statistically different from those in non-survivors. Conclusions and Recommendations: Serum progranulin may be a good biomarker for sepsis diagnosis in pediatrics. [ABSTRACT FROM AUTHOR]

Objective: Oral glucose tolerance test (OGTT) and glycated haemoglobin (HbA1c) have many limitations in diagnosing prediabetes. Glycated albumin (GA) estimation can be a potential tool for its early diagnosis. The present study aims to analyze the diagnostic efficacy of GA to identify prediabetes. Methods: Prediabetics (n = 406) and healthy (n = 406) subjects were included. OGTT was used as the diagnostic standard for identifying prediabetes. HbA1c was estimated in a Bio-Rad D-10 analyzer based on the High-Performance Liquid Chromatography (HPLC) method. GA was measured using the enzyme-linked immunosorbent assay (ELISA) technique and was expressed as a percent of total albumin. Total albumin was measured by the modified bromocresol Purple (BCP) dye-binding method in Siemen's autoanalyzer. Results: HbA1c (5.83 ± 0.57%) and GA (14.43 ± 1.92%) were significantly higher (p < 0.05) in the prediabetics as compared to healthy individuals. Both HbA1c and GA showed a significantly positive correlation with fasting plasma glucose (FPG) and 2-h plasma glucose. However, the correlation was stronger with 2-h plasma glucose for both parameters. GA and HbA1c also showed a significant positive correlation with each other. HbA1c, at 5.7% cut-off, predicted prediabetes with 74% sensitivity and 90% specificity. At the cut-off of 13.5%, GA showed 66% sensitivity and 85% specificity to identify pre-diabetes. The sensitivity of the combined tests was significantly greater than that for HbA1c alone (84% combined versus 74% HbA1c). Conclusion: GA, combined with HbA1c, can be used as a screening test for identifying pre-diabetes. Early diagnosis and interventions could prevent disease progression and limit dreadful complications. [ABSTRACT FROM AUTHOR]

Orexin-A is a neuropeptide product of the lateral hypothalamus that acts on two receptors, OX1R and OX2R. The orexinergic system is involved in feeding, sleep, and pressure regulation. Recently, orexin-A levels have been found to be negatively correlated with renal function. Here, we analyzed orexin-A levels as well as the incidence of SNPs in the hypocretin neuropeptide precursor (HCRT) and its receptors, HCRTR1 and HCRTR2, in 64 patients affected by autosomal dominant polycystic kidney disease (ADPKD) bearing truncating mutations in the PKD1 or PKD2 genes. Twenty-four healthy volunteers constituted the control group. Serum orexin-A was assessed by ELISA, while the SNPs were investigated through Sanger sequencing. Correlations with the main clinical features of PKD patients were assessed. PKD patients showed impaired renal function (mean eGFR 67.8 ± 34.53) and a statistically higher systolic blood pressure compared with the control group (p < 0.001). Additionally, orexin-A levels in PKD patients were statistically higher than those in healthy controls (477.07 ± 69.42 pg/mL vs. 321.49 ± 78.01 pg/mL; p < 0.001). Furthermore, orexin-A inversely correlated with blood pressure (p = 0.0085), while a direct correlation with eGFR in PKD patients was found. None of the analyzed SNPs showed any association with orexin-A levels in PKD. In conclusion, our data highlights the emerging role of orexin-A in renal physiology and its potential relevance to PKD. Further research is essential to elucidate the intricate mechanisms underlying orexin-A signaling in renal function and its therapeutic implications for PKD and associated cardiovascular complications. [ABSTRACT FROM AUTHOR]

Introduction: The genome-wide association study (GWAS) is a powerful approach to identify genomic regions associated with fertility traits that explain a significant portion of the genetic variance associated with these traits and identify the relevant causal mutations. Evaluating the correlation between each genotyped marker and trait is an essential strategy for GWAS studies that examine the effects of all markers by considering their possible interactions, environmental factors, and even mutual effects between markers. Recently, machine learning methods have been introduced to genomic topics, and the basis of these methods is different from the common methods of genomic evaluation. The machine learning method is used to estimate the genomic breeding values of the candidate animals by considering the training data (genotypic and phenotypic information of the reference population). One of the key advantages of this method is the ability to analyze large data. Machine learning is a branch of artificial intelligence whose goal is to achieve machines that can extract knowledge (learning) from the environment. A variety of machine learning methods (random forest, boosting, and deep learning) are used to model genetic variance and environmental factors, study gene networks, GWAS, study epistasis effects, and genomic evaluation. Random forest is one of the machine learning methods that has been successfully used in various fields of science. This research was conducted to identify markers and genes related to reproductive traits such as calving interval (CI), days open (DO), daughter pregnancy rate (DPR), and age at first calving (AFC) in Iranian Holstein dairy cattle. These traits have already been investigated with the ssGBLUP method and using a smaller sample size. However, in the present research, by using more genotyped animals, a random forest algorithm was used to identify markers and genes related to reproductive traits. Materials and methods: The records used in this research were provided by the National Animal Breeding Center and Promotion of Animal Products of Iran and included AFC, DO, CI, and DPR related to the genotyped bulls' daughters. In this research, the pedigree information of 2774183 animals was used. The genotypic information of the markers related to 2419 Holstein bulls was used. Genomic data quality control was performed using factors such as the number of genotyped SNPs per animal (ACR), the number of genotyped animals per SNP (CR), Hardy-Weinberg equilibrium (HWE), and minor allele Frequency (MAF). When filtering genomic data, the markers whose MAF was less than 5% were removed, and then the samples whose genotyped frequency was less than 90% were identified and removed. Then, the markers whose genotyping rate was less than 95% in the samples were identified and removed. Finally, the SNPs that deviated from the HWE test (P<10-6) were excluded from the analysis as a measure of genotyping error. To control the quality of genomic data, PLINK 1.9 software was used. Then Ranfog software was used in the Linux environment to perform analysis through random forest algorithm. Results and discussion: By using the random forest algorithm, a total of 21 important SNPs were observed, then important fertility trait candidate genes were identified by the gene ontology method, and 62 genes were within 250 Kb of these SNPs. The most significant SNP was observed for AFC. The main SNP for AFC is in ARSBFGL-NGS-22647 BTA3, for CI is in ARS-BFGL-NGS-114194 (BTA11), for DO is in BTA-74076 -no-rs (BTA5), and for DPR is in ARS-BFGL-NGS-32553 (BTA26). The researchers, who studied fertility traits in Nellore cattle using machine learning methods, identified MPZL1 and CD247 genes on chromosome number 3 and this gene was associated with age at first calving. Many pathways of cell biology affect the performance of reproductive traits. Research has reported the relationship between the CD247 gene and pathways of biology, including cell development and function. Research has shown that the IFFO2 gene plays an important role in the molecular structure of cells, as well as in the mechanism of blastocyst formation, embryos, and the length of gestation in cattle. In a study conducted on the mouse population on the structure of the flagellum and the sperm maturation process, the role of the ALDH4A1 gene in the sperm maturation process was reported. The association of the RPS6KC1 gene with pregnancy rate and antral follicle number in Nellore heifers has been reported. The KAT2B gene is a transcriptional activator that plays an essential role in regulating the correction of histone acetylation and plays an important role in improving carcass quality, muscle and fat development, and metabolism in native Chinese cattle. In addition, they play a key role in regulating biological processes and are related to cell growth, metabolism and immune system function. Conclusions: According to the objectives of this research, new information on markers and candidate genes related to reproductive traits in Iranian Holstein dairy cattle was reported. The markers and candidate genes identified in the present research can be used in genomic selection to improve the reproductive traits of Holstein dairy cattle. [ABSTRACT FROM AUTHOR]

Abstract Background Gestational diabetes mellitus (GDM) is the most common metabolic complication, which leads to short and long-term consequences in both mother and fetus exposed to hyperglycemia. The aetiology of this condition is proposed to be based on the dysfunction of the adipose tissue, which is characterised by the aberrant generation of adipokines. One of them is preadipocyte factor-1 (Pref-1), which could mediate controlling the adaptation of the maternal metabolism to pregnancy. Aims The study aims to examine the level of Pref-1 in the cord blood of healthy pregnant women’s neonates and fetuses born to mothers with GDM. Materials and methods Cord blood samples were collected from 30 newborns of mothers with GDM and 40 newborns of healthy pregnant women. Pref-1 concentrations were measured with an ELISA kit. Results Fetal Pref-1 concentrations were significantly lower in newborns of mothers with GDM compared to the normal pregnancy group children (5.32 ± 0.29 vs. 7.38 ± 0.53; p

Objective: This study was conducted to investigate the variants of the growth hormone receptor (GHR), growth hormone-releasing hormone (GHRH), pituitary-specific transcription factor-1 (PIT1), and signal transducer and activator of transcription 5A (STAT5) genes and their effect on growth performance and dressing percentage (DP) parameters. Materials and Methods: A total of 401 DNA samples from Sumba Ongole (SO) cattle were utilized for the polymerase chain reaction-restriction fragment length polymorphism method, of which 200 samples were used for the study of DP association and 74 samples were used to investigate growth performance. The SO cattle growth performance includes the following: birth weight, weaning weight at 205 days of age, weaning average daily gain (ADG), yearling weight at 365 days of age, and post-weaning ADG. Results: The GHR, GHRH, PIT1, and STAT5A genes showed polymorphism. The highest polymorphism information content value was shown in the STAT5A gene. The highest DP value was found in the SO cattle population with the CC genotype (STAT5A), and the lowest DP value was found in the SO cattle population with the GG genotype (GHR). The GHR and STAT5A genotypes were highly associated (p < 0.05) with the DP parameter. Based on locus combination analysis, the highest DP value was found in the SO cattle population with AG|CC genotype (GHR|STAT5A) (57.85%), AG|BB|CC genotype (GHR|GHRH|STAT5A) (57.85%), and AA|BB|BB|CC genotype 18 (GHR|GHRH|PIT1|STAT5A) (56.02%). Conclusion: All investigated genes in this study were polymorphic but were not associated with several growth parameters. The GHR and STAT5A genes can be proposed as genetic markers for the high DP trait in SO cattle in Indonesia, especially the AA genotype (GHR) and CC genotype (STAT5A). [J Adv Vet Anim Res 2024; 11(1.000): 85-92]

Abstract Objective Tumors are highly heterogeneous, and within their parenchyma, a small population of tumor-stem cells possessing differentiation potential, high oncogenicity, and self-renewal capabilities exists. These cells are pivotal in mediating tumor development, chemotherapy resistance, and recurrence. Ovarian cancer shares characteristics with tumor stem cells, making it imperative to investigate molecular markers associated with these cells. Methods Stem cell-related genes were collected, and molecular subtypes were established based on gene expression profiles from The Cancer Genome Atlas using the R package tool “ConsensusClusterPlus.” Multi-gene prognostic markers were identified using LASSO regression analysis. Gene set enrichment analysis was employed to gain insights into the potential molecular mechanisms of these identified markers. The robustness of these prognostic markers was analyzed across different cohorts, and their clinical independence was determined through multivariate Cox analysis. A nomogram was constructed to assess the model’s clinical applicability. Immunohistochemistry was performed to validate the expression of hub genes. Results Utilizing 49 tumor stem cell-related genes associated with prognosis, 362 ovarian cancer samples were divided into two distinct clusters, revealing significant prognostic disparities. A seven-gene signature (GALP, CACNA1C, COL16A1, PENK, C4BPA, PSMA2, and CXCL9), identified through LASSO regression, exhibited stability and robustness across various platforms. Multivariate Cox regression analysis confirmed the signature’s independence in predicting survival in patients with ovarian cancer. Furthermore, a nomogram combining the gene signature demonstrated strong predictive abilities. Immunohistochemistry results indicated significantly elevated GALP, CACNA1C, COL16A1, PENK, C4BPA, PSMA2, and CXCL9 expression in cancer tissues. Conclusion The seven-gene signature holds promise as a valuable tool for decision-making and prognosis prediction in patients with ovarian cancer.

Simple Summary: This study suggests that GLR, along with other factors like CA 19-9 levels and symptoms, can help predict long-term survival outcomes in PDAC patients following surgical resection, aiding in the identification of high-risk individuals who may benefit from closer monitoring or more aggressive treatment approaches. Background: We retrospectively evaluated the usefulness of an elevated glucose-to-lymphocyte ratio (GLR) as a sensitive prognostic biomarker of disease-specific survival in 338 patients who underwent surgical resection of pancreatic ductal adenocarcinoma (PDAC). Methods: The optimal GLR cutoff value was determined using the method of Contal and O'Quigley. Patient demographics, clinical information, and imaging data were analyzed to identify preoperative predictors of long-term survival outcomes. Results: Elevated GLR correlated significantly with aggressive tumor biologic behaviors, such as a high carbohydrate antigen (CA) 19-9 level (p = 0.003) and large tumor size (p = 0.011). Multivariate analysis identified (1) GLR > 92.72 [hazard ratio (HR) = 2.475, p < 0.001], (2) CA 19-9 level > 145.35 (HR = 1.577, p = 0.068), and (3) symptoms (p = 0.064) as independent predictors of long-term, cancer-specific survival. These three risk factors were used to group patients into groups 1 (0 factors), 2 (1–2 factors), and 3 (3 factors), which corresponded to significantly different 5-year overall survival rates (50.2%, 34.6%, and 11.7%, respectively; p < 0.001). Conclusions: An elevated preoperative GLR is associated with aggressive tumor characteristics and is an independent predictor of poor postoperative prognosis in patients with PDAC. Further prospective studies are required to verify these findings. [ABSTRACT FROM AUTHOR]

Cassava productivity is constrained by low soil nitrogen, which is predominant in most cassava-growing regions in the tropics and subtropical agroecology. Improving the low nitrogen tolerance of cassava has become an important breeding objective. The current study aimed to develop cassava varieties with improved nitrogen use efficiency by identifying genomic regions and candidate genes linked to nitrogen use efficiency in cassava. A genome-wide association study (GWAS) was performed using the Genome Association and Prediction Integrated Tool (GAPIT). A panel of 265 diverse cassava genotypes was phenotyped for 10 physiological and agronomic traits under optimum and low-nitrogen regimes. Whole-genome genotyping of these cassava cloneswas performed using the Diversity Arrays Technology (DArTseq) sequencing platform. A total of 68,814 single nucleotide polymorphisms (SNPs) were identified, which were spread across the entire 18 chromosomes of the cassava genome, of which 52 SNPs at various densities were found to be associated with nitrogen use efficiency in cassava and other yield-related traits. The putative genes identified through GWAS, especially those with significant associated SNP markers for NUE and related traits have the potential, if deployed appropriately, to develop cassava varieties with improved nitrogen use efficiency, which would translate to a reduction in the economic and environmental cost of cassava production. [ABSTRACT FROM AUTHOR]

Annual medic (Medicago spp.) germplasm was collected from the Crimean Peninsula of Ukraine in 2008 to fill gaps in geographic coverage in the United States department of Agriculture, Agricultural Research Service, National Plant Germplasm System (NPGS) temperate-adapted forage legume collection. A total of 102 accessions across 10 Medicago species were collected. To assess genetic diversity, population structure, and to confirm taxonomic identities, the collections were phenotypically and genetically characterized. Phenotyping included the use of 24 descriptor traits while genetic characterization was accomplished using a 3K Diversity Array Technologies (DArTag) panel developed for alfalfa (Medicago sativa L.). For both field and molecular characterizations, a reference set of 92 geographically diverse and speciesrepresentative accessions were obtained from the NPGS collection. Phenotypic descriptors showed consistency among replicated plants within accessions, some variation across accessions within species, and evident distinctions between species. Because the DArTag panel was developed for cultivated alfalfa, the transferability of markers to the species being evaluated was limited, resulting in an average of ~1,500 marker loci detected per species. From these loci, 448 markers were present in 95% of the samples. Principal component and phylogenetic analysis based on a larger set of 2,396 selected markers clustered accessions by species and predicted evolutionary relationships among species. Additionally, the markers aided in the taxonomic identity of a few accessions that were likely mislabeled. The genotyping results also showed that sampling individual plants for these mostly self-pollinating species is sufficient due to high reproducibility between single (n=3) and pooled (n=7) biological replicate leaf samples. The phenotyping and the 2,396 Single Nucleotide Polymorphism (SNP) marker set were useful in estimating population structure in the Crimean and reference accessions, highlighting novel and unique genetic diversity captured in the Crimean accessions. This research not only demonstrated the utility of the DArTag marker panel in evaluating the Crimean germplasm but also highlighted its broader application in assessing genetic resources within the Medicago genus. Furthermore, we anticipate that our findings will underscore the importance of leveraging genetic resources and advanced genotyping tools for sustainable crop improvement and biodiversity conservation in annual medic species. [ABSTRACT FROM AUTHOR]

Smoking significantly elevates the risk of lung diseases such as chronic obstructive pulmonary disease (COPD) and lung cancer. This risk is attributed to the harmful chemicals in tobacco smoke that damage lung tissue and impair lung function. Current research on the impact of smoking on gene expression in specific lung cells is limited. This study addresses this gap by analyzing gene expression profiles at the single-cell level from 43,539 lung endothelial cells, 234,349 lung epithelial cells, 189,843 lung immune cells, and 16,031 lung stromal cells using advanced machine learning techniques. The data, categorized by different lung cell types, were classified into three smoking states: active smoker, former smoker, and never smoker. Each cell sample encompassed 28,024 feature genes. Employing an incremental feature selection method within a computational framework, several specific genes have been identified as potential markers of smoking status in different lung cell types. These include B2M, EEF1A1, and TPT1 in lung endothelial cells; FTL and MT-ATP8 in lung epithelial cells; HLA-B and HLA-C in lung immune cells; and HSP90B1 and LCN2 in lung stroma cells. Additionally, this study developed quantitative rules for representing the gene expression patterns related to smoking. This research highlights the potential of machine learning in oncology, enhancing our molecular understanding of smoking's harm and laying the groundwork for future mechanism-based studies. [ABSTRACT FROM AUTHOR]

Cancer stem cells (CSCs) represent a subpopulation within tumors that promote cancer progression, metastasis, and recurrence due to their self-renewal capacity and resistance to conventional therapies. CSC-specific markers and signaling pathways highly active in CSCs have emerged as a promising strategy for improving patient outcomes. This review provides a comprehensive overview of the therapeutic targets associated with CSCs of solid tumors across various cancer types, including key molecular markers aldehyde dehydrogenases, CD44, epithelial cellular adhesion molecule, and CD133 and signaling pathways such as Wnt/β-catenin, Notch, and Sonic Hedgehog. We discuss a wide array of therapeutic modalities ranging from targeted antibodies, small molecule inhibitors, and near-infrared photoimmunotherapy to advanced genetic approaches like RNA interference, CRISPR/Cas9 technology, aptamers, antisense oligonucleotides, chimeric antigen receptor (CAR) T cells, CAR natural killer cells, bispecific T cell engagers, immunotoxins, drug-antibody conjugates, therapeutic peptides, and dendritic cell vaccines. This review spans developments from preclinical investigations to ongoing clinical trials, highlighting the innovative targeting strategies that have been informed by CSC-associated pathways and molecules to overcome therapeutic resistance. We aim to provide insights into the potential of these therapies to revolutionize cancer treatment, underscoring the critical need for a multi-faceted approach in the battle against cancer. This comprehensive analysis demonstrates how advances made in the CSC field have informed significant developments in novel targeted therapeutic approaches, with the ultimate goal of achieving more effective and durable responses in cancer patients. [ABSTRACT FROM AUTHOR]

Brain-derived neurotrophic factor (BDNF) is a predominant neurotrophic factor in the brain, indispensable for neuronal growth, synaptic development, neuronal repair, and hippocampal neuroplasticity. Among its genetic variants, the BDNF Val66Met polymorphism is widespread in the population and has been associated with the onset and aggravation of diverse pathologies, including metabolic conditions like obesity and diabetes, cardiovascular ailments, cancer, and an array of psychiatric disorders. Psychiatric disorders constitute a broad category of mental health issues that influence mood, cognition, and behavior. Despite advances in research and treatment, challenges persist that hinder our understanding and effective intervention of these multifaceted conditions. Achieving and maintaining stable body weight is pivotal for overall health and well-being, and the relationship between psychiatric conditions and body weight is notably intricate and reciprocal. Both weight gain and loss have been linked to varying mental health challenges, making the disentanglement of this relationship critical for crafting holistic treatment strategies. The BDNF Val66Met polymorphism's connection to weight fluctuation in psychiatric patients has garnered attention. This review investigated the effects and underlying mechanisms by which the BDNF Val66Met polymorphism moderates body weight among individuals with psychiatric disorders. It posits the polymorphism as a potential biomarker, offering prospects for improved monitoring and therapeutic approaches for mental illnesses. [ABSTRACT FROM AUTHOR]

The utilization of heterosis is of great significance in improving rice yield. To explore the physiological and genetic basis for high yield in indica–japonica hybrid rice, Zheyou18 (z18) and Yongyou12 (y12) were used as materials and compared with indica hybrid rice, Zheyou12 (z12); japonica hybrid rice, Liangyoupeijiu (LYPJ); and the conventional lines zhe04B (04B) and zhehui818 (h818) under seedling growth vigor, functional leaf morphology, chlorophyll content, yield component, panicle trait, and InDel heterosis analysis. Z18 and y12 showed the largest increase in plant height 6 d and 9 d after germination; the root dry weight of z18 was 31.2% and 42.0% higher than its parents on the 12th d. The length of functional leaves ranked in the middle, while the width was the largest, resulting in z18 and y12 having the largest leaf area. Yield components showed that z18 and y12 had the highest number of primary branches, spikelets, and grains, and grain yield, which was 58.1 g in z18, increased by 29.8% and 8.7%, respectively, in comparison with h818 and LYPJ. The InDel genetic distance was significantly positively correlated with single spike weight, with r reaching 0.771, making it the only consistent and most correlated among the seven traits. Therefore, we speculated that as the InDel genetic distance expands, heterosis mainly manifests in the increase in single spike weight. This study comprehensively explored the physiological mechanism of yield improvement in indica–japonica-hybrid rice and used InDel genetic distances to study the genetic basis of heterosis, which will be helpful for future rice yield improvement. [ABSTRACT FROM AUTHOR]

In this paper, a marker and its real-time tracking method are proposed. Different from existing technologies that recognize the markers by spatial event features, which lead to many practical problems, we discover the possibility of using temporal features. Strobe LEDs (light emitting diode) are used as markers to produce periodically flipping events, and a fast clustering-based algorithm is designed to track and recognize these markers simultaneously. Experiments demonstrate that our methods have superior speed and accuracy compared to state-of-the-arts. The markers can be stably tracked in many challenging situations, thus can be used in various visual tracking applications. The proposed method introduces a new marker and its corresponding recognition algorithm for event camera-based targets tracking, offering a reliable solution for various applications. [ABSTRACT FROM AUTHOR]

The study focuses on the application range of nitrous oxide as a hold-up time marker in supercritical fluid chromatography (SFC). This compound has been suggested a decade ago to be used as unretained marker, something that the field of SFC was missing for a long time, since its beneficial properties make it an ideal candidate as hold-up time marker. Determination of the hold-up volume and actual volumetric flow rates have always been problematic in SFC due to the compressibility of carbon dioxide and one part of this is the difficulty of hold-up time measurements. Depending on the mobile phase, different methods have been used to measure the hold-up time with varying results. Nitrous oxide and other molecules have been compared in different conditions, mobile phases and stationary phases. In all cases, nitrous oxide gave the lowest elution times. However, detection was difficult in mobile phases containing 10% or more of organic modifier, because most solvents mask the signal of nitrous oxide. Interestingly, the choice of stationary phase also had a slight effect on detection, while different pressure and temperature settings affected each compound in a different manner. [ABSTRACT FROM AUTHOR]

Objective: Tumors are highly heterogeneous, and within their parenchyma, a small population of tumor-stem cells possessing differentiation potential, high oncogenicity, and self-renewal capabilities exists. These cells are pivotal in mediating tumor development, chemotherapy resistance, and recurrence. Ovarian cancer shares characteristics with tumor stem cells, making it imperative to investigate molecular markers associated with these cells. Methods: Stem cell-related genes were collected, and molecular subtypes were established based on gene expression profiles from The Cancer Genome Atlas using the R package tool "ConsensusClusterPlus." Multi-gene prognostic markers were identified using LASSO regression analysis. Gene set enrichment analysis was employed to gain insights into the potential molecular mechanisms of these identified markers. The robustness of these prognostic markers was analyzed across different cohorts, and their clinical independence was determined through multivariate Cox analysis. A nomogram was constructed to assess the model's clinical applicability. Immunohistochemistry was performed to validate the expression of hub genes. Results: Utilizing 49 tumor stem cell-related genes associated with prognosis, 362 ovarian cancer samples were divided into two distinct clusters, revealing significant prognostic disparities. A seven-gene signature (GALP, CACNA1C, COL16A1, PENK, C4BPA, PSMA2, and CXCL9), identified through LASSO regression, exhibited stability and robustness across various platforms. Multivariate Cox regression analysis confirmed the signature's independence in predicting survival in patients with ovarian cancer. Furthermore, a nomogram combining the gene signature demonstrated strong predictive abilities. Immunohistochemistry results indicated significantly elevated GALP, CACNA1C, COL16A1, PENK, C4BPA, PSMA2, and CXCL9 expression in cancer tissues. Conclusion: The seven-gene signature holds promise as a valuable tool for decision-making and prognosis prediction in patients with ovarian cancer. [ABSTRACT FROM AUTHOR]

Introduction: Lymph node metastasis (LNM) is a critical prognostic factor for colorectal cancer (CRC). Due to the potential influence of immune system on CRC progression, investigation into lymphocyte subsets as clinical markers has gained attention. The objective of this study was to assess the capability of lymphocyte subsets in evaluating the lymph node status and prognosis of CRC. Methods: Lymphocyte subsets, including T cells (CD3+), natural killer cells (NK, CD3- CD56+), natural killer-like T cells (NK-like T, CD3+ CD56+), CD38+ NK cells (CD3- CD56+ CD38+) and CD38+ NK-like T cells (CD3+ CD56+ CD38+), were detected by flow cytometry. Univariate and multivariate analyses were used to assess the risk factors of LNM. The prognostic role of parameters was evaluated by survival analysis. Results: The proportion of CD38+ NK cells within the NK cell population was significantly higher in LNM-positive patients (p <0.0001). However, no significant differences were observed in the proportions of other lymphocyte subsets. Poorer histologic grade (odds ratio [OR] =4.76, p =0.03), lymphovascular invasion (LVI) (OR =22.38, p <0.01), and CD38+ NK cells (high) (OR =4.54, p <0.01) were identified as independent risk factors for LNM. Furthermore, high proportion of CD38+ NK cells was associated with poor prognosis of CRC patients (HR=2.37, p =0.03). Conclusions: It was demonstrated that the proportion of CD38+ NK cells was a marker overexpressed in LNM-positive patients compared with LNM-negative patients. Moreover, an elevated proportion of CD38+ NK cells is a risk factor for LNM and poor prognosis in CRC. [ABSTRACT FROM AUTHOR]