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PurposeIdentifying high-risk populations and diagnosing gastric cancer (GC) early remains challenging. This study aimed to establish and verify a nomogram model for the early diagnosis of GC based on conventional laboratory indicators.MethodsWe performed a retrospective analysis of the clinical data of 2,770 individuals with first diagnosis of GC and 1,513 patients with benign gastric disease from January 2018 to December 2022. The cases were divided into the training set and validation set randomly, with a ratio of 7:3. Variable screening was performed by least absolute shrinkage and selection operator (LASSO) and logistic regression analysis. A nomogram was constructed in the training set to assist in the early diagnosis of GC.ResultsThere were 4283 patients included in the study, with 2998 patients assigned in the training set and 1285 patients in the validation set. Through LASSO regression and logistic regression analysis, independent variables associated with GC were identified, including CEA, CA199, LYM, HGB, MCH, MCHC, PLT, ALB, TG, HDL, and AFR. The nomogram model was constructed using the above 11 independent indicators. The AUC was 0.803 for the training set and 0.797 for the validation set, indicating that the model showed high clinical diagnostic efficacy. The calibration curves and decision curve analysis (DCA) of the nomogram presented good calibration and clinical application ability.ConclusionBased on the analysis of large sample size, we constructed a nomogram model with 11 routine laboratory indicators, which showed good discrimination ability and calibration.

ObjectivesWe evaluated the ability and accuracy of preoperative identification and localization of sentinel lymph nodes (SLNs) using intradermal injection of ultrasound contrast agent.Materials and methodsProspectively recruited 191 early breast cancer patients with clinically negative axillary lymph nodes (ALNs). All participants received intradermal injection of microbubble contrast agent. Following the identification and localization of SLNs using contrast-enhanced ultrasound (CEUS), Markers were deployed in the SLNs US-guided. Subsequently, the SLNs with Markers were stained and marked with a suspension of nano-carbon US-guided to assist in intraoperative localization of SLNs. Standard SLNB with methylene blue tracing was performed intraoperatively to assess the consistency between the two methods of SLNs localization, thereby determining the ability and accuracy of CEUS in identifying and localizing SLNs.ResultsA total of 179 patients were included in the final evaluation analysis, in which a microbubble contrast agent was injected subcutaneously in the areolar region. A total of 201 SLNs were identified, with a median of 1 SLN per patient. Each SLN was identified in 157 patients, and two SLNs were identified in 22 patients. Among the 201 SLNs from the 179 patients, the proportion that could be individually matched between CEUS and the blue dye method was 95.5% (192/201), and the consistency evaluation in SLNs identification between CEUS and blue dye staining was excellent (Kappa value = 0.62, P < 0.001).ConclusionThe consistency of identification and localization of SLNs in early breast cancer patients between CEUS and the blue dye method was strong.

This study focuses on the utilization of augmented reality (AR) to enable comprehensive visualization of objects. Its primary objective is to develop and evaluate an AR application as a medium for introducing pneumatic hydraulic components. The research method employs a development research approach, following the assessment, design, development, implementation, and evaluation steps proposed by Lee and Owens. The feasibility of the product is determined through various assessments, including black box testing, validation by media experts, validation by content experts, and evaluation of initial user response. The outcome of this study is application software incorporating AR technology for the purpose of introducing pneumatic hydraulic components, along with a corresponding workbook. Whereas the application is compatible with the Android operating system and utilizes QR codes as markers for augmented reality objects, which are conveniently included within the workbook. Performance testing reveals that all application functions perform exceptionally well according to black box testing. Furthermore, the content expert feasibility assessment yields results categorized as “Good,” while both the media expert feasibility and initial user response tests indicate “Very Good” outcomes.

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 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

Background and Objectives: Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by a dense desmoplastic stroma with a poor prognosis. The aim of this study was to investigate whether resolvin (Rv) D1 could be used as a potential serum biomarker to discriminate between PDAC and acute pancreatitis (AP). Materials and Methods: In total, 67 patients were enrolled in the present study, including 21 patients with resectable PDAC, 23 patients with metastatic PDAC, 23 patients with AP, and a control group of 21 healthy individuals. RvD1 levels of PDAC patients were also analyzed through ELISA at the 6th postoperative month. Results: The mean RvD1 was 1169.24 ± 285.99 in the control group, 885.04 ± 134.25 in the AP group, 728.57 ± 140.1 in the PDAC group, and 670.09 ± 105.6 in the metastatic pancreatic cancer (PC) group. RvD1 was significantly lower in PDAC and metastatic PC groups compared to controls and patients with AP, while it was significantly lower in patients with AP compared to the control groups. Postoperative RvD1 levels of patients with PDAC were significantly higher than preoperative levels (728.57 ± 140.1 vs. 885.43 ± 275.57). In the ROC analysis, when the cut-off value for serum RvD1 level was 825 ng/L, it was found to predict PDAC from metastatic PC with 84.1% sensitivity and 81.8% specificity. Conclusions: Serum RvD1 is a new biomarker for the detection of PDAC. Serum RvD1 may provide an important diagnostic contribution in clinical practice to predict PDAC. Serum RvD1 levels were found to be predictive with high sensitivity and specificity in differentiating PDAC from metastatic PC. However, it was concluded that serum RvD1 levels cannot be used as a detection marker to differentiate PDAC from AP. RvD1 could be a representative agent of a new class of drugs to be proposed for innovative treatment of AP and PDAC. Our future study will investigate whether RvD1 can be a marker to differentiate from chronic pancreatitis.

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]

The tarnished plant bug, Lygus lineolaris (Palisot de Beauvois) (Hemiptera: Miridae), is a highly polyphagous insect feeding on many wild host plants and a pest of economically important cultivated crops. The landscape composition plays an important role on the population dynamics of tarnished plant bugs and merits further examination to better manage populations across the agroecosystem. In this study, we evaluated the potential of eight oral biomarkers in combination with an inexpensive and portable fluorescent adapter in order to track the movement of L. lineolaris. Tarnished plant bugs from a laboratory colony were exposed to 8 biomarkers (Safranin O, Acridine Orange, Rhodamine B., Fluorescein sodium salt, Acid Fuchsin, Brilliant Blue, Fluorescent Brightener 28, and Carmoisine) contained in a 10% honey solution using three ingestion methods (dye-infused floral foam, dye-overlaid diet, and a dye-incorporated diet). At 24, 48, and 72 h post-exposure, the L. lineolaris nymphs and adults were removed from each treatment, killed by freezing and evaluated for florescence using a microscope equipped with a NightSea™ Florescence adapter under different lighting and filter combinations. The results indicated that Safranin O, Rhodamine B, and Acridine Orange are potentially useful as oral biomarkers for both nymph and adult L. Lineolaris when incorporated into a honey water solution and delivered via ingestion by floral foam, diet-overlay, or incorporated into their diet. This study provides information usable by ecologists and entomologists for to selecting biomarkers for particular life stages to address the different mobile phases of an insect life cycle. Resumen La chinche lygus, Lygus lineolaris (Palisot de Beauvois) (Hemiptera: Meridae) es un insecto altamente polífago que se alimenta de hospederos naturales y cultivos de importancia económica. El medio ambiente juega un papel importante sobre las dinámicas poblacionales de la chinche lygus, y amerita estudios más a fondo para un mejor manejo de sus poblaciones a través del ecosistema. En el presente estudio se evaluó el potencial de ocho marcadores biológicos-orales en combinación con un adaptador fluorescente portátil y fácil de adquirir con el fin de hacer el seguimiento en los movimientos de L. lineolaris. Una colonia de laboratorio de chinche lygus se expuso a 8 biomarcadores (Safranin O, Acridine naranja, Rhodamine B., Flourescein sodio sal, ácido Fuchsin, Brilliant azul, Brillante Floreciente 28, tintura Carmoisine) en una solución de agua con miel al 10%, los cuales se utilizaron tres métodos de ingestión; infusión de tintura en espuma florar, tintura superpuesta sobre la superficie de dieta y tintura incorporada en dieta. En intervalos de 24, 48 y 72 postratamiento, ninfas y adultos de L. lineolaris se removieron de cada tratamiento y se trasladaron a un congelador hasta que murieron. Los cadáveres fueron evaluados por florescencia usando un microscopio equipado con un adaptador NighSea TM fluorescente bajo diferentes combinaciones de luces y filtros. Los resultados indicaron que Safranin O, Rhrodamine B y Acridine naranja, son potencialmente útiles como marcadores biológico-orales para ninfas y adultos de L. lineolaris cuando se incorporan en agua-miel humedecida en espuma floral, solución puesta en la superficie de dieta y solución incorporada en dieta. Este estudio proporciona información útil para ecólogos y entomólogos para seleccionar marcadores biológicos para determinados estados de vida enfocados en las fases móviles del ciclo de vida de un insecto. [ABSTRACT FROM AUTHOR]

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Preclinical test is a stage in evaluating potential drug candidates for diabetes mellitus (DM). However, developing an animal model that accurately replicates the various pathophysiological and etiological aspects of DM as seen in humans presents significant challenges. To induce diabetes, streptozotocin (STZ) in single doses or combination with nicotinamide (NIC) is often used. Treating diabetes conditions has a low success rate, compounded by the complexity of numerous affected biochemical profiles, presenting a significant research challenge. Therefore, this research aimed to determine the biochemical and triglyceride-glucose index (TyG) profile in high doses of STZ-NIC-induced diabetes in the rat model. The population consisted of 18 rates divided into three groups, each containing six. Group I (the normal group) consisted of healthy rats who were given standard feed and drink. In groups II and III, diabetes was induced intraperitoneally with 50 and 65 mg/kg of STZ in addition to 230 mg/kg of NIC. Observations were made for 6 weeks after the rats were diagnosed with diabetes having blood glucose levels of ≥ 250 mg/dL 72 hours after STZ-NIC induction. The data were evaluated statistically by one-way analysis of variance (ANOVA), followed by the least significant difference (LSD) test (p ≤ 0.05). The result showed significant differences in blood biochemistry, specifically in the parameters of blood glucose, SGPT, and SGOT with increasing doses of STZ-NIC (p<0.05), but not in total cholesterol, triglycerides, albumin, total protein, and TyG ( p<0.05). The high doses of STZ-NIC administration can produce DM models with different blood biochemical profiles but not in TyG. [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]

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]

The color Doppler twinkling artifact has been attributed to existing microbubbles or cavitation occurring on rough objects such as kidney stones, some breast biopsy clips, catheter guidewires and sandpaper. The objective was to investigate the correlation between the surface characteristics of helical constructs with different groove geometries and the occurrence of twinkling, as well as to identify locations conducive to bubble retention and/or cavitation. Six half-cylinders were created with a microscale 3-D printer with 5 µm resolution to replicate the geometry of twinkling helical constructs resembling catheter guidewires. Four copies of each marker including a non-twinkling control were printed. The half-cylinders had pitch (peak-to-peak distance) values ranging from 87.5 to 343 µm and amplitude (groove depth) values ranging from 41.5 to 209 µm. The half-cylinders were submerged in degassed water and optically imaged before and after ultrasound insonification to visualize bubbles on the cylinders. The cylinders remained submerged while scanning with the color Doppler mode at frequencies from 3.1 to 6.3 MHz using a GE Logiq E9 scanner and 9L linear array transducer. Two markers exhibited twinkling: one with pitch-to-amplitude ratio of 174/210 µm/µm (0.8) that twinkled only with pre-existing bubbles on the marker; the other had a ratio of 87/87 µm/µm (1.00) that twinkled without pre-existing bubbles on the marker. This work provides strong evidence that both existing bubbles and either cavitation or ultrasound wave interactions with patterned or rough surfaces are significant factors in producing the twinkling signature. [ABSTRACT FROM AUTHOR]

Background: Mid- to late-stage Parkinson's disease (PD) is often linked with worsened and significant impairment of motor activities, but existing prognostic markers do not adequately capture the risk of loss of balance in PD patients. This study aims to develop a risk prognostic model for mid- to late-stage PD and identify prognostic factors that are indicative of impending loss of balance and falls. Methods: The study included 307 participants of which 75 were diagnosed with idiopathic PD and 232 were neurological or non-neurological controls. Among the PD group, 46 were early-stage (Hoehn and Yahr [H&Y] = 1,2) with no significant loss of balance while 29 were mid- to late-stage (H&Y = 3,4,5) which is characterized by loss of balance and falls. Multivariable logistic regression (MLR) was used to develop a prognostic model for mid- to late-stage PD. Model discrimination was assessed by ROC curves. The model was internally validated through bootstrapping and calibration plots. Results: The relevant factors identified and included in the final MLR model were shortness of breath, age, swollen joints, heme oxygenase-1 (HO-1) protein, and total salivary protein. The model had an AUC of 0.82 (95% CI = 0.71–0.92) and was well calibrated (calibration slope = 0.77, intercept = 0.03). The likelihood of shortness of breath (OR = 7.91, 95% CI = 1.63–45.12) was significantly higher among mid- to late-stage PD than early-stage. Age and total salivary protein were also significantly higher among mid- to late-stage PD. Conclusion: The MLR prognostic model for mid- to late-stage PD may assist physicians in identifying patients at high risk for loss of balance and falls. [ABSTRACT FROM AUTHOR]

Pituitary adenomas secreting adrenocorticotropin hormone (ACTH), known as ACTH-secreting pituitary adenomas, cause hypercortisolism by overproducting ACTH and stimulating bilateral adrenal cortical hyperplasia, a condition also known as Cushing’s disease (CD), which is the most common cause of endogenous hypercortisolism. ACTH-secreting pituitary adenomas lead to a series of severe clinical syndromes, including electrolyte disturbances and disorders of glucose and lipid metabolism, affecting multiple organs and systems throughout the body. Transsphenoidal neuroendoscopic surgery is the first-line treatment for ACTH-secreting pituitary adenomas, with a high remission rate, but postoperative recurrence and persistent disease remain unsolved in the treatment of ACTH-secreting pituitary adenomas. The pathological evaluation of ACTH-secreting pituitary adenomas has important value in determining the nature of the lesions, predicting the prognosis, and selecting the drug therapy. This article reviews the advances in the pathologic evaluation of ACTH-secreting pituitary adenomas, including new immunohistochemical markers and microscopic special features. [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]

Summary: The nutritional value of Hainan camellia oil is incomparable to other places, and Hainan camellia oil is expensive, so unscrupulous businessmen often mix other edible oils into them for illegal profit. This study detected the changes of volatile components in Hainan camellia oil adulterated with five edible oils (peanut, soybean, corn, rapeseed, and sunflower oils) using comprehensive two‐dimensional gas chromatography and quadrupole time‐of‐flight mass spectrometry (HS‐SPME‐GC × GC‐Q‐TOFMS). The principal component analysis (PCA) score plot showed that pure Hainan camellia oil (PHCO) and Hainan camellia oil samples were adulterated with other edible oils clearly to identify the adulteration separated from each other. The adulteration of PHCO could be accurately predicted using the developed PCA and OPLS‐DA models for concentrations as low as 5%. More importantly, several potential markers were found to identify the impersonate PHCO. Therefore, the volatile compound determination based on HS‐SPME‐GC × GC‐Q‐TOFMS proved to be an effective method for detecting adulteration of other edible oils in PHCO. [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]

Plant secondary cell wall provides physical support for upright growth and transportation of water and nutrients. Detailed characterization of the molecular mechanism for SCW biosynthesis would be of great importance for breeding maize varieties. Cellulose, synthesized by the cellulose synthase complex (CSC), composed of cellulose synthase (CesA) proteins, is a main component of plant cell walls. However, CesA genes that are specific for SCW biosynthesis in maize were undefined. In our study, ZmCesA10, 11, and 12 were characterized to be responsible for SCW biosynthesis in maize. ZmCesA10, 11, and 12 interact with each other and are co-expressed in maize culms and roots. Mutants for ZmCesA10, 11, and 12, exhibited an increased culm brittleness, a reduced cell wall thickness, and cellulose content. We concluded that ZmCesA10, 11, and 12 would be markers for the SCW study, and finally this study helps in the construction of the molecular network for SCW biosynthesis in maize. [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]

In the realm of biomedical advancement, extracellular vesicles (EVs) are revolutionizing our capacity to diagnose, monitor, and predict disease progression. However, the comprehensive exploration and clinical application of EVs face significant limitations due to the current isolation techniques. The size exclusion chromatography, commercial precipitation reagents, and ultracentrifugation are frequently employed, necessitating skilled operators and entailing challenges related to consistency, reproducibility, quality, and yields. Notably, the formidable challenge of extracellular vesicle isolation persists when dealing with clinical samples of limited availability. This study addresses these challenges by aiming to devise a rapid, user-friendly, and high-recovery EVs isolation technique tailored for blood samples. The NTI-EXO precipitation method demonstrated a 5-fold increase in the recovery of serum EVs compared to current methodologies. Importantly, we illustrate that a mere two drops of blood (∼100 µL) suffice for the recovery of enriched EVs. The integrity and quality of these isolated EVs were rigorously assessed for the size, purity, and contaminants. This method was validated through the successful isolation of EVs from organ transplant recipients to detect disease-specific exosomal markers, including LKB1, SARS-CoV-2 spike protein, and PD-L1. In conclusion, NTI-EXO method can be used for small clinical samples, thereby advancing discoveries in the EV-centric domain and propelling the frontiers of biomedical research and clinical applications.

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.

The progressing industrialization of oceans mandates reliable, accurate and automatable subsea survey methods. Close-range photogrammetry is a promising discipline, which is frequently applied by archaeologists, fish-farmers, and the offshore energy industry. This paper presents a robust approach for the reliable detection and identification of photogrammetric markers in subsea images. The proposed method is robust to severe image degradation, which is frequently observed in underwater images due to turbidity, light absorption, and optical aberrations. This is the first step towards a highly automated work-flow for single-camera underwater photogrammetry. The newly developed approach comprises several machine learning models, which are trained by 10,122 real-world subsea images, showing a total of 338,301 photogrammetric markers. The performance is evaluated using an object detection metrics, and through a comparison with the commercially available software Metashape by Agisoft. Metashape delivers satisfactory results when the image quality is good. In images with strong noise, haze or little light, only the novel approach retrieves sufficient information for a high degree of automation of the subsequent bundle adjustment. While the need for offshore personnel and the time-to-results decreases, the robustness of the survey increases.

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.

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]

The aim of the study was to investigate the changes in serum glypican 4 (GPC4) and clusterin (CLU) levels in patients with polycystic ovary syndrome (PCOS) as well as their correlation with sex hormones and metabolic parameters. A total of 40 PCOS patients and 40 age-matched healthy women were selected. Serum GPC4 and CLU levels were compared between the PCOS and control groups, and binary logistic regression was used to analyze the relative risk of PCOS at different tertiles of serum GPC4 and CLU concentrations. Stepwise linear regression was used to identify the factors influencing serum GPC4 and CLU levels in PCOS patients. Serum GPC4 (1.82 ± 0.49 vs 1.30 ± 0.61 ng/mL, P < 0.001) and CLU (468.79 ± 92.85 vs 228.59 ± 82.42 μg/mL, P < 0.001) were significantly higher in PCOS patients than in healthy women after adjustment for body mass index (BMI). In the PCOS group, serum GPC4 was positively correlated with follicle-stimulating hormone, fasting plasma glucose (FPG), fasting insulin (FINS), homeostatic model assessment of insulin resistance (HOMA-IR), triglyceride, and CLU (P < 0.05), whereas serum CLU was positively correlated with BMI, FPG, FINS, and HOMA-IR (P < 0.05). Multiple stepwise linear regression analysis showed that HOMA-IR was independently associated with serum GPC4, and BMI and HOMA-IR were independently associated with CLU (P < 0.05). Serum GPC4 and CLU levels were significantly higher in PCOS patients than in healthy women, suggesting that GPC4 and CLU may be markers associated with insulin resistance in women with PCOS.

Abstract Global population aging poses a tremendous burden on the health care system worldwide. Frailty is associated with decreased physical reserve and is considered an important indicator of adverse events in the older population. Therefore, there is growing interest in the early diagnosis and intervention of frailty, but the cellular mechanisms responsible for frailty are still not completely understood. Chronic inflammation is related to decreased physical function and increased disease risk. Additionally, multiple human and animal studies suggest that inflammation probably plays the largest role in contributing to frailty. Some inflammatory markers have been proposed to predict physical frailty. However, there are still large gaps in knowledge related to the clinical application of these markers in frail patients. Therefore, understanding the biological processes and identifying recognized and reliable markers are urgent and pivotal tasks for geriatricians. In the present review, we broadly summarize the inflammatory markers that may have potential diagnostic and therapeutic use, thereby translating them into health care for older people with frailty in the near future.

ABSTRACT: The single-step genomic model has become the golden standard for routine evaluation in livestock species, such as Holstein dairy cattle. The single-step genomic model with direct estimation of marker effects has been proven to be efficient in accurately accounting for millions of genotype records. For diverse applications including frequent genomic evaluation updates on a weekly basis, estimates of the marker effects from the single-step evaluations play a central role in genomic prediction. In this study we focused on exploring the marker effect estimates from the single-step evaluation. Phenotypic, genotypic, and pedigree data were taken from the official evaluation for German dairy breeds in April 2021. A multilactation random regression test-day model was applied to more than 242 million test-day records separately for 4 traits: milk, fat, and protein yields, and somatic cell scores (SCS). Approximately one million genotyped Holstein animals were considered in the single-step genomic evaluations including ∼21 million animals in pedigree. Deregressed multiple across-country breeding values of Holstein bulls having daughters outside Germany were integrated into the national test-day data to increase the reliability of genomic breeding values. To assess the stability and bias of the marker effects of the single-step model, test-day records of the last 4 yr were deleted, and the integrated bulls born in the last 4 yr were truncated from the complete phenotypic dataset. Estimates of the marker effects were shown to be highly correlated, with correlations ∼0.9, between the full and truncated evaluations. Regression slope values of the marker-effect estimates from the full on the truncated evaluations were all close to their expected value, being ∼1.03. Calculated using random regression coefficients of the marker effect estimates, drastically different shapes of the genetic lactation curve were seen for 2 markers on chromosome 14 for the 4 test-day traits. The contribution of individual chromosomes to the total additive genetic variances seemed to follow the polygenic inheritance mode for protein yield and SCS. However, chromosome 14 was found to make an exceptionally large contribution to the total additive genetic variance for milk and fat yields because of markers near the major gene DGAT1. For the first lactation test-day traits, we obtained ∼0 correlations of chromosomal direct genomic values between any pair of the chromosomes; no spurious correlations were found in our analysis, thanks to the large reference population. For trait milk yield, chromosomal direct genomic values appeared to have a large variation in the between-lactation correlations among the chromosomes, especially between first and second or third lactations. The optimal features of the random regression test-day model and the single-step marker model allowed us to track the differences in the shapes of genetic lactation curves down to the individual markers. Furthermore, the single-step random regression test-day model enabled us to better understand the inheritance mode of the yield traits and SCS (e.g., variable chromosomal contributions to the total additive genetic variance and to the genetic correlations between lactations).

Abstract Background Hepatocellular carcinoma (HCC) is one of the most prevalent and fatal malignancies worldwide. Following an increase in reactive oxygen species (ROS), cancer cells enter an oxidative stress state. As a result, these cells experience an increase in antioxidant activity to counteract oxidative stress. The thioredoxin (TRX) system is a ubiquitous mammalian antioxidant system that neutralizes ROS and maintains intracellular reduction oxidation (redox) balance, which is essential for HCC growth. However, the role of TRX protein in HCC remains largely unknown. Hence, we aimed to assess the diagnostic utility of serum TRX in patients with HCC. A total of 50 patients were consecutively recruited in this observational study. They were classified into three groups: an HCC group (25 patients), a cirrhosis group (15 patients with liver cirrhosis on top of chronic HCV infection), and a control group (10 healthy individuals). Serum TRX levels were measured using ELISA. Results Higher serum TRX levels were detected in the HCC group than in the cirrhosis and control groups (140.96 ± 12.70 vs 88.33 ± 10.34 vs 73.10 ± 13.22 ng/mL, respectively; P

Background. The development of genetic certificates and nomenclatural standards for newly released cultivars of Malus domestica Borkh. (apple tree) ensures an opportunity to preserve the original and authentic genetic and morphological information on domestic cultivars promising for the south of Russia. The purpose of this study was to develop genetic certificates and nomenclatural standards for 7 apple-tree cultivars developed at the North Caucasian Federal Scientific Center of Horticulture, Viticulture, Wine-making (NCFSCHVW), five of which were released jointly with the All-Russian Research Institute of Fruit Crop Breeding (VNIISPK).Materials and methods. The materials included apple-tree cultivars resistant or immune to scab (Venturia inaequalis (Cooke) G. Winter) from the NCFSCHVW collection stock. Conventional herbarization and DNA fingerprinting methods were used. For cultivar certification, an improved technique of DNA sampling and 12 microsatellite markers were applied.Results. Unique DNA profile certificates and nomenclatural standards were produced for 7 apple-tree cultivars: ‘Vasilisa’, ‘Karmen’, ‘Krasny Yantar’, ‘Soyuz’ and ‘Rassvet’ (with the Rvi6 gene) released jointly by the NCFSCHVW and VNIISPK, plus ‘Zolotoye Letneye’ and ‘Feya’ developed at the NCFSCHVW. The apple-tree herbarium specimens were placed for perpetual storage in the WIR Herbarium of the N.I. Vavilov All-Russian Institute of Plant Genetic Resources (VIR).Conclusion. The results obtained are promising for identification and authenticity verification of new domestic apple-tree cultivars during their reproduction and cultivation.

Background: Ovarian cancer is one of the most common cancers in women. Markers associated with ovarian cancer are still being sought. The aim of this study was to evaluate the expression of BRIP-1 (FANCJ) and FANCI proteins in ovarian cancer tissue and to assess these expressions in differentiating the described clinical features. Methods: The study enrolled 68 patients with ovarian cancer. The cohort was divided into a HGSOC (high-grade serous ovarian cancer) group and a non-HGSOC group, which represented ovarian cancer other than HGSOC. Immunohistochemical evaluation of FANCI and BRIP-1 (FANCJ) protein expression in ovarian cancer tissue samples was performed. All statistical analyses were performed using StatView software (Carry, NC, USA). Results: The FANCI protein mostly showed moderate positive and strong positive expression, while BRIP-1 protein mostly showed no expression or positive expression. Patients with lower expression of FANCI and BRIP-1 showed differences in the clinical stage of HGSOC, which was not observed in patients with higher expression of these proteins. In addition, patients with lower BRIP-1 expression showed differences in menopausal status, which was not observed in patients with higher expression of this protein. Conclusions: This study shows that FANCI protein is a marker associated with lower FIGO stage and histologically high-grade cancer in a group of all ovarian cancers and in non-HGSOC.

Bladder cancer (BC) is the most common neoplasm of the urinary system and ranks tenth in global cancer incidence. Due to its high recurrence rate and the need for continuous monitoring, it is the cancer with the highest cost per patient. Cystoscopy is the traditional method for its detection and surveillance; however, this is an invasive technique, while non-invasive methods, such as cytology, have a limited sensitivity. For this reason, new non-invasive strategies have emerged, analyzing useful markers for BC detection from urine samples. The identification of tumor markers is essential for early cancer detection and treatment. Urine analysis offers a non-invasive method to identify these markers. Microsatellite instability (MSI) has been proposed as a promising marker for tumor cell detection and guided targeted therapies. Therefore, this review aims to explore the evidence supporting the identification of MSI in exfoliated bladder tumor cells (EBTCs) in the urine, emphasizing its potential as a non-invasive and clinically effective alternative for tumor identification. Furthermore, establishing clinical guidelines is crucial for standardizing its application in oncological screening and validating its clinical utility.

Abstract Background Congenital heart defect (CHD) is the most common congenital abnormality, and it has long been a clinical and public health concern. Our previous findings have found Periostin (POSTN) and Pappalysin-1 (PAPPA) as potential biomarkers for fetal CHD. We aim to further elucidate POSTN's role in fetal heart development and explore the clinical applicability of POSTN and PAPPA as diagnostic marker for fetal CHD. This study is poised to establish a theoretical framework for mitigating the incidence of CHD and advance a novel approach for prenatal screening of fetal CHD. Methods We verified differential expression of POSTN and PAPPA in gravida serum and fetal amniotic fluid based on our previous research. We established the Postn knockout mouse by CRISPR/Cas9 to investigate whether Postn deletion leads to cardiac abnormalities in mice. Besides, we explored the mechanism of POSTN on heart development through Postn knockout mouse model and cell experiments. Finally, we established the logistic regression model and decision curve analysis to evaluate the clinical utility of POSTN and PAPPA in fetal CHD. Results We observed a significant decrease in POSTN and increase in PAPPA in the CHD group. Atrial septal defects occurred in Postn −/− and Postn ± C57BL/6 fetal heart, while ventricular septal defects with aortic saddle were observed in Postn ± C57BL/6 fetal heart. Disruption of the extracellular matrix (ECM) in cardiomyocytes and multiple abnormalities in cellular sub-organelles were observed in Postn knockout mice. POSTN may positively regulate cell behaviors and unsettle ECM via the TGFβ-Smad2/3 signaling pathway. The combination of serum biomarkers POSTN and PAPPA with Echocardiogram can enhance the diagnostic accuracy of CHD. Furthermore, the comprehensive model including POSTN, PAPPA, and two clinical indicators (NT and age) exhibits significantly higher predictive ability than the diagnosis group without the use of serum biomarkers or clinical indicators. Conclusions It is the first evidence that Postn deletion leads to cardiac developmental abnormalities in fetal mice. This may involve the regulation of the TGFβ signaling pathway. Importantly, POSTN and PAPPA possess clinical utility as noninvasive prenatal promising screening indicators of CHD.

Amyotrophic lateral sclerosis (ALS) is a severe neurodegenerative disease that is associated with selective and progressive loss of motor neurons. As a consequence, the symptoms of ALS are muscle cramps and weakness, and it eventually leads to death. The general markers for early diagnosis can assist ALS patients in receiving early intervention and prolonging their survival. Recently, some novel approaches or previously suggested methods have validated the potential for early diagnosis of ALS. The purpose of this review is to summarize the status of current general markers discovery and development for early diagnosis of ALS, including genes, proteins neuroimaging, neurophysiology, neuroultrasound, and machine learning models. The main genetic markers evaluated are superoxide dismutase 1 (SOD1), chromosome 9 open reading frame 72 (C9orf72), transactivation-responsive DNA binding protein 43 (TARDBP), and fused in sarcoma (FUS) genes. Among proteins, neurofilament light chain is still the most established disease-specific adaptive change in ALS. The expression of chitinases, glial fibrillary acidic protein (GFAP), and inflammatory factors are changed in the early stage of ALS. Besides, more patient-friendly and accessible feature assays are explored by the development of neuroimaging, neurophysiology, and neuroultrasound techniques. The novel disease-specific changes exhibited the promising potential for early diagnosis of ALS. All of these general markers still have limitations in the early diagnosis, therefore there is an urgent need for the validation and development of new disease-specific features for ALS.