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Correction: CDC2 Mediates Progestin Initiated Endometrial Stromal Cell Proliferation: A PR Signaling to Gene Expression Independently of Its Binding to Chromatin
Cognitive cerebellum dominates motor cerebellum in functional decline of older adults with mild cognitive impairment
Objectives The present study aims to investigate the role that cognitive cerebellar lobules, compared to the motor ones, could have on performance abilities control in older individuals with Mild Cognitive Impairment (MCI). Methods Thirty-six participants with MCI were retrospectively recruited from the outpatient clinic for Cognitive Decline and Dementia at Geriatric Clinic and Regional Center for Brain Aging. Cognition was assessed through a reaction time (RT) task in which a mere cognitive (COG) component (RT/S1 COG, RT/S3 COG) has been isolated from a motor (MOT) component (RT/S1 MOT, RT/S3 MOT). Performance abilities were evaluated using Short Physical Performance Battery (SPPB), Tinetti Scale, and Activities of Daily Living (ADL). Finally, structural neuroimaging was conducted using magnetic resonance imaging at 3T. Results Left_Crus_I showed a correlation with SPPB, ADL%, and RT/S3 COG. Vermis_VI and Right_VI were correlated to ADL%, and RT/S3 COG with the entire lobule VI. ADL% showed negative correlations with RT/S1 COG, RT/S3 COG, and RT/S3 MOT. In the regression analysis, the strongest associations were found between RT/S3 COG and SPPB gait speed (R2 = 0.44, p = 0.03), Tinetti gait speed (R2 = 0.62, p < 0.001), and ADL% (R2 = 0.78, p < 0.001). Regarding cerebellar volumes, Right_Crus_I was associated with all SPPB tests, while Left_VI was associated with functional autonomy (ADL%: R2 = 0.78, p = 0.04). No associations were found between performance variables and total intracranial volume. Conclusions This study highlights that the cognitive cerebellar component dominates over the motor one even in the control of physical and functional capabilities of older adults with MCI.
Author Correction: Endocytosis in the axon initial segment maintains neuronal polarity
Integrating bulk and single-cell RNA sequencing reveals SH3D21 promotes hepatocellular carcinoma progression by activating the PI3K/AKT/mTOR pathway
As a novel genetic biomarker, the potential role of SH3D21 in hepatocellular carcinoma remains unclear. Here, we decipher the expression and function of SH3D21 in human hepatocellular carcinoma. The expression level and clinical significance of SH3D21 in hepatocellular carcinoma patients, the relationship between SH3D21 and the features of tumor microenvironment (TME) and role of SH3D21 in promoting hepatocellular carcinoma progression were analyzed based on the bulk samples obtained from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Single-cell sequencing samples from Gene Expression Omnibus (GEO) database were employed to verify the prediction mechanism. Additionally, different biological effects of SH3D21 on hepatocellular carcinoma cells were investigated by qRT-PCR, CCK-8 assay, colony forming assay and Western blot analysis. Bioinformatics analysis and in vitro experiments revealed that the expression level of SH3D21 was up-regulated in hepatocellular carcinoma and correlated with the poor prognosis in hepatocellular carcinoma patients. SH3D21 effectively promoted the proliferation, invasion, and migration as well as the formation of immunosuppressive microenvironment of hepatocellular carcinoma. In addition, SH3D21 can activate the PI3K/AKT/mTOR signaling pathway. SH3D21 stimulates the progression of hepatocellular carcinoma by activating the PI3K/AKT/mTOR signaling pathway, and SH3D21 can serve as a prognostic biomarker and therapeutic target for hepatocellular carcinoma.
Identification of the co-regulatory siRNAs of “miRNA→target” in Oryza sativa
The current “small interfering RNA(siRNA)→Target” mining tools can only search for targets of known siRNAs, and cannot discover co-regulatory siRNAs of unknown sequences that may exist, which means that the “microRNA(miRNA)→Target” database obtained by these mining tools is incomplete. Using the previously developed sRNATargetDigger, we re-mined the rice “miRNA→Target” database supported by the degradome and found 86.2% of the target genes were co-regulated by one or more miRNAs\siRNAs. Besides the known miRNAs, 30 miRNA isoforms (isomiRs) and 12 siRNAs were identified to be involved in co-regulation, which play important roles in rice response to external auxin regulation, rice blast resistance, adventitious root formation, cold resistance, and tillering etc. Some isomiRs even have higher expression levels than miRNAs. In addition, we also found that the regulatory relationship between 51 miRNAs and 48 target genes in the original database could not be verified due to the low expression levels of miRNA, poor complementarity between miRNA and target, or no specific cleavage signal detected by degradome in the middle of the miRNA binding site in the targets. Four miRNAs (osa-miR530-5p,osa-miR319b,osa-miR172c and osa-miR395a) only found isomiRs involved in regulation. In addition, we also found a number of miRNA→target regulatory relationships missed in the database. This study improved the rice “miRNA→target” database which will contribute to the research of rice miRNA and molecular breeding.
A compendium of human gene functions derived from evolutionary modelling
Abstract A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating a structured body of information about gene functions, which now includes experimental findings reported in more than 175,000 publications for human genes and genes in experimentally tractable model organisms1,2. Here, we describe the results of a large, international effort to integrate all of these findings to create a representation of human gene functions that is as complete and accurate as possible. Specifically, we apply an expert-curated, explicit evolutionary modelling approach to all human protein-coding genes. This approach integrates available experimental information across families of related genes into models that reconstruct the gain and loss of functional characteristics over evolutionary time. The models and the resulting set of 68,667 integrated gene functions cover approximately 82% of human protein-coding genes. The functional repertoire reveals a marked preponderance of molecular regulatory functions, and the models provide insights into the evolutionary origins of human gene functions. We show that our set of descriptions of functions can improve the widely used genomic technique of Gene Ontology enrichment analysis. The experimental evidence for each functional characteristic is recorded, thereby enabling the scientific community to help review and improve the resource, which we have made publicly available.
Prevalence of detectable viral load and its associated factors among adult patients receiving ART in Choma District, Zambia
Background Africa accounts for two-thirds of the global HIV infection and a disproportionate burden is in sub-Saharan Africa. In 2017, the Zambian government launched the U = U campaign which has proven to be key in the prevention of HIV. However, there is a paucity of empirical evidence on the magnitude of detectable viral load in Choma district. This study aimed to estimate the proportion of detectable viral load and identify the associated factors among adults living with HIV receiving antiretroviral therapy (ART) in Choma District, Zambia. Methods This was a cross-sectional study among adults aged 15 years and older on ART ≥ 12 months. Sociodemographic, clinical and laboratory data were collected through a structured questionnaire and data collection form for secondary data from medical records. Detectable Viral load (primary outcome) and Virological failure (secondary outcome) were defined as viral load (VL) > 200cp/ml and VL > 1000cp/ml respectively. The data collected was then analysed using STATA version XII. Descriptive statistics, chi-square test, Wilcoxon rank sum test, and logistic regression were the statistical methods used. Results There was a total of 448 participants. The median (interquartile range (IQR)) age was 41 years (32, 49) of whom 284 (63.2%) were females. The prevalence of detectable and virological failure were 10.3% (n = 46; 95% confidence interval (CI) 7.6, 13.5) and 5.4% (n = 24; 95%CI 3.5, 7.9) respectively. In multivariable analysis, detectable VL was significantly associated with young age (16 – 24 years) (odds ratio (OR) 3.38; 95%CI 1.04, 10.94; p = 0.042), no formal education (OR 3.32; 95%CI 1.06, 10.40; p = 0.040), missing medication (OR 3.99; 95%CI 1.83, 8.73; p = 0.001) and problem taking medication (OR 2.74; 95%CI 1.10; 6.84; p < 0.030); while factors associated with virological failure were being in age group 16 – 24 years (OR 7.28; 95%CI 1.62, 32.68, p = 0.009), male gender (OR 3.12; 95%CI 1.25, 7.76; p = 0.014), Missing taking medication (OR 8.28; 95%CI 2.59, 26.40; p < 0.001) and taking dolutegravir-based regimen with zidovudine/lamivudine backbone (OR 17.80 95% CI 2.29 - 132.31; p = 0.005). Conclusion Detectable VL and virological failure were prevalent among adults receiving ART for ≥ 12 months and were significantly associated with sociodemographic and clinical factors. There is a need for targeted interventions, especially among young people and males to accelerate the attaining of the last 95 of the UNAIDS target; which is imperative in the prevention of HIV transmission. Qualitative research which aims to get an in-depth understanding of why men and young people do not attain optimal viral suppression is encouraged.
Prognostic implications of MUC1 and XBP1 concordant expression in multiple myeloma: A retrospective study
Multiple myeloma (MM) is a disease of malignant plasma cells (PC) with poor survival. Disease progression and treatment relapse are attributed to MM cancer stem cells (CSCs) and signaling molecules such as MUC1 and XBP1. The study aimed to determine the prognostic value of expression of CSC-associated biomarkers, MUC1 and XBP1 in MM, which has not been explored previously. In this study, we determined the immunohistochemical expression of CSC markers (ALDH1, CD117, and CD34), MUC1, and XBP1 in 128 MM formalin-fixed paraffin-embedded bone marrow archival blocks. The expression of biomarkers was assessed for association with clinicopathological variables and patient survival. Descriptive analysis, survival plots and crude association between outcome and independent variables were assessed using Kaplan Meier and Log rank test. Univariate and multivariable analyses were performed using simple and multiple Cox regression models. The results are reported as crude and adjusted hazard ratios with 95% confidence intervals. Expression of ALDH1 and CD117 was found in 51% and 48% of the tumors, respectively. ALDH1 expression was associated with 1.83 years of reduced survival for patients with CD56-negative tumors. MUC1 expression was observed in 62%, whereas XBP1 was expressed in 48% of tumors. Combinatorial group analysis of XBP1 and MUC1 stratified patients into two prognostic groups. Cases with tumors negative for expression of MUC1 and XBP1 (XBP1-/ MUC1-) were categorized as a good prognostic group with increased survival of 3.42 years compared to cases with tumors expressing both (Worst prognosis, XBP1 + /MUC1+). Concordant expression of MUC1 and XBP1 in MM defines a subset of patients with adverse outcomes. The adjusted hazard ratio showed a four-fold increased risk of mortality associated with the concordant expression of MUC1 and XBP1 in patients > 65 years of age.
The look of a leader
Women and minorities are underrepresented in top leadership roles. Besides “supply-side” explanations that focus on the applicant pool, we offer a novel “demand-side” explanation through perceptual imprinting. Using the reverse correlation method, we found that people’s visual templates of leaders are perceptually imprinted by White male leaders. Across 15 studies (N = 3929), we examine what people expect leaders to look like. As demonstrated by the reverse correlation method, compared to followers, people expected leaders to look more White and male. Across all social categories, people also expected leaders to look more dominant, competent, and powerful. But to look like a leader, Black and female leaders also needed to look likable. Additional differences were observed by participant gender. Thus, in addition to having biased perceptual representations of leaders, people also have different perceptual standards for different social groups, as expressed by different expectations for how leaders of different races and genders should look. (151 words).
Using deep learning artificial intelligence for sex identification and taxonomy of sand fly species
Sandflies are vectors for several tropical diseases such as leishmaniasis, bartonellosis, and sandfly fever. Moreover, sandflies exhibit species-specificity in transmitting particular pathogen species, with females being responsible for disease transmission. Thus, effective classification of sandfly species and the corresponding sex identification are important for disease surveillance and control, managing breeding/populations, research and development, and conducting epidemiological studies. This is typically performed manually by observing internal morphological features, which maybe an error-prone tedious process. In this work, we developed a deep learning artificial intelligence system to determine the gender and to differentiate between three species of two sandfly subgenera (i.e., Phlebotomus alexandri, Phlebotomus papatasi, and Phlebotomus sergenti). Using locally field-caught and prepared samples over a period of two years, and based on convolutional neural networks, transfer learning, and early fusion of genital and pharynx images, we achieved exceptional classification accuracy (greater than 95%) across multiple performance metrics and using a wide range of pre-trained convolutional neural network models. This study not only contributes to the field of medical entomology by providing an automated and accurate solution for sandfly gender identification and taxonomy, but also establishes a framework for leveraging deep learning techniques in similar vector-borne disease research and control efforts.
An SDS-NaOH-based method to isolate genome of recombinant adeno-associated virus vectors for physical titer measurement
Recombinant adeno-associated viruses (rAAVs) vectors are promising for their safety and sustained expression of genetic payloads across various tissues. These vectors consist of a protein capsid enclosing a 4.7 kb single-stranded DNA genome. Rapid and accurate determination of the physical titers of rAAV vector is crucial for quality control in rAAV manufacturing and precise drug dosage in clinical trials. To prepare vector DNA for genome titer assessment, it is essential to completely degrade unencapsulated DNA and dissociate the capsid. Conventional methods typically involve co-incubation with DNase I to degrade unencapsidated DNA, followed by co-incubation with Proteinase K to cleave protein shells. Here, we present a “Benzonase & SDS-NaOH" pretreatment as an effective alkaline lysis for releasing the vector DNA. In the presence of producer cell crude extract, Benzonase demonstrated superior efficacy in degrading unencapsidated DNA compared to DNase I. Additionally, the use of SDS-NaOH, effective at 65 °C for 30 min, significantly reduces the time required compared to that of Proteinase K at 56 °C for 2 hours. We also showed that the “Benzonase & SDS-NaOH" pretreatment is applicable for vector genome titration in rAAV production, harvest, and purified stock. Moreover, our method is effective for both scAAV and ssAAV forms and across all serotypes, including the thermally stable rAAV5. Overall, this method offers a rapid and straightforward solution to determine rAAV vector genome titers in both purified preparations and during the manufacturing process.
Network pharmacology and in silico analysis reveal Kochiae Fructus as a potential therapeutic against atopic dermatitis through immunomodulatory pathway interactions
Atopic dermatitis (AD), a chronic inflammatory disorder, poses significant therapeutic challenges owing to its complex pathophysiology, involving disrupted epidermal barrier function and immune dysregulation. This study investigated the therapeutic potential of Kochiae Fructus in AD treatment using bioinformatics, including network pharmacology and molecular docking techniques. We identified 19 key phytochemicals from Kochiae Fructus and 268 potential targets using the Traditional Chinese Medicine Systems Pharmacology Database (TCMSP) and SwissTarget Prediction. Using GeneCards, 1786 AD-related genes were retrieved, resulting in 116 intersecting gene targets for further analysis. Protein-protein interaction (PPI) networks and Molecular Complex Detection (MCODE) analyses highlighted 78 anti-AD key targets, including SRC, MAPK3, MAPK1, JUN, PIK3CA, ESR1, PTGS2, PTPN11, IL-6, and ALOX5, among the top ten anti-AD core targets. Gene ontology (GO) enrichment analysis revealed that Kochiae Fructus affects biological processes and molecular functions, such as positive regulation of the apoptotic response, inflammatory response, and hormone-mediated signaling pathways, which may be associated with its anti-AD effects. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed that the C-type lectin receptor signaling pathway is the main pathway involved in the anti-AD effects of Kochiae Fructus, which interacts with a notably larger number of anti-AD core targets and plays a direct role in intensifying crucial inflammatory and immune responses in the heart of AD pathogenesis. Molecular docking demonstrated robust binding affinities of key phytochemicals, particularly ecdysterone and 11,14-eicosadienoic acid, to the anti-AD core targets. Molecular dynamics simulations of over 1000 ns confirmed the stability and potential efficacy of these interactions. Hence, this study underscores the therapeutic potential of Kochiae Fructus in AD management, offering a mechanistic basis for its clinical application and paving the way for novel anti-AD strategies that leverage TCM phytochemicals.
Journal targeted by paper mill still grappling with the aftermath years later
Research on plasma arc flame length detection technology based on region of interest
With the rapid advancement of metal 3D printing technology, there is a growing demand for spherical metal powder as a primary material for 3D printing. The process technology that ensures the production of high-quality spherical metal powder has become a focal area of research for numerous enterprises and research institutions globally. In the conventional plasma rotating electrode method for powder production, the feed speed of the servo feeding mechanism is manually predetermined, leading to potential variations in the distance between the end face of the metal rod and the plasma gun that generates the plasma arc. Such inconsistency can compromise the quality of the metal powder produced and pose safety hazards if the gap between the metal rod and the plasma gun is too narrow. To address these issues, this study presents a novel plasma arc length detection system based on the concept of the region of interest. The proposed system leverages image processing technology for efficiently detecting the plasma arc length. By incorporating image detection within the region of interest alongside an arc length correction function, the system enhances real-time performance and detection precision. Additionally, real-time monitoring of the detection site is enabled through KingView. Experimental findings indicate that the image target area post plasma arc detection exhibits well-defined edges, clear brightness, and minimal noise, thereby meeting the prerequisites for subsequent image processing and monitoring tasks. The corrected plasma arc length averages around 40mm, with a detection error of less than 1mm when compared to the desired controlled plasma arc length. Moreover, the length variation remains relatively stable, thus fulfilling the measurement criteria. Over time, the detected plasma arc length exhibits negligible fluctuations, suggesting consistent proximity between the plasma gun and the end face of the metal rod during the melting process. The controller can dynamically control the feed speed of the servo feeding mechanism according to the detected plasma arc length, ensuring a constant distance between the plasma arc and the end face of the metal rod throughout the powder production process, thus aligning with practical industrial requirements.
The early origins of bone-tool manufacturing traditions by hominins 1.5 million years ago
An examination of the interrelationships among NASA-TLX dimensions utilizing the DEMATEL method
The NASA TLX is a survey-based method widely used to evaluate cognitive workload across six specific dimensions related to an employee’s tasks. While academic research recognizes that these dimensions may have unequal contributions to mental workload, they are often weighted using multi-criteria decision-making techniques. However, prior studies have not investigated possible relationships between the dimensions. The main objective of this paper is to explore the interconnections and dependencies among these dimensions. This study distinguishes itself by employing the Decision-Making Trial and Evaluation Laboratory (DEMATEL) technique to clarify these relationships and dependencies, and to examine how interactions between dimensions shift under different threshold conditions. The research includes three distinct impact diagrams tailored for individuals performing tasks with varying levels of cognitive workload. By considering the interdependencies among the NASA TLX dimensions, this study offers a significant advancement in the field, as these interrelationships could greatly influence the derived weights. This theoretical contribution has the potential to be groundbreaking in the realm of survey-based mental workload assessment techniques, such as the NASA TLX.
Rethinking Shadowing for Aspiring Physicians
Repeatability and genetic advances in early maturing maize hybrid trials conducted under Striga-infested and non-infested conditions
In sub-Saharan Africa (SSA), maize (Zea mays L.) is both a cash crop and an important staple crop. However, Striga hermonthica infection constrains its production and productivity. A total of 159 hybrids from 21 international trials were evaluated under Striga-infested (STRINF) and Striga non-infested (STRNON) conditions at Mokwa and Abuja, Nigeria, from 2010 to 2021. The data were used to (i) determine the genetic enhancements in grain yield and Striga adaptive traits and (ii) assess the repeatability of the trials in identification of promising hybrids. Significant annual genetic gains in grain yield of 3.40% and 3.71% with increases of 76.87 and 127.02 kg ha − 1 yr − 1 were recorded under STRINF and STRNON conditions, respectively. The genetic gains in grain yield were associated with 3.04 and 2.25% decreases in Striga damage ratings at 8 and 10 weeks after planting (WAP), respectively, and 1.27% in the number of emerged Striga plants at 10 WAP. The results indicated that ears per plant and flowering dates had the highest consistency in repeatability estimates while the number of emerged Striga plants at 8 and 10 WAP recorded the lowest consistency in repeatability estimates. Generally, substantial progress has been achieved with a good level of repeatability estimates for the early maturing maize hybrid trials evaluated under STRINF and STRNON conditions.Those results have demonstrated that the breeding strategies adopted during the 12-year breeding period have been effective, and that the potential of the trials in the exploration of the genetic potential of the hybrids for commercialization in the SSA for food security and poverty alleviation.