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  • RASA1 expression highlights Z/W dosage dynamics and gonadal development in chickens | BMC Genomics

    RASA1 expression highlights Z/W dosage dynamics and gonadal development in chickens | BMC Genomics

    Characterization of mRNA Sequences and Expression of RASA1 in Chicken Embryonic Tissues at E6 and E12

    The RASA1 gene is present on both the Z and W sex chromosomes in chickens, referred to as RASA1-Z and RASA1-W, respectively. According to the…

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  • Exposure to high altitude is associated with an elevated risk of hip fracture: a retrospective cohort study using data from the CHARLS | BMC Geriatrics

    Exposure to high altitude is associated with an elevated risk of hip fracture: a retrospective cohort study using data from the CHARLS | BMC Geriatrics

    Study population and dataset

    The CHARLS is a prospective national cohort study that enrolled 17,708 participants in 2011, and three waves of follow-up were conducted in 2013, 2015, and 2018. Participants were randomly selected using a probability-proportional-to-size (PPS) technique and a four-stage random sample method. The workgroup selected 150 counties in 28 provinces. Administrative villages in rural areas and neighborhoods in urban areas were the primary sampling units (PSUs). Three PSUs within each county-level unit were selected using PPS sampling. Detailed information on the methodology and cohort profile has been reported previously [11].

    We collected data on participants enrolled in the baseline investigation who attended all three follow-up investigations and aged above 60 years old. Those with a history of cancer were excluded because the progression and treatment of cancer affect multiple organs and systems throughout the body; this aspect could have introduced substantial bias into our study. During the data cleaning process, we identified participants with implausible data regarding body weight and height, specifically heights less than 100 cm or weights less than 20 kg. These values were considered erroneous owing to likely data entry mistakes; therefore, participants with an abnormal body mass index (BMI) (BMI < 10 or BMI > 60) in the baseline investigation were excluded.

    Altitude data acquisition

    The participants’ place of residence was determined by their community ID. The latitude and longitude were acquired through amap api (https://restapi.amap.comv3/geocode), and the local altitude was acquired based on the latitude and longitude using geodata (version 0.5-8) [12] packages and the raster package (version 3.6–23) [13]. Participants were stratified into a low-altitude or high-altitude group based on a criterion of 1500 m, which was used in previous studies [14].

    Variable collection

    The primary outcome was hip fractures reported by the participants, which was defined by their answer to the question, “Have you fractured your hip since the last interview?” Participants choosing “yes” were considered to have experienced a hip fracture, and the time point the investigation occurred was recorded as the time the event happened.

    Individual income, marital status, medical history, sex, BMI, smoking status, alcohol consumption, and age were selected as covariates for propensity score matching (PSM). Individual income was acquired from harmonized CHARLS data and evenly divided into five groups. Educational status was retrieved from the answer to the question: “What is the highest level of education completed?” and re-coded into preschool, primary, secondary, and higher education. Marital status was retrieved from the answer to the question: “What is your marital status?” and re-coded as unmarried, married, widowed, divorced (or long-term separation). History of stroke, cardiovascular dysfunction, falls, hip fractures, chronic lung diseases, and arthritis were retrieved from the answer to the question: “Have you been diagnosed with any of the following by a doctor?” The presence of specific diseases was determined based on whether the participant selected “Yes” to the following conditions: (1) “Chronic lung diseases, such as chronic bronchitis and emphysema (excluding tumors or cancer),” (2) “Heart attack, coronary heart disease, angina, congestive heart failure, or other heart problems,” (3) “Stroke,” and (4) “Arthritis or rheumatism.” BMI was calculated using the following formula: BMI (kg/m[2]) = body weight (kg)/body height (m)2.

    Propensity score matching

    Individual income, marital status, medical history, sex, BMI, smoking status, alcohol consumption, and age were selected for PSM. A general linear model was used to calculate the distance, and the nearest method was used for matching with a matching ratio of 1:8 (high altitude: low altitude). After matching, a balance test was performed to evaluate the imbalance between the two groups in the matched data. The MatchIt package [15] was used for matching, and the Cobalt package [16] was used for the balanced test and plotting.

    Statistical analysis

    Categorical variables are shown as counts (percentages, %), and continuous variables are shown as mean ± SD. To compare the differences in baseline data between the two groups, chi-square and t-tests were used for categorical and continuous variables, respectively. Kaplan–Meier survival analysis and Cox regression were used to compare the differences between the two groups regarding fall and hip fracture risks.

    Subgroup analysis was performed, and the participants were divided into subgroups according to sex, smoking history, and overweight status. The effects of high-altitude exposure on fall and hip fracture risks in different subgroups were evaluated using Cox regression analysis.

    To test the robustness of our results, we performed different sensitivity analyses as follows: (1) We randomly sampled 80% and 90% of all participants, respectively, and replicated the previously described analysis workflow. (2) Using optimal matching as the PSM method and a matching ratio of 1:8, we replicated the previously described analysis workflow. (3) Cox regression was performed with and without adjustments for covariates without matching the participants.

    All analyses were performed using R (version 4.3.1). The survival analysis was performed using the survival package (version 3.5-5) [17] and visualized using the Survminer package (version 0.4.9) [18]. The comparison of baseline characteristics and the generation of tables was performed using the gtsummary package (version 1.7.2) [19].

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  • Black Friday Apple deals include the Mac mini M4 for $100 off

    Black Friday Apple deals include the Mac mini M4 for $100 off

    It’s a good idea to look for Black Friday Apple deals this time of year if you’re thinking about upgrading an aging laptop or picking up a pair of AirPods or an Apple Watch as a gift. One of the best discounts we’re tracking at the moment is on…

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  • “Dueling Dinosaurs” Fossil Solves One of Paleontology’s Biggest Debates – SciTechDaily

    1. “Dueling Dinosaurs” Fossil Solves One of Paleontology’s Biggest Debates  SciTechDaily
    2. Decades old T. rex debate ends with stunning discovery  The Brighter Side of News
    3. Burpee Museum’s ‘Jane’ could be an entirely new species of…

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  • Visual analysis of research hotspots and trends from drug treatment to

    Visual analysis of research hotspots and trends from drug treatment to

    Introduction

    Chronic obstructive pulmonary disease (COPD) is a common chronic non-communicable disease among the elderly. Its main pathological feature is persistent airflow limitation caused by abnormal alveolar structures and bronchial…

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  • Unsupervised classification of influenza virus surface spikes from cryo-EM reconstructions using head-to-stem width ratio | Virology Journal

    Unsupervised classification of influenza virus surface spikes from cryo-EM reconstructions using head-to-stem width ratio | Virology Journal

    This section describes the experimental dataset, the reconstruction of influenza B virus (B/Lee/40) particles from cryo-EM tilt series, and the computational pipeline for spike segmentation, feature extraction, and classification. These methods…

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  • Security forces kill 20 Khwarij in Khyber Pakhtunkhwa – RADIO PAKISTAN

    1. Security forces kill 20 Khwarij in Khyber Pakhtunkhwa  RADIO PAKISTAN
    2. At least 20 terrorists killed in KP IBOs, says ISPR  Dawn
    3. Forces neutralise 20 terrorists in KP operations  Geo TV
    4. 20 terrorists killed in Khyber Pakhtunkhwa security operations  

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  • Unrwa has the capacity and expertise to support a postwar Gaza. We want to help make this peace work | Philippe Lazzarini

    Unrwa has the capacity and expertise to support a postwar Gaza. We want to help make this peace work | Philippe Lazzarini

    After two years of brutal warfare in Gaza, a fragile ceasefire – the first phase of US president Donald Trump’s 20-point plan – offers some respite to an exhausted population. For my Unrwa colleagues on the ground in Gaza, the constant fear…

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