Double-stranded cDNA of eight human tissues (brain, heart, kidney, testis, liver, spleen, lung, and skeletal muscle) were generated with the Marathon cDNA amplification kit (Clontech). The cDNA concentration was normalized by quantitative PCR against AGPAT1 and EEF1A1 genes. The PCRs were performed in 386-well plates in a total volume of 12.5 μLl. One microliter of normalized cDNA was mixed with JumpStart REDTaq ReadyMix (Sigma) and primers (4 μM) with a Freedom evo robot (TECAN). The 10 first cycles of amplification were performed with a touchdown annealing temperature decreasing 1°C per cycle from 65°C to 55°C; annealing temperature of the next 30 cycles was carried out at 55°C. For each tissue, 2 μL of each RT-PCR reaction were pooled together and purified with the QIAquick PCR purification Kit (Qiagen) according to the manufacturer's recommendations. This purified DNA was directly used to generate a sequencing library with the “Genomic DNA sample prep kit” (Illumina) according to the manufacturer's recommendations with the exclusion of the fragmentation step. This library was subsequently sequenced on an Illumina Genome Analyzer 2 platform.
Skeletal Muscles
Skeletal Muscles are the striated muscles that are attached to the skeleton and responsible for movement.
They are composed of long, cylindrical muscle fibers arranged in bundles and are innervated by motor neurons.
Skeletal muscles play a crucial role in locomotion, posture, and various physiological functions.
They are essential for maintaining musle strength, flexibility, and overall physical wellbeing.
Researchers studying skeletal muscle biology, physiology, and disorders can leverage PubCompare.ai to optimize their research workflow and enhance reproducibility.
They are composed of long, cylindrical muscle fibers arranged in bundles and are innervated by motor neurons.
Skeletal muscles play a crucial role in locomotion, posture, and various physiological functions.
They are essential for maintaining musle strength, flexibility, and overall physical wellbeing.
Researchers studying skeletal muscle biology, physiology, and disorders can leverage PubCompare.ai to optimize their research workflow and enhance reproducibility.
Most cited protocols related to «Skeletal Muscles»
Brain
cDNA Library
DNA, Complementary
EEF1A1 protein, human
Genes
Genome
Genomic Library
Heart
Homo sapiens
Kidney
Liver
Lung
Marathon composite resin
Oligonucleotide Primers
Reverse Transcriptase Polymerase Chain Reaction
Skeletal Muscles
Spleen
Testis
Tissues
Computed tomography provides a new lens for understanding skeletal muscle in situ, including quantification of tissue area, volume and attenuation. Current research is focused on the appearance of abnormally low radiation attenuation in muscles of some individuals (see below). However, to unify the findings on this parameter across studies, the criteria for muscle attenuation measurement require further agreement and standardization. Absolute values of radiation attenuation obtained on rigorously calibrated equipment are at best accurate to the nearest 4–5 HU. It is important that this calibration be done regularly and on standard materials with attenuation within the range of soft tissues, water (0 HU), fat (−100 HU) and muscle (50 HU).
There is also a need to agree on cut-offs defining normal and low attenuation muscle. The most common and accepted HU range for adipose tissue is −190 to −30 HU, and these values are quite consistent across studies. When muscle cross-sectional area and attenuation are reported, the common practice is to use pre-defined HU ranges. There was a notable disparity in the literature with respect to the HU range used for muscle, and there was considerable variation in both their upper and lower limit, which starts at either 0 HU or −29 HU and extends to 100, 150 or 200 HU (Table1 ). Some reports do not include the range from −29 HU to 0 HU (Table 1 ), and using that approach, any regions within this attenuation range are regarded as being neither muscle nor adipose tissue. Omission of this HU range would, at least in some individuals, fail to account for a significant proportion of the total muscle cross-sectional area. For example in Fig. 1 , Subject 2 has 13.5% of muscle area within the range of −29 HU to 0 HU. Another source of variation between studies is that mean attenuation may be reported for the entire muscle or a selected representative region[s] (Table 1 ). The generally accepted lower boundary of normal attenuation muscle is 30 HU (Goodpaster et al. 2000b (link), Lee et al. 2005 ), and this was defined as two standard deviations below the mean attenuation value across all pixels of muscles of young healthy persons (Goodpaster et al. 2000b (link)). Most of the variation exists in the HU ranges included for low attenuation muscle. Some authors defined low attenuation muscle from 0 to +29 HU (Goodpaster et al. 2000b (link), Deriaz et al. 2001 (link), Lee et al. 2005 ), while others included −29 to +30 HU. While the exact constitution and functional capacity of tissue within this range remain to be determined, it would seem advisable to incorporate the entire range from −29 to +29 HU in the definition of low attenuation muscle. Tissue cross-sectional area within the range of −29 to 0 HU cannot be disregarded. The benefit of a defined range of attenuation values for both muscle and adipose tissue alongside a standardized approach would enable comparison between various studies.
There is also a need to agree on cut-offs defining normal and low attenuation muscle. The most common and accepted HU range for adipose tissue is −190 to −30 HU, and these values are quite consistent across studies. When muscle cross-sectional area and attenuation are reported, the common practice is to use pre-defined HU ranges. There was a notable disparity in the literature with respect to the HU range used for muscle, and there was considerable variation in both their upper and lower limit, which starts at either 0 HU or −29 HU and extends to 100, 150 or 200 HU (Table
Lens, Crystalline
Muscle Tissue
Radiation
Skeletal Muscles
Tissue, Adipose
Tissues
X-Ray Computed Tomography
The gene expression data was obtained as CEL files and processed using Bioconductor [25] (link). The data for E. coli was processed using GCRMA as implemented within Bioconductor [14] (link). The data for human skeletal muscle was processed using the affy package [26] (link) and the mas5calls function. The p values were subtracted from 1 and the resulting value used as a quantitative measure of likelihood that the gene was available. The default parameters were used. For all datasets, the expression level of each reaction was determined by mapping any available data from genes associated with that reaction. If data was not available for any gene associated with a reaction, it was given a score of −1. If data was available for one or more genes, a single score was computed by evaluating the boolean GPR associations; OR's would evaluate to the greater of the two values, AND's to the lesser. The end result was a score for each reaction from each set of data, either −1 or non-negative, with greater numbers implying greater certainty that reaction is present. This is the data that was input into the GIMME algorithm to compute the consistency scores and context-specific metabolic networks.
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Escherichia coli
Gene Expression
Genes
Homo sapiens
Metabolic Networks
Skeletal Muscles
BLOOD
Gene Expression
Genotype
Heart
Left Ventricles
Leg
Lung
Obesity
Skeletal Muscles
Skin
Thyroid Gland
Tibial Arteries
Tibial Nerve
Tissues
We used the nine tissues with the largest sample size in the Genotype-Tissue Expression (GTEx) Pilot Project14 to test the gene prediction models generated in the DGN cohort. Tissue samples included subcutaneous adipose (n=115), tibial artery (n=122), left ventricle heart (n=88), lung (n=126), skeletal muscle (n=143), tibial nerve (n=98), skin from the sun-exposed portion of the lower leg (n=114), thyroid (n=112), and whole blood (n=162). In each tissue, normalized gene expression was adjusted for gender, the top 3 principal components (derived from genotype data), and the top 15 PEER factorsh.2p2csry (to quantify batch effects and experimental confounders)41 . We used GTEx to test the portability of predictors developed in whole blood (from the DGN cohort) across a wide variety of tissues.
BLOOD
Gene Expression
Genotype
Heart
Left Ventricles
Leg
Lung
Obesity
Skeletal Muscles
Skin
Thyroid Gland
Tibial Arteries
Tibial Nerve
Tissues
Most recents protocols related to «Skeletal Muscles»
Myosin II was purified from
rabbit skeletal muscle and fluorescently labeled with DyeLight 488
(Invitrogen, Carlsbad, CA, USA) according to Alvarado and Koenderink.66 (link) Labeled
and unlabeled myosin II were stored separately in myosin storage buffer
(300 mM KCl, 25 mM KH2PO4, 0.5 mM DTT, 50% (v/v)
glycerol, pH 6.5), where the high ionic strength prevents myosin self-assembly
into bipolar filaments. For experiments, myosin II was dialyzed overnight
in glycerol-free myosin buffer (300 mM KCl, 20 mM imidazol, 4 mM MgCl2, 1 mM DTT, pH 7.4) and controlled self-assembly into bipolar
filaments was induced by adjusting a KCl concentration of 50 mM via
mixing with myosin polymerization buffer (20 mM imidazol, 1.6 mM MgCl2, 1 mM DTT, 1.2 mM Trolox, pH 7.4). After an incubation time
of 10 min at 20 °C, the bipolar myosin II filaments were immediately
used for contractile experiments. For the contraction experiments,
the F-actin networks were transferred into an actomyosin buffer by
a 10-fold buffer exchange (50 mM KCl, 20 mM imidazol, 2 mM MgCl2, 1 mM DTT, 1 mM Trolox, pH 7.4). The reorganization of the
networks was performed at a final ATP concentration of 0.1 mM combined
with an ATP-regeneration system of creatine phosphate (10 mM)/creatine
kinase (0.1 mg/mL)66 (link) and a myosin II concentration
of 0.4 μM.
rabbit skeletal muscle and fluorescently labeled with DyeLight 488
(Invitrogen, Carlsbad, CA, USA) according to Alvarado and Koenderink.66 (link) Labeled
and unlabeled myosin II were stored separately in myosin storage buffer
(300 mM KCl, 25 mM KH2PO4, 0.5 mM DTT, 50% (v/v)
glycerol, pH 6.5), where the high ionic strength prevents myosin self-assembly
into bipolar filaments. For experiments, myosin II was dialyzed overnight
in glycerol-free myosin buffer (300 mM KCl, 20 mM imidazol, 4 mM MgCl2, 1 mM DTT, pH 7.4) and controlled self-assembly into bipolar
filaments was induced by adjusting a KCl concentration of 50 mM via
mixing with myosin polymerization buffer (20 mM imidazol, 1.6 mM MgCl2, 1 mM DTT, 1.2 mM Trolox, pH 7.4). After an incubation time
of 10 min at 20 °C, the bipolar myosin II filaments were immediately
used for contractile experiments. For the contraction experiments,
the F-actin networks were transferred into an actomyosin buffer by
a 10-fold buffer exchange (50 mM KCl, 20 mM imidazol, 2 mM MgCl2, 1 mM DTT, 1 mM Trolox, pH 7.4). The reorganization of the
networks was performed at a final ATP concentration of 0.1 mM combined
with an ATP-regeneration system of creatine phosphate (10 mM)/creatine
kinase (0.1 mg/mL)66 (link) and a myosin II concentration
of 0.4 μM.
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Actomyosin
Buffers
Cytoskeletal Filaments
F-Actin
Glycerin
imidazole
Magnesium Chloride
Muscle Contraction
Myosin ATPase
Myosin Type II
Phosphocreatine
Polymerization
Regeneration
Skeletal Muscles
Trolox C
This single-center, prospective, observational cohort study included patients treated at the CICW of National Center for Geriatrics and Gerontology in Japan between July 2015 and November 2020. This registry was completed in November 2020 because CICW was converted to a care ward for patients with COVID-19. Written informed consent was obtained from all patients or their family members, as appropriate. Ethical approval was obtained from the relevant Ethics Committee of Human Research of the National Center for Geriatrics and Gerontology, Japan (No. 830).
Participants registered in the CICW database sequentially during the study period were retrospectively screened. The database was developed for a registry study that focused to clarify the association between frailty and home admission. The database contained information of participants with informed consent and those who were not planned to be discharged from the CICW within 2 weeks, were not in the terminal stage of life, or did not have a pacemaker. The CICW database included the information regarding skeletal muscle mass by using bioelectrical impedance analysis (BIA). We excluded patients having a pacemaker because BIA can cause interference with the pacemakers.
The exclusion criteria of this research were visualized in Figure1 and were as follows: (1) age under 65 years, (2) living in nursing homes before CICW admission, (3) length of hospitalization of less than 2 weeks, (4) Mini-Mental State Examination (MMSE) score not performed or of 9 or less, (14 (link)) and (5) missing measurements. Missing items of MMSE were replaced to 0, because these missing data represented the lacked ability to finish the item (e.g., fracture of the dominant hand, visual impairment or disturbance of consciousness). Of the screened 717 participants, 167 were excluded due to age under 65 years (n=10), living in a nursing home before CICW admission (n=38), CICW stay of less than 2 weeks (n=40), MMSE not performed or MMSE scores ≤9 (n=53), and missing data for Geriatric Depression Sacle 15 (GDS15) or the Mini Nutritional Assessment-Short Form (MNA-SF) or the Functional Independence Measure (FIM) completing all FRAIL-NH components (n=26). Finally, 550 older adults (258 with robust, 97 with prefrail, and 195 with frail status) were included in the analysis.
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Participants registered in the CICW database sequentially during the study period were retrospectively screened. The database was developed for a registry study that focused to clarify the association between frailty and home admission. The database contained information of participants with informed consent and those who were not planned to be discharged from the CICW within 2 weeks, were not in the terminal stage of life, or did not have a pacemaker. The CICW database included the information regarding skeletal muscle mass by using bioelectrical impedance analysis (BIA). We excluded patients having a pacemaker because BIA can cause interference with the pacemakers.
The exclusion criteria of this research were visualized in Figure
Flowchart of inclusion and exclusion for this study
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Aged
Bioelectrical Impedance
Consciousness
COVID 19
Ethics Committees, Research
Family Member
Fracture, Bone
Homo sapiens
Hospitalization
Low Vision
Mini Mental State Examination
Pacemaker, Artificial Cardiac
Patients
Skeletal Muscles
Seventy-seven patients aged ≥ 65 years old with similar diet and environmental conditions in the Second Xiangya Hospital of Central South University were enrolled in this study. Patients were classified into the following 3 categories: 33 HF patients without sarcopenia (HF group), 29 HF patients with sarcopenia (SHF group), and 15 control individuals (Control group). Sarcopenia was diagnosed according to the Asian Working Group for Sarcopenia 2019 Guidelines (Chen et al., 2020 (link)). Low skeletal muscle mass was defined as muscle mass < 7.0 kg/m2 (male) or < 5.7 kg/m2 (female) by bioelectrical impedance analysis using the InBodyS10 body composition analyzer (Chen et al., 2014 (link)). Low muscle strength was defined as handgrip strength <28 kg for male and <18 kg for female. Criteria for low physical performance is a 6-m walk speed < 1 m/s. Sarcopenia was defined as low muscle mass plus either diminished muscle strength or physical performance. Exclude subjects included recurrent diarrhea or constipation, unusual dietary habits (vegetarians), edema, those with tumors, diabetes, intestinal inflammation, irritable bowel syndrome, history of intestinal surgery, being treated with antibiotics or probiotics within 1 month. Demographic characteristics and clinical laboratory examinations were documented for all patients. The study was approved by the local Ethics Committee of the Second Xiangya Hospital of Central South University. Written informed consent was obtained from all participants. This study was conducted under the Declaration of Helsinki.
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Antibiotics, Antitubercular
Asian Persons
Bioelectrical Impedance
Body Composition
Clinical Laboratory Services
Constipation
Diabetes Mellitus
Diarrhea
Edema
Inflammation
Intestines
Irritable Bowel Syndrome
Males
Muscle Strength
Muscle Tissue
Neoplasms
Operative Surgical Procedures
Patients
Performance, Physical
Physical Examination
Probiotics
Regional Ethics Committees
Sarcopenia
Skeletal Muscles
Therapy, Diet
Vegetarians
Woman
Patients diagnosed with HCC and underwent TACE from January 2008 to December 2019 were included and analyzed. The inclusion criteria were as follows: (1) age greater than 18 years; (2) HCC diagnosis by imaging or histological findings according to the American Association for the Study of Liver Disease guidelines15 (link); (3) initial treatment with conventional TACE; (4) HCC with Barcelona Clinic Liver Cancer (BCLC) stage A, B, or C (subsegmental or segmental portal vein tumor thrombosis); (5) available medical records; and (6) Child–Pugh class A or B. The exclusion criteria were as follows: (1) absence of imaging data; (2) inability to measure the skeletal muscle mass; (3) concomitant malignancies; and (4) history of HCC rupture.
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ADAM17 protein, human
Cancer of Liver
Child
Liver Function Tests
Malignant Neoplasms
Neoplasms
Neoplasms, Liver
Patients
Skeletal Muscles
Thrombosis
Veins
Veins, Portal
CT scans within 1 month prior to TACE or in the first post-TACE were selected to measure body composition. Pre-TACE scans were preferentially chosen. When these were unavailable, the earliest post-TACE scans were used in the study. The CT images at the level of the third lumbar vertebra (L3) were carefully chosen and archived as Digital Imaging and Communications in Medicine (DICOM) data. All DICOM data calculated body composition using in-house software developed by MATLAB (The MathWorks, Natick, MA, USA) and freeware Python 3.6.13 (Anaconda, Inc.), to generate the measurement model based on neural network architecture also known as UNet. The valid accuracy of the model was 99.17% and validity of the intersect over union co-efficiency was 89.40%17 (link).
The L3 skeletal muscle index (SMI) is used to identify sarcopenia and is calculated by dividing the cross-sectional area of the muscle by the square of the patient's height (cm2/m2). Sarcopenia was defined as SMI ≤ 36.2 cm2/m2 and ≤ 29.6 cm2/m2 for males and females, respectively11 (link). The areas of the abdominal wall and back muscles were used to calculate the SMD based on the areas of the pixels with attenuation between − 29 and + 150 HU. Myosteatosis was defined as SMD ≤ 44.4 HU or ≤ 39.3 HU in males and females, respectively11 (link). In addition, patients were classified into four groups according to their sarcopenia and myosteatosis status (Group A—neither sarcopenia nor myosteatosis, Group B—sarcopenia without myosteatosis, Group C—myosteatosis without sarcopenia, and Group D—sarcopenia with myosteatosis).
The L3 skeletal muscle index (SMI) is used to identify sarcopenia and is calculated by dividing the cross-sectional area of the muscle by the square of the patient's height (cm2/m2). Sarcopenia was defined as SMI ≤ 36.2 cm2/m2 and ≤ 29.6 cm2/m2 for males and females, respectively11 (link). The areas of the abdominal wall and back muscles were used to calculate the SMD based on the areas of the pixels with attenuation between − 29 and + 150 HU. Myosteatosis was defined as SMD ≤ 44.4 HU or ≤ 39.3 HU in males and females, respectively11 (link). In addition, patients were classified into four groups according to their sarcopenia and myosteatosis status (Group A—neither sarcopenia nor myosteatosis, Group B—sarcopenia without myosteatosis, Group C—myosteatosis without sarcopenia, and Group D—sarcopenia with myosteatosis).
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ADAM17 protein, human
Anaconda
Body Composition
Females
Males
Muscle, Back
Muscle Tissue
Patients
Pharmaceutical Preparations
Python
Radionuclide Imaging
Sarcopenia
Skeletal Muscles
Vertebrae, Lumbar
Wall, Abdominal
X-Ray Computed Tomography
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TRIzol reagent is a monophasic solution of phenol, guanidine isothiocyanate, and other proprietary components designed for the isolation of total RNA, DNA, and proteins from a variety of biological samples. The reagent maintains the integrity of the RNA while disrupting cells and dissolving cell components.
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The RNeasy Mini Kit is a laboratory equipment designed for the purification of total RNA from a variety of sample types, including animal cells, tissues, and other biological materials. The kit utilizes a silica-based membrane technology to selectively bind and isolate RNA molecules, allowing for efficient extraction and recovery of high-quality RNA.
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Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
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Penicillin/streptomycin is a commonly used antibiotic solution for cell culture applications. It contains a combination of penicillin and streptomycin, which are broad-spectrum antibiotics that inhibit the growth of both Gram-positive and Gram-negative bacteria.
More about "Skeletal Muscles"
Skeletal muscles, also known as striated muscles, are a crucial component of the musculoskeletal system.
These muscles are attached to the skeleton and are responsible for locomotion, posture, and various physiological functions.
Skeletal muscle fibers are cylindrical in shape and arranged in bundles, innervated by motor neurons.
Researchers studying skeletal muscle biology, physiology, and disorders can leverage powerful tools like PubCompare.ai to optimize their research workflow and enhance reproducibility.
This AI-driven platform allows researchers to easily locate the best protocols from literature, pre-prints, and patents using advanced search and comparison features.
Skeletal muscle research often involves the use of common laboratory reagents and techniques.
TRIzol reagent and the RNeasy Mini Kit are commonly used for RNA extraction, while the High-Capacity cDNA Reverse Transcription Kit is employed for cDNA synthesis.
Cell culture media like DMEM, supplemented with FBS and antibiotics like penicillin/streptomycin, are essential for maintaining skeletal muscle cell lines.
The IScript cDNA synthesis kit and QDR 4500A analyzer are also frequently utilized in skeletal muscle studies.
Maintaining muscle strength, flexibility, and overall physical wellbeing is crucial.
Researchers can leverage the insights and tools provided by PubCompare.ai to enhance their skeletal muscle research, leading to improved outcomes and a better understanding of this complex and important tissue.
These muscles are attached to the skeleton and are responsible for locomotion, posture, and various physiological functions.
Skeletal muscle fibers are cylindrical in shape and arranged in bundles, innervated by motor neurons.
Researchers studying skeletal muscle biology, physiology, and disorders can leverage powerful tools like PubCompare.ai to optimize their research workflow and enhance reproducibility.
This AI-driven platform allows researchers to easily locate the best protocols from literature, pre-prints, and patents using advanced search and comparison features.
Skeletal muscle research often involves the use of common laboratory reagents and techniques.
TRIzol reagent and the RNeasy Mini Kit are commonly used for RNA extraction, while the High-Capacity cDNA Reverse Transcription Kit is employed for cDNA synthesis.
Cell culture media like DMEM, supplemented with FBS and antibiotics like penicillin/streptomycin, are essential for maintaining skeletal muscle cell lines.
The IScript cDNA synthesis kit and QDR 4500A analyzer are also frequently utilized in skeletal muscle studies.
Maintaining muscle strength, flexibility, and overall physical wellbeing is crucial.
Researchers can leverage the insights and tools provided by PubCompare.ai to enhance their skeletal muscle research, leading to improved outcomes and a better understanding of this complex and important tissue.