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A-101

A-101 is a term used to describe a specific research protocol or assay.
It is often used in the context of scientific publications, preprints, and patents to document experimental methods and procedures.
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Most cited protocols related to «A-101»

1
Robust Identification of Differentially Methylated Regions
Cited 70 times
To find regions exhibiting consistent differences between groups of samples, taking biological variation into account, we compute a signal-to-noise statistic similar to the t-test. Specifically, we denote individuals with i and use Xi do denote group; for example, Xi=0 if the ith sample is a control and Xi=1 if a case. The number of controls is denoted n1 and the number of cases n2. We assume that the samples are biological replicates within a group. Similar to the previous section, we denote the number of reads for the ith sample associated with the jth CpG being methylated and unmethylated with Mi,j and Ui,j, respectively. We assume that Yi,j follows a binomial distribution with Mi,j+Ui,j trials and success probability πi,j, which we assume is a sample-specific smooth function of genomic location lj: πi,j=fi(lj). Furthermore, we assume that fi has the form fi(lj)=α(lj)+β(lj)Xi+εi,j. Here α(lj) represents the baseline methylation profile and β(lj) the true difference between the two groups. The latter is the function of interest, with non-zero values associated with DMRs. The εi,j s represent biological variability with the location-dependent variance var(εi,j)≡σ2(j) assumed to be a smooth function. Note that increasing coverage does not reduce the variability introduced by ε; for this we need to increase the number of biological replicates.
We use the smoothed methylation profiles described in the previous section as estimates for the fi, denoted f^i(lj) . We estimate α and β as empirical averages and difference of averages: α^(lj)=∑if^i(lj) and β^(lj)=∑i:Xi=1f^i(lj)−∑i:Xi=0f^i(lj) . To estimate the smooth location-dependent standard deviation, we first compute the empirical standard deviation across the two groups. To improve precision, we used an approach similar to [30 (link)]: we floored these standard deviations at their 75th percentile. To further improve precision, we smoothed the resulting floored values using a running mean with a window size of 101. We denote this final estimate of local variation with σ^(lj) . We then formed signal-to-noise statistics: t(lj)=β^(lj)/[σ^(lj)1/n1+1/n2] . To find DMRs, that is, regions for which β(lj)≠0, we defined groups of consecutive CpGs for which all t(lj)>c or t(lj)<-c with c>0 a cutoff selected based on the marginal empirical distribution of t. We adapted our algorithm so that CpGs further than 300 bp apart were not permitted to be in the same DMR.
We recommend including in the procedure only CpGs that have some coverage in most or all samples. Furthermore, we recommend filtering the set of DMRs by requiring each DMR to contain at least three CpGs, have an average β of 0.1 or greater, and have at least one CpG every 300 bp.
Hansen K.D., Langmead B, & Irizarry R.A. (2012). BSmooth: from whole genome bisulfite sequencing reads to differentially methylated regions. Genome Biology, 13(10), R83.
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Publication 2012
A-101 Biopharmaceuticals Methylation
2
Validation of a Food Frequency Questionnaire for Pregnant Women
Cited 47 times
We used a semi-quantitative FFQ of 101 food items to assess the usual daily intake of foods and nutrients (available at: http://bibliodieta.umh.es/files/2011/07/CFA101.pdf). The FFQ was a modified version from a previous FFQ based on the Harvard questionnaire [15 (link)], which we developed and validated using four 1-week dietary records in an adult population in Valencia. The validity correlation coefficients (adjusted for energy intake) ranged from 0.27 for folate intake to 0.67 for calcium intake (average 0.47), and the reproducibility correlation coefficient s ranged from 0.30 for carotene intake to 0.65 for calcium intake (average 0.40) [16 ,17 (link)]; this is a similar range to other established diet questionnaires [3 ,4 (link)]. For the dietary assessment of pregnant women in the INMA cohort study, we added additional food items in the FFQ in order to capture the major sources of the most relevant nutrients, including specific carotenoids.
Participants in the study were asked twice during pregnancy how often, on average, they had consumed each food item over two periods of several months. The first period covered the time from the last menstruation to the first prenatal visit that occurred between the 10–13 weeks of pregnancy; the second period was the time between the first visit and the second one between weeks 28–32 of gestation. Serving sizes were specified for each food item in the FFQ. The questionnaire had nine possible responses, ranging from ‘never or less than once per month’ to ‘six or more per day’. Additionally, we asked whether study participants followed special diets.
Nutrient values were primarily obtained from the food composition tables of the US Department of Agriculture publications as well as other published sources for Spanish foods and portion sizes [18 ,19 ]. In order to obtain average daily nutrient intakes from diet for each individual, we multiplied the frequency of use for each food by the nutrient composition of the portion/serving size specified on the FFQ and added the results across all foods. For those nutrients often used in supplements during pregnancy such as folate, vitamin C and vitamin B12, the total daily nutrient intake was estimated by adding the average daily intake from supplements and the usual daily nutrient intake from the FFQ. In order to convert folic acid intake from supplements to dietary folate, we used the equivalence of 1 mcg of folate in the diet equals to 0.6 mcg of folic acid from supplements [20 (link)]. We estimated the mean daily consumption for 17 foods and food groups by grouping the intake of specific foods in the FFQ (Table 1).
Vioque J., Navarrete-Muñoz E.M., Gimenez-Monzó D., García-de-la-Hera M., Granado F., Young I.S., Ramón R., Ballester F., Murcia M., Rebagliato M, & Iñiguez C. (2013). Reproducibility and validity of a food frequency questionnaire among pregnant women in a Mediterranean area. Nutrition Journal, 12, 26.
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Publication 2013
A-101 Adult Ascorbic Acid Calcium, Dietary Carotene Carotenoids Cobalamins Diet Dietary Supplements Eating Folate Folic Acid Food Hispanic or Latino Menstruation Nutrient Intake Nutrients Pregnancy Pregnant Women
3
Diffusion MRI of Cell Phantoms
Cited 43 times
The rat macrophages were isolated from inbred male Brown Norway rats (Harlan, Indianapolis, IN) and cultured as described in an MRI cell phantom study (21 (link)). Phantoms with different cell densities (0.8 x 107, 2 x 107, 4 x 107, and 8 x 107, cells/mL) were prepared by diluting cells in different volumes of 2% agarose gel in shortened 5-mm NMR tubes (Fig. 1a). 4 cell phantoms and one control phantom (2% agarose gel with no cell) were scanned using a Bruker BioSpec 11.7-T scanner (Bruker, Billerica MA). The diffusion acquisition was conducted using a 2D stimulated echo sequence. The b-table was a grid sampling scheme with 101 diffusion encoding gradient directions (22 (link)). The b-table is publicly available on the DSI Studio website (http://dsi-studio.labsolver.org). The maximum b-value was 6,000 mm2/sec, diffusion time Δ = 80 ms (i.e., diffusion gradient separation), and the diffusion gradient pulse duration δ = 1 ms. The diffusion weighted images were acquired with TE = 10 ms, TM = 75 ms, TR = 2600 ms. The FOV was 1.26 cm with an in-plane resolution of 0.2 mm and slices thickness of 0.35 mm. ρ(L) and δ(L) were calculated by Equations 3 and 4, respectively, and correlated with the cell density. The data were analyzed using DSI Studio (http://dsi-studio.labsolver.org).
Yeh F.C., Liu L., Hitchens T.K, & Wu Y.L. (2016). Mapping Immune Cell Infiltration Using Restricted Diffusion MRI. Magnetic resonance in medicine, 77(2), 603-612.
Publication 2016
A-101 Cells Diffusion ECHO protocol Macrophage Males Pulse Rate Rats, Inbred BN Sepharose
4
Kailuan Study: Tracking Cardiovascular Disease
Cited 24 times
The Kailuan study is a prospective cohort study conducted in the Kailuan community in Tangshan, Republic of China, which is a large, modern city southeast of Beijing. Detailed study design and procedures have been described in detail.3 (link),12 (link),13 (link),14 (link),15 (link),16 (link) Since June 2006, a total of 101 510 adult participants, including 81 110 men and 20 400 women, were enrolled from 11 hospitals in the Kailuan community and underwent questionnaire assessments, clinical examinations, and laboratory tests. All participants were then followed up every 2 years and the incidence of chronic diseases (eg, CVD) was recorded annually. In the present study, CHS trajectories were developed from 2006 to 2010 to predict CVD risk from 2010 to 2015. Data analysis was performed from January 1, 2006, to December 31, 2015.
The study protocol was approved by the ethics committee of the Kailuan General Hospital. All participants provided written informed consent; they did not receive financial compensation. This study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cohort studies.
Included in the present analyses were 74 701 participants free of CVD and cancer in or before 2010 (ie, the baseline of present analyses). The flowchart of the participant selection process is shown in the eFigure in the Supplement. Compared with those who were not included in the present analysis owing to missing 2008 and 2010 CHSs, included participants had similar 2006 CHSs (mean, 8.7 vs 8.5 in 2006) but were older (mean age, 50.7 vs 49.0 years in 2006) and had a smaller proportion of men (77.9% vs 86.4%).
Wu S., An S., Li W., Lichtenstein A.H., Gao J., Kris-Etherton P.M., Wu Y., Jin C., Huang S., Hu F.B, & Gao X. (2019). Association of Trajectory of Cardiovascular Health Score and Incident Cardiovascular Disease. JAMA Network Open, 2(5), e194758.
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Publication 2019
A-101 Adult Dietary Supplements Ethics Committees, Clinical Malignant Neoplasms Physical Examination Woman
5
Detecting Neural Activity Events in Calcium Imaging
Cited 19 times
We used the L0-penalized method of Jewell, et al for event detection17 ,71 . We refer to this as “event” detection because low firing rate activity is difficult to detect. For each ΔF/F trace we remove slow timescale shifts in the fluorescence using a median filter of width 101 samples (3.3 seconds). We then apply the L0-penalized algorithm to the corrected ΔF/F trace. The L0 algorithm has two hyperparameters: gamma and lambda. Gamma corresponds to the decay constant of the calcium indicator. We set gamma to be the decay constant obtained from jointly recorded optical and electrophysiology with the same genetic background and calcium indicator. Time constants can be found at https://github.com/AllenInstitute/visual_coding_2p_analysis/blob/master/visual_coding_2p_analysis/l0_analysis.py. Supplementary Figure 23 shows the extracted linear kernels for Emx1-Ai93 and Cux2-Ai93 from which gamma has been extracted by fitting the fluorescence decay with a single exponential. The rise time, amplitude, and shape of the extracted linear kernels are mainly a function of the genetically encoded calcium indicator (GCaMP6f) and appear to be largely independent of the specific promoter driving expression.
To estimate lambda, which controls the strength of the L0 penalty, we estimate the standard deviation of the trace. We set lambda using bisection to minimize the number of events smaller than two standard deviations of the noise, while retaining at least one recovered event. We chose two standard deviations by maximizing the hit-miss rate on eight hand-annotated traces during 8 degree locally sparse noise stimulation. Those traces were uniformly sampled from distribution of signal-to-noise ratio for ΔF/F traces. The noise level was computed as the robust standard deviation (1.4826 times the median absolute deviation) and the signal level was the median ΔF/F after thresholding at the robust standard deviation.
To assess how the events detected using the above procedure relate to actual spikes, we performed event detection on the fluorescence of cells that were imaged simultaneously with loose patch recordings. Since the true spike train is known for these data, we computed the expected probability of detecting an event, as well as the expected event magnitude, as a function of the number of spikes observed in a set of detection windows relevant to the pipeline data analyses (e.g. static gratings, natural scenes, and locally sparse noise templates are presented for 0.25 s each) (Supplementary Figure 23).
de Vries S.E., Lecoq J.A., Buice M.A., Groblewski P.A., Ocker G.K., Oliver M., Feng D., Cain N., Ledochowitsch P., Millman D., Roll K., Garrett M., Keenan T., Kuan L., Mihalas S., Olsen S., Thompson C., Wakeman W., Waters J., Williams D., Barber C., Berbesque N., Blanchard B., Bowles N., Caldejon S.D., Casal L., Cho A., Cross S., Dang C., Dolbeare T., Edwards M., Galbraith J., Gaudreault N., Gilbert T.L., Griffin F., Hargrave P., Howard R., Huang L., Jewell S., Keller N., Knoblich U., Larkin J.D., Larsen R., Lau C., Lee E., Lee F., Leon A., Li L., Long F., Luviano J., Mace K., Nguyen T., Perkins J., Robertson M., Seid S., Shea-Brown E., Shi J., Sjoquist N., Slaughterbeck C., Sullivan D., Valenza R., White C., Williford A., Witten D.M., Zhuang J., Zeng H., Farrell C., Ng L., Bernard A., Phillips J.W., Reid R.C, & Koch C. (2019). A large-scale standardized physiological survey reveals functional organization of the mouse visual cortex. Nature neuroscience, 23(1), 138-151.
Publication 2019
A-101 Calcium Cells Fluorescence Gamma Rays Genetic Background Neoplasm Metastasis Vision

Most recents protocols related to «A-101»

1
Combination Therapy Enhances Cancer Cell Killing
Not available on PMC !

Example 25

This experiment was to evaluate the effect of killing cancer cells by treating MDA-MB-231 cells (human breast cancer cells) with the test substance GI-101 alone or in combination with the TGF-beta signal inhibitor Vactosertib substance in an in vitro environment.

MDA-MB-231 cells were purchased from the Korea cell line bank and cultured in RPMI1640 medium (Gibco) containing 10% FBS (Gibco) and 1% antibiotic/antifungal agent (Gibco). For use in cancer cell killing test, the cells were harvested using trypsin (Gibco), and then suspended in RPMI1640 medium, and then dead cells and debris were removed using Ficoll (GE Healthcare Life Sciences) solution. The cells suspended in RPMI1640 medium were carefully layered on ficoll solution. The cell layer with a low specific gravity formed by centrifuging at room temperature at 350×g for 20 minutes was collected with a pipette, washed with PBS (Gibco), and then centrifuged at room temperature at 350×g for 5 minutes. The separated cell layer was made into a suspension of 2×105 cells/mL with FBS-free RPMI1640 medium. The cancer cell suspension was stained at 37° C. for 1 hour using CELLTRACKER™ Deep Red Dye (Thermo) in order to track proliferation or inhibition of the proliferation of cancer cells. After staining, it was centrifuged at 1300 rpm for 5 minutes, and then it was washed with FBS-free RPMI1640 medium, and then suspended in RPMI1640 medium containing 5% human AB serum (Sigma) to a concentration of 2×105 cells/mL. The cancer cell suspension was added to each well of a 96-well microplate (Corning) by 50 μl (1×104 cells), and then stabilized in an incubator (37° C., 5% CO2) for 1 hour.

Human peripheral blood mononuclear cells (PBMCs) were used in order to identify the effect of killing cancer cells by GI-101. The human PBMCs were purchased from Zen-Bio, and the PBMCs stored frozen were placed in a 37° C. water bath, and thawed as quickly as possible, and then transferred to RPMI1640 medium (Gibco) containing 10% FBS (Gibco) and 1% antibiotic/antifungal agent (Gibco), and centrifuged at 1300 rpm for 5 minutes. The separated cell layer was suspended in RPMI1640 medium, and then dead cells and debris were removed using Ficoll (GE Healthcare Life Sciences) solution in the same manner as the cancer cell line. The cells suspended in RPMI1640 medium were carefully layered on ficoll solution. The cell layer with a low specific gravity formed by centrifuging at room temperature at 350×g for 20 minutes was collected with a pipette, washed with PBS (Gibco), and then centrifuged at room temperature at 350×g for 5 minutes. The separated cell layer was suspended in RPMI1640 medium containing 5% human AB serum (Sigma) to a concentration of 5×105 cells/mL. The PBMC suspension was dispensed 50 μl into each well of a 96-well microplate (Corning) in which cancer cell line has been dispensed, depending on the conditions.

In order to identify the effect of killing the cells, a CytoTox Green reagent (INCUCYTE™ CytoTox Green, Satorius) that binds to the DNA of cells to be killed was prepared in 1 μl per 1 mL of RPMI1640 medium containing 5% human AB serum (Sigma). The prepared medium was used for dilution of the test substance, and the effect of killing the cells could be quantitatively identified by staining the cells to be killed when the test substance was co-cultured with cancer cell lines and PBMCs.

Vactosertib power was dissolved in DMSO (Sigma) to a concentration of 48.4 mM, and diluted using RPMI1640 medium containing a CytoTox Green reagent, and then used in the experiment at a final concentration of 12.1 nM (50 μL) per well of a 96-well microplate.

GI-101 was diluted by ⅓ using RPMI1640 medium containing a CytoTox Green reagent, and then used in the experiment at final concentrations of 0.4 nM, 1.2 nM, 3.7 nM, 11.1 nM, 33.3 nM, and 100 nM by 50 μl per well of a 96-well microplate.

The prepared test substance was placed in each well of a 96-well microplate in which cancer cell lines and PBMCs were dispensed depending on the conditions, and cultured in an incubator (37° C., 5% CO2) for 24 hours, and the proliferation or death of cancer cells was observed through the real-time cell imaging analysis equipment IncuCyte S3 (Satorious). The death of cancer cells was quantified by the integrated intensity of the cells stained in green with a CytoTox Green reagent.

As a result, it was identified that the group having received a combination of GI-101 and Vactosertib exhibited the excellent effect of killing cancer cells as compared with the group having received each drug alone.

US11857601B2. Pharmaceutical composition for cancer treatment comprising fusion protein including IL-2 protein and CD80 protein and anticancer drug (2024-01-02). GI INNOVATION, INC. [KR]. Inventors: Myung Ho Jang [KR], Su Youn Nam [KR], Young Jun Koh [KR].
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Patent 2024
A-101 Antibiotics Antifungal Agents Bath Cell Death Cell Lines Cell Proliferation Cells Ficoll Freezing Gastrointestinal Cancer Homo sapiens Malignant Neoplasms Mammary Carcinoma, Human MCF-7 Cells MDA-MB-231 Cells PBMC Peripheral Blood Mononuclear Cells PER1 protein, human Pharmaceutical Preparations Psychological Inhibition Serum Sulfoxide, Dimethyl Technique, Dilution Transforming Growth Factor beta Trypsin vactosertib
2
Burnout and Stress Among Students
The data were coded before data entry. The data were entered by exporting from an Excel sheet after converting from the web. Stata software version 13.1 (Stata Corp, College Station, Texas USA) was used for data analysis. The primary outcome was burnout. The burnout score was first calculated separately for the disengagement and exhaustion subscales. Students who scored higher than the average value in both disengagement and exhaustion subscales were considered to have burnout. The second outcome was stress. Scores of 0–13 on the PSS were considered as low stress; 14–26 as moderate stress, and 27–40 as high stress.
All continuous variables were tested for normality using the Shapiro–Wilks test. The mean and standard deviation were calculated for all continuous variables. The bivariate associations between the dependent variable (burnout and stress) and other independent variables were tested using Chi-square test and Fisher's exact test, where applicable. A multiple logistic regression model was used to identify risk factors of burnout among the study participants. We used a stepwise technique with a P value for the entrance of independent covariates set at 0.1, and a P value of 0.101 was set as the exit value of the model. The same model was constructed with a locked term “stimulant abuse;” however, all stimulant users experienced burnout, and thus this variable was omitted from the model. We tested the interaction term between age and gender, but there was no significant association. A multiple linear regression model was used to identify predictors of stress among the study participants. We used a stepwise technique with a locked term “stimulant abuse” and a P value for the entrance of independent covariates set to 0.1, and a P value of 0.101 was set as the exit value of the model. There was collinearity between age and academic level, but we decided to keep age because it is a continuous variable and showed a strong association with the outcome of stress. A P value of less than 0.05 with two-tailed probability was considered statistically significant.
Bahlaq M.A., Ramadan I.K., Abalkhail B., Mirza A.A., Ahmed M.K., Alraddadi K.S, & Kadi M. (2023). Burnout, Stress, and Stimulant Abuse among Medical and Dental Students in the Western Region of Saudi Arabia: An Analytical Study. Saudi Journal of Medicine & Medical Sciences, 11(1), 44-53.
Publication 2023
A-101 Burnout, Psychological Drug Abuse Gender Student
3
Multiparous Buffalo Estrous Cycle Management
A total of 101 (n = 101) adult (3–6 years age) multiparous (1–3 lactations) crossbred buffaloes with moderate body weight (621.12 ± 121.3 kg) and body condition score (2.5–3 points; 1–5 scale) (22 (link)), were randomly allocated into three treatment groups based on GnRH dosages. The selected buffaloes were clinically and physically healthy, normal history of reproductive soundness and showed regular estrus cycles, which were determined by tracking follicular development and ovulation through routine ultrasonography. All animals were housed in an open shed with a cemented rooftop and two sides fenced by galvanized wire mesh. The fans were installed for ventilation, and sprinklers for showering during peak heat periods; the grooming brush facilities were also available at the farm. A head-to-head stall-feeding system was in practice. Each animal was allocated an area of ~3.7 m2 and a manager of 0.6 by 0.9 m. Total mixed ration (TMR) was offered to buffaloes at a standard ratio (60:40) forage [corn silage (8%), peanut vine (16%), soybean (17%), rice straw (2%), corn (38%), soybean hulls (16%), flaxseed meal (6.0%), cottonseed cake (6%), cornmeal (17.5%), vinasse (10%), Sodium bicarbonate (0.5%) and mineral-vitamin premix (6%)]. Animals had free access to fresh, clean water.
Abulaiti A., Naseer Z., Liu W., Ahmed Z., Abdelrahman M., Shaukat A., Pang X, & Wang S. (2023). Administration of GnRH at day 20 of AI and embryonic losses in synchronized crossbred buffalo. Frontiers in Veterinary Science, 10, 1118865.
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Publication 2023
A-101 Adult Animals Arachis hypogaea Bicarbonate, Sodium Body Weight Breast Feeding Buffaloes Corns Gonadorelin Head Human Body Minerals Oryza sativa Ovulation Silage Soybeans Ultrasonography Vitamins
4
Eukaryotic Protein Domain Analysis
All protein domain information was extracted from the Pfam database (Finn et al., 2016 (link)). We used the Pfam 33.1 version of May 2020, containing 18,259 entries. Among these domains, we used the Pfam-A subset of 18,101 curated domains for further analysis (Sonnhammer et al., 1997 (link)). Each alignment was filtered to remove information from Archaea, bacteria, viruses, and other sequences to retain only data from eukaryotes. Overall, they contain information from 27,077,043 domains from 1,161 species. The human protein domains were extracted from the canonical Uniprot transcripts used in Pfam and represent 5,168,776 amino acids out of the 12,871,017 amino acids in human proteins (40.2%).
For each residue, we then calculated an amino acid value using the following steps: creation of a count matrix, a corrected frequency matrix, a corrected relative frequency matrix, and the position score matrix.
Corcuff M., Garibal M., Desvignes J.P., Guien C., Grattepanche C., Collod-Béroud G., Ménoret E., Salgado D, & Béroud C. (2023). Protein domains provide a new layer of information for classifying human variations in rare diseases. Frontiers in Bioinformatics, 3, 1127341.
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Publication 2023
A-101 Amino Acids Amino Acids, Acidic Archaea Bacteria Eukaryota Homo sapiens NR4A2 protein, human Protein Domain Virus
5
Comprehensive Gait Kinematics Analysis
Foot contact and foot-off were manually determined for both sides by visual inspection using digitial video recordings and the foot marker trajectories from the Nexus software (Vicon, Oxford, UK) in the children. For the adults, foot contact was defined as the local minima of the heel marker and foot off as the lift-off of the VM marker by 2 cm from the minimum detected at stance (Cappellini et al., 2006 (link)). Strides with jumping, dragging etc. were excluded from further analysis as was gait initiation and termination. Flight phases and double support phases were determined based on right and left foot contact and foot off. The Froude number (Fr) is a dimension-less parameter suitable for the comparison of locomotion in subjects of different size (Alexander and Jayes, 1983 (link)). The Froude number was computed for all gait cycles based on the mean velocity of the horizontal IL marker (v), leg length (l), and the gravitational constant (g) using: Fr = v2/(g ⋅ l). Kinematic parameters were calculated based on the 3D kinematics of the lower legs and trunk. The body was modeled as an interconnected chain of rigid segments: SHO-IL for the trunk, IL-GT for the pelvis, GT-LE for the thigh, LE-LM for the shank, and LM-VM for the foot. The main limb axis was defined as the virtual line connecting GT and VM. Joint and elevation angles were generated accordingly. A total of 101 parameters were estimated for each gait cycle using a custom-written algorithm (Dominici et al., 2012 (link); Bach et al., 2021a (link)) to provide a comprehensive quantification of locomotor patterns. They can be functionally split into themes such as temporal features, limb endpoint trajectory, stability, joint and segment angles, joint and segment angular velocities, intra- and interlimb coordination, intersegmental coordination, and pendulum mechanism. Parameters that were directly influenced by body size were normalized to leg length. For a detailed list we refer to Supplementary material 1. All parameters were visually inspected for outliers due to experimental errors (e.g., partially missing markers) and, if the errors were present, the stride was removed from further analysis (∼4 and ∼8% of total recorded strides for P1 and P2, respectively).
Bach M.M., Zandvoort C.S., Cappellini G., Ivanenko Y., Lacquaniti F., Daffertshofer A, & Dominici N. (2023). Development of running is not related to time since onset of independent walking, a longitudinal case study. Frontiers in Human Neuroscience, 17, 1101432.
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Publication 2023
A-101 Adult Body Size Child Epistropheus Foot Gap Junctions Gravitation Heel Human Body Joints Locomotion Muscle Rigidity Pelvis Thigh

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More about "A-101"

A-101 is a widely used research protocol or assay often referenced in scientific publications, preprints, and patents.
It describes experimental methods and procedures employed in various fields of study.
Optimizing A-101 protocols is crucial for ensuring reproducibility, accuracy, and streamlining the research process.
PubCompare.ai is a powerful tool that can help researchers enhance their A-101 protocols.
By providing AI-driven comparisons, the platform enables researchers to identify the best methods and products for their specific needs.
This can lead to improved experimental outcomes, increased reproducibility, and remarkable results.
Researchers may also leverage other common laboratory techniques and equipment, such as the HiSeq 2000 and HiSeq 2500 sequencing platforms, RNeasy Mini Kit and QIAamp DNA Mini Kit for nucleic acid extraction, Qubit fluorometer for quantification, MiSeq platform for targeted sequencing, Dual-Luciferase Reporter Assay System for gene expression analysis, Power SYBR Green PCR Master Mix and MiScript SYBR Green PCR Kit for real-time PCR, and the Agilent 2100 Bioanalyzer for quality assessment of biomolecules.
By combining these tools and technologies with optimized A-101 protocols, researchers can streamline their workflow and acheive unprecedented results.