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Sweat Glands

Sweat Glands: Exocrine glands located in the skin that produce and secrete sweat, a watery fluid composed of water, salts, and other substances.
Sweat glands play a crucial role in thermoregulation, helping to maintain body temperature through evaporative cooling.
They are distributed widely throughout the body, with the highest concentraions found on the palms, soles, and axillae.
Sweat gland research is essential for understanding physiological processes related to sweating, as well as potential disorders such as hyper- or hypohydrosis.
PubCompare.ai can optimze your sweat gland studies by helping you identify the most accurate and reproducible research methods from literature, preprints, and patents, improving the quailty of your investigations.

Most cited protocols related to «Sweat Glands»

1
Gene ORGANizer: Visualizing Phenotypic Effects
Gene ORGANizer was designed to provide researchers with the ability to analyze the phenotypic effects of genes and to understand the shared impact of groups of genes. The tool consists of two platforms: Browse and ORGANize. Browse allows users to see all of the body parts affected by a single gene of interest. ORGANize is designed to test which body parts, if at all, are over- or under-represented in a gene list. In both platforms, the user can base the analysis on either the typical phenotypes associated with a gene (defined as those that appear in >50% of sick individuals), or on its typical+non-typical phenotypes (i.e. any frequency). Additionally, the user can choose between confident associations (i.e. inferred from data on humans), and confident+tentative ones (inferred also from additional data on mouse and rat).
The output in both Browse and ORGANize comes in two forms: a color-coded body map and a table. The table contains all information whereas the body map visualizes most of it (125 out of the 146 body parts). Non-localized body parts (e.g. blood) or very small parts (e.g. sweat gland) do not appear in the body map and are represented only in the table. In the Browse option, the table and body map simply present the body parts that are phenotypically affected by the gene of interest, colored by the type of association (confident or tentative; typical or non-typical). Hovering over a body part in the table allows the user to see the phenotypes and diseases that are behind the gene–body part association. In the ORGANize option, the body map represents an interactive heat map, where significantly enriched or depleted body parts are colored based on the level of their enrichment or depletion. Non-significant body parts remain in their original gray color.
The enrichment and depletion tests within a gene list are carried out against a list of background genes. By default, the background consists of all genes that are linked to body parts in our DB. This background assures that even if certain anatomical parts are over-represented in the ontology (because some phenotypes are easier to detect, or some diseases are more studied), it would not bias the results (2 (link)). Gene ORGANizer also allows users to enter their own background list. User-specified backgrounds are useful in cases where the initial pool of genes from which the gene list was derived contains an inherent bias. For example, in a list of genes that were found to be differentially regulated based on a microarray experiment, the background should comprise only genes that are represented on that microarray.
Gokhman D., Kelman G., Amartely A., Gershon G., Tsur S, & Carmel L. (2017). Gene ORGANizer: linking genes to the organs they affect. Nucleic Acids Research, 45(Web Server issue), W138-W145.
Publication 2017
BLOOD Genes Genetic Testing Homo sapiens Human Body Mice, Laboratory Microarray Analysis Parts, Body Phenotype Self Confidence Sweat Glands
2
Quantifying Autonomic Skin Innervation in Lewy Body and Non-Lewy Body Neuropathic Orthostatic Hypotension
Regions of interest were drawn (white dotted outlines) around arrector pili muscles (Figure 1A and 1D), blood vessels (Figure 1B and 1E), and sweat glands (Figure 1C and 1F). Average fluorescence intensity of AS (green), SMA (blue), and TH (red) within the regions of interest was measured using Fiji software after background subtraction and tabulated for each visualized constituent.
For colocalization analyses the method of Jaskolski et al.45 (link) was used, with calculation of the AS/TH colocalization index in the entire image as follows: (1) normalized mean deviation product (nMDP) values for colocalization were tabulated from −1.0 to +1.0 (Figure 2A); (2) the counts corresponding to nMDP values from 0.3 to 1.0 were summed (red or blue boxes in Figure 2A); (3) 0.1 was added, so that the sum of the counts was greater than zero; (4) the log of the number from step (3) was calculated. The formula for the colocalization index therefore was the following.
Mean values (± 1 standard error of the mean) for AS, AS/TH ratios, and AS/SMA ratios for each of the 3 skin constituents and for myocardial NE contents were compared between the Lewy body nOH and non-Lewy body nOH groups by independent-means t-tests conducted on log-transformed data. T-tests were also used to compare mean values for 18F-dopamine-derived radioactivity and clinical and other laboratory parameters between the Lewy body nOH and non-Lewy body nOH groups. Frequencies of values in compared groups were analyzed by Fisher’s exact test. A p value less than 0.05 defined statistical significance.
Isonaka R., Rosenberg A.Z., Sullivan P., Corrales A., Holmes C., Sharabi Y, & Goldstein D.S. (2019). Alpha-synuclein deposition within sympathetic noradrenergic neurons is associated with myocardial noradrenergic deficiency in neurogenic orthostatic hypotension. Hypertension (Dallas, Tex. : 1979), 73(4), 910-918.
Publication 2019
Blood Vessel Dopamine Fluorescence Hair Lewy Bodies Muscle Tissue Myocardium Radioactivity Skin Sweat Glands
3
Validation of Galvanic Skin Response Device
Different tests were conducted in order to verify the behavior of the GSR device:

In a calm state, trying to feel relaxed.

Trying to be nervous: at the second stage, we asked the subjects to think about something which makes him nervous or produces anxiety.

Taking in air and expelling it forcefully: the subject is relaxed and, after one minute, he is asked to take in air and expel it, trying to push himself as hard as possible. As the result of this, the nervous system indicates to the sweat glands that an effort has been made.

Mathematical operations: the subject is relaxed and, after one minute, the computer shows him different mathematical operations. The subject is asked to feed the different results into the computer.

Reading: after 90 seconds, the screen shows some words that the user has to read as fast as possible (Figure 3).

Another test where the computer shows different images to the subject was also used. Some of these pictures are “emotional” (they should affect the subject's emotional state) and the others are “neutral” (they have no influence on the subject). It was supposed that the emotional ones would provide a response, but, after trying with some subjects, we have not included this because the results were insignificant.

Table 2 shows the places where the different studies took place. The studies have been made at the subject's home and office because GSR is intended to work in daily situations.
Villarejo M.V., Zapirain B.G, & Zorrilla A.M. (2012). A Stress Sensor Based on Galvanic Skin Response (GSR) Controlled by ZigBee. Sensors (Basel, Switzerland), 12(5), 6075-6101.
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Publication 2012
Anxiety Emotions Feelings Medical Devices Neoplasm Metastasis Nervousness Sweat Glands Systems, Nervous
4
Assessing Sweat Gland Function with SUDOSCAN

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Publication 2013
Arecaceae Chlorides Foot Forests Heart Ions Iontophoresis Kidney Skin Stainless Steel Sweat Glands
5
Non-Invasive Sweat Biomarker Sensing
The SWEATSENSER device consists of a replaceable sweat sensing strip and an electronic reader. The sensing strip is functionalized with specific target capture probes, that is, IL‐6, IL‐8, IL‐10, and TNF‐α monoclonal antibodies as described previously. This sensor strip is mounted onto a wearable electronic reader that transduces the impedance response from the sensor and reports the measured biomarker levels in sweat. The sensor fabrication process has been adapted from Munje et al. and has been described in detail previously.47 (link) Briefly, a sensing‐electrode system is fabricated on the SWEATSENSER strip for enabling transduction of affinity‐based interaction between the target biomarker and capture probe antibody into a measurable electrochemical signal. The sensor has been designed to handle low volumes of sweat and the design has been optimized by considering the sweat gland density, sweating rate, and surface area of contact. Non‐faradaic electrochemical impedance spectroscopy was used as the detection modality to determine the sensing response of the binding interactions between the specific capture probe and target molecule. A very low input of 10 mV sinusoidal voltage was applied to the sensing electrodes and the change in impedance due to the binding interaction between target molecule and capture probe antibody resulting in charge modulation was recorded at 180 Hz. Calibration curve for each study marker was developed by measuring the impedance response for varying concentrations of the target analyte over the physiological range of 0.2–200 pg mL−1.
Jagannath B., Lin K., Pali M., Sankhala D., Muthukumar S, & Prasad S. (2021). Temporal profiling of cytokines in passively expressed sweat for detection of infection using wearable device. Bioengineering & Translational Medicine, 6(3), e10220.
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Publication 2021
Biological Markers Dielectric Spectroscopy IL10 protein, human Immunoglobulins Medical Devices Monoclonal Antibodies physiology Sinusoidal Beds Sweat Sweat Glands TNF protein, human

Most recents protocols related to «Sweat Glands»

1
Electrodermal Activity: A Window into the Autonomic Nervous System
EDA, sometimes also referred to as Galvanic Skin Response (GSR), is a measurement of small fluctuations in the conductance of the skin. It is measured by applying a low and undetectable voltage to the skin and monitoring the changes in conductance afterwards. While in the past, larger devices in combination with (wet) electrodes were used to measure it, various wearable devices such as wristbands are able to detect EDA today as well. Usually, EDA measurements are given in micro Siemens ( μ S) and present values greater than 0 and smaller than 20. The readings are directly related to the sweat secretion on the electrode site, which is linked to the Autonomic Nervous System (ANS), and therefore changes unconsciously and cannot be controlled voluntarily. Here, an increase in the arousal of the sympathetic branch of the ANS leads to increased sweat gland activity, which is visible by a rising EDA. Currently, EDA measurements are leveraged for various ML tasks. Correlated with psychological or physiological arousal, it is often used in emotion recognition [30 ]. Several publications proved that automated pain recognition models can be trained using EDA data [13 (link),20 (link),29 ]. In addition, it was shown that even small differences in the applied pain stimulus lead to changes in the EDA curves [31 (link)]. The analysis of EDA discriminates between the slowly changing Skin Conductance Level (SCL), also referred to as tonic level, and the smaller spikes in the signal called Skin Conductance Responses (SCRs), sometimes also referred to as phasic information. These SCRs can be event-related and triggered by external stimuli, based on motor activity or just spontaneously occur without an impulse or event [32 (link)]. Figure 2 shows an EDA recording during a painful heat stimulus.
Gouverneur P., Li F., Shirahama K., Luebke L., Adamczyk W.M., Szikszay T.M., Luedtke K, & Grzegorzek M. (2023). Explainable Artificial Intelligence (XAI) in Pain Research: Understanding the Role of Electrodermal Activity for Automated Pain Recognition. Sensors (Basel, Switzerland), 23(4), 1959.
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Publication 2023
Arousal Emotions Galvanic Skin Response Medical Devices Nervous System, Autonomic Pain physiology secretion Skin Sweat Sweat Glands
2
Fabrication of Microfluidic Sweat Chip
The microfluidic chip includes a PDMS cover layer and a PDMS channel layer with microfluidic channels and chambers, and a waterproof medical biological double-sided adhesive pasted under the PDMS channel layer. Figures S1 and S2 show the details of the fabrication processing of microfluidic chips and the detailed chip design parameters. The mold of the PDMS channel layer was fabricated by patterning negative photoresist (SU-8 3050, Microchem, Newton, MA, USA) on a silicon wafer using a direct laser writing system (MicroWriter ML3, Durham Magneto Optics Ltd., London, UK). The SU-8 spin speed and time: 1000 rpm, 40 s; select exposure dose was 2200 mJ/cm2. The surface of PDMS was flattened by standing for 1 h on the horizontal plane. There are two reaction chambers with a volume of about 2.5 µL (diameter: 4 mm, height: 200 μm) and short straight ducts (width: 300 μm, height: 200 μm) on the PDMS layer. The PDMS prepolymer and curing agent were prepared in a mass ratio of 15:1, and 10% Triton X-100 was added to mix evenly, poured onto the fabricated mold followed by vacuuming for 30 min to remove the air between micropillars, and then cured at 80 °C for 1 h. After lifting the PDMS channel layer from the silicon mold, the inlets and outlets of the microchannel were punched using a punch with a diameter of 1.5 mm. The PDMS cover layer without Triton X-100 (thickness: 800 μm) was processed in the same way. The processed PDMS channel layer and PDMS cover layer were cut into circles (diameter: 30 mm) with a scriber. Then, the glucose sensor and the pH sensor were placed in the chamber of the PDMS channel layer, followed by bonding two PDMS layers together using oxygen plasma treatment (PDC-002, Harrick Plasma, Ithaca, NY, USA). Finally, three sweat inlets with a diameter of 3 mm were punched on the waterproof medical double-sided glue to ensure that each inlet could cover about 5 to 10 sweat glands. The microfluidic chip and the adhesive layer were aligned according to the position of the inlet and then bonded. The fabricated microfluidic sweat chip was placed in a plastic bag, vacuumed, and stored in a cool and ventilated place for subsequent use.
Liu D., Liu Z., Feng S., Gao Z., Chen R., Cai G, & Bian S. (2023). Wearable Microfluidic Sweat Chip for Detection of Sweat Glucose and pH in Long-Distance Running Exercise. Biosensors, 13(2), 157.
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Publication 2023
A-A-1 antibiotic Biopharmaceuticals DNA Chips Eye Fungus, Filamentous Glucose Plasma Silicon Sweat Sweat Glands Therapies, Oxygen Inhalation Triton X-100
3
Multimodal Sensor Protocol for Psychophysiological Assessment
The PMS proposed in this work includes measurements of cardiorespiratory activity, GSR and ST, as these were found to be the parameters that most closely reflect the activities of the autonomic nervous system in response to external stimuli, such as risk factors [24 (link)].
The electrocardiogram provides multiple pieces of information about the health and cognitive state of the user. Heart Rate (HR) and Heart Rate Variability (HRV) are the two main features that can be extracted from the electrical activity of the heart. Indeed, HR exhibits modifications according to the activity performed and the health status of the user. For instance, HR decelerates after the stimuli administration, and a high varying HR with respect to the baseline value is associated with high aroused conditions [25 (link)]. On the other hand, the HR increases and the HRV decreases whenever the user performs an intense physical activity [26 ].
Many disorders and/or stimulus administrations generate alterations in respiratory activity. Respiration Rate (RR) is a vital sign sensitive to different pathological conditions and/or stressors including emotional stress, cognitive load, heat, cold, physical effort and exercise-induced fatigue [27 (link)]. Moreover, it can be used to assess the psychophysiological state of a user even if its modifications are much slower than those exhibited by other physiological parameters.
GSR is a physiological parameter commonly used to assess users’ cognitive state [28 ]. The higher the sweating, the higher the increase in the electrical conductance of the skin. Hands and feet are commonly used to measure GSR since they exhibit the highest density of sweat glands in the body. Moreover, the GSR is made of two different components—the Skin Conductance Level (SCL), the tonic and slowly changing part—reflecting the participants’ arousal and the Skin Conductance Response (SCR), the phasic fast-changing one, reacting to stimulus administration.
ST is another important parameter for determining the psychophysiological state and can be used to predict heat stroke conditions [29 (link)]. In fact, sudden or excessive increases in the users’ temperature may reveal abnormalities. It may depend on some individual factors (i.e., age, gender) and external factors [30 ].
Tamantini C., Rondoni C., Cordella F., Guglielmelli E, & Zollo L. (2023). A Classification Method for Workers’ Physical Risk. Sensors (Basel, Switzerland), 23(3), 1575.
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Publication 2023
Arousal associated conditions Cognition Cold Temperature Congenital Abnormality Electric Conductivity Electricity Electrocardiography Emotional Stress Fatigue Fever Foot Gender Heart Heat Stroke Human Body Nervous System, Autonomic Pathologic Processes Physical Exertion physiology Rate, Heart Respiratory Rate Signs, Vital Skin Sweat Glands
4
Quantitative Proteomic Analysis of Sweat Glands
Sweat glands from DC tissue samples (n = 9) and sweat glands isolated from normal palmar skin (n = 9) were denatured, alkylated, and digested as previously described [41 (link)]. Samples were injected into Thermo ScientificTM DionexTM UltimateTM 3000 RSLCnano systems equipped with NCS-3500RS (microflow) module and Q Exactive Plus—OrbitrapTM spectrometer (Thermo Fisher Scientific) operated in Data-Independent Acquisition (DIA) mode for peptide and protein quantification. Raw data was processed and analyzed by DIA-NN software [42 (link)] using default parameters. Q value (FDR) cut-off on precursor and protein level was applied 1%. All selected precursors that passed the filters were used for quantification. Proteomic data was analyzed using the Perseus software platform version 1.6.15.0 (www.perseus-framework.org (accessed on 10 November 2022) [43 (link)]). Samples with few data (names in manuscript: Control 7–9, DC 7–9; names in protein dataset: N1, N2 and N8, DD0, DD5 and DD7) as well as keratins, and immunoglobulins were removed. Data was filtered for at least 70% of the total valid values, and missing values were imputed from normal distribution width 0.3, down-shift 1.8. Up- or down-regulation was considered significant when p value < 0.05. The Kyoto Encyclopedia of Genes and Genomes (KEGG) mapper was used to visualize the signaling pathways involved, and enrichment analysis was performed using EnrichR tool (www.maayanlab.cloud/Enrichr/ (accessed on 10 November 2022)).
Cárdenas-León C.G., Mäemets-Allas K., Klaas M., Maasalu K, & Jaks V. (2023). Proteomic Analysis of Dupuytren’s Contracture-Derived Sweat Glands Revealed the Synthesis of Connective Tissue Growth Factor and Initiation of Epithelial-Mesenchymal Transition as Major Pathogenetic Events. International Journal of Molecular Sciences, 24(2), 1081.
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Publication 2023
Arecaceae Cytokeratin Down-Regulation Genes Genome Immunoglobulins Lanugo Peptides Proteins Signal Transduction Pathways Skin Sweat Glands Tissues
5
Proteomics of Dupuytren's Contracture Sweat Glands
Nodular tissue samples from Dupuytren’s contracture (DC samples) were obtained from biopsies taken from twelve patients with DC with extensive, stage 2 or 4 fibrosis of the palmar fascia undergoing open radical palmar fasciectomy. Normal palmar fascia (control samples) were obtained from nine patients unaffected by DC undergoing open carpal tunnel release surgery. All samples were collected at the Tartu University Hospital, Surgery Clinic between January to June 2022 (Permit 335/T-1 from the Committee for Human Studies, University of Tartu), and the procedures were performed in accordance with The Declaration of Helsinki and written informed consent was obtained from the patients. In total twenty-seven samples were collected: twelve control samples and fifteen DC samples, of which, nine samples per condition were used to collect sweat glands for the proteomics experiment, while three control samples and six DC samples were used for immunofluorescence analysis.
The nodular tissue was separated from the DC chords, embedded in O.C.T compound (Sakura Finetek) and stored at −80 °C until further analysis. Six DC samples and three control samples were used for immunofluorescence analysis. Eighteen samples from eighteen different patients were used to collect sweat glands. For sweat gland separation, subcutaneous fat and DC chords were removed under aseptic conditions, the remaining tissues were minced into small pieces and digested overnight with 0.1% Collagenase I (Thermo Fisher Scientific, Grand Island, NY, USA) at 37 °C in an incubator with 5% CO2. On the next day, sweat glands were isolated with a pipettor under an inverse microscope [8 (link)]. Sweat glands were collected into separate tubes (per patient) and stored at −80 °C until further analysis. Supplementary Table S2 shows data on donor age, sex, and experiment in which the samples were used.
Cárdenas-León C.G., Mäemets-Allas K., Klaas M., Maasalu K, & Jaks V. (2023). Proteomic Analysis of Dupuytren’s Contracture-Derived Sweat Glands Revealed the Synthesis of Connective Tissue Growth Factor and Initiation of Epithelial-Mesenchymal Transition as Major Pathogenetic Events. International Journal of Molecular Sciences, 24(2), 1081.
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Publication 2023
Arecaceae Asepsis Biopsy Collagenase, Clostridium histolyticum collagenase 1 Dupuytren Contracture Fascia Fasciotomy Fibrosis Homo sapiens Immunofluorescence Microscopy Operative Surgical Procedures Patients Subcutaneous Fat Sweat Glands Tissue Donors Tissues Wrist Joint

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More about "Sweat Glands"

sudoriferous glands, hyperhidrosis, hypohidrosis, Matrigel, EGF, Leica DM4000 B LED microscope, Dispase, EpiLife medium, TRIzol, Ham's F-12 nutrient mixture, Hydrocortisone 21-hemisuccinate, RNeasy Plus Mini Kit