In general, volatile organic compounds (VOCs) have a high vapor pressure at room temperature (RT). It has been reported that all humans generate unique VOC profiles in their exhaled breath which can be utilized as biomarkers to diagnose disease conditions. The VOCs available in exhaled human breath are the products of metabolic activity in the body and, therefore, any changes in its control level can be utilized to diagnose specific diseases. More than 1000 VOCs have been identified in exhaled human breath along with the respiratory droplets which provide rich information on overall health conditions. This provides great potential as a biomarker for a disease that can be sampled non-invasively from exhaled breath with breath biopsy. However, it is still a great challenge to develop a quick responsive, highly selective, and sensitive VOC-sensing system. The VOC sensors are usually coated with various sensing materials to achieve target-specific detection and real-time monitoring of the VOC molecules in the exhaled breath. These VOC-sensing materials have been the subject of huge interest and extensive research has been done in developing various sensing tools based on electrochemical, chemoresistive, and optical methods. The target-sensitive material with excellent sensing performance and capturing of the VOC molecules can be achieved by optimizing the materials, methods, and its thickness. This review paper extensively provides a detailed literature survey on various non-biological VOC-sensing materials including metal oxides, polymers, composites, and other novel materials. Furthermore, this review provides the associated limitations of each material and a summary table comparing the performance of various sensing materials to give a better insight to the readers. Nowadays, exhaled breath analysis is considered an important area of research in order to diagnose several diseases at an early stage. In ancient times, several physicians observed certain odors in the human exhaled breath which are associated with a certain specific disease and its stage. For example, a diabetic patient was observed to exhale a ‘fruity’ odor while renal failure has shown an association with some ‘fishy’ smell . Later, The concentrations of available VOCs in the exhaled breath are determined in the range of nanomolar to picomolar levels. Hence, it is always a challenging task to distinguish normal individuals from the patients suffering from some chronic disease via endogenously formed VOCs. However, collecting the exhaled breath samples is painless, extremely simple, and noninvasive which provides a great benefit to the patients. Therefore, it is worth investigating human breath VOC detection. Gas chromatography–mass spectrometry (GC–MS) has been considered as the most accurate, selective, and sensitive method which has been utilized for several years to detect these VOCs from exhaled breath. The GC–MS technique utilizes the ion-pair extraction of the breath sample and quantification by mass spectrometry to monitor VOC concentrations as low as part per trillion (ppt). Although the instrument is promising, it faces the most significant limitations due to its cost, time consumption, off-site analyses, and the requirement for skilled technicians. To overcome this limitation, several researchers have proposed various user-friendly interfaces for the sensing system. To detect these VOC biomarkers in the exhaled human breath such as exploiting catalyst , electro2− (<100 °C), O− (100 °C to 300 °C), and O2− (>300 °C) on the surface of sensing materials [Nanoscale sensing materials of sizes varying in the range of 2 nm to 100 nm (within the Debye length of the surface) are utilized as the highly sensitive sensing elements in vapor/gas sensors due to their large surface-to-volume-ratio and their unique optical, chemical, and electrical properties compared to the non-nanoscale sensing materials . Gas cheaterials ,12. Geneaterials ,14. It aThis review is organized in the following manner: The VOC composition in the exhaled breath is complex and determined by several external and internal factors, e.g., metabolic, inflammatory, and oxidative stress processes and environmental conditions . These V5H8), acetone (C3H6O), ammonia (NH3), methane (CH4), aldehyde (R−CH=O), and hydrogen sulfide (H2S) [The most important VOC biomarkers of the diseases in the human body are isoprene (Cde (H2S) . This sede (H2S) :(i). Isoprene: Isoprene generally appears copiously in the exhaled breath of patients suffering from some chronic diseases. In 2001, McGrath et al. investigated the level of isoprene in exhaled breath of patients suffering from heart failure [ failure . Breath  failure . The out(ii). Acetone: Acetone is a metabolite of glucose and human fat. It appears as the most common VOC in exhaled human breath. It was, firstly, recognized as the diabetes biomarker by Petters et al. in 1857 [ in 1857 . Glucose in 1857 . The hig(iii). Ammonia: Ammonia plays a vital role in nutritional benefits including the synthesis of amino sugar, the synthesis of pyrimidines and purines, producing non-essential amino acids, and maintaining the acid-base balance in the human body. However, when the ammonia concentration exceeds its control level, it becomes toxic to the human body. Therefore, this excess amount of ammonia has to be released from the body by ornithine or the urea cycle which converts this excess ammonia into urea and excretes it in the form of urine via the kidney [e kidney . This coe kidney ,26.(iv). Methane: Methane is considered to be an important gas appearing in exhaled human breath. It is produced by the methane-producing bacteria present in the intestine under anaerobic circumstances [mstances . Methanemstances . Methanemstances .(v). Aldehydes: Aldehydes, such as hydroxy alkenals, alkenals, and dialdehydes, are the products of lipid peroxidation and alcohol oxidation. Their elevated levels were observed in cancer patients [patients . During patients . In sevepatients .(vi). Hydrogen sulfide: Hydrogen sulfide is a popular VOC with a malodor. It is a significant gasotransmitter in animals and humans signaling several physical processes including neuromodulation, inflammation, cytoprotection, apoptosis, and vascular tone regulation [gulation ,34. Hydrgulation ,36,37.In The aforementioned discussions show that the human breath contains a variety of VOCs that serve as biomarkers for various diseases and metabolic problems. Therefore, the real-time monitoring of such VOCs in the exhaled human breath is highly essential to enable non-invasive illness detection. In the following subsections, a detailed discussion has been carried out to understand various techniques developed to detect VOCs in very low concentrations of part per million volumes (ppmv), part per billion volumes (ppbv), and part per trillion volumes (pptv).GC–MS is a technique in which a mixture of molecules of various compounds travel by a carrier gas  via a column that separates molecules and detects them by a detector. In the past decades, this technique has been utilized widely along with various types of detectors to detect VOCs in exhaled breath for the purpose of health monitoring. A block schematic diagram of GC–MS is shown in +, H3O+, O2+, etc., which can be later analyzed by a quadrupole mass spectrometer. 2+ as reagent ions in order to quantitatively detect isoprene in the exhaled breath [SIFT-MS is a tool of analytical chemistry which is similar to gas chromatography for the quantitative monitoring of VOCs . In thisd breath . Later id breath . In the d breath . The resd breath ,65,66.Classical PTR-MS is a tool of analytical chemistry which utilizes gas-phase hydronium ion as n ion with purity >99.5% of source reagent. The PTR-MS is utilized to monitor the absolute concentration of the selected VOCs as low as pptv without any calibration . Figure These techniques utilize the ion-pair extraction of the analytes and quantification by mass spectrometry to detect the VOC concentrations. However, a limitation of these techniques is that they can be time-consuming and expensive. They also require a skilled technician to operate which can be done only for off-site analysis. A detailed discussion of the advantages and limitations of these techniques is provided in 2, H2O, etc. MOs are chemical compounds that are formed by metal and oxygen. In general, MOs are known for their active selective material for sensing applications that encounters optical, chemical, and electronic inducement for analyte molecules detection [Oxide is a classification of chemical compound that has one or more oxygen atoms including other elements in its composition such as COetection ,72,73.MO nanostructures, such as ZnO, are n-type semiconductors that have a wide band gap energy (3.37 ev at 300 K), large excitation binding energy (60 meV) at RT , and a hAmong the different VOCs, acetone and ethanol are most studied and reported to be detected by different ZnO nanostructures while inadequate numbers of studies are done for other VOCs such as acetylene, n-butanol, cyclohexane, and benzene. Hardan et al. investigated the use of ZnO thin films on thermally oxidized Si substrates to detect isopropanol, acetone, and ethanol and reported the highest sensitivity of acetone detection at around 500 ppm at 400 °C . The mec2 sensor with hollow nanofibers in structures with a rapid response time of 5 s, with an excellent selective detection to 1 ppm ethanol at 200 °C. According to the report, a noble metal on the surface of ZnO is considered to be a site for adsorbate, catalysts, and surface reaction promoters and can improve the thermal stability of the nanostructure. The main advantages of this structure are its porosity and surface roughness morphology which makes it a promising candidate for efficient ethanol gas detection in the environment [3 micrograss-based composite structure [2/ZnO hollow cubes that were synthesized by using a self-template hydrothermal method followed by a calcination process [Although the different ZnO nanostructures coated sensors have been reported to show an excellent response to the different VOCs, a high selectivity and sensitivity sensor to effectively detect multiple vapors in a mixed volatile environment is still challenging. For this reason, it can be considered as a drawback for using ZnO nanostructure alone as a sensing material for VOCs . Some reironment . In the ironment . These gtructure . The mos process . They ex2 nanorods were found to adhere to those thin walls. With this structure, the VOC vapor sensing was carried out for formaldehyde, acetone, isopropanol, ethanol, n-butanol, methanol, benzene, and another three reductive gases  at 220 °C. Among all the VOC vapors, the hollow SnO2/ZnO cube sensor displayed excellent sensitivity, selectivity, and repeatability towards 100 ppm formaldehyde with stability for a long period of time and the highest response of 148 is achieved. This response was calculated from the ratio between the baseline resistance and the balanced resistance of the composite structure in the air and the test gases.ZnO nanostructure formation was found to be on the thin wall of hollow cubes. SnOThe selectivity of ZnO-based VOC sensors can be further improved by working on the features of the sensitive material as well as the operating parameters of the sensor. In addition, various limitations, and challenges, such as ultralow concentration detection, humidity interference from the individuals, and variability in VOC profiles of the individuals from the time of food intakes, have to be critically considered. Therefore, by changing the property of ZnO nanostructure morphologies with the doping and/or composite materials, a high selectivity sensor in a mixed gaseous environment can be accomplished with an effort to overcome the associated limitations. This can serve as the future development of multifunctional, compatible, and robust ZnO-based VOC sensors.Nickel oxide (NiO) is an intrinsic semiconductor and is widely used for VOC sensing due to its unique characteristics such as wide bad gap, stability at high temperatures, transparency, and excellent chemical stability. The accomplishment of NiO depends on its morphology, dimension, and phase state such as porosity and dimensions.In 2020, Nakate et al. studied the performance of the gas response of NiO nanosheets sensor via a hydrothermal chemical route which was prepared by mixing nickel nitrate solution and sodium hydroxide solution in de-ionized water . The morMeilin and Zhen developed mesoporous NiO for an ammonia sensor via the sol-gel method in 2019 . The synIn 2021, Ayyala et al. developed a chemoresistive NiO-based sensor for the detection of seven different common VOCs that include acetone, ethanol, toluene, hexane, methanol, 2-propanol, and isobutylene vapors between 5 ppm and 25 ppm at 350 °C and 40% relative humidity (RH) . They deNiO has been studied to improve the sensitivity, selectivity, and stability of the VOC sensor by utilizing the sol-gel, solvothermal, hydrothermal, spin coating and doping methods. The main sensing mechanism of the NiO-based VOC sensors is generally based on the adsorption, desorption, and oxidation processes. The pore size of NiO can be modified for VOC’s detection that depends on the size of the targeted VOC molecules. Generally, the highly responsive sensors mostly have mesoporous structures due to their good volatile gas adsorption properties. However, there were reports showing that NiO-based sensors has a slow response time and low limit of detecting different clinical VOC biomarkers in real-time from patients suffering from bladder cancer and cystic fibrosis ,96. Thes3) is an n-type semiconductor that can detect several gases, e.g., carbon monoxide [3-based VOC sensors is the adsorption and desorption of gas molecules in the sensing area. The gas adsorption of the MoO3 sensor depends on its morphology which can be categorized into three types of structures. Firstly, a structure with a high aspect ratio is a one-dimensional structure (1D) such as nanofibers, nanorods, and nanoribbons. They have a limited surface area, but their reaction sites are mostly exposed to the environment. Next, is a two-dimensional structure (2D), such as nanoplates and nanosheets, which provides a larger surface area that can improve the sensitivity of gas detection. Lastly, three-dimensional structures (3D), such as nanoarrays, nanoflowers, and nanospheres, are assembled from low-dimensional structures providing the largest surface area and have more reaction sites for gas adsorption. A larger dimensional structure contains more gas diffusion channels, allowing gas molecules to pass into reaction sites. Therefore, it shows better gas absorption and sensing performance towards VOC molecules.Molybdenum oxide  [3 help to improve the sensing performance but the doping of MoO3 with noble material also plays a significant role in the improvement of sensing performance [3 nanolamella for formaldehyde detection by using the solvothermal method [3 was doped with various doping concentrations of 2.5 mol%, 5 mol%, and 10 mol%. The morphology of α-MoO3 doped with different concentrations of Ni is shown in The MoO3 and Au , α-MnO2,d h-MoO3  affects d h-MoO3 . In 2016ne (TMA) . The senformance . In 2017l method . The α-M3 nanobelts for ethanol detection by applying gold nanoparticles onto α-MoO3 nanobelts using the hydrothermal method [3-coated sensor exhibited a rapid response with a recovery time of 4.3 s compared to a conventional α- MoO3 at 200 °C. The reported material has been investigated over ethanol, acetone, xylene, toluene, ammonia, and formaldehyde and observed to be highly selective for ethanol. In 2019 Shen et al. synthesized porous α- MoO3 nanosheets to detect TMA with a faster response and recovery time of 12 s and 200 s, respectively [3 structure was assembled from nanosheets for ethanol detection by Ji et al. [3 flower-like structures synthesized by the hydrothermal method including (i). sphere-like, (ii). rose-like, and (iii). plate flower as shown in In 2018, Wang et al. developed the multi-component structure of Au/α- MoOl method . The rodectively . The higi et al. . There w3-based VOC sensors can selectively detect specific gases due to their different morphologies. To increase the sensitivity and selectivity of the MoO3-based sensor, a doping material with a transition metal element is recommended. This technique can increase the sensitivity by reducing the activation energy of the chemisorption reaction, leading to more interaction between reaction sites and targeted VOC. Moreover, adding metal components to obtain the hybrid component structure can also be considered for improving the response and recovery times.It can be observed that several MOs have been exploited on a large scale to develop a real-time VOC sensor. MoO2) is a high-resistance n-type semi-conductor with a band gap of 3 eV. It gains huge attention in various applications including solar cells [2 is its chemical stability, catalytic properties, and easy modification of its optical, transport and structural properties which plays a significant role in gas-sensing applications [2 represents three crystal structures in nature which are (i) anatase, (ii) brookite, and (iii) rutile. The rutile structure is considered as the most stable, while the brookite and anatase structures are metastable and can be irreversibly converted to the rutile structure by annealing at 600 °C to 800 °C [2 gas sensors still have limitations that include low selectivity, high operating temperatures, unstable repeatability, and stability when it is exposed to oxidizing gases. In past years, several TiO2 nanomaterials with new composites and structures have been reported and used in VOC monitoring [2 nanostructures can be synthesized in zero-, one-, two-, or even three-dimensional nanostructures [2-based VOC sensors are mainly based on the adsorption phenomenon due to the presence of various active sites suitable for VOCs [2 structures and their role in the enhancement of the sensing performance of VOC gases. The TiO2 nanostructures are considered a potential sensing material for ultrasensitive and miniaturized vapor sensors due to their large specific surface area which provides various active sites for the adsorption of gases.Titanium dioxide  the extremely reactive surface provided by the oxygen-functionalized C60 and (ii) an electronic exchangeability between formaldehyde and the TiO2 nanoparticles via C60 layers.In 2021, Gakhar et al. synthesized fullerene-Caldehyde . The sen2 can be considered an ideal nanostructure for VOC detection due to its inherent properties of a strong adsorption capacity, large specific surface area, superior electron transport rate, and availability of the porous sites for faster diffusion of VOC molecules [2 nanostructure includes nanorods, nanotubes, nanobelts, nanowires, and nanofibers. Several methods have been reported for the synthesis of 1D TiO2 including hydrothermal [2 nanotube arrays synthesized by using electrochemical anodization contain more active sites for effective gas diffusion. The pristine 1D TiO2-based gas sensors have been successfully utilized to detect various VOCs, e.g., acetone [2 nanotubes for the real-time detection of benzene, toluene, and xylene (BTX) with enhanced sensitivity at a low temperature of 50 °C, as shown in The 1D TiOolecules ,124. 1D othermal , electroothermal , electroothermal , templatothermal , and matothermal . Among a acetone , isoprop acetone , ethanol acetone , formald acetone , isoprop acetone , etc. In2 nanotubes/Ti for the selective detection of four different VOCs including ethanol, methanol, acetone, and 2-propanol at RT [2 nanotube array was grown via the electrochemical anodization technique which exhibited a maximum capacitive response towards the methanol compared to the other VOC test gases. However, it cannot completely recover its response for all other test gases. Researchers have also synthesized single-, double-, and triple-layered TiO2 nanotube arrays by using a voltage pulse-assisted anodization method [2 nanorod array on fluorine-doped tin dioxide for the detection of low-concentration ammonia at RT [2 nanorods have a growth time of nearly 6 h with a high gas-sensing response of 102% for 100 ppm to ammonia at RT. The most recent article reported by Cai and Park, in 2022, showed a synthesis of cobalt  oxide (Co3O4)-decorated porous TiO2 nanofibers by using the facile electrospinning technique to detect acetone [3O4 nanoparticle of diameter 30–50 nm was decorated on TiO2 nanofibers via the solvothermal process. The fabricated sensor exhibited a good response for acetone (71.88) compared to the other VOCs including ethanol (7.58), toluene (2.55), benzene (2.01), and p-xylene (3.01). In addition, the sensor exhibited an average response and recovery time of 122 s and 351 s, respectively, for 100 ppm acetone gas at 250 °C.In 2019, Bindra et al. fabricated a sandwich-structured sensor using Au/TiOol at RT . The TiOn method . In 2020ia at RT . The obt acetone . The Co32 exhibited several versatile features including high specific area, flexibility, quantum Hall effect, and superior mechanical strength [2 nanostructure includes thin film, nanoplates and nanosheets. The 2D TiO2 subunits synthesized by using crystal facet engineering can significantly improve the selectivity and surface reactivity [2 nanostructures such as the chemical decomposition method [2 nanostructures. In the past decades, the pristine 2D TiO2 nanostructures have been employed for a wide range of VOCs including isopropanol [2 nanoplate-based micro-electro-mechanical system (MEMS) to detect acetone at RT, as shown in 2 nanoplates with defective and complete {001} crystal facets by varying the concentration ratio of hydrofluoric and hydrochloric acid during the synthesis. The results showed that the sensing performance of TiO2 nanoplates with complete {001} facets was 70% higher compared to the defective TiO2 nanoplates. The poor sensing performance of the defective TiO2 nanoplates is attributed to fewer adsorption sites on the surface. The TiO2 nanoplates with a volume ratio of hydrofluoric acid to hydrochloric acid of 2/50 exhibited good sensing responses of 21.8, 8.46, 4.32, 4.08, 6.64, and 2.73, for acetone, ethanol, toluene, methanol, isopropanol, and benzene, respectively, at 400 °C.The 2D TiOstrength . The 2D activity . Severaln method , the onen method , reactivn method , and then method . Among apropanol , methanopropanol , acetonepropanol , hydrogepropanol , and ammpropanol . In 20192 hexagonal nanosheets obtained from the layered TiSe2 nanosheet templates in a one-step annealing process [2 and acetone was achieved quickly due to the unique porous hierarchical structure of TiO2 nanosheets, crystal facet engineering and strong interface coupling. Recently, Tian et al. developed a MEMS sensor to study the influence of multi-layer of TiO2/SnO2 heterojunction on the detection of ethanol [2 was proposed due to its smooth surface and small particle size which advances the diffusion of ethanol. Although the sensor exhibited a slower response time of 33 s, it can effectively detect a lower concentration (50 ppm) of ethanol at 260 °C along with the sensor response value of 7.54. The sensing response was calculated from the ratio between the electrical resistance of the sensor in the air and the testing gas.In 2020, Ge et al. synthesized hierarchical porous TiO process . The fab ethanol . In the 2 nanoflower gains huge interest in VOC sensing. The TiO2 nanoflower structure comprises unique features allowing the diffusion and adsorption of VOC molecules onto its surface or penetrate into the interior part of these nanoflowers [2 nanoflowers exhibit superior electronic properties compared to 0D, 1D, and 2D TiO2 nanostructures. This performance improvement comes from the structural defects, which act as active sites between the gas and TiO2 material [2 nanoflowers can be synthesized by a facile hydrothermal method using titanium(III) chloride (TiCl3) [4) [4) [2H28O4Ti) [2 nanoflowers consisting of 2D nanosheets utilizing a low-temperature hydrothermal technique [2 nanoflowers surface in order to describe its performance at low operating temperature. They investigated the dual effect of the low bond dissociative activation energy and the higher VOC vapor pressure of the acetone molecules compared to the other VOCs . The result showed a maximum response towards acetone. In 2020, Wang et al. synthesized 3D hierarchical TiO2 nanoflowers to detect ethanol varying from 10 ppm to 500 ppm at RT, as shown in 2 nanostructure is composed of thin nanosheets and was synthesized by the hydrothermal technique. The sensor exhibited good sensing performance in terms of good stability, high selectivity, rapid response/recovery times, and good reproducibility against ethanol vapor at RT. The nanoflower structure and the spacing intervals provide more adsorption sites for the oxygen species and the VOC gases, leading to exceptional gas-sensing performance of the material.Nowadays, 3D structured TiOoflowers . Moreovematerial . The TiO (TiCl3) , titaniuCl3) [4) , Ti powdCl3) [4) , titaniu [4) [4) , TitaniuH28O4Ti) , or Ti fH28O4Ti)  as raw mechnique . The fab2 can be categorized as 0D, 1D, 2D, and 3D nanostructures. Each nanostructure exhibited an excellent sensing performance towards VOCs including selectivity, sensitivity, and rapid response time. From the above discussions, it can be seen that the higher dimension structure of TiO2 showed rapid response and recovery time. The lower dimension structure provided a poor response, but it is easy to synthesize. Even though TiO2 alone can successfully detect several VOCs, it fails to show a selective response in the mixed gaseous environment. Therefore, the noble metal loading/composition technique has been utilized by several researchers to enhance the selectivity for target-specific detection.In summary, TiO3, and TiO2)-based VOC sensors can be improved by reducing the particle sizes to a nanoscale level in the sensing layer. Thus, a larger surface area and a higher active site can be achieved leading to excellent sensitivity. Changing the property of MO-based sensors by doping and/or adding composite materials may offer an option for improving the selectivity and LODs. However, there still exist numerous challenges and limitations on VOC profiling for clinical samples in a multivariate environment and conditions. The MO-based sensors should also be able to overcome the major limitations of the VOC profiling approach such as the extremely high costs of the laboratory instruments based on accurate VOC detection, and standardized sample collection for clinical trials. In addition, the detection of ultralow concentrations of associated VOCs from te different persons, the development of generic MO-based sensors for their durability, robustness, selectivity, reliability, energy efficiency, and standard calibration of these sensors upon malfunction still remain a challenge.The performance of MO  nanoparticles by controlling chemical growth. They reported the composite materials, SnO2-GO (4:1), SnO2-GO (8:1), and SnO2-GO (16:1), and pristine SnO2 material for the detection of ethanol at low concentrations. Among them, the hybrid material SnO2-GO with a ratio of 16:1 was found to be superior for ethanol sensing at 1 ppm concentration both at RT (exploiting the UV light) and 150 °C with response and recovery times of 310 s/320 s and 70 s/75 s, respectively [2 vapor sensor using a combination of rGO and SnS2 [2 particles can adhere to the surface. SnS2 is integrated into rGO to increase the selectivity as it is an n-type semiconductor that has a special affinity allowing the adsorption of NO2 molecules due to the high electronegativity of a semiconductor. However, SnS2-based sensors are not usable at RT when used alone due to a high electrical resistance value. Therefore, integrating rGO with SnS2 to develop a NO2 sensor can allow rGO to benefit from SnS2 by achieving a high level of selectivity for NO2 gas, while SnS2 can utilize the superior level of conductivity from rGO to overcome its inherent resistance value and operate within RT.In the same year, Pargoletti et al. fabricated a novel composite material based on GO sheets that were decorated with tin dioxide  at 50 ppm acetone concentration at 220 °C which was 2.5 times higher than pure Fe3O4/rGO composite structure. This is due to the chemical and electronic excitation effects of Ag nanoparticles which generate more oxygen species and active sites for excellent gas sensing performance. Moreover, introducing the noble metals along with the metal oxide and rGO offers excellent sensitivity, good response, and selectivity of the device for practical applications.The sensitivity of GO and rGO VOC vapor sensors can also be improved by integrating them with nanostructured materials. In 2021, Zhao et al. reported the use of rGO in conjunction with SnOe sensor . The sen in 2022 . The com2 sensor consisting of rGO, ZnO and SnO2 [2-sensing properties of the sensors on rGO improved massively from the formation of the heterostructures between the two metal oxides. With this nanocomposite, the electronic properties of the hybrids and the band structure change thereby promoting effective charge transfer among the interfaces of heterostructures which improves the gas-sensing performance. With this advantage of ternary structure-based sensors, a similar kind of work was also reported by Sen et al. in 2021 using the same materials for the detection of VOC vapor [2/rGO sensor, a p-n-n heterojunction is created allowing a larger surface area for the VOC vapor absorption. This can significantly increase the sensitivity and response of the sensor for multi-VOC vapor detection in mix gaseous environment.In 2019, Wang et al. developed a ternary nanocomposite NOand SnO2 . They reOC vapor . TherefoMost rGO and GO-based VOC vapor sensors are usually fabricated to detect/target only one type of VOC vapor species which is the main limitation of this sensor. Therefore, it is highly desirable to develop a sensor that can be reliable, efficient, cost-effective, and possess a standard calibration for detecting multiple types of VOC vapor in terms of a clinical point of view in real-world applications. rGO is incorporated with other materials to take advantage of the desirable properties of each material to improve the VOCs sensing ability . In addi2 and sp3 hybridization. The perfect hybridization provides a higher electrical conductivity, larger specific surface area and other improved electrochemical properties [Carbon is one of the most abundant elements on the planet. It is a promising material for nanoelectronics as it is able to form itself into various crystal structures, resulting in a different material property. Due to its superior properties from the four valence electrons, allows the mixing of s and p atomic orbitals to form several hybridization, i.e., spoperties . In addi2 hybridization that is even stronger than the diamond lattice formed in the sp3 hybridization [Å) diameter. Therefore, the electrons can be quantized and confined along the circumferences and proceed only in the axial direction with a thousand times better mean free path compared to copper. Furthermore, the resistivity of the CNT can be as low as microohm per centimeter range [3 hybridization [−5 K−1 at RT which hiders the change in shape allowing more possible applications [A carbon nanotube (CNT) is a two-dimensional cylindrical structure with the thickness of one graphene arranged in a hexagonal lattice where each atom forms covalently with the spdization . CNTs hadization . For thidization . Many reer range . The super range . The idedization . In addiications .Carbon atoms can be arranged in a variety of nanostructures including CNTs which can be categorized into two major types, single-walled carbon nanotubes (SWCNTs) and MWCNTs. CNTs can also be categorized according to their chirality to be armchair, zigzag, and chiral, which represent their electronic properties to be metallic-like or semiconductor-like properties. The MWCNTs have a large surface area, high conductivity, and excellent flexibility in chemical stability compared to the SWCNTs . Therefo2)/MWCNTs composite layer using hydrothermal route to detect ammonia ranging from 12 ppm to 325 ppm, at RT [2/Ag and Ag/MoS2/MWCNTs/Ag. The device exhibited n-type semiconducting behavior and is capable of detecting ammonia as low as 12 ppm. The SEM image of MoS2 and MoS2/MWCNTs is shown in 2 configuration, the sensor exhibited a slow response time of 400 s which was later significantly improved by the MoS2/MWCNTs composite layer to be 65 s. It has also been discussed in the report that these significant differences appeared due to the different adsorption energy for different VOC molecules on the surface of MoS2 or MoS2/MWCNTs composite.In 2019, Janfaza et al. reported a highly selective chemoresistive sensor to detect hexanal composite layers of molecularly imprinted polymer (MIP)/MWCNTs on RT . The resm, at RT . In thisThe sensing performance of MWCNTs was later improved in 2022 by Yan et al. utilizing polypyrrole nanocomposite-coated with MWCNTs . Thermop2, PPy, MIP, etc. These composite materials not only solve the problem of deterioration of material but also improve performance in terms of sensitivity and response time.MWCNT can be considered one of the promising candidates in the VOC sensing application due to its superior properties, e.g., electrical, mechanical, and thermal properties. However, the major limitation of the MWCNTs sensor is the deterioration of the structure during long exposure sessions of the VOCs. This can cause a false output measurement which can be very crucial in some applications. Nonetheless, these challenges can be minimized by integrating with composite materials such as PEG, MoSWith the rapid progress of industrialization and constant development of urbanization, VOCs and their toxicity have been a serious concern not only in the environment but also for human health . With thACs are a type of absorption material that has been widely used due to their good physical and chemical properties with a large specific surface area, high chemical stability, high mechanical strength, and abundant functional groups along with alkali and acid resistance. Although ACs have these advantages, they also possess limitations due to their thermal stability and hydrophobic property. The ACs spontaneously ignite or collapse in a porous structure at high temperatures as it is a nonpolar absorbent. Therefore, it limits the adsorption towards hydrophilic VOCs ,217,218.There are several studies on ACs for the VOCs adsorption and its recovery such as alkane, alcohols, ethers, aldehydes, ketones, esters, aromatics, etc. In 2012, Li et al. investigated the influence of the ACs pore structure on the adsorption of VOCs . They reThe VOC investigated in this study was 1-ppm propionic acid. Its adsorption and desorption rates obtained were approximately 90% and 70%, respectively, making it an excellent gas concentrator which is benefited by low concentration for VOC detection. In the same year, Ma et al. studied the adsorption and adsorption mechanisms of toluene and chlorobenzene by two commercial ACs under medium-high-temperature (MHT) conditions . The twoNowadays, the development of the high-performance VOC gas sensor using carbon and carbon composite-based sensing materials offer great advancement and progress in terms of the structure design . HoweverIn A polymer is a substance or material consisting of very large molecules called macromolecules, made by linking up smaller repeating chemical units. In the past decades, polymers have gained huge interest in the field of the development of artificial sensors due to their special characteristics of swelling and shrinkage in the presence of gaseous molecules . Rapid r3)2- groups. PDMS has been considered an ideal material for the fabrication of integrated circuits and microfluidic channels [Poly (dimethylsiloxane) (PDMS) is a silicon-based elastomeric polymer which is formed by the cross-linked structure of the repeating units of -OSi  based optical vapor sensor array for micro-gas chromatography (μGC) applications . The repnd facet , as showIn 2019, Zhao et al. developed PDMS coated optical fiber sensor to form a FPI structure, as shown in Recently, Sappati et al. reported a printed acoustic wave sensor with PDMS as a sensing layer for the detection of the low concentration of VOCs . In thisMonitoring VOCs using conducting polymers (CPs) is at the core of attention for the fabrication of next-generation sensor applications. The CPs are recognized as a class of organic materials with unique optical and electrical features similar to those of metal and inorganic semiconductors. The major advantages of these polymers are their processability . CPs canIn recent years, PPy has been exploited in VOC sensing due to its salient features of high selectivity and sensitivity towards the detection of inorganic and organic gases . PPy, is2 nanosheet coated with PPy to detect ammonia at RT, as shown in 2 is an inorganic semiconductor gas-sensing material that exhibits poor conductivity at RT with no significant response to ammonia gas [2 with PPy to combine the features of both materials to improve the performance of sensors. The nanocomposite sensors exhibited a higher sensitivity of ∼6.2%/ppm for ammonia concentration varying from 1 ppm to 10.7 ppm, with a low LOD ∼257 ppb. The sensor coated with SnO2/PPy exhibited a higher response for ammonia compared to the sensor coated with PPy alone.The composite PPy-PVA film showed better sensing performance and rapid response time towards ethanol among other VOC vapors including ethanol, ammonia, chloroform, toluene, and acetone . Among sonia gas ,260. How2O/PPy nanocomposites for fast responsive and selective detection of ammonia at RT, as shown in 2O/PPy exhibited a 40 times higher amplitude of conductivity variation compared to pristine PPy with the presence of 1000 ppm of ammonia vapor. The sensor also showed excellent selectivity towards ammonia compared to ethanol, acetaldehyde, formaldehyde, benzene toluene, and m-xylene.In 2019, Wu et al. reported a PPy-coated polarization-maintaining fiber sensor to detect isopropanol . The sen°C. Additionally, the fabricated sensor was able to detect a clear signal with the humidity varying in the range of 0% to 80% at a low temperature, which is highly required for medical diagnosis during the breath analysis.Most recently, Byeon et al. synthesized SWCNT/PPy/phenyllactic acid nanocomposite as shown in 2, etc. The only challenging task of the PPy-based VOC sensor is the mixing of PPy with other materials which requires good knowledge of chemistry and expertise in the synthesis.Nowadays, there is a sudden growth in PPy-based VOC sensors due their high sensitivity, selectivity, stability, and rapid response at RT. High sensitivity and significant selectivity sensors can be obtained by integrating or doping the PPy with other materials, e.g., SWCNT, CdTe, SnO2O3) nanocomposite to study its potential for ammonia gas sensing [2O3 doping as well as increasing the concentration of ammonia. Later in 2016, Bai et al. synthesized hybrid material to detect nitrogen dioxide (NO2) utilizing reduced graphene oxide (rGO) and PTh [2 gas and excellent selectivity compared to a pure PTh sensor. Husain et al. reported a series of experiments on PTh and its potential in organic vapor sensing [2 nanocomposite for ethane detection [2 nanocomposite sensor exhibited a 19 times higher electrical conductivity, representing faster adsorption and desorption towards ethane compared to a pure PTh sensor due to its high surface area. In 2020, they proposed the utilization of PTh/SnO2 nanocomposite in a pellet-shaped for alcohol sensing including butan-1-ol , butan-2-ol , and 2-methyl propanol  at RT [2 pellet exhibited the highest sensing response in terms of the variation in DC electrical conductivity and maximal reproducibility for butan-1-ol. In the same year, Husain et al. developed PTh/GO nanocomposite to detect ethanol vapor at RT [Among the various conducting polymers, polythiophene (PTh), which is a p-type semiconductor, has been exploited very less for vapor detection compared to the other conducting polymers. However, the trend of using PTh nanocomposites in VOC-sensing technology has been rapidly increasing in the last few decades. In 2015, Tripathi et al. developed PTh/aluminium oxide . The specificity is a distinctive feature of MIPs that makes them an ideal element in the sensing system. In 1894, an idea of molecular interactions was reported by Emil Fischer using the term “lock-and-key” . The fir2S nanoparticle composite coated on quartz crystal microbalance (QCM) for aliphatic alcohol detection [2S nanoparticles results in a nanocomposite material with the collective properties of both materials. The MIP/Ag2S nanocomposite gave a normalized response of −70 Hz for 1-butanol vapor at 400 ppm, which was two times higher response compared to the pure Ag2S layer of similar thickness. The synergy produced by the strong affinity of Ag2S nanoparticles and the selective ability of MIPs toward 1-butanol vapor allowed fabricated sensors to have a relatively low detection limit (LOD) of 2 ppm. Later in 2016, Hussain et al. reported the QCM sensor coated with MIP for the detection of formaldehyde vapors in air streams [2 nanotube array composite, as shown in 2 nanotube array had a high surface-to-volume ratio, resulting in the improvement of sensing performance. As the humidity is neglected, the sensor can selectively detect formaldehyde in the ppm range at RT along in the long term.In 2014, Mustafaa and Lieberzeit reported a MIP/Agetection . Mixing  streams . The sen2 nanostructured electrochemical sensors utilizing MIP technique to detect acetone and ammonia, simultaneously [2 films were prepared using a spin coater under various conditions of introducing acetone and ammonium hydroxide as template molecules during the hydrothermal synthesis. A 500 nm thicker regular micro sheets have been developed from SnO2 nanoparticles of various sizes ranging from 20 nm to 50 nm (based on the synthesis condition). The sensing response of the device was tested against liquid petroleum gas (LPG), ammonium hydroxide, oxygen, acetone, and benzene. The result showed an increase in response for ammonia and acetone with the increment of the participation of the solvent during the synthesis. The results exhibited a promising response for ammonia gas with a highest sensitivity of 89% at 260 °C while for acetone the sensor exhibited a sensitivity of 77% at 230 °C. In a recent study published in 2022, Pathak et al. reported an optical sensor utilizing a MIP layer on a glass slide to detect isopropanol (IPA) vapor [In 2019, Abdelghani et al. developed highly sensitive SnOaneously . Four SnA) vapor . The worIn the same year, Mousazadeh et al. reported a chemorestive sensor with the use of Au/MIP nanocomposite to detect hexanol, which is a cancer biomarker . The comCP-based VOC sensors are nanomaterial-based sensors. This technology is commercialized under the name Cyranose 320, which comprises an array of 32 polymer composite sensors . AlthougIn Aside from these renowned sensing materials, some other materials have also been exploited by researchers due to their superior adsorption capability towards the VOC gasses. Some of them are selected to be discussed in the following section due to their excellent performance which can be promising in the VOC-sensing area.MOFs have emerged as an excellent sensing material for gas sensing due to its crystalline nature, extreme porosity and high surface areas . These p2/g [−1 (n-butylamine), Astakhov exponent from 0.50 (n-butylamine) to 3.03 (n-hexane), and the limiting adsorption capacity from 0.08 (n-hexane) to 12.8 (n-butylamine) mmol.g−1. MIL-101 showed the weakest affinity for n-hexane and the strongest affinity to n-butylamine. The dynamic adsorption mechanism mainly relies on the metal sites of MIL-101 which leads to greater VOC adsorption capacity and higher affinity compared to the AC. Most recently in 2022, Mousavi and Zeinali reported VOC detection based on resistive gas nanosensor using MIL-101(Cr)/CNT nanocomposite [MIL-n is a series belonging to the class of materials in MOFs which was first synthesized by Ferey’s group . The syn2/g . Due to 2/g . In 20112/g . They reomposite . The senAlthough the MIL-n series shows an excellent performance in gas separation and adsorption, there are still several limitations including poor stability, insufficient storage capacity, and high cost leading to limited research exploitation possibilities. However, the specific surface area, metal sites, pore structure, π-π binding, and modifiable groups are some of the key parameters which can affect the separation and adsorption processes of different VOCs. Currently, researchers are interested in designing and improving the structure of the MOFs materials, in order to develop a new MOFs material to attain specific functions and overcome their limitations.IRMOFs are a series of MOFs that own similar network topologies. Introducing a simple substitution of organic linkers of IRMOF-1 , other IRMOFs can be produced which shows unique property such as high chemical stability and a large Brunauer, Emmett and Teller (BET) surface areas . In 19952, Br, OC3H7, C2H4, OC5H11, and C4H4. In addition, its pore size can be expanded with a long molecular structure such as tetrahydropyrene, terphenyl, pyrene, and biphenyl. In order to improve the adsorption performance, pore texture and crystal structure of MOF-5, Saha et al. utilized diethylformamide as a solvent in the synthesis instead of the conventional solvent [2/g, with a pore size of 8.6 Å and pore volume of 1.39 cm3/g, respectively. Yang et al. developed MOF-177 at 85 °C by using solvent thermal technique and exhibited its superior adsorption capacity for VOC molecules [2/g, with an average pore size of 0.94 nm, and pore volume of 1.11 cm3/g, respectively. The material exhibited great adsorption towards benzene, toluene, acetone, ethylbenzene, o-xylene, m-xylene, and p-xylene in the air. From the above investigation, it is quite clear that the MOFs show an excellent adsorption capacity due to their large specific surface areas and may become good candidate materials in the VOC sensing.In 2015, Yaghi et al. proposed a high-absorptive material named MOF-5 (IRMOF-1) from benzene and octahedral Zn-O-C clusters links . In this solvent . This syolecules . In the 2/g, which can be maximized up to 1769 m2/g [Zeolites are micropores crystalline aluminosilicates with a highly ordered porous structure. Zeolites are widely utilized in various sensing applications including heavy metal detection , biosens769 m2/g .In 2009, Bhatia et al. reported the adsorption of butyl acetate using silver-exchanged yttrium (AgY (IE)) and silver-loaded zeolites (AgZSM-5 (IE)) at 28 °C . The Ag 2/ZSM-5 zeolite for the detection of formaldehyde was reported in 2021 by Sun et al. [2/ZSM-5 composite had a better sensing performance compared to the pure SnO2. This improvement was attributed to the composite structure by integrating ZSM-5 zeolite.An electrochemical sensor developed from SnOn et al. . The comZeolites are generally used in commercial separation processes and VOCs recovery due to their molecular sieving ability to preferentially adsorb certain molecules and to exclude others . The siz2, and MoO3 offer admissible responses to a different variety of VOCs due to their nature of absorbing gases/vapors and converting them into conductivity variations. Moreover, the usage of carbon-based materials, polymers, and other adsorption materials also have similar properties to metal oxides such as charge transfer between the gases/vapor species, oxidation, and the reduction of the dopants (n- or p-type) which are widely accepted as a promising candidate in the VOC-sensing applications. Their different modified morphologies at the nanometric scale with the introduction of different tunable elements have attracted the attention of many researchers because of their increase in a surface-to-volume ratio that gives rise to high sensitivity, fast response speed, lower operating temperatures, and good stabilities. However, the advances in terms of selectivity in a mixed volatile environment still remain to be a challenging task.This review highlights the potential use of active materials including metal oxides, polymers, conductive polymers, carbon-based materials, composites, and other adsorption materials as a VOC biomarker sensor due to their excellent sensing property and wide applicability. These materials are representatives for sensing clinical VOC biomarkers. The enhanced properties of these materials such as sensitivity, thermal stability, conductivity, selectivity, and fast responses generally include the control of their composition, size, and morphology. Some of the modified structures of these materials such as hierarchical structures, bilayer structure formation by the introduction of tunable attractive elements, such as by doping, have displayed an efficient improvement in VOC-sensing performances. VOC has increasingly affected the ecological environment and human health due to its high toxicity, carcinogenic, and photocatalytic in nature. Therefore, there is a need for their precise detection, monitoring, and controlling adverse effects of these VOCs effectively by combing the aforementioned materials in real time. Metal oxides such as ZnO, NiO, TiOAlthough outstanding advantages were achieved by implementing those materials into the VOC sensors, there are still major challenges involved in the clinical diagnosis of the VOC biomarkers. The thorough investigation in the functionality of materials to a larger group of VOCs as well as the implementation of other sensing mechanisms such as optical, electrical, and mechanical-based gas/vapor sensors are in high demand. In terms of materials, the accurate detection, and the sensitivity for the low concentrations (ppb-ppt levels) of the VOC biomarkers is a prime concern. Therefore, there is a strong need in exploring and utilizing new hybrid materials, i.e., Further, numerous reports can be found on the use of doping and composite materials for tailoring the sensor responses towards specific VOCs. However, valid information on efficacy and the role of such materials of VOC detection are limited. Moreover, a large number of reports are available for chemoresistive sensors that work under the resistive principle but not on electrical, optical, and mechanical detection of VOCs. Thus, in the future, the properties of materials for VOC detection should be explored more by utilizing the various physical changes. As these physical changes in the properties of materials may have the possibility to offer better selectivity for VOC-sensing devices.In summary, it can be seen that various challenges and concerns associated with VOC sensors are mostly based on the type of materials synthesis method discussed in this review. From the materials discussed earlier, incorporating them into developing gas sensors for the detection of associated clinical VOC biomarkers is known to influence its sensing performances. These materials are therefore gaining a huge interest in designing clinical and diagnostic tools.Thus, the clinical use of the VOCs from the human exhaled breath can be implemented by developing a versatile breath gas sensor with specific requirements depending on the applications to achieve a high response value, exceptional selectivity, lower LOD, great stability/reproducibility, stable calibration of the sensor system upon malfunction and high response/recovery speeds with a lower detection limit in real time. Moreover, from the economic point of view, these gas sensors based on the materials discussed should be universally available and should provide ease of fabrication, wider compatibility, and simple and low cost for easy implementation in different transducing platforms.Human breath analysis is an interdisciplinary field of research work which includes analytical techniques, data processing, medical science, materials chemistry, and engineering. Health monitoring and disease detection via blood analysis are invasive techniques which are painful to the patient. In the past decades, exhaled breath analysis has emerged as a better alternative to diagnose the disease at an early stage because of its non-invasive nature. However, the method is fraught with several challenges. Direct exhaled breath cannot be used in all breath analysis methods. Breath collection and its storage became a major issue. The collected breath which is stored for a long time is often degraded and hence, their original compositions are changed. Researchers are still not sure whether mouth-exhaled or nose-exhaled breath should be utilized for the VOC analysis. Currently, it is advised that dead space air should not be considered for breath analysis; only end-tidal breath should be used. However, for highly water-soluble breath biomarkers, such as isoprene and acetone, there is no anatomic dead space to be defined. Most of the sensor responses are dependent on the exhaled breath flowrate onto the sensor head. In the direct breath analysis, patients are allowed to directly exhale onto the sensing head. However, different patients would exhale at different flow-speeds, leading to inconsistent measurements. The exhaled breath concentration of various VOC gases varies significantly according to the patient’s gender, age, weight, race, food habits, pregnancy, lifestyle, etc. In addition, not all exhaled breath components are endogenous; rather, most of them are exogenous in origin. Many of the endogenous gases are not even systemic in origin. Therefore, locality becomes another confounding factor. In this section, a comparison of the performance is drawn between the gold-standard devices and other devices based on non-biological sensing materials. The selective detection of diseases from exhaled breath is limited to a small number of diseases, e.g., chronic obstructive pulmonary disease, diabetes, etc., which can be monitored using a single biomarker. In most diseases, especially various cancers, the concentrations of breath VOCs varied simultaneously. Therefore, the use of target-specific detection demands the development of highly selective sensing materials which is a paramount challenge in itself. Other sensors with poor selectivity can suffer problems from low to medium sensitivity. Therefore, obtaining sufficient discrimination between diseased and healthy groups might become difficult.Gold standards: GC–MS, SIFT-MS, and PTR-MS are the most accurate detection techniques for exhaled breath analysis with an analysis time of millisecond. These instruments require a fraction of ml of liquid or gas samples for monitoring. These classical instruments are expensive and require a trained person for handling, data analysis, and data interpretation. These instruments are not like any household devices and can only be available in hospitals and diagnostic clinics. This impedes the use of these instruments as breath analyzers on a day-to-day basis at our homes. One of the major goals of breath analysis is early detection of disease by regular health monitoring and for that to be possible the device used must be financially affordable for the common man, easy to use even for a layman and handheld.MO sensing materials: MO-based VOC sensors are cost-effective, easy to use, compact and capable of detecting several VOC biomarkers at ppm, ppb, and even, at ppt levels. Although most MO sensors exhibit excellent performance, a lack of specificity limits them to be used as a medical diagnostic tool. MO-based VOC sensors are also sensitive to humidity. Human breath contains almost saturated moisture which acts as a major cross-sensitive agent impeding the response of the sensor to target VOC molecules. Currently, thick film MO sensors are available in the market. The thick MO film-based sensors suffer high power consumption and poor sensitivity due to a low diffusion rate. MEMS-based sensor arrays can resolve the issue of power and size to some extent; however, they comprise other problems. The microsystems generally utilize moisture traps, which adsorb moisture along with the target gases. Humidity dependence of gas adsorption can significantly reduce the reliability and reproducibility of the pre-concentrator. Pre-concentration requires longer time; thereby, making real-time analysis difficult. Further, the small volume of pre-concentrator materials present in such microsystems might not be sufficient for the detection of trace gases. Selective and reversible pre-concentration remain challenges.3, and TiO2 with innovative carbon-based sensing materials such as GO, rGO, MWCNTs, AC, etc., the performance of the device can be improved in terms of sensitivity, LOD, response and recovery times towards the specific gaseous targets. Although most of the sensors show excellent performance, many of them fail to fulfill the requirement of medical diagnosis due to poor selective performance in a mixed gaseous environment. Even though GO, CNT, AC, etc., are considered novel VOC-sensing materials, they still require further study and improvement for commercialization.Carbon-based VOC sensors: By coupling MO, e.g., ZnO, NiO, MoOPolymer-based VOC sensors: Polymer-based VOC sensors are considered selective tools for breath biomarkers detection. Among various polymers, the MIP can be considered an excellent material to selectively detect VOC in very low-level concentrations of ppm/ppb. Although the MIP-based sensor provides a good selective response towards the target gas it suffers from the issue of rapid response time. The field is still growing; therefore, the commercialization of polymer-coated VOC sensors has not been explored yet.It has been reported previously that each human generates unique VOC profiles in their exhaled breath which can be utilized as biomarkers in order to monitor and diagnose various disease conditions. In the past decades, several sensing materials have been reported to achieve high selectivity and sensitivity in the sub-ppm range. In this review, a detailed literature survey of the recent progress of VOCs sensing materials and the key factors to improve the sensing response and to make it reliable for real-time utilization are provided. Each sensing material comprises some advantages and limitations which are briefly outlined at the end of each subheading. The new idea and approaches to improve the sensing performance of materials concerning adhesion, stability, and selectivity are also suggested.


Deferribacterota, Akkermansia, Muribaculaceae, Alistipes, and Clostridia VadinBB60. We also revealed that 218 amplicon sequence variants were significantly associated to the Cognitive Frailty Index. We speculated that some of them may guide the microbiome toward maladaptive and dysbiotic conditions, while others may compensate with changes toward adaptive and eubiotic conditions.Frailty during aging is an increasing problem associated with locomotor and cognitive decline, implicated in poor quality of life and adverse health consequences. Considering the microbiome–gut–brain axis, we investigated, in a longitudinal study, whether and how physiological aging affects gut microbiome composition in wild-type male mice, and if and how cognitive frailty is related to gut microbiome composition. To assess these points, we monitored mice during aging at five selected experimental time points, from adulthood to senescence. At all selected experimental times, we monitored cognitive performance using novel object recognition and emergence tests and measured the corresponding Cognitive Frailty Index. Parallelly, murine fecal samples were collected and analyzed to determine the respective alpha and beta diversities, as well as the relative abundance of different bacterial taxa. We demonstrated that physiological aging significantly affected the overall gut microbiome composition, as well as the relative abundance of specific bacterial taxa, including  Aging is a natural process affecting all living organisms, and it is characterized by a deterioration in physiological processes, leading to a higher probability to develop several disorders, i.e., cancer, metabolic, cardiovascular, and neurodegenerative diseases ,2. IndeeIn the elderly, frailty is defined as a clinical state with an increased vulnerability to stressors, thus exposing the organism to negative health-related outcomes, in the absence of recognized pathologies . FrailtyFurther investigations are mandatory to develop strategies to prevent and/or reverse frailty, cognitive impairment, and disability in the elderly .Akkermansiaceae, Lachnospiraceae, Rikenellaceae, and Ruminococcaceae, among others, has been described [The main cause of aging is usually considered the time-dependent increase in cellular damages . Among oescribed .In particular, inflammaging, a low-grade chronic inflammation during aging, was recently considered a trigger of the leaky gut and of the gut microbiome dysbiosis which characterize the elderly. According to this, the relative abundance of several microbes in the gut is dependent on cytokine and chemokine levels .Bacteroidetes and Firmicutes, followed by the Actinobacteria, Proteobacteria, and Verrucomicrobia phyla [In physiological conditions, the human gut is inhabited by mutualistic bacterial, fungal, archaeal, viral, and protozoal communities, which together form the gut microbiome ,18. A heia phyla . Even thia phyla . Indeed,ia phyla .This symbiotic and mutualistic superorganism, composed by the microbiome and host, has important effects on host health ,22,23. IHerein, we investigated the intersection of age, the gut microbiome, and cognitive frailty with a longitudinal study in a mouse model of physiological aging. First, we addressed the differences in the gut microbiome in alpha and beta diversities during physiological aging, also describing the changes in the relative abundance of specific bacterial taxa. In parallel, we monitored the Cognitive Frailty Index during aging by using spontaneous behavioral tests for evaluating recognition memory. Finally, we recognized the specific changes in microbiome composition due to the cognitive frailty, and we tried to describe them from a functional point of view.ad libitum. All experimental protocols and animal handling were carried out in strict conformity with European Council Directive 2010/63/EU and with the guidelines set by the Ethics Committee of Pavia University .Fourteen wild-type male mice (C57BL-6J) were obtained from Charles River, Italy. The mice were acclimated to their environmental conditions for one month before starting experiments, which were conducted in the Animal Care Facility at the University of Pavia. The mice were individually housed in plastic cages with an automatically controlled light-dark cycle: the dark period lasted from 07:00 to 19:00 and the light period was from 19:00 to 07:00. Water and food were furnished The murine cognitive performance was studied accessing the knowledge component of recognition memory , tested In detail, spontaneous behavioral tests in mice were performed at five experimental time points: T0 = 11, T1 = 14, T2 = 17, T3 = 20, and T4 = 21.5 months of age. Notably, T0 and T1 belonged to adulthood, T2 to reproductive senescence, while T3 and T4 occurred during senescence. At the same experimental times, animals were weighed, and the fecal stool samples were collected and stored at −80 °C. The experimental design is summarized here below in Total microbiota genomic DNA in the mice stools was extracted by using a QIAamp DNA stool mini kit  in accordance with the manufacturer’s instructions. DNA quantification was performed by using Qubit FluorometerTM . Libraries for 16S rDNA amplicons sequencing of the V3 and V4 regions were obtained by using PCR primers containing a barcode . Furthermore, for preparing the amplicons for the sequencing by MiSeq Illumina, we used the specific forward (V3 F: 5′-TCGTCGGCAGCGTCAGATGTGTATAAGAGACAG-3’) and reverse (V4 R: 5’-GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAG-3’) adapters. Finally, we performed the PCR analysis by using Bio-Rad MJ Mini Personal Thermal Cycle, and PCR amplicons were sequenced by MiSeq Illumina, relying on the BMR Genomics SRL of Padova.The raw paired-end FASTQ reads were imported into the Quantitative Insights Into Microbial Ecology 2 program   and demuThe resulting amplicon sequence variants (ASVs) with less than a 50× coverage were discarded from further analyses. The classification of the obtained ASVs was run using the feature-classifier plugin , implemeAll data are expressed as mean ± SEM.The analysis on the bacterial diversity, and the corresponding figures, was performed using the phyloseq R package . MicrobiBeta diversity was estimated with quantitative distance metrics using the diversity function in the phyloseq R package. We estimated the Bray-Curtis dissimilarity indices by sampling 10,000 reads per sample  based onVariance partitioning and significant Cognitive FI variation over time were determined by performing linear mixed effects (LME) models with the lme4 R package .Variance partitioning and significance of bacterial communities’ diversity variation over time and with respect to the Cognitive FI were determined by performing PERMANOVA test using the Adonis function implemented in the vegan R package. To overcome repeated measures, the variable that describes the mice was defined as strata.Canonical analysis of principal coordinates (CAP) was computed using the capscale function from the vegan R Package ,36. To hThe structure of microbial communities was explored by the non-multidimensional scaling (NMDS) ordination approach .p-value was <0.05.The DESeq2 R package  was usedThe metacoder R package was used to generate tree plots .All the graphical plots were generated by the ggplot2 R package . The metThe sequences generated in this study were deposited into the EMBL-EBI database in the PRJEB54046 project.We performed a longitudinal study on fourteen mice sampled five times (from T0 to time T4). The gut microbiome of those 70 samples was examined by sequencing of the bacterial 16S rRNA gene. After quality control analysis, sequences of 70 libraries resulted in 1,748,748 million sequence reads, ranging from 564 to 43,360 reads, with a median of 25,801 for a sample see . No readStool profiling revealed large microbiome composition differences over time during the mice lifespans. The alpha diversity  changed significantly during physiological aging, but Shannon diversity index (SDI) and Faith’s phylogenetic distance (PD) exhibited opposite behavior .p = 0.007) and between T2 vs. T3 ; on the contrary, any significant variation was determined between T0 and T1, as well as between T3 and T4 (There was a significant increase in terms of biodiversity observed with Shannon index between time T1 vs. T2 (Wilcoxon rank-sum test (WSRT), 3 and T4 . Supplemp = 0.0002). As regards the other time points, any significant change was measured  decreased from 13.86% at T0 to 3.7% at T2 and almost disappeared at T3 and T4. On the contrary, the Muribaculaceae (Bacteroidota phylum) appeared at T3 at a percentage of 5.3% and increased even more to 14.4% at T4.At the family and genus taxonomic levels, the greatest variations in microbiome composition were observed during aging B,C. The Parabacteroides  and Lachnospiraceae_NK4A136_group  which did not undergo statistical fluctuations  disappeared between adulthood and senescence  (from 0.043% at T0 to 4.2% at T4) (Alistipes (from 4.6% at T0 to 9.8% at T4) (Rikenellaceae family (Bacteroidota phylum). Furthermore, Muribaculaceae genera  appeared in senescence  and Clostridia UCG-014 genera   of the variation in beta diversity  of the Cognitive FI variation on the beta diversity of the microbiomes  in microbiome composition during the mice lifespan, confirming the beta diversity data .These two identified clusters corresponding to microbiome composition in adulthood and senescence were specifically composed of some bacterial ASVs which were decreasing or that were increasing with physiological aging and frailty. In the discussion section, we address this point with specific comments about those ASVs specifically linked to the Cognitive FI change during the aging process.Declarative memory is one of the main features of the human personality, which is the capability to remember an object, a person, or a place previously encountered. The maintenance of the recognition memory capability of declarative memory has a great impact on the elderly social life. Animal and human studies have evidenced the so-called gut–brain axis, in which a crucial role is played by the gut microbiome through a dynamic, complex bidirectional relationship with the host, thus identifying the microbiota–gut–brain axis ,42.Elderly people display a different gut microbiome profile compared to healthy adults for multifactorial factors such as lifestyle, nutrition, lower motor capabilities, and reduced immune system functions . Indeed,To achieve those goals, we monitored the gut microbiota composition and the Cognitive Frailty Index (FI) during aging . PreviouThe current longitudinal study demonstrated that the overall gut microbiome composition changed during the aging process. Nevertheless, as time went on, Cognitive FI increased, making it extremely difficult to isolate the effects of the two covariants (time and Cognitive FI) on overall gut microbiome composition . Despite this, we described a slight correlation between Cognitive FI and microbiomes (in terms of their taxonomic composition in the different mice examined), and this consideration was partly supported by the results of the CAP scale analysis. The not-significant effect of the LME model used for testing beta diversity in our experimental condition highlighted that it is not possible to use this variable as a predictor of total bacterial diversity. However, in a deeper taxonomic microbiome analysis, it was possible to identify some ASVs that specifically increased or decreased with Cognitive FI variation.During aging, gut microbiome alpha diversity measures gave opposite results: the Shannon index increased, whereas Faith’s PD index decreased, in senescence. Shannon alpha diversity is sensitive to both the richness and the evenness . These data are in agreement with a recent paper , describFaith’s PD index represents the number of phylogenetic tree units and their distance within a sample. Therefore, our results suggest that during the aging process, we were witnessing an increase in the number of ASVs that were phylogenetically more similar in senescence compared to adulthood. We may speculate that, despite the high number of species in the aged mice, the similarity to the taxa level accounts for a lower flexibility from a functional point of view compared to young animals. Confirmation that aging significantly affected the overall microbiota composition also came from the inter-individual variation, estimated through the beta diversity, by a non-multidimensional scaling (NMDS) ordination approach. In fact, we identified five clusters, sequentially expressed and each one specific for each experimental time, thus creating a large gap between the adult and senescent mice microbiome.Bacteoroidota and Firmicutes: their relative abundance and ratio remained relatively stable throughout the lifespan. Regarding subcore phyla during aging, Verrucomicrobia disappeared between 20–21.5 months, matched by total disappearance of the Akkermansiaceae family and Akkermansia genus. A change in Akkermansia’s relative abundance was associated with metabolic diseases  [Akkermansia, regulating the host immune response and reducing local inflammation, helps maintain the integrity of the gut barrier. Furthermore, Akkermansia influences the fat and sugar metabolism [Akkermansia could improve cognitive performance in two different preclinical models. In particular, Ou et al. (2020) [Akkermansia gavage, in addition to regulating the inflammation and sugar metabolism, significantly reduced the Aβ 40–42 levels in the cerebral cortex and improved the spatial and recognition memory of APP/PS1 mice, a model of Alzheimer’s disease (AD) [Akkermansia gavage restored cognitive impairment related to nonalcoholic steatohepatitis in rats [Akkermansiaciae, we recorded the appearance of Muribaculaceae (previously known as S24-7). The Muribaculaceae family is one of the major utilizers of mucus-derived monosaccharides in the gut, contributing to SCFA production [Muribaculaceae bacterial family was found as the dominant bacterial taxa in the gut of Spalax leucodon, an exceptional animal model of longevity [Muribaculaceae family in aged mice compared to young animals, and the anti-aging intervention has been shown to partially reverse the gut microbiota composition of elderly mice, also increasing the relative abundance of the Muribaculacea [Muribaculaceae relative abundance during physiological aging suggests a possible adaptive mechanism for the disappearance of the Akkermansia, trying to prevent a possible leaky gut. Next, we demonstrated a significant increase in the Rikenellaceae family during aging. Notably, in our samples, the Alistipes genus represented the entire Rikenellaceae family. Regarding this genus, conflicting data are reported [The core phyla during aging were obesity) ,46,47 buobesity) ,49,50. Atabolism  and Higatabolism  demonstr. (2020)  found thase (AD) . Higarzaase (AD)  demonstr in rats . In paraoduction , in partoduction ,55. The oduction . Indeed,ongevity . Previouaculacea ,57. We hreported , from a reported  to a prereported .Clostridia vadinBB60 between adulthood and senescence. Recently, Juckel and colleagues (2021) [Clostridia vadinBB60 group could be responsible for the neuroplasticity reduction in the central nervous system (CNS). Therefore, we supposed that the increase in Clostridia vadinBB60 could exert a detrimental effect on cognitive performance during aging.Furthermore, we found a significant increase in s (2021) , in patiParabacteroides, Clostridia UCG-014, Oscillibacter, Mucispirillum, Coprostanoligenes, Flavonifractor, Blautia, Monoglobus, Sedis, Lachnoclostridium, Oscillospiraceae_UCG_005, Marvinbryantia, Erysipelotrichaceae, Clostridium sensu stricto 1, Halomonas, Cutibacterium, Ruminococcaceae Candidatus Soleaferrea, Ruminococcaceae incertae sedis, Ruminococcaceae Paludicola, Ruminococcaceae Phocea, and Lachnospiraceae ASF356 significantly decreased in relation with the Cognitive FI increase. On the other hand, ASVs belonging to Ruminococcus, Colidextribacter, Anaerotruncus, Anaeroplasma, Peptococcaceae, Lactobacillus, and Ruminococcaceae incertae sedis increased in parallel to the Cognitive FI increment. We speculated that the increase in health-promoting or the decrease in pathobiont bacteria associated with the Cognitive FI increase could have an adaptive or compensatory role; on the contrary, the increase in unhealthy bacteria and a decrease in healthy bacteria with the FI increase could exert a dysbiotic role (The relative abundance of some ASVs was significantly associated with Cognitive FI changes. In particular, ASVs belonging to tic role .Furthermore, about the other ASVs which decreased or increased, not yet presently described in the present study, any previous literature data are available, to the best of our knowledge, regarding their relationship with both aging and cognitive frailty.In summary, our data demonstrated that aging significantly affected the overall gut microbiome composition in a complex way, increasing the number of ASVs and decreasing the phylogenetic distance among them. Beta diversity confirmed the presence of different clusters between adult and senescent mice. Cognitive frailty was associated with some specific changes in ASVs. We proposed that some of those ASV modifications could be a challenge in the eubiotic and adaptive direction and the opposite in the dysbiotic and maladaptive direction. The inverse correlation between Faith’s PD index and cognitive frailty suggests that cognitive decline is accompanied by a shrinkage of the gut microbiome functionality. Furthermore, this potential plasticity in the gut microbiome composition paves the way to the use of psychobiotics for prevention of cognitive frailty during aging .


Despite inhibition of renin-angiotensin system and sodium-glucose cotransporter type 2, persons with type 2 diabetes (T2D) and chronic kidney disease (CKD) remain on high cardiovascular (CV) residual risk.Overactivation of mineralocorticoid receptors plays a key role in the progression of renal and CV disease, mainly by promoting inflammation and fibrosis that is not targeted by traditional treatments.Finerenone is a nonsteroidal selective mineralocorticoid antagonist that decreases not only albuminuria, but also the risk of CKD progression, and CV risk in subjects with T2D and CKD.Persons with diabetes and chronic kidney disease (CKD) have a high residual risk of developing cardiovascular (CV) complications despite treatment with renin-angiotensin system blockers and sodium-glucose cotransporter type 2 inhibitors. Overactivation of mineralocorticoid receptors plays a key role in the progression of renal and CV disease, mainly by promoting inflammation and fibrosis. Finerenone is a nonsteroidal selective mineralocorticoid antagonist. Recent clinical trials, such as FIDELIO-DKD and FIGARO-DKD and the combined analysis FIDELITY have demonstrated that finerenone decreases albuminuria, risk of CKD progression, and CV risk in subjects with type 2 diabetes (T2D) and CKD. As a result, finerenone should thus be considered as part of a holistic approach to kidney and CV risk in persons with T2D and CKD. In this narrative review, the impact of finerenone treatment on the CV system in persons with type 2 diabetes and CKD is analyzed from a practical point of view. Indeed,Diabetes and CKD are independent risk factors for reduced survival. When both are present in the same person, the risk of mortality and of developing cardiovascular (CV) disease multiplies . IndividTraditionally, angiotensin-converting enzyme (ACE) inhibitors and angiotensin II receptor antagonists (ARBs) have been used to reduce the risk of kidney disease progression and CV complications in individuals with kidney disease and diabetes . UnfortuThe genesis and progression of CKD in persons with type 2 diabetes (T2D) involvings hemodynamic factors , metabolic factors (poor glycemic control), and overactivation of the mineralocorticoid receptor (MR) which promotes inflammation and fibrosis, ultimately leading to alterations at the cardiac, vascular and renal levels ,21. As dFinerenone is a new selective and non-steroidal MR antagonist indicated for the treatment of CKD in T2D persons . The ben2.In individuals with T2D and CKD there is an overarousal of the MR. The MR is expressed in numerous body cells including, among others, the distal and connecting convoluted tubule, macula densa, podocytes, mesangial cells, cardiomyocytes, vascular smooth muscle cells, endothelial cells, adipocytes, fibroblasts, and macrophages ,22.Through various mechanisms, overarousal of the MR increases inflammation and fibrosis, which translates into alterations at the renal level: alteration of sodium-potassium ATPase in the distal convoluted tubule and sodium retention, increased blood pressure, glomerulosclerosis and glomerular hypertrophy, mesangial proliferation, tubulointerstitial fibrosis; vascular level: endothelial dysfunction, increased arterial stiffness; and cardiac level: myocardial hypertrophy and fibrosis, ventricular remodelling, decreased coronary flow, myocardial ischemia, impaired cardiac function, arrhythmias .Ultimately, MR overarousal contributes to the progression of CKD , vascular damage, and CV complications   4,19–22,33.MR blockage produces coronary vasodilatation, increases nitric oxide, overactivation of mitochondrial pathways, and provides better perfusion of the left ventricle at the cardiac level. In addition, it improves endothelial function, decreases arterial stiffness, and reduces neointimal formation after vascular damage at the vascular level. Furthermore, MR blockage decreases albuminuria and enhances the preservation of renal function at the renal level ,34–36.In this manner, MR overactivation plays a central role in the development of CV and renal disease.3.MR antagonists (MRA) available to date are the steroid molecules, spironolactone and eplerenone, whose impact on renal progression or the development of CV complications has not been studied in persons with CKD and T2D despite their reducing proteinuria in the short term. Differences in the mechanisms of action of these drugs underlie differences in their efficacy and safety profiles which have facilitated a successful completion of phase 3 clinical trials with finerenone alone  4,20,2828,37–39.There are notable differences between steroidal MRAs (spironolactone and eplerenone) and non-steroidal MRAs (finerenone), depending on their structure  which isvia CYP3A4, it should not be co-administered with potent inhibitors or inducers of CYP3A4. The recommended target dose of finerenone is 20 mg once daily. The starting dose (10 mg or 20 mg od) depends on the glomerular filtration rate, and dose titration (10 mg or 20 mg od) on the serum potassium levels. It is recommended that renal function and serum potassium are measured at baseline, and 4 weeks after any change in dose of finerenone  associated with T2D , since inerenone  28]..via CYP34.Multiple preclinical and clinical studies have shown the renal and CV benefits of finerenone, as well as its safety.In ovariectomized mice with left ventricular diastolic dysfunction and preserved ejection fraction, finerenone improved left ventricular filling, coronary artery endothelium-dependent relaxation, mitochondrial ATP production, and exercise capacity . Experimp = 0.048) , and decreased the composite secondary endpoint  by 14%  (p = 0.016) [FIDELIO-DKD included approximately 5700 persons with T2DM and CKD who were receiving maximum tolerated doses of an ACE inhibitor or ARB and had a serum potassium concentration ≤ of 4.8 mmol/L  29]. Af. Af29]. 75–0.99) . The ben= 0.016) . AlthougThe FIGARO-DKD trial  includedFIDELITY  was a pr5.Individuals with T2D and CKD are at high risk of progressing to end-stage kidney disease, and even more so of developing CV complications, including atherosclerotic coronary artery disease and HF, or of dying prematurely, especially if there is prior CV disease . In thisRenin-angiotensin system blockers (ACE inhibitors or ARBs) and SGLT2 inhibitors have been shown to slow the progression of CKD and reduce CV risk in individuals with diabetes and CKD , but theThe use of finerenone in the treatment of persons with CKD and T2D is expected to be cost-effective by reducing the health system burden of CV and renal events. For example, hospitalizations for HF represent one of the most important components of healthcare costs and a year of dialysis costs €45,000 . For that reason, finerenone is expected to contribute to a reduction in the overall cost associated with CKD ,63.2, normal serum potassium concentration, and albuminuria  despite a maximum tolerated dose of a renin-angiotensin system blocker (grade A).Recommendations about the use of finerenone have been included in 2022 and 2023 guidelines. Thus, the 2023 American Diabetes Association (ADA) guideline recommends the use of finerenone for individuals with T2D and CKD with albuminuria treated with the maximum tolerated doses of ACE inhibitors/ARB, to improve cardiovascular outcomes and reduce the risk of CKD progression (level of recommendation A) . The 2026.Persons with T2D and CKD are at high risk of developing CV events . ClinicaAs a result, treatment with MR antagonists could be beneficial in this clinical setting. However, not all MR antagonists have demonstrated the same benefits or are equally safe ,28,37–39The evidence suggests that treatment of persons with T2D and CKD should consist of triple therapy with renin-angiotensin system blockade (ACE inhibitors or ARBs), SGLT2 inhibitors and finerenone, to slow the progression of CKD and reduce the risk of developing CV complications. For this reason, it is imperative that persons most likely to benefit from triple therapy are identified. Greater dissemination of clinical trial results and CV risk prevention guidelines and more widespread implementation of the assessment of albuminuria in persons with T2D and/or CKD should be performed. Although albuminuria is routinely assessed by nephrologists, other specialities, such as primary care, cardiology and endocrinology should also incorporate albuminuria measurement into their routine practice in the management of persons with diabetes or CKD. In addition, better coordination between the different care levels would be desirable. In addition, cardiologists are used to prescribing MRA. The better safety profile of finerenone and its lower risk of hyperkalemia should facilitate MRA prescription.2, normal serum potassium concentration, and albuminuria, the current indication of finerenone cannot be extended to the whole population with T2D and CKD. Therefore, new studies are warranted to clarify this point. Ongoing studies are addressing the role of triple therapy  in individuals with T2D and CKD  and the efficacy and safety of finerenone in subjects with CKD without diabetes .However, it should be emphasized that as FIDELIO-DKD and FIGARO-DKD included individuals with T2D and CKD with estimated glomerular filtration rate ≥25 mL/min/1.73 m7.Despite current treatments, individuals with CKD and T2D continue to have a significant CV risk. Albuminuria is a key and independent risk factor for CV and renal events. Determining albuminuria, together with the measurement of glomerular filtration rate, blood glucose, and LDL cholesterol, is the first step in risk stratification that allows for the design of a prevention strategy. Determination of albuminuria is part of the clinical practice of cardiology. Finerenone is a potent and selective non-steroidal MRA that has been shown to slow the progression of CKD and reduce the risk of developing CV complications in persons with T2D and CKD. As such, finerenone should be considered as one of the mainstays of treatment for persons with T2D and CKD, along with ACE inhibitors or ARBs, and SGLT2 inhibitors.


M.AH, female, 54 years, born and raised in São Paulo, with repetition epistaxis, nasal obstruction and hyposmia for two years. A solid tumor was found in her nose, coming from the middle meatus and partially obstructing her left nasal cavity.We performed a contrasted CT scan of her paranasal sinuses and a nasofibroscopy with biopsy. The material was then sent for a pathology exam and immunohistochemistry, which confirmed the diagnosis of a mesenchymal neoplasia originating from the smooth muscle.Surgery was performed under endoscopic view, with a 30° 4mm scope, when we resected the posterior portion of the left middle concha. The patient remained without nasal packing in the postoperative period, and did not have complications.A solid brownish tumor, measuring 4.0 × 2.0 × 2.0cm of regular borders.Under light microscopy we noticed proliferation of elongated cells of low histological aggressiveness, portraying a phenotype suggesting leiomyoma. Histology cross-sections showed a proliferation of smooth muscle fibers, without atypia, in longitudinal and cross-sectional bundles, separated by a mild fibro-conjunctive stroma, vascularized, covered by respiratory mucosa modified by unspecific inflammatory alterations.We used the strepto-avidine-biotine complex method /HRP, investigating antigens Vimentin, PS100, Actine ML, CD34 and Enolase.Positive ML Vimentin and Actine, PS 100, negative CD34 and negative Enolase.The histological pattern profile corresponds to that of a mesenchymal neoplasia originating from the smooth muscle.Leiomyomas are rare in the nasal cavity and in paranasal sinuses because there is very little smooth muscle in the nose, it is only present in the middle layer of blood vessels and in hair erection muscles. The origin is uncertain, it is likely that they should reach the smooth muscle on the vessel wall, the hair erection muscles or aberrant undifferentiated mesenchima.Smooth muscle tumors can be considered malignant even when the rate of mitoses is extremely low.High differentiation of tumor cells, minimum pleomorphism and the low degree of mitotic activity indicate that this is a benign tumor.Josephson et al.In the few reported cases of leiomyoma of the nasal cavity and paranasal sinuses, according to the literature review done by Van IngenThere is a certain predilection for females in a 3:1 ratio, with mean age of 50 years for women and 60 years for men.Less than 1% of leiomyomas happen in the head and neck.LlorenteAlthough rare, leiomyomas must be kept in mind for the differential diagnosis of benign intranasal tumors.