TR2022022096A2 - DEVELOPMENT OF A NEW ELECTROCHEMICAL SENSOR FOR THE DIAGNOSIS OF PARKINSON'S DISEASE FROM REAL SAMPLES - Google Patents
DEVELOPMENT OF A NEW ELECTROCHEMICAL SENSOR FOR THE DIAGNOSIS OF PARKINSON'S DISEASE FROM REAL SAMPLESInfo
- Publication number
- TR2022022096A2 TR2022022096A2 TR2022/022096 TR2022022096A2 TR 2022022096 A2 TR2022022096 A2 TR 2022022096A2 TR 2022/022096 TR2022/022096 TR 2022/022096 TR 2022022096 A2 TR2022022096 A2 TR 2022022096A2
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- Turkey
- Prior art keywords
- disease
- parkinson
- diagnosis
- samples
- sample
- Prior art date
Links
- 208000018737 Parkinson disease Diseases 0.000 title abstract description 13
- 238000003745 diagnosis Methods 0.000 title abstract description 13
- 238000011161 development Methods 0.000 title description 2
- 238000000034 method Methods 0.000 claims abstract description 8
- 239000011521 glass Substances 0.000 claims description 3
- 238000005259 measurement Methods 0.000 claims description 3
- 239000007921 spray Substances 0.000 claims description 2
- 238000005507 spraying Methods 0.000 claims description 2
- 238000000151 deposition Methods 0.000 claims 2
- 210000004243 sweat Anatomy 0.000 abstract description 16
- 201000010099 disease Diseases 0.000 abstract description 12
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 abstract description 12
- VYFYYTLLBUKUHU-UHFFFAOYSA-N dopamine Chemical compound NCCC1=CC=C(O)C(O)=C1 VYFYYTLLBUKUHU-UHFFFAOYSA-N 0.000 description 16
- 239000000523 sample Substances 0.000 description 11
- 229960003638 dopamine Drugs 0.000 description 8
- 239000010409 thin film Substances 0.000 description 7
- OIPILFWXSMYKGL-UHFFFAOYSA-N acetylcholine Chemical compound CC(=O)OCC[N+](C)(C)C OIPILFWXSMYKGL-UHFFFAOYSA-N 0.000 description 5
- 229960004373 acetylcholine Drugs 0.000 description 5
- 208000024891 symptom Diseases 0.000 description 5
- 238000001514 detection method Methods 0.000 description 3
- 238000013473 artificial intelligence Methods 0.000 description 2
- 239000008280 blood Substances 0.000 description 2
- 210000004369 blood Anatomy 0.000 description 2
- 238000003759 clinical diagnosis Methods 0.000 description 2
- 239000013068 control sample Substances 0.000 description 2
- 230000003291 dopaminomimetic effect Effects 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000004044 response Effects 0.000 description 2
- NLXLAEXVIDQMFP-UHFFFAOYSA-N Ammonium chloride Substances [NH4+].[Cl-] NLXLAEXVIDQMFP-UHFFFAOYSA-N 0.000 description 1
- VHUUQVKOLVNVRT-UHFFFAOYSA-N Ammonium hydroxide Chemical compound [NH4+].[OH-] VHUUQVKOLVNVRT-UHFFFAOYSA-N 0.000 description 1
- KXDHJXZQYSOELW-UHFFFAOYSA-N Carbamic acid Chemical group NC(O)=O KXDHJXZQYSOELW-UHFFFAOYSA-N 0.000 description 1
- 241001573498 Compacta Species 0.000 description 1
- 206010061818 Disease progression Diseases 0.000 description 1
- 229910021577 Iron(II) chloride Inorganic materials 0.000 description 1
- 235000011114 ammonium hydroxide Nutrition 0.000 description 1
- 238000004082 amperometric method Methods 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 230000006399 behavior Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000011088 calibration curve Methods 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 230000007850 degeneration Effects 0.000 description 1
- 230000008021 deposition Effects 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- 230000004069 differentiation Effects 0.000 description 1
- 230000005750 disease progression Effects 0.000 description 1
- 229940079593 drug Drugs 0.000 description 1
- 239000003814 drug Substances 0.000 description 1
- 238000002474 experimental method Methods 0.000 description 1
- 239000010408 film Substances 0.000 description 1
- 238000004128 high performance liquid chromatography Methods 0.000 description 1
- 230000001771 impaired effect Effects 0.000 description 1
- NMCUIPGRVMDVDB-UHFFFAOYSA-L iron dichloride Chemical compound Cl[Fe]Cl NMCUIPGRVMDVDB-UHFFFAOYSA-L 0.000 description 1
- 238000004895 liquid chromatography mass spectrometry Methods 0.000 description 1
- 239000004579 marble Substances 0.000 description 1
- 230000000626 neurodegenerative effect Effects 0.000 description 1
- 239000013610 patient sample Substances 0.000 description 1
- 210000002381 plasma Anatomy 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 210000002966 serum Anatomy 0.000 description 1
- 239000000377 silicon dioxide Substances 0.000 description 1
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 1
- 239000000126 substance Substances 0.000 description 1
- 210000003523 substantia nigra Anatomy 0.000 description 1
- 238000003786 synthesis reaction Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 description 1
- 230000003442 weekly effect Effects 0.000 description 1
Abstract
Bu buluş; hastalıklar esnasında fizyolojik numunlerden alınan örneklerde hastalık teşhisi yapılmakta olup, Parkinson hastalığının bilinen herhangi bir numuneden teşhisi mevcut değildir. Patent önerimizde parkinson hastalarının ter numunelerinden hastalığın teşhisine yönelik sensör geliştirilmesi hakkında kullanılacak bir yöntem ile ilgilidir.This invention; Disease diagnosis is made in samples taken from physiological samples during diseases, and there is no diagnosis of Parkinson's disease from any known sample. Our patent proposal is about a method to be used to develop sensors for the diagnosis of the disease from sweat samples of Parkinson's patients.
Description
TARIFNAME GERÇEK NUMUNELERDEN PARKINSON HASTALIGININ TESHISINE YÖNELIK YENI BIR ELEKTROKIMYASAL SENSÖR GELISTIRILMESI TeknikAlan Bu bulus; hastaliklar esnasinda fizyolojik numunlerden alinan örneklerde hastalik teshisi yapilmaktadir. Ancak Parkinson hastaliginin bilinen herhangi bir numuneden teshisi yoktur. Patent önerimizde parkinson hastalarinin ter numunelerinden hastaligin teshisine yönelik sensör gelistirilmesi hakkinda kullanilacak bir yöntem ile ilgilidir. Teknigin Bilinen Durumu Parkinson hastaligi genellikle 60 yas üzerindeki bireylerde görülen ve bu hastaliga yakalanan bireylere nörodejeneratif hasar vererek etkileyen hastaliktir. Parkinson hastaliginin teshisine yönelik yapilan tespitlerin çogu bir takim deneyler sonucu elde edilen veriler ile saglanmaktadir. Bunlar arasinda semptomlarin belirlenmesi ve ayak tabanlarina takilarak toplanan kuvvet sensörlerinden elde edilen verilere dayanmaktadir. Parkinson hastaliginin klinik teshisi, substantia nigra pars compacta'nin dejenerasyonunun bir sonucu olan dopamin eksikligi ile ilgili özelliklerin tanimlanmasina dayanir. Ayrica, non-dopaminerjik ve non-motor semptomlar bazen tanidan önce mevcuttur ve neredeyse kaçinilmaz olarak hastaligin ilerlemesi ile ortaya çikar. Motor olmayan semptomlar ilerlemis Parkinson hastaliginin klinik tablosuna hakimdir ve ciddi sakatliga, bozulmus yasam kalitesine ve kisalan yasam beklentisine katkida bulunur. Tedavinin mevcut oldugu hastaligin dopaminerjik semptomlarinin aksine, motor olmayan semptomlar genellikle yeterince taninmaz ve yetersiz bir sekilde tedavi Parkinson hastaligi için su anda mevcut olan ana teshis yöntemleri, doktorlar tarafindan geleneksel ampirik teshis ve hastaligin teshisine yardimci olmak için yapay zekanin kullanilmasidir. Ancak hekimler tarafindan tani konulmasi zaman alici ve emek yogun bir yaklasim olup, haftalik bir poliklinikte tani konulabilen hasta sayisi doktorlar için sinirli iken, hastalar için çogu zaman taniyi desteklemek için çok sayida test gerekmektedir. Alanda yapilmis bazi arastirmalar vardir. Ancak hepsi daha çok el ve ayak davranislarinin farklilasmasinin izlenmesi ve bunun yapay zeka ile tespitine yöneliktir. Ayrica hastaligin baslangicindan itibaren de sürekli bir ilaç kullanimina bagli kan düzeyinde dopamin seviyesinin sabit tutulmasi amaçlanmaktadir. Hastaligin seyrinde dopamin seviyesi tespitine yönelik de herhangi bir sensör gelistirilmemistir. Ancak alinan vücut örneklerinde (Kan, serum, plazma vs) HPLC, LC-MS gibi kormatografik cihazla ile ancak tespiti mümkün olabilmektedir. Bu bulus, fizyolojik olarak kolayca temin edilebilecek ter numunesinden 10 uL gibi küçük miktarinin elektrot yüzeyine damlatilarak kolayca akim degisimine dayanan sensör sistemiyle tespit edilebilmesi mümkün hale gelecektir. Bu yönüyle yapilacak sensör hastalarin yatak basinda kullanimi yöntemi ile ilgilidir. Bulusun Kisa Açiklamasi Bu bulus, parkinson hastaliginin teshisinde yasanan güçlükleri ortadan kaldirarak ter numunelerinden basit, kolay ve yatak basi kullanimi mümkün kilacak bir sensör önerisi sunulmaktadir. uL gibi çok düsük hacimdeki ter numunelerinin kullanimi ile akimdaki degisimin takibi sonucunda elde edilecek olan kalibrasyon egri denklemi ile bilinmeyen numunedeki dopamine ve asetil kolin miktarindaki degisim tespiti yapilacaktir. Parkinson hastaliginin kisinin kendisinin veya hekimlerin kolayca klinikte tespinin yapilmasi ile ilgilidir. Bulusun Detayli Açiklamasi Bu bulus; amperometrik yöntemle bireylerden alinan 10 mL ter numunesine sabit akim uygulanmasi sonucundaki degisim tespit edilerek miktari bilinen dopamin ve asetil kolin maddelerinin akim-Zaman grafiklerinden elde edilen standart grafiklerinn denkleminden yararlanarak hasta numunelerinin içerigindeki dopamin ve asetil kolin miktari tespitine gidilecektir. Henüz kIinikte teshisi olmayan Parkinson hastaliginin teshisi gerçeklestirilecektir. Bu bulus kapsaminda, primer karbamat grubu ihtiva eden moleküllerin yeni bir yöntemle sentezlerinin; Parkinson hastaliginin teshisinde cam silika yüzeyinde SILAR yöntemi ile olusturulan FeO ince film tabakalari kullanilacaktir. Bu amaçla FeCl2 çözeltisine batirilan cam plaka ardindan amonyak çözeltisine batirilmis ve son asamada saf su ile yikanmistir. 1. Döngü tamamlandiktan sonra, 2. Döngüye baslanmis ve tekrarlanmistir. Yüzeyde FeO NP'lerinin birikmesi tamamlanincaya kadar bu islem tekrarlanmistir. Islem basamaklari Sekil 1'de özetlenmistir. Ayrica USP- Sprey püskürtme yöntemi ile de FeO ince film tabakalri olusturulmustur. Dopamin miktari, asetil kolin miktari ve ter numunelerindeki dopamin ve asetil kolin miktarina iliskin akim degisimi amperometre kullanilarak belirlenmesidir. Bu amaçla kullanilan cihaza özel yaptirilan mermer yüzeyine yerlestirilen FeO ince tabaka ince filmlere her defasinda 10 uL numune damlatilmis ve Keithley 2002 8.5 Digit Multimeter with Scanning, USA cihazi ile uygulanan sabit akim sonucu bagli bulunan bilgisayar ekranindan akim degisimi takip edilmistir. Sonuçlar Akim-Zaman grafigi ile verilmistir. Numune ilave edilmeden ve edildikten sonra ölçümler alinmis ve degisimler asagidaki formül kullanilarak hesaplanmistir: S: %Algilama (Sensivity) etmektedir. Öncelikle kontak yapilan bu filme ter numunesi damlatilmadan önce sabit gerilim uygulanarak yaklasik 150 s boyunca sabit gerilim uygulanarak numuneden geçen akimin degisimi zamana bagli olarak ölçülmüstür. Ardindan FeO nanoyapili ince film yapilarin üzerine 10 uL ter numuneleri esit olacak sekilde damlatilip 150 sn süre ile takip edilerek akimdaki degisim sayesinde ter algilama analizlerinin yapilmasidir. Ter numunelerinin düsük konsantrasyondan yüksek konsantrasyona dogru siralanmis bes farkli konsantrasyondaki numune için elde edilen ölçümler alinmasi hakkindadir. Kontrol numunesinden elde edilen akim degisim grafigi ile Parkinson hastalarinin grafigi karsilastirildiginda hem sekilsel hemde algilanan akim degerlerinde farklilik oldugu belirlenmesidir. Nanoyapili FeO ince film yapisina 1 mg/mL"den 0,0001 mg/mL konsantrasyona giderken 10 uL gibi küçük miktarlarda ter numunesinin damlatilmasi neticesinde akim degerinde artis oldugu görülürken algilama performansinin da önemli ölçüde etkilendigi ve ter konsantrasyonunun artisina bagli olarak verdigi tepkinin dogru orantili olarak arttigi belirlenmistir. Nano yapili FeO ince film yapisina 1 - 0,0001 mg/mL konsantrasyonundaki saglikli kisi ter numunesinin damlatilmasi ile olusan zamana bagli olarak numunenin üzerinden geçen akimin degisim grafigi Nano yapili FeO ince film yapisina 1 -0.0001 mg/mL konsantrasyonundaki Parkinson hastalarina ait ter numuneleri (A: 1. Parkinson hastasi B:2. Parkinson hastasi) damlatilmasi ile olusan zamana bagli olarak numunenin üzerinden geçen akimin degisim grafigi Kontrol numunesinden elde edilen akim degisim grafigi ile Parkinson hastalarinin grafigi karsilastirildiginda hem sekilsel hemde algilanan akim degerlerinde farklilik oldugu belirlenmistir. Nanoyapili FeO ince film yapisina 1 mg/mL"den 0,0001 mg/mL konsantrasyona giderken 10 pL gibi küçük miktarlarda ter numunesinin damlatilmasi neticesinde akim degerinde artis oldugu görülürken algilama performansinin da önemli ölçüde etkilendigi ve ter konsantrasyonunun artisina bagli olarak verdigi tepkinin dogru orantili olarak arttigi hakkindadir. TR TR DESCRIPTION DEVELOPMENT OF A NEW ELECTROCHEMICAL SENSOR FOR DIAGNOSING PARKINSON'S DISEASE FROM REAL SAMPLES Technical Field This invention; During diseases, diseases are diagnosed from samples taken from physiological samples. However, there is no diagnosis of Parkinson's disease from any known sample. Our patent proposal is about a method to be used to develop sensors for the diagnosis of the disease from sweat samples of Parkinson's patients. State of the Art Parkinson's disease is a disease that is generally seen in individuals over the age of 60 and affects individuals suffering from this disease by causing neurodegenerative damage. Most of the findings for the diagnosis of Parkinson's disease are provided by data obtained as a result of a number of experiments. Among these, the determination of symptoms is based on data obtained from force sensors collected by attaching them to the soles of the feet. Clinical diagnosis of Parkinson's disease is based on the identification of features related to dopamine deficiency, which is a result of degeneration of the substantia nigra pars compacta. Furthermore, non-dopaminergic and non-motor symptoms are sometimes present before diagnosis and almost inevitably occur with disease progression. Non-motor symptoms dominate the clinical picture of advanced Parkinson's disease and contribute to severe disability, impaired quality of life, and shortened life expectancy. Unlike the dopaminergic symptoms of the disease, for which treatment is available, non-motor symptoms are often under-recognized and inadequately treated. The main diagnostic methods currently available for Parkinson's disease are traditional empirical diagnosis by doctors and the use of artificial intelligence to assist in diagnosing the disease. However, diagnosis by physicians is a time-consuming and labor-intensive approach, and while the number of patients that can be diagnosed in a weekly outpatient clinic is limited for doctors, many tests are often required for patients to support the diagnosis. There are some studies done in the field. However, all of them are more aimed at monitoring the differentiation of hand and foot behaviors and detecting this with artificial intelligence. In addition, it is aimed to keep the dopamine level in the blood constant due to continuous drug use from the beginning of the disease. No sensors have been developed to detect dopamine levels in the course of the disease. However, it is only possible to detect it in body samples (blood, serum, plasma, etc.) using chromatographic devices such as HPLC, LC-MS. This invention will make it possible to detect a small amount of sweat sample, such as 10 uL, which can be easily obtained physiologically, by dropping it onto the electrode surface with a sensor system based on current change. This aspect is related to the method of using the sensor at the bedside of patients. Brief Description of the Invention: This invention proposes a sensor that will eliminate the difficulties experienced in the diagnosis of Parkinson's disease and enable simple, easy and bedside use from sweat samples. By using very low volume sweat samples such as uL, the change in the amount of dopamine and acetylcholine in the unknown sample will be determined with the calibration curve equation that will be obtained as a result of monitoring the change in flow. It is about the easy clinical diagnosis of Parkinson's disease by the person himself or by the physicians. Detailed Description of the Invention This invention; The change as a result of applying a constant current to a 10 mL sweat sample taken from individuals with the amperometric method will be determined and the amount of dopamine and acetylcholine in the patient samples will be determined by using the equation of standard graphs obtained from the flow-time graphs of dopamine and acetylcholine substances of known amounts. Parkinson's disease, which has not yet been diagnosed in the clinic, will be diagnosed. Within the scope of this invention, the synthesis of molecules containing primary carbamate groups with a new method; FeO thin film layers created by the SILAR method on the glass-silica surface will be used in the diagnosis of Parkinson's disease. For this purpose, the glass plate was dipped in FeCl2 solution, then dipped in ammonia solution and washed with pure water in the last stage. After the 1st Cycle was completed, the 2nd Cycle was started and repeated. This process was repeated until the deposition of FeO NPs on the surface was completed. The process steps are summarized in Figure 1. Additionally, FeO thin film layers were formed by the USP-Spray spraying method. The amount of dopamine, the amount of acetylcholine and the current change related to the amount of dopamine and acetylcholine in sweat samples are determined using an amperometer. 10 uL samples were dropped each time onto the FeO thin films placed on the marble surface, which was specially made for the device used for this purpose, and the current change was monitored on the connected computer screen as a result of the constant current applied with the Keithley 2002 8.5 Digit Multimeter with Scanning, USA device. The results are given with a Current-Time graph. Measurements were taken before and after adding the sample and the changes were calculated using the following formula: S: %Sensitivity. First of all, before dropping the sweat sample onto this contact film, a constant voltage was applied for approximately 150 s, and the change in the current passing through the sample was measured depending on time. Then, 10 uL sweat samples are dropped evenly onto the FeO nanostructured thin film structures and followed for 150 seconds to perform sweat detection analyzes thanks to the change in current. It is about taking measurements of sweat samples obtained for samples of five different concentrations, ranked from low concentration to high concentration. When the flow change graph obtained from the control sample is compared with the graph of Parkinson's patients, it is determined that there is a difference in both the figural and perceived current values. While it was observed that there was an increase in the current value as a result of dropping small amounts of sweat sample such as 10 uL into the nanostructured FeO thin film structure while going from 1 mg/mL to 0.0001 mg/mL concentration, the detection performance was also significantly affected and the response depending on the increase in sweat concentration was directly proportional. The change graph of the current passing over the sample depending on time created by dropping a healthy person's sweat sample at a concentration of 1 - 0.0001 mg/mL onto the nano-structured FeO thin film structure. When the current change graph obtained from the control sample was compared with the graph of Parkinson's patients, it was determined that there was a difference in both the pictorial and perceived current values. While it was observed that there was an increase in the current value as a result of dropping small amounts of sweat sample such as 10 pL into the nanostructured FeO thin film structure while going from 1 mg/mL to 0.0001 mg/mL concentration, the detection performance was also significantly affected and the response depending on the increase in sweat concentration was directly proportional. It's about increasing. TR TR
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| Publication Number | Publication Date |
|---|---|
| TR2022022096A2 true TR2022022096A2 (en) | 2023-05-22 |
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