Betta splendens) was studied for 96 h. The LC50  for 96 h for adult bettas to ammonia-N and nitrite-N was 123.4 mM  and 24.6 mM  respectively. Exposure to 90 mM ammonia did not affect ammonia and urea excretion rates in bettas. There was no significant difference in values between control and ammonia-loaded (90 mM ammonia) individuals in either brain or liver activities of glutamine synthase, while plasma ammonia levels slightly increased. It appears unlikely that ammonia was converted to urea or amino acids for detoxification. Sublethal nitrite (24.6 mM nitrite) affected plasma nitrite, methemoglobin and hemoglobin. Plasma nitrite values remained much lower than ambient concentrations. Betta has a labyrinth organ and can breathe air. Bettas may temporarily reduce the entry of ammonia and nitrite into the body by increasing the rate of air respiration and reducing the contribution of the gill epithelium, which is highly permeable to these nitrogenous pollutants.The acute toxicity and sublethal effects of ammonia and nitrite on the air-beathing Siamese fighting fish, betta ( Betta splendens), native to Thailand, is an ornamental fish with a multicolored body and long, ribbon-like fins. Over the centuries, bettas have been bred for gambling purposes by making two males fight against each other, and to make their appearance more attractive, resulting in a variety of bettas [2−), are toxic to fish.The Siamese fighting fish, betta  and ammonium ions (NH4+). In this paper, we distinguish between NH3 and NH4+ and refer to the sum of NH3 and NH4+ as ammonia. The rate at which ammonia is ionized is highly dependent on temperature and pH. The pKa value, which indicates the pH at which half of the ammonia is NH4+ and half is NH3, is about 9–10. Their toxicities differ, with NH3 being 300–400 times more toxic compared to NH4+ [3, and they keep ammonia levels in the body low [3 flows into the body and accumulates due to an inverse diffusion gradient [Ammonia is mainly produced when animals break down proteins and amino acids. Ammonia is ionized in water and exists in two forms: un-ionized ammonia  were obtained from a local pet store in Wakayama Prefecture, Japan. The fish were held individually in 1000 mL glass beakers with 600 mL of aerated Wakayama tap water  at 25 ± 0.5°C in for at least two weeks prior to experimentation under a constant photoperiod of 12:12 L:D. Water was changed twice a week. Fish were supplied a commercial diet  once every day to satiation. Food was withheld for 2 days before and during the experiments. Because bettas are air-breathing fish, no aeration was used during the acclimation and experiment period. White paper partitions were placed between the containers so that no other fish could be seen.Male Fish (n = 144) were subjected to different concentrations of ammonia or nitrite for 96 h to determine the lethal concentrations (LC50). For each treatment, eight fish were placed in clean containers individually with 600 mL test water under the constant photoperiod. A clear plastic sheet was placed over the container to prevent evaporation during processing.4Cl: 60, 80, 90, 100, 110, 120, 130, 140, and 150 mM. In the ammonia tolerance experiment, water and containers were changed every 24 h by gently transferring fish with a fish net to prevent significant decrease in ammonia concentration due to volatilization. For nitrite tolerance, fish were exposed to nine concentrations of NaNO2: 10, 15, 20, 22, 24, 25, 26, 28, and 30 mM. During the experiment, the same water in the container was used for 96 h.For ammonia tolerance, fish were exposed to nine concentrations of NHFish were monitored for mortality at least 3 times daily. Water samples (3 mL) were withdrawn with a pipette to determine the concentrations of ammonia/nitrite. All water samples were frozen at -20°C until analysis. The fish were weighed after the experiment.3 + NH4+). The corresponding fractions of un-ionized ammonia (NH3) and ammonium (NH4+) were calculated in accordance with the Henderson–Hasselbalch equation:In the present study, ammonia was measured as total ammonia  or 90 mM ammonia dissolved in FW for 96 h. Water pH was measured at 0, 24, 48, 72, and 96 h. External water was collected and frozen for ammonia and urea analysis at 0, 24, 48, 72, and 96 h. After measuring pH and taking water samples, the external water and the containers were changed daily. After 96 h exposure, the fish were anesthetized by immersion in tricaine methanesulphonate , rinsed with clean water, dried with a clean paper towel to removed water on the body surface, and weighed. Blood samples were collected by tail ablation with a scalpel and hematocrit tubes, then transferred into centrifuge tubes and plasma samples were obtained by centrifugation at 9000 g for 2 min. The liver and brain were removed. The plasma and tissues were immediately frozen in liquid nitrogen and stored at -80°C until further analyses.Ammonia in water samples was determined by the indophenol blue method . Plasma 2HPO4, 10 mM HEPES, 0.5 mM EDTA, 1 mM dithiothreitol, 50% glycerol adjusted with NaOH to pH 7.5 at 24°C) using a BioMasher . Homogenates were centrifuged at 8,000 g for 20 min at 4°C. The supernatant was used for assaying the activity of GS by previously described methods [For determination of activity of glutamine synthetase , tissues were homogenized on ice in 20–50 volumes of homogenization buffer , rinsed with clean water, dried with paper towel and weighed. Blood samples were collected by tail ablation with a scalpel and hematocrit tubes. Hematological analyses were performed immediately after blood sampling. For plasma nitrite, whole blood was transferred into centrifuge tubes and plasma samples were obtained by centrifugation at 9000 g for 2 min and stored at -80°C until further analyses.Fish were placed individually in containers with 600 mL of FW or 24.6 mM NaNOFor hematological analyses, hematocrit (Hct) and hemoglobin (Hb) concentrations were determined using whole blood. The Hct value was determined using a capillary hematocrit tube and hematocrit centrifuge . The Hb concentration was measured using the cyanmethemoglobin technique by Drabkin’s reagent . Methemglobin (MetHb) in the blood of fish was measured using the Evelyn and Malloy method , 27. PlaAll data are given as means ± S.E. . Probit analysis was used to evaluate LC50 (SPSS. IBM 25). An independent t-test was used to determine significance. For all analyses, P < 0.05 was considered significant.3-N was 551.2 µM (7.7 mg/L).There was no mortality for fish in concentrations of nitrite up to 20 mM and ammonia up to 90 mM during 96 h of the experiment. The 96 h LC50 value of nitrite-N was 24.6 mM (343.6 mg/L) Table . The 96 The control fish excreted nitrogen waste mostly as ammonia, with urea excretion accounting for less than 23% of total nitrogen excretion (ammonia-N + urea-N) Fig. . Bettas Plasma ammonia levels and brain and liver glutamine synthase (GS) activity levels in control and ammonia-loaded individuals are shown in Table As shown in Table 3-N was 123.4 mM (1.7 g/L) and 551.2 µM (7.7 mg /L), respectively. The 96 h LC50 for freshwater fish is generally in the range of 0.068-2.0 mg/L NH3 [Periophthalmodon schlosseri, showed a 96-h LC50 of 536 µM for NH3 [Heteropneustes fossilis was also reported to be able to survive at 75 mM NH4Cl (pH 7.2) for 4 weeks [The 96 h LC50 for bettas for ammonia-N and NHmg/L NH3 , indicatmg/L NH3 . This is for NH3 . The air 4 weeks .Monopterus albus and the weather loach Misgurnus anguillicaudatus, which may accumulate high concentrations of endogenous ammonia in the body, such as in the muscle and liver, and in plasma during exposure to air, when ammonia excretion is limited [Bettas accumulated ammonia under ammonia-loaded conditions, with the plasma ammonia content of bettas increasing 1.7-fold under ammonia exposure. On the other hand, urea excretion did not change, indicating that bettas do not appear to convert ammonia into urea for emission in short periods such as 96 h. The activity of glutamine synthase was also unchanged in this study, and it is unlikely that ammonia is actively converted to glutamine for detoxification under acute ammonia loading. This is similar to two other air-breathing fish, the swamp eel  limited , 34.2− /L [Micropterus treculi) 187.6 mg NO2-N/L [Lepomis cyanellus) 526.8 mg NO2−/L (160.1 mg NO2-N/L) [Micropteus salmoides) 140.2 mg NO2-N/L [Chitala ornata) [Monopterus albus) [The 96 h LC50 of nitrite-N for bettas was 24.6 mM (343.6 mg /L). The sensitivity of fish to nitrite also varies widely among species, and its toxicity is known to be affected by a variety of factors, including exposure time, fish size, ionic composition in the water, and temperature , 35, 36.2− /L , however NO2-N/L , Green sNO2-N/L) , and Lar NO2-N/L  have not ornata)  and 31 ms albus) .When exposed to nitrite, freshwater fish take up nitrite mainly from gill chloride cells and may accumulate high concentrations in plasma . In someNitrite entering the bloodstream renders the divalent iron ions in hemoglobin unable to transport oxygen, as they are oxidized by nitrite to trivalent iron ions , 19, 37.Under ammonia and nitrite exposure for 96 h, although ammonia and nitrite in plasma in bettas increased significantly, the values were kept much lower than ambient concentrations. Betta has a labyrinth organ and can breathe air. Bettas might temporarily reduce the entry of ammonia and nitrite into the body by reducing the contribution of the gill epithelium, which is highly permeable to ammonia and nitrite, and by increasing the proportion of air respiration. This may be why they can tolerate extremely high concentrations.In nature, ammonia and nitrite in water are usually converted by nitrification by microorganisms and rarely accumulate in high concentrations. How did bettas develop this high tolerance? Bettas are highly territorial, and if males are kept together in a small tank, they will fight violently, so they must be kept separately. In Thailand, where betta breeding is popular, bettas are often kept individually in half-pint liquor bottles with a cut at the shoulder to allow for water drainage, water changes are done directly into the bottles, and they are given food and raised in these bottles until shipment . They ar


Zanthoxylum pipritum) is sanshool, which is easily oxidized and decomposed. We have previously reported several sanshool stabilizers, such as α-tocopherol (α-Toc). Sansho pericarp powder treated with middle-chain triglycerides (MCTs) can be used to obtain extracts containing hydroxy-α-sanshool (HαS). Although HαS is stabilized when α-Toc is added to the MCT extracts, the loss of HαS is accelerated when it is mixed with a powder such as lactose. The separation of α-Toc from sanshools was thought to inevitably lead to their oxidation. Therefore, using sansho pericarp MCT extracts with or without α-Toc, oil/water (o/w) emulsions were prepared by adding a surfactant, glycerin, and water to these extracts. In both emulsions, HαS was stable in accelerated tests at 50 °C. However, when lactose powder was added to the emulsions and an accelerated test was performed, HαS in the emulsion containing α-Toc was stable, but HαS in the emulsion without α-Toc was unstable. These results highlight the importance of maintaining the close proximity of HαS and α-Toc in the emulsion. The stabilization of sanshools using emulsion technology can facilitate the production of various processed beverages, foods, cosmetics, and pharmaceuticals containing Japanese pepper.The pungent component of sansho (Japanese pepper,  Zanthoxylum piperitum) have been used since ancient times as a traditional remedy in Japan . Sansho has a long history as a spice, and its special refreshing aroma and taste have attracted Japanese people. In addition to being used in Japanese cuisine, it is also used as a new flavor in French cuisine and chocolate, and its adoption is expected to increase in the future. In Japan, in preparations using sansho as a raw material, its fruits and pericarps are pulverized and/or extracted. However, while dried sansho fruits and pericarps have relatively stable taste, aroma, color, and other substances, powdered sansho pericarps rapidly lose their flavor, necessitating methods for preventing decomposition and stabilizing the spice components of sansho.The fruits of Japanese pepper   was calculated to obtain the residual rate (%).A Shimadzu LC-2010 instrument was used for the HPLC analysis. All samples were injected into an InertSustainSwift C18 4.6 × 250 mm column . The column was eluted with a mixture of solvents A (30% acetonitrile) and B (80% acetonitrile) at a flow rate of 1.0 mL/min. The conditions were as follows: 0 min, solvent B = 0% → 35 min, solvent B = 45% → 50 min, solvent B = 100% → 51 min, solvent B = 0% → 55 min, solvent B = 0%. All analyses were conducted at 40 ℃ and monitored using UV absorption at 270 nm.n = 3) under the conditions described above. HαS was eluted with a single sharp peak around the retention time of 25.4 min. In this concentration range, a linear relationship was obtained between the HαS concentration and the HPLC peak areas. This calibration curve was used to determine the HαS content in a sample. The experiment was also performed three times on different days, but no daily difference was found. The LOD of this method was 0.00163 µmole/mL.Several methods for the determination of sanshools based on reversed-phase HPLC analysis have been reported ,13. We mA particle size analyzer  was used to measure the particle size of the emulsions.t-test. A value of p < 0.05 was considered statistically significant.All data are expressed as the mean ± standard deviation (SD) values for each group. The statistical analysis was performed using a one-way analysis of variance with Student’s Zanthoxylum. Therefore, we investigated the extraction efficiency of various sanshool solvents. Solvents with different log P oct/wat values were selected, and the extraction efficiencies of these solvents were compared. The following solvents were used: water, methanol (−0.74), ethanol (−0.32), 2-propanol (0.8), acetone (−0.24), ethyl acetate (0.73), chloroform (1.97), n-hexane (3.9), rapeseed oil, and MCTs. The values in parentheses are the log P oct/wat values, which are a measure of lipophilicity or hydrophobicity. The amount of HαS in the ethanol extract was 25.0 ± 0.36 mg/mL (mean ± SD). Taking this amount as 100, the amount of HαS extracted with each solvent is shown as a relative value  was prepared, and this powdered oil is abbreviated as 1:3. If the ratio of lactose to emulsion is less than 1:3, it does not turn into a powder, but becomes mushy or sticky. We also prepared 1:10 and 1:21 powdered oil. As shown in Oil powder (powdered oil) is widely used in the food, pharmaceutical, and cosmetic industries. Therefore, we prepared a powder by mixing the MCT extracts with an excipient and examined the stability of HαS in the powder. Various excipients  were examined, but there was little difference in the results. With sugar, we tried maltose and sucrose in addition to lactose. It became clear that none of the sugars were problematic for use in the powder. Lactose has no sweet taste, so we thought it would be appropriate for powdered oils. A powder with an MCT extracts/lactose ratio of 1:3  as a surfactant. This emulsion containing α-Toc was named the BT emulsion, and the emulsion without it was named the BN emulsion. Each emulsion was mixed with the same amount of water or buffer solutions of pH 2.2 to 7 and incubated at 50 °C. The state of emulsification did not change significantly during the incubation time. As shown in Preventing oxidation and avoiding acidic conditions is an important requirement to stabilize sanshools ,7. SeverPhysical measures to prevent oxidation are also important. Vegetable oil microencapsulation has recently gained prominence in this regard ,10,15. MN-alkylamides widely occur in 25 plant families and have been used in foods [(Capsicum annuum L.), and piperine, present in black pepper (Piper nigrum L.), are also N-alkylamides [Echinacea, are also N-alkylamides and have been reported to be highly unstable substances. Echinacea is a popular herbal medicine in Western countries that has been used to treat colds and influenza [Echinacea have been useful or ineffective. The stabilization techniques used in this study may be useful in solving these problems.It has been reported that in foods . Capsaicylamides . These sylamides  and actiylamides . Therefonfluenza ,20. Howenfluenza . Our finWhen sansho pericarps were treated with MCTs with α-Toc added, HαS was extracted. Glycerol, water, and surfactants were added to this extract and vigorously shaken to create an o/w emulsion. This emulsion was stably maintained, even when diluted with liquid or powder. We believe that this approach can stabilize the spiciness and aroma of sansho and will allow the development of various sansho-based foods and medicines.TM, YY, and NY are named as inventors in patent applications (WO2021255943).


The Tmax of SHR6390 was 3.00 h. In plasma, the t1/2 of SHR6390 and its relative components was approximately 17.50 h. The radioactivity B/P (blood-to-plasma) AUC0-t ratio was 1.81, indicating the preferential distribution of drug-related substances in blood cells. At 312 h after administration, the average cumulative excretion of radioactivity was 94.63% of the dose, including 22.69% in urine and 71.93% in stool. Thirteen metabolites were identified. In plasma, because of the low level of radioactivity, only SHR6390 was detected in pooled AUC0-24 h plasma. Stool SHR6390 was the main component in urine and stool. Five metabolites were identified in urine, and 12 metabolites were identified in stool. Overall, faecal clearance is the main method of excretion.SHR6390  is a selective and effective cyclin-dependent kinase (CDK) 4/6 inhibitor and an effective cancer therapeutic agent. On 31 December 2021, the new drug application was approved by National Medical Product Administration (NMPA). The metabolism, mass balance, and pharmacokinetics of SHR6390 in 6 healthy Chinese male subjects after a single oral dose of 150 mg [ The disorder of cell division, which leads to abnormal cell proliferation, is one of the key signs of cancer. In cancer treatment, the target of blocking cell division is a very important research goal. Cell cycle usually refers to the stage in which cells pass through a predetermined number of stages under the control of a complex network of regulators . The celFirst-generation CDK inhibitors are non-selective universal CDK blockers with limited antitumour activity and obvious toxicity . More re14C]SHR6390 in humans were investigated.SHR6390  is a selective and effective cyclin-dependent kinase (CDK) 4/6 inhibitor and an effective cancer therapeutic agent. On 31 December 2021, the new drug application was approved by NMPA . SHR6390 exhibited potent antiproliferative activity against a wide range of human RB- positive tumor cells, and exclusively induced G1 arrest as well as cellular senescence, with a concomitant reduction in the levels of Ser780-phosphorylated RB protein. Although many research results on SHR6390 have been published, there are still many problems of concern that have not been solved or disclosed . To date14C]SHR6390  and SHR6390 (150 mg) were dissolved in 5% carboxymethylcellulose sodium  and stored at approximately −20°C. For other reagent information, please refer to another article in our group (SHR6390 (purity 99.50%) was provided by Jiangsu Hengrui Medicine Co., Ltd. . SHR6390 (150 µCi) suspension. Rinse the dosing bottle with warm water and give it to the subjects. The total volume of drug preparation and lotion did not exceed 240 mL. After taking the medicine, the subjects fasted for 4 h and refrained from water for 1 h after dosing. Twenty millilitres of whole blood was collected before administration and 2, 6, 10, 24 and 48 h after administration. In 20 mL of whole blood, 1.6 mL was used for the test, and 0.4 mL was placed in the backup tube. Centrifuge  10 mL of whole blood to produce plasma. The volume of plasma in one of the two tubes was 3.2 mL, and the remaining plasma was put into the backup tube. The remaining 8 mL whole blood was centrifuged  to produce plasma for metabolic study. Meanwhile, 10 mL whole blood was collected at 0.5, 1, 3, 4, 8, 72, 96, 120, and 144 h. The plasma required for detection is obtained by whole blood centrifugation. In addition to collecting urine samples before administration and 0–4 h, 4–8 h, 8–12 h and 12–24 h after administration, urine samples will be collected every 24 h in the following collection periods. Collection of fecal samples, except before administration, shall be conducted at 24-h intervals after administration. Plasma samples were stored at −80°C, and urine and stool samples were stored at −20°C until analysis.The clinical trial (No. CTR20230830) was an open-label, single-center, single-dose trial conducted at the First Affiliated Hospital of Soochow University . This study was conducted in accordance with the ethical principles required by the Helsinki Declaration and approved by the Hospital Ethics Committee (2020. No.151). Six healthy Chinese male subjects were recruited between 18 and 45 years old with a body mass index between 19 and 26 kg/mpre-dose . Fastingv: v) was added to the stool and homogenized. Blood and stool homogenate were weighed and burned in a biological oxidizer . Then, the CO2 with 14C labled was trapped in the liquid scintillation cocktail  and detected by LSC.The radioactivity of urine and plasma was detected by liquid scintillation counter (LSC) . Two times the weight of acetonitrile-water . The first two extracted supernatants were combined and concentrated. The concentration of the substance is at 200 μL Acetonitrile water  was dissolved again and centrifuged again . Part of the supernatant was injected into the UHPLC-FC (Fraction collector) system (Thermo). The eluent from the UHPLC was collected into the Deepwell LumaPlate 96 (PerkinElmer) at the rate of 10 s per well within minutes. The total collection time is 35 min. The plates were dried by Integrated SpeedVac (Thermo), and the radiation value of each well were detected by a microplate reader . Data were reconstructed to radio-chromatogram by Laura software  to give the radio profiling of plasma.According to the AUC principle, the plasma of 6 subjects from 0–24 h was pooled . The pla2 and dissolved in a 200 μL mixture of 40 mL acetonitrile and 160 mL-water, and 120 μL was injected into the UHPLC-FC system (Thermo). Other operation steps are the same as those of plasma.According to the principle of equal volume, the urine samples of 6 subjects from 0 to 120 h were merged. The combined samples were centrifuged, concentrated by N2 at 25°C and dissolved in acetonitrile-water  of 200 μL, and 60 μL was injected into the UHPLC-FC system (Thermo). Other operation steps are the same as those of plasma.According to the principle of equal proportion weight, the fecal homogenates of 6 subjects from 0 to 168 h were combined. Add 6 mL methanol acetonitrile  to the combined fecal homogenate (2 g) sample. The mixture was then whirled (1 min) and centrifuged6 . Transfer the supernatant into a clean tube, and then extract the extracted solid again with 2 mL water and 2 mL methanol and 2 mL acetonitrile. The two supernatants were combined, concentrated by NThe MS signal of the metabolites were obtained through UHPLC-HRMS, and the metabolic pathway of the metabolite was speculated. Through the MSMS spectrum obtained, the structure of the metabolite was identified by comparing the mass spectrum fragment with the mass spectrum fragment produced by the parent compound.The application software Phoenix WinNonlin  used a non-compartment model to calculate the parameters related to drug metabolism in this experiment. The related pharmacokinetic parameters for radioactivity are summarized in 25H30O2N6·C2H6O4S, with [M + H]+ at m/z 447.2503 eluted at 17.67 min and showed product ions at m/z 84.0808, 161.1073, 201.0771, 219.0877, 296.1142, 324.1455, 361.1771 and 379.1877  of was 1.81. For SHR6390 in plasma, the mean Cmax value of radioactivity was 42.9 ng/mL, and the mean AUClast value was 1,150 ng/mL h. The mean AUCinf values were 1,250 ng eq./mL*h. The mean Tmax and t1/2 were approximately 3.00 and 43.5 h, respectively.The radioactivity concentration-time profiles, the 14C]SHR6390 (150 µCi), the recovery of total radioactivity was 94.63% (range 92.85%–96.34%). Stool excretion was the predominant route of elimination, accounting for 71.93% of the administered dose, while the mean urinary excretion was 22.69%. The total recovery in urine and stool in radioactive, 312 h after dosing was 94.63%  were also detected as minor metabolites in urine.Parent SHR6390 and 12 metabolites were identified in the pooled 0–168 h fecal samples . Among tm/z 161.1073, 296.1142, 324.1455 and 379.1877,397.1983. Comparing the ion fragments with those of the parent, the structure of M464-1 was deduced, as shown in M464-1: The signal of MS showed that the elemental change of M478 was di-oxidation of parent SHR6390. The main product ions were M478: The details are shown in the urine section above.m/z 217.0720, 294.0986, 322.1299, 377.1717, 395.1926 and 463.2452. Comparing the ion fragments with those of the parent, the structure of M464-1 was deduced, as shown in M542: The signal of MS showed that the elemental change of M542 might be mono-oxidation and sulfation of the parent SHR6390. The main product ions were In addition, M448, M462-1, M462-2, M462-3, M464-2, M476-1, M476-2 and M476-3 were also identified in stool as minor metabolites.14C]SHR6390 in human. After oral administration, 94.63% of the dosed radioactivity was recovered in urine and stool by 312 h post-dose, which indicated complete excretion, with 22.69% in urine and 71.93% in stool.This study reported the mass balance study of [14C]SHR6390. In plasma, because of the low level of radioactivity, only SHR6390 was detected in pooled AUC0-24h plasma. In urine and stool, SHR6390 was the major component; 5 and 12 metabolites were identified, respectively.Based on high radioactivity recovery in sample extraction, the metabolite profiles were evaluated. A total of 13 metabolites were identified, and unchanged SHR6390 was the major metabolite in three matrix following an oral administration of  SHR6390, 94.63% of the dose was recovered in urine and feces, of which 22.69% was recovered in urine and 71.93% in feces. The characterization of SHR6390 pharmacokinetics, mass balance and metabolism is helpful to guide our understanding of SHR6290 metabolism and elimination pathway. In plasma, for the low level of radioactivity, only SHR6390 was detected in pooled AUC0–24 h plasma. In urine and stool, SHR6390 was the major component; 5 and 12 metabolites were identified, respectively. Overall, faecal elimination played a significant role.In conclusion, this study shows that after a single oral administration of [


Alcohol beverages have been widely consumed in several parts of the world. In this study, volatile organic compounds in alcoholic beverages including acetaldehyde, ethyl acetate, methanol, and higher ethanol were investigated and evaluated using a headspace gas chromatograph equipped with a mass spectrometer. This study evaluated the suitability of the chromatographic system, linearity, limit of detection, and limit of quantification, accuracy, and precision of the single and simultaneous determination of acetaldehyde, ethyl acetate, and methanol in thousand folds of ethanol. Results showed that the acetaldehyde concentration in local beer samples and local manual product liqueur samples ranged from 4.65 to 13.22 mg/L and from 5.55 to 75.96 mg/L, respectively, but in local industrial product liqueur samples, acetaldehyde was not detected. Methanol was only detected in a few local beer samples and locally manually produced liqueur samples within low concentrations. Ethyl acetate was only detected in all local beer samples, but it was not present in local industrial product liqueur samples. Ethanol level is important to consumers for the mouthfeel and flavor of alcoholic beverages. Beer, wine, and liqueur have ethanol levels ranging from 3 to 6% (v/v), 7 to 21% (v/v), and 20 to 50% (v/v), respectively . This coOn the other hand, ethanol, methanol, acetaldehyde, and ethyl acetate are volatile compounds whose detection and quantification in alcoholic beverages can be used as a biological indicator to identify the origin of several kinds of alcoholic drinks because the volatile compounds which characterize the beverage type are diverse and originated from raw materials. And these volatile compounds are generated during production, maturation, and storage .Ethanol, acetaldehyde, methanol, and ethyl acetate in alcoholic beverages were determined by several methods. Ana Catarina et al. determined acetaldehyde, ethyl acetate, and methanol in wine spirits, brandy, and grape marc spirits by the GC-FID method . AcetaldMethanol, acetaldehyde, ethyl acetate, ethanol standard, n-butanol internal standard, acetonitrile, and water were purchased from Merck, Darmstadt, Germany. All chemical standards used for the analysis were of analytical grade. Nitrogen, hydrogen, and helium were of extrapure grade 4.5 .Methanol, acetaldehyde, ethyl acetate, ethanol, acetonitrile standard solutions, and n-butanol internal standard solution were prepared in water solvent and stored at −18°C. These solutions were sonicated for 5 min before use.μL of the sample's volatile fraction in the headspace was injected into the GC inlet. A TG-WAXMS 30 m × 0.25 mm × 0.5 μm (polyethylene glycol) capillary column was used to separate the volatile fractions under a constant flow of helium 1.2 mL/min. The duration of the analysis was 8 minutes. For increased sensitivity, other method parameters were optimized. All experimental samples were analyzed in triplicate.5 mL of samples was poured into 20 mL of glass headspace vials, n-butanol was added as internal standard, and then, the vials were sealed with caps lined with a silicon PTFE membrane. The vial samples were incubated for 10 min at 70°C in order to facilitate the transfer of analytes to the sample's volatile fraction. All samples were analyzed by GC-MS Thermo Fisher Scientific ISQ 72008051 gas chromatography with a mass spectrometric detector equipped split/splitless inlets, and a headspace sampling system. For separation of impurities, 1 Each of the acetaldehyde, methanol, and ethyl acetate standard solutions was prepared for calibration at 5 to 240 mg/L and 50 to 2400 mg/L of ethanol standard solution. Every single standard solution was determined in triplicate. All prepared standards were analyzed at optimized parameters by HS-GC-MS Thermo Fisher Scientific ISQ 72008051 gas chromatography. The validation method of single determination was determined by the limit of detection (LOD), the limit of quantification (LOQ), repeatability, and recovery.The LOD is the smallest sample concentration at which the substance signal may be consistently recognized when compared to a blank run's baseline noise. For evaluating the detection limit, a signal-to-noise ratio of 3 : 1 is typically regarded adequate .(1)LOQ=3Intra-assay and inter-assay precision levels were assessed by analyzing the quality control samples. Intra-assay was assessed using a minimum of 9 determinations at 3 concentrations/6 replicates each for the procedure. Inter-assay precision levels were evaluated in three concentrations at 5, 80, and 240 mg/L for acetaldehyde, ethyl acetate, and methanol and 50, 800, and 2400 mg/L for ethanol for six consecutive days. Intra-assay and inter-assay precision was evaluated in terms of relative standard deviation (% RSD).Acetaldehyde, methanol, ethyl acetate, and ethanol recoveries were measured based on accuracy at 5, 80, and 240 mg/L for acetaldehyde, ethyl acetate, methanol, and 50, 800, and 2400 mg/L for ethanol.The experiment was carried out by varying the incubation temperature of headspace at 40°C, 50°C, 60°C, 70°C, and 80°C; incubation time of the headspace at 5 min, 10 min, 15 min, 20 min, 25 min, and 30 min; inlet temperature at 150°C, 170°C, 190°C, 210°C, 230°C, and 250°C; column temperature program at 38°C and increased to 50°C with various heating rate of 3°C/min, 10°C/min, 15°C/min, and 20°C/min, to 25°C/min, where it was held for 1 min and then 50°C and increased to 170°C at 35°C/min; detector temperature at 150°C, 170°C, 190°C, 210°C, 230°C, and 250°C; carrier gas flow rate was surveyed at 1.0 mL/min, 1.2 mL/min, 1.4 mL/min, 1.6 mL/min, 1.8 mL/min, and 2.0 mL/min; split ratio at 1 : 10, 1 : 20, 1 : 40, 1 : 60, and 1 : 100. The chromatogram was recorded, and the area of the peak was calculated to choose the optimal condition.α), the limit of detection (LOD), the limit of quantification (LOQ), repeatability, and recovery.For calibration, the mixer of acetaldehyde, methanol, ethyl acetate, and ethanol standards at 5 to 240 mg/L of acetaldehyde, methanol, and ethyl acetate standard solutions and 50 to 2400 mg/L of ethanol standard solution were prepared. Every mixer standard solution was determined in triplicate. All prepared samples were analyzed at optimized parameters by HS-GC-MS Thermo Fisher Scientific ISQ 72008051 gas chromatography. The validated method simultaneous determination was determined by the selectivity factor . The peak area and retention time of acetaldehyde, methanol, ethyl acetate standard, and internal standard were recorded, and the mean values of the peak area ratio were plotted against the concentrations to obtain the calibration curves. Linear regression of acetaldehyde, methanol, ethyl acetate, and ethanol were y = (0.0164 ± 0.0008) x + 0.0151 ± 0.0098 (mg/L),y = (0.0025 ± 0.00004) x + 0.0008 ± 0.0003 (mg/L), y = (0.0298 ± 0.0064) x + 0.0167 ± 0.0138 (mg/L), and y = (0.0033 ± 0.0002) x + 0.0501 ± 0.0135 (mg/L), respectively Column: TG-WAXMS 30 m × 0.25 mm × 0.5 Detector temperature: 250°CInlet temperature: 150°CGC oven temperature: 38°C and increased to 50°C at 3°C/min, where it was held for 1 min and then 50°C and increased to 170°C at 35°C/minμLInjector volume: 400 Slipt ratio: 1 : 10Mobile phase flow rate: 1.2 mL/minChromatographic conditions include the following:n = 3). Recording the peak area of acetaldehyde, methanol, ethyl acetate, ethanol standard, and n-butanol internal standard, the mean values of the peak area ratio was plotted against the concentrations to obtain the calibration curves. Linear regression and good coefficients of acetaldehyde, methanol, ethyl acetate, and ethanol are shown in The linearity of simultaneous determination of methanol, acetaldehyde, ethyl acetate, and ethanol in the headspace gas chromatography mass spectrometry method was determined at seven concentration levels ranging from 5 to 240 mg/L of acetaldehyde, methanol, and ethyl acetate standard solutions and from 50 to 2400 mg/L of ethanol standard solution. Each of these standard solutions was incubated in the headspace at 70°C for 10 minutes, and then, the evaporative part was injected into the chromatographic system . The RSD of intra-assay and inter-assay precisions in Acetaldehyde, methanol, ethyl acetate, and ethanol recovery were measured based on accuracy at 5, 80, and 240 mg/L for acetaldehyde, ethyl acetate, and methanol and 50, 800, and 2400 mg/L for ethanol. Recovery of acetaldehyde, methanol, ethyl acetate, and ethanol was found to be 95–102%, 97–103%, 98–105%, and 99–107%, respectively .The results showed that the limit of detection, the limit of quantification, linear range, repeatability, and recovery efficiency of the simultaneous method were good, meeting the requirements for method validation of AOAC by GC-MS equipment.Saving analysis time: By only one injection, the simultaneous concentration of methanol, acetaldehyde, ethyl acetate, and ethanol could be determined in samples. The total time required for the chromatographic analysis was 9 min. Several authors have developed GC methods for the simultaneous determination of methanol, acetaldehyde, ethyl acetate, and ethanol. One comparable study was conducted by Schlatter et al. who developed and validated a method for the simultaneous determination of acetaldehyde, methanol, acetone, and ethanol. The total time required for the chromatographic analysis was 15 min, which was 1.5 fold higher than our method .Cost savings: By only a single injection, the concentration of methanol, acetaldehyde, ethyl acetate, and ethanol in the samples can be determined simultaneously, so the cost of the analysis is smaller than in the case of individual substances.Minimizing errors in the analysis process: In the simultaneous analysis process, the steps of the analysis were minimized compared to the single analysis process, thereby limiting the errors arising from the manipulation process.The analytes in the sample have different concentrations. So, it is difficult to process the samples, especially with trace concentration. To minimize this drawback, a standard addition method was performed to decrease the difference in concentration between the analytes.Because the ethanol concentration in the alcohol samples was at 5–40%, the samples should be diluted to analyze at the appropriate ratio. Meanwhile, methanol, acetaldehyde, and ethyl acetate concentrations were lower than ethanol concentrations. Therefore, the dilution samples have done a standard addition at 5 mg/L for each methanol, acetaldehyde, and ethyl acetate, and an internal standard was added into the dilution sample. Ethanol concentration in liqueur product samples varies for each product group. Ethanol concentration in beer was in a range from 4.5% to 5.9%; meanwhile, the ethanol concentration in local liqueur samples  was in a range from 25.7% to 39.6%. These results were in accordance with the declaration of the manufacturers. Most of the beer samples did not contain methanol or contained a little methanol level. In contrast, the content of ethyl acetate in beer samples was high, in the range of 30–40 mg/L. Meanwhile, the content of acetaldehyde ranged from 4.6 to 13.2 mg/L. Beer was produced through fermentation and then filtration without distillation. So, beer samples have a lot of impurities in them, such as acetaldehyde and ethyl acetate.Industrial liqueur products have no or contain very little methanol, acetaldehyde, and ethyl acetate . Most industrial liqueur products were produced using multistage distillation towers to distillate and help separate and decrease impurities in the liqueur. In the group of manual liqueur products, the ethanol concentration is from 25.6 to 37.8%, which depends on the needs of each product. Most of the manual liqueur product samples contained acetaldehyde, but its significant difference lies in the levels of different production facilities. In contrast, ethyl acetate and methanol concentrations did not present or were found very little in manual liqueur products. The reason is that all local artisanal distilleries use simple or self-designed distillation equipment. So, the process of separating ethanol from impurities does not completely depend on the system and conditions of the distillation process. Therefore, the results in the group of manual liqueur products are significantly different in impurity concentration between production facilities. The methanol, acetaldehyde, and ethyl acetate concentrations in these liqueur products were less than these concentrations in several documented previous studies. According to Kokkinakis et al., the concentrations of acetaldehyde, ethyl acetate, and methanol in bottled spirits and in-bulk spirits were 297.58 mg/L, 429.16 mg/L, and 698.02 mg/L and 199.75 mg/L, 1067.66 mg/L, and 781.20 mg/L, respectively . The metThis study was taken to analyze the simultaneous concentration of acetaldehyde, methanol, ethyl acetate, and ethanol in alcohol, which are most commonly consumed by the habitants of Ho Chi Minh City, Vietnam. The HS-GC-MS parameters for simultaneous determination of these volatile compounds were optimized. The simultaneous method was validated. In beer samples, there were impurities such as acetaldehyde and ethyl acetate because the production process did not go through distillation. In industrial liqueur products, there is very little methanol, acetaldehyde, and ethyl acetate because multistage distillation towers were used to distillate to help separate and decrease impurities in the liqueur. For manual liqueur products, there are still impurities such as methanol and acetaldehyde because simple or self-designed distillation equipment was used to separate impurities during the production process.


An inadequate level of vitamin D is associated with autoimmune diseases, hypertension, and cancer. The study was aimed to assess the pharmacological effects of chronic vitamin D3), and in CSF (klotho and β-endorphin). 25-OH Vit D3 was also estimated in liver and kidney homogenate using ELISA. Vitamin D receptor (VDR) was measured spectrophotometrically in liver and adipose tissue.Memory performance (Y-maze task), muscular function (muscle grip strength), and pain score (pressure application measurement meter) were measured. Functional biomarkers were measured using ELISA method in different matrix viz. in serum  and active metabolites of vitamin D3 (25-OH vit.D3) in serum were significantly higher by 48.23% and 280%, respectively. The PTH and CRP levels were significantly reduced by 32.5% and 35.27%, respectively, whereas calcitonin was increased by 36.67% compared with the VDD group. Klotho and β-endorphin expressions in cerebrospinal fluid were significantly elevated by 19.67% and 133.59%, respectively, compared to VDD group.VDD-induced rats showed a decrease in number of entries and time spent in the novel arm and spontaneous alternations in the Y-maze task. Significant improvements of neuromuscular function and pain score after addition of vitamin DOverall, the results indicate that supplementation of cholecalciferol significantly improved spatial memory impairment, VDR expression, and may provide an opportunity to manage vitamin D deficiencies. 3 supplementation significantly improved short-term spatial memory function in VDD rats.Chronic vitamin DSignificant improvement of neuromuscular function and pain score.3 were improved.VDR expression followed by levels of 25-OH vit.DKlotho and β-endorphin expression were significantly improved.PTH and CRP levels were significantly reduced. In brief, about 100 µL of each test sample, including the control and reference standard, were poured into the labeled wells and incubated at 37 °C for an hour. After removing the cover and discarding the liquid, and 100 µL of detection reagent-A working solution was poured into all wells and again incubated at 37 °C for an hour. The plate was then washed three times with 1X washing buffer. Each well was then filled with 100 mL of detection reagent B working solution, sealed, and incubated at 37 °C for 30 min. Following the discarding of the solution, the plate was washed and 90 µL of 3,3’5,5’-Tetramethylbenzidine (TMB) substrate added to each well and incubated at 37 °C for 10 min. After that, 50 µL of stop solution was added to each well, and reading was taken at 450 nm.3 metabolite  using ELISA, as recommended by the manufacturer.A serum, liver, and kidney homogenate were used from all the animals for estimating the 25-OH Vit DCSF was collected by the standard in-house method using a stereotaxic instrument to measure Klotho  and β-endorphin  using ELISA.post-hoc analysis by Tukey’s/Dunnett’s test and between two groups by Student’s t-test. F values p < 0.05 were regarded as statistically significant.Statistical analysis was performed using Sigma-Plot (V11.0). Data are shown as mean ± standard error of the mean. Multiple comparisons were analyzed by one-way analysis of variance (ANOVA) followed by 3 deficient diet (VDD) without cholecalciferol and calcium chloride for three weeks. The level of 25(OH) vitamin D3 in the circulatory system was measured three weeks after VDD administration. Tukey’s post hoc test revealed that the level of 25(OH) vitamin D3 was significantly  = 14.796, p < 0.001) reduced in all the treatment groups than normal control, were considered as VDD-induced animals and selected for further treatment (data not shown).Except for the normal control, all the animals were fed a vitamin Dt = 3.901; p = 0.003) in the number of entries into the novel arm between the two groups. In the Y-maze task, one-way ANOVA  revealed a significant  = 5.585; p = 0.006) increase of spatial memory performance in vitamin D3-treatment groups with low, medium, and high doses by 167.34, 197.11, and 217.46%, respectively than disease control  group than normal control (4.29 ± 0.49). There was a significant difference  in time spent into novel arm between two groups. Positive control (41.41 ± 6.66) showed significant  increased time spent in novel arm by 126.66% compared to disease control. Pair t-test analysis revealed a significant difference between disease control and vit.D3 (1 mg/kg) group . Time spent in novel arm was increased by 72.47, 89.16, and 150.96% in vitamin D3-treatment groups with low, medium, and high doses, respectively than disease control  group than normal control (63.03 ± 7.20). There was a significant difference  group than normal control (66.49 ± 19.78). Positive control (43.11 ± 5.72) showed significant  increased spontaneous alternation by 120.15% compared to disease control. Pair t-test analysis revealed a significant difference between disease control and vit.D3 (1 mg/kg) group . Percentage of spontaneous alternation was increased by 29.42 and 123.70% in vitamin D3-treatment groups with medium and high doses, respectively, than disease control . In the results found at the end of the experiment, despite the VDD treated animals (1219.06 ± 22.33) having presented lower grip strength by 12.30% than normal control (1390.06 ± 35.38). There was a significant difference  in muscle grip strength between two groups. Positive control (1371.56 ± 52.13) showed significant  increased muscle grip strength by 12.51% compared to disease control. Pair t-test analysis revealed a significant difference between disease control and vit.D3 (1 mg/kg) group   decreased by 20.42% in disease control than normal control. Positive control showed significant  increased GF by 11.22% compared to disease control. Pair t-test analysis revealed a significant difference between disease control and vit.D3 (1 mg/kg) group   decreased by 35.09% in the disease control than normal control. Positive control showed significant  increased VDR expression by 97% compared to disease control. VDR expression in liver was increased by 48.23% in vitamin D3-treatment at 1 mg/kg than disease control  in the liver and adipose tissues were evaluated and are presented graphically in Fig. 3 in liver tissue was significantly  decreased by 16.40% in the disease control group than normal control. Dunnett’s post hoc test revealed that the level of 25-OH vitamin D3 in kidney tissue was significantly  = 3.566, p = 0.020) increased by 23.24% in the vit.D3 (1 mg/kg) group compared to VDD  = 3.104, p = 0.033) increased by 278.12% and 281.11% in the 0.5 and 1 mg/kg, respectively compared to VDD  increased by 81.02% in the disease control than normal control.The results of serum biomarkers are graphically presented in Fig. post hoc test revealed that the level of calcitonin was significantly  = 8.011, p = 0.018) increased by 36.66%, while CRP was significantly  = 7.825, p = 0.019) decreased by 35.27% at 1 mg/kg than disease control  = 3.732, p = 0.016) decreased by 33.11% and 32.50% in the positive control and vitamin D3 (1 mg/kg) groups, respectively than disease control  decreased by 27.80% in the disease control than normal control. Positive control showed significant  increased klotho protein by 20.37% compared to disease control  showed significantly increased by 19.67%  = 5.247, p = 0.003) and 133.59% , respectively at 1 mg/kg than disease control  and β-endorphin  on modifying diet regimens in deprived cholecalciferol rats. Therefore, it is unclear whether a potential relationship presents between depletion and supplementation of vitamin D3. We tested the hypothesis that cognitive decline associated with low cholecalciferol can be improved by long term (56 day) administration of cholecalciferol. In addition to, cognitive memories, authors also measured pain score, muscle function, hormonal changes, VDR expression, metabolite levels, and anti-aging protein. Briefly, induction of VDD model, treatment duration, study outcomes, and probable mechanisms are shown schematically in Fig. Recently, there have been growing concerns about vitamin D deficiency as a risk factor associated with cognitive impairment/aging. A few studies have investigated the effects of successive vitamin D supplements  is a novel behavioral rat model to evaluate joint pain hypersensitivity. The reading of PAM as gram force (GF) is considered the gold standard for behavioral hypersensitivity. In addition, the method is a highly reproducible and a useful tool for chronic inflammatory joint pain evaluation [3 treatment regimen is highly effective in pain-reducing activity via VDR receptor.Coradini et al. 2015) reported weak muscle strength in nerve compression model due to hypernociception . Vitamin reportedaluation . In litealuation . Thus, v3 and 1,25 dihydroxy vitamin D3 are mainly mediated by the VDR. Thus, chronic repeated oral administration of vitamin D3 significantly improved the level of VDR expression in the liver and adipose tissues that mediate various biological functions. As a result of vitamin D3 supplementation behavioral activity, VDR level, and joint pain can also be improved. Literature data reported that vitamin D has a significant therapeutic role in many neurological diseases via inhibition of the NADPH oxidase (NOX2), which protects against reactive oxygen species (ROS) production [3 supplementation reduces animal activity through VDR mechanisms.It was reported in many studies that VDR regulates the expression of numerous genes that are responsible for cellular proliferation, calcium/phosphate homeostasis, and immune response . The biooduction , 21. Hen3 significantly increased the level of calcitonin compared with the VDD group. However, CRP is a pentameric protein found in blood plasma, and its level depends on the body’s inflammation. It is defined as an acute phase reactant and depends on the inflammation level [3 treatment at 1 mg/kg.The secretion of calcitonin (antagonist of PTH) is stimulated by an elevated calcium level and low blood calcium. It is indirectly involved in the regulation of bone mineralization and synthesis of bone matrix , 23. VDDon level , 25. In 3 treatment groups, which was abruptly increased in the VDD-treated group. Thyroid hormones play an imperative role in muscular activity, metabolic rate, brain development, and maintenance of bone health [3 treatment with respect to the VDD.PTH, a type of peptide hormone is synthesized from parathyroid gland and regulates the plasma calcium . Howevere health , 30. The3 are less than 20 ng/mL (50 nmol/L). Vitamin D3 is metabolized to form 25-OH vitamin D3 (liver) and 1,25-dihydroxyvitamin D3 (kidney) [3 increased oxidative/nitrosative stress and inflammation. Supplemental with vitamin D3 decreased oxidative DNA damage [3 improves muscle strength and or physical performance [3 significantly improved the metabolite level in serum, liver, and kidney tissues compared with the VDD group. β-endorphin is an endogenous opioid neuropeptide hormone produced in certain neurons within the peripheral nervous system (PNS) and central nervous system (CNS) to relieve pain. In PNS, β-endorphin produce an analgesic effect by binding with opioid (µ) receptor. After binding, a cascade of interactions occurs that inhibits the release of a key protein for pain transmission i.e., substance P. In CNS, β-endorphin similarly bind to the µ-opioid receptor and exert their analgesic effect through inhibits the release of γ-aminobutyric acid (GABA), resulting in excess production of dopamine, which is associated with pleasure [KL gene expression in mouse and human renal cells [3 significantly improved the levels of VDR expression, in addition to the β-endorphin, klotho (an anti-aging gene).Vitamin D deficiency is defined when the serum levels of 25-OH vitamin D(kidney) –33. InsuA damage . Growingformance . Our exppleasure . Emerginpleasure . The leval cells . Clinicaal cells . Severalal cells , and oxial cells , and regal cells , 43. Thual cells . Our fin3 and other functional physiological biomarkers. While vitamin D and calcium deficiencies, which we assumed as a single factor, contribute to the effects observed in the VDD group, they are due to multiple factors. Information on the vitamin D content in the maintenance diet fed to the control group is not standardized. From a mechanistic perspective, further study like estimation of biomarkers in skeletal muscle and hippocampus is needed to clear such a paradox.The current study was significantly improved memory function, muscle function, pain score. It also improved VDR expression followed by levels of 25-OH vit.D3) alleviates neurobehavioral deficits and brain cognition in vitamin D3 deficient diet (VDD)-induced Sprague Dawley rats. It also significantly increases expression of VDR, β-endorphin, and anti-aging protein (Klotho). In light of this, cholecalciferol supplementation may be promising for treating cognitive impairment like Alzheimer’s disease and vitamin D deficiency disorders. Overall, this study shows a strong association between vitamin D3 status and the incidence of spatial memory and cognition abilities as well as muscle strength and chronic joint pain in rats.The findings of this study demonstrate that supplementation with cholecalciferol (vit.D


The average recovery of cefquinome was 88.60 ± 16.33% at 0.2 μg·kg−1, 100.95 ± 2.54% at 10 μg·kg−1, and 97.29 ± 1.77% at 50 μg·kg−1. For 5 consecutive days at the three spiking levels, the intra and inter-day relative standard deviations (RSD) were 1.28%–13.73% and 1.81%–18.44%, respectively; the residual amount of cefquinome was less than the maximum residue limit of 20 μg·kg−1, 36 h after administration; and the residual amount was less than the limit of detection (0.1 μg·kg−1) 48 h after administration. The withdrawal time of cefquinome in cow’s milk was 39.8 h, as calculated using WTM1.4 software. In terms of clinical practical use, the withdrawal period of milk was temporarily set at 48 h after the administration of the cefquinome sulfate uterus injection to cows, in accordance with the recommended dose and course.As set in the maximum residue limit regulations of the European Commission, this study aimed to obtain the residual parameters in milk with optimized UPLC-MS/MS conditions and to determine the conclusive drug withdrawal period to ensure food safety. In this research, an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was developed to study cefquinome sulfate’s residue elimination in milk and to calculate cefquinome’s withdrawal period. Twelve healthy cows free of endometritis were selected for the experiment. Before using the drug, the vaginal orifice and perineum of each cow was disinfected. One dose of intrauterine perfusion was used for each cow, followed by an additional dose after 72 h. Before administration and 12 h, 18 h, 24 h, 36 h, 42 h, 48 h, 60 h, 66 h, 72 h, 84 h, 90 h, and 96 h after the last dose, milk (10 mL) was gathered from each cow’s teat and pooled. For the measurement of cefquinome concentrations in milk, UPLC-MS/MS was performed. A calibration curve was generated using linear regression as follows: Y = 250.86X − 102.29, with a correlation coefficient of 0.9996; the limits of detection and the limits of quantitation were 0.1 μg·kg Escherichia coli. + ions account for more––the precursor ion m/z 529.1, the product ion m/z 134.1, and the product ion m/z 396 [2+ ions account for more––and the precursor ion m/z 265.1, the product ion m/z 134.1, and the product ion m/z 199.3. Therefore, these ions were selected for the detection of cefquinome in milk. In this study, different precursor ion (m/z 265.1 and m/z 529.1) and the same product ion (m/z 134.1) were selected to detect the same concentration of cefquinome. The results showed that the response value of 2.803 × 106 during the fragmentation from m/z 265.1 precursor ion to product ion m/z 134.1 was significantly higher than that of the response value of 8.144 × 104 during the fragmentation from m/z 529.1 precursor ion to product ion m/z 134.1. The peak area of 104,624.0940 during m/z 265.1 precursor ion was fragmented to product ion m/z 134.1, and was significantly higher than that of the peak area of 3856.3210 during m/z 529.1 precursor ion, which was fragmented to product ion m/z 134.1  are shown in −1, 100.95 ± 2.54% at 10 μg·kg−1, and 97.29 ± 1.77% at 50 μg·kg−1. The average recovery of cefquinome was 100.95 ± 2.54% at 10 μg·kg−1. The acceptance standards for mean recovery at each concentration grade vary. For concentrations ≥ 10 μg·kg−1, the recovery deviation must be within the range of −20% to +10% [The accuracy and precision for determination of cefquinome at three spiking concentrations  were compared with chromatograms of blank mobile phase sample spiked with cefquinome (25 μg·kg−1), reconstituted in the same mobile phase  after administration was between 104.22 μg·kg−1 and 347.76 μg·kg−1. The level of cefquinome sulfate in the milk rapidly decreased to a range of 10.43–52.84 μg·kg−1 after 24 h. Cefquinome residues were already less than the maximum residue limit (MRL) of 20 μg·kg−1 in milk samples that were collected 36 h after the last dose. In the milk sample collected 48 h after the last dose, the concentration of cefquinome was below the detection limit of this method (0.1 μg·kg−1). In terms of clinical practical use, the withdrawal period of milk was temporarily set as 48 h after the administration of the cefquinome sulfate uterus injection to cows in accordance with the recommended dose and course.The results showed that the average residual concentrations in the corresponding 12 milk samples at each time point were as follows: 178.74 ± 74.66 μg·kg−1 [Antibiotics are widely applied in animals for dissimilar aims, including feed efficiency and increment promotion as well as preventative and therapeutic impacts. At least 60,000 tons of antibiotics are applied every year in the livestock industry ,41. Meta−1 . It is nThe interval between the last dose of a veterinary medicinal product to animals and the production of foodstuff was called the withdrawal period. WTM 1.4 was published by the European Medicinal Products Evaluation Agency (EMEA), which is based in London, UK, to calculate the withdrawal times in milk using the statistical method proposed by the Committee for Veterinary Medicinal Products (CVMP). For studying the elimination of cefquinome residue in milk, WTM 1.4 software was used to calculate the milk withdrawal period of cefquinome, and it was found to be 39.8 h.The withdrawal period may vary with antibiotics, and the withdrawal period ranged from a few days to a couple of weeks. β-lactam antibiotics are widely used in the treatment of dairy cow diseases. At present, there are many studies on the withdrawal period of β-lactam antibiotics in milk. Smith et al. . reporteWhen the correct withdrawal periods are known, improper drug use and the incidence of antibiotic resistance  can be r−1 in milk samples that were collected. The cefquinome residue concentration in samples collected 48 h after administration was lower than the method’s limit of detection. The withdrawal period of cefquinome in milk was 39.8 h. In terms of clinical practical use, the withdrawal period of milk was temporarily set at 48 h after the administration of cefquinome sulfate uterus injection of cows in accordance with the recommended dose and course. The results of cefquinome residue in milk provide reference for the rational use of cefquinome residue and milk food safety.In this study, UPLC-MS/MS conditions and a preprocessing method were established and validated for detecting cefquinome residue in cow’s milk. The cefquinome recovery was between 72.27% and 103.21%. The UPLC-MS/MS method and a processing method were established for cefquinome’s detection in the milk of cows. The results show that the verification parameters of the method all meet the criteria of commission decision 2002/657/EC . After c


This study characterizes the flood vulnerability of Adama City, Ethiopia, where the city faces high flood vulnerability due to its unplanned urbanization in low-lying floodplain areas surrounding deforested mountains and ridges. The study applied an interlinked Social-Ecological-Technological-Systems (SETS) vulnerability framework using a GIS-based Multi-Criteria Decision-Making and Analytical Hierarchy Process (MCDM-AHP). The framework analyzed exposure, sensitivity, and adaptive capacity to flooding for each of the three SETS domains. The study analyzed 18 variables at the city level within each SETS domain. The result revealed that clusters of flood-vulnerable areas were identified by each SETS domain showing the concentration of flood vulnerability in the study area and the need to consider prompt adaptive mechanisms to severe and recurring flooding. The finding has significant implications for holistic approaches to sustainable cities. Moreover, the reduction of complex urban flood vulnerabilities according to their priority as individual or combined solutions for decision-makers and professionals in early warning and flood management systems is the other contribution of the study. Recent studies have revealed that approximately 1.81 billion people, accounting for 23 % of the global population, are exposed to considerable flood risk . The conFlooding in cities has been widely attributed to urbanization in floodplain areas . UrbanizVulnerability to flooding in urban areas is determined by analyzing the components of exposure, sensitivity, and adaptive capacity. According to Chang, Pallathadka , the SETUrban floods are one of the most frequent natural disasters, resulting in severe economic damage and loss of lives . TherefoAssessment of flood vulnerability is recognized as a pre-emptive undertaking for hazard management and planning . ResearcUrban flooding has become a major issue in developing countries, particularly in Africa, due to rapid urbanization and population growth . InadequUrban flooding has emerged as a significant concern in Ethiopia due to various factors including inadequate urban drainage infrastructure, insufficient land use planning measures, the absence of early warning systems, and a lack of coordination in flood management activities at both federal and local levels. According to the National Disaster Risk Management Commission , EthiopiRecent research highlighted the increasingly significant influence of flood issues in Adama City, given the increasing number of people, economic activities, and ecosystems affected by their unfavorable consequences . The hisMulti-criteria decision-making techniques offer a robust and precise evaluation of urban flood vulnerability, allowing for a comprehensive and accurate assessment. This approach effectively identifies the key factors that significantly contribute to flood risk and determines their relative importance in the decision-making process . The effIn line with this, the objective of this study is to characterize the level of urban flood vulnerability in Adama City using SET frameworks. The study builds upon previous work done by Chang, Pallathadka , which u22.1The present study was conducted in Adama City, Ethiopia. Adama is one of the fastest-growing and second-most populous cities in Ethiopia. It was founded in 1916 on a flat terrain surrounded by plateaus; mountain ranges, and ridged topography, located within the Awash River Watershed and the East African Rift Valley. The study area is located between 8°26′15″– 8° 37′00″ N, and 39° 12′15″- 39°19′45″ E.The altitude of the study area ranges from 1489 to 1976 m above sea level (m a.s.l), and is located 99 km southeast of Addis Ababa, the capital of Ethiopia with a total area of 30,865.4 ha. The city has two extreme points located at its eastern and northwestern borders. The lowest point is situated on the eastern edge, featuring a flat, low-lying area, which collects floodwater from ‘Borticha’ ridge (Ganda Dabe Solloke), and the eastern edge of ‘Migira’ ridges, forming seasonal ponds. The highest elevation point is found at the northern tip of the Wind Farm II substation, with an altitudinal range measuring up to 487 m. This wide altitudinal variation contributes to the presence of a variety of tropical and subtropical microclimates in the region.The 2007 census conducted by the Central Statistics Agency of Ethiopia (CSA) revealed that Adama City had a population of 222,035 people and experienced a 5.4 % growth rate, exceeding the average urban growth rate of Ethiopia which was 2.5 %. The Adama City Structure Plan Revision , reporteAccording to National Meteorology Agency , Adama C2.2The socio-demographic, ecological, and technological frameworks in Adama City were collected both from primary and secondary sources. The secondary data was collected from different bureaus and websites. The spatial data obtained from the Adama city administration was updated from field visits and Google Earth digitalization. For analysis, the collected data was transferred into Arc GIS (version 10.7.1), as presented in 2.3This study utilized the SET frameworks and employed GIS-based AHP to assess the flood vulnerability of Adama City. The analysis encompassed 18 variables, which were categorized into three domains: social, ecological, and technological aspects. These variables were processed and rasterized on a scale of 1–5, representing very low to very high vulnerability levels. The reclassification of the variables was conducted in a GIS environment using the reclassify tool from spatial analysis tools. The resulting data was rescaled and geo-referenced with the same coordinate system of WGS_1984_UTM_Zone_37 N.To determine the importance of each flood-influencing factor, an AHP model was employed. This involved interviewing 20 experts and 20 local elders to gather their insights on the most significant factors contributing to flooding in the study area. The pair-wise comparison matrix was used to calculate the prioritization of these factors, with each factor's weight expressed as a percentage value between 0 and 100 %. The sum of all weights equaled 100 % to ensure consistency.The ranking of each reclassified factor was based on a combination of literature review, expert interviews, and residents' input. Factors were ranked on a scale of 1–5, with rank 5 indicating the highest level of influence and rank 1 indicating the lowest. The assigned weight for each factor reflected its contribution to flooding relative to other factors.Using ArcGIS (version 10.7.1), a multi-criteria analysis was conducted to produce the flooding vulnerability map. This approach allowed for a comprehensive characterization of the various factors contributing to flooding vulnerability in the study area. The resulting map provides valuable insights into the level of flood vulnerability in Adama City. The general workflow followed by this study is represented in 2.3.1www.worldpop.org. The dataset was adjusted to match the corresponding UNPD estimate at the country level and had a spatial resolution of 100 x 100-m cell size grids. The study area's map was extracted from the dataset, resampled to 10 x 10-m cell size grids, and reclassified into five classes using the Natural Breaks standard classification scheme in ArcGIS 10.7.1. The categorization assigned values 1 through 5 to different hazard ratings based on increasing population count. Lower population count categories were assigned lower values due to their low susceptibility to flooding, while higher population count categories were assigned higher values due to their high susceptibility as more people living in an area increase exposure to floods [The spatial population distribution of the 2020 population count of the Ethiopia raster dataset was obtained from o floods .www.worldpop.org. The acquired raster dataset was calibrated to conform to the corresponding United Nations Population Division's estimates at the country level, and it possessed a spatial resolution of 1000 × 1000 m cell size grids. Subsequently, the study area was extracted from the dataset and subjected to resampling, whereby the initial grid-cell size was altered to 10 x 10-m cell size grids ArcGIS 10.7.1. Finally, a five-class Natural Breaks standard classification scheme was employed to reclassify the data set, and the outputs were evaluated from 1 (very low) to 5 (very high) population density. Lower population densities indicate a lower susceptibility to flooding, while higher population densities signify increased vulnerability [The population density of Ethiopia for the year 2020 was obtained from rability .www.worldpop.org. With the spatial resolution of 100 x 100-m cell size grids. Then extracted and resampled to 10 x 10-m cell size grids and reclassified into Natural Breaks 1(very low) to 5 (very high) to flooding in ArcGIS 10.7.1. Older people greater than 65 years of age, children less than 5 years, and women are less mobile and need more assistance more vulnerable to flooding [The total number of people in Ethiopia per grid square broken down by gender (women) and age (less than 5 and greater than 65 years) spatial distribution of the year 2020 was obtained from flooding ,69,70.The study area's unemployment population, categorized by age and gender, was obtained from ACA. By applying the "Calculate Density" tool within ArcGIS 10.7.1 and a newly added field in the attribute table, a density map of the study area was generated from input point features. The resulting map was then resampled to 10 x 10-m cell-size grids and classified into five discrete classes based on Natural Breaks at increasing levels of unemployment. Lower unemployment levels indicate less coping with flood risk, while higher unemployment levels highlight heightened vulnerability ,29,71.http://earthexplorer.usgs.gov/) acquired in February 2023 and resampled to 10 x 10-m cell size grids. The spatial analysis tool slope in percentage ranges was developed using ArcGIS, 10.7.1, and a standard classification scheme called Natural Breaks was applied to classify the slope into five classes. The classification considered the susceptibility of the slope to flooding and assigned each value to a specific hazard rating. The susceptibility decreases from the lowest slope category, which was assigned a value of 5, to the highest slope category with a value of 1. The flatter topography, associated with lower slope values, was particularly vulnerable to flooding, whereas steeper topography, represented by higher slope values, was less vulnerable to flooding [The study area's slope map was generated using DEM with 12.5 m size grids, downloaded from ASTER- Global  was utilized to generate the NDVI map. Equation The productivity of the study area was mapped from the Normalized Difference in Vegetation Index (NDVI). A Sentinel 2 A satellite image, acquired from the USGS website  of the study area was derived from the NDVI of the study area. Based on Skougaard Kaspersen, Fensholt , equatioTo map the proximity of ecosystems to potential toxic industries, shapefiles of potential toxic industries were obtained from ACA and analysis tools from ArcGIS 10.7.1 were utilized to create multiple ring buffers within a given distance for the study area. The resulting index was then subjected to a union process to identify all ecosystems that intersect with potentially toxic industries. The obtained map of ecosystems and potential toxic industry locations were then resampled to 10 x 10-m cell size grids and classified into five categories based on Natural Breaks to identify areas at risk of exposure to toxic substances during floods. Ecosystems near toxic industries are more vulnerable to flooding than further areas due to the potential exposure to toxic substances during floods as it exposes nearby communities to toxic chemicals and hazardous waste ,78.To map the index and average patch size of the study vegetation layer from ACA were derived and digitized to update the layer digitizing based on field visit and high-resolution Google Earth Pro-Satellite imagery (Google Earth Pro_Version 7.3.6). Then, patch sizes of vegetation layers were classified based on their area. Then resampled to 10 x 10-m cell size grids and classified into five classes based on Natural Breaks in ArcGIS 10.7.1. The size of the patches determines areas that are vulnerable to flooding. Smaller patches indicate areas that are more fragmented and less able to provide ecosystem services that help mitigate flood impacts ,80.The bare soil raster dataset was obtained from the Water and Land Resource Center (WLRC), Ethiopia, and the wetland of the study area was obtained from ACA. Then, resampled to 10 x 10-m cell size grids and computed into percentages in ArcGIS 10.7.1. Bare-soil areas are more vulnerable to flooding due to their low infiltration capacity and high erodibility  and wherhttps://livingatlas.arcgis.com/Land cover/(acquired in February 2023) with 10 x 10-m cell size grids. Then, computed into percentages in an ArcGIS 10.7.1 environment. Built-up areas are more vulnerable to flooding due to their inability to percolate water into the subsurface, which makes the area more vulnerable [The built-up area of the study area was extracted from an ESRI website: lnerable .A road density map was created using a road shapefile acquired from ACA, with any missing data supplemented by digitizing based on field visits and high-resolution Google Earth Pro-Satellite imagery (Google Earth ProVersion 7.3.6). Kernel line density tools were utilized to derive linear feature density, which was then resampled to 10 x 10-m cell size grids and classified into five classes based on Natural Breaks. High road density increases the risk of flooding by reducing the area available for water to infiltrate and increasing the speed of runoff ,84. A grCritical infrastructure  that affect public health and safety shapefiles were obtained from ACA was obtained from ACA and analysis tools from ArcGIS 10.7.1 was utilized to create multiple ring buffers within a given distance for the study area. The resulting map was then resampled to 10 x 10-m cell-size grids and classified into five classes based on Natural Breaks. Critical infrastructure such as toxic industries, landfill sites, abattoirs, and gas terminals are exposed to floods and important to identify the areas from the point sources .Emergency centers  shapefiles were obtained from ACA and updated the missing emergency centers through digitizing based on field visits and high-resolution Google Earth Pro-Satellite imagery (Google Earth Pro version 7.3.6). Then, analysis tools from ArcGIS 10.7.1 were utilized to create multiple ring buffers within a given distance for the study area. The resulting map was then resampled to 10 x 10-m cell-size grids and classified into five classes based on Natural Breaks. Emergency centers such as hospitals, schools, and universities play a critical role in assisting the community during floods and serve as emergency response sites ,91.2.3.2The AHP techniques developed by Saaty  were useAHP analysis was implemented to quantify the comparative significance of flood-controlling variables. In this process, a matrix of pairwise comparisons was computed , followe1.The matrix of pair-wise comparisons is constructed based on Saaty's 1 to 9 scale, where each variable was represented in 2.Then, each entry in the given matrix of pair-wise comparisons column was divided by its corresponding sum refer to 3.Finally, each weight was determined by dividing the total of each line in the normalized matrix by eighteen refer to .As suggested by Saaty  the succAfter calculating the weights of each variable related to flood vulnerability characterization, a consistency index check was computed using equation 1.Multiplying each column value  by the weight criteria2.The rows' values are added to calculate the weighted sum3.Weighting each criterion value based on its weighted sum value, and4.A weighted sum of the mean concerning the criteria weights.The following steps were used to compute the maximum Eigenvalue (λmax) of the comparison pair-wise matrix .1.MultipThen, the calculated consistency ratio (CR) which demonstrates the validity of Saaty  comparisAccording to Saaty , if the 2.3.3FP’ denotes flood vulnerability, ‘n’ is the number of decision-making criteria, ‘Xi’ is the specific normalized criterion, and ‘WI’ is the criterion's weight.To develop the flood vulnerability map of the study area, all the selected SET variables were geo-referenced with the same coordinate system of WGS_1984_UTM_Zone_37 N, resampled to 10 x 10-m cell size grids, reclassified, and weighted via Analytic Hierarchy. Afterward, ArcGIS's Spatial Analyst extension's weighted overlay technique was employed, with Equation 2.3.4Global Moran's I to identify if the spatial patterns of flood vulnerability were clustered, dispersed, or random in ArcGIS 10.7.1 Moran's I value close to zero indicates random spatial distribution, while positive and negative values indicate clustering (similar neighborhoods are next to each other) or dispersed (dissimilar neighborhoods are next to each other) spatial patterns, respectively ,98.2.3.5Validation is a crucial step in ensuring that model outputs accurately portray real-world conditions on the ground. For this study, field-based visits and interviews with local dwellers were conducted both before and after modeling to enhance understanding and precision. In addition, ACA experts were interviewed, and historical flood inundation data were cross-checked with satellite imagery from Google Earth Pro Version 7.3.6. Furthermore, the final SETS map was compared with 120 Ground Control Points (GCPs) collected using a handheld Global Positioning System (GPS) device (Model: BHCNav6). The GCPs were then converted to shapefiles, overlaid onto the final SETS map on ArcGIS version 10.7.1 for verification, and proved the model precision.2.4The Social-Ecological-Technological (SET) approach to urban flood vulnerability assessment has been proven as a comprehensive method that utilizes multi-criteria decision-making techniques. However, this approach has certain limitations, such as the absence of climate change projections and scenarios, uncertainty, and risk perception.33.1The eighteen SET variables with their unit, classes, flood susceptibility, rating values, and weight of the study area as analyzed using ArcGIS 10.7.1 Multi-Criteria Decision-Making and Analytical Hierarchy Process is presented in The spatial distribution of the population count in the study area is represented as rasterized data, which varies between 0.45 and 151.39. The data is divided into five categories based on these values: 0.45–8.73 (very low), 8.73–35.36 (low), 35.36–74.40 (medium), 74.40–109.31 (high), and 109.31–151.39 (very high). These categories cover 78.96 %, 11.75 %, 2.64 %, 3.33 %, and 3.32 % of the population respectively, as shown in The population density of the study area ranges from 56.81 to 17,998.16 and is categorized into five classes 56.81–1323.26 (very low), 1323.26–4207.94 (low), 4207.94–8288.72 (medium), 8288.72–12,791.64 (high) and 12,791.64–17,998.16 (very high) which covers 79.53 %, 9.38 %, 4.16 %, 3.18 %, and 3.75 %, as shown in The population of children less than five years was ranges from 0.04 to 2.25 and categorized into five classes 0.04–0.25 (very low), 0.25–0.58 (low), 0.58–1.00 (medium), 1.00–1.43 (high), and 1.43–2.25 (very high) which covers 54.37 %, 18.37 %, 9.18 %, 10.67 %, 7.41 %, as indicated in The population of people greater than 65 years was ranges from 0.02 to 1.17 and categorized into five classes 0.02–0.12 (very low), 0.12–0.30 (low), 0.30–0.52 (medium), 0.52–0.75 (high), 0.75–1.17 (very high) which covers 54.95 %, 17.99 %, 9.06 %, 10.73 %, and 7.26 % respectively, as indicated in The women population of the study area ranges from 0.0094 to 0.59 and is categorized into five classes 0.0094–0.062 (very low), 0.063–0.15(low), 0.16–0.26 (medium), 0.27–0.38 (high), and 0.39–0.59 (very high) which covers 55.17 %, 17.75 %, 8.84 %, 10.69 %, and 7.55 %, as indicated in The unemployment population density of the study area ranges from 0.03 to 31.45 and is categorized into five classes 0.03–0.15 (very low), 0.15–4.22 (low), 4.22–11.49 (medium), 11.49–18.26 (high), and 18.26–31.45 (very high) which covers 63.9, 28.05, 5.98, 1.65, and 0.43, as indicated in The slope of the study area was classified into five classes 0–3.14°(very high), 3.14–7.12°(high), 7.12–13.21°(medium), 13.21–22.21°(low), and 22.22–53.42°(very low) which covers 2.08 %, 5.32 %, 14.38 %, 38.21 %, and 40 % of the total area, as indicated in The Proximity of the ecosystem to toxic release areas was classified into five classes 1–3 (very low), 3–4 (low), 4–5 (medium), 5–6 (high), and 6–7(very high) which covers 21.4 %, 23.51 %, 19.43 %, 24.84 %, 10.82 % respectively, as indicated in The combination of shape index and average patch sizes are categorized into five classes 0.0034–22.77 (very high), 22.77–50.90 (high), 50.91–99.13(medium), 99.13–136.64 (low), and 136.65–341.61 (very low) which covers 42.76 %, 18.95 %, 14.26 %, 10.87 %, and 13.16 %, as shown in The percentage of the bare soil in the study area accounted for 2.3 % (718.74 ha) as indicated in The productivity-based NDVI of the study area was classified into five classes −0.16 - 0.098 (very high), 0.099–0.13 (high), 0.14–0.16 (medium), 0.17–0.23 (low), and 0.24–0.46 (very low), which covers 7.54 %, 39.66 %, 38.68 %, 11.74 %, and 2.38 % of the study area respectively, as shown in Critical Infrastructures of the study area were buffered and categorized into five classes <100 m (very high), 100–500 m (high), 500 - 1000 m (medium), 1000–3000 (low), and >3000 (very low) which covers 3.41 %, 10.34 %, 13.54 %, 44.28 %, and 28.44 % respectively, as indicated in Road density of the study area was classified into five classes 0–2.07 (very low), 2.07–6.31(low), 6.31–12.86 (medium), 12.87–19.41(high), and 19.41–29.28 (very high) which covers 50.86%, 26.97 %, 7.13 %, 6.86 %, and 8.18 % of the study area respectively, as shown in The fractional impervious surface of the study area is classified into five classes −0.0000012 - 0.61(very low), 0.62–0.77(low), 0.78–0.87(medium), 0.88–0.92 (high), and 0.93–1 (very high) which covers 0.67 %, 2.21 %, 8.86 %, 34.29 %, and 53.97 % respectively, as shown in The green infrastructure density of the area was classified into five classes 0–26.57(very high), 26.57–75.64(high), 75.64–145.15 (medium), 145.16–265.77(low), and 265.78–521.31(very low) which covers 60.42, 22.74, 11.28, 4.36, and 1.2 respectively, as shown in Emergency centers  of the study area buffer were classified into five classes <500 m (very low), 500–1500 m (low), 1500–2500 m (medium), 2500–5000 m (high), and >5000 m((very high) which covers 15.86 %, 21.89 %, 22.73 %, 32.41 %, and 7.11 % respectively, as shown in 3.2The weight for all SET variables was taken into consideration as demonstrated in According to the social vulnerability map of the study area, approximately 28.32 % of the total area is moderate to very highly vulnerable to flooding, with 5.16 % (478.55 ha) as very high, 12.26 % (1136.35 ha) as high, 10.9 % (1010.55 ha) as moderate, 18.58 % (1722.36 ha) as low, and 53.11 % (4923.62 ha) as very low. The vulnerable area is located in the central part of the city, including Badhatuu, Odaa, Gurmuu, Dhadacha Araara, Abba Gadaa, Barreecha, Biqqa, Caffee, and Dagaaga, which are densely populated areas where a majority of the residents are women, children under five years, elderly over 65 years, and unemployed individuals. These findings were illustrated in The ecological vulnerability map of the study area revealed that a significant percentage of the land is vulnerable to flooding. Specifically, 4.18 % is very highly vulnerable, 38.95 % is highly vulnerable, 50.9 % is moderately vulnerable, 5.85 % is lowly vulnerable, and 0.11 % is very lowly vulnerable. This indicates that an overwhelming majority of the total area (about 94.03 %) is susceptible to flooding, particularly in the densely urbanized regions characterized by flat terrain, proximity to toxic sites, smaller fragmented patches, bare soil areas, and less productive areas. These regions, which include Migiraa, Dagaaga, Dhadacha Araara, Gaara Luugo, and Irreechaa areas, are represented in The technological vulnerability map of the study area revealed that 14.94% (4655.28 ha) is high, 77.17 % (24046.26 ha) is moderate and 7.88%(2456.69 ha) is low vulnerable to flooding. This implies that about 92.11 % of the area is technologically vulnerable to flooding. This area is characterized by most built-up areas, less availability of critical infrastructures, high road density, less impervious areas, and less green infrastructure density areas. These areas are all part of Dagaaga, Odaa, Badhatuu, Gurmuu, Abba Gadaa, Barreecha, Biqqa, and parts of Gaara.Luugo, Migiraa, Irreechaa, and Gooro as shown in According to the study's SET vulnerability map of the study area, flooding vulnerability levels varied across different neighborhoods. Specifically, 67.3 ha or 0.73 % of the area was identified as very highly vulnerable, while 2307.7 ha or 24.94 %, 3924.55 ha or 42.41 %, 2954.81 ha or 31.93 %, and 0.38 ha or 0.004 % were identified as high, moderate, low, and very low vulnerable, respectively. These findings indicate that approximately 68.08 % of the study area is at moderate to very high risk of flooding. In particular, local neighborhoods such as Dagaaga, Badhatuu, Odaa, Gurmuu, Abba Gadaa, Barreecha, Biqqa, and Dhadacha Araara were found to be among the most vulnerable (very high-to-high), while surrounding areas were deemed highly vulnerable to flooding. Factors contributing to this vulnerability include densely built environments, limited vegetation cover, high population density, proximity to toxic waste sites, unemployment, and fewer impervious surface areas, as illustrated in 3.2.1According to the Global Moran's I summary, all SETS vulnerability maps exhibit clustering and positive autocorrelation , as evidA clustered spatial pattern in Global Moran I for flood vulnerability indicates that areas with high flood vulnerability tend to be clustered together, and this has important implications for the allocation of resources and mitigation strategies. Understanding the clustering of different areas can aid in prioritizing interventions and allocating resources effectively to mitigate flood vulnerability. This information is depicted in 4Analyzing urban flooding complexities through the SETS approach is essential as it examines interdependencies between social, ecological, and technological systems that escalate flood vulnerability of residents in flood-prone areas due to changes in land use, hydrology, population, economic growth, and climate ,20,69. DThe vulnerability of floods was also heightened in locations, where depressed and flat areas are prevalent, proximity to toxic release sites from industries, smaller and fragmented patches, and bare soil areas. Those areas were found within the study area locally known as Migiraa, Dagaaga, Dhadacha Araara, Gaara Luugo, and Irreechaa areas. This study supports the findings of prior research indicating that flatter topographies are prone to flooding and have lower slope values . VegetatAreas characterized by most built-up areas, less availability of critical infrastructures, high road density, less impervious areas, and less green infrastructure density areas which are located in the neighborhoods of Dagaaga, Odaa, Badhatuu, Gurmuu, Abba Gadaa, Barreecha, Biqqa and parts of Gaara Luugo, Migiraa, Irreechaa, and Gooro are vulnerable to flooding. This finding is consistent with previous studies done in different urban areas . The inaThe presence of high fractions of impervious surfaces and dense road networks also exacerbate the risk of floods by impeding water infiltration and accelerating surface runoff ,83. ConsThe study reveals that the area characterized by a lower density of green infrastructure also faces increased susceptibility to flooding. This poses a hindrance to infiltration processes and exacerbates runoff. These findings further support a previous study, conducted by Khodadad, Aguilar-Barajas  and PallAccording to the findings of the present study, certain areas close to critical infrastructure such as toxic industries, landfill sites, abattoirs, and gas terminals face a significant vulnerability to flooding, thus posing a threat to the local community. This finding aligns with previous studies conducted by Murdock, De Bruijn , Qiang , Lin, Wu5This research highlights the significance of applying the SETS framework to characterize the flood vulnerability of urban areas such as Adama City. The findings indicated that vulnerability to flooding across the SETS domains follows a clustered distribution pattern. Moreover, the study identified spatial correlations between S-E, S-T, and E-T vulnerabilities, indicating opportunities to enhance flood mitigation measures in multiple domains simultaneously. This research can provide insights into developing more effective flood vulnerability reduction strategies in Adama City and other urban areas facing similar challenges.The study explored the implications of sustainable urban development, with specific emphasis on exposure, sensitivity, and adaptability to flood vulnerability. The findings of the research have significant implications for cities undertaking sustainable urban development. Based on the SET vulnerability map developed for the study area, it was observed that the levels of vulnerability to flooding differed among various neighborhoods. The results highlighted that approximately 68.08 % of the study area was exposed to moderate to very high flood vulnerability, necessitating immediate attention and mitigation efforts. By utilizing the SETS framework, a better understanding of the interconnectivity between environment, infrastructure, and equitable distribution of hazards within society was gained, which is critical in achieving sustainable urban development. The relevance to other developing cities is that by applying the SETS framework initially tested in Adama City, municipalities can benefit from these findings and evaluate their flood vulnerability status. As flooding is spatially confined to specific areas, municipal administrators and practitioners can effectively target vulnerable neighborhoods to adapt to flooding. Ultimately, this study provides insights into an improved understanding of the complex nature of sustainable urban development, particularly regarding natural hazard management. Additionally, this study also helps to ensure that the SETS frameworks to tailored to the specific needs and concerns of each community, reflecting their unique circumstances and priorities.No additional information is available for this paper.Bikila Merga Leta: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Validation, Writing – original draftWriting – original draft, Writing – review & editingWriting – review & editing. Dagnachew Adugna: Supervision, Validation, Writing – review & editingWriting – review & editing.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.