No platform for objective, synchronous and on-line evaluation of both intraoperative error and surgeon physiology yet exists. Electrokardiogram (EKG) metrics have been associated with cognitive and affective features that are known to impact surgical performance but have not yet been analyzed in conjunction with real-time error signals using objective, real-time methods.EKGs and operating console point-of-views (POVs) for fifteen general surgery residents and five non-medically trained participants were captured during three simulated robotic-assisted surgery (RAS) procedures. Time and frequency-domain EKG statistics were extracted from recorded EKGs. Intraoperative errors were detected from operating console POV videos. EKG statistics were synchronized with intraoperative error signals.P = 3.25e−05), 3.08%  and 1.19% , respectively, during error. Relative LF RMS power decreased 1.44% , and relative HF RMS power increased 5.51% .Relative to personalized baselines, IBI, SDNN and RMSSD decreased 0.15% (S.E. 3.603e−04; Use of a novel, on-line biometric and operating room data capture and analysis platform enabled detection of distinct operator physiological changes during intraoperative errors. Monitoring operator EKG metrics during surgery may help improve patient outcomes through real-time assessments of intraoperative surgical proficiency and perceived difficulty as well as inform personalized surgical skills development.The online version contains supplementary material available at 10.1007/s00464-023-09957-0. Understanding the relationship between operator physiology and performance during robot-assisted surgery (RAS) has the potential to improve operating outcomes, surgical education, training, and skills assessment –3. Time Prior works examining EKG statistics in the context of surgical performance typically consist of retrospective analyses that often aggregate physiological metrics over the entire surgical procedure and use manual rating schemes to characterize per-procedure surgical performance. For example, Langelotz et al. associated perceived stress levels in surgeons during a 24-h shift with heart rate variability (HRV) metrics  while BoThe aim of this study is to analyze intraoperative time and frequency domain EKG statistics of operators participating in RAS simulation using automated annotation of surgical videos for performance metrics. Changes in EKG metrics are compared relative to personalized baselines during periods of operator error to those captured during periods of no error. These differences are then analyzed to examine the differences in EKG statistics for high and low-performing operators during error. It is hypothesized that changes in EKG metrics relative to baseline will be significantly different during error compared to no error and that changes in relative EKG metrics during errors would differ across levels of performance.Twenty participants were recruited for this study under institutional IRB approval. Of these participants, 5 were non-medical graduate students and the remainder were general surgery residents at various levels of training Table . All parThe da Vinci Xi robotic system console  with the da Vinci Skills Simulator (DVSS) software  was used for this study. The operator’s point-of-view (POV) video from the DVSS was recorded using a video capture card with a recording rate of 30 frames-per-second (fps). For EKG recording, we used a Polar H10 (Polar Inc.) chest-strap monitor with a sampling rate of 130 Hertz (Hz).Each participant completed three simulation tasks during a single sitting without breaks. These tasks were completed in the same order for all participants. The tasks utilized were “Ring Rollercoaster 1,” “Ring Rollercoaster 3,” and “Wrist Articulation 1” in this order for all participants.A Polar EKG monitor was fitted on each participant prior to beginning the first task and checked for appropriate positioning and data transfer. Four minutes of baseline EKG readings were then recorded as each participant sat still at the operating console. Following baseline recording, each participant was directed to start the first surgical simulation task and given no other instruction. After completion of the first task, each participant was directed to start the second simulation, also without additional instruction or feedback. After completion of the second simulation, each participant was directed to start the third and final simulation, also without additional instruction or feedback. Following completion of the final simulation, each participant was instructed to complete a demographics survey after which the EKG monitor was removed and the system was reset for future participants.Both the video data stream and the EKG data stream were recorded on the same external computer. Operator POV videos were captured at a frame rate of 30 fps. Each frame was programmatically annotated for the presence or absence of error using pixel-based frequency and intensity filters, Hough transforms, and canny edge detection. Frame-by-frame error annotation provided 30 Hz resolution for intraoperative error.EKG data was captured at a sampling rate of 130 Hz. Interbeat interval (IBI), standard deviation of N–N interval (SDNN), root-mean-square successive differences in N–N interval (RMSSD), low frequency (LF) signal (0.04–0.15 Hz), and high frequency (HF) signal (0.15–0.40 Hz) features were calculated from raw EKG data . SDNN anLF and HF signal components were isolated from raw data using Butterworth bandpass filters with cascaded second-order sections and passbands of (0.04–0.15 Hz) and (0.15–0.40 Hz), respectively. LF and HF signal powers were calculated using root-mean-square (RMS) amplitude.Data streams were synchronized using Lab Streaming Layer . For simIBI reflects the amount of time between successive heart beats Fig. . A decreIncreases in SDNN are associated with increased vagal tone and therefore increased PANS activity . Vagal tLF power Fig.  is an inEKG metrics relative to individual baselines were associated with intraoperative errors using separate linear mixed effects models for each metric. Intraoperative errors were modeled as a fixed effect and individual participant variance as a random effect. Identically structured models were used for each relative frequency-domain metric .All participants were assigned to either a high, middle or low performance group based on the sum total of their simulation scores for all three tasks Table . SimulatHigh Performer and Low Performer groups were analyzed separately. For each group, the association between relative time-domain  EKG metrics and intraoperative error were modeled using separate linear mixed effects models for each time-domain metric. Intraoperative error was modeled as a fixed effect and individual participant variance as a random effect. Identically structured models were used for each relative frequency-domain metric .To compare High Performer and Low Performer group physiology during intraoperative error, separate linear mixed effects models were used for all relative time and frequency-domain metrics. Group membership was modeled as a fixed effect using Low Performer as reference level, and we modeled participant level variance as a random effect.P = 0.01. Given a total of 20 independent tests in this study, we conservatively corrected our significance level by a factor of 20 to P = 0.0005.We independently tested all 5 EKG metrics  for all 4 groupings . Our uncorrected significance level was P = 3.25e−05) during error as compared to no error. Relative SDNN decreased 3.08% , and relative RMSSD decreased 1.19%  during error as compared to no error. Relative LF RMS power increased 1.44% , and relative HF RMS power increased 5.51%  during error as compared to no error  and 5.8% , respectively, during error as compared to no error while relative IBI showed no significant change. Relative LF and HF RMS powers increased 1.1%  and 3.4% , respectively, during error as compared to no error  during error as compared to no error while relative SDNN and relative RMSSD increased 2.4%  and 3.5% , respectively. Relative LF and HF RMS powers increased 2.6%  and 6.6% , respectively, during error as compared to no error  and all relative frequency-domain metrics (LF and HF RMS power) demonstrate significant changes during error as compared to no error. The direction of these changes largely aligns with proposed associations between EKG statistics and cognitive or affective determinants of surgical performance. Decreases in relative IBI, SDNN, and RMSSD, and increases in relative LF RMS power during intraoperative error may reflect an increase in operator stress and mental workload as well as a more negative affective state. The increase in relative HF RMS power during intraoperative error, however, may suggest a decrease in stress, panic, anxiety or worry .For high performers, decreases in relative SDNN and RMSSD associated with intraoperative error are possibly reflective of greater stress, mental workload and negative valence. However, increases in relative LF RMS power, indicative of higher stress and workload, were of smaller magnitude than increases in relative HF RMS power. HF RMS power is reported to be indicative of lower anxiety or worry . For Lowduring error for high as compared to would benefit from further investigation in a higher-powered group comparison. Given the relatively small magnitude of differences in the error compared to no error analyses, detecting even smaller magnitude differences in error compared to error across two groups would benefit from a larger cohort size.In the previous group analyses, EKG statistics during error were compared to those during no error, and the differences between error and no error were of sufficient magnitude to be detected. Examination of the differences in relative IBI and HF RMS There are several limitations of this study. First, the number of participants was neither large nor evenly distributed across skill level, potentially skewing cohort analysis. Second, the use of trailing 30 s windows for SDNN and RMSSD statistics implies that the metrics associated with a particular time point reflect cardiac activity for the entire 30 s up to and including that time point. Third, using bandpass filters and RMS power calculations for frame-by-frame LF and HF power measurements are accompanied by a tradeoff in the settling time of the filter. Fourth, we do not exclude individuals on chronotropic or inotropic medications nor do we correct for the effect of these medications. While this may impact our results, all reported EKG statistics are analyzed relative to each individual participant's personalized baseline EKG. As these baseline characteristics are captured immediately prior to the simulation tasks, the effects of medication are likely to be consistent across both baseline and simulation EKG recording periods. Finally, these results may be affected by other variables such as movement at the console and time at the console. Based on our observations, low performers tended to move and shift body positions more frequently than high performers, potentially indicative of discomfort at the console. Low performers also required more time to complete the simulation tasks.Despite these limitations, this study shows that a novel, on-line operating room data capture and analysis platform can enable the detection of distinct physiological changes associated with intraoperative error. These changes are largely consistent with known relationships between EKG metrics and cognitive or affective factors that impact performance . While tSupplementary file1 (MP4 17463 KB)Below is the link to the electronic supplementary material.


The effect of botanical origin, the flour particle size, and the content of damaged starch on flour pasting properties, dough behavior during a uniaxial deformation test, and bread characteristics were evaluated on rice and buckwheat flours. The rice flour with a median particle size D(0.5) of 60.2, 70.6, 106.8, and 189.4 μm, and buckwheat flour with a D(0.5) of 56.4, 68.4, and 95.8 μm were prepared using the same milling technology. The botanical origin of the flours was the strongest factor influencing the flour pasting properties, stress accumulated in dough during the uniaxial deformation test, loaf characteristics, texture, and sensory characteristics of breads. The flour particle size significantly influenced mainly the flour pasting properties. The effect of the content of damaged starch was the weakest among the studied factors. The flour particle size and the content of damaged starch were closely related. The flour botanical origin was the strongest factor; therefore, it seems not to be possible to predict the bread-baking potential of gluten-free flours based on the results obtained for flour of a different botanical origin. More research on flours from different plants prepared by the same milling process is required to support this hypothesis. The impact of flour particle size on flour, dough, and product quality has been studied by many authors. The studies were focused mainly on wheat flour, since it is often used in bread, pastry, cookies, and noodles. Wheat flour granulation was found to significantly impact flour properties ,2.The increasing demand for gluten-free products brought the need to also study the relation between flour particle size and bread quality in gluten-free flours. Some of the results obtained on wheat flour were found to also be applicable to rice and maize flour. Fine flour has higher damaged starch content ,4 and exRice and buckwheat flours were involved in this study, since rice flour is one of the most used flours in the production of gluten-free bread. This flour exhibits several significant properties, such as bland taste, colorlessness, and hypoallergenic characteristics. A low level of protein, sodium, fat, and fiber and a high amount of easily digestible carbohydrates were also reported ,10. BuckThe aim of this study was to prepare rice and buckwheat flours of similar particle sizes using the same milling procedure. The pasting properties, dough behavior, and characteristics of bread prepared from rice and buckwheat flours were tested and compared. The effects of the flour botanical origin, particle size, and content of damaged starch on flour, dough, and bread parameters were evaluated, and their significance was compared. White rice  and buckwheat seeds with a removed hull  were bought in a local supermarket. Rice and buckwheat were in the form of a commercial blend. Information about the varieties used in the blends was not available. The same milling procedure was applied to the rice and buckwheat seeds. The seeds were grounded using a pin mill . The obtained flour was sifted to separate the flours with different granulations. The flours were vacuum-packed in polyethylene bags and stored at 4 °C before testing. The following sample abbreviations were used for rice flours: R60, R70, R100, and R200. For buckwheat flours, B60, B70, and B100 were used. The number in the flour names indicates the rounded-up value of the flour median particle size D(0.5).Flour particle size distribution was determined with light scattering using laser granulometry , as described in Berton et al. , assuminThe chemical composition of the flours was determined according to the ISO 1871, ISO 11085, and EN ISO 10520 ,18,19 stThe level of damaged starch was determined using a Megazyme kit  according to the method AACCI N° 76-31.01 . The resThe flour samples were coated with a 2 nm layer of gold using a Q150R Plus Rotary Pumped Coater  to improve their electrical conductivity. Images were taken by Tescan Vega3-SBU  using backscattered electrons at the accelerating voltage of 10 kV and 800× magnification.30η, pasting temperature 0T, peak viscosity Peakη, final viscosity Finalη, Breakdown, Total Setback, and Setback region were determined according to Balet et al. [HAAKE RheoStress 1  was used for assessing the pasting properties of the flours. The suspension was prepared from flour (6.0 ± 0.1) g and water (30.0 ± 0.1) g. The rotation temperature ramp was performed using coaxial cylinders Z34 DIN Ti with a gap of 7.2 mm. The viscosity of samples was measured over a given period, during which the sample was being stirred. The profile of the test was: the addition of water to the flour sample, holding at the temperature of 30 °C for 120 s, heating to 90 °C for 220 s, holding at 90 °C for 300 s, cooling to 40 °C for 220 s and holding at 40 °C for 120 s. The suspension was stirred at 160 rpm during the test . Each teMσ and peak Hencky strain HMε were used to describe dough behavior. Each test was performed on dough samples prepared in at least six replicates. The given results are represented as mean values.Dough samples were prepared according to the formula used in bread making see , excludiBreads were prepared according to the previously published method . The douTexture profile analysis (TPA) of bread crumbs was performed on TA.XT plus texture analyzer  according to a previously published method . A 75.0 The sensory attributes of bread were evaluated by 5 panelists trained according to ISO 8586-1 . The pant-test on a 0.05 level. The statistical analyses were performed using Statistica 13.0 .The results were statistically analyzed using analysis of variance (ANOVA). The differences between samples were tested on a 0.05 significance level using the Tukey test. Parameter dependency was tested using a Wilcoxon test and Four rice flours  and three buckwheat flours  were collected during the milling process . The porThe content of starch was higher in fine flours . The conp < 0.05). The level of damaged starch was probably impacted by the different behavior of buckwheat and rice grains during grinding. During the milling process, seeds were subjected to various forces, making them break up into smaller particles. A certain portion of starch granules were loosened from the protein matrix and remained undamaged. During rice milling, the granules were separated mainly in R60 flour (The content of damaged starch varied from 5.9% to 13.3% in the rice flours and from 1.2% to 3.4% in the buckwheat flours . This pa60 flour a. They w60 flour b–d. They60 flour e–g. Howep = 0.13). The effect of the content of damaged starch was weak (p = 0.57) and was observed mainly in rice flours. A wider difference in the content of damaged starch in rice flours than in buckwheat flours may be a possible explanation.Water absorption was influenced by flour botanical origin , the content of damaged starch (p = 0.001), and flour particle size (p = 0.001). The slurries with buckwheat flours exhibited significantly higher viscosity 30η than slurries containing rice flours  in rice and buckwheat flours  during the initial phase. The effect of damaged starch was also significant (p = 0.027). The viscosity started to rise when the temperature T0 of the slurry reached (50–66) °C. Peak viscosity Peakη varied between (91 and 472) mPa·s and final viscosity Finalη between (163 and 540) mPa·s. The differences between slurries with rice and buckwheat flours observed in η0 values disappeared during the heating phase of the test, which may be related to a more rapid increase of viscosity recorded in the slurry with rice flours. Temperature T0, peak viscosity, and final viscosity generally declined with increasing content of damaged starch. According to Barrera, gelatinized damaged granules are probably broken more easily and are more deformable than less damaged granules. Therefore, damaged starch granules do not fully contribute to viscosity increment during slurry heating [The effect of flour botanical origin was significant during the heating phase of the test, but less so . This parameter generally rose with increasing median particle size. A similar relation was observed by Ma et al. [p = 0.001). These parameters were higher in slurries with buckwheat flours and in slurries with fine flours. The setback region decreased with increasing flour particle size, which corresponds to previously published results [The breakdown was significantly impacted by flour particle size , flour particle size (p = 0.001), and the content of damaged starch (p = 0.006). The comparison of the flours of similar median particle size indicates that rice doughs exhibited a generally higher ability to accumulate stress during the uniaxial elongation test than buckwheat doughs . The effect on baking loss (p = 0.002) and crumb cohesiveness (p = 0.046) was weaker. Buckwheat bread exhibited higher loaf-specific volume, springiness, cohesiveness, and chewiness than bread made from rice flours , chewiness (p = 0.010), and springiness (p = 0.020). These parameters rose with the increasing particle size in the rice flours, which had a detrimental impact on bread quality. A similar negative effect of coarse rice flour on breadcrumb hardness was previously observed by Qin et al. [Flour particle size significantly influenced crumb hardness  and baking loss (0.032). Both parameters rose with the decreasing level of damaged starch. High loaf volume is associated with high-quality bread. The effect of damaged starch on loaf volume may be expected due to a known impact of damaged starch on dough viscosity. Optimal viscosity is necessary to trap leavening gas in the dough. Damaged granules gelatinized during baking were probably broken more easily and did not fully contribute to viscosity increment during heating [The content of damaged starch significantly impacted loaf-specific volume . Larger-sized pores and homogeneous porosity were observed in bread from the R100 and B100 flours  was significant. Flour particle size mainly influenced the pasting properties of the flour. The effect of the content of damaged starch was the weakest among the studied factors. Moreover, flour particle size and the content of damaged starch were closely related.The sensory attributes of bread were strongly influenced by flour’s botanical origin. The effect of the other factors was marginal. Sensory characteristics determine if the bread is acceptable to consumers. Therefore, flour botanical origin is the strongest and most important factor influencing the bread-making potential of gluten-free flours. Moreover, it seems to not be possible to predict the bread baking potential of gluten-free flours based on the results obtained for flours of different botanical origins. More research on flours from different plants prepared by the same milling process is required to support this hypothesis.


Our previous studies have reported the effect of swietenine (a major bioactive component of Swietenia macrophylla seeds) in reversing and potentiating the effect of metformin in hyperglycemia and hyperlipidaemia in diabetic rats. Moreover, we reported that the anti-inflammatory effect of swietenine is mediated via the activation of nuclear factor erythroid 2-related factor 2 (Nrf2). This study evaluated the effect of swietenine and its mechanisms in nonalcoholic fatty liver disease (NAFLD) in high-fat diet/streptozotocin-induced diabetic mice. The effect was assessed by determining blood biochemical parameters , asparate transaminase (AST), alkaline phosphatase (ALP), glutathione (GSH), total antioxidant capacity (TAC), and malondialdehyde (MDA)) and liver biochemical parameters . Hepatic lipid accumulation  was determined by oil-O-red staining. Gene expression (qPCR) and immunohistochemical studies were performed to elucidate the mechanism of swietenine’s effect in NAFLD. The critical regulators (genes and proteins) involved in lipogenesis  and oxidative stress  pathways were determined. In mice fed with a high-fat diet followed by streptozotocin injection, the liver cholesterol, triglycerides, and lipids were elevated. These increases were reversed by the oral administration of swietenine, 80 mg/kg body weight, on alternate days for eight weeks. Gene expression and immunohistochemical studies showed that swietenine reversed the elevated levels of crucial enzymes of lipogenesis  and their master transcription factors (SREBP1c and ChREBPβ). Furthermore, swietenine activated the Nrf2 antioxidant defense mechanism, as evidenced by the upregulated levels of Nrf2, NQO-1, and HO-1. It is concluded that swietenine shows beneficial effects in diabetes-induced NAFLD via inhibiting lipogenesis and activating the Nrf2 pathway.  The liver plays a central and crucial role in regulating glucose metabolism , fatty aIn diabetes, glycolysis provides carbons for de novo lipogenesis, which is under the control of various enzymes ,28,29; ASwietenia macrophylla seeds are used in traditional medicine to treat diabetes, and the bioactive compound responsible for the antidiabetic activity is swietenine, a nortetratriterpenoid [S. macrophylla [There is evidence that ethnopharmacology, the scientific exploration of traditional medicinal plants, has provided lead compounds for treating various diseases . In the erpenoid . Many scrophylla ,42,43,44rophylla  and poterophylla . This stm) [Our previous studies reported that swietenine at 40 mg/kg body weight showed a significant reversal of hyperglycaemia and hyperlipidaemia in streptozotocin-induced diabetic rats . C57BL/6m) ,47. The The serum biochemical parameters: glucose, cholesterol, triglycerides, alkaline phosphatase (ALP), asparate transaminase (AST), and alanine transaminase (ALT) were performed on the ‘Siemens Dimension Xpand Plus integrated chemistry system’ with software version 10.1.2  as described in our previous paper . GlutathThe histology of the liver tissues was examined using Oil-O-Red  staining techniques. The Oil O Red stains lipid droplets bright red and is routinely used to determine lipid accumulation in the tissues . The fro®  according to the manufacturer’s protocol. The concentration and purity of RNA were measured using an Ultra-Micro UV Visible Spectrophotometer (TECAN Infinite M200 Pro). RNA samples (100 ng) were dissolved in DNase/RNase-free water . ReverTra Ace® qPCR RT Master Mix Kit was used to synthesize first strand cDNAs according to the manufacturer’s instructions as follows: 37 °C for 15 min, 50 °C for 5 min, 98 °C for 5 min. The qPCR primers used in the present study  were presented in ® qPCR Mix  and an Applied CFX96 Touch Real-Time PCR Detection System . The PCR cycling conditions were 95 °C for 1 min, 40 cycles of 95 °C for 15 s, 60 °C for 25 s, and 72 °C for 45 s. The reference gene, β-actin, was used as a reference gene for the normalization of target gene expression, and the relative expression of genes was determined using the 2−ΔΔCt method [The liver tissues were homogenized in liquid nitrogen, and total RNA was extracted (n = 10 per group) with QIAzolt method .The paraffin-embedded liver tissues were cut into 4-μm thick sections using a rotary microtome and allowed to float on warm water. The immunohistochemistry (IHC) protocol published in the literature elsewhere was followed ,51. The p < 0.05 is considered statistically significant.Results are presented as mean ± standard deviation (SD) of six readings. The difference between the two groups was determined using one-way ANOVA followed by Dunnett’s multiple comparisons tests. GraphPad Prism version 9.0.1 for Windows, GraphPad Software, San Diego, CA, USA, was used for performing the statistical analysis. The effect of Swietnine on serum and liver biochemical parameters is shown in NAFLD is the common cause of chronic liver disease under diabetic conditions. The effect of swietenine treatment on hepatic lipid homeostasis was assessed by quantifying the lipid content using Oil Red O staining. In diabetic mice (D), the neutral fat droplets were significantly increased . Swietenine treatment reversed the elevated levels of neutral fat droplets (from 29.29% ± 5.94 in diabetic mice to 10.30 ± 1.38). The results are shown in Three enzymes, ATP citrate lysase (ACLY), acetyl CoA carboxylase isoform 1 (ACC1), and fatty acid synthase (FASN), are the key enzymes involved in the de novo lipogenesis . The firqPCR and immunohistochemistry studies were carried out to study the effect of swietenine on genes, transcription factors, and proteins involved in de novo lipogenesis. The gene expression study revealed the upregulation genes of three key enzymes  in diabetic mice, and swietenine treatment reversed the elevated levels A–C. The The levels of SREPB1c and ChREBPβ in diabetic mice were 17.07 ± 0.54 and 7.96 ± 0.56, respectively, whereas their levers in swietenine-treated diabetic mice were 9.46 ± 0.19 and 1.90 ± 0.14, respectively. Immunohistochemical studies revealed the upregulation of all three key enzymes  involved in the de novo lipogenesis in diabetic mice, and swietenine treatment reversed the elevated levels . ACLY, AThe transcription factor Nrf2 is a master regulator of adaptive response to oxidative stress and is reported to play a vital role in alleviating NAFLD . The NrfImmunohistochemical studies revealed the levels of Nrf2, NQO-1, and HO-1 in diabetic mice were upregulated , liver cirrhosis and liver cancer. In contrast, NAFLD increases the risk of diabetes development . De novoSwietenia macrophylla seeds are used in folk medicine to maintain health and treat various diseases such as diabetes, hypertension, inflammation, sexual dysfunction etc. [S. macrophylla were developed and are available in the market. Some supplements have received a patent and approval from the Ministry of Health Malaysia https://news.utm.my/ms/2021/04/goswiet-after-7-years-of-research-swietenia-mahagoni-attracted-diabetic-consumer/ accessed on 7 February 2023). Many researchers in Malaysia are researching S. macrophylla seeds to explore their medicinal value. Our survey found that the general public suffering from diabetes consumes S. macrophylla seeds and prescription medicines together. Our previous study showed that swietenine potentiates the effect of metformin in diabetic rats [S. macrophylla seeds, swietenine, we have investigated the activity of swietenine in diabetes-induced NAFLD. Although our studies have shown promising bioactivity, there are limitations in the study design : (1) NAFLD is a multifactorial disease [S. macrophylla seeds either as-it-is or in powder form or capsule form and the seeds contain many bioactive compounds and nutrients in addition to swietenine . Thus, future studies should be focused to determine the effect of whole seeds powder . (4) Since the people consume the seeds and did not report toxic effects, in our opinion, it is not advisable to assume its safety without confirming its safe use scientifically. Thus, detailed safety studies should be carried out to confirm its safe use for therapeutic interventions.ion etc. . Varioustic rats . In conttic rats ,45,74 on disease , and the disease . Thus, fFrom the results of this study, it is concluded that swietenine has shown encouraging beneficial effects in a diabetes-associated NAFLD animal model. Swietenine reversed the hyperglycaemia-induced lipogenesis and oxidative stress. Switenien reversed the elevated levels of blood glucose, cholesterol, and triglycerides in blood and liver, hepatic function markers  in blood, and regulated the oxidative stress markers . The lipogenesis inhibitory activity of swietenine was confirmed using histological studies (Oil-O-Red staining) and gene and protein  expression studies. The ability of swietenine to upregulate the master regulator of oxidative stress (Nrf2) is also confirmed using gene and protein expression  studies. Thus, biochemical, gene expression and protein expression studies have demonstrated the bioactivity of swietenine in diabetes-induced NAFLD. However, future studies should be conducted to determine the bioactivity and pharmacokinetics of swietenine in other NAFLD animal models to confirm the activity of swietenine. The work presented in this paper is the first study reporting the effect of swietenine on NAFLD in diabetic mice and the mechanisms involved.