Simple Laboratory Research Articles

Generative models of complex behavior: A behavioral Turing test. Comment on “beyond simple laboratory studies: Developing sophisticated models to study rich behavior” by Maselli, Gordon, Eluchans, Lancia, Thiery, Moretti, Cisek, and Pezzulo

Generative models of complex behavior: A behavioral Turing test. Comment on “beyond simple laboratory studies: Developing sophisticated models to study rich behavior” by Maselli, Gordon, Eluchans, Lancia, Thiery, Moretti, Cisek, and Pezzulo

Red Blood Cell Distribution Width: A Novel Predictor of Mortality Following Amputation in Diabetic Foot

Category: Diabetes; Other Introduction/Purpose: Red blood cell distribution width (RDW) reflects the degree of heterogeneity of erythrocyte volume. The number of studies investigating the relationship between RDW and various human disorders has exponentially increased over the past decades. However, the association of RDW with diabetic foot amputation has not been evaluated to date. In this study, we assessed the value of RDW as a prognostic factor in diabetic foot amputation. Methods: Data on 415 patients with diabetic foot who underwent amputation between January 2009 and January 2019 were analyzed retrospectively. After establishing optimal cut-off point of preoperative RDW for all-cause mortality, univariable and multivariable analyses with Cox proportional hazard model for survivorship and logistic regression for length of hospital stay more than 30 days were performed to identify significant prognostic factors including RDW, other laboratory results, demographic variables and co-morbidities. Results: RDW cut-off of 14.5% was found to be significantly associated with all-cause mortality (P < 0.001). High RDW was a significant risk factor or all-cause mortality (hazard ratio[HR]: 2.42, 95% confidence interval [CI]: 1.46 to 4.00) on multivariable- adjusted regression analysis. High RDW was also associated with longer hospitalization (odds ratio: 2.17, 95% CI: 1.29 to 3.66). Conclusion: High RDW over 14.5% value is an independent prognostic factor with increased mortality and prolonged hospital stay, implying that RDW may be a simple and inexpensive laboratory parameter for risk stratification in diabetic foot amputation.

Prediction of Smoke Points of Kerosene Distillates Using Simple Laboratory Tests: Artificial Neural Network versus Conventional Correlations

Prediction of Smoke Points of Kerosene Distillates Using Simple Laboratory Tests: Artificial Neural Network versus Conventional Correlations

Temperature-Neutrophils-Multiple Organ Failure Grading as a Prognostic Indicator in Fournier Gangrene.

Background: Severity scoring systems are used widely to predict prognosis in managing various diseases and to tailor the treatment of patients in a personalized way, not in a general concept, by making a risk assessment. This study examines the importance of the Temperature-Neutrophils-Multiple Organ Failure (TNM) scoring system, a new scoring system, in evaluating the prognosis in patients with Fournier gangrene (FG). Patients and Methods: Patients who were operated on with the diagnosis of FG in our clinic between 2012 and 2022 were analyzed with a single-center cross-sectional retrospective study design. Demographic data (age, gender), pre-operative evaluation, body temperature, neutrophil ratio, presence of multiple organ failure, TNM score, and post-operative survival data were recorded. The patients were grouped as those with post-operative hospital mortality (group 1) and without (group 2). Results: The study included 167 patients. Twenty-two (13.2%) of the patients were in group 1 and 145 (86.8%) were in group 2. According to the TNM score, the frequency of stage 3-4 was higher in group 1 than in group 2 (p < 0.001). Patients ≥65 years of age had a 4.80 (95% confidence interval [CI], 1.87-12.29) times greater mortality risk than patients <65. Patients with comorbid disease had a 4.56 (95% CI, 1.47-14.14) times greater risk of mortality than patients without. Patients with TNM scores 3-4 had a 9.38 (95% CI, 3.01-29.28) times greater risk of exit than patients with scores 1-2. Conclusions: The TNM system is a new scoring system that is created quickly using simple laboratory and clinical data in patients with FG and is useful in predicting mortality. Therefore, its clinical use will benefit FG and other deep soft tissue infections.

Accuracy of a Simple Microplastics Investigation Method on Sandy Beaches

Environmental pollution by microplastics (MPs) has become a growing concern, and not only professional researchers but also the citizenry are needed to understand the pollution situation and to confirm the decreasing trend of MP pollution as a result of the global reduction in plastic use. In this study, the author evaluated the accuracy of a simple method of investigating MPs on sandy beaches that can be conducted even by high school students. In a land survey using simple tools such as a tape measure and cardboard, the maximum coefficient of variation is approximately 1%. Even without heavy liquid, 89% of MPs could be recovered using only seawater. An investigation of MP content by sampling 0.5 cm of the surface layer of sand could explain more than half of the MP content when the sand was sampled to a depth of approximately 50 cm below the surface layer. A method in which the recovered MPs are not visually sorted but floating matter after boiling is considered as MPs is acceptable. If there was no concern about pumice contamination, the overestimation was approximately 1.5 times. Simple laboratory equipment such as buckets, sieves, seawater, hot plates, dryers, and electronic balances could achieve lower limits of quantification of MPs of 13 mg-MPs/m2-sand and 2 mg-MPs/kg-sand.

Comparison of a rapid enzymatic assay with column chromatography and nuclear magnetic resonance methods for free asparagine detection and quantification in wheat

A rapid, reliable, and user-friendly method that does not require complex sample preparation and sophisticated instrumentation will fulfill an emerging demand for free asparagine (ASN) analysis to ascertain acrylamide-related food safety issues in baked cereal products. This study validated a new method for wheat free asparagine analysis by comparing a rapid enzymatic test with two established analytical methods: UPLC and 1H-NMR using asparagine standards and whole-wheat flours with a range of free asparagine concentrations. For method validation, various quality parameters were assessed, including accuracy, precision, and sensitivity. Experimental and time costs associated with the analyses were estimated. The rapid test method had consistent accuracy, excellent precision of 1.0 or less (CV%), good sensitivity (0.0389 AU L mg−1) of free asparagine signal detection, and the least cost for experimental materials and instrument usage. A strong correlation (r = 0.997) between the results generated by the rapid enzymatic test and the UPLC method for free ASN quantification in whole-wheat flour was obtained. Overall, the rapid test method is recommended for ASN analysis in simple laboratory environments or in industrial applications.

Tumor-Infiltrating Lymphocytes and Tumor-Stroma Ratio on Early-Stage Cervix Carcinoma: Prognostic Value of Two Distinct Morphological Patterns of Microenvironment.

Background Tumor progression is influenced by the complex network of different cellular elements that make up its microenvironment. Tumor-infiltrating lymphocytes (TILs) and stroma characteristics reflect two faces of the intricate mechanisms involved in the tumor-host interaction and can be easily evaluated by routine histological examination.Their prognostic value could be demonstrated in different tumor tumor types, but they are poorly explored in cervical cancer. Methodology In this retrospective study, we analyzed the association of TILs, tumor-stroma ratio (TSR), and pattern of stromal fibroblasts with prognosis and classical clinicopathological variables. We studied 61 patients with early-stage cervical cancer. We reviewed histological type, tumor grade, Silva pattern of invasion for adenocarcinomas, tumor thickness, depth of stromal invasion, lymph vascular space invasion, and lymph node status. The median follow-up was 37.77 months (range 4.77 to 112.37 months). Results The TSR did not correlate with any clinicopathological features or disease-free and overall survival. On the other hand, the reactive pattern of stroma composed of larger fibroblasts and less collagenization was associated with the FIGO IB2 stage (p=0.04), larger tumor (p=0.03), and deeper infiltration (p=0.005). There were more recurrences in the group of reactive stroma (33.13% vs. 11.5%), although the difference did not reach statistical significance. Reactive stroma was associated with lower survival free of recurrence (p=0.05) and overall survival (p=0.009). High TILs were associated with squamous cell type (p=0.003), higher tumor grade (p=0.02), and more LVSI (p=0.02). Tumors with higher TILs presented higher free recurrence interval (p=0.06) and overall survival (p=0.03). No association was observed between stroma characteristics and TILs. Conclusions Our study suggested that although immune activation and stromal changes are important features of microenvironment remodeling during tumoral progression, they are independent, following distinct carcinogenetic pathways. Pathological assessment of stroma characteristics and TILs adds significant prognostic information and demonstrates how a simple routine laboratory assessment can generate a better understanding of biological phenomena.

Finite Element Analysis on Load-Settlement Behavior of Axially Loaded Pile on Sand

The analysis of geoengineering problems using various constitutive models necessitates substantial field and laboratory research, which entails a significant investment of time and money. As a result, the application of Finite Element Analysis in geoengineering projects is limited. This research focuses on numerically examining the behavior of a pile in a sandy soil layer. The study employs different relationships to estimate soil parameters from standard penetration tests and simple lab tests. These derived parameters, required for the Mohr-Coulomb &amp; Hardening Soil constitutive model and the linear elastic model of the pile, are implemented in the PLAXIS 3D software. This software is used to simulate the settlement of the pile in sandy soil incorporating factors like mesh density and soil-pile interaction. The results of the study reveal that employing a finer mesh size leads to more precise results. Additionally, an interface strength of 67% proves to be more accurate for this study. Furthermore, the correlation introduced by Papadopoulos (1982) exhibits a close relation with field settlement values. In contrast, other correlations either overestimate or underestimate the results. Moreover, the study conclude that Mohr-Coulomb constitutive model satisfactorily predicts the behavior of the pile for the study area.

Discrepancies in indel software resolution with somatic CRISPR/Cas9 tumorigenesis models

CRISPR/Cas9 gene editing has evolved from a simple laboratory tool to a powerful method of in vivo genomic engineering. As the applications of CRISPR/Cas9 technology have grown, the need to characterize the breadth and depth of indels generated by editing has expanded. Traditionally, investigators use one of several publicly-available platforms to determine CRISPR/Cas9-induced indels in an edited sample. However, to our knowledge, there has not been a cross-platform comparison of available indel analysis software in samples generated from somatic in vivo mouse models. Our group has pioneered using CRISPR/Cas9 to generate somatic primary mouse models of malignant peripheral nerve sheath tumors (MPNSTs) through genetic editing of Nf1. Here, we used sequencing data from the in vivo editing of the Nf1 gene in our CRISPR/Cas9 tumorigenesis model to directly compare results across four different software platforms. By analyzing the same genetic target across a wide panel of cell lines with the same sequence file, we are able to draw systematic conclusions about the differences in these software programs for analysis of in vivo-generated indels. Surprisingly, we report high variability in the reported number, size, and frequency of indels across each software platform. These data highlight the importance of selecting indel analysis platforms specific to the context that the gene editing approach is being applied. Taken together, this analysis shows that different software platforms can report widely divergent indel data from the same sample, particularly if larger indels are present, which are common in somatic, in vivo CRISPR/Cas9 tumor models.

Green mining of mining water using surface e-precipitation

Surface e-precipitation (SEP) is a largely unknown in separation electrochemical technique that uniquely combines the kinetic advantage of chemical precipitation with the advantages of conventional surface-based separation techniques such as electrodeposition/electrowinning (e-deposition), electrosorption, and adsorption. This work explores the potential of SEP in recovering valuable elements and removing toxic elements from mining water of a polysulfide ore origin. Without employing any reagent, in a simple batch-type laboratory setup with a carbon electrode, SEP alone or in combination with e-deposition can concentrate groups of dilute (20–30 mg/L) and ultradilute (<2 mg/L) valuable metals such as Zn, Al, Cu, Co, Ni, and rare earth elements (REE) vs gangue metals such as Mn, Fe, and an excess of Ca and Mg by an order of magnitude at highly competitive rate and energy consumption values which can reach 0.25 m3/(kg carbon ⋅ min) and 0.02 kWh/m3, respectively. The recovery and relative content of the concentrated metals can be controlled by the method design and operational variables such as applied potential, retention time (water treatment rate), and the number of stages. The uptake of Zn and Cu by SEP and e-deposition, respectively, is compared in mining waters and synthetic sulfate solutions. This comparison reveals that the ionic matrix of mining water promotes SEP but inhibits e-deposition. The comparison with the chemical precipitation at similar pH and reaction time shows that SEP has higher selectivity but lower recovery. These results demonstrate that SEP is a promising novel approach to valorizing and decontaminating acid mine drainage (AMD), process water, and metal-loaded wastewater.

A teaching-learning sequence about climate change: From theory to practice

We describe a collection of relatively simple experiments and laboratory demonstrations devoted to the physics of Earth's energy balance. Many of the experiments also address fundamental aspects of physics at the undergraduate level. Results of classroom testing of this sequence of activities are presented and discussed.

Data Perspectives in AI-Assisted Fiber-Optic Communication Networks

Machine learning (ML) is widely being regarded as a powerful technology to solve various complex problems in fiberoptic communication networks. Recently, ML algorithms have been considered for a variety of use-cases in optical networks ranging from the design of network devices to the compensation of transmission impairments to predicting network-wide traffic flow patterns. As ML techniques are inherently data driven, the availability of relevant data sets largely dictates the performance of developed ML models. Presently, majority of ML-aided methods in the literature rely either on synthetic data from certain simulation tools or exploit data from some simple laboratory setups. However, developing robust ML-based solutions for real fiber-optic networks demands assembling big data from various parts as well as across different layers and domains of the network. Unfortunately, there is currently a lack of understanding among the research community about various crucial data aspects in practical optical networks as well as key challenges faced. While there has been a plethora of works discussing numerous ML applications in fiber-optic communications and networking, to the best of our knowledge, there is presently no paper which particularly focuses on data perspectives. In this paper, we aim to shed light on various critical data factors by first describing the tools and technologies imperative for adequate network monitoring and data acquisition. We also elucidate different data types, their physical sources, and their applications. Several useful data handling and pre-processing techniques for efficient network data collection, storage, presentation, analysis, etc., are discussed. Major challenges in the generation, transmission, and sharing of the data are highlighted and some potential solutions to the outstanding problems are proposed, thus paving the way for seamless availability of pertinent data sets essential for realizing intelligent data-driven operations in future fiber-optic networks.

A Novel and Rapid Smear Cytomorphology Detection Strategy Based on Upconversion Nanoparticles Immunolabeling Integrated with Wright's Staining for Accurate Diagnosis of Leukemia.

Accurate, sensitive, and rapid identification of leukemia cells in blood and bone marrow is of paramount significance for clinical diagnosis. An integrative technique combining traditional cytomorphology with immunophenotyping was proposed to improve the diagnostic efficiency in leukemia. On account of high photostability, biocompatibility, and signal-to-background ratio, upconversion nanoparticles (UCNPs) as luminescent labels have drawn substantial research scrutiny in immunolabeling. To achieve simultaneous determination, NaYF4:Yb,Er UCNPs were coupled with CD38 antibodies to construct immunofluorescence probes that were developed to bind to diffuse large B cell lymphoma (DLBCL) cells, followed by Wright's staining that has been widely used in clinical work for morphological diagnosis. Further, the experimental conditions were optimized, such as medium, slice-making method, antibody dosage, incubation time, etc. The cell morphology and immunolabeling could be observed simultaneously, and its simple operation rendered it a possibility for clinical diagnosis. The developed immunolabeling assay could achieve DLBCL cell counting with high reproducibility and stability, and the detection limit was as low as 1.54 cell/slice (>3 σ/s). Moreover, the proposed method also realized real blood and bone marrow sample analysis, and the results were consistent with the clinical diagnosis. Overall, this strategy can be carried out after simple laboratory training and has prospective biomedical applications in leukemia classification, diagnosis validation, and differential diagnostics.

Beyond simple laboratory studies: Developing sophisticated models to study rich behavior.

Psychology and neuroscience are concerned with the study of behavior, of internal cognitive processes, and their neural foundations. However, most laboratory studies use constrained experimental settings that greatly limit the range of behaviors that can be expressed. While focusing on restricted settings ensures methodological control, it risks impoverishing the object of study: by restricting behavior, we might miss key aspects of cognitive and neural functions. In this article, we argue that psychology and neuroscience should increasingly adopt innovative experimental designs, measurement methods, analysis techniques and sophisticated computational models to probe rich, ecologically valid forms of behavior, including social behavior. We discuss the challenges of studying rich forms of behavior as well as the novel opportunities offered by state-of-the-art methodologies and new sensing technologies, and we highlight the importance of developing sophisticated formal models. We exemplify our arguments by reviewing some recent streams of research in psychology, neuroscience and other fields (e.g., sports analytics, ethology and robotics) that have addressed rich forms of behavior in a model-based manner. We hope that these "success cases" will encourage psychologists and neuroscientists to extend their toolbox of techniques with sophisticated behavioral models - and to use them to study rich forms of behavior as well as the cognitive and neural processes that they engage.

Monosit-HDL Oranı: Diyabetik Hastaların Takibinde ve Diyabetik Nefropatinin Tanısında Kullanılabilir mi ?

Background and Aim: Diabetic nephropathy is the most common cause of end-stage renal disease and albuminuria is the earliest manifestation of diabetic nephropathy.Oxidative stress and inflammation caused by advanced glyco-oxidation end products contribute to micro and macrovascular complications of diabetes. Monocyte to high-density lipoprotein (HDL) cholesterol ratio (MHR) is an essential indicator of inflammation and oxidative stress. In this study, we aimed to reveal the relationship between diabetes regulation and complications and MHR. Material and Method: A total of 182 subjects, including 152 patients with diabetes mellitus (DM) and 30 healthy controls, were included in this study. All data of the subjects were scanned retrospectively. The DM group was divided into two groups nephropathy (n=68) and non-nephropathy (n=84), with a limit of 30 mg/day for albuminuria. MHR was calculated by dividing the monocyte count by the HDL cholesterol count. Results: When patients with DM were divided into nephropathy and non-nephropathy, patients with nephropathy had higher MHR levels than the other group. We showed that MHR correlated with albuminuria, creatinine, and HbA1c in patients with diabetic nephropathy. In addition, in the regression analysis, albuminuria and MHR were predictors of DN, while MHR, age, and creatinine were found to be independent predictors of albuminuria. Conclusion: MHR, which is an easily calculated marker with simple laboratory tests, which is frequently requested in routine practice in the follow-up of diabetes patients, can help predict the regulation of diabetes and its kidney complications.

Association between red blood cell distribution width and the prognosis of brain death in patients with a Glasgow Coma Scale < 6

Red blood cell distribution width (RDW) has been reported as a meaningful prognostic factor in various diseases. Our study compared patients’ RDW levels and prognosis at admission and discharge time. A total of 128 patients 77 patients who suffered brain death (subject group), and 51 patients who were discharged from the hospital (control group) with GCS ≤ 6 were recruited from 60 hospitals for this study. Demographical data and RDW measurements in these patients at admission time and brain death/discharge time were extracted into two groups. 46 (35.9%) patients were females and 82 patients (64.1%) were males with a median age of 36 years old. A significant difference in baseline characteristics of GCS (P < 0.001), RDW at admission time (P < 0.001), and RDW at discharge or brain death time (P < 0.001) were noted between the two groups. In the overall population, RDW at admission time had a median value of 13.75% and was positively correlated with gender (P < 0.04, rs = 0.582) and age (P < 0.023, rs = − 0.201). Initially, there were no significant differences in RDW upon admission. However, upon discharge, although the RDW in the control group was not significant (P < 0. 1), the RDW level at the time of brain death was notably 0.45 fold higher (P = 0.001) compared to the time of admission. The standardized residuals at the two-time points showed an approximately normal distribution. The most effective RDW cut-off in Brain death was determined as 14.55. Based on the findings, using RDW as a prognostic factor has a sensitivity of 0.468 and a specificity of 0.137 in diagnosing brain death. RDW biomarker is a simple and inexpensive laboratory test that may be seen as a valuable perspective for initial patient evaluation. RDW is a powerful marker for the prognosis of brain death in patients with a GCS ≤ 6 at admission time, in order to identify a subset of patients who may require more aggressive management in the trauma center.

Studying naturalistic actions requires research programs and not trade-off decisions in individual studies: Comment on “Beyond simple laboratory studies: developing sophisticated models to study rich behavior” by Maselli, Gordon, Eluchans, Lancia, Thiery, Moretti, Cisek, and Pezzulo

Studying naturalistic actions requires research programs and not trade-off decisions in individual studies: Comment on “Beyond simple laboratory studies: developing sophisticated models to study rich behavior” by Maselli, Gordon, Eluchans, Lancia, Thiery, Moretti, Cisek, and Pezzulo

Prediction of yield shear strength of saturated sandy soils using artificial neural networks

ABSTRACT The undrained shear strength of sandy soils during flow failures and liquefaction is a critical metric in the analysis of undrained stability. In our study, the numerical technique known as Artificial Neural Network (ANN) is used for simulating the triaxial stress–strain relationship of sandy soils. This paper aims to predict the undrained shear strength of saturated sandy soil. The proposed program requires simple laboratory soil data to proceed. They are median grain diameter (D50), fines content percentage (FC%), void ratios and relative density. In addition, the stress data of undrained loading such as effective vertical stress (σ’1) and effective horizontal stress (σ’3) are needed. Then, using the program, the deviator stress at yield (qu yield) and, consequently, the yield shear strength of sandy soil (Su (yield)) can be determined. A database of experimental undrained triaxial of saturated sandy soils was collected from the literature and prepared to be the inputs of the network. Two artificial neural networks have been built. By comparing the effectiveness of the two networks, the Back Propagation Neural Network (PBNN) approved higher results and more accuracy than the General Regression Neural Network (GRNN). The computer program, yield shear strength prediction application, written in visual basic, has been developed by the author. For model validation, seven case studies (seven patterns of the production set), which were not seen by the network previously, were presented to the application and the results are compared to the actual output. The produced yield shear strength is very close to the actual strength.

Strengthening community empowerment for elderly health service in new normal by Pol-Sadar (Integrated Health Service Post for Elderly)

Before the pandemic, older people actively participated in an integrated health service post named POSYANDU. This high participation is due to community health workers who understand their role in realizing basic health services. During the pandemic, POSYANDU must be held with attention to developments in the COVID-19 case. We implemented the online-based service of integrated health posts to provide online health services for older people. This paper explains the participation of elders, family, and community health workers in the revitalization strategies of integrated health service activities for older people during the pandemic. The activities included health assessments via telemedicine (video call), drive-thru services for vital signs assessment and simple lab checks, home visits, and education via WhatsApp as needed. The implementation began in June 2020 and in May 2021 with 184 older people in some places in Central Java, including Semarang City, District of Semarang, and District of Batang. We also worked with teaching volunteers consisting of five community health workers and 19 nursing students in the community. The results of these activities were the findings of health problems experienced by the elderly during the pandemic (depression, hypertension, and joint stiffness), increased knowledge, and physical activity in the elderly group. The 100 older people participated in online exercise activities accompanied by their families and felt a decrease in complaints of joint stiffness, and 84 elders people participated in health education and exercise activities in open areas by implementing strict health protocols. Most participants said they were satisfied with Pol-Sadar activities as a health service strategy for older people during the pandemic. In conclusion, the online program was effective as a strategy of health services for elderly people, especially during the new normal era, and increased the participation of family and community health workers, but it needs adequate devices to participate.

Development of sugars quantification method using polarimeter couple with UV-Visible quartz cuvette cell

The objective of this study was to develop the method for determination of sugars at low sample volume using UV-Visible quartz cuvette cuvett instead of polarimeter cell. This proposed method could be analysis of sugars with high sample throughput rate and appropriate for analysis of pharmaceutical formulation. This study, the simple determination method by using sample UV-Visible quartz cuvette was developed in order to analyze dextrose, sucrose and lactose. It was found that quartz cuvette was not affected from the sodium light source at wavelength of 589.0 nm and it was possible to adapt for polarimetry technique. The linear calibration curve of dextrose, sucrose and lactose standard solution using polarimeter sample tube were constructed in the concentration ranges of 2.5–15.0 % w/v. Linear regression between the angle of rotation (y) and concentration of each sample (x) were expressed as the equation of y = 1.0941x – 0.1824 (r2= 0.9993), y = 1.3515x –0.1581 (r2= 0.9998) and y= 1.0390x – 0.0162 (r2= 0.9997) for dextrose, sucrose and lactose, respectively. Interestingly, the calibration curve of sugars standard solution using UV-Visible quartz cuvette were shown as y = 0.1050x - 0.1038 (r2= 0.9990), y = 0.1312x – 0.1458 (r2= 0.9989) and y = 0.1072x – 0.0335 (r2= 0.9991) for dextrose, sucrose and lactose, respectively. The detection limits (LOD) of proposed method for determination of dextrose, sucrose and lactose were 0.5, 1.0 and 0.6 % w/v, respectively, while the quantitation limits (LOQ) were 1.6, 3.0 and 1.9 %w/v for anlysis of dextrose, sucrose and lactose, respectively. The interferences study for proposed method from sodium chloride was investigated. It had found that this salt shown none effect for the proposed method. The results acquired the proposed method were compared favorably with those acquired by the reference method at a 95% confidence level with no significant difference (n=10). The developed method had shown accurate, precise, and reproducible. Moreover, this method indicated the possibility of a modified polarimetric method for the quantification of sugars. The method is possible to apply both in simple quality control laboratory and local industrial that involved with pharmaceutical production.