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INDONESIA
SAINS MEDIKA : JURNAL KEDOKTERAN DAN KESEHATAN
Published by Universitas Islam Sultan Agung
ISSN : 20851545     EISSN : 2339093X     DOI : -
Core Subject : Health,
Health Professions Medicine & Pharmacology
Sains Medika is journal of medicine and health, is a peer-reviewed and open access journal that focuses on promoting medical sciences generated from Biomedical Sciences, Public Health, Clinical Sciences, and Medical Education to integrate researches in all aspects of human health. This journal publishes original articles, reviews article, and also interesting case reports.
Arjuna Subject : -
Articles 235 Documents
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Increased levels of Follicle Stimulating Hormone (FSH) and sertoli cells count in wistar rats induced with paraquat after green bean sprout extract supplementation Auliya, Qurrotu A'yuni; Nasihun, Taufiqurrachman; Chodidjah, Chodidjah
Sains Medika: Jurnal Kedokteran dan Kesehatan Vol 13, No 1 (2022): June 2022
Publisher : Faculty of Medicine, Universitas Islam Sultan Agung (UNISSULA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1094.221 KB) | DOI: 10.30659/sainsmed.v13i1.7882

Abstract

Paraquat herbicide disrupts the hormone Follicle Stimulating Hormone (FSH), causes testicular damage and changes in spermatogenesis. This study aims to determine the effect of supplementation of green bean sprout extract (Vigna radiata L.) on FSH levels, Sertoli cell counts in male Wistar rats (Rattus norvegicus) induced by paraquat herbicide. This research uses true experimental with posttest only control group design. A total of 25 rats were divided into 5 groups: P0 was given standard feed, P1 was given paraquat 4 4 mg/g BW, P2 was given green bean sprout extract supplement (GBES) dose 21.6 4 mg/g BW and paraquat 4 mg/g BW P3 was given GBES dose 43.2 4 mg/g BW and paraquat is administered orally for 15 days. Measurement of FSH levels using ELISA, while Sertoli cells were observed using testicular histology preparate. Mann-Whitney test resulted significance of p<0.05, which showed that the administration of GBES influenced FSH levels and the number of Sertoli cells. GBES doses of 21.6 4 mg/g BW, 43.2 4 mg/g BW, and 86.4 4 mg/g BW were shown to increase FSH levels and Sertoli cell counts in paraquat-induced Wistar rats. GBES increased FSH levels and the number of Sertoli cells in paraquat-induced rats.
Effect of Eucheuma cottonii extract on interleukin-1 level and caspase-3 expression in borax-induced rat’s hepatocyte Muhyi, Ahmad; Wibowo, Joko Wahyu; Priyantini, Sri
Sains Medika: Jurnal Kedokteran dan Kesehatan Vol 13, No 1 (2022): June 2022
Publisher : Faculty of Medicine, Universitas Islam Sultan Agung (UNISSULA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (405.799 KB) | DOI: 10.30659/sainsmed.v13i1.25075

Abstract

Borax is a hepatotoxic substance and induces oxidative stress in hepatocytes. It may trigger the expression of pro-inflammatory cytokines like Interleukin-1 and apoptotic signals like Caspase-3. Extract of the seaweed Eucheuma cottonii contains carotenoids and flavonoids which suppress oxidative stress in hepatocyte. This study was conducted to determine the effect of E. cottonii extract on borax-induced Interleukin-1 and Caspase-3 expression in rat hepatocyte cells. This research employs a posttest-control group design. Twenty Wistar male rats were separated into four groups: control group (K1) received no intervention, K2 received Na-CMC 0.5% for 17 days and Borax 40 mg/200 g on the fourth day every hour for 14 days, P1 and P2groups  were administered E. cottonii extracts at doses of 600 mg/200 g and 1200 mg/200 g for 17 days, respectively, followed byborax induction at a dose of 40 mg/200 g on the fourth day with a one-hour interval for 14 days. Interleukin-1 (IL-1) levels were measured with ELISA, while caspase-3 expression was measured with PCR. For the statistical analysis, Kruskal Wallis and Mann Whitney were used. The level of IL-1 in P2 was significantly lower than in K2 (p<0.05). Caspase-3 expression was significantly lower in P1 and P2 than in K2 (p<0.05). IL-1 level and caspase-3 expression of hepatocytes are affected by administration of E. cottonii extract. The extract has the ability to prevent inflammation and hepatocyte apoptosis.<img 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
Skin manifestations in patients with covid-19: A literature review Gunawan, Danny; Stella, Maureen Miracle; Sidharta, Veronika Maria
Sains Medika: Jurnal Kedokteran dan Kesehatan Vol 13, No 1 (2022): June 2022
Publisher : Faculty of Medicine, Universitas Islam Sultan Agung (UNISSULA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1237.235 KB) | DOI: 10.30659/sainsmed.v13i1.15563

Abstract

Coronavirus disease (COVID-19) is an infectious disease caused by the SARS-CoV-2 virus. In December 2019, cases of pneumonia with unknown cause were first reported in Wuhan, Hubei Province, China. Confirmed cases and death rates due to COVID-19 in the world are still increasing. One part of the body that is affected and causes clinical symptoms in COVID-19 is the skin. This review aims to describe and analyze cutaneous manifestation in COVID-19. This study method is a review of the literature sourced from Google Scholar and PubMed. The literature was selected using English language criteria, using the clinical study method in the form of case reports. Meanwhile, literature review, systematic literature, and meta-analysis were excluded. Journal searches were carried out using the keywords "skin" OR "cutaneous" AND "manifestation" AND "COVID-19" OR "coronavirus". The skin manifestations of COVID-19 have been observed. The most common clinical symptoms of COVID-19 were fever (47%), dry or productive cough (25%), sore throat (16%), generalized sore throat (6%), and pain (5%). However, currently there has been a shift in the approach to diagnosing COVID-19 because it can cause symptoms in other organ systems, one of which is skin manifestations. There are early reports of skin involvement (erythematous rash, extensive urticaria, and chickenpox-like vesicles) occurring in 20% of patients in the course of the COVID-19 disease. In addition, several case reports provide descriptions of petechiae and chilblains. Based on the cases that have been reported, patients with COVID-19 who have manifestations on the skin can give a picture of maculopapular eruptions, vesicular eruptions, petechiae, and also childblains.
The influence of parental eating patterns on the nutritional status of Manado city children aged 6-24 months Agustina, Rakhmawati; Puji Ati, Endang
Sains Medika: Jurnal Kedokteran dan Kesehatan Vol 13, No 2 (2022): December 2022
Publisher : Faculty of Medicine, Universitas Islam Sultan Agung (UNISSULA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (361.017 KB) | DOI: 10.30659/sainsmed.v13i2.21022

Abstract

Parental eating habits have a positive effect on children's nutritional health. Numerous studies have examined children's eating patterns; however, few studies have examined the association between parental eating patterns based on the dimensions of demandingness and responsiveness in children and the nutritional status of 6- to 24-month-old children. This study aimed to examine the relationship between parental dietary habits and the nutritional status of children aged 6–24 months in Manado City. The research employed a quantitative approach with a cross-sectional design in the working area of the Ranomut Health Center, which included six neighborhoods from three villages: Paal 2, Ranomut, and Perkamil. This village was chosen because it has the highest concentration of children under the age of five in the Ranomut Health Center's service area. In this study, 96 samples were selected using the method of purposive sampling based on the criteria established by the researcher. The instrument used was the validated and reliable Feeding Practices and Structure Questionnaire for Infants, followed by data analysis using the Spearman rank test. The respondents' parental eating styles were authoritarian (31.3%), permissive (27.1%), democratic (20%), and negligent (20%). The nutritional status of children under the age of five was 26% malnourished and 74% well-nourished. The Spearman rank test resulted in a p-value of 0.674. This can be attributed to other factors, such as family composition and age-inappropriate food portions.
The association between Hb levels in placenta previa patients with apgar scores Nurrahma, Herlin Ajeng; Nur Intan, Yulice Soraya; Meliala, Andreanita; Narwidina, Paramita
Sains Medika: Jurnal Kedokteran dan Kesehatan Vol 13, No 2 (2022): December 2022
Publisher : Faculty of Medicine, Universitas Islam Sultan Agung (UNISSULA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (350.286 KB) | DOI: 10.30659/sainsmed.v13i2.26623

Abstract

Hemoglobin (Hb) level is a biochemical indicator of the nutritional status of pregnant women, and a low Hb level reduces blood supply to the placenta, which influences the incidence of placenta previa. A placenta previa develops in the lower portion of the uterus, completely or partially expanding to cover the entire birth canal and the internal uterine ostium. The APGAR score is commonly used as a predictor of infant mortality and long-term disability and as an indicator of infant health at birth. The risk of maternal and infant mortality and morbidity increases in placenta previa patients with inadequate vascularization, which can be caused by low Hb levels. This study aimed to determine the relationship between Hb levels and APGAR scores in patients with placenta previa at Sultan Agung Islamic Hospital in Semarang. This analytic observation study is a cross-sectional analysis with purposive sampling method. From January 2017 to January 2018, all placenta previa patients hospitalized at Sultan Agung Hospital in Semarang were included in this study. In this study, we used subject data that met the criteria for inclusion. The p-value derived from the chi-square analysis is 0.041 (p< 0.05). A test of association was conducted. This test revealed that the OR was 11.5 (OR > 1). Low Hb levels (11 g/dl) could significantly increase the risk of a lower APGAR score at 5 min in patients with placenta previa who have a low Hb level.
Measurement of Pterygium Tissue Dry Weight Using Two Different Tissue Preparation Techniques in Freeze-Dry Method Hilmi, Mohd Radzi; Mohd Kamal, Khairidzan; Che Azemin, Mohd Zulfaezal; Esmady Ariffin, Azrin
Sains Medika: Jurnal Kedokteran dan Kesehatan Vol 13, No 2 (2022): December 2022
Publisher : Faculty of Medicine, Universitas Islam Sultan Agung (UNISSULA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (370.291 KB) | DOI: 10.30659/sainsmed.v13i2.2958

Abstract

Due to pterygium tissue compression on the corneal surface, it has been hypothesised that the degree of corneal astigmatism caused by pterygium can vary. This study aims to develop a freeze-dried method for estimating net pterygium tissue mass (NPTM) as dry weight. A single surgeon (KMK) excised 60 primary pterygium using the controlled partial avulsion technique and divided them into two groups: formalin-fixed (n=30) and unfixed (n=30). After determining the weight of each sterile container, 5 mL of 5% buffered formaldehyde was added to the formalin-fixed group and stored for one week, while 5 mL of distilled water was added to the non-fixed pterygium group. Each container was pre-frozen for 12 hours before being freeze-dried (-24 hours at -80 degrees Celsius). The result is referred to as the net pterygium tissue mass (NPTM). Using an independent T-test, a comparison of wet and dry weight and percentage of NPTM was conducted between groups. Wet weights for formalin-fixed and non-fixed pterygium were 253.33 82.17 g and 255.17 63.52 g, respectively, while dry weights were 184.92 84.31 g and 179.54 72.85 g. Formalin-fixed pterygium tissue revealed a slightly higher percentage of NPTM than non-fixed pterygium tissue (69.39 13.29% vs. 67.75 13.29%, p = 0.792), but this difference was not statistically significant. The freeze-dried method can be utilised to quantify the NPTM of pterygium fibrovascular tissue and investigate the influence of pterygium translucency on predicting induced-corneal astigmatism.
Intense relationship of blood pressure and stadium of chronic kidney disease at early diagnosis Putra, Wisnu Pratama; Tania, Putu Oky Ari; Njoto, Ibrahim; Suryawati, Sianny
Sains Medika: Jurnal Kedokteran dan Kesehatan Vol 13, No 2 (2022): December 2022
Publisher : Faculty of Medicine, Universitas Islam Sultan Agung (UNISSULA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (341.899 KB) | DOI: 10.30659/sainsmed.v13i2.20235

Abstract

Chronic kidney disease (CKD) is a pathological stage with multiple causes that is characterised by a very high level of urea in the body because the kidneys are unable to balance the metabolism of fluids and electrolytes. Previous research has demonstrated that high blood pressure is one of the causes of chronic kidney disease. This study was conducted to determine the relationship between blood pressure and the initial stage of chronic kidney disease. observational study of Ninety patients with chronic kidney disease (CKD) at the RSUD Dr. Soeroto, Ngawi participated in this cross-sectional. Subjects were required to have CKD stages I-IV, high blood pressure, to be hospitalised for the first time at RSUD dr Soeroto, Ngawi, and to have never been treated for hypertension. This study employed the Spearman rank test, which was analysed by SPSS (p<0.05). 64.5% of patients with chronic kidney disease have reached stage V. In contrast, 47.8% of patients with chronic kidney disease have stage 2 hypertension. The Spearman Rank test revealed a p-value of 0.000 (<0.05) between blood pressure and the stage of chronic kidney disease at the time of initial diagnosis in patients with chronic kidney disease. The correlation coefficient has a value of 0.638, making it a strong correlation. There is a strong correlation between blood pressure and the stage of chronic kidney disease at the initial diagnosis of chronic kidney disease patients at the RSUD Dr. Soeroto, Ngawi.
Hierarchy of clinical decision-making by physicians based on medical and ethical decision making Soffan, Mochammad; Trisnadi, Setyo
Sains Medika: Jurnal Kedokteran dan Kesehatan Vol 13, No 2 (2022): December 2022
Publisher : Faculty of Medicine, Universitas Islam Sultan Agung (UNISSULA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (769.149 KB) | DOI: 10.30659/sainsmed.v13i2.27906

Abstract

From 2011 to 2014, there were six cases of suspected medical malpractice in the Central Java Region; four clinical cases were resolved by an ethics board and two by a public court, so that it serves as a reference for clinical decision-making for physicians, as many ethical problems in addition to legal problems exist in medicine. Doctors, as Indonesian citizens, are obligated to implement the norms and laws that apply in Indonesia. However, as professionals, they are also obligated to implement the norms that apply in medical professional organisations (Indonesian Doctors Association/IDI), including the Indonesian Doctors Association (IDI), the Code of Medical Ethics (KODEKI), and interprofessional ethics. So that the actions of physicians can be accounted for from both a legal and an ethical standpoint of the medical profession. Every clinical case a physician encounters has inextricable ethical and medical dimensions, necessitating a prudent method for making clinical decisions. The challenge is to comprehend the value hierarchy, beginning with norms, morals, principles, standards, and rules. Therefore, when making clinical decisions, physicians are truly guided by the order of applicable values, one of which is Jonsen-4-box Siegler’s method. The culture of the Indonesian people includes a 4-box method as an alternative. Schematics can be made for the order of values and ways of making clinical decisions based on wise ethical decisions in resolving ethical dilemmas and medical disputes.
The effect of lifestyle modification on metabolic, anthropometric parameters and hirsutism score in polycystic ovary syndrome Nur Intan, Yulice Soraya; Reza, Hanif; Gunawan, Robby
Sains Medika: Jurnal Kedokteran dan Kesehatan Vol 13, No 2 (2022): December 2022
Publisher : Faculty of Medicine, Universitas Islam Sultan Agung (UNISSULA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (305.148 KB) | DOI: 10.30659/sainsmed.v13i2.29137

Abstract

Polycystic ovary syndrome (PCOS) is a hormonal disorder that affects women of reproductive age. It is characterised by several clinical signs and symptoms, including hyperandrogenism, ovarian dysfunction, and chronic anovulation. Obesity and hormonal imbalances can be reduced in PCOS by modifying lifestyle habits. The effects of lifestyle changes on PCOS were investigated, and it was found that consuming less fat and engaging in physical activity reduced metabolic disturbances. The purpose of this study was to examine the effects of lifestyle modifications on metabolic parameters, anthropometric parameters, and the hirsutism score as they relate to the pathogenesis of PCOS. This study involved a total of 10 patients diagnosed with PCOS at the Sultan Agung Semarang Islamic Hospital. Blood glucose, triglycerides, HDL (high density lipoprotein), blood pressure, waist circumference, hirsutism score, and vital sign data related to PCOS were measured before and after a 4-month treatment. PCOS patients' fasting blood sugar levels, triglycerides (TG), high density lipoprotein (HDL), hirsutism scores, blood pressure (systolic and diastolic), and waist circumference averaged 92, 60; 48.10; 96.90; 10.5; 121.5/77; 86.80, respectively, at baseline (pretreatment). After four months of treatment, the average levels of fasting blood sugar, triglycerides, high-density lipoproteins, blood pressure (systolic and diastolic), hirsutism scores, and waist circumference were 108.7, 50, 99.8, 7, 122.3, 82.7, and 87.50, respectively. Changes in lifestyle led to significant variations in fasting blood sugar levels as a metabolic parameter and hirsutism scores, but not in triglycerides, high-density lipoprotein, waist circumference, or blood pressure.
The effect of ethanol extract of Andaliman (Zanthoxylum acanthopodium DC.) on kidney damage in tartrazine-induced rats Azhari, Mhd Bayu; Febriani, Husnarika; Syukriah, Syukriah
Sains Medika: Jurnal Kedokteran dan Kesehatan Vol 13, No 2 (2022): December 2022
Publisher : Faculty of Medicine, Universitas Islam Sultan Agung (UNISSULA), Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1431.85 KB) | DOI: 10.30659/sainsmed.v13i2.27610

Abstract

Tartrazine is a yellow synthetic dye with aromatic and chromo groups. It is widely used in food colouring products and cosmetics, and prolonged consumption can cause kidney damage. Andaliman (Zanthoxylum acanthopodium DC.) is a North Sumatra-native spice plant which reported as antioxidant to repair kidney damage. This study was conducted to determine the effect of ethanol extract of andaliman fruit on the morphology, ureum levels, histology, and glomerular diameter of tartrazine-induced rats. This study employed a completely randomised design (CRD). The ethanol extract of andaliman fruit was dissolved in CMC-Na 1%. Twenty-five rats were divided into 5 groups: negative control (KN), positive control (tartrazine indcution/PN), and treated groups (P1, P2, and P3 induced tartazine and treated with andaliman extract at dose 150 mg/kg BW, 300 mg/kg BW, and 450 mg/kg BW, respectively). After 30 days treatment, kidney damage was observed based on colour and surface of kidneys, kidney index, ureum level, kidney damage score, and glomerular diameter. There are no significant different in the kidney index among groups (p > 0.05). Tartrazin at a dose of 15 mg/kg BW was able to induce the kidney damage as indicated by the increase ureum levels, kidney damage score, and the decrease of glomerular diameter in the negative control. The treatment of andaliman fruit ethanol extract was able to repair the tartazine-induced kidney damage as indicated by the decrease of ureum level and kidney damage score and incread the glomerular diameter.

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