Fractional order modelling of omicron SARS-CoV-2 variant containing heart attack effect using real data from the United Kingdom.

In this study, a new approach to COVID-19 pandemic is presented. In this context, a fractional order pandemic model is developed to examine the spread of COVID-19 with and without Omicron variant and its relationship with heart attack using real data from the United Kingdom. In the model, heart attack is adopted by considering its relationship with the quarantine strategy. Then, the existence, uniqueness, positivity and boundedness of the solution are studied. The equilibrium points and their stability conditions are achieved. Subsequently, we calculate the basic reproduction number (the virus transmission coefficient) that simply refers to the number of people, to whom an infected person can make infected, as R 0 = 3.6456 by using the next generation matrix method. Next, we consider the sensitivity analysis of the parameters according to R 0 . In order to determine the values of the parameters in the model, the least squares curve fitting method, which is one of the leading methods in parameter estimation, is benefited. A total of 21 parameter values in the model are estimated by using real Omicron data from the United Kingdom. Moreover, in order to highlight the advantages of using fractional differential equations, applications related to memory trace and hereditary properties are given. Finally, the numerical simulations are presented to examine the dynamic behavior of the system. As a result of numerical simulations, an increase in the number of people who have heart attacks is observed when Omicron cases were first seen. In the future, it is estimated that the risk of heart attack will decrease as the cases of Omicron decrease.

Comparison and ensemble of 2D and 3D approaches for COVID-19 detection in CT images.

Detecting COVID-19 in computed tomography (CT) or radiography images has been proposed as a supplement to the RT-PCR test. We compare slice-based (2D) and volume-based (3D) approaches to this problem and propose a deep learning ensemble, called IST-CovNet, combining the best 2D and 3D systems with novel preprocessing and attention modules and the use of a bidirectional Long Short-Term Memory model for combining slice-level decisions. The proposed ensemble obtains 90.80% accuracy and 0.95 AUC score overall on the newly collected IST-C dataset in detecting COVID-19 among normal controls and other types of lung pathologies; and 93.69% accuracy and 0.99 AUC score on the publicly available MosMedData dataset that consists of COVID-19 scans and normal controls only. The system also obtains state-of-art results (90.16% accuracy and 0.94 AUC) on the COVID-CT-MD dataset which is only used for testing. The system is deployed at Istanbul University Cerrahpasa School of Medicine where it is used to automatically screen CT scans of patients, while waiting for RT-PCR tests or radiologist evaluation.

Useful indicators and models for assessing erosion control ecosystem service in a semi-arid forest landscape.

Forests provide a large array of ecosystem services (ESs) such as wood supply, extreme natural event prevention, and ecotourism opportunities. The quantitative characterization of ESs is a crucial but costly task for environmental managers. The aim of this study was to develop easily applicable models and indicators for assessing erosion control ES in a semi-arid landscape. In order to accomplish this, 107 randomly selected plots were visited for field measurements and topsoil sampling. Several parametric tests were then used to analyze the field data. The findings revealed that (i) normalized difference vegetation index (NDVI), (ii) cover management (C) factor of the Revised Universal Soil Loss Equation (RUSLE), (iii) soil organic matter content, (iv) canopy cover ratio, and (v) land use/land cover (LULC) types could be used as useful performance indicators of erosion control ES. Two regression models were developed based on these indicators and compared to RUSLE results for the study area. Using the first model, we were able to estimate the soil protection performance of different LULC types by NDVI at the pixel level (R2adj = 0.90, p < 0.05). The second model estimated annual potential soil loss using NDVI and ground slope values (R2adj = 0.57, p < 0.05). Based on the ES indicators framework, a practical approach was proposed in this study for rapid assessment of the soil erosion problem without running RUSLE. Thus, environmental managers are expected to make well-informed landscape planning decisions and improve their ES provision application capabilities at a reduced cost.

Diagnosis of SARS-CoV-2 Infection with LamPORE, a High-Throughput Platform Combining Loop-Mediated Isothermal Amplification and Nanopore Sequencing.

LamPORE is a novel diagnostic platform for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA combining loop-mediated isothermal amplification with nanopore sequencing, which could potentially be used to analyze thousands of samples per day on a single instrument. We evaluated the performance of LamPORE against reverse transcriptase PCR (RT-PCR) using RNA extracted from spiked respiratory samples and stored nose and throat swabs collected at two UK hospitals. The limit of detection of LamPORE was 10 genome copies/µl of extracted RNA, which is above the limit achievable by RT-PCR, but was not associated with a significant reduction of sensitivity in clinical samples. Positive clinical specimens came mostly from patients with acute symptomatic infection, and among them, LamPORE had a diagnostic sensitivity of 99.1% (226/228; 95% confidence interval [CI], 96.9% to 99.9%). Among negative clinical specimens, including 153 with other respiratory pathogens detected, LamPORE had a diagnostic specificity of 99.6% (278/279; 98.0% to 100.0%). Overall, 1.4% (7/514; 0.5% to 2.9%) of samples produced an indeterminate result on first testing, and repeat LamPORE testing on the same RNA extract had a reproducibility of 96.8% (478/494; 94.8% to 98.1%). LamPORE has a similar performance as RT-PCR for the diagnosis of SARS-CoV-2 infection in symptomatic patients and offers a promising approach to high-throughput testing.

A five-step protocol for estimating forest cover and rate of change in the New York City watershed.

New York City drinking water quality depends on retention of forest cover in its Catskill Mountains watersheds, yet multiple published analyses of temporally approximate satellite imagery derived no definitive nor agreed upon quantification of either forest cover in the watershed, or, more importantly, its rate of change over time. The objective of this work was to reduce uncertainty surrounding these estimates. We developed a five-pronged protocol that included (1) creation of a 1975-2002 time-series of land use/land cover (LULC) using Cross-Correlation Analysis (CCA); (2) a corrective post classification logic-based algorithm to correct for illogical transitions; (3) a probability-based stratified random sample accuracy assessment; (4) joint probability calculations of the "true" 2002 class proportions; and (5) verification of quantities of our LULC classification, and those of other researchers, versus the statistically derived true proportions. The estimated true percent of forest cover as of 2002 is 72%, far less than that reported by other studies, even with a net reforestation between 1975 and 2002. This protocol is an enhancement over previous LULC monitoring methods. Its more robust estimates of both historic trends and 2002 forest cover reveal information that is vitally important to monitoring and managing future water quality for the nation's largest city.

Acoustic Radiation Force Impulse (ARFI) imaging for the distinction between benign and malignant thyroid nodules.

PURPOSE: The aim of the present study was to evaluate thyroid nodules using virtual touch quantification (VTQ) of force impulse acoustic radiation (ARFI) imaging and to investigate a cutoff value for the differentiation of malignant thyroid nodules. MATERIALS AND METHODS: Ninety-five patients with quantitatively-assessed (VTQ) thyroid nodules were evaluated with ARFI imaging in this prospective study. ARFI imaging with VTQ was performed only on the nodules which were expected to undergo fine-needle aspiration biopsy (FNAB). All of the thyroid lesions were examined histopathologically. RESULTS: The mean shear wave velocity (SWV) value of the malignant nodules (3.18 ± 0.39 m/s) was higher than that of the benign nodules (2.11 ± 0.53 m/s). There was a statistically significant difference between the mean SWV values of benign and malignant nodules (p < 0.001). A SWV cutoff value of greater than 2.66 m/s yielded sensitivity and specificity values of 100 and 82.3 %, respectively, for diagnosis of malignant nodules. CONCLUSION: VTQ of ARFI imaging has high sensitivity and specificity for discriminating between benign and malignant thyroid nodules and may positively contribute to clinical evaluation of these nodules.

The postman always rings twice: two cases of shotgun deaths associated with an unconventional home security alarm system.

Injury and death cases caused by booby traps are not common in forensic medicine practice. Besides, installation of booby traps including firearms is generally for suicidal and rarely for homicidal purposes. Although few patents were described about home security alarm system that were created by firearms in the United States, 1 sample of injury with a similar unconventional mechanism of home safety system was reported by Asirdizer and Yavuz in 2009. In the published case report, the story of an electrical technician who was invited to a summer house by the homeowner to check the home security alarm system was reported. In the so-called report, he was stated to be injured by the shotgun attached to the unconventional home security alarm system while checking the system. As a result, the homeowner was convicted of a possible intent to cause a life-threatening injury to the technician.The so-called homeowner and his wife died by the same shotgun attached to the same unconventional home security alarm system 4 years on from the first event. In the present case report, we have aimed to present the findings of the crime scene and the autopsies of these unusual 2 deaths and to discuss individual and legal factors in paving the way for the deaths of 2 people.

Numerical Analysis of Compound Biochemical Calcium Oscillations Process in Hepatocyte Cells.

The hepatocyte cells regulate the wide range of liver function by moderating cellular activities such as lipid, protein metabolism, carbohydrate, and interact with other cells for proliferation and maintenance. In hepatocyte cells, the concentration of calcium uptake is quite extensive from various agonists such as active G α ${G_\alpha}$ subunit, active phospholipase C, free calcium in the cytosol, and endoplasmic reticulum. The overproduction and degradation of calcium signals can cause homeostasis, liver inflammation, and liver diseases. The spatiotemporal behavior of calcium oscillation reveals the physiological role of these cellular entities in understanding the process of production and degradation. No computational attempt has been registered to date on the compound calcium regulation of these cellular entities including the memory of cells. Hence, the authors proposed a fractional order compartmental model that systematically simulates the exchange of calcium intake in cellular entities. The nonlinear equations of the rate of changes in the active G α ${G_\alpha}$ subunit, active phospholipase C, free calcium in the cytosol, and endoplasmic reticulum are coupled to form a nonlinear fractional order initial value problem. The existence and uniqueness, stability analysis of the model is performed that validate the theoretical results and explore the dynamic behaviour of calcium oscillation in each compartment.

Advancing English as second language communication: The effectiveness of online pragmatic training on essential speech acts.

The development of pragmatic competence is crucial for enhancing learners' ability to communicate more effectively in English in various cultural and social contexts. Numerous studies have explored the impact of implicit and/or explicit training on language learners' pragmatic development. However, the scarcity of online pragmatic training has motivated this research. To this end, a randomized experimental study was conducted to determine whether online pragmatic treatment could enhance students' pragmatic competence and to identify which procedure, explicit or implicit, is more effective. Sixty university students were randomly assigned to three groups of 20: two experimental groups (implicit and explicit) and one control group. 'Google Meet' was used for online training. All three groups were given a Discourse Completion Task (DCT) as a pre-test featuring 12 different scenarios, three for each of four speech acts. At the end of the treatment, the participants of the experimental and control groups received the same DCT as a post-test. The findings revealed that the participants of the experimental groups improved their pragmatic competence compared to the pre-test and post-test results of the control group. Although there is a difference between the implicit and explicit groups' post-test results, the difference is not statistically significant. Still, according to Cohen's d effect size, the effect size of the explicit group (1.5) is larger than that of the implicit group (1.1). According to the results of the study, it can be said that pragmatic training contributes to the effective use of the target language for communicative purposes.

Universal and extensible language-vision models for organ segmentation and tumor detection from abdominal computed tomography.

The advancement of artificial intelligence (AI) for organ segmentation and tumor detection is propelled by the growing availability of computed tomography (CT) datasets with detailed, per-voxel annotations. However, these AI models often struggle with flexibility for partially annotated datasets and extensibility for new classes due to limitations in the one-hot encoding, architectural design, and learning scheme. To overcome these limitations, we propose a universal, extensible framework enabling a single model, termed Universal Model, to deal with multiple public datasets and adapt to new classes (e.g., organs/tumors). Firstly, we introduce a novel language-driven parameter generator that leverages language embeddings from large language models, enriching semantic encoding compared with one-hot encoding. Secondly, the conventional output layers are replaced with lightweight, class-specific heads, allowing Universal Model to simultaneously segment 25 organs and six types of tumors and ease the addition of new classes. We train our Universal Model on 3410 CT volumes assembled from 14 publicly available datasets and then test it on 6173 CT volumes from four external datasets. Universal Model achieves first place on six CT tasks in the Medical Segmentation Decathlon (MSD) public leaderboard and leading performance on the Beyond The Cranial Vault (BTCV) dataset. In summary, Universal Model exhibits remarkable computational efficiency (6× faster than other dataset-specific models), demonstrates strong generalization across different hospitals, transfers well to numerous downstream tasks, and more importantly, facilitates the extensibility to new classes while alleviating the catastrophic forgetting of previously learned classes. Codes, models, and datasets are available at https://github.com/ljwztc/CLIP-Driven-Universal-Model.

Transition dynamics between a novel coinfection model of fractional-order for COVID-19 and tuberculosis via a treatment mechanism.

In this paper, a fractional-order coinfection model for the transmission dynamics of COVID-19 and tuberculosis is presented. The positivity and boundedness of the proposed coinfection model are derived. The equilibria and basic reproduction number of the COVID-19 sub-model, Tuberculosis sub-model, and COVID-19 and Tuberculosis coinfection model are derived. The local and global stability of both the COVID-19 and Tuberculosis sub-models are discussed. The equilibria of the coinfection model are locally asymptotically stable under certain conditions. Later, the impact of COVID-19 on TB and TB on COVID-19 is analyzed. Finally, the numerical simulation is carried out to assess the effect of various biological parameters in the transmission dynamics of COVID-19 and Tuberculosis coinfection.

Modelling and analysis of fractional-order vaccination model for control of COVID-19 outbreak using real data.

In this paper, we construct the SV1V2EIR model to reveal the impact of two-dose vaccination on COVID-19 by using Caputo fractional derivative. The feasibility region of the proposed model and equilibrium points is derived. The basic reproduction number of the model is derived by using the next-generation matrix method. The local and global stability analysis is performed for both the disease-free and endemic equilibrium states. The present model is validated using real data reported for COVID-19 cumulative cases for the Republic of India from 1 January 2022 to 30 April 2022. Next, we conduct the sensitivity analysis to examine the effects of model parameters that affect the basic reproduction number. The Laplace Adomian decomposition method (LADM) is implemented to obtain an approximate solution. Finally, the graphical results are presented to examine the impact of the first dose of vaccine, the second dose of vaccine, disease transmission rate, and Caputo fractional derivatives to support our theoretical results.

Elderly suicides in Turkey.

Due to the unique physical and psychosocial characteristics of this age group, it is expected that the characteristics of elderly suicides are different from other groups. Knowing the characteristics of elderly suicides guides prevention strategies. The objective of this study was to evaluate the demographic characteristics, methods and reasons for suicide in elderly suicide cases using the data of the Turkish Statistical Institute between 2002 and 2019. Of the completed suicides among older adults, 4,208 (74%) cases were men and 1,481 (26%) were women. Crude suicide rates of all elderly age groups were higher than the general population. Illness was the most common reason for suicide. The second leading cause of suicide was marital conflicts in women, while financial difficulties were observed in men. Hanging was the most common method in both genders. It is remarkable that the use of gunshot considerably increases as years progress and the ratio of men (n:962) to women (n:16) reach 60. Considering these findings together with epidemiologic data predicting that this increase in the elderly population will almost double within less than 30 years, it is apparent that suicide is a major issue among older adults.

Modeling the epidemic trend of middle eastern respiratory syndrome coronavirus with optimal control.

Since the outbreak of the Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2012 in the Middle East, we have proposed a deterministic theoretical model to understand its transmission between individuals and MERS-CoV reservoirs such as camels. We aim to calculate the basic reproduction number ($ \mathcal{R}_{0} $) of the model to examine its airborne transmission. By applying stability theory, we can analyze and visualize the local and global features of the model to determine its stability. We also study the sensitivity of $ \mathcal{R}_{0} $ to determine the impact of each parameter on the transmission of the disease. Our model is designed with optimal control in mind to minimize the number of infected individuals while keeping intervention costs low. The model includes time-dependent control variables such as supportive care, the use of surgical masks, government campaigns promoting the importance of masks, and treatment. To support our analytical work, we present numerical simulation results for the proposed model.

[Investigation of the effects of probiotic bacteria on bacterial translocation that developed during diagnostic laparoscopy: an experimental study]. / Tanisal Amaçla Uygulanan Laparoskopi Sirasinda Olusan Bakteriyel Translokasyona Probiyotik Bakterilerin Etkilerinin Arastirilmasi: Deneysel Bir Çalisma.

Probiotics which are non-pathogenic live microorganisms ingested along with food or as dietary supplements, are thought to be beneficial to the host by supporting the microbial balance in digestive system. Various studies suggest that the effects of probiotics on the intestinal mucosa and immunity are protective against bacterial translocation. We aimed to investigate bacterial translocation related to the amount of CO2 insufflation given during laparoscopy and the effect of probiotic bacteria in an experimental peritonitis model. In this study 60 Wistar rats were used in six groups consisting of 10 rats. Group 1, 3 and 5 consisted of the rats that were fed without probiotics, while the rats in Group 2, 4, and 6 were fed with water containing 5 x 108 cfu/ml probiotic bacteria complex (Bifidobacterium lactis, Lactobacillus bulgaricus, Streptococcus thermophilus) for 15 days. To generate experimental peritonitis, 2 x 107 cfu/ml Escherichia coli ATCC 25922 was inoculated intraperitoneally to all of the rats. Thereafter, laparoscopy was applied in all groups. Application in Group 1 and Group 2 was without CO2; Group 3 and Group 4 with 14 mmHg CO2 insufflation, and Group 5 and Group 6 with 20 mmHg CO2 insufflation. Blood samples were taken in 2nd, 4th, and 6th hours. Mesenteric lymph node, liver and spleen samples were taken at 6th hour when the rats were sacrificed and then these were evaluated microbiologically with qualitative and quantitative methods. Bacterial translocation and bacteremia were found in the rats that were undergone experimental peritonitis during laparoscopy. All positive tissue and blood cultures yielded E.coli. The highest level of bacterial translocation was found to be in mesenteric lymph nodes (in 3/10, 6/10 and 10/10 in groups 1, 3 and 5 fed without probiotics, respectively; in 2/10, 3/10 and 4/10 in groups 2, 4 and 6 fed with probiotics, respectively). The bacterial translocation rates were found to be related to the increased CO2 insufflation. It was found that probiotic bacteria were more effective for decreasing bacterial translocation rates and bacteremia in the groups that were given high CO2 pressure during laparoscopy. It was also found that these results were correlated with bacterial translocation per gram of tissue. As an example, the quantitative bacterial growth values detected in mesenteric lymph node were 5.4 ± 2.9 x 103, 10.6 ± 3.3 x 103 and 21.5 ± 12.4 x 103 cfu/g in groups 1, 3 and 5, fed without probiotics, respectively; and 2.0 ± 1.3 x 103, 3.8 ± 1.9 x 103 and 9.0 ± 3.1 x 103 cfu/g in groups 2, 4 and 6, fed with probiotics, respectively. Our data emphasized that probiotic bacteria may be used as prophylactic agents for the prevention of bacterial translocation during laparoscopy, however comprehensive and clinical studies are needed to support these experimental results.

Investigation of interactions between COVID-19 and diabetes with hereditary traits using real data: A case study in Turkey.

In the present paper, interactions between COVID-19 and diabetes are investigated using real data from Turkey. Firstly, a fractional order pandemic model is developed both to examine the spread of COVID-19 and its relationship with diabetes. In the model, diabetes with and without complications are adopted by considering their relationship with the quarantine strategy. Then, the existence and uniqueness of solution are examined by using the fixed point theory. The dynamic behaviors of the equilibria and their stability analysis are studied. What is more, with the help of least-squares curve fitting technique (LSCFT), the fitting of the parameters is implemented to predict the direction of COVID-19 by using more accurately generated parameters. By trying to minimize the mean absolute relative error between the plotted curve for the infected class solution and the actual data of COVID-19, the optimal values of the parameters used in numerical simulations are acquired successfully. In addition, the numerical solution of the mentioned model is achieved through the Adams-Bashforth-Moulton predictor-corrector method. Meanwhile, the sensitivity analysis of the parameters according to the reproduction number is given. Moreover, numerical simulations of the model are obtained and the biological interpretations explaining the effects of model parameters are performed. Finally, in order to point out the advantages of the fractional order modeling, the memory trace and hereditary traits are taken into consideration. By doing so, the effect of the different fractional order derivatives on the COVID-19 pandemic and diabetes are investigated.

Assessment of index value performance of enzyme immunoassay test in predicting the diagnosis of human brucellosis.

INTRODUCTION: Clinical presentation of brucellosis is variable. Therefore, it must be confirmed with laboratory findings. Standard tube agglutination test (STAT) is commonly used for diagnosis of brucellosis. ELISA tests differentiate between IgM and IgG antibodies. However, there are evidences revealing that they do not have sufficient specificity. This study aimed to determine an ELISA optimal index value in the diagnosis of brucellosis. METHODOLOGY: Brucella STAT and ELISA IgM/IgG tests of patients admitted to the hospital with signs and symptoms of brucellosis between January 2017 and December 2019 were evaluated in the Microbiology Laboratory. RESULTS: ELISA IgM and IgG serum median index value was significantly higher in STAT positive (1 ≥ 1:160) group (p < 0.001 for both). By ROC analysis of 117 patients, when the IgM index value was determined to be 2.44, the sensitivity, specificity, positive and negative predictive values were 85.7%, 71.4%, 60%, and 90.9%, respectively, and when the IgG index 7.85 was determined, these values were 85.7%, 53.7%, 36.7%, and 92.3%, respectively was detected. CONCLUSIONS: In this study, it was revealed that Vircell Brucella had a good clinical diagnostic performance for index value of 2.44 for IgM test kit and 7.95 for IgG test kit. If the diagnosis of brucellosis is correctly predicted with index values in Brucella IgM and IgG tests before STAT analysis, they can be used in the process of clinical decision. In addition to the results of Brucella ELISA, reporting index values and determining optimal index values for each laboratory can help the diagnosis of brucellosis.

Extinction and stationary distribution of a stochastic COVID-19 epidemic model with time-delay.

We reformulate a stochastic epidemic model consisting of four human classes. We show that there exists a unique positive solution to the proposed model. The stochastic basic reproduction number R0s is established. A stationary distribution (SD) under several conditions is obtained by incorporating stochastic Lyapunov function. The extinction for the proposed disease model is obtained by using the local martingale theorem. The first order stochastic Runge-Kutta method is taken into account to depict the numerical simulations.

Ameliorative Effects by Hexagonal Boron Nitride Nanoparticles against Beta Amyloid Induced Neurotoxicity.

Alzheimer's disease (AD) is considered as the most common neurodegenerative disease. Extracellular amyloid beta (Aß) deposition is a hallmark of AD. The options based on degradation and clearance of Aß are preferred as promising therapeutic strategies for AD. Interestingly, recent findings indicate that boron nanoparticles not only act as a carrier but also play key roles in mediating biological effects. In the present study, the aim was to investigate the effects of different concentrations (0−500 mg/L) of hexagonal boron nitride nanoparticles (hBN-NPs) against neurotoxicity by beta amyloid (Aß1-42) in differentiated human SH-SY5Y neuroblastoma cell cultures for the first time. The synthesized hBN-NPs were characterized by X-ray diffraction (XRD) measurements, scanning electron microscopy (SEM) and transmission electron microscopy (TEM). Aß1-42-induced neurotoxicity and therapeutic potential by hBN-NPs were assessed on differentiated SH-SY5Y cells using MTT and LDH release assays. Levels of total antioxidant capacity (TAC) and total oxidant status (TOS), expression levels of genes associated with AD and cellular morphologies were examined. The exposure to Aß1-42 significantly decreased the rates of viable cells which was accompanied by elevated TOS level. Aß1-42 induced both apoptotic and necrotic cell death. Aß exposure led to significant increases in expression levels of APOE, BACE 1, EGFR, NCTSN and TNF-α genes and significant decreases in expression levels of ADAM 10, APH1A, BDNF, PSEN1 and PSENEN genes (p < 0.05). All the Aß1-42-induced neurotoxic insults were inhibited by the applications with hBN-NPs. hBN-NPs also suppressed the remarkable elevation in the signal for Aß following exposure to Aß1-42 for 48 h. Our results indicated that hBN-NPs could significantly prevent the neurotoxic damages by Aß. Thus, hBN-NPs could be a novel and promising anti-AD agent for effective drug development, bio-nano imaging or drug delivery strategies.

[Incorrect identification in forensic medicine (wrong conclusion): a case report]. / Adli tibbi uygulamalarda hatali tanimlama, yanlis karar: Olgu sunumu.

Correct identification of lesions in examined patients is as important in forensic medicine application as it is in the medical profession. However, general practitioners and clinicians often fail to give proper attention to the definition and recording of the lesions and clinical findings in patients. Additionally, the identification of the lesion is sometimes deficient or incorrect. This has hindered, particularly in traumatic events that are of a forensic nature, reaching accurate conclusions during the interpretative and legal phases. In this study, we describe the case of a nine-year-old boy admitted to the hospital following a traffic accident. During his evaluation, an ecchymosis "resembling a rail" on his chest was noted. Consequently, legal/judicial authorities suspected the child may have been exposed to violence or child abuse and he was referred to our department. Practitioners may contribute to inaccurate decisions/conclusions if they fail to give the necessary detailed attention during the forensic interpretation (detailed examination and recording of lesions) and judicial process or if they have insufficient knowledge on this subject. This case is submitted as an interesting example since it included the possibility of inaccurate conclusion and judgment.