Information File Research Articles

A Prediction Model of Recidivism of Specific Populations Based on Big Data

This research is aimed at establishing and improving the relevant information database of “released prisoners,” integrating the behavior data of specific populations, constructing the early-warning model of recidivism, evaluating the database file information by using prediction analysis technology, and making a prediction alarm to the people who are most likely to commit the crime again on the basis of big data analysis so as to ultimately achieve the goal of reducing the recidivism rate. The research used the data exchange technology of the heterogeneous database to complete data collection and database establishment, used the feature engineering technology to analyze the big data of specific populations, obtained the multidimensional behavior trajectory data, and carried out sorting and statistics. On this basis, the linear regression algorithm was applied to make the prediction and evaluation, and the visual results were presented to assist in researching and judging the possibility of recidivism of specific personnel. Through programming realization and simulation experiments, the research obtained the tendency prediction of the people to commit crimes again by statistical analysis from multidimensional data with a long time span. In the next step, the real test will be carried out to help the public security work in China and contribute to the maintenance of national and social stability.

Construction and Functionalization of Highly Strained N -Doped Zigzag Hydrocarbon Belts

Construction and Functionalization of Highly Strained <i>N</i> -Doped Zigzag Hydrocarbon Belts

Evaluating an Expedited Process to Assess Fitness to Stand Trial in Canada

In this study, we investigated the potential benefits of using an alternative approach for completing court ordered fitness to stand trial assessments in a Canadian forensic mental health service. Using file information, court databases, and an economic analysis, we compared a hospital-based model of evaluation to a court clinic model in a sample of 96 accused persons from 2013 to 2017. Results revealed a significantly shorter time period for forensic report completion in the court clinic group, but no difference in criminal case processing time between groups. There was a higher rate of accused persons opined to be unfit to stand trial in the court clinic group (25.9%) compared to the hospital-based model (7.7%). Report quality varied somewhat between groups, with forensic assessment reports citing mental disorder and relevant case law more often in the court clinic model. Economic analyses indicated there was a marked cost savings associated with completing assessments at court instead of hospital. Our findings suggest there are several benefits for forensic mental health systems in utilizing community-based models of forensic evaluation.

Deep-Learning-Based End-to-End Predictions of CO2 Capture in Metal-Organic Frameworks.

Metal-organic frameworks (MOFs) have become an active topic because of their excellent carbon capture and storage (CCS) properties. However, it is quite challenging to identify MOFs with superior performance within a massive combinatorial search space. To this end, we propose a deep-learning-based end-to-end prediction model to rapidly and accurately predict the CO2 working capacity and CO2/N2 selectivity of a given MOF under low-pressure conditions. Different from previous methods, our prediction model relies only on the data from the Crystallographic Information File (CIF) rather than handcrafted geometric descriptors and chemical descriptors. The model was developed, trained, and tested on a dataset of 342489 topologically diverse MOFs. Experimental results on the dataset show that the proposed model achieves high prediction performance, i.e., R2 = 0.916 for predicting the CO2 working capacity and R2 = 0.911 for predicting the CO2/N2 selectivity. With regard to the identification of potential high-performing MOFs, 1020 of 1027 (top 3%) high-performance MOFs were recovered while screening only 12% of the entire dataset using our provided pretrained model, reducing the computation time by nearly an order of magnitude when the model was used to prescreen material prior to computationally intensive grand canonical Monte Carlo (GCMC) simulations while still capturing 99% of the high-performance MOFs. In the ab initio training task, the method can achieve R2 = 0.85 with only 20% of the labeled data used for training and recover 995 of 1027 (top 3%) high-performance MOFs with only 12% of the entire dataset screened.

Correlation between Clinical and Histopathological Diagnoses in Oral Cavity Lesions: A 12-Year Retrospective Study.

Objective Proper diagnosis plays a key role in the treatment and prognosis of all diseases. Although histopathological diagnosis is still known as the gold standard, final diagnosis becomes difficult unless precise clinical descriptions are obtained. So, this study aimed to evaluate the concordance of the clinical and histopathological diagnoses of all oral and maxillofacial biopsy specimens in a 12-year duration. Materials and Methods Archive files and clinical findings related to 3001 patients who had been referred to the Department of Oral Pathology during a 12-year period were reviewed. The recorded information in files included age, sex, lesion's location, clinical and histopathological diagnoses, and specialty of dentists. Results Out of 3001 cases included and reviewed in this study, 2167 cases (72.2%) were consistent between clinical and histopathologic diagnoses. Age, sex, and clinician's specialty were indicated to have no significant effect on diagnosis (p values = 0.520, 0.310, 0.281, respectively), but location and type of lesion affected that (p values = 0.040 and 0.022, respectively). In regard to location, the highest concordance of clinical and histopathologic diagnoses was observed in mouth floor lesions, and the lowest one was in gingival mucosa. In terms of lesion category, the highest and the lowest concordance rates belonged to white and red lesions and pigmented lesions, respectively. Conclusion The results of the present study show that the consistency of clinical and histopathological diagnoses was three times more than their inconsistency, and the accuracy of the clinicians was largely acceptable.

MP48-03 PREVALENCE AND NATURAL HISTORY OF NON-METASTATIC CASTRATE RESISTANT PROSTATE CANCER: A POPULATION-BASED ANALYSIS

You have accessJournal of UrologyCME1 May 2022MP48-03 PREVALENCE AND NATURAL HISTORY OF NON-METASTATIC CASTRATE RESISTANT PROSTATE CANCER: A POPULATION-BASED ANALYSIS Amanda Hird, Erind Dvorani, Refik Saskin, Sender Herschorn, Ronald Kodama, Girish Kulkarni, and Robert Nam Amanda HirdAmanda Hird More articles by this author , Erind DvoraniErind Dvorani More articles by this author , Refik SaskinRefik Saskin More articles by this author , Sender HerschornSender Herschorn More articles by this author , Ronald KodamaRonald Kodama More articles by this author , Girish KulkarniGirish Kulkarni More articles by this author , and Robert NamRobert Nam More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000002619.03AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: The natural history of non-metastatic castrate resistant prostate cancer (nmCRPC) prior to the introduction of novel anti-androgen agents in a real-world setting is largely unknown. Our primary aim was to determine the prevalence and natural history of nmCRPC. METHODS: This was a retrospective population-based cohort study of men with nmCRPC in Ontario, Canada. Patients with a diagnosis of prostate cancer, castrate level of testosterone (<1.7 nmol/L) and a PSA >2.0 nmol/L with a subsequent rise >25% from the nadir, and without diagnostic or treatment codes for metastasis were included. Annual prevalence of nmCRPC was calculated. Crude time from nmCRPC to metastasis and death are presented as medians with interquartile range (IQR). Predictors of time from nmCRPC to prostate cancer death were compared using univariable and multivariable Fine and Gray subdistributional hazard models to account for the competing risk of non-prostate cancer death. RESULTS: From January 2007 until March 2018, we identified 2045 patients with nmCRPC. Median age was 79 years (IQR: 72-84). A total of 984 patients (48.1%) received upfront hormonal therapy while 584 (25.8%) received initial radiotherapy (RT) and 478 (23.4%) previously underwent radical prostatectomy. Median time from primary treatment to nmCRPC was 6 years (IQR: 3-10). PSA at the time of meeting nmCRPC criteria was a median of 3.0 ng/L. Patients were followed for a median 31.1 months (IQR: 19.8-47.9). The overall annual prevalence of nmCRPC ranged from 1,519-1,913 patients, representing 7-12% of men with prostate cancer prescribed androgen deprivation therapy each year. Crude median time from nmCRPC to all-cause death was 37.6 months (IQR: 22.1-55.4). Median time from nmCRPC to metastasis and metastasis to all-cause death was 20.0 and 8.3 months, respectively. On regression analysis, older patients, patients who had a higher PSA at the time of meeting nmCRPC criteria, and patients with grade group 4-5 disease had a shorter time from nmCRPC to prostate cancer death. CONCLUSIONS: This is the largest analysis of the prevalence and natural history of nmCRPC. The current study can be used as a historical cohort to compare how novel imaging modalities and advancements in systemic therapy for patients with nmCRPC impact prevalence estimates and disease trajectory over time. Source of Funding: This study was supported by ICES, which is funded by an annual grant from the Ontario Ministry of Health (MOH) and Ministry of Long-Term Care (MLTC) (grant number not applicable). This study also received funding from the Ajmera Family Chair in Urologic Oncology awarded to RKN (grant number not applicable). We thank IQVIA Solutions Canada Inc. for use of their Drug Information File © 2022 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 207Issue Supplement 5May 2022Page: e821 Advertisement Copyright & Permissions© 2022 by American Urological Association Education and Research, Inc.MetricsAuthor Information Amanda Hird More articles by this author Erind Dvorani More articles by this author Refik Saskin More articles by this author Sender Herschorn More articles by this author Ronald Kodama More articles by this author Girish Kulkarni More articles by this author Robert Nam More articles by this author Expand All Advertisement PDF DownloadLoading ...

Pre-trial fronto-occipital electrophysiological connectivity affects perception–action integration in response inhibition

Inhibition of inappropriate behavior is relevant in many everyday situations. Nevertheless, the mechanisms that induce response inhibition based on sensory information and what influences these mechanisms are not entirely understood. We examined neurophysiological processes of perception–action integration in response inhibition and the impact of the pre-trial neurophysiological functional connectivity state in the theta and alpha band on these integration processes. The study was motivated by the Theory of Event Coding framework. Within the trial, fronto-medial theta band activity and occipital alpha band activity revealed an opposing interplay depending on the necessity of (re-)binding event files, i.e., the disintegration and recombination of stimulus–response associations, during response inhibition. When response inhibition required the reconfiguration of event files, this was associated with increased theta band activity but lower alpha band activity, and vice versa for the retrieval of event files. Notably, the most substantial impact of pre-trial connectivity on the within-trial event file binding effect (the difference between conditions that require reconfiguration and those that do not) during response inhibition occurred between fronto-medial areas and areas of the ventral stream in the theta frequency band. This suggests a preparatory top-down control of sensory areas before stimulus presentation. Increased pre-trial connectivity was associated with a decreased event file binding effect in the alpha frequency band and an increased event file binding effect in the theta frequency band during response inhibition. This implies an impact of the pre-trial functional connectivity state on inhibitory gating processes of relevant information and event file (re-)binding during response inhibition. The study shows how perception–action integration during response inhibition is affected by preceding transient neurophysiological connectivity states.

Hebbian plasticity: the elusive missing link at the heart of Alzheimer's disease pathogenesis?

Hebbian plasticity: the elusive missing link at the heart of Alzheimer's disease pathogenesis?

Emerging role of neuregulin-1beta1 in pathogenesis and progression of multiple sclerosis

Emerging role of neuregulin-1beta1 in pathogenesis and progression of multiple sclerosis

The neuroprotective effects of oxygen therapy in Alzheimer’s disease: a narrative review

Alzheimer’s disease (AD) is a degenerative neurological disease that primarily affects the elderly. Drug therapy is the main strategy for AD treatment, but current treatments suffer from poor efficacy and a number of side effects. Non-drug therapy is attracting more attention and may be a better strategy for treatment of AD. Hypoxia is one of the important factors that contribute to the pathogenesis of AD. Multiple cellular processes synergistically promote hypoxia, including aging, hypertension, diabetes, hypoxia/obstructive sleep apnea, obesity, and traumatic brain injury. Increasing evidence has shown that hypoxia may affect multiple pathological aspects of AD, such as amyloid-beta metabolism, tau phosphorylation, autophagy, neuroinflammation, oxidative stress, endoplasmic reticulum stress, and mitochondrial and synaptic dysfunction. Treatments targeting hypoxia may delay or mitigate the progression of AD. Numerous studies have shown that oxygen therapy could improve the risk factors and clinical symptoms of AD. Increasing evidence also suggests that oxygen therapy may improve many pathological aspects of AD including amyloid-beta metabolism, tau phosphorylation, neuroinflammation, neuronal apoptosis, oxidative stress, neurotrophic factors, mitochondrial function, cerebral blood volume, and protein synthesis. In this review, we summarized the effects of oxygen therapy on AD pathogenesis and the mechanisms underlying these alterations. We expect that this review can benefit future clinical applications and therapy strategies on oxygen therapy for AD.

Kombinasi Algoritma Cipher Block Chaining dan Triangle Chain Cipher dalam Penyandian File Text

Currently the use of information technology as a medium of information exchange is growing very widely. Various types of information such as text, images, sound and video can be converted into digital media that allows it to be reproduced or transmitted through various media. One of them is the internet, through the internet we can easily exchange information with other people in various places. However, there are times when information/messages are confidential, where no other party may know the contents of this information other than the sender and recipient. So we need a security against the message. Cryptography is a technique and art to encode messages or information in a medium, such as text, images, audio or video which aims to avoid suspicion from unauthorized people. For that we need a software that can encode confidential information in a text file. However, in hiding messages in text files using cryptography alone is not necessarily safe, so a useful algorithm is needed to improve security, therefore Cipher Block Chaining and Triangle Chain Cipher algorithms are needed. The research objective is to apply the Cipher Block Chaining and Triangle Chain Cipher algorithms for text file encoding applications. This is necessary because it often happens that the text message sent is a secret message that should not be known to just anyone. Block Chaining Ciphers and Triangle Chain Ciphers are useful algorithms to provide an advantage in terms of increased security in text files.

SECURE DATA HIDING MECHANISM USING TEXT COVER MESSAGE

Steganography is the art of hiding secret information within other information that is digitally concealed. It protects the confidentiality of two communicating parties. Information hiding is a highly strong and adaptable strategy that may be used to protect vital information in a variety of situations. There are several steganography techniques available, each with its own set of advantages and disadvantages. This study presents a new data hiding mechanism that hides file information in text cover messages to safeguard user data from vulnerabilities. It also utilize a deduplication strategy that employs the suggested DSHA algorithm to reduce repeated data storage. This novel technique ensures security while maintaining confidentiality.

Direct Spread Spectrum Technology for Data Hiding in Audio.

Direct spread spectrum technology is traditionally used in radio communication systems with multiple access, for example, in CDMA standards, in global satellite navigation systems, in Wi-Fi network wireless protocols, etc. It ensures high security and reliability of information transfer. In addition, spread spectrum technology provides the transmitted signals with a noise-like appearance, thus hiding the semantic content of the messages. We researched this technology for other implementations. The purpose of our study was to investigate new technologies for hiding data in multimedia files. In particular, we investigated the direct spread spectrum in the context of the development of methods for hiding data in audio containers. We considered various spreading sequences (chip codes) and also explored their use for hiding information in audio files. We conducted experimental studies and estimated the bit error rate (BER) in the recovered data. The article also evaluates the distortion of an audio container by the peak signal-to-noise ratio (PSNR). The results of our research enable us to find out which method of forming chip codes gives a lower BER with equal PSNR. We provide recommendations on the formation of spreading sequences to reliably and safely hide informational messages in audio files.

Evaluation of the efficacy and toxicity of oral and topical pumpkin oil on the hair growth of mice

This study aimed to evaluate the efficacy and safety of a topical and oral administration of pumpkin seed oil (PSO) on the hair growth of BALB/c male mice. The animals had their dorsal area shaved (2 ×2 cm) and they were divided into 6 experimental groups. They received orally saline (OS), finasteride (F), or PSO (OP) for 14 days; or topically saline (TS), minoxidil (M), or PSO (TP) for 7 days. The euthanasia of all of the mice occurred on the 22nd day, and the histological slides from the skin area were analyzed. Lipoperoxidation in the liver was assessed through the TBARS method and was also evaluated by the antioxidant enzymes (SOD and CAT). The comet assay and the micronucleus tests were performed for genotoxic/mutagenic safety analyses. A significant increase in the number of hair follicles in the TP group was seen (8.8 ± 0.8) but it was disorganized, with loose dermal collagen. Finasteride presented a significant increase in the levels of the TBARS, SOD, and CAT in the liver, and M increased the DNA damage in the blood and the liver tissues. PSO did not induce any significant changes. In addition, PSO did not induce genotoxic or mutagenic effects. In conclusion, the oral PSO for 14 days acted in the proliferation of the hair follicles, without toxicity signals in the liver. Data availabilityThe authors confirm that all of the relevant data is included in the article and/or in the supplementary information file.

Evaluation of the NANDA International, Inc. diagnostic classification in Spain: Development and validation of the EVALUAN-I tool.

To develop and validate a tool to evaluate the NANDA International, Inc. diagnostic classification. The tool, EVALUAN-I, was validated in a non-probabilistic sample (N = 460) on Spanish Registered Nurses (September-December 2019) in two phases. First, design and construct the instrument in three steps: (1) literature review to define the construct focusing on the orientation toward nursing concepts and theoretical foundations, the level of scientific evidence, the structural configuration, the applicability, the nurses' clinical reasoning skills, and the attitudes toward nursing diagnosis, (2) substantiation of the questionnaire items and design according to the criteria for a diagnostic classification, (3) expert test to establish the face validity and content validity. The second phase revolved around (4) conducting a pilot test and measuring the temporal stability (test-retest) and Cohen's kappa coefficient; assessing psychometric properties by measuring (5) reliability (internal consistency using Cronbach alpha and interfactor correlation) and (6) construct validity (exploratory and confirmatory factor analysis). The manuscript follows the STROBE checklist. The study was approved by the Research Ethics Committee with registration number 2019-190-1. EVALUAN-I displayed moderate test-retest stability, adequate construct validity, and excellent reliability. The confirmatory factor analysis provided evidence about the configuration of EVALUAN-I in relation to nine analytical dimensions: clinical competence, nurses' reasoning skills, attitudes towards nursing diagnosis, discipline's central concepts, classification's contents, physiopathological attributes, level of scientific evidence, diagnostic precision, and conceptual correspondence between terminologies. EVALUAN-I is a valid and reliable instrument, which can be used to improve the epistemological, normative, and intuitive configuration of NANDA International, Inc. in a structured, systematic manner. Comprehensive evaluation of NANDA International, Inc. in different clinical settings around the world using a validated instrument, like EVALUAN-I, would allow strengths and weaknesses to be identified and contribute to the classification's development and practical application.

From the Periodic Properties of Metals to the Rietveld Refinement of the Pharmaceutical Molecule Naproxen: Three Remote Experiments about X-ray Diffraction

Recently there is an increasing need for experiments that can be conducted remotely. In this sense, this paper presents three experiments about materials science and an X-ray diffraction (XRD) technique that can be taught and performed entirely remotely. The first experiment is about the calculation of lattice parameters, atomic radii, and densities of metallic elements with a body-centered cubic (BCC) structure. The second experiment is about the calculation of lattice parameters, axial ratios, unit cell volumes, and densities of yttria-stabilized zirconia (YSZ) solid solutions. The third experiment is about applying the Rietveld refinement technique to distinguish the enantiomers of the pharmaceutical molecule naproxen and determine the hydration degree of commercial naproxen sodium pills. For the first two experiments, students worked with simulated data, whereas for the third one, they worked with experimental data collected and provided by the Instructor. Besides the materials science and XRD concepts, students were introduced to the operation of the free softwares Vesta and GSAS II and to the Crystallography Open Database, a free database for structural data of organic and inorganic compounds. The paper explains the background, goals, and results obtained by the students in each one of the experiments. Detailed information about the experimental procedures and their implementation is complemented by the Supporting Information file and Supporting Videos. Although the experiments were presented in an increasing level of difficulty, they are independent of each other, allowing the instructors to apply them according to their needs and learning objectives.

Improved Deep Learning Model for Static PE Files Malware Detection and Classification

Static analysis and detection of malware is a crucial phase for handling security threats. Most researchers stated that the problem with the static analysis is an imbalance in the dataset, causing invalid result metrics. It requires more time for extracting features from the raw binaries, and methods like neural networks require more time for the training. Considering these problems, we proposed a model capable of building a feature set from the dataset and classifying static PE files efficiently. The research work was conducted to emphasize the importance of feature extraction rather than focusing on model building. The well-extracted features help to provide better results when fed to neural networks with minimal numbers of layers. Using minimum layers will enhance the performance of the model and take fewer resources and time for the processing and evaluation. In this research work, EMBER datasets published by Endgame Inc. containing PE file information are used. Feature extraction, data standardization, and data cleaning techniques are performed to handle the imbalance and impurities from the dataset. Later the extracted features were scaled into a standard form to avoid the problems related to range variations. A total of 2381 features are extracted and pre-processed from both the 2017 and 2018 datasets, respectively. The pre-processed data is then given to a deep learning model for training. The deep learning model created using dense and dropout layers to minimize the resource strain on the model and deliver more accurate results in less amount of time. The results obtained during experimentation for EMBER v2017 and v2018 datasets are 97.53% and 94.09%, respectively. The model is trained for ten epochs with a learning rate of 0.01, and it took 4 minutes/epoch, which is one minute lesser than the Decision Tree model. In terms of precision metrics, our model achieved 98.85%, which is 1.85% more as compared to the existing models.

FPGA-based edge computing: Task modeling for cloud-edge collaboration

With the development of the Internet of Things and devices continuing to scale, using cloud computing resources to process data in real-time is challenging. Edge computing technologies can improve real-time performance in processing data. By introducing the FPGA into the computing node and using the dynamic reconfigurability of the FPGA, the FPGA-based edge node can increase the edge node capability. In this paper, a task-based collaborative method for an FPGA-based edge computing system is proposed in order to meet the collaboration among FPGA-based edge nodes, edge nodes, and the cloud. The modeling of the task includes two parts, task information and task-dependent file. Task information is used to describe the running information and dependency information required for the task execution. Task-dependent file contains the configuration bit-stream of FPGA in running of the task. By analyzing the task behavior, this paper builds four basic behaviors, analyzes the critical attributes of each behavior, and summarizes the task model suitable for FPGA-based edge nodes. Tasks with specific functions can be created by modifying different attributes of model nodes. Finally, the availability of the model and the task-based collaborative method are verified by simulation experiments. The experimental results that the task model proposed in this paper can meet cloud-edge collaboration in the FPGA-based edge computing environment.

Overexpression of angiotensin-converting enzyme 2 contributes to the amelioration of Streptococcus uberis-induced inflammatory injury in mammary epithelial cells

Streptococcus uberis (S. uberis) is an environmentally important pathogenic bacterium and is the main pathogenic microorganism responsible for mastitis, which causes significant economic losses worldwide. Currently, there is no particularly effective treatment other than antibiotic therapy. Angiotensin-converting enzyme 2 (ACE2) plays an anti-inflammatory as well as an anti-injury role in numerous inflammatory diseases. Therefore, this study aimed to assess the hypothesis that S. uberis-induced mammary epithelial cells injury associated with ACE2, angiotensin II (Ang II) as well as angiotensin 1–7 (Ang-(1−7)) imbalance and that overexpression of ACE2 can repair S. uberis-induced mammary epithelial cells injury. We observed that the expression level of ACE2 was significantly downregulated after treatment of EpH4-Ev cells with S. uberis. Next, this assay verified the role of ACE2 in S. uberis-induced inflammatory injury in EpH4-Ev cells by overexpressing the ACE2 gene as well as its silencing. The results showed that overexpression of the ACE2 gene significantly activated the interleukin-10/signal transducer and activator of transcription 3/suppressors-of-cytokine-signaling 3 (IL-10/STAT3/SOCS3) pathway, thereby inhibiting the nuclear factor-κB (NF-κB) as well as pyroptosis pathways. Furthermore, overexpression of the ACE2 gene reversed the downregulation of zonula occludens 1 (ZO-1), Occludin, Claudin-1, and Claudin-2 caused by S. uberis, suggesting that ACE2 could promote to repair the blood-milk barrier. However, siRNA silencing of the ACE2 gene produced the opposite effect. These results suggest that ACE2 ameliorates S. uberis-induced mammary epithelial cells injury. Availability of dataAll data generated or analyzed during this study are included within the article and its additional information file.

Evaluation of Tenofovir Disoproxil Fumarate Treatment in Patients with Chronic Hepatitis B.

The main purpose of chronic hepatitis B (CHB) treatment is to improve the patients' life quality and prevent the disease from progressing to cirrhosis or hepatocellular carcinoma. Continuous suppression of hepatitis B virus (HBV) DNA with nucleoside or nucleotide analogues is the most critical way to achieve this goal. This study aimed to evaluate the CHB patients retrospectively followed up with tenofovir disoproxil fumarate (TDF) treatment. The study was planned as retrospective research by Afyonkarahisar Health Sciences University, Faculty of Medicine, Department of Infectious Diseases and Clinical Microbiology between January 2001 and December 2020. We evaluated all treatment-naive and treatment-experienced patients who received TDF (245 mg/day) treatment with the diagnosis of CHB. The data were obtained by reviewing the file information registered in the hospital automation system. HBsAg, Anti-HBs, HBeAg, Anti-HBe, HBV DNA, aspartate aminotransferase (AST), alanine aminotransferase (ALT) values of the patients were evaluated at 1st, 3rd, 6th, 12th months, and 6-month follow-ups throughout the treatment. Virological (HBV-DNA of < 50 IU/ml), biochemical (decrease below 40 IU/Ml in patients with pre-treatment value of ALT >40 IU/ml) and serological (Anti-HBe seroconversion in HBeAg positives and HBsAg negative and anti-HBs seroconversion in all patients) responses were examined. Adverse effects were also assessed during the treatment. Data from 131 patients who received TDF treatment were evaluated. Virological responses were determined as 78.6%, 81.3%, 94.2%, and 100% in the patients at 24th week, 48th week, 4th year, and 8th year, respectively. While there was no Anti-HBs seroconversion in any patients in four years of the treatment, it was observed at a rate of 10.5% in the eighth year. We did not determine any significant adverse effects requiring discontinuation of the treatment in the long-term follow-up of 131 patients under TDF treatment. As a result of our study, TDF was an effective and well-tolerated choice for CHB treatment.