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1.
Virol J ; 20(1): 154, 2023 07 18.
Article in English | MEDLINE | ID: mdl-37464440

ABSTRACT

BACKGROUND: We compared Fakhravac and BBIBP-Corv2 vaccines in a phase III trial. METHOD: We conducted a multicenter, parallel-group, active-control, non-inferiority clinical trial with pragmatic considerations assessing the safety and efficacy of Fakhravac and BBIBP-Corv2 vaccines. We started with two randomized double-blind arms and added two non-randomized open-label arms (based on participant preference) because of slow recruitment. The adult population received 0.5 ml (10 µg per dose) intramuscular injections of Fakhravac or BBIBP-Corv-2 vaccines 21 days apart. The primary outcome was the occurrence of PCR-positive symptomatic Covid-19 disease 14 days or more after the second injection. A 10% non-inferiority margin to the reported 72.8% efficacy of BBIBP-Corv2 was assumed. Cox proportional hazard modeling was used to estimate hazard ratios and their 95% confidence intervals. RESULT: We enrolled 24,056 adults in four groups (randomized-Fakhravac: 824, randomized-BBIBP-Corv2: 832; Non-randomized-Fakhravac: 19,429, Non-randomized-BBIBP-Corv2: 2971). All observed local and systemic adverse reactions were generally self-limited and resolved completely. We observed similar Serious Adverse Event (SAE) rates in the BBIBP-Corv2 (2.57, 95% CI 1.33-4.49) and Fakhravac (2.25, 95% CI 1.72-2.89) groups; none of which were related to the vaccines received. We recorded 9815 Medically Attendant Adverse Events (MAAE), 736 of which were categorized as somehow related. The rate of related MAAE in the Fakhravac was similar to the BBIBP-Corv2 groups (0.31 and 0.26 per 1000 person-day) in the randomized and considerably higher (0.24 and 0.07 per 1000 person-day) in the non-randomized arms. We observed 129 (35% of the 365 required by target sample size) events of PCR + symptomatic Covid-19 during four months of active follow-up in the randomized arm, demonstrating that those receiving the Fakhravac vaccine were significantly less likely (HR = 0.69; 95% CI 0.49-0.98) to be diagnosed with PCR + symptomatic Covid-19 compared with those receiving BBIBP-Corv2 vaccine. After adjusting for type I error using the O'Brien Fleming method, the Fakhravac vaccine was non-inferior to the BBIBP-Corv2 (assuming a 10% non-inferiority margin to the reported 72.8% BBIBP-Corv2 vaccine efficacy; HR < 1.35) (One-way test: HR = 0.66; 99.8% CI 0.38-1.15). In the non-randomized arm, the results were inconclusive (HR = 1.23; 95% CI 0.96-1.61). We observed 5 cases of hospitalized Covid-19 in the randomized arm, none of which occurred in the Fakhravac vaccine group. Those receiving the Fakhravac vaccine were four times less likely to go to the hospital because of a Covid-19 diagnosis (HR = 0.24; 95% CI 0.10-0.60). The vaccine efficacy of the Fakhravac vaccine is estimated to be 81.5% (95% CI 81-82.4%). CONCLUSION: Fakhravac inactivated SARS-CoV-2 vaccine has comparable safety and efficacy to the BBIBP-Corv2 vaccine. Trial registration This study was registered with the Iranian Registry of Clinical Trials ( www.irct.ir : IRCT20210206050259N3).


Subject(s)
COVID-19 Vaccines , COVID-19 , Adult , Humans , SARS-CoV-2 , COVID-19/prevention & control , COVID-19 Testing , Iran , Double-Blind Method
2.
BMC Infect Dis ; 23(1): 118, 2023 Feb 24.
Article in English | MEDLINE | ID: mdl-36829111

ABSTRACT

BACKGROUND: The FAKHRAVAC®, an inactivated SARS-CoV-2 vaccine, was assessed for safety and immunogenicity in a phase II trial. METHODS: We did a phase II, single-centered, randomized, double-blind, placebo-controlled clinical trial of the FAKHRAVAC inactivated SARS-CoV-2 vaccine on adults aged 18 to 70. The two parallel groups received two intramuscular injections of either a 10-µg vaccine or a placebo at 2-week intervals. The participants' immunogenicity responses and the occurrence of solicited and unsolicited adverse events were compared over the study period of up to 6 months. Immunogenicity outcomes include serum neutralizing antibody activity and specific IgG antibody levels. RESULTS: Five hundred eligible participants were randomly (1:1) assigned to vaccine or placebo groups. The median age of the participants was 36 years, and 75% were male. The most frequent local adverse reaction was tenderness (21.29% after the first dose and 8.52% after the second dose), and the most frequent systemic adverse reaction was headache (11.24% after the first dose and 8.94% after the second dose). Neutralizing antibody titers two and four weeks after the second injection in the vaccine group showed about 3 and 6 times increase compared to the placebo group (GMR = 2.69, 95% CI 2.32-3.12, N:309) and (GMR = 5.51, 95% CI 3.94-8.35, N:285). A four-fold increase in the neutralizing antibody titer was seen in 69.6% and 73.4% of the participants in the vaccine group two and four weeks after the second dose, respectively. Specific ELIZA antibody response against a combination of S1 and RBD antigens 4 weeks after the second injection increased more than three times in the vaccine compared to the placebo group (GMR = 3.34, 95% CI 2.5-4.47, N:142). CONCLUSIONS: FAKHRAVAC® is safe and induces a significant humoral immune response to the SARS-CoV-2 virus at 10-µg antigen dose in adults aged 18-70. A phase III trial is needed to assess the clinical efficacy. TRIAL REGISTRATION: Trial Registry Number: Ref., IRCT20210206050259N2 ( http://irct.ir ; registered on 08/06/2021).


Subject(s)
COVID-19 Vaccines , COVID-19 , Adult , Humans , Male , Female , SARS-CoV-2 , Antibodies, Neutralizing , Antibody Formation , Double-Blind Method , Immunogenicity, Vaccine , Antibodies, Viral
3.
AAPS PharmSciTech ; 24(7): 207, 2023 Oct 10.
Article in English | MEDLINE | ID: mdl-37817041

ABSTRACT

Drug solubility is of central importance to the pharmaceutical sciences, but reported values often show discrepancies. Various factors have been discussed in the literature to account for such differences, but the influence of manual testing in comparison to a robotic system has not been studied adequately before. In this study, four expert researchers were asked to measure the solubility of four drugs with various solubility behaviors (i.e., paracetamol, mesalazine, lamotrigine, and ketoconazole) in the same laboratory with the same instruments, method, and material sources and repeated their measurements after a time interval. In addition, the same solubility data were determined using an automated laser-based setup. The results suggest that manual testing leads to a handling influence on measured solubility values, and the results were discussed in more detail as compared to the automated laser-based system. Within the framework of unavoidable uncertainties of solubility testing, it is a possibility to combine minimal experimental testing that is preferably automated with mathematical modeling. That is a practical suggestion to support future pharmaceutical development in a more efficient way.


Subject(s)
Robotic Surgical Procedures , Solubility , Ketoconazole , Anticonvulsants , Lasers , Pharmaceutical Preparations
4.
J Biomed Inform ; 132: 104114, 2022 08.
Article in English | MEDLINE | ID: mdl-35717011

ABSTRACT

Deep transformer neural network models have improved the predictive accuracy of intelligent text processing systems in the biomedical domain. They have obtained state-of-the-art performance scores on a wide variety of biomedical and clinical Natural Language Processing (NLP) benchmarks. However, the robustness and reliability of these models has been less explored so far. Neural NLP models can be easily fooled by adversarial samples, i.e. minor changes to input that preserve the meaning and understandability of the text but force the NLP system to make erroneous decisions. This raises serious concerns about the security and trust-worthiness of biomedical NLP systems, especially when they are intended to be deployed in real-world use cases. We investigated the robustness of several transformer neural language models, i.e. BioBERT, SciBERT, BioMed-RoBERTa, and Bio-ClinicalBERT, on a wide range of biomedical and clinical text processing tasks. We implemented various adversarial attack methods to test the NLP systems in different attack scenarios. Experimental results showed that the biomedical NLP models are sensitive to adversarial samples; their performance dropped in average by 21 and 18.9 absolute percent on character-level and word-level adversarial noise, respectively, on Micro-F1, Pearson Correlation, and Accuracy measures. Conducting extensive adversarial training experiments, we fine-tuned the NLP models on a mixture of clean samples and adversarial inputs. Results showed that adversarial training is an effective defense mechanism against adversarial noise; the models' robustness improved in average by 11.3 absolute percent. In addition, the models' performance on clean data increased in average by 2.4 absolute percent, demonstrating that adversarial training can boost generalization abilities of biomedical NLP systems. This study takes an important step towards revealing vulnerabilities of deep neural language models in biomedical NLP applications. It also provides practical and effective strategies to develop secure, trust-worthy, and accurate intelligent text processing systems in the biomedical domain.


Subject(s)
Language , Natural Language Processing , Neural Networks, Computer , Reproducibility of Results
5.
J Biomed Inform ; 107: 103452, 2020 07.
Article in English | MEDLINE | ID: mdl-32439479

ABSTRACT

Text summarization tools can help biomedical researchers and clinicians reduce the time and effort needed for acquiring important information from numerous documents. It has been shown that the input text can be modeled as a graph, and important sentences can be selected by identifying central nodes within the graph. However, the effective representation of documents, quantifying the relatedness of sentences, and selecting the most informative sentences are main challenges that need to be addressed in graph-based summarization. In this paper, we address these challenges in the context of biomedical text summarization. We evaluate the efficacy of a graph-based summarizer using different types of context-free and contextualized embeddings. The word representations are produced by pre-training neural language models on large corpora of biomedical texts. The summarizer models the input text as a graph in which the strength of relations between sentences is measured using the domain specific vector representations. We also assess the usefulness of different graph ranking techniques in the sentence selection step of our summarization method. Using the common Recall-Oriented Understudy for Gisting Evaluation (ROUGE) metrics, we evaluate the performance of our summarizer against various comparison methods. The results show that when the summarizer utilizes proper combinations of context-free and contextualized embeddings, along with an effective ranking method, it can outperform the other methods. We demonstrate that the best settings of our graph-based summarizer can efficiently improve the informative content of summaries and decrease the redundancy.


Subject(s)
Natural Language Processing , Unified Medical Language System , Language , Semantics
6.
J Cancer Educ ; 34(4): 796-802, 2019 Aug.
Article in English | MEDLINE | ID: mdl-29926433

ABSTRACT

School-based education programs can be an effective way of educating adolescents about the dangers of exposure to sunlight and about preventive measures against this exposure and its relation to skin cancer. The aim of this study is to survey the effect of educational intervention based on the PRECEDE model on promoting skin cancer preventive behaviors in high school students of Fasa City, Fars Province, Iran. In this quasi-experimental study, 300 students (150 in experimental group and 150 in control group) in Fasa City, Fars Province, Iran, were selected in 2016-2017. The educational intervention for the experimental group consisted of six training sessions. A questionnaire consisting of demographic information, PRECEDE constructs (knowledge, attitude, self-efficacy, enabling factors, and social support), was used to measure skin cancer preventive behaviors before and 4 months after the intervention. Data were analyzed using SPSS 22 and paired t test, independent t test, and chi-square test at a significance level of p < 0.05. The mean age of the students was 16.05 ± 1.76 years in the experimental group and 16.20 ± 1.71 years in the control group. Four months after the intervention, the experimental group showed a significant increase in the knowledge, attitude, self-efficacy, enabling factors, social support, and skin cancer preventive behaviors compared to the control group. This study showed the effectiveness of the intervention based on the PRECEDE constructs in adoption of skin cancer preventive behaviors in 4 months post-intervention in students. Hence, this model can act as a framework for designing and implementing educational intervention for the prevention of skin cancer.


Subject(s)
Health Education/methods , Health Knowledge, Attitudes, Practice , Models, Educational , Skin Neoplasms/prevention & control , Skin Neoplasms/psychology , Students/psychology , Adolescent , Case-Control Studies , Humans , Iran/epidemiology , Male , Non-Randomized Controlled Trials as Topic , Self Efficacy , Skin Neoplasms/epidemiology , Surveys and Questionnaires
7.
J Biomed Inform ; 88: 53-61, 2018 12.
Article in English | MEDLINE | ID: mdl-30445218

ABSTRACT

Automatic text summarizers can reduce the time required to read lengthy text documents by extracting the most important parts. Multi-document summarizers should produce a summary that covers the main topics of multiple related input texts to diminish the extent of redundant information. In this paper, we propose a novel summarization method named Clustering and Itemset mining based Biomedical Summarizer (CIBS). The summarizer extracts biomedical concepts from the input documents and employs an itemset mining algorithm to discover main topics. Then, it applies a clustering algorithm to put the sentences into clusters such that those in the same cluster share similar topics. Selecting sentences from all the clusters, the summarizer can produce a summary that covers a wide range of topics of the input text. Using the Recall-Oriented Understudy for Gisting Evaluation (ROUGE) toolkit, we evaluate the performance of the CIBS method against four summarizers including a state-of-the-art method. The results show that the CIBS method can improve the performance of single- and multi-document biomedical text summarization. It is shown that the topic-based sentence clustering approach can be effectively used to increase the informative content of summaries, as well as to decrease the redundant information.


Subject(s)
Data Mining/methods , Image Processing, Computer-Assisted/methods , Natural Language Processing , Software , Algorithms , Cluster Analysis , Pattern Recognition, Automated , Semantics , Unified Medical Language System
8.
Iran J Kidney Dis ; 17(3): 126-134, 2023 05.
Article in English | MEDLINE | ID: mdl-37337796

ABSTRACT

INTRODUCTION: Indoxyl sulfate (IS) and para-cresol (p-cresol) are uremic toxins with high protein bonding index that accumulate in the body with decreasing kidney function. The main purpose of the current investigation was to compare the concentration of p-cresol and IS in serum of the type II diabetic individuals with and without nephropathy. METHODS: Fifty-five patients with type II diabetes mellitus were divided into two groups: case and control. The case group consisted of 26 diabetic patients with nephropathy (proteinuria and serum creatinine below 1.5 mg/dL) without any other kidney diseases. The control group included 29 patients without diabetic nephropathy. Patients with advanced heart disease, cerebrovascular accident and other inflammatory or infectious diseases were excluded. Five mL of venous blood was taken from each patient in the morning fasting state. Then other laboratory tests including serum uric acid and creatinine levels, serum urea nitrogen, lipids and glucose were measured by standard methods. P-Cresol and IS levels were measured by the spectrofluorimetric method after extraction. We also filled out a checklist with information regarding the duration of their disease, medication history (oral or injectable), and other demographic information. There were no significant differences between the two groups regarding the investigated factors Results. There were no significant difference among the investigated factors between the two groups (P > .05) except for the serum creatinine, proteinuria and estimated glomerular filtration rate, where the mean values of cases were considerably higher than those of the controls. Serum IS and p-cresol levels were also significantly higher in the case group (P < .05). CONCLUSION: According to the findings, it seems that IS, and p-cresol may play a role in the development of diabetic nephropathy and other complications of diabetes mellitus.  DOI: 10.52547/ijkd.7266.


Subject(s)
Diabetes Mellitus, Type 2 , Diabetic Nephropathies , Humans , Diabetic Nephropathies/diagnosis , Diabetic Nephropathies/etiology , Indican/therapeutic use , Diabetes Mellitus, Type 2/complications , Creatinine , Uric Acid , Proteinuria
9.
Sci Data ; 10(1): 528, 2023 08 08.
Article in English | MEDLINE | ID: mdl-37553439

ABSTRACT

Large language models (LLMs) such as GPT-4 have recently demonstrated impressive results across a wide range of tasks. LLMs are still limited, however, in that they frequently fail at complex reasoning, their reasoning processes are opaque, they are prone to 'hallucinate' facts, and there are concerns about their underlying biases. Letting models verbalize reasoning steps as natural language, a technique known as chain-of-thought prompting, has recently been proposed as a way to address some of these issues. Here we present ThoughtSource, a meta-dataset and software library for chain-of-thought (CoT) reasoning. The goal of ThoughtSource is to improve future artificial intelligence systems by facilitating qualitative understanding of CoTs, enabling empirical evaluations, and providing training data. This first release of ThoughtSource integrates seven scientific/medical, three general-domain and five math word question answering datasets.

10.
Vaccine X ; 15: 100401, 2023 Dec.
Article in English | MEDLINE | ID: mdl-37941802

ABSTRACT

Background: The FAKHRAVAC®, an inactivated SARS-CoV-2 vaccine, was assessed for safety and immunogenicity. Methods and findings: In this double-blind, placebo-controlled, phase I trial, we randomly assigned 135 healthy adults between 18 and 55 to receive vaccine strengths of 5 or 10 µg/dose or placebo (adjuvant only) in 0-14 or 0-21 schedules. This trial was conducted in a single center in a community setting. The safety outcomes in this study were reactogenicity, local and systemic adverse reactions, abnormal laboratory findings, and Medically Attended Adverse Events (MAAE). Immunogenicity outcomes include serum neutralizing antibody activity and specific IgG antibody levels.The most frequent local adverse reaction was tenderness (28.9%), and the most frequent systemic adverse reaction was headache (9.6%). All adverse reactions were mild, occurred at a similar incidence in all six groups, and were resolved within a few days. In the 10-µg/dose vaccine group, the geometric mean ratio for neutralizing antibody titers at two weeks after the second injection compared to the placebo group was 9.03 (95% CI: 3.89-20.95) in the 0-14 schedule and 11.77 (95% CI: 2.77-49.94) in the 0-21 schedule. The corresponding figures for the 5-µg/dose group were 2.74 (1.2-6.28) and 5.2 (1.63-16.55). The highest seroconversion rate (four-fold increase) was related to the 10-µg/dose group (71% and 67% in the 0-14 and 0-21 schedules, respectively). Conclusions: FAKHRAVAC® is safe and induces a strong humoral immune response to the SARS-CoV-2 virus at 10-µg/dose vaccine strength in adults aged 18-55. This vaccine strength was used for further assessment in the phase II trial.Trial registrationThis study is registered with https://www.irct.ir; IRCT20210206050259N1.

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