Background: Clinical pharmacists are a critical part of antibiotic stewardship. Stewardship often relies on relationships and persuasion, which may be affected by gender bias. Thus, we aimed to assess the association of sex with the acceptance of antibiotic stewardship recommendations. Methods: Between May and October 2019, medicine pharmacists at single hospital reviewed patients on antibiotics and–when a discharge was anticipated–led an antibiotic discussion (or “timeout”) prior to discharge. To explore differences in antibiotic timeout effectiveness by gender, we assessed the association of pharmacist sex with suggestion and acceptance of antibiotic changes using logistic regression controlling for patient characteristics. We also assessed whether hospitalist sex was associated with or moderated the effect of pharmacist sex on acceptance of timeout recommendations. Results: Between May 1, 2019, and October 31, 2019, pharmacists conducted 295 timeouts (patient characteristics in Fig. Conclusions: In this discharge antibiotic intervention, timeouts conducted by women were less likely to result in an antibiotic change than those conducted by men. The difference in effectiveness resulted both from female pharmacists being less likely to recommend a change and from hospitalists being less likely to accept recommendations from a female pharmacist. These findings suggest that gender bias may play a role acceptance of antibiotic stewardship recommendations, which could affect antibiotic use, pharmacist job satisfaction, and patient outcomes.Funding: NoneDisclosures: None


The interface performance of steel fiber-reinforced concrete (SFRC) is a critical factor in determining mechanical properties and durability. The degradation of the concrete matrix and micro-structure interface is caused by environmental erosion, which shortens the service life of the structure design. Considering different volume contents of steel fiber , the failure mechanism of SFRC under different environmental erosion conditions was studied through a laboratory test scheme. A total of six environmental factors are selected, including water, sodium chloride solution, sodium sulfate solution, dilute sulfuric acid solution, sodium hydroxide solution, and a freeze-thaw cycle. When subjected to different erosion concentrations and periods, micro-structure and axial bearing capacity deterioration laws are compared and analyzed. A durability equation related to fiber mixture ratio and strength is presented based on the experimental data and the numerical simulation method. The influence of different environments on steel fiber-reinforced concrete is analyzed, and the grey correlation degree of axial compressive strength is analyzed. The experimental results show that steel fiber can effectively improve the concrete axial bearing capacity, but different responses are observed under the various erosion conditions. A freeze-thaw cycle environment has the most significant impact on the axial compressive strength of concrete, followed by the sulfuric acid environment, and other environments have a weaker impact. The research results will provide a theoretical basis for predicting the performance deterioration of SFRC concerning other erosion conditions and periods. Concrete is a composite material with high overall strength, excellent durability, good workability, and volume stability. It is widely used in ocean dam waterproofing, airport pavements, long-span steel bridge deck pavement, railway, and national defense ,4,5,6,7.The service life of concrete buildings and structures is closely related to the durability of the materials. Due to the differences in use function and environment, concrete materials are often corroded by various ions, which significantly impacts the durability of concrete structures ,9,10. InThe damage mentioned above and degradation of concrete in a single environment are the main ones, but a comprehensive comparative study on microstructure and axial bearing capacity of steel fiber reinforced concrete under freeze-thaw cycles and various chemical attacks are lacking. Therefore, a durability test was carried out to study the mechanical properties of steel fiber reinforced concrete (SFRC) with different content in different erosion environments. In this study, three kinds of steel fiber content were designed, and steel fiber-reinforced concrete specimens with volume fractions of 0%, 1%, and 2% were made for comparative study. At the same time, six external environments, including water, sodium chloride solution, sodium sulfate solution, dilute sulfuric acid solution, sodium hydroxide solution, and a freeze-thaw cycle were set up. Furthermore, six cylindrical specimens (4 in each group) were made for the axial compression and cross-section microscopic observation tests. By comparing the compressive strength and microstructure of SFRC with different dosages in different erosion environments, the correlation between SFRC damage and environment is analyzed, which provides a theoretical basis for durability design and evaluation of SFRC structure and ensures its safety in structural engineering.The specimen components include coarse aggregate, fine aggregate, cement, water, and steel fiber. Gravel is used as coarse aggregate with a silt content of 0.7%, divided into two particle size zones: 4.75 mm to 9.5 mm and 9.5 mm to 19 mm, with a mixing ratio of 3:7. Natural river sand is used as fine aggregate with a water content of 4% and a fineness modulus of 2.3. All indexes meet the specification requirements, as shown in The steel fiber was milled from steel ingots produced by Shanghai Helex Technology Co., Ltd.  is shown in The compressive strength grade of concrete is C30, and a water–cement ratio of 0.54 is used . Therefo3 cube, with three specimens in each group and nine specimens with three different steel fiber contents. The axial compression concrete test specimens used Φ100 × 200 mm3 cylinders. There are four samples in each group . Three kinds of concrete cylindrical specimens with different steel fiber contents and six different corrosive environments  were selected, and 156 specimens were used in the experiment.In this experiment, the volume content of steel fiber is selected for 0%, 1%, and 2%, respectively. The size of concrete compressive strength specimens is 150 × 150 × 150 mmCoarse aggregate and fine aggregate were sieved and weighed, then put into a concrete mixer for dry mixing for 2 min, then water was added for mixing for 3–5 min, and finally evenly sprinkled with a specified amount of steel fiber for mixing for 2–5 min. Next, coarse and fine aggregate were sieved, weighed and put in a concrete mixer for dry mixing for 2 min, then water was added and stirred for 3–5 min. Finally, a specified amount of steel fiber was evenly sprinkle and stirred for 2–5 min. Next, the prepared fiber concrete was added into the mold twice, and vibrated for 20–30 s. During the vibrating process, the vibrating rod is inserted and tamped many times to improve the compactness. After curing for 24 h, the mold was removed and put into the curing room for curing for 28 days, as shown in Six environmental factors were selected in this study: water, sodium chloride solution, sodium sulfate solution, dilute sulfuric acid solution, sodium hydroxide solution, and a freeze-thaw cycle. The specific test method is as follows.The laboratory rapid freeze-thaw method and KRD-V5 concrete rapid freeze-thaw testing machine were used. At the end of each freezing cycle, the center temperature of the sample was −18 °C ± 2 °C. Similarly, at the end of the melting cycle, the center temperature of the sample is +7 °C ± 2 °C, and a freeze-thaw cycle is completed in 2–4 h. The specimen was placed in a freeze-thaw tester, water added, and the liquid level was 5 cm above the surface of the specimen. The number of large cycles was set to 100 and minor cycles to 25 times.2SO4 solution, 5%H2SO4 solution and 2 mol/L NaOH solution were prepared as shown in The 3.5%NaCl solution, 10%NaThe cured cylindrical specimen was placed as shown in A digital optical microscope was used  to obserThe bearing capacity under axial pressure was tested . When suAfter 100 freeze-thaw cycles, soaking in sodium chloride solution, sodium sulfate solution, sulfuric acid solution, and sodium hydroxide solution for 28 days. The surface (position 1) and cross-section  of three kinds of specimens with different fiber contents were observed microscopically, and 100 times magnification was selected to compare the influence degree of different environments on the specimens.After different kinds of environmental erosion, except water immersion, cracks appeared on the surfaces of different kinds of micro-concrete specimens under the action of other environments. From the microscopic results, comparing the number and depth of cracks, adding steel fiber did not inhibit the cracks on the surfaces of specimens. Compared with six kinds of erosion environments, the freeze-thaw cycle and sulfuric acid environment have the most decisive influence on the surface cracks for the three kinds of specimens. In contrast, water has a minor influence on the cracks.Microscopic observation of position 2 after environmental erosion shows that the magnification is 100 times. Microscopic observation of position 2 after environmental erosion shows that the magnification is 100 times. Microscopic observation of position 2 after environmental erosion shows that the magnification is 100 times. Comparing the microscopic observation results of position 2, the concrete without steel fiber is cracked after the freeze-thaw cycle and NaCl environmental erosion. However, only the freeze-thaw cycle environmental erosion causes cracks in the specimen after adding steel fiber. Comparing the two dosages, the concrete cracks with 2% content are minor, which shows that steel fiber can inhibit the internal cracks of concrete, thus reducing the environmental damage to concrete. Adding 2% concrete is more effective than 1% concrete. It can be known that the freeze-thaw cycle has the most significant influence on the damage to concrete specimens in the six erosion environments. Comparing the microscopic results of position 3, as shown in There is no crack in the center of the concrete cross-section with different fiber content in the other five environments. In this paper, after soaking in NaCl solution, as shown in Comparing the three locations, except for the water environment, all the specimens with three dosages have cracks on their surfaces in location 1. Similarly, except for the cracks caused by the freeze-thaw cycle, only the cracks were caused by plain concrete after soaking in NaCl solution in location 2. Therefore, the environmental erosion on the specimen surface is more significant than inside, indicating environmental damage is from outside to inside. Compared with positions 2 and 3, the same point is that freeze-thaw cycles have destroyed concrete specimens under six kinds of environmental erosion. The length and width of cracks decrease with the increase of steel fiber. This observation shows that the freeze-thaw cycle has the most significant influence on the damage to concrete, and adding steel fiber can inhibit the development of cracks in concrete specimens. That is, it can inhibit the damage to concrete.The concrete cubic compressive test is set up in The test shows that the increase in steel fiber content has a positive effect on the compressive strength of SFRC. When the fiber content is 1% and 2%, the compressive strength increases by 11.4% and 30.6%, respectively. The addition of steel fiber can inhibit the transverse deformation of concrete and improve the compressive strength of concrete. However, due to the existence of steel fibers, a harmful interface is formed between the concrete and steel fiber. The interface area is suddenly destroyed when the compression load reaches a specific value.Cylindrical concrete specimens with a steel fiber content of 0%, 1%, and 2% were subjected to an axial compression test after 100 freeze-thaw cycles and 28 days in different solutions. An axial compression test is carried out on cylinder specimens before erosion, and the test results are shown in A schematic diagram of the axial compression test of specimens with other volume content of steel fiber is shown in The axial compression test results of cylindrical specimens are shown in The table can show that the intensity changes are different under different erosion environments. After adding steel fiber into concrete, the compressive strength of concrete in various environments mainly increases with the increase in steel fiber. Compared with ordinary concrete, the compressive load of the steel-fiber concrete is improved. When the pressure direction of fiber in the member is oriented vertically, it can effectively stop the transverse deformation and show the best reinforcement effect. With the increase in soaking time, the soaked water specimens are considered the control group. The axial compressive strength of the specimens soaked in other solutions decreased, indicating that various adverse environments have large or small destructive effects on the concrete specimens. The steel fiber can effectively prevent the corrosion of the chemical environment on the concrete. Generally speaking, the more steel fiber is added, the higher the strength of the specimen. However, with the decrease in erosion failure strength, the strength of the specimen with the same fiber volume content is different in different erosion environments. The influence of different environments on the strength of steel fiber-reinforced concrete needs further study.2SO4 environment, adding 2% steel fiber is worse than adding 1% steel fiber, and it also reduces the mechanical properties of concrete. After adding 2% steel fiber, the mechanical properties of specimens are less than those of plain concrete, which makes the addition of fiber negatively correlated with compressive strength, so it is not always the case that adding more steel fiber will achieve better results. Therefore, it is essential to carry out experimental research before steel fiber is applied to practical construction projects, which can avoid the waste of material resources and the adverse effects caused by improper mix proportions.The experimental data show that adding steel fiber in different erosion environments is beneficial. Adding more steel fiber in most environments will have better mechanical properties, effectively resisting the damage of adverse environments. However, in the NaCl and NaAdding excessive steel fiber in the environment of sodium chloride and sodium sulfate not only causes material waste, but also adversely affects the performance of building structures.According to the microscopic observation results, it can be seen that freeze-thaw cycles have the greatest impact on the concrete specimen. According to the strength changes before and after 100 freeze-thaw cycles, the strength loss rate is calculated, which is the ratio of the change before and after erosion to the compressive strength before erosion. The strength increase rate is the ratio of the strength after erosion to the compressive strength before erosion of the plain concrete. After 100 freeze-thaw cycles, the compressive strength of the specimens with 0%, 1% and 2% content lost 35.0%, 33.7% and 34.5% respectively. The compressive strength of steel fiber reinforced concrete specimens with 1% and 2% content increased by 17.6% and 69.2% respectively. From the calculated value, it can be concluded that adding steel fiber can effectively inhibit the damage of concrete caused by freeze-thaw cycle, and the effect of adding 2% steel fiber is better than that of adding 1% volume fraction steel fiber.After freezing and thawing for 100 times and soaking for 28 days, the relationship between all data of axial compressive strength of various cylindrical specimens and steel fiber content was numerically simulated and analyzed. The fitting curve is shown in The figure shows that concrete with different fiber contents has different erosion degrees in different environments. After adding steel fiber, the axial compressive strength of concrete is improved, and the optimum range of steel fiber is different in different environments. The regression analysis results are shown in The results show that concrete with different fiber content has different erosion degrees in different environments. After adding steel fiber, the axial compressive strength of concrete is improved, and the optimum range of steel fiber is different in different environments. The addition of steel fiber significantly improves the compressive strength of concrete, but in not all environments, the more steel fiber is added, the better. Adding too much steel fiber in a sodium chloride environment and sodium sulfate environment will be counterproductive. According to the test results, the optimal dosage is 1% in a sodium sulfate and sodium chloride environment, and 2% in a sulfuric acid and sodium hydroxide environment.Grey relational analysis is a statistical analysis technique that originates from the grey system theory in the system science theory. It is suitable for the quantitative analysis of the dynamic development process, and there will be no discrepancy between the quantitative and qualitative results.Compared with traditional analysis methods, such as variance analysis or regression analysis, which only take a single index as the measurement standard, the grey correlation degree analysis can comprehensively and genuinely reflect the changes of comprehensive factors by comparing multiple traits. As a result, its comprehensive evaluation results are more scientific and accurate ,41,42.Grey correlation analysis theory is an integral part of grey system theory, and correlation is the correlation between the reference and influencing factors. The greater the correlation, the greater the correlation value, and the more sensitive the influencing factors are to comparative factors. This study divides the grey correlation analysis into six steps ,44.0 = , Compare the sequence Xi = , where i = 1, 2, 3…, n. The data sequence that reflects the characteristics of system behavior is called the reference sequence. A data sequence composed of factors that affect system behavior is called a comparative sequence.Step 1: Select the reference sequence X0. The axial compressive data sequences of concrete specimens soaked in sodium chloride solution, sodium sulfate solution, dilute sulfuric acid solution, and sodium hydroxide solution and the frozen-thawed cycle is taken as the comparison sequences. From the numerical simulation analysis, it can be seen that the optimal content of steel fiber is different in different environments. However, considering the economy and applicability, the data of 1% volume content of steel fiber is selected in the grey correlation analysis, and the data of reference sequence and comparison sequence are shown in This paper takes the axial compressive strength of concrete specimens soaked in water as the reference sequence Xi = Xi/xi1 = , i = 0, 1, 2, 3…, m. The above Step 2: Dimensionless processing of variables. Due to the different physical meanings of the factors in the system, the data dimensions are not necessarily the same, which makes it inconvenient to compare or difficult to obtain a correct conclusion when comparing. Therefore, dimensionless data processing is generally required when analyzing the grey correlation degree. Common methods include the initial value method and the average value method. Here, the initial value method is used to obtain X’Step 3: Find the business trip sequence, maximum and minimum difference.0i(k) = |x’0(k) − x’i(k)|, k = 1, 2, …, n.Sequence difference is ΔThe maximum difference of n is: M = Maxi Maxk Δi (k), and the minimum difference is: m = Mini Mink Δi(k).The difference sequence values are calculated from Step 4: Calculate the correlation coefficient. The degree of correlation is essentially the difference in geometric shapes between curves. Therefore, the difference between curves can be used to measure the correlation degree.r(x0(k), xi(k)) = (m + §M)/(Δ0i(k) + §M), § ∈ . k = 1, 2, …, n. i = 0, 1, 2, …, m. Where § is the resolution coefficient, which is often taken as 0.5.The maximum difference between two poles M = 0.624, the minimum difference between two poles m = 0, and the resolution = 0.5, respectively, can be used to obtain the grey correlation coefficient and grey correlation degree see .Step 5: Find the correlation degree. Because the correlation coefficient is the correlation degree value between the comparison series and the reference series at each moment (each point in the curve), it has more than one number. The information is too scattered to make an overall comparison. Therefore, it is necessary to concentrate the correlation coefficient of each moment (each point in the curve) into one value, that is, to find its average value, which can be used as a quantitative expression of the correlation degree between the comparison series and the reference series.0, x1) = 0.567, r = 0.642, r = 0.824, r = 0.798, r = 0.845.According to the above results, we can know that r > r > r > … > r, it means that xi is better than xj, xj is better than xk, and so on. xi > xj > xk > … > xz. xi > xj indicates that the grey correlation degree of factor xi to reference sequence x0 is greater than xj. The greater the correlation, the stronger the closeness between this group of factors and parent factors.Step 6: Analyze the results. If r. For example, the best content is 2% in the freeze-thaw cycle, dilute sulfuric acid and sodium hydroxide, and the best content is 1% in sodium chloride and sodium sulfate. Adding excessive steel fiber in the environment of sodium chloride and sodium sulfate not only causes material waste, but also adversely affects the performance of building structures.This study only compares the existence, length, and quantity of cracks in different erosion environments and cannot find out the influence of different environments on the development of concrete surface and internal cracks. Furthermore, there is limited research on crack width and specific crack size, which is also the limitation and deficiency of this research, and further research is necessary.


Helicobacter pylori antibiotic resistance, that are not present in common antibiotic resistance KBs or publications studying H. pylori. These genes would be candidates for further lab-based antibiotic research and inclusion in these KBs. For relation extraction, state-of-the-art deep learning models were used. These models were trained on a newly developed silver corpus which was generated by distant supervision of abstracts using the facts obtained from KBs. The top performing model was superior to a co-occurrence model, achieving a recall of 95%, a precision of 60% and F1-score of 74% on a manually annotated holdout dataset. To our knowledge, this project was the first attempt at developing a complete text mining pipeline that incorporates deep learning models to extract gene-antibiotic resistance relations from the literature. Additional related data can be found at https://github.com/AndreBrincat/Gene-Antibiotic-Resistance-Relation-ExtractionThe detection of bacterial antibiotic resistance phenotypes is important when carrying out clinical decisions for patient treatment. Conventional phenotypic testing involves culturing bacteria which requires a significant amount of time and work. Whole-genome sequencing is emerging as a fast alternative to resistance prediction, by considering the presence/absence of certain genes. A lot of research has focused on determining which bacterial genes cause antibiotic resistance and efforts are being made to consolidate these facts in knowledge bases (KBs). KBs are usually manually curated by domain experts to be of the highest quality. However, this limits the pace at which new facts are added. Automated relation extraction of gene-antibiotic resistance relations from the biomedical literature is one solution that can simplify the curation process. This paper reports on the development of a text mining pipeline that takes in English biomedical abstracts and outputs genes that are predicted to cause resistance to antibiotics. To test the generalisability of this pipeline it was then applied to predict genes associated with  The increasing prevalence of antibiotic-resistant bacteria is one of the greatest challenges humanity is currently facing . With thHelicobacter pylori. This organism is estimated to infect the stomachs of more than half of the world’s human population and is seen to be very common in developing countries, having a prevalence of up to 80%  models, BioBERT and PCNN, using subsets of the silver standard corpus composed of single-entity and multi-entity training dataset configurations.H. pylori using the developed pipeline. These genes were found to be linked with metronidazole resistance in other bacterial species and are candidates for further lab-based testing involving H. pylori.We propose potentially novel genes for metronidazole resistance in The is organized as follows: Section 2 presents a literature review of related works; Section 3 outlines the developed pipeline in detail; Section 4 and 5 present and discuss the results respectively and lastly, Section 6 presents the conclusions of the paper.Relation extraction (RE) is a task of interest in natural language processing (NLP) that studies automated extraction of relations from text. Relations can be defined as triplets consisting of two entities, and an association or property that links them together . Entitieet al. , initially using rule-based approaches that incorporated entity co-occurrences and pattern matching, as was tackled by Ng and Wong . Methodset al. , who inc . The PubTator Application Programming Interface (API) was used to obtain raw abstract texts from PubMed as well as metadata related to the publications and annotations of various biomedical entities. As for the gene-antibiotic resistance facts, these were obtained from CARD (https://card.mcmaster.ca/) and UniProtKB (www.uniprot.org/).The documents used were in the form of English abstracts obtained from PubMed/PubTator  dataset was also produced for evaluation of the final models.RE was carried out using deep-learning models. Once trained, the models were evaluated on the holdout dataset.H. pylori gene and antibiotic mentions. This was used to further validate the prediction outputs.The best performing model was applied on abstracts containing https://pubmed.ncbi.nlm.nih.gov/) using: ‘ NOT (“review”[Publication Type])) AND  AND )’. Additionally, all literature referenced in CARD and all publications mentioning genes linked to the Gene Ontology (GO) (http://geneontology.org/) term for ‘response to antibiotic’ in UniProtKB using the query ‘goa:(“response to antibiotic [46 677]”) taxonomy: “Bacteria [2]”’ were included. The obtained list of publication identifiers (PMIDs) was then used to obtain a total of 61 219 abstracts from PubTator.English abstracts were obtained by querying PubMed  and automatically annotated (TrEMBL) gene entries. Moreover, UniProtKB is linked to several other biomedical databases including the GO. Linking to GO terms can occur both through manual curation and automated inferences. For the scope of this paper, all manual and automated entries were included in order to increase recall of known genes with responses to different antibiotics at the cost of including false relations. However, only those genes that explicitly stated which antibiotics were involved in their resistance were kept, which helped to keep possible false relations to a minimum. This information was obtained from the ‘Function [CC]’ field of UniProtKB which often contains references linking to publications stating those assertions.s), and the addition of other terms of relevance such as ‘multidrug’ and ‘multi-drug’, which themselves are not antibiotics but are terms used to refer to resistance to multiple types of antibiotics. These amounted to a total of 405 antibiotic entities.The NER system developed was based on dictionary searches of all known gene identifiers and antibiotics. A list of bacterial gene identifiers  was generated from UniProtKB which resulted in 31 146 310 unique entries. The dictionary of antibiotics was generated by extracting all antibiotic terms found in CARD. Several additional antibiotic entities were manually added by the additional of plurals . A total of 29 935 unique sentences were obtained that had at least one gene and one antibiotic mention. To increase the dataset quality, both short sentences having character lengths of less than 25 and long sentences with character lengths of more than 600 were removed. From these sentences, 81 889 candidate gene-antibiotic relations were extracted. Extracted candidate relations that were present in the KBs were labelled as ‘relation’ while those that were not present in the KBs were labelled as ‘NA’. It is reasonable to assume that not all possible gene-antibiotic resistance facts are present in the KBs used. This has the implication that multiple gene-antibiotic relations that are true but not present in the KBs will be incorrectly labelled as ‘NA’ . To reduce incorrectly labelling these cases in the training datasets, only those candidate relations having gene entities present in the KBs were considered for labelling, while the rest were removed. Additional filtering was required to prevent several false negatives. While in the literature the term ‘multidrug’ (which is detected as an antibiotic entity in the developed NER module) can be used to refer to resistance to several antibiotics, this proved difficult to link in KBs where an explicit relation of a gene-multidrug resistance was not present. Thus, candidate relation pairs extracted from texts having genes paired to ‘multidrug’ were removed since a number of them could possibly be labelled incorrectly as ‘NA’. The only exceptions were cases where a candidate relation containing ‘multidrug’ was explicitly found in the KBs, which usually were found in UniProtKB. These were kept and labelled as ‘relation’.NER was carried out by using the annotated output of PubTator using a custom dictionary-based approach for genes and antibiotics. Genes were normalized to their UniRef50 cluster IDs which refer to clusters where the protein sequences of each gene member in that cluster have a 50% sequence identity with the seed sequence of the cluster. By using the UniRef50 IDs, genes that are highly similar in their sequence  and that could have been referred to with different gene identifiers in the literature, can still be grouped together. For example, the gene Several extracted sentences contained more than one antibiotic and gene candidate relation. These sentences were expected to be more difficult for the models to learn meaningful patterns from than sentences with a single candidate relation. To test this, several different training and validation sets were produced to study the impact of the different types of data subsets used on the models’ performances. https://prodi.gy/) annotation toolkit, using 600 randomly selected candidate relations obtained from unique sentences not present in the training and validation datasets, of which 541 were used following further manual inspection. When grouped by gene-antibiotic entity pairs (using the gene UniRef50 ID and the antibiotic main group ID) the testing dataset consisted of 186 bags with the ‘relation’ label and 235 bags with the ‘NA’ label  dataset was manually annotated by an expert in antibiotic resistance using the prodigy . python package were used for this task. A total of 4 different model configurations were used  model was based on the implementation of Soares et al.  contained sentences with both a gene and antibiotic mention. Sentences containing both entities are sentences that potentially express a relation between the genes and antibiotics mentioned. This study only considered sentence-level relations, at the cost of missing any gene-antibiotic relations which are expressed between multiple sentences. In fact, an additional 20 349 (34%) abstracts contained gene and antibiotic mentions without ever occurring in the same sentences. After segmenting the abstracts into different sentences, a total of 29 935 unique sentences were obtained that contained both gene and antibiotic mentions. On average, these sentences had more than one unique gene and antibiotic mention see .Several sentences contained combinations of the same genes and antibiotics. These represented well-studied genes that are known to cause antibiotic resistance. All possible combinations of gene and antibiotic mentions found in the different sentences were all candidate relations. Each sentence could have multiple candidate relations depending on the number of possible combinations of gene and antibiotic entities present. The example below was obtained from PubTator and illustrates a sentence having two candidate relations which in this case were positive relations.H. pylori. A total of 81 889 candidate relations were obtained from all sentences, out of which 4976 were identified as being related to The quality of the silver standard corpus was evaluated using the manually annotated holdout dataset refer to . A degreKnown gene-antibiotic relations (facts) were obtained from the CARD and UniProt KBs. These amounted to 42 380 unique facts when considering all gene identifiers and antibiotic names, and 2455 unique facts when considering Gene UniRef50 IDs and antibiotic groups refer to .H. pylori. From the 4976 candidate relations, 3369 were predicted to contain true relations (67.7%). All these candidate relations were not present in the KBs used at the time of writing. The number of unique gene-antibiotic relations amounted to 956 out of which 750 (78.5%) were not found in sentences obtained from abstracts of publications studying H. pylori, suggesting that these relations have not been directly studied in association with H. pylori. However, this was still limited by mentions in the abstracts and does not exclude the possibility of these relations being mentioned in the main body of other publications studying H. pylori.To further validate the pipeline, we applied it to extract gene-antibiotic relations for H. pylori were mostly obtained from those studying Escherichia coli—a highly researched organism that is used for a multitude of different experiments, including antibiotic resistance experimentation  or presence of genes that cause resistance (association via presence). In either case, an association is present. From manual reviewing of sentences, whenever negation occurred, it was used to indicate cases of association via absence or complete lack of an association. Using the python package negspaCy v.1.0.0 we obtained estimates for the prevalence of negations in the training dataset as being 7.6% and 5.0% for positive (relation) and negative (NA) samples respectively and in the case of the prediction dataset as being 9.7% and 8.2% for positive (relation) and negative (NA) samples respectively. Thus, the negation prevalence estimates in both the training and predictions were low. In the case of the predictions, certain negated sentences were incorrectly predicted as having an association such as:However, other negation sentences were also correctly predicted as having no relation:Moreover, cases of negation expressing association via absence were correctly predicted:While RE has been studied for various biomedical tasks it has not been investigated in the field of antibiotic resistance research. Instead, several studies take a different approach by utilizing gene/protein sequence data obtained from genomic sequencing, with more recent approaches employing machine learning and deep learning to predict similar genes that have the same antibiotic resistance phenotype . RE of gTo further reduce the impact of noise, several different subsets of the original full dataset were used to train different models to see if any subset would perform better. This was driven by the assumption that certain examples in the dataset, such as sentences containing multiple gene and antibiotic entities, were more likely to be mislabelled via distant supervision than sentences with a single mention of a gene and an antibiotic entity. Sentences with multiple different antibiotic and gene entities were highly prevalent . The largest dataset used for training, which was the FULL dataset, contained 55 709 instances. In the field of deep learning this is still considered as a small dataset size. In fact, in other BioRE tasks such as protein–protein interactions Hong et al.  obtainedH. pylori for testing the model’s output. All H. pylori genes (including genes from other species that are similar in sequence) that were predicted by the model to be associated with resistance to the antibiotic group nitroimidazole were manually reviewed. This group was chosen because one of its members, metronidazole, is a very important antibiotic for the treatment of H. pylori. Metronidazole resistance can arise from various mechanisms and while various resistance-causing genes have been investigated, certain studies ascertain the possibility of other unknown genes contributing to resistance (To assess the output of the best performing model and its usefulness in uncovering potentially novel genes associated with antibiotic resistance, we choose the bacterium sistance .frxA has the highest number of predicted relations with this antibiotic group and in fact is well known to be associated with metronidazole resistance in the literature (cagA, recA, hefA and vacA all of which have experimental evidence to indicate this (PPI which in most studies refers to ‘proton pump inhibitor’ and PGM which was used as an abbreviation for metronidazole in one study, were incorrectly identified as gene entities.terature . Other wate this . PPI whikatA gene was extracted from a sentence expressing a negation in the relation and was also wrongly predicted to be associated with metronidazole resistance:The def gene was also wrongly predicted to be associated with metronidazole resistance:Similarly, the H. pylori metronidazole-resistance but were not detected in their abstracts (uvrA, tcdA, porA. These three remaining genes were found in sentences expressing an association with metronidazole in studies concerning other bacteria:The rest of the genes all had a single predicted association. Manual reviewing of the literature showed that these genes are mentioned in the main text of publications evaluating bstracts , 40–47, uvrAtcdAPorAH. pylori antibiotic resistance in the literature but are known to participate in resistance in other species, they are potential candidates for further lab-based studies involving H. pylori to verify whether they also cause similar resistance in H. pylori. Associations do not mean casual relationships, especially in cases of single studies, but they are drivers of further investigations. Additional predicted relations can be viewed in NA relations correctly, which is still a significant improvement over the alternative of using a simple co-occurrence model or manual curation, while also maintaining a relatively high recall rate.Since these genes have not yet been described to be associated with Future work needs to tackle the shortcomings mentioned in the previous sections, namely the development of novel manually annotated gold standard corpora for validating models and increased dataset sizes used for training. Moreover, there is a need for developing models better suited for this domain rather than simply utilizing models that have shown success in other domains. From the results obtained it appears that in certain cases there was not enough information conveyed in the sentences to differentiate between true and false relations of this type. Since it appears that from the sources used in this project, the number of training examples is limited to less than 60 K, additional information outside the text at the sentence level is necessary to further improve models’ performance. One such solution would be to include additional information in the form of KB embeddings of the gene and antibiotic entities. KB embeddings have recently been studied and used within RE frameworks . The Genet al. (Since the datasets obtained were of relatively small size, using just English biomedical abstracts as a source, the next step would be to also utilize full publications from the Medline PMC repository which should significantly increase the size of the datasets obtained through distant supervision. Moreover, a larger manually annotated dataset would also help in developing better-performing models. Studies have shown that training a model on a combined distantly annotated and manually annotated dataset can increase performance . These let al.  that wouH. pylori which were not previously present in the KBs, were true or false relations. Using the nitroimidazole antibiotic group as a case study, the predicted genes related to this antibiotic group were manually reviewed. Out of a total of 28 unique genes, 2 were NER errors, 23 were found in studies concerning H. pylori that should be included in KBs and 3 genes were found to be studied for metronidazole resistance in other organisms only, making them good candidates for further lab-based experimental studies. From this case study, the pipeline showed great potential for aiding in the curation process for KBs/databases such as CARD. Further studies in this direction are perceived to have the potential to improve upon the results of this paper.To the best of our knowledge, this paper presented the first attempt of applying BioRE for genes that are associated with antibiotic resistance using biomedical abstracts. We developed a new NLP pipeline for biomedical RE of gene-antibiotic resistance relations, that included data acquisition via PubMed and PubTator, NER using PubTator complimented with custom dictionaries and RE through distant supervision using current SOTA models. Since no pre-annotated corpora of gene-antibiotic relations were available, a silver standard corpus was developed by using the facts present in the CARD and UniProt KBs. Multiple models were then trained using different subsets of this dataset. Multi-instance learning models that are known to perform well in other domains when using distant supervision were shown to perform underwhelmingly for the task of gene-antibiotic resistance RE. Shortcomings and future improvements to model performance were discussed. Nevertheless, the BioBERT model, trained on the MULTI dataset subset of the silver standard corpus, was found to perform well having an F1-score of 0.74, being 0.09 points higher than the baseline co-occurrence model. To further test the generalisability of this pipeline and the model’s output, the best performing model was used to predict whether candidate gene-antibiotic resistance relations of baab077_SuppClick here for additional data file.


Studies have shown reduced rates of recurrence of periprosthetic joint infection (PJI) with the use of oral antibiotics after stage-two revision. We examined the effects of these antibiotics on the antibiotic susceptibility patterns of subsequent PJI.We conducted a retrospective cohort study of patients who underwent two-stage exchange for PJI in the Veterans Affairs system from 1/1/2015 – 6/1/2020. We compared patients who were prescribed oral antibiotic prophylaxis for ³14 days following stage-two revision arthroplasty with those who received < 14 days of antibiotics. The primary outcome was the presence of antibiotic-resistant organisms isolated in cultures from subsequent infections of the same joint. Secondary outcomes included comparisons of rates of recurrent PJI and time-to-subsequent PJI between each group. We used Chi square and Fisher exact tests to compare the two groups.605 patients met inclusion criteria. Of these, 154 received ³14 days of oral antibiotics following stage 2 surgery. Tetracyclines (48.1%), beta-lactams (27.3%) and trimethoprim-sulfamethoxazole, TMP-SMX (18.8%) were the most common antibiotics used. There was decreased susceptibility to tetracyclines , TMP-SMX , and clindamycin  in organisms isolated from subsequent PJI in the antibiotic prophylaxis group compared to the control group. Subsequent PJI was diagnosed in 29 out of 154 (18.8%) in those who received antibiotic prophylaxis, compared with 80 of 451 (17.7%) who did not. Days to subsequent infection was higher for those who received antibiotics compared to those who did not .Prophylactic antibiotics following stage 2 revision for PJI may increase the risk for drug-resistant organisms in subsequent index joint infections, most notably against tetracyclines and TMP-SMX. Based on our data, antibiotics given after stage 2 revision postponed, rather than prevented, subsequent infection.All Authors: No reported disclosures.


Sirolimus (SRL) is widely used as an immunosuppressant to prevent graft rejection, despite the risk of impairing glucose metabolism. Metformin (MET) can reduce the detrimental effects of SRL in many patients, including diabetes and renal transplant recipients. Limited in vivo studies have reported on SRL and MET therapy, particularly in relation to cellular bioenergetics, glucose metabolism, and insulin resistance. Herein, we investigated the efficacy of SRL and MET co-treatment in BALB/c mice over 4 weeks. Balb/c mice (4–6 weeks old) were divided into four groups and injected intraperitoneally (i.p.) with water , MET (200 µg/g), SRL (5 µg/g), or MET (200 µg/g) +SRL (5 µg/g) over a period of one month. We evaluated the body weight, food consumption rate, random blood glucose (BG), insulin levels, serum biochemistry parameters , and histomorphology in all groups using standardized techniques and assays. All drug-treated groups showed a statistically significant decrease in weight gain compared to the CTRL group, despite normal food intake. Treatment with SRL caused elevated BG and insulin levels, which were restored with SRL + MET combination. Serum biochemical parameters were within the normal range in all the studied groups. SRL+ MET co-treatment decreased liver cellular respiration and increased cellular ATP levels in the liver. In the pancreas, co-treatment resulted in increased cellular respiration and decreased cellular ATP levels. Liver and pancreatic histology were unchanged in all groups. This study showed that co-treatment of SRL with MET alleviates hyperglycemia induced by SRL without any deleterious effects. These results provide initial insights into the potential use of SRL + MET therapy in various settings. Sirolimus (SRL) is an FDA-approved mammalian target of rapamycin (mTOR) inhibitor and immunosuppressant that is extensively used in transplant and oncology clinical settings ,2. SRL mMetformin  is one of the most effective hypoglycemic agents against type 2 diabetes (T2D) . MET is Inhibition of mTOR is a promising strategy for preventing rejection after transplantation and autoimmune diseases. However, few studies have addressed the possibility of co-treatment with MET to reduce the deleterious effects of SRL in the treatment of diabetes and renal transplant recipients ,16. HoweHowever, limited in vivo studies are available regarding co-treatment with SRL and MET therapy ,17. Furtn = 6) of CTRL, SRL, MET, and SRL + MET groups were 23.2 ± 3.9 g, 24.6 ±1.8 g, 24.45 ± 2.5 g and 23.7 ± 2.4 g respectively. Compared to the CTRL group, all three treated groups showed a significant reduction in percentage weight gain (*** p < 0.001). There was no significant difference in the percentage of weight gain among the three treated groups.The effect of CTRL, SRL, MET, and SRL+ MET administration on the body weight of mice is shown in To determine whether the diminished weight gain in the treated groups was due to reduced appetite, food consumption was determined . No signp < 0.05). Although the difference in BG levels was insignificant (p = 0.212) between SRL alone and SRL+MET group, the levels were in the pre-diabetic range (168.7 ± 44.0 mg/dL) in the SRL+MET group . The SRL group of mice produced lower levels of insulin than the CTRL group, but the difference was not statistically significant. The insulin concentration was 0.62 ± 0.22 ng/mL in the CTRL group, which was reduced to 0.53 ng/mL ± 0.17 in the SRL-treated group. Co-treatment with MET improved insulin concentration in the SRL+MET group of mice (p < 0.05). The decrease in insulin concentration in the SRL alone group was rescued in SRL, MET co-treatment group .We also measured the differences in insulin secretion, and it was noted that MET treatment caused an increase in the secretion of insulin B. Mice tThe percentage and distribution pattern of insulin-producing β cells and glucagon-producing α cells in the pancreatic tissue was studied using the immunofluorescence (IF) technique . We did p = 0.180, p = 0.045, p = 0.016, Cellular respiration rate and ATP content were measured in the liver and pancreatic tissues to study any differences in glucose metabolism. Graphical representations of cellular respiration in different organs are shown in our previous publications . In the p > 0.05, To assess the potential toxicity/complications associated with SRL + MET co-treatment, we sacrificed mice at the end of 4 weeks of treatment, and their blood was collected for biochemical analysis. Serum creatinine, BUN, ALT, and albumin levels were measured. We did not observe any significant differences in the levels of creatinine, BUN, ALT, or albumin in all treatment groups as compared to control  was procured from MedChem Express . For preparation, SRL was dissolved in dimethyl sulfoxide (DMSO) to a stock concentration of 50 µg/µL (55 mM) and kept at −20 °C in small aliquots. Immediately before use, aliquots were diluted to 0.5 µg/µL in dH2O. The Pd (II) complex (meso-tetra-(4-sulfonatophenyl)-tetrabenzoporphyrin (Pd phosphor) was purchased from Porphyrin Products , and a stock solution (2.5 mg/mL = 2 mM) was prepared in distilled water and frozen at −20 °C until use. A complete protease inhibitor cocktail was purchased from Roche ; one tablet was dissolved in 1.0 mL H2O and stored at −20 °C. RPMI 1640 medium and other reagents were purchased from Sigma-Aldrich . The cellular respiration reaction mixture contained 3 reagents-1.0 mL of RPMI medium, 3 µM Pd phosphor, and 0.5% fat-free albumin.MET (molecular weight: 129.164 g/mol) was obtained from Toronto Research Chemicals ; a 100 mM solution was prepared in H2O. Percent weight changes (mean ± SD) were defined as the daily weight divided by the starting weight and used as a surrogate marker for drug activity. Fragments of the liver and pancreas were collected at the end of in vivo treatment and processed to determine cellular respiration, cellular ATP, and histology.Adult BALB/c mice, 6–8 weeks old, were housed at 22 °C, 60% humidity, and 12-h light-dark cycles. Mice were provided filtered water and rodent chow ad libitum. Mice food consumption was determined by subtracting leftover weights from initial known weights. This study was approved by the Animal Ethics Committee of the College of Medicine and Health Sciences, UAE University (#A29-13). Mice received i. p. injections of distilled water , MET alone 200 µg/g), SRL (5 µg/g), or co-treatment (MET 200 µg/g +SRL 5 µg/g) for five uninterrupted days every week for four weeks. SRL and MET doses were selected based on previous mouse studies and correspond to the mouse equivalent of the maximum tolerated dose (MTD) 0 µg/g, S. The METAnesthesia was induced with 10 µL/g urethane (25% w/v) administered intraperitoneally for anesthesia. Fragments of the liver and pancreas were then quickly excised with a sterile scalpel and immersed in 10 mL ice-cold RPMI medium supplemented with 10 µL of complete protease inhibitor cocktail solution and saturated with 95% O2 and 5% CO2. One tissue piece was immediately immersed in ice-cold 2% trichloroacetic acid and processed for ATP determination. Another piece of tissue was immediately placed in an oxygen-measuring vial to determine the rate of cellular respiration at 37 °C.For histological analysis, tissue fragments were fixed in 10% formalin and embedded in paraffin. ®  and observed using a Nikon Eclipse Ni fluorescent microscope . The images were analyzed using ImageJ software.For insulin glucagon co-staining using the Immunofluorescence technique, primary antibodies against insulin  and glucagon  were applied for incubation overnight at 4 °C. Alexa fluor-conjugated secondary antibodies were applied for 1 h at room temperature . Nuclei were stained with DAPI, and sections were covered using ImmunomountImmunohistochemistry staining was performed for Ki-67 , Caspase-3 , and Cytochrome c . The rabbit- and mouse-specific secondary antibodies  followed by horseradish peroxidase/3,3′-diaminobenzidine detection immune-histochemistry kit .Biochemical analysis of the blood, including glucose, creatinine, BUN, ALT, and albumin levels, was performed using standard laboratory methods. A commercially available kit was purchased from Roche  using a blood chemistry analyzer .Serum insulin levels were determined using an ultrasensitive rat insulin ELISA kit , according to the manufacturer’s instructions. A standard curve was constructed using standards of known concentrations provided with the kit. The insulin concentration in each sample was then interpolated from the standard curve. Insulin concentration was measured at a wavelength of 450 nm using an EMax Plus microplate reader .2) analyzer was used to determine the rate of cellular mitochondrial O2 consumption [2, and kq is the second-order oxygen quenching rate constant in s-1 • τ M-1).A phosphorescence oxygen , and the supernatant was stored for later use at −20 °C. Before ATP determination, the supernatant was neutralized with tris-acetate (100 mM) and 2 mM ethylenediaminetetraacetic acid (pH 7.75). The results are expressed as μmol ATP per mg dry pellet weight. Measurements were performed using the Enliten ATP Assay System , as previously described .p < 0.05, ** p < 0.01, *** p < 0.001, or **** p < 0.0001. Cellular bioenergetics data were analyzed using SPSS statistical package (version 29).The results are expressed as either the mean ± SD or mean ± SE, as indicated. Statistical analysis was performed using one-way ANOVA or unpaired t-test. GraphPad Prism version 9 software  was used for the statistical analysis. Differences were considered significant at * In this study, we determine the effect of MET co-treatment in alleviating the SRL-induced side effects for a duration of four weeks in Balb/C mice.It is well known that SRL affects animal weight, and some studies have also reported the underlying mechanisms ,26,27. OSRL-induced hyperglycemia was evident in the SRL alone group compared to CTRL. The mice showed significantly increased BG levels in comparison with the CTRL group, which may be due to the disruption of glucose homeostasis by SRL therapy. SRL+MET co-treatment significantly lowers BG levels in mice after 4 weeks suggesting MET can counteract the adverse effects of SRL. It has been well established clinically that MET, unlike SRL, lowers gluconeogenesis ,29. The Serum insulin levels were examined in all treatment groups as it plays a major role in maintaining glucose homeostasis . Reduced2 to the mitochondria, breaking down reduced metabolic fuels, and passing electrons to O2 to form H2O (oxidation) [As mTOR influences the flux of nutrients into mitochondria, we also studied the effect of SRL+ MET co-treatment on cellular bioenergetics, including cellular respiration and quantification of ATP levels, in the liver and pancreas. Cellular bioenergetics encompasses biochemical processes involved in energy conversion. More specifically, cellular respiration involves the delivery of Oidation) . The effidation) ,42. In tidation) . AlsoMoridation) .To study the safety of SRL and MET alone and co-treatment, we also studied the biochemical and morphological changes within the groups. We did not observe any significant changes in the levels of BUN, ALT, and albumin in any of the treatment groups, and all the parameters were within the normal range, suggesting the safety of this co-treatment.Histological analysis revealed no deleterious morphological effects on both liver and pancreas tissues after 4 weeks of treatment in any of the studied groups. Both proliferative and apoptotic markers showed minimal positivity in all the treated and CTRL groups. This may suggest that all the metabolic changes were happening at the molecular level.This study was conducted over a period of 4 weeks, and no structural or morphological changes were observed among the studied groups. Further studies are planned to examine the structural and ultrastructural changes induced by chronic treatment to better understand the mechanisms. Advanced research is needed to determine whether the mitochondrial ultrastructure is affected by any of these drugs.This study evaluates the potency, effectiveness, and safety of MET co-treatment in alleviating SRL-induced side effects. SRL-induced hyperglycemia is improved by the addition of MET to the treatment regimen. The declined insulin secretion caused by the SRL is also improved by the introduction of MET therapy. Overall, the results of our study demonstrate that MET is certainly beneficial when used in combination with SRL. It contributes to the growing evidence suggesting alternative treatment regimens with SRL may be useful for maximizing its effects with minimal side effects.


Acquired immunodeficiency syndrome (AIDS) is an acquired defect of the cellular immunity associated with the infection by the human immunodeficiency virus (HIV). The disease has reached pandemic proportion and has been considered a public health concern. This study is aimed at analyzing the trend of HIV/AIDS research in Nigeria.We used the PUBMED database to a conduct bibliometric analysis of HIV/AIDS-related research in Nigeria from 1986 to 2021 employing “HIV”, “AIDS”, “acquired immunodeficiency syndrome”, “Human immunodeficiency virus”, and “Nigeria” as search description. The most common bibliometric indicators were applied for the selected publications.The number of scientific research articles retrieved for HIV/AIDS-related research in Nigeria was 2796. Original research was the predominant article type. Articles authored by 4 authors consisted majority of the papers. The University of Ibadan was found to be the most productive institution. Institutions in the United States dominated external production with the University of Maryland at the top. The most utilized journal was PLoS ONE. While Iliyasu Z. was the most productive principal author, Crowel TA. was the overall most productive author with the highest collaborative strength. The keyword analysis using overlay visualization showed a gradual shift from disease characteristics to diagnosis, treatment and prevention. Trend in HIV/AIDS research in Nigeria is increasing yet evolving. Four articles were retracted while two had an expression of concern.The growth of scientific literature in HIV/AIDS-related research in Nigeria was found to be high and increasing. However, the hotspot analysis still shows more unexplored grey areas in future.The online version contains supplementary material available at 10.1186/s12981-022-00489-6. Acquired Immunodeficiency Syndrome (AIDS) is an acquired defect of the cellular immunity associated with infection by the human immunodeficiency virus (HIV), a CD4 positive lymphocyte count of less than 200 cells/micrometer and increased susceptibility to opportunistic infection .The first cases of AIDS were reported in May 1981 in the United States of America by Dr. Michael Gottlieb of the Medical School of Los Angeles, United States, and was followed by an official report by the Centre for Disease Control (CDC) on June 5, 1981. The first victims were five homosexual men who were suffering from unusual pneumonia called Pneumocystis Carinii pneumonia and Kaposi’s sarcoma. The causative organisms were first isolated and named Human T-Lymphotropic Virus type III (HTLV-III) in the US and Lymphadenopathy Associated Virus (LAV) in France –4. SpeciOn the African Continent, HIV/AIDS was first reported in Uganda, East Africa in 1982 .The first case of HIV and AIDS in Nigeria was identified in 1985 and reported at an international conference in 1986. The first two cases as reported by the Federal Ministry of Health were; a sexually active 13 year-old girl and a female commercial sex worker from a neighboring West African country , 4.2  OR “AIDS” [Title/Abstract] OR “Acquired Immunodeficiency Syndrome” [Title/Abstract] OR “Human Immunodeficiency Virus” [Title/Abstract] AND “Nigeria” [Title/Abstract]. We retrieved all data under the above predefined search query without restriction on article type. The retrieved data were used to compute bibliometric indicators. Since PUBMED does not store citation records, we retrieved the citation information about authors and articles via Google scholar. We also re-searched PUBMED using the above search descriptors in addition to “Retraction” and Expression of concern”. We also searched the Retraction database setting the location to Nigeria. Extra detail on search query is presented in the Additional file Only articles with focus on HIV/AIDS in Nigeria were included. Articles that were not focused on HIV/AIDS but mentioned same on passing were excluded as well as those not in Nigeria. There was no restriction on the type of article. Duplicate articles were also removed. Two review groups among the authors independently performed the article selection. Differences in opinion were settled via consensus of both grouping. The full detail of exclusion diagram is presented in the Additional file We used the VOSviewer  version 1.6.18 to map HIV/AIDS terms and collaboration in the retrieved data from PUBMED.The impact factor (IF) is utilized as a measure of the journal’s influence and was originally developed by the Institute for Science Information  as a bibliometric indicator. It is updated annually in the Journal Citation Report (JCR) of Clarivate Analytics and the value is often a marker of prestige. We used JCR data of 2021.WE evaluated the overall 1986–2021 scientific publication in the discipline of HIV/AIDS in Nigeria. It is the number of documents on the topic in question (in this case HIV/AIDS in Nigeria) by an author/institution with respect to the total publications in that domain.WE used keyword analysis to ratify the trend of discussion and research in view of the disease characteristics, pathology and treatment.CO-authorship refers to the interaction of authors contributing to the particular field of study. The co-authorship of papers between authors shows collaboration , 27. TheBibliometric mapping was divided into two parts: co-authorship mapping and co-occurrence mapping. Co-authorship refers to the interactions of authors in institutions contributing to the field of study, while co-occurrence refers to relationship among keywords.The following keys of interpretation are utilized in the visualization of co-authorship network analysis: The size of the nodes or bubbles (circles) within the network corresponds to the frequency or number of documents from an author or institution. Secondly, the lines or arcs between nodes correlate/reflect the existence and intensity of the co-authorship link. Finally, the last legend is the color of the node: VOSviewer clustering algorithm assigns the colors to the nodes based on the estimation of a measure of similarity between them. Consequently, it is safe to conclude that nodes of same color are related. Also, the shorter the distance between two (2) nodes, the closer the relationship between them .We retrieved 2838 publications and only included 2796 publications after removing 9 duplicate publications and 33 publications that were either not related to Nigeria  or not related to HIV/AIDS (Only mentioned in abstract background) . Of these, 92.13% (n = 2576) were original articles, 2.79% (n = 78) were narrative reviews, while 1.14% (n = 32) were systematic reviews. Other forms of publications recorded were Case reports/Case series (0.96%), Perspectives (0.86%), Correspondence/Letters to Editor/Comments on articles (0.71%), Gazettes/Law reviews and other official publications (0.39%), Commentary (0.29%), Erratum/Corrections (0.25%), Conference /Workshop papers (0.18%), Editorials (0.14%), Books/Book chapters (0.11%) and Expressions of concern (0.03%) (Table The first publications (2 in number) were published in 1986. There was a slow pace of publication of HIV/AIDS related literature from then till the year 2004 when publications shot up more than 20-fold. The tempo of research since then has been sustained and has remained ≥ 150 publications per year after 2011 Fig. .Fig. 3TrOur result showed a large span of number of authors per document ranging from single author documents to > 10 authors per document. Furthermore, the result showed that more than half  of the published articles were by collaboration of < 6 authors Table . The docThe top most productive institutions in HIV/AIDS research in Nigeria were represented in Table On account of external participating countries, institutions in the USA produced 12.84% n = 359) of the total published literature. This was followed by South Africa, United Kingdom, Canada and Netherlands  was found between the US Military HIV Research Program and Institute of Human Virology University of Maryland.Table . in PLOS Medicine and Swartz et al. in Lancet HIV had the highest number of citation per year; 152 citations per year and 26.5 citations per year, respectively. Next were the 2nd and 1st most cited publications in PLoS ONE and PLoS Medicine with 24 citations per year and 22 citations per year, respectively.Table Table Figure The node symbol represents an author while the node size represents activity/publications of the author, while links between the authors represent relationship between them. Exactly 78 (19.80%) of the 394 authors who met the minimum selection criteria (at least 5 publications) had no connection (collaboration).Based on total link strength, Crowel TA , Okonkwo P , Ndembi N , Nowak R , Baral SD , Dakum P , Kanki P , Charurat MP , Aliyu MH , Adebajo S  and Ezeanolue E  were the most influential authors in HIV/AIDS research in Nigeria network. Considering the total number of co-authored articles , Crowell TA (n = 45), Okonkwo P (n = 43), Aliyu MH (n = 40), Ndembi N (n = 38), Dakum P (n = 37), Kanki PJ (n = 34), Ezeanolue E (n = 32), Nowak R (n = 31), Baral SD (n = 30) Adebajo S (n = 29) and Ake JA (n = 24) are in this order the most productive authors. Crowell TA, Okonkwo P and Ndembi N retained the position of the most co-authorship as well as the top total link strength. The three are affiliated to Uniformed Service University USA, Bingham University Nigeria and Africa CDC, respectively  retained the 6th most productive author position by principal author analysis (n = 19) as well as the 3rd most co-authored author (n = 40) while having the 10th highest total link strength. Similarly, Ezeanolue E made it on both list as the 12th most published principal author as well as the 7th most co-authored author and the 12th highest total link strength Tables .Figure On the ground of different average appearing year of keywords, VOSviewer under overlay visualization marked keywords included in the map with different colors Fig. b. KeyworKeywords such as antiretroviral therapy and PMTCT showed no links are therefore research areas still open for new researches.Overall, our analysis found 4 retracted articles and 2 articles with expression of concern in HIV/AIDS related publications in Nigeria. Two of the retracted articles were systematic reviews published in Cochrane Database of Systematic Reviews published by Wiley Publishing Company. The other 2 were a conference paper published in Sexually Transmitted Infections (published by BMJ Publishing) and an original article published in African Journal of AIDS Research (published by Taylor & Francis). The 2 articles with expressions of concern were published in Kidney International (published by Elsevier). Most of the reasons for retractions/expressions of concerns were raised by the authors Table .This study provides a quantitative description of HIV/AIDS related research in Nigeria from 1986 to 2021 in PUBMED. The most utilized document type by the authors was original article implying that the subject matter was mostly experimental or clinical.The trend of research output on HIV/AIDS in Nigeria showed a progressive increase and reassuring trend. However, we found that there was a sluggish growth of HIV/AIDS related literature in Nigeria until 2004 when dramatic growth was observed with an inflection point at about 2008. The earlier lag in scientific productivity could be related to the initial response to the epidemic. Balogun and colleagues  reportedThe core journals that served as sources for HIV/AIDS related publication in Nigeria were PLoS ONE, Pan African Medical Journal, African Journal of Reproductive Health, AIDS Care, Journal of Acquired Immune Deficiency Syndrome, African Journal of Medicine and Medical Science. These journals could possibly be avenues for future breakthroughs in HIV/AIDS research in Nigeria. More so, the patronage of PLoS ONE with a high impact factor may not be unconnected to the editorial policy of the journal. PLoS ONE emphasizes scientific rigor of a research work over novelty unlike other journals within that category .The article “Discriminating attitude and practice by health workers towards patients with HIV/AIDS in Nigeria” published in PLoS Medicine was the most cited article. The article was dedicated to assessing the attitude of health care workers toward HIV infected persons in Nigeria; refusal to attend to HIV/AIDS patients, suitability to attend to HIV/AIDS patients in general ward and the need to disclose HIV status to all health workers. The second most cited article was on phases 3 double-blind randomized clinical trial of a vaginal gel intended for prevention of HIV infection. The article with the most citations per year was an article published in Lancet HIV that dwelt on effect of same sex marriage. All the top 10 most cited articles were published in journals with impact factor > 3. The feat of the article published in Lancet is not surprising considering the high impact factor (16.070) and wider coverage of the journal. However, there have been counter argument on the translation of journal impact factor to individual article citation .University of Ibadan, University of Lagos and University of Nigeria, Enugu and Obafemi Awolowo University were the most outstanding in terms of productivity in HIV/AIDS related research in Nigeria. The above institutions have been consistently documented to occupy the top five (5) positions in researches in biotechnology research , Lassa fInstitutions in the United States dominated external publications in HIV/AIDS research in Nigeria and accounted for 12.84% of all publications. Prominent among these institutions were University of Maryland USA and Centre for Disease Control. The United States has been in the forefront of HIV/AIDS research/treatment and funding in Nigeria. This has been via national and corporate funding. For instance, the US President’s Emergency Plan for AIDS Relief (PEPFAR) has shown the highest commitment in HIV/AIDS research, diagnosis and antiretroviral therapies , 39. TheCrowel TA, Okonkwo P, Aliyu MH, Ndembi N, DakumP,Kanki P, Ezeanolue E, Nowak RG, Baral SD, Adebajo S, Charurat ME and Ake JA were the all-round most productive authors in HIV/AIDS related research in Nigeria. Collaborative link analysis presented Crowel TA, Okonkwo P, Ndenbi N, Nowak RG, Baral BD, Ake JA, Dakum P, Kanki PJ, and others as the most influential in terms of diversity of links. Prominent to note is Crowel TA who is the most productive author as well as the one with the highest collaborative strength. On the other hand, analysis of authors’ contribution based on principal author (first author) analysis showed Iliyasu Z, Folayan MO, Ogoina D, Uneke CJ, Olowookere SA, Aliyu MH, Ogunbayo A, Olakunde BO, Olley BO, Sam-Agudu MA, Lawson L, Ezeanolue EE, Daniel OJ, Aliyu G and Agaba PA to be the most productive authors. The above authors in the two categories are core to HIV research in Nigeria and are likely to have tremendous impact in HIV/AIDS research in future.Analysis of the co-authorship collaboration network showed that Aliyu MH and Ezeanolue were the only authors in the top list of principal authors who had high link strength of collaboration. Also, most of the top authors with high collaborative strength were affiliated to institutions in the United States and some Nigerian government agencies with external funding. Only Okonkwo P of Bingham University (Private University) and Ezeanolue E (University of Nigeria) were the only top list authors from Universities in Nigeria in terms of collaboration. This observation is further corroborated by the institutional collaboration network analysis. The major collaborating institutions were USA-based institutions and externally funded federal agencies. Most of the federal universities only had inter-university collaboration and were in periphery of the network, hence, their exclusion in the network link map. There is poor funding of research in Nigeria, especially with regards to Nigerian Universities. Nigeria spends only 0.13% of her GDP on research and development (R&D) . This isThe keyword analysis using overlay visualization showed a gradual shift from disease characteristics to diagnosis, treatment and prevention. The current discussions are on mapping current epidemiology, administration of antiretroviral therapy and the prevention of mother-to-child-transmission of HIV. For instance, there have been varying current discussions on trends, predictors, spatial patterns, knowledge and the reduction of mother-to-child transmission of HIV in Nigeria –50. OfteThe analysis of articles that had post-publication remarks showed 4 articles withdrawn (retracted) and 2 with an expression of concern. We observed that some of the articles continued to accumulate citations even after they were retracted. For example, the article “Higher risk sexual behavior among HIV patients receiving antiretroviral treatment in Ibadan Nigeria” had 18 citations in total, 7 of which occurred after retraction on May 16, 2014. This observation supports the argument and submission of some researchers  that mosThe present study may contain some limitations which are inherent in bibliometric studies. First, the criteria mapped out by the PUBMED database themselves determine the subsequent product of the studied materials. Secondly, local journals that were not indexed in PUBMED within the study period would have been missed. We might have excluded HIV/AIDS research articles in Nigeria if the authors did not include our specific search descriptors. Lastly, we were limited to use PUBMED a free to use database, we may have missed some articles indexed only elsewhere. However, we believe the output is a true representation of research trend in the study domain.Irrespective of the inherent limitations, we believe that this study has made available a significant representation of the trends in HIV/AIDS research in Nigeria. We have shown that research on HIV/AIDS in Nigeria had a slow start, possibly due to delay in accepting the reality of the disease, but has grown significantly over time. As current treatment approaches are yet to be curative, it highlights the fact that there remains enormous research potential for the future. The major collaborations were found to be from oversea institutions majorly the United States of America.Additional file 1: Table S1. Search Strategy For The Study In Pubmed.Additional file 2: Fig. S2.. Screening protocol of retrieved dataAdditional file 3:Table S3. Countries with the most published articles.


Background: The COVID-19 pandemic heavily affected healthcare delivery systems in the United States. However, little is known about its impact on overall antimicrobial consumption, especially in outpatient settings. We assessed the impact of the COVID-19 pandemic on antimicrobial consumption in both outpatient and inpatient  settings in the Veterans’ Health Administration (VHA) during the 2 years before and after the start of the pandemic. Methods: We conducted a retrospective study for all patients who received care within the VHA from January 2018 to December 2021. We used antibiotic days as the primary outcome measure (days of therapy for inpatient settings and dispensed days supply for outpatient settings), and we obtained data for antimicrobial consumption from the VHA Corporate Data Warehouse. Antibiotics were categorized into classes by the NHSN protocol and included only systemic agents . We defined 2018–2019 as the prepandemic period and 2020–2021 as the pandemic period. We compared the relative and absolute difference in antibiotic consumption between the 2 periods. Results: Across all periods, 8.3 million patients received care in the VHA, and an average of 28,709,680 antibiotic days were prescribed per year. Overall, 92.9% of all antibiotic days were outpatient and 7.1% were inpatient. Total antibiotic days during the pandemic period decreased by 12.4% compared to the prepandemic period . This reduction was primarily driven by reductions in outpatient settings , but antibiotic days in inpatient settings decreased more modestly  (Fig. Conclusions: Compared to the prepandemic period, the pandemic was associated with a substantial reduction in overall antibiotic consumption, especially in outpatient settings, which accounted for 95% of the overall reduction despite being outside the domain of most traditional antibiotic stewardship programs. The impact of the pandemic was most modest in the use of tetracyclines and trimethoprim–sulfamethoxazole and was most prominent in the use of fluoroquinolones and lincosamides. Further studies are required to improve the causal inference between the COVID-19 pandemic and this reduction in antibiotic consumption, as well as its impact on patient outcomes.Funding: NoneDisclosures: None