Lythrum salicaria. Taguchi design was used to optimize the synthesis method, taking into account various working conditions. The optimum parameters were established using a 3 mM AgNO3 concentration, a 1:9 extract:AgNO3 volume ratio, a pH value of 8, 60 ℃ temperature, and 180 min reaction time. The synthesized AgNPs were characterized using UV-Vis and FTIR spectroscopy, and TEM and EDX analysis. The SPR band at 410 nm, as well as the functional groups of biomolecules identified by FTIR and the EDX signals at ~3 keV, confirmed the synthesis of spherical AgNPs. The average AgNPs size was determined to be 40 nm, through TEM, and the zeta potential was −19.62 mV. The antimicrobial assay showed inhibition against S. aureus and C. albicans. Moreover, the results regarding the inhibition of lipoxygenase and of peroxyl radical-mediated hemolysis assays were promising and justify further antioxidant studies.This research describes an eco-friendly green route for the synthesis of AgNPs using an aqueous extract of  Noble metal  nanoparticles have gained researchers’ attention due to their multiple benefits in various fields, such as medicine, the food industry, material science, physics, and chemistry. In the biomedical field, noble metal nanoparticles are versatile agents used in drug delivery, diagnosis, radiotherapy enhancement, photo-ablation procedures, and hyperthermia studies ,2. The pSeveral methods can be applied for AgNPs synthesis, each presenting advantages and disadvantages. A general classification divides them into bottom-up and top-down techniques. In the top-down category, the principle relies upon reducing the size of bulk material by mechanical milling, laser ablation or sputtering. Although the final product presents uniform physico-chemical properties, these methods also involve high energy consumption. The bottom-up techniques use molecules or atoms to prepare nanoparticles through various procedures that can be either physical and chemical  or biological . Nowadays, biological methods are of high interest as they allow the overcoming of several drawbacks, such as using unsafe organic solvents that may be dangerous to human life and the environment, complicated synthesis procedures with many intermediate steps, expensive equipment or reagents, and high energy consumption. Thus, synthesis using plant material presents the advantages of lack of pathogenicity and production of homogenous nanoparticles. Secondary metabolites in plant extracts, such as polyphenols, flavonoids, terpenoids and alkaloids, reduce the metallic precursor and stabilize the surface. The reaction between the plant extract and the silver salt proceeds under the influence of reaction conditions, such as silver ions concentration, temperature, pH and period of time for magnetic stirring . ThroughLythrum salicaria L. (purple loosestrife) is a native Eurasian flowering plant that is nowadays naturalized in most temperate areas of the world, being a member of the Lythraceae family [L. salicaria includes polyphenols, along with nonpolar constituents, such as steroids , triterpenes , phthalates , coumarins  and alkaloids . Polar phytochemicals in L. salicaria belong to the class of ellagitannins , flavonoids , anthocyanins , and phenolic acids . The rich composition in biologically active principles justifies the several promising activities shown in in vitro and in vivo studies. Oral administration of extracts from the aerial part/flowering top of L. salicaria, obtained using various solvents  tested on animal models, proved to have antidiarrheal and anti-inflammatory activities, along with a hypoglycemic effect [L. salicaria extracts showed remarkable antioxidant, antimicrobial and antitumoral activities [e family . This spe family . The chec effect ,12. Moretivities ,14,15.L. salicaria extract has recently been reported in the literature, although the studies were conducted in order to incorporate the nanoparticles in nanohybrids, with cellulose, chitosan and lignocellulose [L. salicaria aqueous extract, establishing optimal reaction conditions, for the first time, using the Taguchi design. Applying the Taguchi model to optimize AgNPs synthesis is an advantage, since it is a fast and efficient method that provides information on different parameters and levels in the same experiment. Here, we characterized the synthesized AgNPs using physico-chemical attributes and microbiological and antioxidant activities. In order to achieve valuable physico-chemical data, UV-Vis Spectroscopy, Dynamic Light Scattering (DLS), Transmission Electron Microscopy (TEM), Energy Dispersive X-ray analysis (EDX) and Fourier Transform Infrared (FTIR) spectroscopy were used. Moreover, to the best of our knowledge, the present study is the only one that has used, for antioxidant activity testing, the determination of the inhibition of lipoxygenase and of peroxyl radical-mediated hemolysis for AgNPs obtained using L. salicaria aqueous extract.Successful biological AgNPs synthesis using ellulose . Other cellulose . Thus, tL. salicaria extract, 10 g of plant material, as grounded aerial part , were added to 100 mL distilled water, at an adjusted temperature of 40 ℃, while continuously stirring at 500 rpm for 30 min. After the mixture was cooled at room temperature, filtration was carried out using a Whatman filter paper no. 1 and the filtrate was stored at 4 ℃ for further experiments.For the preparation of the 3) solution, in various volume ratios. These mixtures were subjected to magnetic stirring at 500 rpm, at different adjusted pH values, using 1 M HCl and 1 M NaOH, at different temperatures and time intervals. The change in color was monitored and the maximum absorbance was recorded in the 300–600 nm range by UV-Vis spectroscopy. The analysis was performed in triplicate.The Taguchi design was used to study AgNPs synthesis conditions in an experiment that uses minimal resources and, in our case, tested five parameters. AgNPs were synthesized by adding different concentrations of extract to silver nitrate , D = 133.5 × 10−7 cm (average diameter of nanoparticles), M = 107.868 g/mol (atomic mass of silver) and NA = 6.023 × 1023 mol−1 (Avogadro’s number).The theoretical concentration of AgNPs in the colloidal synthesis mixture was calculated using a mathematical method ,19. FirsC) could be calculated only by considering that all silver ions (Ag+) were entirely converted to AgNPs in the biosynthesis process. Equation (2) was applied for the determination of C:TN = total amount of Ag atoms added as AgNO3 (3.0 mM = 0.003 M), N = average number of atoms per nanoparticle, V = reaction volume (0.22 L) and AN = Avogadro’s number [Secondly, the molar concentration of nanoparticles in the resulting colloidal mixture , using a Delsa Nano Submicron Particle Size Analyzer ; TEM (dimensions and morphology), using a Hitachi High-Tech HT 7700 Transmission Electron Microscope , using a Quanta 200 Environmental Scanning Electron Microscope (ESEM) with EDX .Regarding the physico-chemical characterization of AgNPs, the change in mixture color was initially visually monitored and then the UV-Vis spectra were recorded, observing the presence of the peak due to surface plasmon resonance (SPR). The absorbances were recorded with a Jasco V-530 UV-Vis double beam spectrophotometer  in the 300–600 nm range. The functional groups involved in the green synthesis of AgNPs were analyzed by FTIR spectroscopy  in the 4000–310 cmL. salicaria extract (diluted correspondingly) and supernatant (after the first separation of AgNPs) was performed using a previously described UV-Vis spectrophotometric method, with gallic acid as standard [Furthermore, the total phenolic content of the standard . The anaStaphylococcus aureus ATCC 25923, Pseudomonas aeruginosa ATCC 27853) and fungal  pathogens, obtained from the Culture Collection of the Department of Microbiology, “Grigore T. Popa” University of Medicine and Pharmacy, Iasi, Romania. Standard culture mediums, such as Mueller–Hinton agar (Biolab) for fungi and Mueller–Hinton agar (Oxoid) for bacteria, were used. After the samples and positive controls  were applied, the plates were incubated at 35 ℃ for 24 h. All experiments were conducted in triplicate, and, after the inhibition zones were measured (mm), the mean ± standard deviation was calculated. The Minimal Inhibitory Concentration (MIC) and Minimal Bactericidal Concentration (MBC) or Minimal Fungicidal Concentration (MFC), were determined by the broth microdilution method. Subsequent double dilutions of the tested samples in Mueller-Hinton broth were inoculated with the suspension of the microorganism test.The synthetized AgNPs and the corresponding extract were investigated for antimicrobial activity, using disk diffusion methods ,22, agai50 value was also calculated and expressed as µg extract/mL final solution.The antioxidant activities of the samples (AgNPs and extract) were determined using 15-lipoxygenase (LOX) inhibition and peroxyl radical-mediated hemolysis inhibition assays. Regarding the first method, after the mixture of lipoxygenase (in pH 9 borate buffer solution) and samples were left to stand in the dark at room temperature for 10 min, linoleic acid (in pH 9 borate buffer solution) was added, and the absorbances were recorded at 234 nm . SamplesThe optimization of parameters for more efficient AgNPs synthesis was based on an L9 orthogonal array design, a method that combines mathematical and statistical principles in order to obtain a predictive knowledge of a complex process with several variables, but with a reduced number of attempts ,26. ThisThe model was obtained using variables presented in S/N ratio was calculated using Equation (3). The S/N ratio measures the quality characteristic deviating from the desired value, and represents the ratio of the target value  to the standard deviation for the response variable (noise), which can be calculated by selecting the formula corresponding to the quality characteristic “larger is better”.n = number of experiments, yi = response variable for the experiment (absorbance) [In order to process the data, the orbance) ,27.S/N ratio are presented in The obtained results for the S/N ratio calculated for each level, the optimal synthesis conditions were A3B1C3D3E3 , followed by A2B1C2D2E3 (L4), and, therefore, we could say that, in both cases, a volume ratio of 1:9 extract:AgNO3 and 180 min reaction time were optimal. The average S/N ratio for each level is presented in Taking into account the average value of absorbance and the S/N ratio, the optimum conditions for AgNPs synthesis were A2B1C3D3E3, with a 3 mM AgNO3 concentration, 1:9 extract:AgNO3 ratio, a pH value of 8, 60 ℃ temperature and 180 min reaction time.Considering the L. salicaria extract. Moreover, the traditional optimization of synthesis can be found in a single study carried out by Srećković et al., which led to the following conditions: 20 mM AgNO3 concentration, 25 ℃, pH 12, and 30 min reaction time [To the best of our knowledge, the present study is the only one that has used the Taguchi model to establish the reaction conditions for AgNPs synthesized using an ion time . In bothion time .+ and agglomeration of colloidal nanoparticles with oligomeric clusters formation [AgNPs synthesis by means of green methods represents the focus of scientists, given that they imply lower costs and ease in the monitoring and sampling processes. Moreover, plants are easy to grow and safe to handle, and, implicitly, this type of eco-friendly synthesis could replace chemical techniques for obtaining AgNPs . The steormation .The first indicator of AgNPs synthesis is noticed through visual observation, but the formation of nanoparticles must be confirmed by other methods as well. Therefore, we continued monitoring the color change by means of UV-Vis spectroscopy .3 under specific conditions. When analyzing the UV-Vis spectra, no absorption peak was observed in the 300–600 range for either the extract or AgNO3 solution, but a distinct peak at 410 nm was revealed for the obtained colloidal solution. This peak could be due to excitation of SPR [L. salicaria extracts, in which the SPR band was observed at 415 nm [−10 mol/L.As seen in the inset of n of SPR , which cn of SPR . The pren of SPR . The obtt 415 nm  or in tht 415 nm . The calDifferences in the position and appearance of the peak, even for the same plant species, can be explained by different harvesting areas, different conditions for extract preparation and for AgNPs synthesis. Nonetheless, these conditions can also lead to modifications in the shape and size of AgNPs. A wide peak generally indicates larger particles . Moreove+ to Ag0 can take place. This process is generally followed by agglomeration of free silver atoms and, eventually, by the formation of the AgNPs colloidal solution. Such biomolecules also participate in the functionalization and stabilization of AgNPs [+, which is reduced to Ag0. On the other hand, caffeic acid is transformed into a free radical which, in turn, reduces another Ag+ and is converted to ortho-quinone. By the coupling of two free radicals of caffeic acid, an oxidative dimer is formed which releases 4 electrons that participate in the reduction of Ag+, being transformed into quinone. The formed quinones can bind to AgNPs and cause steric hindrance, thus, stabilizing the particles [+ to Ag0 [The mechanism of AgNPs synthesis is explained through biomolecules present in the extract , which are compounds capable of donating electrons, so the reduction process from Agof AgNPs ,35. For of AgNPs  combinedarticles . Flavono+ to Ag0 . Thus, tOcimum sanctum extract. Following the redox reaction, the -OH group of the ursolic acid structure deprotonates and oxidizes with the formation of a radical, promoting the reduction of silver from Ag+ to Ag0. Further agglomeration and formation of oligomeric clusters occurs. During these steps, several species of AgNPs can be formed, given that Ag+ reacts with Ag0, forming Ag2+, which dimerizes to Ag4+2.Other examples of biosubstances involved in AgNPs synthesis are triterpenes. Aazam et al.  proposedIn order to highlight the functional groups and, implicitly, the compounds that participate in AgNPs synthesis, FTIR analysis was used. −1, which was related to the stretching vibration of -OH groups found in alcohols and phenols and to the N-H stretching from amides. The peaks at 2924 cm−1 and 2854 cm−1 corresponded to C-H stretching and bending vibrations of CH3 and CH2  [−1 and 1624 cm−1 were connected to the vibration of C=O from amides and carboxylic groups, and -C=C- aromatic rings, respectively [−1 and 1364 cm−1 could be attributed to stretching vibrations of CO of carboxylic acids or esters, to bending vibration of N-H in amides or to stretching vibrations of N-H in secondary amines, or to the C-N stretch vibration of aromatic amines. Furthermore, the 1184 cm−1 and 1038 cm−1 bands could be attributed to the C-O stretching vibrations of alcohols, esters, ethers and carboxylic acids from terpenoids and flavonoids and to the C-O-C stretching of aromatic ethers and polysaccharides [−1 range corresponded to CH out of plane bending vibrations and the peak at 524 cm−1 could be responsible for C=C torsion and ring torsion of phenyl, or to C-N stretch from secondary amines and amides [The FTIR spectrum of the extract shows a broad absorption peak at 3452 cmalkanes) ,28. The ectively . The bancharides ,40. The d amides . Generald amides . Therefod amides . The firThe morphological analysis of AgNPs was examined by TEM  and the The DLS analysis revealed an average AgNPs hydrodynamic dimension of 133.5 nm b. Other The quantitative elemental structure of AgNPs was investigated by EDX analysis .Data analysis revealed that EDX spectra of AgNPs mainly contained a specific and intense peak at 3 keV for Ag (37.52 wt %), but also C (18.83 wt %), O (24.49 wt %) and small quantities of N, Br, Si, Cl and K. Consequently, the results confirmed the synthesis of AgNPs. The presence of other elements might be related to the breakdown of capping agents from the surface of nanoparticles.Staphylococcus aureus (S. aureus) and Pseudomonas aeruginosa (P. aeruginosa) and a fungal strain, Candida albicans . The results are presented in Firstly, the disk diffusion method was used, which is a routine, simple and low-cost antimicrobial susceptibility test. The antimicrobial activity was assessed using two bacterial strains, The AgNPs presented better activity, compared to the extract against the Gram-positive bacteria and pathogenic yeast. However, no activity was detected for either in the case of the Gram-negative bacteria.S. aureus ATCC 25923 and C. albicans ATCC 90028 were determined and are presented in Further, the broth microdilution method was applied, in order to determine the MIC and MBC values, and since it represents a standardized method, the results could be of clinical relevance . ImpliciS. aureus and 0.62 for C. albicans. In our study, we obtained the same value for S. aureus, but for C. albicans the value was smaller (0.03 mg/mL).MIC was the lowest concentration of the sample at which bacterial growth was completely inhibited after 24 h incubation at 37 °C. In the study carried out by Srećković et al. , the MICL. salicaria has not been reported until now. The highest dilution showing 100 % inhibition was 0.62 mg/mL for S. aureus and 0.31 for C. albicans. For both tested microorganisms, the obtained results for MIC and MBC/MFC for the synthesized AgNPs were better than those obtained for the extract.To the best of our knowledge, the MBC value for AgNPs synthesized from S. aureus, compared to E. coli for AgNPs formed using mango peel [Indeed, most literature studies show better antibacterial activity of AgNPs on Gram-negative bacteria than on Gram-positive bacteria . Howeverngo peel . A similngo peel . An explngo peel . Therefongo peel .Moreover, the antimicrobial activity depends on the size and shape of AgNPs. Nanoparticles of smaller sizes, with a diameter of approximately 1–10 nm, have a higher surface:volume ratio and more efficient antimicrobial activity, interacting preferentially with bacteria . TruncatThe mechanism surrounding the antibacterial activity has not been fully elucidated, but several explanations are possible, taking into account that AgNPs can adhere to, or can pass through, cell walls/membranes of microorganisms, or induce cellular toxicity and ROS generation, or modulate cell signaling.The first proposed mechanism is that, following the electrostatic attraction between AgNPs and the cell membrane, nanoparticles tend to adhere to the membrane, which leads to alteration of the structure and rupture of the cell wall. Moreover, the interaction between AgNPs and sulfur-containing proteins found in the cell wall can lead to a chain reaction, starting with structural modifications, affecting the transport process and increasing permeability, which leads to cell content  leakage and, sometimes, ATP synthesis inhibition.+ ions with nucleic acids, can lead to the destruction of the double helix structure.The second mechanism consists of the penetration of AgNPs inside the cell and nucleus, which can modify cellular functioning by interacting with the cell structure or biomolecules. Therefore, the destabilization and denaturation of proteins containing thiol groups can occur via interaction with silver ions, or AgNPs, and silver ions can interact with disulfide bonds, thus, blocking the active binding site, leading to functional deficiencies in microorganisms. Moreover, AgNPs can interact with DNA, and through the reaction of Ag+ ions produce cellular oxidative stress by generation of radicals and ROS. Free radicals can cause destruction of the mitochondrial membrane and can interact with lipids, enhancing lipid peroxidation. ROS generation can lead to hyperoxidation of lipids, proteins and DNA.For the third mechanism, a high concentration of AgThe last possible mechanism focuses on the modulation of the cellular signal system, which can lead to modifications in bacterial growth, as well as affect the processes at molecular and cellular levels ,53.L. salicaria extract, and of the corresponding AgNPs, by DPPH and ABTS scavenging activity methods, and the results showed for the extract from the aerial parts slightly better activity (86.38 ± 0.13 µg/mL by DPPH method and 65.33 ± 2.08 µg/mL by ABTS test) versus AgNPs (>100 µg/mL by DPPH and 141.66 ± 17.05 µg/mL by ABTS test) [Given that Srećković et al.  determinEA is the difference between the absorbances of the enzyme solution without inhibitor at 90 and 30 s and EIA is the difference between the absorbances of the enzyme-inhibitor solution at 90 and 30 s, respectively.The inhibition of lipoxygenase, which was determined using the modified Malterud method , can be 50 value being also slightly better than that of gallic acid. Their influence on lipoxygenase is most probably achieved through changes in the spatial structure of the enzyme or of its active center [Lipoxygenases  are metalloenzymes that contain ferrous or ferric ions in their catalytic center, depending on the stage of the redox reaction (oxidation or reduction) . Lipoxyge center .SA is the absorbance of the sample and AAAPH is the absorbance of the positive control.Antioxidant compounds can also block the peroxyl radical synthesis induced by AAPH, with consequent protection of the erythrocyte membrane. The reduction in the concentration of peroxyl radicals determines the decrease of the absorbance measured at 540 nm . The eryAAPH is a prooxidant compound that causes the oxidation of hemoglobin to methemoglobin, consequently inducing hemolysis, and possibly affecting the lipophilic structure of the erythrocyte membrane . The syn3 as a precursor and an L. salicaria extract as a reducing and capping agent, as demonstrated by FTIR analysis, which also revealed the functional groups found in the extract that are responsible for the obtaining of AgNPs. Moreover, the synthesis was confirmed through the presence of the SPR band, by both visual observation of color change and UV-Vis spectroscopy. The presence of silver was highlighted by EDX analysis, and the negative zeta potential indicated a stable AgNPs colloidal solution. The formed nanoparticles showed antimicrobial activity against S. aureus and C. albicans. The novelty of the research consisted of, besides establishing the optimal reaction conditions using the Taguchi design, testing the antioxidant activity through inhibition of lipoxygenase and peroxyl radical-mediated hemolysis, which showed promising results for the formed nanoparticles, as well as for MBC testing. Therefore, further studies are justified, with the synthesized AgNPs being potential resources for nanotechnological applications.In the present study, AgNPs were obtained via a simple and eco-friendly method, using a robust design, namely the Taguchi method, in order to identify the optimal synthesis parameters, which was achieved, for the first time, for such nanoparticles. AgNPs were successfully synthesized using AgNO


A proficiency test was performed to verify that the regional veterinary laboratories in Germany can provide reliable foot-and-mouth disease virus (FMDV) diagnostics. Overall, 24 samples were to be analyzed for FMDV-specific nucleic acids by real-time RT-PCR, and 16 samples had to be tested by ELISA for antibodies against non-structural proteins of FMDV. For both methods, a range of dilutions of the original materials  was prepared, and negative samples were included as well. All 23 participating laboratories were able to detect FMDV genome down to a dilution of 1:100,000 of the vaccine preparation. Even at a dilution of 1:1,000,000, FMDV genome was detected by more than half of the participants. With the antibody ELISA, all sera were correctly identified by all participating laboratories. No false-positive results were returned with either method. All participating laboratories were found to be fully proficient in FMDV diagnostics. For the first time in history, 10 years have passed without a single case of foot-and-mouth disease (FMD) in the European Union (EU). However, the disease still circulates in countries close to the EU and in many other places in Africa, the Middle East, and Asia [FMD virus (FMDV) is most likely to be spread by the movement of infected animals , but theIncreasing global trade and travel pose a significant risk of reintroduction of FMDV to the EU and Germany. Effective control can only be achieved by early recognition of the disease ,6,7,8,9.Besides virological detection, the tasks of the state laboratories also include serological tests. These do not play a big role in FMD exclusion testing but will be essential if the FMD-free status of Germany is to be regained after an outbreak. In the case of emergency vaccination not followed by slaughter, serological testing of large cohorts of animals must prove that there is no evidence of infection in the vaccinated population . It is tDuring the production of DIVA-capable FMD vaccines, the virus is replicated in cell culture, chemically inactivated, and the non-structural proteins (NSP) produced by the infected cells are then removed. In theory, the final formulated vaccine only contains viral capsids  and denatured viral RNA but no NSP . VaccinaIn summary, the state laboratories must be able to perform rapid and reliable virological and serological examinations for FMD, in extreme cases also on a very large scale. At regular intervals, the NRL carries out a ring trial for the state laboratories to confirm their diagnostic proficiency. Each of the 23 participating laboratories was provided 24 samples for analysis by RT-qPCR for FMD-specific nucleic acids and 16 samples for detection of antibodies to non-structural proteins of FMDV by ELISA. The samples were prepared and distributed by the NRL, and the results returned by the participating labs were analyzed and compared to assess their diagnostic capability and the performance of the assays. A high level of diagnostic proficiency must be maintained by the state laboratories to reliably detect a reintroduction of FMD to Germany, effectively contain an outbreak, and quickly regain FMD-free status.A total of 23 virology panels consisting of 24 samples and 19 serology panels consisting of 16 samples were prepared. The volume of each sample was 500 µL.t) of 35, the A Argentina vaccine was diluted by 1:10,000 (Ct 28), and A24 Cruzeiro was diluted by 1:1000 (Ct 22). In addition, a tenfold dilution series of an O1 Manisa/O-3039 vaccine was prepared from 1:100 to 1:1,000,000 in fetal bovine serum (FBS). FBS was also used for the negative samples. Multiple replicates were included for all samples of the serotype O dilution series, but the SAT2, A Argentina, and A24 vaccines were represented by only one sample. From the dilution levels 1:100, 1:1000, and 1:10,000 of the O1 Manisa/O-3039 vaccine, three identical aliquots were provided. Of the samples with lower RNA concentrations , a total of four aliquots were provided. Each panel included four aliquots of FMDV-free FBS , Freiburg, Gießen, Hamburg, Hannover, Karlsruhe, Koblenz, Krefeld, Kronshagen, Leipzig, Neumünster, Oberschleißheim, Oldenburg, Rostock, Saarbrücken, and Stendal. All participants are accredited by DAkkS, the national accreditation body for the Federal Republic of Germany. It was left up to the participants to decide whether they wanted to receive only the virology or serology panel or both. Virological testing was performed by all participants and all used the FMDV 3D RT-qPCR assay  recommenIn addition to testing the provided samples, the laboratories were asked to voluntarily report the number of virological and serological exclusion tests for FMD for each of the preceding four years (2017–2020) and provide details about their exclusion testing scheme. To verify the diagnostic specificity of the ELISA, the laboratories were requested to use the remaining reactions from the provided kits to test other samples from their routine caseload. t values had only increased by 1.3 on average compared to the frozen samples. Testing of the panels stored at the NRL confirmed the stability of the samples in the virology panel during shipping at ambient temperature. Even after 5 days at ambient temperature, CUp to a dilution of 1:10,000  or automated extraction using the NucleoMag VET Kit  with a KingFisherFlex magnetic particle processor , followed by RT-qPCR with the SuperScript III One-Step RT-PCR System (Thermo Fisher Scientific).Similarly, the more strongly positive samples P23 and P24 were detected reliably by all participants. Sample P22, which was the weakest sample in the virological panel, was correctly identified by 76% of the laboratories. All negative samples were correctly identified by all participants. Overall, the best results in terms of low CThe results obtained by the 12 laboratories using the IRES1 PCR were roughly similar to the 3D-OIE assay, but with reduced sensitivity, especially at the higher dilutions. Up to and including the 1:10,000 dilution (P07–P09), all positive samples were detected by all participants. Starting at the 1:100,000 dilution (P10–P13), however, some laboratories could no longer correctly identify some or all of the replicates. At the 1:1,000,000 dilution (P14–P17), only 23% of the participants returned positive results for all four replicates. The negative samples were identified correctly, with the exception of one laboratory, which evaluated one of the four replicates as positive. To analyze the spread of the PCR results obtained by the participants, the two-fold standard deviation was calculated see . There iTesting of the panels stored at the NRL confirmed the stability of the samples in the serology panel during shipping at ambient temperature. On average, after 5 days of storage, the S/N% ratios between the unrefrigerated and frozen samples differed by 2.1 percentage points, which had no impact on the interpretation of the ELISA. All 19 participants receiving the serology panel correctly identified all samples see . All negEleven of the participating laboratories provided ELISA data for additional samples from their routine caseload. These data were also collected using the ID Screen FMD NSP Competition ELISA. With nearly 50% of the samples, the dominant animal species was cattle, followed by 20% small ruminants and approx. 30% pigs (domestic and wild boar). Some zoo animals were represented, such as six samples from Bactrian camels, two samples from okapi and Kirk’s dik-dik, and one sample from a bison. A total of 2040 measurements were submitted, of which 2028 were negative and 12 were positive , which also avoids issues related to low sample quality. Bacterial contaminants can produce antibody-binding proteins that cause unspecific reactions . It is possible, however, that the positive reaction will persist even with repeated sampling. For swine vesicular disease virus, between 1 and 3 of 1000 pigs are so-called “singleton reactors”, which are serologically positive in the absence of any evidence of previous infection . SimilarUltimately, the final interpretation of each case must consider all available clinical, serological, virological, and epidemiological evidence. In the exclusion testing scheme, RT-qPCR plays a much larger role than NSP antibody ELISAs (1581 vs. 232 tests between 2017 and 2020) because FMD exclusion tests are usually prompted by acute clinical observations or suspicious post-mortem findings. Only a few hundred samples per year are submitted for FMD exclusion testing in Germany, which is very low compared to the number of cattle and pigs (approx. 11.3 million and 26 million) . Most saAll participating laboratories are fully proficient in FMD diagnostics. FMDV antigen detection by RT-qPCR is routinely used for FMD exclusion tests. The number of exclusion tests is at an acceptable level but should be further increased to safeguard the freedom from FMD in Germany and the EU.


Rheumatoid arthritis (RA) composite disease activity indices have become handy tools in daily clinical practice and crucial in defining remission or low disease activity, the main target of the RA treatment. However, there is no definition of the best index to assess disease activity in clinical practice.To compare the residual activity among the indices with the ACR/EULAR remission criteria (Boolean method) to identify the most feasible for assessing remission in daily practice, also considering correlation and concordance, sensibility, and specificity.We selected 1116 patients with established RA from the real-life rheumatoid arthritis study database—REAL. The composite disease activity indices—DAS28-ESR, DAS28-CRP, SDAI, and CDAI–and their components were compared to the Boolean method to identify residual activity using binomial regression. The indices were analyzed for correlation and agreement using the Spearman index and weighted kappa. The chi-square test evaluated sensibility and specificity for remission based on the Boolean method.k:0,88). CDAI and SDAI showed higher sensitivity and specificity for remission based on the Boolean method. CDAI was performed in 99% of patients, while DAS28 and SDAI were completed in approximately 85%.DAS28-CRP overestimated remission and confirmed higher residual activity than SDAI and CDAI. The indices showed good correlation and agreement, with a better relationship between SDAI and CDAI (Although all composite indices of activity can be used in clinical practice and showed good agreement, CDAI and SDAI have better performance in evaluating remission based on the Boolean method, showing less residual activity and higher sensibility and specificity. In addition, CDAI seems to be more feasible for disease activity evaluation in daily clinical practice, especially in developing countries. Rheumatoid arthritis (RA) is a systemic inflammatory disease characterized by erosive peripheral joint involvement that can lead to structural damage, deformities, functional impairment, and poor quality of life. The worldwide prevalence is 0.2 to 1%, concordant with Brazilian data .In the past decades, RA treatment has undergone a significant transformation. The use of disease-modifying anti-rheumatic drugs (DMARDs) under a strict treatment regimen (treat-to-target or T2T) reduced the loss of function, improved quality of life, and reduced radiographic progression compared to previous strategies .28-joint Disease Activity Score (DAS28) was validated in 1995 with an erythrocyte sedimentation rate (ESR) as an inflammatory marker. In 2004, C-reactive protein (CRP) was included in the formula .One thousand one hundred and sixteen (1116) patients were enrolled in the present cohort. Their demographics and clinical and laboratory characteristics are shown in Approximately 90% of patients were female, with a mean age of 56.7 years and a median disease duration of 12.7 years. Most patients were white (56.8%), with a median educational time of 8 years. The seropositivity rate was almost 80% for both rheumatoid factor and ACPA. A low rate of smoking (10.8%) and fibromyalgia  was observed. Median HAQ-DI was 0.875, with mild functional loss. DAS28-ESR median was 3.5 and DAS28-CRP 3.04, SDAI 10.5, and CDAI 9, all representing low disease activity but revealing approximately 50% of patients presenting moderate to high disease activity.By classifying patients according to disease activity, approximately 50% had low activity or remission, except for DAS28-ESR, whose rate was around 40% . AlthougHowever, there is a difference in activity classification, and the indices disagreed when classifying low activity and remission, with a higher rate of low activity status by SDAI and CDAI than remission and a higher percentage of remission status by DAS28, both ESR and CRP .The components of the indices were evaluated according to residual activity, which was characterized as the proportion of patients that did not meet the Boolean remission criteria and presented values superior to 1 in all components of the latter . The estThe proportion of patients with swollen and painful joint counts out of target is higher for DAS28-ESR and DAS28-CRP when compared to SDAI and CDAI. While the former two have 3% to 10% of patients with > 1 joint involvement, the latter two have only 1%.Patient assessment (GH and PtGA) was elevated in all indices, including SDAI and CDAI. But, in the latter two, the rate was lower than DAS28-ESR and DAS28-CRP. While DAS28-CRP and DAS28-ESR showed patient pain assessment rates between 40 to 50%, SDAI and CDAI showed around 14% . Although not part of the Boolean method, physician assessment showed higher rates in DAS28 and less residual activity in SDAI and CDAI (10%). SDAI and CDAI had a lower proportion of patients who did not fulfill the Boolean remission criteria in all components .p<0.01), confirming a higher residual activity by DAS28, especially DAS28-CRP. No statistical difference was observed between CDAI and SDAI  and 96.8% (342) of the patients with up to 1 swollen joint and 1 tender joint, respectively, 10% (34) had up to 8 swollen joints in remission. CRP ≤ 1.0 mg/dL was found in 80.4% (289) of the patients, and almost one-fifth showed values greater than 1. Considering DAS28-ESR, 94% (229) of the patients had up to 1 tender joint, and 93.4% (227) had up to 1 swollen joint. Nevertheless, approximately 6% had up to 8 both swollen and tender joints.When considering SDAI and CDAI, 98.8% (178) and 98.6% (220) of the patients presented up to 1 swollen joint, respectively. The maximum tender joint count was 3 for SDAI and 2 for CDAI. CRP was ≤ 1 mg /dL in 85.5% (154) of patients evaluated by SDAI. CRP > 1mg/dL was observed in similar proportions in SDAI and DAS28-CRP . CRP was the only component that has shown more residual activity in CDAI compared to DAS28, but it is important to note that CRP is not part of the CDAI.When considering the low activity, a more significant number of affected joints was observed by DAS28-ESR, pointing up to 20 swollen joints and 13 by DAS28-CRP, while SDAI and CDAI showed a maximum of 8 swollen joints. But it is also important to note there were no newer validated criteria for low activity other than the indices themselves .⍴ 0.971, p <0.001).Correlation among the indices was shown in k = 0.88; CI 95% 0.86–0.90).When comparing sensibility and specificity to achieve remission by the Boolean method, CDAI and SDAI presented higher sensitivity, specificity, and accuracy when compared to other indices .This report is the first large Brazilian cohort study with patients with RA, representing almost all regions of the country that describes demographic, clinical, and therapeutics features of patients with RA and allows comparison of disease activity indices in a real-life setting. Although several studies support the importance of composite disease activity indices, there are limited data related to Brazil. This is the first national study with more than one thousand patients that demonstrates the presence of higher residual activity by DAS28-CRP and DAS28-ESR and encourages the use of SDAI and CDAI as indices for daily practice as an alternative to DAS28.In this study, considering remission, only 117 of the 1116 patients (10.4%) analyzed were concordant for remission by the four indices simultaneously, and 139 (13.4%) were in remission by the Boolean method. These findings differ from other studies, in which remission may be possible in up to 50% of patients with RA with the appropriate treatment strategy . AccordiBased on the Boolean method of remission, residual activity was present in all indices evaluated but lesser in SDAI and CDAI. The estimated difference rate in each component was superior in DAS28-CRP and DAS28-ESR when compared with CDAI and SDAI , with no difference between the latter. In this study, up to 8 tender or swollen joints were observed by DAS28 remission status, a much higher value than the threshold for remission by the Boolean method, which is a concerning result once swollen joint count is directly related to structural and irreversible damage progression in the longer term .Therefore, several studies of composite disease activity indices have already suggested overestimated remission by DAS28, especially DAS28-CRP, even considering stricter cut-offs , 35. AccInterestingly, pain assessment parameters, especially the global health assessment, are elevated in all indices at remission; however, PtGA used in SDAI and CDAI can better classify these patients and show less residual activity. The established disease with irreversible joint damage, comorbidities, and polypharmacy in these patients may contribute to higher pain scores and activity status . On the Although residual symptoms were not evaluated, it is noteworthy that pain, fatigue, and global health assessment described in k:0,88), which correspond to the linear sum and have the same component weight [This study showed good correlation and concordance among indices, supporting the literature data, which already recognized the positive correlation and agreement among indices, especially between SDAI and CDAI , 41–43. t weight , 41–43.Finally, SDAI and CDAI were closer to the Boolean remission concept, and both showed lower residual activity when compared with DAS28-ESR and DAS28-CRP. DAS28 and SDAI were performed in approximately 85%. In comparison, CDAI was performed in 99% of patients and presented a maximum of two joints affected in remission, favoring the latter use routinely when laboratory tests are unavailable and considering its performance in almost the totality of patients , 41–43. The study presents several limitations, including the impossibility of comparison of the indices with the gold standard imaging method, classification of residual activity only by disease activity scores, no control of variables, and no standardization of laboratory tests. However, this real-world study can recognize local challenges and allow rational allocation of resources and the development of strategies that better adjust to the local reality.Although all composite disease activity indices can be used in clinical practice and showed good agreement, CDAI and SDAI showed less residual activity, higher sensibility, and specificity for remission based on the Boolean method. In developing countries, the availability of a low-cost and readily accessible index such as CDAI may be better for public health planning strategy. This study encourages using SDAI and CDAI indices for daily practice as an alternative to DAS28.


Dengue is a vector-borne disease present in most tropical countries, infecting an average of 50 to 100 million people per year. Socioeconomic, demographic, and environmental factors directly influence the transmission cycle of the dengue virus (DENV). In Brazil, these factors vary between regions producing different profiles of dengue transmission and challenging the epidemiological surveillance of the disease. In this article, we aimed at classifying the profiles of dengue transmission in 1,823 Brazilian municipalities, covering different climates, from 2010 to 2019. Time series data of dengue cases were obtained from six states: Ceará and Maranhão in the semiarid Northeast, Minas Gerais in the countryside, Espírito Santo and Rio de Janeiro in the tropical Atlantic coast, and Paraná in the subtropical region. To describe the time series, we proposed a set of epi-features of the magnitude and duration of the dengue epidemic cycles, totaling 13 indicators. Using these epi-features as inputs, a multivariate cluster algorithm was employed to classify the municipalities according to their dengue transmission profile. Municipalities were classified into four distinct dengue transmission profiles: persistent transmission (7.8%), epidemic (21.3%), episodic/epidemic (43.2%), and episodic transmission (27.6%). Different profiles were associated with the municipality’s population size and climate. Municipalities with higher incidence and larger populations tended to be classified as persistent transmission, suggesting the existence of critical community size. This association, however, varies depending on the state, indicating the importance of other factors. The proposed classification is useful for developing more specific and precise surveillance protocols for regions with different dengue transmission profiles, as well as more precise public policies for dengue prevention. Aedes aegypti. Health promotion campaigns aimed at encouraging people to reduce mosquito breeding sites have limited effect. In addition, the heterogeneity of the territories that have dengue becomes a major challenge for the epidemiological surveillance of the disease. Brazil has a territory of continental size, and single standardized surveillance is not very effective for monitoring this arbovirus. Classifying types of dengue dynamics based on features of the epidemiological cycle in each location has the potential to increase the precision of surveillance and control strategies. In our study, we were able to classify areas according to different dengue transmission profiles, ranging from episodic to persistent transmission. These results can provide tools to guide actions aimed at achieving the World Health Organization’s goals of eliminating neglected tropical diseases in countries that have the virus.Dengue is one of the fastest-growing vector-borne diseases in the world. Currently, vaccines are experimental and are not very effective, so prevention depends on the control of the mosquito  Dengue is a disease of great public health concern worldwide, mainly in growing urban centers of tropical regions –3. BraziAedes aegypti mosquito is the main dengue vector, while Aedes albopictus is considered a potential vector in rural and semi-urban [Ae. aegypti. Reproduction rate, mosquito abundance, and longevity are important components of the vectorial capacity and are all dependent on adequate temperature and humidity [Brazil’s continental size and socioeconomic, demographic, climatic, and environmental heterogeneity affect the local temporal patterns of dengue transmission, contributing to disease maintenance at endemic levels in some areas, alternating with areas characterized by epidemic periods throughout almost the entire Brazilian territory –11. The mi-urban . The abumi-urban ,14. Morehumidity –17. Low humidity –20.In a context of heterogeneous population density and different climate regimes, it is expected that dengue transmission will not behave similarly in all places. Less populated municipalities in drier or cooler climates will experience less dengue outbreaks than municipalities with large urban populations in wet and humid climates. Discriminating these different profiles is important for many reasons. First, from an academic perspective, the existence of a critical community size for dengue, above which dengue transmission is more persistent has been debated –24. Whethttps://info.dengue.mat.br/) an arbovirus alert system that harmonizes official dengue notification data from the Brazilian Notifiable Diseases Information System (SINAN), with climate data from meteorological stations at Brazilian airports [http://portalsinan.saude.gov.br/) are public and aggregated by week and municipality and, according to current Brazilian laws, there is no need for additional approval from the ethics committee.The disease data consist of dengue cases reported from residents of 1,823 municipalities located in six Brazilian states, from September 2010 to September 2020. The source is the Infodengue platform  [To describe the time series of dengue transmission in each municipality, we developed a set of summary descriptors inspired by the concept of epi-features proposed by Tabataba . (2017)  for resp. (2017)  and has . (2017) ,34,35. S. (2017) ,37. Besi. (2017) ,38. The . (2017) . In summHere, we adapted and proposed new epi-features to describe the transmission pattern of dengue during an epidemiological year, including measures such as the magnitude of cases, the length of periods with and without notified cases, and measures of seasonality and trend . Before Multivariate cluster analysis was performed to define groups of municipalities with similar epi-features First, a correlation matrix was calculated for all proposed epi-features. Highly correlated epi-features (>0.80) were analyzed and three were removed from subsequent analysis to reduce collinearity. Between Dsmax and Dsmed, we opted to keep Dsmax although similar results are obtained using Dsmed. Dsmax is a good descriptor of longest periods without cases. Between P and Dcmax, we kept Dcmax, accounting for the longest periods with cases. Although not highly correlated, we dropped Dsmed from the analysis, since its counterpart Dcmed was removed, as well. The correlation matrix of the final set of variables is shown in . Second,The clustering algorithm of choice was PAM (partitioning around medoids) because of its robustness, low sensitivity to outliers and its ability to preselect the number of clusters ,41. The The six states under investigation account for 29.5%  of the Brazilian population. During the study period, an average of 2,568 cases were reported per epidemiological year per municipality, ranging from 0 to 577,674 cases. Distribution of epi-features per state is shown as violin plots in The magnitude of the epidemic peak (Xp) varied widely between municipalities, with 95.4% showing Xp fewer than 100 cases. At the other extreme, there were municipalities with very high epidemic peaks, for example, Belo Horizonte (MG), with Xp = 5,563 cases. In most municipalities , the peak occurred between weeks Tp = 15 and Tp = 25, corresponding to the summer months in Brazil. In MA and CE, the northeastern states, the week of the epidemic peak varies more and can occur later in the year, ranging from Tp = 1 to 34 in MA and Tp = 5 to 36 in CE. The epi-feature Dc3 ranged between 0 and 2.8. Dc3 equal to 0 means the absence of any 3-week period with continuous reporting of dengue cases throughout the entire decade. There are 604 municipalities with Dc3 = 0, mainly in Minas Gerais (299 or 49.5%) and Maranhão (125 or 20.7%). All states had at least one municipality with Dc3 > 1, which indicates intermittent transmission, that is, transmission periods interspersed by weeks with 0 cases (133 or 7.9%). The epi-feature Dc6 measures the occurrence of longer transmission periods, of at least six weeks or two-generation cycles. These were more frequent in Rio de Janeiro and Espírito Santo. Dcmax measures the duration of the longest period with cases during an epidemiological year. It ranged from 0 to 52 weeks (mean = 3.4 weeks). The longest periods of continuous transmission occurred in the municipalities of Rio de Janeiro (RJ) and Londrina (PR), while the shortest periods were in the state of Maranhão. Dci measures the presence of isolated dengue detection events (a positive week preceded and followed by negative weeks). Dci ranged from 0 to 3.6 (mean = 0.46), with 39 municipalities (2.13%) presenting mean Dci = 1, that is, only one isolated week per year with five or more dengue cases (Dci). Such events were frequent in all states except Rio de Janeiro and Espírito Santo.The epi-features Ds3, Ds6, and Dsmax characterize periods with no dengue cases. Ds3 varied from 0 to 4.7 (mean = 2.4), while Ds6 varied from 0 to 3 (median = 2.6). Events of six weeks or more without cases occurred with an average frequency of once a year (Ds6). It ranged from 0 to 1.3–1.6 across all the states and was more frequent in Maranhão and Ceará in the Northeast and Minas Gerais in the Southeast. The distributions of Ds3 and Ds6 were similar in CE and MA, ranging mostly between values Ds3 = 1 to 3 and Ds6 = 1 to 2.5. The other states presented higher variability, particularly RJ and ES. The maximum period without cases, Dsmax, varied from 0 to 52 weeks (mean = 25.17). There were 28 municipalities without any record of dengue during the whole year (Dsmax = 52), including Cajapió (MA), Bias Fortes (MG) and Agudos do Sul (PR). All are small municipalities with low population density. The latter two have cold climates, with mean temperatures from 10 to 15°C.Finally, ST is an indicator of the trend-to-seasonality ratio. Low values imply a strong seasonal signal relative to the historical trend of the municipality, while high values indicate the opposite. ST varied from 0 to 597, with values concentrated between 0 and 10. Belo Horizonte (MG) is an example of high trend-to-seasonality ratio, where the seasonal component was 2.76 and the trend was 316.9, resulting in ST = 597.04. Bacuritiba (MA), on the other hand, is an example of strong seasonality compared to the historical trend, with the seasonal component = 52 and trend = 0.0019, resulting in ST = 0.001923.(k-medoids) was applied, considering k = 2, 3, 4, or 5 clusters. The silhouette method was used to assess the goodness of the classification in 2, 3, 4, or 5 groups . AccordiAs a result, we chose the classification in four groups, which also provides us with a more detailed description of the patterns found.Persistent dengue transmission is defined by medium to high frequency of weeks with disease occurrence, with few or no periods without records of cases, thus implying conditions for continuous maintenance of viral circulation. Cluster 4 was interpreted as Persistent Transmission because the municipalities in it presented large epidemic peaks (Xp) , high frequency of periods with 3 weeks  or 6 weeks (mean = 0.95 times/year) with dengue cases (Dc3 and Dc6), and the largest continuous periods with cases (Dcmax), with 51.9 of 52 weeks. Cluster 4 also presented the lowest frequency of consecutive weeks without cases . In this cluster, the ST epi-feature shows a trend component greater than the seasonality component, with an average of 15. A typical example of a municipality with persistent dengue transmission is Nova Friburgo in the mountainous region of Rio de Janeiro.Epidemic dengue transmission is defined by the seasonal or periodic occurrence of weeks with high incidence of cases, interspersed with periods with no cases. The transmission period can be short or long, but incidence in the transmission period can reach high values. After careful consideration of the distribution of the epi-features among the clusters, we assigned this profile to Cluster 1. In this cluster, municipalities presented epidemic peaks (Xp) with moderate values  and presented less frequent periods with 3 or 6 consecutive weeks with cases (Dc3 and Dc6), when compared to the persistent pattern. On average, Ds6 = 1, suggesting one period per year. Furthermore, these municipalities presented 3 or 6 weeks without cases (Ds3 and Ds6) only twice a year on average. The Dcmax, on average, was 5 consecutive weeks, corresponding to approximately two generations of dengue transmission. The maximum period without cases (Dsmax) was 13 weeks on average, accounting for about 25% of an epidemiological year. Finally, the ratio between trend and seasonality (ST) suggests that the seasonality of dengue in municipalities within this cluster is higher than those in cluster 4, having an average value of 1.4, reaching 7.1. This means that these municipalities have more seasonally marked periods of disease occurrence, an indicator of climate-mediated transmission. A typical example of a municipality with an epidemic dengue profile is Guaxupé, located in southwest Minas Gerais state.The Episodic / Epidemic transmission profile encompasses the transition between the Episodic dengue transmission profile (which will be described below) and the above-mentioned Epidemic profile. It is characterized by the occurrence of a few weeks per year with dengue cases and the non-sustainability of dengue transmission for a long period. When there are cases, the number exceeds those observed in the Episodic profile. Cluster 3 was assigned to this profile because the municipalities in it showed case peaks (Xp) with intermediate values between the Episodic and Epidemic profiles  and there was a low frequency, although higher than in the Episodic profile, of periods with 3 or 6 consecutive weeks with cases . Cluster 3 contains municipalities with long periods without cases ). Finally, the ratio between trend and seasonality (ST) shows that the trend varies considerably in relation to the seasonality, with values ranging from 0.2 to 2.4. An example of a municipality with an Episodic/Epidemic dengue profile is Confins, located in Greater Metropolitan Belo Horizonte, capital of Minas Gerais state. Confins is 39 km from the city of Belo Horizonte, classified in the Persistent Transmission dengue profile.The Episodic profile stands out for an irregular occurrence of the disease in a particular location. When there are cases, they cannot be sustained, the cycle is short, and the number of cases is small. There are long periods during which the disease is not detected. Cluster 2 was interpreted as Episodic, as the municipalities in it presented the lowest dengue peaks (Xp), in fact almost non-existent , there were rare periods with 3 or 6 consecutive weeks with cases (Dc3 and Dc6), about 0.02 times a year, and long case-free periods (Dsmax) of 41.7 weeks on average. The ratio between trend and seasonality (ST) of dengue in each location shows that the trend is smaller than the seasonality component. An example of a municipality with an Episodic dengue profile is Davinópolis, located in western Maranhão state. A summary of the characteristics of the transmission profiles can be seen in Of all 1,823 municipalities, only 7.8% were classified as having Persistent Dengue Transmission, compared to 21.3% with Epidemic Dengue Transmission, 43.2% with Episodic/Epidemic Dengue Transmission, and 27.6% with Episodic Transmission . The EpiIn the states of Espírito Santo (ES), Minas Gerais (MG), and Rio de Janeiro (RJ), located in the more populated and urbanized Southwest region of Brazil, we found the Persistent Transmission profile in municipalities with populations greater than 25,000. Meanwhile, Episodic Transmission occurs in municipalities with fewer than 9,800 inhabitants in ES, 15,000 in RJ, and 30,000 in MG. The Epidemic profile, on the other hand, can be detected in very small municipalities in ES and MG, with as few as 3,700 and 5,800 inhabitants, respectively. Paraná, located in the subtropical region, showed the largest differences in population size per profile when compared to other states, especially in the Persistent Transmission profile. Ten municipalities in northern Paraná, in Greater Metropolitan Londrina, presented Persistent Transmission despite having fewer than 20,000 inhabitants. In this state, some municipalities with fewer than 2,000 inhabitants showed Epidemic profiles.This study aimed to propose a classification of dengue transmission profiles based on epi-features extracted from the time series of cases in Brazilian municipalities varying in population size, mean annual dengue incidence, and climate. The Persistent Transmission profile predominated in the states of Espírito Santo and Rio de Janeiro, characterized by tropical humid and warm climate, higher population density, and more urbanization, while the Episodic and Episodic/Epidemic profiles were concentrated in Ceará and parts of Maranhão and Minas Gerais, where the climate is predominantly dry, and the municipalities are less populated and more rural. Paraná, in the subtropical region, showed a clear spatial separation of profiles, likely associated with the temperature limits for dengue transmission.et al. (2009) [Climate and population density are important drivers of dengue transmission. All large municipalities in this study  presented Persistent Transmission, independent of climate. Meanwhile, the Episodic profile was limited to municipalities with fewer than 50,000 inhabitants. In Peru, a study at the state level by Chowell . (2009)  found a . (2009) ,45,46. M. (2009) ,14,15,19. (2009) ,47–49. Tet al. (2019) and Seah et al. (2020) [Aedes mosquito. Meanwhile, Costa et al. (2013) and Souza et al. (2018) [Aedes populations even in unfavorable climates.Several studies have shown the association between climatic variables and dengue transmission ,24,50,51. (2020) ,53 show . (2018) ,55 discuParaná is situated in the subtropical zone. The state has two climates, humid subtropical, where there are more municipalities with Persistent and Epidemic profiles. A cluster of municipalities with the persistent transmission is found in the state, including the city of Londrina and its surroundings. This case deserves closer scrutiny, as this region has shown Persistent Transmission even in small municipalities with 2,400 inhabitants. This phenomenon may be explained by the high connectivity between these populations, maintaining the disease in a source-sink dynamics. In southern Paraná, with mean temperatures between 10 and 15°C, there are mainly municipalities classified as having Episodic and Episodic/Epidemic Transmission. In the literature, other authors have defined transmission profiles (“epidemic types”) of transmissible diseases based on population size and associated variables for other transmissible diseases. Among the seminal studies, Bartlett (1960)  used a sThe usefulness of classifying epidemic profiles for defining public health policies related to dengue is exemplified by the World Health Organization manual (2013) that categorizes Southeast Asian countries according to their epidemiological characteristics for dengue. Four classes were established: Class A comprises countries with hospitalizations and deaths of children from the disease and circulation of the virus in rural areas while dengue is endemic in urban areas; Class B refers to countries with the occurrence of frequent epidemic cycles accompanied by expansion into the interior; Class C presents indefinite disease endemicity, and Class D has no evidence of endemicity. Each of these classes emerges from a combination of profiles, which could be determined in a more systematic way by using the methodology introduced here. With this bottom-up approach, the municipal classification allows building a new classification at the state or national level.et al. (2020)[et al. (2021) [There are other studies on dengue transmission patterns and their determinants in Brazil, using different methodologies. Silva l. (2020) used a m. (2021)  used spaThere are limitations to the present analysis. First, differences in the dengue profile can be influenced by the reporting effort, for example, transmission can occur even if there are no reported cases. Second, in Brazil, chikungunya emerged in late 2014, causing two epidemic years, 2015 and 2016, and Zika emerged in 2015, with two epidemic years, 2016 and 2017. In these years, the number of dengue cases may have been affected by misdiagnosis. However, in the other seven years of the study’s time series (2010–2019) dengue was always dominant, corroborating the fact that Brazil is endemic for the disease. Third, the proposed epi-features represent only a subset of all possible descriptors that we could derive from these time series. Other characteristics may provide a better discrimination between Clusters 3 and 4. Fourth, the classification may change if the study includes more municipalities or considers a longer time series. Finally, the classification proposed in this study used the PAM algorithm method, although there are studies that describe other clustering methods that could be used, such as the Kamila algorithm and Latent Class Analysis, for example , the oneThe classification of dengue transmission profiles based on the epi-features of the epidemic curves provided a useful characterization. A gradient of profiles was obtained, ranging from Episodic to Persistent Transmission. We found evidence of an association between these profiles, climate and population size, consistent with the literature on dengue. All the proposed epi-features were important for the classification of municipalities in relation to their dengue transmission, but there is no limit to the inclusion of other descriptors in futures to increase the discriminatory power between the clusters. This method can also be adapted to other communicable diseases, such as other arboviruses and respiratory diseases, as the descriptors are easily modifiable to measure the epidemic cycle of other acute diseases.In conclusion, the classification of municipalities in temporal transmission profiles can bring significant benefits for the effective monitoring of the disease. It can be used to improve dengue alerts, such as those carried out by Infodengue, as well as to develop more precise public policies to combat this disease.S1 Fig(A) Matrix with the 13 initially proposed epi-features; (B) Matrix with 10 epi-features after excluding Dsmed, Dcmed and P.(TIF)Click here for additional data file.


The study aimed to investigate the potentiality of chemokines, including MCP-1, CCL15, CCL20, and CXCL14, as biomarkers for differential diagnosis between benign tumors and ovarian cancer (OC).A cross-sectional study was conducted in women aged >18 years who had adnexal masses treated with elective surgery at the HRH Maha Chakri Sirindhorn Medical Center, Srinakharinwirot University, between 2020 and 2021. The preoperative MCP-1, CCL15, CCL20, and CXCL14 serum levels were measured using a sandwich enzyme-linked immunosorbent assay. Preoperative diagnosis was defined according to the risk of malignancy index. The histological diagnosis and cancer subtype were confirmed using pathological specimens.CCL20 was observed in ovarian cancers comparing with that in benign tissues. We found that CCL20 levels could differentiate between benign tumors and OC with 60.61% sensitivity and 75.44% specificity at the optimal cutoff value of 38.79 pg/ml. Finally, the logistic regression model integrating CCL20, CA125, and menopause status promoted diagnostic accuracy by increasing the specificity to 91.23%.Ninety-eight participants were preoperatively diagnosed with malignant tumors. The pathological diagnosis confirmed OC in 33 patients and disclosed 27 misdiagnosed cases, of which endometriotic cyst was the most common (44.44%). CCL20 and CA125 serum levels were significantly higher in the patients with cancer than in those with benign. In addition, CCL20 level could differentiate between benign and early-stage malignancy. Furthermore, only CCL20 levels could distinguish endometriotic cysts from OC, whereas CA125 levels could not. Concordant with the serum protein level, the increased mRNA level of Our study revealed the potential usefulness of CCL20 level as a biomarker for diagnosing early-stage OC with endometriosis differentiation. We recommend further studies to confirm the accuracy of CCL20 levels with the current diagnosis in a large patient sample. Ovarian cancer (OC) is the second most common gynecological cancer, with a reported incidence rate of 7.9 per 100,000 women annually , 3. Its via several mechanisms, including angiogenesis, cell proliferation, migration, and immune invasion, which are necessary to ensure the success of growing tumors and disseminating metastasis . Written informed consent was obtained from all participants. All procedures were performed in accordance with the relevant guidelines and regulations. Research staff members had completed the Good Clinical Practice training.via a peripheral venous puncture. Clinical data, preoperative diagnosis, operative procedure, and postoperative diagnosis were recorded. Preoperative diagnosis was defined according to the risk of malignancy index (RMI) based on the score calculated from the serum CA125 level, menopause status, and ultrasonography. Postoperative diagnosis was based on pathologists’ histological interpretations.The inclusion criteria were women with clinically diagnosed ovarian or adnexal masses who underwent elective surgery between July 2020 and October 2021, with ages >18 years, and with an American Society of Anesthesiologists physical status score of I–II. Participants were excluded if they had a history of chemotherapy or radiotherapy, serious psychiatric disease, pregnancy, previous history of OC or any malignancy, active inflammatory disorders, i.e., rheumatoid arthritis, multiple sclerosis, and type I diabetes, and refused to sign an informed consent form. Patients without intraoperative findings indicating a pelvic or adnexal mass were also excluded from the data analysis. All participants were hospitalized for preoperative preparation at least 24 hours before surgery, and a blood sample was preoperatively collected r2 value of the fitting line was >0.98. The CA125 level was obtained from routine hospital laboratory measurements.The clot blood sample was centrifuged at 3,000 RPM for 10 minutes to separate serum immediately and stored at −20°C until the analysis. Chemokines were quantitatively analyzed in patient serum using a sandwich enzyme-linked immunosorbent assay (ELISA) kit from R&D Systems , in accordance with the manufacturer’s instructions. The absorbance was determined instantly using a CLARIOstar Plus microplate reader  at wavelengths of 450 and 570 nm. The concentration of each chemokine was calculated by subtracting each absorbance reading at 570 nm from the reading at 450 nm and the average of duplicate readings, and then normalized with the average of the blanks. A standard curve was created with a quadratic polynomial fitting curve in Microsoft Excel for MAC version 16.58. The standard curve was considered as best fitted if CCL20 and CA125 (MUC16) in human ovarian tissues were retrieved from two public datasets, GSE4122  curves were plotted, and the area under the curve (AUC) was calculated to compare the performance of the biomarkers for predicting OC in terms of sensitivity, specificity, positive predictive value, and negative predictive value. The ROC curves were compared using a chi-square test. The web tools easyROC version 1.3.1 and STATA 14.1  were used to calculate the optimal cutoff values (Youden index) (https://www.graphpad.com) and Statistical Package for Social Sciences (SPSS) versions 28 for Windows .Statistical analysis was performed using a power of 80% and an n index) . A logisThis study included 100 patients for eligibility. Two patients with gastrointestinal stromal tumors were excluded from the analysis; thus, 98 patients were included in the analysis, as shown in To determine the preoperative protein levels in the patients’ serum samples, an ELISA kit was used to measure the concentrations of MCP-1, CCL15, CCL20, and CXCL14 chemokines. A total of 98 samples were analyzed for MCP-1, CCL15, and CXCL14. Two samples had CCL20 concentrations below the detection limit, leaving 96 samples analyzed for this chemokine. The concentrations of MCP-1 and CCL20 in the preoperatively diagnosed malignant group were significantly higher than those in the benign group  and advanced stage (stages III and IV). CCL20 levels (pg/ml) significantly increased in early-stage tumor than in benign cases  Figure 3CCL20 and pathological diagnosis results. GSE4122 dataset showed that CCL20 level significantly increased in the malignancy compared to benign groups , we did not find any candidate biomarkers for the histological subtypes of OC (data not shown). The only tissue subtype that could be differentiated was the tissue origin, that is, epithelial, or nonepithelial cells, based on the elevated CA125 levels in the epithelial subtype  can be found in the article/The studies involving human participants were reviewed and approved by Institutional Review Board (IRB), Strategic Wisdom and Research Institute, Srinakharinwirot University. The patients/participants provided their written informed consent to participate in this study.WS, WW, PV, and CC performed formal analysis and investigation. WS also performed data curation, statistical analysis, and visualization. WS wrote the first draft of the manuscript. VY supervised formal analysis and investigation. PN contributed the resources. VY and PN contributed to the conceptualization, methodology, design of the study, validation of the results, funding acquisition, and reviewing and editing of the manuscript. All authors contributed to the article and approved the submitted version.This study was granted by Research Fund, the Faculty of Medicine, Srinakharinwirot University and supported by The Second Century Fund (C2F), Chulalongkorn UniversityAll members of Department of Obstetrics and Gynecology, Faculty of Medicine, Srinakharinwirot University. WS and VY are supported by The Second Century Fund (C2F), Chulalongkorn University.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. 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With the intensification of ecosystem damage, birds have become the symbolic species of the ecosystem. Ornithology with interdisciplinary technical research plays a great significance for protecting birds and evaluating ecosystem quality. Deep learning shows great progress for birdsongs recognition. However, as the number of network layers increases in traditional CNN, semantic information gradually becomes richer and detailed information disappears. Secondly, the global information carried by the entire input may be lost in convolution, pooling, or other operations, and these problems will weaken the performance of classification. In order to solve such problems, based on the feature spectrogram from the wavelet transform for the birdsongs, this paper explored the multi-scale convolution neural network (MSCNN) and proposed an ensemble multi-scale convolution neural network (EMSCNN) classification framework. The experiments compared the MSCNN and EMSCNN models with other CNN models including LeNet, VGG16, ResNet101, MobileNetV2, EfficientNetB7, Darknet53 and SPP-net. The results showed that the MSCNN model achieved an accuracy of 89.61%, and EMSCNN achieved an accuracy of 91.49%. In the experiments on the recognition of 30 species of birds, our models effectively improved the classification effect with high stability and efficiency, indicating that the models have better generalization ability and are suitable for birdsongs species recognition. It provides methodological and technical scheme reference for bird classification research. The study of birds is of great significance for protecting birds, understanding wetland ecosystems and evaluating the quality of ecosystems. The International Union for Conservation of Nature (IUCN 2014)3 listed that there are 1373 bird species in the world and more than 13% of species are vulnerable and even face immediate danger of extinction. Due to the characteristics of birds with high flexibility of movement, extensive moving range, and strong environmental adaptability, birdsong, a sign of activities of birds, is often used to detect, monitor, and quantify species. Birdsong contains rapid time modulation, and has stability in the same species and discrimination between species. Automatic bird classification model, established with birdsong audio data, has many potential applications in protection, ecology and archives4.As the construction of ecological civilization advances, methods for efficient and quick assessment of the quality of the environment need to be further studied. Birds play an essential role in the ecosystem, and their communities are a crucial indicator of environmental quality5. Therefore, many researchers in bird song recognition often use MFCC as extracted audio features. In addition, to better analyze bird song, audio data is usually converted into a spectrogram with methods such as short-time Fourier transform (STFT)7 and wavelet9. Many researchers have carried out a lot of research based on traditional machine learning methods for birdsong classification. For limited data, an automated birdsong phrase classification algorithm, dynamic time warping (DTW), is developed to reduce the need for manual annotation10. Ladislav Ptacek11 and Chang-Hsing Lee12 using Gaussian Mixture Model (GMM) to classify birds on different feature data sets, have achieved good results. Douwe Gelling13 used HMM and GMM models to study the importance of using time information in recognizing bird vocalizations. Diego Rafael Lucio14 built a support vector machines (SVM) classification model based on the acoustic and visual features extracted from birdsong, and obtained an accuracy rate of 91.08%.Research on birdsongs has demonstrated that human language and birdsongs have striking analogies in vocal articulation and neural functionality15, which learns feature representation via a hierarchical structure, has achieved remarkable success in various fields. Inspired by this, Ahmad Salman16 used the deep learning method in the LifeCLEF14 and LifeCLEF15 fish data sets to achieve a classification rate of more than 90%. Le-Qing Zhu17 proposed a cascade structure combined deep convolutional neural networks (DCNNs) and SVM to identify lepidopteran insects by images. In addition, deep learning is also widely used in birdsong research. Piczak18 and Tóth19 in the BirdCLEF 2016 competition, used deep learning to identify birdsong with good results. Gaurav Gupta20 presented a deep learning approach targeting large-scale prediction and analyzed bird acoustics from 100 different species. Xie21 used selectively fuse model on classifying 43 bird species and increased the classification performance effectively. Although, semantic information becomes richer, detailed information disappears as the number of layers in the network increases33. In addition, the global information carried by the entire input may be lost in convolution, pooling, or other operations, which may affect the performance of the classification34. To mitigate this problem, Di Wang22 proposed a multi-scale information compensation module on CNN. By integrating the original input with more abstract hierarchical learning feature maps, this module maintained detailed semantic information. Research has demonstrated multi-scale is suitable for computing hierarchical features and successful in a range of pixel-level prediction tasks26. It can be seen that deep learning models and Multi-scale CNN models have powerful classification capabilities and can be used in a variety of research fields.In recent years, deep learning27. Ensemble methods have been applied in many research fields such as computational intelligence, statistics, and machine learning28. Zhao29 reported the application of ensemble neural networks. Compared with a single neural network model, an ensemble neural network can effectively improve the generalization ability of the classifier. Antipov30 proposed a convolutional neural network ensemble model to improve the state-of-the-art accuracy of gender recognition from face images on one of the most challenging face image datasets. In summary, ensemble learning has carried out a lot of research in different fields, which provides theoretical support for the follow-up research of this paper.Ensemble learning is well known effective method for combining multiple learning methods to yield better performanceTherefore, classify birds through bird songs based on modern computer technology greatly promote ecological, environmental protection, and biodiversity research. To improve the performance and the knowledge gained from it, we adopted deep learning, transfer learning and ensemble technology on spectrogram in this paper. Our work proposed a multi-scale deep learning model and an ensembled multi-scale deep learning model, characterized by constructing classification models using wavelet spectrogram of birdsong. The contributions of the current work are: (1) The wavelet spectrograms of 30 kinds of bird songs indicate good separability; (2) We propose a multi-scale convolution kernel decomposition method, which can effectively generate multiple convolution kernels from a fixed scale; (3) A multi-scale CNN(MSCNN) model and an ensembled multi-scale CNN(EMSCNN) model are constructed for the different convolution kernels. Our models achieve a better performance than LeNet, VGG16, MobileNetV2, ResNet101, EfficientNetB7, Darknet53 and SPP-net models.This paper is organized as follows: Firstly, we describe the proposed approach for birdsong recognition, which mainly includes wavelet spectrogram generation, multi-scale CNN model and ensemble multi-scale CNN model construction. Secondly, describe the experiment design. Thirdly, discuss and analyze the experimental results. Finally, present conclusions and directions for future work.31. It combines the characteristics of time-domain and frequency-domain. The features on the wavelet scale can also analyze the changes of frequency components over time. Wavelet transform uses a finite-length or fast-decaying "mother wavelet" oscillating waveform to represent a signal; the "mother wavelet" is multi-scaled and translated to match the input signal. The WT provides a time–frequency window that can be modulated, and the width of the window changes with frequency, which make it more suitable for non-stationary signal analysis.The wavelet transform (WT) is the typical time–frequency analysis methodThe wavelet transforms, entclass1pt{minima35. The complex morlet wavelet is defined by formula  is a feedforward neural network, a representative algorithm of deep learning, with convolution calculation and deep structureFeature extraction is affected by the scale of the convolution kernel. Sometimes a single convolution kernel cannot fully extract the key features in a complex image, resulting in the loss of some key features. So, a new multi-scale method is proposed, which uses multiple convolution kernels to obtain features at multiple scales. In this paper, the multiple different scale convolution kernels are derived from the decomposition of large-scale. Taking the 5 × 5 convolution kernel as an example, its decomposed process is shown in Fig. In the constructed CNN model, each convolutional layer uses a different convolution kernel to form a multi-scale convolutional neural network (MSCNN). The operation is defined as:The MSCNN for birdsong classification model is established as shown in Fig. In CNN, the size of the convolution kernel determines the final learned features. The spectral image has the nature of high-dimensional features, which makes it challenging to apply a single convolution kernel. Using a deep CNN network can obtain more information by extracting deeper features, but many useful features will lose as the number of model layers increases. Eventually, the recognition of complex small samples of high-dimensional images becomes difficult. To increase the richness and diversity of model, this work ensembles different scale CNN to achieve better performance. The ensemble multi-scale convolutional neural network (EMSCNN) is defined as:Here, we use the fusion method to ensemble the calculation results under different convolution kernel scales. In formula  \documenThe performance of our proposed birdsong classification model was evaluated using accuracy, precision, recall, F1-score, Top-1, and Top-5. Among them, TP is genuinely positive, indicating the number of samples that have been correctly classified as actual samples. TN is a true negative, which means that the number is correctly classified as not accurate. FP is false positive, which means the number of falsely classified samples as actual samples. FN is a false negative representing the number of actual labels that the classification model did not predict.Accuracy: Represents the percentage of correct predictions.Precision: Indicates the proportion of samples with correct predictions among samples whose actual values are positive.Recall: Indicates the proportion of samples whose actual values are positive and predicted to be positive.F1-score: Takes into account the precision and recall of the classification model.Top-1: It means that the largest probability vector among the predicted results is taken as the expected result. If the classification with the most considerable probability in your predicted effect is correct, the prediction is accurate. Otherwise, the prediction is wrong.Top-5: Among the results of the classification model prediction, the top five with the largest probability vector are selected. As long as the correct probability appears in the top five, the prediction is accurate. Otherwise, the prediction is wrong.The hardware platform used in this experiment is a desktop computer with 128G memory, Ryzen 9 5950X with 16 core and 32 thread CPU, 3.40 GHz frequency and 3090 24G GPU. The operating system is Windows 10 64-bit professional operating system. Annaconda3, PyCharm 2020.1, Python 3.7, TensorFlow 2.6.0 as deep learning platform and MATLAB 2018 as data processing platform are exploited.In this paper, the experiments did not use live birds.The experiments contain three modules: wavelet spectrogram generation, classification model construction and evaluation. Firstly, wavelet spectrograms are generated for collecting bird song data. Then, the MSCNN and EMSCNN models are built on WT spectrograms, and finally, the classification results are obtained through SoftMax. The detail of the experimental design process is shown in Fig. Module 1: Wavelet spectrogram generation. Wavelet spectrogram is generated using wavelet transform for collecting bird song data.Module 2: Classification model construction. The spectrogram of birdsongs is divided into training and validation sets in the ratio of 8:2. The MSCNN and EMSCNN are built by training with input WT spectrograms and compared with the state-art such as LeNet, VGG16, MobileNetV2, ResNet101, EfficientNetB7, Darknet53, and CNN.Module 3: Classification model evaluations. The indicators, Accuracy, Precision, F1-score, Recall, Top-1 and Top-5, are adopted to evaluate the performance of the above classification models.https://www.xeno-canto.org/ and http://www.birder.cn/). Table In this study, a total of 30 kinds of birdsong data were collected from the public birdsong dataset , CNN Scale 2 × 3 (CNN-S23), CNN Scale 3 × 2 (CNN-S32), CNN Scale 3 × 3 (CNN-S33), CNN Scale 5 × 5 (CNN-S55), our MSCNN and EMSCNN. Epoch is set to 30 times; the optimization function is Adam. The activation function used by the convolutional layer of the CNN model is ReLU. The evaluation of the above models is completed through the above 6 indicators.In this work, CNN architecture with different scales is presented as ‘CNN-SXX’, where ‘XX’ stands for the kernel size. For example, CNN-S23 refers to the kernel size is 2 × 3. The structure of CNN models is the same except for the different scales of the convolution kernel. The CNN parameters are listed in Table In the models of LeNet, VGG16, MobileNetV2, ResNet101, EfficientNetB7, and SPP-net the input image size is uniformly set to 112 × 112 × 3, 500 as the output of the dense layer, and the SoftMax is 30 to start model training and verification. For the Darknet53 model, the input image size is set to 112 × 112 × 3, the SoftMax value is 30, and other parameters are default values for training. The results obtained by establishing the models through experiments are shown in Table The Top-1, Top-5, model training time, and the number of iterations of the classification model are obtained through experiments, as shown in Table According to the Top-1 comparison of 14 models, it can be seen that our EMSCNN model achieves the best Accuracy compared with other models with the same training time. Compared with other models, our EMSCNN achieves the most outstanding Accuracy with a slight increase in model training time. It shows that our MSCNN and EMSCNN have more significant advantages in efficiency and performance. In order to evaluate the model more comprehensively, the experiment outputs the results of the Accuracy, precision, Recall, F1-score, Accuracy and loss with epochs transformation of the validation model, as shown in Tables Table The curves in Fig. To further study the utility of our proposed models, two schemes are designed to verify the performance of MSCNN and EMSCNN, respectively.The classification results of CNN-S22, CNN-S23, CNN-S32, CNN-S33, CNN-S55 and MSCNN models in the validation set are shown in Table In Fig. In order to further study the difference of the integrated multi-scale model EMSCNN, each model of EMSCNN is built with the single-scale convolution kernel  while keeping the CNN structure and parameters unchanged. The results are shown in Table According to the experimental results, EMSCNN  proposed in this paper achieves the best results in the different scales. In Table In this paper, we consistently demonstrate that multi-scale CNN models outperform other models for learning wavelet-transformed spectrograms, especially when ensemble multi-scale applications.44 or use short-time Fourier transforms45, and Mel filters46 to generate spectrograms as input into CNN. Mel filtering is designed to imitate human hearing habits, and there is a lack of evidence about whether birds have the same characteristics. The method of directly extracting multi-scale features from birdsong waveforms has limited feature scales, and uses a fixed scale of STFT to extract a single feature. The above methods are difficult to adapt the fast-changing frequency of birdsong in a short period of time. The wavelet transform for multi-resolution analysis can effectively overcome these shortcomings. Continuous wavelet transform generates more discriminative multi-scale spectrograms for subsequent convolutions. Secondly, considering the different sensitivity of the convolution kernel scale to the spectrogram, the small-scale convolution kernel is used to extract high-frequency information, and the large-scale convolution kernel extracts low-frequency information. So as shown in Fig. With respect to the recognition of speech and birdsong, many researchers often learn multi-scale features directly from waveformsRecently, CNN has received more attention from researchers in various fields. The structures CNN have shown great potential in classification problems as well as other tasks such as object detection, semantic segmentation, natural language processing. The well-known architectures such as LeNet, VGG16, MobileNetV2, ResNet101, and EfficientNetB7 have become more popular in image classification. Few people have built multi-scale CNN model with WT spectrum for birdsong recognition. This study explored the characteristic of WT of birdsong and multi-scale CNN to propose the MSCNN and EMSCNN architectures. Compared with the performance of LeNet, VGG16, MobileNetV2, ResNet101, and EfficientNetB7, our MSCNN model accuracy improved 2.21–42.4%, EMSCNN model achieves an increase of 2.21–44.28% compared to other models.36 model achieves better performance in the classification field. SPP-net trains a deep network with a spatial pyramid pooling layer. It can deal with different size of input images. Features extracted at any scale can be pooled. Pyramid pooling makes the network more robust. SPP-net has been applied to object detection, image classification and other fields. In order to better reflect the performance of the model proposed in this paper, an image multi-scale model SPP-net was built in the experiment, and trained on the data set used in this paper. The results are shown in Table Similar to the multi-scale model proposed in this paper, the SPP-netThe performance of MSCNN and EMSCNN proposed in this paper are better than SPP-net. The accuracy of SPP-net is 78.42%, which is 11.19%, 13.07% lower than MSCNN and EMSCNN, respectively. Experimental results demonstrate the effectiveness of the model proposed in this paper, which may provide a reference for the establishment of subsequent multi-scale models.However, the method proposed in this paper still has some limitations. First of all, this paper only uses the wavelet transform extraction method to generate the bird song spectrogram, and does not use other feature extraction methods. Second, the proposed network has only been tested on 30 kinds of bird song data, and it is uncertain whether it will be effective in the increasingly complex birdsong data. Third, the division method of the convolution kernel may not be the optimal solution, and further exploration is needed.Based on the WT spectrogram, this paper proposed a classification method and explored MSCNN and EMSCNN to solve the problem of birdsong classification. We first generated the WT spectrograms of 30 species birdsongs. The MSCNN and EMSCNN classification models were constructed on the WT spectrogram. The results show that in the 5 × 5 convolution kernel decomposition experiment, the performance of the MSCNN model is better than that of LeNet, VGG16, ResNet101, MobileNetV2, EfficientNetB7, Darknet53 and SPP-net models. The accuracy rate of EMSCNN is more excellent than MSCNN with an increase of 1.88%. In the experiments on 30 bird species, MSCNN and EMSCNN effectively improved the classification effect of the model while ensuring the stability and efficiency of the model compared with other models. All indicators are higher than other models, indicating that the models proposed in this paper have better generalization ability. In the future, we will fuse multi-view birdsong features to explore the applicability of the proposed network, and extend the MSCNN and EMSCNN models to more bird song audios and other audio data classification tasks.