Log Score Research Articles

Diagnostic performance of an automated robot for MALDI target preparation in microbial identification.

The MBT Pathfinder is an automated colony-picking robot designed for efficient sample preparation in matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. This article presents results from three key experiments evaluating the instrument's performance in conjunction with MALDI Biotyper instrument. The method comparison experiment assessed its clinical performance, demonstrating comparable results with gram-positive, gram-negative, and anaerobic bacteria (scores larger than 2.00) and superior performance over simple direct yeast transfer (score: 1.80) when compared to samples prepared manually. The repeatability experiment confirmed consistent performance over multiple days and labs (average log score: 2.12, std. deviation: 0.59). The challenge panel experiment showcased its consistent and accurate performance across various samples and settings, yielding average scores between 1.76 and 2.19. These findings underline the MBT Pathfinder as a reliable and efficient tool for MALDI-TOF mass spectrometry sample preparation in clinical and research applications.

Lower extremity physical function and quality of life in patients with stroke: a longitudinal cohort study

PurposeLower extremity physical function (LEPF) is a key component for mobility and is impacted in stroke-related disability. A reduction in LEPF can have a significant impact on an individual’s Quality of Life (QoL). The aim of this study is to characterise the relationship between LEPF and QoL.MethodsThe MOBITEC-Stroke Study is a longitudinal cohort-study including patients with their first occurrence of ischaemic stroke. Using a linear mixed-effects model, the relationship between LEPF (timed up-and-go performance (TUG); predictor) and QoL (Stroke Specific Quality of Life scale (SS-QoL); outcome) at 3 and 12 months post stroke was investigated and adjusted for sex, age, Instrumental Activities of Daily Living (IADL), fear of falling (Falls Efficacy Scale-International Version, FES-I), and stroke severity (National Institute of Stroke Severity scale, NIHSS), accounting for the repeated measurements.ResultsData of 51 patients (65 % males, 35% females) were analysed. The mean age was 71.1 (SD 10.4) years, median NIHSS score was 2.0. SS-QoL was 201.5 (SD 20.5) at 3 months and 204.2 (SD 17.4) at 12 months; the mean change was 2.7 (95% CI -2.4 to 7.7), p= 0.293. A positive association was found between baseline TUG performance (estimate log score -13.923; 95% CI -27.495 to -0.351; p=0.048) and change in SS-QoL score in multivariate regression analysis.ConclusionHigher LEPF (i.e better TUG performance) at baseline, was associated with an improvement in QoL from 3- to 12-months post stroke. These results highlight the critical role of physical function, particularly baseline LEPF, in influencing the QoL of stroke survivors.

Temporal evolution of anxiety and depression in chronic heart failure and its association with clinical outcome

BackgroundAlthough anxiety and depression have been associated with adverse outcomes in chronic heart failure (HF), data on temporal evolution of these symptoms are scarce. We aimed to investigate the association between repeatedly measured depression and anxiety symptoms and clinical outcome in chronic HF patients. MethodsIn this prospective observational study, outpatients with chronic HF were included and followed-up for a maximum of 2.5 years. The hospital anxiety and depression scale (HADS) questionnaire was conducted every six months. The primary endpoint was a composite of HF hospitalization, cardiovascular death, heart transplantation and left ventricular assist device (LVAD) implantation. Cox and joint models were used to investigate the association between the HADS score and the endpoint. ResultsA total of 362 patients filled out a median (25th–75th percentile) of 3 [2–4] questionnaires each. Mean ± SD age was 63 ± 13 years, 72% were men. Anxiety scores remained relatively stable leading up to the endpoint, while depression scores increased. Higher baseline depression scores were significantly associated with the endpoint (hazard ratio [HR] 1.68 and 95% confidence interval [CI] 1.19–2.36 per log(score+1), p = 0.003), while higher baseline anxiety scores did not reach statistical significance (HR [95% CI] 1.34 [0.99–1.83], p = 0.061). When repeatedly measured, both higher anxiety (HR [95% CI] 1.57[1.07–2.30], p = 0.022) and depression (HR [95% CI] 2.04 [1.39–3.06], p < 0.001) scores were significantly associated with the endpoint. ConclusionSerial measurements of depression and anxiety symptoms identify chronic HF patients with increased risk of adverse clinical outcomes. Screening for both disorders should be considered in clinical practice.

Scaling and measurement error sensitivity of scoring rules for distribution forecasts

SummaryThis paper examines the impact of data rescaling and measurement error on scoring rules for distribution forecast. First, I show that all commonly used scoring rules for distribution forecasts are robust to rescaling the data. Second, the forecast ranking based on the continuous ranked probability score is less sensitive to gross measurement error than the ranking based on the log score. The theoretical results are complemented by a simulation study aligned with frequently revised quarterly US gross domestic product (GDP) growth data, a simulation study aligned with financial market volatility, and an empirical application forecasting realized variances of S&amp;P 100 constituents.

Uncovering emotion sequence patterns in different interaction groups using deep learning and sequential pattern mining

AbstractBackgroundInvestigating emotion sequence patterns in the posts of discussion forums in massive open online courses (MOOCs) holds a vital role in shaping online interactions and impacting learning achievement. While the majority of research focuses on the relationship between emotions and interactions in MOOC forum discussions, research on identifying the crucial difference in emotion sequence patterns among different interaction groups remains in its infancy.ObjectivesThis research utilizes deep learning and sequential pattern mining to investigate whether there are differences in emotion sequence patterns across different groups of learners who exhibit various types of interactions in online discussion forums.MethodsData from a comprehensive array of sources, including log files, discussion texts and scores from 498 learners in online discussion forums, were collected for this study. The agglomerative hierarchical algorithm is used to classify learners into groups with different levels of interactions. Additionally, we implement and evaluate multiple deep learning models for detecting different emotions from online discussions. Relevant emotion sequence patterns were identified using sequence pattern analysis and the identified emotion sequence patterns were compared across different groups with different levels of interactions.Results and ConclusionsUsing an agglomerative hierarchical algorithm, we classified learners into three distinct groups characterized by different levels of interactions: high, average and low level. Leveraging the bi‐directional long short‐term memory model for emotion detection yielded the highest predictive performance, with an impressive F‐measure of 94.01%, a recall rate of 93.83% and an accuracy score of 95.01%. The results also revealed that learners in the low‐level interaction group experienced more emotion transition from boredom to frustration than the other two groups. Therefore, the aggregation of students into groups and the utilization of their MOOC log data offer educators the capability to provide adaptive emotional feedback, customize assessments and offer more personalized attention as needed.

Bayesian joint species distribution model selection for community‐level prediction

AbstractAimJoint species distribution models (JSDMs) are an important tool for predicting ecosystem diversity and function under global change. The growing complexity of modern JSDMs necessitates careful model selection tailored to the challenges of community prediction under novel conditions (i.e., transferable models). Common approaches to evaluate the performance of JSDMs for community‐level prediction are based on individual species predictions that do not account for the species correlation structures inherent in JSDMs. Here, we formalize a Bayesian model selection approach that accounts for species correlation structures and apply it to compare the community‐level predictive performance of alternative JSDMs across broad environmental gradients emulating transferable applications.InnovationWe connect the evaluation of JSDM predictions to Bayesian model selection theory under which the log score is the preferred performance measure for probabilistic prediction. We define the joint log score for community‐level prediction and distinguish it from more commonly applied JSDM evaluation metrics. We then apply the joint community log score to evaluate predictions of 1918 out‐of‐sample boreal forest understory communities spanning 39 species generated using a novel multinomial JSDM framework that supports alternative species correlation structures: independent, compositional dependence and residual dependence.Main conclusionsThe best performing JSDM included all observed environmental variables and compositional dependence modelled using a multinomial likelihood. The addition of flexible residual species correlations improved model predictions only within JSDMs applying a reduced set of environmental variables highlighting potential confounding between unobserved environmental conditions and residual species dependence. The best performing JSDM was consistent across successional and bioclimatic gradients regardless of whether interest was in species‐ or community‐level prediction. Our study demonstrates the utility of the joint community log score to compare the predictive performance of JSDMs and highlights the importance of accounting for species dependence when interest is in community composition under novel conditions.

Identification of termites from Gabon using MALDI-TOF MS

Termites are one of the most common pests that damage wood and other cellulosic materials. Although Africa has more varieties of termite species than any other continent, few entomological studies have been conducted in Gabon. Identifying termites poses significant difficulties for entomologists. The aim of this study was to evaluate the reliability and confirm the significance of MALDI-TOF MS in identifying fresh termites collected in equatorial Africa.A total of 108 termites were collected from 13 termite nests during a field mission in 2021 in Lekedi and Bongoville, Gabon. Termites were morphologically identified and subjected to MALDI-TOF MS, then molecular analyses using the COI and 12S rRNA genes.Four termite species were morphologically identified in this study: Pseudacanthotermes militaris, Macrotermes muelleri, Macrotermes nobilis, and Noditermes indoensis. However, when using molecular biology, only three species were identified, namely Macrotermes bellicosus, P. militaris, and N. indoensis, because the specimens initially identified as M. muelleri and M. nobilis were found to be M. bellicosus.The MALDI-TOF MS spectral profiles of the termites were all of good quality, with intra-species reproducibility and inter-species specificity. The spectra of 98 termites were blind tested against our upgraded database, which included the spectra of ten termite specimens. All tested spectra were correctly matched to their respective species, with log score values (LSVs) ranging from 1.649 to 2.592. The mean LSV was 2.215 ± 0.203, and the median was 2.241. However, 95.91% (94/98) of our spectra had LSVs above 1.8. This study demonstrates how a proteomic approach can overcome termites' molecular and morphological identification limitations and serve as a useful taxonomic tool.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry traces the geographical source of Biomphalariapfeifferi and Bulinusforskalii, involved in schistosomiasis transmission

BackgroundFreshwater snails of the genera Bulinus spp., Biomphalaria spp., and Oncomelania spp. are the main intermediate hosts of human and animal schistosomiasis. Identification of these snails has long been based on morphological and/or genomic criteria, which have their limitations. These limitations include a lack of precision for the morphological tool and cost and time for the DNA-based approach. Recently, Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight (MALDI–TOF) mass spectrometry, a new tool used which is routinely in clinical microbiology, has emerged in the field of malacology for the identification of freshwater snails. This study aimed to evaluate the ability of MALDI–TOF MS to identify Biomphalariapfeifferi and Bulinusforskalii snail populations according to their geographical origin.MethodsThis study was conducted on 101 Bi.pfeifferi and 81 Bu.forskalii snails collected in three distinct geographical areas of Senegal (the North-East, South-East and central part of the country), and supplemented with wild and laboratory strains. Specimens which had previously been morphologically described were identified by MALDI–TOF MS [identification log score values (LSV) ≥ 1.7], after an initial blind test using the pre-existing database. After DNA-based identification, new reference spectra of Bi.pfeifferi (n = 10) and Bu.forskalii (n = 5) from the geographical areas were added to the MALDI–TOF spectral database. The final blind test against this updated database was performed to assess identification at the geographic source level.ResultsMALDI–TOF MS correctly identified 92.1% of 101 Bi.pfeifferi snails and 98.8% of 81 Bu.forskalii snails. At the final blind test, 88% of 166 specimens were correctly identified according to both their species and sampling site, with LSVs ranging from 1.74 to 2.70. The geographical source was adequately identified in 90.1% of 91 Bi.pfeifferi and 85.3% of 75 Bu.forskalii samples.ConclusionsOur findings demonstrate that MALDI–TOF MS can identify and differentiate snail populations according to geographical origin. It outperforms the current DNA-based approaches in discriminating laboratory from wild strains. This inexpensive high-throughput approach is likely to further revolutionise epidemiological studies in areas which are endemic for schistosomiasis.

Enterococcus montenegrensis sp. nov., isolated from artisanal Montenegrin dry sausage.

A novel, Gram-positive, facultative anaerobe, coccoid and non-motile bacterium, designated as CoE-012-22T was isolated from dried beef sausage (the original name in Montenegro is Govedji Kulen) manufactured in the municipality of Rozaje (Montenegro) in 2021. Cells of this strain were oxidase- and catalase-negative. Growth occurred at 4-50 °C, at pH 5.0-8.0 and with 0-6.5 % (w/v) NaCl in diverse growth media. MALDI-TOF analysis identified the strain as Enterococcus canintestini (log score 2). Phylogenetic analysis of the 16S rRNA gene and whole genome sequences assigned the strain to the genus Enterococcus. The closest relatives were E. canintestini DSM 21207T and E. dispar ATCC 51266T with 16S rRNA gene sequence pairwise similarities of 99.34 and 98.59 %, respectively. The average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) values between isolate CoE-012-22T and other enterococci species were below the thresholds for species delineation thresholds (95.0 % ANI; 70.0 % dDDH) with maximum identities of 84.13 % (ANIb), 86.43 % (ANIm) and 28.4 % (dDDH) to E. saigonensis JCM 31193T and 70.97 % (ANIb), 88.99 % (ANIm) and 32.4 % (dDDH) to E. malodoratus ATCC 43197T. Two unknown Enterococcus isolates, Enterococcus sp. MJM12 and Enterococcus SMC-9, showed identities of 99.87 and 99.94 % (16S rRNA), 98.57 and 98.65 % (ANIb), 98.93 and 99.02 % (ANIm), and 89.8 and 90.0 % (dDDH) to strain CoE-012-22T and can therefore be regarded as the same species. Based on the characterization results, strain CoE-012-22T was considered to represent a novel species, for which the name Enterococcus montenegrensis sp. nov. is proposed. The type strain is CoE-012-22T (=DSM 115843T=NCIMB 15468T).

Effects of Kinesio Taping and Modified Constraint-Induced Movement Therapy on Upper Extremity Function, Quality of Life, and Spasticity in Individuals Recovering from Stroke

Background: Cerebral palsy is a neurological condition affecting children and adolescents, often resulting in hemiparesis and impaired upper limb functionality. Constraint-Induced Movement Therapy (CIMT) has shown promise in rehabilitation, and Kinesio Taping (KT) is increasingly considered for its potential benefits. This study explores the synergistic impact of CIMT and KT on upper limb function and muscle tone in this population, filling a critical gap in research. Objective: To investigate the combined effects of CIMT and KT on upper limb functionality and spasticity in children and adolescents with hemiparesis. Methods: A comprehensive randomized clinical trial adhering to CONSORT guidelines was conducted. Forty-six participants aged 6 to 17 years, diagnosed with hemiparesis due to cerebral palsy, were divided into two groups: CIMT-only and CIMT + KT. Baseline assessments included age, gender, stroke type, time since stroke, and initial upper limb function (FMA-UE, BBT, SF-36, MAS). CIMT sessions were conducted intensively over four weeks, with the CIMT + KT group additionally receiving KT application. Post-intervention assessments were conducted using the same measures. Results: Both the CIMT and CIMT + KT groups demonstrated significant improvements in the use of the affected limb for daily tasks, as indicated by the Motor Activity Log (MAL) scores. The CIMT-only Group showed a mean change in MAL score of 15.4 ± 8.1, while the CIMT + KT Group exhibited a mean change of 10.2 ± 6.5. Strong performance in upper limb functionality, assessed through the Wolf Motor Function Test (WMFT) Functional Ability Scale (FAS), was observed in both groups. The CIMT-only Group demonstrated a mean change in WMFT FAS score of 12.3 ± 6.2, and the CIMT + KT Group had a mean change of 8.4 ± 5.1. Additionally, both groups experienced a notable reduction in muscle tone, assessed using the Modified Ashworth Scale (MAS). The CIMT-only Group had a mean change in MAS score of -0.6 ± 0.4, while the CIMT + KT Group had a mean change of -0.4 ± 0.5. No statistically significant differences were observed between the two groups regarding the quality and quantity of movement. Conclusion: Integrating Kinesio Taping with Constraint-Induced Movement Therapy effectively reduces muscular tone in the wrist and fingers, enhancing upper limb functionality in children and adolescents with hemiparesis. While Kinesio Taping alone and in combination with CIMT demonstrates efficacy, further research is warranted to optimize therapeutic applications.

IDENTIFICATION OF https://www.uaiasi.ro/revmvis/index_htm_files/ArtHROPODS BY THE MALDI TOF TEHNIQUE

MALDI-TOF mass spectrometry is a relatively new diagnostic technique that has revolutionised clinical microbiology by accurately identifying species of bacteria, filamentous fungi and yeasts. Recently, new applications to identify parasites and https://www.uaiasi.ro/revmvis/index_htm_files/Arthropods of medical interest have been developed, but few have developed MALDI-TOF analysis protocols for characterizing https://www.uaiasi.ro/revmvis/index_htm_files/Arthropod species. Thus, there is a need for a standardization in terms of the anatomical phttps://www.uaiasi.ro/revmvis/index_htm_files/Art(s) to be used according to https://www.uaiasi.ro/revmvis/index_htm_files/Arthropod families (head, thorax, legs) and the steps for protein extraction and homogenization. In this study we created a bank of 47 specimens including the following species: Aedes caspius, Anopheles hyrcanus, Anopheles maculipennis, Coquillettidia richiardii, Culiseta annulata, Culex pipiens. Thus, the aim of this study was to compare the quality of spectra and of results in the identification between different anatomical phttps://www.uaiasi.ro/revmvis/index_htm_files/Arts of mosquitoes, head, thorax (with wings) and legs, in order to optimize the use of the MALDI-TOF spectrometry tool. We evaluated the bank using the "bank versus bank" test (database provided by the laboratory of parasitology and mycology of Paris, Sorbonne University), each specimen had 4 deposits of protein extracts and the identification threshold log(score) was set to 1.7. Identifications were confirmed by morphological identification keys. There were differences in the protein profiles between each anatomical phttps://www.uaiasi.ro/revmvis/index_htm_files/Art. Leg spectra had the lowest number of high intensity peaks compared to those of the head or thorax.

Correlation between kinetic and kinematic measures, clinical tests and subjective self-evaluation questionnaires of the affected upper limb in people after stroke.

Assessment of stroke recovery should include multiple sources of information in order to obtain a complete understanding of the individual's rehabilitation progress. Self-evaluation questionnaires' scores do not always correspond to the scores of commonly used clinical evaluation tools. The purpose of this study was to assess the relationship between self-evaluation questionnaires, clinical tests, and kinematic and kinetic analyses of the affected upper limb after stroke, and to determine the correlation between these measures and self-reported general function 2-4 years after the stroke. Twenty-six subjects recovering from stroke were included in the study. Spearman's correlation coefficient was used to measure the correlation between Stroke Impact Scale (SIS), Motor activity Log (MAL), Fugl-Meyer Assessment (FMA) and Action Reach Arm Test (ARAT) scores, and kinematic and kinetic analyses. A logistic regression was used to assess the extent to which these measures may predict the participants' functional self-reported status 2-4 years post stroke. Sections regarding hand function, hand force and general ADL of the self-evaluation questionnaires correlated with kinematic variables. However, only questionnaires that focus on hand function correlated with clinical tests. Mean and maximal hand velocity had the strongest correlations with self-evaluation questionnaires and with the clinical tests, more than other kinematic variables. Self-evaluation questionnaires and clinical tests were found to be correlated with hand kinetic metrics force-to-time ratio and number of force peaks. SIS hand force domain, mean velocity and maximal velocity predicted self-reported general function 2-4 years after the stroke. Self-evaluation questionnaires should be considered for wider use in the clinical evaluation of a patient's stroke recovery, since they add important information on the individual's functional status, which is not reflected in the clinical tests.

Frequency and Antimicrobial Resistance Patterns of Foodborne Pathogens in Ready-to-Eat Foods: An Evolving Public Health Challenge

Food products that are ready-to-eat have become increasingly popular in recent years due to their efficiency, affordability, and convenience. However, there are concerns about public health because certain products, particularly animal products, may contain antibiotic-resistant bacteria. This study aimed to quickly and accurately identify foodborne pathogens, such as Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus), in samples of shawarma and chicken burgers using peptide mass fingerprinting (PMF) technology. Additionally, the prevalence and levels of antibiotic resistance in the pathogens were determined. The study utilized 300 samples obtained from fast food restaurants in Al Qassim, Saudi Arabia. A variety of methods were used to identify foodborne pathogens, including culture on specific media, bacterial counts by numerical dilutions of homogenized samples, and proteome identification by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). The Kirby–Bauer method was applied to detect the susceptibility and resistance of the bacteria to various antibiotics. PCR was utilized to identify antimicrobial resistance genes such as blaTEM, tet(A), blaZ, and mecA in S. aureus and E. coli isolates. The percentage of E. coli, S. aureus, Salmonella, Listeria monocytogenes (L. monocytogenes), Acinetobacter baumannii (A. baumannii), and Hafnia alevei (H. alevei) was 34%, 31%, 10.67%, 7.33%, 6.67%, and 4%, respectively. Shawarma samples were found to contain the highest levels of pathogens, compared with chicken burger samples. According to the MBT Compass Flex Series Version 1.3 software, all isolates were identified with 100% accuracy. The log score for MBT identification ranged from 2.00 to 2.56. Among E. coli isolates, ampicillin, and penicillin had the highest resistance rate (100%), followed by tetracycline (35.29%). A number of antibiotics were reported to be resistant to S. aureus, including nalidixic acid (100%), followed by penicillin (96.77%), piperacillin (45.16%), and norfloxacin (32.26%). Some E. coli isolates were susceptible to tetracycline (49.02%), nalidixic acid (47.06%), and piperacillin (43.14%), whereas amikacin was the only drug that was effective against 32.72% of S. aureus isolates. The proportions of the blaTEM and tet(A) genes in E. coli isolates were 55.89% and 45.1%, respectively, whereas S. aureus strains did not possess either of these genes. However, 21.5% and 47.31% of blaz and mecA genes were present among various isolates of S. aureus, respectively. In contrast, E. coli strains did not possess either of these genes. In conclusion, the fast identification and antimicrobial profiles of the foodborne pathogens were useful in identifying which restaurants and fast food outlets may need to improve their food safety practices. Ultimately, our results will be used to devise targeted strategies to control foodborne pathogens.

Campylobacter magnus sp. nov., isolated from caecal contents of domestic pigs (Sus scrofa domesticus).

During the 2021 European Food Safety Authority coordinated harmonized monitoring of antimicrobial resistance in Campylobacter species in Slovenia, five Campylobacter-like strains were cultured from caeca of a total of 104 domestic pigs that could not be identified using the standard-prescribed biochemical tests or MALDI-TOF MS. The isolates were obtained using the standard ISO 10272 procedure for the isolation of thermotolerant Campylobacter with prolonged cultivation time. Small Campylobacter-like colonies were observed on mCCDA and CASA agar plates after 2-4 days of incubation; dark-field microscopy revealed relatively big spirilli-shaped bacteria exhibiting characteristic Campylobacter-like motility. The cells were 1.5-3 µm long and 0.5-0.7 µm wide, Gram-negative, oxidase-positive and catalase-positive. MALDI-TOF mass spectra were distinctive and consistent, but with low MALDI-TOF MS log scores and the closest matches being those of Campylobacter hyointestinalis and Campylobacter fetus. All five strains underwent whole-genome sequencing. Analysis of 16S rRNA gene sequences revealed that the isolates were most similar (98.3-98.4 % identity) to Campylobacter lanienae. Pairwise average nucleotide identity (ANI) values revealed that the five studied strains shared pairwise ANI of 96.2-96.5 % but were clearly distinct from the previously described Campylobacter species (ANI ≤72.8 %). The core genome-based phylogeny confirmed that the new strains form a distinct and well-supported clade within the genus Campylobacter. The conducted polyphasic taxonomic analysis confirmed that the five strains represent a novel Campylobacter species for which the name Campylobacter magnus sp. nov. is suggested, with strain 46386T (=DSM 115534T=CCUG 76865T) as the type strain.

Evolution of MALDI-TOF MS Profiles from Lice and Fleas Preserved in Alcohol over Time.

MALDI-TOF is now considered a relevant tool for the identification of arthropods, including lice and fleas. However, the duration and conditions of storage, such as in ethanol, which is frequently used to preserve these ectoparasites, could impede their classification. The purpose of the present study was to assess the stability of MS profiles from Pediculus humanus corporis lice and Ctenocephalides felis fleas preserved in alcohol from one to four years and kinetically submitted to MALDI-TOF MS. A total of 469 cephalothoraxes from lice (n = 170) and fleas (n = 299) were tested. The reproducibility of the MS profiles was estimated based on the log score values (LSVs) obtained for query profiles compared to the reference profiles included in the MS database. Only MS spectra from P. humanus corporis and C. felis stored in alcohol for less than one year were included in the reference MS database. Approximately 75% of MS spectra from lice (75.2%, 94/125) and fleas (74.4%, 122/164) specimens stored in alcohol for 12 to 48 months, queried against the reference MS database, obtained relevant identification. An accurate analysis revealed a significant decrease in the proportion of identification for both species stored for more than 22 months in alcohol. It was hypothesized that incomplete drying was responsible for MS spectra variations. Then, 45 lice and 60 fleas were subjected to longer drying periods from 12 to 24 h. The increase in the drying period improved the proportion of relevant identification for lice (95%) and fleas (80%). This study highlighted that a correct rate of identification by MS could be obtained for lice and fleas preserved in alcohol for up to four years on the condition that the drying period was sufficiently long for accurate identification.

Comparison of combination methods to create calibrated ensemble forecasts for seasonal influenza in the U.S.

The characteristics of influenza seasons vary substantially from year to year, posing challenges for public health preparation and response. Influenza forecasting is used to inform seasonal outbreak response, which can in turn potentially reduce the impact of an epidemic. The United States Centers for Disease Control and Prevention, in collaboration with external researchers, has run an annual prospective influenza forecasting exercise, known as the FluSight challenge. Uniting theoretical results from the forecasting literature with domain-specific forecasts from influenza outbreaks, we applied parametric forecast combination methods that simultaneously optimize model weights and calibrate the ensemble via a beta transformation and made adjustments to the methods to reduce their complexity. We used the beta-transformed linear pool, the finite beta mixture model, and their equal weight adaptations to produce ensemble forecasts retrospectively for the 2016/2017, 2017/2018, and 2018/2019 influenza seasons in the U.S. We compared their performance to methods that were used in the FluSight challenge to produce the FluSight Network ensemble, namely the equally weighted linear pool and the linear pool. Ensemble forecasts produced from methods with a beta transformation were shown to outperform those from the equally weighted linear pool and the linear pool for all week-ahead targets across in the test seasons based on average log scores. We observed improvements in overall accuracy despite the beta-transformed linear pool or beta mixture methods' modest under-prediction across all targets and seasons. Combination techniques that explicitly adjust for known calibration issues in linear pooling should be considered to improve probabilistic scores in outbreak settings.

Spectrometric Characterization of Clinical and Environmental Isolates of Aspergillus Series Versicolores.

Aspergillus series Versicolores are molds distributed among 17 species, commonly found in our environment, and responsible for infections. Since 2022, a new taxonomy has grouped them into 4 major lineages: A. versicolor, A. subversicolor, A. sydowii, and A. creber. Matrix-Assisted Laser Desorption/Ionization Time-Of-Flight Mass Spectrometry (MALDI-TOF MS) could be a faster and more cost-effective alternative to molecular techniques for identifying them by developing a local database. To evaluate this technique, 30 isolates from Aspergillus series Versicolores were used. A total of 59 main spectra profiles (MSPs) were created in the local database. This protocol enabled accurate identification of 100% of the extracted isolates, of which 97% (29/30) were correctly identified with a log score ≥ 2.00. Some MSPs recorded as Aspergillus versicolor in the supplier's database could lead to false identifications as they did not match with the correct lineages. Although the local database is still limited in the number and diversity of species of Aspergillus series Versicolores, it is sufficiently effective for correct lineage identification according to the latest taxonomic revision, and better than the MALDI-TOF MS supplier's database. This technology could improve the speed and accuracy of routine fungal identification for these species.

Survey of bed bug infestations in homeless shelters in southern France

Bed bug has become a major public health pest worldwide. Infestation may result in numerous negative health effects. Homeless shelters are one of the most habitats that can be infested with bed bugs, a few studies have focused on bed bug infestations in these settings. We conducted a survey of infestations of bed bugs in a homeless shelter in southern France, using an innovative seven-level scale (0–6) to assess the degree of infestation, MALDI TOF-MS to identify bed bugs, and a biomolecular tool to detect bacteria. Bed bug infestations were documented in 13% (9/68) of investigated rooms. A total of 184 bed bugs were collected and morphologically identified as Cimex lectularius. MALDI TOF–MS analysis allowed us to obtain high-quality MS spectra for all 184 specimens, to correctly identify all specimens, and included 178/184 (97%) Log Score Values higher than 1.8. Among the bacteria tested, Wolbachia sp. DNA was found in 149/184 (81%) of the bed bugs, and one sample was positive for Coxiella burnetii, the agent of Q fever. Our study is the first of its kind that offers new perspectives for increasing public awareness of the conditions in homeless shelters.

Predicting the dengue cluster outbreak dynamics in Yogyakarta, Indonesia: a modelling study.

Human mobility and climate conditions are recognised key drivers of dengue transmission, but their combined and individual role in the local spatiotemporal clustering of dengue cases is not well understood. This study investigated the effects of human mobility and weather conditions on dengue risk in an urban area in Yogyakarta, Indonesia. We established a Bayesian spatiotemporal model for neighbourhood outbreak prediction and evaluated the performances of two different approaches for constructing an adjacency matrix: one based on geographical proximity and the other based on human mobility patterns. We used population, weather conditions, and past dengue cases as predictors using a flexible distributed lag approach. The human mobility data were estimated based on proxies from social media. Unseen data from February 2017 to January 2020 were used to estimate the one-month ahead prediction accuracy of the model. When human mobility proxies were included in the spatial covariance structure, the model fit improved in terms of the log score (from 1.748 to 1.561) and the mean absolute error (from 0.676 to 0.522) based on the validation data. Additionally, showed only few observations outside the credible interval of predictions (1.48%) and weather conditions were not found to contribute additionally to the clustering of cases at this scale. The study shows that it is possible to make highly accurate predictions of the within-city cluster dynamics of dengue using mobility proxies from social media combined with disease surveillance data. These insights are important for proactive and timely outbreak management of dengue. Swedish Research Council Formas, Umeå Centre for Global Health Research, Swedish Council for Working Life and Social Research, Swedish research council VINNOVA and Alexander von Humboldt Foundation (Germany).

Improved MALDI-TOF MS Identification of Mycobacterium tuberculosis by Use of an Enhanced Cell Disruption Protocol.

Mycobacterium tuberculosis is the microorganism that causes tuberculosis, a disease affecting millions of people worldwide. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a fast, reliable, and cost-effective method for microorganism identification which has been used for the identification of Mycobacterium spp. isolates. However, the mycobacteria cell wall is rich in lipids, which makes it difficult to obtain proteins for MALDI-TOF MS analysis. In this study, two cell preparation protocols were compared: the MycoEx, recommended by MALDI-TOF instrument manufacturer Bruker Daltonics, and the MycoLyser protocol described herein, which used the MagNA Lyser instrument to enhance cell disruption with ethanol. Cell disruption and protein extraction steps with the two protocols were performed using the Mycobacterium tuberculosis H37Rv strain, and the MALDI-TOF MS results were compared. The MycoLyser protocol allowed for improved Biotyper identification of M. tuberculosis since the log(score) values obtained with this protocol were mostly ≥ 1.800 and significantly higher than that underwent MycoEx processing. The identification reliability was increased as well, considering the Bruker criteria. In view of these results, it is concluded that the MycoLyser protocol for mycobacterial cell disruption and protein extraction improves the MALDI-TOF MS method's efficacy for M. tuberculosis identification.