Relative quantification of the recA gene for antimicrobial susceptibility testing in response to ciprofloxacin for pathogens of concern

Antimicrobial resistance (AR) is one of the greatest threats to global health and is associated with higher treatment costs, longer hospital stays, and increased mortality. Current gold standard antimicrobial susceptibility tests (AST) rely on organism growth rates that result in prolonged time-to-answer for slow growing organisms. Changes in the cellular transcriptome can be rapid in the presence of stressors such as antibiotic pressure, providing the opportunity to develop AST towards transcriptomic signatures. Here, we show that relative quantification of the recA gene is an indicator of pathogen susceptibly when select species are challenged with relevant concentrations of ciprofloxacin. We demonstrate that ciprofloxacin susceptible strains of Y. pestis and B. anthracis have significant increases in relative recA gene expression after 15 min of exposure while resistant strains show no significant differences. Building upon this data, we designed and optimized seven duplex RT-qPCR assays targeting the recA and 16S rRNA gene, response and housekeeping genes, respectively, for multiple biothreat and ESKAPE pathogens. Final evaluation of all seven duplex assays tested against 124 ciprofloxacin susceptible and resistant strains, including Tier 1 pathogens, demonstrated an overall categorical agreement compared to microbroth dilution of 97% using a defined cutoff. Testing pathogen strains commonly associated with urinary tract infections in contrived mock sample sets demonstrated an overall categorical agreement of 96%. These data indicate relative quantification of a single highly conserved gene accurately determines susceptibility for multiple bacterial species in response to ciprofloxacin.

Disseminated Aspergillus citrinoterreus and concurrent localized dermal phaeohyphomycosis in an immunosuppressed dog

Key Clinical message

We report on a dog with immune-mediated hemolytic anemia (IMHA) treated with immunomodulatory therapy that developed phaeohyphomycosis and Aspergillus citrinoterreus infections. This is the first reported case of A. citrinoterreus in dogs. It details cytological and microbiological findings leading to diagnosis and highlights the importance of investigating new lesions in immunocompromised patients.

Abstract

A 5-year-old Staffordshire terrier mix treated with immunosuppressive therapy for IMHA was diagnosed with concurrent disseminated A. citrinoterreus and localized Curvularia lunata infections. This case highlights the potential development of multiple concurrent opportunistic fungal infections and is the first reported case of A. citrinoterreus infection in a dog.

Prevalence of persistent SARS-CoV-2 in a large community surveillance study

Persistent SARS-CoV-2 infections may act as viral reservoirs that could seed future outbreaks1-5, give rise to highly divergent lineages6-8 and contribute to cases with post-acute COVID-19 sequelae (long COVID)9,10. However, the population prevalence of persistent infections, their viral load kinetics and evolutionary dynamics over the course of infections remain largely unknown. Here, using viral sequence data collected as part of a national infection survey, we identified 381 individuals with SARS-CoV-2 RNA at high titre persisting for at least 30 days, of which 54 had viral RNA persisting at least 60 days. We refer to these as 'persistent infections' as available evidence suggests that they represent ongoing viral replication, although the persistence of non-replicating RNA cannot be ruled out in all. Individuals with persistent infection had more than 50% higher odds of self-reporting long COVID than individuals with non-persistent infection. We estimate that 0.1-0.5% of infections may become persistent with typically rebounding high viral loads and last for at least 60 days. In some individuals, we identified many viral amino acid substitutions, indicating periods of strong positive selection, whereas others had no consensus change in the sequences for prolonged periods, consistent with weak selection. Substitutions included mutations that are lineage defining for SARS-CoV-2 variants, at target sites for monoclonal antibodies and/or are commonly found in immunocompromised people11-14. This work has profound implications for understanding and characterizing SARS-CoV-2 infection, epidemiology and evolution.

SARS-CoV-2 Pandemic: A Comparison Between the Epidemiological Situation in Greece and Romania

Introduction Since the onset of the SARS-CoV-2 pandemic, there seems to be scarce data targeting the comparison of epidemiological data among different countries. In an attempt to reveal and characterize the epidemiological profile in the Balkan peninsula, a cross-sectional study has been conducted, aiming to retrospectively collect all the existing information regarding the SARS-CoV-2 pandemic over a period of three years, starting from March 2020 until March 2023. The comparative analysis of the epidemiological features and the main indicators between Romania and Greece can generate a good overview of the factors that can influence public health and create an adequate system of measures to limit the COVID-19 pandemic in the area. A retrospective comparative study aiming to detect and associate the main indicators determining the evolution of the SARS-CoV-2 pandemic data with the control measures adopted in Romania and Greece was performed. Methods Publicly available data were obtained from official sources such as the World Health Organization, the European Centre for Disease Control, the Romanian and Greek Ministries of Health, and the Romanian National Centre for Surveillance and Control of Communicable Diseases. The reported number of cases, in total and in conjunction with the age distribution, total number of deaths, and vaccination coverage, from the onset of the pandemic in March 2020 until March 2023, were collected. All officially reported cases of COVID-19 were included in this analysis. Reports with missing or incomplete values regarding the timeframe, age distribution, and vaccination status were excluded. Results During the timeframe of the study, from March 2020 until March 2023, Greece reported a higher number of confirmed SARS-CoV-2 cases as compared to Romania (5,910,103 cases and 3,352,356 cases, respectively). Still, in terms of the overall death toll, Romania recorded a higher mortality rate than Greece during the pandemic (67.773 deaths vs. 36.372 deaths). Concerning both cumulative incidence rates and the 14-day case notification rate per 100.000 inhabitants, it is evident that Romania exhibited greater numbers throughout the course of the pandemic. Although it is not clearly stated, the compulsory vaccination of elderly people that was set as a high priority in Greece may have contributed to the above results. In terms of the 14-day death notification rate per 100.000 inhabitants in 2020 and 2021, Romania showed a higher rate than Greece, while Greece reported a greater rate in 2022 and up until March 2023. Between 2020 and 2023, Greece presented both a higher number of vaccinated individuals and a higher vaccination coverage with two doses (7,034,695 individuals, 70% of the general population), as compared to Romania (6,467,804 individuals, 33.68% of the general population, p<0.0001). Conclusions Despite the similar restrictions and preventive actions adopted by Romania and Greece, some of the epidemiological data between the two countries tends to differ. It must not be ignored that every nation should be considered a unique entity with distinct features, including individuals, customs, and policies, rather than being categorized with other countries based on geographic proximity or regionalization.

High-speed centrifugation rather than Lipoclear reagent can be used for removing the interference of lipemia on serological tests of infectious diseases: AIDS, hepatitis B, hepatitis C, and syphilis by chemiluminescent microparticle immunoassay

The aim of this study was to investigate the interference of lipemia on measurement of HBsAg, anti-HBs, HBeAg, anti-HBe, anti-HBc, anti-HCV, HIV Ag/Ab, and anti-TP in serum by chemiluminescent microparticle immunoassay (CMIA) and compare lipemia removing performance between high-speed centrifugation and Lipoclear reagent. Mixed native serum samples (NSs) and hyperlipemia serum samples (HLS) were prepared for the investigated parameters. The levels of these parameters in NS and HLS were determined by CMIA on an Abbott ARCHITECT i2000SR immunoassay analyzer. HBsAg, anti-HBs, and anti-TP were affected with relative bias >12.5% (acceptable limit) when the level of triacylglycerol (TG) was higher than 27.12 mmol/L in HLS. Clinically unacceptable bias were observed for HBeAg and anti-HBe in HLS with TG higher than 40.52 mmol/L. However, anti-HCV and HIV Ag/Ab were not interfered in severe lipemia with TG < 52.03 mmol/L. In addition, the Lipoclear reagent did not reduce the interference of lipemia with relative bias from -62.50% to -18.02%. The high-speed centrifugation under the optimized condition of 12 000g for 10 min successfully removed the interference of lipemia with relative bias from -5.93% to 0% for HBsAg, anti-HBs, HBeAg, anti-HBe, anti-HBc, and anti-TP. To conclude, high-speed centrifugation can be used for removing the interference of lipemia to measure HBsAg, anti-HBs, HBeAg, anti-HBe, anti-HBc, and anti-TP. Accordingly, a standardized sample preanalytical preparation of the patients and other screening participants as well as a specimen examination procedure for removing lipemia interference on the serological tests was recommended.

Investigating and Summarizing Information Resources Related to the Clinical Presentation and Diagnosis of Cutaneous Manifestations of Infectious Diseases in Patients With Skin of Color

Patients with skin of color (SOC) present diseases differently in many circumstances, yet there is a lack of information regarding the presentation and diagnosis of cutaneous manifestations in such patients experiencing infectious diseases. Therefore, we conducted a scoping review to investigate and summarize information pertaining to the clinical presentation and diagnosis of cutaneous manifestations of infectious diseases in patients with SOC focusing on the following viral, bacterial, toxin-mediated, and infestation diseases and fungal infections: human immunodeficiency virus, shingles, impetigo, scarlet fever, Lyme disease, toxic shock syndrome, scabies, rickettsioses, and cutaneous fungal infections. This scoping review identified literature gaps regarding cutaneous manifestations of infectious diseases in patients with SOC such as a lack of visual examples and more precise descriptions of common infectious diseases. The lack of better-quality literature and educational resources describing cutaneous manifestations of infectious diseases in patients with SOC may contribute to care barriers; therefore, more research and collaboration are needed in the specialties of both infectious diseases and dermatology.

A Case of Notifiable Alithiatic Cholecystitis

Acute alithiatic cholecystitis is an inflammation of the gallbladder without evidence of gallstones, often due to infection. It can occur at any age, and it is predominant in males. Listeriosis is a rare bacterial infection caused by Listeria monocytogenes (LM) through the ingestion of contaminated food such as dairy, legumes, and raw meats. Clinical presentations of listeriosis include bacteremia, meningitis, and gastroenteritis. Acute cholecystitis caused by listeria is even more uncommon, with only 23 cases reported in the literature. We present a case of a 65-year-old male, admitted to the Emergency Department with fever and altered state of consciousness which revealed bacteremia due to cholecystitis to LM. The patient was submitted to laparoscopic cholecystectomy and appropriate antibiotic coverage and was discharged seven days later. Early recognition and treatment of this disease are crucial for reducing morbidity and mortality.

The History of Controlling and Treating Infectious Diseases in Ancient China

Infectious diseases are the common enemies of mankind. In the course of historical development, they persistently threaten human health and safety. Even today, despite the developments in medical science, we cannot escape the fear and suffering caused by infectious diseases. Whether in ancient or modern times, the source of infection, route of transmission, and a susceptible population are the three key conditions for the prevalence and spread of infectious diseases. All factors closely related to these three conditions can affect the prevalence of infectious diseases. China is one of the cradles of world civilization. The ancient people accumulated a great deal of experience and lessons in the long struggle against infectious diseases. In the face of the current threat posed by widespread infectious disease, it is imperative to review and summarize ancient Chinese ideas and health policies on epidemic prevention and control to inspire contemporary efforts in the prevention and control of infectious disease. The combination of prevention-oriented epidemic prevention ideology and traditional medicine provides valuable insights, especially for impoverished and medically underserved regions.

The unequal effects of the health-economy trade-off during the COVID-19 pandemic

Despite the global impact of the coronavirus disease 2019 pandemic, the question of whether mandated interventions have similar economic and public health effects as spontaneous behavioural change remains unresolved. Addressing this question, and understanding differential effects across socioeconomic groups, requires building quantitative and fine-grained mechanistic models. Here we introduce a data-driven, granular, agent-based model that simulates epidemic and economic outcomes across industries, occupations and income levels. We validate the model by reproducing key outcomes of the first wave of coronavirus disease 2019 in the New York metropolitan area. The key mechanism coupling the epidemic and economic modules is the reduction in consumption due to fear of infection. In counterfactual experiments, we show that a similar trade-off between epidemic and economic outcomes exists both when individuals change their behaviour due to fear of infection and when non-pharmaceutical interventions are imposed. Low-income workers, who perform in-person occupations in customer-facing industries, face the strongest trade-off.

Paying for Parenthood: Understanding Parental Leave Policies in Infectious Disease Fellowship

Background

Many physician trainees plan pregnancy during residency and fellowship. A study of internal medicine program directors (PDs) demonstrated frequent misinterpretation of American Board of Internal Medicine (ABIM) leave policies applied to parental leave. The primary aim was to investigate how infectious disease (ID) PDs interpret current ABIM leave policies.

Methods

We surveyed 155 ID PDs in an online anonymous questionnaire about knowledge of ABIM leave policies and application toward trainee leaves.

Results

Of 155 PDs, 56 (36%) responded to the survey. Nearly 70% incorrectly identified leave limits permitted. A majority mistakenly chose to extend training when a competent fellow was within the allowed duration of leave. PDs reported that the majority of ID trainee maternity/birth parent leaves (60%) were ≤7 weeks and only 7% were ≥12 weeks; 50% of paternity/nonbirth parent leaves were ≤3 weeks.

Conclusions

Surveyed ID fellowship PDs often misinterpret ABIM leave policies and apply policies incorrectly when given sample scenarios..

Task redistribution from general practitioners to nurses in acute infection care: A prospective cohort study

AIM

To examine the impact of implementing nurse-led consultations compared to physician-led consultations on the frequency of follow-up contacts within 14 days following an acute infectious consultation.

DESIGN

Monocentric, prospective cohort study.

METHODS

The study was conducted in a multidisciplinary, capitation-based general practice in Belgium. Through analysis of patient files, the number of follow-up contacts within 14 days after an infection consultation was investigated to determine any difference between physician-led or nurse-led consultations. Secondary outcomes included pharmacological interventions and the prescribing behaviour of medical leave certificates.

RESULTS

A total of 352 consultations were analysed, of which 174 conducted by physicians and 178 by nurses. No significant difference was found in the number of follow-up contacts. However, the probability of a pharmacological intervention by a physician was revealed to be significantly higher. The presence or absence of such pharmacological intervention did not significantly influence the number of follow-up contacts.

CONCLUSION

This study demonstrates that nurses can be safely and efficiently utilized in acute infection care within a general practice setting. Although these results are promising, more extensive research is needed which incorporates the experiences of patients and healthcare providers. Furthermore, it is advisable to consider the experience and education of the nurses and incorporate them into the analyses.

IMPACT

This study addressed the high workload on general practitioners by researching a task shift in the acute infectious, primary health care. The results demonstrate the feasibility of this task shift, which may have an impact on primary health care professionals (whose workload may be reorganized), as well as on patients for whom primary care may become more accessible.

PATIENT OR PUBLIC CONTRIBUTION

This study includes direct patient data from people who presented themselves with acute infectious complaints in a primary healthcare practice.

Analysis of related factors of plasma antibody levels in patients with severe and critical COVID-19

Coronavirus disease 2019 (COVID-19) continues to impact global public health. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become less virulent as it mutates, prompting China to ease restrictions at the end of 2022. With the complete reopening, a surge in COVID-19 cases has ensued. Therefore, we conducted a study to explore the correlation between plasma antibody levels and baseline conditions or clinical outcomes in severe and critical patients. We collected the basic information of 79 included patients. Enzyme-linked immunosorbent assay (ELISA) tests were performed on plasma samples. The receptor-binding domain (RBD) IgG antibody level of the mild group was significantly higher than that of the severe/critical group (P = 0.00049). And in the severe/critical group, there existed an association between plasma antibody levels and age (P < 0.001, r = - 0.471), as well as plasma antibody levels and vaccination status (P = 0.00147, eta2 = 0.211). Besides, the level of plasma antibody seemed to be moderately correlated with the age, indicating the need for heightened attention to infections in the elderly. And plasma antibody levels were strongly associated with vaccination status in the severe/critical patients.

Maternal pertussis immunization and the blunting of routine vaccine effectiveness: a meta-analysis and modeling study

A key goal of pertussis control is to protect infants too young to be vaccinated, the age group most vulnerable to this highly contagious respiratory infection. In the last decade, maternal immunization has been deployed in many countries, successfully reducing pertussis in this age group. Because of immunological blunting, however, this strategy may erode the effectiveness of primary vaccination at later ages. Here, we systematically reviewed the literature on the relative risk (RR) of pertussis after primary immunization of infants born to vaccinated vs. unvaccinated mothers. The four studies identified had ≤6 years of follow-up and large statistical uncertainty (meta-analysis weighted mean RR: 0.71, 95% CI: 0.38-1.32). To interpret this evidence, we designed a new mathematical model with explicit blunting mechanisms and evaluated maternal immunization's short- and long-term impact on pertussis transmission dynamics. We show that transient dynamics can mask blunting for at least a decade after rolling out maternal immunization. Hence, the current epidemiological evidence may be insufficient to rule out modest reductions in the effectiveness of primary vaccination. Irrespective of this potential collateral cost, we predict that maternal immunization will remain effective at protecting unvaccinated newborns, supporting current public health recommendations.

The host mannose-6-phosphate pathway and viral infection

Viruses, despite their simple structural composition, engage in intricate and complex interactions with their hosts due to their parasitic nature. A notable demonstration of viral behavior lies in their exploitation of lysosomes, specialized organelles responsible for the breakdown of biomolecules and clearance of foreign substances, to bolster their own replication. The man-nose-6-phosphate (M6P) pathway, crucial for facilitating the proper transport of hydrolases into lysosomes and promoting lysosome maturation, is frequently exploited for viral manipulation in support of replication. Recently, the discovery of lysosomal enzyme trafficking factor (LYSET) as a pivotal regulator within the lysosomal M6P pathway has introduced a fresh perspective on the intricate interplay between viral entry and host factors. This groundbreaking revelation illuminates unexplored dimensions of these interactions. In this review, we endeavor to provide a thorough overview of the M6P pathway and its intricate interplay with viral factors during infection. By consolidating the current understanding in this field, our objective is to establish a valuable reference for the development of antiviral drugs that selectively target the M6P pathway.

Temporal dynamics of the early immune response following Mycobacterium bovis infection of cattle

Bovine tuberculosis is an infectious disease of global significance that remains endemic in many countries. Mycobacterium bovis infection in cattle is characterized by a cell-mediated immune response (CMI) that precedes humoral responses, however the timing and trajectories of CMI and antibody responses determined by newer generation assays remain undefined. Here we used defined-antigen interferon-gamma release assays (IGRA) and an eleven-antigen multiplex ELISA (Enferplex TB test) alongside traditional tuberculin-based IGRA and IDEXX M. bovis antibody tests to assess immune trajectories following experimental M. bovis infection of cattle. The results show CMI responses developed as early as two-weeks post-infection, with all infected cattle testing positive three weeks post-infection. Interestingly, 6 of 8 infected animals were serologically positive with the Enferplex TB assay as early as 4 weeks post-infection. As expected, application of the tuberculin skin test enhanced subsequent serological reactivity. Infrequent M. bovis faecal shedding was observed but was uncorrelated with observed immune trajectories. Together, the results show that early antibody responses to M. bovis infection are detectable in some individuals and highlight an urgent need to identify biomarkers that better predict infection outcomes, particularly for application in low-and-middle income countries where test-and-slaughter based control methods are largely unfeasible.

Assessing the feasibility of applying machine learning to diagnosing non-effusive feline infectious peritonitis

Feline infectious peritonitis (FIP) is a severe feline coronavirus-associated syndrome in cats, which is invariably fatal without anti-viral treatment. In the majority of non-effusive FIP cases encountered in practice, confirmatory diagnostic testing is not undertaken and reliance is given to the interpretation of valuable, but essentially non-specific, clinical signs and laboratory markers. We hypothesised that it may be feasible to develop a machine learning (ML) approach which may be applied to the analysis of clinical data to aid in the diagnosis of disease. A dataset encompassing 1939 suspected FIP cases was scored for clinical suspicion of FIP on the basis of history, signalment, clinical signs and laboratory results, using published guidelines, comprising 683 FIP (35.2%), and 1256 non-FIP (64.8%) cases. This dataset was used to train, validate and evaluate two diagnostic machine learning ensemble models. These models, which analysed signalment and laboratory data alone, allowed the accurate discrimination of FIP and non-FIP cases in line with expert opinion. To evaluate whether these models may have value as a diagnostic tool, they were applied to a collection of 80 cases for which the FIP status had been confirmed (FIP: n = 58 (72.5%), non-FIP: n = 22 (27.5%)). Both ensemble models detected FIP with an accuracy of 97.5%, an area under the curve (AUC) of 0.969, sensitivity of 95.45% and specificity of 98.28%. This work demonstrates that, in principle, ML can be usefully applied to the diagnosis of non-effusive FIP. Further work is required before ML may be deployed in the laboratory as a diagnostic tool, such as training models on datasets of confirmed cases and accounting for inter-laboratory variation. Nevertheless, these results illustrate the potential benefit of applying ML to standardising and accelerating the interpretation of clinical pathology data, thereby improving the diagnostic utility of existing laboratory tests.

Nanopore sequencing of infectious fluid is a promising supplement for gold-standard culture in real-world clinical scenario

Introduction

Infectious diseases are major causes of morbidity and mortality worldwide, necessitating the rapid identification and accurate diagnosis of pathogens. While unbiased metagenomic next-generation sequencing (mNGS) has been extensively utilized in clinical pathogen identification and scientific microbiome detection, there is limited research about the application of nanopore platform-based mNGS in the diagnostic performance of various infectious fluid samples.

Methods

In this study, we collected 297 suspected infectious fluids from 10 clinical centers and detected them with conventional microbiology culture and nanopore platform-based mNGS. The objective was to assess detective and diagnostic performance of nanopore-sequencing technology (NST) in real-world scenarios.

Results

Combined with gold-standard culture and clinical adjudication, nanopore sequencing demonstrated nearly 100% positive predictive agreements in microbial-colonized sites, such as the respiratory and urinary tracts. For samples collected from initially sterile body sites, the detected microorganisms were highly suspected pathogens, and the negative predictive agreements were relatively higher than those in the microbial-colonized sites, particularly with 100% in abscess and 95.7% in cerebrospinal fluid. Furthermore, consistent performance was also observed in the identification of antimicrobial resistance genes and drug susceptibility testing of pathogenic strains of Escherichia coli, Staphylococcus aureus, and Acinetobacter baumannii.

Discussion

Rapid NST is a promising clinical tool to supplement gold-standard culture, and it has the potential improve patient prognosis and facilitate clinical treatment of infectious diseases.

First archaeological evidence for ginger consumption as a potential medicinal ingredient in a late medieval leprosarium at St Leonard, Peterborough, England

Leprosy was one of the most outwardly visible diseases in the European Middle Ages, a period during which leprosaria were founded to provide space for the sick. The extant documentary evidence for leprosy hospitals, especially in relation to diet, therapeutic, and medical care, is limited. However, human dental calculus stands to be an important source of information as it provides insight into the substances people were exposed to and accumulated in their bodies during their lives. In the present study, microremains and DNA were analysed from the calculus of individuals buried in the late medieval cemetery of St Leonard, a leprosarium located in Peterborough, England. The results show the presence of ginger (Zingiber officinale), a culinary and medicinal ingredient, as well as evidence of consumption of cereals and legumes. This research suggests that affected individuals consumed ingredients mentioned in medieval medical textbooks that were used to treat regions of the body typically impacted by leprosy. To the authors' knowledge, this is the first study which has identified Zingiber officinale in human dental calculus in England or on the wider European continent.

CAR Immunotherapy for the treatment of infectious diseases: a systematic review

Immunotherapy treatments aim to modulate the host's immune response to either mitigate it in inflammatory/autoimmune disease or enhance it against infection or cancer. Among different immunotherapies reaching clinical application during the last years, chimeric antigen receptor (CAR) immunotherapy has emerged as an effective treatment for cancer where different CAR T cells have already been approved. Yet their use against infectious diseases is an area still relatively poorly explored, albeit with tremendous potential for research and clinical application. Infectious diseases represent a global health challenge, with the escalating threat of antimicrobial resistance underscoring the need for alternative therapeutic approaches. This review aims to systematically evaluate the current applications of CAR immunotherapy in infectious diseases and discuss its potential for future applications. Notably, CAR cell therapies, initially developed for cancer treatment, are gaining recognition as potential remedies for infectious diseases. The review sheds light on significant progress in CAR T cell therapy directed at viral and opportunistic fungal infections.

Vaccination against emerging and reemerging infectious diseases in places of detention: a global multistage scoping review

Background

Despite the elevated risks of infection transmission, people in prisons frequently encounter significant barriers in accessing essential healthcare services in many countries. The present scoping review aimed to evaluate the state of availability and model of delivery of vaccination services within correctional facilities across the globe.

Methods

Following the methodological framework for scoping reviews and adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) extension for scoping reviews criteria, we conducted a systematic search across four peer-reviewed literature databases (Medline via PubMed, Web of Science, the Cochrane Library, Science Direct, and EBSCO), as well as 14 sources of grey literature. Two researchers meticulously examined the identified papers independently to extract pertinent data published between 2012 and 2022. The quality of the selected publications was assessed using established quality assessment tools.

Results

Of the 11,281 identified papers 52 met the inclusion criteria. With the exception of one, all the included publications presented data from high-income countries, predominantly originating from the United States. Across the world, the most prevalent vaccines available in prison settings were COVID-19 and HBV vaccines, typically distributed in response to health crises such as pandemics, epidemics, and local outbreaks. Vaccine coverage and uptake rates within correctional facilities displayed noteworthy disparities among various countries and regions. Besides, individual and organizational barriers and facilitating factors of vaccination in prison settings emerged and discussed in the text.

Discussion

The lack of vaccination services combined with low rates of vaccination coverage and uptake among people living and working in correctional facilities represents a cause for concern. Prisons are not isolated from the broader community, therefore, efforts to increase vaccine uptake among people who live and work in prisons will yield broader public health benefits.

Post-Exposure Prophylaxis for Varicella-Zoster Virus Exposure in High-Risk Children

BACKGROUND

Post-exposure prophylaxis (PEP) with varicella immunoglobulin is recommended to minimize risk of varicella complications for high-risk children. However, providers frequently use alternatives like acyclovir or intravenous immunoglobulin.

METHODS

A retrospective cohort study was conducted of PEP for varicella in children from January 2009 to December 2019. Data were provided by 47 children's hospitals who participate in the Pediatric Health Information Systems database. Patients with clinical encounters for varicella exposure were reviewed. Choice of varicella PEP regimens, including differences by underlying condition and institution, and incidence of varicella disease were determined.

RESULTS

A total of 1704 patients with first clinical encounters for varicella met inclusion criteria. Of these patients, 509 (29.9%) were prescribed PEP after varicella exposure, and 65 (3.8%) ultimately had a subsequent encounter for varicella disease. Of 509 patients who received PEP, acyclovir was most frequently prescribed (n = 195, 38.3%), followed by varicella immunoglobulin (n = 146, 28.7%), IVIG (n = 115, 22.6%), and combination therapy (n = 53, 10.4%). The highest proportion of varicella immunoglobulin use (10/20, 50%) was amongst children with diagnoses of rheumatological/gastrointestinal conditions. The highest proportion of acyclovir use (29/684, 4.2%) was amongst children with diagnoses of oncology/stem cell transplant conditions. The proportion of patients who subsequently had clinical encounters for varicella disease was highest for Acyclovir (30/195, 15.4%) followed by varicella immunoglobulin (5/146, 3.4%), combination therapy (2/53, 3.8%), and intravenous immunoglobulin alone (0/115) (P < .0001).

CONCLUSIONS

Varicella PEP in high-risk children was highly varied among children's hospitals. In our dataset, use of acyclovir was associated with a higher rate of subsequent encounters for Varicella disease.

Phase II prefusion non-stabilised Covid-19 mRNA vaccine randomised study

ChulaCov19 mRNA vaccine demonstrated promising phase 1 results. Healthy adults aged 18-59 years were double-blind randomised 4:1 to receive two intramuscular doses of ChulaCov19 50 µg or placebo. Primary endpoints were safety and microneutralization antibody against-wild-type (Micro-VNT50) at day 50. One hundred fifty adults with median (IQR) age 37 (30-46) years were randomised. ChulaCov19 was well tolerated, and most adverse events were mild to moderate and temporary. Geometric mean titres (GMT) of neutralizing titre against wild-type for ChulaCov19 on day 50 were 1367 IU/mL. T-cell IFN-γ-ELISpot showed the highest responses at one week (Day29) after dose 2 then gradually declined. ChulaCov19 50 µg is well tolerated and elicited high neutralizing antibodies and strong T-cell responses in healthy adults.Trial registration number: ClinicalTrials.gov Identifier NCT04566276, 28/09/2020.

Impact of pre-existing mental health diagnoses on development of post-COVID and related symptoms: a claims data-based cohort study

This study aimed to examine the association of prior mental health diagnoses with the onset of Post-COVID-19 condition (PCC). We conducted a retrospective comparative cohort study and secondary analysis of routinely collected claims data from participants in statutory health insurance in Bavaria, Germany, from January 2015 to June 2022. Study participants were 619,560 patients with confirmed COVID-19, 42,969 with other respiratory tract infection (ORI), and 438,023 controls. Using diagnoses coded according to the German modification of the ICD-10, the associations between prior mental health diagnoses and a PCC diagnosis (primary outcome) or associated symptoms (secondary outcomes) were estimated using multiple Cox proportional hazards regression models. Mental disorders (hazard ratio [HR] 1.36, 95% confidence interval [CI] 1.30-1.42), anxiety (HR 1.14, 95% CI 1.07-1.20), depression (HR 1.25, 95% CI 1.19-1.30) and somatoform disorders (HR 1.30, 95% CI 1.24-1.36) were associated with higher risks for PCC. Mental disorders were associated with the same or even greater risk for a diagnosis of malaise and fatigue in the control cohort (HR 1.71, 95% CI 1.52-1.93) and ORI cohort (HR 1.43, 95% CI 1.20-1.72), than in the COVID-19 cohort (HR 1.43, 95% CI 1.35-1.51). In summary, prior mental comorbidity was associated with an increased risk of PCC and its associated symptoms in all cohorts, not specifically in COVID-19 patients.

The Effect of a Video-Assisted Health Education Program Followed by Peer Education on the Health Literacy of COVID-19 and Other Infectious Diseases Among School Children: Quasi-Randomized Controlled Trial

BACKGROUND

To improve the engagement and effectiveness of traditional health programs, it is necessary to explore alternative models of health education including video-assisted lectures and peer education.

OBJECTIVE

This study aimed to evaluate the effects of a combination of video-assisted lectures and peer education on health literacy related to infectious diseases among students.

METHODS

Third-grade classes from 11 pilot schools in Longgang District of Shenzhen, China, were randomized to the intervention and control groups. In the intervention group, a video-assisted interactive health education program was conducted twice over a time span of 5 months. Each of the 2 sessions included a 40-minute lecture on COVID-19 and other common infectious diseases in schools and a 5-minute science video. In addition, 5 "little health supervisors" at the end of the first session were elected in each class, who were responsible for helping class members to learn health knowledge and develop good hygiene habits. Students answered the same quiz before the first and after the second session. Models based on item response theory (IRT) were constructed to score the students' knowledge of infectious diseases based on the quiz.

RESULTS

In total, 52 classes and 2526 students (intervention group: n=1311; control group: n=1215) were enrolled. Responses of the baseline survey were available for 2177 (86.2%; intervention group: n=1306; control group: n=871) students and those of the postintervention survey were available for 1862 (73.7%; intervention group: n=1187; control group: n=675). There were significant cross-group differences in the rates of correctly answering questions about influenza symptoms, transmission, and preventive measures; chicken pox symptoms; norovirus diarrhea symptoms; mumps symptoms; and COVID-19 symptoms. Average IRT scores of questions related to infectious diseases in the intervention and control groups were, respectively, -0.0375 (SD 0.7784) and 0.0477 (SD 0.7481) before the intervention (P=.01), suggesting better baseline knowledge in the control group. After the intervention, the average scores of the intervention and control groups were 0.0543 (SD 0.7569) and -0.1115 (SD 0.7307), respectively (P<.001), suggesting not only significantly better scores but also greater improvement in the intervention group.

CONCLUSIONS

After the health education project, the correct answer rate of infectious disease questions in the intervention group was higher than that of the control group, which indicates significant effects of the combination of video-assisted lectures and peer education for the promotion of health literacy. In addition, the intervention effect of the first session persisted for at least 4 months up to the second session. As such, the proposed program was effective in improving the health literacy of school children in relation to infectious diseases and should be considered for massive health promotion campaigns during pandemics.

TRIAL REGISTRATION

ISRCTN ISRCTN49297995; https://www.isrctn.com/ISRCTN49297995.

Identifying the need for infection-related consultations in intensive care patients using machine learning models

Infection-related consultations on intensive care units (ICU) have a positive impact on quality of care and clinical outcome. However, timing of these consultations is essential and to date they are typically event-triggered and reactive. Here, we investigate a proactive approach to identify patients in need for infection-related consultations by machine learning models using routine electronic health records. Data was retrieved from a mixed ICU at a large academic tertiary care hospital including 9684 admissions. Infection-related consultations were predicted using logistic regression, random forest, gradient boosting machines, and long short-term memory neural networks (LSTM). Overall, 7.8% of admitted patients received an infection-related consultation. Time-sensitive modelling approaches performed better than static approaches. Using LSTM resulted in the prediction of infection-related consultations in the next clinical shift (up to eight hours in advance) with an area under the receiver operating curve (AUROC) of 0.921 and an area under the precision recall curve (AUPRC) of 0.541. The successful prediction of infection-related consultations for ICU patients was done without the use of classical triggers, such as (interim) microbiology reports. Predicting this key event can potentially streamline ICU and consultant workflows and improve care as well as outcome for critically ill patients with (suspected) infections.

Evaluating repellence properties of catnip essential oil against the mosquito species Aedes aegypti using a Y-tube olfactometer

The mosquito species Aedes aegypti (L.) is known to act as a vector in the transmission of various diseases, including dengue fever and yellow fever. The use of insect repellents is one of precautionary measures used to mitigate the risk of these diseases in humans by reducing mosquito biting. Nepetalactone, a potent natural insect repellent primarily found in catnip (Nepeta cataria) essential oil, has emerged as a promising candidate for mosquito repellence. Here, we evaluated the potential of catnip essential oil (> 95% nepetalactone) for use as a mosquito repellent. Using a Y-tube olfactometer and human hands as an attractant, we analysed the effectiveness of catnip oil at repelling the mosquito species Aedes aegypti. We tested a range of dilutions of catnip essential oil and found that concentrations as low as 2% were effective at repelling > 70% of mosquitoes for between one and four hours after repellent application. These findings suggest that nepetalactone could potentially be used as a natural, effective alternative to synthetic mosquito repellents, thereby offering protection against vector-borne diseases.

Alkyl deoxyglycoside-polymyxin combinations against critical priority carbapenem-resistant gram-negative bacteria

The escalating antimicrobial resistance crisis urges the development of new antibacterial treatments with innovative mechanisms of action, particularly against the critical priority carbapenem-resistant Acinetobacter baumannii (CRAB), Pseudomonas aeruginosa (CRPA) and Enterobacteriaceae (CRE). Membrane-disrupting dodecyl deoxyglycosides have been reported for their interesting phosphatidylethanolamine-associated bactericidal activity against Gram-positive strains; however, their inability to penetrate the Gram-negative outer membrane (OM) renders them useless against the most challenging pathogens. Aiming to repurpose alkyl deoxyglycosides against Gram-negative bacteria, this study investigates the antimicrobial effects of five reference compounds with different deoxygenation patterns or anomeric configurations in combination with polymyxins as adjuvants for enhanced OM permeability. The generation of the lead 4,6-dideoxy scaffold was optimized through a simultaneous dideoxygenation step and applied to the synthesis of a novel alkyl 4,6-dideoxy C-glycoside 5, herein reported for the first time. When combined with subtherapeutic colistin concentrations, most glycosides demonstrated potent antimicrobial activity against several multidrug-resistant clinical isolates of CRAB, CRE and CRPA exhibiting distinct carbapenem resistance mechanisms, together with acceptable cytotoxicity against human HEK-293T and Caco-2 cells. The novel 4,6-dideoxy C-glycoside 5 emerged as the most promising prototype structure for further development (MIC 3.1 μg/mL when combined with colistin 0.5 μg/mL against CRPA or 0.25 μg/mL against several CRE and CRAB strains), highlighting the potential of C-glycosylation for an improved bioactive profile. This study is the first to show the potential of IM-targeting carbohydrate-based compounds for the treatment of infections caused by MDR Gram-negative pathogens of clinical importance.

Investigating the etiologies of non-malarial febrile illness in Senegal using metagenomic sequencing

The worldwide decline in malaria incidence is revealing the extensive burden of non-malarial febrile illness (NMFI), which remains poorly understood and difficult to diagnose. To characterize NMFI in Senegal, we collected venous blood and clinical metadata in a cross-sectional study of febrile patients and healthy controls in a low malaria burden area. Using 16S and untargeted sequencing, we detected viral, bacterial, or eukaryotic pathogens in 23% (38/163) of NMFI cases. Bacteria were the most common, with relapsing fever Borrelia and spotted fever Rickettsia found in 15.5% and 3.8% of cases, respectively. Four viral pathogens were found in a total of 7 febrile cases (3.5%). Sequencing also detected undiagnosed Plasmodium, including one putative P. ovale infection. We developed a logistic regression model that can distinguish Borrelia from NMFIs with similar presentation based on symptoms and vital signs (F1 score: 0.823). These results highlight the challenge and importance of improved diagnostics, especially for Borrelia, to support diagnosis and surveillance.

Derivation and validation of novel integrated inpatient mortality prediction score for COVID-19 (IMPACT) using clinical, laboratory, and AI-processed radiological parameter upon admission: a multicentre study

Limited studies explore the use of AI for COVID-19 prognostication. This study investigates the relationship between AI-aided radiographic parameters, clinical and laboratory data, and mortality in hospitalized COVID-19 patients. We conducted a multicentre retrospective study. The derivation and validation cohort comprised of 512 and 137 confirmed COVID-19 patients, respectively. Variable selection for constructing an in-hospital mortality scoring model was performed using the least absolute shrinkage and selection operator, followed by logistic regression. The accuracy of the scoring model was assessed using the area under the receiver operating characteristic curve. The final model included eight variables: anosmia (OR: 0.280; 95%CI 0.095-0.826), dyspnoea (OR: 1.684; 95%CI 1.049-2.705), loss of consciousness (OR: 4.593; 95%CI 1.702-12.396), mean arterial pressure (OR: 0.928; 95%CI 0.900-0.957), peripheral oxygen saturation (OR: 0.981; 95%CI 0.967-0.996), neutrophil % (OR: 1.034; 95%CI 1.013-1.055), serum urea (OR: 1.018; 95%CI 1.010-1.026), affected lung area score (OR: 1.026; 95%CI 1.014-1.038). The Integrated Inpatient Mortality Prediction Score for COVID-19 (IMPACT) demonstrated a predictive value of 0.815 (95% CI 0.774-0.856) in the derivation cohort. Internal validation resulted in an AUROC of 0.770 (95% CI 0.661-0.879). Our study provides valuable evidence of the real-world application of AI in clinical settings. However, it is imperative to conduct prospective validation of our findings, preferably utilizing a control group and extending the application to broader populations.

Aedes albopictus in a recently invaded area in Spain: effects of trap type, locality, and season on mosquito captures

Mosquitoes are primary vectors of pathogens impacting humans, wildlife, and livestock. Among them, the Asian tiger mosquito, Aedes albopictus, stands out as an invasive species with a global distribution, having established populations on every continent except Antarctica. Recent findings incriminate Ae. albopictus in the local transmission of several pathogens causing human diseases, including dengue, chikungunya, and Zika viruses and worm parasites as Dirofilaria. In Spain, the establishment of Ae. albopictus occurred in 2004 and it rapidly expanded, currently reaching southern provinces and creating novel epidemiological scenarios in recently invaded areas. In this study, we conducted captures of Ae. albopictus from May to November 2022 in two provinces, Granada and Malaga, situated near the current edge of the species' expanding range in Spain. The objective was to identify the primary factors influencing their captures in these regions. Mosquitoes were captured using BG-Sentinel traps baited with CO2 and BG-Lure, and miniature CDC-UV traps in five different localities. Our findings underscore the influence of both extrinsic factors, such as locality, and intrinsic factors, including mosquito sex, on the abundance of captured Ae. albopictus. A higher abundance of Ae. albopictus was observed in the Malaga province compared to localities in the Granada province. Furthermore, similar numbers of Ae. albopictus mosquitoes were captured in more urbanized areas of Granada, while the lowest counts were recorded in the less urbanized area. These results were compared to captures of another common species in the area, specifically Culex pipiens. Overall, these results represent the first monitoring of invasive Ae. albopictus in the area and are discussed in the light of the potential importance of the species as a nuisance for humans and vectors of pathogens of public health relevance.

Within-Host Evolution of Bacterial Pathogens in Acute and Chronic Infection

Bacterial pathogens undergo remarkable adaptive change in response to the selective forces they encounter during host colonization and infection. Studies performed over the past few decades have demonstrated that many general evolutionary processes can be discerned during the course of host adaptation, including genetic diversification of lineages, clonal succession events, convergent evolution, and balanced fitness trade-offs. In some cases, elevated mutation rates resulting from mismatch repair or proofreading deficiencies accelerate evolution, and active mobile genetic elements or phages may facilitate genome plasticity. The host immune response provides another critical component of the fitness landscapes guiding adaptation, and selection operating on pathogens at this level may lead to immune evasion and the establishment of chronic infection. This review summarizes recent advances in this field, with a special focus on different forms of bacterial genome plasticity in the context of infection, and considers clinical consequences of adaptive changes for the host.

Neonatal nephrotic syndrome: all is not gloomy

Congenital nephrotic syndrome (CNS) is a rare clinical syndrome with a constellation of proteinuria, hypoalbuminaemia and oedema, presenting within 3 months of birth. We present a rare case of neonatal nephrotic syndrome with a probable sepsis induced aetiology. The neonate was referred at day of life 15 with Klebsiella pneumonia sepsis and anasarca. On investigation, the patient had nephrotic range proteinuria, hypoalbuminaemia, generalised anasarca and ascites. The neonate was started on broad-spectrum antibiotics and furosemide. Genetic and other secondary causes of CNS were ruled out. With supportive management and resolution of sepsis, the neonate improved. This case highlights the rare cause of sepsis-induced nephrotic syndrome (NS), which required only supportive treatment without the need for aggressive management of CNS.

Identification of shared pathogenetic mechanisms between COVID-19 and IC through bioinformatics and system biology

COVID-19 increased global mortality in 2019. Cystitis became a contributing factor in SARS-CoV-2 and COVID-19 complications. The complex molecular links between cystitis and COVID-19 are unclear. This study investigates COVID-19-associated cystitis (CAC) molecular mechanisms and drug candidates using bioinformatics and systems biology. Obtain the gene expression profiles of IC (GSE11783) and COVID-19 (GSE147507) from the Gene Expression Omnibus (GEO) database. Identified the common differentially expressed genes (DEGs) in both IC and COVID-19, and extracted a number of key genes from this group. Subsequently, conduct Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis on the DEGs. Additionally, design a protein-protein interaction (PPI) network, a transcription factor gene regulatory network, a TF miRNA regulatory network, and a gene disease association network using the DEGs. Identify and extract hub genes from the PPI network. Then construct Nomogram diagnostic prediction models based on the hub genes. The DSigDB database was used to forecast many potential molecular medicines that are associated with common DEGs. Assess the precision of hub genes and Nomogram models in diagnosing IC and COVID-19 by employing Receiver Operating Characteristic (ROC) curves. The IC dataset (GSE57560) and the COVID-19 dataset (GSE171110) were selected to validate the models' diagnostic accuracy. A grand total of 198 DEGs that overlapped were found and chosen for further research. FCER1G, ITGAM, LCP2, LILRB2, MNDA, SPI1, and TYROBP were screened as the hub genes. The Nomogram model, built using the seven hub genes, demonstrates significant utility as a diagnostic prediction model for both IC and COVID-19. Multiple potential molecular medicines associated with common DEGs have been discovered. These pathways, hub genes, and models may provide new perspectives for future research into mechanisms and guide personalised and effective therapeutics for IC patients infected with COVID-19.

Application of multi-gene genetic programming to the prognosis prediction of COVID-19 using routine hematological variables

Identifying patients who may develop severe COVID-19 has been of interest to clinical physicians since it facilitates personalized treatment and optimizes the allocation of medical resources. In this study, multi-gene genetic programming (MGGP), as an advanced artificial intelligence (AI) tool, was used to determine the importance of laboratory predictors in the prognosis of COVID-19 patients. The present retrospective study was conducted on 1455 patients with COVID-19 (727 males and 728 females), who were admitted to Allameh Behlool Gonabadi Hospital, Gonabad, Iran in 2020-2021. For each patient, the demographic characteristics, common laboratory tests at the time of admission, duration of hospitalization, admission to the intensive care unit (ICU), and mortality were collected through the electronic information system of the hospital. Then, the data were normalized and randomly divided into training and test data. Furthermore, mathematical prediction models were developed by MGGP for each gender. Finally, a sensitivity analysis was performed to determine the significance of input parameters on the COVID-19 prognosis. Based on the achieved results, MGGP is able to predict the mortality of COVID-19 patients with an accuracy of 60-92%, the duration of hospital stay with an accuracy of 53-65%, and admission to the ICU with an accuracy of 76-91%, using common hematological tests at the time of admission. Also, sensitivity analysis indicated that blood urea nitrogen (BUN) and aspartate aminotransferase (AST) play key roles in the prognosis of COVID-19 patients. AI techniques, such as MGGP, can be used in the triage and prognosis prediction of COVID-19 patients. In addition, due to the sensitivity of BUN and AST in the estimation models, further studies on the role of the mentioned parameters in the pathophysiology of COVID-19 are recommended.

Understanding China's shifting priorities and priority-setting processes in development assistance for health

Over the past two decades, China has become a distinctive and increasingly important donor of development assistance for health (DAH). However, little is known about what factors influence China's priority-setting for DAH. In this study, we provide an updated analysis of trends in the priorities of Chinese DAH and compare them to comparable trends among OECD Development Assistance Committee (DAC) donors using data from the AidData's Global Chinese Development Finance Dataset (2000-2017, version 2.0) and the Creditor Reporting System (CRS) database (2000-2017). We also analyse Chinese medical aid exports before and after the start of the COVID-19 pandemic using a Chinese Aid Exports Database. We further explore the potential factors influencing China's shifting priority-setting processes by reviewing Chinese official documents following Walt and Gilson's policy analysis framework (context-actors-process-content) and by testing our conjectures empirically. We find that China has become an important DAH donor to most regions if measured using project value, including but not limited to Africa. China has prioritized aid to African and Asian countries as well as to CRS subsectors that are not prioritized by DAC donors, such as medical services and basic health infrastructure. Chinese quarterly medical aid exports almost quintupled after the start of the COVID-19 pandemic. Noticeably, China has allocated more attention to Asia, eye diseases and infectious disease outbreaks over time. In contrast, the priority given to malaria has declined over the same period. Regarding factors affecting priority shifts, the outbreaks of SARS and Ebola, the launch of the Belt and Road Initiative and the COVID-19 pandemic appear to be important milestones in the timeline of Chinese DAH. Unlike stereotypes of China as a 'lone wolf' donor, our analysis suggests multilateral processes are influential in informing and setting Chinese DAH priorities.

Association between reduced muscle mass and poor prognosis of biliary sepsis

Sepsis is a life-threatening disease, contributing to significant morbidity and mortality. This study aimed to investigate the association between low muscle mass and the prognosis of patients with biliary sepsis, focusing on outcomes such as length of hospital stay (LOS), intensive care unit (ICU) admission, and in-hospital mortality. This retrospective, single-center, observational study included adult patients with biliary sepsis who visited the emergency department between January 2016 and December 2021. Low muscle mass was assessed using the psoas muscle index (PMI). Using computed tomography imaging, the area of both sides of the psoas muscle at the L3 level was measured, and the PMI, corrected by the patient's height was calculated. The primary outcome was in-hospital mortality, and the secondary outcomes were intensive care unit (ICU) admission, LOS, and 14-day mortality. A total of 745 patients were included in this study. Low muscle mass was defined as a PMI < 421 mm2/m2 for males and < 268 mm2/m2 for females with the lower quartile of PMI according to sex. The cohort was classified into sarcopenic (n = 189) and non-sarcopenic (n = 556) groups. There was a significant association between low muscle mass and in-hospital mortality (odds ratio, 3.81; 95% confidence interval, 1.08-13.47; p < 0.001), while there was no significant association between low muscle mass and ICU admission. In addition, the median LOS in the sarcopenic group (10 [7-14] days) was significantly longer than the median (8 [6-11] days) in the non-sarcopenic group. Low muscle mass was significantly associated with clinical outcomes, particularly in-hospital mortality and LOS, in patients with biliary sepsis.

Development and validation of the MosquitoWise survey to assess perceptions towards mosquitoes and mosquito-borne viruses in Europe

Due to climate change and the expanding geographical ranges of key mosquito species, several mosquito-borne viruses (MBVs) have recently emerged in Europe. Understanding people's perceptions and behaviours towards these viruses and the mosquitoes capable of transmitting them is crucial for implementing effective prevention measures and targeted communication campaigns. However, there is currently no appropriate validated survey for European populations to assess this. This study developed and validated a standardized survey, based on the Health Belief Model (HBM), to assess perceptions of mosquitoes and MBVs among Europe's residents. The survey was distributed online to United Kingdom (UK), Dutch and Spanish participants through panel providers. Survey validity and reliability were tested using confirmatory factor analysis (CFA) and Cronbach's alpha. The optimised survey was completed by 336 UK, 438 Dutch and 475 Spanish residents, respectively, and the HBM items passed our validity and reliability testing in all three countries. The final survey has 57 questions, including 19 validated HBM items, and questions to assess demographic characteristics, knowledge, prevention measures and behavioural determinants. Our MosquitoWise survey bridges researchers' understandings of European residents' perceptions and knowledge as a first step to improve preventive behaviour towards mosquitoes and MBVs and guide prevention and communication initiatives.

Road networks and socio-demographic factors to explore COVID-19 infection during its different waves

The COVID-19 pandemic triggered an unprecedented level of restrictive measures globally. Most countries resorted to lockdowns at some point to buy the much-needed time for flattening the curve and scaling up vaccination and treatment capacity. Although lockdowns, social distancing and business closures generally slowed the case growth, there is a growing concern about these restrictions' social, economic and psychological impact, especially on the disadvantaged and poorer segments of society. While we are all in this together, these segments often take the heavier toll of the pandemic and face harsher restrictions or get blamed for community transmission. This study proposes a road-network-based networked approach to model mobility patterns between localities during lockdown stages. It utilises a panel regression method to analyse the effects of mobility in transmitting COVID-19 in an Australian context, together with a close look at a suburban population's characteristics like their age, income and education. Firstly, we attempt to model how the local road networks between the neighbouring suburbs (i.e., neighbourhood measure) and current infection count affect the case growth and how they differ between delta and omicron variants. We use a geographic information system, population and infection data to measure road connections, mobility and transmission probability across the suburbs. We then looked at three socio-demographic variables: age, education and income and explored how they moderate independent and dependent variables (infection rates and neighbourhood measures). The result shows strong model performance to predict infection rate based on neighbourhood road connection. However, apart from age in the delta variant context, the other variables (income and education level) do not seem to moderate the relationship between infection rate and neighbourhood measure. The results indicate that suburbs with a more socio-economically disadvantaged population do not necessarily contribute to more community transmission. The study findings could be potentially helpful for stakeholders in tailoring any health decision for future pandemics.

GrowthPredict: A toolbox and tutorial-based primer for fitting and forecasting growth trajectories using phenomenological growth models

Simple dynamic modeling tools can help generate real-time short-term forecasts with quantified uncertainty of the trajectory of diverse growth processes unfolding in nature and society, including disease outbreaks. An easy-to-use and flexible toolbox for this purpose is lacking. This tutorial-based primer introduces and illustrates GrowthPredict, a user-friendly MATLAB toolbox for fitting and forecasting time-series trajectories using phenomenological dynamic growth models based on ordinary differential equations. This toolbox is accessible to a broad audience, including students training in mathematical biology, applied statistics, and infectious disease modeling, as well as researchers and policymakers who need to conduct short-term forecasts in real-time. The models included in the toolbox capture exponential and sub-exponential growth patterns that typically follow a rising pattern followed by a decline phase, a common feature of contagion processes. Models include the 1-parameter exponential growth model and the 2-parameter generalized-growth model, which have proven useful in characterizing and forecasting the ascending phase of epidemic outbreaks. It also includes the 2-parameter Gompertz model, the 3-parameter generalized logistic-growth model, and the 3-parameter Richards model, which have demonstrated competitive performance in forecasting single peak outbreaks. We provide detailed guidance on forecasting time-series trajectories and available software ( https://github.com/gchowell/forecasting_growthmodels ), including the full uncertainty distribution derived through parametric bootstrapping, which is needed to construct prediction intervals and evaluate their accuracy. Functions are available to assess forecasting performance across different models, estimation methods, error structures in the data, and forecasting horizons. The toolbox also includes functions to quantify forecasting performance using metrics that evaluate point and distributional forecasts, including the weighted interval score. This tutorial and toolbox can be broadly applied to characterizing and forecasting time-series data using simple phenomenological growth models. As a contagion process takes off, the tools presented in this tutorial can help create forecasts to guide policy regarding implementing control strategies and assess the impact of interventions. The toolbox functionality is demonstrated through various examples, including a tutorial video, and the examples use publicly available data on the monkeypox (mpox) epidemic in the USA.

Neutrophil extracellular trap-related mechanisms in acne vulgaris inspire a novel treatment strategy with adipose-derived stem cells

Acne vulgaris is a type of chronic skin disorder caused by Propionibacterium acnes (P. acnes). Neutrophil extrinsic traps (NETs) play key role in many types of inflammatory skin diseases. Adipose-derived stem cells (ADSCs) was reported modulate immune responses and neutrophil activity. Here, we explored the potential role of ADSCs and the potential mechanism associated with neutrophil extracellular traps (NETs) in relieving acne vulgaris. In the P. acnes-infected ear skin model, histological staining was used to evaluate the inflammatory infiltration and NET formation in control, P. acnes, and P. acnes + ADSCs groups. Besides, western blot was used to detect the expression levels of cit-H3, MPO, and Nrf2 in ear tissue. In vitro, the immunofluorescence staining of MPO and cit-H3, and SYTOX green staining were performed to measure the NET formation. CCK-8 assay, EdU staining, and wound healing assay were used to detect the proliferation and migration abilities of keratinocytes. ELISA assay was utilized to detect the secretion of inflammatory cytokines. In P. acnes-infected ear skin, ADSC treatment significantly attenuated inflammation and NET formation via activating Nrf2 signaling pathway. In vitro, the conditioned medium of ADSCs reduced the formation of P. acne-induced NETs. Besides, ADSCs could inhibit that the NETs efficiently promoted the proliferation, migration, and inflammatory cytokine secretion of keratinocytes. Our study suggested that ADSCs could attenuate P. acne-related inflammation by inhibiting NET formation. This study provides a novel therapeutic perspective of ADSCs in combating acne vulgaris.

Definition and measurement of post-COVID-19 conditions in real-world practice: a global systematic literature review

Post-COVID-19 conditions (PCC) is an umbrella term that encompasses a range of signs, symptoms and conditions present weeks after the acute phase of a SARS-CoV-2 infection. This systematic literature review summarises the heterogeneous methodology used to measure PCC across real-world studies and highlights trends by region, age group, PCC follow-up period and data source.

METHODS

Medline, EMBASE and the Cochrane Library were searched and supplemented with conference and grey literature searches. Eligible studies included individuals with (1) PCC or (2) a positive SARS-CoV-2 test or COVID-19 diagnosis who were followed over time. Included studies were published in English between 1 January 2020 and 14 November 2022.

FINDINGS

Of 291 publications included, 175 (60%) followed individuals with confirmed COVID-19 over time for PCC and 116 (40%) used a prespecified PCC definition. There was substantial heterogeneity in study design, geography, age group, PCC conditions/symptoms assessed and their classification and duration of follow-up. Among studies using a prespecified PCC definition, author-defined criteria (51%) were more common than criteria recommended by major public health organisations (19%). Measurement periods for PCC outcomes from date of acute COVID-19 test were primarily 3 to <6 months (39.2%), followed by 6 to <12 months (27.5%) and <3 months (22.9%). When classified by organ/system, constitutional-related PCC were the most frequently assessed in adult (86%) and paediatric (87%) populations. Within constitutional symptoms, fatigue was most frequently assessed in adult (91.6%) and paediatric (95.0%) populations, followed by fever/chills (37.9% and 55%, respectively).

CONCLUSIONS

PCC definitions are heterogenous across real-world studies, which limits reliable comparisons between studies. However, some similarities were observed in terms of the most frequently measured PCC-associated symptoms/conditions, which may aid clinical management of patients with PCC.CRD42022376111.

Multivalent next generation influenza virus vaccines protect against seasonal and pre-pandemic viruses

Each year, new influenza virus vaccine formulations are generated to keep up with continuously circulating and mutating viral variants. A next-generation influenza virus vaccine would provide long-lasting, broadly-reactive immune protection against current and future influenza virus strains for both seasonal and pre-pandemic viruses. Next generation immunogens were designed using computationally optimized broadly reactive antigen (COBRA) methodology to protect against a broad range of strains over numerous seasons. Novel HA and NA amino acid sequences were derived from multilayered consensus sequence alignment for multiple subtypes of influenza. This multivalent formulation was hypothesized to elicit broadly protective immune responses against both seasonal and pre-pandemic influenza viruses. Mice were vaccinated with multivalent mixtures of HA and NA (H1, H2, H3, H5, H7, N1, N2) proteins. Multivalent COBRA vaccinations elicited antibodies that recognized a broad panel of strains and vaccinated mice were protected against viruses representing multiple subtypes. This is a promising candidate for a universal influenza vaccine that elicits protective immune responses against seasonal and pre-pandemic strains over multiple seasons.

Understanding the exposure risk of aerosolized Coccidioides in a Valley fever endemic metropolis

Coccidioides is the fungal causative agent of Valley fever, a primarily pulmonary disease caused by inhalation of fungal arthroconidia, or spores. Although Coccidioides has been an established pathogen for 120 years and is responsible for hundreds of thousands of infections per year, little is known about when and where infectious Coccidioides arthroconidia are present within the ambient air in endemic regions. Long-term air sampling programs provide a means to investigate these characteristics across space and time. Here we present data from > 18 months of collections from 11 air sampling sites across the Phoenix, Arizona, metropolitan area. Overall, prevalence was highly variable across space and time with no obvious spatial or temporal correlations. Several high prevalence periods were identified at select sites, with no obvious spatial or temporal associations. Comparing these data with weather and environmental factor data, wind gusts and temperature were positively associated with Coccidioides detection, while soil moisture was negatively associated with Coccidioides detection. These results provide critical insights into the frequency and distribution of airborne arthroconidia and the associated risk of inhalation and potential disease that is present across space and time in a highly endemic locale.

Recent advances in infectious disease research using cryo-electron tomography

With the increasing spread of infectious diseases worldwide, there is an urgent need for novel strategies to combat them. Cryogenic sample electron microscopy (cryo-EM) techniques, particularly electron tomography (cryo-ET), have revolutionized the field of infectious disease research by enabling multiscale observation of biological structures in a near-native state. This review highlights the recent advances in infectious disease research using cryo-ET and discusses the potential of this structural biology technique to help discover mechanisms of infection in native environments and guiding in the right direction for future drug discovery.

Contrasted life trajectories: reconstituting the main population exposomes in French Guiana

In French Guiana, life expectancy is between 2 and 3 years below that of France, reflecting differences in mortality rates that are largely sensitive to primary healthcare and thus preventable. However, because poverty affects half of the population in French Guiana, global measurements of life expectancy presumably conflate at least two distinct situations: persons who have similar life expectancies as in mainland France and persons living in precariousness who have far greater mortality rates than their wealthier counterparts. We thus aimed to synthesize what is known about statistical regularities regarding exposures and sketch typical French Guiana exposomes in relation to health outcomes. We conducted a narrative review on common exposures in French Guiana and made comparisons between French Guiana and mainland France, between rich and poor in French Guiana, and between urban and rural areas within French Guiana. The most striking fact this panorama shows is that being a fetus or a young child in French Guiana is fraught with multiple threats. In French Guiana, poverty and poor pregnancy follow-up; renouncing healthcare; wide variety of infectious diseases; very high prevalence of food insecurity; psychosocial stress; micronutrient deficiencies; obesity and metabolic problems; and frequent exposure to lead and mercury in rural areas constitute a stunningly challenging exposome for a new human being to develop into. A substantial part of the population's health is hence affected by poverty and its sources of nutrition.

Breaking barriers in Candida spp. detection with Electronic Noses and artificial intelligence

The timely and accurate diagnosis of candidemia, a severe bloodstream infection caused by Candida spp., remains challenging in clinical practice. Blood culture, the current gold standard technique, suffers from lengthy turnaround times and limited sensitivity. To address these limitations, we propose a novel approach utilizing an Electronic Nose (E-nose) combined with Time Series-based classification techniques to analyze and identify Candida spp. rapidly, using culture species of C. albicans, C.kodamaea ohmeri, C. glabrara, C. haemulonii, C. parapsilosis and C. krusei as control samples. This innovative method not only enhances diagnostic accuracy and reduces decision time for healthcare professionals in selecting appropriate treatments but also offers the potential for expanded usage and cost reduction due to the E-nose's low production costs. Our proof-of-concept experimental results, carried out with culture samples, demonstrate promising outcomes, with the Inception Time classifier achieving an impressive average accuracy of 97.46% during the test phase. This paper presents a groundbreaking advancement in the field, empowering medical practitioners with an efficient and reliable tool for early and precise identification of candidemia, ultimately leading to improved patient outcomes.