Proceedings of the National Academy of Sciences, Volume 121, Issue 40, October 2024.

Proceedings of the National Academy of Sciences, Volume 121, Issue 40, October 2024.

Proceedings of the National Academy of Sciences, Volume 121, Issue 40, October 2024.

Proceedings of the National Academy of Sciences, Volume 121, Issue 40, October 2024.

Proceedings of the National Academy of Sciences, Volume 121, Issue 40, October 2024.

Proceedings of the National Academy of Sciences, Volume 121, Issue 41, October 2024.

Proceedings of the National Academy of Sciences, Volume 121, Issue 41, October 2024.

Concerns regarding “a cluster of pneumonia cases of unknown origin” in Wuhan, China, were globally disseminated in December, 2019. By Jan 25, 2020, Public Health England (now the UK Health Security Agency) had warned the UK Government that person-to-person transmission of the new pathogen (the ‘Wuhan coronavirus’, later named SARS-CoV-2) had been identified outside of China and that the first case had been confirmed in Europe. In the few months that followed, SARS-CoV-2 and the resulting disease, COVID-19, spread across the globe, causing an estimated 22 million excess deaths by the end of the pandemic; a global mortality level not experienced with a respiratory pathogen since the H1N1 influenza pandemic in 1918–20.

Growing up in Amsterdam, The Netherlands, Louis Bont\'s father who worked at the Netherlands Cancer Institute (NKI), often said “doctors will never make good scientists”. This way, his father provided him with a challenge to become a clinician scientist, Bont realised only decades later. Today he is Department Head of Pediatrics at the Wilhelmina Children\'s Hospital, University Medical Center Utrecht, Utrecht, The Netherlands, where his main area of research is respiratory syncytial virus (RSV). He has also been appointed an adjunct professor at Yale University (New Haven, CT, USA).

The data from PROMIS-I suggest a clinically important benefit of colistimethate sodium delivered via the I-neb adaptive aerosol delivery system in patients with bronchiectasis and P aeruginosa infection. These results were not replicated in PROMIS-II, which was affected by the COVID-19 pandemic and prematurely terminated.

Respiratory syncytial virus (RSV) is a leading cause of lower respiratory tract infection (LRTI), hospital admission, and mortality in children worldwide. Early-life RSV LRTI has also been associated with subsequent long-term respiratory sequelae, including recurrent LRTI, recurrent wheezing, asthma, and lung function impairment, and these effects can persist into adulthood as chronic respiratory disease. New preventive measures (maternal vaccine or long-acting monoclonal antibodies) have been licensed to reduce the burden of acute RSV LRTI in infants and children at high risk through passive immunisation.

Respiratory syncytial virus (RSV), an RNA virus spread by droplet infection that affects all ages, is increasingly recognised as an important pathogen in adults, especially among older people living with comorbidities. Distinguishing RSV from other acute viral infections on clinical grounds alone, with sufficient precision to be clinically useful, is not possible. The reference standard diagnosis is by PCR: point-of-care tests perform less well with lower viral loads. Testing samples from a single respiratory tract site could result in underdetection.

Invasive fungal infections in allogeneic hematopoietic stem cell transplant (allo-HSCT) recipients on antimicrobial prophylaxis is a major cause of infectious mortality, although its underlying pathophysiological mechanisms remain unclear. In a new report, Zhai and colleagues provide evidence that heteroresistance drives breakthrough Candida parapsilosis bloodstream infections in allo-HSCT recipients receiving micafungin prophylaxis.

Decomposer microbial communities are gatekeepers in the redistribution of carbon and nutrients from dead animals (carrion) to terrestrial ecosystems. The flush of decomposition products from a carcass creates a hot spot of microbial activity in the soil below, and the animal’s microbiome is released into the environment, mixing with soil communities. Changes in soil physicochemistry, especially reduced oxygen, temporarily constrain microbial nutrient cycling, and influence the timing of these processes and the fate of carrion resources. Carcass-related factors, such as mass, tissue composition, or even microbiome composition may also influence the functional assembly and succession of decomposer communities. Understanding these local scale microbially mediated processes is important for predicting consequences of carrion decomposition beyond the hot spot and hot moment.

The genetics of Plasmodium as an intracellular, mostly haploid, sexually reproducing, eukaryotic organism with a complex life cycle, presents unprecedented challenges in studying drug resistance. This article summarizes current knowledge on the genetic basis of artemisinin resistance (AR) – a main component of current drug therapies for falciparum malaria. Although centered on nonsynonymous single-nucleotide polymorphisms (nsSNPs), we describe multifaceted resistance mechanisms as part of a complex, cumulative genetic trait that involves regulation of expression by a wide array of polymorphisms in noncoding regions. These genetic variations alter transcriptome profiles linked to Plasmodium\'s development and population dynamics, ultimately influencing the emergence and spread of the resistance.

Volume 13, Issue 1, December 2024 .

Volume 13, Issue 1, December 2024 .

Volume 13, Issue 1, December 2024 .

Volume 13, Issue 1, December 2024 .

by The PLOS ONE Editors …

by Roxana Hossain, Glenda Willems, Niels Wynant, Simon Borgolte, Kristof Govaerts, Mark Varrelmann Beet yellows virus (BYV), one of the causal agents of virus yellows (VY) disease in sugar beet (Beta vulgaris subsp. vulgaris), induces economically important damage to the sugar production in Europe. In the absence of effective natural resistance traits, a deeper understanding of molecular reactions in plants to virus infection is required. In this study, the transcriptional modifications in a BYV susceptible sugar beet genotype following aphid-mediated inoculation on mature leaves were studied at three early infection stages [6, 24 and 72 hours post inoculation (hpi)] using RNA sequencing libraries. On average, 93% of the transcripts could be mapped to the B. vulgaris reference genome RefBeet-1.2.2. In total, 588 differentially expressed genes (DEGs) were identified across the three infection stages. Of these, 370 were up- regulated and 218 down-regulated when individually compared to mock-aphid inoculated leaf samples at the same time point, thereby eliminating the effect of aphid feeding itself. Using MapMan ontology for categorisation of sugar beet transcripts, early differential gene expression identified importance of the BIN categories “enzyme classification”, “RNA biosynthesis”, “cell wall organisation” and “phytohormone action”. A particularly high transcriptional change was found for diverse transcription factors, cell wall regulating proteins, signalling peptides and transporter proteins. 28 DEGs being important in “nutrient uptake”, “lipid metabolism”, “phytohormone action”, “protein homeostasis” and “solute transport”, were represented at more than one infection stage. The RT-qPCR validation of thirteen selected transcripts confirmed that BYV is down-regulating chloroplast-related genes 72 hpi, putatively already paving the way for the induction of yellowing symptoms characteristic for the disease. Our study provides deeper insight into the early interaction between BYV and the economically important crop plant sugar beet and opens up the possibility of using the knowledge of identified proviral plant factors as well as plant defense-related factors for resistance breeding.

by Jooyeon Park, Kyoung Hwa Lee, Young Goo Song, Hyungmin Park, Kwang Suk Lee Since the COVID-19 pandemic, there has been persistent emphasis on the importance of indoor air disinfection and ventilation in isolation units in the hospital environment. Nevertheless, no optimal and concrete disinfection protocol has been proposed to inactivate the viruses as quickly as possible. In this study, we experimentally evaluated various ventilation and disinfection protocols based on the combination of negative-pressure ventilation, ultraviolet (UV) light illumination, and Hypochlorous acid (HOCl) spray against three active virus species in a 3.5 cubic meters isolation unit. This small-size unit has gained attention during the pandemic due to the high demand for compact mobile laboratory systems capable of rapid disease diagnosis. In accordance with the WHO laboratory biosafety guidance, which states that all enclosed units where diagnostic work is conducted must ensure proper ventilation and disinfection activities, we aim to propose virus removal protocols for units compact enough to be installed within a van or deployed outdoor. The results confirmed the superiority (in terms of virus removal rate and time required) of the virus removal methods in the order of UV light, ventilation, and HOCl spray. Ultimately, we propose two optimal protocols: (i) UV light alone for three minutes, and (ii) UV light with ventilation for three minutes, followed by one-minute ventilation only. The time span of three minutes in the latter protocol is based on the clinical practice such that the medical staffs have a sufficient time to process the samples taken in transition to next patient to care.

by Marie Y. Detrait, Stéphanie Warnon, Raphaël Lagasse, Laurent Dumont, Stéphanie De Prophétis, Amandine Hansenne, Juliette Raedemaeker, Valérie Robin, Géraldine Verstraete, Aline Gillain, Nicolas Depasse, Pierre Jacmin, Delphine Pranger Introduction Primary refractory disease affects 30–40% of patients diagnosed with DLBCL and is a significant challenge in disease management due to its poor prognosis. Predicting refractory status could greatly inform treatment strategies, enabling early intervention. Various options are now available based on patient and disease characteristics. Supervised machine-learning techniques, which can predict outcomes in a medical context, appear highly suitable for this purpose. Design Retrospective monocentric cohort study. Patient population Adult patients with a first diagnosis of DLBCL admitted to the hematology unit from 2017 to 2022. Aim We evaluated in our Center five supervised machine-learning (ML) models as a tool for the prediction of primary refractory DLBCL. Main results One hundred and thirty patients with Diffuse Large B-cell lymphoma (DLBCL) were included in this study between January 2017 and December 2022. The variables used for analysis included demographic characteristics, clinical condition, disease characteristics, first-line therapy and PET-CT scan realization after 2 cycles of treatment. We compared five supervised ML models: support vector machine (SVM), Random Forest Classifier (RFC), Logistic Regression (LR), Naïve Bayes (NB) Categorical classifier and eXtreme Gradient Boost (XGboost), to predict primary refractory disease. The performance of these models was evaluated using the area under the receiver operating characteristic curve (ROC-AUC), accuracy, false positive rate, sensitivity, and F1-score to identify the best model. After a median follow-up of 19.5 months, the overall survival rate was 60% in the cohort. The Overall Survival at 3 years was 58.5% (95%CI, 51–68.5) and the 3-years Progression Free Survival was 63% (95%CI, 54–71) using Kaplan-Meier method. Of the 124 patients who received a first line treatment, primary refractory disease occurred in 42 patients (33.8%) and 2 patients (1.6%) experienced relapse within 6 months. The univariate analysis on refractory disease status shows age (p = 0.009), Ann Arbor stage (p = 0.013), CMV infection (p = 0.012), comorbidity (p = 0.019), IPI score (p…

by Viet Q. Dao, Crystal N. Johnson, William J. Platt Processes modifying newly deposited litter substrates should affect fine fuels in fire-managed tidal marsh ecosystems. Differences in chemical composition and dynamics of litter should arise from fire histories that generate pyrodiverse plant communities, tropical cyclones that deposit wrack as litter, tidal inundation that introduces and alters sediments and microbes, and interactions among these different processes. The resulting diversity and dynamics of available litter compounds should affect microbial (fungal and bacterial) communities and their roles in litter substrate dynamics and ecosystem responses over time. We experimentally examined effects of differences in litter types produced by different fire regimes and litter loads (simulating wrack deposition) on microbial community composition and changes over time. We established replicated plots at similar elevations within frequent tidal-inundation zones of a coastal brackish Louisiana marsh. Plots were located within blocks with different prescribed fire regimes. We deployed different measured loads of new sterilized litter collected from zones in which plots were established, then re-measured litter masses at subsequent collection times. We used DNA sequencing to characterize microbial communities, indicator families, and inferred ecosystem functions in litter subsamples. Differences in fire regimes had large, similar effects on fungal and bacterial indicator families and community compositions and were associated with alternate trajectories of community development over time. Both microbial and plant community compositional patterns were associated with fire regimes, but in dissimilar ways. Differences in litter loads introduced differences in sediment accumulation associated with tidal inundation that may have affected microbial communities. Our study further suggests that fire regimes and tropical cyclones, in the context of frequent tidal inundation, may interactively generate substrate heterogeneities and alter microbial community composition, potentially modifying fine fuels and hence subsequent fires. Understanding microbial community compositional and functional responses to fire regimes and tropical cyclones should be useful in management of coastal marsh ecosystems.

by Mohammed S. Almuhayawi, Mohammed H. Alruhaili, Mohamed K. Y. Soliman, Muyassar K. Tarabulsi, Ruba A. Ashy, Amna A. Saddiq, Samy Selim, Yasir Alruwaili, Salem S. Salem It is thought to be risk-free, environmentally benign, and safe for biological processes to produce zinc oxide nanoparticles from renewable resources. This study examined Cassia javanica’s ability to create ZnONPs. The generated ZnONPs were analyzed using a variety of techniques, such as TEM, FTIR spectroscopy, UV-Vis spectroscopy, and XRD analysis. The antibacterial potential of ZnONPs has been investigated using both Agar well diffusion and microtitreplate (MTP) methods. One method used to evaluate ZnONPs’ capacity to scavenge free radicals at different concentrations was the DPPH method. The permanent zinc oxide (ZnO) shape and the naturally occurring crystal structure of ZnONPs were validated by the XRD data. ZnONPs showed antibacterial activity with MICs of 31.7 μg/mL toward Bacillus subtilis, 62.5 μg/mL for Salmonella typhimurium, Escherichia coli while Clostridium sporogenes and Bacillus pumilus was 125μg/mL. Furthermore, ZnONPs demonstrated a range of antibiofilm activities toward Staphylococcus aureus (MRSA). ZnONPs showed an intriguing antioxidant capacity, achieving IC50 of 109.3 μg/ml μg/mL. Additionally, ZnONPs demonstrated low toxic effect on Vero cell with IC50 154.01 μg/mL as well as possible anticancer action when applied to the carcinoma cell lines HepG2 with IC50 of 47.48 μg/mL. Furthermore, ZnONPs at 62.5 μg/mL had a promising antiviral impact against HSV1 and COX B4, with antiviral activities of 75.4% and 65.8%, respectively.

by Yichong Zhao, Kenta Oono, Hiroki Takizawa, Masaaki Kotera The design of RNA plays a crucial role in developing RNA vaccines, nucleic acid therapeutics, and innovative biotechnological tools. However, existing techniques frequently lack versatility across various tasks and are dependent on pre-defined secondary structure or other prior knowledge. To address these limitations, we introduce GenerRNA, a Transformer-based model inspired by the success of large language models (LLMs) in protein and molecule generation. GenerRNA is pre-trained on large-scale RNA sequences and capable of generating novel RNA sequences with stable secondary structures, while ensuring distinctiveness from existing sequences, thereby expanding our exploration of the RNA space. Moreover, GenerRNA can be fine-tuned on smaller, specialized datasets for specific subtasks, enabling the generation of RNAs with desired functionalities or properties without requiring any prior knowledge input. As a demonstration, we fine-tuned GenerRNA and successfully generated novel RNA sequences exhibiting high affinity for target proteins. Our work is the first application of a generative language model to RNA generation, presenting an innovative approach to RNA design.

by Noelle M. Nieskens, Yukiko Miyamoto, Brianna M. Hurysz, Anthony J. O’Donoghue, Lars Eckmann Trichomonas vaginalis is the causative agent of the common sexually transmitted disease, trichomoniasis, which affects more than a hundred million people worldwide. Metronidazole and tinidazole, agents belonging to the 5-nitroheterocyclic class of antimicrobials, are most often used to treat infection, but increased resistance has been reported and adverse effects of these drugs can be significant. Consequently, an urgent need exists for the development of novel drug entities against trichomoniasis. Critical for antimicrobial drug development is the demonstration of in vivo efficacy. Murine models of vaginal T. vaginalis infection are unreliable for unknown reasons. Meanwhile, murine infections with the related bovine pathogen, Tritrichomonas foetus, tend to be more robust, although susceptibility to different antimicrobials might differ from T. vaginalis. Here, we explored the utility of T. foetus infection as a surrogate model for drug development against T. vaginalis. Four different T. foetus strains caused robust vaginal infection in young mice, while none of four diverse T. vaginalis strains did. Comparison of drug susceptibility profiles revealed that T. foetus and T. vaginalis were similarly susceptible to a range of 5-nitroheterocyclic and gold(I) compounds. By comparison, proteasome inhibitors were 10- to 15-fold less active against T. foetus than T. vaginalis, although one of the proteasome inhibitors, bortezomib, had low micromolar activity or better against multiple strains of both trichomonads. Different strains of T. foetus were used to demonstrate the utility of the murine vaginal infection models for in vivo efficacy testing, including for bortezomib and a gold(I) compound. The differences in susceptibility to proteasome inhibitors may be partially explained by differences in the proteasome subunit sequences between the two trichomonads, although the functional relevance of the proteasome was similar in both organisms. These findings indicate that T. foetus can serve as a reliable surrogate model for T. vaginalis in vitro and in murine infections in vivo, but caution must be exercised for specific drug classes with targets, such as the proteasome, that may display genetic divergence between the trichomonads.

by Rajkumar Kulandaivel, Manikandan Ramachandran, Sathishkumar Veerappampalayam Easwaramoorthy, Jaehyuk Cho Recent evolution in connected devices modelled a massive stipulation for network traffic resources and classification. Software-defined networking (SDN) enables ML techniques with the Internet of Things (IoT) to automate network traffic. This helps to reduce accuracy and improves latency. Problems by conventional techniques to categorize network traffic acquired from IoT and assign resources can be resolved through SDN solutions. This manuscript proposes a proposed network traffic classification technique on IoT with SDN called Gauss Markov and Flow-balanced Vector Radial Learning (GM-FVRL). With the network traffic features acquired from the IoT devices, SDN-enabled Gauss Markov Correlation-based IoT Network Traffic Feature Extraction is applied to extort relevant network aspects. Next, the flow-balanced radial-based ML model for network traffic categorization uses the relevant extracted network traffic features. With the aid of flow, the balanced radial basis function reduces the influence of noise due to distinct network flow. This helps to improve accuracy and minimize latency. Due to this, better precision and recall is ensured. Performance of our method has been evaluated utilizing a scheme using an SDN traffic dataset. The results show that our method classifies the network traffic with high classification accuracy and minimum latency, ensuring better precision and recall.

Publication date: Available online 30 September 2024 Source: Immunity Author(s): Ye Liu, Yifang Chen, Uyanga Batzorig, Jingting Li, Celia Fernández-Méndez, Samiksha Mahapatra, Fengwu Li, Shebin Sam, Tatsuya Dokoshi, Seung-Phil Hong, Teruaki Nakatsuji, Richard L. Gallo, George L. Sen …

Publication date: Available online 30 September 2024 Source: Immunity Author(s): Alexander Lercher, Jin-Gyu Cheong, Michael J. Bale, Chenyang Jiang, Hans-Heinrich Hoffmann, Alison W. Ashbrook, Tyler Lewy, Yue S. Yin, Corrine Quirk, Emma J. DeGrace, Luis Chiriboga, Brad R. Rosenberg, Steven Z. Josefowicz, Charles M. Rice …

Infection and Immunity, Ahead of Print.

Antimicrobial Agents and Chemotherapy, Ahead of Print.

Antimicrobial Agents and Chemotherapy, Ahead of Print.

Antimicrobial Agents and Chemotherapy, Ahead of Print.

Journal of Medical Virology, Volume 96, Issue 10, October 2024.

BackgroundTwo decades have passed since the beginning of the Iraq War in 2003. Iraq has long suffered from conflicts and instability, where the people have limited access to healthcare. The coronavirus disease (COVID-19) pandemic brought additional disruption to health service provision. ObjectivesAt the midpoint towards universal health coverage (UHC) in 2030, this study aims to gain a better understanding of the trends of UHC progress in Iraq in the context of the conflicts and the COVID-19 pandemic and to indicate possible pragmatic options. DesignThis study employed Bayesian hierarchical regression models to estimate trends and projections of health service availability and coverage indicators up to 2030. Furthermore, for health service coverage, four scenarios were defined based on the availability of health services, and projections were made for each scenario up to 2030. SettingOur approach used the yearly data from the Ministry of Health and four nationally representative household surveys between 2000 and 2020. We evaluated the subnational-level progress in three health service availability indicators and 13 health service coverage indicators in 18 governorates in Iraq from 2000 to 2030. ResultsThe findings from 2000 to 2020 revealed a lack of progress in the indicators of health facility and inpatient bed, and pronounced detrimental effects from major conflicts and the pandemic on all measured health service coverage indicators. Despite these setbacks, several health service coverage indicators demonstrated resilience and elasticity in their recovery. The projected trends for 2021 to 2030 indicated limited alternations in the health service availability. By 2030, five health service coverage indicators will achieve the designated 80% targets. A scenario-based analysis predicts improved coverage of antenatal care, and child immunisation and treatment if health service availability is bolstered to globally recommended standards. Under this scenario, several governorates—Anbar, Baghdad, Nainawa, Qadissiyah, Salahaddin, Thiqar and Wasit—presented improved health service coverage in more indicators. ConclusionStrengthened health service availability has the potential to significantly improve fragile health service coverage indicators and in more vulnerable governorates. …

ObjectiveThis study aimed to evaluate the safety and performance of PowerPICC catheters in a real-world setting. DesignProspective, observational, multicentre study. SettingNine European countries, involving 14 centres. ParticipantsGeneral patient population. InterventionPowerPICC catheter inserted by the clinician as standard of care with routinely collected outcomes followed through device removal or 180 days postinsertion. Primary and secondary outcomes measuresSafety and performance outcomes were assessed for PowerPICC, PowerPICC SOLO 2 and PowerGroshong PICC. The primary safety endpoint was the incidence of symptomatic venous thrombosis (VT), and secondary safety endpoints included phlebitis, extravasation, vessel laceration, vessel perforation local infection, accidental dislodgment and catheter-related bloodstream infection (CRBSI). The primary performance endpoint was the percentage of patients whose PowerPICC device remained in place through the completion of therapy. The secondary performance endpoints included catheter patency, placement success in a single attempt and usability. ResultsThe enrolled patients (N=451) received either PowerPICC, PowerPICC SOLO 2 or PowerGroshong PICC catheters. Across all devices, 1.6% of patients developed symptomatic VT, and CRBSI occurred in 1.6% of patients. There were no cases of phlebitis or extravasation and only three cases of vein laceration or vein perforation. The catheters showed high success rates in completing therapy (81.8%), maintaining patency (93.9%) and achieving successful placement in a single attempt (90.4%). Clinicians overwhelmingly agreed that both the guidewire and stylet (93.3% and 94.4%, respectively) were easy or very easy to use. ConclusionsThis study demonstrates the safety and performance of PowerPICC catheters across diverse settings and patient cohorts in real-world hospital settings across Europe. The findings indicate that these catheters are safe and can be effectively used in the general patient setting and when inserted by a variety of clinicians. The low incidence of complications and high success rates further support the clinical utility of these catheters. Trial registration numberNCT04263649. …

ObjectivesTo validate and test the generalisability of the SASKit-ML pipeline, a prepublished feature selection and machine learning pipeline for the prediction of health deterioration after a stroke or pancreatic adenocarcinoma event, by using it to identify biomarkers of health deterioration in chronic disease. DesignThis is a validation study using a predefined protocol applied to multiple publicly available datasets, including longitudinal data from cohorts with type 2 diabetes (T2D), inflammatory bowel disease (IBD), rheumatoid arthritis (RA) and various cancers. The datasets were chosen to mimic as closely as possible the SASKit cohort, a prospective, longitudinal cohort study. Data sourcesPublic data were used from the T2D (77 patients with potential pre-diabetes and 18 controls) and IBD (49 patients with IBD and 12 controls) branches of the Human Microbiome Project (HMP), RA Map (RA-MAP, 92 patients with RA, 22 controls) and The Cancer Genome Atlas (TCGA, 16 cancers). MethodsData integration steps were performed in accordance with the prepublished study protocol, generating features to predict disease outcomes using 10-fold cross-validated random survival forests. Outcome measuresHealth deterioration was assessed using disease-specific clinical markers and endpoints across different cohorts. In the HMP-T2D cohort, the worsening of glycated haemoglobin (HbA1c) levels (5.7% or more HbA1c in the blood), fasting plasma glucose (at least 100 mg/dL) and oral glucose tolerance test (at least 140) results were considered. For the HMP-IBD cohort, a worsening by at least 3 points of a disease-specific severity measure, the \'Simple Clinical Colitis Activity Index\' or \'Harvey-Bradshaw Index\' indicated an event. For the RA-MAP cohort, the outcome was defined as the worsening of the \'Disease Activity Score 28\' or \'Simple Disease Activity Index\' by at least five points, or the worsening of the \'Health Assessment Questionnaire\' score or an increase in the number of swollen/tender joints were evaluated. Finally, the outcome for all TCGA datasets was the progression-free interval. ResultsModels for the prediction of health deterioration in T2D, IBD, RA and 16 cancers were produced. The T2D (C-index of 0.633 and Integrated Brier Score (IBS) of 0.107) and the RA (C-index of 0.654 and IBS of 0.150) models were modestly predictive. The IBD model was uninformative. TCGA models tended towards modest predictive power. ConclusionsThe SASKit-ML pipeline produces informative and useful features with the power to predict health deterioration in a variety of diseases and cancers; however, this performance is disease-dependent. …

IntroductionFetal growth restriction (FGR) affects about 3%–5% of term pregnancies. If prenatally detected and anterograde umbilical artery flow is preserved (stage I), it is recommended to deliver at term (≥ 37+0 weeks). In the absence of contraindications, the vaginal route is preferred, and labour induction is usually required. It has been postulated that mechanical methods for cervical ripening may have an optimal profile for the induction of term FGR fetuses since they are associated with less uterine stimulation than the standard pharmacological methods, and therefore, could be better tolerated by fetuses with reduced placental reserve. This study aims to evaluate whether cervical ripening with a Cook’s balloon for the induction of labour from 37+0 weeks of gestation in the stage I FGR manages to increase the rate of vaginal delivery compared with vaginal dinoprostone. Methods and analysisThis will be an open-labelled, randomised, parallel-group clinical trial to be held in five Spanish maternities. Women aged ≥18 years with singleton pregnancies complicated with stage I FGR (defined as the presence of at least one of these two criteria: (1) estimated fetal weight (EFW)

Abstract Background Since May 7 2022, mpox has been endemic in many countries which has attracted the attention of health authorities in various countries and made control decisions, in which vaccination is the mainstream strategy. However, the shortage of vaccine doses and the reduction of protective efficacy have led to unresolved issues such as vaccine allocation decisions and evaluation of transmission scale. Methods We developed an epidemiological model to describe the prevalence of the mpox virus in New York City and calibrated the model to match surveillance data from May 19 to November 3, 2022. Finally, we adjusted the model to simulate and compare several scenarios of non-vaccination and pre-pandemic vaccination. Results Relative to the status quo, if vaccination is not carried out, the number of new infections increases to about 385%, and the transmission time will be extended to about 350%, while if vaccinated before the epidemic, the number of new infections decreases to 94.2-96%. Conclusions The mpox outbreak in New York City may be linked to the Pride event. However, with current vaccine coverage, there will be no more large-scale outbreaks of mpox, even if there is another similar activity. For areas with limited vaccines, priority is given to high-risk groups in the age group [34–45] years as soon as possible. …

Abstract Background Viral neutralization (NT) assays can be used to determine the immune status of patients or assess the potency of candidate vaccines or therapeutic monoclonal antibodies (mAbs). Focus reduction neutralization test (FRNT) is a conventional neutralization test (cVNT) with superior specificity for measurement of neutralizing antibodies against a specific virus. Unfortunately, the application of FRNT to the chikungunya virus (CHIKV) involves a highly pathogenic bio-agent requiring biosafety level 3 (BSL3) facilities, which inevitably imposes high costs and limits accessibility. In this study, we evaluated a safe surrogate virus neutralization test (sVNT) that uses novel CHIKV replicon particles (VRPs) expressing eGFP and luciferase (Luc) to enable the rapid detection and quantification of neutralizing activity in clinical human serum samples. Methods This unmatched case-control validation study used serum samples from laboratory-confirmed cases of CHIKV (n = 19), dengue virus (DENV; n = 9), Japanese encephalitis virus (JEV; n = 5), and normal individuals (n = 20). We evaluated the effectiveness of sVNT, based on mosquito cell-derived CHIK VRPs (mos-CHIK VRPs), in detecting (eGFP) and quantifying (Luc) neutralizing activity, considering specificity, sensitivity, and reproducibility. We conducted correlation analysis between the proposed rapid method (20 h) versus FRNT assay (72 h). We also investigated the correlation between sVNT and FRNT in NT titrations in terms of Pearson’s correlation coefficient (r) and sigmoidal curve fitting. Results In NT screening assays, sVNT-eGFP screening achieved sensitivity and specificity of 100%. In quantitative neutralization assays, we observed a Pearson’s correlation coefficient of 0.83 for NT50 values between sVNT-Luc and FRNT. Conclusions Facile VRP-based sVNT within 24 h proved highly reliable in the identification and quantification of neutralizing activity against CHIKV in clinical serum samples. …

Abstract Background After recovering from the acute phase of COVID-19, some of the infected children manifest long COVID symptoms. The present study aims to identify long COVID symptoms in children and adolescents admitted to hospitals in Bushehr, Iran, during 2021 to 2023, and compare them with the non-affected group. Methods This historical cohort study with a population-based control group was conducted on 141 children and adolescents with COVID-19 hospitalized in Bushehr city hospitals and 141 non-affected peers. Out of 10 comprehensive health service centers in Bushehr city, 5 centers were selected by random sampling and the non-Covid-19 group was chosen from them (matched by gender and age with the affected group). The data were collected using the data recorded in the patients’ records, conducting telephone interviews and completing the prevalent long COVID symptom form. Data were analyzed using SPSS version 18. Descriptive statistics, Chi-square/Fisher’s exact tests, and stepwise logistic regression were used. Odds ratios (ORs) with 95% confidence intervals (CIs) were calculated, with p 

Abstract Background Pulmonary nocardiosis (PN) is a rare and opportunistic infection. This study aimed to analyze clinical, radiological, and microbiological features, treatment and outcome of PN in southern china. Methods Clinical, laboratory, imaging, treatment and outcome data of PN patients at two tertiary hospitals from January 1, 2018, to January 1, 2024 were collected. Factors associated with clinical outcomes were determined by multivariate logistic regression analysis. Results 67 PN patients including 53 with clinical improvement and 14 with treatment failure were enrolled. Bronchiectasis was the most common respiratory disease in patients with PN (31.3%). The major symptoms of PN were cough (89.6%) and sputum (79.1%). Lung nodules, bronchiectasis, consolidation, pleural involvement, mass, cavity, and lymph node enlargement were the frequent computed tomography findings of PN. Among the Nocardia species detected, N. farcinica was the most common pathogen. Neutrophil-to-lymphocyte ratio (OR = 1.052, p = 0.010), concurrent bacterial infection (OR = 7.706, p = 0.016), and the use of carbapenems (OR = 9.345, p = 0.023) were independently associated with poor prognosis in patients with PN. Conclusions This study provides important insights into the clinical features of PN in southern china. neutrophil-to-lymphocyte ratio, concurrent bacterial infection, and the use of carbapenems were independently associated with poor prognosis in patients with PN. …