Pattern Of Spread Research Articles

Enhancing clinical microbiology for genomic surveillance of antimicrobial resistance implementation in Africa.

Surveillance is essential in the fight against antimicrobial resistance (AMR), to monitor the extent of resistance, inform prevention, control measures, and evaluate intervention progress. Traditional surveillance methods based on phenotypic antimicrobial susceptibility data offer important but limited insights into resistance mechanisms, transmission networks, and spread patterns of resistant bacterial strains. Fortunately, genomic technologies are increasingly accessible and can overcome these limitations. Genomics has the potential to advance traditional bacteriology in routine diagnosis and surveillance, it often relies on the initial isolation of bacterial strains from clinical specimens using conventional culture methods. Culture-based phenotypic characteristics are essential for making inferences about newly recognized genomic patterns. The Africa CDC Pathogen Genomics Initiative (Africa PGI) aims to enhance disease surveillance and public health partnerships through integrated, cross-continent laboratory networks equipped with the tools, human resource capacity and data infrastructure to fully leverage critical genomic sequencing technologies. For genomic surveillance of AMR, it is essential to optimize routine clinical microbiology laboratory services that are weak in many African countries. In this review, we outline shortcomings in clinical microbiology laboratories across Africa that compromise pathogen genomic epidemiology. We emphasize the necessity of investing in bacteriology and enhancing leadership capacity to fully capitalize on the advantages offered by genomic antimicrobial resistance (AMR) surveillance.

Patterns of tau, amyloid and synuclein pathology in ageing, Alzheimer's disease and synucleinopathies.

Alzheimer's disease (AD) is neuropathologically defined by deposits of misfolded hyperphosphorylated tau (HP-tau) and β-amyloid. Lewy body (LB) dementia, which includes dementia with Lewy bodies (DLB) and Parkinson's disease dementia (PDD), is characterised pathologically by α-synuclein aggregates. HP-tau and β-amyloid can also occur as copathologies in LB dementia, and a diagnosis mixedAD/DLB can be made if present in sufficient quantities. We hypothesised the spread of these abnormal proteins selectively affects vulnerable areas, resulting in pathologic regional covariance that differentially associates with pre-mortem clinical characteristics. Our aims were to map regional quantitative pathology (HP-tau, β-amyloid, α-synuclein) and investigate the spatial distributions from tissue microarray (TMA) post-mortem samples across healthy aging, AD and LB dementia. The study involved 159 clinico-pathologically diagnosed human post-mortem brains (48 controls, 47 AD, 25 DLB, 20 mixedAD/DLB, 19 PDD). The burden of HP-tau, β-amyloid and α-synuclein was quantitatively assessed in cortical and subcortical areas. Principal components (PC) analysis was applied across all cases to determine the pattern nature of HP-tau, β-amyloid and α-synuclein. Further analyses explored the relationships of these pathological patterns with cognitive and symptom variables. Cortical (tauPC1) and temporolimbic (tauPC2) patterns were observed for HP-tau. For β-amyloid, a cortical-subcortical pattern (amylPC1) was identified. For α-synuclein, four patterns emerged: 'posterior temporal - occipital (synPC1)', 'anterior temporal-frontal (synPC2)', 'parieto-cingulate-insula (synPC3)', and 'frontostriatal-amygdala (synPC4)'. Distinct synPC scores were apparent among DLB, mixedAD/DLB and PDD, and may relate to different spreading patterns of α-synuclein pathology. In dementia, cognitive measures correlated with tauPC1, tauPC2 and amylPC1 pattern scores (P≤0.02), whereas such variables did not relate to α-synuclein parameters in these or combined LB dementia cases. Mediation analysis then revealed that in the presence of amylPC1, tauPC1 had a direct effect on global cognition in dementia (n=65, P=0.04), while tauPC1 mediated the relationship between amylPC1 and cognition through the indirect pathway (amylPC1→ tauPC1 → global cognition) (P<0.05). Lastly, in synucleinopathies, synPC1 and synPC4 pattern scores were associated with visual hallucinations and motor impairment, respectively (P=0.02). In conclusion, distinct patterns of α-synuclein pathology were apparent in LB dementia, which could explain some of the disease heterogeneity and differing spreading patterns among these conditions. Visual hallucinations and motor severity were associated with specific α-synuclein topographies in LB dementia that may be important to the clinical phenotype, and could, after necessary testing/validation, be integrated into semi-quantitative routine pathological assessment.

Duffy Binding Protein Ligand (PvDBP) gene duplication in Indian P. Vivax Malaria isolates: implication for malaria research.

Plasmodium vivax malaria poses a major global health challenge, fueled by the parasite's ability to establish chronic infections via dormant liver hypnozoites that enable immune evasion and show transmission resilience. A key virulence determinant of P. vivax blood-stage infection is the ligand-receptor interaction of infected erythrocytes mediated by the Duffy Binding Protein (PvDBP) ligand. Gene duplication events leading to increased PvDBP copy numbers have been documented in parasite populations in Cambodia, Brazil, and Sudan, but whether such changes exist in Indian isolates is not known. India shoulders a disproportionately high P. vivax burden in the world. DNA extracted from malaria-positive samples from a multisite survey was subjected to diagnostic PCR to evaluate PvDBP duplication. We identified PvDBP duplication at 18.6% frequency across various regions in India via diagnostic PCR. Both 'Cambodian-type' and 'Malagasy-type' duplication patterns were detected. PvDBP copy number variations associated with specific Duffy antigen receptor genotypes were correlated in the patient cohort. While PvDBP duplication was widespread, its geographic distribution varied, occurring most prevalently in northeastern regions of India. The presence of Duffy binding protein gene duplication in nearly one-fifth of P. vivax isolates in India may have significant epidemiological and clinical implications. This genetic variation could potentially impact, parasite fitness and invasion efficiency, possibly leading to higher parasitemia levels and immune evasion capabilities, which may affect the efficacy of natural immunity and vaccine development efforts and / or transmission dynamics if the duplication confers any advantage in mosquito stages. To fully understand these implications, we propose longitudinal studies tracking patients with and without PvDBP duplications, comparing clinical outcomes, parasitemia levels, and transmission rates. Additionally, spatial and temporal analyses of duplication frequency across India could reveal patterns of spread and potential selective pressures driving this genetic change.

Machine learning insights into regional dynamics and prevalence of COVID-19 variants in US health and human services regions

BackgroundThe COVID-19 pandemic arising from the emergence of SARS-CoV-2 in late 2019 has led to global devastation with millions of lives lost by January 2024. Despite the WHO’s declaration of the end of the global health emergency in May 2023, the virus persists, propelled by mutations. Variants continue to challenge vaccination efforts, underscoring the necessity for ongoing vigilance. This study aimed at contributing to a more data-driven approach to pandemic management by employing random forest regression to analyze regional variant prevalence.MethodsThis study utilized data from various sources including National COVID Cohort Collaborative database, Bureau of Transportation Statistics, World Weather Online, EPA, and US Census. Key variables include pollution, weather, travel patterns, and demographics. Preprocessing steps involved merging and normalization of datasets. Training data spanned from January 2021 to February 2023. The Random Forest (RF) Regressor was chosen for its accuracy in modeling. To prevent data leakage, time series splits were employed. Model performance was evaluated using metrics such as MSE and R-squared.ResultsThe Alpha variant was predominant in the Southeast, with less than 80% share even at its peak. Delta surged initially in Kansas City and maintained dominance there for over 5 months. Omicron subvariant BA.5 spread nationwide, becoming predominant across all Health and Human Services regions simultaneously, with New York seeing the earliest and fastest decline in its share. Variant XBB.1.5 concentrated more in the Northeast, but limited data hindered full analysis. Using RF Regressor, key features affecting spread patterns were identified, with high predictive accuracy. Each variant showed specific environmental correlations; for instance, Alpha with air quality index, Delta with ozone density, BA.5 with UV index, and XBB.1.5 with land area and income. Correlation analysis further highlighted variant-specific associations.ConclusionsThis research provides a comprehensive analysis of the regional distribution of COVID-19 variants, offering critical insights for devising targeted public health strategies. By utilizing machine learning, the study uncovers the complex factors contributing to variant spread and reveals how specific factors contribute to variant prevalence, offering insights crucial for pandemic management.

The effects of ventilation layout on cough droplet dynamics relating to seasonal influenza

The primary aim of this paper is to investigate airborne virus transmission in a typical meeting room relating to the heating, ventilation, and air conditioning (A.C.) systems. While the installation of 4-way cassette A.C. systems in offices and meeting rooms has become increasingly common, their efficiency in mitigating short-range airborne virus spread remains poorly understood. Addressing this gap is critical in the post-pandemic era, where understanding the limitations of various ventilation systems is paramount for public health. We systematically compare the performance of the 4-way cassette A.C., various configurations of mixing and displacement ventilation systems, and natural ventilation in controlling the spread of respiratory viruses. Our research uniquely integrates evaporation models to accurately simulate cough clouds' multiphase behavior under both quiescent and thermally influenced conditions. The study benchmarks these systems against two widely recognized ventilation standards (i.e., 5 air changes per hour and 10 l/s per person), offering evidence-based insights applicable across diverse indoor settings. Our findings reveal significant thermal effects in the quiescent case, resulting in 32.3%, 54.3%, and 8.0% changes in the axial, vertical, and lateral spread of the virus-laden droplets, respectively. Notably, the 0.5 m/s 4-way cassette A.C. system demonstrated superior performance, reducing the axial spread by 29.6% compared to other mechanical ventilation configurations. Furthermore, the role of exhaust outlets or doors was found to be critical in shaping the spread pattern in natural ventilation scenarios. This work can offer practical guidance to office workers, engineers, and public health officials on enhancing indoor airborne infection control.

A case study of the 2023 highly pathogenic avian influenza (HPAI) outbreak in tern (Sternidae) colonies on the east coast of the Republic of Ireland

ABSTRACT Capsule:HPAI H5N1 had a significant impact on breeding Common Terns Sterna hirundo, Arctic Terns Sterna paradisaea and Roseate Terns Sterna dougallii on the east coast of the Republic of Ireland (ROI) in 2023, with a lesser impact on Sandwich Terns Thalasseus sandvicensis and only two cases among Little Terns Sternula albifrons. Aims: To document the outbreak of HPAI H5N1 in the tern colonies on the east coast of ROI during the 2023 breeding season. Methods:Precautions were taken from the start of the breeding season, including personal protective equipment (PPE) and safe operating procedures. Regular meetings were held between BirdWatch Ireland and the National Parks and Wildlife Service (NPWS) to respond to the emerging situation. Once HPAI was confirmed in a colony, all ringing and nest visits were stopped. Carcass removal was carried out at all affected colonies and most carcasses were incinerated. Results: Common Terns suffered the highest mortality across all colonies in 2023, with smaller but notable numbers of dead Roseate Terns and Arctic Terns, but very few Sandwich Terns and only two Little Tern deaths were attributed to HPAI. Conclusion: Regular meetings between relevant organizations were invaluable in preparing for outbreaks and ensuring an adaptive approach as the situation changed over time and between colonies. There was no way of knowing if the actions taken were effective, as the pattern of virus spread between species and sites remains poorly understood. Future clarity over the role of various state agencies and other relevant bodies in responding to HPAI in wild birds, greater sharing of real-time information, and pre-arranged agreements to ensure rapid testing and disposal of carcasses, would be useful to ensure an effective response to future outbreaks.

Formulation and Physicochemical Evaluation of Spray Gel Containing Cordyline fruticosa L. Leaf Extract for Topical Delivery

Spray gel is a gel system applied through a spray pump, producing small or large liquid droplets. Cordyline fruticosa (L.) A. Cheval, commonly known as Andong Merah, is a plant with various medicinal properties, including wound healing activity attributed to its flavonoid content. This research aimed to formulate and evaluate the physicochemical properties of a spray gel containing Cordyline fruticosa leaf extract for topical delivery, focusing on the effects of different concentrations of Carbopol 940 as a gelling agent and sorbitol as a humectant. Cordyline fruticosa leaf extract was obtained by maceration using 96% ethanol. Three spray gel formulations were prepared, varying the concentrations of Carbopol 940 (0.4 g, 0.6 g, and 0.8 g) and sorbitol (5 ml, 7.5 ml, and 10 ml). The prepared spray gels were then subjected to physicochemical evaluation, including organoleptic tests (color, odor, and consistency), homogeneity tests, pH measurements, viscosity measurements, spray pattern analysis, and adhesion tests. All spray gel formulations exhibited acceptable physicochemical properties. The formulations were homogeneous, with a pH within the acceptable range for topical applications. The viscosity and adhesion properties varied with the concentrations of Carbopol 940 and sorbitol. The spray pattern analysis revealed a circular spread pattern, with the pressure required for spraying influenced by the viscosity of the formulation. The spray gel formulations containing Cordyline fruticosa leaf extract demonstrated good physicochemical qualities, indicating their potential suitability for topical delivery. Further studies are recommended to optimize the formulation for enhanced stability and therapeutic efficacy.

Advanced ultrasound diagnosis of extrahepatic bile duct lesions.

Ultrasound (US) has high specificity and sensitivity, and it should be performed first for patients with suspicion of biliary tract cancer. However, the complicated anatomy in addition to the gas images makes it difficult to delineate the entire extrahepatic bile duct (EHBD). The keys to depiction of EHBD are the "J" shape manipulation in the left lateral decubitus position and the use of magnified images with high-frequency transducers. Furthermore, indirect findings such as gallbladder (GB) distension, BD dilatation, and debris echo in the GB and BD are also important for detecting occult lesions, particularly in the ampullary region of Vater. For the differential diagnosis of BD wall thickening, the spreading pattern in the long and short axial directions should be assessed first. Then, the characteristics of the innermost hyperechoic layer (IHL) and outermost hyperechoic layer (OHL) should be evaluated. Asymmetrical wall thickening, absence of IHL, and presence of irregularity or discontinuity in OHL are characteristic patterns of cholangiocarcinoma (CCA). Because CCA is the most common BD polypoid lesion, it is important to diagnose tumor extension and depth invasion in addition to differential diagnosis. Nodular-type CCA is usually hypoechoic and more likely to invade vertically. In contrast, papillary-type CCA is often hyperechoic and extends laterally. Contrast‑enhanced US may be useful for evaluating these findings. However, if the possibility of CCA cannot be ruled out or a definitive diagnosis is needed, a transpapillary biopsy or endoscopic US-guided tissue acquisition should be considered.

Features that matter: Evolutionary signatures can predict viral transmission routes.

Routes of virus transmission between hosts are key to understanding viral epidemiology. Different routes have large effects on viral ecology, and likelihood and rate of transmission; for example, respiratory and vector-borne viruses together encompass the majority of rapid outbreaks and high-consequence animal and plant epidemics. However, determining the specific transmission route(s) can take months to years, delaying mitigation efforts. Here, we identify the vial features and evolutionary signatures which are predictive of viral transmission routes and use them to predict potential routes for fully-sequenced viruses in silico and rapidly, for both viruses with no observed routes, as well as viruses with missing routes. This was achieved by compiling a dataset of 24,953 virus-host associations with 81 defined transmission routes, constructing a hierarchy of virus transmission encompassing those routes and 42 higher-order modes, and engineering 446 predictive features from three complementary perspectives. We integrated those data and features to train 98 independent ensembles of LightGBM classifiers. We found that all features contributed to the prediction for at least one of the routes and/or modes of transmission, demonstrating the utility of our broad multi-perspective approach. Our framework achieved ROC-AUC = 0.991, and F1-score = 0.855 across all included transmission routes and modes, and was able to achieve high levels of predictive performance for high-consequence respiratory (ROC-AUC = 0.990, and F1-score = 0.864) and vector-borne transmission (ROC-AUC = 0.997, and F1-score = 0.921). Our framework ranks the viral features in order of their contribution to prediction, per transmission route, and hence identifies the genomic evolutionary signatures associated with each route. Together with the more matured field of viral host-range prediction, our predictive framework could: provide early insights into the potential for, and pattern of viral spread; facilitate rapid response with appropriate measures; and significantly triage the time-consuming investigations to confirm the likely routes of transmission.

Enhancing non-invasive pre-surgical evaluation through functional connectivity and graph theory in drug-resistant focal epilepsy

BackgroundEpilepsy, characterized as a network disorder, involves widely distributed areas following seizure propagation from a limited onset zone. Accurate delineation of the epileptogenic zone (EZ) is crucial for successful surgery in drug-resistant focal epilepsy. While visual analysis of scalp electroencephalogram (EEG) primarily elucidates seizure spreading patterns, we employed brain connectivity techniques and graph theory principles during the pre-ictal to ictal transition to define the epileptogenic network. MethodCortical sources were reconstructed from 40-channel scalp EEG in five patients during pre-surgical evaluation for focal drug-resistant epilepsy. Temporal Granger connectivity was estimated ten seconds before seizure and at seizure onset. Results have been analyzed using some centrality indices taken from Graph theory (Outdegree, Hubness). A new lateralization index is proposed by taking into account the sum of the most relevant hubness values across left and right regions of interest. ResultsIn three patients with positive surgical outcomes, analysis of the most relevant Hubness regions closely aligned with clinical hypotheses, demonstrating consistency in EZ lateralization and location. In one patient, the method provides unreliable results due to the abundant movement artifacts preceding the seizure. In a fifth patient with poor surgical outcome, the proposed method suggests a wider epileptic network compared with the clinically suspected EZ, providing intriguing new indications beyond those obtained with traditional electro-clinical analysis. ConclusionsThe proposed method could serve as an additional tool during pre-surgical non-invasive evaluation, complementing data obtained from EEG visual inspection. It represents a first step toward a more sophisticated analysis of seizure onset based on connectivity imbalances, electrical propagation, and graph theory principles.

Reinterpreting Chronic Wasting Disease Emergence in the USA in Light of Historical Surveillance Limitations.

We estimated the probabilities of detecting one or more chronic wasting disease (CWD) cases (Pdet) in free-ranging cervids in the continental US during 1997 - 2001. Based on sample sizes reported by respective state authorities at the time and a target for detectable apparent prevalence (i.e., a design prevalence) of 0.001 (one positive per 1,000 animals statewide), estimated Pdet were <50% for 39/46 states where CWD had not been detected in the wild prior to 1997 and were <5% in 20/26 states located east of the Mississippi River. The survey designs and sample sizes reported by most states prior to 2002 would have yielded exceedingly small detection probabilities for focal CWD outbreaks. Although most CWD foci in the US were first detected in 2002 or after, the data presented here and elsewhere suggest it is plausible that an unknown number of these-some established perhaps decades earlier-were already present but had simply eluded detection. These data highlight uncertainty regarding timelines for CWD emergence in the US. Accepting-and to the extent possible quantifying-uncertainty in the historical distribution of CWD throughout the US seems a necessary foundation for better understanding its emergence, its drivers and patterns of spread, and its response to various interventions-past, present, and future.

Primary cervical malignant melanoma: A rare entity case report

Primary malignant melanoma of female genital tract is rare, and rarer are those arising from the cervix. Pathogenesis involving BRAF &amp; RAS pathway whether holds true for these tumours as well is a question yet to be answered. Patients come with bleeding PV as their main complain. To reach at the diagnosis of primary malignant melanoma of cervix it is important to have clinical examination with speculum assessment along with pathological evaluation of the lesion. Case presentation: We report a case of 49/F, Para 1, living 1 (P1L1), who was postmenopausal since 13 years with complains of white discharge and bleeding per vaginum since 1 week. Per vaginal examination revealed a greysih white brown growth in the cervix involving vagina. Biopsy and immunohistochemistry showed malignant melanoma (MM). Conclusion: Clinical presentation and spread pattern of primary MM of cervix is similar to that of cervical carcinoma and clinically diagnosing as melanoma is even more difficult when more than 50% tumours are amelanotic. But early diagnosis is need of the hour as these cases have poor prognosis with no standardize treatment protocol available. The FIGO staging system has been accepted by most researchers. Reporting of such cases is pertinent so as to allow the study of this extremely rare tumour for bringing up the correct and new therapies for early treatment.

Liquidity Preference, Interest Rate Spread, and the Transformation of the US Financial System

This article examines empirical patterns of interest rate spreads between yields on long-term corporate bonds and the Federal Funds Rate (FFR) in the United States over the period from 1960 through 2023. Since the early 1980s, discernible patterns of interest spreads have emerged, revealing marked deviations in corporate bond yields from the FFR. We focus on financial market forces particularly arising from financial intermediaries in analyzing these patterns. To this end, the article develops a theoretical framework based on the concept of liquidity preference in Keynes’s 1937 papers and the works of Hyman Minsky and Victoria Chick. We also conduct cointegration analyses for corporate bond yields, the FFR, and financial intermediaries’ leverage ratios. Overall, our empirical results indicate that the relationship between the FFR and corporate bond yields—particularly with respect to their long-run relationship and interest rate markups—has markedly changed since the 1980s and is significantly affected by financial intermediaries’ asset/capital leverage ratios. As a policy implication, regulatory reforms aimed at enhancing the Federal Reserve Bank’s capacity to steer long-term rates and contain intermediaries’ balance sheet leverage, particularly those centered on risky asset trading to increase gains from price differentials, are required JEL Classification: B26, E11, E43, E52

Investigation of probable Salmonella outbreak in the National Cancer Institute, Sri Lanka

Abstract Background An outbreak is the occurrence of case of disease in excess of what would normally be expected in a defined community. Outbreaks in immune compromised population can lead to devastating morbidity and mortality. Infection prevention and control (IPC) team has a pivotal role in both averting and managing outbreaks in health care settings. There were 7 cases of Salmonella spp, isolated from blood and stools since 12th July 2023 up to 11th August. Assuming of a possible outbreak, IPC team decided to investigate in order to find a possible source for the outbreak. Methods As soon as the outbreak was confirmed, immediate relevant control measures were taken after studying the available information. Working case definitions was constructed with clinical criteria and laboratory criteria with restrictions by time, place and person. Different categories of case definitions were used as the diagnosis was uncertain, such as “confirmed”, “probable” and “possible”. Active surveillance was conducted to collect information on additional case. Data collection tool was prepared with demographic information, clinical information and risk factor information. Then more cases were detected and line listing was created to organize important information for the investigation. Epidemic curve was drawn to see the pattern of spread and it was an irregularly jagged curve which interprets as intermittent common source epidemic. Specific control and prevention measures were implemented. Inquiries were made regarding the dietary intake of the patients over the last seven days and it was difficult to find a common source of food item however, all patients have consumed food prepared in the hospital kitchen. Therefore an audit was conducted in the hospital kitchen to identify probable source. Kitchen staff was educated about the food safety measures and personal hygiene. Kitchen staff was screened for Salmonella carrier state in their stool. Quality of the water from the kitchen and wards was checked for fecal contamination. No residual food was available for microbiological testing. Hypothesis was formulated to gather information after discussion with patients and staff. Findings were communicated to all relevant parties including Director and clinicians in the hospital. Salmonella isolates were sent to the Enteric Reference Laboratory, Medical Research Institute, Colombo for serotype identification. Results It was difficult find a common source. There were some malpractices in the kitchen and those were corrected immediately. Water quality in the hospital was satisfactory. Kitchen staff were not colonized with salmonella. However egg supplier to the kitchen was changed recently and eggs were supplied last minute and the eggs were not washed prior to cooking. Three isolates sent to the reference laboratory were identified as Salmonella Weltevreden, one as Salmonella Enteritidis, while the remaining three isolates could not be identified to serotype level with the available resources. Conclusion The exact contributory factor to the outbreak remained elusive. However, numerous food safety issues which can lead to cross contamination during the preparation of food were identified. Consequently, prompt investigation and control measures are essential to prevent further food borne outbreaks.

Analysis of Spatial Distribution of Maternal Death Cases in the Special Region of Yogyakarta Province

Maternal mortality is an important indicator of improving health in a country which is included in the target of achieving the Subtainable Development Goals (SDGs). The Maternal Mortality Rate (MMR) in Indonesia in 2018 was still high at around 305/100,000 KH. Maternal mortality in the Yogyakarta Special Region Province experienced a significant increase in 2021. Objective: to analyze the Maternal Mortality Rate (MMR) in the Yogyakarta Special Region Province and determine the relationship between spatial accessibility of Community Health Centers. Method: This is a quantitative descriptive study to see the pattern of distribution of maternal mortality cases using GIS using ArcGis. Results: Maternal deaths in 2020-2022 have a spreading pattern with the highest cases being in Banguntapan sub-district and the distribution of health centers has been evenly distributed in each sub-district. Conclusion: Maternal death cases occur almost in all sub-districts, with a widespread distribution pattern. The highest case in the last three years occurred in 2021 due to exposure to Covid-19. The distribution of health centers is evenly distributed, but hospitals are still concentrated in Sleman district and Yogyakarta city.

Local patterns of spread of influenza A H3N2 virus in coastal Kenya over a 1-year period revealed through virus sequence data.

The patterns of spread of influenza A viruses in local populations in tropical and sub-tropical regions are unclear due to sparsity of representative spatiotemporal sequence data. We sequenced and analyzed 58 influenza A(H3N2) virus genomes sampled between December 2015 and December 2016 from nine health facilities within the Kilifi Health and Demographic Surveillance System (KHDSS), a predominantly rural region, covering approximately 891km2 along the Kenyan coastline. The genomes were compared with 1571 contemporaneous global sequences from 75 countries. We observed at least five independent introductions of A(H3N2) viruses into the region during the one-year period, with the importations originating from Africa, Europe, and North America. We also inferred 23 virus location transition events between the nine facilities included in the study. International virus imports into the study area were captured at the facilities of Chasimba, Matsangoni, Mtondia, and Mavueni, while all four exports from the region were captured from the Chasimba facility, all occurring to Africa destinations. A strong spatial clustering of virus strains at all locations was observed associated with local evolution. Our study shows that influenza A(H3N2) virus epidemics in local populations appear to be characterized by limited introductions followed by significant local spread and evolution. Knowledge of the viral lineages that circulate within specific populations in understudied tropical and subtropical regions is required to understand the full diversity and global ecology of influenza viruses and to inform vaccination strategies within these populations.

A single amplified genome catalog reveals the dynamics of mobilome and resistome in the human microbiome

BackgroundThe increase in metagenome-assembled genomes (MAGs) has advanced our understanding of the functional characterization and taxonomic assignment within the human microbiome. However, MAGs, as population consensus genomes, often aggregate heterogeneity among species and strains, thereby obfuscating the precise relationships between microbial hosts and mobile genetic elements (MGEs). In contrast, single amplified genomes (SAGs) derived via single-cell genome sequencing can capture individual genomic content, including MGEs.ResultsWe introduce the first substantial SAG dataset (bbsag20) from the human oral and gut microbiome, comprising 17,202 SAGs above medium-quality without co-assembly. This collection unveils a diversity of bacterial lineages across 312 oral and 647 gut species, demonstrating different taxonomic compositions from MAGs. Moreover, the SAGs showed cellular-level evidence of the translocation of oral bacteria to the gut. We also identified broad-host-range MGEs harboring antibiotic resistance genes (ARGs), which were not detected in the MAGs.ConclusionsThe difference in taxonomic composition between SAGs and MAGs indicates that combining both methods would be effective in expanding the genome catalog. By connecting mobilomes and resistomes in individual samples, SAGs could meticulously chart a dynamic network of ARGs on MGEs, pinpointing potential ARG reservoirs and their spreading patterns in the microbial community.DX-3H-wDoVG35Spx9tFU_UVideo

Integrated analyses of the transmission history of SARS-CoV-2 and its association with molecular evolution of the virus underlining the pandemic outbreaks in Italy, 2019-2023

BackgroundItaly was significantly affected by the COVID-19 pandemic, experiencing multiple waves of infection following the sequential emergence of new variants. Understanding the transmission patterns and evolution of SARS-CoV-2 is vital for future preparedness. MethodsWe conducted an analysis of viral genome sequences, integrating epidemiological and phylodynamic approaches, to characterize how SARS-CoV-2 variants have spread within the country. ResultsOur findings indicate bidirectional international transmission, with Italy transitioning between importing and exporting the virus. Italy experienced four distinct epidemic waves, each associated with a significant reduction in fatalities from 2021 to 2023. These waves were primarily driven by the emergence of VOCs such as Alpha, Delta, and Omicron, which were reflected in observed transmission dynamics and effectiveness of public health measures. ConclusionsThe changing patterns of viral spread and variant prevalence throughout Italy's pandemic response underscore the continued importance of flexible public health strategies and genomic surveillance, both of which are crucial for tracking the evolution of variants and adapting control measures effectively to ensure preparedness for future outbreaks.

Optimal Setup and Parameters of Diffusion-Weighted Magnetic Resonance Imaging for Translational Evaluation of a Tumor Progression Model for Soft Tissue Sarcomas

PurposeDefining a microscopic tumor infiltration boundary is critical to the success of radiation therapy. Currently, radiation oncologists use margins to geometrically expand the visible tumor for radiation treatment planning in soft tissue sarcomas (STS). Image-based models of tumor progression would be critical to personalize treatment radiation field to the pattern of sarcoma spread. Evaluation of these models is necessary to demonstrate feasibility in the clinical setting. This study presents an imaging protocol for the preclinical evaluation of a tumor progression model in extremity STS. MethodsWe recruited seven healthy volunteers and acquired diffusion-weighted MRI (DW-MRI) images of the thigh on an MRI scanner used for imaging cancer patients in a radiation oncology department. We developed a protocol, which includes positioning the patient, configuring the RF coils, and setting the diffusion-weighted MRI sequence parameters. To find the optimal parameter configuration, the image signal-to-noise ratio (SNR) and the directional variability (DV) of the principal eigenvector of the diffusion tensor were calculated. ResultsThe mean SNR across all trials and 12 thigh muscles was 41 with a range of 12 to 72. The mean DV was 13° and ranged from 11° to 23°. The longest scan time was 22 min 58 s and the shortest 11 min 46 s. For the high-resolution image with a voxel volume of 1.3×1.3×6 mm3 and 38 slices, the optimal parameters were found to be a repetition time of 8000 ms, 12 signal averages, and 6 gradient directions. This configuration resulted in a scan time of 11 min 46 s, an SNR of 34, and a DV of 13°. ConclusionsA DW-MRI scan duration acceptable for imaging cancer patients was achieved with an image quality suitable for reproducible modeling of tumor infiltration. The developed protocol can be used for preclinical evaluation in STS patients.

Spatial distribution of poultry farms using point pattern modelling: A method to address livestock environmental impacts and disease transmission risks.

The distribution of farm locations and sizes is paramount to characterize patterns of disease spread. With some regions undergoing rapid intensification of livestock production, resulting in increased clustering of farms in peri-urban areas, measuring changes in the spatial distribution of farms is crucial to design effective interventions. However, those data are not available in many countries, their generation being resource-intensive. Here, we develop a farm distribution model (FDM), which allows the prediction of locations and sizes of poultry farms in countries with scarce data. The model combines (i) a Log-Gaussian Cox process model to simulate the farm distribution as a spatial Poisson point process, and (ii) a random forest model to simulate farm sizes (i.e. the number of animals per farm). Spatial predictors were used to calibrate the FDM on intensive broiler and layer farm distributions in Bangladesh, Gujarat (Indian state) and Thailand. The FDM yielded realistic farm distributions in terms of spatial clustering, farm locations and sizes, while providing insights on the factors influencing these distributions. Finally, we illustrate the relevance of modelling realistic farm distributions in the context of epidemic spread by simulating pathogen transmission on an array of spatial distributions of farms. We found that farm distributions generated from the FDM yielded spreading patterns consistent with simulations using observed data, while random point patterns underestimated the probability of large outbreaks. Indeed, spatial clustering increases vulnerability to epidemics, highlighting the need to account for it in epidemiological modelling studies. As the FDM maintains a realistic distribution of farm location and sizes, its use to inform mathematical models of disease transmission is particularly relevant for regions where these data are not available.