Influence of base designs on the manufacturing accuracy of vat-polymerized diagnostic casts using two different technologies.

STATEMENT OF PROBLEM: Diagnostic casts can incorporate different base designs and be manufactured using different vat-polymerization technologies. However, the influence of the interrelation between the base design and the 3D printing technology on the casts' final accuracy remains unclear. PURPOSE: The purpose of this in vitro study was to assess the influence of different base designs of 3D printed casts on the accuracy of 2 vat-polymerization technologies. MATERIAL AND METHODS: A digital maxillary cast was obtained and used to generate 3 different base designs: solid (S group), honeycombed (HC group), and hollow (H group). The HC and H groups were subdivided based on the wall thickness of the cast design, resulting in 2 subgroups with thicknesses of 1 mm (HC1 and H1) and 2 mm (HC2 and H2) (N=100, n=10). Eleven reference cubes were added to each specimen for subsequent measurements. Specimens were manufactured by using 2 vat-polymerization 3D printers: Nextdent 5100 (ND group) and Sonic Mini 4K (SM4K group) and a resin material suitable for both 3D printers (Nextdent Model 2.0). A coordinate measuring machine quantified the linear and 3-dimensional discrepancies between the digital cast and each reference specimen. Trueness was defined as the average absolute dimensional discrepancy between the virtual cast and the specimens produced through additive manufacturing (AM), while precision was delineated as the standard deviation in dimensional discrepancies between the digital cast and the AM specimens. The data were analyzed using the Kruskal-Wallis and Mann-Whitney U pairwise comparison tests (α=.05). RESULTS: For the NextDent group the trueness ranged from 21.83 µm to 28.35 µm, and the precision ranged from 17.82 µm to 37.70 µm. For the Phrozen group, the trueness ranged from 45.15 µm to 64.51 µm, and the precision ranged from 33.51 µm to 48.92 µm. The Kruskal-Wallis test showed significant differences on the x-, y-, and z-axes and in the 3D discrepancy (all P<.001). On the x-axis, the Mann-Whitney U test showed significant differences for the Phrozen group between the H-2 and H-1 groups (P=.001), H-2 and S groups (P<.001), and HC-2 and S groups (P=.012). On the y-axis, significant differences were found in the Phrozen group between the H-2 and H-1 groups (P=.001), the H-2 and S, H-1 and HC-1, and HC-1 and S groups (P<.001), the H-1 and HC-2 groups (P=.007), and the HC-2 and S groups (P=.009). The NextDent group exhibited significant differences, particularly among the HC-1 and H-2 groups (P=.004), H-1 (P=.020), and HC-2 (P=.001) groups; and on the z-axis significant differences were found in the Phrozen group between the H-2 and H-1 and S groups and the HC-2 group and H-1 and S groups (both P<.001). In the NextDent group, significant differences were found between the H-2 and HC-2 (P=.047) and HC-1 (P=.028) groups. For the 3D discrepancy analysis, significant differences were found in the Phrozen group between the H-2 and H-1 and S groups (P<.001), the H-1 and HC-2 groups (P=.001), the S and HC-1 and HC-2 groups (P<.001), and the H-1 and HC-1 groups (P=.002). In the NextDent group, significant differences were observed between the H-2 and HC-1 groups (P=.012). CONCLUSIONS: The accuracy of digital casts depends on the manufacturing trinomial and base design of the casts. The honeycomb and hollow based designs provided the highest accuracy in the NextDent and Phrozen groups respectively for the material polymer tested. All specimens fell in the clinically acceptable range.

Modified Oblique Lobenhoffer (MOL) approach for posterolateral and posteromedial column access in tibial plateau fractures: a detailed cadaveric anatomical study.

BACKGROUND: Tibial plateau fractures involving posteromedial (PM) and posterolateral (PL) columns are complex injuries that require an appropriate approach. The management of the PL column in these cases can be controversial, and limitations using deep posteromedial interval approaches have been referenced. In this paper, a modification of the Lobenhoffer approach, designed to optimize the access to the PL column, is described in detail. The aim of this study was to assess the feasibility of this approach in a cadaveric anatomical study. MATERIALS AND METHODS: In total, five fresh-frozen cadaveric specimens were used for detailed anatomical study surrounding the approach. Relationships with cutaneous and deep neurovascular structures were evaluated. The exposure area of the PL and PM columns using this approach was assessed. RESULTS: The cadaveric study showed safe and adequate exposure. Oblique skin and fascia incision just medial to the posterior midline was safe to protect the medial sural cutaneous nerve and the small saphenous vein. Elevation of the popliteus and tibialis posterior muscles offered safe protection of the anterior tibial artery and popliteal neurovascular bundle during retractor placement. Adequate full proximal exposure of the PM and PL columns, including the posterolateral lateral (PLL) and posterolateral central (PLC) segments, was obtained in all specimens. CONCLUSIONS: The Modified Oblique Lobenhoffer (MOL) approach can be a feasible option to access PL and PM columns in tibial plateau fractures. LEVEL OF EVIDENCE: IV.

Translational kinetic-pharmacodynamics of mRNA-6231, an investigational mRNA therapeutic encoding mutein interleukin-2.

Regulatory T cells (Tregs) are essential for maintaining immune homeostasis by serving as negative regulators of adaptive immune system effector cell responses. Reduced production or function of Tregs has been implicated in several human autoimmune diseases. The cytokine interleukin 2 plays a central role in promoting Treg differentiation, survival, and function in vivo and may therefore have therapeutic benefits for autoimmune diseases. mRNA-6231 is an investigational, lipid nanoparticle-encapsulated, mRNA-based therapy that encodes a modified human interleukin 2 mutein fused to human serum albumin (HSA-IL2m). Herein, we report the development of a semi-mechanistic kinetic-pharmacodynamic model to quantify the relationship between subcutaneous dose(s) of mRNA-6231, HSA-IL2m protein expression, and Treg expansion in nonhuman primates. The nonclinical kinetic-pharmacodynamic model was extrapolated to humans using allometric scaling principles and the physiological basis of pharmacological mechanisms to predict the clinical response to therapy a priori. Model-based simulations were used to inform the dose selection and design of the first-in-human clinical study (NCT04916431). The modeling approach used to predict human responses was validated when data became available from the phase I clinical study. This validation indicates that the approach is valuable in informing clinical decision-making.

A Proposal for Neurography Referral in Patients with Carpal Tunnel Syndrome Based on Clinical Symptoms and Demographic Variables of 797 Patients.

The clinical manifestation of median nerve entrapment at the carpal tunnel level is known as carpal tunnel syndrome (CTS). Electroneurography (ENG) is considered the gold standard in CTS evaluation. We conducted a retrospective study and analyzed some clinical and demographic variables, relating them to the degree of neuropathy using ENG, to better understand the role of ENG in this very common disease. We studied 816 patients referred to our service for neurographic evaluation. Their symptoms were classified as compatible with CTS (cCTS) (n = 646) and atypical for CTS (aCTS) (n = 170). A blind ENG was performed on 797 patients. Patient characteristics were coded as variables and analyzed to study whether they could predict neuropathy severity (sensory and motor involvement or grade ≥ 3 in our classification). We found a correlation between typical symptomatology, age over 50 years, male gender, positivity of Phalen's maneuver and Tinel's sign, and a neuropathy grade ≥ 3. We also found a correlation with CTS in the contralateral hand if the other hand showed neuropathy, despite the lack of symptoms in this hand. We propose a practical algorithm for ENG referral based on clinical symptoms, demographic factors, and neurophysiological variables.

Microwave-Mediated Synthesis of Lead-Free Cesium Titanium Bromide Double Perovskite: A Sustainable Approach.

Theoretical studies have identified cesium titanium bromide (Cs2TiBr6), a vacancy-ordered double perovskite, as a promising lead-free and earth-abundant candidate to replace Pb-based perovskites in photovoltaics. Our research is focused on overcoming the limitations associated with the current Cs2TiBr6 syntheses, which often involve high-vacuum and high-temperature evaporation techniques, high-energy milling, or intricate multistep solution processes conducted under an inert atmosphere, constraints that hinder industrial scalability. This study presents a straightforward, low-energy, and scalable solution procedure using microwave radiation to induce the formation of highly crystalline Cs2TiBr6 in a polar solvent. This methodology, where the choice of the solvent plays a crucial role, not only reduces the energy costs associated with perovskite production but also imparts exceptional stability to the resulting solid, in comparison with previous reports. This is a critical prerequisite for any technological advancement. The low-defective material demonstrates unprecedented structural stability under various stimuli such as moisture, oxygen, elevated temperatures (over 130 °C), and continuous exposure to white light illumination. In summary, our study represents an important step forward in the efficient and cost-effective synthesis of Cs2TiBr6, offering a compelling solution for the development of eco-friendly, earth-abundant Pb-free perovskite materials.

Largest comparison between onset and relapses of acquired thrombotic thrombocytopenic purpura reveals severe neurological involvement and worse analytic parameters at debut.

It has been proposed that the onset of Acquired Thrombotic Thrombocytopenic Purpura (iTTP) is more severe than subsequent relapses; however, existing studies have limitations. We conducted a retrospective observational study to compare analytical and clinical severity of onset and relapse aTTP cases between 2012 and 2023. A total of 370 episodes of aTTP were analyzed, comprising 272 at initial diagnosis and 98 relapses. At onset, analytical parameters indicative of severity (low hemoglobin, low platelet count, and increased LDH) were significantly worse; patients had severe neurological symptoms (p<0.001) and ≥ 3 points in the TMA mortality score (p<0.001). In conclusion, the onset of aTTP is associated with worse analytical parameters and severe neurological involvement.

Community-acquired Staphylococcus aureus skin and soft tissue infection risk assessment using hotspot analysis and risk maps: the case of California emergency departments.

BACKGROUND: Community-acquired Staphylococcus aureus (CA-Sa) skin and soft tissue infections (SSTIs) are historically associated with densely populated urban areas experiencing high poverty rates, intravenous drug use, and homelessness. However, the epidemiology of CA-Sa SSTIs in the United States has been poorly understood since the plateau of the Community-acquired Methicillin-resistant Staphylococcus aureus epidemic in 2010. This study examines the spatial variation of CA-Sa SSTIs in a large, geographically heterogeneous population and identifies neighborhood characteristics associated with increased infection risk. METHODS: Using a unique neighborhood boundary, California Medical Service Study Areas, a hotspot analysis, and estimates of neighborhood infection risk ratios were conducted for all CA-Sa SSTIs presented in non-Federal California emergency departments between 2016 and 2019. A Bayesian Poisson regression model evaluated the association between neighborhood-level infection risk and population structure, neighborhood poverty rates, and being a healthcare shortage area. RESULTS: Emergency departments in more rural and mountainous parts of California experienced a higher burden of CA-Sa SSTIs between 2016 and 2019. Neighborhoods with high infection rates were more likely to have a high percentage of adults living below the federal poverty level and be a designated healthcare shortage area. Measures of population structure were not associated with infection risk in California neighborhoods. CONCLUSIONS: Our results highlight a potential change in the epidemiology of CA-Sa SSTIs in California emergency departments. Future studies should investigate the CA-Sa burden in other geographies to identify whether this shift in epidemiology holds across other states and populations. Further, a more thorough evaluation of potential mechanisms for the clustering of infections seen across California neighborhoods is needed.

Novel species of Triatoma (Hemiptera: Reduviidae) identified in a case of vectorial transmission of Chagas disease in northern Belize.

Chagas disease is a leading cause of non-ischemic cardiomyopathy in endemic regions of Central and South America. In Belize, Triatoma dimidiata sensu lato has been identified as the predominate taxon but vectorial transmission of Chagas disease is considered to be rare in the country. We recently identified an acute case of vector-borne Chagas disease in the northern region of Belize. Here we present a subsequent investigation of triatomines collected around the case-patient's home. We identified yet undescribed species, closely related to Triatoma huehuetenanguensis vector by molecular systematics methods occurring in the peridomestic environment. The identification of a T. cruzi-positive, novel species of Triatoma in Belize indicates an increased risk of transmission to humans in the region and warrants expanded surveillance and further investigation.

Antimicrobial Susceptibility in Respiratory Pathogens and Farm and Animal Variables in Weaned California Dairy Heifers: Logistic Regression and Bayesian Network Analyses.

Weaned dairy heifers are a relatively understudied production group. Bovine respiratory disease (BRD) is the most common cause of antimicrobial drug (AMD) use, morbidity, and mortality in this production group. The study of antimicrobial resistance (AMR) is complicated because many variables that may affect AMR are related. This study generates hypotheses regarding the farm- and animal-level variables (e.g., vaccination, lane cleaning, and AMD use practices) that may be associated with AMR in respiratory isolates from weaned dairy heifers. A cross-sectional study was performed using survey data and respiratory isolates (Pasteurella multocida, Mannheimia haemolytica, and Histophilus somni) collected from 341 weaned dairy heifers on six farms in California. Logistic regression and Bayesian network analyses were used to evaluate the associations between farm- and animal-level variables with minimum inhibitory concentration (MIC) classification of respiratory isolates against 11 AMDs. Farm-level variables associated with MIC classification of respiratory isolates included the number of source farms of a calf-rearing facility, whether the farm practiced onsite milking, the use of lagoon water for flush lane cleaning, and respiratory and pinkeye vaccination practices. Animal-level variables associated with a MIC classification included whether the calf was BRD-score-positive and time since the last phenicol treatment.

The peroxisome protein translocation machinery is developmentally regulated in the fungus Podospora anserina.

IMPORTANCE: Sexual reproduction allows eukaryotic organisms to produce genetically diverse progeny. This process relies on meiosis, a reductional division that enables ploidy maintenance and genetic recombination. Meiotic differentiation also involves the renewal of cell functioning to promote offspring rejuvenation. Research in the model fungus Podospora anserina has shown that this process involves a complex regulation of the function and dynamics of different organelles, including peroxisomes. These organelles are critical for meiosis induction and play further significant roles in meiotic development. Here we show that PEX13-a key constituent of the protein conduit through which the proteins defining peroxisome function reach into the organelle-is subject to a developmental regulation that almost certainly involves its selective ubiquitination-dependent removal and that modulates its abundance throughout meiotic development and at different sexual differentiation processes. Our results show that meiotic development involves a complex developmental regulation of the peroxisome protein translocation system.

Surveillance of Flea-Borne Typhus in California, 2011-2019.

Flea-borne typhus (FBT), also referred to as murine typhus, is an acute febrile disease in humans caused by the bacteria Rickettsia typhi. Currently, cases of FBT are reported for public health surveillance purposes (i.e., to detect incidence and outbreaks) in a few U.S. states. In California, healthcare providers and testing laboratories are mandated to report to their respective local public health jurisdictions whenever R. typhi or antibodies reactive to R. typhi are detected in a patient, who then report cases to state health department. In this study, we characterize the epidemiology of flea-borne typhus cases in California from 2011 to 2019. A total of 881 cases were reported during this period, with most cases reported among residents of Los Angeles and Orange Counties (97%). Demographics, animal exposures, and clinical courses for case patients were summarized. Additionally, spatiotemporal cluster analyses pointed to five areas in southern California with persistent FBT transmission.

Vaccination and Nutritional Outcomes of Hemodialysis Patients Infected With SARS-CoV-2.

BACKGROUND: Patients on hemodialysis are particularly vulnerable to COVID-19 and may have a reduced response to vaccination because of a decreased immune response. The nutritional status before or during the infection could also impact on the clinical effectiveness of vaccination. OBJECTIVES: We aim to describe the evolution of clinical and nutritional biomarkers of hemodialysis patients infected with SARS-CoV-2 and to assess their association with vaccination status. METHODS: An observational, analytic, longitudinal, retrospective multicenter study was carried out in 82 patients on hemodialysis with SARS-CoV-2 infection. Nutritional status was assessed using the Geriatric Nutritional Risk Index (GNRI), anthropometry, and biochemical parameters. The association of the vaccine doses with clinical- and nutritional-related variables was also evaluated. RESULTS: The percentage of vaccinated patients was similar to that of nonvaccinated patients. Before infection, most of the patients were malnourished. They presented lower albumin, creatinine, and urea levels than the well-nourished patients. Significant deterioration of nutritional status after infection was evidenced considering GNRI score, dry weight, and body mass index. Albumin and creatinine also decreased significantly after infection, whereas C-reactive protein increased in the acute phase. Significant inverse correlation was found between the variation of post-pre GNRI scores and basal albumin and C-reactive protein at 7 days. In addition, we observed the opposite trend between albumin at 30 days and basal cholesterol. A negative value in the GNRI variation was associated with bilateral pneumonia, need for hospitalization, and nutritional support. Vaccinated patients presented substantially less bilateral pneumonia and hospitalization. No significant effects were observed between vaccine doses and the variation in nutritional status, although a positive correlation was detected with the albumin at 7 days and C-reactive protein before infection and the number of vaccine doses received. DISCUSSION: COVID-19 is associated with affectations in the nutritional status and biomarkers in hemodialysis patients. In this study, vaccines have shown a protective effect against the clinical consequences of COVID. However, they have shown limitations in preventing the deterioration of nutritional status after infection. The results highlight the importance of promoting the vaccination in these patients as well as incorporating nutritional assessment before, during, and after the infection.

Using Regional Sero-Epidemiology SARS-CoV-2 Anti-S Antibodies in the Dominican Republic to Inform Targeted Public Health Response.

Incidence of COVID-19 has been associated with sociodemographic factors. We investigated variations in SARS-CoV-2 seroprevalence at sub-national levels in the Dominican Republic and assessed potential factors influencing variation in regional-level seroprevalence. Data were collected in a three-stage cross-sectional national serosurvey from June to October 2021. Seroprevalence of antibodies against the SARS-CoV-2 spike protein (anti-S) was estimated and adjusted for selection probability, age, and sex. Multilevel logistic regression was used to estimate the effect of covariates on seropositivity for anti-S and correlates of 80% protection (PT80) against symptomatic infection for the ancestral and Delta strains. A total of 6683 participants from 134 clusters in all 10 regions were enrolled. Anti-S, PT80 for the ancestral and Delta strains odds ratio varied across regions, Enriquillo presented significant higher odds for all outcomes compared with Yuma. Compared to being unvaccinated, receiving ≥2 doses of COVID-19 vaccine was associated with a significantly higher odds of anti-S positivity (OR 85.94, [10.95-674.33]) and PT80 for the ancestral (OR 4.78, [2.15-10.62]) and Delta strains (OR 3.08, [1.57-9.65]) nationally and also for each region. Our results can help inform regional-level public health response, such as strategies to increase vaccination coverage in areas with low population immunity against currently circulating strains.

Prevalence of African animal trypanosomiasis among livestock and domestic animals in Uganda: a systematic review and meta-regression analysis from 1980 to 2022.

African animal trypanosomiasis (AAT) is one of the major constraints to animal health and production in sub-Saharan Africa. To inform AAT control in Uganda and help advance along the progressive control pathway (PCP), we characterized AAT prevalence among eight host species in Uganda and explored factors that influence the prevalence variation between studies. We retrieved AAT prevalence publications (n = 2232) for Uganda (1980-2022) from five life sciences databases, focusing on studies specifying AAT detection methods, sample size, and the number of trypanosome-positive animals. Following PRISMA guidelines, we included 56 publications, and evaluated publication bias by the Luis Furuya-Kanamori (LFK) index. National AAT prevalence under DNA diagnostic methods for cattle, sheep and goats was 22.15%, 8.51% and 13.88%, respectively. Under DNA diagnostic methods, T. vivax was the most common Trypanosoma sp. in cattle (6.15%, 95% CI: 2.91-10.45) while T. brucei was most common among small ruminants (goats: 8.78%, 95% CI: 1.90-19.88, and sheep: 8.23%, 95% CI: 4.74-12.50, respectively). Northern and Eastern regions accounted for the highest AAT prevalence. Despite the limitations of this study (i.e., quality of reviewed studies, underrepresentation of districts/regions), we provide insights that could be used for better control of AAT in Uganda and identify knowledge gaps that need to be addressed to support the progressive control of AAT at country level and other regional endemic countries with similar AAT eco-epidemiology.

Dimensionality reduction and features visual representation based on conditional probabilities applied to activity classification.

A large part of the information emitted by contemporary technological devices comes in the form of time series. The massive commercialization of these kinds of devices has made the study of time series feature extraction techniques acquire a vital relevance in last years. Two main things are essential when applying feature extraction techniques to time series: to reduce the dimensionality so it occupies the least amount of storage memory possible, and to make features that contain the relevant information regarding the nature of the data set and the goals to be achieved. For this purpose, we propose in this work a brand new technique called the State Changes Representation for Time Series (SCRTS), which relies on the relevant data associated with the conditional probabilities of the time series (also known in the literature as Markov model's features), and the distribution of its values. This method is length-independent, which means that we can apply it to time series of different dimensions obtaining the same number of features for each one. Also, it provides a visual representation of the input data, so it is possible to interpret what makes a certain time series different from the other. After explaining how it works, we apply it to 3 different wearable accelerometer data sets. This algorithm reduces the original dimension of the time series considerably (in the best case from 5499 values to 31), having a good performance in the classification results (in the best chance with an accuracy of 98%).

Infection prediction in swine populations with machine learning.

The pork industry is an essential part of the global food system, providing a significant source of protein for people around the world. A major factor restraining productivity and compromising animal wellbeing in the pork industry is disease outbreaks in pigs throughout the production process: widespread outbreaks can lead to losses as high as 10% of the U.S. pig population in extreme years. In this study, we present a machine learning model to predict the emergence of infection in swine production systems throughout the production process on a daily basis, a potential precursor to outbreaks whose detection is vital for disease prevention and mitigation. We determine features that provide the most value in predicting infection, which include nearby farm density, historical test rates, piglet inventory, feed consumption during the gestation period, and wind speed and direction. We utilize these features to produce a generalizable machine learning model, evaluate the model's ability to predict outbreaks both seven and 30 days in advance, allowing for early warning of disease infection, and evaluate our model on two swine production systems and analyze the effects of data availability and data granularity in the context of our two swine systems with different volumes of data. Our results demonstrate good ability to predict infection in both systems with a balanced accuracy of [Formula: see text] on any disease in the first system and balanced accuracies (average prediction accuracy on positive and negative samples) of [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text] on porcine reproductive and respiratory syndrome, porcine epidemic diarrhea virus, influenza A virus, and Mycoplasma hyopneumoniae in the second system, respectively, using the six most important predictors in all cases. These models provide daily infection probabilities that can be used by veterinarians and other stakeholders as a benchmark to more timely support preventive and control strategies on farms.

Evaluation of the application of sequence data to the identification of outbreaks of disease using anomaly detection methods.

Anomaly detection methods have a great potential to assist the detection of diseases in animal production systems. We used sequence data of Porcine Reproductive and Respiratory Syndrome (PRRS) to define the emergence of new strains at the farm level. We evaluated the performance of 24 anomaly detection methods based on machine learning, regression, time series techniques and control charts to identify outbreaks in time series of new strains and compared the best methods using different time series: PCR positives, PCR requests and laboratory requests. We introduced synthetic outbreaks of different size and calculated the probability of detection of outbreaks (POD), sensitivity (Se), probability of detection of outbreaks in the first week of appearance (POD1w) and background alarm rate (BAR). The use of time series of new strains from sequence data outperformed the other types of data but POD, Se, POD1w were only high when outbreaks were large. The methods based on Long Short-Term Memory (LSTM) and Bayesian approaches presented the best performance. Using anomaly detection methods with sequence data may help to identify the emergency of cases in multiple farms, but more work is required to improve the detection with time series of high variability. Our results suggest a promising application of sequence data for early detection of diseases at a production system level. This may provide a simple way to extract additional value from routine laboratory analysis. Next steps should include validation of this approach in different settings and with different diseases.

Risk mapping and risk factors analysis of rabies in livestock in Bangladesh using national-level passive surveillance data.

Rabies is a major zoonotic disease around the world, causing significant mortality to both humans and animals, especially in low- and middle-income countries. In Bangladesh, rabies is transmitted mostly by the bite of infected dogs and jackals to humans and domestic livestock, causing severe economic losses and public health hazards. Our study analyzed national passive surveillance data of veterinary hospital-reported rabies cases in cattle, buffalo, sheep, and goats from 2015 to 2017 in all 64 districts of Bangladesh. We used a zero-inflated negative binomial regression model to identify the main environmental and socio-economic risk factors associated with rabies occurrence in livestock, and we used model results to generate risk maps. Our study revealed that monsoon precipitation (RR=1.28, p-value=0.043) was positively associated with rabies cases in livestock, and the percentage of adults who have completed university education was also a significant predictor (RR=0.58, p-value<0.001) likely suggesting that districts with higher education levels tended to have a lower reporting of rabies cases in livestock. The standardized incidence ratio maps and predicted relative risk maps revealed a high risk of rabies cases in southeast areas in Bangladesh. We recommend implementing risk-based vaccination strategies in dogs and jackals in those high-risk areas before monsoon to reduce the burden of rabies cases in domestic ruminants and humans in Bangladesh.

Applications of Natural Language Processing for the Management of Stroke Disorders: Scoping Review.

BACKGROUND: Recent advances in natural language processing (NLP) have heightened the interest of the medical community in its application to health care in general, in particular to stroke, a medical emergency of great impact. In this rapidly evolving context, it is necessary to learn and understand the experience already accumulated by the medical and scientific community. OBJECTIVE: The aim of this scoping review was to explore the studies conducted in the last 10 years using NLP to assist the management of stroke emergencies so as to gain insight on the state of the art, its main contexts of application, and the software tools that are used. METHODS: Data were extracted from Scopus and Medline through PubMed, using the keywords "natural language processing" and "stroke." Primary research questions were related to the phases, contexts, and types of textual data used in the studies. Secondary research questions were related to the numerical and statistical methods and the software used to process the data. The extracted data were structured in tables and their relative frequencies were calculated. The relationships between categories were analyzed through multiple correspondence analysis. RESULTS: Twenty-nine papers were included in the review, with the majority being cohort studies of ischemic stroke published in the last 2 years. The majority of papers focused on the use of NLP to assist in the diagnostic phase, followed by the outcome prognosis, using text data from diagnostic reports and in many cases annotations on medical images. The most frequent approach was based on general machine learning techniques applied to the results of relatively simple NLP methods with the support of ontologies and standard vocabularies. Although smaller in number, there has been an increasing body of studies using deep learning techniques on numerical and vectorized representations of the texts obtained with more sophisticated NLP tools. CONCLUSIONS: Studies focused on NLP applied to stroke show specific trends that can be compared to the more general application of artificial intelligence to stroke. The purpose of using NLP is often to improve processes in a clinical context rather than to assist in the rehabilitation process. The state of the art in NLP is represented by deep learning architectures, among which Bidirectional Encoder Representations from Transformers has been found to be especially widely used in the medical field in general, and for stroke in particular, with an increasing focus on the processing of annotations on medical images.

Quantitative risk assessment of African swine fever introduction into Spain by legal import of swine products.

African swine fever (ASF) is currently threatening the global swine industry. Its unstoppable global spread poses a serious risk to Spain, one of the world's leading producers. Over the past years, there has been an increased global burden of ASF not only in swine but also swine products. Unfortunately, many pigs are not diagnosed before slaughter and their products are used for human consumption. These ASF-contaminated products are only a source for new ASF outbreaks when they are consumed by domestic pigs or wild boar, which may happen either by swill feeding or landfill access. This study presents a quantitative stochastic risk assessment model for the introduction of ASF into Spain via the legal import of swine products, specifically pork and pork products. Entry assessment, exposure assessment, consequence assessment and risk estimation were carried out. The results suggest an annual probability of ASF introduction into Spain of 1.74 × 10-4, the highest risk being represented by Hungary, Portugal, and Poland. Monthly risk distribution is homogeneously distributed throughout the year. Illegal trade and pork product movement for own consumption (e.g., air and ship passenger luggage) have not been taken into account due to the lack of available, accredited data sources. This limitation may have influenced the model's outcomes and, the risk of introduction might be higher than that estimated. Nevertheless, the results presented herein would contribute to allocating resources to areas at higher risk, improving prevention and control strategies and, ultimately, would help reduce the risk of ASF introduction into Spain.