Towards universal health coverage in Vietnam: a mixed-method case study of enrolling people with tuberculosis into social health insurance.

BACKGROUND: Vietnam's primary mechanism of achieving sustainable funding for universal health coverage (UHC) and financial protection has been through its social health insurance (SHI) scheme. Steady progress towards access has been made and by 2020, over 90% of the population were enrolled in SHI. In 2022, as part of a larger transition towards the increased domestic financing of healthcare, tuberculosis (TB) services were integrated into SHI. This change required people with TB to use SHI for treatment at district-level facilities or to pay out of pocket for services. This study was conducted in preparation for this transition. It aimed to understand more about uninsured people with TB, assess the feasibility of enrolling them into SHI, and identify the barriers they faced in this process. METHODS: A mixed-method case study was conducted using a convergent parallel design between November 2018 and January 2022 in ten districts of Hanoi and Ho Chi Minh City, Vietnam. Quantitative data were collected through a pilot intervention that aimed to facilitate SHI enrollment for uninsured individuals with TB. Descriptive statistics were calculated. Qualitative interviews were conducted with 34 participants, who were purposively sampled for maximum variation. Qualitative data were analyzed through an inductive approach and themes were identified through framework analysis. Quantitative and qualitative data sources were triangulated. RESULTS: We attempted to enroll 115 uninsured people with TB into SHI; 76.5% were able to enroll. On average, it took 34.5 days to obtain a SHI card and it cost USD 66 per household. The themes indicated that a lack of knowledge, high costs for annual premiums, and the household-based registration requirement were barriers to SHI enrollment. Participants indicated that alternative enrolment mechanisms and greater procedural flexibility, particularly for undocumented people, is required to achieve full population coverage with SHI in urban centers. CONCLUSIONS: Significant addressable barriers to SHI enrolment for people affected by TB were identified. A quarter of individuals remained unable to enroll after receiving enhanced support due to lack of required documentation. The experience gained during this health financing transition is relevant for other middle-income countries as they address the provision of financial protection for the treatment of infectious diseases.

Effects of Standardized Patient Simulation and Mobile Applications on Nursing Students' Clinical Competence, Self-Efficacy, and Cultural Competence: A Quasi-Experimental Study.

BACKGROUND: Simulation-based education has emerged as an effective approach in nursing education worldwide. We aimed to evaluate the effectiveness of a surgical nursing education program based on a simulation using standardized patients and mobile applications among nursing students. METHODS: A mixed-methods design with a quasi-experimental longitudinal approach and focus group interviews was employed. The data were collected from 130 third-year nursing students at three different time points who were equally divided into experimental and control groups. This study measured the level of clinical surgical nursing competence, self-efficacy in clinical performance, cultural competence, and satisfaction with simulation experience. Four focus group interviews were conducted using open-ended questions to explore the participants' perspectives on the course's efficacy and satisfaction. RESULTS: There were statistically significant differences in clinical surgical nursing competence (F = 8.68, p < 0.001), self-efficacy in clinical performance (F = 13.56, p < 0.001), and cultural competence (F = 10.35, p < 0.001) across time between the intervention and control groups. Student satisfaction with the simulation-based training was high, particularly regarding debriefing and reflection, with an overall mean satisfaction level of 4.25 (0.40). Students' perspectives regarding integrated hybrid training are categorized into three themes: educational achievement, dynamic learning experiences, and satisfaction and suggestion. CONCLUSION: Simulation-based learning provides a dynamic and immersive educational experience that enables undergraduate nursing students to develop and refine essential clinical skills while also fostering confidence and cultural competence.

3D-IncNet: Head and Neck (H&N) Primary Tumors Segmentation and Survival Prediction.

Cancer begins when healthy cells change and grow out of control, forming a mass called a tumor. Head and neck (H&N) cancers usually develop in or around the head and neck, including the mouth (oral cavity), nose and sinuses, throat (pharynx), and voice box (larynx). 4% of all cancers are H&N cancers with a very low survival rate (a five-year survival rate of 64.7%). FDG-PET/CT imaging is often used for early diagnosis and staging of H&N tumors, thus improving these patients' survival rates. This work presents a novel 3D-Inception-Residual aided with 3D depth-wise convolution and squeeze and excitation block. We introduce a 3D depth-wise convolution-inception encoder consisting of an additional 3D squeeze and excitation block and a 3D depth-wise convolution-based residual learning decoder (3D-IncNet), which not only helps to recalibrate the channel-wise features but adaptively through explicit inter-dependencies modeling but also integrate the coarse and fine features resulting in accurate tumor segmentation. We further demonstrate the effectiveness of inception-residual encoder-decoder architecture in achieving better dice scores and the impact of depth-wise convolution in lowering the computational cost. We applied random forest for survival prediction on deep, clinical, and radiomics features. Experiments are conducted on the benchmark HECKTOR21 challenge, which showed significantly better performance by surpassing the state-of-the-artwork and achieved 0.836 and 0.811 concordance index and dice scores, respectively. We made the model and code publicly available.

Determinants of catastrophic costs among households affected by multi-drug resistant tuberculosis in Ho Chi Minh City, Viet Nam: a prospective cohort study.

BACKGROUND: Globally, most people with multidrug-resistant tuberculosis (MDR-TB) and their households experience catastrophic costs of illness, diagnosis, and care. However, the factors associated with experiencing catastrophic costs are poorly understood. This study aimed to identify risk factors associated with catastrophic costs incurrence among MDR-TB-affected households in Ho Chi Minh City (HCMC), Viet Nam. METHODS: Between October 2020 and April 2022, data were collected using a locally-adapted, longitudinal WHO TB Patient Cost Survey in ten districts of HCMC. Ninety-four people with MDR-TB being treated with a nine-month TB regimen were surveyed at three time points: after two weeks of treatment initiation, completion of the intensive phase and the end of the treatment (approximately five and 10 months post-treatment initiation respectively). The catastrophic costs threshold was defined as total TB-related costs exceeding 20% of annual pre-TB household income. Logistic regression was used to identify variables associated with experiencing catastrophic costs. A sensitivity analysis examined the prevalence of catastrophic costs using alternative thresholds and cost estimation approaches. RESULTS: Most participants (81/93 [87%]) experienced catastrophic costs despite the majority 86/93 (93%) receiving economic support through existing social protection schemes. Among participant households experiencing and not experiencing catastrophic costs, median household income was similar before MDR-TB treatment. However, by the end of MDR-TB treatment, median household income was lower (258 [IQR: 0-516] USD vs. 656 [IQR: 462-989] USD; p = 0.003), and median income loss was higher (2838 [IQR: 1548-5418] USD vs. 301 [IQR: 0-824] USD; p < 0.001) amongst the participant households who experienced catastrophic costs. Being the household's primary income earner before MDR-TB treatment (aOR = 11.2 [95% CI: 1.6-80.5]), having a lower educational level (aOR = 22.3 [95% CI: 1.5-344.1]) and becoming unemployed at the beginning of MDR-TB treatment (aOR = 35.6 [95% CI: 2.7-470.3]) were associated with experiencing catastrophic costs. CONCLUSION: Despite good social protection coverage, most people with MDR-TB in HCMC experienced catastrophic costs. Incurrence of catastrophic costs was independently associated with being the household's primary income earner or being unemployed. Revision and expansion of strategies to mitigate TB-related catastrophic costs, in particular avoiding unemployment and income loss, are urgently required.

A qualitative assessment on the acceptability of providing cash transfers and social health insurance for tuberculosis-affected families in Ho Chi Minh City, Vietnam.

To achieve the Sustainable Development Goal's targets of universal health coverage (UHC) and poverty reduction, interventions are required that strengthen and harmonize both UHC and social protection. Vietnam is committed to achieving financial protection and over 90% of the general population has enrolled in its social health insurance (SHI) scheme. However, an estimated 63% of tuberculosis (TB)-affected households in Vietnam still face catastrophic costs and little is known about the optimal strategies to mitigate the costs of TB care for vulnerable families. This study assessed the acceptability of a social protection package containing cash transfers and SHI using individual interviews (n = 19) and focus group discussions (n = 3 groups). Interviews were analyzed through framework analysis. The study's main finding indicated that both conditional and unconditional cash transfers paired with SHI were acceptable, across six dimensions of acceptability. Cash transfers were considered beneficial for mitigating out-of-pocket expenditure, increasing TB treatment adherence, and improving mental health and general well-being, but the value provided was inadequate to fully alleviate the economic burden of the illness. The conditionality of the cash transfers was not viewed by participants as inappropriate, but it increased the workload of the TB program, which brought into question the feasibility of scale-up. SHI was viewed as a necessity by almost all participants, but people with TB questioned the quality of care received when utilizing it for auxiliary TB services. Access to multiple sources of social protection was deemed necessary to fully offset the costs of TB care. Additional research is needed to assess the impact of cash transfer interventions on health and economic outcomes in order to create an enabling policy environment for scale-up.

Comparative study of encoded and alignment-based methods for virus taxonomy classification.

The emergence of viruses and their variants has made virus taxonomy more important than ever before in controlling the spread of diseases. The creation of efficient treatments and cures that target particular virus properties can be aided by understanding virus taxonomy. Alignment-based methods are commonly used for this task, but are computationally expensive and time-consuming, especially when dealing with large datasets or when detecting new virus variants is time sensitive. An alternative approach, the encoded method, has been developed that does not require prior sequence alignment and provides faster results. However, each encoded method has its own claimed accuracy. Therefore, careful evaluation and comparison of the performance of different encoded methods are essential to identify the most accurate and reliable approach for virus taxonomy classification. This study aims to address this issue by providing a comprehensive and comparative analysis of the potential of encoded methods for virus classification and phylogenetics. We compared the vectors generated for each encoded method using distance metrics to determine their similarity to alignment-based methods. The results and their validation show that K-merNV followed by CgrDft encoded methods, perform similarly to state-of-the-art multi-sequence alignment methods. This is the first study to incorporate and compare encoded methods that will facilitate future research in making more informed decisions regarding selection of a suitable method for virus taxonomy.

Telecoupled urban demand from West African cities causes social-ecological land use transformation in Saharan oases.

Little is known about the long-distance telecoupling effects of urban food demands on land use changes (LUCs) in remote oases of the Southern Sahara. Using the example of two typical oasis settlements on Mont Bagzam in the southern Aϊr Mountains of Niger which are linked to regional and global markets by an unpaved road since 2015, this study aimed at analyzing time trajectories of LUCs and related changing agricultural production patterns. LUCs were quantified for 1955 to 2022 using GIS-based mapping of agriculture and natural vegetation based on historical aerial photographs, CORONA and multi-spectral satellite images, and high resolution drone-based surveys. The results show a major increment in actively used agricultural land in the 850 ha watershed of the two oases from 11 ha in 1955 to 13 ha in 2003 and 68 ha in 2022 as well as the addition of 92 irrigation wells to 16 existing ones between 2003 and 2022. LUCs and evapotranspiration calculated from climatic data of a local weather station allowed to estimate changes of irrigation water needs in the selected watershed. While annual precipitation averages only 214 mm, local reference evapotranspiration may reach 1,476 mm year-1. Therefore, the additional annual irrigation water needs for the newly established fields between 2003 and 2022 cultivated to cash crops rose by 696 million l. To detect LUC effects on soil quality, soil samples of onion and garlic fields of different ages were collected employing a false-time-series approach. Results reveal increasing soil pH and salt concentrations and falling ground water tables, which reflects a negative water balance and ground water extraction above recharge levels. Our study provides evidence that the newly established telecoupled production systems on Mont Bagzam threaten the sustainability of existing local agricultural production and related livelihoods of agro-pastoralists.

Upregulation of immunoproteasome PSMB8 is associated with Parkinson's disease.

BACKGROUND: Immunoproteasome, a part of ubiquitin-proteasome system, is involved in immune response as well as protein degradation. However, the relationship between immunoproteasome and Parkinson's disease (PD) was not evaluated clearly. We hypothesized that the shift of immunoproteasome attributes to PD pathogenesis due to its role in inflammation and protein homeostasis. OBJECTIVE: To determine whether immunoproteasome in peripheral blood mononuclear cells (PBMC) and brain is expressed differently between patients with PD and healthy controls (HC). METHODS: Blood samples were collected from 19 HC to 40 patients with PD of comparable ages. Peripheral blood mononuclear cells were isolated and followed by RT-qPCR to measure the mRNA levels of three catalytic subunits of immunoproteasome, namely, PSMB8, PSMB9, and PSMB10. Then, the protein levels of each subunit were measured by western blot. Finally, we confirmed the altered immunoproteasome subunit in the post-mortem human brain of PD. RESULTS: In PBMCs, PSMB8 mRNA expression of PD group significantly increased compared to HC (p = 0.004), whereas PSMB9 and PSMB10 mRNA were not different between the PD and HC. The ratio of PSMB10 and PSMB8 mRNA (PSMB10/8 ratio) also reflected the significant difference between the PD and HC (p = 0.002). The PSMB10/8 ratio was well correlated with the UPDRS total and Part III score in the early stage of PD (Hoehn and Yahr ≤2.5) or drug-naïve PD subgroups. In terms of the protein level of immunoproteasome subunits in PBMCs, the increase of PSMB8 protein was observed in PD compared to HC (p = 0.0009), while PSMB9 and PSMB10 were not different between groups. Finally, we confirmed that immunoproteasome PSMB8 was expressed abundantly in the postmortem PD brain compared with normal control. CONCLUSION: Our novel findings implicate that immunoproteasome PSMB8 is engaged in PD pathomechanism.

Effects of a low-iodine diet in post-thyroidectomy thyroid cancer patients undergoing I131 therapy at the Vietnam National Cancer Hospital.

Background: I131 therapy is regarded as an "internal surgery" (i.e., a non-invasive approach involving no incision or bleeding) that supports "external surgery" (i.e., using a scalpel) in completely eradicating the root cause of thyroid cancer. Limiting iodine intake is of paramount importance in I131 therapy. I131 therapy protocols recommend that patients follow a low-iodine diet, ideally with a maximum iodine intake of 50 µg/day for two weeks before the I131 therapy. Methods: A pre-post compassion uncontrolled clinic intervention study was conducted on a group of over 70 post-thyroidectomy thyroid cancer patients with indications for I131 therapy at the Vietnam National Cancer Hospital from December 2020 to December 2022. Aim: It aimed to assess the effects of a low-iodine diet on post-thyroidectomy thyroid cancer patients with indications for I131 therapy. Results: The study found that following the intervention, the percentage of participants at risk of mild to moderate malnutrition, as assessed by the PG-SGA tool, decreased to 4.3% from 40.0% before the intervention, with a statistically significant difference of p < 0.001. There was a considerable improvement in the low calcemia level among the study participants, with 35.7% of patients experiencing hypocalcemia prior to the intervention, which reduced to 17.1% after the intervention. This difference was statistically significant (p = 0.01). The study also revealed a urinary iodine level improvement among the study participants. Before the intervention, patients' average urinary iodine level was 14.9 ± 11.3 µg/dl. Following the intervention, it reduced to 12.7 ± 3.9 µg/dl, although this difference was not statistically significant (p = 0.29). Patients' quality of life after adhering to the low-iodine diet tended to decline; however, the change in scores before and after the intervention did not show a significant difference. Conclusion: Despite its negative impact on patients' quality of life, active nutrition counseling and intervention during the low-iodine diet contributed to the substantial improvement in the hypocalcemia level and the reduced urinary iodine level among patients, which in turn could enhance the efficacy of the subsequent I131 therapy.

Monitoring rural-urban transformation in the coastal region of Rabat-Sale-Kenitra, Morocco.

Worldwide urbanization drives rural-urban transformation (RUT) which has major consequences in many countries of the Global South where there is an urgent need to better understand and manage the underlying processes and consequences for ecosystem services. To fill existing knowledge gaps on the extent and time course of RUT in Morocco, this study focused on (i) analyzing the spatial patterns of rural-urban transformation in the Rabat-Sale-Kenitra (RSK) region from 1972 to 2020, (ii) identifying key mechanisms of change, and (iii) defining the main driving forces behind the spatial transformation patterns. To this end, we processed data of the Landsat free archive, historical grayscale Corona images, and nighttime lights datasets on Google Earth Engine (GEE) using machine learning classifiers and LandTrendr spectral-temporal segmentation algorithms. With an overall accuracy (OA) ranging from 88-95%, the results revealed that during the study period the RSK region experienced a 473% growth of horizontal built-up reflected in an area increase from 63.4 km2 to 299.9 km2. The main changes occurred along the Kenitra-Rabat-Temara axis and in central cities connected to the main road network. The horizontal expansion of large and medium-sized cities led to the formation of a Rural-Urban Interface (RUI) on the outskirts. The urban sprawl of some cities has affected the surrounding rural lands within the RUI. Environmental, social, economic, and political forces have interacted in shaping the changes in rural-urban landscapes.

Modernized Crowd Counting Strategies for Mass Gatherings-A Review.

Estimation of crowd size for large gatherings is an indispensable metric for event planners, local authorities, and emergency management. Currently, most crowd counting relies on dated methods such as people counters, entrance sensors, and ticket sales. Over the past decade, there has been rapid development in crowd counting techniques and related technology. Despite progress, theoretical advances in crowd counting technology have outpaced practical applications. The emergence of the vast array of crowd counting techniques has added to the challenge of determining those advances that can be most readily implemented. This article aims to provide an overview of promising crowd counting strategies and recent developments applied within the disaster medicine context along with the best use cases and limitations.

Differential Infectivity of Human Neural Cell Lines by a Dengue Virus Serotype-3 Genotype-III with a Distinct Nonstructural Protein 2A (NS2A) Amino Acid Substitution Isolated from the Cerebrospinal Fluid of a Dengue Encephalitis Patient.

Dengue encephalitis is considered as a severe but unusual clinical presentation of dengue infection. Limited molecular information is available on the neurotropism of dengue virus (DENV), highlighting the need for further research. During a dengue outbreak in Vietnam in 2013, two DENV-3 strains were isolated, in which one was isolated from cerebrospinal fluid (CSF) samples from a dengue encephalitis patient and another strain was isolated from a patient with classical dengue fever in Hai Phong, Vietnam. DENV serotype-3 (DENV-3) isolated from these samples belonged to genotype III, marking the first report of this genotype in the country at that time. Genetic variation between both strains was elucidated by using a full genome sequencing by next-generation sequencing (NGS). The infectivity of the isolated DENV-3 strains was further characterized using human and mouse neuronal cell lines. Phylogenetic analysis of the isolates demonstrated high homogeneity between the CSF-derived and serum-derived DENV-3, in which the full genome sequences of the CSF-derived DENV-3 presented a Thr-1339-Ile mutation in the nonstructural 2A (NS2A) protein. The CSF-derived DENV-3 isolate grew preferentially in human neuronal cells, with a significant proportion of cells that were positive for nonstructural 1 (NS1), nonstructural 4B (NS4B), and nonstructural 5 (NS5) antigens. These results suggest that NS2A may be a crucial region in the neuropathogenesis of DENV-3 and its growth in human neuronal cells. Taken together, our results demonstrate that a CSF-derived DENV-3 has unique infectivity characteristics for human neuronal cells, which might play a crucial role in the neuropathogenesis of DENV infection.

Fruit-CoV: An efficient vision-based framework for speedy detection and diagnosis of SARS-CoV-2 infections through recorded cough sounds.

COVID-19 is an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This deadly virus has spread worldwide, leading to a global pandemic since March 2020. A recent variant of SARS-CoV-2 named Delta is intractably contagious and responsible for more than four million deaths globally. Therefore, developing an efficient self-testing service for SARS-CoV-2 at home is vital. In this study, a two-stage vision-based framework, namely Fruit-CoV, is introduced for detecting SARS-CoV-2 infections through recorded cough sounds. Specifically, audio signals are converted into Log-Mel spectrograms, and the EfficientNet-V2 network is used to extract their visual features in the first stage. In the second stage, 14 convolutional layers extracted from the large-scale Pretrained Audio Neural Networks for audio pattern recognition (PANNs) and the Wavegram-Log-Mel-CNN are employed to aggregate feature representations of the Log-Mel spectrograms and the waveform. Finally, the combined features are used to train a binary classifier. In this study, a dataset provided by the AICovidVN 115M Challenge is employed for evaluation. It includes 7,371 recorded cough sounds collected throughout Vietnam, India, and Switzerland. Experimental results indicate that the proposed model achieves an Area Under the Receiver Operating Characteristic Curve (AUC) score of 92.8% and ranks first on the final leaderboard of the AICovidVN 115M Challenge. Our code is publicly available.

Deep Reinforcement Learning for Cyber Security.

The scale of Internet-connected systems has increased considerably, and these systems are being exposed to cyberattacks more than ever. The complexity and dynamics of cyberattacks require protecting mechanisms to be responsive, adaptive, and scalable. Machine learning, or more specifically deep reinforcement learning (DRL), methods have been proposed widely to address these issues. By incorporating deep learning into traditional RL, DRL is highly capable of solving complex, dynamic, and especially high-dimensional cyber defense problems. This article presents a survey of DRL approaches developed for cyber security. We touch on different vital aspects, including DRL-based security methods for cyber-physical systems, autonomous intrusion detection techniques, and multiagent DRL-based game theory simulations for defense strategies against cyberattacks. Extensive discussions and future research directions on DRL-based cyber security are also given. We expect that this comprehensive review provides the foundations for and facilitates future studies on exploring the potential of emerging DRL to cope with increasingly complex cyber security problems.

Symptom Burden among Hospitalised Older Patients with Heart Failure in Hanoi, Vietnam.

This study aimed to assess the symptom burden among older patients hospitalised for heart failure. This hospital-based, cross-sectional study was conducted at the National Geriatric Hospital, Hanoi, Vietnam, from June 2019 to August 2020. Face-to-face interviews were performed to gather the following information: socio-demographic characteristics, heart failure classification, and clinical characteristics (comorbidities, polypharmacy, pro-B-type natriuretic peptide, left ventricular ejection fraction (LVEF), symptom burden, and depression). Symptom burden was assessed using the Edmonton Symptom Assessment Scale (ESAS), and depression was measured using the Patient Health Questionnaire. A total of 314 patients participated in the study. The mean participant age was 72.67 (SD = 9.42) years. The most frequently reported symptoms on the ESAS were shortness of breath (95.5%), fatigue (94.8%), and anxiety (81.2%). In univariate analyses, depression was significantly associated with heart failure class (p < 0.05). Multivariate linear regression revealed that major depression was significantly associated with total symptom burden score (Beta: 11.74; 95% CI: 9.24-14.23) and LVEF (Beta: -0.09; 95% CI: -0.17-(-0.007)). Patients hospitalised for heart failure experienced a high burden of symptoms. Further studies addressing adverse outcomes and expanding to community-dwelling older people are essential. Palliative care approaches that target symptom reduction should be considered in patients with heart failure.

Advancements in Algorithms and Neuromorphic Hardware for Spiking Neural Networks.

Artificial neural networks (ANNs) have experienced a rapid advancement for their success in various application domains, including autonomous driving and drone vision. Researchers have been improving the performance efficiency and computational requirement of ANNs inspired by the mechanisms of the biological brain. Spiking neural networks (SNNs) provide a power-efficient and brain-inspired computing paradigm for machine learning applications. However, evaluating large-scale SNNs on classical von Neumann architectures (central processing units/graphics processing units) demands a high amount of power and time. Therefore, hardware designers have developed neuromorphic platforms to execute SNNs in and approach that combines fast processing and low power consumption. Recently, field-programmable gate arrays (FPGAs) have been considered promising candidates for implementing neuromorphic solutions due to their varied advantages, such as higher flexibility, shorter design, and excellent stability. This review aims to describe recent advances in SNNs and the neuromorphic hardware platforms (digital, analog, hybrid, and FPGA based) suitable for their implementation. We present that biological background of SNN learning, such as neuron models and information encoding techniques, followed by a categorization of SNN training. In addition, we describe state-of-the-art SNN simulators. Furthermore, we review and present FPGA-based hardware implementation of SNNs. Finally, we discuss some future directions for research in this field.

Origin of novel coronavirus causing COVID-19: A computational biology study using artificial intelligence.

Origin of the COVID-19 virus (SARS-CoV-2) has been intensely debated in the scientific community since the first infected cases were detected in December 2019. The disease has caused a global pandemic, leading to deaths of thousands of people across the world and thus finding origin of this novel coronavirus is important in responding and controlling the pandemic. Recent research results suggest that bats or pangolins might be the hosts for SARS-CoV-2 based on comparative studies using its genomic sequences. This paper investigates the SARS-CoV-2 origin by using artificial intelligence (AI)-based unsupervised learning algorithms and raw genomic sequences of the virus. More than 300 genome sequences of COVID-19 infected cases collected from different countries are explored and analysed using unsupervised clustering methods. The results obtained from various AI-enabled experiments using clustering algorithms demonstrate that all examined SARS-CoV-2 genomes belong to a cluster that also contains bat and pangolin coronavirus genomes. This provides evidence strongly supporting scientific hypotheses that bats and pangolins are probable hosts for SARS-CoV-2. At the whole genome analysis level, our findings also indicate that bats are more likely the hosts for the COVID-19 virus than pangolins.

Spatial patterns of urbanising landscapes in the North Indian Punjab show features predicted by fractal theory.

Understanding and governing human settlement patterns is a major challenge of the urban age. While rural settlements emerge as parts of agricultural landscapes, cities typically evolve in economically strategic locations, and over time form hierarchical systems of cities. Purposeful planning and the collective, self-organized behavior of the inhabitants interact in the development of regional settlement patterns. Since self-organizing systems often produce fractal patterns in nature, this study combines approaches of land use science, city ranking, and urban planning under a fractal theory framework, to analyze the settlement system of the Indian Punjab. Scaling levels were defined by discontinuities in the size distribution of built-up areas (Global Urban Footprint), which correlated to population-based classifications (r = 0.9591). Self-similarity across scales was supported by geo-statistical similarity (p < 0.05) of distances and angles between settlements of successive classes, and the overall fractal dimension of DB = 1.95. When compared to a modeled Sierpinski Carpet, more than 50% of the settlements met the fractal geometry rules at larger scales. The spatial distribution of small villages, however, deviated, indicating a scale-related shift in organizing principles. Explicitly acknowledging cross-scale relations and self-organisation in regional planning policies may lead to more sustainable settlement structures that are in harmony with natural system properties.

In vitro antiviral activities of ethanol and aqueous extracts of Vietnamese traditional medicinal plants against Porcine Epidemic Diarrhea virus: a coronavirus family member.

Porcine epidemic diarrhea virus (PEDV) causes diarrhea in pigs leading to severe illnesses and high mortality rates. The development of medicinal agents to treat PEDV infection is therefore crucial. In this study, antiviral activities against PEDV of ethanol and aqueous extracts of 17 Vietnamese traditional medicinal plants were evaluated using the cytopathic effect-based assay. The results showed that 14 out of 17 medicinal plants could inhibit the cytopathic effect of PEDV. The ethanol extract of Stixis scandens was identified as the most active extract with its MIC (minimum inhibitory concentration) being 0.15 µg/mL. Other plant extracts also displayed strong antiviral activity against PEDV, including Anisomeles indica, Pericampylus glaucus and Croton kongensis. The results demonstrate that certain medicinal plants have a high antiviral potential and may serve as a lead to develop novel pharmaceutical agents to cure PED as well as the diseases caused by other coronaviruses.