Abolished frameshifting for predicted structure-stabilizing SARS-CoV-2 mutants: Implications to alternative conformations and their statistical structural analyses (preprint)

The SARS-CoV-2 frameshifting element (FSE) has been intensely studied and explored as a therapeutic target for coronavirus diseases including COVID-19. Besides the intriguing virology, this small RNA is known to adopt many length-dependent conformations, as verified by multiple experimental and computational approaches. However, the role these alternative conformations play in the frameshifting mechanism and how to quantify this structural abundance has been an ongoing challenge. Here, we show by DMS and dual-luciferase functional assays that previously predicted FSE mutants (using the RAG graph theory approach) suppress structural transitions and abolish frameshifting. Furthermore, correlated mutation analysis of DMS data by three programs (DREEM, DRACO, and DANCE-MaP) reveals important differences in their estimation of specific RNA conformations, suggesting caution in the interpretation of such complex conformational landscapes. Overall, the abolished frameshifting in three different mutants confirms that all alternative conformations play a role in the pathways of ribosomal transition.

Challenges in Trials on Neonatal Sepsis- Case of ProSPoNS Trial & Role of Central Endpoint Adjudication (preprint)

Background: Despite progress in reducing Infant mortality in India, neonatal mortality decline is slower, necessitating concerted efforts to achieve Sustainable Development Goal-3. A promising strategy aiming prevention of neonatal sepsis in high-risk, vulnerable, low birth weight neonates through an innovative intervention, including probiotic supplementation. This article communicates the decision by ProSPoNS trial investigators to establish a Central Endpoint Adjudication committee as an addendum to the published protocol in 'Trials 2021.' Methods:  In the pursuit of clarity regarding the primary outcome of Sepsis/PSBI in a clinical trial, a crucial decision was reached during the investigators' meeting at MGIMS Sevagram on 17th-18th August 2023. The unanimous consensus was to explicitly define "Physician diagnosed sepsis" as the primary study outcome, encompassing Sepsis/PSBI. This alignment aimed to synchronize the primary objective and outcome with the stated hypothesis, necessitating the establishment of a Central Endpoint Adjudication (CEA) process across all six trial sites. To enact this, the CEA committee, chaired by an external Subject Expert and comprising Site Principal Investigators, a Trial Statistician, and a Microbiologist, will employ four criteria to determine 'Physician diagnosed sepsis' for each sickness event in a study participant. These criteria include Blood culture status, Sepsis screen status, PSBI/non-PSBI signs and symptoms, and the Clinical course during the event, including antibiotic usage. Importantly, this clarification maintains consistency with the approved study protocol (Protocol No.5/7/915/2012 Version 3.1 dated 14 Feb 2020), emphasizing the commitment to methodological transparency and adherence to predefined standards. Results:  The challenges faced in the trial implementation, such as complex multi-centric design, heterogeneity / extreme variation across sites, inconsistency with definition of sepsis in the neonatal/young infant population, remote vs. on-site training/monitoring during the Covid-19 Pandemic have been described and potential solutions to some of the challenges in clinical trials suggested. Conclusions: The decision to utilize the guidance of a Central Endpoint Adjudication Committee has been suggested as a way forward in the ProSPoNS and other multicentre complex clinical trials. Trial registration: Clinical Trial Registry of India (CTRI) CTRI/2019/05/019197. Registered on 16 May 2019.

Evaluation of safety concerns for COVID-19 immunization of pregnant women: A systematic review of emerging evidence (preprint)

Background: There is an urgent need to review the status of COVID-19 vaccine immunization in pregnant women globally so that the adverse outcomes may be prevented. Objective: To evaluate the probable outcome of COVID-19 vaccination in pregnant women. Search strategy: An electronic search was conducted over the period of 3 months (June 15-August 15, 2021). Selection criteria: The original studies evaluating safety concerns in pregnant women for COVID-19 vaccination were included. Data collection and analysis: Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 guidelines were used for the collection of the data and reporting of the findings. The inclusion and exclusion criteria for the studies were determined based on ‘PICO principle’ (Population, Intervention, Comparator, and Outcome, Study design. Risk of bias assessment was done using National Institute of Health (NIH) tool for systematic reviews. Main results: COVID-19 vaccination in pregnant women was not associated with increased adverse effects or complications to the mother as well as developing fetus or newborn compared to non-vaccinated pregnant women. Vaccinated pregnant women showed a robust immune response against COVID-19 infection. Conclusions: COVID-19 vaccination during pregnancy causes no significant health risks for the mother or developing fetus or newborn.

Feasibility and preliminary efficacy of an online mindful walking intervention among COVID-19 long haulers: A mixed method study including daily diary surveys (preprint)

Objective: Mindful walking (MW) intervention could be an effective strategy to address the psychosocial stressors and physical health challenges faced by COVID-19 long haulers. This study aims to test the feasibility of digitally delivering MW intervention among long haulers via social media and assess its preliminary efficacy in enhancing physical and psychosocial well-being. Method: We recruited 23 participants via Facebook groups in March and November 2021 for a 4-week online MW intervention, consisting of mindfulness practices (2 sessions per week), delivered entirely through the Facebook group. The intervention was assessed using mixed methods. Quantitative data were collected through 28-day brief daily evening surveys over the 4-week intervention period, including affect, cognition, mindfulness, physical activity, and MW engagement. Qualitative data were extracted from Paradata (i.e., participants responses to the social media posts). Multilevel modeling was employed for statistical analysis and a pragmatic approach was used for qualitative analysis. Results: The mean feasibility score was 4.93/7 (SD=1.88). Multilevel models showed that MW uptake on a given day was positively associated with positive affect (beta=0.89, p<0.01), perceived cognition (beta=0.52, p<0.05), and physical activity levels (beta=0.41, p<0.05), and negatively associated with negative affect (beta=-0.83, p<0.01). The total number of MW days across the study period was positively associated with mindfulness levels (beta=0.3 p<0.01). Paradata reported satisfaction in mindfulness skill enhancement, symptom management, and well-being promotion. Conclusion: The digital delivery of our MW intervention via Facebook showed high acceptability. Preliminary efficacy findings indicate improved mental well-being and physical activity among long haulers.

Effect of Paxlovid Treatment on Long COVID Onset: An EHR-Based Target Trial Emulation from N3C (preprint)

Preventing and treating post-acute sequelae of SARS-CoV-2 infection (PASC), commonly known as Long COVID, has become a public health priority. In this study, we examined whether treatment with Paxlovid in the acute phase of COVID-19 helps prevent the onset of PASC. We used electronic health records from the National Covid Cohort Collaborative (N3C) to define a cohort of 426,461 patients who had COVID-19 since April 1, 2022, and were eligible for Paxlovid treatment due to risk for progression to severe COVID-19. We used the target trial emulation (TTE) framework to estimate the effect of Paxlovid treatment on PASC incidence. Our primary outcome measure was a PASC computable phenotype. Secondary outcomes were the onset of novel cognitive, fatigue, and respiratory symptoms in the post-acute period. Paxlovid treatment did not have a significant effect on overall PASC incidence (relative risk [RR] = 0.99, 95% confidence interval [CI] 0.96-1.01). However, its effect varied across the cognitive (RR = 0.85, 95% CI 0.79-0.90), fatigue (RR = 0.93, 95% CI 0.89-0.96), and respiratory (RR = 0.99, 95% CI 0.95-1.02) symptom clusters, suggesting that Paxlovid treatment may help prevent post-acute cognitive and fatigue symptoms more than others.

Outcomes of the EMDataResource Cryo-EM Ligand Modeling Challenge (preprint)

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibitor, SARS-CoV-2 RNA-dependent RNA polymerase with covalently bound nucleotide analog, and SARS-CoV-2 ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. We found that (1) the quality of submitted ligand models and surrounding atoms varied, as judged by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics, and contact scores, and (2) a composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

Reengineering a machine learning phenotype to adapt to the changing COVID-19 landscape: A study from the N3C and RECOVER consortia (preprint)

Background. In 2021, we used the National COVID Cohort Collaborative (N3C) as part of the NIH RECOVER Initiative to develop a machine learning (ML) pipeline to identify patients with a high probability of having post-acute sequelae of SARS-CoV-2 infection (PASC), or Long COVID. However, the increased home testing, missing documentation, and reinfections that characterize the latter years of the pandemic necessitate reengineering our original model to account for these changes in the COVID-19 research landscape. Methods. Our updated XGBoost model gathers data for each patient in overlapping 100-day periods that progress through time, and issues a probability of Long COVID for each 100-day period. If a patient has known acute COVID-19 during any 100-day window (including reinfections), we censor the data from 7 days prior to the diagnosis/positive test date through 28 days after. These fixed time windows replace the prior model's reliance on a documented COVID-19 index date to anchor its data collection, and are able to account for reinfections. Results. The updated model achieves an area under the receiver operating characteristic curve of 0.90. Precision and recall can be adjusted according to a given use case, depending on whether greater sensitivity or specificity is warranted. Discussion. By eschewing the COVID-19 index date as an anchor point for analysis, we are now able to assess the probability of Long COVID among patients who may have tested at home, or with suspected (but untested) cases of COVID-19, or multiple SARS-CoV-2 reinfections. We view this exercise as a model for maintaining and updating any ML pipeline used for clinical research and operations.

Unveiling Public Perceptions: Machine Learning-Based Sentiment Analysis of COVID-19 Vaccines in India (preprint)

In March 2020, the World Health Organisation declared COVID-19 a global pandemic as it spread to nearly every country. By mid-2021, India had introduced three vaccines: Covishield, Covaxin, and Sputnik. To ensure successful vaccination in a densely populated country like India, understanding public sentiment was crucial. Social media, particularly Reddit with over 430 million users, played a vital role in disseminating information. This study employs data mining techniques to analyze Reddit data and gauge Indian sentiments towards COVID-19 vaccines. Using Python's Text Blob library, comments are annotated to assess general sentiments. Results show that most Reddit users in India expressed neutrality about vaccination, posing a challenge for the Indian government's efforts to vaccinate a significant portion of the population.

SARS-CoV-2 nsp15 endoribonuclease antagonizes dsRNA-induced antiviral signaling (preprint)

Severe acute respiratory syndrome coronavirus (SARS-CoV)-2 has caused millions of deaths since emerging in 2019. Innate immune antagonism by lethal CoVs such as SARS-CoV-2 is crucial for optimal replication and pathogenesis. The conserved nonstructural protein 15 (nsp15) endoribonuclease (EndoU) limits activation of double-stranded (ds)RNA-induced pathways, including interferon (IFN) signaling, protein kinase R (PKR), and oligoadenylate synthetase/ribonuclease L (OAS/RNase L) during diverse CoV infections including murine coronavirus and Middle East respiratory syndrome (MERS)-CoV. To determine how nsp15 functions during SARS-CoV-2 infection, we constructed a mutant recombinant SARS-CoV-2 (nsp15mut) expressing a catalytically inactive nsp15. Infection with SARS-CoV-2 nsp15 mut led to increased activation of the IFN signaling and PKR pathways in lung-derived epithelial cell lines and primary nasal epithelial air-liquid interface (ALI) cultures as well as significant attenuation of replication in ALI cultures compared to wild-type (WT) virus. This replication defect was rescued when IFN signaling was inhibited with the Janus activated kinase (JAK) inhibitor ruxolitinib. Finally, to assess nsp15 function in the context of minimal (MERS-CoV) or moderate (SARS-CoV-2) innate immune induction, we compared infections with SARS-CoV-2 nsp15mut and previously described MERS-CoV nsp15 mutants. Inactivation of nsp15 had a more dramatic impact on MERS-CoV replication than SARS-CoV-2 in both Calu3 cells and nasal ALI cultures suggesting that SARS-CoV-2 can better tolerate innate immune responses. Taken together, SARS-CoV-2 nsp15 is a potent inhibitor of dsRNA-induced innate immune response and its antagonism of IFN signaling is necessary for optimal viral replication in primary nasal ALI culture. SIGNIFICANCESevere acute respiratory syndrome coronavirus (SARS-CoV)-2 causes a spectrum of respiratory disease ranging from asymptomatic infections to severe pneumonia and death. Innate immune responses during SARS-CoV-2 infection have been associated with clinical disease severity, with robust early interferon responses in the nasal epithelium reported to be protective. Thus, elucidating mechanisms through which SARS-CoV-2 induces and antagonizes host innate immune responses is crucial to understanding viral pathogenesis. CoVs encode various innate immune antagonists, including the conserved nonstructural protein 15 (nsp15) which contains an endoribonuclease (EndoU) domain. We demonstrate that SARS-CoV-2 EndoU is a crucial interferon antagonist, by providing further evidence for the role of the conserved CoV nsp15 in antagonizing innate immune activation, thereby optimizing CoV replication.

Pre-dominance of dengue non-cross-reacting SARS-CoV-2 spike antibodies during the Omicron era and their role in the ADE-mediated surge of Dengue virus serotype 3 (preprint)

In India, the SARS-CoV-2 Delta wave (2020-21) gradually faded away with the advent of the Omicron variants (2021-present). Dengue incidences were observably less in Southeast Asia during the active years of the pandemic (2020-21). However, Dengue virus type 3 (DV3) cases were increasingly reported in India and many other dengue-endemic countries concurrent with the progression of the Omicron wave since 2022. This observation prompted us to investigate the current state of cross-reactivity between prevalent SARS-CoV-2 variants and different DV serotypes. Fifty-five COVID-19 serum samples (collected between January-September, 2022) and three pre-pandemic healthy serum samples were tested for DV or SARS-CoV-2 Immunoglobulin G/Immunoglobulin M (IgG/IgM) using the lateral flow immunoassays (LFIAs). The SARS-CoV-2 antibody (Ab)-positive samples were further tested for their ability to cross-neutralize DV types 1-4 (DV1-4) in Huh7 cell lines. Cross-reactivity between SARS-CoV-2 and DV diminished with the shift from Delta to Omicron prevalence. COVID-19 serum samples that were DV cross-reactive neutralized all DV serotypes, including DV3. However, Omicron wave serum samples were predominantly DV non-cross-reactive (about 70%) in LFIAs and coincided with the prevalence of BA.2 Omicron variant. They also cross-neutralized DV1, 2 and 4 but enhanced DV3 infectivity as evident from increased DV3 titres in virus neutralization test (VNT) compared to control serum samples. In conclusion, DV non-cross-reactive COVID-19 serum samples are becoming increasingly prominent in the present times. These non-cross-reactive serums could neutralize DV1, 2 and 4 but they are contributing to the surge in DV3 cases worldwide by means of ADE.

Impact of Emerging COVID-19 variants on psychosocial health: A Systematic Review (preprint)

Background: The COVID-19 pandemic has had significant psychological effects on individuals and communities around the world. Studies have found that the prevalence of anxiety and depression symptoms increased significantly during the pandemic. The goal of the study is to understand how the emerging new virus variants keep the world in a state of fear and the ways in which mental health measures can be implemented and adopted to alleviate anxiety. Methods: A broad search for observational studies were carried out in Pubmed, Google Scholar, Clinical Key, and World Medical Library. Studies that reported and/or related the existence of anxiety generated by suffering or not from diseases caused by the new emerging Covid-19 viruses and that for which the full text of the article was accessible were included in the study while systematic review and meta-analysis and studies in groups were excluded. Results: 22 studies were included in the review. The deleterious psychosocial effects were the restructuring of life, establishment of unhealthy habits, emergence of "corona phobia", fear and stigma of being afflicted with the disease and spreading it to loved ones, and lack of contact with others. Increased rates of depression and anxiety were also seen. The circulating variants responsible for these main psychosocial repercussions were: Epsilon, Zeta, Eta, Iota, Kappa, Alpha, Beta, Gamma, and Delta. Social support was found to be protective. Conclusion: Hence interventions targeted at promoting mental health should be considered a public health priority.

Effectiveness of Virtual Training in the Post-Pandemic Period Using the Kirkpatrick Model (preprint)

Teaching and training through online tools were used by most of the (HEIs) Higher Education Institute worldwide during covid-19 to cater to the needs of students who stay far away from universities/colleges. After the pandemic, the virtual model of education and training became a trend. The students and teachers are also more used to this trend and which is giving more opportunities to both learners and instructors.  One of the notable benefits of virtual teaching and learning platform is that it provides a flexible environment to gain knowledge, skills, and attitude simultaneously along with formal off-line education. This directly influences the employability of outgoing UG and PG students. In this paper, an attempt has been made to assess the perceived effectiveness of virtual training and education among outgoing graduates under the Kirkpatrick model.

COVID-19: From Emergence to Endemicity - A Comprehensive Review (preprint)

Severe Acute Respiratory Syndrome Coronavirus - 2 (SARS-CoV-2), later renamed Coronavirus Disease 2019 (COVID-19) was first identified in Wuhan, China, in early December 2019. Initially, the China office of the World Health Organization was informed of numerous cases of pneumonia of unidentified etiology in Wuhan, Hubei Province on December 31, 2019. This would subsequently result in a global pandemic with over 76 million confirmed cases of COVID-19 and 6.9 million deaths reported to the WHO. We have analyzed most of the data published since the beginning of the pandemic to compile this comprehensive review of SARS-CoV-2. We look at the core ideas, such as the etiology, epidemiology, pathogenesis, clinical symptoms, diagnostics, histopathologic findings, consequences, therapies, and vaccines. We have also included the long-term effects and myths associated with some therapeutics of COVID-19. This study comprehensively assesses of the SARS-CoV-2 virology, vaccines, medicines, and significant variants identified during the pandemic. Our review article is intended to provide medical practitioners with a better understanding of the fundamental sciences, clinical treatment, and prevention of COVID-19. As of June 2023, this paper contains the most recent data made accessible.

Runtime Safety Assurance of Autonomous Vehicles used for Last-mile Delivery in Urban Environments (preprint)

Last-mile delivery of goods has gained a lot of attraction during the COVID-19 pandemic. However, current package delivery processes often lead to parking in the second lane, which in turn has negative effects on the urban environment in which the deliveries take place, i.e., traffic congestion and safety issues for other road users. To tackle these challenges, an effective autonomous delivery system is required that guarantees efficient, flexible and safe delivery of goods. The project LogiSmile, co-funded by EIT Urban Mobility, pilots an autonomous delivery vehicle dubbed the Autonomous Hub Vehicle (AHV) that works in cooperation with a small autonomous robot called the Autonomous Delivery Device (ADD). With the two cooperating robots, the project LogiSmile aims to find a possible solution to the challenges of urban goods distribution in congested areas and to demonstrate the future of urban mobility. As a member of Nieders\"achsische Forschungszentrum f\"ur Fahrzeugtechnik (NFF), the Institute for Software and Systems Engineering (ISSE) developed an integrated software safety architecture for runtime monitoring of the AHV, with (1) a dependability cage (DC) used for the on-board monitoring of the AHV, and (2) a remote command control center (CCC) which enables the remote off-board supervision of a fleet of AHVs. The DC supervises the vehicle continuously and in case of any safety violation, it switches the nominal driving mode to degraded driving mode or fail-safe mode. Additionally, the CCC also manages the communication of the AHV with the ADD and provides fail-operational solutions for the AHV when it cannot handle complex situations autonomously. The runtime monitoring concept developed for the AHV has been demonstrated in 2022 in Hamburg. We report on the obtained results and on the lessons learned.

SELEX based aptamers with diagnostic and entry inhibitor therapeutic potential for SARS-CoV-2 (preprint)

Frequent mutation and variable immunological protection against vaccination is a common feature for COVID-19 pandemic. Early detection and confinement remain key to controlling further spread of infection. In response, we have developed an aptamer-based system that possesses both diagnostic and therapeutic potential towards the virus. A random aptamer library (~ 1017 molecules) was screened using systematic evolution of ligands by exponential enrichment (SELEX) and aptamer R was identified as a potent binder for the SARS-CoV-2 spike receptor binding domain (RBD) using in vitro binding assay. Using a pseudotyped viral entry assay we have shown that aptamer R specifically inhibited the entry of a SARS-CoV-2 pseudotyped virus in HEK293T-ACE2 cells but did not inhibit the entry of a Vesicular Stomatitis Virus (VSV) glycoprotein (G) pseudotyped virus, hence establishing its specificity towards SARS-CoV-2 spike protein. The antiviral potential of aptamers R and J (same central sequence as R but lacking flanked primer regions) was tested and showed 95.4% and 82.5% inhibition, respectively, against the SARS-CoV-2 virus. Finally, intermolecular interactions between the aptamers and the RBD domain were analyzed using in silico docking and molecular dynamics simulations that provided additional insight into the binding and inhibitory action of aptamers R and J.

Quantifying optimal resource allocation strategies for controlling epidemics.

Frequent emergence of communicable diseases is a major concern worldwide. Lack of sufficient resources to mitigate the disease burden makes the situation even more challenging for lower-income countries. Hence, strategy development for disease eradication and optimal management of the social and economic burden has garnered a lot of attention in recent years. In this context, we quantify the optimal fraction of resources that can be allocated to two major intervention measures, namely reduction of disease transmission and improvement of healthcare infrastructure. Our results demonstrate that the effectiveness of each of the interventions has a significant impact on the optimal resource allocation in both long-term disease dynamics and outbreak scenarios. The optimal allocation strategy for long-term dynamics exhibits non-monotonic behaviour with respect to the effectiveness of interventions, which differs from the more intuitive strategy recommended in the case of outbreaks. Further, our results indicate that the relationship between investment in interventions and the corresponding increase in patient recovery rate or decrease in disease transmission rate plays a decisive role in determining optimal strategies. Intervention programmes with decreasing returns promote the necessity for resource sharing. Our study provides fundamental insights into determining the best response strategy when controlling epidemics in resource-constrained situations.

Current Status of Intranasal COVID-19 Vaccine, its Usage and Efficacy: A Narrative Review

The creation of a vaccine against Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) has received top focus worldwide. The majority of the COVID-19 vaccine candidates created is given Intramuscularly (IM). Intranasal (IN) vaccines offer a great benefit due to the first involvement of mucosa of the nasal cavity in the due course of disease, also SARS-CoV-2 is spread through respiratory secretions which are infectious, and mucosal immunity due to IN vaccination could contribute significantly to controlling this disease. IN vaccination has been shown in preclinical and clinical investigations to produce significant levels of neutralising antibodies, mucosal IgA, and T-cell responses that protect against SARS-CoV-2 infection in the respiratory pathway. Blocking Coronavirus Disease-2019 (COVID-19) infection and transmission requires the immune system response at the initial infection site of the virus. Many IN vaccines are currently under trial for their safety and efficacy, while some are recently approved for use in specific conditions in India and are proven to be protective against the virus and safe also. In this context, this review will provide knowledge of the IN vaccines for their effectiveness and application. [ FROM AUTHOR] Copyright of Journal of Clinical & Diagnostic Research is the property of JCDR Research & Publications Private Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Ensuring self-sustainability in decentralized communities through solar cookers combined with food dryers

In the background of the COVID 2019 pandemic, the importance of developing realistic and efficient decentralized energy solutions is one of the essential requirements. This paper presents the performance of a small-scale solar box cooker cum dryer (SBCD) for decentralized communities and domestic scale applications. The drying process in SBCD uses a simple and effective method for moisture removal. It enables de-moisturization of the cooker interior, allowing efficient use of SBCD for the simultaneous dual-mode operation of cooking and drying. Cooker Opto-thermal Ratio (COR) as a thermal performance parameter and glycerin as a test load enable cooking process analysis. COR-based objective parameters (OPs) realistically comment on the cooker performance in the dual-mode operation. Drying kinetic studies describe the drying performance of the device. The levelized cost of cooking meals (LCCM) allows understating of the economics of SBCD. The mean value of COR for the cooker is 0.104 ± 0.0028 (m2·°C)/W with a percentage standard deviation of 2.69%. The experimental values of OPs, reference cooking time, and maximum achievable load temperature varies between 74 and 86 min and 103–111 °C, respectively. Thus, SBCD cooks in approximately 80–90 min and dries ∼ 100 g of food products simultaneously with 70–80 % moisture removal. The LCCM for SBCD is $ 0.0174 per meal. Thus, SBCD depicts a realistic solution for ensuring self-sustainability in decentralized communities.