bluuebunny/crossref_metadata_2025 huggingface dataset:
Barriers and Facilitators in the Transition From Higher Education to Employment for Students With Disabilities: A Rapid Systematic Review
Authors: Goodall Gemma , Mjøen Odd Morten , Witsø Aud Elisabeth , Horghagen Sissel , Kvam Lisbeth
Published: April 2022

Despite legislation promoting equal opportunities for people with disabilities in education and employment, evidence suggests that these environments are far from inclusive. While there is a wealth of evidence on the barriers that people with disabilities face in both higher education and the workplace, there is currently a lack of literature that summarizes knowledge on the transition between these two settings. As such, this rapid systematic literature review aimed to identify barriers and facilitators in the transition from higher education to employment for students and graduates with disabilities. Following PRISMA guidelines, we conducted a systematic search across three databases (PsycINFO, ERIC, and Web of Science) and included 59 studies for review. The included studies reported on research conducted across 20 countries, reporting on various types of disabilities and on different subject areas and professions. In addition to a quality appraisal, we performed a narrative synthesis on the included studies. From the synthesis, we identified numerous barriers and facilitators, and grouped them into seven themes: disclosure; attitudinal barriers and facilitators; accommodations, accessibility; institutional and organizational barriers and facilitators; discipline-specific barriers and facilitators; and disability-specific barriers and facilitators. Overall, findings suggest that students with disabilities must often work beyond their capacity in order to succeed in higher education and access opportunities for meaningful employment. Findings also suggest there is still much to be done in creating inclusive education and employment environments on an international level. Recommendations from this review include developing inclusive disclosure processes and providing education on disabilities for staff in both the education and labor sectors. Finally, we call for collaboration between higher education institutions, employment sectors, and students with disabilities.
Statistical Analysis Based Feature Selection Enhanced RF-PUF With >99.8% Accuracy on Unmodified Commodity Transmitters for IoT Physical Security
Authors: Bari Md Faizul , Agrawal Parv , Chatterjee Baibhab , Sen Shreyas
Published: April 2022

Due to the diverse and mobile nature of the deployment environment, smart commodity devices are vulnerable to various spoofing attacks which can allow a rogue device to get access to a large network. The vulnerability of the traditional digital signature-based authentication system lies in the fact that it uses only a key/pin, ignoring the device fingerprint. To circumvent the inherent weakness of the traditional system, various physical signature-based RF fingerprinting methods have been proposed in literature and RF-PUF is a promising choice among them. RF-PUF utilizes the inherent nonidealities of the traditional RF communication system as features at the receiver to uniquely identify a transmitter. It is resilient to key-hacking methods due to the absence of secret key requirements and does not require any additional circuitry on the transmitter end (no additional power, area, and computational burden). However, the concept of RF-PUF was proposed using MATLAB-generated data, which cannot ensure the presence of device entropy mapped to the system-level nonidealities. Hence, an experimental validation using commercial devices is necessary to prove its efficacy. In this work, for the first time, we analyze the effectiveness of RF-PUF on commodity devices, purchased off-the-shelf, without any modifications whatsoever. We have collected data from 30 Xbee S2C modules used as transmitters and released as a public dataset. A new feature has been engineered through PCA and statistical property analysis. With a new and robust feature set, it has been shown that 95% accuracy can be achieved using only ∼1.8 ms of test data fed into a neural network of 10 neurons in 1 layer, reaching >99.8% accuracy with a network of higher model capacity, for the first time in literature without any assisting digital preamble. The design space has been explored in detail and the effect of the wireless channel has been investigated. The performance of some popular machine learning algorithms has been tested and compared with the neural network approach. A thorough investigation of various PUF properties has been done. With extensive testing of 41238000 cases, the detection probability for RF-PUF for our data is found to be 0.9987, which, for the first time, experimentally establishes RF-PUF as a strong authentication method. Finally, the potential attack models and the robustness of RF-PUF against them have been discussed.
Development, Validation, and Application of the Turbulent Combustion Model for 3D CFD Code CYCAS
Authors: Yabing Li , Peng Chen , Chubin Lin , Meilan Chen
Published: April 2022

The CYCAS code is a 3D CFD code developed independently by the China Nuclear Power Research Institute, aiming at hydrogen safety analysis in containments. In order to equip the CYCAS code with the capability of combustion analysis, a combustion model is screened and developed, and validated with two cases from International Standard Problems. Then a combustion analysis is conducted with a containment to demonstrate the capability of CYCAS to evaluate the pressure and thermal load of combustion. Firstly, the mature and widely-used combustion model, i.e., the Burning Velocity Model (BVM) with Zimont correlation is developed for the CYCAS code in this study. Thereafter, the lamiar flame speed correlation for CYCAS is screened based on the containment atmospheric condition during the accidents. Then, two cases from the THAI facility are calculated to validate the model. The results show that the combustion model in CYCAS manages to have reasonable prediction on the slow deflagration for the gas mixture both with and without steam. Finally, a containment combustion analysis is conducted with the initial hydrogen distribution calculated from a postulated accident. The analysis shows that the CYCAS manages to calculate the pressure and thermal load of the combustion to evaluate the influence of the combustion on the containment integrity and equipment survivability.
Optimal Capacity Allocation Model for Integrated Energy Microgrids Considering Aggregation of Prosumers Under Multi-Market Mechanisms
Authors: Wang Xinwen , Bai Xiaoqing , Wang Puming
Published: April 2022

Traditional energy consumers gradually change to the new form of aggregation of prosumers (AOP) in the integrated energy microgrid (IEM) on the demand side. The emergence of the AOPs has led to the IEM’s structure changes, resulting in the emergence of two major stakeholders, the integrated energy microgrid service providers (IEMSPs) and the AOPs. The primary studies of this study are to configure the capacity for devices managed by IEMSP and AOPs with minimal costs. To achieve satisfaction for both IEMSP and AOPs, the approach of the non-cooperative game is used to allocate the capacity of devices managed by IEMSP and devices of AOPs. In detail, the IEMSP acts as a leader who determines the electricity pricing to minimize the cost, while the AOPs respond with electricity purchase or sales as the followers according to the price information provided by IEMSP. Moreover, electricity trading between AOPs is considered to reduce transmission losses and promote energy consumption nearby. To investigate the application of the multi-market mechanism in the optimal capacity allocation of IEM, a coupling mechanism of green certificate trading, carbon emission trading, and the electricity market is built in the proposed model. The cases are studied to verify the effectiveness of the proposed model in terms of saving the configuration capacity, reducing carbon emissions, and increasing the environmental benefits.
A Detailed Review Investigating the Mathematical Modeling of Solar Stills
Authors: Ayoobi Ahmadreza , Ramezanizadeh Mahdi
Published: April 2022

In recent years providing potable water for humans has become a major problem, especially in rural and remote regions. In the last few decades, methods of providing potable water using solar radiation have proved that there are methods without negative impacts. Solar is a solution and attractive alternative to still non-potable water without adverse consequences on ecosystems. Researchers have presented the results of their investigations in journals, using experimental, numerical, and analytical forms through the study of solar still performance in native climatic conditions. This paper undertakes an extensive review of recent modeling processes in solar stills and the thermal models proposed and derived for different types of solar stills and the modifications recommended to enhance efficiency and performance. During the selection of appropriate geometry and belonging components, this evaluation demonstrates that numerous designs and characteristics are useful in terms of productivity and efficiency. According to the reviewed results, the definition of concentration ratio is a fundamental concept for evaluating the evaporative heat transfer coefficient in relation to the convective heat transfer coefficient. Employing phase change materials, the results reveal that a large mass of PCM produces less solar still productivity, whereas increasing the PCM to water mass ratio from 10 to 100 reduces productivity by up to 30%. Using a parabolic concentrator, results show that productivity can be increased by 56 and 38.5% in the winter and summer, respectively.
Short-Term Probability Density Function Forecasting of Industrial Loads Based on ConvLSTM-MDN
Authors: Wang Yuan Y. , Wang Ting Y. , Chen Xiao Q. , Zeng Xiang J. , Huang Jing J. , Tang Xia F.
Published: April 2022

Load forecasting for industrial customers is essential for reliable operation decisions in the electric power industry. However, most of the load forecasting literature has been focused on deterministic load forecasting (DLF) without considering information on the uncertainty of industrial load. This article proposes a probabilistic density load forecasting model comprising convolutional long short-term memory (ConvLSTM) and a mixture density network (MDN). First, a sliding window strategy is adopted to convert one-dimensional (1D) data into two-dimensional (2D) matrices to reconstruct input features. Then the ConvLSTM is utilized to capture the deep information of the input features. At last, the mixture density network capable of directly predicting probability density functions of loads is adopted. Experimental results on the load datasets of three different industries show the accuracy and reliability of the proposed method.
Effect of Sewage Treatment Plant Effluent on Water Quality of Zhangze Reservoir Based on EFDC Model
Authors: Yang Long , Wei Jia , Qi Jun , Zhang Min
Published: April 2022

Understanding how external water affects the water quality of target water bodies is an important prerequisite for predicting water quality changes and formulating pollutant reduction plans. Using the EFDC modeling system platform, this study constructed the hydrodynamic and pollutant dispersion and diffusion models of Zhangze Reservoir, and by using the hydrology and water quality data from 2013 to 2018, this study examines the different water quality responses of Zhangze Reservoir under different inflow water control scenarios. The results show that the simulated value of the hydrological station is basically consistent with the measured value of the hydrological station. Under the current Class III water quality requirements for Zhangze Reservoir, direct inflow of effluent from the wastewater treatment plant of the main urban area into the reservoir will have a significant impact on the water quality. When the effluent is purified through constructed wetlands, it significantly improves the water quality of the reservoir, but the concentration of TN and TP still cannot reach the Class III standard in the short term,. When all rivers entering the reservoir meet the standard and the effluent from the wastewater treatment plant in the main urban area does not enter the reservoir, the content of COD, ammonia nitrogen and TP in water will reach the Class III standard, but reducing the TN content to meet the standard requirement will be difficult within 3 years.
The Sustainable Environment in Uruguay: The Roles of Financial Development, Natural Resources, and Trade Globalization
Authors: Awosusi Abraham Ayobamiji , Xulu Nkosinathi G. , Ahmadi Mohsen , Rjoub Husam , Altuntaş Mehmet , Uhunamure Solomon Eghosa , Akadiri Seyi Saint , Kirikkaleli Dervis
Published: April 2022

As the world continues to be a globalized society, there have been variations in environmental quality, but studies including trade globalization into the environmental policy framework remain inconclusive. Therefore, employing the time series dataset of Uruguay over the period between 1980 and 2018, the main objective of this current study is to investigate the effect of trade globalization, natural resources rents, economic growth, and financial development on carbon emissions. By employing the bounds testing procedures in combination with the critical approximation p-values of Kripfganz and Schneider (2018), the Autoregressive Distributed Lag estimator, and spectral causality test to achieve the goal of this research. The outcomes of the bounds test confirm a long-run connection between carbon emissions and these determinants. Moreover, from the outcome of the Autoregressive Distributed Lag estimator, we observed that trade liberalization is found to exert CO2 emissions in the long and short run. The economic expansion in Uruguay imposes significant pressure on the quality of the environment in the long and short run. The abundance of natural resources significantly increases environmental deterioration in the long and short run. Furthermore, we uncover that financial development does not impact environmental deterioration in Uruguay. Finally, the outcome of the spectral causality test detected that trade globalization, economic growth, and natural resources forecast carbon emissions with the exclusion of financial development. Based on the outcome, this study suggests that policies should be tailored towards international trade must be reassessed, and the restrictions placed on the exportation of polluting-intensive commodities must be reinforced.
Sing or Jam? Density-Dependent Food Competition Strategies in Mexican Free-Tailed Bats (Tadarida brasiliensis)
Authors: Corcoran Aaron J.
Published: April 2022

Organisms compete for food in many ways, but it is often difficult to know why they use certain competition strategies over others. Bats compete for food either through aggression coupled with food-claiming signals or by actively interfering with a competitor’s sensory processing during prey pursuit (i.e., jamming). It is not known why these different behaviors are exhibited. I studied food competition between Mexican free-tailed bats (Tadarida brasiliensis) at foraging sites in Arizona and New Mexico using passive acoustic recording, insect sampling and 3-D infrared videography with or without supplemental lighting that concentrated prey. Bat activity was quantified by the number of recorded echolocation calls, while feeding behavior was indicated by feeding buzzes. Two competitive behaviors were observed—song, which was produced by bats chasing conspecifics, and sinFM calls, which jam echolocation of competitors pursuing prey. Song production was most common when few bats were present and feeding at low rates. In contrast, jamming signals were most common with many bats present and feeding at high rates. Supplemental lighting increased the numbers of bats, feeding buzzes and sinFM calls, but not song. These results indicate that bats employ different strategies—singing and chasing competitors at low bat densities but jamming competitors at high bat densities. Food claiming signals (song) may only be effective with few competitors present, whereas jamming can be effective with many bats at a foraging site. Multiple competition strategies appear to have evolved in bats that are used under different densities of competitors.
The bZIP Transcription Factor Family in Adzuki Bean (Vigna Angularis): Genome-Wide Identification, Evolution, and Expression Under Abiotic Stress During the Bud Stage
Authors: Yin Zhengong , Meng Xianxin , Guo Yifan , Wei Shuhong , Lai Yongcai , Wang Qiang
Published: April 2022

Adzuki bean (Vigna angularis) is an important dietary legume crop that was first cultivated and domesticated in Asia. Currently, little is known concerning the evolution and expression patterns of the basic leucine zipper (bZIP) family transcription factors in the adzuki bean. Through the PFAM search, 72 bZIP members of adzuki bean (VabZIP) were identified from the reference genome. Most of them were located on 11 chromosomes and seven on an unknown chromosome. A comprehensive analysis, including evolutionary, motifs, gene structure, cis-elements, and collinearity was performed to identify VabZIP members. The subcellular localization results showed VabZIPs might locate on the nuclear. Quantitative real-time PCR (qRT-PCR) analysis of the relative expression of VabZIPs in different tissues at the bud stage revealed that VabZIPs had a tissue-specific expression pattern, and its expression was influenced by abiotic stress. These characteristics of VabZIPs provide insights for future research aimed at developing interventions to improve abiotic stress resistance.
PredMHC: An Effective Predictor of Major Histocompatibility Complex Using Mixed Features
Authors: Chen Dong , Li Yanjuan
Published: April 2022

The major histocompatibility complex (MHC) is a large locus on vertebrate DNA that contains a tightly linked set of polymorphic genes encoding cell surface proteins essential for the adaptive immune system. The groups of proteins encoded in the MHC play an important role in the adaptive immune system. Therefore, the accurate identification of the MHC is necessary to understand its role in the adaptive immune system. An effective predictor called PredMHC is established in this study to identify the MHC from protein sequences. Firstly, PredMHC encoded a protein sequence with mixed features including 188D, APAAC, KSCTriad, CKSAAGP, and PAAC. Secondly, three classifiers including SGD, SMO, and random forest were trained on the mixed features of the protein sequence. Finally, the prediction result was obtained by the voting of the three classifiers. The experimental results of the 10-fold cross-validation test in the training dataset showed that PredMHC can obtain 91.69% accuracy. Experimental results on comparison with other features, classifiers, and existing methods showed the effectiveness of PredMHC in predicting the MHC.
Lactoferrin as Immune-Enhancement Strategy for SARS-CoV-2 Infection in Alzheimer’s Disease Patients
Authors: Bartolomé Fernando , Rosa Luigi , Valenti Piera , Lopera Francisco , Hernández-Gallego Jesús , Cantero José Luis , Orive Gorka , Carro Eva
Published: April 2022

Coronavirus 2 (SARS-CoV2) (COVID-19) causes severe acute respiratory syndrome. Severe illness of COVID-19 largely occurs in older people and recent evidence indicates that demented patients have higher risk for COVID-19. Additionally, COVID-19 further enhances the vulnerability of older adults with cognitive damage. A balance between the immune and inflammatory response is necessary to control the infection. Thus, antimicrobial and anti-inflammatory drugs are hopeful therapeutic agents for the treatment of COVID-19. Accumulating evidence suggests that lactoferrin (Lf) is active against SARS-CoV-2, likely due to its potent antiviral and anti-inflammatory actions that ultimately improves immune system responses. Remarkably, salivary Lf levels are significantly reduced in different Alzheimer’s disease (AD) stages, which may reflect AD-related immunological disturbances, leading to reduced defense mechanisms against viral pathogens and an increase of the COVID-19 susceptibility. Overall, there is an urgent necessity to protect AD patients against COVID-19, decreasing the risk of viral infections. In this context, we propose bovine Lf (bLf) as a promising preventive therapeutic tool to minimize COVID-19 risk in patients with dementia or AD.
Complement Mediated Endothelial Damage in Thrombotic Microangiopathies
Authors: Blasco Miquel , Guillén-Olmos Elena , Diaz-Ricart Maribel , Palomo Marta
Published: April 2022

Thrombotic microangiopathies (TMA) constitute a group of different disorders that have a common underlying mechanism: the endothelial damage. These disorders may exhibit different mechanisms of endothelial injury depending on the pathological trigger. However, over the last decades, the potential role of the complement system (CS) has gained prominence in their pathogenesis. This is partly due to the great efficacy of complement-inhibitors in atypical hemolytic syndrome (aHUS), a TMA form where the primary defect is an alternative complement pathway dysregulation over endothelial cells (genetic and/or adquired). Complement involvement has also been demonstrated in other forms of TMA, such as thrombotic thrombocytopenic purpura (TTP) and in Shiga toxin-producing Escherichia coli hemolytic uremic syndrome (STEC-HUS), as well as in secondary TMAs, in which complement activation occurs in the context of other diseases. However, at present, there is scarce evidence about the efficacy of complement-targeted therapies in these entities. The relationship between complement dysregulation and endothelial damage as the main causes of TMA will be reviewed here. Moreover, the different clinical trials evaluating the use of complement-inhibitors for the treatment of patients suffering from different TMA-associated disorders are summarized, as a clear example of the entry into a new era of personalized medicine in its management.
The Effectiveness of a Group Kickboxing Training Program on Sarcopenia and Osteoporosis Parameters in Community-Dwelling Adults Aged 50–85 Years
Authors: Lin Yen-An , Chen Lee-Hwa , Chen Fang-Ping , Wong Alice May-Kuen , Hsu Chih-Chan , Chen Jau-Yuan
Published: April 2022

Background

Sarcopenia and osteoporosis are important health issues faced by older people. These are often associated with each other and share common risk factors and pathologic mechanisms. In the recently revised consensus of the European Working Group on Sarcopenia in Older People, low muscle strength has been defined as the first characteristic of sarcopenia rather than a loss in muscle mass, and walking speed has been stated as an indicator of the severity of sarcopenia. It is believed that these markers of muscle function can be potentially reversed via exercise-based interventions. The purpose of this study was to evaluate the effects of kickboxing exercise training on the parameters of sarcopenia and osteoporosis in community-dwelling adults.

Methods

In total, one hundred eligible subjects were randomized into an intervention group (n = 50) with 76% women and control group (n = 50) with 86% women. Both the intervention and control groups were provided with classroom lectures and personal consultations pertaining to sarcopenia and osteoporosis, whereas a 12-week kickboxing exercise training was arranged only for the intervention group. All anthropometric, physical performance, body composition, and bone mineral density measurements along with participant completed questionnaires were conducted before and after the training period.

Results

After 12 weeks, 41 participants in the intervention group and 34 participants in the control group completed the final assessments. There was no difference between the intervention and control groups in terms of basic demographic data. The BMI (+1.14%) of the control group increased significantly during the study period. The waist circumference (−6.54%), waist-to-height ratio (−6.57%), waist–to–hip ratio (−4.36%), total body fat (−1.09%), and visceral fat area (−4.6%) decreased significantly in the intervention group. Handgrip strength (+5.46%) and gait speed (+5.71%) improved significantly in the intervention group. The lean body mass increased by 0.35% in the intervention group and by 0.9% in the control group. The femoral neck bone mineral density (−1.45%) and T score (−3.72%) of the control group decreased significantly. The intervention group had more improvement in the status of sarcopenia (OR 1.91) and osteoporosis over the control group. Finally, the intervention group had less deterioration in the status of sarcopenia (OR 0.2) and osteoporosis (OR 0.86) compared with the control group.

Conclusion

Our study demonstrated that a 12-week kickboxing exercise training program is effective for improving sarcopenic parameters of muscle strength and function, but not muscle mass in adults, aged 50–85 years. Furthermore, markers of osteoporosis also showed improvement. These findings suggest that a 12-week kickboxing program is effective for muscle and bone health among community-dwelling older individuals.
Interaction Between CD34+ Fibrocytes and Airway Smooth Muscle Promotes IL-8 Production and Akt/PRAS40/mTOR Signaling in Asthma
Authors: Lin Ting-Yu , Chang Po-Jui , Lo Chun-Yu , Lo Yu-Lun , Yu Chih-Teng , Lin Shu-Min , Kuo Chih-His Scott , Lin Horng-Chyuan
Published: April 2022

Background

The circulating progenitor cells of fibroblasts (fibrocytes) have been shown to infiltrate the airway smooth muscle compartment of asthma patients; however, the pathological significance of this discovery has yet to be elucidated. This study established a co-culture model of airway smooth muscle cells (ASMCs) and fibrocytes from asthmatic or normal subjects to evaluate innate cytokine production, corticosteroid responses, and signaling in ASMCs.

Methods

CD34+ fibrocytes were purified from peripheral blood of asthmatic (Global Initiative for Asthma treatment step 4–5) and normal subjects and cultured for 5∼7 days. In a transwell plate, ASMCs were co-cultured with fibrocytes at a ratio of 2:1, ASMCs were cultured alone (control condition), and fibrocytes were cultured alone for 48 h. Measurements were obtained of interleukin-8 (IL-8), IL-6, IL-17, thymic stromal lymphopoietin, and IL-33 levels in the supernatant and IL-33 levels in the cell lysate of the co-culture. Screening for intracellular signaling in the ASMCs after stimulation was performed using condition medium from the patients’ co-culture (PtCM) or IL-8. mRNA and western blot analysis were used to analyze AKT/mTOR signaling in ASMCs stimulated via treatment with PtCM or IL-8.

Results

Compared with ASMCs cultured alone, IL-8 levels in the supernatant and IL-33 levels in the ASMCs lysate were significantly higher in samples co-cultured from asthmatics, but not in those co-cultured from normal subjects. Corticosteroid-induced suppression of IL-8 production was less pronounced in ASMCs co-cultured with fibrocytes from asthma patients than in ASMCs co-cultured from normal subjects. ASMCs stimulated using PtCM and IL-8 presented elevating activated AKT substrate PRAS40. Treatment with IL-8 and PtCM increased mRNA expression of mTOR and P70S6 kinases in ASMCs. Treatment with IL-8 and PtCM also significantly increased phosphorylation of AKT and mTOR subtract S6 ribosomal protein in ASMCs.

Conclusion

The interaction between ASMCs and fibrocytes from asthmatic patients was shown to increase IL-8 and IL-33 production and promote AKT/mTOR signaling in ASMCs. IL-8 production in the co-culture from asthmatic patients was less affected by corticosteroid than was that in the co-culture from normal subjects. Our results elucidate the novel role of fibrocytes and ASMCs in the pathogenesis of asthma.
Can Leprosy Reaction States Mimic Symptoms of Fibromyalgia? A Cross-Sectional Analytical Study
Authors: Feitosa Maria Stella Cochrane , Santos Gabriela Profírio Jardim , Cerqueira Selma Regina Penha Silva , Rodrigues Gabriel Lima , Mota Licia Maria Henrique da , Gomes Ciro Martins
Published: April 2022

Leprosy causes significant pain in affected patients, especially those experiencing reactional states. Fibromyalgia is characterized by widespread pain and is often accompanied by fatigue. Confusion between the clinical manifestations of fibromyalgia and those of leprosy reactions is possible at the primary care level, the first contact with the health system in most cases. We aimed to determine whether the presence of leprosy reactional states is related to the development of signs and symptoms included in the case definition of fibromyalgia and establish recommendations for obtaining the correct diagnosis. We performed a cross-sectional study in which the main independent variable was the presence of any leprosy reactional state and the primary dependent variable was the diagnosis of fibromyalgia according to the 2016 Revisions of the 2010/2011Fibromyalgia Provisional Criteria of the American College of Rheumatology. Forty-three patients were included in the study. Twenty-eight (65.12%) patients had a type I reactional state, only 1 (2.33%) had an isolated type II reactional state, and 5 (11.63%) had both type I and type II reactional states. Only 2 patients who suffered from cooccurring type I and II reactional states obtained sufficient scores for the diagnosis of fibromyalgia. Although diffuse pain was common in leprosy patients, none of the types of reactional states were associated with a higher frequency of criteria for fibromyalgia. We can conclude that a leprosy reactional state is probably not a risk factor for fibromyalgia but can act as a confounder, as tender points may be similar in both diagnoses. In patients diagnosed with fibromyalgia, leprosy must be considered in the differential diagnosis in endemic regions.
Pharmaceutical Industry Evaluation of the Effectiveness and Efficiency of the ZaZiBoNa Collaborative Medicines Registration Initiative: The Way Forward
Authors: Sithole Tariro , Mahlangu Gugu , Walker Stuart , Salek Sam
Published: April 2022

Introduction

The common technical document (CTD) format harmonised the requirements for the registration of medicines, which had traditionally differed from country to country, making it possible for countries to collaborate and conduct joint reviews of applications. One such collaborative medicines registration initiative is the Southern African Development Community ZaZiBoNa, established in 2013. A recent study was carried out with the nine active member regulatory authorities of the ZaZiBoNa to determine their views on its operational effectiveness and efficiency. Having obtained the authorities’ views, the aim of this study was to evaluate the effectiveness and efficiency of the current operating model of the ZaZiBoNa initiative including the challenges it faces as well as identifying opportunities for improvement from the applicants’ perspective.

Methods

Applicants who had submitted registration/marketing authorisation applications for assessment under the ZaZiBoNa initiative during 2017–2021 were recruited into the study. Data was collected in 2021 using the Process, Effectiveness and Efficiency rating questionnaire (PEER-IND) developed by the authors. The questionnaire was completed by a representative responsible for ZaZiBoNa submissions in each company.

Results

The pharmaceutical industry was of the view that the ZaZiBoNa initiative has achieved shorter timelines for approval of medicines, resulting in increased availability of quality-assured medicines for patients in the SADC region. Harmonisation of registration requirements and joint reviews have reduced the workload for both the pharmaceutical industry and the regulatory authorities. Some of the challenges identified were the lack of a centralised submission and tracking system, and the lack of information for applicants on the process for submission of ZaZiBoNa dossiers/applications in the individual countries, including contact details of the focal person. The establishment of a regional unit hosted in one of the member countries to centrally receive and track ZaZiBoNa dossiers/applications was identified as the best strategy for moving forward in the interim with the long-term goal being the establishment of a regional medicines authority.

Conclusion

There was consensus between the pharmaceutical industry and the regulatory authorities as to the way forward to improve the effectiveness and efficiency of the ZaZiBoNa initiative. Implementation of the recommendations identified in this study will lead to enhanced regulatory performance.
The Association Between Diabetes Mellitus and the Risk of Latent Tuberculosis Infection: A Systematic Review and Meta-Analysis
Authors: Liu Qiao , Yan Wenxin , Liu Runqing , Bo Ershu , Liu Jue , Liu Min
Published: April 2022

Background

The estimated global latent tuberculosis infection (LTBI) burden indicates a large reservoir of population at risk of developing active tuberculosis (TB). Previous studies suggested diabetes mellitus (DM) might associate with LTBI, though still controversial. We aimed to systematically assess the association between DM and LTBI.

Methods

We searched PubMed, Embase, Cochrane Library and Web of Science. Observational studies reporting the number of LTBI and non-LTBI individuals with and without DM were included. Random-effects or fixed-effects models were used to estimate the pooled effect by risk ratios (RRs) and odds ratios (ORs) and its 95% confidence interval (CI), using the original number of participants involved.

Results

20 studies involving 4,055,082 participants were included. The pooled effect showed a significant association between DM and LTBI (for cohort studies,RR= 1.62, 95% CI: 1.02–2.56; for cross-sectional studies,OR= 1.55, 95% CI: 1.30–1.84). The pooled OR was high in studies with healthcare workers (5.27, 95% CI: 1.52–8.20), refugees (2.88, 95% CI: 1.93–4.29), sample size of 1,000–5,000 (1.99, 95% CI: 1.49–2.66), and male participants accounted for less than 40% (2.28, 95% CI: 1.28–4.06). Prediabetes also associated with LTBI (OR= 1.36, 95% CI: 1.01–1.84).

Conclusion

The risk of LTBI was found to be a 60% increase in DM patients, compared with non-DM patients. LTBI screening among DM patients could be of vital importance. More studies are needed to explore appropriate strategies for targeted LTBI screening among DM patients.
Longitudinal and Comparative Analysis of Gut Microbiota of Tunisian Newborns According to Delivery Mode
Authors: Hanachi Mariem , Maghrebi Olfa , Bichiou Haifa , Trabelsi Ferdaous , Bouyahia Najla Maha , Zhioua Fethi , Belghith Meriam , Harigua-Souiai Emna , Baouendi Meriem , Guizani-Tabbane Lamia , Benkahla Alia , Souiai Oussema
Published: April 2022

Microbiota colonization is a dynamic process that impacts the health status during an individual's lifetime. The composition of the gut microbiota of newborns is conditioned by multiple factors, including the delivery mode (DM). Nonetheless, the DM's influence remains uncertain and is still the subject of debate. In this context, the medical indication and the emergency of a cesarean delivery might have led to confounding conclusions regarding the composition and diversity of the neonatal microbiome. Herein, we used high-resolution shotgun sequencing to decipher the composition and dynamics of the gut microbiota composition of Tunisian newborns. Stool samples were collected from 5 elective cesarean section (ECS) and 5 vaginally delivered (VD) newborns at the following time points: Day 0, Day 15, and Day 30. The ECS and VD newborns showed the same level of bacterial richness and diversity. In addition, our data pointed to a shift in microbiota community composition during the first 2 weeks, regardless of the DM. Both ECS and VD showed a profile dominated by Proteobacteria, Actinobacteria, and Firmicutes. However, ECS showed an underrepresentation of Bacteroides and an enrichment of opportunistic pathogenic species of the ESKAPE group, starting from the second week. Besides revealing the intestinal microbiota of Tunisian newborns, this study provides novel insights into the microbiota perturbations caused by ECS.
Single and Combined Effects of Clostridium butyricum and Coccidiosis Vaccine on Growth Performance and the Intestinal Microbiome of Broiler Chickens
Authors: Cai Haiming , Liao Shenquan , Li Juan , Liu Qihong , Luo Shengjun , Lv Minna , Lin Xuhui , Hu Junjing , Zhang Jianfei , Qi Nanshan , Sun Mingfei
Published: April 2022

Avian coccidiosis is an important intestinal protozoan disease that has caused major economic losses to the poultry industry. Clostridium butyricum can not only maintain the stability of the intestinal barrier, but can also improve the production performance of broiler chickens. We studied the effects of feeding C. butyricum alone, administration of coccidiosis vaccine alone, and the combined administration of C. butyricum and coccidiosis vaccine on body weight gain, feed consumption, and feed conversion ratio of broilers. Meanwhile, intestinal contents of 8- and 15-day-old broilers were collected, and their intestinal microbiome was characterized by high-throughput sequencing of the V3–V4 region of 16S rDNA. We analyzed the oocysts per gram values and lesion scores in the C. butyricum alone group, in a group challenged with the coccidiosis-causing parasite, Eimeria, and in groups simultaneously challenged Eimeria and pretreated with C. butyricum, the coccidiosis vaccine, or combined C. butyricum and coccidiosis vaccine. Intestinal tissue samples were collected from 32-day-old broilers for microbiome analysis. Our results showed that combination of C. butyricum with coccidiosis vaccine significantly improved the performance of broiler chickens and also significantly reduced the oocysts per gram value and intestinal lesions caused by Eimeria sp. infection. Furthermore, C. butyricum and coccidiosis vaccine administered alone or in combination significantly increased the relative abundance of the immune biomarker genus Barnesiella. The significant increase in the abundance of the Clostridia_UCG.014, Eubacterium coprostanoligenes group and Bacteroides was a key factor in controlling Eimeria sp. infection.
Microbial Communities in Volcanic Glacier Ecosystems
Authors: Garcia-Lopez Eva , Ruiz-Blas Fatima , Sanchez-Casanova Silvia , Peña Perez Sonia , Martin-Cerezo Maria Luisa , Cid Cristina
Published: April 2022

Glaciers constitute a polyextremophilic environment characterized by low temperatures, high solar radiation, a lack of nutrients, and low water availability. However, glaciers located in volcanic regions have special characteristics, since the volcanic foci provide them with heat and nutrients that allow the growth of microbial communities highly adapted to this environment. Most of the studies on these glacial ecosystems have been carried out in volcanic environments in the northern hemisphere, including Iceland and the Pacific Northwest. To better know, the microbial diversity of the underexplored glacial ecosystems and to check what their specific characteristics were, we studied the structure of bacterial communities living in volcanic glaciers in Deception Island, Antarctica, and in the Kamchatka peninsula. In addition to geographic coordinates, many other glacier environmental factors (like volcanic activity, altitude, temperature, pH, or ice chemical composition) that can influence the diversity and distribution of microbial communities were considered in this study. Finally, using their taxonomic assignments, an attempt was made to compare how different or similar are the biogeochemical cycles in which these microbiomes are involved.
Diversity of Lysis-Resistant Bacteria and Archaea in the Polyextreme Environment of Salar de Huasco
Authors: Corona Ramírez Andrea , Cailleau Guillaume , Fatton Mathilda , Dorador Cristina , Junier Pilar
Published: April 2022

The production of specialized resting cells is a remarkable strategy developed by several organisms to survive unfavorable environmental conditions. Spores are specialized resting cells that are characterized by low to absent metabolic activity and higher resistance. Spore-like cells are known from multiple groups of bacteria, which can form spores under suboptimal growth conditions (e.g., starvation). In contrast, little is known about the production of specialized resting cells in archaea. In this study, we applied a culture-independent method that uses physical and chemical lysis, to assess the diversity of lysis-resistant bacteria and archaea and compare it to the overall prokaryotic diversity (direct DNA extraction). The diversity of lysis-resistant cells was studied in the polyextreme environment of the Salar de Huasco. The Salar de Huasco is a high-altitude athalassohaline wetland in the Chilean Altiplano. Previous studies have shown a high diversity of bacteria and archaea in the Salar de Huasco, but the diversity of lysis-resistant microorganisms has never been investigated. The underlying hypothesis was that the combination of extreme abiotic conditions might favor the production of specialized resting cells. Samples were collected from sediment cores along a saline gradient and microbial mats were collected in small surrounding ponds. A significantly different diversity and composition were found in the sediment cores or microbial mats. Furthermore, our results show a high diversity of lysis-resistant cells not only in bacteria but also in archaea. The bacterial lysis-resistant fraction was distinct in comparison to the overall community. Also, the ability to survive the lysis-resistant treatment was restricted to a few groups, including known spore-forming phyla such as Firmicutes and Actinobacteria. In contrast to bacteria, lysis resistance was widely spread in archaea, hinting at a generalized resistance to lysis, which is at least comparable to the resistance of dormant cells in bacteria. The enrichment of Natrinema and Halarchaeum in the lysis-resistant fraction could hint at the production of cyst-like cells or other resistant cells. These results can guide future studies aiming to isolate and broaden the characterization of lysis-resistant archaea.
Interfacing Machine Learning and Microbial Omics: A Promising Means to Address Environmental Challenges
Authors: McElhinney James M. W. R. , Catacutan Mary Krystelle , Mawart Aurelie , Hasan Ayesha , Dias Jorge
Published: April 2022

Microbial communities are ubiquitous and carry an exceptionally broad metabolic capability. Upon environmental perturbation, microbes are also amongst the first natural responsive elements with perturbation-specific cues and markers. These communities are thereby uniquely positioned to inform on the status of environmental conditions. The advent of microbial omics has led to an unprecedented volume of complex microbiological data sets. Importantly, these data sets are rich in biological information with potential for predictive environmental classification and forecasting. However, the patterns in this information are often hidden amongst the inherent complexity of the data. There has been a continued rise in the development and adoption of machine learning (ML) and deep learning architectures for solving research challenges of this sort. Indeed, the interface between molecular microbial ecology and artificial intelligence (AI) appears to show considerable potential for significantly advancing environmental monitoring and management practices through their application. Here, we provide a primer for ML, highlight the notion of retaining biological sample information for supervised ML, discuss workflow considerations, and review the state of the art of the exciting, yet nascent, interdisciplinary field of ML-driven microbial ecology. Current limitations in this sphere of research are also addressed to frame a forward-looking perspective toward the realization of what we anticipate will become a pivotal toolkit for addressing environmental monitoring and management challenges in the years ahead.
Overexpression of BIT33_RS14560 Enhances the Biofilm Formation and Virulence of Acinetobacter baumannii
Authors: Yang Ruifu , Lai Bipeng , Liao Kang , Liu Baomo , Huang Lixia , Li Shaoli , Gu Jincui , Lin Ziying , Chen Yili , Wang Shuaishuai , Qiu Yanli , Deng Jiating , Chen Simin , Zhuo Chao , Zhou Yanbin
Published: April 2022

Acinetobacter baumannii, a strictly aerobic, non-lactose fermented Gram-negative bacteria, is one of the important pathogens of nosocomial infection. Major facilitator superfamily (MFS) transporter membrane proteins are a class of proteins that widely exists in microbial genomes and have been revealed to be related to biofilm formation in a variety of microorganisms. However, as one of the MFS transporter membrane proteins, little is known about the role of BIT33_RS14560 in A. baumannii. To explore the effects of BIT33_RS14560 on biofilm formation of A. baumannii, the biofilm formation abilities of 62 isolates were firstly investigated and compared with their transcript levels of BIT33_RS14560. Then, this specific gene was over-expressed in a standard A. baumannii strain (ATCC 19606) and two isolates of extensively drug-resistant A. baumannii (XDR-Ab). Bacterial virulence was observed using a Galleria mellonella infection model. High-throughput transcriptome sequencing (RNA seq) was performed on ATCC 19606 over-expressed strain and its corresponding empty plasmid control strain. Spearman’s correlation analysis indicated a significant negative correlation (R = −0.569, p = 0.000) between the △CT levels of BIT33_RS1456 and biofilm grading of A. baumannii isolates. The amount of A. baumannii biofilm was relatively high within 12–48 h. Regardless of standard or clinical strains; the biofilm biomass in the BIT33_RS14560 overexpression group was significantly higher than that in the control group ( p < 0.0001). Kaplan–Meier survival curve analysis showed that the mortality of G. mellonella was significantly higher when infected with the BIT33_RS14560 overexpression strain (χ2 = 8.462, p = 0.004). RNA-Seq showed that the mRNA expression levels of three genes annotated as OprD family outer membrane porin, glycosyltransferase family 39 protein, and glycosyltransferase family 2 protein, which were related to bacterial adhesion, biofilm formation, and virulence, were significantly upregulated when BIT33_RS14560 was over-expressed. Our findings provided new insights in identifying potential drug targets for the inhibition of biofilm formation. We also developed a practical method to construct an over-expressed vector that can stably replicate in XDR-Ab isolates.