bluuebunny/crossref_metadata_2025 huggingface dataset:
Effects of indoor lighting conditions and window views on occupants’ well-being and behavior: a systematic review.
Authors: Vasquez Natalia G , Rupp Ricardo F , Andersen Rune K , Toftum Jørn
Published: November 2022

This paper reviews 49 studies that addressed how window view, daylighting, and lighting in buildings affect occupants’ behavior and well-being. The systematic literature search was performed in November 2021 and focused on office and educational buildings. We quantified the number of papers per study type, study aim, and lighting condition. Predictor categories and methods for data collection were also considered. We analyzed the results according to a structure of records, defined by the number of predictors and type of outcomes from a study. We obtained 106 records. A gap in the number of studies under different lighting conditions and building types was identified. Studies under natural light and studies conducted in learning environments were fewer than studies dealing with artificial lighting in offices. A wide variety of methods for data collection was found. Artificial lighting features and correlated color temperature were the most used predictors. Based on the analysis of records, we found that 61.3% of the associations between predictors and outcomes were statistically significant. The type of effect was not reported in 3.8% of the records-meaning that approximately 35% of the records found no significant associations between predictors and outcomes.
Modelling of Coastal Vulnerability Index Along the East Coast of Peninsular Malaysia due to Sea Level Rise Impact
Authors: Ismail I , Husain M L , Abdullah W S W , Zakaria R
Published: November 2022

Sea level rise is a very serious phenomena around the world and caused by expansion of sea water due to the high temperature and the melting of ice at the poles. In Malaysia, areas located on the East Coast of Peninsular Malaysia are more vulnerable to the impact of rising sea water because they are facing the South China Sea where the waves are stronger, especially during the monsoon season in November to March. The study site is along the East Coast of Peninsular Malaysia, over 675km and covered fifteen districts located along the coast. This study focuses on developing vulnerability indices on physical, socioeconomic and correlation between both parameters. The analysis of physical vulnerability index (PVI) consist seven variables namely geomorphology, shoreline change rate, coastal slope, wave height, tidal range, sea level rise change and rock type. While for socioeconomic index (SeVI) focuses on three parameters such as quality of life, economic value and infrastructures. After obtaining the index for each parameter, coastal vulnerability index (CVI) is then calculated to determine the overall vulnerability for the coastal area. For CVI, the highest index along coastal area is Kuantan and the lowest index is Tumpat.
Mining The Microbiome: A Mini Review on Natural Products Discovery from Soil
Authors: Sani Suraya Abdul , Paul Joyce , Sulaiman Dayang Iman Maisarah Abang , Haris Akid Md , Faik Ainol Azifa Mohd , Abdulla Rahmath
Published: November 2022

In this review, we touch on the historical overview of natural products discovery from soil and discuss their classification up to date. New advancement on innovation and technological pipeline that contributed on the foundation of isolation of microbial biosynthetic diversity across soil environmental community have revealed massive reservoirs of as yet untapped natural product chemistry. We highlight the successful strategies that has emerged and threats that must be overcome to enable the development of a high throughput approach for natural product discovery from complex microbial communities.
Hydrology of Acidic Mine Pit Lake: A Case Study of ex-Copper mine Pit Lake, Mamut, Sabah Malaysia.
Authors: Cleophas F , Isidore F , Musta B , Bidin K
Published: November 2022

Hydrological study of pit lake was carried out in ex-Mamut Copper Mine (MCM), Ranau Sabah. Gauging stations were established to measure surface inflows and outflows of the pit lake. Each station was equipped with a continuous water level recorder to record water level data at 10–minutes intervals. Rainfall and evaporation were measured respectively using storage gauge and evaporation pan. Over the entire study period, surface inflow accounted for 32.11% of the water entering the lake, the rest being provided by direct precipitation on the lake surface. Surface outflow discharges 53.13% of the water from the lake. Evaporation from the lake contributed 30.10% of water loss to the atmosphere. Changes of storage ranged from 61.09 mm to 241.56 mm per month. Simple linear regression analysis showed that, changes in lake level can be explained through rainfall and resulting tributary inflows, rate of surface outflow and evaporation, which would allow projections of possible future levels to be made by analysis of these components.
A Review on Food Security Policy on Agriculture and Food in Sabah, Malaysia
Authors: Sani Suraya Abdul , Osman Noor Dzuhaidah , Saari Erni Marlina , Idrus Wan Abdul Rahman Wan
Published: November 2022

Agriculture and food security are inextricably linked since agriculture is one of the sources of food security. The agriculture sector in Malaysia generates the most revenue for economic growth, apart from other sources, due to Malaysia’s vast areas of land and biodiversity. As such, the food security aims and objectives should be aligned with Malaysia’s agricultural policies, rules and regulations for economic growth and social development. This paper seeks to uncover Malaysia’s relevant and current agriculture and food security policies to identify meeting points to achieve food security goals and objectives in the future. This is also in line with the United Nations Sustainable Development Goals and in addition to maintaining the most fundamental human rights of the right to food. While there are many issues relating to agriculture, particularly concerning the advancement of science and technology, it is for the long-term benefits of food security for the population that local and indigenous people should embrace. This article adopts doctrinal method in analysing the policies by examining primary and secondary sources of laws and regulations and thus establishing common grounds for those two related areas of agriculture and food security. The findings show that while the Food Security Plan is still in the building up and perhaps future related-policies, the agriculture policies and rules and regulations should be further improved by taking an advantage of its available natural resources, only varies in line with the current commercial commodity agricultural trend, research and development. This is crucial not only to fulfil the sustainable development goals but also to improve Malaysian’s economy, standard of living, social development and their well-being. Thus, Malaysians will not go hungry due to its effective policies and rich biodiversity.
Characterization of wild type yeast isolated from Sabah soil for environmental friendly biofuel production
Authors: Abdulla R , Ahmad N H , Sabullah M K , Gansau J A
Published: November 2022

Biofuel production by utilizing yeast during fermentation process is one of the main concern to maximize the ethanol productivity. In this study, a total of 20 soil examples were collected from 4 sampling site around Kota Kinabalu. They were selected due to their potential habitat of yeast S. cerevisiae. The purpose of this study was to isolate and characterize S. cerevisiae from soil for bioethanol production. A total of 6 strains of yeast were isolated with the use of yeast-extract peptone agar medium. The isolated strains were identified by morphological, physiological and molecular characterization, resulting in discovery of the S. cerevisiae from the samples. In physiological characterization by fermentation of six different carbohydrates showed that the yeast isolates P2A have potential to ferment maltose, glucose and galactose. The strain P2A was evaluated further for their ethanol tolerance capacity. The strain can tolerate up to 12.5% concentration of ethanol. Pure strain of P2A was inoculated in anaerobic conditions with 200 rpm for 48 h at 30°C to be used for ethanol. The concentration of glucose after 72 h of fermentation for P2A was found to be 0.982 mg/mL.
Liquefaction Resistance of Sand-Kaolin Mixtures: Effect of Sand Sizes
Authors: Othman B.A. , Marto A. , Uzuoka R. , Ueda K. , Satar M.H. Mohd
Published: November 2022

Grading characteristics, particle sizes, particle shapes and fines content are the factors contributing to liquefaction incidents besides major factors such as earthquake magnitude. Recent publications and reports from incidents of liquefied or potential liquefied soils show some evidence that the size of sand particles, particle shapes and grading characteristics will increase or decrease the liquefaction resistance. However, to date the results are still disputed and need to be expanded. Hence, the aim of this paper is to investigate the effects of different sizes of sand in sand-kaolin mixtures on liquefaction resistance. The liquefaction resistance of sand mixtures with the application of different sizes of sand-coarse sand, medium sand and fine sand mixed with fines (kaolin) content (0%,10%, 20%, 30%, and 40%) are investigated through a cyclic triaxial test under undrained conditions. Each reconstituted sample was prepared with a target relative density of 15% (loose state) and 5% of initial moisture content for the triaxial test. Effective consolidation pressures of 100 kPa were applied on the cyclic triaxial tests. Microstructure analysis on the soil samples were carried out to explain the behaviour of the samples tested. The centrifuge test was carried out on selected samples so that the behaviour of the soils in actual conditions could be visualised. The results clearly show that the liquefaction resistance was reduced at reduced sand sizes. At a constant fines content for each parent sand, the liquefaction resistance decreased with an increase of fines content up to certain percentage, then increased thereafter. The fth decreased from 30% to 20% of fines content with a decrease in parent sand sizes. The outcomes of this study are useful to advance the understanding of the behaviour of sand mixtures with different sizes of sand for design purposes.
Developing the Earthquake Early Warning and Evacuation Systems (EEWES) for Schools in Ranau District
Authors: Nasirin Syed , Miskon Suraya
Published: November 2022

This article presents the main development components Early Earthquake Warning and Evacuation System (EEWES) for the Ranau District of Sabah. Many early earthquake warning systems have been developed since the last major earthquake in Ranau in 2015, but none has appropriately investigated the school children evacuation processes/exercises. The system was developed not just to expedite the evacuation process at these schools but also to help evacuate the school children and to get in touch with the children’s parents who are outstation. Those parents will be updated on the evacuation initiative that is taking place on a real-time basis. The system may also transfer the evacuation details to the local and federal emergency services and other agencies concerned with the evacuation exercises. The system mainly utilised the APIs released by regional disaster centres, which may deliver speedy transmission alerts. The future research direction is to incorporate the local tremor sensor details into the system.
Nowcasting Earthquake Occurrence in Sabah
Authors: Chin Su Na , Felix Tongkul , Omar Zaturrawiah A. , Rodeano Roslee
Published: November 2022

In line with the increasing availability of seismic data, nowcasting method provides a systematic way to depict the current state of earthquake hazard within a specific geographic area. This paper implements nowcasting method to statistically assess the earthquake progression in Sabah region over the large earthquakes cycle. The analysis includes earthquake data in the state of Sabah and the surrounding regions, which is acquired from Malaysia Meteorological Department catalogue and United States Geological Survey (USGS) catalogue from year 2009 to 2018. This study discovered that EPS corresponding to M ≥ 4 events in Ranau and Lahad Datu reach about 92% and 97%, respectively. These findings indicate that both areas are in the last quarter way through their cycle to magnitude 4.0 or larger earthquakes.
A comprehensive study on physico-mechanical properties of non-metallic fibre reinforced SCC blended with metakaolin and alcofine
Authors: Vivek S S , Karthikeyan B , Selvaraj Senthil Kumaran , Pradeep Kumar M , Chadha Utkarsh , Das Sreethul , Ranjani G , Rajasakthivel R , Tamilvendhan K , Adane Tezeta Moges
Published: November 2022

This study presents a detailed experimental investigation on the effects incorporating non-metallic fibers in hybrid form in self-compacting concrete (SCC). In this regard SCC was prepared with Alccofine and Metakaolin as partial replacement for cement in 15% and 20% respectively along with the hybrid fibre combinations namely abaca fibres (0.25%, 0.5% & 0.75%), polypropylene fibres (0.5%, 1%, 1.5% & 2%) and glass fibres (0.5%, 1%, 1.5%, & 2%). The fresh properties of SCC with and without hybrid fibre combinations were assessed through the standard tests such as slump flow, J ring and V-funnel tests. The conventional mechanical tests such as compressive strength test, split tensile strength test and flexural strength test were performed at 7 and 28 days. The experimental results reveal that the fresh properties of SCC were highly influenced by alccofine and Metakaolin adopted in this research. Furthermore, that the hybrid combination of abaca with polypropylene and glass fibres improved the mechanical properties of SCC and in particular the mix with 1% glass fibre and 0.25% Abaca fibre had shown better flexural and tensile strength behaviour. Microstructure analyses were also done to confirm the improvement in mechanical properties. The Scanning Electron Microscope images of the mix with 1% glass fibre and 0.25% abaca fibre showed less voids presence and presence of more hydrated components conveying that the usage of hybrid fibres had restricted the propagation of cracks there by reducing the percentage of voids and the use of metakaolin and alcofine helping in forming hydrated components at earlier stage leading to better strength.
Experimental study on toluene removal by a two-stage plasma-biofilter system
Authors: HUANG Hao , HE Lihao , WANG Yuxuan , CHEN Liang , HU Hui , ZHANG Mi
Published: November 2022

Volatile organic compounds (VOCs) are typical pollutants that affect air quality. Discharge plasma is thought to be a potential method that can remove VOCs from flue gas. In this experiment, pulsed corona discharge plasma combined with a biological tower was carried out to remove the benzene series, and toluene was selected as the typical VOC. The results indicated that the removal efficiency of toluene by pulsed corona plasma was slightly higher than that of direct current (DC) corona plasma, while its energy efficiency was much higher than DC corona plasma. Under the optimal experimental conditions of pulse voltage 8.5 kV, initial toluene concentration 1400 mg m−3, and toluene flow rate of 12 l h−1, the toluene removal efficiency reached 77.11% by the single method of pulsed corona discharge plasma, and the energy efficiency was up to 1.515 g/(kW·h) under the pulse voltage of 4.0 kV. The trickling biofilter was constructed by using the screened and domesticated Acinetobacter baumannii, and the highest toluene removal efficiency by the pulsed corona discharge plasma combined with the trickling biofilter rose up to 97.84%. Part of the toluene was degraded into CO2, H2O, and some intermediate products such as o-diphenol under the influence of Acinetobacter baumannii. When the remaining waste gas passed through the discharge plasma reactor, the benzene ring structure could be directly destroyed by the collision between toluene and plasma. Meanwhile, O·, OH·, and some other oxidizing radicals generated by the discharge also join into the oxidative decomposition of toluene and its intermediate products, thereby further improving the removal efficiency of toluene. Therefore, the two-stage plasma-biofilter system not only showed a high toluene removal efficiency, but also had a good energy efficiency. The results of this study will provide theoretical support and technical reference for industrial VOC treatment.
Machine learning versus crop growth models: an ally, not a rival
Authors: Zhang Ningyi , Zhou Xiaohan , Kang Mengzhen , Hu Bao-Gang , Heuvelink Ep , Marcelis Leo F M
Published: November 2022

The rapid increases of the global population and climate change pose major challenges to a sustainable production of food to meet consumer demands. Process-based models (PBMs) have long been used in agricultural crop production for predicting yield and understanding the environmental regulation of plant physiological processes and its consequences for crop growth and development. In recent years, with the increasing use of sensor and communication technologies for data acquisition in agriculture, machine learning (ML) has become a popular tool in yield prediction (especially on a large scale) and phenotyping. Both PBMs and ML are frequently used in studies on major challenges in crop production and each has its own advantages and drawbacks. We propose to combine PBMs and ML given their intrinsic complementarity, to develop knowledge- and data-driven modelling (KDDM) with high prediction accuracy as well as good interpretability. Parallel, serial and modular structures are three main modes can be adopted to develop KDDM for agricultural applications. The KDDM approach helps to simplify model parameterization by making use of sensor data and improves the accuracy of yield prediction. Furthermore, the KDDM approach has great potential to expand the boundary of current crop models to allow upscaling towards a farm, regional or global level and downscaling to the gene-to-cell level. The KDDM approach is a promising way of combining simulation models in agriculture with the fast developments in data science while mechanisms of many genetic and physiological processes are still under investigation, especially at the nexus of increasing food production, mitigating climate change and achieving sustainability.
Assessing time-varying causal effect moderation in the presence of cluster-level treatment effect heterogeneity and interference
Authors: Shi J , Wu Z , Dempsey W
Published: November 2022

The micro-randomized trial is a sequential randomized experimental design to empirically evaluate the effectiveness of mobile health intervention components that may be delivered at hundreds or thousands of decision points. Micro-randomized trials have motivated a new class of causal estimands, termed causal excursion effects, for which semiparametric inference can be conducted via a weighted, centred least-squares criterion (Boruvka et al., 2018). Causal excursion effects allow health scientists to answer important scientific questions about how intervention effectiveness may change over time or may be moderated by individual characteristics, time-varying context or past responses. Existing definitions and associated methods assume between-subject independence and noninterference. Deviations from these assumptions often occur. In this paper, causal excursion effects are revisited under potential cluster-level treatment effect heterogeneity and interference, where the treatment effect of interest may depend on cluster-level moderators. Utility of the proposed methods is shown by analysing data from a multi-institution cohort of first-year medical residents in the United States.
Domestic Accountability Efforts in Response to the Russia–Ukraine War
Authors: Marchuk Iryna
Published: November 2022

Since the beginning of Russia’s invasion of Ukraine on 24 February 2022, the Ukrainian authorities have faced an unprecedented surge in the numbers of alleged mass atrocity crimes committed in the areas of hostilities and parts of Ukraine’s (de)occupied territories. Eight months into the war, the Office of the Prosecutor General of Ukraine has already registered over 47,000 instances of alleged crimes, including war crimes and the crime of aggression. Ukrainian courts have swiftly delivered first verdicts in the war crimes trials signalling their willingness to deliver justice even in the midst of the raging war. This article provides a brief recap of the domestic prosecution of atrocity crimes prior to Russia’s invasion of Ukraine on 24 February 2022. It then evaluates the progress that has been achieved by the Ukrainian authorities and judiciary in relation to the prosecution and adjudication of war crimes since the beginning of Russia’s invasion of Ukraine. It analyses key findings of the first war crimes verdicts rendered by the Solomyanskyy District City Court in Kyiv (later modified by the Kyiv Court of Appeals with respect to the sentence) and the Kotelevskyy District Court in the Poltava region, and appraises the application of international humanitarian law by Ukrainian judges. The article concludes by situating Ukrainian domestic efforts within the larger context in closing the impunity gap for atrocity crimes against the backdrop of a broader discussion of transitional justice in Ukraine.
Concepts of radioprotection
Authors: Beattie Anna , Pugliese Francesca
Published: November 2022

Patient exposure to ionizing radiation associated with medical imaging procedures should be justified and optimised (the ALARA principle). In cardiac CT, a few scan parameters and scan protocols can be controlled to optimize radiation exposure. In general, an unnecessarily large scan range, high X-ray tube kilovoltage and tube current, and use of retrospectively electrocardiogram (ECG)-gated protocols are not dose-efficient choices. However, a smaller tailored scan range, optimized exposure control settings, staff training, optimal patient heart rate control, and prospectively ECG-triggered scanning approaches are more favourably associated with dose reduction.
CT for suspected acute coronary syndrome
Authors: Dedic Admir , Arslan Murat
Published: November 2022

Coronary CT angiography (CCTA) can be a valuable diagnostic tool in suspected acute coronary syndrome without ST segment elevation. Patients in whom the initial clinical work-up, including serial cardiac (high-sensitivity) troponins, remains inconclusive are most suited to being examined with CCTA. This chapter provides an overview of the use of CCTA in suspected acute coronary syndrome without ST segment elevation.
Infective endocarditis
Authors: Baggiano Andrea
Published: November 2022

Infective endocarditis (IE) is an infection of the endocardium. It may include cardiac valves, the mural endocardium, or septal defects, and affects more than 10 in 100,000 people annually. The infection is commonly characterized by small, usually floating, masses called vegetations, attached to the endocardium. If IE is not properly treated with specific antibiotic therapy, it can spread to the surrounding tissues, or migrate through the blood, with negative prognostic implications. The presence of IE leads to variable functional consequences like valvular regurgitation and congestive heart failure as a result of the entity of anatomical abnormalities. CT angiography with dedicated acquisition protocol emerged as useful imaging technique for a detailed description of the presence and location of such infectious disease at the level of cardiac structures, as well as the detection of associated complications, such as pseudoaneurysms, fistulae, abscesses, dehiscence of prosthetic material, or embolization of septic fragments.
Cardiomyopathies
Authors: Benz Dominik C.
Published: November 2022

Cardiomyopathies are defined as a myocardial disorder with a structurally and functionally abnormal heart muscle in the absence of coronary artery disease, valvular disease, hypertension, and congenital heart disease. Based on morphological and functional phenotypes, and according to the 2008 European Society of Cardiology classification of cardiomyopathies, these are grouped into hypertrophic cardiomyopathy, dilated cardiomyopathy, arrhythmogenic cardiomyopathy, restrictive cardiomyopathy, and unclassified cardiomyopathies. In addition, each cardiomyopathy is subclassified into familial and non-familial forms. CT may be a useful alternative to echocardiography and cardiac magnetic resonance imaging in the diagnosis of cardiomyopathies. Important CT findings include myocardial tissue abnormalities, abnormal ejection fraction and volumes, exclusion of underlying coronary or valvular disease, and abnormal myocardial perfusion/myocardial fibrosis.
Particles: Electrons, protons, and neutrons
Authors: Morgan Andrew , Nisbet Andrew
Published: November 2022

‘Particles: electrons, protons, and neutrons’ provides the basis for understanding charged particle therapy. In photon radiotherapy, photons are deposited in tissue, their energy is imparted to electrons in tissue and these electrons then cause biological damage. In contrast, in charged particle radiotherapy it is the charged particles themselves that are deposited in tissue directly causing biological damage. The charged particles in routine clinical use are electrons, with proton therapy growing rapidly but still limited to specialist centres. Neutron therapy is no longer used, although photon beams can be contaminated with neutrons. This chapter describes particle interactions (soft collisions, hard collisions, and radiative interactions) and defines and explains stopping power and its link with radiobiology. The pattern of energy deposition of a charged particle beam in tissue, the Bragg peak and production of protons are also covered.
Putting the IT in RT
Authors: MacDougall Niall , Morgan Andrew
Published: November 2022

‘Putting the IT into RT’ addresses the whole process of modern RT from introduction of patient demographic data into a Hospital Information System, through imaging associated with target definition, treatment planning and delivery, to end of treatment and eventually follow-up as it works ‘under the bonnet’ in a fully electronic department. The chapter also provides a simple set of references for all IT concepts that occur in the book. Frequently used terms such as DICOM (Digital Imaging and Communication in Medicine), IP addressing, databases, IT security, and ‘the cloud’ are described. The chapter summarizes the possibilities and benefits of modern radiotherapy IT systems, but also the potential pitfalls and dangers that might befall the unwary.
External beam treatment planning
Authors: Dean Christopher , MacDougall Niall , Morgan Andrew
Published: November 2022

This chapter, ‘Treatment planning’, covers the processes that are involved in the production of a patient specific treatment plan, ranging from simple single field palliative treatments through to complex radical treatments using volumetric modulated arc therapy (VMAT). The step-wise methodology for creating planning target volumes (PTVs) from gross tumour volumes (GTVs), taking into account uncertainties at each step is discussed as is the evaluation of treatment plans using isodose distributions and dose volume histograms. The processes of plan checking and patient specific checks for complex treatment plans are discussed. The basics of monitor unit calculations are described and sample calculations are presented. A new and relevant section in this edition of the book describes stereotactic treatments such as SRS (stereotactic radiosurgery) and SABR (stereotactic ablative body radiotherapy) and how evaluation of these plans differs from more conventional techniques. The chapter concludes with a short discussion on the more common dose calculation models (algorithms) implemented on treatment planning systems.
STANDARD-DEVIATION BASED CONFORMITY INDEX FOR EVALUATING TREATMENT PLAN OF INTENSITY MODULATED RADIOTHERAPY IN LUNG CANCER
Authors: Qingya Pan , Yizhong Fan , Fuke Zhang , Shengjie Luan , Linzhao Tian , Yuling Lv
Published: November 2022

This paper attempts to find a new conformity index (CI) calculation method with slice and angle information for evaluating lung cancer radiation treatment plan. A total of 20 lung cancer patients in 2016–2019 were selected. Treatment plans were made for each patient. Parameters used in the process of making treatment plans were set the same. The CI and the standard-deviation based CI (SDCI) that contains angle and slice information were calculated. Comparison of results calculated with SDCI and CI were made. The results of the two methods for the patients showed the same trend. Different shapes of simulated dose distribution line shows SDCI can provide more detail information about the target area. Special shapes of simulated dose distribution line for SDCI showed inaccuracy in angle information. The parameter SDCI has more advantage towards the traditional CI for it can provide angle and slice information. However, more angles need to be calculated.
Proteiniphilum propionicum sp. nov., a novel member of the phylum Bacteroidota isolated from pit clay used to produce Chinese liquor
Authors: Liu Qiuju , Zheng Huizhen , Wang Huilin , Zhou Weicheng , Zhao Dong , Qiao Zongwei , Zheng Jia , Ren Cong , Xu Yan
Published: November 2022

A novel, Gram-stain-negative, rod-shaped, strictly anaerobic bacterium of genus

Proteiniphilum

of the phylum Bacteroidota, named strain JNU-WLY501T, was isolated from pit clay used to produce strong aroma-type liquor in PR China. The genomic DNA G+C content and genome size of JNU-WLY501T were 41.4 % and 3.9 Mbp, respectively. The results of phylogenetic analysis based on 16S rRNA gene sequences indicated that JNU-WLY501T was closely related to

Proteiniphilum acetatigenes

DSM 18083T (95.7 %) and

Proteiniphilum saccharofermentans

M3/6T (94.9 %). The pairwise average nucleotide identity based on blast and average amino acid identity values of JNU-WLY501T compared with

Proteiniphilum saccharofermentans

M3/6T were 73.6 and 77.3 %, respectively, which both were lower than the threshold values for bacterial species delineation. The strain grew at 20–40 °C, with optimum growth at 37 °C. The pH range for growth was 5.4–9.1, with optimum growth at pH 7.5. The sodium chloride range for growth was 0.0–4.0 %, with optimum growth at 0 %. The strain did not use glucose, maltose, fructose or starch. Yeast extract, tryptone and peptone supported the growth of JNU-WLY501T, and the main fermentation products were acetate and propionate. The predominant cellular fatty acids (>5 %) of JNU-WLY501T were anteiso-C15 : 0 (30.6 %), anteiso-C17 : 0 (26.1 %), C16 : 0 (7.7 %), iso-C16 : 0 (5.0 %) and iso-C17 : 0 (5.0 %). The respiratory quinone of JNU-WLY501T was MK-5. On the basis of the morphological, physiological, biochemical, chemotaxonomic, genotypic and phylogenetic results, JNU-WLY501T represents a novel species of the genus

Proteiniphilum

, for which the name Proteiniphilum propionicum sp. nov. is proposed. The type strain is JNU-WLY501T (=GDMCC 1.2686T=JCM 34753T).
Novel application of metagenomics for the strain-level detection of bacterial contaminants within non-sterile industrial products – a retrospective, real-time analysis
Authors: Cunningham-Oakes Edward , Pointon Tom , Murphy Barry , Campbell-Lee Stuart , Connor Thomas R. , Mahenthiralingam Eshwar
Published: November 2022

The home and personal care (HPC) industry generally relies on initial cultivation and subsequent biochemical testing for the identification of microorganisms in contaminated products. This process is slow (several days for growth), labour intensive, and misses organisms which fail to revive from the harsh environment of preserved consumer products. Since manufacturing within the HPC industry is high-throughput, the process of identification of microbial contamination could benefit from the multiple cultivation-independent methodologies that have developed for the detection and analysis of microbes. We describe a novel workflow starting with automated DNA extraction directly from a HPC product, and subsequently applying metagenomic methodologies for species and strain-level identification of bacteria. The workflow was validated by application to a historic microbial contamination of a general-purpose cleaner (GPC). A single strain of

Pseudomonas oleovorans

was detected metagenomically within the product. The metagenome mirrored that of a contaminant isolated in parallel by a traditional cultivation-based approach. Using a dilution series of the incident sample, we also provide evidence to show that the workflow enables detection of contaminant organisms down to 100 CFU/ml of product. To our knowledge, this is the first validated example of metagenomics analysis providing confirmatory evidence of a traditionally isolated contaminant organism, in a HPC product.
Standing genetic variation and chromosome differences drove rapid ecotype formation in a major malaria mosquito
Authors: Small Scott T. , Costantini Carlo , Sagnon N’Fale , Guelbeogo Moussa W. , Emrich Scott J. , Kern Andrew D. , Fontaine Michael C. , Besansky Nora J.
Published: November 2022

Species distributed across heterogeneous environments often evolve locally adapted ecotypes, but understanding of the genetic mechanisms involved in their formation and maintenance in the face of gene flow is incomplete. In Burkina Faso, the major African malaria mosquitoAnopheles funestuscomprises two strictly sympatric and morphologically indistinguishable yet karyotypically differentiated forms reported to differ in ecology and behavior. However, knowledge of the genetic basis and environmental determinants ofAn. funestusdiversification was impeded by lack of modern genomic resources. Here, we applied deep whole-genome sequencing and analysis to test the hypothesis that these two forms are ecotypes differentially adapted to breeding in natural swamps versus irrigated rice fields. We demonstrate genome-wide differentiation despite extensive microsympatry, synchronicity, and ongoing hybridization. Demographic inference supports a split only ~1,300 years ago, closely following the massive expansion of domesticated African rice cultivation ~1,850 years ago. Regions of highest divergence, concentrated in chromosomal inversions, were under selection during lineage splitting, consistent with local adaptation. The origin of nearly all variation implicated in adaptation, including chromosomal inversions, substantially predates the ecotype split, suggesting that rapid adaptation was fueled mainly by standing genetic variation. Sharp inversion frequency differences likely facilitated adaptive divergence between ecotypes, both by suppressing recombination between opposing chromosomal orientations of the two ecotypes, and by maximizing recombination within the structurally monomorphic rice ecotype. Our results align with growing evidence from diverse taxa that rapid ecological diversification can arise from evolutionarily old structural genetic variants that modify genetic recombination.

Significance Statement

Local adaptation to heterogeneous environments is pervasive, but its underlying genetic basis is incompletely understood. Within a major African malaria vector,An. funestus, are two chromosomally differentiated groups that are co-localized, morphologically indistinguishable, and reported to differ both in ecology and behavior relevant to malaria transmission and control. Progress in understanding the genetic basis and environmental determinants of vector diversification was impeded by the lack of modern genomic resources. Here we perform deep whole-genome sequencing on individuals from these groups, establishing that they are differentiated genome-wide in a manner consistent with recent ecotype formation associated with the exploitation of a new anthropogenic larval habitat. Such rapid malaria vector diversification was facilitated by standing genetic variation, including evolutionarily old chromosomal rearrangements.
gtexture: novel extension of image texture analysis to graphs and its application to cancer informatics
Authors: Barker-Clarke Rowan J , Weaver Davis , Scott Jacob G
Published: November 2022

Objective

The calculation of texture features, such as those derived by Haralicket al., has been traditionally limited to 2D-imaging data. We present the novel derivation of an extension to these texture features that can be applied to graphs and networks and set out to illustrate the potential of these metrics for use in cancer informatics.

Approach

We extend the pixel-based calculation of texture and generate analogous novel metrics for graphs and networks. The graph structures in question must have ordered or continuous node weights/attributes. To demonstrate the utility of these metrics in cancer biology, we demonstrate these metrics can distinguish different fitness landscapes, gene co-expression and regulatory networks, and protein interaction networks with both simulated and publicly available experimental gene expression data.

Main Results

We demonstrate that texture features are informative of graph structure and analyse their sensitivity to discretization parameters and node label noise. We demonstrate that graph texture varies across multiple network types including fitness landscapes and large protein interaction networks with experimental expression data. We show the ability of these texture metrics, calculated on specific protein interaction subnetworks, to classify cell line expression by lineage, generating classifiers with 82% and 89% accuracy.

Significance

Graph texture features are a novel second order graph metric that can distinguish cancer types and topologies of evolutionary landscapes. It appears that no similar metrics currently exist and thus we open up the potential derivation of more metrics for the classification and analysis of network-structured data. This may be particularly useful in the complex setting of cancer, where large graph and network structures underlie the omics data generated. Network-based data underlies drug discovery, drug response prediction and single-cell dynamics and thus these metrics provide an additional tool in tackling these problems in cancer.
Improving protein secondary structure prediction by deep language models and transformer networks
Authors: Wu Tianqi , Cheng Weihang , Cheng Jianlin
Published: November 2022

Protein secondary structure prediction is useful for many applications. It can be considered a language translation problem, i.e., translating a sequence of 20 different amino acids into a sequence of secondary structure symbols (e.g., alpha helix, beta strand, and coil). Here, we develop a novel protein secondary structure predictor called TransPross based on the transformer network and attention mechanism widely used in natural language processing to directly extract the evolutionary information from the protein language (i.e., raw multiple sequence alignment (MSA) of a protein) to predict the secondary structure. The method is different from traditional methods that first generate a MSA and then calculate expert-curated statistical profiles from the MSA as input. The attention mechnism used by TransPross can effectively capture long-range residue-residue interactions in protein sequences to predict secondary structures. Benchmarked on several datasets, TransPross outperforms the state-of-art methods. Moreover, our experiment shows that the prediction accuracy of TransPross positively correlates with the depth of MSAs and it is able to achieve the average prediction accuracy (i.e., Q3 score) above 80% for hard targets with few homologous sequences in their MSAs. TransPross is freely available athttps://github.com/BioinfoMachineLearning/TransPro
Multi-layer guilt-by-association-based drug repurposing by integrating clinical knowledge on biological heterogeneous networks
Authors: Bang Dongmin , Lim Sangsoo , Lee Sangseon , Kim Sun
Published: November 2022

Computational drug repurposing attempts to leverage rapidly accumulating high-throughput data to discover new indications for existing drugs, often by clarifying biological mechanisms with relevant genes. Leveraging the Guilt-by-association (GBA), the principle of “similar genes share similar functions,” we introducedclinicalneighbors of drug and disease entities while learning their mechanisms on thebiologicalnetwork. To overcome the hurdle of connecting drugs and diseases through large and dense gene-gene network and simultaneously realize the concept of “semantic multi-layer GBA”, we present a random walk-based algorithm with a novel clinical-knowledge guided teleport. As a result, drug-disease association prediction accuracy increased up to 8.7% compared to existing state-of-the-art models. In addition, exploration of the generated embedding space displays harmony between biological and clinical contexts. Through repurposing case studies for breast carcinoma and Alzheimer’s disease, we demonstrate the potential power of multi-layer GBA, a novel perspective for predicting clinical-level associations on heterogeneous biomedical networks.
Forecasting the numbers of disease vectors with deep learning
Authors: Ceia-Hasse Ana , Sousa Carla A. , Gouveia Bruna R. , Capinha César
Published: November 2022

Arboviral diseases such as dengue, Zika, chikungunya or yellow fever are a worldwide concern. The abundance of vector species plays a key role in the emergence of outbreaks of these diseases, so forecasting these numbers is fundamental in preventive risk assessment. Here we describe and demonstrate a novel approach that uses state-of-the-art deep learning algorithms to forecast disease vector numbers. Unlike classical statistical and machine learning methods, deep learning models use time series data directly as predictors and identify the features that are most relevant from a predictive perspective. We demonstrate the application of this approach to predict temporal trends in the number ofAedes aegyptimosquito eggs across Madeira Island for the period 2013 to 2019. Specifically, we apply the deep learning models to predict whether, in the following week, the number ofAe. aegyptieggs will remain unchanged, or whether it will increase or decrease, considering different percentages of change. We obtained high predictive accuracy for all years considered (mean AUC = 0.92 ± 0.05 sd). We also found that the preceding numbers of eggs is a highly informative predictor of future numbers. Linking our approach to disease transmission or importation models will contribute to operational, early warning systems of arboviral disease risk.
IFNγ drives neuroinflammation and demyelination in a mouse model of multiple system atrophy
Authors: Gallups Nicole J. , Childers Gabrielle M. , Webster Jhodi M. , Zane Asta , Yang Ya-Ting , Mudium Nikhita , Manfredsson Fredric P. , Kordower Jeffrey H. , Harms Ashley S.
Published: November 2022

Multiple system atrophy (MSA) is a rare and fatal synucleinopathy characterized by insoluble alpha-synuclein (α-syn) cytoplasmic inclusions located within oligodendroglia. Neuroinflammation, demyelination, and neurodegeneration are correlated with areas of GCI pathology, however it is not known what specifically drives disease pathogenesis. Recently in a mouse model of MSA, CD4+ T cells have been shown to drive neuroinflammation and demyelination, however the mechanism by which this occurs also remains unclear. In this study we use genetic and pharmacological approaches in a novel model of MSA to show that the pro-inflammatory cytokine interferon gamma (IFNγ) drives neuroinflammation and demyelination. Furthermore, using an IFNγ reporter mouse, we found that infiltrating CD4+ T cells were the primary producers of IFNγ in response to α-syn overexpression in oligodendrocytes. Results from these studies indicate that IFNγ expression in CD4 T cells drives α-syn-mediated neuroinflammation and demyelination, and strategies to target IFNγ expression may be a potential disease modifying therapeutic strategy for MSA.
Genomic differentiation among European perch in the western Baltic Sea reflects colonisation history and local adaptation
Authors: Skovrind Mikkel , Pacheco George , Flindt Christensen Emil Aputsiaq , Gopalakrishnan Shyam , Fietz Katharina , Holm-Hansen Tore Hejl , Vieira Filipe Garrett , Krag Marcus Anders , Carl Henrik , Gilbert M Thomas P , Olsen Morten Tange , Møller Peter Rask
Published: November 2022

Environmental variation across the distribution of wild species can lead to local adaptations. The Baltic Sea was formed when the Fenno-Scandian ice sheet retreated around 12 thousand years ago, creating a new brackish water habitat colonised by both marine and freshwater fish species. The European perch (Perca fluviatilis) is a predatory freshwater fish with a large geographical distribution across Eurasia, where it inhabits a wide range of environmental niches. In the Baltic Sea region it has even developed a specialised brackish water phenotype that can tolerate environmental salinity levels, which are lethal to the ancestral freshwater phenotype. However, very little is known about the colonisation history and underlying genomic mechanisms facilitating the colonisation and adaptation of perch to the Baltic Sea. Here, we use Genotyping-By-Sequencing data from six freshwater and six brackish water localities to disclose the evolutionary relationship between the freshwater and brackish water phenotype. Our results show that the brackish water perch phenotype occurs in multiple distinct genetic clusters. We find that gene flow between brackish water phenotypes with full access to the sea likely led to lower levels of differentiation and higher diversity than in freshwater phenotypes. Selection analyses suggest that genomic adaptation played a role in the colonisation of the Baltic Sea and that the top three regions under selection harbour salinity tolerance genes. We also find a link between the historic salinity of the Baltic Sea and the demographic history of the brackish water phenotypes and go on to discuss the implications of our findings for management of brackish water perch in the western Baltic sea.

Highlights

GBS data from 12 perch populations, six with brackish and six with freshwater origin

Colonisation history and differentiated gene flow shaped the current population structure

The brackish water ecotype was found in all three major genetic clades

Top three regions under selection harboured salinity tolerance genes

Salinity influenced Ne during the formation of the Baltic Sea

Graphical abstract
Engineered reporter phages for rapid detection ofEscherichia coli, Klebsiellaspp., andEnterococcusspp. in urine
Authors: Meile Susanne , Du Jiemin , Staubli Samuel , Grossman Sebastian , Koliwer-Brandl Hendrik , Piffaretti Pietro , Leitner Lorenz , Matter Cassandra I. , Baggenstos Jasmin , Hunold Laura , Milek Sonja , Gübeli Christian , Kozomara-Hocke Marko , Neumeier Vera , Botteon Angela , Klumpp Jochen , Marschall Jonas , McCallin Shawna , Zbinden Reinhard , Kessler Thomas M. , Loessner Martin J. , Dunne Matthew , Kilcher Samuel
Published: November 2022

The rapid detection and species-level differentiation of bacterial pathogens facilitates antibiotic stewardship and improves disease management. Here, we develop a rapid bacteriophage-based diagnostic assay to detect the most prevalent pathogens causing urinary tract infections:Escherichia coli, Klebsiellaspp., andEnterococcusspp. For each uropathogen, two virulent phages were genetically engineered to express a nanoluciferase reporter gene upon host infection. Using 206 patient urine samples, reporter phage-induced bioluminescence was quantified to identify bacteriuria and the assay was benchmarked against conventional urinalysis. Overall,E. coli, Klebsiellaspp., andEnterococcusspp. were each detected with high sensitivity (68%, 78%, 85%), specificity (99%, 99%, 99%), and accuracy (90%, 94%, 96%) at a resolution of ⩾103CFU/ml within 5 h. We further demonstrate how bioluminescence in urine can be used to predict phage antibacterial activity, demonstrating the future potential of reporter phages as companion diagnostics that guide patient-phage matching prior to therapeutic phage application.