Deciphering the functional and structural complexity of the Solar Lake flat mat microbial benthic communities.

The Solar Lake in Taba, Egypt, encompasses one of the few modern-day microbial mats' systems metabolically analogous to Precambrian stromatolites. Solar Lake benthic communities and their adaptation to the Lake's unique limnological cycle have not been described for over two decades. In this study, we revisit the flat mat and describe the summer's shallow water versus exposed microbial community; the latter occurs in response to the seasonal partial receding of water. We employed metagenomic NovaSeq-6000 shotgun sequencing and 16S rRNA, mcrA, and dsrB quantitative PCR. A total of 292 medium-to-high-quality metagenome-assembled genomes (MAGs) were reconstructed. At the structural level, Candidatus Aenigmatarchaeota, Micrarchaeota, and Omnitrophota MAGs were exclusively detected in the shallow-water mats, whereas Halobacteria and Myxococcota MAGs were specific to the exposed microbial mat. Functionally, genes involved in reactive oxygen species (ROS) detoxification and osmotic pressure were more abundant in the exposed than in the shallow-water microbial mats, whereas genes involved in sulfate reduction/oxidation and nitrogen fixation were ubiquitously detected. Genes involved in the utilization of methylated amines for methane production were predominant when compared with genes associated with alternative methanogenesis pathways. Solar Lake methanogen MAGs belonged to Methanosarcinia, Bathyarchaeia, Candidatus Methanofastidiosales, and Archaeoglobales. The latter had the genetic capacity for anaerobic methane oxidation. Moreover, Coleofasciculus chthonoplastes, previously reported to dominate the winter shallow-water flat mat, had a substantial presence in the summer. These findings reveal the taxonomic and biochemical microbial zonation of the exposed and shallow-water Solar Lake flat mat benthic community and their capacity to ecologically adapt to the summer water recession. IMPORTANCE: Fifty-five years ago, the extremophilic "Solar Lake" was discovered on the Red Sea shores, garnering microbiologists' interest worldwide from the 1970s to 1990s. Nevertheless, research on the lake paused at the turn of the millennium. In our study, we revisited the Solar Lake benthic community using a genome-centric approach and described the distinct microbial communities in the exposed versus shallow-water mat unveiling microbial zonation in the benthic communities surrounding the Solar Lake. Our findings highlighted the unique structural and functional adaptations employed by these microbial mat communities. Moreover, we report new methanogens and phototrophs, including an intriguing methanogen from the Archaeoglobales family. We describe how the Solar Lake's flat mat microbial community adapts to stressors like oxygen intrusion and drought due to summer water level changes, which provides insights into the genomic strategies of microbial communities to cope with altered and extreme environmental conditions.

Cooling of a PVT System Using an Underground Heat Exchanger: An Experimental Study.

In the recent decades, the researchers have been focused on the use of photovoltaic thermal (PVT) systems that provide the best performance and cooling for the photovoltaic panels. In this study, a PVT system consisting of a monocrystalline PV panel and a spiral heat exchanger was connected to an underground heat exchanger that is buried at a depth of 4 m below the surface of the earth. The procedure of the current study can be considered the first of its kind in the Middle East and North Africa region (based on the researchers' knowledge). The study was carried out on agricultural land in Baghdad-Iraq during months of July and August-2022, which are considered the harshest weather conditions for this city. The heat exchanger consists of a copper tube with a length of 21 m and formed in the shape of 3U, and it was buried in the earth and connected with a PVT system. The results of the study showed that the site chosen to bury the heat exchanger (4 m deep) has a stable soil temperature at 22.5 °C. From various volumetric flow rates, a flow rate of 0.18 l/s was selected which is considered the highest flow rate that can show vibration in the PVT system which may harm the system. The practical measurements showed that the largest difference in the surface temperatures of standalone PV and PVT was around 20 °C in favor of the latter. The electrical efficiency of the studied PVT system also increased to outperform the standalone PV system by 127.3%. By comparing the results of the current study with studies of water-cooled PVT systems from the literature, it is clear that the proposed system is feasible and has an acceptable efficiency in such harsh weather conditions tested during the experiment.

Optimizing MWCNT-Based Nanofluids for Photovoltaic/Thermal Cooling through Preparation Parameters.

Multiwalled carbon nanotubes (MWCNTs) were employed as added particles for nanofluids in this practical investigation. To identify the most appropriate nanofluid for cooling PVT systems that are functional in the extreme summer environment of Baghdad, the parameters of base fluid, surfactant, and sonication time used for mixing were examined. Water was chosen as the base fluid instead of other potential candidates such as ethylene glycol (EG), propylene glycol (PG), and heat transfer oil (HTO). Thermal conductivity and stability were important thermophysical qualities that were impacted by the chosen parameters. The nanofluid tested in Baghdad city (consisting of 0.5% MWCNTs, water, and CTAB with a sonication period of three and a quarter hours) resulted in a 119.5, 308, and 210% enhancement of thermal conductivity (TC) for water compared with EG, PG, and oil, respectively. In addition, the nanofluid-cooled PVT system had an electrical efficiency that was 88.85% higher than standalone PV technology and 44% higher than water-cooled PVT systems. Moreover, the thermal efficiency of the nanofluid-cooled PVT system was 20% higher than the water-cooled PVT system. Finally, the nanofluid-cooled PVT system displayed the least decrease in electrical efficiency and a greater thermal efficiency even when the PV panel was at its hottest at noon.

Metagenomic profiling of antibiotic resistance genes in Red Sea brine pools.

Antibiotic resistance (AR) is an alarming global health concern, causing an annual death rate of more than 35,000 deaths in the US. AR is a natural phenomenon, reported in several pristine environments. In this study, we report AR in pristine Red Sea deep brine pools. Antimicrobial resistance genes (ARGs) were detected for several drug classes with tetracycline and macrolide resistance being the most abundant. As expected, ARGs abundance increased in accordance with the level of human impact with pristine Red Sea samples having the lowest mean ARG level followed by estuary samples, while activated sludge samples showed a significantly higher ARG level. ARG hierarchical clustering grouped drug classes for which resistance was detected in Atlantis II Deep brine pool independent of the rest of the samples. ARG abundance was significantly lower in the Discovery Deep brine pool. A correlation between integrons and ARGs abundance in brine pristine samples could be detected, while insertion sequences and plasmids showed a correlation with ARGs abundance in human-impacted samples not seen in brine pristine samples. This suggests different roles of distinct mobile genetic elements (MGEs) in ARG distribution in pristine versus human-impacted sites. Additionally, we showed the presence of mobile antibiotic resistance genes in the Atlantis II brine pool as evidenced by the co-existence of integrases and plasmid replication proteins on the same contigs harboring predicted multidrug-resistant efflux pumps. This study addresses the role of non-pathogenic environmental bacteria as a silent reservoir for ARGs, and the possible horizontal gene transfer mechanism mediating ARG acquisition.

Quality Estimates for 3D Protein Models.

Protein structure modeling is one of the most advanced and complex processes in computational biology. One of the major problems for the protein structure prediction field has been how to estimate the accuracy of the predicted 3D models, on both a local and global level, in the absence of known structures. We must be able to accurately measure the confidence that we have in the quality predicted 3D models of proteins for them to become widely adopted by the general bioscience community. To address this major issue, it was necessary to develop new model quality assessment (MQA) methods and integrate them into our pipelines for building 3D protein models. Our MQA method, called ModFOLD, has been ranked as one of the most accurate MQA tools in independent blind evaluations. This chapter discusses model quality assessment in the protein modeling field, demonstrating both its strengths and limitations. We also present some of the best methods according to independent benchmarking data, which has been gathered in recent years.

Evaluation of knowledge about osteoporosis risk factors among adults above 40 years of age in Qassim region, Saudi Arabia.

OBJECTIVE: Osteoporosis is a bone disease that develops when bone mineral density and bone mass decrease, or when the quality of bone changes. It is the most common bone disease, representing a major public health problem. This study aimed to assess the knowledge of risk factors for osteoporosis among adults above 40 in the Qassim region, Saudi Arabia. SUBJECTS AND METHODS: This is a cross-sectional study conducted among adults who were above 40 years of age and living in the Qassim region, Saudi Arabia. A survey questionnaire was distributed to respondents while they attended primary health care as well as online via social media. RESULTS: 390 participants responded to our survey (65.6% females vs. 34.4% males). The most common age group was 41 to 50 years (59.7%). The prevalence of participants who were having information about osteoporosis was 59%. Overall, the knowledge of participants about osteoporosis was good (63.1%), 33.3% had moderate knowledge and only 3.6% were assumed to have a poor knowledge level. Factors associated with increased knowledge was being a female and being an employee. CONCLUSIONS: Although the knowledge of the adult population aged above 40 years old seems adequate, there is still room for improvement. Female participants who were currently employed demonstrated a better understanding of osteoporosis than other adults. Further research is warranted to establish the effect of advanced age on their level of understanding regarding osteoporosis and its risk factors.

Design configuration and operational parameters of bi-fluid PVT collectors: an updated review.

The bi-fluid photovoltaic thermal (PVT) collector was introduced to provide more heating options along with improved cooling capabilities for the PV module. Since its introduction, this type of PVT system has been investigated thoroughly in various original works. In this review paper, we intend to put the concept and applications of this technology into question and revise the main achievements and discoveries through research and development with a focus on climatic and operational parameters. The paper encompasses a critical review of the discussed research and future directions for PVT collectors. The main utilized operational modes are discussed in detail, which are (i) water used in both channels, (ii) water in one channel and air in the other, and (iii) air in both channels. The modes were found to lead to different enhancement and performance effects for the utilized photovoltaic modules. The impact of mass flow rate was also taken by keeping one working fluid constant while varying the other to obtain its impact on the energy and exergy efficiency of the collector. In some cases, the fluids were run simultaneously and, in other cases, independently.

Bovine anaplasmosis: A systematic review with meta-analysis on the global prevalence

@#Bovine anaplasmosis, caused by Anaplasma marginale, is a significant infectious disease affecting cattle populations globally. However, the prevalence and distribution of bovine anaplasmosis vary across regions, making it crucial to assess its global burden systematically. This study aims to provide a comprehensive understanding of the global prevalence of bovine anaplasmosis and synthesized data from diverse geographic regions. A literature search was conducted to identify all relevant published articles reporting the prevalence of bovine anaplasmosis and a total of 164 studies were found eligible for final systematic review and meta-analysis. Meta-analysis was conducted using meta package of R software and summary estimates of the prevalence were calculated. Meta-analysis of 129,851 samples from 42 countries was conducted and the overall estimated prevalence of bovine anaplasmosis was found to be 38% (100% CI = 33% - 42%). The prevalence was found to be higher in cattle (39.9%) in comparison to yaks (6.4%). Diagnosis using serology (40.2%) yielded a higher prevalence compared to molecular testing (38.3%) and blood smears (22.4%) methods. Additionally, there were significant differences in the prevalence of bovine anaplasmosis between different countries (p<0.05). This study will inform evidence-based strategies for control and prevention of bovine anaplasmosis on a global scale by discovering the true extent of the disease and identifying high-prevalence areas.

Insights into the global freshwater virome.

Viruses are by far the most abundant life forms on this planet. Yet, the full viral diversity remains mostly unknown, especially in environments like freshwater. Therefore, we aimed to study freshwater viruses in a global context. To this end, we downloaded 380 publicly available viral metagenomes (>1 TB). More than 60% of these metagenomes were discarded based on their levels of cellular contamination assessed by ribosomal DNA content. For the remaining metagenomes, assembled contigs were decontaminated using two consecutive steps, eventually yielding 273,365 viral contigs longer than 1,000 bp. Long enough contigs (≥ 10 kb) were clustered to identify novel genomes/genome fragments. We could recover 549 complete circular and high-quality draft genomes, out of which 10 were recognized as being novel. Functional annotation of these genomes showed that most of the annotated coding sequences are DNA metabolic genes or phage structural genes. On the other hand, taxonomic analysis of viral contigs showed that most of the assigned contigs belonged to the order Caudovirales, particularly the families of Siphoviridae, Myoviridae, and Podoviridae. The recovered viral contigs contained several auxiliary metabolic genes belonging to several metabolic pathways, especially carbohydrate and amino acid metabolism in addition to photosynthesis as well as hydrocarbon degradation and antibiotic resistance. Overall, we present here a set of prudently chosen viral contigs, which should not only help better understanding of freshwater viruses but also be a valuable resource for future virome studies.

A comparison of dust impacts on polycrystalline and monocrystalline solar photovoltaic performance: an outdoor experimental study.

Solar cells are considered one of the most important and widespread solar applications in the world. However, the performance of the PV modules is significantly affected by the dust in the air. This paper, therefore, presents a comparison of an outdoor experimental study of dust effect on monocrystalline, and polycrystalline photovoltaic (PV) modules. For analysis, four 100 W PVs were installed horizontally in Sohar, Oman. For each pair of PV modules, one was left dusty due to environmental impact, and the second was cleaned daily. PV performance and environmental parameter measurements were conducted every 30 min for 35 days. The effects of dust on current, voltage, power, and energy were discussed in terms of time and normalized values. Also, cleaning methods were tested to determine the optimum one. It is found that power degradation of monocrystalline (20%) is higher compared with polycrystalline (12%) due to dust accumulation. For monocrystalline, the current, voltage, and power losses ranged between 10.0-24.0%, 2.0-3.5%, and 14.0-31.0%, respectively. However, for polycrystalline, the degradation rates were 16.88-27.92%, 0.455-0.455%, and 17.14-28.1% for current, voltage, and power losses after exposure to outdoor conditions for the same period, respectively. The dust accumulation on the PV surface found after 5 weeks is 0.493 mg/cm2, which can be considered the lowest accumulation rate compared to other Gulf countries, but which, however, leads to less energy degradation as well. It is found that water is sufficient to clean PV in the study area. However, sodium detergent as a cleaner introduced better results compared to water, especially when there is high pollution in the location.

Long-term power forecasting using FRNN and PCA models for calculating output parameters in solar photovoltaic generation.

This paper evaluated a 1.4 kW grid-connected photovoltaic system (GCPV) using two neural network models based on experimental data for one year. The novelty of this study is to propose and compare full recurrent neural network (FRNN), and principal component analysis (PCA) models based on entire year experimental data, considering limited research conducted to predict GCPV behaviour using the two methods. The system data was collected for 12 months secondly and hourly data with 50400 samples daily. The GCPV evaluates using specific yield, energy cost, capacity factor, payback period, current, voltage, power, and efficiency. The predicted GCPV current and power using FRNN and PCA were evaluated and compared with measured values to validate results. However, the results indicated that FRNN is better in simulating the experimental results curve compared with PCA. The measured and predicted data are compared and evaluated. It is found that the GCPV is suitable and promising for the study area in terms of technical and economic evaluation with a 3.24-4.82 kWh/kWp-day yield, 21.7% capacity factor, 0.045 USD/kWh cost of energy, and 11.17 years payback period.

Estimating the Quality of 3D Protein Models Using the ModFOLD7 Server.

Assessing the accuracy of 3D models has become a keystone in the protein structure prediction field. ModFOLD7 is our leading resource for Estimates of Model Accuracy (EMA), which has been upgraded by integrating a number of the pioneering pure-single- and quasi-single-model approaches. Such an integration has given our latest version the strengths to accurately score and rank predicted models, with higher consistency compared to older EMA methods. Additionally, the server provides three options for producing global score estimates, depending on the requirements of the user: (1) ModFOLD7_rank, which is optimized for ranking/selection, (2) ModFOLD7_cor, which is optimized for correlations of predicted and observed scores, and (3) ModFOLD7 global for balanced performance. ModFOLD7 has been ranked among the top few EMA methods according to independent blind testing by the CASP13 assessors. Another evaluation resource for ModFOLD7 is the CAMEO project, where the method is continuously automatically evaluated, showing a significant improvement compared to our previous versions. The ModFOLD7 server is freely available at http://www.reading.ac.uk/bioinf/ModFOLD/ .

A Multi-crosslinking Nanocapsule-Based Serial-Stimuli-Responsive Leakage-Free Drug-Delivery System In Vitro.

As some stimuli utilized in conventional drug delivery systems can also be found in normal cells, it is inevitable that encapsulated drugs escape from carriers into normal cells. Based on mutual interactions among proteins, polyphenol compounds, and metal ions, we developed a serial-stimuli-responsive drug delivery system. With multi-crosslinking structure, nanocapsules can maintain the integrity of the framework, even with a certain amount of stimuli present, and eventually reach tumor cells to initiate apoptosis, and protect normal cells from being damaged. Meanwhile, the fluorescence of DOX will be quenched when encapsulated in nanocapsules. This property means that the DOX that is released from nanocapsules can be monitored in real-time based on the recovery of fluorescence. These versatile nanocapsules exhibit great potentials to treat cancer.

Estimation of model accuracy in CASP13.

Methods to reliably estimate the accuracy of 3D models of proteins are both a fundamental part of most protein folding pipelines and important for reliable identification of the best models when multiple pipelines are used. Here, we describe the progress made from CASP12 to CASP13 in the field of estimation of model accuracy (EMA) as seen from the progress of the most successful methods in CASP13. We show small but clear progress, that is, several methods perform better than the best methods from CASP12 when tested on CASP13 EMA targets. Some progress is driven by applying deep learning and residue-residue contacts to model accuracy prediction. We show that the best EMA methods select better models than the best servers in CASP13, but that there exists a great potential to improve this further. Also, according to the evaluation criteria based on local similarities, such as lDDT and CAD, it is now clear that single model accuracy methods perform relatively better than consensus-based methods.

IntFOLD: an integrated web resource for high performance protein structure and function prediction.

The IntFOLD server provides a unified resource for the automated prediction of: protein tertiary structures with built-in estimates of model accuracy (EMA), protein structural domain boundaries, natively unstructured or disordered regions in proteins, and protein-ligand interactions. The component methods have been independently evaluated via the successive blind CASP experiments and the continual CAMEO benchmarking project. The IntFOLD server has established its ranking as one of the best performing publicly available servers, based on independent official evaluation metrics. Here, we describe significant updates to the server back end, where we have focused on performance improvements in tertiary structure predictions, in terms of global 3D model quality and accuracy self-estimates (ASE), which we achieve using our newly improved ModFOLD7_rank algorithm. We also report on various upgrades to the front end including: a streamlined submission process, enhanced visualization of models, new confidence scores for ranking, and links for accessing all annotated model data. Furthermore, we now include an option for users to submit selected models for further refinement via convenient push buttons. The IntFOLD server is freely available at: http://www.reading.ac.uk/bioinf/IntFOLD/.

Solid-state emissive O-BODIPY dyes with bimodal emissions across red and near infrared region.

Fluorescent compounds with solid-state emission are expected to have broad applications in the development of optoelectronic devices. In this study, we develop O-BODIPY based fluorescent dyes which exhibit strong bimodal solid-state emissions across red and NIR regions. After one pot synthesis, samples are characterized by X-ray diffraction, cyclic voltammetry, UV-vis absorption, and fluorescence spectra. All the experimental data reveal the multiple excitation and efficient emission features in the aggregation states. Furthermore, the two produced probes can be successfully applied for tracking lysosomes in HeLa cells with low cytotoxicity.

The Human Virome Protein Cluster Database (HVPC): A Human Viral Metagenomic Database for Diversity and Function Annotation.

Human virome, including those of bacteria (bacteriophages) have received an increasing attention recently, owing to the rapid developments in human microbiome research and the awareness of the far-reaching influence of microbiomes on health and disease. Nevertheless, human viromes are still underrepresented in literature making viruses a virtually untapped resource of diversity, functional and physiological information. Here we present the human virome protein cluster database as an effort to improve functional annotation and characterization of human viromes. The database was built out of hundreds of virome datasets from six different body sites. We also show the utility of this database through its use for the characterization of three bronchoalveolar lavage (BAL) viromes from one healthy control in addition to one moderate and one severe chronic obstructive pulmonary disease (COPD) patients. The use of the database allowed for a better functional annotation, which were otherwise poorly characterized when limited to annotation using sequences from full-length viral genomes. In addition, our BAL samples gave a first insight into viral communities of COPD patients and confirm a state of dysbiosis for viruses that increases with disease progression. Moreover, they shed light on the potential role of phages in the horizontal gene transfer of bacterial virulence factors, a phenomenon that highlights a possible contribution of phages to etiopathology.

Anti-viral therapy is associated with improved survival but is underutilised in patients with hepatitis B virus-related hepatocellular carcinoma: real-world east and west experience.

BACKGROUND: Hepatitis B virus (HBV) is the leading cause of hepatocellular carcinoma (HCC) worldwide. It remains incompletely understood in the real world how anti-viral therapy affects survival after HCC diagnosis. METHODS: This was an international multicentre cohort study of 2518 HBV-related HCC cases diagnosed between 2000 and 2015. Cox proportional hazards models were utilised to estimate hazard ratios (HR) with 95% (CI) for anti-viral therapy and cirrhosis on patients' risk of death. RESULTS: Approximately, 48% of patients received anti-viral therapy at any time, but only 17% were on therapy at HCC diagnosis (38% at US centres, 11% at Asian centres). Anti-viral therapy would have been indicated for >60% of the patients not on anti-viral therapy based on American criteria. Patients with cirrhosis had lower 5-year survival (34% vs 46%; P < 0.001) while patients receiving anti-viral therapy had increased 5-year survival compared to untreated patients (42% vs 25% with cirrhosis and 58% vs 36% without cirrhosis; P < 0.001 for both). Similar findings were seen for other patient subgroups by cancer stages and cancer treatment types. Anti-viral therapy was associated with a decrease in risk of death, whether started before or after HCC diagnosis (adjusted HR 0.62 and 0.79, respectively; P < 0.001). CONCLUSIONS: Anti-viral therapy improved overall survival in patients with HBV-related HCC across cancer stages and treatment types but was underutilised at both US and Asia centres. Expanded use of anti-viral therapy in HBV-related HCC and better linkage-to-care for HBV patients are needed.

Methods for estimation of model accuracy in CASP12.

Methods to reliably estimate the quality of 3D models of proteins are essential drivers for the wide adoption and serious acceptance of protein structure predictions by life scientists. In this article, the most successful groups in CASP12 describe their latest methods for estimates of model accuracy (EMA). We show that pure single model accuracy estimation methods have shown clear progress since CASP11; the 3 top methods (MESHI, ProQ3, SVMQA) all perform better than the top method of CASP11 (ProQ2). Although the pure single model accuracy estimation methods outperform quasi-single (ModFOLD6 variations) and consensus methods (Pcons, ModFOLDclust2, Pcomb-domain, and Wallner) in model selection, they are still not as good as those methods in absolute model quality estimation and predictions of local quality. Finally, we show that when using contact-based model quality measures (CAD, lDDT) the single model quality methods perform relatively better.