bluuebunny/crossref_metadata_2025 huggingface dataset:
ANALISA KONVERGENSI KELAYAKAN PENETAPAN TARIF RETRIBUSI MENARA TELEKOMUNIKASI DALAM TINJAUAN SPASIAL KOTA BOGOR
Authors: Dan WAHYU GENDAM PRAKOSO MUHAMAD MAHFUDZ
Published: July 2022

Penelitan ini di dasarkan pada sebuah kondisi kekosongan hukum di Pemerintah Daerah, yang mendasarkan perhitungan retribusi menara telekomunikasi menggunakan dasar 2% (dua persen) dari nilai jual obyek pajak. Dalam rangka mengatasi kekosongan hukum dasar penetapan tarif retribusi menara telekomunikasi di daerah akibat Putusan MK Nomor : 46/PUU-XII/2014, Kementerian Keuangan telah mengeluarkan 3 (tiga) Surat Edaran yang menjelaskan formulasi perhitungan  tarif retribusi menara telekomunikasi berdasarkan Pasal 151 dan Pasal 152 UU-PDRD. Adapun penelitian ini bertujuan untuk meramu formula penentuan tarif retribusi dan mengetahui gambaran umum serta sebaran menara telekomunikasi di Kota Bogor. Sedangkan sistem penentuan tarif retribusi menara telekomunikasi ini berdasarkan zonasi, ketinggian menara, jenis menara dan jarak tempuh. Pengumpulan data,  penganalisanya menggunakan data spasial sebagai penunjang keputusan  dalam rangka peningkatan efisiensi waktu dan ketelitian menggunakan metode Sistem Informasi Geografi (SIG). Penggabungan kombinasi zonasi, tinggi menara, jenis menara dan jarak tempuh dengan SIG mampu memudahkan dalam proses pengambilan keputusan. Sehingga memudahkan peneliti untuk meramu formula perhitungan tarif retribusi menara telekomunikasi dan dapat menentukan besaran tarif retribusi menara telekomunikasi. Kata kunci : tarif retribusi, menara telekomunikasi, sig
POTENSI SUMBER DAYA DAN PEMANFAATAN BAHAN GALIAN TUF DI DAERAH PARUNGKUJANG
Authors: Dan IIT ADHITIA SOLIHIN
Published: July 2022

Daerah penelitian sebagai bagian dari Mandala Cekungan Banten diindikasikan mengandung pelamparan tuf yang cukup luas sehingga menjadikan daerah ini memiliki potensi sumber daya bahan galian tuf yang dapat dimanfaatkan sebagai bahan baku industri. Bahan galian tuf yang tersingkap merupakan bagian dari Formasi Genteng di bagian selatan daerah penelitian dengan luas pelamparan barat-timur. Penelitian bertujuan untuk mengetahui potensi secara ekonomis dari keterdapatan bahan galian tuf, baik mengenai estimasi besarnya sumberdaya (resource estimation) bahan galian tuf daerah penelitian, beserta kualitas sampel yang diperoleh dari singkapan maupun peruntukkannya dengan menggunakan Metoda Avgustinik. Metode perhitungan volume sumberdaya bahan galian tuf dengan metoda kontur, didapatkan hasil perhitungan volume kotor sebesar 218,219,070.11m3, dan  hasil perhitungan volume tanah penutup sebesar 9,424,416.37m3, dan dikurangi faktor koreksi sebesar 41,758,930.748m3 sehingga didapatkan volume bersih bahan galian tuf sebesar 167,035,722.992 m³. Dengan berat jenis tuf  2.54 gr/cm3, maka estimasi sumber daya bahan galian tuf di daerah penelitian sebesar  424,270,736.4 ton. Ploting  di Diagram Avgustinik berada di area 5 dan  area 6 dengan berdasarkan hasil analisa kimia sampel BA-10 dan BA-21, dan hasil perhitungan dengan Metoda Avgustinik sampel BA-10 dan BA-21 menjadikan bahan galian tuf daerah penelitian cocok untuk digunakan di dunia industri sebagai bahan baku pembuatan bata klinker dan bata biasa. Bahan galian tuf yang dijumpai di daerah penelitian merupakan bagian dari Formasi Genteng mempunyai kualitas yang baik dan sumber daya yang cukup, sehingga tahap eksplorasi lanjutan perlu dilakukan hingga studi kelayakan untuk mendapatkan cadangan terbukti, sehingga bisa dilakukan produksi dan pemanfaatan yang optimal bagi dunia industri. Kata Kunci : mandala cekungan banten, metoda avgustinik, metoda kontur, tuf
Estimation of Resilience Parameters Following LPS Injection Based on Activity Measured With Computer Vision
Authors: van der Zande Lisette E. , Guzhva Oleksiy , Parois Séverine , van de Leemput Ingrid A. , Bolhuis J. Elizabeth , Rodenburg T. Bas
Published: July 2022

Resilience could be referred to as the animal’s ability to successfully adapt to a challenge. This is typically displayed by a quick return to initial metabolic or activity levels and behaviors. Pigs have distinct diurnal activity patterns. Deviations from these patterns could potentially be utilized to quantify resilience. However, human observations of activity are labor intensive and not feasible in practice on a large scale. In this study, we show the use of a computer vision tracking algorithm to quantify resilience based on activity individual patterns following a lipopolysaccharide (LPS) challenge, which induced a sickness response. We followed 121 individual pigs housed in barren or enriched housing systems, as previous work suggests an impact of housing on resilience, for eight days. The enriched housing consisted of delayed weaning in a group farrowing system and extra space compared with the barren pens and environmental enrichment. Enriched housed pigs were more active pre-injection of LPS, especially during peak activity times, than barren housed pigs (49.4 ± 9.9 vs. 39.1 ± 5.0 meter/hour). Four pigs per pen received an LPS injection and two pigs a saline injection. LPS injected animals were more likely to show a dip in activity than controls (86% vs 17%). Duration and Area Under the Curve (AUC) of the dip were not affected by housing. However, pigs with the same AUC could have a long and shallow dip or a steep and short dip. Therefore the AUC:duration ratio was calculated, and enriched housed pigs had a higher AUC:duration ratio compared to barren housed pigs (9244.1 ± 5429.8 vs 5919.6 ± 4566.1). Enriched housed pigs might therefore have a different strategy to cope with an LPS sickness challenge. However, more research on this strategy and the use of activity to quantify resilience and its relationship to physiological parameters is therefore needed.
Fatty Acid Accumulations and Transcriptome Analyses Under Different Treatments in a Model Microalga Euglena gracilis
Authors: He Jiayi , Du Ming , Chen Yehua , Liu Yerong , Zhang Jinlin (Kenny) , Fu Wen , Lei Anping , Wang Jiangxin
Published: July 2022

With the continuous growth of the world’s population and the increasing development of industrialization, the demand for energy by human beings has been expanding, resulting in an increasingly severe energy crisis. Microalgae are considered the most potential alternatives to traditional fossil fuels due to their many advantages, like fast growth rate, strong carbon sequestration capacity, and low growth environment requirements. Euglena can use carbon sources such as glucose, ethanol, and others for heterotrophic growth. Moreover, Euglena is highly adaptable to the environment and has a high tolerance to various environmental stresses, such as salinity, heavy metals, antibiotics, etc. Different treatments of Euglena cells could affect their growth and the accumulation of bioactive substances, especially fatty acids. To expand the industrial application of Euglena as a potential biodiesel candidate, we determine the physiological responses of Euglena against environmental stresses (antibiotics, heavy metals, salinity) or carbon resources (glucose and ethanol), and evaluate the potential for higher quality and yield of fatty acid with a high growth rate. Adding glucose into the culture media increases cell biomass and fatty acid production with high-quality biodiesel characters. The transcriptome analysis helped explore the possible regulation and biosynthesis of fatty acids under different treatments and exploited in the improvement of biodiesel production. This study provides insights for further improvement and various culture treatments for Euglena-based biodiesel and jet fuels.
Discovery of TIGIT inhibitors based on DEL and machine learning
Authors: Xiong Feng , Yu Mingao , Xu Honggui , Zhong Zhenmin , Li Zhenwei , Guo Yuhan , Zhang Tianyuan , Zeng Zhixuan , Jin Feng , He Xun
Published: July 2022

Drug discovery has entered a new period of vigorous development with advanced technologies such as DNA-encoded library (DEL) and artificial intelligence (AI). The previous DEL-AI combination has been successfully applied in the drug discovery of classical kinase and receptor targets mainly based on the known scaffold. So far, there is no report of the DEL-AI combination on inhibitors targeting protein-protein interaction, including those undruggable targets with few or unknown active scaffolds. Here, we applied DEL technology on the T cell immunoglobulin and ITIM domain (TIGIT) target, resulting in the unique hit compound 1 (IC50 = 20.7 μM). Based on the screening data from DEL and hit derivatives a1-a34, a machine learning (ML) modeling process was established to address the challenge of poor sample distribution uniformity, which is also frequently encountered in DEL screening on new targets. In the end, the established ML model achieved a satisfactory hit rate of about 75% for derivatives in a high-scored area.
Systematic review and meta-analysis of prognostic models in Southeast Asian populations with acute myocardial infarction
Authors: Ismail Sophia Rasheeqa , Khalil Muhamad Khairul Nazrin , Mohamad Mohd Shawal Faizal , Azhar Shah Shamsul
Published: July 2022

Background

The cultural and genetic diversity of the Southeast Asian population has contributed to distinct cardiovascular disease risks, incidence, and prognosis compared to the Western population, thereby raising concerns about the accuracy of predicted risks of existing prognostic models.

Objectives

We aimed to evaluate the predictive performances of validated, recalibrated, and developed prognostic risk prediction tools used in the Southeast Asian population with acute myocardial infarction (AMI) events for secondary events

Methods

We searched MEDLINE and Cochrane Central databases until March 2022. We included prospective and retrospective cohort studies that exclusively evaluated populations in the Southeast Asian region with a confirmed diagnosis of an AMI event and evaluated for risk of secondary events such as mortality, recurrent AMI, and heart failure admission. The CHARMS and PRISMA checklists and PROBAST for risk of bias assessment were used in this review.

Results

We included 7 studies with 11 external validations, 3 recalibrations, and 3 new models from 4 countries. Both short- and long-term outcomes were assessed. Overall, we observed that the external validation studies provided a good predictive accuracy of the models in the respective populations. The pooled estimate of the C-statistic in the Southeast Asian population for GRACE risk score is 0.83 (95%CI 0.72–0.90, n = 6 validations) and for the TIMI risk score is 0.80 (95%CI: 0.772–0.83, n = 5 validations). Recalibrated and new models demonstrated marginal improvements in discriminative values. However, the method of predictive accuracy measurement in most studies was insufficient thereby contributing to the mixed accuracy effect. The evidence synthesis was limited due to the relatively low quality and heterogeneity of the available studies.

Conclusion

Both TIMI and GRACE risk scores demonstrated good predictive accuracies in the population. However, with the limited strength of evidence, these results should be interpreted with caution. Future higher-quality studies spanning various parts of the Asian region will help to understand the prognostic utility of these models better.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?%20RecordID=228486.
IRX3 plays an important role in the pathogenesis of metabolic-associated fatty liver disease by regulating hepatic lipid metabolism
Authors: Ma Yongqiang , Chen Guangshun , Yi Junfang , Li Qiang , Tan Zhi , Fan Wenling , Luo Xiaohua , He Zhiyong , Si Zhongzhou , Li Jiequn
Published: July 2022

Metabolic-associated fatty liver disease (MAFLD) affects approximately a quarter of the global population. Identification of the key genes and pathways involved in hepatic lipid metabolism is of the utmost importance for the diagnosis, treatment, and prevention of MAFLD. In this study, differentially expressed genes were identified through whole-genome transcriptional analysis of liver tissue from MAFLD patients and healthy controls, and a series of lipid metabolism-related molecules and pathways were obtained through pathway analysis. Subsequently, we focused on Iroquois homeobox protein 3 (IRX3), one of 13 transcription factors that were screened from the 331 differentially expressed genes. The transcription factor IRX3 was significantly decreased in the liver tissue of patients with MAFLD when compared with healthy controls. Pearson’s correlation analysis showed that the expression levels of IRX3 in liver tissue were negatively correlated with serum total cholesterol, triglycerides, low-density lipoprotein cholesterol, and uric acid levels. The overexpression and interference of IRX3 induced the increased and decreased lipid droplet accumulation in vitro, respectively. Moreover, interference of IRX3 expression increased mitochondrial fragmentation and reduced the activity of the mitochondrial respiratory chain complex IV. In summary, the study demonstrated that IRX3 regulated hepatic lipid metabolism of MAFLD, and also revealed the effect of IRX3 on mitochondria might be an important mechanism by which IRX3 regulated hepatic lipid metabolism of MAFLD.
Tenuous Transcriptional Threshold of Human Sex Determination. I. SRY and Swyer Syndrome at the Edge of Ambiguity
Authors: Chen Yen-Shan , Racca Joseph D. , Weiss Michael A.
Published: July 2022

Male sex determination in mammals is initiated by SRY, a Y-encoded transcription factor. The protein contains a high-mobility-group (HMG) box mediating sequence-specific DNA bending. Mutations causing XY gonadal dysgenesis (Swyer syndrome) cluster in the box and ordinarily arisede novo. Rare inherited variants lead to male development in one genetic background (the father) but not another (his sterile XY daughter).De novoand inherited mutations occur at an invariant Tyr adjoining the motif’s basic tail (box position 72; Y127 in SRY). In SRY-responsive cell lines CH34 and LNCaP,de novomutations Y127H and Y127C reduced SRY activity (as assessed by transcriptional activation of principal target geneSox9) by 5- and 8-fold, respectively. Whereas Y127H impaired testis-specific enhancer assembly, Y127C caused accelerated proteasomal proteolysis; activity was in part rescued by proteasome inhibition. Inherited variant Y127F was better tolerated: its expression was unperturbed, and activity was reduced by only twofold, a threshold similar to other inherited variants. Biochemical studies of wild-type (WT) and variant HMG boxes demonstrated similar specific DNA affinities (within a twofold range), with only subtle differences in sharp DNA bending as probed by permutation gel electrophoresis and fluorescence resonance-energy transfer (FRET); thermodynamic stabilities of the free boxes were essentially identical. Such modest perturbations are within the range of species variation. Whereas our cell-based findings rationalize thede novogenotype-phenotype relationships, a molecular understanding of inherited mutation Y127F remains elusive. Our companion study uncovers cryptic biophysical perturbations suggesting that thepara-OH group of Y127 anchors a novel water-mediated DNA clamp.
Short-Term Power Prediction of a Wind Farm Based on Empirical Mode Decomposition and Mayfly Algorithm–Back Propagation Neural Network
Authors: Gong Zeweiyi , Ma Xianlong , Xiao Ni , Cao Zhanguo , Zhou Shuai , Wang Yaolong , Guo Chenjun , Yu Hong
Published: July 2022

With the improvement of energy consumption structure, the installed capacity of wind power increases gradually. However, the inherent intermittency and instability of wind energy bring severe challenges to the dispatching operation. Wind power forecasting is one of the main solutions. In this work, a new combined wind power prediction model is proposed. First, a quartile method is used for data cleaning, namely, identifying and eliminating the abnormal data. Then, the wind power data sequence is decomposed by empirical mode decomposition to eliminate non-stationary characteristics. Finally, the wind generator data are trained by the MA-BP network to establish the wind power prediction model. Also, the simulation tests verify the prediction effect of the proposed method. Specifically speaking, the average MAPE is decreased to 12.4979% by the proposed method. Also, the average RMSE and MAE are 107.1728 and 71.604 kW, respectively.
Research on μPMU Configuration Optimization Considering Multiple Operation Modes of Distribution Network
Authors: Liang Zhenfeng , Wang Jing , Wang Xiaowei , Zhang Yining
Published: July 2022

A micro-phasor measurement unit (μPMU) configuration optimization approach is proposed in this article, considering the numerous operation modes of distribution network reconfiguration. The PSO algorithm with dynamic adaptability is used to optimize the setup of μPMU and improve the accuracy of state estimation for each distribution network operation mode. The configuration nodes of various operation modes are grouped and assessed by K-means according to the shortest distance, and the weights of the evaluation indexes are calculated by the AHP-CRITIC subjective and objective combination weighting method. The node with the highest comprehensive evaluation index is selected as the configuration node. The probability of multiple operation modes is then introduced. Finally, using the IEEE 118-bus distribution system as an example, the simulation demonstrates the proposed method’s effectiveness in improving distribution network state estimate.
Evaluation and evolution analysis of water ecosystem service value in the yangtze river delta region based on meta-analysis
Authors: Shao Hongmei , Long Dian , He Jiaqi , Zhang Ling
Published: July 2022

Rapid economic development, industrialization and urbanization lead to environmental pollution and damage the stability of regional ecosystems. The Yangtze River Delta region is an economically developed region in China, faces the problems of water environment pollution and water ecosystem service degradation. Reasonable assessment of water ecosystem service value (ESV) is of great significance for grasping the status of regional water ecosystem services, improving water ecological environment, and realizing regional sustainable development. This study collects 119 research literature about China, including 156 observations to establish a value transfer database; specially builds a Meta-analysis model including the variables of climate conditions, environmental pollution and environmental protection, then assesses the waters ESV in the Yangtze River Delta using the model and analyzes the changes from 2009 to 2018. The study finds that the location, population density, the area of the site, average annual precipitation, literature characteristics, landscape characteristics, wastewater discharge, environmental protection expenditure, and wastewater treatment costs can affect the water ESV significantly. Based on the meta-analysis benefit transfer model to evaluate the water ESV in Yangtze River Delta region is RMB 177,126 yuan/ hha/year and the growth rate is 27.18%. The place with the highest value per unit area is Shanghai, and the total value in Jiangsu Province is the highest. Economic development, waste water discharge and wastewater treatment costs are the main reasons for the changes and differences in the value of water ecosystem services in the Yangtze River Delta region. The contribution of this study to the field of water ESV assessment is that the meta-analysis model includes a broader set of influencing variables, including landscape, population density, climate change and environmental protection. It provides a practical reference for water ESV assessment on the local scale and a scientific basis for water area management related to the development of water area and ecological compensation, as well as promote the sustainable development of water ecosystems.
Genetic Structure of the Endangered Coral Cladocora caespitosa Matches the Main Bioregions of the Mediterranean Sea
Authors: Repullés Mar , López-Márquez Violeta , Templado José , Taviani Marco , Machordom Annie
Published: July 2022

Population connectivity studies are a useful tool for species management and conservation planning, particular of highly threatened or endangered species. Here, we evaluated the genetic structure and connectivity pattern of the endangered coralCladocora caespitosaacross its entire distribution range in the Mediterranean Sea. Additionally, we examined the relative importance of sexual and asexual reproduction in the studied populations and their genetic diversity. A total of 541 individuals from 20 localities were sampled and analysed with 19 polymorphic microsatellite markers. Of the genotyped individuals, 482 (89%) had unique multilocus genotypes. Clonality percentages of the populations varied from 0% (in eight populations) to nearly 69% (in one population from Crete). A heterozygosity deficit and a high degree of inbreeding was the general trend in our data set. Population differentiation inC. caespitosawas characterised by significant pairwiseFSTvalues with lower ones observed at an intraregional scale and higher ones, between populations from different biogeographic regions. Genetic structure analyses showed that the populations are divided according to the three main sub-basins of the Mediterranean Sea: the Western (Balearic, Ligurian and Tyrrhenian seas), the Central (Adriatic and Ionian seas) and the Eastern (Levantine and Aegean seas), coinciding with previously described gene flow barriers. However, the three easternmost populations were also clearly separated from one another, and a substructure was observed for the other studied areas. An isolation-by-distance pattern was found among, but not within, the three main population groups. This substructure is mediated mainly by dispersal along the coastline and some resistance to larval movement through the open sea. Despite the low dispersal ability and high self-recruitment rate ofC. caespitosa, casual dispersive events between regions seem to be enough to maintain the species’ considerable genetic diversity. Understanding the population connectivity and structure of this endangered scleractinian coral allows for more informed conservation decision making.
Longitudinal Serum Proteome Characterization of COVID-19 Patients With Different Severities Revealed Potential Therapeutic Strategies
Authors: Wu Songfeng , Xu Yuan , Zhang Jian , Ran Xiaoju , Jia Xue , Wang Jing , Sun Longqin , Yang Huan , Li Yulei , Fu Bin , Huang Changwu , Liao Pu , Sun Wei
Published: July 2022

The COVID-19 pandemic caused by SARS-CoV-2 is exerting huge pressure on global healthcare. Understanding of the molecular pathophysiological alterations in COVID-19 patients with different severities during disease is important for effective treatment. In this study, we performed proteomic profiling of 181 serum samples collected at multiple time points from 79 COVID-19 patients with different severity levels (asymptomatic, mild, moderate, and severe/critical) and 27 serum samples from non-COVID-19 control individuals. Dysregulation of immune response and metabolic reprogramming was found in severe/critical COVID-19 patients compared with non-severe/critical patients, whereas asymptomatic patients presented an effective immune response compared with symptomatic COVID-19 patients. Interestingly, the moderate COVID-19 patients were mainly grouped into two distinct clusters using hierarchical cluster analysis, which demonstrates the molecular pathophysiological heterogeneity in COVID-19 patients. Analysis of protein-level alterations during disease progression revealed that proteins involved in complement activation, the coagulation cascade and cholesterol metabolism were restored at the convalescence stage, but the levels of some proteins, such as anti-angiogenesis protein PLGLB1, would not recovered. The higher serum level of PLGLB1 in COVID-19 patients than in control groups was further confirmed by parallel reaction monitoring (PRM). These findings expand our understanding of the pathogenesis and progression of COVID-19 and provide insight into the discovery of potential therapeutic targets and serum biomarkers worth further validation.
Quantitative anti-HBc combined with quantitative HBsAg can predict HBsAg clearance in sequential combination therapy with PEG-IFN-α in NA-suppressed chronic hepatitis B patients
Authors: Wang Wen-Xin , Jia Rui , Gao Ying-Ying , Liu Jia-Ye , Luan Jun-Qing , Qiao Fei , Liu Li-Min , Zhang Xiao-Ning , Wang Fu-Sheng , Fu Junliang
Published: July 2022

Background and aims

Precise predictors are lacking for hepatitis B surface antigen (HBsAg) clearance under the combination therapy of nucleos(t)ide analogs (NA) and pegylated interferon-alpha (PEG-IFN-α) in patients with chronic hepatitis B (CHB). This study aimed to determine the quantitative anti-hepatitis B core antibody (qAnti-HBc) and quantitative hepatitis B core-related antigen (qHBcrAg) as predictors for HBsAg clearance in NA-suppressed patients with CHB receiving PEG-IFN-α add-on therapy.

Methods

Seventy-four CHB patients who achieved HBV DNA suppression (HBV DNA < 20 IU/ml) and quantitative HBsAg (qHBsAg) < 1,500 IU/ml after ≥1 year of NA treatment were enrolled. Fifteen patients continued on NA monotherapy, while 59 patients received PEG-IFN-α add-on therapy. Serum qAnti-HBc and qHBcrAg levels were detected every 12 or 24 weeks for add-on and NA-alone groups, respectively.

Results

Serum qAnti-HBc but not qHBcrAg levels at baseline were negatively correlated with the duration of prior NA therapy. After 48-week treatment, both qAnti-HBc and qHBcrAg levels declined further, and 17/59 (28.81%) and 0/15 (0%) achieved HBsAg clearance in add-on and NA groups, respectively. In the add-on group, the rate of HBsAg clearance was significantly higher in patients with baseline qAnti-HBc < 0.1 IU/ml (52.63%). Logistic regression analysis identified baseline qAnti-HBc but not qHBcrAg, which was an independent predictor for HBsAg loss. Receiver operating characteristic curve analysis showed that the combination of qAnti-HBc and qHBsAg had a better predictive value for HBsAg clearance.

Conclusions

A combination of qHBsAg and baseline qAnti-HBc levels may be a better prediction strategy for HBsAg clearance in NA-suppressed CHB patients receiving PEG-IFN-α add-on therapy.
Case report: Variant-specific pre-exposure prophylaxis of SARS-CoV-2 infection in multiple sclerosis patients lacking vaccination responses
Authors: Woopen Christina , Konofalska Urszula , Akgün Katja , Ziemssen Tjalf
Published: July 2022

Sphingosine-1-phosphate receptor modulators and anti-CD20 treatment are widely used disease-modifying treatments for multiple sclerosis. Unfortunately, they may impair the patient’s ability to mount sufficient humoral and T-cellular responses to vaccination, which is of special relevance in the context of the SARS-CoV-2 pandemic. We present here a case series of six multiple sclerosis patients on treatment with sphingosine-1-phosphate receptor modulators who failed to develop SARS-CoV-2-specific antibodies and T-cells after three doses of vaccination. Due to their ongoing immunotherapy, lacking vaccination response, and additional risk factors, we offered them pre-exposure prophylactic treatment with monoclonal SARS-CoV-2-neutralizing antibodies. Initially, treatment was conducted with the antibody cocktail casirivimab/imdevimab. When the SARS-CoV-2 Omicron variant became predominant, we switched treatment to monoclonal antibody sotrovimab due to its sustained neutralizing ability also against the Omicron strain. Since sotrovimab was approved only for the treatment of COVID-19 infection and not for pre-exposure prophylaxis, we switched treatment to tixagevimab/cilgavimab as soon as it was granted marketing authorization in the European Union. This antibody cocktail has retained, albeit reduced, neutralizing activity against the Omicron variant and is approved for pre-exposure prophylaxis. No severe adverse events were recorded for our patients. One patient had a positive RT-PCR for SARS-CoV-2 under treatment with sotrovimab, but was asymptomatic. The other five patients did not develop symptoms of an upper respiratory tract infection or evidence of a SARS-CoV-2 infection during the time of treatment up until the finalization of this report. SARS-CoV-2-neutralizing antibody treatment should be considered individually for multiple sclerosis patients lacking adequate vaccination responses on account of their immunomodulatory treatment, especially in times of high incidences of SARS-CoV-2 infection.
Divergent complement system activation in two clinically distinct murine models of multiple sclerosis
Authors: Linzey Michael , DiSano Krista , Welsh Nora , Pachner Andrew , Gilli Francesca
Published: July 2022

Multiple sclerosis (MS) is a neurological disease featuring neuroinflammation and neurodegeneration in young adults. So far, most research has focused on the peripheral immune system, which appears to be the driver of acute relapses. Concurrently, the mechanisms underlying neurodegeneration in the progressive forms of the disease remain unclear. The complement system, a molecular component of the innate immunity, has been recently implicated in several neurological disorders, including MS. However, it is still unknown if the complement proteins detected in the central nervous system (CNS) are actively involved in perpetuating chronic inflammation and neurodegeneration. To address this knowledge gap, we compared two clinically distinct mouse models of MS: 1) proteolipid protein (PLP)-induced experimental autoimmune encephalomyelitis (rEAE) resembling a relapsing-remitting disease course, and 2) Theiler’s murine encephalomyelitis virus-induced demyelinating disease (TMEV-IDD) resembling a progressive disease. Real-time PCR was performed in the spinal cord of rEAE mice, TMEV-IDD mice and age-matched sham controls to quantify gene expression for a broad range of complement components. In both experimental models, we found significantly increased expression of complement factors, such as C1q, C3, CfB, and C3aR. We showed that the complement system, specifically the classical complement pathway, was associated with TMEV-IDD pathogenesis, as the expression of C1q, C3 and C3aR1 were all significantly correlated to a worse disease outcome (all P≤0.0168). In line with this finding, C1q and C3 deposition was observed in the spinal cord of TMEV-IDD mice. Furthermore, C1q deposition was detected in spinal cord regions characterized by inflammation, demyelination, and axonal damage. Conversely, activation of the classical complement cascade seemed to result in protection from rEAE (C1q: P=0.0307). Interestingly, the alternative pathway related to a worse disease outcome in rEAE (CFb: P=0.0006). Overall, these results indicate potential divergent roles for the complement system in MS. The chronic-progressive disease form is more reliant on the activation of the classic complement pathway, while protecting from acute relapses. Conversely, relapsing MS appears more likely affected by the alternative pathway. Understanding the functions of the complement system in MS is critical and can lead to better, more targeted therapies in the future.
Detection of neutrophil extracellular traps in patient plasma: method development and validation in systemic lupus erythematosus and healthy donors that carry IRF5 genetic risk
Authors: Matta Bharati , Battaglia Jenna , Barnes Betsy J.
Published: July 2022

Neutrophil extracellular traps (NETs) are web-like structures extruded by neutrophils after activation or in response to microorganisms. These extracellular structures are decondensed chromatin fibers loaded with antimicrobial granular proteins, peptides, and enzymes. NETs clear microorganisms, thus keeping a check on infections at an early stage, but if dysregulated, may be self-destructive to the body. Indeed, NETs have been associated with autoimmune diseases such as systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), antiphospholipid syndrome (APS), psoriasis, and gout. More recently, increased NETs associate with COVID-19 disease severity. While there are rigorous and reliable methods to quantify NETs from neutrophils via flow cytometry and immunofluorescence, the accurate quantification of NETs in patient plasma or serum remains a challenge. Here, we developed new methodologies for the quantification of NETs in patient plasma using multiplex ELISA and immunofluorescence methodology. Plasma from patients with SLE, non-genotyped healthy controls, and genotyped healthy controls that carry either the homozygous risk or non-risk IRF5-SLE haplotype were used in this study. The multiplex ELISA using antibodies detecting myeloperoxidase (MPO), citrullinated histone H3 (CitH3) and DNA provided reliable detection of NETs in plasma samples from SLE patients and healthy donors that carry IRF5 genetic risk. An immunofluorescence smear assay that utilizes only 1 µl of patient plasma provided similar results and data correlate to multiplex ELISA findings. The immunofluorescence smear assay is a relatively simple, inexpensive, and quantifiable method of NET detection for small volumes of patient plasma.
Characteristics of Dissolved Organic Matter in a Semi-closed Bay in Summer: Insights from Stable Isotope and Optical Analyses
Authors: Zhong Yafeng , Pan Gang , Zhao Hui , Wang Chao
Published: July 2022

Dissolved organic matter (DOM) serves as the most active and sensitive organic component in the bay, and its biogeochemical characteristics and reactivity are affected by the properties of terrestrial and marine substances significantly. In this study, in order to study the distribution and characteristics of DOM in a semi-closed bay, 34 water samples from 19 stations were collected from Zhanjiang Bay and analyzed for δ13C of dissolved inorganic carbon (DIC) and fluorescent components of DOM. The results showed that there were many sources of organic matter in the bay, including soil input, algae input, and sewage input. Influenced by freshwater input, DOM in the bay decreased from the upper bay to the outer bay. The organic matter in the bay displayed two characteristics, where the northern bay is composed of terrigenous organic matter mainly with high humus, while the southern bay is more inclined to marine sources with a high biological index (BIX) and low humification index (HIX). The correlation between organic matter with different characteristics and environmental parameters such as salinity, pH, and chlorophyll a was analyzed. The discrepancy may be caused by the weak turbulent mixing in the semi-closed bay.
Diurnal fluctuations in seawater pCO2 amplify the negative effects of ocean acidification on the biotic performance of the calcifying macroalga Halimeda opuntia
Authors: Wei Zhangliang , Zhang Yating , Yang Fangfang , Long Lijuan
Published: July 2022

Although the adverse effects of increasing atmospheric CO2-induced ocean acidification (OA) on marine calcifying macroalgae have been widely reported, there are limited studies on how daily fluctuations in pCO2 (pH) within shallow ecosystems influence the growth and physiological performance of these calcifiers. Therefore, a 42-day laboratory mimetic experiment to determine how growth, biological performance and related carbon and nitrogen metabolic products of the calcifying macroalga, Halimeda opuntia are generated in response to fluctuating pCO2 under OA conditions (1200 ppmv) was performed. The results of present study showed that the adverse effects of OA were more determined by the adverse influence of elevated acidity (H+) on growth rates, calcification, photosynthesis and the related biotic performance of H. opuntia compared with the positive effects that higher CO2 provided. Moreover, diurnal fluctuations in pCO2 levels [with higher (nearly 8.10) and lower pH (nearly 7.40) values during day and night times, respectively] have amplified these negative influences on H. opuntia. To mitigate elevated pCO2-related stress, higher contents of free amino acids and proline were highly secreted and likely linked to protecting the integrity of algal cellular structures. The above results contribute to increasing our understanding of the biological consequences of pCO2 (pH) variability on calcifying Halimeda species and their physiological plasticity in response to further oceanic pCO2 changes.
Topological optimization of a variable cross-section cantilever-based piezoelectric wind energy harvester
Authors: Zhao Kaiyuan , Zhang Qichang , Wang Wei , Han Jianxin , Hao Shuying
Published: July 2022

Wind energy is a typical foreseeable renewable energy source. This study constructs and optimizes a variable cross-section cantilever-based piezoelectric energy harvester for low-speed wind energy harvesting. The Galerkin approach is usually used to discretize the continuum model and then get the ordinary differential equations. However, this method is more suitable for calculating uniformity than the variable cross-sectional beam model. To solve this problem, we proposed an improved piecewise Galerkin approach for discretizing the continuum model with a variable cross section. By modifying the boundary expressions and modal functions between segments, it can improve both computation speed and accuracy. COMSOL simulations demonstrate that natural frequencies calculated via the improved method are more accurate than those of the traditional Galerkin method. The method of multiple scales is applied to determine the output power and critical wind velocity. A distinctive numerical approach is presented for shape optimization by combining the analytical calculation method with the particle swarm optimization (PSO) technique for low-speed wind energy harvesting. Additionally, the logic function is chosen to produce the optimal shape’s fitting expression for engineering applications. With all the improvements, the output power of a variable cross-section beam-based harvester reaches as much as 3.668 times that of a uniform beam model, demonstrating the importance of structural optimization for this type of energy harvesters. Finally, experiments are set up to verify the optimization procedure. Actually, it builds an analytical framework for the adaptive selection of variable-section piezoelectric cantilever wind-induced vibration energy harvesters.
Does patient and public involvement influence the development of competency frameworks for the health professions? A systematic review
Authors: Murray Nicole , Palermo Claire , Batt Alan , Bell Kristie
Published: July 2022

Competency frameworks typically describe the perceived knowledge, skills, attitudes and other characteristics required for a health professional to practice safely and effectively. Patient and public involvement in the development of competency frameworks is uncommon despite delivery of person-centered care being a defining feature of a competent health professional. This systematic review aimed to determine how patients and the public are involved in the development of competency frameworks for health professions, and whether their involvement influenced the outcome of the competency frameworks. Studies were identified from six electronic databases (MEDLINE, CINAHL, PsycINFO, EMBASE, Web of Science and ERIC). The database search yielded a total of 8,222 citations, and 43 articles were included for data extraction. Most studies were from the United Kingdom (27%) and developed through multidisciplinary collaborations involving two or more professions (40%). There was a large variation in the number of patients and members of the public recruited (range 1–1,398); recruitment sources included patients and carers with the clinical condition of interest (30%) or established consumer representative groups (22%). Common stages for involving patients and the public were in generation of competency statements (57%) or reviewing the draft competency framework (57%). Only ten studies (27%) took a collaborative approach to the engagement of patients and public in competency framework development. The main ways in which involvement influenced the competency framework were validation of health professional-derived competency statements, provision of desirable behaviors and attitudes and generation of additional competency statements. Overall, there was a lack of reporting regarding the details and outcome of patient and public involvement. Further research is required to optimize approaches to patient and public involvement in competency framework development including guidance regarding who, how, when and for what purposes they should be engaged and the requirements for reporting.

Systematic review registration:

https://www.crd.york.ac.uk/prospero/, identifier: CRD42020203117.
Probiotic-Based Bacteriocin: Immunity Supplementation Against Viruses. An Updated Review
Authors: Umair Muhammad , Jabbar Saqib , Zhaoxin Lu , Jianhao Zhang , Abid Muhammad , Khan Kashif-Ur R. , Korma Sameh A. , Alghamdi Mashail A. , El-Saadony Mohamed T. , Abd El-Hack Mohamed E. , Cacciotti Ilaria , AbuQamar Synan F. , El-Tarabily Khaled A. , Zhao Liqing
Published: July 2022

Viral infections are a major cause of severe, fatal diseases worldwide. Recently, these infections have increased due to demanding contextual circumstances, such as environmental changes, increased migration of people and product distribution, rapid demographic changes, and outbreaks of novel viruses, including the COVID-19 outbreak. Internal variables that influence viral immunity have received attention along with these external causes to avert such novel viral outbreaks. The gastrointestinal microbiome (GIM), particularly the present probiotics, plays a vital role in the host immune system by mediating host protective immunity and acting as an immune regulator. Bacteriocins possess numerous health benefits and exhibit antagonistic activity against enteric pathogens and immunobiotics, thereby inhibiting viral infections. Moreover, disrupting the homeostasis of the GIM/host immune system negatively affects viral immunity. The interactions between bacteriocins and infectious viruses, particularly in COVID-19, through improved host immunity and physiology are complex and have not yet been studied, although several studies have proven that bacteriocins influence the outcomes of viral infections. However, the complex transmission to the affected sites and siRNA defense against nuclease digestion lead to challenging clinical trials. Additionally, bacteriocins are well known for their biofunctional properties and underlying mechanisms in the treatment of bacterial and fungal infections. However, few studies have shown the role of probiotics-derived bacteriocin against viral infections. Thus, based on the results of the previous studies, this review lays out a road map for future studies on bacteriocins for treating viral infections.
The risk profile of patients with COVID-19 as predictors of lung lesions severity and mortality—Development and validation of a prediction model
Authors: Rahimi Ezat , Shahisavandi Mina , Royo Albert Cid , Azizi Mohammad , el Bouhaddani Said , Sigari Naseh , Sturkenboom Miriam , Ahmadizar Fariba
Published: July 2022

Objective

We developed and validated a prediction model based on individuals' risk profiles to predict the severity of lung involvement and death in patients hospitalized with coronavirus disease 2019 (COVID-19) infection.

Methods

In this retrospective study, we studied hospitalized COVID-19 patients with data on chest CT scans performed during hospital stay (February 2020-April 2021) in a training dataset (TD) (n = 2,251) and an external validation dataset (eVD) (n = 993). We used the most relevant demographical, clinical, and laboratory variables (n = 25) as potential predictors of COVID-19-related outcomes. The primary and secondary endpoints were the severity of lung involvement quantified as mild (≤25%), moderate (26–50%), severe (>50%), and in-hospital death, respectively. We applied random forest (RF) classifier, a machine learning technique, and multivariable logistic regression analysis to study our objectives.

Results

In the TD and the eVD, respectively, the mean [standard deviation (SD)] age was 57.9 (18.0) and 52.4 (17.6) years; patients with severe lung involvement [n (%):185 (8.2) and 116 (11.7)] were significantly older [mean (SD) age: 64.2 (16.9), and 56.2 (18.9)] than the other two groups (mild and moderate). The mortality rate was higher in patients with severe (64.9 and 38.8%) compared to moderate (5.5 and 12.4%) and mild (2.3 and 7.1%) lung involvement. The RF analysis showed age, C reactive protein (CRP) levels, and duration of hospitalizations as the three most important predictors of lung involvement severity at the time of the first CT examination. Multivariable logistic regression analysis showed a significant strong association between the extent of the severity of lung involvement (continuous variable) and death; adjusted odds ratio (OR): 9.3; 95% CI: 7.1–12.1 in the TD and 2.6 (1.8–3.5) in the eVD.

Conclusion

In hospitalized patients with COVID-19, the severity of lung involvement is a strong predictor of death. Age, CRP levels, and duration of hospitalizations are the most important predictors of severe lung involvement. A simple prediction model based on available clinical and imaging data provides a validated tool that predicts the severity of lung involvement and death probability among hospitalized patients with COVID-19.
Mapping trends and hotspot regarding gut microbiota and host immune response: A bibliometric analysis of global research (2011–2021)
Authors: Ni Zhexin , Wang Sheng , Li Yangshuo , Zhou Ling , Zhai Dongxia , Xia Demeng , Yu Chaoqin
Published: July 2022

Background

Gut microbiota is a complex ecosystem that is vital for the development and function of the immune system, is closely associated with host immunity, and affects human health and disease. Therefore, the current progress and trends in this field must be explored.

Purpose

No bibliometric analysis has been conducted on gut microbiota and host immune response. This study aimed to analyze the current progress and developing trends in this field through bibliometric and visual analysis.

Methods

Global publications on gut microbiota and host immune response from January 2011 to December 2021 were extracted from the Web of Science (WOS) collection database. GraphPad Prism, VOSviewer software, and CiteSpace were employed to perform a bibliometric and visual study.

Results

The number of publications has rapidly increased in the last decade but has declined in the most recent year. The Cooperation network shows that the United States, Harvard Medical School, and Frontiers in Immunology were the most active country, institute, and journal in this field, respectively. Co-occurrence analysis divided all keywords into four clusters: people, animals, cells, and diseases. The latest keyword within all clusters was “COVID,” and the most frequently occurring keyword was “SCFA.”

Conclusion

Gut microbiota and host immune response remain a research hotspot, and their relation to cancer, CNS disorders, and autoimmune disease has been explored. However, additional studies on gut microbiota must be performed, particularly its association with bacterial strain screening and personalized therapy.