bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Pollution load on tide conditions in Air Hitam River, Pekanbaru City, Riau Province
Authors: Yuliati Y , Sumiarsih E , Efawani E , Mulyani I , Fahreza M I 
Published: December 2022

Abstract
The Air Hitam River is one of the 13 creeks of the Siak River that flows in a peat swamp area. The watershed area of Air Hitam River is a peat swamp that has been converted into oil palm plantations, residential areas, and industrial warehousing. This study aims to calculate the pollution load of the Air Hitam River in tidal conditions with the parameters TSS, BOD, COD, nitrite and total phosphate. Samples were taken from January-March 2022 and analyzed to estimate the pollution load in the tributary. The results of the analysis of the pollution load at high tide were 18163.2 kg/day (TSS), 10.982.4 kg/day (BOD), 15.415 kg/day (COD), 249.22 (nitrate), 234.432 and 240.768, (total phosphate). While at low tide the pollution load was 26379.648 kg/day for TSS, 5.354,36 kg/day BOD, 12.818 kg/day COD, 253.70 kg/day nitrate and 238.61 kg/day total phosphate.
Growth Patterns Analysis of Yellow-Finned Medaka (Oryzias profundicola) as Endemic Fish in Lake Towuti
Authors: Nursyahran N , Jayadi J , Tamsil A , Harlina H 
Published: December 2022

Abstract
Lake Towuti has the potential biological resource and a wide diversity of endemic fish with ecological and economic value. Lake Towuti is also known as a biodiversity hotspot that needs attention to conservation because of the number of threads increasing. Fisheries resources in Lake Towuti has a significant role in increasing income, expanding job opportunity, and as a nutritional source for the community. Lake Towuti is also known as rich in endemic fisheries that have economic and ecological value. One of them is known as Yellow-Finned Medaka (Oryzias profundicola). Yellow-Finned Medaka is a biological native resource and endemic fish in Lake Towuti, South Sulawesi. A study about this fish has never been conducted before so it needs research to analyse the growth pattern in Lake Towuti. This study aims to determine the growth pattern of yellow-finned medaka in Lake Towuti. Samples were collected from January to July 2022 every month and measured their length and weight. During the study were found 2949 fish, consisting of 1202 males and 1747 females. The length-weight relationship was W=1.3366L0.0041 for males and 0.9127L0.0187 for females. These results indicate that the growth pattern for yellow-finned Medaka is negative allometric.
Monitoring the Ecotoxicology of the Koto Panjang Reservoir by Determining the Levels of Heavy Metals
Authors: Harjoyudanto Y , Hendrizal A , Junaidi R , Budijono  
Published: December 2022

Abstract
Water quality monitoring activities are important to be carried out regularly. This activity is intended as an effort to create sustainable cultivation activities. The Koto Panjang Reservoir is one of the reservoirs used for aquaculture activities, so monitoring activities at this location are important things to do. This activity was carried out using a survey method at two observation locations. Location 1 is the floating net caged area, and Location 2 is the upstream or non-floating net cages area. Direct water quality measurements were carried out in both locations: temperature, pH, and DO. In addition, water samples were taken to see the content of heavy metals, namely Cd and Pb. Water samples were carried out to see the heavy metal content at the Basic Chemistry Laboratory, Faculty of Engineering, Riau University. The results showed that overall, the physicochemical quality of water at the Koto Panjang Reservoir, both Locations 1 and 2, namely temperature, dissolved oxygen, and pH, still met the requirements for fish farming. While the value of Cd in all observation locations at the Koto Panjang Reservoir exceeds the quality standard, it can be said to be polluted. Unlike Cd, there is a difference in the value of Pb at Location I and II, namely Pb at Location I; the Pb value is outside the quality standard threshold or is said to be polluted, while Location II still has not exceeded the quality standard. The high Pb value at Location I was due to many fishing boat activities with engines.
Bacterial pathogens in fresh fish sold from the wet market in Kota Kinabalu, Malaysia
Authors: Gao P , Shaarani S M , Nor Qhairul Izzreen M N 
Published: December 2022

Abstract
This study aimed to evaluate the microbiological quality of commercial fresh fish. A total of 7 marine fish species (n = 9 per species) were collected and sold from the wet market in Kota Kinabalu, Malaysia. The prevalence of Pseudomonas spp. (100%) in fish was the highest followed by Aeromonas spp. (58%), Escherichia coli (46.03%), Vibrio spp. (22%), and Salmonella spp. (6.35%). The mean of the total plate counts in gill, gastrointestinal tract, skin and flesh samples were 5.32 ± 0.69 log cfu/g, 4.81 ± 0.81 log cfu/g, 4.23 ± 0.58 log cfu/cm2 and 3.99 ± 0.58 log cfu/g, respectively. Therefore, fresh fish sold in Kora Kinabalu has the potential to be contaminated with pathogenic bacteria. Effective control measures are required to prevent contamination during postharvest fish processing and consumers are advised to avoid eating raw fish to reduce health hazards from bacteria.
Implementation of Biodiversity Conventions in Protecting and Conserving Indonesia’s Marine Environment
Authors: Widayanti T F , Syarif L M , Aswan M , Hakim M Z , Djafart E M , Ratnawati  
Published: December 2022

Abstract
Indonesia has three main ecosystems, mangroves, coral reefs and sea grass bed ecosystems as characteristics of a coastal countries. However, the three ecosystems are getting more and more damaged daily. This is caused by activities carried out by humans such as very fast infrastructure of coastal areas, marine debris and overfishing, and other consequences. To overcome this, the government has issued various policies, especially regarding protecting biodiversity in the three ecosystems. One of the actions taken by the government is to ratify the biodiversity convention (CBD) through Law Number 5 of 1994. Since the agenda for the Sustainable Development Goals (SDGs) as a global development established, the implementation of the biodiversity convention must be aligned with the SDGs, to create equitable development and ensure human welfare. Subsequently, a conflict emerged, was how to align policies to provide effective protection for the conservation of the three marine ecosystems while continuing to develop globally so that the marine environment preservation was maintained and developed for the community, especially in coastal areas continued to develop. This study uses a normative approach by analyzing international conventions and related national regulations and then be written down by descriptive analysis. This research has purposed to find the perfect concept of policy for the implementation of CBD to give protection and conservation the environment in the Indonesia sea. Research shows that it is necessary to make legal regulations that contain strict sanctions against perpetrators of destroying marine ecosystems because so far, there have been no strict sanctions given by law enforcement officers against those who violate these rules.
The dynamics of benthic invertebrates in different part of peat swamp forests converted to rice fields
Authors: Erniaty E , Gumiri S , Ardianor A , Haryono A , Yulintine Y 
Published: December 2022

Abstract
The Indonesian government plans to turn Central Kalimantan province into a national food barn by planting rice paddies in several places, including in shallow peatlands. Tropical peatlands have limited potential to be used as agricultural land since the growing media in some cases, is not conducive to root development, saturated-water soil that poissons the plants. Aquatic invertebrates can be used as indicators to determine whether water quality in a field is safe for plants or not. The objective of this study is to evaluate the dynamics of benthic in different part of aquatic ecosystems on peat swamp forests. This study was conducted in Peat Techno Park (PTP) of the University of Palangka Raya, Central Kalimantan. Samples were collected from 9 stations with different forms of land use for agricultural activities, namely unplowed paddy fields, plowed fields, swamps, connecting ditches, beje, natural peat swamp forests, breeding ponds, and irrigation ponds. Data were collected over 6 months and coincided with the peak of dry and wet seasons. The abundance and species of aquatic invertebrates were then analyzed some related physic-chemical parameters, such as depth, water temperature, pH, and dissolved oxygen (DO). The results showed that the macrozoobenthos species found on this study was slightly rare. There was identified merely 3 genera, include in the two benthic groups, e.i. Annelida and insect. As to the insect, the dominant species was from the order of Diptera and family of Chironomidae, especially Chironomus. Spatially, stations 1 (unplowed rice fields), 2 (ploughed rice fields), 3 (peat swamp forest), 7 (cultivated ponds), and 9 (new beje) were particularly abundant. In this case, the conversion of peat swamp forests to rice fields and fish culture ponds will possibly promote greater diversity and abundance of macroinvertebrate communities.
The competitiveness of Indonesia’s frozen shrimp exports in international market
Authors: Yolandika C , Sofyani T , Mursyid H , Anggraini N , Berliana D 
Published: December 2022

AbstractShrimp is the first Indonesia’s leading fishery export commodity, above tuna, squid, crab, and seaweed. The categories of shrimp that are exported are frozen shrimp, fresh shrimp, and processed shrimp, where the largest quantity for the shrimp export category is frozen shrimp. However, Indonesia’s export value growth for frozen shrimp is still lower than its competitors. This study aims to analyze the level of competitiveness of frozen shrimp exports in Indonesia among competing countries in international market. The data used was secondary data obtained from related agencies. The analytical method used to analyze competitiveness is Revealed Comparative Advantage (RCA). This method was used to analyze changes in the level of competition for 1 years, namely 2007 – 2021. The results showed that in international market on 2007-2021, Indonesia’s frozen shrimp exports has a strong competitiveness. Indonesian frozen shrimp the competitiveness had a trend that tends to decline within 11 years. Based on the analysis results using RCA method, Indonesian frozen shrimp competitiveness on the 2007-2021 period was seen to decrease until 2012 and began to increase in 2013, while other competing countries, namely Argentina, Ecuador and India, showed an increase in competitiveness. Meanwhile, several other competing countries such as Bangladesh, Belgium, Denmark, Mexico, Thailand, and Vietnam experienced a decline in competitiveness as well as the value of RCA decreased.
A novel method for multichannel discharge image diagnosis in gas switches based on multi-axis tomography techniques
Authors: ZHANG Yanhong , SHENG Liang , LI Yang , ZHANG Mei , HEI Dongwei 
Published: December 2022

Abstract
The discharge channel is a crucial diagnostic tool for identifying the properties of gas switches. However, single-view images cannot easily be used to inherently understand the discharge channel characteristics of trigger electrodes. A reconstruction method of the discharge channel in gas switches is proposed based on a multi-axis tomography technique, which uses very few projections of optical images to reconstruct the location of a multichannel discharge in annular electrodes. In this paper, an algorithm named TVM-OSEM (total variation minimization ordered subsets expectation maximization) is proposed, which can effectively remove artifact noise to improve the reconstruction accuracy of discharge channels. The method is validated against simulations of a radiator with high-density-difference boundary. The calculated discharge channel distribution from one experiment is presented.
Inhibition of Ceramide Synthesis Attenuates Chronic Ethanol Induced Cardiotoxicity by Restoring Lysosomal Function and Reducing Necroptosis
Authors: Xue Qiupeng , Zhang Tianyi , Zhu Rongzhe , Qian Yile , Dong Xiaoru , Mo Lingjie , Jiang Yan 
Published: December 2022

AbstractAimsChronic alcohol misuse could cause alcoholic cardiomyopathy (ACM), and the specific mechanisms remained largely unknown. In this study, we aimed to explore the effects of endogenous ceramides on chronic ethanol-induced myocardial injury or cell loss (e.g. necroptosis).MethodsWe established chronic alcohol intoxication models in vivo (male C57BL/6 mice) and in vitro (H9c2 cardiomyoblasts). The ceramide profiles were analyzed in mice myocardium and cultured cardiomyocytes. Further research on the role of ceramides and underlying signaling pathways was carried out in H9c2 cells.Results and conclusionsThe ceramide profiles analysis revealed increased long and very long–chain ceramides in alcoholic myocardium and ethanol-treated cardiomyocytes. Next, we proved that endogenous ceramide inhibition could reduce necroptosis and alleviate cardiomyocytes injury as suggested by decreased levels of p-RIPK1, p-RIPK3 and p-MLKL proteins and cardiac injury factors expression. Furthermore, we found that lysosomal dysfunction also contributed to alcohol-induced cardiac damage and inhibiting ceramide biosynthesis could repaired this to some extent. Cells studies with exogenous C6 ceramide confirmed the pleotropic roles of ceramide in myocardial damage by causing both necroptosis and lysosomal dysfunction. Finally, our data suggested that lysosomal dysfunction could sensitize cardiomyocytes to induction of necroptosis due to the restriction on degradation of RIPK1/RIPK3 proteins. In conclusion, chronic ethanol treatment boosted myocardial ceramide synthesis in animal hearts and cultured cardiomyocytes. Moreover, ceramides exerted crucial roles in the intrinsic signaling pathways of alcohol-induced cardiotoxicity. Targeting ceramide biosynthesis to simultaneously attenuate necroptosis and lysosomal dysfunction might be a novel strategy for preventing alcoholic cardiotoxicity.
Effect of Clomethiazole Vs. Clorazepate on Hepatic Fat and Serum Transaminase Activities in Alcohol-Associated Liver Disease: Results from a Randomized, Controlled Phase II Clinical Trial
Authors: Hohmann Nicolas , Schröder Fabian , Moreira Bernardo , Teng Haidong , Burhenne Jürgen , Bruckner Thomas , Mueller Sebastian , Haefeli Walter E , Seitz Helmut K 
Published: December 2022

AbstractAimsAlcohol-associated liver disease (ALD) is a global health problem caused, among other factors, by oxidative stress from the formation of reactive oxygen species (ROS). One important source of ROS is microsomal ethanol metabolism catalyzed by cytochrome P450 2E1 (CYP2E1), which is induced by chronic ethanol consumption. Inhibition of CYP2E1 by clomethiazole (CMZ) decreases oxidative stress in cell cultures and improves ALD in animal studies. Our study aimed to assess the benefits of a CYP2E1 inhibitor (clomethiazole) in detoxification of patients with ALD.MethodsOpen label, randomized controlled clinical trial to study whether CYP2E1 inhibition improves ALD in the patients with alcohol use disorders admitted for alcohol detoxification therapy (ADT). Patients had to have a serum aspartate aminotransferase (AST) activity exceeding twice the upper normal limit at time of admission and be non-cirrhotic defined by fibroscan value &lt;12 kPa. Sixty patients were randomly assigned to ADT with either CMZ or clorazepate (CZP) for 7–10 days in a 1:1 ratio. The chlorzoxazone test of CYP2E1 activity was performed at enrolment and at 2 points during the study.ResultsADT improved hepatic steatosis (controlled attenuation parameter) in both groups significantly. A trend towards a greater improvement in hepatic fat content during ADT (−21.5%) was observed in the CMZ group (252 ± 48 dB/m vs. 321 ± 38 dB/m; P &lt; 0.0001) compared with the CZP group (−13.9%; 273 ± 38 dB/m vs. 317 ± 39 dB/m; P &lt; 0.0001). As already reported, serum AST (P &lt; 0.004) and alanine aminotransferase (ALT) activities (P &lt; 0.0006) significantly decreased in CMZ patients as compared with patients on CZP by the end of hospitalization. A significant correlation was found between AST (P = 0.023), ALT (P = 0.009), GGT (P = 0.039) and CAP.ConclusionThis study demonstrates that CMZ improves clinical biomarkers for ALD in humans most likely due to its inhibitory effect on CYP2E1. Because of its addictive potential, CMZ can only be given for a short period of time and therefore other CYP2E1 inhibitors to treat ALD are needed.
DRONet: effectiveness-driven drug repositioning framework using network embedding and ranking learning
Authors: Yang Kuo , Yang Yuxia , Fan Shuyue , Xia Jianan , Zheng Qiguang , Dong Xin , Liu Jun , Liu Qiong , Lei Lei , Zhang Yingying , Li Bing , Gao Zhuye , Zhang Runshun , Liu Baoyan , Wang Zhong , Zhou Xuezhong 
Published: December 2022

AbstractAs one of the most vital methods in drug development, drug repositioning emphasizes further analysis and research of approved drugs based on the existing large amount of clinical and experimental data to identify new indications of drugs. However, the existing drug repositioning methods didn’t achieve enough prediction performance, and these methods do not consider the effectiveness information of drugs, which make it difficult to obtain reliable and valuable results. In this study, we proposed a drug repositioning framework termed DRONet, which make full use of effectiveness comparative relationships (ECR) among drugs as prior information by combining network embedding and ranking learning. We utilized network embedding methods to learn the deep features of drugs from a heterogeneous drug-disease network, and constructed a high-quality drug-indication data set including effectiveness-based drug contrast relationships. The embedding features and ECR of drugs are combined effectively through a designed ranking learning model to prioritize candidate drugs. Comprehensive experiments show that DRONet has higher prediction accuracy (improving 87.4% on Hit@1 and 37.9% on mean reciprocal rank) than state of the art. The case analysis also demonstrates high reliability of predicted results, which has potential to guide clinical drug development.
SiameseCPP: a sequence-based Siamese network to predict cell-penetrating peptides by contrastive learning
Authors: Zhang Xin , Wei Lesong , Ye Xiucai , Zhang Kai , Teng Saisai , Li Zhongshen , Jin Junru , Kim Min Jae , Sakurai Tetsuya , Cui Lizhen , Manavalan Balachandran , Wei Leyi 
Published: December 2022

AbstractBackgroundCell-penetrating peptides (CPPs) have received considerable attention as a means of transporting pharmacologically active molecules into living cells without damaging the cell membrane, and thus hold great promise as future therapeutics. Recently, several machine learning-based algorithms have been proposed for predicting CPPs. However, most existing predictive methods do not consider the agreement (disagreement) between similar (dissimilar) CPPs and depend heavily on expert knowledge-based handcrafted features.ResultsIn this study, we present SiameseCPP, a novel deep learning framework for automated CPPs prediction. SiameseCPP learns discriminative representations of CPPs based on a well-pretrained model and a Siamese neural network consisting of a transformer and gated recurrent units. Contrastive learning is used for the first time to build a CPP predictive model. Comprehensive experiments demonstrate that our proposed SiameseCPP is superior to existing baseline models for predicting CPPs. Moreover, SiameseCPP also achieves good performance on other functional peptide datasets, exhibiting satisfactory generalization ability.
Incorporating higher order network structures to improve miRNA–disease association prediction based on functional modularity
Authors: He Yizhou , Yang Yue , Su Xiaorui , Zhao Bowei , Xiong Shengwu , Hu Lun 
Published: December 2022

Abstract
As microRNAs (miRNAs) are involved in many essential biological processes, their abnormal expressions can serve as biomarkers and prognostic indicators to prevent the development of complex diseases, thus providing accurate early detection and prognostic evaluation. Although a number of computational methods have been proposed to predict miRNA–disease associations (MDAs) for further experimental verification, their performance is limited primarily by the inadequacy of exploiting lower order patterns characterizing known MDAs to identify missing ones from MDA networks. Hence, in this work, we present a novel prediction model, namely HiSCMDA, by incorporating higher order network structures for improved performance of MDA prediction. To this end, HiSCMDA first integrates miRNA similarity network, disease similarity network and MDA network to preserve the advantages of all these networks. After that, it identifies overlapping functional modules from the integrated network by predefining several higher order connectivity patterns of interest. Last, a path-based scoring function is designed to infer potential MDAs based on network paths across related functional modules. HiSCMDA yields the best performance across all datasets and evaluation metrics in the cross-validation and independent validation experiments. Furthermore, in the case studies, 49 and 50 out of the top 50 miRNAs, respectively, predicted for colon neoplasms and lung neoplasms have been validated by well-established databases. Experimental results show that rich higher order organizational structures exposed in the MDA network gain new insight into the MDA prediction based on higher order connectivity patterns.
Improving therapeutic synergy score predictions with adverse effects using multi-task heterogeneous network learning
Authors: Yue Yang , Liu Yongxuan , Hao Luoying , Lei Huangshu , He Shan 
Published: December 2022

Abstract
Drug combinations could trigger pharmacological therapeutic effects (TEs) and adverse effects (AEs). Many computational methods have been developed to predict TEs, e.g. the therapeutic synergy scores of anti-cancer drug combinations, or AEs from drug–drug interactions. However, most of the methods treated the AEs and TEs predictions as two separate tasks, ignoring the potential mechanistic commonalities shared between them. Based on previous clinical observations, we hypothesized that by learning the shared mechanistic commonalities between AEs and TEs, we could learn the underlying MoAs (mechanisms of actions) and ultimately improve the accuracy of TE predictions. To test our hypothesis, we formulated the TE prediction problem as a multi-task heterogeneous network learning problem that performed TE and AE learning tasks simultaneously. To solve this problem, we proposed Muthene (multi-task heterogeneous network embedding) and evaluated it on our collected drug–drug interaction dataset with both TEs and AEs indications. Our experimental results showed that, by including the AE prediction as an auxiliary task, Muthene generated more accurate TE predictions than standard single-task learning methods, which supports our hypothesis. Using a drug pair Vincristine—Dasatinib as a case study, we demonstrated that our method not only provides a novel way of TE predictions but also helps us gain a deeper understanding of the MoAs of drug combinations.