bluuebunny/crossref_metadata_2025 huggingface dataset:
Long read sequencing characterises a novel structural variant, revealing underactive AKR1C1 with overactive AKR1C2 as a possible cause of severe chronic fatigue
Authors: Oakley Julia , Hill Martin , Giess Adam , Tanguy Mélanie , Elgar Greg
Published: November 2023

Background

Causative genetic variants cannot yet be found for many disorders with a clear heritable component, including chronic fatigue disorders like myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). These conditions may involve genes in difficult-to-align genomic regions that are refractory to short read approaches. Structural variants in these regions can be particularly hard to detect or define with short reads, yet may account for a significant number of cases. Long read sequencing can overcome these difficulties but so far little data is available regarding the specific analytical challenges inherent in such regions, which need to be taken into account to ensure that variants are correctly identified. Research into chronic fatigue disorders faces the additional challenge that the heterogeneous patient populations likely encompass multiple aetiologies with overlapping symptoms, rather than a single disease entity, such that each individual abnormality may lack statistical significance within a larger sample. Better delineation of patient subgroups is needed to target research and treatment.

Methods

We use nanopore sequencing in a case of unexplained severe fatigue to identify and fully characterise a large inversion in a highly homologous region spanning the AKR1C gene locus, which was indicated but could not be resolved by short-read sequencing. We then use GC–MS/MS serum steroid analysis to investigate the functional consequences.

Results

Several commonly used bioinformatics tools are confounded by the homology but a combined approach including visual inspection allows the variant to be accurately resolved. The DNA inversion appears to increase the expression of AKR1C2 while limiting AKR1C1 activity, resulting in a relative increase of inhibitory GABAergic neurosteroids and impaired progesterone metabolism which could suppress neuronal activity and interfere with cellular function in a wide range of tissues.

Conclusions

This study provides an example of how long read sequencing can improve diagnostic yield in research and clinical care, and highlights some of the analytical challenges presented by regions containing tandem arrays of genes. It also proposes a novel gene associated with a novel disease aetiology that may be an underlying cause of complex chronic fatigue. It reveals biomarkers that could now be assessed in a larger cohort, potentially identifying a subset of patients who might respond to treatments suggested by the aetiology.
Cyanidin-3-O-glucoside protects the brain and improves cognitive function in APPswe/PS1ΔE9 transgenic mice model
Authors: Baek Hana , Sanjay  , Park Miey , Lee Hae-Jeung
Published: November 2023

Cyanidin-3-O-glucoside (C3G) is a natural anthocyanin with antioxidant, anti-inflammatory, and antitumor properties. However, as the effects of C3G on the amyloidogenic pathway, autophagy, tau phosphorylation, neuronal cell death, and synaptic plasticity in Alzheimer’s disease models have not been reported, we attempted to investigate the same in the brains of APPswe/PS1ΔE9 mice were analyzed. After oral administration of C3G (30 mg/kg/day) for 16 weeks, the cortical and hippocampal regions in the brains of APPswe/PS1ΔE9 mice were analyzed. C3G treatment reduced the levels of soluble and insoluble Aβ (Aβ40 and Aβ42) peptides and reduced the protein expression of the amyloid precursor protein, presenilin-1, and β-secretase in the cortical and hippocampal regions. And C3G treatment upregulated the expression of autophagy-related markers, LC3B-II, LAMP-1, TFEB, and PPAR-α and downregulated that of SQSTM1/p62, improving the autophagy of Aβ plaques and neurofibrillary tangles. In addition, C3G increased the protein expression of phosphorylated-AMPK/AMPK and Sirtuin 1 and decreased that of mitogen-activated protein kinases, such as phosphorylated-Akt/Akt and phosphorylated-ERK/ERK, thus demonstrating its neuroprotective effects. Furthermore, C3G regulated the PI3K/Akt/GSK3β signaling by upregulating phosphorylated-Akt/Akt and phosphorylated-GSK3β/GSK3β expression. C3G administration mitigated tau phosphorylation and improved synaptic function and plasticity by upregulating the expression of synapse-associated proteins synaptophysin and postsynaptic density protein-95. Although the potential of C3G in the APPswe/PS1ΔE9 mouse models has not yet been reported, oral administration of the C3G is shown to protect the brain and improve cognitive behavior.

Graphical Abstract
In-house ELISA protocols for capsid p24 detection of diverse HIV isolates
Authors: Molina Mariano A. , Vink Monique , Berkhout Ben , Herrera-Carrillo Elena
Published: November 2023

Background

The capsid p24 (CA-p24) antigen is a component of the viral capsid of human immunodeficiency virus (HIV) that has been commonly used for clinical diagnosis and monitoring of HIV infections in Enzyme-linked Immunosorbent Assays (ELISAs). Commercial CA-p24 ELISAs are widely used in research settings, but these kits are costly and have limited breadth for detecting diverse HIV isolates.

Methods

Commercial CA-p24 antibodies were used as capture and detection antibodies. Specific CA-p24 ELISAs were established with these antibodies and tested for the detection of HIV-1 isolates with the aim of developing in-house protocols to recognize HIV-1 infections in vitro for research purposes.

Results

Here we present four protocols for in-house ELISAs to detect HIV CA-p24 using commercial antibodies. The assays were able to detect the CA-p24 antigen of different HIV-1 isolates tested. Comparison between the protocols showed that these in-house ELISAs exhibit high specificity, sensitivity, and reproducibility for CA-p24 quantitation but their reactivity varied per HIV-1 isolate and subtype.

Conclusions

These optimized ELISA protocols represent valuable tools to investigate HIV-1 infections in research facilities at a lower price than commercial CA-p24 kits.
Anodal transcranial direct current stimulation associated with aerobic exercise on the functional and physical capacity of patients with heart failure with reduced ejection fraction: ELETRIC study protocol
Authors: da Silva Vanessa Christina Costa , da Silva Arêas Fernando Zanela , Lopes Antônio Luiz Ribeiro Boechat , de Almeida e Val Fernando Fonseca , da Costa Allyson Guimarães , dos Santos Joana Colares Correa , Ferreira João Marcos Bemfica Barbosa , Peixoto Tinoco Arêas Guilherme
Published: November 2023

Background

The hallmark symptom of heart failure (HF) is severe exercise intolerance. Fortunately, accumulated evidence suggests that exercise programs improve physical performance, enhance autonomy in daily activities and quality of life, and reduce cardiovascular and other hospitalizations. Recently, experimental studies have explored the application of non-invasive brain stimulation techniques, especially transcranial direct current stimulation (tDCS), aiming to improve physical performance due to its ability to modulate brain functioning. The primary objective of the present study is to evaluate the effects of anodal tDCS associated with aerobic exercise on the functional capacity of patients with HF with reduced ejection fraction (HFrEF). Secondary objectives are to compare the effects of tDCS associated with aerobic exercise vs. sham-tDCS associated with aerobic exercise on cardiopulmonary exercise capacity; inflammatory cytokines; and quality of life.

Methods

This is a two-arm, prospectively registered, randomized trial with concealed allocation, double-blind, and intention-to-treat analysis. Forty-four patients with HFrEF will be recruited. The experimental group will undertake 25–30 min aerobic exercise training associated with tDCS, for 4 weeks. The control group will undergo the same aerobic exercise training, but with sham-tDCS. The primary outcome will be functional performance by the 6-min walk test. Secondary outcomes will include cardiopulmonary exercise capacity, inflammatory cytokines, and quality of life. Outcomes will be collected by a researcher blinded to group allocation at baseline (T0) and after 4 weeks of intervention (T1).

Discussion

Although previous studies have investigated the combined effect of tDCS on T3 area and physical performance and have suggested that tDCS could have reduced ratings of perceived exertion by affecting the activity of the insular cortex, and therefore increase exercise tolerance, this study is the first to evaluate the effects of the addition of anodal tDCS to aerobic exercise training for improving physical and functional performance, decreasing the perceived exertion, altering the quantification of inflammatory cytokines, and improving the subclinical values of the cardiopulmonary test in patients with HFrEF, which could result in an important advance in cardiac rehabilitation for patients with chronic HF.

Trial registration

Brazilian Registry of Clinical Trials (ReBEC) RBR-10w787j6. Registered on 25 April 2023. https://ensaiosclinicos.gov.br/pesquisador
Predicting attrition of men with a history of violence from randomised clinical trials
Authors: Doring Natalie , Hwang Ye In , Akpanekpo Emaediong , Gullotta Mathew , Ton Bianca , Knight Lee , Knight Crosbi , Schofield Peter , Butler Tony Gerard
Published: November 2023

Preventing dropout (attrition) from clinical trials is vital for improving study validity. Dropout is particularly important in justice-involved populations as they can be very challenging to engage and recruit in the first instance. This study identifies factors associated with dropout in a double-blind, placebo-controlled randomised control trial of a selective serotonin reuptake inhibitor (SSRI) aimed at reducing reoffending in highly impulsive men with histories of violent offending. Age, education, social support, psychiatric history, and length of previous incarceration were identified as factors that predict attrition. These findings are consistent with previous research examining variables associated with attrition in clinical trials for community and offender populations. We also explored referral source and treatment allocation as attrition predictors. Although neither significantly predicted attrition, we identified that there are discernible differences in the median time to attrition among the referral source subgroups. Understanding factors that predict treatment completion and attrition will allow researchers to identify participants for whom additional provisions may optimise retention and inform development of targeted interventions.
TIGIT reverses IFN-α-promoted Th1-like Tregs via in-sequence effects dependent on STAT4
Authors: Yu Shihan , Gu Jia , Wang Rui , Lee Seunghyun , Shan Yu , Wang Jiakai , Sun Yini , Ma Xiaoxue
Published: November 2023

Objectives

The induction direction of interferon (IFN)-α in T-cell phenotype and function varies depending on the activation state of the cell and the time of stimulation. To assess the effects of elevated IFN-α on regulatory T cells (Tregs) in systemic lupus erythematosus (SLE) patients, we investigated the differentiation of Th1-like Tregs under in-sequence and out-of-sequence conditions and the reversal effect of activating TIGIT on immune suppression.

Methods

Phenotypes and activation levels of Tregs from SLE patients and healthy controls were analyzed using flow cytometry. In vitro culture conditions based on the sequence of TCR activation and IFN-α stimulation simulated in-sequence or out-of-sequence effects. CD4+T cells and Tregs were cultured under the above conditions with or without TIGIT agonist. Expression of related characteristic markers and phosphorylation levels of AKT, mTOR, and STATs were detected using flow cytometry and ELISA.

Results

The frequency of Th1-like Tregs and activation levels of Tregs increased, but TIGIT expression in Tregs decreased in SLE patients. IFN-α promoted the conversation of Tregs to Th1-like Tregs while reducing immunosuppressive function under in-sequence conditions. The STAT4 pathway, but not the STAT1 pathway, was crucial for the IFN-α-mediated in-sequence effects. Reactivation of TIGIT reversed Th1 polarization of Tregs by suppressing AKT/mTOR and STAT4 signaling.

Conclusions

Our findings suggest that IFN-α mediated in-sequence effects on Tregs may be responsible for the expansion of Th1-like Tregs in SLE. TIGIT can restore immune suppression damage in Tregs and represents a potential therapeutic target for SLE.
LEP (G2548A-G19A) and ADIPOQ (T45G-G276T) gene polymorphisms are associated with markers for metabolic syndrome
Authors: Ortega Fred Luque , Camberos Alejandra Martínez , Arredondo Martín Irigoyen , Magallanes Noemí García , Meraz Eliakym Arámbula
Published: November 2023

Background and aims

There is a link between genetics with metabolic balance and adiposity homeostasis on metabolic syndrome (MetS). Polymorphism in adipokine genes such as leptin and adiponectin may play an important role in its development. This study aimed to determine the association of the individual and general components of MetS with genetic alterations in LEP (rs7799039 and rs2167270) and ADIPOQ (rs1501299 and rs2241766) genes in the Mexican population.

Methods and results

The polymorphisms of the LEP gene rs7799039 and rs2167270, together with rs1501299 and rs2241766 polymorphisms of the ADIPOQ gene were genotyped using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) on 328 individuals (n = 131 MetS). The rs7799039 under the recessive inheritance model was found to be associated with increased risk of MetS (OR = 2.16, 95% CI = 1.06–4.37), dyslipidemia (OR = 7.97, 95% CI = 2.17–29.36), low HDL (OR = 7.01, 95% CI = 1.65–29.71) and hypertension (OR = 13.02, 95% CI = 1.76–96.44); the heterozygote demonstrate a protective effect on MetS (OR = 0.48, 95% CI = 0.28–0.88) and diabetes (OR = 0.09, 95% CI = 0.02–0.53) under the over the dominant model. Haplotype analysis showed linkage disequilibrium between the SNPs of ADIPOQ rs1501299/rs2241766, and their association as risk factors for low HDL and hypertension.

Conclusion

The association of rs7799039 with the presence of MetS, suggests a risk factor for the development of dyslipidemia, as well as its heterozygous as a protective factor for DM. There is a linkage disequilibrium between the SNPs of ADIPOQ.
Evaluation of the effectiveness regarding the participation of pharmacists in perioperative blood glucose management via the iGMS: a pilot RCT
Authors: Song Jinfang , Pan Xiaojun , Chen Ya , Ding Yongjuan , Li Xia
Published: November 2023

Background

Excellent blood glucose management is a key guarantee for successful progress of surgery. However, the impact of clinical pharmacists on blood glucose management of perioperative patients needs to be further investigated. To investigate the effectiveness regarding the participation of pharmacists in blood glucose management via the informatized glucose management system (iGMS) on perioperative patients with type 2 diabetes mellitus (T2DM).

Methods

The working mode of clinical pharmacists participating in blood glucose management of perioperative patients with diabetes was constructed. A total of 300 patients with T2DM who underwent elective surgery were recruited and divided into a clinical pharmacist management group (intervention group) of 150 patients (94 men and 56 women; mean age: 44.38 ± 14.03 years) and a control group of 150 patients (101 men and 49 women; mean age: 47.85 ± 12.26 years) between September 2019 to April 2020. The outcomes of perioperative blood glucose management, and healthcare indicators such as preoperative waiting time, total hospitalization time, postoperative infection rate and other indicators were analyzed statistically between the two groups.

Result

In the blood glucose management team of the whole hospital, the physicians, clinical pharmacists and nurses of blood glucose management in endocrinology department were the core members, and were responsible for perioperative blood glucose management of the participants in the intervention group. All subjects had lower blood glucose after 3 days of management compared to the time of admission, and blood glucose was significantly lower in the intervention group compared to the control group (P < 0.05). As compared with the control group, subjects in intervention group demonstrated significant differences in outcome measures. The relevant parameters included preoperative blood glucose compliance rate (60.67% vs. 35.33%, P<0.05), preoperative waiting time [(5.27 ± 3.34) vs. (7.45 ± 4.38), P<0.05], length of hospitalization [(11.11 ± 4.56) vs. (14.87 ± 5.39), P<0.05], incidence of hypoglycemia (8.67% vs. 18.00%, P<0.05), incidence of hyperglycemia (32.00% vs. 62.67%, P<0.05) and postoperative infection rate (18.00% vs. 24.67%, P > 0.05).

Conclusion

The involvement of clinical pharmacists in blood glucose management utilizing the iGMS can control the blood glucose level of patients with T2DM in the perioperative period more stably and effectively, thereby leading to an improvement in the quality of healthcare.
EFL learners’ boredom coping strategies: the role of teacher-student rapport and support
Authors: Zhang Yanbo
Published: November 2023

Background

A significant issue in the language education context is examining the coping strategies that learners apply to combat boredom in the class environment. As a significant contextual element affecting different dimensions of learners’ acquisition, teacher support in general education has been extensively studied but widely neglected in the English as a Foreign Language (EFL) setting. Also, having a relationship with a teacher can help a learner cope better with school challenges as the teacher can act as a reference for the learner.

Methods

To this end, 268 EFL learners participated to fill out the three scales namely, Teacher Support, Teacher-Student Rapport (T-SR), and learners’ Boredom Coping Strategies (BCS).

Results

Using multiple regressions, the results revealed that there are constructive links between these concepts as they affect learners’ BCS, and both T-SR and teacher support were predictors of learners’ BCS while the better predictor was teacher support.

Conclusions

As a result, it can be assumed that these two elements can enhance the students’ BCS in language acquisition which ends in declining boredom. Additionally, this research may have further implications for the team members of language teaching in academic environments.
Molecular and functional profiling of chemotolerant cells unveils nucleoside metabolism-dependent vulnerabilities in medulloblastoma
Authors: Mariotto Elena , Rampazzo Elena , Bortolozzi Roberta , Rruga Fatlum , Zeni Ilaria , Manfreda Lorenzo , Marchioro Chiara , Canton Martina , Cani Alice , Magni Ruben , Luchini Alessandra , Bresolin Silvia , Viola Giampietro , Persano Luca
Published: November 2023

Chemotherapy resistance is considered one of the main causes of tumor relapse, still challenging researchers for the identification of the molecular mechanisms sustaining its emergence. Here, we setup and characterized chemotherapy-resistant models of Medulloblastoma (MB), one of the most lethal pediatric brain tumors, to uncover targetable vulnerabilities associated to their resistant phenotype. Integration of proteomic, transcriptomic and kinomic data revealed a significant deregulation of several pathways in resistant MB cells, converging to cell metabolism, RNA/protein homeostasis, and immune response, eventually impacting on patient outcome. Moreover, resistant MB cell response to a large library of compounds through a high-throughput screening (HTS), highlighted nucleoside metabolism as a relevant vulnerability of chemotolerant cells, with peculiar antimetabolites demonstrating increased efficacy against them and even synergism with conventional chemotherapeutics. Our results suggest that drug-resistant cells significantly rewire multiple cellular processes, allowing their adaptation to a chemotoxic environment, nevertheless exposing alternative actionable susceptibilities for their specific targeting.
Prolonged use of neuromuscular blocking agents is associated with increased long-term mortality in mechanically ventilated medical ICU patients: a retrospective cohort study
Authors: Lin Chun , Chao Wen-Cheng , Pai Kai-Chih , Yang Tsung-Ying , Wu Chieh-Liang , Chan Ming-Cheng
Published: November 2023

Background

Neuromuscular blockade agents (NMBAs) can be used to facilitate mechanical ventilation in critically ill patients. Accumulating evidence has shown that NMBAs may be associated with intensive care unit (ICU)-acquired weakness and poor outcomes. However, the long-term impact of NMBAs on mortality is still unclear.

Methods

We conducted a retrospective analysis using the 2015–2019 critical care databases at Taichung Veterans General Hospital, a referral center in central Taiwan, as well as the Taiwan nationwide death registry profile.

Results

A total of 5709 ventilated patients were eligible for further analysis, with 63.8% of them were male. The mean age of enrolled subjects was 67.8 ± 15.8 years, and the one-year mortality was 48.3% (2755/5709). Compared with the survivors, the non-survivors had a higher age (70.4 ± 14.9 vs 65.4 ± 16.3, p < 0.001), Acute Physiology and Chronic Health Evaluation II score (28.0 ± 6.2 vs 24.7 ± 6.5, p < 0.001), a longer duration of ventilator use (12.6 ± 10.6 days vs 7.8 ± 8.5 days, p < 0.001), and were more likely to receive NMBAs for longer than 48 h (11.1% vs 7.8%, p < 0.001). After adjusting for age, sex, and relevant covariates, the use of NMBAs for longer than 48 h was found to be independently associated with an increased risk of mortality (adjusted HR: 1.261; 95% CI: 1.07–1.486). The analysis of effect modification revealed that this association was tended to be strong in patients with a Charlson Comorbidity Index of 3 or higher.

Conclusions

Our study demonstrated that prolonged use of NMBAs was associated with an increased risk of long-term mortality in critically ill patients requiring mechanical ventilation. Further studies are needed to validate our findings.
MicroServices-driven enterprise architecture model for infrastructure optimization
Authors: Abd-Elwahab A. M. , Mohamed A. G. , Shaaban E. M.
Published: November 2023

Enterprise architecture (EA) is a discipline that is becoming increasingly important for businesses that are undergoing digital transformation. EA encompasses the practice of designing and managing the entire architecture of an organization, including its business processes, information systems, and technology infrastructure. In this paper, we will explore the main objectives of EA in digital transformation and the ways in which EA can help businesses achieve their digital transformation goals. Enterprise architects can use MicroServices technology to enable digital transformation by designing the MicroServices architecture, establishing best practices and standards, supporting tools such as DevOps, aligning with the enterprise's cloud strategy, and enabling data integration. Decision makers can use enterprise architecture with MicroServices to make digital transformation by leveraging the benefits of MicroServices architecture to achieve their digital transformation goals.
A literature review of the maxillary sinus with special emphasis on its anatomy and odontogenic diseases associated with it
Authors: Somayaji Krishnaraj , Muliya Vidya Saraswathi , KG Mohandas Rao , Malladi Ujwal Kumar , Nayak Satheesha B.
Published: November 2023

Maxillary air sinus (MS) is the largest and clinically most important air sinus because of its anatomical relationship with the nasal cavity and especially with teeth of the upper jaw. Periapical dental infection frequently spreads to the maxillary sinus leading to its secondary infection. The occurrence of maxillary sinusitis due to the odontogenic causes is one of the common clinical conditions which is frequently encountered by the endodontists. While handling such cases, the gross anatomy and structure of MS are visualized using various radiological images. However, most of the time, it is challenging for dentists to understand the MS due to its complicated morphology. Keeping this in mind, this literature review is done to comprehensively compile the details on MS from anatomy, radiology, and endodontic importance point of view. The articles were selected from databases like PubMed, Scopus, Embase, and Google Scholar using the keywords “maxillary sinus,” “maxillary sinusitis,” “Endo antral syndrome,” “periapical surgery,” and “odontogenic infections.” In addition, a literature survey was also done using phrases like “roots extending into maxillary sinus,” “foreign bodies in maxillary sinus,” etc. Anatomical variation of sinus could be of clinical importance and the knowledge about the same could come in handy in treatment planning of upper teeth. Extruded materials from the root of a tooth into the sinus can make it prone to infection. The dentist should carefully evaluate the root of a tooth during root canal treatment.
Beyond the cold baths: contemporary applications of cold-water immersion in the treatment of clinical depression and anxiety
Authors: Carona Carlos , Marques Sandra
Published: November 2023

Cold-water immersion (e.g. adapted cold showers, partial or whole-body immersion, cold swimming) are nowadays increasingly being used as an adjunctive procedure to enhance the effects of primary treatment of various clinical conditions, including depressive and anxiety disorders. This brief article reviews the evidence regarding the beneficial effects of cold-water immersion on clinical depression and anxiety and outlines potential therapeutic mechanisms underlying the intervention. Promising avenues for future research and best practice recommendations are also discussed to improve the clinical effectiveness of cold-water immersion.
A Case Report of Percutaneous Right Ventricular Assist Device Utilization After Cesarean Delivery in a Patient With Severe Pulmonary Arterial Hypertension
Authors: Thomas Caroline , Tobes Daniel , Trela Kristin , Montes Mariana , Cuppini Candice , Petty Kyle , Saini Gurjit , Perdigao Joana , Song Tae , Dalton Allison , Tung Avery
Published: November 2023

Physiologic changes of pregnancy are poorly tolerated in patients with pulmonary arterial hypertension (PAH), and peripartum maternal mortality is high. We present a case of a 31-year-old G3P0020 patient at 35 weeks’ gestation with severe World Health Organization group I PAH who underwent cesarean delivery followed by percutaneous right ventricular assist device placement. Risks and benefits of the mode of delivery, neuraxial versus general anesthesia, and mechanical circulatory support are reviewed.
The genome sequence of the Chestnut, Conistra vaccinii (Linnaeus, 1761)
Authors: Lees David C. ,   Natural History Museum Genome Acquisition Lab,   Darwin Tree of Life Barcoding collective,   Wellcome Sanger Institute Tree of Life programme,   Wellcome Sanger Institute Scientific Operations: DNA Pipelines collective,   Tree of Life Core Informatics collective,   Darwin Tree of Life Consortium
Published: November 2023

We present a genome assembly from an individual male Conistra vaccinii (the Chestnut; Arthropoda; None; Lepidoptera; Noctuidae). The genome sequence is 720.8 megabases in span. Most of the assembly is scaffolded into 31 chromosomal pseudomolecules, including the Z sex chromosome. The mitochondrial genome has also been assembled and is 15.44 kilobases in length. Gene annotation of this assembly on Ensembl identified 13,109 protein coding genes.
Predictive Maintenance System for Rotating Machinery Onboard Ships for Detecting Performance Degradation
Authors: Jayaswal Bharat , Agrawal Smita S , Jain Swati , Singh Ravi , Kashyap Kashyap , Chauhan Prakrut
Published: November 2023

Maintenance of rotating machinery is crucial for extending the lifespan and increasing the reliability of equipment onboard ships. Presently, breakdown and preventive methodologies are used for the maintenance of equipment. Further, dataloggers collect critical machinery parameters, and parameter data is used for real-time parameter monitoring. The availability of such extensive monitoring data has also led to the adoption predictive maintenance methodologies in the industry, wherein machine learning-based analysis of recorded data is used to predict impending defects and prompt required maintenance. In this paper, we propose a predictive maintenance system that records data through a network of sensors installed over multiple electrical motor pump sets onboard the ship and uses statistical analysis to detect equipment degradation. Our system has been deployed onboard a ship to undertake real-time predictive maintenance of electrical motor pump sets used in firemain, AC plants, stabilizers, steering pumps and other auxiliary engine room machinery.
Confidential Training and Inference using Secure Multi-Party Computation on Vertically Partitioned Dataset
Authors: Tiwari Kapil , Sarkar Nirmalya , George Jossy P
Published: November 2023

Digitalization across all spheres of life has given rise to issues like data ownership and privacy. Privacy-Preserving Machine Learning (PPML), an active area of research, aims to preserve privacy for machine learning (ML) stakeholders like data owners, ML model owners, and inference users. The Paper, CoTraIn-VPD, proposes private ML inference and training of models for vertically partitioned datasets with Secure Multi-Party Computation (SPMC) and Differential Privacy (DP) techniques. The proposed approach addresses complications linked with the privacy of various ML stakeholders dealing with vertically portioned datasets. This technique is implemented in Python using open-source libraries such as SyMPC (SMPC functions), PyDP (DP aggregations), and CrypTen (secure and private training). The paper uses information privacy measures, including mutual information and KL-Divergence, across different privacy budgets to empirically demonstrate privacy preservation with high ML accuracy and minimal performance cost.
Design of a Drag-reducing System for Smart Bar Conveying Chain Plate
Authors: Pan Jiangyi , Jianjun Yang  , Wenjuan Lu
Published: November 2023

This paper presents a solution to the issue of high frictional resistance between the chain plate and guide rail in cigarette conveying systems, which can result in chain plate failure. The proposed solution is an intelligent drag reduction system that incorporates lubrication and automatic dust removal. The system includes a conveyor chain plate, supporting roller assembly, air knife dust removal assembly, chain plate lubrication assembly, and controller. The controller manages the dust removal assembly's air source output and the lubrication of the chain plate assembly through the opening and closing of an electromagnetic valve, which controls the oil output to decrease resistance. Experimental testing of the system shows that it effectively reduces the chain plate's frictional resistance in the cigarette conveying line, resulting in improved system efficiency.
Ensemble Hybrid Model for COVID-19 Sentiment Analysis with Cuckoo Search Optimization Algorithm
Authors: Jain Vipin , Kashyap Kanchan Lata
Published: November 2023

The COVID-19 pandemic has caused anxiety and fear worldwide, affecting people's physical and mental health. This research work proposes a sentiment analysis approach to better understand the public's perception of COVID-19 in India. Two datasets are created by collecting tweets regarding COVID-19 in India. Pre-processing and analysis of datasets are performed by using natural language processing (NLP) techniques. Various features are extracted from collected tweets using three-word embeddings GloVe, fastText, Elmo. The optimal features are selected by cuckoo search optimization algorithm. Finally, the proposed hybrid model of Gated Recurrent Unit (GRU) and Bidirectional Long Short-Term Memory (BiLSTM) is used to categorize the tweets into three sentiment categories. Proposed model achieved 94.44% accuracy, 90.34% precision, 88.53% sensitivity, and 89.53% F1 score. It significantly improved over previous approaches, which achieved 80% accuracy.
Multilingual Code-Mixed Sentiment Analysis in Hate Speech
Authors: Ranjan Tulika , Singh Anish , Kumari Rina , Swain Sujata , Bandyopadhyay Anjan , Parida Ajaya Kumar
Published: November 2023

Sentiment analysis discovers the emotion expressed in a text. It helps in analyzing the product reviews, customer feedback and survey responses. Researchers have developed various algorithms for this purpose, however, they have majorly focused only on the sentiment analysis in English language. Although, few works are available for Hindi and multilingual sentiment analysis, however, these works are not efficient enough to perform sentiment analysis in code-mixed languages. To overcome the limitation of the existing works, this paper presents a multilingual code-mixed language model which identifies the sentiments of the hate speech dataset extracted from Twitter. As the hate speech dataset with sentiment labels are not available, we first collect the data from Twitter. After that we label the data using a transformer-based pretrained sentiment analysis model trained on a large corpus of tweets in multiple languages. We pass our collected data as test data to this model and predict the sentiment labels. Now, we train six different machine learning models to perform our own task i.e sentiment analysis for multilingual code-mixed hate speech dataset. The machine learning models perform well across multiple languages and also code-mixed languages. In future, it can be easily adapted to different classification tasks based on code-mixed languages. The results yield that hate speech invokes negative sentiment whereas non-hate speech reflects either positive or neutral sentiment.
AI-Assisted Chinese Language Teaching System in Distributed Sensor Networks
Authors: Shan Huafeng
Published: November 2023

The Chinese learning system gained enormous importance to support the population of China with recent technologies. The AI and ML-assisted classes are useful for learners. However, it can cut down the employment of teachers. Various planning and act was passed to reform the Chinese education system with artificial intelligence and machine language. On the other hand, this education process is interesting, customized, and unsupervised based. It was observed that the human touch study process is more satisfying and clears doubts easily. The key object of data gathering sensor-based network is accumulating all the data from the nodes and sending those sensed data to the base station. These nodes are basically working while focusing on one thought: all the nodes present in the sensor-based system are well aware of all the other nodes currently working in the same network and transmitting data in the base station. Although AI comes with a few challenges like lack of resources, training, and various security issues, if these are overcome with proper strategies, AI can be the equipment to reign in the 21${}^{st}$ century. Additionally, LLMs and NLP modeling are described in the results that helped to understand the use of different models. Moreover, the Benefits of LLMs and NLP for Chinese language training are discussed in the study.
Personalized Art Work Recommendation System and Methods Based on User Interest Characteristics and Emotional Preferences
Authors: Li Huihong
Published: November 2023

To familiarize users with their interests and hobbies through online data collection, and improve their experience when browsing art works, research based on K-means algorithm has received widespread attention. However, with the explosive growth of various types of art works, it is difficult to estimate the K value of the K-means algorithm when processing these data. To solve this problem, this research predicts the user behavior of Wink dataset based on K-means algorithm, introduces regularization specified process and emotional precision, and generates fusion algorithm. The study first proposes the concept of similar users and calculates the Pearson correlation coefficient between them to determine their similarity; Then several regularization terms are added to the user group, and the prediction results are obtained by changing the parameters; Further screening of art works clustering categories is to address the issue of slow user startup. Finally, the algorithm studied will be applied to the Wink dataset and the prediction accuracy of the particle swarm optimization algorithm will be tested and compared with the fusion algorithm. A total of 400 experiments are conducted, and the fusion algorithm achieve a prediction accuracy of 392 times, with an accuracy rate of 98.0%; The accuracy of particle swarm optimization algorithm is close to that of fusion algorithm, at 88.2%. The experimental results show that the algorithm model proposed in the study can effectively map the relationship between user interest features, emotional factors, and personalized art recommendation, thereby providing users with a good viewing experience.
Mapping Learner's Query to Learning Objects using Topic Modeling and Machine Learning Techniques
Authors: Sengupta Souvik , Pal Saurabh , Dutta Pramanik Pijush Kanti
Published: November 2023

Inquiry-based learning supports the independent knowledge development of the learner in an e-learning environment. It is crucial for the learner to obtain the appropriate Learning Object (LO) for the intended query. Mapping a learner's query to the right LO is a challenging task, as keyword-based searching on the topics or content does not guarantee the best result for various reasons. A query that apparently connects a topic may also implicitly refer to multiple other topics. Besides, the content of an LO with the same topic name often varies over different portals. Therefore, there is always a need for a method to automatically identify the latent topics of the query and then find the most relevant LO that covers the query. This paper aims to build a recommender system that maps a given input query to a suitable LO based on the most appropriate matching of learning contents. The proposed work employs an amalgamation of different supervised and unsupervised methods of natural language processing and machine learning. The machine learning model is trained on a handcrafted dataset to map queries into predefined topics. The proposed algorithm also leverages a dynamic topic modeling technique on learning content collected from three popular e-learning portals and uses a similarity score to map the learner's (user) query to the most appropriate LO.
A Statistical Analysis of Sentiment over Different Social Platforms on Drug Usage across High, Middle and Low-Income Countries
Authors: Chhabra Anureet , Sharma Akash , Chhabra Kunal , Chhabra Amit
Published: November 2023

Social media serves as a platform for sharing information and connecting with others on various subjects, including healthcare and drugs. Analyzing drug sentiment from various social media like Twitter, reddit, quora etc are crucial for monitoring drug safety, identifying adverse reactions, and providing an early warning system for potential safety concerns, benefiting healthcare organizations and governments. This paper aims to study the opinions of people from all over the world by analyzing their messages, posts on social media. For this study 39,069 drug related message corpus were fetched making a comparison between the high income countries, and middle income and low income countries on the basis of drug consumption from 2021 to 2023. The dataset used for the study consisted of 41.63% text-corpus from high income countries out of which on an average from 2021 to 2023, 40.2% was found to have a positive sentiment. Whereas 34.65% of text-corpus are from middle-income countries out of which on an average 26.4% of was of a positive sentiment and 23.70% text-corpus are from low income countries with 23.6% having a positive sentiment. Furthermore, the primary factor for having such differences from people’s sentiment on drug consumption from high to low income countries includes Cultural and Social Norms, Legalization, availability etc therefore, In high-income countries, drug use is more socially accepted than in other regions. This proposed study gives an insight into people’s opinion on various drugs from different countries and regions. The results of this study attempted to understand how the public is responding to different types of information and to identify potential misinformation which can be used to formulate policies for existing and future drug prevention campaigns in order to improve public health and promote public education.
V-Learning—A Simple, Efficient, Decentralized Algorithm for Multiagent Reinforcement Learning
Authors: Jin Chi , Liu Qinghua , Wang Yuanhao , Yu Tiancheng
Published: November 2023

A major challenge of multiagent reinforcement learning (MARL) is the curse of multiagents, where the size of the joint action space scales exponentially with the number of agents. This remains to be a bottleneck for designing efficient MARL algorithms, even in a basic scenario with finitely many states and actions. This paper resolves this challenge for the model of episodic Markov games. We design a new class of fully decentralized algorithms—V-learning, which provably learns Nash equilibria (in the two-player zero-sum setting), correlated equilibria, and coarse correlated equilibria (in the multiplayer general-sum setting) in a number of samples that only scales with [Formula: see text], where Ai is the number of actions for the ith player. This is in sharp contrast to the size of the joint action space, which is [Formula: see text]. V-learning (in its basic form) is a new class of single-agent reinforcement learning (RL) algorithms that convert any adversarial bandit algorithm with suitable regret guarantees into an RL algorithm. Similar to the classical Q-learning algorithm, it performs incremental updates to the value functions. Different from Q-learning, it only maintains the estimates of V-values instead of Q-values. This key difference allows V-learning to achieve the claimed guarantees in the MARL setting by simply letting all agents run V-learning independently.

Funding: This work was partially supported by Office of Naval Research Grant N00014-22-1-2253.
A rare case of paraneoplastic Guillain-Barré syndrome in a patient with endometrial cancer
Authors: Farook Asif Mohamed , Priyankara Dilshan , Aluwihare Chamali , Mendis Anthony
Published: November 2023

Introduction: Guillain-Barré syndrome is an acute, inflammatory polyradiculoneuropathy of autoimmune aetiology. It is a rare disease seen in 1 in 100,000 person-years. Up to 20% of those affected develop severe disability; mortality in Guillain-Barré syndrome is 5%. Guillain-Barré, associated with many malignancies as a paraneoplastic phenomenon, has been reported – especially in haematological malignancies such as lymphoma and leukaemia. Solid tumours associated with paraneoplastic Guillain-Barré syndrome are breast and lung cancers. The association between paraneoplastic Guillain-Barré syndrome and gynaecological malignancies are rare, and only a handful of cases have been previously reported in gynaecological cancers. Case description: We discuss a 65-year-old Sri Lankan female patient diagnosed with metastatic endometrial carcinoma who presented with paraneoplastic Guillain-Barré syndrome. The patient was treated appropriately and eventually recovered from her condition. Conclusion: Paraneoplastic Guillain-Barré syndrome is a rare phenomenon that clinicians can easily miss, and it has rarely been described in gynaecological cancers. Our patient was diagnosed with this rare phenomenon. The timely recognition and prompt treatment of this potentially life-threatening condition with multiple complications is essential in managing patients with malignancies and neuropathy. Further studies on paraneoplastic Guillain-Barré syndrome are needed as cases may be underreported.
Long-term tolerance and efficacy of siltuximab (anti-IL-6) in a young adult with idiopathic multicentric Castleman disease during COVID-19
Authors: Bedier Helbies , Isnard Stéphane , Maedler-Kron Chelsea , Routy Jean-Pierre
Published: November 2023

Background: Castleman disease (CD) is a rare lymphoproliferative disorder with various subtypes, including the HHV-8-negative/idiopathic multicentric CD (iMCD). The diagnosis of iMCD remains challenging due to its non-specific presentation, in the form of generalised lymphadenopathies and inflammation. Two clinical presentations have been recently defined: a severe form iMCD-TAFRO and a milder form of iMCD not otherwise specified (iMCD-NOS). identification of interleukin-6 (IL-6) as a major culprit of inflammatory symptoms led to the development of anti-IL-6 therapies, with siltuximab being the approved first-line treatment. Case description: A 16-year-old male presented with recurrent fever, night sweats and several other non-specific symptoms. After extensive evaluations, an excisional lymph node biopsy confirmed the iMCD-NOS diagnosis. The patient received high-dose steroid therapy followed by siltuximab for four years. This treatment was well tolerated with only mild neutropenia not leading to dose adjustment. On siltuximab, the patient developed two mild COVID-19 episodes. His response to siltuximab remained effective throughout four years. Discussion: The absence of biomarker or causal agent identification poses a diagnostic challenge requiring lymph node histopathology for a definitive diagnosis of iMCD. Anti-IL 6 (siltuximab) is the recommended frontline therapy, suppressing inflammation and halting disease progression. Intravenous administration every 3 to 6 weeks can impact patient quality of life, prompting further research for alternative treatments. High-dose steroids, rituximab, cyclosporine, tacrolimus, lenalidomide or combined chemotherapy such as rituximab-bortezomib-dexamethasone are among the considered options according to disease severity. Conclusion: Overall, long-term siltuximab effectively controlled iMCD symptoms and was well tolerated by this young adult, who endured two mild COVID-19 episodes.