bluuebunny/crossref_metadata_2025_split huggingface dataset:
Essential Pharmaceutical Care Services for Optimizing Medication Management Amongst Hospitalized Elderly Patients: A Systematic Review
Authors: Syed Jehath , Kaur Bavneet , Ramesh Madhan , Pereira Prathiba , Chalasani Sri Harsha 
Published: November 2023

Abstract
Because the elderly are more likely to experience adverse drug reactions than the younger population, the American Society of Consultant Pharmacists (ASCP) emphasizes the importance of pharmacists in managing medications in this age group. Clinical pharmacists in geriatrics, like other medical disciplines, strive to promote rational and safe use of medicines. The focus is on dose adjustment, minimizing polypharmacy, identifying and preventing adverse drug reactions, potentially inappropriate medications and improving compliance. However, there is no standard in the developing countries for what is required of a clinical pharmacist to provide comprehensive geriatric care. Therefore, this review critically evaluates studies that report the various pharmaceutical services provided to optimise the elderly care during their hospital stay.
Following the PRISMA guidelines, we will conduct a systematic review that will include two databases: PubMed and Scopus. We will summarise the available evidence on pharmaceutical care services for optimizing drug therapy in hospitalized elderly patients.
A photorespiratory cycle that regulates plant responses to atmospheric CO2
Authors: Bloom Arnold 
Published: November 2023

Abstract

Rubisco (ribulose-1,5-bisphosphate carboxylase-oxygenase), the most prevalent protein on the planet 1,2, catalyzes two competing chemical reactions. One reaction is the carboxylation of ribulose 1,5-bisphosphate (RuBP), which initiates plant carbohydrate synthesis. The other is the oxygenation of RuBP, which initiates photorespiration 3. The common assumption is that photorespiration is a futile cycle that dissipates more than 25% of a plant’s energy as waste heat 4–6, but inhibiting photorespiration decreases shoot protein synthesis 7–11. Here is evidence for a previously unrecognized photorespiratory cycle in which rubisco converts RuBP into pyruvate, malic enzyme carboxylates pyruvate into malate, and malate dehydrogenase oxidizes malate, generating reductants that convert nitrate into amino acids (Fig. 1). This cycle becomes prominent only when rubisco or malic enzyme are associated with manganese, but prior experiments replaced the manganese bound to these enzymes with magnesium 3,12,13. The proposed cycle coordinates photorespiration with several other processes including C3 carbon fixation, pentose phosphate shunt, malate valve, and nitrogen metabolism. It thereby balances plant organic carbon and nitrogen as atmospheric CO2 fluctuates daily, seasonally, and over millennia 14. This carbon:nitrogen homeostasis improves photosynthetic efficiency 3 and explains why C3 species, plants that photorespire at substantial rates, remain dominant in most habitats.
Combined Unsupervised Machine Learning and clinical cohort for phenotyping complex diseases with its application to Amyotrophic lateral sclerosis
Authors: Fan Jing , Yang Xunzhe , Shen Dongchao , Cui Liying , Liu Mingsheng 
Published: November 2023

Abstract
Amyotrophic lateral sclerosis (ALS) is a highly heterogeneous disease. Identifying subtypes of ALS to better predict prognosis with different methods is essential in clinical practice. Traditional cluster methods are limited by data and computation, and are hard to indicate heterogeneity and predict the prognosis of ALS. This study aims to develop a new classification system for ALS to predict prognosis adopting a data-driven approach. This was a single-center retrospective study based on an independent cohort of patients diagnosed with ALS recruited by Peking union medical college hospital (PUMCH) from 2014 to 2020. The mean follow-up time was 23.3±16.9 months. One thousand and two hundred fifty-four patients were recruited, and 303 variables were selected at baseline. We applied machine learning algorithms to train and test the performance of different hyperparameters. Fifty-nine baseline variables were included and 1166 patients (mean [SD] age, 53.3[10.7] years, 518 [55.5%] male patients; mean [SD] ALSFRS-R, 38.4 [6.3]), with <50 % missing data were identified and were used as input for the ML algorithm. K-Means Model classified four phenogroups (phenogroup 0= 245, phenogroup 1= 428, phenogroup 2=235, phenogroup 3=258) whose outcome are different from each other (hazard ratio, 1.12; 95% CI, 1.01-1.25; P < 0.001). In particular, there is a significant difference between phenogroup 0 and phenogroup 3 regarding decreased ALSFRS-R, swallowing function, decrease in BMI, and prognosis. Phenogroup 1 and phenogroup 2 have a moderate prognosis, but their characteristics are significantly different in terms of sex ratio, mean age, weight, and complications.
Data-driven automated approaches could develop a new classification system for ALS to precisely predict the prognosis
Trial Registration: Chinese Clinical Trial Registry, ChiCTR-IPR-15007385
A rare case of adult-onset spastic paraparesis in association with Klinefelter syndrome
Authors: Adams Louise , De Bleecker Jan 
Published: November 2023

Abstract
Report

The rare association of Klinefelter syndrome and the clinical presentation of a late onset chronic progressive spastic paresis.

Clinical presentation and genetics

An infertile 61-year-old man with late adult onset of gait problems, deep muscle pain and bladder problems. He presented for the first time, years after onset with a spastic paraparesis with high arched feet. His mother also had gait problems and high arched feet. Further information of the mother is lacking. After thorough investigation, an additional X chromosome was found, where after the diagnosis of Klinefelter syndrome was made. Other acquired and genetic causes for spastic paraparesis or hereditary motor neuropathy are excluded.

Conclusion

This rare case, together with two other literature reports, suggests that Klinefelter syndrome can be associated with spastic paraparesis, besides the other various neuropsychiatric symptoms that are more commonly described [1,2].
A Hybrid Deep Learning Model for Short-Term Hydropower Generation Prediction Incorporating Hydrometeorological Factors
Authors: Peng Wang , Jiang Zhiqiang , Yao Huaming , Zhang Li , Yu Jianhua 
Published: November 2023

Abstract
Hydropower is a clean and renewable source of energy, reliable forecasts of hydropower generation are critical for reservoir management and efficient use of water resources. In this study, a Double Attention mechanism-Convolutional Neural Network-Bidirectional Gated Recurrent Unit(DAC-BiGRU) hybrid deep learning model considering hydrometeorological factors is proposed for predicting short-term hydropower generation. DAC-BIGRU first extracts the local features of the input data using a 1-dimensional CNN and weights the features using an attentional mechanism instead of a pooling layer. Then passes features to the BiGRU layer for time series modelling. Finally performs the attentional mechanism weighting again and maps the results to the final output via a dense layer. The Qiamusa and Aertashi hydropower stations on the mainstem of the Yarkant River in Northwest China are used as the study object for cross-training and validation. The Pearson Correlation Coefficient and Maximum mutual Information Coefficient were used to determine hydropower generation, steamflow and soil temperature for the past 7 days as input features.Through rigorous and reasonable evaluation, the results demonstrate that: Root Mean Squared Error (RMSE) of DAC-BiGRU on the test set decreased by 8.8% on average compared with CNN-LSTM and CNN-GRU. DAC-BiGRU model performance was significantly better than CNN-LSTM, CNN-GRU, Long Short-Term Memory (LSTM) and Support Vector Machine (SVM). In addation, relative error of DAC-BiGRU mainly occurred from October to March, RMSE of the DAC-BiGRU decreased by about 3% after adding streamflow and soil temperature as factors. The prediction performance of DAC-BiGRU for the next 3–7 days began to decline significantly.
Qualitative Study of Public Mental Health and Lifestyle Behaviours in Malaysia During the COVID-19 Pandemic
Authors: Yi Ng Jia , Lin Mei-Hua , Yong Min Hooi 
Published: November 2023

Abstract

Our objective was to explore the Malaysian public’s experience during the lockdown with a focus on mental health and lifestyle behaviour factors. Fifteen Malaysians (10 females, Mage = 37.64, SD = 1.64, range = 20-68) were interviewed about their experience on what were affecting their mental health and lifestyle behaviours. Four main categories were identified: factors affecting (1) mental health and (2) lifestyle behaviours during the pandemic lockdown, and (3) the consequences, and (4) coping strategies during the pandemic. Participants revealed largely negative consequences that affected their mental health and lifestyle behaviours with the factors of deterioration emerging from the environmental to the individual level. Most participants distracted themselves as a form of coping strategy while engaged minimally in other coping behaviours. Our findings showed the complexity underlying the maintenance of mental health and lifestyle behaviours during the pandemic across the individual level to environmental, which affects the design of effective public policies and interventions.
Investigating Rectification in Gap Junctions within the Antennal Lobe of the Insect Neuropil: A Computational Model
Authors: Chowdhury Shubhajit Roy , G Dileep , Joseph Joby 
Published: November 2023

Abstract
In insects, the antennal lobe (AL) serves as the primary processing center for olfactory signals, housing a complex network of neurons that analyze and integrate olfactory information. Gap junctions, an integral part of the AL neural network, have been shown to play a significant role in processing and transmitting olfactory information. However, their specific function within the AL system remains not fully understood. To bridge this knowledge gap, this study aims to investigate the role of gap junctions in the AL circuitry using experimental and computational methods. The focus is on developing a computational model of the gap junctions between local neurons and projection neurons within the AL. By employing a biologically accurate model to mimic the behavior of the AL neural network, the researchers aim to explore the impact of gap junctions on the processing and transmission of olfactory information. The study's findings highlight the critical role of gap junctions in synchronizing the activity of neurons within the AL circuitry. The computational model serves as a valuable framework for understanding the function of these junctions in the AL network and could potentially be applied to evaluate their impact on olfactory processing in other insects.
Biofabricated green synthesized hibiscus silver nanoparticles potentiates antibacterial and cytotoxicity in human lung cancer cells
Authors: Ahirwar Bharti , Ahirwar Dheeraj , Jain Ritesh , Agrawal Bhagyashri , Sahu Parvin , Sakure Kalyani , Badwaik Hemant 
Published: November 2023

Abstract
Traditional medicine has long employed the shrub Hibiscus sabdariffa to treat a variety of illnesses. The biochemical characteristics of nanoparticles of silver made using the plant extract and plant extracts of Hibiscus sabdariffa were examined in this work. According to the results, the plant extract of Hibiscus sabdariffa had a total phenolic quantity of 84.9 mg/gm and a total quantity of flavonoids of 41.50 mg/gm. The extract also showed antibacterial action against Escherichia coli and Staphylococcus aureus (75.15% scavenging activity). The nanoparticles of silver from plant extracts were stable in PBS solution for at least 30 days and had a mean size of particles of 21.22 nm. Human cancer of the lung line of cells A-549 was effectively cytotoxic and anti-inflammatory by the silver nanoparticles. Overall, the research's findings demonstrate the fascinating biological activity of the nanoparticles of silver made from the extract of the Hibiscus sabdariffa plant. To assess these compounds' potential as medicines, more research is required.
An novel approach for pressure demand control in electro-hydraulic brake-by-wire system
Authors: Duan Wei , Hu Junyi , Wang Shixiong , Zhang Shuya 
Published: November 2023

Abstract

As the electrification of vehicles continues to become more widespread, the electric brake system is also continuously improving. This has led to higher demands on the capabilities and performance of active braking and regenerative braking in the field of vehicle dynamics control. Therefore, this paper proposes a novel pressure demand control approach for the electro-hydraulic brake-by-wire system, aimed at accurately and swiftly tracking the target pressure. Firstly, we establish a simplified model of the system and use a second-order function to approximate the pressure-position relationship. The sliding mode control is employed to convert the desired pressure into the required piston position. Then, the kinematic relationship is used to convert it into the motor rotation angle. Moreover, we apply a proportional-integral controller to adjust the motor rotation angle, and further fine-tune the controller parameters using a particle swarm optimization algorithm. Finally, a joint simulation platform are built, and a brake test bench is established for three pressure signal tests. The experimental results demonstrate that the pressure demand control method achieves precise tracking of the target pressure, with a maximum error not exceeding 2%. Compared to other methods, this approach exhibits superior control accuracy and response characteristics.
A Chinese Named Entity Recognition Model Incorporating Recurrent Cell and Information State Recursion
Authors: Han Qingbin , Ma Jialin 
Published: November 2023

Abstract
Chinese is characterised by high syntactic complexity, chaotic annotation granularity, and slow convergence. Joint learning models can effectively improve the accuracy of Chinese Named Entity Recognition (NER), but they focus too much on local feature information and reduce the ability of long sequence feature extraction. To address the limitations of long sequence feature extraction ability, we propose a Chinese NER model called Incorporating Recurrent Cell and Information State Recursion(IRCSR-NER). The model integrates recurrent cells and information state recursion to improve the recognition ability of long entity boundaries. To solve the problem that Chinese and English have different focuses in syntactic analysis. We use the syntactic dependency approach to add lexical relationship information to sentences represented at the word level. The IRCSR-NER is applied to sequence feature extraction to improve the model efficiency and long-text feature extraction ability. The model captures contextual long-distance dependent information while focusing on local feature information. We evaluated our proposed model using two public datasets and compared it with five mainstream models. Experimental results demonstrate that our model outperforms traditional and mainstream models.
Diode LASER surgery for early stage Oral Cavity and Oropharyngeal cancer - A comparison study with conventional electrosurgery
Authors: Nakai Marianne Yumi , Tenório Lucas Ribeiro , Menezes Marcelo Benedito , Lima Lurian Rei Caetano , Gusmão Rodrigo Vasconcellos , Bertelli Antonio Augusto Tupinambá , Mercante Giuseppe , Gaino Francesca , Gonçalves Antonio José 
Published: November 2023

Abstract
Introduction:Any surgical resection of the oral cavity and pharynx could lead to serious impairment and compromise swallowing, chewing, breathing, and speaking. Early-stage tumors of the oral cavity and oropharynx are usually accessed by the transoral approach. The resections after using an electronic scalpel may create complex defects, with the raw area causing severe pain and bleeding in the postoperative period. Consequently, flap reconstruction(local flap or free flap) is usually indicated, which is also important to achieve better functional results. The Diode LASER is not a new tool for treating Head and Neck (H&N) tumors, and its usage for treating early glottic cancer is well established, but CO2 LASER has been more broadly adopted worldwide.
Objective: Evaluate the hospital length of stay and postoperative complications in transoral surgical resection of oral cavity and oropharynx early-stage malignant neoplasms, comparing Diode LASER surgery with conventional electrosurgical resection.
Method: That study is a retrospective cohort that includes all patients with early-stage malignant neoplasm of oral cavity and oropharynx treated with transoral Diode LASER surgical resection compared to patients submitted to electrosurgery conventional resection between August 2019 and August 2022 in a Head and Neck Cancer Center. The evaluated outcomes were hospital length of stay, postoperative complications, enteral feeding tube, tracheostomy, and oncologic outcomes (recurrence rate and margins).
Results: The mean hospital stay was lower in the Diode LASER group (3.2 days vs. 4.8 days / p=0.01). Postoperative complication rates were similar in both groups. None of the patients presented local or regional recurrence during the follow-up. The mean follow-up time was 23 months.
Conclusion: The Diode LASER surgery is associated with a reduction in the hospital length of stay for early-stage oral cavity and oropharynx carcinomas.
Measuring Network interdependency using Mutual Information Technique: A Case study of Power-Water Network
Authors: Garg Paras , Soni Gunjan , Yadav OM Prakash , Rathore A.P.S. 
Published: November 2023

Abstract
This paper presents a novel approach to the Dependent Network interdependencies analysis, based on the Mutual Information Technique. This is a statistical measure that quantifies the amount of information shared between two variables. In the context of networks, we can calculate the mutual information between the nodes in each network and use it as a measure of the strength of their interdependency. This Technique is useful in capturing the functional and service level interdependencies between the networks. The Mutual Information based approach is a useful analytical tool for determining the degree of mutual effect and reliance between variables in linked systems. We want to shed light on how Mutual Information might help us comprehend and analyse the interplay of critical infrastructure networks by applying this technique to the example of a hydroelectric power plant depending on a river for water supplies A case study of simulated power network used in this paper for illustration and validation of the technique.
Supporting or pushing too hard? The impact of parental support on overeducation in Poland
Authors: Krzywda-Starzyk Patrycja 
Published: November 2023

Abstract
Education's pivotal role in securing a satisfying future - especially career prospects - is hindered by a phenomenon known as overeducation, which consistently impacts a notable proportion of European degree holders. The incidence of overeducation depends greatly on one’s educational trajectory which, in turn, relies heavily on family. This study, based on data from a dedicated 2022 questionnaire, examines how parental support influences the risk of labour market mismatch in Poland. Accounting for the specificity of Polish society, it further explores how being raised in rural areas and maternal education moderate this relationship. These two factors are considered due to the notable socio-economic marginalization of rural areas on the one hand, and the profound childcare gap in Poland on the other.
The results of the regression model confirm that heightened parental support during adolescence increases the likelihood of educational attainment being aligned with job requirements in Poland. The application of moderation analysis reveals that this relationship is moderated both by a rural upbringing and the level of maternal education. While several variations emerge from the moderation models, the key finding is that the offspring of highly educated mothers from rural areas defy the general trend. In their case, increased support lowers the chance of a labour-education match.
Our findings emphasize the need to develop robust institutions in rural areas, and to empower parents to make informed educational choices for their children. Furthermore, the study prompts nuanced discussions about Poland's higher education narrative and its relevance in a dynamic job market.
Neoantigens heterogeneity as a prognostic marker in patients with resected intrahepatic cholangiocarcinoma
Authors: Lin Jianzhen , Hu Bo , Shi Yang , Wang Jiaqian , Yang Xu , Hu Weikang , Yang Xiaobo , Lu Xin , Sang Xinting , Gao Zhibo , Xi Ruibin , Zhao Haitao 
Published: November 2023

Abstract
Background
The prognostic significance of neoantigens and the understanding of neoantigen-associated heterogeneity in intrahepatic cholangiocarcinoma (iCCA) is still unclear. This study aims to investigate the prognostic role of neoantigens and their intratumor heterogeneity (ITH) in postoperative prognoses of patients with resected iCCA.
Methods
A cohort enrolled 68 iCCA patients underwent surgical resections was performed whole-exome sequencing to analyze the impact of neoantigens on postoperative survival. Immunohistochemistry for CD4 and CD8 was performed and T cells in tumor were quantified by visually counted. RNA sequencing and TCR sequencing were performed to demonstrate tumor immunogenicity and immune recognition associated with neoantigen heterogeneity.
Results
The neoantigen intratumor heterogeneity (NeoITH) metric was an independent prognostic factor, with NeoITH-low iCCA associated with improved prognosis in the discovery and the validation cohort. Immunogenetic analyses revealed that NeoITH-low iCCA harbored an increased CD8+ T cell infiltration and higher immunogenicity compared to NeoITH-high iCCA. Characterization on the TCR repertoire identified 36 iCCA-related TCR clusters which were enriched in NeoITH-low tumors. Patients identified as the high number of iCCA-related TCR clusters and NeoITH-low iCCAs had the best postoperative prognosis, and vice versa. A retrospective immunotherapy cohort confirmed that patients with NeoITH-low iCCAs had significant therapeutic advantages then patients with NeoITH-high iCCAs.
Conclusions
This study provides a novel insight into neoantigen heterogeneity for predicting postoperative survival and immunotherapeutic prognosis in iCCA patients.
Approximately half of the magnitude of ocular residual astigmatism comes from posterior corneal astigmatism in myopic patients aged 18-40 years
Authors: Lin Jian , An Dexiang , Wu Haiqian , Lu Yun , Yan Dongmei 
Published: November 2023

Abstract
To determine the main sources of ocular residual astigmatism (ORA) and the contribution of posterior corneal astigmatism (PCA) to ORA. Anterior corneal astigmatism (ACA) and PCA was obtained from Pentacam. ORA was calculated by Thibos vector analysis. Pearson correlation coefficient was used to assess relationships between variables. The contribution of PCA to ORA was evaluated by a physical method. Mean magnitude of PCA was 0.40 ± 0.15 D. Mean amount of ORA was 0.69 ± 0.33 D. There was a significant correlation between the magnitudes of PCA and ORA (r = 0.38, P < 0.001). The PCA in 171 eyes (96.61%) supplemented ORA. The mean superimposed values (SV) was 0.37 ± 0.16 D (rang 0.01 to 0.70 D). The against-the-rule PCA can not only superimpose but also counteract with-the-rule and oblique ORA. The against-the-rule ORA can be superimposed by with-the-rule, against-the-rule and oblique PCA. Of the 171 eyes, the SV of 85 eyes(49.71%) were larger than half of the magnitude of ORA. In a minority of eyes, PCA can have a negative effect on ORA and may be greater than it. The SV/ORA ratio may be used to personalize the surgical method proposed by Alpins, resulting in better outcomes.