bluuebunny/crossref_metadata_2025_split huggingface dataset:
Association between oral health status and survival time in terminally ill cancer patients
Authors: Lee Yoo Jeong , Hwang In Cheol , Choi Youn Seon , Ahn Hong Yup , Lee Eun Jeong , Kim Da Eun 
Published: May 2023

Abstract
Purpose
Patients with terminal cancer often experience various oral problems. Whether oral health status is associated with the survival of terminally ill cancer patients receiving palliative care remains unclear.
Methods
We analyzed the data of 59 Korean patients with terminal cancer receiving palliative care, including their oral health status, using a modified Korean version of the Oral Health Assessment Tool (OHAT). Patients were categorized into “Good,” “Moderate,” or “Poor” groups based on OHAT scores. The Kaplan–Meier method was used to compare the median survival time, and the prognosis between groups was estimated using Cox proportional hazard models.
Results
The most common oral symptoms observed were xerostomia (69.5%) and mucositis (17.0%). Significantly shorter survival times were observed in patients with hyperbilirubinemia, elevated creatinine levels, and no use of dentures. The “Poor” group had a shorter survival than the “Good” oral group (P = 0.010). A multivariate Cox proportional hazards analysis revealed that the “Poor” group was significantly associated with poor survival compared to the “Good” group (hazard ratio, 2.05; P = 0.047).
Conclusion
Terminally ill cancer patients with poor oral health may have a higher risk of shorter survival. Palliative care professionals should pay attention to oral health. Further research is needed to determine the effects of oral care on survival.
Monitoring of Rainwater Quality in Kandy and Peradeniya, Sri Lanka
Authors: Wijewantha H.L.S.S. , Dharaka B.D.P. , Priyantha N. , Deeyamulla M.P. 
Published: May 2023

Abstract
The composition of atmospheric deposition is a measure of air quality, an important aspect of the health of the ecosystem. Consequently, continuous monitoring of atmospheric deposition is crucial to obtain remedial measures to avoid undesirable aspects that would affect living things. In this context, the objective of this study was to determine the rainwater quality at selected locations in Kandy and Peradeniya area of Sri Lanka, namely, Kandy city, Polgolla and University of Peradeniya (UOP), and to identify possible correlations between quality parameters through statistical means. Forty (40) rainwater samples from the UOP site and seven (07) samples each from the Kandy city and Polgolla sites were collected from the 18th May 2020 to 28th April 2021. The volume weighted average (VWA) pH values of UOP, Kandy and Polgolla sites were determined to be 7.44, 7.19 and 7.19, respectively, and moreover, acid rain (pH < 5.6) occurrences were not detected during the sampling period. The VWA values of rainfall, conductivity, salinity, TDS and hardness at the UOP site were 40.12 mm, 51.93 µS cm− 1, 0.0300 ppt, 26.59 mg L− 1 and 13.55 mg L− 1, respectively. The corresponding values of the Kandy city site were 16.52 mm, 64.04 µS cm− 1, 0.0361 ppt, 30.80 mg L− 1 and 19.49 mg L− 1, respectively; and those of the Polgolla site were 33.10 mm, 53.90 µS cm− 1, 0.0310 ppt, 25.76 mg L− 1 and 19.31 mg L− 1, respectively. The VWA values of conductivity, salinity, TDS were the highest at the Kandy city site. Further, the VWA values of hardness at Kandy and Polgolla were approximately equal, probably due to spring of Ca2+ and Mg2+ particulates from the dolomite quarry located in Digana area. The most prominent anion was identified as Cl− in bulk deposition at all three sites, while NO3− showed the lowest concentration of all sites. Moreover, very strong significant positive correlations were identified between conductivity-TDS, conductivity-salinity, conductivity-hardness, TDS-hardness, TDS-salinity, salinity-hardness, SO42− - Cl−, and NO3− - Cl− according to relevant Pearson correlation coefficients. It is thus concluded that the pollutants come from the same sources, either natural or anthropogenic.
Development and Validation of a Nomogram for Predicting Drug-induced thrombocytopenia in Hospitalized Patients: A Case‒Control Study Based on Propensity-Score Matching
Authors: Tang zhihui , Li Jiuxu , Zhu man , xie tingting , Guo Kaixin , Zhang Ru , Niu Jing'e , Zhou Fengye , Li Yu , Guo Daihong 
Published: May 2023

Abstract

Objective
Drug-induced thrombocytopenia (DITP) is associated with increased mortality. This study aims to establish a nomogram to predict the occurrence of DITP in hospitalized patients in a multidrug environment.
Methods
A single-centre retrospective study among hospitalized adult patients was conducted from January 2021 to December 2021 and was based on the Adverse Drug Events Active Surveillance and Assessment System-Ⅱ (ADE-ASAS-Ⅱ). Three controls were matched for each case according to the propensity score matching algorithm to eliminate confounding bias due to individual baseline variables. Predictors of DITP were obtained by LASSO regression and were used to build the nomogram.
Results
Among 88151 hospitalized patients, 478 were confirmed to have DITP, which is an incidence rate of 0.54%. After matching, 382 pairs and 1146 patients were included in the study, including 1070 cases in the development group and 427 cases in the validation group. Five variables were used to construct the nomogram: hospital stay ≥ 14days, surgery before using suspected drugs, baseline platelet count < 150×109/L, higher baseline BUN and combined with antibacterial. The areas under the curve (AUC) in the development group and validation group were 0.827 (95% CI 0.800-0.854) and 0.785 (95% CI 0.736–0.834), respectively, and the model also showed good calibration (P > 0.05) in the development group and validation group.
Conclusion
The established nomogram can help identify high-risk patients with DITP, assist doctors in decision-making, and effectively prevent DITP in the early stage.
Towards More Transparent and Accurate Cancer Diagnosis with an Unsupervised CAE Approach
Authors: Tabatabaei Zahra , Colomer Adrían , Moll Javier Oliver , Naranjo Valery 
Published: May 2023

Abstract
Background: Digital pathology has significantly impacted the cancer diagnosis field, with Content-Based Medical Image Retrieval (CBMIR) emerging as a powerful tool for analyzing histopathological Whole Slide Images (WSIs). CBMIR allows users to search a database for similar content to a query, providing pathologists with access to collections of cases with comparable features. This can improve the reliability of diagnostic references and help in making more accurate and timely diagnoses. Objective: In 2020, the Global Cancer Observatory (GCO) reported that breast cancer is the most prevalent cancer type in both men and women, accounting for 11.7% of all cases, while prostate cancer is the second most common cancer type in men, comprising 14.1% of cases. The aim of the proposed Unsupervised CBMIR (UCBMIR) is to replicate the traditional cancer diagnosis workflow and provide a dependable method for supporting pathologists when making diagnostic conclusions based on WSIs. By reducing the workload of pathologists, this approach could potentially enhance the accuracy and efficiency of cancer diagnosis.
Method and results: The study presents an innovative approach to address the problem of the lack of labeled histopathological images in CBMIR. A customized unsupervised Convolutional Auto Encoder (CAE) was developed to extract 200 features per image, which were then used by the search engine component. The proposed UCBMIR was evaluated using two widely used numerical techniques in CBMIR and visual evaluation, and compared with a classifier to determine if retrieved images belong to the same cancer type as the query. The validation process was conducted using three distinct data sets, with an external evaluation to demonstrate its effectiveness. The UCBMIR outperformed previous studies, achieving a top 5 recall of 99% and 80% on BreaKHis and SICAPv2, respectively, using the first evaluation technique. Using the second evaluation technique, UCBMIR achieved precision rates of 91% and 70% for BreaKHis and SICAPv2, respectively. Moreover, the UCBMIR was able to identify various patterns in patches and achieved an accuracy of 81% in the top 5 when tested on an external image from Arvaniti, having been trained using SICAPv2 with the second evaluation technique.
A model of pregnancy-associated malaria for inducing adverse pregnancy outcomes in ICR mouse
Authors: Zhang Yingying , Liang Zhiming , Xing Haoyu , Yu Chuyi , Liang Jianming , Xu Qin , Song Jianping , He Zhouqing 
Published: May 2023

Abstract
Background Based on understanding of placental pathological features and safe medication in pregnancy-associated malaria (PAM), establishment of a stable pregnant mouse infection model with Plasmodium was urgently needed.Methods ICR mice with vaginal plugs detected were randomly divided into post-pregnancy infection (Malaria+) and uninfected pregnancy (Malaria−) cohorts. Age-matched mice that had not been mated were infected as pre-pregnancy infection group (Virgin control), which were subsequently mated with ICR males. All mice were inoculated with 1×106 Plasmodium berghei ANKA-infected RBCs by intraperitoneal injection, and the same amount of saline was given to Malaria− group. We recorded the incidence of adverse pregnancy outcomes and the amounts of offspring in each group.Results The Virgin group mice were unable to conceive normally, and vaginal bleeding, abortion, or stillbirth appeared in the Malaria+ group. The incidence of adverse pregnancy outcomes was extremely high and statistically significant compared with the control (Malaria−) group (P < 0.05), of which placenta exhibited pathological features associated with human gestational malaria.Conclusions The intraperitoneal injection of 1×106 Plasmodium berghei ANKA-infected RBCs could establish a mouse model of post-pregnancy malaria infection.
Silicon-induced modulations in growth, physiological, biochemical and root attributes of Soybean (Glycine max L.) under drought stress
Authors: Abdullah Malik Muhammad , Waraich Ejaz Ahmad , Hussain Saddam , Asghar Hafiz Naeem , Haider Arslan , Ahmad Muhammad , Ahmad Zahoor , Bibi Sadia 
Published: May 2023

Abstract
Purpose: One of the main abiotic stresses that reduces crop production globally is drought. Among various strategies to improve drought tolerance in plants, the treatment of silicon is very feasible method as it has potential to improve stress tolerance in soybean. The present experiment was conducted to determine the drought stress tolerance in response to application of silicon (Si) in soybean.
Methods: In present study, different treatment levels were i) Two different field capacity levels (100% F.C and 60% F.C) ii) Four levels of silicon 0 kg/ha, 100kg/ha, 200 kg/ha and 300 kg/ha were applied, and sand culture was used as sowing media at vegetative stage (15 days after emergence).
Results: The results of present study revealed that plant biomass was significantly improved by application of silicon, such as leaf area, dry and fresh weight of root and shoot and shoot and root length. Shoot length reduced upto 23% and root length increased upto 24% under drought stress conditions contradictory to control while application of silicon (200kg/ha) considerably enhanced the shoot and root length upto 45% and 85%. Leaf osmotic potential (LOP) decreased upto 5% under stress conditions as compared to control while the (LOP) increased 27% with the application of silicon (200kg/ha). Gas exchange parameters and soluble proteins were significantly reduced under water deficit conditions. Silicon application (200kg/ha) prominently improved the total soluble proteins and gas exchange parameters. chlorophyll a,b were enhanced upto 32% and 24% in comparison to the control. Root surface area increased under stress conditions and enhanced by application of silicon and maximum improvement was observed in treatment where silicon was applied @200kg/ha. Enzymatic antioxidants (SOD, POD and CAT) reduced under drought stress but silicon significantly enhanced the enzymatic antioxidants upto 19%, 53%, 30% in comparison to stress
In conclusion, the soil applied silicon at 200kg/ha enhanced plant growth, photosynthetic pigments, osmolytes, antioxidants, and lowered oxidative stress determinants to ameliorate drought stress condition.
Expanding host range and geographical distribution of Thrips parvispinus (Karny): Onion as new host from Northern India
Authors: Saini Shubham , Raj Kushal , Saini Ankit , Saini Anil Kumar , Lal Makhan , Tyagi Kaomud , R.R. Rachana 
Published: May 2023

Abstract

The South East Asian thrips, Thrips parvispinus (Karny) (Thripidae: Thysanoptera) was witnessed for the first time infesting onion (Allium cepa) crop in Haryana, India. This invasive pest is a looming to agricultural crops in the country owing to expanding host range over the time. The occurrence of Thrips parvispinus on economically important vegetable crop like onion in India is a serious economic implication and is a source of concern for a quarantine. A regular monitoring of this invasive thrips is the need of an hour as it may become a greater nuisance in the future.
We will lose leadership position in the church: Belief systems of indigenous Ugandan men on LARCs
Authors: Kibonire Ronald Arineitwe , Mphuthi DAVID Ditaba 
Published: May 2023

Abstract
Many women Pregnancy, childbirth, and postpartum complications are the primary causes of mortality worldwide. Contraceptives, especially long-acting reversible contraceptives (LARCs), are the most essential and effective interventions for reducing maternal mortality. LARCs aid in the postponement of pregnancy and allow for longer intervals between deliveries. However, LARC use remains minimal globally and in Uganda due to insufficient male partner support. The aim of this study was to understand the belief systems of rural Ugandan males regarding the use of LARCs by rural women. Using purposive sampling, 65 married men between the ages of 20 and 49 were chosen for focus group interviews, and 30 were chosen for individual interviews. The study was conducted in the districts of Rubanda and Kiboga in Uganda. The researcher employed semi-structured questions in individual and focus group interviews. During the data analysis, the researcher Listened to recordings, perusing field notes and interviews, classifying and categorised the data, and then identifying the phenomenon's emerging themes. The study revealed that rural indigenous Ugandan men had beliefs about their rural wives' use of LARCs, and that these beliefs acted as barriers to use. These belief systems included preference of natural family planning methods, children as a source of labour, children for expanding and strengthening the clan, sex preference for boys for wealth inheritance, dowry wealth, cultural recognition. Specifically, among Catholics and Muslims, the study found that religious beliefs include the dread of losing a leadership position in the church and not to contradict the doctrines of the religion. The study recommends enhancing Social and Behavioural Change Communication, strengthening the service delivery for LARCs, and monitoring and evaluation systems, fostering an environment conducive to the delivery of LARC services, and preparing the pre-service and in-service healthcare professionals through health training institutions and universities to deliver LARC services.
Instance Segmentation on Distributed Deep Learning Big Data Cluster
Authors: Elhmadany Mohammed , Elmadah Islam , Abdelmunim Hossam E. 
Published: May 2023

Abstract
This paper presents workflow in deep learning inference models in a distributed manner. This is often required in production environments where real-time predictions need to be made on a massive scale., optimization approaches were applied to the instance segmentation YOLACT model to improve the inference throughput. , and the experiments show that the execution time taken by the OpenVino (Open Visual Inference and Neural Network Optimization) model with 16 FP is the least compared to ONNX (Open Neural Network Exchange) and the original PyTorch model. ONNX and OpenVINO provide a set of tools for optimizing deep learning models for deployment on a range of edge devices such as smartphones, laptops, tablets, IoT devices, sensors, and other devices that collect, process, and transmit data between the end user and the cloud or datacenter. The model optimizer in these frameworks plays a critical role in preparing deployment models, by reducing their size and increasing their performance.YOLACT in OpenVino format we run it on a big data cluster using the BigDL framework to apply inference on spark stand-alone and yarn clusters. where BigDL is a distributed deep learning library for Apache Spark that provides a high-level programming interface for defining and training deep neural networks. It supports a wide range of deep learning models and is designed to be scalable, making it ideal for large-scale deep learning applications. In distributed deep learning reference, the input data is partitioned and sent to multiple machines in parallel for processing. Each machine runs its portion and produces a partial output, which is then combined with the outputs of other machines to produce a final result. Spark stand alone perform better depending on the obtaining results under different conditions whereas significant speedups can be achieved by increasing the number of executors across the cluster.
Work-related musculoskeletal disorders among desludging operators in Uganda
Authors: Tamale Bridget Nagawa , Ssekamatte Tonny , Isunju John Bosco , Nalugya Aisha , Mukasa Mujjabi Martin , Tigaiza Arnold , Nakalembe Doreen , Kansiime Winnie K. , Kimbugwe Ceaser , Mselle Jane Sembuche , Mugambe Richard K. 
Published: May 2023

Abstract

Background
Despite the limited evidence, desludging operators remain at a heightened risk of work-related musculoskeletal disorders (WMSDs). This study established the prevalence and predictors of WMSDs among desludging operators in Uganda.
Methods
A digitalized structured questionnaire was used to collect cross-sectional data on musculoskeletal disorders and routine workplace activities from 303 desludging operators in Uganda. Data were analyzed using STATA version 15.0.
Results
The prevalence of WMSDs among desludging operators was 29.7%. The background characteristics associated with WMSDs included; attending safety training in the last 12 months (APR = 0.55, 95% CI: 0.31–0.98) and undertaking regular health check-ups (APR = 1.68, 95% CI: 1.16–2.44). The ergonomic factors associated with WMSDs were; working with a bent wrist (APR = 2.64, 95%CI: 1.54–4.52), working with hands above the head (APR = 0.40, 95% CI: 0.26–0.62), and pinching unsupported objects (APR = 0.87, 95% CI: 0.59–1.29). Psychosocial factors associated with WMSDs included; neither agreeing nor disagreeing about being able to influence the availability of equipment needed to do their work = 0.43, 95% CI: 0.20–0.94), having much influence over the amount of work done (APR = 1.75, 95% CI: 1.05–2.91), and sometimes feeling that everything done was an effort (APR = 1.71, 95% CI: 1.01–2.89).
Conclusion
The prevalence of WMSDs was high among desludging operators in Uganda. We recommend providing comprehensive training on occupational health and safety, with a specific focus on ergonomic hazards. In addition, personal protective equipment uses, regular exercise programs, and considerations for work pace, rest, and recovery opportunities should be prioritized to reduce the risk of WMSDs.
Foliar Application of Silicon Alleviates Adverse Effect of Drought Stress by improving Growth, Physiological attributes, and Antioxidant Defense of Camelina (Camelina sativa L.) and Canola (Brassica napus L.)
Authors: Shahzad Bilal Ahmad , Waraich Ejaz Ahmad , Saleem Muhammad , Hussain Saddam , Ullah Saif 
Published: May 2023

Abstract
Purpose: Drought stress is a global phenomenon that poses harmful impacts on crop growth and development leading to yield losses in oilseed crops. Canola and camlina are highly sensitive to drought stress. The present study investigated the role of foliar-applied silicon to alleviate the harmful effect of drought stress in camelina and canola genotypes.
Methods: Different concentrations of silicon (Si) foliar applications (NS= no spray, WS= water spray, Si-2= 2 mM Si, Si-4= 4 mM Si, Si-6= 6 mM Si) were used along with different levels of drought stress i.e., control (100% field-capacity) and drought stress (50% field-capacity), for two genotypes of camelina (611 and 618) and two canola genotypes (Super and Rachna).
Results: Drought stress caused marked reductions in the growth of canola and camelina genotypes as compared with control-100% field capacity. Compared to control, drought stress decreased shoot length of canola and cameline by 25% and 28%, respectively. Physiological attributes were also decreased under drought stress as photosynthetic rate, relative water content (RWC), and chlorophyll content were decreased by 39, 38 and 42% in canola and 35, 45, and 39% in camelina, respectively, as compared to control. Drought stress was found to increase the oxidative damage in both crops. Foliar applications of Si improved the morpho-physiological and biochemical attributes in canola and camelina genotypes as compared to NS. Silicon applications at 4 mM upregulated the activities of catalase, superoxide dismutase, and peroxidase were increased by 16, 18, and 12% in canola and 17, 14, and 15% in camelina respectively, reducing the electrolyte leakage as compared to NS. Under drought stress, maximum improvements in plants performances were observed when Si was foliarly applied at 4 mM followed by 6 mM and 2 mM. Among the genotypes, canola genotype Rachna showed better performance as compared to Super, while camelina genotype 618 showed better performance as compared with 611.
Conclusion: In crux, Si foliar application particularly at 4 mM improved the morpho-physiological and biochemical attributes in canola and camelina genotypes under drought-stressed conditions. The better growth and greater stress tolerance of Si-applied plants was attributed to maintaince of plant water status and photosynthetic pigments, lower oxidative damage, and higher activities of antioxidant enzymes under drought.
Elemental Profiling and mapping analysis of the Excreta of Trogopterus xanthipes (Wulingzhi) Collected from Different Regions using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Multivariate Statistical Analysis
Authors: Wang Anqi , Li Zheng , Zhao Yiyi , Wang Jinghui , Fu Xintong , Chen Yougen , Ye Min , Guo Hongzhu 
Published: May 2023

Abstract
Inorganic element content is an important quality and origin indicator for herbs. The excreta of Trogopterus xanthipes (“Wulingzhi” in Chinese; WLZ) is a well-known traditional Chinese medicine that has been widely used to treat amenorrhea, menstrual pain, and postpartum abdominal pain for thousands of years. However, there has been less emphasis on the analysis of trace element content in WLZ. This study aimed to investigate the elemental characteristics of WLZ obtained from different regions (Shānxi, Shănxi, Hubei, Hebei) and perform a risk and benefit analysis to assess its quality and safety. Thirty elements in sixty batches of WLZ and their products processed with vinegar (V-WLZ) were compared using inductively coupled plasma mass spectrometry (ICP-MS). Multivariate statistical techniques, including principal component analysis (PCA), correlation analysis, elemental mapping analysis, and metal pollution index (MPI) analysis, were applied to interpret the data. The box plots showed a heterogeneous distribution of almost all analyzed elements, indicating significant differences between the samples. This is the first study to provide the reference values for major, trace, and toxic elements in WLZ. Furthermore, the results revealed that the average value of heavy-MPI in V-WLZ (2.030) was slightly lower than that in WLZ (2.096). Combining the PCA data and the inorganic element spectra, we identified Fe, Al, Cu, Se, Pb, Rb, V, K, P, (Na), Cr, As, and Ni as the characteristic elements of WLZ and V-WLZ.