bluuebunny/crossref_metadata_2025 huggingface dataset:
Utilization of carob bean pulp and seeds in preparing some functional bakery products
Authors: Hafez Hoda , Mahgoub Saad
Published: September 2022

This study aimed to (i) utilize roasted carob powder (130° C/ 30 min) from carob bean pulp as a natural sweetener in replacement with cane sugar at 0, 25, 50, and 75% in cacao cupcakes formula; (ii) utilize carob bean gum from carob bean seeds as a by-product of pods in gluten-free bread at 0, 0.5, 1.0 and 1.5%, (iii) assess the chemical, viscosity and antioxidant properties of the raw materials, (iv) evaluate the sensory, physicochemical and texture properties of the produced cupcakes and gluten-free bread. Roasted carob powder hadP ≤ 0.05 values of fiber (7.11%), ash (2.73%), Fe (38.7%), Ca (228.5%), Zn (3.1%), Total phenol (205.53 mg/100g) and antioxidant activity (91.78%). The aqueous dispersion (1%) of carob bean gum showed pseudoplastic behavior with apparent viscosity (η) from 2110-438.33 cP. Both cupcakes and gluten-free bread had water activity (aw) < 0.94. Roasted carob powder could be used as a natural sweetener in replacement with cane sugar up to 50% in cacao cupcakes formula, with nop ≥ 0.05 increase in appearance, crust color, crumb texture, odor, and acid value compared with the control sample, which can suit low glycemic diet. Carob bean gum could be used as a binder up to 1.0% in gluten-free bread withP ≤ 0.05 soft texture, shape symmetry, bright color, and higher overall acceptability, which can meet celiac patient needs.
Epidemiological and clinicopathological features of lung cancer in Algeria
Authors: Lahmadi Mohamed , Beddar Leila , Ketit Souad , Filali Taha , Djemaa Aicha , Satta Dalila
Published: September 2022

Purpose: Lung cancer is the most commonly diagnosed cancer in men and the leading cause of cancer-related death in Algeria. We investigated the clinicopathological characteristics of a group of patients with lung cancer in Eastern Algeria, that might reflect a national landscape.
Methods: This retrospective study was performed on 173 histologically proven cases of lung cancer at Benbadis university hospital of Constantine from January 2015 to February 2021. Clinical and pathological variables were investigated based on the available data found in the patient's medical records.
Results: Lung cancer showed a male predominance with a sex ratio of 6.5. Majority of our patients (86%) aged greater than 50 years with a median age of 61 years. Histologically, adenocarcinoma was found in over 56.6% of the cases, followed by squamous cell carcinoma with 22.5%, whereas 12.8% were non-NSCLC subtypes. Tobacco smoking was estimated at 79.1% in men. Non-smokers represented over 32.5% of patients, of which 45.1% were female. Most of our patients (79%) have an advanced stage at diagnosis, including 57.3% with metastatic disease. Around 60% of patients underwent chemotherapy, of which 81% was first-line treatment, with a median diagnostic delay of almost 4 months.
Conclusion: Lung cancer presents at an early age and advanced stage in Algerian patients. Smoking remains the most important risk factor in men and adenocarcinoma is the predominant histological subtype. Thus, primary prevention, based on tobacco control and screening programs, and access to novel therapies may be the best strategies to reduce lung cancer morbidity and mortality.
From Zero-Shot Machine Learning to Zero-Day Attack Detection
Authors: Sarhan Mohanad , Layeghy Siamak , Gallagher Marcus , Portmann Marius
Published: September 2022

Machine learning (ML) models have proven to be efficient in classifying data samples into their respective categories. The standard ML evaluation methodology assumes that test data samples are derived from pre-observed classes used in the training phase. However, in applications such as Network Intrusion Detection Systems (NIDSs), obtaining data samples of all attack classes to be observed is challenging. ML-based NIDSs face new attack traffic known as zero-day attacks that are not used in training due to their non-existence at the time. Therefore, this paper proposes a novel zero-shot learning methodology to evaluate the performance of ML-based NIDSs in detecting zero-day attack scenarios. In the attribute learning stage, the learning models map network data features to semantic attributes that distinguish between known attacks and benign behaviour. In the inference stage, the models construct the relationships between known and zero-day attacks to detect them as malicious. A new evaluation metric is defined as Zero-day Detection Rate (Z-DR) to measure the effectiveness of the learning model in detecting unknown attacks. The proposed framework is evaluated using two key ML models and two modern NIDS data sets. The results demonstrate that for certain zero-day attack groups discovered in this paper, ML-based NIDSs are ineffective in detecting them as malicious. Further analysis shows that attacks with a low Z-DR have a significantly distinct feature distribution and a higher Wasserstein Distance range than the other attack classes.
Reduction of glutamatergic activity through cholinergic dysfunction in the hippocampus of hippocampal cholinergic neurostimulating peptide precursor protein knockout mice
Authors: Suzuki Kengo , Ohi Yoshiaki , Sato Toyohiro , Tsuda Yo , Moadokoro Yuta , Mizuno Masayuki , Adachi Ken-ichi , Uchida Yuto , Haji Akira , Ojika Kosei , Matsukawa Noriyuki
Published: September 2022

Cholinergic activation can enhance glutamatergic activity in the hippocampus under pathologic conditions, such as Alzheimer’s disease and Lewy body disease. We aimed to elucidate the relationship between glutamatergic neural suppression and cholinergic neural dysfunction. We reported the importance of hippocampal cholinergic neurostimulating peptide (HCNP) in inducing acetylcholine synthesis in the MSN. Here, we demonstrated that HCNP-precursor protein (pp) knockout (KO) mice electrophysiologically presented with glutamatergic dysfunction in the hippocampus with age. The impairment of cholinergic dysfunction and the vesicular acetylcholine transporter decrease in the pre-synapse with reactive upregulation of the muscarinic M1 receptor may be partly involved in glutamatergic dysfunction in the hippocampus of HCNP-pp KO mice. These results in combination with our previous reports support the reduction of hippocampal theta power as region-specific in the stratum oriens of CA1 and a decrease in choline acetyltransferase and a direct reduction in acetylcholine in the hippocampus. This may support that HCNP-pp KO mice are an adequate genetic model for cholinergic functional impairment in septo-hippocampal interactions. Thus, according to cholinergic hypothesis this model mice might have a potential as a partial pathological animal model for Alzheimer’s disease.
CCECGP:Causal Consistency Model of Edge-Cloud Collaborative Based on Grouping Protocol
Authors: Tian Junfeng , Jia Haoyi , Bai Wenqing
Published: September 2022

At present, most causal consistency models based on cloud storage can no longer meet the needs of delay-sensitive applications. Moreover, the overhead of data synchronization between replicas is too high. This paper proposes a causal consistency model of edge-cloud collaborative based on grouping protocol. The model based on the edge-cloud collaboration architecture, partitions cloud data centers and groups edge nodes by distributed hash tables, and stores a subset of the complete data set in nodes located at the edge of the network. Thereby realize partial geo-replication in edge-cloud collaboration environment. At the same time, we design a group synchronization algorithm called Imp_Paxos, so that the update only needs to be synchronized to the main group, which reduces the visibility delay of the update and decreases the data synchronization overhead. Besides, a sort timestamp is proposed in this paper, which generates different timestamps according to the type of update to track causality, keeping the amount of metadata managed in a relatively stable and low state.Threrfore, the proposed model reduces the overhead of metadata for system management, and improves throughput quantity of system. Experiments show that, our model performs well in terms of throughput, operation latency, and update visibility latency compared with existing causal consistency models.
Dissipative Particle Dynamics Simulation of Chitosan-Citral Microcapsules
Authors: Wu Wensheng , Li Zhiwei , Feng Dachun , Tang Qing , Liu Shuijiao , Lin Wenjing
Published: September 2022

In this paper, the dissipative particle dynamics (DPD) method is used to simulate the self-assembly process, appearance, mesoscopic structure and wrapping properties of microcapsules formed with citral as the core material and chitosan and sodium alginate as single wall materials, and with citral as the core material and chitosan-sodium alginate, chitosan-methylcellulose, sodium alginate-chitosan and sodium alginate-methylcellulose as double wall materials. The effects of chitosan content and wall material composition on the structure, morphology, encapsulation performance and stability of microcapsules are compared and analyzed. In addition, the microcapsules are deeply analyzed by using the mesoscopic structure, radial distribution function and diffusion coefficient. This study provides a new idea and method for the preparation of citral microcapsules and is of great significance for the design and development of new composite wall microcapsules.
Development and validation of asthma risk prediction models using co- expression gene modules and machine learning methods
Authors: Dessie Eskezeia Y. , Gautam Yadu , Ding Lili , Altaye Mekibib , Beyene Joseph , Mersha Tesfaye B.
Published: September 2022

Asthma is a chronic inflammatory disease of the airways with a strong genetic component. Because multiple genes may affect asthma, identifying differentially co-expressed genes followed by functional annotation can inform our understanding of the molecular mechanisms in asthma pathogenesis. In this study, we used airway epithelial cells (AECs) and nasal epithelial cells (NECs) datasets and implemented weighted gene co-expression network analysis (WGCNA) and machine learning (ML) techniques to develop asthma classification and predictive models. The models were validated using external bronchial epithelial cells (BECs), airway smooth muscle (ASM) and whole blood (WB) datasets. WGCNA and ML-based procedure identified 23 and 34 gene signatures that can discriminate asthmatic from control subjects in AECs (Area under the curve: AUC =0.90) and NECs (AUC = 0.99), respectively. We further validated AECs derived DEGs in BECs (AUC= 0.96), ASM (AUC= 0.72) and WB (AUC= 0.67). Similarly, NECs derived DEGs in BECs (AUC= 0.88), ASM (AUC= 0.87) and WB (AUC= 0.68). Both AECs and NECs based gene-signatures showed a strong diagnostic performance with high sensitivity and specificity. Functional annotation of NEC-derived hub genes showed several enriched pathways related to Th1 and Th2 activation pathway, while AECs-derived hub genes were significantly enriched in pulmonary fibrosis and idiopathic signaling. Several asthma related genes were prioritized including Cathepsin C (CTSC) which showed functional relevance in multiple cells relevant to asthma pathogenesis. Taken together, epithelium gene signature-based model could serve as robust surrogate model for hard-to-get tissues including BECs to improve asthma classification.
Clinical study of two-stage total knee arthroplasty in the treatment of advanced complex and severely active tuberculosis of the knee
Authors: Li jin-ping , Yu min , shen feng , li liang-jun , xu yi , xiong jie-peng , zhu wei , gu yun , chou ke
Published: September 2022

Objective： To investigate the feasibility and efficacy of one-stage debridement and two-stage total knee arthroplasty in the treatment of advanced complicated and severely active tuberculosis of the knee joint.
Methods: A retrospective analysis was performed on the clinical data of 12 patients who underwent two stages of artificial knee replacement for advanced severely active tuberculosis of the knee in the department of Osteoarthrosis of our hospital from January 2015 to December 2019. The average age was 50.5 years (21-71 years). All patients received lesion removal and perioperative anti-tuberculosis drug therapy. In the first phase, debridement was performed after at least 2 weeks of anti-tuberculosis chemotherapy to remove abscesses and infected necrotic tissue as thoroughly as possible, and SPACER was implanted in 7 cases, followed by at least 3 months of anti-tuberculosis chemotherapy (mean 5.4 months). In the second stage, if CRP and ESR were reduced to less than 2 times of the normal value and the wound healed well, artificial knee replacement was performed. Anti-tuberculosis chemotherapy was continued for 8-9 months after the operation, and the total anti-tuberculosis chemotherapy lasted 12-20 months. HSS knee score and range of motion, as well as prosthesis stability, ESR and CRP, and X-ray were evaluated.
Results: All patients received 18-76 months of follow-up and 12-20 months of regular anti-tuberculosis treatment. No pulmonary tuberculosis recurrence or co-infection was found in all patients, and ESR and CRP were reduced to within 2 times of normal after several months. At the last follow-up, no recurrence of tuberculosis was found in all patients, and no loosening of prosthesis was found in X-ray examination. HSS score of knee increased from (41.42±10.47) points before surgery to (82.58±9.14) points, and ROM of knee increased from (40.42°±15.73°) to (100.83°±9.73°). There were statistically significant differences before and after operation (P<0.001).
Conclusions: For advanced complicated and severely active tuberculosis of the knee, one-stage debridement and two-stage total knee arthroplasty can effectively control infection, relieve pain and reconstruct the function of the knee joint
Vertical hydrologic exchange flows control methane emissions from riverbed sediments
Authors: Chen Kewei , Chen Xingyuan , Stegen James , Villa Jorge , Bohrer Gil , Song Xuehang , Chang Kuang-Yu , Kaufman Matthew , Liang Xiuyu , Guo Zhilin , Roden Eric , Zheng Chunmiao
Published: September 2022

CH4emissions from inland waters are highly uncertain in the current global CH4budget, especially for the lotic systems like rivers. Previous studies have attributed the strong spatiotemporal heterogeneity of riverine CH4to different environmental factors through correlation analysis. However, a mechanistic understanding for such heterogeneity is lacking. Here we combine sediment CH4data with a biogeochemical-transport model to show that vertical hydrologic exchange flows (VHEFs), driven by the difference between river stage and groundwater level, determine CH4flux at the sediment-water interface. CH4fluxes show a nonlinear relationship with the magnitude of VHEFs. In addition, VHEFs lead to the hysteresis of temperature rise and CH4emissions because high river discharge leads to strong downwelling flow that offsets increasing CH4production with temperature rise. Our findings reveal how the interplay between hydrologic flux and microbial metabolic pathways that compete with methanogenic pathways can produce complex patterns in CH4production and emission in riverbed sediments.
Scenic Routing Navigation Using Property Valuation
Authors: Rishe Naphtali , Amini Hadi , Adjouadi Malek
Published: September 2022

Extensive prior work has provided methods for the optimization of routing based on the criteria of travel time and/or the cost of travel and/or the distance traveled. Routing can be in various modalities, such as by car, on foot, by bicycle, via public transit, or by boat. A typical method of routing involves building a graph comprised of street segments, assigning a normalized weighted value to each segment, and then applying the weighted-shorted path algorithm to the graph in order to find the best route. Some users desire that the routing suggestion include consideration pertaining to the scenic architectural quality of the path. For example, a user desires a leisure walk via what they might deem as visually attractive architecture. Here, we are proposing a method to quantify such user preferences and scenic quality and to augment the standard routing methods by giving weight to the scenic quality. That is, instead of suggesting merely the time & cost-optimal route, we will find the best route that is tailored towards the user’s scenic quality preferences, as an additional criterion to the time and cost.
Optimization of green and environmentally-benign synthesis of isoamyl acetate in the presence of ball-milled seashells by response surface methodology
Authors: Fattahi Amir Hossein , Dekamin Mohammad G. , Clark James H
Published: September 2022

Ball-Milled seashells, as a nano-biocomposite catalyst and natural source of CaCO3 in its aragonite microcrystalline form and fixed CO2, was optimized for the synthesis of isoamyl acetate by response surface methodology (RSM) with a five-level three-factor rotatable circumscribed central composite design (RCCCD). The seashells nano-biocomposite was proved to be an excellent heterogeneous catalyst for the green and environmentally-benign synthesis of isoamyl acetate from acetic acid and isoamyl alcohol under solvent-free conditions. High yield of 91% was obtained under the following optimal conditions: molar ratio of alcohol: acetic acid (1:3.7), catalyst loading (15.7 mg), the reaction temperature (98°C), and the reaction time (219 min). The outstanding advantages of this protocol are the use of a naturally occurring and easily prepared nano-biocomposite material without any modifications with hazardous reagents, lower catalyst loading and required temperature, avoiding the use of corrosive Bronsted acids as well as toxic azeotropic solvents or water adsorbents, and simplicity of the procedure.
Threshold photoproduction of neutral pions off protons in nuclearmodel with explicit mesons
Authors: Fedorov D.V. , Mikkelsen M.
Published: September 2022

We apply the nuclear model with explicit mesons to photoproduction ofneutral pions off protons at the threshold. In this model the nucleons donot interact with each other via a potential but rather emit and absorbmesons that are treated explicitly on equal footing with the nucleons. We calculate the total cross section of the reaction for energies close tothreshold and compare the calculations with available experimental data. We show that the model is able to reproduce the experimental data anddetermine the range of the parameters where the model is compatible withthe experiment.
Oleanolic Acid as a Possible Inhibitor of Pfn2: In silico Approach
Authors: Cárdenas-Pillco Berly , Cabrera-del-Carpio Zunilda N. , Quispe Lina G. , Ayqui-Cueva Flor , Del-Carpio-M Bruno A. , Bellido-Vallejo Karen L. , Gómez Badhin
Published: September 2022

Colorectal cancer (CRC) has a high mortality rate and has recently involved human profilin II (Pfn2), an actin-binding protein promoter of its invasiveness and progression. This work evaluated the binding affinity of oleanolic acid (Naturally Occurring Saponin) over Pfn2 and its structural stability. QM and MM techniques were applied to perform geometrical optimization and calculation of the reactive sites from Oleanolic Acid, whereas molecular docking and MD simulations for protein-ligand interaction under physiological conditions. Oleanolic acid saponin showed a high binding affinity to the Pfn2 PLP-binding site. Analysis of the protein-ligand structure suggests saponin as a molecule with high potential for developing new drugs against Pfn2 in colorectal cancer cells.
Evaluation of auto-segmentation for brachytherapy of postoperative cervical cancer using deep learning-based workflow
Authors: Wang Jiahao , Chen Yuanyuan , Tu Yeqiang , Xie Hongling , Chen Yukai , Luo Lumeng , Zhou Pengfei , Tang Qiu
Published: September 2022

Objective: The purpose of this study was to evaluate the accuracy of brachytherapy (BT) planning structures derived from Deep learning (DL) based auto-segmentation compared with standard manual delineation for postoperative cervical cancer.
Methods: We introduced a convolutional neural networks (CNN) which was developed and presented for auto-segmentation in cervical cancer radiotherapy. The dataset of 60 patients received BT of postoperative cervical cancer was used to train and test this model for delineation of high-risk clinical target volume (HRCTV) and organs at risk (OARs). Dice similarity coefficient (DSC), 95% hausdorff distance (95%HD), jaccard coefficient (JC) and dose-volume index (DVI) were used to evaluate the accuracy. The correlation between geometric metrics and dosimetric difference was performed by Spearman’s correlation analysis. The radiation oncologists scored the auto-segmented contours by rating the lever of satisfaction (no edits, minor edits, major edits).
Results: The mean DSC values of DL based model were 0.87, 0.94, 0.86, 0.79 and 0.92 for HRCTV, bladder, rectum, sigmoid and small intestine, respectively. The Bland-Altman test obtained dose agreement for HRCTV_D90%, HRCTV_Dmean, bladder_D2cc, sigmoid_D2cc and small intestine_D2cc. Wilcoxon’s signed-rank test indicated significant dosimetric differences in bladder_D0.1cc, rectum_D0.1cc and rectum_D2cc (P<0.05). A strong correlation between HRCTV_D90% with its DSC (R=-0.842, P=0.002) and JC (R=-0.818, P=0.004) were found in Spearman’s correlation analysis. From the physician review, 80% of HRCTVs and 72.5% of OARs in the test dataset were shown satisfaction (no edits).
Conclusion: The proposed DL based model achieved a satisfied agreement between the auto-segmented and manually defined contours of HRCTV and OARs, although the clinical acceptance of small volume dose of OARs around the target was a concern. DL based auto-segmentation was an essential component in cervical cancer workflow which would generate the accurate contouring.
An assessment of the ENSO-monsoon teleconnection in a warming climate
Authors: An Soon-Il , Goswami Bidyut
Published: September 2022

The El Niño–Southern Oscillation (ENSO) and the Indian summer monsoon (ISM, or simply, monsoon) are two giants of tropical climate, which are delicately related. Here we present an assessment of the future evolution of the ENSO-monsoon teleconnection based on an analysis of climate simulations comprising of 28 ensembles (each 140 years long) with idealized forcing of CO2 increment at a rate of 1% per year starting from a concentration value of 367 p.p.m. until quadrupling. We find that the model-simulated climate exhibits monotonous weakening of the ENSO-monsoon teleconnection with the increase in CO2 forcing. Our analysis reveals that increasing number of co-occurrences of El Niño and the positive phase of Indian Ocean Dipole (pIOD) in a warmer climate causes weakening of the ENSO-Monsoon teleconnection. The co-occurrences of El Niño and pIOD is attributable to mean state warming of the SST that resemble a pIOD-type warming pattern in the Indian Ocean and an El Niño-type warming pattern in the Pacific. Since ENSO-Monsoon teleconnection is one of the precursors of the strength of the Indian monsoon, a weakening this relation may mean a more unpredictable Indian monsoon in a warmer climate.
Does Hounsfield Unit have any significance in predicting intra and postoperative outcomes in retrograde intrarenal surgery using holmium and Thulium fiber laser? A critical analysis of results from the FLEXible ureteroscopy Outcomes Registry (FLEXOR)
Authors: Keat William Ong Lay , Somani Bhaskar Kumar , Pietropaolo Amelia , Chew Ben Hall , Chai Chu Ann , Inoue Takaaki , Ragoori Deepak , Biligere Sarvajit , Galosi Andrea Benedetto , Pavia Maria Pia , Milanese Giulio , Ahn Thomas , More Sumit , Sarica Kemal , Traxer Olivier , Teoh Jeremy Yuen-Chun , Gauhar Vineet , Castellani Daniele
Published: September 2022

The objective was to evaluate outcomes of retrograde renal surgery for intrarenal stones of any size, number, and position, comparing hard versus soft stones based on their attenuation on computed tomography (Hounsfield Unit-HU). Exclusion criteria; children/adolescents, ureteric stones, renal anomalies, or bilateral surgery. Patients were divided into two groups according to the type of laser employed, i.e. Holmium:YAG (HL) and Thulium fiber laser (TFL). Residual fragments (RF) were defined as > 2 mm. Multivariable logistic regression analysis was performed to evaluate factors associated with RF and RF needing further intervention. 4208 patients from 20 centers were included. 3070 patients were operated on with HL. In HU < 1000 stones, the TFL group had larger stones (11.56 ± 10.38 vs 9.98 ± 6.89 mm,p < 0.001). Multiple and lower pole stones were more prevalent in the HL group. Lasing time was shorter in the TFL group (15.34 ± 12.55 vs 23.32 ± 15.66 minutes,p < 0.001). HL group had a higher incidence of RF (29.1% vs 13.7%,p < 0.001). Age, stone size, and HL were predictors of RF, whereas multiple stones, and HL of RF requiring retreatment. In HU ≥ 1000 stones, stone size was similar between the two groups, whilst multiple and lower pole stones were more prevalent in the HL group. Surgical time was significantly shorter in the HL group (64.48 ± 33.92 vs 79.54 ± 88.56,p < 0.001). Significantly higher incidence of RF was noted in HL (22.7% vs 9.8%,p < 0.001), whilst reintervention rate was significantly higher TFL group (69.6% vs 43.8%,p < 0.001). Age, stone size, and use of HL were predictors of RF, whilst recurrent stone formers, multiple stones, and use of TFL of RF requiring retreatment.
Real-World Study of Neoadjuvant Chemotherapy with Bevacizumab in Patients with Ovarian Cancer: A Chinese single-institution study
Authors: Zhang Nan , Zheng Hong , Gao Yunong , Shu Tong , Wang Hongguo
Published: September 2022

Background Bevacizumab was the first anti-angiogenic agent approved for the treatment of newly diagnosed and relapsed ovarian cancer. For patients with extensive tumor metastasis that is unsuitable for primary debulking surgery(PDS), platinum-based neoadjuvant chemotherapy(NACT) followed by interval debulking surgery(IDS) has become an important therapy strategy. The bevacizumab-containing regimens are also options for NACT and post-IDS chemotherapy. Although there have been many high-quality clinical trials of bevacizumab for ovarian cancer, real-world evidence is still necessary for clinical practice. Objective This study aimed to retrospectively assess the pattern, compliance, efficacy, and safety of bevacizumab as NACT in Chinese patients with ovarian cancer. Methods We reviewed the clinicopathological data of patients with histologically confirmed epithelial ovarian cancer, fallopian tube cancer and primary peritoneal adenocarcinoma, who were diagnosed and treated at the Department of Gynecologic Oncology of Peking University Cancer Hospital between May 2012 and January 2022. Results A total of 58 patients were ultimately enrolled in this study, with 35 receiving bevacizumab during NACT alone(NT) and 23 receiving bevacizumab during both neoadjuvant and first-line chemotherapy(NT + FL). Among the 43 patients in NT and NT + FL groups undergoing IDS, 38(88.4%) patients achieved optimal debulking and 24(55.8%) patients had no residual disease after IDS. All patients had a median PFS of 15 months (95%CI: 9.595–21.405), and the 12-month PFS was 60.2%. The median PFS of the NT and NT + FL groups were 13 months(95% CI: 9.738–16.262) and 20 months(95% CI:11.362–28.638), respectively. Nevertheless, there was no significant difference between the two groups(p = 0.113). According to multivariate analysis, patients treated with 15 mg/kg had a better PFS than those treated with ≤ 7.5 mg/kg(HR = 0.352, 95% CI: 0.143–0.864, P = 0.023). Hypertension was the most common adverse event associated with bevacizumab. A total of 5.2% (3/58) of patients discontinued bevacizumab due to toxicity. Conclusion Bevacizumab is effective and well-tolerated in the real-world setting of ovarian cancer NACT treatment. Receiving the regimen containing bevacizumab in the last preoperative chemotherapy did not result in increased intraoperative bleeding. Patients receiving the dosage of 15mg/kg may have better survival outcomes than those receiving the dosage of ≤ 7.5mg/kg.
Effectiveness of implementing of an infection control link nurse program to improve compliance with standard precautions and hand hygiene among nurses: A quasi- experimental study
Authors: Ghorbanmovahhed Shamsi , Shahbazi Shahla , Gilani Neda , Ostadi Ali , Gholizadeh Leila , Shabanloei Reza
Published: September 2022

Background: Standard precautions (SPs) including hand hygiene are considered fundamental protective measures to manage health care-associated infections (HCAIs) and to reduce occupational health hazards. The purpose of this research was to examine the effectiveness of an infection control link nurse (ICLN) program on compliance with SPs and hand hygiene among nurses.
Methods: A quasi-experimental study with a pretest-post-test design was conducted with participating of 154 clinical nurses who worked in different wards of a tertiary referral teaching hospital in Iran. The intervention group (n=77) had 16 infection control link nurses nominated. The control group (n=77) received only the standard multimodal approach used in the hospital. Pre- and post-test assessment of compliance with standard precautions and hand hygiene compliance was performed via the Compliance with Standard Precautions Scale (CSPS) and the World Health Organization observational hand hygiene form. Two independent sample t-tests were used to examine differences between Compliance with Standard Precautions and hand hygiene Complianceamong nurses in intervention and control group. Multiple linear regression analysis was used to assess the effect size.
Results: After developing and implementing the infection control link nurse program, no statistically significant improvement was found in the Compliance with Standard Precautions (β= 5.18; 95% CI= -0.3–10.65, p=0.064). An improvement in hand hygiene compliance was observed among nurses in the intervention group that improved statistically significant from 18.8% before the program to 37.32% 6 months after the program (β= 20.82; 95% CI 16.40–25.25, p<0.001).
Conclusions: Given the continuing level of interest that exists in improving health care workers’ hand hygiene practices, the findings of this study provide significant practical implications for hospitals seeking to improve compliance with hand hygiene among nurses, showing the effectiveness of using infection control link nurse program. Further research is needed to assess effectiveness of using infection control link nurse program to improve compliance with standard precautions.
Flood risk assessment of metro stations based on SMAA-2-FFS-H: A case study of the "7·20" rainstorm in Zhengzhou, China
Authors: Tu Yan , Shi Han , Zhou Xiaoyang , Liu Liyi , Lev Benjamin
Published: September 2022

Motivated by the realistic demand of reducing the flood risk of urban metro stations, this paper creatively proposes a research framework for flood risk classification assessment of metro stations. In the framework, a specified criterion system is established from the perspective of hazard, vulnerability, exposure and rescue capacity. Furthermore, a SMAA-2-FFS-H method is proposed, which is comprised of stochastic multi-criteria acceptability analysis-2 (SMAA-2), fuzzy flowsort (FFS) and multi-criteria hierarchy process (MCHP). For verifying the practicality and efficiency of the proposed framework, the flood risk evaluation of 32 stations in Zhengzhou Metro Line 5 during the "7·20" rainstorm event is taken as a case study. The results show that only Shakoulu Station is at high risk, which is correspond to the reality of the "7·20" rainstorm event. Moreover, the risk class characteristics of the remaining stations are correspond to historical flooding events. Among them, 10 metro stations are classified as medium risk, 21 metro stations are classified as low risk, and none metro station is classified as very low risk. As proved above all metro stations have a certain degree of flood risk, and the classes of flood risk are indeed different between some metro stations. In addition, the validity and robustness of the proposed method are demostrated by comparative analysis and sensitivity analysis. Finally, some managerial suggestions are provided for strengthening the flood control capacity of metro stations.
Evaluate levels of 18 toxic and/or essential trace elements exposure in maternal and cord plasma during pregnancy at advanced maternal age
Authors: Gu Tingfei , Jia xiqoqian , Shi Huifeng , Gong Xiaoli , Ma Jinxi , Gan Zhihang , Yu Zhixin , Li Zhiwen , Wei Yuan
Published: September 2022

Pregnant women with advanced maternal age (AMA) are vulnerable to the surrounding environment exposure. Assessment of the trace elements in pregnant women living in specific areas is important for biomonitoring. However, the exposure levels and variation pattern of elements’ exposure during pregnancy is still controversial and attracting extensive public concern. Therefore, we aimed to evaluate exposure of 18 toxic and/or essential trace elements’ exposure in maternal plasma during pregnancy of AMA and in paired cord plasma. A total of 48 pregnant women with AMA were recruited in Peking University Third Hospital from 2018 to 2021. 18 elements of Maternal plasma in 1st, 2nd, 3rd pregnancy and paired cord plasma were measured by 7700x ICP-MS (Agilent Technologies, USA) and Elan DRC type II ICP-MS (The Perkin-Elmer Corporation, USA). Concentrations of Pb, Se, Fe, Zn, Mo all decreased during pregnancy, while Cu increased in the opposite. Interestingly, concentrations of Rb decreased first but subsequently increased. Elements as Al, Co, Se, Cu, Ni showed significantly lower levels in cord than in maternal plasma, while elements as Sr, Fe, Rb, Mn, Zn displayed significantly higher levels in cord than in maternal plasma. What’s more, positively-interacted clusters were found in Ni-Co-Cu-Al-Rb-Zn and Zn-Mn-Al-Pb in maternal blood. Similar positively-interacted clusters were found in Zn-Ni-Co, Zn-Ni-Fe, Mn-Al-Pb, Fe-Pb-Mn, Fe-Ni-Cu and Rb-Cu-Sb-Fe-Mn in cord plasma. Last but not least, correlations between paired maternal and cord blood samples for As, Sr and Mo were statistically significant, indicating that the fetus burden might reflect the maternal exposure to some extent. Admittedly, levels of toxic and essential elements in our cohort study were comparatively lower in the scientific literature.
Perceptions of the COVID-19 pandemic: a qualitative study with South African adults
Authors: Silubonde Takana M , Draper Catherine , Norris Shane
Published: September 2022

Introduction
In South Africa, public perceptions of the COVID-19 pandemic and risk mitigation measures remain mixed. To better understand health behaviours in the context of COVID-19, a qualitative study was conducted, which aimed to investigate perceptions relating to the COVID-19 pandemic among the South African adult population.
Methods
Twelve online focus groups were conducted across the following age groups: 18–34, 35–54, 55 + years old (total n = 70) in December 2021. Diversity across socioeconomic status, geographical areas, and urban and rural settings was maximised, with an equal representation of men and women. Focus groups were conducted, and audio recorded using an online platform, transcribed verbatim and thematically analysed using MAXQDA.
Results
The ten themes that were identified from the qualitative analysis were: 1) general perceptions of the pandemic and preventative measures; 2) economic and employment impacts; 3) educational impacts of the pandemic; 4) family and social issues; 5) emotional, social, and psychological impacts of the pandemic; 6) media during the pandemic; 7) government handling of the pandemic.; 8) Healthcare and other government systems; and 9) vaccination 10) solutions for COVID-19 and future pandemics. Participants generally reported an understanding and appreciation of the preventative measures put in place by government. However, the findings also showed that lack of government trust, communication by government of specific scientific information around COVID-19, and the pervasiveness of social media had affected the implementation of preventative measures. Moreover, the impacts of the pandemic were reported to vary with socio-economic level.
Conclusion
With the existing mistrust of government, there is need for government to leverage existing trusted sources in communities to aid in the implementation of preventative measures. These findings support the development of context specific solutions to address challenges faced at different socioeconomic levels.
LCAT activity, ox-LDL, and lipid profile in patients with endometrial carcinoma and diabetes mellitus: The interactive effect of concurrent disease
Authors: Qahremani Reihane , Rabizadeh Soghra , Mirmiranpoor Hossein , Yadegar Amirhossein , Mohammadi Fatemeh , Sahebi Leyla , Heidari Firouzeh , Esteghamati Alireza , Nakhjavani Manouchehr
Published: September 2022

Background: Decreased Lecithin-cholesterol acyltransferase (LCAT) activity, increased level of oxidized low-density lipoproteins (ox-LDL), and dyslipidemia in diabetes and cancer were studied. In this research, LCAT activity, ox-LDL, and lipid profile in patients with endometrial carcinoma, diabetes, and the combination of them, and healthy subjects were measured.
Objective: The aim of this study was the evaluation of lipid profile, LCAT activity, and ox-LDL level as an oxidative stress marker in three different pathologic conditions and comparison of them to healthy metabolic state.
Methods: In this case-control study, a total of 93 female participants were recruited. Participants were divided into four groups, including endometrial carcinoma with diabetes (EC with DM, n=19), endometrial carcinoma without diabetes (EC, n=17), diabetes (DM, n=31), and Healthy group (H, n=26). The level of LCAT activity, triglycerides (TG), total cholesterol, high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), and ox-LDL were measured.
Results: The LCAT activity was decreased in all patient groups compared to healthy controls (p-value<0.001). LCAT activity (nmol/ml/h) was significantly lower in endometrial carcinoma with or without diabetes (mean ± SD = 28.31 ± 2.78, 34.00 ± 4.97, respectively) than in patients with diabetes alone (46.58 ± 9.47). A higher level of TG and ox-LDL and a lower level of HDL-C were seen in all patient groups compared to the healthy controls (all p-values < 0.001). The decrease in LCAT activity (∆ LCAT= LCAThealthy - LCATpatient) was 31.61 in endometrial carcinoma with diabetes, 25.92 in endometrial carcinoma without diabetes, and 13.34 nmol/ml/h in diabetes alone.
Conclusion: A decrease in LCAT activity and an increase in ox-LDL level were seen in both endometrial carcinoma and diabetes. The combination of endometrial carcinoma and diabetes had a sub-additive effect on LCAT activity and ox-LDL level.
The effects of long-term molybdenum exposure in drinking water on molybdenum metabolism and production performance of beef cattle consuming a high forage diet
Authors: Thorndyke M. P. , Guimaraes O. , Medrado M. , Loh H. Y. , Tangredi B. V. , Reyes A. , Barrington B. K. , Schmidt K. , Tilquist N. M. , Li L. , Ippolito J. A. , Zervoudakis J. T. , Wagner J. J , Engle T. E.
Published: September 2022

Fifty-four multiparous beef cows with calves were used to evaluate the effects of Mo source (feed or water) on reproduction, mineral status, and performance over two cow-calf production cycles (553 d). Cows were stratified by age, body weight, liver Cu and Mo status, and were then randomly assigned to one of six treatment groups. Treatments were: 1) Negative control (NC; basal diet with no supplemental Mo or Cu); 2) Positive control (NC + Cu; 3 mg of supplemental Cu/kg DM); 3) NC + 500 µg Mo/L from Na2MoO4·2H2O supplied in drinking water; 4) NC + 1000 µg Mo/L of Na2MoO4·2H2O supplied in drinking water; 5) NC + Mo 1000-water + 3 mg of supplemental Cu/kg DM; and 6) NC + 3.0 mg of supplemental Mo/kg diet DM from Na2MoO4·2H2O. Animals were allowed ad libitum access to both harvested grass hay (DM basis: 6.6% crude protein; 0.15% S, 6.7 mg Cu/kg, 2.4 mg Mo/kg) and water throughout the experiment. Calves were weaned at approximately 6 months of age each year. Dietary Cu concentration below 10.0 mg Cu/kg DM total diet reduced liver and plasma Cu concentrations to values indicative of a marginal Cu deficiency in beef cows. However, no production parameters measured in this experiment were affected by treatment. Results suggest that Mo supplemented in water or feed at the concentrations used in this experiment had minimal impact on Cu status and overall performance.
Dimensionally Reduced Machine Learning Model for Predicting Single Component Octanol-Water Partition Coefficients
Authors: Kenney David H. , Paffenroth Randy C. , Timko Michael T. , Teixeira Andrew R.
Published: September 2022

MF-LOGP, a new method for determining a single component octanol-water partition coefficients LogP is presented which uses molecular formula as the only input. Octanol-water partition coefficients are useful in many applications, ranging from environmental fate and drug delivery. Currently, partition coefficients are either experimentally measured or predicted as a function of structural fragments, topological descriptors, or thermodynamic properties known or calculated from precise molecular structures. The MF-LOGP method presented here differs from classical methods as it does not require any structural information and uses molecular formula as the sole model input. MF-LOGP is therefore useful for situations in which the structure is unknown or where the use of a low dimensional, easily automatable, and computationally inexpensive calculations is required. MF-LOGP is a random forest algorithm that is trained and tested on 15,420 data points, using 10 features derived from the molecular formula to make LogP predictions. Using an independent validation set of 2,722 data points, MF-LOGP was found to have an average RMSE = 0.77 ± 0.007, MAE = 0.52 ± 0.003, and R2 = 0.83 ± 0.003. This performance fell within the spectrum of performances reported in the published literature for conventional higher dimensional models RMSE = 0.42–1.54, MAE = 0.09–1.07, and R2 = 0.32–0.95). Compared with existing models, MF-LOGP requires a maximum of ten features and no structural information, thereby providing a practical and yet predictive tool. The development of MF-LOGP provides the groundwork for development of more physical prediction models leveraging big data analytical methods or complex multicomponent mixtures.
Modulatory role of curcumin on cobalt-induced cognitive deficit, hippocampal oxidative damage, astrocytosis, and Nrf2 expression
Authors: Oria Rademene , Emeka Anyanwu , Esom Emmanuel , Nto Johnson , Katchy Amechi , Agu Augustine , Ijomone Omamuyovwi
Published: September 2022

Chemical overexposure is a growing environmental risk factor for many medical issues. Cobalt toxicity from environmental, industrial, and medical exposure, has previously been linked to neurological impairment. Hence, the current study looked into the neuroprotective potential of curcumin, a natural polyphenol contained in spice turmeric, against cobalt-induced neurotoxicity. Adult rats were randomly divided into six groups as follows: control, 40 mg/kg cobalt chloride (CoCl2) only, 240 mg/kg curcumin only, 120 mg/kg or 240 mg/kg curcumin or 100 mg/kg Vitamin C co-administered with CoCl2. The administration was via oral route daily for four weeks. After that, neurobehavioral tests were undertaken to evaluate short-term spatial memory. Biochemical investigation was performed to determine the hippocampal levels of status via measures of SOD, CAT, GST, and LPO). Furthermore, immunohistochemical assessment of the expression of GFAP and Nrf2 in the hippocampus was carried out. In the CoCl2 group, the results showed altered behavioral responses, a decrease in antioxidant activities, increased expression of GFAP and the number of activated astrocytes, and decreased immunoexpression of Nrf2. These effects were mitigated in the Curcumin and Vitamin C treated groups. These results collectively imply that curcumin enhances cognitive functions in rats exposed to cobalt possibly by attenuating oxidative responses, mitigating astrocytosis, and modulating Nrf2 signaling.
Histo-Fusion: A novel domain specific learning to identify Invasive Ductal Carcinoma (IDC) from Histopathological Images
Authors: Jawad M Abdul , Khursheed Farida
Published: September 2022

Today breast cancer is the leading type of cancer among women undergoing cancer screening. A slight delay in detecting and diagnosing this disease may result in irreversible convolutions. Histopathological images from the biopsy examination present a large amount of structural information that can significantly improve the prognosis for breast cancer. The pathological analysis, which involves the microscopic examination of the histopathological slides, is a challenging task. An automated computer-aided detection (CAD) procedure is inevitable, as it may decrease the pathologist examination time and help detect the disease at an early stage. Lately, deep learning methods using artificial neural networks are consistently in use to improve the performance of CAD methods. A common practice among recent studies is to use the transfer learning approach of training deep neural network architectures. Transfer Learning is an established learning approach that facilitates a deep neural network to train quickly on a specific dataset and resolve an interdisciplinary problem. Deep Learning methods employing the transfer learning approach have provided highly competitive results on the datasets consisting of the whole slide images, which are captured generally at high resolutions. However, the performance is not remarkably appreciable on the small and low-resolution image datasets, in particular the datasets that include patch samples. In this direction, the present study proposes a novel domain-specific learning strategy, Breast Histo-Fusion, which aims to detect breast cancer even from images of low resolution and small size. Further, four state-of-the-art deep CNNs (AlexNet, VGG19, ResNet, and DenseNet) are trained using both learning approaches: Transfer Learning and Histo-Fusion on the IDC dataset. The proposed Histo-Fusion learning approach has improved the discriminating abilities and performance of each deep CNN by providing better results of (AlexNet – 95.75%, VGG19–95.96%, ResNet34–96.17%, ResNet50–96.67%, and DenseNet121–97.49%) compared to (AlexNet – 90.41, VGG19–90.51%, ResNet34–90.83%, ResNet50–92.27%, and DenseNet121–93.05%) using the transfer learning strategy. As a result, the procedure can help expert pathologists to perform accurate diagnoses and reduce false-positive rates.