bluuebunny/crossref_metadata_2025_split huggingface dataset:
Addressing Depression and Comorbid Health Conditions through Solution-Focused Brief Therapy in an Integrated Care Setting: A Randomized Clinical Trial
Authors: Cooper Zach , Mowbray Orion , Ali Mohammed , Johnson Leslie 
Published: March 2024

Abstract

Background: Co-occurring physical and mental health conditions are common, but effective and sustainable interventions are needed for primary care settings.
Purpose: Our paper analyzes the effectiveness of a Solution-Focused Brief Therapy (SFBT) Intervention for treating depression and co-occurring health conditions in primary care.
Methods: A Randomized Clinical Trial was conducted at a rural federally qualified health center. Eligible participants scored ≥10 on the Patient Health Questionnaire (PHQ-9) and met criteria for co-occurring health conditions (hypertension, obesity, diabetes) evidenced by chart review. SFBT participants (n=40) received three SFBT interventions over three weeks in addition to treatment as usual (TAU). The control group (n=40) received TAU over three weeks. Measures included depression (PHQ-9) and anxiety (GAD-7), well-being (Human Flourishing Index), and SFBT scores, along with physical health outcomes.
Results: Of 80 consented participants, 69 completed all measures and were included in the final analysis. 80% identified as female and the mean age was 38.1 (SD 14.5). Most participants were White (72%) followed by Hispanic (15%) and Black (13%). When compared to TAU, SFBI participants had significant reductions in depression (baseline: M=18.17, SD=3.97, outcome: (M=9.71, SD=3.71) and anxiety (baseline: M=14.69, SD=4.9, outcome: M=8.43, SD= 3.79). SFBI participants also had significantly increased flourishing scores (baseline: M=58.37, SD= 16.36, outcome: M=73.43, SD= 14.70) when compared to TAU. Changes in BMI and blood pressure were not statistically significant.
Conclusions: SFBI demonstrated efficacy in reducing depressive and anxiety symptoms and increasing well-being.
Trial Registration: The study was pre-registered at ClinicalTrials.gov Identifier: NCT05838222 on 4/20/2023.
Predicting Big data Drug Interactions and associated side effects by Using Artificial Neural Networks (ANN) over Traditional Graph Convolutional Networks (GCNs)
Authors: IBRAHIM Abdullahi Abdu , Mohammed Tareq Abed , DARA Omer Nabeel 
Published: March 2024

Abstract
Rapid advances in machine learning have enabled the prediction of complex drug-drug interactions (DDIs) and associated harmful effects. This study aims to develop a neural network model that can predict drug-drug interactions (DDIs) for various side effects. Our study intends to create a reliable and easy-to-understand tool that can transform pharmaceutical research and healthcare by lowering polypharmacy risks. Our method begins with the careful selection and compilation of large datasets on medicine combinations, side effects, drug-side effect connections, and drug-protein interactions. We use an adjacency matrix to establish a drug-protein network. Then, we use PCA to shrink the network. Using artificial neural networks, our neural network is designed for binary categorization. This model is rigorously trained, validated, and tested using performance metrics to ensure its strength and adaptability. Our model has remarkable accuracy, with AUC-ROC scores of 98.67% for certain interactions. Reading and handling structured input is a major advantage of Artificial Neural Networks (ANNs) over Graph Convolutional Networks (GCNs). The findings demonstrate our approach's versatility in pharmaceutical research and healthcare, including medication development and real-time clinical decision help. To conclude, this study advances DDI prediction and management. Resilience, comprehensibility, and accuracy make the model a flexible polypharmacy solution. By solving DDI prediction and side effect control, our strategy might improve pharmaceutical research, patient safety, and healthcare results. This study shows how advanced machine learning may be used in pharmaceuticals.
Generation of cutting heat and simulation of coring tube wall temperature during coring in primary structure coal seam
Authors: MA Shujun , Wang Zhaofeng , Yue Jiwei , An Fenghua , Chen Haidong 
Published: March 2024

Abstract

When the drilling core method is used to determine the coalbed gas content, the cutting heat generated by the coring bit cutting coal will increase the coring tube temperature, and the excessively high coring tube temperature will have an heating effect on the coal core, which will accelerate the coal core gas desorption rate and increase the gas loss amount. The generation of cutting heat of coring bit and the measurement of coring tube temperature are the basis for grasping the gas desorption law of coal core and projecting the amount of gas loss. Firstly, the self-developed coring tube temperature measurement device was used to conduct on-site coring temperature measurement experiments at different cutting speeds. Then, the cutting temperature of coring bit was solved by establishing thermodynamic model for cutting coal and heat transfer model of cutting edge. Finally, based on the thermal conductivity characteristics of the coring tube, the coring tube temperature at different cutting speeds was simulated, and the simulated temperature was compared with the on-site measured temperature to verify the reliability of the model. The results show that when coring in primary structural coal, the temperature change trend of coring tube wall temperature measurement point at different cutting speeds is basically consistent, the temperature measurement point at the front end of the coring tube mainly goes through a relatively stable period in the drilling process, a sharp rising period in the cutting process, a slow rise and cooling period in the withdrawal process. However, the temperature measurement point at the back end of the coring tube wall mainly goes through a relatively stable phase and a slowly increasing phase. The temperature rise of the coring bit and the coring tube wall are significantly positively correlated with the cutting speed. When coring in hard coal seam and the coring depth is not large, the cutting heat generated by the coring bit and the coal body is the dominant factor for the temperature rise of the coring tube. The coring tube wall temperature calculated using the model matches well with the field measured temperature, and the error is small, which fully shows that the coring thermodynamic model is feasible. This study provides a basis for further research on the dynamic distribution characteristic of coal core temperature during coring, which is of profound significance to calculate the gas loss and coalbed gas content.
Efficacy of Local Agents Used in Premature Ejaculation Treatment
Authors: hamarat Mustafa , kafkaslı alper , kucuktopcu onur , Karatas Berk 
Published: March 2024

Abstract

Premature ejaculation is a common sexual dysfunction in men. Some topical anesthetic agents are used in the treatment to reduce the hypersensitivity of the glans. The number of patients in studies showing the effectiveness of topical agents is limited. This study aimed to evaluate the effects of a eutectic mixture of lidocaine and prilocaine-containing local anesthetic creams(EMLA), lidocaine spray, and benzocaine condoms on ejaculation, which are widely used in Turkey in premature ejaculation patients. Between November 2020 and December 2022, 273 male patients who were admitted to the andrology policlinic of the hospital and diagnosed with PE for life were included in the study. Age, body mass index, marriage periods, intercourse durations, relationship frequency, comorbidities, duration of intravaginal ejaculation latency time(IELT) before and 2 months after treatment and side effects of the patients after treatment were prospectively collected. Patients were divided into 3 groups. Group 1 consisted of patients using EMLA cream, respectively; group 2 consisted of patients using lidocaine spray, and group 3 consisted of patients using benzocaine condoms. 59 people in group 1, 126 in group 2, and 88 in group 3 were included in the study. Pre-treatment IELT values of Groups 1, 2, and 3 were 32.5+17.7 sec, 29.8+17.9 sec, and 30.1+13.9 s, respectively. Post-treatment IELT values were 104.5+135.81 sec, 144.1+179.8 sec, and 75.1+50.4 s, respectively. In all three groups, post-treatment IELT values were significantly higher than before treatment. Our study found that spray and EMLA cream significantly increased IELT duration compared to condoms. Although local treatments used in premature ejaculation are effective in the short term, further studies showing long-term efficacy are needed.
Hydrogeochemical Characteristics and Sulfate source of Groundwater in Sangu Spring Basin
Authors: Hou Xinwei , Li Xiangquan , Wang Zhenxing , Zhang Chunchao , Gui Chunlei , Zuo Xuefeng 
Published: March 2024

Abstract

Sangu Spring Basin is located in an important economic area，and groundwater is the main source of water for local life and industry. Understanding the sources of chemical components in groundwater is important for the development and utilization of groundwater. In this paper, we analyzed the origin of the chemical components of groundwater and their evolution in the Sangu Spring Basin using statistical analysis, Piper diagram, Gibbs diagrams, ion ratios, and combined hydrochemistry-isotope analyses. The results show that groundwater is the origin of atmospheric precipitation, the groundwater in stagnant and confined environment zones is formed under colder climatic conditions, and the surface water (SW) has a close hydraulic relation with the groundwater. Water-rock interaction is the main factor controlling the composition of groundwater. The compositions of groundwater are mainly derived from carbonate weathering, silicate weathering and dissolution of gypsum. Na+ and K+ in groundwater mainly come from the dissolution of albite and potassium feldspar, rather than rock salt. Ion exchange occurs in KGW and FGW, and the ion exchange is dominated by the exchange of Mg2+ and Ca2+ in the groundwater by Na+ and K+ in the rock or soil. De-dolomitization of KGW in deeply buried and stagnant flow zones occurred, causing elevated Mg2+ and SO42- concentrations. Nitrates and chlorides in groundwater are affected by a combination of agricultural activities, industrial activities, and weathering of rocks. Sulfate in groundwater is derived from dissolution of gypsum, infiltration of atmospheric precipitation and leakage of SW. Groundwaters with the highest sulfate content are located in the vicinity of SW, as a result of receiving recharge from SW seepage. Groundwaters with higher sulfate contents are located in the stagnant and deeply buried zones, where sulfate is mainly derived from the dissolution of gypsum. SW seepage recharges groundwater, resulting in the increased levels of Cl-, NO3- and SO42- in groundwater. These insights can provide assistance in groundwater protection and effective management.
Antibacterial Susceptibility of Bacteria Isolated from Wound Swab of Patient Receiving Medication in University Teaching Hospital, Gwagwalada, Abuja-Nigeria.
Authors: Amos Jimba Rai , Aigboeghian Egbenoma , Preciousgift Aigboeghian , Omolehin O.O. 
Published: March 2024

Abstract
This research examined the antibacterial sensitivity of bacteria isolated from wound infection. Ten samples were collected using swab stick. From the isolates of this research identified both Gram positive and Gram negative bacteria; these include Staphylococcus aureus, Staphylococcus epidermidis, Enterococci, Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, Enterobacter species. These organisms are of public health importance. Susceptibility outcome revealed that Ofloxacillin and ciprofloxacin were effective against Gram positive bacteria. Amikacin, Ciprofloxacin, Ceftriaxone and Norflaxacin were effective against Gram negative bacteria hence, the study indicate that Gram negative bacteria are more susceptible to antibiotic than Gram positive bacteria. Antimicrobial multi-resistant (AMR) was higher among Gram positive bacteria compared to Gram negative bacteria. Treatment of wound infection remains a significant concern for surgeons and physicians in a health care facility. The problem has been magnified due to the unrestrained and rapidly spreading resistance to the available array of antimicrobial agents. The study therefore, recommends multi-drug administration to patient suffering from wound infection, either caused by burn, accident or of any kind.
Regulation of lipid metabolism in grass carp hepatocytes by exosomes derived from fatty hepatocytes though GRP78
Authors: Yang Lulu , lu ronghua , Cao Kunkun , Chen Mengdi , Xu Xinxin , Cao Xianglin , Zhang Yuru , Nie Guoxing 
Published: March 2024

Abstract

Exosomes regulate lipid metabolism by carrying miRNAs, nucleic acids, and proteins, thereby influencing the function of receptor cells. Glucose-regulated protein 78 (GRP78) is also involved in the regulation of lipid metabolism. However, it remains unclear whether exosomes derived from fatty hepatocytes (OA-Exo) regulate lipid metabolism through the enrichment of GRP78. In this study, we observed lipid accumulation after incubating hepatocytes with oleic acid (OA) for 24 hours (fatty hepatocytes) (P < 0.05). Interestingly, the expression of GRP78 was significantly increased in fatty hepatocytes and OA-Exo (P < 0.05). We hypothesized that GRP78 plays an important role in the regulation of lipid metabolism. Subsequently, the hepatocytes were separately incubated with OA-Exo (50 µg/mL) and GRP78 protein (1 µg/mL) for 24 hours. The results showed a significant increase in the content of Triacylglycerol (TG) and total cholesterol (TC), as well as up-regulation of the expression of GRP78 and inositol-requiring enzyme-1alpha (IRE1α) protein (P < 0.05). It suggested that exosomal GRP78 promoted lipid accumulation in hepatocytes. Therefore, we used YUM70 (an inhibitor of GRP78) to inhibit endogenous GRP78, followed by incubation of hepatocytes with OA-Exo and GRP78 for 24 hours. Compared with the control group, the content of TG and the expression of GRP78 protein were significantly decreased in the YUM70 group (P < 0.05). However, when compared with the YUM70 group, OA-Exo reversed the effect of YUM70 and increased the content of TG, TC, and the expression of GRP78 protein in hepatocytes (P < 0.05). These results suggested that OA-Exo promoted lipid accumulation in hepatocytes through the recruitment of GRP78, and the IRE1α pathway may be important in this process. Furthermore, the inhibition of the IRE1α pathway with 4µ8C resulted in a significant decrease in TG content compared to the control group (P < 0.05). However, when compared with the 4µ8C group, OA-Exo and GRP78 reversed the effect of 4µ8C and significantly increased TG content (P < 0.05). Taken together, these results indicated that OA-Exo activated IRE1α to promote lipid accumulation in hepatocytes through the enrichment of GRP78. This study provided a new perspective for further exploration of exosomal lipid metabolism in fish.
Carbothermal Reduction Behavior of Micro-silica
Authors: Li Fei , Wu HanZe , Fu WangWang , Kang YuXuan , Xia FanQin 
Published: March 2024

Abstract
Micro-silica, a predominant byproduct of industrial silicon enterprises, presents a substantial opportunity for recycling within the production of industrial silicon. In this study, we utilized micro-silica procured from an industrial silicon facility and commercially accessible N991 carbon black as experimental materials. We scrutinized the influence of micro-silica and carbon black on the yield and velocity of SiC formation under varying conditions: temperatures of 1625°C, 1650°C, and 1675°C (1898 K, 1923 K, and 1948 K), disparate CO partial pressures, and diverse SiO2 to C molar ratios. Our findings reveal that micro-silica initiates melting at a threshold of 1600°C. At a temperature of 1650°C, the loss rate of SiO is minimized, resulting in the highest reaction matching degree. Elevated temperatures and increased CO partial pressures correspond to accelerated reaction rates. The reaction of molten SiO2 and CO accelerates the carbothermal reduction reaction rate. A harmonious correlation was observed between the SiO2 reactivity of the micro-silica and the SiO reactivity of the carbon black. The reaction between SiO2 and SiC in the molten state increases the weight loss rate and the reaction rate. The optimal agglomerate composition was determined to be mol(SiO2): mol(C) = 1:3.
Family history of dementia and brain health in childhood and middle age: a prospective community-based study
Authors: Hussainali Rowina Farzia , Schuurmans Isabel K. , Zijlmans Jendé L. , Cecil Charlotte A. M. , Vernooij Meike W. , Luik Annemarie I. , Muetzel Ryan L. , Ikram M. Arfan , Wolters Frank J. 
Published: March 2024

Abstract

Objectives We aimed to determine the association of family history of dementia with structural brain measures and cognitive performance in childhood and mid-life adulthood.
Methods We studied 1,259 parents (mean age: 47.3 years, standard deviation: 4.7) and 866 of their children (mean age 9.9 years standard deviation: 0.5) of the population-based Generation R Study. Parents filled in a questionnaire on family history, and both parents and children underwent cognitive assessment and neuroimaging.
Results Of all participants, 109 parents (8.6%) reported a parental family history of dementia and 73 children (8.4%) had a grandparental history of dementia with mean age of dementia diagnosis in those affected 75 years (± 7.3) We observed no associations of dementia family history with cognitive ability in either parents or their children, except for worse manual dexterity in parents with a parental history of dementia, compared to those without (mean difference [95%CI]: -1.28 [-2.26; -0.30]). In parents and children, subclinical brain health did not differ significantly by family history. Results were consistent across age, sex, and APOEgenotype.
Discussion Family history of dementia was associated with worse manual dexterity in mid-life adulthood, but not with any other measures of cognitive ability or subclinical brain health in childhood and mid-life. These findings suggest that the association of family history with dementia risk is due chiefly to neurodegenerative rather than neurodevelopmental processes, and might first present with motor deficits.
The Use of Machine Learning Techniques and Distance Measures in Capturing Collusive Pricing:
A Case Study for Algorithmic Pricing in E-Commerce Industry
Authors: Yalçın Yalçıner , Öztürk Selcen 
Published: March 2024

Abstract

The rapid progress of “Machine Learning” (ML) and “Artificial Intelligence” (AI) is altering the dynamics of competition such as pricing and production, market regulation and common understanding of economies. This paper examines the complex link between algorithmic pricing strategies and contemporary market dynamics, offering insights into their multi-layered implications. Our findings indicate a systematic relationship between algorithmic pricing and competitive dynamics. Price dispersion grows with the possibility of being an algorithmic seller in online sale of milk products, indicating a non-collusive pricing strategy takes place. On the other hand, quality differences and higher production within a market may result in a collusive pricing scheme in online markets where pricing choices are made by machines.
JEL Classification: C51, D43, L41
Derivation and Validation of a Clinical Predictive Model for Longer Duration Diarrhea among Pediatric Patients in Kenya using Machine Learning Algorithms
Authors: Ogwel Billy , Mzazi Vincent , Awuor Alex O. , Okonji Caleb , Anyango Raphael O. , Oreso Caren , Ochieng John B. , Munga Stephen , Nasrin Dilruba , Tickell Kirkby D. , Pavlinac Patricia B. , Kotloff Karen L. , Omore Richard 
Published: March 2024

Abstract

Background
Despite the adverse health outcomes associated with longer duration diarrhea (LDD), there are currently no clinical decision tools for timely identification and better management of children with increased risk. This study utilizes machine learning (ML) to derive and validate a predictive model for LDD among children presenting with diarrhea to health facilities.
Methods
LDD was defined as a diarrhea episode lasting ≥ 7 days. We used 7 ML algorithms to build prognostic models for the prediction of LDD among children < 5 years using de-identified data from Vaccine Impact on Diarrhea in Africa study (N = 1,482) in model development and data from Enterics for Global Heath Shigella study (N = 682) in temporal validation of the champion model. Features included demographic, medical history and clinical examination data collected at enrolment in both studies. We conducted split-sampling and employed K-fold cross-validation with over-sampling technique in the model development. Moreover, critical predictors of LDD and their impact on prediction were obtained using an explainable model agnostic approach. The champion model was determined based on the area under the curve (AUC) metric.
Results
There was a significant difference in prevalence of LDD between the development and temporal validation cohorts (478 [32.3%] vs 69 [10.1%]; p < 0.001). The following variables were associated with LDD in decreasing order: pre-enrolment diarrhea days (55.1%), modified Vesikari score(18.2%), age group (10.7%), vomit days (8.8%), respiratory rate (6.5%), vomiting (6.4%), vomit frequency (6.2%), rotavirus vaccination (6.1%), skin pinch (2.4%) and stool frequency (2.4%). While all models showed good prediction capability, the random forest model achieved the best performance (AUC [95% Confidence Interval]: 83.0 [78.6–87.5] and 71.0 [62.5–79.4]) on the development and temporal validation datasets, respectively.
Conclusions
Our study suggests ML derived algorithms could be used to rapidly identify children at increased risk of LDD. Integrating ML derived models into clinical decision-making may allow clinicians to target these children with closer observation and enhanced management.