bluuebunny/crossref_metadata_2025 huggingface dataset:
The Effect of Resistance Training for Elderly with Mild Cognitive Impairment and Frailty: A Randomized Controlled Trial
Authors: Wu Ting-Ting , Wang Xiao-Xia , Xu Yi-Fei , Zhang Chu-Fan , Huang Mei-Zhen , Li Hong
Published: March 2024

Background: Cognitive decline and the progression to dementia are hastened in individuals with Mild Cognitive Impairment (MCI) and frailty. Exercise interventions benefit cognitive function in patient with MCI. While the optimal implementation of resistance training for MCI and frailty is still being explored. The aims of this study were to develop and evaluate the effect of a novel, hybrid online-offline resistance training regimen for the MCI and frailty cohort.
Methods: In this double-blind, randomized controlled trial, 68 elderly individuals with MCI and frailty were enrolled and allocated to either a resistance training program or a standard elderly fitness exercise regimen. The resistance training, designed based on the intervention mapping framework, comprised a 12-week hybrid intervention, blending online and offline sessions, conducted three times a week. The primary outcomes measured were global cognitive function and physical function. Data analysis was conducted meticulously using covariance analysis, with a commitment to the intention-to-treat principle.
Results: The hybrid online-offline resistance training regimen was both safe and feasible. Participants in the resistance training group exhibited significantly greater improvements in global cognitive function (F=6.289, p=0.011) and 4-meter walk time (F=10.951, P=0.002), with effect sizes of 1.299 (95% CI: 0.306 to 2.291) and -0.576 (95% CI: -0.924 to -0.228), respectively. Furthermore, resistance training proved more effective in boosting attention and enhancing quality of life. Between the groups, no significant differences were noted in executive, language, and memory functions, as well as in measures of anxiety, depression, and self-efficacy, among other aspects.
Conclusions: Our study demonstrated that a hybrid online-offline resistance training model is safe and effective for elderly with MCI and frailty, showing superior benefits over traditional exercises in enhancing global cognitive function, attention, physical function and quality of life.
Trial registration: ChiCTR2200057685 was registered on 04/03/2021.
RETRACTED: The investigation of mechanism isoniazid adsorption onto cassia fistula-based activated carbon
Authors: Murti Restu Hikmah Ayu , Jawwad Muhammad Abdus Salam , Sheng-Jie You , Ya-Fen Wang
Published: March 2024

The authors have requested that this preprint be removed from Research Square.
Preoperative cardiac structural changes are associated with subcortical nuclei changes and neurocognition in preschool-aged children with tetralogy of Fallot after corrective surgery
Authors: Hu Liang , Wu Kede , Li Huijun , Zhu Meijiao , Zhang Yaqi , Fu Mingcui , Tang Minghui , Lu Fan , Cai Xinyu , An Jia , Patel Nishant , Lin Ye , Zhang Zhen , Yang Ming , Mo Xuming
Published: March 2024

Background: Neurocognitive disorders are common in cyanotic congenital heart disease (CCHD). Preoperative cardiac structural changes have been known to cause hemodynamic abnormalities that lead to a series of events including hypoxia episodes, brain abscesses, atrial fibrillation and cerebrovascular accidents neurodevelopmental outcomes. We aimed to evaluate subcortical nuclei changes and neurocognition following corrective surgery in tetralogy of Fallot (TOF) children and analyze their relationship with preoperative cardiac structural changes.
Methods: In this study, thirty-six repaired TOF children and twenty-nine healthy children (HC) were recruited. Three-dimensional (3D) T1-weighted high-resolution structural images and the Wechsler preschool and primary scale of intelligence-Fourth edition (WPPSI-Ⅳ) were used to assess the cognitions between children with TOF and HCs.
Results: Significant subcortical nuclei differences were found in the left amygdala nucleus (LAM), left thalamus proper nucleus (LTHA) and right thalamus proper nucleus (RTHA) between children with TOF and HC. Impaired left amygdala nucleus integrity which was inversely related to the size of the preoperative VSD, was correlated with the working memory index in TOF.
Conclusions: This study demonstrated subcortical nuclei structure injury possibly caused by cardiac abnormal anatomical malformations, and this injury is related to worse working memory performance in preschool-aged children with TOF. These findings suggested that LAM may be a potential biomarker of neurocognitive impairments in TOF and can be used to predict future neurodevelopmental outcomes, which also provide new insights into the underlying neurophysiological mechanisms of neurocognitive impairments in TOF.
Preparation and Characterization of Ox Bone Powder and Bamboo Fibers Reinforced Hybrid Epoxy Composites
Authors: Molla Yonas , Belay Mezigebu
Published: March 2024

Composite materials are one of the fastest growing due to their high specific strength, stiffness, and versatile application in various fields. This study aimed to develop an ox bone powder and bamboo fiber-reinforced hybrid epoxy composite for stock and bumper applications and investigate the effect of the reinforcements on the composite's mechanical properties.. The reinforcements used in this work were random orientations of animal bone (ox) powder of 75 microns and bamboo fiber. The matrix used for this work was epoxy resin. Composite materials were prepared using the hand layup method with a 40% weight fraction of reinforcement (bone powder and bamboo fiber) and a 60% weight fraction of epoxy resin matrix. Five different combinations of bone powder and bamboo fiber with a fixed amount of epoxy resin were used for this work. The combinations of bamboo fiber and bone powder were: 40% bamboo fiber with 0% bone powder; 30% bamboo fiber with 10% bone powder; 20% bamboo fiber with 20% bone powder; and 0% bamboo fiber with 40% bone powder. The mechanical properties studied were compressive strength, impact strength, and flexural strength. In addition, water absorption was studied for all combinations. The maximum results of the flexural and impact strengths were 278.91 MPa and 7.5 J/m, respectively, at a 0:40 (bone powder: bamboo fiber) composite. The maximum compressive strength and the lowest absorption obtained were 283.3 MPa and 1.05%, respectively, at the 40:0 (bone powder: bamboo fiber) composite. For the hybrid composite case, optimal flexural and impact strengths were 236.78 MPa and 6.66 J/m, respectively, and water absorption was 1.52% at 10:30 (bone powder: bamboo fiber). Since reasonable flexural strength, impact strength, and water absorption were obtained with the hybrid composite of 10:30 (bone powder: bamboo fiber), this combination of the hybrid composite is recommended for stock and bumper applications.
Male Partners` Involvement in Antenatal Care and its Associated Factors: A Community-based Cross-sectional study, Westcentral Ethiopia
Authors: Gessesse Nigusu Ayalew , Gela Getahun Belay , Aweke Amlaku Mulat , Balcha Wondu Feyisa , Chekole Fentahun Alemnew , Beyene Fentahun Yenealem , Kassahun Eden Asmare , Getu Alemwork Abie , Alemayehu Bezawit Abeje , Gezahegn Tigist Wubet , Getie Simegnew Asmer , Adugna Kebede Feyisa
Published: March 2024

Background
Male partner involvement in antenatal care has been recognized as a key factor in reducing maternal and neonatal mortality. However, little attention has been given to male partners’ involvement in maternity care, particularly in developing countries.
Objective
This study aimed to assess male partners’ involvement in antenatal care and its associated factors among male partners whose wives gave birth within the last one-year in Bichena town, Westcentral, Ethiopia, 2019.
Methods
A community-based cross-sectional study design was conducted from March 1 to 15/2019, in Bichena town, among 406 male partners. The data was collected by a simple random sampling technique and analyzed using the Statistical Package of the Social Science 23.0 version. Bivariate and multivariable logistic regression analyses were employed to estimate the crude and adjusted odds ratio with a confidence interval of 95% and a P-value of < 0.05 considered statistically significant. Frequency tables, figures, and descriptive summaries were used to describe the study variables.
Results
In this study, 53.4% [95% CI: 48.3–58.1%] of male partners` were involved in antenatal care. The age group of 20–29 years [AOR = 2.14, 95% CI = 1.04–4.38], having primary, secondary, and diploma and above educational level [AOR = 2.04, 95% CI = 1.02–4.07], [AOR = 3.02, 95% CI = 1.49–6.11] and [AOR = 4.03, 95% CI = 2.06–7.89] respectively, ≤ 10 years marriage length [AOR = 2.92, 95% CI = 1.46–5.87], good knowledge of the services provided in antenatal care visits [AOR = 2.68, 95%, CI = 1.62–4.42], good awareness of the danger signs of pregnancy [AOR = 1.77, 95 CI = 1.10–2.85], favorable attitude towards antenatal care visit [AOR = 2.62, 95% CI = 1.64–4.19], travel less than 15 minutes to reach a nearby health facility [AOR = 3.43, 95% CI = 1.54–7.65] and making decision together to seek care in health facility [AOR = 2.44, 95% CI = 1.19–5.03] were associated with male partners involvement in antenatal care.
Conclusions
Male partners' involvement in antenatal care was encouraging in the study area compared to previous studies done in Ethiopia. We suggest strengthening awareness creation among male partners on their shared responsibility during pregnancy. Male partners should be invited to attend the antenatal care and making the antenatal care visiting times flexible is also needed.
A small neural network deployed on edge devices for detecting citrus Huanglongbing.
Authors: Tang Weijie , Shi Yu , Chen Hang , Liu Haifeng , Zhong Linyi , Chen Wenli
Published: March 2024

Citrus Huanglongbing (HLB) poses a significant threat to the profitability of the citrus industry worldwide. In traditional agricultural practices, manually identifying citrus trees infected with HLB based on certain leaf characteristics is time-consuming, subjective, and inefficient. The initial automatic identification of citrus Huanglongbing (HLB) relies on traditional image processing and machine learning algorithms, exhibiting low accuracy and slow processing speed. In order to enhance both the detection accuracy and speed, researchers have introduced deep learning methods based on neural networks for the identification of citrus HLB. However, the neural network models currently used for citrus leaf HLB identification have large parameter sizes, high deployment costs, and require high computational power, making them unsuitable for deployment on edge devices for field detection. Therefore, in order to promptly detect and address diseased plants, improve farmers' agricultural operational efficiency, ensure the accessibility of deep learning in small-scale agriculture, and address the need for cost-effective measures, there is an urgent need for a low-cost deep learning framework. Therefore, we compared the performance of several commonly used deep convolutional neural networks in industry for citrus Huanglongbing (HLB) detection. We constructed image classification networks based on AlexNet, ResNet, MobileNet-V1, and MobileNet-V3, and evaluated the network models based on model size, parameter count, and classification performance. As a result, we proposed a deep learning-based method for detecting citrus HLB. This method has a small model parameter count, low computational cost, fast detection speed, and high detection accuracy. It can be deployed on edge devices or other embedded devices. This method has a small model parameter count, fast detection speed, and high accuracy. The classification task is achieved by training the overall feature extraction network and the classification network at the network's tail on the constructed training set. The actual detection results show that the detection accuracy for healthy citrus leaves reaches 99.02%, and for HLB-infected leaves, the detection accuracy reaches 99.07%. The overall accuracy is 99.04%. Both recall and precision rates are excellent, meeting the precision requirements for on-site detection.
Convective Dynamics of Swarming Enzymatic Nanomotors
Authors: Sánchez Samuel , Chen Shuqin , Peetroons Xander , Bakenecker Anna , Lezcano Florencia , Aronson Igor
Published: March 2024

Enzymatic nanomotors harvest kinetic energy through the catalysis of chemical fuels. When a group of self-propelled nanomotors is placed in a fuel-rich environment, they assemble into ordered groups and exhibit intriguing swarming behaviors akin to the self-organization observed in bacterial colonies, bioconvection of aerobic microorganismal suspensions, and the coordinated movements of fish, ants, and birds. This swarming behavior presents numerous advantages compared to individual nanomotors, including expanded coverage and prolonged propulsion duration. However, the physical mechanisms underlying the swarming have yet to be fully elucidated. Our study investigates the formation of enzymatic swarms using experimental analysis and computational modeling. We show that the directional movement of enzymatic nanomotor swarms is due to their solutal buoyancy. We investigated various factors that impact the movement of nanomotor swarms, such as particle concentration, fuel concentration, fuel viscosity, and vertical confinement. We examine the effects of these factors on swarm self-organization to gain a deeper understanding. In addition, the urease catalysis reaction produces ammonia and carbon dioxide, accelerating the directional movement of active swarms in urea compared with passive ones in the same conditions. The numerical analysis agrees with the experimental findings. Our findings are crucial for the potential biomedical applications of enzymatic nanomotor swarms, ranging from enhanced diffusion in bio-fluids and targeted delivery to high- efficiency cancer therapy.
A study on urban street garbage detection based onYOLOX
Authors: Li Lingqiao , Zhang Hongwei , Lu Feng , Wang Zhuojian , Lu Huan
Published: March 2024

Urban street garbage detection is a pressing issue for governments at all levels. The traditional manual detection method isbecoming inadequate to keep up with the demands of urban expansion. We must implement a more innovative approach toreplace it. Swift progress in object identification technology has provided a new method for identifying litter on city streets. Theexisting street waste detection is hindered by inadequate datasets and visual features that do not align with the semanteme.There is still a significant gap to cover in utilizing target detection technology for street litter detection. As a result, weproposed a new approach to tackle deficiencies in the dataset for detecting waste in urban streets. It includes a technique forexpanding data that can assist in resolving the problem of an incomplete dataset. In addition, we have introduced a ContextualTransformer (CoT) module based on YOLOX-S, which enables us to harmonize the disparity between visual characteristicsand semantics. By enhancing the aforementioned techniques, our approach achieves a 9% increase in detection accuracycompared to the original YOLOX-S on the identical dataset. Ultimately, it attains a precision of 92.82% in the mean AveragePrecision (mAP) statistic.
Landslide Susceptibility Mapping using Geospatial framework -A Study of Pinder Basin, Chamoli District, Uttarakhand, India
Authors: Naik Deepa D , Palakuzhiyil Yadu
Published: March 2024

The study of the landslides in the Himalayan catchment is crucial due to adverse climatic conditions, increasing anthropogenic activities, and infrastructure management. The Pinder valley falls under Uttarakhand's seismic zone (IV & V). There are many proposed and operational hydropower stations across the catchment, which is increasing the risk of landslides. The widespread digging and tunnelling in the mountain scape make the area vulnerable. As per the Geological Survey of India, villages around Pinder witness many landslides every year. Due to such hydropower projects, landslides have increased (Matu Jansangthan et al., 2016). There are various techniques to study landslides here in this work, a GIS-based spatial multicriteria method and statistical model used to create the Landslide hazard zonation Map (LZM) for the Pinder Basin. This paper considered nine causative elements: slope angle, slope aspect rainfall, lithology, land use land cover and fault, lineament, road, and stream buffer. In this research, considering the historical landslide inventory of Geological survey of India, it is investigated that 20% of the area (GIS-based AHP model) is highly vulnerable and susceptible to landslides. The frequency ratio (Statistical Model) shows around 32% of the area is susceptible to high landslides, which are majorly observed nearer to the mainstream. Studying landslides is essential for stakeholders, policymakers, the landslide hazard zonation map are influential, proactive decision-making tools that prevent economic losses and property damage. Utilizing such models can enhance their resilience and longevity. It also plays a vital role in ecological restoration, sustainable land management, and planning.
Urban Predatory Birds: Unveiling the impact of urban variables on Diversity and Guild Structure in a Neotropical Megacity
Authors: Casas Daniel Augusto Montejo , Parrado-Rosselli Ángela
Published: March 2024

Urbanization poses a considerable threat to biodiversity and ecosystem services, particularly affecting fauna through loss of connectivity, habitat reduction, and limited green spaces. In response, the concept of eco-urbanism has emerged, introducing contrasting urbanization models advocating either a compact city with intensive land use and limited green spaces, coupled with conservation in peri-urban natural areas, or a dispersed city with a large, occupied area, coexisting with natural/green areas. Focusing on predatory birds in Bogotá, a Latin American mega-city, this study evaluates their response to urban variables along a forest (peri-urban)-urban gradient. We evaluated how gray urban variables (e.g. construction index, occupancy index, urban compactness) and green urban variables influence predatory bird diversity and guild structure. Our findings revealed contrasting impacts of gray infrastructure, with construction and occupancy indexes negatively affecting bird communities. Positive influences on diversity and abundance were associated with native plant species richness, herbaceous vegetation, and less impervious surface, particularly in green areas. Interestingly, migratory species exhibited positive associations with gray urban variables, potentially attracted by warmer urban temperatures and increased artificial lighting. The study highlights the contrasting impacts of the "land sparing" and "land sharing" models, indicating that neither inherently supports predatory bird communities. Instead, the effective influence and management of specific variables will be crucial for sustaining predatory bird communities within urban landscapes. This research contributes valuable insights into urban planning practices to support diverse predatory bird communities in megacities, highlighting the significance of studying trophic guilds as sensitive indicators of environmental changes.
Predicting graft survival in paediatric kidney transplant recipients using machine learning
Authors: Aksoy Gulsah Kaya , Akçay Hüseyin Gökhan , Arı Çağlar , Adar Mehtap , Koyun Mustafa , Çomak Elif , Akman Sema
Published: March 2024

Identification of factors that affect graft survival in kidney transplantation can increase graft survival and reduce mortality. Artificial intelligence modelling enables an impartial evaluation of clinician bias. The objective of this study is to examine the factors that affect the survival of grafts in paediatric kidney transplantation through the use of machine learning.
Methods
A retrospective review was conducted on records of paediatric patients who underwent kidney transplantation between 1994 and 2021 and had a post-transplant follow-up of more than 12 months. The nearest neighbour method was used to impute missing fields from a total of 48 variables in the dataset. Models including Naive Bayes, logistic regression, support vector machine (SVM), multi-layer perceptron and XGBoost were trained to predict graft survival. The study used 80% of the patients for training and the remaining 20% for testing. The modelling's success was evaluated based on the accuracy and F1 score metrics.
Results
The study analysed 465 kidney transplant recipients. Of these, 56.7% were male. The mean age at transplantation was 12.08 ± 5.01 years. Of the kidney transplants, 73.1% (n = 339) were from living donors, 34.5% (n = 160) were pre-emptive transplants, and 2.2% (n = 10) were second-time transplants. The machine learning model identified several features associated with graft survival, including antibody-mediated rejection (+ 0.7), acute cellular rejection (+ 0.66), eGFR at 3 years (+ 0.43), eGFR at 5 years (+ 0.34), pre-transplant peritoneal dialysis (+ 0.2), and cadaveric donor (+ 0.2). The successes of the logistic regression and SVM models was similar. The F1 score was 91.9%, and the accuracy was 96.5%.
Discussion
Machine learning can be used to identify factors that affect graft survival in kidney transplant recipients. By expanding similar studies, risk maps can be created prior to transplantation.
Surface Passivation of Carbon Dots for Tunable Biological Performance
Authors: Mikhail Mary M. , Ahmed Hanan B. , Abdallah Amira E. M. , El-Shahat Mahmoud , Emam Hossam E.
Published: March 2024

Recent investigations were shifted this trend toward exploring the biomedical applicability of CDs, relevant to chronic diseases. Herein, a systematic approach is demonstrated for studying tuning of optical character and biological performance for different surface passivated CDs. Alginate and pectin were successfully clustered oxygen-surface passivated CDs, while, chitin was used to nucleate nitrogen-surface passivated CDs. Pectin-treated with base (4.1 ± 1.8 nm) and chitin-treated acid (3.5 ± 1.7 nm) were ingrained the smallest O-surface passivated CDs and N-surface passivated CDs, respectively. However, N-surface passivated CDs were shown with the highest optical activity. CDs colloids prepared from alginate, pectin & chitin, resulted in reduction of tumor cell viability percentage to be 80.8%, 74.0% & 69.0% respectively. O-surface passivated CDs nucleated from alginate showed the highest anti-proliferative effects. Moreover, O-surface passivated CDs (from alginate) showed the supremacy in inhibition of inflammation, while, increasing of its concentration ten times resulted in significant increment in inhibition percent to be 28% & 42%, using 1 μg/mL & 10 μg/mL, respectively. So, O-surface passivated CDs (from alginate) can be applied as concurrent anti-inflammatory/antitumor drug, so as a potential therapeutic for treatment of inflammation, in production of vaccines, immune-therapeutics, and immune-suppressive drugs.
A Novel Cuckoo Search-Based Optimized Deep CNN Model for Phishing Attack Detection in IoT Environment
Authors: Gupta Brij B. , Gaurav Akshat , Attar Razaz Waheeb , Arya Varsha
Published: March 2024

There is a serious risk to information privacy and security in the IoT ecosystem from phishing attacks. This research offers a unique strategy for increasing phishing attack detection by employing the Cuckoo Search algorithm to tune hyperparameters in a deep Convolutional Neural Network (CNN) model. Our suggested approach is very effective, with a 90\% success rate in detecting phishing attacks. To distinguish between legal and fraudulent IoT network activity, we systematically tune hyperparameters using Cuckoo Search to optimise the deep CNN model's performance. This study helps ensure the safety of sensitive information and IoT devices by providing a novel and effective approach for real-time phishing detection.
A comparison of feed forward and recurrent neural networks in time series forecasting
Authors: charef charef Fahima
Published: March 2024

Exchange rate prediction has been treated as a key research matter in international finance because it’s a crucial and an important subject. For this reason, many researchers have sought to develop an accurate technique to forecast series of exchange rates. In this same context, this paper targets at making a comparison between two neural networks architectures, such as RNN( Recurrent Neural Networks) and FFNN (Feed Forward Neural Networks), to forecast the series of exchange rates as USD/NOK, USD/EUR for a daily frequency extending from november 2017 throught november 2022 either 1305 observations. In order to evaluate and compare the quality and performance of these approaches, we have resorted to MSE( Mean Square Error).
The back propagation method is used as the basis for developing algorithms capable of forecasting the series of exchange rates. To our knowledge, this is the only paper that focuses on the comparison between two techniques of neural networks, such as RNN and FFNN for predicting exchange rates.
The results clearly show that the recurrent neural network approach (RNN) yielded the highest prediction accuracy, and it’s more robust and more efficient in forecasting compared to the Feed Forward Neural Network model (FFNN). It’s, therefore, the most recommended.
Exploring the Dimensions of Mental Healthcare Accessibility for Vulnerable Migrant Groups and Actions to Improve Access: A Qualitative Study Conducted in Munich, Germany
Authors: Baierl Sophia , ÖCEK ZELİHA ASLI , Jung-Sievers Caroline , Coenen Michaela
Published: March 2024

Background: The experience of migration is often associated with stressors that affect mental health. Furthermore, migrants face barriers to accessing mental healthcare. This study aims to explore the dimensions influencing mental healthcare access for migrants in Munich, Germany and to develop recommendations for action.
Methods: The study used a two-phase qualitative approach. Phase 1 included individual interviews with 24 migrants from three vulnerable groups (students, refugees, and LGBTQ+ people). Based on the data gathered, seven interviews with health professionals experienced in mental health services for migrants were conducted in Phase 2. The framework from Levesque et al. was applied for analyzing and conceptualization of the dimensions of healthcare access. The health professionals’ proposed actions were grouped based on their respective levels as macro, meso, and micro. Validation was achieved by reviewing the data analysis during a meeting attended by all authors and a professional who was not involved in the interviews.
Results: The dimensions of mental healthcare access encompassed: 1) ability to perceive mental problems, including stigma and knowledge about mental health; 2) ability to seek care, encompassing knowledge about the new healthcare system and social support; 3) acceptability of services, involving provider identity and gender; 4) availability and affordability, including insurance coverage, bureaucratic processes, and capacity and geographical distribution of services; 5) appropriateness including providers’ and patients’ understanding of mental healthcare, and providers’ competence. Language and culture exhibited a strong interplay across all dimensions. The analysis yielded 17 action recommendations. Macro-level recommendations target barriers caused by discrimination and inequality. Meso-level recommendations included increased care capacity and coordination and eliminating language and culture barriers in health services. The micro-level recommendations included activities to promote mental health.
Conclusion: Migrants face numerous barriers to mental healthcare due to health system and providers in Munich. However, culture and language remain the most important access factors, necessitating social support. Actions pertaining to acceptability, accessibility, affordability, and appropriateness of health services are required to ensure that all individuals, including migrants, have access to mental healthcare. However, improving migrant mental health begins with the removal of structural barriers created by discrimination and inequality at the macro level.
Zfp36l1b is a marker of poor prognosis in Hepatocellular carcinoma suppression metastasis
Authors: Chen Jing , Cheng Wenhua , Chen Pinggui , Li Yaoxuan , Liu Ting , Liu Jingmei , Chen Yongjing , Li Gaopeng , Zhang Bo , Gao Zefeng
Published: March 2024

Background & Aims: Given the pivotal role of Zfp36l1b in angiogenesis, proliferation and migration of endothelial cells, we aimed to explore its role in HCC metastasis.
Methods: Zfp36l1b expressions in HCC tissues and cells were assessed by qRT-PCR, western blot and immunohistochemistry. The effect of Zfp36l1b on HCC metastasis was studied in vitroand in vivo.
Results: Zfp36l1b was frequently down-regulated in HCC and its expression level was significantly associated with aggressive clinicopathological features and overall and disease-free survival of HCC patients after hepatectomy. Loss of Zfp36l1b markedly promoted HCC cells invasion and migration in vitro, and facilitated tumor metastasis in vivo.
Conclusions: Zfp36l1b contributes to the development and progression of HCC as an anti-oncogene and may serve as a valuable prognostic marker for HCC patients.
A Novel amino acid metabol-Related Gene Signature to Predict Overall Survival of Esophageal Squamous Cell Carcinoma
Authors: Xu Kebing , Lin Zhizhong , Lin Yijin , Shen Yongshi , Chen Juhui , Chen Yuanmei , Xu Yuanji , Xin Yong
Published: March 2024

Esophageal squamous cell carcinoma (ESCC) is known as low early diagnosis rate and poor prognosis survival. Effective prognostic markers are urgently required to predict outcome for ESCC treatment. Accumulating evidence supports a strong relationship among cancer cell growth and amino acid metabolism. This work focused on the comprehensive evaluation of the association between amino acid metabolism-related gene (AAMRGs) expression profiles and prognosis in ESCC patients based on The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). 2 AAMRGs (BCAT1 and MMACHC) were selected to develop a novel AAMRGs -related gene predictor for 1-year and 2-years prognostic risk in ESCC patients. Both BCAT1 and MMACHC expression were verified by RT-qPCR. Prognosis nomogram by incorporating clinical factors and BCAT1 and MMACHC gene expression was constructed and the calibration plots illustrated good prognostic performance. In summary, the AAMRGs signature presented in our study is efficient and holds potential for clinical use in forecasting the prognosis of ESCC.
Deficits in Prosodic Speech-in-Noise Recognition in Schizophrenia Patients and Its Association with Psychiatric Symptoms
Authors: She Shenglin , Gong Bingyan , Li Qiuhong , Xia Yu , Lu Xiaohua , Liu Yi , Wu Huawang , Zheng Yingjun , Wu Chao
Published: March 2024

Background
Uncertainty in speech perception and emotional disturbances are intertwined with psychiatric symptoms. How prosody embedded in target speech affects speech-in-noise recognition (SR) and is related to psychiatric symptoms in patients with schizophrenia remains unclear. This study aimed to examine the neural substrates of prosodic SR deficits and their associations with psychiatric symptom dimensions in patients with schizophrenia.
Methods
Fifty-four schizophrenia patients (SCHs) and 59 healthy control participants (HPs) completed the SR task (the target pseudosentences were uttered in neutral, happy, sad, angry, fear, and disgust prosody), positive and negative syndrome scale (PANSS) assessment, and magnetic resonance imaging scanning. We examined the deficits of the six prosodic SRs in schizophrenia patients and examined their associations with brain gray matter volume (GMV) reduction and psychiatric symptoms.
Results
Negative prosody worsened SR and reduced SR change rates across groups. SCHs had lower rates of change in prosodic SR and SR than HPs. Prosodic SR was associated with acoustic features. The GMV PLS component (covering 47 brain regions with group differences) was related to group differences in the six prosodic SRs. A happy SR was associated with the PANSS total, negative, and general scores after adjusting for covariates.
Conclusions
A better prosodic SR was related to better emotional salience, shorter duration, and lower shimmer (local) of the target sentences. The prosodic SR abnormalities in SCHs were associated with brain GMV reductions in the regions involved in sensorimotor, speech, and emotion processing. These findings suggest the possibility of improving negative symptoms by improving a happy SR in schizophrenia patients based on neuroplasticity.
The SEMA3F-NRP1/NRP2 axis is a key factor in the acquisition of invasive traits in in situ breast ductal carcinoma
Authors: Moragas Núria , Fernandez-Nogueira Patricia , Recalde-Percaz Leire , Inman Jamie L. , López-Plana Anna , Bergholtz Helga , Noguera-Castells Aleix , Burgo Pedro J. del , Chen Xieng , Sorlie Therese , Gascón Pere , Bragado Paloma , Bissell Mina , Carbó Neus , Fuster Gemma
Published: March 2024

Background: A better understanding of ductal carcinoma in situ (DCIS) is urgently needed to identify these preinvasive lesions as distinct clinical entities. Semaphorin 3F (SEMA3F) is a soluble axonal guidance molecule, and its coreceptors Neuropilin 1 (NRP1) and NRP2 are strongly expressed in invasive epithelial BC cells.
Methods: We utilized two cell line models to represent the progression from a healthy state to the mild-aggressive or ductal carcinoma in situ (DCIS) stage and, ultimately, to invasive cell lines. Additionally, we employed in vivo models and conducted analyses on patient databases to ensure the translational relevance of our results.
Results: We revealed SEMA3F as a promoter of invasion during the DCIS-to-invasive ductal carcinoma (IDC) transition in breast cancer (BC) through the action of NRP1 and NRP2. In epithelial cells, SEMA3F activates epithelial mesenchymal transition (EMT), whereas it promotes extracellular matrix degradation and basal membrane and myoepithelial cell layer breakdown.
Conclusions:Together with our patient database data, these proof-of-concept results reveal new SEMA3F-mediated mechanisms occurring in the most common preinvasive BC lesion, DCIS, and represent potent and direct activation of its transition to invasion. Moreover, and of clinical and therapeutic relevance, the effects of SEMA3F can be blocked directly through both its receptors and coreceptors, thus preventing invasion and keeping DCIS lesions in the preinvasive state.
Low genetic variation among trees in cocoa hand pollination in the Offinso Municipality of Ghana revealed by SSR markers
Authors: Dompreh Daniel , Kuranchie Pearl , Prempeh Ruth Naa Ashiokai , Acquah Emmanuel , Sevor Dora
Published: March 2024

Cocobod introduced nationwide artificial hand pollination in Ghana in 2017 to supplement natural pollination of Theobroma cacao L. (cocoa) by insects (Forcipomyia midges) to increase yield. Hybrid farms of 8-20years old are mostly selected. Pollen donor and receiver trees are selected based on morphological characteristics. This study analyzed the genetic diversity among donor and recipient trees of cocoa hand pollination in three farms in the Offinso Municipality of Ghana using SSR markers. Twelve forward and reverse primer pairs out of fifteen primers screened were used to evaluate genetic intraspecific and interspecific diversity among twenty-five accessions based on clear amplification and reproducible scorable bands. A total of 115 polymorphic bands were detected which ranged between 5.00 and 17.00 with a mean of 9.58 alleles per locus. Cluster analysis showed similarity coefficient range of 0.10 to 0.83. Analysis of molecular variance (AMOVA) showed13% genetic variation between populations and 87% within populations of T. cacao. PhiPT value of 0.130 recorded showed weak genetic differentiation between populations. Gene diversity varied from 0.64 to 0.88 with primers MTcCIR33 and MTcCIR07 respectively. Highest observed heterozygosity (Ho) of 0.60 and least Polymorphism Information Content (PIC) of 0.57 were recorded. Pollen donor and recipient trees selected from the same or nearby farms accounts for present genetic structure of low genetic diversity between populations. Though hand pollination designs focus much on high yields, improving genetic diversity to prevent inbreeding in cocoa is recommended.
A novel approach to electroactivation: Designing of an electroactivated reactor to constrain the growth of MDR Salmonella strains by sodium caprylate solutions
Authors: Rawat Pallavi , Chauhan Vidya , Chaudhary Juhi , Singh Chhaya , Rawat Pramod , Singh Yashaswi , Chauhan Neha
Published: March 2024

The present research explored the antimicrobial efficacy of different solutions of the electroactivated salt of organic acid (sodium caprylate) against four multidrug-resistant strains of nontyphoidal Salmonella (Salmonella enterica subsp. arizonae, Salmonella Newport, Salmonella enterica ser. Typhi, Salmonella enterica ser. Paratyphi. The tested solutions were electroactivated in an electrochemical cell with three sections (anodic, central, and cathodic) partitioned by anionic and cationic exchange membranes. Electric current strengths of 100 mA, 150 mA, 200 mA, and 250 mA were applied for a total of 45 minutes. The salt solutions had concentrations of 0.5 M/L, 0.25 M/L, 0.125 M/L, 0.0625 M/L, and 0.0312 M/L. Antibacterial efficacy was tested at three concentrations, i.e., 1%, 3%, and 5%, in which 5% of the solutions showed superior inhibitory activity against all strains. In the course of the whole experimental test, four different membrane locations and solution amounts were investigated. All the current intensities showed the maximum inhibition by sodium caprylate for the MTCC 660. However, in combination with conjugated caprylic acid, its inactivating power was considerably greater. Principally, this study unambiguously showed that electroactivation can create exceptionally reactive organic acids from conjugated salts. These electroactivated solutions have the potential to be effective antimicrobial and sporicidal compounds in the food preparation industry.
The Effect of Symmetry Breaking In Coupled Cavity Photonic Crystal Waveguide on Dispersion Characteristics
Authors: Oguz Hasan , Yuksel Zekeriya Mehmet , Karakilinc Ozgur Onder , Berberoglu Halil , Turduev Mirbek , Kart Sevgi Ozdemir , Adak Muzaffer
Published: March 2024

In this study, we explore the effect of integrated auxiliary rods at varying angles to the primary cavity rod on the dispersion characteristics of the photonic crystal coupled cavity waveguide (PC CCW). Here, it is intended to break the symmetry of the cavity region by introducing auxiliary rods which gives the degree of freedom for tuning effective index of the PC waveguide. Furthermore, rotational angle variations of auxiliary rods reveal slow light operation of the PC CCW where the group index is maximized and group velocity dispersion, as well as the third-order dispersion, are minimized. In addition, auxiliary rods with a broken symmetry increase not only group index but also operating bandwidth and accordingly increase group bandwidth product by 675\%. Leveraging these results, we demonstrate effective rainbow trapping by manipulating the auxiliary rod angles in photonic crystal coupled cavity waveguides. Our results have encouraging implications for optical buffering, multiplexing, demultiplexing, advanced time-domain and spatial signal processing.
Numerical solution of the first kind Fredholm integral equations using a regularized projection method.
Authors: Bechouat Tahar , Boussetila Nadjib
Published: March 2024

In this study, we utilize the Tikhonov regularization method in conjunction with projection methods, aiming to obtain an optimal approximate solution for the first kind of Fredholm integral equations. Our analysis encompasses a comprehensive discussion on convergence, wherein we establish convergence rates by employing an a priori parameter choice strategy. Additionally, we explore the application of the Engl-type discrepancy principle as a posteriori parameter strategy for determining the regularization parameter, and we assess the resulting convergence rate, which exhibits an optimal order. To validate our theoretical findings, we present numerical experiments.
MSC Classification: 47A52 , 65R30
The impact of histological subtype on postoperative recurrence pattern and timing in locally advanced esophagogastric junction cancer
Authors: Maeda Shinsuke , Ota Masaho , Ito Shunichi , Hosoda Kei
Published: March 2024

Purpose
The differences of tumoral behavior between histological subtypes of esophagogastric junction (EGJ) cancer have yet to be well investigated. The purpose of this study is to gain insights that can contribute to the tailored treatments and follow-up strategies by analyzing correlation between histological subtypes and oncological outcomes.
Methods
Retrospective analysis was used to determine the characteristics of the histological subtype of EGJ cancer by comparing the appearance of postoperative recurrences. A total of 102 consecutive cases of pathological Stage IIA to IVA EGJ cancer, who underwent R0 surgery in our department from 2004 to 2020, were enrolled. The recurrence pattern, timing, survival, and potential prognostic factors were compared.
Results
After a median follow-up time of 70.1 months, the AC group demonstrated a comparable lymph node metastasis-free survival (P = 0.291) and a significantly worse non-lymphogenous failure-free survival (P = 0.035) than the SCC group. A significantly longer period from surgery to recurrence in the AC group was also observed (P = 0.029). Multivariate analysis indicated that histological subtype (P = 0.015, 95% CI = 1.24–7.28) was significantly correlated with the incidence of non-lymphogenous recurrence.
Conclusions
The pattern and timing of postoperative recurrence for EGJ cancer were found to be significantly different between the histological subtypes. EGJ AC may have a stronger tendency of non-lymphogenous progression and a propensity for longer surgery-to-recurrence periods compared to EGJ SCC.
Can Large Language Models be sensitive to Culture Suicide Risk Assessment?
Authors: Levkovich Inbar , Shinan-Altman Shiri , Elyoseph Zohar
Published: March 2024

Suicide remains a pressing global public health issue. Previous studies have shown the promise of Generative Intelligent (GenAI) Large Language Models (LLMs) in assessing suicide risk in relation to professionals. But the considerations and risk factors that the models use to assess the risk remain as a black box. This study investigates if ChatGPT-3.5 and ChatGPT-4 integrate cultural factors in assessing suicide risks (probability of suicidal ideation, potential for suicide attempt, likelihood of severe suicide attempt, and risk of mortality from a suicidal act) by vignette methodology. The vignettes examined were of individuals from Greece and South Korea, representing countries with low and high suicide rates, respectively. The contribution of this research is to examine risk assessment from an international perspective, as large language models are expected to provide culturally-tailored responses. However, there is a concern regarding cultural biases and racism, making this study crucial. In the evaluation conducted via ChatGPT-4, only the risks associated with a severe suicide attempt and potential mortality from a suicidal act were rated higher for the South Korean characters than for their Greek counterparts. Furthermore, only within the ChatGPT-4 framework was male gender identified as a significant risk factor, leading to a heightened risk evaluation across all variables. ChatGPT models exhibit significant sensitivity to cultural nuances. ChatGPT-4, in particular, offers increased sensitivity and reduced bias, highlighting the importance of gender differences in suicide risk assessment.
Optimizing the NGS-based discrimination of multiple lung cancers from the perspective of evolution
Authors: Wang Ziyang , Yuan Xiaoqiu , Liu Ke , Sun Kunkun , Chervova Olga , Nie Yuntao , Yang Airong , Jin Yichen , Li Jing , Li Yun , Yang Fan , Wang Jun , Beck Stephan , Carbone David , Chen Kezhong
Published: March 2024

Background: Next-generation sequencing (NGS) can help differentiate multiple primary lung cancers (MPLC) from intrapulmonary metastasis (IPM), but remains vague in panel choice and clonal relatedness interpretation.
Methods: First, cases with definite diagnosis of MPLC or IPM were simulatedusing the whole-exome sequencing (WES)data from 80 single lung cancer, samples from different tumors mimicking MPLC while those from the same tumor simulating IPM. Different panels were modeled by gene subsampling. Two interpretation methods of clonal relatedness were compared: counting the shared mutations (MoleA) versus probability calculation based on all the mutations (MoleB). We drew ROC curves for each panel and interpretation method with reference to the definite diagnosis, and selected the optimal combinations according to area under the ROC curve (AUCs) and inconclusive rate.
Results: MoleB outperformed MoleA with all panels. The AUCs plateaued at high levels when applying NCCNplus MoleB (9 driver genes recommended by the National Comprehensive Cancer Network [NCCN] plus TP53) (AUC = 0.950±0.002) or pancancer MoleA (363-genes) (AUC = 0.792±0.004). Then the superiority of selected strategies was validated in two independent cohorts of multiple lung cancers. All NGS-based methodologies significantly separated the disease-free survival in the WES cohort (N = 42), and NCCNplus MoleB also successfully stratified the prognosis in the non-WES cohort (N = 94). Further phylogenetic analysis and timing of driver alterations revealed the evolutionary differences between MPLC and IPM.
Conclusions: These findings have established the first modified panel and corresponding NGS-based procedures to discriminate multiple lung cancers (MLCs).
INTRA-ARTICULAR PLATELET RICH PLASMA IN THE TREATMENT OF PATIENTS WITH KNEE OSTEOARTHRITIS
Authors:   Consultant Orthopaedics, SDH, Bijbahara., Mohammed Chowdhary Bashir , Ahmad Bhat Mudasir ,   MS Orthopaedics.
Published: March 2024

Introduction: Osteoarthritis of knee is the most common worldwide degenerative joint disease and is a common condition associated with pain and morbidity which significantly impacts the patients mobility and quality of life. It is treated by use of exercises, weight reduction, walking supports, bracing, topical and oral NSAID, intra-articular (IA) injections of corticosteroids and blood-derived products, including platelet-rich-plasma. An autologous blood product containing a high percentage of various growth factors (GFs), cytokines and modulating factors as PRP has shown promising results in achieving this goal. The aim of this prospective study was to evaluate the efficacy and safety of Platelet Rich Plasma (PRP) injections in patients affected by knee osteoarthritis (KOA) of grades from 1 to 3 Kellgrenâ€‘Lawrence (KL) grading. Materials and Methods: In this study a total of 30 patients, radiologically confirmed with knee osteoarthritis. All patients were managed with intra-articular platelet rich plasma injection. The pain and function of the target knee were evaluated by the VAS, KSS and IKDC scales at the baseline, 1 week, 6 weeks, 12 weeks, 18 weeks, 24 weeks and 48 weeks after treatment. Results: In this study, there was reduction of 5 Â± 0.4 and 4 in mean VAS from baseline was found after 24 and 48 weeks after treatment. A significant function improvements of 32.10Â±1.5 and 21.4Â±4.9 in mean KSS from baseline was seen after 24 and 48 weeks respectively after treatment. Similarly a significant function improvements of 47.1Â±3.9 and 32.1Â±4.6 in mean IKDC from baseline was seen after 24 and 48 weeks respectively after treatment. Conclusion: Intra articular platelet rich plasma produce superior outcomes for symptomatic management in the treatment of patients with knee osteoarthritis grade I, II and III, including improved pain management, less joint stiffness and better participation in daily activity.