bluuebunny/crossref_metadata_2025 huggingface dataset:
In silico medical device testing of anatomically and mechanically conforming patient-specific spinal fusion cages designed by full-scale topology optimisation
Authors: Smit Thijs , Aage Niels , Haschtmann Daniel , Ferguson Stephen J. , Helgason Benedikt
Published: September 2024

A full-scale topology optimisation formulation has been developed to automate the design of cages used in instrumented transforaminal lumbar interbody fusion. The method incorporates the mechanical response of the adjacent bone structures in the optimisation process, yielding patient-specific spinal fusion cages that both anatomically and mechanically conform to the patient, effectively mitigating subsidence risk compared to generic, off-the-shelf cages and patient-specific devices. In this study, in silico medical device testing on a cohort of seven patients was performed to investigate the effectiveness of the anatomically and mechanically conforming devices using titanium and PEEK implant materials. A median reduction in the subsidence risk by 89% for titanium and 94% for PEEK implant materials was demonstrated compared to an off-the-shelf implant. A median reduction of 75% was achieved for a PEEK implant material compared to an anatomically conforming implant. A credibility assessment of the computational model used to predict the subsidence risk was provided according to the ASME V&V40–2018 standard.
Biofabrication of prevascularized spheroids for bone tissue engineering by fusion of microvascular fragments with osteoblasts
Authors: Wrublewsky Selina , Schultz Jessica , Ammo Tekoshin , Bickelmann Caroline , Metzger Wolfgang , Später Thomas , Pohlemann Tim , Menger Michael D. , Laschke Matthias W.
Published: September 2024

Introduction

Spheroids are promising building blocks for scaffold-free bone tissue engineering. Their rapid vascularization is of major importance to guarantee their survival after transplantation. To achieve this, we herein introduce the biofabrication of prevascularized spheroids by fusion of adipose tissue-derived microvascular fragments (MVF) with osteoblasts (OB).

Methods

For this purpose, 200 MVF from donor mice and 5,000, 10,000 or 20,000 murine OB (MC3T3-E1) were co-cultured in a liquid overlay system for 3 days to generate OB + MVF spheroids. OB mono-culture spheroids served as controls.

Results and discussion

During the generation process, the diameters of all spheroids progressively decreased, resulting in compact, viable spheroids of homogeneous sizes. MVF promoted the maturation of spheroids containing 5,000 OB, as shown by an accelerated decline of cell proliferation due to contact inhibition. Moreover, MVF most effectively reassembled into new microvascular networks within these small spheroids when compared to the other spheroid types, indicating the most beneficial MVF to OB ratio. Accordingly, these spheroids also showed a high angiogenic sprouting activity in vitro. In contrast to OB spheroids, they further rapidly vascularized in vivo after transplantation into dorsal skinfold chambers. This was caused by the interconnection of incorporated MVF with surrounding blood vessels. These findings indicate that OB + MVF spheroids may be suitable for bone tissue engineering, which should be next tested in appropriate in vivo bone defect models.
Exploration of a model driven by climate to simulate pond water temperature in aquaculture systems
Authors: Resnick Drew , Baethgen Walter , Hossain Peerzadi Rumana , Kadam Sanketa
Published: September 2024

Introduction

Interannual climate variability in the Asian mega deltas has been posing a wide range of climate risks in the aquaculture systems of the region. Water temperature variation is one of the key risks related to disease outbreak, fish health, and loss and damage in fish production. However, Climate information can improve the ability to predict changes in pond water quality parameters at the farm level using publicly available weather and climate data. Little research has been done to translate weather data into water temperature forecasts using mechanistic models in order to provide farmers with relevant forecasting information in the context of climate services.

Methods

The advantage of mechanistic models over statistical models is that they are based on physical processes and can therefore be used in a wider range of environmental conditions. In this study, we used an energy balance model to investigate its ability to simulate pond water temperature at daily and seasonal timescales in the southwest and northeast regions of Bangladesh. The model was able to adequately simulate pond water temperature at a daily timescale using publicly available weather data, and the accuracy of the model was lower at the study site with very heavy rainfall events.

Results

Sensitivity analyses showed that the model was also able to simulate the impact of air temperature cold and hot spells on the pond water temperature. Connecting the model with seasonal air temperature forecasts resulted in very small variations in the forecasted seasonal pond water temperature, in large part due to the low variability observed in water temperature at seasonal scale in the study sites.

Discussion

Climate information can improve the ability to predict changes in pond water quality parameters at the farm level using publicly available weather and climate data. Hence, these improved predictions are important to help fish-farmers make informed decisions for managing associated climate risks.
Multi-version interactive assessment through the integration of GeoGebra with Moodle
Authors: Hamady Saleem , Mershad Khaleel , Jabakhanji Bilal
Published: September 2024

AI systems are now capable of providing accurate solutions to questions presented in text format, causing a major problem in assessment integrity. To address this issue, interactive material can be integrated with the questions, preventing current AI systems from processing the requirements. This study proposes a novel approach that combines two important tools: GeoGebra and Moodle. GeoGebra is a widely used tool in schools and universities for creating dynamic and interactive material in the STEM field. On the other hand, Moodle is a popular learning management system with integrated tools capable of generating multiple versions of the same question to enhance academic integrity. We combine these two tools to automatically create unique interactive questions for each student in a computer-based assessment. Detailed implementation steps that do not require prior coding experience or the installation of additional plugins are presented, making the technique accessible to a wider range of instructors. The proposed approach was tested on a group of students and showed enhanced performance in animation-based questions compared to traditional question formats. Moreover, a survey exploring the students’ opinions on the proposed approach reported strong student endorsement of animated questions.
What can I do as a farmer to reduce losses? Willingness to use meteorological information as an exit strategy to deal with meteorological hazards
Authors: Valizadeh Naser , Haji Latif , Karami Shobeir , Ahmadi Dehrashid Atefeh , Jalilian Sara , Azadi Hossein
Published: September 2024

Meteorological information and forecasts are of great importance to reduce agro-meteorological hazards. However, the gap between production and application of these forecasts is one of the most ambiguous issues of crop management at the farmers’ level. In this regard, investigating the factors influencing Iranian farmers willingness to use meteorological information and predictions was selected as the main aim of the present study. To this end, an extended version of Theory of Planned Behavior (TPB) was employed and modeled. The results revealed that attitude towards the use of meteorological information and predictions, subjective norms in the use of meteorological information and predictions, perceived behavioral control and self-identity in the use of meteorological information and prediction, and moral norm variables regarding the use of meteorological information and predictions positively and significantly affected willingness to use meteorological information and predictions. These variables could account for 46% of willingness to use meteorological information and predictions variance. According to the results, it was suggested that by creating multimedia programs, the agricultural community become aware of the benefits and consequences of using meteorological information in their activities. Furthermore, it was recommended that social cooperation and research groups be formed on the use of meteorological information in agricultural activities. This can contribute to examine the various dimensions (strengths, weaknesses, threats, and opportunities) of using meteorological information from a collective perspective. Making a social decision in this regard can have a profound effect on a person’s subjective norms and dramatically increase the speed of using meteorological information. The results of this study can help policymakers and decision-makers in the field of agriculture to design suitable intervention programs for the effective use of meteorological information by farmers. Also, the results of this study help farmers to effectively reduce the impacts of meteorological hazards.
Impact of carbon emission trading on urban green innovation: empirical evidence from China’s carbon emission trading pilot policy
Authors: Tian Kun , Zhai Duanqiang , Han Shuo
Published: September 2024

In the face of global climate change challenges, China’s implementation of the carbon emission trading (CET) pilot policy has provided new empirical research opportunities. Based on a dataset covering 281 Chinese cities from 2005 to 2021, this paper employs econometric models to conduct an in-depth analysis of the policy’s impact on urban green innovation (UGI). The findings indicate that the CET pilot policy has significantly promoted green innovation activities in affected cities, with positive effects observed both directly in pilot cities and indirectly in non-pilot cities through spatial spillover effects. In addition, the policy has been found to encourage technological investment and enhance public environmental awareness (PEA), further advancing green innovation. The paper also unveils comprehensive policy effects, indicating that the Big Data Comprehensive Test Zone policy and the New Energy Demonstration City policy work synergistically with the CET pilot policy in advancing green innovation. These findings provide valuable experiences and insights for designing environmental policy tools at the national level, promoting green development, and constructing climate change response strategies.
Short-term PM2.5 forecasting using a unique ensemble technique for proactive environmental management initiatives
Authors: Iftikhar Hasnain , Qureshi Moiz , Zywiołek Justyna , López-Gonzales Javier Linkolk , Albalawi Olayan
Published: September 2024

Particulate matter with a diameter of 2.5 microns or less (PM2.5) is a significant type of air pollution that affects human health due to its ability to persist in the atmosphere and penetrate the respiratory system. Accurate forecasting of particulate matter is crucial for the healthcare sector of any country. To achieve this, in the current work, a new time series ensemble approach is proposed based on various linear (autoregressive, simple exponential smoothing, autoregressive moving average, and theta) and nonlinear (nonparametric autoregressive and neural network autoregressive) models. Three ensemble models are also developed, each employing distinct weighting strategies: equal distribution of weight among all single models (ESME), weight assignment based on training average accuracy errors (ESMT), and weight assignment based on validation mean accuracy measures (ESMV). This technique was applied to daily PM2.5 concentration data from 1 January 2019, to 31 May 2023, in Pakistan’s main cities, including Lahore, Karachi, Peshawar, and Islamabad, to forecast short-term PM2.5 concentrations. When compared to other models, the best ensemble model (ESMV) demonstrated mean errors ranging from 3.60% to 25.79% in Islamabad, 0.81%–13.52% in Lahore, 1.08%–7.06% in Karachi, and 1.09%–12.11% in Peshawar. These results indicate that the proposed ensemble approach is more efficient and accurate for short-term PM2.5 forecasting than existing models. Furthermore, using the best ensemble model, a forecast was made for the next 15 days (June 1 to 15 June 2023). The forecast showed that in Lahore, the highest PM2.5 value (236.00 μg/m3) was observed on 8 June 2023. Other days also displayed higher and poor air quality throughout the 15 days. Conversely, Karachi experienced moderate PM2.5 concentration levels between 50 μg/m3 and 80 μg/m3. In Peshawar, the PM2.5 concentration levels were consistently unhealthy, with the highest peak (153.00 μg/m3) observed on 9 June 2023. This forecasting experience can assist environmental monitoring organizations in implementing cost-effective planning to minimize air pollution.
Small molecule innate immune modulators in cancer therapy
Authors: Goswami Avijit , Goyal Sandeep , Khurana Princy , Singh Kawaljit , Deb Barnali , Kulkarni Aditya
Published: September 2024

Immunotherapy has proved to be a breakthrough in cancer treatment. So far, a bulk of the approved/late-stage cancer immunotherapy are antibody-based. Although these antibody-based drugs have demonstrated great promise, a majority of them are limited due to their access to extracellular targets, lack of oral bioavailability, tumor microenvironment penetration, induction of antibody dependent cytotoxicity etc. In recent times, there has been an increased research focus on the development of small molecule immunomodulators since they have the potential to overcome the aforementioned limitations posed by antibodies. Furthermore, while most biologics based therapeutics that are in clinical use are limited to modulating the adaptive immune system, very few clinically approved therapeutic modalities exist that modulate the innate immune system. The innate immune system, which is the body’s first line of defense, has the ability to turn cold tumors hot and synergize strongly with existing adaptive immune modulators. In preclinical studies, small molecule innate immune modulators have demonstrated synergistic efficacy as combination modalities with current standard-of-care immune checkpoint antibodies. In this review, we highlight the recent advances made by small molecule innate immunomodulators in cancer immunotherapy.
Variation in worldwide incidence of Guillain-Barré syndrome: a population-based study in urban China and existing global evidence
Authors: Xu Lu , Zhao Chen , Bao Yutong , Liu Yuchen , Liang Yuqing , Wei Jiyu , Liu Guozhen , Wang Jinxi , Zhan Siyan , Wang Shengfeng , Fan Dongsheng
Published: September 2024

Background and objectives

Geographical variation existed in the incidences of Guillain-Barré syndrome (GBS), but no national population-based study has evaluated the incidences of GBS in China. This study aimed to estimate the incidence of GBS in urban China and evaluate the worldwide variation in the incidence of GBS.

Methods

Firstly, we did a population-based study to calculate the incidence of GBS in urban China based on the National Urban Medical Insurance database from 2013 to 2017. To identify GBS cases, natural language processing was used first for handling the lengthy and unstructured diagnostic information and then checked by prestigious neurologists. Secondly, a systematic review and meta-analysis were performed to analyze the incidence of GBS worldwide. Up to July 4, 2022, Medline, Embase, and Web of Science were retrieved to identify the population-based studies regarding the incidence of GBS. The basic information and the statistics regarding incidence were extracted. Quality assessment considered sample representativeness, condition assessment, and statistical methods.

Results

A total of 1.44 billion person-years in insurance data was covered, with 3,534 GBS cases identified. The annual incidences of GBS in urban China between 2013 and 2017 ranged from 0.41 (95% CI: 0.27 to 0.58) to 0.58 (95% CI: 0.38 to 0.82) per 100,000 person-years. The incidence was the highest in Northwest China and the lowest in Northeast China. The meta-analysis included 122 articles. The quality assessment showed that the quality scores of 43.3% of studies were ≥ 0.75 (the total score is 1). The global incidence of GBS was 1.12 (95% CI: 0.98 to 1.27) per 100,000 person-years. The incidences in West Europe, South Asia, and North Europe were higher, while the incidences in Australia and New Zealand, Southeast Asia, and North Africa were lower. The incidence of enteric infections was positively associated with the incidence of GBS (coefficient=0.0000185, P=0.007). The incidence in Europe, Australia, and America rose significantly from 1960 to 2020 (coefficient=0.01, t=2.52, P=0.015).

Discussion

There is a clear regional variation of the GBS incidence at both national and global levels. Careful control of enteric infections should be conducted to reduce the disease burden.
The lifestyle and nutritional factors for dry eye disease in depression population: a retrospective case–control study
Authors: Lee Chia-Yi , Yang Shun-Fa , Lian Ie-Bin , Chang Yu-Ling , Jhan Yan-Ni , Chang Chao-Kai
Published: September 2024

Background

We aim to evaluate lifestyle and nutritional factors that lead to dry eye disease (DED) in a depressed population using data from the Taiwan BioBank (TWB).

Methods

A retrospective case–control study was conducted, and patients with depression based on a questionnaire were selected as the depression group. Each patient in the depression group was matched by age and sex to two individuals without depression, and a total of 3,754 and 7,508 patients constituted the depression and non-depression groups, respectively. Based on the questionnaire, the primary outcome was the presence of DED. Additionally, the chi-square test and interaction test were applied to survey the effect of lifestyle and nutritional factors on DED in the depression and non-depression groups.

Results

There were 822 (21.90%) and 958 (12.76%) DED patients in the depression and non-depression groups, respectively, and the incidence of DED was significantly higher in the depression group (p < 0.001). In terms of lifestyle and nutritional factors in the depression population, a higher rate of chronic pain and a sedentary lifestyle were observed than in the patients with depression without DED (both p < 0.05). According to the interaction test, the chronic pain (p = 0.0227) and sedentary lifestyle (p = 0.0002) were significant risk factors for DED presence in the depression group than in the non-depression group, while the persistent coffee consumption (p = 0.0005) and tea consumption (p = 0.0003) were significant protective factors for the DED exclusively for the depression group and not for the non-depression group.

Conclusion

The depression population could be significantly benefited from physical activity, coffee intake and tea intake regarding DED development compared to the general population.
The gut microbiota-immune-brain axis in a wild vertebrate: dynamic interactions and health impacts
Authors: Pereira Hugo , Hoffman Joseph I. , Krüger Oliver , Czirják Gábor Á. , Rinaud Tony , Ottensmann Meinolf , Gladow Kai-Philipp , Caspers Barbara A. , Maraci Öncü , Kaiser Sylvia , Chakarov Nayden
Published: September 2024

The gut microbiota-immune-brain axis is a feedback network which influences diverse physiological processes and plays a pivotal role in overall health and wellbeing. Although research in humans and laboratory mice has shed light into the associations and mechanisms governing this communication network, evidence of such interactions in wild, especially in young animals, is lacking. We therefore investigated these interactions during early development in a population of common buzzards (Buteo buteo) and their effects on individual condition. In a longitudinal study, we used a multi-marker approach to establish potential links between the bacterial and eukaryotic gut microbiota, a panel of immune assays and feather corticosterone measurements as a proxy for long-term stress. Using Bayesian structural equation modeling, we found no support for feedback between gut microbial diversity and immune or stress parameters. However, we did find strong relationships in the feedback network. Immunity was negatively correlated with corticosterone levels, and microbial diversity was positively associated with nestling body condition. Furthermore, corticosterone levels and eukaryotic microbiota diversity decreased with age while immune activity increased. The absence of conclusive support for the microbiota-immune-brain axis in common buzzard nestlings, coupled with the evidence for stress mediated immunosuppression, suggests a dominating role of stress-dominated maturation of the immune system during early development. Confounding factors inherent to wild systems and developing animals might override associations known from adult laboratory model subjects. The positive association between microbial diversity and body condition indicates the potential health benefits of possessing a diverse and stable microbiota.
Clinical decision support system using hierarchical fuzzy diagnosis model for migraine and tension-type headache based on International Classification of Headache Disorders, 3rd edition
Authors: Yin Ziming , Li Heng , Han Xun , Ran Ye , Wang Zhichen , Dong Zhao
Published: September 2024

Objective

To determine whether the diagnostic ability of the newly designed hierarchical fuzzy diagnosis method is consistent with that of headache experts for probable migraine (PM) and probable tension-type headache (PTTH).

Background

Clinical decision support systems (CDSS) are computer systems designed to help doctors to make clinician decisions by information technology, and have proven to be effective in improving headache diagnosis by making medical knowledge readily available to users in some studies. However, one serious drawback is that the CDSS lacks the ability to deal with some fuzzy boundaries of the headache features utilized in diagnostic criteria, which might be caused by patients’ recall bias and subjective bias.

Methods

A hybrid mechanism of rule-based reasoning and hierarchical fuzzy diagnosis method based on International Classification of Headache Disorders, 3rd edition (ICHD-3) was designed and then validated by a retrospective study with 325 consecutive patients and a prospective study with 380 patients who were clinically diagnosed with migraine and TTH at the headache clinic of Chinese PLA General Hospital.

Results

The results of the diagnostic test in the retrospective study indicated that the fuzzy-based CDSS can be used in the diagnosis of migraine without aura (MO) (sensitivity 97.71%, specificity 100%), TTH (sensitivity 98.57%, specificity 100%), PM (sensitivity 91.25%, specificity 98.75%) and PTTH (sensitivity 90.91%, specificity 99.63%). While in the prospective study, the diagnostic performances were MO (sensitivity 91.62%, specificity 96.52%), TTH (sensitivity 92.17%, specificity 95.47%), PM (sensitivity 85.48%, specificity 98.11%) and PTTH (sensitivity 87.50%, specificity 98.60%). Cohen’s kappa values for the consistency test were 0.984 ± 0.018 (MO), 0.991 ± 0.018 (TTH), 0.916 ± 0.051 (PM), 0.932 ± 0.059 (PTTH) in the retrospective study and 0.884 ± 0.047 (MO), 0.870 ± 0.055 (TTH), 0.853 ± 0.073 (PM), 0.827 ± 0.118 (PTTH) in the prospective study, which indicated good consistency with the fuzzy-based CDSS and the gold standard (p < 0.001).

Conclusion

We developed a fuzzy-based CDSS performs much more similarly to expert diagnosis and performs better than the routine CDSS method in the diagnosis of migraine and TTH, and it could promote the application of artificial intelligence in the area of headache diagnosis.
Management of infections for patient treated with ibrutinib in clinical practice
Authors: Baratè Claudia , Scortechini Ilaria , Ciofini Sara , Picardi Paola , Angeletti Ilaria , Loscocco Federica , Sanna Alessandro , Isidori Alessandro , Sportoletti Paolo
Published: September 2024

Ibrutinib, a highly effective inhibitor of the Bruton tyrosine kinase, has significantly transformed the therapeutic approach in chronic lymphocytic leukemia (CLL). Despite these advancements, the disease continues to be characterized by immune dysfunction and increased susceptibility to infections, with mortality rates from infections showing no significant improvement over the past few decades. Therefore, timely prevention, recognition, and treatment of infections remains an important aspect of the standard management of a patient with CLL. A panel of hematologists with expertise in CLL met to discuss existing literature and clinical insights for the management of infectious in CLL undergoing ibrutinib treatment. Despite not being a fully comprehensive review on the topic, this work provides a set of practical recommendations that can serve as a guide to healthcare professionals who manage these patients in their daily clinical practice.
Case Report: Supercharged end-to-side anterior interosseous to ulnar motor nerve transfer for ulnar nerve neuropathy after cross pinning of pediatric supracondylar humerus fracture
Authors: Chen Jian-Jiun , Yang Chen-Yuan
Published: September 2024

Ulnar nerve neuropathy following pediatric supracondylar humerus fracture fixation with cross pinning poses challenges in management. Despite various treatment strategies, including conservative approaches and early intervention, achieving complete neural recovery remains elusive in some cases. This paper presents a novel approach utilizing supercharged end-to-side anterior interosseous nerve transfer for a 13-year-old patient who experienced persistent ulnar neuropathy after K-wire removal. The patient underwent neurolysis of the ulnar nerve followed by nerve transfer, resulting in significant improvement in function and strength. This case highlights the potential efficacy of combining neurolysis and supercharge techniques in pediatric ulnar neuropathy cases refractory to conservative treatment, offering a promising avenue for enhancing patient outcomes.
Case Report: A successful outcome of nadroparin calcium therapy for cerebral venous sinus thrombosis in a child with acute lymphoblastic leukemia
Authors: Xie Lichun , Xu Ye , Zhou Guichi , Chen Fen , Li Changgang , Ma Lian , Wen Feiqiu
Published: September 2024

Background

The appearance of cerebral venous sinus thrombosis (CVST) in childhood acute lymphocytic leukemia (ALL) is a rare life-threatening disease that can cause significant morbidity, neurological sequelae, and potentially poor outcomes.

Case presentation

We present the case of a 13-year-old boy with ALL who developed CVST and intrinsic hemorrhage approximately 30 days after receiving chemotherapy with vincristine, dexamethasone, daunorubicin, and pegylated-asparaginase (PEG-Asp). He complained of a severe headache and then developed a generalized seizure at night. T1- and T2-weighted magnetic resonance imaging (MRI) and cerebral magnetic resonance venography sequences revealed superior sagittal sinus thrombosis and intrinsic hemorrhagic changes in the bilateral frontoparietal lobes. He received nadroparin calcium as the anticoagulant treatment and was switched to Erwinia asparaginase (Erwinia Asp) rather than PEG-Asp. Oxcarbazepine and clonazepam were started with good seizure control. Intrathecal treatment was delayed until 1 month later. Anticoagulation treatment was stopped for 24 h before and 6 h after lumbar puncture. Platelet transfusion was administered to ensure the platelet count remained at >50 × 109/L. Oral acetazolamide (500–1,000 mg, daily) was administered to relieve headache and reduce intracranial pressure. Three months later, brain MRI showed a complete resolution of or significant improvement in the filling defect. Nadroparin calcium was administered for 1 week after switching to Erwinia Asp to prevent clot recurrence. He completed the 6-month chemotherapy and is doing well with no neurological sequelae and no recurrence of bleeding or thrombosis.

Conclusions

Nadroparin calcium therapy appears to be safe and effective for pediatric CVST with ALL. The reintroduction of Erwinia Asp should be accompanied by anticoagulant therapy with nadroparin calcium.
Combined analysis of cecal microbiota and metabolomics reveals the intervention mechanism of Dayuan Yin in acute lung injury
Authors: Zhang Lei , Zhu Wei , Zhang Zepeng
Published: September 2024

The ancient Chinese medicinal formula, Dayuan Yin (DYY), has a long history of use in treating respiratory ailments and is shown to be effective in treating acute infectious diseases. This study aims to explore how DYY may impact intestinal flora and metabolites induced by acute lung injury (ALI). ALI rats were induced with lipopolysaccharide (LPS) to serve as models for assessing the anti-ALI efficacy of DYY through multiple lung injury indices. Changes in intestinal microflora were assessed via 16SrRNA gene sequencing, while cecum contents were analyzed using non-targeted metabonomics. Differential metabolites were identified through data analysis, and correlations between metabolites, microbiota, and inflammatory markers were examined using Pearson’s correlation analysis. DYY demonstrated a significant improvement in LPS-induced lung injury and altered the composition of intestinal microorganisms, and especially reduced the potential harmful bacteria and enriched the beneficial bacteria. At the gate level, DYY exhibited a significant impact on the abundance of Bacteroidota and Firmicutes in ALI rats, as well as on the regulation of genera such as Ruminococcus, Lactobacillus, and Romboutsia. Additionally, cecal metabonomics analysis revealed that DYY effectively modulated the abnormal expression of 12 key metabolic biomarkers in ALI rats, thereby promoting intestinal homeostasis through pathways such as purine metabolism. Furthermore, Pearson’s analysis indicated a strong correlation between the dysregulation of intestinal microbiota, differential metabolites, and inflammation. These findings preliminarily confirm that ALI is closely related to cecal microbial and metabolic disorders, and DYY can play a protective role by regulating this imbalance, which provides a new understanding of the multi-system linkage mechanism of DYY improving ALI.
Combination of Youhua Kuijie Prescription and sulfasalazine can alleviate experimental colitis via IL-6/JAK2/STAT3 pathway
Authors: Tang Lili , Liu Yuedong , Tao Hongwu , Feng Wenzhe , Ren Cong , Shu Yuping , Luo Ruijuan , Wang Xiangyi
Published: September 2024

Introduction

Youhua Kuijie prescription (YHKJ) is a hospital preparation that is composed of nine kinds of herbs. Sulfasalazine (SASP) is widely used as a first-line clinical treatment for UC. Traditional Chinese medicine and Western medicine have their own advantages in the treatment of UC, and the mechanism of YHKJ combined with SASP in the treatment of UC needs to be investigated.

Methods

In this study, the therapeutic mechanism of YHKJ combined with SASP in the treatment of UC was predicted by network pharmacology and molecular docking. The chemical components and related targets of YHKJ were obtained from the TCMSP database. The chemical structure of SASP was obtained from the PubChem server, and related targets of SASP molecules were identified using the PharmMapper database. UC-related targets were obtained from the DisGeNET, GeneCards, OMIM, TTD, DrugBank and PharmGkb databases.

Results

In total, 197 shared targets were identified by constructing a Venn diagram. PPI network data obtained from the STRING database were imported into Cytoscape to visualize the “drug-disease” target network, and STAT3 was selected as the core target by topological analysis. Gene Ontology revealed the biological functions of target genes, and KEGG analysis revealed that the core target STAT3 was differentially expressed in Th17 cells and the JAK-STAT signaling pathway. Thus, the core target STAT3 was subjected to molecular docking with the top 10 components, including nine YHKJ components (quercetin, luteolin, ursolic acid, daidzein, kaempferol, wogonin, myricetin, formononetin, indirubin) and SASP (C18H14N4O5S). The molecular docking results showed that STAT3 had favorable binding with the nine YHKJ components and SASP; STAT3 had the strongest binding with ursolic acid (−10.26 kcal/mol), followed by SASP (−8.54 kcal/mol). Qualitative analysis of the chemical constituents of YHKJ by HPLC revealed that sitosterol, ursolic acid, myricetin, daidzein, quercetin, kaempferol and formononetin were the main components. Additional experiments verified that YHKJ combined with SASP inhibited activation of the IL-6/JAK2/STAT3 pathway and alleviated inflammation in UC model rats.

Discussion

Our results showed that seven chemical components in YHKJ cooperate with SASP to interfere with activation of the IL-6/JAK2/STAT3 pathway, thus playing a role in the treatment of UC.
Training set optimization is a feasible alternative for perennial orphan crop domestication and germplasm management: an Acrocomia aculeata example
Authors: Couto Evellyn G. O. , Chaves Saulo F. S. , Dias Kaio Olimpio G. , Morales-Marroquín Jonathan A. , Alves-Pereira Alessandro , Motoike Sérgio Yoshimitsu , Colombo Carlos Augusto , Zucchi Maria Imaculada
Published: September 2024

Orphan perennial native species are gaining importance as sustainability in agriculture becomes crucial to mitigate climate change. Nevertheless, issues related to the undomesticated status and lack of improved germplasm impede the evolution of formal agricultural initiatives. Acrocomia aculeata - a neotropical palm with potential for oil production - is an example. Breeding efforts can aid the species to reach its full potential and increase market competitiveness. Here, we present genomic information and training set optimization as alternatives to boost orphan perennial native species breeding using Acrocomia aculeata as an example. Furthermore, we compared three SNP calling methods and, for the first time, presented the prediction accuracies of three yield-related traits. We collected data for two years from 201 wild individuals. These trees were genotyped, and three references were used for SNP calling: the oil palm genome, de novo sequencing, and the A. aculeata transcriptome. The traits analyzed were fruit dry mass (FDM), pulp dry mass (PDM), and pulp oil content (OC). We compared the predictive ability of GBLUP and BayesB models in cross- and real validation procedures. Afterwards, we tested several optimization criteria regarding consistency and the ability to provide the optimized training set that yielded less risk in both targeted and untargeted scenarios. Using the oil palm genome as a reference and GBLUP models had better results for the genomic prediction of FDM, OC, and PDM (prediction accuracies of 0.46, 0.45, and 0.39, respectively). Using the criteria PEV, r-score and core collection methodology provides risk-averse decisions. Training set optimization is an alternative to improve decision-making while leveraging genomic information as a cost-saving tool to accelerate plant domestication and breeding. The optimized training set can be used as a reference for the characterization of native species populations, aiding in decisions involving germplasm collection and construction of breeding populations
A study on the mediating-moderate effect of the types of illicit drugs on mental health in China
Authors: Zhou Bo , Tan Jintao , Li Wenli , Yu Cheng
Published: September 2024

Background

In China, over 5 million people have been identified and registered by the public security institutions for using illicit drugs. The aim of this study is to compare the influence of different types of illicit drugs on the self-reported mental health of Chinese people. In particular, we want to assess the damage of Heroin, Methamphetamine and Ketamine to mental health in a social environment where drug use is strictly regulated.

Methods

The study is based on survey with 6,906 people who use drugs in Guangdong province, China. Risk of mental health issue is measured using the Brief Symptoms Inventory 18 (BSI-18) Scale, and a higher BSI-18 score indicates more severe mental health problems. The data was analyzed through multilevel regression analysis, propensity score matching analysis and mediation analysis.

Results

The three major types of illicit drugs have both moderating and mediating effects on the length of drug-use history, that Heroin use leads to longer drug-use duration, while Ketamine use causes more damage on mental health per unit time of drug-use duration. Average duration of Methamphetamine use is 0.7 year shorter than average duration of Heroin use, and average duration of Ketamine use is 1.7 year shorter than average duration of Heroin use. For each year of increase of drug-use duration, Ketamine use leads to 1.2 times more of BSI score increase than Heroin use, and 2.3 times more of BSI score increase than Methamphetamine use.

Conclusion

These three drugs are associated with severe mental health issue in a society with strict drug regulation. Attention should be paid to the mental health of people regardless of the type of drugs they use.
Impact of storm drains on the maintenance of dengue endemicity in Presidente Prudente, São Paulo, Brazil: a geospatial and epidemiologic approach
Authors: Bertacco Elaine Aparecida Maldonado , Prestes-Carneiro Luiz Euribel , de Araújo Renata Ribeiro , D'Andrea Lourdes Aparecida Zampieri , Pinheiro Luiza Sant'Anna , Flores Edilson Ferreira
Published: September 2024

Introduction

Dengue is a public health challenge worldwide. Brazil registered about 70% of cases in Latin America in 2023; in 2024, the country is experiencing an unprecedented increase in the number of infected individuals. By May 2024, more than 4 million people were infected. Our goal was to: (1) determine the epidemiology of dengue cases and their spatiotemporal distribution and (2) carry out a survey of the storm drains and through a geospatial analysis to determine their possible correlation with cases of dengue in Presidente Prudente, São Paulo, Brazil.

Methods

Cases and information on the habitat of mosquito in the storm drain underground drainage system from 2020 to 2021 were obtained from public agencies. Larvae, pupae, and Ae. aegypti were identified according to species and described in taxonomic keys. Kernel density maps were constructed.

Results

From 1996 to 2023, the prevalence of cases peaked in 2016 and 2019, and in 2023 reached alarming levels, and the city was considered hyperendemic. In 2021, 2,609 cases were registered with 2 clusters of high density. Of 5,492 storm drains analyzed, 18.0% were found to have water, 9.0% had larvae or pupae of Aedes aegypti and 91.0% were classified as dirty or damaged. A direct correlation between the kernel layer of cases in 2021 with the kernel layer of storm drains containing water (r = 0.651) and larvae and pupae (r = 0.576) was found, suggesting that storm drains are risk factors and have an impact on the maintenance of dengue endemicity. The high number of damaged units found demonstrated the lack of storm drain management, compromising the urban drainage system and possibly contributing to dengue outbreaks.

Conclusion

Policymakers may use these findings to improve existing dengue control strategies focusing on the control of storm drains and increase local and global perspectives on reducing dengue outbreaks.
Deep beamforming for speech enhancement and speaker localization with an array response-aware loss function
Authors: Chang Hsinyu , Hsu Yicheng , Bai Mingsian R.
Published: September 2024

Recent research advances in deep neural network (DNN)-based beamformers have shown great promise for speech enhancement under adverse acoustic conditions. Different network architectures and input features have been explored in estimating beamforming weights. In this paper, we propose a deep beamformer based on an efficient convolutional recurrent network (CRN) trained with a novel ARray RespOnse-aWare (ARROW) loss function. The ARROW loss exploits the array responses of the target and interferer by using the ground truth relative transfer functions (RTFs). The DNN-based beamforming system, trained with ARROW loss through supervised learning, is able to perform speech enhancement and speaker localization jointly. Experimental results have shown that the proposed deep beamformer, trained with the linearly weighted scale-invariant source-to-noise ratio (SI-SNR) and ARROW loss functions, achieves superior performance in speech enhancement and speaker localization compared to two baselines.
A Segmentation-Based Automated Corneal Ulcer Grading System for Ocular Staining Images Using Deep Learning and Hough Circle Transform
Authors: Manawongsakul Dulyawat , Patanukhom Karn
Published: September 2024

Corneal ulcer is a prevalent ocular condition that requires ophthalmologists to diagnose, assess, and monitor symptoms. During examination, ophthalmologists must identify the corneal ulcer area and evaluate its severity by manually comparing ocular staining images with severity indices. However, manual assessment is time-consuming and may provide inconsistent results. Variations can occur with repeated evaluations of the same images or with grading among different evaluators. To address this problem, we propose an automated corneal ulcer grading system for ocular staining images based on deep learning techniques and the Hough Circle Transform. The algorithm is structured into two components for cornea segmentation and corneal ulcer segmentation. Initially, we apply a deep learning method combined with the Hough Circle Transform to segment cornea areas. Subsequently, we develop the corneal ulcer segmentation model using deep learning methods. In this phase, the predicted cornea areas are utilized as masks for training the corneal ulcer segmentation models during the learning phase. Finally, this algorithm uses the results from these two components to determine two outputs: (1) the percentage of the ulcerated area on the cornea, and (2) the severity degree of the corneal ulcer based on the Type–Grade (TG) grading standard. These methodologies aim to enhance diagnostic efficiency across two key aspects: (1) ensuring consistency by delivering uniform and dependable results, and (2) enhancing robustness by effectively handling variations in eye size. In this research, our proposed method is evaluated using the SUSTech-SYSU public dataset, achieving an Intersection over Union of 89.23% for cornea segmentation and 82.94% for corneal ulcer segmentation, along with a Mean Absolute Error of 2.51% for determining the percentage of the ulcerated area on the cornea and an Accuracy of 86.15% for severity grading.
An Economic Perspective on the Implementation of Artificial Intelligence in the Restaurant Sector
Authors: Dancausa Millán Mª Genoveva , Millán Vázquez de la Torre Mª Genoveva
Published: September 2024

Technology is evolving and being implemented across nearly every sector of society, including health, nutrition, and sustainability. Specifically, artificial intelligence (AI) has become an essential tool in gastronomy, not only facilitating chefs’ work but also fostering business innovation through cost reduction. However, for a gastronomic business to be profitable, it is crucial to understand its strategic elements. In this study, three groups associated with gastronomy—chefs, entrepreneurs, and gastronomic experts—were surveyed to gather their opinions on the application of artificial intelligence in the restaurant sector in Spain. Additionally, the Business Model Canvas and Lean Model Canvas were developed, specifically adapted for the restaurant sector. These models, as novel approaches, allowed for the identification of key success factors based on the respondents’ experiences, considering that the Business Model Canvas focuses on the market and the company, while the Lean Model Canvas prioritizes the market and the product. This distinction is essential for mitigating the high failure rate in the restaurant industry in Spain. The results from the Canvas models and SWOT analysis have allowed us to understand the participants’ views. They largely see the use of AI in gastronomy as beneficial due to innovation in recipes and cost savings. However, concerns were raised about the potential loss of human touch in dish preparation and increased unemployment due to the automation of some cooking processes. These findings could be highly relevant for future restaurant entrepreneurs.
Mixed-Flow Turbofan Engine Model for the Conceptual Design of Sustainable Supersonic Airplanes
Authors: Piccirillo Grazia , Gregorio Antonio , Fusaro Roberta , Ferretto Davide , Viola Nicole
Published: September 2024

Current research efforts on commercial supersonic flight aim to overcome past challenges by designing a new generation of sustainable supersonic airplanes. Achieving this goal requires careful consideration of the propulsion system during the design process. This study proposes a mixed-flow turbofan engine model coupled with emission estimation routines to increase the reliability of the conceptual design of future supersonic aircraft. The model enables parametric analyses by analyzing variations in main engine design parameters (πc,πf, BPR) as function of the system and mission requirements, such as the Mach number, and suggesting applicability boundaries. The overall methodology was applied to a low-boom Mach 1.5 case study, allowing for both on-design and off-design analyses and generating a propulsive database to support preliminary mission simulations and chemical emission estimation. Finally, the accuracy and reliability of the engine model was validated against GSP 11 data for a generic mixed-flow turbofan engine. A modified version of the Fuel Flow Method, originally developed by Boeing, allows for emissions estimation throughout the mission for a supersonic engine using biofuels. The application of the methodology led to the definition of an engine with a πc  of 30 and BPR of 0.7 for the selected case study, which was successful in meeting the initial mission requirements.
Monocular Visual Pig Weight Estimation Method Based on the EfficientVit-C Model
Authors: Wan Songtai , Fang Hui , Wang Xiaoshuai
Published: September 2024

The meat industry is closely related to people’s daily lives and health, and with the growing global population and increasing demand for meat, the development of efficient pig farming technology is particularly important. However, China’s pig industry still faces multiple challenges, such as high labor costs, high biosecurity risks, and low production efficiency. Therefore, there is an urgent need to develop a fast, accurate, and non-invasive method to estimate pig body data to increase production efficiency, enhance biosecurity measures, and improve pig health. This study proposes EfficientVit-C model for image segmentation and cascade several models to estimate the weight of pigs. The EfficientVit-C network uses a cascading group attention module and improves computational efficiency through parameter redistribution and structured pruning. This method uses only one camera for weight estimation, reducing equipment costs and maintenance expenses. The results show that the improved EfficientVit-C model can segment pigs accurately and efficiently the mAP50 curve convergence is 98.2%, the recall is 92.6%, and the precision is 96.5%. The accuracy of pig weight estimation is 100 kg +/− 3.11 kg. On the Jetson Orin NX platform, the average time to complete image segmentation for each 640*480 resolution image was 4.1 ms, and the average time required to complete pig weight estimation was 31 ms. The results show that this method can quickly and accurately estimate the weight of pigs and provide guidance for the subsequent weight evaluation procedures of pigs.