bluuebunny/crossref_metadata_2025 huggingface dataset:
NAPH-Fluorescence Lifetime Imaging informed machine learning modelling reliably predicts Temozolomide responsiveness in Glioblastoma
Authors: Pastore Aldo , Corradi Elena , Morelli Mariangela , Mazzanti Chiara , Aretini Paolo
Published: March 2024

Glioblastoma (GBM) is a highly deadly brain tumor. The chemotherapeutic treatment still lacks solid patient stratification, as temozolomide (TMZ) is administered to the majority of GBM patients. In this study, we explored the effectiveness of NAD(P)H-fluorescence lifetime imaging microscopy (NAD(P)H-FLIM) in furnishing clinically relevant insights into GBM responsiveness, a realm constrained by the absence of corresponding clinical outcome data. Using the information obtained by NAD(P)H-FLIM, we conducted a DE analysis on an RNA-seq private dataset, comparing TMZ responder and non-responder tumors. To validate the NAD(P)H-FLIM classification, we conducted a comparable DE analysis on the GBM TCGA (The Cancer Genome Atlas) RNA-seq data using the progression-free interval (PFI) as a responsiveness indicator. We selected the most informative genes shared by both the DE analyses (BIRC3, CBLC, IL6, PTX3, SRD5A1, TNFAIP3) and employed them as transcriptomic signature. Using a different dataset (GBM TCGA Agilent-Microarray), we built a signature-based machine learning model capable of predicting the PFI. We also showed that the performance of our model is similar to that obtained with a well-established biomarker: the methylation status of the MGMT promoter. In conclusion, we assessed the reliability of the NAD(P)H-FLIM in providing clinically relevant drug response information in GBM and provided a new transcriptomic based model for determining patients’ responsiveness to TMZ treatment.
The predictive role of PD-L1 expression and CD8+ TIL levels in determining the neoadjuvant chemotherapy response in advanced ovarian cancer.
Authors: Aliyeva Turkan , Elvin Chalabiyev , Fatma Gundogdu , Aktas Burak Yasin , Arik Zafer , Usubutun Alp
Published: March 2024

Objective: To analyze how the PD-L1 expression and CD8+ tumor infiltrating lymphocyte (TIL) levels in biopsy samples before neoadjuvant chemotherapy (NAC) can predict chemotherapy response score and survival for advanced high-grade serous ovarian cancer.
Methods: We retrospectively analyzed 45 patients with advanced epithelial ovarian cancer between 2010 and 2018, who had received at least three cycles of neoadjuvant chemotherapy. PD-L1 expression and CD8+ TIL levels were evaluated by immunohistochemical staining in the pre-NAC tumor samples from which the patients had been diagnosed. The post-NACT tissue samples taken during interval debulking surgery (IDS) were used to evaluate the chemotherapy response score (CRS).
Results: Among all the patients, CRS 1 (no response) was found in 8 patients, CRS 2 (partial response) in 28 patients, and CRS 3 (complete response) in 9 patients. A total of 20 (44.4%) patients had high intraepithelial CD8+ TIL levels, and 35(77.8%) patients had high expression stromal CD8 TIL. No statistically significant relationship was found between high and low expression of intratumoral/stromal CD8+ TIL levels with PFS and CRS. The study found that 33(73.3%) patients had high levels of stromal PD-L1 expression and 28(62.2%) patients had high levels of intratumoral PD-L1 expression. In the intratumoral PD-L1 group, patients with low expression had a PFS of 28 months, whereas those with high expression had a PFS of 17 months (p=0.028). Among the patients with high intratumoral PD-L1 expression, 23 (82.1%) patients showed CRS2, 4 (44.4%) showed CRS3, and only 1(3.6%) showed CRS1 (p=0.000). However, high or low expression stromal PD-L1 did not significantly affect PFS and CRS (p=0.928 and p=0.305; respectively).
Conclusions: We found that intraepithelial PD-L1 expression levels in diagnostic biopsy in ovarian cancer can predict the chemotherapy response score in interval debulking surgery.
Quantum-inspired modeling of distributed intelligence systems with artificial intelligent agents self-organization
Authors: Alodjants Alexander , Tsarev Dmitriy , Avdyushina Anna , Boukhanovsky Alexander , Khrennikov Andrei
Published: March 2024

Distributed intelligence systems (DIS) containing natural (NIA) and artificial (AIA) intelligence agents of decision making (DM) belong to interdisciplinary areas of promising studies aimed at digitalization of routine processes in industry, economy, management, and everyday life. In this work, we suggest a novel quantum-inspired approach to study crucial features of DIS consisting of NIAs (users) and AIAs (digital assistants) that possess self-organization within a complex network. We propose a mapping procedure for Russell’s valence-arousal circumplex model onto an effective quantum-like two-level system to characterize a NIA cognitive system in a simple DM process. We demonstrate that conditions for opinion formation and social impact in a DIS are relevant to the second-order (laser-like) phase transition that establishes a nonvanishing average information field in the DIS, which is reminiscent of the social laser phenomenon that may appear in social networks. We demonstrate the complex behavior of social impact in the DIS that implies the hierarchical formation of opinion leaders in the network, which we elucidated using the eigenvector centrality criterion. We introduce a set of cooperativity parameters for the users, which play a significant role in DIS features. Cooperativity parameters reveal how frequently AIAs and NIAs communicate with each other accounting for their facilities in information exchange. We show that at weak AIA -- NIA coupling many uncertainties in the DIS complicate a certain (non-zero) opinion formation for DM agents. We offer an adaptive approach to increase the users' impact by establishing a network-dependent coupling rate with their digital assistants. In this case, the mechanism of AIA control helps resolve the DM process in the presence of some uncertainties evoked by the variety of users' preferences. Our findings open new prospectives in different areas where AIAs represent useful teammates in solving common problems with humans in the framework of network organizations.
MS-GD-P: Priority-Based Service Deployment for Cloud-Edge-End Scenarios
Authors: Jin Honghua , Wang Haiyan , Luo Jian
Published: March 2024

In cloud-edge-end scenarios, how to achieve rational resource allocation, implement effective service deployment, and ensure high service quality has become a hot research topic in academic domains. Service providers usually deploy services by considering the characteristics of different geographical regions, which helps to meet the diverse needs of users in different regions and optimize resource allocation and utilization. However, due to the widespread distribution of users and limited server resources, providing all types of services to users in every geographical region is not feasible. In addition, edge servers are prone to operational failures caused by software anomalies, hardware malfunctions, and malicious attacks, which will decrease service reliability. To address the problems above, this paper proposes a metric for service priorities based on user demands and regional characteristics for different geographical regions. Building upon this foundation, a Multi-Service Geographic region Deployment based on Priority (MS-GD-P) is proposed. This method takes user coverage and service reliability into consideration, which facilitates users' needs for multiple services in different geographical regions. Experimental results on real datasets demonstrate that MS-GD-P outperforms baseline methods in user coverage and service reliability.
The superiority trial of Baduanjin training on patients Chronic Low back pain: a study protocol for a randomized controlled trial
Authors: Tan Tianyang , Cao Bing yan , Liang Wen ming , Lou Shuang , Han Zheng , Ji Yu xuan , Xiao Jing
Published: March 2024

Background
CNSLBP accounts for 85% of all LBP cases and impairs physical health, quality of life, and work productivity, posing a significant health and economic burden. Baduanjin (BDJ) exercises are traditional Chinese Qi Gong mind-body exercises that have been practiced for over 1,000 years. However, the standard BDJ protocol established by the State Sports General Administration does not stimulate core muscles, limiting the effectiveness of low back pain rehabilitation. Therefore, it is necessary to improve the original BDJ protocol.
Methods:
This 24-week single‐center, single-blind, parallel-group randomized control superiority trial will allocate 100 patients into two groups (control and intervention) at a 1:1 ratio. The patients in the control group will perform the standard BDJ protocol established by the State Sports General Administration. The patients in the patients in the control group will perform the standard BDJ protocol established by the State Sports General Administration. The intervention group will perform intervention. The primary outcomes will be Quebec back pain disability scale. Secondary outcomes will include visual analog scale pain scores, Surface electromyography. The assessments of the tests will be performed at four time points. Adverse events will be recorded faithfully during the study.
Discussion:
This randomized control trial is the first to compare a standard BDJ protocol and an optimized protocol in patients with CNSLBP. This study can help guide rehabilitation programs.
Trial registration:
Chinese Clinical Trial Registry, ChiCTR2200065618, Registered on 10 Nov. 2022
Identification and validation of inflammatory subtypes in Intrahepatic Cholangiocellular Carcinoma
Authors: Gao Biao , Wang Yafei , Zhang Xianzhou , Jiang Hao , Han Feng , Li Chonghui , Lu Shichun
Published: March 2024

Background: Inflammation plays an important role in tumor development, and inflammatory cell infiltration and inflammatory mediator production cause changes in the tumour microenvironment(TME), especially in intrahepatic cholangiocellular carcinoma(ICC). However, determining the inflammatory state of patients based on reliable biomarkers is still being explored.
Method: RNA sequencing, gene mutations, and corresponding clinical of 244 ICC patients were derived from previous studies. Consensus clustering was performed to identify molecular subtypes associated with inflammation. Prognosis, clinical features, somatic mutation profiles and immune cell infiltration were compared across inflammatory subtypes. Quantitative real-time polymerase chain reaction(qRT-PCR) and immunohistochemistry(IHC) were used to confirm gene overexpression.Logistic regression analyses were used to construct nomogram predicting inflammatory status of patients with ICC.
Results: Our results confirm that ICC can be categorised into inflammation-high subtype(IHS) and inflammation-high subtype(ILS), a and that both groups have different prognosis, clinical features and TME composition. The IHS has a poorer prognosis due to the immunosuppressive microenvironment and high frequency of KRAS and TP53 gene mutations.Cancer-associated fibroblast(CAF)-derived COLEC11 reduces myeloid inflammatory cell infiltration and attenuates the inflammatory response. qRT-PCR and IHC confirm that tumor tissue promotes tumor cell progression by downregulating COLEC11 expression. The IHS was more likely to be responsive to immune checkpoint inhibitors(ICIs) attributed to higher tumor mutational load scores, tumor neoantigen scores, neoantigen counts and immune checkpoint expression levels. Finally, we developed a nomogram that can effectively predict inflammatory status in patients with ICC based on clinical features and inflammatory gene expression levels. The calibration, discrimination and clinical utility of the nomogram were evaluated.
Conclusion: The inflammatory response of the IHS is mainly induced by myeloid cells, and COLEC11 can reduce the infiltration level of this group of cells, and targeting myeloid inflammatory cells is expected to be a new target for ICC treatment. We have created a novel nomogram that can effectively predict the inflammatory state of ICC patients, which is useful for guiding the individualised treatment plan.
The SPECTRA study: using co-design to develop a new memory training program for older adults based on the Episodic Specificity Induction
Authors: PURKART Rudy , MELLAH Samira , BELLEVILLE Sylvie
Published: March 2024

Background. Normal aging impacts episodic memory retrieval. Given the crucial role of retrieval for abilities such as future thinking and social problem-solving, the potential of cognitive interventions targeting retrieval extends beyond memory enhancement. Yet only a limited number of such interventions exist. This article outlines the design process of a novel memory training program targeting episodic retrieval.
Methods. Using an Intervention Mapping approach, a general outline of the training program was created by leveraging the knowledge base on older adults’ retrieval performance and the principles of the Episodic Specificity Induction (ESI) technique. Two in-person 2-hour co-creation sessions with a focus group of six healthy older adults were conducted in Montréal (Québec, Canada) to develop guidelines for adapting the ESI technique into a training format and to determine tailored user-relevant content. Session recordings and notes were qualitatively analyzed. Training format and content proposed by the focus group were reviewed and approved by the research team.
Results. The co-designed training program consisted in six 2-hour sessions provided in small groups of 4 participants. Sessions included supervised ESI administration, complemented by unsupervised ESI self-administration at home.
Conclusion. A new program was co-designed to enhance memory retrieval in older adults using the ESI technique. Co-designing the program increases the likelihood that its content and structure respond to users’ challenges and needs, thereby enhancing relevance, engagement, and retention. It holds the potential to generate lasting improvements in retrieval and transfer to crucial cognitive and social abilities.
The Mystery of Black Rice: food, medicinal and spiritual use of Oryza glaberrima by Maroons in Suriname and French Guyana
Authors: Pinas Nicholaas , Jackson John , Mosis Noeki André , Andel Tinde
Published: March 2024

During plantation slavery, African rice (Oryza glaberrima Steud.) was widely cultivated in the Americas but it was soon replaced by Asian rice (Oryza sativa L.). Maroons, descendants of Africans who escaped slavery in Suriname, are nowadays the only ones who cultivate African rice. They claim that their ancestors found it growing wild in a swamp owned by a forest spirit, but its specific use remained unclear. Genomic research linked this rice to an O. glaberrima variety in the Ivory Coast, but how did a fully domesticated African crop end up wild in an Amazonian swamp? Based on interviews with 99 Maroon farmers, of which 20% cultivated black rice, we describe its diverse uses in (ceremonial) food, offerings, spiritual medicine, and its role during funerals. Maroon's oral history accounts on the origin of black rice differ between and within communities: enslaved women brought it from Africa or plantations, runaways found it in the savanna during their escape, and ancestors encountered it in interior swamps. The ability of black rice to compete with weeds, grow on poor soil, its shattering seeds, and its visibility to birds explains how this African domesticate could become wild in the Amazonian forest. Migration to cities, gold mining, and evangelization may lead to the loss of black rice knowledge and practices. The multiple and sometimes contradicting stories about black rice have to do with the diverse ethnic and geographical backgrounds of the Africans who were brought to Suriname and their different histories with the crop after marronnage.
Reliability and Quality of Online Multiple Mini interviews for Admissions in an MBBS program
Authors: Iftikhar Sundus , Shoaib Syed Hasan , Sarfaraz Shaur , Ali Syed Kauser
Published: March 2024

Background: MMI is a widely used method for assessing the non-cognitive skills of students, but the logistics and costs associated with organizing in-person MMI can be substantial. Virtual MMI, such as those conducted through platforms like WhatsApp Video calls, offer increased convenience, yet their reliability and quality remain uncertain. The objective of the study is to determine the reliability and quality (difficulty and discrimination indices) metrics of MMI scores conducted through WhatsApp Video call.
Methods: Six MMI stations were used to assess the non-cognitive attributes of the students. In this descriptive study, the scores obtained by 678 students in MMI, F.Sc (equivalent of high school) and MDCAT were used to analyze the data. Item analysis was employed to assess quality of MMI stations. The reliability was calculated using Cronbach’s alpha and Pearson correlation (r) was performed between MDCAT scores, F.Sc. Scores and MMI scores to assess significant correlation.
Results: The overall reliability of MMI in this study was 0.87 while the reliability for each interview station ranged between 0.92 - 0.95. The difficulty level of MMI stations ranged from easy (0.57) to moderately difficult (0.77). The discrimination index was found to be in the range of 0.53-0.78.
Conclusion: The psychometric analysis of MMI scores demonstrated good reliability and quality (discrimination and difficulty index) with the stations showing acceptable discrimination and moderate difficulty. Hence, online multiple mini-interviews were found useful to assess non-cognitive skills for admission in MBBS program.
Hydrogen-rich water enhanced salt tolerance in tomato seedlings by regulating strigolactone biosynthesis genes SlMAX1 and SlD27
Authors: Ye Fujin , Fang Hua , Feng Li , Shi Meimei , Yang Ruirui , Liao Weibiao
Published: March 2024

Background
Hydrogen gas (H2) and strigolactones (SLs) are involved in various biotic and abiotic stress response in plants. However, the crosstalk between H2 and SLs has not been investigated.
Methods
Using pharmacological methods and virus-induced gene-silencing, the regulatory roles of H2 and SLs and their interaction in tomato (Solanum lycopersicum L. ‘Micro-Tom’) under salt stress were investigated.
Results
Both GR24 (a SLs synthetic analog) and hydrogen rich water (HRW, a H2 donor) significantly reversed salt-induced growth retardation as evidenced by promoted root morphological parameters and root activity. SLs might be involved in H2-enhanced salt stress tolerance in tomato seedling roots. Additionally, HRW treatment increased endogenous SLs content in tomato seedling roots under salt stress However, the positive roles of HRW were blocked by TIS108 (a specific SLs synthesis). In addition, HRW and GR24 could effectively maintain the integrity of the internal anatomical structure in roots under salt stress; while TIS108 also inhibited the positive roles of HRW. Thus,. Simultaneously, HRW treatment significantly up-regulated the expression levels of SL biosynthesis-related genes SlCCD7, SlCCD8, SlD27 and SlMAX1 and SL signal transduction genes SlD14 and SlMAX2 under salt stress. Further, after silencing SlD27 and SlMAX1 genes, the alleviation effect of HRW on tomato roots under salt stress was basically eliminated. HRW did not increase the content of endogenous SLs in SlD27 and SlMAX1 silenced seedlings.
Conclusion
SLs biosynthesis genes SlMAX1 and SlD27 may be involved in H2-alleviated salt stress in tomato seedlings.
The inhibitory effect of isavuconazole on almonertinib metabolism and its underlying mechanism
Authors: Chen Zhe , Liu Ya-nan , Xia Hailun , Yu Yige , Xu Ren-ai
Published: March 2024

As a third-generation epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), almonertinib is effective for the treatment of non-small cell lung cancer (NSCLC), and there is not much interaction research on its combination with other drugs. Here, an ultra performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) was validated and enabled stable and rapid determination of plasma concentrations of almonertinib and its main metabolite HAS-719. In human liver microsomes (HLMs), rat liver microsomes (RLMs) and recombinant human CYP3A4 (rCYP3A4), we found that isavuconazole as an inhibitor was able to inhibit almonertinib metabolism at medium inhibitory effect with IC50 of 5.26 µM, 1.59 µM and 1.14 µM, respectively. In addition, we further investigated the mechanism of inhibition of almonertinib by isavuconazole in HLMs and RLMs in vitro as the mixed inhibitory mechanism and in rCYP3A4 with the competitive inhibition. Almonertinib's pharmacokinetic parameters, such as AUC(0−t), CLz/F, and Cmax, were significantly altered by isavuconazole in pharmacokinetic experiments in rats, but did not affect the metabolism of HAS-719. The above results showed that isavuconazole inhibited the metabolism of almonertinib in vivo and in vitro, which will alert the plasma concentration of almonertinib in clinic. Thus, the interaction between almonertinib and isavuconazole should be taken into consideration when almonertinib is used in the clinic.
Physiological Vital Time Series Forecasting using Fractional Calculus and Deep Neural Network
Authors: Nemati Sama , Jafari Seyed Amin Seyed , Fakhri Mostafa , Seraji Kosar , Vosoughi-Motlagh Farzane , Hajihasani Mojtaba
Published: March 2024

Continuous physiological monitoring integrated with time series analysis and multi-step forecasting is vital when encountering postoperative cases either hospitalized in intensive care units (ICU) or given home health care will experience adverse cardiac events. The low-cost common vital signs, i.e., heart rate and arterial blood pressure are captured and predicted with adjustable horizons up to 30 minutes in advance to achieve punctual clinical decision-making to prevent the events of bradycardia, tachycardia, hypo-tension, and hypertension. Scaling properties of physiological stationary/non-stationary signals are necessarily determined and drastically affected by the selection and architecture design of time series forecasting models. In contrast to integer-order difference that achieves stationary memory-erased series, fractional order difference ensures the stationary of the data while preserving as much memory as possible. The deep learning architecture for multi-step forecasting is the combination of two direct and iterative methods which utilizes the concepts of U-Net convolutional networks and multi-layer bi-directional long short-term memories (Bi-LSTMs). Various scenarios of observe-target windows e.g. (20, 30, 60, or 120) - (7, 15, 20, or 30) minutes are trained using hyper-parameter tuning and evaluated by mean absolute percentage error (MAPE). The results of the proposed method indicate that crucial vital signs such as heart rate, systolic blood pressure and mean arterial blood pressure will be predictable in an adjustable observe-target window size from 20 − 7 to 120 − 30 minutes with narrow ranges of MAPE values between [2.78%, 4.17%], [4.69%, 6.47%] and [4.45%, 6.86%], respectively.
State and Disturbance Observer based Robust Disturbance Rejection Control for Friction Electro-Hydraulic Load Simulator
Authors: Jing Chenghu , Zhang Hui , Yan Bingsheng , Hui Yanbo , Xu Hongguang
Published: March 2024

Friction electro-hydraulic load simulator (FEHLS) classified as an electro-hydraulic torque servo mechanism, encounters significant challenges in the form of parameter uncertainties, external disturbances, and unmodeled dynamics, all of which notably degrade the system's capacity for accurate tracking. This study introduces the design of a state-and-disturbance estimation observer (SDEO) aimed at approximating unobservable states and nonconforming perturbations. A specifically tailored nonlinear disturbance observer (NDO) is constructed for the purpose of estimating such mismatched disturbances. Using backstepping designed method with prescribed performance, robust disturbance rejection control (RDRC) is proposed, ingeniously integrating SDEO, NDO, and a continuous sliding mode control. The stability of the proposed RDRC is systematically scrutinized utilizing the principles of Lyapunov stability method. The practical efficacy and robustness of the devised control scheme have been convincingly validated through meticulous experimental execution and analysis.
Whole genome sequencing and analysis of the symbiotic Armillaria gallica M3 with Gastrodia elata
Authors: Luo Chengying , Lu Yao , Su Lei , Li Xindong , Liu Jiajia , Miao Jiayun , Lin Yicen , Lin Lianbing
Published: March 2024

Background
Armillariaare phytopathogens that cause severe root rot of trees in forests, but at the same time, some Armillaria are important symbiotic fungi of the valuable Chinese herb Gastrodia elata. Currently, the whole genome database of Armillaria is relatively limited, and it is expected that a more comprehensive understanding of the symbiotic interactions between Armillaria and G. elata can be achieved through genome-wide comparisons and functional annotations. Whole genome sequencing of Armillaria gallica M3 strain was performed using Oxford Nanopore Technologies sequencing platform, and the sequencing data were used to perform genome assembly, gene prediction and functional annotation, carbohydrate-active enzymes, and host-pathogen interactions using bioinformatics methods.
Results
In this study, we obtained an 83.33 M genome of A. gallicaM3 strain, which consisted of 38 overlapping clusters with an N50 of 6,065,498 bp and a GC content of 47.43 %. A total of 12,557 genes were identified in the genome of A. gallica M3, and the repetitive sequences accounted for about 44.36 % of the genome. 42.26 % of the genome was composed of glycoside hydrolases (GHs), 16.15 % of the genome was composed of glycosyltransferases (GTs), and 16.15 % of the genome was composed of glycoside hydrolases (GHs). GHs accounted for 42.26 % and glycosyltransferases (GTs) for 16.15 %. In addition, 3412 genes in A. gallica M3 were involved in the host-pathogen interaction mechanism.
Conclusions
These results have elucidated the characteristics of A. gallica M3 from a genomic perspective to a certain extent. They help to analyze the inner mechanism of A. gallicaM3 being able to symbiosis with G. elataat the genomic level, which is of great significance to the next related research of A. gallica M3.
Biomechanical effects of different approaches and titanium mesh in combined anterior cervical corpectomy decompression and fusion：a finite element study
Authors: Li Dan , Yu Yuting , Dong Chao , Zhou Bo , Gu Lin
Published: March 2024

Background: Anterior Cervical Corpectomy and Fusion(ACCF), which is one of the common surgeries used to treat cervical spine diseases, has been widely applied in clinical practice. The commonly used internal fixation forms in ACCF surgery include the traditional anterior vertebral body screw-plate (AVBSP) structure and the anterior cervical pedicle screw-plate (APSP) structure, both of which are combined with titanium mesh to achieve support and bone fusion.
Objetives: The purpose was to investigate the effects of different surgical plans on cervical spine biomechanics and the interplay between internal fixation instruments after surgery.
Methods: In this study, a finite element model of the human lower cervical spine (C3-C7) after ACCF surgery was established. The surgical plan consisted of two internal fixation forms (AVBSP and APSP) and two titanium mesh forms (linear and curved), combined in different ways.
Results: The mechanical sensitivity of adjacent intervertebral disc nuclei to different surgical plans was significantly different. The stress concentration areas on the vertebral body entry surface varied with different entry methods, and the stress values were greatly affected by cervical movements. The related instrument studies showed that the choice of anterior fixation method would affect the stress level and distribution of the titanium mesh. Theoretically, the combination of curved titanium mesh and AVBSP is beneficial to reducing the overall stress level of the internal fixation instruments and titanium mesh.
Conclusion:The research provides theoretical basis for the selection of clinical surgical plans. It is advantageous in enhancing postoperative stability of cervical vertebrae while reducing the risk of recurrence or other complications such as adjacent segment disease. Clinically, when selecting the excision fusion surgical plan based on the condition of the patient's cervical lesion, consideration should also be given to the matching characteristics between internal fixation methods and titanium mesh forms, as well as their effects on the biomechanics of adjacent segments.
A simple structure and high sensitivity side-polished micro-structured fiber RI sensor based on open-loop channel gold-coated
Authors: Wang Yujun , Li Peng , Liu Yundong , Tang Chunjuan , Liu Lina , Shan Feng
Published: March 2024

A highly sensitive and simple structure side-polished micro-structured fiber (MOF) refractive index (RI) sensor based on surface plasmon resonance (SPR) is proposed and studied by the finite element method (FEM). The gold nanofilm used to stimulate plasmons is directly deposited on the inner wall of the open-loop channel of a MOF consisting of an arrangement of six cladding air-holes. The sample analyte is arranged on the outer surface of the optical fiber to improve the utilization rate of the sensor and reduce the tediousness of operation. Meanwhile, in order to increase the leakage intensity of evanescent field, three large air-holes were introduced near the fiber core. Research has shown that the proposed sensor can achieve sensing detection in the range of 1.19–1.37 RI. The maximum sensitivity in the x-polarized direction can reach 12,500 nm/RIU, and its corresponding resolution is 3.64 × 10− 5 RIU. Moreover, it has a high linear response of 0.9944 within the RI detection range of 1.19–1.33. Obviously, the proposed sensor has a simple structure, wide RI detection range, and high sensitivity, which can make it widely used in biomedical and analytical chemistry.
Historical contingencies linked to past drought-wetting cycles as a driver of bacterial–not fungal–community assembly processes in an arid desert
Authors: Maurice Kenji , Boukcim Hassan , Selosse Marc-André , Ducousso Marc
Published: March 2024

Soil microbial communities are complex and dynamic, and their composition is jointly driven by niche and neutral processes. Otherwise, the assembly processes of these communities are known to be influenced by both biotic and abiotic factors, yet the extent to which past events could explain their contemporary composition remains unclear, particularly in natural desert environments. We used a phylogenetic framework to quantify the deterministic and stochastic community assembly processes of bacteria and fungi facing historical contingencies linked to past short- and long-term drought-wetting cycles. We found that deterministic and stochastic processes underpinned bacterial community assembly, while fungal communities were mainly assembled via stochastic processes. Abundant bacterial species were at the origin of the differences in phylodiversity noted between natural sites and those facing historical contingencies, while rare fungal species were at the origin of these differences. Furthermore, we showed that historical contingencies increased selection while decreasing dispersal limitation and homogeneous dispersal of bacterial communities. Yet fungal communities were found to be unaffected by past events and their assembly was constantly supported by stochastic processes. These results shed light on the differential impacts of historical contingencies on both bacteria and fungi. They also provide crucial information that could contribute to enhancing desert ecosystem resilience and conservation, and improving our comprehension of soil microbial community assembly in desert ecosystems.
Validation of the Molecular International Prognostic Scoring System (IPSS-M) for myelodysplastic neoplasms (MDS) and comparison with the revised International Prognostic Scoring System (IPSS-R) in Chinese Population: A Multicenter Retrospective Study.
Authors: Hu Mengmeng , Zhou Ming , Shen Yingying , He Guangsheng , Huang Li , Zhou Shujuan , Fu Jiaping , Jiang Huifang , Chen Sai , Ye Xiujin , Zheng Zhiyin , Wu Liqiang , Wang Bo , Wu Gongqiang , Lin Shengyun , Ye Baodong , Yu Qinghong
Published: March 2024

Objectives The Revised international prognostic scoring system (IPSS-R) is now commonly being used clinically to guide the treatment of myelodysplastic neoplasms (MDS). Recently, the Molecular International Prognostic Scoring System (IPSS-M)was proposed. In this study, we have validated the potential predictive value of the comparative IPSS-M in Chinese MDS patients.
Design Retrospective multicenter observational study.
Setting and participants 113 MDS patients(April 2019 - June 2022) from 10 distinct centers in Jiangnan region of China, grouped by IPSS-R and IPSS-M was obtained and the scoring criteria were retrospectively analyzed to compare the prognostic assessment efficacy of the different prognostic assessment systems.
Main outcome measures The prognostic indicators of MDS patients are main outcome measures.
Results 72 (63.7%) patients were reclassified after regrouping from IPSS-R to IPSS-M, and 52 of them were transferred to a higher risk group, with a higher percentage of patients aged ≥ 60 years in the higher risk group. Survival analysis confirmed that overall survival(OS) was variable in the different risk strata, with shorter survival time in the higher risk group and lower OS in the older(≥ 60 years) than in the younger group; whereas in univariate and multifactorial analysis, age ≥ 60 years, percentage of bone marrow blasts, chromosomal classification of IPSS-R, TP53, RUNX1, DNMT3A, NRAS, CBL, GNAS, and FLT3_ITD gene mutation were associated with OS. Leukemia-free survival(LFS)analysis revealed that higher IPSS-R and IPSS-M risk stratification was linked with shorter LFS time. Receiver operating characteristic (ROC) curves were drawn according to OS displaying AUC = 0.629 for IPSS-R and AUC = 0.705 for IPSS-M; AUC = 0.635 for IPSS-M younger group and AUC = 0.691 for older group.
Conclusions Our study confirmed that the IPSS-M prognostic scoring system could be applicable to Chinese patients and that IPSS-M was significantly better than IPSS-R for the prognostic assessment of MDS patients. Moreover, IPSS-M appeared to have better predictive validity in older patients compared to younger patients.
Research on Applying Machine Learning Models to Predict and Assess Return on Assets (Roa)
Authors: Pham Vu Hong Son , Le Tung Duong
Published: March 2024

Return on Assets (ROA), a profitability measure, is crucial in corporate finance for assessing how efficiently a company uses assets to generate profit. Currently, the prediction of the ROA index at present is a tedious, manual process. It usually involves making educated guesses or waiting for the accurate data, which becomes available only after financial reports have been compiled. This paper introduces a machine learning model for predicting the ROA index. The model draws data from 78 companies listed on the Vietnam Stock Exchanges (HOSE and HNX) over the span of 2012 to 2022.The Random Forest (RF) model was put to the test using datasets from selected Vietnamese businesses in 2023. The results demonstrated a high level of precision, with an error rate of less than 1%, an R2 value of 0.9762, and a Root Mean Square Error (RMSE) of 0.5826. These findings indicate potential real-world uses in predicting and boosting business performance. In conclusion, the integration of machine learning in financial analysis and prediction represents substantial progress. It enhances both accuracy and efficiency and holds promise for future advancements in financial management practices. This study aims to encourage more research and development in this area, leading to more advanced and efficient financial management tools.
The Association Between County Ordinances Allowing Off-Road Vehicles on Public Roads and Crash Rates
Authors: Monson Christopher D. , Vakkalanka J. Priyanka , Denning Gerene M. , Stange Nicholas R. , Jennissen Charles A.
Published: March 2024

Background
Legislative bodies across the country have increasingly allowed off-road vehicles (ORVs) including all-terrain vehicles (ATVs) and utility task vehicles (UTVs) on public roads, an environment for which they are not designed. In 2009, Iowa gave individual counties the discretion to pass ordinances allowing ORVs on public roadways. The objective of this study was to evaluate the relationship between the passage of ORV ordinances and ORV crash rates, especially on public roads.
Methods
An Iowa ORV roadway ordinance database and an Iowa ORV crash database (2002-2018) for all 99 counties were compiled. Crashes for which county location could not be determined were excluded. Utilizing a zero-inflated Poisson model, correcting for background crash frequency trends and population, investigators compared the relative rates of crashes after ordinance passage to time points before ordinance implementation and to counties without such ordinances. Sub-analyses, including that focused on more recent years (2008-2018), were also performed.
Results
Forty-five county ORV roadway ordinances went into effect between 2011-2018 and 2,347 crashes (69%) met inclusion criteria. Adjusted for year, there was a 58% greater ORV crash rate in counties after passing an ORV roadway ordinance (incidence rate ratio (IRR) 1.58, 95% CI 1.32-1.90). Roadway crashes (n=834) increased 48% after ordinance passage (IRR 1.48, 95% CI 1.14-1.94). This roadway crash association remained statistically significant when analysis was limited to the years 2008-2018 (IRR 1.39, CI 1.06-1.83, n=544); to ATV crashes only (IRR 1.70, CI 1.20-2.40, n=683); and to ATV crashes excluding counties with UTV-only ordinances (IRR 1.74, CI 1.40-2.15, n=2,011).
Conclusions
ORV roadway and total crashes increased significantly after implementation of county ordinances allowing ORVs on public roadways and when compared to counties without such ordinances. It is likely that these increased crashes have resulted in more deaths and serious injuries. Results from this study may help inform policymakers as they consider legislation regarding ORV usage on public roads.
Dapagliflozin Reduces Systemic Inflammation in Patients with Type 2 Diabetes Without Known Heart Failure
Authors: Wang Dennis , Naumova Anna , Isquith Daniel , Sapp Jaime , Huynh Kim Anh , Tucker Isabella , Balu Niranjan , Voronyuk Anna , Chu Baocheng , Ordovas Karen , Maynard Charles , Tian Rong , Zhao Xue-Qiao , Kim Francis
Published: March 2024

Objective: Sodium glucose cotransporter 2 (SGLT2) inhibitors significantly improve cardiovascular outcomes in diabetic patients; however, the mechanism is unclear. We hypothesized that dapagliflozin improves cardiac outcomes via beneficial effects on systemic and cardiac inflammation and cardiac fibrosis.
Research and Design Methods: This randomized placebo-controlled clinical trial enrolled 62 adult patients (mean age 62, 17% female) with type 2 diabetes (T2D) without known heart failure. Subjects were randomized to 12 months of daily 10 mg dapagliflozin or placebo. For all patients, blood/plasma samples and cardiac magnetic resonance imaging (CMRI) were obtained at time of randomization and at the end of 12 months. Systemic inflammation was assessed by plasma IL-1B, TNFα, IL-6 and ketone levels and PBMC mitochondrial respiration, an emerging marker of sterile inflammation. Cardiac fibrosis was assessed by T1 mapping to calculate extracellular volume fraction (ECV); cardiac tissue inflammation was assessed by T2 mapping.
Results: Between the baseline and 12-month time point, plasma IL-1B was reduced (-1.8 pg/mL, P=0.003) while ketones were increased (0.26 mM, P=0.0001) in patients randomized to dapagliflozin. PBMC maximal oxygen consumption rate (OCR) decreased over the 12-month period in the placebo group but did not change in patients receiving dapagliflozin (-158.9 pmole/min/106cells, P=0.0497 vs -45.2 pmole/min/106cells, P=0.41), a finding consistent with an anti-inflammatory effect of SGLT2i. ECV and T2 relaxation time did not change in both study groups.
Conclusion: This study demonstrates that 12 months of dapagliflozin reduces IL-1B mediated systemic inflammation but affect cardiac fibrosis in T2D.
Clinical Trial.gov Registration NCT03782259
Why models underestimate West African tropical forest productivity
Authors: Zhang-Zheng Huanyuan , Deng Xiongjie , Stocker Benjamin , Ding Ruijie , Thomson Eleanor , Gutiérrez Jesús Aguirre , Adu-Bredu Stephen , Duah-Gyamfi Akwasi , Gvozdevaite Agne , Moore Sam , Menor Imma Oliveras , Prentice Iain , Malhi Yadvinder
Published: March 2024

Tropical forests dominate terrestrial photosynthesis, yet there are major contradictions in our understanding due to a lack of field studies, especially outside the tropical Americas. A recent field study indicated that West African forests have among the highest forests gross primary productivity (GPP) yet observed, contradicting models that rank them lower than Amazonian forests. Here, we explore possible reasons for this data-model mismatch. We found the in situ GPP measurements higher than multiple global GPP products at the studied sites in Ghana. The underestimation of GPP by models largely disappears when a standard photosynthesis model is informed by local field-measured values of (a) fractional absorbed photosynthetic radiation (fAPAR), and (b) photosynthetic traits. Satellites systematically underestimate fAPAR in the tropics due to cloud contamination issues. The study highlights the potential widespread underestimation of tropical forests GPP and carbon cycling and hints at the ways forward for model and input data improvement.
INTERGEN: a computational package applied to large-scale animal and plant genetic analysis
Authors: Junqueira Vinícius Silva , Campos Gabriel Soares , Cardoso Fernando Flores
Published: March 2024

Background
Genomic selection has become the standard genetic evaluation approach for estimating the genetic merit of animal and plant populations. That trend is mainly driven by the cost reduction for obtaining genomic data, such as single-nucleotide polymorphism (SNP) cost as novel genotyping and sequencing becomes more efficient and worldwide accessible. Although several software options are available for efficient estimation of non-genomic (i.e., traditional) genetic evaluations, the constant increase in genomic data availability requires new software that handles this data efficiently. The INTERGEN package has been constantly developing using Fortran programming language over the last two decades. The most recent of INTERGEN contains three different binaries (intergen, intergeniod, intergenacc). The initial developments in intergen were focused on Bayesian modeling with reaction norms, multiple-breed, and parentage uncertainty allowing for Gaussian and heavier-tailed alternatives such as Student’s t or Slash densities for variance component estimation. More recently, intergen has been constantly expanded to include the Best Linear Unbiased Prediction (BLUP), genomic module. The intergeniod and intergenacc are new binary and it intends to estimate genetic merit using iteration on data (IOD), and approximate accuracy, respectively.
Results
Several single-step GBLUP (ssGBLUP) single- and multi-trait models were implemented for running validations with benchmarking software (intergen and BLUPF90). The software produced reliable estimates for both genetic merit and accuracy in all IOD and approximate accuracy analyses. Rank correlation for the genetic merit for all bivariate ssGBLUP analyses in intergeniod was equal to intergen solutions. The approximate accuracies were compared with the exact accuracies estimated in BLUPF90. The rank correlation, regression slopes, and bias in intergenacc varied based on the amount of information (i.e., genotypes and phenotypes) for each animal across the different analyses.
Conclusions
The INTERGEN package can be applied to the genetic analysis of large-scale datasets using Bayesian and BLUP analysis. For traditional methods such as BLUP, intergen is a flexible tool. The package allows users to adopt IOD and approximate accuracy using intergeniod and intergenacc, respectively.
Distribution of EGFR fusions in 35,023 Chinese patients with solid tumors-the frequency, fusion partners and clinical outcome
Authors: Zhang Haiping , Wang Julei , Li Xiaoxiao , Zhang Dongfeng , Qi Yingxue , Zhang Qin , Luo Ningning , Wang Xiaoou , Wang Tuo
Published: March 2024

Background
Epidermal growth factor receptor (EGFR) fusions are rare but potentially actionable oncogenic drivers across multiple solid tumors. However, the distribution and molecular characteristics of EGFR fusions in Chinese patients with solid malignancies have not been explored.
Methods
Panel-based next-generation sequencing (NGS) data of 35,023 patients with various types of solid tumors were collected and analyzed from the Simcere Diagnostics (Nanjing, China) database. A 9563-patient cohort was derived from The Cancer Genome Atlas (TCGA) to explore the relationship between EGFR fusion status and overall survival (OS).
Results
In this study, prevalence of functional EGFR fusions was 0.303% (106/35016) in total across solid tumors, which occur more commonly in gastroesophageal junction cancer (1.613%), followed by medatloblastoma (1.515%) and glioma (1.370%). Analysis showed a prevalence for fusion partners in different tumor types. The top 3 co-mutant genes with EGFR fusion were TP53 (mutation frequency, MF: 65%), BRCA2 (MF: 43%), and ALK (MF: 41%). Furthermore, patients in the EGFR fusion group had a significantly shorter OS than those in the non-EGFR fusion group (p < 0.0001) in the TCGA cohort,, suggesting that EGFR fusion might be a high-risk factor for poor prognosis.
Conclusions
Our study is the first retrospective analysis of EGFR fusions in a large-scale solid tumor population, which may provide a reference for future EGFR-TKI clinical trials with EGFR fusions.
Seismic activity characteristics of the Chinese continent based on a ‘hybrid’ probability forecasting model
Authors: Ma Yong , Bi Jinmeng , Dong Demiao
Published: March 2024

In the research on Operational Earthquake Forecasting (OEF), a crucial aspect involves constructing a predictive model capable of assessing its efficacy while aligning with the regional seismic activity characteristics. This study delineates Chinese continent, characterized by complex seismotectonic, into six distinct zones: Northeast, North China, South China, North-South Zone, Xinjiang, and Xizang. Three earthquake probability forecasting models-namely, the relative intensity (RI) model, the moment ratio (MR) model, and the simple smoothing (Triple-S) model are employed. Utilizing seismic catalog data from the China Earthquake Networks Center dating back to 1970, with a ‘anomaly learning period’ spanning 10 years and a step length of 1 year, a retrospective sliding forecasting analysis is conducted for earthquakes of magnitude Ms5.0 or greater over varying intervals, such as 3 years and 5 years. The efficacy of the forecasting models is assessed through the Molchan chart method and T-test method. Model parameters are fine-tuned, determining the optimal computational parameters for the three forecasting models. A composite probability forecasting model, adaptable across different time scales and tailored to the seismic activity characteristics of Chinese continent, is developed. An analysis of seismic activity over the past decade provides insights into the current landscape. This analysis highlights that the high-risk areas identified through the composite model closely align with previous findings and correlate well with actual earthquake occurrences in Chinese continent in 2023.