bluuebunny/crossref_metadata_2025 huggingface dataset:
Linc-NSC affects cell differentiation, apoptosis and proliferation in mouse neural stem cells and embryonic stem cells in vitro and in vivo
Authors: Zou Dan , guo lili , Qiu Wenqiao , Fei Fan , Chen Lihua , Chen Wenjin , xiong Huan , Li Xinda , Wang Yangyang , Gao Mingjun , Zhu Jianwei , Zhang Jin , He Yunsen , Gao Mou , Xu Ruxiang
Published: August 2023

Background
Stem cell therapy is a promising therapeutic strategy. Our previous study evaluated tumorigenicity by stereotactic transplantation of mouse neural stem cells (NSCs) and mouse embryonic stem cells (ESCs). When the mice were examined 28 days later, there was no evidence of tumor formation or long-term engraftment in the NSCs transplantation group. In contrast, due to the high proliferative capacity, ESCs transplantation caused tumor formation. Based on transcriptome sequencing, we found that a long intergenic noncoding RNA (named linc-NSC) with unknown structure and function was 1100 times more expressed on NSCs than on ESCs. It is suggested that linc-NSC is negatively correlated with stem cell pluripotency and tumor development, but positively correlated with neurogenesis. Therefore, we further wanted to clarify the role of linc-NSC in NSCs/ESCs in tumor formation and neurogenesis.
Methods
Whole transcriptome profiling by RNA sequencing and bioinformatics was used to predict the lncRNA widely associated with enhanced tumorigenicity. The expression of linc-NSC was assessed by quantitative real-time PCR. The cell proliferation assay, differentiation assay, immunofluorescence, flow cytometry in vitro, and survival rate and immunofluorescence assays in vivo were performed to investigate the impacts of linc-NSC on tumor formation and neurogenesis in NSCs and ESCs.
Results
We discovered that after the knockdown of linc-NSC in NSCs, NSCs cultured in vitro and those transplanted into the mouse cortex showed stronger survival ability, enhanced proliferation, and reduced apoptosis, and the opposite result was observed with linc-NSC overexpression in ESCs. Meanwhile, overexpression of linc-NSC in ECSs can induce enhanced apoptosis and differentiation, and inhibit tumorigenesis in vivo, reduction in tumor weight.
Conclusions
The linc-NSC, a promising gene-edited target, may promote the differentiation of mouse NSCs and inhibit tumorigenesis of mouse ESCs. In other words, knockdown of linc-NSC inhibits NSCs apoptosis in vitro and in vivo, and is unable to trigger tumor formation, revealing a new dimension into the lncRNA of low survival NSCs and providing a prospective gene manipulation target before transplantation. In parallel, overexpression of linc-NSC induces ESCs apoptosis in vitro and in vivo，attenuating the tumorigenicity of ESCs in vivo, although it can’t completely prevent tumor formation.
Feature-based vs. deep-learning fusion methods for the in vivo detection of early radiation dermatitis using Optical Coherence Tomography
Authors: Photiou Christos , Cloconi Constantina , Strouthos Iosif
Published: August 2023

More than half of all cancer patients receive some form of radiation therapy during the course of their illness. Unfortunately, acute radiation dermatitis (ARD) is a common side effect of radiation that leads to significant morbidity. Although there are various treatment options, ARD is still the cause of significant distress, thus, additional research is required to improve prevention and treatment strategies. Unfortunately, the lack of biomarkers for quantitative assessment of early changes associated with the condition, impedes further progress. This study was designed to explore the identification of early ARD using intensity-based and novel features of Optical Coherence Tomography (OCT) images, combined with machine learning. Twenty-two patients underwent imaging twice weekly, at six locations on the neck, until the end of their radiation treatment. An expert oncologist graded the severity of their ARD. A traditional feature-based machine learning (ML) and a deep learning (DL) fusion approach were compared for their ability to classify normal skin vs. early ARD from the 1487-image dataset collected. Results showed that the deep learning approach outperformed traditional ML, achieving an accuracy of 88%. These findings provide a promising foundation for future research aimed at creating a quantitative assessment tool to improve the management of ARD.
Unravelling Ultralow Thermal Conductivity in Double Perovskite Cs2AgBiBr6: Dominant Wave-like Phonon Tunnelling, Strong Quartic Anharmonicity and Lattice Instability
Authors: Huang Baoling , Zheng Jiongzhi , Lin Changpeng , Lin Chongjia , Hautier Geoffroy , Guo Ruiqiang
Published: August 2023

Efficient manipulation of thermal energy in halide perovskites is crucial for their opto-electronic, photovoltaic and thermoelectric applications. However, understanding the lattice dynamics and heat transport physics in the lead-free halide double perovskites remains an outstanding challenge due to their lattice dynamical instability and strong anharmonicity. In this work, we investigate the microscopic mechanisms of anharmonic lattice dynamics and thermal transport in lead-free halide double perovskite Cs2AgBiBr6 from first principles. We combine self-consistent phonon calculations with bubble diagram correction and a unified theory of lattice thermal transport that considers both the particle-like phonon propagation and wave-like tunnelling of phonons. An ultra-low thermal conductivity at room temperature (~0.21 Wm-1K-1) is predicted with weak temperature dependence(~T-0.45), in sharp contrast to the conventional ~T-1 dependence. Particularly, the vibrational properties of Cs2AgBiBr6 are featured by strong anharmonicity and wave-like tunnelling of phonons. Anharmonic phonon renormalization from both the cubic and quartic anharmonicities are found essential in precisely predicting the phase transition temperature in Cs2AgBiBr6 while the negative phonon energy shifts induced by cubic anharmonicity has a significant influence on particle-like phonon propagation. Further, the contribution of the wave-like tunnelling to the total thermal conductivity surpasses that of the particle-like propagation above around 340 K, indicating the breakdown of the phonon gas picture conventionally used in the Peierls-Boltzmann Transport Equation. Importantly, further including four-phonon scatterings is required in achieving the dominance of wave-like tunnelling, as compared to the dominant particle-like propagation channel when considering only three-phonon scatterings. Our work highlights the importance of lattice anharmonicity and wave-like tunnelling of phonons in the thermal transport in lead-free halide double perovskites.
Outcome of vaccinated COVID-19 patients at Eka Kotebe General Hospital, national COVID-19 treatment center Addis Ababa, Ethiopia.
Authors: Derese Tadios Niguss , Tefera Rediet Yitagesu , Hundie Tsegaye Gebreyes , Seyoum Abebaw Bekele , Abera Lidya Abebe , Butta Bemnet Fekre , Tilahun Robel Bayou , Soboka Tariku Assefa
Published: August 2023

Introduction: The majority of wealthy countries are distributing the COVID-19 vaccine to their citizens, and the World Health Organization has registered more than eight COVID-19 vaccines. Ethiopia wants to provide COVID-19 vaccinations to at least half of the populace by the end of 2022 as a COVAX facility under the direction of the World Health Organization. Since the outbreak of the novel coronavirus (COVID-19), a number of studies have been conducted, mainly focusing on the clinical characteristics of COVID-19 patients. There are limited studies on the outcomes of COVID-19-vaccinated patients worldwide. The aim of this study was to assess the outcome of vaccinated COVID-19 patients in Addis Ababa, Ethiopia.
Methods: An institutional-based cross-sectional study was conducted at the Eka Kotebe General Hospital National COVID-19 Treatment Center. After pretesting a structured quantitative tool, it was applied to study subjects using chart review to obtain the necessary data. Data were checked, coded, entered into EpiData version 3.1 and exported to SPSS version 24 for analysis. Descriptive statistics were presented using text, figures, and tables. The association between variables was analyzed using binary logistic regression analysis. Statistical significance was declared at p <=0.05 with a 95% confidence interval.
Result: Data from 284 fully vaccinated COVID-19 patients were reviewed in this study, with a mean age of 55.45 years. Forty-seven (16.5%) of the study participants died despite having been vaccinated against COVID-19. Age (AOR=2.80, 95% CI = 1.72, 10.91), chronic kidney disease (AOR=3.60, 95% CI = (1.17, 11.09)), stroke (AOR=7.43, 95% CI = (2.13, 25.92)), and taking antipyretics (AOR=5.57, 95% CI = (2.01, 15.45)) were the factors that had a significant association with COVID-19-admitted patient mortality.
Conclusion and recommendation: Death is a common condition among vaccinated elderly patients with severe COVID-19 comorbidities. The magnitude of death among vaccinated COVID-19 patients at Eka Kotebe General Hospital, a national COVID-19 treatment center, was found to be 16.5%. Age <=35 years, chronic kidney disease, stroke, and anti-pain/antipyretic medications were significantly associated with COVID-19 mortality among vaccinated patients. Healthcare providers should prioritize and closely monitor elderly patients who have received the COVID-19 vaccine.
Outdoor Air Pollution in Dakar city (Senegal) and Health Risk Assessment: A pilot study
Authors: Daffe Mouhamadou Lamine , THIAM Salimata , BAH Fatoumata , NDONG Awa , YESSA Jackline , Cabral Mathilde , DIOP Cheikh , TOURE Aminata , LAM Absa , MBOW-DIOKHANE Aminata , FALL Mamadou
Published: August 2023

Outdoor air pollution is the underlying cause of 4.2 million premature deaths per year, of which some 18% were due to chronic obstructive pulmonary disease (COPD) and 23% due to acute lower respiratory tract infections (IRI). In West African countries, anthropogenic sources of air pollution are concentrated near residential areas, thus exposing populations to high risks of adverse effects. In order to stimulate the implementation of policies to reduce population exposure, this study aimed to describe outdoor air pollution in Dakar (Senegal) and to estimate its health impact. The description was made by comparing the annual averages of various pollutants (NO2, SO2, PM10 and PM2.5) to guideline values ​​and on the other hand by converting the monthly averages into time-series which trends and seasonality are described using the R software. The impact was estimated with AirQ+ software by calculating the number of specific health outcomes (hospital admissions for respiratory diseases and all-cause mortality) from short-term exposure to outdoor air pollutants’ levels above the threshold of 10 ug/m3. Monthly levels follow a linear trend (except that of NO2), with a seasonal component. Pollution peaks are always observed in the December-January-February quarter, while the lowest levels are observed in the July-August-September quarter. Moreover, the annual levels are all above the guideline values, except for SO2. Between 2016 and 2018, and for all ages combined, 1379 (13.38%) cases of hospital admission for respiratory diseases can be attributed to short-term exposure to PM10. The latter is also the underlying cause of 315 (7.48%) non-accident deaths noted in 2017. Air pollution is a real problem in Dakar in view of the level of indicators. With regard to their health impact, a more exhaustive and more robust estimation would be very useful for better exposure reduction policies. To this end, air quality monitoring and health data management could be improved.
The rule of four: anomalous stoichiometries of inorganic compounds
Authors: Gazzarrini Elena , Cersonsky Rose , Bercx Marnik , Adorf Simon , Marzari Nicola
Published: August 2023

Why are materials with specific characteristics more abundant than others?
This is a fundamental question in materials science and one that is traditionally difficult to tackle, given the vastness of compositional and configurational space.
We highlight here the anomalous abundance of inorganic compounds whose primitive unit cell contains a number of atoms that is a multiple of four.
This occurrence - named here the rule of four - has to our knowledge not previously been reported or studied.
Here, we first highlight the rule's existence, especially notable when restricting oneself to experimentally known compounds, and explore its possible relationship with established descriptors of crystal structures, from symmetries to energies.
We then investigate this relative abundance by looking at structural descriptors, both of global (packing configurations) and local (the smooth overlap of atomic positions) nature.
Contrary to intuition, the overabundance does not correlate with low-energy or high-symmetry structures; in fact, structures which obey the rule of four are characterized by low symmetries and loosely packed arrangements maximizing the free volume.
We are able to correlate this abundance with local structural symmetries, and visualize the results using a hybrid supervised-unsupervised machine learning method.
Shallow serpentinization promoted the up-dip high-frequency seismic wave radiation during the 2021 Mw8.1 Kermadec megathrust earthquake
Authors: Wei Shengji , Zeng Hongyu , Yang Hongfeng
Published: August 2023

Large megathrust earthquakes exhibit frequency-dependent rupture, with high-frequency (HF) seismic waves primarily emanating from the down-dip region of the coseismic slip. This has been attributed to mechanical heterogeneity at the locking zone’s lower boundary 1–3. However, we present that the 2021 Mw 8.1 Kermadec megathrust earthquake defied this trend by predominantly radiating HF energy from the up dip of its coseismic slip. To examine this phenomenon, we resolve the mainshock’s coseismic slip and HF evolution by employing finite fault inversions 4 and a path-calibrated back-projection 5 with travel time path calibration from relocated seismicity, respectively. The coseismic slip reveals a compact patch at 20–50 km depth, elongating ~ 100 km along the slab's strike. Interestingly, HF sources are distributed along the up-dip edge of the patch, coinciding with the forearc Moho depth and bursting within an active seismic belt comprising background events, aftershocks, the mainshock epicenter, and triggered HF sources from the Mw 7.4 foreshock. We attribute the prominent up-dip HF radiation to strong friction heterogeneity near the over-riding Moho, likely resulting from serpentinization initiation in the overriding oceanic mantle wedge. Significant slip on the partially serpentinized plate interface necessitates a re-evaluation of earthquake hazards in conventionally considered aseismic regions.
Intelligent ontology alignment to improve semantic data integration across research domains in biomedicine
Authors: Malik Muhammad Shoaib , Inau Esther Thea
Published: August 2023

Ontology alignment is a key component of semantic web interoperability, with a long history of applications in traditional data integration tasks that address the problem of semantic heterogeneity. Ontology alignment tools take two ontologiesas input and determine alignments as output i.e. a set of correspondences between semantically related units of these ontologies. These correspondences can then be used to merge ontologies, link data across knowledge domains, answer semantic queries, navigate through knowledge graphs, and many more. The process of determining alignments, called matching, therefore is a basic requirement for linking knowledge across scientific domains covered by one or more ontologies. A matching exists if entities from different ontologies are semantically equivalent. The goal of this study is to find all semantically equivalent entity pairs given a source ontology Os and a target ontology Ot, each consisting of a set of entities. We propose to use Inverse Document Frequency (IDF) and Jaccard distance to find candidate entities with high precision and less computational effort. Our goal to cross-link different research fields in the biomedical and clinical domains.
Construction of a predictive model for osteoporosis risk in men: using the IOF one-minute Osteoporosis Test
Authors: Zhang Kun , Wang Min , Yi Weihong , Yang Dazhi
Published: August 2023

Objective To construct a clinical prediction nomogram model using the one-minute IOF osteoporosis risk test as an evaluation tool for male osteoporosis.
Methods The one-minute test results and the incidence of osteoporosis were collected from 354 patients in the osteoporotic clinic of our hospital. LASSO regression model and multi-factor Logtisic regression were used to analyze the risk factors of osteoporosis in patients, and the risk prediction model of osteoporosis was established. Verify with an additional 140 objects.
Results We used logtisic regression to construct a nomogram model. According to the model, the AUC value of the training set was 0.760 (0.704-0.817). The validation set has an AUC value of 0.806 (0.733-0.879). The test set AUC value is 0.714 (0.609-0.818). The calibration curve shows that its advantage is that the deviation correction curve of the nomogram model can maintain a good consistency with the ideal curve. In terms of clinical applicability, compared with the "total intervention" and "no intervention" schemes, the clinical net return rate of the nomogram model showed certain advantages.
Conclusion Using the one-minute osteoporosis risk test provided by IOF, we built a male osteoporosis risk prediction model with good prediction effect, which can provide greater reference and help for clinicians.
Ultra-high µC* beyond 10 000 F cm-1 V-1 s-1 in organic electrochemical transistors
Authors: Bardagot Olivier , Durand Pablo , Guchait Shubhradip , Rebetez Gonzague , Cavassin Priscila , Réhault Julien , Brinkmann Martin , Leclerc Nicolas , Banerji Natalie
Published: August 2023

Organic electrochemical transistors (OECTs) are the heart of promising high-sensitivity biosensors, electrophysiological monitors, and neuromorphic devices. In a context of growing interest for such strategic electronics, we investigate a novel PBTTT polymer bearing single ether side chains (PBTTT-8O) in OECTs. Pristine, non-aligned, devices match state-of-the-art transconductance, confirming the value of single ethers for designing next-generation organic mixed ionic-electronic conductors (OMIECs). Moreover, a ten-fold enhancement of 𝜇C*, reaching 12 000 F cm-1 V-1 s-1, is achieved by unidirectional alignment of PBTTT-8O, opening doors to unprecedented device sensitivity. Such improvement is mainly attributed to enhanced hopping along ordered polymer chains, resulting in ultra high mobility over 25 cm2 V-1 s-1. Interestingly, aligned channels dope twice and dedope fifteen times faster than pristine ones, offering a path to achieve rapid ON/OFF device switching. This study reports an easily transferable solution to concomitantly boost the signal amplification and switching speed of bioelectronic devices.
Climate and humans interact to shape the fire regime of a chir pine forest in eastern Bhutan
Authors: Tenzin Karma , Nitschke Craig R , Allen Kathryn J , Krusic Paul J , Cook Edward R , Nguyen Thiet V , Baker Patrick J
Published: August 2023

Background: Chir pine (pinus roxburghii Sarg.) forests are distributed in the dry valleys of Bhutan Himalaya. These forests are heavily influenced by biotic activities such as grazing, resin tapping and NWFP (non-wood forests produce) collection. Understanding the relationship between past and present climate and the frequency and severity of forest fires is important for assessing the relative importance of potential drivers on fire occurrence and extent. This study aimed to reconstruct the fire history of a forested landscape dominated by chir pine in eastern Bhutan using crossdated fire scars disc samples.
Results: The chir pine fire chronology extended to the early 1900s. Between 1900 and ~1970 fires were typically small and limited to a small number of sites within the larger study area. After 1970 a distinct shift in fire activity occurred with fires in 1985, 1989, 1996, 2000, and 2013 burning >90% of sample plots. Fire activity was positively associated with La Niña conditions (wetter, cooler) in the preceding year, which likely contributed to a greater accumulation of fuels on the forest floor.
Conclusions: Historical reconstruction of fire activity from a site in eastern Bhutan highlights the interaction between human activity and climatic conditions. Prior to 1970 fire activity was dominated by patchy, low-intensity fires. After 1970 fires became larger and more damaging. This shift is associated with the enactment of the Bhutan Forest Act in 1969, which regulated grazing and implemented a policy of strict fire exclusion in government-reserved forests. This led to large build-ups of fuels, particularly after La Niña years. The ubiquity of ignition sources and strong rainfall seasonality ensured that fire could occur in most years. However, the change in forest policy and local community activities in the forests altered the amount and connectivity of fuels within the landscape, reshaping the fire regime in the chir pine forests of eastern Bhutan.
The Association Between CYP7B1 and Diabetes in Prostate Cancer patients (DIAMOND study)
Authors: Russo Giorgio Ivan , Durukan Emil , Broggi Giuseppe , Asmundo Maria Giovanna , Giudice Arturo Lo , Salzano Serena , Cimino Sebastiano , Morgia Giuseppe , Fode Mikkel , Caltabiano Rosario
Published: August 2023

Background: Prostate cancer (PCa) is the second most frequently diagnosed cancer in men, and the extent of CYP7B1's involvement in androgen metabolism and its impact on the progression of PCa is still uncertain. The aim of this study is to investigate the role of the CYP7B1 enzyme in prostate cancer aggressiveness.
Methods: A retrospective analysis was performed on 390 patients with prostate cancer (PCa) or benign prostatic hyperplasia (BPH) at the Department of Urology, University of Catania, where we examined CYP7B1 protein expression through immunohistochemical analysis in malignant and benign prostatic tissue. We investigated the interactions between CYP7B1 expression and proteins associated with PCa and metabolic processes, followed by an analysis of the risk of biochemical recurrence based on CYP7B1 expression.
Results: Among 286 patients with PCa and 104 patients with BPH, CYP7B1 expression was higher in malignant tissue. Of the 139 patients with elevated CYP7B1 expression, 92.8% had prostate cancer. Logistic regression revealed significantly higher positive scores for IR-α (OR 5.73, CI: 2.77-11.84, p < 0.01), IR-β (OR 6.61, CI: 2.19-19.96, p < 0.01), SRSF-1 (OR 2.04, CI: 1.27-3.29, p < 0.01), FAS (OR 2.15, CI: 1.28-3.62, p < 0.01), PSMA (OR 1.66, CI: 1.04-2.66, p = 0.03), and ACC-1 (OR 1.83, CI: 1.14-2.93, p = 0.01). Overall, no increased risk of biochemical recurrence was associated with CYP7B1 expression. However, in a non-diabetic subgroup analysis, higher CYP7B1 expression indicated a higher risk of biochemical recurrence with HR of 1.78 (CI: 1.0-3.2, p = 0.05).
Conclusion: PCa is associated with elevated CYP7B1 expression. In a subgroup of non-diabetic patients, elevated CYP7B1 expression was associated with increased risk of biochemical recurrence, suggesting increased cancer aggressiveness.
Convolutional neural networks from the perspective of the problems of multivalued logic
Authors: Vitulyova Yelizaveta S , Matrassulova Dinara , SULEIMENOV IBRAGIM , Bakirov Akhat
Published: August 2023

It is shown that it is possible to reduce the operations performed by convolutional neural networks to algebraic, and then to operations of multivalued logic. The tool for this is signal models, which are functions that take values in Galois fields and algebraic rings. This approach, among other things, allows us to switch to the use of partial convolutions, which significantly simplify the analysis of digital signals and images. Such convolutions are performed directly in terms of Galois fields, which makes it possible to use a digital analogue of the classical convolution theorem. The advantage in this regard is the possibility of using a digital analogue of transfer functions, because in terms of Fourier-Galois spectra, the convolution operation is reduced to the multiplication operation by the transfer function. This, in turn, allows us to exhaustively describe a convolutional neural network through a set of transfer functions that take values in Galois fields. The close connection between Galois fields and multivalued logics makes it possible to describe the functioning of convolutional neural networks using variables of multivalued logic.
The real-world outcomes of multiple myeloma treated with elotuzumab, pomalidomide, and dexamethasone
Authors: Nakayama Hitomi , Aisa Yoshinobu , Ito Chisako , Sakurai Aki , Kurosawa Shuhei , Nakazato Tomonori
Published: August 2023

Background
We present the outcome of relapsed/refractory multiple myeloma (RRMM) patients heavily pre-treated who received a combination of elotuzumab, pomalidomide, and dexamethasone (EPd) outside of clinical trials to evaluate the safety and efficacy of this combination in a real-world setting.
Patients and Methods
The medical records of 22 patients who received EPd for RRMM at our institution between January 2020 and July 2021 were reviewed.
Results
The median age was 73.5 years. The overall response rate was 55%. With a median follow-up of 20.2 months, the median progression-free survival (PFS) was 9.1 months (95% confidence interval [CI], 2.5–23.0 months). The median PFS was shorter in patients with a poor performance status (PS) than in those with favorable PS (2.5 vs. 10.8 months; P<0.01). Patients with prior daratumumab had significantly shorter PFS than those without prior daratumumab (2.1 vs. 23.0 months; P<0.01). In the multivariate analysis, poor PS (hazard ratio [HR]=4.1, 95% CI: 1.1–15.6; P=0.04) and prior exposure to daratumumab (HR=3.8, 95% CI: 1.1–13.8; P=0.04) remained significantly associated with shorter PFS.
Conclusions
Our results suggest that EPd is an active and well-tolerated regimen in RRMM, even in real-world patients. Furthermore, EPd may be useful, especially in daratumumab-naïve patients.
Porphyry Copper Prospectivity using Machine Learning Methods: A Case Study of the Shahr-e-Babak Prospecting Area, South Eastern Iran
Authors: Jahantigh Moslem , Ramazi Hamidreza
Published: August 2023

Mineral prospectivity modelling (MPM) is an essential step in reducing cost and time at the reconnaissance stage of mineral exploration. In this paper, the MPM was conducted in the Shahr-e-Babak study area for porphyry copper prospectivity. For achieving this goal, the evidential layers, including geology, remote sensing, airborne geophysics, geochemistry, and elevation model, were used as the input of training models. Four machine learning methods, consisting of multilayer perceptron (MLP), Adaptive neuro fuzzy inference system (ANFIS), random forest (RF), and generalized regression neural network (GRNN), were used to generate the models. Then, the fractal method and the prediction area plot were applied to evaluate the models. The models were divided into low potential, moderate potential, and high potential zones. The effective weight of evidential layers was extracted using the P-A plot method. The weight of Cu anomalies, phyllic, argillic and iron oxide alterations, elevation data, PC1 geochemical anomalies, magnetic anomalies, and subvolcanic bodies were 0.71, 0.62, 0.49, 0.4, 0.32, 0.25, 0.25 and -0.49, respectively. In the next step, the weights were extracted for MLP, ANFIS, RF, and GRNN as 0.85, 0.78, 1.26, and 0.76, respectively. The statistical correlation coefficients between argillic, phyllic, and iron oxide alterations were calculated. In the final step, an integrated model was generated using machine learning methods. Then, the integrated model was divided into low, moderate, and high potential zones based on the fractal method. Favorable areas are located in the western and eastern parts of the study area based on the integrated model.
A conserved signaling axis integrates conflicting environmental drought and heat signals to control stomatal aperture in plants
Authors: De Smet Ive , Xu Xiangyu , Praat Myrthe , Pizzio Gaston , Jiang Zhang , Driever Steven , Wang Ren , de Cotte Brigitte van , Villers Selwyn , Gevaert Kris , LEONHARDT Nathalie , Nelissen Hilde , Kinoshita Toshinori , Vanneste Steffen , Rodriguez Pedro , Zanten Martijn van , Vu Lam
Published: August 2023

Plants continuously respond to changing environmental conditions to prevent damage and maintain optimal performance. To regulate gas exchange with the environment and to control abiotic stress relief, plants have pores in their leaf epidermis, called stomata 1. Multiple environmental signals affect the opening and closing of these stomata 2. Heat promotes stomatal opening (to cool down) and drought induces stomatal closing (to prevent water loss). Coinciding stress conditions, however, may evoke conflicting stomatal responses, but the cellular mechanisms to resolve these conflicts are unknown. Here, we demonstrate that the high temperature-associated kinase TARGET OF TEMPERATURE 3 (TOT3) directly controls the activity of plasma membrane H+-ATPases to induce stomatal opening. This TOT3 activity is directly antagonized by OPEN STOMATA 1 (OST1), to prevent water loss during drought stress. This signaling axis harmonizes conflicting heat and drought signals to regulate stomatal aperture. In the context of global climate change, understanding how conflicting stress signals converge on stomatal regulation allows the development of climate change-ready crops.
Association of gut microbiota with dyslipidemia and chronic coronary syndrome patients undergoing coronary angiography
Authors: Luangphiphat Wongsakorn , Prombutara Pinidphon , Muangsillapasart Viroj , Sukitpunyaroj Damrong , Eeckhout Eric , Taweechotipatr Malai
Published: August 2023

Chronic coronary syndrome (CCS) has a high mortality rate, and dyslipidemia is a major risk factor. Atherosclerosis, a cause of CCS, is influenced by gut microbiota dysbiosis and its metabolites. We aimed to study the diversity and composition of gut microbiota and related clinical parameters among CCS patients undergoing coronary angiography and dyslipidemia patients in comparison to healthy volunteers in Thailand. We reported that CCS patients had more risk factors and higher inflammatory marker, high-sensitivity C-reactive protein (hs-CRP) than others. We showed that the alpha diversity was lower in dyslipidemia and CCS patients than in the healthy group. A significant difference in the composition of gut microbiota was observed among the three groups. The relative abundance of Proteobacteria, Fusobacteria, Enterobacteriaceae, Prevotella and Streptococcus were significantly increased while Roseburia, Ruminococcus and Faecalibacterium were lower in CCS patients. In CCS patients, Lachnospiraceae, Peptostreptococcaceae and Pediococcus were positively correlated with hs-CRP. In dyslipidemia patients, Megasphaera was strongly positively correlated with triglyceride (TG) level and negatively correlated with high-density lipoprotein cholesterol (HDL-C). The modification of gut microbiota was associated with changes in clinical parameters involved in the development of coronary artery disease (CAD) in CCS patients.
Exclusive Radio±chemoTherapy versus upfront Surgery in the treatment of HPV-related localized or locally ADvanced Oropharyngeal squamous cell Carcinoma (RT-SHADOC): a tricentric study of efficacy, tolerance and quality of life
Authors: Baude Jérémy , Guigou Caroline , Thibouw David , Vulquin Noémie , Folia Mireille , Constantin Guillaume , Boustani Jihane , Duvillard Christian , Ladoire Sylvain , Truc Gilles , Bertaut Aurélie , Chevalier Cédric
Published: August 2023

Background The treatment of stage I-III HPV + oropharyngeal squamous cell carcinoma (HPV-OPSCC) is based on either surgery ± adjuvant therapy or exclusive radio ± chemotherapy. We sought to compare these two therapeutic strategies in terms of efficacy, tolerance and quality of life (QoL).Methods Patients treated for stage I-III HPV-OPSCC from 2010 to 2021in 3 academic centers were included and sorted according to the treatment strategy: surgery or exclusive radio ± chemotherapy. Efficacy and tolerance were retrospectively assessed, and QoL was prospectively evaluated using QoL assessment instruments.Results Eighty-three patients were included, 21 underwent surgery and 62 definitive radio-±chemotherapy. 2-year progression-free survival (PFS) and overall survival (OS) were respectively 80% and 86% in the surgical group and 92% and 95% in the non-surgical group, with no significant difference. At the end of treatment, 64.5% of patients presented a grade III symptom, without significant difference between the two groups. No patient had late grade III toxicity at 24 months. Forty-five patients (11 in the surgical group, 34 in the nonsurgical group) participated in the prospective quality-of-life analysis. Patients reported significantly more fatigue and loss of appetite after surgery, whereas patients in the radio ± chemotherapy group described significantly more salivary and oral problems and difficulty swallowing. The global quality of life score tended to be better in the radio ± chemotherapy group (EORTC QLQ-C30 77.6 vs 65.2, p = 0.07).Conclusion No significant difference in terms of efficacy, physician-reported toxicity and patient-reported quality of life was found between surgery and radio ± chemotherapy in the treatment of stage I-III HPV-OPSCC.
Integrating Behavioral Health Services into Primary Care Clinics within a Large Public Healthcare System: Provider Satisfaction and Patient Outcomes
Authors: Miller Emily K. , O’Donnell Kari , Fiegl Jordan , Berko Eric , Leon Janeen , Kaelber David C. , Luca Susan
Published: August 2023

Background: Behavioral health integration within primary care has demonstrated improved access to mental health services, patient outcomes, and satisfaction with care. This pre-post, mixed-methods quality improvement study examined factors of healthcare provider satisfaction in 10 integrated behavioral health (IBH) clinics in a Midwestern public healthcare system. This study also examined implementation indicators, including referral rates, scheduling time from referral to initial behavioral health encounter, and emergency department (ED) utilization to better understand patient experiences and outcomes.
Methods: Providers were asked to complete online pre- and post-surveys (n = 110 patients, n = 115 patients, respectively) related to provider satisfaction with IBH services between October 2021 and April 2022. All other analyses were completed using electronic health record (EHR) patient data corresponding to IBH implementation across the 10 sites (pre-integration n = 42,397 patients, post-integration n = 37,129 patients).
Results: Increases in organizational and relational scores were associated with significant improvements in provider satisfaction scores. Additionally, the results showed a significant increase in referrals to behavioral health in the post-integration period and a significant reduction in days to a behavior health appointment in the post-integration timeframe. Finally, ED utilization dropped from pre- to post-integration, but this was not statistically significant. Analysis of opened-ended questions revealed two main themes: positive regard for the value of IBH and structural and organizational barriers to IBH.
Conclusions: Findings suggest that IBH implementation resulted in improvements in some areas of patient care and coordination and, importantly, points to areas where even more improvement is needed. This study highlights the value of collaboration among different providers toward creating a more supportive primary care environment for the patient.
Daily streamflow of Argentinian rivers analysis using information theory quantifiers.
Authors: Suriano Micaela , Caram Leonidas Facundo , Rosso Osvaldo Anibal
Published: August 2023

This paper analyzes the temporal evolution of the streamflow for different rivers in Argentina, based on information quantifiers such as statistical complexity and permutation entropy. The main objective is to identify essential details of the dynamics of the processes to differentiate the degrees of randomness and chaos. The permutation entropy is used with the probability distribution of Ordinal Patterns and the Jensen-Shannon divergence to calculate the disequilibrium and then the statistical complexity. Daily streamflow series at different river stations were analyzed to classify the different hydrological systems. The Complexity Entropy Causality Plane (CEPC) and the representation of the Shannon Entropy and Fisher Information Measure (FIM) show that the daily discharge series could be represented approximately with Gaussian noise, but the variances highlight the difficulty of modeling a series of natural phenomena. An analysis of stations downstream from the Yacyretá dam shows that the operation affects the randomness of the daily discharge series in hydrometric stations near the dam, but when the station is further downstream this effect is attenuated. The size of the basin plays a relevant role in modulating the process, large catchments have smaller values for entropy and the signal is less noisy due to integration over larger time scales. The small and mountain basins present a rapid response that influences the behavior of daily discharge while presenting a higher entropy and lower complexity. The results obtained characterize the behavior of the daily discharge series in Argentinian rivers and provide key information for hydrological modeling.
Optimization of weld penetration prediction based on weld pool image and deep learning approach in gas tungsten arc welding
Authors: Baek Daehyun , Moon Hyeong Soon , Park Sang-Hu
Published: August 2023

Gas tungsten arc welding (GTAW) is a popular technology for joining metallic parts with high stability and quality. However, many GTAW-related processes are conducted manually, which is time-consuming and the weld quality strongly depends on the skill of the welder. Although various automatic GTAW methods and systems have been developed, controlling the weld quality remains a challenge because of the difficulties involved in predicting the weld quality, such as the penetration depth and backside bead geometry, during welding. Hence, this paper proposes an accurate and effective method for estimating the penetration depth through weld pool monitoring using a convolutional neural network (CNN) trained on weld pool images. The weld pool images contained several objects, each influencing the prediction accuracy. The CNN architecture and the structure of the fully connected layers (FCLs) also affected the prediction accuracy. To optimize the performance of the estimation model, the effects of each object in the weld pool image and the structure of the CNN architecture were analyzed and evaluated. The structure of the FCLs that outputted a quantitative penetration depth was optimized and evaluated through hyperparameter tuning. With the proposed method, the optimized model could quantitatively predict the penetration depth; the mean absolute error was 0.0516 mm, with an R2 value of 0.998. Accurately predicting the penetration depth can be employed in real-time weld quality control to ensure a sound weld back bead.
Classification of molecular subtypes of breast cancer in whole-slide histopathological images using a deep learning algorithm
Authors: Kim Hyung Suk , Min Kyueng-Whan , Kim Jong Soo
Published: August 2023

Classification of molecular subtypes of breast cancer is widely used in clinical decision-making, leading to different treatment responses and clinical outcomes. We classified molecular subtypes using a novel deep learning algorithm in whole-slide histopathological images (WSIs) with invasive ductal carcinoma of the breast. We obtained 1,094 breast cancer cases with available hematoxylin and eosin-stained WSIs from the TCGA database. We applied a new deep learning algorithm for artificial neural networks (ANNs) that is completely different from the back-propagation method developed in previous studies. Our model based on the ANN algorithm had an accuracy of 67.8% for all datasets (training and testing), and the area under the receiver operating characteristic curve was 0.819 when classifying molecular subtypes of breast cancer. In approximately 30% of cases, the molecular subtype did not reflect the unique histological subtype, which lowered the accuracy. The set revealed relatively high sensitivity (70.5%) and specificity (84.4%). Our approach involving this ANN model has favorable diagnostic performance for molecular classification of breast cancer based on WSIs and could provide reliable results for planning treatment strategies.
Effect of intelligent interactive projection combined with a three-ball respiratory trainer on shoulder mobility and pulmonary function in post- thoracic surgery patients: an interventional study
Authors: Ma Guojing , Yue Qin , Zhao Dan , Ma Xiaoli , Wang Min , Li Fanfan , Wang Xiaolan , Wang Ting , Wang Panpan , Ba Hailan , Ma Minjie
Published: August 2023

Objective
The study aimed to investigate the impact of combining intelligent interactive projection with a three-ball respiratory trainer on shoulder mobility and pulmonary function in post-thoracic surgery patients.
Methods
A total of seventy-four patients admitted to the Department of Thoracic Surgery at the First Hospital of Lanzhou University from January 2023 to April 2023 were selected for this intervention study. The control group received conventional nursing care, while the intervention group underwent exercises using the Intelligent Interactive Projection Combined with the Three-Ball Breathing Trainer to improve upper limb function and lung function. After excluding some patients, a total of 70 patients completed the study. The study compared the shoulder joint mobility, lung function, chest tube retention time, and occurrence of subcutaneous emphysema during hospitalization between the two groups.
Results
The intervention group showed significantly higher mobility in supination, posterior extension, and external rotation compared to the control group (P < 0.05).
Conclusion
The combination of the intelligent interactive projection system and the three-ball respiratory trainer has been shown to effectively enhance the recovery of patients' upper limb function and lung function. Additionally, this combination provides patients with a more comprehensive nursing intervention, ultimately improving the overall quality of care and facilitating postoperative recovery.
Headache-related characteristics of biopsy-confirmed giant cell arteritis and the relationship of transmural inflammation with artery tenderness and chordal thickening
Authors: shimohama sho , Imai Noboru , Tsubata Takuya , Shinohara Kei , Moriya Asami , Yagi Nobuyasu , Konishi Takashi , Serizawa Masahiro , Tashiro Kazuhiro
Published: August 2023

Giant cell arteritis (GCA) is characterised by headache, but few studies have examined detailed characteristics in pathologically confirmed cases. We aimed to investigate the characteristics of GCA, particularly headache, and their correlation with pathologic findings. We retrospectively analysed 26 patients (median age: 77.5 years, male: 38.4%) with GCA who underwent superficial temporal artery (STA) biopsy at the Japanese Red Cross Shizuoka Hospital between May 2001 and February 2022. All patients fulfilled the American College of Rheumatology and European League Against Rheumatism diagnostic criteria for GCA. We focused on the relationship between clinical features, especially headache, and pathologic findings. Twenty-four patients had unilateral, non-pulsating, intermittent headaches. Transmural inflammation (TMI), a characteristic pathology of GCA, was present in 14 patients. Bivariate analysis revealed significant associations between TMI and STA tenderness (odds ratio [OR]=11, 95% confidence interval [CI] 1.14 to 106.43, p=0.046) and between TMI and STA chordal thickening (OR=0.19, 95% CI 0.068 to 0.52, p=0.021). Headache in GCA patients was often unilateral, non-pulsatile, and intermittent. This study highlights the significant association of TMI with STA tenderness and ligamentous thickening, which has not been reported previously. Abnormal STA findings were significantly associated with pathologic changes in GCA, emphasising their importance in suspecting GCA.
Colour change in potato (Solanum tuberosum L.) tubers by disruption of the anthocyanin pathway via ribonucleoprotein complex delivery of the CRISPR/Cas9 system
Authors: Wulff-Vester Anders , Andersson Mariette , Brurberg May Bente , Hofvander Per , Alsheikh Muath , Harwood Wendy , Hvoslef-Eide Trine
Published: August 2023

Potato is an important part of the traditional Norwegian diet, and the crop faces several challenges with respect to pests and diseases, as well as the increasingly challenging changes in climate. Genome editing may provide tools to improve the resilience of Norwegian potato cultivars to new climate challenges. We have altered the skin colour of two potato cultivars, ‘Desirée’ and ‘Nansen’ from red to yellow, as a proof-of-concept for the use of CRISPR/Cas9 in a Norwegian cultivar. Our method has involved the use of protoplasts and we have grown the regenerants for three successive clonal tuber generations to evaluate the stability of the edited plants over time and under varying temperature conditions in contained rooms in a greenhouse. We found that the protoplast method is well suited to achieving CRISPR/Cas9 applications. The results show that the yellow skin is consistent over the three generations of tuber propagation. We found some suspected somaclonal variation in the regenerants. Some of the variation which we observed under high temperatures (up to nearly 40ºC) during the second growth cycle, disappeared when cultivated under lower temperatures in the third cultivation cycle.
A Novel Approach to Voice of Customer Extraction using GPT-3.5 Turbo: Linking Advanced NLP and Lean Six Sigma 4.0
Authors: Shahin Mohammad , Chen F. Frank , Hosseinzadeh Ali , Maghanaki Mazdak , Eghbalian Ayda
Published: August 2023

This research breaks new ground by utilizing the advanced natural language processing (NLP) capabilities of OpenAI's GPT-3.5 Turbo model for the extraction of Voice of Customer (VoC) data from online customer support interactions on Twitter. Traditional methods of VoC extraction have typically fallen short in capturing the richness and nuance of customer sentiment. Contemporary Machine Learning (ML) approaches, while improved, still struggle to interpret the contextual subtleties of digital customer communications effectively. This study showcases the innovative deployment of GPT-3.5 Turbo, demonstrating its superior performance in extracting VoC through a deeper understanding of conversational context and a more intuitive, chat-based data processing. Furthermore, the large-scale, multilingual processing capabilities of this model offer a more comprehensive and inclusive analysis of VoC. The study ties these advancements to Lean Six Sigma 4.0, illustrating how the integration of GPT-3.5 Turbo's transformative capabilities can elevate the customer-centric approach of Lean Six Sigma in the era of Industry 4.0. This innovative exploration points to a significant evolution in VoC analysis, offering potential for more insightful, real-time data-driven customer service strategies and a more substantial foundation for decision-making in product development and process improvement. Future research is encouraged to validate these preliminary findings and to investigate ethical considerations associated with the use of such advanced NLP models.