bluuebunny/crossref_metadata_2025 huggingface dataset:
Baseline conditions and nutritional state upon hospitalization are the greatest risks for mortality for cardiovascular diseases and for several classes of diseases: a retrospective study
Authors: Loreggian Lara , Giorgini Filippo , Zakaria Ahmed S. , Fanchini Marco , Veronelli Annamaria , Pontiroli Antonio E. , Tagliabue Elena
Published: June 2022

The aim of this retrospective study was to evaluate risk factors for 3-years mortality after hospital discharge in all inpatients admitted to a general hospital in Milano, Italy. A total of 2580 consecutive patients admitted to Ospedale San Paolo, July 1 to December 31, 2012, for several classes of diseases (internal medicine, cancer, infectious diseases, trauma and surgery, pneumonia, and heart diseases) were studied. Age, total disease, type of admission, length of admission, age-adjusted Charlson index, prognostic nutritional index (PNI), and full blood count were evaluated. Univariate Cox models were used to evaluate the association between variables and death. Of the 2580 consecutive patients (age 66.8 ± 19.36 years, mean ± SD), 920 died within 3 years after discharge. At univariate analysis, all investigated variables, except sex and lymphocytes, were associated with patient death. Stepwise regression analyses revealed that the age-adjusted Charlson index or age plus total diseases, type of admission, number of admissions, and PNI were significant risk factors in the whole sample and in some classes of disease. Results were superimposable when considering death from date of admission instead of date of discharge, meaning that in-hospital death was not relevant to the total death count (115 out of 902). Seriousness of baseline conditions represents the major risk factor for mortality in most classes of disease, and possibly influences other predictors, such as type of admission and length of stay. This suggests that the current model of hospital admission might be improved, for instance, through comprehensive care at home, instead of hospital admission, or before admission.
The first long-read nuclear genome assembly of Oryza australiensis, a wild rice from northern Australia
Authors: Phillips Aaron L. , Ferguson Scott , Watson-Haigh Nathan S. , Jones Ashley W. , Borevitz Justin O. , Burton Rachel A. , Atwell Brian J.
Published: June 2022

Oryza australiensisis a wild rice native to monsoonal northern Australia. The InternationalOryzaMap Alignment Project emphasises its significance as the sole representative of the EE genome clade. Assembly of theO. australiensisgenome has previously been challenging due to its high Long Terminal Repeat (LTR) retrotransposon (RT) content. Oxford Nanopore long reads were combined with Illumina short reads to generate a high-quality ~ 858 Mbp genome assembly within 850 contigs with 46× long read coverage. Reference-guided scaffolding increased genome contiguity, placing 88.2% of contigs into 12 pseudomolecules. After alignment to theOryza sativacv. Nipponbare genome, we observed several structural variations. PacBio Iso-Seq data were generated for five distinct tissues to improve the functional annotation of 34,587 protein-coding genes and 42,329 transcripts. We also report SNV numbers for three additionalO. australiensisgenotypes based on Illumina re-sequencing. Although genetic similarity reflected geographical separation, the density of SNVs also correlated with our previous report on variations in salinity tolerance. This genome re-confirms the genetic remoteness of theO. australiensislineage within theO. officinalisgenome complex. Assembly of a high-quality genome forO. australiensisprovides an important resource for the discovery of critical genes involved in development and stress tolerance.
Cortical changes in patients with schizophrenia across two ethnic backgrounds
Authors: Langenbach Benedikt P. , Kohl Waldemar , Murai Toshiya , Suslow Thomas , Ohrmann Patricia , Bauer Jochen , Matsukawa Noriko , Son Shuraku , Pedersen Anya , Lichtenstein Theresa , Miyata Jun , Koelkebeck Katja
Published: June 2022

While it is known that cultural background influences the healthy brain, less is known about how it affects cortical changes in schizophrenia. Here, we tested whether schizophrenia differentially affected the brain in Japanese and German patients. In a sample of 155 patients with a diagnosis of schizophrenia and 191 healthy controls from Japan and Germany, we acquired 3 T-MRI of the brain. We subsequently compared cortical thickness and cortical surface area to identify whether differences between healthy controls and patients might be influenced by ethnicity. Additional analyses were performed to account for effects of duration of illness and medication. We found pronounced interactions between schizophrenia and cultural background in the cortical thickness of several areas, including the left inferior and middle temporal gyrus, as well as the right lateral occipital cortex. Regarding cortical surface area, interaction effects appeared in the insula and the occipital cortex, among others. Some of these brain areas are related to the expression of psychotic symptoms, which are known to differ across cultures. Our results indicate that cultural background impacts cortical structures in different ways, probably resulting in varying clinical manifestations, and call for the inclusion of more diverse samples in schizophrenia research.
Birds adapted to cold conditions show greater changes in range size related to past climatic oscillations than temperate birds
Authors: Carrera Lisa , Pavia Marco , Varela Sara
Published: June 2022

Investigation of ecological responses of species to past climate oscillations provides crucial information to understand the effects of global warming. In this work, we investigated how past climate changes affected the distribution of six bird species with different climatic requirements and migratory behaviours in the Western Palearctic and in Africa. Species Distribution Models and Marine Isotopic Stage (MIS) 2 fossil occurrences of selected species were employed to evaluate the relation between changes in range size and species climatic tolerances. The Last Glacial Maximum (LGM) range predictions, generally well supported by the MIS 2 fossil occurrences, suggest that cold-dwelling species considerably expanded their distribution in the LGM, experiencing more pronounced net changes in range size compared to temperate species. Overall, the thermal niche proves to be a key ecological trait for explaining the impact of climate change in species distributions. Thermal niche is linked to range size variations due to climatic oscillations, with cold-adapted species currently suffering a more striking range reduction compared to temperate species. This work also supports the persistence of Afro-Palearctic migrations during the LGM due to the presence of climatically suitable wintering areas in Africa even during glacial maxima.
Loss of starch synthase IIIa changes starch molecular structure and granule morphology in grains of hexaploid bread wheat
Authors: Fahy Brendan , Gonzalez Oscar , Savva George M. , Ahn-Jarvis Jennifer H. , Warren Frederick J. , Dunn Jack , Lovegrove Alison , Hazard Brittany A.
Published: June 2022

Starch synthase III plays a key role in starch biosynthesis and is highly expressed in developing wheat grains. To understand the contribution of SSIII to starch and grain properties, we developed wheat ssIIIa mutants in the elite cultivar Cadenza using in silico TILLING in a mutagenized population. SSIIIa protein was undetectable by immunoblot analysis in triple ssIIIa mutants carrying mutations in each homoeologous copy of ssIIIa (A, B and D). Loss of SSIIIa in triple mutants led to significant changes in starch phenotype including smaller A-type granules and altered granule morphology. Starch chain-length distributions of double and triple mutants indicated greater levels of amylose than sibling controls (33.8% of starch in triple mutants, and 29.3% in double mutants vs. 25.5% in sibling controls) and fewer long amylopectin chains. Wholemeal flour of triple mutants had more resistant starch (6.0% vs. 2.9% in sibling controls) and greater levels of non-starch polysaccharides; the grains appeared shrunken and weighed ~ 11% less than the sibling control which was partially explained by loss in starch content. Interestingly, our study revealed gene dosage effects which could be useful for fine-tuning starch properties in wheat breeding applications while minimizing impact on grain weight and quality.
Determination of roughness coefficient in 3D digital representations of rocks
Authors: Scalco Leonardo , Tonietto Leandro , Velloso Raquel Quadros , Racolte Graciela , Gonzaga Luiz , Veronez Mauricio Roberto
Published: June 2022

The roughness property of rocks is significant in engineering studies due to their mechanical and hydraulic performance and the possibility of quantifying flow velocity and predicting the performance of wells and rock mass structures. However, the study of roughness in rocks is usually carried out through 2D linear measurements (through mechanical profilometer equipment), obtaining a coefficient that may not represent the entire rock surface. Thus, based on the hypothesis that it is possible to quantify the roughness coefficient in rock plugs reconstructed three-dimensionally by the computer vision technique, this research aims to an alternative method to determine the roughness coefficient in rock plugs. The point cloud generated from the 3D model of the photogrammetry process was used to measure the distance between each point and a calculated fit plane over the entire rock surface. The roughness was quantified using roughness parameters ($$R_a$$

R
a

) calculated in hierarchically organized regions. In this hierarchical division, the greater the quantity of division analyzed, the greater the detail of the roughness. The main results show that obtaining the roughness coefficient over the entire surface of the three-dimensional model has peculiarities that would not be observed in the two-dimensional reading. From the 2D measurements, mean roughness values ($$R_a$$

R
a

) of $$0.35\,\upmu \hbox {m}$$

0.35

μ
m

and $$0.235\,\upmu \hbox {m}$$

0.235

μ
m

were obtained for samples 1 and 2, respectively. By the same method, the results of the $$R_a$$

R
a

coefficient applied three-dimensionally over the entire rocky surface were at most $$0.165\,\upmu \hbox {m}$$

0.165

μ
m

and $$0.166\,\upmu \hbox {m}$$

0.166

μ
m

, respectively, showing the difference in values along the surface and the importance of this approach.
Investigating the association between infertility and psychological distress using Australian Longitudinal Study on Women's Health (ALSWH)
Authors: Bagade Tanmay , Thapaliya Kailash , Breuer Erica , Kamath Rashmi , Li Zhuoyang , Sullivan Elizabeth , Majeed Tazeen
Published: June 2022

Infertility affects millions of people globally. Although an estimated 1 in 6 couples in Australia are unable to conceive without medical intervention, little is known about the mental health impacts of infertility. This study investigated how infertility impacts the mental health of women. The study used nationally representative Australian Longitudinal Study on Women's Health (ALSWH) data. We analysed data from survey periods 2–8 conducted every three years between 2000 and 2018 for 6582 women born in 1973–78. We used a Generalised Equation Modelling (GEE) method to investigate the association of primary, secondary and resolved fertility status and psychological distress over time. Multiple measures were used to measure psychological distress: the (1) the mental health index subscale of the 36-item short form survey (SF-36), (2) the Center for Epidemiological Studies Depression Scale (CESD-10), (3) the Goldberg Anxiety and Depression Scale (GADanx) anxiety subscale; and a (4) composite psychological distress variable. About a third (30%) of women reported infertility at any of the survey rounds; a steady increase over 18 years from 1.7% at round 2 to 19.3% at round 8. Half of the women reporting primary or secondary infertility reported psychological distress, with the odds of having psychological distress was higher in women reporting primary (odds ratio (OR) 1.24, 95% confidence interval (CI) 1.06–1.45), secondary (OR 1.27, 95% CI 1.10–1.46) or resolved infertility (OR 1.15, 95% CI 1.05–1.26) compared to women reporting normal fertility status. Women with partners, underweight or higher BMI, smoking, and high-risk alcohol use had higher odds of psychological distress, whereas women in paid work had significantly lower odds of psychological distress (p < 0.001). Diabetes, high blood pressure, asthma, and other chronic physical illness were independently associated with higher odds of psychological distress. Infertility has a significant impact on mental health even after it is resolved. Frequent mental health assessment and a holistic approach to address the lifestyle factors should be undertaken during the treatment of infertility.
Cerebral oxygenation and body mass index association with cognitive function in chronic kidney disease patients without dialysis: a longitudinal study
Authors: Ookawara Susumu , Ito Kiyonori , Sasabuchi Yusuke , Miyahara Mayako , Miyashita Tomoka , Takemi Nana , Nagamine Chieko , Nakahara Shinobu , Horiuchi Yuko , Inose Nagisa , Shiina Michiko , Murakoshi Miho , Sanayama Hidenori , Hirai Keiji , Morishita Yoshiyuki
Published: June 2022

In chronic kidney disease (CKD) patients, the prevalence of cognitive impairment increases with CKD progression; however, longitudinal changes in cognitive performance remain controversial. Few reports have examined the association of cerebral oxygenation with cognitive function in longitudinal studies. In this study, 68 CKD patients were included. Cerebral regional oxygen saturation (rSO2) was monitored. Cognitive function was evaluated using mini-mental state examination (MMSE) score. Clinical assessments were performed at study initiation and 1 year later. MMSE score was higher at second measurement than at study initiation (p = 0.022). Multivariable linear regression analysis showed that changes in MMSE were independently associated with changes in body mass index (BMI, standardized coefficient: 0.260) and cerebral rSO2 (standardized coefficient: 0.345). This was based on clinical factors with p < 0.05 (changes in BMI, cerebral rSO2, and serum albumin level) and the following confounding factors: changes in estimated glomerular filtration rate, hemoglobin level, proteinuria, salt and energy intake, age, presence of diabetes mellitus, history of comorbid cerebrovascular disease, and use of renin–angiotensin system blocker. Further studies with a larger sample size and longer observational period are needed to clarify whether maintaining BMI and cerebral oxygenation improve or prevent the deterioration of cognitive function.
Morphology of en face Haller vessel and macular neovascularization at baseline and 3 months as predictive factors in age-related macular degeneration
Authors: Lee Hyungwoo , Kim SoHyeon , Kim Myung Ae , Chung Hyewon , Kim Hyung Chan
Published: June 2022

The clinical implication of en face imaging of Haller vessels and macular neovascularization (MNV) in neovascular age-related macular degeneration (nAMD) is not well established. The purpose of this study is to investigate whether the early-phase morphology of en face Haller vessel and MNV is related to the injection frequency and visual outcome in treatment-naïve nAMD. En face images of Haller vessel and MNV were acquired from 52 eyes at baseline, after three loading doses and at 12 months later using optical coherence tomography (OCT) and OCT angiography. Vessel area, diameter, length, intersection number, fractal dimension, and lacunarity were calculated. Patients were classified according to the injection frequency (< 5 as the infrequent group) and visual gain (≥ 0.3 logMAR) over 12 months. The infrequent group was associated with a longer Haller vessel length after loading doses (OR 3.05, P = 0.01), while visual gain was associated with a smaller maximal MNV diameter after loading doses (OR 0.22, P = 0.03). A predictive model for frequent injection based on the Haller vessel length demonstrated an AUC of 0.71. In conclusion, the en face Haller vessel and MNV morphology after loading doses can be used as biomarkers for the injection frequency and visual gain during the first year in treatment-naïve nAMD patients.
Cell-repellent polyampholyte for conformal coating on microstructures
Authors: Suzuki Kohei , Hiroi Yoshiomi , Abe-Fukasawa Natsuki , Nishino Taito , Shouji Takeaki , Katayama Junko , Kageyama Tatsuto , Fukuda Junji
Published: June 2022

Repellent coatings are critical for the development of biomedical and analytical devices to prevent nonspecific protein and cell adhesion. In this study, prevelex (polyampholytes containing phosphate and amine units) was synthesized for the fine coating of microdevices for cell culture. The dip-coating of the prevelex on hydrophobic substrates altered their surfaces to be highly hydrophilic and electrically neutral. The range of prebake temperature (50–150 °C) after dip-coating was moderate and within a preferable range to treat typical materials for cell culture such as polystyrene and polydimethylsiloxane. Scanning electron microscopy revealed a conformal and ultra-thin film coating on the micro/nano structures. When compared with poly(2-hydroxyethyl methacrylate) and poly(2-methacryloyloxyethyl phosphorylcholine), prevelex exhibited better characteristics for coating on microwell array devices, thereby facilitating the formation of spheroids with uniform diameters using various cell types. Furthermore, to examine cellular functionalities, mouse embryonic epithelial and mesenchymal cells were seeded in a prevelex-coated microwell array device. The two types of cells formed hair follicle germ-like aggregates in the device. The aggregates were then transplanted to generate de novo hair follicles in nude mice. The coating material provided a robust and fine coating approach for the preparation of non-fouling surfaces for tissue engineering and biomedical applications.
Seroprevalence of SARS-CoV-2 in Sweden, April 26 to May 9, 2021
Authors: Beser Jessica , Galanis Ilias , Enkirch Theresa , Kühlmann Berenzon Sharon , van Straten Edward , Duracz Jan , Rapp Marie , Zakikhany Katherina , Mansjö Mikael , Wigren Byström Julia , Forsell Mattias N. E. , Groenheit Ramona , Tegmark Wisell Karin , Bråve Andreas
Published: June 2022

A national point seroprevalence study of SARS-CoV-2 was conducted in Sweden in April–May 2021. In total, 2860 individuals 3 to 90 years old from a probability-based web panel were included. Results showed that an estimated 32.6% of the population in Sweden had detectable levels of antibodies, and among non-vaccinated 20.1% had detectable levels of antibodies. We tested for differences in seroprevalence between age groups and by sex and estimated seroprevalence among previously infected participants by time since reporting.
Ribonuclease 4 is associated with aggressiveness and progression of prostate cancer
Authors: Vanli Nil , Sheng Jinghao , Li Shuping , Xu Zhengping , Hu Guo-Fu
Published: June 2022

Prostate specific antigen screening has resulted in a decrease in prostate cancer-related deaths. However, it also has led to over-treatment affecting the quality of life of many patients. New biomarkers are needed to distinguish prostate cancer from benign prostate hyperplasia (BPH) and to predict aggressiveness of the disease. Here, we report that ribonuclease 4 (RNASE4) serves as such a biomarker as well as a therapeutic target. RNASE4 protein level in the plasma is elevated in prostate cancer patients and is positively correlated with disease stage, grade, and Gleason score. Plasma RNASE4 level can be used to predict biopsy outcome and to enhance diagnosis accuracy. RNASE4 protein in prostate cancer tissues is enhanced and can differentiate prostate cancer and BPH. RNASE4 stimulates prostate cancer cell proliferation, induces tumor angiogenesis, and activates receptor tyrosine kinase AXL as well as AKT and S6K. An RNASE4-specific monoclonal antibody inhibits the growth of xenograft human prostate cancer cell tumors in athymic mice.
Sensitivity of subregional distribution of socioeconomic conditions to the global assessment of water scarcity
Authors: Modi Prakat , Hanasaki Naota , Yamazaki Dai , Boulange Julien Eric Stanislas , Oki Taikan
Published: June 2022

Water availability per capita is among the most fundamental water-scarcity indicators used extensively in global grid-based water resources assessments. Recently, it has extended to include the economic aspect, a proxy of the capability for water management which we applied globally under socioeconomic-climate scenarios using gridded population and economic conditions. We found that population and economic projection choices significantly influence the global water scarcity assessment, particularly the assumption of urban concentrated and dispersed population. Using multiple socioeconomic-climate scenarios, global climate models, and two gridded population datasets, capturing extremities, we show that the water-scarce population ranges from 0.32–665 million in the future. Uncertainties in the socioeconomic-climate scenarios and global climate models are 6.58–489 million and 0.03–248 million, respectively. The population distribution has a similar impact, with an uncertainty of 169.1–338 million. These results highlight the importance of the subregional distribution of socioeconomic factors for future global environment prediction.
A coordination strategy to achieve instant dissolution of a biomedical polymer in water via manual shaking
Authors: Tang Jingyu , Cai Caiyun , Cao Dinglingge , Rao Weihan , Guo Wen , Yu Lin , Ding Jiandong
Published: June 2022

Chain-like polymers with condensed long chains have very low solubility in water, which has significantly hindered their medical applications. Herein, a strategy was suggested and rapid dissolution was achieved in half a minute via manual shaking.
Co-based metal–organic framework for photocatalytic hydrogen generation
Authors: Pukdeejorhor Ladawan , Adpakpang Kanyaporn , Wannapaiboon Suttipong , Bureekaew Sareeya
Published: June 2022

Co-triazole MOF, obtained by facile hydrothermal synthesis, can be utilized as an efficient photo-driven catalyst in hydrogen production. The framework is highly robust and exhibits excellent activity, producing hydrogen of 9.32 mmol g−1 in 4 h.
Mesoscale clusters of organic solutes in solution and their role in crystal nucleation
Authors: Svärd Michael
Published: June 2022

Despite recent advances, fundamental knowledge of the properties, thermodynamics and kinetics of mesoscale clusters, and their role in nucleation, is still limited.
Photoinduced deformation of amorphous polyimide enabled by an improved azobenzene isomerization efficiency
Authors: Sun Xuejie , Wei Jia , Yu Yanlei
Published: June 2022

A newly designed azo-PI, without pre-stretching or polarized-light irradiation, exhibits reversible bending behaviors under alternate UV and visible light irradiation, providing a facile route to deformable 2D/3D structure actuators.
Amine-catalyzed site- and stereo-selective coupling of epoxy amines and carbon dioxide to construct oxazolidinones
Authors: Qiu Wenqin , Jin Feng , Hao Yanhong , Bao Xiaoguang , Yuan Dan , Yao Yingming
Published: June 2022

NEt3catalyzed the cycloaddition of epoxy amine and CO2, which generated oxazolidinones. Reactions of chiral epoxy amine achieved 100% configuration inversion, enabling the synthesis of linezolid. DFT studies show that NEt3acted as a nucleophile.
Advances in hydrogels for stem cell therapy: regulation mechanisms and tissue engineering applications
Authors: Liu Guiting , Zhou Yuan , Zhang Xianlong , Guo Shaoyun
Published: June 2022

Here, the recent advances in hydrogels for stem cell therapy are summarized, aiming to provide a reference for the crossover and integration of hydrogels and stem cells in the field of tissue engineering.
Bilateral U‐Net semantic segmentation with spatial attention mechanism
Authors: Zhao Guangzhe , Zhang Yimeng , Ge Maoning , Yu Min
Published: June 2022

Aiming at the problem that the existing models have a poor segmentation effect on imbalanced data sets with small‐scale samples, a bilateral U‐Net network model with a spatial attention mechanism is designed. The model uses the lightweight MobileNetV2 as the backbone network for feature hierarchical extraction and proposes an Attentive Pyramid Spatial Attention (APSA) module compared to the Attenuated Spatial Pyramid module, which can increase the receptive field and enhance the information, and finally adds the context fusion prediction branch that fuses high‐semantic and low‐semantic prediction results, and the model effectively improves the segmentation accuracy of small data sets. The experimental results on the CamVid data set show that compared with some existing semantic segmentation networks, the algorithm has a better segmentation effect and segmentation accuracy, and its mIOU reaches 75.85%. Moreover, to verify the generality of the model and the effectiveness of the APSA module, experiments were conducted on the VOC 2012 data set, and the APSA module improved mIOU by about 12.2%.
Attention‐based multi‐channel feature fusion enhancement network to process low‐light images
Authors: Xu Xintao , Li Jinjiang , Hua Zhen , Fan Linwei
Published: June 2022

In realistic low‐light environments, images captured by imaging devices often have problems such as low brightness and low contrast, serious loss of detail information, and a large amount of noise, posing major challenges to computer vision tasks. Low‐light image enhancement can effectively improve the overall quality of the image, which has important significance and application value. In this study, an attention‐based multi‐channel feature fusion enhancement network (M‐FFENet) is proposed to process low‐light images. In this network, a feature extraction model is first used to obtain the deep features of the downsampled low‐light images and fit them to an affine bilateral grid. Second, the addition of attention‐based residual dense blocks (ARDB) allows the network to focus on more details and spatial information. Meanwhile, all color channels are considered. The channel features and bilateral meshes are then linearly interpolated using the feature reconfiguration model (FRM) to obtain high‐quality features containing rich color and texture information. Next, the feature fusion module (FFM) is used to fuse features that contain different information. Enhancement model is used to further recover texture and detail in the image. Finally, the enhanced image is output. Numerous experimental results have shown that the method achieves better results in both quantitative and qualitative aspects compared to other methods.
Pricing iterative optimization for multi‐agent simulation of setting electric vehicle charging model in public parking lots
Authors: Mei Zhenyu , Liu Yi , Zhao Jinhuan , Cai Zhengyi
Published: June 2022

Despite the increasing scale of the electric vehicle market in recent years, in view of the long charging time of EVs (Electric Vehicles), the accessibility of charging facilities is still an obstacle to the rapid development of EVs. Therefore, the Chinese government has promulgated a one‐size‐fits‐all construction strategy which means constructing charging piles in parking lots with a fixed proportion. This paper mainly simulates the actual demand and adjusts the charging price of charging stations to reduce the uneven spatial distribution of charging demand. In particular, this paper constructs a multi‐agent system of the road network, vehicle, and charging station to simulate the charging behaviour in the mixed scenario of EVs and traditional fuel vehicles. The impact of charging pricing adjustment on individuals and charging stations is fed back in real‐time by using the characteristics of agents to respond to dynamic changes and make intelligent decisions. This paper proposes an iterative optimization method to obtain the optimal pricing strategy for charging stations to reduce the imbalance of charging demand. Taking the Wulin Square business district in Hangzhou as an example, the results show that the proposed pricing optimization method can improve the overall utility.
Exploration of the spatiotemporal heterogeneity of metro ridership prompted by built environment: A multi‐source fusion perspective
Authors: Fu Xin , Zhao Xiao‐Xuan , Li Ceng‐Ceng , Cui Meng‐Yan , Wang Jian‐Wei , Qiang Yong‐Jie
Published: June 2022

The spatial and temporal characteristics of the factors influencing metro passenger flow are basic phenomena reflecting the environment‐land relationship. Existing studies tend to focus more on the characteristics of metro trips and the static built environment. One of the outstanding contributions of this paper is to expand the scope of the factors influencing the built environment of metro stations and explore the spatial differentiation and pattern characteristics of the static and dynamic environments. This paper provides additional empirical insights into spatiotemporal influencing factors of metro mobility patterns from the dynamic perspective. The results show spatial and temporal heterogeneity between four types of metro stations and their influencing factors. 21.59% of the stations are in in active areas, while the distribution of parking lots has a positive effect on metro passenger flow; 29.55% of the stations belong to integrated residential areas, and the number of residential areas is the dominant factor in such agglomerations; 38.64% of the areas belong to work areas, and such areas have the highest work‐related coefficients, but the work variable in the central city has a certain inhibiting effect; 10.23% of the stations are in commercial areas, which are mainly distributed within the central urban area.
Reinforcement learning based mainline dynamic speed limit adjustment of expressway off‐ramp upstream under connected and autonomous vehicles environment
Authors: Xiao Daiquan , Kang Shengyang , Xu Xuecai , Shen Zhenwu
Published: June 2022

With the rapid progress of urbanization and continuous increasing of automobiles, expressway on‐ and off‐ramp area becomes the bottleneck, and recurrent congestion occurs frequently. In order to solve the problem of traffic jam caused around off‐ramps, various methods have been employed. Among all, mainline variable speed limit (VSL) control accounts for some proportion. In this study, mainline VSL adjustment of off‐ramp upstream is investigated with the reinforcement learning algorithm under the connected vehicles environment to alleviate the traffic congestion. First, the assumptions are made to be suitable for the traffic conditions of mainline VSL control on off‐ramp upstream, and then VSL algorithm based on reinforcement learning is presented, and Q‐learning is chosen as the main algorithm. Next, the state space, action space, and reward function required by Q‐learning are constructed orderly, and the related parameters are labelled. After that, according to the platform based on Python and VISSIM, three schemes, free control (Scheme 0), mainline VSL adjustment of off‐ramp upstream based on rule (Scheme 1), and mainline VSL adjustment of off‐ramp upstream based on Q‐learning algorithm (Scheme 2), are designed, and the three schemes are simulated and compared quantitatively to reflect the off‐ramp travel efficiency. The results indicate that mainline dynamic VSL adjustment of off‐ramp upstream based on Q‐learning algorithm performs the best in terms of general and specific indexes. The results provide potential insights for relieving the traffic congestion and traffic flow control under CAVs environment.
Locating dust and molecules in the inner circumstellar environment of R Sculptoris with MATISSE
Authors: Drevon J. , Millour F. , Cruzalèbes P. , Paladini C. , Hron J. , Meilland A. , Allouche F. , Hofmann K.-H. , Lagarde S. , Lopez B. , Matter A. , Petrov R. , Robbe-Dubois S. , Schertl D. , Scicluna P. , Wittkowski M. , Zins G. , Ábrahám P. , Antonelli P. , Beckmann U. , Berio P. , Bettonvil F. , Glindemann A. , Graser U. , Heininger M. , Henning Th. , Isbell J. W. , Jaffe W. , Labadie L. , Leinert C. , Lehmitz M. , Morel S. , Meisenheimer K. , Soulain A. , Varga J. , Weigelt G. , Woillez J. , Augereau J.-C. , van Boekel R. , Burtscher L. , Danchi W. C. , Dominik C. , Gámez Rosas V. , Hocdé V. , Hogerheijde M. R. , Klarmann L. , Kokoulina E. , Leftley J. , Stee P. , Vakili F. , Waters R. , Wolf S. , Yoffe G.
Published: June 2022

Context. Asymptotic giant branch (AGB) stars are one of the main sources of dust production in the Galaxy. However, it is not yet clear what this process looks like and where the dust happens to be condensing in the circumstellar environment.

Aims. By characterizing the location of the dust and the molecules in the close environment of an AGB star, we aim to achieve a better understanding the history of the dust formation process.

Methods. We observed the carbon star R Scl with the thermal-infrared VLTI/MATISSE instrument in L- and N-bands. The high angular resolution of the VLTI observations (as small as 4.4 mas in the L-band and 15 mas in the N-band with ATs), combined with a large uv-plane coverage allowed us to use image reconstruction methods. To constrain the dust and molecules’ location, we used two different methods: one using MIRA image reconstruction algorithm and the second using the 1D code RHAPSODY.

Results. We found evidence of C2H2 and HCN molecules between 1 and 3.4 R* which is much closer to the star than the location of the dust (between 3.8 and 17.0 R*). We also estimated a mass-loss rate of 1.2 ± 0.4 × 10−6 M⊙ yr−1. In the meantime, we confirmed the previously published characteristics of a thin dust shell, composed of amorphous carbon (amC) and silicon carbide (SiC). However, no clear SiC feature has been detected in the MATISSE visibilities. This might be caused by molecular absorption that can affect the shape of the SiC band at 11.3 µm.

Conclusions. The appearance of the molecular shells is in good agreement with predictions from dynamical atmosphere models. For the first time, we co-located dust and molecules in the environment of an AGB star. We confirm that the molecules are located closer to the star than the dust. The MIRA images unveil the presence of a clumpy environment in the fuzzy emission region beyond 4.0 R*. Furthermore, with the available dynamic range and angular resolution, we did not detect the presence of a binary companion. To solve this problem, additional observations combining MATISSE and SAM-VISIR instrument should enable this detection in future studies.
Maximal growth rate of the ascending phase of a sunspot cycle for predicting its amplitude
Authors: Podladchikova Tatiana , Jain Shantanu , Veronig Astrid M. , Sutyrina Olga , Dumbović Mateja , Clette Frédéric , Pötzi Werner
Published: June 2022

Context. Forecasting the solar cycle amplitude is important for a better understanding of the solar dynamo as well as for many space weather applications. Different empirical relations of solar cycle parameters with the peak amplitude of the upcoming solar cycle have been established and used for solar cycle forecasts, as, for instance, the Waldmeier rule relating the cycle rise time with its amplitude, the polar fields at previous minimum, and so on. Recently, a separate consideration of the evolution of the two hemispheres revealed even tighter relations.

Aims. We aim to introduce the maximal growth rate of sunspot activity in the ascending phase of a cycle as a new and reliable precursor of a subsequent solar cycle amplitude. We also intend to investigate whether the suggested precursor provides benefits for the prediction of the solar cycle amplitude when using the sunspot indices (sunspot numbers, sunspot areas) derived separately for the two hemispheres compared to the total sunspot indices describing the entire solar disc.

Methods. We investigated the relationship between the maximal growth rate of sunspot activity in the ascending phase of a cycle and the subsequent cycle amplitude on the basis of four data sets of solar activity indices: total sunspot numbers, hemispheric sunspot numbers from the new catalogue from 1874 onwards, total sunspot areas, and hemispheric sunspot areas.

Results. For all the data sets, a linear regression based on the maximal growth rate precursor shows a significant correlation. Validation of predictions for cycles 1–24 shows high correlations between the true and predicted cycle amplitudes reaching r = 0.93 for the total sunspot numbers. The lead time of the predictions varies from 2 to 49 months, with a mean value of 21 months. Furthermore, we demonstrated that the sum of maximal growth rate indicators determined separately for the north and the south hemispheric sunspot numbers provides more accurate predictions than that using total sunspot numbers. The advantages reach 27% and 11% on average in terms of rms and correlation coefficient, respectively. The superior performance is also confirmed with hemispheric sunspot areas with respect to total sunspot areas.

Conclusions. The maximal growth rate of sunspot activity in the ascending phase of a solar cycle serves as a reliable precursor of the subsequent cycle amplitude. Furthermore, our findings provide a strong foundation for supporting regular monitoring, recording, and predictions of solar activity with hemispheric sunspot data, which capture the asymmetric behaviour of the solar activity and solar magnetic field and enhance solar cycle prediction methods.
High-Throughput Screening of Epigenetic Inhibitors in Meningiomas Identifies HDAC, G9a, and Jumonji-Domain Inhibition as Potential Therapies
Authors: Tatman Philip D. , Wroblewski Tadeusz H. , Fringuello Anthony R. , Scherer Samuel R. , Foreman William B. , Damek Denise M. , Youssef A. Samy , Lillehei Kevin O. , Jensen Randy L. , Graner Michael W. , Ormond D. Ryan
Published: June 2022

Background Epigenetics may predict treatment sensitivity and clinical course for patients with meningiomas more accurately than histopathology. Nonetheless, targeting epigenetic mechanisms is understudied for pharmacotherapeutic development for these tumors. The bio-molecular insights and potential therapeutic development of meningioma epigenetics led us to investigate epigenetic inhibition in meningiomas.

Methods We screened a 43-tumor cohort using a 139-compound epigenetic inhibitor library to assess sensitivity of relevant meningioma subgroups to epigenetic inhibition. The cohort was composed of 5 cell lines and 38 tumors cultured directly from surgery; mean patient age was 56.6 years ± 13.9 standard deviation. Tumor categories: 38 primary tumors, 5 recurrent; 33 from females, 10 from males; 32 = grade 1; 10 = grade 2; 1 = grade 3.

Results Consistent with our previous results, histone deacetylase inhibitors (HDACi) were the most efficacious class. Panobinostat significantly reduced cell viability in 36 of 43 tumors; 41 tumors had significant sensitivity to some HDACi. G9a inhibition and Jumonji-domain inhibition also significantly reduced cell viability across the cohort; tumors that lost sensitivity to panobinostat maintained sensitivity to either G9a or Jumonji-domain inhibition. Sensitivity to G9a and HDAC inhibition increased with tumor grade; tumor responses did not separate by gender. Few differences were found between recurrent and primary tumors, or between those with prior radiation versus those without.

Conclusions Few efforts have investigated the efficacy of targeting epigenetic mechanisms to treat meningiomas, making the clinical utility of epigenetic inhibition largely unknown. Our results suggest that epigenetic inhibition is a targetable area for meningioma pharmacotherapy.
Applying Automated Machine Learning to Predict Mode of Delivery Using Ongoing Intrapartum Data in Laboring Patients
Authors: Wong Melissa S. , Wells Matthew , Zamanzadeh Davina , Akre Samir , Pevnick Joshua M. , Bui Alex A.T. , Gregory Kimberly D.
Published: June 2022

Objective This study aimed to develop and validate a machine learning (ML) model to predict the probability of a vaginal delivery (Partometer) using data iteratively obtained during labor from the electronic health record.

Study Design A retrospective cohort study of deliveries at an academic, tertiary care hospital was conducted from 2013 to 2019 who had at least two cervical examinations. The population was divided into those delivered by physicians with nulliparous term singleton vertex (NTSV) cesarean delivery rates <23.9% (Partometer cohort) and the remainder (control cohort). The cesarean rate among this population of lower risk patients is a standard metric by which to compare provider rates; <23.9% was the Healthy People 2020 goal. A supervised automated ML approach was applied to generate a model for each population. The primary outcome was accuracy of the model developed on the Partometer cohort at 4 hours from admission to labor and delivery. Secondary outcomes included discrimination ability (receiver operating characteristics–area under the curve [ROC-AUC]), precision-recall AUC, and calibration of the Partometer. To assess generalizability, we compared the performance and clinical predictors identified by the Partometer to the control model.

Results There were 37,932 deliveries during the study period; after exclusions, 9,385 deliveries were included in the Partometer cohort and 19,683 in the control cohort. Accuracy of predicting vaginal delivery at 4 hours was 87.1% for the Partometer (ROC-AUC: 0.82). Clinical predictors of greatest importance in the stacked Intrapartum Partometer Model included the Admission Model prediction and ongoing measures of dilatation and station which mirrored those found in the control population.

Conclusion Using automated ML and intrapartum factors improved the accuracy of prediction of probability of a vaginal delivery over both previously published models based on logistic regression. Harnessing real-time data and ML could represent the bridge to generating a truly prescriptive tool to augment clinical decision-making, predict labor outcomes, and reduce maternal and neonatal morbidity.

Key Points
Leaving the Placenta In Situ in Placenta Accreta Spectrum Disorders: A Single-Center Case Series
Authors: Pineles Beth L. , Coselli Jennie , Ghorayeb Tala , Fishel Bartal Michal , Zvavanjanja Rodrick C. , Blackwell Sean C. , Papanna Ramesha , Sibai Baha M.
Published: June 2022

Objective The most common treatment for placenta accreta spectrum (PAS) disorders is planned primary cesarean hysterectomy. However, other management strategies may improve outcomes and/or allow fertility preservation. The objective of this study was to describe the course and outcomes of patients with PAS managed by leaving the placenta in situ.

Study Design This is a series of 11 patients with PAS managed by leaving the placenta in situ at a single academic center in the United States from 2015 to 2022. The approach described involves delivery of the fetus via cesarean, no attempt at placental removal, closure of the hysterotomy, prophylactic intravenous antibiotics for up to 1 week, and close outpatient follow-up until the uterus is empty.

Results The uterus was successfully preserved in six (55%), minimally invasive hysterectomy was performed in four (36%), and abdominal hysterectomy was performed in 1 (9%). During cesarean delivery, the median estimated blood loss was 650mL (range: 200–1,000mL). The majority of patients had no vaginal discharge for several weeks after delivery, followed by brown or bloody discharge, and intermittent mild-to-moderate cramping. The median time to resolution of PAS was 18 weeks in patients with successful uterine preservation (range: 5–25 weeks). Indications for hysterectomy included hemorrhage (n=1), coagulopathy (n=1), endomyometritis (n=2), and pain (n=1), and these occurred at a median of 5 weeks postpartum (range: 1–25 weeks). Four patients had subsequent pregnancies of whom three were live births at or near term and one was a spontaneous abortion at 19 weeks.

Conclusion Leaving the placenta in situ may be an appropriate management strategy for some carefully selected and counseled patients with PAS.

Key Points
Dual-Energy X-Ray Absorptiometry and Anthropometry for Assessment of Nutritional Status at Diagnosis in Children with Cancer: A Single-Center Experience from India
Authors: Priyanka Soni , Sandeep Jain , Gauri Kapoor , Gayatri Vishwakarma
Published: June 2022

Background The survival of children with cancer has improved owing to advances in chemotherapy and better supportive care, and nutritional support is an important component of the latter especially in low- and middle-income countries like India.

Materials and Methods A prospective observational study of 137 newly diagnosed children with cancer aged less than 18 years was planned. Nutritional assessment was done using dual-energy X-ray absorptiometry (DXA), anthropometry, and serum albumin. Patients were followed for 3 months for assessment of treatment-related morbidity.

Results Lean body mass (LBM; DXA), mid-upper arm circumference (MUAC), and body mass index detected undernutrition in 44, 45, and 14% patients, respectively. Combination of arm anthropometry (MUAC and triceps skinfold thickness) with serum albumin categorized patients as adequately nourished (32%), moderately depleted (18%), and severely depleted (49%). Patients with hematological malignancy had a higher prevalence of undernutrition but there was no difference in morbidities between the undernourished and adequately nourished children by any parameter. Hypoalbuminemia observed in 25% patients was associated with significant chemotherapy delays (p, 0.01) and interval admissions (p, 0.03). Using LBM as a criterion, linear regression analysis revealed MUAC (R
2 = 0.681) as the best predictor of undernutrition with lowest standard error.

Conclusion Our study reports undernutrition among two-fifths of newly diagnosed patients of childhood cancer associated with high prevalence of sarcopenia and adiposity. These findings are of utmost clinical relevance in planning interventional strategies.
Influence of New FIGO 2018 Staging on Treatment Outcomes in Early-Stage Cervical Cancer: A Single-Center Study
Authors: Kaur Satinder , Garg Hemlata , Nandwani Megha , Kalita Manoj , Bansal Satish , Singh Randeep
Published: June 2022

Purpose The aim of this article was to study survival outcomes of early-stage cervical cancer patients and impact on survival after restaging them as per International Federation of Gynecology and Obstetrics (FIGO) 2018.

Materials and Methods A retrospective study was conducted from June 1, 2013 to May 31, 2018 in a tertiary care hospital in North India. One-hundred patients of early-stage cervical cancer (as per FIGO 2009 staging) who had been treated by surgery followed by risk based tailored adjuvant therapy in our hospital were evaluated. The clinicopathological features and survival outcomes of these patients were analyzed. These patients were then restaged as per new FIGO 2018 staging and survival outcomes between two FIGO classifications were compared.

Results The median age of the study population was 52.5 years with median follow-up of 62.1 months. Ninety percent of our patients had more than 2 years follow-up and 59% had more than 5 years follow-up. The overall survival and relapse-free survival were 87.5 and 91.4%, respectively. The study population was then reclassified according to new FIGO 2018 staging. It was seen that the patients with stage IB1and IB2 cervical cancer had overall survival of 91.1 and 90%, respectively. The overall survival of stage IB3 was 80% and the survival of stage IIIC1 was only 60%.

Conclusion The new FIGO 2018 classification has a significant effect on survival outcome and in prognostication of patients with cervical cancer.