bluuebunny/crossref_metadata_2025_split huggingface dataset:
Subjective Successful Aging Predicts Probability of Mortality Over 9 Years Among Adults Aged 50–74
Authors: Pruchno Rachel , Sands Laura P , Cartwright Francine P , Rose Miriam , Zhu Xiaofan 
Published: October 2023

Abstract

Background and Objectives
Although the relationship between mortality and objective successful aging (health, functional ability, social engagement) is clear, the relationship between subjective successful aging (SSA) and mortality is inconclusive. Building on the broader literature regarding psychological well-being, these analyses examine the relationship between SSA and mortality, adjusting for demographic, health, and lifestyle characteristics with known mortality risks.

Research Design and Methods
We analyzed self-report data collected between 2006 and 2008 from 5,483 people. In addition to demographic, health, and lifestyle variables, we measured SSA using a valid, reliable measure. Over the course of 3,285 days, 695 people died. We computed 4 sequential Cox proportional hazard models to examine the association between SSA and time to death. The first model included only SSA; Model 2 added demographic characteristics; Model 3 added health characteristics; Model 4 added lifestyle characteristics.

Results
We found that SSA had a significant association with mortality, accounting for known mortality risk factors. Each 1-point rise in SSA decreased the risk of mortality by 3% (0.97; 95% confidence interval = 0.95–0.99; p &lt; .05). The probability of death within 9 years for persons with SSA scores from 0 to 5 was 45%; for persons with SSA scores from 25 to 30, risk of mortality was less than 10%.

Discussion and Implications
Findings provide evidence that lower SSA scores reveal greater risk for mortality beyond demographic, health, and lifestyle variables. A brief assessment of SSA can provide unique clinical information and be used to identify people who might benefit from interventions to reduce mortality risk.
The haplotype-resolved autotetraploid genome assembly provides insights into the genomic evolution and fruit divergence in wax apple (Syzygium samarangense (Blume) Merr. and Perry)
Authors: Wei Xiuqing , Chen Min , Zhang Xijuan , Wang Yinghao , Li Liang , Xu Ling , Wang Huanhuan , Jiang Mengwei , Wang Caihui , Zeng Lihui , Xu Jiahui 
Published: October 2023

Abstract
Wax apple (Syzygium samarangense) is an economically important fruit crop with great potential value to human health because of its richness in antioxidant substances. Here, we present a haplotype-resolved autotetraploid genome assembly of the wax apple with a size of 1.59 Gb. Comparative genomic analysis revealed three rounds of whole-genome duplication (WGD) events, including two independent WGDs after WGT-γ. Resequencing analysis of 35 accessions partitioned these individuals into two distinct groups, including 28 landraces and seven cultivated species, and several genes subject to selective sweeps possibly contributed to fruit growth, including the KRP1-like, IAA17-like, GME-like, and FLACCA-like genes. Transcriptome analysis of three different varieties during flower and fruit development identified key genes related to fruit size, sugar content, and male sterility. We found that AP2 also affected fruit size by regulating sepal development in wax apples. The expression of sugar transport-related genes (SWEETs and SUTs) was high in ‘ZY’, likely contributing to its high sugar content. Male sterility in ‘Tub’ was associated with tapetal abnormalities due to the decreased expression of DYT1, TDF1, and AMS, which affected early tapetum development. The chromosome-scale genome and large-scale transcriptome data presented in this study offer new valuable resources for biological research on S. samarangense and shed new light on fruit size control, sugar metabolism, and male sterility regulatory metabolism in wax apple.
Addressing class imbalance in deep learning for acoustic target classification
Authors: Pala Ahmet , Oleynik Anna , Utseth Ingrid , Handegard Nils Olav 
Published: October 2023

AbstractAcoustic surveys provide important data for fisheries management. During the surveys, ship-mounted echo sounders send acoustic signals into the water and measure the strength of the reflection, so-called backscatter. Acoustic target classification (ATC) aims to identify backscatter signals by categorizing them into specific groups, e.g. sandeel, mackerel, and background (as bottom and plankton). Convolutional neural networks typically perform well for ATC but fail in cases where the background class is similar to the foreground class. In this study, we discuss how to address the challenge of class imbalance in the sampling of training and validation data for deep convolutional neural networks. The proposed strategy seeks to equally sample areas containing all different classes while prioritizing background data that have similar characteristics to the foreground class. We investigate the performance of the proposed sampling methodology for ATC using a previously published deep convolutional neural network architecture on sandeel data. Our results demonstrate that utilizing this approach enables accurate target classification even when dealing with imbalanced data. This is particularly relevant for pixel-wise semantic segmentation tasks conducted on extensive datasets. The proposed methodology utilizes state-of-the-art deep learning techniques and ensures a systematic approach to data balancing, avoiding ad hoc methods.
SGMM: Stochastic Approximation to Generalized Method of Moments
Authors: Chen Xiaohong , Lee Sokbae , Liao Yuan , Seo Myung Hwan , Shin Youngki , Song Myunghyun 
Published: October 2023

Abstract
We introduce a new class of algorithms, stochastic generalized method of moments (SGMM), for estimation and inference on (overidentified) moment restriction models. Our SGMM is a novel stochastic approximation alternative to the popular Hansen (1982) (offline) GMM, and offers fast and scalable implementation with the ability to handle streaming datasets in real time. We establish the almost sure convergence, and the (functional) central limit theorem for the inefficient online 2SLS and the efficient SGMM. Moreover, we propose online versions of the Durbin–Wu–Hausman and Sargan–Hansen tests that can be seamlessly integrated within the SGMM framework. Extensive Monte Carlo simulations show that as the sample size increases, the SGMM matches the standard (offline) GMM in terms of estimation accuracy and gains over computational efficiency, indicating its practical value for both large-scale and online datasets. We demonstrate the efficacy of our approach by a proof of concept using two well-known empirical examples with large sample sizes.
Unique multidisciplinary approach in a patient with small bowel obstruction and chronic mesenteric ischemia
Authors: Tan Sally , Maniar Yesha , Pacheco Tulio B S , Spentzouris Georgios , Malhotra Anuj , Kella Venkata 
Published: October 2023

Abstract
Management of small bowel obstruction (SBO) in patients with symptomatic chronic mesenteric ischemia is a phenomenon that has not been previously described in the literature. This is an index case report describing the utilization of a multidisciplinary approach in a patient that suffered from SBO from cecal perforation with history of chronic mesenteric ischemia attributed to superior mesenteric artery (SMA) and celiac trunk stenosis. The patient was a 70-year-old female with recent diagnosis of ischemic colitis and chronic mesenteric ischemia, found to have high-grade SBO with transition point in the right lower quadrant. Computerized tomography angiogram showed occluded SMA, and severe celiac artery stenosis. Interventional radiology revascularized the celiac trunk with stent placement prior to right hemicolectomy for management of her high-grade SBO. Prospective research should ascertain whether revascularization indeed leads to improved post-operative outcomes.
The failure of cut-elimination in cyclic proof for first-order logic with inductive definitions
Authors: Oda Yukihiro , Brotherston James , Tatsuta Makoto 
Published: October 2023

Abstract
A cyclic proof system is a proof system whose proof figure is a tree with cycles. The cut-elimination in a proof system is fundamental. It is conjectured that the cut-elimination in the cyclic proof system for first-order logic with inductive definitions does not hold. This paper shows that the conjecture is correct by giving a sequent not provable without the cut rule but provable in the cyclic proof system.
Spectral properties of GX 339−4 in the intermediate state using AstroSat observation
Authors: Jana Arghajit , Chatterjee Debjit , Chang Hsiang-Kuang , Naik Sachindra , Mondal Santanu 
Published: October 2023

ABSTRACT
We present the results obtained from the spectral studies of black hole X-ray binary GX 339−4 using AstroSat observations during its 2021 outburst. AstroSat observed the source in the intermediate state for ∼600 ks. The combined spectra of SXT and LAXPC in the 0.7−25 keV energy range are studied with phenomenological and physical models. The spectral study reveals a receding disc and a contracting corona during the observation period. The outflow rate is found to be increased though the accretion rates did not vary during the observation period. The X-ray flux decreases as the disc recedes and the spectrum becomes hard. At the same time, the Comptonized flux decreases with increasing fraction of thermal emission. This could be plausible that episodic jet ejection modified the corona and reduced Comptonized flux. An iron emission line at 6.4 keV is observed in the spectra of all the orbits of observation. We find that the equivalent width of the iron emission line correlates with the photon index, indicating a decrease in the reflection strength as the spectrum becomes hard. We observe that the disc flux does not follow FDBB − T4 relation.
New technique to select recent fast-quenching galaxies at z ~ 2 using the optical colours
Authors: Kubo Mariko , Nagao Tohru , Uchiyama Hisakazu , Yamashita Takuji , Toba Yoshiki , Kajisawa Masaru , Yamamoto Yuta 
Published: October 2023

ABSTRACT
Many massive quiescent galaxies have been discovered at z &gt; 2 thanks to multiwavelength deep and wide surveys; however, substantial deep near-infrared spectroscopic observations are needed to constrain their star formation histories statistically. Here, we present a new technique to select quiescent galaxies with a short quenching time-scale (≤0.1 Gyr) at z ∼ 2 photometrically. We focus on a spectral break at ∼1600 Å that appears for such fast-quenching galaxies ∼1 Gyr after quenching when early A-type stars go out, but late A-type stars still live. This spectral break at z ∼ 2 is similar to a Lyman break at z ∼ 4. We construct a set of colour criteria for z ∼ 2 fast-quenching galaxies on g − r versus r − i and i − J versus J − H or $\rm {\it i}-[3.6]$ versus $\rm [3.6]-[4.5]$ colour diagrams, which are available with the existing and/or future wide imaging surveys, by simulating various model galaxy spectra and test their robustnesses using the COSMOS2020 catalogue. Galaxies with photometric and/or spectroscopic redshifts z ∼ 2 and low specific star formation rates are successfully selected using these colours. The number density of these fast-quenching galaxy candidates at z ∼ 2 suggests that massive galaxies not so far above the star formation main sequence at z = 3–4 should be their progenitors.
Detection of 12 426 SB2 candidates in the LAMOST-MRS, using a binary spectral model
Authors: Kovalev Mikhail , Zhou Zenghua , Chen Xuefei , Han Zhanwen 
Published: October 2023

ABSTRACT
We use an updated method for the detection of double-lined spectroscopic binaries (SB2s) using Vsin i values from spectral fits. The method is applied to all spectra from Large sky Area Multi-Object fiber Spectroscopic Telescope Medium Resolution Survey. Using this method, we detect 12 426 SB2 candidates, where 4321 are already known and 8105 are new discoveries. We check their spectra manually to minimize possible false positives. We also detect several cases of contamination of the spectra by solar light. Additionally, for candidates with multiple observations, we compute mass ratios with systemic velocities and determine Keplerian orbits. We present an updated catalogue of all SB2 candidates together with additional information for some of them in separate data tables.
Amir Timur
Authors: Jackson Peter 
Published: October 2023

Timur (Temür-i lang, “Temür the Lame” in Persian; hence the Europeanized form “Tamerlane”) was born in Kish (later Shahr-i Sabz), in Transoxiana, in c. 1328 as a member of the ruling family of the nomadic Turco-Mongol Barlas tribe in Transoxiana (now the southern part of Uzbekistan). Through a succession of alliances, in 1370 he effectively became ruler of the “Ulus Chaghadai,” the western part of the Central Asian territory bequeathed by Chinggis (Genghis) Khan to his second son and divided into two separate khanates since 1347–1348. As a commoner, Timur was debarred from sovereign rank. He governed in the name of a khan of Chinggisid descent and was styled simply Amir (or Great Amir) and also Güregen (“imperial son-in-law”) by virtue of his marriage to a Chinggisid princess, though later in life he appears to have claimed descent from one of Chinggis Khan’s ancestors. His principal residence was Samarkand, but he spent much of his life on campaign. His tireless military operations aimed at restoring the imperial Mongol order, which had lapsed since the mid-fourteenth century, and were directed against those who had usurped control in the Mongol dominions. Timur brought most of Iran, Iraq, and present-day Afghanistan under his authority, ravaged the lands of the Mongol Golden Horde in the southern Russian steppes, sacked Delhi, overran Syria, and defeated the Ottoman Sultan Bayezid at Ankara in 1402. At his death in 1405, he was poised to invade the Ming Empire in China, the only part of the formerly Mongol dominions that he had not attacked. Timur’s mixed reputation reflects the contradictions in his character that have long fascinated historians. His taste for the colossal found expression both in his appalling treatment of cities that refused to surrender and in the splendid buildings he left to posterity. Though probably illiterate, he spoke Persian as well as Turkish, evinced a strong interest in history, and enjoyed discussion with scholars. Albeit a Muslim who favored shaykhs and Sufis and whose campaigns against Christian Georgia and the Ming were portrayed as holy war, he devoted most of his energies to conflict with other Muslim potentates. His empire, founded on his personal authority, lacked strong institutional underpinnings, and his death inaugurated a conflict among his heirs, who were unable to preserve his empire in its entirety. Nevertheless, members of the Timurid dynasty ruled over Transoxiana until 1500 and eastern Iran until 1507, and in 1526 another descendant, Babur, founded the Mughal Empire in India.
Enzyme redesign and genetic code expansion
Authors: Opuu Vaitea , Simonson Thomas 
Published: October 2023

Abstract
Enzyme design is an important application of computational protein design (CPD). It can benefit enormously from the additional chemistries provided by noncanonical amino acids (ncAAs). These can be incorporated into an ‘expanded’ genetic code, and introduced in vivo into target proteins. The key step for genetic code expansion is to engineer an aminoacyl-transfer RNA (tRNA) synthetase (aaRS) and an associated tRNA that handles the ncAA. Experimental directed evolution has been successfully used to engineer aaRSs and incorporate over 200 ncAAs into expanded codes. But directed evolution has severe limits, and is not yet applicable to noncanonical AA backbones. CPD can help address several of its limitations, and has begun to be applied to this problem. We review efforts to redesign aaRSs, studies that designed new proteins and functionalities with the help of ncAAs, and some of the method developments that have been used, such as adaptive landscape flattening Monte Carlo, which allows an enzyme to be redesigned with substrate or transition state binding as the design target.
Polyurethane scaffold-based 3D lung cancer model recapitulates in vivo tumor biological behavior for nanoparticulate drug screening
Authors: Sun Lu , Wang Xiaofei , He Yushui , Chen Boran , Shan Baoyin , Yang Jinlong , Wang Ruoran , Zeng Xihang , Li Jiehua , Tan Hong , Liang Ruichao 
Published: October 2023

Abstract
Lung cancer is the leading cause of cancer mortality worldwide. Preclinical studies in lung cancer hold the promise of screening for effective antitumor agents, but mechanistic studies and drug discovery based on 2D cell models have a high failure rate in getting to the clinic. Thus, there is an urgent need to explore more reliable and effective in vitro lung cancer models. Here, we prepared a series of three-dimensional (3D) waterborne biodegradable polyurethane (WBPU) scaffolds as substrates to establish biomimetic tumor models in vitro. These 3D WBPU scaffolds were porous and could absorb large amounts of free water, facilitating the exchange of substances (nutrients and metabolic waste) and cell growth. The scaffolds at wet state could simulate the mechanics (elastic modulus ∼1.9 kPa) and morphology (porous structures) of lung tissue and exhibit good biocompatibility. A549 lung cancer cells showed adherent growth pattern and rapidly formed 3D spheroids on WBPU scaffolds. Our results showed that the scaffold-based 3D lung cancer model promoted the expression of anti-apoptotic and epithelial–mesenchymal transition-related genes, giving it a more moderate growth and adhesion pattern compared to 2D cells. In addition, WBPU scaffold-established 3D lung cancer model revealed a closer expression of proteins to in vivo tumor, including tumor stem cell markers, cell proliferation, apoptosis, invasion and tumor resistance proteins. Based on these features, we further demonstrated that the 3D lung cancer model established by the WBPU scaffold was very similar to the in vivo tumor in terms of both resistance and tolerance to nanoparticulate drugs. Taken together, WBPU scaffold-based lung cancer model could better mimic the growth, microenvironment and drug response of tumor in vivo. This emerging 3D culture system holds promise to shorten the formulation cycle of individualized treatments and reduce the use of animals while providing valid research data for clinical trials.
Akkermansia muciniphila promotes testosterone‐mediated hair growth inhibition in mice
Authors: Lee Eunyoung , Kim Daedong , Seo Hyo‐Deok , Hahm Jeong‐Hoon , Seo Jae‐Gu , Lee Sang‐Nam , Kim Do‐Hak , Ahn Jiyun , Jung Chang Hwa 
Published: October 2023

AbstractThe beneficial effects of Akkermansia muciniphila (Akk) on gut health and inflammation reduction have been demonstrated; however, scientific evidence of hair growth enhancement by Akk has not been reported. Therefore, this study was undertaken to investigate the effect of Akk on improving testosterone‐mediated hair growth inhibition. Hair growth inhibition was induced through subcutaneous injection of testosterone into the shaved dorsal skin of C57BL/6 male mice. Live and pasteurized Akk were orally administered at a concentration of 1 × 108 colony‐forming unit. After 5 weeks, hair length and skin tissues were analyzed. The live and pasteurized Akk significantly stimulated hair growth, countering the inhibitory effect of testosterone compared to the testosterone‐alone group. Hematoxylin and eosin staining revealed a significant increase in hair follicle size in the Akk‐treated group. An increase in β‐catenin levels, which are associated with hair growth and cell cycle progression, was also observed. Moreover, the Akk‐treated group exhibited increased levels of fibroblast growth factors, including Fgf7, Igf1, Fgf7, Fgf10, and Fgf21. However, no significant difference was observed between the live and pasteurized Akk groups. These results underscore the potential of live and pasteurized Akk in improving testosterone‐mediated hair growth inhibition.
Decision-making in anesthesiology: will artificial intelligence make intraoperative care safer?
Authors: Duran Huong-Tram , Kingeter Meredith , Reale Carrie , Weinger Matthew B. , Salwei Megan E. 
Published: October 2023

Purpose of review
This article explores the impact of recent applications of artificial intelligence on clinical anesthesiologists’ decision-making.

Recent findings
Naturalistic decision-making, a rich research field that aims to understand how cognitive work is accomplished in complex environments, provides insight into anesthesiologists’ decision processes. Due to the complexity of clinical work and limits of human decision-making (e.g. fatigue, distraction, and cognitive biases), attention on the role of artificial intelligence to support anesthesiologists’ decision-making has grown. Artificial intelligence, a computer's ability to perform human-like cognitive functions, is increasingly used in anesthesiology. Examples include aiding in the prediction of intraoperative hypotension and postoperative complications, as well as enhancing structure localization for regional and neuraxial anesthesia through artificial intelligence integration with ultrasound.

Summary
To fully realize the benefits of artificial intelligence in anesthesiology, several important considerations must be addressed, including its usability and workflow integration, appropriate level of trust placed on artificial intelligence, its impact on decision-making, the potential de-skilling of practitioners, and issues of accountability. Further research is needed to enhance anesthesiologists’ clinical decision-making in collaboration with artificial intelligence.
Immune checkpoint inhibitors as adjuvant therapy in patients with completely resected nonsmall cell lung cancer
Authors: Pirker Robert 
Published: October 2023

Purpose of review
The purpose of the review is to summarize the current status of immune checkpoint inhibitors as adjuvant therapy in patients with resected nonsmall cell lung cancer (NSCLC).

Recent findings
The IMpower010 phase 3 trial demonstrated improved disease-free survival and, in case of PD-L1 at least 50%, also improved overall survival for atezolizumab compared to best supportive care among patients with completely resected stage II-IIIA NSCLC. The PEARLS/KEYNOTE-091 trial showed increased disease-free survival for pembrolizumab among patients with stage IB-IIIA NSCLC. Trials with nivolumab and durvalumab are ongoing.

Summary
Atezolizumab or pembrolizumab have become options for adjuvant therapy in patients with completely resected NSCLC.