bluuebunny/crossref_metadata_2025_split huggingface dataset:
Prognostic nomogram and risk factors for predicting survival in patients with pT2N0M0 esophageal squamous carcinoma
Authors: Kang Mei , Wang Yichun , Yang Mingwei , Wang Xiumei , Zhu Liyang , Zhang Mei 
Published: March 2023

AbstractThis study analyzed the impact of factors affecting overall survival in patients with pT2N0M0 esophageal squamous carcinoma (ESCC) and developed a nomogram to predict overall survival (OS). We reviewed the clinical data of 413 patients with pathological T2N0M0 ESCC after radical esophagectomy in two hospitals. Data from one institution was used as the training cohort. A nomogram was established using Cox proportional hazard regression for identifying the prognostic factors affecting for OS in ESCC patients. The area under the curve (AUC), calibration curves and decision curve analysis (DCA) were used to evaluate prognostic efficacy, which was validated in an independent validation cohort. In the training cohort (N = 304), the median OS was 69.33 months, and the 3-, 5- and 10-year OS rates were 76.80%, 67.00% and 56.90%, respectively. The median OS of the validation cohort (N = 109) was 73.50 months, and the 3-, 5- and 10-year OS rates were 77.00%, 67.80% and 55.60%, respectively. According to Cox univariate and multivariate analyses, sex, age, tumor length and the number of resected lymph nodes were identified as predictors of OS. We developed nomograms and performed internal and external validation. The time-dependent receiver operating characteristic (ROC) curve and area under the curve (AUC) value, calibration curve and decision curve analysis (DCA) showed good prediction ability of the nomogram. The developed nomogram can effectively predict OS after esophagectomy in patients with pT2N0M0 ESCC.
Machine learning for accurate estimation of fetal gestational age based on ultrasound images
Authors: Lee Lok Hin , Bradburn Elizabeth , Craik Rachel , Yaqub Mohammad , Norris Shane A. , Ismail Leila Cheikh , Ohuma Eric O. , Barros Fernando C. , Lambert Ann , Carvalho Maria , Jaffer Yasmin A. , Gravett Michael , Purwar Manorama , Wu Qingqing , Bertino Enrico , Munim Shama , Min Aung Myat , Bhutta Zulfiqar , Villar Jose , Kennedy Stephen H. , Noble J. Alison , Papageorghiou Aris T. 
Published: March 2023

AbstractAccurate estimation of gestational age is an essential component of good obstetric care and informs clinical decision-making throughout pregnancy. As the date of the last menstrual period is often unknown or uncertain, ultrasound measurement of fetal size is currently the best method for estimating gestational age. The calculation assumes an average fetal size at each gestational age. The method is accurate in the first trimester, but less so in the second and third trimesters as growth deviates from the average and variation in fetal size increases. Consequently, fetal ultrasound late in pregnancy has a wide margin of error of at least ±2 weeks’ gestation. Here, we utilise state-of-the-art machine learning methods to estimate gestational age using only image analysis of standard ultrasound planes, without any measurement information. The machine learning model is based on ultrasound images from two independent datasets: one for training and internal validation, and another for external validation. During validation, the model was blinded to the ground truth of gestational age (based on a reliable last menstrual period date and confirmatory first-trimester fetal crown rump length). We show that this approach compensates for increases in size variation and is even accurate in cases of intrauterine growth restriction. Our best machine-learning based model estimates gestational age with a mean absolute error of 3.0 (95% CI, 2.9–3.2) and 4.3 (95% CI, 4.1–4.5) days in the second and third trimesters, respectively, which outperforms current ultrasound-based clinical biometry at these gestational ages. Our method for dating the pregnancy in the second and third trimesters is, therefore, more accurate than published methods.
Enabling fully automated insulin delivery through meal detection and size estimation using Artificial Intelligence
Authors: Mosquera-Lopez Clara , Wilson Leah M. , El Youssef Joseph , Hilts Wade , Leitschuh Joseph , Branigan Deborah , Gabo Virginia , Eom Jae H. , Castle Jessica R. , Jacobs Peter G. 
Published: March 2023

AbstractWe present a robust insulin delivery system that includes automated meal detection and carbohydrate content estimation using machine learning for meal insulin dosing called robust artificial pancreas (RAP). We conducted a randomized, single-center crossover trial to compare postprandial glucose control in the four hours following unannounced meals using a hybrid model predictive control (MPC) algorithm and the RAP system. The RAP system includes a neural network model to automatically detect meals and deliver a recommended meal insulin dose. The meal detection algorithm has a sensitivity of 83.3%, false discovery rate of 16.6%, and mean detection time of 25.9 minutes. While there is no significant difference in incremental area under the curve of glucose, RAP significantly reduces time above range (glucose >180 mg/dL) by 10.8% (P = 0.04) and trends toward increasing time in range (70–180 mg/dL) by 9.1% compared with MPC. Time below range (glucose <70 mg/dL) is not significantly different between RAP and MPC.
Application of smart devices in investigating the effects of air pollution on atrial fibrillation onset
Authors: Liu Cong , Tai Meihui , Hu Jialu , Zhu Xinlei , Wang Weidong , Guo Yutao , Kan Haidong , Chen Renjie 
Published: March 2023

AbstractFew studies have examined the link between short-term exposure to air pollutants and atrial fibrillation (AF) episodes. This study aims to examine the association of hourly criteria air pollutants with AF episodes. We employ a smart device-based photoplethysmography technology to screen AF from 2018 to 2021. Hourly concentrations of six criteria air pollutants are matched to the onset hour of AF for each participant. We adopt a time-stratified case-crossover design to capture the acute effects of air pollutants on AF episodes, using conditional logistic regression models. Subgroup analyses are conducted by age, gender, and season. A total of 11,906 episodes of AF are identified in 2976 participants from 288 Chinese cities. Generally, the strongest associations of air pollutants are present at lag 18–24 h, with positive and linear exposure-response relationships. For an interquartile range increase in inhalable particles, fine particles, nitrogen dioxide, and carbon monoxide, the odds ratio (OR) of AF is 1.19 [95% confidential interval (CI): 1.03, 1.37], 1.38 (95%CI: 1.14, 1.67), 1.60 (95%CI: 1.16, 2.20) and 1.48 (95%CI: 1.19, 1.84), respectively. The estimates are robust to the adjustment of co-pollutants, and they are larger in females, older people, and in cold seasons. There are insignificant associations for sulfur dioxide and ozone. This nationwide case-crossover study demonstrates robust evidence of significant associations between hourly exposure to air pollutants and the onset of AF episodes, which underscores the importance of ongoing efforts to further improve air quality as an effective target for AF prevention.
Intermittent antibiotic treatment of bacterial biofilms favors the rapid evolution of resistance
Authors: Usui Masaru , Yoshii Yutaka , Thiriet-Rupert Stanislas , Ghigo Jean-Marc , Beloin Christophe 
Published: March 2023

AbstractBacterial antibiotic resistance is a global health concern of increasing importance and intensive study. Although biofilms are a common source of infections in clinical settings, little is known about the development of antibiotic resistance within biofilms. Here, we use experimental evolution to compare selection of resistance mutations in planktonic and biofilm Escherichia coli populations exposed to clinically relevant cycles of lethal treatment with the aminoglycoside amikacin. Consistently, mutations in sbmA, encoding an inner membrane peptide transporter, and fusA, encoding the essential elongation factor G, are rapidly selected in biofilms, but not in planktonic cells. This is due to a combination of enhanced mutation rate, increased adhesion capacity and protective biofilm-associated tolerance. These results show that the biofilm environment favors rapid evolution of resistance and provide new insights into the dynamic evolution of antibiotic resistance in biofilms.
Setd2 inactivation sensitizes lung adenocarcinoma to inhibitors of oxidative respiration and mTORC1 signaling
Authors: Walter David M. , Gladstein Amy C. , Doerig Katherine R. , Natesan Ramakrishnan , Baskaran Saravana G. , Gudiel A. Andrea , Adler Keren M. , Acosta Jonuelle O. , Wallace Douglas C. , Asangani Irfan A. , Feldser David M. 
Published: March 2023

AbstractSETD2 is a tumor suppressor that is frequently inactivated in several cancer types. The mechanisms through which SETD2 inactivation promotes cancer are unclear, and whether targetable vulnerabilities exist in these tumors is unknown. Here we identify heightened mTORC1-associated gene expression programs and functionally higher levels of oxidative metabolism and protein synthesis as prominent consequences of Setd2 inactivation in KRAS-driven mouse models of lung adenocarcinoma. Blocking oxidative respiration and mTORC1 signaling abrogates the high rates of tumor cell proliferation and tumor growth specifically in SETD2-deficient tumors. Our data nominate SETD2 deficiency as a functional marker of sensitivity to clinically actionable therapeutics targeting oxidative respiration and mTORC1 signaling.
Anterior cingulate and medial prefrontal cortex oscillations underlie learning alterations in trait anxiety in humans
Authors: Hein Thomas P. , Gong Zheng , Ivanova Marina , Fedele Tommaso , Nikulin Vadim , Herrojo Ruiz Maria 
Published: March 2023

AbstractAnxiety has been linked to altered belief formation and uncertainty estimation, impacting learning. Identifying the neural processes underlying these changes is important for understanding brain pathology. Here, we show that oscillatory activity in the medial prefrontal, anterior cingulate and orbitofrontal cortex (mPFC, ACC, OFC) explains anxiety-related learning alterations. In a magnetoencephalography experiment, two groups of human participants pre-screened with high and low trait anxiety (HTA, LTA: 39) performed a probabilistic reward-based learning task. HTA undermined learning through an overestimation of volatility, leading to faster belief updating, more stochastic decisions and pronounced lose-shift tendencies. On a neural level, we observed increased gamma activity in the ACC, dmPFC, and OFC during encoding of precision-weighted prediction errors in HTA, accompanied by suppressed ACC alpha/beta activity. Our findings support the association between altered learning and belief updating in anxiety and changes in gamma and alpha/beta activity in the ACC, dmPFC, and OFC.
CD83 expression characterizes precursor exhausted T cell population
Authors: Wu Zhiwen , Yoshikawa Toshiaki , Inoue Satoshi , Ito Yusuke , Kasuya Hitomi , Nakashima Takahiro , Zhang Haosong , Kotaka Saki , Hosoda Waki , Suzuki Shiro , Kagoya Yuki 
Published: March 2023

AbstractT cell exhaustion is a main obstacle against effective cancer immunotherapy. Exhausted T cells include a subpopulation that maintains proliferative capacity, referred to as precursor exhausted T cells (TPEX). While functionally distinct and important for antitumor immunity, TPEX possess some overlapping phenotypic features with the other T-cell subsets within the heterogeneous tumor-infiltrating T-lymphocytes (TIL). Here we explore surface marker profiles unique to TPEX using the tumor models treated by chimeric antigen receptor (CAR)-engineered T cells. We find that CD83 is predominantly expressed in the CCR7+PD1+ intratumoral CAR-T cells compared with the CCR7-PD1+ (terminally differentiated) and CAR-negative (bystander) T cells. The CD83+CCR7+ CAR-T cells exhibit superior antigen-induced proliferation and IL-2 production compared with the CD83- T cells. Moreover, we confirm selective expression of CD83 in the CCR7+PD1+ T-cell population in primary TIL samples. Our findings identify CD83 as a marker to discriminate TPEX from terminally exhausted and bystander TIL.
Acetate attenuates hyperoxaluria-induced kidney injury by inhibiting macrophage infiltration via the miR-493-3p/MIF axis
Authors: Zhu Wei , Wu Chengjie , Zhou Zhen , Zhang Guangyuan , Luo Lianmin , Liu Yang , Huang Zhicong , Ai Guoyao , Zhao Zhijian , Zhong Wen , Liu Yongda , Zeng Guohua 
Published: March 2023

AbstractHyperoxaluria is well known to cause renal injury and end-stage kidney disease. Previous studies suggested that acetate treatment may improve the renal function in hyperoxaluria rat model. However, its underlying mechanisms remain largely unknown. Using an ethylene glycol (EG)-induced hyperoxaluria rat model, we find the oral administration of 5% acetate reduced the elevated serum creatinine, urea, and protected against hyperoxaluria-induced renal injury and fibrosis with less infiltrated macrophages in the kidney. Treatment of acetate in renal tubular epithelial cells in vitro decrease the macrophages recruitment which might have reduced the oxalate-induced renal tubular cells injury. Mechanism dissection suggests that acetate enhanced acetylation of Histone H3 in renal tubular cells and promoted expression of miR-493-3p by increasing H3K9 and H3K27 acetylation at its promoter region. The miR-493-3p can suppress the expression of macrophage migration inhibitory factor (MIF), thus inhibiting the macrophages recruitment and reduced oxalate-induced renal tubular cells injury. Importantly, results from the in vivo rat model also demonstrate that the effects of acetate against renal injury were weakened after blocking the miR-493-3p by antagomir treatment. Together, these results suggest that acetate treatment ameliorates the hyperoxaluria-induced renal injury via inhibiting macrophages infiltration with change of the miR-493-3p/MIF signals. Acetate could be a new therapeutic approach for the treatment of oxalate nephropathy.
LncRNA-MIAT activates hepatic stellate cells via regulating Hippo pathway and epithelial-to-mesenchymal transition
Authors: Zhan Yating , Tao Qiqi , Meng Qishan , Zhang Rongrong , Lin Lifan , Li Xinmiao , Zheng Lei , Zheng Jianjian 
Published: March 2023

AbstractLong non-coding RNA-myocardial infarction-associated transcript (lncRNA-MIAT) has been reported to play an important role in the development of multiple cancers. However, the biological roles of MIAT in liver fibrosis are still unknown. In this study, the expression of MIAT is up-regulated during liver fibrosis. Silencing MIAT leads to the suppression of hepatic stellate cell (HSC) proliferation and collagen expression. Double immunofluorescence analysis additionally demonstrates that MIAT inhibition leads to the suppression of type I collagen and α-SMA in vitro. In vivo, MIAT knockdown contributes to the inhibition of fibrosis progression and collagen accumulation. MIAT is confirmed as a target of miR-3085-5p, and the co-location of MIAT and miR-3085-5p is found in HSC cytoplasm. Interestingly, there is a negative correlation between MIAT expression and miR-3085-5p level in cirrhotic patients as well as activated HSCs. In addition, the effects of MIAT inhibition on HSC inactivation are blocked down by miR-3085-5p inhibitor. YAP is a target of miR-3085-5p. Reduced YAP caused by loss of MIAT is reversed by miR-3085-5p inhibitor. Notably, YAP knockdown results in the suppression of MIAT-mediated epithelial-to-mesenchymal transition (EMT) process. In conclusion, we demonstrate that MIAT enhances the activation of HSCs, at least in part, via miR-3085-5p/YAP/EMT signaling pathway.
Analysis of well-annotated next-generation sequencing data reveals increasing cases of SARS-CoV-2 reinfection with Omicron
Authors: Burkholz Scott , Rubsamen Michael , Blankenberg Luke , Carback Richard T. , Mochly-Rosen Daria , Harris Paul E. 
Published: March 2023

AbstractSARS-CoV-2 has extensively mutated creating variants of concern (VOC) resulting in global infection surges. The Omicron VOC reinfects individuals exposed to earlier variants of SARS-CoV-2 at a higher frequency than previously seen for non-Omicron VOC. An analysis of the sub-lineages associated with an Omicron primary infection and Omicron reinfection reveals that the incidence of Omicron-Omicron reinfections is occurring over a shorter time interval than seen after a primary infection with a non-Omicron VOC. Our analysis suggests that a single infection from SARS-CoV-2 may not generate the protective immunity required to defend against reinfections from emerging Omicron lineages. This analysis was made possible by Next-generation sequencing (NGS) of a Danish cohort with clinical metadata on both infections occurring in the same individual. We suggest that the continuation of COVID-19 NGS and inclusion of clinical metadata is necessary to ensure effective surveillance of SARS-CoV-2 genomics, assist in treatment and vaccine development, and guide public health recommendations.
Tunning the tilt of the Dirac cone by atomic manipulations in 8Pmmn borophene
Authors: Yekta Yasin , Hadipour Hanif , Jafari Seyed Akbar 
Published: March 2023

AbstractTwo dimensional quantum materials possessing Dirac cones in their spectrum are fascinating due to their emergent low-energy Dirac fermions. In 8Pmmn borophene the Dirac cone is furthermore tilted, which is a proxy for spacetime geometry, since the future light-cone depends on the underlying metric. Therefore it is important to understand the microscopic origin of the tilt. Here, based on ab-initio calculations, we decipher the atomistic mechanism of the formation of tilt. First, nearest-neighbor hopping on a buckled honeycomb lattice forms an upright Dirac cone. Then, the difference in the renormalized anisotropic second-neighbor hopping, formed by virtual hoppings on one-dimensional chains of atoms, tilts the Dirac cone. We construct an accurate tight-binding model on honeycomb graph for analytical investigation, and we find that substitution of certain boron atoms by carbon provides a way to change the tilt of the cone.
Development and challenges in perovskite scintillators for high-resolution imaging and timing applications
Authors: Wibowo Arie , Sheikh Md Abdul Kuddus , Diguna Lina Jaya , Ananda Muhammad Bagas , Marsudi Maradhana Agung , Arramel Arramel , Zeng Shuwen , Wong Liang Jie , Birowosuto Muhammad Danang 
Published: March 2023

AbstractInorganic scintillators play a major role in ionizing radiation detection due to their high versatility to detect multiple radiation sources such as X-rays, gamma-rays, alpha, beta, and neutron particles, and their fast and high light yield, making them especially convenient for imaging, spectroscopy, and timing applications. Scintillators-based detection systems are found, among various applications, in medical imaging, homeland security, high-energy physics, industrial control, oil drilling explorations, and energy management. This Review discusses advances and prospects of perovskite scintillators, particularly low-dimensional hybrid organic-inorganic perovskite crystals and all-inorganic perovskite nanocrystals. We highlight the promise of two-dimensional lithium-doped (PEA)2PbBr4 crystals and CsPbBr3 nanocrystals as scintillators with high light yields, exceeding 20 photons/keV, and fast decay times of less than 15 ns. Such a combination may result in fast-spectral X-ray imaging, an output count rate exceeding 30 Mcps/pixel in photon-counting computed tomography, and coincidence timing resolution of less than 100 ps in positron emission tomography. We review recent strategies to further improve light yield, decay time, and coincidence timing resolution through light-matter interactions such as extraction efficiency enhancement and Purcell-enhanced scintillators. These advancements in light yields and decay times of perovskite scintillators will be particularly useful in the medical and security applications.
Routes to reduction of phosphate by high-energy events
Authors: Bindi Luca , Feng Tian , Pasek Matthew A. 
Published: March 2023

AbstractPhosphate minerals such as those in the apatite group tend to be the dominant forms of phosphorus in minerals on the Earth’s surface. Phosphate can be reduced to phosphides during high-energy events, such as lightning and impacts. Here we show that, in addition to formation of metal phosphides, a new compound was formed by lightning in a fulgurite from New Port Richey, Florida, USA. A calcium phosphite material, ideally CaHPO3, was found in spherules mainly consisting of iron silicides that formed by lightning-induced fusion of sand around a tree root. This phosphite material bears a phosphorus oxidation state intermediate of that of phosphides and phosphates in a geologic sample and implicates phosphites as being potentially relevant to other high-energy events where phosphorus may partially change its redox state, and material similar to this phosphite may also be the source of phosphite that makes up part of the phosphorus biogeochemical cycle.
Andean headwater and piedmont streams are hot spots of carbon dioxide and methane emissions in the Amazon basin
Authors: Chiriboga Gonzalo , Borges Alberto V. 
Published: March 2023

AbstractRivers substantially contribute to global greenhouse gas emissions, yet emissions from headwater streams are poorly constrained. Here, we report dissolved concentrations of carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) in Andean headwater and piedmont streams in the Napo River basin in Ecuador, part of the Amazon River catchment. Concentrations increased exponentially with elevation decrease between 3990 and 175 m above sea level. Concentration changes scaled with catchment slope, and were attributed to variations in gas transfer velocity, forest cover, inundation extent, and water temperature. We estimate river emissions across the whole Amazon basin using existing data for the lowland Central Amazon. We find that Andean mountainous headwater and piedmont streams are hotspots of CO2 and CH4 emission, with respective areal fluxes being 1.7 and 4.5 higher in headwater streams, and 1.2 and 6.6 higher in piedmont streams than in lowland streams. Together, Andean mountainous headwater and piedmont streams and rivers represented 35% CO2 and 72% CH4 of basin scale integrated fluvial diffusive emissions. Conversely, N2O emissions from headwater and piedmont streams were low compared to lowland streams.