Extremely preterm infants born outside a provincial tertiary perinatal center and transferred postnatally associated with poor outcomes: a real-world observational study

IntroductionExtremely preterm infants (EPIs) have high morbidity and mortality, and are recommended to be born in a tertiary perinatal center (inborn). However, many EPIs in central China are born in lower-level hospitals and transferred postnatally, the outcomes of which remain to be investigated.MethodsEPIs admitted to the Department of Neonatology, Maternal and Child Health Hospital of Hubei Province from January 2013 to December 2022 were retrospectively recruited and divided into the control (inborn) and transfer groups (born in other hospitals). The neonatal and maternal characteristics, neonatal outcomes, and the treatment of survival EPIs were analyzed.ResultsA total of 174 and 109 EPIs were recruited in the control and transfer groups, respectively. EPIs in the transfer group have a higher birth weight and a lower proportion of multiple pregnancies than the control group (all P < 0.05). The proportions of antenatal steroids, magnesium sulfate, cesarean delivery, premature rupture of membranes ≥18 h, gestational diabetes, and amniotic fluid abnormalities were lower in the transfer group (all P < 0.05). Survival rates (64.22% vs. 56.32%), proportions of severe periventricular-intraventricular hemorrhage (PIVH) (11.93% vs. 11.49%), severe bronchopulmonary dysplasia (sBPD) (21.05% vs. 20%), and severe retinopathy of prematurity (ROP) (24.77% vs. 20.11%) were similar in the transfer and control groups (all P > 0.05). However, the transfer group had higher proportions of severe birth asphyxia (34.86% vs. 13.22%, P < 0.001), PIVH (42.20% vs. 29.89%, P = 0.034), and extrauterine growth retardation (EUGR) (17.43% vs. 6.32%, P = 0.003). Less surfactant utilization was found in the transfer group among survival EPIs (70.00% vs. 93.88%, P < 0.001).ConclusionEPIs born outside a tertiary perinatal center and transferred postnatally did not have significantly higher mortality and rates of severe complications (severe PIVH, severe ROP, and sBPD), but there may be an increased risk of severe asphyxia, PIVH and EUGR. This may be due to differences in maternal and neonatal characteristics and management. Further follow-up is needed to compare neurodevelopmental outcomes, and it is recommended to transfer the EPIs in utero to reduce the risk of poor physical and neurological development

The Next-Generation Surgical Robots

The chronicle of surgical robots is short but remarkable. Within 20 years since the regulatory approval of the first surgical robot, more than 3,000 units were installed worldwide, and more than half a million robotic surgical procedures were carried out in the past year alone. The exceptionally high speeds of market penetration and expansion to new surgical areas had raised technical, clinical, and ethical concerns. However, from a technological perspective, surgical robots today are far from perfect, with a list of improvements expected for the next-generation systems. On the other hand, robotic technologies are flourishing at ever-faster paces. Without the inherent conservation and safety requirements in medicine, general robotic research could be substantially more agile and explorative. As a result, various technical innovations in robotics developed in recent years could potentially be grafted into surgical applications and ignite the next major advancement in robotic surgery. In this article, the current generation of surgical robots is reviewed from a technological point of view, including three of possibly the most debated technical topics in surgical robotics: vision, haptics, and accessibility. Further to that, several emerging robotic technologies are highlighted for their potential applications in next-generation robotic surgery

A multiple-time-scale comparative study for the added value of magnetic resonance imaging-based radiomics in predicting pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer

ObjectiveRadiomics based on magnetic resonance imaging (MRI) shows potential for prediction of therapeutic effect to neoadjuvant chemoradiotherapy (nCRT) in locally advanced rectal cancer (LARC); however, thorough comparison between radiomics and traditional models is deficient. We aimed to construct multiple-time-scale (pretreatment, posttreatment, and combined) radiomic models to predict pathological complete response (pCR) and compare their utility to those of traditional clinical models.MethodsIn this research, 165 LARC patients undergoing nCRT followed by surgery were enrolled retrospectively, which were divided into training and testing sets in the ratio of 7:3. Morphological features on pre- and posttreatment MRI, coupled with clinical data, were evaluated by univariable and multivariable logistic regression analysis for constructing clinical models. Radiomic parameters were derived from pre- and posttreatment T2- and diffusion-weighted images to develop the radiomic signatures. The clinical-radiomics models were then generated. All the models were developed in the training set and then tested in the testing set, the performance of which was assessed using the area under the receiver operating characteristic curve (AUC). Radiomic models were compared with the clinical models with the DeLong test.ResultsOne hundred and sixty-five patients (median age, 55 years; age interquartile range, 47–62 years; 116 males) were enrolled in the study. The pretreatment maximum tumor length, posttreatment maximum tumor length, and magnetic resonance tumor regression grade were selected as independent predictors for pCR in the clinical models. In the testing set, the pre- and posttreatment and combined clinical models generated AUCs of 0.625, 0.842, and 0.842 for predicting pCR, respectively. The MRI-based radiomic models performed reasonably well in predicting pCR, but neither the pure radiomic signatures (AUCs, 0.734, 0.817, and 0.801 for the pre- and posttreatment and combined radiomic signatures, respectively) nor the clinical-radiomics models (AUCs, 0.734, 0.860, and 0.801 for the pre- and posttreatment and combined clinical-radiomics models, respectively) showed significant added value compared with the clinical models (all P > 0.05).ConclusionThe MRI-based radiomic models exhibited no definite added value compared with the clinical models for predicting pCR in LARC. Radiomic models can serve as ancillary tools for tailoring adequate treatment strategies

Cell-Type Specific Distribution of T-Type Calcium Currents in Lamina II Neurons of the Rat Spinal Cord

Spinal lamina II (substantia gelatinosa, SG) neurons integrate nociceptive information from the primary afferents and are classified according to electrophysiological (tonic firing, delayed firing, single spike, initial burst, phasic firing, gap firing and reluctant firing) or morphological (islet, central, vertical, radial and unclassified) criteria. T-type calcium (Cav3) channels play an essential role in the central mechanism of pathological pain, but the electrophysiological properties and the cell-type specific distribution of T-type channels in SG neurons have not been fully elucidated. To investigate the electrophysiological and morphological features of T-type channel-expressing or -lacking neurons, voltage- and current-clamp recordings were performed on either transverse or parasagittal spinal cord slices. Recording made in transverse spinal cord slices showed that an inward current (IT) was observed in 44.5% of the SG neurons that was fully blocked by Ni2+ and TTA-A2. The amplitude of IT depended on the magnitude and the duration of hyperpolarization pre-pulse. The voltage for eliciting and maximizing IT were −70 mV and −35 mV, respectively. In addition, we found that most of the IT-expressing neurons are tonic firing neurons and exhibit more negative action potential (AP) threshold and smaller difference of AP threshold and resting membrane potential (RMP) than those neurons lacking IT. Consistently, a specific T-type calcium channel blocker TTA-P2 increased the AP threshold and enlarged the difference between AP threshold and membrane potential (Ihold = 0). Meanwhile, the morphological analysis indicated that most of the IT-expressing neurons are islet neurons. In conclusion, we identify a cell-type specific distribution and the function of T-type channels in SG neurons. These findings might provide new insights into the mechanisms underlying the contribution of T-type channels in sensory transmission

Modified Carbon Fiber Paper-Based Electrodes Wrapped by Conducting Polymers with Enhanced Electrochemical Performance for Supercapacitors

An easy approach to fabricating carbon fiber paper (CFP) based electrodes has been developed. This method can be mainly divided into two steps, for which the mixture of cellulose nanofibers (CNFs) and carbon nanotubes (CNTs) was first deposited on the surface of carbon fiber paper through a vacuum filtration device followed by immersing the hybrid paper into concentrated aniline solution to polymerize polyaniline (PANI). Compared to carbon fiber paper, the acid-treated carbon fiber paper (A-CFP)-based electrode provides more active sites, which are beneficial for the polymerization of polyaniline. The mixture of CNFs and CNTs could coat on the A-CFP by vacuum-filtration due to the high hydrophilicity of A-CFP improved by acid-treatment. PANI with different polymerization time was in-situ synthesized on the surface of the hybrid paper to form a three-dimensional cross-linked structure that greatly enhanced the electrochemical performance of the electrode by improving high capacitance, high rate-capability, and long cycle-life. Moreover, the assembled symmetrical supercapacitor showed a high area capacitance of 626 mF·cm−2 and an energy density of 87 µWh·cm−2. This facile, easy performed, and low-cost strategy may provide a feasible method for the production of supercapacitor electrodes

Ultralight super-hydrophobic carbon aerogels based on cellulose nanofibers/poly(vinyl alcohol)/graphene oxide (CNFs/PVA/GO) for highly effective oil–water separation

With the worsening of the oil-product pollution problem, oil–water separation has attracted increased attention in recent years. In this study, a porous three-dimensional (3D) carbon aerogel based on cellulose nanofibers (CNFs), poly(vinyl alcohol) (PVA) and graphene oxide (GO) was synthesized by a facile and green approach. The resulting CNF/PVA/GO aerogels were synthesized through an environmentally friendly freeze-drying process and then carbonized to yield CNF/PVA/GO carbon aerogels with low density (18.41 mg cm−3), high porosity (98.98%), a water contact angle of 156° (super-hydrophobic) and high oil absorption capacity (97 times its own weight). The carbonization treatment of the CNF/PVA/GO aerogel not only improved the hydrophobic properties but also enhanced the adsorption capacity and specific surface area. Given the many good performance characteristics and the facile preparation process of carbon aerogels, these materials are viable candidates for use in oil–water separation and environmental protection

A state of the art survey of data mining-based fraud detection and credit scoring

Credit risk has been a widespread and deep penetrating problem for centuries, but not until various credit derivatives and products were developed and novel technologies began radically changing the human society, have fraud detection, credit scoring and other risk management systems become so important not only to some specific firms, but to industries and governments worldwide. Frauds and unpredictable defaults cost billions of dollars each year, thus, forcing financial institutions to continuously improve their systems for loss reduction. In the past twenty years, amounts of studies have proposed the use of data mining techniques to detect frauds, score credits and manage risks, but issues such as data selection, algorithm design, and hyperparameter optimization affect the perceived ability of the proposed solutions and it is difficult for auditors and researchers to explore and figure out the highest level of general development in this area. In this survey we focus on a state of the art survey of recently developed data mining techniques for fraud detection and credit scoring. Several outstanding experiments are recorded and highlighted, and the corresponding techniques, which are mostly based on supervised learning algorithms, unsupervised learning algorithms, semisupervised algorithms, ensemble learning, transfer learning, or some hybrid ideas are explained and analysed. The goal of this paper is to provide a dense review of up-to-date techniques for fraud detection and credit scoring, a general analysis on the results achieved and upcoming challenges for further researches

A state of the art survey of data mining-based fraud detection and credit scoring

Credit risk has been a widespread and deep penetrating problem for centuries, but not until various credit derivatives and products were developed and novel technologies began radically changing the human society, have fraud detection, credit scoring and other risk management systems become so important not only to some specific firms, but to industries and governments worldwide. Frauds and unpredictable defaults cost billions of dollars each year, thus, forcing financial institutions to continuously improve their systems for loss reduction. In the past twenty years, amounts of studies have proposed the use of data mining techniques to detect frauds, score credits and manage risks, but issues such as data selection, algorithm design, and hyperparameter optimization affect the perceived ability of the proposed solutions and it is difficult for auditors and researchers to explore and figure out the highest level of general development in this area. In this survey we focus on a state of the art survey of recently developed data mining techniques for fraud detection and credit scoring. Several outstanding experiments are recorded and highlighted, and the corresponding techniques, which are mostly based on supervised learning algorithms, unsupervised learning algorithms, semisupervised algorithms, ensemble learning, transfer learning, or some hybrid ideas are explained and analysed. The goal of this paper is to provide a dense review of up-to-date techniques for fraud detection and credit scoring, a general analysis on the results achieved and upcoming challenges for further researches

Integrin β1 in Pancreatic Cancer: Expressions, Functions, and Clinical Implications

Pancreatic cancer (PC) is characterized by rapid progression and a high mortality rate. The current treatment is still based on surgical treatment, supplemented by radiotherapy and chemotherapy, and new methods of combining immune and molecular biological treatments are being explored. Despite this, the survival rate of PC patients is still very disappointing. Therefore, clarifying the molecular mechanism of PC pathogenesis and developing precisely targeted drugs are key to improving PC prognosis. As the most common β subunit of the integrin family, integrin β1 has been proved to be closely related to the vascular invasion, distant metastasis, and survival of PC patients, and treatment targeting integrin β1 in PC has gained initial success in animal models. In this review, we summarize the various signaling pathways by which integrins are involved in PC, focusing on the roles of integrin β1 in the malignant behaviors of PC. Additionally, recent studies regarding the feasibility of integrin β1 as a diagnostic and prognostic biomarker in PC are also discussed. Finally, we present the progress of several integrin β1-based clinical trials to highlight the potential of integrin β1 as a target for personalized therapy in PC