We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.
To save content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about saving content to .
To save content items to your Kindle, first ensure no-reply@cambridge.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
Advances in mobile apps, remote sensing, and big data have enabled remote monitoring of mental health conditions, but the cost-effectiveness is unknown. This study proposed a systematic framework integrating computational tools and decision-analytic modeling to assess cost-effectiveness and guide emerging monitoring technologies development.
Methods
Using a novel decision-analytic Markov-cohort model, we simulated chronic depression patients’ disease progression over 2 years, allowing treatment modifications at follow-up visits. The cost-effectiveness, from a payer’s viewpoint, of five monitoring strategies was evaluated for patients in low-, medium-, and high-risk groups: (i) remote monitoring technology scheduling follow-up visits upon detecting treatment change necessity; (ii) rule-based follow-up strategy assigning the next follow-up based on the patient’s current health state; and (iii–v) fixed frequency follow-up at two-month, four-month, and six-month intervals. Health outcomes (effects) were measured in quality-adjusted life-years (QALYs).
Results
Base case results showed that remote monitoring technology is cost-effective in the three risk groups under a willingness-to-pay (WTP) threshold of U.S. GDP per capita in year 2023. Full scenario analyses showed that, compared to rule-based follow-up, remote technology is 74 percent, 67 percent, and 74 percent cost-effective in the high-risk, medium-risk, and low-risk groups, respectively, and it is cost-effective especially if the treatment is effective and if remote monitoring is highly sensitive and specific.
Conclusions
Remote monitoring for chronic depression proves cost-effective and potentially cost-saving in the majority of simulated scenarios. This framework can assess emerging remote monitoring technologies and identify requirements for the technologies to be cost-effective in psychiatric and chronic care delivery.
Recent developments have indicated a potential association between tinnitus and COVID-19. The study aimed to understand tinnitus following COVID-19 by examining its severity, recovery prospects, and connection to other lasting COVID-19 effects. Involving 1331 former COVID-19 patients, the online survey assessed tinnitus severity, cognitive issues, and medical background. Of the participants, 27.9% reported tinnitus after infection. Findings showed that as tinnitus severity increased, the chances of natural recovery fell, with more individuals experiencing ongoing symptoms (p < 0.001). Those with the Grade II mild tinnitus (OR = 3.68; CI = 1.89–7.32; p = 0.002), Grade III tinnitus (OR = 3.70; CI = 1.94–7.22; p < 0.001), Grade IV (OR = 6.83; CI = 3.73–12.91; p < 0.001), and a history of tinnitus (OR = 1.96; CI = 1.08–3.64; p = 0.03) had poorer recovery outcomes. Grade IV cases were most common (33.2%), and severe tinnitus was strongly associated with the risk of developing long-term hearing loss, anxiety, and emotional disorders (p < 0.001). The study concludes that severe post-COVID tinnitus correlates with a worse prognosis and potential hearing loss, suggesting the need for attentive treatment and management of severe cases.
As a required sample preparation method for 14C graphite, the Zn-Fe reduction method has been widely used in various laboratories. However, there is still insufficient research to improve the efficiency of graphite synthesis, reduce modern carbon contamination, and test other condition methodologies at Guangxi Normal University (GXNU). In this work, the experimental parameters, such as the reduction temperature, reaction time, reagent dose, Fe powder pretreatment, and other factors, in the Zn-Fe flame sealing reduction method for 14C graphite samples were explored and determined. The background induced by the sample preparation process was (2.06 ± 0.55) × 10–15, while the 12C– beam current were better than 40μA. The results provide essential instructions for preparing 14C graphite of ∼1 mg at the GXNU lab and technical support for the development of 14C dating and tracing, contributing to biology and environmental science.
A new vacuum line to extract CO2 from carbonate and dissolved inorganic carbon (DIC) in water was established at Guangxi Normal University. The vacuum line consisted of two main components: a CO2 bubble circulation region and a CO2 purification collection region, both of which were made of quartz glass and metal pipelines. To validate its reliability, a series of carbonate samples were prepared using this system. The total recovery rate of CO2 extraction and graphitization exceeded 80%. Furthermore, the carbon content in calcium carbonate exhibited a linear relationship with the CO2 pressure within the system, demonstrating its stability and reliability. The system was also employed to prepare and analyze various samples, including calcium carbonate blanks, foraminiferal, shell, groundwater, and subsurface oil-water samples. The accelerator mass spectrometry (AMS) results indicated that the average beam current for 12C- in the samples exceeded 40 μA. Additionally, the contamination introduced during the liquid sample preparation process was approximately (1.77 ± 0.57) × 10−14. Overall, the graphitized preparation system for carbonate and DIC in water exhibited high efficiency and recovery, meeting the requirements for samples dating back to approximately 30,000 years.
This study aimed to assess how Bacillus subtilis and Enterococcus faecium co-fermented feed (FF) affects the antioxidant capacity, muscle fibre types and muscle lipid profiles of finishing pigs. In this study, a total of 144 Duroc × Berkshire × Jiaxing Black finishing pigs were randomly assigned into three groups with four replicates (twelve pigs per replication). The three treatments were a basal diet (0 % FF), basal diet + 5 % FF and basal diet + 10 % FF, respectively. The experiment lasted 38 d after 4 d of acclimation. The study revealed that 10 % FF significantly increased the activity of superoxide dismutase (SOD) and catalase (CAT) compared with 0 % FF group, with mRNA levels of up-regulated antioxidant-related genes (GPX1, SOD1, SOD2 and CAT) in 10 % FF group. 10 % FF also significantly up-regulated the percentage of slow-twitch fibre and the mRNA expression of MyHC I, MyHC IIa and MyHC IIx, and slow MyHC protein expression while reducing MyHC IIb mRNA expression. Lipidomics analysis showed that 5 % FF and 10 % FF altered lipid profiles in longissimus thoracis. 10 % FF particularly led to an increase in the percentage of TAG. The Pearson correlation analysis indicated that certain molecular markers such as phosphatidic acid (PA) (49:4), Hex2Cer (d50:6), cardiolipin (CL) (72:8) and phosphatidylcholine (PC) (33:0e) could be used to indicate the characteristics of muscle fibres and were closely related to meat quality. Together, our findings suggest that 10 % FF improved antioxidant capacity, enhanced slow-twitch fibre percentage and altered muscle lipid profiles in finishing pigs.
As nurse practitioners and physician assistants (APPs) become more prevalent in delivering pediatric care, their involvement in antimicrobial stewardship efforts increases in importance. This project aimed to create and assess the efficacy of a problem-based learning (PBL) approach to teaching APPs antimicrobial stewardship principles.
Methods:
A PBL education initiative was developed after communication with local APP leadership and focus group feedback. It was offered to all APPs associated with Lurie Children’s Hospital of Chicago. Participants completed a survey which assessed opinions on antimicrobial stewardship and included knowledge-based questions focused on antimicrobial stewardship. Prescriptions for skin and soft tissue infections associated with APPs were recorded via chart review before and after the education campaign.
Results:
Eighty APPs participated in the initial survey and teaching initiative with 44 filling out the 2-week follow-up and 29 filling out the 6-month follow-up. Subjective opinions of antimicrobial stewardship and comfort with basic principles of AS increased from pre-intervention. Correct responses to knowledge-based assessments increased from baseline after 2-week follow-up (p < 0.01) and were maintained at the 6-month follow-up (p = 0.03). Simple skin and soft tissue infection prescriptions for clindamycin went from 44.4% pre-intervention to 26.5% (p = 0.2) post-intervention.
Conclusions:
A PBL approach for APP education on antimicrobial stewardship can be effective in increasing knowledge and comfort with principles of antimicrobial stewardship. These changes are maintained in long-term follow-up. Changes in prescribing habits showed a strong trend towards recommended empiric therapy choice. Institutions should develop similar education campaigns for APPs.
This article aims to analyze the relationship between user characteristics on social networks and influenza.
Methods:
Three specific research questions are investigated: (1) we classify Weibo updates to recognize influenza-related information based on machine learning algorithms and propose a quantitative model for influenza susceptibility in social networks; (2) we adopt in-degree indicator from complex networks theory as social media status to verify its coefficient correlation with influenza susceptibility; (3) we also apply the LDA topic model to explore users’ physical condition from Weibo to further calculate its coefficient correlation with influenza susceptibility. From the perspective of social networking status, we analyze and extract influenza-related information from social media, with many advantages including efficiency, low cost, and real time.
Results:
We find a moderate negative correlation between the susceptibility of users to influenza and social network status, while there is a significant positive correlation between physical condition and susceptibility to influenza.
Conclusions:
Our findings reveal the laws behind the phenomenon of online disease transmission, and providing important evidence for analyzing, predicting, and preventing disease transmission. Also, this study provides theoretical and methodological underpinnings for further exploration and measurement of more factors associated with infection control and public health from social networks.
Compared with nitrogen and argon, helium is lighter and can better reduce the beam loss caused by angular scattering during beam transmission. The molecular dissociation cross-section in helium is high and stable at low energies, which makes helium the prevalent stripping gas in low-energy accelerator mass spectrometry (AMS). To study the stripping behavior of 14C ions in helium at low energies, the charge state distributions of carbon ion beams with −1, +1, +2, +3, and +4 charge states were measured at energies of 70–220 keV with a compact 14C-AMS at Guangxi Normal University (GXNU). The experimental data were used to analyze the stripping characteristics of C-He in the energy range of 70–220 keV, and new charge state yields and exchange cross-sections in C-He were obtained at energies of 70–220 keV.
The neurobiological pathogenesis of major depression disorder (MDD) remains largely controversial. Previous literatures with limited sample size utilizing group-level structural covariance networks (SCN) commonly generated mixed findings regarding the topology of brain networks.
Methods
We analyzed T1 images from a high-powered multisite sample including 1173 patients with MDD and 1019 healthy controls (HCs). We used regional gray matter volume to construct individual SCN by utilizing a novel approach based on the interregional effect size difference. We further investigated MDD-related structural connectivity alterations using topological metrics.
Results
Compared to HCs, the MDD patients showed a shift toward randomization characterized by increased integration. Further subgroup analysis of patients in different stages revealed this randomization pattern was also observed in patients with recurrent MDD, while the first-episode drug naïve patients exhibited decreased segregation. Altered nodal properties in several brain regions which have a key role in both emotion regulation and executive control were also found in MDD patients compared with HCs. The abnormalities in inferior temporal gyrus were not influenced by any specific site. Moreover, antidepressants increased nodal efficiency in the anterior ventromedial prefrontal cortex.
Conclusions
The MDD patients at different stages exhibit distinct patterns of randomization in their brain networks, with increased integration during illness progression. These findings provide valuable insights into the disruption in structural brain networks that occurs in patients with MDD and might be useful to guide future therapeutic interventions.
A single-stage accelerator mass spectrometer (GXNU-AMS) developed for radiocarbon and tritium measurements was installed and commissioned at Guangxi Normal University in 2017. After several years of operational and methodological upgrades, its performance has been continuously improved and applied in multidisciplinary fields. Currently, the measurement sensitivity for radiocarbon and tritium is 14C/12C ∼ (3.14 ± 0.05) ×10–15 and 3H/1H ∼ (1.23 ± 0.17)×10–16, respectively, and the measurement accuracy is ∼0.6%, which can meet the measurement requirements in the nuclear, earth, environmental and life science fields. This study presents the performance characteristics of GXNU-AMS and several interesting application studies.
It is generally accepted that high-oleic crops have at least 70% oleate. As compared to their normal-oleic counterparts, oil and food products made from high-oleic peanut have better keeping quality and are much healthier. Therefore, high-oleic peanut is well recognized by processors and consumers. However, owing to the limited availability of high-oleic donors, most present-day high-oleic peanut varietal releases merely have F435 type FAD2 mutations. Through screening of a mutagenized peanut population of 15L46, a high-yielding peanut line with desirable elliptical oblong large seeds, using near infrared model for predicting oleate content in individual single seeds, high-oleic peanut mutants were identified. Sequencing FAD2A and FAD2B of the mutants along with the wild type revealed that these mutants possessed G448A FAD2A (F435 type FAD2A mutation) and G558A FAD2B (non-F435 type FAD2B mutation). Expression of the wild and mutated type FAD2B in yeast verified that the functional mutation contributed to the high-oleic phenotype in these mutants. The mutants provided additional high-oleic donors to peanut quality improvement.
This chapter introduces automation techniques for intracytoplasmic sperm injection (ICSI). These techniques are used for sperm motility and morphology quantification, sperm immobilization, sperm aspiration, oocyte orientation control, and sperm injection. Emerging techniques are also described such as computer assisted sperm analysis, laser immobilization, deep learning based polar body detection, and piezo drilling for reducing cell deformation in penetration. Finally, outlooks for future development of automation techniques in ICSI are provided.
Iodine is an important element in thyroid hormone biosynthesis. Thyroid function is regulated by the hypothalamic–pituitary–thyroid axis. Excessive iodine leads to elevated thyroid-stimulating hormone (TSH) levels, but the mechanism is not yet clear. Type 2 deiodinase (Dio2) is a Se-containing protease that plays a vital role in thyroid function. The purpose of this study was to explore the role of hypothalamus Dio2 in regulating TSH increase caused by excessive iodine and to determine the effects of iodine excess on thyrotropin-releasing hormone (TRH) levels. Male Wistar rats were randomised into five groups and administered different iodine dosages (folds of physiological dose): normal iodine, 3-fold iodine, 6-fold iodine, 10-fold iodine and 50-fold iodine. Rats were euthanised at 4, 8, 12 or 24 weeks after iodine administration. Serum TRH, TSH, total thyroxine (TT4) and total triiodothyronine (TT3) were determined. Hypothalamus tissues were frozen and sectioned to evaluate the expression of Dio2, Dio2 activity and monocarboxylate transporter 8 (MCT8). Prolonged high iodine intake significantly increased TSH expression (P < 0·05) but did not affect TT3 and TT4 levels. Prolonged high iodine intake decreased serum TRH levels in the hypothalamus (P < 0·05). Dio2 expression and activity in the hypothalamus exhibited an increasing trend compared at each time point with increasing iodine intake (P < 0·05). Hypothalamic MCT8 expression was increased in rats with prolonged high iodine intake (P < 0·05). These results indicate that iodine excess affects the levels of Dio2, TRH and MCT8 in the hypothalamus.
GBF1 [Golgi brefeldin A (BFA) resistance factor 1] is a member of the guanine nucleotide exchange factors Arf family. GBF1 localizes at the cis-Golgi and endoplasmic reticulum (ER)-Golgi intermediate compartment where it participates in ER-Golgi traffic by assisting in the recruitment of the coat protein COPI. However, the roles of GBF1 in oocyte meiotic maturation are still unknown. In the present study, we investigated the regulatory functions of GBF1 in mouse oocyte organelle dynamics. In our results, GBF1 was stably expressed during oocyte maturation, and GBF1 localized at the spindle periphery during metaphase I. Inhibiting GBF1 activity led to aberrant accumulation of the Golgi apparatus around the spindle. This may be due to the effects of GBF1 on the localization of GM130, as GBF1 co-localized with GM130 and inhibiting GBF1 induced condensation of GM130. Moreover, the loss of GBF1 activity affected the ER distribution and induced ER stress, as shown by increased GRP78 expression. Mitochondrial localization and functions were affected, as the mitochondrial membrane potential was altered. Taken together, these results suggest that GBF1 has wide-ranging effects on the distribution and functions of Golgi apparatus, ER, and mitochondria as well as normal polar body formation in mouse oocytes.
Thermal conductivity behaviors are one of the most important evaluations of carbon fiber-reinforced carbon matrix (C/C) composites in the field of thermal protective structures. In order to deepen the understanding of the thermal conductivity behaviors of C/C composites, the out-of-plane thermal conductivity of C/C composites is studied by considering voids and the fiber volume fractions. The representative volume element (RVE) models of microscale and mesoscale are proposed. The parameters of the RVE models are captured by X-ray micro-computed tomography. The carbon matrix equivalent models and fiber volume fraction models along the z-direction were established. The effects of the porosity and fiber volume fraction along the z-direction on the thermal conductivity were analyzed. The proposed model was validated by experimental results at room temperature. Further, the numerical methods developed in this study can provide guidance for predicting the thermal conductivity of C/C composites with complex structures.
The various vision-based tactile sensors have been developed for robotic perception in recent years. In this paper, the novel soft robotic finger embedded with the visual sensor is proposed for perception. It consists of a colored soft inner chamber, an outer structure, and an endoscope camera. The bending perception algorithm based on image preprocessing and deep learning is proposed. The boundary of color regions and the position of marker dots are extracted from the inner chamber image and label image, respectively. Then the convolutional neural network with multi-task learning is trained to obtain bending states of the finger. Finally, the experiments are implemented to verify the effectiveness of the proposed method.
The aim of this study was to analyze the profile of chest injuries, oxygen therapy for respiratory failure, and the outcomes of victims after the Jiangsu tornado, which occurred on June 23, 2016 in Yancheng City, Jiangsu Province, China.
Methods:
The clinical records of 144 patients referred to Yancheng City No.1 People’s Hospital from June 23 through June 25 were retrospectively investigated. Of those patients, 68 (47.2%) sustained major chest injuries. The demographic details, trauma history, details of injuries and Abbreviated Injury Scores (AIS), therapy for respiratory failure, surgical procedures, length of intensive care unit (ICU) and hospital stay, and mortality were analyzed.
Results:
Of the 68 patients, 41 (60.3%) were female and 27 (39.7%) were male. The average age of the injured patients was 57.1 years. Forty-six patients (67.6%) suffered from polytrauma. The mean thoracic AIS of the victims was calculated as 2.85 (SD = 0.76). Rib fracture was the most common chest injury, noted in 56 patients (82.4%). Pulmonary contusion was the next most frequent injury, occurring in 12 patients (17.7%). Ten patients with severe chest trauma were admitted to ICU. The median ICU stay was 11.7 (SD = 8.5) days. Five patients required intubation and ventilation, one patient was treated with noninvasive positive pressure ventilation (NPPV), and four patients were treated with high-flow nasal cannula (HFNC). Three patients died during hospitalization. The hospital mortality was 4.41%.
Conclusions:
Chest trauma was a common type of injury after tornado. The most frequent thoracic injuries were rib fractures and pulmonary contusion. Severe chest trauma is usually associated with a high incidence of respiratory support requirements and a long length of stay in the ICU. Early initiation of appropriate oxygen therapy was vital to restoring normal respiratory function and saving lives. Going forward, HFNC might be an effective and well-tolerated therapeutic addition to the management of acute respiratory failure in chest trauma.
The micro-nano rough structure promotes the formation of superhydrophobic surfaces, while the formation of superoleophobic surfaces requires the support of re-entrant structures. Electrochemical etching and boiling water treatment methods were used to process the superoleophobic surface in the Al–Mg alloy substrate. The differences between the potential of the aluminum and the magnesium promoted the formation of the surface microstructure under the current stimulation, and the surface was formed into dense nanoscale needle-like coating after boiling water treatment. Scanning electron microscopy, energy dispersive spectroscopy, and contact angle measurement were performed to characterize the morphological features, chemical composition, and surface wettability, respectively. The so-prepared superoleophobic surfaces showed high contact angles and small sliding angles for water, ethylene glycol, and hexadecane. In addition, surface topography, reaction mechanism, and experimental parameters were also studied.
Sterol regulatory element binding protein 1 (SREBP1) has a central regulatory effect on milk fat synthesis. Lipopolysaccharides (LPS) can induce mastitis and cause milk fat depression in cows. SREBP1 is also known to be associated with inflammatory regulation. Thus, in the current study, we hypothesized that LPS-induced milk fat depression in dairy cow mammary epithelial cells (DCMECs) operates via decreased SREBP1 expression and activity. To examine the hypothesis, DCMECs were isolated and purified from dairy cow mammary tissue and treated with LPS (10 µg/ml). LPS treatment of DCMECs suppressed lipid-metabolism-related transcription factor SREBP1 mRNA expression, nuclear translocation and protein expression, leading to reduced triglyceride content. The transcription levels of acetyl-CoA carboxylase-1 and fatty acid synthetase were significantly down-regulated in DCMECs after LPS treatment, suggesting that acetyl-CoA carboxylase-1 and fatty acid synthetase involved in de novo milk fat synthesis was regulated by SREBP1. In summary, these results suggest that LPS induces milk fat depression in dairy cow mammary epithelial cells via decreased expression of SREBP1 in a time-dependent manner.