Arabidopsis FIN219/JAR1 interacts with phytochrome A under far-red light and jasmonates in regulating hypocotyl elongation via a functional demand manner.

Integration of light and phytohormones is essential for plant growth and development. FAR-RED INSENSITIVE 219 (FIN219)/JASMONATE RESISTANT 1 (JAR1) participates in phytochrome A (phyA)-mediated far-red (FR) light signaling in Arabidopsis and is a jasmonate (JA)-conjugating enzyme for the generation of an active JA-isoleucine. Accumulating evidence indicates that FR and JA signaling integrate with each other. However, the molecular mechanisms underlying their interaction remain largely unknown. Here, the phyA mutant was hypersensitive to JA. The double mutant fin219-2phyA-211 showed a synergistic effect on seedling development under FR light. Further evidence revealed that FIN219 and phyA antagonized with each other in a mutually functional demand to modulate hypocotyl elongation and expression of light- and JA-responsive genes. Moreover, FIN219 interacted with phyA under prolonged FR light, and MeJA could enhance their interaction with CONSTITUTIVE PHOTOMORPHOGENIC 1 (COP1) in the dark and FR light. FIN219 and phyA interaction occurred mainly in the cytoplasm, and they regulated their mutual subcellular localization under FR light. Surprisingly, the fin219-2 mutant abolished the formation of phyA nuclear bodies under FR light. Overall, these data identified a vital mechanism of phyA-FIN219-COP1 association in response to FR light, and MeJA may allow the photoactivated phyA to trigger photomorphogenic responses.

Protection-Free Strategy for the Synthesis of Boro-Depsipeptides in Aqueous Media under Microwave-Assisted Conditions.

In this report, 19 boron-containing depsipeptides were synthesized via microwave-assisted Passerini three-component reaction (P-3CR) in an aqueous environment. The linker-free DAHMI fluorescent tagging approach was used on selected boron-containing compounds to study the relationship between their structures and their level of cellular uptake of HEK293 cells. The biological data retrieved from the DAHMI experiments indicated that while the structures of tested compounds may be highly similar, their bio-distribution profile could be vastly distinctive. The reported optimized one-pot synthetic strategy along the linker-free in vitro testing protocol could provide an efficient platform to accelerate the development of boron-containing drugs.

Body Mass Index-Adjusted Body Weight Loss Grading Predicts Overall Survival in Esophageal Squamous Cell Carcinoma Patients.

PURPOSE: Various malnutrition and inflammation criteria were associated with prognosis of esophageal squamous cell carcinoma (ESCC) patients. Nonetheless, the interplay of clinicopathological features, malnutrition, and inflammation criteria with overall survival in ESCC patients remains unclear. METHODS: We retrospectively reviewed medical records of 205 patients diagnosed with ESCC between 2007 and 2012, and evaluated the status of participant malnutrition and inflammation, including body mass index < 18.5 kg/m2, body weight loss > 5.0%, serum albumin level < 3.5 g/dl, neutrophil-to-lymphocyte ratio > 3.5, platelet-to-lymphocyte ratio > 20, prognostic nutrition index < 40, blood total lymphocyte count < 1600 cells/mm3, and grades of body mass index-adjusted body weight loss (combined BMI-BWL). We assessed the association of clinicopathological features, nutritional status, and inflammation condition with overall survival using univariate and multivariate Cox regression analyses. RESULTS: The mean overall survival of ESCC patients was 28.8 mo,. The multivariate logistic regression model after adjustment for clinicopathological variables, malnutrition status, inflammation condition, and co-morbid status found that tumor stage and grades of combined BMI-BML served as equally important prognostic factors for overall survival. CONCLUSIONS: Advanced tumor stage and high grades of combined BMI-BWL were independent prognostic factors for overall survival in ESCC patients.

On-Site Earthquake Early Warning Using Smartphones.

In this study, the measured accelerations of a single smartphone were used to provide an earthquake early warning system. In the presented system, after the smartphone is triggered, the triggering event is then classified as an earthquake event or not. Once an earthquake event is detected, the peak ground acceleration is then predicted every second until 10 s after the trigger. These predictions are made by the neural network classifier and predictor embedded in the smartphone, and an alert can be issued if a large peak ground acceleration is predicted. The proposed system is unique among approaches that use crowdsourcing ideas for earthquake early warning because the proposed system provides on-site earthquake early warning. In general, the accuracy rates of the earthquake classifications and peak ground acceleration predictions of the system were quite high according to the results of large amounts of earthquake and non-earthquake data. More specifically, according to said earthquake data, 96.9% of the issued alerts would be correct and 61.9% of the earthquakes that exceeded the threshold would have resulted in an alert being issued before the arrival of the peak ground acceleration. Among the false negative cases, approximate 97.8% would occur because of negative lead time. Using the shake table tests of worldwide and Meinong earthquake datasets, the proposed approach is confirmed to be quite promising.

A Stand-Alone Smart Camera System for Online Post-Earthquake Building Safety Assessment.

Computer vision-based approaches are very useful for dynamic displacement measurement, damage detection, and structural health monitoring. However, for the application using a large number of existing cameras in buildings, the computational cost of videos from dozens of cameras using a centralized computer becomes a huge burden. Moreover, when a manual process is required for processing the videos, prompt safety assessment of tens of thousands of buildings after a catastrophic earthquake striking a megacity becomes very challenging. Therefore, a decentralized and fully automatic computer vision-based approach for prompt building safety assessment and decision-making is desired for practical applications. In this study, a prototype of a novel stand-alone smart camera system for measuring interstory drifts was developed. The proposed system is composed of a single camera, a single-board computer, and two accelerometers with a microcontroller unit. The system is capable of compensating for rotational effects of the camera during earthquake excitations. Furthermore, by fusing the camera-based interstory drifts with the accelerometer-based ones, the interstory drifts can be measured accurately even when residual interstory drifts exist. Algorithms used to compensate for the camera's rotational effects, algorithms used to track the movement of three targets within three regions of interest, artificial neural networks used to convert the interstory drifts to engineering units, and some necessary signal processing algorithms, including interpolation, cross-correlation, and filtering algorithms, were embedded in the smart camera system. As a result, online processing of the video data and acceleration data using decentralized computational resources is achieved in each individual smart camera system to obtain interstory drifts. Using the maximum interstory drifts measured during an earthquake, the safety of a building can be assessed right after the earthquake excitation. We validated the feasibility of the prototype of the proposed smart camera system through the use of large-scale shaking table tests of a steel building. The results show that the proposed smart camera system had very promising results in terms of assessing the safety of steel building specimens after earthquake excitations.

Analysis of Environmental and Typhoon Effects on Modal Frequencies of a Power Transmission Tower.

The structural health monitoring of power transmission towers (PTTs) has drawn increasing attention from researchers in recent years; however, no long-term monitoring of the dynamic parameters of PTTs has previously been reported in the literature. This study performed the long-term monitoring of an instrumented PTT. An automated subspace identification technique was used to extract the dynamic parameters of the PTT from ambient vibration measurements taken over approximately ten months in 2017. Ten target modal frequencies were selected to explore the effects of environmental factors, such as temperature and wind speed, as well as the root-mean-square (RMS) acceleration response of the PTT. Variations in the modal frequencies of approximately 2% to 8% were observed during the study period. In general, among the environmental factors, the temperature was found to be the primary cause of decreases in the modal frequencies, except in the case of some of the higher modes. Typhoon Nesat, which affected the PTT on July 29th, 2017, seems to have decreased the modal frequencies of the PTT, especially for the higher modes. This reduction in the modal frequencies seems to have lasted for approximately two and a half months, after which they recovered to their normal state, probably due to a seasonal cool down in temperature. The reduction percentages in the modal frequencies due to Typhoon Nesat were quantified as approximately -0.89% to -1.34% for the higher modes, but only -0.07% to -0.46% for the remaining lower modes. Although the unusual reductions in the modal frequencies are reported in this study, the reason for this phenomenon is not clear yet. Further studies would be required in the future in order to find the cause.

Construction of a Lactobacillus plantarum Strain Expressing the Capsid Protein of Porcine Circovirus Type 2d (PCV2d) as an Oral Vaccine.

Porcine circovirus type 2 (PCV2) is a pathogenic virus that causes high rates of porcine death, resulting in severe economic losses to the swine industry. In recent years, the prevalence of PCV2d genotype infection in pigs has increased, but most commercially available vaccines were developed against the PCV2a strain and do not ensure complete protection from PCV2d. Here, we first constructed an expression vector for the antigenic ORF2-encoded capsid protein of PCV2d (pLp3050-His6-tag-capsid). We then utilized Lactobacillus plantarum to express the protein at mucosal sites in orally vaccinated mice. After transducing L. plantarum with pLp3050-His6-tag-capsid, the expressed protein could be found in cell wall and cell-free supernatant fractions by Western blotting. Using flow cytometry, we found that L. plantarum cells with surface-displayed capsid protein increased with time after SppIP induction. Finally, mice that were orally immunized 18 times with capsid-expressing L. plantarum showed increased levels of capsid-specific sIgA and virus neutralizing activity at mucosal sites, suggesting mucosal immunity had been stimulated by the vaccine. Overall, our findings demonstrate the feasibility and utility of a PCV2d-based vaccine, which may be of great value in porcine agriculture.

Evaluating Post-Earthquake Building Safety Using Economical MEMS Seismometers.

The earthquake early warning (EEW)-research group at National Taiwan University has been developing a microelectromechanical system-based accelerometer called “P-Alert”, designed for issuing EEWs. The main advantage of P-Alert is that it is a relatively economical seismometer. However, because of the expensive nature of commercial hardware for structural health monitoring (SHM) systems, the application of SHM to buildings remains limited. To determine the performance of P-Alert for evaluating post-earthquake building safety, we conducted a series of steel-frame shaking table tests with incremental damage. We used the fragility curves of different damage levels and the interstory drift ratios (calculated by the measured acceleration of each story using double integration and a filter) to gauge the potential damage levels. We concluded that the acceptable detection of damage for an entire building is possible. With improvements to the synchronization of the P-Alert sensors, we also anticipate a damage localization feature for the stories of a building.

EBV oncogene N-LMP1 induces CD4 T cell-mediated angiogenic blockade in the murine tumor model.

Antivascular immunity may provide long-term protection by preventing neovascularization that precedes tumor progression. Although the tumorigenesis promoted by EBV-encoded oncogene latent membrane protein 1 derived from Taiwanese nasopharyngeal carcinoma (N-LMP1) has been demonstrated, the potential of N-LMP1 for inducing immune surveillance remains elusive. In this article, we describe the immunogenicity of N-LMP1 (1510) and its induction of antivascular immunity in a transplantable tumor model in immunocompetent BALB/c mice. The immunogenicity of N-LMP1 was evaluated on the basis of tumor rejection following immunization. The impact of the immunization on the dynamics of tumor angiogenesis was assessed by temporal noninvasive dynamic contrast-enhanced magnetic resonance imaging and was further confirmed by histologic study and vascular count. Through the experiments of in vivo depletion and adoptive transfer, CD4 T cells were identified as effectors that depend on IFN-γ for tumor prevention. The response was further verified by the identification of an MHC H-2 I-E(d)-restricted peptide derived from N-LMP1 and by the immunization of mice with N-LMP1 peptide-loaded dendritic cells. These studies provide insight into N-LMP1-specific immunity in vivo, which suggests that CD4 T cells may play an important role in angiogenic surveillance against LMP1-associated cancer via tumor stroma targeting.

Tailoring the Size of Reduced Graphene Oxide Sheets to Fabricate Silicon Composite Anodes for Lithium-Ion Batteries.

The integration of a silicon (Si) anode into lithium-ion batteries (LIBs) holds great promise for energy storage, but challenges arise from unstable electrochemical reactions and volume changes during cycling. This study investigates the influence of reduced graphene oxide (rGO) size on the performance of rGO-protected Si composite (Si@rGO) anodes. Two sizes of graphene oxide (GO(L) and GO(S)) are used to synthesize Si@rGO composites with a core-shell structure by spray drying and thermal reduction. Electrochemical evaluations show the advantages of the Si@rGO(S) anode with improved cycle life and cycling efficiency over Si@rGO(L) and pure Si. The Si@rGO(S) anode facilitates the formation of a stable LiF-rich solid electrolyte interface (SEI) after cycling, ensuring enhanced capacity retention and swelling control. Rate capability tests also demonstrate the superior high-power performance of Si@rGO(S) with low and stable resistances in Si@rGO(S) over extended cycles. This study provides critical insights into the tailoring of graphene-protected Si composites, highlighting the critical role of rGO size in shaping structural and electrochemical properties. The Si material wrapped by graphene with an optimal lateral size of graphene emerges as a promising candidate for high-performance LIB anodes, thereby advancing electrochemical energy storage technologies.

The Browning Properties, Antioxidant Activity, and α-Glucosidase Inhibitory Improvement of Aged Oranges (Citrus sinensis).

Oranges contain many natural active chemicals, organic acids, and polysaccharides. Aging processing is commonly used to modify the color, quality, functional components, and stability of fruits. This study assesses the preparation of aging black oranges using various pre-treatments and solid fermentation. Oranges were aged for six weeks in fresh, non-blanching, blanching, and hot air-assisted aging cycle (AA) groups. The oranges' shrinkage ratio, color difference values, and soluble solids content changed significantly (p < 0.05). Principal component analysis indicated that aging fermentation treatment accelerated glycolysis and increased the ratio of reducing sugars. The enhanced browning can be associated with the oxidation of ascorbic acid (0.66-0.47 mg/g) and the formation of 5-hydroxymethylfurfural (5-HMF) (0.09 mg/g). Furthermore, the presence of free polyphenols led to an increase in the total polyphenol and total flavonoid content. It also had a synergistic effect with 5-HMF in increasing the 2,2-diphenyl-1-picrylhydrazyl free radical-scavenging capacity and ferric ion-reducing antioxidant power (p < 0.05). AA had superior α-glucosidase inhibitory ability increasing from 67.31 to 80.48%. It also reduced the development time by 33%. Therefore, aging technology can enhance the bioactive compounds in oranges and provide a reference for future whole-fruit aging fermentation and health product creation.

Explainable Deep Learning Model for Predicting Serious Adverse Events in Hospitalized Geriatric Patients Within 72 Hours.

Background: The global aging population presents a significant challenge, with older adults experiencing declining physical and cognitive abilities and increased vulnerability to chronic diseases and adverse health outcomes. This study aims to develop an interpretable deep learning (DL) model to predict adverse events in geriatric patients within 72 hours of hospitalization. Methods: The study used retrospective data (2017-2020) from a major medical center in Taiwan. It included non-trauma geriatric patients who visited the emergency department and were admitted to the general ward. Data preprocessing involved collecting prognostic factors like vital signs, lab results, medical history, and clinical management. A deep feedforward neural network was developed, and performance was evaluated using accuracy, sensitivity, specificity, positive predictive value (PPV), and area under the receiver operating characteristic curve (AUC). Model interpretation utilized the Shapley Additive Explanation (SHAP) technique. Results: The analysis included 127,268 patients, with 2.6% experiencing imminent intensive care unit transfer, respiratory failure, or death during hospitalization. The DL model achieved AUCs of 0.86 and 0.84 in the validation and test sets, respectively, outperforming the Sequential Organ Failure Assessment (SOFA) score. Sensitivity and specificity values ranged from 0.79 to 0.81. The SHAP technique provided insights into feature importance and interactions. Conclusion: The developed DL model demonstrated high accuracy in predicting serious adverse events in geriatric patients within 72 hours of hospitalization. It outperformed the SOFA score and provided valuable insights into the model's decision-making process.

Droplet epitaxy of InGaN quantum dots on Si (111) by plasma-assisted molecular beam epitaxy.

The droplet epitaxy of indium gallium nitride quantum dots (InGaN QDs), the formation of In-Ga alloy droplets in ultra-high vacuum and then surface nitridation by plasma treatment, is firstly investigated by using plasma-assisted molecular beam epitaxy. During the droplet epitaxy process, in-situ reflection high energy electron diffraction patterns performs the amorphous In-Ga alloy droplets transform to polycrystalline InGaN QDs, which are also confirmed by the characterizations of transmission electron microscopy and X-ray photoelectron spectroscopy. The substrate temperature, In-Ga droplet deposition time, and duration of nitridation are set as parameters to study the growth mechanism of InGaN QDs on Si. Self-assembled InGaN QDs with a density of 1.33 × 1011 cm-2 and an average size of 13.3 ± 3 nm can be obtained at the growth temperature of 350 °C. The photoluminescence emissions of uncapped InGaN QDs in wavelength of the visible red (715 nm) and infrared region (795 and 857 nm) are observed. The formation of high-indium composition of InGaN QDs via droplet epitaxy technique could be applied in long wavelength optoelectronic devices.

Evaluating the performance of ChatGPT-4 on the United Kingdom Medical Licensing Assessment.

Introduction: Recent developments in artificial intelligence large language models (LLMs), such as ChatGPT, have allowed for the understanding and generation of human-like text. Studies have found LLMs abilities to perform well in various examinations including law, business and medicine. This study aims to evaluate the performance of ChatGPT in the United Kingdom Medical Licensing Assessment (UKMLA). Methods: Two publicly available UKMLA papers consisting of 200 single-best-answer (SBA) questions were screened. Nine SBAs were omitted as they contained images that were not suitable for input. Each question was assigned a specialty based on the UKMLA content map published by the General Medical Council. A total of 191 SBAs were inputted in ChatGPT-4 through three attempts over the course of 3 weeks (once per week). Results: ChatGPT scored 74.9% (143/191), 78.0% (149/191) and 75.6% (145/191) on three attempts, respectively. The average of all three attempts was 76.3% (437/573) with a 95% confidence interval of (74.46% and 78.08%). ChatGPT answered 129 SBAs correctly and 32 SBAs incorrectly on all three attempts. On three attempts, ChatGPT performed well in mental health (8/9 SBAs), cancer (11/14 SBAs) and cardiovascular (10/13 SBAs). On three attempts, ChatGPT did not perform well in clinical haematology (3/7 SBAs), endocrine and metabolic (2/5 SBAs) and gastrointestinal including liver (3/10 SBAs). Regarding to response consistency, ChatGPT provided correct answers consistently in 67.5% (129/191) of SBAs but provided incorrect answers consistently in 12.6% (24/191) and inconsistent response in 19.9% (38/191) of SBAs, respectively. Discussion and conclusion: This study suggests ChatGPT performs well in the UKMLA. There may be a potential correlation between specialty performance. LLMs ability to correctly answer SBAs suggests that it could be utilised as a supplementary learning tool in medical education with appropriate medical educator supervision.

The Impact of Do-Not-Resuscitate Order in the Emergency Department on Respiratory Failure after ICU Admission.

(1) Background: It has been hypothesized that a discrepancy exists in the understanding of a do-not-resuscitate (DNR) order among physicians. We hypothesized that a DNR order signed in the emergency department (ED) could influence the patients' prognosis after intensive care unit (ICU) admission. (2) Methods: We included patients older than 17 years, who visited the emergency department for non-traumatic disease, who had respiratory failure, required ventilator support, and were admitted to the ICU between January 2010 and December 2016. The associations between DNR and mortality, hospital length of stay (LOS), and medical fees were analyzed. Prolonged hospital LOS was defined as hospital stay ≥75th percentile (≥26 days for the study). Patients were classified as those who did and did not sign a DNR order. A 1:4 propensity score matching was conducted for demographics, comorbidities, and etiology. (3) Results: The study enrolled a total of 1510 patients who signed a DNR and 6040 patients who did not sign a DNR. The 30-day mortality rates were 47.4% and 28.0% among patients who did and did not sign a DNR, respectively. A DNR order was associated with mortality after adjusting for confounding factors (hazard ratio, 1.9; confidence interval, 1.70−2.03). It was also a risk factor for prolonged hospital LOS in survivors (odds ratio, 1.2; confidence interval, 1.02−1.44). Survivors who signed a DNR order were charged higher medical fees than those who did not sign a DNR (217,159 vs. 245,795 New Taiwan Dollars, p < 0.001). (4) Conclusions: Signing a DNR order in the ED increased the ICU mortality rate among patients who had respiratory failure and needed ventilator support. It increased the risk of prolonged hospital LOS among survivors. Finally, signing a DNR order was associated with high medical fees among survivors.

The Effect of Bacillus licheniformis-Fermented Products and Postpartum Dysgalactia Syndrome on Litter Performance Traits, Milk Composition, and Fecal Microbiota in Sows.

This study was designed to evaluate the effects of Bacillus licheniformis-fermented products (BLFP) and postpartum dysgalactia syndrome (PDS) on litter performance traits, milk composition, and fecal microbiota in sows in a commercial farrow to finish pig farm. Fifty multiparous cross-bred pregnant sows were randomly assigned to two groups in a completely randomized design. The dietary treatments comprised a basal diet (pregnancy and nursery diet) as control and basal diet supplemented with 1.5 g/kg of BLFP. Sows with PDS in the two groups were further verified 12 h post-partum. Results show that the piglet body weight at weaning was increased in sows fed the BLFP compared to those fed the control diet. The milk fat content of prepartum sows was reduced in sows fed the BLFP. Postpartum sows with PDS had increased milk solid content compared with healthy sows. Microbial composition and species relative abundance analysis indicated distinct bacterial clusters between the groups. The abundance of the family Prevotellaceae in the feces decreased in sows with PDS. BLFP increased the average abundance of the genus (Eubacterium) coprostanoligenes group in feces of sows. These findings demonstrate that BLFP in the diet of sows can improve the piglet body weight at weaning and modulate the fecal microbiota of sows. PDS also has an impact on milk composition and fecal microbiota in sows.

Characteristics of the dual-bridge giant magnetoresistance magnetometer.

The responsivity and the field noise characteristics of the giant magnetoresistance (GMR) magnetometer driven by an alternating magnetic field are investigated. The harmonic spectrum of the sensor voltage shows that only the odd harmonics of excitation frequency are sensitive to the external dc field. To cancel out the even harmonics, the dual-bridge GMR magnetometer with the balanced output is proposed. With the dual-bridge configuration, the field-to-voltage transfer coefficient is doubled and the field noise is reduced by a factor of 1.4. The minimum field noise is 7 nT∕√Hz at 1 Hz with the ac excitation power of 5.5 mW. The proposed sensor is suitable for the electronic compass application.