Machine learning-based modeling of surface water temperature dynamics in arctic lakes.

Lake surface-water temperature (LSWT) regulates physical and biochemical processes in lakes. Therefore, understanding the LSWT dynamics is important, especially in Arctic zone since the region is experiencing a warming rate that is greater than the Earth's average. However, regular measurements of LSWT in the remote Arctic lakes always face difficulties or cannot be done by satellites accurately due to the cloud cover and their limited spatiotemporal resolution. Here, we used a historically rich data (1960-2023) to develop four machine learning-based algorithms for the daily LSWT modeling in Lake Inari, situated in Arctic zone, using the air-temperature data. Our results showed that both air-temperature (0.030 °C/yr) and LSWT (0.023m °C/yr) were warming with a rate faster than those in the globe. The long-short-term memory model, with the coefficients of determination varied from 0.96 to 0.98, outperformed other algorithms in modeling of the daily LSWT dynamics in Lake Inari, followed by both support vector regression and neural network tools, and random forest model. As the air-temperature data are widely accessible through synoptic stations and remote sensing techniques, our suggested models can be simply adopted for other Arctic lakes, where the local water-temperature data are often lacking or contain large windows of missing data due to harsh atmospheric conditions and equipment failure.

Prompt Tuning of Deep Neural Networks for Speaker-adaptive Visual Speech Recognition.

Visual Speech Recognition (VSR) aims to infer speech into text depending on lip movements alone. As it focuses on visual information to model the speech, its performance is inherently sensitive to personal lip appearances and movements, and this makes the VSR models show degraded performance when they are applied to unseen speakers. In this paper, to remedy the performance degradation of the VSR model on unseen speakers, we propose prompt tuning methods of Deep Neural Networks (DNNs) for speaker-adaptive VSR. Specifically, motivated by recent advances in Natural Language Processing (NLP), we finetune prompts on adaptation data of target speakers instead of modifying the pre-trained model parameters. Different from the previous prompt tuning methods mainly limited to Transformer variant architecture, we explore different types of prompts, the addition, the padding, and the concatenation form prompts that can be applied to the VSR model which is composed of CNN and Transformer in general. With the proposed prompt tuning, we show that the performance of the pre-trained VSR model on unseen speakers can be largely improved by using a small amount of adaptation data (e.g., less than 5 minutes), even if the pre-trained model is already developed with large speaker variations. Moreover, by analyzing the performance and parameters of different types of prompts, we investigate when the prompt tuning is preferred over the finetuning methods. The effectiveness of the proposed method is evaluated on both word- and sentence-level VSR databases, LRW-ID and GRID.

Incorporation of water quality index models with machine learning-based techniques for real-time assessment of aquatic ecosystems.

Water quality index (WQI) is a well-established tool for assessing the overall quality of fresh inland-waters. However, the effectiveness of real-time assessment of aquatic ecosystems using the WQI is usually impacted by the absence of some water quality parameters in which their accurately in-situ measurements are impossible and face difficulties. Using a rich water quality dataset spanned from 1980 to 2023, we employed four machine learning-based models to estimate the British Colombia WQI (BCWQI) in the Lake Päijänne, Finland, without parameters like chemical oxygen demand (COD) and total phosphorus (TP). Measurement of both COD and TP is time-consuming, needs laboratory equipment and labor costs, and faces sampling-related difficulties. Our results suggest the machine learning-based models successfully estimate the BCWQI in Lake Päijänne when TP and COD are omitted from the dataset. The long-short term memory model is the least sensitive model to exclusion of COD and TP from inputs. This model with the coefficient of determination and root-mean squared error of 0.91 and 0.11, respectively, outperforms the support vector regression, random forest, and neural network models in real-time estimation of the BCWQI in Lake Päijänne. Incorporation of BCWQI with the machine learning-based models could enhance assessment of overall quality of inland-waters with a limited database in a more economical and time-saving way. Our proposed method is an effort to replace the traditional offline water quality assessment tools with a real-time model and improve understanding of decision-makers on the effectiveness of management practices on the changes in lake water quality.

Characterization of banned colorants in cosmetics: A tandem mass-based molecular networking approach.

Colorants have been a staple in the cosmetics industry for a considerable time, although certain varieties have been banned owing to health risks. Detecting and confirming these banned colorants simultaneously poses several challenges when employing LC-MS/MS. Molecular networking is a promising analytical technology that can be used to predict the structure of components and the correlation between them using structural and MS/MS spectral similarities. Molecular networking entails assessing the number of fragmented ions and the cosine score (the closer it is to one, the higher the similarity). In this study, we developed and verified a method for the simultaneous quantitative analysis of the 26 banned colorants in cosmetics using LC-MS/MS. Additionally, we propose a novel approach that combines LC-Q-TOF-MS and molecular networking technology to detect banned colorants in cosmetics. For successful molecular networking, a minimum of six fragment ions with cosine scores exceeding 0.5 is required. We developed a screening method for characterizing banned colorants using molecular networking based on LC-TOF-MS results for 26 banned colorants. Furthermore, we demonstrated that our established method can be used for screening by analyzing actual cosmetics (eyebrow tattoo, lipstick tattoo, and hair tint) spiked with three non-targeted banned colorants with similar structures (m/z 267.116, 315.149, and 345.157) in cosmetics. The combination of molecular networking techniques and LC-MS/MS proves highly advantageous for the swift characterization and screening of non-targeted colorants in cosmetics.

Establishment of high-performance liquid chromatography-photodiode array method for 43 weight loss agents and effect of basic environment on bisacodyl degradation.

RATIONALE: The demand for weight loss products is increasing as slimness emerges as the new aesthetic standard and people's desire to achieve it increases. In addition, the distribution and sale of products containing illegal ingredients, pharmaceuticals, and chemicals for which safety is not guaranteed and that cannot be used as foods or dietary supplements are increasing. Thus, the development of an analytical method that could monitor these illegal products is required. METHODS: A high-performance liquid chromatography-photodiode array method capable of rapid and reliable qualitative and quantitative analyses of 43 weight loss agents was established and validated. RESULTS: The process involved dividing analytes into three groups for rapid analysis; when bisacodyl was mixed with chlorocyclopentylsibutramine, it decomposed into its metabolites: monoacetyl bisacodyl and bis-(p-hydroxypheny)-pyridyl-2-methane. This decomposition was due to NaOH that was used to prepare the chlorocyclopentylsibutramine standard solution. Bisacodyl did not degrade when mixed with neutralized chlorocyclopentylsibutramine, whereas when NaOH was added, it rapidly degraded. We identified the bisacodyl degradation products using liquid chromatography-quadrupole-Orbitrap/mass spectrometry. MS2 spectra with proposed structures of fragment peaks were also obtained. CONCLUSIONS: The developed method could be used to regulate slimming products that threaten public health, and knowledge of bisacodyl degradation will be used as the basis for developing an analytic method.

End-tidal carbon dioxide after sodium bicarbonate infusion during mechanical ventilation or ongoing cardiopulmonary resuscitation.

PURPOSE: End-tidal CO2 is used to monitor the ventilation status or hemodynamic efficacy during mechanical ventilation or cardiopulmonary resuscitation (CPR), and it may be affected by various factors including sodium bicarbonate administration. This study investigated changes in end-tidal CO2 after sodium bicarbonate administration. MATERIALS AND METHODS: This single-center, prospective observational study included adult patients who received sodium bicarbonate during mechanical ventilation or CPR. End-tidal CO2 elevation was defined as an increase of ≥20% from the baseline end-tidal CO2 value. The time to initial increase (lag time, Tlag), time to peak (Tpeak), and duration of the end-tidal CO2 rise (Tduration) were compared between the patients with spontaneous circulation (SC group) and those with ongoing resuscitation (CPR group). RESULTS: Thirty-three patients, (SC group, n = 25; CPR group, n = 8), were included. Compared with the baseline value, the median values of peak end-tidal CO2 after sodium bicarbonate injection increased by 100% (from 21 to 41 mmHg) in all patients, 89.5% (from 21 to 39 mmHg) in the SC group, and 160.2% (from 15 to 41 mmHg) in the CPR group. The median Tlag was 17 s (IQR: 12-21) and the median Tpeak was 35 s (IQR: 27-52). The median Tduration was 420 s (IQR: 90-639). The median Tlag, Tpeak, and Tduration were not significantly different between the groups. Tduration was associated with the amount of sodium bicarbonate for SC group (correlation coefficient: 0.531, p = 0.006). CONCLUSION: The administration of sodium bicarbonate may lead to a substantial increase in end-tidal CO2 for several minutes in patients with spontaneous circulation and in patients with ongoing CPR. After intravenous administration of sodium bicarbonate, the use of end-tidal CO2 pressure as a physiological indicator may be limited.

Visualizing Hand Force with Wearable Muscle Sensing for Enhanced Mixed Reality Remote Collaboration.

In this paper, we present a prototype system for sharing a user's hand force in mixed reality (MR) remote collaboration on physical tasks, where hand force is estimated using wearable surface electromyography (sEMG) sensor. In a remote collaboration between a worker and an expert, hand activity plays a crucial role. However, the force exerted by the worker's hand has not been extensively investigated. Our sEMG-based system reliably captures the worker's hand force during physical tasks and conveys this information to the expert through hand force visualization, overlaid on the worker's view or on the worker's avatar. A user study was conducted to evaluate the impact of visualizing a worker's hand force on collaboration, employing three distinct visualization methods across two view modes. Our findings demonstrate that sensing and sharing hand force in MR remote collaboration improves the expert's awareness of the worker's task, significantly enhances the expert's perception of the collaborator's hand force and the weight of the interacting object, and promotes a heightened sense of social presence for the expert. Based on the findings, we provide design implications for future mixed reality remote collaboration systems that incorporate hand force sensing and visualization.

Effects of Avatar Transparency on Social Presence in Task-Centric Mixed Reality Remote Collaboration.

Despite the importance of avatar representation on user experience for Mixed Reality (MR) remote collaboration involving various device environments and large amounts of task-related information, studies on how controlling visual parameters for avatars can benefit users in such situations have been scarce. Thus, we conducted a user study comparing the effects of three avatars with different transparency levels (Nontransparent, Semi-transparent, and Near-transparent) on social presence for users in Augmented Reality (AR) and Virtual Reality (VR) during task-centric MR remote collaboration. Results show that avatars with a strong visual presence are not required in situations where accomplishing the collaborative task is prioritized over social interaction. However, AR users preferred more vivid avatars than VR users. Based on our findings, we suggest guidelines on how different levels of avatar transparency should be applied based on the context of the task and device type for MR remote collaboration.

Stereoscopic Vision Recalling Memory for Monocular 3D Object Detection.

Monocular 3D object detection has drawn increasing attention in various human-related applications, such as autonomous vehicles, due to its cost-effective property. On the other hand, a monocular image alone inherently contains insufficient information to infer the 3D information. In this paper, we propose a new monocular 3D object detector that can recall the stereoscopic visual information about an object, given a left-view monocular image. Here, we devise a location embedding module to handle each object by being aware of its location. Next, given the object appearance of the left-view monocular image, we devise Monocular-to-Stereoscopic (M2S) memory that can recall the object appearance of the right-view and depth information. For this purpose, we introduce a stereoscopic vision memorizing loss that guides the M2S memory to store the stereoscopic visual information. Furthermore, we propose a binocular vision association loss to guide the M2S memory that can associate the information of the left-right view about the object when estimating the depth. As a result, our monocular 3D object detector with the M2S memory can effectively exploit the recalled stereoscopic visual information in the inference phase. The comprehensive experimental results on two public datasets, KITTI 3D Object Detection Benchmark and Waymo Open Dataset, demonstrate the effectiveness of the proposed method. We claim that our method is a step-forward method that follows the behaviors of humans that can recall the stereoscopic visual information even when one eye is closed.

Simultaneous quantitation of 17 female sex hormones in illegal products by validated liquid chromatography-high resolution mass spectrometry and liquid chromatography-tandem mass spectrometry methods.

The consumption of food and drugs adulterated with female sex hormones can have an extremely adverse effect on human health. Therefore, developing appropriate monitoring methods for the identification of various exogenous female sex hormones is crucial for minimizing and eliminating the related health risks. Herein, 17 female hormones categorized into two groups: estrogen and progestin, were analyzed using reversed-phase liquid chromatography coupled to Orbitrap or triple quadrupole mass spectrometry. The fragmentation patterns for all compounds were discovered, and fragmented structures were also derived from them through liquid chromatography-high-resolution mass spectrometry followed by qualitative sample analysis. In addition, a quantitative analysis of 67 samples of illicit drugs and dietary supplements was performed using the validated liquid chromatography-tandem mass spectrometry method. Female hormone components were detected in two samples of an unauthorized injectable solution and a tablet-type drug. Medroxyprogesterone was detected in the samples in the range of 96.4-206 ng/g. Notably, eight components similar in structure to steroids were simultaneously detected as male sex hormones by confirming their fragmentation ion patterns using liquid chromatography-high-resolution mass spectrometry. The developed methods thus offer a dependable and practically applicable approach for the screening and detection of exogenous female sex hormones in real food and drug samples to ensure public health.

Liquid chromatography-quadrupole orbitrap and liquid chromatography-tandem mass spectrometry system for rapid identification and quantitation of thirty nonsteroidal anti-inflammatory drugs and acetaminophen in illegal products.

RATIONALE: As the public interest in healthcare increases, illegal dietary supplements, foods, and drugs containing unauthorized pharmaceutical ingredients, including nonsteroidal anti-inflammatory drugs (NSAIDs) and acetaminophen, have been identified. Excessive and unintentional consumption is toxic to the gastrointestinal tract, kidneys, and liver; therefore, these pharmaceuticals must be monitored using analytical methods. METHODS: A rapid and reliable analysis system involving liquid chromatography-quadrupole orbitrap mass spectrometry (LC-Q-Orbitrap/MS) and liquid chromatography-tandem mass spectrometry (LC/MS/MS) was established and validated to identify and quantify 30 NSAIDs and acetaminophen. In addition, we obtained the MS2 spectrum for each component with the proposed structure of the fragment ions. RESULTS: The analytical method was applied to 505 samples of illicitly distributed dietary supplements, foods, and pharmaceuticals. Non-steroidal analgesics were detected in 126 samples. Carbamazepine (42.9%) and diclofenac (30.2%) were the most detected components in the samples; other pharmaceutical adulterants were also detected in some cases. Additionally, we present the identification of an unknown component, dexamethasone (799 µg/g), using LC-Q-Orbitrap/MS in a sample containing the unknown component with meloxicam (15.4 mg/g). CONCLUSIONS: The developed analysis system, consisting of qualitative analysis using LC-Q-Orbitrap/MS and quantitative analysis using LC/MS/MS, can rapidly and accurately identify and quantify NSAIDs and acetaminophen while also identifying non-analytical components.

Various injury patterns due to combustion (typical but unfamiliar to physicians and easy to miss) in Korea: a case report.

Patients transported from fire sites may exhibit various injury patterns. Major trauma, skin burn, inhalation burn, and carbon monoxide poisoning are typical injuries. However, most physicians may be unfamiliar that cyanide poisoning can frequently occur due to combustion. Cyanide poisoning is highly significant owing to high mortality and the existence of antidotes. I present a 35-year-old man who was transported from a burning building and suffered severe metabolic acidosis despite no major bleeding as well as mild carbon monoxide poisoning. I suspected cyanide poisoning and administered the antidote; subsequently, the patient showed improvement. The next day, sudden airway obstruction developed, and emergency endotracheal intubation was performed. The inhalation damage was detected only in the lower airway tract and not in the upper airway. Physicians should be aware of cyanide poisoning and inhalation burn to avoid missing treatment opportunities.

No frequency change of prehospital treatments by emergency medical services providers for traumatic cardiac arrest patients before and after the COVID-19 pandemic in Korea: an observational study.

Purpose: Out-of-hospital traumatic cardiac arrest (TCA) often has a poor prognosis despite rescue efforts. Although the incidence and mortality of out-of-hospital cardiac arrest have increased, bystander cardiopulmonary resuscitation (CPR) has decreased in some countries during the COVID-19 pandemic. In the prehospital setting, immediate treatment of cardiac arrest is required without knowing the patient's COVID-19 status. Because COVID-19 is usually transmitted through the respiratory tract, airway management can put medical personnel at risk for infection. This study explored whether on-scene treatments involving CPR for TCA patients changed during the COVID-19 pandemic in Korea. Methods: This retrospective study used data from emergency medical services (EMS) run sheets in Gangwon Province from January 2019 to December 2021. Patients whose initial problem was cardiac arrest and who received CPR were included. Data in 2019 were classified as pre-COVID-19 and all subsequent data (from 2020 and 2021) as post-COVID-19. Age, sex, possible cause of cardiac arrest, and treatments including airway maneuvers, oropharyngeal airway (OPA) or i-gel insertion, endotracheal intubation (ETI), bag-valve mask (BVM) ventilation, intravenous (IV) line establishment, neck collar application, and wound dressing with hemostasis were investigated. Results: During the study period, 2,007 patients received CPR, of whom 596 patients had TCA and 367 had disease-origin cardiac arrest (DCA). Among the patients with TCA, 192 (32.2%) were pre-COVID-19 and 404 (67.8%) were post-COVID-19. In the TCA group, prehospital treatments did not decrease. The average frequencies were 59.7% for airway maneuvers, 47.5% for OPA, 57.4% for BVM, and 51.3% for neck collar application. The rates of ETI, i-gel insertion, and IV-line establishment increased. The treatment rate for TCA was significantly higher than that for DCA. Conclusions: Prehospital treatments by EMS workers for patients with TCA did not decrease during the COVID-19 pandemic. Instead, the rates of ETI, i-gel insertion, and IV-line establishment increased.

Delayed Presentation of Spontaneous Shockable Rhythm After Death: Another Subtype of Lazarus Phenomenon?

Lazarus phenomenon was defined as spontaneous circulatory restoration after death. It is important because survival discharge is possible. A 44-year-old woman developed traumatic cardiac arrest. She was declared dead after 30 minutes of resuscitation. Suddenly, pulseless ventricular tachycardia was shown after 6 minutes of death declaration. Resuscitation with epinephrine injection was resumed but was terminated after 7 minutes, and she was declared dead once more. A case where an electrocardiography appears spontaneously should be classified as a subtype of the Lazarus phenomenon. If the transition from asystole to spontaneous shockable rhythm follows a mechanism similar to that of the Lazarus phenomenon, active resuscitation and monitoring for a period of time following death declaration should be considered.

Effects of Brain Factor­7® against motor deficit and oxidative stress in a mouse model of MPTP­induced Parkinson's disease.

Oxidative stress is strongly implicated in the pathogenesis of Parkinson's disease (PD) through degeneration of dopaminergic neurons. The present study was designed to investigate the underlying mechanisms and therapeutic potential of Brain Factor-7® (BF-7®), a natural compound in silkworm, in a mouse model of PD induced by 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). MPTP (20 mg/kg) was intraperitoneally injected into mice to cause symptoms of PD. Mice were orally administered BF-7® (a mixture of silk peptides) before and after MPTP treatment. Rotarod performance test was used to assess motor performance. Fluoro-Jade B staining for neurons undergoing degeneration and immunohistochemistry of tyrosine hydroxylase for dopaminergic neurons, 4-hydroxy-2-nonenal (4HNE) for lipid peroxidation, 8-hydroxy-2'-deoxyguanosine (8OHdG) for DNA damage and superoxide dismutase (SOD) 1 and SOD2 for antioxidative enzymes in the pars compacta of the substantia nigra were performed. Results showed that BF-7® treatment significantly improved MPTP-induced motor deficit and protected MPTP-induced dopaminergic neurodegeneration. Furthermore, BF-7® treatment significantly ameliorated MPTP-induced oxidative stress. Increased 4HNE and 8OHdG immunoreactivities induced by MPTP were significantly reduced by BF-7®, whereas SOD1 and SOD2 immunoreactivities decreased by MPTP were significantly enhanced by BF-7®. In conclusion, BF-7® exerted protective and/or therapeutic effects in a mouse model of PD by decreasing effects of oxidative stress on dopaminergic neurons in the substantia nigra pars compacta.

Entropy-Aware Model Initialization for Effective Exploration in Deep Reinforcement Learning.

Effective exploration is one of the critical factors affecting performance in deep reinforcement learning. Agents acquire data to learn the optimal policy through exploration, and if it is not guaranteed, the data quality deteriorates, which leads to performance degradation. This study investigates the effect of initial entropy, which significantly influences exploration, especially in the early learning stage. The results of this study on tasks with discrete action space show that (1) low initial entropy increases the probability of learning failure, (2) the distributions of initial entropy for various tasks are biased towards low values that inhibit exploration, and (3) the initial entropy for discrete action space varies with both the initial weight and task, making it hard to control. We then devise a simple yet powerful learning strategy to deal with these limitations, namely, entropy-aware model initialization. The proposed algorithm aims to provide a model with high initial entropy to a deep reinforcement learning algorithm for effective exploration. Our experiments showed that the devised learning strategy significantly reduces learning failures and enhances performance, stability, and learning speed.

Application of LC-MS/MS and UHPLC-Q-Orbitrap methods for determining 54 steroids in illegal dietary supplements and other sample types.

RATIONALE: With the development of the Internet and social network services, the public access to or use of illegal products has been increased via on/offline black markets. Steroids refer to the compounds yielding strong treatment effects on some diseases or muscle building, and are classified as the pharmaceutical compounds that are prohibited for personal use without a prescription. The prohibition is made for their potential risk to cause serious adverse effects along with their efficacies. METHODS: To monitor the distribution of illicit products containing steroids, a simple and reliable analytical method was established and validated, allowing rapid and simultaneous determination of 54 steroids in them. During the screening, LC-Q-Orbitrap/MS was performed first followed by quantitative analysis using LC-MS/MS. For the accurate and reliable analysis, the samples were extracted using QuEChERS to reduce the matrix effect. RESULTS: After the screening of 617 illegal samples advertised as being effective in alleviating various diseases or improving athletic performance with the established LC-Q-Orbitrap/MS method, the validated LC-MS/MS method was used to perform the quantitative analysis of the detected steroids. Of these, 142 samples were adulterated with steroids, and several samples with two or more steroids were detected. Due to the lack of previous studies on the toxicity of these illicit products, the side effects of consuming them are unpredictable and could be harmful. CONCLUSIONS: The development of LC-Q-Orbitrap/MS method accompanied by LC-MS/MS could be successfully applied to the inspection of illegal steroid products for public health, enabling the rapid and accurate detection of analytes and incorporation of non-analyte components.

Application of liquid chromatography-high resolution mass spectrometry and liquid chromatography-tandem mass spectrometry methods to 45 weight loss compounds in health functional food, food, and illegal drug.

In order to effectively and quickly monitor such illegal food and drugs, simultaneous screening and quantitative analysis for multiple compounds are needed. In this study, we established a method of identifying fragmentation ions of 45 compounds for weight loss using liquid chromatography and high-resolution mass spectrometry and developed a quantitation method through liquid chromatography and tandem mass spectrometry. Note that, 656 samples selected as health functional food, food, and illegal drug were applied. The detection rate of banned weight loss compounds in health functional food, food, and illegal drug was showed as 19.2, 27.3, 40.7%, respectively. Among them, sibutramine, sennoside A and B, ephedrine were most frequently detected in 237 samples that contained weight loss compounds. The detection range about sibutramine was 0.03-159.3 mg/g, sennoside was 0.1-97.6 mg/g, and ephedrine was 0.1-587.7 mg/g in the detected 237 samples. In addition, the unknown compounds not included in our simultaneous analysis method in some samples were identified as furosemide and chlorpheniramine. High selectivity of high resolution mass spectrometry combined with these fragmentation pathways and tandem mass spectrometry methods can be successfully applied to screening and identifying 45 weight loss compounds for continuous blocking and supervision of illegally distributed health functional food, food, and illegal drug.

Hyperthermia accelerates neuronal loss differently between the hippocampal CA1 and CA2/3 through different HIF­1α expression after transient ischemia in gerbils.

The hippocampus has a different vulnerability to ischemia according to the subfields CA1 to CA3 (initials of cornu ammonis). It has been reported that body temperature changes during ischemia affect the degree of neuronal death following transient ischemia. Hypoxia­inducible factor 1α (HIF­1α) plays a key role in regulating cellular adaptation to low oxygen conditions. In the present study, we investigated the pattern of neuronal death (loss) in CA1 and CA2/3 following 5 min transient forebrain ischemia (TFI) under hyperthermia (39.5±0.2˚C) and the relationship between neuronal death and changes in HIF­1α expression using western blot analysis and immunohistochemistry in gerbils. Normothermia or hyperthermia was induced for 30 min before and during the TFI, and neuronal death and HIF­1α expression were observed at 0, 3, 6 and 12 h, 1, 2 and 5 days after TFI. Under normothermia, TFI­induced neuronal death of CA1 pyramidal neurons occurred on day 5 after TFI, but CA2/3 pyramidal neurons did not die. In contrast, under hyperthermia, the death of CA1 and CA2/3 pyramidal neurons was observed on day 2 after TFI. Under normothermia, HIF­1α expression was significantly elevated in both CA1 and CA2/3 pyramidal neurons at 12 h and 1 day after TFI, and the increased HIF­1α immunoreactivity in CA1 was dramatically reduced from 2 days after TFI, but not in CA2/3 pyramidal neurons. Under hyperthermia, the basal expression of HIF­1α in the sham group was significantly higher in both CA1 and CA2/3 pyramidal neurons at 0 h after TFI than in the normothermia group. HIF­1 expression was continuously higher, peaked at 12 h after TFI, and then significantly decreased from 1 day after TFI. Overall, the present results indicate that resistance to ischemia in CA2/3 pyramidal neurons is closely associated with the persistence of increased expression of HIF­1α after ischemic insults and that hyperthermia­induced exacerbation of death of pyramidal neurons is closely related to decreased HIF­1α expression after ischemic insults.

Pattern of change of C-reactive protein levels and its clinical implication in patients with acute poisoning.

OBJECTIVES: C-reactive protein is well known as an inflammatory indicator in injury, infection, and cancer. However, little is known about its role in poisoning. C-reactive protein levels first increase and then decrease within several days during poisoning management. This study aimed to verify the C-reactive protein change pattern and its clinical co-infection possibility in patients with poisoning. METHODS: Daily C-reactive protein levels of the patients with poisoning, who were admitted for more than 5 days, were measured. Microbial cultures were conducted, and fever (⩾38°C) and infection-related symptoms were investigated. RESULTS: In the enrolled 56 patients, the initial median C-reactive protein levels at hospital day 1, 2, 3, 4, and 5 were 0.28, 4.85, 10.91, 10.57, and 6.68 mg/dL, respectively. C-reactive protein level was the highest at hospital day 3 and decreased thereafter. No statistical difference was observed in the daily and maximal C-reactive protein levels between the culture-positive and culture-negative groups. The levels at hospital days 3-5 and the maximal level were 8.4, 9.2, 5.49, and 11.02 mg/dL, respectively, in non-fever group. The levels at hospital days 3-5 and the maximal level were 7.4, 9.2, 4.74, and 10.81 mg/dL, respectively, in non-symptoms group. Levels at hospital days 3-5 and the maximal level were 5.21, 4.93, 3.7, and 5.28 mg/dL, respectively, in all-negative (culture-negative without fever or infection symptoms) group. CONCLUSIONS: Acute rise and fall of C-reactive protein levels can be observed in the infection-unlikely patients with poisoning. The levels were similar to bacterial infection levels, possibly due to the drug reaction itself, rather than for superimposed infections.