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The bigfin reef squid (Sepioteuthis lessoniana) is a valuable commercial species, especially in East Asia. While small-scale cultivation exists, efforts to achieve large-scale aquaculture are underway. However, full-life cycle aquaculture remains challenging due to reproductive issues, particularly in later generations, where abnormal offspring production is common. One possible issue is sex reversal under culture conditions, possibly due to high temperatures and smaller egg sizes in later generations. Therefore, a reliable method to determine the genetic sex of bigfin reef squid is crucial. Analysis of the female and male genome coverage along the assembly confirms a ZZ/Z0 female hemizygous sex-determination system in bigfin reef squid. We identified Z chromosome linked regions and developed a quantitative PCR (qPCR)-based method to measure the copy number variance of these Z-specific regions, normalized by autosomal regions, with ratios of 1:0.5 in ZZ males and Z0 females, respectively. Among the primer pairs designed for qPCR, two primer pairs in Z-specific regions and one primer pair in autosomal region exhibited a single melting curve (indicating the predicted same fragment) across all lineages. This genetic sexing method was validated in samples from different populations across Taiwan, demonstrating its effectiveness in determining the genetic sex of bigfin reef squid. Our findings provide a valuable tool for aquaculture management and offer new insights into sex determination mechanisms in cephalopods.

This paper uses Long Short-Term Memory (LSTM) networks to predict the stock prices of the Yuanta Taiwan Top 50 ETF (ETF50). To improve the accuracy of the model’s predictions, a calibration procedure called “Short-Term Bias Compensation” (STBC) is proposed to adjust the predicted stock prices. In STBC, the daily prediction error is calculated to estimate the short-term bias (STB) in prediction. Then, the predicted price of its next day will be corrected if this STB has exceeded a certain threshold. In this paper, we apply Genetic Algorithms (GAs) to optimize the parameters used in STBC for providing more confidence in its estimation. Based on these predicted stock prices, we propose a Genetic Fuzzy System (GFS) to determine the trading strategy, with trading points for buying and selling stocks. In GFS, various technical indicators are used to establish the fuzzy rules of the trading strategy, and GAs are used to evolve the best parameters for these fuzzy rules. Our experiments cover over 17 years of data (from 2003 to 2020) for ETF50 to consider black swan events such as the 2020 COVID-19 pandemic, the 2018 US–China trade war, and the 2011 US debt crisis. The first 90% of the data is used as training data, and the last 10% is used as testing data. We use 12 technical indicators of these data as the input of LSTM. The predicted values of LSTM are corrected using STBC and compared to the uncorrected prices. We use Mean Square Error (MSE) to evaluate the prediction accuracy. The results show that STBC can nearly reduce 90% of the prediction error (where MSE drops from 11.5758 to 1.2687). By using GFS with STBC to determine trading points, we achieve a return rate of 32.0%.

Abstract Background Stroke may cause debilitating neurological deficiencies that result in motor, sensory, and cognitive deficits and poorer psychosocial functioning. Prior studies have provided some initial evidence for the significant roles of health literacy and poor oral health for old people. However, few studies have focused on the health literacy of individuals who had a stroke; therefore, the relationships between the health literacy and oral health-related quality of life (OHRQoL) among middle-aged and older adults who had a stroke are unknown. We aimed to assess the relationships between stroke prevalence, health literacy status, and OHRQoL in middle-aged and older adults. Methods We retrieved the data from The Taiwan Longitudinal Study on Aging, a population-based survey. For each eligible subject, we gathered data in 2015 on age, sex, level of education, marital status, health literacy, the activity daily living (ADL), stroke history and OHRQoL. We evaluated the respondents’ health literacy by using a nine-item health literacy scale and categorized their health literacy level as low, medium, or high. OHRQoL was identified based on the Taiwan version of the Oral Health Impact Profile (OHIP-7T). Results The final study contained 7702 community-based dwelling elderly people (3630 male and 4072 female) were analysis in our study. Stroke history was reported in 4.3% of participants, 25.3% reported low health literacy, and 41.9% had at least one ADL disability. Furthermore, 11.3% of participants had depression, 8.3% had cognitive impairment, and 3.4% had poor OHRQoL. Age, health literacy, ADL disability, stroke history, and depression status were significantly associated with poor OHRQoL after sex and marital status was adjusted. Medium (odds ratio [OR] = 1.784, 95% confidence interval [CI] = 1.177, 2.702) to low health literacy (OR = 2.496, 95% CI = 1.628, 3.828) was significantly associated with poor OHRQoL. Conclusions Base our study results, people with stroke history had poor OHRQoL. Lower health literacy and ADL disability were associated with worse QHRQoL. Further studies are necessary to define practical strategies for reducing the risk of stroke and oral health with constantly lower health literacy, thereby improving the quality of life and providing health care of older people.

IoT content usually comes from power-constrained sensors and requires applying different levels of protection. We design a bounded-error-pruned IoT content market (BIoTCM) framework with preserving privacy protection (BEPDPP) scheme using blockchain smart contract. According to payment level applied in smart contract of BIoTCM, our BEPDPP will prune original data within a given level of bounded-error to provide different resolutions of content for consumers. As the real data is intrinsically hidden, content protection is provided with privacy-preserving. Experimental results generated by five different types of IoT content demonstrate that our content protection solution is cost-effective in sensor lifetime.

Although most indoor positioning systems use radio waves, such as Wi-Fi, Bluetooth, or RFID, for application in department stores, exhibition halls, stations, and airports, the accuracy of such technology is easily affected by human shadowing and multipath propagation delay. This study combines the earth’s magnetic field strength and Wi-Fi signals to obtain the indoor positioning information with high availability. Wi-Fi signals are first used to identify the user’s area under several kinds of environment partitioning methods. Then, the signal pattern comparison is used for positioning calculations using the strength change in the earth’s magnetic field among the east–west, north–south, and vertical directions at indoor area. Finally, the k-nearest neighbors (KNN) method and fingerprinting algorithm are used to calculate the fine-grained indoor positioning information. The experiment results show that the average positioning error is 0.57 m in 12-area partitioning, which is almost a 90% improvement in relation to that of one area partitioning. This study also considers the positioning error if the device is held at different angles by hand. A rotation matrix is used to convert the magnetic sensor coordinates from a mobile phone related coordinates into the geographic coordinates. The average positioning error is decreased by 68%, compared to the original coordinates in 12-area partitioning with a 30-degree pitch. In the offline procedure, only the northern direction data are used, which is reduced by 75%, to give an average positioning error of 1.38 m. If the number of reference points is collected every 2 m for reducing 50% of the database requirement, the average positioning error is 1.77 m.

Abstract Background The postoperative severity of symptoms among women with breast cancer affects their quality of life (QoL). Although it is recommended that performing shoulder-arm exercise 30 min/day can alleviate symptoms and improve the QoL, there is little research on the mediating effects of performing shoulder-arm exercise 30 min/day on the postoperative severity of symptoms and QoL among patients with breast cancer. Methods A cross-sectional study was conducted 2 ~ 4 months after surgery on women diagnosed with breast cancer but with no distant metastasis and who had undergone breast cancer surgery for the first time. A structured questionnaire was employed which included a severity of symptoms scale, performing shoulder-arm exercise for 30 min/day, a QoL scale, demographic characteristics, and medical status. Results In total, 117 women with breast cancer completed the survey. The severity of symptoms and performing shoulder-arm exercise 30 min/day separately affected the QoL (B = -0.447, standard error (SE) = 0.050, p

Background and PurposeIn this study, we aimed to evaluate the relationship between tinnitus and a subsequent diagnosis of major depressive disorder (MDD) by studying the incidence of both entities.DesignA retrospective cohort study.MethodsData for this observational follow-up study were retrieved from the Taiwan's National Health Insurance Dataset. A total of 375,272 patients with newly diagnosed tinnitus (study group) were retrieved. The date of first diagnosis of tinnitus was assigned as their index date. Comparison patients were selected by propensity score matching (one per case, n = 375,272 controls) from the same dataset, with their index date being the date of their first health service claim in the year of diagnosis of their matched index case. We tracked each patient's claims records for 1 year from the index date to identify those who received a diagnosis of MDD. Cox proportional hazards regression was performed to calculate the MDD hazard ratio for cases vs. controls.ResultsWe found that the overall incidence rate for MDD was 0.78 (95% CI = 0.76~0.80) per 100 person-years, being 1.17 (95% CI = 1.14~1.21) among the study cohorts and 0.38 (95% CI = 0.36~0.40) among the comparison cohorts. The log-rank test revealed that the patients in the study cohort had significantly lower one-year MDD-free survival when compared to the comparison cohort (p < 0.001). Cox proportional hazards analysis showed that the patients in the study cohort had a higher hazard of developing MDD than the patients in the comparison cohort (adjusted HR = 3.08, 95% CI = 2.90~3.27).ConclusionsIn this study, we demonstrate that tinnitus is associated with an increased hazard of subsequent MDD in Taiwan.

Central line-associated bloodstream infections are frequent, deadly, costly, and preventable. The study aimed to explore how some hospital-related characteristics were associated with incidence rates of central line-associated bloodstream infections reported by community hospitals in California from January to December 2019. This retrospective, cross-sectional study used combined data from records submitted to the California Department of Public Health, California Open Data Portal, the California Health and Human Services Open Data Portal, and the American Hospital Directory by community hospitals in California with central line-associated bloodstream infections in 2019. Results showed that CLABSIs are significantly associated with bed capacity, health care system affiliation, ownership, and hospital accreditation status (p < 0.0001). CLABSI remains a relevant threat to patient safety and quality of care, even more so in the community hospital setting. Understanding if a relationship exists between institutional factors and CLABSI rates might better prepare leaders in healthcare organizations to reduce HAIs.

Nowadays, many old analog gauges still require the use of manual gauge reading. It is a time-consuming, expensive, and error-prone process. A cost-effective solution for automatic gauge reading has become a very important research topic. Traditionally, different types of gauges have their own specific methods for gauge reading. This paper presents a systematized solution called SGR (Scale-mark-based Gauge Reading) to automatically read gauge values from different types of gauges. Since most gauges have scale marks (circular or in an arc), our SGR algorithm utilizes PCA (principal components analysis) to find the primary eigenvector of each scale mark. The intersection of these eigenvectors is extracted as the gauge center to ascertain the scale marks. Then, the endpoint of the gauge pointer is found to calculate the corresponding angles to the gauge’s center. Using OCR (optical character recognition), the corresponding dial values can be extracted to match with their scale marks. Finally, the gauge reading value is obtained by using the linear interpolation of these angles. Our experiments use four videos in real environments with light and perspective distortions. The gauges in the video are first detected by YOLOv4 and the detected regions are clipped as the input images. The obtained results show that SGR can automatically and successfully read gauge values. The average error of SGR is nearly 0.1% for the normal environment. When the environment becomes abnormal with respect to light and perspective distortions, the average error of SGR is still less than 0.5%.

According to the ever-growing supply and demand of IoT content, IoT big data in diversified applications are deemed a valuable asset by private and public sectors. Their privacy protection has been a hot research topic. Inspired by previous work on bounded-error-pruned IoT content market, we observe that the anonymity protection with robust watermarking can be developed by further pruning data for better resource-efficient IoT big data without violating the required quality of sensor service or quality of decision-making. In this paper, resource-efficient anonymity protection with watermarking is thus proposed for data consumers and owners of IoT big data market via blockchain. Our proposed scheme can provide the IoT data with privacy protections of both anonymity and ownership in IoT big data market with resource efficiency. The experiments of four different-type IoT datasets with different settings included bounded-errors, sub-stream sizes, watermark lengths, and ratios of data tampering. The performance results demonstrated that our proposed scheme can provide data owners and consumers with ownership and anonymity via watermarking the IoT big data streams for lossless compressibility. Meanwhile, the developed DApp with our proposed scheme on the Ethereum blockchain can help data owners freely share and trade with consumers in convenience with availability, reliability, and security without mutual trust.

Bluetooth Low Energy (BLE) is a positioning technology that is commonly used in indoor positioning systems (IPS) such as shopping malls or underground parking lots, because of its low power consumption and the low cost of Bluetooth devices. It also maintains high positioning accuracy. Since the cost of BLE itself is low, it has now been used in larger environments such as parking lots or shopping malls for a long time. However, it is necessary to configure a large number of devices in the environment to obtain accurate positioning results. The most accurate method of using signal strength for positioning is the signal pattern-matching method. The positioning result is compared through a database with the overheads of time and labor costs, since the amount of data will be proportional to the size of the environment for BLE-IPS. A planar model that conforms to the signal strength in the environment was generated, wherein the database comparison method is replaced by an equation solution, to improve various costs but diminish the positioning accuracy. In this paper, we propose to further replace the planar model with a cost-effective fitting model to both save costs and improve positioning accuracy. The experimental results demonstrate that this model can effectively reduce the average positioning error in distance by 31%.

To improve our knowledge of the migration pathway of a highly threatened fish species along the Mekong River, strontium isotope ratios (87Sr/86Sr) and 18 trace element concentrations were measured in the water and in the otoliths of an anadromous catfish, Pangasius krempfi, to infer its natal origin and potential migration pathways. Water was sampled at 18 locations along the mainstream, tributaries and distributaries of the Mekong River. To check for accuracy and precision, measurements of the 87Sr/86Sr ratios and trace element concentrations were then compared in two laboratories that use different analytical methods. Differences in trace element concentrations between locations were not significant and could not, therefore, be used to discriminate between migration pathways. However, the Mekong mainstream, tributaries and distributaries could all be discriminated using Sr isotopes. The 87Sr/86Sr profiles recorded in P. krempfi otoliths showed that there were three contingents with obligate freshwater hatching and variable spawning sites along the Mekong mainstream, from Phnom Penh (Cambodia) to Nong Khai (Thailand) or further. After hatching, the fish migrated more or less rapidly to the Mekong Delta and then settled for most of their lifetime in brackish water. Spawning habitats and migration routes may be threatened by habitat shifts and the increasing number of hydropower dams along the river, especially the contingents born above Khone Falls (Laos). The conservation of P. krempfi, as well as other migratory fish in the Mekong River, requires agreements, common actions and management by all countries along the Mekong River. This study highlighted the importance of using both Sr/Ca and 87Sr/86Sr ratios to understand life history of anadromous fishes as the 87Sr/86Sr ratio in the water was shown to be less effective than the Sr/Ca ratio in identifying movements between different saline areas.

Depression in older population is more common now. Due to increasing numbers of older patients in hospitals, nurses have more opportunities to care for these patients. Therefore, nurses should have correct knowledge of late-life depression and more favorable attitudes about depression. The study aimed to understand hospital nurses’ knowledge level of late-life depression and attitudes about depression. A cross-sectional research design was used. A convenience sample of 307 nurses from 3 hospitals in Taiwan was recruited. Nurses scored 55.15% in the Late-Life Depression Quiz. The average score of the Revised Depression Attitude Questionnaire was 71.76 (SD = 6.13). The study also found that hospital nurses had more favorable attitudes about depression when their late-life depression knowledge was higher; their interest level in providing care for older patients with depression was greater; they had ever taken care of older patients with depressive symptoms or depression; they had never received in-service training on depression in the past year; and they had ever attended lectures about depression in school. Hospital nurses’ knowledge about late-life depression was limited, and they had neutral to slightly favorable attitudes about depression in Taiwan. It is suggested to carefully examine and evaluate in-service training related to depression for nurses in hospitals. In addition, developing appropriate interventions to increase hospital nurses’ knowledge level of late-life depression and attitudes toward depression is recommended.

Sepioteuthis lessoniana is a widely distributed neritic squid in the Indo-Pacific Ocean. It is an important species in fisheries, but species management is difficult because of inadequate information regarding its life history. The daily growth and δ18O values from the core to the edge of statoliths of S. lessoniana collected in northern Taiwan were analyzed to predict the experienced temperature history along with ontogenetic stages. The probability of occurrence in a given area at each life stage in three seasonal groups was determined using salinity values, deduced and measured temperatures, and the known ecology of S. lessoniana. The results showed that ontogenetic variation in the statolith δ18O values in S. lessoniana reflected the seasonal temperature fluctuation observed in Taiwanese waters, which indicated the reliability of the prediction method. Complex and diverse distribution and movement patterns were observed in the three seasonal groups. The results also indicated the importance of the waters near the coast of northeastern Taiwan as a spawning ground. Based on a model prediction, the distribution of S. lessoniana is likely associated with water temperature and current. A potential migration route from the Penghu Islands to northeastern Taiwan suggests a high level of population connectivity in S. lessoniana in Taiwan. This study provides information on the spatial and vertical distribution of S. lessoniana at various ontogenetic stages, which is essential for resource management and conservation of this commercial species.

Since the power of transmitting one-bit data is higher than that of computing one thousand lines of code in IoT (Internet of Things) applications, it is very important to reduce communication costs to save battery power and prolong system lifetime. In IoT sensors, the transformation of physical phenomena to data is usually with distortion (bounded-error tolerance). It introduces bounded-error data in IoT applications according to their required QoS2 (quality-of-sensor service) or QoD (quality-of-decision making). In our previous work, we proposed a bounded-error data compression scheme called BESDC (Bounded-Error-pruned Sensor Data Compression) to reduce the point-to-point communication cost of WSNs (wireless sensor networks). Based on BESDC, this paper proposes an online bounded-error query (OBEQ) scheme with edge computing to handle the entire online query process. We propose a query filter scheme to reduce the query commands, which will inform WSN to return unnecessary queried data. It not only satisfies the QoS2/QoD requirements, but also reduces the communication cost to request sensing data. Our experiments use real data of WSN to demonstrate the query performance. Results show that an OBEQ with a query filter can reduce up to 88% of the communication cost when compared with the traditional online query process.

Cuttlebone is a hard calcified structure that supports the cuttlefish body and aids in the regulation of buoyancy. The calcification rate of cuttlebone is high and is close to the growth rate of the cuttlefish mantle. The growth rate of the body mantle may strongly influence the incorporation of elements into the cuttlebone; however, the process has not been well studied. This is the first study to examine trace element incorporation into cuttlebone in detail. Controlled laboratory experiments and analyses of wild-caught cuttlefish revealed that both temperature and growth rate influence the elemental ratios of Li/Ca and Sr/Ca in cuttlebone. The variation in the elemental ratio was influenced the most by growth rates. After controlling for the minor influence of temperature, cuttlebone Li/Ca ratios appeared to be a potential proxy of cuttlefish growth. The relationship between growth rate and temperature-corrected Li/Ca ratios is positive and linear, and the trend does not vary between the sexes or across most of the life stages. In addition, the Li/Ca ratio is a promising growth rate proxy for evaluating differences among wild populations of cuttlefish, and the proxy could facilitate studies on cuttlefish biology and cuttlefish fisheries management.

The impact of urbanization on cataract incidence is still inconclusive. This study aimed to examine the association of urbanization and sunlight exposure with cataract incidence using a nationwide population-based database in Taiwan. The researchers used data retrieved from the Taiwan Longitudinal Health Insurance Database from 2001 to 2010 (LHID2010). The LHID2010 consists of medical claims data for reimbursement for 1 million individuals randomly selected from all enrollees (N = 23.25 million) in the Taiwan National Health Insurance (NHI) program in 2010. For adults aged over 40, we identified a total of 3080 people diagnosed with senile cataracts (ICD-9:360) and 393,241 people without senile cataracts in the LHID2010. In addition, sunlight exposure data between 2001 and 2011 were obtained from 28 meteorological stations of the Taiwan Central Weather Bureau. Logistic regression was performed to test the hypothesis. When controlled for the confounding factors, such as demographic factors, comorbidities, and sunlight exposure, the logistic regression results showed that those living in highly urbanized areas are more likely to suffer from senile cataracts (p < 0.001).

Free-range chicken farming allows egg-laying hens to move freely through their environment and perform their natural behavior, including laying her eggs. However, it takes time to gather these eggs manually, giving rise to high labor costs. This study proposes a smart mobile robot for poultry farms that can recognize eggs of two different colors on free-range farms. The robot can also pick up and sort eggs without damaging them. An egg feature extraction method with automatic thresholding is employed to detect both white and brown eggs, and a behavior-based navigation method is applied to allow the robot to reach the eggs while avoiding obstacles. The robot can move towards the position of each egg via visual tracking. Once the egg is within the collection area of the robot, it is gathered, sorted and stored in the tank inside the robot. Experiments are carried out in an outdoor field of size 5 m × 5 m under different climatic conditions, and the results showed that the average egg recognition rate is between 94.7% and 97.6%. The proposed mobile poultry robot is low in production cost and simple in operation. It can provide chicken farmers with automatic egg gathering on free-range farms.

Emerging IoT (Internet of Things) technologies have enjoyed tremendous success in a variety of applications. Since sensors in IoT consume a lot of energy to transmit their data, data compression used to prolong system lifetime has become a hot research topic. In many real-world applications, such as IEI (IoT of environmental intelligence), the required sensing data usually have limited error tolerance according to the QoS2 (quality of sensor service) or QoD (quality of decision-making) required. However, the bounded-error-pruned sensor data can achieve higher data correlation for better compression without jeopardizing QoS2/QoD. Moreover, the sensing data in widely spread sensors usually have strong temporal and spatial correlations. We thus propose a BESDC (bounded-error-pruned sensor data compression) scheme to achieve better leverage between the bounded error and compression ratio for sensor data. In this paper, our experiments on a sensor network of two-tier tree architecture consider four different environmental datasets including PM 2.5, CO, temperature and seismic wave with different scales of bounded errors. With the bounded errors required by the given IEI applications, our BESDC can reduce the total size of data transmission to minimize both energy consumption in sensor-tier devices and storage of fog-tier servers. The experimental results demonstrate that our BESDC can reduce transmission data by over 55% and save 50% energy consumption when assigning 1% of error tolerance within QoS2/QoD requirement. To the best of our knowledge, the proposed BESDC scheme can help other energy-efficient IoT schemes applying network topologies and routing protocols to further enhance energy-efficient IoT services.

ObjectiveResearch on publication trends in journal articles on sleep disorders (SDs) and the associated methodologies by using text mining has been limited. The present study involved text mining for terms to determine the publication trends in sleep-related journal articles published during 2000-2013 and to identify associations between SD and methodology terms as well as conducting statistical analyses of the text mining findings.MethodsSD and methodology terms were extracted from 3,720 sleep-related journal articles in the PubMed database by using MetaMap. The extracted data set was analyzed using hierarchical cluster analyses and adjusted logistic regression models to investigate publication trends and associations between SD and methodology terms.ResultsMetaMap had a text mining precision, recall, and false positive rate of 0.70, 0.77, and 11.51%, respectively. The most common SD term was breathing-related sleep disorder, whereas narcolepsy was the least common. Cluster analyses showed similar methodology clusters for each SD term, except narcolepsy. The logistic regression models showed an increasing prevalence of insomnia, parasomnia, and other sleep disorders but a decreasing prevalence of breathing-related sleep disorder during 2000-2013. Different SD terms were positively associated with different methodology terms regarding research design terms, measure terms, and analysis terms.ConclusionInsomnia-, parasomnia-, and other sleep disorder-related articles showed an increasing publication trend, whereas those related to breathing-related sleep disorder showed a decreasing trend. Furthermore, experimental studies more commonly focused on hypersomnia and other SDs and less commonly on insomnia, breathing-related sleep disorder, narcolepsy, and parasomnia. Thus, text mining may facilitate the exploration of the publication trends in SDs and the associated methodologies.

To evaluate the roles of plasma sTREM-1 (soluble triggering receptor expressed on myeloid cells-1) and C-reactive protein (CRP) in predicting treatment response in patients with community-acquired pneumonia (CAP). Methods: Patients with CAP were enrolled prospectively at a medical center in central Taiwan from September 1, 2004 to July 31, 2005. They were treated according to the guidelines proposed by the American Thoracic Society. Patients were noted as nonresponsive to initial treatment if they had one of the following: persistent fever for more than 3 days, progression on chest radiograph, switching to other antibiotics, or need of mechanical ventilation and/or chest tube drainage. Results: Fifty-eight patients (43 males/15 females; mean age, 67 ± 21 years) with CAP were enrolled. Twelve (12/58, 21%) were nonresponsive. In the response group, CRP was reduced up to 58% from day 1 to day 3 (from 18.8 to 7.8 mg/dL), whereas sTREM-1 was reduced by only 15% (from 32.8 to 28.1 pg/mL). In the nonresponse group, CRP still declined 20% (from 22.2 to 17.7 mg/dL), whereas sTREM-1 was persistently high (from 61.7 to 63.7 pg/mL). Using multivariate logistic regression analysis, both CRP (p = 0.006) and sTREM-1 (p = 0.046) on day 3 predicted treatment response significantly, but CRP on day 3 had stronger statistic power. Conclusion: Both CRP and sTREM-1 on day 3 could be useful in predicting nonresponsive CAP patients. Differential trends between sTREM-1 and CRP in nonresponsive CAP suggest that sTREM-1 could be an adjuvant biomarker to CRP in predicting CAP patients without response to empiric treatment. [J Formos Med Assoc 2007;106(3):187-195]

Otolith trace elements were used as natural tags to study the dispersal patterns of goby larvae in an estuary. Ninety-six larval gobies representing 10 species were collected in the estuary of Gongshytyan Creek in northwestern Taiwan in September 1997. Fifteen trace elements in fish otoliths were analysed with solution-based ICPMS. Trace elemental composition in otoliths differed significantly among the species. Habitat use by the larvae of the 10 species can be divided into four groups, based on principal component analysis of otolith elemental composition. All 10 goby species used the estuary as a nursery area irrespective of the fish being amphidromous or non-amphidromous. A part of the population may be lost during larval dispersal, as indicated from trace elemental composition recorded in the otolith.

The emerging multimedia Internet application IPTV over P2P network preserves significant advantages in scalability. IPTV media content delivered in P2P networks over public Internet still preserves the issues of privacy and intellectual property rights. In this paper, we use SIP protocol to construct a secure application-layer multicast overlay network for IPTV, called SIPTVMON. SIPTVMON can secure all the IPTV media delivery paths against eavesdroppers via elliptic-curve Diffie-Hellman (ECDH) key exchange on SIP signaling and AES encryption. Its load-balancing overlay tree is also optimized from peer heterogeneity and churn of peer joining and leaving to minimize both service degradation and latency. The performance results from large-scale simulations and experiments on different optimization criteria demonstrate SIPTVMON's cost effectiveness in quality of privacy protection, stability from user churn, and good perceptual quality of objective PSNR values for scalable IPTV services over Internet.

MicroRNAs (miRNAs) are small fragments of single-stranded RNA containing 18-24 nucleotides, and are generated from endogenous transcripts. MicroRNAs function in post-transcriptional gene silencing by targeting the 3'-untranslated region (UTR) of mRNAs, resulting in translational repression. We have developed a system to study the role of miRNAs in cell differentiation. We have found that one of the miRNAs tested in our system (miR-378, also called miR-378*) plays a role in modulating nephronectin-mediated differentiation in the osteoblastic cell line, MC3T3-E1. Nephronectin is an extracellular matrix protein, and we have demonstrated that its over-expression enhanced osteoblast differentiation and bone nodule formation. Furthermore, we found that the nephronectin 3'-untranslated region (3'UTR) contains a binding site for miR-378. Stable transfection of MC3T3-E1 cells with miR-378 inhibited cell differentiation. MC3T3-E1 cells stably transfected with nephronectin exhibited higher rates of differentiation and nodule formation as compared with cells transfected with nephronectin containing the 3'UTR in the early stages of development, suggesting that endogenous miR-378 is present and active. However, in the later stages of MC3T3-E1 development, the differentiation rates were opposite, with higher rates of differentiation and nodule formation in the cells over-expressing the 3'UTR of nephronectin. This appeared to be the consequence of competition between nephronectin and UDP-N-acetyl-alpha-D-galactosamine:polypeptide N-acetylgalactosaminyltransferase 7 (GalNAc-T7 or GalNT7) for miR-378 binding, resulting in increased GalNT7 activity, which in turn lead to increased nephronectin glycosylation and product secretion, thereby resulting in a higher rate of osteoblast differentiation.

Morphogenesis is crucial to initiate physiological development and tumor invasion. Here we show that a microRNA controls zonation morphogenesis by targeting hyaluronan receptor CD44. We have developed a novel system to study microRNA functions by generating constructs expressing pre-miRNAs and mature miRNAs. Using this system, we have demonstrated that expression of miR-328 reduced cell adhesion, aggregation, and migration, and regulated formation of capillary structure. Protein analysis indicated that miR-328 repressed CD44 expression. Activities of luciferase constructs harboring the target site in CD44, but not the one containing mutation, were repressed by miR-328. Zonation morphogenesis appeared in cells transfected by miR-328: miR-328-transfected cells were present on the surface of zonating structures while the control cells stayed in the middle. MiR-328-mediated CD44 actions was validated by anti-CD44 antibody, hyaluronidase, CD44 siRNA, and CD44 expression constructs. In vivo experiments showed that CD44-silencing cells appeared as layers on the surfaces of nodules or zonating structures. Immuno-histochemistry also exhibited CD44-negative cells on the surface layers of normal rat livers and the internal zones of Portal veins. Our results demonstrate that miR-328 targets CD44, which is essential in regulating zonation morphogenesis: silencing of CD44 expression is essential in sealing the zonation structures to facilitate their extension and to inhibit complex expansion.