Timing of lactational oestrus in intermittent suckling regimes: consequences for sow fertility

Three intermittent suckling (IS) regimes were evaluated for their effects on lactational oestrus and subsequent fertility. Control sows were weaned (CW; n = 38) at d 26 ± 2 of lactation. In IS19-7D (n=40) and IS19-14D (n=42) sows, IS started at d 19 ± 1 of lactation and sows were weaned 7 or 14 d later. In IS26-7D (n=41), IS started at d 26 ± 1 of lactation and sows were weaned 7d later. During IS, sows were separated from their piglets for 10h/day. Oestrus detection was performed twice daily without a boar and ovulation was confirmed by ultrasound once a week. In IS19-7D, IS19-14D and IS26-7D, respectively, 50%, 64% and 61% of the sows showed oestrus and ovulation during IS (P>0.05), and, of the remaining sows, 100%, 93%, and 69% showed oestrus in the first week after weaning. In CW sows, 95% showed oestrus in the first week after weaning. Parity 1 sows were considerably less likely than older parities (23% vs. 68%) to show oestrus in lactation. Pregnancy rate of the first post partum oestrus (during lactation or after weaning) was 89% (CW), 92% (IS19-7D), 80% (IS19-14D) and 77% (IS26-7D) (P>0.05) and subsequent litter size was 14.5 ± 0.5, 14.5 ± 0.6, 15.3 ± 0.5 and 15.2 ± 0.8, respectively (P>0.05). Sows mated during lactation had similar pregnancy rate and litter size to those mated after weaning. Hence, ongoing lactation for the first 2-9 d of pregnancy did not negatively affect fertility. A total of 50-64% of IS sows showed lactational oestrus, regardless of the stage of lactation. Pregnancy rates and litter size were similar to control sows, and were not affected by stage of lactation at mating.     

Application-oriented deep learning model for early warning of rice blast in Taiwan

Rice blast is one of the most devastating diseases that threatens rice production in Taiwan. A rice blast forecasting model is required to guide the precise application of fungicide. Therefore, BlastGRU-TW model based on deep learning algorithms was developed in this study. The input data comprised approximately 1000 rice blast surveys, collected from 50 fields throughout Taiwan between 2014 and 2021, and the corresponding weather data retrieved from weather observation network in Taiwan. Common and easily accessible meteorological factors, i.e. temperature, humidity, precipitation, and wind, were converted into 20 daily meteorological features which were coupled with different time intervals between 1 and 30 days before survey (DBS) to train the model. The results showed that seven meteorological features (daily maximum temperature, daily mean temperature, daily minimum temperature, daily mean humidity, daily mean WV and daily mean Wu) and the interval from −4 to −24 DBS were informative in disease prediction, thereby indicating that the proposed model could predict the risk of rice blast by using meteorological data 4–24 days before new disease symptoms appeared. The proposed BlastGRU-TW model achieved an accuracy of 87.3%. Furthermore, on adding the 3 day forecast weather data from Weather Research and Forecasting (WRF) model in the proposed model, the forecast extended to 7 days ahead of the appearance of new symptoms. Moreover, the BLASTAM model developed in Japan was implemented and validated in Taiwan to evaluate its applicability in different geographical areas. Finally, a rice blast early warning system (https://mycolab.pp.nchu.edu.tw/blast_forecast/index_en.php) equipped with an interactive web-based map is now available for real-time forecasting of the risk of rice blast in paddy field across Taiwan.     

Post-partum oestrus in the sow in relation to the concentration of plasma oestrogens.

Ten sows, three entire and seven which had been ovariectomized at different stages of late gestation, were observed for post-partum oestrus. Serial blood samples were collected from six sows during the pre-and post-partum periods, and plasma oestrogen concentrations determined by radioimmunoassay. Morphological aspects of ovarian activity in the entire sows were examined at laparotomy and at autopsy. Although peak values of oestrogen concentration in the plasma varied from 3-9 to 8-0 ng/ml between individuals, the pattern of oestrogen levels was similar for control and ovariectomized sows. Peak concentrations occurred just before parturition, and the timing of ovariectomy did not affect the incidence of the oestrogen peak. Oestrus was detected in one control and one ovariectomized sow at 46 and 40 hr post partum respectively, there being no evidence of ovarian activity in the entire sows. The occurrence of post-partum oestrus in a sow ovariectomized at Day 108 of gestation indicates that this phenomenon is not directly connected with ovarian secretion of oestrogens. The post-partum oestrus is apparently a result of the peak of feto-placental oestrogens that occurs at parturition.     

基于环境DNA-宏条形码技术的水生生态系统入侵生物的早期监测与预警

外来生物入侵是继生境破坏后造成生物多样性丧失的第二大威胁因素, 已对入侵地的生态安全、经济和社会发展及人类健康等造成严重负面影响, 成为21世纪五大全球性环境问题之一。作为水产养殖、航运和水生宠物交易大国, 我国水生生态系统的生物入侵问题尤为严重。研究表明, 系统地构建并应用早期监测预警技术是防控水生生态系统生物入侵最有效的途径。和陆生生物相比, 水生生物群落的物种繁多、群落结构复杂、生物形体微小且在入侵初期群体规模极小、隐匿于水下、可用于物种鉴定的外部形态缺乏, 使得在水生生态系统中构建并应用早期监测和预警体系在技术层面更具挑战。随着高通量测序技术的快速发展, 环境DNA-宏条形码技术成为构建水生生态系统入侵生物早期监测与预警技术的首选。本文主要综述了基于环境DNA-宏条形码技术的水生生态系统入侵生物的早期监测与预警技术方法; 解析了环境DNA-宏条形码监测系统的应用现状、技术优势; 着重探讨了影响监测结果准确性的I型和II型错误及其产生原因, 并为避免两类错误提供了可行的优化/改进方案; 最后对该方法在水生入侵生物监测中的应用前景进行了展望。     

Malaria early warning in Kenya

Kenya displays large spatiotemporal diversity in its climate and ecology. It follows that malaria transmission will reflect this environmental heterogeneity in both space and time. In this article, we discuss how such heterogeneity, and its epidemiological consequences, should be considered in the development of early warning systems for malaria epidemics.     

A corticothalamic circuit model for sound identification in complex scenes

The identification of the sound sources present in the environment is essential for the survival of many animals. However, these sounds are not presented in isolation, as natural scenes consist of a superposition of sounds originating from multiple sources. The identification of a source under these circumstances is a complex computational problem that is readily solved by most animals. We present a model of the thalamocortical circuit that performs level-invariant recognition of auditory objects in complex auditory scenes. The circuit identifies the objects present from a large dictionary of possible elements and operates reliably for real sound signals with multiple concurrently active sources. The key model assumption is that the activities of some cortical neurons encode the difference between the observed signal and an internal estimate. Reanalysis of awake auditory cortex recordings revealed neurons with patterns of activity corresponding to such an error signal.     

An early warning system for aquatic environment state monitoring based on an analysis of mussel valve movements

An early warning system for biological monitoring of aquatic environment is proposed, which is based on an analysis of mussel valve movements. It consists of an analog monitor of an original design (analog recorder and analyzer of opening/closing of valves in a group of mussels) and outside devices (multimeters, computers, and mobile phones). In the monitor, an analysis of the state of valve position sensors, summing/averaging of voltage values, and generation of a warning signal are performed in the analog mode. The proposed system (a) diagnoses the state of valve position sensors, (b) determines the voltage representing the average valve opening in a group of mussels (6–12 individuals), (c) generates a warning signal; and, by means of peripheral devices, (d) registers the average voltage of sensors and (e) transmits a warning signal via a mobile communication net. The system can provide an addition (and, sometimes, an alternative) to complicated digital systems analogous to MosselMonitor®.     

A simple bioluminescence procedure for early warning detection of coliform bacteria in drinking water

Traditional cultivation-dependent tests for coliform bacteria in food and drinking water take 18–24 h to complete. Bioluminescence-based enzyme assays can potentially reduce analysis time for indicator bacteria such as coliforms. In the present study, we developed a simple presence/absence (P/A) bioluminescence procedure for rapid detection of coliform bacteria in groundwater-based drinking water. The bioluminescence procedure targeting β-d-galactosidase activity in coliform bacteria was based on hydrolysis of 6-O-β-galactopyranosyl-luciferin. Bacteria immobilized on membrane filters were enriched for 6–8 h in selective media containing isopropyl-β-d-thiogalactopyranoside (IPTG) to induce β-d-galactosidase activity in coliform bacteria. The equivalent of approximately 300 E. coli cells was required for bioluminescence detection of β-d-galactosidase activity. In comparison, PCR based detection of E. coli in drinking water required approximately 30 target cells. Analysis of contaminated drinking water samples showed comparable results for coliform bacteria using traditional multiple-tube fermentation, Colilert-18, and the bioluminescence procedure. Aeromonas hydrophila or indigenous groundwater bacteria did not interfere with the procedure. The bioluminescence procedure can be combined with commercial substrates such as Fluorocult or Colilert-18, and will allow the detection of one coliform in 100 ml drinking water within one working day. The results suggest the bioluminescence assays targeting β-d-galactosidase activity may be used for or for early warning screening of drinking water and/or rapid identification of contaminated drinking water wells.     

Spontaneous electromyographic activity throughout the cycle in the sow and its change by intrauterine oestrogen infusion during oestrus

Two experiments were carried out to monitor influences on the uterine electromyographic activity (EMG) in cyclic gilts with chronic uterine EMG electrodes. In Exp. 1 the EMG was recorded continuously from Day -1 for 24 days and was evaluated for frequency, duration and amplitude. Progesterone and oestradiol in peripheral plasma were measured daily. As high amounts of oestrogens are characteristic for boar semen, in Exp. 2 the influence of seminal oestrogens on uterine contractions at Day 0 (first day of standing reflex) was investigated in gilts with chronic intrauterine catheters. They were infused with 10 ml saline (N = 4) or saline with physiological amounts of oestrogens (5 micrograms oestradiol + 2 micrograms oestrone + 4.5 micrograms oestrone sulphate; N = 4). Sham-treated gilts (infusion catheters, no infusion; N = 5) served as controls. The EMG was recorded for 2 h before and 9 h after infusion. In Exp. 1 the maximal amplitude (2040 +/- 98 microV) and duration (32 +/- 1.7 sec) but the lowest frequency (15.8 +/- 2.1 contractions/h) were found on Day 0. With decreasing oestrogen and increasing progesterone concentrations the frequency increased continuously until Day 5 (63.5 +/- 1.0 contractions/h) while the amplitude (183 +/- 13 microV) and duration (3.3 +/- 0.7 sec) decreased. During Days 6-13 the EMG activity was not detectable. The reverse pattern was found from the onset of luteolysis until the following Day 0. On Day 0 a significant correlation between oestradiol and the duration (r = 0.81; P less than 0.01; n = 10) but not the frequency was observed.(ABSTRACT TRUNCATED AT 250 WORDS)     

A simple model for early morphogenesis

Despite the large amount of knowledge which continues to accumulate about early developmental events, very little is known about the processes which control them. Part of the problem may lie in that workers applying different approaches and techniques have different points of view and appear to be reluctant to read each others' literature. My aim in this paper is not to give a generative, formal model for early development, but rather to suggest several connecting strands between the physiological, biochemical, cell biological and experimental embryological approaches which may stimulate new research in fields between those already exploited.     

A multistate model for early decision-making in oncology

The development of oncology drugs progresses through multiple phases, where after each phase, a decision is made about whether to move a molecule forward. Early phase efficacy decisions are often made on the basis of single-arm studies based on a set of rules to define whether the tumor improves (“responds”), remains stable, or progresses (response evaluation criteria in solid tumors [RECIST]). These decision rules are implicitly assuming some form of surrogacy between tumor response and long-term endpoints like progression-free survival (PFS) or overall survival (OS). With the emergence of new therapies, for which the link between RECIST tumor response and long-term endpoints is either not accessible yet, or the link is weaker than with classical chemotherapies, tumor response-based rules may not be optimal. In this paper, we explore the use of a multistate model for decision-making based on single-arm early phase trials. The multistate model allows to account for more information than the simple RECIST response status, namely, the time to get to response, the duration of response, the PFS time, and time to death. We propose to base the decision on efficacy on the OS hazard ratio (HR) comparing historical control to data from the experimental treatment, with the latter predicted from a multistate model based on early phase data with limited survival follow-up. Using two case studies, we illustrate feasibility of the estimation of such an OS HR. We argue that, in the presence of limited follow-up and small sample size, and making realistic assumptions within the multistate model, the OS prediction is acceptable and may lead to better early decisions within the development of a drug.     

A spike-based model of binaural sound localization

This paper describes a spike-based model of binaural sound localization using interaural time differences (ITDs). To handle the problem of temporal coding and to facilitate a hardware implementation all neurons are simulated by a spike response model, which includes postsynaptic potentials (PSPs) and a refractory period. A winner-take-all (WTA) network selects the dominant source from the representation of the sound's angles of incidences, and can be biased by a multisensory support. We use simulations on real audio data to investigate the function and the practical application of the system.     

Comparing models for early warning systems of neglected tropical diseases

Background

Early warning systems (EWS) are management tools to predict the occurrence of epidemics of infectious diseases. While climate-based EWS have been developed for malaria, no standard protocol to evaluate and compare EWS has been proposed. Additionally, there are several neglected tropical diseases whose transmission is sensitive to environmental conditions, for which no EWS have been proposed, though they represent a large burden for the affected populations.

Methodology/Principal Findings

In the present paper, an overview of the available linear and non-linear tools to predict seasonal time series of diseases is presented. Also, a general methodology to compare and evaluate models for prediction is presented and illustrated using American cutaneous leishmaniasis, a neglected tropical disease, as an example. The comparison of the different models using the predictive R ² for forecasts of “out-of-fit” data (data that has not been used to fit the models) shows that for the several linear and non-linear models tested, the best results were obtained for seasonal autoregressive (SAR) models that incorporate climatic covariates. An additional bootstrapping experiment shows that the relationship of the disease time series with the climatic covariates is strong and consistent for the SAR modeling approach. While the autoregressive part of the model is not significant, the exogenous forcing due to climate is always statistically significant. Prediction accuracy can vary from 50% to over 80% for disease burden at time scales of one year or shorter.

Conclusions/Significance

This study illustrates a protocol for the development of EWS that includes three main steps: (i) the fitting of different models using several methodologies, (ii) the comparison of models based on the predictability of “out-of-fit” data, and (iii) the assessment of the robustness of the relationship between the disease and the variables in the model selected as best with an objective criterion.     

Effects of continuous elevated cortisol concentrations during oestrus on concentrations and patterns of progesterone, oestradiol and LH in the sow

This study investigated the effect of continuous elevated cortisol concentrations during standing oestrus on time of ovulation and patterns of progesterone, oestradiol and luteinising hormone (LH) in sows. The elevation of cortisol concentrations was achieved through repeated intravenous injections of synthetic adrenocorticotropic hormone (ACTH) every 2 h for approximately 48 h, from the onset of the second standing oestrus after weaning. Treatment was terminated when ovulation was detected (monitored by transrectal ultrasonography every 4h) or when the sow had received a maximum of 24 injections. The dose of ACTH (2.5 microg/kg) was chosen to mimic the cortisol concentrations seen during mixing of unfamiliar sows. The sows (n=14) were surgically fitted with jugular vein catheters and randomly divided into a control (C group where only NaCl solution were injected) or an ACTH group. Blood samples were collected every 2 h. In parallel with the blood sampling, saliva samples for cortisol analyses were taken from eight sows before onset of treatment and from four of the sows during treatment. There was no difference in time from onset of standing oestrus to ovulation between the two groups. The interval between the peaks of oestradiol and LH to ovulation was prolonged in the ACTH group compared to the C group (p<0.05), with a tendency towards an earlier decline of oestradiol in the ACTH group. Cortisol and progesterone concentrations were significantly elevated during treatment in the ACTH group (p<0.001), with cortisol peak concentrations occurring between 40 and 80 min after each ACTH injection. Cortisol concentrations in saliva and plasma were highly correlated (p<0.001). In conclusion, elevated cortisol concentrations from the onset of standing oestrus increase progesterone concentrations and prolong the interval between oestradiol and LH peaks to ovulation, the latter possible due to an early decline in oestradiol concentrations and a change of the LH peak outline. The effect these hormonal changes have on reproductive performance need to be further investigated. Saliva samples might be a useful and non-invasive method to assess cortisol concentrations in sows.