The economic effect of cow-based reproductive management programs with a systematic use of reproductive hormones.

Hormone-based reproductive management programs can be beneficial to improve dairy cow's reproductive performance. This study aimed to compare the economic impact of reproductive management programs using systematic hormonal treatments to individual cows with a specific DIM range with a reproductive management program using cow-specific hormonal treatment based on a veterinary diagnosis of ovarian dysfunction during a fertility check. An existing individual cow-based, dynamic, and stochastic bio-economic simulation model, mimicking the production dynamics of a 200 cow-herd in daily time steps, was extended with ovarian dysfunction and fertility inputs. Four hormone-based reproductive management programs were modeled. In the default reproductive management program, reflecting the current reproductive management of Dutch herds, lactating dairy cows are inseminated based on detection of estrus and non-cyclic dairy cows are treated with hormones based on a veterinary diagnosis of ovarian dysfunction during a fertility check. Hormone treatments prescribed by the veterinarian for anestrus, cystic, and sub-estrus cows were an 8-d progesterone-releasing intravaginal device (PRID)-Synch protocol (PRIDsynch), an Ovsynch protocol, and a PGF2⍺ treatment, respectively. The 3 other reproductive management programs reflected systematic hormonal treatments to cows at specific DIM and included a 1) Double-Ovsynch protocol for TAI with nonpregnant cows submitted to a resynchronization protocol (FTAI), 2) Double-Ovsynch protocol for TAI with nonpregnant cows detected in estrus or submitted to a resynchronization protocol (FTAI+ED), and 3) detection of estrus with cows not detected submitted to a PRIDsynch protocol (ED+TAI). All nonpregnant cows were submitted to a resynchronization protocol based on the absence (PRIDsynch) or presence (Ovsynch protocol) of a corpus luteum (CL). The annual mean net economic return (NER) was calculated for all reproductive management programs. Compared with the default reproductive management program, the highest NER was observed for the FTAI+ED reproductive management program with €23,764 higher net revenues, followed by the FTAI and the ED+TAI reproductive management programs with €19,550 and €14,314 higher net revenues, respectively. Overall, systematic hormone-based reproductive management programs gave higher costs due to more hormones administered and higher calving and feed costs due to more pregnant cows. Nevertheless, the additional revenues of milk and calves in the systematic hormone-based reproductive management programs outweighed the total cost. For instance, the FTAI+ED reproductive management program gave €8,953 higher total cost per year compared with the default but with €32,654 higher revenues. In summary, reproductive management programs where hormones were systematically used gave economic advantages over the current default reproductive management program in which hormones are administered to individual cows based on a veterinary diagnosis of ovarian dysfunction during a fertility check.

Early detection and follow-up of colorectal neoplasia based on faecal volatile organic compounds.

AIM: Early detection and removal of colorectal cancer (CRC) and advanced adenomas (AAs) decreases the incidence of and mortality from the disease. We aimed to evaluate the potential of faecal volatile organic compounds (VOCs) for detection and follow-up of colorectal adenoma using advanced electronic nose technology. METHOD: This was a prospective multi-centre case-control cohort including two district hospitals and one tertiary referral hospital. Patients undergoing colonoscopy were instructed to collect a faecal sample prior to bowel cleansing and were included in the study when CRC, AAs, large adenomas (LAs; 0.5-1.0 cm), small adenomas (SAs; 0.1-0.5 cm) or no endoscopic abnormalities (controls) were observed. Patients undergoing polypectomy and controls were asked for a second sample after 3 months. Faecal VOCs were measured with gas chromatography-ion mobility spectrometry. Random forest, support vector machine, Gaussian process and neural net classification were used to evaluate accuracy. RESULTS: In total, 14 patients with CRC, 64 with AAs, 69 with LAs, 127 with SAs and 227 controls were included. A second sample was collected from 32 polypectomy patients and 32 controls. Faecal VOCs discriminated CRC and adenomas from control [AUC (95% CI): CRC vs control 0.96 (0.89-1); AA vs control 0.96 (0.93-1); LA vs control 0.96 (0.92-0.99); SA vs control 0.96 (0.94-0.99)]. There were no significant differences between CRC and adenoma groups. Patients with adenomas and controls were discriminated prior to polypectomy, whereas 3 months after polypectomy VOC profiles were similar [T0 adenoma vs control 0.98 (0.95-1); T1 adenoma vs control 0.55 (0.40-0.69)]. CONCLUSIONS: Faecal VOC profiles may be useful for early detection of CRC and adenomas and the timing of polyp surveillance as polypectomy led to a normalization of the VOC profile.

Colorectal cancer and adenoma screening using urinary volatile organic compound (VOC) detection: early results from a single-centre bowel screening population (UK BCSP).

BACKGROUND: The United Kingdom (UK) bowel cancer screening programme has reduced mortality from colorectal cancer (CRC), but poor uptake with stool-based tests and lack of specificity of faecal occult blood testing (FOBT), has prompted investigation for a more suitable screening test. The aim of this study was to investigate the feasibility of a urinary volatile organic compounds (VOC)-based screening tool for CRC. METHODS: The urine from FOBT-positive patients was analysed using field asymmetric ion mobility spectrometry (FAIMS) and gas chromatography coupled with ion mobility spectrometry (GC-IMS). Data were analysed using a machine learning algorithm to calculate the test accuracy for correct classification of CRC against adenomas and other gastrointestinal pathology. RESULTS: One hundred and sixty-three patients were enrolled in the study. Test accuracy was high for differentiating CRC from control: area under the curve (AUC) 0.98 (95% CI 0.93-1) and 0.82 (95% CI 0.67-0.97) using FAIMS and GC-IMS respectively. Correct classification of CRC from adenoma was high with AUC range 0.83-0.92 (95% CI 0.43-1.0). Classification of adenoma from control was poor with AUC range 0.54-0.61 (95% CI 0.47-0.75) using both analytical modalities. CONCLUSIONS: CRC was correctly distinguished from adenomas or no bowel pathology using urinary VOC markers, within the bowel screening population. This pilot study demonstrates the potential of this method for CRC detection, with higher test uptake and superior sensitivity than FOBT. In addition, this is the first application of GC-IMS in CRC detection which has shown high test accuracy and usability.

Risk stratification of symptomatic patients suspected of colorectal cancer using faecal and urinary markers.

AIM: Faecal markers, such as the faecal immunochemical test for haemoglobin (FIT) and faecal calprotectin (FCP), have been increasingly used to exclude colorectal cancer (CRC) and colonic inflammation. However, in those with lower gastrointestinal symptoms there are considerable numbers who have cancer but have a negative FIT test (i.e. false negative), which has impeded its use in clinical practice. We undertook a study of diagnostic accuracy CRC using FIT, FCP and urinary volatile organic compounds (VOCs) in patients with lower gastrointestinal symptoms. METHOD: One thousand and sixteen symptomatic patients with suspected CRC referred by family physicians were recruited prospectively in accordance with national referring protocol. A total of 562 patients who completed colonic investigations, in addition to providing stool for FIT and FCP as well as urine samples for urinary VOC measurements, were included in the final outcome measures. RESULTS: The sensitivity and specificity for CRC using FIT was 0.80 [95% confidence interval (CI) 0.66-0.93] and 0.93 (CI 0.91-0.95), respectively. For urinary VOCs, the sensitivity and specificity for CRC was 0.63 (CI 0.46-0.79) and 0.63 (CI 0.59-0.67), respectively. However, for those who were FIT-negative CRC (i.e. false negatives), the addition of urinary VOCs resulted in a sensitivity of 0.97 (CI 0.90-1.0) and specificity of 0.72 (CI 0.68-0.76). CONCLUSIONS: When applied to the FIT-negative group, urinary VOCs improve CRC detection (sensitivity rises from 0.80 to 0.97), thus showing promise as a second-stage test to complement FIT in the detection of CRC.

Agromorphological traits dataset of butterfly pea accessions from Thailand, Indonesia, and Brazil.

Butterfly pea (Clitoria ternatea L.) is a horticultural crop also known as underutilized crop. All parts of the butterfly pea can be used into various products including flowers that can be used as natural dyes and traditional medicines. Besides that, the plant parts can be used as fodder and cover crop. The development of butterfly pea in Indonesia is still very low both in cultivation and utilization. Therefore, a breeding program is required to increase usefulness of butterfly pea can be done for the development. To assemble superior varieties of butterfly pea, it is necessary to determine the genetic diversity of both in agronomy and morphology. Genetic diversity and relationships are needed to evaluate plant germplasm. Raw data analysis was conducted after standardization using Principal Componet Analysis (PCA) and Hierarchical Clustering Analysis (HCA) to determine phenotypic diversity and relationship among the newly collected genetic resources. The data in this article showed broad phenotypic diversity with weight of fresh flower per plant, seed color, weight of total seed, pod width, calix length, flower color, petal number, number of total pods, plant height, number of seed per pod, weight total fresh flower, seed width, weight of fresh flower per plant, and seed length as distinguishing traits among the accessions. PCA based on agromorphogical traits showed eigenvalue ranged from 1.13 to 9.47 with a cumulative contribution of 93.02%. HCA showed butterfly pea accessions divided into two cluster with euclidean distance 0.27-4.65.