Search Results (23)

Timely, objective pain recognition in dairy cattle is essential for welfare assurance, productivity, and ethical husbandry yet remains elusive because evolutionary pressure renders bovine distress signals brief and inconspicuous. Without verbal self-reporting, cows suppress overt cues, so automated vision is indispensable for on-farm triage. Although earlier systems tracked whole-body posture or static grimace scales, frame-level detection of facial micro-expressions has not been explored fully in livestock. We translate micro-expression analytics from automotive driver monitoring to the barn, linking modern computer vision with veterinary ethology. Our two-stage pipeline first detects faces and 30 landmarks using a custom You Only Look Once (YOLO) version 8-Pose network, achieving a 96.9% mean average precision ($mAP$) at an Intersection over the Union (IoU) threshold of 0.50 for detection and 83.8% Object Keypoint Similarity (OKS) for keypoint placement. Cropped eye, ear, and muzzle patches are encoded using a pretrained MobileNetV2, generating 3840-dimensional descriptors that capture millisecond muscle twitches. Sequences of five consecutive frames are fed into a 128-unit Long Short-Term Memory (LSTM) classifier that outputs pain probabilities. On a held-out validation set of 1700 frames, the system records 99.65% accuracy and an F1-score of 0.997, with only three false positives and three false negatives. Tested on 14 unseen barn videos, it attains 64.3% clip-level accuracy (i.e., overall accuracy for the whole video clip) and 83% precision for the pain class, using a hybrid aggregation rule that combines a 30% mean probability threshold with micro-burst counting to temper false alarms. As an early exploration from our proof-of-concept study on a subset of our custom dairy farm datasets, these results show that micro-expression mining can deliver scalable, non-invasive pain surveillance across variations in illumination, camera angle, background, and individual morphology. Future work will explore attention-based temporal pooling, curriculum learning for variable window lengths, domain-adaptive fine-tuning, and multimodal fusion with accelerometry on the complete datasets to elevate the performance toward clinical deployment. Full article

Background: Polymerase chain reaction (PCR) is highly sensitive and specific for the rapid diagnosis of invasive fungal disease (IFD) but is not yet widely implemented due to concerns regarding limited standardisation between assays, the lack of commercial options and the absence of clear guidance on interpreting results. Objectives and Methods: This review provides an update on technical and clinical aspects of PCR for the diagnosis of the most pertinent fungal pathogens, including Aspergillus, Candida, Pneumocystis jirovecii, Mucorales spp., and endemic mycoses. Summary: Recent meta-analyses have demonstrated that quantitative PCR (qPCR) offers high sensitivity for diagnosing IFD, surpassing conventional microscopy, culture and most serological tests. The reported specificity of qPCR is likely underestimated due to comparison with imperfect reference standards with variable sensitivity. Although the very low limit of detection of qPCR can generate false positive results due to procedural contamination or patient colonisation (particularly in pulmonary specimens), the rates are comparable to those observed for biomarker testing. When interpreting qPCR results, it is essential to consider the pre-test probability, determined by the patient population, host factors, clinical presentation and risk factors. For patients with low to moderate pre-test probability, the use of sensitive molecular tests, often in conjunction with serological testing or biomarkers, can effectively exclude IFD when all tests return negative results, reducing the need for empirical antifungal therapy. Conversely, for patients with high pre-test probability and clinical features of IFD, qPCR testing on invasive specimens from the site of infection (such as tissue or bronchoalveolar lavage fluid) can confidently rule in the disease. The development of next-generation sequencing methods to detect fungal infection has the potential to enhance the diagnosis of IFD, but standardisation and optimisation are essential, with improved accessibility underpinning clinical utility. Full article

During pregnancy, primary Toxoplasma gondii infection can cause congenital toxoplasmosis (CT). We described the newborns’ outcomes from a multicentre cohort of mothers with seroconversion (SC) at different gestational ages. This retrospective observational study (from 2007 to 2018) was conducted in two Italian referral hospitals: Fondazione IRCCS Policlinico San Matteo in Pavia and Spedali Civili in Brescia. In total, 247 pregnant women were enrolled: seroconversions were enrolled: seroconversions documented as having occurred in the two months preceding pregnancy in 12 cases (4.9%; 95% CI 2.2–7.5%), and during pregnancy in 235 cases (95.1%; 95% CI 92.5–97.8%). SC is defined as the appearance of specific anti-Toxoplasma antibodies (IgM/IgG) during pregnancy in a previously seronegative woman. A total of 56 (22.5%; 95% CI 17.3–27.7%) newborns were lost to follow-up; thus, the outcome of 193 (77.5%; 95% CI 72.3–82.7%) newborns was analyzed. The overall transmission rate of T. gondii infection was 23.8% (95% CI 17.8–29.8%), 0% (95% CI 0.0–11.9%) among the 1st trimester SCs, 12.5% (95% CI 5.6–19.4%) among the 2nd trimester SCs, 53.8% (95% CI 41.7–66.0%) among the 3rd trimester ones. No CT were found in the group of periconceptional infection. Among the infected newborns, clinically manifest cases were 12 (26.1%; 95% CI 13.4–38.8%), including 1 case (2.2%; 95% CI 2.0–6.4%) of stillbirth and 11 symptomatic neonates (23.9%; 95% CI 11.6–36.2%). A total of 83 amniocentesis were performed (33.6%; 95% CI 27.7–39.5%), no complication was recorded and no false positive or false negative results were registered. The results are in line with the fetal risks reported in literature for T. gondii infection during pregnancy, even if at a lower percentage probably due to a prompt treatment. Full article

In many forensic cases, the identification of human remains is performed by comparing their genetic profile with profiles from reference samples of relatives, usually the parents. Here, we report, for the first time, the identification of the remains of an adult using DNA from the person’s deciduous teeth as a reference sample. Fragments of a skeletonized and burned body were found, and a short tandem repeat (STR) profile was obtained. A woman looking for her missing son went to the authorities. When the DNA profile of the woman was compared to a database, a positive match suggested a first-degree kinship with the person to whom the remains belonged. The woman had kept three deciduous molars from her son for more than thirty years. DNA typing of dental pulp was performed. The genetic profiles obtained from the molars and those from the remains coincided in all alleles. The random match probability was 1 in 2.70 × 10²¹. Thus, the remains were fully identified. In the routine identification of human remains, ambiguous STR results may occur due to the presence of null alleles or other mutational events. In addition, erroneous results can be produced by false matches with close family members or even with people who are completely unrelated to the victim, such that, in some cases, a probability of paternity greater than 99.99% does not necessarily indicate biological paternity. Whenever possible, it is preferable to use reference samples from the putative victim as a source of DNA for identification. Full article

Transfusion-transmitted bacterial infection (TTBI) is the leading cause of transfusion-transmitted infections. Platelet components are more likely to be associated with bacterial contamination due to their storage requirements. Australian Red Cross Lifeblood introduced the bacterial contamination screening (BCS) of all platelet components in 2008. The process was recently updated with the use of BACT/ALERT^® VIRTUO^®, a large-volume delayed sampling (LVDS) protocol and extending platelet shelf-life to seven days. This article describes the results from the routine BCS of platelet components in Australia. Use of VIRTUO has resulted in lower false-positive rates, reducing wastage and improving platelet inventory. Our findings show that the combination of LVDS and VIRTUO improves the safety of platelet transfusions through earlier time to detection, especially for pathogenic bacterial species. Pathogenic bacteria grew within 24 h of incubation with a clear delineation between pathogenic and non-pathogenic species. The data show this protocol is very safe, with no TTBI cases during this time. There were no TTBI reports in recipients of platelet components that subsequently had a positive culture with Cutibacterium species, probably due to the low pathogenic potential of these organisms and slow replication in aerobic platelet bags. We conclude there is no advantage in incubating culture bottles beyond five days. Full article

Background: An increasing number of studies have reported associations between single nucleotide polymorphisms (SNPs) and ovarian cancer (OC) risk. However, some of the findings were inconsistent. The objective of this umbrella review was to evaluate the associations comprehensively and quantitatively. Methods: The protocol of this review was registered in PROSPERO (No. CRD42022332222). We searched the PubMed, Web of Science, and Embase databases to identify related systematic reviews and meta-analyses from inception to 15 October 2021. In addition to estimating the summary effect size by using fixed and random effects models and calculating the 95% prediction interval, we evaluated the cumulative evidence for associations with nominally statistical significance based on the Venice criteria and false positive report probability (FPRP). Results: Forty articles were included in this umbrella review, which referred to a total of 54 SNPs. The median number of original studies per meta-analysis was four, while the median number of total subjects was 3455. All included articles had greater than moderate methodological quality. A total of 18 SNPs were nominally statistically associated with OC risk; 6 SNPs (8 genetic models), 5 SNPs (7 genetic models), and 16 SNPs (25 genetic models) were identified as strong, moderate, and weak cumulative evidence, respectively. Conclusion: This umbrella review revealed associations between SNPs and OC risk and suggested strong cumulative evidence of associations of six SNPs (eight genetic models) with OC risk. Full article

This study aimed to set up indirect, rapid methods involving near infrared (NIR) spectroscopy analysis, to detect illicit treatments with glucocorticoids in bull. The ethanol fixation method (EtOH) was applied to 7 different tissues obtained from 20 Friesian bulls, 12 of which were experimentally administered with dexamethasone as part of a growth-promoting protocol for 60 days and slaughtered 26 days after the end of the treatment. A perfect discrimination was obtained for the 7 sampled tissues, considering a full UV-Vis-NIR range (350 ÷ 2500 nm), for both false positive and negative animals. The validated true positive and negative errors were zero for the longissimus thoracis muscle, 10% for the skin-dermis, 15% for the fat, 25% for the thymus gland and the semitendinosus muscle, 30% for the sternomandibularis muscle and 35% for the skin-hair. A multiple test on the most accessible tissues, that is, the thymus gland, the sternomandibularis muscle and fat, can be used as an alternative to provide indications about animals that have been subjected to illicit treatments. In the short space of three days from the slaughter, NIR spectroscopy of ETOH fixed tissues, would allow at least cost the detection of a probable illicit which could eventually be reported to health authorities for specific investigation in the frame of official controls. Full article

Controlling thermal comfort in the indoor environment demands research because it is fundamental to indicating occupants’ health, wellbeing, and performance in working productivity. A suitable thermal comfort must monitor and balance complex factors from heating, ventilation, air-conditioning systems (HVAC Systems) and outdoor and indoor environments based on advanced technology. It needs engineers and technicians to observe relevant factors on a physical site and to detect problems using their experience to fix them early and prevent them from worsening. However, it is a labor-intensive and time-consuming task, while experts are short on diagnosing and producing proactive plans and actions. This research addresses the limitations by proposing a new Internet of Things (IoT)-driven fault detection system for indoor thermal comfort. We focus on the well-known problem caused by an HVAC system that cannot transfer heat from the indoor to outdoor and needs engineers to diagnose such concerns. The IoT device is developed to observe perceptual information from the physical site as a system input. The prior knowledge from existing research and experts is encoded to help systems detect problems in the manner of human-like intelligence. Three standard categories of machine learning (ML) based on geometry, probability, and logical expression are applied to the system for learning HVAC system problems. The results report that the MLs could improve overall performance based on prior knowledge around 10% compared to perceptual information. Well-designed IoT devices with prior knowledge reduced false positives and false negatives in the predictive process that aids the system to reach satisfactory performance. Full article

Amyloid β 42/40 concentration quotient has been empirically shown to improve accuracy of the neurochemical diagnostics of Alzheimer’s Disease (AD) compared to the Aβ42 concentration alone, but this improvement in diagnostic performance has not been backed up by a theoretical argumentation so far. In this report we show that better accuracy of Aβ42/40 compared to Aβ1-42 is granted by fundamental laws of probability. In particular, it can be shown that the dispersion of a distribution of a quotient of two random variables (Aβ42/40) is smaller than the dispersion of the random variable in the numerator (Aβ42), provided that the two variables are proportional. Further, this concept predicts and explains presence of outlying observations, i.e., AD patients with falsely negatively high Aβ42/40 ratio, and non-AD subjects with extremely low, falsely positive, Aβ42/40 ratio. Full article

Aims: The hypothermia outcome prediction after extracorporeal life support (ECLS) score, or HOPE score, provides an estimate of the survival probability in hypothermic cardiac arrest patients undergoing ECLS rewarming. The aim of this study was to assess the performance of the HOPE score in case reports from the literature. Methods: Cases were identified through a systematic review of the literature. We included cases of hypothermic cardiac arrest patients rewarmed with ECLS and not included in the HOPE derivation and validation studies. We calculated the survival probability of each patient according to the HOPE score. Results: A total of 70 patients were included. Most of them (62/70 = 89%) survived. The discrimination using the HOPE score was good (Area Under the Receiver Operating Characteristic Curve = 0.78). The calibration was poor, with HOPE survival probabilities averaging 54%. Using a HOPE survival probability threshold of at least 10% as a decision criterion for rewarming a patient would have resulted in only five false positives and a single false negative, i.e., 64 (or 91%) correct decisions. Conclusions: In this highly selected sample, the HOPE score still had a good practical performance. The selection bias most likely explains the poor calibration found in the present study, with survivors being more often described in the literature than non-survivors. Our finding underscores the importance of working with a representative sample of patients when deriving and validating a score, as was the case in the HOPE studies that included only consecutive patients in order to minimize the risk of publication bias and lower the risk of overly optimistic outcomes. Full article

We propose a new framework, PlasmodiumVF-Net, to analyze thick smear microscopy images for a malaria diagnosis on both image and patient-level. Our framework detects whether a patient is infected, and in case of a malarial infection, reports whether the patient is infected by Plasmodium falciparum or Plasmodium vivax. PlasmodiumVF-Net first detects candidates for Plasmodium parasites using a Mask Regional-Convolutional Neural Network (Mask R-CNN), filters out false positives using a ResNet50 classifier, and then follows a new approach to recognize parasite species based on a score obtained from the number of detected patches and their aggregated probabilities for all of the patient images. Reporting a patient-level decision is highly challenging, and therefore reported less often in the literature, due to the small size of detected parasites, the similarity to staining artifacts, the similarity of species in different development stages, and illumination or color variations on patient-level. We use a manually annotated dataset consisting of 350 patients, with about 6000 images, which we make publicly available together with this manuscript. Our framework achieves an overall accuracy above 90% on image and patient-level. Full article

Early detection of SARS-CoV-2 in the emergency department (ED) is a crucial necessity, especially in settings of overcrowding: establishing a pre-diagnostic test probability of infection would help to triage patients and reduce diagnostic errors, and it could be useful in resource-limited countries. Here, we established and validated a clinical predictor of infection based on routine admission hematological parameters. The diagnostic model was developed by comparing 85 consecutive patients with symptomatic COVID-19 confirmed by RT-PCR with 85 symptomatic, SARS-CoV-2-negative controls. Abnormal hematological parameters significantly (p < 0.05) associated with SARS-CoV-2 infection were used to derive a “cumulative score” between 0 and 16. The model was validated in an independent cohort of 170 SARS-CoV-2-positive patients. Several routine hematology parameters were significantly (p < 0.05) associated with SARS-CoV-2 infection. A “cumulative score” score ≥7 discriminated COVID-19-postive patients from controls with a sensitivity of 94% and specificity of 100% (p < 0.001). The high sensitivity of the predictive model was confirmed in the prospective validation set, and the cumulative score (i) predicted SARS-CoV-2 positivity even when the first oro-nasopharyngeal swab RT-PCR result was reported as a false negative in both cohorts and (ii) resulted to be independent from disease severity. The cumulative score based on routine blood parameters can be used to predict an early and accurate diagnosis of SARS-CoV-2 infection in symptomatic patients, thereby facilitating triage and optimizing early management and isolation from the COVID-19 free population, particularly useful in overcrowding situations and in resource-poor settings. Full article

To assess prospectively the capability of our previously reported global multiparameter scoring system to predict coarctation of the aorta (CoAo) in fetuses with cardiac asymmetry, we applied and analyzed the performance of our scoring system in predicting postnatal CoAo in fetuses undergoing prenatal echocardiographic assessment because of cardiac asymmetry between 2011 and 2021, and we determined the cut-off points of the score with the best balance between specificity and sensitivity, and of maximum sensitivity and specificity. CoAo was confirmed in 39/179 newborns (21.8%). We found a significantly higher probability of CoAo in fetuses with CoAo than in cases without CoAo (84.2 ± 18.2% vs. 26.0 ± 28.6%, p < 0.001). The AUC of the ROC of the score was 0.93 (95% CI 0.89–0.97). The cut-off value with the best balance between specificity and sensitivity was a predicted risk of ≥53% (sensitivity 92.3% and specificity 80.0%). The cut-off point of maximum sensitivity was ≥35% (sensitivity 100% and specificity 72.9%), and that of maximum specificity was ≥96% (sensitivity 43.6% and specificity 96.4%). In none of the fetuses with a probability of CoAo < 35% was this condition confirmed after birth. This occurred in 102 fetuses in the whole study population (57%) and in 84 of the 111 in whom CoAo was suspected beyond 28 weeks (75.7%). This multiparameter score allows an adequate discrimination between fetuses without CoAo and those with CoAo, reducing the false positive diagnoses in cardiac asymmetry. Full article

(1) Background: All deaths that occurred in a hospital of Southern Italy (“San Giuseppe Moscati” Hospital of Avellino) with medium jurisdiction (up to 425,000 citizens approximately) in the period from 9 March to 4 May 2020 were analyzed. The primary endpoint of the study was to analyze the causes of death in the period study. Secondary endpoints included: (1) the assessment of overall mortality in the emergency period compared with the same period of the past years (2018–2019) in the jurisdiction area; (2) the assessment of the amounts of deaths with positive and negative reverse transcription-polymerase chain reaction (RT-PCR) of nasopharyngeal and oropharyngeal swabs; (3) the frequency of clinical and radiological features consistent with Covid-19 infection in negative RT-PCR cases. (2) Methods: Patients’ information and laboratory data were collected through the computerized medical record system (My Hospital, Italy) used for the clinical management of all referring patients. Epidemiological, clinical, and radiological data were reviewed along with the results of nasopharyngeal and oropharyngeal swabs. (3) Results: From 9 March to 4 May 2020, 140 deaths (87 males, 53 females) from all causes occurred in total at “San Giuseppe Moscati” Hospital, of which 32 deaths were Covid-19 related. (4) Conclusions: The excess of mortality could be higher than the one reported in the official epidemiological surveys. False negative cases can have a distorting effect on the assessment of the real mortality rate and the excess mortality. Furthermore, many who died from Covid-19 were likely never tested or they had false negative RT-PCR results. Other victims probably died from causes indirectly related to Covid-19. Full article

Monitoring programs should be based on the measurement of two main pillars for evaluating the conservation status of a species: population size and geographical distribution. To date, the only way reported in the literature to obtain detailed information on L. cervus population size is to use the capture-mark-recapture method. This is an expensive and time-consuming technique that implies physical capture and handling of individuals, which could affect their survival. Therefore, in this study we tested and compared two non-invasive sampling approaches, namely evening walk transects and diurnal tree trunk surveys, to derive accurate abundance estimates by means of N-mixture models in a Bayesian framework. In our study, both methods showed relatively high detection probability (≥56%). However, tree surveys performed better than walk transects (≈80%), especially with the progression of the sampling season. Tree surveys proved to be more effective than walk transects in providing data for an accurate population density estimate (much smaller 95% Bayesian Confidence Intervals). In light of a cost and benefit assessment, the tree survey is undoubtedly more convenient, as well as more effective, as it is more time consuming but less expensive than a walk transect (one operator for 2–3 h vs. two operators for 30 min each). Moreover, it needs fewer expert operators because of the greater proximity to the species, increasing the probability of correctly identifying it, i.e., reducing type I error (false positive or overestimation of counts). For the first time, we applied N-mixture models for estimating population abundance of L. cervus. Overcoming all the limits imposed by the use of the capture-mark-recapture method, in this study we performed a further step forward in the planning of monitoring aimed at the conservation of L. cervus and the evaluation of its demographic trend. Full article