A porencephalic cyst is a rare disorder, with the etiology of brain parenchymal loss as a result of perinatal cerebral ischemia or hemorrhage leading to the accumulation of cerebrospinal fluid within the parenchyma. It is diagnosed radiologically, and management depends on the clinical manifestations. The present case depicts a porencephalic cyst presenting with cerebral right-sided hemiparesis in adulthood. The cyst dimensions measured 2.6*0.6*0.5 cm in the left lateral ventricle with associated hemiparesis of the right side at the time of the first MRI scan before Deep Brain Sound Stimulation (DBSS) sessions. A reduction in the size of the cyst to 16*7*7 mm and then to a subsequent 8 mm was documented during a novel, non-invasive deep brain stimulation via sound (DBSS) treatment. In addition, right upper and lower limb power increased to 5/5 with improved coordination in a complete neurological evaluation. DEXA scan showed an increased bone density and muscle bulk.

Background: Despite the growing awareness of Cystic Fibrosis (CF) in China, few cases have been reported in Henan, which is the most populous province in the country. This study aimed to describe the clinical phenotype and genotype of children with CF in Henan. Methods: We recruited 14 Chinese children with CF who presented to Children’s Hospital affiliated to Zhengzhou University from January 2019 to January 2023. The demographic data, imaging examinations, and laboratory tests of the patients were reviewed to clarify the clinical phenotype. Whole exome sequencing was conducted to identify the genotype. Results: Respiratory diseases were the main clinical manifestation, including recurrent/persistent pneumonia (85.7%), sinusitis (71.4%), bronchiectasis (71.4%). CF-related liver disease (CFLD) and pancreatic insufficiency (PI) were less common (21.4% each). Infant cases had high frequency of pseudo-Bartter Syndrome (80.0%). Chest computed tomography showed bronchiectasis in older children and air trapping in infant cases. The most common pathogens in the airway were Pseudomonas aeruginosa and Staphylococcus aureus (71.4% respectively). Twenty-four different CFTR gene variants were detected, including four novel observations (c.869+3A>T, c.1064C>G[p.Pro355Arg], c.1209+1G>C and c.1925C>G [p.Ser642X]). The most common variant was c.2909G>A (p.Gly970Asp), with a detected rate of 16.7%. Conclusion: Children with CF in Henan had varied clinical phenotypes by age, with respiratory disease being predominant. The most frequent CFTR gene variant was c.2909G>A(p.Gly970Asp). This study is the first and most comprehensive one on the clinical phenotype and genotype of children with CF in Henan, China. We also reported the first CF case of M. abscessus infection in China.

The leading cause of cerebrovascular disease, cerebral apoplexy, is by far one of the three conditions that pose the greatest risk to human health. With the trend toward an elderly society, cerebral apoplexy research has advanced incredibly quickly in recent years. Bibliometric analysis is used in the current investigation to assess trends in this sector. Articles were searched for in the Web of Science (subsequently referred to as WOS) database up until January 20, 2023. Bibliographic details, including country, institution, journal, author, citation, and keywords, of the chosen publications were automatically converted and analyzed using the Bibliometric software program. For this analysis, 3 617 articles were chosen from 1971 to 2023 in total. Thirteen articles received more than 100 citations overall, according to the citation analysis. Based on a Bibliometric examination of the literature used in this study, it could be seen that China (256 articles), Japan (366 articles), and the United States (1127 articles) provided the most publications. The most publications came from Northern University (164 records, 4.53% of articles). Levin, MF was the most productive author, with 40 papers (1.11% of the articles). These articles were published in 667 journals, most of which (145, or 4.01% of the articles) were published in the Archives of Physical Medicine and Rehabilitation. The curve is particularly prominent for the keywords “hemiparesis,” “rehabilitation,” and “stroke.” The effects of cerebral apoplexy-causing hemiparesis and the efficiency of interventions, particularly restorative therapies, are anticipated to be the main topics of future research.

Purpose To describe utilization patterns, characteristics of users and prescriber responsibility of the new oral antiviral medication, molnupiravir, indicated for mild-to-moderate COVID-19. Methods Using nationwide registries, we identified all Danish adults who filled a prescription for molnupiravir from December 16 th, 2021, to August 31 st, 2022. We described weekly incidence rates and patient characteristics over time, prescriber responsibility as well as time between molnupiravir initiation and a positive SARs-CoV-2 test. Patient characteristics were compared to an untreated SARS-CoV-2 positive cohort. Results By August 31 st, 2022, 5,847 individuals had filled a prescription for molnupiravir. The incidence rate gradually increased to 2,000 weekly prescriptions per 100,000 RT-PCR SARS-CoV-2 positives. Users of molnupiravir were most often men (55% vs. 45% women). The majority (81%) had a positive RT-PCR SARS-CoV-2 test and few (2.9%) redeemed molnupiravir outside the recommended window of 5 days from the positive test result. Compared to an untreated SARS-CoV-2 positive cohort, users of molnupiravir had a median age of 74 years vs. 44 years, a higher proportion resided in a nursing home (12% vs. 1.1%) and had a higher number of comorbidities (median of 3 vs. 0); most commonly hypertension (38%), chronic lung disease (35%), diabetes (20%) and mood disorders (20%). General practitioners were the primary prescribers of molnupiravir (91%). Conclusions Molnupiravir was mainly prescribed by general practitioners to RT-PCR SARS-CoV-2 positive individuals who had a potentially increased risk of severe COVID-19. Though some off-label prescribing occurred, our study indicates a high level of adherence to contemporary guidelines.

Species detection using eDNA is revolutionizing global capacity to monitor biodiversity. However, the lack of regional, vouchered, genomic sequence information—especially sequence information that includes intraspecific variation—creates a bottleneck for management agencies wanting to harness the complete power of eDNA to monitor taxa and implement eDNA analyses. eDNA studies depend upon regional databases of mitogenomic sequence information to evaluate the effectiveness of such data to detect and identify taxa. We created the Oregon Biodiversity Genome Project to create a database of complete, nearly error-free mitogenomic sequences for all of Oregon’s fishes. We have successfully assembled the complete mitogenomes of 313 specimens of freshwater, anadromous, and estuarine fishes representing 24 families, 55 genera, and 128 species and lineages. Comparative analyses of these sequences illustrate that many regions of the mitogenome are taxonomically informative, that the short (~150 bp) mitochondrial “barcode” regions typically used for eDNA assays do not consistently diagnose for species, and that complete single or multiple genes of the mitogenome are preferable for identifying Oregon’s fishes. This project provides a blueprint for other researchers to follow as they build regional databases, illustrates the taxonomic value and limits of complete mitogenomic sequences, and offers clues as to how current eDNA assays and environmental genomics methods of the future can best leverage this information.

Mutations are the primary source of all genetic variation. Knowledge about their rates is critical for any evolutionary genetic analyses, but for a long time, that knowledge has remained elusive and indirectly inferred. In recent years, parent-offspring comparisons have yielded the first direct mutation rate estimates. The analyses are, however, challenging due to high rate of false positives and no consensus regarding standardized filtering of candidate de novo mutations. Here, we validate the application of a machine learning approach for such a task and estimate the mutation rate for the guppy (Poecilia reticulata), a model species in eco-evolutionary studies. We sequenced 4 parents and 20 offspring, followed by screening their genomes for de novo mutations. The initial large number of candidate de novo mutations was hard-filtered to remove false-positive results. These results were compared with mutation rate estimated with a supervised machine learning approach. Both approaches were followed by molecular validation of all candidate de novo mutations and yielded similar results. The ML method uniquely identified 3 mutations, but overall required more work and had higher rates of false positives and false negatives. We, thus, recommend its application if most of the mutations are expected to be identified or in case of experiment-specific biases. Both methods concordantly showed that guppy mutation rate is among the lowest directly estimated mutation rates in vertebrates. Similarly, low estimates were obtained for two other teleost fishes. We discuss potential explanations for such a pattern, as well as future utility and limitations of machine-learning approaches.

Objectives: To identify knowledge and attitude factors influencing primary care clinician decision-making in diagnosing, managing, and treating urinary tract infections. Design: A qualitative think-aloud study. Methods: Semi-structured qualitative interviews were conducted with primary care clinicians in England over Microsoft Teams. Interviews were transcribed and coded in two ways. First, clinicians’ responses for each scenario were coded as either following (optimal) or not following (suboptimal) evidence-based national guidelines. Second, the knowledge and attitude factors that influenced decision-making were coded according to an empirically-informed umbrella framework. Clinicians external to the study team reviewed the findings to promote their trustworthiness and utility. Setting: English primary care clinicians with the right to prescribe medications in England. Sample: Ten clinicians with prescribing rights in primary care took part. Results: Despite clinicians’ expressing high awareness of relevant evidence-based guidelines (a knowledge factor) and high confidence (an attitude factor), more than half of their decisions were suboptimal in some way. Our framework analysis suggests that knowledge could impede adherence, e.g., where local guidelines conflicted with national guidelines. Conclusions: Suboptimal prescribing decisions could result from a combination of different knowledge and attitude factors. Most clinicians relied on their experiential knowledge rather than using evidence-based guidelines. To optimise antibiotic prescribing, policy-level interventions could increase concordance across local and national guidelines, or more tailored individual-level interventions could help clinicians recognize where their experiential knowledge causes deviations from evidence-based guidelines when diagnosing, treating, and managing urinary tract infections.

The granite residual soil slopes in southeast Guangxi, China, occur failures and cause frequent landslides under rainfall conditions. Shallow landslides are the main failure mode. Shearing dilation effect and groundwater seepage both exist within the landslide movement. The movement characteristic is the scientific basis of landslide prevention and warning. In this study, a shallow landslide model of granite residual soil is established to reflect the coexistence of shearing dilation effect and groundwater seepage. The results include three aspects. (1) Groundwater seepage along the slope can lead to the increase of the sliding force, which is not conducive to slope stability. (2) Dilation promotes the formation of negative excess pore pressure, which can counteract the increase in static pore pressure caused by rain infiltration. It has a certain inhibitive effect on landslide motion. Such restriction weakens with the decrease of dilation angle and enhances with the increase of dilation angle. (3) Contraction can prompt the positive excess pore water pressure to increase rapidly to the limit of liquefaction in a short period of time. The research results will provide a theoretical basis for the prevention and warning of rainfall-induced granite residual soil landslide in southeast Guangxi.

Background: Mechanical bowel preparation before gynecologic surgeries has been administered for decades but its use is controversial today. Objectives: To assess the efficacy and tolerance of mechanical bowel preparation before benign laparoscopic or vaginal gynecologic surgeries. Search strategy: MEDLINE (PubMed), EMBASE (OVID), Cochrane Central Register of Controlled Trials (CENTRAL), and Web of Sciences published up to December 2021. Selection criteria: Randomized clinical trials in any language comparing mechanical bowel preparation before laparoscopic and vaginal gynecologic surgeries with no preparation were included. Data collection and analysis: Two reviewers independently screened and extracted data from selected articles and assessed the risk of bias. Surgeon findings, operative outcomes and patient’s pre-operative symptoms and satisfaction were collected. Main results: Twelve studies (1715 patients) of the 925 records screened were included. No significant differences were observed on surgical field view (RR=1.01, 95%CI 0.97-1.05, p=0.66, I 2=0%); bowel handling (RR=1.01, 95%CI 0.95-1.08, p=0.78, I 2=67%). There were no statistically significant differences in peri-operative findings. Mechanical bowel preparation was associated with increased pain (MD=11.62[2.80-20.44], I 2=76, p=0.01); weakness (MD=10.73[0.60-20.87], I 2=94, p=0.04); hunger (MD=17.52[8.04-27.00], I 2=83, p=0.0003); insomnia (MD=10.13[0.57-19.68], I 2=82, p=0.04); and lower satisfaction (RR=0.68 95%CI 0.53-0.87, I 2=76%, p=0.002). Conclusion: In view of the adverse effects induced by mechanical bowel preparation and the lack of any surgical benefit, the routine its use prior to benign gynecological surgeries should be abandoned. Funding: This work was granted by the French network of University Hospitals HUGO and Fonds de recherche du Québec-Santé.

Due to submission process, there is no abstract or subheadings.

Objective: Ovarian cancer has a dismal prognosis. Standard treatment following surgery relies on platinum-based chemotherapy. However, sizeable percentages of patients are unresponsive. Identification of markers predicting response to chemotherapy might help select eligible patients while sparing unresponsive ones treatment-associated toxicity. Cancer/testis antigens (CTA) are expressed by healthy germ cells and malignant cells of diverse histological origin. This expression profile identifies them as attractive targets of cancer immunotherapies. We analyzed correlations between expression of MAGE-A10 and New York esophageal-1 cancer (NY-ESO-1) CTAs at protein level and effectiveness of platinum-based chemotherapy in patients with advanced-stage high-grade serous ovarian carcinoma (HGSOC). Methods: MAGE-A10 and NY-ESO-1 protein expression was analyzed by immunohistochemistry (IHC) in formalin-fixed, paraffin-embedded samples from 93 patients with advanced-stage HGSOC treated at our institutions between January 1996 and December 2013. Correlation between expression of these markers and response to platinum-based chemotherapy, evaluated according to RECIST 1.1 criteria, platinum sensitivity, measured as platinum free interval (PFI), progression free (PFS) and overall survival (OS) was explored. Results : MAGE-A10 protein expression predicts unresponsiveness to platinum-based chemotherapy ( p=0.005), poor platinum sensitivity ( p<0.001), and poor PFS ( p<0.001) and OS ( p<0.001). Multivariate analysis identifies MAGE-A10 protein expression as independent predictor of poor platinum sensitivity ( p=0.005) and shorter OS ( p<0.001). Instead, no correlation was observed between NY-ESO-1 protein expression and response to platinum-based chemotherapy (p=0.832), platinum sensitivity (p= 0.168), PFS (p=0.126) and OS (p=0.335). Conclusion : MAGE-A10 protein expression reliably identifies advanced-stage HGSOC unresponsive to platinum-based chemotherapy. Targeted immunotherapy could represent an important alternative therapeutic option in these cancers.

A document by Wen-Hung Chung. Click on the document to view its contents.

A subtropical mangrove along the Miyara River in Ishigaki Island, Japan was studied for evaluating the carrying capacity for biomass of the monospecific stands. Rhizophora stylosa and Bruguiera gymnorrhiza were dominant in the downstream area whereas B. gymnorrhiza in the upstream. The stem diameter D, stem height H, fine roots mass were measured and, aboveground biomass AGB, belowground coarse root biomass BGBcoarse were estimated. The AGB, BGBcoarse and fine root mass were estimated as 128.46 Mg ha-1, 31.01 Mg ha-1 and 12.75 Mg ha-1 in the R. stylosa; 269.82 Mg ha-1, 93.68 Mg ha-1 and 11.13 Mg ha-1 in the downstream B. gymnorrhiza; and, 227.94 Mg ha-1, 81.05 Mg ha-1 and 6.35 Mg ha-1 in the upstream B. gymnorrhiza plots, respectively. The AGB did not differ among the plots, meanwhile BGBcoarse was significantly lower and fine root mass was significantly higher in the R. stylosa plots than in the downstream B. gymnorrhiza plots. Significantly lower mean individual phytomass wt specific to tree density  of R. stylosa plots than B. gymnorrhiza plots in the  – wt relationship was found, which denoted the lower carrying capacity for AGB of R. stylosa than that of B. gymnorrhiza. The results rejected our hypothesis that the stressful edaphic conditions, such as high soil salinity and low pH at the downstream, limit biomass and potential canopy height Hmax of mangrove along a river gradient but partly supported another hypothesis that biomass and Hmax differs between different mangrove species at the same edaphic environment.

Zero signifies absence or an amount of no measure. This mathematical object purportedly exemplifies one of humanity's most splendid insights. Endorsement of the continuum consolidated zero as a cultural latecomer that, at present, everybody uses daily as an indispensable number. Zero and infinity represent symmetric and complementary concepts; why did algebra embrace the former as a number and dismiss the latter? Why is zero an unprecedented number in arithmetic? Is zero a cardinal number? Is it an ordinal number? Is zero a "real" point? Has it a geometrical meaning? To what extent is zero naturalistic?A preliminary analysis indicates that zero is short of numerical competence, contrived, and unsolvable. We find it elusive when we dig into zero's role in physics, especially in thermodynamics, quantum field theory, cosmology, and metrology. A minimal fundamental extent is plausible but hard to accept due to zero's long shade. In information theory, the digit 0 is inefficient; we should replace standard positional notation with bijective notation. In communication theory, the transmission of no bits is impossible, and information propagation is never error-free. In statistical mechanics, the uniform distribution is inaccessible. In set theory, the empty set is ontologically paradoxical. Likewise, other mathematical zeroes are semantically vacuous (e.g., the empty sum, zero vector, zero function, unknot). Because division by zero is intractable, we advocate for the nonzero rational numbers, Q-{0}, to build a new physics that reflects nature's countable character. We provide a zero-free and unique rational-based representation of the algebraic numbers punctured at the origin, A-{0}, the computable version of the complex numbers.In a linear scale, we must handle zero as the limit of an asymptotically vanishing sequence of rationals or substitute it for the smallest possible nonzero rational. Zero, as such, is the predetermined power indicating the beginning of logarithmically encoded data via log(1). The exponential function decodes the logarithmic scale's beables back to the linear scale. The exponential map is crucial to understand advanced algebraic concepts such as the Lie algebra-group correspondence, the Laplace transform, and univariate rational functions in cross-ratio form. Specifically, linear fractional transformations over a ring lead to the critical notion of conformality, the property of a projection or mapping between spaces that preserves angles between intersecting conics. Ultimately, we define "coding space" as a doubly conformal transformation domain that allows for zero-fleeing hyperbolic (logarithmic) geometry while keeping relationships of structure and scale.

A low-power NPN-based bandgap voltage reference (BGR) over an ultra-wide temperature range is presented. The conventional NPN-based BGRs cannot maintain a low-temperature coefficient (TC) over an ultra-wide temperature range due to the inherent substrate leakage current of the NPN bipolar junction transistors (BJT) in the high-temperature range. This work introduces a new NPN-based BGR unaffected by substrate leakage current and receives low TC over the range of -40℃ to 150℃. The proposed circuit was fabricated in a 180 nm CMOS process. It consumes 2uA from a 4V power supply, and its average TC is 14.89ppm/℃. Also, the average line sensitivity is 0.039%/V.

With the development of renewable sources power generation technology, virtual synchronous generator (VSG) has attracted the attention of the electrical field. Although VSG has the advantage that parameters can be set at will, VSG does not have the actual rotor. Therefore, VSG should contain energy storage equipment to provide necessary power support for relative parameters. The similarities and differences between synchronous generator and VSG are analyzed. The influence of inertia coefficient setting on VSG DC side voltage is deduced when the generator inertia support is insufficient. The simulation circuit under two VSG operation scenarios is built, and the simulation results are consistent with the theoretical analysis. The conclusions can provide reference for the design of VSG inertia coefficient.

Abstract The penetration of wind turbines in the power grid is increasing rapidly. Still, the wind turbine output power has uncertainty, leading to poor grid reliability, affecting the grid’s dispatching plan, and increasing the total cost. Thus, a distributionally robust optimization (DRO) method for thermal power unit commitment considering the uncertainty of wind power is proposed. For this method, energy storage and interruptible load are added to simulate increasingly complex electricity consumption scenarios. Furthermore, the amount of load cutting reflects the satisfaction level of electricity consumption on the user side. Based on Wasserstein metric, an ambiguity set is established to reflect the probabilistic distribution information of the wind power uncertainty. An ambiguity set preprocessing method is proposed to depict the probability distribution of ambiguity set more clearly, to minimize the operation cost under the condition that the uncertainty of wind turbine output power obeys the extreme probabilistic distribution of the ambiguity set. The test case in a modified version of the IEEE 6-bus system shows that the proposed method can flexibly adjust the robustness and economy of optimization decisions by controlling the sample size and the confidence of Wasserstein ambiguity set radius. In addition, the proposed ambiguity set preprocessing method can obtain more economical dispatching decisions with a smaller sample size.

Model ensemble is widely used in deep learning since it can balance the variance and bias of complex models. The mainstream model ensemble methods can be divided into “implicit” and “explicit”. The “implicit” method obtains different models by randomly inactivating the internal parameters in the complex structure of the deep learning model, and these models are integrated by sharing parameters. However, these methods lack flexibility because they can only ensemble homogeneous models with the similar structure. While the “explicit” ensemble method can fuse completely different heterogeneous model structures, which significantly enhances the flexibility of model selection and makes it possible to integrate more models with entirely different perspectives. However, the explicit ensemble will face the challenge of averaging the outputs, leading to a chaotic result. To this end, researchers further proposed using knowledge distillation and adversarial learning technologies to perform a nonlinear combination of multiple heterogeneous models to obtain better ensemble performance, however these require significant modifications to the training or testing procedure and are computationally expensive compared to simply averaging. In this paper, based on the linear combination assumption, we propose an interpretable ensemble method for averaging model results which is simple to implement, and conducting experiments on the representation learning tasks of Computer Vision(CV) and Natural Language Processing(NLP). The results show that our method is superior to direct averaging results while retaining the practicality of direct averaging.

With the rapid development of science and technology, paper-based functional materials have become the core of the field of new materials. Recently, they have received extensive attention in the field of energy storage due to their advantages of rich and adjustable porous network structure, good flexibility. As an important energy storage device, paper-based supercapacitors have important application prospects in many fields, and have also received extensive attention from researchers in recent years. At present, researchers have modified and regulated paper-based materials by different means such as structural design and material composition to enhance their electrochemical storage capacity. The development of paper-based supercapacitors provides an important direction for the development of green and sustainable energy. Therefore, it is of great significance to summarize the relevant work of paper-based supercapacitors for their rapid development and application. In this review, the recent research progress of paper-based supercapacitors based on cellulose was summarized in terms of various cellulose-based composites, preparation skills and electrochemical performance. Finally, some opinions on the problems in the development of this field and the future development trend were proposed. It is hoped that this review can provide valuable references and ideas for the rapid development of paper-based energy storage devices.

Supported by artificial intelligence, recently, two different topics have taken an essential role in many applications, which are chatbots and virtual humans, owing to their capability in establishing communication between them and the users for accomplishing different tasks depending on their goal. Virtual humans are getting a lot of attention in different industries due to their realistic human form, behavior, and ability to convey emotional feedback, especially when experienced in a virtual reality environment. While Chatbots are considered the most promising example of building interaction between humans and machines because of their high efficiency in communicating with people resulting in being utilized in various applications. Combining a chatbot with a virtual human results in an Embodied Digital Conversational Agent; hence it will achieve positive feedback because face-to-face communication has always played a main role in how people interact and develop throughout history. Therefore, we present an Open-Domain Conversational Digital Human System that allows you to have a friendly virtual avatar and establishes realistic interaction with users. The system consists of a 3D virtual character and a set of artificial intelligence models, each specified for completing a task like emotion recognition, dialogue generation, facial expression extraction, animations, text-to-speech, and speech-to-text conversion.

This paper presents a novel real-time facial feature extraction algorithm, producing a small feature set, suitable for implementing emotion recognition with online game and metaverse avatars. The algorithm aims to reduce data transmission and storage requirements, hurdles in the adoption of emotion recognition in these mediums. The early results presented show a facial emotion recognition accuracy of up to 92% on one benchmark dataset, with an overall accuracy of 77.2% across a wide range of datasets, demonstrating the early promise of the research.

Abstract:Nothing is known regarding the clinical characteristics associated with the incidence of acute respiratory distress syndrome (ARDS) in hospitalised Coronavirus illness 2019 patients (COVID-19). The purpose of this study was to characterise the incidence of pre-admission antithrombotic medications in patients with COVID-19 and to examine the potential connection between antithrombotic therapy and ARDS as clinical disease presentation or in-hospital mortality.We enrolled 192 consecutive patients admitted to the emergency departments of five Italian hospitals with laboratory-confirmed COVID-19. The study population was separated into two groups based on the presence of ARDS on admission chest computed tomography. A propensity score weighted regression analysis was used to estimate the risk of ARDS at admission and death during hospitalisation in patients treated or not with antiplatelet and anticoagulant medications.73 cases (38%) were diagnosed with ARDS and were more likely to have hypertension than those without ARDS (57.8% vs. 49.6%; P = 0.005). Thirty-five patients (18.5%) passed away while hospitalised. Patients who did not survive COVID-19 had statistically significant increases in age (77 8.31 vs 65.57 8.31; P = 0.001), hypertension (77.1% vs 53.5%; P = 0.018), and coronary artery disease prevalence (28.6% vs 10.5%; P = 0.009). Both unadjusted and adjusted regression models revealed no difference in the risk of ARDS at admission or mortality during hospitalisation between antiplatelet and anticoagulant-treated and untreated patients. Pre-admission Antithrombotic medication, including antiplatelet and anticoagulant, does not appear to be protective in severe cases of COVID-19 presenting with ARDS and fast progressing to mortality.  1.    Introduction SARS-CoV-2 is a novel, highly deadly human coronavirus recently identified as the cause of coronavirus sickness in 2019. (COVID-19). The outbreak began in Wuhan, the capital of China's Hubei region, and swiftly spread to neighbouring nations, reaching pandemic proportions [1]. Italy is among the countries hardest impacted by COVID-19, with over 200,000 laboratory-confirmed cases expected by May 2, 2020 [2]. Many life-threatening diseases, including sepsis, respiratory failure, heart failure, severe renal and cardiac damage, and septic shock, may worsen the clinical course of COVID-19 [3]. Nothing is known about the clinical characteristics of patients that predispose them to these life-threatening illnesses.Acute respiratory distress syndrome (ARDS) is one of the most often observed complications of COVID-19, and it has been related to significantly reduced hospital survival rates for patients. The relationship between inflammation and coagulation seems crucial in its pathophysiology [4], even though its aetiology is not fully understood.It has not yet been determined whether anti-inflammatory medications and anticoagulants may influence the onset of ARDS in COVID-19.This multicenter study aimed to assess the prevalence of antithrombotic treatments upon admission in patients with COVID-19, as well as any potential association between antithrombotic therapy and ARDS, as illness clinical presentation, or in-hospital mortality.  Methods:We enrolled 192 consecutive patients with laboratory-confirmed COVID-19 from a large cohort of 963 patients admitted from February to April 2020 for fever and dyspnea to the Emergency Department (ED) of five Italian hospitals (Humanitas Hospital of Milan, Fatebenefratelli Hospital of Naples, Bergamo Hospital, Rivoli Hospital of Turin, Health Authority Bergamo East). Real-time quantitative reverse-transcription polymerase chain reaction (RT- PCR) assay on nose/throat swab or sputum sample positive for SARS-CoV-2 provided laboratory confirmation.Upon admission, all patients were given a medical history, physical examination, and laboratory evaluation. A chest X-ray and computed tomography (CT) scan were also conducted to rule out pneumonia in one or many sites. The COVID-19 population was separated into two groups based on the presence or absence of pneumonia with acute respiratory distress syndrome (ARDS) and in-hospital mortality. The diagnosis of ARDS was based on the Berlin definition [5].We evaluated the prevalence and kind of antithrombotic treatment between these groups. The discontinuation of antithrombotic therapy during hospitalisation was assessed as an exclusion criterion. The institution's ethical committee authorised the protocol. All patients provided verbal and written informed consent for participation.   Statistical analysisThe Kolmogorov–Smirnov and Shapiro–Wilk tests distributed continuous data. Normally distributed data were expressed as the mean, and standard deviation (SD), while non-normally distributed variables were described as the median and interquartile range (IQR). Numbers and percentages were supplied for categorical variables.Student's t-test was used to compare regularly distributed continuous data, whereas the Mann-Whitney U test was utilised to evaluate non-normally distributed continuous variables. Categorical variables were compared using the chi-square test or the Fisher exact test when applicable. Using logistic regression models, the unadjusted and adjusted risk ratios (RR) for the outcomes of interest were determined and presented as RR with their 95% confidence intervals (CI). We employed propensity score weighting to account for the possibility of selection bias in treatment assignment between the two study groups (average treatment effect weights). The propensity score model was created by integrating all pre-procedural covariates potentially associated with the outcome and treatment decision, irrespective of their statistical significance or collinearity with other variables included in the model. Age, smoking, chronic obstructive pulmonary disease (COPD), hypertension, diabetes, coronary artery disease (CAD), heart failure, obesity, dyslipidemia, stroke, and chronic kidney disease were baseline factors included in the propensity score model (CKD). Following weighting, standardised mean differences were computed to evaluate the balance of all covariates included in the propensity score model; values more than 0.10 were deemed statistically significant for differences across groups.A p-value 0.05 was considered statistically significant for all tests.Version 3.5.1 of R was used to conduct analyses (R Foundation for Statistical Computing, Vienna, Austria).   ResultsTable 1 details the characteristics of the study population. 67.7 15.2 years was the mean age; 115 (59.9%) were men. 73 cases (38%) were diagnosed with ARDS and were more likely to have hypertension than those without ARDS (57.8% vs. 49.6%; P = 0.005).At the time of admission, 55 COVID-19 patients (28.6%) were on antiplatelet medication, with 44 (22.9%) using acetylsalicylic acid, 5 (2.6%) P2y12 inhibitors, and 6 (3.1%) receiving dual antiplatelet therapy. They were older (73.7 9.2 vs 65.2 16.4; P = 0.001) and had a greater prevalence of hypertension (78.2% vs 49.6%; P = 0.001), dyslipidemia (30.9% vs 4.4%; P 0.001), and coronary artery disease (26.4% vs 4.4%; P = 0.001). At admission, 26 COVID-19 patients (13.5%) were on anticoagulant medication, with 18 (9.4%) receiving non-vitamin K oral anticoagulant (NOAC) and 8 (4.2%) on well-controlled vitamin K oral anticoagulant (VKA). They had a higher prevalence of hypertension (80.8% vs 54.2%; P = 0.02), atrial fibrillation (84.6% vs 1.2%; P 0.001), heart failure (30.8% vs 7.2%; P = 0.001), chronic kidney disease (19.2% vs 1.2%; P = 0.012), prior stroke (23.1% vs 6.0%; P = 0.011), and coronary artery disease (30.8% vs Thirty-five patients (18.5%) passed away while hospitalised. Patients who did not survive COVID-19 had a statistically significant increase in age (77 15.6 vs 65.6 8.3; P = 0.001), hypertension (77.1% vs 53.5%; P = 0.018), and CAD prevalence (28.6% vs 10.5%; P = 0.009). (Table 2). The proportion of deaths according to pre-mission antiplatelet and anticoagulant medication is depicted in Figure 1.Notwithstanding the significant disparities in baseline characteristics between COVID-19 patients who survived and those who did not, the inverse probability weighting achieved a solid covariate balance, with absolute standard deviations of less than 10% for all variables. Antiplatelet and anticoagulant arms were more evenly distributed in allocation probability among patients who did not use antithrombotic medicines at admission, as depicted in Figure 2. Table 3 displays the unadjusted and adjusted regression models for the likelihood of ARDS and death according to pre-mission antithrombotic treatment. In COVID-19 patients, pre-admission antithrombotic medication with antiplatelets or anticoagulants was not linked with an elevated risk of ARDS at admission or in-hospital death.Discussion:Patients who did not survive were older and showed a higher prevalence of comorbidities. Both antiplatelet and anticoagulant therapy did not affect the risk of severe clinical presentation as ARDS at admission. These findings can be summed up as follows: many patients admitted for COVID-19 are on treatment with antithrombotic agents.The epidemiological link between CV risk factors and individual susceptibility to SARS-CoV2 infection, as established in Chinese and American cohort studies [6,7], was confirmed in our study sample, which included hospitalised COVID-19 patients from Italy. Individual vulnerability to SARS-CoV2 infection has been linked to preexisting conditions such as hypertension, diabetes, and coronary cardiovascular risk (CV) factors, as revealed in Chinese and American cohort studies [6,7]. The most common co-existing conditions included high blood pressure, diabetes, and heart disease. Early Chinese data [8,9] also demonstrated that the prevalence of CV diseases, especially hypertension, was significantly higher in critically ill COVID-19 patients with ARDS compared to those with milder forms of illness and that the majority of hypertension and CAD was similarly higher in non-survivors of COVID-19 compared to survivors.The prevalence of AF among the patients in our study was 12.5%, which is greater than what is seen in the general population [10]. However, AF prevalence has yet to be reported in COVID-19 patients with a more severe form of the disease, characterised by ARDS and poor clinical outcomes.The direct effects of SARS-CoV-2 on alveolar epithelial cells and indirect effects of infection-related hypoxia, which predispose to thrombotic events, may contribute to the development of ARDS in the clinical context of COVID-19. Furthermore, recent data [11,12] suggest that COVID-19 individuals may be predisposed to pulmonary microvascular thrombosis due to a robust inflammatory response and disseminated intravascular coagulation (DIC).We hypothesised that pre-admission antithrombotic therapy, including both antiplatelet and anticoagulant drugs, might affect the clinical course and prognosis of hospitalised COVID-19 patients due to the pathophysiological hypothesis that microvascular thrombotic processes may drive COVID-19-induced ARDS patients.This study found that pre-admission anticoagulation did not affect the clinical presentation of COVID-19 concerning ARDS or in-hospital mortality. Given the complex interplay between clotting system activation and the SARS-CoV2 immuno-mediated inflammatory response, these findings suggest that pre-admission antithrombotic treatment does not affect the pathophysiology of pulmonary microvascular thrombosis in the clinical context of COVID19-induced pneumonia.This study's weaknesses can be attributed to the fact that it was conducted based on past data. Confirmation of our preliminary findings requires more extensive multicenter prospective trials.\ Conclusion:Although our results need confirmation by prospective studies in- including a larger population, the antithrombotic therapy, both anti-platelet and anticoagulant, does not seem to show a protective effect in severe forms of COVID-19 characterized by ARDS and rapidly evolving toward death.Table 1Clinical characteristic of the study population  according to the presence or not of ARDS at admission.   Overall (N = 192) Patients without ARDS (N = 119) Patients with ARDS (N = 73) P Males, n (%) 115 (59.9) 73 (61.3) 42 (57.5) 0.710 Age, mean years (SD) 67.7 (15.2) 66.1 (16.7) 70.3 (12.1) 0.063 Smoke, n (%) 16 (8.3) 11 (9.2) 5 (6.8) 0.754 Hypertension, n (%) 111 (57.8) 59 (49.6) 52 (71.2) 0.005 Diabetes Mellitus, n 42 (21.9) 24 (20.2) 18 (24.7) 0.582 (%) Dyslipidemia   23 (12.0)   12 (10.1)   11 (15.1)   0.422 Obesity, n (%) 26 (13.5) 16 (13.4) 10 (13.7) 1.000 Atrial fibrillation, n (%) 24* (12.5) 12 (10.1) 12 (16.4) 0.286 Heart Failure, n (%) 20 (10.4) 12 (10.1) 8 (11.0) 1.000 Previous Ischemic 16 (8.3) 12 (10.1) 4 (5.5) 0.394 Stroke, n (%) CKD, n (%)   12 (6.2)   4 (3.4)   8 (11.0)   0.071 CAD, n (%) 26 (13.5) 14 (11.8) 12 (16.4) 0.483 COPD, n (%) 26 (13.5) 19 (16.0) 7 (9.6) 0.300 Antiplatelet Therapy, n 55 (28.6) 36 (30.3) 19 (26.0) 0.643 (%) Anticoagulant   26 (13.5)   15 (12.6)   11 (15.1)   0.789 Therapy, n (%)         CAD, coronary artery disease; CKD, chronic kidney disease; COPD, chronic obstructive pulmonary disease. *13 paroxysmal, 7 persistent, 4 permanent. 

Montane birds experience a range of challenges that may limit their breeding success, including nest predation and severe climactic conditions. The continuing effects of climate change are causing shifts in biotic and abiotic factors that may compound these threats to montane bird species. In northeastern montane forests, many bird species are shifting downslope, potentially as the result of increased precipitation and temperature at higher elevations. Although lower elevations might be more favorable in terms of climactic conditions, nest predation is higher at lower elevations. Thus, montane birds might be faced with the opposing pressures of adverse climactic conditions at higher elevations and increased predation at lower elevations. We monitored nests of Swainson’s thrush (Catharus ustulatus) along an elevation gradient in the White Mountain National Forest in New Hampshire in 2016, 2018, 2019 and 2021 to examine the effect of biotic and abiotic factors on nest survival. We found a significant negative effect of rain intensity (millimeters per hour per day) on daily nest survival, suggesting that heavier rain per hour decreases Swainson’s thrush daily daily nest survival. Moreover, we found a negative interaction effect of elevation in conjunction with minimum daily temperature and average daily temperature, suggesting that at higher elevations, temperature, specifically on colder days, decreases Swainson’s thrush nest survival. Our results provide evidence for a potential mechanism of how climate change will affect nesting survival of montane breeding birds as heavier precipitation events become more frequent and intense, a likely outcome due to the changing climate within the White Mountains and other montane ecosystems, putting other passerine species at risk in this system.

1. Conservation detection dogs (CDD) use their exceptional olfactory abilities to assist a range of conservation projects. CDD are generally quicker, can cover wider areas, and find more samples than humans and other analytical tools. However, their efficacy varies between studies; methodological standardisation in the field is lacking. Considering the cost of deploying a CDD team and the limited financial resources within conservation, it is vital that their performance is quantified and reliable. This review aims to summarise what is currently known about the use of detection dogs in conservation and elucidate which factors affect efficacy. 2. We describe the efficacy of CDD across species and situational contexts like training and field work. Reported sensitivities (i.e., proportion of target samples found out of total available) ranged from 23.8% to 100% and precision rates (i.e., proportion of alerts that are true positives) from 28% to 100%. CDD are consistently shown to be better than other techniques, but performance varies substantially across the literature. There is no consistent difference in efficacy between training, testing, and field work, hence we need to understand the factors affecting this. 3. We highlight the key variables that alter CDD performance. External effects include target odour, training methods, sample management, search methodology and environment, and the CDD handler. Internal effects include dog breed, personality, diet, age, and health. Unfortunately, much of the research fails to provide adequate information on the dogs, handlers, training, experience, and samples. This results in an inability to determine precisely why an individual study has high or low efficacy. 4. It is clear that CDD can be applied to possibly limitless scenarios but moving forward researchers must provide more consistent and detailed methodologies so that comparisons can be conducted, results are more easily replicated, and progress can be made in standardising CDD work.