A novel homozygous nonsense variant of AK7 is associated with multiple morphological abnormalities of the sperm flagella.

RESEARCH QUESTION: Is the novel homozygous nonsense variant of AK7 associated with multiple morphological abnormalities of the sperm flagella (MMAF), a specific type of oligoasthenoteratozoospermia leading to male infertility? DESIGN: Whole-exome sequencing and Sanger sequencing were performed to identify potential gene variants. Immunoblotting and immunofluorescence were applied to confirm the relationship between mutated genes and disease phenotypes. The concentration of reactive oxygen species and the rate of apoptosis were measured to evaluate the mitochondrial function of spermatozoa. Transmission electron microscopy and scanning electron microscopy were employed to observe sperm ultrastructure. RESULTS: A novel homozygous nonsense variant of AK7, c.1153A>T (p. Lys385*), was identified in two infertile siblings with asthenoteratozoospermia through whole-exome sequencing. Both immunoblotting and immunofluorescence assays showed practically complete absence of AK7 in the patient's spermatozoa. Additionally, the individual with the novel AK7 variant exhibited a phenotype characterized by severe oxidative stress and apoptosis caused by mitochondrial metabolic dysfunction of spermatozoa. Notably, remarkable flagellar defects with multiple axonemes in uniflagellate spermatozoa, accompanied by mitochondrial vacuolization, were observed; this has not been reported previously in patients with other AK7 variants. CONCLUSIONS: This study found that a novel identified homozygous nonsense variant of AK7 may be associated with MMAF-related asthenoteratozoospermia. The observed functional associations between mitochondria and sperm flagellar assembly provide evidence for potential mutual regulation between AK7 and flagella-associated proteins during spermatogenesis.

Serologic reactivity of unidentified specificity in antenatal testing and hemolytic disease of the fetus and newborn: The BEST collaborative study.

BACKGROUND: The clinical significance of serologic reactivity of unidentified specificity (SRUS) in pregnancy is not clear based on available literature. The aim of this study is to determine if SRUS is associated with hemolytic disease of the fetus and newborn (HDFN). STUDY DESIGN AND METHODS: Retrospective data were collected from eight institutions over an 11-year study period (2010-2020), when available (5/8 sites). The outcome of the pregnancies with SRUS-no, mild, moderate, or severe HDFN-was determined. RESULTS: SRUS was demonstrated in 589 pregnancies. After excluding those with incomplete data, a total of 284 pregnancies were included in the primary HDFN outcome analysis. SRUS was detected in 124 (44%) pregnancies in isolation, and none were affected by HDFN. Of 41 pregnancies with SRUS and ABO incompatibility, 37 (90%) were unaffected, and 4 (10%) were associated with mild HDFN. Of 98 pregnancies with SRUS and concurrent identifiable antibody reactivity(s), 80 (81%) were unaffected, and 19 (19%) were associated with mild to severe HDFN. There was 1 case of mild HDFN and 1 case of severe HDFN in the 21 pregnancies with SRUS, ABO incompatibility, and concurrent identifiable antibody reactivity(s), and 19 (90%) were unaffected by HDFN. Among all patients with repeat testing, newly identified alloantibodies or other antibodies were identified in 63 of 212 (30%) patients. Although most were not clinically significant, on occasion SRUS preceded clinically significant antibody(s) associated with HDFN (3%, 5/188). CONCLUSION: The antenatal serologic finding of SRUS in isolation is not associated with HDFN but may precede clinically significant antibodies.

An endometrium of type C along with an endometrial thickness of < 8 mm are risk factors for ectopic pregnancy after stimulated cycles with fresh embryo transfer.

BACKGROUND: The study investigated whether specific ultrasonographically observed endometrial features (including endometrium type and thickness) were linked to ectopic pregnancy after stimulated cycles with fresh embryo transfer. METHOD: Of 6246 pregnancy cycles after fresh embryo transfer, 6076 resulted in intrauterine pregnancy and 170 in ectopic pregnancy. The primary outcome of the study was ectopic pregnancy, with the main variables being endometrium type and endometrial thickness. Univariate and subsequent multiple-stepwise logistic regression analyses were used to identify the risk factors of ectopic pregnancy. RESULTS: 1. Compared with patients with an endometrial thickness ≥ 8 mm, the adjusted odds ratio for those with an endometrial thickness < 8 mm was 3.368 (P < 0.001). The adjusted odds ratio for women with a type-C endometrium was 1.897 (P = 0.019) compared with non-type C. 2. A larger dose of gonadotropin used during controlled ovarian hyperstimulation was a protective factor against ectopic pregnancy (P = 0.008). 3. The GnRH antagonist protocol (P = 0.007) was a risk factor for ectopic pregnancy, compared with the use of GnRH agonists. CONCLUSION: (1) An endometrial thickness < 8 mm coupled with a type C endometrium significantly increased the risk of ectopic pregnancy after fresh embryo transfer. (2) A thin endometrial thickness and a type C endometrium could be further related to an abnormal endometrial receptivity/peristaltic wave. (3) Patients at a high risk of ectopic pregnancy should therefore be given special attention, with early diagnosis during the peri-transplantation period may assist in the prevention of ectopic pregnancy.

Loss of phenotypic inheritance associated with ydcI mutation leads to increased frequency of small, slow persisters in Escherichia coli.

Whenever a genetically homogenous population of bacterial cells is exposed to antibiotics, a tiny fraction of cells survives the treatment, the phenomenon known as bacterial persistence [G.L. Hobby et al., Exp. Biol. Med. 50, 281-285 (1942); J. Bigger, The Lancet 244, 497-500 (1944)]. Despite its biomedical relevance, the origin of the phenomenon is still unknown, and as a rare, phenotypically resistant subpopulation, persisters are notoriously hard to study and define. Using computerized tracking we show that persisters are small at birth and slowly replicating. We also determine that the high-persister mutant strain of Escherichia coli, HipQ, is associated with the phenotype of reduced phenotypic inheritance (RPI). We identify the gene responsible for RPI, ydcI, which encodes a transcription factor, and propose a mechanism whereby loss of phenotypic inheritance causes increased frequency of persisters. These results provide insight into the generation and maintenance of phenotypic variation and provide potential targets for the development of therapeutic strategies that tackle persistence in bacterial infections.

Two-Level Attention Module Based on Spurious-3D Residual Networks for Human Action Recognition.

In recent years, deep learning techniques have excelled in video action recognition. However, currently commonly used video action recognition models minimize the importance of different video frames and spatial regions within some specific frames when performing action recognition, which makes it difficult for the models to adequately extract spatiotemporal features from the video data. In this paper, an action recognition method based on improved residual convolutional neural networks (CNNs) for video frames and spatial attention modules is proposed to address this problem. The network can guide what and where to emphasize or suppress with essentially little computational cost using the video frame attention module and the spatial attention module. It also employs a two-level attention module to emphasize feature information along the temporal and spatial dimensions, respectively, highlighting the more important frames in the overall video sequence and the more important spatial regions in some specific frames. Specifically, we create the video frame and spatial attention map by successively adding the video frame attention module and the spatial attention module to aggregate the spatial and temporal dimensions of the intermediate feature maps of the CNNs to obtain different feature descriptors, thus directing the network to focus more on important video frames and more contributing spatial regions. The experimental results further show that the network performs well on the UCF-101 and HMDB-51 datasets.

Phosphoric-Acid Retention in High-Temperature Proton-Exchange Membranes.

Great efforts have been conducted to develop high temperature proton exchange membrane fuel cell (HT-PEMFC) due to its features of enhanced electrocatalyst reactivity, simplified hydrothermal management system and high CO tolerance of catalysts, and remarkable progress has been achieved. However, the easy leaching of phosphoric acid (PA) from the membranes during operation limits its commercial scale-up in complicated environments. This concept here mainly focuses on the recent developments for mitigation of PA loss in PEMs. The probable mechanisms of PA loss are proposed. The approaches to improve PA retention for example via introduction of phosphonic acid by covalent bond, using ion-pairs interaction and siphoning effect, and blending with inorganic nanoparticles are described in detail. Among these strategies, the siphoning effect from the intrinsic microporous PEMs is the most efficient and enables the cell to operate flexibly within a broad temperature range. Therefore, this concept may provide new ideas for the scientists to retain PA, to improve the cell performance and expand the potential applications of PA doped PEMs at elevated humidity and wide temperature range.

Hospital red blood cell and platelet supply and utilization from March to December of the first year of the COVID-19 pandemic: The BEST collaborative study.

BACKGROUND: At the start of the coronavirus disease 2019 (COVID-19) pandemic, widespread blood shortages were anticipated. We sought to determine how hospital blood supply and blood utilization were affected by the first wave of COVID-19. STUDY DESIGN AND METHODS: Weekly red blood cell (RBC) and platelet (PLT) inventory, transfusion, and outdate data were collected from 13 institutions in the United States, Brazil, Canada, and Denmark from March 1st to December 31st of 2020 and 2019. Data from the sites were aligned based on each site's local first peak of COVID-19 cases, and data from 2020 (pandemic year) were compared with data from the corresponding period in 2019 (pre-pandemic baseline). RESULTS: RBC inventories were 3% lower in 2020 than in 2019 (680 vs. 704, p < .001) and 5% fewer RBCs were transfused per week compared to 2019 (477 vs. 501, p < .001). However, during the first COVID-19 peak, RBC and PLT inventories were higher than normal, as reflected by deviation from par, days on hand, and percent outdated. At this time, 16% fewer inpatient beds were occupied, and 43% fewer surgeries were performed compared to 2019 (p < .001). In contrast to 2019 when there was no correlation, there was, in 2020, significant negative correlations between RBC and PLT days on hand and both percentage occupancy of inpatient beds and percentage of surgeries performed. CONCLUSION: During the COVID-19 pandemic in 2020, RBC and PLT inventories remained adequate. During the first wave of cases, significant decreases in patient care activities were associated with excess RBC and PLT supplies and increased product outdating.

A Low Complexity Persistent Reconnaissance Algorithm for FANET.

In recent years, with the rapid progress of unmanned aerial vehicle (UAV) technology, UAV-based systems have been widely used in both civilian and military applications. Researchers have proposed various network architectures and routing protocols to address the network connectivity problems associated with the high mobility of UAVs, and have achieved considerable results in a flying ad hoc network (FANET). Although scholars have noted various threats to UAVs in practical applications, such as local magnetic field variation, acoustic interference, and radio signal hijacking, few studies have taken into account the dynamic nature of these threat factors. Moreover, the UAVs' high mobility combined with dynamic threats makes it more challenging to ensure connectivity while adapting to ever-changing scenarios. In this context, this paper introduces the concept of threat probability density function (threat PDF) and proposes a particle swarm optimization (PSO)-based threat avoidance and reconnaissance FANET construction algorithm (TARFC), which enables UAVs to dynamically adapt to avoid high-risk areas while maintaining FANET connectivity. Inspired by the graph editing distance, the total edit distance (TED) is defined to describe the alterations of the FANET and threat factors over time. Based on TED, a dynamic threat avoidance and continuous reconnaissance FANET operation algorithm (TA&CRFO) is proposed to realize semi-distributed control of the network. Simulation results show that both TARFC and TA&CRFO are effective in maintaining network connectivity and avoiding threats in dynamic scenarios. The average threat value of UAVs using TARFC and TA&CRFO is reduced by 3.99~27.51% and 3.07~26.63%, respectively, compared with the PSO algorithm. In addition, with limited distributed moderation, the complexity of the TA&CRFO algorithm is only 20.08% of that of TARFC.

An Improved Q-Learning-Based Sensor-Scheduling Algorithm for Multi-Target Tracking.

Target tracking is an essential issue in wireless sensor networks (WSNs). Compared with single-target tracking, how to guarantee the performance of multi-target tracking is more challenging because the system needs to balance the tracking resource for each target according to different target properties and network status. However, the balance of tracking task allocation is rarely considered in those prior sensor-scheduling algorithms, which may result in the degradation of tracking accuracy for some targets and additional system energy consumption. To address this issue, we propose in this paper an improved Q-learning-based sensor-scheduling algorithm for multi-target tracking (MTT-SS). First, we devise an entropy weight method (EWM)-based strategy to evaluate the priority of targets being tracked according to target properties and network status. Moreover, we develop a Q-learning-based task allocation mechanism to obtain a balanced resource scheduling result in multi-target-tracking scenarios. Simulation results demonstrate that our proposed algorithm can obtain a significant enhancement in terms of tracking accuracy and energy efficiency compared with the existing sensor-scheduling algorithms.

Entropy Measures of Electroencephalograms towards the Diagnosis of Psychogenic Non-Epileptic Seizures.

Psychogenic non-epileptic seizures (PNES) may resemble epileptic seizures but are not caused by epileptic activity. However, the analysis of electroencephalogram (EEG) signals with entropy algorithms could help identify patterns that differentiate PNES and epilepsy. Furthermore, the use of machine learning could reduce the current diagnosis costs by automating classification. The current study extracted the approximate sample, spectral, singular value decomposition, and Renyi entropies from interictal EEGs and electrocardiograms (ECG)s of 48 PNES and 29 epilepsy subjects in the broad, delta, theta, alpha, beta, and gamma frequency bands. Each feature-band pair was classified by a support vector machine (SVM), k-nearest neighbour (kNN), random forest (RF), and gradient boosting machine (GBM). In most cases, the broad band returned higher accuracy, gamma returned the lowest, and combining the six bands together improved classifier performance. The Renyi entropy was the best feature and returned high accuracy in every band. The highest balanced accuracy, 95.03%, was obtained by the kNN with Renyi entropy and combining all bands except broad. This analysis showed that entropy measures can differentiate between interictal PNES and epilepsy with high accuracy, and improved performances indicate that combining bands is an effective improvement for diagnosing PNES from EEGs and ECGs.

Facilitating diabetic retinopathy screening using automated retinal image analysis in underresourced settings.

AIM: To evaluate an automated retinal image analysis (ARIA) of indigenous retinal fundus images against a human grading comparator for the classification of diabetic retinopathy (DR) status. METHODS: Indigenous Australian adults with type 2 diabetes (n = 410) from three remote and very remote primary-care services in the Northern Territory, Australia, underwent teleretinal DR screening. A single, central retinal fundus photograph (opportunistic mydriasis) for each eye was later regraded using a single ARIA and a UK human grader and national DR classification system. The sensitivity and specificity of ARIA were assessed relative to the comparator. Proportionate agreement and a Kappa statistic were also computed. RESULTS: Retinal images from 391 and 393 participants were gradable for 'Any DR' by the human grader and ARIA grader, respectively. 'Any DR' was detected by the human grader in 185 (47.3%) participants and by ARIA in 202 (48.6%) participants (agreement =88.0%, Kappa = 0.76,), whereas proliferative DR was detected in 31 (7.9%) and 37 (9.4%) participants (agreement = 98.2%, Kappa = 0.89,), respectively. The ARIA software had 91.4 (95% CI, 86.3-95.0) sensitivity and 85.0 (95% CI, 79.3-89.5) specificity for detecting 'Any DR' and 96.8 (95% CI, 83.3-99.9) sensitivity and 98.3 (95% CI, 96.4-99.4) specificity for detecting proliferative DR. CONCLUSIONS: This ARIA software has high sensitivity for detecting 'Any DR', hence could be used as a triage tool for human graders. High sensitivity was also found for detection of proliferative DR by ARIA. Future versions of this ARIA should include maculopathy and referable DR (CSME and/or PDR). Such ARIA software may benefit diabetes care in less-resourced regions.

Associations between dyslipidaemia and pregnancy outcomes in the first complete cycle of IVF/ICSI: a real-world analysis.

RESEARCH QUESTION: Are there associations between dyslipidaemia and pregnancy outcomes in the first complete cycle of IVF/intracytoplasmic sperm injection (ICSI)? DESIGN: This long-term, retrospective real-world analysis involved 5030 infertile women who underwent a first complete IVF/ICSI cycle between January 2015 and October 2020. They were categorized into dyslipidaemia (n = 1903) and control (n = 3127) groups according to serum lipid concentrations before ovarian stimulation. Propensity score matching and multivariable logistic regression were used to control for confounding variables. RESULTS: In the raw cohort, women with dyslipidaemia had a significantly increased late miscarriage rate (P = 0.039), decreased term birth rate (P = 0.002) and decreased live birth rate (P = 0.005) compared with non-dyslipidaemic women. In the propensity score-matched cohort, the term birth rate (P = 0.038) and live birth rate (P = 0.044) were significantly lower in the dyslipidaemia group (n = 1686) than the controls (n = 1686). Multivariable logistic regression indicated that infertile women with dyslipidaemia (P = 0.026) and elevated serum total cholesterol concentrations (total cholesterol ≥5.20 mmol/l; P = 0.028) were significantly less likely to have a live birth. Rates of late miscarriage (P = 0.027), term birth (P = 0.003) and live birth (P = 0.010) differed significantly among women with normal, borderline increased and increased serum lipid concentrations. Compared with controls, women with increased serum lipid concentrations had a significantly higher late miscarriage rate, lower term birth rate and lower live birth rate. Women with increased serum lipid concentrations were significantly less likely than controls to have a live birth. CONCLUSIONS: Dyslipidaemia, total cholesterol ≥5.20 mmol/l and degrees of elevated serum lipid concentrations are negatively associated with live birth rate in the first complete IVF/ICSI cycle in infertile women.

Enhanced recovery after surgery promotes the postoperative recovery of lung and gastrointestinal function of pseudomyxoma peritonei. / åŠ é€Ÿåº·å¤å¤–ç§‘ä¿ƒè¿›è ¹è†œå‡é»æ¶²ç˜¤æœ¯åŽè‚ºä¸Žèƒƒè‚ é“åŠŸèƒ½çš„åº·å¤.

OBJECTIVES: Pseudomyxoma peritonei (PMP) is a rare low-grade malignant tumor, which is difficult to operate with many postoperative complications. In recent years, enhanced recovery after surgery (ERAS) has been greatly developed in the perioperative management of surgical diseases, and it plays an important role in improving the postoperative prognosis of surgical patients. This study was conducted to explore the application of ERAS in the perioperative management of PMP patients, and to study the effect of ERAS on postoperative respiratory and digestive tract complications. METHODS: We retrospectively analyzed clinical data of patients with PMP from January 2014 to December 2018. These patients were treated with surgery in our center and they were divided into an observation group and a control group. The patients in the control group didn't perform ERAS in perioperative period, and patients in the observation group was performed ERAS. Then, we analyzed and compared the postoperative pulmonary complications (PPC) and gastrointestinal function between the 2 groups. RESULTS: There was no significant difference in the incidence of atelectasis, pleural effusion, pulmonary infection and acute respiratory distress syndrome (ARDS) between the two groups, but the total incidence of PPC in the observation group was significantly lower than that in the control group (P=0.032). The incidence of postoperative gastrointestinal dysfunction (PGID) in the observation group was significantly lower than that in the control group (P=0.025), and the postoperative first exhaust time, first defecation time, oral feeding time, and albumin level in the observation group were all better than those in the control group (all P<0.05). CONCLUSIONS: ERAS can significantly reduce the incidence of postoperative PPC and PGID in the PMP patients and improve their postoperative recovery.

miR-155-5p is Negatively Associated with Acute Pancreatitis and Inversely Regulates Pancreatic Acinar Cell Progression by Targeting Rela and Traf3.

BACKGROUND/AIMS: Acute pancreatitis contributes to high mortality in pancreatitis patients, and miRNAs play a vital role in the development of acute pancreatitis (AP), however, its precise biological role remains largely elusive. METHODS: To clarify the potential mechanisms of miRNAs in AP, we built mouse models of mild acute pancreatitis (MAP) and moderate/ severe acute pancreatitis (SAP). MiRNA microarray analysis and Real-time quantitative PCR (qRT-PCR) were used to analyze the expression of miRNA in MAP/SAP. TargetScan software, dual-luciferase gene reporter assays and Western blotting were used to assess the target genes of miR-155-5p in AP. RESULTS: miR-155-5p was significantly decreased in MAP/SAP mice compared to controls. In pancreatic acinar AR42J cells transfected with miR-155-5p mimic, the expression of Rela and Traf3 notably decreased in both the caerulein- and TLC-S-induced groups compared with the negative control (NC); however, the expression of Rela and Traf3 notably increased after transfection with miR-155-5p inhibitor. Combined analysis using the TargetScan software and dual-luciferase gene reporter assays indicated that Rela and Traf3 were both targeted by miR-155-5p. Meanwhile, the expression of Ptgs2 also decreased after transfection of the AR42J cells with miR-155-5p mimic. The opposite results were found when miR-155-5p inhibitor was transfected into the AR42J cells. In addition, we treated caerulein- and TLC-S-induced AR42J cells with the Rela inhibitor helenalin and found that the expression of Rela, Traf3 and Ptgs2 decreased compared with the NC, while the expression of miR-155-5p did not show any significant difference. Furthermore, we found that miR-155-5p was significantly down-regulated in pancreatitis patients. CONCLUSION: miR-155-5p inversely regulated AP development through the Rela/Traf3/Ptgs2 signaling pathway.

Endothelial Cell-Specific Deletion of P2Y2 Receptor Promotes Plaque Stability in Atherosclerosis-Susceptible ApoE-Null Mice.

OBJECTIVE: Nucleotide P2Y2 receptor (P2Y2R) contributes to vascular inflammation by increasing vascular cell adhesion molecule-1 expression in endothelial cells (EC), and global P2Y2R deficiency prevents fatty streak formation in apolipoprotein E null (ApoE-/-) mice. Because P2Y2R is ubiquitously expressed in vascular cells, we investigated the contribution of endothelial P2Y2R in the pathogenesis of atherosclerosis. APPROACH AND RESULTS: EC-specific P2Y2R-deficient mice were generated by breeding VEcadherin5-Cre mice with the P2Y2R floxed mice. Endothelial P2Y2R deficiency reduced endothelial nitric oxide synthase activity and significantly altered ATP- and UTP (uridine 5'-triphosphate)-induced vasorelaxation without affecting vasodilatory responses to acetylcholine. Telemetric blood pressure and echocardiography measurements indicated that EC-specific P2Y2R-deficient mice did not develop hypertension. We investigated the role of endothelial P2Y2R in the development of atherosclerotic lesions by crossing the EC-specific P2Y2R knockout mice onto an ApoE-/- background and evaluated lesion development after feeding a standard chow diet for 25 weeks. Histopathologic examination demonstrated reduced atherosclerotic lesions in the aortic sinus and entire aorta, decreased macrophage infiltration, and increased smooth muscle cell and collagen content, leading to the formation of a subendothelial fibrous cap in EC-specific P2Y2R-deficient ApoE-/- mice. Expression and proteolytic activity of matrix metalloproteinase-2 was significantly reduced in atherosclerotic lesions from EC-specific P2Y2R-deficient ApoE-/- mice. Furthermore, EC-specific P2Y2R deficiency inhibited nitric oxide production, leading to significant increase in smooth muscle cell migration out of aortic explants. CONCLUSIONS: EC-specific P2Y2R deficiency reduces atherosclerotic burden and promotes plaque stability in ApoE-/- mice through impaired macrophage infiltration acting together with reduced matrix metalloproteinase-2 activity and increased smooth muscle cell migration.

Dynamic Hierarchical Energy-Efficient Method Based on Combinatorial Optimization for Wireless Sensor Networks.

Routing protocols based on topology control are significantly important for improving network longevity in wireless sensor networks (WSNs). Traditionally, some WSN routing protocols distribute uneven network traffic load to sensor nodes, which is not optimal for improving network longevity. Differently to conventional WSN routing protocols, we propose a dynamic hierarchical protocol based on combinatorial optimization (DHCO) to balance energy consumption of sensor nodes and to improve WSN longevity. For each sensor node, the DHCO algorithm obtains the optimal route by establishing a feasible routing set instead of selecting the cluster head or the next hop node. The process of obtaining the optimal route can be formulated as a combinatorial optimization problem. Specifically, the DHCO algorithm is carried out by the following procedures. It employs a hierarchy-based connection mechanism to construct a hierarchical network structure in which each sensor node is assigned to a special hierarchical subset; it utilizes the combinatorial optimization theory to establish the feasible routing set for each sensor node, and takes advantage of the maximum-minimum criterion to obtain their optimal routes to the base station. Various results of simulation experiments show effectiveness and superiority of the DHCO algorithm in comparison with state-of-the-art WSN routing algorithms, including low-energy adaptive clustering hierarchy (LEACH), hybrid energy-efficient distributed clustering (HEED), genetic protocol-based self-organizing network clustering (GASONeC), and double cost function-based routing (DCFR) algorithms.

An Effective and Robust Decentralized Target Tracking Scheme in Wireless Camera Sensor Networks.

In this paper, we propose an effective and robust decentralized tracking scheme based on the square root cubature information filter (SRCIF) to balance the energy consumption and tracking accuracy in wireless camera sensor networks (WCNs). More specifically, regarding the characteristics and constraints of camera nodes in WCNs, some special mechanisms are put forward and integrated in this tracking scheme. First, a decentralized tracking approach is adopted so that the tracking can be implemented energy-efficiently and steadily. Subsequently, task cluster nodes are dynamically selected by adopting a greedy on-line decision approach based on the defined contribution decision (CD) considering the limited energy of camera nodes. Additionally, we design an efficient cluster head (CH) selection mechanism that casts such selection problem as an optimization problem based on the remaining energy and distance-to-target. Finally, we also perform analysis on the target detection probability when selecting the task cluster nodes and their CH, owing to the directional sensing and observation limitations in field of view (FOV) of camera nodes in WCNs. From simulation results, the proposed tracking scheme shows an obvious improvement in balancing the energy consumption and tracking accuracy over the existing methods.

Spectrally encoded extended source optical coherence tomography.

We have developed an extended source optical coherence tomography (SEES-OCT) technique in an attempt to improve signal strength for ophthalmic imaging. A line illumination with a visual angle of 7.9 mrad is produced by introducing a dispersive element in the infinity space of the sample arm. The maximum permissible exposure (MPE) of such an extended source is 3.1 times larger than that of a "standard" point source OCT, which corresponds to sensitivity improvement of 5 dB. The advantage of SEES-OCT in providing superior penetration depth over a point source system is demonstrated using swine eye tissues ex vivo.

Real-time processing for frequency domain optical imaging based on field programmable gated arrays.

Frequency domain optical imaging (OFDI) provides high resolution and sensitivity. However, the speed of the data processing program in C language limits its application. A real-time imaging system of OFDI based on field programmable gate arrays (FPGAs) is proposed. It adopts a high-speed digitizer board PXI14400 from Signatec for interferometric data acquisition. The acquired data is processed in the user defined FPGA on board in real-time with a pipeline data processing algorithm. The algorithm eliminates the complex conjugate ambiguity, overcomes the swept laser source's nonlinearity in k-space, and allows the data to be processed continuously. We also provide an economic method of IQ demodulation for FPGA data processing. The design breaks through the speed bottleneck of data processing, and allows the system to process each sample point at a frequency of 200 MHz.

Unraveling pathogenesis, biomarkers and potential therapeutic agents for endometriosis associated with disulfidptosis based on bioinformatics analysis, machine learning and experiment validation.

BACKGROUND: Endometriosis (EMs) is an enigmatic disease of yet-unknown pathogenesis. Disulfidptosis, a novel identified form of programmed cell death resulting from disulfide stress, stands a chance of treating diverse ailments. However, the potential roles of disulfidptosis-related genes (DRGs) in EMs remain elusive. This study aims to thoroughly explore the key disulfidptosis genes involved in EMs, and probe novel diagnostic markers and candidate therapeutic compounds from the aspect of disulfidptosis based on bioinformatics analysis, machine learning, and animal experiments. RESULTS: Enrichment analysis on key module genes and differentially expressed genes (DEGs) of eutopic and ectopic endometrial tissues in EMs suggested that EMs was closely related to disulfidptosis. And then, we obtained 20 and 16 disulfidptosis-related DEGs in eutopic and ectopic endometrial tissue, respectively. The protein-protein interaction (PPI) network revealed complex interactions between genes, and screened nine and ten hub genes in eutopic and ectopic endometrial tissue, respectively. Furthermore, immune infiltration analysis uncovered distinct differences in the immunocyte, human leukocyte antigen (HLA) gene set, and immune checkpoints in the eutopic and ectopic endometrial tissues when compared with health control. Besides, the hub genes mentioned above showed a close correlation with the immune microenvironment of EMs. Furthermore, four machine learning algorithms were applied to screen signature genes in eutopic and ectopic endometrial tissue, including the binary logistic regression (BLR), the least absolute shrinkage and selection operator (LASSO), the support vector machine-recursive feature elimination (SVM-RFE), and the extreme gradient boosting (XGBoost). Model training and hyperparameter tuning were implemented on 80% of the data using a ten-fold cross-validation method, and tested in the testing sets which determined the excellent diagnostic performance of these models by six indicators (Sensitivity, Specificity, Positive Predictive Value, Negative Predictive Value, Accuracy, and Area Under Curve). And seven eutopic signature genes (ACTB, GYS1, IQGAP1, MYH10, NUBPL, SLC7A11, TLN1) and five ectopic signature genes (CAPZB, CD2AP, MYH10, OXSM, PDLIM1) were finally identified based on machine learning. The independent validation dataset also showed high accuracy of the signature genes (IQGAP1, SLC7A11, CD2AP, MYH10, PDLIM1) in predicting EMs. Moreover, we screened 12 specific compounds for EMs based on ectopic signature genes and the pharmacological impact of tretinoin on signature genes was further verified in the ectopic lesion in the EMs murine model. CONCLUSION: This study verified a close association between disulfidptosis and EMs based on bioinformatics analysis, machine learning, and animal experiments. Further investigation on the biological mechanism of disulfidptosis in EMs is anticipated to yield novel advancements for searching for potential diagnostic biomarkers and revolutionary therapeutic approaches in EMs.