Current Animal Models of Postoperative Spine Infection and Potential Future Advances.

Implant related infection following spine surgery is a devastating complication for patients and can potentially lead to significant neurological compromise, disability, morbidity, and even mortality. This paper provides an overview of the existing animal models of postoperative spine infection and highlights the strengths and weaknesses of each model. In addition, there is discussion regarding potential modifications to these animal models to better evaluate preventative and treatment strategies for this challenging complication. Current models are effective in simulating surgical procedures but fail to evaluate infection longitudinally using multiple techniques. Potential future modifications to these models include using advanced imaging technologies to evaluate infection, use of bioluminescent bacterial species, and testing of novel treatment strategies against multiple bacterial strains. There is potential to establish a postoperative spine infection model using smaller animals, such as mice, as these would be a more cost-effective screening tool for potential therapeutic interventions

Towards Analyzing Semantic Robustness of Deep Neural Networks

Despite the impressive performance of Deep Neural Networks (DNNs) on various vision tasks, they still exhibit erroneous high sensitivity toward semantic primitives (e.g. object pose). We propose a theoretically grounded analysis for DNN robustness in the semantic space. We qualitatively analyze different DNNs' semantic robustness by visualizing the DNN global behavior as semantic maps and observe interesting behavior of some DNNs. Since generating these semantic maps does not scale well with the dimensionality of the semantic space, we develop a bottom-up approach to detect robust regions of DNNs. To achieve this, we formalize the problem of finding robust semantic regions of the network as optimizing integral bounds and we develop expressions for update directions of the region bounds. We use our developed formulations to quantitatively evaluate the semantic robustness of different popular network architectures. We show through extensive experimentation that several networks, while trained on the same dataset and enjoying comparable accuracy, do not necessarily perform similarly in semantic robustness. For example, InceptionV3 is more accurate despite being less semantically robust than ResNet50. We hope that this tool will serve as a milestone towards understanding the semantic robustness of DNNs.Comment: Presented at European conference on computer vision (ECCV 2020) Workshop on Adversarial Robustness in the Real World ( https://eccv20-adv-workshop.github.io/ ) [best paper award]. The code is available at https://github.com/ajhamdi/semantic-robustnes

The First Record of Argulus foliacesus (Crustacea: Branchiura) Infestation on Lionhead Goldfish (Carassius auratus) in Iran

Argulus foliaceus (Crustacea: Branchiura), or the fish louse, is an ectoparasite of the skin or gill of the fresh water fish species. Clinical signs in infected fish include scratching on aquarium walls, erratic swimming, and poor growth. It causes pathological changes due to direct tissue damage and secondary infections. In the present study, lionhead goldfish (Carassius auratus), taken from a goldfish aquarium with symptoms such as abnormal swimming, poor growth and death, were examined for ectoparasites. The parasites collected from the skin and fins of fish were identified as A. foliaceus. Then, treatment was carried out by trichlorfon. After administration, no parasite was observed on the fish. This is the first report of infection with A. foliaceus of lionhead goldfish (Carassius auratus) in Iran

Postural Changes in Blood Pressure Associated with Interactions between Candidate Genes for Chronic Respiratory Diseases and Exposure to Particulate Matter

BACKGROUND. Fine particulate matter [aerodynamic diameter ≤ 2.5 μm (PM2.5)] has been associated with autonomic dysregulation. OBJECTIVE. We hypothesized that PM2.5 influences postural changes in systolic blood pressure (ΔSBP) and in diastolic blood pressure (ΔDBP) and that this effect is modified by genes thought to be related to chronic lung disease. METHODS. We measured blood pressure in participants every 3-5 years. ΔSBP and ΔDBP were calculated as sitting minus standing SBP and DBP. We averaged PM2.5 over 48 hr before study visits and analyzed 202 single nucleotide polymorphisms (SNPs) in 25 genes. To address multiple comparisons, data were stratified into a split sample. In the discovery cohort, the effects of SNP x PM2.5 interactions on ΔSBP and ΔDBP were analyzed using mixed models with subject-specific random intercepts. We defined positive outcomes as p < 0.1 for the interaction; we analyzed only these SNPs in the replicate cohort and confirmed them if p < 0.025 with the same sign. Confirmed associations were analyzed within the full cohort in models adjusted for anthropometric and lifestyle factors. RESULTS. Nine hundred forty-five participants were included in our analysis. One interaction with rs9568232 in PHD finger protein 11 (PHF11) was associated with greater ΔDBP. Interactions with rs1144393 in matrix metalloprotease 1 (MMP1) and rs16930692, rs7955200, and rs10771283 in inositol 1,4,5-triphosphate receptor, type 2 (ITPR2) were associated with significantly greater ΔSBP. Because SNPs associated with ΔSBP in our analysis are in genes along the renin-angiotensin pathway, we then examined medications affecting that pathway and observed significant interactions for angiotensin receptor blockers but not angiotensin-converting enzyme inhibitors with PM2.5. CONCLUSIONS. PM2.5 influences blood pressure and autonomic function. This effect is modified by genes and drugs that also act along this pathway.National Institute of Environmental Health Sciences (T32 ES07069, ES0002, ES015172-01, ES014663, P01 ES09825); United States Environmental Protection Agency (R827353, R832416); National Institutes of Health/National Institute of Aging (AG027014); United States Department of Veterans Affairs; Massachusetts Veterans Epidemiology Research and Information Cente

New Spectrophotometric Methods for the Determination of p-Aminosalicylic Acid in Tablets

Purpose: To develop a new spectrophotometric method with improved sensitivity and at higher wavelength for the determination of p-aminosalicylic acid in tablets.Methods: Two simple and sensitive spectrophotometric methods (methods A and B) were developed using p-dimethylaminobenzaldehyde (DAB), and p-dimethylaminocinnamaldehyde (DAC) as derivatizing reagents for the determination of p-aminosalicylic acid (PAS) in tablets. The derivatization was carried out using 3M HCl-KCl buffer for DAB and 5M HCl-KCl buffer solutions.Result: The new derivatives of PAS absorbed maximally with bathochromic shift to 460 and 555 nm in the linear concentration range of 0.4 – 2.0 μg/mL with molar absorptivities of 2.4 × 104 and 3.8 × 104 L/mole/cm, respectively, compared to pure PAS which absorbed at λmax of 264 nm with molar absorptivity 7.65 × 103 L/mole/cm in the linear concentration range of 2 - 10 μg/mL. The developed methods were successfully applied to assay PAS in tablets with % recovery of 97.6 ± 1.71 and 98.4 ± 1.45 for methods A and B, respectively.Conclusion: Both PAS derivatives absorb in the visible spectral region. The presence of excipients in pharmaceutical preparations did not interfere in the determination of PAS as PAS-DAB and PAS-DAC derivatives. Both methods can be applied to determine PAS from bulk and various pharmaceutical dosage forms.Keywords: p-Aminosalicylic acid, p-dimethylaminobenzaldehyde, p-dimethylaminocinnamaldehyde, Spectrophotometr

Impact of mobility on the IoT MAC infrastructure: IEEE 802.15.4e TSCH and LLDN platform

Realizing the target of high reliability and availability is a crucial concept in the IoT context. Different types of IoT applications introduce several requirements and obstacles. One of the important aspects degrading network performance is the node mobility inside the network. Without a solid and adaptive mechanism, node mobility can disrupt the network performance due to dissociations from the network. Hence, reliable techniques must be incorporated to tackle the overhead of node movement. In this paper, the overhead of mobility on both IEEE 802.15.4e timeslotted channel hopping (TSCH) and low latency deterministic (LLDN) modes is investigated. These two modes can be considered as the MAC layer of the IoT paradigm because of their importance and resilience to different network obstacles. In addition, the set of metrics and limitations that influence the network survivability will be identified to ensure efficient mobile node handling process. Both TSCH and LLDN have been implemented via the Contiki OS to determine their functionality. TSCH has been demonstrated to have better node connectivity due to the impact of frame collision in LLDN. In addition, by neglecting the overhead of collision, the LLDN has been shown to have better connectivity and low radio duty cycle (RDC)

Dynamic cluster head election protocol for mobile wireless sensor networks

A dynamic cluster head election protocol (DCHEP) is proposed in this work to improve network availability and energy efficiency for mobile wireless sensor networks (WSNs) under the beacon-enabled IEEE 802.15.4 standard. The proposed protocol (DCHEP) is developed and simulated using CASTALIA/OMNET++ with a realistic radio model and node behaviour. DCHEP improves the network availability and lifetime and maintains clusters hierarchy in a proactive manner even in a mobile WSN where all the nodes including cluster heads (CHs) are mobile, this is done by dynamically switching CHs allowing nodes to act as multiple backup cluster heads (BCHs) with different priorities based on their residual energy and connectivity to other clusters. DCHEP is a flexible and scalable solution targeted for dense WSNs with random mobility. The proposed protocol achieves an average of 33% and 26% improvement to the availability and energy efficiency respectively compared with the original standard

Mesh-under cluster-based routing protocol for IEEE 802.15.4 sensornetwork

The radio duty cycle (RDC) of wireless sensor nodes can be considered as a crucial factor that determines the wireless sensor network (WSN) lifetime and its service availability. Clustering would be a preferable solution to minimize node radio duty cycle by electing multiple cluster heads (CHs) around the network to schedule node transmissions and collect readings. This paper presents a mesh-under cluster-based routing (MUCBR) protocol that will divide the sensor network into multiple clusters and perform the routing function within the IEEE 802.15.4 platform. MUCBR is implemented via the Contiki operating system (OS). It reschedules the structure of the 802.15.4 standard in order to reduce the RDC of the sensor nodes and minimize the number of collisions. The election of the CHs is density-aware and determined by the routing direction inside the network which in turn reduces the number of hops and minimizes the number of collisions caused by the existence of multiple CHs in a single area. The proposed MUCBR manages to achieve a RDC of 0.08% for non-CH nodes and 1.3% for CH nodes while reducing the impact of collision by 40% as compared to the 802.15.4 standard

Tackling Mobility in Low Latency Deterministic Multihop IEEE 802.15.4e Sensor Network

Providing reliable services for low latency (LL) applications within the IoT context is a challenging issue. Several wireless sensor network (WSN) applications require deterministic systems that ensure a reliable and low latency aggregation service. The IEEE 802.15.4e standard, which is considered as the backbone of the IoT regarding WSN, has presented the low-latency deterministic network mode (LLDN) that can fulfil the major requirements of low latency applications. Meanwhile, several LL applications, for example in the automotive industry, demand the support of sensor node mobility which in turn affects network performance. Node mobility triggers several dissociations from the network that will increase latency and degrade node throughput. In this paper, we investigate the impact of node mobility over the LLDN mode while defining key factors that maximize latency and degrade throughput. In addition, an enhanced version of the LLDN mode is presented and evaluated that supports node mobility while maintaining the targeted limits of LL application requirements. The proposed mobility aware (MA-LLDN) technique manages to reduce the dissociation overhead by a factor of 75% while the packet delivery ratio (PDR) has been enhanced by 30%. Furthermore, this paper presents an analytical model that provides a snapshot of the tradeoff process between different metrics in the IEEE 802.15.4e LLDN design, which must be considered prior network deployment in mobile LL applications