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Peripheral arterial disease (PAD) affects over 236 million people globally, with endovascular treatment as the predominant mode of revascularization. While pre-procedural lesion assessment typically relies on non-invasive Doppler measurement, invasive physiological assessment offers a promising approach to guide lesion selection and provide real-time evaluation of angioplasty success. This review explores the current methods, challenges, and future directions of invasive physiological assessment in PAD. Sensor-tipped wires, particularly pressure sensor-tipped wires (pressure-wires), enable precise evaluation of stenoses through indices such as peripheral fractional flow reserve (pFFR) measured during hyperaemia. pFFR can identify significant flow-limiting lesions, assess angioplasty efficacy, and predict tissue healing. Additional indices, including Doppler-wire derived flow reserves and resistance measurements, further enhance the understanding of lesion physiology. Early data support the utility of these techniques for guiding treatment decisions, although the variability in methodologies highlights the need for standardization and outcome-driven cut-off values. This review uniquely consolidates evidence on invasive physiological assessment in PAD, addressing critical gaps and providing a framework for future research. By advancing lesion-specific evaluation and procedural optimization, this work underscores the transformative potential of these techniques in improving patient outcomes and redefining PAD management.

Continuous Thermodilution is a novel method of quantifying coronary flow (Q) in mL/min. To account for variability of Q within the cardiac cycle, the trace is smoothened with a 2 s moving average filter. This can sometimes be ineffective due to significant heart rate variability, ventricular extrasystoles, and deep inspiration, resulting in a fluctuating temperature trace and ambiguity in the location of the “steady state”. This study aims to assess whether a longer moving average filter would smoothen any fluctuations within the continuous thermodilution traces resulting in improved interpretability and reproducibility on a test–retest basis. Patients with ANOCA underwent repeat continuous thermodilution measurements. Analysis of traces were performed at averages of 10, 15, and 20 s to determine the maximum acceptable average. The maximum acceptable average was subsequently applied as a moving average filter and the traces were re-analysed to assess the practical consequences of a longer moving average. Reproducibility was then assessed and compared to a 2 s moving average. Of the averages tested, only 10 s met the criteria for acceptance. When the data was reanalysed with a 10 s moving average filter, there was no significant improvement in reproducibility, however, it resulted in a 12% diagnostic mismatch. Applying a longer moving average filter to continuous thermodilution data does not improve reproducibility. Furthermore, it results in a loss of fidelity on the traces, and a 12% diagnostic mismatch. Overall, current practice should be maintained.

Intracoronary continuous thermodilution has been recently proposed as an invasive method to quantify absolute coronary flow (Qabs) and resistance (Rabs) in vivo. The aim of the present study is to develop and validate of a novel pressure-wire- and microcatheter-free surrogate of coronary flow and resistance derived from a standard coronary angiogram. Angiography derived coronary flow (Qangio) and resistance (Rangio) was prospectively validated in a two-center cohort of patients from Oxford Heart Centre and the Essex Cardiothoracic Centre. Qabs and Rabs were measured during resting and hyperemic conditions with continuous thermodilution using the Rayflow microcatheter. Qangio and Rangio were computed from the diagnostic coronary angiogram in a blinded fashion in resting and hyperemic conditions. A total of 62 patients and 115 vessels were included in the present analysis. The median Qabs at rest was 75 ml/min (53–95) and 151 ml/min (105–203) during hyperemia; Qangio at rest was 84 ml/min (66–108) and 154 ml/min (115–195) during hyperemia. There was a strong correlation between Qabs and Qangio (R = 0,72; p < 0.001, R = 0,86; p < 0.001 respectively) with satisfactory interclass correlation (0.841, 95% CI 0.509–0.957; p = 0.0003). The median Rabs was 1111 mmHg/(L/min) (830-1581.4) at rest and 454 mmHg/(L/min) (348–610) during hyperemia; angiographic resistance (Rangio) was 937.4 mmHg/(L/min) (695.4–1261.9) at rest and 492.4 mmHg/(L/min) (406–697) during hyperemia. There was a strong correlation between Rabs and Rangio in both conditions (R = 0,81; p < 0.001 and R = 0,78; p < 0.001 respectively). The was a good correlation between absolute coronary flow reserve (CFR) and angiography-derived CFR (R = 0,61; p < 0.001) and between absolute microvascular resistance reserve (MRR) and angiography-derived MRR (R = 0,49; p < 0.001).Condensed abstractWe developed and validated a novel non-invasive, fully angiographic, pressure-wire- and microcatheter-free method to quantify coronary flow and resistance in resting and hyperemic conditions. Angiography-derived coronary flow and resistance was prospectively validated in a two-center cohort of 62 patients and 115 vessels against absolute coronary flow and resistance measured with Rayflow microcatheter. We found a strong correlation between angiography-derived flow and resistance and absolute coronary flow and resistance, with satisfactory interclass correlation. There was a good correlation between absolute coronary flow reserve (CFR) and angiography-derived CFR and between absolute microvascular resistance reserve (MRR) and angiography-derived MRR.

It is common knowledge that organizations today face the challenges of growing competition. Therefore, organizations need to develop smarter to plan for several diverse and real-time challenges. The aim of this paper is to test the impact of knowledge management (KM) processes, organizational capabilities (OC), and mediating KM mechanisms and KM technologies toward a smart organization (SO). In this paper, structural equation modeling was applied by using Smart PLS 3.3.3 software to test hypotheses and the accuracy of the suggested model. The results showed a direct impact between all constructs and are a reflection of the SO of the employees (N=225) working in three Jordanian telecommunications companies. Additionally, the outcomes provision the partial mediating role of KM mechanisms and KM technology with OC in the SO. These outcomes can support leaders in generating a consciousness in addition to favorable OC, KM mechanisms, and KM technologies inside the organization, which enables the actual implementation of SO and uses the outcomes to plan their SO strategies.

Background: To assess whether hydrostatic pressure gradients caused by coronary height differences in supine versus prone positioning during invasive physiological stenosis assessment affect resting and hyperaemic pressure-based indices or coronary flow. Methods: Twenty-three coronary stenoses were assessed in twenty-one patients with stable coronary artery disease. All patients had a stenosis of at least 50% visually defined on previous coronary angiography. Pd/Pa, iFR, FFR, and coronary flow velocity (APV) measured using a Doppler were recorded across the same stenosis, with the patient in the prone position, followed by repeat measurements in the standard supine position. Results: When comparing prone to supine measurements in the same stenosis, in the LAD, there was a significant change in mean Pd/Pa of 0.08 ± 0.04 (p = 0.0006), in the iFR of 0.06 ± 0.07 (p = 0.02), and in the FFR of 0.09 ± 0.07 (p = 0.003). In the Cx, there was a change in mean Pd/Pa of 0.05 ± 0.04 (p = 0.009), iFR of 0.07 ± 0.04 (p = 0.01), and FFR of 0.05 ± 0.03 (p = 0.006). In the RCA, there was a change in Pd/Pa of 0.05 ± 0.04 (p = 0.032), iFR of 0.04 ± 0.05 (p = 0.19), and FFR of 0.04+−0.03 (p = 0.004). Resting and hyperaemic coronary flow did not change significantly (resting delta APV = 1.6 cm/s, p = 0.31; hyperaemic delta APV = 0.9 cm/s, p = 0.85). Finally, 36% of iFR measurements and 26% of FFR measurements were re-classified across an ischaemic threshold when prone and supine measurements were compared across the same stenosis. Conclusions: Pd/Pa, iFR, and FFR were affected by hydrostatic pressure variations caused by coronary height differences in prone versus supine positioning. Coronary flow did not change signifying a purely pressure-based phenomenon.

One of the common types of cancer for women is ovarian cancer. Still, at present, there are no drug therapies that can properly cure this deadly disease. However, early-stage detection could boost the life expectancy of the patients. The main aim of this work is to apply machine learning models along with statistical methods to the clinical data obtained from 349 patient individuals to conduct predictive analytics for early diagnosis. In statistical analysis, Student’s t-test as well as log fold changes of two groups are used to find the significant blood biomarkers. Furthermore, a set of machine learning models including Random Forest (RF), Support Vector Machine (SVM), Decision Tree (DT), Extreme Gradient Boosting Machine (XGBoost), Logistic Regression (LR), Gradient Boosting Machine (GBM) and Light Gradient Boosting Machine (LGBM) are used to build classification models to stratify benign-vs.-malignant ovarian cancer patients. Both of the analysis techniques recognized that the serumsamples carbohydrate antigen 125, carbohydrate antigen 19-9, carcinoembryonic antigen and human epididymis protein 4 are the top-most significant biomarkers as well as neutrophil ratio, thrombocytocrit, hematocrit blood samples, alanine aminotransferase, calcium, indirect bilirubin, uric acid, natriumas as general chemistry tests. Moreover, the results from predictive analysis suggest that the machine learning models can classify malignant patients from benign patients with accuracy as good as 91%. Since generally, early-stage detection is not available, machine learning detection could play a significant role in cancer diagnosis.

Background Knowing what to eat and realizing the significance of healthful eating habits are among the important steps to promoting eating behavior. The current study aims to assess the nutrition knowledge (NK) among a convenient sample in four different countries, determine the association between different demographic factors and NK, and investigate the need for future interventions on nutrition in the four selected countries. Methods A cross-sectional multi-national survey study among a convenient sample of 8,191 subjects from Egypt, Syria, Saudi Arabia, and Jordan who undertook surveys between January 2019 and January 2020. A pre-tested interview questionnaire was utilized for data collection from study participants. It included three sections: i) Sociodemographic characteristics:. ii). Section two included twenty-one questions related to NK.. iii). Section three included one question about NK sources. Results About three-quarters showed inadequate nutrition knowledge (73.1%). Youth (15–24 yrs.) were more dependent on social media, with 87% using it as a primary source of NK, while adults (≥ 25 yrs.) demonstrated that 43% of them used social media. In contrast, TV was more prominent among them, with participants’ characteristics such as living with parents, body mass index, and country of residence showing no association with NK. However, female sex, education, and reading nutrition articles are significantly correlated with adequate knowledge ( p  < 0.001). Significant predictors of satisfactory knowledge were age, sex, education, living with parents, and reading nutrition articles. Conclusion The study revealed low levels of NK indicating an urgent need to implement educational programs to promote nutrition knowledge. As NK is a modifiable determinant of diet intake and can positively impact the need for developing strategies in counselling and raising awareness among the general population to improve their health status.

LoRaWAN is a popular internet of things (IoT) solution over the unlicensed radio band. It sustains low-cost, durable, and long range IoT wireless communications. Nonetheless, with over 24 billion connected IoT devices being expected by the end of the year, and over 50 billion by 2025, the concurrent and legacy approaches to spreading factor and channel assignment in LoRaWAN networks can no longer keep up. This is exacerbated with the growing densification of IoT device deployments and, with the increasing requirements for better throughput and packet delivery ratios. In this paper, we propose a proportional fair-based joint optimal formulation for spreading factor and channel assignment in multi-operator LoRaWAN deployments. The objective of this problem is to maximize the total sum of the logarithmic normalized throughput. We split the problem into two subproblems, and propose a game theoretic approach to solving them. We prove that our games converge towards a pure Nash equilibrium and, afterwards, solve the optimization problems using both semi-distributed and completely distributed algorithms. Via simulations, we show that our algorithms greatly improve the total normalized throughput for LoRaWAN as well as the packet success rate, in comparison to the legacy approaches.

Contemporary progress in telecommunication technologies have made full-duplex wireless communications feasible. The latter promise to double the capacity of wireless networks by allowing devices to concurrently transmit and receive on the same radio resources. In this paper, we devise mathematical optimal formulations for scheduling in full-duplex and hybrid full-duplex/half-duplex orthogonal frequency division multiple access networks. Our optimal models are queue-aware and address the new interferences that arise from working with full-duplex wireless networks: self-interference and intra-cell co-channel interference. We apply these models with different scheduling objectives, tackling issues such as signal-to-interference-plus-noise ratio (SINR) maximization and user fairness. Accordingly, we first propose an optimal full-duplex Max-SINR algorithm and an optimal full-duplex Proportional Fair algorithm. Additionally, and since full-duplex communications may not always be profitable, we introduce an optimal hybrid Max-SINR algorithm and an optimal hybrid Proportional Fair algorithm. These algorithms switch between full-duplex and half-duplex transmissions, so as to enhance network performance. Moreover, to avoid possible intractability with the optimization problems, we propose heuristic versions of our algorithms. We simulate these proposals, showing that they achieve near optimal performances, and asserting the different gains they attain with respect to their half-duplex counterparts: more than a 50% increase in user equipment throughput values alongside a three fold decrease in the average user equipment waiting delay.

Breeding for resistance to Fusarium head blight (FHB) pathogens often relies on irrigation before and shortly after anthesis to encourage disease development. However, some reports investigated the effects of post-anthesis weather on FHB growth in bread heads. To elucidate this, the impact of moisture on the development of FHB in three bread wheat of contrasting FHB susceptibility and infected with 16 fungal isolates of diverse aggressiveness of four different fungal species was examined. A pot experiment under natural climatic conditions was designed as split-split-plot with five replicates. Main plots were durations of spraying-irrigation of 0, 7, 14, 21, and 28 days; sub-plots were bread wheat cultivars; and sub-sub-plots were the FHB isolates. Incidence (DI) and severity (DS) of FHB were assessed 21 days after inoculation, and Fusarium-damaged kernel (FDK) percentages were determined on harvested grain. No significant differences were observed between treatments receiving the least amount of spraying-irrigation, suggesting that extended moisture promotes FHB development. As a result, 21 or 28 days of spraying had the same effect and were associated with an increase in mean DI, DS and FDK compared with 0 or 7 days of spraying, and 14 days of spraying was also associated with an increase in mean of these pathogenic criteria. This is the first investigation to show that extended post-flowering moisture can have a significant enhancing effect on DI, DS and FDK following infection with F. culmorum, F. solani, F. verticillioides, and F. equiseti, and is harmony with earlier reports conduced with bread wheat infected with F. graminearum.