The traditional A* algorithm suffers from issues such as sharp turning points in the path, weak directional guidance during the search, and a large number of computed nodes. To address these ...problems, a modified approach called the Directional Search A* algorithm along with a path smoothing technique has been proposed. Firstly, the Directional Search A* algorithm introduces an angle constraint condition through the evaluation function. By converting sharp turns into obtuse angles, the path turning points become smoother. This approach reduces the occurrence of sharp turns in the path, resulting in improved path smoothness. Secondly, the algorithm enhances the distance function to strengthen the directional guidance during the path search. By optimizing the distance function, the algorithm tends to prefer directions that lead towards the target, which helps reduce the search space and shorten the overall path planning time. Additionally, the algorithm removes redundant nodes along the path, resulting in a more concise path representation. Lastly, the algorithm proposes an improved step size adjustment method to optimize the number of path nodes obtained. By appropriately adjusting the step size, the algorithm further reduces the number of nodes, leading to improved path planning efficiency. By applying these methods together, the Directional Search A* algorithm effectively addresses the limitations of the traditional A* algorithm and produces smoother and more efficient path planning results. Simulation experiments comparing the modified A* algorithm with the traditional A* algorithm were conducted using MATLAB. The experimental results demonstrate that the improved A* algorithm can generate shorter paths, with reduced planning time and smoother trajectories. This indicates that the Directional Search A* algorithm, incorporating the angle constraint condition in the evaluation function and the direction-guided strategy, outperforms the traditional A* algorithm in path planning and provides better solutions to the existing issues.
Unsupervised clustering of intensive care unit (ICU) medications may identify unique medication clusters (i.e., pharmacophenotypes) in critically ill adults. We performed an unsupervised analysis ...with Restricted Boltzmann Machine of 991 medications profiles of patients managed in the ICU to explore pharmacophenotypes that correlated with ICU complications (e.g., mechanical ventilation) and patient-centered outcomes (e.g., length of stay, mortality). Six unique pharmacophenotypes were observed, with unique medication profiles and clinically relevant differences in ICU complications and patient-centered outcomes. While pharmacophenotypes 2 and 4 had no statistically significant difference in ICU length of stay, duration of mechanical ventilation, or duration of vasopressor use, their mortality differed significantly (9.0% vs. 21.9%, p < 0.0001). Pharmacophenotype 4 had a mortality rate of 21.9%, compared with the rest of the pharmacophenotypes ranging from 2.5 to 9%. Phenotyping approaches have shown promise in classifying the heterogenous syndromes of critical illness to predict treatment response and guide clinical decision support systems but have never included comprehensive medication information. This first-ever machine learning approach revealed differences among empirically-derived subgroups of ICU patients that are not typically revealed by traditional classifiers. Identification of pharmacophenotypes may enable enhanced decision making to optimize treatment decisions.
Bensulfuron methyl (BSM) is a widely used sulfonylurea herbicide in agriculture. However, the large-scale BSM application causes severe environmental problems. Biodegradation is an important way to ...remove BSM residue. In this study, an endophytic bacterium strain CD3, newly isolated from barnyard grass (
Echinochloa crus-galli
), could effectively degrade BSM in mineral salt medium. The strain CD3 was identified as
Proteus
sp. based on the phenotypic features, physiological biochemical characteristics, and 16S rRNA gene sequence. The suitable conditions for BSM degradation by this strain were 20–40°C, pH 6–8, the initial concertation of 12.5–200 mg L
−1
with 10 g L
−1
glucose as additional carbon source. The endophyte was capable of degrading above 98% BSM within 7 d under the optimal degrading conditions. Furthermore, strain CD3 could also effectively degrade other sulfonylurea herbicides including nicosulfuron, halosulfuron methyl, pyrazosulfuron, and ethoxysulfuron. Extracellular enzyme played a critical role on the BSM degradation by strain CD3. Two degrading metabolites were detected and identified by using liquid chromatography–mass spectrometry (LC–MS). The biochemical degradation pathways of BSM by this endophyte were proposed. The genomic analysis of strain CD3 revealed the presence of putative hydrolase or esterase genes involved in BSM degradation, suggesting that a novel degradation enzyme for BSM was present in this BSM-degrading
Proteus
sp. CD3. The results of this research suggested that strain CD3 may have potential for using in the bioremediation of BSM-contaminated environment.
Dihydrotestosterone (DHT) is the most potent androgen that regulates hair cycling. Hair cycling involves cross-talk between the androgen and Wnt/β-catenin pathways. However, how DHT regulates hair ...follicle (HF) growth through the Wnt/β-catenin pathway has not been well investigated. This study aimed to investigate the roles of DHT in hair growth
and
. Human scalp HFs were treated with different concentrations of DHT (10
, 10
, 10
, 10
, and 10
mol/L) for 10 days. The effects of DHT on hair shaft elongation, the proliferation of hair matrix cells, and the levels of β-catenin, GSK-3β, and phosphorylated GSK-3β (ser9) were evaluated in the cultured HFs. The effects of DHT were further investigated in C57BL/6 mice. Moreover, the growth of cultured human HFs was observed after interfering with the β-catenin pathway through inhibitors or activators in the presence or absence of DHT. We found that different concentrations of DHT had different effects on human HFs
and C57BL/6 mice. At 10
mol/L, DHT inhibited HF growth and β-catenin/p-GSK-3β expression, whereas 10
mol/L DHT induced HF growth and β-catenin/p-GSK-3β expression. In addition, a β-catenin inhibitor (21H7) inhibited HF growth
, while a β-catenin activator (IM12) promoted HF growth
and antagonized the inhibition of HFs by high levels of DHT. These results suggest that DHT plays a pivotal role in region-specific hair growth, which may be related to the Wnt/β-catenin pathway.
Fluid overload, while common in the ICU and associated with serious sequelae, is hard to predict and may be influenced by ICU medication use. Machine learning (ML) approaches may offer advantages ...over traditional regression techniques to predict it. We compared the ability of traditional regression techniques and different ML-based modeling approaches to identify clinically meaningful fluid overload predictors. This was a retrospective, observational cohort study of adult patients admitted to an ICU ≥ 72 h between 10/1/2015 and 10/31/2020 with available fluid balance data. Models to predict fluid overload (a positive fluid balance ≥ 10% of the admission body weight) in the 48-72 h after ICU admission were created. Potential patient and medication fluid overload predictor variables (n = 28) were collected at either baseline or 24 h after ICU admission. The optimal traditional logistic regression model was created using backward selection. Supervised, classification-based ML models were trained and optimized, including a meta-modeling approach. Area under the receiver operating characteristic (AUROC), positive predictive value (PPV), and negative predictive value (NPV) were compared between the traditional and ML fluid prediction models. A total of 49 of the 391 (12.5%) patients developed fluid overload. Among the ML models, the XGBoost model had the highest performance (AUROC 0.78, PPV 0.27, NPV 0.94) for fluid overload prediction. The XGBoost model performed similarly to the final traditional logistic regression model (AUROC 0.70; PPV 0.20, NPV 0.94). Feature importance analysis revealed severity of illness scores and medication-related data were the most important predictors of fluid overload. In the context of our study, ML and traditional models appear to perform similarly to predict fluid overload in the ICU. Baseline severity of illness and ICU medication regimen complexity are important predictors of fluid overload.
In this study, we investigate the structural characteristics of the upper-level outflow and its impact on the rapid intensification (RI) of Typhoon Roke (2011), which experienced an evident outflow ...transformation from equatorward to poleward during its RI period. The simulations by the Weather Research and Forecasting Model suggest that the upper-level outflow extends from 100 hPa to 150 hPa, with an upper-level warm core at around 150 hPa. The upper-level outflow is enhanced ahead of the typhoon intensification, which is closely related to the outflow-environment interaction. Further analyses indicate that at the early stage of Roke (2011) before the RI, the strong equatorward outflow and the updraft south of the typhoon center are enhanced, favoring the onset of RI. During the RI period, the strong divergent flow near the entrance of the southwesterly jet in front of the upper-level trough, induces the poleward outflow. The eddy flux convergence of angular momentum inward propagated to the typhoon center from a 1000-km radius further enhances the poleward outflow and leads to the development of the vertical motion north of the typhoon center. Then Roke (2011) intensifies rapidly. Simultaneously, the shallow weak positive potential vorticity (PV) anomaly south of the southwesterly jet increases the inner-core PV, favoring the sustained intensification of Roke (2011). After Roke (2011) reaches its peak intensity, its intensity decreases due to the increase of vertical wind shear and the approaching of the southwesterly jet. It is indicated that the interaction between the upper-level outflow and the upper-tropospheric trough has significant influence on the RI of TC.
While medication regimen complexity, as measured by a novel medication regimen complexity-intensive care unit (MRC-ICU) score, correlates with baseline severity of illness and mortality, whether the ...MRC-ICU improves hospital mortality prediction is not known. After characterizing the association between MRC-ICU, severity of illness and hospital mortality we sought to evaluate the incremental benefit of adding MRC-ICU to illness severity-based hospital mortality prediction models. This was a single-center, observational cohort study of adult intensive care units (ICUs). A random sample of 991 adults admitted ≥ 24 h to the ICU from 10/2015 to 10/2020 were included. The logistic regression models for the primary outcome of mortality were assessed via area under the receiver operating characteristic (AUROC). Medication regimen complexity was evaluated daily using the MRC-ICU. This previously validated index is a weighted summation of medications prescribed in the first 24 h of ICU stay e.g., a patient prescribed insulin (1 point) and vancomycin (3 points) has a MRC-ICU = 4 points. Baseline demographic features (e.g., age, sex, ICU type) were collected and severity of illness (based on worst values within the first 24 h of ICU admission) was characterized using both the Acute Physiology and Chronic Health Evaluation (APACHE II) and the Sequential Organ Failure Assessment (SOFA) score. Univariate analysis of 991 patients revealed every one-point increase in the average 24-h MRC-ICU score was associated with a 5% increase in hospital mortality Odds Ratio (OR) 1.05, 95% confidence interval 1.02-1.08, p = 0.002. The model including MRC-ICU, APACHE II and SOFA had a AUROC for mortality of 0.81 whereas the model including only APACHE-II and SOFA had a AUROC for mortality of 0.76. Medication regimen complexity is associated with increased hospital mortality. A prediction model including medication regimen complexity only modestly improves hospital mortality prediction.
Extreme hourly precipitation is amongst the most prominent driving factors of flash floods and geological disasters. Based on the hourly precipitation data of 35 stations in the Three Gorges ...Reservoir Region (TGRR) from 1998 to 2020, we analyzed the spatiotemporal variation characteristics of hourly extreme precipitation indexes. The selected indicators included the frequency, intensity, period, annual maximum, trend of hourly heavy precipitation (20–50 mm/h) and hourly extreme heavy precipitation (≥50 mm/h) in the TGRR. Closely related climatic factors such as the Western Pacific Subtropical High Intensity (WPSHI) were also discussed. The results showed that in 2010–2020, the cumulative frequency of heavy precipitation magnitude between 25 and 40 mm/h slightly increased, while the corresponding frequency for magnitudes ≥50 mm/h decreased. In summer, the frequency of both heavy and extreme heavy precipitation increased in June and decreased in August, indicating a shift of extreme events to an earlier time in the flood season. The cumulative frequency of heavy precipitation in July had a period of about 7a, and that of extreme heavy precipitation had a period of 3a. The annual average intensity of heavy precipitation and extreme heavy precipitation in the TGRR was 28.9 mm/h and 61.4 mm/h per station, respectively, and both fluctuated and insignificantly decreased from 1998 to 2020. The annual maximum hourly precipitation center in the TGRR moved downstream from west to northeast. The frequency of heavy precipitation was relatively small along the main stream of the river valley. Both the frequency and total amount of heavy precipitation in southeast of the TGRR were significantly higher than those in other regions. Heavy precipitation in the majority of stations with high elevation (higher than 500 m) showed a decreasing trend. The cumulative frequency of precipitation with an intensity of 20–50 mm/h was closely correlated with the Western Hemisphere Warm Pool (WHWP) Index in February and the WPSHI Index in January, and especially, the abnormal large annual frequency (top 20%) showed strong correlation with the two indexes, implying highly predictable factors for extreme events. The frequency of precipitation intensity above 50 mm/h was correlated with the Western Pacific Warm Pool (WPWP) Area Index in January and the WPWP Intensity Index in November of last year. The research results provide a strong and refined factual basis for the assessment and prediction of extreme precipitation, and for disaster prevention and mitigation, in the TGRR.
Purpose
To compare the differences between involved-field irradiation (IFI) and elective nodal irradiation (ENI) in selecting the optimal target area for neoadjuvant chemoradiotherapy (nCRT) in ...patients with locally advanced esophageal squamous cell carcinoma (LA-ESCC).
Materials and methods
We retrospectively analyzed 267 patients with LA-ESCC, of whom 165 underwent ENI and 102 underwent IFI. Dosimetry, treatment-related complications, pathological responses, recurrence/metastasis patterns, and survival were compared between the two groups.
Results
The median follow-up duration was 27.9 months. The R0 resection rates in the IFI and ENI groups were 95.1% and 92.7%, respectively (
p
=0.441), while the pathological complete response (pCR) rates were 42.2% and 34.5%, respectively (
p
=0.12). The ENI group received higher radiation doses to the heart (HV
30
:23.9%
vs
. 18%,
p
=0.033) and lungs (LV
30
:7.7%
vs.
4.9%,
p
<0.001) than the IFI group. Consequently, the ENI group showed a higher incidence of grade 2 or higher radiation pneumonitis (30.3%
vs.
17.6%,
p
=0.004) and pericardial effusion (26.7%
vs.
11.8%,
p
=0.021) than the IFI group. Post-operation fistulas were observed in 3 (2.9%) and 17 cases (10.3%) in the IFI and ENI groups, respectively (
p
=0.026). In the multivariate analysis, smoking, positive lymph node involvement (pN+), and anastomotic fistula were independent predictors of overall survival (OS). The pN+ patients exhibited a greater propensity for recurrence compared to pN- patients, especially in the first year of follow-up (6.67%
vs.
0.56%,
p
=0.003).
Conclusion
The ENI group had a higher incidence of radiation-induced adverse events compared to the IFI group, likely due to the higher radiation doses to normal tissues. Considering the similar disease-free survival (DFS) and OS rates in the two groups, IFI may be suitable for nCRT in patients with LA-ESCC, although further prospective studies are warranted.
Mangrove ecosystems can be both significant sources and sinks of greenhouse gases. The restoration of mangrove forests is increasingly used as a natural climate solution tool to mitigate climate ...change. However, the estimates of carbon exchanges remain unclear, especially from restored mangroves. In this study, we observed the temporal variations in carbon dioxide (CO2) and methane (CH4) fluxes and their biophysical controls for 4 years, based on a closed-path eddy covariance (EC) system. The measurements were conducted in a mangrove wetland park with 14-year-old restored mangroves surrounded by open waters in Guangdong Province, China. The EC measurements showed that the mangrove ecosystem acted as a CO2 source with a net CO2 ecosystem exchange (NEE) of 305 g C m−2 from January 2019 to May 2020 by the 5-m tower measurement. After the tower was adjusted to 10 m, the mangrove showed a CO2 sink with an NEE of −345 g C m−2 from June 2020 to December 2022. The change in tower height influenced the interpretation of interannual trends on NEE. There were no significant interannual trends in the gross primary productivity (GPP) and the ecosystem respiration (Re) values. The change from CO2 source to sink may be attributed to the decrease in land surface proportion by the tower replacement, which reduces the proportion of the mangrove canopy respiration and, therefore, captures lower CO2 fluxes from open waters. The restored mangroves indicated strong CH4 sources of 23.2–26.3 g C m−2 a−1. According to the random forest analysis, the land surface proportion, radiation, and relative humidity were the three most important predictors of NEE, while the CH4 flux was most sensitive to air temperature. Compared to the natural and long-term restored mangroves, this 14-year-old restored mangrove had not yet achieved a maximum carbon sequestration capability. Our study highlights the need for the careful design of long-term observations from restored mangroves and proposes future needs in the context of carbon neutrality.
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