Search Results (284)

Background: Cardiac surgery patients with pre- or post-operative atrial fibrillation are at an increased risk for thromboembolic stroke, often due left atrial appendage (LAA) thrombus. Surgical LAA exclusion (LAAE) can be performed and must be complete to avoid increased thrombus formation. Methods: This prospective, multi-center, post-market study (NCT05101993) evaluated the long-term safety and performance of the epicardial V-shape AtriClip device. Patients ≥18 years who had received V-shape AtriClip devices during non-emergent cardiac surgery consented to a prospective 12-month follow-up visit and LAA imaging. The primary performance was LAAE without residual left atrium-LAA communication, assessed by imaging at the last follow-up visit. The primary safety was device- or implant procedure-related serious adverse events (SAEs) (death, major bleeding, surgical site infection, pericardial effusion requiring intervention, myocardial infarction) within 30 days. Results: Of 155 patients from 11 U.S. centers, 151 patients had evaluable imaging. Complete LAAE was obtained in all patients. Primary performance in the intent-to-treat population was met, with 97% (95% CI 93.52%, 99.29%; p = 0.0001) complete LAAE. Primary safety was met, with 100% (95% CI 97.75%, 100%; p < 0.0001) of patients free from pre-defined SAEs within 30 days. One device-related SAE was reported, which resolved intraprocedurally. Conclusions: AtriClip V-Clip showed safe and successful LAAE through 12 months of follow-up. Full article

Phytate, an antinutritional molecule in poultry feed, can be degraded by applying phytase, but its use in low- and middle-income countries is often limited due to importation instead of local production. Here, inexpensive raw materials were used to optimize the production of a thermostable phytase from an indigenous strain of Bacillus subtilis SP11 that was isolated from a broiler farm in Dhaka. SP11 was identified using 16s rDNA and the fermentation of phytase was optimized using a Plackett–Burman design and response surface methodology, revealing that three substrates, including the raw material mustard meal (2.21% w/v), caused a maximum phytase production of 436 U/L at 37 °C and 120 rpm for 72 h, resulting in a 3.7-fold increase compared to unoptimized media. The crude enzyme showed thermostability up to 80 °C (may withstand the feed pelleting process) with an optimum pH of 6 (near pH of poultry small-intestine), while retaining 96% activity at 41 °C (the body temperature of the chicken). In vitro dephytinization demonstrated its applicability, releasing 978 µg of inorganic phosphate per g of wheat bran per hour. This phytase has the potential to reduce the burden of phytase importation in Bangladesh by making local production and application possible, contributing to sustainable poultry nutrition. Full article

Vibrio parahaemolyticus is a major foodborne pathogen worldwide, responsible for seafood-associated poisoning. Among its toxin genes, tdh2 is the most critical. To investigate the role of tdh2 in V. parahaemolyticus under gastrointestinal conditions, we constructed tdh2 deletion and complementation strains and compared their survival under acid (pH 3 and 4) and bile stress (2%). The results showed that tdh2 expression was significantly upregulated under cold (4 °C) and bile stress (0.9%). Survival assays and PI staining revealed that the tdh2 mutant strain (VP: △tdh2) was more sensitive to acid and bile stress than the wild-type (WT), and this sensitivity was rescued by tdh2 complementation. These findings suggest that tdh2 plays a protective role in enhancing V. parahaemolyticus tolerance to acid and bile stress. In the VP: △tdh2 strain, seven genes were significantly upregulated and six were downregulated as a result of tdh2 deletion. These genes included VPA1332 (vtrA), VPA1348 (vtrB), VP2467 (ompU), VP0301 and VP1995 (ABC transporters), VP0527 (nhaR), and VP2553 (rpoS), among others. Additionally, LC-MS/MS analysis identified 12 differential metabolites between the WT and VP: △tdh2 strains, including phosphatidylserine (PS) (17:2 (9Z,12Z) /0:0 and 20:1 (11Z) /0:0), phosphatidylglycerol (PG) (17:0/0:0), flavin mononucleotide (FMN), and various nucleotides. The protective mechanism of tdh2 may involve preserving cell membrane permeability through regulation of ompU and ABC transporters and enhancing electron transfer efficiency via regulation of nhaR. The resulting reduction in ATP, DNA, and RNA synthesis—along with changes in membrane permeability and electron transfer due to decreased FMN—likely contributed to the reduced survival of the VP: △tdh2 strain. Meanwhile, the cells actively synthesized phospholipids to repair membrane damage, leading to increased levels of PS and PG. This study provides important insights into strategies for preventing and controlling food poisoning caused by tdh⁺ V. parahaemolyticus. Full article

With the rapid advancement of UAV-based remote sensing and image recognition techniques, identifying environmental risk factors from aerial imagery has emerged as a focal point in intelligent inspection during the power transmission and distribution projects construction phase. The uneven spatial distribution of risk factors on construction sites, their weak texture signatures, and the inherently multi-scale nature of UAV imagery pose significant detection challenges. To address these issues, we propose a one-stage SRW-YOLO algorithm built upon the YOLOv11 framework. First, a P2-scale shallow feature detection layer is added to capture high-resolution fine details of small targets. Second, we integrate a reparameterized convolution based on channel shuffle (RCS) of a one-shot aggregation (RCS-OSA) module into the backbone and neck’s shallow layers, enhancing feature extraction while significantly reducing inference latency. Finally, a dynamic non-monotonic focusing mechanism WIoU v3 loss function is employed to reweigh low-quality annotations, thereby improving small-object localization accuracy. Experimental results demonstrate that SRW-YOLO achieves an overall precision of 80.6% and mAP of 79.1% on the State Grid dataset, and exhibits similarly superior performance on the VisDrone2019 dataset. Compared with other one-stage detectors, SRW-YOLO delivers markedly higher detection accuracy, offering critical technical support for multi-scale, heterogeneous environmental risk monitoring during the power transmission and distribution projects construction phase, and establishes the theoretical foundation for rapid and accurate inspection using UAV-based intelligent imaging. Full article

Background/Objectives: Hispanic adolescents experience elevated rates of disordered eating behaviors and body dissatisfaction, yet limited research has examined how gender and weight status interact to shape these risks within this population. Methods: A cross-sectional survey was conducted among 680 Hispanic adolescents (ages 9–15) from a predominantly Mexican-American middle school. Participants completed the Modified Kids Eating Disorder Survey (M-KEDS), and height and weight were objectively measured to determine BMI-for-age percentile. Chi-square tests, Mann–Whitney U tests, and logistic regression were used to assess differences by gender and weight status, including interaction effects. Bonferroni correction was applied for multiple comparisons. Effect sizes (Cramér’s V, odds ratios with 95% CI) were reported. Results: Approximately 73% of participants reported body dissatisfaction, with significant differences observed by gender and weight status. Adolescents with overweight/obesity reported significantly higher negative weight attitudes and extreme weight control behaviors than healthy-weight peers (p < 0.001), with large effect sizes. Females endorsed more disordered attitudes and behaviors, except for exercise to lose weight, which was more common among overweight/obese males. Conclusions: These findings underscore the high prevalence and significance of disordered eating behaviors in Hispanic adolescents, including those at a healthy weight. Results highlight the importance of culturally tailored, gender-sensitive screening and prevention strategies. Schools serve as critical settings for early identification, and tools like the M-KEDS can help address disparities in care access and improve outcomes among Hispanic youth. Full article

An expanded Pacific Earthquake Engineering Research (PEER) Center Next Generation Attenuation Phase 2 (NGA-West2) ground motion database, compiled using shallow crustal earthquakes in active crustal regions (ACRs), was used to develop the closed-form GS24b backbone ground motion model (GMM) for the RotD50 horizontal components of peak ground acceleration (PGA), peak ground velocity (PGV), and 5% damped elastic pseudo-absolute response spectral accelerations (SA). The GS24b model is applicable to earthquakes with moment magnitudes of 4.0 ≤ M ≤ 8.5, at rupture distances of 0 ≤ $R_{rup}$ ≤ 400 km, with time-averaged S-wave velocity in the upper 30 m of the profile at 150 ≤ $V_{S30}$ ≤ 1500 m/s, and for periods of 0.01 ≤ T ≤ 10 s. The new backbone model includes $V_{S30}$ site correction developed based on multiple representative S-wave velocity profiles. For crustal wave attenuation, we used the apparent anelastic attenuation of SA—Q_SA (f, M). In contrast to the GK17, the GS24b backbone is a generic ACR model designed specifically to be adjusted to any ACRs. The GS24bc is an example of a partially non-ergodic model created by adjusting the backbone GS24b model for magnitude M, S-wave velocity $V_{S30}$, and fault rupture distance residuals. Full article

This paper mainly studies the existence of sign-changing solutions for the following $p\left(x\right)$-biharmonic Kirchhoff-type equations: $-\left(a+b{\int }_{{\mathbb{R}}^N}{\displaystyle \frac{1}{p\left(x\right)}}{|\Delta u|}^{p\left(x\right)}\mathrm{d}x\right){\Delta }_{p\left(x\right)}^{2}u+V\left(x\right){|u|}^{p\left(x\right)-2}u$ = $K\left(x\right)f\left(u\right),x\in {\mathbb{R}}^N$, where ${\Delta }_{p\left(x\right)}^{2}u=\Delta \left({|\Delta u|}^{p\left(x\right)-2}\Delta u\right)$ is the $p\left(x\right)$ biharmonic operator, $a,b>0$ are constants, $N\ge 2$, $V\left(x\right),K\left(x\right)$ are positive continuous functions which vanish at infinity, and the nonlinearity f has subcritical growth. Using the Nehari manifold method, deformation lemma, and other techniques of analysis, it is demonstrated that there are precisely two nodal domains in the problem’s least energy sign-changing solution $u_b$. In addition, the convergence property of $u_b$ as $b\to 0$ is also established. Full article

Unmanned Aerial Vehicles (UAVs) face a significant challenge in balancing high accuracy and high efficiency when performing real-time object detection tasks, especially amidst intricate backgrounds, diverse target scales, and stringent onboard computational resource constraints. To tackle these difficulties, this study introduces YOLO-SRMX, a lightweight real-time object detection framework specifically designed for infrared imagery captured by UAVs. Firstly, the model utilizes ShuffleNetV2 as an efficient lightweight backbone and integrates the novel Multi-Scale Dilated Attention (MSDA) module. This strategy not only facilitates a substantial 46.4% reduction in parameter volume but also, through the flexible adaptation of receptive fields, boosts the model’s robustness and precision in multi-scale object recognition tasks. Secondly, within the neck network, multi-scale feature extraction is facilitated through the design of novel composite convolutions, ConvX and MConv, based on a “split–differentiate–concatenate” paradigm. Furthermore, the lightweight GhostConv is incorporated to reduce model complexity. By synthesizing these principles, a novel composite receptive field lightweight convolution, DRFAConvP, is proposed to further optimize multi-scale feature fusion efficiency and promote model lightweighting. Finally, the Wise-IoU loss function is adopted to replace the traditional bounding box loss. This is coupled with a dynamic non-monotonic focusing mechanism formulated using the concept of outlier degrees. This mechanism intelligently assigns elevated gradient weights to anchor boxes of moderate quality by assessing their relative outlier degree, while concurrently diminishing the gradient contributions from both high-quality and low-quality anchor boxes. Consequently, this approach enhances the model’s localization accuracy for small targets in complex scenes. Experimental evaluations on the HIT-UAV dataset corroborate that YOLO-SRMX achieves an ${\mathrm{mAP}}_{50}$ of 82.8%, representing a 7.81% improvement over the baseline YOLOv8s model; an F1 score of 80%, marking a 3.9% increase; and a substantial 65.3% reduction in computational cost (GFLOPs). YOLO-SRMX demonstrates an exceptional trade-off between detection accuracy and operational efficiency, thereby underscoring its considerable potential for efficient and precise object detection on resource-constrained UAV platforms. Full article

For the first time, the deposition area of heavy metals and other trace elements (Al, Ba, Cd, Co, Cr, Cu, Fe, Mn, Ni, P, Pb, S, Sr, Sb, V, Zn, and Hg) on the territory surrounding a landfill of domestic (municipal) waste at the 9th km of the Vilyuisky tract of Yakutsk within a radius of 51 km was assessed using the method of moss biomonitors and ICP-OES as an analytical technique. Mosses were analyzed for radionuclide content (⁴⁰K, ¹³⁷Cs, ²¹² Pb, ²¹⁴Pb, ²¹²Bi, ²¹⁴Bi, ²⁰⁸Tl, ⁷Be, and ²²⁸Ac) in a number of selected samples by semiconductor gamma spectrometry. The results of the examination of moss samples by ICP-OES indicate the presence of large amounts of toxic Ba and metal debris (Al, Co, Cr, Fe, S, and Pb) at the landfill. In addition, it is shown that the investigated samples contain elements such as Cd, Co, Cr, Cu, Cu, Mn, Ni, Pb, Sr, V, Zn, and Hg. The method of gamma spectrometry revealed that the studied samples contain such radioactive elements as ¹³⁷Cs, daughter products of ²³⁸U and ²³²Th. Detection of the same heavy metals and radionuclides in the atmospheric air of the city and in the vegetation near the landfill may indicate that one of the sources of environmental pollution may be products of incineration of the landfill contents at the 9th km of the Vilyuisky tract. Full article

LiDAR point clouds, as direct carriers of 3D spatial information, comprehensively record the geometric features and spatial topological relationships of object surfaces, providing intelligent systems with rich 3D scene representation capability. However, current point cloud semantic segmentation methods primarily extract features through operations such as convolution and pooling, yet fail to adequately consider sparse features that significantly influence the final results of point cloud-based scene perception, resulting in insufficient feature representation capability. To address these problems, a sparse feature dynamic graph convolutional neural network, abbreviated as SFDGNet, is constructed in this paper for LiDAR point clouds of complex scenes. In the context of this paper, sparse features refer to feature representations in which only a small number of activation units or channels exhibit significant responses during the forward pass of the model. First, a sparse feature regularization method was used to motivate the network model to learn the sparsified feature weight matrix. Next, a split edge convolution module, abbreviated as SEConv, was designed to extract the local features of the point cloud from multiple neighborhoods by dividing the input feature channels, and to effectively learn sparse features to avoid feature redundancy. Finally, a multi-neighborhood feature fusion strategy was developed that combines the attention mechanism to fuse the local features of different neighborhoods and obtain global features with fine-grained information. Taking S3DIS and ScanNet v2 datasets, we evaluated the feasibility and effectiveness of SFDGNet by comparing it with six typical semantic segmentation models. Compared with the benchmark model DGCNN, SFDGNet improved overall accuracy $\left(OA\right)$, mean accuracy $\left(mAcc\right)$, mean intersection over union $\left(mIoU\right)$, and $sparsity$ by $1.8\%$, $3.7\%, 3.5\%$, and $85.5\%$ on the S3DIS dataset, respectively. The $mIoU$ on the ScanNet v2 validation set, $mIoU$ on the test set, and $sparsity$ were improved by $3.2\%, 7.0\%$, and $54.5\%$, respectively. Full article

Deep learning-based individual recognition of beef cattle has improved the efficiency and effectiveness of individual recognition, providing technical support for modern large-scale farms. However, issues such as over-reliance on back patterns, similar patterns of adjacent cattle leading to low recognition accuracy, and difficulties in deploying models on edge devices exist in the process of group cattle recognition. In this study, we proposed a model based on improved YOLO v5. Specifically, a Simple, Parameter-Free (SimAM) attention module is connected with the residual network and Multidimensional Collaborative Attention mechanism (MCA) to obtain the MCA-SimAM-Resnet (MRS-ATT) module, enhancing the model’s feature extraction and expression capabilities. Then, the $L_{MPDIoU}$ loss function is used to improve the localization accuracy of bounding boxes during target detection. Finally, structural pruning is applied to the model to achieve a lightweight version of the improved YOLO v5. Using 211 test images, the improved YOLO v5 model achieved an individual recognition precision (P) of 93.2%, recall (R) of 94.6%, mean Average Precision (mAP) of 94.5%, FLOPs of 7.84, 13.22 M parameters, and an average inference speed of 0.0746 s. The improved YOLO v5 model can accurately and quickly identify individuals within groups of cattle, with fewer parameters, making it easy to deploy on edge devices, thereby accelerating the development of intelligent cattle farming. Full article

Hypericum perforatum L. (H.P.), a plant renowned for its wound-healing properties, was investigated for antioxidant/antimicrobial efficacy, toxicological safety, and in vivo wound-healing effects in this research to develop and characterize novel nanoemulsion hydrogel (NG) formulations. NG were prepared via emulsion diffusion–solvent evaporation and polymer hydration using Cremophor RH40 and Ultrez 21/30. A D-optimal design optimized oil/surfactant ratios, considering particle size, PDI, and drug loading. Antioxidant activity was tested via DPPH, ABTS⁺, and FRAP. Toxicological assessment followed HET-CAM (ICH-endorsed) and ICCVAM guidelines. The optimized NG-2 (NE-HPM-10 + U30 0.5%) demonstrated stable and pseudoplastic flow, with a particle size of 174.8 nm, PDI of 0.274, zeta potential of −23.3 mV, and 99.83% drug loading. Release followed the Korsmeyer–Peppas model. H.P. macerates/NEs showed potent antioxidant activity (DPPH IC₅₀: 28.4 µg/mL; FRAP: 1.8 mmol, Fe²⁺/g: 0.3703 ± 0.041 mM TE/g). Antimicrobial effects against methicillin-resistant S. aureus (MIC: 12.5 µg/mL) and E. coli (MIC: 25 µg/mL) were significant. Stability studies showed no degradation. HET-CAM tests confirmed biocompatibility. Histopathology revealed accelerated re-epithelialization/collagen synthesis, with upregulated TGF-β1. The NG-2 formulation demonstrated robust antioxidant, antimicrobial, and wound-healing efficacy. Enhanced antibacterial activity and biocompatibility highlight its therapeutic potential. Clinical/pathological evaluations validated tissue regeneration without adverse effects, positioning H.P.-based nanoemulsions as promising for advanced wound care. Full article

Background: Understanding immune response is essential for preparing for public health crises. COVID-19 vaccination provides robust immunity against SARS-CoV-2, but immunocompromised populations may have weaker immune responses. We assessed SARS-CoV-2 spike (trimer) total IgG/IgM/IgA (total Ig) to investigate immune response to COVID-19 vaccination in people living with HIV (PLWH), considering CD4⁺ T cell count, viral load, substance use, and comorbidities. Methods: This cross-sectional study was conducted in Miami, Florida, between May 2021 and December 2021 as part of the NIH Rapid Acceleration of Diagnostics-Underserved Populations (RADx-UP) initiative (3U01DA040381-05S1) and the Miami Adult Studies on HIV (MASH) cohort (U01DA040381). Blood samples were collected and SARS-CoV-2 spike (trimer) total Ig was quantified. HIV serostatus, viral load, CD4⁺ T cell count, and COVID-19 vaccinations were abstracted from medical records. Substance use (tobacco, alcohol, and drug use [marijuana, cocaine, heroin, fentanyl, methamphetamine, amphetamine, hallucinogens, ecstasy, or misuse of prescription drugs]), and comorbidities (hypertension, diabetes, autoimmune disease, obesity, chronic kidney disease, and substance use disorders) were assessed via validated questionnaires. Drug use was confirmed via urine toxicology. Multivariable linear regression was conducted. Results: Median age (n = 1317) was 57.8 years, 49.8% were male, 50% were Black non-Hispanic, 66.2% had received ≥1 dose of a COVID-19 vaccine, and 29.6% were PLWH (71.3% virally suppressed and median CD4⁺ T cell count > 500 cells/µL). PLWH, compared to people without HIV, were more likely to have received ≥1 dose of a COVID-19 vaccine (76.2% vs. 62.0%, p < 0.001) and present with substance use (77.2% vs. 42.9%, p < 0.001) and comorbidities (72.8% vs. 48.2%, p < 0.001). Vaccinated PLWH, compared to unvaccinated PLWH, had higher CD4⁺ T cell counts (577.5 vs. 517.5, p = 0.011) and were more likely to be virally suppressed (76.4% vs. 54.8%, p < 0.001). A lower CD4⁺ T cell count (<200 vs. ≥500, β = −0.400, p = 0.033) and higher HIV viral load (≥200–<5000 vs. <200, β = −0.275, p < 0.001) were associated with lower spike (trimer) total Ig titers, indicating a diminished response to COVID-19 vaccination. Conclusions: A lower CD4⁺ T cell count and higher HIV viremia were linked to reduced SARS-CoV-2 immunogenicity in racial/ethnic minority PLWH, a population underrepresented in vaccine clinical trials. HIV care providers should target efforts to maintain viral suppression to avoid diminished responses to COVID-19 vaccination. Full article

In the study presented herein, an aerobic, Gram-stain-positive, spore-forming bacterium, designated as WLY-B-L8^T, was isolated from a qu-starter (baobaoqu) cultivation facility used for the production of Wuliangye baijiu in Yibin city (Sichuan province, China). The strain comprised short, rod-shape cells of 1.2–1.9 μm in width and 1.7–4.8 μm in length, arranged singly or in pairs. The isolate was able to grow at temperatures of 20–42 °C (optimum growth at 40 °C), pH 5.0–10.0 (optimum growth at pH 8.0), and in the presence of 0–2% (w/v) NaCl (optimum growth with 1% NaCl). Ribose, xylose, arabinose, mannose, glucose, and galactose constituted the major cell-wall sugars. Moreover, meso-diaminopimelic acid (meso-DAP) constituted the diagnostic amino acid. The main polar lipids of WLY-B-L8^T included diphosphatidylglycerol (DPG), phosphatidylglycerol (PG), phosphatidylethanolamine (PE), unidentified aminolipids (UAL 1–2), an unidentified aminophospholipid (UAPL), an unidentified aminoglycolipid (UAGL), and an unidentified lipid (UL). MK-7 was the predominant menaquinone and iso-C_15:0 (23.00%) was the major fatty acid. Comparisons of the 16S rRNA gene sequence indicated that WLY-B-L8^T was most closely related to Bacillus rhizoplanae JJ-63 DSM 12442^T (98.71%), Bacillus pseudomycoides DSM 12442^T (98.21%), and Bacillus cytotoxicus NVH 391–98^T (98.14%). The average nucleotide identity (ANI) values of strain WLY-B-L8^T and the three type strains mentioned above were 88.24%, 80.57%, and 78.70%. The average amino identity (AAI) values between them were 89.84%, 79.51%, and 80.41%. In addition, the digital DNA–DNA hybridization (dDDH) values between them were 36.70%, 26.10%, and 23.90%. The genomic DNA G+C content was 35.97%. Based on the evidence presented herein, WLY-B-L8^T (CICC 25210^T = JCM 36284^T) exhibits promise as the type strain of a novel species, designated as Bacillus multifaciens sp. nov., that can produce protease (119.38 ± 7.44 U/mL) and volatile flavor components when cultured on raw wheat, such as 2-pipendinone (21.95 ± 1.56 mg/L), phenylethyl alcohol (19.08 ± 0.82 mg/L), hydrocinnamic acid (18.60 ± 0.53 mg/L), and acetoin (7.58 ± 0.11 mg/L). Full article

Chelidonium majus L. is a species with a wide medicinal use, commonly found in anthropogenically degraded habitats, forest edges, and urban parks. This study aimed to determine the chemical composition of the leaves, stems, and roots of Ch. majus and the soil in its rhizosphere in terms of the content of the main elements (Fe, Ca, P, Mg, Al, Na, K, S), trace elements and rare earth minerals (Ti, Mo, Ag, U, Au, Th, Sb, Bi, V, La, B, W, Sc, Tl, Se, Te, Ga, Cs, Ge, Hf, Nb, Rb, Sn, Ta, Zr, Y, Ce, In, Be, and Li), and their comparison in the parts analyzed. The study was conducted in five urban parks in southern Poland in a historically industrialized area. The results showed that Ca has the highest content among the macroelements. Its leaf content ranges from 24,700 to 40,700 mg·kg⁻¹, while in soil, it ranges from 6500 to 15,000 mg·kg⁻¹. In leaves, low values of Al (100–500 mg·kg⁻¹) and Na (100 mg·kg⁻¹) were found in comparison to the other elements tested, while high values of Al (5100–9800 mg·kg⁻¹) were found in soils. Among the macroelements in the Ch. majus stems, K showed the highest concentration (>100,000 mg·kg⁻¹), while the Ca content was 3–4 times lower in the stems than in the leaves. Rhizomes of Ch. majus accumulate the most K and Ca, in the range of 22,800–29,900 mg·kg⁻¹ and 5400–8900 mg·kg⁻¹, respectively. Fe and Al in all locations have higher values in the soil than in the tissues. In turn, the content of Ca, P, Mg, K, and S is higher in plants than in the soil. Determining the elemental content of medicinal plants is important information, as the plant draws these elements from the soil, and, at higher levels of toxicity, it may indicate that the plant should not be taken from this habitat for medicinal purposes. Full article