Understanding the Relationship Between Vascular Smooth Muscle Cell Function and the Efficacy of Acupuncture in Treating Cerebral Ischemic Stroke: A Preclinical Meta-Analysis and Systematic Review.

Background: Cerebral blood flow and vascular structures serve as the fundamental components of brain metabolism and circulation. Acupuncture, an alternative and complementary medical approach, has demonstrated efficacy in treating cerebral ischemic stroke (CIS). Nevertheless, the mechanisms underlying the impact of acupuncture on vascular smooth muscle cell (VSMC) function remain uncertain. The objective of this systematic review and meta-analysis is to assess the alterations in VSMC function following acupuncture stimulation in CIS models. Methods: The databases PubMed, Web of Science, SCOPUS, and EMBASE were queried until November 2022 using a predetermined search strategy. The FORMAT BY SYRCLE guidelines were adhered to, and the risk of bias of the included studies was evaluated using the Risk of Bias tool developed by the Systematic Review Centre for Laboratory Animal Experimentation. The random-effects model was employed to estimate the standardized mean difference (SMD). Results: Eighteen articles are included in this review. Acupuncture showed significant positive effects on the region cerebral blood flow (SMD=8.15 [95% CI, 4.52 to 11.78]) and neurological deficiency (SMD=-3.75 [95% CI, -5.54 to -1.97]). Descriptive analysis showed a probable mechanism of acupuncture stimulation in CIS rats related to VSMC function. Limitations and publication bias were presented in the studies. Conclusion: In this systematic review and meta-analysis, our findings indicate that acupuncture stimulation has the potential to improve regional cerebral blood flow and alleviate neurological deficits, possibly by regulating VSMC function. However, it is important to exercise caution when interpreting these results due to the limitations of animal experimental design and methodological quality.

AppleQSM: Geometry-Based 3D Characterization of Apple Tree Architecture in Orchards.

The architecture of apple trees plays a pivotal role in shaping their growth and fruit-bearing potential, forming the foundation for precision apple management. Traditionally, 2D imaging technologies were employed to delineate the architectural traits of apple trees, but their accuracy was hampered by occlusion and perspective ambiguities. This study aimed to surmount these constraints by devising a 3D geometry-based processing pipeline for apple tree structure segmentation and architectural trait characterization, utilizing point clouds collected by a terrestrial laser scanner (TLS). The pipeline consisted of four modules: (a) data preprocessing module, (b) tree instance segmentation module, (c) tree structure segmentation module, and (d) architectural trait extraction module. The developed pipeline was used to analyze 84 trees of two representative apple cultivars, characterizing architectural traits such as tree height, trunk diameter, branch count, branch diameter, and branch angle. Experimental results indicated that the established pipeline attained an R2 of 0.92 and 0.83, and a mean absolute error (MAE) of 6.1 cm and 4.71 mm for tree height and trunk diameter at the tree level, respectively. Additionally, at the branch level, it achieved an R2 of 0.77 and 0.69, and a MAE of 6.86 mm and 7.48° for branch diameter and angle, respectively. The accurate measurement of these architectural traits can enable precision management in high-density apple orchards and bolster phenotyping endeavors in breeding programs. Moreover, bottlenecks of 3D tree characterization in general were comprehensively analyzed to reveal future development.

The relationship between serum resolvin D1, NLRP3, cytokine levels, and adolescents with first-episode medication-naïve major depressive disorder.

BACKGROUND: Inflammation has become a critical pathological mechanism of Major Depressive Disorder (MDD). NLRP3 is a critical inflammatory pathway to maintain the immune balance. Recently, preclinical evidence showed that Resolvin D1 might potentially offer a new option for antidepressant treatment due to its protective effects through the inhibition of neuroinflammation. However, whether they have clinical value in the diagnosis and treatment evaluation of adolescent depression was unclear. METHODS: Forty-eight untreated first-episode adolescent patients with moderate to severe major depressive disorder, as well as 30 healthy adolescents (HCs, age and gender-matched), were enrolled for this study. Their ages ranged from 13 to 18 (15.75 ± 1.36) years. The patients were treated with fluoxetine for 6-8 weeks. HDRS-17 was used to evaluate the severity of depressive symptoms. Venous blood samples were collected at baseline for the two groups and at the time-point of post-antidepressant treatment for the patients. Serum concentrations of RvD1, NLRP3, IL-1ß, IL-18, and IL-4 were measured by enzyme-linked immunosorbent assays (ELISA) pre- and post-fluoxetine treatment. RESULTS: Serum levels of RvD1 and anti-inflammatory cytokine IL-4 were significantly elevated in adolescents with MDD compared to healthy adolescents, but no significant difference in NLRP3, IL-1ß, and IL-18 between the two groups. Meanwhile, RvD1 (positively) and IL-4 (negatively) were correlated with the severity of symptoms (HDRS-17 scores) after adjusting age, gender, and BMI. Interestingly, fluoxetine treatment significantly reduced the serum levels of RvD1, NLRP3, IL-1ß, and IL-18 in MDD adolescents but increased the levels of IL-4 relative to baseline. Furthermore, we observed that serum levels of RvD1 might be an excellent distinguishing indicator for depression and healthy adolescents. CONCLUSIONS: Our study is the first to compare RvD1 and NLRP3 between adolescent MDD and HCs. Our findings of reactive increase of RvD1 in adolescent MDD comprised a novel and critical contribution. Our results showed the presence of inflammation resolution unbalanced in adolescents with MDD and indicated that RvD1 might be an ideal biomarker for diagnosing and treating adolescent MDD.

Pneumonic-type lung adenocarcinoma with KRAS G12V mutation and sustained response to Afatinib.

BACKGROUND: Pneumonic-type lung adenocarcinoma (P-ADC) is a rare and challenging subtype of primary lung cancer that can be difficult to distinguish from pneumonia based on radiological images. Furthermore, no drugs are currently available that specifically target KRAS G12V. CASE PRESENTATION: Here we report a case of P-ADC with typical and informative imaging features throughout the course of the disease, including patchy shadows, high-density lesions with aerated bronchus, diffuse ground-glass opacities, and nodular shadows from computed tomography (CT) scan. The KRAS G12V mutation was detected using Next-generation sequencing (NGS). An individualized Afatinib-based therapeutic schedule was prescribed and achieved sustained response after multiple lines of treatment had failed. CONCLUSION: Our case highlights the typical and dynamic changes in imaging features of P-ADC and provides an indicative treatment strategy for KRAS G12V-mutated lung adenocarcinoma.

Bioorthogonal masked acylating agents for proximity-dependent RNA labelling.

RNA localization is highly regulated, with subcellular organization driving context-dependent cell physiology. Although proximity-based labelling technologies that use highly reactive radicals or carbenes provide a powerful method for unbiased mapping of protein organization within a cell, methods for unbiased RNA mapping are scarce and comparably less robust. Here we develop α-alkoxy thioenol and chloroenol esters that function as potent acylating agents upon controlled ester unmasking. We pair these probes with subcellular-localized expression of a bioorthogonal esterase to establish a platform for spatial analysis of RNA: bioorthogonal acylating agents for proximity labelling and sequencing (BAP-seq). We demonstrate that, by selectively unmasking the enol probe in a locale of interest, we can map RNA distribution in membrane-bound and membrane-less organelles. The controlled-release acylating agent chemistry and corresponding BAP-seq method expand the scope of proximity labelling technologies and provide a powerful approach to interrogate the cellular organization of RNAs.

[Air Microbial Contamination and Risk of Respiratory Exposure of Workers in Chicken Farms].

Animal farms are important sources of microbial contamination in the air environment. However, there are few reports on the time-regularity characteristics of airborne microbial contamination in farms. In the context of this situation, a study was conducted for more than 80 weeks using 16S rRNA gene amplicon sequencing to characterize the bacterial distribution and respiratory exposure in the farm air and fecal environment, respectively, taking a layer farm as an example. The results showed that 16S rRNA concentrations in air and manure samples ranged from 6.08×105-4.90×106 copies·m-3 and 4.27×108-1.15×1010 copies·g-1, respectively. The mean values of airborne bacterial concentrations were significantly higher in winter than in summer, whereas the biodiversity showed the opposite trend. The dominant bacterial phylum in both air and manure in the layer farm was Firmicutes. During the investigated time, the top three dominant genera in the air were relatively stable, in the order of Lactobacillus, Bacteroides, and Faecalibacterium, whereas the dominant genera in feces fluctuated with the increase in breeding time. The correlation between the community structure of bacteria and pathogenic bacteria in both air and manure was not significant, but the concentrations of both target microorganisms in different media were significantly correlated. The bioaerosolization index of bacteria in manure showed an increasing trend with increasing breeding time, whereas the opposite trend was observed for pathogenic bacteria. In this case, [Ruminococcus]_torques_group, Bacteroides, and Faecalibacterium were the top three pathogenic genera that were the most prone to aerosolization. There were seasonal differences in bacterial respiratory exposures of chicken farm workers, with mean intake values of 2.54×107 copies·d-1 and 2.87×105 copies·d-1 for bacteria and pathogenic bacteria, respectively. The results of this study will provide a scientific basis for systematically assessing the contamination characteristics and potential health risks of airborne microorganisms on farms and for developing corresponding industry standards for occupational exposure and prevention and control measures.

A simple one-electron expression for electron rotational factors.

Within the context of fewest-switch surface hopping (FSSH) dynamics, one often wishes to remove the angular component of the derivative coupling between states J and K. In a previous set of papers, Shu et al. [J. Phys. Chem. Lett. 11, 1135-1140 (2020)] posited one approach for such a removal based on direct projection, while we isolated a second approach by constructing and differentiating a rotationally invariant basis. Unfortunately, neither approach was able to demonstrate a one-electron operatorÔ whose matrix element JÔK was the angular component of the derivative coupling. Here, we show that a one-electron operator can, in fact, be constructed efficiently in a semi-local fashion. The present results yield physical insight into designing new surface hopping algorithms and are of immediate use for FSSH calculations.

Practical phase-space electronic Hamiltonians for ab initio dynamics.

Modern electronic structure theory is built around the Born-Oppenheimer approximation and the construction of an electronic Hamiltonian Hel(X) that depends on the nuclear position X (and not the nuclear momentum P). In this article, using the well-known theory of electron translation (Γ') and rotational (Γ″) factors to couple electronic transitions to nuclear motion, we construct a practical phase-space electronic Hamiltonian that depends on both nuclear position and momentum, HPS(X,P). While classical Born-Oppenheimer dynamics that run along the eigensurfaces of the operator Hel(X) can recover many nuclear properties correctly, we present some evidence that motion along the eigensurfaces of HPS(X,P) can better capture both nuclear and electronic properties (including the elusive electronic momentum studied by Nafie). Moreover, only the latter (as opposed to the former) conserves the total linear and angular momentum in general.

Research on reliability index and failure probability of inherent defect insurance from the insurance perspective.

With the continuous improvement of people 's living standards, people have put forward higher requirements for the safety and comfort of housing. Therefore, Inherent Defect Insurance, a financial method to guarantee the quality of construction projects, has also emerged. At present, China 's Inherent Defect Insurance has been gradually promoted, but its claim mechanism has not been analyzed and studied. From the perspective of construction engineering, this paper first makes a bibliometric analysis of the influencing factors of insurance claims that may be caused by construction engineering quality through VOSViewers, and the evaluation index system of inherent defects is constructed. Then, according to the influencing factors, the PSO-LSSVR model is adopted to fit the performance function of the inherent defects. Finally, based on the reliability design principle of engineering structure, the reliability index and failure probability of Inherent Defect Insurance are derived from the performance function of inherent defects. This paper also analyzes its application in insurance practice and determines the relationship between the number of insurance underwriting policies and the initial reserve of insurance at a certain risk level. This paper studies the probability of Inherent Defect Insurance by constructing the reliability model of inherent defect risks in construction quality, and analyzes the anti-risk ability of insurance companies from the perspective of claim, which provides scientific analysis methods and theoretical basis for the scientific decision-making of insurance companies.

An Unusual Presentation of Cobblestone Esophagus From Bisphosphonate Use.

Cobblestone esophagus is a rare finding that has been previously described in cases of eosinophilic esophagitis (EoE), candidiasis, Barrett's esophagus, or severe reflux esophagitis from distal gastrointestinal obstruction. We describe a case of asymptomatic cobblestone esophagus secondary to bisphosphonate use.  A 67-year-old female was seen in the clinic for evaluation of microcytic anemia that was incidentally picked up on routine chronic disease follow-up. She had no gastrointestinal symptoms. She has been taking oral alendronate 70mg once a week for osteoporosis since a year ago. Barium meal was performed as the patient initially opted for non-invasive testing, which incidentally showed a diffuse "cobblestone" appearance. Subsequent oesophago-gastro-duodenoscopy (OGD) showed diffuse white nodular lesions along the esophagus with a cobblestone appearance but no ulcer or mass. Segmental esophageal biopsies were negative for fungal stain and did not show any pathology. In the absence of infection, eosinophilic esophagitis, and dysplasia, her "cobblestone" esophagus was attributed to bisphosphonate use by diagnosis of exclusion. Alendronate acid was held off, and serial barium meals over the next year showed significant interval improvement.  Bisphosphonates, such as alendronate acid, are commonly associated with drug-induced esophagitis. With the cessation of the offending medication, there was indeed a significant improvement in our patient's serial barium meal. It is important to review the medication list when encountering patients who present with cobblestone esophagus, as some of these patients with drug-induced esophagitis may be asymptomatic clinically.

Microplastic-induced NAFLD: Hepatoprotective effects of nanosized selenium.

Polystyrene microplastics (MPs) are persistent environmental pollutants commonly encountered in daily human life. Numerous studies have demonstrated their ability to induce liver damage, including oxidative stress, inflammation, and lipid accumulation. However, limited information exists regarding preventive measures against this issue. In our study, we investigated the potential preventive role of selenium nanoparticles (YC-3-SeNPs) derived from Yak-derived Bacillus cereus, a novel nanobiomaterial known for its antioxidant properties and lipid metabolism regulation. Using transcriptomic and metabolomic analyses, we identified key genes and metabolites associated with oxidative stress and lipid metabolism imbalance induced by MPs. Upregulated genes (Scd1, Fasn, Irs2, and Lpin) and elevated levels of arachidonic and palmitic acid accumulation were observed in MP-exposed mice, but not in those exposed to SeNPs. Further experiments confirmed that SeNPs significantly attenuated liver lipid accumulation and degeneration caused by MPs. Histological results and pathway screening validated our findings, revealing that MPs suppressed the Pparα pathway and Nrf2 pathway, whereas SeNPs activated both pathways. These findings suggest that MPs may contribute to the development of nonalcoholic fatty liver disease (NAFLD), while SeNPs hold promise as a future nanobio-product for its prevention.

Wormwood-infused porous-CaCO3 for synthesizing antibacterial natural rubber latex.

Wormwood leaf is a traditional Chinese herbal medicine with a high medicinal value and long application history and its essential oil is a high-purity plant oil extracted from Wormwood leaf. Pharmacological research reveals that Wormwood leaf and Wormwood essential oil are a broad-spectrum antibacterial and antiviral drug, which can inhibit and kill many bacteria and viruses. We loaded wormwood extract on porous calcium carbonate (Porous-CaCO3) and introduced it and Wormwood essential oil into Natural rubber latex (NRL), thus synthesizing NRL composites with excellent vitro and in vivo antibacterial effect, cell compatibility and mechanical properties. This NRL material can delay the light aging and thermal oxidation of some mechanical properties, which provides a broader avenue for its commercialization.

Functional Characterization of CYP6QE1 and CYP6FV21 in Resistance to λ-Cyhalothrin and Imidacloprid in Bradysia odoriphaga.

Cytochrome P450 monooxygenases (P450s) belong to a family of metabolic enzymes that are involved in the detoxification of insecticides. In this study, our bioassay results showed that a field-collected population of Bradysia odoriphaga displayed a moderate resistance to λ-cyhalothrin and imidacloprid. Compared to susceptible population, CYP6QE1 and CYP6FV21 were significantly overexpressed in the field population. The expression of CYP6QE1 and CYP6FV21 was more abundant in the third and fourth larval stages, and CYP6QE1 and CYP6FV21 were most highly expressed in the midgut and Malpighian tubules. Exposure to λ-cyhalothrin and imidacloprid significantly increased the expression levels of CYP6QE1 and CYP6FV21. Furthermore, the silencing of CYP6QE1 and CYP6FV21 significantly increased the susceptibility of B. odoriphaga larvae to λ-cyhalothrin and imidacloprid. The overexpression of CYP6QE1 and CYP6FV21 significantly enhanced the tolerance of transgenic Drosophila melanogaster lines to λ-cyhalothrin and imidacloprid. In addition, molecular docking revealed that these two P450 proteins have strong binding affinity toward λ-cyhalothrin and imidacloprid insecticides. Taken together, these results indicate that the overexpression of CYP6QE1 and CYP6FV21 is responsible for resistance to λ-cyhalothrin and imidacloprid in B. odoriphaga.

Predicting Risk of Bullying Victimization among Primary and Secondary School Students: Based on a Machine Learning Model.

School bullying among primary and secondary school students has received increasing attention, and identifying relevant factors is a crucial way to reduce the risk of bullying victimization. Machine learning methods can help researchers predict and identify individual risk behaviors. Through a machine learning approach (i.e., the gradient boosting decision tree model, GBDT), the present longitudinal study aims to systematically examine individual, family, and school environment factors that can predict the risk of bullying victimization among primary and secondary school students a year later. A total of 2767 participants (2065 secondary school students, 702 primary school students, 55.20% female students, mean age at T1 was 12.22) completed measures of 24 predictors at the first wave, including individual factors (e.g., self-control, gender, grade), family factors (family cohesion, parental control, parenting style), peer factor (peer relationship), and school factors (teacher-student relationship, learning capacity). A year later (i.e., T2), they completed the Olweus Bullying Questionnaire. The GBDT model predicted whether primary and secondary school students would be exposed to school bullying after one year by training a series of base learners and outputting the importance ranking of predictors. The GBDT model performed well. The GBDT model yielded the top 6 predictors: teacher-student relationship, peer relationship, family cohesion, negative affect, anxiety, and denying parenting style. The protective factors (i.e., teacher-student relationship, peer relationship, and family cohesion) and risk factors (i.e., negative affect, anxiety, and denying parenting style) associated with the risk of bullying victimization a year later among primary and secondary school students are identified by using a machine learning approach. The GBDT model can be used as a tool to predict the future risk of bullying victimization for children and adolescents and to help improve the effectiveness of school bullying interventions.

MET alterations detection platforms and clinical implications in solid tumors: a comprehensive review of literature.

MET alterations, including MET exon 14 skipping variants, MET amplification, MET overexpression, and MET fusion, play pivotal roles in primary tumorigenesis and acquired resistance to targeted therapies, especially EGFR tyrosine kinase inhibitors. They represent important diagnostic, prognostic, and predictive biomarkers in many solid tumor types. However, the detection of MET alterations is challenging due to the complexity of MET alterations and the diversity of platform technologies. Therefore, techniques with high sensitivity, specificity, and reliable molecular detection accuracy are needed to overcome such hindrances and aid in biomarker-guided therapies. The current review emphasizes the role of MET alterations as oncogenic drivers in a variety of cancers and their involvement in the development of resistance to targeted therapies. Moreover, our review provides an overview of and recommendations on the selection of various cross-platform technologies for the detection of MET exon 14 skipping variants, MET amplification, MET overexpression, and MET fusion. Furthermore, challenges and hurdles underlying these common detection platforms are discussed.

Detection, Quantification, and Isomer Differentiation of Per- and Polyfluoroalkyl Substances (PFAS) Using MALDI-TOF with Trapped Ion Mobility.

Per- and polyfluoroalkyl substances (PFAS) are a class of organic compounds that have attracted global attention for their persistence in the environment, exposure to biological organisms, and their adverse health effects. There is an urgent need to develop analytical methodologies for the characterization of PFAS in various sample matrices. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) represents a chromatography-free MS method that performs laser-based ionization and in situ analysis on samples. In this study, we present PFAS analysis by MALDI-time-of-flight (TOF) MS with trapped ion mobility spectrometry (TIMS), which provides an additional dimension of gas phase separation based on the size-to-charge ratios. MALDI matrix composition and key instrument parameters were optimized to produce different ranges of calibration curves. Parts per billion (ppb) range of calibration curves were achieved for a list of legacy and alternative perfluorosulfonic acids (PFSAs) and perfluorocarboxylic acids (PFCAs), while ion mobility spectrum filtering enabled parts per trillion (ppt) range of calibration curves for PFSAs. We also successfully demonstrated the separation of three perfluorooctanesulfonic acid (PFOS) structural isomers in the gas phase using TIMS. Our results demonstrated the new development of utilizing MALDI-TOF-MS coupled with TIMS for fast, quantitative, and sensitive analysis of PFAS, paving ways to future high-throughput and in situ analysis of PFAS such as MS imaging applications.

Non-Destructive Monitoring of Foliar Fungicide Efficacy with Hyperspectral Sensing in Grapevine.

Frequent fungicide applications are required to manage grapevine powdery mildew (Erysiphe necator). However, this practice is costly and has led to widespread fungicide resistance. A method of monitoring in-field fungicide efficacy could help growers maximize spray-interval length, thereby reducing costs and the rate of fungicide resistance emergence. The goal of this study was to evaluate if hyperspectral sensing in the visible to shortwave infrared range (400 to 2,400 nm) can quantify foliar fungicide efficacy on grape leaves. Commercial formulations of metrafenone, Bacillus mycoides isolate J (BmJ), and sulfur were applied on Chardonnay grapevines in vineyard or greenhouse settings. Foliar reflectance was measured with handheld hyperspectral spectroradiometers at multiple days post-application. Fungicide efficacy was estimated as a proxy for fungicide residue and disease control measured with the Blackbird microscopy imaging robot. Treatments could be differentiated from the untreated control with an accuracy of 73.06% for metrafenone, 67.76% for BmJ, and 94.10% for sulfur. The change in spectral reflectance was moderately correlated with the cube root of the area under the disease progress curve for metrafenone- and sulfur-treated samples (R2 = 0.38 and 0.36, respectively) and with sulfur residue (R2 = 0.42). BmJ treatment impacted foliar physiology by enhancing the leaf mass/area and reducing the nitrogen and total phenolic content as estimated from spectral reflectance. The results suggest that hyperspectral sensing can be used to monitor in-situ fungicide efficacy, and the prediction accuracy depends on the fungicide and the time point measured. The ability to monitor in-situ fungicide efficacy could facilitate more strategic fungicide applications and promote sustainable grapevine protection. [Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Outcome of monochorionic diamniotic twin pregnancy with selective intrauterine growth restriction, a single center study in China.

INTRODUCTION: This retrospective study aimed to evaluate clinical outcomes of monochorionic diamniotic (MCDA) twins with selective intrauterine growth restriction (sIUGR). MATERIALS AND METHODS: MCDA twins, either sIUGR and non-sIUGR, underwent expectant management from 2016 to 2019 in our hospital were included. sIUGR fetuses were classified into three types according to umbilical artery Doppler assessment. Non-sIUGR were considered as the control group. Outcomes were pregnancy outcomes and maternal complications. RESULTS: Forty-three sIUGR (type I: 23; type II: 14, and type III: 6) and 282 non-sIUGR fetuses were included. The sIUGR group had a significantly earlier birth, lower birth weight of the twins, larger inter-twin weight difference, lower Apgar score of the twins, and higher intrauterine fetal death (IUFD) than the non-sIUGR group (all p < 0.001). The same trend was found in the sIUGR type II group compared to type I and III groups. A significantly lower gestational diabetes rate (p = 0.01) and placenta weight (p < 0.001), and higher proportions of abnormal placental umbilical cord insertion (p < 0.001), and ultrasound Doppler monitoring indicators (p = 0.006) were found in the sIUGR group than the non-sIUGR group. CONCLUSIONS: The MCDA twins with sIUGR showed poorer outcomes than the non-sIUGR group. Doppler interrogation was a useful clinical marker for fetal outcome.

Dynamically adjustable SVEIR(MH) model of multiwave epidemics: Estimating the effects of public health measures against COVID-19.

The COVID-19 pandemic was characterized by multiple subsequent, overlapping outbreaks, as well as extremely rapid changes in viral genomes. The information about local epidemics spread and the epidemic control measures was shared on a daily basis (number of cases and deaths) via centralized repositories. The vaccines were developed within the first year of the pandemic. New modes of monitoring and sharing of epidemic data were implemented using Internet resources. We modified the basic SEIR compartmental model to include public health measures, multiwave scenarios, and the variation of viral infectivity and transmissibility reflected by the basic reproduction number R0 of emerging viral variants. SVEIR(MH) model considers the capacity of the medical system, lockdowns, vaccination, and changes in viral reproduction rate on the epidemic spread. The developed model uses daily infection reports for assessing the epidemic dynamics, and daily changes of mobility data from mobile phone networks to assess the lockdown effectiveness. This model was deployed to six European regions Baden-Württemberg (Germany), Belgium, Czechia, Lombardy (Italy), Sweden, and Switzerland for the first 2 years of the pandemic. The correlation coefficients between observed and reported infection data showed good concordance for both years of the pandemic (ρ = 0.84-0.94 for the raw data and ρ = 0.91-0.98 for smoothed 7-day averages). The results show stability across the regions and the different epidemic waves. Optimal control of epidemic waves can be achieved by dynamically adjusting epidemic control measures in real-time. SVEIR(MH) model can simulate different scenarios and inform adjustments to the public health policies to achieve the target outcomes. Because this model is highly representative of actual epidemic situations, it can be used to assess both the public health and socioeconomic effects of the public health measures within the first 7 days of the outbreak.