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Ischemic postconditioning initially referred to a stuttering reperfusion performed immediately after reperfusion, for preventing ischemia/reperfusion injury in both myocardial and cerebral infarction. It has evolved into a concept that can be induced by a broad range of stimuli or triggers, and may even be performed as late as 6 h after focal ischemia and 2 days after transient global ischemia. The concept is thought to be derived from ischemic preconditioning or partial/gradual reperfusion, but in fact the first experiment for postconditioning was carried out much earlier than that of preconditioning or partial/gradual reperfusion, in the research on myocardial ischemia. This review first examines the protective effects and parameters of postconditioning in various cerebral ischemic models. Thereafter, it provides insights into the protective mechanisms of postconditioning associated with reperfusion injury and the Akt, mitogen-activated protein kinase (MAPK), protein kinase C (PKC), and ATP-sensitive K+ (KATP) channel cell signaling pathways. Finally, some open issues and future challenges regarding clinical translation of postconditioning are discussed.

ObjectiveThe purpose of this systematic review and meta-analysis was to evaluate the effectiveness of mindfulness-based stress reduction (MBSR) in breast cancer patients.MethodsA systematic search of Cochrane Library, Cochrane Central Register of Controlled Trials, PsycINFO database, Web of science, Medline, EMBASE, CNKI, and CBM database was carried out from February to May 2018, with no language restrictions. Trials examining the effects of MBSR versus control group on symptom variables and health-related quality of life were included. Data concerning studies, patient characteristics, and outcomes were extracted. Methodological quality of each included randomized controlled trials were assessed individually by two reviewers independently using criteria recommended in the Cochrane Handbook for Systematic Reviews of Interventions 5.1.0. Meanwhile, Newcastle-Ottawa Quality Assessment Scale (NOS) was used to evaluate methodological quality of non-randomized studies.ResultsIn all, 14 studies involving 1505 participants were included. Due to the effect of MBSR, statistically significant results were found on physiological function (SMD = 0.28, 95% CI [0.07, 0.049], P = 0.008), cognitive function (SMD = 1.48, 95% CI [0.34, 2.61], P = 0.01), fatigue (SMD = − 0.66, 95% CI [− 1.11, − 0.20], P = 0.004), emotional wellbeing (SMD = 1.01, 95% CI [0.35, 1.67], P = 0.003), anxiety (SMD = − 0.54, 95% CI [− 1.01, − 0.07], P = 0.02), depression (SMD = − 0.61, 95% CI [− 1.11, − 0.11], P = 0.02), stress (SMD = − 0.48, 95% CI [− 0.81, − 0.15], P = 0.004), distress (SMD = − 0.56, 95% CI [− 0.85, − 0.26], P = 0.0002) and mindfulness (SMD = 0.94, 95% CI [0.10, 1.79], P = 0.03). Although the effects on pain, sleep quality, and global QoL were in the expected direction, they were not statistically significant (P > 0.05) based on insufficient evidence.ConclusionsMBSR is worthy of being recommended to breast cancer patients as a complementary treatment or adjunctive therapy.

The clinical application of quinolone antibiotics is particularly extensive. In addition to their high efficiency in infectious diseases, the treatment process brings multiple hidden dangers or side effects. In this regard, drug resistance becomes a major challenge and is almost unavoidable in the clinical application of quinolones. Both genetic and phenotypic variations contribute to bacterial survival resistance under antibiotic therapy. This review is focusing on the drug discovery history, compound structure, and bactericidal mechanism of quinolone antibiotics. Recent studies bring a more in-depth insight into the research progress of quinolone antibiotics in the causes of death, drug resistance formation, and closely related SOS response after disease treatment at this stage. Combined with the latest clinical studies, we summarize the clinical application of quinolone antibiotics and further lay a theoretical foundation for the mechanism study of resistant or sensitive bacteria in response to quinolone treatment.

Intelligent process control and automation systems require verification authentication through digital or handwritten signatures. Digital copies of handwritten signatures have different pixel intensities and spatial variations due to the factors of the surface, writing object, etc. On the verge of this fluctuating drawback for control systems, this manuscript introduces a Spatial Variation-dependent Verification (SVV) scheme using textural features (TF). The handwritten and digital signatures are first verified for their pixel intensities for identification point detection. This identification point varies with the signature’s pattern, region, and texture. The identified point is spatially mapped with the digital signature for verifying the textural feature matching. The textural features are extracted between two successive identification points to prevent cumulative false positives. A convolution neural network aids this process for layered analysis. The first layer is responsible for generating new identification points, and the second layer is responsible for selecting the maximum matching feature for varying intensity. This is non-recurrent for the different textures exhibited as the false factor cuts down the iterated verification. Therefore, the maximum matching features are used for verifying the signatures without high false positives. The proposed scheme’s performance is verified using accuracy, precision, texture detection, false positives, and verification time.

Background Tea trees originated in southwest China 60 million or 70 million years ago. Written records show that Chinese ancestors had begun drinking tea over 3000 years ago. Nowadays, with the aging of populations worldwide and more people suffering from non-communicable diseases or poor health, tea beverages have become an inexpensive and fine complementary and alternative medicine (CAM) therapy. At present, there are 3 billion people who like to drink tea in the world, but few of them actually understand tea, especially on its development process and the spiritual and cultural connotations. Methods We searched PubMed, Google Scholar, Web of Science, CNKI, and other relevant platforms with the key word “tea”, and reviewed and analyzed tea-related literatures and pictures in the past 40 years about tea’s history, culture, customs, experimental studies, and markets. Results China is the hometown of tea, tea trees, tea drinking, and tea culture. China has the oldest wild and planted tea trees in the world, fossil of a tea leaf from 35,400,000 years ago, and abundant tea-related literatures and art works. Moreover, tea may be the first Chinese herbal medicine (CHM) used by Chinese people in ancient times. Tea drinking has many benefits to our physical health via its antioxidant, anti-inflammatory, immuno-regulatory, anticancer, cardiovascular-protective, anti-diabetic, and anti-obesity activities. At the moment, COVID-19 is wreaking havoc across the globe and causing severe damages to people’s health and lives. Tea has anti-COVID-19 functions via the enhancement of the innate immune response and inhibition of viral growth. Besides, drinking tea can allow people to acquire a peaceful, relaxed, refreshed and cheerful enjoyment, and even longevity. According to the meridian theory of traditional Chinese medicine, different kinds of tea can activate different meridian systems in the human body. At present, black tea (fermented tea) and green tea (non-fermented tea) are the most popular in the world. Black tea accounts for over 90% of all teas sold in western countries. The world’s top-grade black teas include Qi Men black in China, Darjeeling and Assam black tea in India, and Uva black tea in Sri Lanka. However, all top ten famous green teas in the world are produced in China, and Xi Hu Long Jing tea is the most famous among all green teas. More than 700 different kinds of components and 27 mineral elements can be found in tea. Tea polyphenols and theaflavin/thearubigins are considered to be the major bioactive components of black tea and green tea, respectively. Overly strong or overheated tea liquid should be avoided when drinking tea. Conclusions Today, CAM provides an array of treatment modalities for the health promotion in both developed and developing countries all over the world. Tea drinking, a simple herb-based CAM therapy, has become a popular man-made non-alcoholic beverage widely consumed worldwide, and it can improve the growth of economy as well. Tea can improve our physical and mental health and promote the harmonious development of society through its chemical and cultural elements.

By means of first principles calculation and experiments, a detailed mechanism is proposed to include the stages of slip, adjustment, and expansion for the HCP → FCC phase transformation with the prismatic relation of { 10 1 ¯ 0 } hcp ∥ { 1 1 ¯ 0 } fcc and [ 0001 ] hcp ∥ [ 001 ] fcc in titanium. It is revealed that the formation of four FCC layers is preferable after the slip of Shockley partial dislocations of 1/6 〈 1 2 ¯ 10 〉 on { 10 1 ¯ 0 } planes, and that the adjustment of interplanar spacing and the volume expansion are energetically favorable and could happen spontaneously without any energy barrier. It is also found that the transformed FCC lattice first follows the c / a ratio (1.583) of HCP and then becomes an ideal FCC stru c ture ( c / a  = √2). The proposed mechanism could not only provide a deep understanding to the process of HCP → FCC prismatic transformation in titanium, but also clarify the controversy regarding volume expansion of HCP-FCC phase transition of titanium in the literature.

Machine learning (ML) plays a pivotal role in extending the reach of quantum chemistry methods for simulating both molecules and materials. However, leveraging ML to overcome the limitations of human-designed density functional approximations (DFAs), the primary workhorse for quantum simulations, remains a major challenge due to their severely limited transferability to unseen chemical systems. Here, we demonstrate how transferability is achieved using real-space ML, where energies are learned point by point in space through energy densities. Central to our real-space learning strategy is the derivation and implementation of correlation energy densities from regularized perturbation theory. This enables two key advances toward constructing highly transferable DFAs, grounded in the Møller-Plesset adiabatic connection framework, for correlation energies defined with respect to the Hartree-Fock reference. First, we introduce the Local Energy Loss, whose data efficiency (expanding each system’s single energy into thousands of data points) dramatically enhances transferability when combined with a physically informed ML model. Second, we formulate a real-space, machine-learned, and regularized extension of Spin-Component-Scaled second-order Møller-Plesset perturbation theory, yielding transferable DFAs that effectively mitigate the self-interaction errors common to traditional DFAs. Machine learning expands quantum chemistry’s reach, but it struggles to generalize to unseen chemistry. Here, the authors develop a real-space learning strategy based on energy densities to build highly transferable quantum-chemical models.

Telemedicine can help specialists in providing efficient care to patients from a distance and it has been growing steadily in healthcare. This study aims to provide an operational perspective by investigating the effect of telemedicine on patients' choices, healthcare providers' service decisions, service quality and total social welfare. We propose an optimization model that incorporates patients' choices and physicians' actions under two scenarios: full coverage and partial coverage. We analyze the model and conduct numerical experiments to explore the impact of telemedicine in a referral-based healthcare system with heterogeneous patients. The findings show that telemedicine can induce greater collaboration between generalists and the specialist, which would result in the specialist spending less time on each patient. Interestingly, we find that after the introduction of telemedicine, the average quality cost decreases under full coverage but increases under partial coverage. Moreover, the introduction of telemedicine could lead to higher social welfare as it improves the accessibility of services to patients, especially in rural areas. Finally, this study also demonstrates that the referral-based healthcare system may benefit more from telemedicine when there is a heavier travel burden for patients or a higher financial incentive for generalists. The introduction of telemedicine mainly contributes to the patients' service accessibility, particularly for patients in remote areas, and can foster closer collaboration between generalists and specialists. However, in hospitals where medical resources are already strained, it may worsen specialist overuse and lead to lower service quality. These findings highlight that telemedicine is not universally beneficial. The policymaker should consider regional coverage conditions and use targeted financial incentives to improve its effectiveness within referral-based healthcare systems.

High-efficiency organic solar cells are often achieved using toxic halogenated solvents and additives that are constrained in organic solar cells industry. Therefore, it is important to develop materials or processing methods that enabled highly efficient organic solar cells processed by halogen free solvents. In this paper, we report an innovative processing method named auxiliary sequential deposition that enables 19%-efficiency organic solar cells processed by halogen free solvents. Our auxiliary sequential deposition method is different from the conventional blend casting or sequential deposition methods in that it involves an additional casting of dithieno[3,2-b:2’,3’-d]thiophene between the sequential depositions of the donor (D18-Cl) and acceptor (L8-BO) layers. The auxiliary sequential deposition method enables dramatic performance enhancement from 15% to over 18% compared to the blend casting and sequential deposition methods. Furthermore, by incorporating a branched-chain-engineered acceptor called L8-BO-X, device performance can be boosted to over 19% due to increased intermolecular packing, representing top-tier values for green-solvent processed organic solar cells. Comprehensive morphological and time-resolved characterizations reveal that the superior blend morphology achieved through the auxiliary sequential deposition method promotes charge generation while simultaneously suppressing charge recombination. This research underscores the potential of the auxiliary sequential deposition method for fabricating highly efficient organic solar cells using environmentally friendly solvents. The optimization of morphology of active layers for halogen-free solvent processing is essential to enhance performance of organic solar cells. Here, the authors report auxiliary sequential deposition method together with branched-chain-engineered acceptor, realizing device efficiency of over 19%.