Molecular Targeted Therapy for the Bone Loss Secondary to Pyogenic Spondylodiscitis Using Medications for Osteoporosis: A Literature Review

Pyogenic spondylodiscitis can cause severe osteolytic and destructive lesions in the spine. Elderly or immunocompromised individuals are particularly susceptible to infectious diseases; specifically, infections in the spine can impair the ability of the spine to support the trunk, causing patients to be bedridden, which can also severely affect the physical condition of patients. Although treatments for osteoporosis have been well studied, treatments for bone loss secondary to infection remain to be elucidated because they have pathological manifestations that are similar to but distinct from those of osteoporosis. Recently, we encountered a patient with severely osteolytic pyogenic spondylodiscitis who was treated with romosozumab and exhibited enhanced bone formation. Romosozumab stimulated canonical Wnt/β-catenin signaling, causing robust bone formation and the inhibition of bone resorption, which exceeded the bone loss secondary to infection. Bone loss due to infections involves the suppression of osteoblastogenesis by osteoblast apoptosis, which is induced by the nuclear factor-κB and mitogen-activated protein kinase pathways, and osteoclastogenesis with the receptor activator of the nuclear factor-κB ligand-receptor combination and subsequent activation of the nuclear factor of activated T cells cytoplasmic 1 and c-Fos. In this study, we review and discuss the molecular mechanisms of bone loss secondary to infection and analyze the efficacy of the medications for osteoporosis, focusing on romosozumab, teriparatide, denosumab, and bisphosphonates, in treating this pathological condition.     

Multifaceted Mechanisms of Action of Metformin Which Have Been Unraveled One after Another in the Long History

While there are various kinds of drugs for type 2 diabetes mellitus at present, in this review article, we focus on metformin which is an insulin sensitizer and is often used as a first-choice drug worldwide. Metformin mainly activates adenosine monophosphate-activated protein kinase (AMPK) in the liver which leads to suppression of fatty acid synthesis and gluconeogenesis. Metformin activates AMPK in skeletal muscle as well, which increases translocation of glucose transporter 4 to the cell membrane and thereby increases glucose uptake. Further, metformin suppresses glucagon signaling in the liver by suppressing adenylate cyclase which leads to suppression of gluconeogenesis. In addition, metformin reduces autophagy failure observed in pancreatic β-cells under diabetic conditions. Furthermore, it is known that metformin alters the gut microbiome and facilitates the transport of glucose from the circulation into excrement. It is also known that metformin reduces food intake and lowers body weight by increasing circulating levels of the peptide hormone growth/differentiation factor 15 (GDF15). Furthermore, much attention has been drawn to the fact that the frequency of various cancers is lower in subjects taking metformin. Metformin suppresses the mechanistic target of rapamycin (mTOR) by activating AMPK in pre-neoplastic cells, which leads to suppression of cell growth and an increase in apoptosis in pre-neoplastic cells. It has been shown recently that metformin consumption potentially influences the mortality in patients with type 2 diabetes mellitus and coronavirus infectious disease (COVID-19). Taken together, metformin is an old drug, but multifaceted mechanisms of action of metformin have been unraveled one after another in its long history.     

Study on maximum power point tracking of photovoltaic array in irregular shadow

Traditional maximum power point tracking (MPPT) methods can hardly find global maximum power point (MPP) because output characteristics curve of photovoltaic (PV) array may have multi local maximum power points in irregular shadow, and thus easily fall into the local maximum power point. To address this drawback, Considering that sliding mode variable structure (SMVS) control strategy have such advantages as simple structure, fast response and strong robustness, and P&O method have the advantages of simple principle and convenient implementation, so a new algorithm combining SMVS control method and P&O method is proposed, besides, PI controller is applied to reduce system chattering caused by switching sliding surface. It is applied to MPPT control of PV array in irregular shadow to solve the problem of multi-peak optimization in partial shadow. In order to verity the rationality of the proposed algorithm, the experimental circuit is built, which achieves MPPT control by means of the proposed algorithm and P&O method. The experimental results show that compared with the traditional P&O algorithm, the proposed algorithm can fast track the global MPP, tracking speed increases by 60% and the relative error decreased by 20%. Moreover, the system becomes more stable near the MPP, the fluctuations of output power is greatly reduced, and thus make full use of solar energy.     

Oxidation of caffeic acid in the presence of l-cysteine: isolation of 2-S-cysteinylcaffeic acid and evaluation of its antioxidant properties

Caffeic acid (3,4-dihydroxycinnamic acid) was oxidized in wine-like model solutions (citrate buffer, pH 3.5) containing l-cysteine, by means of sodium periodate that mimics the mechanism of polyphenol oxidase (PPO). The reaction lead to the formation of a l-cysteine/caffeic acid adduct, which was isolated and tentatively identified as 2-S-cysteinylcaffeic acid (2-CCA), on the basis of LC-MS and ¹H NMR data. The antioxidant properties of 2-CCA were assessed by employing the DPPH and a ferric-reducing test, and compared with both caffeic acid and l-cysteine, but also with gallic acid, which was used as a reference antioxidant. The results indicated that the adduct exhibits slightly improved antiradical activity in relation with the parent molecule (caffeic acid), but its reducing capacity was dramatically reduced, a fact that was theoretically ascribed to its strong chelating ability.     

Recovery of Sb(V) using a functional-ligand-containing porous hollow-fiber membrane prepared by radiation-induced graft polymerization

A ligand-containing porous membrane was prepared by radiation-induced graft polymerization of an epoxy-group-containing monomer of glycidyl methacrylate onto a polyethylene porous hollow-fiber membrane and by subsequent conversion of the epoxy group to an N-methylglucamino (NMG) group at a density of 0.78 mmol/g of the membrane. Sb(V) solution was permeated through the NMG-ligand-containing porous hollow-fiber membrane. Optimum pH for Sb(V) recovery was 3.0. Breakthrough curves of Sb (V) overlapped irrespective of residence times of Sb (V) in the membrane, due to negligible diffusional mass-transfer resistance. Maximum amount of Sb (V) adsorbed was 130 mg/g-membrane, which was equivalent to 1.3 binding molar ratio. Repeated usage of the membrane for adsorption and elution was possible.     

A Micellar Route to Ordered Arrays of Magnetic Nanoparticles: From Size‐Selected Pure Cobalt Dots to Cobalt–Cobalt Oxide Core–Shell Systems

Starting with Co‐salt‐loaded inverse micelles, which form if the diblock copolymer polystyrene‐block‐poly(2‐vinylpyridine) is dissolved in a selective solvent like toluene and CoCl₂ is added to the solution, monomicellar arrays of such micelles exhibiting a significant hexagonal order can be prepared on top of various substrates with tailored intermicellar distances and structure heights. In order to remove the polymer matrix and to finally obtain arrays of pure Co nanoparticles, the micelles are first exposed to an oxygen plasma, followed by a treatment in a hydrogen plasma. Applying in‐situ X‐ray photoelectron spectroscopy, it is demonstrated that: 1) The oxygen plasma completely removes the polymer, though conserving the original order of the micellar array. Furthermore, the resulting nanoparticles are entirely oxidized with a chemical shift of the Co 2p_3/2 line pointing to the formation of Co₃O₄. 2) By the subsequent hydrogen plasma treatment the nanoparticles are fully reduced to metallic Co. 3) By exposing the pure Co nanoparticles for 100 s to various oxygen partial pressures pequation/tex2gif-inf-5.gif, a stepwise oxidation is observed with a still metallic Co core surrounded by an oxide shell. The data allow the extraction of the thickness of the oxide shell as a function of the total exposure to oxygen (pequation/tex2gif-inf-7.gif × time), thus giving the opportunity to control the ferromagnetic–antiferromagnetic composition of an exchange‐biased magnetic system.     

Corrosion morphologies on magnesium alloy AZ 91

Initiation and early propagation of pitting and filiform corrosion on bare alloy AZ91 (9% Al, 1% Zn) are investigated by natural immersion corrosion tests, electrochemical measurements and microanalytical studies. Initiation sites are few. Corrosion spreads from these sites first in the form of filiform corrosion for a limited period of time and pitting which later develops into a cellular type of etching. The important factors affecting filiform corrosion are temperature, material structure and degree of polarization at the anodic sites. Filiform attack on AZ91, unlike the classical mechanisms of filiform corrosion on coated metals, is driven by hydrogen evolution reaction on the cathodic sites of the surface, occurs under significant anodic control, propagates at a high, constant speed independent of degree of polarization along preferential paths determined by compositional and crystallographic factors, and is a temporary phenomenon under open circuit conditions. Pitting corrosion is more predominant with decreasing anodic polarization.     

Short-term load forecasting using bayesian neural networks learned by Hybrid Monte Carlo algorithm

This paper presents a short term load forecasting model based on Bayesian neural network (shorted as BNN) learned by the Hybrid Monte Carlo (shorted as HMC) algorithm. The weight vector parameter of the Bayesian neural network is a multi-dimensional random variable. In learning process, the Bayesian neural network is considered as a special Hamiltonian dynamical system, and the weights vector as the system position variable. The HMC algorithm is used to learn the weight vector parameter with respect to Normal prior distribution and Cauchy prior distribution, respectively. The Bayesian neural networks learned by Laplace algorithm and HMC algorithm and the artificial neural network (ANN) learned by the BP algorithm were used to forecast the hourly load of 25 days of April (Spring), August (Summer), October (Autumn) and January (Winter), respectively. The roots mean squared error (RMSE) and the mean absolute percent errors (MAPE) were used to measured the forecasting performance. The experimental result shows that the BNNs learned by HMC algorithm have far better performance than the BNN learned by Laplace algorithm and the neural network learned BP algorithm and the BNN learned by HMC has powerful generalizing capability, it can welly solve the overfitting problem.     

CHID1 Is a Novel Prognostic Marker of Non-Small Cell Lung Cancer

There is an urgent need for identification of new prognostic markers and therapeutic targets for non-small cell lung cancer (NSCLC). In this study, we evaluated immune cells markers in 100 NSCLC specimens. Immunohistochemical analysis revealed no prognostic value for the markers studied, except CD163 and CD206. At the same time, macrophage markers iNOS and CHID1 were found to be expressed in tumor cells and associated with prognosis. We showed that high iNOS expression is a marker of favorable prognosis for squamous cell lung carcinoma (SCC), and NSCLC in general. Similarly, high CHID1 expression is a marker of good prognosis in adenocarcinoma and in NSCLC in general. Analysis of prognostic significance of a high CHID1/iNOS expression combination showed favorable prognosis with 20 months overall survival of patients from the low CHID1/iNOS expression group. For the first time, we demonstrated that CHID1 can be expressed by NSCLC cells and its high expression is a marker of good prognosis for adenocarcinoma and NSCLC in general. At the same time, high expression of iNOS in tumor cells is a marker of good prognosis in SCC. When used in combination, CHID1 and iNOS show a very good prognostic capacity for NSCLC. We suggest that in the case of lung cancer, tumor-associated macrophages are likely ineffective as a therapeutic target. At the same time, macrophage markers expressed by tumor cells may be considered as targets for anti-tumor therapy or, as in the case of CHID1, as potential anti-tumor agents.