Xiao Cheng Qi Decoction, an Ancient Chinese Herbal Mixture, Relieves Loperamide-Induced Slow-Transit Constipation in Mice: An Action Mediated by Gut Microbiota.

Xiao Cheng Qi (XCQ) decoction, an ancient Chinese herbal mixture, has been used in treating slow-transit constipation (STC) for years. The underlying action mechanism in relieving the clinical symptoms is unclear. Several lines of evidence point to a strong link between constipation and gut microbiota. Short-chain fatty acids (SCFAs) and microbial metabolites have been shown to affect 5-HT synthesis by activating the GPR43 receptor localized on intestinal enterochromaffin cells, since 5-HT receptors are known to influence colonic peristalsis. The objective of this study was to evaluate the efficacy of XCQ in alleviating clinical symptoms in a mouse model of STC induced by loperamide. The application of loperamide leads to a decrease in intestinal transport and fecal water, which is used to establish the animal model of STC. In addition, the relationship between constipation and gut microbiota was determined. The herbal materials, composed of Rhei Radix et Rhizoma (Rhizomes of Rheum palmatum L., Polygonaceae) 55.2 g, Magnoliae Officinalis Cortex (Barks of Magnolia officinalis Rehd. et Wils, Magnoliaceae) 27.6 g, and Aurantii Fructus Immaturus (Fruitlet of Citrus aurantium L., Rutaceae) 36.0 g, were extracted with water to prepare the XCQ decoction. The constipated mice were induced with loperamide (10 mg/kg/day), and then treated with an oral dose of XCQ herbal extract (2.0, 4.0, and 8.0 g/kg/day) two times a day. Mosapride was administered as a positive drug. In loperamide-induced STC mice, the therapeutic parameters of XCQ-treated mice were determined, i.e., (i) symptoms of constipation, composition of gut microbiota, and amount of short-chain fatty acids in feces; (ii) plasma level of 5-HT; and (iii) expressions of the GPR43 and 5-HT4 receptor in colon. XCQ ameliorated the constipation symptoms of loperamide-induced STC mice. In gut microbiota, the treatment of XCQ in STC mice increased the relative abundances of Lactobacillus, Prevotellaceae_UCG_001, Prevotellaceae_NK3B31_group, Muribaculaceae, and Roseburia in feces and decreased the relative abundances of Desulfovibrio, Tuzzerella, and Lachnospiraceae_ NK4A136_group. The levels of SCFAs in stools from the STC group were significantly lower than those the control group, and were greatly elevated via treatment with XCQ. Compared with the STC group, XCQ increased the plasma level of 5-HT and the colonic expressions of the GPR43 and 5-HT4 receptor, significantly. The underlying mechanism of XCQ in anti-constipation could be related to the modulation of gut microbiota, the increase in SCFAs, the increase in plasma 5-HT, and the colonic expressions of the GPR43 and 5-HT4 receptor. Our results indicate that XCQ is a potent natural product that could be a therapeutic strategy for constipation.

Muscle Inflammation Susceptibility: A Potential Phenotype for Guiding Precision Rehabilitation After Total Hip Arthroplasty in End-Stage Osteoarthritis.

The progression of osteoarthritis of the hip to its end stage and ultimately to total hip arthroplasty (THA) is complex; the multifactorial pathophysiology involves myriad collaborating tissues in and around the diseased joint. We have named the heightened state of periarticular muscle inflammation at the time of surgery "muscle inflammation susceptibility" (MuIS) because it is distinct from systemic inflammation. In this review article, we discuss how MuIS and heightened atrophy-associated signaling in the periarticular skeletal muscles may contribute to reduced muscle mass, impaired muscle quality (ie, through fibrosis), and a muscle microenvironment that challenges regenerative capacity and thus functional recovery from THA. We also review directions for future research that should advance understanding of the key determinants of precision for optimized success of THA for each individual.

Importing Antibonding-Orbital Occupancy through Pd-O-Gd Bridge Promotes Electrocatalytic Oxygen Reduction.

The active-site density, intrinsic activity, and durability of Pd-based materials for oxygen reduction reaction (ORR) are critical to their application in industrial energy devices. This work constructs a series of carbon-based rare-earth (RE) oxides (Gd2 O3 , Sm2 O3 , Eu2 O3 , and CeO2 ) by using RE metal-organic frameworks to tune the ORR performance of the Pd sites through the Pd-REx Oy interface interaction. Taking Pd-Gd2 O3 /C as a representative, it is identified that the strong coupling between Pd and Gd2 O3 induces the formation of the Pd-O-Gd bridge, which triggers charge redistribution of Pd and Gd2 O3 . The screened Pd-Gd2 O3 /C exhibits impressive ORR performance with high onset potential (0.986 VRHE ), half-wave potential (0.877 VRHE ), and excellent stability. Similar ORR results are also found for Pd-Sm2 O3 /C, Pd-Eu2 O3 /C, and Pd-CeO2 /C catalysts. Theoretical analyses reveal that the coupling between Pd and Gd2 O3 promotes electron transfer through the Pd-O-Gd bridge, which induces the antibonding-orbital occupancy of Pd-*OH for the optimization of *OH adsorption in the rate-determining step of ORR. The pH-dependent microkinetic modeling shows that Pd-Gd2 O3 is close to the theoretical optimal activity for ORR, outperforming Pt under the same conditions. By its ascendancy in ORR, the Pd-Gd2 O3 /C exhibits superior performance in Zn-air battery as an air cathode, implying its excellent practicability.

CT features combined with RECIST 1.1 criteria improve progression assessments of sunitinib-treated gastrointestinal stromal tumors.

OBJECTIVES: To explore the auxiliary value of combining CT features with existing response evaluation criteria in the prediction of progressive disease (PD) in gastrointestinal stromal tumors (GIST) patients treated with sunitinib. MATERIAL AND METHODS: Eighty-one patients with GISTs who received sunitinib were included in this retrospective multicenter study and divided into training and external validation cohorts. Progression at six months was determined as a reference standard. The predictive performance of the RECIST 1.1 and Choi criteria was compared. CT features at baseline and the first follow-up were analyzed. Logistic regression analyses were used to determine the most significant predictors and develop modified criteria. RESULTS: A total of 216 lesions showed a good response and 107 showed a poor response in 81 patients. The RECIST 1.1 criteria performed better than the Choi criteria in predicting progression (AUC, 0.75 vs. 0.69, p = 0.04). The expanded/intensified high-enhancement area, blurred tumor-tissue interface, and progressive enlarged vessels feeding or draining the mass (EVFDM) differed significantly between lesions with good and poor responses in the training cohort (p = 0.001, 0.003, and 0.000, respectively). Multivariate analysis revealed that the expanded/intensified high-enhancement area (p = 0.001), progressive EVFDM (p = 0.000), and RECIST PD (p = 0.000) were independent predictive factors. Modified RECIST (mRECIST) criteria were developed and showed significantly higher AUCs in the training and external validation cohorts than the RECIST 1.1 criteria (training: 0.81 vs. 0.73, p = 0.002; validation: 0.82 vs. 0.77, p = 0.04). CONCLUSION: The mRECIST criteria, combining CT features with the RECIST 1.1 criteria, demonstrated superior performance in the prediction of early progression in GIST patients receiving sunitinib. CLINICAL RELEVANCE STATEMENT: The mRECIST criteria, which combine CT features with the RECIST 1.1 criteria, may facilitate the early detection of progressive disease in GIST patients treated with sunitinib, thereby potentially guiding the timely switch to late-line medications or combination with surgical excision. KEY POINTS: • The RECIST 1.1 criteria outperformed the Choi criteria in identifying progression of GISTs in patients treated with sunitinib. • GISTs displayed different morphologic features on CT depending on how they responded to sunitinib. • Combining CT morphologic features with the RECIST 1.1 criteria allowed for the prompt and accurate identification of progressing GIST lesions.

Ultrathin Cobalt-Based Prussian Blue Analogue Nanosheet-Assembled Nanoboxes Interpenetrated with Carbon Nanotubes as a Fast Electron/Potassium-Ion Conductor for Superior Potassium Storage.

Rechargeable potassium-ion batteries (PIBs) are regarded as potential substitutes for industrial lithium-ion batteries in large scale energy storage systems due to the world's abundant potassium supplies. Althogh cobalt hexacyanocobaltate (CoHCC) exhibits broad potential as a PIB anode material, its performance is currently unsatisfactory. Herein, novel 5 nm scale ultrathin CoHCC nanosheet-assembled nanoboxes with interspersed carbon nanotubes (CNTs/CoHCC nanoboxes) are fabricated to realize a highly reactive PIB anode. The ultrathin CoHCC layers substantially accelerate electron conduction and provide numerous active sites, while the connected CNTs provide fast axial electron transport. Consequently, the optimized anode exhibits a remarkable discharge capacity of 580.9 mAh g-1 at 0.1 A g-1 and long-term stability with 71.3% retention over 1000 cycles. In situ and ex situ characterizations and density functional theory calculations are further employed to elucidate the K+ storage process and the reason for the enhanced performance of the CNTs/CoHCC nanoboxes.

Numerical simulation for strip-island freshwater lenses involving a precipitation-fed freshwater table.

The freshwater table is the upper boundary of the entire freshwater lens and is very important for understanding the formation of freshwater lenses and for managing fresh groundwater on islands. However, little attention has been given to the position of the freshwater table, as it is difficult to visually distinguish it from the unsaturated zone in physical models. Under the natural conditions, the process of rainfall infiltration into soils involves both pore-water flow and air flow in soil voids, and thus, the airflow induced by infiltration has implications for groundwater recharge and formation of freshwater lenses. Therefore, research on the precipitation-fed freshwater table in an oceanic island should consider the water-air two-phase flow induced by rainwater infiltration. This study focuses on simulating the steady-state position of the freshwater table using TOUGH2/EOS7, a model that considers liquid and gas two-phase flow and brine, water and air three-component in unsaturated-saturated porous media, and verifying it by comparing the numerical results with the analytical solutions. The numerical results delineated the entire geometry of island freshwater lenses that involve a freshwater table replenished by precipitation, which were then compared with the Dupuit-Ghyben-Herzberg (DGH) analytical solutions that ignore the outflow face and with Van der Veer's analytical solutions that consider the outflow face. Reasonable fits between the numerical results and the DGH analytical solutions were obtained, with the exception that the lens obtained by the DGH analytical model is smaller in size than that simulated by the numerical model for various cases; a better agreement was found between the results from the numerical model and Van der Veer's analytical solutions for the homogeneous island case. The agreements between the results from the proposed numerical model and the DGH and Van der Veer's analytical models verified the proposed numerical model. The numerical modeling method investigated here enhanced the numerical simulation techniques for studying groundwater movements and the interaction of freshwater and saltwater on oceanic islands and can provide a reference for modeling more complicated island groundwater patterns.

Predictive role of serum C-peptide in new-onset renal dysfunction in type 2 diabetes: a longitudinal observational study.

Background: Our previous cross-sectional study has demonstrated the independently non-linear relationship between fasting C-peptide with renal dysfunction odds in patients with type 2 diabetes (T2D) in China. This longitudinal observational study aims to explore the role of serum C-peptide in risk prediction of new-onset renal dysfunction, then construct a predictive model based on serum C-peptide and other clinical parameters. Methods: The patients with T2D and normal renal function at baseline were recruited in this study. The LASSO algorithm was performed to filter potential predictors from the baseline variables. Logistic regression (LR) was performed to construct the predictive model for new-onset renal dysfunction risk. Power analysis was performed to assess the statistical power of the model. Results: During a 2-year follow-up period, 21.08% (35/166) of subjects with T2D and normal renal function at baseline progressed to renal dysfunction. Six predictors were determined using LASSO regression, including baseline albumin-to-creatinine ratio, glycated hemoglobin, hypertension, retinol-binding protein-to-creatinine ratio, quartiles of fasting C-peptide, and quartiles of fasting C-peptide to 2h postprandial C-peptide ratio. These 6 predictors were incorporated to develop model for renal dysfunction risk prediction using LR. Finally, the LR model achieved a high efficiency, with an AUC of 0.83 (0.76 - 0.91), an accuracy of 75.80%, a sensitivity of 88.60%, and a specificity of 70.80%. According to the power analysis, the statistical power of the LR model was found to be 0.81, which was at a relatively high level. Finally, a nomogram was developed to make the model more available for individualized prediction in clinical practice. Conclusion: Our results indicated that the baseline level of serum C-peptide had the potential role in the risk prediction of new-onset renal dysfunction. The LR model demonstrated high efficiency and had the potential to guide individualized risk assessments for renal dysfunction in clinical practice.

Optimization of Coupling Efficiency in Butterfly Optical Communication Laser Based on Chaotic Adaptive Seeker Optimization Algorithm.

A chaotic adaptive seeker optimization algorithm (CASOA) is proposed in this study to improve the coupling efficiency and accuracy of a butterfly optical communication laser. It primarily relies on chaotic disturbance to improve seeker search performance. The chaotic disturbance enables the algorithm to jump out from local extremes. Furthermore, chaos is associated with a novel strategy for optimizing search paths with a small population. A simulation and experiment are conducted to demonstrate that the CASOA with a few seekers has an excellent search success rate with few iterations in the coupling alignment. These results indicate that the proposed CASOA can reliably improve the coupling accuracy and efficiency of laser diodes and single-mode fibers.

A Versatile Extended Stöber Approach to Monodisperse Sub-40 nm Carbon Nanospheres for Stabilizing Atomically Dispersed Fe─N4 Sites Toward Efficient Oxygen Reduction Electrocatalysis.

The development of atomically dispersed iron-nitrogen-carbon (Fe─N─C) catalysts as an alternative to precious platinum holds great potential for the substantial progress of a variety of oxygen reduction reaction (ORR)-associated energy conversion technologies. Nevertheless, the precise synthesis of Fe─N─C single atomic catalysts (SACs) with a high density of accessible active sites and pronounced electrocatalytic performance still remains an enormous challenge. Herein, an innovative extended Stöber method is designed for the controllable preparation of monodisperse small-sized N-doped carbon colloidal nanospheres (≈40 nm) anchoring atomically isolated Fe─N4 sites (abbreviated as Fe-SA@N-CNSs hereafter) with a narrow size distribution and high uniformity. Benefiting from the single Fe─N4 moieties and the unique spherical carbon substrate, the resultant Fe-SA@N-CNSs exhibit excellent ORR activity, outstanding long-term durability, and methanol tolerance in KOH electrolyte. More impressively, when further assembled into a flexible solid-state rechargeable zinc-air battery (ZAB), the Fe-SA@N-CNSs-driven ZAB delivers a higher open circuit voltage, a larger power density, and robust cycling/mechanical stability, outperforming the state-of-the-art Pt/C-based counterpart and further testifying the great potential of the as-prepared Fe-SA@N-CNSs in diverse ORR-related practical energy devices. The developed extended Stöber method provides an efficient and versatile avenue toward the preparation of a series of well-defined SACs for diverse electrocatalytic systems.

Identifying inpatient mortality in MarketScan claims data using machine learning.

PURPOSE: Inpatient mortality is an important variable in epidemiology studies using claims data. In 2016, MarketScan data began obscuring specific hospital discharge status types for patient privacy, including inpatient deaths, by setting the values to missing. We used a machine learning approach to correctly identify hospitalizations that resulted in inpatient death using data prior to 2016. METHODS: All hospitalizations from 2011 to 2015 with discharge status of missing, died, or one of the other subsequently obscured values were identified and divided into a training set and two test sets. Predictor variables included age, sex, elapsed time from hospital discharge until last observed claim and until healthcare plan disenrollment, and absence of any discharge diagnoses. Four machine learning methods were used to train statistical models and assess sensitivity and positive predictive value (PPV) for inpatient mortality. RESULTS: Overall 1 307 917 hospitalizations were included. All four machine learning approaches performed well in all datasets. Random forest performed best with 88% PPV and 93% sensitivity for the training set and both test sets. The two factors with the highest relative importance for identifying inpatient mortality were having no observed claims for the patient on days 2-91 following hospital discharge and patient disenrollment from the healthcare plan within 60 days following hospital discharge. CONCLUSION: We successfully developed machine learning algorithms to identify inpatient mortality. This approach can be applied to obscured data to accurately identify inpatient mortality among hospitalizations with missing discharge status.

Spin-Selective Coupling in Mott-Schottky Er2 O3 -Co Boosts Electrocatalytic Oxygen Reduction.

Alkaline oxygen reduction reaction (ORR) is critical to electrochemical energy conversion technology, yet the rational breaking of thermodynamic inhibition for ORR through spin regulation remains a challenge. Herein, a Mott-Schottky catalyst consisting of Er2 O3 -Co particles uniformly implanted into carbon nanofibers (Er2 O3 -Co/CNF) is designed for enhancing ORR via spin-selective coupling. The optimized Er2 O3 -Co/CNF affords a high half-wave potential (0.835 V vs reversible hydrogen electrode, RHE) and onset potential (0.989 VRHE ) for the ORR surpassing individual Co/CNF and Er2 O3 /CNF. Theoretical calculations reveal the introduction of Er2 O3 optimizes the electronic structure of Co through Er(4f)-O(2p)-Co(3d) gradient orbital coupling, resulting in significantly enhanced ORR performance. Through gradient orbital coupling, the induced spin-up hole in Co 3d states endows the Er-O-Co unit active site with a spin-selective coupling channel for electron transition. This favors the decrease of the energy gap in the potential-limiting step, thus achieving a high theoretical limiting potential of 0.77 VRHE for the Er2 O3 -Co. Moreover, the potential practicability of Er2 O3 -Co/CNF as an air-cathode is also demonstrated in Zn-air batteries. This work is believed to provide, new perspectives for the design of efficient ORR electrocatalysts by engineering spin-selective coupling induced by rare-earth oxides.

Reinforcing CoO Covalency via Ce(4f)─O(2p)─Co(3d) Gradient Orbital Coupling for High-Efficiency Oxygen Evolution.

Rare-earth (RE)-based transition metal oxides (TMO) are emerging as a frontier toward the oxygen evolution reaction (OER), yet the knowledge regarding their electrocatalytic mechanism and active sites is very limited. In this work, atomically dispersed Ce on CoO is successfully designed and synthesized by an effective plasma (P)-assisted strategy as a model (P-Ce SAs@CoO) to investigate the origin of OER performance in RE-TMO systems. The P-Ce SAs@CoO exhibits favorable performance with an overpotential of only 261 mV at 10 mA cm-2 and robust electrochemical stability, superior to individual CoO. X-ray absorption spectroscopy and in situ electrochemical Raman spectroscopy reveal that the Ce-induced electron redistribution inhibits CoO bond breakage in the CoOCe unit site. Theoretical analysis demonstrates that the gradient orbital coupling reinforces the CoO covalency of the Ce(4f)─O(2p)─Co(3d) unit active site with an optimized Co-3d-eg occupancy, which can balance the adsorption strength of intermediates and in turn reach the apex of the theoretical OER maximum, in excellent agreement with experimental observations. It is believed that the establishment of this Ce-CoO model can set a basis for the mechanistic understanding and structural design of high-performance RE-TMO catalysts.

A Novel Strategy for Screening Active Components in Cistanche tubulosa Based on Spectrum-Effect Relationship Analysis and Network Pharmacology.

Cistanche tubulosa (Schenk) R. Wight is a valuable herbal medicine in China. The study aimed to explore the potential mechanisms of C. tubulosa on antioxidant activity using spectrum-effect relationship and network pharmacology and the possibilities of utilizing herbal dregs. In this work, different extracts of C. tubulosa, including herbal materials, water extracts, and herbal residues, were evaluated using high-performance liquid chromatography (HPLC) technology. In addition, the antioxidant activities were estimated in vitro, including 2, 2-diphenyl-1-picrylhydrazyl; superoxide anion; and hydroxyl radical scavenging assays. The spectrum-effect relationships between the HPLC fingerprints and the biological capabilities were analyzed via partial least squares regression, bivariate correlation analysis, and redundancy analysis. Furthermore, network pharmacology was used to predict potential mechanisms of C. tubulosa in the treatment of antioxidant-related diseases. According to the results, eleven common peaks were shared by different extracts. Geniposidic acid, echinacoside, verbascoside, tubuloside A, and isoacteoside were quantified and compared among different forms of C. tubulosa. The spectrum-effect relationship study indicated that peak A 6 might be the most decisive component among the three forms. Based on network pharmacology, there were 159 target genes shared by active components and antioxidant-related diseases. Targets related to antioxidant activity and relevant pathways were discussed. Our results provide a theoretical basis for recycling the herbal residues and the potential mechanisms of C. tubulosa in the treatment of antioxidant-related diseases.

Comparison of cytokine level changes in gingival crevicular fluid between the aligner and pendulum appliance during early molar distalization : A single-center, prospective, observational study.

PURPOSE: There is currently a lack of evidence pertaining to gingival crevicular fluid cytokine levels in patients treated with the pendulum appliance. This study aimed to compare changes in cytokine secretion levels in gingival crevicular fluid (GFC) between the aligner and pendulum appliance in patients undergoing molar distalization. METHODS: GFC samples were collected from 28 participants with asymmetrical dental class II malocclusion who were undergoing molar distalization using aligners or pendulum appliances. An enzyme-linked immunosorbent assay was used to detect cytokine secretion levels during asymmetrical molar distalization for up to 14 days. Periodontal health indices and tooth movements were also assessed. RESULTS: No significant difference was found for the distalization distance between the two appliances. The Silness and Loe Plaque Index and Lobene Modified Gingival Index increased in the pendulum group but not in the aligner group at 14 days. Interleukin-1ß and tumor necrosis factor­α were upregulated in both groups. In the pendulum group, receptor activator of nuclear factor kappa­Β ligand and osteoprotegerin secretion levels were significantly upregulated and downregulated, respectively; smaller changes in these two cytokines were observed in the aligner group. CONCLUSIONS: Pendulum appliances exert stronger forces than aligners, which cause more changes in the secretion of inflammatory mediators in young patients.

Development and Validation of an Emergency Department Electronic Medical Record Gout Flare Alert.

OBJECTIVE: Patients with acute gout are frequently treated in the emergency department (ED) and represent a typically underresourced and understudied population. A key limitation for gout research in the ED is the timely ability to identify acute gout patients. Our goal was to refine a multicriteria, electronic medical record alert for gout flares and to determine its diagnostic characteristics in the ED. METHODS: The gout flare alert used electronic medical record data from ED nursing notes and was triggered by the term 'gout' preceding past medical history in the chief complaint, the term 'gout' and a musculoskeletal problem in the chief complaint, or the term 'gout' in the problem list and a musculoskeletal chief complaint. We validated its diagnostic properties to assess presence/absence of gout through manual medical record review using adjudicated expert consensus as the gold standard. RESULTS: In January 2020, we analyzed 202 patient records from 2 university-based EDs; from these records, 57 patients were identified by our gout flare alert, and 145 were identified by other means as potentially having an acute gout flare. The gout flare alert's positive predictive value was 47% (95% confidence interval [95% CI] 34-60%), negative predictive value was 94% (95% CI 90-98%), sensitivity was 75% (95% CI 61-89%), and specificity was 82% (95% CI 76-88%). The diagnostic properties were similar at both institutions. CONCLUSION: Our multicomponent gout flare alert had reasonable sensitivity and specificity, albeit a modest positive predictive value. An electronic gout flare alert may help enable the conduct of gout research in the ED setting.

Improving the Oxygen Evolution Activity of Layered Double-Hydroxide via Erbium-Induced Electronic Engineering.

Layered double-hydroxide (LDH) has been considered an important class of electrocatalysts for the oxygen evolution reaction (OER), but the adsorption-desorption behaviors of oxygen intermediates on its surface still remain unsatisfactory. Apart from transition-metal doping to solve this electrocatalytic problem of LDH, rare-earth (RE) species have sprung up as emerging dopants owing to their unique 4f valence-electronic configurations. Herein, the Er is chosen as a RE model to improve OER activity of LDH via constructing nickel foam supported Er-doped NiFe-LDH catalyst (Er-NiFe-LDH@NF). The optimal Er-NiFe-LDH@NF exhibits a low overpotential (191 mV at 10 mA cm-2 ), high turnover frequency (0.588 s-1 ), and low activation energy (36.03 kJ mol-1 ), which are superior to Er-free sample. Electrochemical in situ Raman spectra reveal the facilitated transition of Ni-OH into Ni-OOH for promoted OER kinetics through the Er doping effect. Theoretical calculations demonstrate that the introduction of Er facilitates the spin crossover of valence electrons by optimizing the d band center of NiFe-LDH, which leads to the GO -GHO closer to the optimal activity of the kinetic OER volcano by balancing the bonding strength of *O and *OH. Moreover, the Er-NiFe-LDH@NF presents high practicability in electrochemical water-splitting devices with a low driving potential of and a well-extended driving period.

Component analysis using UPLC-Q-Exactive Orbitrap-HRMS and quality control of Kudingcha (Ligustrum robustum (Roxb.) Blume).

Although Kudingcha (Ligustrum robustum (Roxb.) Blume) has been widely used as both traditional medicine and food, systematic studies on their basic active components and quality control are lacking. In this study, a rapid method of identifying the general chemical components of Ligustrum robustum (Roxb.) Blume was established for the first time using UPLC-Q-Exactive Orbitrap-HRMS, and its major basic components were specified as phenylpropanoid, monoterpene, and flavonoid glycosides. The characteristic cleavage pathways of the phenylpropanoid, monoterpene, and flavonoid glycosides were further investigated and elaborated, which could assist in identifying the structures of similar components of other Chinese herbal medicines. A breakthrough was achieved in establishing a chemical fingerprinting profile of Ligustrum robustum (Roxb.) Blume from its original growing areas in China, and chemometric measures were applied to investigate the causes for the variations in its quality stability. The results indicated significant differences in the characteristic compositions of phenylpropanoid and monoterpene glycosides between mature and young leaves of Ligustrum robustum (Roxb.) Blume; however, no significant variation was observed owing to different production areas. Graded harvesting criteria should be established, and harvest period should be specified according to the target active components while considering agricultural metrics, such as leaf shape index, leaf length, and leaf width, to ensure the consistency in quality of active components during their production. From the perspective of overall quality control, an unprecedented quantitative analysis of multi-components by single marker was set up to analyze the signature components of phenylpropanoid glycosides (acteoside, isoacteoside, ligurobustoside N, and ligupurpuroside B) to increase the analytical efficiency and reduce research costs. This study created a scientific basis for the standardized operation, elucidation of the pharmacological materials, and quality control of food and supplements production with Ligustrum robustum (Roxb.) Blume as a raw material.

A case series of constrictive pericarditis and suggested echocardiographic diagnostic criteria.

BACKGROUND: The diagnosis of constrictive pericarditis (CP) is challenging as there are currently no standard echocardiographic diagnostic criteria. In this retrospective case series, we analyzed and summarized the features of 25 patients with CP and proposed echocardiographic diagnostic criteria. It is hoped that the suggested criteria help professionals make decisions in their daily practice so that patients receive timely diagnosis and effective treatment. METHODS: Twenty-five patients with CP were selected for this retrospective study. The clinical and echocardiographic imaging data were analyzed and summarized, and echocardiographic diagnostic criteria for CP were proposed. RESULTS: The main clinical manifestations were fatigue, breathlessness, exertional dyspnea (88%), lower-limb edema (84%), hepatomegaly, and jugular vein filling (84%). Echocardiographic features comprised pericardial thickening (88%) and calcification (60%), pulmonary hypertension (52%), inferior vena cava dilation (80%), left and/or right atrial enlargement (100%), diastolic flattening of the left ventricular (LV) posterior wall (72%), septal shudder and bounce (64%), restrictive LV and right ventricular diastolic filling pattern (100%), early filling changes of mitral and tricuspid flow (80% and 60%, respectively), and mitral annulus reversus (73%). CONCLUSIONS: Echocardiography is a simple and valuable examination for CP. The echocardiographic diagnostic criteria are valid and worth promoting.

Engineering 3d-2p-4f Gradient Orbital Coupling to Enhance Electrocatalytic Oxygen Reduction.

The development of highly efficient and economical materials for the oxygen reduction reaction (ORR) plays a key role in practical energy conversion technologies. However, the intrinsic scaling relations exert thermodynamic inhibition on realizing highly active ORR electrocatalysts. Herein, a novel and feasible gradient orbital coupling strategy for tuning the ORR performance through the construction of Co 3d-O 2p-Eu 4f unit sites on the Eu2 O3 -Co model is proposed. Through the gradient orbital coupling, the pristine ionic property between Eu and O atoms is assigned with increased covalency, which optimizes the eg occupancy of Co sites, and weakens the OO bond, thus ultimately breaking the scaling relation between *OOH and *OH at Co-O-Eu unit sites. The optimized model catalyst displays onset and half-wave potential of 1.007 and 0.887 V versus reversible hydrogen electrode, respectively, which are higher than those of commercial Pt/C and most Co-based catalysts ever reported. In addition, the catalyst is found to possess superior selectivity and durability. It also reveals better cell performance than commercial noble-metal catalysts in Zn-air batteries in terms of high power/energy densities and long cycle life. This study provides a new perspective for electronic modulation strategy by the construction of gradient 3d-2p-4f orbital coupling.

A Crowdsourcing Approach to Develop Machine Learning Models to Quantify Radiographic Joint Damage in Rheumatoid Arthritis.

Importance: An automated, accurate method is needed for unbiased assessment quantifying accrual of joint space narrowing and erosions on radiographic images of the hands and wrists, and feet for clinical trials, monitoring of joint damage over time, assisting rheumatologists with treatment decisions. Such a method has the potential to be directly integrated into electronic health records. Objectives: To design and implement an international crowdsourcing competition to catalyze the development of machine learning methods to quantify radiographic damage in rheumatoid arthritis (RA). Design, Setting, and Participants: This diagnostic/prognostic study describes the Rheumatoid Arthritis 2-Dialogue for Reverse Engineering Assessment and Methods (RA2-DREAM Challenge), which used existing radiographic images and expert-curated Sharp-van der Heijde (SvH) scores from 2 clinical studies (674 radiographic sets from 562 patients) for training (367 sets), leaderboard (119 sets), and final evaluation (188 sets). Challenge participants were tasked with developing methods to automatically quantify overall damage (subchallenge 1), joint space narrowing (subchallenge 2), and erosions (subchallenge 3). The challenge was finished on June 30, 2020. Main Outcomes and Measures: Scores derived from submitted algorithms were compared with the expert-curated SvH scores, and a baseline model was created for benchmark comparison. Performances were ranked using weighted root mean square error (RMSE). The performance and reproductivity of each algorithm was assessed using Bayes factor from bootstrapped data, and further evaluated with a postchallenge independent validation data set. Results: The RA2-DREAM Challenge received a total of 173 submissions from 26 participants or teams in 7 countries for the leaderboard round, and 13 submissions were included in the final evaluation. The weighted RMSEs metric showed that the winning algorithms produced scores that were very close to the expert-curated SvH scores. Top teams included Team Shirin for subchallenge 1 (weighted RMSE, 0.44), HYL-YFG (Hongyang Li and Yuanfang Guan) subchallenge 2 (weighted RMSE, 0.38), and Gold Therapy for subchallenge 3 (weighted RMSE, 0.43). Bootstrapping/Bayes factor approach and the postchallenge independent validation confirmed the reproducibility and the estimation concordance indices between final evaluation and postchallenge independent validation data set were 0.71 for subchallenge 1, 0.78 for subchallenge 2, and 0.82 for subchallenge 3. Conclusions and Relevance: The RA2-DREAM Challenge resulted in the development of algorithms that provide feasible, quick, and accurate methods to quantify joint damage in RA. Ultimately, these methods could help research studies on RA joint damage and may be integrated into electronic health records to help clinicians serve patients better by providing timely, reliable, and quantitative information for making treatment decisions to prevent further damage.