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Craniofacial tissue defects caused by trauma, developmental malformation, or surgery are critical issues of high incidence, which are harmful to physical and psychological health. Transplantation of engineered tissues or biomaterials is a potential method to repair defects and regenerate the craniofacial tissues. Revascularization is essential to ensure the survival and regeneration of the grafts. Since microvessels play a critical role in blood circulation and substance exchange, the pre-establishment of the microvascular network in transplants provides a technical basis for the successful regeneration of the tissue defect. In this study, we reviewed the recent development of strategies and applications of prevascularization in tissue engineering and regeneration of craniofacial tissues. We focused on the cellular foundation of the

Elderly patients living in long-term care facilities have been restricted from leaving to comply with social distancing guidelines during the COVID-19 pandemic. This has led to a worsening of disorders, such as anxiety and depression. This study aims to understand the health benefits of an immersive garden experience to elderly nursing home residents with mild-to-moderate cognitive impairments. Virtual reality devices were used to provide immersive garden experiences for the residents who were unable to go outside. The heart rate and heart rate variability (HRV) data of the participants of the participants were collected using biofeedback instruments, and changes in the low frequency/high frequency (LF/HF) and the standard deviation of the NN interval (SDNN) values caused by immersive garden experiences were discussed. The results show that the immersive garden experiences were beneficial to these elderly residents. Within 6 min of completing the experiment, we found that the heart rates of participants had dropped slightly, while SDNN and HF values continued to rise. SDNN values before and after the experiment demonstrated a statistically significant improvement. Furthermore, participants expressed their satisfaction with the video intervention program. The results indicated that nursing homes can provide immersive landscape experiences to help increase HRV and SDNN of their elderly residents. This will not only help these residents recall beautiful memories of their past, but will also improve their quality of life. Supplementary Information The online version contains supplementary material available at 10.1007/s11355-021-00480-9.

Acetaminophen (APAP), one of the most widely used antipyretic and analgesic drugs, principally contributes to drug-induced liver injury when taken at a high dose. APAP-induced liver injury (AILI) results in extensive necrosis of hepatocytes along with the occurrence of multiple intracellular events such as metabolic activation, cell injury, and signaling pathway activation. However, the specific role of the immune response in AILI remains controversial for its complicated regulatory mechanisms. A variety of inflammasomes, immune cells, inflammatory mediators, and signaling transduction pathways are activated in AILI. These immune components play antagonistic roles in aggravating the liver injury or promoting regeneration. Recent experimental studies indicated that natural products showed remarkable therapeutic effects against APAP hepatotoxicity due to their favorable efficacy. Therefore, this study aimed to review the present understanding of the immune response in AILI and attempted to establish ties among a series of inflammatory cascade reactions. Also, the immune molecular mechanisms of natural products in the treatment of AILI were extensively reviewed, thus providing a fundamental basis for exploring the potential pharmacological targets associated with immune interventions.

Although root canal therapy is the most common and widely used treatment at clinical presentation, there are still some postoperative complications. As cell biology and tissue engineering techniques advance rapidly, the use of biological therapy to regenerate dental pulp has become a new trend; Relevant literatures in recent five years were searched using key words such as “root canal therapy”, “Dental pulp stem cells”, “Dental pulp regeneration”, and “Cell homing” in PubMed, Web of Science, etc; Dental pulp stem cells (DPSCs) have multi-differentiation potential, self-renewal capability, and high proliferative ability. Stem cell-based dental pulp regeneration has emerged as a new research hot spot in clinical therapy. Recently, dental pulp-like structures have been generated by the transplantation of exogenous DPSCs or the induction of homing of endogenous DPSCs. Studies on DPSCs are important and significant for dental pulp regeneration and dental restoration; In this review, the existing clinical treatment methods, dental pulp regeneration, and DPSC research status are revealed, and their application prospects are discussed. The stem cell-based pulp regeneration exerts promising potential in clinical therapy for pulp regeneration.

Introduction The transplantation of dental pulp stem cells (DPSCs) has emerged as a novel strategy for the regeneration of lost dental pulp after pulpitis and trauma. Dental pulp regeneration of the young permanent tooth with a wide tooth apical foramen has achieved significant progress in the clinical trials. However, because of the narrow apical foramen, dental pulp regeneration in adult teeth using stem cells remains difficult in the clinic. Finding out how to promote vascular reconstitution is essential for the survival of stem cells and the regeneration of dental pulp after transplantation into the adult tooth. Methods Adipose tissue–derived microvascular fragments (ad-MVFs) were isolated from human adipose tissues. The apoptosis and senescence of DPSCs cultured in conditioned media were evaluated to explore the effects of ad-MVFs on DPSCs. DPSCs combined with ad-MVFs were inserted into the human tooth root segments and implanted subcutaneously into immunodeficient mice. Regenerated pulplike tissues were analyzed by hematoxylin and eosin and immunohistochemistry. The vessels in regenerated tissues were analyzed by Micro-CT and immunofluorescence. Results The isolated ad-MVFs contained endothelial cells and pericytes. ad-MVFs effectively prevented the apoptosis and senescence of the transplanted DPSCs both in vivo and in vitro. Combined with DPSCs, ad-MVFs obviously facilitated the formation of vascular networks in the transplants. DPSCs combined with ad-MVFs formed dental pulp–like tissues with abundant cells and matrix after 4 weeks of implantation. The supplementation of ad-MVFs led to more odontoblastlike cells and increased the formation of mineralized substance around the root canal. Conclusions Cotransplantation with ad-MVFs promotes the angiogenesis and revascularization of transplanted DPSC aggregates, leading to robust regeneration of dental pulp.

This paper examines the impact of large-scale alternative data on predicting consumer delinquency. Using a proprietary double-blinded test from a traditional lender, we find that the big data credit score predicts an individual’s likelihood of defaulting on a loan with 18.4% greater accuracy than the lender’s internal score. Moreover, the impact of the big data credit score is more significant when evaluating borrowers without public credit records. We also provide evidence that big data have the potential to correct financial misreporting.

With thousands of co-existing and competing platforms, the Chinese peer-to-peer (P2P) lending market experienced both high growth and high failure rate. We hand collect unique data for these P2P platforms and investigate the differences in performances and survivals for platforms with and without affiliations with state-owned enterprises (SOEs). P2P platforms with SOE affiliations have higher trading volumes, attract more investors, and offer lower interest rates. These platforms also survive significantly better than those without the SOE affiliations, especially during market downturns. Using P2P platforms with fake SOE affiliations as identification, we show that the SOE affiliation itself (not related to the fundamentals) is an important signal for P2P market participants. These results can be helpful to investors and regulators, especially those from other emerging markets.

The quick growth and fast spread of electronic word-of-mouth (eWOM) have created a new threat to Internet merchants and marketers through paid online reviewers flooding sites with product and service reviews that could confuse and deter customers. This study examined the effects of the posts by paid reviewers—specifically, the negative reviews—on consumers’ risk perception, product attitude, and purchase intention. While extant research examined negative eWOM as an information source, little attention has been paid to the role of a hired reviewer's post aimed at destroying the reputation of certain targets (Internet Water Army Attack [IWAA]). To gain a better understanding of this phenomenon, three experiments were conducted to investigate the effects of the amount, quality, and presentation order of negative eWOM on consumers’ perception change and decision making. We tested the hypothesis using a test environment that mimicked a PTT online forum ( https://www.ptt.cc/ ) in Taiwan. Three simulation cases (smartphone, digital camera, and tablet) based on real-world events were used. A total of 193 participants completed all three experiments and provided valid responses. The results of this study are mostly consistent with previous research findings that online marketing is greatly threatened by negative eWOM. Nevertheless, it was also found that the effects of the amount, quality, and presentation order of negative eWOM are more complicated than we have anticipated. The findings revealed that IWAA can effectively increase customers’ risk perception toward a product and change their attitude and purchase intention.

A large number of modern communication technologies and sensing technologies are incorporated into the smart grid, which makes its structure unique. The centralized optimized dispatch method of traditional power grids is difficult to achieve effective dispatch of smart grids. Based on the analysis of power generation plan and maintenance plan optimization model, this paper establishes a smart grid power generation and maintenance collaborative optimization model with distributed renewable energy. The objective function of this collaborative optimization problem is the operating cost of conventional units, the cost of wind power generation, and the cost of overhauling units; the constraints considered mainly include system constraints and overhaul constraints. The solution method of combinatorial optimization is analyzed, and the genetic optimization algorithm adopted in this paper is selected and discussed. According to the characteristics of the system, various loads are modeled, and power supply constraints are considered. By establishing an effective objective function, the adjustable load scheduling problem is transformed into a solvable optimal control problem. Taking into account the uncertain factors in the system, the advantage of the real-time control system is that it can realize the dynamic update scheduling of the load, so it is more in line with the requirements of the actual system. The real-time algorithm proposed in the paper is based on a distributed control strategy, which can not only realize dynamic compensation for random fluctuations in renewable energy power generation but also satisfy the load curve optimization under the premise of making full use of power supply resources. In addition, simulation experiments compare the load dispatching capabilities of the proposed algorithm with the existing algorithms, thereby verifying the performance of the proposed method.

To observe the effects of laurocapram and borneol as transdermal penetration enhancers applied to herbal cake-partitioned moxibustion on liver lipids, hormone-sensitive lipase (HSL) and hydroxymethylglutaryl CoA (HMG-CoA) reductase in hyperlipidemia rabbits. Forty New-Zealand rabbits were randomly divided into 5 groups using the random number table method, with 8 rats in each group. Rabbits in the blank group were fed routinely with a normal diet; rabbits in the other groups were fed with high-fat diet for 12 weeks to establish the hyperlipidemia model. Rabbits in the blank and the model groups were not given any intervention. After the model was prepared successfully, rabbits in the non-transdermal penetration enhancer group received herbal cake-partitioned moxibustion without transdermal penetration enhancers; rabbits in the laurocapram group and the borneol group received herbal cake-partitioned moxibustion with laurocapram or borneol respectively. After 4 weeks of treatment, the serum was isolated and enzyme-linked immunosorbent assay (ELISA) was applied for the detection of HSL and HMG-CoA reductase. The liver tissues were isolated, and total cholesterol (TC) and triglycerides (TG) were measured by enzymatic methods. One-step method was applied for high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) detection, and transmission turbidimetry was for apolipoprotein A1 (Apo-A1) and apolipoprotein B (Apo-B) detection. The serum concentrations of the drugs in the laurocapram and the borneol groups were significantly higher than those in the non-transdermal penetration enhancer group (both P

Background: Very-low-birth-weight (VLBW) infants have a high risk of postdischarge growth retardation (GR). Continued GR might exert negative long-term effects on their health. This study examined the prevalence and the risk factors for postdischarge GR among VLBW infants in Taiwan. Methods: Nationwide data from the Taiwan Premature Infant Follow-up Network between 2007 and 2011 were analyzed. Infants with a gestational age (GA)

Objective: To observe the lipid-lowering effect of different transdermal absorption enhancers applied to the herbal cake-partitioned moxibustion in hyperlipidemia model rabbits, and to explore the possible mechanism. Methods: Forty New-Zealand rabbits were randomly divided into 5 groups using the random number table method, with 8 rats in each group. Rabbits in the blank group were fed routinely with normal diet; rabbits in the other groups were fed with high-fat diet for 12 weeks to establish the hyperlipidemia model. Rabbits in the blank and the model groups were not treated. After the model was prepared, rabbits in the non-transdermal absorption enhancer group received herbal cake-partitioned moxibustion without transdermal absorption enhancer; rabbits in the laurocapram group and the borneol group received herbal cake-partitioned moxibustion with laurocapram or borneol respectively. After 4 weeks of treatment, serum was collected for enzyme-linked immunosorbent assay (ELISA), and the liver tissues were isolated for immunohistochemistry, quantitative polymerase chain reaction (qPCR) and Western-blotting (WB) detection. Results: Serum ELISA results showed that leptin was significantly decreased in the model group compared with the blank group (P 0.05). The qPCR results of rabbit liver tissues showed that the mRNA expressions of leptin, Janus kinase 2 (JAK2) and signal transducer and activator of transcription 3 (STAT3) in the model group were significantly lower than those in the blank group (all P

BackgroundComorbidity is the phenomenon of two or more diseases occurring simultaneously not by random chance and presents great challenges to accurate diagnosis and treatment. As an effort toward better understanding the genetic causes of comorbidity, in this work, we have developed a computational method to predict comorbid diseases. Two diseases sharing common genes tend to increase their comorbidity. Previous work shows that after mapping the associated genes onto the human interactome the distance between the two disease modules (subgraphs) is correlated with comorbidity.MethodsTo fully incorporate structural characteristics of interactome as features into prediction of comorbidity, our method embeds the human interactome into a high dimensional geometric space with weights assigned to the network edges and uses the projection onto different dimension to “fingerprint” disease modules. A supervised machine learning classifier is then trained to discriminate comorbid diseases versus non-comorbid diseases.ResultsIn cross-validation using a benchmark dataset of more than 10,000 disease pairs, we report that our model achieves remarkable performance of ROC score = 0.90 for comorbidity threshold at relative risk RR = 0 and 0.76 for comorbidity threshold at RR = 1, and significantly outperforms the previous method and the interactome generated by annotated data. To further incorporate prior knowledge pathways association with diseases, we weight the protein-protein interaction network edges according to their frequency of occurring in those pathways in such a way that edges with higher frequency will more likely be selected in the minimum spanning tree for geometric embedding. Such weighted embedding is shown to lead to further improvement of comorbid disease prediction.ConclusionThe work demonstrates that embedding the two-dimension planar graph of human interactome into a high dimensional geometric space allows for characterizing and capturing disease modules (subgraphs formed by the disease associated genes) from multiple perspectives, and hence provides enriched features for a supervised classifier to discriminate comorbid disease pairs from non-comorbid disease pairs more accurately than based on simply the module separation.

ObjectiveThis study aimed to develop a blood test for the prediction of pre-eclampsia (PE) early in gestation. We hypothesised that the longitudinal measurements of circulating adipokines and sphingolipids in maternal serum over the course of pregnancy could identify novel prognostic biomarkers that are predictive of impending event of PE early in gestation.Study designRetrospective discovery and longitudinal confirmation.SettingMaternity units from two US hospitals.ParticipantsSix previously published studies of placental tissue (78 PE and 95 non-PE) were compiled for genomic discovery, maternal sera from 15 women (7 non-PE and 8 PE) enrolled at ProMedDx were used for sphingolipidomic discovery, and maternal sera from 40 women (20 non-PE and 20 PE) enrolled at Stanford University were used for longitudinal observation.Outcome measuresBiomarker candidates from discovery were longitudinally confirmed and compared in parallel to the ratio of placental growth factor (PlGF) and soluble fms-like tyrosine kinase (sFlt-1) using the same cohort. The datasets were generated by enzyme-linked immunosorbent and liquid chromatography-tandem mass spectrometric assays.ResultsOur discovery integrating genomic and sphingolipidomic analysis identified leptin (Lep) and ceramide (Cer) (d18:1/25:0) as novel biomarkers for early gestational assessment of PE. Our longitudinal observation revealed a marked elevation of Lep/Cer (d18:1/25:0) ratio in maternal serum at a median of 23 weeks’ gestation among women with impending PE as compared with women with uncomplicated pregnancy. The Lep/Cer (d18:1/25:0) ratio significantly outperformed the established sFlt-1/PlGF ratio in predicting impending event of PE with superior sensitivity (85% vs 20%) and area under curve (0.92 vs 0.52) from 5 to 25 weeks of gestation.ConclusionsOur study demonstrated the longitudinal measurement of maternal Lep/Cer (d18:1/25:0) ratio allows the non-invasive assessment of PE to identify pregnancy at high risk in early gestation, outperforming the established sFlt-1/PlGF ratio test.

Background Inference of protein’s membership in metabolic pathways has become an important task in functional annotation of protein. The membership information can provide valuable context to the basic functional annotation and also aid reconstruction of incomplete pathways. Previous works have shown success of inference by using various similarity measures of gene ontology. Results In this work, we set out to explore integrating ontology and sequential information to further improve the accuracy. Specifically, we developed a neural network model with an architecture tailored to facilitate the integration of features from different sources. Furthermore, we built models that are able to perform predictions from pathway-centric or protein-centric perspectives. We tested the classifiers using 5-fold cross validation for all metabolic pathways reported in KEGG database. Conclusions The testing results demonstrate that by integrating ontology and sequential information with a tailored architecture our deep neural network method outperforms the existing methods significantly in the pathway-centric mode, and in the protein-centric mode, our method either outperforms or performs comparably with a suite of existing GO term based semantic similarity methods.

Background To estimate the prevalence of elevated blood glucose level (EBG, including type 2 diabetes mellitus and impaired fasting glucose), and its association with non-valvular atrial fibrillation (NVAF) in Guangzhou, China. Methods The population-based follow-up Guangzhou Heart Study collected baseline data from July 2015 to August 2017 among 12,013 permanent residents aged > 35 from 4 Guangzhou districts. Two streets (Dadong and Baiyun) in the Yuexiu District, and one street (Xiaoguwei) and two towns (Xinzao and Nancun) in the Panyu District were chosen as representative of urban and rural areas, respectively. Each participant completed a comprehensive questionnaire, and underwent physical examination, blood sample collection for laboratory testing, electrocardiography, and other evaluations. Multivariable logistic regression analyses were used to estimate the independent association between hyperglycemia and NVAF prevalence. Results The prevalence of EBG in overall study population was 29.9%. Compared with residents without EBG, the odds ratio (OR) for AF among residents with EBG was significantly higher (1.94, 95% confidence interval [CI]: 1.40–2.70, P P = 0.007), and driven by women (OR = 1.80, 95% CI: 1.12–2.91, P = 0.016). Conclusions In Guangzhou, China, prevalence of EBG is high among residents aged > 35 years and associated with a multivariate adjusted increase in prevalence of NVAF overall and in women.

Background Growing evidence indicates that high phosphoserine phosphatase (PSPH) expression is associated with tumor prognosis in many types of cancers. However, the role of PSPH in non-small cell lung cancer (NSCLC) is unclear. The purpose of this study was to investigate the clinical significance of PSPH in NSCLC. Methods One hundred forty-three patients with histologically confirmed NSCLC who underwent surgery were included. Quantitative real-time PCR and Western blot were used to assess PSPH expression in paired tumor and corresponding adjacent non-tumorous tissues. The role of PSPH in invasion and cell growth was investigated in vitro. Results Compared to adjacent normal lung tissues, PSPH messenger RNA and protein levels were significantly higher in NSCLC tissues, and the PSPH expression level was positively related to clinical stage, metastasis, and recurrence. High PSPH expression was predictive of poor overall survival. A549 cells transfected with small interfering-PSPH showed inhibited cell migration, invasion, and proliferation. We further demonstrated that PSPH might promote the invasive capabilities of NSCLC cells through the AKT/AMPK signaling pathway. Conclusion Our results indicate that PSPH may act as a putative oncogene in NSCLC, and may be a vital molecular marker for the metastasis and proliferation of NSCLC cells by regulating the AKT/AMPK signaling pathway.

The pathogenesis of rhegmatogenous retinal detachment depends on three factors, namely, retinal rupture, vitreous liquefaction and traction causing the retina to separate from the pigment epithelium, among which retinal rupture is the most important. Retinopathy is caused by a gap between the neurosensory retina and the retinal pigment epithelium, which severely damages the visual function of the patient. Therefore, early clinical discovery, prevention and selection of an appropriate treatment are important. This article reviews progress in the treatment of retinal detachment.

Epidermal growth factor receptor (EGFR) mutations are associated with leptomeningeal metastases (LM) of nonsmall cell lung cancer and sensitivity to tyrosine kinase inhibitor (TKI) treatment. Owing to the difficulty of obtaining carcinomatous meningeal tissue for analysis, cerebrospinal fluid (CSF) might be an alternative.To investigate the EGFR mutation detection in the CSF of lung adenocarcinoma patients with LM.Twenty-five lung adenocarcinoma patients with LM diagnosed by CSF cytology were retrospectively evaluated. The results of EGFR mutation detection in CSF, the treatment plan, and clinical outcome information were recorded.Nineteen patients had a known EGFR status in their primary tumors. Twenty patients received EGFR mutation analysis in CSF after LM diagnosis and 14 of them with a known EGFR mutation status of both primary tumors and CSF. Ten (71.4%) had the same EGFR gene status. In primary tumors, no T790M mutations were detected, whereas in CSF, 2 L858R cases and 1 19del case had T790M mutations at the same time. The detection rate of T790M mutations in CSF was 18.1% (2 of 11) in all cases with EGFR-sensitive mutations in the primary lesion.EGFR mutation detection in CSF of lung adenocarcinoma patients with LM might be an alternative when leptomeningeal biopsy cannot be applied and may help to guide TKI treatments.

Therapeutic guidance in non-small cell lung cancer (NSCLC) tumors that are positive for anaplastic lymphoma kinase (ALK) fluorescent in situ hybridization (FISH), but negative for ALK immunohistochemistry, is still challenging. Parallel routine screening of 4588 NSCLC cases identified 22 discordant cases. We rechecked these samples using ALK antibodies and selected reaction monitoring (SRM) quantitative multiplexed proteomics screening multiple protein targets, including ALK and MET for the ALK tyrosine kinase inhibitor (TKI), and FR-alpha, hENT1, RRM1, TUBB3, ERCC1, and XRCC1 for chemotherapy. The presence of ALK (31.8%), MET (36.4%), FR-alpha (72.7%), hENT1 (18.2%), RRM1 (31.8%), TUBB3 (72.9%), ERCC1 (4.5%), and a low level of XRCC1 (54.4%) correlated with clinical outcomes. SRM was more sensitive than the ALK D5F3 assay. Among the eight cases receiving ALK TKI, four cases with ALK or MET detected by SRM had complete or partial responses, whereas four cases without ALK or MET showed progression. Twenty-seven treatment outcomes from 20 cases were assessed and cases expressing more than half of the specific predictive proteins were sensitive to matching therapeutic agents and showed longer progression-free survival than the other cases (p &lt, 0.001). SRM showed a potential role in therapeutic decision making in NSCLC patients with ambiguous ALK test results.

AIM: To describe the clinical features of acute myopic onset of optic neuropathy and observe the effects of retrobulbar and systemic glucocorticoid therapy in a real-world setting. METHODS: A retrospective observational case series included 18 patients with a clinical diagnosis of acute onset of myopic optic neuropathy in a real-world setting. While the patients were using retrobulbar and systemic glucocorticoid therapy, various imaging examination data were analysed, and the clinical features of myopic optic neuropathy were summarized for 6mo to 2y. RESULTS: The included group of patients with acute onset of myopic optic neuropathy consisted mostly of females (n=11). The visual field (VF) showed abnormalities in bilateral eyes, including the spread of physiological blind spots, central and paracentral dark spots, and centripetal peripheral VF reduction; but central vision with no subjective changes. The visual evoked potential (VEP) was abnormal in all eyes with vision loss. The best corrected visual acuity (BCVA) was improved from 1.04±0.63 to 0.47±0.57 (logMAR) after glucocorticoid treatment (P0.05). There was no recurrence during long-term follow-up observation. CONCLUSION: The acute onset of myopic optic neuropathy is characterized by BCVA and VF abnormalities in bilateral eyes. Retrobulbar and systemic glucocorticoid therapy is effective.

Quercetin is the major representative of the flavonoid subgroup of flavones, with good pharmacological activities for the treatment of liver diseases, including liver steatosis, fatty hepatitis, liver fibrosis, and liver cancer. It can significantly influence the development of liver diseases via multiple targets and multiple pathways via antifat accumulation, anti-inflammatory, and antioxidant activity, as well as the inhibition of cellular apoptosis and proliferation. Despite extensive research on understanding the mechanism of quercetin in the treatment of liver diseases, there are still no targeted therapies available. Thus, we have comprehensively searched and summarized the different targets of quercetin in different stages of liver diseases and concluded that quercetin inhibited inflammation of the liver mainly through NF-κB/TLR/NLRP3, reduced PI3K/Nrf2-mediated oxidative stress, mTOR activation in autophagy, and inhibited the expression of apoptotic factors associated with the development of liver diseases. In addition, quercetin showed different mechanisms of action at different stages of liver diseases, including the regulation of PPAR, UCP, and PLIN2-related factors via brown fat activation in liver steatosis. The compound inhibited stromal ECM deposition at the liver fibrosis stage, affecting TGF1β, endoplasmic reticulum stress (ERs), and apoptosis. While at the final liver cancer stage, inhibiting cancer cell proliferation and spread via the hTERT, MEK1/ERK1/2, Notch, and Wnt/β-catenin-related signaling pathways. In conclusion, quercetin is an effective liver protectant. We hope to explore the pathogenesis of quercetin in different stages of liver diseases through the review, so as to provide more accurate targets and theoretical basis for further research of quercetin in the treatment of liver diseases.

Background: Vascular endothelial growth factor (VEGF) is a supergene family derived from a platelet growth factor. It plays a pivotal role in regulating angiogenesis and lymphangiogenesis. sFlt-1 is a soluble antagonist of VEGF with an essential effect of maintaining the balance of vascular growth. Recently, sFlt-1 has emerged as a new marker for early diagnosis and disease surveillance of angiogenesis-related diseases. However, few comprehensive reviews focus on the relationship between sFlt-1 and related diseases despite that many results have yielded. Methods: In this review, we analyzed the relationship between sFlt-1 and angiogenesis-related diseases by searching PubMed, Web of Science, and other databases, and summarized our current understanding of the role of sFlt-1 in angiogenesis-related diseases. Results: sFlt-1 is associated with pre-eclampsia, perinatal cardiomyopathy, diabetic nephropathy, hypertension, tumor, atherosclerosis, and other diseases. The mechanisms of sFlt-1 that regulate those diseases are mainly associated with the bioavailability of VEGF and vascular endothelial cell integrity. Conclusion: From the summary article, sFlt-1 is a double regulator in angiogenesis-related diseases; too much or too little may cause different diseases. Therefore, maintaining the stability of sFlt-1 content in the body is essential to control the development of related diseases.

Objective To evaluate whether longitudinal measurements of serological adipokines and sphingolipids can predict preeclampsia early in gestation. Design Retrospective multi-omics discovery and longitudinal validation. Setting Maternity units in two US hospitals. Methods A multi-omics approach integrating genomic and lipidomic discoveries was employed to identify leptin (Lep) and ceramide (Cer) as novel PE early gestational biomarkers. The levels of placental growth factor (PlGF), soluble fms-like tyrosine kinase (sFlt-1), Lep, and Cer in maternal sera were then determined by enzyme-linked immunosorbent and liquid chromatography-tandem mass spectrometric assays. Main outcome measures Interval from positive prediction to confirmative diagnosis. Results Genomic meta-analysis compiled six PE placental cohorts with 78 PE and 95 non-PE control placentas. The Testing Cohort included sera from 7 non-PE and 8 PE women collected at confirmatory diagnosis. The Validation Cohort included sera from 20 non-PE and 20 PE women collected longitudinally through gestation. Our findings revealed a marked elevation of maternal serum Leptin/Ceramide (d18:1/25:0) ratio from early gestation (a median of 23 weeks) when comparing later PE-complicated with uncomplicated pregnancies. The maternal Lep/Cer (d18:1/25:0) ratio significantly outperformed the established sFlt-1/PlGF ratio in predicting PE for sensitivity (85% vs. 40%), positive predictive value (89% vs. 42%), and AUC (0.92 vs. 0.52) from 5 to 25 weeks of gestation. Conclusions Non-invasive longitudinal assessment by serological evaluation of Lep/Cer (d18:1/25:0) ratio can case find early pregnancies at risk of preeclampsia, outperforming sFlt-1/PlGF ratio test. Tweetable abstract Non-invasive longitudinal assessment by serological evaluation of Lep and Cer ratio can predict preeclampsia early in gestation.

Background. Solute carrier family 12 member 5 (SLC12A5) has been reported to play an oncogenic role in certain malignancies. Its prognostic roles and immune mechanisms of action in human cancers, however, remain largely unknown. Methods. Data derived from TCGA, GEPIA, and TIMER databases were utilized to delve into the expressing patterns, prognostic values, clinical significances, and tumor immunity of SLC12A5 in tumors. Additionally, the association of SLC12A5 expressions with tumor mutation burden (TMB), methyltransferases, and mismatch repairs (MMRs) was also analyzed. Results. Herein, we observed that SLC12A5 was significantly overexpressed in various malignancies, and SLC12A5 levels correlated with overall survival, disease-specific survival, and tumor stage of certain cancers. Furthermore, we noticed that SLC12A5 was distinctly associated with methyltransferases, mismatch repair proteins, TMB, and MSI in human cancers. Conclusions. SLC12A5 may act as a potential prognostic and immunological biomarker and therapeutic target for human cancers.

We study the behavior of an individual avoiding peer information on charity giving. Manipulating how the peer donation information was revealed to potential donors in a field experiment, we find 89% of individuals were “information avoiders.” We further use an instrumental variable estimation strategy to show that, given the option to avoid the information, these individuals were less likely to give and to help promote charity campaigns, which reduced the total distribution of campaigns on the platform by 8.5% and the total donation amount by 7.7%. Finally, we use a theoretical model to illustrate how the pressure from peer comparison may drive the findings.

Ultrasound-guided perineural dextrose injection (PDI) has been reported effective for carpal tunnel syndrome (CTS). Higher volume of injectate may reduce adhesion of median nerve from other tissues, but volume-dependent effects of PDI in CTS remain unknown. We aimed to investigate whether PDI with different injectate volumes had different effects for CTS participants. In this randomized, double-blinded, three-arm trial, 63 wrists diagnosed with CTS were randomized into three groups that received ultrasound-guided PDI with either 1, 2 or 4 ml of 5% dextrose water. All participants finished this study. Primary outcome as visual analog scale (VAS) and secondary outcomes including Boston Carpal Tunnel Questionnaire (BCTQ), Disability of the Arm, Shoulder and Hand score (QuickDASH), electrophysiological studies and cross-sectional area (CSA) of the median nerve at carpal tunnel inlet were assessed before and after PDI at the 1st, 4th, 12th and 24th weeks. For within-group analysis, all three groups (21 participants, each) revealed significant improvement from baseline in VAS, BCTQ and QuickDASH at the 1st, 4th, 12th and 24th weeks. For between-group analysis, 4 ml-group yielded better VAS reduction at the 4th and 12th weeks as well as improvement of BCTQ and QuickDASH at the 1st, 4th, and 12th weeks, compared to other groups. No significant between-group differences were observed in electrophysiological studies or median nerve CSA at any follow-up time points. There were no severe complications in this trial, and transient minor adverse effects occurred equally in the three groups. In conclusion, ultrasound-guided PDI with 4 ml of 5% dextrose provided better efficacy than with 1 and 2 ml based on symptom relief and functional improvement for CTS at the 1st, 4th, and 12th week post-injection, with no reports of severe adverse effects. There was no significant difference between the three groups at the 24th-week post-injection follow-up.Clinical Trial Registration:www.ClinicalTrials.gov, identifier NCT03598322.

Aiming at the problem of the lack of power load data in the forecasting of the delivery capacity of the sending end area and the load level forecasting of the receiving end during the clean energy delivery in the southwestern region, this paper gives the power load data recovery from the perspective of time series data characteristic analysis and modeling and estimation method. Based on the analysis of the multi-scale time series characteristics of the annual, monthly, and daily fluctuations of the electric load, the multi-scale time series characteristic modeling of the electric load is established. Spline interpolation is introduced to solve the non-parametric and variable coefficient problems of the load model, and the estimation method of the key parameters in the load model is given. According to the obtained load recovery model, a recovery method for missing data of weekly power load is proposed, and the idea of recovering daily load data is given. The actual calculation examples prove that the method proposed in this paper is accurate and effective.

Using data from a major online peer-to-peer lending platform, we document that, due to time pressure, investors appear to focus on interest rates and only partially account for credit ratings in their decisions. The effect is stronger for mobile-based investors than for PC-based ones. Our evidence suggests that this variation is caused by the difference in information content on the interfaces rather than differences in the devices’ physical attributes per se. Investors improve their decisions by slowing down and paying more attention to credit ratings after experiencing a loan default firsthand, but not after observing others experiencing defaults.

API recommendation is a promising approach which is widely used during software development. However, the evaluation of API recommendation is not explored with sufficient rigor. The current evaluation of API recommendation mainly focuses on correctness, the measurement is conducted by matching recommended results with ground-truth results. In most cases, there is only one set of ground-truth APIs for each recommendation attempt, but the object code can be implemented in dozens of ways. The neglect of code diversity results in a possible defect in the evaluation. To address the problem, we invite 15 developers to analyze the unmatched results in a user study. The online evaluation confirms that some unmatched APIs can also benefit to programming due to the functional correlation with ground-truth APIs. Then we measure the API functional correlation based on the relationships extracted from API knowledge graph, API method name, and API documentation. Furthermore, we propose an approach to improve the measurement of correctness based on API functional correlation. Our measurement is evaluated on a dataset of 6141 requirements and historical code fragments from related commits. The results show that 28.2% of unmatched APIs can contribute to correctness in our experiments.

Data clustering, as one of the major algorithms in facial feature data mining, its efficiency and quality plays a key role. DBSCAN is a classic density-based clustering algorithm. It is applicable to any shape of subset or cluster and is comparatively anti-noise, but because of its slow running speed, it has long convergence time when the data set is large. For this reason, the paper presents an improved DBSCAN algorithm based on distributed computing system, by making full use of the characteristic of high time partial similarity of facial feature under the monitoring scene, first to merge the features which belong to the same target, then to segment the merged result using DBSCAN algorithm. The test results show that although this new algorithm has no modification in the aspect of time complexity, but greatly improved clustering speed, which enables the system to process million-level datasets.

Amplification of and oncogenic mutations in ERBB2, the gene encoding the HER2 receptor tyrosine kinase, promote receptor hyperactivation and tumor growth. Here we demonstrate that HER2 ubiquitination and internalization, rather than its overexpression, are key mechanisms underlying endocytosis and consequent efficacy of the anti-HER2 antibody–drug conjugates (ADC) ado-trastuzumab emtansine (T-DM1) and trastuzumab deruxtecan (T-DXd) in lung cancer cell lines and patient-derived xenograft models. These data translated into a 51% response rate in a clinical trial of T-DM1 in 49 patients with ERBB2-amplified or -mutant lung cancers. We show that cotreatment with irreversible pan-HER inhibitors enhances receptor ubiquitination and consequent ADC internalization and efficacy. We also demonstrate that ADC switching to T-DXd, which harbors a different cytotoxic payload, achieves durable responses in a patient with lung cancer and corresponding xenograft model developing resistance to T-DM1. Our findings may help guide future clinical trials and expand the field of ADC as cancer therapy.Significance:T-DM1 is clinically effective in lung cancers with amplification of or mutations in ERBB2. This activity is enhanced by cotreatment with irreversible pan-HER inhibitors, or ADC switching to T-DXd. These results may help address unmet needs of patients with HER2-activated tumors and no approved targeted therapy.See related commentary by Rolfo and Russo, p. 643.This article is highlighted in the In This Issue feature, p. 627

Most patients with KRASG12C–mutant non–small cell lung cancer (NSCLC) experience clinical benefit from selective KRASG12C inhibition, whereas patients with colorectal cancer bearing the same mutation rarely respond. To investigate the cause of the limited efficacy of KRASG12C inhibitors in colorectal cancer, we examined the effects of AMG510 in KRASG12C colorectal cancer cell lines. Unlike NSCLC cell lines, KRASG12C colorectal cancer models have high basal receptor tyrosine kinase (RTK) activation and are responsive to growth factor stimulation. In colorectal cancer lines, KRASG12C inhibition induces higher phospho-ERK rebound than in NSCLC cells. Although upstream activation of several RTKs interferes with KRASG12C blockade, we identify EGFR signaling as the dominant mechanism of colorectal cancer resistance to KRASG12C inhibitors. The combinatorial targeting of EGFR and KRASG12C is highly effective in colorectal cancer cells and patient-derived organoids and xenografts, suggesting a novel therapeutic strategy to treat patients with KRASG12C colorectal cancer. Significance: The efficacy of KRASG12C inhibitors in NSCLC and colorectal cancer is lineage-specific. RTK dependency and signaling rebound kinetics are responsible for sensitivity or resistance to KRASG12C inhibition in colorectal cancer. EGFR and KRASG12C should be concomitantly inhibited to overcome resistance to KRASG12C blockade in colorectal tumors. See related commentary by Koleilat and Kwong, p. 1094. This article is highlighted in the In This Issue feature, p. 1079

Background. Chinese oral herbal paste has been widely used in the treatment of chronic obstructive pulmonary disease (COPD). However, the treatment effects of herbal paste were controversial and lack evidence to support its clinical use. This study aims to systematically assess the efficacy and safety of Chinese oral herbal paste for the treatment of stable COPD. Methods. PubMed, Web of Science, CENTRAL, EMBASE, CNKI, VIP, CBM, and WANFANG database in addition to two websites of clinical trial registry were searched from respective inception to August 2019. Only randomized controlled trials (RCTs) studying Chinese herbal paste for the treatment of stable COPD were included. Methodological quality was assessed based on Cochrane risk of bias and GRADE approach. Data were analyzed using RevMan 5.3. Results. A total of 19 RCTs with 1303 individuals compared Chinese oral herbal paste and Western medicine (WM) with WM alone were included for meta-analysis. The review showed compared with WM alone, the combination of herbal paste and WM reduced exacerbation frequency. Subgroup analyses showed that after two to three months of treatment, compared with WM alone, Chinese herbal paste plus WM significantly decreased the St George’s Respiratory Questionnaire (SGRQ) scores, COPD assessment test (CAT) scores, and scores of traditional Chinese medicine (TCM) syndrome, and improved clinical effective rates, lung function, and 6-minute walk distance. No serious adverse events related to herbal paste were reported. Conclusion. Current evidence showed that Chinese oral herbal paste may be an effective and well-tolerated adjuvant therapy for stable COPD. Considering the risks of bias and heterogeneity, more high-quality, well-designed RCTs are still needed.

We probe the effects of the COVID-19 pandemic and the subsequent containment policies on business activities in China by exploiting big data on 1.5 billion sales invoices. Using a difference-in-differences approach, we estimate that the average drop in sales is between 23% and 35%, depending on firm size, for the 12-week period after Wuhan's lockdown. The unprecedented plunge in countrywide economic activities is more evident in the first eight weeks, and firm sales gradually resume to 85% of the normal level afterward. Firms in industries requiring more intensive face-to-face interactions suffer more during the public health measures. Also, cities relying on investment-driven economic growth are more resilient. Lastly, local governments' economic stimulus policies, aimed at alleviating financial losses for small and micro firms, are actually more effective for medium-sized and large firms. Our results provide implications for other economies seeking to develop strategies to contain the disease and reopen the economy.

Natural Language Processing (NLP) library is widely used while analyzing software documents. The numerous toolkits result in a problem on NLP library selection. The selection of NLP library in current work commonly misses some objective reasons, which may pose threats to validity. And it is also not clear that whether the existing guideline on selection still works for the latest versions. In this work, we propose a solution for NLP library selection when the effectiveness is unknown. We use the NLP libraries together in a combined method. Our combined method can utilize the strengths of different NLP libraries to obtain accurate results. The combination is conducted through two steps, i.e., document-level selection of NLP library and sentence-level overwriting. In document-level selection of primary library, the results are obtained from the library that has the highest overall accuracy. Through sentence-level overwriting, the possible fine-gained improvements from other libraries are extracted to overwrite the outputs of primary library. We evaluate the combined method with 4 widely used NLP libraries and 200 documents from 3 different sources. The results show that the combined method can generally outperform all the studied NLP libraries in terms of accuracy. The finding means that our combined method can be used instead of individual NLP library for more effective results.

Objective To perform a meta-analysis to quantitatively assess functional magnetic resonance imaging (MRI) in the diagnosis of locally recurrent prostate cancer. Materials and methods A comprehensive search of the PubMed, Embase, Cochrane Central Register of Controlled Trials, and Cochrane Database of Systematic Reviews was conducted from January 1, 1995 to December 31, 2016. Diagnostic accuracy was quantitatively pooled for all studies by using hierarchical logistic regression modeling, including bivariate modeling and hierarchical summary receiver operating characteristic (HSROC) curves (AUCs). The Z test was used to determine whether adding functional MRI to T2-weighted imaging (T2WI) results in significantly increased diagnostic sensitivity and specificity. Results Meta-analysis of 13 studies involving 826 patients who underwent radical prostatectomy showed a pooled sensitivity and specificity of 91%, and the AUC was 0.96. Meta-analysis of 7 studies involving 329 patients who underwent radiotherapy showed a pooled sensitivity of 80% and specificity of 81%, and the AUC was 0.88. Meta-analysis of 11 studies reporting 1669 sextant biopsies from patients who underwent radiotherapy showed a pooled sensitivity of 54% and specificity of 91%, and the AUC was 0.85. Sensitivity after radiotherapy was significantly higher when diffusion-weighted MRI data were combined with T2WI than when only T2WI results were used. This was true when meta-analysis was performed on a per-patient basis (p = 0.027) or per sextant biopsy (p = 0.046). A similar result was found when 1H-magnetic resonance spectroscopy (1H-MRS) data were combined with T2WI and sextant biopsy was the unit of analysis (p = 0.036). Conclusion Functional MRI data may not strengthen the ability of T2WI to detect locally recurrent prostate cancer in patients who have undergone radical prostatectomy. By contrast, diffusion-weight MRI and 1H-MRS data may improve the sensitivity of T2WI for patients who have undergone radiotherapy.

Background and Aims Esophageal stricture is a common adverse event after endoscopic submucosal dissection (ESD) when it involves the entire circumference of the esophagus. We aimed to assess the effectiveness and safety of endoscopic transplantation of autologous esophageal mucosa in preventing stricture formation after circumferential ESD. Methods Nine patients who underwent circumferential ESD for early esophageal cancer were enrolled. After the patients underwent ESD, autologous esophageal mucosal patches were attached to the ulcer surface by using hemoclips and were then fixed with a covered metal mesh stent. The stent was removed 7 days after the procedure. The patients were followed up with endoscopy at scheduled times. Results Epithelialization occurred within a median of 7.1 days, with a graft survival rate of 96.5%. Strictures occurred at a mean of 24.7 days (range 18-34 days) after the procedure. The median number of endoscopic balloon dilatation sessions was 2.7 (range 0-6). Conclusions Transplantation of autologous esophageal mucosa could be a safe way of relieving the severity of esophageal stricture after circumferential ESD.

Background and purpose We hypothesized that a plan’s robustness to anatomical changes can be improved by optimizing with multiple CT scans of a patient. The purpose of this study was to determine whether an intensity modulated proton therapy (IMPT) plan could be developed to meet dose criteria on both planning and adaptive CT plans. Material and methods Eight lung cancer patients who underwent adaptive IMPT were retrospectively selected. Each patient had two CTs: a primary planning CT (PCT) and an adaptive planning CT (ACT), and IMPT plans associated with the scans. PCT and ACT were then used in combination to optimize one plan (MCT plan). The doses to the target and organs at risk from the PCT plan, ACT plan, P-ACT plan (PCT plan calculated on ACT data), and MCT plans calculated on both CTs were compared. Results The MCT plan maintained the D 95% on both CTs (mean, 65.99 Gy on PCT and 66.02 Gy on ACT). Target dose coverage on ACT was significantly better with the MCT plan than with the P-ACT plan ( p = 0.01). MCT plans had slightly higher lung V 20 (0.6%, p = 0.02) than did PCT plans. The various plans showed no statistically significant difference in heart and spinal cord dose. Conclusions The results of this study indicate that an IMPT plan can meet the dose criteria on both PCT and ACT, and that MCT optimization can improve the plan’s robustness to anatomical change.

Ke-Li Liao,1 Song Huang,1 Yu-Peng Wu2 1Department of Neurosurgery, ZigongFirst People’s Hospital, Zigong, Sichuan, People’s Republic of China; 2Department of Neurosurgery, TheSecond Hospital of Hebei MedicalUniversity, Shijiazhuang, Hebei, People’s Republic of China Background: A combination of temozolomide (TMZ) and radiotherapy and subsequent adjuvant chemotherapy is the gold standard of treatment for glioblastoma (GB). Bevacizumab (BEV), a humanized monoclonal antibody that blocks the effects of vascular endothelial growth factor A, has produced impressive response rates for recurrent GB and has been approved as second-line therapy. The efficacy and safety of BEV in newly diagnosed GB are not known. Aim: This systematic meta-analysis was undertaken to evaluate the value of combination therapy involving BEV in newly diagnosed GB. Methods: Electronic databases were searched for eligible literature up to October 2017. Randomized controlled trials assessing the efficacy and safety of BEV in patients with newly diagnosed GB were included, of which the main outcomes were progression-free survival (PFS), overall survival (OS), and adverse events (AEs). All the data were pooled with the corresponding 95% confidence intervals (CIs) using RevMan software. Sensitivity analyses and heterogeneity were quantitatively evaluated. Results: A total of six randomized controlled trials were included in this analysis. The experimental BEV group had significantly improved the overall PFS (OR =0.46, 95% CI =0.26–0.81, P=0.007), as well as PFS at 6months (OR =3.47, 95% CI =2.85–4.22, P

Background Protein-protein interaction (PPI) prediction remains a central task in systems biology to achieve a better and holistic understanding of cellular and intracellular processes. Recently, an increasing number of computational methods have shifted from pair-wise prediction to network level prediction. Many of the existing network level methods predict PPIs under the assumption that the training network should be connected. However, this assumption greatly affects the prediction power and limits the application area because the current golden standard PPI networks are usually very sparse and disconnected. Therefore, how to effectively predict PPIs based on a training network that is sparse and disconnected remains a challenge. Results In this work, we developed a novel PPI prediction method based on deep learning neural network and regularized Laplacian kernel. We use a neural network with an autoencoder-like architecture to implicitly simulate the evolutionary processes of a PPI network. Neurons of the output layer correspond to proteins and are labeled with values (1 for interaction and 0 for otherwise) from the adjacency matrix of a sparse disconnected training PPI network. Unlike autoencoder, neurons at the input layer are given all zero input, reflecting an assumption of no a priori knowledge about PPIs, and hidden layers of smaller sizes mimic ancient interactome at different times during evolution. After the training step, an evolved PPI network whose rows are outputs of the neural network can be obtained. We then predict PPIs by applying the regularized Laplacian kernel to the transition matrix that is built upon the evolved PPI network. The results from cross-validation experiments show that the PPI prediction accuracies for yeast data and human data measured as AUC are increased by up to 8.4 and 14.9% respectively, as compared to the baseline. Moreover, the evolved PPI network can also help us leverage complementary information from the disconnected training network and multiple heterogeneous data sources. Tested by the yeast data with six heterogeneous feature kernels, the results show our method can further improve the prediction performance by up to 2%, which is very close to an upper bound that is obtained by an Approximate Bayesian Computation based sampling method. Conclusions The proposed evolution deep neural network, coupled with regularized Laplacian kernel, is an effective tool in completing sparse and disconnected PPI networks and in facilitating integration of heterogeneous data sources.

// Junbao Wei 1, * , Hengzong Zhu 2, * and Xiaoli Liao 3 1 Department of Therapeutic Radiology, Guangxi Autonomous Regional Cancer Hospital & Cancer Hospital of Guangxi Medical University, Nanning, 530021, China 2 Department of General Medicine, Longan Hospital of Traditional Chinese Medicine, Nanning, 532700, China 3 The Oncology Department, Guangxi Autonomous Regional Cancer Hospital & Cancer Hospital of Guangxi Medical University, Nanning, 530021, China * These authors contributed equally to this work Correspondence to: Xiaoli Liao, email: 121021866@qq.com Keywords: prostate cancer; recurrence; choline PET/CT; PSA; meta-analysis Received: July 27, 2017 Accepted: December 13, 2017 Epub: January 24, 2018 Published: March 06, 2018 ABSTRACT Purpose: To assess the relationship between the diagnostic accuracy of Choline positron emission tomography/computed tomography (PET/CT) and the trigger prostate-specific antigen (PSA) level in patients with a biochemical recurrence of prostate cancer. Materials and Methods: A meta-analysis was conducted to synthesize data across multiple studies. Results: The pooled sensitivity and specificity of choline PET/CT were 82% (95% Confidence Interval (CI):80–84%) and 92% (95%CI: 90–93%), respectively. The pooled sensitivity and specificity of 18 F-choline PET/CT were 81% (95%CI: 78–84%) and 90% (95%CI: 85–93%), respectively. The pooled sensitivity and specificity of 11 C-choline PET/CT were 83% (95% CI: 80–86%) and 92% (95% CI: 90–94%), respectively. The pooled detection rate of 18 F-choline PET/CT and 11 C-choline PET/CT were 58% (95% CI: 48–68%) and 58% (95%CI: 49–68%), respectively. Conclusions: Trigger PSA is an important risk factor for positive findings of Choline PET/CT and the detection rate of Choline PET/CT for recurrent prostate cancer increased in parallel with raises in PSA-values. Choline PET/CT got higher detection rate while the trigger PSA > 2ng/ml.

Bone marrow-derived mesenchymal stem cell (BMSC) cytotherapy has emerged as a promising treatment strategy for refractory immune diseases; however, the influence of the pathologic conditions of donors on the immunomodulatory properties of BMSCs is still poorly understand. Here, we found that BMSCs that were derived from donors with osteoporosis were ineffective as cytotherapy for patients with experimental colitis and graft- vs.-host disease (GVHD). In vivo and in vitro assays revealed that the capacity of osteoporotic BMSCs to induce T-cell apoptosis declined as a result of decreased Fas and FasL protein. Additional analysis revealed that let-7a, a microRNA induced by TNF-α in osteoporosis, inhibited the expression of the Fas/FasL system via post-transcriptional regulation. By knocking down let-7a expression, we successfully recovered the immunosuppressive capacity of osteoporotic BMSCs and improved their therapy for experimental colitis and GVHD. Taken together, our study demonstrates that the immunomodulatory properties of BMSCs are suppressed in osteoporosis and illustrates the molecular mechanism that underlies this suppression. These findings might have important implications for the development of targeted strategies to improve BMSC cytotherapy.-Liao, L., Yu, Y., Shao, B., Su, X., Wang, H., Kuang, H., Jing, H., Shuai, Y., Yang, D., Jin, Y. Redundant let-7a suppresses the immunomodulatory properties of BMSCs by inhibiting the Fas/FasL system in osteoporosis.

This paper provides a thorough literature review of current state-of-the-art systems analysis techniques for urban solid waste collection and identifies four intrinsic deficiencies of the existing studies over different types of cities. As a demonstration, a multiconstrained and multicompartment routing problem is modeled with roll-on roll-off scheduling strategies in a two-stage decision-making process to exhibit the highest complexity of its kind in practical implementation. The constraints of time windows, intermediate facilities, multishifts, and split deliveries make an ideal combination of all essential complexities in modeling practices. To overcome the relevant challenges, a unified heuristic algorithm is proposed for addressing node routing and roll-on roll-off routing problems. The proposed heuristic algorithm that concatenates initialization and improvement phases solves the models with numerical efficiency to search for the most cost-effective and environmentally benign solutions. Results indicate that differentiated collection increases opportunities to pursue the best routing strategies with sustainable implications through sensitivity analysis at the expense of higher collection costs. The analysis concludes with the perspectives of a smart and green waste collection system designed to create a more sustainable waste management systems in the future.