A xenogeneic extracellular matrix-based 3D printing scaffold modified by ceria nanoparticles for craniomaxillofacial hard tissue regeneration via osteo-immunomodulation.

Hard tissue engineering scaffolds especially 3D printed scaffolds were considered an excellent strategy for craniomaxillofacial hard tissue regeneration, involving crania and facial bones and teeth. Porcine treated dentin matrix (pTDM) as xenogeneic extracellular matrix has the potential to promote the stem cell differentiation and mineralization as it contains plenty of bioactive factors similar with human-derived dentin tissue. However, its application might be impeded by the foreign body response induced by the damage-associated molecular patterns of pTDM, which would cause strong inflammation and hinder the regeneration. Ceria nanoparticles (CNPs) show a great promise at protecting tissue from oxidative stress and influence the macrophages polarization. Using 3D-bioprinting technology, we fabricated a xenogeneic hard tissue scaffold based on pTDM xenogeneic TDM-polycaprolactone (xTDM/PCL) and we modified the scaffolds by CNPs (xTDM/PCL/CNPs). Through series ofin vitroverification, we found xTDM/PCL/CNPs scaffolds held promise at up-regulating the expression of osteogenesis and odontogenesis related genes including collagen type 1, Runt-related transcription factor 2 (RUNX2), bone morphogenetic protein-2, osteoprotegerin, alkaline phosphatase (ALP) and DMP1 and inducing macrophages to polarize to M2 phenotype. Regeneration of bone tissues was further evaluated in rats by conducting the models of mandibular and skull bone defects. Thein vivoevaluation showed that xTDM/PCL/CNPs scaffolds could promote the bone tissue regeneration by up-regulating the expression of osteogenic genes involving ALP, RUNX2 and bone sialoprotein 2 and macrophage polarization into M2. Regeneration of teeth evaluated on beagles demonstrated that xTDM/PCL/CNPs scaffolds expedited the calcification inside the scaffolds and helped form periodontal ligament-like tissues surrounding the scaffolds.

A scoping review of fair machine learning techniques when using real-world data.

OBJECTIVE: The integration of artificial intelligence (AI) and machine learning (ML) in health care to aid clinical decisions is widespread. However, as AI and ML take important roles in health care, there are concerns about AI and ML associated fairness and bias. That is, an AI tool may have a disparate impact, with its benefits and drawbacks unevenly distributed across societal strata and subpopulations, potentially exacerbating existing health inequities. Thus, the objectives of this scoping review were to summarize existing literature and identify gaps in the topic of tackling algorithmic bias and optimizing fairness in AI/ML models using real-world data (RWD) in health care domains. METHODS: We conducted a thorough review of techniques for assessing and optimizing AI/ML model fairness in health care when using RWD in health care domains. The focus lies on appraising different quantification metrics for accessing fairness, publicly accessible datasets for ML fairness research, and bias mitigation approaches. RESULTS: We identified 11 papers that are focused on optimizing model fairness in health care applications. The current research on mitigating bias issues in RWD is limited, both in terms of disease variety and health care applications, as well as the accessibility of public datasets for ML fairness research. Existing studies often indicate positive outcomes when using pre-processing techniques to address algorithmic bias. There remain unresolved questions within the field that require further research, which includes pinpointing the root causes of bias in ML models, broadening fairness research in AI/ML with the use of RWD and exploring its implications in healthcare settings, and evaluating and addressing bias in multi-modal data. CONCLUSION: This paper provides useful reference material and insights to researchers regarding AI/ML fairness in real-world health care data and reveals the gaps in the field. Fair AI/ML in health care is a burgeoning field that requires a heightened research focus to cover diverse applications and different types of RWD.

Exploration of therapeutic models for psycho-cardiology: From cardiac to psychological rehabilitation.

The prevalence and mortality of cardiovascular disease are relatively high. Currently, depression has been proven to be an independent risk factor for the occurrence and poor prognosis of cardiovascular disease. Psycho-cardiovascular comorbidity, as a reciprocal cause and effect, affects each other, leading to the deterioration of clinical prognosis and forming a vicious circle. Coronary artery disease comorbidity with depression is a common disease in psycho-cardiology medicine. This paper expounds on the exploration of the treatment model of psycho-cardiology from the aspects of epidemiological characteristics, comorbidity mechanism, screening, diagnosis, and treatment.

Develop and Validate a Computable Phenotype for the Identification of Alzheimer's Disease Patients Using Electronic Health Record Data.

INTRODUCTION: Alzheimer's Disease (AD) are often misclassified in electronic health records (EHRs) when relying solely on diagnostic codes. This study aims to develop a more accurate, computable phenotype (CP) for identifying AD patients by using both structured and unstructured EHR data. METHODS: We used EHRs from the University of Florida Health (UF Health) system and created rule-based CPs iteratively through manual chart reviews. The CPs were then validated using data from the University of Texas Health Science Center at Houston (UT Health) and the University of Minnesota (UMN). RESULTS: Our best-performing CP is " patient has at least 2 AD diagnoses and AD-related keywords " with an F1-score of 0.817 at UF, and 0.961 and 0.623 at UT Health and UMN, respectively. DISCUSSION: We developed and validated rule-based CPs for AD identification with good performance, crucial for studies that aim to use real-world data like EHRs.

Bisdemethoxycurcumin, a curcumin, protects chondrocytes, and reduces cartilage inflammation via the NRF2/HO-1/NLRP3 pathway.

BACKGROUND: The objective of this thesis is to evaluate the effect of bisdemethoxycurcumin (BDMC) on osteoarthritis (OA) and comprehensively evaluate the role of the Nuclear Factor erythroid 2-Related Factor 2 (Nrf2) signalling pathway in chondrocytes. METHOD: In our study, we treated chondrocytes with BDMC in an in vitro chondrocyte assay and measured its influence on extracellular matrix (ECM) expression, downstream heme oxygenase-1 (HO-1) and NOD-like receptor thermal protein domain associated protein 3 (NLRP3) levels. RESULTS: Our study indicates that BDMC significantly activates the Nrf2 signaling pathway in chondrocytes in vitro. Furthermore, the expression of matrix metalloproteinase 3, interleukin 1ß, recombinant a disintegrin and metalloproteinase with thrombospondin motifs (ADAMTS)4 and (ADAMTS)5 was significantly suppressed by BDMC. CONCLUSION: This study confirms the potential for BDMC to activate the Nrf2/HO-1/NLRP3 signalling pathway and alleviate OA symptoms. Therefore, BDMC is a promising therapeutic agent for OA that offers new insights and treatment methods.

Network meta-analysis of the efficacy and safety of monoclonal antibodies and traditional conventional dichotomous agents for chronic obstructive pulmonary disease.

Introduction: Monoclonal antibodies (mAbs) against cytokines and chemokines or their receptors promise to be a potential therapeutic option to address chronic obstructive pulmonary disease (COPD). We aim to provide a comprehensive literature review of the improvement in FEV1 and safety when comparing mAbs with conventional dichotomous agents. Methods: We systematically searched 3 electronic databases (PubMed, EMBASE, and CENTRAL) up to August 1, 2023 to collect eligible randomized controlled trials (RCTs). A frequentist network meta-analysis using a random-effects model was deployed to calculate mean differences (MD) for FEV1, relative risk (RR) of treatment-emergent adverse events (TEAEs), and estimate the surface under cumulative rankings (SUCRA). A higher SUCRA indicates a better outcome. Results: This study included 23 RCTs involving a total of 20,853 patients. Overall, except for Dupilumab, mAbs did not significantly improve FEV1 compared to traditional conventional dichotomous agents. Among all the interventions included, Aclidinium bromide/Formoterol (AB/FF) (SUCRA 97.7%) ranked highest, followed by Umeclidinium/vilanterol (UMEC/VI) (SUCRA 93.5%), and Glycopyrrolate Formoterol Fumarate (GFF) (SUCRA 84.7%). Dupilumab (SUCRA 66.9%) ranked the fourth among all interventions but ranked the first among all the mAbs. Importantly, all mAbs demonstrated a good safety profile compared with placebo. Conclusion: Considering the improvement in FEV1 and its safety, the development of mAbs for COPD still holds significant clinical potential. Systematic review registration: PROSPERO, CRD42023452714.

Heterogeneous treatment effects of metformin on risk of dementia in patients with type 2 diabetes: A longitudinal observational study.

INTRODUCTION: Little is known about the heterogeneous treatment effects of metformin on dementia risk in people with type 2 diabetes (T2D). METHODS: Participants (≥ 50 years) with T2D and normal cognition at baseline were identified from the National Alzheimer's Coordinating Center database (2005-2021). We applied a doubly robust learning approach to estimate risk differences (RD) with a 95% confidence interval (CI) for dementia risk between metformin use and no use in the overall population and subgroups identified through a decision tree model. RESULTS: Among 1393 participants, 104 developed dementia over a 4-year median follow-up. Metformin was significantly associated with a lower risk of dementia in the overall population (RD, -3.2%; 95% CI, -6.2% to -0.2%). We identified four subgroups with varied risks for dementia, defined by neuropsychiatric disorders, non-steroidal anti-inflammatory drugs, and antidepressant use. DISCUSSION: Metformin use was significantly associated with a lower risk of dementia in individuals with T2D, with significant variability among subgroups.

A lightweight path consistency verification based on INT in SDN.

The existing path consistency verification solutions in software-defined networking (SDN) were implemented by proactive injecting large number of probing packets or by embedding linear-scale tags as the path lengthens, which incurred significant bandwidth and communication overhead. A lightweight path consistency validation mechanism based on in-band network telemetry (INT) in SDN is proposed. Based on INT, in the scheme, the ingress switch inserts a telemetry instruction header with probability, each subsequent switch updates the telemetry data using a uniform sampling algorithm and only carries partial path information in INT packet to keep the head space size constant, the egress switch reports the final sampled telemetry data to the controller to verify the path compliance according to aggregated telemetry data. A heuristic flow selection algorithm is proposed to implement network-level path consistency validation. The proposed scheme was implemented and evaluated. The analyses and experiments demonstrate the proposed mechanism effectively limits the packet head overhead and introduces less than 7% of additional forwarding delays and 6% of throughput degradation at most.

A Fair Individualized Polysocial Risk Score for Identifying Increased Social Risk in Type 2 Diabetes.

Background: Racial and ethnic minority groups and individuals facing social disadvantages, which often stem from their social determinants of health (SDoH), bear a disproportionate burden of type 2 diabetes (T2D) and its complications. It is crucial to implement effective social risk management strategies at the point of care. Objective: To develop an electronic health records (EHR)-based machine learning (ML) analytical pipeline to address unmet social needs associated with hospitalization risk in patients with T2D. Methods: We identified real-world patients with T2D from the EHR data from University of Florida (UF) Health Integrated Data Repository (IDR), incorporating both contextual SDoH (e.g., neighborhood deprivation) and individual-level SDoH (e.g., housing instability). The 2015-2020 data were used for training and validation and 2021-2022 data for independent testing. We developed a machine learning analytic pipeline, namely individualized polysocial risk score (iPsRS), to identify high social risk associated with hospitalizations in T2D patients, along with explainable AI (XAI) and fairness optimization. Results: The study cohort included 10,192 real-world patients with T2D, with a mean age of 59 years and 58% female. Of the cohort, 50% were non-Hispanic White, 39% were non-Hispanic Black, 6% were Hispanic, and 5% were other races/ethnicities. Our iPsRS, including both contextual and individual-level SDoH as input factors, achieved a C statistic of 0.72 in predicting 1-year hospitalization after fairness optimization across racial and ethnic groups. The iPsRS showed excellent utility for capturing individuals at high hospitalization risk because of SDoH, that is, the actual 1-year hospitalization rate in the top 5% of iPsRS was 28.1%, ~13 times as high as the bottom decile (2.2% for 1-year hospitalization rate). Conclusion: Our ML pipeline iPsRS can fairly and accurately screen for patients who have increased social risk leading to hospitalization in real word patients with T2D.

Meta-analysis of Association between Newer Glucose-Lowering Drugs and Risk of Parkinson's Disease.

Background: The association between newer classes of glucose-lowering drugs (GLDs) and the risk of Parkinson's disease (PD) remains unclear. Objective: The aim was to examine the effect of newer GLDs on the risk of PD through a meta-analysis of randomized outcome trials. Methods: The methods included randomized placebo-controlled outcome trials that reported PD events associated with three newer classes of GLDs (ie, dipeptidyl peptidase-4 inhibitors, glucagon-like peptide-1 receptor agonists, and sodium-glucose co-transporter-2 inhibitors) in participants with or without type 2 diabetes. The pooled odds ratio (OR) and 95% confidence interval (CI) were estimated using Peto's method. Results: The study included 24 trials involving 33 PD cases among 185,305 participants during a median follow-up of 2.2 years. Newer GLDs were significantly associated with a lower PD risk (OR: 0.50; 95% CI: 0.25-0.98) than placebo. Conclusion: Newer GLDs may possibly be associated with a decreased risk of PD; however, larger datasets are required to confirm or refute this notion.

CDC42-mediated Wnt signaling facilitates odontogenic differentiation of DPCs during tooth root elongation.

BACKGROUND: CDC42 is a member of Rho GTPase family, acting as a molecular switch to regulate cytoskeleton organization and junction maturation of epithelium in organ development. Tooth root pattern is a highly complicated and dynamic process that dependens on interaction of epithelium and mesenchyme. However, there is a lack of understanding of the role of CDC42 during tooth root elongation. METHODS: The dynamic expression of CDC42 was traced during tooth development through immunofluorescence staining. Then we constructed a model of lentivirus or inhibitor mediated Cdc42 knockdown in Herwig's epithelial root sheath (HERS) cells and dental papilla cells (DPCs), respectively. Long-term influence of CDC42 abnormality was assessed via renal capsule transplantation and in situ injection of alveolar socket. RESULTS: CDC42 displayed a dynamic spatiotemporal pattern, with abundant expression in HERS cells and apical DPCs in developing root. Lentivirus-mediated Cdc42 knockdown in HERS cells didn't disrupt cell junctions as well as epithelium-mesenchyme transition. However, inhibition of CDC42 in DPCs undermined cell proliferation, migration and odontogenic differentiation. Wnt/ß-catenin signaling as the downstream target of CDC42 modulated DPCs' odontogenic differentiation. The transplantation and in situ injection experiments verified that loss of CDC42 impeded root extension via inhibiting the proliferation and differentiation of DPCs. CONCLUSIONS: We innovatively revealed that CDC42 was responsible for guiding root elongation in a mesenchyme-specific manner. Furthermore, CDC42-mediated canonical Wnt signaling regulated odontogenic differentiation of DPCs during root formation.

Initiation of Antihypertensive Medication from Midlife on Incident Dementia: The Health and Retirement Study.

BACKGROUND: Hypertension has been identified as a risk factor of dementia, but most randomized trials did not show efficacy in reducing the risk of dementia. Midlife hypertension may be a target for intervention, but it is infeasible to conduct a trial initiating antihypertensive medication from midlife till dementia occurs late life. OBJECTIVE: We aimed to emulate a target trial to estimate the effectiveness of initiating antihypertensive medication from midlife on reducing incident dementia using observational data. METHODS: The Health and Retirement Study from 1996 to 2018 was used to emulate a target trial among non-institutional dementia-free subjects aged 45 to 65 years. Dementia status was determined using algorithm based on cognitive tests. Individuals were assigned to initiating antihypertensive medication or not, based on the self-reported use of antihypertensive medication at baseline in 1996. Observational analog of intention-to-treat and per-protocol effects were conducted. Pooled logistic regression models with inverse-probability of treatment and censoring weighting using logistic regression models were applied, and risk ratios (RRs) were calculated, with 200 bootstrapping conducted for the 95% confidence intervals (CIs). RESULTS: A total of 2,375 subjects were included in the analysis. After 22 years of follow-up, initiating antihypertensive medication reduced incident dementia by 22% (RR = 0.78, 95% CI: 0.63, 0.99). No significant reduction of incident dementia was observed with sustained use of antihypertensive medication. CONCLUSION: Initiating antihypertensive medication from midlife may be beneficial for reducing incident dementia in late life. Future studies are warranted to estimate the effectiveness using large samples with improved clinical measurements.

Personalized 3D-Printed Scaffolds with Multiple Bioactivities for Bioroot Regeneration.

Recent advances in 3D printing offer a prospective avenue for producing transplantable human tissues with complex geometries; however, the appropriate 3D-printed scaffolds possessing the biological compatibility for tooth regeneration remain unidentified. This study proposes a personalized scaffold of multiple bioactivities, including induction of stem cell proliferation and differentiation, biomimetic mineralization, and angiogenesis. A brand-new bioink system comprising a biocompatible and biodegradable polymer is developed and reinforced with extracellular matrix generated from dentin tissue (treated dentin matrix, TDM). Adding TDM optimizes physical properties including microstructure, hydrophilicity, and mechanical strength of the scaffolds. Proteomics analysis reveals that the released proteins of the 3D-printed TDM scaffolds relate to multiple biological processes and interact closely with each other. Additionally, 3D-printed TDM scaffolds establish a favorable microenvironment for cell attachment, proliferation, and differentiation in vitro. The 3D-printed TDM scaffolds are proangiogenic and facilitate whole-thickness vascularization of the graft in a subcutaneous model. Notably, the personalized TDM scaffold combined with dental follicle cells mimics the anatomy and physiology of the native tooth root three months after in situ transplantation in beagles. The remarkable in vitro and in vivo outcomes suggest that the 3D-printed TDM scaffolds have multiple bioactivities and immense clinical potential for tooth-loss therapy.

Hepatitis C Cascade of Care in the Direct-Acting Antivirals Era: A Meta-Analysis.

INTRODUCTION: The hepatitis C virus (HCV) epidemic remains a public health problem worldwide. A systematic review and meta-analysis were conducted to provide evidence of outcomes attained across the HCV care cascade in the era of direct-acting antivirals. METHODS: Studies from North America, Europe, and Australia (January 2014 through March 2021) reporting on HCV care cascade outcomes (screening to cure) were included. When calculating the proportions of individuals completing each step, the numerator for Steps 1-8 was the number of individuals completing each step; the denominator was the number of individuals completing the previous step for Steps 1-3 and Step 3 for Steps 4-8. In 2022, random effects meta-analyses were conducted to estimate pooled proportions with 95% CIs. RESULTS: Sixty-five studies comprising 7,402,185 individuals were identified. Among individuals with positive HCV ribonucleic acid test results, 62% (95% CI=55%, 70%) attended their first care appointment, 41% (95% CI=37%, 45%) initiated treatment, 38% (95% CI=29%, 48%) completed treatment, and 29% (95% CI=25%, 33%) achieved cure. HCV screening rates were 43% (95% CI=22%, 66%) in prisons or jails and 20% (95% CI=11%, 31%) in emergency departments. Linkage to care rates were 62% (95% CI=46%, 75%) for homeless individuals and 26% (95% CI=22%, 31%) for individuals diagnosed in emergency departments. Cure rates were 51% (95% CI=30%, 73%) in individuals with substance use disorder and 17% (95% CI=17%, 17%) in homeless individuals. Cure rates were lowest in the U.S. DISCUSSION: Despite the availability of effective all-oral direct-acting antiviral therapies, persistent gaps remain across the HCV care cascade, especially among traditionally marginalized populations. Public health interventions targeting identified priority areas (e.g., emergency departments) may improve screening and healthcare retention of vulnerable populations with HCV infection (e.g., substance use disorder populations).

Ethnic Variations in Cardiovascular and Renal Outcomes From Newer Glucose-Lowering Drugs: A Meta-Analysis of Randomized Outcome Trials.

Background Hispanic populations are more likely to develop diabetes and its related diseases than non-Hispanic White populations. Little evidence exists to support whether the cardiovascular and renal benefits of sodium-glucose cotransporter 2 inhibitors and glucagon-like peptide-1 receptor agonists are generalizable to the Hispanic populations. Methods and Results We included the cardiovascular and renal outcome trials (up to March 2021) that reported the major adverse cardiovascular events (MACEs), cardiovascular death/hospitalization for heart failure, and composite renal outcomes by ethnicity in individuals with type 2 diabetes (T2D), calculated pooled hazard ratios (HRs) with 95% CIs using fixed-effects models, and tested the differences between Hispanic and non-Hispanic populations (P for interaction [Pinteraction]). In 3 sodium-glucose cotransporter 2 inhibitor trials, there was a statistically significant difference between Hispanic (HR, 0.70 [95% CI, 0.54-0.91]) and non-Hispanic (HR, 0.96 [95% CI, 0.86-1.07]) groups in treatment effects on MACE risk (Pinteraction=0.03), except for risks of cardiovascular death/hospitalization for heart failure (Pinteraction=0.46) and composite renal outcome (Pinteraction=0.31). In 5 glucagon-like peptide-1 receptor agonist trials, there was no statistically significant difference in treatment effect on MACE risk between Hispanic (HR, 0.82 [95% CI, 0.70-0.96]) and non-Hispanic (HR, 0.92 [95% CI, 0.84-1.00]) populations (Pinteraction=0.22). In 3 dipeptidyl peptidase-4 inhibitor trials, the HR for MACE risk appeared greater in Hispanic (HR, 1.15 [95% CI, 0.98-1.35]) than non-Hispanic (HR, 0.96 [95% CI, 0.88-1.04]) populations (Pinteraction=0.045). Conclusions Compared with non-Hispanic individuals, Hispanic individuals with T2D appeared to obtain a greater benefit of lowered MACE risk with sodium-glucose cotransporter 2 inhibitors.

Newer glucose-lowering drugs and risk of dementia: A systematic review and meta-analysis of observational studies.

BACKGROUND: Preclinical studies have suggested potential beneficial effects of newer glucose-lowering drugs (GLDs) including dipeptidyl peptidase (DPP)-4 inhibitors, glucagon-like peptide-1 receptor agonists (GLP-1RAs), and sodium glucose co-transporter-2 (SGLT2) inhibitors, in protecting humans against cognitive decline and dementia. However, population studies aiming to demonstrate such cognitive benefits from newer GLDs have produced mixed findings. This meta-analysis aimed to evaluate the association between newer GLDs and risk of dementia in adults with type 2 diabetes (T2D). METHODS: Electronic databases were searched up to March 11, 2022 to include observational studies that examined the association between DPP-4 inhibitors, GLP-1RAs, and SGLT2 inhibitors and risk of dementia (including all-cause dementia, Alzheimer's disease [AD], and vascular dementia [VD]) in people with T2D. We conducted a random-effects meta-analysis to calculate the relative risk (RR) with 95% confidence interval (CI) for each class of newer GLD. RESULTS: Ten studies (from nine articles) involving 819,511 individuals with T2D were included. Three studies found that SGLT2 inhibitor users had a lower risk of all-cause dementia than non-SGLT2 inhibitor users (RR, 0.62; 95% CI, 0.39-0.97). Five studies found that users versus nonusers of GLP-1RAs were associated with a significant reduction in the risk of all-cause dementia (RR, 0.72; 95% CI, 0.54-0.97). However, a meta-analysis for AD and VD was unavailable for SGLT2 inhibitors and GLP-1RAs because only one study was included for each drug. In seven studies, users vs. nonusers of DPP-4 inhibitors were significantly associated with a decreased risk of all-cause dementia (RR, 0.84; 95% CI, 0.74-0.94) and VD (RR, 0.59; 95% CI, 0.47-0.75) but not AD (RR, 0.82; 95% CI, 0.63-1.08). CONCLUSION: Newer GLDs were associated with a decreased risk of all-cause dementia in people with T2D. Because of the observational nature and significant heterogeneity between studies, the results should be interpreted with caution. Further research is warranted to confirm our findings.

The efficacy and safety of prophylactic antibiotics for post-acute stroke infection: A systematic review and meta-analysis.

AIMS: Infections are common complications after stroke and associated with unfavourable outcomes. We aimed to evaluate the efficacy and safety of prophylactic antibiotics for post-acute stroke infection. METHODS: We searched PubMed, Embase, the Cochrane Library, SinoMed, China National Knowledge Infrastructure, WanFang Data, China Science and Technology Journal Database, and clinical trial register platforms from inception to 15 February 2022. We included randomized clinical trials that evaluated the efficacy and safety of prophylactic antibiotics. Primary outcomes were mortality rate and incidence of pneumonia. The pooled risk ratio (RR) and mean differences with 95% confidence interval (CI) were calculated using the random or fixed-effect model depending on heterogeneity. The quality of evidence was evaluated using the Grading of Recommendations, Assessment, Development and Evaluations. RESULTS: Twelve studies (4809 participants) were included. There was no significant difference in the mortality rate (12 trials, n = 4740, RR 1.03 [95% Cl: 0.91-1.16], high-quality evidence), incidence of pneumonia (7 trials, n = 4352, RR 0.94 [95% CI: 0.79-1.11], high-quality evidence) and the incidence of adverse events between the prophylactic antibiotics and control groups. Prophylactic antibiotics significantly reduced the incidence of infections (8 trials, n = 4517, RR 0.72 [95% CI: 0.58-0.89], moderate-quality evidence) and urinary tract infections (7 trials, n = 4352, RR 0.39 [95% CI: 0.3-0.49], moderate-quality evidence). None of the subgroup analyses showed a significant difference in mortality or the incidence of pneumonia. CONCLUSION: For acute stroke patients, prophylactic antibiotics were significantly associated with fewer incidences of any infections and urinary tract infections without significant differences in mortality rate and pneumonia.

Hertwig's epithelial root sheath cells show potential for periodontal complex regeneration.

BACKGROUND: Although researchers have been exploring therapeutic strategies of treating serious periodontal tissue loss, including the application of stem cells, tissue regeneration of the periodontal complex involving cementum, periodontium, and alveolar bone has hardly been achieved. Aiming at tackling the problem of severely damaged periodontal complex, it is worth trying to make advantages of Hertwig's epithelial root sheath (HERS) cells to tissue regeneration mimicking the physiological developmental process with their ability of cementum, bone, and periodontium formation. METHODS: HERS cells and dental follicle cells (DFCs) were acquired from Sprague Dawley rats' molar germs and identified by immunofluorescence. Alizarin red assay, ALP staining, AKP test, real-time quantitative polymerase chain reaction (RT-qPCR) and Western blot were conducted to confirm the osteogenic potential, epithelial-mesenchymal transition (EMT) character of harvested HERS cells and epithelial-mesenchymal interaction (EMI) with DFCs. An animal model of periodontal defect was constructed to testify the tissue regeneration ability in vivo. Micro-CT and histological examinations were interpreted to unveil the tissue repair outcomes. RESULTS: HERS cells expressed strong epithelial cell markers CK14 and E-cadherin. The in vitro experiments overall showed the concretely enhanced osteogenic differentiation ability in either HERS group or HERS+DFC group. Meanwhile, the in vivo conduction of rat mandibular periodontal repair experiment showed regenerative effectiveness of periodontal complex structure in both HERS and HERS+DFC group in situ, testified by Micro-CT and histological analysis. CONCLUSIONS: HERS cells show potential for periodontal tissue regeneration which suggests the future possibilities of being considered as one of the cell choices for severely damaged periodontal tissue repair.

Systematic literature review and meta-analysis of clinical outcomes and prognostic factors for melanoma brain metastases.

Background: More than 60% of all stage IV melanoma patients develop brain metastases, while melanoma brain metastases (MBM) is historically difficult to treat with poor prognosis. Objectives: To summarize clinical outcomes and prognostic factors in MBM patients. Methods: A systematic review with meta-analysis was conducted, and a literature search for relevant studies was performed on November 1, 2020. Weighted average of median overall survival (OS) was calculated by treatments. The random-effects model in conducting meta-analyses was applied. Results: A total of 41 observational studies and 12 clinical trials with our clinical outcomes of interest, and 31 observational studies addressing prognostic factors were selected. The most common treatments for MBM were immunotherapy (IO), MAP kinase inhibitor (MAPKi), stereotactic radiosurgery (SRS), SRS+MAPKi, and SRS+IO, with median OS from treatment start of 7.2, 8.6, 7.3, 7.3, and 14.1 months, respectively. Improved OS was observed for IO and SRS with the addition of IO and/or MAPKi, compared to no IO and SRS alone, respectively. Several prognostic factors were found to be significantly associated with OS in MBM. Conclusion: This study summarizes pertinent information regarding clinical outcomes and the association between patient characteristics and MBM prognosis.

Burden and Risk Factors of Brain Metastases in Melanoma: A Systematic Literature Review.

Melanoma can frequently metastasize to the brain with severe consequences. However, variation of melanoma brain metastases (MBM) development among populations is not well studied, and underlying mechanisms and risk factors for MBM development are not consistently documented. We conducted a systematic literature review (SLR) including a total of 39 articles to evaluate the proportion of melanoma patients who are diagnosed with, or develop, brain metastases, and summarize the risk factors of MBM. The average proportion of MBM was calculated and weighted by the sample size of each study. Meta-analyses were conducted for the selected risk factors using a random-effects model. The proportion of MBM at diagnosis was 33% (975 with MBM out of 2948 patients) among patients with cutaneous melanoma (excluding acral) and 23% (651/2875) among patients with cutaneous mixed with other types of melanoma. The proportion at diagnosis was lower among populations with mucosal (9/96, 9%) or uveal (4/184, 2%) melanoma and among populations outside the United States and Europe. Meta-analysis demonstrated that male vs. female gender and left-sided tumors vs. right-sided were significantly associated with increased risk of melanoma brain metastases. These data may help clinicians to assess an individual patient's risk of developing melanoma brain metastases.