Disseminated Talaromyces marneffei infection initially presenting as cutaneous and subcutaneous lesion in an HIV-Negative renal transplant recipient: a case report and literature review.

BACKGROUND: The incidence of Talaromyces marneffei (T. marneffei) infection has increased in recent years with the development of organ transplantation and the widespread use of immunosuppressive agents. However, the lack of clinical suspicion leading to delay or misdiagnosis is an important reason for the high mortality rate in non-human immunodeficiency virus (HIV) and non-endemic population. Herein, we report a case of disseminated T. marneffei infection in a non-HIV and non-endemic recipient after renal transplant, who initially presented with skin rashes and subcutaneous nodules and developed gastrointestinal bleeding. CASE PRESENTATION: We describe a 54-year-old renal transplantation recipient presented with scattered rashes, subcutaneous nodules and ulcerations on the head, face, abdomen, and right upper limb. The HIV antibody test was negative. The patient had no obvious symptoms such as fever, cough, etc. Histopathological result of the skin lesion sites showed chronic suppurative inflammation with a large number of fungal spores. Subsequent fungal culture suggested T. marneffei infection. Amphotericin B deoxycholate was given for antifungal treatment, and there was no deterioration in the parameters of liver and kidney function. Unfortunately, the patient was soon diagnosed with gastrointestinal bleeding, gastrointestinal perforation and acute peritonitis. Then he rapidly developed multiple organ dysfunction syndrome and abandoned treatment. CONCLUSIONS: The risk of fatal gastrointestinal bleeding can be significantly increased in kidney transplant patients with T. marneffei infection because of the long-term side effects of post-transplant medications. Strengthening clinical awareness and using mNGS or mass spectrometry technologies to improve the detection rate and early diagnosis of T. marneffei are crucial for clinical treatment in non-HIV and non-endemic population.

Conditional reprogrammed human limbal epithelial cell model for anti-SARS-CoV-2 drug screening.

To minimize the global pandemic COVID-19 spread, understanding the possible transmission routes of SARS-CoV-2 and discovery of novel antiviral drugs are necessary. We describe here that the virus can infect ocular surface limbal epithelial, but not other regions. Limbal supports wild type and mutant SARS-CoV-2 entry and replication depending on ACE2, TMPRSS2 and possibly other receptors, resulting in slight CPE and arising IL-6 secretion, which symbolizes conjunctivitis in clinical symptoms. With this limbal model, we have screened two natural product libraries and discovered several unreported drugs. Our data reveal important commonalities between COVID-19 and ocular infection with SARS-CoV-2, and establish an ideal cell model for drug screening and mechanism research.

Online causal inference with application to near real-time post-market vaccine safety surveillance.

Streaming data routinely generated by social networks, mobile or web applications, e-commerce, and electronic health records present new opportunities to monitor the impact of an intervention on an outcome via causal inference methods. However, most existing causal inference methods have been focused on and applied to static data, that is, a fixed data set in which observations are pooled and stored before performing statistical analysis. There is thus a pressing need to turn static causal inference into online causal learning to support near real-time monitoring of treatment effects. In this paper, we present a framework for online estimation and inference of treatment effects that can incorporate new information as it becomes available without revisiting prior observations. We show that, under mild regularity conditions, the proposed online estimator is asymptotically equivalent to the offline oracle estimator obtained by pooling all data. Our proposal is motivated by the need for near real-time vaccine effectiveness and safety monitoring, and our proposed method is applied to a case study on COVID-19 vaccine safety surveillance.

To weight or not to weight? The effect of selection bias in 3 large electronic health record-linked biobanks and recommendations for practice.

OBJECTIVES: To develop recommendations regarding the use of weights to reduce selection bias for commonly performed analyses using electronic health record (EHR)-linked biobank data. MATERIALS AND METHODS: We mapped diagnosis (ICD code) data to standardized phecodes from 3 EHR-linked biobanks with varying recruitment strategies: All of Us (AOU; n = 244 071), Michigan Genomics Initiative (MGI; n = 81 243), and UK Biobank (UKB; n = 401 167). Using 2019 National Health Interview Survey data, we constructed selection weights for AOU and MGI to represent the US adult population more. We used weights previously developed for UKB to represent the UKB-eligible population. We conducted 4 common analyses comparing unweighted and weighted results. RESULTS: For AOU and MGI, estimated phecode prevalences decreased after weighting (weighted-unweighted median phecode prevalence ratio [MPR]: 0.82 and 0.61), while UKB estimates increased (MPR: 1.06). Weighting minimally impacted latent phenome dimensionality estimation. Comparing weighted versus unweighted phenome-wide association study for colorectal cancer, the strongest associations remained unaltered, with considerable overlap in significant hits. Weighting affected the estimated log-odds ratio for sex and colorectal cancer to align more closely with national registry-based estimates. DISCUSSION: Weighting had a limited impact on dimensionality estimation and large-scale hypothesis testing but impacted prevalence and association estimation. When interested in estimating effect size, specific signals from untargeted association analyses should be followed up by weighted analysis. CONCLUSION: EHR-linked biobanks should report recruitment and selection mechanisms and provide selection weights with defined target populations. Researchers should consider their intended estimands, specify source and target populations, and weight EHR-linked biobank analyses accordingly.

The implications of single-cell RNA-seq analysis in prostate cancer: unraveling tumor heterogeneity, therapeutic implications and pathways towards personalized therapy.

In recent years, advancements in single-cell and spatial transcriptomics, which are highly regarded developments in the current era, particularly the emerging integration of single-cell and spatiotemporal transcriptomics, have enabled a detailed molecular comprehension of the complex regulation of cell fate. The insights obtained from these methodologies are anticipated to significantly contribute to the development of personalized medicine. Currently, single-cell technology is less frequently utilized for prostate cancer compared with other types of tumors. Starting from the perspective of RNA sequencing technology, this review outlined the significance of single-cell RNA sequencing (scRNA-seq) in prostate cancer research, encompassing preclinical medicine and clinical applications. We summarize the differences between mouse and human prostate cancer as revealed by scRNA-seq studies, as well as a combination of multi-omics methods involving scRNA-seq to highlight the key molecular targets for the diagnosis, treatment, and drug resistance characteristics of prostate cancer. These studies are expected to provide novel insights for the development of immunotherapy and other innovative treatment strategies for castration-resistant prostate cancer. Furthermore, we explore the potential clinical applications stemming from other single-cell technologies in this review, paving the way for future research in precision medicine.

Identification of immune-associated biomarker for predicting lung adenocarcinoma: bioinformatics analysis and experiment verification of PTK6.

BACKGROUND: Abnormal expression of protein tyrosine kinase 6 (PTK6) has been proven to be involved in the development of gynecological tumors. However, its immune-related carcinogenic mechanism in other tumors remains unclear. OBJECTIVE: The aim of this study was to identify PTK6 as a novel prognostic biomarker in pan-cancer, especially in lung adenocarcinoma (LUAD), which is correlated with immune infiltration, and to clarify its clinicopathological and prognostic significance. METHODS: The prognostic value and immune relevance of PTK6 were investigated by using bio-informatics in this study. PTK6 expression was validated in vitro experiments (lung cancer cell lines PC9, NCI-H1975, and HCC827; human normal lung epithelial cells BEAS-2B). Western blot (WB) revealed the PTK6 protein expression in lung cancer cell lines. PTK6 expression was inhibited by Tilfrinib. Colony formation and the Cell Counting Kit-8 (CCK-8) assay were used to detect cell proliferation. The wound healing and trans-well were performed to analyze the cell migration capacity. Then flow cytometry was conducted to evaluate the cell apoptosis. Eventually, the relationship between PTK6 and immune checkpoints was examined. WB was used to estimate the PD-L1 expression at different Tilfrinib doses. RESULTS: PTK6 was an independent predictive factor for LUAD and was substantially expressed in LUAD. Pathological stage was significantly correlated with increased PTK6 expression. In accordance with survival analysis, poor survival rate in LUAD was associated with a high expression level of PTK6. Functional enrichment of the cell cycle and TGF-ß signaling pathway was demonstrated by KEGG and GSEA analysis. Moreover, PTK6 expression considerably associated with immune infiltration in LUAD, as determined by immune analysis. Thus, the result of vitro experiments indicated that cell proliferation and migration were inhibited by the elimination of PTK6. Additionally, PTK6 suppression induced cell apoptosis. Obviously, PD-L1 protein expression level up-regulated while PTK6 was suppressed. CONCLUSION: PTK6 has predictive value for LUAD prognosis, and could up regulated PD-L1.

Mechanisms of electroacupuncture relieves uterine smooth muscle spasm in dysmenorrhea rats based on Rho/ROCK signaling pathway. / 基于Rho/ROCKä¿¡å·é€šè·¯æŽ¢è®¨ç”µé’ˆä»»è„‰ã€ç£è„‰ç»ç©´ç¼“è§£ç±»ç—›ç»æ¨¡åž‹å¤§é¼ å­å®«å¹³æ»‘è‚Œç—‰æŒ›çš„æœºåˆ¶.

OBJECTIVES: To investigate the effect of electroacupuncture (EA) on Rho/Rho-associated coiled-coil-forming kinases (ROCK) signaling pathway of uterus tissue in rats with dysmenorrhea, so as to explore the underlying mechanism of EA treating primary dysmenorrhea (PD) and uterine smooth muscle spasm, and to observe whether there is a difference in the effect of meridian acupoints in Conception Vessel (CV) and Governer Vessel (GV). METHODS: Sixty female SD rats were randomly divided into saline, model, CV, GV, and non-acupoint groups, with 12 rats in each group. The dysmenorrhea model was established by subcutaneous injection of estradiol diphenhydrate combined with intraperitoneal injection of oxytocin (OT). EA (2 Hz) was applied to "Qihai" (CV6) and "Zhongji" (CV3) for CV group, "Mingmen" (GV4) and "Yaoshu" (GV2) for GV group, "non-acupoint 1" and "non-acupoint 3" on the left side for non-acupoint group, and manual acupuncture was applied to "Guanyuan" (CV4) for CV group, "Yaoyangguan" (GV3) for GV group, "non-acupoint 2" on the left side for non-acupoint group. The treatment was conducted for 20 min each time, once daily for 10 days. The writhing score was evaluated. The smooth myoelectric signals of rats' uterus in vivo were recorded by multi-channel physiological recorder. The uterine histopathological changes were observed by HE staining. The contents of prostaglandin F2α (PGF2α), OT and calcium ion (Ca2+) in uterine tissue of rats were detected by ELISA. The protein and mRNA expression levels of smooth muscle 22-α (SM22-α), RhoA and ROCKⅡ in uterine tissue were detected by Western blot and fluorescence quantitative PCR, respectively. RESULTS: Compared with the saline group, the writhing score of rats in the model group was increased (P<0.01), the amplitude voltage of uterine smooth muscle in vivo was elevated (P<0.01), the contents of PGF2α, OT and Ca2+, the protein and mRNA expression of SM22-α, RhoA and ROCK Ⅱ in uterine tissue were all increased (P<0.01). Compared with the model and the non-acupoint groups, the writhing scores of the CV and the GV groups were decreased (P<0.01, P<0.05), the amplitude voltage of uterine smooth muscle was decreased (P<0.01), the contents of PGF2α, OT and Ca2+ in uterine tissue were decreased (P<0.01, P<0.05), and the protein expression and mRNA expression of SM22-α, RhoA and ROCKⅡ in uterine tissue were decreased (P<0.01, P<0.05). HE staining showed extensive exfoliation of uterine intima with severe edema and increased glandular secretion in the model group, which was alleviated in the CV and GV groups. CONCLUSIONS: EA at acupoints of CV and GV can significantly reduce the writhing score, uterine smooth muscle amplitude voltage, pathological injury degree of uterus, and relieve spasm of uterine smooth muscle in dysmenorrhea rats, which may be related to its effect in regulating PGF2α and OT contents, inhibiting the Rho/ROCK signaling pathway, and reducing the SM22-α, RhoA, ROCKⅡ protein and mRNA expression, and Ca2+ content in uterine tissue.

BCAA-nitrogen flux in brown fat controls metabolic health independent of thermogenesis.

Brown adipose tissue (BAT) is best known for thermogenesis. Rodent studies demonstrated that enhanced BAT thermogenesis is tightly associated with increased energy expenditure, reduced body weight, and improved glucose homeostasis. However, human BAT is protective against type 2 diabetes, independent of body weight. The mechanism underlying this dissociation remains unclear. Here, we report that impaired mitochondrial catabolism of branched-chain amino acids (BCAAs) in BAT, by deleting mitochondrial BCAA carriers (MBCs), caused systemic insulin resistance without affecting energy expenditure and body weight. Brown adipocytes catabolized BCAA in the mitochondria as nitrogen donors for the biosynthesis of non-essential amino acids and glutathione. Impaired mitochondrial BCAA-nitrogen flux in BAT resulted in increased oxidative stress, decreased hepatic insulin signaling, and decreased circulating BCAA-derived metabolites. A high-fat diet attenuated BCAA-nitrogen flux and metabolite synthesis in BAT, whereas cold-activated BAT enhanced the synthesis. This work uncovers a metabolite-mediated pathway through which BAT controls metabolic health beyond thermogenesis.

Combined exposure of emamectin benzoate and microplastics induces tight junction disorder, immune disorder and inflammation in carp midgut via lysosome/ROS/ferroptosis pathway.

Pesticides and plastics bring convenience to agriculture and life, but also bring residual pollution in the environment. Emamectin benzoate (EMB) is the most popular pesticide at present. The harm of microplastics (MPs) to water and aquatic organisms is gradually increasing, and the possibility that it appears synchronously with various pesticides increases. However, the damage of EMB and MPs to the carp midgut and its mechanism have not been clarified. Therefore, based on the EMB or/and MPs exposure models, this study explored the mechanism of midgut injury through transcriptomics, immunofluorescence, western blot methods, and so on. Studies in vivo and in vitro showed that EMB or MPs exposure caused cilia shortening, lysosome damage, and ROS overproduction, which led to Fe2+ content increase, GSH/GSSG system disorder, lipid peroxidation, and ferroptosis. This process further led to the down-regulation of Cx43, Occludin, Claudin, and ZO-1, which further caused barrier damage, immune-related genes (immunoglobulin, IFN-γ) decrease and inflammation-related genes (TNF-α, IL-1ß) increase. Combined exposure was more significant than that of single exposure, and the addition of EN6 and NAC proved that lysosome/ROS/ferroptosis regulated these midgut damages. In conclusion, EMB or/and MPs exposure induce tight junction disorder, immune disorder and inflammation in carp midgut through the lysosome/ROS/ferroptosis pathway.

Association between sleep-disordered breathing and post-stroke fatigue in patients with ischemic stroke.

OBJECTIVES: Post-stroke fatigue (PSF) is common and often disabling. Sleep-disordered breathing (SDB) is highly prevalent among stroke survivors and can cause fatigue. We explored the relationship between SDB and PSF over time. MATERIALS AND METHODS: Ischemic stroke (IS) patients within the BASIC project were offered SDB screening with a well-validated cardiopulmonary sleep apnea test at 0, 3-, 6-, and 12-months post-stroke. The primary exposure was the respiratory event index (REI; sum of apneas plus hypopneas per hour). The primary outcome was PSF, measured by the SF-36 vitality scale. Associations between REI and PSF were evaluated using linear regression including time-by-REI interactions, allowing the effect of REI to vary over time. RESULTS: Of the 411 IS patients who completed at least one outcome interview, 44 % were female, 61 % Mexican American (MA), 26 % non-Hispanic white, with a mean age of 64 (SD 10). Averaged across timepoints, REI was not associated with PSF. In a time-varying model, higher REI was associated with greater PSF at 3-months (ß = 1.75, CI = 0.08, 3.43), but not at 6- or 12-months. Across timepoints, female sex, depressive symptoms, and comorbidity burden were associated with greater PSF, whereas MA ethnicity was associated with less PSF. CONCLUSIONS: Higher REI was associated with modestly greater PSF in the early post-stroke period, but no association was observed at 6 months and beyond. SDB may be a modest modifiable risk factor for early PSF, but its treatment is unlikely to have a substantial impact on long-term PSF. MA ethnicity seems to be protective against PSF.

Lac-Phe mediates the effects of metformin on food intake and body weight.

Metformin is a widely prescribed anti-diabetic medicine that also reduces body weight. There is ongoing debate about the mechanisms that mediate metformin's effects on energy balance. Here, we show that metformin is a powerful pharmacological inducer of the anorexigenic metabolite N-lactoyl-phenylalanine (Lac-Phe) in cells, in mice and two independent human cohorts. Metformin drives Lac-Phe biosynthesis through the inhibition of complex I, increased glycolytic flux and intracellular lactate mass action. Intestinal epithelial CNDP2+ cells, not macrophages, are the principal in vivo source of basal and metformin-inducible Lac-Phe. Genetic ablation of Lac-Phe biosynthesis in male mice renders animals resistant to the effects of metformin on food intake and body weight. Lastly, mediation analyses support a role for Lac-Phe as a downstream effector of metformin's effects on body mass index in participants of a large population-based observational cohort, the Multi-Ethnic Study of Atherosclerosis. Together, these data establish Lac-Phe as a critical mediator of the body weight-lowering effects of metformin.

Targeted Learning with an Undersmoothed Lasso Propensity Score Model for Large-Scale Covariate Adjustment in Healthcare Database Studies.

Lasso regression is widely used for large-scale propensity score (PS) estimation in healthcare database studies. In these settings, previous work has shown that undersmoothing (overfitting) Lasso PS models can improve confounding control, but it can also cause problems of non-overlap in covariate distributions. It remains unclear how to select the degree of undersmoothing when fitting large-scale Lasso PS models to improve confounding control while avoiding issues that can result from reduced covariate overlap. Here, we used simulations to evaluate the performance of using collaborative-controlled targeted learning to data-adaptively select the degree of undersmoothing when fitting large-scale PS models within both singly and doubly robust frameworks to reduce bias in causal estimators. Simulations showed that collaborative learning can data-adaptively select the degree of undersmoothing to reduce bias in estimated treatment effects. Results further showed that when fitting undersmoothed Lasso PS-models, the use of cross-fitting was important for avoiding non-overlap in covariate distributions and reducing bias in causal estimates.

Collaborative inference for treatment effect with distributed data-sharing management in multicenter studies.

Data sharing barriers present paramount challenges arising from multicenter clinical studies where multiple data sources are stored and managed in a distributed fashion at different local study sites. Merging such data sources into a common data storage for a centralized statistical analysis requires a data use agreement, which is often time-consuming. Data merging may become more burdensome when propensity score modeling is involved in the analysis because combining many confounding variables, and systematic incorporation of this additional modeling in a meta-analysis has not been thoroughly investigated in the literature. Motivated from a multicenter clinical trial of basal insulin treatment for reducing the risk of post-transplantation diabetes mellitus, we propose a new inference framework that avoids the merging of subject-level raw data from multiple sites at a centralized facility but needs only the sharing of summary statistics. Unlike the architecture of federated learning, the proposed collaborative inference does not need a center site to combine local results and thus enjoys maximal protection of data privacy and minimal sensitivity to unbalanced data distributions across data sources. We show theoretically and numerically that the new distributed inference approach has little loss of statistical power compared to the centralized method that requires merging the entire data. We present large-sample properties and algorithms for the proposed method. We illustrate its performance by simulation experiments and the motivating example on the differential average treatment effect of basal insulin to lower risk of diabetes among kidney-transplant patients compared to the standard-of-care.

Potassium-Competitive Acid Blocker Versus Proton Pump Inhibitor: A Pilot Study on Comparable Efficacy in the Treatment of Gastroesophageal Reflux-Related Cough.

Acid inhibitors have been considered in treating gastroesophageal reflux-related cough (GERC). Compared to proton pump inhibitors (PPIs), potassium-competitive acid blockers (P-CABs) have more potent and durable effects on anti-acid secretion. However, whether vonoprazan and esomeprazole have different therapeutic effects on GERC remains unknown. Patients diagnosed with GERC were enrolled in our study and randomly treated with vonoprazan (20 mg, once daily, P-CAB) or esomeprazole (20 mg, twice daily, PPI) for two months. A prokinetic agent was also administered. Patients were followed up once a month. Cough severity visual analogue scale (VAS) was measured as the primary outcome, while cough symptom score (CSS) and scores for cough-related quality-of-life or reflux-related symptoms were the secondary endpoints. A total of 50 patients completed the study, with 25 patients in each group. P-CAB and PPI groups showed similar decreases in cough severity VAS and CSS scores after the 2-month treatment (all P < 0.001). For quality-of-life, the Leicester Cough Questionnaire (LCQ) score increased significantly from baseline in both groups, but the P-CAB group had greater improvement and a higher LCQ score in month 2 (all P ≤ 0.05). For reflux-related symptoms, the Hull Airway Reflux Questionnaire (HARQ) score declined substantially over time in the P-CAB group, while the reflux symptom index (RSI) score decreased in both groups. The P-CAB group tended to have a lower HARQ (P = 0.051) and RSI (P = 0.069) scores in month 2. In conclusion, vonoprazan may be comparable to esomeprazole in cough symptom relief in GERC during the 2-month treatment period, but possibly provides better gains on classic reflux symptoms and quality-of-life. The long-term efficacy of P-CABs on GERC may be worth further exploration. Trial Registration: Chinese Clinical Trial Registry Identifier: ChiCTR2200067089.

Insight into the relationship between metabolic enzymes and oxadiazon degradation in Oryza sativa for reducing environmental risks.

Oxadiazon (ODZ) is extensively utilized in agricultural fields for weed control owing to its strong effectiveness. However, excessive loading of ODZ in water bodies and agricultural soils can lead to various environmental concerns. Therefore, it is crucial to understand the ODZ metabolic process and associated mechanisms in crops to assess the likelihood of ODZ contamination in the environment. This study aimed to assess the effects of ODZ on the growth and toxicological responses of rice (Oryza sativa). The growth of rice tissues was notably compromised with the increase in ODZ concentrations. RNA sequencing in combination with liquid chromatography-quadrupole-time-of-flight-high-resolution mass spectrometry/mass spectrometry (LC-Q-TOF-HRMS/MS) analysis allowed for the identification of numerous transcriptional components associated with ODZ metabolism. Four libraries comprising rice roots and shoots exposed to ODZ were RNA-sequenced in triplicate. The application of environmentally realistic ODZ concentrations upregulated the expression of 844 genes in shoots and 1476 genes in roots. Gene enrichment analysis revealed the presence of multiple enzymes involved in ODZ metabolism and detoxification. These enzymes play a critical role in mitigating environmental stress and facilitating xenobiotic metabolism. Notably, among differentially expressed genes, several key enzymes were identified, including cytochrome P450s, protein kinases, aminotransferases, and ATP-binding cassette transporters involved in the metabolic process. Using LC-Q-TOF-HRMS/MS, 3 metabolites and 13 conjugates were identified in multiple metabolic pathways involving oxidation, hydrolysis, glycosylation, acetylation, and methylation. This study successfully established a potential link between the specific metabolic products of ODZ and increased activities of their corresponding enzymes. Moreover, this study considerably elucidates the detailed pathways and mechanisms involved in ODZ metabolism. The study findings provide valuable insights into the development of genotypes for reducing ODZ residues in paddy fields and minimizing their accumulation in rice crops.

MRSL: a causal network pruning algorithm based on GWAS summary data.

Causal discovery is a powerful tool to disclose underlying structures by analyzing purely observational data. Genetic variants can provide useful complementary information for structure learning. Recently, Mendelian randomization (MR) studies have provided abundant marginal causal relationships of traits. Here, we propose a causal network pruning algorithm MRSL (MR-based structure learning algorithm) based on these marginal causal relationships. MRSL combines the graph theory with multivariable MR to learn the conditional causal structure using only genome-wide association analyses (GWAS) summary statistics. Specifically, MRSL utilizes topological sorting to improve the precision of structure learning. It proposes MR-separation instead of d-separation and three candidates of sufficient separating set for MR-separation. The results of simulations revealed that MRSL had up to 2-fold higher F1 score and 100 times faster computing time than other eight competitive methods. Furthermore, we applied MRSL to 26 biomarkers and 44 International Classification of Diseases 10 (ICD10)-defined diseases using GWAS summary data from UK Biobank. The results cover most of the expected causal links that have biological interpretations and several new links supported by clinical case reports or previous observational literatures.

A Randomized Controlled Trial to Improve Unmet Social Needs and Clinical Outcomes Among Adults with Diabetes.

BACKGROUND: Adults with type 1 or type 2 diabetes often face financial challenges and other unmet social needs to effective diabetes self-management. OBJECTIVE: Whether a digital intervention focused on addressing socioeconomic determinants of health improves diabetes clinical outcomes more than usual care. DESIGN: Randomized trial from 2019 to 2023. PARTICIPANTS: A total of 600 adults with diabetes, HbA1c ≥ 7.5%, and self-reported unmet social needs or financial burden from a health system and randomized to the intervention or standard care. INTERVENTION: CareAvenue is an automated, e-health intervention with eight videos that address unmet social needs contributing to poor outcomes. MEASURES: Primary outcome was HbA1c, measured at baseline, and 6 and 12 months after randomization. Secondary outcomes included systolic blood pressure and reported met social needs, cost-related non-adherence (CRN), and financial burden. We examined main effects and variation in effects across predefined subgroups. RESULTS: Seventy-eight percent of CareAvenue participants completed one or more modules of the website. At 12-month follow-up, there were no significant differences in HbA1c changes between CareAvenue and control group (p = 0.24). There were also no significant between-group differences in systolic blood pressure (p = 0.29), met social needs (p = 0.25), CRN (p = 0.18), and perceived financial burden (p = 0.31). In subgroup analyses, participants with household incomes 100-400% FPL (1.93 (SE = 0.76), p < 0.01), 201-400% FPL (1.30 (SE = 0.62), p < 0.04), and > 400% FPL (1.27 (SE = 0.64), p < 0.05) had significantly less A1c decreases compared to the control group. CONCLUSIONS: On average, CareAvenue participants did not achieve better A1c lowering, met needs, CRN, or perceived financial burden compared to control participants. CareAvenue participants with higher incomes achieved significantly less A1c reductions than control. Further research is needed on social needs interventions that consider tailored approaches to population subgroups. CLINICAL TRIALS REGISTRY: ClinicalTrials.gov ID NCT03950973, May 2019.

Initial Experience with Hybrid Partial Nephrectomy with Ultrasound-guided Balloon Catheter Occlusion of the Renal Artery for Recurrent Renal Tumors.

Repeat partial nephrectomy (PN) is an effective treatment in improving the prognosis for patients with recurrent renal cancer after initial PN. However, salvage PN (sPN) is inevitably associated with a higher rate of complications, largely because of intraperitoneal adhesions and fibrosis. Here we describe three initial cases for which recurrent renal tumors were treated with a novel minimally invasive approach, namely Ultrasound-guided Renal Artery Balloon catheter Occluded Hybrid Partial Nephrectomy (UBo-HPN).With laparoscopic ultrasound (LUS) guiding a Fogarty catheter to occlude the arterial blood supply, dissection of the renal hilum and most of the abdominal cavity can be avoided. UBo-HPN was successfully performed in three patients. One case of postoperative fever (Clavien-Dindo grade II) occurred, with no other complications. The mean operative time was 106 min, with a mean warm ischemia time of 21 min. UBo-HPN may be considered a safe and effective alternative for sPN, with a minimally invasive surgical footprint and better surgical outcomes.