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Prior research has demonstrated disparities in general medical care for patients with mental health conditions, but little is known about disparities in pain care. The objective of this retrospective cohort study was to determine whether mental health conditions are associated with indicators of pain care quality (PCQ) as documented by primary care clinicians in the Veterans Health Administration (VHA). We used natural language processing to analyze electronic health record data from a national sample of Veterans with moderate to severe musculoskeletal pain during primary care visits in the Fiscal Year 2017. Twelve PCQ indicators were annotated from clinician progress notes as present or absent; PCQ score was defined as the sum of these indicators. Generalized estimating equation Poisson models examined associations among mental health diagnosis categories and PCQ scores. The overall mean PCQ score across 135,408 person-visits was 8.4 (SD = 2.3). In the final adjusted model, post-traumatic stress disorder was associated with higher PCQ scores (RR = 1.006, 95%CI 1.002-1.010, P = .007). Depression, alcohol use disorder, other substance use disorder, schizophrenia, and bipolar disorder diagnoses were not associated with PCQ scores. Overall, results suggest that in this patient population, presence of a mental health condition is not associated with lower quality pain care. PERSPECTIVE: This study used a natural language processing approach to analyze medical records to determine whether mental health conditions are associated with indicators of pain care quality as documented by primary care clinicians. Findings suggest that presence of a diagnosed mental health condition is not associated with lower quality pain care.

To determine if women Veterans who deployed in support of Operations Enduring Freedom/Iraqi Freedom (OEF/OIF) would show a greater likelihood of breast cancer (BC) than other women Veterans.This was a retrospective cohort study of women aged60 years who received Veterans Affairs medical center primary care, 2001-2021. The exposure was OEF/OIF deployment and the outcome was a BC diagnosis after entering Veterans Affairs care. Poisson models evaluated the association between deployment and BC incidence, covarying demographics, lifestyle factors, and hormonal contraceptive and hormone replacement therapy use. Analyses were also stratified by age and race, and a sensitivity analysis adjusted for healthcare utilization over the initial 2 years.Of 576,601 women, 24.6% (n = 141,935) deployed during post-9/11 conflicts. Across follow-up [median: 8.2 years], 1.2% women were diagnosed with BC. Those who deployed in support of OEF/OIF were 21% less likely to be diagnosed with BC than women who did not deploy (95% CI: 0.73, 0.86). The association remained in stratified models and when including healthcare utilization.Despite the exposures of OEF/OIF deployment, there was a significantly lower incidence of BC among women who deployed versus not, possibly due to a healthy soldier effect or to differences in screening.

Cardiometabolic diseases (CMDs) are associated with depression. However, it is unclear whether coexisting CMDs may increase the risk of depression. We examined associations between cardiometabolic multimorbidity and depressive symptoms among middle-aged and older Chinese.Participants aged ≥45 years were enrolled from the China Health and Retirement Longitudinal Study 2011-2018 (N = 18,002). Cardiometabolic multimorbidity was defined as the coexistence of ≥2 CMDs, including stroke, heart disease, diabetes, hypertension, and dyslipidemia. Depressive symptoms were assessed by the Center for Epidemiological Studies Depression Scale. We used generalized estimating equation models to examine associations between cardiometabolic multimorbidity and depressive symptoms, including the dose effect of disease count and prevalent disease combinations, as well as individual and additive effects of specific CMDs.The prevalence of cardiometabolic multimorbidity was 24.5%. A higher number of CMDs had an additive dose effect on depressive symptoms that persisted consistently in specific CMDs. Stroke only, heart disease only, and diabetes only were each associated with a higher risk of depressive symptoms compared with no CMDs. CMD combinations involving stroke, heart disease, or diabetes were each associated with an increased risk of depressive symptoms compared with the absence of stroke, heart disease, or diabetes.Self-reported chronic conditions.Stroke, heart disease, and diabetes showed individual and additive effects on CMD combinations, whereas hypertension and dyslipidemia only showed associations with depressive symptoms in combinations with other CMDs. These results suggest person-centered healthcare of mental health prevention and treatment for middle-aged and older adults with individual or multiple CMDs.

Graphical abstract, Resistance to the last-line polymyxins is emerging in multidrug-resistant Klebsiella pneumoniae and phage therapy is a promising alternative. However, phage monotherapy often rapidly causes resistance and few studies have examined antibiotic-phage combinations against K. pneumoniae. Here, we investigated the combination of polymyxin B with a novel phage pK8 against an mcr-1-carrying polymyxin-resistant clinical isolate Kp II-503 (polymyxin B MIC, 8 mg/L). The phage genome was sequenced and bacterial metabolomes were analysed at 4 and 24 h following the treatment with polymyxin B (16 mg/L), phage pK8 (102 PFU/mL) and their combination. Minimal metabolic changes across 24 h were observed with polymyxin B alone; whereas a significant inhibition of the citrate cycle, pentose phosphate pathway, amino acid and nucleotide metabolism occurred with the phage-polymyxin combination at both 4 and 24 h, but with phage alone only at 4 h. The development of resistance to phage alone was associated with enhanced membrane lipid and decreased amino acid biosynthesis in Kp II-503. Notably, cAMP, cGMP and cCMP were significantly enriched (3.1–6.6 log2fold) by phage alone and the combination only at 4 h. This is the first systems pharmacology study to investigate the enhanced bacterial killing by polymyxin-phage combination and provides important mechanistic information on phage killing, resistance and antibiotic-phage combination in K. pneumoniae.

We propose a deep learning framework by the probability of the predicting semantic spatial position distribution for remote sensing image registration. Traditional matching methods optimize similarity metrics with pixel-by-pixel searching, which is time consuming and sensitive to radiometric differences. Driven by learning-based methods, we take the reference and template images as inputs and map them to the semantic distribution position of the corresponding reference image. We apply the affine invariant to obtain a correspondence between the overlap of the barycenter position of the semantic template and the center pixel point, which transforms the semantic boundary alignment into a point-to-point matching problem. Additionally, two loss functions are proposed, one for optimizing the subpixel matching position and the other for determining the semantic spatial probability distribution of the matching template. In this work, we explore the influence of the template radius size, the filling form of training labels, and the weighted combination of loss function on the matching accuracy. Our experiments show that the trained model is robust to template deformation while still operating orders of magnitude faster. Furthermore, our proposed method implements high matching accuracy in four large scene images with radiometric differences. This ensures the improved speed of remote sensing image analysis and pipeline processing while facilitating novel directions in learning-based registration. Our code is freely available at https://github.com/liliangzhi110/semantictemplatematching .

Facing rapid ecological degradation in the Qinghai Tibet Plateau (QTP), the determination of priority areas for conservation (CPAs) based on ecosystem services (ESs) is a key step for nature conservation and sustainable development. However, the trade-off between services makes the plan of maintaining protected areas (PAs) a challenge. In this study, by quantifying a variety of essential ESs in the QTP from 2000 to 2015, we used the multi-criteria ordered weighted average method to balance the trade-offs and determine the key CPAs for ES conservation. We found that the multi-criteria based selection of CPAs leads to higher (1.35) and more balanced ES protection efficiency (PE) than the single strategy. The CPAs obtained based on the logical framework of this paper are mainly located in the southeastern QTP and cover an area of 12.78 % of the QTP (330,124.76 km2). The comprehensive PE of ES was 1.68, and the PE of carbon storage, water yield, soil conservation, and cultural service were 2.20, 2.17, 4.54, and 1.59, respectively. Additionally, compared with the existing PA settings, our results can increase the proportion of biodiversity of amphibians and birds by more than 12 %. The framework of CPAs selection in this paper can provide a reference for the government’s growing nature conservation affairs, which will contribute to sustainable development.

Objective This study aims to investigate the status of fertility preservation (FP) in young breast cancer patients. Materials and methods A clinical database of six women with breast cancer who wished to undergo FP before starting chemotherapy were analyzed between January 2018 and December 2019 in our hospital. Among the six women, three were unmarried and three were married. Results Three patients chose oocyte preservation and obtained 23, 7, and 17 MII oocytes, respectively. One patient chose embryo freezing, and three embryos were frozen. Fertility preservation failed for two patients, one of whom had premature ovulation, while the other patient abandoned egg retrieval on the human chorionic gonadotropin (HCG) day. Conclusion The present results indicate that oocyte and embryo cryopreservation are effective optional methods for young breast cancer patients. However, a lack of knowledge, the urgency of cancer treatment, and financial constraints are causes for a low access rate regarding this process.

This study aimed to analyze the risk factors for stroke-associated pneumonia (SAP) and assess the predictive effect of neutrophil-to-lymphocyte ratio (NLR) on acute SAP.The study included acute stroke patients from April 2018 to June 2019. These patients were divided into the SAP and Non-SAP groups. The patients' history of chronic diseases was assessed, including history of hypertension, diabetes, hyperlipidemia, chronic lung disease, and current smoking status. The clinical characteristics of all studied cases were recorded, including the initial stroke type (cerebral infarction or cerebral hemorrhage), National Institute of Health Stroke Scale (NIHSS) score, indwelling nasogastric tubes, stroke-associated pneumonia within 7 days of hospitalization, and length of hospitalization. The study also recorded the laboratory testing data, including fasting blood glucose, triglyceride, total cholesterol, low-density lipoprotein cholesterol, glycosylated hemoglobin, and high-sensitivity C-reactive protein (hsCRP) as well as white blood cell (WBC), neutrophil, and lymphocyte counts. SPSS 19.0 was used for statistical analysis.A total of 328 eligible acute stroke patients were included. Among all participants, SAP occurred in 64 (19.5%) patients. In the SAP group, the patients were older, the proportion of cerebral hemorrhage was higher, the NIHSS score was higher, and more patients had nasogastric tubes (P 0.05). Concomitantly, the blood glucose, hsCRP, WBC count, neutrophil count, and NLR of the SAP group were significantly higher than those of the Non-SAP group, whereas the lymphocyte count was significantly lower than that of the Non-SAP group (P 0.05). Multivariable analysis of Binary Logistic regression revealed that stroke type (cerebral hemorrhage), indwelling gastric tube, and NLR were independent risk factors for SAP. Receiver operating characteristic curve analysis demonstrated that the area under the curve for the NLR's ability to predict SAP was 0.861. The optimal cutoff threshold, sensitivity, and specificity were 3.745, 0.891, and 0.727, respectively.The risk factors for SAP were multifaceted. Cerebral hemorrhage, indwelling nasogastric tube, and high NLR were independent risk factors. An early NLR had a predictive effect on the occurrence of SAP in patients with acute stroke.

Objectives The objectives of this study were to identify variables associated with dementia and entry into aged residential care (ARC) and derive and validate a risk prediction model for dementia and entry into ARC. Design This was an observational study of prospectively collected Home Care International Residential Assessment Instrument (interRAI-HC) assessment data. Setting and Participants Participants included all people age ≥65 years who had completed an interRAI-HC assessment between July 1, 2012 and June 30, 2018. Exclusion criteria included death or entry into ARC within 30 days of assessment and not living at home at the time of the assessment. Measures InterRAI data from 94,202 older New Zealanders were evaluated for presence or absence of dementia. A multivariable competing-risks model for entry into ARC with death as the competing event was used to estimate subdistribution hazard ratios (SHR). Results In total, there were 18,672 (19.8%) persons with dementia (PWD). PWD were almost twice as likely to enter ARC as persons without dementia [42.8% vs 25.3%; difference 17.5% (95% confidence interval 16.7%‒18.2%)]. PWD at highest risk of entering ARC were those where there was a desire to live elsewhere (SHR 1.44), depression (indicated, SHR 1.15), poor cognitive performance (Cognitive Performance Scale minimal SHR 1.32 and severe plus SHR 1.91), and wandering (SHR 1.19). Factors associated with reduced risks of PWD entering ARC were living with a child or relative, alcohol consumption, and comorbidities. Conclusions and Implications A desire to live elsewhere, social isolation, independent activities of daily living, and depression were independently associated with entry into ARC. Supporting caregivers may improve outcomes for PWD that delay entry into ARC. Future revisions of the interRAI questionnaire could provide more insight on this matter.

Highlights • BAI score of respondents here is higher than those in previous studies with Chinese • Quarantined people presented the highest BAI score and incidence of anxiety • People in high epidemic area showed higher BAI score and incidence of anxiety • All factors impacted respondents’ anxiety level significantly, except gender, Background COVID-19 outbreak happened last December in China and is still continuing. Here, we reported effects of COVID-19 outbreak on the mood of general public and ascertained impacts of psychosocial factors on the plague-related emotional measures. Methods During Feb. 4-6, 2020, a self-reported questionnaire Beck Anxiety Inventory (BAI) was disseminated to general public via Wechat, along with a sociodemographic information sheet. BAI score and incidences of moderate and severe anxiety in subgroups of respondents were compared. Multiple linear and logistic regressions were done for correlation analysis and to identify factors predictive of anxiety. Results Averaged BAI score of all respondents is higher than those of general public in two previous studies. The people quarantined for probable COVID-19 infection presented higher BAI score and incidences of moderate and severe anxiety relative to non-quarantined respondents. People in high epidemic area showed higher BAI score and incidences of moderate and severe anxiety compared to those in low epidemic area. Significant associations existed between anxiety level of the respondents and each of the investigated factors, except for gender. Quarantine was the predictor with a highest OR, followed by divorced/widow. The other factors showed smaller but significant effects on the anxiety level of respondents. Limitations This cross-sectional study was unable to track the emotional changes in the respondents over time. It had a relatively small sample and involved some of emotional measures only. Conclusion These data are of help in planning psychological interventions for the different subpopulations in general public during and after COVID-19 outbreak.

Objectives Pan-drug-resistant (PDR) Pseudomonas aeruginosa is one of the three top-priority pathogens identified by the WHO, and bacteriophages have been investigated as an alternative therapy. However, knowledge on the pharmacokinetics/pharmacodynamics (PK/PD) of phage therapy is sparse, limiting its clinical applications. This study aimed to evaluate the PK/PD of the antipseudomonal phage oPEV20 in vivo following intravenous administration. Methods Healthy Sprague-Dawley rats were given oPEV20 as a single intravenous bolus of ~6, 9 and 11-log10PFU/rat. Arterial blood was sampled over 72 h. At 72 h, the animals were killed and multiple tissues were harvested for biodistribution studies. A PK model was developed using the importance sampling algorithm and deterministic simulations with a PD model were performed. Results A three-compartment model with non-linear clearance described the exposure of oPEV20 in blood. Model evaluation indicated that the model was robust and parameter estimates were accurate. The median (standard error) values of model-predicted PK parameters for VC, VP1, VP2, Q1, Q2, Vm and Km were 111 mL/rat (8.5%), 128 mL/rat (4.97%), 180 mL/rat (4.59%), 30.4 mL/h/rat (19.2%), 538 mL/h/rat (4.97%), 4.39 × 1010 PFU/h/rat (10.2%) and 1.64 × 107 PFU/mL/rat (3.6%), respectively. The distribution of oPEV20 was not homogeneous; there was preferential accumulation in the liver and spleen. Deterministic simulations with a PD model confirmed the importance of the host immune system in facilitating phage-mediated bacterial elimination. Conclusions We developed a robust PK model to describe the disposition of phages in healthy rats. This model may have significant potential in facilitating future preclinical and clinical PK/PD investigations.

Although roots are mainly embedded in the soil, recent studies revealed that light regulates mineral nutrient uptake by roots. However, it remains unclear whether the change in root system architecture in response to different rhizosphere nutrient statuses involves light signaling. Here, we report that blue light regulates primary root growth inhibition under phosphate-deficient conditions through the cryptochromes and their downstream signaling factors. We showed that the inhibition of root elongation by low phosphate requires blue light signal perception at the shoot and transduction to the root. In this process, SPA1 and COP1 play a negative role while HY5 plays a positive role. Further experiments revealed that HY5 is able to migrate from the shoot to root and that the shoot-derived HY5 autoactivates root HY5 and regulates primary root growth by directly activating the expression of LPR1, a suppressor of root growth under phosphate starvation. Taken together, our study reveals a regulatory mechanism by which blue light signaling regulates phosphate deficiency-induced primary root growth inhibition, providing new insights into the crosstalk between light and nutrient signaling.