Statistical groupings of mental and social health measurements correlate with musculoskeletal capability - A cross sectional study.

OBJECTIVE: A better understanding of the degree to which social health factors contribute uniquely to statistical clusters associated with variation in levels of capability might inform targeted whole person care strategies for more comprehensive management of musculoskeletal health. Therefore, we asked: (1) What are the statistical groupings of social and mental health measurements in patients seeking specialty care for musculoskeletal conditions? (2) Do identified psychosocial groupings correspond with different mean magnitudes of incapability accounting for demographic and clinical factors? METHODS: We included 158 patients seeking musculoskeletal specialty care and collected measures of magnitude of incapability, unhelpful thoughts and distress regarding symptoms, symptoms of depression, symptoms of anxiety, and social health. A k-means clustering algorithm was fit to the data and a linear regression model compared mean PROMIS-PF CAT scores for grouping. RESULTS: A quantitative social health measure contributed to 4 statistical clusters as follows: 1) relatively low levels of all mental health measures and high social health; 2) greater unhelpful thoughts and distress regarding symptoms, average symptoms of general anxiety and depression, and average social health; 3) higher levels of all mental health measures and severely compromised social health; and 4) severely compromised mental health and lower social health. Magnitude of incapability was significantly greater for groups with worse mental and social health. CONCLUSION: The finding of a relatively independent association of social and mental health factors with greater incapability supports the importance of introducing comprehensive health strategies in musculoskeletal specialty care. Strategies may include mindset training and case management of social unmet needs. LEVEL OF EVIDENCE: Level III; Cross-sectional study.

Comparison of proactive and conventional treatment of anastomotic leakage in rectal cancer surgery: a multicentre retrospective cohort series.

PURPOSE: Comparative studies on efficacy of treatment strategies for anastomotic leakage (AL) after low anterior resection (LAR) are almost non-existent. This study aimed to compare different proactive and conservative treatment approaches for AL after LAR. METHODS: This retrospective cohort study included all patients with AL after LAR in three university hospitals. Different treatment approaches were compared, including a pairwise comparison of conventional treatment and endoscopic vacuum-assisted surgical closure (EVASC). Primary outcomes were healed and functional anastomosis rates at end of follow-up. RESULTS: Overall, 103 patients were included, of which 59 underwent conventional treatment and 23 EVASC. Median number of reinterventions was 1 after conventional treatment, compared to 7 after EVASC (p < 0.01). Median follow-up was 39 and 25 months, respectively. Healed anastomosis rate was 61% after conventional treatment, compared to 78% after EVASC (p = 0.139). Functional anastomosis rate was higher after EVASC, compared to conventional treatment (78% vs. 54%, p = 0.045). Early initiation of EVASC in the first week after primary surgery resulted in better functional anastomosis rate compared to later initiation (100% vs. 55%, p = 0.008). CONCLUSION: Proactive treatment of AL consisting of EVASC resulted in improved healed and functional anastomosis rates for AL after LAR for rectal cancer, compared to conventional treatment. If EVASC was initiated within the first week after index surgery, a 100% functional anastomosis rate was achievable.

Safety and technical success of diphenhydramine as an alternative local anaesthetic agent for radiology procedures.

AIM: To evaluate retrospectively the safety and technical success of subcutaneous diphenhydramine as an alternative local anaesthetic for radiology procedures. MATERIALS AND METHODS: Between January 2000 and April 2021, 84 image-guided procedures were performed in 81 adult patients (mean age 61 years, 86% female) using 1% injectable diphenhydramine as a local anaesthetic. Indications were history of severe allergy to "-caine" local anaesthetics in 76 (90%) patients and recent administration of bupivacaine liposomal injectable suspension in eight (10%) patients. Twelve of the 84 (14%) procedures were performed with concomitant moderate sedation. Patient characteristics, procedural techniques, and clinical outcomes were reviewed. Early and delayed (30-day) complications were classified as either related to local diphenhydramine injection or to the procedure itself. Procedure-related complications were gradated using the Clavien-Dindo system. RESULTS: Percutaneous biopsy was the most frequently performed procedure (57/84, 67%). Fifty-nine (70%) of the 84 procedures were ultrasound guided. The most common procedural site was the breast (34/84, 40%). All procedures were technically successful. There were two minor injection-related complications related to post-procedural pain. A single minor procedure-related complication involved a patient requiring hospital admission for post-renal biopsy related haematuria. CONCLUSION: Injectable diphenhydramine appears to be a safe and effective local anaesthetic alternative in patients with "-caine" class contraindications undergoing radiology procedures. A future prospective trial would be useful to assess the safety profile in an large cohort of patients.

The InSight HP3 Penetrator (Mole) on Mars: Soil Properties Derived from the Penetration Attempts and Related Activities.

The NASA InSight Lander on Mars includes the Heat Flow and Physical Properties Package HP3 to measure the surface heat flow of the planet. The package uses temperature sensors that would have been brought to the target depth of 3-5 m by a small penetrator, nicknamed the mole. The mole requiring friction on its hull to balance remaining recoil from its hammer mechanism did not penetrate to the targeted depth. Instead, by precessing about a point midway along its hull, it carved a 7 cm deep and 5-6 cm wide pit and reached a depth of initially 31 cm. The root cause of the failure - as was determined through an extensive, almost two years long campaign - was a lack of friction in an unexpectedly thick cohesive duricrust. During the campaign - described in detail in this paper - the mole penetrated further aided by friction applied using the scoop at the end of the robotic Instrument Deployment Arm and by direct support by the latter. The mole tip finally reached a depth of about 37 cm, bringing the mole back-end 1-2 cm below the surface. It reversed its downward motion twice during attempts to provide friction through pressure on the regolith instead of directly with the scoop to the mole hull. The penetration record of the mole was used to infer mechanical soil parameters such as the penetration resistance of the duricrust of 0.3-0.7 MPa and a penetration resistance of a deeper layer ( > 30 cm depth) of 4.9 ± 0.4 MPa . Using the mole's thermal sensors, thermal conductivity and diffusivity were measured. Applying cone penetration theory, the resistance of the duricrust was used to estimate a cohesion of the latter of 2-15 kPa depending on the internal friction angle of the duricrust. Pushing the scoop with its blade into the surface and chopping off a piece of duricrust provided another estimate of the cohesion of 5.8 kPa. The hammerings of the mole were recorded by the seismometer SEIS and the signals were used to derive P-wave and S-wave velocities representative of the topmost tens of cm of the regolith. Together with the density provided by a thermal conductivity and diffusivity measurement using the mole's thermal sensors, the elastic moduli were calculated from the seismic velocities. Using empirical correlations from terrestrial soil studies between the shear modulus and cohesion, the previous cohesion estimates were found to be consistent with the elastic moduli. The combined data were used to derive a model of the regolith that has an about 20 cm thick duricrust underneath a 1 cm thick unconsolidated layer of sand mixed with dust and above another 10 cm of unconsolidated sand. Underneath the latter, a layer more resistant to penetration and possibly containing debris from a small impact crater is inferred. The thermal conductivity increases from 14 mW/m K to 34 mW/m K through the 1 cm sand/dust layer, keeps the latter value in the duricrust and the sand layer underneath and then increases to 64 mW/m K in the sand/gravel layer below. Supplementary Information: The online version contains supplementary material available at 10.1007/s11214-022-00941-z.

SARS-CoV-2 monitoring at three sewersheds of different scales and complexity demonstrates distinctive relationships between wastewater measurements and COVID-19 case data.

Wastewater monitoring of SARS-CoV-2 presents a means of tracking COVID-19 community infection dynamics on a broader geographic scale. However, accounting for environmental and sample-processing losses may be necessary for wastewater measurements to readily inform our understanding of infection prevalence. Here, we present measurements of the SARS-CoV-2 N1 and N2 gene targets from weekly wastewater samples at three sites in Hamilton County, Ohio, during an increase and subsequent decline of COVID-19 infections. The concentration of N1 or N2 RNA in wastewater, measured over the course of six months, ranged from below the detection limit to over 104 gene copies/l, and correlated with case data at two wastewater treatment plants, but not at a sub-sewershed-level sampling site. We also evaluated the utility of a broader range of variables than has been reported consistently in previous work, in improving correlations of SARS-CoV-2 concentrations with case data. These include a spiked matrix recovery control (OC43), flow-normalization, and assessment of fecal loading using endogenous fecal markers (HF183, PMMoV, crAssphage). We found that adjusting for recovery, flow, and fecal indicators increased these correlations for samples from a larger sewershed (serving ~488,000 people) with greater industrial and stormwater inputs, but raw N1/N2 concentrations corresponded better with case data at a smaller, residential-oriented sewershed. Our results indicate that the optimal adjustment factors for correlating wastewater and clinical case data moving forward may not be generalizable to all sewersheds.

Human- and infrastructure-associated bacteria in greywater.

Greywater, the wastewater from sinks, showers and laundry, is an understudied environment for bacterial communities. Most greywater studies focus on quantifying pathogens, often via proxies used in other wastewater, like faecal indicator bacteria; there is a need to identify more greywater-appropriate surrogates, like Staphylococcus sp. Sequencing-based studies have revealed distinct communities in different types of greywater as well as in different parts of greywater infrastructure, including biofilms on pipes, holding tanks and filtration systems. The use of metagenomic sequencing provides high resolution on both the taxa and genes present, which may be of interest in cases like identifying pathogens and surrogates relevant to different matrices, monitoring antibiotic resistance genes and understanding metabolic processes occurring in the system. Here, we review what is known about bacterial communities in different types of greywater and its infrastructure. We suggest that wider adoption of environmental sequencing in greywater research is important because it can describe the entire bacterial community along with its metabolic capabilities, including pathways for removal of nutrients and organic materials. We briefly describe a metagenomic dataset comparing different types of greywater samples in a college dormitory building to highlight the type of questions these methods can address. Metagenomic sequencing can help further the understanding of greywater treatment for reuse because it allows for identification of new pathogens or genes of concern.

Twenty-first century molecular methods for analyzing antimicrobial resistance in surface waters to support One Health assessments.

Antimicrobial resistance (AMR) in the environment is a growing global health concern, especially the dissemination of AMR into surface waters due to human and agricultural inputs. Within recent years, research has focused on trying to understand the impact of AMR in surface waters on human, agricultural and ecological health (One Health). While surface water quality assessments and surveillance of AMR have historically utilized culture-based methods, culturing bacteria has limitations due to difficulty in isolating environmental bacteria and the need for a priori information about the bacteria for selective isolation. The use of molecular techniques to analyze AMR at the genetic level has helped to overcome the difficulties with culture-based techniques since they do not require advance knowledge of the bacterial population and can analyze uncultivable environmental bacteria. The aim of this review is to provide an overview of common contemporary molecular methods available for analyzing AMR in surface waters, which include high throughput real-time polymerase chain reaction (HT-qPCR), metagenomics, and whole genome sequencing. This review will also feature how these methods may provide information on human and animal health risks. HT-qPCR works at the nanoliter scale, requires only a small amount of DNA, and can analyze numerous gene targets simultaneously, but may lack in analytical sensitivity and the ability to optimize individual assays compared to conventional qPCR. Metagenomics offers more detailed genomic information and taxonomic resolution than PCR by sequencing all the microbial genomes within a sample. Its open format allows for the discovery of new antibiotic resistance genes; however, the quantity of DNA necessary for this technique can be a limiting factor for surface water samples that typically have low numbers of bacteria per sample volume. Whole genome sequencing provides the complete genomic profile of a single environmental isolate and can identify all genetic elements that may confer AMR. However, a main disadvantage of this technique is that it only provides information about one bacterial isolate and is challenging to utilize for community analysis. While these contemporary techniques can quickly provide a vast array of information about AMR in surface waters, one technique does not fully characterize AMR nor its potential risks to human, animal, or ecological health. Rather, a combination of techniques (including both molecular- and culture-based) are necessary to fully understand AMR in surface waters from a One Health perspective.

Characterization of the relative importance of human- and infrastructure-associated bacteria in grey water: a case study.

AIMS: Development of efficacious grey water (GW) treatment systems would benefit from detailed knowledge of the bacterial composition of GW. Thus, the aim of this study was to characterize the bacterial composition from (i) various points throughout a GW recycling system that collects shower and sink handwash (SH) water into an equalization tank (ET) prior to treatment and (ii) laundry (LA) water effluent of a commercial-scale washer. METHODS AND RESULTS: Bacterial composition was analysed by high-throughput pyrosequencing of the 16S rRNA gene. LA was dominated by skin-associated bacteria, with Corynebacterium, Staphylococcus, Micrococcus, Propionibacterium and Lactobacillus collectively accounting for nearly 50% of the total sequences. SH contained a more evenly distributed community than LA, with some overlap (e.g. Propionibacterium), but also contained distinct genera common to wastewater infrastructure (e.g. Zoogloea). The ET contained many of these same wastewater infrastructure-associated bacteria, but was dominated by genera adapted for anaerobic conditions. CONCLUSIONS: The data indicate that a relatively consistent set of skin-associated genera are the dominant human-associated bacteria in GW, but infrastructure-associated bacteria from the GW collection system and ET used for transient storage will be the most common bacteria entering GW treatment and reuse systems. SIGNIFICANCE AND IMPACT OF THE STUDY: This study is the first to use high-throughput sequencing to identify the bacterial composition of various GW sources.

Detection of multiple waterborne pathogens using microsequencing arrays.

AIMS: A microarray was developed to simultaneously detect Cryptosporidium parvum, Cryptosporidium hominis, Enterococcus faecium, Bacillus anthracis and Francisella tularensis in water. METHODS AND RESULTS: A DNA microarray was designed to contain probes that specifically detected C. parvum, C. hominis, Ent. faecium, B. anthracis and F. tularensis. The microarray was then evaluated with samples containing target and nontarget DNA from near-neighbour micro-organisms, and tap water spiked with multiple organisms. Results demonstrated that the microarray consistently detected Ent. faecium, B. anthracis, F. tularensis and C. parvum when present in samples. Cryptosporidium hominis was only consistently detected through the use of shared probes between C. hominis and C. parvum. CONCLUSIONS: This study successfully developed and tested a microarray-based assay that can specifically detect faecal indicator bacteria and human pathogens in tap water. SIGNIFICANCE AND IMPACT OF THE STUDY: The use of indicator organisms has become a practical solution for monitoring for water quality. However, they do not always correlate well with the presence of many microbial pathogens, thus necessitating direct monitoring for most pathogens. This microarray can be used to simultaneously detect multiple organisms in a single sample. More importantly, it can provide occurrence information that may be used in assessing potential exposure risks to waterborne pathogens.