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Gaoshiti-moxi block of Anyue Gas field is a highly heterogeneous carbonate gas reservoir with low porosity and low permeability. According to the production dynamic data, deng4 gas reservoir in Gaoshiti-Moxi block is blocked to some extent. Combined with reservoir parameters, productivity parameters, gas well production curve, RTA analysis and other means, the cause of plugging in special single well was analyzed. Through various experiments, the composition of the plugging material is analyzed, and the formation mechanism of the plugging material is deduced, which provides a reference for the later gas field development and the research of plugging measures.

Background The prevention of type 2 diabetes is challenging due to the variable effects of risk factors at an individual level. Data-driven methods could be useful to detect more homogeneous groups based on risk factor variability. The aim of this study was to derive characteristic phenotypes using cluster analysis of common risk factors and to assess their utility to stratify the risk of type 2 diabetes. Methods Data on 7317 diabetes-free adults from Sweden were used in the main analysis and on 2332 diabetes-free adults from Mexico for external validation. Clusters were based on sex, family history of diabetes, educational attainment, fasting blood glucose and insulin levels, estimated insulin resistance and β-cell function, systolic and diastolic blood pressure, and BMI. The risk of type 2 diabetes was assessed using Cox proportional hazards models. The predictive accuracy and long-term stability of the clusters were then compared to different definitions of prediabetes. Results Six risk phenotypes were identified independently in both cohorts: very low-risk (VLR), low-risk low β-cell function (LRLB), low-risk high β-cell function (LRHB), high-risk high blood pressure (HRHBP), high-risk β-cell failure (HRBF), and high-risk insulin-resistant (HRIR). Compared to the LRHB cluster, the VLR and LRLB clusters showed a lower risk, while the HRHBP, HRBF, and HRIR clusters showed a higher risk of developing type 2 diabetes. The high-risk clusters, as a group, had a better predictive accuracy than prediabetes and adequate stability after 20 years. Conclusions Phenotypes derived using cluster analysis were useful in stratifying the risk of type 2 diabetes among diabetes-free adults in two independent cohorts. These results could be used to develop more precise public health interventions.

Subspecialization of adrenal surgery through regionalization has not been adequately evaluated. We assessed implementation of subspecialization and the association of regionalization with adrenalectomy outcomes in a community-based setting. In this longitudinal retrospective cohort study, we used an interrupted time series analysis on consecutive adrenal surgeries at Kaiser Permanente Northern California, 2010–2019. The intervention was regionalization of surgery in 2016. Main outcomes include surgical volumes, operative time, length of stay, 30-day return-to-care, and 30-day complications obtained from the electronic medical record. t-Tests and multivariable models were used to analyze time trends in outcomes after accounting for changes in patient and disease characteristics. In total, 850 adrenal surgery cases were eligible. Between 2010 and 2019, the annual incidence of surgery (per 100,000 persons) increased from 2.4 (95% CI 1.9–3.1) to 4.1 (95% CI 3.5–4.8). Average annual surgeon volume increased from 2.4 (95% CI 1.6–3.1) to 9.9 (95% CI 4.9–14.9), while hospital volume increased from 3.5 (95% CI 2.3–4.6) to 15.4 (95% CI 6.9–24.0). Operative time was 34 (23–45) min faster in 2018–2019 compared with 2010–2011. After regionalization, same-day discharges increased to 64% in 2019 (p < 0.0001). The frequency of return-to-care (p = 0.69) and the overall complication rate (p = 0.31) did not change. Regionalizing adrenal surgery through surgical subspecialization and standardized care pathways was feasible and decreased operative time, and hospital stay, while increasing the frequency of same-day discharges without increasing return-to-care or complications.

The intervertebral disc is a complex structure that experiences multiaxial stresses regularly. Disc failure through herniation is a common cause of lower back pain, which causes reduced mobility and debilitating pain, resulting in heavy socioeconomic burdens. Unfortunately, herniation etiology is not well understood, partially due to challenges in replicating herniation in vitro. Previous studies suggest that flexion elevated risks of herniation. Thus, the objective of this study was to use a multiscale and multiphasic finite element model to evaluate the risk of failure under torque- or muscle-driven flexion. Models were developed to represent torque-driven flexion with the instantaneous center of rotation (ICR) located on the disc, and the more physiologically representative muscle-driven flexion with the ICR located anterior of the disc. Model predictions highlighted disparate disc mechanics regarding bulk deformation, stress-bearing mechanisms, and intradiscal stress–strain distributions. Specifically, failure was predicted to initiate at the bone-disc boundary under torque-driven flexion, which may explain why endplate junction failure, instead of herniation, has been the more common failure mode observed in vitro. By contrast, failure was predicted to initiate in the posterolateral annulus fibrosus under muscle-driven flexion, resulting in consistent herniation. Our findings also suggested that muscle-driven flexion combined with axial compression could be sufficient for provoking herniation in vitro and in silico. In conclusion, this study provided a computational framework for designing in vitro testing protocols that can advance the assessment of disc failure behavior and the performance of engineered disc implants.

Subspecialization of adrenal surgery through regionalization has not been adequately evaluated. We assessed implementation of subspecialization and the association of regionalization with adrenalectomy outcomes in a community-based setting.In this longitudinal retrospective cohort study, we used an interrupted time series analysis on consecutive adrenal surgeries at Kaiser Permanente Northern California, 2010-2019. The intervention was regionalization of surgery in 2016. Main outcomes include surgical volumes, operative time, length of stay, 30-day return-to-care, and 30-day complications obtained from the electronic medical record. t-Tests and multivariable models were used to analyze time trends in outcomes after accounting for changes in patient and disease characteristics.In total, 850 adrenal surgery cases were eligible. Between 2010 and 2019, the annual incidence of surgery (per 100,000 persons) increased from 2.4 (95% CI 1.9-3.1) to 4.1 (95% CI 3.5-4.8). Average annual surgeon volume increased from 2.4 (95% CI 1.6-3.1) to 9.9 (95% CI 4.9-14.9), while hospital volume increased from 3.5 (95% CI 2.3-4.6) to 15.4 (95% CI 6.9-24.0). Operative time was 34 (23-45) min faster in 2018-2019 compared with 2010-2011. After regionalization, same-day discharges increased to 64% in 2019 (p0.0001). The frequency of return-to-care (p = 0.69) and the overall complication rate (p = 0.31) did not change.Regionalizing adrenal surgery through surgical subspecialization and standardized care pathways was feasible and decreased operative time, and hospital stay, while increasing the frequency of same-day discharges without increasing return-to-care or complications.

Background Type 2 diabetes (T2D) is an important cause of mortality, disability and health care expenditures. Prevention is crucial to counter global trends, but individual variability of different risk factors leading to T2D has made prevention difficult to achieve. We aimed to identify clusters of individuals based on individual level characteristics of different risk factors using a data driven approach. Methods We used data from the Stockholm Diabetes Prevention Program. A population-based, prospective study. Healthy participants who were born in Sweden and aged 35 to 55 years old were recruited between 1992 and 1998 and followed up after 10 and 20 years. At each visit, participants answered extensive questionnaires, anthropometric measures, laboratory examinations and an oral glucose tolerance test. We used age, sex, family history of diabetes, fasting and two hours glucose and insulin, body mass index (BMI), systolic and diastolic blood pressure, and level of education were at baseline to group participants using the k-prototype algorithm. We then examined the risk of diabetes between clusters using survival analysis. Results A total of 7,173 participants representing 138,942 person years of follow-up were included in this study. Among them, 998 (14%) developed T2D. We identified six stable clusters: the group with the lowest cumulative incidence of T2D (2.3%) was used as reference (n = 1,265). In the group with the highest risk, 47% developed T2D (n = 772, HR 26.3, 95%CI 17.9-38.5) followed by 17.1% (n = 1,146, HR 7.6, 95%CI 5.1-11.22), 15.2% (n = 1,453, HR 6.7, 95%CI 4.5-9.8), 9.5% (n = 1,384, HR 4.1, 95%CI 2.8-6.2) and 5.2% (n = 1,157, HR 2.0, 95%CI 1.3-3.1) in the remaining groups. Conclusions There is important variability between individuals regarding the effect of different risk factors on the incidence of T2D. Data driven categorization strategies can be useful epidemiological tools to pave the way for more precise T2D intervention programs. Key messages Prevention strategies for T2D usually follow a one-size fits all approach, ignoring the important variability of risk factors and their consequences among individuals. It is possible to identify subgroups of people with different risk of T2D based on simple clinical and phenotypical characteristics, and could help to improve prevention and treatment of T2D.

A comprehensive understanding of biological tissue mechanics is crucial for designing engineered tissues that aim to recapitulate native tissue behavior. Tensile mechanics of many fiber-reinforced tissues have been shown to depend on specimen geometry, which makes it challenging to compare data between studies. In this study, a validated multiscale, structure-based finite element model was used to evaluate the effect of specimen geometry on multiscale annulus fibrosus tensile mechanics through a fiber engagement analysis. The relationships between specimen geometry and modulus, Poisson's ratio, tissue stress-strain distributions, and fiber reorientation behaviors were investigated at both tissue and sub-tissue levels. It was observed that annulus fibrosus tissue level tensile properties and stress transmission mechanisms were dependent on specimen geometry. The model also demonstrated that the contribution of fiber-matrix interactions to tissue mechanical response was specimen size- and orientation-dependent. The results of this study reinforce the benefits of structure-based finite element modeling in studies investigating multiscale tissue mechanics. This approach also provides guidelines for developing optimal combined computational-experimental study designs for investigating fiber-reinforced biological tissue mechanics. Additionally, findings from this study help explain the geometry dependence of annulus fibrosus tensile mechanics previously reported in the literature, providing a more fundamental and comprehensive understanding of tissue mechanical behavior. In conclusion, the methods presented here can be used in conjunction with experimental tissue level data to simultaneously investigate tissue and sub-tissue scale mechanics, which is important as the field of soft tissue biomechanics advances toward studies that focus on diminishing length scales.

Precise control of tissue water content is essential for ensuring accurate, repeatable, and physiologically relevant measurements of tissue mechanics and biochemical composition. While previous studies have found that saline and polyethylene glycol (PEG) blends were effective at controlling tendon and ligament hydration levels, this work has yet to be extended to the annulus fibrosus (AF). Thus, the first objective of this study was to determine and validate an optimal buffer solution for targeting and maintaining hydration levels of tissue-level AF specimens in vitro. This was accomplished by measuring the transient swelling behavior of bovine AF specimens in phosphate-buffered saline (PBS) and PEG buffers across a wide range of concentrations. Sub-failure, failure, and post-failure mechanics were measured to determine the relationship between changes in tissue hydration and tensile mechanical response. The effect of each buffer solution on tissue composition was also assessed. The second objective of this study was to assess the feasibility and effectiveness of using multi-phasic finite element models to investigate tissue swelling and mechanical responses in different external buffer solutions. A solution containing 6.25%w/v PBS and 6.25%w/v PEG effectively maintained tissue-level AF specimen hydration at fresh-frozen levels after 18 h in solution. Modulus, failure stress, failure strain, and post-failure toughness of specimens soaked in this solution for 18 h closely matched those of fresh-frozen specimens. In contrast, specimens soaked in 0.9%w/v PBS swelled over 100% after 18 h and exhibited significantly diminished sub-failure and failure properties compared to fresh-frozen controls. The increased cross-sectional area with swelling contributed to but was not sufficient to explain the diminished mechanics of PBS-soaked specimens, suggesting additional sub-tissue scale mechanisms. Computational simulations of these specimens generally agreed with experimental results, highlighting the feasibility and importance of including a fluid-phase description when models aim to provide accurate predictions of biological tissue responses. As numerous previous studies suggest that tissue hydration plays a central role in maintaining proper mechanical and biological function, robust methods for controlling hydration levels are essential as the field advances in probing the relationship between tissue hydration, aging, injury, and disease.

Intervertebral disc research has sought to develop a deeper understanding of spine biomechanics, the complex relationship between disc health and back pain, and the mechanisms of spinal injury and repair. To do so, many researchers have focused on characterizing tissue-level properties of the disc, where the roles of tissue subcomponents can be more systematically investigated. Unfortunately, experimental challenges often limit the ability to measure important disc tissue- and subtissue-level behaviors, including fiber–matrix interactions, transient nutrient and electrolyte transport, and damage propagation. Numerous theoretical and numerical modeling frameworks have been introduced to explain, complement, guide, and optimize experimental research efforts. The synergy of experimental and computational work has significantly advanced the field, and these two aspects have continued to develop independently and jointly. Meanwhile, the relationship between experimental and computational work has become increasingly complex and interdependent. This has made it difficult to interpret and compare results between experimental and computational studies, as well as between solely computational studies. This paper seeks to explore issues of model translatability, robustness, and efficient study design, and to propose and motivate potential future directions for experimental, computational, and combined tissue-level investigations of the intervertebral disc.

Bovine caudal discs have been widely used in spine research due to their increased availability, large size, and mechanical and biochemical properties that are comparable to healthy human discs. However, despite their extensive use, the radial variations in bovine disc composition have not yet been rigorously quantified with high spatial resolution. Previous studies were limited to qualitative analyses or provided limited spatial resolution in biochemical properties. Thus, the main objective of this study was to provide quantitative measurements of biochemical composition with higher spatial resolution than previous studies that employed traditional biochemical techniques. Specifically, traditional biochemical analyses were used to measure water, sulfated glycosaminoglycan, collagen, and DNA contents. Gravimetric water content was compared to data obtained through Raman spectroscopy and differential scanning calorimetry. Additionally, spatial distribution of lipids in the disc's collagen network was visualized and quantified, for the first time, using multi‐modal second harmonic generation (SHG) and Coherent anti‐Stokes Raman (CARS) microscopy. Some heterogeneity was observed in the nucleus pulposus, where the water content and water‐to‐protein ratio of the inner nucleus were greater than the outer nucleus. In contrast, the bovine annulus fibrosus exhibited a more heterogeneous distribution of biochemical properties. Comparable results between orthohydroxyproline assay and SHG imaging highlight the potential benefit of using SHG microscopy as a less destructive method for measuring collagen content, particularly when relative changes are of interest. CARS images showed that lipid deposits were distributed equally throughout the disc and appeared either as individual droplets or as clusters of small droplets. In conclusion, this study provided a more comprehensive assessment of spatial variations in biochemical composition of the bovine caudal disc.

Tears in the annulus fibrosus (AF) of the intervertebral disk can result in disk herniation and progressive degeneration. Understanding AF failure mechanics is important as research moves toward developing biological repair strategies for herniated disks. Unfortunately, failure mechanics of fiber-reinforced tissues, particularly tissues with fibers oriented off-axis from the applied load, is not well understood, partly due to the high variability in reported mechanical properties and a lack of standard techniques ensuring repeatable failure behavior. Therefore, the objective of this study was to investigate the effectiveness of midlength (ML) notch geometries in producing repeatable and consistent tissue failure within the gauge region of AF mechanical test specimens. Finite element models (FEMs) representing several notch geometries were created to predict the location of bulk tissue failure using a local strain-based criterion. FEM results were validated by experimentally testing a subset of the modeled specimen geometries. Mechanical testing data agreed with model predictions (∼90% agreement), validating the model's predictive power. Two of the modified dog-bone geometries (“half” and “quarter”) effectively ensured tissue failure at the ML for specimens oriented along the circumferential-radial and circumferential-axial directions. The variance of measured mechanical properties was significantly lower for notched samples that failed at the ML, suggesting that ML notch geometries result in more consistent and reliable data. In addition, the approach developed in this study provides a framework for evaluating failure properties of other fiber-reinforced tissues, such as tendons and meniscus.

Background Breast-specific gamma imaging (BSGI) has brought scintimammography back to the forefront by using a dedicated small field-of-view system designed to detect and localize lesions down to 2 mm. Initial studies have reported sensitivity equaling that of magnetic resonance imaging, but with improved specificity. We reviewed our initial experience to evaluate the impact of this technology at our community breast center. Methods We performed a retrospective review of the initial 176 patients who underwent BSGI. Results A total of 128 patients underwent BSGI because of suspicious imaging, abnormal physical examination, or high risk with dense breasts. BSGI was positive in 12 of 107 patients with breast imaging reporting and data system (BI-RADS) 1, 2, or 3. Two of these were cancer. Of the 21 patients with BI-RADS 4, 18 were BSGI negative (11 with benign biopsy, 7 observed), and 3 were BSGI positive with 2 being cancer. Forty-eight patients with a new diagnosis of cancer obtained BSGI for further work-up. It was positive at a new location in 6 cases: 2 cases were new cancers in the contralateral breast, 1 was in the ipsilateral breast, and the remaining 3 had benign pathology. Of the 176 initial patients, clinical management was changed significantly in 14.2%, with another 6.3% in whom a negative BSGI could have prevented a biopsy. Conclusions BSGI has played an important role in our clinical management of breast patients with complex breast tissue. BSGI is also a good adjunctive imaging tool in the work-up of newly diagnosed breast cancer patients.

Nutrients have traditionally been viewed as a means to provide basic calories to sustain homeostasis. However, critically ill, surgical, and trauma patients are in a constant dynamic state between systemic inflammatory response (SIRS) and compensatory anti-inflammatory response (CARS). Results from ongoing research strongly support the use of specific nutrients to modulate the immune and/or metabolic response. These agents can now be considered therapeutic tools in the management of complex hypermetabolic diseases. The principle of using nutrients as a therapeutic strategy rather than just as "nutritional support" requires a shift in the current dogma. The most common nutrients found in currently available enteral immune-modulating formulas are omega-3 fatty acids (eicosapentaenoic acid and docosahexaenoic acid), antioxidants, nucleotides, glutamine, and arginine. Multiple individual reports and at least five meta-analyses using combinations of immune-modulating nutrients have reported almost uniform beneficial results. However, certain conflicting hypotheses continue to revolve around the use of arginine in septic patients.

The use of photography and video recording is common place in healthcare. Before and after photos are necessities and required in plastic surgery, intraoperative videos of laparoscopic procedures are routinely used for teaching and seminars, families often record the birth of a child.

BACKGROUND: Breast-specific gamma imaging (BSGI) is a functional imaging modality that has comparable sensitivity but superior specificity compared with magnetic resonance imaging, yielding fewer false-positive results and thereby improving clinical management of the newly diagnosed breast cancer patient. METHODS: A retrospective review was performed from 2 community-based breast imaging centers of newly diagnosed breast cancer patients in whom BSGI was performed as part of the imaging work-up. RESULTS: A total of 138 patients (69 invasive ductal carcinoma, 20 invasive lobular carcinoma, 32 ductal carcinoma in situ, and 17 mixtures of invasive ductal carcinoma, invasive lobular carcinoma, or ductal carcinoma in situ and other) were reviewed. Twenty-five patients (18.1%) had a positive BSGI study at a site remote from their known cancer or more extensive disease than detected from previous imaging. Fifteen patients (10.9%) were positive for a synchronous or more extensive malignancy in the same or contralateral breast. Five patients had benign findings on pathology, 5 benign on ultrasound follow-up (false-positive rate, 7.2%). Findings converted 7 patients to mastectomy, 1 patient to neoadjuvant chemotherapy, and 7 patients were found to have previously undetected contralateral cancer. The positive predictive value for BSGI was 92.9%. CONCLUSIONS: BSGI detected additional or more extensive malignancy in the same or contralateral breast in 10.9% of newly diagnosed breast cancer patients. Only 7.2% incurred an additional work-up. BSGI provides accurate evaluation of remaining breast tissue in newly diagnosed breast cancer patients with few false-positive readings.

Spontaneous infection with Clostridium septicum (C. septicum) is rare, but when isolated it is commonly associated with malignancy. We report a case of a 47-year-old man with infected pancreatic necrosis involving greater than 80% of the pancreas, transmural gastric necrosis, and liquefaction necrosis of the spleen. Initial cultures revealed C. septicum infection. He was managed with prompt aggressive surgical debridement, resection, appropriate broad spectrum antibiotics, and early enteral nutrition.

Arginine is a nonessential amino acid in the normal physiological state that becomes conditionally essential during periods of hypermetabolic stress. Recent literature supports the hypothesis that arginine plays an important role in the intermediary metabolism of the critically ill patient. Current critical care literature is conflicting on arginine use in the clinical setting, with some proposing it as a panacea, whereas others report it as poison. Multiple individual reports and at least 5 major meta-analyses using combinations of immune-modulating nutrients have reported mostly beneficial results, but few have evaluated the effects of arginine when given as a single supplemental nutrient. This review attempts to objectively analyze the literature and evaluate the potential role of arginine in the critical care setting.