Nevin Manimala

Altern Ther Health Med. 2022 Sep 9:AT7466. Online ahead of print.

ABSTRACT

OBJECTIVE: To evaluate the effect of the Milch technique on quality of life (QoL) in patients with anterior dislocation of the shoulder joint.

METHODS: A total of 126 patients undergoing manual reduction for anterior dislocation of the shoulder in our hospital from January 2021 to January 2022 were prospectively enrolled in this study. The randomized number table method was used to divide patients into the study group (63 patients) and the control group (63 patients). The study group was treated with a modified Milch technique while the control group was treated with the Hippocratic method. Success rate and complications were compared to evaluate the effectiveness of manual reduction. Clinical assessment of shoulder function included the Constant-Murley Score and visual analog scale (VAS) before, during and after manual reduction.

RESULTS: The success rate of primary and secondary reduction in the study group was significantly higher than in the control group (87.30% vs 61.90, respectively; P = .001; 11.11% vs 25.40%, respectively; P = .038). The failure rate in the study group was significantly lower than in the control group (1.59% vs 12.70%, respectively; P = .015). The time required for reduction in the study and control groups was 58.87 ± 7.92 seconds and 93.09 ± 8.01 seconds, respectively; a significant difference (t = -24.113; P < .001). There was no statistically significant difference in VAS scores before and during reduction in the 2 groups. After reduction, VAS scores in the study group were significantly lower than in the control group (1.02 ± 0.01 vs 1.14 ± 0.26, respectively; P < .001). There were no significant differences in pain level, activities of daily living, joint range of motion or muscle strength between the 2 groups before and after reduction (P > .05). After reduction, health status, emotional function, mental health, physiological function, physiological function, physical pain, vitality and social function scores in the study group were significantly higher than in the control group (P < .05). There were 4 avulsion fractures and 2 humeral fractures in the control group; no complications occurred in the study group, with a significant difference (χ2 = 6.289; P = .012).

CONCLUSION: The Milch technique can improve the QoL in patients with anterior dislocation of the shoulder, and the success rate of the reduction is high.

PMID:36074960

J Cell Physiol. 2022 Sep 8. doi: 10.1002/jcp.30872. Online ahead of print.

ABSTRACT

The high level of progesterone and 17β-estradiol ratio (P4/E2) in follicular fluid has been considered as a biomarker of follicular atresia. CYP11A1, the crucial gene encoding the rate-limiting enzyme for steroid hormone synthesis, has been reported differently expressed in the ovary during follicular atresia. However, the regulation mechanism of CYP11A1 expression during follicular atresia still remains unclear. Here, we have demonstrated that lnc2300, a novel pig ovary-specific highly expressed cis-acting long noncoding RNA (lncRNA) transcribed from chromosome 7, has the ability to induce the expression of CYP11A1 and inhibit the apoptosis of porcine granulosa cells (GCs). Mechanistically, lnc2300, mainly located in the cytoplasm of porcine GCs, sponges and suppresses the expression of miR-365-3p through acting as a competing endogenous RNA (ceRNA), which further relieves the inhibitory effects of miR-365-3p on the expression of CYP11A1. Besides, CYP11A1 is validated as a direct functional target of miR-365-3p in porcine GCs. Functionally, lnc2300 is an antiapoptotic lncRNA that reduces porcine GC apoptosis by inhibiting the proapoptotic function of miR-365-3p. In summary, our findings reveal a cis-acting regulation mechanism of CYP11A1 through lncRNA, and define a novel signaling pathway, lnc2300/miR-365-3p/CYP11A1 axis, which is involved in the regulation of GC apoptosis and follicular atresia.

PMID:36074900 | DOI:10.1002/jcp.30872

J Feline Med Surg. 2022 Sep 8:1098612X221114851. doi: 10.1177/1098612X221114851. Online ahead of print.

ABSTRACT

OBJECTIVES: The aim of our study was to describe a biomechanical testing protocol to reproduce ex vivo craniodorsal hip luxation specific to the feline model, and evaluate the biomechanical properties of an intact hip joint compared with the fixation strength of two different techniques of extra-articular hip stabilisation.

METHODS: Eighteen hip joints (femur and hemipelvis) were harvested from nine mature feline cadavers. CT was performed for each hip joint so that a biomechanical base specific to each joint morphotype could be created using computer-aided design. The biomechanical bases were then produced using a three-dimensional printer to secure the hip joints during testing. A total of 34 biomechanical compression tests were performed. Eighteen compression tests were performed in the control group, of which two fractured. The remaining 16 hip joints were then randomly assigned either to group A (hip joints stabilised with an extra-articular ultra-high molecular weight polyethylene (UHMWPE) implant secured by an interference screw [n = 8]) or to group B (hip joints stabilised with a UHMWPE iliofemoral suture [n = 8]).

RESULTS: Mean ± SD yield, failure load and linear stiffness in the control group were 616 ± 168 N, 666 ± 158 N and 231 ± 50 N/mm, respectively. The relative fixation strength (% of intact joint) before hip luxation in groups A and B was 43.8% and 34.7%, respectively. No statistical difference was found between groups A and B for yield and failure load. However, the reoccurrence of craniodorsal hip luxation was higher in group B than in group A, in 5/8 and 0/8 tests, respectively. Moreover, in group A, the extra-articular UHMWPE implant induced caudodorsal hip luxation, reported as failure mode in 7/8 cases.

CONCLUSIONS AND RELEVANCE: This modified biomechanical protocol for testing craniodorsal hip luxation in a feline model was validated as repeatable and with acceptable variance. The extra-articular UHMWPE implant stabilisation technique proved to be more efficient in avoiding reoccurrence of craniodorsal hip luxation than UHMWPE iliofemoral suture.

PMID:36074899 | DOI:10.1177/1098612X221114851

IEEE Trans Pattern Anal Mach Intell. 2022 Sep 8;PP. doi: 10.1109/TPAMI.2022.3205036. Online ahead of print.

ABSTRACT

Multi-output Gaussian process (MGP) has been attracting increasing attention as a transfer learning method to model multiple outputs. Despite its high flexibility and generality, MGP still faces two critical challenges when applied to transfer learning. The first one is negative transfer, which occurs when there exists no shared information among the outputs. The second challenge is the input domain inconsistency, which is commonly studied in transfer learning yet not explored in MGP. In this paper, we propose a regularized MGP modeling framework with domain adaptation to overcome these challenges. More specifically, a sparse covariance matrix of MGP is constructed using convolution process, where penalization terms are added to adaptively select the most informative outputs for knowledge transfer. To deal with the domain inconsistency, a domain adaptation method is proposed by marginalizing inconsistent features and expanding missing features to align the input domains among different outputs. Statistical properties of the proposed method are provided to guarantee the performance practically and asymptotically. The proposed framework outperforms state-of-the-art benchmarks in comprehensive simulation studies and one real case study of a ceramic manufacturing process. The results demonstrate the effectiveness of our method in dealing with both the negative transfer and the domain inconsistency.

PMID:36074880 | DOI:10.1109/TPAMI.2022.3205036

IEEE J Biomed Health Inform. 2022 Sep 8;PP. doi: 10.1109/JBHI.2022.3205167. Online ahead of print.

ABSTRACT

Chest X-ray (CXR) is commonly performed as an initial investigation in COVID-19, whose fast and accurate diagnosis is critical. Recently, deep learning has a great potential in detecting people who are suspected to be infected with COVID-19. However, deep learning resulting with black-box models, which often breaks down when forced to make predictions about data for which limited supervised information is available and lack inter-pretability, still is a major barrier for clinical integration. In this work, we hereby propose a semantic-powered explainable model-free few-shot learning scheme to quickly and precisely diagnose COVID-19 with higher reliability and transparency. Specifically, we design a Report Image Explanation Cell (RIEC) to exploit clinically indicators derived from radiology reports as interpretable driver to introduce prior knowledge at training. Meanwhile, multi-task colla-borative diagnosis strategy (MCDS) is developed to construct [Formula: see text]-way [Formula: see text]-shot tasks, which adopts a cyclic and collaborative training approach for producing better generalization performance on new tasks. Extensive experiments demonstrate that the proposed scheme achieves competitive results (accuracy of 98.91%, precision of 98.95%, recall of 97.94% and F1-score of 98.57%) to diagnose COVID-19 and other pneumonia infected categories, even with only 200 paired CXR images and radiology reports for training. Furthermore, statistical results of comparative experiments show that our scheme provides an interpretable window into the COVID-19 diagnosis to improve the performance of the small sample size, the reliability and transparency of black-box deep learning mod-els. Our source codes will be released on https://github.com/AI-medical-diagnosis-team-of-JNU/SPEMFSL-Diagnosis-COVID-19.

PMID:36074872 | DOI:10.1109/JBHI.2022.3205167

J Public Health Manag Pract. 2022 Sep 5. doi: 10.1097/PHH.0000000000001549. Online ahead of print.

ABSTRACT

CONTEXT: The Asbestos Hazard Emergency Response Act (AHERA) became a law in 1986, and the US Environmental Protection Agency (USEPA) was mandated to promulgate rules to regulate the inspection, management, and abatement of asbestos-containing building materials (ACBM) in schools. This study describes 10 years (2008-2017) of AHERA compliance site inspection data conducted by the New Jersey Department of Health (NJDOH).

OBJECTIVES: To establish the level to which inspected NJ schools comply with AHERA regulations, to characterize compliance deficiencies including those that may lead to increased asbestos exposure risk to students and school employees, and to determine whether age, type, and geographic location of school impacted the likelihood of noncompliance.

DESIGN: Information collected during 456 unique inspections between 2008 and 2017 was analyzed.

SETTING AND PARTICIPANTS: Inspections were conducted at public and private schools in New Jersey. These included elementary, middle, and high schools, as well as charter and vocational/technical schools.

MAIN OUTCOME MEASURES: Descriptive statistics and multiple logistic regression modeling of 3 factors, school type, geographical region, and school age.

RESULTS: NJDOH inspectors found damage to friable ACBM in 50% (n = 229) of the schools and fiber release episodes in 27% of inspections (n = 121). The case of schools failing to attach warning labels on or immediately adjacent to ACBM was the most frequently noted compliance deficiency over the 10-year period. The modeling output showed that compliance was associated with the type of school and geographical region.

CONCLUSIONS: Inspected schools during the 10-year period were in serious noncompliance with AHERA regulations. This included deficiencies that demonstrate a potential exposure to asbestos such as missing ACBM in management plans, damaged ACBM, lack of protection of short-term workers and custodial staff, and the identification of fiber release episodes. Modeling results of specific school characteristics can help direct limited resources to mitigate potential asbestos exposures.

PMID:36074796 | DOI:10.1097/PHH.0000000000001549

Nurs Open. 2022 Sep 8. doi: 10.1002/nop2.1346. Online ahead of print.

ABSTRACT

AIMS: To measure the effectiveness of educational programmes for nurses regarding knowledge and practice of advanced resuscitation for newborn infants.

DESIGN: This is a quasi-experimental study in (Sudan, White Nile state), to evaluate the effectiveness of designed guidelines regarding advanced neonatal resuscitation for midwives during the period November 2020-January 2021.

METHODS: Data were collected using two tools: semi-structured questionnaire and checklist. The number of the respondents to the questionnaire is 75 nurses. Statistical analyses were conducted using SPSS (version 22). Data were expressed as percentages. The results show that the level of knowledge is improved significantly after training programme interventions, with safe practice reaching (98.70%) compared with a pre-test percentage of (11.5%). This indicates a steep rise in safe practice after the simulation section, a sharp decrease in unsafe practice after the practical section, followed by subsequent decrease in neonatal mortality rate. This paper has been guided by (STROBE, cohort study) checklist.

RESULTS: The study concluded that the majority of nurses and midwives have some knowledge regarding advanced neonatal resuscitation but still, there is a practice gap because of a shortage of facilities and lack of training, However, training programmes do add value on knowledge and practice for nurses and eventually decrease neonatal mortality rate.

PMID:36074779 | DOI:10.1002/nop2.1346

PLoS One. 2022 Sep 8;17(9):e0273931. doi: 10.1371/journal.pone.0273931. eCollection 2022.

ABSTRACT

Childhood maltreatment, specifically during sensitive developmental periods, is a major risk factor for poor physical and mental health. Despite its enormous clinical relevance, there is still a lack of scales measuring different types, timing, and duration of childhood maltreatment. The current study sought to validate and determine the psychometric properties of the brief German version of the Maltreatment and Abuse Chronology of Exposure (MACE) scale, the KERF-40. The KERF-40 was administered as an interview (i.e., KERF-40-I) to 287 adult participants with and without mental disorders. Based on item response theory, items of the KERF-40-I were assigned to different types of maltreatment, resulting in a scaled version, the KERF-40+. Test-retest reliability was assessed in a small subsample (n = 14). Convergent and relative predictive validity were measured with correlations of the KERF-40+ and the Childhood Trauma Questionnaire (CTQ) as well as self-report measures of general and trauma-related psychopathology. Rasch analysis and fit statistics yielded a 49-item version, encompassing ten different types of maltreatment. The test-retest reliability of the KERF-40+ was shown to be acceptable to excellent for almost all global and subscale scores (.74 ≤ ρ ≤ 1.00), with the exception of the subscale emotional neglect (ρ = .55). Convergent validity with the CTQ was confirmed for both KERF-40+ global scores (.72 ≤ r ≤ .87) and corresponding subscale scores (.56 ≤ r ≤ .78). Relative predictive validity was reflected by significant small-to-moderate correlations between KERF-40+ global scores and indices of general and trauma-related psychopathology (.24 ≤ r ≤ .45). Taken together, the KERF-40+ appears to be suited for clinicians and researchers interested in retrospectively assessing different types, timing, and duration of childhood maltreatment experiences during sensitive periods in adults.

PMID:36074774 | DOI:10.1371/journal.pone.0273931

PLoS One. 2022 Sep 8;17(9):e0272628. doi: 10.1371/journal.pone.0272628. eCollection 2022.

ABSTRACT

OBJECTIVE: Twitter as a social media platform has revolutionized the way we interact with others and receive information. The presence of dental schools in Twitter facilitates the engagement of students, educators, dental professionals, and the community. Given the explosive popularity of Twitter as a social media platform and its potential use in the areas of education and branding, the questions of why and how dental schools use these services warrant comprehensive research. Thus, the aim of this study was to analyze the pattern and use of Twitter as a social media platform for dental schools in Saudi Arabia.

METHODS: The tweets were extracted within the timeframe from July 15, 2019, to July 15, 2020. The Twitter data collected included: full text content, the count of retweets, quotes, replies and likes. Extracted tweets were categorized into five main themes: news and announcement, dental professional communication, general communication, oral health education, and promoting participation. Tweets in each main theme were further categorized according to the dental schools’ academic roles namely; education, research and community service. In addition, tweets were classified according to originality of the tweet, language used, nature of the tweet and the use of hashtags and mentions. Descriptive analysis presented in the form of frequency tables with percentages and mean (SD) as well as graphical presentation of the pattern and use of Twitter for Saudi dental schools in the form of bar, pie and line charts. Categorical data were analyzed using chi square test, while continuous data were analyzed using ANOVA. Statistical significance was set at p ≤ 0.05.

RESULTS: A total of 15 Saudi dental schools with Twitter accounts were included in the analysis. King Saud University (KSU) had the largest number of followers with 17,200. Within the time frame of this study, a total of 1,889 original tweets from dental schools were found. Imam Abdulrahman Bin Faisal University (IAU) had the highest number of posted tweets (n = 647, 34.3%). The distribution of tweets was highest in September 2019 (n = 239) and lowest in July 2020 (n = 22). Majority of the tweets (81.9%) belonged to five out of the 15 dental schools. News and announcements were the most tweeted thematic subject with 1,034 tweets (55%). While community service was the most tweeted academic role with 803 tweets (42%). The top five active dental schools’ performance for both thematic and academic role classifications were significantly different based on the chi square test (p < 0.001).

CONCLUSION: This study highlights the importance of Twitter as a social media platform, in dental education especially when it comes to presence and branding for dental schools. Twitter is a helpful platform to expose dental schools to the community, this can be seen by their academic achievements as well as their active role with community service.

PMID:36074762 | DOI:10.1371/journal.pone.0272628

MMWR Morb Mortal Wkly Rep. 2022 Sep 9;71(36):1159. doi: 10.15585/mmwr.mm7136a4.

NO ABSTRACT

PMID:36074740 | DOI:10.15585/mmwr.mm7136a4