Clinical analysis of high-intensity focussed ultrasound ablation for abdominal wall endometriosis: a 4-year experience at a specialty gynecological institution

Objective: To evaluate the long-term clinical effect of high-intensity focussed ultrasound (HIFU) as a non-invasive modality for ablation of abdominal wall endometriosis (AWE) foci.

Methods: All women who were diagnosed with cutaneous endometriosis and underwent HIFU ablation and 4-year follow-up were included. Patient symptoms, imaging performed, HIFU ablation, recurrence, lesion location, size and number were collected and analyzed.

Results: A total of 51 women with 57 painful abdominal wall masses with a median volume of 4.00?cm³ and a mean age of 30.5±2.12 years were treated with HIFU. The main symptoms were a palpable painful abdominal mass (93%), protrusion of the skin (28.1%, 16) or lack of protrusion of the skin (71.9%, 41). Ultrasound was initially performed in 100% (51) of women, whereas 6% (3) required MRI examinations to distinguish the features and range of the masses. Ablation was performed with a median 300?s of sonication time, 40?min treatment time, 150?W of power and 41800?J of total energy to treat lesions that were a median volume of 3.83?cm³. No severe complications occurred, except in one patient with a first-degree skin burn, during the 48-month follow-up period. The pooled recurrence of cutaneous endometriosis occurred in 3.9% (2) of women.

Conclusion: The diagnosis of AWE should be confirmed with imaging of the lesion number, location, size and features before HIFU ablation. HIFU should be the first choice for the treatment of AWE as it is a non-invasive method, with high efficiency and safety and rapid postoperative recovery.     

经胫骨隧道前交叉韧带双束八股解剖重建的临床研究

目的观察关节镜下采用自体腘绳肌腱经胫骨隧道前交叉韧带（anterior cruciate ligament, ACL）双束八股解剖重建的临床效果。方法随访上海交通大学附属第六人民医院运动医学科2018年12月—2020年1月收治的103例ACL断裂患者资料，其中男78例，女25例，年龄18~45岁，平均（26.8±5.86）岁；左侧47例，右侧56例，均采用关节镜下自体腘绳肌腱经胫骨隧道打股骨骨隧道，ACL双束八股解剖重建。按照Lysholm评分、国际膝关节评分委员会（IKDC）膝关节评分、Tegner膝关节评分标准和膝关节自我效能量表K-SES评价疗效。结果所有患者术后获随访12～42个月，平均（24±8.18）个月；手术前、末次随访评分比较，Lysholm评分分别为（48.41±4.44）分和（95.34±1.91）分，2组比较差异有统计学意义（P<0.001)；IKDC评分分别为（44.05±4.36）分和（95.66±1.89）分，2组比较差异有统计学意义（P<0.001)；Tegner评分分别为（2.84±0.95）分和（6.15±0.89）分，2组比较差异有统计学意义（P<0.001)；膝关节自我效能量表K-SES量表（3.10±0.83）分和（7.12±1.10）分，2组比较差异有统计学意义（P<0.001)。末次随访103例患者前抽屉试验阴性，轴移试验阴性。98例（95.1%）Lachman试验阴性，5例（4.9%）Lachman试验1°阳性。结论关节镜下采用自体腘绳肌腱经胫骨隧道双束八股解剖重建前交叉韧带是一种恢复膝关节稳定性，恢复伤前活动水平的有效方法。     

Low potential for evolutionary rescue from climate change in a tropical fish

Climate change is increasing global temperatures and intensifying the frequency and severity of extreme heat waves. How organisms will cope with these changes depends on their inherent thermal tolerance, acclimation capacity, and ability for evolutionary adaptation. Yet, the potential for adaptation of upper thermal tolerance in vertebrates is largely unknown. We artificially selected offspring from wild-caught zebrafish (Danio rerio) to increase (Up-selected) or decrease (Down-selected) upper thermal tolerance over six generations. Selection to increase upper thermal tolerance was also performed on warm-acclimated fish to test whether plasticity in the form of inducible warm tolerance also evolved. Upper thermal tolerance responded to selection in the predicted directions. However, compared to the control lines, the response was stronger in the Down-selected than in the Up-selected lines in which evolution toward higher upper thermal tolerance was slow (0.04 ± 0.008 °C per generation). Furthermore, the scope for plasticity resulting from warm acclimation decreased in the Up-selected lines. These results suggest the existence of a hard limit in upper thermal tolerance. Considering the rate at which global temperatures are increasing, the observed rates of adaptation and the possible hard limit in upper thermal tolerance suggest a low potential for evolutionary rescue in tropical fish living at the edge of their thermal limits.

Globally, both mean and extreme environmental temperatures are increasing due to climate change with mean temperatures predicted to increase by 0.3–4.8 °C by the end of the century (1, 2). Aquatic ectotherms are particularly vulnerable to rising temperatures as their body temperature closely tracks the environmental temperature (3). These organisms can avoid thermal stress by migrating to cooler waters, acclimating, and/or adapting genetically (4–6). For species with a limited dispersal ability (e.g., species from shallow freshwater habitats; ref. 7), acclimation and evolutionary adaptation are the only possible strategies. Furthermore, for ectotherms living at the edge of their upper thermal limits, an increase in extreme temperatures may generate temperature peaks that exceed physiological limits and cause high mortality (5, 8–10). Although this is expected to cause strong selection toward higher upper thermal tolerance, it is largely unknown, particularly within vertebrates, whether and at what rate organisms may adapt by evolving their thermal limits (11–14). These are important issues because constrained or limited evolvability (15) of upper thermal tolerance could lead to population extinctions as climate change increases the severity of heat waves.Ectotherms can also increase their thermal limits through physiological and biochemical adjustments, in a process known as thermal acclimation when they are exposed to elevated temperatures for a period of time (16, 17). Thermal acclimation, sometimes called thermal compensation, is here used interchangeably with the term physiological plasticity as outlined by Seebacher et al. (18). In the wild, individuals may experience days or weeks of warmer temperatures prior to a thermal extreme. Through physiological plasticity, the severity of an ensuing thermal extreme may be reduced, thus increasing the chance for survival (19). Furthermore, in some cases, adaptation can be accelerated by plasticity (20–22). This requires that the physiological mechanisms responsible for acclimation are also (at least partly) involved in the acute response; that is, that there is a positive genetic correlation between physiological plasticity and (acute) upper thermal tolerance. It is therefore crucial to quantify the evolutionary potential of upper thermal tolerance of fish populations threatened by climate change (23, 24) and to understand the link between the evolutionary response of upper thermal tolerance and physiological plasticity.Previously detected evolution of upper thermal tolerance generally points toward a slow process (12, 13, 25–31). However, estimates of the evolutionary potential in upper thermal tolerance mostly come from studies on Drosophila (12, 25, 27, 32), and empirical evidence in aquatic ectotherms and specifically vertebrates is limited. The few studies that have been performed on fish show disparate responses to selection on heat tolerance even within the same species. Baer and Travis (33) detected no response to selection yet Doyle et al. (34) and Klerks et al. (28) detected selection responses with heritabilities of 0.2 in killifish (Heterandria formosa). Despite the typical asymmetry of thermal performance curves (3, 35), studies in vertebrates are limited to unidirectional estimates of evolutionary potential (28, 31, 33) or do not account for the direction of evolution when estimating heritability in upper thermal tolerance from breeding designs (36, 37). Furthermore, while several studies have found that populations with different thermal histories have evolved different levels of heat tolerance (29–31), we still lack a good understanding of how physiological plasticity within a generation, in response to a short heat exposure, interacts with genetic changes during evolution of thermal tolerance.To investigate possible asymmetry in the evolutionary potential of upper thermal tolerance in a vertebrate species, we artificially selected offspring of wild-caught zebrafish (Danio rerio) to increase and decrease upper thermal tolerance for six generations. Furthermore, to disentangle the contribution of acclimation from the genetic response to increase upper thermal tolerance, we selected two lines that were exposed to a period of warm acclimation prior to a thermal challenge. The size (>20,000 phenotyped fish) and duration (six generations) of this study are unique in a vertebrate species for a climate change-relevant selection experiment, and the results provide critical and robust information on how tropical fish may adapt to a changing climate.Being a freshwater and tropical species, zebrafish are likely to be especially vulnerable to climate change (7, 38). In the wild, zebrafish can already be found living only a few degrees below their thermal limits (17, 39) and live in shallow streams and pools (40) that have the potential to rapidly warm during heat waves. Zebrafish therefore represent a species living at the edge of its thermal limit in which rapid adaptation of thermal tolerance would be particularly beneficial for its survival. Wild-caught zebrafish originating from different sites in West Bengal, India (17, 40), were used to maximize the genetic diversity of the parental population. These wild-caught zebrafish (n = 2,265) served as parents of the starting F₀ generation (n = 1,800) on which we selected upper thermal tolerance for six generations. Upper thermal tolerance was measured as the critical thermal maximum (CT_max), a commonly used measure of an organism’s acute upper thermal tolerance (16, 41). CT_max is defined as the temperature at which an individual loses equilibrium (i.e., uncontrolled and disorganized swimming in zebrafish; ref. 42) during thermal ramping. Measuring CT_max is rapid, repeatable, and does not appear to harm zebrafish (42). CT_max is ecologically relevant because it is highly correlated with both tolerance to slow warming (43) and to the upper temperature range boundaries of wild aquatic ectotherms (9).Our selection experiment consisted of four treatment groups (Up-selected, Down-selected, Acclimated Up-selected, and Control) with two replicate lines in each treatment. We established these lines by selecting fish on their CT_max in the F₀ generation with each line consisting of 150 individuals (see Methods for further details of F₀ generation). The offspring of those fish formed the F₁ generation that consisted of 450 offspring in each line. At each generation, the Up, Down, and Control lines were all held at optimal temperature (28 °C) (39), whereas the Acclimated Up-selected lines were acclimated to a supraoptimal temperature (32 °C) for 2 wk prior to selection (17). From the F₁ to F₆ generations, we measured CT_max for all 450 fish in each line and selected the 33% with the highest CT_max in the Up-selected and in the Acclimated Up-selected lines, and the 33% with the lowest CT_max in the Down-selected lines. In the Control lines, 150 fish were randomly selected, measured, and retained. Thus, CT_max was measured on a total of 3,000 fish per generation and 150 individuals remained in each of the eight lines after selection, forming the parents for the next generation. The nonselected lines (Control) represented a control for the Up-selected and Down-selected lines, while the Up-selected lines represented a control for the Acclimated Up-selected lines, because these two treatments solely differed by the acclimation period to which the latter were exposed before selection. Thus, differences in CT_max between Up-selected and Acclimated Up-selected lines represent the contribution of physiological plasticity to upper thermal tolerance. If the difference between these two treatments increases during selection, it would suggest that plasticity increases during adaptation to higher CT_max (i.e., the slope the reaction norm describing the relationship between CT_max and acclimation temperature would become steeper).After six generations of selection, upper thermal tolerance had evolved in both the Up-selected and the Down-selected lines (Fig. 1). In the Up-selected lines, upper thermal tolerance increased by 0.22 ± 0.05 °C ($\bar{x}$ ± 1 SE) compared to the Control lines whereas the Down-selected lines displayed a mean upper thermal tolerance 0.74 ± 0.05 °C lower than the Control (Fig. 1B; estimates for replicated lines combined). The asymmetry in the response to selection was confirmed by the estimated realized heritability, which was more than twice as high in the Down-selected lines (h² = 0.24; 95% CI: 0.19–0.28) than in the Up-selected lines (h² = 0.10; 95% CI: 0.05–0.14; Fig. 2).Open in a separate windowFig. 1.Upper thermal tolerance (CT_max) of wild-caught zebrafish over six episodes of selection. Duplicated lines were selected for increased (Up-selected, orange lines and triangles) and decreased (Down-selected, blue lines and squares) upper thermal tolerance. In addition, we had two Control lines (green dashed lines and diamonds). The Up, Down, and Control lines were all acclimated to a temperature of 28 °C. In addition, two lines were selected for increased upper thermal tolerance after 2 wk of warm acclimation at 32 °C (Acclimated Up-selected, red lines and circles). At each generation, the mean and 95% CIs of each line are shown (n ∼ 450 individuals per line). (A) Absolute upper thermal tolerance values. (B) The response to selection in the Up and Down lines centered on the Control lines (dashed green line). Difference between Up-selected and Acclimated-Up lines are shown in Fig. 3. The rate of adaptation (°C per generation) is reported for each treatment using estimates obtained from linear mixed effects models using the Control-centered response in the Up-selected and Down-selected lines and the absolute response for the Acclimated-Up lines (SE = ±0.01 °C in all lines).Open in a separate windowFig. 2.Realized heritability (h²) of upper thermal tolerance (CT_max) in wild-caught zebrafish. The realized heritability was estimated for each treatment as the slope of the regression of the cumulative response to selection on the cumulative selection differential using mixed effect models passing through the origin with replicate as a random effect. Slopes are presented with their 95% CIs (shaded area) for the Down-selected lines (blue) and Up-selected lines (orange). Data points represent the mean of each replicate line (n ∼ 450) over six generations of selection. Average selection differentials are 0.57 (Down) and 0.39 (Up), respectively, see SI Appendix, Table S1 for more information.At the start of the experiment (F₀), warm acclimation (32 °C) increased thermal tolerance by 1.31 ± 0.05 °C (difference in CT_max between the Up-selected and Acclimated Up-selected lines in Figs. 1A and ​and3),3), which translates to a 0.3 °C change in CT_max per 1 °C of warming. In the last generation, the effect of acclimation had decreased by 25%, with the Acclimated-Up lines having an average CT_max 0.98 ± 0.04 °C higher than the Up lines (Fig. 3). This suggests that, despite a slight increase in CT_max in the Acclimated Up-selected lines during selection, the contribution of plasticity decreased over the course of the experiment.Open in a separate windowFig. 3.Contribution of acclimation to the upper thermal tolerance in the Acclimated-Up selected lines at each generation of selection. The contribution of acclimation was estimated as the difference between the Up and Acclimated-Up selected lines. Points and error bars represent the estimates (±SE) from a linear mixed effects model with CT_max as the response variable; Treatment (factor with two levels: Up and Acclimated Up), Generation (factor with seven levels), and their interaction as the predictor variables; and replicate line as a random factor.During the experiment, the phenotypic variation of CT_max that was left-skewed at F₀ increased in the Down-selected lines and decreased in the Up-selected lines (Fig. 4). At the F₆ generation, phenotypic variance was four times lower in the Up-selected lines (0.09 ± 0.01 and 0.12 ± 0.02 °C²; variance presented for each replicate line separately and SE obtained by nonparametric bootstrapping) than in the Down-selected lines (0.41 ± 0.03 and 0.50 ± 0.04 °C²), which had doubled since the start of the experiment (F₀: 0.20 ± 0.01 °C², see SI Appendix, Fig. S1). In the Acclimated Up-selected lines, the phenotypic variance that was already much lower than the Control at the F₀ also decreased and reached 0.06 ± 0.01 °C² and 0.07 ± 0.01 °C² for the two replicates at the last generation (SI Appendix, Fig. S1).Open in a separate windowFig. 4.Distribution of upper thermal tolerance (CT_max) in selected lines. (A) Distribution for each line at each generation (F₀ to F₆). In the F₀ generation, histograms show the preselection distribution in gray for the nonacclimated fish, in dark green for the Control lines, and in red for the Acclimated-Up fish. In all subsequent generations the Down-selected lines are in blue, the Up-selected lines in yellow, the Control lines in dark green, and Acclimated-up lines in red. All treatments use two shades, one for each replicate line. Dashed lines represent the mean CT_max for each line (n ∼ 450 individuals). (B) Distribution of upper thermal tolerance at the start (F₀, in gray) and the end (F₆, in blue and yellow) of the experiment for the Up-selected and Down-selected lines. The dashed gray line represents the mean of the Up-selected and Down-selected lines in the F₀ generation preselection (n ∼ 900 individuals). Dashed blue and yellow lines represent the mean CT_max for Up and Down-selected lines for the F₆ generation (n ∼ 450 individuals).Together with the asymmetrical response to selection and the lower response of the Acclimated Up-selected lines, these changes in phenotypic variance suggest the existence of a hard-upper limit for thermal tolerance (e.g., major protein denaturation (44), similar to the “concrete ceiling” for physiological responses to warming (14)). Such a hard-upper limit is expected to generate a nonlinear mapping of the genetic and environmental effects on the phenotypic expression of CT_max. This nonlinearity will affect the phenotypic variance of CT_max when mean CT_max approaches its upper limit (SI Appendix, Fig. S2A). For example, with directional selection toward higher CT_max, genetic changes in upper thermal tolerance will translate into progressively smaller phenotypic changes. Similarly, warm acclimation that shifts CT_max upwards will also decrease phenotypic variation in CT_max (see differences in phenotypic variance between control and Acclimated lines at the F₀). This hard ceiling can also explain why an evolutionary increase in CT_max reduces the magnitude of physiological plasticity in CT_max achieved after a period of acclimation (Fig. 3 and see SI Appendix, Fig. S2B). If the sum of the genetic and plastic contributions to CT_max cannot exceed a ceiling value, this should generate a zero-sum gain between the genetic and plastic determinants of thermal tolerance. An increase in the genetic contribution to CT_max via selection should thus decrease the contribution of plasticity. Selection for a higher CT_max should therefore negatively affect the slope of the reaction norm of thermal acclimation because acclimation will increase CT_max more strongly at low than high acclimation temperature (SI Appendix, Fig. S2B).To test this hypothesis, we measured CT_max in all selected lines at the final generation (F₆) after acclimation to 24, 28, and 32 °C. At all three acclimation temperatures, the Acclimated-Up lines did not differ from the Up-selected lines (average difference 0.14 ± 0.08 °C; 0.12 ± 0.09 °C; 0.14 ± 0.09 °C; at 24, 28, and 32 °C respectively; Fig. 5). This suggests that warm acclimation prior to selection did not affect the response to selection. However, considering the within-treatment differences in CT_max between fish acclimated to 28 and 32 °C, we show that the gain in CT_max due to acclimation decreases in both the Up and Acclimated-Up treatments compared to the Control and Down treatments (SI Appendix, Fig. S3). This confirms a loss of thermal plasticity in both Up-selected treatments (Up and Acclimated-Up) at higher acclimation temperatures. Notably, the loss of thermal plasticity is not evident in fish acclimated to 24 and 28 °C, possibly because at these temperatures CT_max remains further away from its hard upper limit.Open in a separate windowFig. 5.Upper thermal tolerance (CT_max) of the selected lines measured at the last generation (F₆) after acclimation at 24, 28, and 32 °C. The response is calculated as the mean difference in upper thermal tolerance (CT_max) relative to the Control lines. Large points and whiskers represent mean ±1 SE for each treatment (n = 120 individuals): Up-selected (orange triangles), Down-selected (blue squares), Acclimated Up-selected (red circles), and Control (green diamonds). Smaller translucent points represent means of each replicate line (n = 60 individuals). See SI Appendix, Fig. S3 for absolute CT_max values and model estimates.Acclimated Up-selected lines are perhaps the most ecologically relevant in our selection experiment. In the wild, natural selection on upper thermal tolerance may not result from increasing mean temperatures but through rapid heating events such as heat waves (45). During heat waves, temperature may rise for days before reaching critical temperatures. This gives individuals the possibility to acclimate and increase their upper thermal tolerance prior to peak temperatures. Our results show that while warm acclimation allowed individuals to increase their upper thermal tolerance, it did not increase the magnitude or the rate of adaptation of upper thermal tolerance.For the past two decades it has been recognized that rapid evolution, at ecological timescales, occurs and may represent an essential mechanism for the persistence of populations in rapidly changing environments (24, 46, 47). Yet, in the absence of an explicit reference, rates of evolution are often difficult to categorize as slow or rapid (48). For traits related to thermal tolerance or thermal performance, this issue is complicated by the fact that the scale on which traits are measured (temperature in °C) cannot meaningfully be transformed to a proportional scale. This prevents us from comparing rates of evolution between traits related to temperature with other traits measured on different scales (49, 50). However, for thermal tolerance, the rate of increase in ambient temperature predicted over the next century represents a particularly meaningful standard against which the rate of evolution observed in our study can be compared.In India and surrounding countries where zebrafish are native, heat waves are predicted to increase in frequency, intensity, and duration, and maximum air temperatures in some regions are predicted to exceed 44 °C in all future climate scenarios (51). Air temperature is a good predictor of water temperature in shallow ponds and streams where wild zebrafish are found (17, 40, 52, 53). Thus, strong directional selection on the thermal limits of zebrafish is very likely to occur in the wild. At first sight, changes in the upper thermal tolerance observed in our study (0.04 °C per generation) as well as the heritability estimates (Down-selected: h² = 0.24, Up-selected: h² = 0.10) similar to those obtained in fruit flies (Drosophila melanogaster) selected for acute upper thermal tolerance (Down-selected: h² = 0.19, Up-selected: h² = 0.12; ref. 12), suggest that zebrafish may just be able to keep pace with climate change and acutely tolerate temperatures of 44 °C predicted by the end of the century. However, several cautions make such an optimistic prediction unlikely.First, such an extrapolation assumes a generation time of 1 y, which is likely for zebrafish but unrealistic for many other fish species. Second, such a rate of evolution is associated with a thermal culling of two-thirds of the population at each generation, a strength of selection that may be impossible to sustain in natural populations exposed to other selection pressures such as predation or harvesting. Third, the heritability and rate of adaptation toward higher upper thermal tolerance observed here may be considered as upper estimates because of the potentially high genetic variance harbored by our parental population where samples from several sites were mixed. While mixing of zebrafish populations often occurs in the wild during monsoon flooding (54, 55), there are likely to be some isolated populations that may have a lower genetic diversity and adaptation potential than our starting population. Finally, and most importantly, the reduced phenotypic variance and decreased acclimation capacity with increasing CT_max observed in our study suggest the existence of a hard-upper limit to thermal tolerance that will lead to an evolutionary plateau similar to those reached in Drosophila selected for increased heat resistance over many generations (12, 56). Overall, the rate of evolution observed in our study is likely higher than what will occur in the wild and, based on this, it seems unlikely that zebrafish, or potentially other tropical fish species, will be able to acutely tolerate temperatures predicted by the end of the century. It is possible that other fish species, especially those living in cooler waters and with wider thermal safety margins, will display higher rates of adaptation than the ones we observed here, and more studies of this kind in a range of species are needed to determine whether slow adaptation of upper thermal tolerance is a general phenomenon.Transgenerational plasticity (e.g., epigenetics) has been suggested to modulate physiological thermal tolerance (57). However, the progressive changes in CT_max observed across generations in our study indicate that these changes were primarily due to genetic changes because effects of transgenerational plasticity are not expected to accumulate across generations. Therefore, the effects of transgenerational plasticity in the adaptation of upper thermal tolerance may be insufficient to mitigate impacts of climate change on zebrafish, yet the potential contribution of transgenerational plasticity is still an open question.By phenotyping more than 20,000 fish over six generations of selection, we show that evolution of upper thermal tolerance is possible in a vertebrate over short evolutionary time. However, the evolutionary potential for increased upper thermal tolerance is low due to the slow rate of adaptation compared to climate warming, as well as the diminishing effect of acclimation as adaptation progresses. Our results thus suggest that fish populations, especially warm water species living close to their thermal limits, may struggle to adapt with the rate at which water temperatures are increasing.     

Necroptotic TNFα-Syndecan 4-TNFα Vicious Cycle as a Therapeutic Target for Preventing Temporomandibular Joint Osteoarthritis

Temporomandibular joint osteoarthritis (TMJOA) is a chronic degenerative disease for which the underlying mechanism still remains unclear. Compared with apoptosis and autophagy, necroptosis causes greater harm to tissue homeostasis by releasing damage-associated molecular patterns (DAMPs). However, the role of necroptosis and downstream key DAMPs in TMJOA is unknown. Here, rodent models of TMJOA were established by the unilateral anterior crossbite (UAC). Transmission electron microscopy (TEM) and immunohistochemistry of receptor interacting protein kinase 3 (RIPK3)/phosphorylation of mixed lineage kinase domain-like protein (pMLKL) were conducted to evaluate the occurrence of necroptosis in vivo. The therapeutic effects of blocking necroptosis were achieved by intra-articularly injecting RIPK3 or MLKL inhibitors and using RIPK3 or MLKL knockout mice. In vitro necroptosis of condylar chondrocyte was induced by combination of tumor necrosis factor alpha (TNFα), second mitochondria-derived activator of caspases (SMAC) mimetics and carbobenzoxy-valyl-alanyl-aspartyl-[O-methyl]- fluoromethylketone (z-VAD-fmk). The possible DAMPs released by necroptotic chondrocytes were screened by quantitative proteomics and blocked by specific antibody. Translucent cytosol, swollen organelles, and ruptured cell membranes, features of necroptosis, were frequently manifested in chondrocytes at the early stage of condylar cartilage degeneration in TMJOA, which was accompanied by upregulation of RIPK3/pMLKL. Inhibiting or knocking out RIPK3/MLKL significantly prevented cartilage degeneration. DAMPs released by necroptotic condylar chondrocytes, such as syndecan 4 (SDC4) and heat shock protein 90 (HSP90), were verified. Furthermore, blocking the function of SDC4 significantly attenuated the expression of TNFα in cartilage and synovium, and accordingly increased cartilage thickness and reduced synovial inflammation. Thus, the necroptotic vicious cycle of TNFα-SDC4-TNFα contributes to cartilage degeneration and synovitis, and can serve as a potential therapeutic target for treating TMJOA. © 2022 American Society for Bone and Mineral Research (ASBMR).     

Fertility Outcome After Renal Transplantation: A Single-Center Experience

BackgroundWomen suffering from kidney disease are more prone to fertility problems, due to uremia. Fortunately, their fertility rate increases dramatically after renal transplantation. This study analyzes the predictors/risk factors of successful pregnancy with live birth outcome while presenting an overview of the 7-year experience of a single center.MethodsThis retrospective cohort study includes 239 women of reproductive age (18–40 years) who underwent renal transplantation in a tertiary Turkish clinic between October 1, 2011, and August 24, 2017. The subjects were invited to take part in a survey questioning their obstetric characteristics and they were assessed in 2 groups: fertile and infertile. Multivariable linear regression analysis was conducted to determine the predictors of a successful pregnancy.ResultsThirty-five 35 patients wished to become pregnant: 12 got pregnant spontaneously, while 21 failed to become pregnant (spontaneously). The mean age of the patients at the survey was 34 ± 7. Regular menstrual cycles after renal transplantation, tacrolimus-mycophenolate mofetil maintenance protocol, and age at transplantation were found to be predictors of spontaneous pregnancy. The duration of peritoneal dialysis was significantly longer in the infertile group (48 vs 12 months).ConclusionEnd-stage renal disease's negative impacts, including menstrual abnormality and fertility problems, can be overcome by successful kidney transplantation with appropriate immunosuppression. Minimizing the duration of peritoneal dialysis, particularly in patients who desire future fertility, may be accepted as a logical management strategy.     

Association of genetic variants at MYP10 and MYP15 with high myopia in a Han Chinese population

Background: Previous genome-wide association study (GWAS) has revealed the association between MYP10 at 8p23 and MYP15 at 10q21.1 and high myopia (HM) in a French population. This study is managed to discover the connection between some single nucleotide polymorphism (located at MYP10 and MYP15) and Han Chinese HM.

Methods and Results: This case-control association study contained 1673 samples, including 869 ophthalmic patients and 804 controls. Twelve tag SNPs have been selected from the MYP10 and MYP15 loci and genotyped by SNaPshot method. Among 12 SNPs, rs4840437 and rs6989782 in TNKS gene were found significant association with HM. Carriers of rs4840437G allele and rs4840437GG genotype created a low risk of high myopia (P = .036, OR = 0.81, 95%CI = 0.71–0.93; P = .016, OR = 0.73, 95%CI = 0.56–0.96; respectively). Carriers of rs6989782T allele and rs6989782TT+CT genotype also had a decreased risk of high myopia (P = .048, OR = 0.82, 95%CI = 0.71–0.94; P = .006, OR = 0.74, 95%CI = 0.59–0.92; respectively). Other 10 SNPs displaced nonsignificant association with HM. Additionally, the risk haplotype AC and the protective haplotype GT, generated by two SNPs in TNKS, were considerably more likely to be association with HM (for AC, P = .002 and OR = 1.26; for GT, P = .027 and OR = 0.84).

Conclusions: Our results demonstrated that some heritable variants in the TNKS gene are associated with HM in the Han population. The possible functions of TNKS in the development and pathogenesis of hereditary high myopia still require further researches to identify.